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.gitattributes

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 *.csv filter=lfs diff=lfs merge=lfs -text
+default/train/0000.parquet filter=lfs diff=lfs merge=lfs -text
+default/train/0001.parquet filter=lfs diff=lfs merge=lfs -text

README.md

@@ -1,9 +0,0 @@
-
-# AI/Tech Dataset
-
-This dataset is a collection of AI/tech articles scraped from the web.
-
-- [analytics.ipynb](analytics.ipynb) - Notebook containing some details about the dataset and how to load it.
-- [index.csv](./index.csv) - CSV file containing all the data. You can load this with `pandas.read_csv`.
-- [counts.csv](./counts.csv) - CSV file containing the counts of each year.
-- For raw text files, see the [scraper repo](https://github.com/siavava/scrape.hs)

analytics.ipynb

@@ -1,399 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Data Analytics for the Corpus\n",
-    "\n",
-    "## Author: Amittai Siavava"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Load the CSV metadata"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import numpy as np\n",
-    "import pandas as pd\n",
-    "import matplotlib.pyplot as plt\n",
-    "from collections import Counter\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>id</th>\n",
-       "      <th>year</th>\n",
-       "      <th>title</th>\n",
-       "      <th>url</th>\n",
-       "      <th>text</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>0</td>\n",
-       "      <td>2023.0</td>\n",
-       "      <td>\"MIT Technology Review\"</td>\n",
-       "      <td>\"https://www.technologyreview.com\"</td>\n",
-       "      <td>\"Featured Topics Newsletters Events Podcasts F...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>1</td>\n",
-       "      <td>2023.0</td>\n",
-       "      <td>\"WIRED - The Latest in Technology, Science, Cu...</td>\n",
-       "      <td>\"https://www.wired.com\"</td>\n",
-       "      <td>\"Open Navigation Menu To revisit this article,...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>2</td>\n",
-       "      <td>2019.0</td>\n",
-       "      <td>\"The Verge\"</td>\n",
-       "      <td>\"https://www.theverge.com\"</td>\n",
-       "      <td>\"The Verge homepage The Verge The Verge logo.\\...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>3</td>\n",
-       "      <td>2023.0</td>\n",
-       "      <td>\"TechCrunch | Startup and Technology News\"</td>\n",
-       "      <td>\"https://www.techcrunch.com\"</td>\n",
-       "      <td>\"WeWork reportedly on the verge of filing for ...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>4</td>\n",
-       "      <td>2022.0</td>\n",
-       "      <td>\"A new vision of artificial intelligence for t...</td>\n",
-       "      <td>\"https://www.technologyreview.com/2022/04/22/1...</td>\n",
-       "      <td>\"Featured Topics Newsletters Events Podcasts A...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>5</th>\n",
-       "      <td>5</td>\n",
-       "      <td>2022.0</td>\n",
-       "      <td>\"The scientist who co-created CRISPR isn’t rul...</td>\n",
-       "      <td>\"https://www.technologyreview.com/2022/04/26/1...</td>\n",
-       "      <td>\"Featured Topics Newsletters Events Podcasts F...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>6</th>\n",
-       "      <td>6</td>\n",
-       "      <td>2022.0</td>\n",
-       "      <td>\"These fast, cheap tests could help us coexist...</td>\n",
-       "      <td>\"https://www.technologyreview.com/2022/04/27/1...</td>\n",
-       "      <td>\"Featured Topics Newsletters Events Podcasts F...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>7</th>\n",
-       "      <td>7</td>\n",
-       "      <td>2022.0</td>\n",
-       "      <td>\"Tackling multiple tasks with a single visual ...</td>\n",
-       "      <td>\"http://www.deepmind.com/blog/tackling-multipl...</td>\n",
-       "      <td>\"DeepMind Search Search Close DeepMind About O...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8</th>\n",
-       "      <td>8</td>\n",
-       "      <td>2019.0</td>\n",
-       "      <td>\"About - Google DeepMind\"</td>\n",
-       "      <td>\"https://www.deepmind.com/about\"</td>\n",
-       "      <td>\"DeepMind Search Search Close DeepMind About O...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>9</th>\n",
-       "      <td>9</td>\n",
-       "      <td>2023.0</td>\n",
-       "      <td>\"Blog - Google DeepMind\"</td>\n",
-       "      <td>\"https://www.deepmind.com/blog-categories/appl...</td>\n",
-       "      <td>\"DeepMind Search Search Close DeepMind About O...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>10</th>\n",
-       "      <td>10</td>\n",
-       "      <td>2022.0</td>\n",
-       "      <td>\"Accelerating fusion science through learned p...</td>\n",
-       "      <td>\"https://www.deepmind.com/blog/accelerating-fu...</td>\n",
-       "      <td>\"DeepMind Search Search Close DeepMind About O...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>11</th>\n",
-       "      <td>11</td>\n",
-       "      <td>2022.0</td>\n",
-       "      <td>\"DeepMind’s latest research at ICLR 2022 - Goo...</td>\n",
-       "      <td>\"https://www.deepmind.com/blog/deepminds-lates...</td>\n",
-       "      <td>\"DeepMind Search Search Close DeepMind About O...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>12</th>\n",
-       "      <td>12</td>\n",
-       "      <td>2022.0</td>\n",
-       "      <td>\"MuZero’s first step from research into the re...</td>\n",
-       "      <td>\"https://www.deepmind.com/blog/muzeros-first-s...</td>\n",
-       "      <td>\"DeepMind Search Search Close DeepMind About O...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>13</th>\n",
-       "      <td>13</td>\n",
-       "      <td>2022.0</td>\n",
-       "      <td>\"Predicting the past with Ithaca - Google Deep...</td>\n",
-       "      <td>\"https://www.deepmind.com/blog/predicting-the-...</td>\n",
-       "      <td>\"DeepMind Search Search Close DeepMind About O...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>14</th>\n",
-       "      <td>14</td>\n",
-       "      <td>2022.0</td>\n",
-       "      <td>\"Tackling multiple tasks with a single visual ...</td>\n",
-       "      <td>\"https://www.deepmind.com/blog/tackling-multip...</td>\n",
-       "      <td>\"DeepMind Search Search Close DeepMind About O...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>15</th>\n",
-       "      <td>15</td>\n",
-       "      <td>2016.0</td>\n",
-       "      <td>\"AlphaGo - Google DeepMind\"</td>\n",
-       "      <td>\"https://www.deepmind.com/research/highlighted...</td>\n",
-       "      <td>\"DeepMind Search Search Close DeepMind About O...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>17</th>\n",
-       "      <td>17</td>\n",
-       "      <td>2023.0</td>\n",
-       "      <td>\"Responsibility &amp; Safety - Google DeepMind\"</td>\n",
-       "      <td>\"https://www.deepmind.com/safety-and-ethics\"</td>\n",
-       "      <td>\"DeepMind Search Search Close DeepMind About O...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>18</th>\n",
-       "      <td>18</td>\n",
-       "      <td>2022.0</td>\n",
-       "      <td>\"This Week’s Awesome Tech Stories From Around ...</td>\n",
-       "      <td>\"https://singularityhub.com/2022/04/16/this-we...</td>\n",
-       "      <td>\"Topics AI Biotech Computing Space Energy Futu...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>19</th>\n",
-       "      <td>19</td>\n",
-       "      <td>2022.0</td>\n",
-       "      <td>\"There's Now an Algorithm to Help Workers Avoi...</td>\n",
-       "      <td>\"https://singularityhub.com/2022/04/18/theres-...</td>\n",
-       "      <td>\"Topics AI Biotech Computing Space Energy Futu...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>20</th>\n",
-       "      <td>20</td>\n",
-       "      <td>2022.0</td>\n",
-       "      <td>\"This Week’s Awesome Tech Stories From Around ...</td>\n",
-       "      <td>\"https://singularityhub.com/2022/04/23/this-we...</td>\n",
-       "      <td>\"Topics AI Biotech Computing Space Energy Futu...</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "    id    year                                              title  \\\n",
-       "0    0  2023.0                            \"MIT Technology Review\"   \n",
-       "1    1  2023.0  \"WIRED - The Latest in Technology, Science, Cu...   \n",
-       "2    2  2019.0                                        \"The Verge\"   \n",
-       "3    3  2023.0         \"TechCrunch | Startup and Technology News\"   \n",
-       "4    4  2022.0  \"A new vision of artificial intelligence for t...   \n",
-       "5    5  2022.0  \"The scientist who co-created CRISPR isn’t rul...   \n",
-       "6    6  2022.0  \"These fast, cheap tests could help us coexist...   \n",
-       "7    7  2022.0  \"Tackling multiple tasks with a single visual ...   \n",
-       "8    8  2019.0                          \"About - Google DeepMind\"   \n",
-       "9    9  2023.0                           \"Blog - Google DeepMind\"   \n",
-       "10  10  2022.0  \"Accelerating fusion science through learned p...   \n",
-       "11  11  2022.0  \"DeepMind’s latest research at ICLR 2022 - Goo...   \n",
-       "12  12  2022.0  \"MuZero’s first step from research into the re...   \n",
-       "13  13  2022.0  \"Predicting the past with Ithaca - Google Deep...   \n",
-       "14  14  2022.0  \"Tackling multiple tasks with a single visual ...   \n",
-       "15  15  2016.0                        \"AlphaGo - Google DeepMind\"   \n",
-       "17  17  2023.0        \"Responsibility & Safety - Google DeepMind\"   \n",
-       "18  18  2022.0  \"This Week’s Awesome Tech Stories From Around ...   \n",
-       "19  19  2022.0  \"There's Now an Algorithm to Help Workers Avoi...   \n",
-       "20  20  2022.0  \"This Week’s Awesome Tech Stories From Around ...   \n",
-       "\n",
-       "                                                  url  \\\n",
-       "0                  \"https://www.technologyreview.com\"   \n",
-       "1                             \"https://www.wired.com\"   \n",
-       "2                          \"https://www.theverge.com\"   \n",
-       "3                        \"https://www.techcrunch.com\"   \n",
-       "4   \"https://www.technologyreview.com/2022/04/22/1...   \n",
-       "5   \"https://www.technologyreview.com/2022/04/26/1...   \n",
-       "6   \"https://www.technologyreview.com/2022/04/27/1...   \n",
-       "7   \"http://www.deepmind.com/blog/tackling-multipl...   \n",
-       "8                    \"https://www.deepmind.com/about\"   \n",
-       "9   \"https://www.deepmind.com/blog-categories/appl...   \n",
-       "10  \"https://www.deepmind.com/blog/accelerating-fu...   \n",
-       "11  \"https://www.deepmind.com/blog/deepminds-lates...   \n",
-       "12  \"https://www.deepmind.com/blog/muzeros-first-s...   \n",
-       "13  \"https://www.deepmind.com/blog/predicting-the-...   \n",
-       "14  \"https://www.deepmind.com/blog/tackling-multip...   \n",
-       "15  \"https://www.deepmind.com/research/highlighted...   \n",
-       "17       \"https://www.deepmind.com/safety-and-ethics\"   \n",
-       "18  \"https://singularityhub.com/2022/04/16/this-we...   \n",
-       "19  \"https://singularityhub.com/2022/04/18/theres-...   \n",
-       "20  \"https://singularityhub.com/2022/04/23/this-we...   \n",
-       "\n",
-       "                                                 text  \n",
-       "0   \"Featured Topics Newsletters Events Podcasts F...  \n",
-       "1   \"Open Navigation Menu To revisit this article,...  \n",
-       "2   \"The Verge homepage The Verge The Verge logo.\\...  \n",
-       "3   \"WeWork reportedly on the verge of filing for ...  \n",
-       "4   \"Featured Topics Newsletters Events Podcasts A...  \n",
-       "5   \"Featured Topics Newsletters Events Podcasts F...  \n",
-       "6   \"Featured Topics Newsletters Events Podcasts F...  \n",
-       "7   \"DeepMind Search Search Close DeepMind About O...  \n",
-       "8   \"DeepMind Search Search Close DeepMind About O...  \n",
-       "9   \"DeepMind Search Search Close DeepMind About O...  \n",
-       "10  \"DeepMind Search Search Close DeepMind About O...  \n",
-       "11  \"DeepMind Search Search Close DeepMind About O...  \n",
-       "12  \"DeepMind Search Search Close DeepMind About O...  \n",
-       "13  \"DeepMind Search Search Close DeepMind About O...  \n",
-       "14  \"DeepMind Search Search Close DeepMind About O...  \n",
-       "15  \"DeepMind Search Search Close DeepMind About O...  \n",
-       "17  \"DeepMind Search Search Close DeepMind About O...  \n",
-       "18  \"Topics AI Biotech Computing Space Energy Futu...  \n",
-       "19  \"Topics AI Biotech Computing Space Energy Futu...  \n",
-       "20  \"Topics AI Biotech Computing Space Energy Futu...  "
-      ]
-     },
-     "execution_count": 6,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "df = pd.read_csv(\"index.csv\")\n",
-    "df.dropna(inplace=True)\n",
-    "df.head(20)\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 11,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "unique_years = [2001, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "[1950 = 0] [1951 = 0] [1952 = 0] [1953 = 0] [1954 = 0] [1955 = 0] [1956 = 0] [1957 = 0] [1958 = 0] [1959 = 0] [1960 = 0] [1961 = 0] [1962 = 0] [1963 = 0] [1964 = 0] [1965 = 0] [1966 = 0] [1967 = 0] [1968 = 0] [1969 = 0] [1970 = 0] [1971 = 0] [1972 = 0] [1973 = 0] [1974 = 0] [1975 = 0] [1976 = 0] [1977 = 0] [1978 = 0] [1979 = 0] [1980 = 0] [1981 = 0] [1982 = 0] [1983 = 0] [1984 = 0] [1985 = 0] [1986 = 0] [1987 = 0] [1988 = 0] [1989 = 0] [1990 = 0] [1991 = 0] [1992 = 0] [1993 = 0] [1994 = 0] [1995 = 0] [1996 = 0] [1997 = 0] [1998 = 0] [1999 = 0] [2000 = 0] [2001 = 3] [2002 = 0] [2003 = 1] [2004 = 1] [2005 = 6] [2006 = 4] [2007 = 3] [2008 = 5] [2009 = 12] [2010 = 3] [2011 = 4] [2012 = 8] [2013 = 6] [2014 = 10] [2015 = 31] [2016 = 56] [2017 = 82] [2018 = 155] [2019 = 168] [2020 = 297] [2021 = 445] [2022 = 608] [2023 = 521] "
-     ]
-    }
-   ],
-   "source": [
-    "# df = pd.read_csv(\"index.csv\")\n",
-    "# df.head()\n",
-    "\n",
-    "\n",
-    "data = np.array(df)\n",
-    "years = data[:, 1]\n",
-    "\n",
-    "for i in range(len(years)):\n",
-    "  try:\n",
-    "    years[i] = int(years[i])\n",
-    "  except ValueError:\n",
-    "    continue\n",
-    "\n",
-    "years = [year for year in years if isinstance(year, int) and 2000 <= year <= 2024 ]\n",
-    "counters = Counter(years)\n",
-    "unique_years = sorted(list(counters.keys()))\n",
-    "print(f\"{unique_years = }\")\n",
-    "counts = [counters[year] for year in unique_years]\n",
-    "plt.bar(unique_years, counts, label=\"Total\")\n",
-    "plt.show()\n",
-    "with open(\"counts.csv\", \"w\") as f:\n",
-    "  for year in range(1950, 2024):\n",
-    "    count = counters.get(year, 0)\n",
-    "    print(f\"[{year} = {count}]\", end=\" \")\n",
-    "    f.write(f\"{year},{count}\\n\")\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "interpreter": {
-   "hash": "607b7d84c7d8e26dbbffb4014e40424fe2faf80a09a85d717e93e42c2773dc40"
-  },
-  "kernelspec": {
-   "display_name": "Python 3.10.4 ('ml')",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.11.5"
-  },
-  "orig_nbformat": 4
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}

counts.csv → default/train/0000.parquet

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:06a4a5ec4a4ac58a3f578ae83ad05450730de0a7700dab86e0ce8c21c60dde9f
-size 535
+oid sha256:b30f4a2abf20ca5b55459c7c253f7c3ac812527e28b415bc985599d5108fd33b
+size 45439611

index.csv → default/train/0001.parquet

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:4d0325d722a804c20464d84097b498ece3793fe63081de03ad8b3c6b88b765dd
-size 128154723
+oid sha256:b30f4a2abf20ca5b55459c7c253f7c3ac812527e28b415bc985599d5108fd33b
+size 45439611

index.py

@@ -1,123 +0,0 @@
-#!/usr/bin/env python3
-# -*- coding: utf-8 -*-
-
-"""
-  Simple script to generate metadata about corpus.
-"""
-
-__author__  = "Amittai Siavava"
-__version__ = "0.0.1"
-
-from os import mkdir
-from collections import Counter
-import csv
-import pandas as pd
-
-def count_words():
-  """
-    This is a simple script to count the number of words in this directory.
-    
-    It loops over all the lines in `.all` and counts the occurrence of each word,
-    then sums them up.
-
-    HACK:
-    This is a hacky way to count the number of words in the corpus.
-    >>> count_words()
-  """
-  total = 0
-  with open("all", "r") as f:
-    for line in f:
-      try:
-        total += int(line.strip().split()[0])
-      except:
-        pass
-    f.close()
-  if total > 0:
-    with open (".total", "w") as f:
-      print(f"Total words = {total}")
-      f.write(f"Total words = {total}")
-      f.close()
-
-def index_pages():
-  """
-    Generate a friendly index of the pages.
-
-    We create a csv and a tsv (in case one proves more convenient than the other).
-  """
-  docID = 0
-
-  with open("index.csv", "w") as csv_file, open("urls", "w") as urls:
-    writer = csv.writer(csv_file)
-    # csv.write("id,year,title,url\n")
-    writer.writerow(["id", "year", "title", "url", "text"])
-    while True:
-      try:
-        with open(f"../log/{docID}", "r") as meta, open(f"../log/{docID}.txt", "r") as data:
-          title = meta.readline().strip()
-          year = meta.readline().strip()
-          url = meta.readline().strip()
-          # read remaining text
-          text = data.read()
-          # print(f"{text = }")
-
-
-
-          meta.close()
-          data.close()
-
-          print(f"Indexing: {docID}")
-          # csv.write(f'{docID},{year},"{title}","{url}","{text}"\n')
-          
-          writer.writerow([docID, year, f'"{title}"', f'"{url}"', f'"{text}"'])
-          # tsv.write(f"{docID}\t{year}\t{title}\t{url}\n")
-          urls.write(f"{url}\n")
-          docID += 1
-      except:
-        break
-  print("Done.")
-
-def categorize():
-  """
-    Categorize the pages by year.
-  """
-
-  docID = 0
-  years = Counter()
-  while True:
-    try:
-      with open(f"../log/{docID}.txt", "r") as doc, open(f"../log/{docID}", "r") as meta:
-        title = meta.readline().strip()
-        year = meta.readline().strip()
-        url = meta.readline().strip()
-        text = doc.read()
-        doc.close()
-        meta.close()
-
-        if year == "":
-          year = "unknown"
-
-        try:
-          mkdir(f"../categorized/{year}")
-        except:
-          pass
-
-        id = years.get(year, 0)
-        with open(f"../categorized/{year}/{id}.txt", "w") as f:
-          f.write(f"old id = {docID}\n{title}\n{year}\n{url}\n\n{text}")
-          f.close()
-        years[year] = id + 1
-        docID += 1
-        
-    except:
-      break
-
-# def load_data():
-#   df = pd.read_csv("index.csv")
-#   df.head(5)
-
-
-if __name__ == "__main__":
-  # count_words()
-  index_pages()
-  categorize()
-  # load_data()