robotstxt_analysis.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "5c8b3503",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "\n",
    "from urllib.parse import urlparse\n",
    "\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "from prettytable import PrettyTable"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "652b4b7f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['/home/osama/CC-MAIN-2021-43-robotstxt/output/1634323583423.96.csv',\n",
       " '/home/osama/CC-MAIN-2021-43-robotstxt/output/1634323583083.92.csv',\n",
       " '/home/osama/CC-MAIN-2021-43-robotstxt/output/1634323583087.95.csv',\n",
       " '/home/osama/CC-MAIN-2021-43-robotstxt/output/1634323583408.93.csv']"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "path = '/home/osama/CC-MAIN-2021-43-robotstxt/output/'\n",
    "csv_files = []\n",
    "\n",
    "for file_name in os.listdir(path='/home/osama/CC-MAIN-2021-43-robotstxt/output/'):\n",
    "    csv_files.append(path + file_name)\n",
    "\n",
    "csv_files"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "fb651b08",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1634323583423.96.csv --> 592722/592722\n",
      "1634323583083.92.csv --> 1717608/2195703\n",
      "1634323583087.95.csv --> 590460/590460\n",
      "1634323583408.93.csv --> 580222/580222\n"
     ]
    }
   ],
   "source": [
    "df_list = []\n",
    "\n",
    "for file in csv_files:\n",
    "    df = pd.read_csv(file, header=None).rename(columns={1:'robotstxt_url', 2:'no_bias', 3:'favored', 4:'disfavored', 5:'fav_count_diff', 6:'disfav_count_diff'}).drop(columns=[0], axis=1)\n",
    "    df_list.append(df)\n",
    "    print(file.split('/')[-1] + ' --> ' + str(df['robotstxt_url'].nunique()) + '/' + str(len(df)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "aa8c596c",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.concat(df_list, axis=0, ignore_index=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "56d1b115",
   "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>robotstxt_url</th>\n",
       "      <th>no_bias</th>\n",
       "      <th>favored</th>\n",
       "      <th>disfavored</th>\n",
       "      <th>fav_count_diff</th>\n",
       "      <th>disfav_count_diff</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>http://1lt.upc04m9.cn/robots.txt</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>http://25film.net/robots.txt</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>http://344.oplkuqz.cn/robots.txt</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>http://a1groundtransportation.com/robots.txt</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>http://abdipersadafm.co.id/robots.txt</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</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>3959102</th>\n",
       "      <td>https://youriguide.com/robots.txt</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3959103</th>\n",
       "      <td>https://yourstrulyxblog.com/robots.txt</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3959104</th>\n",
       "      <td>https://youtube-binaryoption.forextr.website/r...</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3959105</th>\n",
       "      <td>https://zvukipro.com/robots.txt</td>\n",
       "      <td>[]</td>\n",
       "      <td>['Mediapartners-Google']</td>\n",
       "      <td>[]</td>\n",
       "      <td>[43]</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3959106</th>\n",
       "      <td>https://zwahxd.cn/robots.txt</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3959107 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                             robotstxt_url no_bias  \\\n",
       "0                         http://1lt.upc04m9.cn/robots.txt      []   \n",
       "1                             http://25film.net/robots.txt      []   \n",
       "2                         http://344.oplkuqz.cn/robots.txt      []   \n",
       "3             http://a1groundtransportation.com/robots.txt      []   \n",
       "4                    http://abdipersadafm.co.id/robots.txt      []   \n",
       "...                                                    ...     ...   \n",
       "3959102                  https://youriguide.com/robots.txt      []   \n",
       "3959103             https://yourstrulyxblog.com/robots.txt      []   \n",
       "3959104  https://youtube-binaryoption.forextr.website/r...      []   \n",
       "3959105                    https://zvukipro.com/robots.txt      []   \n",
       "3959106                       https://zwahxd.cn/robots.txt      []   \n",
       "\n",
       "                          favored disfavored fav_count_diff disfav_count_diff  \n",
       "0                              []         []             []                []  \n",
       "1                              []         []             []                []  \n",
       "2                              []         []             []                []  \n",
       "3                              []         []             []                []  \n",
       "4                              []         []             []                []  \n",
       "...                           ...        ...            ...               ...  \n",
       "3959102                        []         []             []                []  \n",
       "3959103                        []         []             []                []  \n",
       "3959104                        []         []             []                []  \n",
       "3959105  ['Mediapartners-Google']         []           [43]                []  \n",
       "3959106                        []         []             []                []  \n",
       "\n",
       "[3959107 rows x 6 columns]"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "5ef2ff6b",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.drop_duplicates(keep='first', inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "9738efea",
   "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>robotstxt_url</th>\n",
       "      <th>no_bias</th>\n",
       "      <th>favored</th>\n",
       "      <th>disfavored</th>\n",
       "      <th>fav_count_diff</th>\n",
       "      <th>disfav_count_diff</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>http://1lt.upc04m9.cn/robots.txt</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>http://25film.net/robots.txt</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>http://344.oplkuqz.cn/robots.txt</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>http://a1groundtransportation.com/robots.txt</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>http://abdipersadafm.co.id/robots.txt</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</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>3378059</th>\n",
       "      <td>https://zao-era.ru/robots.txt</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3378060</th>\n",
       "      <td>https://zappiagioielli.com/robots.txt</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3378062</th>\n",
       "      <td>https://zh.move-glamping.com/robots.txt</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>['AdsBot-Google', 'AdsBot-Google-Mobile']</td>\n",
       "      <td>[]</td>\n",
       "      <td>[-3, -3]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3378063</th>\n",
       "      <td>https://zitamama.wordpress.com/robots.txt</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3378064</th>\n",
       "      <td>https://zlatanov.ro/robots.txt</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2022878 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                        robotstxt_url no_bias favored  \\\n",
       "0                    http://1lt.upc04m9.cn/robots.txt      []      []   \n",
       "1                        http://25film.net/robots.txt      []      []   \n",
       "2                    http://344.oplkuqz.cn/robots.txt      []      []   \n",
       "3        http://a1groundtransportation.com/robots.txt      []      []   \n",
       "4               http://abdipersadafm.co.id/robots.txt      []      []   \n",
       "...                                               ...     ...     ...   \n",
       "3378059                 https://zao-era.ru/robots.txt      []      []   \n",
       "3378060         https://zappiagioielli.com/robots.txt      []      []   \n",
       "3378062       https://zh.move-glamping.com/robots.txt      []      []   \n",
       "3378063     https://zitamama.wordpress.com/robots.txt      []      []   \n",
       "3378064                https://zlatanov.ro/robots.txt      []      []   \n",
       "\n",
       "                                        disfavored fav_count_diff  \\\n",
       "0                                               []             []   \n",
       "1                                               []             []   \n",
       "2                                               []             []   \n",
       "3                                               []             []   \n",
       "4                                               []             []   \n",
       "...                                            ...            ...   \n",
       "3378059                                         []             []   \n",
       "3378060                                         []             []   \n",
       "3378062  ['AdsBot-Google', 'AdsBot-Google-Mobile']             []   \n",
       "3378063                                         []             []   \n",
       "3378064                                         []             []   \n",
       "\n",
       "        disfav_count_diff  \n",
       "0                      []  \n",
       "1                      []  \n",
       "2                      []  \n",
       "3                      []  \n",
       "4                      []  \n",
       "...                   ...  \n",
       "3378059                []  \n",
       "3378060                []  \n",
       "3378062          [-3, -3]  \n",
       "3378063                []  \n",
       "3378064                []  \n",
       "\n",
       "[2022878 rows x 6 columns]"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "4ab6758f",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.to_csv('/home/osama/CC-MAIN-2021-43-robotstxt/output/robotstxt.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "id": "a22c93a0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "298"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sum(df['robotstxt_url'].value_counts() > 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "id": "c36db296",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "https://www.projecthoneypot.org/robots.txt    4\n",
       "https://saleofcar.com/robots.txt              4\n",
       "https://reachmd.com/robots.txt                3\n",
       "https://forum.fxopen.com/robots.txt           2\n",
       "https://varu.hu/robots.txt                    2\n",
       "https://be.sportsdirect.com/robots.txt        2\n",
       "https://barathier.it/robots.txt               2\n",
       "https://www.rirun.co/robots.txt               2\n",
       "https://www.memagazine.it/robots.txt          2\n",
       "https://www.gopostyle.com/robots.txt          2\n",
       "Name: robotstxt_url, dtype: int64"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['robotstxt_url'].value_counts()[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "f8addc9d",
   "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>robotstxt_url</th>\n",
       "      <th>no_bias</th>\n",
       "      <th>favored</th>\n",
       "      <th>disfavored</th>\n",
       "      <th>fav_count_diff</th>\n",
       "      <th>disfav_count_diff</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>587661</th>\n",
       "      <td>https://www.rirun.co/robots.txt</td>\n",
       "      <td>['AhrefsBot', 'AhrefsSiteAudit']</td>\n",
       "      <td>['MJ12bot', 'Pinterest', 'adsbot-google']</td>\n",
       "      <td>['Nutch']</td>\n",
       "      <td>[9, 7, 4]</td>\n",
       "      <td>[-1]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2863266</th>\n",
       "      <td>https://www.rirun.co/robots.txt</td>\n",
       "      <td>['AhrefsBot', 'AhrefsSiteAudit']</td>\n",
       "      <td>['MJ12bot', 'Pinterest', 'adsbot-google']</td>\n",
       "      <td>['Nutch']</td>\n",
       "      <td>[10, 10, 5]</td>\n",
       "      <td>[-1]</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           robotstxt_url                           no_bias  \\\n",
       "587661   https://www.rirun.co/robots.txt  ['AhrefsBot', 'AhrefsSiteAudit']   \n",
       "2863266  https://www.rirun.co/robots.txt  ['AhrefsBot', 'AhrefsSiteAudit']   \n",
       "\n",
       "                                           favored disfavored fav_count_diff  \\\n",
       "587661   ['MJ12bot', 'Pinterest', 'adsbot-google']  ['Nutch']      [9, 7, 4]   \n",
       "2863266  ['MJ12bot', 'Pinterest', 'adsbot-google']  ['Nutch']    [10, 10, 5]   \n",
       "\n",
       "        disfav_count_diff  \n",
       "587661               [-1]  \n",
       "2863266              [-1]  "
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# https://www.projecthoneypot.org/robots.txt : changes user-agent every new access to robots.txt \n",
    "# https://saleofcar.com/robots.txt : gives MediaPartners-Google bot more access in time\n",
    "# https://varu.hu/robots.txt : moved MJ12bot from no_bias to disfavored\n",
    "\n",
    "# Those duplicated robots.txt changed over the different 4 crawls, for differnt reason, to be analysed further after\n",
    "# Time series Analyse for bots is possible to see how they tend to differ over differnt crawls (and so different time) to see how their access change and their categories too.\n",
    "\n",
    "df[df['robotstxt_url'] == 'https://www.rirun.co/robots.txt']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "id": "8913316e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# drop duplicates with same robotstxt_url but different values for other columns, as those to be analyzed seperately\n",
    "\n",
    "df.drop_duplicates('robotstxt_url', keep='last', inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "id": "c0a540f1",
   "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>robotstxt_url</th>\n",
       "      <th>no_bias</th>\n",
       "      <th>favored</th>\n",
       "      <th>disfavored</th>\n",
       "      <th>fav_count_diff</th>\n",
       "      <th>disfav_count_diff</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>http://1lt.upc04m9.cn/robots.txt</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>http://25film.net/robots.txt</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>http://344.oplkuqz.cn/robots.txt</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>http://a1groundtransportation.com/robots.txt</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>http://abdipersadafm.co.id/robots.txt</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</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>3378059</th>\n",
       "      <td>https://zao-era.ru/robots.txt</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3378060</th>\n",
       "      <td>https://zappiagioielli.com/robots.txt</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3378062</th>\n",
       "      <td>https://zh.move-glamping.com/robots.txt</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>['AdsBot-Google', 'AdsBot-Google-Mobile']</td>\n",
       "      <td>[]</td>\n",
       "      <td>[-3, -3]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3378063</th>\n",
       "      <td>https://zitamama.wordpress.com/robots.txt</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3378064</th>\n",
       "      <td>https://zlatanov.ro/robots.txt</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2022575 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                        robotstxt_url no_bias favored  \\\n",
       "0                    http://1lt.upc04m9.cn/robots.txt      []      []   \n",
       "1                        http://25film.net/robots.txt      []      []   \n",
       "2                    http://344.oplkuqz.cn/robots.txt      []      []   \n",
       "3        http://a1groundtransportation.com/robots.txt      []      []   \n",
       "4               http://abdipersadafm.co.id/robots.txt      []      []   \n",
       "...                                               ...     ...     ...   \n",
       "3378059                 https://zao-era.ru/robots.txt      []      []   \n",
       "3378060         https://zappiagioielli.com/robots.txt      []      []   \n",
       "3378062       https://zh.move-glamping.com/robots.txt      []      []   \n",
       "3378063     https://zitamama.wordpress.com/robots.txt      []      []   \n",
       "3378064                https://zlatanov.ro/robots.txt      []      []   \n",
       "\n",
       "                                        disfavored fav_count_diff  \\\n",
       "0                                               []             []   \n",
       "1                                               []             []   \n",
       "2                                               []             []   \n",
       "3                                               []             []   \n",
       "4                                               []             []   \n",
       "...                                            ...            ...   \n",
       "3378059                                         []             []   \n",
       "3378060                                         []             []   \n",
       "3378062  ['AdsBot-Google', 'AdsBot-Google-Mobile']             []   \n",
       "3378063                                         []             []   \n",
       "3378064                                         []             []   \n",
       "\n",
       "        disfav_count_diff  \n",
       "0                      []  \n",
       "1                      []  \n",
       "2                      []  \n",
       "3                      []  \n",
       "4                      []  \n",
       "...                   ...  \n",
       "3378059                []  \n",
       "3378060                []  \n",
       "3378062          [-3, -3]  \n",
       "3378063                []  \n",
       "3378064                []  \n",
       "\n",
       "[2022575 rows x 6 columns]"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "id": "4d527de2",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.to_csv('/home/osama/CC-MAIN-2021-43-robotstxt/output/robotstxt_with_no_different_crawls_duplicates.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "099d3cfb",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('/home/osama/CC-MAIN-2021-43-robotstxt/output/robotstxt_with_no_different_crawls_duplicates.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "edec90fc",
   "metadata": {},
   "outputs": [],
   "source": [
    "def to_1D(series):\n",
    " return pd.Series([x for _list in series for x in _list])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 444,
   "id": "f74c3263",
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_most_frequently_appeared_bots(top_10_appeared_bots_name, y_disfavored, y_no_bias, y_favored):\n",
    "    fig, ax = plt.subplots(figsize=(20, 10))\n",
    "\n",
    "    ax.bar(top_10_appeared_bots_name, y_disfavored, color='r', label='disfavored')\n",
    "    ax.bar(top_10_appeared_bots_name, y_no_bias, bottom=y_disfavored, color='g', label='no_bias')\n",
    "    ax.bar(top_10_appeared_bots_name, y_favored, bottom=y_disfavored + y_no_bias, color='b', label='favored')\n",
    "\n",
    "    ax.set_title('Most frequently used robot names in robots.txt files. The height of the bar represents the number of times a robot appeared in the dataset')\n",
    "    ax.set_xlabel('Bot name')\n",
    "    ax.set_ylabel('Number of times appeared')\n",
    "\n",
    "    ax.legend()\n",
    "\n",
    "    # helper method to auto-label bars\n",
    "    ax.bar_label(ax.containers[2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 445,
   "id": "9454182c",
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_number_of_time_bot_appears_distribution(nb_of_times_appeared, total_number_of_user_agents):\n",
    "    percentage_of_the_count_by_number_of_appearance = nb_of_times_appeared.value_counts().map(lambda v: v/total_number_of_user_agents*100)\n",
    "    fig, ax = plt.subplots(figsize=(8,6))\n",
    "    sns.scatterplot(x=percentage_of_the_count_by_number_of_appearance.index, y=percentage_of_the_count_by_number_of_appearance.values)\n",
    "\n",
    "    ax.set_xlabel('Number of times a robot appears')\n",
    "    ax.set_ylabel('Percentage')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 447,
   "id": "169f05a2",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_bots_favorability(favored_1d_series, disfavored_1d_series, N):\n",
    "    # favorability of a robot is = (#favored - #disfavored)/N  ; where N is the dataset size\n",
    "    favorability_of_robots = (favored_1d_series.value_counts().sub(disfavored_1d_series.value_counts(), fill_value=0)/N).sort_values(ascending=False)\n",
    "    return favorability_of_robots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 449,
   "id": "c68f145e",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_metrics(df):\n",
    "    # Get 1d series from the 3 columns\n",
    "    favored_1d_series = to_1D(df['favored'].apply(eval))\n",
    "    disfavored_1d_series = to_1D(df['disfavored'].apply(eval))\n",
    "    no_bias_1d_series = to_1D(df['no_bias'].apply(eval))\n",
    "    \n",
    "    # Get series with number of time a bot appeared overall in the dataset\n",
    "    nb_of_times_appeared = favored_1d_series.value_counts().add(disfavored_1d_series.value_counts(), fill_value=0).add(no_bias_1d_series.value_counts(), fill_value=0).sort_values(ascending=False)\n",
    "    \n",
    "    # Get the name of top 10 appeared bots\n",
    "    top_10_appeared_bots_name = nb_of_times_appeared[:10].index\n",
    "    \n",
    "    # Get number of times the top 10 robots have been disfavored, no_bias or favored\n",
    "    y_disfavored = disfavored_1d_series.value_counts()[top_10_appeared_bots_name].values\n",
    "    y_no_bias = no_bias_1d_series.value_counts()[top_10_appeared_bots_name].values\n",
    "    y_favored = favored_1d_series.value_counts()[top_10_appeared_bots_name].values\n",
    "    \n",
    "    # Total number of user_agents in the dataset\n",
    "    total_number_of_user_agents = nb_of_times_appeared.size\n",
    "    \n",
    "    # Let N be the total number of robots.txt files in the dataset. Used to calculate favorability\n",
    "    N = df.shape[0]\n",
    "    \n",
    "    return disfavored_1d_series, no_bias_1d_series, favored_1d_series, nb_of_times_appeared, top_10_appeared_bots_name, y_disfavored, y_no_bias, y_favored, total_number_of_user_agents, N"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 466,
   "id": "e59b882f",
   "metadata": {},
   "outputs": [],
   "source": [
    "def draw_favorability_table(favorability_of_robots, favored_1d_series, disfavored_1d_series, f=1):\n",
    "    table = PrettyTable()\n",
    "\n",
    "    table.field_names = ['Bot name', '#favored', '#disfavored', '#favorability', 'σ: categorical standard deviation']\n",
    "    favorability_of_robots_list = favorability_of_robots[:10] if f==1 else favorability_of_robots[-1:-11:-1]\n",
    "    for bot,score in favorability_of_robots_list.items():\n",
    "        N_favored = favored_1d_series.value_counts().get(bot, 0)\n",
    "        N_disfavored = disfavored_1d_series.value_counts().get(bot, 0)\n",
    "        sigma = np.sqrt(np.abs(score) * (1 - np.abs(score))/N)\n",
    "        table.add_row([bot, N_favored, N_disfavored, round(score, 6), round(sigma, 6)])\n",
    "\n",
    "    print(table)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "3f34141a",
   "metadata": {},
   "outputs": [],
   "source": [
    "favored_1d_series = to_1D(df['favored'].apply(eval))\n",
    "disfavored_1d_series = to_1D(df['disfavored'].apply(eval))\n",
    "no_bias_1d_series = to_1D(df['no_bias'].apply(eval)) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "db918430",
   "metadata": {},
   "outputs": [],
   "source": [
    "nb_of_times_appeared = favored_1d_series.value_counts().add(disfavored_1d_series.value_counts(), fill_value=0).add(no_bias_1d_series.value_counts(), fill_value=0).sort_values(ascending=False)\n",
    "top_10_appeared_bots_name = nb_of_times_appeared[:10].index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "e09c3cca",
   "metadata": {},
   "outputs": [],
   "source": [
    "y_disfavored = disfavored_1d_series.value_counts()[top_10_appeared_bots_name].values\n",
    "y_no_bias = no_bias_1d_series.value_counts()[top_10_appeared_bots_name].values\n",
    "y_favored = favored_1d_series.value_counts()[top_10_appeared_bots_name].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "e9fed0a0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "23613\n"
     ]
    }
   ],
   "source": [
    "# Total number of user_agents\n",
    "total_number_of_user_agents = nb_of_times_appeared.size\n",
    "print(total_number_of_user_agents)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 209,
   "id": "0a305b7e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Text(0, 0, '106347'),\n",
       " Text(0, 0, '98028'),\n",
       " Text(0, 0, '85706'),\n",
       " Text(0, 0, '79679'),\n",
       " Text(0, 0, '78549'),\n",
       " Text(0, 0, '74407'),\n",
       " Text(0, 0, '59948'),\n",
       " Text(0, 0, '52021'),\n",
       " Text(0, 0, '48092'),\n",
       " Text(0, 0, '47237')]"
      ]
     },
     "execution_count": 209,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(20, 10))\n",
    "\n",
    "ax.bar(top_10_appeared_bots_name, y_disfavored, color='r', label='disfavored')\n",
    "ax.bar(top_10_appeared_bots_name, y_no_bias, bottom=y_disfavored, color='g', label='no_bias')\n",
    "ax.bar(top_10_appeared_bots_name, y_favored, bottom=y_disfavored + y_no_bias, color='b', label='favored')\n",
    "\n",
    "ax.set_title('Most frequently used robot names in robots.txt files. The height of the bar represents the number of times a robot appeared in the dataset')\n",
    "ax.set_xlabel('Bot name')\n",
    "ax.set_ylabel('Number of times appeared')\n",
    "\n",
    "ax.legend()\n",
    "\n",
    "# helper method to auto-label bars\n",
    "ax.bar_label(ax.containers[2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "e58c3bd1",
   "metadata": {},
   "outputs": [],
   "source": [
    "percentage_of_the_count_by_number_of_appearance = nb_of_times_appeared.value_counts().map(lambda v: v/total_number_of_user_agents*100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 359,
   "id": "86b76a19",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Percentage')"
      ]
     },
     "execution_count": 359,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(8,6))\n",
    "sns.scatterplot(x=percentage_of_the_count_by_number_of_appearance.index, y=percentage_of_the_count_by_number_of_appearance.values)\n",
    "\n",
    "ax.set_xlabel('Number of times a robot appears')\n",
    "ax.set_ylabel('Percentage')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "8d40217d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Advanced customization of the boxplot\n",
    "plt.ylim(0, 100)\n",
    "plt.xlim(0, 100)\n",
    "\n",
    "sns.boxplot(x=nb_of_times_appeared.values)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 399,
   "id": "4e8a5691",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count     23613.000000\n",
       "mean        180.467624\n",
       "std        1899.308540\n",
       "min           1.000000\n",
       "25%           1.000000\n",
       "50%           2.000000\n",
       "75%          13.000000\n",
       "max      106347.000000\n",
       "dtype: float64"
      ]
     },
     "execution_count": 399,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nb_of_times_appeared.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 316,
   "id": "e39468c2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2022575\n"
     ]
    }
   ],
   "source": [
    "# Let N be the total number of robots.txt files in the dataset.\n",
    "N = df.shape[0]\n",
    "print(N)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 317,
   "id": "b82ba927",
   "metadata": {},
   "outputs": [],
   "source": [
    "# favorability of a robot is = (#favored - #disfavored)/N\n",
    "favorability_of_robots = (favored_1d_series.value_counts().sub(disfavored_1d_series.value_counts(), fill_value=0)/N).sort_values(ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 314,
   "id": "714529b4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+----------------------+----------+-------------+---------------+-----------------------------------+\n",
      "|       Bot name       | #favored | #disfavored | #favorability | σ: categorical standard deviation |\n",
      "+----------------------+----------+-------------+---------------+-----------------------------------+\n",
      "| Mediapartners-Google |  70470   |     1169    |    0.034264   |              0.000128             |\n",
      "|      Pinterest       |  43759   |      71     |     0.0216    |              0.000102             |\n",
      "|    adsbot-google     |  39463   |      9      |    0.019507   |              9.7e-05              |\n",
      "|      Googlebot       |  51560   |    13022    |    0.019054   |              9.6e-05              |\n",
      "|       bingbot        |  27409   |     4909    |    0.011124   |              7.4e-05              |\n",
      "|   Googlebot-Image    |  17341   |     2463    |    0.007356   |               6e-05               |\n",
      "|      Twitterbot      |  14729   |     532     |    0.007019   |              5.9e-05              |\n",
      "|     Yahoo! Slurp     |  12523   |     374     |    0.006007   |              5.4e-05              |\n",
      "|        msnbot        |  14938   |     2838    |    0.005982   |              5.4e-05              |\n",
      "|        Slurp         |  19369   |    10031    |    0.004617   |              4.8e-05              |\n",
      "+----------------------+----------+-------------+---------------+-----------------------------------+\n"
     ]
    }
   ],
   "source": [
    "table = PrettyTable()\n",
    "\n",
    "table.field_names = ['Bot name', '#favored', '#disfavored', '#favorability', 'σ: categorical standard deviation']\n",
    "\n",
    "for bot,score in favorability_of_robots[:10].items():\n",
    "    N_favored = favored_1d_series.value_counts()[bot]\n",
    "    N_disfavored = disfavored_1d_series.value_counts()[bot]\n",
    "    sigma = np.sqrt(np.abs(score) * (1 - np.abs(score))/N)\n",
    "    table.add_row([bot, N_favored, N_disfavored, round(score, 6), round(sigma, 6)])\n",
    "    \n",
    "print(table)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 315,
   "id": "e8b5af62",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+----------------------+----------+-------------+---------------+-----------------------------------+\n",
      "|       Bot name       | #favored | #disfavored | #favorability | σ: categorical standard deviation |\n",
      "+----------------------+----------+-------------+---------------+-----------------------------------+\n",
      "| AdsBot-Google-Mobile |   2089   |    77385    |   -0.037228   |              0.000133             |\n",
      "|    AdsBot-Google     |   6842   |    77671    |   -0.035019   |              0.000129             |\n",
      "|        Nutch         |   954    |    46170    |   -0.022356   |              0.000104             |\n",
      "|      AhrefsBot       |   5342   |    42518    |   -0.018381   |              9.4e-05              |\n",
      "|      SemrushBot      |   5623   |    36679    |   -0.015355   |              8.6e-05              |\n",
      "|       NerdyBot       |    8     |    21368    |   -0.010561   |              7.2e-05              |\n",
      "|       BLEXBot        |   3676   |    24061    |   -0.010079   |               7e-05               |\n",
      "|        dotbot        |   1356   |    18272    |   -0.008364   |              6.4e-05              |\n",
      "|      WebCopier       |   210    |    13438    |    -0.00654   |              5.7e-05              |\n",
      "|        psbot         |   1396   |    14602    |   -0.006529   |              5.7e-05              |\n",
      "+----------------------+----------+-------------+---------------+-----------------------------------+\n"
     ]
    }
   ],
   "source": [
    "table = PrettyTable()\n",
    "\n",
    "table.field_names = ['Bot name', '#favored', '#disfavored', '#favorability', 'σ: categorical standard deviation']\n",
    "\n",
    "for bot,score in favorability_of_robots[-1:-11:-1].items():\n",
    "    N_favored = favored_1d_series.value_counts()[bot]\n",
    "    N_disfavored = disfavored_1d_series.value_counts()[bot]\n",
    "    sigma = np.sqrt(np.abs(score) * (1 - np.abs(score))/N)\n",
    "    table.add_row([bot, N_favored, N_disfavored, round(score, 6), round(sigma, 6)])\n",
    "    \n",
    "print(table)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 411,
   "id": "511c7a59",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['tld'] = df.apply(lambda row: urlparse(row['robotstxt_url']).netloc.split('.')[-1], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 416,
   "id": "83b27a7e",
   "metadata": {},
   "outputs": [],
   "source": [
    "tld_stats_series = df.groupby('tld').size().sort_values(ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 439,
   "id": "84810339",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x864 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Pie chart, where the slices will be ordered and plotted counter-clockwise:\n",
    "labels = tld_stats_series.index[:10]\n",
    "sizes = tld_stats_series.values[:10]\n",
    "explode = (0, 0.2, 0, 0, 0, 0, 0, 0, 0, 0)  # only \"explode\" the 2nd slice (i.e. 'Hogs')\n",
    "\n",
    "fig1, ax1 = plt.subplots(figsize=(12, 12))\n",
    "\n",
    "ax1.pie(sizes, explode=explode, labels=labels, autopct='%1.1f%%',\n",
    "        shadow=True, startangle=90)\n",
    "ax1.axis('equal')  # Equal aspect ratio ensures that pie is drawn as a circle.\n",
    "\n",
    "ax1.set_title(f'TLD distribution in the dataset of {N} unique website')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 436,
   "id": "8836d48a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tld\n",
       "bg:2096     1\n",
       "220         1\n",
       "bg:8474     1\n",
       "kr:447      1\n",
       "de:9050     1\n",
       "de:9000     1\n",
       "kr:4447     1\n",
       "kr:44466    1\n",
       "de:8080     1\n",
       "de:8006     1\n",
       "care:443    1\n",
       "dtype: int64"
      ]
     },
     "execution_count": 436,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tld_stats_series[-11:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 481,
   "id": "652412ad",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_cn = df[df['tld'] == 'cn']\n",
    "df_ru = df[df['tld'] == 'ru']\n",
    "df_de = df[df['tld'] == 'de']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "98c2701e",
   "metadata": {},
   "source": [
    "## Analysing Chinese domains"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 453,
   "id": "c9bc2f5f",
   "metadata": {},
   "outputs": [],
   "source": [
    "disfavored_1d_series, no_bias_1d_series, favored_1d_series, nb_of_times_appeared, top_10_appeared_bots_name, y_disfavored, y_no_bias, y_favored, total_number_of_user_agents, N = get_metrics(df_cn)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 454,
   "id": "749eac3e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_most_frequently_appeared_bots(top_10_appeared_bots_name, y_disfavored, y_no_bias, y_favored)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 458,
   "id": "91b64daa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_number_of_time_bot_appears_distribution(nb_of_times_appeared, total_number_of_user_agents)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 459,
   "id": "2c65656a",
   "metadata": {},
   "outputs": [],
   "source": [
    "favorability_of_robots = get_bots_favorability(favored_1d_series, disfavored_1d_series, N)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 462,
   "id": "944c627e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Baiduspider           0.004668\n",
       "360Spider             0.001984\n",
       "Sogou blog            0.001605\n",
       "Baiduspider-image     0.001167\n",
       "Twitterbot            0.000992\n",
       "HaosouSpider          0.000875\n",
       "Baiduspider-news      0.000846\n",
       "Googlebot-Image       0.000817\n",
       "Baiduspider-mobile    0.000817\n",
       "Googlebot-Mobile      0.000788\n",
       "dtype: float64"
      ]
     },
     "execution_count": 462,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "favorability_of_robots[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 467,
   "id": "a1b4bbb6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+--------------------+----------+-------------+---------------+-----------------------------------+\n",
      "|      Bot name      | #favored | #disfavored | #favorability | σ: categorical standard deviation |\n",
      "+--------------------+----------+-------------+---------------+-----------------------------------+\n",
      "|    Baiduspider     |   185    |      25     |    0.004668   |              0.000368             |\n",
      "|     360Spider      |    76    |      8      |    0.001984   |              0.00024              |\n",
      "|     Sogou blog     |    59    |      4      |    0.001605   |              0.000216             |\n",
      "| Baiduspider-image  |    46    |      6      |    0.001167   |              0.000184             |\n",
      "|     Twitterbot     |    35    |      1      |    0.000992   |              0.00017              |\n",
      "|    HaosouSpider    |    30    |      0      |    0.000875   |              0.00016              |\n",
      "|  Baiduspider-news  |    30    |      1      |    0.000846   |              0.000157             |\n",
      "|  Googlebot-Image   |    31    |      3      |    0.000817   |              0.000154             |\n",
      "| Baiduspider-mobile |    28    |      0      |    0.000817   |              0.000154             |\n",
      "|  Googlebot-Mobile  |    28    |      1      |    0.000788   |              0.000152             |\n",
      "+--------------------+----------+-------------+---------------+-----------------------------------+\n"
     ]
    }
   ],
   "source": [
    "draw_favorability_table(favorability_of_robots, favored_1d_series, disfavored_1d_series, f=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 468,
   "id": "7e5db62a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+------------+----------+-------------+---------------+-----------------------------------+\n",
      "|  Bot name  | #favored | #disfavored | #favorability | σ: categorical standard deviation |\n",
      "+------------+----------+-------------+---------------+-----------------------------------+\n",
      "| Googlebot  |   122    |     910     |   -0.022991   |              0.00081              |\n",
      "|  MJ12bot   |    8     |     784     |    -0.02264   |              0.000803             |\n",
      "| AhrefsBot  |    5     |     744     |   -0.021561   |              0.000785             |\n",
      "|   Slurp    |    41    |     719     |   -0.019781   |              0.000752             |\n",
      "|   DotBot   |    4     |     618     |   -0.017914   |              0.000716             |\n",
      "| YandexBot  |    4     |     612     |   -0.017739   |              0.000713             |\n",
      "|  BLEXBot   |    4     |     586     |    -0.01698   |              0.000698             |\n",
      "|  bingbot   |    46    |     613     |   -0.016543   |              0.000689             |\n",
      "| SemrushBot |    5     |     569     |   -0.016455   |              0.000687             |\n",
      "| Bytespider |    41    |     603     |   -0.016397   |              0.000686             |\n",
      "+------------+----------+-------------+---------------+-----------------------------------+\n"
     ]
    }
   ],
   "source": [
    "draw_favorability_table(favorability_of_robots, favored_1d_series, disfavored_1d_series, f=-1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8625345e",
   "metadata": {},
   "source": [
    "## Analysing Russian domains"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 472,
   "id": "1b7058a4",
   "metadata": {},
   "outputs": [],
   "source": [
    "disfavored_1d_series, no_bias_1d_series, favored_1d_series, nb_of_times_appeared, top_10_appeared_bots_name, y_disfavored, y_no_bias, y_favored, total_number_of_user_agents, N = get_metrics(df_ru)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 473,
   "id": "bf4408ef",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_most_frequently_appeared_bots(top_10_appeared_bots_name, y_disfavored, y_no_bias, y_favored)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 474,
   "id": "8204c314",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAfYAAAFzCAYAAADMlivXAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjQuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/MnkTPAAAACXBIWXMAAAsTAAALEwEAmpwYAAAkZElEQVR4nO3dfZgedX3v8fd3N5vnBx6yhJSA4SGWIz5EXDlwrD0I1SLVitai6Kl46jnRthYstT7UXorXZXu0rfhQWz1REOyhKlVRihbNoYj1tIILxkBEBWNA0pAECCQkbJLd/Z4/ZjbcCbvJ7rJz72bm/bqu+9q5f/fMPb/fzCafnZnfzC8yE0mSVA8dk10BSZI0cQx2SZJqxGCXJKlGDHZJkmrEYJckqUYMdkmSamTaZFdgNBYuXJhLly6d7GpIktQWt91224OZ2T2eZQ+JYF+6dCm9vb2TXQ1JktoiIu4d77KeipckqUYMdkmSasRglySpRgx2SZJqxGCXJKlGKg/2iOiMiB9ExPXl++Mj4paIuCcivhgR06uugyRJTdGOI/aLgbta3n8I+EhmngRsBd7UhjpIktQIlQZ7RCwBfgP4TPk+gLOAL5WzXAWcV2UdJElqkqqP2D8KvAMYLN8fCTySmf3l+/uBYyqugyRJjVFZsEfEy4DNmXnbOJdfERG9EdG7ZcuWCanT4GCybstj/PvPHmTdlscYHMwJ+V5JkqaKKh8p+wLgNyPiXGAmMB/4GHBYREwrj9qXABuGWzgzVwIrAXp6ep5yAg8OJjesfYBLrllN355BZnZ1cNn5yznnlKPp6Iin+vWSJE0JlR2xZ+a7M3NJZi4FXgv8S2a+HrgJeHU524XA16qqQ6v1D+3YG+oAfXsGueSa1ax/aEc7Vi9JUltMxn3s7wQuiYh7KK65X96OlW7a1rc31If07Rlk8/a+dqxekqS2aMvobpn5beDb5fQ64LR2rLfVovkzmdnVsU+4z+zq4Kh5M9tdFUmSKtOYJ88tPXIOl52/nJldRZOHrrEvPXLOJNdMkqSJc0iMxz4ROjqCc045mpMveiGbt/dx1LyZLD1yjh3nJEm10phghyLcT+ieywndcye7KpIkVaIxp+IlSWoCg12SpBox2CVJqhGDXZKkGjHYJUmqEYNdkqQaMdglSaoRg12SpBox2CVJqhGDXZKkGjHYJUmqEYNdkqQaMdglSaoRg12SpBox2CVJqhGDXZKkGjHYJUmqEYNdkqQaMdglSaoRg12SpBox2CVJqhGDXZKkGjHYJUmqEYNdkqQaMdglSaoRg12SpBqpLNgjYmZE3BoRP4yItRHx/rL8yoj4eUSsLl/Lq6qDJElNM63C794FnJWZj0VEF/DdiPjn8rM/ycwvVbhuSZIaqbJgz8wEHivfdpWvrGp9kiSp4mvsEdEZEauBzcCqzLyl/OjPI2JNRHwkImaMsOyKiOiNiN4tW7ZUWU1Jkmqj0mDPzIHMXA4sAU6LiGcC7wZOBp4PHAG8c4RlV2ZmT2b2dHd3V1lNSZJqoy294jPzEeAm4JzM3JiFXcBngdPaUQdJkpqgyl7x3RFxWDk9C3gx8OOIWFyWBXAecGdVdZAkqWmq7BW/GLgqIjop/oC4JjOvj4h/iYhuIIDVwFsqrIMkSY1SZa/4NcBzhyk/q6p1SpLUdD55TpKkGjHYJUmqEYNdkqQaMdglSaoRg12SpBox2CVJqhGDXZKkGjHYJUmqEYNdkqQaMdglSaoRg12SpBox2CVJqhGDXZKkGjHYJUmqEYNdkqQaMdglSaoRg12SpBox2CVJqhGDXZKkGjHYJUmqEYNdkqQaMdglSaoRg12SpBox2CVJqhGDXZKkGjHYJUmqEYNdkqQaMdglSaqRyoI9ImZGxK0R8cOIWBsR7y/Lj4+IWyLinoj4YkRMr6oOkiQ1TZVH7LuAszLzOcBy4JyIOB34EPCRzDwJ2Aq8qcI6SJLUKJUFexYeK992la8EzgK+VJZfBZxXVR0kSWqaSq+xR0RnRKwGNgOrgJ8Bj2RmfznL/cAxVdZBkqQmqTTYM3MgM5cDS4DTgJNHu2xErIiI3ojo3bJlS1VVlCSpVtrSKz4zHwFuAs4ADouIaeVHS4ANIyyzMjN7MrOnu7u7HdWUJOmQV2Wv+O6IOKycngW8GLiLIuBfXc52IfC1quogSVLTTDv4LOO2GLgqIjop/oC4JjOvj4gfAV+IiA8APwAur7AOkiQ1SmXBnplrgOcOU76O4nq7JEmaYD55TpKkGjHYJUmqEYNdkqQaMdglSaoRg12SpBox2CVJqhGDXZKkGjHYJUmqEYNdkqQaMdglSaoRg12SpBox2CVJqhGDXZKkGjHYJUmqEYNdkqQaMdglSaoRg12SpBox2CVJqhGDXZKkGjHYJUmqEYNdkqQaMdglSaoRg12SpBox2CVJqhGDXZKkGjHYJUmqEYNdkqQaMdglSaoRg12SpBqpLNgj4tiIuCkifhQRayPi4rL80ojYEBGry9e5VdVBkqSmmVbhd/cDf5yZt0fEPOC2iFhVfvaRzPzrCtctSVIjVRbsmbkR2FhOb4+Iu4BjqlqfJElq0zX2iFgKPBe4pSx6a0SsiYgrIuLwEZZZERG9EdG7ZcuWdlRTkqRDXuXBHhFzgS8Db8vMbcAngROB5RRH9B8ebrnMXJmZPZnZ093dXXU1JUmqhUqDPSK6KEL96sz8CkBmbsrMgcwcBD4NnFZlHSRJapIqe8UHcDlwV2Ze1lK+uGW2VwJ3VlUHSZKapspe8S8Afge4IyJWl2V/ClwQEcuBBNYDb66wDpIkNUqVveK/C8QwH32jqnVKktR0PnlOkqQaMdglSaoRg12SpBox2CVJqhGDXZKkGjHYJUmqEYNdkqQaMdglSaqRUQV7FP5bRLy3fH9cRPiMd0mSppjRHrH/HXAGcEH5fjvwt5XUSJIkjdtoHyn7nzPz1Ij4AUBmbo2I6RXWS5IkjcNoj9j3REQnxcAtREQ3MFhZrSRJ0riMNtg/DlwLHBURfw58F/iLymolSZLGZVSn4jPz6oi4DTibYsS28zLzrkprJkmSxmxUwR4RRwCbgc+3lHVl5p6qKiZJksZutKfibwe2AD8F7i6n10fE7RHxvKoqJ0mSxma0wb4KODczF2bmkcBLgeuB36e4FU6SJE0Bow320zPzm0NvMvNbwBmZ+T1gRiU1kyRJYzba+9g3RsQ7gS+U718DbCpvgfO2N0mSpojRHrG/DlgCfLV8HVeWdQLnV1ExSZI0dqO93e1B4A9H+PieiauOJEl6KkZ7u1s38A7gFGDmUHlmnlVRvSRJ0jiM9lT81cCPgeOB9wPrge9XVCdJkjROow32IzPzcmBPZt6cmb8LeLQuSdIUM9pe8UNPmNsYEb8B/AdwRDVVkiRJ4zXaYP9ARCwA/hj4G2A+8LaqKiVJksZntMG+NTMfBR4FXgQQES+orFaSJGlcRnuN/W9GWSZJkibRAY/YI+IM4L8A3RFxSctH8ykeTiNJkqaQgx2xTwfmUvwBMK/ltQ149YEWjIhjI+KmiPhRRKyNiIvL8iMiYlVE3F3+PPypN0OSJMFBjtgz82bg5oi4MjPvHeN39wN/nJm3R8Q84LaIWAW8EbgxMz8YEe8C3gW8cxx1lyRJ+xlt57kZEbESWNq6zIGePJeZG4GN5fT2iLgLOAZ4BXBmOdtVwLcx2CVJmhCjDfZ/BD4FfAYYGOtKImIp8FzgFmBRGfoADwCLRlhmBbAC4LjjjhvrKiVJaqTRBnt/Zn5yPCuIiLnAl4G3Zea2iNj7WWZmRORwy2XmSmAlQE9Pz7DzSJKkfY32drd/iojfj4jFZee3IyLioE+ei4guilC/OjO/UhZviojF5eeLgc3jqrkkSXqS0R6xX1j+/JOWsgROGGmBKA7NLwfuyszLWj66rvy+D5Y/vzbq2kqSpAMa7Xjsx4/ju18A/A5wR0SsLsv+lCLQr4mINwH3AueP47slSdIwRjse+2zgEuC4zFwREcuAX87M60daJjO/C8QIH5895ppKkqSDGu019s8CuymeQgewAfhAJTWSJEnjNtpgPzEz/5Jy+NbM3MnIR+OSJGmSjDbYd0fELIoOc0TEicCuymolSZLGZbS94t8H3AAcGxFXU3SMe2NVlZIkSeMz2l7xqyLiduB0ilPwF2fmg5XWTJIkjdmoTsVHxCspnj739bInfH9EnFdpzSRJ0piN9hr7+zLz0aE3mfkIxel5SZI0hYw22Iebb7TX5yVJUpuMNth7I+KyiDixfF0G3FZlxSRJ0tiNNtj/kOIBNV8EvgD0AX9QVaUkSdL4HPR0ekR0Atdn5ovaUB9JkvQUHPSIPTMHgMGIWNCG+kiSpKdgtB3gHqMYpW0VsGOoMDMvqqRWkiRpXEYb7F8pX5IkaQob7ZPnriqfFX9cZv6k4jpJkqRxGu2T514OrKZ4XjwRsTwirquwXpIkaRxGe7vbpcBpwCMAmbkaOKGSGkmSpHEbbbDvaX2kbGlwoisjSZKemtF2nlsbEa8DOiNiGXAR8G/VVUuSJI3HWJ48dwqwC/gH4FHgbRXVSZIkjdMBj9gjYibwFuAk4A7gjMzsb0fFJEnS2B3siP0qoIci1F8K/HXlNZIkSeN2sGvsz8jMZwFExOXArdVXSZIkjdfBjtj3DE14Cl6SpKnvYEfsz4mIbeV0ALPK9wFkZs6vtHaSJGlMDhjsmdnZropIkqSnbrS3u0mSpEOAwS5JUo1UFuwRcUVEbI6IO1vKLo2IDRGxunydW9X6JUlqoiqP2K8Ezhmm/COZubx8faPC9UuS1DiVBXtmfgd4uKrvlyRJTzYZ19jfGhFrylP1h0/C+iVJqq12B/sngROB5cBG4MMjzRgRKyKiNyJ6t2zZ0qbqSZJ0aGtrsGfmpswcyMxB4NPAaQeYd2Vm9mRmT3d3d/sqKUnSIaytwR4Ri1vevhK4c6R5JUnS2B3skbLjFhGfB84EFkbE/cD7gDMjYjmQwHrgzVWtX5KkJqos2DPzgmGKL69qfZIkySfPSZJUKwa7JEk1YrBLklQjBrskSTVisEuSVCMGuyRJNWKwS5JUIwa7JEk1YrBLklQjBrskSTVisEuSVCMGuyRJNWKwS5JUIwa7JEk1YrBLklQjBrskSTVisEuSVCMGuyRJNWKwS5JUIwa7JEk1YrBLklQjBrskSTVisEuSVCMGuyRJNWKwS5JUIwa7JEk1YrBLklQjBrskSTVisEuSVCOVBXtEXBERmyPizpayIyJiVUTcXf48vKr1S5LURFUesV8JnLNf2buAGzNzGXBj+V6SJE2QyoI9M78DPLxf8SuAq8rpq4Dzqlq/JElN1O5r7Isyc2M5/QCwaKQZI2JFRPRGRO+WLVvaUztJkg5xk9Z5LjMTyAN8vjIzezKzp7u7u401kyTp0NXuYN8UEYsByp+b27x+SZJqrd3Bfh1wYTl9IfC1Nq9fkqRam1bVF0fE54EzgYURcT/wPuCDwDUR8SbgXuD8qtY/nMHBZP1DO9i0rY9F82ey9Mg5dHREO6sgSVKlKgv2zLxghI/OrmqdBzI4mNyw9gEuuWY1fXsGmdnVwWXnL+ecU4423CVJtdGYJ8+tf2jH3lAH6NszyCXXrGb9QzsmuWaSJE2cxgT7pm19e0N9SN+eQTZv75ukGkmSNPEaE+yL5s9kZte+zZ3Z1cFR82ZOUo0kSZp4jQn2pUfO4bLzl+8N96Fr7EuPnDPJNZMkaeJU1nluqunoCF7ynxbxxRWns/HRPhYvmMUpi+fbcU6SVCuNCfbBweRbd22yV7wkqdYacyreXvGSpCZoTLDbK16S1ASNCXZ7xUuSmqAxwW6veElSEzSm81xHR3DOKUdz8kUvZPP2Po6a57PiJUn105hghyLcT+ieywndcye7KpIkVaIxp+IlSWoCg12SpBox2CVJqhGDXZKkGjHYJUmqEYNdkqQaMdglSaqRRt3HDsUob+sf2sGmbX0smu9DaiRJ9dKoYB8cTG5Y+4BDt0qSaqtRp+IdulWSVHeNCnaHbpUk1V2jgt2hWyVJddeoa+xLj5zDJ173XNbc/yiDCZ0Bz1qywKFbJUm10ahgB9jdn6z8zrp9Os9JklQXjToVb+c5SVLdNSrY7TwnSaq7STkVHxHrge3AANCfmT3tWO9Q57nWcLfznCSpTibziP1Fmbm8XaEORee5y85fvrdn/NA1djvPSZLqolGd5zo6gnNOOZqTL3ohm7f3cdQ8HykrSaqXyQr2BL4VEQn878xc2a4Vd3QEJ3TP5YTuue1apSRJbTNZwf4rmbkhIo4CVkXEjzPzO60zRMQKYAXAcccdNyErdQAYSVLdTUqwZ+aG8ufmiLgWOA34zn7zrARWAvT09ORTXacDwEiSmqDtneciYk5EzBuaBl4C3Fn1er2HXZLUBJPRK34R8N2I+CFwK/D1zLyh6pV6D7skqQnafio+M9cBz2n3er2HXZLUBI158pz3sEuSmqAx97F7D7skqQkaE+zgPeySpPprVLB7H7skqe4aE+zexy5JaoLGdJ7zPnZJUhM0Jti9j12S1ASNCfah+9hbeR+7JKluGhPs3scuSWqCxnSe8z52SVITNCbYwfvYJUn115hT8ZIkNYHBLklSjTTqVLxPnpMk1V1jgt0nz0mSmqAxp+J98pwkqQkaE+w+eU6S1ASNCXafPCdJaoLGBLtPnpMkNUFjOs/55DlJUhM0JtjBJ89JkuqvUcEO3ssuSaq3RgW797JLkuquMZ3nAO57eAc/fmAb/+OFJ/DWs07i8NnTvZddklQrjQn2wcFk7X9sY1ZXJ8ceNouTj57HB847hacfNdd72SVJtdGYYL/v4R1seORxbrzrAWbNmMaOXf1Mn9bJW88+iaPney+7JKkeGnONfdO2XfSuf5D3vvwZ9O1ONm1Ppk/roKuzc7KrJknShGlMsO8eGOAPXnQiHdHBQPYTBB3A/Nld7OrvZ3Aw+cXWHWx6dBcP7tjFMYfN5pTF85k2rTEnNSRJNdCY1Fo4Zzqbt/czbxZ0dgQJENC3G36xtY/b73uYR3fuYdfAIEGwq3+A237xIP39gwf7akmSpoxJOWKPiHOAjwGdwGcy84NVr3N73wAnL57JvQ/uYuHc6Rw5ZzaP74H+gUEGBpKduwfomBEcPb+LnTOncfjsYOeeTnrve5gABhMe6+tn3qwu5s7oZOvO3Uzv7OSoeTOIgI2PFk+z6+wop+fO4PH+Ae7f+jiLF8zilMXz6eiIvffQL14wk4FB2Lx9+PvpBweTnz+4g3sf3sGc6dNYNH8GSw6bzX1bdw57D37r/fmt9RiaD/D+/UnisxOk+pqK/77bHuwR0Qn8LfBi4H7g+xFxXWb+qMr1PrhjF/NmzmbHrkFmde1hW98gj+zs593X3rH3nvaLz17GMYfN5JcOm8FdG/ewdOEs7t+6k4d37OGyVT/dZ77ZXZ1c8W8/57XPP4450zv55M3r2LpzNxefvYzP/fu9T5r+wHnPpHvedN7897dz+OzpvOGMp/GxG+8e9n764e63v/jsZSw5fBZ//a2fcO9Dj++zDDDs/EPrvuz85UyfFrz1H37g/ftt5rMTpPqaqv++J+NU/GnAPZm5LjN3A18AXlH1So85bDbb+gZYu3EbA4OddHZ07A11KIZw/diNd3PPlh0MDnawZwAe3TnIzGnT9oZ663wP7dzNy559DB+78W4e3LGbV526ZO9nw03/2VfvZPvjA/TtGeRVpy7ZG+pD39l6P/1wY8d/7Ma7uXvzY7zs2cc8aZmR5h9a9yXXrGbN/Y86Fv0kGG7fuO2lepiq/74nI9iPAX7R8v7+smwfEbEiInojonfLli1PeaWnLJ7P5u27GEzYtL2Ph3fsGXZ89qHPd+zu3/tzpPki9p0e+myk6R27+8u2ccCx4UcaO751Pa3LjDR/67oHkyd97v371Rtp37jtpUPfVP33PWU7z2Xmyszsycye7u7up/x906Z1cPT8GXRGMTb7EXO6hh2fvSNg0byZxXXt8udI82XuOz302UjTc6ZP2+c79v/OobHhRxo7vnU9rcuMNH/ruvc/K+RY9O0x0r5x20uHvqn673sygn0DcGzL+yVlWeWetXgBz1g8n84YYGBwkP/1ymftMz77xWcv46TuOXR0DNLVCQtmd9DX388lL376k+Y7cvZ0rl+zgYvPXsbCOdP5yu337/1suOkPnPdM5s3qZGZXB1++7X4uPnvZiGPDDzd2/MVnL2PZUXO5fs2GJy0z0vxD677s/OU8e8kCx6KfBMPtG7e9VA9T9d93ZObB55rIFUZMA34KnE0R6N8HXpeZa0dapqenJ3t7eydk/X19/azfup2uztjbK37ztt3MmN7BvOnTmDerg527ksPmFJ8/srN/n17x82d1MWd6J488vpuull7xD2zro3tu0Rv9gW19LJwzg77+ATZsfZyjF8zklMUL9vaK37y9j6PnF73itzw2/NjwQ73i73t4B7P36xU/3HjyQz0zN2/ftx5D8wF7P3cs+vZq3Tdue6leqvr3HRG3ZWbPuJZtd7ADRMS5wEcpbne7IjP//EDzT2SwS5I01T2VYJ+U+9gz8xvANyZj3ZIk1dmU7TwnSZLGzmCXJKlGDHZJkmrEYJckqUYMdkmSasRglySpRgx2SZJqxGCXJKlGDHZJkmpkUh4pO1YRsQW4dwK/ciHw4AR+31Rne+utSe1tUlvB9tbdgdr7tMwc19Cmh0SwT7SI6B3vM3gPRba33prU3ia1FWxv3VXVXk/FS5JUIwa7JEk10tRgXznZFWgz21tvTWpvk9oKtrfuKmlvI6+xS5JUV009YpckqZYaF+wRcU5E/CQi7omId012fcYjIo6NiJsi4kcRsTYiLi7LL42IDRGxunyd27LMu8s2/yQifr2l/JDYHhGxPiLuKNvVW5YdERGrIuLu8ufhZXlExMfLNq2JiFNbvufCcv67I+LCyWrPgUTEL7fsw9URsS0i3lan/RsRV0TE5oi4s6VswvZnRDyv/H25p1w22tvCJ4zQ1r+KiB+X7bk2Ig4ry5dGxOMt+/hTLcsM26aRtttkGaG9E/a7GxHHR8QtZfkXI2J6+1r3ZCO094stbV0fEavL8vbs38xszAvoBH4GnABMB34IPGOy6zWOdiwGTi2n5wE/BZ4BXAq8fZj5n1G2dQZwfLkNOg+l7QGsBxbuV/aXwLvK6XcBHyqnzwX+GQjgdOCWsvwIYF358/By+vDJbttB2t0JPAA8rU77F/hV4FTgzir2J3BrOW+Uy750irX1JcC0cvpDLW1d2jrfft8zbJtG2m5TrL0T9rsLXAO8tpz+FPB7U629+33+YeC97dy/TTtiPw24JzPXZeZu4AvAKya5TmOWmRsz8/ZyejtwF3DMARZ5BfCFzNyVmT8H7qHYFof69ngFcFU5fRVwXkv557LwPeCwiFgM/DqwKjMfzsytwCrgnDbXeazOBn6WmQd6QNMht38z8zvAw/sVT8j+LD+bn5nfy+J/w8+1fFfbDdfWzPxWZvaXb78HLDnQdxykTSNtt0kxwr4dyZh+d8uj2LOAL5XLT+n2lvU9H/j8gb5jovdv04L9GOAXLe/v58CBOOVFxFLgucAtZdFby9N7V7Scshmp3YfS9kjgWxFxW0SsKMsWZebGcvoBYFE5XYf2Dnkt+/6nUNf9CxO3P48pp/cvn6p+l+IIbcjxEfGDiLg5Il5Ylh2oTSNtt6lmIn53jwQeafmjaKrv2xcCmzLz7payyvdv04K9ViJiLvBl4G2ZuQ34JHAisBzYSHEKqC5+JTNPBV4K/EFE/Grrh+VfubW6xaO8dvibwD+WRXXev/uo4/4cTkS8B+gHri6LNgLHZeZzgUuAf4iI+aP9vim83Rrzu7ufC9j3D/O27N+mBfsG4NiW90vKskNORHRRhPrVmfkVgMzclJkDmTkIfJridBaM3O5DZntk5oby52bgWoq2bSpPYQ2dytpczn7It7f0UuD2zNwE9d6/pYnanxvY99T2lGx3RLwReBnw+vI/bMpT0g+V07dRXGd+Ogdu00jbbcqYwN/dhyguxUzbr3zKKev4KuCLQ2Xt2r9NC/bvA8vKXpXTKU5zXjfJdRqz8rrN5cBdmXlZS/niltleCQz10rwOeG1EzIiI44FlFB01DontERFzImLe0DRFx6M7Keo61BP6QuBr5fR1wBuicDrwaHkq65vASyLi8PJU4EvKsqlqn7/267p/W0zI/iw/2xYRp5f/Vt7Q8l1TQkScA7wD+M3M3NlS3h0RneX0CRT7ct1B2jTSdpsyJup3t/wD6Cbg1eXyU7K9pV8DfpyZe0+xt23/jqX3Xx1eFD1sf0rxl9J7Jrs+42zDr1CcjlkDrC5f5wJ/D9xRll8HLG5Z5j1lm39CSw/hQ2F7UPSM/WH5WjtUT4rrbTcCdwP/FziiLA/gb8s23QH0tHzX71J00LkH+O+T3bYDtHkOxdHJgpay2uxfij9YNgJ7KK4nvmki9yfQQxEePwM+QfkwrinU1nsoriEP/fv9VDnvb5W/46uB24GXH6xNI223KdbeCfvdLf8/uLXchv8IzJhq7S3LrwTest+8bdm/PnlOkqQaadqpeEmSas1glySpRgx2SZJqxGCXJKlGDHZJkmrEYFctRURGxIdb3r89Ii6doO++MiJeffA5n/J6fjsi7oqIm/YrXxoRr2t53xMRH6+6PhMtIs6MiOvHuMyfVlUfqS4MdtXVLuBVEbFwsivSquWJWaPxJuB/ZuaL9itfCuwN9szszcyLJqB6E658qMxE/j8zpYO9gvZKY+YvoOqqH1gJ/NH+H+x/xB0Rj5U/zywHZvhaRKyLiA9GxOsj4tYoxkk+seVrfi0ieiPipxHxsnL5zijG2f5+FINdvLnle/81Iq4DfjRMfS4ov//OiPhQWfZeigcRXR4Rf7XfIh8EXhjFeM5/1HrkG8W411eV67s3Il4VEX9Zfv8NUTyKeGjs55ujGFTnm/HEIysviogflfX/wjB1XVp+9+3l67+MMM9PIuJzFA/cOLbcLneW9XhNy+zzI+Lr5fyfGgrFEbbJB4FZZbuvHma9nyz3ydqIeH9L+fqWbXBrRJzU8nvwqTHsx7kRcWPZ7jsi4hUHaO+VLe190u+gVKnJfGKPL19VvYDHgPkU47gvAN4OXFp+diXw6tZ5y59nAo9QjHc/g+JZze8vP7sY+GjL8jdQ/GG8jOJpUzOBFcCflfPMAHopxpg+E9gBHD9MPX8JuA/oBqYB/wKcV372bVqestayzJnA9cO9pxj3+rtAF/AcYCdPjOt8LcWQj13AvwHdZflrgCvK6f+gfJIXcNgw654NzCynlwG9w8yzFBgETi/f/xbFkKqdFCNT3Vdu4zOBPooniXWW87z6INvksQPs86En1XWW2+7Z5fv1PPG0wje0bKux7sdpFENrAiykePJZDNPe51EMJ8tI29GXrypfYzktKB1SMnNbeRR1EfD4KBf7fpZDJEbEz4BvleV3AK2nxK/JYkCLuyNiHXAyxbPKn91yNmABRWDsBm7NYrzp/T0f+HZmbinXeTXwq8BXR1nf4fxzZu6JiDsoQu6GljYsBX4ZeCawKiIo5xkaFnINcHVEfHWEOnQBn4iI5cAAxQAWw7k3i7HToTjz8PnMHKAY0OJminZvo9gu6wAi4vPlvHsY3zY5P4ohfadR/OHwjLI98MQz9z8PfKRlmbHsx/uBv4hiZMFBimE1h4bQbG3vOuCEiPgb4Os88TsktYXBrrr7KMUzmT/bUtZPeRmqPPU7veWzXS3Tgy3vB9n338v+z2JOiqO3P8zMfQaWiYgzKY7Y22UXQGYORsSezByq61AbAlibmWcMs+xvUIToy4H3RMSz8omxr6G4tLGJ4mxAB8UR93BG297htuOYRTGAyNuB52fm1oi4kuLoe7jvHWl66P1I+/GNFGcRnlf+4bS+ZR1721uu/znArwNvAc6neKa91BZeY1etZebDwDUUHdGGrKc4XQrFeOdd4/jq346IjvK6+wkUA1h8E/i9luvYT49iNLoDuRX4rxGxMIpRny4Abj7IMtuBeeOo85CfAN0RcUZZz66IOKX8I+fYzLwJeCfFkerc/ZZdAGwsj3J/h+Jo/2D+FXhNee26m+IPh1vLz06LYgSvDopLAt/lwNtkz9D23c98inB9NCIWUQx52+o1LT//vaV8LPtxAbC5DPUXAU8brrFRdNjsyMwvA38GnHrQLSRNII/Y1QQfBt7a8v7TwNci4ocUp6nHczR9H0UAzacYwakvIj5Dcar79ijOcW+huKY9oszcGBHvohiKMoCvZ+bBhmVcAwyU9b8S+MFYKp6Zu8vTzB+PiAUU/w98lGIkrf9TlgXw8cx8ZL/F/w74ckS8gdFvu2uBMyhG50vgHZn5QEScTDE85yeAkyi2wbXlmYaRtslKYE1E3J6Zr29p0w8j4gfAjylGTft/+9Xh8IhYQ3E244KW8rHsx6uBfyovcfSW6xrOMcBn44ne8e8exTaSJoyju0mqtfKUeU9mPrhf+ZUUHem+NBn1kqriqXhJkmrEI3ZJkmrEI3ZJkmrEYJckqUYMdkmSasRglySpRgx2SZJqxGCXJKlG/j9O2Xk6yHW2qwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_number_of_time_bot_appears_distribution(nb_of_times_appeared, total_number_of_user_agents)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 476,
   "id": "831251c6",
   "metadata": {},
   "outputs": [],
   "source": [
    "favorability_of_robots = get_bots_favorability(favored_1d_series, disfavored_1d_series, N)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 478,
   "id": "dbb3bd64",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Yandex                  0.036116\n",
       "Googlebot-Image         0.029292\n",
       "Googlebot               0.028009\n",
       "Mediapartners-Google    0.027645\n",
       "YandexImages            0.026489\n",
       "msnbot                  0.017448\n",
       "YaDirectBot             0.013648\n",
       "YandexDirect            0.007822\n",
       "GoogleBot               0.007822\n",
       "YadirectBot             0.005130\n",
       "dtype: float64"
      ]
     },
     "execution_count": 478,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "favorability_of_robots[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 479,
   "id": "681bd4c1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+----------------------+----------+-------------+---------------+-----------------------------------+\n",
      "|       Bot name       | #favored | #disfavored | #favorability | σ: categorical standard deviation |\n",
      "+----------------------+----------+-------------+---------------+-----------------------------------+\n",
      "|        Yandex        |   4161   |     1880    |    0.036116   |              0.000742             |\n",
      "|   Googlebot-Image    |   1902   |      52     |    0.029292   |              0.000671             |\n",
      "|      Googlebot       |   2459   |     690     |    0.028009   |              0.000657             |\n",
      "| Mediapartners-Google |   1768   |      22     |    0.027645   |              0.000652             |\n",
      "|     YandexImages     |   1713   |      40     |    0.026489   |              0.000639             |\n",
      "|        msnbot        |   1255   |     153     |    0.017448   |              0.000521             |\n",
      "|     YaDirectBot      |   868    |      6      |    0.013648   |              0.000462             |\n",
      "|     YandexDirect     |   520    |      26     |    0.007822   |              0.000351             |\n",
      "|      GoogleBot       |   553    |      59     |    0.007822   |              0.000351             |\n",
      "|     YadirectBot      |   328    |      4      |    0.00513    |              0.000284             |\n",
      "+----------------------+----------+-------------+---------------+-----------------------------------+\n"
     ]
    }
   ],
   "source": [
    "draw_favorability_table(favorability_of_robots, favored_1d_series, disfavored_1d_series, f=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 480,
   "id": "f9faeead",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+------------------+----------+-------------+---------------+-----------------------------------+\n",
      "|     Bot name     | #favored | #disfavored | #favorability | σ: categorical standard deviation |\n",
      "+------------------+----------+-------------+---------------+-----------------------------------+\n",
      "|    SemrushBot    |    69    |     2266    |   -0.034786   |              0.000729             |\n",
      "|    AhrefsBot     |   177    |     2354    |   -0.034469   |              0.000726             |\n",
      "|  SemrushBot-SA   |    9     |     1298    |   -0.020409   |              0.000563             |\n",
      "|     BLEXBot      |    17    |     626     |   -0.009642   |              0.000389             |\n",
      "|      dotbot      |    8     |     461     |   -0.007172   |              0.000336             |\n",
      "|      psbot       |    17    |     422     |   -0.006412   |              0.000318             |\n",
      "| Offline Explorer |    12    |     379     |   -0.005811   |              0.000302             |\n",
      "|    WebCopier     |    10    |     361     |   -0.005557   |              0.000296             |\n",
      "|       Wget       |    12    |     354     |   -0.005415   |              0.000292             |\n",
      "|   WebStripper    |    10    |     352     |   -0.005415   |              0.000292             |\n",
      "+------------------+----------+-------------+---------------+-----------------------------------+\n"
     ]
    }
   ],
   "source": [
    "draw_favorability_table(favorability_of_robots, favored_1d_series, disfavored_1d_series, f=-1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f9fc4ed4",
   "metadata": {},
   "source": [
    "## Analysing German domains"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 489,
   "id": "a95784ff",
   "metadata": {},
   "outputs": [],
   "source": [
    "disfavored_1d_series, no_bias_1d_series, favored_1d_series, nb_of_times_appeared, top_10_appeared_bots_name, y_disfavored, y_no_bias, y_favored, total_number_of_user_agents, N = get_metrics(df_de)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 490,
   "id": "06a6837c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_most_frequently_appeared_bots(top_10_appeared_bots_name, y_disfavored, y_no_bias, y_favored)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 491,
   "id": "5b185a3d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_number_of_time_bot_appears_distribution(nb_of_times_appeared, total_number_of_user_agents)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 492,
   "id": "6dcc1da4",
   "metadata": {},
   "outputs": [],
   "source": [
    "favorability_of_robots = get_bots_favorability(favored_1d_series, disfavored_1d_series, N)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 493,
   "id": "eb9b3ba0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Googlebot               0.036072\n",
       "DuckDuckBot             0.021063\n",
       "BingBot                 0.019896\n",
       "Mediapartners-Google    0.019045\n",
       "bingbot                 0.018375\n",
       "Yahoo! Slurp            0.012971\n",
       "Seznambot               0.008303\n",
       "rdfbot                  0.008293\n",
       "YetiBot                 0.008293\n",
       "ichiro                  0.008150\n",
       "dtype: float64"
      ]
     },
     "execution_count": 493,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "favorability_of_robots[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 494,
   "id": "219f71d2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+----------------------+----------+-------------+---------------+-----------------------------------+\n",
      "|       Bot name       | #favored | #disfavored | #favorability | σ: categorical standard deviation |\n",
      "+----------------------+----------+-------------+---------------+-----------------------------------+\n",
      "|      Googlebot       |   4550   |     779     |    0.036072   |              0.000577             |\n",
      "|     DuckDuckBot      |   2249   |      47     |    0.021063   |              0.000444             |\n",
      "|       BingBot        |   2081   |      1      |    0.019896   |              0.000432             |\n",
      "| Mediapartners-Google |   2061   |      70     |    0.019045   |              0.000423             |\n",
      "|       bingbot        |   1987   |      66     |    0.018375   |              0.000415             |\n",
      "|     Yahoo! Slurp     |   1366   |      10     |    0.012971   |              0.00035              |\n",
      "|      Seznambot       |   868    |      0      |    0.008303   |              0.000281             |\n",
      "|        rdfbot        |   867    |      0      |    0.008293   |              0.00028              |\n",
      "|       YetiBot        |   867    |      0      |    0.008293   |              0.00028              |\n",
      "|        ichiro        |   879    |      27     |    0.00815    |              0.000278             |\n",
      "+----------------------+----------+-------------+---------------+-----------------------------------+\n"
     ]
    }
   ],
   "source": [
    "draw_favorability_table(favorability_of_robots, favored_1d_series, disfavored_1d_series, f=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 495,
   "id": "599e8581",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+----------------------+----------+-------------+---------------+-----------------------------------+\n",
      "|       Bot name       | #favored | #disfavored | #favorability | σ: categorical standard deviation |\n",
      "+----------------------+----------+-------------+---------------+-----------------------------------+\n",
      "|      AhrefsBot       |   221    |     1747    |   -0.014597   |              0.000371             |\n",
      "| AdsBot-Google-Mobile |   185    |     1580    |   -0.013344   |              0.000355             |\n",
      "|       MJ12bot        |   706    |     2044    |   -0.012799   |              0.000348             |\n",
      "|    AdsBot-Google     |   312    |     1645    |   -0.012751   |              0.000347             |\n",
      "|      SemrushBot      |    45    |     1261    |   -0.011632   |              0.000332             |\n",
      "|      WebCopier       |    23    |     1018    |   -0.009518   |               0.0003              |\n",
      "|   Offline Explorer   |    20    |     935     |   -0.008752   |              0.000288             |\n",
      "|    EmailCollector    |    44    |     959     |   -0.008752   |              0.000288             |\n",
      "|        psbot         |    42    |     909     |   -0.008293   |              0.00028              |\n",
      "|     SiteSnagger      |    10    |     853     |   -0.008064   |              0.000277             |\n",
      "+----------------------+----------+-------------+---------------+-----------------------------------+\n"
     ]
    }
   ],
   "source": [
    "draw_favorability_table(favorability_of_robots, favored_1d_series, disfavored_1d_series, f=-1)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}