UE4Project.ipynb

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        "outputId": "f183856b-bb92-40d9-89b9-fbab260bde26"
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          "text": [
            "Collecting vaderSentiment\n",
            "  Downloading vaderSentiment-3.3.2-py2.py3-none-any.whl (125 kB)\n",
            "\u001b[?25l     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m0.0/126.0 kB\u001b[0m \u001b[31m?\u001b[0m eta \u001b[36m-:--:--\u001b[0m\r\u001b[2K     \u001b[91m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[91m╸\u001b[0m\u001b[90m━━━━\u001b[0m \u001b[32m112.6/126.0 kB\u001b[0m \u001b[31m3.2 MB/s\u001b[0m eta \u001b[36m0:00:01\u001b[0m\r\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m126.0/126.0 kB\u001b[0m \u001b[31m2.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from vaderSentiment) (2.31.0)\n",
            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests->vaderSentiment) (3.3.2)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->vaderSentiment) (3.4)\n",
            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->vaderSentiment) (2.0.7)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->vaderSentiment) (2023.7.22)\n",
            "Installing collected packages: vaderSentiment\n",
            "Successfully installed vaderSentiment-3.3.2\n"
          ]
        }
      ],
      "source": [
        "pip install vaderSentiment"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import re\n",
        "import string\n",
        "import numpy as np\n",
        "import random\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "%matplotlib inline\n",
        "from plotly import graph_objs as go\n",
        "import plotly.express as px\n",
        "import plotly.figure_factory as ff\n",
        "from collections import Counter\n",
        "\n",
        "from PIL import Image\n",
        "from wordcloud import WordCloud, STOPWORDS, ImageColorGenerator\n",
        "\n",
        "import nltk\n",
        "from nltk.corpus import stopwords\n",
        "from nltk.tokenize import word_tokenize\n",
        "\n",
        "from tqdm import tqdm\n",
        "import os\n",
        "import nltk\n",
        "import spacy\n",
        "import random\n",
        "from spacy.util import compounding\n",
        "from spacy.util import minibatch\n",
        "\n",
        "import warnings\n",
        "warnings.filterwarnings(\"ignore\")\n",
        "\n",
        "# Any results you write to the current directory are saved as output"
      ],
      "metadata": {
        "id": "Ct5240NkFwNY"
      },
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#import the necessary libraries\n",
        "from vaderSentiment.vaderSentiment import SentimentIntensityAnalyzer\n",
        "import matplotlib.pyplot as plt"
      ],
      "metadata": {
        "id": "aaqxrlP0F3KK"
      },
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "data=pd.read_csv('reviews_data.csv')"
      ],
      "metadata": {
        "id": "RAfsivp5F-Na"
      },
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "data.shape"
      ],
      "metadata": {
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        },
        "id": "DGjTcFXIGLhH",
        "outputId": "d7d1af22-9820-422c-f464-d9bef4daf0a8"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(850, 6)"
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Removing Missing Values"
      ],
      "metadata": {
        "id": "e4nl2gzXGS4z"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# remove missing values\n",
        "data = data.dropna().reset_index(drop=True)"
      ],
      "metadata": {
        "id": "VUB-8JlqGQOm"
      },
      "execution_count": 6,
      "outputs": []
    },
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      "source": [
        "data"
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        "outputId": "e03e1f83-acaa-42fb-d159-d0ebddf425d8"
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      "execution_count": 7,
      "outputs": [
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              "         name           location                     Date  Rating  \\\n",
              "0       Helen  Wichita Falls, TX  Reviewed Sept. 13, 2023     5.0   \n",
              "1    Courtney         Apopka, FL   Reviewed July 16, 2023     5.0   \n",
              "2    Daynelle  Cranberry Twp, PA    Reviewed July 5, 2023     5.0   \n",
              "3      Taylor        Seattle, WA    Reviewed May 26, 2023     5.0   \n",
              "4     Tenessa        Gresham, OR   Reviewed Jan. 22, 2023     5.0   \n",
              "..        ...                ...                      ...     ...   \n",
              "700  Margaret         Cotati, CA    Reviewed Oct. 2, 2011     1.0   \n",
              "701       Ric       Oakville, ON   Reviewed Aug. 31, 2011     3.0   \n",
              "702     Jayne             Ny, NY   Reviewed Aug. 24, 2011     1.0   \n",
              "703     Norma      La Puente, CA   Reviewed Aug. 15, 2011     1.0   \n",
              "704   Kenneth        Beecher, IL    Reviewed Feb. 6, 2010     5.0   \n",
              "\n",
              "                                                Review  \\\n",
              "0    Amber and LaDonna at the Starbucks on Southwes...   \n",
              "1    ** at the Starbucks by the fire station on 436...   \n",
              "2    I just wanted to go out of my way to recognize...   \n",
              "3    Me and my friend were at Starbucks and my card...   \n",
              "4    I’m on this kick of drinking 5 cups of warm wa...   \n",
              "..                                                 ...   \n",
              "700  I ordered Via Starbucks coffee online. I recei...   \n",
              "701  My name is Ric **, I am journalist by professi...   \n",
              "702   The bagel was ice cold, not cut and not toasted.   \n",
              "703  In the morning of Monday, August 15, 2011, at ...   \n",
              "704  I found the coffee at Starbucks overrated and ...   \n",
              "\n",
              "                                           Image_Links  \n",
              "0                                        ['No Images']  \n",
              "1                                        ['No Images']  \n",
              "2    ['https://media.consumeraffairs.com/files/cach...  \n",
              "3                                        ['No Images']  \n",
              "4    ['https://media.consumeraffairs.com/files/cach...  \n",
              "..                                                 ...  \n",
              "700                                      ['No Images']  \n",
              "701                                      ['No Images']  \n",
              "702                                      ['No Images']  \n",
              "703                                      ['No Images']  \n",
              "704                                      ['No Images']  \n",
              "\n",
              "[705 rows x 6 columns]"
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              "      <th>name</th>\n",
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              "      <th>0</th>\n",
              "      <td>Helen</td>\n",
              "      <td>Wichita Falls, TX</td>\n",
              "      <td>Reviewed Sept. 13, 2023</td>\n",
              "      <td>5.0</td>\n",
              "      <td>Amber and LaDonna at the Starbucks on Southwes...</td>\n",
              "      <td>['No Images']</td>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Courtney</td>\n",
              "      <td>Apopka, FL</td>\n",
              "      <td>Reviewed July 16, 2023</td>\n",
              "      <td>5.0</td>\n",
              "      <td>** at the Starbucks by the fire station on 436...</td>\n",
              "      <td>['No Images']</td>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Daynelle</td>\n",
              "      <td>Cranberry Twp, PA</td>\n",
              "      <td>Reviewed July 5, 2023</td>\n",
              "      <td>5.0</td>\n",
              "      <td>I just wanted to go out of my way to recognize...</td>\n",
              "      <td>['https://media.consumeraffairs.com/files/cach...</td>\n",
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              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Taylor</td>\n",
              "      <td>Seattle, WA</td>\n",
              "      <td>Reviewed May 26, 2023</td>\n",
              "      <td>5.0</td>\n",
              "      <td>Me and my friend were at Starbucks and my card...</td>\n",
              "      <td>['No Images']</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Tenessa</td>\n",
              "      <td>Gresham, OR</td>\n",
              "      <td>Reviewed Jan. 22, 2023</td>\n",
              "      <td>5.0</td>\n",
              "      <td>I’m on this kick of drinking 5 cups of warm wa...</td>\n",
              "      <td>['https://media.consumeraffairs.com/files/cach...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
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              "      <th>700</th>\n",
              "      <td>Margaret</td>\n",
              "      <td>Cotati, CA</td>\n",
              "      <td>Reviewed Oct. 2, 2011</td>\n",
              "      <td>1.0</td>\n",
              "      <td>I ordered Via Starbucks coffee online. I recei...</td>\n",
              "      <td>['No Images']</td>\n",
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              "    <tr>\n",
              "      <th>701</th>\n",
              "      <td>Ric</td>\n",
              "      <td>Oakville, ON</td>\n",
              "      <td>Reviewed Aug. 31, 2011</td>\n",
              "      <td>3.0</td>\n",
              "      <td>My name is Ric **, I am journalist by professi...</td>\n",
              "      <td>['No Images']</td>\n",
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              "    <tr>\n",
              "      <th>702</th>\n",
              "      <td>Jayne</td>\n",
              "      <td>Ny, NY</td>\n",
              "      <td>Reviewed Aug. 24, 2011</td>\n",
              "      <td>1.0</td>\n",
              "      <td>The bagel was ice cold, not cut and not toasted.</td>\n",
              "      <td>['No Images']</td>\n",
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              "    <tr>\n",
              "      <th>703</th>\n",
              "      <td>Norma</td>\n",
              "      <td>La Puente, CA</td>\n",
              "      <td>Reviewed Aug. 15, 2011</td>\n",
              "      <td>1.0</td>\n",
              "      <td>In the morning of Monday, August 15, 2011, at ...</td>\n",
              "      <td>['No Images']</td>\n",
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              "      <th>704</th>\n",
              "      <td>Kenneth</td>\n",
              "      <td>Beecher, IL</td>\n",
              "      <td>Reviewed Feb. 6, 2010</td>\n",
              "      <td>5.0</td>\n",
              "      <td>I found the coffee at Starbucks overrated and ...</td>\n",
              "      <td>['No Images']</td>\n",
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              "    }\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-489d1dd9-b5b9-40dc-8f31-102092160270 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Download NLTK resources (stopwords and punkt tokenizer)\n",
        "nltk.download('stopwords')\n",
        "nltk.download('punkt')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ObSA5eA4GhMC",
        "outputId": "d69cf9d8-3b5a-4ce7-97fb-cadbfea0641f"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "[nltk_data] Downloading package stopwords to /root/nltk_data...\n",
            "[nltk_data]   Unzipping corpora/stopwords.zip.\n",
            "[nltk_data] Downloading package punkt to /root/nltk_data...\n",
            "[nltk_data]   Unzipping tokenizers/punkt.zip.\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "True"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Preprocessing"
      ],
      "metadata": {
        "id": "JSvbEUMYGkWp"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Function to clean and preprocess a single tweet\n",
        "def clean_and_preprocess(coffee):\n",
        "    # Convert to lowercase\n",
        "    coffee = coffee.lower()\n",
        "\n",
        "    # Remove URLs\n",
        "    coffee = re.sub(r'http\\S+|www\\S+|https\\S+', '', coffee, flags=re.MULTILINE)\n",
        "\n",
        "    # Remove mentions\n",
        "    #tweet = re.sub(r'@\\w+', '', tweet)\n",
        "\n",
        "    # Remove special characters and numbers\n",
        "    coffee = re.sub(r'[^a-zA-Z\\s]', '', coffee)\n",
        "\n",
        "    # Tokenize the tweet\n",
        "    words = word_tokenize(coffee)\n",
        "\n",
        "    # Remove stopwords\n",
        "    stop_words = set(stopwords.words('english'))\n",
        "    words = [word for word in words if word not in stop_words]\n",
        "\n",
        "    # Join the words back into a single string\n",
        "    cleaned_coffee = ' '.join(words)\n",
        "\n",
        "    return cleaned_coffee\n",
        "\n",
        "# Apply the cleaning function to each tweet in the 'text' column\n",
        "data['cleaned_Review'] = data['Review'].apply(clean_and_preprocess)\n",
        "\n",
        "# Display the cleaned dataset\n",
        "print(\"\\nCleaned Dataset:\")\n",
        "print(data[ 'cleaned_Review'].head())"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Zoi0TgHWGmkN",
        "outputId": "c0709abe-79e2-4d03-db13-861a43e1c363"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "Cleaned Dataset:\n",
            "0    amber ladonna starbucks southwest parkway alwa...\n",
            "1    starbucks fire station altamonte springs fl ma...\n",
            "2    wanted go way recognize starbucks employee bil...\n",
            "3    friend starbucks card didnt work thankful work...\n",
            "4    im kick drinking cups warm water work instacar...\n",
            "Name: cleaned_Review, dtype: object\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data.head(10)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 536
        },
        "id": "YDNADvELH67w",
        "outputId": "be80b4db-1293-4594-fc4b-429da1fabdff"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       name           location                     Date  Rating  \\\n",
              "0     Helen  Wichita Falls, TX  Reviewed Sept. 13, 2023     5.0   \n",
              "1  Courtney         Apopka, FL   Reviewed July 16, 2023     5.0   \n",
              "2  Daynelle  Cranberry Twp, PA    Reviewed July 5, 2023     5.0   \n",
              "3    Taylor        Seattle, WA    Reviewed May 26, 2023     5.0   \n",
              "4   Tenessa        Gresham, OR   Reviewed Jan. 22, 2023     5.0   \n",
              "5    Alyssa      Sunnyvale, TX  Reviewed Sept. 14, 2023     1.0   \n",
              "6       ken    Spring Hill, FL   Reviewed Sept. 8, 2023     1.0   \n",
              "7     Nikki      Asheville, NC   Reviewed Aug. 25, 2023     1.0   \n",
              "8      Alex   Reisterstown, MD    Reviewed Aug. 5, 2023     1.0   \n",
              "9     Sunny   Zionville, Other    Reviewed Aug. 4, 2023     1.0   \n",
              "\n",
              "                                              Review  \\\n",
              "0  Amber and LaDonna at the Starbucks on Southwes...   \n",
              "1  ** at the Starbucks by the fire station on 436...   \n",
              "2  I just wanted to go out of my way to recognize...   \n",
              "3  Me and my friend were at Starbucks and my card...   \n",
              "4  I’m on this kick of drinking 5 cups of warm wa...   \n",
              "5  We had to correct them on our order 3 times. T...   \n",
              "6  I have tried Starbucks several different times...   \n",
              "7  Starbucks near me just launched new fall foods...   \n",
              "8  I ordered online for the Reisterstown Rd, St T...   \n",
              "9  Staff at the Smythe St. Superstore location in...   \n",
              "\n",
              "                                         Image_Links  \\\n",
              "0                                      ['No Images']   \n",
              "1                                      ['No Images']   \n",
              "2  ['https://media.consumeraffairs.com/files/cach...   \n",
              "3                                      ['No Images']   \n",
              "4  ['https://media.consumeraffairs.com/files/cach...   \n",
              "5                                      ['No Images']   \n",
              "6                                      ['No Images']   \n",
              "7                                      ['No Images']   \n",
              "8                                      ['No Images']   \n",
              "9                                      ['No Images']   \n",
              "\n",
              "                                      cleaned_Review  \n",
              "0  amber ladonna starbucks southwest parkway alwa...  \n",
              "1  starbucks fire station altamonte springs fl ma...  \n",
              "2  wanted go way recognize starbucks employee bil...  \n",
              "3  friend starbucks card didnt work thankful work...  \n",
              "4  im kick drinking cups warm water work instacar...  \n",
              "5  correct order times never got right manager ca...  \n",
              "6  tried starbucks several different times differ...  \n",
              "7  starbucks near launched new fall foods beverag...  \n",
              "8  ordered online reisterstown rd st thomas sc ga...  \n",
              "9  staff smythe st superstore location fredericto...  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-9fc3490b-e1a1-4ff9-a8cc-d9b630ba303f\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>name</th>\n",
              "      <th>location</th>\n",
              "      <th>Date</th>\n",
              "      <th>Rating</th>\n",
              "      <th>Review</th>\n",
              "      <th>Image_Links</th>\n",
              "      <th>cleaned_Review</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Helen</td>\n",
              "      <td>Wichita Falls, TX</td>\n",
              "      <td>Reviewed Sept. 13, 2023</td>\n",
              "      <td>5.0</td>\n",
              "      <td>Amber and LaDonna at the Starbucks on Southwes...</td>\n",
              "      <td>['No Images']</td>\n",
              "      <td>amber ladonna starbucks southwest parkway alwa...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Courtney</td>\n",
              "      <td>Apopka, FL</td>\n",
              "      <td>Reviewed July 16, 2023</td>\n",
              "      <td>5.0</td>\n",
              "      <td>** at the Starbucks by the fire station on 436...</td>\n",
              "      <td>['No Images']</td>\n",
              "      <td>starbucks fire station altamonte springs fl ma...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Daynelle</td>\n",
              "      <td>Cranberry Twp, PA</td>\n",
              "      <td>Reviewed July 5, 2023</td>\n",
              "      <td>5.0</td>\n",
              "      <td>I just wanted to go out of my way to recognize...</td>\n",
              "      <td>['https://media.consumeraffairs.com/files/cach...</td>\n",
              "      <td>wanted go way recognize starbucks employee bil...</td>\n",
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              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Taylor</td>\n",
              "      <td>Seattle, WA</td>\n",
              "      <td>Reviewed May 26, 2023</td>\n",
              "      <td>5.0</td>\n",
              "      <td>Me and my friend were at Starbucks and my card...</td>\n",
              "      <td>['No Images']</td>\n",
              "      <td>friend starbucks card didnt work thankful work...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Tenessa</td>\n",
              "      <td>Gresham, OR</td>\n",
              "      <td>Reviewed Jan. 22, 2023</td>\n",
              "      <td>5.0</td>\n",
              "      <td>I’m on this kick of drinking 5 cups of warm wa...</td>\n",
              "      <td>['https://media.consumeraffairs.com/files/cach...</td>\n",
              "      <td>im kick drinking cups warm water work instacar...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Alyssa</td>\n",
              "      <td>Sunnyvale, TX</td>\n",
              "      <td>Reviewed Sept. 14, 2023</td>\n",
              "      <td>1.0</td>\n",
              "      <td>We had to correct them on our order 3 times. T...</td>\n",
              "      <td>['No Images']</td>\n",
              "      <td>correct order times never got right manager ca...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>ken</td>\n",
              "      <td>Spring Hill, FL</td>\n",
              "      <td>Reviewed Sept. 8, 2023</td>\n",
              "      <td>1.0</td>\n",
              "      <td>I have tried Starbucks several different times...</td>\n",
              "      <td>['No Images']</td>\n",
              "      <td>tried starbucks several different times differ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>Nikki</td>\n",
              "      <td>Asheville, NC</td>\n",
              "      <td>Reviewed Aug. 25, 2023</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Starbucks near me just launched new fall foods...</td>\n",
              "      <td>['No Images']</td>\n",
              "      <td>starbucks near launched new fall foods beverag...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>Alex</td>\n",
              "      <td>Reisterstown, MD</td>\n",
              "      <td>Reviewed Aug. 5, 2023</td>\n",
              "      <td>1.0</td>\n",
              "      <td>I ordered online for the Reisterstown Rd, St T...</td>\n",
              "      <td>['No Images']</td>\n",
              "      <td>ordered online reisterstown rd st thomas sc ga...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>Sunny</td>\n",
              "      <td>Zionville, Other</td>\n",
              "      <td>Reviewed Aug. 4, 2023</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Staff at the Smythe St. Superstore location in...</td>\n",
              "      <td>['No Images']</td>\n",
              "      <td>staff smythe st superstore location fredericto...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-9fc3490b-e1a1-4ff9-a8cc-d9b630ba303f')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
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              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
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              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
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              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
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              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
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              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
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              "  </style>\n",
              "\n",
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              "      const buttonEl =\n",
              "        document.querySelector('#df-9fc3490b-e1a1-4ff9-a8cc-d9b630ba303f 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-9fc3490b-e1a1-4ff9-a8cc-d9b630ba303f');\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",
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              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
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              "  [theme=dark] .colab-df-quickchart {\n",
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              "\n",
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              "  }\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",
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              "</style>\n",
              "\n",
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              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-e9ae7e00-961b-4b06-a20f-0b00b7f5ac5f button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Sentimental Analysis"
      ],
      "metadata": {
        "id": "RnoH8hMnIqvT"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#Create an instance of the VADER sentiment analyzer\n",
        "analyzer = SentimentIntensityAnalyzer()\n",
        "\n",
        "#Define a function to perform sentiment analysis using VADER\n",
        "def get_sentiment(coffee):\n",
        "    Rating = analyzer.polarity_scores(coffee)\n",
        "    compound_score = Rating['compound']\n",
        "    return compound_score\n",
        "\n",
        "# Apply the function to the 'tokens' column of the DataFrame\n",
        "data['SentimentVADER'] = data['cleaned_Review'].apply(get_sentiment)\n",
        "\n",
        "# Print the DataFrame with sentiment scores\n",
        "print(data['SentimentVADER'])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "XZRbGNbbIpL-",
        "outputId": "1aa80616-71ce-4ab2-8952-a36af64169fb"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0      0.8779\n",
            "1      0.9670\n",
            "2      0.4215\n",
            "3      0.9028\n",
            "4      0.9714\n",
            "        ...  \n",
            "700   -0.1779\n",
            "701   -0.2960\n",
            "702   -0.2732\n",
            "703    0.0000\n",
            "704    0.8957\n",
            "Name: SentimentVADER, Length: 705, dtype: float64\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data.head(10)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 675
        },
        "id": "pu_-QpV8JCdi",
        "outputId": "ab18db07-291e-4888-a398-2aa6d68f0875"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       name           location                     Date  Rating  \\\n",
              "0     Helen  Wichita Falls, TX  Reviewed Sept. 13, 2023     5.0   \n",
              "1  Courtney         Apopka, FL   Reviewed July 16, 2023     5.0   \n",
              "2  Daynelle  Cranberry Twp, PA    Reviewed July 5, 2023     5.0   \n",
              "3    Taylor        Seattle, WA    Reviewed May 26, 2023     5.0   \n",
              "4   Tenessa        Gresham, OR   Reviewed Jan. 22, 2023     5.0   \n",
              "5    Alyssa      Sunnyvale, TX  Reviewed Sept. 14, 2023     1.0   \n",
              "6       ken    Spring Hill, FL   Reviewed Sept. 8, 2023     1.0   \n",
              "7     Nikki      Asheville, NC   Reviewed Aug. 25, 2023     1.0   \n",
              "8      Alex   Reisterstown, MD    Reviewed Aug. 5, 2023     1.0   \n",
              "9     Sunny   Zionville, Other    Reviewed Aug. 4, 2023     1.0   \n",
              "\n",
              "                                              Review  \\\n",
              "0  Amber and LaDonna at the Starbucks on Southwes...   \n",
              "1  ** at the Starbucks by the fire station on 436...   \n",
              "2  I just wanted to go out of my way to recognize...   \n",
              "3  Me and my friend were at Starbucks and my card...   \n",
              "4  I’m on this kick of drinking 5 cups of warm wa...   \n",
              "5  We had to correct them on our order 3 times. T...   \n",
              "6  I have tried Starbucks several different times...   \n",
              "7  Starbucks near me just launched new fall foods...   \n",
              "8  I ordered online for the Reisterstown Rd, St T...   \n",
              "9  Staff at the Smythe St. Superstore location in...   \n",
              "\n",
              "                                         Image_Links  \\\n",
              "0                                      ['No Images']   \n",
              "1                                      ['No Images']   \n",
              "2  ['https://media.consumeraffairs.com/files/cach...   \n",
              "3                                      ['No Images']   \n",
              "4  ['https://media.consumeraffairs.com/files/cach...   \n",
              "5                                      ['No Images']   \n",
              "6                                      ['No Images']   \n",
              "7                                      ['No Images']   \n",
              "8                                      ['No Images']   \n",
              "9                                      ['No Images']   \n",
              "\n",
              "                                      cleaned_Review  SentimentVADER  \n",
              "0  amber ladonna starbucks southwest parkway alwa...          0.8779  \n",
              "1  starbucks fire station altamonte springs fl ma...          0.9670  \n",
              "2  wanted go way recognize starbucks employee bil...          0.4215  \n",
              "3  friend starbucks card didnt work thankful work...          0.9028  \n",
              "4  im kick drinking cups warm water work instacar...          0.9714  \n",
              "5  correct order times never got right manager ca...         -0.8316  \n",
              "6  tried starbucks several different times differ...          0.0000  \n",
              "7  starbucks near launched new fall foods beverag...          0.8885  \n",
              "8  ordered online reisterstown rd st thomas sc ga...         -0.8316  \n",
              "9  staff smythe st superstore location fredericto...         -0.7655  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-d01df20e-b746-48d4-bf35-2bd18ba4cc77\" 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>name</th>\n",
              "      <th>location</th>\n",
              "      <th>Date</th>\n",
              "      <th>Rating</th>\n",
              "      <th>Review</th>\n",
              "      <th>Image_Links</th>\n",
              "      <th>cleaned_Review</th>\n",
              "      <th>SentimentVADER</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Helen</td>\n",
              "      <td>Wichita Falls, TX</td>\n",
              "      <td>Reviewed Sept. 13, 2023</td>\n",
              "      <td>5.0</td>\n",
              "      <td>Amber and LaDonna at the Starbucks on Southwes...</td>\n",
              "      <td>['No Images']</td>\n",
              "      <td>amber ladonna starbucks southwest parkway alwa...</td>\n",
              "      <td>0.8779</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Courtney</td>\n",
              "      <td>Apopka, FL</td>\n",
              "      <td>Reviewed July 16, 2023</td>\n",
              "      <td>5.0</td>\n",
              "      <td>** at the Starbucks by the fire station on 436...</td>\n",
              "      <td>['No Images']</td>\n",
              "      <td>starbucks fire station altamonte springs fl ma...</td>\n",
              "      <td>0.9670</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Daynelle</td>\n",
              "      <td>Cranberry Twp, PA</td>\n",
              "      <td>Reviewed July 5, 2023</td>\n",
              "      <td>5.0</td>\n",
              "      <td>I just wanted to go out of my way to recognize...</td>\n",
              "      <td>['https://media.consumeraffairs.com/files/cach...</td>\n",
              "      <td>wanted go way recognize starbucks employee bil...</td>\n",
              "      <td>0.4215</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Taylor</td>\n",
              "      <td>Seattle, WA</td>\n",
              "      <td>Reviewed May 26, 2023</td>\n",
              "      <td>5.0</td>\n",
              "      <td>Me and my friend were at Starbucks and my card...</td>\n",
              "      <td>['No Images']</td>\n",
              "      <td>friend starbucks card didnt work thankful work...</td>\n",
              "      <td>0.9028</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Tenessa</td>\n",
              "      <td>Gresham, OR</td>\n",
              "      <td>Reviewed Jan. 22, 2023</td>\n",
              "      <td>5.0</td>\n",
              "      <td>I’m on this kick of drinking 5 cups of warm wa...</td>\n",
              "      <td>['https://media.consumeraffairs.com/files/cach...</td>\n",
              "      <td>im kick drinking cups warm water work instacar...</td>\n",
              "      <td>0.9714</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Alyssa</td>\n",
              "      <td>Sunnyvale, TX</td>\n",
              "      <td>Reviewed Sept. 14, 2023</td>\n",
              "      <td>1.0</td>\n",
              "      <td>We had to correct them on our order 3 times. T...</td>\n",
              "      <td>['No Images']</td>\n",
              "      <td>correct order times never got right manager ca...</td>\n",
              "      <td>-0.8316</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>ken</td>\n",
              "      <td>Spring Hill, FL</td>\n",
              "      <td>Reviewed Sept. 8, 2023</td>\n",
              "      <td>1.0</td>\n",
              "      <td>I have tried Starbucks several different times...</td>\n",
              "      <td>['No Images']</td>\n",
              "      <td>tried starbucks several different times differ...</td>\n",
              "      <td>0.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>Nikki</td>\n",
              "      <td>Asheville, NC</td>\n",
              "      <td>Reviewed Aug. 25, 2023</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Starbucks near me just launched new fall foods...</td>\n",
              "      <td>['No Images']</td>\n",
              "      <td>starbucks near launched new fall foods beverag...</td>\n",
              "      <td>0.8885</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>Alex</td>\n",
              "      <td>Reisterstown, MD</td>\n",
              "      <td>Reviewed Aug. 5, 2023</td>\n",
              "      <td>1.0</td>\n",
              "      <td>I ordered online for the Reisterstown Rd, St T...</td>\n",
              "      <td>['No Images']</td>\n",
              "      <td>ordered online reisterstown rd st thomas sc ga...</td>\n",
              "      <td>-0.8316</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>Sunny</td>\n",
              "      <td>Zionville, Other</td>\n",
              "      <td>Reviewed Aug. 4, 2023</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Staff at the Smythe St. Superstore location in...</td>\n",
              "      <td>['No Images']</td>\n",
              "      <td>staff smythe st superstore location fredericto...</td>\n",
              "      <td>-0.7655</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-d01df20e-b746-48d4-bf35-2bd18ba4cc77')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-d01df20e-b746-48d4-bf35-2bd18ba4cc77 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-d01df20e-b746-48d4-bf35-2bd18ba4cc77');\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-cdf0afaa-ab75-4358-a121-5ff459f7492f\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-cdf0afaa-ab75-4358-a121-5ff459f7492f')\"\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-cdf0afaa-ab75-4358-a121-5ff459f7492f button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "temp = data.groupby('Rating').count()['Review'].reset_index().sort_values(by='Review',ascending=False)\n",
        "temp.style.background_gradient(cmap='Purples')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "tU41umlBJo6_",
        "outputId": "a0747bd6-37ec-49d1-ff4d-27420e559711"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x78f69999ef50>"
            ],
            "text/html": [
              "<style type=\"text/css\">\n",
              "#T_82edb_row0_col0, #T_82edb_row4_col1 {\n",
              "  background-color: #fcfbfd;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82edb_row0_col1, #T_82edb_row2_col0 {\n",
              "  background-color: #3f007d;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82edb_row1_col0 {\n",
              "  background-color: #dadaeb;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82edb_row1_col1 {\n",
              "  background-color: #eae8f2;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82edb_row2_col1 {\n",
              "  background-color: #f0eef5;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82edb_row3_col0 {\n",
              "  background-color: #6950a3;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82edb_row3_col1 {\n",
              "  background-color: #fbfafc;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82edb_row4_col0 {\n",
              "  background-color: #9e9ac8;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "</style>\n",
              "<table id=\"T_82edb\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th class=\"blank level0\" >&nbsp;</th>\n",
              "      <th id=\"T_82edb_level0_col0\" class=\"col_heading level0 col0\" >Rating</th>\n",
              "      <th id=\"T_82edb_level0_col1\" class=\"col_heading level0 col1\" >Review</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th id=\"T_82edb_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
              "      <td id=\"T_82edb_row0_col0\" class=\"data row0 col0\" >1.000000</td>\n",
              "      <td id=\"T_82edb_row0_col1\" class=\"data row0 col1\" >451</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_82edb_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
              "      <td id=\"T_82edb_row1_col0\" class=\"data row1 col0\" >2.000000</td>\n",
              "      <td id=\"T_82edb_row1_col1\" class=\"data row1 col1\" >99</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_82edb_level0_row2\" class=\"row_heading level0 row2\" >4</th>\n",
              "      <td id=\"T_82edb_row2_col0\" class=\"data row2 col0\" >5.000000</td>\n",
              "      <td id=\"T_82edb_row2_col1\" class=\"data row2 col1\" >83</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_82edb_level0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
              "      <td id=\"T_82edb_row3_col0\" class=\"data row3 col0\" >4.000000</td>\n",
              "      <td id=\"T_82edb_row3_col1\" class=\"data row3 col1\" >39</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_82edb_level0_row4\" class=\"row_heading level0 row4\" >2</th>\n",
              "      <td id=\"T_82edb_row4_col0\" class=\"data row4 col0\" >3.000000</td>\n",
              "      <td id=\"T_82edb_row4_col1\" class=\"data row4 col1\" >33</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n"
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(12,6))\n",
        "sns.countplot(x='Rating',data=data)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 559
        },
        "id": "Xz6ZQVzMM7d1",
        "outputId": "35592fe7-1bfb-41df-efff-a2179485e3fe"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: xlabel='Rating', ylabel='count'>"
            ]
          },
          "metadata": {},
          "execution_count": 14
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "fig = go.Figure(go.Funnelarea(\n",
        "    text =temp.Rating,\n",
        "    values = temp.Review,\n",
        "    title = {\"position\": \"top center\", \"text\": \"Funnel-Chart of Sentiment Rating Distribution\"}\n",
        "    ))\n",
        "fig.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 542
        },
        "id": "b5GmrUYRNFbP",
        "outputId": "6f3b97dc-5a8d-470d-8c8b-9d73b796466c"
      },
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
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    {
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      "source": [
        "# Define a function to categorize sentiment based on VADER score\n",
        "def categorize_sentiment(score):\n",
        "    if score < 0:\n",
        "        return 'negative'\n",
        "    elif score > 0:\n",
        "        return 'positive'\n",
        "    else:\n",
        "        return 'neutral'\n",
        "\n",
        "# Apply the function to create the 'SentimentCategory' column\n",
        "data['SentimentCategory'] = data['SentimentVADER'].apply(categorize_sentiment)"
      ],
      "metadata": {
        "id": "fWYzbFfbNx9R"
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      "execution_count": 16,
      "outputs": []
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      "source": [
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          "data": {
            "text/plain": [
              "       name           location                     Date  Rating  \\\n",
              "0     Helen  Wichita Falls, TX  Reviewed Sept. 13, 2023     5.0   \n",
              "1  Courtney         Apopka, FL   Reviewed July 16, 2023     5.0   \n",
              "2  Daynelle  Cranberry Twp, PA    Reviewed July 5, 2023     5.0   \n",
              "3    Taylor        Seattle, WA    Reviewed May 26, 2023     5.0   \n",
              "4   Tenessa        Gresham, OR   Reviewed Jan. 22, 2023     5.0   \n",
              "5    Alyssa      Sunnyvale, TX  Reviewed Sept. 14, 2023     1.0   \n",
              "6       ken    Spring Hill, FL   Reviewed Sept. 8, 2023     1.0   \n",
              "7     Nikki      Asheville, NC   Reviewed Aug. 25, 2023     1.0   \n",
              "8      Alex   Reisterstown, MD    Reviewed Aug. 5, 2023     1.0   \n",
              "9     Sunny   Zionville, Other    Reviewed Aug. 4, 2023     1.0   \n",
              "\n",
              "                                              Review  \\\n",
              "0  Amber and LaDonna at the Starbucks on Southwes...   \n",
              "1  ** at the Starbucks by the fire station on 436...   \n",
              "2  I just wanted to go out of my way to recognize...   \n",
              "3  Me and my friend were at Starbucks and my card...   \n",
              "4  I’m on this kick of drinking 5 cups of warm wa...   \n",
              "5  We had to correct them on our order 3 times. T...   \n",
              "6  I have tried Starbucks several different times...   \n",
              "7  Starbucks near me just launched new fall foods...   \n",
              "8  I ordered online for the Reisterstown Rd, St T...   \n",
              "9  Staff at the Smythe St. Superstore location in...   \n",
              "\n",
              "                                         Image_Links  \\\n",
              "0                                      ['No Images']   \n",
              "1                                      ['No Images']   \n",
              "2  ['https://media.consumeraffairs.com/files/cach...   \n",
              "3                                      ['No Images']   \n",
              "4  ['https://media.consumeraffairs.com/files/cach...   \n",
              "5                                      ['No Images']   \n",
              "6                                      ['No Images']   \n",
              "7                                      ['No Images']   \n",
              "8                                      ['No Images']   \n",
              "9                                      ['No Images']   \n",
              "\n",
              "                                      cleaned_Review  SentimentVADER  \\\n",
              "0  amber ladonna starbucks southwest parkway alwa...          0.8779   \n",
              "1  starbucks fire station altamonte springs fl ma...          0.9670   \n",
              "2  wanted go way recognize starbucks employee bil...          0.4215   \n",
              "3  friend starbucks card didnt work thankful work...          0.9028   \n",
              "4  im kick drinking cups warm water work instacar...          0.9714   \n",
              "5  correct order times never got right manager ca...         -0.8316   \n",
              "6  tried starbucks several different times differ...          0.0000   \n",
              "7  starbucks near launched new fall foods beverag...          0.8885   \n",
              "8  ordered online reisterstown rd st thomas sc ga...         -0.8316   \n",
              "9  staff smythe st superstore location fredericto...         -0.7655   \n",
              "\n",
              "  SentimentCategory  \n",
              "0          positive  \n",
              "1          positive  \n",
              "2          positive  \n",
              "3          positive  \n",
              "4          positive  \n",
              "5          negative  \n",
              "6           neutral  \n",
              "7          positive  \n",
              "8          negative  \n",
              "9          negative  "
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              "      <th>name</th>\n",
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              "      <th>0</th>\n",
              "      <td>Helen</td>\n",
              "      <td>Wichita Falls, TX</td>\n",
              "      <td>Reviewed Sept. 13, 2023</td>\n",
              "      <td>5.0</td>\n",
              "      <td>Amber and LaDonna at the Starbucks on Southwes...</td>\n",
              "      <td>['No Images']</td>\n",
              "      <td>amber ladonna starbucks southwest parkway alwa...</td>\n",
              "      <td>0.8779</td>\n",
              "      <td>positive</td>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Courtney</td>\n",
              "      <td>Apopka, FL</td>\n",
              "      <td>Reviewed July 16, 2023</td>\n",
              "      <td>5.0</td>\n",
              "      <td>** at the Starbucks by the fire station on 436...</td>\n",
              "      <td>['No Images']</td>\n",
              "      <td>starbucks fire station altamonte springs fl ma...</td>\n",
              "      <td>0.9670</td>\n",
              "      <td>positive</td>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Daynelle</td>\n",
              "      <td>Cranberry Twp, PA</td>\n",
              "      <td>Reviewed July 5, 2023</td>\n",
              "      <td>5.0</td>\n",
              "      <td>I just wanted to go out of my way to recognize...</td>\n",
              "      <td>['https://media.consumeraffairs.com/files/cach...</td>\n",
              "      <td>wanted go way recognize starbucks employee bil...</td>\n",
              "      <td>0.4215</td>\n",
              "      <td>positive</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Taylor</td>\n",
              "      <td>Seattle, WA</td>\n",
              "      <td>Reviewed May 26, 2023</td>\n",
              "      <td>5.0</td>\n",
              "      <td>Me and my friend were at Starbucks and my card...</td>\n",
              "      <td>['No Images']</td>\n",
              "      <td>friend starbucks card didnt work thankful work...</td>\n",
              "      <td>0.9028</td>\n",
              "      <td>positive</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Tenessa</td>\n",
              "      <td>Gresham, OR</td>\n",
              "      <td>Reviewed Jan. 22, 2023</td>\n",
              "      <td>5.0</td>\n",
              "      <td>I’m on this kick of drinking 5 cups of warm wa...</td>\n",
              "      <td>['https://media.consumeraffairs.com/files/cach...</td>\n",
              "      <td>im kick drinking cups warm water work instacar...</td>\n",
              "      <td>0.9714</td>\n",
              "      <td>positive</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Alyssa</td>\n",
              "      <td>Sunnyvale, TX</td>\n",
              "      <td>Reviewed Sept. 14, 2023</td>\n",
              "      <td>1.0</td>\n",
              "      <td>We had to correct them on our order 3 times. T...</td>\n",
              "      <td>['No Images']</td>\n",
              "      <td>correct order times never got right manager ca...</td>\n",
              "      <td>-0.8316</td>\n",
              "      <td>negative</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>ken</td>\n",
              "      <td>Spring Hill, FL</td>\n",
              "      <td>Reviewed Sept. 8, 2023</td>\n",
              "      <td>1.0</td>\n",
              "      <td>I have tried Starbucks several different times...</td>\n",
              "      <td>['No Images']</td>\n",
              "      <td>tried starbucks several different times differ...</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>neutral</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>Nikki</td>\n",
              "      <td>Asheville, NC</td>\n",
              "      <td>Reviewed Aug. 25, 2023</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Starbucks near me just launched new fall foods...</td>\n",
              "      <td>['No Images']</td>\n",
              "      <td>starbucks near launched new fall foods beverag...</td>\n",
              "      <td>0.8885</td>\n",
              "      <td>positive</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>Alex</td>\n",
              "      <td>Reisterstown, MD</td>\n",
              "      <td>Reviewed Aug. 5, 2023</td>\n",
              "      <td>1.0</td>\n",
              "      <td>I ordered online for the Reisterstown Rd, St T...</td>\n",
              "      <td>['No Images']</td>\n",
              "      <td>ordered online reisterstown rd st thomas sc ga...</td>\n",
              "      <td>-0.8316</td>\n",
              "      <td>negative</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>Sunny</td>\n",
              "      <td>Zionville, Other</td>\n",
              "      <td>Reviewed Aug. 4, 2023</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Staff at the Smythe St. Superstore location in...</td>\n",
              "      <td>['No Images']</td>\n",
              "      <td>staff smythe st superstore location fredericto...</td>\n",
              "      <td>-0.7655</td>\n",
              "      <td>negative</td>\n",
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              "\n",
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              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-a324ea30-261c-4c13-b7db-997fa68415ec 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-a324ea30-261c-4c13-b7db-997fa68415ec');\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",
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              "\n",
              "  .colab-df-quickchart {\n",
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              "    border: none;\n",
              "    border-radius: 50%;\n",
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              "\n",
              "  .colab-df-quickchart:hover {\n",
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              "    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",
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              "    20% {\n",
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              "    }\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",
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              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
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              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
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              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Topic Modeling\n"
      ],
      "metadata": {
        "id": "jGox91hUFB8n"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import os\n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "from plotly.offline import download_plotlyjs, init_notebook_mode, plot, iplot\n",
        "import plotly as py\n",
        "import plotly.graph_objs as go\n",
        "import gensim\n",
        "from gensim import corpora, models, similarities\n",
        "import logging\n",
        "import tempfile\n",
        "from nltk.corpus import stopwords\n",
        "from string import punctuation\n",
        "from collections import OrderedDict\n",
        "import seaborn as sns\n",
        "!pip install pyLDAvis\n",
        "\n",
        "import pyLDAvis\n",
        "import pyLDAvis.gensim_models\n",
        "import matplotlib.pyplot as plt\n",
        "%matplotlib inline\n",
        "\n",
        "init_notebook_mode(connected=True) #do not miss this line\n",
        "\n",
        "import warnings\n",
        "warnings.filterwarnings(\"ignore\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 801
        },
        "id": "8i8D1sZVNDh_",
        "outputId": "6c6030a8-cd90-4106-ff3f-4dd696bf6277"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting pyLDAvis\n",
            "  Downloading pyLDAvis-3.4.1-py3-none-any.whl (2.6 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m2.6/2.6 MB\u001b[0m \u001b[31m13.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting numpy>=1.24.2 (from pyLDAvis)\n",
            "  Downloading numpy-1.26.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (18.2 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m18.2/18.2 MB\u001b[0m \u001b[31m37.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: scipy in /usr/local/lib/python3.10/dist-packages (from pyLDAvis) (1.11.3)\n",
            "Collecting pandas>=2.0.0 (from pyLDAvis)\n",
            "  Downloading pandas-2.1.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (12.3 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m12.3/12.3 MB\u001b[0m \u001b[31m52.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: joblib>=1.2.0 in /usr/local/lib/python3.10/dist-packages (from pyLDAvis) (1.3.2)\n",
            "Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/dist-packages (from pyLDAvis) (3.1.2)\n",
            "Requirement already satisfied: numexpr in /usr/local/lib/python3.10/dist-packages (from pyLDAvis) (2.8.7)\n",
            "Collecting funcy (from pyLDAvis)\n",
            "  Downloading funcy-2.0-py2.py3-none-any.whl (30 kB)\n",
            "Requirement already satisfied: scikit-learn>=1.0.0 in /usr/local/lib/python3.10/dist-packages (from pyLDAvis) (1.2.2)\n",
            "Requirement already satisfied: gensim in /usr/local/lib/python3.10/dist-packages (from pyLDAvis) (4.3.2)\n",
            "Requirement already satisfied: setuptools in /usr/local/lib/python3.10/dist-packages (from pyLDAvis) (67.7.2)\n",
            "Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.10/dist-packages (from pandas>=2.0.0->pyLDAvis) (2.8.2)\n",
            "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.10/dist-packages (from pandas>=2.0.0->pyLDAvis) (2023.3.post1)\n",
            "Collecting tzdata>=2022.1 (from pandas>=2.0.0->pyLDAvis)\n",
            "  Downloading tzdata-2023.3-py2.py3-none-any.whl (341 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m341.8/341.8 kB\u001b[0m \u001b[31m17.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: threadpoolctl>=2.0.0 in /usr/local/lib/python3.10/dist-packages (from scikit-learn>=1.0.0->pyLDAvis) (3.2.0)\n",
            "Requirement already satisfied: smart-open>=1.8.1 in /usr/local/lib/python3.10/dist-packages (from gensim->pyLDAvis) (6.4.0)\n",
            "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->pyLDAvis) (2.1.3)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.8.2->pandas>=2.0.0->pyLDAvis) (1.16.0)\n",
            "Installing collected packages: funcy, tzdata, numpy, pandas, pyLDAvis\n",
            "  Attempting uninstall: numpy\n",
            "    Found existing installation: numpy 1.23.5\n",
            "    Uninstalling numpy-1.23.5:\n",
            "      Successfully uninstalled numpy-1.23.5\n",
            "  Attempting uninstall: pandas\n",
            "    Found existing installation: pandas 1.5.3\n",
            "    Uninstalling pandas-1.5.3:\n",
            "      Successfully uninstalled pandas-1.5.3\n",
            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
            "lida 0.0.10 requires fastapi, which is not installed.\n",
            "lida 0.0.10 requires kaleido, which is not installed.\n",
            "lida 0.0.10 requires python-multipart, which is not installed.\n",
            "lida 0.0.10 requires uvicorn, which is not installed.\n",
            "cupy-cuda11x 11.0.0 requires numpy<1.26,>=1.20, but you have numpy 1.26.2 which is incompatible.\n",
            "google-colab 1.0.0 requires pandas==1.5.3, but you have pandas 2.1.3 which is incompatible.\u001b[0m\u001b[31m\n",
            "\u001b[0mSuccessfully installed funcy-2.0 numpy-1.26.2 pandas-2.1.3 pyLDAvis-3.4.1 tzdata-2023.3\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "        <script type=\"text/javascript\">\n",
              "        window.PlotlyConfig = {MathJaxConfig: 'local'};\n",
              "        if (window.MathJax && window.MathJax.Hub && window.MathJax.Hub.Config) {window.MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n",
              "        if (typeof require !== 'undefined') {\n",
              "        require.undef(\"plotly\");\n",
              "        requirejs.config({\n",
              "            paths: {\n",
              "                'plotly': ['https://cdn.plot.ly/plotly-2.24.1.min']\n",
              "            }\n",
              "        });\n",
              "        require(['plotly'], function(Plotly) {\n",
              "            window._Plotly = Plotly;\n",
              "        });\n",
              "        }\n",
              "        </script>\n",
              "        "
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "datafile = 'reviews_data.csv'"
      ],
      "metadata": {
        "id": "rdtsAYFtNK18"
      },
      "execution_count": 19,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "coffees = pd.read_csv(datafile, encoding='latin1')\n",
        "print(\"Number of Reviews: \",len(coffees['Review']))\n",
        "coffees.head(5)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 223
        },
        "id": "klwKYzeNRULe",
        "outputId": "85e66503-ab3e-4380-e65e-7c16cd4ed431"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Number of Reviews:  850\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       name           location                     Date  Rating  \\\n",
              "0     Helen  Wichita Falls, TX  Reviewed Sept. 13, 2023     5.0   \n",
              "1  Courtney         Apopka, FL   Reviewed July 16, 2023     5.0   \n",
              "2  Daynelle  Cranberry Twp, PA    Reviewed July 5, 2023     5.0   \n",
              "3    Taylor        Seattle, WA    Reviewed May 26, 2023     5.0   \n",
              "4   Tenessa        Gresham, OR   Reviewed Jan. 22, 2023     5.0   \n",
              "\n",
              "                                              Review  \\\n",
              "0  Amber and LaDonna at the Starbucks on Southwes...   \n",
              "1  ** at the Starbucks by the fire station on 436...   \n",
              "2  I just wanted to go out of my way to recognize...   \n",
              "3  Me and my friend were at Starbucks and my card...   \n",
              "4  Iâm on this kick of drinking 5 cups of warm ...   \n",
              "\n",
              "                                         Image_Links  \n",
              "0                                      ['No Images']  \n",
              "1                                      ['No Images']  \n",
              "2  ['https://media.consumeraffairs.com/files/cach...  \n",
              "3                                      ['No Images']  \n",
              "4  ['https://media.consumeraffairs.com/files/cach...  "
            ],
            "text/html": [
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              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
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              "      <th>name</th>\n",
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              "      <td>Helen</td>\n",
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              "      <td>Reviewed Sept. 13, 2023</td>\n",
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              "      <th>1</th>\n",
              "      <td>Courtney</td>\n",
              "      <td>Apopka, FL</td>\n",
              "      <td>Reviewed July 16, 2023</td>\n",
              "      <td>5.0</td>\n",
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              "      <td>Daynelle</td>\n",
              "      <td>Cranberry Twp, PA</td>\n",
              "      <td>Reviewed July 5, 2023</td>\n",
              "      <td>5.0</td>\n",
              "      <td>I just wanted to go out of my way to recognize...</td>\n",
              "      <td>['https://media.consumeraffairs.com/files/cach...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Taylor</td>\n",
              "      <td>Seattle, WA</td>\n",
              "      <td>Reviewed May 26, 2023</td>\n",
              "      <td>5.0</td>\n",
              "      <td>Me and my friend were at Starbucks and my card...</td>\n",
              "      <td>['No Images']</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Tenessa</td>\n",
              "      <td>Gresham, OR</td>\n",
              "      <td>Reviewed Jan. 22, 2023</td>\n",
              "      <td>5.0</td>\n",
              "      <td>Iâm on this kick of drinking 5 cups of warm ...</td>\n",
              "      <td>['https://media.consumeraffairs.com/files/cach...</td>\n",
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          "metadata": {},
          "execution_count": 20
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      ]
    },
    {
      "cell_type": "code",
      "source": [
        "corpus=[]\n",
        "a=[]\n",
        "for i in range(len(coffees['Review'])):\n",
        "        a=coffees['Review'][i]\n",
        "        corpus.append(a)\n",
        "\n",
        "corpus[0:10]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "veIQXRlnNR4t",
        "outputId": "0e9d9b47-a9ac-4f06-d93a-ba10615b2380"
      },
      "execution_count": 21,
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        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['Amber and LaDonna at the Starbucks on Southwest Parkway are always so warm and welcoming. There is always a smile in their voice when they greet you at the drive-thru. And their customer service is always spot-on, they always get my order right and with a smile. I would actually give them more than 5 stars if they were available.',\n",
              " '** at the Starbucks by the fire station on 436 in Altamonte Springs, FL made my day and finally helped me figure out the way to make my drink so Iâ\\x80\\x99d love it. She took time out to talk to me for 2 minutes to make my experience better than what Iâ\\x80\\x99m used to. It was much appreciated! Iâ\\x80\\x99ve had bad experiences one after another at the Starbucks thatâ\\x80\\x99s closest to me in my work building with my drinks not being great along with not great customer service from specific baristas. Niko was refreshing to speak to and pleasant. The drink was perfect! Store 11956',\n",
              " 'I just wanted to go out of my way to recognize a Starbucks employee Billy at the Franklin Park location! I was running late to work & placed an order at the wrong location and not only did he make my order with a smile he made it within 60 seconds! Thank you SOO much I was having a bad morning and people like you just make this world a better place.',\n",
              " 'Me and my friend were at Starbucks and my card didnâ\\x80\\x99t work. Thankful the worker there, paid for our drinks. And was very nice about it, it didnâ\\x80\\x99t seem to bother him that he paid for our drinks. This made my day, but made me look like a fool because my card didnâ\\x80\\x99t work. All thanks to Dillon. At Shoreline WA in Safeway. Thank you so much Dillon for the help, support and, kindness. I rate this 1000/10 if I could but, other than that, 10/10.',\n",
              " 'Iâ\\x80\\x99m on this kick of drinking 5 cups of warm water. I work for Instacart right now and every location of Starbucks I was given free hot water because I asked for it without being charged. I really appreciate Starbucks for giving me the opportunity to do such thing. Thatâ\\x80\\x99s why I give them five stars. They fully have my support. Theyâ\\x80\\x99re super nice and professional and the coffee is great. Go to Starbucks.',\n",
              " 'We had to correct them on our order 3 times. They never got it right then the manager came over to us and said we made her employee uncomfortable because we were trying to correct our order. The manager tried was racist against my stepmom (Chinese) taking over her but when I (**) would talk she would stop talking and listen to me.',\n",
              " \"I have tried Starbucks several different times in different locations just in case it was just the one store. But it's not. If you like coffee that taste like dirt scooped off the ground at a garbage dump, then this is the place for you.\",\n",
              " 'Starbucks near me just launched new fall foods and beverages yesterday. By noon yesterday they were out of all new items. The fall launch is huge and many people look forward to it all year. Maybe if you donâ\\x80\\x99t have enough product to last even a couple of days, push back the launch until you do? I was so happy to get the email that it had come out that I left work on my break to brighten my day and so very disappointed to get there at 12:30pm and find out that it was all gone. Please Starbucks, do better.',\n",
              " 'I ordered online for the Reisterstown Rd, St Thomas SC 99000 and they gave me the wrong drink size so ordered a venti they gave me a grande. Just a bit upset that I paid over 5 bucks for a drink and got the wrong thing.',\n",
              " 'Staff at the Smythe St. Superstore location in Fredericton, NB often seen tired but today, a woman named Senoa (Senora?) was morose, glum, uncommunicative (even after I tried to engage her to sympathize, as there was obviously a bad mood happening), scruffy looking, almost rude. And, the Americano I ordered tastes watery. I go to Starbucks for a treat after a long day. It a difficult experience, to ease stress and have a pleasant experience. Iâ\\x80\\x99m going to sell a different location after todayâ\\x80\\x99s grumpy girl.']"
            ]
          },
          "metadata": {},
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "coffees.head(5)"
      ],
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          "height": 206
        },
        "id": "q2ToxYe_RHIQ",
        "outputId": "2cb29b0a-89dd-42f8-bc6b-17440799cddf"
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      "execution_count": 22,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       name           location                     Date  Rating  \\\n",
              "0     Helen  Wichita Falls, TX  Reviewed Sept. 13, 2023     5.0   \n",
              "1  Courtney         Apopka, FL   Reviewed July 16, 2023     5.0   \n",
              "2  Daynelle  Cranberry Twp, PA    Reviewed July 5, 2023     5.0   \n",
              "3    Taylor        Seattle, WA    Reviewed May 26, 2023     5.0   \n",
              "4   Tenessa        Gresham, OR   Reviewed Jan. 22, 2023     5.0   \n",
              "\n",
              "                                              Review  \\\n",
              "0  Amber and LaDonna at the Starbucks on Southwes...   \n",
              "1  ** at the Starbucks by the fire station on 436...   \n",
              "2  I just wanted to go out of my way to recognize...   \n",
              "3  Me and my friend were at Starbucks and my card...   \n",
              "4  Iâm on this kick of drinking 5 cups of warm ...   \n",
              "\n",
              "                                         Image_Links  \n",
              "0                                      ['No Images']  \n",
              "1                                      ['No Images']  \n",
              "2  ['https://media.consumeraffairs.com/files/cach...  \n",
              "3                                      ['No Images']  \n",
              "4  ['https://media.consumeraffairs.com/files/cach...  "
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              "      <td>Helen</td>\n",
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              "      <th>1</th>\n",
              "      <td>Courtney</td>\n",
              "      <td>Apopka, FL</td>\n",
              "      <td>Reviewed July 16, 2023</td>\n",
              "      <td>5.0</td>\n",
              "      <td>** at the Starbucks by the fire station on 436...</td>\n",
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              "      <td>['https://media.consumeraffairs.com/files/cach...</td>\n",
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              "      <td>Reviewed May 26, 2023</td>\n",
              "      <td>5.0</td>\n",
              "      <td>Me and my friend were at Starbucks and my card...</td>\n",
              "      <td>['No Images']</td>\n",
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              "      <td>Reviewed Jan. 22, 2023</td>\n",
              "      <td>5.0</td>\n",
              "      <td>Iâm on this kick of drinking 5 cups of warm ...</td>\n",
              "      <td>['https://media.consumeraffairs.com/files/cach...</td>\n",
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              "                                                    [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",
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              "\n",
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              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-70c4556a-66c5-4681-8ae8-af22256c7976')\"\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",
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              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    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",
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              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
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              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
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              "      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-70c4556a-66c5-4681-8ae8-af22256c7976 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "TEMP_FOLDER = tempfile.gettempdir()\n",
        "print('Folder \"{}\" will be used to save temporary dictionary and corpus.'.format(TEMP_FOLDER))\n",
        "\n",
        "logging.basicConfig(format='%(asctime)s : %(levelname)s : %(message)s', level=logging.INFO)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Uz5Yc3z1Rl-o",
        "outputId": "cfba1a3c-eadd-44cb-a2eb-10887f50dc54"
      },
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Folder \"/tmp\" will be used to save temporary dictionary and corpus.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import nltk\n",
        "nltk.download('stopwords')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "KbTWN-aDRqZm",
        "outputId": "463e7a30-d122-48b3-eefd-58f6ee27331d"
      },
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "[nltk_data] Downloading package stopwords to /root/nltk_data...\n",
            "[nltk_data]   Package stopwords is already up-to-date!\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "True"
            ]
          },
          "metadata": {},
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# removing common words and tokenizing\n",
        "list1 = ['**']\n",
        "stoplist = stopwords.words('english') + list(punctuation) + list1\n",
        "\n",
        "texts = [[word for word in str(document).lower().split() if word not in stoplist] for document in corpus]\n",
        "\n",
        "dictionary = corpora.Dictionary(texts)\n",
        "dictionary.save(os.path.join(TEMP_FOLDER, 'sb.dict'))  # store the dictionary, for future reference\n",
        "\n",
        "#print(dictionary)\n",
        "#print(dictionary.token2id)"
      ],
      "metadata": {
        "id": "V0axW4NhRrbc"
      },
      "execution_count": 25,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "corpus = [dictionary.doc2bow(text) for text in texts]\n",
        "corpora.MmCorpus.serialize(os.path.join(TEMP_FOLDER, 'sb.mm'), corpus)  # store to disk, for later use"
      ],
      "metadata": {
        "id": "1931yO0qTY1q"
      },
      "execution_count": 55,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "tfidf = models.TfidfModel(corpus) # step 1 -- initialize a model"
      ],
      "metadata": {
        "id": "4Eh3J_9YTv9H"
      },
      "execution_count": 27,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "corpus_tfidf = tfidf[corpus]  # step 2 -- use the model to transform vectors"
      ],
      "metadata": {
        "id": "sr-DlAw0Tw4t"
      },
      "execution_count": 28,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "total_topics = 5"
      ],
      "metadata": {
        "id": "lxsUCXfTTyrj"
      },
      "execution_count": 29,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "lda = gensim.models.LdaMulticore(corpus, id2word=dictionary, num_topics=total_topics)\n",
        "corpus_lda = lda[corpus_tfidf] # create a double wrapper over the original corpus: bow->tfidf->fold-in-lsi"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6FY_vcDET11o",
        "outputId": "d5aadd95-d800-4664-e76b-1ba31ca27447"
      },
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "WARNING:gensim.models.ldamulticore:too few updates, training might not converge; consider increasing the number of passes or iterations to improve accuracy\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Shows the most important topic number"
      ],
      "metadata": {
        "id": "p2Sn5IWRgQCF"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#Show first n important word in the topics:\n",
        "lda.show_topics(total_topics,5)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "aSSifBOWT505",
        "outputId": "810fe1ea-4e9c-49f2-eb4f-9ba67d3e3371"
      },
      "execution_count": 36,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[(0,\n",
              "  '0.021*\"starbucks\" + 0.013*\"coffee\" + 0.008*\"get\" + 0.007*\"go\" + 0.006*\"customer\"'),\n",
              " (1,\n",
              "  '0.019*\"starbucks\" + 0.010*\"coffee\" + 0.006*\"get\" + 0.005*\"one\" + 0.005*\"customer\"'),\n",
              " (2,\n",
              "  '0.024*\"starbucks\" + 0.006*\"coffee\" + 0.006*\"one\" + 0.006*\"would\" + 0.006*\"drink\"'),\n",
              " (3,\n",
              "  '0.011*\"starbucks\" + 0.008*\"coffee\" + 0.008*\"store\" + 0.006*\"go\" + 0.006*\"get\"'),\n",
              " (4,\n",
              "  '0.013*\"starbucks\" + 0.008*\"coffee\" + 0.006*\"get\" + 0.006*\"customer\" + 0.005*\"went\"')]"
            ]
          },
          "metadata": {},
          "execution_count": 36
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "The top topic that were talked about here are Starbucks and Coffee.\n",
        "With the unique value we had, they are probably talking about the starbucks's customer card, the time they get coffee (usually morning), the quantity of drinks they usually order it at the store (which is once) and also the customers' services that they get"
      ],
      "metadata": {
        "id": "0al760IFh-js"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "data_lda = {i: OrderedDict(lda.show_topic(i,25)) for i in range(total_topics)}\n",
        "#data_lda"
      ],
      "metadata": {
        "id": "h9ThyfrkT9JR"
      },
      "execution_count": 32,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df_lda = pd.DataFrame(data_lda)\n",
        "df_lda = df_lda.fillna(0).T\n",
        "print(df_lda.shape)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7zdRv7QnT_MB",
        "outputId": "ea4fc36f-760d-4a14-ee46-544c4d016ff2"
      },
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "(5, 41)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_lda"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 255
        },
        "id": "OYujElXqUBqY",
        "outputId": "07c67f44-d16e-4bc9-ee83-ab07f813c57c"
      },
      "execution_count": 34,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   starbucks    coffee       get        go  customer      like       one  \\\n",
              "0   0.020601  0.013028  0.008304  0.007223  0.005951  0.005630  0.005586   \n",
              "1   0.018842  0.010049  0.005583  0.003766  0.005180  0.004902  0.005391   \n",
              "2   0.024005  0.006175  0.002723  0.000000  0.005547  0.004479  0.006077   \n",
              "3   0.011100  0.008348  0.005806  0.005815  0.003126  0.004067  0.003851   \n",
              "4   0.012586  0.008189  0.006199  0.002628  0.006036  0.002920  0.004359   \n",
              "\n",
              "     always     drink      time  ...      good     every   review   manager  \\\n",
              "0  0.004758  0.004129  0.004087  ...  0.000000  0.000000  0.00000  0.000000   \n",
              "1  0.002592  0.000000  0.002979  ...  0.002845  0.002423  0.00000  0.000000   \n",
              "2  0.002500  0.005871  0.003732  ...  0.000000  0.000000  0.00285  0.002812   \n",
              "3  0.003185  0.002828  0.003730  ...  0.000000  0.002440  0.00000  0.002899   \n",
              "4  0.000000  0.004337  0.004027  ...  0.000000  0.000000  0.00000  0.000000   \n",
              "\n",
              "      money      text    people     make       way       i'm  \n",
              "0  0.000000  0.000000  0.000000  0.00000  0.000000  0.000000  \n",
              "1  0.000000  0.000000  0.000000  0.00000  0.000000  0.000000  \n",
              "2  0.002727  0.002666  0.000000  0.00000  0.000000  0.000000  \n",
              "3  0.000000  0.000000  0.000000  0.00000  0.000000  0.000000  \n",
              "4  0.000000  0.000000  0.002756  0.00249  0.002472  0.002434  \n",
              "\n",
              "[5 rows x 41 columns]"
            ],
            "text/html": [
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              "  <div id=\"df-23dfa632-d724-4f28-9713-728a718b0676\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "    .dataframe tbody tr th {\n",
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              "    .dataframe thead th {\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>starbucks</th>\n",
              "      <th>coffee</th>\n",
              "      <th>get</th>\n",
              "      <th>go</th>\n",
              "      <th>customer</th>\n",
              "      <th>like</th>\n",
              "      <th>one</th>\n",
              "      <th>always</th>\n",
              "      <th>drink</th>\n",
              "      <th>time</th>\n",
              "      <th>...</th>\n",
              "      <th>good</th>\n",
              "      <th>every</th>\n",
              "      <th>review</th>\n",
              "      <th>manager</th>\n",
              "      <th>money</th>\n",
              "      <th>text</th>\n",
              "      <th>people</th>\n",
              "      <th>make</th>\n",
              "      <th>way</th>\n",
              "      <th>i'm</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0.020601</td>\n",
              "      <td>0.013028</td>\n",
              "      <td>0.008304</td>\n",
              "      <td>0.007223</td>\n",
              "      <td>0.005951</td>\n",
              "      <td>0.005630</td>\n",
              "      <td>0.005586</td>\n",
              "      <td>0.004758</td>\n",
              "      <td>0.004129</td>\n",
              "      <td>0.004087</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0.018842</td>\n",
              "      <td>0.010049</td>\n",
              "      <td>0.005583</td>\n",
              "      <td>0.003766</td>\n",
              "      <td>0.005180</td>\n",
              "      <td>0.004902</td>\n",
              "      <td>0.005391</td>\n",
              "      <td>0.002592</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.002979</td>\n",
              "      <td>...</td>\n",
              "      <td>0.002845</td>\n",
              "      <td>0.002423</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0.024005</td>\n",
              "      <td>0.006175</td>\n",
              "      <td>0.002723</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.005547</td>\n",
              "      <td>0.004479</td>\n",
              "      <td>0.006077</td>\n",
              "      <td>0.002500</td>\n",
              "      <td>0.005871</td>\n",
              "      <td>0.003732</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00285</td>\n",
              "      <td>0.002812</td>\n",
              "      <td>0.002727</td>\n",
              "      <td>0.002666</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0.011100</td>\n",
              "      <td>0.008348</td>\n",
              "      <td>0.005806</td>\n",
              "      <td>0.005815</td>\n",
              "      <td>0.003126</td>\n",
              "      <td>0.004067</td>\n",
              "      <td>0.003851</td>\n",
              "      <td>0.003185</td>\n",
              "      <td>0.002828</td>\n",
              "      <td>0.003730</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
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              "      <td>0.00000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0.012586</td>\n",
              "      <td>0.008189</td>\n",
              "      <td>0.006199</td>\n",
              "      <td>0.002628</td>\n",
              "      <td>0.006036</td>\n",
              "      <td>0.002920</td>\n",
              "      <td>0.004359</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.004337</td>\n",
              "      <td>0.004027</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.002756</td>\n",
              "      <td>0.00249</td>\n",
              "      <td>0.002472</td>\n",
              "      <td>0.002434</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 41 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-23dfa632-d724-4f28-9713-728a718b0676')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-23dfa632-d724-4f28-9713-728a718b0676 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-23dfa632-d724-4f28-9713-728a718b0676');\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-0339caa1-b77e-4012-b2eb-ea579cd41313\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-0339caa1-b77e-4012-b2eb-ea579cd41313')\"\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-0339caa1-b77e-4012-b2eb-ea579cd41313 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 34
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "g=sns.clustermap(df_lda.corr(), center=0, standard_scale=1, cmap=\"RdBu\", metric='cosine', linewidths=.75, figsize=(15, 15))\n",
        "plt.setp(g.ax_heatmap.yaxis.get_majorticklabels(), rotation=0)\n",
        "plt.show()\n",
        "#plt.setp(ax_heatmap.get_yticklabels(), rotation=0)  # For y axis"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "o3B5K-jDUG1Z",
        "outputId": "a0b34f86-a3b5-4a4c-bffd-6c8889794296"
      },
      "execution_count": 35,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1500x1500 with 4 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Named Entity Recognition"
      ],
      "metadata": {
        "id": "HMIaITY3KwnO"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#libraries\n",
        "import pandas as pd\n",
        "import spacy\n",
        "from spacy import displacy\n",
        "import en_core_web_sm\n",
        "import re\n",
        "from nltk.corpus import stopwords\n",
        "from nltk.tokenize import word_tokenize\n",
        "import nltk\n",
        "import re\n",
        "import string\n",
        "import numpy as np\n",
        "import random\n",
        "import pandas as pd\n",
        "from nltk.corpus import stopwords\n",
        "\n",
        "from tqdm import tqdm\n",
        "import os\n",
        "import nltk\n",
        "import spacy\n",
        "import random\n",
        "from spacy.util import compounding\n",
        "from spacy.util import minibatch\n",
        "\n",
        "import warnings\n",
        "warnings.filterwarnings(\"ignore\")"
      ],
      "metadata": {
        "id": "WMg2AGnpK3UI"
      },
      "execution_count": 37,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Loading spaCy's pre-trained model\n",
        "nlp = en_core_web_sm.load()\n",
        "\n",
        "# Loading the airline reviews dataset\n",
        "df = pd.read_csv('reviews_data.csv')"
      ],
      "metadata": {
        "id": "bFKjACnKLiGT"
      },
      "execution_count": 38,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df.head(5)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "IJHJrUyaLsUa",
        "outputId": "eef3e383-cffe-40a0-e693-73b03997e98f"
      },
      "execution_count": 39,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       name           location                     Date  Rating  \\\n",
              "0     Helen  Wichita Falls, TX  Reviewed Sept. 13, 2023     5.0   \n",
              "1  Courtney         Apopka, FL   Reviewed July 16, 2023     5.0   \n",
              "2  Daynelle  Cranberry Twp, PA    Reviewed July 5, 2023     5.0   \n",
              "3    Taylor        Seattle, WA    Reviewed May 26, 2023     5.0   \n",
              "4   Tenessa        Gresham, OR   Reviewed Jan. 22, 2023     5.0   \n",
              "\n",
              "                                              Review  \\\n",
              "0  Amber and LaDonna at the Starbucks on Southwes...   \n",
              "1  ** at the Starbucks by the fire station on 436...   \n",
              "2  I just wanted to go out of my way to recognize...   \n",
              "3  Me and my friend were at Starbucks and my card...   \n",
              "4  I’m on this kick of drinking 5 cups of warm wa...   \n",
              "\n",
              "                                         Image_Links  \n",
              "0                                      ['No Images']  \n",
              "1                                      ['No Images']  \n",
              "2  ['https://media.consumeraffairs.com/files/cach...  \n",
              "3                                      ['No Images']  \n",
              "4  ['https://media.consumeraffairs.com/files/cach...  "
            ],
            "text/html": [
              "\n",
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              "    <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>name</th>\n",
              "      <th>location</th>\n",
              "      <th>Date</th>\n",
              "      <th>Rating</th>\n",
              "      <th>Review</th>\n",
              "      <th>Image_Links</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Helen</td>\n",
              "      <td>Wichita Falls, TX</td>\n",
              "      <td>Reviewed Sept. 13, 2023</td>\n",
              "      <td>5.0</td>\n",
              "      <td>Amber and LaDonna at the Starbucks on Southwes...</td>\n",
              "      <td>['No Images']</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Courtney</td>\n",
              "      <td>Apopka, FL</td>\n",
              "      <td>Reviewed July 16, 2023</td>\n",
              "      <td>5.0</td>\n",
              "      <td>** at the Starbucks by the fire station on 436...</td>\n",
              "      <td>['No Images']</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Daynelle</td>\n",
              "      <td>Cranberry Twp, PA</td>\n",
              "      <td>Reviewed July 5, 2023</td>\n",
              "      <td>5.0</td>\n",
              "      <td>I just wanted to go out of my way to recognize...</td>\n",
              "      <td>['https://media.consumeraffairs.com/files/cach...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Taylor</td>\n",
              "      <td>Seattle, WA</td>\n",
              "      <td>Reviewed May 26, 2023</td>\n",
              "      <td>5.0</td>\n",
              "      <td>Me and my friend were at Starbucks and my card...</td>\n",
              "      <td>['No Images']</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Tenessa</td>\n",
              "      <td>Gresham, OR</td>\n",
              "      <td>Reviewed Jan. 22, 2023</td>\n",
              "      <td>5.0</td>\n",
              "      <td>I’m on this kick of drinking 5 cups of warm wa...</td>\n",
              "      <td>['https://media.consumeraffairs.com/files/cach...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-4285df3d-8834-49e3-9577-767195861050')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-4285df3d-8834-49e3-9577-767195861050 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-4285df3d-8834-49e3-9577-767195861050');\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-84d77e55-8849-41d0-a82c-0de3bf414525\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-84d77e55-8849-41d0-a82c-0de3bf414525')\"\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-84d77e55-8849-41d0-a82c-0de3bf414525 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 39
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Function to clean and preprocess a single tweet\n",
        "def clean_and_preprocess(coffee):\n",
        "\n",
        "    # Remove URLs\n",
        "    coffee = re.sub(r'http\\S+|www\\S+|https\\S+', '', coffee, flags=re.MULTILINE)\n",
        "\n",
        "    # Remove mentions\n",
        "    coffee = re.sub(r'@\\w+', '', coffee)\n",
        "\n",
        "    # Remove special characters and numbers\n",
        "    coffee = re.sub(r'[^a-zA-Z\\s]', '', coffee)\n",
        "\n",
        "    return coffee\n",
        "\n",
        "# Apply the cleaning function to each tweet in the 'text' column\n",
        "df['cleaned_review'] = df['Review'].apply(clean_and_preprocess)\n",
        "\n",
        "# Display the cleaned dataset\n",
        "print(\"\\nCleaned Dataset:\")\n",
        "print(df[ 'cleaned_review'].head())"
      ],
      "metadata": {
        "id": "j67kQgcuL3m7",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "03417211-bfcf-4a93-ef86-32bbe6e3548c"
      },
      "execution_count": 41,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "Cleaned Dataset:\n",
            "0    Amber and LaDonna at the Starbucks on Southwes...\n",
            "1     at the Starbucks by the fire station on  in A...\n",
            "2    I just wanted to go out of my way to recognize...\n",
            "3    Me and my friend were at Starbucks and my card...\n",
            "4    Im on this kick of drinking  cups of warm wate...\n",
            "Name: cleaned_review, dtype: object\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.head(5)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 293
        },
        "id": "MjJvZ-jkm1CR",
        "outputId": "bbcff7f3-e2f7-493a-e261-8e5852025661"
      },
      "execution_count": 42,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       name           location                     Date  Rating  \\\n",
              "0     Helen  Wichita Falls, TX  Reviewed Sept. 13, 2023     5.0   \n",
              "1  Courtney         Apopka, FL   Reviewed July 16, 2023     5.0   \n",
              "2  Daynelle  Cranberry Twp, PA    Reviewed July 5, 2023     5.0   \n",
              "3    Taylor        Seattle, WA    Reviewed May 26, 2023     5.0   \n",
              "4   Tenessa        Gresham, OR   Reviewed Jan. 22, 2023     5.0   \n",
              "\n",
              "                                              Review  \\\n",
              "0  Amber and LaDonna at the Starbucks on Southwes...   \n",
              "1  ** at the Starbucks by the fire station on 436...   \n",
              "2  I just wanted to go out of my way to recognize...   \n",
              "3  Me and my friend were at Starbucks and my card...   \n",
              "4  I’m on this kick of drinking 5 cups of warm wa...   \n",
              "\n",
              "                                         Image_Links  \\\n",
              "0                                      ['No Images']   \n",
              "1                                      ['No Images']   \n",
              "2  ['https://media.consumeraffairs.com/files/cach...   \n",
              "3                                      ['No Images']   \n",
              "4  ['https://media.consumeraffairs.com/files/cach...   \n",
              "\n",
              "                                      cleaned_review  \n",
              "0  Amber and LaDonna at the Starbucks on Southwes...  \n",
              "1   at the Starbucks by the fire station on  in A...  \n",
              "2  I just wanted to go out of my way to recognize...  \n",
              "3  Me and my friend were at Starbucks and my card...  \n",
              "4  Im on this kick of drinking  cups of warm wate...  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-b8673549-1416-4e5d-b5ed-3e1522317436\" 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>name</th>\n",
              "      <th>location</th>\n",
              "      <th>Date</th>\n",
              "      <th>Rating</th>\n",
              "      <th>Review</th>\n",
              "      <th>Image_Links</th>\n",
              "      <th>cleaned_review</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Helen</td>\n",
              "      <td>Wichita Falls, TX</td>\n",
              "      <td>Reviewed Sept. 13, 2023</td>\n",
              "      <td>5.0</td>\n",
              "      <td>Amber and LaDonna at the Starbucks on Southwes...</td>\n",
              "      <td>['No Images']</td>\n",
              "      <td>Amber and LaDonna at the Starbucks on Southwes...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Courtney</td>\n",
              "      <td>Apopka, FL</td>\n",
              "      <td>Reviewed July 16, 2023</td>\n",
              "      <td>5.0</td>\n",
              "      <td>** at the Starbucks by the fire station on 436...</td>\n",
              "      <td>['No Images']</td>\n",
              "      <td>at the Starbucks by the fire station on  in A...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Daynelle</td>\n",
              "      <td>Cranberry Twp, PA</td>\n",
              "      <td>Reviewed July 5, 2023</td>\n",
              "      <td>5.0</td>\n",
              "      <td>I just wanted to go out of my way to recognize...</td>\n",
              "      <td>['https://media.consumeraffairs.com/files/cach...</td>\n",
              "      <td>I just wanted to go out of my way to recognize...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Taylor</td>\n",
              "      <td>Seattle, WA</td>\n",
              "      <td>Reviewed May 26, 2023</td>\n",
              "      <td>5.0</td>\n",
              "      <td>Me and my friend were at Starbucks and my card...</td>\n",
              "      <td>['No Images']</td>\n",
              "      <td>Me and my friend were at Starbucks and my card...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Tenessa</td>\n",
              "      <td>Gresham, OR</td>\n",
              "      <td>Reviewed Jan. 22, 2023</td>\n",
              "      <td>5.0</td>\n",
              "      <td>I’m on this kick of drinking 5 cups of warm wa...</td>\n",
              "      <td>['https://media.consumeraffairs.com/files/cach...</td>\n",
              "      <td>Im on this kick of drinking  cups of warm wate...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-b8673549-1416-4e5d-b5ed-3e1522317436')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-b8673549-1416-4e5d-b5ed-3e1522317436 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-b8673549-1416-4e5d-b5ed-3e1522317436');\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-8585ab78-096e-4511-bef5-1a5ba885db89\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-8585ab78-096e-4511-bef5-1a5ba885db89')\"\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-8585ab78-096e-4511-bef5-1a5ba885db89 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 42
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Processing each review and extracting named entities\n",
        "for i in range(0, 20):\n",
        "    review = df['cleaned_review'][i]\n",
        "\n",
        "# Process the review using spaCy NLP pipeline\n",
        "    doc = nlp(review)\n",
        "\n",
        "# Manually correct 'Store' to 'FAC'\n",
        "    for token in doc:\n",
        "        if token.text == 'Store':\n",
        "            token.ent_type_ = 'FAC'\n",
        "\n",
        "# Manually correct 'SOO' to 'RB'\n",
        "    for token in doc:\n",
        "        if token.text == 'SOO':\n",
        "            token.ent_type_ = 'RB'\n",
        "\n",
        "# Manually correct 'Dillon' to 'PERSON'\n",
        "    for token in doc:\n",
        "        if token.text == 'Dillon':\n",
        "            token.ent_type_ = 'PERSON'\n",
        "\n",
        "# Print entities and their labels\n",
        "    print(f\"Review #{i + 1}: {review}\")\n",
        "    for ent in doc.ents:\n",
        "        print(f\"Entity: {ent.text} - Label: {ent.label_}\")\n",
        "\n",
        "    print('\\n')\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jLSPT3azm7_b",
        "outputId": "788945a8-13d7-4d43-938a-212281120ff7"
      },
      "execution_count": 46,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Review #1: Amber and LaDonna at the Starbucks on Southwest Parkway are always so warm and welcoming There is always a smile in their voice when they greet you at the drivethru And their customer service is always spoton they always get my order right and with a smile I would actually give them more than  stars if they were available\n",
            "Entity: LaDonna - Label: PERSON\n",
            "Entity: Starbucks - Label: ORG\n",
            "\n",
            "\n",
            "Review #2:  at the Starbucks by the fire station on  in Altamonte Springs FL made my day and finally helped me figure out the way to make my drink so Id love it She took time out to talk to me for  minutes to make my experience better than what Im used to It was much appreciated Ive had bad experiences one after another at the Starbucks thats closest to me in my work building with my drinks not being great along with not great customer service from specific baristas Niko was refreshing to speak to and pleasant The drink was perfect Store \n",
            "Entity: Starbucks - Label: ORG\n",
            "Entity: Altamonte Springs FL - Label: GPE\n",
            "Entity: minutes - Label: TIME\n",
            "Entity: Starbucks - Label: ORG\n",
            "Entity: Niko - Label: PERSON\n",
            "Entity: Store - Label: FAC\n",
            "\n",
            "\n",
            "Review #3: I just wanted to go out of my way to recognize a Starbucks employee Billy at the Franklin Park location I was running late to work  placed an order at the wrong location and not only did he make my order with a smile he made it within  seconds Thank you SOO much I was having a bad morning and people like you just make this world a better place\n",
            "Entity: Starbucks - Label: ORG\n",
            "Entity: Billy - Label: PERSON\n",
            "Entity: Franklin Park - Label: LOC\n",
            "Entity: SOO - Label: RB\n",
            "Entity: a bad morning - Label: TIME\n",
            "\n",
            "\n",
            "Review #4: Me and my friend were at Starbucks and my card didnt work Thankful the worker there paid for our drinks And was very nice about it it didnt seem to bother him that he paid for our drinks This made my day but made me look like a fool because my card didnt work All thanks to Dillon At Shoreline WA in Safeway Thank you so much Dillon for the help support and kindness I rate this  if I could but other than that \n",
            "Entity: Starbucks - Label: ORG\n",
            "Entity: Dillon At - Label: PERSON\n",
            "Entity: Safeway Thank - Label: FAC\n",
            "Entity: Dillon - Label: PERSON\n",
            "\n",
            "\n",
            "Review #5: Im on this kick of drinking  cups of warm water I work for Instacart right now and every location of Starbucks I was given free hot water because I asked for it without being charged I really appreciate Starbucks for giving me the opportunity to do such thing Thats why I give them five stars They fully have my support Theyre super nice and professional and the coffee is great Go to Starbucks\n",
            "Entity: Instacart - Label: ORG\n",
            "Entity: Starbucks - Label: ORG\n",
            "Entity: Starbucks - Label: ORG\n",
            "Entity: five - Label: CARDINAL\n",
            "Entity: Starbucks - Label: ORG\n",
            "\n",
            "\n",
            "Review #6: We had to correct them on our order  times They never got it right then the manager came over to us and said we made her employee uncomfortable because we were trying to correct our order The manager tried was racist against my stepmom Chinese taking over her but when I  would talk she would stop talking and listen to me\n",
            "Entity: Chinese - Label: NORP\n",
            "\n",
            "\n",
            "Review #7: I have tried Starbucks several different times in different locations just in case it was just the one store But its not If you like coffee that taste like dirt scooped off the ground at a garbage dump then this is the place for you\n",
            "Entity: Starbucks - Label: ORG\n",
            "Entity: one - Label: CARDINAL\n",
            "\n",
            "\n",
            "Review #8: Starbucks near me just launched new fall foods and beverages yesterday By noon yesterday they were out of all new items The fall launch is huge and many people look forward to it all year Maybe if you dont have enough product to last even a couple of days push back the launch until you do I was so happy to get the email that it had come out that I left work on my break to brighten my day and so very disappointed to get there at pm and find out that it was all gone Please Starbucks do better\n",
            "Entity: yesterday - Label: DATE\n",
            "Entity: noon - Label: TIME\n",
            "Entity: yesterday - Label: DATE\n",
            "Entity: a couple of days - Label: DATE\n",
            "Entity: Please Starbucks - Label: PRODUCT\n",
            "\n",
            "\n",
            "Review #9: I ordered online for the Reisterstown Rd St Thomas SC  and they gave me the wrong drink size so ordered a venti they gave me a grande Just a bit upset that I paid over  bucks for a drink and got the wrong thing\n",
            "\n",
            "\n",
            "Review #10: Staff at the Smythe St Superstore location in Fredericton NB often seen tired but today a woman named Senoa Senora was morose glum uncommunicative even after I tried to engage her to sympathize as there was obviously a bad mood happening scruffy looking almost rude And the Americano I ordered tastes watery I go to Starbucks for a treat after a long day It a difficult experience to ease stress and have a pleasant experience Im going to sell a different location after todays grumpy girl\n",
            "Entity: the Smythe St Superstore - Label: FAC\n",
            "Entity: Fredericton NB - Label: ORG\n",
            "Entity: today - Label: DATE\n",
            "Entity: Senoa Senora - Label: PERSON\n",
            "Entity: Starbucks - Label: ORG\n",
            "Entity: a long day - Label: DATE\n",
            "\n",
            "\n",
            "Review #11: I filed a BBB complaint last month because Starbucks canceled my Starbucks Reward cards I couldnt remember the balances so I guessed about  Starbucks played nothing but games and tried everything they could to avoid responding to the complaint I received a couple of phone call messages asking me to contact them directly and discuss the matter The number provided was the customer service number and when I spoke with one representative Linda hung up the phone on me I did not use my card since  which is my prerogative Because of this and other reasons Starbucks decided to close my Starbucks account I reopened one about a few weeks ago and added a new card that I have not used yet\n",
            "Entity: BBB - Label: ORG\n",
            "Entity: last month - Label: DATE\n",
            "Entity: Starbucks - Label: ORG\n",
            "Entity: Starbucks Reward - Label: PRODUCT\n",
            "Entity: Starbucks - Label: ORG\n",
            "Entity: one - Label: CARDINAL\n",
            "Entity: Linda hung - Label: PERSON\n",
            "Entity: Starbucks - Label: ORG\n",
            "Entity: Starbucks - Label: PRODUCT\n",
            "Entity: one - Label: CARDINAL\n",
            "Entity: a few weeks ago - Label: DATE\n",
            "\n",
            "\n",
            "Review #12: Every time I try to buy a Strawberry Refresher Starbucks never has strawberries to put into the drink How is the drink called Strawberry Refresher and you guys never have any damn strawberries It seems every time we go on the Starbucks to order a specialty drink you guys are constantly out of it Its like calling a pizza place and theyre telling us theyre out of cheese I dont give you a partial payment so I dont expect a partial drink\n",
            "Entity: Strawberry Refresher Starbucks - Label: PERSON\n",
            "Entity: Strawberry Refresher - Label: PERSON\n",
            "Entity: Starbucks - Label: ORG\n",
            "\n",
            "\n",
            "Review #13: Insulted by customer service representative as I called to complain instead of acknowledge they have issues and they are providing low quality She called me suspicious even though I spend at least average  dollars a day Was so upset and I decided to close the account after being with them for more than  yrs Company that doesnt appreciate feedback soon to fall especially that it lost its quality\n",
            "\n",
            "\n",
            "Review #14: I would give Starbucks zero stars if I could I received an email that I would be receiving a birthday reward on the day of my birthday and it would be good on the day of my birthday only The email also stated that the reward would be for any drink or food item I went to an Starbucks near my home The cashier told me my coupon had expired I told her I dont have a coupon Its a birthday reward I ordered a sandwich The cashier said I could only purchase a drink I showed her the email She said lets try it and swiped my card She said it didnt take so she asked if I wanted a drink I told her to just give me a venti hot coffee She swiped my card again and said it didnt work Then she asked Are you sure its your birthday I showed her the email that said in big letters  I told her this is July  and this is my birthday \n",
            "Entity: Starbucks - Label: ORG\n",
            "Entity: the day - Label: DATE\n",
            "Entity: the day - Label: DATE\n",
            "Entity: Starbucks - Label: ORG\n",
            "Entity: July - Label: DATE\n",
            "\n",
            "\n",
            "Review #15: On June   I purchased coffee and a breakfast sandwich for  at the Starbucks located at the Target store in Mays Landing NJ I was not given purchase credit and star points for the purchase even though the cashier there scanned my Starbucks app I reported this to customer service the next day and was told to email them a copy of my credit card receipt to their customer service address which I did I have still not been given stars to my account or credit for this purchase I have attempted to contact them on multiple occasions and they have not responded\n",
            "Entity: June - Label: DATE\n",
            "Entity: Starbucks - Label: ORG\n",
            "Entity: Target - Label: ORG\n",
            "Entity: Mays Landing NJ - Label: ORG\n",
            "Entity: Starbucks - Label: PRODUCT\n",
            "Entity: the next day - Label: DATE\n",
            "\n",
            "\n",
            "Review #16: My mother sent me a  gift card purchased from Walgreens in June She came to visit me this past weekend and brought the Gift card receipts I contacted Walgreens to replace the cards I was told to contact the Merchant Starbucks I called Starbucks and spoke with a representative today explained my problem He asked for the card number When I provided it he transferred me to a different department that handles these issues I got another representative I told this representative why I was transferred over She got silent and ended the call It is like no one wants to handle issues or do their job \n",
            "Entity: Walgreens - Label: PERSON\n",
            "Entity: June - Label: DATE\n",
            "Entity: this past weekend - Label: DATE\n",
            "Entity: Gift - Label: PERSON\n",
            "Entity: Walgreens - Label: PERSON\n",
            "Entity: the Merchant Starbucks - Label: WORK_OF_ART\n",
            "Entity: Starbucks - Label: PRODUCT\n",
            "Entity: today - Label: DATE\n",
            "\n",
            "\n",
            "Review #17: Was handed a coffee in a drive through The lid was not on right and the top edge of the cup was bent When I accepted the coffee and was going to place it in my cup holder the cup bent the lid fell off and the coffee spilled all over myself and my newly detailed interior Not the way to start a day especially on the way to an appointment Now  for coffee and detailing\n",
            "\n",
            "\n",
            "Review #18: Im at th and L in DC There are a dozen people here and only one employee to make drinks Unacceptable I have commitments to get to and I dont have time to wait Its already been  minutes I wont come to this location again\n",
            "Entity: L in DC - Label: GPE\n",
            "Entity: a dozen - Label: CARDINAL\n",
            "Entity: only one - Label: CARDINAL\n",
            "Entity: Unacceptable - Label: ORG\n",
            "\n",
            "\n",
            "Review #19: I have been purchasing Starbucks a lot using my cash app card I reached out to Starbucks customer service so they could add my purchases or receipts to my account for points I emailed them and received an automated email back saying someone will reach out to me No one has as of yet I sent out another email and still didnt get any assistance Starbucks is ignoring me about receiving help\n",
            "Entity: Starbucks - Label: ORG\n",
            "Entity: Starbucks - Label: ORG\n",
            "Entity: Starbucks - Label: ORG\n",
            "\n",
            "\n",
            "Review #20: Starbucks Como Lake Bad attitude of the cashier demonstrative arrogance and didnt greet me misspelled my name then laughed at me with the staff Orders are often confused it is better to take a check in order to get the desired drink later The order took a long time one day we had to wait  minutes Bad place\n",
            "\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from collections import Counter\n",
        "# Initializing a Counter to keep track of entity frequencies\n",
        "entity_counter = Counter()\n",
        "\n",
        "# Processing each review and extract named entities\n",
        "for i in range(0,850):\n",
        "    review = df['Review'][i]\n",
        "    doc = nlp(review)\n",
        "\n",
        "    # Counting the frequency of each named entity\n",
        "    for ent in doc.ents:\n",
        "        entity_counter[ent.text] += 1\n",
        "\n",
        "# Printing the most common named entities and their frequencies\n",
        "print(\"Top 10 Most Common Named Entities:\")\n",
        "for entity, freq in entity_counter.most_common(10):\n",
        "    print(f\"Entity: {entity} - Frequency: {freq}\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8PR4w3fasBKD",
        "outputId": "a7d614e5-e4bb-48cf-eca0-36115cfacaab"
      },
      "execution_count": 54,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Top 10 Most Common Named Entities:\n",
            "Entity: Starbucks - Frequency: 895\n",
            "Entity: one - Frequency: 86\n",
            "Entity: two - Frequency: 71\n",
            "Entity: first - Frequency: 63\n",
            "Entity: 2 - Frequency: 49\n",
            "Entity: today - Frequency: 45\n",
            "Entity: 3 - Frequency: 38\n",
            "Entity: Today - Frequency: 23\n",
            "Entity: One - Frequency: 21\n",
            "Entity: years - Frequency: 21\n"
          ]
        }
      ]
    }
  ]
}