BERTopic_2024.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "gpuType": "T4"
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "code",
      "source": [
        "# Set Dependency(Ubuntu) for KoNLpy\n",
        "!apt-get update\n",
        "!apt-get install g++ openjdk-8-jdk python-dev\n",
        "\n",
        "# Install KoNLpy\n",
        "!python3 -m pip instlall --upgrade pip\n",
        "!pip install konlpy"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "eNxnzLUBWGe7",
        "outputId": "244b427c-7ce8-4573-f1bf-c909030052e8"
      },
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\r0% [Working]\r            \rGet:1 https://cloud.r-project.org/bin/linux/ubuntu jammy-cran40/ InRelease [3,626 B]\n",
            "\r0% [Waiting for headers] [Waiting for headers] [1 InRelease 3,626 B/3,626 B 100%] [Connected to r2u.\r0% [Waiting for headers] [Waiting for headers] [Connected to r2u.stat.illinois.edu (192.17.190.167)]\r                                                                                                    \rHit:2 https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64  InRelease\n",
            "\r0% [Waiting for headers] [Waiting for headers] [Connected to r2u.stat.illinois.edu (192.17.190.167)]\r                                                                                                    \rHit:3 http://security.ubuntu.com/ubuntu jammy-security InRelease\n",
            "Hit:4 http://archive.ubuntu.com/ubuntu jammy InRelease\n",
            "Hit:5 http://archive.ubuntu.com/ubuntu jammy-updates InRelease\n",
            "Hit:6 http://archive.ubuntu.com/ubuntu jammy-backports InRelease\n",
            "Ign:7 https://r2u.stat.illinois.edu/ubuntu jammy InRelease\n",
            "Hit:8 https://r2u.stat.illinois.edu/ubuntu jammy Release\n",
            "Hit:9 https://ppa.launchpadcontent.net/deadsnakes/ppa/ubuntu jammy InRelease\n",
            "Hit:10 https://ppa.launchpadcontent.net/graphics-drivers/ppa/ubuntu jammy InRelease\n",
            "Hit:11 https://ppa.launchpadcontent.net/ubuntugis/ppa/ubuntu jammy InRelease\n",
            "Fetched 3,626 B in 3s (1,281 B/s)\n",
            "Reading package lists... Done\n",
            "W: Skipping acquire of configured file 'main/source/Sources' as repository 'https://r2u.stat.illinois.edu/ubuntu jammy InRelease' does not seem to provide it (sources.list entry misspelt?)\n",
            "Reading package lists... Done\n",
            "Building dependency tree... Done\n",
            "Reading state information... Done\n",
            "Package python-dev is not available, but is referred to by another package.\n",
            "This may mean that the package is missing, has been obsoleted, or\n",
            "is only available from another source\n",
            "However the following packages replace it:\n",
            "  python2-dev python2 python-dev-is-python3\n",
            "\n",
            "E: Package 'python-dev' has no installation candidate\n",
            "ERROR: unknown command \"instlall\" - maybe you meant \"install\"\n",
            "Requirement already satisfied: konlpy in /usr/local/lib/python3.10/dist-packages (0.6.0)\n",
            "Requirement already satisfied: JPype1>=0.7.0 in /usr/local/lib/python3.10/dist-packages (from konlpy) (1.5.0)\n",
            "Requirement already satisfied: lxml>=4.1.0 in /usr/local/lib/python3.10/dist-packages (from konlpy) (4.9.4)\n",
            "Requirement already satisfied: numpy>=1.6 in /usr/local/lib/python3.10/dist-packages (from konlpy) (1.26.4)\n",
            "Requirement already satisfied: packaging in /usr/local/lib/python3.10/dist-packages (from JPype1>=0.7.0->konlpy) (24.1)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Korean BERTopic pip install\n",
        "!pip install bertopic[visualization]\n",
        "\n",
        "# Mecab(형태소단위 토큰분리기) 설치\n",
        "!git clone https://github.com/SOMJANG/Mecab-ko-for-Google-Colab.git\n",
        "%cd Mecab-ko-for-Google-Colab\n",
        "!bash install_mecab-ko_on_colab_light_220429.sh"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "R6zkfMU1JC_5",
        "outputId": "09a8b031-8638-4f16-8094-67e78ce20dd9"
      },
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: bertopic[visualization] in /usr/local/lib/python3.10/dist-packages (0.16.3)\n",
            "\u001b[33mWARNING: bertopic 0.16.3 does not provide the extra 'visualization'\u001b[0m\u001b[33m\n",
            "\u001b[0mRequirement already satisfied: hdbscan>=0.8.29 in /usr/local/lib/python3.10/dist-packages (from bertopic[visualization]) (0.8.38.post1)\n",
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            "Requirement already satisfied: nvidia-nvtx-cu12==12.1.105 in /usr/local/lib/python3.10/dist-packages (from torch>=1.11.0->sentence-transformers>=0.4.1->bertopic[visualization]) (12.1.105)\n",
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            "fatal: destination path 'Mecab-ko-for-Google-Colab' already exists and is not an empty directory.\n",
            "/content/Mecab-ko-for-Google-Colab/Mecab-ko-for-Google-Colab\n",
            "Installing konlpy.....\n",
            "Requirement already satisfied: konlpy in /usr/local/lib/python3.10/dist-packages (0.6.0)\n",
            "Requirement already satisfied: JPype1>=0.7.0 in /usr/local/lib/python3.10/dist-packages (from konlpy) (1.5.0)\n",
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            "Requirement already satisfied: packaging in /usr/local/lib/python3.10/dist-packages (from JPype1>=0.7.0->konlpy) (24.1)\n",
            "Done\n",
            "Installing mecab-0.996-ko-0.9.2.tar.gz.....\n",
            "Downloading mecab-0.996-ko-0.9.2.tar.gz.......\n",
            "from https://bitbucket.org/eunjeon/mecab-ko/downloads/mecab-0.996-ko-0.9.2.tar.gz\n",
            "--2024-08-20 17:27:46--  https://bitbucket.org/eunjeon/mecab-ko/downloads/mecab-0.996-ko-0.9.2.tar.gz\n",
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            "Saving to: ‘mecab-0.996-ko-0.9.2.tar.gz.6’\n",
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            "\n",
            "2024-08-20 17:27:47 (3.50 MB/s) - ‘mecab-0.996-ko-0.9.2.tar.gz.6’ saved [1414979/1414979]\n",
            "\n",
            "Done\n",
            "Unpacking mecab-0.996-ko-0.9.2.tar.gz.......\n",
            "Done\n",
            "Change Directory to mecab-0.996-ko-0.9.2.......\n",
            "installing mecab-0.996-ko-0.9.2.tar.gz........\n",
            "configure\n",
            "make\n",
            "make check\n",
            "make install\n",
            "ldconfig\n",
            "Done\n",
            "Change Directory to /content\n",
            "Downloading mecab-ko-dic-2.1.1-20180720.tar.gz.......\n",
            "from https://bitbucket.org/eunjeon/mecab-ko-dic/downloads/mecab-ko-dic-2.1.1-20180720.tar.gz\n",
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            "Resolving bitbucket.org (bitbucket.org)... 104.192.142.25, 104.192.142.26, 104.192.142.24, ...\n",
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            "Resolving bbuseruploads.s3.amazonaws.com (bbuseruploads.s3.amazonaws.com)... 54.231.166.41, 3.5.30.207, 16.182.72.89, ...\n",
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            "Length: 49775061 (47M) [application/x-tar]\n",
            "Saving to: ‘mecab-ko-dic-2.1.1-20180720.tar.gz.6’\n",
            "\n",
            "mecab-ko-dic-2.1.1- 100%[===================>]  47.47M  35.0MB/s    in 1.4s    \n",
            "\n",
            "2024-08-20 17:28:06 (35.0 MB/s) - ‘mecab-ko-dic-2.1.1-20180720.tar.gz.6’ saved [49775061/49775061]\n",
            "\n",
            "Done\n",
            "Unpacking  mecab-ko-dic-2.1.1-20180720.tar.gz.......\n",
            "Done\n",
            "Change Directory to mecab-ko-dic-2.1.1-20180720\n",
            "Done\n",
            "installing........\n",
            "configure\n",
            "make\n",
            "make install\n",
            "bash <(curl -s https://raw.githubusercontent.com/konlpy/konlpy/v0.6.0/scripts/mecab.sh)\n",
            "https://github.com/konlpy/konlpy/issues/395#issue-1099168405 - 2022.01.11\n",
            "Done\n",
            "Install mecab-python\n",
            "Successfully Installed\n",
            "Now you can use Mecab\n",
            "from konlpy.tag import Mecab\n",
            "mecab = Mecab()\n",
            "사용자 사전 추가 방법 : https://bit.ly/3k0ZH53\n",
            "NameError: name 'Tagger' is not defined 오류 발생 시 런타임을 재실행 해주세요\n",
            "블로그에 해결 방법을 남겨주신 tana님 감사합니다.\n",
            "light 버전 작성 : Dogdriip님 ( https://github.com/Dogdriip )\n",
            "문제를 해결해주신 combacsa님 감사합니다.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install git+https://github.com/MaartenGr/BERTopic.git@fix_2100"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "blCrsVZMw2cY",
        "outputId": "676aeade-7431-4a0d-edef-f83c6e805056"
      },
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting git+https://github.com/MaartenGr/BERTopic.git@fix_2100\n",
            "  Cloning https://github.com/MaartenGr/BERTopic.git (to revision fix_2100) to /tmp/pip-req-build-haumtt27\n",
            "  Running command git clone --filter=blob:none --quiet https://github.com/MaartenGr/BERTopic.git /tmp/pip-req-build-haumtt27\n",
            "  Running command git checkout -b fix_2100 --track origin/fix_2100\n",
            "  Switched to a new branch 'fix_2100'\n",
            "  Branch 'fix_2100' set up to track remote branch 'fix_2100' from 'origin'.\n",
            "  Resolved https://github.com/MaartenGr/BERTopic.git to commit 12c5d26c87384bed199a5314440e4300b415a521\n",
            "  Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n",
            "  Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n",
            "  Preparing metadata (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
            "Requirement already satisfied: hdbscan>=0.8.29 in /usr/local/lib/python3.10/dist-packages (from bertopic==0.16.3) (0.8.38.post1)\n",
            "Requirement already satisfied: numpy>=1.20.0 in /usr/local/lib/python3.10/dist-packages (from bertopic==0.16.3) (1.26.4)\n",
            "Requirement already satisfied: pandas>=1.1.5 in /usr/local/lib/python3.10/dist-packages (from bertopic==0.16.3) (2.1.4)\n",
            "Requirement already satisfied: plotly>=4.7.0 in /usr/local/lib/python3.10/dist-packages (from bertopic==0.16.3) (5.15.0)\n",
            "Requirement already satisfied: scikit-learn>=0.22.2.post1 in /usr/local/lib/python3.10/dist-packages (from bertopic==0.16.3) (1.3.2)\n",
            "Requirement already satisfied: sentence-transformers>=0.4.1 in /usr/local/lib/python3.10/dist-packages (from bertopic==0.16.3) (3.0.1)\n",
            "Requirement already satisfied: tqdm>=4.41.1 in /usr/local/lib/python3.10/dist-packages (from bertopic==0.16.3) (4.66.5)\n",
            "Requirement already satisfied: umap-learn>=0.5.0 in /usr/local/lib/python3.10/dist-packages (from bertopic==0.16.3) (0.5.6)\n",
            "Requirement already satisfied: scipy>=1.0 in /usr/local/lib/python3.10/dist-packages (from hdbscan>=0.8.29->bertopic==0.16.3) (1.13.1)\n",
            "Requirement already satisfied: joblib>=1.0 in /usr/local/lib/python3.10/dist-packages (from hdbscan>=0.8.29->bertopic==0.16.3) (1.4.2)\n",
            "Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.10/dist-packages (from pandas>=1.1.5->bertopic==0.16.3) (2.8.2)\n",
            "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.10/dist-packages (from pandas>=1.1.5->bertopic==0.16.3) (2024.1)\n",
            "Requirement already satisfied: tzdata>=2022.1 in /usr/local/lib/python3.10/dist-packages (from pandas>=1.1.5->bertopic==0.16.3) (2024.1)\n",
            "Requirement already satisfied: tenacity>=6.2.0 in /usr/local/lib/python3.10/dist-packages (from plotly>=4.7.0->bertopic==0.16.3) (9.0.0)\n",
            "Requirement already satisfied: packaging in /usr/local/lib/python3.10/dist-packages (from plotly>=4.7.0->bertopic==0.16.3) (24.1)\n",
            "Requirement already satisfied: threadpoolctl>=2.0.0 in /usr/local/lib/python3.10/dist-packages (from scikit-learn>=0.22.2.post1->bertopic==0.16.3) (3.5.0)\n",
            "Requirement already satisfied: transformers<5.0.0,>=4.34.0 in /usr/local/lib/python3.10/dist-packages (from sentence-transformers>=0.4.1->bertopic==0.16.3) (4.42.4)\n",
            "Requirement already satisfied: torch>=1.11.0 in /usr/local/lib/python3.10/dist-packages (from sentence-transformers>=0.4.1->bertopic==0.16.3) (2.3.1+cu121)\n",
            "Requirement already satisfied: huggingface-hub>=0.15.1 in /usr/local/lib/python3.10/dist-packages (from sentence-transformers>=0.4.1->bertopic==0.16.3) (0.23.5)\n",
            "Requirement already satisfied: Pillow in /usr/local/lib/python3.10/dist-packages (from sentence-transformers>=0.4.1->bertopic==0.16.3) (9.4.0)\n",
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            "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from huggingface-hub>=0.15.1->sentence-transformers>=0.4.1->bertopic==0.16.3) (3.15.4)\n",
            "Requirement already satisfied: fsspec>=2023.5.0 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub>=0.15.1->sentence-transformers>=0.4.1->bertopic==0.16.3) (2024.6.1)\n",
            "Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub>=0.15.1->sentence-transformers>=0.4.1->bertopic==0.16.3) (6.0.2)\n",
            "Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from huggingface-hub>=0.15.1->sentence-transformers>=0.4.1->bertopic==0.16.3) (2.32.3)\n",
            "Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub>=0.15.1->sentence-transformers>=0.4.1->bertopic==0.16.3) (4.12.2)\n",
            "Requirement already satisfied: llvmlite<0.44,>=0.43.0dev0 in /usr/local/lib/python3.10/dist-packages (from numba>=0.51.2->umap-learn>=0.5.0->bertopic==0.16.3) (0.43.0)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.8.2->pandas>=1.1.5->bertopic==0.16.3) (1.16.0)\n",
            "Requirement already satisfied: sympy in /usr/local/lib/python3.10/dist-packages (from torch>=1.11.0->sentence-transformers>=0.4.1->bertopic==0.16.3) (1.13.2)\n",
            "Requirement already satisfied: networkx in /usr/local/lib/python3.10/dist-packages (from torch>=1.11.0->sentence-transformers>=0.4.1->bertopic==0.16.3) (3.3)\n",
            "Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/dist-packages (from torch>=1.11.0->sentence-transformers>=0.4.1->bertopic==0.16.3) (3.1.4)\n",
            "Requirement already satisfied: nvidia-cuda-nvrtc-cu12==12.1.105 in /usr/local/lib/python3.10/dist-packages (from torch>=1.11.0->sentence-transformers>=0.4.1->bertopic==0.16.3) (12.1.105)\n",
            "Requirement already satisfied: nvidia-cuda-runtime-cu12==12.1.105 in /usr/local/lib/python3.10/dist-packages (from torch>=1.11.0->sentence-transformers>=0.4.1->bertopic==0.16.3) (12.1.105)\n",
            "Requirement already satisfied: nvidia-cuda-cupti-cu12==12.1.105 in /usr/local/lib/python3.10/dist-packages (from torch>=1.11.0->sentence-transformers>=0.4.1->bertopic==0.16.3) (12.1.105)\n",
            "Requirement already satisfied: nvidia-cudnn-cu12==8.9.2.26 in /usr/local/lib/python3.10/dist-packages (from torch>=1.11.0->sentence-transformers>=0.4.1->bertopic==0.16.3) (8.9.2.26)\n",
            "Requirement already satisfied: nvidia-cublas-cu12==12.1.3.1 in /usr/local/lib/python3.10/dist-packages (from torch>=1.11.0->sentence-transformers>=0.4.1->bertopic==0.16.3) (12.1.3.1)\n",
            "Requirement already satisfied: nvidia-cufft-cu12==11.0.2.54 in /usr/local/lib/python3.10/dist-packages (from torch>=1.11.0->sentence-transformers>=0.4.1->bertopic==0.16.3) (11.0.2.54)\n",
            "Requirement already satisfied: nvidia-curand-cu12==10.3.2.106 in /usr/local/lib/python3.10/dist-packages (from torch>=1.11.0->sentence-transformers>=0.4.1->bertopic==0.16.3) (10.3.2.106)\n",
            "Requirement already satisfied: nvidia-cusolver-cu12==11.4.5.107 in /usr/local/lib/python3.10/dist-packages (from torch>=1.11.0->sentence-transformers>=0.4.1->bertopic==0.16.3) (11.4.5.107)\n",
            "Requirement already satisfied: nvidia-cusparse-cu12==12.1.0.106 in /usr/local/lib/python3.10/dist-packages (from torch>=1.11.0->sentence-transformers>=0.4.1->bertopic==0.16.3) (12.1.0.106)\n",
            "Requirement already satisfied: nvidia-nccl-cu12==2.20.5 in /usr/local/lib/python3.10/dist-packages (from torch>=1.11.0->sentence-transformers>=0.4.1->bertopic==0.16.3) (2.20.5)\n",
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            "Requirement already satisfied: tokenizers<0.20,>=0.19 in /usr/local/lib/python3.10/dist-packages (from transformers<5.0.0,>=4.34.0->sentence-transformers>=0.4.1->bertopic==0.16.3) (0.19.1)\n",
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          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from tqdm import tqdm\n",
        "from bertopic import BERTopic\n",
        "from konlpy.tag import Mecab\n",
        "from sklearn.feature_extraction.text import CountVectorizer\n",
        "\n",
        "import pandas as pd"
      ],
      "metadata": {
        "id": "5EyIBIADL1oB"
      },
      "execution_count": 24,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "news_df = pd.read_csv(\"/content/2024_한국경제.csv\")"
      ],
      "metadata": {
        "id": "bPd2Q834M0yL"
      },
      "execution_count": 25,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "news_df.shape"
      ],
      "metadata": {
        "id": "aNCh8LFMOOnm",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "5d4ac639-db56-41c2-e2f2-649f797c6ac1"
      },
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(4644, 10)"
            ]
          },
          "metadata": {},
          "execution_count": 26
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# 기존 BERTopic의 토큰분리 기준이 한국어와 맞지않아 Tokenizer를 Custom\n",
        "class CustomTokenizer:\n",
        "    def __init__(self, tagger):\n",
        "        self.tagger = tagger\n",
        "\n",
        "    def __call__(self, text):\n",
        "        tokens = self.tagger.morphs(text)\n",
        "        return tokens"
      ],
      "metadata": {
        "id": "NJ__qy6dRpcv"
      },
      "execution_count": 27,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "custom_tokenizer = CustomTokenizer(Mecab())\n",
        "vectorizer = CountVectorizer(tokenizer=custom_tokenizer,\n",
        "                             max_features=3000)\n",
        "model = BERTopic(embedding_model=\"sentence-transformers/xlm-r-100langs-bert-base-nli-stsb-mean-tokens\", \\\n",
        "                 vectorizer_model=vectorizer,\n",
        "                 nr_topics=50,\n",
        "                 top_n_words=10,\n",
        "                 calculate_probabilities=True)"
      ],
      "metadata": {
        "id": "riqzQYhTSdFH"
      },
      "execution_count": 28,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Make every sequence items to str type -> It can prevent unexpected TypeError\n",
        "news_df[\"body\"] = news_df[\"body\"].astype(str)\n",
        "documents = news_df[\"body\"].tolist()\n",
        "\n",
        "# Get topics and probs\n",
        "topics, probs = model.fit_transform(documents)"
      ],
      "metadata": {
        "id": "Yup-kLn4TENX"
      },
      "execution_count": 29,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "### 분류 정보 ###\n",
        "model.get_topic_info()"
      ],
      "metadata": {
        "id": "aEriId0PmeoN",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "c426c9db-d90f-45bd-8e45-df4cc60bac7b"
      },
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "    Topic  Count                 Name  \\\n",
              "0      -1   2392           -1_._다_이_는   \n",
              "1       0    309            0_다_이_을_.   \n",
              "2       1    272          1_0_지수_%)_.   \n",
              "3       2    154         2_._다_반도체_분기   \n",
              "4       3    147         3_중국_반도체_이_의   \n",
              "5       4     98          4_반도체_다_._이   \n",
              "6       5     96            5_을_다_._이   \n",
              "7       6     75       6_에어컨_탄소_포크_비스   \n",
              "8       7     62          7_로봇_틱_로보_스   \n",
              "9       8     62            8_이_의_는_.   \n",
              "10      9     56       9_대통령_윤_uae_회장   \n",
              "11     10     49      10_갤럭시_s_'_스마트폰   \n",
              "12     11     44           11_이_\"_다_고   \n",
              "13     12     39        12_반도체_칩_ai_패   \n",
              "14     13     36        13_스타트업_,_'_를   \n",
              "15     14     36          14_._(_%)_0   \n",
              "16     15     36          15_을_통신_는_다   \n",
              "17     16     34          16_이_._금리_가   \n",
              "18     17     33          17_원_._(_%)   \n",
              "19     18     32      18_습니다_죠_pro_마켓   \n",
              "20     19     31     19_arm_반도체_상장_기업   \n",
              "21     20     29           20_다_._이_는   \n",
              "22     21     29      21_갤럭시_카메라_제품_을   \n",
              "23     22     29          22_ai_를_는_을   \n",
              "24     23     28          23_'_독일_을_는   \n",
              "25     24     28          24_%_분기_._다   \n",
              "26     25     26        25_반도체_이_다_일본   \n",
              "27     26     24           26_을_는_다_,   \n",
              "28     27     23        27_는_을_테슬라_ai   \n",
              "29     28     22    28_tv_oled_형_qled   \n",
              "30     29     21          29_회장_을_)_이   \n",
              "31     30     20     30_tv_라이브_유튜브_방송   \n",
              "32     31     20           31_을_이_다_.   \n",
              "33     32     20         32_센서_xr_을_는   \n",
              "34     33     19           33_는_을_'_,   \n",
              "35     34     18        34_0_-_%),_지수   \n",
              "36     35     18         35_\"_을_전경련_하   \n",
              "37     36     17      36_베트남_대통령_회장_윤   \n",
              "38     37     17        37_서비스_페이_a_다   \n",
              "39     38     16        38_씨_기술_유출_혐의   \n",
              "40     39     16           39_의_이_하_있   \n",
              "41     40     16  40_네덜란드_asml_대통령_방문   \n",
              "42     41     13        41_분기_%_4_반도체   \n",
              "43     42     13           42_다_._는_했   \n",
              "44     43     12         43_요금제_\"_이_다   \n",
              "45     44     12          44_0_._원_%)   \n",
              "46     45     12          45_-_._(_지수   \n",
              "47     46     12     46_회장_그룹_ceo_대통령   \n",
              "48     47     11      47_계약_반도체_중국_공장   \n",
              "49     48     10        48_습니다_금리_._'   \n",
              "\n",
              "                                    Representation  \\\n",
              "0                   [., 다, 이, 는, 을, 에, 의, 은, 를, 하]   \n",
              "1                   [다, 이, 을, ., ,, 는, 의, 에, 를, ']   \n",
              "2            [0, 지수, %), ., (, 원, 포인트, %),, 하락, 억]   \n",
              "3                [., 다, 반도체, 분기, 이, %, 은, 는, 했, 에]   \n",
              "4               [중국, 반도체, 이, 의, 을, 미국, 는, 하, 에, 다]   \n",
              "5           [반도체, 다, ., 이, 삼성전자, 가, (, 은, 원, 하이닉스]   \n",
              "6                 [을, 다, ., 이, 는, 반도체, ,, 에, 의, 를]   \n",
              "7           [에어컨, 탄소, 포크, 비스, 에너지, 을, 제품, ‘, ’, 하]   \n",
              "8              [로봇, 틱, 로보, 스, 레인보우, ., 는, 이, 을, 다]   \n",
              "9                   [이, 의, 는, ., 은, 을, 하, 다, 에, 적]   \n",
              "10          [대통령, 윤, uae, 회장, 방문, 과, 한국, 국빈, 이, ,]   \n",
              "11       [갤럭시, s, ', 스마트폰, 시리즈, 23, 북, 출시, 을, 울트라]   \n",
              "12                  [이, \", 다, 고, 는, ., 하, 은, 을, 에]   \n",
              "13               [반도체, 칩, ai, 패, 징, 키, ), 는, 을, ,]   \n",
              "14               [스타트업, ,, ', 를, 는, 을, 하, 의, 이, 다]   \n",
              "15           [., (, %), 0, 지수, 습니다, %),, 원, 상승, 에]   \n",
              "16              [을, 통신, 는, 다, 부스, ces, g, 를, 이, .]   \n",
              "17               [이, ., 금리, 가, 다, 는, 은, %, 으로, 증시]   \n",
              "18              [원, ., (, %), %),, 억, 1, 다, 0, 지수]   \n",
              "19         [습니다, 죠, pro, 마켓, 한경, ✔, 투자, 종목, 주가, 들]   \n",
              "20           [arm, 반도체, 상장, 기업, 억, ), 설계, (, 에, ,]   \n",
              "21                  [다, ., 이, 는, \", 을, 에, 를, 하, 만]   \n",
              "22        [갤럭시, 카메라, 제품, 을, 화면, 플립, 다, 는, 스마트폰, s]   \n",
              "23             [ai, 를, 는, 을, ., 하, 서비스, 데이터, 있, 가]   \n",
              "24                [', 독일, 을, 는, ,, 다, 한, 에서, 의, )]   \n",
              "25               [%, 분기, ., 다, 원, 영업, 은, 억, 으로, 이]   \n",
              "26               [반도체, 이, 다, 일본, 는, 을, ., 에, 의, 은]   \n",
              "27                  [을, 는, 다, ,, 의, 하, 이, ., 에, 를]   \n",
              "28            [는, 을, 테슬라, ai, 를, 하, ), ., 삼성전자, 다]   \n",
              "29      [tv, oled, 형, qled, k, 네오, 8, 사운드, 시장, 제품]   \n",
              "30              [회장, 을, ), 이, 다, 의, 이스라엘, (, 인, .]   \n",
              "31           [tv, 라이브, 유튜브, 방송, ', 을, 쇼핑, 는, 하, 다]   \n",
              "32                [을, 이, 다, ., 는, 의, 기업, 으로, 은, 등]   \n",
              "33             [센서, xr, 을, 는, 이미지, ), 하, 의, ap, 를]   \n",
              "34                  [는, 을, ', ,, 하, 에, 를, ., 있, 의]   \n",
              "35             [0, -, %),, 지수, (, ., %), 원, 하락, 다]   \n",
              "36                [\", 을, 전경련, 하, 고, 를, 의, 다, 이, 는]   \n",
              "37        [베트남, 대통령, 회장, 윤, 방문, ”, “, 윤석열, 만찬, 국빈]   \n",
              "38             [서비스, 페이, a, 다, 하, 는, 수수료, ., 를, 이]   \n",
              "39             [씨, 기술, 유출, 혐의, 검찰, 비밀, a, 텍, 에, 받]   \n",
              "40                [의, 이, 하, 있, 는, 되, 시장, 적, 으로, 고]   \n",
              "41  [네덜란드, asml, 대통령, 방문, 윤, 국빈, 반도체, euv, 양국, 회장]   \n",
              "42              [분기, %, 4, 반도체, d, 억, ., 램, 실적, 은]   \n",
              "43                  [다, ., 는, 했, \", 에, 를, 이, 의, ,]   \n",
              "44              [요금제, \", 이, 다, 것, 만, 은, ddr, 원, 의]   \n",
              "45              [0, ., 원, %), (, 지수, %),, 다, -, 억]   \n",
              "46             [-, ., (, 지수, 하락, %), %),, 원, 했, 다]   \n",
              "47     [회장, 그룹, ceo, 대통령, 스위스, 한국, 행사, 포럼, 다, uae]   \n",
              "48           [계약, 반도체, 중국, 공장, 억, 지분, 의, 원, 에프, 년]   \n",
              "49           [습니다, 금리, ., ', (, fed, 가, 이, 는, 입니다]   \n",
              "\n",
              "                                  Representative_Docs  \n",
              "0   [올해 한국 기업을 둘러싼 환경은 녹록지 않다. 미·중 갈등과 글로벌 경기 침체, ...  \n",
              "1   [원격 SW 선두주자 알서포트를 가다서형수 대표 2년 만에 인터뷰\"차세대 커뮤니케이...  \n",
              "2   [4일 오후 서울 중구 하나은행 명동점 딜링룸./사진=뉴스1코스피가 2거래일 연속 ...  \n",
              "3   [삼성전자·SK하이닉스, 이달 들어 주가 흐름 '멈칫'\"외국인 순매수 축소·업황 반...  \n",
              "4   [美, 삼성 中반도체공장 사실상 투자 금지첨단공정서 웨이퍼 투입량10년간 5% 이상...  \n",
              "5   [삼성전자, 7만원 대 안착외국인 5500억 이상 순매수하며 상승 주도개인 투자자 ...  \n",
              "6   [美서 경력 쌓고 귀국해 창업리벨리온·딥엑스·퓨리오사AI인텔·애플·AMD 등서 개발...  \n",
              "7   ['비스포크 무풍 시스템에어컨 인피니트 라인'. 사진=삼성전자삼성전자가 ‘비스포크 ...  \n",
              "8   [돌아온 로봇주…대기업 협업에 잇단 강세상장 앞둔 두산로보틱스 흥행 여부 관심사진=...  \n",
              "9   [무역수지 적자 와중에도엔저 즐기는 일본관광 바람경제는 피크아웃 경고등첨단 투자는 ...  \n",
              "10  [이재용·정의선·최태원 등 기업인 130여명 동행사진=김범준 한국경제신문 기자아랍에...  \n",
              "11  [스마트폰 디자인 비슷해지는 추세갤S23 울트라, 2억 화소 카메라 탑재 전망갤럭시...  \n",
              "12  [허은아 국민의힘 의원 인터뷰\"'게임 질병 아냐' 말했던 입장서 롤드컵 우승 기뻐\"...  \n",
              "13  [첨단패키징서 테스트까지개별 칩 효율적 배치로 성능↑첨단 패키징 시장 날로 커져맞춤...  \n",
              "14  [이 기사는 프리미엄 스타트업 미디어 플랫폼 한경 긱스에 게재된 기사입니다.한경 긱...  \n",
              "15  [지난 4일 오후 하나은행 명동점 딜링룸./사진=뉴스1장 초반 코스피 지수가 260...  \n",
              "16  [한경·KAIST 특별취재3년 만의 대면행사 '인산인해'세상에 없던 VR·AR 장비...  \n",
              "17  [사진=게티이미지뱅크제롬 파월 미국 중앙은행(Fed) 의장은 물가안정을 위해 통화정...  \n",
              "18  [지난 6일 오후 서울 중구 하나은행 딜링룸. 사진=연합뉴스코스피가 이스라엘-팔레스...  \n",
              "19  [※한경 마켓PRO는 한 주간 짚어본 종목·투자 전략을 돌아보는 '마켓PRO 위클리...  \n",
              "20  [英 반도체기업 ARM 상장최대 13조원 조달 계획에삼성 애플 TSMC 앵커투자자서...  \n",
              "21  [비용 효율화 차원 결정사진=뉴스1네이버가 경기 침체 등으로 성장세가 둔화함에 따라...  \n",
              "22  [2023 하반기 한경 소비자 대상갤럭시 Z 플립5삼성전자가 올해 출시한 갤럭시Z플...  \n",
              "23  [생성 AI 경쟁 2라운드MS, 기업용 신규 서비스 시작챗GPT 두뇌 GPT-4 활...  \n",
              "24  [LG전자 \"세계 1위 방어 자신있다\"류재철 LG전자 H&A(홈앤드어플라이언스) 사...  \n",
              "25  [사진=게티이미지뱅크18일(현지시간) 인플레 둔화 신호로 장 초반 잘 나가던 미국 ...  \n",
              "26  [日 반도체 부활 전략 뜯어보니(6)일본은 왜 TSMC 구형 공장에 5조원을 지원하...  \n",
              "27  ['CPHI 월드와이드'서 만난 삼성바이오로직스 사장대형제약사 14곳과 CDO 협업...  \n",
              "28  [조용준 플러그앤플레이 코리아 대표‘실리콘밸리 줌인센터’는 이 지역의 창업자, 최고...  \n",
              "29  [77형 QD-OLED TV 전파인증온라인몰서 55·65형 사전주문\"TV 시장 불황...  \n",
              "30  [명절 때마다 해외 현장경영사우디·이스라엘·이집트 방문네옴시티 산악터널 등 점검\"글...  \n",
              "31  ['삼성 퍼스트 룩 2023'서 신제품 공개'동글' 없이도 200개 IoT 기기 연...  \n",
              "32  [사진=산업통상자원부정부와 민간이 첨단 투자에 대해 경쟁국 이상의 인센티브를 보장하...  \n",
              "33  ['엑시노스 2400' 출시게임, 인공지능 성능 향상CPU 성능 1.7배, AI는 ...  \n",
              "34  [이 기사는 국내 최대 해외 투자정보 플랫폼 한경 글로벌마켓에 게재된 기사입니다.#...  \n",
              "35  [지난 9일 오후 서울 중구 하나은행 본점 딜링룸. 사진=연합뉴스코스피가 외국인과 ...  \n",
              "36  [첫 '민선 4선' 김기문 중소기업중앙회장前정부, 불법파업 강 건너 불보듯이젠 '투...  \n",
              "37  [베트남을 국빈 방문 중인 윤석열 대통령과 보 반 트엉 베트남 국가주석이 23일 하...  \n",
              "38  [사진=삼성전자 제공삼성전자는 삼성전자서비스가 '2023 한국서비스품질지수(KS-S...  \n",
              "39  [연매출 1조 FCCL 제조기업 직원이직과정에서 경쟁사에 기술 유출사진=연합뉴스세계...  \n",
              "40  [※한경 마켓PRO 텔레그램을 구독하시면 프리미엄 투자 콘텐츠를 보다 편리하게 볼 ...  \n",
              "41  [이재용 삼성전자 회장, 네덜란드서윤석열 대통령과 ASML 방문“반도체 산업에 변화...  \n",
              "42  [반도체 예상 밖 회복세 더뎌게임·콘텐츠회사 계속 고전원전·건설사는 해외수주 '단비...  \n",
              "43  [서울 중구 하나은행 딜링룸./사진=연합뉴스코스피가 개인의 순매수세에 힘입어 소폭 ...  \n",
              "44  [목표가 12만8000원→14만원사진=연합뉴스BNK투자증권은 9일 SK하이닉스의 목...  \n",
              "45  [4일 오후 서울 중구 하나은행 명동점 딜링룸. 사진=뉴스1코스피가 장초반 소폭 오...  \n",
              "46  [10일 오전 서울 중구 하나은행 명동점 딜링룸. 사진=뉴스1국내 증시가 '중동 전...  \n",
              "47  ['한국의 밤'에 주요 그룹 총수·글로벌 CEO 등 참석18일(현지시간) 스위스 다...  \n",
              "48  [디아이는 삼성전자 중국 소주 법인과 214억원 규모의 반도체 검사 장비 공급계약을...  \n",
              "49  [◆뉴욕증시, 유가 상승에 긴축 장기화 우려…나스닥 1%↓뉴욕증시에서 주요 지수들은...  "
            ],
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              "      <th></th>\n",
              "      <th>Topic</th>\n",
              "      <th>Count</th>\n",
              "      <th>Name</th>\n",
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              "      <td>-1</td>\n",
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              "      <td>-1_._다_이_는</td>\n",
              "      <td>[., 다, 이, 는, 을, 에, 의, 은, 를, 하]</td>\n",
              "      <td>[올해 한국 기업을 둘러싼 환경은 녹록지 않다. 미·중 갈등과 글로벌 경기 침체, ...</td>\n",
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              "      <th>1</th>\n",
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              "      <td>[다, 이, 을, ., ,, 는, 의, 에, 를, ']</td>\n",
              "      <td>[원격 SW 선두주자 알서포트를 가다서형수 대표 2년 만에 인터뷰\"차세대 커뮤니케이...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1</td>\n",
              "      <td>272</td>\n",
              "      <td>1_0_지수_%)_.</td>\n",
              "      <td>[0, 지수, %), ., (, 원, 포인트, %),, 하락, 억]</td>\n",
              "      <td>[4일 오후 서울 중구 하나은행 명동점 딜링룸./사진=뉴스1코스피가 2거래일 연속 ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2</td>\n",
              "      <td>154</td>\n",
              "      <td>2_._다_반도체_분기</td>\n",
              "      <td>[., 다, 반도체, 분기, 이, %, 은, 는, 했, 에]</td>\n",
              "      <td>[삼성전자·SK하이닉스, 이달 들어 주가 흐름 '멈칫'\"외국인 순매수 축소·업황 반...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>3</td>\n",
              "      <td>147</td>\n",
              "      <td>3_중국_반도체_이_의</td>\n",
              "      <td>[중국, 반도체, 이, 의, 을, 미국, 는, 하, 에, 다]</td>\n",
              "      <td>[美, 삼성 中반도체공장 사실상 투자 금지첨단공정서 웨이퍼 투입량10년간 5% 이상...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>4</td>\n",
              "      <td>98</td>\n",
              "      <td>4_반도체_다_._이</td>\n",
              "      <td>[반도체, 다, ., 이, 삼성전자, 가, (, 은, 원, 하이닉스]</td>\n",
              "      <td>[삼성전자, 7만원 대 안착외국인 5500억 이상 순매수하며 상승 주도개인 투자자 ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>5</td>\n",
              "      <td>96</td>\n",
              "      <td>5_을_다_._이</td>\n",
              "      <td>[을, 다, ., 이, 는, 반도체, ,, 에, 의, 를]</td>\n",
              "      <td>[美서 경력 쌓고 귀국해 창업리벨리온·딥엑스·퓨리오사AI인텔·애플·AMD 등서 개발...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>6</td>\n",
              "      <td>75</td>\n",
              "      <td>6_에어컨_탄소_포크_비스</td>\n",
              "      <td>[에어컨, 탄소, 포크, 비스, 에너지, 을, 제품, ‘, ’, 하]</td>\n",
              "      <td>['비스포크 무풍 시스템에어컨 인피니트 라인'. 사진=삼성전자삼성전자가 ‘비스포크 ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>7</td>\n",
              "      <td>62</td>\n",
              "      <td>7_로봇_틱_로보_스</td>\n",
              "      <td>[로봇, 틱, 로보, 스, 레인보우, ., 는, 이, 을, 다]</td>\n",
              "      <td>[돌아온 로봇주…대기업 협업에 잇단 강세상장 앞둔 두산로보틱스 흥행 여부 관심사진=...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>8</td>\n",
              "      <td>62</td>\n",
              "      <td>8_이_의_는_.</td>\n",
              "      <td>[이, 의, 는, ., 은, 을, 하, 다, 에, 적]</td>\n",
              "      <td>[무역수지 적자 와중에도엔저 즐기는 일본관광 바람경제는 피크아웃 경고등첨단 투자는 ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>9</td>\n",
              "      <td>56</td>\n",
              "      <td>9_대통령_윤_uae_회장</td>\n",
              "      <td>[대통령, 윤, uae, 회장, 방문, 과, 한국, 국빈, 이, ,]</td>\n",
              "      <td>[이재용·정의선·최태원 등 기업인 130여명 동행사진=김범준 한국경제신문 기자아랍에...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>10</td>\n",
              "      <td>49</td>\n",
              "      <td>10_갤럭시_s_'_스마트폰</td>\n",
              "      <td>[갤럭시, s, ', 스마트폰, 시리즈, 23, 북, 출시, 을, 울트라]</td>\n",
              "      <td>[스마트폰 디자인 비슷해지는 추세갤S23 울트라, 2억 화소 카메라 탑재 전망갤럭시...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>11</td>\n",
              "      <td>44</td>\n",
              "      <td>11_이_\"_다_고</td>\n",
              "      <td>[이, \", 다, 고, 는, ., 하, 은, 을, 에]</td>\n",
              "      <td>[허은아 국민의힘 의원 인터뷰\"'게임 질병 아냐' 말했던 입장서 롤드컵 우승 기뻐\"...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>12</td>\n",
              "      <td>39</td>\n",
              "      <td>12_반도체_칩_ai_패</td>\n",
              "      <td>[반도체, 칩, ai, 패, 징, 키, ), 는, 을, ,]</td>\n",
              "      <td>[첨단패키징서 테스트까지개별 칩 효율적 배치로 성능↑첨단 패키징 시장 날로 커져맞춤...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>13</td>\n",
              "      <td>36</td>\n",
              "      <td>13_스타트업_,_'_를</td>\n",
              "      <td>[스타트업, ,, ', 를, 는, 을, 하, 의, 이, 다]</td>\n",
              "      <td>[이 기사는 프리미엄 스타트업 미디어 플랫폼 한경 긱스에 게재된 기사입니다.한경 긱...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>14</td>\n",
              "      <td>36</td>\n",
              "      <td>14_._(_%)_0</td>\n",
              "      <td>[., (, %), 0, 지수, 습니다, %),, 원, 상승, 에]</td>\n",
              "      <td>[지난 4일 오후 하나은행 명동점 딜링룸./사진=뉴스1장 초반 코스피 지수가 260...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>15</td>\n",
              "      <td>36</td>\n",
              "      <td>15_을_통신_는_다</td>\n",
              "      <td>[을, 통신, 는, 다, 부스, ces, g, 를, 이, .]</td>\n",
              "      <td>[한경·KAIST 특별취재3년 만의 대면행사 '인산인해'세상에 없던 VR·AR 장비...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>16</td>\n",
              "      <td>34</td>\n",
              "      <td>16_이_._금리_가</td>\n",
              "      <td>[이, ., 금리, 가, 다, 는, 은, %, 으로, 증시]</td>\n",
              "      <td>[사진=게티이미지뱅크제롬 파월 미국 중앙은행(Fed) 의장은 물가안정을 위해 통화정...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>17</td>\n",
              "      <td>33</td>\n",
              "      <td>17_원_._(_%)</td>\n",
              "      <td>[원, ., (, %), %),, 억, 1, 다, 0, 지수]</td>\n",
              "      <td>[지난 6일 오후 서울 중구 하나은행 딜링룸. 사진=연합뉴스코스피가 이스라엘-팔레스...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>18</td>\n",
              "      <td>32</td>\n",
              "      <td>18_습니다_죠_pro_마켓</td>\n",
              "      <td>[습니다, 죠, pro, 마켓, 한경, ✔, 투자, 종목, 주가, 들]</td>\n",
              "      <td>[※한경 마켓PRO는 한 주간 짚어본 종목·투자 전략을 돌아보는 '마켓PRO 위클리...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>19</td>\n",
              "      <td>31</td>\n",
              "      <td>19_arm_반도체_상장_기업</td>\n",
              "      <td>[arm, 반도체, 상장, 기업, 억, ), 설계, (, 에, ,]</td>\n",
              "      <td>[英 반도체기업 ARM 상장최대 13조원 조달 계획에삼성 애플 TSMC 앵커투자자서...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>20</td>\n",
              "      <td>29</td>\n",
              "      <td>20_다_._이_는</td>\n",
              "      <td>[다, ., 이, 는, \", 을, 에, 를, 하, 만]</td>\n",
              "      <td>[비용 효율화 차원 결정사진=뉴스1네이버가 경기 침체 등으로 성장세가 둔화함에 따라...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>21</td>\n",
              "      <td>29</td>\n",
              "      <td>21_갤럭시_카메라_제품_을</td>\n",
              "      <td>[갤럭시, 카메라, 제품, 을, 화면, 플립, 다, 는, 스마트폰, s]</td>\n",
              "      <td>[2023 하반기 한경 소비자 대상갤럭시 Z 플립5삼성전자가 올해 출시한 갤럭시Z플...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>22</td>\n",
              "      <td>29</td>\n",
              "      <td>22_ai_를_는_을</td>\n",
              "      <td>[ai, 를, 는, 을, ., 하, 서비스, 데이터, 있, 가]</td>\n",
              "      <td>[생성 AI 경쟁 2라운드MS, 기업용 신규 서비스 시작챗GPT 두뇌 GPT-4 활...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>23</td>\n",
              "      <td>28</td>\n",
              "      <td>23_'_독일_을_는</td>\n",
              "      <td>[', 독일, 을, 는, ,, 다, 한, 에서, 의, )]</td>\n",
              "      <td>[LG전자 \"세계 1위 방어 자신있다\"류재철 LG전자 H&amp;A(홈앤드어플라이언스) 사...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>24</td>\n",
              "      <td>28</td>\n",
              "      <td>24_%_분기_._다</td>\n",
              "      <td>[%, 분기, ., 다, 원, 영업, 은, 억, 으로, 이]</td>\n",
              "      <td>[사진=게티이미지뱅크18일(현지시간) 인플레 둔화 신호로 장 초반 잘 나가던 미국 ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>25</td>\n",
              "      <td>26</td>\n",
              "      <td>25_반도체_이_다_일본</td>\n",
              "      <td>[반도체, 이, 다, 일본, 는, 을, ., 에, 의, 은]</td>\n",
              "      <td>[日 반도체 부활 전략 뜯어보니(6)일본은 왜 TSMC 구형 공장에 5조원을 지원하...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>26</td>\n",
              "      <td>24</td>\n",
              "      <td>26_을_는_다_,</td>\n",
              "      <td>[을, 는, 다, ,, 의, 하, 이, ., 에, 를]</td>\n",
              "      <td>['CPHI 월드와이드'서 만난 삼성바이오로직스 사장대형제약사 14곳과 CDO 협업...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>27</td>\n",
              "      <td>23</td>\n",
              "      <td>27_는_을_테슬라_ai</td>\n",
              "      <td>[는, 을, 테슬라, ai, 를, 하, ), ., 삼성전자, 다]</td>\n",
              "      <td>[조용준 플러그앤플레이 코리아 대표‘실리콘밸리 줌인센터’는 이 지역의 창업자, 최고...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29</th>\n",
              "      <td>28</td>\n",
              "      <td>22</td>\n",
              "      <td>28_tv_oled_형_qled</td>\n",
              "      <td>[tv, oled, 형, qled, k, 네오, 8, 사운드, 시장, 제품]</td>\n",
              "      <td>[77형 QD-OLED TV 전파인증온라인몰서 55·65형 사전주문\"TV 시장 불황...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>30</th>\n",
              "      <td>29</td>\n",
              "      <td>21</td>\n",
              "      <td>29_회장_을_)_이</td>\n",
              "      <td>[회장, 을, ), 이, 다, 의, 이스라엘, (, 인, .]</td>\n",
              "      <td>[명절 때마다 해외 현장경영사우디·이스라엘·이집트 방문네옴시티 산악터널 등 점검\"글...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>31</th>\n",
              "      <td>30</td>\n",
              "      <td>20</td>\n",
              "      <td>30_tv_라이브_유튜브_방송</td>\n",
              "      <td>[tv, 라이브, 유튜브, 방송, ', 을, 쇼핑, 는, 하, 다]</td>\n",
              "      <td>['삼성 퍼스트 룩 2023'서 신제품 공개'동글' 없이도 200개 IoT 기기 연...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>32</th>\n",
              "      <td>31</td>\n",
              "      <td>20</td>\n",
              "      <td>31_을_이_다_.</td>\n",
              "      <td>[을, 이, 다, ., 는, 의, 기업, 으로, 은, 등]</td>\n",
              "      <td>[사진=산업통상자원부정부와 민간이 첨단 투자에 대해 경쟁국 이상의 인센티브를 보장하...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>33</th>\n",
              "      <td>32</td>\n",
              "      <td>20</td>\n",
              "      <td>32_센서_xr_을_는</td>\n",
              "      <td>[센서, xr, 을, 는, 이미지, ), 하, 의, ap, 를]</td>\n",
              "      <td>['엑시노스 2400' 출시게임, 인공지능 성능 향상CPU 성능 1.7배, AI는 ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>34</th>\n",
              "      <td>33</td>\n",
              "      <td>19</td>\n",
              "      <td>33_는_을_'_,</td>\n",
              "      <td>[는, 을, ', ,, 하, 에, 를, ., 있, 의]</td>\n",
              "      <td>[이 기사는 국내 최대 해외 투자정보 플랫폼 한경 글로벌마켓에 게재된 기사입니다.#...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>35</th>\n",
              "      <td>34</td>\n",
              "      <td>18</td>\n",
              "      <td>34_0_-_%),_지수</td>\n",
              "      <td>[0, -, %),, 지수, (, ., %), 원, 하락, 다]</td>\n",
              "      <td>[지난 9일 오후 서울 중구 하나은행 본점 딜링룸. 사진=연합뉴스코스피가 외국인과 ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>36</th>\n",
              "      <td>35</td>\n",
              "      <td>18</td>\n",
              "      <td>35_\"_을_전경련_하</td>\n",
              "      <td>[\", 을, 전경련, 하, 고, 를, 의, 다, 이, 는]</td>\n",
              "      <td>[첫 '민선 4선' 김기문 중소기업중앙회장前정부, 불법파업 강 건너 불보듯이젠 '투...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>37</th>\n",
              "      <td>36</td>\n",
              "      <td>17</td>\n",
              "      <td>36_베트남_대통령_회장_윤</td>\n",
              "      <td>[베트남, 대통령, 회장, 윤, 방문, ”, “, 윤석열, 만찬, 국빈]</td>\n",
              "      <td>[베트남을 국빈 방문 중인 윤석열 대통령과 보 반 트엉 베트남 국가주석이 23일 하...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>38</th>\n",
              "      <td>37</td>\n",
              "      <td>17</td>\n",
              "      <td>37_서비스_페이_a_다</td>\n",
              "      <td>[서비스, 페이, a, 다, 하, 는, 수수료, ., 를, 이]</td>\n",
              "      <td>[사진=삼성전자 제공삼성전자는 삼성전자서비스가 '2023 한국서비스품질지수(KS-S...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>39</th>\n",
              "      <td>38</td>\n",
              "      <td>16</td>\n",
              "      <td>38_씨_기술_유출_혐의</td>\n",
              "      <td>[씨, 기술, 유출, 혐의, 검찰, 비밀, a, 텍, 에, 받]</td>\n",
              "      <td>[연매출 1조 FCCL 제조기업 직원이직과정에서 경쟁사에 기술 유출사진=연합뉴스세계...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>40</th>\n",
              "      <td>39</td>\n",
              "      <td>16</td>\n",
              "      <td>39_의_이_하_있</td>\n",
              "      <td>[의, 이, 하, 있, 는, 되, 시장, 적, 으로, 고]</td>\n",
              "      <td>[※한경 마켓PRO 텔레그램을 구독하시면 프리미엄 투자 콘텐츠를 보다 편리하게 볼 ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>41</th>\n",
              "      <td>40</td>\n",
              "      <td>16</td>\n",
              "      <td>40_네덜란드_asml_대통령_방문</td>\n",
              "      <td>[네덜란드, asml, 대통령, 방문, 윤, 국빈, 반도체, euv, 양국, 회장]</td>\n",
              "      <td>[이재용 삼성전자 회장, 네덜란드서윤석열 대통령과 ASML 방문“반도체 산업에 변화...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>42</th>\n",
              "      <td>41</td>\n",
              "      <td>13</td>\n",
              "      <td>41_분기_%_4_반도체</td>\n",
              "      <td>[분기, %, 4, 반도체, d, 억, ., 램, 실적, 은]</td>\n",
              "      <td>[반도체 예상 밖 회복세 더뎌게임·콘텐츠회사 계속 고전원전·건설사는 해외수주 '단비...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>43</th>\n",
              "      <td>42</td>\n",
              "      <td>13</td>\n",
              "      <td>42_다_._는_했</td>\n",
              "      <td>[다, ., 는, 했, \", 에, 를, 이, 의, ,]</td>\n",
              "      <td>[서울 중구 하나은행 딜링룸./사진=연합뉴스코스피가 개인의 순매수세에 힘입어 소폭 ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>44</th>\n",
              "      <td>43</td>\n",
              "      <td>12</td>\n",
              "      <td>43_요금제_\"_이_다</td>\n",
              "      <td>[요금제, \", 이, 다, 것, 만, 은, ddr, 원, 의]</td>\n",
              "      <td>[목표가 12만8000원→14만원사진=연합뉴스BNK투자증권은 9일 SK하이닉스의 목...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>45</th>\n",
              "      <td>44</td>\n",
              "      <td>12</td>\n",
              "      <td>44_0_._원_%)</td>\n",
              "      <td>[0, ., 원, %), (, 지수, %),, 다, -, 억]</td>\n",
              "      <td>[4일 오후 서울 중구 하나은행 명동점 딜링룸. 사진=뉴스1코스피가 장초반 소폭 오...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>46</th>\n",
              "      <td>45</td>\n",
              "      <td>12</td>\n",
              "      <td>45_-_._(_지수</td>\n",
              "      <td>[-, ., (, 지수, 하락, %), %),, 원, 했, 다]</td>\n",
              "      <td>[10일 오전 서울 중구 하나은행 명동점 딜링룸. 사진=뉴스1국내 증시가 '중동 전...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>47</th>\n",
              "      <td>46</td>\n",
              "      <td>12</td>\n",
              "      <td>46_회장_그룹_ceo_대통령</td>\n",
              "      <td>[회장, 그룹, ceo, 대통령, 스위스, 한국, 행사, 포럼, 다, uae]</td>\n",
              "      <td>['한국의 밤'에 주요 그룹 총수·글로벌 CEO 등 참석18일(현지시간) 스위스 다...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48</th>\n",
              "      <td>47</td>\n",
              "      <td>11</td>\n",
              "      <td>47_계약_반도체_중국_공장</td>\n",
              "      <td>[계약, 반도체, 중국, 공장, 억, 지분, 의, 원, 에프, 년]</td>\n",
              "      <td>[디아이는 삼성전자 중국 소주 법인과 214억원 규모의 반도체 검사 장비 공급계약을...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>49</th>\n",
              "      <td>48</td>\n",
              "      <td>10</td>\n",
              "      <td>48_습니다_금리_._'</td>\n",
              "      <td>[습니다, 금리, ., ', (, fed, 가, 이, 는, 입니다]</td>\n",
              "      <td>[◆뉴욕증시, 유가 상승에 긴축 장기화 우려…나스닥 1%↓뉴욕증시에서 주요 지수들은...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-d2f9a19c-650d-4226-bd4a-02c64d7c692a')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-d2f9a19c-650d-4226-bd4a-02c64d7c692a 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-d2f9a19c-650d-4226-bd4a-02c64d7c692a');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-65b507de-5f9e-407c-9eec-727b1b4e2ca0\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-65b507de-5f9e-407c-9eec-727b1b4e2ca0')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-65b507de-5f9e-407c-9eec-727b1b4e2ca0 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"model\",\n  \"rows\": 50,\n  \"fields\": [\n    {\n      \"column\": \"Topic\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 14,\n        \"min\": -1,\n        \"max\": 48,\n        \"num_unique_values\": 50,\n        \"samples\": [\n          12,\n          38,\n          29\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Count\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 337,\n        \"min\": 10,\n        \"max\": 2392,\n        \"num_unique_values\": 34,\n        \"samples\": [\n          33,\n          28,\n          18\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Name\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 50,\n        \"samples\": [\n          \"12_\\ubc18\\ub3c4\\uccb4_\\uce69_ai_\\ud328\",\n          \"38_\\uc528_\\uae30\\uc220_\\uc720\\ucd9c_\\ud610\\uc758\",\n          \"29_\\ud68c\\uc7a5_\\uc744_)_\\uc774\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Representation\",\n      \"properties\": {\n        \"dtype\": \"object\",\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Representative_Docs\",\n      \"properties\": {\n        \"dtype\": \"object\",\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "### 모든 문서들이 분류되었는지 확인하기 ###\n",
        "# 'Count'열은 해당 주제로 분류된 문서의 수를 나타냄\n",
        "# -> 모든 'Count'열의 수를 더했을때 원래 문서의 수와 동일하면 모든 문서가 분류된 것\n",
        "\n",
        "SUM = model.get_topic_info()[\"Count\"].sum()\n",
        "print(\"Current document total :\", news_df.shape[0])\n",
        "print(\"Sum of 'Count' column :\", SUM)"
      ],
      "metadata": {
        "id": "z7RniC0Hb48r",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "1fd09fea-0041-432b-d35f-3c5af5b21887"
      },
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Current document total : 4644\n",
            "Sum of 'Count' column : 4644\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "### 분류된 주제 시각화하기 ###\n",
        "# LDA 알고리즘과 유사한 원리인듯?\n",
        "# 시각화를 통해 분류된 주제들에 대한 통찰력을 얻을 수 있음\n",
        "\n",
        "model.visualize_topics()"
      ],
      "metadata": {
        "id": "jP0boR18m6R5",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 667
        },
        "outputId": "d666bc5f-d784-452b-d5b5-8a68f7bf9500"
      },
      "execution_count": 32,
      "outputs": [
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    },
    {
      "cell_type": "code",
      "source": [
        "### 각 주제별 유사도 시각화하기 ###\n",
        "\n",
        "model.visualize_heatmap()"
      ],
      "metadata": {
        "id": "Enz75oPUnaKd",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 817
        },
        "outputId": "b6cb9bfb-aa21-4cec-fd3e-7b5c95855524"
      },
      "execution_count": 33,
      "outputs": [
        {
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    {
      "cell_type": "code",
      "source": [
        "# Create a dictionary to store indices for each topic\n",
        "topic_to_docs = dict()\n",
        "\n",
        "topic_to_docs[-1] = []\n",
        "for i in range(49):\n",
        "    topic_to_docs[i] = []\n",
        "\n",
        "# Populate the dictionary with document indices for each topic\n",
        "for idx, topic in enumerate(topics):\n",
        "    topic_to_docs[topic].append(idx)\n",
        "\n",
        "# Display the indices of documents for each topic\n",
        "for topic, doc_indices in topic_to_docs.items():\n",
        "    print(f\"Topic {topic}: {doc_indices}\")"
      ],
      "metadata": {
        "id": "-O9eXq7GoBCy",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "43d0d9fc-e741-4139-c170-9e3f939923b7"
      },
      "execution_count": 36,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Topic -1: [0, 2, 3, 5, 6, 7, 8, 9, 10, 11, 14, 17, 18, 19, 22, 24, 25, 26, 28, 31, 32, 33, 34, 35, 36, 37, 41, 43, 44, 45, 46, 50, 51, 52, 53, 57, 60, 64, 65, 70, 72, 73, 77, 78, 82, 83, 85, 88, 90, 92, 97, 98, 100, 105, 106, 107, 108, 109, 110, 111, 113, 114, 116, 117, 118, 119, 121, 123, 126, 129, 130, 133, 135, 138, 141, 142, 144, 145, 148, 150, 151, 154, 155, 156, 159, 160, 162, 167, 168, 175, 176, 177, 179, 180, 181, 182, 185, 187, 191, 192, 197, 199, 204, 206, 211, 212, 214, 215, 219, 220, 221, 224, 227, 228, 230, 232, 233, 234, 240, 241, 245, 247, 250, 252, 255, 256, 258, 266, 267, 273, 279, 280, 282, 284, 286, 289, 290, 292, 293, 295, 301, 304, 306, 313, 315, 321, 323, 326, 329, 332, 335, 339, 345, 346, 347, 348, 349, 350, 351, 352, 354, 355, 357, 358, 360, 361, 362, 363, 365, 366, 367, 369, 370, 371, 372, 373, 374, 378, 381, 385, 388, 389, 390, 391, 394, 396, 397, 399, 400, 401, 402, 404, 408, 409, 413, 418, 419, 420, 421, 422, 423, 424, 426, 428, 429, 435, 436, 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3437, 3441, 3445, 3453, 3454, 3457, 3459, 3465, 3468, 3469, 3471, 3473, 3474, 3475, 3476, 3478, 3483, 3487, 3490, 3491, 3492, 3494, 3495, 3498, 3499, 3502, 3505, 3506, 3507, 3508, 3511, 3512, 3515, 3516, 3519, 3520, 3522, 3523, 3525, 3526, 3527, 3528, 3531, 3533, 3536, 3537, 3538, 3541, 3543, 3545, 3546, 3549, 3550, 3552, 3553, 3554, 3555, 3557, 3558, 3559, 3561, 3562, 3565, 3566, 3569, 3570, 3571, 3572, 3575, 3577, 3579, 3582, 3583, 3584, 3587, 3588, 3590, 3591, 3592, 3593, 3595, 3596, 3597, 3600, 3601, 3602, 3604, 3605, 3607, 3608, 3609, 3611, 3612, 3615, 3616, 3618, 3619, 3620, 3622, 3623, 3627, 3628, 3629, 3631, 3634, 3635, 3638, 3639, 3644, 3646, 3647, 3648, 3650, 3652, 3655, 3656, 3657, 3658, 3659, 3660, 3661, 3663, 3664, 3667, 3668, 3669, 3671, 3672, 3675, 3676, 3678, 3679, 3680, 3681, 3683, 3684, 3688, 3689, 3691, 3692, 3693, 3696, 3698, 3699, 3700, 3702, 3703, 3704, 3708, 3709, 3710, 3711, 3713, 3714, 3715, 3723, 3725, 3726, 3727, 3728, 3729, 3730, 3734, 3738, 3740, 3741, 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4360, 4362, 4366, 4367, 4368, 4369, 4372, 4374, 4375, 4379, 4380, 4382, 4384, 4385, 4386, 4388, 4391, 4394, 4397, 4398, 4401, 4402, 4403, 4404, 4407, 4408, 4409, 4410, 4411, 4414, 4415, 4416, 4419, 4420, 4422, 4423, 4424, 4425, 4426, 4428, 4430, 4432, 4437, 4442, 4444, 4445, 4448, 4450, 4452, 4453, 4454, 4455, 4458, 4460, 4461, 4463, 4464, 4466, 4474, 4475, 4476, 4477, 4479, 4482, 4483, 4487, 4490, 4496, 4497, 4498, 4500, 4504, 4505, 4506, 4507, 4508, 4509, 4510, 4511, 4514, 4515, 4516, 4519, 4526, 4527, 4528, 4531, 4533, 4537, 4538, 4539, 4540, 4541, 4542, 4543, 4544, 4545, 4546, 4548, 4550, 4552, 4554, 4557, 4558, 4560, 4566, 4567, 4568, 4569, 4570, 4572, 4575, 4577, 4583, 4585, 4586, 4587, 4588, 4590, 4591, 4594, 4595, 4596, 4597, 4598, 4600, 4602, 4603, 4606, 4607, 4608, 4610, 4617, 4622, 4630, 4634, 4636, 4637, 4638, 4640, 4642]\n",
            "Topic 0: [4, 29, 30, 104, 166, 172, 184, 186, 188, 210, 248, 253, 300, 307, 376, 379, 407, 415, 416, 425, 434, 442, 450, 489, 504, 515, 518, 532, 548, 569, 585, 604, 657, 670, 683, 686, 690, 737, 752, 763, 799, 800, 838, 877, 887, 897, 944, 980, 982, 986, 993, 1000, 1009, 1054, 1060, 1063, 1070, 1081, 1094, 1119, 1123, 1137, 1145, 1154, 1176, 1183, 1184, 1185, 1207, 1209, 1225, 1231, 1237, 1258, 1259, 1264, 1266, 1267, 1316, 1324, 1328, 1352, 1374, 1394, 1403, 1438, 1454, 1458, 1491, 1494, 1504, 1506, 1507, 1524, 1550, 1560, 1572, 1578, 1586, 1670, 1675, 1700, 1733, 1746, 1747, 1757, 1758, 1767, 1770, 1782, 1798, 1828, 1838, 1910, 1920, 1924, 1950, 1957, 2001, 2003, 2014, 2032, 2046, 2061, 2119, 2135, 2159, 2175, 2206, 2221, 2244, 2251, 2255, 2297, 2300, 2376, 2431, 2436, 2437, 2440, 2445, 2453, 2457, 2526, 2541, 2544, 2554, 2568, 2570, 2594, 2596, 2638, 2654, 2655, 2659, 2676, 2690, 2696, 2707, 2714, 2719, 2721, 2722, 2734, 2737, 2747, 2754, 2760, 2766, 2772, 2779, 2780, 2796, 2799, 2817, 2831, 2847, 2848, 2876, 2880, 2890, 2907, 2923, 2931, 2934, 2936, 2957, 2959, 2979, 2993, 3013, 3018, 3020, 3033, 3037, 3069, 3085, 3098, 3100, 3102, 3116, 3137, 3138, 3162, 3229, 3243, 3248, 3280, 3311, 3319, 3356, 3358, 3387, 3391, 3392, 3415, 3416, 3418, 3427, 3436, 3438, 3447, 3484, 3497, 3503, 3504, 3521, 3540, 3568, 3574, 3576, 3585, 3598, 3606, 3640, 3643, 3651, 3653, 3670, 3686, 3690, 3722, 3743, 3763, 3769, 3773, 3803, 3810, 3814, 3817, 3833, 3836, 3846, 3850, 3853, 3862, 3866, 3870, 3896, 3904, 3918, 3952, 3954, 3957, 3961, 3972, 3973, 4001, 4016, 4030, 4053, 4069, 4078, 4089, 4097, 4099, 4100, 4116, 4128, 4144, 4145, 4147, 4148, 4161, 4180, 4194, 4221, 4233, 4251, 4280, 4281, 4287, 4292, 4309, 4319, 4387, 4393, 4440, 4469, 4484, 4494, 4525, 4549, 4551, 4553, 4574, 4581, 4589, 4609]\n",
            "Topic 1: [13, 16, 42, 59, 63, 74, 89, 193, 194, 209, 223, 238, 288, 294, 327, 380, 427, 433, 445, 470, 477, 522, 525, 537, 542, 550, 552, 567, 579, 590, 619, 649, 663, 687, 718, 735, 743, 751, 776, 815, 851, 880, 883, 888, 905, 936, 940, 964, 966, 1004, 1030, 1066, 1075, 1093, 1108, 1113, 1148, 1155, 1167, 1178, 1201, 1213, 1217, 1251, 1255, 1303, 1304, 1319, 1372, 1391, 1431, 1439, 1453, 1474, 1475, 1523, 1541, 1556, 1558, 1562, 1574, 1595, 1621, 1658, 1662, 1685, 1709, 1721, 1723, 1754, 1793, 1842, 1858, 1886, 1901, 1915, 1943, 1984, 1996, 2020, 2036, 2062, 2067, 2087, 2103, 2114, 2131, 2190, 2217, 2235, 2247, 2261, 2266, 2288, 2292, 2301, 2302, 2322, 2347, 2368, 2370, 2390, 2393, 2424, 2448, 2450, 2532, 2536, 2550, 2556, 2581, 2604, 2612, 2648, 2662, 2674, 2680, 2693, 2694, 2729, 2756, 2759, 2789, 2809, 2853, 2859, 2871, 2875, 2878, 2879, 2913, 2919, 2921, 2947, 2950, 2954, 2962, 2966, 2994, 3012, 3029, 3035, 3050, 3110, 3114, 3127, 3131, 3150, 3167, 3170, 3186, 3193, 3194, 3232, 3259, 3292, 3306, 3310, 3341, 3343, 3347, 3359, 3372, 3386, 3389, 3405, 3408, 3425, 3430, 3444, 3455, 3458, 3470, 3496, 3589, 3594, 3695, 3701, 3716, 3731, 3733, 3736, 3746, 3752, 3760, 3767, 3778, 3789, 3811, 3816, 3831, 3845, 3856, 3895, 3897, 3913, 3916, 3927, 3931, 3939, 3948, 3969, 3978, 3986, 4005, 4007, 4008, 4022, 4040, 4061, 4074, 4096, 4107, 4110, 4112, 4127, 4136, 4142, 4154, 4182, 4185, 4189, 4211, 4213, 4216, 4256, 4277, 4283, 4290, 4302, 4303, 4305, 4324, 4325, 4350, 4373, 4377, 4381, 4389, 4417, 4421, 4443, 4446, 4468, 4518, 4522, 4535, 4547, 4599, 4605, 4618, 4619]\n",
            "Topic 2: [20, 21, 66, 80, 87, 101, 102, 131, 147, 157, 163, 222, 243, 261, 263, 298, 319, 343, 406, 411, 417, 439, 458, 461, 463, 464, 507, 508, 512, 570, 638, 733, 742, 774, 775, 779, 797, 821, 828, 832, 833, 898, 939, 977, 989, 1037, 1082, 1097, 1109, 1177, 1179, 1193, 1206, 1238, 1270, 1290, 1295, 1299, 1309, 1327, 1345, 1354, 1361, 1364, 1397, 1482, 1502, 1516, 1529, 1537, 1591, 1593, 1599, 1613, 1614, 1626, 1628, 1629, 1659, 1707, 1708, 1739, 1778, 1801, 1804, 1930, 1939, 1986, 2008, 2018, 2034, 2148, 2161, 2172, 2196, 2205, 2211, 2256, 2299, 2406, 2414, 2422, 2441, 2443, 2488, 2513, 2527, 2599, 2646, 2708, 2724, 2736, 2743, 2791, 2820, 2899, 2901, 2912, 2983, 3025, 3073, 3079, 3120, 3128, 3132, 3156, 3400, 3414, 3449, 3450, 3461, 3481, 3510, 3556, 3560, 3666, 3877, 3910, 3924, 3982, 3985, 4011, 4017, 4072, 4098, 4140, 4146, 4198, 4224, 4323, 4344, 4349, 4429, 4470]\n",
            "Topic 3: [84, 225, 229, 235, 257, 265, 268, 333, 564, 635, 688, 720, 772, 783, 786, 787, 843, 863, 925, 934, 948, 1042, 1086, 1088, 1089, 1101, 1106, 1107, 1197, 1233, 1240, 1245, 1257, 1359, 1427, 1447, 1451, 1521, 1528, 1531, 1540, 1548, 1552, 1583, 1619, 1625, 1663, 1666, 1698, 1726, 1728, 1736, 1748, 1775, 1808, 1869, 1870, 1871, 1882, 1890, 1896, 1923, 1949, 1951, 2092, 2141, 2164, 2166, 2181, 2185, 2191, 2207, 2215, 2218, 2310, 2320, 2337, 2375, 2416, 2456, 2496, 2503, 2545, 2592, 2620, 2621, 2623, 2658, 2677, 2685, 2823, 2850, 2884, 2908, 2917, 2918, 2940, 2980, 3047, 3065, 3106, 3141, 3182, 3217, 3244, 3255, 3268, 3287, 3288, 3303, 3318, 3344, 3373, 3382, 3443, 3466, 3472, 3479, 3480, 3485, 3529, 3530, 3535, 3564, 3613, 3621, 3632, 3633, 3637, 3642, 3721, 3758, 3871, 3878, 4035, 4122, 4132, 4197, 4343, 4346, 4363, 4451, 4456, 4517, 4530, 4593, 4601]\n",
            "Topic 4: [76, 287, 331, 336, 392, 405, 586, 625, 630, 659, 773, 1019, 1021, 1120, 1196, 1285, 1330, 1366, 1443, 1510, 1514, 1639, 1714, 1856, 1861, 1864, 1865, 1885, 1898, 1933, 1936, 1983, 1993, 2007, 2025, 2050, 2084, 2108, 2333, 2339, 2349, 2352, 2364, 2434, 2439, 2500, 2557, 2575, 2617, 2642, 2647, 2666, 2668, 2713, 2839, 2851, 2864, 2973, 3006, 3055, 3096, 3123, 3204, 3212, 3236, 3330, 3376, 3381, 3488, 3489, 3567, 3724, 3739, 3754, 3912, 3981, 4038, 4077, 4087, 4150, 4258, 4279, 4294, 4310, 4330, 4348, 4361, 4418, 4431, 4559, 4563, 4565, 4616, 4627, 4628, 4629, 4632, 4633]\n",
            "Topic 5: [12, 55, 71, 236, 249, 259, 324, 544, 557, 632, 725, 757, 873, 889, 928, 985, 1015, 1020, 1034, 1092, 1100, 1117, 1152, 1246, 1274, 1335, 1370, 1435, 1461, 1687, 1689, 1702, 1712, 1760, 1779, 1802, 1813, 1818, 1922, 1945, 2109, 2165, 2178, 2194, 2308, 2404, 2497, 2717, 2769, 2790, 2795, 2813, 2895, 2902, 2946, 2985, 2989, 3002, 3015, 3021, 3028, 3045, 3135, 3157, 3158, 3187, 3230, 3245, 3296, 3329, 3353, 3396, 3411, 3448, 3464, 3509, 3524, 3586, 3943, 3994, 4000, 4190, 4205, 4210, 4241, 4263, 4266, 4352, 4378, 4400, 4405, 4449, 4499, 4573, 4578, 4612]\n",
            "Topic 6: [61, 125, 205, 297, 382, 432, 510, 526, 556, 684, 712, 801, 836, 840, 875, 901, 1079, 1156, 1198, 1499, 1643, 1651, 1678, 1786, 1788, 1796, 2053, 2055, 2151, 2173, 2200, 2269, 2278, 2279, 2280, 2281, 2282, 2283, 2285, 2286, 2287, 2309, 2324, 2326, 2328, 2444, 2446, 2558, 2572, 2573, 2681, 2682, 2683, 2771, 2777, 2829, 2888, 2927, 2997, 3016, 3076, 3172, 3197, 3439, 3442, 3460, 3477, 3697, 3732, 3917, 4026, 4043, 4163, 4284, 4624]\n",
            "Topic 7: [48, 54, 75, 79, 94, 95, 99, 149, 164, 165, 169, 278, 281, 296, 302, 342, 398, 403, 431, 499, 631, 929, 998, 1023, 1031, 1043, 1071, 1073, 1076, 1080, 1103, 1194, 1347, 1353, 1478, 1486, 1964, 1967, 2082, 2246, 2313, 2425, 2712, 2757, 3046, 3195, 3218, 3237, 3242, 3256, 3260, 3295, 3395, 3514, 3544, 3687, 3706, 3838, 3890, 4191, 4471, 4615]\n",
            "Topic 8: [146, 299, 305, 317, 482, 605, 610, 716, 854, 900, 1191, 1211, 1220, 1318, 1337, 1338, 1390, 1392, 1440, 1449, 1450, 1546, 1585, 1612, 1635, 1655, 1717, 1745, 1781, 1799, 1900, 1962, 1963, 2024, 2076, 2093, 2144, 2150, 2177, 2180, 2199, 2277, 2312, 2321, 2334, 2384, 2449, 2469, 2499, 2501, 2508, 2982, 3071, 3291, 3361, 3614, 3820, 3855, 4088, 4249, 4427, 4492]\n",
            "Topic 9: [246, 251, 254, 269, 270, 271, 272, 275, 276, 283, 810, 825, 837, 918, 921, 961, 965, 1282, 1289, 1375, 1479, 1545, 1570, 1571, 1576, 1584, 1587, 1601, 1604, 1610, 1641, 1677, 1908, 1913, 1925, 1969, 2070, 2542, 2593, 3362, 3624, 3779, 3783, 3794, 3802, 3818, 3827, 3828, 3829, 4021, 4102, 4178, 4268, 4300, 4365, 4613]\n",
            "Topic 10: [58, 196, 203, 208, 226, 260, 274, 291, 337, 341, 356, 384, 387, 448, 497, 509, 516, 517, 529, 536, 554, 572, 575, 662, 711, 771, 862, 872, 915, 1067, 1090, 1121, 1221, 1384, 1409, 2056, 2094, 2229, 2590, 2758, 2792, 3433, 3482, 3573, 3712, 4172, 4459, 4571, 4631]\n",
            "Topic 11: [81, 231, 368, 513, 640, 643, 645, 808, 956, 1013, 1014, 1307, 1616, 1729, 1763, 1764, 1841, 2224, 2252, 2383, 2472, 2490, 2552, 2577, 2741, 2968, 3078, 3215, 3317, 3440, 3463, 3532, 3886, 3915, 3928, 3929, 3970, 4042, 4109, 4114, 4121, 4333, 4495, 4520]\n",
            "Topic 12: [412, 414, 543, 615, 633, 660, 705, 1057, 1166, 1227, 1232, 1243, 1422, 1744, 1789, 2030, 2043, 2068, 2222, 2242, 2305, 2342, 2597, 2607, 2748, 2761, 2883, 2903, 2932, 3036, 3070, 3183, 3240, 3800, 4033, 4358, 4406, 4614, 4643]\n",
            "Topic 13: [237, 239, 328, 353, 473, 628, 1069, 1143, 1215, 1581, 1582, 1832, 1887, 2004, 2065, 2102, 2389, 2534, 2584, 2616, 2732, 2773, 2854, 2874, 2898, 2938, 2963, 3008, 3091, 3189, 3422, 3759, 3830, 4029, 4095, 4512]\n",
            "Topic 14: [86, 320, 393, 479, 498, 563, 796, 869, 874, 1091, 1242, 1471, 1812, 2049, 2133, 2344, 2396, 2478, 2498, 2781, 2803, 2937, 3325, 3842, 3906, 3932, 3941, 3944, 3950, 3987, 4392, 4413, 4438, 4513, 4536, 4620]\n",
            "Topic 15: [38, 39, 49, 56, 62, 91, 115, 120, 127, 132, 134, 136, 137, 189, 195, 202, 334, 501, 580, 827, 860, 876, 1271, 1588, 1598, 2077, 2421, 2955, 3082, 3312, 3314, 3331, 3630, 4339, 4345, 4354]\n",
            "Topic 16: [158, 207, 481, 561, 609, 867, 1028, 1371, 1395, 1649, 1657, 1719, 1903, 1974, 2653, 2805, 3056, 3320, 3501, 3534, 3649, 3654, 3718, 3719, 3737, 3821, 3901, 3937, 4353, 4370, 4486, 4488, 4502, 4579]\n",
            "Topic 17: [122, 161, 190, 262, 701, 835, 996, 1356, 1378, 1444, 1544, 1704, 1977, 2095, 2249, 2486, 2601, 2818, 2873, 3180, 3578, 3641, 3662, 3673, 3764, 3894, 4059, 4286, 4390, 4462, 4561, 4576, 4611]\n",
            "Topic 18: [140, 244, 340, 377, 410, 480, 527, 601, 1041, 1138, 1323, 1398, 1402, 1405, 1530, 1543, 1633, 1777, 1952, 1954, 2052, 2566, 2699, 2740, 2857, 3315, 3720, 3735, 4118, 4159, 4395, 4584]\n",
            "Topic 19: [213, 330, 762, 782, 841, 1078, 1099, 1377, 1385, 1411, 1489, 1640, 1681, 1868, 2045, 2253, 2405, 2492, 2978, 3092, 3171, 3222, 3273, 3284, 3413, 3452, 4094, 4169, 4480, 4562, 4604]\n",
            "Topic 20: [201, 456, 459, 870, 967, 1096, 1124, 1425, 1555, 1627, 1632, 1634, 1703, 1814, 1961, 2225, 2340, 2460, 2733, 2860, 2939, 3148, 3233, 4063, 4131, 4270, 4272, 4532, 4534]\n",
            "Topic 21: [67, 143, 277, 322, 395, 528, 531, 693, 781, 1055, 1174, 1202, 1269, 1701, 2330, 2764, 2793, 2797, 2824, 2999, 3094, 3357, 3518, 3580, 3685, 3694, 4371, 4592, 4623]\n",
            "Topic 22: [93, 128, 198, 485, 644, 678, 802, 1159, 1432, 1442, 1505, 1513, 1522, 1579, 1824, 1840, 1895, 2091, 2284, 2464, 2763, 2900, 2911, 3451, 3717, 3807, 4219, 4299, 4621]\n",
            "Topic 23: [364, 541, 818, 952, 1260, 1410, 1420, 2021, 2374, 2428, 2783, 2930, 2995, 3083, 3113, 3118, 3192, 3201, 3223, 3231, 3241, 3253, 3258, 3486, 3677, 3682, 4295, 4412]\n",
            "Topic 24: [40, 139, 152, 183, 312, 647, 750, 760, 1175, 1203, 1254, 1263, 1567, 1568, 1835, 2009, 2451, 2549, 2842, 3000, 3806, 3899, 3900, 3956, 3993, 4179, 4473, 4493]\n",
            "Topic 25: [170, 174, 511, 519, 728, 865, 1153, 1208, 1351, 1565, 1605, 1623, 1780, 1973, 2158, 2179, 2606, 2723, 2784, 2826, 2863, 3227, 3539, 4317, 4383, 4580]\n",
            "Topic 26: [856, 1144, 1476, 1566, 1620, 1630, 1807, 1929, 1937, 1940, 1968, 2649, 2692, 2894, 3161, 3513, 3625, 3748, 3858, 3863, 4200, 4217, 4278, 4501]\n",
            "Topic 27: [359, 576, 853, 1044, 1463, 1771, 1785, 1854, 2146, 2583, 2605, 2688, 2689, 2984, 3014, 3024, 3379, 3636, 3744, 3889, 3903, 3983, 4062]\n",
            "Topic 28: [173, 603, 613, 722, 759, 766, 922, 932, 1022, 1332, 1826, 1905, 2085, 2627, 2631, 2635, 2881, 3563, 4086, 4153, 4164, 4625]\n",
            "Topic 29: [153, 574, 588, 795, 1050, 1132, 1136, 1310, 2075, 2338, 3103, 3332, 3354, 3547, 3548, 3551, 3617, 3883, 4091, 4173, 4183]\n",
            "Topic 30: [68, 69, 216, 217, 344, 452, 703, 1436, 1683, 1749, 1844, 2306, 2463, 2505, 2609, 2768, 2822, 3074, 3340, 4376]\n",
            "Topic 31: [27, 103, 112, 264, 303, 311, 386, 490, 534, 707, 1133, 1990, 2241, 2427, 2482, 2641, 3049, 3304, 4465, 4555]\n",
            "Topic 32: [47, 375, 494, 664, 788, 812, 1284, 1459, 1647, 2016, 2112, 2171, 2419, 3178, 3301, 3462, 3603, 3610, 4024, 4529]\n",
            "Topic 33: [338, 383, 890, 1376, 1656, 2600, 2614, 2622, 3032, 3117, 3599, 3626, 3674, 3865, 4041, 4049, 4364, 4521, 4582]\n",
            "Topic 34: [430, 913, 1006, 1553, 2213, 2348, 2413, 2715, 2716, 2778, 2782, 2981, 3456, 3933, 4018, 4203, 4335, 4342]\n",
            "Topic 35: [124, 730, 960, 1039, 1083, 2047, 2474, 2650, 2749, 2852, 2882, 3038, 3048, 3219, 3765, 3824, 3825, 4265]\n",
            "Topic 36: [917, 2042, 2319, 2341, 2345, 2346, 2353, 2354, 2355, 2358, 2359, 2360, 2367, 2640, 4177, 4235, 4242]\n",
            "Topic 37: [23, 599, 617, 724, 861, 1059, 1866, 1941, 2023, 2273, 2325, 2528, 2531, 2651, 2726, 3080, 3446]\n",
            "Topic 38: [1820, 2356, 2369, 2523, 2618, 2625, 2630, 2637, 3112, 3367, 3665, 3839, 4481, 4485, 4489, 4491]\n",
            "Topic 39: [1369, 1408, 1740, 1755, 2069, 2233, 2518, 2786, 3130, 3410, 3429, 3493, 3542, 3979, 4054, 4635]\n",
            "Topic 40: [3705, 4320, 4396, 4399, 4433, 4434, 4435, 4436, 4439, 4441, 4447, 4457, 4467, 4472, 4503, 4564]\n",
            "Topic 41: [444, 732, 1048, 1126, 1317, 1607, 2059, 3581, 3815, 3819, 3934, 4523, 4556]\n",
            "Topic 42: [1214, 1481, 1849, 1863, 2697, 2698, 2706, 2710, 3345, 3467, 4104, 4524, 4639]\n",
            "Topic 43: [651, 1622, 2128, 2188, 2294, 2504, 3384, 3385, 3421, 3707, 4478, 4626]\n",
            "Topic 44: [96, 468, 923, 1268, 2511, 2598, 3003, 3324, 3911, 3947, 4201, 4641]\n",
            "Topic 45: [1, 694, 2240, 2543, 2546, 2832, 3500, 3517, 3645, 3776, 3860, 3861]\n",
            "Topic 46: [200, 242, 285, 308, 309, 310, 314, 316, 318, 325, 646, 3962]\n",
            "Topic 47: [178, 453, 927, 1344, 1360, 1676, 2117, 2169, 2303, 3914, 4176]\n",
            "Topic 48: [15, 171, 218, 717, 1149, 1355, 1734, 2226, 3290, 4103]\n",
            "Topic 49: []\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "vXHvZ-sF77-P"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}