script_scanner.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Script Scanning Notebook\n",
    "Contains a simple script to collect character and line-level info from script objects."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-03-29T16:41:39.190465Z",
     "start_time": "2018-03-29T16:41:39.184814Z"
    }
   },
   "outputs": [],
   "source": [
    "# Imports\n",
    "from collections import Counter        # Python library Counter object\n",
    "from os import listdir                 # Diretory listing function\n",
    "import json                            # json handling\n",
    "\n",
    "import pandas as pd                    # Pandas for data aggregation\n",
    "from bs4 import BeautifulSoup as soup  # BeautifulSoup object\n",
    "from tqdm import tqdm_notebook         # Visual progress bar"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-03-29T16:46:51.305072Z",
     "start_time": "2018-03-29T16:44:33.996765Z"
    }
   },
   "outputs": [
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       "<p>Failed to display Jupyter Widget of type <code>HBox</code>.</p>\n",
       "<p>\n",
       "  If you're reading this message in the Jupyter Notebook or JupyterLab Notebook, it may mean\n",
       "  that the widgets JavaScript is still loading. If this message persists, it\n",
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       "  Widgets Documentation</a> for setup instructions.\n",
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       "<p>\n",
       "  If you're reading this message in another frontend (for example, a static\n",
       "  rendering on GitHub or <a href=\"https://nbviewer.jupyter.org/\">NBViewer</a>),\n",
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     "text": [
      "Error parsing Matchstick Men\n",
      "Error parsing Harry Potter and the Deathly Hallows Part 1\n",
      "Error parsing Lion King, The\n",
      "Error parsing Casablanca\n",
      "Error parsing Jade\n",
      "Error parsing Benny & Joon\n",
      "Error parsing Batman Returns\n",
      "Error parsing Unforgiven\n",
      "Error parsing Sneakers\n",
      "Error parsing Mr. Holland's Opus\n",
      "Error parsing Incredibles, The\n",
      "Error parsing Harry Potter and the Prisoner of Azkaban\n",
      "Error parsing Superfights\n",
      "Error parsing Eyes Wide Shut\n",
      "Error parsing 25th Hour\n",
      "Error parsing Donnie Darko\n",
      "Error parsing Robocop\n",
      "Error parsing Harry Potter and the Sorcerer's Stone\n",
      "Error parsing Equilibrium\n",
      "Error parsing Shadow of the Vampire\n",
      "Error parsing Lethal Weapon 4\n",
      "Error parsing Kiss of the Spider Woman\n",
      "Error parsing Speed\n",
      "Error parsing El Mariachi\n",
      "Error parsing Goodfellas\n",
      "Error parsing Vertigo\n",
      "Error parsing Batman Forever\n",
      "Error parsing Outbreak\n",
      "Error parsing Clockwork Orange, A\n",
      "Error parsing Innerspace\n",
      "Error parsing A.I.\n",
      "Error parsing Monster's Ball\n",
      "Error parsing Harry Potter and the Chamber of Secrets\n",
      "Error parsing 8 Mile\n",
      "Error parsing Troy\n",
      "Error parsing Courage Under Fire\n",
      "Error parsing Valentine's Day\n",
      "Error parsing Full Metal Jacket\n",
      "Error parsing Officer and a Gentleman, An\n",
      "Error parsing Back to the Future II & III\n",
      "Error parsing Village, The\n",
      "Error parsing Collateral\n",
      "Error parsing Dark Knight, The\n",
      "Error parsing Harry Potter and the Half-Blood Prince\n",
      "Error parsing Contact\n",
      "Error parsing Harry Potter and the Goblet of Fire\n",
      "Error parsing Executive Decision\n",
      "Error parsing Rushmore\n",
      "Error parsing When Harry Met Sally\n",
      "Error parsing Get Shorty\n",
      "Error parsing Napoleon Dynamite\n",
      "Error parsing Batman Begins\n",
      "Error parsing Bourne Supremacy, The\n",
      "Error parsing Batman and Robin\n",
      "Error parsing Back to the Future\n",
      "Error parsing Lethal Weapon\n",
      "Error parsing Fury\n",
      "Error parsing Blues Brothers, The\n",
      "Error parsing Star Wars: Revenge of the Sith\n",
      "Error parsing Catwoman\n",
      "\n"
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>253.0</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>695.0</td>\n",
       "      <td>213.0</td>\n",
       "      <td>213.0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>630.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>384.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>508.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>639.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>2.0</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>559.0</td>\n",
       "      <td>104.0</td>\n",
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       "      <td>487.0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>6478.0</td>\n",
       "      <td>43750.0</td>\n",
       "      <td>111.0</td>\n",
       "      <td>262.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1081.0</td>\n",
       "      <td>393.0</td>\n",
       "      <td>393.0</td>\n",
       "      <td>1038.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>6980.0</td>\n",
       "      <td>151236.0</td>\n",
       "      <td>386.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1369.0</td>\n",
       "      <td>266.0</td>\n",
       "      <td>266.0</td>\n",
       "      <td>1497.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>5517.0</td>\n",
       "      <td>19797.0</td>\n",
       "      <td>244.0</td>\n",
       "      <td>111.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>801.0</td>\n",
       "      <td>205.0</td>\n",
       "      <td>203.0</td>\n",
       "      <td>1281.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>6630.0</td>\n",
       "      <td>148699.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>981.0</td>\n",
       "      <td>271.0</td>\n",
       "      <td>271.0</td>\n",
       "      <td>1253.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>5799.0</td>\n",
       "      <td>118353.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>859.0</td>\n",
       "      <td>326.0</td>\n",
       "      <td>326.0</td>\n",
       "      <td>979.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>6378.0</td>\n",
       "      <td>112766.0</td>\n",
       "      <td>440.0</td>\n",
       "      <td>95.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>858.0</td>\n",
       "      <td>297.0</td>\n",
       "      <td>299.0</td>\n",
       "      <td>946.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>5611.0</td>\n",
       "      <td>49713.0</td>\n",
       "      <td>560.0</td>\n",
       "      <td>71.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>108.0</td>\n",
       "      <td>639.0</td>\n",
       "      <td>290.0</td>\n",
       "      <td>290.0</td>\n",
       "      <td>867.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>7694.0</td>\n",
       "      <td>121655.0</td>\n",
       "      <td>1457.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1147.0</td>\n",
       "      <td>107.0</td>\n",
       "      <td>107.0</td>\n",
       "      <td>1081.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>5928.0</td>\n",
       "      <td>133545.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>153.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>833.0</td>\n",
       "      <td>175.0</td>\n",
       "      <td>175.0</td>\n",
       "      <td>1419.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>7913.0</td>\n",
       "      <td>124937.0</td>\n",
       "      <td>372.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>1053.0</td>\n",
       "      <td>433.0</td>\n",
       "      <td>433.0</td>\n",
       "      <td>1214.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>4937.0</td>\n",
       "      <td>51738.0</td>\n",
       "      <td>207.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>962.0</td>\n",
       "      <td>301.0</td>\n",
       "      <td>303.0</td>\n",
       "      <td>1564.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>6099.0</td>\n",
       "      <td>69053.0</td>\n",
       "      <td>63.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>840.0</td>\n",
       "      <td>95.0</td>\n",
       "      <td>95.0</td>\n",
       "      <td>887.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>4701.0</td>\n",
       "      <td>103106.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>599.0</td>\n",
       "      <td>286.0</td>\n",
       "      <td>286.0</td>\n",
       "      <td>817.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1079</th>\n",
       "      <td>3679.0</td>\n",
       "      <td>86442.0</td>\n",
       "      <td>386.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>651.0</td>\n",
       "      <td>222.0</td>\n",
       "      <td>222.0</td>\n",
       "      <td>710.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1080</th>\n",
       "      <td>6310.0</td>\n",
       "      <td>66032.0</td>\n",
       "      <td>55.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1086.0</td>\n",
       "      <td>265.0</td>\n",
       "      <td>265.0</td>\n",
       "      <td>835.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1081</th>\n",
       "      <td>4906.0</td>\n",
       "      <td>72347.0</td>\n",
       "      <td>126.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>863.0</td>\n",
       "      <td>159.0</td>\n",
       "      <td>160.0</td>\n",
       "      <td>1257.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1082</th>\n",
       "      <td>5560.0</td>\n",
       "      <td>78133.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>59.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>915.0</td>\n",
       "      <td>350.0</td>\n",
       "      <td>350.0</td>\n",
       "      <td>838.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1083</th>\n",
       "      <td>6982.0</td>\n",
       "      <td>93254.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>758.0</td>\n",
       "      <td>316.0</td>\n",
       "      <td>327.0</td>\n",
       "      <td>1338.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1084</th>\n",
       "      <td>5715.0</td>\n",
       "      <td>79642.0</td>\n",
       "      <td>178.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>107.0</td>\n",
       "      <td>107.0</td>\n",
       "      <td>778.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1085</th>\n",
       "      <td>6086.0</td>\n",
       "      <td>126900.0</td>\n",
       "      <td>448.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>997.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1296.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1086</th>\n",
       "      <td>15179.0</td>\n",
       "      <td>169232.0</td>\n",
       "      <td>409.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>178.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2915.0</td>\n",
       "      <td>1317.0</td>\n",
       "      <td>1321.0</td>\n",
       "      <td>2705.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1087</th>\n",
       "      <td>5749.0</td>\n",
       "      <td>20083.0</td>\n",
       "      <td>165.0</td>\n",
       "      <td>108.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>971.0</td>\n",
       "      <td>278.0</td>\n",
       "      <td>277.0</td>\n",
       "      <td>695.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1088</th>\n",
       "      <td>7476.0</td>\n",
       "      <td>107700.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>106.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>911.0</td>\n",
       "      <td>218.0</td>\n",
       "      <td>218.0</td>\n",
       "      <td>1241.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1089</th>\n",
       "      <td>7649.0</td>\n",
       "      <td>102726.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>76.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>924.0</td>\n",
       "      <td>349.0</td>\n",
       "      <td>349.0</td>\n",
       "      <td>1209.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1090</th>\n",
       "      <td>13266.0</td>\n",
       "      <td>172104.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1606.0</td>\n",
       "      <td>272.0</td>\n",
       "      <td>272.0</td>\n",
       "      <td>1074.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1091</th>\n",
       "      <td>8238.0</td>\n",
       "      <td>160515.0</td>\n",
       "      <td>252.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>893.0</td>\n",
       "      <td>210.0</td>\n",
       "      <td>210.0</td>\n",
       "      <td>674.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1092</th>\n",
       "      <td>4432.0</td>\n",
       "      <td>65372.0</td>\n",
       "      <td>359.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>697.0</td>\n",
       "      <td>148.0</td>\n",
       "      <td>148.0</td>\n",
       "      <td>601.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1093</th>\n",
       "      <td>8107.0</td>\n",
       "      <td>106616.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>954.0</td>\n",
       "      <td>465.0</td>\n",
       "      <td>465.0</td>\n",
       "      <td>1354.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1094</th>\n",
       "      <td>5598.0</td>\n",
       "      <td>96373.0</td>\n",
       "      <td>123.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>413.0</td>\n",
       "      <td>267.0</td>\n",
       "      <td>270.0</td>\n",
       "      <td>713.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1095</th>\n",
       "      <td>3994.0</td>\n",
       "      <td>37979.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>511.0</td>\n",
       "      <td>96.0</td>\n",
       "      <td>96.0</td>\n",
       "      <td>597.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1096</th>\n",
       "      <td>6426.0</td>\n",
       "      <td>20291.0</td>\n",
       "      <td>128.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1325.0</td>\n",
       "      <td>319.0</td>\n",
       "      <td>319.0</td>\n",
       "      <td>1096.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1097</th>\n",
       "      <td>7348.0</td>\n",
       "      <td>33077.0</td>\n",
       "      <td>155.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1161.0</td>\n",
       "      <td>246.0</td>\n",
       "      <td>246.0</td>\n",
       "      <td>1876.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1098</th>\n",
       "      <td>6029.0</td>\n",
       "      <td>34737.0</td>\n",
       "      <td>137.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>904.0</td>\n",
       "      <td>61.0</td>\n",
       "      <td>61.0</td>\n",
       "      <td>1385.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1099</th>\n",
       "      <td>5377.0</td>\n",
       "      <td>108932.0</td>\n",
       "      <td>151.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>55.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>878.0</td>\n",
       "      <td>234.0</td>\n",
       "      <td>234.0</td>\n",
       "      <td>389.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1100</th>\n",
       "      <td>6753.0</td>\n",
       "      <td>89763.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>354.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>893.0</td>\n",
       "      <td>510.0</td>\n",
       "      <td>513.0</td>\n",
       "      <td>2539.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1101</th>\n",
       "      <td>5078.0</td>\n",
       "      <td>63440.0</td>\n",
       "      <td>551.0</td>\n",
       "      <td>61.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>470.0</td>\n",
       "      <td>99.0</td>\n",
       "      <td>98.0</td>\n",
       "      <td>678.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1102</th>\n",
       "      <td>5711.0</td>\n",
       "      <td>84084.0</td>\n",
       "      <td>520.0</td>\n",
       "      <td>376.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>629.0</td>\n",
       "      <td>474.0</td>\n",
       "      <td>474.0</td>\n",
       "      <td>748.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1103</th>\n",
       "      <td>6314.0</td>\n",
       "      <td>129302.0</td>\n",
       "      <td>320.0</td>\n",
       "      <td>238.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>893.0</td>\n",
       "      <td>430.0</td>\n",
       "      <td>433.0</td>\n",
       "      <td>1714.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1104</th>\n",
       "      <td>7052.0</td>\n",
       "      <td>161044.0</td>\n",
       "      <td>134.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>807.0</td>\n",
       "      <td>409.0</td>\n",
       "      <td>410.0</td>\n",
       "      <td>1268.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1105</th>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1106</th>\n",
       "      <td>5804.0</td>\n",
       "      <td>23355.0</td>\n",
       "      <td>591.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>644.0</td>\n",
       "      <td>357.0</td>\n",
       "      <td>353.0</td>\n",
       "      <td>940.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1107</th>\n",
       "      <td>7016.0</td>\n",
       "      <td>146788.0</td>\n",
       "      <td>634.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1412.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>2177.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1108</th>\n",
       "      <td>5692.0</td>\n",
       "      <td>82932.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>823.0</td>\n",
       "      <td>222.0</td>\n",
       "      <td>225.0</td>\n",
       "      <td>756.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1109 rows × 212 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           \\n                 !      \"      #      &       '       (       )  \\\n",
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       "2      5672.0  127975.0   174.0  124.0    2.0    NaN  1037.0   411.0   411.0   \n",
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       "4      7784.0   28594.0   179.0   83.0    NaN    NaN  1285.0   389.0   389.0   \n",
       "5      6065.0   60699.0   168.0  169.0   11.0    NaN   852.0   296.0   296.0   \n",
       "6      3976.0   81484.0   212.0   34.0    NaN    1.0   564.0   185.0   185.0   \n",
       "7      8783.0   28954.0   137.0    9.0    1.0    NaN   175.0   553.0   553.0   \n",
       "8      4361.0   42152.0     7.0    2.0    NaN    NaN   630.0    94.0    93.0   \n",
       "9      4635.0   63641.0   533.0  122.0   35.0    2.0   677.0   253.0   253.0   \n",
       "10     6803.0  114832.0   185.0   78.0    NaN    NaN   695.0   213.0   213.0   \n",
       "11     4466.0   93148.0    33.0    2.0    NaN    NaN   630.0   150.0   150.0   \n",
       "12     4610.0   87181.0    17.0   48.0    NaN    NaN   508.0    60.0    60.0   \n",
       "13     8539.0  154802.0   117.0   30.0    2.0    2.0   810.0   417.0   417.0   \n",
       "14     6127.0   77869.0   140.0   38.0    NaN    NaN   559.0   104.0   104.0   \n",
       "15       15.0      26.0     NaN    4.0    NaN    NaN     NaN     NaN     NaN   \n",
       "16     7694.0  114060.0    65.0  113.0    1.0    3.0   924.0   370.0   370.0   \n",
       "17     6478.0   43750.0   111.0  262.0    5.0    1.0  1081.0   393.0   393.0   \n",
       "18     6980.0  151236.0   386.0   32.0    7.0    2.0  1369.0   266.0   266.0   \n",
       "19     5517.0   19797.0   244.0  111.0    1.0    1.0   801.0   205.0   203.0   \n",
       "20     6630.0  148699.0    70.0   24.0    NaN    NaN   981.0   271.0   271.0   \n",
       "21     5799.0  118353.0    51.0   91.0    2.0    2.0   859.0   326.0   326.0   \n",
       "22     6378.0  112766.0   440.0   95.0    NaN    3.0   858.0   297.0   299.0   \n",
       "23     5611.0   49713.0   560.0   71.0    1.0  108.0   639.0   290.0   290.0   \n",
       "24     7694.0  121655.0  1457.0   26.0    NaN    5.0  1147.0   107.0   107.0   \n",
       "25     5928.0  133545.0    36.0  153.0    NaN    NaN   833.0   175.0   175.0   \n",
       "26     7913.0  124937.0   372.0   38.0    7.0   11.0  1053.0   433.0   433.0   \n",
       "27     4937.0   51738.0   207.0   82.0    NaN    NaN   962.0   301.0   303.0   \n",
       "28     6099.0   69053.0    63.0   77.0   11.0    NaN   840.0    95.0    95.0   \n",
       "29     4701.0  103106.0   230.0   40.0    NaN    NaN   599.0   286.0   286.0   \n",
       "...       ...       ...     ...    ...    ...    ...     ...     ...     ...   \n",
       "1079   3679.0   86442.0   386.0   38.0    NaN    2.0   651.0   222.0   222.0   \n",
       "1080   6310.0   66032.0    55.0   40.0    NaN    NaN  1086.0   265.0   265.0   \n",
       "1081   4906.0   72347.0   126.0   68.0    NaN    NaN   863.0   159.0   160.0   \n",
       "1082   5560.0   78133.0    68.0   59.0   34.0    2.0   915.0   350.0   350.0   \n",
       "1083   6982.0   93254.0    81.0    2.0    NaN    NaN   758.0   316.0   327.0   \n",
       "1084   5715.0   79642.0   178.0   22.0    1.0    6.0  1000.0   107.0   107.0   \n",
       "1085   6086.0  126900.0   448.0   45.0    NaN    3.0   997.0     3.0     3.0   \n",
       "1086  15179.0  169232.0   409.0    2.0  178.0    NaN  2915.0  1317.0  1321.0   \n",
       "1087   5749.0   20083.0   165.0  108.0    4.0    NaN   971.0   278.0   277.0   \n",
       "1088   7476.0  107700.0    50.0  106.0   10.0    1.0   911.0   218.0   218.0   \n",
       "1089   7649.0  102726.0    44.0   76.0    8.0    2.0   924.0   349.0   349.0   \n",
       "1090  13266.0  172104.0    51.0   58.0   16.0    1.0  1606.0   272.0   272.0   \n",
       "1091   8238.0  160515.0   252.0    NaN    NaN    1.0   893.0   210.0   210.0   \n",
       "1092   4432.0   65372.0   359.0   20.0    NaN    4.0   697.0   148.0   148.0   \n",
       "1093   8107.0  106616.0    21.0   62.0    9.0    NaN   954.0   465.0   465.0   \n",
       "1094   5598.0   96373.0   123.0   38.0    8.0    5.0   413.0   267.0   270.0   \n",
       "1095   3994.0   37979.0    12.0   24.0    NaN    NaN   511.0    96.0    96.0   \n",
       "1096   6426.0   20291.0   128.0   68.0    2.0    NaN  1325.0   319.0   319.0   \n",
       "1097   7348.0   33077.0   155.0   62.0    2.0    NaN  1161.0   246.0   246.0   \n",
       "1098   6029.0   34737.0   137.0   20.0    NaN    NaN   904.0    61.0    61.0   \n",
       "1099   5377.0  108932.0   151.0   24.0   55.0    NaN   878.0   234.0   234.0   \n",
       "1100   6753.0   89763.0    10.0  354.0    1.0    2.0   893.0   510.0   513.0   \n",
       "1101   5078.0   63440.0   551.0   61.0   11.0    1.0   470.0    99.0    98.0   \n",
       "1102   5711.0   84084.0   520.0  376.0   14.0    2.0   629.0   474.0   474.0   \n",
       "1103   6314.0  129302.0   320.0  238.0    6.0    9.0   893.0   430.0   433.0   \n",
       "1104   7052.0  161044.0   134.0   30.0   24.0    1.0   807.0   409.0   410.0   \n",
       "1105      1.0       NaN     NaN    NaN    NaN    NaN     NaN     NaN     NaN   \n",
       "1106   5804.0   23355.0   591.0    2.0    NaN    4.0   644.0   357.0   353.0   \n",
       "1107   7016.0  146788.0   634.0   22.0    NaN    4.0  1412.0    11.0    11.0   \n",
       "1108   5692.0   82932.0    46.0   92.0    NaN    NaN   823.0   222.0   225.0   \n",
       "\n",
       "           , ...                ¨   ¼   ²   ¹         \n",
       "0      804.0 ...  NaN NaN NaN NaN NaN NaN NaN NaN NaN  NaN  \n",
       "1     1115.0 ...  NaN NaN NaN NaN NaN NaN NaN NaN NaN  NaN  \n",
       "2     1046.0 ...  NaN NaN NaN NaN NaN NaN NaN NaN NaN  NaN  \n",
       "3     1117.0 ...  NaN NaN NaN NaN NaN NaN NaN NaN NaN  NaN  \n",
       "4     2268.0 ...  NaN NaN NaN NaN NaN NaN NaN NaN NaN  NaN  \n",
       "5     1346.0 ...  NaN NaN NaN NaN NaN NaN NaN NaN NaN  NaN  \n",
       "6      706.0 ...  NaN NaN NaN NaN NaN NaN NaN NaN NaN  NaN  \n",
       "7     1619.0 ...  NaN NaN NaN NaN NaN NaN NaN NaN NaN  NaN  \n",
       "8     1115.0 ...  NaN NaN NaN NaN NaN NaN NaN NaN NaN  NaN  \n",
       "9     1099.0 ...  NaN NaN NaN NaN NaN NaN NaN NaN NaN  NaN  \n",
       "10    1321.0 ...  NaN NaN NaN NaN NaN NaN NaN NaN NaN  NaN  \n",
       "11     384.0 ...  NaN NaN NaN NaN NaN NaN NaN NaN NaN  NaN  \n",
       "12     639.0 ...  NaN NaN NaN NaN NaN NaN NaN NaN NaN  NaN  \n",
       "13    1639.0 ...  NaN NaN NaN NaN NaN NaN NaN NaN NaN  NaN  \n",
       "14     487.0 ...  NaN NaN NaN NaN NaN NaN NaN NaN NaN  NaN  \n",
       "15       3.0 ...  NaN NaN NaN NaN NaN NaN NaN NaN NaN  NaN  \n",
       "16     746.0 ...  NaN NaN NaN NaN NaN NaN NaN NaN NaN  NaN  \n",
       "17    1038.0 ...  NaN NaN NaN NaN NaN NaN NaN NaN NaN  NaN  \n",
       "18    1497.0 ...  NaN NaN NaN NaN NaN NaN NaN NaN NaN  NaN  \n",
       "19    1281.0 ...  NaN NaN NaN NaN NaN NaN NaN NaN NaN  NaN  \n",
       "20    1253.0 ...  NaN NaN NaN NaN NaN NaN NaN NaN NaN  NaN  \n",
       "21     979.0 ...  NaN NaN NaN NaN NaN NaN NaN NaN NaN  NaN  \n",
       "22     946.0 ...  NaN NaN NaN NaN NaN NaN NaN NaN NaN  NaN  \n",
       "23     867.0 ...  NaN NaN NaN NaN NaN NaN NaN NaN NaN  NaN  \n",
       "24    1081.0 ...  NaN NaN NaN NaN NaN NaN NaN NaN NaN  NaN  \n",
       "25    1419.0 ...  NaN NaN NaN NaN NaN NaN NaN NaN NaN  NaN  \n",
       "26    1214.0 ...  NaN NaN NaN NaN NaN NaN NaN NaN NaN  NaN  \n",
       "27    1564.0 ...  NaN NaN NaN NaN NaN NaN NaN NaN NaN  NaN  \n",
       "28     887.0 ...  NaN NaN NaN NaN NaN NaN NaN NaN NaN  NaN  \n",
       "29     817.0 ...  NaN NaN NaN NaN NaN NaN NaN NaN NaN  NaN  \n",
       "...      ... ...   ..  ..  ..  ..  ..  ..  ..  ..  ..  ...  \n",
       "1079   710.0 ...  NaN NaN NaN NaN NaN NaN NaN NaN NaN  NaN  \n",
       "1080   835.0 ...  NaN NaN NaN NaN NaN NaN NaN NaN NaN  NaN  \n",
       "1081  1257.0 ...  NaN NaN NaN NaN NaN NaN NaN NaN NaN  NaN  \n",
       "1082   838.0 ...  NaN NaN NaN NaN NaN NaN NaN NaN NaN  NaN  \n",
       "1083  1338.0 ...  NaN NaN NaN NaN NaN NaN NaN NaN NaN  NaN  \n",
       "1084   778.0 ...  NaN NaN NaN NaN NaN NaN NaN NaN NaN  NaN  \n",
       "1085  1296.0 ...  NaN NaN NaN NaN NaN NaN NaN NaN NaN  NaN  \n",
       "1086  2705.0 ...  NaN NaN NaN NaN NaN NaN NaN NaN NaN  NaN  \n",
       "1087   695.0 ...  NaN NaN NaN NaN NaN NaN NaN NaN NaN  NaN  \n",
       "1088  1241.0 ...  NaN NaN NaN NaN NaN NaN NaN NaN NaN  NaN  \n",
       "1089  1209.0 ...  NaN NaN NaN NaN NaN NaN NaN NaN NaN  NaN  \n",
       "1090  1074.0 ...  NaN NaN NaN NaN NaN NaN NaN NaN NaN  NaN  \n",
       "1091   674.0 ...  NaN NaN NaN NaN NaN NaN NaN NaN NaN  NaN  \n",
       "1092   601.0 ...  NaN NaN NaN NaN NaN NaN NaN NaN NaN  NaN  \n",
       "1093  1354.0 ...  NaN NaN NaN NaN NaN NaN NaN NaN NaN  NaN  \n",
       "1094   713.0 ...  NaN NaN NaN NaN NaN NaN NaN NaN NaN  NaN  \n",
       "1095   597.0 ...  NaN NaN NaN NaN NaN NaN NaN NaN NaN  NaN  \n",
       "1096  1096.0 ...  NaN NaN NaN NaN NaN NaN NaN NaN NaN  NaN  \n",
       "1097  1876.0 ...  NaN NaN NaN NaN NaN NaN NaN NaN NaN  NaN  \n",
       "1098  1385.0 ...  NaN NaN NaN NaN NaN NaN NaN NaN NaN  NaN  \n",
       "1099   389.0 ...  NaN NaN NaN NaN NaN NaN NaN NaN NaN  NaN  \n",
       "1100  2539.0 ...  NaN NaN NaN NaN NaN NaN NaN NaN NaN  NaN  \n",
       "1101   678.0 ...  NaN NaN NaN NaN NaN NaN NaN NaN NaN  1.0  \n",
       "1102   748.0 ...  NaN NaN NaN NaN NaN NaN NaN NaN NaN  NaN  \n",
       "1103  1714.0 ...  NaN NaN NaN NaN NaN NaN NaN NaN NaN  NaN  \n",
       "1104  1268.0 ...  NaN NaN NaN NaN NaN NaN NaN NaN NaN  NaN  \n",
       "1105     NaN ...  NaN NaN NaN NaN NaN NaN NaN NaN NaN  NaN  \n",
       "1106   940.0 ...  NaN NaN NaN NaN NaN NaN NaN NaN NaN  NaN  \n",
       "1107  2177.0 ...  NaN NaN NaN NaN NaN NaN NaN NaN NaN  NaN  \n",
       "1108   756.0 ...  NaN NaN NaN NaN NaN NaN NaN NaN NaN  NaN  \n",
       "\n",
       "[1109 rows x 212 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get list of all json script objects\n",
    "scripts = listdir('./scripts')\n",
    "scripts.remove('.DS_Store')\n",
    "SCRIPT_DIR = './scripts/{}'\n",
    "\n",
    "# Create DataFrame to capture output\n",
    "df = pd.DataFrame()\n",
    "\n",
    "# Create loop to run through jsons\n",
    "for script in tqdm_notebook(scripts):\n",
    "    with open(SCRIPT_DIR.format(script)) as f:\n",
    "        data = json.load(f)\n",
    "    try: \n",
    "        raw = str(soup(data['script'], \"lxml\").find_all(\"pre\")[-1])\n",
    "        raw_chars = [c for c in raw]\n",
    "        raw_lines = raw.split(sep='\\n')\n",
    "\n",
    "        # Count characters\n",
    "        char_count = len(raw_chars)\n",
    "        char_counter = Counter(raw_chars)\n",
    "\n",
    "        # Count lines and line lengths\n",
    "        line_count = len(raw_lines)\n",
    "        line_lengths = [len(x) for x in raw_lines]\n",
    "\n",
    "        # Output info as a dictionary\n",
    "        result = {\n",
    "            'script':script[:-5],\n",
    "            'lines':line_count,\n",
    "            'chars':char_count,\n",
    "            'max_length':max(line_lengths),\n",
    "            'avg_length':sum(line_lengths)/len(line_lengths),\n",
    "        }\n",
    "        result.update(char_counter)\n",
    "\n",
    "        # Append ``result`` to df\n",
    "        df = df.append(result, ignore_index=True)\n",
    "    except:\n",
    "        print(\"Error parsing {}\".format(script[:-5]))\n",
    "        \n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-03-29T16:52:41.076836Z",
     "start_time": "2018-03-29T16:52:41.072177Z"
    }
   },
   "outputs": [],
   "source": [
    "stats = df[['avg_length','chars','lines','max_length','script']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-03-29T17:16:39.632581Z",
     "start_time": "2018-03-29T17:16:39.627433Z"
    }
   },
   "outputs": [],
   "source": [
    "chars = df.columns.values.tolist()\n",
    "for x in stats.columns.values.tolist():\n",
    "    chars.remove(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-03-29T17:12:47.163281Z",
     "start_time": "2018-03-29T17:12:46.444551Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x119129e80>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib import pyplot as plt\n",
    "\n",
    "fig = plt.figure(figsize=(9.6, 5.4), dpi=200)\n",
    "ax1 = plt.subplot(221)\n",
    "ax2 = plt.subplot(222)\n",
    "ax3 = plt.subplot(223)\n",
    "ax4 = plt.subplot(224)\n",
    "\n",
    "stats['lines'].hist(ax=ax1, bins=25)\n",
    "stats['chars'].hist(ax=ax3, bins=25)\n",
    "stats[stats['avg_length'] < 500]['avg_length'].hist(ax=ax2, bins=25)\n",
    "stats[stats['max_length'] < 500]['max_length'].hist(ax=ax4, bins=25)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-03-29T17:41:59.350605Z",
     "start_time": "2018-03-29T17:41:59.336070Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2    78.988517\n",
       "0    70.846525\n",
       "é    67.232394\n",
       "    60.307692\n",
       "3    55.652216\n",
       "q    55.368814\n",
       "4    51.637245\n",
       "5    50.627432\n",
       "9    50.493177\n",
       "­    48.677419\n",
       "6    47.047619\n",
       "Z    45.828685\n",
       "7    45.038000\n",
       "Á    44.750000\n",
       "8    44.680830\n",
       "    44.600000\n",
       "î    41.777778\n",
       "Î    41.666667\n",
       "ô    40.454545\n",
       "«    37.500000\n",
       "·    34.333333\n",
       "Ñ    33.333333\n",
       "ç    32.818182\n",
       "ù    32.166667\n",
       "»    28.444444\n",
       "dtype: float64"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[chars].mean(axis=0).sort_values(ascending=False)[75:100]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "hide_input": false,
  "kernelspec": {
   "display_name": "Python [conda root]",
   "language": "python",
   "name": "conda-root-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.4"
  },
  "varInspector": {
   "cols": {
    "lenName": 16,
    "lenType": 16,
    "lenVar": 40
   },
   "kernels_config": {
    "python": {
     "delete_cmd_postfix": "",
     "delete_cmd_prefix": "del ",
     "library": "var_list.py",
     "varRefreshCmd": "print(var_dic_list())"
    },
    "r": {
     "delete_cmd_postfix": ") ",
     "delete_cmd_prefix": "rm(",
     "library": "var_list.r",
     "varRefreshCmd": "cat(var_dic_list()) "
    }
   },
   "types_to_exclude": [
    "module",
    "function",
    "builtin_function_or_method",
    "instance",
    "_Feature"
   ],
   "window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}