32k.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "2e3ac4f4-d8b4-4b98-b441-120ed4e20387",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Went from 32480 to 30882 rows after dropping nans.\n"
     ]
    },
    {
     "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>page_id</th>\n",
       "      <th>page_title</th>\n",
       "      <th>page_random</th>\n",
       "      <th>pp_propname</th>\n",
       "      <th>gap</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "      <th>10</th>\n",
       "      <th>11</th>\n",
       "      <th>12</th>\n",
       "      <th>total</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>28448998</td>\n",
       "      <td>Korita,_Tomislavgrad</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>31575239</td>\n",
       "      <td>Larry_Douglas_(American_football)</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.776510e-07</td>\n",
       "      <td>35.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>39.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4404980</td>\n",
       "      <td>Nine_Mile_Road</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>disambiguation</td>\n",
       "      <td>NaN</td>\n",
       "      <td>55.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>65.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>66.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>712</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4895341</td>\n",
       "      <td>MSN_Chat</td>\n",
       "      <td>0.500001</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.651280e-07</td>\n",
       "      <td>1462.0</td>\n",
       "      <td>988.0</td>\n",
       "      <td>1251.0</td>\n",
       "      <td>793.0</td>\n",
       "      <td>748.0</td>\n",
       "      <td>738.0</td>\n",
       "      <td>695.0</td>\n",
       "      <td>726.0</td>\n",
       "      <td>773.0</td>\n",
       "      <td>829.0</td>\n",
       "      <td>519.0</td>\n",
       "      <td>634.0</td>\n",
       "      <td>10156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>30992386</td>\n",
       "      <td>NAMA_(gene)</td>\n",
       "      <td>0.500001</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.481600e-08</td>\n",
       "      <td>8.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>95</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    page_id                         page_title  page_random     pp_propname  \\\n",
       "0  28448998               Korita,_Tomislavgrad     0.500000             NaN   \n",
       "1  31575239  Larry_Douglas_(American_football)     0.500000             NaN   \n",
       "2   4404980                     Nine_Mile_Road     0.500000  disambiguation   \n",
       "3   4895341                           MSN_Chat     0.500001             NaN   \n",
       "4  30992386                        NAMA_(gene)     0.500001             NaN   \n",
       "\n",
       "            gap       1      2       3      4      5      6      7      8  \\\n",
       "0           NaN     6.0    0.0     3.0    1.0   12.0    1.0    4.0    4.0   \n",
       "1  2.776510e-07    35.0   32.0    20.0   21.0   25.0   27.0   20.0   31.0   \n",
       "2           NaN    55.0   44.0    65.0   60.0   48.0   69.0   66.0   53.0   \n",
       "3  1.651280e-07  1462.0  988.0  1251.0  793.0  748.0  738.0  695.0  726.0   \n",
       "4  3.481600e-08     8.0    5.0    14.0    2.0    3.0   11.0    5.0    5.0   \n",
       "\n",
       "       9     10     11     12  total  \n",
       "0    3.0    6.0   12.0    7.0     59  \n",
       "1   13.0   35.0   39.0   35.0    333  \n",
       "2   49.0   83.0   68.0   52.0    712  \n",
       "3  773.0  829.0  519.0  634.0  10156  \n",
       "4   11.0    6.0   18.0    7.0     95  "
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "sns.set_theme()\n",
    "sns.set(rc={'figure.figsize':(8,6)})\n",
    "from matplotlib import pyplot as plt\n",
    "\n",
    "df_raw = pd.read_csv('merged_32k.csv')\n",
    "\n",
    "def dropped_nan_views(df):\n",
    "    columns = [str(monthno) for monthno in range(1, 13)]\n",
    "    return df.dropna(axis=0, subset=columns)\n",
    "\n",
    "df = dropped_nan_views(df_raw).copy()\n",
    "print(f\"Went from {len(df_raw)} to {len(df)} rows after dropping nans.\")\n",
    "\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "6c9d005e-200e-43e9-8d14-0403b952c724",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Nvm, no 0s to deal with after dropping nans\n",
    "#df['totalplus'] = df['total'] + 1\n",
    "df['dab'] = df['pp_propname'] == 'disambiguation'\n",
    "# Sub-frame for non-disambiguation pages\n",
    "nd = df[~df.dab]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "891ab520-bb96-4596-9231-553f46c2d8a9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    3.088200e+04\n",
       "mean     1.254067e+04\n",
       "std      7.662463e+04\n",
       "min      3.000000e+00\n",
       "25%      1.990000e+02\n",
       "50%      7.320000e+02\n",
       "75%      3.461000e+03\n",
       "max      4.525873e+06\n",
       "Name: total, dtype: float64"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.total.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "37fb1e2f-eb60-470a-ad96-6d1b79d5b4ea",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "9eae79ce-a87d-4962-8e92-b0f11ce4da6a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib import ticker\n",
    "import os\n",
    "\n",
    "ax = sns.histplot(data=df, x='total', log_scale=True)\n",
    "ax.xaxis.set_major_formatter(ticker.StrMethodFormatter('{x:,.0f}'))\n",
    "ax.set_xlabel(\"2021 pageviews\")\n",
    "ax.set_ylabel(\"# articles\")\n",
    "#ax.set_title(\"Distribution of pageviews for random sample of 32k articles\")\n",
    "img_dir = \"/home/colin/src/colinmorris.github.com/assets/wiki-floor/\"\n",
    "def savefig(fname, dpi=144):\n",
    "    path = os.path.join(img_dir, fname)\n",
    "    plt.savefig(path, bbox_inches='tight', dpi=dpi)\n",
    "    \n",
    "savefig(\"32k_pageview_distribution.png\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "b1bb2c47-e5a5-4a3f-bfed-e78217d262a5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "70 pages with < 10 views. 8 non-dabs.\n"
     ]
    },
    {
     "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>page_id</th>\n",
       "      <th>page_title</th>\n",
       "      <th>page_random</th>\n",
       "      <th>pp_propname</th>\n",
       "      <th>gap</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "      <th>10</th>\n",
       "      <th>11</th>\n",
       "      <th>12</th>\n",
       "      <th>total</th>\n",
       "      <th>dab</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4503</th>\n",
       "      <td>41629959</td>\n",
       "      <td>Weimer_Township</td>\n",
       "      <td>0.500702</td>\n",
       "      <td>disambiguation</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23481</th>\n",
       "      <td>35904444</td>\n",
       "      <td>Goleh-ye_Cheshmeh</td>\n",
       "      <td>0.503623</td>\n",
       "      <td>disambiguation</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26855</th>\n",
       "      <td>62309280</td>\n",
       "      <td>Governor_Terry</td>\n",
       "      <td>0.504145</td>\n",
       "      <td>disambiguation</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15491</th>\n",
       "      <td>34571617</td>\n",
       "      <td>Dom_Darreh</td>\n",
       "      <td>0.502386</td>\n",
       "      <td>disambiguation</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1295</th>\n",
       "      <td>41903849</td>\n",
       "      <td>Eslamabad-e_Pain</td>\n",
       "      <td>0.500197</td>\n",
       "      <td>disambiguation</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13673</th>\n",
       "      <td>30167321</td>\n",
       "      <td>Symphony_in_A</td>\n",
       "      <td>0.502107</td>\n",
       "      <td>disambiguation</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10350</th>\n",
       "      <td>34219005</td>\n",
       "      <td>Khvoshnam</td>\n",
       "      <td>0.501583</td>\n",
       "      <td>disambiguation</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31945</th>\n",
       "      <td>40446200</td>\n",
       "      <td>Koli-ye_Olya</td>\n",
       "      <td>0.504918</td>\n",
       "      <td>disambiguation</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17337</th>\n",
       "      <td>44172578</td>\n",
       "      <td>Robert_Macgeorge</td>\n",
       "      <td>0.502664</td>\n",
       "      <td>disambiguation</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8769</th>\n",
       "      <td>39221085</td>\n",
       "      <td>Sar_Asiab-e_Farsangi</td>\n",
       "      <td>0.501337</td>\n",
       "      <td>disambiguation</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22433</th>\n",
       "      <td>40621893</td>\n",
       "      <td>Idahluy</td>\n",
       "      <td>0.503464</td>\n",
       "      <td>disambiguation</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17574</th>\n",
       "      <td>41026079</td>\n",
       "      <td>Barar_Deh</td>\n",
       "      <td>0.502705</td>\n",
       "      <td>disambiguation</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24197</th>\n",
       "      <td>58834217</td>\n",
       "      <td>Valea_Gruiului_River</td>\n",
       "      <td>0.503732</td>\n",
       "      <td>disambiguation</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>520</th>\n",
       "      <td>64299074</td>\n",
       "      <td>Senator_Gentile</td>\n",
       "      <td>0.500075</td>\n",
       "      <td>disambiguation</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30862</th>\n",
       "      <td>18558522</td>\n",
       "      <td>West_Parish</td>\n",
       "      <td>0.504743</td>\n",
       "      <td>disambiguation</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20905</th>\n",
       "      <td>23432153</td>\n",
       "      <td>Golujeh</td>\n",
       "      <td>0.503228</td>\n",
       "      <td>disambiguation</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27442</th>\n",
       "      <td>39938104</td>\n",
       "      <td>Deh-e_Bar_Aftab</td>\n",
       "      <td>0.504235</td>\n",
       "      <td>disambiguation</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19702</th>\n",
       "      <td>36939384</td>\n",
       "      <td>Gheyzaniyeh</td>\n",
       "      <td>0.503039</td>\n",
       "      <td>disambiguation</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30484</th>\n",
       "      <td>40863242</td>\n",
       "      <td>Kachaleh</td>\n",
       "      <td>0.504691</td>\n",
       "      <td>disambiguation</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22428</th>\n",
       "      <td>34328249</td>\n",
       "      <td>Taomiao</td>\n",
       "      <td>0.503463</td>\n",
       "      <td>disambiguation</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30475</th>\n",
       "      <td>18943870</td>\n",
       "      <td>Ardabilya</td>\n",
       "      <td>0.504690</td>\n",
       "      <td>disambiguation</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22707</th>\n",
       "      <td>22988415</td>\n",
       "      <td>George_Johnson_House</td>\n",
       "      <td>0.503505</td>\n",
       "      <td>disambiguation</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6663</th>\n",
       "      <td>28307477</td>\n",
       "      <td>San_Marcos_Municipality</td>\n",
       "      <td>0.501018</td>\n",
       "      <td>disambiguation</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6962</th>\n",
       "      <td>18306250</td>\n",
       "      <td>Gauliga_Danzig</td>\n",
       "      <td>0.501063</td>\n",
       "      <td>disambiguation</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24612</th>\n",
       "      <td>46911671</td>\n",
       "      <td>Kankabchén</td>\n",
       "      <td>0.503797</td>\n",
       "      <td>disambiguation</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9462</th>\n",
       "      <td>36845502</td>\n",
       "      <td>Gurab-e_Olya</td>\n",
       "      <td>0.501443</td>\n",
       "      <td>disambiguation</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20541</th>\n",
       "      <td>43349592</td>\n",
       "      <td>Ormeniș_River</td>\n",
       "      <td>0.503172</td>\n",
       "      <td>disambiguation</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7250</th>\n",
       "      <td>43000144</td>\n",
       "      <td>Henderson_Constituency</td>\n",
       "      <td>0.501102</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.767700e-08</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25182</th>\n",
       "      <td>38233012</td>\n",
       "      <td>Morlaiter</td>\n",
       "      <td>0.503883</td>\n",
       "      <td>disambiguation</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11017</th>\n",
       "      <td>20256380</td>\n",
       "      <td>Hope_Front</td>\n",
       "      <td>0.501684</td>\n",
       "      <td>disambiguation</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11153</th>\n",
       "      <td>41141000</td>\n",
       "      <td>Lialehkal</td>\n",
       "      <td>0.501706</td>\n",
       "      <td>disambiguation</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14063</th>\n",
       "      <td>13241450</td>\n",
       "      <td>Higashi-Matsue_Station</td>\n",
       "      <td>0.502165</td>\n",
       "      <td>disambiguation</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5366</th>\n",
       "      <td>37401292</td>\n",
       "      <td>Ploceus_melanotis</td>\n",
       "      <td>0.500821</td>\n",
       "      <td>disambiguation</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31254</th>\n",
       "      <td>63768944</td>\n",
       "      <td>Senator_Gale</td>\n",
       "      <td>0.504807</td>\n",
       "      <td>disambiguation</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20384</th>\n",
       "      <td>25388659</td>\n",
       "      <td>B._gouldii</td>\n",
       "      <td>0.503148</td>\n",
       "      <td>disambiguation</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31151</th>\n",
       "      <td>19900647</td>\n",
       "      <td>Szczepkowo</td>\n",
       "      <td>0.504791</td>\n",
       "      <td>disambiguation</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6182</th>\n",
       "      <td>59674157</td>\n",
       "      <td>Kamantan</td>\n",
       "      <td>0.500947</td>\n",
       "      <td>disambiguation</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18154</th>\n",
       "      <td>31872840</td>\n",
       "      <td>Gălășești</td>\n",
       "      <td>0.502798</td>\n",
       "      <td>disambiguation</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>8</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14634</th>\n",
       "      <td>36878451</td>\n",
       "      <td>Shartaq</td>\n",
       "      <td>0.502258</td>\n",
       "      <td>disambiguation</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5588</th>\n",
       "      <td>61636665</td>\n",
       "      <td>Hilarigona_obscurata</td>\n",
       "      <td>0.500858</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.462000e-09</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>8</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7427</th>\n",
       "      <td>36263772</td>\n",
       "      <td>Vinkov</td>\n",
       "      <td>0.501131</td>\n",
       "      <td>disambiguation</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14961</th>\n",
       "      <td>65427346</td>\n",
       "      <td>Senator_Rummel</td>\n",
       "      <td>0.502307</td>\n",
       "      <td>disambiguation</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>606</th>\n",
       "      <td>33040730</td>\n",
       "      <td>Avonbeg</td>\n",
       "      <td>0.500089</td>\n",
       "      <td>disambiguation</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14848</th>\n",
       "      <td>13357966</td>\n",
       "      <td>Moluccan_thrush</td>\n",
       "      <td>0.502289</td>\n",
       "      <td>disambiguation</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19629</th>\n",
       "      <td>15084322</td>\n",
       "      <td>Howard_Township,_Indiana</td>\n",
       "      <td>0.503028</td>\n",
       "      <td>disambiguation</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5345</th>\n",
       "      <td>26573324</td>\n",
       "      <td>Bryan_County_Courthouse</td>\n",
       "      <td>0.500818</td>\n",
       "      <td>disambiguation</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3561</th>\n",
       "      <td>60156789</td>\n",
       "      <td>Endangered_Girls</td>\n",
       "      <td>0.500556</td>\n",
       "      <td>disambiguation</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>8</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21955</th>\n",
       "      <td>63176628</td>\n",
       "      <td>Senator_Innes</td>\n",
       "      <td>0.503391</td>\n",
       "      <td>disambiguation</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>8</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26828</th>\n",
       "      <td>15825179</td>\n",
       "      <td>Middlebury_Township</td>\n",
       "      <td>0.504140</td>\n",
       "      <td>disambiguation</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27509</th>\n",
       "      <td>63484076</td>\n",
       "      <td>Senator_Adelman</td>\n",
       "      <td>0.504245</td>\n",
       "      <td>disambiguation</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        page_id                page_title  page_random     pp_propname  \\\n",
       "4503   41629959           Weimer_Township     0.500702  disambiguation   \n",
       "23481  35904444         Goleh-ye_Cheshmeh     0.503623  disambiguation   \n",
       "26855  62309280            Governor_Terry     0.504145  disambiguation   \n",
       "15491  34571617                Dom_Darreh     0.502386  disambiguation   \n",
       "1295   41903849          Eslamabad-e_Pain     0.500197  disambiguation   \n",
       "13673  30167321             Symphony_in_A     0.502107  disambiguation   \n",
       "10350  34219005                 Khvoshnam     0.501583  disambiguation   \n",
       "31945  40446200              Koli-ye_Olya     0.504918  disambiguation   \n",
       "17337  44172578          Robert_Macgeorge     0.502664  disambiguation   \n",
       "8769   39221085      Sar_Asiab-e_Farsangi     0.501337  disambiguation   \n",
       "22433  40621893                   Idahluy     0.503464  disambiguation   \n",
       "17574  41026079                 Barar_Deh     0.502705  disambiguation   \n",
       "24197  58834217      Valea_Gruiului_River     0.503732  disambiguation   \n",
       "520    64299074           Senator_Gentile     0.500075  disambiguation   \n",
       "30862  18558522               West_Parish     0.504743  disambiguation   \n",
       "20905  23432153                   Golujeh     0.503228  disambiguation   \n",
       "27442  39938104           Deh-e_Bar_Aftab     0.504235  disambiguation   \n",
       "19702  36939384               Gheyzaniyeh     0.503039  disambiguation   \n",
       "30484  40863242                  Kachaleh     0.504691  disambiguation   \n",
       "22428  34328249                   Taomiao     0.503463  disambiguation   \n",
       "30475  18943870                 Ardabilya     0.504690  disambiguation   \n",
       "22707  22988415      George_Johnson_House     0.503505  disambiguation   \n",
       "6663   28307477   San_Marcos_Municipality     0.501018  disambiguation   \n",
       "6962   18306250            Gauliga_Danzig     0.501063  disambiguation   \n",
       "24612  46911671                Kankabchén     0.503797  disambiguation   \n",
       "9462   36845502              Gurab-e_Olya     0.501443  disambiguation   \n",
       "20541  43349592             Ormeniș_River     0.503172  disambiguation   \n",
       "7250   43000144    Henderson_Constituency     0.501102             NaN   \n",
       "25182  38233012                 Morlaiter     0.503883  disambiguation   \n",
       "11017  20256380                Hope_Front     0.501684  disambiguation   \n",
       "11153  41141000                 Lialehkal     0.501706  disambiguation   \n",
       "14063  13241450    Higashi-Matsue_Station     0.502165  disambiguation   \n",
       "5366   37401292         Ploceus_melanotis     0.500821  disambiguation   \n",
       "31254  63768944              Senator_Gale     0.504807  disambiguation   \n",
       "20384  25388659                B._gouldii     0.503148  disambiguation   \n",
       "31151  19900647                Szczepkowo     0.504791  disambiguation   \n",
       "6182   59674157                  Kamantan     0.500947  disambiguation   \n",
       "18154  31872840                 Gălășești     0.502798  disambiguation   \n",
       "14634  36878451                   Shartaq     0.502258  disambiguation   \n",
       "5588   61636665      Hilarigona_obscurata     0.500858             NaN   \n",
       "7427   36263772                    Vinkov     0.501131  disambiguation   \n",
       "14961  65427346            Senator_Rummel     0.502307  disambiguation   \n",
       "606    33040730                   Avonbeg     0.500089  disambiguation   \n",
       "14848  13357966           Moluccan_thrush     0.502289  disambiguation   \n",
       "19629  15084322  Howard_Township,_Indiana     0.503028  disambiguation   \n",
       "5345   26573324   Bryan_County_Courthouse     0.500818  disambiguation   \n",
       "3561   60156789          Endangered_Girls     0.500556  disambiguation   \n",
       "21955  63176628             Senator_Innes     0.503391  disambiguation   \n",
       "26828  15825179       Middlebury_Township     0.504140  disambiguation   \n",
       "27509  63484076           Senator_Adelman     0.504245  disambiguation   \n",
       "\n",
       "                gap    1    2    3    4    5    6    7    8    9   10   11  \\\n",
       "4503            NaN  0.0  0.0  1.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  2.0   \n",
       "23481           NaN  0.0  0.0  1.0  1.0  0.0  0.0  0.0  0.0  0.0  1.0  1.0   \n",
       "26855           NaN  0.0  0.0  1.0  0.0  0.0  0.0  1.0  0.0  0.0  1.0  1.0   \n",
       "15491           NaN  0.0  0.0  1.0  0.0  0.0  0.0  1.0  0.0  0.0  1.0  1.0   \n",
       "1295            NaN  0.0  1.0  0.0  0.0  1.0  0.0  1.0  0.0  0.0  0.0  1.0   \n",
       "13673           NaN  0.0  0.0  1.0  0.0  0.0  0.0  1.0  0.0  0.0  0.0  3.0   \n",
       "10350           NaN  0.0  1.0  1.0  1.0  0.0  0.0  0.0  0.0  0.0  1.0  0.0   \n",
       "31945           NaN  0.0  0.0  1.0  0.0  0.0  0.0  0.0  0.0  2.0  1.0  1.0   \n",
       "17337           NaN  0.0  0.0  1.0  0.0  0.0  0.0  0.0  1.0  0.0  0.0  3.0   \n",
       "8769            NaN  0.0  0.0  1.0  0.0  0.0  0.0  1.0  0.0  0.0  0.0  3.0   \n",
       "22433           NaN  0.0  0.0  1.0  0.0  0.0  0.0  1.0  0.0  0.0  2.0  1.0   \n",
       "17574           NaN  0.0  0.0  1.0  0.0  0.0  0.0  1.0  0.0  0.0  2.0  1.0   \n",
       "24197           NaN  0.0  0.0  1.0  0.0  0.0  0.0  0.0  2.0  0.0  0.0  2.0   \n",
       "520             NaN  0.0  0.0  1.0  0.0  0.0  0.0  2.0  0.0  0.0  0.0  2.0   \n",
       "30862           NaN  0.0  1.0  0.0  1.0  0.0  0.0  1.0  1.0  0.0  1.0  1.0   \n",
       "20905           NaN  0.0  0.0  1.0  0.0  2.0  2.0  0.0  0.0  0.0  1.0  0.0   \n",
       "27442           NaN  1.0  0.0  0.0  0.0  1.0  0.0  1.0  0.0  0.0  2.0  1.0   \n",
       "19702           NaN  0.0  0.0  1.0  0.0  1.0  0.0  1.0  0.0  0.0  1.0  2.0   \n",
       "30484           NaN  0.0  0.0  1.0  0.0  0.0  0.0  1.0  0.0  1.0  1.0  1.0   \n",
       "22428           NaN  1.0  0.0  0.0  1.0  0.0  1.0  1.0  0.0  0.0  0.0  2.0   \n",
       "30475           NaN  0.0  0.0  1.0  1.0  0.0  0.0  1.0  0.0  0.0  2.0  1.0   \n",
       "22707           NaN  0.0  0.0  1.0  0.0  0.0  0.0  2.0  0.0  0.0  2.0  1.0   \n",
       "6663            NaN  0.0  1.0  0.0  0.0  0.0  0.0  2.0  0.0  0.0  0.0  3.0   \n",
       "6962            NaN  0.0  0.0  2.0  1.0  0.0  0.0  1.0  0.0  0.0  1.0  1.0   \n",
       "24612           NaN  0.0  1.0  0.0  0.0  0.0  0.0  1.0  1.0  0.0  1.0  1.0   \n",
       "9462            NaN  0.0  1.0  0.0  0.0  2.0  0.0  1.0  0.0  0.0  1.0  1.0   \n",
       "20541           NaN  0.0  0.0  2.0  0.0  0.0  0.0  1.0  0.0  0.0  0.0  3.0   \n",
       "7250   5.767700e-08  0.0  1.0  0.0  0.0  2.0  1.0  1.0  0.0  0.0  1.0  1.0   \n",
       "25182           NaN  0.0  0.0  1.0  0.0  0.0  0.0  1.0  0.0  0.0  0.0  5.0   \n",
       "11017           NaN  0.0  0.0  1.0  1.0  0.0  0.0  1.0  0.0  0.0  2.0  2.0   \n",
       "11153           NaN  0.0  0.0  1.0  0.0  1.0  2.0  1.0  0.0  0.0  1.0  1.0   \n",
       "14063           NaN  1.0  1.0  1.0  0.0  0.0  0.0  1.0  0.0  0.0  1.0  2.0   \n",
       "5366            NaN  1.0  0.0  1.0  0.0  0.0  0.0  1.0  1.0  0.0  0.0  3.0   \n",
       "31254           NaN  0.0  1.0  1.0  0.0  0.0  0.0  2.0  0.0  1.0  0.0  2.0   \n",
       "20384           NaN  0.0  0.0  1.0  0.0  0.0  0.0  1.0  0.0  1.0  2.0  2.0   \n",
       "31151           NaN  0.0  0.0  1.0  0.0  0.0  0.0  1.0  2.0  0.0  0.0  2.0   \n",
       "6182            NaN  0.0  1.0  1.0  0.0  0.0  0.0  2.0  1.0  0.0  2.0  0.0   \n",
       "18154           NaN  0.0  0.0  1.0  0.0  0.0  2.0  0.0  0.0  0.0  2.0  2.0   \n",
       "14634           NaN  0.0  0.0  1.0  2.0  1.0  0.0  2.0  0.0  0.0  0.0  2.0   \n",
       "5588   9.462000e-09  0.0  0.0  1.0  0.0  1.0  2.0  1.0  0.0  0.0  1.0  1.0   \n",
       "7427            NaN  2.0  0.0  1.0  0.0  2.0  0.0  0.0  0.0  0.0  0.0  3.0   \n",
       "14961           NaN  0.0  0.0  1.0  0.0  0.0  0.0  3.0  1.0  1.0  0.0  2.0   \n",
       "606             NaN  1.0  0.0  1.0  0.0  0.0  1.0  2.0  0.0  0.0  2.0  1.0   \n",
       "14848           NaN  0.0  0.0  0.0  0.0  2.0  0.0  1.0  0.0  1.0  1.0  3.0   \n",
       "19629           NaN  1.0  0.0  1.0  0.0  0.0  0.0  1.0  0.0  0.0  1.0  4.0   \n",
       "5345            NaN  0.0  0.0  1.0  0.0  2.0  0.0  1.0  0.0  1.0  2.0  1.0   \n",
       "3561            NaN  2.0  1.0  1.0  0.0  0.0  0.0  1.0  0.0  0.0  1.0  1.0   \n",
       "21955           NaN  0.0  1.0  0.0  0.0  1.0  0.0  2.0  0.0  0.0  0.0  2.0   \n",
       "26828           NaN  0.0  2.0  1.0  0.0  1.0  0.0  1.0  0.0  0.0  0.0  3.0   \n",
       "27509           NaN  0.0  0.0  1.0  1.0  2.0  0.0  2.0  0.0  0.0  0.0  2.0   \n",
       "\n",
       "        12  total    dab  \n",
       "4503   0.0      3   True  \n",
       "23481  0.0      4   True  \n",
       "26855  0.0      4   True  \n",
       "15491  0.0      4   True  \n",
       "1295   0.0      4   True  \n",
       "13673  0.0      5   True  \n",
       "10350  1.0      5   True  \n",
       "31945  0.0      5   True  \n",
       "17337  0.0      5   True  \n",
       "8769   0.0      5   True  \n",
       "22433  0.0      5   True  \n",
       "17574  0.0      5   True  \n",
       "24197  0.0      5   True  \n",
       "520    1.0      6   True  \n",
       "30862  0.0      6   True  \n",
       "20905  0.0      6   True  \n",
       "27442  0.0      6   True  \n",
       "19702  0.0      6   True  \n",
       "30484  1.0      6   True  \n",
       "22428  0.0      6   True  \n",
       "30475  0.0      6   True  \n",
       "22707  0.0      6   True  \n",
       "6663   0.0      6   True  \n",
       "6962   0.0      6   True  \n",
       "24612  1.0      6   True  \n",
       "9462   0.0      6   True  \n",
       "20541  0.0      6   True  \n",
       "7250   0.0      7  False  \n",
       "25182  0.0      7   True  \n",
       "11017  0.0      7   True  \n",
       "11153  0.0      7   True  \n",
       "14063  0.0      7   True  \n",
       "5366   0.0      7   True  \n",
       "31254  0.0      7   True  \n",
       "20384  0.0      7   True  \n",
       "31151  1.0      7   True  \n",
       "6182   0.0      7   True  \n",
       "18154  1.0      8   True  \n",
       "14634  0.0      8   True  \n",
       "5588   1.0      8  False  \n",
       "7427   0.0      8   True  \n",
       "14961  0.0      8   True  \n",
       "606    0.0      8   True  \n",
       "14848  0.0      8   True  \n",
       "19629  0.0      8   True  \n",
       "5345   0.0      8   True  \n",
       "3561   1.0      8   True  \n",
       "21955  2.0      8   True  \n",
       "26828  0.0      8   True  \n",
       "27509  0.0      8   True  "
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(f\"{len(df[df.total < 10])} pages with < 10 views. {len(nd[nd.total < 10])} non-dabs.\")\n",
    "df.sort_values(by='total').head(50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "30fd1c4a-c83c-4d76-9462-f119d448eb22",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Haack blah blah\n",
    "qf = df.copy()\n",
    "qf['disambiguation'] = qf['dab']\n",
    "ax = sns.histplot(data=qf, x='total', log_scale=True, hue='disambiguation', multiple=\"stack\");\n",
    "ax.set_xlabel(\"2021 pageviews\")\n",
    "ax.set_ylabel(\"# articles\")\n",
    "ax.xaxis.set_major_formatter(ticker.StrMethodFormatter('{x:,.0f}'))\n",
    "savefig(\"32k_pageview_distribution_split.png\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "ab0593cd-5a04-4916-ab2d-d3f7745b1891",
   "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>page_id</th>\n",
       "      <th>page_title</th>\n",
       "      <th>page_random</th>\n",
       "      <th>pp_propname</th>\n",
       "      <th>gap</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "      <th>10</th>\n",
       "      <th>11</th>\n",
       "      <th>12</th>\n",
       "      <th>total</th>\n",
       "      <th>dab</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>7250</th>\n",
       "      <td>43000144</td>\n",
       "      <td>Henderson_Constituency</td>\n",
       "      <td>0.501102</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.767700e-08</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4944</th>\n",
       "      <td>45302000</td>\n",
       "      <td>Erygia_sigillata</td>\n",
       "      <td>0.500765</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.463000e-09</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5588</th>\n",
       "      <td>61636665</td>\n",
       "      <td>Hilarigona_obscurata</td>\n",
       "      <td>0.500858</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.462000e-09</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>8</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24582</th>\n",
       "      <td>43631456</td>\n",
       "      <td>Loxocrambus_hospition</td>\n",
       "      <td>0.503792</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.511000e-09</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18741</th>\n",
       "      <td>39775848</td>\n",
       "      <td>Makhoshin</td>\n",
       "      <td>0.502888</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.255000e-09</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12369</th>\n",
       "      <td>47650275</td>\n",
       "      <td>Bojerud</td>\n",
       "      <td>0.501899</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.208000e-09</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13183</th>\n",
       "      <td>12473958</td>\n",
       "      <td>Iranian_ground_jay</td>\n",
       "      <td>0.502029</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.449100e-08</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>9</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12665</th>\n",
       "      <td>47715180</td>\n",
       "      <td>Scrobipalpula_crustaria</td>\n",
       "      <td>0.501948</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.300500e-08</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>9</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2427</th>\n",
       "      <td>53477493</td>\n",
       "      <td>Glenea_griseolineata</td>\n",
       "      <td>0.500381</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.007000e-09</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21199</th>\n",
       "      <td>51273199</td>\n",
       "      <td>Cephalodina_crassiceps</td>\n",
       "      <td>0.503274</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.260000e-09</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>10</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5039</th>\n",
       "      <td>40179183</td>\n",
       "      <td>Mecyclothorax_filipes</td>\n",
       "      <td>0.500777</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.020000e-09</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31120</th>\n",
       "      <td>36045373</td>\n",
       "      <td>Mordellistena_pallipes</td>\n",
       "      <td>0.504785</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.115000e-09</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>10</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        page_id               page_title  page_random pp_propname  \\\n",
       "7250   43000144   Henderson_Constituency     0.501102         NaN   \n",
       "4944   45302000         Erygia_sigillata     0.500765         NaN   \n",
       "5588   61636665     Hilarigona_obscurata     0.500858         NaN   \n",
       "24582  43631456    Loxocrambus_hospition     0.503792         NaN   \n",
       "18741  39775848                Makhoshin     0.502888         NaN   \n",
       "12369  47650275                  Bojerud     0.501899         NaN   \n",
       "13183  12473958       Iranian_ground_jay     0.502029         NaN   \n",
       "12665  47715180  Scrobipalpula_crustaria     0.501948         NaN   \n",
       "2427   53477493     Glenea_griseolineata     0.500381         NaN   \n",
       "21199  51273199   Cephalodina_crassiceps     0.503274         NaN   \n",
       "5039   40179183    Mecyclothorax_filipes     0.500777         NaN   \n",
       "31120  36045373   Mordellistena_pallipes     0.504785         NaN   \n",
       "\n",
       "                gap    1    2    3    4    5    6    7    8    9   10   11  \\\n",
       "7250   5.767700e-08  0.0  1.0  0.0  0.0  2.0  1.0  1.0  0.0  0.0  1.0  1.0   \n",
       "4944   3.463000e-09  1.0  0.0  1.0  0.0  1.0  1.0  1.0  0.0  1.0  1.0  1.0   \n",
       "5588   9.462000e-09  0.0  0.0  1.0  0.0  1.0  2.0  1.0  0.0  0.0  1.0  1.0   \n",
       "24582  7.511000e-09  1.0  2.0  0.0  0.0  1.0  1.0  0.0  2.0  0.0  1.0  1.0   \n",
       "18741  4.255000e-09  1.0  1.0  1.0  0.0  0.0  0.0  4.0  0.0  1.0  1.0  0.0   \n",
       "12369  8.208000e-09  0.0  1.0  2.0  0.0  0.0  0.0  1.0  1.0  0.0  2.0  2.0   \n",
       "13183  4.449100e-08  0.0  0.0  1.0  0.0  2.0  1.0  1.0  1.0  0.0  1.0  1.0   \n",
       "12665  2.300500e-08  0.0  0.0  1.0  0.0  1.0  1.0  0.0  0.0  0.0  1.0  3.0   \n",
       "2427   9.007000e-09  0.0  0.0  2.0  0.0  1.0  0.0  1.0  3.0  0.0  2.0  1.0   \n",
       "21199  8.260000e-09  0.0  0.0  1.0  0.0  2.0  1.0  0.0  0.0  0.0  3.0  1.0   \n",
       "5039   9.020000e-09  0.0  0.0  1.0  0.0  1.0  2.0  1.0  1.0  0.0  2.0  2.0   \n",
       "31120  4.115000e-09  0.0  1.0  0.0  0.0  1.0  2.0  1.0  0.0  0.0  0.0  4.0   \n",
       "\n",
       "        12  total    dab  \n",
       "7250   0.0      7  False  \n",
       "4944   0.0      8  False  \n",
       "5588   1.0      8  False  \n",
       "24582  0.0      9  False  \n",
       "18741  0.0      9  False  \n",
       "12369  0.0      9  False  \n",
       "13183  1.0      9  False  \n",
       "12665  2.0      9  False  \n",
       "2427   0.0     10  False  \n",
       "21199  2.0     10  False  \n",
       "5039   0.0     10  False  \n",
       "31120  1.0     10  False  "
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nd.sort_values(by='total').head(12)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "62c55a04-dc63-42d0-8bca-8b52b8ec96e9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8.666666666666667e-09"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sum([3e-9, 9e-9, 8e-9, 4e-9, 8e-9, 2e-8])/6"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "f5f0f341-2ce0-4072-aa1e-e669c5b50cff",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-226293.65000000002, 4752166.65)"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ax.get_ylim()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "83e1c4d0-fe3c-4cf2-844a-3a58e9ac85f9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "#ax.set_yscale('log')\n",
    "sns.scatterplot(data=df, x='gap', y='total', alpha=.5, ax=ax, marker='.')\n",
    "#ax.set_ylim(0, 200)\n",
    "#ax.set_ylim(0, 100000)\n",
    "ax.set_xlim(0, \n",
    "            #1e-6,\n",
    "            7.5e-7,\n",
    "           )\n",
    "ax.vlines(1.67e-7, 0, ax.get_ylim()[1], label=\"Average random gap size\", color='orange', linestyles='--')\n",
    "plt.legend()\n",
    "ax.set_xlabel(\"Random gap\")\n",
    "ax.set_ylabel(\"2021 page views\")\n",
    "ax.yaxis.set_major_formatter(ticker.StrMethodFormatter('{x:,.0f}'))\n",
    "savefig(\"gap_vs_views.png\")\n",
    "#ax.set_yscale('log');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "0ae5fd45-7449-4593-bc2f-bf08c665c31b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "#ax.set_yscale('log')\n",
    "sns.scatterplot(data=df, x='gap', y='total', alpha=.5, ax=ax, marker='.')\n",
    "ax.set_ylim(0, 200)\n",
    "#ax.set_ylim(0, 100000)\n",
    "ax.set_xlim(0, \n",
    "            #1e-6,\n",
    "            7.5e-7,\n",
    "           )\n",
    "ax.vlines(1.67e-7, 0, 200, label=\"Average random gap size\", color='orange', linestyles='--')\n",
    "plt.legend()\n",
    "ax.set_xlabel(\"Random gap\")\n",
    "ax.set_ylabel(\"2021 page views\")\n",
    "savefig(\"gap_vs_views_zoomed.png\")\n",
    "#ax.set_yscale('log');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d9ce25ce-7b96-427d-b20b-4dcbfcc6f657",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "fc96e9d4-0400-41a0-8e2e-e93cfff68a7b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    2.928400e+04\n",
       "mean     1.625466e-07\n",
       "std      1.627326e-07\n",
       "min      0.000000e+00\n",
       "1%       1.401490e-09\n",
       "5%       7.921200e-09\n",
       "10%      1.667070e-08\n",
       "20%      3.545280e-08\n",
       "50%      1.132793e-07\n",
       "90%      3.737489e-07\n",
       "95%      4.886955e-07\n",
       "98%      6.350505e-07\n",
       "99%      7.465726e-07\n",
       "99.5%    8.698185e-07\n",
       "max      1.715519e-06\n",
       "Name: gap, dtype: float64"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.gap.describe(percentiles=[.01, .05, .1, .2, .5, .9, .95, .98, .99, .995])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "13db45a2-ed0e-47ce-b564-bf0faa21e141",
   "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>page_id</th>\n",
       "      <th>page_title</th>\n",
       "      <th>page_random</th>\n",
       "      <th>pp_propname</th>\n",
       "      <th>gap</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "      <th>10</th>\n",
       "      <th>11</th>\n",
       "      <th>12</th>\n",
       "      <th>total</th>\n",
       "      <th>dab</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>28448998</td>\n",
       "      <td>Korita,_Tomislavgrad</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>59</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>31575239</td>\n",
       "      <td>Larry_Douglas_(American_football)</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.776510e-07</td>\n",
       "      <td>35.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>39.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>333</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4895341</td>\n",
       "      <td>MSN_Chat</td>\n",
       "      <td>0.500001</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.651280e-07</td>\n",
       "      <td>1462.0</td>\n",
       "      <td>988.0</td>\n",
       "      <td>1251.0</td>\n",
       "      <td>793.0</td>\n",
       "      <td>748.0</td>\n",
       "      <td>738.0</td>\n",
       "      <td>695.0</td>\n",
       "      <td>726.0</td>\n",
       "      <td>773.0</td>\n",
       "      <td>829.0</td>\n",
       "      <td>519.0</td>\n",
       "      <td>634.0</td>\n",
       "      <td>10156</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>30992386</td>\n",
       "      <td>NAMA_(gene)</td>\n",
       "      <td>0.500001</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.481600e-08</td>\n",
       "      <td>8.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>95</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>48711187</td>\n",
       "      <td>Paola_Musiani</td>\n",
       "      <td>0.500001</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.197000e-09</td>\n",
       "      <td>29.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>39.0</td>\n",
       "      <td>333</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    page_id                         page_title  page_random pp_propname  \\\n",
       "0  28448998               Korita,_Tomislavgrad     0.500000         NaN   \n",
       "1  31575239  Larry_Douglas_(American_football)     0.500000         NaN   \n",
       "3   4895341                           MSN_Chat     0.500001         NaN   \n",
       "4  30992386                        NAMA_(gene)     0.500001         NaN   \n",
       "5  48711187                      Paola_Musiani     0.500001         NaN   \n",
       "\n",
       "            gap       1      2       3      4      5      6      7      8  \\\n",
       "0           NaN     6.0    0.0     3.0    1.0   12.0    1.0    4.0    4.0   \n",
       "1  2.776510e-07    35.0   32.0    20.0   21.0   25.0   27.0   20.0   31.0   \n",
       "3  1.651280e-07  1462.0  988.0  1251.0  793.0  748.0  738.0  695.0  726.0   \n",
       "4  3.481600e-08     8.0    5.0    14.0    2.0    3.0   11.0    5.0    5.0   \n",
       "5  3.197000e-09    29.0   24.0    31.0   19.0   28.0   26.0   29.0   28.0   \n",
       "\n",
       "       9     10     11     12  total    dab  \n",
       "0    3.0    6.0   12.0    7.0     59  False  \n",
       "1   13.0   35.0   39.0   35.0    333  False  \n",
       "3  773.0  829.0  519.0  634.0  10156  False  \n",
       "4   11.0    6.0   18.0    7.0     95  False  \n",
       "5   32.0   13.0   35.0   39.0    333  False  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nd.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "0b482180-495c-4002-b545-e4cc3a8d666b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 792x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# For some reason trying to use a log scale more directly is giving janky results, so whatever.\n",
    "def zipf_plot(df, marker=None):\n",
    "    d = df.copy()\n",
    "    d['ltrank'] = np.log10(d.total.rank(ascending=False, method='first'))\n",
    "    d['ltotal'] = np.log10(d.total)\n",
    "    f, ax = plt.subplots()\n",
    "    sns.regplot(x='ltrank', y='ltotal', data=d,\n",
    "                 ax=ax,\n",
    "                 marker=marker,\n",
    "                )\n",
    "    return ax\n",
    "\n",
    "zipf_plot(\n",
    "    nd,\n",
    "    #nd.sample(1000, random_state=1),\n",
    "    #marker='o',\n",
    ");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "ba783a0a-6387-4600-be23-21bfd01d904f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "30498      1.0\n",
       "2330       2.0\n",
       "17060      3.0\n",
       "5571       4.0\n",
       "28652      5.0\n",
       "         ...  \n",
       "19878     96.0\n",
       "23966     97.5\n",
       "19058     97.5\n",
       "15095     99.0\n",
       "30065    100.0\n",
       "Name: total, Length: 100, dtype: float64"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nd.sample(100, random_state=1).total.rank(ascending=False).sort_values()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "3513e046-7310-4302-86b9-f43dc8d50e2e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "\n",
    "x = 10 ** np.arange(1, 10)\n",
    "y = x * 2\n",
    "data = pd.DataFrame(data={'x': x, 'y': y})\n",
    "\n",
    "f, ax = plt.subplots(figsize=(7, 7))\n",
    "#ax.set(xscale=\"log\", yscale=\"log\")\n",
    "sns.regplot(x=x, y=y, ax=ax, scatter_kws={\"s\": 100})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "ad80ab63-b7e0-4751-b3f2-10e31e89037e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    3.088200e+04\n",
       "mean     1.254067e+04\n",
       "std      7.662463e+04\n",
       "min      3.000000e+00\n",
       "25%      1.990000e+02\n",
       "50%      7.320000e+02\n",
       "75%      3.461000e+03\n",
       "max      4.525873e+06\n",
       "Name: total, dtype: float64"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.total.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "181d612c-39bb-4f28-8e57-d8d0697588f6",
   "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>page_id</th>\n",
       "      <th>page_title</th>\n",
       "      <th>page_random</th>\n",
       "      <th>pp_propname</th>\n",
       "      <th>gap</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "      <th>10</th>\n",
       "      <th>11</th>\n",
       "      <th>12</th>\n",
       "      <th>total</th>\n",
       "      <th>dab</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3235</th>\n",
       "      <td>444222</td>\n",
       "      <td>Narendra_Modi</td>\n",
       "      <td>0.500506</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.900600e-08</td>\n",
       "      <td>421757.0</td>\n",
       "      <td>368405.0</td>\n",
       "      <td>430324.0</td>\n",
       "      <td>449893.0</td>\n",
       "      <td>533994.0</td>\n",
       "      <td>313632.0</td>\n",
       "      <td>355167.0</td>\n",
       "      <td>312590.0</td>\n",
       "      <td>436826.0</td>\n",
       "      <td>298020.0</td>\n",
       "      <td>286203.0</td>\n",
       "      <td>319062.0</td>\n",
       "      <td>4525873</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23467</th>\n",
       "      <td>160811</td>\n",
       "      <td>Camilla,_Duchess_of_Cornwall</td>\n",
       "      <td>0.503622</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.284054e-07</td>\n",
       "      <td>531010.0</td>\n",
       "      <td>260029.0</td>\n",
       "      <td>617367.0</td>\n",
       "      <td>644946.0</td>\n",
       "      <td>270019.0</td>\n",
       "      <td>159279.0</td>\n",
       "      <td>146625.0</td>\n",
       "      <td>133987.0</td>\n",
       "      <td>112128.0</td>\n",
       "      <td>190333.0</td>\n",
       "      <td>201382.0</td>\n",
       "      <td>113159.0</td>\n",
       "      <td>3380264</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3084</th>\n",
       "      <td>1673570</td>\n",
       "      <td>Fran_Lebowitz</td>\n",
       "      <td>0.500484</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.399530e-07</td>\n",
       "      <td>1847440.0</td>\n",
       "      <td>558102.0</td>\n",
       "      <td>176619.0</td>\n",
       "      <td>176811.0</td>\n",
       "      <td>110183.0</td>\n",
       "      <td>70783.0</td>\n",
       "      <td>86361.0</td>\n",
       "      <td>51539.0</td>\n",
       "      <td>46660.0</td>\n",
       "      <td>41129.0</td>\n",
       "      <td>39076.0</td>\n",
       "      <td>89240.0</td>\n",
       "      <td>3293943</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20169</th>\n",
       "      <td>298602</td>\n",
       "      <td>Leicester_City_F.C.</td>\n",
       "      <td>0.503114</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.040650e-07</td>\n",
       "      <td>152178.0</td>\n",
       "      <td>139892.0</td>\n",
       "      <td>142495.0</td>\n",
       "      <td>189552.0</td>\n",
       "      <td>546997.0</td>\n",
       "      <td>129279.0</td>\n",
       "      <td>176643.0</td>\n",
       "      <td>262764.0</td>\n",
       "      <td>141083.0</td>\n",
       "      <td>163397.0</td>\n",
       "      <td>116602.0</td>\n",
       "      <td>134698.0</td>\n",
       "      <td>2295580</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29630</th>\n",
       "      <td>30770</td>\n",
       "      <td>The_Troubles</td>\n",
       "      <td>0.504566</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.508743e-07</td>\n",
       "      <td>234381.0</td>\n",
       "      <td>189585.0</td>\n",
       "      <td>244212.0</td>\n",
       "      <td>275068.0</td>\n",
       "      <td>198775.0</td>\n",
       "      <td>145138.0</td>\n",
       "      <td>149654.0</td>\n",
       "      <td>148664.0</td>\n",
       "      <td>155160.0</td>\n",
       "      <td>157963.0</td>\n",
       "      <td>188652.0</td>\n",
       "      <td>172382.0</td>\n",
       "      <td>2259634</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       page_id                    page_title  page_random pp_propname  \\\n",
       "3235    444222                 Narendra_Modi     0.500506         NaN   \n",
       "23467   160811  Camilla,_Duchess_of_Cornwall     0.503622         NaN   \n",
       "3084   1673570                 Fran_Lebowitz     0.500484         NaN   \n",
       "20169   298602           Leicester_City_F.C.     0.503114         NaN   \n",
       "29630    30770                  The_Troubles     0.504566         NaN   \n",
       "\n",
       "                gap          1         2         3         4         5  \\\n",
       "3235   8.900600e-08   421757.0  368405.0  430324.0  449893.0  533994.0   \n",
       "23467  4.284054e-07   531010.0  260029.0  617367.0  644946.0  270019.0   \n",
       "3084   1.399530e-07  1847440.0  558102.0  176619.0  176811.0  110183.0   \n",
       "20169  2.040650e-07   152178.0  139892.0  142495.0  189552.0  546997.0   \n",
       "29630  1.508743e-07   234381.0  189585.0  244212.0  275068.0  198775.0   \n",
       "\n",
       "              6         7         8         9        10        11        12  \\\n",
       "3235   313632.0  355167.0  312590.0  436826.0  298020.0  286203.0  319062.0   \n",
       "23467  159279.0  146625.0  133987.0  112128.0  190333.0  201382.0  113159.0   \n",
       "3084    70783.0   86361.0   51539.0   46660.0   41129.0   39076.0   89240.0   \n",
       "20169  129279.0  176643.0  262764.0  141083.0  163397.0  116602.0  134698.0   \n",
       "29630  145138.0  149654.0  148664.0  155160.0  157963.0  188652.0  172382.0   \n",
       "\n",
       "         total    dab  \n",
       "3235   4525873  False  \n",
       "23467  3380264  False  \n",
       "3084   3293943  False  \n",
       "20169  2295580  False  \n",
       "29630  2259634  False  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.sort_values(by='total', ascending=False).head()"
   ]
  }
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