리뷰분류.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/dmscornjs/Hotelreview/blob/main/%EB%A6%AC%EB%B7%B0%EB%B6%84%EB%A5%98.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ytHz6gH_1LZC",
        "outputId": "1a99654e-0f86-4feb-9035-d6cba985eaca"
      },
      "source": [
        "```\n",
        "!pip install git+https://github.com/ssut/py-hanspell.git\n",
        "!pip install git+https://github.com/haven-jeon/PyKoSpacing.git\n",
        "!pip install konlpy\n",
        "!pip install wordcloud\n",
        "!pip install gensim\n",
        "```\n",
        "\n",
        "\n",
        "*   클러스터링\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "코랩 런타임 끊기지 않고 하는 법\n",
        "\n",
        "\n",
        "\n",
        "```\n",
        "function ClickConnect(){ console.log(\"Working\"); document.querySelector(\"colab-toolbar-button\").click() }setInterval(ClickConnect, 1800000)\n",
        "\n",
        "```\n",
        "\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "id": "R1D7FOPkqMAg"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 리뷰 분류"
      ],
      "metadata": {
        "id": "uY4y8QdZBgpj"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "metadata": {
        "id": "R-6c1PlNL0N8",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "0dea51f4-43fe-4bc4-bdc6-52b055ecd66c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "dkV-xdrgQwzM",
        "outputId": "172ba255-2cca-45c6-cd18-9326fe33a7cc"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Collecting konlpy\n",
            "  Downloading konlpy-0.6.0-py2.py3-none-any.whl (19.4 MB)\n",
            "\u001b[K     |████████████████████████████████| 19.4 MB 1.4 MB/s \n",
            "\u001b[?25hCollecting JPype1>=0.7.0\n",
            "  Downloading JPype1-1.4.0-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.whl (453 kB)\n",
            "\u001b[K     |████████████████████████████████| 453 kB 58.7 MB/s \n",
            "\u001b[?25hRequirement already satisfied: lxml>=4.1.0 in /usr/local/lib/python3.7/dist-packages (from konlpy) (4.2.6)\n",
            "Requirement already satisfied: numpy>=1.6 in /usr/local/lib/python3.7/dist-packages (from konlpy) (1.21.6)\n",
            "Requirement already satisfied: typing-extensions in /usr/local/lib/python3.7/dist-packages (from JPype1>=0.7.0->konlpy) (4.2.0)\n",
            "Installing collected packages: JPype1, konlpy\n",
            "Successfully installed JPype1-1.4.0 konlpy-0.6.0\n",
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Requirement already satisfied: gensim in /usr/local/lib/python3.7/dist-packages (3.6.0)\n",
            "Requirement already satisfied: smart-open>=1.2.1 in /usr/local/lib/python3.7/dist-packages (from gensim) (6.0.0)\n",
            "Requirement already satisfied: scipy>=0.18.1 in /usr/local/lib/python3.7/dist-packages (from gensim) (1.4.1)\n",
            "Requirement already satisfied: numpy>=1.11.3 in /usr/local/lib/python3.7/dist-packages (from gensim) (1.21.6)\n",
            "Requirement already satisfied: six>=1.5.0 in /usr/local/lib/python3.7/dist-packages (from gensim) (1.15.0)\n"
          ]
        }
      ],
      "source": [
        "!pip install konlpy\n",
        "!pip install gensim"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "yUsyjoOh0QzB"
      },
      "outputs": [],
      "source": [
        "import pandas as pd \n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "%matplotlib inline \n",
        "import sys\n",
        "from konlpy.tag import Okt\n",
        "from collections import Counter\n",
        "from wordcloud import WordCloud\n",
        "from sklearn.model_selection import train_test_split\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "xqAn-bKaOF4t",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 363
        },
        "outputId": "031915a3-6e80-4dcf-85fc-6b4a04bc5d09"
      },
      "outputs": [
        {
          "output_type": "error",
          "ename": "FileNotFoundError",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mFileNotFoundError\u001b[0m                         Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-4-dfe2c54d1ab2>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0msent\u001b[0m\u001b[0;34m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread_csv\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"/content/drive/MyDrive/호텔감성분석확률.csv\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0mtop\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread_csv\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"/content/drive/MyDrive/야놀자명사100.csv\"\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mencoding\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'utf-8'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mdelimiter\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"\\t\"\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mheader\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mNone\u001b[0m \u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 4\u001b[0;31m \u001b[0mttt\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread_csv\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"위치.txt\"\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mheader\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/pandas/util/_decorators.py\u001b[0m in \u001b[0;36mwrapper\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m    309\u001b[0m                     \u001b[0mstacklevel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mstacklevel\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    310\u001b[0m                 )\n\u001b[0;32m--> 311\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    312\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    313\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mwrapper\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/pandas/io/parsers/readers.py\u001b[0m in \u001b[0;36mread_csv\u001b[0;34m(filepath_or_buffer, sep, delimiter, header, names, index_col, usecols, squeeze, prefix, mangle_dupe_cols, dtype, engine, converters, true_values, false_values, skipinitialspace, skiprows, skipfooter, nrows, na_values, keep_default_na, na_filter, verbose, skip_blank_lines, parse_dates, infer_datetime_format, keep_date_col, date_parser, dayfirst, cache_dates, iterator, chunksize, compression, thousands, decimal, lineterminator, quotechar, quoting, doublequote, escapechar, comment, encoding, encoding_errors, dialect, error_bad_lines, warn_bad_lines, on_bad_lines, delim_whitespace, low_memory, memory_map, float_precision, storage_options)\u001b[0m\n\u001b[1;32m    584\u001b[0m     \u001b[0mkwds\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mupdate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkwds_defaults\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    585\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 586\u001b[0;31m     \u001b[0;32mreturn\u001b[0m \u001b[0m_read\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilepath_or_buffer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    587\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    588\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/pandas/io/parsers/readers.py\u001b[0m in \u001b[0;36m_read\u001b[0;34m(filepath_or_buffer, kwds)\u001b[0m\n\u001b[1;32m    480\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    481\u001b[0m     \u001b[0;31m# Create the parser.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 482\u001b[0;31m     \u001b[0mparser\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mTextFileReader\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilepath_or_buffer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    483\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    484\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mchunksize\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0miterator\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/pandas/io/parsers/readers.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, f, engine, **kwds)\u001b[0m\n\u001b[1;32m    809\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0moptions\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"has_index_names\"\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mkwds\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"has_index_names\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    810\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 811\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_make_engine\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mengine\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    812\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    813\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mclose\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/pandas/io/parsers/readers.py\u001b[0m in \u001b[0;36m_make_engine\u001b[0;34m(self, engine)\u001b[0m\n\u001b[1;32m   1038\u001b[0m             )\n\u001b[1;32m   1039\u001b[0m         \u001b[0;31m# error: Too many arguments for \"ParserBase\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1040\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mmapping\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mengine\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0moptions\u001b[0m\u001b[0;34m)\u001b[0m  \u001b[0;31m# type: ignore[call-arg]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1041\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1042\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_failover_to_python\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/pandas/io/parsers/c_parser_wrapper.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, src, **kwds)\u001b[0m\n\u001b[1;32m     49\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     50\u001b[0m         \u001b[0;31m# open handles\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 51\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_open_handles\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msrc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     52\u001b[0m         \u001b[0;32massert\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mhandles\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     53\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/pandas/io/parsers/base_parser.py\u001b[0m in \u001b[0;36m_open_handles\u001b[0;34m(self, src, kwds)\u001b[0m\n\u001b[1;32m    227\u001b[0m             \u001b[0mmemory_map\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mkwds\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"memory_map\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;32mFalse\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    228\u001b[0m             \u001b[0mstorage_options\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mkwds\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"storage_options\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 229\u001b[0;31m             \u001b[0merrors\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mkwds\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"encoding_errors\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"strict\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    230\u001b[0m         )\n\u001b[1;32m    231\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/pandas/io/common.py\u001b[0m in \u001b[0;36mget_handle\u001b[0;34m(path_or_buf, mode, encoding, compression, memory_map, is_text, errors, storage_options)\u001b[0m\n\u001b[1;32m    705\u001b[0m                 \u001b[0mencoding\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mioargs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mencoding\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    706\u001b[0m                 \u001b[0merrors\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0merrors\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 707\u001b[0;31m                 \u001b[0mnewline\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"\"\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    708\u001b[0m             )\n\u001b[1;32m    709\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: '위치.txt'"
          ]
        }
      ],
      "source": [
        "df= pd.read_csv(\"/content/drive/MyDrive/최종합친호텔리뷰.csv\")\n",
        "sent= pd.read_csv(\"/content/drive/MyDrive/호텔감성분석확률.csv\")\n",
        "top = pd.read_csv(\"/content/drive/MyDrive/야놀자명사100.csv\",encoding='utf-8',delimiter=\"\\t\",header = None )\n",
        "ttt = pd.read_csv(\"위치.txt\",header = None)"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "in_file = open(\"stations.txt\",'rt', encoding='UTF8')\n",
        "stations = []\n",
        "for line in in_file:\n",
        "    data = line.strip().split(\" - \")\n",
        "    stations+=data"
      ],
      "metadata": {
        "id": "WiEkYw5gLp8K"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df_sent = sent.loc[:,['sentiment','sent_proba']] "
      ],
      "metadata": {
        "id": "nxW_a6VReWFl"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "top = top[:100]\n",
        "top.columns=[\"n\", \"c\", \"t\"]"
      ],
      "metadata": {
        "id": "E-4RwxzkBXLI"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "top.t.value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ctpG23tAXVte",
        "outputId": "7ed5ca70-983d-4d0e-f30b-5cc478053de5"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0    36\n",
              "1    30\n",
              "2    13\n",
              "5    11\n",
              "3     7\n",
              "4     3\n",
              "Name: t, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 89
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "n1 = list(top.n.loc[top.t==1])\n",
        "n2 = list(top.n.loc[top.t==2])\n",
        "n3 = list(top.n.loc[top.t==3])\n",
        "n4 = list(top.n.loc[top.t==4])"
      ],
      "metadata": {
        "id": "hvE_ouQAQY4e"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "lt = ttt[0].values.tolist()"
      ],
      "metadata": {
        "id": "Q2hUgVgp1fuM"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "n3+=lt\n",
        "n3+=stations"
      ],
      "metadata": {
        "id": "DYyHcGii5KTZ"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "n3 = list(set(n3))"
      ],
      "metadata": {
        "id": "NJKVb2Kk5HTE"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "n3"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Z7WynUiu6DUp",
        "outputId": "b3f0a8cf-c260-4c20-88f9-b74a68d83093"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[' 녹번',\n",
              " ' 수리산',\n",
              " '의정부중앙',\n",
              " ' 신정네거리',\n",
              " ' 신촌',\n",
              " ' 상갈',\n",
              " '석남',\n",
              " '온양온천',\n",
              " ' 금호',\n",
              " ' 캠퍼스타운',\n",
              " '화계',\n",
              " ' 양수',\n",
              " '구산',\n",
              " ' 우장산',\n",
              " '테크노파크',\n",
              " '검단사거리',\n",
              " ' 석촌',\n",
              " ' 산성',\n",
              " '동묘앞',\n",
              " ' 홍제',\n",
              " '인천시청',\n",
              " ' 을지로입구',\n",
              " '두정',\n",
              " '시장',\n",
              " '여의도',\n",
              " '남대문',\n",
              " '가까워',\n",
              " ' 구로디지털단지',\n",
              " ' 인천대입구',\n",
              " ' 신원',\n",
              " '화곡',\n",
              " '솔밭공원',\n",
              " '이동',\n",
              " ' 녹양',\n",
              " '구로',\n",
              " ' 학여울',\n",
              " ' 상봉',\n",
              " '중앙보훈병원',\n",
              " '연수',\n",
              " '동대문',\n",
              " '온수',\n",
              " ' 범계',\n",
              " ' 관악',\n",
              " ' 왕십리',\n",
              " '효창공원앞',\n",
              " '상도',\n",
              " '광화문',\n",
              " ' 용산',\n",
              " '이태원',\n",
              " ' 삼각지',\n",
              " ' 죽전',\n",
              " ' 아신',\n",
              " '동백',\n",
              " ' 송정',\n",
              " '광운대',\n",
              " '불광',\n",
              " '신대방삼거리',\n",
              " '마두',\n",
              " ' 금촌',\n",
              " '신창',\n",
              " ' 마포',\n",
              " '남영',\n",
              " '올림픽공원',\n",
              " ' 금곡',\n",
              " ' 정왕',\n",
              " ' 보문',\n",
              " '인천공항2터미널',\n",
              " '화전',\n",
              " '당산',\n",
              " ' 잠실',\n",
              " ' 일원',\n",
              " '교통',\n",
              " ' 방학',\n",
              " '가깝',\n",
              " '부천시청',\n",
              " '지행',\n",
              " '청구',\n",
              " '백양리',\n",
              " ' 서초',\n",
              " ' 창동',\n",
              " ' 중랑',\n",
              " '광나루',\n",
              " '김포공항',\n",
              " '동두천',\n",
              " ' 오류동',\n",
              " ' 계양',\n",
              " '둔촌오륜',\n",
              " '부천종합운동장',\n",
              " ' 경찰병원',\n",
              " ' 부평구청',\n",
              " ' 청명',\n",
              " '위치',\n",
              " '용문',\n",
              " ' 반포',\n",
              " ' 구성',\n",
              " ' 역삼',\n",
              " '한대앞',\n",
              " ' 대치',\n",
              " ' 양재시민의숲',\n",
              " '보평',\n",
              " '신촌',\n",
              " '영등포시장',\n",
              " '운연',\n",
              " ' 가양',\n",
              " '거리',\n",
              " ' 세류',\n",
              " ' 석계',\n",
              " '양평',\n",
              " ' 매봉',\n",
              " ' 단대오거리',\n",
              " ' 대성리',\n",
              " ' 중화',\n",
              " '석촌고분',\n",
              " '검단오류',\n",
              " ' 문산',\n",
              " ' 신금호',\n",
              " ' 삼산체육관',\n",
              " ' 중동',\n",
              " '종로3가',\n",
              " ' 까치울',\n",
              " '석천사거리',\n",
              " '서부여성회관',\n",
              " '행당',\n",
              " ' 쌍용',\n",
              " '남동구청',\n",
              " ' 애오개',\n",
              " '서정리',\n",
              " ' 김유정',\n",
              " '성수',\n",
              " '대흥',\n",
              " ' 을지로3가',\n",
              " ' 종로3가',\n",
              " ' 복정',\n",
              " '서빙고',\n",
              " '외대앞',\n",
              " ' 인천논현',\n",
              " ' 망포',\n",
              " ' 새절',\n",
              " ' 방배',\n",
              " '석바위시장',\n",
              " '춘의',\n",
              " '운동장.송담대',\n",
              " ' 흑석',\n",
              " '오이도',\n",
              " '길음',\n",
              " '이촌',\n",
              " ' 수진',\n",
              " ' 동두천중앙',\n",
              " '코엑스',\n",
              " ' 국회의사당',\n",
              " ' 마포구청',\n",
              " ' 개봉',\n",
              " ' 송파',\n",
              " ' 대곡',\n",
              " '간석오거리',\n",
              " '상현',\n",
              " '초월',\n",
              " ' 신창',\n",
              " '인천대공원',\n",
              " ' 효창공원앞',\n",
              " ' 강동구청',\n",
              " ' 공항화물청사',\n",
              " '사릉',\n",
              " ' 안양',\n",
              " '강촌',\n",
              " ' 군자',\n",
              " '사평',\n",
              " '부평구청',\n",
              " ' 남성',\n",
              " '중랑',\n",
              " '아산',\n",
              " ' 망우',\n",
              " '신도림',\n",
              " '상봉',\n",
              " '신둔도예촌',\n",
              " ' 정부과천청사',\n",
              " '수서',\n",
              " ' 서울역',\n",
              " '보라매',\n",
              " ' 선릉',\n",
              " ' 상일동',\n",
              " '경마공원',\n",
              " '성환',\n",
              " '삼양사거리',\n",
              " '고진',\n",
              " '노들',\n",
              " '범골',\n",
              " ' 길동',\n",
              " '응암',\n",
              " '과천',\n",
              " ' 능곡',\n",
              " ' 화랑대',\n",
              " ' 금릉',\n",
              " ' 공덕',\n",
              " '어정',\n",
              " ' 운정',\n",
              " '혜화',\n",
              " ' 가능',\n",
              " '양재',\n",
              " ' 오리',\n",
              " ' 신길온천',\n",
              " '기흥',\n",
              " ' 약수',\n",
              " ' 가산디지털단지',\n",
              " '대청',\n",
              " '솔샘',\n",
              " ' 구리',\n",
              " '문래',\n",
              " ' 공릉',\n",
              " '충정로',\n",
              " '연신내',\n",
              " '삼성',\n",
              " ' 성환',\n",
              " '도원',\n",
              " '수원',\n",
              " ' 금정',\n",
              " '가까워서',\n",
              " ' 가평',\n",
              " ' 노원',\n",
              " ' 선정릉',\n",
              " ' 양정',\n",
              " ' 마석',\n",
              " '시청.용인대',\n",
              " '대림',\n",
              " '출구',\n",
              " ' 서동탄',\n",
              " '용답',\n",
              " ' 석수',\n",
              " ' 명학',\n",
              " ' 검암',\n",
              " '매탄권선',\n",
              " '팔당',\n",
              " ' 신갈',\n",
              " ' 덕정',\n",
              " ' 개포동',\n",
              " ' 아산',\n",
              " '수원시청',\n",
              " ' 구일',\n",
              " ' 녹천',\n",
              " '세마',\n",
              " '가재울',\n",
              " ' 기흥',\n",
              " ' 안산',\n",
              " ' 동암',\n",
              " '모란',\n",
              " '호구포',\n",
              " '중곡',\n",
              " ' 부평시장',\n",
              " '삼가',\n",
              " '방화',\n",
              " ' 양평',\n",
              " ' 영등포구청',\n",
              " '청량리',\n",
              " '광교중앙',\n",
              " ' 상동',\n",
              " ' 아차산',\n",
              " '경전철의정부',\n",
              " ' 군포',\n",
              " '서대문',\n",
              " '군자',\n",
              " ' 동작',\n",
              " ' 정발산',\n",
              " ' 경원대',\n",
              " '언주',\n",
              " '익선동',\n",
              " ' 한남',\n",
              " '공덕',\n",
              " '장한평',\n",
              " '대야미',\n",
              " ' 신논현',\n",
              " '전망',\n",
              " '주변',\n",
              " ' 아현',\n",
              " '마장',\n",
              " ' 이대',\n",
              " '응봉',\n",
              " ' 목동',\n",
              " '일산',\n",
              " ' 백운',\n",
              " ' 신당',\n",
              " '둔전',\n",
              " '천안',\n",
              " ' 몽촌토성',\n",
              " ' 무악재',\n",
              " ' 증산',\n",
              " '이랑',\n",
              " ' 원당',\n",
              " '마전',\n",
              " '동천',\n",
              " '진위',\n",
              " ' 주엽',\n",
              " '종합운동장',\n",
              " '종로5가',\n",
              " ' 수색',\n",
              " '서울역',\n",
              " '신대방',\n",
              " ' 합정',\n",
              " '양천향교',\n",
              " '새말',\n",
              " '한성백제',\n",
              " '신촌(경의중앙선)',\n",
              " ' 상천',\n",
              " ' 병점',\n",
              " ' 성신여대입구',\n",
              " '강변',\n",
              " '월곡',\n",
              " ' 봉은사',\n",
              " ' 운길산',\n",
              " ' 영등포',\n",
              " '도림천',\n",
              " ' 진위',\n",
              " '가정중앙시장',\n",
              " '용두',\n",
              " '양천구청',\n",
              " '만수',\n",
              " '장암',\n",
              " ' 양재',\n",
              " ' 디지털미디어시티',\n",
              " '김량장',\n",
              " ' 태릉입구',\n",
              " '용마산',\n",
              " ' 주안',\n",
              " '샛강',\n",
              " ' 송도',\n",
              " '성신여대입구',\n",
              " ' 온양온천',\n",
              " ' 신천',\n",
              " '신반포',\n",
              " '성복',\n",
              " '접근성',\n",
              " '공항',\n",
              " ' 세마',\n",
              " ' 당정',\n",
              " ' 구의',\n",
              " ' 남태령',\n",
              " '선유도',\n",
              " ' 화서',\n",
              " ' 안암',\n",
              " ' 여의나루',\n",
              " '의정부시청',\n",
              " ' 사당',\n",
              " '신설동',\n",
              " '왕길',\n",
              " ' 광흥창',\n",
              " '태평',\n",
              " '마들',\n",
              " '평택',\n",
              " '검암',\n",
              " '고속터미널',\n",
              " ' 금천구청',\n",
              " ' 신연수',\n",
              " ' 탄현',\n",
              " '숙대입구',\n",
              " ' 천안',\n",
              " '송탄',\n",
              " ' 사가정',\n",
              " ' 서정리',\n",
              " ' 의왕',\n",
              " '센트럴파크',\n",
              " ' 가좌',\n",
              " ' 망월사',\n",
              " ' 까치산',\n",
              " ' 개롱',\n",
              " ' 삼송',\n",
              " ' 임학',\n",
              " ' 성수',\n",
              " '철산',\n",
              " '경기광주',\n",
              " ' 서강',\n",
              " '아시아드경기장',\n",
              " ' 홍대입구',\n",
              " ' 청구',\n",
              " '성역',\n",
              " ' 도화',\n",
              " ' 월드컵경기장',\n",
              " ' 숭실대입구',\n",
              " '가정',\n",
              " '신풍',\n",
              " ' 도농',\n",
              " ' 의정부',\n",
              " '대모산입구',\n",
              " ' 운서',\n",
              " ' 별내역',\n",
              " ' 상왕십리',\n",
              " ' 구반포',\n",
              " ' 송탄',\n",
              " '4·19민주묘지',\n",
              " '삼양',\n",
              " ' 오목교',\n",
              " '독정',\n",
              " ' 명일',\n",
              " '먹거리',\n",
              " '계양',\n",
              " ' 먹골',\n",
              " '동대문역사문화공원',\n",
              " '강남대',\n",
              " '지하철역',\n",
              " '선릉',\n",
              " '도봉',\n",
              " '교대',\n",
              " ' 가락시장',\n",
              " ' 마곡',\n",
              " '국제업무지구',\n",
              " '광교',\n",
              " '지제',\n",
              " ' 도봉산',\n",
              " ' 개화산',\n",
              " '예술회관',\n",
              " '강남',\n",
              " '쌍용',\n",
              " '이천',\n",
              " ' 어린이대공원',\n",
              " ' 종합운동장',\n",
              " '동춘',\n",
              " '주안국가산단',\n",
              " '신답',\n",
              " '을지로4가',\n",
              " ' 쌍문',\n",
              " ' 답십리',\n",
              " '도봉산',\n",
              " '압구정로데오',\n",
              " '오산대',\n",
              " ' 보정',\n",
              " ' 청계산입구',\n",
              " ' 부개',\n",
              " ' 동묘앞',\n",
              " '반월',\n",
              " ' 양원',\n",
              " ' 신림',\n",
              " '을지로3가',\n",
              " ' 평내호평',\n",
              " ' 문정',\n",
              " ' 평택',\n",
              " '암사',\n",
              " ' 고속터미널',\n",
              " '북한산우이',\n",
              " ' 신길',\n",
              " ' 백석',\n",
              " '중앙',\n",
              " '발곡',\n",
              " '송산',\n",
              " ' 부천',\n",
              " ' 장지',\n",
              " ' 충정로',\n",
              " '지식정보단지',\n",
              " ' 신중동',\n",
              " ' 강동',\n",
              " ' 공항시장',\n",
              " '당고개',\n",
              " ' 상수',\n",
              " ' 오산대',\n",
              " '완정',\n",
              " '마곡나루',\n",
              " ' 이수',\n",
              " '곤제',\n",
              " ' 증미',\n",
              " ' 을지로4가',\n",
              " '버스',\n",
              " ' 천호',\n",
              " ' 구파발',\n",
              " '상계',\n",
              " ' 강남',\n",
              " ' 논현',\n",
              " ' 광명',\n",
              " ' 한티',\n",
              " '까치산',\n",
              " ' 강남구청',\n",
              " '둔촌동',\n",
              " '한강진',\n",
              " ' 오빈',\n",
              " '천왕',\n",
              " '서구청',\n",
              " '청담',\n",
              " '인천터미널',\n",
              " '서울',\n",
              " '삼각지',\n",
              " ' 송내',\n",
              " '신당',\n",
              " '삼전',\n",
              " ' 망원',\n",
              " '한양대',\n",
              " ' 정자',\n",
              " ' 압구정',\n",
              " ' 야탑',\n",
              " ' 회기',\n",
              " '세종대왕릉',\n",
              " '방이',\n",
              " '신흥',\n",
              " ' 산본',\n",
              " '창신',\n",
              " ' 파주',\n",
              " ' 굽은다리',\n",
              " '경기도청북부청사',\n",
              " ' 거여',\n",
              " '서울대입구',\n",
              " '춘천',\n",
              " ' 도곡',\n",
              " '대방',\n",
              " '개화',\n",
              " ' 봉명',\n",
              " ' 뚝섬유원지',\n",
              " '신정',\n",
              " ' 모란',\n",
              " ' 교대',\n",
              " '가오리',\n",
              " ' 풍산',\n",
              " ' 성균관대',\n",
              " ' 장승배기',\n",
              " ' 신도림',\n",
              " '편의',\n",
              " ' 상월곡',\n",
              " ' 동막',\n",
              " '\\ufeff소요산',\n",
              " '안국',\n",
              " ' 영통',\n",
              " ' 동대문',\n",
              " ' 덕소',\n",
              " ' 시청',\n",
              " '초당',\n",
              " '인천',\n",
              " '행신',\n",
              " ' 대림',\n",
              " ' 백마',\n",
              " '대화',\n",
              " ' 갈매',\n",
              " ' 인덕원',\n",
              " '선바위',\n",
              " ' 화정',\n",
              " ' 하계',\n",
              " '시민공원',\n",
              " '정릉',\n",
              " '충무로',\n",
              " '보문',\n",
              " ' 미아',\n",
              " '버티고개',\n",
              " '봉천',\n",
              " '지하철',\n",
              " ' 청량리',\n",
              " '신길',\n",
              " '효자',\n",
              " ' 남부터미널',\n",
              " ' 월계',\n",
              " ' 면목',\n",
              " ' 회현',\n",
              " ' 수서',\n",
              " ' 발산',\n",
              " ' 역촌',\n",
              " ' 갈산',\n",
              " '잠실나루',\n",
              " ' 국수',\n",
              " '천호',\n",
              " ' 학동',\n",
              " '수지구청',\n",
              " '인천가좌',\n",
              " '신용산',\n",
              " ' 광명사거리',\n",
              " ' 등촌',\n",
              " ' 소래포구',\n",
              " '신사',\n",
              " '봉명',\n",
              " ' 불광',\n",
              " '청평',\n",
              " ' 염창',\n",
              " ' 귤현',\n",
              " '모래내시장',\n",
              " '동오',\n",
              " '명지대',\n",
              " '명동',\n",
              " '봉화산',\n",
              " '보산',\n",
              " ' 독바위',\n",
              " ' 중계',\n",
              " '검바위',\n",
              " ' 고덕',\n",
              " '삼동',\n",
              " '곤지암',\n",
              " ' 구룡',\n",
              " '남동인더스파크',\n",
              " ' 간석',\n",
              " '녹사평',\n",
              " ' 고려대',\n",
              " '왕십리',\n",
              " ' 동수',\n",
              " '문학경기장',\n",
              " '근처',\n",
              " '신포',\n",
              " ' 김포공항',\n",
              " ' 수원',\n",
              " ' 신목동',\n",
              " ' 역곡',\n",
              " '시청',\n",
              " '남춘천',\n",
              " ' 소사',\n",
              " ' 곡산',\n",
              " '독립문',\n",
              " ' 월롱',\n",
              " '숭의',\n",
              " ' 오금',\n",
              " '이매',\n",
              " ' 노량진',\n",
              " '여주',\n",
              " ' 수유',\n",
              " '삼성중앙',\n",
              " '편리',\n",
              " ' 성북',\n",
              " '석촌',\n",
              " ' 박촌',\n",
              " '흥선',\n",
              " '송파나루',\n",
              " '굴포천',\n",
              " ' 서현',\n",
              " ' 신방화',\n",
              " ' 한성대입구',\n",
              " ' 동인천',\n",
              " ' 수내',\n",
              " ' 경인교대입구',\n",
              " '회룡',\n",
              " ' 덕계',\n",
              " ' 양주',\n",
              " ' 이매',\n",
              " ' 미금',\n",
              " '돌곶이',\n",
              " ' 종각',\n",
              " ' 작전',\n",
              " '가산디지털단지',\n",
              " ' 상록수',\n",
              " ' 부평삼거리',\n",
              " '주안',\n",
              " ' 건대입구',\n",
              " '원인재',\n",
              " ' 잠원',\n",
              " '인하대',\n",
              " ' 굴봉산',\n",
              " ' 낙성대',\n",
              " '부발',\n",
              " ' 응암',\n",
              " ' 마천',\n",
              " ' 도심',\n",
              " ' 온수',\n",
              " ' 지축',\n",
              " '내방',\n",
              " ' 신이문',\n",
              " '선학',\n",
              " '평촌',\n",
              " ' 배방',\n",
              " '전대.에버랜드',\n",
              " ' 제물포',\n",
              " ' 옥수',\n",
              " '동대입구',\n",
              " ' 남구로',\n",
              " '매교',\n",
              " '제기동',\n",
              " ' 원덕',\n",
              " '북한산보국문',\n",
              " '직산',\n",
              " ' 고잔',\n",
              " '서울숲',\n",
              " '탑석',\n",
              " '수락산',\n",
              " ' 미아삼거리',\n",
              " '회기',\n",
              " '배방',\n",
              " ' 계산',\n",
              " '명동역',\n",
              " ' 부평',\n",
              " ' 남한산성입구',\n",
              " '역과',\n",
              " '퇴계원',\n",
              " '어룡',\n",
              " ' 공단',\n",
              " '판교',\n",
              " '오산',\n",
              " '지석',\n",
              " ' 대공원',\n",
              " '경복궁',\n",
              " ' 인천공항1터미널',\n",
              " '독산',\n",
              " '월곶',\n",
              " '뚝섬',\n",
              " '석계']"
            ]
          },
          "metadata": {},
          "execution_count": 34
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df['시설']=0\n",
        "df['서비스']=0\n",
        "df['위치']=0\n",
        "df['가격']=0"
      ],
      "metadata": {
        "id": "3s7OKDjX1xaI"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 659
        },
        "id": "2TMZcdu7nvQ-",
        "outputId": "5a5c7572-1983-4ac3-8973-2e01d1f0f372"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                      hotel  star  \\\n",
              "0                       AC 호텔 바이 메리어트 서울 강남     4   \n",
              "1                       AC 호텔 바이 메리어트 서울 강남     5   \n",
              "2                       AC 호텔 바이 메리어트 서울 강남     3   \n",
              "3                       AC 호텔 바이 메리어트 서울 강남     5   \n",
              "4       몬드리안 서울 이태원(Mondrian Seoul Itaewon)     5   \n",
              "...                                     ...   ...   \n",
              "237445                              뜨랑블루 호텔     2   \n",
              "237446                              뜨랑블루 호텔     5   \n",
              "237447                              뜨랑블루 호텔     5   \n",
              "237448                              뜨랑블루 호텔     5   \n",
              "237449                              뜨랑블루 호텔     4   \n",
              "\n",
              "                                                   review          date  \\\n",
              "0                     발렛파킹 비용이 있긴 했지만 방도 나름 괜찮고 조식도 맛있었어요        10시간 전   \n",
              "1                                                   굳굳굳굳굳          6일 전   \n",
              "2       생각보다 방이 좁아서 놀랐어요 아무래도 안마의자나 고급 블루투스 스피커처럼 주변기기...          6일 전   \n",
              "3       오픈하고 얼마안되서 갔었는데 깔끔하고 좋은 호텔이였습니다 오픈초기에 사소한 부분에서...  2022. 03. 27   \n",
              "4                                        객실이 깨끗하고 너무 예뻣어요          3일 전   \n",
              "...                                                   ...           ...   \n",
              "237445  시설 깨끗하고 다 좋은데퇴실도 안햇는데 청소하시는분인지 입구문을 맘대로 여시더라구요...          5년 전   \n",
              "237446               깔끔하고 친철하고 모두 만족해요꼭 한번더 오고 싶은 숙박업소입니다          5년 전   \n",
              "237447                     괜찮았어요 좋더라구요 마음에 들었어요냄새도 안나드러구요          5년 전   \n",
              "237448  시설 신림권에서 최고청결하고 수건에서 냄새도 안나고흠이라면 1000원받는 일회용품이...          5년 전   \n",
              "237449  일단 조식이 포함되어있어서 좋았구요 방도 깨끗하고하루정도 지내기엔 좋은거 같네요야경...          5년 전   \n",
              "\n",
              "           real_date  length  \\\n",
              "0       2022. 04. 03      35   \n",
              "1       2022. 04. 01       5   \n",
              "2       2022. 04. 01      84   \n",
              "3       2022. 03. 27      99   \n",
              "4       2022. 04. 01      16   \n",
              "...              ...     ...   \n",
              "237445          5년 전      60   \n",
              "237446          5년 전      36   \n",
              "237447          5년 전      30   \n",
              "237448          5년 전      51   \n",
              "237449          5년 전      77   \n",
              "\n",
              "                                       review_spell_check  site  시설  서비스  위치  \\\n",
              "0                     발레파킹 비용이 있긴 했지만 방도 나름 괜찮고 조식도 맛있었어요     0   0    0   0   \n",
              "1                                                   굳굳굳굳굳     0   0    0   0   \n",
              "2       생각보다 방이 좁아서 놀랐어요 아무래도 안마의자나 고급 블루투스 스피커처럼 주변기기...     0   0    0   0   \n",
              "3       오픈하고 얼마 안 돼서 갔었는데 깔끔하고 좋은 호텔이었습니다 오픈 초기에 사소한 부...     0   0    0   0   \n",
              "4                                        객실이 깨끗하고 너무 예뻤어요     0   0    0   0   \n",
              "...                                                   ...   ...  ..  ...  ..   \n",
              "237445  시설 깨끗하고 다 좋은데 퇴실도 안 했는데 청소하시는 분인지 입구물을 맘대로 여시더...     1   0    0   0   \n",
              "237446            깔끔하고 친절하고 모두 만족해요 꼭 한 번 더 오고 싶은 숙박업소입니다     1   0    0   0   \n",
              "237447                    괜찮았어요 좋더라고요 마음에 들었어요 냄새도 안나드러구요     1   0    0   0   \n",
              "237448  시설 신림권에서 최고 청결하고 수건에서 냄새도 안 나고 흠이라면 1000원 받는 일...     1   0    0   0   \n",
              "237449  일단 조식이 포함되어있어서 좋았고요 방도 깨끗하고 하루 정도 지내기엔 좋은 거 같네...     1   0    0   0   \n",
              "\n",
              "        가격  \n",
              "0        0  \n",
              "1        0  \n",
              "2        0  \n",
              "3        0  \n",
              "4        0  \n",
              "...     ..  \n",
              "237445   0  \n",
              "237446   0  \n",
              "237447   0  \n",
              "237448   0  \n",
              "237449   0  \n",
              "\n",
              "[237450 rows x 12 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-97f6f834-8735-4b13-9704-7ba0c00e57c3\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>hotel</th>\n",
              "      <th>star</th>\n",
              "      <th>review</th>\n",
              "      <th>date</th>\n",
              "      <th>real_date</th>\n",
              "      <th>length</th>\n",
              "      <th>review_spell_check</th>\n",
              "      <th>site</th>\n",
              "      <th>시설</th>\n",
              "      <th>서비스</th>\n",
              "      <th>위치</th>\n",
              "      <th>가격</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>AC 호텔 바이 메리어트 서울 강남</td>\n",
              "      <td>4</td>\n",
              "      <td>발렛파킹 비용이 있긴 했지만 방도 나름 괜찮고 조식도 맛있었어요</td>\n",
              "      <td>10시간 전</td>\n",
              "      <td>2022. 04. 03</td>\n",
              "      <td>35</td>\n",
              "      <td>발레파킹 비용이 있긴 했지만 방도 나름 괜찮고 조식도 맛있었어요</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>AC 호텔 바이 메리어트 서울 강남</td>\n",
              "      <td>5</td>\n",
              "      <td>굳굳굳굳굳</td>\n",
              "      <td>6일 전</td>\n",
              "      <td>2022. 04. 01</td>\n",
              "      <td>5</td>\n",
              "      <td>굳굳굳굳굳</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>AC 호텔 바이 메리어트 서울 강남</td>\n",
              "      <td>3</td>\n",
              "      <td>생각보다 방이 좁아서 놀랐어요 아무래도 안마의자나 고급 블루투스 스피커처럼 주변기기...</td>\n",
              "      <td>6일 전</td>\n",
              "      <td>2022. 04. 01</td>\n",
              "      <td>84</td>\n",
              "      <td>생각보다 방이 좁아서 놀랐어요 아무래도 안마의자나 고급 블루투스 스피커처럼 주변기기...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>AC 호텔 바이 메리어트 서울 강남</td>\n",
              "      <td>5</td>\n",
              "      <td>오픈하고 얼마안되서 갔었는데 깔끔하고 좋은 호텔이였습니다 오픈초기에 사소한 부분에서...</td>\n",
              "      <td>2022. 03. 27</td>\n",
              "      <td>2022. 03. 27</td>\n",
              "      <td>99</td>\n",
              "      <td>오픈하고 얼마 안 돼서 갔었는데 깔끔하고 좋은 호텔이었습니다 오픈 초기에 사소한 부...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>몬드리안 서울 이태원(Mondrian Seoul Itaewon)</td>\n",
              "      <td>5</td>\n",
              "      <td>객실이 깨끗하고 너무 예뻣어요</td>\n",
              "      <td>3일 전</td>\n",
              "      <td>2022. 04. 01</td>\n",
              "      <td>16</td>\n",
              "      <td>객실이 깨끗하고 너무 예뻤어요</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>237445</th>\n",
              "      <td>뜨랑블루 호텔</td>\n",
              "      <td>2</td>\n",
              "      <td>시설 깨끗하고 다 좋은데퇴실도 안햇는데 청소하시는분인지 입구문을 맘대로 여시더라구요...</td>\n",
              "      <td>5년 전</td>\n",
              "      <td>5년 전</td>\n",
              "      <td>60</td>\n",
              "      <td>시설 깨끗하고 다 좋은데 퇴실도 안 했는데 청소하시는 분인지 입구물을 맘대로 여시더...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>237446</th>\n",
              "      <td>뜨랑블루 호텔</td>\n",
              "      <td>5</td>\n",
              "      <td>깔끔하고 친철하고 모두 만족해요꼭 한번더 오고 싶은 숙박업소입니다</td>\n",
              "      <td>5년 전</td>\n",
              "      <td>5년 전</td>\n",
              "      <td>36</td>\n",
              "      <td>깔끔하고 친절하고 모두 만족해요 꼭 한 번 더 오고 싶은 숙박업소입니다</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>237447</th>\n",
              "      <td>뜨랑블루 호텔</td>\n",
              "      <td>5</td>\n",
              "      <td>괜찮았어요 좋더라구요 마음에 들었어요냄새도 안나드러구요</td>\n",
              "      <td>5년 전</td>\n",
              "      <td>5년 전</td>\n",
              "      <td>30</td>\n",
              "      <td>괜찮았어요 좋더라고요 마음에 들었어요 냄새도 안나드러구요</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>237448</th>\n",
              "      <td>뜨랑블루 호텔</td>\n",
              "      <td>5</td>\n",
              "      <td>시설 신림권에서 최고청결하고 수건에서 냄새도 안나고흠이라면 1000원받는 일회용품이...</td>\n",
              "      <td>5년 전</td>\n",
              "      <td>5년 전</td>\n",
              "      <td>51</td>\n",
              "      <td>시설 신림권에서 최고 청결하고 수건에서 냄새도 안 나고 흠이라면 1000원 받는 일...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>237449</th>\n",
              "      <td>뜨랑블루 호텔</td>\n",
              "      <td>4</td>\n",
              "      <td>일단 조식이 포함되어있어서 좋았구요 방도 깨끗하고하루정도 지내기엔 좋은거 같네요야경...</td>\n",
              "      <td>5년 전</td>\n",
              "      <td>5년 전</td>\n",
              "      <td>77</td>\n",
              "      <td>일단 조식이 포함되어있어서 좋았고요 방도 깨끗하고 하루 정도 지내기엔 좋은 거 같네...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>237450 rows × 12 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-97f6f834-8735-4b13-9704-7ba0c00e57c3')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-97f6f834-8735-4b13-9704-7ba0c00e57c3 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-97f6f834-8735-4b13-9704-7ba0c00e57c3');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 91
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "for x in n1:\n",
        "  df['시설'][df.review_spell_check.str.contains(x)]+=df.review_spell_check.str.count(x)\n",
        "for x in n2:\n",
        "  df['서비스'][df.review_spell_check.str.contains(x)]+=df.review_spell_check.str.count(x)\n",
        "for x in n3:\n",
        "  df['위치'][df.review_spell_check.str.contains(x)]+=df.review_spell_check.str.count(x)\n",
        "for x in n4:\n",
        "  df['가격'][df.review_spell_check.str.contains(x)]+=df.review_spell_check.str.count(x)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "k7I0kDOoeHyx",
        "outputId": "d9d782f7-e696-43ae-96e5-f08b8e80c92f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:2: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:2: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:2: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:2: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:2: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:2: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:2: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:2: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:2: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:2: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:2: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:2: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:2: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:2: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:2: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:2: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:2: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:2: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:2: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:2: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:2: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:2: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:2: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:2: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:2: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:2: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:2: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:2: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:2: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:2: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:4: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  after removing the cwd from sys.path.\n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:4: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  after removing the cwd from sys.path.\n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:4: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  after removing the cwd from sys.path.\n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:4: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  after removing the cwd from sys.path.\n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:4: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  after removing the cwd from sys.path.\n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:4: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  after removing the cwd from sys.path.\n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:4: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  after removing the cwd from sys.path.\n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:4: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  after removing the cwd from sys.path.\n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:4: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  after removing the cwd from sys.path.\n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:4: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  after removing the cwd from sys.path.\n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:4: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  after removing the cwd from sys.path.\n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:4: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  after removing the cwd from sys.path.\n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:4: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  after removing the cwd from sys.path.\n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: UserWarning: This pattern has match groups. To actually get the groups, use str.extract.\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:8: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:8: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:8: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_new = df.loc[:,['시설', '서비스', '위치', '가격']].max(axis=1)"
      ],
      "metadata": {
        "id": "7yukrcNdUv78"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df['label'] = 0"
      ],
      "metadata": {
        "id": "DISCw3AbZ8DF"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df.label.loc[df['시설']==df_new]=1\n",
        "df.label.loc[df['서비스']==df_new]=2\n",
        "df.label.loc[df['위치']==df_new]=3\n",
        "df.label.loc[df['가격']==df_new]=4"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "74R8yLTuYEO9",
        "outputId": "ed1f10d6-bd25-4eaf-b1fb-e38d7e0f0d30"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/pandas/core/indexing.py:1732: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  self._setitem_single_block(indexer, value, name)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.label.loc[df_new==0]=0"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "tLadR4cuav-8",
        "outputId": "ecd339b0-ddf9-440b-d48c-6c2a4733c105"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/pandas/core/indexing.py:1732: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  self._setitem_single_block(indexer, value, name)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#토픽 위치 추가 후\n",
        "df.label.value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "XZOFvokq6y7u",
        "outputId": "51283504-d1a8-4333-c4e1-5d778a916b8d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0    77677\n",
              "1    77466\n",
              "2    47305\n",
              "3    25372\n",
              "4     9630\n",
              "Name: label, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#역명 정보 추가 후\n",
        "df.label.value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qMq0N5SZQDk6",
        "outputId": "c31099fc-289d-4b43-c65c-31c7ee263a4f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0    76984\n",
              "1    74596\n",
              "2    45809\n",
              "3    31146\n",
              "4     8915\n",
              "Name: label, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 97
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.describe()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        },
        "id": "PtClM2gZB9Op",
        "outputId": "99f51cb5-8289-4873-8674-0e7c41932974"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                star         length           site             시설  \\\n",
              "count  237450.000000  237450.000000  237450.000000  237450.000000   \n",
              "mean        4.635641      57.506161       0.483799       1.554218   \n",
              "std         0.744728      76.847789       0.499739       2.443693   \n",
              "min         1.000000       1.000000       0.000000       0.000000   \n",
              "25%         4.000000      11.000000       0.000000       0.000000   \n",
              "50%         5.000000      23.000000       0.000000       1.000000   \n",
              "75%         5.000000      66.000000       1.000000       2.000000   \n",
              "max         5.000000     500.000000       1.000000      60.000000   \n",
              "\n",
              "                 서비스             위치             가격          label  \n",
              "count  237450.000000  237450.000000  237450.000000  237450.000000  \n",
              "mean        0.856500       0.686966       0.131998       1.243681  \n",
              "std         1.522661       1.561282       0.470919       1.149058  \n",
              "min         0.000000       0.000000       0.000000       0.000000  \n",
              "25%         0.000000       0.000000       0.000000       0.000000  \n",
              "50%         0.000000       0.000000       0.000000       1.000000  \n",
              "75%         1.000000       1.000000       0.000000       2.000000  \n",
              "max        25.000000      41.000000      36.000000       4.000000  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-8d7be1ad-8a46-43e2-be64-4ed08c475900\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>star</th>\n",
              "      <th>length</th>\n",
              "      <th>site</th>\n",
              "      <th>시설</th>\n",
              "      <th>서비스</th>\n",
              "      <th>위치</th>\n",
              "      <th>가격</th>\n",
              "      <th>label</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>237450.000000</td>\n",
              "      <td>237450.000000</td>\n",
              "      <td>237450.000000</td>\n",
              "      <td>237450.000000</td>\n",
              "      <td>237450.000000</td>\n",
              "      <td>237450.000000</td>\n",
              "      <td>237450.000000</td>\n",
              "      <td>237450.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>4.635641</td>\n",
              "      <td>57.506161</td>\n",
              "      <td>0.483799</td>\n",
              "      <td>1.554218</td>\n",
              "      <td>0.856500</td>\n",
              "      <td>0.686966</td>\n",
              "      <td>0.131998</td>\n",
              "      <td>1.243681</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>0.744728</td>\n",
              "      <td>76.847789</td>\n",
              "      <td>0.499739</td>\n",
              "      <td>2.443693</td>\n",
              "      <td>1.522661</td>\n",
              "      <td>1.561282</td>\n",
              "      <td>0.470919</td>\n",
              "      <td>1.149058</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>4.000000</td>\n",
              "      <td>11.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>5.000000</td>\n",
              "      <td>23.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>5.000000</td>\n",
              "      <td>66.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>2.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>5.000000</td>\n",
              "      <td>500.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>60.000000</td>\n",
              "      <td>25.000000</td>\n",
              "      <td>41.000000</td>\n",
              "      <td>36.000000</td>\n",
              "      <td>4.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-8d7be1ad-8a46-43e2-be64-4ed08c475900')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-8d7be1ad-8a46-43e2-be64-4ed08c475900 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-8d7be1ad-8a46-43e2-be64-4ed08c475900');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 44
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 분류 지도학습"
      ],
      "metadata": {
        "id": "DBs65xUgDEI6"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# train_test_split\n",
        "x_train, x_test, y_train, y_test = train_test_split(df.review_spell_check, df.label, test_size=0.3, shuffle=True, stratify=df.label, random_state=777)"
      ],
      "metadata": {
        "id": "Zc-muJaVDNk-"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "y_train.value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hEYnVuieZ1Dd",
        "outputId": "82bec3b9-09ef-4ecc-96c1-6ab74f89336b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0    53889\n",
              "1    52217\n",
              "2    32066\n",
              "3    21802\n",
              "4     6241\n",
              "Name: label, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 46
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.feature_extraction.text import CountVectorizer #sklearn 패키지의 CountVectorizer import\n",
        "vectorizer = CountVectorizer() #countvectorizer 생성\n",
        "vectorizer.fit(x_train) # countvectorizer 학습\n",
        "X = vectorizer.transform(x_train) # transform"
      ],
      "metadata": {
        "id": "DjBic_zXa0Ab"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.linear_model import LogisticRegression\n",
        "model = LogisticRegression()\n",
        "model.fit(X,y_train)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "H2LKgxwcSRGy",
        "outputId": "5458c596-0f4f-48ae-ed7f-83f2e125eae4"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/sklearn/linear_model/_logistic.py:818: ConvergenceWarning: lbfgs failed to converge (status=1):\n",
            "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
            "\n",
            "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
            "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
            "Please also refer to the documentation for alternative solver options:\n",
            "    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n",
            "  extra_warning_msg=_LOGISTIC_SOLVER_CONVERGENCE_MSG,\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "LogisticRegression()"
            ]
          },
          "metadata": {},
          "execution_count": 48
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#입력해서 확인하는 용도\n",
        "#run model\n",
        "X_pred = vectorizer.transform([input()]) \n",
        "y_pred = model.predict(X_pred)\n",
        "print(y_pred)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "dAmqPi6oTH1r",
        "outputId": "f0c847cb-07d3-48d5-ea87-8c6105854f09"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "가격 대비 괜찮네요\n",
            "[4]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "model.score(X, y_train)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "U8dXpSVHTmDe",
        "outputId": "6d0e208d-b2df-495c-c5ed-dd8290027c35"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.9778299190807087"
            ]
          },
          "metadata": {},
          "execution_count": 55
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#run model\n",
        "X_pred = vectorizer.transform(x_test) \n",
        "y_pred = model.predict(X_pred)"
      ],
      "metadata": {
        "id": "QrbGTKWfTyEW"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "model.score(X_pred, y_test)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "rOJgIdwkTtrs",
        "outputId": "5089e967-9986-4757-8f06-38e3dff89848"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.9209517793219625"
            ]
          },
          "metadata": {},
          "execution_count": 58
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# confusion matrix\n",
        "from sklearn.metrics import classification_report, confusion_matrix, precision_score, recall_score, f1_score\n",
        "import seaborn as sns\n",
        "cm = confusion_matrix(y_test,y_pred)\n",
        "sns.heatmap(cm, annot = True, fmt = 'd',cmap = 'Blues')\n",
        "plt.xlabel('True Label')\n",
        "plt.ylabel('Predict Label')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 279
        },
        "id": "_6ofoo0HVV5g",
        "outputId": "658fa38f-6789-4383-99f5-011fbeeb33d2"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_train = df.review_spell_check"
      ],
      "metadata": {
        "id": "jaNv3dmbVZ7S"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#run model\n",
        "df_vec= vectorizer.transform(df_train) \n",
        "l_pred = model.predict(df_vec)\n",
        "proba = model.predict_proba(df_vec)"
      ],
      "metadata": {
        "id": "R-6ntPSsSc7s"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df_proba= pd.DataFrame(proba)"
      ],
      "metadata": {
        "id": "niz9c71vSzab"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df_proba"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "37mn7nwuTL4l",
        "outputId": "18645121-5bb9-4212-e9dd-c4874b7920c1"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                   0         1         2             3             4\n",
              "0       3.874113e-05  0.922787  0.068350  8.489839e-03  3.334874e-04\n",
              "1       9.811697e-01  0.006099  0.005713  4.876576e-03  2.141469e-03\n",
              "2       1.694947e-06  0.999445  0.000018  5.338017e-04  8.318019e-07\n",
              "3       9.436890e-09  0.999912  0.000014  7.195487e-05  1.896939e-06\n",
              "4       2.520743e-02  0.882314  0.032072  4.726061e-02  1.314650e-02\n",
              "...              ...       ...       ...           ...           ...\n",
              "237445  7.543127e-07  0.999801  0.000024  1.561764e-04  1.834974e-05\n",
              "237446  1.853394e-03  0.013259  0.936564  4.551936e-02  2.803765e-03\n",
              "237447  2.309130e-01  0.759288  0.002379  6.161991e-03  1.258047e-03\n",
              "237448  2.890378e-10  0.999997  0.000002  5.563171e-07  1.298812e-07\n",
              "237449  5.698022e-08  0.069143  0.928922  1.920503e-03  1.477086e-05\n",
              "\n",
              "[237450 rows x 5 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-fb510c1f-d98c-4807-8076-7db8f09a304a\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>0</th>\n",
              "      <th>1</th>\n",
              "      <th>2</th>\n",
              "      <th>3</th>\n",
              "      <th>4</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>3.874113e-05</td>\n",
              "      <td>0.922787</td>\n",
              "      <td>0.068350</td>\n",
              "      <td>8.489839e-03</td>\n",
              "      <td>3.334874e-04</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>9.811697e-01</td>\n",
              "      <td>0.006099</td>\n",
              "      <td>0.005713</td>\n",
              "      <td>4.876576e-03</td>\n",
              "      <td>2.141469e-03</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1.694947e-06</td>\n",
              "      <td>0.999445</td>\n",
              "      <td>0.000018</td>\n",
              "      <td>5.338017e-04</td>\n",
              "      <td>8.318019e-07</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>9.436890e-09</td>\n",
              "      <td>0.999912</td>\n",
              "      <td>0.000014</td>\n",
              "      <td>7.195487e-05</td>\n",
              "      <td>1.896939e-06</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2.520743e-02</td>\n",
              "      <td>0.882314</td>\n",
              "      <td>0.032072</td>\n",
              "      <td>4.726061e-02</td>\n",
              "      <td>1.314650e-02</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>237445</th>\n",
              "      <td>7.543127e-07</td>\n",
              "      <td>0.999801</td>\n",
              "      <td>0.000024</td>\n",
              "      <td>1.561764e-04</td>\n",
              "      <td>1.834974e-05</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>237446</th>\n",
              "      <td>1.853394e-03</td>\n",
              "      <td>0.013259</td>\n",
              "      <td>0.936564</td>\n",
              "      <td>4.551936e-02</td>\n",
              "      <td>2.803765e-03</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>237447</th>\n",
              "      <td>2.309130e-01</td>\n",
              "      <td>0.759288</td>\n",
              "      <td>0.002379</td>\n",
              "      <td>6.161991e-03</td>\n",
              "      <td>1.258047e-03</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>237448</th>\n",
              "      <td>2.890378e-10</td>\n",
              "      <td>0.999997</td>\n",
              "      <td>0.000002</td>\n",
              "      <td>5.563171e-07</td>\n",
              "      <td>1.298812e-07</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>237449</th>\n",
              "      <td>5.698022e-08</td>\n",
              "      <td>0.069143</td>\n",
              "      <td>0.928922</td>\n",
              "      <td>1.920503e-03</td>\n",
              "      <td>1.477086e-05</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>237450 rows × 5 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-fb510c1f-d98c-4807-8076-7db8f09a304a')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-fb510c1f-d98c-4807-8076-7db8f09a304a button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-fb510c1f-d98c-4807-8076-7db8f09a304a');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 69
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "label_prob = df_proba.max(axis=1)"
      ],
      "metadata": {
        "id": "jHoyqc0nT2B7"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# confusion matrix\n",
        "from sklearn.metrics import classification_report, confusion_matrix, precision_score, recall_score, f1_score\n",
        "import seaborn as sns\n",
        "cm = confusion_matrix(df.label,l_pred)\n",
        "sns.heatmap(cm, annot = True, fmt = 'd',cmap = 'Blues')\n",
        "plt.xlabel('True Label')\n",
        "plt.ylabel('Predict Label')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 279
        },
        "id": "wvouzm01WypB",
        "outputId": "0a3bcb5d-41ca-4252-f6b6-c65c438788ca"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "model.score(df_vec, df.label)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "A1o5MUDeXQ5O",
        "outputId": "f99d851f-6bda-4252-f2cf-63794bae76e5"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.9607664771530848"
            ]
          },
          "metadata": {},
          "execution_count": 78
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df['label_pred'] = l_pred"
      ],
      "metadata": {
        "id": "EFJairInY2ym"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df['label_proba'] = label_prob"
      ],
      "metadata": {
        "id": "rNUNVzjlZC-u"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df['sentiment']= sent['sentiment']\n",
        "df['sent_proba'] = sent['sent_proba']"
      ],
      "metadata": {
        "id": "79S9auzfZPXA"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df.describe()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        },
        "id": "AfNbjwbQmq2S",
        "outputId": "3bdedfea-73d1-4dcf-b7cd-edd770af37e8"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                star         length           site             시설  \\\n",
              "count  237450.000000  237450.000000  237450.000000  237450.000000   \n",
              "mean        4.635641      57.506161       0.483799       1.554218   \n",
              "std         0.744728      76.847789       0.499739       2.443693   \n",
              "min         1.000000       1.000000       0.000000       0.000000   \n",
              "25%         4.000000      11.000000       0.000000       0.000000   \n",
              "50%         5.000000      23.000000       0.000000       1.000000   \n",
              "75%         5.000000      66.000000       1.000000       2.000000   \n",
              "max         5.000000     500.000000       1.000000      60.000000   \n",
              "\n",
              "                 서비스             위치             가격          label  \\\n",
              "count  237450.000000  237450.000000  237450.000000  237450.000000   \n",
              "mean        0.856500       0.686966       0.131998       1.243681   \n",
              "std         1.522661       1.561282       0.470919       1.149058   \n",
              "min         0.000000       0.000000       0.000000       0.000000   \n",
              "25%         0.000000       0.000000       0.000000       0.000000   \n",
              "50%         0.000000       0.000000       0.000000       1.000000   \n",
              "75%         1.000000       1.000000       0.000000       2.000000   \n",
              "max        25.000000      41.000000      36.000000       4.000000   \n",
              "\n",
              "          label_pred    label_proba      sentiment    sent_proba  \n",
              "count  237450.000000  237450.000000  237450.000000  2.374500e+05  \n",
              "mean        1.213321       0.926556       0.785172  7.022491e-01  \n",
              "std         1.148170       0.102708       0.410704  3.023777e-01  \n",
              "min         0.000000       0.280929       0.000000  1.531017e-18  \n",
              "25%         0.000000       0.916623       1.000000  5.535977e-01  \n",
              "50%         1.000000       0.961131       1.000000  8.077600e-01  \n",
              "75%         2.000000       0.993543       1.000000  9.426238e-01  \n",
              "max         4.000000       1.000000       1.000000  1.000000e+00  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-bc26d0eb-bfc7-424b-bcdb-90a43e9611f9\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>star</th>\n",
              "      <th>length</th>\n",
              "      <th>site</th>\n",
              "      <th>시설</th>\n",
              "      <th>서비스</th>\n",
              "      <th>위치</th>\n",
              "      <th>가격</th>\n",
              "      <th>label</th>\n",
              "      <th>label_pred</th>\n",
              "      <th>label_proba</th>\n",
              "      <th>sentiment</th>\n",
              "      <th>sent_proba</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>237450.000000</td>\n",
              "      <td>237450.000000</td>\n",
              "      <td>237450.000000</td>\n",
              "      <td>237450.000000</td>\n",
              "      <td>237450.000000</td>\n",
              "      <td>237450.000000</td>\n",
              "      <td>237450.000000</td>\n",
              "      <td>237450.000000</td>\n",
              "      <td>237450.000000</td>\n",
              "      <td>237450.000000</td>\n",
              "      <td>237450.000000</td>\n",
              "      <td>2.374500e+05</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>4.635641</td>\n",
              "      <td>57.506161</td>\n",
              "      <td>0.483799</td>\n",
              "      <td>1.554218</td>\n",
              "      <td>0.856500</td>\n",
              "      <td>0.686966</td>\n",
              "      <td>0.131998</td>\n",
              "      <td>1.243681</td>\n",
              "      <td>1.213321</td>\n",
              "      <td>0.926556</td>\n",
              "      <td>0.785172</td>\n",
              "      <td>7.022491e-01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>0.744728</td>\n",
              "      <td>76.847789</td>\n",
              "      <td>0.499739</td>\n",
              "      <td>2.443693</td>\n",
              "      <td>1.522661</td>\n",
              "      <td>1.561282</td>\n",
              "      <td>0.470919</td>\n",
              "      <td>1.149058</td>\n",
              "      <td>1.148170</td>\n",
              "      <td>0.102708</td>\n",
              "      <td>0.410704</td>\n",
              "      <td>3.023777e-01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.280929</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.531017e-18</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>4.000000</td>\n",
              "      <td>11.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.916623</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>5.535977e-01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>5.000000</td>\n",
              "      <td>23.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.961131</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>8.077600e-01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>5.000000</td>\n",
              "      <td>66.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>0.993543</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>9.426238e-01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>5.000000</td>\n",
              "      <td>500.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>60.000000</td>\n",
              "      <td>25.000000</td>\n",
              "      <td>41.000000</td>\n",
              "      <td>36.000000</td>\n",
              "      <td>4.000000</td>\n",
              "      <td>4.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000e+00</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-bc26d0eb-bfc7-424b-bcdb-90a43e9611f9')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-bc26d0eb-bfc7-424b-bcdb-90a43e9611f9 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-bc26d0eb-bfc7-424b-bcdb-90a43e9611f9');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 112
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.to_csv(\"호텔리뷰모델포함.csv\", index=False)"
      ],
      "metadata": {
        "id": "poEo0eoTnK5r"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 서비스 형태"
      ],
      "metadata": {
        "id": "QSnynX6u_gUU"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df = pd.read_csv(\"/content/drive/MyDrive/호텔리뷰모델포함.csv\")"
      ],
      "metadata": {
        "id": "OR5zUwex8-D-"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df.hotel.loc[df.hotel=='ENA 스위트호텔 남대문']='ENA 스위트 호텔 남대문'\n",
        "df.hotel.loc[df.hotel=='SR호텔 서울 마곡']='SR 호텔 서울 마곡'\n",
        "df.hotel.loc[df.hotel=='노보텔 앰배서더 동대문 호텔&레지던스']='노보텔 앰배서더 동대문 호텔 & 레지던스'\n",
        "df.hotel.loc[df.hotel=='라이즈 오토그래프 컬렉션 바이메리어트']= '라이즈 오토그래프 컬렉션 바이 메리어트'\n",
        "df.hotel.loc[df.hotel=='롯데호텔 서울 이그제큐티브타워'] = '롯데 호텔 서울'\n",
        "df.hotel.loc[df.hotel=='소피텔 앰배서더 서울 호텔 & 서비스드 레지던스']='소피텔 앰배서더 서울'\n",
        "df.hotel.loc[df.hotel=='솔라리아 니시테츠 호텔 명동']= '솔라리아 니시테츠 명동'\n",
        "df.hotel.loc[df.hotel=='몬드리안 서울 이태원(Mondrian Seoul Itaewon)'] = '몬드리안 서울 이태원'\n",
        "df.hotel.loc[df.hotel=='이비스 앰배서더 서울 명동'] = '이비스 앰배서더 명동'\n",
        "df.hotel.loc[df.hotel=='스타즈호텔 독산'] = '스타즈 호텔 독산'\n",
        "df.hotel.loc[df.hotel=='호텔 리베라 청담'] = '호텔 리베라'\n",
        "df.hotel.loc[df.hotel=='홍대 나인브릭호텔']='홍대 나인브릭 호텔'"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ysViPmF0wU-v",
        "outputId": "048b63a0-daae-40a7-d32e-8c2949988b9b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/pandas/core/indexing.py:1732: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  self._setitem_single_block(indexer, value, name)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 919
        },
        "id": "uMNTYhwEfXM5",
        "outputId": "c0d890e6-7f88-4bcf-db3b-d263c70f2ea6"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                      hotel  star  \\\n",
              "0       AC 호텔 바이 메리어트 서울 강남     4   \n",
              "1       AC 호텔 바이 메리어트 서울 강남     5   \n",
              "2       AC 호텔 바이 메리어트 서울 강남     3   \n",
              "3       AC 호텔 바이 메리어트 서울 강남     5   \n",
              "4               몬드리안 서울 이태원     5   \n",
              "...                     ...   ...   \n",
              "237445              뜨랑블루 호텔     2   \n",
              "237446              뜨랑블루 호텔     5   \n",
              "237447              뜨랑블루 호텔     5   \n",
              "237448              뜨랑블루 호텔     5   \n",
              "237449              뜨랑블루 호텔     4   \n",
              "\n",
              "                                                   review          date  \\\n",
              "0                     발렛파킹 비용이 있긴 했지만 방도 나름 괜찮고 조식도 맛있었어요        10시간 전   \n",
              "1                                                   굳굳굳굳굳          6일 전   \n",
              "2       생각보다 방이 좁아서 놀랐어요 아무래도 안마의자나 고급 블루투스 스피커처럼 주변기기...          6일 전   \n",
              "3       오픈하고 얼마안되서 갔었는데 깔끔하고 좋은 호텔이였습니다 오픈초기에 사소한 부분에서...  2022. 03. 27   \n",
              "4                                        객실이 깨끗하고 너무 예뻣어요          3일 전   \n",
              "...                                                   ...           ...   \n",
              "237445  시설 깨끗하고 다 좋은데퇴실도 안햇는데 청소하시는분인지 입구문을 맘대로 여시더라구요...          5년 전   \n",
              "237446               깔끔하고 친철하고 모두 만족해요꼭 한번더 오고 싶은 숙박업소입니다          5년 전   \n",
              "237447                     괜찮았어요 좋더라구요 마음에 들었어요냄새도 안나드러구요          5년 전   \n",
              "237448  시설 신림권에서 최고청결하고 수건에서 냄새도 안나고흠이라면 1000원받는 일회용품이...          5년 전   \n",
              "237449  일단 조식이 포함되어있어서 좋았구요 방도 깨끗하고하루정도 지내기엔 좋은거 같네요야경...          5년 전   \n",
              "\n",
              "           real_date  length  \\\n",
              "0       2022. 04. 03      35   \n",
              "1       2022. 04. 01       5   \n",
              "2       2022. 04. 01      84   \n",
              "3       2022. 03. 27      99   \n",
              "4       2022. 04. 01      16   \n",
              "...              ...     ...   \n",
              "237445          5년 전      60   \n",
              "237446          5년 전      36   \n",
              "237447          5년 전      30   \n",
              "237448          5년 전      51   \n",
              "237449          5년 전      77   \n",
              "\n",
              "                                       review_spell_check  site  시설  서비스  위치  \\\n",
              "0                     발레파킹 비용이 있긴 했지만 방도 나름 괜찮고 조식도 맛있었어요     0   2    1   0   \n",
              "1                                                   굳굳굳굳굳     0   0    0   0   \n",
              "2       생각보다 방이 좁아서 놀랐어요 아무래도 안마의자나 고급 블루투스 스피커처럼 주변기기...     0   4    0   2   \n",
              "3       오픈하고 얼마 안 돼서 갔었는데 깔끔하고 좋은 호텔이었습니다 오픈 초기에 사소한 부...     0   2    1   0   \n",
              "4                                        객실이 깨끗하고 너무 예뻤어요     0   1    0   0   \n",
              "...                                                   ...   ...  ..  ...  ..   \n",
              "237445  시설 깨끗하고 다 좋은데 퇴실도 안 했는데 청소하시는 분인지 입구물을 맘대로 여시더...     1   3    0   0   \n",
              "237446            깔끔하고 친절하고 모두 만족해요 꼭 한 번 더 오고 싶은 숙박업소입니다     1   0    1   0   \n",
              "237447                    괜찮았어요 좋더라고요 마음에 들었어요 냄새도 안나드러구요     1   2    0   0   \n",
              "237448  시설 신림권에서 최고 청결하고 수건에서 냄새도 안 나고 흠이라면 1000원 받는 일...     1   4    0   1   \n",
              "237449  일단 조식이 포함되어있어서 좋았고요 방도 깨끗하고 하루 정도 지내기엔 좋은 거 같네...     1   3    2   0   \n",
              "\n",
              "        가격  label  label_pred  label_proba  sentiment  sent_proba  \n",
              "0        0      1           1     0.922787          0    0.157060  \n",
              "1        0      0           0     0.981170          1    0.690170  \n",
              "2        0      1           1     0.999445          0    0.168279  \n",
              "3        0      1           1     0.999912          1    0.880336  \n",
              "4        0      1           1     0.882314          1    0.807030  \n",
              "...     ..    ...         ...          ...        ...         ...  \n",
              "237445   0      1           1     0.999801          0    0.090315  \n",
              "237446   0      2           2     0.936564          1    0.996796  \n",
              "237447   0      1           1     0.759288          1    0.726964  \n",
              "237448   0      1           1     0.999997          1    0.615526  \n",
              "237449   0      1           2     0.928922          1    0.865782  \n",
              "\n",
              "[237450 rows x 17 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-f0f21bbb-68e0-4d3a-8f55-4e8a0532c922\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>hotel</th>\n",
              "      <th>star</th>\n",
              "      <th>review</th>\n",
              "      <th>date</th>\n",
              "      <th>real_date</th>\n",
              "      <th>length</th>\n",
              "      <th>review_spell_check</th>\n",
              "      <th>site</th>\n",
              "      <th>시설</th>\n",
              "      <th>서비스</th>\n",
              "      <th>위치</th>\n",
              "      <th>가격</th>\n",
              "      <th>label</th>\n",
              "      <th>label_pred</th>\n",
              "      <th>label_proba</th>\n",
              "      <th>sentiment</th>\n",
              "      <th>sent_proba</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>AC 호텔 바이 메리어트 서울 강남</td>\n",
              "      <td>4</td>\n",
              "      <td>발렛파킹 비용이 있긴 했지만 방도 나름 괜찮고 조식도 맛있었어요</td>\n",
              "      <td>10시간 전</td>\n",
              "      <td>2022. 04. 03</td>\n",
              "      <td>35</td>\n",
              "      <td>발레파킹 비용이 있긴 했지만 방도 나름 괜찮고 조식도 맛있었어요</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0.922787</td>\n",
              "      <td>0</td>\n",
              "      <td>0.157060</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>AC 호텔 바이 메리어트 서울 강남</td>\n",
              "      <td>5</td>\n",
              "      <td>굳굳굳굳굳</td>\n",
              "      <td>6일 전</td>\n",
              "      <td>2022. 04. 01</td>\n",
              "      <td>5</td>\n",
              "      <td>굳굳굳굳굳</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.981170</td>\n",
              "      <td>1</td>\n",
              "      <td>0.690170</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>AC 호텔 바이 메리어트 서울 강남</td>\n",
              "      <td>3</td>\n",
              "      <td>생각보다 방이 좁아서 놀랐어요 아무래도 안마의자나 고급 블루투스 스피커처럼 주변기기...</td>\n",
              "      <td>6일 전</td>\n",
              "      <td>2022. 04. 01</td>\n",
              "      <td>84</td>\n",
              "      <td>생각보다 방이 좁아서 놀랐어요 아무래도 안마의자나 고급 블루투스 스피커처럼 주변기기...</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0.999445</td>\n",
              "      <td>0</td>\n",
              "      <td>0.168279</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>AC 호텔 바이 메리어트 서울 강남</td>\n",
              "      <td>5</td>\n",
              "      <td>오픈하고 얼마안되서 갔었는데 깔끔하고 좋은 호텔이였습니다 오픈초기에 사소한 부분에서...</td>\n",
              "      <td>2022. 03. 27</td>\n",
              "      <td>2022. 03. 27</td>\n",
              "      <td>99</td>\n",
              "      <td>오픈하고 얼마 안 돼서 갔었는데 깔끔하고 좋은 호텔이었습니다 오픈 초기에 사소한 부...</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0.999912</td>\n",
              "      <td>1</td>\n",
              "      <td>0.880336</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>몬드리안 서울 이태원</td>\n",
              "      <td>5</td>\n",
              "      <td>객실이 깨끗하고 너무 예뻣어요</td>\n",
              "      <td>3일 전</td>\n",
              "      <td>2022. 04. 01</td>\n",
              "      <td>16</td>\n",
              "      <td>객실이 깨끗하고 너무 예뻤어요</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0.882314</td>\n",
              "      <td>1</td>\n",
              "      <td>0.807030</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>237445</th>\n",
              "      <td>뜨랑블루 호텔</td>\n",
              "      <td>2</td>\n",
              "      <td>시설 깨끗하고 다 좋은데퇴실도 안햇는데 청소하시는분인지 입구문을 맘대로 여시더라구요...</td>\n",
              "      <td>5년 전</td>\n",
              "      <td>5년 전</td>\n",
              "      <td>60</td>\n",
              "      <td>시설 깨끗하고 다 좋은데 퇴실도 안 했는데 청소하시는 분인지 입구물을 맘대로 여시더...</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0.999801</td>\n",
              "      <td>0</td>\n",
              "      <td>0.090315</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>237446</th>\n",
              "      <td>뜨랑블루 호텔</td>\n",
              "      <td>5</td>\n",
              "      <td>깔끔하고 친철하고 모두 만족해요꼭 한번더 오고 싶은 숙박업소입니다</td>\n",
              "      <td>5년 전</td>\n",
              "      <td>5년 전</td>\n",
              "      <td>36</td>\n",
              "      <td>깔끔하고 친절하고 모두 만족해요 꼭 한 번 더 오고 싶은 숙박업소입니다</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>0.936564</td>\n",
              "      <td>1</td>\n",
              "      <td>0.996796</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>237447</th>\n",
              "      <td>뜨랑블루 호텔</td>\n",
              "      <td>5</td>\n",
              "      <td>괜찮았어요 좋더라구요 마음에 들었어요냄새도 안나드러구요</td>\n",
              "      <td>5년 전</td>\n",
              "      <td>5년 전</td>\n",
              "      <td>30</td>\n",
              "      <td>괜찮았어요 좋더라고요 마음에 들었어요 냄새도 안나드러구요</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0.759288</td>\n",
              "      <td>1</td>\n",
              "      <td>0.726964</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>237448</th>\n",
              "      <td>뜨랑블루 호텔</td>\n",
              "      <td>5</td>\n",
              "      <td>시설 신림권에서 최고청결하고 수건에서 냄새도 안나고흠이라면 1000원받는 일회용품이...</td>\n",
              "      <td>5년 전</td>\n",
              "      <td>5년 전</td>\n",
              "      <td>51</td>\n",
              "      <td>시설 신림권에서 최고 청결하고 수건에서 냄새도 안 나고 흠이라면 1000원 받는 일...</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0.999997</td>\n",
              "      <td>1</td>\n",
              "      <td>0.615526</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>237449</th>\n",
              "      <td>뜨랑블루 호텔</td>\n",
              "      <td>4</td>\n",
              "      <td>일단 조식이 포함되어있어서 좋았구요 방도 깨끗하고하루정도 지내기엔 좋은거 같네요야경...</td>\n",
              "      <td>5년 전</td>\n",
              "      <td>5년 전</td>\n",
              "      <td>77</td>\n",
              "      <td>일단 조식이 포함되어있어서 좋았고요 방도 깨끗하고 하루 정도 지내기엔 좋은 거 같네...</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>0.928922</td>\n",
              "      <td>1</td>\n",
              "      <td>0.865782</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>237450 rows × 17 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-f0f21bbb-68e0-4d3a-8f55-4e8a0532c922')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-f0f21bbb-68e0-4d3a-8f55-4e8a0532c922 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-f0f21bbb-68e0-4d3a-8f55-4e8a0532c922');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.groupby(['hotel']).mean().sort_values(['sentiment'])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 455
        },
        "id": "_d3UlcBjond_",
        "outputId": "837025bd-a8ac-42b2-db19-6ab7bb237b8c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                          star      length  site        시설       서비스  \\\n",
              "hotel                                                                  \n",
              "메이원호텔                 4.000000   78.750000   1.0  3.000000  0.250000   \n",
              "서울시티호텔                3.576923   67.307692   1.0  1.807692  0.807692   \n",
              "명동 이코노미 호텔 프리미어       3.629630   78.333333   1.0  2.481481  0.814815   \n",
              "명동 뉴 스테이 인            4.102564   36.435897   0.0  1.051282  0.102564   \n",
              "명동 MUST STAY HOTEL    3.304348   87.217391   1.0  2.217391  0.956522   \n",
              "...                        ...         ...   ...       ...       ...   \n",
              "조선 팰리스 서울 강남 럭셔리 컬렉션  4.888889  161.655556   1.0  3.488889  2.777778   \n",
              "로이넷호텔 서울 마포           4.866667   40.600000   0.0  1.533333  0.400000   \n",
              "호텔28 명동               4.916667  147.958333   1.0  3.958333  1.958333   \n",
              "종로 호텔팝 리즈 프리미어        5.000000   20.000000   1.0  2.000000  0.000000   \n",
              "유에이치 스위트 더 서울         5.000000   14.000000   0.0  0.000000  1.000000   \n",
              "\n",
              "                            위치        가격     label  label_pred  label_proba  \\\n",
              "hotel                                                                         \n",
              "메이원호텔                 2.500000  0.500000  1.000000    1.000000     0.973024   \n",
              "서울시티호텔                1.346154  0.500000  2.269231    2.000000     0.933135   \n",
              "명동 이코노미 호텔 프리미어       0.814815  0.407407  1.518519    1.629630     0.946582   \n",
              "명동 뉴 스테이 인            0.641026  0.230769  1.000000    0.948718     0.915728   \n",
              "명동 MUST STAY HOTEL    0.739130  0.304348  1.826087    1.869565     0.908069   \n",
              "...                        ...       ...       ...         ...          ...   \n",
              "조선 팰리스 서울 강남 럭셔리 컬렉션  0.633333  0.233333  1.311111    1.322222     0.967908   \n",
              "로이넷호텔 서울 마포           0.066667  0.000000  0.933333    0.933333     0.947418   \n",
              "호텔28 명동               1.791667  0.208333  1.687500    1.687500     0.933411   \n",
              "종로 호텔팝 리즈 프리미어        0.000000  0.000000  1.000000    1.000000     0.997135   \n",
              "유에이치 스위트 더 서울         0.000000  0.000000  2.000000    2.000000     0.964869   \n",
              "\n",
              "                      sentiment  sent_proba  \n",
              "hotel                                        \n",
              "메이원호텔                  0.250000    0.369443  \n",
              "서울시티호텔                 0.269231    0.305602  \n",
              "명동 이코노미 호텔 프리미어        0.333333    0.371095  \n",
              "명동 뉴 스테이 인             0.333333    0.380198  \n",
              "명동 MUST STAY HOTEL     0.347826    0.395280  \n",
              "...                         ...         ...  \n",
              "조선 팰리스 서울 강남 럭셔리 컬렉션   0.922222    0.886289  \n",
              "로이넷호텔 서울 마포            0.933333    0.801742  \n",
              "호텔28 명동                0.958333    0.882087  \n",
              "종로 호텔팝 리즈 프리미어         1.000000    0.837922  \n",
              "유에이치 스위트 더 서울          1.000000    0.975040  \n",
              "\n",
              "[291 rows x 12 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-0a0e3982-ab0c-453c-a635-e5333f1c165b\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>star</th>\n",
              "      <th>length</th>\n",
              "      <th>site</th>\n",
              "      <th>시설</th>\n",
              "      <th>서비스</th>\n",
              "      <th>위치</th>\n",
              "      <th>가격</th>\n",
              "      <th>label</th>\n",
              "      <th>label_pred</th>\n",
              "      <th>label_proba</th>\n",
              "      <th>sentiment</th>\n",
              "      <th>sent_proba</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>hotel</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>메이원호텔</th>\n",
              "      <td>4.000000</td>\n",
              "      <td>78.750000</td>\n",
              "      <td>1.0</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>0.250000</td>\n",
              "      <td>2.500000</td>\n",
              "      <td>0.500000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.973024</td>\n",
              "      <td>0.250000</td>\n",
              "      <td>0.369443</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>서울시티호텔</th>\n",
              "      <td>3.576923</td>\n",
              "      <td>67.307692</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.807692</td>\n",
              "      <td>0.807692</td>\n",
              "      <td>1.346154</td>\n",
              "      <td>0.500000</td>\n",
              "      <td>2.269231</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>0.933135</td>\n",
              "      <td>0.269231</td>\n",
              "      <td>0.305602</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>명동 이코노미 호텔 프리미어</th>\n",
              "      <td>3.629630</td>\n",
              "      <td>78.333333</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2.481481</td>\n",
              "      <td>0.814815</td>\n",
              "      <td>0.814815</td>\n",
              "      <td>0.407407</td>\n",
              "      <td>1.518519</td>\n",
              "      <td>1.629630</td>\n",
              "      <td>0.946582</td>\n",
              "      <td>0.333333</td>\n",
              "      <td>0.371095</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>명동 뉴 스테이 인</th>\n",
              "      <td>4.102564</td>\n",
              "      <td>36.435897</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.051282</td>\n",
              "      <td>0.102564</td>\n",
              "      <td>0.641026</td>\n",
              "      <td>0.230769</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.948718</td>\n",
              "      <td>0.915728</td>\n",
              "      <td>0.333333</td>\n",
              "      <td>0.380198</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>명동 MUST STAY HOTEL</th>\n",
              "      <td>3.304348</td>\n",
              "      <td>87.217391</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2.217391</td>\n",
              "      <td>0.956522</td>\n",
              "      <td>0.739130</td>\n",
              "      <td>0.304348</td>\n",
              "      <td>1.826087</td>\n",
              "      <td>1.869565</td>\n",
              "      <td>0.908069</td>\n",
              "      <td>0.347826</td>\n",
              "      <td>0.395280</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>조선 팰리스 서울 강남 럭셔리 컬렉션</th>\n",
              "      <td>4.888889</td>\n",
              "      <td>161.655556</td>\n",
              "      <td>1.0</td>\n",
              "      <td>3.488889</td>\n",
              "      <td>2.777778</td>\n",
              "      <td>0.633333</td>\n",
              "      <td>0.233333</td>\n",
              "      <td>1.311111</td>\n",
              "      <td>1.322222</td>\n",
              "      <td>0.967908</td>\n",
              "      <td>0.922222</td>\n",
              "      <td>0.886289</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>로이넷호텔 서울 마포</th>\n",
              "      <td>4.866667</td>\n",
              "      <td>40.600000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.533333</td>\n",
              "      <td>0.400000</td>\n",
              "      <td>0.066667</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.933333</td>\n",
              "      <td>0.933333</td>\n",
              "      <td>0.947418</td>\n",
              "      <td>0.933333</td>\n",
              "      <td>0.801742</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>호텔28 명동</th>\n",
              "      <td>4.916667</td>\n",
              "      <td>147.958333</td>\n",
              "      <td>1.0</td>\n",
              "      <td>3.958333</td>\n",
              "      <td>1.958333</td>\n",
              "      <td>1.791667</td>\n",
              "      <td>0.208333</td>\n",
              "      <td>1.687500</td>\n",
              "      <td>1.687500</td>\n",
              "      <td>0.933411</td>\n",
              "      <td>0.958333</td>\n",
              "      <td>0.882087</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>종로 호텔팝 리즈 프리미어</th>\n",
              "      <td>5.000000</td>\n",
              "      <td>20.000000</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.997135</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.837922</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>유에이치 스위트 더 서울</th>\n",
              "      <td>5.000000</td>\n",
              "      <td>14.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>0.964869</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.975040</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>291 rows × 12 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-0a0e3982-ab0c-453c-a635-e5333f1c165b')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-0a0e3982-ab0c-453c-a635-e5333f1c165b button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-0a0e3982-ab0c-453c-a635-e5333f1c165b');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.hotel.value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "tk0aryQx50X8",
        "outputId": "dffd6006-e739-4e55-f306-a71bdf6b032f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "신라스테이 구로          9261\n",
              "글래드 마포            7245\n",
              "신라스테이 마포          6651\n",
              "노보텔 앰배서더 서울 용산    5513\n",
              "롯데시티호텔 명동         5138\n",
              "                  ... \n",
              "메이원호텔                4\n",
              "사월 호텔                3\n",
              "마리호텔                 2\n",
              "유에이치 스위트 더 서울        1\n",
              "종로 호텔팝 리즈 프리미어       1\n",
              "Name: hotel, Length: 291, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "z = df.hotel.value_counts()\n",
        "zz = pd.DataFrame(z)"
      ],
      "metadata": {
        "id": "4x9xDCpstNYP"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "zz.columns = ['hotelcount']"
      ],
      "metadata": {
        "id": "IenENEvAfpnj"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "mz = zz.reset_index(drop=False)"
      ],
      "metadata": {
        "id": "NIiLS77s4jSk"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "mz.columns = ['hotel', 'hotelcount']"
      ],
      "metadata": {
        "id": "9PXwyGB54oSy"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "mz"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "_jFlNwhn47Gs",
        "outputId": "fcb5abe4-1e14-4b64-b9b1-e8dacd08ce11"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "              hotel  hotelcount\n",
              "0          신라스테이 구로        9261\n",
              "1            글래드 마포        7245\n",
              "2          신라스테이 마포        6651\n",
              "3    노보텔 앰배서더 서울 용산        5513\n",
              "4         롯데시티호텔 명동        5138\n",
              "..              ...         ...\n",
              "286           메이원호텔           4\n",
              "287           사월 호텔           3\n",
              "288            마리호텔           2\n",
              "289   유에이치 스위트 더 서울           1\n",
              "290  종로 호텔팝 리즈 프리미어           1\n",
              "\n",
              "[291 rows x 2 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-1b21d14f-afbc-4e80-9ea7-d0b922297027\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>hotel</th>\n",
              "      <th>hotelcount</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>신라스테이 구로</td>\n",
              "      <td>9261</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>글래드 마포</td>\n",
              "      <td>7245</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>신라스테이 마포</td>\n",
              "      <td>6651</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>노보텔 앰배서더 서울 용산</td>\n",
              "      <td>5513</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>롯데시티호텔 명동</td>\n",
              "      <td>5138</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>286</th>\n",
              "      <td>메이원호텔</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>287</th>\n",
              "      <td>사월 호텔</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>288</th>\n",
              "      <td>마리호텔</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>289</th>\n",
              "      <td>유에이치 스위트 더 서울</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>290</th>\n",
              "      <td>종로 호텔팝 리즈 프리미어</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>291 rows × 2 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-1b21d14f-afbc-4e80-9ea7-d0b922297027')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-1b21d14f-afbc-4e80-9ea7-d0b922297027 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-1b21d14f-afbc-4e80-9ea7-d0b922297027');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df = pd.merge(df,mz, on='hotel')"
      ],
      "metadata": {
        "id": "Y5cjc7lR4BDK"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "IABCumrP5ork",
        "outputId": "1b1ece8a-a31d-4e8d-f266-af1f23bb4400"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                      hotel  star  \\\n",
              "0       AC 호텔 바이 메리어트 서울 강남     4   \n",
              "1       AC 호텔 바이 메리어트 서울 강남     5   \n",
              "2       AC 호텔 바이 메리어트 서울 강남     3   \n",
              "3       AC 호텔 바이 메리어트 서울 강남     5   \n",
              "4       AC 호텔 바이 메리어트 서울 강남     4   \n",
              "...                     ...   ...   \n",
              "237445              뜨랑블루 호텔     2   \n",
              "237446              뜨랑블루 호텔     5   \n",
              "237447              뜨랑블루 호텔     5   \n",
              "237448              뜨랑블루 호텔     5   \n",
              "237449              뜨랑블루 호텔     4   \n",
              "\n",
              "                                                   review          date  \\\n",
              "0                     발렛파킹 비용이 있긴 했지만 방도 나름 괜찮고 조식도 맛있었어요        10시간 전   \n",
              "1                                                   굳굳굳굳굳          6일 전   \n",
              "2       생각보다 방이 좁아서 놀랐어요 아무래도 안마의자나 고급 블루투스 스피커처럼 주변기기...          6일 전   \n",
              "3       오픈하고 얼마안되서 갔었는데 깔끔하고 좋은 호텔이였습니다 오픈초기에 사소한 부분에서...  2022. 03. 27   \n",
              "4                     발렛파킹 비용이 있긴 했지만 방도 나름 괜찮고 조식도 맛있었어요        16시간 전   \n",
              "...                                                   ...           ...   \n",
              "237445  시설 깨끗하고 다 좋은데퇴실도 안햇는데 청소하시는분인지 입구문을 맘대로 여시더라구요...          5년 전   \n",
              "237446               깔끔하고 친철하고 모두 만족해요꼭 한번더 오고 싶은 숙박업소입니다          5년 전   \n",
              "237447                     괜찮았어요 좋더라구요 마음에 들었어요냄새도 안나드러구요          5년 전   \n",
              "237448  시설 신림권에서 최고청결하고 수건에서 냄새도 안나고흠이라면 1000원받는 일회용품이...          5년 전   \n",
              "237449  일단 조식이 포함되어있어서 좋았구요 방도 깨끗하고하루정도 지내기엔 좋은거 같네요야경...          5년 전   \n",
              "\n",
              "           real_date  length  \\\n",
              "0       2022. 04. 03      35   \n",
              "1       2022. 04. 01       5   \n",
              "2       2022. 04. 01      84   \n",
              "3       2022. 03. 27      99   \n",
              "4       2022. 04. 03      35   \n",
              "...              ...     ...   \n",
              "237445          5년 전      60   \n",
              "237446          5년 전      36   \n",
              "237447          5년 전      30   \n",
              "237448          5년 전      51   \n",
              "237449          5년 전      77   \n",
              "\n",
              "                                       review_spell_check  site  시설  서비스  위치  \\\n",
              "0                     발레파킹 비용이 있긴 했지만 방도 나름 괜찮고 조식도 맛있었어요     0   2    1   0   \n",
              "1                                                   굳굳굳굳굳     0   0    0   0   \n",
              "2       생각보다 방이 좁아서 놀랐어요 아무래도 안마의자나 고급 블루투스 스피커처럼 주변기기...     0   4    0   2   \n",
              "3       오픈하고 얼마 안 돼서 갔었는데 깔끔하고 좋은 호텔이었습니다 오픈 초기에 사소한 부...     0   2    1   0   \n",
              "4                     발레파킹 비용이 있긴 했지만 방도 나름 괜찮고 조식도 맛있었어요     0   2    1   0   \n",
              "...                                                   ...   ...  ..  ...  ..   \n",
              "237445  시설 깨끗하고 다 좋은데 퇴실도 안 했는데 청소하시는 분인지 입구물을 맘대로 여시더...     1   3    0   0   \n",
              "237446            깔끔하고 친절하고 모두 만족해요 꼭 한 번 더 오고 싶은 숙박업소입니다     1   0    1   0   \n",
              "237447                    괜찮았어요 좋더라고요 마음에 들었어요 냄새도 안나드러구요     1   2    0   0   \n",
              "237448  시설 신림권에서 최고 청결하고 수건에서 냄새도 안 나고 흠이라면 1000원 받는 일...     1   4    0   1   \n",
              "237449  일단 조식이 포함되어있어서 좋았고요 방도 깨끗하고 하루 정도 지내기엔 좋은 거 같네...     1   3    2   0   \n",
              "\n",
              "        가격  label  label_pred  label_proba  sentiment  sent_proba  hotelcount  \n",
              "0        0      1           1     0.922787          0    0.157060          11  \n",
              "1        0      0           0     0.981170          1    0.690170          11  \n",
              "2        0      1           1     0.999445          0    0.168279          11  \n",
              "3        0      1           1     0.999912          1    0.880336          11  \n",
              "4        0      1           1     0.922787          0    0.157060          11  \n",
              "...     ..    ...         ...          ...        ...         ...         ...  \n",
              "237445   0      1           1     0.999801          0    0.090315         250  \n",
              "237446   0      2           2     0.936564          1    0.996796         250  \n",
              "237447   0      1           1     0.759288          1    0.726964         250  \n",
              "237448   0      1           1     0.999997          1    0.615526         250  \n",
              "237449   0      1           2     0.928922          1    0.865782         250  \n",
              "\n",
              "[237450 rows x 18 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-2f8d1acc-7491-49be-9ba3-8f7b208a70f2\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>hotel</th>\n",
              "      <th>star</th>\n",
              "      <th>review</th>\n",
              "      <th>date</th>\n",
              "      <th>real_date</th>\n",
              "      <th>length</th>\n",
              "      <th>review_spell_check</th>\n",
              "      <th>site</th>\n",
              "      <th>시설</th>\n",
              "      <th>서비스</th>\n",
              "      <th>위치</th>\n",
              "      <th>가격</th>\n",
              "      <th>label</th>\n",
              "      <th>label_pred</th>\n",
              "      <th>label_proba</th>\n",
              "      <th>sentiment</th>\n",
              "      <th>sent_proba</th>\n",
              "      <th>hotelcount</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>AC 호텔 바이 메리어트 서울 강남</td>\n",
              "      <td>4</td>\n",
              "      <td>발렛파킹 비용이 있긴 했지만 방도 나름 괜찮고 조식도 맛있었어요</td>\n",
              "      <td>10시간 전</td>\n",
              "      <td>2022. 04. 03</td>\n",
              "      <td>35</td>\n",
              "      <td>발레파킹 비용이 있긴 했지만 방도 나름 괜찮고 조식도 맛있었어요</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0.922787</td>\n",
              "      <td>0</td>\n",
              "      <td>0.157060</td>\n",
              "      <td>11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>AC 호텔 바이 메리어트 서울 강남</td>\n",
              "      <td>5</td>\n",
              "      <td>굳굳굳굳굳</td>\n",
              "      <td>6일 전</td>\n",
              "      <td>2022. 04. 01</td>\n",
              "      <td>5</td>\n",
              "      <td>굳굳굳굳굳</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.981170</td>\n",
              "      <td>1</td>\n",
              "      <td>0.690170</td>\n",
              "      <td>11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>AC 호텔 바이 메리어트 서울 강남</td>\n",
              "      <td>3</td>\n",
              "      <td>생각보다 방이 좁아서 놀랐어요 아무래도 안마의자나 고급 블루투스 스피커처럼 주변기기...</td>\n",
              "      <td>6일 전</td>\n",
              "      <td>2022. 04. 01</td>\n",
              "      <td>84</td>\n",
              "      <td>생각보다 방이 좁아서 놀랐어요 아무래도 안마의자나 고급 블루투스 스피커처럼 주변기기...</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0.999445</td>\n",
              "      <td>0</td>\n",
              "      <td>0.168279</td>\n",
              "      <td>11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>AC 호텔 바이 메리어트 서울 강남</td>\n",
              "      <td>5</td>\n",
              "      <td>오픈하고 얼마안되서 갔었는데 깔끔하고 좋은 호텔이였습니다 오픈초기에 사소한 부분에서...</td>\n",
              "      <td>2022. 03. 27</td>\n",
              "      <td>2022. 03. 27</td>\n",
              "      <td>99</td>\n",
              "      <td>오픈하고 얼마 안 돼서 갔었는데 깔끔하고 좋은 호텔이었습니다 오픈 초기에 사소한 부...</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0.999912</td>\n",
              "      <td>1</td>\n",
              "      <td>0.880336</td>\n",
              "      <td>11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>AC 호텔 바이 메리어트 서울 강남</td>\n",
              "      <td>4</td>\n",
              "      <td>발렛파킹 비용이 있긴 했지만 방도 나름 괜찮고 조식도 맛있었어요</td>\n",
              "      <td>16시간 전</td>\n",
              "      <td>2022. 04. 03</td>\n",
              "      <td>35</td>\n",
              "      <td>발레파킹 비용이 있긴 했지만 방도 나름 괜찮고 조식도 맛있었어요</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0.922787</td>\n",
              "      <td>0</td>\n",
              "      <td>0.157060</td>\n",
              "      <td>11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>237445</th>\n",
              "      <td>뜨랑블루 호텔</td>\n",
              "      <td>2</td>\n",
              "      <td>시설 깨끗하고 다 좋은데퇴실도 안햇는데 청소하시는분인지 입구문을 맘대로 여시더라구요...</td>\n",
              "      <td>5년 전</td>\n",
              "      <td>5년 전</td>\n",
              "      <td>60</td>\n",
              "      <td>시설 깨끗하고 다 좋은데 퇴실도 안 했는데 청소하시는 분인지 입구물을 맘대로 여시더...</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0.999801</td>\n",
              "      <td>0</td>\n",
              "      <td>0.090315</td>\n",
              "      <td>250</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>237446</th>\n",
              "      <td>뜨랑블루 호텔</td>\n",
              "      <td>5</td>\n",
              "      <td>깔끔하고 친철하고 모두 만족해요꼭 한번더 오고 싶은 숙박업소입니다</td>\n",
              "      <td>5년 전</td>\n",
              "      <td>5년 전</td>\n",
              "      <td>36</td>\n",
              "      <td>깔끔하고 친절하고 모두 만족해요 꼭 한 번 더 오고 싶은 숙박업소입니다</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>0.936564</td>\n",
              "      <td>1</td>\n",
              "      <td>0.996796</td>\n",
              "      <td>250</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>237447</th>\n",
              "      <td>뜨랑블루 호텔</td>\n",
              "      <td>5</td>\n",
              "      <td>괜찮았어요 좋더라구요 마음에 들었어요냄새도 안나드러구요</td>\n",
              "      <td>5년 전</td>\n",
              "      <td>5년 전</td>\n",
              "      <td>30</td>\n",
              "      <td>괜찮았어요 좋더라고요 마음에 들었어요 냄새도 안나드러구요</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0.759288</td>\n",
              "      <td>1</td>\n",
              "      <td>0.726964</td>\n",
              "      <td>250</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>237448</th>\n",
              "      <td>뜨랑블루 호텔</td>\n",
              "      <td>5</td>\n",
              "      <td>시설 신림권에서 최고청결하고 수건에서 냄새도 안나고흠이라면 1000원받는 일회용품이...</td>\n",
              "      <td>5년 전</td>\n",
              "      <td>5년 전</td>\n",
              "      <td>51</td>\n",
              "      <td>시설 신림권에서 최고 청결하고 수건에서 냄새도 안 나고 흠이라면 1000원 받는 일...</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0.999997</td>\n",
              "      <td>1</td>\n",
              "      <td>0.615526</td>\n",
              "      <td>250</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>237449</th>\n",
              "      <td>뜨랑블루 호텔</td>\n",
              "      <td>4</td>\n",
              "      <td>일단 조식이 포함되어있어서 좋았구요 방도 깨끗하고하루정도 지내기엔 좋은거 같네요야경...</td>\n",
              "      <td>5년 전</td>\n",
              "      <td>5년 전</td>\n",
              "      <td>77</td>\n",
              "      <td>일단 조식이 포함되어있어서 좋았고요 방도 깨끗하고 하루 정도 지내기엔 좋은 거 같네...</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>0.928922</td>\n",
              "      <td>1</td>\n",
              "      <td>0.865782</td>\n",
              "      <td>250</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>237450 rows × 18 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-2f8d1acc-7491-49be-9ba3-8f7b208a70f2')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-2f8d1acc-7491-49be-9ba3-8f7b208a70f2 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-2f8d1acc-7491-49be-9ba3-8f7b208a70f2');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df100 = df.loc[df.hotelcount>100]"
      ],
      "metadata": {
        "id": "Y_DiA8Gh5R_D"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# 전체 리뷰 중 긍정 감성이 높은 호텔\n",
        "df100.groupby(['hotel']).mean().sort_values(['sentiment'])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 455
        },
        "id": "fuZKRIvx6uOS",
        "outputId": "25f7bc65-b343-4d9f-fede-1f3b5deeb4b4"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                          star      length  site        시설       서비스  \\\n",
              "hotel                                                                  \n",
              "케이팝호텔 서울타워            3.655629   76.867550   1.0  2.456954  0.854305   \n",
              "동대문 바티카 호텔            3.884298   71.314050   1.0  2.380165  0.760331   \n",
              "노원 노블레스호텔             3.975862   52.368966   1.0  1.837931  0.844828   \n",
              "더 리버사이드 호텔            3.917120   31.080163   0.0  1.236413  0.233696   \n",
              "가락 호텔                 4.061404   37.903509   1.0  1.280702  0.614035   \n",
              "...                        ...         ...   ...       ...       ...   \n",
              "포시즌스 호텔               4.892157  151.460784   1.0  3.333333  3.019608   \n",
              "비스타 워커힐 서울            4.885965   92.052632   1.0  2.043860  1.456140   \n",
              "오라카이 대학로 호텔           4.850191   90.634542   1.0  2.524809  1.459924   \n",
              "인사동 썬비호텔              4.859060   89.355705   1.0  2.879195  1.302013   \n",
              "그랜드 머큐어 앰배서더 호텔앤레지던스  4.904615  115.944615   1.0  2.796923  1.910769   \n",
              "\n",
              "                            위치        가격     label  label_pred  label_proba  \\\n",
              "hotel                                                                         \n",
              "케이팝호텔 서울타워            1.000000  0.337748  1.655629    1.609272     0.919285   \n",
              "동대문 바티카 호텔            1.115702  0.173554  1.429752    1.363636     0.912458   \n",
              "노원 노블레스호텔             0.410345  0.210345  1.455172    1.434483     0.926431   \n",
              "더 리버사이드 호텔            0.278533  0.111413  0.894022    0.849185     0.927587   \n",
              "가락 호텔                 0.403509  0.289474  1.429825    1.385965     0.905068   \n",
              "...                        ...       ...       ...         ...          ...   \n",
              "포시즌스 호텔               0.882353  0.107843  1.431373    1.431373     0.947272   \n",
              "비스타 워커힐 서울            0.315789  0.061404  1.403509    1.377193     0.908842   \n",
              "오라카이 대학로 호텔           1.073473  0.164122  1.443702    1.424618     0.926483   \n",
              "인사동 썬비호텔              1.000000  0.228188  1.590604    1.590604     0.921132   \n",
              "그랜드 머큐어 앰배서더 호텔앤레지던스  0.646154  0.095385  1.436923    1.406154     0.929294   \n",
              "\n",
              "                      sentiment  sent_proba  hotelcount  \n",
              "hotel                                                    \n",
              "케이팝호텔 서울타워             0.370861    0.385243       151.0  \n",
              "동대문 바티카 호텔             0.479339    0.452647       121.0  \n",
              "노원 노블레스호텔              0.500000    0.475676       290.0  \n",
              "더 리버사이드 호텔             0.508152    0.464588       736.0  \n",
              "가락 호텔                  0.517544    0.482041       114.0  \n",
              "...                         ...         ...         ...  \n",
              "포시즌스 호텔                0.892157    0.863636       102.0  \n",
              "비스타 워커힐 서울             0.894737    0.821347       114.0  \n",
              "오라카이 대학로 호텔            0.897901    0.835874      1048.0  \n",
              "인사동 썬비호텔               0.899329    0.828680       149.0  \n",
              "그랜드 머큐어 앰배서더 호텔앤레지던스   0.904615    0.854717       325.0  \n",
              "\n",
              "[227 rows x 13 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-f762e0f1-e8ad-425f-8c44-cc1268e1e9f3\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>star</th>\n",
              "      <th>length</th>\n",
              "      <th>site</th>\n",
              "      <th>시설</th>\n",
              "      <th>서비스</th>\n",
              "      <th>위치</th>\n",
              "      <th>가격</th>\n",
              "      <th>label</th>\n",
              "      <th>label_pred</th>\n",
              "      <th>label_proba</th>\n",
              "      <th>sentiment</th>\n",
              "      <th>sent_proba</th>\n",
              "      <th>hotelcount</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>hotel</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>케이팝호텔 서울타워</th>\n",
              "      <td>3.655629</td>\n",
              "      <td>76.867550</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2.456954</td>\n",
              "      <td>0.854305</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.337748</td>\n",
              "      <td>1.655629</td>\n",
              "      <td>1.609272</td>\n",
              "      <td>0.919285</td>\n",
              "      <td>0.370861</td>\n",
              "      <td>0.385243</td>\n",
              "      <td>151.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>동대문 바티카 호텔</th>\n",
              "      <td>3.884298</td>\n",
              "      <td>71.314050</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2.380165</td>\n",
              "      <td>0.760331</td>\n",
              "      <td>1.115702</td>\n",
              "      <td>0.173554</td>\n",
              "      <td>1.429752</td>\n",
              "      <td>1.363636</td>\n",
              "      <td>0.912458</td>\n",
              "      <td>0.479339</td>\n",
              "      <td>0.452647</td>\n",
              "      <td>121.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>노원 노블레스호텔</th>\n",
              "      <td>3.975862</td>\n",
              "      <td>52.368966</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.837931</td>\n",
              "      <td>0.844828</td>\n",
              "      <td>0.410345</td>\n",
              "      <td>0.210345</td>\n",
              "      <td>1.455172</td>\n",
              "      <td>1.434483</td>\n",
              "      <td>0.926431</td>\n",
              "      <td>0.500000</td>\n",
              "      <td>0.475676</td>\n",
              "      <td>290.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>더 리버사이드 호텔</th>\n",
              "      <td>3.917120</td>\n",
              "      <td>31.080163</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.236413</td>\n",
              "      <td>0.233696</td>\n",
              "      <td>0.278533</td>\n",
              "      <td>0.111413</td>\n",
              "      <td>0.894022</td>\n",
              "      <td>0.849185</td>\n",
              "      <td>0.927587</td>\n",
              "      <td>0.508152</td>\n",
              "      <td>0.464588</td>\n",
              "      <td>736.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>가락 호텔</th>\n",
              "      <td>4.061404</td>\n",
              "      <td>37.903509</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.280702</td>\n",
              "      <td>0.614035</td>\n",
              "      <td>0.403509</td>\n",
              "      <td>0.289474</td>\n",
              "      <td>1.429825</td>\n",
              "      <td>1.385965</td>\n",
              "      <td>0.905068</td>\n",
              "      <td>0.517544</td>\n",
              "      <td>0.482041</td>\n",
              "      <td>114.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>포시즌스 호텔</th>\n",
              "      <td>4.892157</td>\n",
              "      <td>151.460784</td>\n",
              "      <td>1.0</td>\n",
              "      <td>3.333333</td>\n",
              "      <td>3.019608</td>\n",
              "      <td>0.882353</td>\n",
              "      <td>0.107843</td>\n",
              "      <td>1.431373</td>\n",
              "      <td>1.431373</td>\n",
              "      <td>0.947272</td>\n",
              "      <td>0.892157</td>\n",
              "      <td>0.863636</td>\n",
              "      <td>102.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>비스타 워커힐 서울</th>\n",
              "      <td>4.885965</td>\n",
              "      <td>92.052632</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2.043860</td>\n",
              "      <td>1.456140</td>\n",
              "      <td>0.315789</td>\n",
              "      <td>0.061404</td>\n",
              "      <td>1.403509</td>\n",
              "      <td>1.377193</td>\n",
              "      <td>0.908842</td>\n",
              "      <td>0.894737</td>\n",
              "      <td>0.821347</td>\n",
              "      <td>114.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>오라카이 대학로 호텔</th>\n",
              "      <td>4.850191</td>\n",
              "      <td>90.634542</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2.524809</td>\n",
              "      <td>1.459924</td>\n",
              "      <td>1.073473</td>\n",
              "      <td>0.164122</td>\n",
              "      <td>1.443702</td>\n",
              "      <td>1.424618</td>\n",
              "      <td>0.926483</td>\n",
              "      <td>0.897901</td>\n",
              "      <td>0.835874</td>\n",
              "      <td>1048.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>인사동 썬비호텔</th>\n",
              "      <td>4.859060</td>\n",
              "      <td>89.355705</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2.879195</td>\n",
              "      <td>1.302013</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.228188</td>\n",
              "      <td>1.590604</td>\n",
              "      <td>1.590604</td>\n",
              "      <td>0.921132</td>\n",
              "      <td>0.899329</td>\n",
              "      <td>0.828680</td>\n",
              "      <td>149.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>그랜드 머큐어 앰배서더 호텔앤레지던스</th>\n",
              "      <td>4.904615</td>\n",
              "      <td>115.944615</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2.796923</td>\n",
              "      <td>1.910769</td>\n",
              "      <td>0.646154</td>\n",
              "      <td>0.095385</td>\n",
              "      <td>1.436923</td>\n",
              "      <td>1.406154</td>\n",
              "      <td>0.929294</td>\n",
              "      <td>0.904615</td>\n",
              "      <td>0.854717</td>\n",
              "      <td>325.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>227 rows × 13 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-f762e0f1-e8ad-425f-8c44-cc1268e1e9f3')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-f762e0f1-e8ad-425f-8c44-cc1268e1e9f3 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-f762e0f1-e8ad-425f-8c44-cc1268e1e9f3');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.loc[(df.hotel == \"그랜드 머큐어 앰배서더 호텔앤레지던스\") & (df.sentiment == 0)]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "iU5uarqw1agg",
        "outputId": "902f39a4-64c8-48d6-e692-50b329fb07ca"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                       hotel  star  \\\n",
              "211220  그랜드 머큐어 앰배서더 호텔앤레지던스     4   \n",
              "211224  그랜드 머큐어 앰배서더 호텔앤레지던스     4   \n",
              "211240  그랜드 머큐어 앰배서더 호텔앤레지던스     5   \n",
              "211251  그랜드 머큐어 앰배서더 호텔앤레지던스     2   \n",
              "211261  그랜드 머큐어 앰배서더 호텔앤레지던스     4   \n",
              "211273  그랜드 머큐어 앰배서더 호텔앤레지던스     3   \n",
              "211278  그랜드 머큐어 앰배서더 호텔앤레지던스     4   \n",
              "211281  그랜드 머큐어 앰배서더 호텔앤레지던스     5   \n",
              "211299  그랜드 머큐어 앰배서더 호텔앤레지던스     5   \n",
              "211322  그랜드 머큐어 앰배서더 호텔앤레지던스     4   \n",
              "211334  그랜드 머큐어 앰배서더 호텔앤레지던스     5   \n",
              "211346  그랜드 머큐어 앰배서더 호텔앤레지던스     5   \n",
              "211361  그랜드 머큐어 앰배서더 호텔앤레지던스     4   \n",
              "211367  그랜드 머큐어 앰배서더 호텔앤레지던스     4   \n",
              "211383  그랜드 머큐어 앰배서더 호텔앤레지던스     4   \n",
              "211386  그랜드 머큐어 앰배서더 호텔앤레지던스     4   \n",
              "211395  그랜드 머큐어 앰배서더 호텔앤레지던스     5   \n",
              "211399  그랜드 머큐어 앰배서더 호텔앤레지던스     3   \n",
              "211410  그랜드 머큐어 앰배서더 호텔앤레지던스     5   \n",
              "211412  그랜드 머큐어 앰배서더 호텔앤레지던스     5   \n",
              "211416  그랜드 머큐어 앰배서더 호텔앤레지던스     5   \n",
              "211423  그랜드 머큐어 앰배서더 호텔앤레지던스     5   \n",
              "211437  그랜드 머큐어 앰배서더 호텔앤레지던스     4   \n",
              "211440  그랜드 머큐어 앰배서더 호텔앤레지던스     5   \n",
              "211449  그랜드 머큐어 앰배서더 호텔앤레지던스     3   \n",
              "211451  그랜드 머큐어 앰배서더 호텔앤레지던스     4   \n",
              "211452  그랜드 머큐어 앰배서더 호텔앤레지던스     5   \n",
              "211482  그랜드 머큐어 앰배서더 호텔앤레지던스     4   \n",
              "211486  그랜드 머큐어 앰배서더 호텔앤레지던스     4   \n",
              "211506  그랜드 머큐어 앰배서더 호텔앤레지던스     5   \n",
              "211530  그랜드 머큐어 앰배서더 호텔앤레지던스     5   \n",
              "\n",
              "                                                   review    date real_date  \\\n",
              "211220  딱딱한 침대 매트리스부터 높은 베개 침구류가 너무 별로예요  이점만 개선되면 좋을것같아요   2개월 전     2개월 전   \n",
              "211224  직원분들 친절도는 좋았으나 바닥에 떨어진 머리카락이 너무 많았어요 저는 다른건 참아...   2개월 전     2개월 전   \n",
              "211240  호텔 방 안에 주방 시설이 있는 게 가장 큰 장점입니다 가까운 아이파크몰에서 먹을 ...   6개월 전     6개월 전   \n",
              "211251  음개인적으로는 조금 아쉽네요  일반 슈페리어 객실보다는 완전 좋다라는 생각은 들지 ...   9개월 전     9개월 전   \n",
              "211261  일요일 4시경 체크인 했는데 최저층 9층을 받았습니다 게다가 엘리베이터 바로 앞 객...  10개월 전    10개월 전   \n",
              "211273  딱용산그정도입니다 너무기대를했나봅니다 그냥 강남호텔정도 가격은저렴한데 너무상류호텔따...  11개월 전    11개월 전   \n",
              "211278  그냥 그랬음침구류 상태가 안좋아서교체요구함침대밑에먹지도 않은 아이스크림 막대기가 있...  11개월 전    11개월 전   \n",
              "211281  일단 직원들의 고객응대와 친절에 높은 점수를 드리고 싶습니다 체크인때 많이 붐볐지만...    1년 전      1년 전   \n",
              "211299  코로나19로 취사가 가능한 머큐어를 자주 가게된다주니어 객실은 다 좋은데 인덕션 화...    1년 전      1년 전   \n",
              "211322  시설도 좋고 세제까지 없는게없어요 직원분들도 넘 친절하시구요 다만 온돌바닥이라 따로...    1년 전      1년 전   \n",
              "211334  요즘처럼 외부식당 가기가 어려울때 객실에서 간단한 조리가 가능한 호텔 좋은데 호텔요...    1년 전      1년 전   \n",
              "211346  프런트 직원은 언제나 친절하고 방은 예전보다 청결이 좀 아니었음 다만 애들있는 윗방...    1년 전      1년 전   \n",
              "211361  깨끗하고 좋았는데 온도가 너무 아끼는거 같아요보통 호텔은 더워서 옷을 반팔 반바지 ...    1년 전      1년 전   \n",
              "211367                  룸 컨디션이랑 시설 자체는 괜찮았는데 서비스가 좀 별로였네요    1년 전      1년 전   \n",
              "211383                        친절하고 너무 좋았는데 에어컨이 안되서 더웠어오     1년 전      1년 전   \n",
              "211386  객실문열자마자 주방쪽바닥은 대리석이고침실쪽은 카페트입니다주방쪽대리석바닥이 요리로인한...    1년 전      1년 전   \n",
              "211395                                직원분들이 친절했고 방이 깨끗합니다    1년 전      1년 전   \n",
              "211399  객실은 생각보다 좋았는데 침대는 그냥 그랬어요36시간 스테이라 오래 머물 수 있는 ...    1년 전      1년 전   \n",
              "211410  모든게 다 만족인데 조싯9시에 먹으러내려갓더니 직원분들이 좀 부족한듯햇어요 커피컵이...    1년 전      1년 전   \n",
              "211412                    객실이나 환경은 깨끗한데 조식 부페가 아니여서 아쉬웠네요    1년 전      1년 전   \n",
              "211416  깔끔하고 넓어요 다만 뷰가 좀 아쉽고 욕조가 없는 점 체크인 대기시간이 긴 점 아쉽...    2년 전      2년 전   \n",
              "211423  키친도구들이 우수하고 좋습니다 객실은 쥬니어스위트 이용했는데 노보텔스위트 보다 약간...    2년 전      2년 전   \n",
              "211437  용산드래곤시티 계속 노보텔에서 묵다가요번에는 새롭게 라며 그랜드머큐어로 방을 잡았습...    2년 전      2년 전   \n",
              "211440     주소가 제대로 나오지 않아서 주차장찾는데 시간이 쫌 걸렸지만 그래도 완전 만족했습니    2년 전      2년 전   \n",
              "211449  꽝입니다이 가격에 여기 다시는 안가죠장점은 딱 하나인데 취사가 가능한거근데 인덕션은...    2년 전      2년 전   \n",
              "211451  2602호 싱크대 수도에서 물이 새어 나오는건 수리를통해 개선 하셔야 될듯 합니다조...    2년 전      2년 전   \n",
              "211452  외관도 내부도 멋지고 체크아웃할때 컵을 하나 깨먹었는데 먼저 다치지않았냐고 물어봐주...    2년 전      2년 전   \n",
              "211482  체크인할때 조금 소통이 안된점이 아쉽네요 편의를 제공해주는것이니 받아들이라는 호텔측...    2년 전      2년 전   \n",
              "211486  가격대비 좋아요 직원들 정말 교육 잘 되있고 체계가 잘잡혀있어서 너무 만족스러웠어요...    2년 전      2년 전   \n",
              "211506  슈페리어 스위트 1박 호캉스 다녀왔습니다용산역에서 호텔 건물까지 이어지도록 되어있어...    3년 전      3년 전   \n",
              "211530                              다좋아요 부족한게없었어서 적을것도적내요    3년 전      3년 전   \n",
              "\n",
              "        length                                 review_spell_check  site  시설  \\\n",
              "211220      49  딱딱한 침대 매트리스부터 높은 베개 침구류가 너무 별로예요  이점만 개선되면 좋을 ...     1   2   \n",
              "211224     174  직원분들 친절도는 좋았으나 바닥에 떨어진 머리카락이 너무 많았어요 저는 다른 건 참...     1   4   \n",
              "211240     326  호텔 방 안에 주방 시설이 있는 게 가장 큰 장점입니다 가까운 아이파크몰에서 먹을 ...     1   9   \n",
              "211251     199  이 개인적으로는 조금 아쉽네요  일반 슈페리어 객실보다는 정말 좋다는 생각은 들지 ...     1   1   \n",
              "211261     325  일요일 4시경 체크인했는데 최저층 9층을 받았습니다 게다가 엘리베이터 바로 앞 객실...     1  10   \n",
              "211273      64  딱 용산 그 정도입니다 너무 기대를 했나 봅니다 그냥 강남 호텔 정도 가격은 저렴한...     1   3   \n",
              "211278      52  그냥 그랬음 침구류 상태가 안 좋아서 교체 요구함 침대 밑에 먹지도 않은 아이스크림...     1   3   \n",
              "211281     352  일단 직원들의 고객 응대와 친절에 높은 점수를 드리고 싶습니다 체크인 때 많이 붐볐...     1   8   \n",
              "211299      59  코로나 19로 취사가 가능한 머큐어를 자주 가게 된다 주니어 객실은 다 좋은데 인덕...     1   1   \n",
              "211322     439  시설도 좋고 세제까지 없는 게 없어요 직원분들도 너무 친절하시고요 다만 온돌바닥이라...     1  15   \n",
              "211334      57  요즘처럼 외부 식당 가기가 어려울 때 객실에서 간단한 조리가 가능한 호텔 좋은데 호...     1   3   \n",
              "211346      82  프런트 직원은 언제나 친절하고 방은 예전보다 청결이 좀 아니었음 다만 애들 있는 윗...     1   3   \n",
              "211361     251  깨끗하고 좋았는데 온도가 너무 아끼는 거 같아요 보통 호텔은 더워서 옷을 반팔 반바...     1   7   \n",
              "211367      33                  룸 컨디션이랑 시설 자체는 괜찮았는데 서비스가 좀 별로였네요     1   2   \n",
              "211383      27                        친절하고 너무 좋았는데 에어컨이 안돼서 더웠어 오     1   2   \n",
              "211386     173  객실 문 열자마자 주방 쪽 바닥은 대리석이고 침실 쪽은 카페트입니다주방쪽대리석바닥이...     1  14   \n",
              "211395      19                                직원분들이 친절했고 방이 깨끗합니다     1   2   \n",
              "211399     363  객실은 생각보다 좋았는데 침대는 그냥 그랬어요 36시간 스테이라 오래 머물 수 있는...     1  11   \n",
              "211410      91  모든 게 다 만족인데 조시 9시에 먹으러 내려갔더니 직원분들이 좀 부족한듯했어요 커...     1   0   \n",
              "211412      31                    객실이나 환경은 깨끗한데 조식 뷔페가 아니어서 아쉬웠네요     1   1   \n",
              "211416      61  깔끔하고 넓어요 다만 뷰가 좀 아쉽고 욕조가 없는 점 체크인 대기시간이 긴 점 아쉽...     1   1   \n",
              "211423     142  키친 도구들이 우수하고 좋습니다 객실은 주니어 스위트 이용했는데 노보텔 스위트 보다...     1   5   \n",
              "211437     456  용산 드래건 시티 계속 노보텔에서 묵다가 요번에는 새롭게 하며 그랜드 머큐어로 방을...     1  17   \n",
              "211440      46   주소가 제대로 나오지 않아서 주차장 찾는데 시간이 좀 걸렸지만 그래도 완전히 만족했습니     1   2   \n",
              "211449     129  꽝입니다 이 가격에 여기 다시는 안 가죠 장점은 딱 하나인데 취사가 가능한 거 근데...     1   3   \n",
              "211451     100  2602호 싱크대 수도에서 물이 새어 나오는 건 수리를 통해 개선하셔야 될 듯합니다...     1   0   \n",
              "211452     194  외관도 내부도 멋지고 체크아웃할 때 컵을 하나 깨 먹었는데 먼저 다치지 않았냐고 물...     1   5   \n",
              "211482      72  체크인할 때 조금 소통이 안된 점이 아쉽네요 편의를 제공해주는 것이니 받아들이라는 ...     1   2   \n",
              "211486     363  가격 대비 좋아요 직원들 정말 교육 잘 돼있고 체계가 잘 잡혀있어서 너무 만족스러웠...     1   6   \n",
              "211506     474  슈페리어 스위트 1박 호캉스 다녀왔습니다 용산역에서 호텔 건물까지 이어지도록 되어있...     1  12   \n",
              "211530      21                          다 좋아요 부족한 게 없어서 적을 것도 적네요     1   0   \n",
              "\n",
              "        서비스  위치  가격  label  label_pred  label_proba  sentiment    sent_proba  \\\n",
              "211220    0   0   0      1           1     0.999319          0  1.336924e-01   \n",
              "211224    3   0   2      1           1     0.987286          0  3.562123e-04   \n",
              "211240    4   1   0      1           1     0.999946          0  6.626490e-02   \n",
              "211251    1   0   0      2           2     0.834737          0  3.848027e-04   \n",
              "211261    4   0   0      1           1     0.999998          0  2.460166e-03   \n",
              "211273    0   3   1      3           3     0.901945          0  1.649254e-02   \n",
              "211278    0   0   0      1           1     0.999661          0  5.939710e-02   \n",
              "211281    5   2   0      1           1     0.999314          0  1.264925e-03   \n",
              "211299    0   1   0      3           3     0.605423          0  4.772744e-01   \n",
              "211322    5   0   1      1           1     0.999999          0  9.186754e-05   \n",
              "211334    0   1   0      1           1     0.988859          0  4.083203e-01   \n",
              "211346    4   0   0      2           2     0.999361          0  8.371344e-02   \n",
              "211361    0   1   0      1           1     1.000000          0  9.841360e-04   \n",
              "211367    1   1   0      1           1     0.669029          0  1.288524e-01   \n",
              "211383    1   0   0      1           1     0.937551          0  4.763223e-01   \n",
              "211386    0   0   0      1           1     1.000000          0  1.579232e-01   \n",
              "211395    2   1   0      2           2     0.780760          0  4.246884e-01   \n",
              "211399    7   3   0      1           1     0.991327          0  2.503589e-07   \n",
              "211410    2   1   0      2           2     0.974385          0  2.301837e-01   \n",
              "211412    1   0   0      2           2     0.845362          0  3.191029e-01   \n",
              "211416    2   1   0      2           2     0.395276          0  4.994381e-01   \n",
              "211423    3   0   0      1           1     0.969533          0  1.066844e-01   \n",
              "211437    4   0   0      1           1     1.000000          0  6.616569e-08   \n",
              "211440    1   0   0      1           1     0.947845          0  1.673817e-01   \n",
              "211449    1   1   2      1           4     0.931283          0  2.379601e-02   \n",
              "211451    2   0   0      2           2     0.994566          0  1.950704e-01   \n",
              "211452    3   1   0      1           1     0.999965          0  4.890619e-01   \n",
              "211482    1   1   0      1           1     0.869180          0  2.499194e-01   \n",
              "211486    4   4   3      1           1     0.999850          0  4.077246e-02   \n",
              "211506    6   6   0      1           1     0.997838          0  7.794117e-03   \n",
              "211530    0   0   0      0           0     0.908421          0  4.694251e-01   \n",
              "\n",
              "        hotelcount  \n",
              "211220         325  \n",
              "211224         325  \n",
              "211240         325  \n",
              "211251         325  \n",
              "211261         325  \n",
              "211273         325  \n",
              "211278         325  \n",
              "211281         325  \n",
              "211299         325  \n",
              "211322         325  \n",
              "211334         325  \n",
              "211346         325  \n",
              "211361         325  \n",
              "211367         325  \n",
              "211383         325  \n",
              "211386         325  \n",
              "211395         325  \n",
              "211399         325  \n",
              "211410         325  \n",
              "211412         325  \n",
              "211416         325  \n",
              "211423         325  \n",
              "211437         325  \n",
              "211440         325  \n",
              "211449         325  \n",
              "211451         325  \n",
              "211452         325  \n",
              "211482         325  \n",
              "211486         325  \n",
              "211506         325  \n",
              "211530         325  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-e86bc49d-0d7f-483d-a119-c066a20102e0\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>hotel</th>\n",
              "      <th>star</th>\n",
              "      <th>review</th>\n",
              "      <th>date</th>\n",
              "      <th>real_date</th>\n",
              "      <th>length</th>\n",
              "      <th>review_spell_check</th>\n",
              "      <th>site</th>\n",
              "      <th>시설</th>\n",
              "      <th>서비스</th>\n",
              "      <th>위치</th>\n",
              "      <th>가격</th>\n",
              "      <th>label</th>\n",
              "      <th>label_pred</th>\n",
              "      <th>label_proba</th>\n",
              "      <th>sentiment</th>\n",
              "      <th>sent_proba</th>\n",
              "      <th>hotelcount</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>211220</th>\n",
              "      <td>그랜드 머큐어 앰배서더 호텔앤레지던스</td>\n",
              "      <td>4</td>\n",
              "      <td>딱딱한 침대 매트리스부터 높은 베개 침구류가 너무 별로예요  이점만 개선되면 좋을것같아요</td>\n",
              "      <td>2개월 전</td>\n",
              "      <td>2개월 전</td>\n",
              "      <td>49</td>\n",
              "      <td>딱딱한 침대 매트리스부터 높은 베개 침구류가 너무 별로예요  이점만 개선되면 좋을 ...</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0.999319</td>\n",
              "      <td>0</td>\n",
              "      <td>1.336924e-01</td>\n",
              "      <td>325</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>211224</th>\n",
              "      <td>그랜드 머큐어 앰배서더 호텔앤레지던스</td>\n",
              "      <td>4</td>\n",
              "      <td>직원분들 친절도는 좋았으나 바닥에 떨어진 머리카락이 너무 많았어요 저는 다른건 참아...</td>\n",
              "      <td>2개월 전</td>\n",
              "      <td>2개월 전</td>\n",
              "      <td>174</td>\n",
              "      <td>직원분들 친절도는 좋았으나 바닥에 떨어진 머리카락이 너무 많았어요 저는 다른 건 참...</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0.987286</td>\n",
              "      <td>0</td>\n",
              "      <td>3.562123e-04</td>\n",
              "      <td>325</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>211240</th>\n",
              "      <td>그랜드 머큐어 앰배서더 호텔앤레지던스</td>\n",
              "      <td>5</td>\n",
              "      <td>호텔 방 안에 주방 시설이 있는 게 가장 큰 장점입니다 가까운 아이파크몰에서 먹을 ...</td>\n",
              "      <td>6개월 전</td>\n",
              "      <td>6개월 전</td>\n",
              "      <td>326</td>\n",
              "      <td>호텔 방 안에 주방 시설이 있는 게 가장 큰 장점입니다 가까운 아이파크몰에서 먹을 ...</td>\n",
              "      <td>1</td>\n",
              "      <td>9</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0.999946</td>\n",
              "      <td>0</td>\n",
              "      <td>6.626490e-02</td>\n",
              "      <td>325</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>211251</th>\n",
              "      <td>그랜드 머큐어 앰배서더 호텔앤레지던스</td>\n",
              "      <td>2</td>\n",
              "      <td>음개인적으로는 조금 아쉽네요  일반 슈페리어 객실보다는 완전 좋다라는 생각은 들지 ...</td>\n",
              "      <td>9개월 전</td>\n",
              "      <td>9개월 전</td>\n",
              "      <td>199</td>\n",
              "      <td>이 개인적으로는 조금 아쉽네요  일반 슈페리어 객실보다는 정말 좋다는 생각은 들지 ...</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>0.834737</td>\n",
              "      <td>0</td>\n",
              "      <td>3.848027e-04</td>\n",
              "      <td>325</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>211261</th>\n",
              "      <td>그랜드 머큐어 앰배서더 호텔앤레지던스</td>\n",
              "      <td>4</td>\n",
              "      <td>일요일 4시경 체크인 했는데 최저층 9층을 받았습니다 게다가 엘리베이터 바로 앞 객...</td>\n",
              "      <td>10개월 전</td>\n",
              "      <td>10개월 전</td>\n",
              "      <td>325</td>\n",
              "      <td>일요일 4시경 체크인했는데 최저층 9층을 받았습니다 게다가 엘리베이터 바로 앞 객실...</td>\n",
              "      <td>1</td>\n",
              "      <td>10</td>\n",
              "      <td>4</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0.999998</td>\n",
              "      <td>0</td>\n",
              "      <td>2.460166e-03</td>\n",
              "      <td>325</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>211273</th>\n",
              "      <td>그랜드 머큐어 앰배서더 호텔앤레지던스</td>\n",
              "      <td>3</td>\n",
              "      <td>딱용산그정도입니다 너무기대를했나봅니다 그냥 강남호텔정도 가격은저렴한데 너무상류호텔따...</td>\n",
              "      <td>11개월 전</td>\n",
              "      <td>11개월 전</td>\n",
              "      <td>64</td>\n",
              "      <td>딱 용산 그 정도입니다 너무 기대를 했나 봅니다 그냥 강남 호텔 정도 가격은 저렴한...</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>0.901945</td>\n",
              "      <td>0</td>\n",
              "      <td>1.649254e-02</td>\n",
              "      <td>325</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>211278</th>\n",
              "      <td>그랜드 머큐어 앰배서더 호텔앤레지던스</td>\n",
              "      <td>4</td>\n",
              "      <td>그냥 그랬음침구류 상태가 안좋아서교체요구함침대밑에먹지도 않은 아이스크림 막대기가 있...</td>\n",
              "      <td>11개월 전</td>\n",
              "      <td>11개월 전</td>\n",
              "      <td>52</td>\n",
              "      <td>그냥 그랬음 침구류 상태가 안 좋아서 교체 요구함 침대 밑에 먹지도 않은 아이스크림...</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0.999661</td>\n",
              "      <td>0</td>\n",
              "      <td>5.939710e-02</td>\n",
              "      <td>325</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>211281</th>\n",
              "      <td>그랜드 머큐어 앰배서더 호텔앤레지던스</td>\n",
              "      <td>5</td>\n",
              "      <td>일단 직원들의 고객응대와 친절에 높은 점수를 드리고 싶습니다 체크인때 많이 붐볐지만...</td>\n",
              "      <td>1년 전</td>\n",
              "      <td>1년 전</td>\n",
              "      <td>352</td>\n",
              "      <td>일단 직원들의 고객 응대와 친절에 높은 점수를 드리고 싶습니다 체크인 때 많이 붐볐...</td>\n",
              "      <td>1</td>\n",
              "      <td>8</td>\n",
              "      <td>5</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0.999314</td>\n",
              "      <td>0</td>\n",
              "      <td>1.264925e-03</td>\n",
              "      <td>325</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>211299</th>\n",
              "      <td>그랜드 머큐어 앰배서더 호텔앤레지던스</td>\n",
              "      <td>5</td>\n",
              "      <td>코로나19로 취사가 가능한 머큐어를 자주 가게된다주니어 객실은 다 좋은데 인덕션 화...</td>\n",
              "      <td>1년 전</td>\n",
              "      <td>1년 전</td>\n",
              "      <td>59</td>\n",
              "      <td>코로나 19로 취사가 가능한 머큐어를 자주 가게 된다 주니어 객실은 다 좋은데 인덕...</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>0.605423</td>\n",
              "      <td>0</td>\n",
              "      <td>4.772744e-01</td>\n",
              "      <td>325</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>211322</th>\n",
              "      <td>그랜드 머큐어 앰배서더 호텔앤레지던스</td>\n",
              "      <td>4</td>\n",
              "      <td>시설도 좋고 세제까지 없는게없어요 직원분들도 넘 친절하시구요 다만 온돌바닥이라 따로...</td>\n",
              "      <td>1년 전</td>\n",
              "      <td>1년 전</td>\n",
              "      <td>439</td>\n",
              "      <td>시설도 좋고 세제까지 없는 게 없어요 직원분들도 너무 친절하시고요 다만 온돌바닥이라...</td>\n",
              "      <td>1</td>\n",
              "      <td>15</td>\n",
              "      <td>5</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0.999999</td>\n",
              "      <td>0</td>\n",
              "      <td>9.186754e-05</td>\n",
              "      <td>325</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>211334</th>\n",
              "      <td>그랜드 머큐어 앰배서더 호텔앤레지던스</td>\n",
              "      <td>5</td>\n",
              "      <td>요즘처럼 외부식당 가기가 어려울때 객실에서 간단한 조리가 가능한 호텔 좋은데 호텔요...</td>\n",
              "      <td>1년 전</td>\n",
              "      <td>1년 전</td>\n",
              "      <td>57</td>\n",
              "      <td>요즘처럼 외부 식당 가기가 어려울 때 객실에서 간단한 조리가 가능한 호텔 좋은데 호...</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0.988859</td>\n",
              "      <td>0</td>\n",
              "      <td>4.083203e-01</td>\n",
              "      <td>325</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>211346</th>\n",
              "      <td>그랜드 머큐어 앰배서더 호텔앤레지던스</td>\n",
              "      <td>5</td>\n",
              "      <td>프런트 직원은 언제나 친절하고 방은 예전보다 청결이 좀 아니었음 다만 애들있는 윗방...</td>\n",
              "      <td>1년 전</td>\n",
              "      <td>1년 전</td>\n",
              "      <td>82</td>\n",
              "      <td>프런트 직원은 언제나 친절하고 방은 예전보다 청결이 좀 아니었음 다만 애들 있는 윗...</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>4</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>0.999361</td>\n",
              "      <td>0</td>\n",
              "      <td>8.371344e-02</td>\n",
              "      <td>325</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>211361</th>\n",
              "      <td>그랜드 머큐어 앰배서더 호텔앤레지던스</td>\n",
              "      <td>4</td>\n",
              "      <td>깨끗하고 좋았는데 온도가 너무 아끼는거 같아요보통 호텔은 더워서 옷을 반팔 반바지 ...</td>\n",
              "      <td>1년 전</td>\n",
              "      <td>1년 전</td>\n",
              "      <td>251</td>\n",
              "      <td>깨끗하고 좋았는데 온도가 너무 아끼는 거 같아요 보통 호텔은 더워서 옷을 반팔 반바...</td>\n",
              "      <td>1</td>\n",
              "      <td>7</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0</td>\n",
              "      <td>9.841360e-04</td>\n",
              "      <td>325</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>211367</th>\n",
              "      <td>그랜드 머큐어 앰배서더 호텔앤레지던스</td>\n",
              "      <td>4</td>\n",
              "      <td>룸 컨디션이랑 시설 자체는 괜찮았는데 서비스가 좀 별로였네요</td>\n",
              "      <td>1년 전</td>\n",
              "      <td>1년 전</td>\n",
              "      <td>33</td>\n",
              "      <td>룸 컨디션이랑 시설 자체는 괜찮았는데 서비스가 좀 별로였네요</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0.669029</td>\n",
              "      <td>0</td>\n",
              "      <td>1.288524e-01</td>\n",
              "      <td>325</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>211383</th>\n",
              "      <td>그랜드 머큐어 앰배서더 호텔앤레지던스</td>\n",
              "      <td>4</td>\n",
              "      <td>친절하고 너무 좋았는데 에어컨이 안되서 더웠어오</td>\n",
              "      <td>1년 전</td>\n",
              "      <td>1년 전</td>\n",
              "      <td>27</td>\n",
              "      <td>친절하고 너무 좋았는데 에어컨이 안돼서 더웠어 오</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0.937551</td>\n",
              "      <td>0</td>\n",
              "      <td>4.763223e-01</td>\n",
              "      <td>325</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>211386</th>\n",
              "      <td>그랜드 머큐어 앰배서더 호텔앤레지던스</td>\n",
              "      <td>4</td>\n",
              "      <td>객실문열자마자 주방쪽바닥은 대리석이고침실쪽은 카페트입니다주방쪽대리석바닥이 요리로인한...</td>\n",
              "      <td>1년 전</td>\n",
              "      <td>1년 전</td>\n",
              "      <td>173</td>\n",
              "      <td>객실 문 열자마자 주방 쪽 바닥은 대리석이고 침실 쪽은 카페트입니다주방쪽대리석바닥이...</td>\n",
              "      <td>1</td>\n",
              "      <td>14</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0</td>\n",
              "      <td>1.579232e-01</td>\n",
              "      <td>325</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>211395</th>\n",
              "      <td>그랜드 머큐어 앰배서더 호텔앤레지던스</td>\n",
              "      <td>5</td>\n",
              "      <td>직원분들이 친절했고 방이 깨끗합니다</td>\n",
              "      <td>1년 전</td>\n",
              "      <td>1년 전</td>\n",
              "      <td>19</td>\n",
              "      <td>직원분들이 친절했고 방이 깨끗합니다</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>0.780760</td>\n",
              "      <td>0</td>\n",
              "      <td>4.246884e-01</td>\n",
              "      <td>325</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>211399</th>\n",
              "      <td>그랜드 머큐어 앰배서더 호텔앤레지던스</td>\n",
              "      <td>3</td>\n",
              "      <td>객실은 생각보다 좋았는데 침대는 그냥 그랬어요36시간 스테이라 오래 머물 수 있는 ...</td>\n",
              "      <td>1년 전</td>\n",
              "      <td>1년 전</td>\n",
              "      <td>363</td>\n",
              "      <td>객실은 생각보다 좋았는데 침대는 그냥 그랬어요 36시간 스테이라 오래 머물 수 있는...</td>\n",
              "      <td>1</td>\n",
              "      <td>11</td>\n",
              "      <td>7</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0.991327</td>\n",
              "      <td>0</td>\n",
              "      <td>2.503589e-07</td>\n",
              "      <td>325</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>211410</th>\n",
              "      <td>그랜드 머큐어 앰배서더 호텔앤레지던스</td>\n",
              "      <td>5</td>\n",
              "      <td>모든게 다 만족인데 조싯9시에 먹으러내려갓더니 직원분들이 좀 부족한듯햇어요 커피컵이...</td>\n",
              "      <td>1년 전</td>\n",
              "      <td>1년 전</td>\n",
              "      <td>91</td>\n",
              "      <td>모든 게 다 만족인데 조시 9시에 먹으러 내려갔더니 직원분들이 좀 부족한듯했어요 커...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>0.974385</td>\n",
              "      <td>0</td>\n",
              "      <td>2.301837e-01</td>\n",
              "      <td>325</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>211412</th>\n",
              "      <td>그랜드 머큐어 앰배서더 호텔앤레지던스</td>\n",
              "      <td>5</td>\n",
              "      <td>객실이나 환경은 깨끗한데 조식 부페가 아니여서 아쉬웠네요</td>\n",
              "      <td>1년 전</td>\n",
              "      <td>1년 전</td>\n",
              "      <td>31</td>\n",
              "      <td>객실이나 환경은 깨끗한데 조식 뷔페가 아니어서 아쉬웠네요</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>0.845362</td>\n",
              "      <td>0</td>\n",
              "      <td>3.191029e-01</td>\n",
              "      <td>325</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>211416</th>\n",
              "      <td>그랜드 머큐어 앰배서더 호텔앤레지던스</td>\n",
              "      <td>5</td>\n",
              "      <td>깔끔하고 넓어요 다만 뷰가 좀 아쉽고 욕조가 없는 점 체크인 대기시간이 긴 점 아쉽...</td>\n",
              "      <td>2년 전</td>\n",
              "      <td>2년 전</td>\n",
              "      <td>61</td>\n",
              "      <td>깔끔하고 넓어요 다만 뷰가 좀 아쉽고 욕조가 없는 점 체크인 대기시간이 긴 점 아쉽...</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>0.395276</td>\n",
              "      <td>0</td>\n",
              "      <td>4.994381e-01</td>\n",
              "      <td>325</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>211423</th>\n",
              "      <td>그랜드 머큐어 앰배서더 호텔앤레지던스</td>\n",
              "      <td>5</td>\n",
              "      <td>키친도구들이 우수하고 좋습니다 객실은 쥬니어스위트 이용했는데 노보텔스위트 보다 약간...</td>\n",
              "      <td>2년 전</td>\n",
              "      <td>2년 전</td>\n",
              "      <td>142</td>\n",
              "      <td>키친 도구들이 우수하고 좋습니다 객실은 주니어 스위트 이용했는데 노보텔 스위트 보다...</td>\n",
              "      <td>1</td>\n",
              "      <td>5</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0.969533</td>\n",
              "      <td>0</td>\n",
              "      <td>1.066844e-01</td>\n",
              "      <td>325</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>211437</th>\n",
              "      <td>그랜드 머큐어 앰배서더 호텔앤레지던스</td>\n",
              "      <td>4</td>\n",
              "      <td>용산드래곤시티 계속 노보텔에서 묵다가요번에는 새롭게 라며 그랜드머큐어로 방을 잡았습...</td>\n",
              "      <td>2년 전</td>\n",
              "      <td>2년 전</td>\n",
              "      <td>456</td>\n",
              "      <td>용산 드래건 시티 계속 노보텔에서 묵다가 요번에는 새롭게 하며 그랜드 머큐어로 방을...</td>\n",
              "      <td>1</td>\n",
              "      <td>17</td>\n",
              "      <td>4</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0</td>\n",
              "      <td>6.616569e-08</td>\n",
              "      <td>325</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>211440</th>\n",
              "      <td>그랜드 머큐어 앰배서더 호텔앤레지던스</td>\n",
              "      <td>5</td>\n",
              "      <td>주소가 제대로 나오지 않아서 주차장찾는데 시간이 쫌 걸렸지만 그래도 완전 만족했습니</td>\n",
              "      <td>2년 전</td>\n",
              "      <td>2년 전</td>\n",
              "      <td>46</td>\n",
              "      <td>주소가 제대로 나오지 않아서 주차장 찾는데 시간이 좀 걸렸지만 그래도 완전히 만족했습니</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0.947845</td>\n",
              "      <td>0</td>\n",
              "      <td>1.673817e-01</td>\n",
              "      <td>325</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>211449</th>\n",
              "      <td>그랜드 머큐어 앰배서더 호텔앤레지던스</td>\n",
              "      <td>3</td>\n",
              "      <td>꽝입니다이 가격에 여기 다시는 안가죠장점은 딱 하나인데 취사가 가능한거근데 인덕션은...</td>\n",
              "      <td>2년 전</td>\n",
              "      <td>2년 전</td>\n",
              "      <td>129</td>\n",
              "      <td>꽝입니다 이 가격에 여기 다시는 안 가죠 장점은 딱 하나인데 취사가 가능한 거 근데...</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>0.931283</td>\n",
              "      <td>0</td>\n",
              "      <td>2.379601e-02</td>\n",
              "      <td>325</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>211451</th>\n",
              "      <td>그랜드 머큐어 앰배서더 호텔앤레지던스</td>\n",
              "      <td>4</td>\n",
              "      <td>2602호 싱크대 수도에서 물이 새어 나오는건 수리를통해 개선 하셔야 될듯 합니다조...</td>\n",
              "      <td>2년 전</td>\n",
              "      <td>2년 전</td>\n",
              "      <td>100</td>\n",
              "      <td>2602호 싱크대 수도에서 물이 새어 나오는 건 수리를 통해 개선하셔야 될 듯합니다...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>0.994566</td>\n",
              "      <td>0</td>\n",
              "      <td>1.950704e-01</td>\n",
              "      <td>325</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>211452</th>\n",
              "      <td>그랜드 머큐어 앰배서더 호텔앤레지던스</td>\n",
              "      <td>5</td>\n",
              "      <td>외관도 내부도 멋지고 체크아웃할때 컵을 하나 깨먹었는데 먼저 다치지않았냐고 물어봐주...</td>\n",
              "      <td>2년 전</td>\n",
              "      <td>2년 전</td>\n",
              "      <td>194</td>\n",
              "      <td>외관도 내부도 멋지고 체크아웃할 때 컵을 하나 깨 먹었는데 먼저 다치지 않았냐고 물...</td>\n",
              "      <td>1</td>\n",
              "      <td>5</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0.999965</td>\n",
              "      <td>0</td>\n",
              "      <td>4.890619e-01</td>\n",
              "      <td>325</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>211482</th>\n",
              "      <td>그랜드 머큐어 앰배서더 호텔앤레지던스</td>\n",
              "      <td>4</td>\n",
              "      <td>체크인할때 조금 소통이 안된점이 아쉽네요 편의를 제공해주는것이니 받아들이라는 호텔측...</td>\n",
              "      <td>2년 전</td>\n",
              "      <td>2년 전</td>\n",
              "      <td>72</td>\n",
              "      <td>체크인할 때 조금 소통이 안된 점이 아쉽네요 편의를 제공해주는 것이니 받아들이라는 ...</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0.869180</td>\n",
              "      <td>0</td>\n",
              "      <td>2.499194e-01</td>\n",
              "      <td>325</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>211486</th>\n",
              "      <td>그랜드 머큐어 앰배서더 호텔앤레지던스</td>\n",
              "      <td>4</td>\n",
              "      <td>가격대비 좋아요 직원들 정말 교육 잘 되있고 체계가 잘잡혀있어서 너무 만족스러웠어요...</td>\n",
              "      <td>2년 전</td>\n",
              "      <td>2년 전</td>\n",
              "      <td>363</td>\n",
              "      <td>가격 대비 좋아요 직원들 정말 교육 잘 돼있고 체계가 잘 잡혀있어서 너무 만족스러웠...</td>\n",
              "      <td>1</td>\n",
              "      <td>6</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0.999850</td>\n",
              "      <td>0</td>\n",
              "      <td>4.077246e-02</td>\n",
              "      <td>325</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>211506</th>\n",
              "      <td>그랜드 머큐어 앰배서더 호텔앤레지던스</td>\n",
              "      <td>5</td>\n",
              "      <td>슈페리어 스위트 1박 호캉스 다녀왔습니다용산역에서 호텔 건물까지 이어지도록 되어있어...</td>\n",
              "      <td>3년 전</td>\n",
              "      <td>3년 전</td>\n",
              "      <td>474</td>\n",
              "      <td>슈페리어 스위트 1박 호캉스 다녀왔습니다 용산역에서 호텔 건물까지 이어지도록 되어있...</td>\n",
              "      <td>1</td>\n",
              "      <td>12</td>\n",
              "      <td>6</td>\n",
              "      <td>6</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0.997838</td>\n",
              "      <td>0</td>\n",
              "      <td>7.794117e-03</td>\n",
              "      <td>325</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>211530</th>\n",
              "      <td>그랜드 머큐어 앰배서더 호텔앤레지던스</td>\n",
              "      <td>5</td>\n",
              "      <td>다좋아요 부족한게없었어서 적을것도적내요</td>\n",
              "      <td>3년 전</td>\n",
              "      <td>3년 전</td>\n",
              "      <td>21</td>\n",
              "      <td>다 좋아요 부족한 게 없어서 적을 것도 적네요</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.908421</td>\n",
              "      <td>0</td>\n",
              "      <td>4.694251e-01</td>\n",
              "      <td>325</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-e86bc49d-0d7f-483d-a119-c066a20102e0')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-e86bc49d-0d7f-483d-a119-c066a20102e0 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-e86bc49d-0d7f-483d-a119-c066a20102e0');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "gg = df100.groupby(['hotel','label']).mean()\n",
        "ggg = gg.sort_values(['sentiment'])"
      ],
      "metadata": {
        "id": "DzU28L2a73WZ"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "gggg = ggg.reset_index(drop=False)"
      ],
      "metadata": {
        "id": "V1n5AICqHg7P"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "gggg.loc[gggg.label ==1].sort_values(['sentiment'])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "hYbgiGU49L0H",
        "outputId": "b529d57c-b3aa-42ac-9f89-9b234e3b4a38"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                  hotel  label      star      length  site        시설  \\\n",
              "2            케이팝호텔 서울타워      1  3.152778  106.069444   1.0  4.263889   \n",
              "4            영등포 갤럭시 호텔      1  3.241758   54.604396   0.0  2.692308   \n",
              "9            더 리버사이드 호텔      1  3.277344   61.093750   0.0  3.257812   \n",
              "10            노원 노블레스호텔      1  3.507937   77.428571   1.0  3.619048   \n",
              "11                가락 호텔      1  3.395349   57.720930   1.0  2.651163   \n",
              "..                  ...    ...       ...         ...   ...       ...   \n",
              "779          티마크 그랜드 호텔      1  4.770318  122.909894   1.0  4.596290   \n",
              "809  그랜드 인터컨티넨탈 서울 파르나스      1  4.689655  151.310345   1.0  4.425287   \n",
              "832           파크 하얏트 서울      1  4.897059  163.705882   1.0  4.602941   \n",
              "852             로얄호텔 서울      1  4.788732  139.000000   1.0  5.211268   \n",
              "915             포시즌스 호텔      1  4.933333  184.955556   1.0  5.266667   \n",
              "\n",
              "          서비스        위치        가격  label_pred  label_proba  sentiment  \\\n",
              "2    0.833333  0.875000  0.277778    1.013889     0.932238   0.152778   \n",
              "4    0.340659  0.197802  0.043956    0.912088     0.908827   0.230769   \n",
              "9    0.226562  0.417969  0.105469    0.996094     0.938139   0.253906   \n",
              "10   0.753968  0.468254  0.095238    1.031746     0.940496   0.277778   \n",
              "11   0.511628  0.279070  0.209302    1.023256     0.884406   0.279070   \n",
              "..        ...       ...       ...         ...          ...        ...   \n",
              "779  1.179329  1.213781  0.217314    1.045936     0.936223   0.853357   \n",
              "809  1.655172  0.931034  0.080460    1.022989     0.923857   0.862069   \n",
              "832  2.073529  1.161765  0.073529    1.102941     0.904824   0.867647   \n",
              "852  1.507042  1.239437  0.253521    1.014085     0.941651   0.873239   \n",
              "915  2.488889  0.933333  0.155556    1.000000     0.934586   0.888889   \n",
              "\n",
              "     sent_proba  hotelcount  \n",
              "2      0.205478       151.0  \n",
              "4      0.286620       357.0  \n",
              "9      0.280568       736.0  \n",
              "10     0.300266       290.0  \n",
              "11     0.316897       114.0  \n",
              "..          ...         ...  \n",
              "779    0.808124      2629.0  \n",
              "809    0.822231       214.0  \n",
              "832    0.823470       211.0  \n",
              "852    0.829717       173.0  \n",
              "915    0.877474       102.0  \n",
              "\n",
              "[227 rows x 14 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-1faeaf4f-1675-47f3-903d-c4831841e917\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>hotel</th>\n",
              "      <th>label</th>\n",
              "      <th>star</th>\n",
              "      <th>length</th>\n",
              "      <th>site</th>\n",
              "      <th>시설</th>\n",
              "      <th>서비스</th>\n",
              "      <th>위치</th>\n",
              "      <th>가격</th>\n",
              "      <th>label_pred</th>\n",
              "      <th>label_proba</th>\n",
              "      <th>sentiment</th>\n",
              "      <th>sent_proba</th>\n",
              "      <th>hotelcount</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>케이팝호텔 서울타워</td>\n",
              "      <td>1</td>\n",
              "      <td>3.152778</td>\n",
              "      <td>106.069444</td>\n",
              "      <td>1.0</td>\n",
              "      <td>4.263889</td>\n",
              "      <td>0.833333</td>\n",
              "      <td>0.875000</td>\n",
              "      <td>0.277778</td>\n",
              "      <td>1.013889</td>\n",
              "      <td>0.932238</td>\n",
              "      <td>0.152778</td>\n",
              "      <td>0.205478</td>\n",
              "      <td>151.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>영등포 갤럭시 호텔</td>\n",
              "      <td>1</td>\n",
              "      <td>3.241758</td>\n",
              "      <td>54.604396</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2.692308</td>\n",
              "      <td>0.340659</td>\n",
              "      <td>0.197802</td>\n",
              "      <td>0.043956</td>\n",
              "      <td>0.912088</td>\n",
              "      <td>0.908827</td>\n",
              "      <td>0.230769</td>\n",
              "      <td>0.286620</td>\n",
              "      <td>357.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>더 리버사이드 호텔</td>\n",
              "      <td>1</td>\n",
              "      <td>3.277344</td>\n",
              "      <td>61.093750</td>\n",
              "      <td>0.0</td>\n",
              "      <td>3.257812</td>\n",
              "      <td>0.226562</td>\n",
              "      <td>0.417969</td>\n",
              "      <td>0.105469</td>\n",
              "      <td>0.996094</td>\n",
              "      <td>0.938139</td>\n",
              "      <td>0.253906</td>\n",
              "      <td>0.280568</td>\n",
              "      <td>736.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>노원 노블레스호텔</td>\n",
              "      <td>1</td>\n",
              "      <td>3.507937</td>\n",
              "      <td>77.428571</td>\n",
              "      <td>1.0</td>\n",
              "      <td>3.619048</td>\n",
              "      <td>0.753968</td>\n",
              "      <td>0.468254</td>\n",
              "      <td>0.095238</td>\n",
              "      <td>1.031746</td>\n",
              "      <td>0.940496</td>\n",
              "      <td>0.277778</td>\n",
              "      <td>0.300266</td>\n",
              "      <td>290.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>가락 호텔</td>\n",
              "      <td>1</td>\n",
              "      <td>3.395349</td>\n",
              "      <td>57.720930</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2.651163</td>\n",
              "      <td>0.511628</td>\n",
              "      <td>0.279070</td>\n",
              "      <td>0.209302</td>\n",
              "      <td>1.023256</td>\n",
              "      <td>0.884406</td>\n",
              "      <td>0.279070</td>\n",
              "      <td>0.316897</td>\n",
              "      <td>114.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>779</th>\n",
              "      <td>티마크 그랜드 호텔</td>\n",
              "      <td>1</td>\n",
              "      <td>4.770318</td>\n",
              "      <td>122.909894</td>\n",
              "      <td>1.0</td>\n",
              "      <td>4.596290</td>\n",
              "      <td>1.179329</td>\n",
              "      <td>1.213781</td>\n",
              "      <td>0.217314</td>\n",
              "      <td>1.045936</td>\n",
              "      <td>0.936223</td>\n",
              "      <td>0.853357</td>\n",
              "      <td>0.808124</td>\n",
              "      <td>2629.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>809</th>\n",
              "      <td>그랜드 인터컨티넨탈 서울 파르나스</td>\n",
              "      <td>1</td>\n",
              "      <td>4.689655</td>\n",
              "      <td>151.310345</td>\n",
              "      <td>1.0</td>\n",
              "      <td>4.425287</td>\n",
              "      <td>1.655172</td>\n",
              "      <td>0.931034</td>\n",
              "      <td>0.080460</td>\n",
              "      <td>1.022989</td>\n",
              "      <td>0.923857</td>\n",
              "      <td>0.862069</td>\n",
              "      <td>0.822231</td>\n",
              "      <td>214.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>832</th>\n",
              "      <td>파크 하얏트 서울</td>\n",
              "      <td>1</td>\n",
              "      <td>4.897059</td>\n",
              "      <td>163.705882</td>\n",
              "      <td>1.0</td>\n",
              "      <td>4.602941</td>\n",
              "      <td>2.073529</td>\n",
              "      <td>1.161765</td>\n",
              "      <td>0.073529</td>\n",
              "      <td>1.102941</td>\n",
              "      <td>0.904824</td>\n",
              "      <td>0.867647</td>\n",
              "      <td>0.823470</td>\n",
              "      <td>211.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>852</th>\n",
              "      <td>로얄호텔 서울</td>\n",
              "      <td>1</td>\n",
              "      <td>4.788732</td>\n",
              "      <td>139.000000</td>\n",
              "      <td>1.0</td>\n",
              "      <td>5.211268</td>\n",
              "      <td>1.507042</td>\n",
              "      <td>1.239437</td>\n",
              "      <td>0.253521</td>\n",
              "      <td>1.014085</td>\n",
              "      <td>0.941651</td>\n",
              "      <td>0.873239</td>\n",
              "      <td>0.829717</td>\n",
              "      <td>173.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>915</th>\n",
              "      <td>포시즌스 호텔</td>\n",
              "      <td>1</td>\n",
              "      <td>4.933333</td>\n",
              "      <td>184.955556</td>\n",
              "      <td>1.0</td>\n",
              "      <td>5.266667</td>\n",
              "      <td>2.488889</td>\n",
              "      <td>0.933333</td>\n",
              "      <td>0.155556</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.934586</td>\n",
              "      <td>0.888889</td>\n",
              "      <td>0.877474</td>\n",
              "      <td>102.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>227 rows × 14 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-1faeaf4f-1675-47f3-903d-c4831841e917')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-1faeaf4f-1675-47f3-903d-c4831841e917 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-1faeaf4f-1675-47f3-903d-c4831841e917');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "gggg.loc[gggg.label ==2].sort_values(['sentiment'])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "n0ijR_N_I4HQ",
        "outputId": "3ad67c88-15b3-4dc5-e9d3-0f33a8373cef"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                     hotel  label      star      length  site        시설  \\\n",
              "65              더 리버사이드 호텔      2  4.053571   34.464286   0.0  0.607143   \n",
              "78              동대문 바티카 호텔      2  3.833333   66.500000   1.0  0.916667   \n",
              "103          밀리오레 호텔 서울 명동      2  4.266667  148.333333   1.0  2.400000   \n",
              "108              호텔 안테룸 서울      2  4.458333  137.250000   1.0  1.250000   \n",
              "128        코업시티호텔 (오류스테이션)      2  4.048780   74.536585   1.0  0.951220   \n",
              "...                    ...    ...       ...         ...   ...       ...   \n",
              "1069  그랜드 머큐어 앰배서더 호텔앤레지던스      2  4.922481  106.317829   1.0  1.744186   \n",
              "1075       잠실(방이1호)호텔 더 캐슬      2  4.700000   27.950000   0.0  0.350000   \n",
              "1086            도봉 호텔베이204      2  4.804348   62.173913   1.0  1.195652   \n",
              "1096            비스타 워커힐 서울      2  4.885714   88.257143   1.0  1.371429   \n",
              "1118              인사동 썬비호텔      2  4.972973   60.108108   1.0  1.027027   \n",
              "\n",
              "           서비스        위치        가격  label_pred  label_proba  sentiment  \\\n",
              "65    1.642857  0.071429  0.053571    1.928571     0.892877   0.482143   \n",
              "78    2.250000  0.750000  0.000000    1.916667     0.857132   0.500000   \n",
              "103   3.933333  0.933333  0.733333    2.000000     0.929859   0.533333   \n",
              "108   2.833333  0.208333  0.000000    1.958333     0.925465   0.541667   \n",
              "128   2.219512  0.512195  0.195122    1.975610     0.902336   0.560976   \n",
              "...        ...       ...       ...         ...          ...        ...   \n",
              "1069  3.000000  0.232558  0.038760    1.945736     0.926342   0.945736   \n",
              "1075  1.650000  0.000000  0.050000    1.900000     0.935125   0.950000   \n",
              "1086  2.260870  0.282609  0.021739    1.956522     0.948116   0.956522   \n",
              "1096  2.628571  0.142857  0.057143    1.971429     0.923418   0.971429   \n",
              "1118  2.027027  0.405405  0.027027    1.972973     0.868618   1.000000   \n",
              "\n",
              "      sent_proba  hotelcount  \n",
              "65      0.502404       736.0  \n",
              "78      0.442539       121.0  \n",
              "103     0.597302       158.0  \n",
              "108     0.590515       154.0  \n",
              "128     0.522971       329.0  \n",
              "...          ...         ...  \n",
              "1069    0.902667       325.0  \n",
              "1075    0.867856       149.0  \n",
              "1086    0.875415       211.0  \n",
              "1096    0.908146       114.0  \n",
              "1118    0.904343       149.0  \n",
              "\n",
              "[227 rows x 14 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-fe178b30-c7ad-4cfd-af66-14f23bf4d361\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>hotel</th>\n",
              "      <th>label</th>\n",
              "      <th>star</th>\n",
              "      <th>length</th>\n",
              "      <th>site</th>\n",
              "      <th>시설</th>\n",
              "      <th>서비스</th>\n",
              "      <th>위치</th>\n",
              "      <th>가격</th>\n",
              "      <th>label_pred</th>\n",
              "      <th>label_proba</th>\n",
              "      <th>sentiment</th>\n",
              "      <th>sent_proba</th>\n",
              "      <th>hotelcount</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>65</th>\n",
              "      <td>더 리버사이드 호텔</td>\n",
              "      <td>2</td>\n",
              "      <td>4.053571</td>\n",
              "      <td>34.464286</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.607143</td>\n",
              "      <td>1.642857</td>\n",
              "      <td>0.071429</td>\n",
              "      <td>0.053571</td>\n",
              "      <td>1.928571</td>\n",
              "      <td>0.892877</td>\n",
              "      <td>0.482143</td>\n",
              "      <td>0.502404</td>\n",
              "      <td>736.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>78</th>\n",
              "      <td>동대문 바티카 호텔</td>\n",
              "      <td>2</td>\n",
              "      <td>3.833333</td>\n",
              "      <td>66.500000</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.916667</td>\n",
              "      <td>2.250000</td>\n",
              "      <td>0.750000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.916667</td>\n",
              "      <td>0.857132</td>\n",
              "      <td>0.500000</td>\n",
              "      <td>0.442539</td>\n",
              "      <td>121.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>103</th>\n",
              "      <td>밀리오레 호텔 서울 명동</td>\n",
              "      <td>2</td>\n",
              "      <td>4.266667</td>\n",
              "      <td>148.333333</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2.400000</td>\n",
              "      <td>3.933333</td>\n",
              "      <td>0.933333</td>\n",
              "      <td>0.733333</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>0.929859</td>\n",
              "      <td>0.533333</td>\n",
              "      <td>0.597302</td>\n",
              "      <td>158.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>108</th>\n",
              "      <td>호텔 안테룸 서울</td>\n",
              "      <td>2</td>\n",
              "      <td>4.458333</td>\n",
              "      <td>137.250000</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.250000</td>\n",
              "      <td>2.833333</td>\n",
              "      <td>0.208333</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.958333</td>\n",
              "      <td>0.925465</td>\n",
              "      <td>0.541667</td>\n",
              "      <td>0.590515</td>\n",
              "      <td>154.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>128</th>\n",
              "      <td>코업시티호텔 (오류스테이션)</td>\n",
              "      <td>2</td>\n",
              "      <td>4.048780</td>\n",
              "      <td>74.536585</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.951220</td>\n",
              "      <td>2.219512</td>\n",
              "      <td>0.512195</td>\n",
              "      <td>0.195122</td>\n",
              "      <td>1.975610</td>\n",
              "      <td>0.902336</td>\n",
              "      <td>0.560976</td>\n",
              "      <td>0.522971</td>\n",
              "      <td>329.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1069</th>\n",
              "      <td>그랜드 머큐어 앰배서더 호텔앤레지던스</td>\n",
              "      <td>2</td>\n",
              "      <td>4.922481</td>\n",
              "      <td>106.317829</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.744186</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>0.232558</td>\n",
              "      <td>0.038760</td>\n",
              "      <td>1.945736</td>\n",
              "      <td>0.926342</td>\n",
              "      <td>0.945736</td>\n",
              "      <td>0.902667</td>\n",
              "      <td>325.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1075</th>\n",
              "      <td>잠실(방이1호)호텔 더 캐슬</td>\n",
              "      <td>2</td>\n",
              "      <td>4.700000</td>\n",
              "      <td>27.950000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.350000</td>\n",
              "      <td>1.650000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.050000</td>\n",
              "      <td>1.900000</td>\n",
              "      <td>0.935125</td>\n",
              "      <td>0.950000</td>\n",
              "      <td>0.867856</td>\n",
              "      <td>149.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1086</th>\n",
              "      <td>도봉 호텔베이204</td>\n",
              "      <td>2</td>\n",
              "      <td>4.804348</td>\n",
              "      <td>62.173913</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.195652</td>\n",
              "      <td>2.260870</td>\n",
              "      <td>0.282609</td>\n",
              "      <td>0.021739</td>\n",
              "      <td>1.956522</td>\n",
              "      <td>0.948116</td>\n",
              "      <td>0.956522</td>\n",
              "      <td>0.875415</td>\n",
              "      <td>211.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1096</th>\n",
              "      <td>비스타 워커힐 서울</td>\n",
              "      <td>2</td>\n",
              "      <td>4.885714</td>\n",
              "      <td>88.257143</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.371429</td>\n",
              "      <td>2.628571</td>\n",
              "      <td>0.142857</td>\n",
              "      <td>0.057143</td>\n",
              "      <td>1.971429</td>\n",
              "      <td>0.923418</td>\n",
              "      <td>0.971429</td>\n",
              "      <td>0.908146</td>\n",
              "      <td>114.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1118</th>\n",
              "      <td>인사동 썬비호텔</td>\n",
              "      <td>2</td>\n",
              "      <td>4.972973</td>\n",
              "      <td>60.108108</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.027027</td>\n",
              "      <td>2.027027</td>\n",
              "      <td>0.405405</td>\n",
              "      <td>0.027027</td>\n",
              "      <td>1.972973</td>\n",
              "      <td>0.868618</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.904343</td>\n",
              "      <td>149.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>227 rows × 14 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-fe178b30-c7ad-4cfd-af66-14f23bf4d361')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-fe178b30-c7ad-4cfd-af66-14f23bf4d361 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-fe178b30-c7ad-4cfd-af66-14f23bf4d361');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df100.loc[(df100.hotel == '인사동 썬비호텔') & (df100.서비스 >0) & (df100.sentiment == 0)]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 796
        },
        "id": "fOBJIPUNJEMJ",
        "outputId": "12f4d90a-3e12-4d80-cda7-324ce71926ab"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "           hotel  star                                             review  \\\n",
              "206026  인사동 썬비호텔     3  친절하게 맞아주셨습니다그런데 코로나시대에 온도체크는 안하시더라구요도 생각보다 넓고 ...   \n",
              "206050  인사동 썬비호텔     5  아이들과 서울 나들이를 위해 선택한호텔 입니다 위치는 조용하고 지하철 및 명소들과 ...   \n",
              "206078  인사동 썬비호텔     4  직원분들은 정말친절했습니다엘리베이터는 조금 낡은듯했구객실은 사진과는 다소 차이가욕실...   \n",
              "206093  인사동 썬비호텔     5  세종문화회관에서 공연중인 딸아이와의 1박일단방이커서답답한기분은NO샤워실이랑죄변기가따...   \n",
              "206107  인사동 썬비호텔     4  청결상태는 아주좋았구요서비스도 위치도 좋았습니다만방음이 살짝 아쉬워서 예민하신분들은...   \n",
              "206135  인사동 썬비호텔     4  시설  내부인테리어는 한옥스타일이라 좋았음 주차장면수 부족으로 사전에 호텔에 문의해...   \n",
              "206142  인사동 썬비호텔     5  직원대응은 만족함 호텔입구 인테리어 이쁨 골목만 나오면 바로 인사동 거리로 나오는것...   \n",
              "206143  인사동 썬비호텔     5  길 찾기가 조금 어려웠고 침실에 거울이 없어 화장하기 조금 어려운거 빼고 욕실 깔끔...   \n",
              "\n",
              "        date real_date  length  \\\n",
              "206026  1년 전      1년 전     176   \n",
              "206050  2년 전      2년 전     195   \n",
              "206078  2년 전      2년 전      95   \n",
              "206093  3년 전      3년 전     121   \n",
              "206107  3년 전      3년 전      88   \n",
              "206135  4년 전      4년 전     102   \n",
              "206142  5년 전      5년 전     145   \n",
              "206143  5년 전      5년 전     101   \n",
              "\n",
              "                                       review_spell_check  site  시설  서비스  위치  \\\n",
              "206026  친절하게 맞아주셨습니다 그런데 코로나 시대에 온도 체크는 안 하시더라고 요도 생각보...     1  10    2   2   \n",
              "206050  아이들과 서울 나들이를 위해 선택한 호텔입니다 위치는 조용하고 지하철 및 명소들과 ...     1  10    1   5   \n",
              "206078  직원분들은 정말 친절했습니다 엘리베이터는 조금 낡은듯했고 객실은 사진과는 다소 차이...     1   4    2   1   \n",
              "206093  세종문화회관에서 공연 중인 딸아이와의 1박 일단 방이 커서 답답한 기분은 NO 샤워...     1   5    1   2   \n",
              "206107  청결상태는 아주 좋았고요 서비스도 위치도 좋았습니다만 방음이 살짝 아쉬워서 예민하신...     1   6    1   1   \n",
              "206135  시설  내부 인테리어는 한 옥 스타일이라 좋았음 주차장 면수 부족으로 사전에 호텔에...     1   6    3   0   \n",
              "206142  직원 대응은 만족함 호텔 입구 인테리어 이쁨 골목만 나오면 바로 인사동 거리로 나오...     1   7    1   3   \n",
              "206143  길 찾기가 조금 어려웠고 침실에 거울이 없어 화장하기 조금 어려운 거 빼고 욕실 깔...     1   3    2   0   \n",
              "\n",
              "        가격  label  label_pred  label_proba  sentiment  sent_proba  hotelcount  \n",
              "206026   0      1           1     1.000000          0    0.002231         149  \n",
              "206050   2      1           1     0.999889          0    0.482728         149  \n",
              "206078   0      1           1     0.986347          0    0.010417         149  \n",
              "206093   1      1           1     0.993240          0    0.276538         149  \n",
              "206107   0      1           1     0.999999          0    0.405201         149  \n",
              "206135   0      1           1     0.999979          0    0.059926         149  \n",
              "206142   0      1           1     0.999367          0    0.036765         149  \n",
              "206143   0      1           1     0.973841          0    0.283902         149  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-6d481338-135f-4bc9-8378-5615b0c50eae\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>hotel</th>\n",
              "      <th>star</th>\n",
              "      <th>review</th>\n",
              "      <th>date</th>\n",
              "      <th>real_date</th>\n",
              "      <th>length</th>\n",
              "      <th>review_spell_check</th>\n",
              "      <th>site</th>\n",
              "      <th>시설</th>\n",
              "      <th>서비스</th>\n",
              "      <th>위치</th>\n",
              "      <th>가격</th>\n",
              "      <th>label</th>\n",
              "      <th>label_pred</th>\n",
              "      <th>label_proba</th>\n",
              "      <th>sentiment</th>\n",
              "      <th>sent_proba</th>\n",
              "      <th>hotelcount</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>206026</th>\n",
              "      <td>인사동 썬비호텔</td>\n",
              "      <td>3</td>\n",
              "      <td>친절하게 맞아주셨습니다그런데 코로나시대에 온도체크는 안하시더라구요도 생각보다 넓고 ...</td>\n",
              "      <td>1년 전</td>\n",
              "      <td>1년 전</td>\n",
              "      <td>176</td>\n",
              "      <td>친절하게 맞아주셨습니다 그런데 코로나 시대에 온도 체크는 안 하시더라고 요도 생각보...</td>\n",
              "      <td>1</td>\n",
              "      <td>10</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0</td>\n",
              "      <td>0.002231</td>\n",
              "      <td>149</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>206050</th>\n",
              "      <td>인사동 썬비호텔</td>\n",
              "      <td>5</td>\n",
              "      <td>아이들과 서울 나들이를 위해 선택한호텔 입니다 위치는 조용하고 지하철 및 명소들과 ...</td>\n",
              "      <td>2년 전</td>\n",
              "      <td>2년 전</td>\n",
              "      <td>195</td>\n",
              "      <td>아이들과 서울 나들이를 위해 선택한 호텔입니다 위치는 조용하고 지하철 및 명소들과 ...</td>\n",
              "      <td>1</td>\n",
              "      <td>10</td>\n",
              "      <td>1</td>\n",
              "      <td>5</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0.999889</td>\n",
              "      <td>0</td>\n",
              "      <td>0.482728</td>\n",
              "      <td>149</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>206078</th>\n",
              "      <td>인사동 썬비호텔</td>\n",
              "      <td>4</td>\n",
              "      <td>직원분들은 정말친절했습니다엘리베이터는 조금 낡은듯했구객실은 사진과는 다소 차이가욕실...</td>\n",
              "      <td>2년 전</td>\n",
              "      <td>2년 전</td>\n",
              "      <td>95</td>\n",
              "      <td>직원분들은 정말 친절했습니다 엘리베이터는 조금 낡은듯했고 객실은 사진과는 다소 차이...</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0.986347</td>\n",
              "      <td>0</td>\n",
              "      <td>0.010417</td>\n",
              "      <td>149</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>206093</th>\n",
              "      <td>인사동 썬비호텔</td>\n",
              "      <td>5</td>\n",
              "      <td>세종문화회관에서 공연중인 딸아이와의 1박일단방이커서답답한기분은NO샤워실이랑죄변기가따...</td>\n",
              "      <td>3년 전</td>\n",
              "      <td>3년 전</td>\n",
              "      <td>121</td>\n",
              "      <td>세종문화회관에서 공연 중인 딸아이와의 1박 일단 방이 커서 답답한 기분은 NO 샤워...</td>\n",
              "      <td>1</td>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0.993240</td>\n",
              "      <td>0</td>\n",
              "      <td>0.276538</td>\n",
              "      <td>149</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>206107</th>\n",
              "      <td>인사동 썬비호텔</td>\n",
              "      <td>4</td>\n",
              "      <td>청결상태는 아주좋았구요서비스도 위치도 좋았습니다만방음이 살짝 아쉬워서 예민하신분들은...</td>\n",
              "      <td>3년 전</td>\n",
              "      <td>3년 전</td>\n",
              "      <td>88</td>\n",
              "      <td>청결상태는 아주 좋았고요 서비스도 위치도 좋았습니다만 방음이 살짝 아쉬워서 예민하신...</td>\n",
              "      <td>1</td>\n",
              "      <td>6</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0.999999</td>\n",
              "      <td>0</td>\n",
              "      <td>0.405201</td>\n",
              "      <td>149</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>206135</th>\n",
              "      <td>인사동 썬비호텔</td>\n",
              "      <td>4</td>\n",
              "      <td>시설  내부인테리어는 한옥스타일이라 좋았음 주차장면수 부족으로 사전에 호텔에 문의해...</td>\n",
              "      <td>4년 전</td>\n",
              "      <td>4년 전</td>\n",
              "      <td>102</td>\n",
              "      <td>시설  내부 인테리어는 한 옥 스타일이라 좋았음 주차장 면수 부족으로 사전에 호텔에...</td>\n",
              "      <td>1</td>\n",
              "      <td>6</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0.999979</td>\n",
              "      <td>0</td>\n",
              "      <td>0.059926</td>\n",
              "      <td>149</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>206142</th>\n",
              "      <td>인사동 썬비호텔</td>\n",
              "      <td>5</td>\n",
              "      <td>직원대응은 만족함 호텔입구 인테리어 이쁨 골목만 나오면 바로 인사동 거리로 나오는것...</td>\n",
              "      <td>5년 전</td>\n",
              "      <td>5년 전</td>\n",
              "      <td>145</td>\n",
              "      <td>직원 대응은 만족함 호텔 입구 인테리어 이쁨 골목만 나오면 바로 인사동 거리로 나오...</td>\n",
              "      <td>1</td>\n",
              "      <td>7</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0.999367</td>\n",
              "      <td>0</td>\n",
              "      <td>0.036765</td>\n",
              "      <td>149</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>206143</th>\n",
              "      <td>인사동 썬비호텔</td>\n",
              "      <td>5</td>\n",
              "      <td>길 찾기가 조금 어려웠고 침실에 거울이 없어 화장하기 조금 어려운거 빼고 욕실 깔끔...</td>\n",
              "      <td>5년 전</td>\n",
              "      <td>5년 전</td>\n",
              "      <td>101</td>\n",
              "      <td>길 찾기가 조금 어려웠고 침실에 거울이 없어 화장하기 조금 어려운 거 빼고 욕실 깔...</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0.973841</td>\n",
              "      <td>0</td>\n",
              "      <td>0.283902</td>\n",
              "      <td>149</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-6d481338-135f-4bc9-8378-5615b0c50eae')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-6d481338-135f-4bc9-8378-5615b0c50eae button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-6d481338-135f-4bc9-8378-5615b0c50eae');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "gggg.loc[gggg.label ==3].sort_values(['sentiment'])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "zQ7HHoPvGTvD",
        "outputId": "58bec100-eab7-4af8-eaf0-46f4195b7c85"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "               hotel  label      star      length  site        시설       서비스  \\\n",
              "12            호텔 카파스      3  4.285714   43.285714   1.0  0.714286  0.714286   \n",
              "43        더 리버사이드 호텔      3  3.981481   27.018519   0.0  0.481481  0.333333   \n",
              "73        동대문 바티카 호텔      3  4.000000   97.750000   1.0  1.625000  0.833333   \n",
              "79        케이팝호텔 서울타워      3  3.954545   90.545455   1.0  1.590909  0.954545   \n",
              "114   웨스턴 코업 호텔&레지던스      3  4.156863  120.019608   1.0  2.215686  1.039216   \n",
              "...              ...    ...       ...         ...   ...       ...       ...   \n",
              "1108          호텔 디오레      3  4.500000  120.750000   1.0  2.750000  0.750000   \n",
              "1110       메이필드호텔 서울      3  4.375000   81.875000   1.0  1.250000  0.750000   \n",
              "1112         포시즌스 호텔      3  5.000000  153.000000   1.0  1.000000  0.000000   \n",
              "1114      라이프스타일 S호텔      3  4.687500   56.375000   1.0  0.875000  0.687500   \n",
              "1130        인사동 썬비호텔      3  4.947368   95.526316   1.0  1.789474  1.000000   \n",
              "\n",
              "            위치        가격  label_pred  label_proba  sentiment  sent_proba  \\\n",
              "12    2.000000  0.142857    2.714286     0.834913   0.285714    0.363229   \n",
              "43    1.611111  0.111111    2.703704     0.847837   0.444444    0.452397   \n",
              "73    3.208333  0.208333    2.750000     0.876609   0.500000    0.544054   \n",
              "79    3.590909  0.272727    3.045455     0.922731   0.500000    0.502784   \n",
              "114   5.941176  0.529412    2.862745     0.846141   0.549020    0.556311   \n",
              "...        ...       ...         ...          ...        ...         ...   \n",
              "1108  4.750000  0.000000    3.000000     0.987048   1.000000    0.845839   \n",
              "1110  2.125000  0.250000    2.750000     0.863260   1.000000    0.925795   \n",
              "1112  5.400000  0.000000    3.000000     0.890632   1.000000    0.949408   \n",
              "1114  2.250000  0.187500    2.375000     0.866865   1.000000    0.870256   \n",
              "1130  2.842105  0.157895    3.000000     0.901861   1.000000    0.956271   \n",
              "\n",
              "      hotelcount  \n",
              "12         105.0  \n",
              "43         736.0  \n",
              "73         121.0  \n",
              "79         151.0  \n",
              "114        254.0  \n",
              "...          ...  \n",
              "1108       102.0  \n",
              "1110       113.0  \n",
              "1112       102.0  \n",
              "1114       198.0  \n",
              "1130       149.0  \n",
              "\n",
              "[227 rows x 14 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-80c4ea69-1855-41f5-b2a5-f0079eba302c\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>hotel</th>\n",
              "      <th>label</th>\n",
              "      <th>star</th>\n",
              "      <th>length</th>\n",
              "      <th>site</th>\n",
              "      <th>시설</th>\n",
              "      <th>서비스</th>\n",
              "      <th>위치</th>\n",
              "      <th>가격</th>\n",
              "      <th>label_pred</th>\n",
              "      <th>label_proba</th>\n",
              "      <th>sentiment</th>\n",
              "      <th>sent_proba</th>\n",
              "      <th>hotelcount</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>호텔 카파스</td>\n",
              "      <td>3</td>\n",
              "      <td>4.285714</td>\n",
              "      <td>43.285714</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.714286</td>\n",
              "      <td>0.714286</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>0.142857</td>\n",
              "      <td>2.714286</td>\n",
              "      <td>0.834913</td>\n",
              "      <td>0.285714</td>\n",
              "      <td>0.363229</td>\n",
              "      <td>105.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>43</th>\n",
              "      <td>더 리버사이드 호텔</td>\n",
              "      <td>3</td>\n",
              "      <td>3.981481</td>\n",
              "      <td>27.018519</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.481481</td>\n",
              "      <td>0.333333</td>\n",
              "      <td>1.611111</td>\n",
              "      <td>0.111111</td>\n",
              "      <td>2.703704</td>\n",
              "      <td>0.847837</td>\n",
              "      <td>0.444444</td>\n",
              "      <td>0.452397</td>\n",
              "      <td>736.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>73</th>\n",
              "      <td>동대문 바티카 호텔</td>\n",
              "      <td>3</td>\n",
              "      <td>4.000000</td>\n",
              "      <td>97.750000</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.625000</td>\n",
              "      <td>0.833333</td>\n",
              "      <td>3.208333</td>\n",
              "      <td>0.208333</td>\n",
              "      <td>2.750000</td>\n",
              "      <td>0.876609</td>\n",
              "      <td>0.500000</td>\n",
              "      <td>0.544054</td>\n",
              "      <td>121.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>79</th>\n",
              "      <td>케이팝호텔 서울타워</td>\n",
              "      <td>3</td>\n",
              "      <td>3.954545</td>\n",
              "      <td>90.545455</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.590909</td>\n",
              "      <td>0.954545</td>\n",
              "      <td>3.590909</td>\n",
              "      <td>0.272727</td>\n",
              "      <td>3.045455</td>\n",
              "      <td>0.922731</td>\n",
              "      <td>0.500000</td>\n",
              "      <td>0.502784</td>\n",
              "      <td>151.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>114</th>\n",
              "      <td>웨스턴 코업 호텔&amp;레지던스</td>\n",
              "      <td>3</td>\n",
              "      <td>4.156863</td>\n",
              "      <td>120.019608</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2.215686</td>\n",
              "      <td>1.039216</td>\n",
              "      <td>5.941176</td>\n",
              "      <td>0.529412</td>\n",
              "      <td>2.862745</td>\n",
              "      <td>0.846141</td>\n",
              "      <td>0.549020</td>\n",
              "      <td>0.556311</td>\n",
              "      <td>254.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1108</th>\n",
              "      <td>호텔 디오레</td>\n",
              "      <td>3</td>\n",
              "      <td>4.500000</td>\n",
              "      <td>120.750000</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2.750000</td>\n",
              "      <td>0.750000</td>\n",
              "      <td>4.750000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>0.987048</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.845839</td>\n",
              "      <td>102.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1110</th>\n",
              "      <td>메이필드호텔 서울</td>\n",
              "      <td>3</td>\n",
              "      <td>4.375000</td>\n",
              "      <td>81.875000</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.250000</td>\n",
              "      <td>0.750000</td>\n",
              "      <td>2.125000</td>\n",
              "      <td>0.250000</td>\n",
              "      <td>2.750000</td>\n",
              "      <td>0.863260</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.925795</td>\n",
              "      <td>113.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1112</th>\n",
              "      <td>포시즌스 호텔</td>\n",
              "      <td>3</td>\n",
              "      <td>5.000000</td>\n",
              "      <td>153.000000</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>5.400000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>0.890632</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.949408</td>\n",
              "      <td>102.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1114</th>\n",
              "      <td>라이프스타일 S호텔</td>\n",
              "      <td>3</td>\n",
              "      <td>4.687500</td>\n",
              "      <td>56.375000</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.875000</td>\n",
              "      <td>0.687500</td>\n",
              "      <td>2.250000</td>\n",
              "      <td>0.187500</td>\n",
              "      <td>2.375000</td>\n",
              "      <td>0.866865</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.870256</td>\n",
              "      <td>198.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1130</th>\n",
              "      <td>인사동 썬비호텔</td>\n",
              "      <td>3</td>\n",
              "      <td>4.947368</td>\n",
              "      <td>95.526316</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.789474</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>2.842105</td>\n",
              "      <td>0.157895</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>0.901861</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.956271</td>\n",
              "      <td>149.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>227 rows × 14 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-80c4ea69-1855-41f5-b2a5-f0079eba302c')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-80c4ea69-1855-41f5-b2a5-f0079eba302c button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-80c4ea69-1855-41f5-b2a5-f0079eba302c');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "gggg.loc[gggg.label ==4].sort_values(['sentiment'])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "kIiU1_SgGweK",
        "outputId": "f173874d-44cc-414c-c931-5ee22ee74056"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                     hotel  label      star      length  site        시설  \\\n",
              "0                   해밀톤 호텔      4  3.333333   25.333333   1.0  0.333333   \n",
              "1                  롯데호텔 월드      4  5.000000   32.000000   1.0  0.000000   \n",
              "3                호텔 안테룸 서울      4  4.000000  117.400000   1.0  1.600000   \n",
              "5               영등포 갤럭시 호텔      4  4.000000   19.538462   0.0  0.307692   \n",
              "6                 어반스테이 명동      4  4.000000  123.750000   1.0  0.750000   \n",
              "...                    ...    ...       ...         ...   ...       ...   \n",
              "1101      프레이저 플레이스 센트럴 서울      4  4.166667   29.666667   1.0  0.166667   \n",
              "1100         밀리오레 호텔 서울 명동      4  4.777778   53.000000   1.0  0.888889   \n",
              "1099  그랜드 머큐어 앰배서더 호텔앤레지던스      4  5.000000   78.000000   1.0  1.333333   \n",
              "1113               로얄호텔 서울      4  5.000000   60.000000   1.0  1.000000   \n",
              "1129       잠실(방이1호)호텔 더 캐슬      4  5.000000   43.000000   0.0  1.000000   \n",
              "\n",
              "           서비스        위치        가격  label_pred  label_proba  sentiment  \\\n",
              "0     0.000000  0.333333  2.000000    4.000000     0.996187   0.000000   \n",
              "1     0.000000  0.000000  1.000000    4.000000     0.880190   0.000000   \n",
              "3     1.200000  0.400000  2.200000    3.400000     0.815188   0.200000   \n",
              "5     0.038462  0.384615  1.461538    3.961538     0.916878   0.230769   \n",
              "6     1.500000  0.750000  2.500000    4.000000     0.939486   0.250000   \n",
              "...        ...       ...       ...         ...          ...        ...   \n",
              "1101  0.500000  0.166667  1.333333    4.000000     0.885091   1.000000   \n",
              "1100  0.333333  1.111111  1.888889    3.666667     0.890814   1.000000   \n",
              "1099  1.000000  1.333333  2.333333    4.000000     0.972271   1.000000   \n",
              "1113  0.000000  0.000000  2.000000    4.000000     0.998612   1.000000   \n",
              "1129  0.000000  0.000000  1.000000    1.000000     0.361976   1.000000   \n",
              "\n",
              "      sent_proba  hotelcount  \n",
              "0       0.142409       133.0  \n",
              "1       0.496822       121.0  \n",
              "3       0.242479       154.0  \n",
              "5       0.334486       357.0  \n",
              "6       0.352771       172.0  \n",
              "...          ...         ...  \n",
              "1101    0.812166       221.0  \n",
              "1100    0.816798       158.0  \n",
              "1099    0.835164       325.0  \n",
              "1113    0.802213       173.0  \n",
              "1129    0.995102       149.0  \n",
              "\n",
              "[223 rows x 14 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-5c46c260-823e-452f-bc05-ad87b9c8012e\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>hotel</th>\n",
              "      <th>label</th>\n",
              "      <th>star</th>\n",
              "      <th>length</th>\n",
              "      <th>site</th>\n",
              "      <th>시설</th>\n",
              "      <th>서비스</th>\n",
              "      <th>위치</th>\n",
              "      <th>가격</th>\n",
              "      <th>label_pred</th>\n",
              "      <th>label_proba</th>\n",
              "      <th>sentiment</th>\n",
              "      <th>sent_proba</th>\n",
              "      <th>hotelcount</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>해밀톤 호텔</td>\n",
              "      <td>4</td>\n",
              "      <td>3.333333</td>\n",
              "      <td>25.333333</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.333333</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.333333</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>4.000000</td>\n",
              "      <td>0.996187</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.142409</td>\n",
              "      <td>133.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>롯데호텔 월드</td>\n",
              "      <td>4</td>\n",
              "      <td>5.000000</td>\n",
              "      <td>32.000000</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>4.000000</td>\n",
              "      <td>0.880190</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.496822</td>\n",
              "      <td>121.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>호텔 안테룸 서울</td>\n",
              "      <td>4</td>\n",
              "      <td>4.000000</td>\n",
              "      <td>117.400000</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.600000</td>\n",
              "      <td>1.200000</td>\n",
              "      <td>0.400000</td>\n",
              "      <td>2.200000</td>\n",
              "      <td>3.400000</td>\n",
              "      <td>0.815188</td>\n",
              "      <td>0.200000</td>\n",
              "      <td>0.242479</td>\n",
              "      <td>154.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>영등포 갤럭시 호텔</td>\n",
              "      <td>4</td>\n",
              "      <td>4.000000</td>\n",
              "      <td>19.538462</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.307692</td>\n",
              "      <td>0.038462</td>\n",
              "      <td>0.384615</td>\n",
              "      <td>1.461538</td>\n",
              "      <td>3.961538</td>\n",
              "      <td>0.916878</td>\n",
              "      <td>0.230769</td>\n",
              "      <td>0.334486</td>\n",
              "      <td>357.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>어반스테이 명동</td>\n",
              "      <td>4</td>\n",
              "      <td>4.000000</td>\n",
              "      <td>123.750000</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.750000</td>\n",
              "      <td>1.500000</td>\n",
              "      <td>0.750000</td>\n",
              "      <td>2.500000</td>\n",
              "      <td>4.000000</td>\n",
              "      <td>0.939486</td>\n",
              "      <td>0.250000</td>\n",
              "      <td>0.352771</td>\n",
              "      <td>172.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1101</th>\n",
              "      <td>프레이저 플레이스 센트럴 서울</td>\n",
              "      <td>4</td>\n",
              "      <td>4.166667</td>\n",
              "      <td>29.666667</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.166667</td>\n",
              "      <td>0.500000</td>\n",
              "      <td>0.166667</td>\n",
              "      <td>1.333333</td>\n",
              "      <td>4.000000</td>\n",
              "      <td>0.885091</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.812166</td>\n",
              "      <td>221.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1100</th>\n",
              "      <td>밀리오레 호텔 서울 명동</td>\n",
              "      <td>4</td>\n",
              "      <td>4.777778</td>\n",
              "      <td>53.000000</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.888889</td>\n",
              "      <td>0.333333</td>\n",
              "      <td>1.111111</td>\n",
              "      <td>1.888889</td>\n",
              "      <td>3.666667</td>\n",
              "      <td>0.890814</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.816798</td>\n",
              "      <td>158.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1099</th>\n",
              "      <td>그랜드 머큐어 앰배서더 호텔앤레지던스</td>\n",
              "      <td>4</td>\n",
              "      <td>5.000000</td>\n",
              "      <td>78.000000</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.333333</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.333333</td>\n",
              "      <td>2.333333</td>\n",
              "      <td>4.000000</td>\n",
              "      <td>0.972271</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.835164</td>\n",
              "      <td>325.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1113</th>\n",
              "      <td>로얄호텔 서울</td>\n",
              "      <td>4</td>\n",
              "      <td>5.000000</td>\n",
              "      <td>60.000000</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>4.000000</td>\n",
              "      <td>0.998612</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.802213</td>\n",
              "      <td>173.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1129</th>\n",
              "      <td>잠실(방이1호)호텔 더 캐슬</td>\n",
              "      <td>4</td>\n",
              "      <td>5.000000</td>\n",
              "      <td>43.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.361976</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.995102</td>\n",
              "      <td>149.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>223 rows × 14 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-5c46c260-823e-452f-bc05-ad87b9c8012e')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-5c46c260-823e-452f-bc05-ad87b9c8012e button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-5c46c260-823e-452f-bc05-ad87b9c8012e');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "gggg.loc[gggg.label ==1].sort_values(['sentiment']).hotel[::-1][:5]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "BvAxPKNAzEqW",
        "outputId": "398661bd-dbda-4c74-9593-3c4be65c5c95"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "915               포시즌스 호텔\n",
              "852               로얄호텔 서울\n",
              "832             파크 하얏트 서울\n",
              "809    그랜드 인터컨티넨탈 서울 파르나스\n",
              "779            티마크 그랜드 호텔\n",
              "Name: hotel, dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "gggg.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "uS3Bi5B-6R9L",
        "outputId": "f0dab897-da34-49ba-a505-3e65200f14e0"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 1131 entries, 0 to 1130\n",
            "Data columns (total 14 columns):\n",
            " #   Column       Non-Null Count  Dtype  \n",
            "---  ------       --------------  -----  \n",
            " 0   hotel        1131 non-null   object \n",
            " 1   label        1131 non-null   int64  \n",
            " 2   star         1131 non-null   float64\n",
            " 3   length       1131 non-null   float64\n",
            " 4   site         1131 non-null   float64\n",
            " 5   시설           1131 non-null   float64\n",
            " 6   서비스          1131 non-null   float64\n",
            " 7   위치           1131 non-null   float64\n",
            " 8   가격           1131 non-null   float64\n",
            " 9   label_pred   1131 non-null   float64\n",
            " 10  label_proba  1131 non-null   float64\n",
            " 11  sentiment    1131 non-null   float64\n",
            " 12  sent_proba   1131 non-null   float64\n",
            " 13  hotelcount   1131 non-null   float64\n",
            "dtypes: float64(12), int64(1), object(1)\n",
            "memory usage: 123.8+ KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def recommend(x):\n",
        "  x = float(x)\n",
        "  top = gggg.loc[gggg.label == x].sort_values(['sentiment']).hotel[::-1][:5].to_list()\n",
        "  return top\n",
        "\n",
        "def posre(hotel):\n",
        "  pos = df100.loc[df100.hotel == hotel].sort_values(['sentiment'])[::-1][:1]\n",
        "  return list(pos.review)\n",
        "\n",
        "def negre(hotel):\n",
        "  neg = df100.loc[df100.hotel == hotel].sort_values(['sentiment'])[:1]\n",
        "  return list(neg.review)\n"
      ],
      "metadata": {
        "id": "ZQdtfTJlK3Za"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df100.loc[df100.hotel == '포시즌스 호텔'].sort_values(['sentiment'])[:1]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 212
        },
        "id": "dF1x-Go_KYz_",
        "outputId": "d29af1a6-bee3-43e3-d5db-5527880ad2f2"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "          hotel  star                                             review  \\\n",
              "202586  포시즌스 호텔     4  님들은 저와 마치 엇나간 인연같네요룸업글해줘서 감동해서 방에 올라갔눈데방도 개조은데...   \n",
              "\n",
              "         date real_date  length  \\\n",
              "202586  8개월 전     8개월 전     130   \n",
              "\n",
              "                                       review_spell_check  site  시설  서비스  위치  \\\n",
              "202586  님들은 저와 마치 엇나간 인연 같네요 룸업글해줘서 감동해서 방에 올라갔는데 방도 개...     1   5    0   0   \n",
              "\n",
              "        가격  label  label_pred  label_proba  sentiment  sent_proba  hotelcount  \n",
              "202586   0      1           1          1.0          0    0.421616         102  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-a9e392b7-e1bd-4370-91d5-0e6577d675f4\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>hotel</th>\n",
              "      <th>star</th>\n",
              "      <th>review</th>\n",
              "      <th>date</th>\n",
              "      <th>real_date</th>\n",
              "      <th>length</th>\n",
              "      <th>review_spell_check</th>\n",
              "      <th>site</th>\n",
              "      <th>시설</th>\n",
              "      <th>서비스</th>\n",
              "      <th>위치</th>\n",
              "      <th>가격</th>\n",
              "      <th>label</th>\n",
              "      <th>label_pred</th>\n",
              "      <th>label_proba</th>\n",
              "      <th>sentiment</th>\n",
              "      <th>sent_proba</th>\n",
              "      <th>hotelcount</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>202586</th>\n",
              "      <td>포시즌스 호텔</td>\n",
              "      <td>4</td>\n",
              "      <td>님들은 저와 마치 엇나간 인연같네요룸업글해줘서 감동해서 방에 올라갔눈데방도 개조은데...</td>\n",
              "      <td>8개월 전</td>\n",
              "      <td>8개월 전</td>\n",
              "      <td>130</td>\n",
              "      <td>님들은 저와 마치 엇나간 인연 같네요 룸업글해줘서 감동해서 방에 올라갔는데 방도 개...</td>\n",
              "      <td>1</td>\n",
              "      <td>5</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.421616</td>\n",
              "      <td>102</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-a9e392b7-e1bd-4370-91d5-0e6577d675f4')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-a9e392b7-e1bd-4370-91d5-0e6577d675f4 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-a9e392b7-e1bd-4370-91d5-0e6577d675f4');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 42
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "gggg.loc[gggg.label == 1].sort_values(['sentiment']).hotel[::-1][:5].to_list()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "dTrkd3EoC9Nt",
        "outputId": "99686fc1-99de-4391-c24c-443430acda7e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['포시즌스 호텔', '로얄호텔 서울', '파크 하얏트 서울', '그랜드 인터컨티넨탈 서울 파르나스', '티마크 그랜드 호텔']"
            ]
          },
          "metadata": {},
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(\"호텔 선택 시 가장 중요하게 생각하는 항목을 선택해주세요.\")\n",
        "x = input(\"시설: 1, 서비스: 2, 위치: 3, 가격: 4를 입력하세요.\")\n",
        "print(recommend(x), \"를 추천합니다.\")\n",
        "hotel = input(\"리뷰가 궁금한 호텔 이름을 정확히 입력하세요.\")\n",
        "print(\"긍정 리뷰:\", posre(hotel))\n",
        "print(\"부정 리뷰:\", negre(hotel))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_J8xOULIG9XA",
        "outputId": "f41e999a-91da-45e2-8594-236d506a805f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "호텔 선택 시 가장 중요하게 생각하는 항목을 선택해주세요.\n",
            "시설: 1, 서비스: 2, 위치: 3, 가격: 4를 입력하세요.1\n",
            "['포시즌스 호텔', '로얄호텔 서울', '파크 하얏트 서울', '그랜드 인터컨티넨탈 서울 파르나스', '티마크 그랜드 호텔'] 를 추천합니다.\n",
            "리뷰가 궁금한 호텔 이름을 정확히 입력하세요.포시즌스 호텔\n",
            "긍정 리뷰: ['최고에요  너무 좋았구 사우나 수영 다 한곳에 서 할 수 있어 좋았어요']\n",
            "부정 리뷰: ['님들은 저와 마치 엇나간 인연같네요룸업글해줘서 감동해서 방에 올라갔눈데방도 개조은데어머 글쎄 화장실 변기가 안내려가는거 있져2번이었어서 망정이지 1번이었다면 당신은 영원히 저와 이별할뻔하지만 체인지 하고 즐겁게 보내다 갔서요헬스장 굳']\n"
          ]
        }
      ]
    }
  ],
  "metadata": {
    "colab": {
      "name": "리뷰분류.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "toc_visible": true,
      "include_colab_link": true
    },
    "kernelspec": {
      "display_name": "Python 3",
      "language": "python",
      "name": "python3"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.8.5"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}