{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "joclHpOJPld7",
        "outputId": "1db9e5fe-b0ba-488e-b965-6c6618b8419d"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ],
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install spacy transformers sentencepiece rouge"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "HzFIaplBPuFc",
        "outputId": "da2c704e-514f-47b2-d6fc-74850ae487f0"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: spacy in /usr/local/lib/python3.10/dist-packages (3.7.4)\n",
            "Requirement already satisfied: transformers in /usr/local/lib/python3.10/dist-packages (4.40.1)\n",
            "Requirement already satisfied: sentencepiece in /usr/local/lib/python3.10/dist-packages (0.1.99)\n",
            "Collecting rouge\n",
            "  Downloading rouge-1.0.1-py3-none-any.whl (13 kB)\n",
            "Requirement already satisfied: spacy-legacy<3.1.0,>=3.0.11 in /usr/local/lib/python3.10/dist-packages (from spacy) (3.0.12)\n",
            "Requirement already satisfied: spacy-loggers<2.0.0,>=1.0.0 in /usr/local/lib/python3.10/dist-packages (from spacy) (1.0.5)\n",
            "Requirement already satisfied: murmurhash<1.1.0,>=0.28.0 in /usr/local/lib/python3.10/dist-packages (from spacy) (1.0.10)\n",
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            "Requirement already satisfied: preshed<3.1.0,>=3.0.2 in /usr/local/lib/python3.10/dist-packages (from spacy) (3.0.9)\n",
            "Requirement already satisfied: thinc<8.3.0,>=8.2.2 in /usr/local/lib/python3.10/dist-packages (from spacy) (8.2.3)\n",
            "Requirement already satisfied: wasabi<1.2.0,>=0.9.1 in /usr/local/lib/python3.10/dist-packages (from spacy) (1.1.2)\n",
            "Requirement already satisfied: srsly<3.0.0,>=2.4.3 in /usr/local/lib/python3.10/dist-packages (from spacy) (2.4.8)\n",
            "Requirement already satisfied: catalogue<2.1.0,>=2.0.6 in /usr/local/lib/python3.10/dist-packages (from spacy) (2.0.10)\n",
            "Requirement already satisfied: weasel<0.4.0,>=0.1.0 in /usr/local/lib/python3.10/dist-packages (from spacy) (0.3.4)\n",
            "Requirement already satisfied: typer<0.10.0,>=0.3.0 in /usr/local/lib/python3.10/dist-packages (from spacy) (0.9.4)\n",
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            "Requirement already satisfied: tqdm<5.0.0,>=4.38.0 in /usr/local/lib/python3.10/dist-packages (from spacy) (4.66.2)\n",
            "Requirement already satisfied: requests<3.0.0,>=2.13.0 in /usr/local/lib/python3.10/dist-packages (from spacy) (2.31.0)\n",
            "Requirement already satisfied: pydantic!=1.8,!=1.8.1,<3.0.0,>=1.7.4 in /usr/local/lib/python3.10/dist-packages (from spacy) (2.7.1)\n",
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            "Requirement already satisfied: setuptools in /usr/local/lib/python3.10/dist-packages (from spacy) (67.7.2)\n",
            "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.10/dist-packages (from spacy) (24.0)\n",
            "Requirement already satisfied: langcodes<4.0.0,>=3.2.0 in /usr/local/lib/python3.10/dist-packages (from spacy) (3.4.0)\n",
            "Requirement already satisfied: numpy>=1.19.0 in /usr/local/lib/python3.10/dist-packages (from spacy) (1.25.2)\n",
            "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from transformers) (3.13.4)\n",
            "Requirement already satisfied: huggingface-hub<1.0,>=0.19.3 in /usr/local/lib/python3.10/dist-packages (from transformers) (0.20.3)\n",
            "Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.10/dist-packages (from transformers) (6.0.1)\n",
            "Requirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.10/dist-packages (from transformers) (2023.12.25)\n",
            "Requirement already satisfied: tokenizers<0.20,>=0.19 in /usr/local/lib/python3.10/dist-packages (from transformers) (0.19.1)\n",
            "Requirement already satisfied: safetensors>=0.4.1 in /usr/local/lib/python3.10/dist-packages (from transformers) (0.4.3)\n",
            "Requirement already satisfied: six in /usr/local/lib/python3.10/dist-packages (from rouge) (1.16.0)\n",
            "Requirement already satisfied: fsspec>=2023.5.0 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub<1.0,>=0.19.3->transformers) (2023.6.0)\n",
            "Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub<1.0,>=0.19.3->transformers) (4.11.0)\n",
            "Requirement already satisfied: language-data>=1.2 in /usr/local/lib/python3.10/dist-packages (from langcodes<4.0.0,>=3.2.0->spacy) (1.2.0)\n",
            "Requirement already satisfied: annotated-types>=0.4.0 in /usr/local/lib/python3.10/dist-packages (from pydantic!=1.8,!=1.8.1,<3.0.0,>=1.7.4->spacy) (0.6.0)\n",
            "Requirement already satisfied: pydantic-core==2.18.2 in /usr/local/lib/python3.10/dist-packages (from pydantic!=1.8,!=1.8.1,<3.0.0,>=1.7.4->spacy) (2.18.2)\n",
            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests<3.0.0,>=2.13.0->spacy) (3.3.2)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests<3.0.0,>=2.13.0->spacy) (3.7)\n",
            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests<3.0.0,>=2.13.0->spacy) (2.0.7)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests<3.0.0,>=2.13.0->spacy) (2024.2.2)\n",
            "Requirement already satisfied: blis<0.8.0,>=0.7.8 in /usr/local/lib/python3.10/dist-packages (from thinc<8.3.0,>=8.2.2->spacy) (0.7.11)\n",
            "Requirement already satisfied: confection<1.0.0,>=0.0.1 in /usr/local/lib/python3.10/dist-packages (from thinc<8.3.0,>=8.2.2->spacy) (0.1.4)\n",
            "Requirement already satisfied: click<9.0.0,>=7.1.1 in /usr/local/lib/python3.10/dist-packages (from typer<0.10.0,>=0.3.0->spacy) (8.1.7)\n",
            "Requirement already satisfied: cloudpathlib<0.17.0,>=0.7.0 in /usr/local/lib/python3.10/dist-packages (from weasel<0.4.0,>=0.1.0->spacy) (0.16.0)\n",
            "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->spacy) (2.1.5)\n",
            "Requirement already satisfied: marisa-trie>=0.7.7 in /usr/local/lib/python3.10/dist-packages (from language-data>=1.2->langcodes<4.0.0,>=3.2.0->spacy) (1.1.0)\n",
            "Installing collected packages: rouge\n",
            "Successfully installed rouge-1.0.1\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import spacy\n",
        "import json\n",
        "import pandas as pd\n",
        "import os\n",
        "from rouge import Rouge\n",
        "import copy"
      ],
      "metadata": {
        "id": "07ZEIyyaPwTD"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#FUNC: save JSONL file\n",
        "def save_jsonl(dataset, fname):\n",
        "    f = open(fname, 'w', encoding='utf-8')\n",
        "    for i in dataset:\n",
        "        json.dump(i, f, ensure_ascii=False)\n",
        "        f.write(\"\\n\")\n",
        "    print('JSONL File saved..')"
      ],
      "metadata": {
        "id": "xarZ5NKdP0Jr"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#Func : Read JSON Line from dataset file & Return JSON Obj\n",
        "def read_jsonl(file_name):\n",
        "  data = []\n",
        "  #Opening JSON file of Scrapped Summaries for finding links for retrieval\n",
        "  with open(file_name, 'r', encoding='utf-8') as f:\n",
        "    for line in f:\n",
        "      data.append(json.loads(line))\n",
        "    print ('No of Article / Summaries Pair : ', len(data))\n",
        "  return data"
      ],
      "metadata": {
        "id": "yx4AcEGaP3X5"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#FUNC: token length using spacy\n",
        "def word_len(text):\n",
        "  len_word = 0\n",
        "  nlp = spacy.blank('ur')\n",
        "  doc = nlp(text)\n",
        "  for word in doc:\n",
        "    len_word += 1\n",
        "  return len_word"
      ],
      "metadata": {
        "id": "Dvdb1f8pP6Rr"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#Func : Split Test and Train from Dataset\n",
        "def train_test_split(df, frac=0.1):\n",
        "    # get random sample\n",
        "    test = df.sample(frac=frac, axis=0)\n",
        "    # get everything but the test sample\n",
        "    train = df.drop(index=test.index)\n",
        "    return train, test"
      ],
      "metadata": {
        "id": "3u66mhfhP_ws"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#Func : Read Stop Words\n",
        "def remove_stopwords(text, file_name='/content/drive/MyDrive/Urdu/BBC New/StopWords.txt'):\n",
        "  words = []\n",
        "  with open(file_name, 'r', encoding='utf-8') as f:\n",
        "    for line in f:\n",
        "      words.append(line.rstip())\n",
        "  for w in words:\n",
        "    text.replace(w, '')\n",
        "  return text"
      ],
      "metadata": {
        "id": "d1UB4B5dQCJS"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "ds = read_jsonl('/content/drive/MyDrive/Urdu/BBC New/Articles.jsonl')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "aHSH901zQE0_",
        "outputId": "7ed627fe-b8c9-4c1c-c497-80ed39e2f773"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "No of Article / Summaries Pair :  4959\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Load Dataset in pandas df\n",
        "df = pd.DataFrame(read_jsonl('/content/drive/MyDrive/Urdu/BBC New/Articles.jsonl'))\n",
        "# Drop unneccessary columns BBCUr\n",
        "df = df.drop([ 'firstPublished','title'], axis=1)\n",
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "yJ10fAgYQHrV",
        "outputId": "d0643098-8217-4f21-eaeb-e6b25c288924"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "No of Article / Summaries Pair :  4959\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                                 url  \\\n",
              "0     https://www.bbc.com/urdu/articles/cv20nxzl544o   \n",
              "1     https://www.bbc.com/urdu/articles/c109pqg9v1vo   \n",
              "2     https://www.bbc.com/urdu/articles/cj78ev79mdmo   \n",
              "3     https://www.bbc.com/urdu/articles/c3gl4pp0gzgo   \n",
              "4     https://www.bbc.com/urdu/articles/c2q3k4nq39no   \n",
              "...                                              ...   \n",
              "4954  https://www.bbc.com/urdu/articles/cz4dp89r8p8o   \n",
              "4955  https://www.bbc.com/urdu/articles/cn0995kvnzgo   \n",
              "4956  https://www.bbc.com/urdu/articles/cy0ddzg77zko   \n",
              "4957  https://www.bbc.com/urdu/articles/czd8jkzn0nno   \n",
              "4958  https://www.bbc.com/urdu/articles/crgye1440r0o   \n",
              "\n",
              "                                                summary            id  \\\n",
              "0     پاکستان کے زیرانتظام کشمیر میں بجلی کی قیمتوں ...  cv20nxzl544o   \n",
              "1     پاکستان میں معیشت اور ٹیکس کے ماہرین کے مطابق ...  c109pqg9v1vo   \n",
              "2     تحقیقات سے پتا چلا ہے کہ ماسکو کا ساتھ نہ دینے...  cj78ev79mdmo   \n",
              "3     رقبے کے لحاظ سے دنیا کے دوسرے سب سے بڑے ملک کے...  c3gl4pp0gzgo   \n",
              "4     انڈیا کے وزیر اعظم نریندر مودی کا کہنا ہے کہ د...  c2q3k4nq39no   \n",
              "...                                                 ...           ...   \n",
              "4954  انڈیا کی شمالی ریاست اتراکھنڈ کے شہر ہلدوانی م...  cz4dp89r8p8o   \n",
              "4955  کانگریس پارٹی نے گزشتہ سال اپنی حکومت بناتے ہو...  cn0995kvnzgo   \n",
              "4956  انتہا پسند ہندو تنظیموں کے ارکان نے اس فلم کے ...  cy0ddzg77zko   \n",
              "4957  نوکری ٹھکرا کر یا نوکری چھوڑ کر اپنا کاروبار ش...  czd8jkzn0nno   \n",
              "4958  یو پی بورڈ میں ٹاپ کرنے والی طالبہ پراچی کہتی ...  crgye1440r0o   \n",
              "\n",
              "                                                article  \n",
              "0     [’میرا دو ماہ کا بجلی کا بل 80 ہزار روپے آیا ہ...  \n",
              "1     [بین الاقوامی مالیاتی فنڈ (آئی ایم ایف)  کی م...  \n",
              "2     [گذشتہ سال فروری میں جب یوکرین میں جنگ شروع ہو...  \n",
              "3     [عموماً یورپی اور سکینڈینیوین ممالک کا شمار دن...  \n",
              "4     [انڈیا کے وزیر اعظم نریندر مودی نے ایک حالیہ ر...  \n",
              "...                                                 ...  \n",
              "4954  [انڈیا کی شمالی ریاست اتراکھنڈ کے شہر ہلدوانی ...  \n",
              "4955  [انڈیا کی جنوبی ریاست کرناٹک میں پیش آنے والے ...  \n",
              "4956  [ایک انڈین فلم، جسے ’ہندوؤں کے مذہبی جذبات مجر...  \n",
              "4957  [نوکری کو ٹھکرا کر یا نوکری کو چھوڑ کر اپنا کا...  \n",
              "4958  [یو پی بورڈ کے نتائج کا پانچواں دن تھا۔ صبح سا...  \n",
              "\n",
              "[4959 rows x 4 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-18d87ce0-354a-413c-b160-e1725f32308b\" 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>url</th>\n",
              "      <th>summary</th>\n",
              "      <th>id</th>\n",
              "      <th>article</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>https://www.bbc.com/urdu/articles/cv20nxzl544o</td>\n",
              "      <td>پاکستان کے زیرانتظام کشمیر میں بجلی کی قیمتوں ...</td>\n",
              "      <td>cv20nxzl544o</td>\n",
              "      <td>[’میرا دو ماہ کا بجلی کا بل 80 ہزار روپے آیا ہ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>https://www.bbc.com/urdu/articles/c109pqg9v1vo</td>\n",
              "      <td>پاکستان میں معیشت اور ٹیکس کے ماہرین کے مطابق ...</td>\n",
              "      <td>c109pqg9v1vo</td>\n",
              "      <td>[بین الاقوامی مالیاتی فنڈ (آئی ایم ایف)  کی م...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>https://www.bbc.com/urdu/articles/cj78ev79mdmo</td>\n",
              "      <td>تحقیقات سے پتا چلا ہے کہ ماسکو کا ساتھ نہ دینے...</td>\n",
              "      <td>cj78ev79mdmo</td>\n",
              "      <td>[گذشتہ سال فروری میں جب یوکرین میں جنگ شروع ہو...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>https://www.bbc.com/urdu/articles/c3gl4pp0gzgo</td>\n",
              "      <td>رقبے کے لحاظ سے دنیا کے دوسرے سب سے بڑے ملک کے...</td>\n",
              "      <td>c3gl4pp0gzgo</td>\n",
              "      <td>[عموماً یورپی اور سکینڈینیوین ممالک کا شمار دن...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>https://www.bbc.com/urdu/articles/c2q3k4nq39no</td>\n",
              "      <td>انڈیا کے وزیر اعظم نریندر مودی کا کہنا ہے کہ د...</td>\n",
              "      <td>c2q3k4nq39no</td>\n",
              "      <td>[انڈیا کے وزیر اعظم نریندر مودی نے ایک حالیہ ر...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4954</th>\n",
              "      <td>https://www.bbc.com/urdu/articles/cz4dp89r8p8o</td>\n",
              "      <td>انڈیا کی شمالی ریاست اتراکھنڈ کے شہر ہلدوانی م...</td>\n",
              "      <td>cz4dp89r8p8o</td>\n",
              "      <td>[انڈیا کی شمالی ریاست اتراکھنڈ کے شہر ہلدوانی ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4955</th>\n",
              "      <td>https://www.bbc.com/urdu/articles/cn0995kvnzgo</td>\n",
              "      <td>کانگریس پارٹی نے گزشتہ سال اپنی حکومت بناتے ہو...</td>\n",
              "      <td>cn0995kvnzgo</td>\n",
              "      <td>[انڈیا کی جنوبی ریاست کرناٹک میں پیش آنے والے ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4956</th>\n",
              "      <td>https://www.bbc.com/urdu/articles/cy0ddzg77zko</td>\n",
              "      <td>انتہا پسند ہندو تنظیموں کے ارکان نے اس فلم کے ...</td>\n",
              "      <td>cy0ddzg77zko</td>\n",
              "      <td>[ایک انڈین فلم، جسے ’ہندوؤں کے مذہبی جذبات مجر...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4957</th>\n",
              "      <td>https://www.bbc.com/urdu/articles/czd8jkzn0nno</td>\n",
              "      <td>نوکری ٹھکرا کر یا نوکری چھوڑ کر اپنا کاروبار ش...</td>\n",
              "      <td>czd8jkzn0nno</td>\n",
              "      <td>[نوکری کو ٹھکرا کر یا نوکری کو چھوڑ کر اپنا کا...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4958</th>\n",
              "      <td>https://www.bbc.com/urdu/articles/crgye1440r0o</td>\n",
              "      <td>یو پی بورڈ میں ٹاپ کرنے والی طالبہ پراچی کہتی ...</td>\n",
              "      <td>crgye1440r0o</td>\n",
              "      <td>[یو پی بورڈ کے نتائج کا پانچواں دن تھا۔ صبح سا...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>4959 rows × 4 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-18d87ce0-354a-413c-b160-e1725f32308b')\"\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",
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              "  </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-18d87ce0-354a-413c-b160-e1725f32308b 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-18d87ce0-354a-413c-b160-e1725f32308b');\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-08977d0e-108d-49a4-a3ea-b611e6a02a79\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-08977d0e-108d-49a4-a3ea-b611e6a02a79')\"\n",
              "            title=\"Suggest charts\"\n",
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              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
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              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    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-08977d0e-108d-49a4-a3ea-b611e6a02a79 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_0f6e378a-c238-41f7-9417-59f392c4877d\">\n",
              "    <style>\n",
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              "        background-color: #E8F0FE;\n",
              "        border: none;\n",
              "        border-radius: 50%;\n",
              "        cursor: pointer;\n",
              "        display: none;\n",
              "        fill: #1967D2;\n",
              "        height: 32px;\n",
              "        padding: 0 0 0 0;\n",
              "        width: 32px;\n",
              "      }\n",
              "\n",
              "      .colab-df-generate:hover {\n",
              "        background-color: #E2EBFA;\n",
              "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "        fill: #174EA6;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate {\n",
              "        background-color: #3B4455;\n",
              "        fill: #D2E3FC;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate:hover {\n",
              "        background-color: #434B5C;\n",
              "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "        fill: #FFFFFF;\n",
              "      }\n",
              "    </style>\n",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('df')\"\n",
              "            title=\"Generate code using this dataframe.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
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              "    </button>\n",
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              "      (() => {\n",
              "      const buttonEl =\n",
              "        document.querySelector('#id_0f6e378a-c238-41f7-9417-59f392c4877d button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('df');\n",
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              "  </div>\n",
              "\n",
              "    </div>\n",
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            "application/vnd.google.colaboratory.intrinsic+json": {
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              "variable_name": "df",
              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 4959,\n  \"fields\": [\n    {\n      \"column\": \"url\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1856,\n        \"samples\": [\n          \"https://www.bbc.com/urdu/regional-63355513\",\n          \"https://www.bbc.com/urdu/world-59708445\",\n          \"https://www.bbc.com/urdu/pakistan-58928517\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"summary\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1843,\n        \"samples\": [\n          \"\\u0628\\u0627\\u0644\\u06cc \\u0648\\u0688 \\u0633\\u0679\\u0627\\u0631 \\u0631\\u0646\\u0628\\u06cc\\u0631 \\u06a9\\u067e\\u0648\\u0631 \\u06a9\\u06cc \\u06cc\\u06a9\\u0645 \\u062f\\u0633\\u0645\\u0628\\u0631 \\u06a9\\u0648 \\u0631\\u06cc\\u0644\\u06cc\\u0632 \\u06c1\\u0648\\u0646\\u06d2 \\u0648\\u0627\\u0644\\u06cc 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\\u0645\\u0635\\u0646\\u0648\\u0639\\u0627\\u062a \\u067e\\u0631 \\u062f\\u06cc \\u062c\\u0627\\u0646\\u06d2 \\u0648\\u0627\\u0644\\u06cc \\u0633\\u0628\\u0633\\u0688\\u06cc \\u0637\\u06d2 \\u0634\\u062f\\u06c1 \\u0645\\u0639\\u0627\\u06c1\\u062f\\u06d2 \\u06a9\\u06d2 \\u062e\\u0644\\u0627\\u0641 \\u062a\\u06be\\u06cc\\u06d4 \\u062c\\u0628\\u06a9\\u06c1 \\u067e\\u0627\\u06a9\\u0633\\u062a\\u0627\\u0646 \\u06a9\\u06d2 \\u0648\\u0632\\u06cc\\u0631 \\u062e\\u0632\\u0627\\u0646\\u06c1 \\u0645\\u0641\\u062a\\u0627\\u062d \\u0627\\u0633\\u0645\\u0627\\u0639\\u06cc\\u0644 \\u06a9\\u0627 \\u06a9\\u06c1\\u0646\\u0627 \\u06c1\\u06d2 \\u06a9\\u06c1 \\u0622\\u0626\\u06cc \\u0627\\u06cc\\u0645 \\u0627\\u06cc\\u0641 \\u0679\\u06cc\\u0645 \\u06a9\\u06d2 \\u0633\\u0627\\u062a\\u06be \\u062c\\u0627\\u0626\\u0632\\u06c1 \\u0645\\u0630\\u0627\\u06a9\\u0631\\u0627\\u062a \\u06a9\\u0627\\u0641\\u06cc \\u0645\\u0641\\u06cc\\u062f \\u0627\\u0648\\u0631 \\u062a\\u0639\\u06cc\\u0645\\u0631\\u06cc \\u0631\\u06c1\\u06d2\\u06d4\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"id\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1856,\n        \"samples\": [\n          \"e99e16cf-1a56-40be-93e6-2c9bd50bed10\",\n          \"2a50ce8f-c8c2-47f9-8b91-0e0d0d6d09da\",\n          \"5813042a-fa83-4941-afbc-2cdf487fe987\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"article\",\n      \"properties\": {\n        \"dtype\": \"object\",\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "t_len_summary = []\n",
        "t_len_article = []\n",
        "ratio = []\n",
        "\n",
        "#cats = df[\"category\"].value_counts()\n",
        "\n",
        "count = 0\n",
        "for i in ds:\n",
        "  para_count = 0\n",
        "  article_len = []\n",
        "  for j in i['article']:\n",
        "    tmp = {}\n",
        "    tmp['para'] = para_count\n",
        "    tmp['len'] = word_len(j)\n",
        "    article_len.append(tmp)\n",
        "    para_count += 1\n",
        "\n",
        "\n",
        "    # Display message after every 100 articles\n",
        "  #if count % 100 == 0 and count > 0:\n",
        "    print(f\"Total articles iterated: {count}\")\n",
        "    #break\n",
        "\n",
        "  count += 1\n",
        "  summary_len = word_len(i['summary'])\n",
        "  t_len_article.append(article_len)\n",
        "  t_len_summary.append(summary_len)\n",
        "  length = sum(tmp['len'] for tmp in article_len)\n",
        "  if length > 0:\n",
        "    ratio.append(summary_len / length * 100)\n",
        "  else:\n",
        "    ratio.append(0)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "m2Jv1furQKyg",
        "outputId": "a9a95fa3-7eeb-4a90-f677-1c3ff293d067"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[1;30;43mStreaming output truncated to the last 5000 lines.\u001b[0m\n",
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      ]
    },
    {
      "cell_type": "code",
      "source": [
        "with open('/content/drive/MyDrive/Urdu/BBC New/Length-Article-Initial.jsonl', 'w', encoding='utf-8') as f:\n",
        "  for i in t_len_article:\n",
        "    for j in i:\n",
        "      json.dump(j, f, ensure_ascii=False)\n",
        "      f.write(\"\\n\")\n",
        "    f.write(\"||\")\n",
        "    f.write(\"\\n\")\n",
        "\n",
        "with open('/content/drive/MyDrive/Urdu/BBC New/Length-Summary-Intial.txt', 'w') as f:\n",
        "  for i in t_len_summary:\n",
        "    f.write(str(i))\n",
        "    f.write(\"\\n\")\n",
        "with open('/content/drive/MyDrive/Urdu/BBC New/Ratios-Intial.txt', 'w') as f:\n",
        "  for i in ratio:\n",
        "    f.write(str(i))\n",
        "    f.write(\"\\n\")"
      ],
      "metadata": {
        "id": "a2nVMUS4-P-g"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "t_len_summary = []\n",
        "t_len_article = []\n",
        "ratio = []\n",
        "\n",
        "with open('/content/drive/MyDrive/Urdu/BBC New/Length-Article-Initial.jsonl', 'r', encoding='utf-8') as f:\n",
        "  tmp = []\n",
        "  for line in f:\n",
        "    if line.rstrip() == '||':\n",
        "      t_len_article.append(tmp)\n",
        "      tmp = []\n",
        "      continue\n",
        "    tmp.append(json.loads(line))\n",
        "  print ('No of Article / Summaries Pair : ', len(t_len_article))\n",
        "\n",
        "with open('/content/drive/MyDrive/Urdu/BBC New/Length-Summary-Intial.txt', 'r') as f:\n",
        "  for line in f:\n",
        "    t_len_summary.append(int(line.rstrip()))\n",
        "with open('/content/drive/MyDrive/Urdu/BBC New/Ratios-Intial.txt', 'r') as f:\n",
        "  for line in f:\n",
        "    ratio.append(float(line.rstrip()))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "gWdt8U6V-RUZ",
        "outputId": "7bca571d-77c5-4b4a-ce86-b0a7cf5bd168"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "No of Article / Summaries Pair :  4959\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print('Max Tokens in Summary(s) :', max(t_len_summary))\n",
        "print('Min Tokens in Summary(s) :', min(t_len_summary))\n",
        "print('Avg Tokens in Summary(s) :', sum(t_len_summary)/len(t_len_summary))\n",
        "print('Max Compression Ratio :', max(ratio))\n",
        "print('Min Compression Ratio :', min(ratio))\n",
        "print('Avg Compression Ratio :', sum(ratio)/len(ratio))\n",
        "article_len = []\n",
        "for i in t_len_article:\n",
        "  article_len.append(sum(tmp['len'] for tmp in i))\n",
        "print('Max Tokens in Article(s) :', max(article_len))\n",
        "print('Min Tokens in Article(s) :', min(article_len))\n",
        "print('Avg Tokens in Article(s) :', sum(article_len)/len(article_len))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "iGh_YGte-XzH",
        "outputId": "1b9df2f1-acbb-487f-a979-a1d9572c4ab2"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Max Tokens in Summary(s) : 105\n",
            "Min Tokens in Summary(s) : 0\n",
            "Avg Tokens in Summary(s) : 46.76830006049607\n",
            "Max Compression Ratio : 100.0\n",
            "Min Compression Ratio : 0.0\n",
            "Avg Compression Ratio : 4.188447478114642\n",
            "Max Tokens in Article(s) : 9388\n",
            "Min Tokens in Article(s) : 13\n",
            "Avg Tokens in Article(s) : 1424.6144383948376\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pd_article=pd.DataFrame({'length': article_len})\n",
        "pd_article.describe()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        },
        "id": "gtw5d-k--d58",
        "outputId": "531711e8-94ae-4394-ea47-31171d6bbad8"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "            length\n",
              "count  4959.000000\n",
              "mean   1424.614438\n",
              "std     719.789760\n",
              "min      13.000000\n",
              "25%     966.000000\n",
              "50%    1324.000000\n",
              "75%    1718.000000\n",
              "max    9388.000000"
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              "      <th>mean</th>\n",
              "      <td>1424.614438</td>\n",
              "    </tr>\n",
              "    <tr>\n",
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              "      <td>13.000000</td>\n",
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              "      <th>25%</th>\n",
              "      <td>966.000000</td>\n",
              "    </tr>\n",
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              "      <th>50%</th>\n",
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              "    <div class=\"colab-df-buttons\">\n",
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              "      buttonEl.style.display =\n",
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              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-9a4bab71-c18f-4c37-9981-c57b1300265b');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
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              "        docLink.innerHTML = docLinkHtml;\n",
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              "      --bg-color: #E8F0FE;\n",
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              "\n",
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              "\n",
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              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
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              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
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              "\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",
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              "    20% {\n",
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              "      border-left-color: var(--fill-color);\n",
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              "      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",
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              "    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-f8bbada0-a137-417b-99c6-78847531f287 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\": \"pd_article\",\n  \"rows\": 8,\n  \"fields\": [\n    {\n      \"column\": \"length\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 3124.0274565904224,\n        \"min\": 13.0,\n        \"max\": 9388.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          1424.6144383948376,\n          1324.0,\n          4959.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pd_summary=pd.DataFrame({'length': t_len_summary})\n",
        "pd_summary.describe()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        },
        "id": "-5mqXIF--hF-",
        "outputId": "c6668829-1689-4062-e7cb-7b6db4a13a11"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "            length\n",
              "count  4959.000000\n",
              "mean     46.768300\n",
              "std      13.783806\n",
              "min       0.000000\n",
              "25%      38.000000\n",
              "50%      45.000000\n",
              "75%      56.000000\n",
              "max     105.000000"
            ],
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              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>length</th>\n",
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              "      <th>count</th>\n",
              "      <td>4959.000000</td>\n",
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              "      <th>mean</th>\n",
              "      <td>46.768300</td>\n",
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              "      <th>std</th>\n",
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              "      <td>0.000000</td>\n",
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              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
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              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
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              "\n",
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              "      background-color: #E2EBFA;\n",
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              "\n",
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              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-389ee538-d321-41c7-9c46-6afa25f36e99 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-389ee538-d321-41c7-9c46-6afa25f36e99');\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",
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              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
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              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
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              "\n",
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              "  .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-4f37b913-4d28-499c-a913-07dca5f5c990 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\": \"pd_summary\",\n  \"rows\": 8,\n  \"fields\": [\n    {\n      \"column\": \"length\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1738.1667547389018,\n        \"min\": 0.0,\n        \"max\": 4959.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          46.76830006049607,\n          45.0,\n          4959.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pd_ratio=pd.DataFrame({'length': ratio})\n",
        "pd_ratio.describe()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        },
        "id": "aVXfV2nw-j7S",
        "outputId": "18ace2e4-a7d7-4ed1-dab4-029b5dd46d27"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "            length\n",
              "count  4959.000000\n",
              "mean      4.188447\n",
              "std       4.940009\n",
              "min       0.000000\n",
              "25%       2.566261\n",
              "50%       3.486239\n",
              "75%       4.750566\n",
              "max     100.000000"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-b27a4b29-77c9-4452-a36f-f43c6a89981f\" 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",
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              "\n",
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              "        text-align: right;\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>length</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>4959.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>4.188447</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>4.940009</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>2.566261</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>3.486239</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>4.750566</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>100.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
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              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-b27a4b29-77c9-4452-a36f-f43c6a89981f')\"\n",
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              "  </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",
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              "\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-b27a4b29-77c9-4452-a36f-f43c6a89981f 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-b27a4b29-77c9-4452-a36f-f43c6a89981f');\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-cde3ba4a-b033-454c-89d9-d33aa505e1c3\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-cde3ba4a-b033-454c-89d9-d33aa505e1c3')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
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              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    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-cde3ba4a-b033-454c-89d9-d33aa505e1c3 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\": \"pd_ratio\",\n  \"rows\": 8,\n  \"fields\": [\n    {\n      \"column\": \"length\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1747.5419912870993,\n        \"min\": 0.0,\n        \"max\": 4959.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          4.1884474781146555,\n          3.486238532110092,\n          4959.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "\n",
        "tokenized_articles_lengths = article_len\n",
        "ax=sns.histplot(tokenized_articles_lengths)\n",
        "ax.set(xlabel='Length of tokenized articles', ylabel='Count', xlim=(0, 4000), title='Distribution of the tokenized articles lengths')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 472
        },
        "id": "BkkbynrR-n5w",
        "outputId": "5cc805dd-48ca-480c-a47f-f4faf95a9980"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from scipy.stats import percentileofscore\n",
        "print(f'Percentile of length=512: {int(percentileofscore(tokenized_articles_lengths,513))}%')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8EIceNW9-u-R",
        "outputId": "408eeade-9a00-474f-9bc8-0f6adbb502ae"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Percentile of length=512: 3%\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#FUNC: score paras from articles based on rouge\n",
        "def score_paras(paras, summary, articleNo):\n",
        "  result = []\n",
        "  count = 0\n",
        "  for p in paras:\n",
        "    tmp = {}\n",
        "    tmp['index'] = count\n",
        "    tmp['para'] = p\n",
        "    rouge = Rouge()\n",
        "    if t_len_article[articleNo][count]['len'] > 3:\n",
        "      scores = rouge.get_scores(p, summary, ignore_empty=True)\n",
        "      tmp['score'] = scores[0]['rouge-1']['r']\n",
        "    else:\n",
        "      tmp['score'] = 0\n",
        "    count += 1\n",
        "    result.append(tmp)\n",
        "  return result\n",
        "\n",
        "#FUNC: trunc length of articles to 512 tokens for Bert Tokenizer\n",
        "def trunc_article(paras, summary, articleNo):\n",
        "  # strip blank spaces\n",
        "  for p in paras:\n",
        "    p = p.lstrip().rstrip()\n",
        "\n",
        "  if len(' '.join(paras)) != 0 and len(summary) != 0:\n",
        "    if article_len[articleNo] <= 512:\n",
        "      #print('Length less than 512..')\n",
        "      return paras, article_len[articleNo]\n",
        "    else:\n",
        "      result = score_paras(paras, summary, articleNo)\n",
        "      result = sorted(result, key = lambda i: i['score'])\n",
        "\n",
        "      for r in result:\n",
        "        r['len'] = [item for item in t_len_article[articleNo] if item['para'] == r['index']][0]['len']\n",
        "\n",
        "      # while length is greater than 512\n",
        "      para_removed = 0\n",
        "\n",
        "      result_paras = []\n",
        "      len_article = 0\n",
        "\n",
        "      while sum(tmp['len'] for tmp in result) > 512:\n",
        "        #print('Length > 512 : ', sum(tmp['len'] for tmp in result))\n",
        "        del result[0]\n",
        "        para_removed += 1\n",
        "        if sum(tmp['len'] for tmp in result) <= 512:\n",
        "          result = sorted(result, key = lambda i: i['index'])\n",
        "          tmp = {}\n",
        "          for i in result:\n",
        "            len_article = sum(tmp['len'] for tmp in result)\n",
        "            result_paras.append(i['para'])\n",
        "\n",
        "      return result_paras, len_article\n",
        "\n",
        "  else:\n",
        "    print(\"Zero Length Article/ Summary during Trunc..\")\n",
        "    return 0"
      ],
      "metadata": {
        "id": "RtzS1gx6-3ZN"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "count = 0\n",
        "zerocount = 0\n",
        "temp_ds = copy.deepcopy(ds)\n",
        "\n",
        "trunc_len = []\n",
        "for row in temp_ds:\n",
        "  trunc = trunc_article(row['article'], row['summary'], count)\n",
        "  if trunc == 0:\n",
        "    zerocount += 1\n",
        "    count += 1\n",
        "    continue\n",
        "  else:\n",
        "    row['article'], tmp_len = trunc\n",
        "    trunc_len.append(tmp_len)\n",
        "    #print('Len of Row : ',word_len(''.join(row['article'])))\n",
        "  #print('After Processing : ', len(row['article']))\n",
        "  if count % 100 == 0:\n",
        "    print('Article Trunc : ', count)\n",
        "  count += 1\n",
        "print('Zero Count : ', zerocount)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "CjW9ltR1_APJ",
        "outputId": "58a38a96-e62b-4ab0-ae42-900e1bf285ec"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Article Trunc :  0\n",
            "Zero Length Article/ Summary during Trunc..\n",
            "Article Trunc :  100\n",
            "Article Trunc :  200\n",
            "Zero Length Article/ Summary during Trunc..\n",
            "Article Trunc :  300\n",
            "Article Trunc :  400\n",
            "Article Trunc :  500\n",
            "Article Trunc :  600\n",
            "Article Trunc :  700\n",
            "Article Trunc :  800\n",
            "Article Trunc :  900\n",
            "Zero Length Article/ Summary during Trunc..\n",
            "Article Trunc :  1000\n",
            "Zero Length Article/ Summary during Trunc..\n",
            "Article Trunc :  1100\n",
            "Zero Length Article/ Summary during Trunc..\n",
            "Article Trunc :  1200\n",
            "Zero Length Article/ Summary during Trunc..\n",
            "Zero Length Article/ Summary during Trunc..\n",
            "Zero Length Article/ Summary during Trunc..\n",
            "Article Trunc :  1300\n",
            "Article Trunc :  1400\n",
            "Zero Length Article/ Summary during Trunc..\n",
            "Article Trunc :  1500\n",
            "Article Trunc :  1600\n",
            "Zero Length Article/ Summary during Trunc..\n",
            "Article Trunc :  1700\n",
            "Article Trunc :  1800\n",
            "Article Trunc :  1900\n",
            "Article Trunc :  2000\n",
            "Article Trunc :  2100\n",
            "Article Trunc :  2200\n",
            "Article Trunc :  2300\n",
            "Zero Length Article/ Summary during Trunc..\n",
            "Article Trunc :  2400\n",
            "Zero Length Article/ Summary during Trunc..\n",
            "Article Trunc :  2500\n",
            "Zero Length Article/ Summary during Trunc..\n",
            "Article Trunc :  2600\n",
            "Zero Length Article/ Summary during Trunc..\n",
            "Zero Length Article/ Summary during Trunc..\n",
            "Zero Length Article/ Summary during Trunc..\n",
            "Article Trunc :  2700\n",
            "Article Trunc :  2800\n",
            "Article Trunc :  2900\n",
            "Zero Length Article/ Summary during Trunc..\n",
            "Article Trunc :  3000\n",
            "Article Trunc :  3100\n",
            "Zero Length Article/ Summary during Trunc..\n",
            "Article Trunc :  3300\n",
            "Zero Length Article/ Summary during Trunc..\n",
            "Article Trunc :  3400\n",
            "Article Trunc :  3500\n",
            "Article Trunc :  3600\n",
            "Article Trunc :  3700\n",
            "Article Trunc :  3800\n",
            "Article Trunc :  3900\n",
            "Article Trunc :  4000\n",
            "Zero Length Article/ Summary during Trunc..\n",
            "Article Trunc :  4100\n",
            "Zero Length Article/ Summary during Trunc..\n",
            "Article Trunc :  4200\n",
            "Zero Length Article/ Summary during Trunc..\n",
            "Article Trunc :  4300\n",
            "Zero Length Article/ Summary during Trunc..\n",
            "Zero Length Article/ Summary during Trunc..\n",
            "Zero Length Article/ Summary during Trunc..\n",
            "Article Trunc :  4400\n",
            "Article Trunc :  4500\n",
            "Article Trunc :  4600\n",
            "Zero Length Article/ Summary during Trunc..\n",
            "Article Trunc :  4700\n",
            "Article Trunc :  4800\n",
            "Article Trunc :  4900\n",
            "Zero Count :  26\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "count = 0\n",
        "ds_0 = []\n",
        "for i in article_len:\n",
        "  copy_flag = True\n",
        "  if i < 50 or ratio[count] > 50 or ratio[count] == 0:\n",
        "     copy_flag = False\n",
        "  if copy_flag:\n",
        "    ds_0.append(temp_ds[count])\n",
        "  count += 1"
      ],
      "metadata": {
        "id": "11PKm164_H3I"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "save_jsonl(ds_0, '/content/drive/MyDrive/Urdu/BBC New/BBCUr512.jsonl')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "RUsfdWbKAb1K",
        "outputId": "e3fe530b-70a0-49de-92c9-d7ce238d3694"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "JSONL File saved..\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#join paras\n",
        "for i in ds_0:\n",
        "  i['article'] = ' '.join(i['article'])"
      ],
      "metadata": {
        "id": "j7lxNvHKAfKq"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "save_jsonl(ds_0, '/content/drive/MyDrive/Urdu/BBC New/BBCUr512J.jsonl')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cs4A7V2JAh3R",
        "outputId": "a42020c1-f8ea-452f-d46d-4cd09f0c1d6b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "JSONL File saved..\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "ds_p = read_jsonl('/content/drive/MyDrive/Urdu/BBC New/BBCUr512.jsonl')\n",
        "df_p = pd.DataFrame(ds_p)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Rrd6KsjPAkG6",
        "outputId": "3240f6dd-7270-4d09-fad0-110e4341ded0"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "No of Article / Summaries Pair :  4916\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "t_len_summary2 = []\n",
        "t_len_article2 = []\n",
        "ratio2 = []\n",
        "count = 0\n",
        "for i in ds_p:\n",
        "  para_count = 0\n",
        "  article_len = []\n",
        "  for j in i['article']:\n",
        "    tmp = {}\n",
        "    tmp['para'] = para_count\n",
        "    tmp['len'] = word_len(j)\n",
        "    article_len.append(tmp)\n",
        "    para_count += 1\n",
        "  if count % 100 == 0 and count > 0:\n",
        "    print(f\"Total articles iterated: {count}\")\n",
        "  summary_len = word_len(i['summary'])\n",
        "  count +=1\n",
        "\n",
        "  t_len_article2.append(article_len)\n",
        "  t_len_summary2.append(summary_len)\n",
        "  length = sum(tmp['len'] for tmp in article_len)\n",
        "  if length > 0:\n",
        "    ratio2.append(summary_len / length * 100)\n",
        "  else:\n",
        "    ratio2.append(0)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2yYsm3xyAm_5",
        "outputId": "899b0d09-821c-4f28-acca-5b5067de31cf"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Total articles iterated: 100\n",
            "Total articles iterated: 200\n",
            "Total articles iterated: 300\n",
            "Total articles iterated: 400\n",
            "Total articles iterated: 500\n",
            "Total articles iterated: 600\n",
            "Total articles iterated: 700\n",
            "Total articles iterated: 800\n",
            "Total articles iterated: 900\n",
            "Total articles iterated: 1000\n",
            "Total articles iterated: 1100\n",
            "Total articles iterated: 1200\n",
            "Total articles iterated: 1300\n",
            "Total articles iterated: 1400\n",
            "Total articles iterated: 1500\n",
            "Total articles iterated: 1600\n",
            "Total articles iterated: 1700\n",
            "Total articles iterated: 1800\n",
            "Total articles iterated: 1900\n",
            "Total articles iterated: 2000\n",
            "Total articles iterated: 2100\n",
            "Total articles iterated: 2200\n",
            "Total articles iterated: 2300\n",
            "Total articles iterated: 2400\n",
            "Total articles iterated: 2500\n",
            "Total articles iterated: 2600\n",
            "Total articles iterated: 2700\n",
            "Total articles iterated: 2800\n",
            "Total articles iterated: 2900\n",
            "Total articles iterated: 3000\n",
            "Total articles iterated: 3100\n",
            "Total articles iterated: 3200\n",
            "Total articles iterated: 3300\n",
            "Total articles iterated: 3400\n",
            "Total articles iterated: 3500\n",
            "Total articles iterated: 3600\n",
            "Total articles iterated: 3700\n",
            "Total articles iterated: 3800\n",
            "Total articles iterated: 3900\n",
            "Total articles iterated: 4000\n",
            "Total articles iterated: 4100\n",
            "Total articles iterated: 4200\n",
            "Total articles iterated: 4300\n",
            "Total articles iterated: 4400\n",
            "Total articles iterated: 4500\n",
            "Total articles iterated: 4600\n",
            "Total articles iterated: 4700\n",
            "Total articles iterated: 4800\n",
            "Total articles iterated: 4900\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "with open('/content/drive/MyDrive/Urdu/BBC New/Length-Article-512.jsonl', 'w', encoding='utf-8') as f:\n",
        "  for i in t_len_article2:\n",
        "    for j in i:\n",
        "      json.dump(j, f, ensure_ascii=False)\n",
        "      f.write(\"\\n\")\n",
        "    f.write(\"||\")\n",
        "    f.write(\"\\n\")\n",
        "\n",
        "with open('/content/drive/MyDrive/Urdu/BBC New/Length-Summary-512.txt', 'w') as f:\n",
        "  for i in t_len_summary2:\n",
        "    f.write(str(i))\n",
        "    f.write(\"\\n\")\n",
        "with open('/content/drive/MyDrive/Urdu/BBC New/Ratios-512.txt', 'w') as f:\n",
        "  for i in ratio2:\n",
        "    f.write(str(i))\n",
        "    f.write(\"\\n\")"
      ],
      "metadata": {
        "id": "TrbRRsZ-GRfk"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "t_len_summary2 = []\n",
        "t_len_article2 = []\n",
        "ratio2 = []\n",
        "\n",
        "with open('/content/drive/MyDrive/Urdu/BBC New/Length-Article-512.jsonl', 'r', encoding='utf-8') as f:\n",
        "  tmp = []\n",
        "  for line in f:\n",
        "    if line.rstrip() == '||':\n",
        "      t_len_article2.append(tmp)\n",
        "      tmp = []\n",
        "      continue\n",
        "    tmp.append(json.loads(line))\n",
        "  print ('No of Article / Summaries Pair : ', len(t_len_article2))\n",
        "\n",
        "with open('/content/drive/MyDrive/Urdu/BBC New/Length-Summary-512.txt', 'r') as f:\n",
        "  for line in f:\n",
        "    t_len_summary2.append(int(line.rstrip()))\n",
        "with open('/content/drive/MyDrive/Urdu/BBC New/Ratios-512.txt', 'r') as f:\n",
        "  for line in f:\n",
        "    ratio2.append(float(line.rstrip()))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "iHS-tfW2GSYV",
        "outputId": "794787e7-b0e0-42c6-b127-30e95acfa412"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "No of Article / Summaries Pair :  4916\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print('Max Tokens in Summary(s) :', max(t_len_summary2))\n",
        "print('Min Tokens in Summary(s) :', min(t_len_summary2))\n",
        "print('Avg Tokens in Summary(s) :', sum(t_len_summary2)/len(t_len_summary2))\n",
        "print('Max Compression Ratio :', max(ratio2))\n",
        "print('Min Compression Ratio :', min(ratio2))\n",
        "print('Avg Compression Ratio :', sum(ratio2)/len(ratio2))\n",
        "article_len = []\n",
        "for i in t_len_article2:\n",
        "  article_len.append(sum(tmp['len'] for tmp in i))\n",
        "print('Max Tokens in Article(s) :', max(article_len))\n",
        "print('Min Tokens in Article(s) :', min(article_len))\n",
        "print('Avg Tokens in Article(s) :', sum(article_len)/len(article_len))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fTZoIgkCGWcb",
        "outputId": "0fe2b45c-c067-4cd1-8903-25333f9c5082"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Max Tokens in Summary(s) : 105\n",
            "Min Tokens in Summary(s) : 12\n",
            "Avg Tokens in Summary(s) : 47.035394629780306\n",
            "Max Compression Ratio : 39.23076923076923\n",
            "Min Compression Ratio : 2.5210084033613445\n",
            "Avg Compression Ratio : 9.821779378846337\n",
            "Max Tokens in Article(s) : 512\n",
            "Min Tokens in Article(s) : 71\n",
            "Avg Tokens in Article(s) : 482.576688364524\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pd_article=pd.DataFrame({'length': article_len})\n",
        "pd_article.describe()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        },
        "id": "1Mtr0tI8GZAT",
        "outputId": "900cd59a-e95f-40cd-9238-cf92ca982c46"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "            length\n",
              "count  4916.000000\n",
              "mean    482.576688\n",
              "std      31.201932\n",
              "min      71.000000\n",
              "25%     473.000000\n",
              "50%     487.000000\n",
              "75%     500.000000\n",
              "max     512.000000"
            ],
            "text/html": [
              "\n",
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              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "    <tr style=\"text-align: right;\">\n",
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              "      <th>length</th>\n",
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              "      <th>mean</th>\n",
              "      <td>482.576688</td>\n",
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              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>31.201932</td>\n",
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              "      <th>min</th>\n",
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              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
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              "          + ' to learn more about interactive tables.';\n",
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              "\n",
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              "\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",
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              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
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              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
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              "    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-c239719b-70de-4fce-afa1-99923673956b 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\": \"pd_article\",\n  \"rows\": 8,\n  \"fields\": [\n    {\n      \"column\": \"length\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1621.2292638825006,\n        \"min\": 31.20193178308438,\n        \"max\": 4916.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          482.576688364524,\n          487.0,\n          4916.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 38
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pd_summary=pd.DataFrame({'length': t_len_summary2})\n",
        "pd_summary.describe()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        },
        "id": "uPzEzhzPGbGE",
        "outputId": "ffe77718-ab0a-44c8-db1b-f618ae20c181"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "            length\n",
              "count  4916.000000\n",
              "mean     47.035395\n",
              "std      13.399107\n",
              "min      12.000000\n",
              "25%      38.000000\n",
              "50%      45.000000\n",
              "75%      56.000000\n",
              "max     105.000000"
            ],
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              "\n",
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              "      <td>4916.000000</td>\n",
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              "      <th>mean</th>\n",
              "      <td>47.035395</td>\n",
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              "      <td>12.000000</td>\n",
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              "      <td>38.000000</td>\n",
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              "\n",
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              "\n",
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              "      fill: #D2E3FC;\n",
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              "\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",
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              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-4faa9b0e-4780-4fdc-83cd-faa5559785c9 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-4faa9b0e-4780-4fdc-83cd-faa5559785c9');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
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              "\n",
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              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-38c78cd1-176a-490d-8c2b-ff601e201ce2')\"\n",
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              "    </g>\n",
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              "  </button>\n",
              "\n",
              "<style>\n",
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              "      --bg-color: #E8F0FE;\n",
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              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
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              "      --hover-bg-color: #434B5C;\n",
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              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
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              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
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              "    border-radius: 50%;\n",
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              "\n",
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              "    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-38c78cd1-176a-490d-8c2b-ff601e201ce2 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\": \"pd_summary\",\n  \"rows\": 8,\n  \"fields\": [\n    {\n      \"column\": \"length\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1722.3292165823327,\n        \"min\": 12.0,\n        \"max\": 4916.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          47.035394629780306,\n          45.0,\n          4916.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 41
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pd_ratio=pd.DataFrame({'length': ratio2})\n",
        "pd_ratio.describe()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        },
        "id": "79WGh0ueGdg-",
        "outputId": "0d8298f4-e625-40c0-b356-a8ebe5812f47"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "            length\n",
              "count  4916.000000\n",
              "mean      9.821779\n",
              "std       3.070791\n",
              "min       2.521008\n",
              "25%       7.773109\n",
              "50%       9.421842\n",
              "75%      11.548240\n",
              "max      39.230769"
            ],
            "text/html": [
              "\n",
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              "        vertical-align: middle;\n",
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              "\n",
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              "\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>length</th>\n",
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              "      <td>4916.000000</td>\n",
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              "      <th>mean</th>\n",
              "      <td>9.821779</td>\n",
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              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>3.070791</td>\n",
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              "      <th>25%</th>\n",
              "      <td>7.773109</td>\n",
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              "      <td>39.230769</td>\n",
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              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
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              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-c6c144da-0741-47d2-994f-8ed125ac9da4')\"\n",
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              "  </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",
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              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
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              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
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              "\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-c6c144da-0741-47d2-994f-8ed125ac9da4 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-c6c144da-0741-47d2-994f-8ed125ac9da4');\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-8b263eac-191b-474f-8bba-c87effbaba7c\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-8b263eac-191b-474f-8bba-c87effbaba7c')\"\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-8b263eac-191b-474f-8bba-c87effbaba7c 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\": \"pd_ratio\",\n  \"rows\": 8,\n  \"fields\": [\n    {\n      \"column\": \"length\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1733.8955063924948,\n        \"min\": 2.5210084033613445,\n        \"max\": 4916.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          9.821779378846362,\n          9.421841541755889,\n          4916.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 40
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "\n",
        "tokenized_articles_lengths = article_len\n",
        "ax=sns.histplot(tokenized_articles_lengths)\n",
        "ax.set(xlabel='Length of tokenized articles', ylabel='Count', xlim=(0, 530), title='Distribution of the tokenized articles lengths')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 472
        },
        "id": "PPayT3pkGf3I",
        "outputId": "32dbb4e0-c248-4df9-fe90-83a7211e119f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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FlfVmlU2bNkVaWhrWrl2LN998U+fLO3/vwOLFi9GyZcsiX1+wzoq+T48fP8agQYOgVCrxyy+/6FylmF/Hu+++i6CgoCJfX5EvyKIMHjwYR44cwYwZM9CyZUtYW1sjLy8PPXr0KHJva1X8vpWmPO/L4MGD8fLLL2PTpk3Ys2cPFi9ejE8++QQbN25Ez549y73OtWvXFhkOCl5VWl1/F0pb37OfuylTpqBv377YvHkzdu/ejTlz5mDhwoWIjo5Gq1atqqvUGothh8ok/8S64v5Y5zMyMkJAQAACAgKwdOlSLFiwAB988AH27duHwMDASr/jcv5/bPmEENBqtfDx8ZGm1a5du8j7uVy7dk3nP8Ty1Obu7o7IyEhkZmbq7N25ePGiNL8yuLu748yZM8jLy9PZu/O863ne98HLywtCCHh6eqJhw4aVtn53d3fk5eXh0qVL0t4rAEhJSUFaWlqh7bW3t8eGDRvQsWNHBAQE4NChQ3BxcZFqBJ7+1x4YGFjuGsvj7bffRmxsLA4ePFjopPr8z5ipqWmpdbi7uxf6TAMo0z2e/vnnH0RFRSE8PBwffvihNL2o5ZWkrJ8NBwcHqFQqnDt3rlzLL+/74uzsjLfeegtvvfUWUlNT0bp1a3z88cflCjv563R0dKy0z4K7uzv27dsn3R4jn1arLdS2sv7ueXl5Yfr06Zg+fTouXbqEli1bYsmSJTpXyVLReM4OlSo6Ohrz58+Hp6dniecO3Lt3r9C0/P/c8i8bzr+PR2XdTO5///ufznlEGzZsQFJSks4fQi8vLxw7dkznUtht27YVukS6PLX16tULubm5+O9//6szfdmyZVAoFOX6Q1zaepKTk/Hzzz9L03JycvDFF1/A2toanTt3rtByraysnus9GDBgAIyNjREeHl5or4cQotClzkWtHyjc17169QIALF++XGd6/mGh3r17F1qWq6srIiMj8fDhQ3Tr1k1at6+vL7y8vPDpp58iKyur0Otu375dYo1ltWrVKnz99deIiIgodHUX8PQLtkuXLvj666+RlJRUYh29evXCsWPH8Oeff+rM//HHH0utI3/vQMH3o2BflqasvwdGRkbo378/tm7dipMnTxaaX9zesLK+L7m5uYUOvTk6OsLFxaVMtyF4VlBQEFQqFRYsWIAnT54Uu87yLvPJkyc6N5jMy8uTLjN/1vP+3Xvw4AEePXqkM83Lywu1atUqd1+8qLhnh3Ts3LkTFy9eRE5ODlJSUhAdHY29e/fC3d0dv//+e4k3FZs3bx4OHjyI3r17w93dHampqfjyyy/h6uqKjh07Anj6C2pjY4OvvvoKtWrVgpWVFfz8/Cp87oCtrS06duyI0aNHIyUlBcuXL0f9+vV1ThocO3YsNmzYgB49emDw4MG4fPkyfvjhh0KXW5entr59++KVV17BBx98gKtXr6JFixbYs2cPtmzZgilTphRadkWNHz8eX3/9NUaNGoWYmBh4eHhgw4YNOHz4MJYvX17onKGy8vX1RWRkJJYuXQoXFxd4enoWea5Icby8vPDRRx8hNDQUV69eRf/+/VGrVi1cuXIFmzZtwvjx4/Huu++WuH4A+OCDDzB06FCYmpqib9++aNGiBYKDg7Fy5UqkpaWhc+fO+PPPP7FmzRr0798fr7zySpHLq1+/Pvbs2YMuXbogKCgI0dHRUKlU+Pbbb9GzZ080bdoUo0ePRp06dXDz5k3s27cPKpUKW7duLV/HFXDnzh289dZb8Pb2hlKpLPQf9muvvQYrKytERESgY8eOaN68OcaNG4d69eohJSUFR48exY0bN3D69GkAwHvvvYe1a9eiR48eeOedd6RLz/P38JVEpVKhU6dOWLRoEZ48eYI6depgz549uHLlSrm2Kf+9efvttxEUFARjY2MMHTq0yLYLFizAnj170LlzZ4wfPx5NmjRBUlISfv31Vxw6dKjI2w8YGRmV6X3JzMyEq6srBg0ahBYtWsDa2hqRkZE4ceIElixZUq5tUqlUWLFiBUaMGIHWrVtj6NChcHBwQGJiIrZv344OHToU+selNP3790e7du0wffp0aLVaNG7cGL///rv0T9+ze3PK06dFSUhIQEBAAAYPHgxvb2+YmJhg06ZNSElJKddyXmh6uQaMDE7+pZr5g5mZmdBoNKJbt27is88+07nEOV/BS8+joqJEv379hIuLizAzMxMuLi5i2LBhIiEhQed1W7ZsEd7e3sLExETnEs3OnTuLpk2bFllfcZee//TTTyI0NFQ4OjoKCwsL0bt3b3Ht2rVCr1+yZImoU6eOUCqVokOHDuLkyZOFlllSbQUvPRfi6eWsU6dOFS4uLsLU1FQ0aNBALF68WOdyWiGeXq5b1OWzpV3CnC8lJUWMHj1a2NvbCzMzM9G8efMiL48vz6XnFy9eFJ06dRIWFhYCgFRH/nta8PYBBS/lzffbb7+Jjh07CisrK2FlZSUaN24sQkJCRHx8fKk1zJ8/X9SpU0cYGRnpLPvJkyciPDxceHp6ClNTU+Hm5iZCQ0N1LtsubnuPHz8uatWqJTp16iRdhn3q1CkxYMAAYWdnJ5RKpXB3dxeDBw8WUVFR0uvKs93Pvm/5lw4XNzz7usuXL4uRI0cKjUYjTE1NRZ06dUSfPn3Ehg0bdNZ55swZ0blzZ2Fubi7q1Kkj5s+fL7777rsyXXp+48YN8dprrwkbGxuhVqvF66+/Lm7dulXokvHitlcIIXJycsTkyZOFg4ODUCgUOr/jBZcjhBDXrl0TI0eOFA4ODkKpVIp69eqJkJAQkZ2dLYQofOl5vtLel+zsbDFjxgzRokULUatWLWFlZSVatGghvvzyyxL7QIjiP6/79u0TQUFBQq1WC3Nzc+Hl5SVGjRolTp48KbUJDg4WVlZWhZZZ8O+dEELcvn1bvPHGG6JWrVpCrVaLUaNGicOHDwsAYv369aX2af7np6hLyp/t6zt37oiQkBDRuHFjYWVlJdRqtfDz8xO//PJLqX1BTymEMNAzJImIiGqYzZs347XXXsOhQ4fQoUMHfZdD/x/DDhERUQU8fPhQ54q23NxcdO/eHSdPnkRycrJernajovGcHSIiogqYPHkyHj58CH9/f2RnZ2Pjxo04cuQIFixYwKBjYLhnh4iIqALWrVuHJUuWQKvV4tGjR6hfvz4mTpyISZMm6bs0KoBhh4iIiGSN99khIiIiWWPYISIiIlnjCcp4etfLW7duoVatWpX+OAMiIiKqGkIIZGZmwsXFpcQHTjPsALh16xbc3Nz0XQYRERFVwPXr1+Hq6lrsfIYdQLrl/vXr16FSqfRcDREREZVFRkYG3NzcSn10DsMO/u8ZJiqVimGHiIiohintFBSeoExERESyxrBDREREssawQ0RERLLGsENERESyxrBDREREssawQ0RERLLGsENERESyxrBDREREssawQ0RERLLGsENERESyxrBDREREssawQ0RERLLGsENERESyxrBDREREsmai7wKIiIjoxZCTk4OEhARpvGHDhjAxqfoowrBDRERE1SIhIQFvRmyDtYMrsm7fwNchfeDt7V3l62XYISIiompj7eAKtYtnta6T5+wQERGRrDHsEBERkawx7BAREZGsMewQERGRrPEEZSIiIiozfV0+/jwMuzoiIiIyKPq6fPx5MOwQERFRuejj8vHnwXN2iIiISNYYdoiIiEjWGHaIiIhI1hh2iIiISNYYdoiIiEjWGHaIiIhI1hh2iIiISNYYdoiIiEjWGHaIiIhI1hh2iIiISNYYdoiIiEjWGHaIiIhI1vQadlasWAEfHx+oVCqoVCr4+/tj586d0vwuXbpAoVDoDBMmTNBZRmJiInr37g1LS0s4OjpixowZyMnJqe5NISIioiLk5OQgLi4OcXFx0Gq1EEJUew16feq5q6sr/vOf/6BBgwYQQmDNmjXo168fTp06haZNmwIAxo0bh3nz5kmvsbS0lH7Ozc1F7969odFocOTIESQlJWHkyJEwNTXFggULqn17iIiISFdCQgLejNgGawdXpMbHQFW3abXXoNew07dvX53xjz/+GCtWrMCxY8eksGNpaQmNRlPk6/fs2YO4uDhERkbCyckJLVu2xPz58zFz5kyEhYXBzMysyreBiIiISmbt4Aq1iyeybt/Qy/oN5pyd3NxcrF+/Hvfv34e/v780/ccff4S9vT2aNWuG0NBQPHjwQJp39OhRNG/eHE5OTtK0oKAgZGRk4Pz588WuKzs7GxkZGToDERERyZNe9+wAwNmzZ+Hv749Hjx7B2toamzZtgre3NwDgjTfegLu7O1xcXHDmzBnMnDkT8fHx2LhxIwAgOTlZJ+gAkMaTk5OLXefChQsRHh5eRVtEREREhkTvYadRo0aIjY1Feno6NmzYgODgYBw4cADe3t4YP3681K558+ZwdnZGQEAALl++DC8vrwqvMzQ0FNOmTZPGMzIy4Obm9lzbQURERIZJ74exzMzMUL9+ffj6+mLhwoVo0aIFPvvssyLb+vn5AQC0Wi0AQKPRICUlRadN/nhx5/kAgFKplK4Ayx+IiIhInvQedgrKy8tDdnZ2kfNiY2MBAM7OzgAAf39/nD17FqmpqVKbvXv3QqVSSYfCiIiI6MWm18NYoaGh6NmzJ+rWrYvMzEysW7cO+/fvx+7du3H58mWsW7cOvXr1gp2dHc6cOYOpU6eiU6dO8PHxAQB0794d3t7eGDFiBBYtWoTk5GTMnj0bISEhUCqV+tw0IiIiMhB6DTupqakYOXIkkpKSoFar4ePjg927d6Nbt264fv06IiMjsXz5cty/fx9ubm4YOHAgZs+eLb3e2NgY27Ztw8SJE+Hv7w8rKysEBwfr3JeHiIiIXmx6DTvfffddsfPc3Nxw4MCBUpfh7u6OHTt2VGZZREREJCMGd84OERERUWVi2CEiIiJZY9ghIiIiWWPYISIiIlnT+x2UiYiIyPDk5OQgISFBGm/YsCFMTGpmbKiZVRMREVGVSkhIwJsR22Dt4Iqs2zfwdUifGnvDXoYdIiIiKpK1gyvULp76LuO58ZwdIiIikjWGHSIiIpI1hh0iIiKSNYYdIiIikjWGHSIiIpI1Xo1FRET0ApDTfXPK68XYSiIiohecnO6bU14MO0RERC8Iudw3p7x4zg4RERHJGvfsEBERUaV69vwgrVYLIYRe62HYISIiokr17PlBqfExUNVtqtd6eBiLiIiIKl3++UGWtk76LoVhh4iIiOSNYYeIiIhkjWGHiIiIZI1hh4iIiGSNYYeIiIhkjWGHiIiIZI1hh4iIiGSNYYeIiIhkjWGHiIiIZI1hh4iIiGSNYYeIiIhkjWGHiIiIZI1hh4iIiGSNYYeIiIhkjWGHiIiIZI1hh4iIiGRNr2FnxYoV8PHxgUqlgkqlgr+/P3bu3CnNf/ToEUJCQmBnZwdra2sMHDgQKSkpOstITExE7969YWlpCUdHR8yYMQM5OTnVvSlERERkoPQadlxdXfGf//wHMTExOHnyJLp27Yp+/frh/PnzAICpU6di69at+PXXX3HgwAHcunULAwYMkF6fm5uL3r174/Hjxzhy5AjWrFmD1atX48MPP9TXJhEREZGBMdHnyvv27asz/vHHH2PFihU4duwYXF1d8d1332HdunXo2rUrAGDVqlVo0qQJjh07hvbt22PPnj2Ii4tDZGQknJyc0LJlS8yfPx8zZ85EWFgYzMzM9LFZREREZEAM5pyd3NxcrF+/Hvfv34e/vz9iYmLw5MkTBAYGSm0aN26MunXr4ujRowCAo0ePonnz5nBycpLaBAUFISMjQ9o7RERERFUjLy8XWq0WcXFxiIuLM9jTSPS6ZwcAzp49C39/fzx69AjW1tbYtGkTvL29ERsbCzMzM9jY2Oi0d3JyQnJyMgAgOTlZJ+jkz8+fV5zs7GxkZ2dL4xkZGZW0NURERC+OB3eT8NGWq7Bzy0LW7Rv4OqQPvL299V1WIXoPO40aNUJsbCzS09OxYcMGBAcH48CBA1W6zoULFyI8PLxK10FERPQisLKvA7WLp77LKJHeD2OZmZmhfv368PX1xcKFC9GiRQt89tln0Gg0ePz4MdLS0nTap6SkQKPRAAA0Gk2hq7Pyx/PbFCU0NBTp6enScP369crdKCIiIjIYeg87BeXl5SE7Oxu+vr4wNTVFVFSUNC8+Ph6JiYnw9/cHAPj7++Ps2bNITU2V2uzduxcqlarE3WhKpVK63D1/ICIiInnS62Gs0NBQ9OzZE3Xr1kVmZibWrVuH/fv3Y/fu3VCr1RgzZgymTZsGW1tbqFQqTJ48Gf7+/mjfvj0AoHv37vD29saIESOwaNEiJCcnY/bs2QgJCYFSqdTnphEREZGB0GvYSU1NxciRI5GUlAS1Wg0fHx/s3r0b3bp1AwAsW7YMRkZGGDhwILKzsxEUFIQvv/xSer2xsTG2bduGiRMnwt/fH1ZWVggODsa8efP0tUlERERkYPQadr777rsS55ubmyMiIgIRERHFtnF3d8eOHTsquzQiIiKSCYM7Z4eIiIioMjHsEBERkawx7BAREZGsMewQERGRrDHsEBERkawx7BAREZGsMewQERGRrDHsEBERkawx7BAREZGsMewQERGRrDHsEBERkawx7BAREZGsMewQERGRrDHsEBERkawx7BAREZGsMewQERGRrDHsEBERkayZ6LsAIiIiMmx5ebnQarUAAK1WCyGEnisqH4YdIiIiKtGDu0n4aMtV2LllITU+Bqq6TfVdUrnwMBYRERGVysq+DtQunrC0ddJ3KeXGsENERESyxrBDREREssZzdoiIiF5gOTk5SEhIkMYbNmwIExN5xQN5bQ0RERGVS0JCAt6M2AZrB1dk3b6Br0P6wNvbW99lVSqGHSIiohectYMr1C6e+i6jyvCcHSIiIpI1hh0iIiKSNYYdIiIikjWGHSIiIpI1hh0iIiKSNYYdIiIikjWGHSIiIpI1hh0iIiKSNYYdIiIikjWGHSIiIpI1hh0iIiKSNb2GnYULF6Jt27aoVasWHB0d0b9/f8THx+u06dKlCxQKhc4wYcIEnTaJiYno3bs3LC0t4ejoiBkzZiAnJ6c6N4WIiIgMlF4fBHrgwAGEhISgbdu2yMnJwaxZs9C9e3fExcXByspKajdu3DjMmzdPGre0tJR+zs3NRe/evaHRaHDkyBEkJSVh5MiRMDU1xYIFC6p1e4iIiGqyvLxcaLVaAIBWq4UQQs8VVQ69hp1du3bpjK9evRqOjo6IiYlBp06dpOmWlpbQaDRFLmPPnj2Ii4tDZGQknJyc0LJlS8yfPx8zZ85EWFgYzMzMqnQbiIiI5OLB3SR8tOUq7NyykBofA1XdpvouqVIY1Dk76enpAABbW1ud6T/++CPs7e3RrFkzhIaG4sGDB9K8o0ePonnz5nBycpKmBQUFISMjA+fPny9yPdnZ2cjIyNAZiIiICLCyrwO1iycsbZ1Kb1xD6HXPzrPy8vIwZcoUdOjQAc2aNZOmv/HGG3B3d4eLiwvOnDmDmTNnIj4+Hhs3bgQAJCcn6wQdANJ4cnJyketauHAhwsPDq2hLiIiIyJAYTNgJCQnBuXPncOjQIZ3p48ePl35u3rw5nJ2dERAQgMuXL8PLy6tC6woNDcW0adOk8YyMDLi5uVWscCIiIjJoBnEYa9KkSdi2bRv27dsHV1fXEtv6+fkBgHQClUajQUpKik6b/PHizvNRKpVQqVQ6AxEREcmTXsOOEAKTJk3Cpk2bEB0dDU9Pz1JfExsbCwBwdnYGAPj7++Ps2bNITU2V2uzduxcqlQre3t5VUjcRERHVHHo9jBUSEoJ169Zhy5YtqFWrlnSOjVqthoWFBS5fvox169ahV69esLOzw5kzZzB16lR06tQJPj4+AIDu3bvD29sbI0aMwKJFi5CcnIzZs2cjJCQESqVSn5tHREREBkCve3ZWrFiB9PR0dOnSBc7OztLw888/AwDMzMwQGRmJ7t27o3Hjxpg+fToGDhyIrVu3SsswNjbGtm3bYGxsDH9/f/zrX//CyJEjde7LQ0RERC8uve7ZKe1mRW5ubjhw4ECpy3F3d8eOHTsqqywiIiKSEYM4QZmIiIioqhjMpedERERUcxnyoyYYdoiIiOi5GfKjJngYi4iIiCqFoT5qgmGHiIiIZI1hh4iIiGSNYYeIiIhkjWGHiIiIZI1hh4iIiGSNYYeIiIhkjWGHiIiIZI1hh4iIiGSNYYeIiIhkjWGHiIiIZI1hh4iIiGSNYYeIiIhkjWGHiIiIZI1hh4iIiGSNYYeIiIhkjWGHiIiIZI1hh4iIiGSNYYeIiIhkjWGHiIiIZI1hh4iIiGStQmGnXr16uHv3bqHpaWlpqFev3nMXRURERFRZKhR2rl69itzc3ELTs7OzcfPmzecuioiIiKiymJSn8e+//y79vHv3bqjVamk8NzcXUVFR8PDwqLTiiIiIiJ5XucJO//79AQAKhQLBwcE680xNTeHh4YElS5ZUWnFEREREz6tcYScvLw8A4OnpiRMnTsDe3r5KiiIiIqLnl5OTg4SEBACAVquFEELPFelHucJOvitXrlR2HURERFTJEhIS8GbENlg7uCI1Pgaquk31XZJeVCjsAEBUVBSioqKQmpoq7fHJ9/333z93YURERPT8rB1coXbxRNbtG/ouRW8qFHbCw8Mxb948tGnTBs7OzlAoFJVdFxEREVGlqFDY+eqrr7B69WqMGDGisushIiIiqlQVus/O48eP8dJLL1V2LURERESVrkJhZ+zYsVi3bl1l10JERETVIC8vF1qtFnFxcS/EVVoVOoz16NEjrFy5EpGRkfDx8YGpqanO/KVLl1ZKcURERFT5HtxNwkdbrsLOLeuFuEqrQnt2zpw5g5YtW8LIyAjnzp3DqVOnpCE2NrbMy1m4cCHatm2LWrVqwdHREf3790d8fLxOm0ePHiEkJAR2dnawtrbGwIEDkZKSotMmMTERvXv3hqWlJRwdHTFjxgzk5ORUZNOIiIheCFb2daB28YSlrZO+S6lyFdqzs2/fvkpZ+YEDBxASEoK2bdsiJycHs2bNQvfu3REXFwcrKysAwNSpU7F9+3b8+uuvUKvVmDRpEgYMGIDDhw8DePqYit69e0Oj0eDIkSNISkrCyJEjYWpqigULFlRKnURERFRzVfg+O5Vh165dOuOrV6+Go6MjYmJi0KlTJ6Snp+O7777DunXr0LVrVwDAqlWr0KRJExw7dgzt27fHnj17EBcXh8jISDg5OaFly5aYP38+Zs6cibCwMJiZmelj04iIiMhAVCjsvPLKKyXeWyc6OrpCxaSnpwMAbG1tAQAxMTF48uQJAgMDpTaNGzdG3bp1cfToUbRv3x5Hjx5F8+bN4eT0f7vhgoKCMHHiRJw/fx6tWrUqtJ7s7GxkZ2dL4xkZGRWql4iIiAxfhcJOy5YtdcafPHmC2NhYnDt3rtADQssqLy8PU6ZMQYcOHdCsWTMAQHJyMszMzGBjY6PT1snJCcnJyVKbZ4NO/vz8eUVZuHAhwsPDK1QnERER1SwVCjvLli0rcnpYWBiysrIqVEhISAjOnTuHQ4cOVej15REaGopp06ZJ4xkZGXBzc6vy9RIREVH1q9DVWMX517/+VaHnYk2aNAnbtm3Dvn374OrqKk3XaDR4/Pgx0tLSdNqnpKRAo9FIbQpenZU/nt+mIKVSCZVKpTMQERGRPFVq2Dl69CjMzc3L3F4IgUmTJmHTpk2Ijo6Gp6enznxfX1+YmpoiKipKmhYfH4/ExET4+/sDAPz9/XH27FmkpqZKbfbu3QuVSgVvb+/n3CIiIiKq6Sp0GGvAgAE640IIJCUl4eTJk5gzZ06ZlxMSEoJ169Zhy5YtqFWrlnSOjVqthoWFBdRqNcaMGYNp06bB1tYWKpUKkydPhr+/P9q3bw8A6N69O7y9vTFixAgsWrQIycnJmD17NkJCQqBUKiuyeURERCQjFQo7arVaZ9zIyAiNGjXCvHnz0L179zIvZ8WKFQCALl266ExftWoVRo0aBeDp+UFGRkYYOHAgsrOzERQUhC+//FJqa2xsjG3btmHixInw9/eHlZUVgoODMW/evIpsGhEREclMhcLOqlWrKmXlZXkWh7m5OSIiIhAREVFsG3d3d+zYsaNSaiIiIiJ5ea6bCsbExODChQsAgKZNmxZ5TxsiIiIifapQ2ElNTcXQoUOxf/9+6R44aWlpeOWVV7B+/Xo4ODhUZo1EREREFVahq7EmT56MzMxMnD9/Hvfu3cO9e/dw7tw5ZGRk4O23367sGomIiIgqrEJ7dnbt2oXIyEg0adJEmubt7Y2IiIhynaBMREREVNUqtGcnLy8PpqamhaabmpoiLy/vuYsiIiIiqiwVCjtdu3bFO++8g1u3bknTbt68ialTpyIgIKDSiiMiIiJ6XhUKO//973+RkZEBDw8PeHl5wcvLC56ensjIyMAXX3xR2TUSERERVViFztlxc3PDX3/9hcjISFy8eBEA0KRJEwQGBlZqcURERETPq1x7dqKjo+Ht7Y2MjAwoFAp069YNkydPxuTJk9G2bVs0bdoUf/zxR1XVSkRERFRu5Qo7y5cvx7hx44p8Srharcabb76JpUuXVlpxRERERM+rXGHn9OnT6NGjR7Hzu3fvjpiYmOcuioiIiKiylCvspKSkFHnJeT4TExPcvn37uYsiIiIiqizlCjt16tTBuXPnip1/5swZODs7P3dRRERERJWlXGGnV69emDNnDh49elRo3sOHDzF37lz06dOn0oojIiIiel7luvR89uzZ2LhxIxo2bIhJkyahUaNGAICLFy8iIiICubm5+OCDD6qkUCIiIqKKKFfYcXJywpEjRzBx4kSEhoZCCAEAUCgUCAoKQkREBJycnKqkUCIiIqKKKPdNBd3d3bFjxw78888/0Gq1EEKgQYMGqF27dlXUR0RERPRcKnQHZQCoXbs22rZtW5m1EBEREVW6Cj0bi4iIiKimYNghIiIiWWPYISIiIllj2CEiIiJZY9ghIiIiWWPYISIiIllj2CEiIiJZY9ghIiIiWavwTQWJiIjI8OTk5CAhIQEApCcdvOgYdoiIiGQkISEBb0Zsg7WDK1LjY6Cq21TfJekdD2MRERHJjLWDK9QunrC05cO5AYYdIiIikjmGHSIiIpI1hh0iIiKSNYYdIiIikjWGHSIiIpI1hh0iIiKSNb2GnYMHD6Jv375wcXGBQqHA5s2bdeaPGjUKCoVCZ+jRo4dOm3v37mH48OFQqVSwsbHBmDFjkJWVVY1bQURERIZMr2Hn/v37aNGiBSIiIopt06NHDyQlJUnDTz/9pDN/+PDhOH/+PPbu3Ytt27bh4MGDGD9+fFWXTkRERDWEXu+g3LNnT/Ts2bPENkqlEhqNpsh5Fy5cwK5du3DixAm0adMGAPDFF1+gV69e+PTTT+Hi4lLpNRMREVHNYvDn7Ozfvx+Ojo5o1KgRJk6ciLt370rzjh49ChsbGynoAEBgYCCMjIxw/PhxfZRLRERU7XJychAXF4e4uDg+D6sIBv1srB49emDAgAHw9PTE5cuXMWvWLPTs2RNHjx6FsbExkpOT4ejoqPMaExMT2NraIjk5udjlZmdnIzs7WxrPyMiosm0gIiKqanweVskMOuwMHTpU+rl58+bw8fGBl5cX9u/fj4CAgAovd+HChQgPD6+MEomIiAxC/vOwsm7f0HcpBsfgD2M9q169erC3t4dWqwUAaDQapKam6rTJycnBvXv3ij3PBwBCQ0ORnp4uDdevX6/SuomIiEh/alTYuXHjBu7evQtnZ2cAgL+/P9LS0hATEyO1iY6ORl5eHvz8/IpdjlKphEql0hmIiIhInvR6GCsrK0vaSwMAV65cQWxsLGxtbWFra4vw8HAMHDgQGo0Gly9fxnvvvYf69esjKCgIANCkSRP06NED48aNw1dffYUnT55g0qRJGDp0KK/EIiIiIgB63rNz8uRJtGrVCq1atQIATJs2Da1atcKHH34IY2NjnDlzBq+++ioaNmyIMWPGwNfXF3/88QeUSqW0jB9//BGNGzdGQEAAevXqhY4dO2LlypX62iQiIiIyMHrds9OlS5cSL4/bvXt3qcuwtbXFunXrKrMsIiIikpEadc4OERERUXkx7BAREZGsMewQERGRrDHsEBERkawx7BAREZGsMewQERGRrDHsEBERkawx7BAREZGsMewQERGRrOn1DspERERUMTk5OUhISAAAaLXaEp9I8KJj2CEiIqqBEhIS8GbENlg7uCI1Pgaquk31XZLB4mEsIiKiGsrawRVqF09Y2jrpuxSDxrBDREREssawQ0RERLLGsENERESyxrBDREREssawQ0RERLLGsENERESyxrBDREREssabChIREdUQvGtyxTDsEBER1RC8a3LF8DAWERFRDcK7Jpcfww4RERHJGsMOERERyRrDDhEREckaww4RERHJGsMOERERyRrDDhEREckaww4RERHJGsMOERERyRrDDhEREckaww4RERHJGsMOERERyRrDDhEREckaww4RERHJGsMOERERyZpew87BgwfRt29fuLi4QKFQYPPmzTrzhRD48MMP4ezsDAsLCwQGBuLSpUs6be7du4fhw4dDpVLBxsYGY8aMQVZWVjVuBRERERkyvYad+/fvo0WLFoiIiChy/qJFi/D555/jq6++wvHjx2FlZYWgoCA8evRIajN8+HCcP38ee/fuxbZt23Dw4EGMHz++ujaBiIiIDJyJPlfes2dP9OzZs8h5QggsX74cs2fPRr9+/QAA//vf/+Dk5ITNmzdj6NChuHDhAnbt2oUTJ06gTZs2AIAvvvgCvXr1wqeffgoXF5dq2xYiIiIyTAZ7zs6VK1eQnJyMwMBAaZparYafnx+OHj0KADh69ChsbGykoAMAgYGBMDIywvHjx4tddnZ2NjIyMnQGIiIikieDDTvJyckAACcnJ53pTk5O0rzk5GQ4OjrqzDcxMYGtra3UpigLFy6EWq2WBjc3t0qunoiIiAyFwYadqhQaGor09HRpuH79ur5LIiIiKlJOTg7i4uIQFxcHrVYLIYS+S6px9HrOTkk0Gg0AICUlBc7OztL0lJQUtGzZUmqTmpqq87qcnBzcu3dPen1RlEollEpl5RdNRERUyRISEvBmxDZYO7giNT4GqrpN9V1SjWOwe3Y8PT2h0WgQFRUlTcvIyMDx48fh7+8PAPD390daWhpiYmKkNtHR0cjLy4Ofn1+110xERFQVrB1coXbxhKWtU+mNqRC97tnJysqCVquVxq9cuYLY2FjY2tqibt26mDJlCj766CM0aNAAnp6emDNnDlxcXNC/f38AQJMmTdCjRw+MGzcOX331FZ48eYJJkyZh6NChvBKLiIiIAOg57Jw8eRKvvPKKND5t2jQAQHBwMFavXo333nsP9+/fx/jx45GWloaOHTti165dMDc3l17z448/YtKkSQgICICRkREGDhyIzz//vNq3hYiIiAyTXsNOly5dSjzRSqFQYN68eZg3b16xbWxtbbFu3bqqKI+IiIhkwGDP2SEiIiKqDAw7REREJGsMO0RERCRrDDtEREQkaww7REREJGsMO0RERCRrDDtEREQkaww7REREJGsMO0RERCRrDDtEREQkaww7REREJGsMO0RERCRren0QKBERERWWk5ODhIQEAIBWqy3xodlUOoYdIiIiA5OQkIA3I7bB2sEVqfExUNVtqu+SajQexiIiIjJA1g6uULt4wtLWSd+l1HgMO0RERCRrDDtEREQkaww7REREJGsMO0RERCRrDDtEREQkaww7REREJGsMO0RERCRrDDtEREQkaww7REREJGsMO0RERCRrDDtEREQkaww7REREJGsMO0RERCRrDDtEREQkaww7REREJGsMO0RERCRrDDtEREQkaww7REREJGsMO0RERCRrDDtEREQkaww7REREJGsGHXbCwsKgUCh0hsaNG0vzHz16hJCQENjZ2cHa2hoDBw5ESkqKHismIiIiQ2PQYQcAmjZtiqSkJGk4dOiQNG/q1KnYunUrfv31Vxw4cAC3bt3CgAED9FgtERERGRoTfRdQGhMTE2g0mkLT09PT8d1332HdunXo2rUrAGDVqlVo0qQJjh07hvbt21d3qURERGSADH7PzqVLl+Di4oJ69eph+PDhSExMBADExMTgyZMnCAwMlNo2btwYdevWxdGjR0tcZnZ2NjIyMnQGIiIikieDDjt+fn5YvXo1du3ahRUrVuDKlSt4+eWXkZmZieTkZJiZmcHGxkbnNU5OTkhOTi5xuQsXLoRarZYGNze3KtwKIiIi0ieDPozVs2dP6WcfHx/4+fnB3d0dv/zyCywsLCq83NDQUEybNk0az8jIYOAhIiKSKYPes1OQjY0NGjZsCK1WC41Gg8ePHyMtLU2nTUpKSpHn+DxLqVRCpVLpDERERCRPNSrsZGVl4fLly3B2doavry9MTU0RFRUlzY+Pj0diYiL8/f31WCUREVHZ5OTkIC4uThpycnL0XZIsGfRhrHfffRd9+/aFu7s7bt26hblz58LY2BjDhg2DWq3GmDFjMG3aNNja2kKlUmHy5Mnw9/fnlVhERFQjJCQk4M2IbbB2cEXW7Rv4OqQPvL299V2W7Bh02Llx4waGDRuGu3fvwsHBAR07dsSxY8fg4OAAAFi2bBmMjIwwcOBAZGdnIygoCF9++aWeqyYiIio7awdXqF089V2GrBl02Fm/fn2J883NzREREYGIiIhqqoiIiKhkOTk5SEhIkMYbNmwIExOD/rqVPfY+ERFRJeKhKcPDsENERFTJeGjKsNSoq7GIiIiIyothh4iIiGSNYYeIiIhkjWGHiIiIZI1hh4iIiGSNYYeIiIhkjWGHiIiIZI332SEiIjIAeXm50Gq1AACtVgshhJ4rkg+GHSIioirybIABSn50xIO7Sfhoy1XYuWUhNT4GqrpNq6tM2WPYISIiqiLPBpiyPDrCyr4O1C6eyLp9oxqrlD+GHSIioiqUH2DyPfugUB6uqh4MO0RERNUg/5CWVqvFol0XUMvRjYerqgnDDhERUTXIP6SV+yANqrpNebiqGjHsEBERVRMr+zrIyVLqu4wXDu+zQ0RERLLGsENERESyxrBDREREssawQ0RERLLGsENERESyxrBDREREssawQ0RERLLGsENERESyxrBDREREssY7KBMREZXg2Qd3AkDDhg1hYsKvz5qE7xYREVEJEhIS8GbENlg7uCLr9g18HdIH3t7eOm34JHPDxrBDRERUCmsHV6hdPIud/2wg4pPMDQ/P2SEiIqoE+YHI0tZJ36VQAQw7REREJGs8jEVERHrHk4CpKvGTREREeleWk4CJKophh4iIDEJpJwETVRTDDhERSXg4ieSIn2AiIgOi77BhaIeTnqc/9N2XZDhk865HRERg8eLFSE5ORosWLfDFF1+gXbt2+i6LiKhcDCFsGNLhpOfpj+JeW5YQxJsEyossws7PP/+MadOm4auvvoKfnx+WL1+OoKAgxMfHw9HRUd/lEVENYSh7AgwpbJSmvMGhuDYleZ7+KOq1z4agzJRreK9nU9SvXx85OTkAABMTE2i1WizadQG1HN10bhKYl5cLrVYrbdez7RmIDJcsws7SpUsxbtw4jB49GgDw1VdfYfv27fj+++/x/vvv67k6+SruD5ihfGFURHXWXtX9V5PfB30p72MBgKr5cq9JytJnVbG3qrx9/GxI0Wq1sLKvA7WLJ7Ju38BHW07Dzi0LqfExMLa0gZ2blxRw8tvke3A3CR9tuVpsezJMNf637/Hjx4iJiUFoaKg0zcjICIGBgTh69KgeK6t5yvvlW9wfMEPYDf+s8vxRrM7ay9J/z/7X+WztZdmmyvrilqOStrs8jwV4ni93OfV9Wfa8lGfvTMFgkr/HpOD0/D0vZfldLRhSng0mzwYfE2v7QgGnoPK2J/2rmb9Zz7hz5w5yc3Ph5KR7e24nJydcvHixyNdkZ2cjOztbGk9PTwcAZGRkVF2hNcDFixcxduH3sLBxwMO025g1pAvq1auHv//+Gwt+3l/k9JzHj5CT/QA5jx/hzJkzyMrKKna6vhRXf3Ftq6v2svRf1u2beO9rLdSOLmV6T8q7LeXpGzkp6TOddlP7tO/v3MKZM0ZF9llZ+rWifV+WGqpSeddf1j4rT5vbl2LxXsxDqB1d8M/1BNRyro/cxw+LnG6hLrmP85eZmZIIYws1crIfIPdJNjJuXYaJUd7T6Rnp1fpz7sP0al+nIf6cdecWsrLqP9d3b/5rSz2EKGq4mzdvCgDiyJEjOtNnzJgh2rVrV+Rr5s6dKwBw4MCBAwcOHGQwXL9+vcSsUOP37Njb28PY2BgpKSk601NSUqDRaIp8TWhoKKZNmyaNp6Wlwd3dHYmJiVCr1VVaLz2VkZEBNzc3XL9+HSqVSt/lvDDY79WPfa4f7Hf9qO5+F0IgMzMTLi4uJbar8WHHzMwMvr6+iIqKQv/+/QEAeXl5iIqKwqRJk4p8jVKphFKpLDRdrVbzl6KaqVQq9rkesN+rH/tcP9jv+lGd/V6WnRQ1PuwAwLRp0xAcHIw2bdqgXbt2WL58Oe7fvy9dnUVEREQvLlmEnSFDhuD27dv48MMPkZycjJYtW2LXrl2FTlomIiKiF48swg4ATJo0qdjDVqVRKpWYO3dukYe2qGqwz/WD/V792Of6wX7XD0Ptd4UQvOUjERERyZeRvgsgIiIiqkoMO0RERCRrDDtEREQkaww7REREJGsvfNiJiIiAh4cHzM3N4efnhz///FPfJdVoBw8eRN++feHi4gKFQoHNmzfrzBdC4MMPP4SzszMsLCwQGBiIS5cu6bS5d+8ehg8fDpVKBRsbG4wZM0avz9YydAsXLkTbtm1Rq1YtODo6on///oiPj9dp8+jRI4SEhMDOzg7W1tYYOHBgobuOJyYmonfv3rC0tISjoyNmzJiBnJyc6tyUGmPFihXw8fGRbpzm7++PnTt3SvPZ39XjP//5DxQKBaZMmSJNY99XvrCwMCgUCp2hcePG0vwa0eeV8oCqGmr9+vXCzMxMfP/99+L8+fNi3LhxwsbGRqSkpOi7tBprx44d4oMPPhAbN24UAMSmTZt05v/nP/8RarVabN68WZw+fVq8+uqrwtPTUzx8+FBq06NHD9GiRQtx7Ngx8ccff4j69euLYcOGVfOW1BxBQUFi1apV4ty5cyI2Nlb06tVL1K1bV2RlZUltJkyYINzc3ERUVJQ4efKkaN++vXjppZek+Tk5OaJZs2YiMDBQnDp1SuzYsUPY29uL0NBQfWySwfv999/F9u3bRUJCgoiPjxezZs0Spqam4ty5c0II9nd1+PPPP4WHh4fw8fER77zzjjSdfV/55s6dK5o2bSqSkpKk4fbt29L8mtDnL3TYadeunQgJCZHGc3NzhYuLi1i4cKEeq5KPgmEnLy9PaDQasXjxYmlaWlqaUCqV4qeffhJCCBEXFycAiBMnTkhtdu7cKRQKhbh582a11V6TpaamCgDiwIEDQoinfWxqaip+/fVXqc2FCxcEAHH06FEhxNOQamRkJJKTk6U2K1asECqVSmRnZ1fvBtRQtWvXFt9++y37uxpkZmaKBg0aiL1794rOnTtLYYd9XzXmzp0rWrRoUeS8mtLnL+xhrMePHyMmJgaBgYHSNCMjIwQGBuLo0aN6rEy+rly5guTkZJ0+V6vV8PPzk/r86NGjsLGxQZs2baQ2gYGBMDIywvHjx6u95pooPT0dAGBrawsAiImJwZMnT3T6vXHjxqhbt65Ovzdv3lznruNBQUHIyMjA+fPnq7H6mic3Nxfr16/H/fv34e/vz/6uBiEhIejdu7dOHwP8rFelS5cuwcXFBfXq1cPw4cORmJgIoOb0uWzuoFxed+7cQW5ubqFHSjg5OeHixYt6qkrekpOTAaDIPs+fl5ycDEdHR535JiYmsLW1ldpQ8fLy8jBlyhR06NABzZo1A/C0T83MzGBjY6PTtmC/F/W+5M+jws6ePQt/f388evQI1tbW2LRpE7y9vREbG8v+rkLr16/HX3/9hRMnThSax8961fDz88Pq1avRqFEjJCUlITw8HC+//DLOnTtXY/r8hQ07RHIUEhKCc+fO4dChQ/ouRfYaNWqE2NhYpKenY8OGDQgODsaBAwf0XZasXb9+He+88w727t0Lc3NzfZfzwujZs6f0s4+PD/z8/ODu7o5ffvkFFhYWeqys7F7Yw1j29vYwNjYudMZ4SkoKNBqNnqqSt/x+LanPNRoNUlNTdebn5OTg3r17fF9KMWnSJGzbtg379u2Dq6urNF2j0eDx48dIS0vTaV+w34t6X/LnUWFmZmaoX78+fH19sXDhQrRo0QKfffYZ+7sKxcTEIDU1Fa1bt4aJiQlMTExw4MABfP755zAxMYGTkxP7vhrY2NigYcOG0Gq1Nebz/sKGHTMzM/j6+iIqKkqalpeXh6ioKPj7++uxMvny9PSERqPR6fOMjAwcP35c6nN/f3+kpaUhJiZGahMdHY28vDz4+flVe801gRACkyZNwqZNmxAdHQ1PT0+d+b6+vjA1NdXp9/j4eCQmJur0+9mzZ3WC5t69e6FSqeDt7V09G1LD5eXlITs7m/1dhQICAnD27FnExsZKQ5s2bTB8+HDpZ/Z91cvKysLly5fh7Oxccz7v1XIatIFav369UCqVYvXq1SIuLk6MHz9e2NjY6JwxTuWTmZkpTp06JU6dOiUAiKVLl4pTp06Ja9euCSGeXnpuY2MjtmzZIs6cOSP69etX5KXnrVq1EsePHxeHDh0SDRo04KXnJZg4caJQq9Vi//79OpeGPnjwQGozYcIEUbduXREdHS1Onjwp/P39hb+/vzQ//9LQ7t27i9jYWLFr1y7h4ODAy3GL8f7774sDBw6IK1euiDNnzoj3339fKBQKsWfPHiEE+7s6PXs1lhDs+6owffp0sX//fnHlyhVx+PBhERgYKOzt7UVqaqoQomb0+QsddoQQ4osvvhB169YVZmZmol27duLYsWP6LqlG27dvnwBQaAgODhZCPL38fM6cOcLJyUkolUoREBAg4uPjdZZx9+5dMWzYMGFtbS1UKpUYPXq0yMzM1MPW1AxF9TcAsWrVKqnNw4cPxVtvvSVq164tLC0txWuvvSaSkpJ0lnP16lXRs2dPYWFhIezt7cX06dPFkydPqnlraoZ///vfwt3dXZiZmQkHBwcREBAgBR0h2N/VqWDYYd9XviFDhghnZ2dhZmYm6tSpI4YMGSK0Wq00vyb0uUIIIapnHxIRERFR9Xthz9khIiKiFwPDDhEREckaww4RERHJGsMOERERyRrDDhEREckaww4RERHJGsMOERERyRrDDtELbtSoUejfv3+lLzc5ORndunWDlZVVoSciP6+qqvlZXbp0wZQpU6p0HQqFAps3b67SdTzLw8MDy5cvL1Pb1atXV/r7RqQvfOo5UTUYNWoU0tLSqvWLraCrV6/C09MTp06dQsuWLat8fcuWLUNSUhJiY2OhVquLbGMI/VKcjRs3wtTUVN9lVMjq1asxZcqUQg9nPHHiBKysrPRTFJEeMewQUZW4fPkyfH190aBBA32XUiG2trb6LqFCnjx5Uuw8BweHaqyEyHDwMBaRATh37hx69uwJa2trODk5YcSIEbhz5440v0uXLnj77bfx3nvvwdbWFhqNBmFhYTrLuHjxIjp27Ahzc3N4e3sjMjJS5zBJ/tPQW7VqBYVCgS5duui8/tNPP4WzszPs7OwQEhJS4pcmAKxYsQJeXl4wMzNDo0aNsHbtWmmeh4cHfvvtN/zvf/+DQqHAqFGjCr0+LCwMa9aswZYtW6BQKKBQKLB//34AwNmzZ9G1a1dYWFjAzs4O48ePR1ZWVrG1nDhxAg4ODvjkk08AAGlpaRg7diwcHBygUqnQtWtXnD59WmfdLVu2xNq1a+Hh4QG1Wo2hQ4ciMzNTp8/zD2Pt379fqvHZ4dnt2rJlC1q3bg1zc3PUq1cP4eHhyMnJkeZfunQJnTp1kt6fvXv3lti/ALBr1y507NgRNjY2sLOzQ58+fXD58mVp/tWrV6FQKPDzzz+jc+fOMDc3x48//ojRo0cjPT1dqjP/s1LwMFZaWhrefPNNODk5wdzcHM2aNcO2bduKraekbRRCICwsDHXr1oVSqYSLiwvefvvtUreRqFpU21O4iF5gwcHBol+/fkXO++eff6QnAF+4cEH89ddfolu3buKVV16R2nTu3FmoVCoRFhYmEhISxJo1a3Sesp2TkyMaNWokunXrJmJjY8Uff/wh2rVrJwCITZs2CSGE+PPPPwUAERkZKZKSksTdu3el2lQqlZgwYYK4cOGC2Lp1q7C0tBQrV64sdns2btwoTE1NRUREhIiPjxdLliwRxsbGIjo6WgghRGpqqujRo4cYPHiwSEpKEmlpaYWWkZmZKQYPHix69OghPak9OztbZGVlCWdnZzFgwABx9uxZERUVJTw9PaWHyRbsz6ioKKFWq8XXX38tzQ8MDBR9+/YVJ06cEAkJCWL69OnCzs5O2ua5c+cKa2traR0HDx4UGo1GzJo1S6fP8x8wmZ2drfNE+ejoaGFubi6+++47IYQQBw8eFCqVSqxevVpcvnxZ7NmzR3h4eIiwsDAhhBC5ubmiWbNmIiAgQMTGxooDBw6IVq1a6bw/RdmwYYP47bffxKVLl8SpU6dE3759RfPmzUVubq4QQogrV64IAMLDw0P89ttv4u+//xZXr14Vy5cvFyqVSqo3/0G67u7uYtmyZVJN7du3F02bNhV79uwRly9fFlu3bhU7duwQQgixatUqoVarpVpK28Zff/1VqFQqsWPHDnHt2jVx/PjxEj9DRNWJYYeoGpQUdubPny+6d++uM+369esCgPRE+M6dO4uOHTvqtGnbtq2YOXOmEEKInTt3ChMTE50nDe/du1fnyzT/i/HUqVOFanN3dxc5OTnStNdff10MGTKk2O156aWXxLhx43Smvf7666JXr17SeL9+/XQCSlGK6peVK1eK2rVri6ysLGna9u3bhZGRkUhOTtZ53caNG4W1tbVYv3691PaPP/4QKpVKPHr0SGe5Xl5eUiCaO3eusLS0FBkZGdL8GTNmCD8/P2m84NO08925c0fUq1dPvPXWW9K0gIAAsWDBAp12a9euFc7OzkIIIXbv3i1MTEzEzZs3pfk7d+4sNewUdPv2bQFAnD17Vgjxf+/p8uXLddoVDCr5ng07u3fvFkZGRtJnrKCCyyhtG5csWSIaNmwoHj9+XObtIaouPIxFpGenT5/Gvn37YG1tLQ2NGzcGAJ1DFj4+Pjqvc3Z2RmpqKgAgPj4ebm5u0Gg00vx27dqVuYamTZvC2Ni4yGUX5cKFC+jQoYPOtA4dOuDChQtlXmdJy27RooXOibQdOnRAXl4e4uPjpWnHjx/H66+/jrVr12LIkCHS9NOnTyMrKwt2dnY6fXrlyhWd/vTw8ECtWrWk8dK2GXh6PszAgQPh7u6Ozz77TGed8+bN01nfuHHjkJSUhAcPHuDChQtwc3ODi4uL9Bp/f/9S++LSpUsYNmwY6tWrB5VKBQ8PDwBAYmKiTrs2bdqUuqyCYmNj4erqioYNG5apfWnb+Prrr+Phw4eoV68exo0bh02bNukcxiPSJ56gTKRnWVlZ6Nu3r3S+ybOcnZ2lnwteGaRQKJCXl1cpNVTlsquKl5cX7Ozs8P3336N3797SNmRlZcHZ2Vk6/+dZz15KXZFtnjhxIq5fv44///wTJib/9+czKysL4eHhGDBgQKHXmJubl2OrdPXt2xfu7u745ptv4OLigry8PDRr1gyPHz/WaVeRK6wsLCzK1b60bXRzc0N8fDwiIyOxd+9evPXWW1i8eDEOHDhQY69qI/lg2CHSs9atW+O3336Dh4eHzhdoeTRq1AjXr19HSkoKnJycADw9afdZZmZmAIDc3NznKxhAkyZNcPjwYQQHB0vTDh8+DG9v73Itx8zMrFA9TZo0werVq3H//n3pS/zw4cMwMjJCo0aNpHb29vbYuHEjunTpgsGDB+OXX36BqakpWrdujeTkZJiYmEh7QirD0qVL8csvv+DIkSOws7PTmde6dWvEx8ejfv36Rb62SZMmuH79OpKSkqQAe+zYsRLXd/fuXcTHx+Obb77Byy+/DAA4dOhQmWotql8L8vHxwY0bN5CQkFCmvTulbSPwNED17dsXffv2RUhICBo3boyzZ8+idevWZaqbqKow7BBVk/T0dMTGxupMy7/y6ZtvvsGwYcOkq620Wi3Wr1+Pb7/9VufwUnG6desGLy8vBAcHY9GiRcjMzMTs2bMBPN1jAQCOjo6wsLDArl274OrqCnNz82Lvf1OaGTNmYPDgwWjVqhUCAwOxdetWbNy4EZGRkeVajoeHB3bv3o34+HjY2dlBrVZj+PDhmDt3LoKDgxEWFobbt29j8uTJGDFihBTk8jk6OiI6OhqvvPIKhg0bhvXr1yMwMBD+/v7o378/Fi1ahIYNG+LWrVvYvn07XnvttQod8omMjMR7772HiIgI2NvbIzk5GcDTL3e1Wo0PP/wQffr0Qd26dTFo0CAYGRnh9OnTOHfuHD766CMEBgaiYcOGCA4OxuLFi5GRkYEPPvigxHXWrl0bdnZ2WLlyJZydnZGYmIj333+/zP2alZWFqKgotGjRApaWlrC0tNRp07lzZ3Tq1AkDBw7E0qVLUb9+fVy8eBEKhQI9evQotMzStnH16tXIzc2Fn58fLC0t8cMPP8DCwgLu7u5l7GWiqsNzdoiqyf79+9GqVSudITw8HC4uLjh8+DByc3PRvXt3NG/eHFOmTIGNjQ2MjMr2K2psbIzNmzcjKysLbdu2xdixY6Uv0/zDKCYmJvj888/x9ddfw8XFBf369avwtvTv3x+fffYZPv30UzRt2hRff/01Vq1aVehy9tKMGzcOjRo1Qps2beDg4IDDhw/D0tISu3fvxr1799C2bVsMGjQIAQEB+O9//1vkMjQaDaKjo3H27FkMHz4ceXl52LFjBzp16oTRo0ejYcOGGDp0KK5du1YoLJXVoUOHkJubiwkTJsDZ2Vka3nnnHQBAUFAQtm3bhj179qBt27Zo3749li1bJn3RGxkZYdOmTXj48CHatWuHsWPH4uOPPy5xnUZGRli/fj1iYmLQrFkzTJ06FYsXLy5TvS+99BImTJiAIUOGwMHBAYsWLSqy3W+//Ya2bdti2LBh8Pb2xnvvvVfsHqHSttHGxgbffPMNOnToAB8fH0RGRmLr1q2F9oIR6YNCCCH0XQQRVb7Dhw+jY8eO0Gq18PLy0nc5RER6w7BDJBObNm2CtbU1GjRoAK1Wi3feeQe1a9cu83keRERyxXN2iGQiMzMTM2fORGJiIuzt7REYGIglS5bouywiIr3jnh0iIiKSNZ6gTERERLLGsENERESyxrBDREREssawQ0RERLLGsENERESyxrBDREREssawQ0RERLLGsENERESyxrBDREREsvb/ANd+HfWqo9RIAAAAAElFTkSuQmCC\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from scipy.stats import percentileofscore\n",
        "print(f'Percentile of length=512: {int(percentileofscore(tokenized_articles_lengths,513))}th')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "aK8yXzjMGkr6",
        "outputId": "aca3e531-bc1e-4a87-b435-c6ac2ebf6a6e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Percentile of length=512: 100th\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_p"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "uOt4phDHGnWj",
        "outputId": "cbff992c-5273-4185-df8b-5793d44e2739"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                                 url  \\\n",
              "0     https://www.bbc.com/urdu/articles/cv20nxzl544o   \n",
              "1     https://www.bbc.com/urdu/articles/c109pqg9v1vo   \n",
              "2     https://www.bbc.com/urdu/articles/cj78ev79mdmo   \n",
              "3     https://www.bbc.com/urdu/articles/c3gl4pp0gzgo   \n",
              "4     https://www.bbc.com/urdu/articles/c2q3k4nq39no   \n",
              "...                                              ...   \n",
              "4911  https://www.bbc.com/urdu/articles/cz4dp89r8p8o   \n",
              "4912  https://www.bbc.com/urdu/articles/cn0995kvnzgo   \n",
              "4913  https://www.bbc.com/urdu/articles/cy0ddzg77zko   \n",
              "4914  https://www.bbc.com/urdu/articles/czd8jkzn0nno   \n",
              "4915  https://www.bbc.com/urdu/articles/crgye1440r0o   \n",
              "\n",
              "                                                summary  \\\n",
              "0     پاکستان کے زیرانتظام کشمیر میں بجلی کی قیمتوں ...   \n",
              "1     پاکستان میں معیشت اور ٹیکس کے ماہرین کے مطابق ...   \n",
              "2     تحقیقات سے پتا چلا ہے کہ ماسکو کا ساتھ نہ دینے...   \n",
              "3     رقبے کے لحاظ سے دنیا کے دوسرے سب سے بڑے ملک کے...   \n",
              "4     انڈیا کے وزیر اعظم نریندر مودی کا کہنا ہے کہ د...   \n",
              "...                                                 ...   \n",
              "4911  انڈیا کی شمالی ریاست اتراکھنڈ کے شہر ہلدوانی م...   \n",
              "4912  کانگریس پارٹی نے گزشتہ سال اپنی حکومت بناتے ہو...   \n",
              "4913  انتہا پسند ہندو تنظیموں کے ارکان نے اس فلم کے ...   \n",
              "4914  نوکری ٹھکرا کر یا نوکری چھوڑ کر اپنا کاروبار ش...   \n",
              "4915  یو پی بورڈ میں ٹاپ کرنے والی طالبہ پراچی کہتی ...   \n",
              "\n",
              "                                                  title  \\\n",
              "0     پاکستان کے زیرانتظام کشمیر میں احتجاج کیوں ہو ...   \n",
              "1     پاکستان میں متوسط طبقے اور غریبوں پر ٹیکسوں کا...   \n",
              "2     معاشی پابندیوں پر روس کا جواب: ’دشمن‘ مغربی مم...   \n",
              "3     کینیڈا کے تین شہر رہائش کے لیے دنیا کے 10 بہتر...   \n",
              "4     کیا انڈیا، مشرق وسطیٰ اور یورپ کا راہداری منصو...   \n",
              "...                                                 ...   \n",
              "4911  انڈیا: ریاست اتراکھنڈ میں مدرسے کی عمارت کو گر...   \n",
              "4912  ہندو لڑکے سے ملنے جانے والی مسلمان لڑکی پر ’تش...   \n",
              "4913  ’برہمن عورت کی بریانی پکانے سے قبل نماز‘ نیٹ ف...   \n",
              "4914  ’اپنا باس خود بننے کی خواہش یا آمدن کے محدود م...   \n",
              "4915  ’اگر میں ٹاپ نہ کرتی تو لوگ میری شکل پر توجہ ن...   \n",
              "\n",
              "                firstPublished            id  \\\n",
              "0     2023-10-06T06:51:11.061Z  cv20nxzl544o   \n",
              "1     2023-10-05T03:03:41.630Z  c109pqg9v1vo   \n",
              "2     2023-10-04T02:20:54.824Z  cj78ev79mdmo   \n",
              "3     2023-10-03T04:25:50.938Z  c3gl4pp0gzgo   \n",
              "4     2023-10-03T03:20:38.534Z  c2q3k4nq39no   \n",
              "...                        ...           ...   \n",
              "4911  2024-02-10T09:31:10.954Z  cz4dp89r8p8o   \n",
              "4912  2024-01-13T03:45:15.429Z  cn0995kvnzgo   \n",
              "4913  2024-01-12T15:13:09.862Z  cy0ddzg77zko   \n",
              "4914  2024-04-27T06:02:58.918Z  czd8jkzn0nno   \n",
              "4915  2024-04-27T10:33:29.384Z  crgye1440r0o   \n",
              "\n",
              "                                                article  \n",
              "0     [پاکستان کے زیر انتظام کشمیر میں احتجاج تو کئی...  \n",
              "1     [اس شرط کے تحت زیادہ ٹیکس وصولی کے مختلف شعبوں...  \n",
              "2     [تاہم، تحقیقات میں یہ بھی پتا چلا ہے کہ کریملن...  \n",
              "3     [سمانتھا فالک، جو مونٹریال، کیلگری اور ٹورنٹو ...  \n",
              "4     [انڈیا کے وزیر اعظم نریندر مودی نے ایک حالیہ ر...  \n",
              "...                                                 ...  \n",
              "4911  [انڈیا کی شمالی ریاست اتراکھنڈ کے شہر ہلدوانی ...  \n",
              "4912  [خاتون نے بتایا کہ اس کے بعد انھیں ہوٹل سے سات...  \n",
              "4913  [ایک انڈین فلم، جسے ’ہندوؤں کے مذہبی جذبات مجر...  \n",
              "4914  [نوکری کو ٹھکرا کر یا نوکری کو چھوڑ کر اپنا کا...  \n",
              "4915  [پراچی کہتی ہیں کہ ’اس ٹرولنگ اور ہجوم کو دیکھ...  \n",
              "\n",
              "[4916 rows x 6 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-ee226292-1800-45e6-a254-52827845170a\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
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              "        vertical-align: middle;\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>url</th>\n",
              "      <th>summary</th>\n",
              "      <th>title</th>\n",
              "      <th>firstPublished</th>\n",
              "      <th>id</th>\n",
              "      <th>article</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>https://www.bbc.com/urdu/articles/cv20nxzl544o</td>\n",
              "      <td>پاکستان کے زیرانتظام کشمیر میں بجلی کی قیمتوں ...</td>\n",
              "      <td>پاکستان کے زیرانتظام کشمیر میں احتجاج کیوں ہو ...</td>\n",
              "      <td>2023-10-06T06:51:11.061Z</td>\n",
              "      <td>cv20nxzl544o</td>\n",
              "      <td>[پاکستان کے زیر انتظام کشمیر میں احتجاج تو کئی...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>https://www.bbc.com/urdu/articles/c109pqg9v1vo</td>\n",
              "      <td>پاکستان میں معیشت اور ٹیکس کے ماہرین کے مطابق ...</td>\n",
              "      <td>پاکستان میں متوسط طبقے اور غریبوں پر ٹیکسوں کا...</td>\n",
              "      <td>2023-10-05T03:03:41.630Z</td>\n",
              "      <td>c109pqg9v1vo</td>\n",
              "      <td>[اس شرط کے تحت زیادہ ٹیکس وصولی کے مختلف شعبوں...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>https://www.bbc.com/urdu/articles/cj78ev79mdmo</td>\n",
              "      <td>تحقیقات سے پتا چلا ہے کہ ماسکو کا ساتھ نہ دینے...</td>\n",
              "      <td>معاشی پابندیوں پر روس کا جواب: ’دشمن‘ مغربی مم...</td>\n",
              "      <td>2023-10-04T02:20:54.824Z</td>\n",
              "      <td>cj78ev79mdmo</td>\n",
              "      <td>[تاہم، تحقیقات میں یہ بھی پتا چلا ہے کہ کریملن...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>https://www.bbc.com/urdu/articles/c3gl4pp0gzgo</td>\n",
              "      <td>رقبے کے لحاظ سے دنیا کے دوسرے سب سے بڑے ملک کے...</td>\n",
              "      <td>کینیڈا کے تین شہر رہائش کے لیے دنیا کے 10 بہتر...</td>\n",
              "      <td>2023-10-03T04:25:50.938Z</td>\n",
              "      <td>c3gl4pp0gzgo</td>\n",
              "      <td>[سمانتھا فالک، جو مونٹریال، کیلگری اور ٹورنٹو ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>https://www.bbc.com/urdu/articles/c2q3k4nq39no</td>\n",
              "      <td>انڈیا کے وزیر اعظم نریندر مودی کا کہنا ہے کہ د...</td>\n",
              "      <td>کیا انڈیا، مشرق وسطیٰ اور یورپ کا راہداری منصو...</td>\n",
              "      <td>2023-10-03T03:20:38.534Z</td>\n",
              "      <td>c2q3k4nq39no</td>\n",
              "      <td>[انڈیا کے وزیر اعظم نریندر مودی نے ایک حالیہ ر...</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",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4911</th>\n",
              "      <td>https://www.bbc.com/urdu/articles/cz4dp89r8p8o</td>\n",
              "      <td>انڈیا کی شمالی ریاست اتراکھنڈ کے شہر ہلدوانی م...</td>\n",
              "      <td>انڈیا: ریاست اتراکھنڈ میں مدرسے کی عمارت کو گر...</td>\n",
              "      <td>2024-02-10T09:31:10.954Z</td>\n",
              "      <td>cz4dp89r8p8o</td>\n",
              "      <td>[انڈیا کی شمالی ریاست اتراکھنڈ کے شہر ہلدوانی ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4912</th>\n",
              "      <td>https://www.bbc.com/urdu/articles/cn0995kvnzgo</td>\n",
              "      <td>کانگریس پارٹی نے گزشتہ سال اپنی حکومت بناتے ہو...</td>\n",
              "      <td>ہندو لڑکے سے ملنے جانے والی مسلمان لڑکی پر ’تش...</td>\n",
              "      <td>2024-01-13T03:45:15.429Z</td>\n",
              "      <td>cn0995kvnzgo</td>\n",
              "      <td>[خاتون نے بتایا کہ اس کے بعد انھیں ہوٹل سے سات...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4913</th>\n",
              "      <td>https://www.bbc.com/urdu/articles/cy0ddzg77zko</td>\n",
              "      <td>انتہا پسند ہندو تنظیموں کے ارکان نے اس فلم کے ...</td>\n",
              "      <td>’برہمن عورت کی بریانی پکانے سے قبل نماز‘ نیٹ ف...</td>\n",
              "      <td>2024-01-12T15:13:09.862Z</td>\n",
              "      <td>cy0ddzg77zko</td>\n",
              "      <td>[ایک انڈین فلم، جسے ’ہندوؤں کے مذہبی جذبات مجر...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4914</th>\n",
              "      <td>https://www.bbc.com/urdu/articles/czd8jkzn0nno</td>\n",
              "      <td>نوکری ٹھکرا کر یا نوکری چھوڑ کر اپنا کاروبار ش...</td>\n",
              "      <td>’اپنا باس خود بننے کی خواہش یا آمدن کے محدود م...</td>\n",
              "      <td>2024-04-27T06:02:58.918Z</td>\n",
              "      <td>czd8jkzn0nno</td>\n",
              "      <td>[نوکری کو ٹھکرا کر یا نوکری کو چھوڑ کر اپنا کا...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4915</th>\n",
              "      <td>https://www.bbc.com/urdu/articles/crgye1440r0o</td>\n",
              "      <td>یو پی بورڈ میں ٹاپ کرنے والی طالبہ پراچی کہتی ...</td>\n",
              "      <td>’اگر میں ٹاپ نہ کرتی تو لوگ میری شکل پر توجہ ن...</td>\n",
              "      <td>2024-04-27T10:33:29.384Z</td>\n",
              "      <td>crgye1440r0o</td>\n",
              "      <td>[پراچی کہتی ہیں کہ ’اس ٹرولنگ اور ہجوم کو دیکھ...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>4916 rows × 6 columns</p>\n",
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              "\n",
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              "        document.querySelector('#' + key + ' button');\n",
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              "\n",
              "  <div id=\"id_c0b2e7f4-64c9-4871-b23f-40a52d9f68a8\">\n",
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              "      .colab-df-generate:hover {\n",
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              "\n",
              "      [theme=dark] .colab-df-generate {\n",
              "        background-color: #3B4455;\n",
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              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate:hover {\n",
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              "type": "dataframe",
              "variable_name": "df_p",
              "summary": "{\n  \"name\": \"df_p\",\n  \"rows\": 4916,\n  \"fields\": [\n    {\n      \"column\": \"url\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1842,\n        \"samples\": [\n          \"https://www.bbc.com/urdu/articles/c729ye0vvd9o\",\n          \"https://www.bbc.com/urdu/pakistan-60992404\",\n          \"https://www.bbc.com/urdu/regional-61514819\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"summary\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1837,\n        \"samples\": [\n          \"\\u062f\\u0641\\u0627\\u0639\\u06cc \\u0686\\u06cc\\u0645\\u067e\\u06cc\\u0646 \\u0627\\u0646\\u06af\\u0644\\u06cc\\u0646\\u0688 \\u06a9\\u06cc \\u0686\\u0627\\u0631 \\u0645\\u06cc\\u0686\\u0648\\u06ba \\u0645\\u06cc\\u06ba \\u062a\\u06cc\\u0633\\u0631\\u06cc \\u0634\\u06a9\\u0633\\u062a \\u0646\\u06d2 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\\u067e\\u06cc\\u063a\\u0627\\u0645 \\u0648\\u0627\\u0644\\u06d2 \\u062c\\u0648\\u062a\\u06d2 \\u067e\\u06c1\\u0646\\u0646\\u06d2 \\u06a9\\u06cc \\u0627\\u062c\\u0627\\u0632\\u062a \\u0646\\u06c1 \\u062f\\u06cc\\u06d2 \\u062c\\u0627\\u0646\\u06d2 \\u06a9\\u06d2 \\u0641\\u06cc\\u0635\\u0644\\u06d2 \\u06a9\\u0627 \\u0627\\u062d\\u062a\\u0631\\u0627\\u0645 \\u06a9\\u0631\\u062a\\u06d2 \\u06c1\\u06cc\\u06ba \\u0644\\u06cc\\u06a9\\u0646 \\u0648\\u06c1 \\u0627\\u0633 \\u0639\\u0645\\u0644 \\u06a9\\u06cc \\u0627\\u062c\\u0627\\u0632\\u062a \\u0644\\u06cc\\u0646\\u06d2 \\u06a9\\u06d2 \\u0644\\u06cc\\u06d2 \\u06a9\\u0648\\u0634\\u0634 \\u06a9\\u0631\\u06cc\\u06ba \\u06af\\u06d2\\u06d4\",\n          \"\\u0627\\u0646\\u0688\\u06cc\\u0646 \\u0641\\u0627\\u0633\\u0679 \\u0628\\u0648\\u0644\\u0631 \\u0645\\u062d\\u0645\\u062f \\u0634\\u0627\\u0645\\u06cc \\u0646\\u06d2 \\u0631\\u0648\\u0627\\u06ba \\u0648\\u0631\\u0644\\u0688 \\u06a9\\u067e \\u0645\\u06cc\\u06ba \\u062f\\u0648 \\u0628\\u0627\\u0631 \\u067e\\u0627\\u0646\\u0686 \\u0648\\u06a9\\u0679\\u06cc\\u06ba \\u0644\\u06d2 \\u06a9\\u0631 \\u062c\\u06c1\\u0627\\u06ba \\u0627\\u067e\\u0646\\u06cc \\u0627\\u06c1\\u0645\\u06cc\\u062a \\u0648\\u0627\\u0636\\u062d \\u06a9\\u06cc \\u06c1\\u06d2 \\u0648\\u06c1\\u06cc\\u06ba \\u0648\\u06c1 \\u0627\\u0646\\u0688\\u06cc\\u0627 \\u06a9\\u06cc \\u062c\\u0627\\u0646\\u0628 \\u0633\\u06d2 \\u0648\\u0631\\u0644\\u0688 \\u06a9\\u067e \\u0645\\u06cc\\u06ba \\u0633\\u0628 \\u0633\\u06d2 \\u0632\\u06cc\\u0627\\u062f\\u06c1 45 \\u0648\\u06a9\\u0679 \\u0644\\u06cc\\u0646\\u06d2 \\u0648\\u0627\\u0644\\u06d2 \\u0628\\u0648\\u0644\\u0631 \\u0628\\u06be\\u06cc \\u0628\\u0646 \\u06af\\u0626\\u06d2 \\u06c1\\u06cc\\u06ba\\u06d4\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"title\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1840,\n        \"samples\": [\n          \"\\u0645\\u0648\\u0646\\u0627 \\u0644\\u06cc\\u0632\\u0627 \\u06a9\\u06cc \\u0645\\u0633\\u06a9\\u0631\\u0627\\u06c1\\u0679 \\u06a9\\u06d2 \\u067e\\u06cc\\u0686\\u06be\\u06d2 \\u0633\\u0627\\u0626\\u0646\\u0633 \\u06cc\\u0627 \\u0631\\u0627\\u0632 \\u06a9\\u06cc\\u0627 \\u06c1\\u06d2\\u061f\",\n          \"\\u0627\\u06cc\\u0645 \\u06a9\\u06cc\\u0648 \\u0627\\u06cc\\u0645 \\u0646\\u06d2 \\u06a9\\u0628 \\u06a9\\u0628 \\u0627\\u0648\\u0631 \\u06a9\\u0633 \\u0633\\u06d2 \\u0688\\u06cc\\u0644 \\u06a9\\u06cc\\u061f\",\n          \"\\u0628\\u062d\\u0631\\u0627\\u0646 \\u0645\\u06cc\\u06ba \\u06af\\u06be\\u0631\\u06d2 \\u0633\\u0631\\u06cc \\u0644\\u0646\\u06a9\\u0627 \\u06a9\\u0627 \\u0627\\u0639\\u062a\\u0645\\u0627\\u062f \\u062d\\u0627\\u0635\\u0644 \\u06a9\\u0631\\u0646\\u06d2 \\u06a9\\u06d2 \\u0644\\u06cc\\u06d2 \\u0627\\u0646\\u0688\\u06cc\\u0627 \\u06a9\\u06cc\\u0627 \\u06a9\\u0631 \\u0631\\u06c1\\u0627 \\u06c1\\u06d2\\u061f\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"firstPublished\",\n      \"properties\": {\n        \"dtype\": \"object\",\n        \"num_unique_values\": 1836,\n        \"samples\": [\n          \"2020-09-25T04:44:12.000Z\",\n          \"2023-11-12T05:51:17.793Z\",\n          \"2023-11-24T02:15:10.552Z\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"id\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1842,\n        \"samples\": [\n          \"c729ye0vvd9o\",\n          \"3a970cfb-fa4d-4ef9-af36-86d9c514a89b\",\n          \"a1715453-c727-49b9-a1f3-75d26b3073c8\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"article\",\n      \"properties\": {\n        \"dtype\": \"object\",\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 44
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Drop unneccessary columns BBCUr\n",
        "df_p = df_p.drop(['id'], axis=1)"
      ],
      "metadata": {
        "id": "Agb5gCSbGpyS"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df_p"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "X-48h91FGsrF",
        "outputId": "7bcc0017-d36f-46a3-f98e-1c0f93d33ad7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                                 url  \\\n",
              "0     https://www.bbc.com/urdu/articles/cv20nxzl544o   \n",
              "1     https://www.bbc.com/urdu/articles/c109pqg9v1vo   \n",
              "2     https://www.bbc.com/urdu/articles/cj78ev79mdmo   \n",
              "3     https://www.bbc.com/urdu/articles/c3gl4pp0gzgo   \n",
              "4     https://www.bbc.com/urdu/articles/c2q3k4nq39no   \n",
              "...                                              ...   \n",
              "4911  https://www.bbc.com/urdu/articles/cz4dp89r8p8o   \n",
              "4912  https://www.bbc.com/urdu/articles/cn0995kvnzgo   \n",
              "4913  https://www.bbc.com/urdu/articles/cy0ddzg77zko   \n",
              "4914  https://www.bbc.com/urdu/articles/czd8jkzn0nno   \n",
              "4915  https://www.bbc.com/urdu/articles/crgye1440r0o   \n",
              "\n",
              "                                                summary  \\\n",
              "0     پاکستان کے زیرانتظام کشمیر میں بجلی کی قیمتوں ...   \n",
              "1     پاکستان میں معیشت اور ٹیکس کے ماہرین کے مطابق ...   \n",
              "2     تحقیقات سے پتا چلا ہے کہ ماسکو کا ساتھ نہ دینے...   \n",
              "3     رقبے کے لحاظ سے دنیا کے دوسرے سب سے بڑے ملک کے...   \n",
              "4     انڈیا کے وزیر اعظم نریندر مودی کا کہنا ہے کہ د...   \n",
              "...                                                 ...   \n",
              "4911  انڈیا کی شمالی ریاست اتراکھنڈ کے شہر ہلدوانی م...   \n",
              "4912  کانگریس پارٹی نے گزشتہ سال اپنی حکومت بناتے ہو...   \n",
              "4913  انتہا پسند ہندو تنظیموں کے ارکان نے اس فلم کے ...   \n",
              "4914  نوکری ٹھکرا کر یا نوکری چھوڑ کر اپنا کاروبار ش...   \n",
              "4915  یو پی بورڈ میں ٹاپ کرنے والی طالبہ پراچی کہتی ...   \n",
              "\n",
              "                                                  title  \\\n",
              "0     پاکستان کے زیرانتظام کشمیر میں احتجاج کیوں ہو ...   \n",
              "1     پاکستان میں متوسط طبقے اور غریبوں پر ٹیکسوں کا...   \n",
              "2     معاشی پابندیوں پر روس کا جواب: ’دشمن‘ مغربی مم...   \n",
              "3     کینیڈا کے تین شہر رہائش کے لیے دنیا کے 10 بہتر...   \n",
              "4     کیا انڈیا، مشرق وسطیٰ اور یورپ کا راہداری منصو...   \n",
              "...                                                 ...   \n",
              "4911  انڈیا: ریاست اتراکھنڈ میں مدرسے کی عمارت کو گر...   \n",
              "4912  ہندو لڑکے سے ملنے جانے والی مسلمان لڑکی پر ’تش...   \n",
              "4913  ’برہمن عورت کی بریانی پکانے سے قبل نماز‘ نیٹ ف...   \n",
              "4914  ’اپنا باس خود بننے کی خواہش یا آمدن کے محدود م...   \n",
              "4915  ’اگر میں ٹاپ نہ کرتی تو لوگ میری شکل پر توجہ ن...   \n",
              "\n",
              "                firstPublished  \\\n",
              "0     2023-10-06T06:51:11.061Z   \n",
              "1     2023-10-05T03:03:41.630Z   \n",
              "2     2023-10-04T02:20:54.824Z   \n",
              "3     2023-10-03T04:25:50.938Z   \n",
              "4     2023-10-03T03:20:38.534Z   \n",
              "...                        ...   \n",
              "4911  2024-02-10T09:31:10.954Z   \n",
              "4912  2024-01-13T03:45:15.429Z   \n",
              "4913  2024-01-12T15:13:09.862Z   \n",
              "4914  2024-04-27T06:02:58.918Z   \n",
              "4915  2024-04-27T10:33:29.384Z   \n",
              "\n",
              "                                                article  \n",
              "0     [پاکستان کے زیر انتظام کشمیر میں احتجاج تو کئی...  \n",
              "1     [اس شرط کے تحت زیادہ ٹیکس وصولی کے مختلف شعبوں...  \n",
              "2     [تاہم، تحقیقات میں یہ بھی پتا چلا ہے کہ کریملن...  \n",
              "3     [سمانتھا فالک، جو مونٹریال، کیلگری اور ٹورنٹو ...  \n",
              "4     [انڈیا کے وزیر اعظم نریندر مودی نے ایک حالیہ ر...  \n",
              "...                                                 ...  \n",
              "4911  [انڈیا کی شمالی ریاست اتراکھنڈ کے شہر ہلدوانی ...  \n",
              "4912  [خاتون نے بتایا کہ اس کے بعد انھیں ہوٹل سے سات...  \n",
              "4913  [ایک انڈین فلم، جسے ’ہندوؤں کے مذہبی جذبات مجر...  \n",
              "4914  [نوکری کو ٹھکرا کر یا نوکری کو چھوڑ کر اپنا کا...  \n",
              "4915  [پراچی کہتی ہیں کہ ’اس ٹرولنگ اور ہجوم کو دیکھ...  \n",
              "\n",
              "[4916 rows x 5 columns]"
            ],
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              "\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>url</th>\n",
              "      <th>summary</th>\n",
              "      <th>title</th>\n",
              "      <th>firstPublished</th>\n",
              "      <th>article</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>https://www.bbc.com/urdu/articles/cv20nxzl544o</td>\n",
              "      <td>پاکستان کے زیرانتظام کشمیر میں بجلی کی قیمتوں ...</td>\n",
              "      <td>پاکستان کے زیرانتظام کشمیر میں احتجاج کیوں ہو ...</td>\n",
              "      <td>2023-10-06T06:51:11.061Z</td>\n",
              "      <td>[پاکستان کے زیر انتظام کشمیر میں احتجاج تو کئی...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>https://www.bbc.com/urdu/articles/c109pqg9v1vo</td>\n",
              "      <td>پاکستان میں معیشت اور ٹیکس کے ماہرین کے مطابق ...</td>\n",
              "      <td>پاکستان میں متوسط طبقے اور غریبوں پر ٹیکسوں کا...</td>\n",
              "      <td>2023-10-05T03:03:41.630Z</td>\n",
              "      <td>[اس شرط کے تحت زیادہ ٹیکس وصولی کے مختلف شعبوں...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>https://www.bbc.com/urdu/articles/cj78ev79mdmo</td>\n",
              "      <td>تحقیقات سے پتا چلا ہے کہ ماسکو کا ساتھ نہ دینے...</td>\n",
              "      <td>معاشی پابندیوں پر روس کا جواب: ’دشمن‘ مغربی مم...</td>\n",
              "      <td>2023-10-04T02:20:54.824Z</td>\n",
              "      <td>[تاہم، تحقیقات میں یہ بھی پتا چلا ہے کہ کریملن...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>https://www.bbc.com/urdu/articles/c3gl4pp0gzgo</td>\n",
              "      <td>رقبے کے لحاظ سے دنیا کے دوسرے سب سے بڑے ملک کے...</td>\n",
              "      <td>کینیڈا کے تین شہر رہائش کے لیے دنیا کے 10 بہتر...</td>\n",
              "      <td>2023-10-03T04:25:50.938Z</td>\n",
              "      <td>[سمانتھا فالک، جو مونٹریال، کیلگری اور ٹورنٹو ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>https://www.bbc.com/urdu/articles/c2q3k4nq39no</td>\n",
              "      <td>انڈیا کے وزیر اعظم نریندر مودی کا کہنا ہے کہ د...</td>\n",
              "      <td>کیا انڈیا، مشرق وسطیٰ اور یورپ کا راہداری منصو...</td>\n",
              "      <td>2023-10-03T03:20:38.534Z</td>\n",
              "      <td>[انڈیا کے وزیر اعظم نریندر مودی نے ایک حالیہ ر...</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>4911</th>\n",
              "      <td>https://www.bbc.com/urdu/articles/cz4dp89r8p8o</td>\n",
              "      <td>انڈیا کی شمالی ریاست اتراکھنڈ کے شہر ہلدوانی م...</td>\n",
              "      <td>انڈیا: ریاست اتراکھنڈ میں مدرسے کی عمارت کو گر...</td>\n",
              "      <td>2024-02-10T09:31:10.954Z</td>\n",
              "      <td>[انڈیا کی شمالی ریاست اتراکھنڈ کے شہر ہلدوانی ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4912</th>\n",
              "      <td>https://www.bbc.com/urdu/articles/cn0995kvnzgo</td>\n",
              "      <td>کانگریس پارٹی نے گزشتہ سال اپنی حکومت بناتے ہو...</td>\n",
              "      <td>ہندو لڑکے سے ملنے جانے والی مسلمان لڑکی پر ’تش...</td>\n",
              "      <td>2024-01-13T03:45:15.429Z</td>\n",
              "      <td>[خاتون نے بتایا کہ اس کے بعد انھیں ہوٹل سے سات...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4913</th>\n",
              "      <td>https://www.bbc.com/urdu/articles/cy0ddzg77zko</td>\n",
              "      <td>انتہا پسند ہندو تنظیموں کے ارکان نے اس فلم کے ...</td>\n",
              "      <td>’برہمن عورت کی بریانی پکانے سے قبل نماز‘ نیٹ ف...</td>\n",
              "      <td>2024-01-12T15:13:09.862Z</td>\n",
              "      <td>[ایک انڈین فلم، جسے ’ہندوؤں کے مذہبی جذبات مجر...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4914</th>\n",
              "      <td>https://www.bbc.com/urdu/articles/czd8jkzn0nno</td>\n",
              "      <td>نوکری ٹھکرا کر یا نوکری چھوڑ کر اپنا کاروبار ش...</td>\n",
              "      <td>’اپنا باس خود بننے کی خواہش یا آمدن کے محدود م...</td>\n",
              "      <td>2024-04-27T06:02:58.918Z</td>\n",
              "      <td>[نوکری کو ٹھکرا کر یا نوکری کو چھوڑ کر اپنا کا...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4915</th>\n",
              "      <td>https://www.bbc.com/urdu/articles/crgye1440r0o</td>\n",
              "      <td>یو پی بورڈ میں ٹاپ کرنے والی طالبہ پراچی کہتی ...</td>\n",
              "      <td>’اگر میں ٹاپ نہ کرتی تو لوگ میری شکل پر توجہ ن...</td>\n",
              "      <td>2024-04-27T10:33:29.384Z</td>\n",
              "      <td>[پراچی کہتی ہیں کہ ’اس ٹرولنگ اور ہجوم کو دیکھ...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>4916 rows × 5 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-1da7c164-753c-45a5-a3de-94a8989e3481')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
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              "  </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",
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              "\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",
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              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-1da7c164-753c-45a5-a3de-94a8989e3481 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-1da7c164-753c-45a5-a3de-94a8989e3481');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
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              "  </button>\n",
              "\n",
              "<style>\n",
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              "  [theme=dark] .colab-df-quickchart {\n",
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              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
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              "  }\n",
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              "  .colab-df-quickchart:hover {\n",
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              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
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              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
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              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
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              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
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              "      border-top-color: var(--fill-color);\n",
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              "    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-7fe1b884-8f33-46a7-af79-f3314b26b160 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
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              "\n",
              "  <div id=\"id_eeddaaf9-8cc1-43e4-a66d-acfbbad475d4\">\n",
              "    <style>\n",
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              "        border: none;\n",
              "        border-radius: 50%;\n",
              "        cursor: pointer;\n",
              "        display: none;\n",
              "        fill: #1967D2;\n",
              "        height: 32px;\n",
              "        padding: 0 0 0 0;\n",
              "        width: 32px;\n",
              "      }\n",
              "\n",
              "      .colab-df-generate:hover {\n",
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              "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "        fill: #174EA6;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate {\n",
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              "        fill: #D2E3FC;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate:hover {\n",
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              "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "        fill: #FFFFFF;\n",
              "      }\n",
              "    </style>\n",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('df_p')\"\n",
              "            title=\"Generate code using this dataframe.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
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              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('df_p');\n",
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              "\n",
              "    </div>\n",
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            }
          },
          "metadata": {},
          "execution_count": 46
        }
      ]
    }
  ]
}