sentiment_analysis_openai.ipynb

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 "cells": [
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "07ae39d8",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import json\n",
    "import re\n",
    "import seaborn as sns\n",
    "from plotly.subplots import make_subplots\n",
    "import plotly.express as px\n",
    "import time\n",
    "import openai\n",
    "import os\n",
    "from dotenv import load_dotenv\n",
    "import tiktoken"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "f933b095",
   "metadata": {},
   "outputs": [],
   "source": [
    "data = pd.read_csv(\"googlemaps_review.csv\")\n",
    "info = pd.read_csv(\"googlemaps_info.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "82920aa3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['id_33', 'id_48', 'id_93']"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "id_list = data[\"location_id\"].unique().tolist()\n",
    "id_list"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c94a24d2",
   "metadata": {},
   "source": [
    "### Extract the data from the reviews in json"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "9a69a8bc",
   "metadata": {},
   "outputs": [],
   "source": [
    "rating_list = []\n",
    "review_date_list = []\n",
    "rating_cat_list = []\n",
    "review_text_list = []\n",
    "for id_num in id_list:\n",
    "    \n",
    "    current_df = data[data[\"location_id\"]==id_num]\n",
    "    current_review = current_df[\"moreReview\"].tolist()\n",
    "    \n",
    "    for i in range(len(current_review)):\n",
    "        # review in json object\n",
    "        json_obj = json.loads(current_review[i])\n",
    "        # extract ratings\n",
    "        ratings = int(json_obj[\"rating\"][0])\n",
    "        rating_list.append(ratings)\n",
    "        # categorize ratings\n",
    "        if ratings >3:\n",
    "            rating_cat_list.append(\"> 3 stars\")\n",
    "        else:\n",
    "            rating_cat_list.append(\"<= 3 stars\")\n",
    "        # extract review date\n",
    "        date = json_obj[\"review_date\"]\n",
    "        split_date = date.split(\" \")[0:-1]\n",
    "        if re.match(\"(year)s?\",split_date[1]):\n",
    "            review_date_list.append(\"> a year\")\n",
    "        else:\n",
    "            review_date_list.append(\"<= a year\")\n",
    "        # extract review text content\n",
    "        review_text_list.append(json_obj[\"review\"])\n",
    "\n",
    "data[\"review_rating\"] = rating_list\n",
    "data[\"review_rating_category\"] = rating_cat_list\n",
    "data[\"review_date\"] = review_date_list\n",
    "data[\"review_content\"] = review_text_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "b06813ef",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Add the location name\n",
    "data[\"location_name\"] = data[\"location_id\"].apply(lambda x: info[info[\"location_id\"]==x][\"location\"].values[0])\n",
    "data= data.reindex(columns = [\"location_id\", \"location_name\",\n",
    "                              \"moreReview\", \"review_rating\",\"review_rating_category\", \"review_date\", \"review_content\"])\n",
    "data[\"location_name\"] = data[\"location_name\"].apply(lambda x : \" \".join(x.split(\" \")[1::]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "b8d85b41",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Clean the location name \n",
    "data[\"location_name\"] = data[\"location_name\"].apply(lambda x: x[1:5] if not x.isascii() else x)\n",
    "data[\"location_name\"] = data[\"location_name\"].apply(lambda x: x.replace(\"*\", \"\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "20d221ab",
   "metadata": {},
   "source": [
    "### Bar plot of the ratings based on group category"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "00e95a8d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>location_id</th>\n",
       "      <th>location_name</th>\n",
       "      <th>review_rating_category</th>\n",
       "      <th>count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>id_33</td>\n",
       "      <td>香港大學</td>\n",
       "      <td>&lt;= 3 stars</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>id_33</td>\n",
       "      <td>香港大學</td>\n",
       "      <td>&gt; 3 stars</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>id_48</td>\n",
       "      <td>The Henry</td>\n",
       "      <td>&lt;= 3 stars</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>id_48</td>\n",
       "      <td>The Henry</td>\n",
       "      <td>&gt; 3 stars</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>id_93</td>\n",
       "      <td>Imperial Kennedy</td>\n",
       "      <td>&lt;= 3 stars</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>id_93</td>\n",
       "      <td>Imperial Kennedy</td>\n",
       "      <td>&gt; 3 stars</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  location_id     location_name review_rating_category  count\n",
       "0       id_33              香港大學             <= 3 stars      7\n",
       "1       id_33              香港大學              > 3 stars     13\n",
       "2       id_48         The Henry             <= 3 stars      9\n",
       "3       id_48         The Henry              > 3 stars     11\n",
       "4       id_93  Imperial Kennedy             <= 3 stars      8\n",
       "5       id_93  Imperial Kennedy              > 3 stars     12"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stats_rate_df = pd.DataFrame(data.groupby(['location_id','location_name', 'review_rating_category']).size().reset_index(name=\"count\"))\n",
    "stats_rate_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "d021550d",
   "metadata": {},
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Ratings\"},\"categoryorder\":\"array\",\"categoryarray\":[\"<= 3 stars\",\"> 3 stars\"]},\"yaxis\":{\"anchor\":\"x\",\"domain\":[0.0,1.0],\"title\":{\"text\":\"Count\"}},\"xaxis2\":{\"anchor\":\"y2\",\"domain\":[0.33666666666666667,0.6633333333333333],\"matches\":\"x\",\"title\":{\"text\":\"Review Ratings\"},\"categoryorder\":\"array\",\"categoryarray\":[\"<= 3 stars\",\"> 3 stars\"]},\"yaxis2\":{\"anchor\":\"x2\",\"domain\":[0.0,1.0],\"matches\":\"y\",\"showticklabels\":false},\"xaxis3\":{\"anchor\":\"y3\",\"domain\":[0.6733333333333333,1.0],\"matches\":\"x\",\"title\":{\"text\":\"Review Ratings\"},\"categoryorder\":\"array\",\"categoryarray\":[\"<= 3 stars\",\"> 3 stars\"]},\"yaxis3\":{\"anchor\":\"x3\",\"domain\":[0.0,1.0],\"matches\":\"y\",\"showticklabels\":false},\"annotations\":[{\"font\":{},\"showarrow\":false,\"text\":\"Location=\\u9999\\u6e2f\\u5927\\u5b78\",\"x\":0.16333333333333333,\"xanchor\":\"center\",\"xref\":\"paper\",\"y\":1.0,\"yanchor\":\"bottom\",\"yref\":\"paper\"},{\"font\":{},\"showarrow\":false,\"text\":\"Location=The Henry\",\"x\":0.5,\"xanchor\":\"center\",\"xref\":\"paper\",\"y\":1.0,\"yanchor\":\"bottom\",\"yref\":\"paper\"},{\"font\":{},\"showarrow\":false,\"text\":\"Location=Imperial Kennedy\",\"x\":0.8366666666666667,\"xanchor\":\"center\",\"xref\":\"paper\",\"y\":1.0,\"yanchor\":\"bottom\",\"yref\":\"paper\"}],\"legend\":{\"title\":{\"text\":\"Review Ratings:\"},\"tracegroupgap\":0,\"orientation\":\"h\",\"yanchor\":\"top\",\"y\":1.25,\"xanchor\":\"center\",\"x\":0.5,\"bordercolor\":\"#B0C4DE\",\"borderwidth\":1},\"title\":{\"text\":\"Bar Chart of the Ratings (Overview)\",\"y\":0.95,\"x\":0.5,\"xanchor\":\"center\",\"yanchor\":\"top\"},\"barmode\":\"relative\",\"showlegend\":true,\"width\":600,\"height\":400},                        {\"responsive\": true}                    ).then(function(){\n",
       "                            \n",
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       "        if (!display || display === 'none') {{\n",
       "            console.log([gd, 'removed!']);\n",
       "            Plotly.purge(gd);\n",
       "            observer.disconnect();\n",
       "        }}\n",
       "}});\n",
       "\n",
       "// Listen for the removal of the full notebook cells\n",
       "var notebookContainer = gd.closest('#notebook-container');\n",
       "if (notebookContainer) {{\n",
       "    x.observe(notebookContainer, {childList: true});\n",
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       "var outputEl = gd.closest('.output');\n",
       "if (outputEl) {{\n",
       "    x.observe(outputEl, {childList: true});\n",
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "color_sequence = px.colors.sequential.RdBu\n",
    "\n",
    "n_colors = 2\n",
    "color_range = [i*(len(color_sequence)-1)//(n_colors-1) for i in range(n_colors)]\n",
    "color_list = [color_sequence[idx] for idx in color_range]\n",
    "\n",
    "fig = px.bar(stats_rate_df, \n",
    "             x=\"review_rating_category\", y=\"count\", \n",
    "             color=\"review_rating_category\", color_discrete_sequence =color_list,\n",
    "             text = \"count\",\n",
    "             facet_col=\"location_name\",\n",
    "             facet_col_spacing =0.01,\n",
    "             labels={\"count\":\"Count\", \n",
    "                     \"review_rating_category\":\"Review Ratings\",\n",
    "                    \"location_name\": \"Location\"},\n",
    "             title = \"Bar Chart of the Ratings (Overview)\"\n",
    "            )\n",
    "\n",
    "fig.update_traces(marker_line_color='black', marker_line_width=0.4)\n",
    "fig.update_layout(showlegend=True,\n",
    "                  legend=dict(title=\"Review Ratings:\", orientation='h', yanchor='top',y=1.25,xanchor='center',x=0.5, bordercolor=\"#B0C4DE\", borderwidth=1),\n",
    "                  title=dict(y=0.95, x=0.5, xanchor='center', yanchor='top'), \n",
    "                  width=600, height=400\n",
    "                 )\n",
    "\n",
    "fig.write_image(\"1bar_overview.jpeg\")\n",
    "fig.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "126e6551",
   "metadata": {},
   "source": [
    "### Bar plot of the ratings based on ratings values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "3896918e",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>location_id</th>\n",
       "      <th>location_name</th>\n",
       "      <th>review_rating</th>\n",
       "      <th>review_date</th>\n",
       "      <th>count</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>id_33</td>\n",
       "      <td>香港大學</td>\n",
       "      <td>1</td>\n",
       "      <td>&lt;= a year</td>\n",
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       "      <td>id_33</td>\n",
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       "      <td>id_33</td>\n",
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       "      <td>id_33</td>\n",
       "      <td>香港大學</td>\n",
       "      <td>4</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>id_33</td>\n",
       "      <td>香港大學</td>\n",
       "      <td>4</td>\n",
       "      <td>&gt; a year</td>\n",
       "      <td>3</td>\n",
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       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>id_33</td>\n",
       "      <td>香港大學</td>\n",
       "      <td>5</td>\n",
       "      <td>&gt; a year</td>\n",
       "      <td>9</td>\n",
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       "      <td>1</td>\n",
       "      <td>&lt;= a year</td>\n",
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       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>id_48</td>\n",
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       "      <td>&gt; a year</td>\n",
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       "    <tr>\n",
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       "      <td>id_48</td>\n",
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       "      <td>4</td>\n",
       "      <td>&gt; a year</td>\n",
       "      <td>7</td>\n",
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       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>id_48</td>\n",
       "      <td>The Henry</td>\n",
       "      <td>5</td>\n",
       "      <td>&lt;= a year</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>id_48</td>\n",
       "      <td>The Henry</td>\n",
       "      <td>5</td>\n",
       "      <td>&gt; a year</td>\n",
       "      <td>3</td>\n",
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       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>id_93</td>\n",
       "      <td>Imperial Kennedy</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>id_93</td>\n",
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       "      <td>2</td>\n",
       "      <td>&gt; a year</td>\n",
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       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>id_93</td>\n",
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       "      <td>3</td>\n",
       "      <td>&gt; a year</td>\n",
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       "    <tr>\n",
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       "      <td>id_93</td>\n",
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       "    <tr>\n",
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       "      <td>id_93</td>\n",
       "      <td>Imperial Kennedy</td>\n",
       "      <td>4</td>\n",
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       "      <td>id_93</td>\n",
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       "    <tr>\n",
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       "      <td>6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      ],
      "text/plain": [
       "   location_id     location_name review_rating review_date  count\n",
       "0        id_33              香港大學             1   <= a year      2\n",
       "1        id_33              香港大學             1    > a year      3\n",
       "2        id_33              香港大學             3    > a year      2\n",
       "3        id_33              香港大學             4   <= a year      1\n",
       "4        id_33              香港大學             4    > a year      3\n",
       "5        id_33              香港大學             5    > a year      9\n",
       "6        id_48         The Henry             1   <= a year      2\n",
       "7        id_48         The Henry             2    > a year      3\n",
       "8        id_48         The Henry             3    > a year      4\n",
       "9        id_48         The Henry             4    > a year      7\n",
       "10       id_48         The Henry             5   <= a year      1\n",
       "11       id_48         The Henry             5    > a year      3\n",
       "12       id_93  Imperial Kennedy             1    > a year      1\n",
       "13       id_93  Imperial Kennedy             2    > a year      4\n",
       "14       id_93  Imperial Kennedy             3    > a year      3\n",
       "15       id_93  Imperial Kennedy             4   <= a year      1\n",
       "16       id_93  Imperial Kennedy             4    > a year      3\n",
       "17       id_93  Imperial Kennedy             5   <= a year      2\n",
       "18       id_93  Imperial Kennedy             5    > a year      6"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
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  {
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mbers\":\"strict\",\"colorway\":[\"#636efa\",\"#EF553B\",\"#00cc96\",\"#ab63fa\",\"#FFA15A\",\"#19d3f3\",\"#FF6692\",\"#B6E880\",\"#FF97FF\",\"#FECB52\"],\"font\":{\"color\":\"#2a3f5f\"},\"hovermode\":\"closest\",\"hoverlabel\":{\"align\":\"left\"},\"paper_bgcolor\":\"white\",\"plot_bgcolor\":\"#E5ECF6\",\"polar\":{\"bgcolor\":\"#E5ECF6\",\"angularaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"radialaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"ternary\":{\"bgcolor\":\"#E5ECF6\",\"aaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"baxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"caxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"coloraxis\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"colorscale\":{\"sequential\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"sequentialminus\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"diverging\":[[0,\"#8e0152\"],[0.1,\"#c51b7d\"],[0.2,\"#de77ae\"],[0.3,\"#f1b6da\"],[0.4,\"#fde0ef\"],[0.5,\"#f7f7f7\"],[0.6,\"#e6f5d0\"],[0.7,\"#b8e186\"],[0.8,\"#7fbc41\"],[0.9,\"#4d9221\"],[1,\"#276419\"]]},\"xaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"automargin\":true,\"zerolinewidth\":2},\"yaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"automargin\":true,\"zerolinewidth\":2},\"scene\":{\"xaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\",\"gridwidth\":2},\"yaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\",\"gridwidth\":2},\"zaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\",\"gridwidth\":2}},\"shapedefaults\":{\"line\":{\"color\":\"#2a3f5f\"}},\"annotationdefaults\":{\"arrowcolor\":\"#2a3f5f\",\"arrowhead\":0,\"arrowwidth\":1},\"geo\":{\"bgcolor\":\"white\",\"landcolor\":\"#E5ECF6\",\"subunitcolor\":\"white\",\"showland\":true,\"showlakes\":true,\"lakecolor\":\"white\"},\"title\":{\"x\":0.05},\"mapbox\":{\"style\":\"light\"}}},\"xaxis\":{\"anchor\":\"y\",\"domain\":[0.0,0.32666666666666666],\"title\":{\"text\":\"Review Ratings\"},\"categoryorder\":\"array\",\"categoryarray\":[\"1\",\"2\",\"3\",\"4\",\"5\"]},\"yaxis\":{\"anchor\":\"x\",\"domain\":[0.0,1.0],\"title\":{\"text\":\"Count\"}},\"xaxis2\":{\"anchor\":\"y2\",\"domain\":[0.33666666666666667,0.6633333333333333],\"matches\":\"x\",\"title\":{\"text\":\"Review Ratings\"},\"categoryorder\":\"array\",\"categoryarray\":[\"1\",\"3\",\"4\",\"5\",\"2\"]},\"yaxis2\":{\"anchor\":\"x2\",\"domain\":[0.0,1.0],\"matches\":\"y\",\"showticklabels\":false},\"xaxis3\":{\"anchor\":\"y3\",\"domain\":[0.6733333333333333,1.0],\"matches\":\"x\",\"title\":{\"text\":\"Review Ratings\"},\"categoryorder\":\"array\",\"categoryarray\":[\"1\",\"3\",\"4\",\"5\",\"2\"]},\"yaxis3\":{\"anchor\":\"x3\",\"domain\":[0.0,1.0],\"matches\":\"y\",\"showticklabels\":false},\"annotations\":[{\"font\":{},\"showarrow\":false,\"text\":\"Location=\\u9999\\u6e2f\\u5927\\u5b78\",\"x\":0.16333333333333333,\"xanchor\":\"center\",\"xref\":\"paper\",\"y\":1.0,\"yanchor\":\"bottom\",\"yref\":\"paper\"},{\"font\":{},\"showarrow\":false,\"text\":\"Location=The Henry\",\"x\":0.5,\"xanchor\":\"center\",\"xref\":\"paper\",\"y\":1.0,\"yanchor\":\"bottom\",\"yref\":\"paper\"},{\"font\":{},\"showarrow\":false,\"text\":\"Location=Imperial Kennedy\",\"x\":0.8366666666666667,\"xanchor\":\"center\",\"xref\":\"paper\",\"y\":1.0,\"yanchor\":\"bottom\",\"yref\":\"paper\"}],\"legend\":{\"title\":{\"text\":\"Review Ratings:\"},\"tracegroupgap\":0,\"orientation\":\"h\",\"yanchor\":\"top\",\"y\":1.25,\"xanchor\":\"center\",\"x\":0.5,\"bordercolor\":\"#B0C4DE\",\"borderwidth\":1},\"title\":{\"text\":\"Bar Chart of the Ratings (Detail)\",\"y\":0.95,\"x\":0.5,\"xanchor\":\"center\",\"yanchor\":\"top\"},\"barmode\":\"relative\",\"showlegend\":true,\"width\":800,\"height\":400},                        {\"responsive\": true}                    ).then(function(){\n",
       "                            \n",
       "var gd = document.getElementById('ce278700-ab05-43a0-a14a-f6e9403ee76c');\n",
       "var x = new MutationObserver(function (mutations, observer) {{\n",
       "        var display = window.getComputedStyle(gd).display;\n",
       "        if (!display || display === 'none') {{\n",
       "            console.log([gd, 'removed!']);\n",
       "            Plotly.purge(gd);\n",
       "            observer.disconnect();\n",
       "        }}\n",
       "}});\n",
       "\n",
       "// Listen for the removal of the full notebook cells\n",
       "var notebookContainer = gd.closest('#notebook-container');\n",
       "if (notebookContainer) {{\n",
       "    x.observe(notebookContainer, {childList: true});\n",
       "}}\n",
       "\n",
       "// Listen for the clearing of the current output cell\n",
       "var outputEl = gd.closest('.output');\n",
       "if (outputEl) {{\n",
       "    x.observe(outputEl, {childList: true});\n",
       "}}\n",
       "\n",
       "                        })                };                });            </script>        </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "color_sequence = px.colors.sequential.RdBu\n",
    "\n",
    "n_colors = 5\n",
    "color_range = [i*(len(color_sequence)-1)//(n_colors-1) for i in range(n_colors)]\n",
    "color_list = [color_sequence[idx] for idx in color_range]\n",
    "custom_order= [\"1\",\"2\",\"3\",\"4\",\"5\"]\n",
    "color_map = {key:val for (key, val) in zip(custom_order,color_list)}\n",
    "\n",
    "\n",
    "fig = px.bar(stats_df, \n",
    "             x=\"review_rating\", y=\"count\", \n",
    "             color=\"review_rating\", \n",
    "             color_discrete_map = color_map,\n",
    "             text = \"review_date\",\n",
    "             facet_col=\"location_name\",\n",
    "             facet_col_spacing =0.01,\n",
    "             labels={\"count\":\"Count\", \n",
    "                     \"review_rating\":\"Review Ratings\",\n",
    "                    \"location_name\": \"Location\"},\n",
    "             title = \"Bar Chart of the Ratings (Detail)\"\n",
    "            )\n",
    "\n",
    "fig.update_traces(texttemplate='%{text}', \n",
    "                  textposition='inside', \n",
    "                  textfont=dict(size=10), \n",
    "                  textangle=45,\n",
    "                  marker_line_color='black', marker_line_width=0.4)\n",
    "fig.update_layout(showlegend=True,\n",
    "                  xaxis={'categoryorder': 'array', 'categoryarray': custom_order},\n",
    "                  legend=dict(title=\"Review Ratings:\", orientation='h', yanchor='top',y=1.25,xanchor='center',x=0.5, bordercolor=\"#B0C4DE\", borderwidth=1),\n",
    "                  title=dict(y=0.95, x=0.5, xanchor='center', yanchor='top'), \n",
    "                  width=800, height=400\n",
    "                 )\n",
    "fig.write_image(\"2bar_detail.jpeg\")\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a59c86a0",
   "metadata": {},
   "source": [
    "## chatgpt sentiment analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "408ae9e6",
   "metadata": {},
   "outputs": [],
   "source": [
    "load_dotenv(\"config.env\")\n",
    "openai.api_key  = os.getenv('OPENAI_API_KEY')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "f307dcf8",
   "metadata": {},
   "outputs": [],
   "source": [
    "def prompt_text(text):\n",
    "    prompt= f\"\"\" Review is provided and delimited by triple backticks.\\\n",
    "\n",
    "    Determine the following information:\n",
    "    1. What is the overall sentiment of the review?\\\n",
    "    Give your answer as either\\\n",
    "    'Positive', 'Neutral' or 'Negative'.\\\n",
    "\n",
    "    2. Determine the emotions that is portrayed in the review by the reviewer.\\\n",
    "    Give 3 emotions that is expressed by the reviewer. \\\n",
    "    Ensure each word is an adjective and do not repeat the word.\\\n",
    "    \n",
    "    3. Determine if 'customer service' \\\n",
    "    was mentioned in the review.\\\n",
    "    Provide the answer in either 'Positive', 'Negative' or 'NA' only.\\\n",
    "    \n",
    "    Format the output in dictionary format, and use\\\n",
    "    \"Sentiment\", \\\n",
    "    \"Emotions\",\\\n",
    "    \"Customer Service\" as the keys.\\\n",
    "\n",
    "    Review: '''{text}'''\n",
    "    \"\"\"\n",
    "    return prompt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "68798829",
   "metadata": {},
   "outputs": [],
   "source": [
    "def model_response(prompt):\n",
    "    response = openai.ChatCompletion.create(\n",
    "    model=\"gpt-3.5-turbo\",\n",
    "    messages= [{\"role\": \"user\", \"content\": prompt}],\n",
    "    temperature=0,\n",
    "    )\n",
    "    return response.choices[0].message[\"content\"], response.usage.total_tokens"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "80c44f08",
   "metadata": {},
   "source": [
    "### chatgpt extract the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "5bcf049b",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Review No 1\n",
      "\n",
      "\n",
      "Review No 2\n",
      "\n",
      "\n",
      "Review No 3\n",
      "\n",
      "\n",
      "Review No 4\n",
      "\n",
      "\n",
      "Review No 5\n",
      "\n",
      "\n",
      "Review No 6\n",
      "\n",
      "\n",
      "Review No 7\n",
      "\n",
      "\n",
      "Review No 8\n",
      "\n",
      "\n",
      "Review No 9\n",
      "\n",
      "\n",
      "Review No 10\n",
      "\n",
      "\n",
      "Review No 11\n",
      "\n",
      "\n",
      "Review No 12\n",
      "\n",
      "\n",
      "Review No 13\n",
      "\n",
      "\n",
      "Review No 14\n",
      "\n",
      "\n",
      "Review No 15\n",
      "\n",
      "\n",
      "Review No 16\n",
      "\n",
      "\n",
      "Review No 17\n",
      "\n",
      "\n",
      "Review No 18\n",
      "\n",
      "\n",
      "Review No 19\n",
      "\n",
      "Starting the pause...\n",
      "Pause is over.\n",
      "\n",
      "Review No 20\n",
      "\n",
      "\n",
      "Review No 21\n",
      "\n",
      "\n",
      "Review No 22\n",
      "\n",
      "\n",
      "Review No 23\n",
      "\n",
      "\n",
      "Review No 24\n",
      "\n",
      "\n",
      "Review No 25\n",
      "\n",
      "\n",
      "Review No 26\n",
      "\n",
      "\n",
      "Review No 27\n",
      "\n",
      "\n",
      "Review No 28\n",
      "\n",
      "\n",
      "Review No 29\n",
      "\n",
      "\n",
      "Review No 30\n",
      "\n",
      "\n",
      "Review No 31\n",
      "\n",
      "\n",
      "Review No 32\n",
      "\n",
      "\n",
      "Review No 33\n",
      "\n",
      "\n",
      "Review No 34\n",
      "\n",
      "\n",
      "Review No 35\n",
      "\n",
      "\n",
      "Review No 36\n",
      "\n",
      "\n",
      "Review No 37\n",
      "\n",
      "\n",
      "Review No 38\n",
      "\n",
      "\n",
      "Review No 39\n",
      "\n",
      "Starting the pause...\n",
      "Pause is over.\n",
      "\n",
      "Review No 40\n",
      "\n",
      "\n",
      "Review No 41\n",
      "\n",
      "\n",
      "Review No 42\n",
      "\n",
      "\n",
      "Review No 43\n",
      "\n",
      "\n",
      "Review No 44\n",
      "\n",
      "\n",
      "Review No 45\n",
      "\n",
      "\n",
      "Review No 46\n",
      "\n",
      "\n",
      "Review No 47\n",
      "\n",
      "\n",
      "Review No 48\n",
      "\n",
      "\n",
      "Review No 49\n",
      "\n",
      "\n",
      "Review No 50\n",
      "\n",
      "\n",
      "Review No 51\n",
      "\n",
      "\n",
      "Review No 52\n",
      "\n",
      "\n",
      "Review No 53\n",
      "\n",
      "\n",
      "Review No 54\n",
      "\n",
      "\n",
      "Review No 55\n",
      "\n",
      "\n",
      "Review No 56\n",
      "\n",
      "\n",
      "Review No 57\n",
      "\n",
      "\n",
      "Review No 58\n",
      "\n",
      "\n",
      "Review No 59\n",
      "\n",
      "Starting the pause...\n",
      "Pause is over.\n",
      "\n",
      "Review No 60\n",
      "\n"
     ]
    }
   ],
   "source": [
    "output_list = []\n",
    "total_tokens_list = []\n",
    "\n",
    "for index in range(len(data)):\n",
    "    \n",
    "    if (index+1)%20 == 0:\n",
    "        print(\"Starting the pause...\")\n",
    "        time.sleep(60)\n",
    "        print(\"Pause is over.\")\n",
    "    \n",
    "    print(f\"\\nReview No {index+1}\\n\")    \n",
    "    text = data[\"review_content\"].tolist()[index]\n",
    "\n",
    "    prompt = prompt_text(text)\n",
    "    output, total_tokens = model_response(prompt)\n",
    "    \n",
    "    output_refine = json.loads(output.replace(\"\\n\", \"\"))\n",
    "    output_list.append(output_refine)\n",
    "    \n",
    "    total_tokens_list.append(total_tokens)  \n",
    "\n",
    "data[\"gpt_output\"] = output_list\n",
    "data[\"gpt_total_tokens\"] = total_tokens_list"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f2315220",
   "metadata": {},
   "source": [
    "### process and create new columns for the extracted data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "9996c3de",
   "metadata": {},
   "outputs": [],
   "source": [
    "sentiment_list = []\n",
    "service_list = []\n",
    "emotions_list = []\n",
    "for index in range(len(data)):\n",
    "    gpt_output = data[\"gpt_output\"].tolist()[index]\n",
    "    sentiment_list.append(gpt_output[\"Sentiment\"])\n",
    "    service_list.append(gpt_output[\"Customer Service\"])\n",
    "    emotions_list.append(gpt_output[\"Emotions\"])\n",
    "\n",
    "data[\"gpt_output_sentiment\"] = sentiment_list\n",
    "data[\"gpt_output_service\"] = service_list\n",
    "data[\"gpt_output_emotions\"] = emotions_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "00006560",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>location_id</th>\n",
       "      <th>location_name</th>\n",
       "      <th>moreReview</th>\n",
       "      <th>review_rating</th>\n",
       "      <th>review_rating_category</th>\n",
       "      <th>review_date</th>\n",
       "      <th>review_content</th>\n",
       "      <th>gpt_output</th>\n",
       "      <th>gpt_total_tokens</th>\n",
       "      <th>gpt_output_sentiment</th>\n",
       "      <th>gpt_output_service</th>\n",
       "      <th>gpt_output_emotions</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>id_33</td>\n",
       "      <td>香港大學綜合大樓地下2號舖</td>\n",
       "      <td>{\"author_name\": \"Coey\", \"rating\": \"1 star\", \"r...</td>\n",
       "      <td>1</td>\n",
       "      <td>&lt;= 3 stars</td>\n",
       "      <td>&lt;= a year</td>\n",
       "      <td>the staff is insanely rude, the man with glass...</td>\n",
       "      <td>{'Sentiment': 'Negative', 'Emotions': ['Rude',...</td>\n",
       "      <td>337</td>\n",
       "      <td>Negative</td>\n",
       "      <td>Negative</td>\n",
       "      <td>[Rude, Doubtful, Frustrated]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>id_33</td>\n",
       "      <td>香港大學綜合大樓地下2號舖</td>\n",
       "      <td>{\"author_name\": \"Momo Yung\", \"rating\": \"1 star...</td>\n",
       "      <td>1</td>\n",
       "      <td>&lt;= 3 stars</td>\n",
       "      <td>&gt; a year</td>\n",
       "      <td>I am in a rush to get my car out of carpark bu...</td>\n",
       "      <td>{'Sentiment': 'Negative', 'Emotions': ['Hungry...</td>\n",
       "      <td>297</td>\n",
       "      <td>Negative</td>\n",
       "      <td>Negative</td>\n",
       "      <td>[Hungry, Disappointed, Ignored]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>id_33</td>\n",
       "      <td>香港大學綜合大樓地下2號舖</td>\n",
       "      <td>{\"author_name\": \"TSZ LOK Cheng\", \"rating\": \"1 ...</td>\n",
       "      <td>1</td>\n",
       "      <td>&lt;= 3 stars</td>\n",
       "      <td>&lt;= a year</td>\n",
       "      <td>They don't accept cash to order coffee nor top...</td>\n",
       "      <td>{'Sentiment': 'Negative', 'Emotions': ['Disapp...</td>\n",
       "      <td>227</td>\n",
       "      <td>Negative</td>\n",
       "      <td>NA</td>\n",
       "      <td>[Disappointing, Frustrated, Unhappy]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>id_33</td>\n",
       "      <td>香港大學綜合大樓地下2號舖</td>\n",
       "      <td>{\"author_name\": \"Jasper\", \"rating\": \"5 stars\",...</td>\n",
       "      <td>5</td>\n",
       "      <td>&gt; 3 stars</td>\n",
       "      <td>&gt; a year</td>\n",
       "      <td>30% discount for HKU students 😄 …</td>\n",
       "      <td>{'Sentiment': 'Positive', 'Emotions': ['Happy'...</td>\n",
       "      <td>213</td>\n",
       "      <td>Positive</td>\n",
       "      <td>NA</td>\n",
       "      <td>[Happy, Excited, Pleased]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>id_33</td>\n",
       "      <td>香港大學綜合大樓地下2號舖</td>\n",
       "      <td>{\"author_name\": \"Patrick Bai\", \"rating\": \"5 st...</td>\n",
       "      <td>5</td>\n",
       "      <td>&gt; 3 stars</td>\n",
       "      <td>&gt; a year</td>\n",
       "      <td>With the student discount, drinks are outrageo...</td>\n",
       "      <td>{'Sentiment': 'Positive', 'Emotions': ['Thrill...</td>\n",
       "      <td>228</td>\n",
       "      <td>Positive</td>\n",
       "      <td>NA</td>\n",
       "      <td>[Thrilled, Pleased, Impressed]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>id_33</td>\n",
       "      <td>香港大學綜合大樓地下2號舖</td>\n",
       "      <td>{\"author_name\": \"Jeshurun Ratnasamy\", \"rating\"...</td>\n",
       "      <td>4</td>\n",
       "      <td>&gt; 3 stars</td>\n",
       "      <td>&lt;= a year</td>\n",
       "      <td>it’s a starbucks.  not much to say apart from ...</td>\n",
       "      <td>{'Sentiment': 'Neutral', 'Emotions': ['Conveni...</td>\n",
       "      <td>230</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>NA</td>\n",
       "      <td>[Convenient, Routine, Unremarkable]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>id_33</td>\n",
       "      <td>香港大學綜合大樓地下2號舖</td>\n",
       "      <td>{\"author_name\": \"Tim Leung\", \"rating\": \"4 star...</td>\n",
       "      <td>4</td>\n",
       "      <td>&gt; 3 stars</td>\n",
       "      <td>&gt; a year</td>\n",
       "      <td>Reasonable price for HKU personnel. Only a sma...</td>\n",
       "      <td>{'Sentiment': 'Neutral', 'Emotions': ['Reasona...</td>\n",
       "      <td>220</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>NA</td>\n",
       "      <td>[Reasonable, Small, Available]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>id_33</td>\n",
       "      <td>香港大學綜合大樓地下2號舖</td>\n",
       "      <td>{\"author_name\": \"Terence Wan\", \"rating\": \"4 st...</td>\n",
       "      <td>4</td>\n",
       "      <td>&gt; 3 stars</td>\n",
       "      <td>&gt; a year</td>\n",
       "      <td>Cold Brew less ice</td>\n",
       "      <td>{'Sentiment': 'Neutral', 'Emotions': ['Cold', ...</td>\n",
       "      <td>206</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>NA</td>\n",
       "      <td>[Cold, Less, Icy]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>id_33</td>\n",
       "      <td>香港大學綜合大樓地下2號舖</td>\n",
       "      <td>{\"author_name\": \"Paul Fong\", \"rating\": \"1 star...</td>\n",
       "      <td>1</td>\n",
       "      <td>&lt;= 3 stars</td>\n",
       "      <td>&gt; a year</td>\n",
       "      <td>Staff not so professional n caring。。。。</td>\n",
       "      <td>{'Sentiment': 'Negative', 'Emotions': ['Unprof...</td>\n",
       "      <td>213</td>\n",
       "      <td>Negative</td>\n",
       "      <td>NA</td>\n",
       "      <td>[Unprofessional, Uncaring, Disappointing]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>id_33</td>\n",
       "      <td>香港大學綜合大樓地下2號舖</td>\n",
       "      <td>{\"author_name\": \"msblue737\", \"rating\": \"5 star...</td>\n",
       "      <td>5</td>\n",
       "      <td>&gt; 3 stars</td>\n",
       "      <td>&gt; a year</td>\n",
       "      <td>Good place to get a coffee in tai kok tsui.</td>\n",
       "      <td>{'Sentiment': 'Positive', 'Emotions': ['Good',...</td>\n",
       "      <td>215</td>\n",
       "      <td>Positive</td>\n",
       "      <td>NA</td>\n",
       "      <td>[Good, Enjoyable, Satisfying]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>id_33</td>\n",
       "      <td>香港大學綜合大樓地下2號舖</td>\n",
       "      <td>{\"author_name\": \"Liza Ng\\u5433\\u5c11\\u840d\", \"...</td>\n",
       "      <td>5</td>\n",
       "      <td>&gt; 3 stars</td>\n",
       "      <td>&gt; a year</td>\n",
       "      <td>Never been so subtle &amp; quiet with picturesque ...</td>\n",
       "      <td>{'Sentiment': 'Neutral', 'Emotions': ['Subtle'...</td>\n",
       "      <td>218</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>NA</td>\n",
       "      <td>[Subtle, Quiet, Picturesque]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>id_33</td>\n",
       "      <td>香港大學綜合大樓地下2號舖</td>\n",
       "      <td>{\"author_name\": \"Victor Li\", \"rating\": \"5 star...</td>\n",
       "      <td>5</td>\n",
       "      <td>&gt; 3 stars</td>\n",
       "      <td>&gt; a year</td>\n",
       "      <td>Enjoy Starbucks coffee with 30% discount price...</td>\n",
       "      <td>{'Sentiment': 'Positive', 'Emotions': ['Enjoya...</td>\n",
       "      <td>216</td>\n",
       "      <td>Positive</td>\n",
       "      <td>NA</td>\n",
       "      <td>[Enjoyable, Popular, Discounted]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>id_33</td>\n",
       "      <td>香港大學綜合大樓地下2號舖</td>\n",
       "      <td>{\"author_name\": \"Hsu George\", \"rating\": \"3 sta...</td>\n",
       "      <td>3</td>\n",
       "      <td>&lt;= 3 stars</td>\n",
       "      <td>&gt; a year</td>\n",
       "      <td>The coffee is good. Service ordinary</td>\n",
       "      <td>{'Sentiment': 'Neutral', 'Emotions': ['Good', ...</td>\n",
       "      <td>209</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>NA</td>\n",
       "      <td>[Good, Ordinary, NA]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>id_33</td>\n",
       "      <td>香港大學綜合大樓地下2號舖</td>\n",
       "      <td>{\"author_name\": \"Sean Massa\", \"rating\": \"1 sta...</td>\n",
       "      <td>1</td>\n",
       "      <td>&lt;= 3 stars</td>\n",
       "      <td>&gt; a year</td>\n",
       "      <td>20 minute wait for mobile order latte</td>\n",
       "      <td>{'Sentiment': 'Neutral', 'Emotions': ['Impatie...</td>\n",
       "      <td>216</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>NA</td>\n",
       "      <td>[Impatient, Frustrated, Annoyed]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>id_33</td>\n",
       "      <td>香港大學綜合大樓地下2號舖</td>\n",
       "      <td>{\"author_name\": \"William Tang\", \"rating\": \"3 s...</td>\n",
       "      <td>3</td>\n",
       "      <td>&lt;= 3 stars</td>\n",
       "      <td>&gt; a year</td>\n",
       "      <td>Small. Not good.</td>\n",
       "      <td>{'Sentiment': 'Negative', 'Emotions': ['Disapp...</td>\n",
       "      <td>212</td>\n",
       "      <td>Negative</td>\n",
       "      <td>NA</td>\n",
       "      <td>[Disappointing, Unsatisfactory, Unimpressive]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>id_33</td>\n",
       "      <td>香港大學綜合大樓地下2號舖</td>\n",
       "      <td>{\"author_name\": \"Gabriela Sofia\", \"rating\": \"5...</td>\n",
       "      <td>5</td>\n",
       "      <td>&gt; 3 stars</td>\n",
       "      <td>&gt; a year</td>\n",
       "      <td>good price inside HKU</td>\n",
       "      <td>{'Sentiment': 'Neutral', 'Emotions': ['Good', ...</td>\n",
       "      <td>208</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>NA</td>\n",
       "      <td>[Good, Affordable, Convenient]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>id_33</td>\n",
       "      <td>香港大學綜合大樓地下2號舖</td>\n",
       "      <td>{\"author_name\": \"Ahmed Zaeneldin\", \"rating\": \"...</td>\n",
       "      <td>5</td>\n",
       "      <td>&gt; 3 stars</td>\n",
       "      <td>&gt; a year</td>\n",
       "      <td>Very good as usual</td>\n",
       "      <td>{'Sentiment': 'Positive', 'Emotions': ['Satisf...</td>\n",
       "      <td>210</td>\n",
       "      <td>Positive</td>\n",
       "      <td>NA</td>\n",
       "      <td>[Satisfactory, Consistent, Pleasant]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>id_33</td>\n",
       "      <td>香港大學綜合大樓地下2號舖</td>\n",
       "      <td>{\"author_name\": \"\\u9673\\u6cd5\\u62c9\\uff08Cat3\\...</td>\n",
       "      <td>4</td>\n",
       "      <td>&gt; 3 stars</td>\n",
       "      <td>&gt; a year</td>\n",
       "      <td>Have a break, coffee</td>\n",
       "      <td>{'Sentiment': 'Neutral', 'Emotions': ['Relaxin...</td>\n",
       "      <td>210</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>NA</td>\n",
       "      <td>[Relaxing, Refreshing, Satisfying]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>id_33</td>\n",
       "      <td>香港大學綜合大樓地下2號舖</td>\n",
       "      <td>{\"author_name\": \"Benjoman Choi\", \"rating\": \"5 ...</td>\n",
       "      <td>5</td>\n",
       "      <td>&gt; 3 stars</td>\n",
       "      <td>&gt; a year</td>\n",
       "      <td>Online Apps purchase</td>\n",
       "      <td>{'Sentiment': 'Neutral', 'Emotions': ['Conveni...</td>\n",
       "      <td>208</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>NA</td>\n",
       "      <td>[Convenient, Efficient, Impersonal]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>id_33</td>\n",
       "      <td>香港大學綜合大樓地下2號舖</td>\n",
       "      <td>{\"author_name\": \"noemi amador\", \"rating\": \"5 s...</td>\n",
       "      <td>5</td>\n",
       "      <td>&gt; 3 stars</td>\n",
       "      <td>&gt; a year</td>\n",
       "      <td>love it</td>\n",
       "      <td>{'Sentiment': 'Positive', 'Emotions': ['Adorat...</td>\n",
       "      <td>208</td>\n",
       "      <td>Positive</td>\n",
       "      <td>NA</td>\n",
       "      <td>[Adoration, Affectionate, Fondness]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>id_48</td>\n",
       "      <td>The Henry*</td>\n",
       "      <td>{\"author_name\": \"Jack Poon\", \"rating\": \"5 star...</td>\n",
       "      <td>5</td>\n",
       "      <td>&gt; 3 stars</td>\n",
       "      <td>&gt; a year</td>\n",
       "      <td>I’ve always been a Starbucks fan. I bought the...</td>\n",
       "      <td>{'Sentiment': 'Positive', 'Emotions': ['Favour...</td>\n",
       "      <td>264</td>\n",
       "      <td>Positive</td>\n",
       "      <td>NA</td>\n",
       "      <td>[Favourable, Wishful, Satisfied]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>id_48</td>\n",
       "      <td>The Henry*</td>\n",
       "      <td>{\"author_name\": \"EY\", \"rating\": \"1 star\", \"rev...</td>\n",
       "      <td>1</td>\n",
       "      <td>&lt;= 3 stars</td>\n",
       "      <td>&lt;= a year</td>\n",
       "      <td>ordered a vanilla sweet cream cold brew but it...</td>\n",
       "      <td>{'Sentiment': 'Negative', 'Emotions': ['Watery...</td>\n",
       "      <td>226</td>\n",
       "      <td>Negative</td>\n",
       "      <td>NA</td>\n",
       "      <td>[Watery, Disappointing, Unsatisfactory]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>id_48</td>\n",
       "      <td>The Henry*</td>\n",
       "      <td>{\"author_name\": \"Mark Lam\", \"rating\": \"1 star\"...</td>\n",
       "      <td>1</td>\n",
       "      <td>&lt;= 3 stars</td>\n",
       "      <td>&lt;= a year</td>\n",
       "      <td>Extremely slow to take orders</td>\n",
       "      <td>{'Sentiment': 'Negative', 'Emotions': ['Frustr...</td>\n",
       "      <td>214</td>\n",
       "      <td>Negative</td>\n",
       "      <td>NA</td>\n",
       "      <td>[Frustrated, Impatient, Annoyed]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>id_48</td>\n",
       "      <td>The Henry*</td>\n",
       "      <td>{\"author_name\": \"Joaquim D'Silva\", \"rating\": \"...</td>\n",
       "      <td>4</td>\n",
       "      <td>&gt; 3 stars</td>\n",
       "      <td>&gt; a year</td>\n",
       "      <td>Fresh coffees [one of the best] to your liking...</td>\n",
       "      <td>{'Sentiment': 'Neutral', 'Emotions': ['Polite'...</td>\n",
       "      <td>255</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>NA</td>\n",
       "      <td>[Polite, Warm, Better]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>id_48</td>\n",
       "      <td>The Henry*</td>\n",
       "      <td>{\"author_name\": \"Eve K\", \"rating\": \"2 stars\", ...</td>\n",
       "      <td>2</td>\n",
       "      <td>&lt;= 3 stars</td>\n",
       "      <td>&gt; a year</td>\n",
       "      <td>Really cold... super strong AC. Food there is ...</td>\n",
       "      <td>{'Sentiment': 'Negative', 'Emotions': ['Cold',...</td>\n",
       "      <td>255</td>\n",
       "      <td>Negative</td>\n",
       "      <td>NA</td>\n",
       "      <td>[Cold, Old, Infrequent]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>id_48</td>\n",
       "      <td>The Henry*</td>\n",
       "      <td>{\"author_name\": \"Bloggers Boyfriend\", \"rating\"...</td>\n",
       "      <td>2</td>\n",
       "      <td>&lt;= 3 stars</td>\n",
       "      <td>&gt; a year</td>\n",
       "      <td>wifi is Slow AF and limited 30 minutes per tra...</td>\n",
       "      <td>{'Sentiment': 'Negative', 'Emotions': ['Frustr...</td>\n",
       "      <td>224</td>\n",
       "      <td>Negative</td>\n",
       "      <td>NA</td>\n",
       "      <td>[Frustrated, Annoyed, Disappointed]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>id_48</td>\n",
       "      <td>The Henry*</td>\n",
       "      <td>{\"author_name\": \"Dmitry Belousov\", \"rating\": \"...</td>\n",
       "      <td>3</td>\n",
       "      <td>&lt;= 3 stars</td>\n",
       "      <td>&gt; a year</td>\n",
       "      <td>Typical Starbucks, not very crowded but extrem...</td>\n",
       "      <td>{'Sentiment': 'Negative', 'Emotions': ['Crowde...</td>\n",
       "      <td>233</td>\n",
       "      <td>Negative</td>\n",
       "      <td>NA</td>\n",
       "      <td>[Crowded, Small, Dirty]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>id_48</td>\n",
       "      <td>The Henry*</td>\n",
       "      <td>{\"author_name\": \"Michael JD Castro\", \"rating\":...</td>\n",
       "      <td>5</td>\n",
       "      <td>&gt; 3 stars</td>\n",
       "      <td>&gt; a year</td>\n",
       "      <td>Staff are prompt and helpful, remembers my usu...</td>\n",
       "      <td>{'Sentiment': 'Positive', 'Emotions': ['Helpfu...</td>\n",
       "      <td>218</td>\n",
       "      <td>Positive</td>\n",
       "      <td>Positive</td>\n",
       "      <td>[Helpful, Prompt, Memorable]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>id_48</td>\n",
       "      <td>The Henry*</td>\n",
       "      <td>{\"author_name\": \"Lilly-Beth Bushell\", \"rating\"...</td>\n",
       "      <td>3</td>\n",
       "      <td>&lt;= 3 stars</td>\n",
       "      <td>&gt; a year</td>\n",
       "      <td>service wasn't great, nice food and drinks tho</td>\n",
       "      <td>{'Sentiment': 'Neutral', 'Emotions': ['Nice', ...</td>\n",
       "      <td>211</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>Negative</td>\n",
       "      <td>[Nice, Great, Neutral]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>id_48</td>\n",
       "      <td>The Henry*</td>\n",
       "      <td>{\"author_name\": \"\\u5229\\u840a\\u60e0\\u6c11Leyno...</td>\n",
       "      <td>3</td>\n",
       "      <td>&lt;= 3 stars</td>\n",
       "      <td>&gt; a year</td>\n",
       "      <td>Serene corner, tastful coffee and food, nice l...</td>\n",
       "      <td>{'Sentiment': 'Positive', 'Emotions': ['Serene...</td>\n",
       "      <td>218</td>\n",
       "      <td>Positive</td>\n",
       "      <td>NA</td>\n",
       "      <td>[Serene, Tasteful, Nice]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>id_48</td>\n",
       "      <td>The Henry*</td>\n",
       "      <td>{\"author_name\": \"Kdbdbsk Idbdjfk\", \"rating\": \"...</td>\n",
       "      <td>4</td>\n",
       "      <td>&gt; 3 stars</td>\n",
       "      <td>&gt; a year</td>\n",
       "      <td>All good, relatively small and too cold on the...</td>\n",
       "      <td>{'Sentiment': 'Neutral', 'Emotions': ['Good', ...</td>\n",
       "      <td>215</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>NA</td>\n",
       "      <td>[Good, Small, Cold]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>id_48</td>\n",
       "      <td>The Henry*</td>\n",
       "      <td>{\"author_name\": \"KWAI LING VANESSA TAM\", \"rati...</td>\n",
       "      <td>2</td>\n",
       "      <td>&lt;= 3 stars</td>\n",
       "      <td>&gt; a year</td>\n",
       "      <td>Quiet place. But most of their staffs are unpl...</td>\n",
       "      <td>{'Sentiment': 'Negative', 'Emotions': ['Unplea...</td>\n",
       "      <td>213</td>\n",
       "      <td>Negative</td>\n",
       "      <td>NA</td>\n",
       "      <td>[Unpleasant, Quiet, Reserved]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>id_48</td>\n",
       "      <td>The Henry*</td>\n",
       "      <td>{\"author_name\": \"Alfred Chan\", \"rating\": \"4 st...</td>\n",
       "      <td>4</td>\n",
       "      <td>&gt; 3 stars</td>\n",
       "      <td>&gt; a year</td>\n",
       "      <td>Good service. Nice place for a short break</td>\n",
       "      <td>{'Sentiment': 'Positive', 'Emotions': ['Good',...</td>\n",
       "      <td>210</td>\n",
       "      <td>Positive</td>\n",
       "      <td>NA</td>\n",
       "      <td>[Good, Nice, Short]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>id_48</td>\n",
       "      <td>The Henry*</td>\n",
       "      <td>{\"author_name\": \"Michael Davies\", \"rating\": \"5...</td>\n",
       "      <td>5</td>\n",
       "      <td>&gt; 3 stars</td>\n",
       "      <td>&lt;= a year</td>\n",
       "      <td>Great service as usual</td>\n",
       "      <td>{'Sentiment': 'Positive', 'Emotions': ['Great'...</td>\n",
       "      <td>206</td>\n",
       "      <td>Positive</td>\n",
       "      <td>NA</td>\n",
       "      <td>[Great, Usual, Service]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>id_48</td>\n",
       "      <td>The Henry*</td>\n",
       "      <td>{\"author_name\": \"Jamil Ahmad\", \"rating\": \"4 st...</td>\n",
       "      <td>4</td>\n",
       "      <td>&gt; 3 stars</td>\n",
       "      <td>&gt; a year</td>\n",
       "      <td>Same old Starbucks but practical location and ...</td>\n",
       "      <td>{'Sentiment': 'Neutral', 'Emotions': ['Practic...</td>\n",
       "      <td>217</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>NA</td>\n",
       "      <td>[Practical, Quiet, Chaotic]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>id_48</td>\n",
       "      <td>The Henry*</td>\n",
       "      <td>{\"author_name\": \"Douglas Baird\", \"rating\": \"4 ...</td>\n",
       "      <td>4</td>\n",
       "      <td>&gt; 3 stars</td>\n",
       "      <td>&gt; a year</td>\n",
       "      <td>Small store but the usual coffee. Friendly hel...</td>\n",
       "      <td>{'Sentiment': 'Positive', 'Emotions': ['Small'...</td>\n",
       "      <td>213</td>\n",
       "      <td>Positive</td>\n",
       "      <td>Positive</td>\n",
       "      <td>[Small, Usual, Friendly]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>id_48</td>\n",
       "      <td>The Henry*</td>\n",
       "      <td>{\"author_name\": \"William Thong\", \"rating\": \"4 ...</td>\n",
       "      <td>4</td>\n",
       "      <td>&gt; 3 stars</td>\n",
       "      <td>&gt; a year</td>\n",
       "      <td>Cosy but music is too soft, almost unheardable</td>\n",
       "      <td>{'Sentiment': 'Neutral', 'Emotions': ['Cosy', ...</td>\n",
       "      <td>215</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>NA</td>\n",
       "      <td>[Cosy, Soft, Unheardable]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>id_48</td>\n",
       "      <td>The Henry*</td>\n",
       "      <td>{\"author_name\": \"Colin Sze\", \"rating\": \"5 star...</td>\n",
       "      <td>5</td>\n",
       "      <td>&gt; 3 stars</td>\n",
       "      <td>&gt; a year</td>\n",
       "      <td>A global success you have chosen</td>\n",
       "      <td>{'Sentiment': 'Neutral', 'Emotions': ['Global'...</td>\n",
       "      <td>208</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>NA</td>\n",
       "      <td>[Global, Successful, Chosen]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>id_48</td>\n",
       "      <td>The Henry*</td>\n",
       "      <td>{\"author_name\": \"Annebabe Cheer\", \"rating\": \"3...</td>\n",
       "      <td>3</td>\n",
       "      <td>&lt;= 3 stars</td>\n",
       "      <td>&gt; a year</td>\n",
       "      <td>The cake is not tasty, and quite expensive</td>\n",
       "      <td>{'Sentiment': 'Negative', 'Emotions': ['Unplea...</td>\n",
       "      <td>215</td>\n",
       "      <td>Negative</td>\n",
       "      <td>NA</td>\n",
       "      <td>[Unpleasant, Overpriced, Disappointing]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>id_48</td>\n",
       "      <td>The Henry*</td>\n",
       "      <td>{\"author_name\": \"\\u30b1\\u30fc\\u30d3\", \"rating\"...</td>\n",
       "      <td>4</td>\n",
       "      <td>&gt; 3 stars</td>\n",
       "      <td>&gt; a year</td>\n",
       "      <td>Risotto Bianco is the best!!</td>\n",
       "      <td>{'Sentiment': 'Positive', 'Emotions': ['Delici...</td>\n",
       "      <td>213</td>\n",
       "      <td>Positive</td>\n",
       "      <td>NA</td>\n",
       "      <td>[Delicious, Amazing, Satisfying]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>id_93</td>\n",
       "      <td>Imperial Kennedy</td>\n",
       "      <td>{\"author_name\": \"Mugi Yamamoto\", \"rating\": \"4 ...</td>\n",
       "      <td>4</td>\n",
       "      <td>&gt; 3 stars</td>\n",
       "      <td>&lt;= a year</td>\n",
       "      <td>I had a very good experience at Starbucks this...</td>\n",
       "      <td>{'Sentiment': 'Positive', 'Emotions': ['Effici...</td>\n",
       "      <td>419</td>\n",
       "      <td>Positive</td>\n",
       "      <td>NA</td>\n",
       "      <td>[Efficient, Enjoyed, Clean]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>id_93</td>\n",
       "      <td>Imperial Kennedy</td>\n",
       "      <td>{\"author_name\": \"Lisa Tang\", \"rating\": \"3 star...</td>\n",
       "      <td>3</td>\n",
       "      <td>&lt;= 3 stars</td>\n",
       "      <td>&gt; a year</td>\n",
       "      <td>Nice and quite. However, its not busy and with...</td>\n",
       "      <td>{'Sentiment': 'Negative', 'Emotions': ['Quiet'...</td>\n",
       "      <td>223</td>\n",
       "      <td>Negative</td>\n",
       "      <td>Negative</td>\n",
       "      <td>[Quiet, Nice, Unacceptable]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>id_93</td>\n",
       "      <td>Imperial Kennedy</td>\n",
       "      <td>{\"author_name\": \"Tareq Muhmood\", \"rating\": \"4 ...</td>\n",
       "      <td>4</td>\n",
       "      <td>&gt; 3 stars</td>\n",
       "      <td>&gt; a year</td>\n",
       "      <td>Always a good shelter to jump into from the hu...</td>\n",
       "      <td>{'Sentiment': 'Positive', 'Emotions': ['Relaxi...</td>\n",
       "      <td>244</td>\n",
       "      <td>Positive</td>\n",
       "      <td>NA</td>\n",
       "      <td>[Relaxing, Comforting, Special]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>id_93</td>\n",
       "      <td>Imperial Kennedy</td>\n",
       "      <td>{\"author_name\": \"Brian\", \"rating\": \"2 stars\", ...</td>\n",
       "      <td>2</td>\n",
       "      <td>&lt;= 3 stars</td>\n",
       "      <td>&gt; a year</td>\n",
       "      <td>Nice ambiance.\\nGood average coffee (starbucks...</td>\n",
       "      <td>{'Sentiment': 'Neutral', 'Emotions': ['Nice', ...</td>\n",
       "      <td>248</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>NA</td>\n",
       "      <td>[Nice, Average, Important]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>id_93</td>\n",
       "      <td>Imperial Kennedy</td>\n",
       "      <td>{\"author_name\": \"Adam Newbold\", \"rating\": \"5 s...</td>\n",
       "      <td>5</td>\n",
       "      <td>&gt; 3 stars</td>\n",
       "      <td>&gt; a year</td>\n",
       "      <td>Friendly staff make this an inviting Starbucks...</td>\n",
       "      <td>{'Sentiment': 'Positive', 'Emotions': ['Friend...</td>\n",
       "      <td>255</td>\n",
       "      <td>Positive</td>\n",
       "      <td>Positive</td>\n",
       "      <td>[Friendly, Efficient, Hospitable]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>id_93</td>\n",
       "      <td>Imperial Kennedy</td>\n",
       "      <td>{\"author_name\": \"Gideon Oi\", \"rating\": \"5 star...</td>\n",
       "      <td>5</td>\n",
       "      <td>&gt; 3 stars</td>\n",
       "      <td>&gt; a year</td>\n",
       "      <td>Very nice staff. Went over everyday for 3 days...</td>\n",
       "      <td>{'Sentiment': 'Positive', 'Emotions': ['Friend...</td>\n",
       "      <td>260</td>\n",
       "      <td>Positive</td>\n",
       "      <td>NA</td>\n",
       "      <td>[Friendly, Efficient, Relaxing]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>id_93</td>\n",
       "      <td>Imperial Kennedy</td>\n",
       "      <td>{\"author_name\": \"Kelly H\", \"rating\": \"2 stars\"...</td>\n",
       "      <td>2</td>\n",
       "      <td>&lt;= 3 stars</td>\n",
       "      <td>&gt; a year</td>\n",
       "      <td>Air conditioning hasnt been functioning for ab...</td>\n",
       "      <td>{'Sentiment': 'Negative', 'Emotions': ['Frustr...</td>\n",
       "      <td>265</td>\n",
       "      <td>Negative</td>\n",
       "      <td>NA</td>\n",
       "      <td>[Frustrated, Disgusted, Uncomfortable]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>id_93</td>\n",
       "      <td>Imperial Kennedy</td>\n",
       "      <td>{\"author_name\": \"Sachin Pradhan\", \"rating\": \"5...</td>\n",
       "      <td>5</td>\n",
       "      <td>&gt; 3 stars</td>\n",
       "      <td>&gt; a year</td>\n",
       "      <td>Beautiful an amazing place 🥰 …</td>\n",
       "      <td>{'Sentiment': 'Positive', 'Emotions': ['Beauti...</td>\n",
       "      <td>210</td>\n",
       "      <td>Positive</td>\n",
       "      <td>NA</td>\n",
       "      <td>[Beautiful, Amazing, Lovely]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>id_93</td>\n",
       "      <td>Imperial Kennedy</td>\n",
       "      <td>{\"author_name\": \"Alu LO\", \"rating\": \"2 stars\",...</td>\n",
       "      <td>2</td>\n",
       "      <td>&lt;= 3 stars</td>\n",
       "      <td>&gt; a year</td>\n",
       "      <td>Dunno why shut down the Air condition in summe...</td>\n",
       "      <td>{'Sentiment': 'Negative', 'Emotions': ['Frustr...</td>\n",
       "      <td>242</td>\n",
       "      <td>Negative</td>\n",
       "      <td>NA</td>\n",
       "      <td>[Frustrated, Disappointed, Confused]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>id_93</td>\n",
       "      <td>Imperial Kennedy</td>\n",
       "      <td>{\"author_name\": \"Ma Gina Aclan\", \"rating\": \"5 ...</td>\n",
       "      <td>5</td>\n",
       "      <td>&gt; 3 stars</td>\n",
       "      <td>&lt;= a year</td>\n",
       "      <td>peaceful and enjoyable 😉 with a good company ❤️</td>\n",
       "      <td>{'Sentiment': 'Positive', 'Emotions': ['Peacef...</td>\n",
       "      <td>214</td>\n",
       "      <td>Positive</td>\n",
       "      <td>NA</td>\n",
       "      <td>[Peaceful, Enjoyable, Good]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>id_93</td>\n",
       "      <td>Imperial Kennedy</td>\n",
       "      <td>{\"author_name\": \"Alexandra Edwards\", \"rating\":...</td>\n",
       "      <td>5</td>\n",
       "      <td>&gt; 3 stars</td>\n",
       "      <td>&gt; a year</td>\n",
       "      <td>Quick and efficient service, the air con can g...</td>\n",
       "      <td>{'Sentiment': 'Positive', 'Emotions': ['Quick'...</td>\n",
       "      <td>216</td>\n",
       "      <td>Positive</td>\n",
       "      <td>NA</td>\n",
       "      <td>[Quick, Efficient, High]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>id_93</td>\n",
       "      <td>Imperial Kennedy</td>\n",
       "      <td>{\"author_name\": \"Princess Haruchan\", \"rating\":...</td>\n",
       "      <td>3</td>\n",
       "      <td>&lt;= 3 stars</td>\n",
       "      <td>&gt; a year</td>\n",
       "      <td>You only get 30 minutes to use their WiFi and ...</td>\n",
       "      <td>{'Sentiment': 'Neutral', 'Emotions': ['Limited...</td>\n",
       "      <td>240</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>NA</td>\n",
       "      <td>[Limited, Satisfied, Indifferent]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>id_93</td>\n",
       "      <td>Imperial Kennedy</td>\n",
       "      <td>{\"author_name\": \"Rick Liu\", \"rating\": \"2 stars...</td>\n",
       "      <td>2</td>\n",
       "      <td>&lt;= 3 stars</td>\n",
       "      <td>&gt; a year</td>\n",
       "      <td>This Starbucks didn't have enough worker to ti...</td>\n",
       "      <td>{'Sentiment': 'Negative', 'Emotions': ['Disgus...</td>\n",
       "      <td>240</td>\n",
       "      <td>Negative</td>\n",
       "      <td>NA</td>\n",
       "      <td>[Disgusting, Unsatisfied, Unpleasant]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>id_93</td>\n",
       "      <td>Imperial Kennedy</td>\n",
       "      <td>{\"author_name\": \"Peugeot Chu\", \"rating\": \"5 st...</td>\n",
       "      <td>5</td>\n",
       "      <td>&gt; 3 stars</td>\n",
       "      <td>&gt; a year</td>\n",
       "      <td>Cozy shop. Signature chocolate milk and cream ...</td>\n",
       "      <td>{'Sentiment': 'Positive', 'Emotions': ['Cozy',...</td>\n",
       "      <td>222</td>\n",
       "      <td>Positive</td>\n",
       "      <td>NA</td>\n",
       "      <td>[Cozy, Signature, Top]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>id_93</td>\n",
       "      <td>Imperial Kennedy</td>\n",
       "      <td>{\"author_name\": \"reginald\", \"rating\": \"4 stars...</td>\n",
       "      <td>4</td>\n",
       "      <td>&gt; 3 stars</td>\n",
       "      <td>&gt; a year</td>\n",
       "      <td>its a pretty decent place. good atmosphere, qu...</td>\n",
       "      <td>{'Sentiment': 'Positive', 'Emotions': ['Decent...</td>\n",
       "      <td>216</td>\n",
       "      <td>Positive</td>\n",
       "      <td>NA</td>\n",
       "      <td>[Decent, Good, Quick]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>id_93</td>\n",
       "      <td>Imperial Kennedy</td>\n",
       "      <td>{\"author_name\": \"Kimtsy Tai\", \"rating\": \"5 sta...</td>\n",
       "      <td>5</td>\n",
       "      <td>&gt; 3 stars</td>\n",
       "      <td>&lt;= a year</td>\n",
       "      <td>Good coffee, food and nice staff.</td>\n",
       "      <td>{'Sentiment': 'Positive', 'Emotions': ['Good',...</td>\n",
       "      <td>208</td>\n",
       "      <td>Positive</td>\n",
       "      <td>NA</td>\n",
       "      <td>[Good, Nice, Food]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>id_93</td>\n",
       "      <td>Imperial Kennedy</td>\n",
       "      <td>{\"author_name\": \"Trent H\", \"rating\": \"5 stars\"...</td>\n",
       "      <td>5</td>\n",
       "      <td>&gt; 3 stars</td>\n",
       "      <td>&gt; a year</td>\n",
       "      <td>Top notch service from the barista team here. ...</td>\n",
       "      <td>{'Sentiment': 'Positive', 'Emotions': ['Passio...</td>\n",
       "      <td>224</td>\n",
       "      <td>Positive</td>\n",
       "      <td>Positive</td>\n",
       "      <td>[Passionate, Proactive, Professional]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>id_93</td>\n",
       "      <td>Imperial Kennedy</td>\n",
       "      <td>{\"author_name\": \"JH 78\", \"rating\": \"1 star\", \"...</td>\n",
       "      <td>1</td>\n",
       "      <td>&lt;= 3 stars</td>\n",
       "      <td>&gt; a year</td>\n",
       "      <td>Dont go this place, huge shop but only 1 staff...</td>\n",
       "      <td>{'Sentiment': 'Negative', 'Emotions': ['Frustr...</td>\n",
       "      <td>233</td>\n",
       "      <td>Negative</td>\n",
       "      <td>Negative</td>\n",
       "      <td>[Frustrated, Impatient, Disappointed]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>id_93</td>\n",
       "      <td>Imperial Kennedy</td>\n",
       "      <td>{\"author_name\": \"Ross Adcock\", \"rating\": \"4 st...</td>\n",
       "      <td>4</td>\n",
       "      <td>&gt; 3 stars</td>\n",
       "      <td>&gt; a year</td>\n",
       "      <td>A comfortable coffee shop with lots of natural...</td>\n",
       "      <td>{'Sentiment': 'Positive', 'Emotions': ['Comfor...</td>\n",
       "      <td>223</td>\n",
       "      <td>Positive</td>\n",
       "      <td>NA</td>\n",
       "      <td>[Comfortable, Enjoyable, Light]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>id_93</td>\n",
       "      <td>Imperial Kennedy</td>\n",
       "      <td>{\"author_name\": \"Florence Tam\", \"rating\": \"3 s...</td>\n",
       "      <td>3</td>\n",
       "      <td>&lt;= 3 stars</td>\n",
       "      <td>&gt; a year</td>\n",
       "      <td>Dim light, the environment is not very good. F...</td>\n",
       "      <td>{'Sentiment': 'Neutral', 'Emotions': ['Dim', '...</td>\n",
       "      <td>231</td>\n",
       "      <td>Neutral</td>\n",
       "      <td>NA</td>\n",
       "      <td>[Dim, Occupied, Standard]</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   location_id     location_name   \n",
       "0        id_33     香港大學綜合大樓地下2號舖  \\\n",
       "1        id_33     香港大學綜合大樓地下2號舖   \n",
       "2        id_33     香港大學綜合大樓地下2號舖   \n",
       "3        id_33     香港大學綜合大樓地下2號舖   \n",
       "4        id_33     香港大學綜合大樓地下2號舖   \n",
       "5        id_33     香港大學綜合大樓地下2號舖   \n",
       "6        id_33     香港大學綜合大樓地下2號舖   \n",
       "7        id_33     香港大學綜合大樓地下2號舖   \n",
       "8        id_33     香港大學綜合大樓地下2號舖   \n",
       "9        id_33     香港大學綜合大樓地下2號舖   \n",
       "10       id_33     香港大學綜合大樓地下2號舖   \n",
       "11       id_33     香港大學綜合大樓地下2號舖   \n",
       "12       id_33     香港大學綜合大樓地下2號舖   \n",
       "13       id_33     香港大學綜合大樓地下2號舖   \n",
       "14       id_33     香港大學綜合大樓地下2號舖   \n",
       "15       id_33     香港大學綜合大樓地下2號舖   \n",
       "16       id_33     香港大學綜合大樓地下2號舖   \n",
       "17       id_33     香港大學綜合大樓地下2號舖   \n",
       "18       id_33     香港大學綜合大樓地下2號舖   \n",
       "19       id_33     香港大學綜合大樓地下2號舖   \n",
       "20       id_48        The Henry*   \n",
       "21       id_48        The Henry*   \n",
       "22       id_48        The Henry*   \n",
       "23       id_48        The Henry*   \n",
       "24       id_48        The Henry*   \n",
       "25       id_48        The Henry*   \n",
       "26       id_48        The Henry*   \n",
       "27       id_48        The Henry*   \n",
       "28       id_48        The Henry*   \n",
       "29       id_48        The Henry*   \n",
       "30       id_48        The Henry*   \n",
       "31       id_48        The Henry*   \n",
       "32       id_48        The Henry*   \n",
       "33       id_48        The Henry*   \n",
       "34       id_48        The Henry*   \n",
       "35       id_48        The Henry*   \n",
       "36       id_48        The Henry*   \n",
       "37       id_48        The Henry*   \n",
       "38       id_48        The Henry*   \n",
       "39       id_48        The Henry*   \n",
       "40       id_93  Imperial Kennedy   \n",
       "41       id_93  Imperial Kennedy   \n",
       "42       id_93  Imperial Kennedy   \n",
       "43       id_93  Imperial Kennedy   \n",
       "44       id_93  Imperial Kennedy   \n",
       "45       id_93  Imperial Kennedy   \n",
       "46       id_93  Imperial Kennedy   \n",
       "47       id_93  Imperial Kennedy   \n",
       "48       id_93  Imperial Kennedy   \n",
       "49       id_93  Imperial Kennedy   \n",
       "50       id_93  Imperial Kennedy   \n",
       "51       id_93  Imperial Kennedy   \n",
       "52       id_93  Imperial Kennedy   \n",
       "53       id_93  Imperial Kennedy   \n",
       "54       id_93  Imperial Kennedy   \n",
       "55       id_93  Imperial Kennedy   \n",
       "56       id_93  Imperial Kennedy   \n",
       "57       id_93  Imperial Kennedy   \n",
       "58       id_93  Imperial Kennedy   \n",
       "59       id_93  Imperial Kennedy   \n",
       "\n",
       "                                           moreReview  review_rating   \n",
       "0   {\"author_name\": \"Coey\", \"rating\": \"1 star\", \"r...              1  \\\n",
       "1   {\"author_name\": \"Momo Yung\", \"rating\": \"1 star...              1   \n",
       "2   {\"author_name\": \"TSZ LOK Cheng\", \"rating\": \"1 ...              1   \n",
       "3   {\"author_name\": \"Jasper\", \"rating\": \"5 stars\",...              5   \n",
       "4   {\"author_name\": \"Patrick Bai\", \"rating\": \"5 st...              5   \n",
       "5   {\"author_name\": \"Jeshurun Ratnasamy\", \"rating\"...              4   \n",
       "6   {\"author_name\": \"Tim Leung\", \"rating\": \"4 star...              4   \n",
       "7   {\"author_name\": \"Terence Wan\", \"rating\": \"4 st...              4   \n",
       "8   {\"author_name\": \"Paul Fong\", \"rating\": \"1 star...              1   \n",
       "9   {\"author_name\": \"msblue737\", \"rating\": \"5 star...              5   \n",
       "10  {\"author_name\": \"Liza Ng\\u5433\\u5c11\\u840d\", \"...              5   \n",
       "11  {\"author_name\": \"Victor Li\", \"rating\": \"5 star...              5   \n",
       "12  {\"author_name\": \"Hsu George\", \"rating\": \"3 sta...              3   \n",
       "13  {\"author_name\": \"Sean Massa\", \"rating\": \"1 sta...              1   \n",
       "14  {\"author_name\": \"William Tang\", \"rating\": \"3 s...              3   \n",
       "15  {\"author_name\": \"Gabriela Sofia\", \"rating\": \"5...              5   \n",
       "16  {\"author_name\": \"Ahmed Zaeneldin\", \"rating\": \"...              5   \n",
       "17  {\"author_name\": \"\\u9673\\u6cd5\\u62c9\\uff08Cat3\\...              4   \n",
       "18  {\"author_name\": \"Benjoman Choi\", \"rating\": \"5 ...              5   \n",
       "19  {\"author_name\": \"noemi amador\", \"rating\": \"5 s...              5   \n",
       "20  {\"author_name\": \"Jack Poon\", \"rating\": \"5 star...              5   \n",
       "21  {\"author_name\": \"EY\", \"rating\": \"1 star\", \"rev...              1   \n",
       "22  {\"author_name\": \"Mark Lam\", \"rating\": \"1 star\"...              1   \n",
       "23  {\"author_name\": \"Joaquim D'Silva\", \"rating\": \"...              4   \n",
       "24  {\"author_name\": \"Eve K\", \"rating\": \"2 stars\", ...              2   \n",
       "25  {\"author_name\": \"Bloggers Boyfriend\", \"rating\"...              2   \n",
       "26  {\"author_name\": \"Dmitry Belousov\", \"rating\": \"...              3   \n",
       "27  {\"author_name\": \"Michael JD Castro\", \"rating\":...              5   \n",
       "28  {\"author_name\": \"Lilly-Beth Bushell\", \"rating\"...              3   \n",
       "29  {\"author_name\": \"\\u5229\\u840a\\u60e0\\u6c11Leyno...              3   \n",
       "30  {\"author_name\": \"Kdbdbsk Idbdjfk\", \"rating\": \"...              4   \n",
       "31  {\"author_name\": \"KWAI LING VANESSA TAM\", \"rati...              2   \n",
       "32  {\"author_name\": \"Alfred Chan\", \"rating\": \"4 st...              4   \n",
       "33  {\"author_name\": \"Michael Davies\", \"rating\": \"5...              5   \n",
       "34  {\"author_name\": \"Jamil Ahmad\", \"rating\": \"4 st...              4   \n",
       "35  {\"author_name\": \"Douglas Baird\", \"rating\": \"4 ...              4   \n",
       "36  {\"author_name\": \"William Thong\", \"rating\": \"4 ...              4   \n",
       "37  {\"author_name\": \"Colin Sze\", \"rating\": \"5 star...              5   \n",
       "38  {\"author_name\": \"Annebabe Cheer\", \"rating\": \"3...              3   \n",
       "39  {\"author_name\": \"\\u30b1\\u30fc\\u30d3\", \"rating\"...              4   \n",
       "40  {\"author_name\": \"Mugi Yamamoto\", \"rating\": \"4 ...              4   \n",
       "41  {\"author_name\": \"Lisa Tang\", \"rating\": \"3 star...              3   \n",
       "42  {\"author_name\": \"Tareq Muhmood\", \"rating\": \"4 ...              4   \n",
       "43  {\"author_name\": \"Brian\", \"rating\": \"2 stars\", ...              2   \n",
       "44  {\"author_name\": \"Adam Newbold\", \"rating\": \"5 s...              5   \n",
       "45  {\"author_name\": \"Gideon Oi\", \"rating\": \"5 star...              5   \n",
       "46  {\"author_name\": \"Kelly H\", \"rating\": \"2 stars\"...              2   \n",
       "47  {\"author_name\": \"Sachin Pradhan\", \"rating\": \"5...              5   \n",
       "48  {\"author_name\": \"Alu LO\", \"rating\": \"2 stars\",...              2   \n",
       "49  {\"author_name\": \"Ma Gina Aclan\", \"rating\": \"5 ...              5   \n",
       "50  {\"author_name\": \"Alexandra Edwards\", \"rating\":...              5   \n",
       "51  {\"author_name\": \"Princess Haruchan\", \"rating\":...              3   \n",
       "52  {\"author_name\": \"Rick Liu\", \"rating\": \"2 stars...              2   \n",
       "53  {\"author_name\": \"Peugeot Chu\", \"rating\": \"5 st...              5   \n",
       "54  {\"author_name\": \"reginald\", \"rating\": \"4 stars...              4   \n",
       "55  {\"author_name\": \"Kimtsy Tai\", \"rating\": \"5 sta...              5   \n",
       "56  {\"author_name\": \"Trent H\", \"rating\": \"5 stars\"...              5   \n",
       "57  {\"author_name\": \"JH 78\", \"rating\": \"1 star\", \"...              1   \n",
       "58  {\"author_name\": \"Ross Adcock\", \"rating\": \"4 st...              4   \n",
       "59  {\"author_name\": \"Florence Tam\", \"rating\": \"3 s...              3   \n",
       "\n",
       "   review_rating_category review_date   \n",
       "0              <= 3 stars   <= a year  \\\n",
       "1              <= 3 stars    > a year   \n",
       "2              <= 3 stars   <= a year   \n",
       "3               > 3 stars    > a year   \n",
       "4               > 3 stars    > a year   \n",
       "5               > 3 stars   <= a year   \n",
       "6               > 3 stars    > a year   \n",
       "7               > 3 stars    > a year   \n",
       "8              <= 3 stars    > a year   \n",
       "9               > 3 stars    > a year   \n",
       "10              > 3 stars    > a year   \n",
       "11              > 3 stars    > a year   \n",
       "12             <= 3 stars    > a year   \n",
       "13             <= 3 stars    > a year   \n",
       "14             <= 3 stars    > a year   \n",
       "15              > 3 stars    > a year   \n",
       "16              > 3 stars    > a year   \n",
       "17              > 3 stars    > a year   \n",
       "18              > 3 stars    > a year   \n",
       "19              > 3 stars    > a year   \n",
       "20              > 3 stars    > a year   \n",
       "21             <= 3 stars   <= a year   \n",
       "22             <= 3 stars   <= a year   \n",
       "23              > 3 stars    > a year   \n",
       "24             <= 3 stars    > a year   \n",
       "25             <= 3 stars    > a year   \n",
       "26             <= 3 stars    > a year   \n",
       "27              > 3 stars    > a year   \n",
       "28             <= 3 stars    > a year   \n",
       "29             <= 3 stars    > a year   \n",
       "30              > 3 stars    > a year   \n",
       "31             <= 3 stars    > a year   \n",
       "32              > 3 stars    > a year   \n",
       "33              > 3 stars   <= a year   \n",
       "34              > 3 stars    > a year   \n",
       "35              > 3 stars    > a year   \n",
       "36              > 3 stars    > a year   \n",
       "37              > 3 stars    > a year   \n",
       "38             <= 3 stars    > a year   \n",
       "39              > 3 stars    > a year   \n",
       "40              > 3 stars   <= a year   \n",
       "41             <= 3 stars    > a year   \n",
       "42              > 3 stars    > a year   \n",
       "43             <= 3 stars    > a year   \n",
       "44              > 3 stars    > a year   \n",
       "45              > 3 stars    > a year   \n",
       "46             <= 3 stars    > a year   \n",
       "47              > 3 stars    > a year   \n",
       "48             <= 3 stars    > a year   \n",
       "49              > 3 stars   <= a year   \n",
       "50              > 3 stars    > a year   \n",
       "51             <= 3 stars    > a year   \n",
       "52             <= 3 stars    > a year   \n",
       "53              > 3 stars    > a year   \n",
       "54              > 3 stars    > a year   \n",
       "55              > 3 stars   <= a year   \n",
       "56              > 3 stars    > a year   \n",
       "57             <= 3 stars    > a year   \n",
       "58              > 3 stars    > a year   \n",
       "59             <= 3 stars    > a year   \n",
       "\n",
       "                                       review_content   \n",
       "0   the staff is insanely rude, the man with glass...  \\\n",
       "1   I am in a rush to get my car out of carpark bu...   \n",
       "2   They don't accept cash to order coffee nor top...   \n",
       "3                   30% discount for HKU students 😄 …   \n",
       "4   With the student discount, drinks are outrageo...   \n",
       "5   it’s a starbucks.  not much to say apart from ...   \n",
       "6   Reasonable price for HKU personnel. Only a sma...   \n",
       "7                                  Cold Brew less ice   \n",
       "8              Staff not so professional n caring。。。。   \n",
       "9         Good place to get a coffee in tai kok tsui.   \n",
       "10  Never been so subtle & quiet with picturesque ...   \n",
       "11  Enjoy Starbucks coffee with 30% discount price...   \n",
       "12               The coffee is good. Service ordinary   \n",
       "13              20 minute wait for mobile order latte   \n",
       "14                                   Small. Not good.   \n",
       "15                              good price inside HKU   \n",
       "16                                 Very good as usual   \n",
       "17                               Have a break, coffee   \n",
       "18                               Online Apps purchase   \n",
       "19                                            love it   \n",
       "20  I’ve always been a Starbucks fan. I bought the...   \n",
       "21  ordered a vanilla sweet cream cold brew but it...   \n",
       "22                      Extremely slow to take orders   \n",
       "23  Fresh coffees [one of the best] to your liking...   \n",
       "24  Really cold... super strong AC. Food there is ...   \n",
       "25  wifi is Slow AF and limited 30 minutes per tra...   \n",
       "26  Typical Starbucks, not very crowded but extrem...   \n",
       "27  Staff are prompt and helpful, remembers my usu...   \n",
       "28     service wasn't great, nice food and drinks tho   \n",
       "29  Serene corner, tastful coffee and food, nice l...   \n",
       "30  All good, relatively small and too cold on the...   \n",
       "31  Quiet place. But most of their staffs are unpl...   \n",
       "32         Good service. Nice place for a short break   \n",
       "33                             Great service as usual   \n",
       "34  Same old Starbucks but practical location and ...   \n",
       "35  Small store but the usual coffee. Friendly hel...   \n",
       "36     Cosy but music is too soft, almost unheardable   \n",
       "37                   A global success you have chosen   \n",
       "38         The cake is not tasty, and quite expensive   \n",
       "39                       Risotto Bianco is the best!!   \n",
       "40  I had a very good experience at Starbucks this...   \n",
       "41  Nice and quite. However, its not busy and with...   \n",
       "42  Always a good shelter to jump into from the hu...   \n",
       "43  Nice ambiance.\\nGood average coffee (starbucks...   \n",
       "44  Friendly staff make this an inviting Starbucks...   \n",
       "45  Very nice staff. Went over everyday for 3 days...   \n",
       "46  Air conditioning hasnt been functioning for ab...   \n",
       "47                     Beautiful an amazing place 🥰 …   \n",
       "48  Dunno why shut down the Air condition in summe...   \n",
       "49    peaceful and enjoyable 😉 with a good company ❤️   \n",
       "50  Quick and efficient service, the air con can g...   \n",
       "51  You only get 30 minutes to use their WiFi and ...   \n",
       "52  This Starbucks didn't have enough worker to ti...   \n",
       "53  Cozy shop. Signature chocolate milk and cream ...   \n",
       "54  its a pretty decent place. good atmosphere, qu...   \n",
       "55                  Good coffee, food and nice staff.   \n",
       "56  Top notch service from the barista team here. ...   \n",
       "57  Dont go this place, huge shop but only 1 staff...   \n",
       "58  A comfortable coffee shop with lots of natural...   \n",
       "59  Dim light, the environment is not very good. F...   \n",
       "\n",
       "                                           gpt_output  gpt_total_tokens   \n",
       "0   {'Sentiment': 'Negative', 'Emotions': ['Rude',...               337  \\\n",
       "1   {'Sentiment': 'Negative', 'Emotions': ['Hungry...               297   \n",
       "2   {'Sentiment': 'Negative', 'Emotions': ['Disapp...               227   \n",
       "3   {'Sentiment': 'Positive', 'Emotions': ['Happy'...               213   \n",
       "4   {'Sentiment': 'Positive', 'Emotions': ['Thrill...               228   \n",
       "5   {'Sentiment': 'Neutral', 'Emotions': ['Conveni...               230   \n",
       "6   {'Sentiment': 'Neutral', 'Emotions': ['Reasona...               220   \n",
       "7   {'Sentiment': 'Neutral', 'Emotions': ['Cold', ...               206   \n",
       "8   {'Sentiment': 'Negative', 'Emotions': ['Unprof...               213   \n",
       "9   {'Sentiment': 'Positive', 'Emotions': ['Good',...               215   \n",
       "10  {'Sentiment': 'Neutral', 'Emotions': ['Subtle'...               218   \n",
       "11  {'Sentiment': 'Positive', 'Emotions': ['Enjoya...               216   \n",
       "12  {'Sentiment': 'Neutral', 'Emotions': ['Good', ...               209   \n",
       "13  {'Sentiment': 'Neutral', 'Emotions': ['Impatie...               216   \n",
       "14  {'Sentiment': 'Negative', 'Emotions': ['Disapp...               212   \n",
       "15  {'Sentiment': 'Neutral', 'Emotions': ['Good', ...               208   \n",
       "16  {'Sentiment': 'Positive', 'Emotions': ['Satisf...               210   \n",
       "17  {'Sentiment': 'Neutral', 'Emotions': ['Relaxin...               210   \n",
       "18  {'Sentiment': 'Neutral', 'Emotions': ['Conveni...               208   \n",
       "19  {'Sentiment': 'Positive', 'Emotions': ['Adorat...               208   \n",
       "20  {'Sentiment': 'Positive', 'Emotions': ['Favour...               264   \n",
       "21  {'Sentiment': 'Negative', 'Emotions': ['Watery...               226   \n",
       "22  {'Sentiment': 'Negative', 'Emotions': ['Frustr...               214   \n",
       "23  {'Sentiment': 'Neutral', 'Emotions': ['Polite'...               255   \n",
       "24  {'Sentiment': 'Negative', 'Emotions': ['Cold',...               255   \n",
       "25  {'Sentiment': 'Negative', 'Emotions': ['Frustr...               224   \n",
       "26  {'Sentiment': 'Negative', 'Emotions': ['Crowde...               233   \n",
       "27  {'Sentiment': 'Positive', 'Emotions': ['Helpfu...               218   \n",
       "28  {'Sentiment': 'Neutral', 'Emotions': ['Nice', ...               211   \n",
       "29  {'Sentiment': 'Positive', 'Emotions': ['Serene...               218   \n",
       "30  {'Sentiment': 'Neutral', 'Emotions': ['Good', ...               215   \n",
       "31  {'Sentiment': 'Negative', 'Emotions': ['Unplea...               213   \n",
       "32  {'Sentiment': 'Positive', 'Emotions': ['Good',...               210   \n",
       "33  {'Sentiment': 'Positive', 'Emotions': ['Great'...               206   \n",
       "34  {'Sentiment': 'Neutral', 'Emotions': ['Practic...               217   \n",
       "35  {'Sentiment': 'Positive', 'Emotions': ['Small'...               213   \n",
       "36  {'Sentiment': 'Neutral', 'Emotions': ['Cosy', ...               215   \n",
       "37  {'Sentiment': 'Neutral', 'Emotions': ['Global'...               208   \n",
       "38  {'Sentiment': 'Negative', 'Emotions': ['Unplea...               215   \n",
       "39  {'Sentiment': 'Positive', 'Emotions': ['Delici...               213   \n",
       "40  {'Sentiment': 'Positive', 'Emotions': ['Effici...               419   \n",
       "41  {'Sentiment': 'Negative', 'Emotions': ['Quiet'...               223   \n",
       "42  {'Sentiment': 'Positive', 'Emotions': ['Relaxi...               244   \n",
       "43  {'Sentiment': 'Neutral', 'Emotions': ['Nice', ...               248   \n",
       "44  {'Sentiment': 'Positive', 'Emotions': ['Friend...               255   \n",
       "45  {'Sentiment': 'Positive', 'Emotions': ['Friend...               260   \n",
       "46  {'Sentiment': 'Negative', 'Emotions': ['Frustr...               265   \n",
       "47  {'Sentiment': 'Positive', 'Emotions': ['Beauti...               210   \n",
       "48  {'Sentiment': 'Negative', 'Emotions': ['Frustr...               242   \n",
       "49  {'Sentiment': 'Positive', 'Emotions': ['Peacef...               214   \n",
       "50  {'Sentiment': 'Positive', 'Emotions': ['Quick'...               216   \n",
       "51  {'Sentiment': 'Neutral', 'Emotions': ['Limited...               240   \n",
       "52  {'Sentiment': 'Negative', 'Emotions': ['Disgus...               240   \n",
       "53  {'Sentiment': 'Positive', 'Emotions': ['Cozy',...               222   \n",
       "54  {'Sentiment': 'Positive', 'Emotions': ['Decent...               216   \n",
       "55  {'Sentiment': 'Positive', 'Emotions': ['Good',...               208   \n",
       "56  {'Sentiment': 'Positive', 'Emotions': ['Passio...               224   \n",
       "57  {'Sentiment': 'Negative', 'Emotions': ['Frustr...               233   \n",
       "58  {'Sentiment': 'Positive', 'Emotions': ['Comfor...               223   \n",
       "59  {'Sentiment': 'Neutral', 'Emotions': ['Dim', '...               231   \n",
       "\n",
       "   gpt_output_sentiment gpt_output_service   \n",
       "0              Negative           Negative  \\\n",
       "1              Negative           Negative   \n",
       "2              Negative                 NA   \n",
       "3              Positive                 NA   \n",
       "4              Positive                 NA   \n",
       "5               Neutral                 NA   \n",
       "6               Neutral                 NA   \n",
       "7               Neutral                 NA   \n",
       "8              Negative                 NA   \n",
       "9              Positive                 NA   \n",
       "10              Neutral                 NA   \n",
       "11             Positive                 NA   \n",
       "12              Neutral                 NA   \n",
       "13              Neutral                 NA   \n",
       "14             Negative                 NA   \n",
       "15              Neutral                 NA   \n",
       "16             Positive                 NA   \n",
       "17              Neutral                 NA   \n",
       "18              Neutral                 NA   \n",
       "19             Positive                 NA   \n",
       "20             Positive                 NA   \n",
       "21             Negative                 NA   \n",
       "22             Negative                 NA   \n",
       "23              Neutral                 NA   \n",
       "24             Negative                 NA   \n",
       "25             Negative                 NA   \n",
       "26             Negative                 NA   \n",
       "27             Positive           Positive   \n",
       "28              Neutral           Negative   \n",
       "29             Positive                 NA   \n",
       "30              Neutral                 NA   \n",
       "31             Negative                 NA   \n",
       "32             Positive                 NA   \n",
       "33             Positive                 NA   \n",
       "34              Neutral                 NA   \n",
       "35             Positive           Positive   \n",
       "36              Neutral                 NA   \n",
       "37              Neutral                 NA   \n",
       "38             Negative                 NA   \n",
       "39             Positive                 NA   \n",
       "40             Positive                 NA   \n",
       "41             Negative           Negative   \n",
       "42             Positive                 NA   \n",
       "43              Neutral                 NA   \n",
       "44             Positive           Positive   \n",
       "45             Positive                 NA   \n",
       "46             Negative                 NA   \n",
       "47             Positive                 NA   \n",
       "48             Negative                 NA   \n",
       "49             Positive                 NA   \n",
       "50             Positive                 NA   \n",
       "51              Neutral                 NA   \n",
       "52             Negative                 NA   \n",
       "53             Positive                 NA   \n",
       "54             Positive                 NA   \n",
       "55             Positive                 NA   \n",
       "56             Positive           Positive   \n",
       "57             Negative           Negative   \n",
       "58             Positive                 NA   \n",
       "59              Neutral                 NA   \n",
       "\n",
       "                              gpt_output_emotions  \n",
       "0                    [Rude, Doubtful, Frustrated]  \n",
       "1                 [Hungry, Disappointed, Ignored]  \n",
       "2            [Disappointing, Frustrated, Unhappy]  \n",
       "3                       [Happy, Excited, Pleased]  \n",
       "4                  [Thrilled, Pleased, Impressed]  \n",
       "5             [Convenient, Routine, Unremarkable]  \n",
       "6                  [Reasonable, Small, Available]  \n",
       "7                               [Cold, Less, Icy]  \n",
       "8       [Unprofessional, Uncaring, Disappointing]  \n",
       "9                   [Good, Enjoyable, Satisfying]  \n",
       "10                   [Subtle, Quiet, Picturesque]  \n",
       "11               [Enjoyable, Popular, Discounted]  \n",
       "12                           [Good, Ordinary, NA]  \n",
       "13               [Impatient, Frustrated, Annoyed]  \n",
       "14  [Disappointing, Unsatisfactory, Unimpressive]  \n",
       "15                 [Good, Affordable, Convenient]  \n",
       "16           [Satisfactory, Consistent, Pleasant]  \n",
       "17             [Relaxing, Refreshing, Satisfying]  \n",
       "18            [Convenient, Efficient, Impersonal]  \n",
       "19            [Adoration, Affectionate, Fondness]  \n",
       "20               [Favourable, Wishful, Satisfied]  \n",
       "21        [Watery, Disappointing, Unsatisfactory]  \n",
       "22               [Frustrated, Impatient, Annoyed]  \n",
       "23                         [Polite, Warm, Better]  \n",
       "24                        [Cold, Old, Infrequent]  \n",
       "25            [Frustrated, Annoyed, Disappointed]  \n",
       "26                        [Crowded, Small, Dirty]  \n",
       "27                   [Helpful, Prompt, Memorable]  \n",
       "28                         [Nice, Great, Neutral]  \n",
       "29                       [Serene, Tasteful, Nice]  \n",
       "30                            [Good, Small, Cold]  \n",
       "31                  [Unpleasant, Quiet, Reserved]  \n",
       "32                            [Good, Nice, Short]  \n",
       "33                        [Great, Usual, Service]  \n",
       "34                    [Practical, Quiet, Chaotic]  \n",
       "35                       [Small, Usual, Friendly]  \n",
       "36                      [Cosy, Soft, Unheardable]  \n",
       "37                   [Global, Successful, Chosen]  \n",
       "38        [Unpleasant, Overpriced, Disappointing]  \n",
       "39               [Delicious, Amazing, Satisfying]  \n",
       "40                    [Efficient, Enjoyed, Clean]  \n",
       "41                    [Quiet, Nice, Unacceptable]  \n",
       "42                [Relaxing, Comforting, Special]  \n",
       "43                     [Nice, Average, Important]  \n",
       "44              [Friendly, Efficient, Hospitable]  \n",
       "45                [Friendly, Efficient, Relaxing]  \n",
       "46         [Frustrated, Disgusted, Uncomfortable]  \n",
       "47                   [Beautiful, Amazing, Lovely]  \n",
       "48           [Frustrated, Disappointed, Confused]  \n",
       "49                    [Peaceful, Enjoyable, Good]  \n",
       "50                       [Quick, Efficient, High]  \n",
       "51              [Limited, Satisfied, Indifferent]  \n",
       "52          [Disgusting, Unsatisfied, Unpleasant]  \n",
       "53                         [Cozy, Signature, Top]  \n",
       "54                          [Decent, Good, Quick]  \n",
       "55                             [Good, Nice, Food]  \n",
       "56          [Passionate, Proactive, Professional]  \n",
       "57          [Frustrated, Impatient, Disappointed]  \n",
       "58                [Comfortable, Enjoyable, Light]  \n",
       "59                      [Dim, Occupied, Standard]  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "99da5345",
   "metadata": {},
   "source": [
    "### Histogram plot of review sentiment"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "6a4da599",
   "metadata": {},
   "outputs": [
    {
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         "legendgroup": "Negative",
         "marker": {
          "color": "rgb(103,0,31)",
          "line": {
           "color": "black",
           "width": 0.4
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         },
         "name": "Negative",
         "offsetgroup": "Negative",
         "orientation": "v",
         "showlegend": true,
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         "xaxis": "x",
         "yaxis": "y"
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         "alignmentgroup": "True",
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         "legendgroup": "Negative",
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         "showlegend": false,
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         "xaxis": "x2",
         "yaxis": "y2"
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         "alignmentgroup": "True",
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     },
     "metadata": {},
     "output_type": "display_data"
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   ],
   "source": [
    "custom_order = [\"Negative\", \"Neutral\", \"Positive\"]\n",
    "color_list= ['rgb(103,0,31)','rgb(247,247,247)','rgb(5,48,97)']\n",
    "color_map = {key:val for (key, val) in zip(custom_order,color_list)}\n",
    "\n",
    "\n",
    "fig = px.histogram(data, x=\"gpt_output_sentiment\", \n",
    "                   color=\"gpt_output_sentiment\", \n",
    "                   color_discrete_map = color_map,\n",
    "\n",
    "                   facet_col=\"location_name\",\n",
    "                   facet_col_spacing =0.01,\n",
    "                   labels={\"count\":\"Count\", \n",
    "                     \"gpt_output_sentiment\":\"Review Sentiment\",\n",
    "                    \"location_name\": \"Location\"},\n",
    "                   title = \"Histogram Chart of Review Sentiment\"                  \n",
    "                  )\n",
    "\n",
    "fig.update_traces(marker_line_color='black', marker_line_width=0.4)\n",
    "fig.update_layout(showlegend=True,\n",
    "                  xaxis={'categoryorder': 'array', 'categoryarray': custom_order},\n",
    "                  legend=dict(title=\"Review Ratings:\", orientation='h', yanchor='top',y=1.15,xanchor='center',x=0.5, bordercolor=\"#B0C4DE\", borderwidth=1),\n",
    "                  title=dict(y=0.95, x=0.5, xanchor='center', yanchor='top'),\n",
    "                 )\n",
    "fig.write_image(\"1hist_overview.jpeg\", width=800, height=500)\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a2d913ab",
   "metadata": {},
   "source": [
    "### Histogram plot of customer service standard"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "7fe53f96",
   "metadata": {},
   "outputs": [
    {
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true}                    ).then(function(){\n",
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       "            Plotly.purge(gd);\n",
       "            observer.disconnect();\n",
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       "\n",
       "// Listen for the removal of the full notebook cells\n",
       "var notebookContainer = gd.closest('#notebook-container');\n",
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     },
     "metadata": {},
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   ],
   "source": [
    "custom_order = [\"Negative\", \"Positive\", \"NA\"]\n",
    "color_list= ['rgb(103,0,31)', 'rgb(5,48,97)', \"grey\"]\n",
    "color_map = {key:val for (key, val) in zip(custom_order,color_list)}\n",
    "\n",
    "\n",
    "fig = px.histogram(data, x=\"gpt_output_service\", \n",
    "                   color=\"gpt_output_service\", \n",
    "                   color_discrete_map = color_map,\n",
    "\n",
    "                   facet_col=\"location_name\",\n",
    "                   facet_col_spacing =0.01,\n",
    "                   labels={\"count\":\"Count\", \n",
    "                     \"gpt_output_service\":\"Customer Service\",\n",
    "                    \"location_name\": \"Location\"},\n",
    "                   title = \"Histogram Chart of Customer Service Standard\"                  \n",
    "                  )\n",
    "\n",
    "fig.update_traces(marker_line_color='black', marker_line_width=0.4)\n",
    "fig.update_layout(showlegend=True,\n",
    "                  xaxis={'categoryorder': 'array', 'categoryarray': custom_order},\n",
    "                  legend=dict(title=\"Review Ratings:\", orientation='h', yanchor='top',y=1.15,xanchor='center',x=0.5, bordercolor=\"#B0C4DE\", borderwidth=1),\n",
    "                  title=dict(y=0.95, x=0.5, xanchor='center', yanchor='top'),\n",
    "                 )\n",
    "fig.write_image(\"2hist_overview.jpeg\", width=800, height=500)\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "19bd014a",
   "metadata": {},
   "source": [
    "### Save the data processed and extracted into csv file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "481d16a9",
   "metadata": {},
   "outputs": [],
   "source": [
    "data.to_csv(\"googlemaps_review_detail.csv\", index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b661be56",
   "metadata": {},
   "source": [
    "### Convert the emotions data to be plotted on Tableau"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "e60073d3",
   "metadata": {},
   "outputs": [],
   "source": [
    "emotion_list = []\n",
    "location_list = []\n",
    "for loc_id in data[\"location_name\"].unique().tolist():\n",
    "    # extract emotions one at a time by its location name\n",
    "    current_data = data[data[\"location_name\"]==loc_id]\n",
    "    # combine all emotions into one list\n",
    "    for i in current_data[\"gpt_output_emotions\"]:\n",
    "        # combine emotion words\n",
    "        emotion_list += i\n",
    "        # build a list based on location name\n",
    "        location_list += [loc_id]*len(i)\n",
    "\n",
    "# Save emotion data and location name to be used on Tableau\n",
    "collect_df = pd.DataFrame(data = {\"location_name\":location_list ,\"emotions\":emotion_list})\n",
    "collect_df.to_csv(\"googlemaps_tableau.csv\", index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "469d56a8",
   "metadata": {},
   "outputs": [],
   "source": []
  },
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   "cell_type": "code",
   "execution_count": null,
   "id": "fc386eb1",
   "metadata": {},
   "outputs": [],
   "source": []
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   "cell_type": "code",
   "execution_count": null,
   "id": "58e28e84",
   "metadata": {},
   "outputs": [],
   "source": []
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  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cf0e4fb7",
   "metadata": {},
   "outputs": [],
   "source": []
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