rotten-tomatoes/rotten tomatoes score scraper.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting git+https://github.com/akamhy/waybackpy.git\n",
      "  Cloning https://github.com/akamhy/waybackpy.git to /tmp/pip-req-build-e61sgjvv\n",
      "Requirement already satisfied (use --upgrade to upgrade): waybackpy==2.4.2 from git+https://github.com/akamhy/waybackpy.git in /opt/conda/lib/python3.8/site-packages\n",
      "Requirement already satisfied: requests in /opt/conda/lib/python3.8/site-packages (from waybackpy==2.4.2) (2.25.1)\n",
      "Requirement already satisfied: certifi>=2017.4.17 in /opt/conda/lib/python3.8/site-packages (from requests->waybackpy==2.4.2) (2019.11.28)\n",
      "Requirement already satisfied: chardet<5,>=3.0.2 in /opt/conda/lib/python3.8/site-packages (from requests->waybackpy==2.4.2) (3.0.4)\n",
      "Requirement already satisfied: idna<3,>=2.5 in /opt/conda/lib/python3.8/site-packages (from requests->waybackpy==2.4.2) (2.8)\n",
      "Requirement already satisfied: urllib3<1.27,>=1.21.1 in /opt/conda/lib/python3.8/site-packages (from requests->waybackpy==2.4.2) (1.25.7)\n",
      "Building wheels for collected packages: waybackpy\n",
      "  Building wheel for waybackpy (setup.py) ... \u001b[?25ldone\n",
      "\u001b[?25h  Created wheel for waybackpy: filename=waybackpy-2.4.2-py3-none-any.whl size=21204 sha256=4b3aa9dbc2ff63c88d8868d3d07ecd526cf5e59f5aac1919293bb5319de1b3e4\n",
      "  Stored in directory: /tmp/pip-ephem-wheel-cache-am6lhmjm/wheels/82/0d/a7/6c38a890cf03c2cae59ff65b5b128f82054db3c373179e6d95\n",
      "Successfully built waybackpy\n"
     ]
    }
   ],
   "source": [
    "!pip install git+https://github.com/akamhy/waybackpy.git"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import urllib\n",
    "from urllib.request import urlopen\n",
    "from bs4 import BeautifulSoup\n",
    "import datetime\n",
    "import requests\n",
    "import waybackpy\n",
    "import pandas as pd\n",
    "\n",
    "user_agent = \"Mozilla/5.0 (Windows NT 5.1; rv:40.0) Gecko/20100101 Firefox/40.0\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "#2018 scraper\n",
    "\n",
    "def get_score(soup):\n",
    "    critic = soup.find('span', {'class': \"meter-value superPageFontColor\"})\n",
    "    audience = soup.find('div', {'class': \"audience-score meter\"}).find('span', {'class': \"superPageFontColor\"})\n",
    "    return [critic.text, audience.text]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "#2019-21 scraper\n",
    "def getScore(soup):\n",
    "    temp = soup.find_all('div', class_='mop-ratings-wrap__half')\n",
    "    try:\n",
    "        critic = temp[0].text.strip().replace('\\n', '').split(' ')[0] #2020 scraper        \n",
    "        if len(temp) > 1:\n",
    "            audience = temp[1].text.strip().replace('\\n', '').split(' ')[0]\n",
    "        else:\n",
    "            audience = \"Coming\"\n",
    "    except:\n",
    "        scores = soup.find(\"score-board\") #2021 scraper\n",
    "        return [scores[\"tomatometerscore\"], scores[\"audiencescore\"]]\n",
    "    return [critic, audience]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "#get number of critic and audience reviews\n",
    "def getNumReviews(soup):        \n",
    "    critic = soup.find_all(\"small\", class_=\"mop-ratings-wrap__text--small\")\n",
    "    audience = soup.find_all(\"strong\", class_=\"mop-ratings-wrap__text--small\")\n",
    "    if critic:\n",
    "        critic = critic[0].text.replace(\"\\n\", '').strip()\n",
    "    else:\n",
    "        critic = soup.find_all(\"a\", class_='scoreboard__link scoreboard__link--tomatometer')\n",
    "        critic = critic[0].text\n",
    "    if len(audience) > 1:\n",
    "        audience = audience[1].text.replace(\"Verified Ratings: \", '')\n",
    "    else:\n",
    "        audience = soup.find_all(\"a\", class_='scoreboard__link scoreboard__link--audience')\n",
    "        if audience:\n",
    "            audience = audience[0].text\n",
    "        else:    \n",
    "            audience = \"Coming\"\n",
    "    return [critic, audience]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "movie_urls = {'Wonder Woman 1984': 'https://www.rottentomatoes.com/m/wonder_woman_1984/', \n",
    "              'Soul':'https://www.rottentomatoes.com/m/soul_2020/', \n",
    "              'Mulan': 'https://www.rottentomatoes.com/m/mulan_2020/',\n",
    "              'Birds of Prey': 'https://www.rottentomatoes.com/m/birds_of_prey_2020/',\n",
    "              'Sonic': 'https://www.rottentomatoes.com/m/sonic_the_hedgehog_2020/'\n",
    "             }\n",
    "\n",
    "movie_urls[\"Captain Marvel\"] = \"https://www.rottentomatoes.com/m/captain_marvel/\"\n",
    "movie_urls[\"Lion King\"] = \"https://www.rottentomatoes.com/m/the_lion_king_2019/\"\n",
    "movie_urls[\"Aladdin\"] = \"https://www.rottentomatoes.com/m/aladdin/\"\n",
    "movie_urls[\"Joker\"] = \"https://www.rottentomatoes.com/m/joker_2019/\"\n",
    "movie_urls[\"Shazam!\"] = \"https://www.rottentomatoes.com/m/shazam/\"\n",
    "movie_urls[\"Godzilla: King of the Monsters\"] = \"https://www.rottentomatoes.com/m/godzilla_king_of_the_monsters_2019/\"\n",
    "\n",
    "movie_urls['Tenet'] = 'https://www.rottentomatoes.com/m/tenet/'\n",
    "movie_urls['Scoob'] = 'https://www.rottentomatoes.com/m/scoob/'\n",
    "movie_urls['The Marksman'] = 'https://www.rottentomatoes.com/m/the_marksman_2021/'\n",
    "movie_urls['Artemis Fowl'] = 'https://www.rottentomatoes.com/m/artemis_fowl/'\n",
    "movie_urls['Lovebirds'] = 'https://www.rottentomatoes.com/m/the_lovebirds_2020/'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "#for 2019-21\n",
    "def build(key, date1, date2):\n",
    "    dates = pd.date_range(date1, date2).tolist()\n",
    "    wayback = waybackpy.Url(movie_urls[key], user_agent)\n",
    "    scores = []\n",
    "    for date in dates:\n",
    "        try:\n",
    "            archived = wayback.near(year=date.year, month=date.month, day=date.day).archive_url\n",
    "        except:\n",
    "            print(date)\n",
    "            continue\n",
    "        page = requests.get(archived).text\n",
    "        soup = BeautifulSoup(page, 'lxml')\n",
    "        scores.append(getScore(soup) + getNumReviews(soup) + [date, key])\n",
    "    return scores"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "#for 2017-18\n",
    "def build2(key, date1, date2):\n",
    "    dates = pd.date_range(date1, date2).tolist()\n",
    "    wayback = waybackpy.Url(movie_urls[key], user_agent)\n",
    "    scores = []\n",
    "    for date in dates:\n",
    "        try:\n",
    "            archived = wayback.near(year=date.year, month=date.month, day=date.day).archive_url\n",
    "        except:\n",
    "            print(date)\n",
    "            continue\n",
    "        page = requests.get(archived).text\n",
    "        soup = BeautifulSoup(page, 'lxml')\n",
    "        scores.append(get_score(soup) + getNumReviews(soup) + [date, key])\n",
    "    return scores"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2019-11-28 00:00:00\n",
      "2019-11-29 00:00:00\n",
      "2019-12-05 00:00:00\n",
      "2019-12-15 00:00:00\n",
      "2019-12-21 00:00:00\n",
      "2020-01-11 00:00:00\n",
      "2020-02-04 00:00:00\n",
      "2020-02-12 00:00:00\n",
      "2020-02-13 00:00:00\n",
      "2020-02-19 00:00:00\n",
      "2020-02-20 00:00:00\n",
      "2020-02-21 00:00:00\n",
      "2020-03-04 00:00:00\n",
      "2020-03-11 00:00:00\n",
      "2020-03-12 00:00:00\n",
      "2020-03-19 00:00:00\n",
      "2020-03-22 00:00:00\n",
      "2020-03-23 00:00:00\n",
      "2020-03-27 00:00:00\n",
      "2020-03-29 00:00:00\n",
      "2020-04-14 00:00:00\n",
      "2020-07-12 00:00:00\n"
     ]
    },
    {
     "data": {
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       "  'Ratings: Not yet available',\n",
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       "  'Joker'],\n",
       " ['77%',\n",
       "  'Coming',\n",
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       "  'Ratings: Not yet available',\n",
       "  Timestamp('2019-09-28 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['77%',\n",
       "  'Coming',\n",
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       "  'Ratings: Not yet available',\n",
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       "  'Joker'],\n",
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       "  'Joker'],\n",
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       "  Timestamp('2019-10-17 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
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       "  Timestamp('2019-10-18 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
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       "  '489',\n",
       "  '48,102',\n",
       "  Timestamp('2019-10-19 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
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       "  '48,102',\n",
       "  Timestamp('2019-10-20 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
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       "  '49,895',\n",
       "  Timestamp('2019-10-21 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
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       "  '50,604',\n",
       "  Timestamp('2019-10-23 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['69%',\n",
       "  '89%',\n",
       "  '500',\n",
       "  '53,408',\n",
       "  Timestamp('2019-10-24 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['69%',\n",
       "  '89%',\n",
       "  '500',\n",
       "  '53,408',\n",
       "  Timestamp('2019-10-25 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['69%',\n",
       "  '89%',\n",
       "  '500',\n",
       "  '53,408',\n",
       "  Timestamp('2019-10-26 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['69%',\n",
       "  '89%',\n",
       "  '500',\n",
       "  '54,263',\n",
       "  Timestamp('2019-10-27 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['69%',\n",
       "  '89%',\n",
       "  '500',\n",
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       "  Timestamp('2020-06-06 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '554',\n",
       "  '66,291',\n",
       "  Timestamp('2020-06-07 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '554',\n",
       "  '66,291',\n",
       "  Timestamp('2020-06-08 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '554',\n",
       "  '66,291',\n",
       "  Timestamp('2020-06-09 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '554',\n",
       "  '66,291',\n",
       "  Timestamp('2020-06-10 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '554',\n",
       "  '66,291',\n",
       "  Timestamp('2020-06-11 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
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       "  '88%',\n",
       "  '554',\n",
       "  '66,291',\n",
       "  Timestamp('2020-06-12 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '554',\n",
       "  '66,291',\n",
       "  Timestamp('2020-06-13 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
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       "  '88%',\n",
       "  '554',\n",
       "  '66,291',\n",
       "  Timestamp('2020-06-14 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
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       "  '554',\n",
       "  '66,291',\n",
       "  Timestamp('2020-06-15 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
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       "  '88%',\n",
       "  '554',\n",
       "  '66,291',\n",
       "  Timestamp('2020-06-16 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '554',\n",
       "  '66,291',\n",
       "  Timestamp('2020-06-17 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
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       "  '554',\n",
       "  '66,291',\n",
       "  Timestamp('2020-06-18 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '554',\n",
       "  '66,291',\n",
       "  Timestamp('2020-06-19 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
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       "  '88%',\n",
       "  '554',\n",
       "  '66,291',\n",
       "  Timestamp('2020-06-20 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
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       "  '88%',\n",
       "  '554',\n",
       "  '66,291',\n",
       "  Timestamp('2020-06-21 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
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       "  '88%',\n",
       "  '554',\n",
       "  '66,291',\n",
       "  Timestamp('2020-06-22 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
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       "  '88%',\n",
       "  '554',\n",
       "  '66,291',\n",
       "  Timestamp('2020-06-23 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '554',\n",
       "  '66,291',\n",
       "  Timestamp('2020-06-24 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '554',\n",
       "  '66,291',\n",
       "  Timestamp('2020-06-25 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '554',\n",
       "  '66,291',\n",
       "  Timestamp('2020-06-26 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '554',\n",
       "  '66,291',\n",
       "  Timestamp('2020-06-27 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '554',\n",
       "  '66,291',\n",
       "  Timestamp('2020-06-28 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '554',\n",
       "  '66,291',\n",
       "  Timestamp('2020-06-29 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
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       "  '88%',\n",
       "  '554',\n",
       "  '66,291',\n",
       "  Timestamp('2020-06-30 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
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       "  '88%',\n",
       "  '563',\n",
       "  '66,292',\n",
       "  Timestamp('2020-07-01 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '563',\n",
       "  '66,292',\n",
       "  Timestamp('2020-07-02 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '563',\n",
       "  '66,292',\n",
       "  Timestamp('2020-07-03 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '563',\n",
       "  '66,292',\n",
       "  Timestamp('2020-07-04 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '563',\n",
       "  '66,292',\n",
       "  Timestamp('2020-07-05 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '563',\n",
       "  '66,292',\n",
       "  Timestamp('2020-07-06 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
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       "  '563',\n",
       "  '66,292',\n",
       "  Timestamp('2020-07-07 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '563',\n",
       "  '66,292',\n",
       "  Timestamp('2020-07-08 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '563',\n",
       "  '66,292',\n",
       "  Timestamp('2020-07-09 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '563',\n",
       "  '66,292',\n",
       "  Timestamp('2020-07-10 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '563',\n",
       "  '66,292',\n",
       "  Timestamp('2020-07-11 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '563',\n",
       "  '66,292',\n",
       "  Timestamp('2020-07-13 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '563',\n",
       "  '66,292',\n",
       "  Timestamp('2020-07-14 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '563',\n",
       "  '66,292',\n",
       "  Timestamp('2020-07-15 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '563',\n",
       "  '66,292',\n",
       "  Timestamp('2020-07-16 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '563',\n",
       "  '66,292',\n",
       "  Timestamp('2020-07-17 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '563',\n",
       "  '66,292',\n",
       "  Timestamp('2020-07-18 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '563',\n",
       "  '66,292',\n",
       "  Timestamp('2020-07-19 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '563',\n",
       "  '66,292',\n",
       "  Timestamp('2020-07-20 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '563',\n",
       "  '66,292',\n",
       "  Timestamp('2020-07-21 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
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       "  '563',\n",
       "  '66,292',\n",
       "  Timestamp('2020-07-22 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '563',\n",
       "  '66,292',\n",
       "  Timestamp('2020-07-23 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '563',\n",
       "  '66,292',\n",
       "  Timestamp('2020-07-24 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
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       "  '563',\n",
       "  '66,292',\n",
       "  Timestamp('2020-07-25 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '563',\n",
       "  '66,292',\n",
       "  Timestamp('2020-07-26 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '563',\n",
       "  '66,292',\n",
       "  Timestamp('2020-07-27 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '563',\n",
       "  '66,292',\n",
       "  Timestamp('2020-07-28 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '563',\n",
       "  '66,292',\n",
       "  Timestamp('2020-07-29 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '563',\n",
       "  '66,292',\n",
       "  Timestamp('2020-07-30 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '563',\n",
       "  '66,292',\n",
       "  Timestamp('2020-07-31 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '568',\n",
       "  '66,293',\n",
       "  Timestamp('2020-08-01 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '568',\n",
       "  '66,293',\n",
       "  Timestamp('2020-08-02 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '568',\n",
       "  '66,293',\n",
       "  Timestamp('2020-08-03 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '568',\n",
       "  '66,293',\n",
       "  Timestamp('2020-08-04 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '568',\n",
       "  '66,293',\n",
       "  Timestamp('2020-08-05 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '568',\n",
       "  '66,293',\n",
       "  Timestamp('2020-08-06 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '568',\n",
       "  '66,293',\n",
       "  Timestamp('2020-08-07 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '568',\n",
       "  '66,293',\n",
       "  Timestamp('2020-08-08 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '568',\n",
       "  '66,293',\n",
       "  Timestamp('2020-08-09 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '568',\n",
       "  '66,293',\n",
       "  Timestamp('2020-08-10 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '568',\n",
       "  '66,293',\n",
       "  Timestamp('2020-08-11 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '568',\n",
       "  '66,293',\n",
       "  Timestamp('2020-08-12 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '568',\n",
       "  '66,293',\n",
       "  Timestamp('2020-08-13 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '568',\n",
       "  '66,293',\n",
       "  Timestamp('2020-08-14 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '568',\n",
       "  '66,293',\n",
       "  Timestamp('2020-08-15 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '568',\n",
       "  '66,293',\n",
       "  Timestamp('2020-08-16 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '568',\n",
       "  '66,293',\n",
       "  Timestamp('2020-08-17 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '568',\n",
       "  '66,293',\n",
       "  Timestamp('2020-08-18 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '568',\n",
       "  '66,293',\n",
       "  Timestamp('2020-08-19 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '568',\n",
       "  '66,293',\n",
       "  Timestamp('2020-08-20 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '568',\n",
       "  '66,293',\n",
       "  Timestamp('2020-08-21 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '568',\n",
       "  '66,293',\n",
       "  Timestamp('2020-08-22 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '568',\n",
       "  '66,293',\n",
       "  Timestamp('2020-08-23 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '568',\n",
       "  '66,293',\n",
       "  Timestamp('2020-08-24 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '568',\n",
       "  '66,293',\n",
       "  Timestamp('2020-08-25 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '568',\n",
       "  '66,293',\n",
       "  Timestamp('2020-08-26 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '568',\n",
       "  '66,293',\n",
       "  Timestamp('2020-08-27 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '568',\n",
       "  '66,293',\n",
       "  Timestamp('2020-08-28 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '568',\n",
       "  '66,293',\n",
       "  Timestamp('2020-08-29 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '568',\n",
       "  '66,293',\n",
       "  Timestamp('2020-08-30 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '568',\n",
       "  '66,293',\n",
       "  Timestamp('2020-08-31 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['68%',\n",
       "  '88%',\n",
       "  '568',\n",
       "  '66,293',\n",
       "  Timestamp('2020-09-01 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['69%',\n",
       "  '88%',\n",
       "  '572',\n",
       "  '66,299',\n",
       "  Timestamp('2020-09-02 00:00:00', freq='D'),\n",
       "  'Joker'],\n",
       " ['69%',\n",
       "  '88%',\n",
       "  '572',\n",
       "  '66,299',\n",
       "  Timestamp('2020-09-03 00:00:00', freq='D'),\n",
       "  'Joker']]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "joker = build(\"Joker\", '2019-09-03', '2020-09-03')\n",
    "joker"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2019-07-05 00:00:00\n",
      "2019-07-24 00:00:00\n",
      "2019-09-05 00:00:00\n",
      "2019-10-17 00:00:00\n",
      "2019-11-17 00:00:00\n",
      "2019-12-06 00:00:00\n",
      "2019-12-14 00:00:00\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[['84%',\n",
       "  'Audience',\n",
       "  '170',\n",
       "  'User Ratings: ',\n",
       "  Timestamp('2019-03-06 00:00:00', freq='D'),\n",
       "  'Captain Marvel'],\n",
       " ['82%',\n",
       "  'Audience',\n",
       "  '229',\n",
       "  'User Ratings: ',\n",
       "  Timestamp('2019-03-07 00:00:00', freq='D'),\n",
       "  'Captain Marvel'],\n",
       " ['81%',\n",
       "  '35%',\n",
       "  '289',\n",
       "  'liked it',\n",
       "  Timestamp('2019-03-08 00:00:00', freq='D'),\n",
       "  'Captain Marvel'],\n",
       " ['79%',\n",
       "  '53%',\n",
       "  '333',\n",
       "  'liked it',\n",
       "  Timestamp('2019-03-09 00:00:00', freq='D'),\n",
       "  'Captain Marvel'],\n",
       " ['80%',\n",
       "  '57%',\n",
       "  '350',\n",
       "  'liked it',\n",
       "  Timestamp('2019-03-10 00:00:00', freq='D'),\n",
       "  'Captain Marvel'],\n",
       " ['80%',\n",
       "  '59%',\n",
       "  '378',\n",
       "  'liked it',\n",
       "  Timestamp('2019-03-11 00:00:00', freq='D'),\n",
       "  'Captain Marvel'],\n",
       " ['80%',\n",
       "  '61%',\n",
       "  '395',\n",
       "  'liked it',\n",
       "  Timestamp('2019-03-12 00:00:00', freq='D'),\n",
       "  'Captain Marvel'],\n",
       " ['79%',\n",
       "  '63%',\n",
       "  '406',\n",
       "  'liked it',\n",
       "  Timestamp('2019-03-13 00:00:00', freq='D'),\n",
       "  'Captain Marvel'],\n",
       " ['79%',\n",
       "  '62%',\n",
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       "  'liked it',\n",
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       "  '504',\n",
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       "  '504',\n",
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       "  Timestamp('2020-02-28 00:00:00', freq='D'),\n",
       "  'Captain Marvel'],\n",
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       "  '504',\n",
       "  'User Ratings: 94,467',\n",
       "  Timestamp('2020-02-29 00:00:00', freq='D'),\n",
       "  'Captain Marvel'],\n",
       " ['78%',\n",
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       "  '504',\n",
       "  'User Ratings: 94,467',\n",
       "  Timestamp('2020-03-01 00:00:00', freq='D'),\n",
       "  'Captain Marvel'],\n",
       " ['78%',\n",
       "  '48%',\n",
       "  '504',\n",
       "  'User Ratings: 94,467',\n",
       "  Timestamp('2020-03-02 00:00:00', freq='D'),\n",
       "  'Captain Marvel'],\n",
       " ['78%',\n",
       "  '48%',\n",
       "  '504',\n",
       "  'User Ratings: 94,467',\n",
       "  Timestamp('2020-03-03 00:00:00', freq='D'),\n",
       "  'Captain Marvel'],\n",
       " ['78%',\n",
       "  '48%',\n",
       "  '504',\n",
       "  'User Ratings: 94,467',\n",
       "  Timestamp('2020-03-04 00:00:00', freq='D'),\n",
       "  'Captain Marvel'],\n",
       " ['78%',\n",
       "  '48%',\n",
       "  '504',\n",
       "  'User Ratings: 94,467',\n",
       "  Timestamp('2020-03-05 00:00:00', freq='D'),\n",
       "  'Captain Marvel'],\n",
       " ['78%',\n",
       "  '48%',\n",
       "  '504',\n",
       "  'User Ratings: 94,467',\n",
       "  Timestamp('2020-03-06 00:00:00', freq='D'),\n",
       "  'Captain Marvel']]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "captain = build(\"Captain Marvel\", '2019-03-06', '2020-03-06')\n",
    "captain"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  Timestamp('2020-06-21 00:00:00', freq='D'),\n",
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       "  Timestamp('2020-06-22 00:00:00', freq='D'),\n",
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       "  'Lion King'],\n",
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       "  Timestamp('2020-07-03 00:00:00', freq='D'),\n",
       "  'Lion King'],\n",
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       "  '88%',\n",
       "  '411',\n",
       "  '76,335',\n",
       "  Timestamp('2020-07-04 00:00:00', freq='D'),\n",
       "  'Lion King'],\n",
       " ['53%',\n",
       "  '88%',\n",
       "  '411',\n",
       "  '76,335',\n",
       "  Timestamp('2020-07-05 00:00:00', freq='D'),\n",
       "  'Lion King'],\n",
       " ['53%',\n",
       "  '88%',\n",
       "  '412',\n",
       "  '76,335',\n",
       "  Timestamp('2020-07-06 00:00:00', freq='D'),\n",
       "  'Lion King'],\n",
       " ['53%',\n",
       "  '88%',\n",
       "  '412',\n",
       "  '76,335',\n",
       "  Timestamp('2020-07-07 00:00:00', freq='D'),\n",
       "  'Lion King'],\n",
       " ['53%',\n",
       "  '88%',\n",
       "  '412',\n",
       "  '76,335',\n",
       "  Timestamp('2020-07-08 00:00:00', freq='D'),\n",
       "  'Lion King'],\n",
       " ['53%',\n",
       "  '88%',\n",
       "  '412',\n",
       "  '76,335',\n",
       "  Timestamp('2020-07-09 00:00:00', freq='D'),\n",
       "  'Lion King'],\n",
       " ['53%',\n",
       "  '88%',\n",
       "  '412',\n",
       "  '76,335',\n",
       "  Timestamp('2020-07-10 00:00:00', freq='D'),\n",
       "  'Lion King'],\n",
       " ['53%',\n",
       "  '88%',\n",
       "  '412',\n",
       "  '76,335',\n",
       "  Timestamp('2020-07-11 00:00:00', freq='D'),\n",
       "  'Lion King']]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lion = build(\"Lion King\", '2019-07-11', '2020-07-11')\n",
    "lion"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2019-06-30 00:00:00\n",
      "2019-08-03 00:00:00\n",
      "2019-09-08 00:00:00\n",
      "2020-03-28 00:00:00\n"
     ]
    },
    {
     "data": {
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       "  '362',\n",
       "  '59,041',\n",
       "  Timestamp('2020-05-23 00:00:00', freq='D'),\n",
       "  'Aladdin']]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "aladdin = build(\"Aladdin\", '2019-05-23', '2020-05-23')\n",
    "aladdin"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2019-04-03 00:00:00\n",
      "2019-04-09 00:00:00\n",
      "2019-06-14 00:00:00\n",
      "2019-09-09 00:00:00\n",
      "2019-09-20 00:00:00\n",
      "2019-09-21 00:00:00\n",
      "2020-01-04 00:00:00\n",
      "2020-01-07 00:00:00\n",
      "2020-01-10 00:00:00\n"
     ]
    },
    {
     "data": {
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       "  Timestamp('2020-01-25 00:00:00', freq='D'),\n",
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       "  Timestamp('2020-01-26 00:00:00', freq='D'),\n",
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       "  Timestamp('2020-01-28 00:00:00', freq='D'),\n",
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       "  Timestamp('2020-01-29 00:00:00', freq='D'),\n",
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       "  Timestamp('2020-01-31 00:00:00', freq='D'),\n",
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       "  Timestamp('2020-02-01 00:00:00', freq='D'),\n",
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       "  'User Ratings: 16,343',\n",
       "  Timestamp('2020-02-03 00:00:00', freq='D'),\n",
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       "  'User Ratings: 16,343',\n",
       "  Timestamp('2020-02-04 00:00:00', freq='D'),\n",
       "  'Shazam!'],\n",
       " ['90%',\n",
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       "  Timestamp('2020-02-07 00:00:00', freq='D'),\n",
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       "  Timestamp('2020-02-10 00:00:00', freq='D'),\n",
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       "  'User Ratings: 16,343',\n",
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       "  Timestamp('2020-02-16 00:00:00', freq='D'),\n",
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       "  Timestamp('2020-02-17 00:00:00', freq='D'),\n",
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       "  'User Ratings: 16,343',\n",
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       "  '392',\n",
       "  'User Ratings: 16,343',\n",
       "  Timestamp('2020-02-19 00:00:00', freq='D'),\n",
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       " ['90%',\n",
       "  '83%',\n",
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       "  'User Ratings: 16,343',\n",
       "  Timestamp('2020-02-20 00:00:00', freq='D'),\n",
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       " ['90%',\n",
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       "  'User Ratings: 16,343',\n",
       "  Timestamp('2020-02-21 00:00:00', freq='D'),\n",
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       " ['90%',\n",
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       "  '392',\n",
       "  'User Ratings: 16,343',\n",
       "  Timestamp('2020-02-22 00:00:00', freq='D'),\n",
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       " ['90%',\n",
       "  '83%',\n",
       "  '392',\n",
       "  'User Ratings: 16,343',\n",
       "  Timestamp('2020-02-23 00:00:00', freq='D'),\n",
       "  'Shazam!'],\n",
       " ['90%',\n",
       "  '83%',\n",
       "  '392',\n",
       "  'User Ratings: 16,343',\n",
       "  Timestamp('2020-02-24 00:00:00', freq='D'),\n",
       "  'Shazam!'],\n",
       " ['90%',\n",
       "  '83%',\n",
       "  '392',\n",
       "  'User Ratings: 16,343',\n",
       "  Timestamp('2020-02-25 00:00:00', freq='D'),\n",
       "  'Shazam!'],\n",
       " ['90%',\n",
       "  '83%',\n",
       "  '392',\n",
       "  'User Ratings: 16,343',\n",
       "  Timestamp('2020-02-26 00:00:00', freq='D'),\n",
       "  'Shazam!'],\n",
       " ['90%',\n",
       "  '83%',\n",
       "  '392',\n",
       "  'User Ratings: 16,343',\n",
       "  Timestamp('2020-02-27 00:00:00', freq='D'),\n",
       "  'Shazam!'],\n",
       " ['90%',\n",
       "  '83%',\n",
       "  '392',\n",
       "  'User Ratings: 16,343',\n",
       "  Timestamp('2020-02-28 00:00:00', freq='D'),\n",
       "  'Shazam!'],\n",
       " ['90%',\n",
       "  '83%',\n",
       "  '392',\n",
       "  'User Ratings: 16,343',\n",
       "  Timestamp('2020-02-29 00:00:00', freq='D'),\n",
       "  'Shazam!'],\n",
       " ['90%',\n",
       "  '83%',\n",
       "  '392',\n",
       "  'User Ratings: 16,343',\n",
       "  Timestamp('2020-03-01 00:00:00', freq='D'),\n",
       "  'Shazam!'],\n",
       " ['90%',\n",
       "  '83%',\n",
       "  '392',\n",
       "  'User Ratings: 16,343',\n",
       "  Timestamp('2020-03-02 00:00:00', freq='D'),\n",
       "  'Shazam!'],\n",
       " ['90%',\n",
       "  '83%',\n",
       "  '392',\n",
       "  'User Ratings: 16,343',\n",
       "  Timestamp('2020-03-03 00:00:00', freq='D'),\n",
       "  'Shazam!'],\n",
       " ['90%',\n",
       "  '83%',\n",
       "  '392',\n",
       "  'User Ratings: 16,343',\n",
       "  Timestamp('2020-03-04 00:00:00', freq='D'),\n",
       "  'Shazam!'],\n",
       " ['90%',\n",
       "  '83%',\n",
       "  '392',\n",
       "  'User Ratings: 16,343',\n",
       "  Timestamp('2020-03-05 00:00:00', freq='D'),\n",
       "  'Shazam!'],\n",
       " ['90%',\n",
       "  '83%',\n",
       "  '392',\n",
       "  'User Ratings: 16,343',\n",
       "  Timestamp('2020-03-06 00:00:00', freq='D'),\n",
       "  'Shazam!'],\n",
       " ['90%',\n",
       "  '83%',\n",
       "  '392',\n",
       "  'User Ratings: 16,343',\n",
       "  Timestamp('2020-03-07 00:00:00', freq='D'),\n",
       "  'Shazam!'],\n",
       " ['90%',\n",
       "  '83%',\n",
       "  '392',\n",
       "  'User Ratings: 16,343',\n",
       "  Timestamp('2020-03-08 00:00:00', freq='D'),\n",
       "  'Shazam!'],\n",
       " ['90%',\n",
       "  '83%',\n",
       "  '392',\n",
       "  'User Ratings: 16,343',\n",
       "  Timestamp('2020-03-09 00:00:00', freq='D'),\n",
       "  'Shazam!'],\n",
       " ['90%',\n",
       "  '83%',\n",
       "  '392',\n",
       "  'User Ratings: 16,343',\n",
       "  Timestamp('2020-03-10 00:00:00', freq='D'),\n",
       "  'Shazam!'],\n",
       " ['90%',\n",
       "  '83%',\n",
       "  '392',\n",
       "  'User Ratings: 16,343',\n",
       "  Timestamp('2020-03-11 00:00:00', freq='D'),\n",
       "  'Shazam!'],\n",
       " ['90%',\n",
       "  '83%',\n",
       "  '392',\n",
       "  'User Ratings: 16,343',\n",
       "  Timestamp('2020-03-12 00:00:00', freq='D'),\n",
       "  'Shazam!'],\n",
       " ['90%',\n",
       "  '83%',\n",
       "  '392',\n",
       "  'User Ratings: 16,343',\n",
       "  Timestamp('2020-03-13 00:00:00', freq='D'),\n",
       "  'Shazam!'],\n",
       " ['90%',\n",
       "  '83%',\n",
       "  '392',\n",
       "  'User Ratings: 16,343',\n",
       "  Timestamp('2020-03-14 00:00:00', freq='D'),\n",
       "  'Shazam!'],\n",
       " ['90%',\n",
       "  '83%',\n",
       "  '392',\n",
       "  'User Ratings: 16,343',\n",
       "  Timestamp('2020-03-15 00:00:00', freq='D'),\n",
       "  'Shazam!'],\n",
       " ['90%',\n",
       "  '83%',\n",
       "  '392',\n",
       "  'User Ratings: 16,385',\n",
       "  Timestamp('2020-03-16 00:00:00', freq='D'),\n",
       "  'Shazam!'],\n",
       " ['90%',\n",
       "  '83%',\n",
       "  '392',\n",
       "  'User Ratings: 16,385',\n",
       "  Timestamp('2020-03-17 00:00:00', freq='D'),\n",
       "  'Shazam!'],\n",
       " ['90%',\n",
       "  '83%',\n",
       "  '392',\n",
       "  'User Ratings: 16,385',\n",
       "  Timestamp('2020-03-18 00:00:00', freq='D'),\n",
       "  'Shazam!'],\n",
       " ['90%',\n",
       "  '83%',\n",
       "  '392',\n",
       "  'User Ratings: 16,385',\n",
       "  Timestamp('2020-03-19 00:00:00', freq='D'),\n",
       "  'Shazam!'],\n",
       " ['90%',\n",
       "  '83%',\n",
       "  '392',\n",
       "  'User Ratings: 16,385',\n",
       "  Timestamp('2020-03-20 00:00:00', freq='D'),\n",
       "  'Shazam!'],\n",
       " ['90%',\n",
       "  '83%',\n",
       "  '392',\n",
       "  'User Ratings: 16,385',\n",
       "  Timestamp('2020-03-21 00:00:00', freq='D'),\n",
       "  'Shazam!'],\n",
       " ['90%',\n",
       "  '83%',\n",
       "  '392',\n",
       "  'User Ratings: 16,385',\n",
       "  Timestamp('2020-03-22 00:00:00', freq='D'),\n",
       "  'Shazam!'],\n",
       " ['90%',\n",
       "  '83%',\n",
       "  '392',\n",
       "  'User Ratings: 16,385',\n",
       "  Timestamp('2020-03-23 00:00:00', freq='D'),\n",
       "  'Shazam!'],\n",
       " ['90%',\n",
       "  '83%',\n",
       "  '392',\n",
       "  'User Ratings: 16,385',\n",
       "  Timestamp('2020-03-24 00:00:00', freq='D'),\n",
       "  'Shazam!']]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "shazam = build(\"Shazam!\", '2019-03-24', '2020-03-24')\n",
    "shazam"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2019-06-03 00:00:00\n",
      "2019-06-24 00:00:00\n",
      "2019-08-04 00:00:00\n",
      "2019-08-15 00:00:00\n",
      "2019-11-10 00:00:00\n",
      "2019-11-22 00:00:00\n",
      "2019-12-20 00:00:00\n",
      "2020-02-24 00:00:00\n"
     ]
    },
    {
     "data": {
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       "  '203',\n",
       "  'Coming',\n",
       "  Timestamp('2019-05-31 00:00:00', freq='D'),\n",
       "  'Godzilla: King of the Monsters'],\n",
       " ['40%',\n",
       "  'Coming',\n",
       "  '217',\n",
       "  'Coming',\n",
       "  Timestamp('2019-06-01 00:00:00', freq='D'),\n",
       "  'Godzilla: King of the Monsters'],\n",
       " ['39%',\n",
       "  'Coming',\n",
       "  '226',\n",
       "  'Coming',\n",
       "  Timestamp('2019-06-02 00:00:00', freq='D'),\n",
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       "  Timestamp('2019-06-04 00:00:00', freq='D'),\n",
       "  'Godzilla: King of the Monsters'],\n",
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       "  Timestamp('2019-06-15 00:00:00', freq='D'),\n",
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       "  'Godzilla: King of the Monsters'],\n",
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       "  'Godzilla: King of the Monsters'],\n",
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       "  Timestamp('2020-05-08 00:00:00', freq='D'),\n",
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       " ['42%',\n",
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       "  '331',\n",
       "  '25,203',\n",
       "  Timestamp('2020-05-09 00:00:00', freq='D'),\n",
       "  'Godzilla: King of the Monsters'],\n",
       " ['42%',\n",
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       "  '331',\n",
       "  '25,203',\n",
       "  Timestamp('2020-05-10 00:00:00', freq='D'),\n",
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       " ['42%',\n",
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       "  '331',\n",
       "  '25,203',\n",
       "  Timestamp('2020-05-11 00:00:00', freq='D'),\n",
       "  'Godzilla: King of the Monsters'],\n",
       " ['42%',\n",
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       "  '331',\n",
       "  '25,203',\n",
       "  Timestamp('2020-05-12 00:00:00', freq='D'),\n",
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       " ['42%',\n",
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       " ['42%',\n",
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       "  Timestamp('2020-05-14 00:00:00', freq='D'),\n",
       "  'Godzilla: King of the Monsters'],\n",
       " ['42%',\n",
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       "  '25,203',\n",
       "  Timestamp('2020-05-15 00:00:00', freq='D'),\n",
       "  'Godzilla: King of the Monsters'],\n",
       " ['42%',\n",
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       "  'Godzilla: King of the Monsters'],\n",
       " ['43%',\n",
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       "  '338',\n",
       "  '25,209',\n",
       "  Timestamp('2020-05-17 00:00:00', freq='D'),\n",
       "  'Godzilla: King of the Monsters'],\n",
       " ['43%',\n",
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       "  '338',\n",
       "  '25,209',\n",
       "  Timestamp('2020-05-18 00:00:00', freq='D'),\n",
       "  'Godzilla: King of the Monsters'],\n",
       " ['43%',\n",
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       "  '338',\n",
       "  '25,209',\n",
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       "  'Godzilla: King of the Monsters'],\n",
       " ['43%',\n",
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       "  '338',\n",
       "  '25,209',\n",
       "  Timestamp('2020-05-20 00:00:00', freq='D'),\n",
       "  'Godzilla: King of the Monsters'],\n",
       " ['43%',\n",
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       "  '338',\n",
       "  '25,209',\n",
       "  Timestamp('2020-05-21 00:00:00', freq='D'),\n",
       "  'Godzilla: King of the Monsters'],\n",
       " ['43%',\n",
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       "  '338',\n",
       "  '25,209',\n",
       "  Timestamp('2020-05-22 00:00:00', freq='D'),\n",
       "  'Godzilla: King of the Monsters'],\n",
       " ['43%',\n",
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       "  '338',\n",
       "  '25,209',\n",
       "  Timestamp('2020-05-23 00:00:00', freq='D'),\n",
       "  'Godzilla: King of the Monsters'],\n",
       " ['43%',\n",
       "  '83%',\n",
       "  '338',\n",
       "  '25,209',\n",
       "  Timestamp('2020-05-24 00:00:00', freq='D'),\n",
       "  'Godzilla: King of the Monsters'],\n",
       " ['43%',\n",
       "  '83%',\n",
       "  '338',\n",
       "  '25,209',\n",
       "  Timestamp('2020-05-25 00:00:00', freq='D'),\n",
       "  'Godzilla: King of the Monsters'],\n",
       " ['43%',\n",
       "  '83%',\n",
       "  '338',\n",
       "  '25,209',\n",
       "  Timestamp('2020-05-26 00:00:00', freq='D'),\n",
       "  'Godzilla: King of the Monsters'],\n",
       " ['43%',\n",
       "  '83%',\n",
       "  '338',\n",
       "  '25,209',\n",
       "  Timestamp('2020-05-27 00:00:00', freq='D'),\n",
       "  'Godzilla: King of the Monsters'],\n",
       " ['43%',\n",
       "  '83%',\n",
       "  '338',\n",
       "  '25,209',\n",
       "  Timestamp('2020-05-28 00:00:00', freq='D'),\n",
       "  'Godzilla: King of the Monsters'],\n",
       " ['43%',\n",
       "  '83%',\n",
       "  '338',\n",
       "  '25,209',\n",
       "  Timestamp('2020-05-29 00:00:00', freq='D'),\n",
       "  'Godzilla: King of the Monsters'],\n",
       " ['43%',\n",
       "  '83%',\n",
       "  '338',\n",
       "  '25,209',\n",
       "  Timestamp('2020-05-30 00:00:00', freq='D'),\n",
       "  'Godzilla: King of the Monsters'],\n",
       " ['43%',\n",
       "  '83%',\n",
       "  '338',\n",
       "  '25,209',\n",
       "  Timestamp('2020-05-31 00:00:00', freq='D'),\n",
       "  'Godzilla: King of the Monsters']]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "godzilla = build(\"Godzilla: King of the Monsters\", '2019-05-31', '2020-05-31')\n",
    "godzilla"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "arr = [captain, joker, lion, aladdin, shazam, godzilla]\n",
    "dfs = []\n",
    "\n",
    "for movie in arr:\n",
    "    dfs.append(pd.DataFrame(movie, columns=[\"critic\", \"audience\", \"criticNum\", \"audienceNum\", \"date\", \"film\"]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "pd.concat(dfs).to_csv('all_films_wayback_2019_reviews.csv',index=False)"
   ]
  }
 ],
 "metadata": {
  "history": [
   {
    "code": "import requests\nimport time\n\n# requirements\nfrom bs4 import BeautifulSoup\nfrom requests import TooManyRedirects\nimport re\n\ndef _make_soup(url):\n    try:\n        r = requests.get(url)\n        soup = BeautifulSoup(r.content, 'html.parser')\n    except TooManyRedirects:\n        soup = ''\n    return soup\n\n#regex patterns\npage_pat = re.compile(r'Page 1 of \\d+')\nreview_pat = re.compile(r'<div class=\\\"the_review\\\" data-qa=\\\"review-text\\\">[;a-zA-Z\\s,-.\\'\\/\\?\\[\\]\\\":\\']*</div>')\nrating_pat = re.compile(r'Original Score:\\s([A-Z](\\+|-)?|\\d(.\\d)?(\\/\\d)?)')\nfresh_pat = re.compile(r'small\\s(fresh|rotten)\\\"')\ncritic_pat = re.compile(r'\\/\\\"\\>([A-Z][a-zA-Z]+\\s[A-Z][a-zA-Z\\-]+)|([A-Z][a-zA-Z.]+\\s[A-Z].?\\s[A-Z][a-zA-Z]+)|([A-Z][a-zA-Z]+\\s[A-Z]+\\'[A-Z][a-zA-Z]+)')\npublisher_pat = re.compile(r'\\\"subtle\\\">[a-zA-Z\\s,.\\(\\)\\'\\-&;!\\/\\d+]+</em>')\ndate_pat = re.compile(r'[a-zA-Z]+\\s\\d+,\\s\\d+')",
    "id": "c5e03962df7f4eb788e0b020cc093cc3",
    "idx": 0,
    "time": "2021-01-25T01:18:09.597Z",
    "type": "execution"
   },
   {
    "id": "c5e03962df7f4eb788e0b020cc093cc3",
    "time": "2021-01-25T01:18:09.848Z",
    "type": "completion"
   },
   {
    "code": "def _get_critic_reviews_from_page(soup):\n    reviews = list()\n    rating = list()\n    fresh = list()\n    critic = list()\n    top_critic = list()\n    publisher = list()\n    date = list()\n    \n    soup = str(soup)\n    review_soup = soup.split('=\"review_table')[1].split('row review_table_row')\n    review_soup.pop(0)\n\n    for review in review_soup:\n        match = re.findall(review_pat, str(review))\n        if len(match) > 0:\n            m = match[0]            \n            for iden in ['<div class=\"the_review\" data-qa=\"review-text\"> ','</div>']:\n                m = m.replace(iden,'')\n            reviews.append(m.strip('\"'))            \n            # extract rating\n            match = re.findall(rating_pat, str(review))\n            if len(match) > 0:\n                m = match[0][0]\n                if '/1' in m:\n                    sp_m = m.split('/')\n                    if sp_m[-1] == '1':\n                        sp_m[-1] = '10'\n                    m = '/'.join(sp_m)\n                rating.append(m)\n            else:\n                rating.append(None)            \n            # extract fresh indicator\n            match = re.findall(fresh_pat, str(review))\n            if len(match) > 0:\n                fresh.append(match[0])\n            else:\n                fresh.append(None)            \n            # extract critic\n            match = re.findall(critic_pat, str(review))\n            if len(match) > 0:\n                critic.append(''.join(match[0]))\n            else:\n                critic.append(None)            \n            # check if top critic\n            if '> Top Critic<' in str(review):\n                top_critic.append(1)\n            else:\n                top_critic.append(0)            \n            # extract publisher\n            match = re.findall(publisher_pat, str(review))\n            if len(match) > 0:\n                m = match[0]\n                m = m.replace('\"subtle\">', '')\n                m = m.replace('</em>','')\n                publisher.append(m)\n            else:\n                publisher.append(None)            \n            # extract date\n            match = re.findall(date_pat, str(review))\n            if len(match) > 0:\n                date.append(match[0].strip('\"'))\n            else:\n                date.append(None)\n            \n    return [reviews, rating, fresh, critic, top_critic, publisher, date]\n\ndef _get_num_pages(soup):\n    match = re.findall(page_pat,str(list(soup)))\n    if len(match) > 0:\n        match = match[0]\n        match = match.split(' of ')[-1]\n        return match\n    else:\n        return None",
    "id": "9533bf2ea5d947349cad1e0e253e092b",
    "idx": 1,
    "time": "2021-01-25T01:18:09.871Z",
    "type": "execution"
   },
   {
    "id": "9533bf2ea5d947349cad1e0e253e092b",
    "time": "2021-01-25T01:18:09.948Z",
    "type": "completion"
   },
   {
    "code": "def get_critic_reviews(page):\n    info = [[],[],[],[],[],[],[]]\n    soup = _make_soup(page + \"reviews\")\n    pages = _get_num_pages(soup)    \n    if pages is not None:\n        for page_num in range(1,int(pages)+1):\n            soup = _make_soup(page + \"reviews?page=\" + str(page_num) + \"&sort=\")\n            c_info = _get_critic_reviews_from_page(soup)\n            \n            # accumulate review info\n            for i in range(len(c_info)):\n                info[i] = info[i] + c_info[i]\n        \n        c_info = dict()\n        keys = ['reviews', 'rating', 'fresh', 'critic', 'top_critic', 'publisher', 'date']\n        for k in range(len(keys)):\n            c_info[keys[k]] = info[k]        \n    else:\n        c_info = None        \n    return c_info",
    "id": "0e35305f712b4af996a3444a84d10747",
    "idx": 2,
    "time": "2021-01-25T01:18:11.533Z",
    "type": "execution"
   },
   {
    "id": "0e35305f712b4af996a3444a84d10747",
    "time": "2021-01-25T01:18:11.602Z",
    "type": "completion"
   },
   {
    "code": "movie_urls = {'Wonder Woman 1984': 'https://www.rottentomatoes.com/m/wonder_woman_1984/', \n              'Soul':'https://www.rottentomatoes.com/m/soul_2020/', \n              'Mulan': 'https://www.rottentomatoes.com/m/mulan_2020/',\n              'Birds of Prey': 'https://www.rottentomatoes.com/m/birds_of_prey_2020/',\n              'Sonic': 'https://www.rottentomatoes.com/m/sonic_the_hedgehog_2020/'\n             }\nmovie_urls.keys()",
    "id": "4ff40fa9832744578de2781a362a030c",
    "idx": 3,
    "time": "2021-01-25T01:20:41.344Z",
    "type": "execution"
   },
   {
    "id": "4ff40fa9832744578de2781a362a030c",
    "time": "2021-01-25T01:20:41.435Z",
    "type": "completion"
   },
   {
    "code": "movie_urls = {'Wonder Woman 1984': 'https://www.rottentomatoes.com/m/wonder_woman_1984/', \n              'Soul':'https://www.rottentomatoes.com/m/soul_2020/', \n              'Mulan': 'https://www.rottentomatoes.com/m/mulan_2020/',\n              'Birds of Prey': 'https://www.rottentomatoes.com/m/birds_of_prey_2020/',\n              'Sonic': 'https://www.rottentomatoes.com/m/sonic_the_hedgehog_2020/'\n             }\nmovie_urls.keys()",
    "id": "4ff40fa9832744578de2781a362a030c",
    "idx": 3,
    "time": "2021-01-25T01:21:27.087Z",
    "type": "execution"
   },
   {
    "id": "4ff40fa9832744578de2781a362a030c",
    "time": "2021-01-25T01:21:27.155Z",
    "type": "completion"
   },
   {
    "code": "dfs = []\nfor key in movie_urls.keys():\n    temp = get_critic_reviews(movie_urls[key])\n    df = pd.DataFrame.from_dict(temp)\n    df['Film'] = key\n    dfs.append(df)",
    "id": "f38e9518a8674699aba6001147c83642",
    "idx": 4,
    "time": "2021-01-25T01:21:54.833Z",
    "type": "execution"
   },
   {
    "id": "f38e9518a8674699aba6001147c83642",
    "time": "2021-01-25T01:22:06.677Z",
    "type": "completion"
   },
   {
    "code": "import pandas as pd\n\ndfs = []\nfor key in movie_urls.keys():\n    temp = get_critic_reviews(movie_urls[key])\n    df = pd.DataFrame.from_dict(temp)\n    df['Film'] = key\n    dfs.append(df)",
    "id": "f38e9518a8674699aba6001147c83642",
    "idx": 4,
    "time": "2021-01-25T01:22:13.794Z",
    "type": "execution"
   },
   {
    "code": "pd.concat(dfs)",
    "id": "0a80902cb72546b59051eb0895f29b1a",
    "idx": 5,
    "time": "2021-01-25T01:22:18.569Z",
    "type": "execution"
   },
   {
    "id": "f38e9518a8674699aba6001147c83642",
    "time": "2021-01-25T01:22:59.103Z",
    "type": "completion"
   },
   {
    "id": "0a80902cb72546b59051eb0895f29b1a",
    "time": "2021-01-25T01:22:59.156Z",
    "type": "completion"
   },
   {
    "code": "all_films = pd.concat(dfs)\nall_films",
    "id": "0a80902cb72546b59051eb0895f29b1a",
    "idx": 5,
    "time": "2021-01-25T01:24:16.759Z",
    "type": "execution"
   },
   {
    "id": "0a80902cb72546b59051eb0895f29b1a",
    "time": "2021-01-25T01:24:16.865Z",
    "type": "completion"
   },
   {
    "code": "all_films['score'] = all_films['fresh'].apply(lambda x: 1 if x == 'fresh' else 0)\nall_films",
    "id": "24b2201e34ef4f7ea1e3069df916f172",
    "idx": 6,
    "time": "2021-01-25T01:24:26.846Z",
    "type": "execution"
   },
   {
    "id": "24b2201e34ef4f7ea1e3069df916f172",
    "time": "2021-01-25T01:24:26.938Z",
    "type": "completion"
   },
   {
    "code": "all_films['date'] = pd.to_datetime(all_films['date'], format=\"%B %d, %Y\")\nall_films = all_films.sort_values('date')",
    "id": "f265c65d26c94a1f810d653b11a0e943",
    "idx": 7,
    "time": "2021-01-25T01:24:49.576Z",
    "type": "execution"
   },
   {
    "id": "f265c65d26c94a1f810d653b11a0e943",
    "time": "2021-01-25T01:24:49.651Z",
    "type": "completion"
   },
   {
    "code": "import numpy as np\n\n\ndef calculate_score(film):\n    df = all_films[all_films['Film'] == film]\n    grouped_1 = df[['date', 'score']].groupby('date').agg([sum, 'count'])\n    grouped_1.columns = grouped_1.columns.droplevel(0)\n    return grouped_1.cumsum()['sum']/grouped_1.cumsum()['count']\n\ncalculate_score(\"Wonder Woman 1984\")",
    "id": "12d2e21a5f854cdf88a0d8024380245c",
    "idx": 8,
    "time": "2021-01-25T01:27:31.558Z",
    "type": "execution"
   },
   {
    "id": "12d2e21a5f854cdf88a0d8024380245c",
    "time": "2021-01-25T01:27:31.667Z",
    "type": "completion"
   },
   {
    "code": "import numpy as np\n\n\ndef calculate_score(film):\n    df = all_films[all_films['Film'] == film]\n    grouped_1 = df[['date', 'score']].groupby('date').agg([sum, 'count'])\n    grouped_1.columns = grouped_1.columns.droplevel(0)\n    return grouped_1.cumsum()['sum']/grouped_1.cumsum()['count']\n\ncalculate_score(\"Wonder Woman 1984\")",
    "id": "12d2e21a5f854cdf88a0d8024380245c",
    "idx": 8,
    "time": "2021-01-25T01:28:00.501Z",
    "type": "execution"
   },
   {
    "id": "12d2e21a5f854cdf88a0d8024380245c",
    "time": "2021-01-25T01:28:00.600Z",
    "type": "completion"
   },
   {
    "code": "calculate_score(\"Wonder Woman 1984\").plot()",
    "id": "65a620d143384f8a889dd2ca82c2bf76",
    "idx": 9,
    "time": "2021-01-25T01:28:52.064Z",
    "type": "execution"
   },
   {
    "id": "65a620d143384f8a889dd2ca82c2bf76",
    "time": "2021-01-25T01:28:55.601Z",
    "type": "completion"
   },
   {
    "code": "calculate_score(\"Sonic\").plot()",
    "id": "65a620d143384f8a889dd2ca82c2bf76",
    "idx": 9,
    "time": "2021-01-25T01:29:10.973Z",
    "type": "execution"
   },
   {
    "id": "65a620d143384f8a889dd2ca82c2bf76",
    "time": "2021-01-25T01:29:11.391Z",
    "type": "completion"
   },
   {
    "code": "calculate_score(\"Mulan\").plot()",
    "id": "65a620d143384f8a889dd2ca82c2bf76",
    "idx": 9,
    "time": "2021-01-25T01:29:20.660Z",
    "type": "execution"
   },
   {
    "id": "65a620d143384f8a889dd2ca82c2bf76",
    "time": "2021-01-25T01:29:21.117Z",
    "type": "completion"
   },
   {
    "code": "calculate_score(\"Soul\").plot()",
    "id": "65a620d143384f8a889dd2ca82c2bf76",
    "idx": 9,
    "time": "2021-01-25T01:29:32.892Z",
    "type": "execution"
   },
   {
    "id": "65a620d143384f8a889dd2ca82c2bf76",
    "time": "2021-01-25T01:29:33.218Z",
    "type": "completion"
   },
   {
    "code": "# calculate_score(\"Soul\").plot()\nimport matplotlib.pyplot as plt\n\nfor key in movie_urls.keys():\n#     pd.to_numeric(df.Subs).plot.line()\n    df = all_films[all_films==key]\n    plt.plot(calculate_score(key), label=key)\n#     plt.plot(np.arange(len(df.index)), pd.to_numeric(df.Total).pct_change(), label = df.Name.values[0], color = colors[i])\n#     plt.axvline(x=30, color='red', linestyle='dashed',linewidth=0.5)\n    plt.ylabel('Percent Change in Subscribers by Day')\n    plt.xlabel(\"Day (0 is 1 month before Content Cop's release)\")\n    plt.legend()\n# plt.annotate('Content Cop released', xy=(30, 0.015), ha='center', size=10)\n# plt.title('The Impact of Content Cop')\n# plt.savefig('pct_cc.svg')",
    "id": "65a620d143384f8a889dd2ca82c2bf76",
    "idx": 9,
    "time": "2021-01-25T01:32:47.689Z",
    "type": "execution"
   },
   {
    "id": "65a620d143384f8a889dd2ca82c2bf76",
    "time": "2021-01-25T01:32:48.148Z",
    "type": "completion"
   },
   {
    "code": "#add more movies\n\nmovie_urls['Tenet'] = 'https://www.rottentomatoes.com/m/tenet'\nmovie_urls['Scoob'] = 'https://www.rottentomatoes.com/m/scoob'\nmovie_urls['The Marksman'] = 'https://www.rottentomatoes.com/m/the_marksman_2021'\nmovie_urls['Artemis Fowl'] = 'https://www.rottentomatoes.com/m/the_marksman_2021'\nmovie_urls['Lovebirds'] = 'https://www.rottentomatoes.com/m/the_lovebirds_2020'\n\nnewkeys = ['Tenet', 'Scoob', 'The Marksman', 'Artemis Fowl', 'Lovebirds']\nfor key in newkeys:\n    temp = get_critic_reviews(movie_urls[key])\n    df = pd.DataFrame.from_dict(temp)\n    df['Film'] = key\n    dfs.append(df)",
    "id": "08428b7591c54ae38b82e220e5d57d2c",
    "idx": 10,
    "time": "2021-01-25T01:38:14.916Z",
    "type": "execution"
   },
   {
    "code": "dfs",
    "id": "e3d4885a365b48c2a6ac5911004a5418",
    "idx": 11,
    "time": "2021-01-25T01:38:16.323Z",
    "type": "execution"
   },
   {
    "id": "08428b7591c54ae38b82e220e5d57d2c",
    "time": "2021-01-25T01:38:16.437Z",
    "type": "completion"
   },
   {
    "id": "e3d4885a365b48c2a6ac5911004a5418",
    "time": "2021-01-25T01:38:16.488Z",
    "type": "completion"
   },
   {
    "code": "#add more movies\n\nmovie_urls['Tenet'] = 'https://www.rottentomatoes.com/m/tenet'\nmovie_urls['Scoob'] = 'https://www.rottentomatoes.com/m/scoob'\nmovie_urls['The Marksman'] = 'https://www.rottentomatoes.com/m/the_marksman_2021'\nmovie_urls['Artemis Fowl'] = 'https://www.rottentomatoes.com/m/the_marksman_2021'\nmovie_urls['Lovebirds'] = 'https://www.rottentomatoes.com/m/the_lovebirds_2020'\n\nnewkeys = ['Tenet', 'Scoob', 'The Marksman', 'Artemis Fowl', 'Lovebirds']\nfor key in newkeys:\n    temp = get_critic_reviews(movie_urls[key])\n    print(temp)\n    df = pd.DataFrame.from_dict(temp)\n    df['Film'] = key\n    dfs.append(df)",
    "id": "08428b7591c54ae38b82e220e5d57d2c",
    "idx": 10,
    "time": "2021-01-25T01:38:48.438Z",
    "type": "execution"
   },
   {
    "id": "08428b7591c54ae38b82e220e5d57d2c",
    "time": "2021-01-25T01:38:49.943Z",
    "type": "completion"
   },
   {
    "code": "movie_urls['Tenet']",
    "id": "e3d4885a365b48c2a6ac5911004a5418",
    "idx": 11,
    "time": "2021-01-25T01:39:06.356Z",
    "type": "execution"
   },
   {
    "id": "e3d4885a365b48c2a6ac5911004a5418",
    "time": "2021-01-25T01:39:06.441Z",
    "type": "completion"
   },
   {
    "code": "get_critic_reviews(movie_urls['Tenet'])",
    "id": "e3d4885a365b48c2a6ac5911004a5418",
    "idx": 11,
    "time": "2021-01-25T01:39:14.875Z",
    "type": "execution"
   },
   {
    "id": "e3d4885a365b48c2a6ac5911004a5418",
    "time": "2021-01-25T01:39:15.298Z",
    "type": "completion"
   },
   {
    "code": "all_films.to_csv(\"all_films.csv\", index=False)",
    "id": "dd041b290f0b4e958b7399ea871fb054",
    "idx": 10,
    "time": "2021-01-25T01:39:42.406Z",
    "type": "execution"
   },
   {
    "id": "dd041b290f0b4e958b7399ea871fb054",
    "time": "2021-01-25T01:39:42.507Z",
    "type": "completion"
   },
   {
    "code": "#add more movies\n\nmovie_urls['Tenet'] = 'https://www.rottentomatoes.com/m/tenet'\nmovie_urls['Scoob'] = 'https://www.rottentomatoes.com/m/scoob'\nmovie_urls['The Marksman'] = 'https://www.rottentomatoes.com/m/the_marksman_2021'\nmovie_urls['Artemis Fowl'] = 'https://www.rottentomatoes.com/m/the_marksman_2021'\nmovie_urls['Lovebirds'] = 'https://www.rottentomatoes.com/m/the_lovebirds_2020'\n\nnewkeys = ['Tenet', 'Scoob', 'The Marksman', 'Artemis Fowl', 'Lovebirds']\nfor key in newkeys:\n    temp = get_critic_reviews(movie_urls[key])\n    df = pd.DataFrame.from_dict(temp)\n    df['Film'] = key\n    dfs.append(df)",
    "id": "08428b7591c54ae38b82e220e5d57d2c",
    "idx": 11,
    "time": "2021-01-25T01:40:12.653Z",
    "type": "execution"
   },
   {
    "id": "08428b7591c54ae38b82e220e5d57d2c",
    "time": "2021-01-25T01:40:14.176Z",
    "type": "completion"
   },
   {
    "code": "dfs",
    "id": "e3d4885a365b48c2a6ac5911004a5418",
    "idx": 12,
    "time": "2021-01-25T01:40:18.809Z",
    "type": "execution"
   },
   {
    "id": "e3d4885a365b48c2a6ac5911004a5418",
    "time": "2021-01-25T01:40:18.966Z",
    "type": "completion"
   },
   {
    "code": "dfs[7]",
    "id": "e3d4885a365b48c2a6ac5911004a5418",
    "idx": 12,
    "time": "2021-01-25T01:40:32.974Z",
    "type": "execution"
   },
   {
    "id": "e3d4885a365b48c2a6ac5911004a5418",
    "time": "2021-01-25T01:40:33.061Z",
    "type": "completion"
   },
   {
    "code": "#add more movies\n\nmovie_urls['Tenet'] = 'https://www.rottentomatoes.com/m/tenet'\nmovie_urls['Scoob'] = 'https://www.rottentomatoes.com/m/scoob'\nmovie_urls['The Marksman'] = 'https://www.rottentomatoes.com/m/the_marksman_2021'\nmovie_urls['Artemis Fowl'] = 'https://www.rottentomatoes.com/m/the_marksman_2021'\nmovie_urls['Lovebirds'] = 'https://www.rottentomatoes.com/m/the_lovebirds_2020'\n\nnewkeys = ['Tenet', 'Scoob', 'The Marksman', 'Artemis Fowl', 'Lovebirds']\nfor key in newkeys:\n    print(key)\n    temp = get_critic_reviews(movie_urls[key])\n    df = pd.DataFrame.from_dict(temp)\n    df['Film'] = key\n    dfs.append(df)",
    "id": "08428b7591c54ae38b82e220e5d57d2c",
    "idx": 11,
    "time": "2021-01-25T01:40:40.093Z",
    "type": "execution"
   },
   {
    "id": "08428b7591c54ae38b82e220e5d57d2c",
    "time": "2021-01-25T01:40:42.183Z",
    "type": "completion"
   },
   {
    "code": "#add more movies\n\nmovie_urls['Tenet'] = 'https://www.rottentomatoes.com/m/tenet'\nmovie_urls['Scoob'] = 'https://www.rottentomatoes.com/m/scoob'\nmovie_urls['The Marksman'] = 'https://www.rottentomatoes.com/m/the_marksman_2021'\nmovie_urls['Artemis Fowl'] = 'https://www.rottentomatoes.com/m/the_marksman_2021'\nmovie_urls['Lovebirds'] = 'https://www.rottentomatoes.com/m/the_lovebirds_2020'\n\nnewkeys = ['Tenet', 'Scoob', 'The Marksman', 'Artemis Fowl', 'Lovebirds']\nfor key in newkeys:\n    print(key)\n    temp = get_critic_reviews(movie_urls[key])\n    df = pd.DataFrame.from_dict(temp)\n    df['Film'] = key\n    dfs.append(df)",
    "id": "6fcb345e6cd240d19986ad40e631977a",
    "idx": 11,
    "time": "2021-01-25T02:30:24.984Z",
    "type": "execution"
   },
   {
    "code": "import requests\nimport time\n\n# requirements\nfrom bs4 import BeautifulSoup\nfrom requests import TooManyRedirects\nimport re\n\ndef _make_soup(url):\n    try:\n        r = requests.get(url)\n        soup = BeautifulSoup(r.content, 'html.parser')\n    except TooManyRedirects:\n        soup = ''\n    return soup\n\n#regex patterns\npage_pat = re.compile(r'Page 1 of \\d+')\nreview_pat = re.compile(r'<div class=\\\"the_review\\\" data-qa=\\\"review-text\\\">[;a-zA-Z\\s,-.\\'\\/\\?\\[\\]\\\":\\']*</div>')\nrating_pat = re.compile(r'Original Score:\\s([A-Z](\\+|-)?|\\d(.\\d)?(\\/\\d)?)')\nfresh_pat = re.compile(r'small\\s(fresh|rotten)\\\"')\ncritic_pat = re.compile(r'\\/\\\"\\>([A-Z][a-zA-Z]+\\s[A-Z][a-zA-Z\\-]+)|([A-Z][a-zA-Z.]+\\s[A-Z].?\\s[A-Z][a-zA-Z]+)|([A-Z][a-zA-Z]+\\s[A-Z]+\\'[A-Z][a-zA-Z]+)')\npublisher_pat = re.compile(r'\\\"subtle\\\">[a-zA-Z\\s,.\\(\\)\\'\\-&;!\\/\\d+]+</em>')\ndate_pat = re.compile(r'[a-zA-Z]+\\s\\d+,\\s\\d+')",
    "id": "6565956e55e14dfdbbf8d8aa6047c9a5",
    "idx": 0,
    "time": "2021-01-25T02:31:11.131Z",
    "type": "execution"
   },
   {
    "code": "#add more movies\n\nmovie_urls['Tenet'] = 'https://www.rottentomatoes.com/m/tenet'\nmovie_urls['Scoob'] = 'https://www.rottentomatoes.com/m/scoob'\nmovie_urls['The Marksman'] = 'https://www.rottentomatoes.com/m/the_marksman_2021'\nmovie_urls['Artemis Fowl'] = 'https://www.rottentomatoes.com/m/the_marksman_2021'\nmovie_urls['Lovebirds'] = 'https://www.rottentomatoes.com/m/the_lovebirds_2020'\n\nnewkeys = ['Tenet', 'Scoob', 'The Marksman', 'Artemis Fowl', 'Lovebirds']\nfor key in newkeys:\n    print(key)\n    temp = get_critic_reviews(movie_urls[key])\n    df = pd.DataFrame.from_dict(temp)\n    df['Film'] = key\n    dfs.append(df)",
    "id": "452da246cc0b4216939ee0c2d35311c0",
    "idx": 11,
    "time": "2021-01-25T04:58:20.981Z",
    "type": "execution"
   },
   {
    "id": "452da246cc0b4216939ee0c2d35311c0",
    "time": "2021-01-25T04:58:21.206Z",
    "type": "completion"
   },
   {
    "code": "import requests\nimport time\n\n# requirements\nfrom bs4 import BeautifulSoup\nfrom requests import TooManyRedirects\nimport re\n\ndef _make_soup(url):\n    try:\n        r = requests.get(url)\n        soup = BeautifulSoup(r.content, 'html.parser')\n    except TooManyRedirects:\n        soup = ''\n    return soup\n\n#regex patterns\npage_pat = re.compile(r'Page 1 of \\d+')\nreview_pat = re.compile(r'<div class=\\\"the_review\\\" data-qa=\\\"review-text\\\">[;a-zA-Z\\s,-.\\'\\/\\?\\[\\]\\\":\\']*</div>')\nrating_pat = re.compile(r'Original Score:\\s([A-Z](\\+|-)?|\\d(.\\d)?(\\/\\d)?)')\nfresh_pat = re.compile(r'small\\s(fresh|rotten)\\\"')\ncritic_pat = re.compile(r'\\/\\\"\\>([A-Z][a-zA-Z]+\\s[A-Z][a-zA-Z\\-]+)|([A-Z][a-zA-Z.]+\\s[A-Z].?\\s[A-Z][a-zA-Z]+)|([A-Z][a-zA-Z]+\\s[A-Z]+\\'[A-Z][a-zA-Z]+)')\npublisher_pat = re.compile(r'\\\"subtle\\\">[a-zA-Z\\s,.\\(\\)\\'\\-&;!\\/\\d+]+</em>')\ndate_pat = re.compile(r'[a-zA-Z]+\\s\\d+,\\s\\d+')",
    "id": "76632974c4304b76a236574d6b4f470e",
    "idx": 0,
    "time": "2021-01-25T04:58:25.502Z",
    "type": "execution"
   },
   {
    "id": "76632974c4304b76a236574d6b4f470e",
    "time": "2021-01-25T04:58:25.772Z",
    "type": "completion"
   },
   {
    "code": "def _get_critic_reviews_from_page(soup):\n    reviews = list()\n    rating = list()\n    fresh = list()\n    critic = list()\n    top_critic = list()\n    publisher = list()\n    date = list()\n    \n    soup = str(soup)\n    review_soup = soup.split('=\"review_table')[1].split('row review_table_row')\n    review_soup.pop(0)\n\n    for review in review_soup:\n        match = re.findall(review_pat, str(review))\n        if len(match) > 0:\n            m = match[0]            \n            for iden in ['<div class=\"the_review\" data-qa=\"review-text\"> ','</div>']:\n                m = m.replace(iden,'')\n            reviews.append(m.strip('\"'))            \n            # extract rating\n            match = re.findall(rating_pat, str(review))\n            if len(match) > 0:\n                m = match[0][0]\n                if '/1' in m:\n                    sp_m = m.split('/')\n                    if sp_m[-1] == '1':\n                        sp_m[-1] = '10'\n                    m = '/'.join(sp_m)\n                rating.append(m)\n            else:\n                rating.append(None)            \n            # extract fresh indicator\n            match = re.findall(fresh_pat, str(review))\n            if len(match) > 0:\n                fresh.append(match[0])\n            else:\n                fresh.append(None)            \n            # extract critic\n            match = re.findall(critic_pat, str(review))\n            if len(match) > 0:\n                critic.append(''.join(match[0]))\n            else:\n                critic.append(None)            \n            # check if top critic\n            if '> Top Critic<' in str(review):\n                top_critic.append(1)\n            else:\n                top_critic.append(0)            \n            # extract publisher\n            match = re.findall(publisher_pat, str(review))\n            if len(match) > 0:\n                m = match[0]\n                m = m.replace('\"subtle\">', '')\n                m = m.replace('</em>','')\n                publisher.append(m)\n            else:\n                publisher.append(None)            \n            # extract date\n            match = re.findall(date_pat, str(review))\n            if len(match) > 0:\n                date.append(match[0].strip('\"'))\n            else:\n                date.append(None)\n            \n    return [reviews, rating, fresh, critic, top_critic, publisher, date]\n\ndef _get_num_pages(soup):\n    match = re.findall(page_pat,str(list(soup)))\n    if len(match) > 0:\n        match = match[0]\n        match = match.split(' of ')[-1]\n        return match\n    else:\n        return None",
    "id": "2ad68878ffa14d7798b340fc2cb50f73",
    "idx": 1,
    "time": "2021-01-25T04:58:26.357Z",
    "type": "execution"
   },
   {
    "id": "2ad68878ffa14d7798b340fc2cb50f73",
    "time": "2021-01-25T04:58:26.438Z",
    "type": "completion"
   },
   {
    "code": "def get_critic_reviews(page):\n    info = [[],[],[],[],[],[],[]]\n    soup = _make_soup(page + \"reviews\")\n    pages = _get_num_pages(soup)    \n    if pages is not None:\n        for page_num in range(1,int(pages)+1):\n            soup = _make_soup(page + \"reviews?page=\" + str(page_num) + \"&sort=\")\n            c_info = _get_critic_reviews_from_page(soup)\n            \n            # accumulate review info\n            for i in range(len(c_info)):\n                info[i] = info[i] + c_info[i]\n        \n        c_info = dict()\n        keys = ['reviews', 'rating', 'fresh', 'critic', 'top_critic', 'publisher', 'date']\n        for k in range(len(keys)):\n            c_info[keys[k]] = info[k]        \n    else:\n        c_info = None        \n    return c_info",
    "id": "37eabf1671044138af9a456423454050",
    "idx": 2,
    "time": "2021-01-25T04:58:27.372Z",
    "type": "execution"
   },
   {
    "id": "37eabf1671044138af9a456423454050",
    "time": "2021-01-25T04:58:27.437Z",
    "type": "completion"
   },
   {
    "code": "movie_urls = {'Wonder Woman 1984': 'https://www.rottentomatoes.com/m/wonder_woman_1984/', \n              'Soul':'https://www.rottentomatoes.com/m/soul_2020/', \n              'Mulan': 'https://www.rottentomatoes.com/m/mulan_2020/',\n              'Birds of Prey': 'https://www.rottentomatoes.com/m/birds_of_prey_2020/',\n              'Sonic': 'https://www.rottentomatoes.com/m/sonic_the_hedgehog_2020/'\n             }\nmovie_urls.keys()",
    "id": "99926b7aff5d493eabbdb4a843b55104",
    "idx": 3,
    "time": "2021-01-25T04:58:28.385Z",
    "type": "execution"
   },
   {
    "id": "99926b7aff5d493eabbdb4a843b55104",
    "time": "2021-01-25T04:58:28.460Z",
    "type": "completion"
   },
   {
    "code": "#add more movies\nimport pandas as pd\n\nmovie_urls['Tenet'] = 'https://www.rottentomatoes.com/m/tenet'\nmovie_urls['Scoob'] = 'https://www.rottentomatoes.com/m/scoob'\nmovie_urls['The Marksman'] = 'https://www.rottentomatoes.com/m/the_marksman_2021'\nmovie_urls['Artemis Fowl'] = 'https://www.rottentomatoes.com/m/the_marksman_2021'\nmovie_urls['Lovebirds'] = 'https://www.rottentomatoes.com/m/the_lovebirds_2020'\n\nnewkeys = ['Tenet', 'Scoob', 'The Marksman', 'Artemis Fowl', 'Lovebirds']\nfor key in newkeys:\n    print(key)\n    temp = get_critic_reviews(movie_urls[key])\n    df = pd.DataFrame.from_dict(temp)\n    df['Film'] = key\n    dfs.append(df)",
    "id": "452da246cc0b4216939ee0c2d35311c0",
    "idx": 11,
    "time": "2021-01-25T04:58:41.486Z",
    "type": "execution"
   },
   {
    "id": "452da246cc0b4216939ee0c2d35311c0",
    "time": "2021-01-25T04:58:42.435Z",
    "type": "completion"
   },
   {
    "code": "#add more movies\nimport pandas as pd\n\nmovie_urls['Tenet'] = 'https://www.rottentomatoes.com/m/tenet'\nmovie_urls['Scoob'] = 'https://www.rottentomatoes.com/m/scoob'\nmovie_urls['The Marksman'] = 'https://www.rottentomatoes.com/m/the_marksman_2021'\nmovie_urls['Artemis Fowl'] = 'https://www.rottentomatoes.com/m/the_marksman_2021'\nmovie_urls['Lovebirds'] = 'https://www.rottentomatoes.com/m/the_lovebirds_2020'\n\nnewkeys = ['Tenet', 'Scoob', 'The Marksman', 'Artemis Fowl', 'Lovebirds']\ndfs = []\n\nfor key in newkeys:\n    print(key)\n    temp = get_critic_reviews(movie_urls[key])\n    df = pd.DataFrame.from_dict(temp)\n    df['Film'] = key\n    dfs.append(df)",
    "id": "452da246cc0b4216939ee0c2d35311c0",
    "idx": 11,
    "time": "2021-01-25T04:58:57.238Z",
    "type": "execution"
   },
   {
    "id": "452da246cc0b4216939ee0c2d35311c0",
    "time": "2021-01-25T04:58:58.931Z",
    "type": "completion"
   },
   {
    "code": "dfs",
    "id": "d2b653a5564e49b588c9834bf6ae03c3",
    "idx": 12,
    "time": "2021-01-25T04:59:00.950Z",
    "type": "execution"
   },
   {
    "id": "d2b653a5564e49b588c9834bf6ae03c3",
    "time": "2021-01-25T04:59:01.025Z",
    "type": "completion"
   },
   {
    "code": "#add more movies\nimport pandas as pd\n\nmovie_urls['Tenet'] = 'https://www.rottentomatoes.com/m/tenet'\nmovie_urls['Scoob'] = 'https://www.rottentomatoes.com/m/scoob'\nmovie_urls['The Marksman'] = 'https://www.rottentomatoes.com/m/the_marksman_2021'\nmovie_urls['Artemis Fowl'] = 'https://www.rottentomatoes.com/m/the_marksman_2021'\nmovie_urls['Lovebirds'] = 'https://www.rottentomatoes.com/m/the_lovebirds_2020'\n\nnewkeys = ['Tenet', 'Scoob', 'The Marksman', 'Artemis Fowl', 'Lovebirds']\ndfs = []\n\nfor key in newkeys:\n    print(movie_urls[key])\n    temp = get_critic_reviews(movie_urls[key])\n    df = pd.DataFrame.from_dict(temp)\n    df['Film'] = key\n    dfs.append(df)",
    "id": "452da246cc0b4216939ee0c2d35311c0",
    "idx": 11,
    "time": "2021-01-25T04:59:34.058Z",
    "type": "execution"
   },
   {
    "code": "#add more movies\nimport pandas as pd\n\nmovie_urls['Tenet'] = 'https://www.rottentomatoes.com/m/tenet'\nmovie_urls['Scoob'] = 'https://www.rottentomatoes.com/m/scoob'\nmovie_urls['The Marksman'] = 'https://www.rottentomatoes.com/m/the_marksman_2021'\nmovie_urls['Artemis Fowl'] = 'https://www.rottentomatoes.com/m/the_marksman_2021'\nmovie_urls['Lovebirds'] = 'https://www.rottentomatoes.com/m/the_lovebirds_2020'\n\nnewkeys = ['Tenet', 'Scoob', 'The Marksman', 'Artemis Fowl', 'Lovebirds']\ndfs = []\n\nfor key in newkeys:\n    print(movie_urls[key])\n    temp = get_critic_reviews(movie_urls[key])\n    df = pd.DataFrame.from_dict(temp)\n    df['Film'] = key\n    dfs.append(df)",
    "id": "d7130be7a30d41d69ee77114450264e8",
    "idx": 11,
    "time": "2021-01-25T05:01:13.573Z",
    "type": "execution"
   },
   {
    "code": "import requests\nimport time\n\n# requirements\nfrom bs4 import BeautifulSoup\nfrom requests import TooManyRedirects\nimport re\n\ndef _make_soup(url):\n    try:\n        r = requests.get(url)\n        soup = BeautifulSoup(r.content, 'html.parser')\n    except TooManyRedirects:\n        soup = ''\n    return soup\n\n#regex patterns\npage_pat = re.compile(r'Page 1 of \\d+')\nreview_pat = re.compile(r'<div class=\\\"the_review\\\" data-qa=\\\"review-text\\\">[;a-zA-Z\\s,-.\\'\\/\\?\\[\\]\\\":\\']*</div>')\nrating_pat = re.compile(r'Original Score:\\s([A-Z](\\+|-)?|\\d(.\\d)?(\\/\\d)?)')\nfresh_pat = re.compile(r'small\\s(fresh|rotten)\\\"')\ncritic_pat = re.compile(r'\\/\\\"\\>([A-Z][a-zA-Z]+\\s[A-Z][a-zA-Z\\-]+)|([A-Z][a-zA-Z.]+\\s[A-Z].?\\s[A-Z][a-zA-Z]+)|([A-Z][a-zA-Z]+\\s[A-Z]+\\'[A-Z][a-zA-Z]+)')\npublisher_pat = re.compile(r'\\\"subtle\\\">[a-zA-Z\\s,.\\(\\)\\'\\-&;!\\/\\d+]+</em>')\ndate_pat = re.compile(r'[a-zA-Z]+\\s\\d+,\\s\\d+')",
    "id": "f6c275693e8745899eb9ab41762579c5",
    "idx": 0,
    "time": "2021-01-25T16:36:33.413Z",
    "type": "execution"
   },
   {
    "id": "f6c275693e8745899eb9ab41762579c5",
    "time": "2021-01-25T16:36:33.660Z",
    "type": "completion"
   },
   {
    "code": "def _get_critic_reviews_from_page(soup):\n    reviews = list()\n    rating = list()\n    fresh = list()\n    critic = list()\n    top_critic = list()\n    publisher = list()\n    date = list()\n    \n    soup = str(soup)\n    review_soup = soup.split('=\"review_table')[1].split('row review_table_row')\n    review_soup.pop(0)\n\n    for review in review_soup:\n        match = re.findall(review_pat, str(review))\n        if len(match) > 0:\n            m = match[0]            \n            for iden in ['<div class=\"the_review\" data-qa=\"review-text\"> ','</div>']:\n                m = m.replace(iden,'')\n            reviews.append(m.strip('\"'))            \n            # extract rating\n            match = re.findall(rating_pat, str(review))\n            if len(match) > 0:\n                m = match[0][0]\n                if '/1' in m:\n                    sp_m = m.split('/')\n                    if sp_m[-1] == '1':\n                        sp_m[-1] = '10'\n                    m = '/'.join(sp_m)\n                rating.append(m)\n            else:\n                rating.append(None)            \n            # extract fresh indicator\n            match = re.findall(fresh_pat, str(review))\n            if len(match) > 0:\n                fresh.append(match[0])\n            else:\n                fresh.append(None)            \n            # extract critic\n            match = re.findall(critic_pat, str(review))\n            if len(match) > 0:\n                critic.append(''.join(match[0]))\n            else:\n                critic.append(None)            \n            # check if top critic\n            if '> Top Critic<' in str(review):\n                top_critic.append(1)\n            else:\n                top_critic.append(0)            \n            # extract publisher\n            match = re.findall(publisher_pat, str(review))\n            if len(match) > 0:\n                m = match[0]\n                m = m.replace('\"subtle\">', '')\n                m = m.replace('</em>','')\n                publisher.append(m)\n            else:\n                publisher.append(None)            \n            # extract date\n            match = re.findall(date_pat, str(review))\n            if len(match) > 0:\n                date.append(match[0].strip('\"'))\n            else:\n                date.append(None)\n            \n    return [reviews, rating, fresh, critic, top_critic, publisher, date]\n\ndef _get_num_pages(soup):\n    match = re.findall(page_pat,str(list(soup)))\n    if len(match) > 0:\n        match = match[0]\n        match = match.split(' of ')[-1]\n        return match\n    else:\n        return None",
    "id": "86f10fc9d73f494b92c2cfddf43a204b",
    "idx": 1,
    "time": "2021-01-25T16:36:34.078Z",
    "type": "execution"
   },
   {
    "id": "86f10fc9d73f494b92c2cfddf43a204b",
    "time": "2021-01-25T16:36:34.165Z",
    "type": "completion"
   },
   {
    "code": "def get_critic_reviews(page):\n    info = [[],[],[],[],[],[],[]]\n    soup = _make_soup(page + \"reviews\")\n    pages = _get_num_pages(soup)    \n    if pages is not None:\n        for page_num in range(1,int(pages)+1):\n            soup = _make_soup(page + \"reviews?page=\" + str(page_num) + \"&sort=\")\n            c_info = _get_critic_reviews_from_page(soup)\n            \n            # accumulate review info\n            for i in range(len(c_info)):\n                info[i] = info[i] + c_info[i]\n        \n        c_info = dict()\n        keys = ['reviews', 'rating', 'fresh', 'critic', 'top_critic', 'publisher', 'date']\n        for k in range(len(keys)):\n            c_info[keys[k]] = info[k]        \n    else:\n        c_info = None        \n    return c_info",
    "id": "8e2d555ea9a54a3eb45e118bc3006d87",
    "idx": 2,
    "time": "2021-01-25T16:36:34.830Z",
    "type": "execution"
   },
   {
    "id": "8e2d555ea9a54a3eb45e118bc3006d87",
    "time": "2021-01-25T16:36:34.898Z",
    "type": "completion"
   },
   {
    "code": "#add more movies\nimport pandas as pd\n\nmovie_urls['Tenet'] = 'https://www.rottentomatoes.com/m/tenet'\nmovie_urls['Scoob'] = 'https://www.rottentomatoes.com/m/scoob'\nmovie_urls['The Marksman'] = 'https://www.rottentomatoes.com/m/the_marksman_2021'\nmovie_urls['Artemis Fowl'] = 'https://www.rottentomatoes.com/m/the_marksman_2021'\nmovie_urls['Lovebirds'] = 'https://www.rottentomatoes.com/m/the_lovebirds_2020'\n\nnewkeys = ['Tenet', 'Scoob', 'The Marksman', 'Artemis Fowl', 'Lovebirds']\ndfs = []\n\nfor key in newkeys:\n    print(movie_urls[key])\n    temp = get_critic_reviews(movie_urls[key])\n    df = pd.DataFrame.from_dict(temp)\n    df['Film'] = key\n    dfs.append(df)",
    "id": "22fa8e30b0f64b598b8acd6736da276a",
    "idx": 11,
    "time": "2021-01-25T16:36:47.045Z",
    "type": "execution"
   },
   {
    "id": "22fa8e30b0f64b598b8acd6736da276a",
    "time": "2021-01-25T16:36:47.674Z",
    "type": "completion"
   },
   {
    "code": "movie_urls = {'Wonder Woman 1984': 'https://www.rottentomatoes.com/m/wonder_woman_1984/', \n              'Soul':'https://www.rottentomatoes.com/m/soul_2020/', \n              'Mulan': 'https://www.rottentomatoes.com/m/mulan_2020/',\n              'Birds of Prey': 'https://www.rottentomatoes.com/m/birds_of_prey_2020/',\n              'Sonic': 'https://www.rottentomatoes.com/m/sonic_the_hedgehog_2020/'\n             }\nmovie_urls.keys()",
    "id": "ca47067600704db28d331a12c9536b11",
    "idx": 3,
    "time": "2021-01-25T16:36:53.406Z",
    "type": "execution"
   },
   {
    "id": "ca47067600704db28d331a12c9536b11",
    "time": "2021-01-25T16:36:53.481Z",
    "type": "completion"
   },
   {
    "code": "#add more movies\nimport pandas as pd\n\nmovie_urls['Tenet'] = 'https://www.rottentomatoes.com/m/tenet'\nmovie_urls['Scoob'] = 'https://www.rottentomatoes.com/m/scoob'\nmovie_urls['The Marksman'] = 'https://www.rottentomatoes.com/m/the_marksman_2021'\nmovie_urls['Artemis Fowl'] = 'https://www.rottentomatoes.com/m/the_marksman_2021'\nmovie_urls['Lovebirds'] = 'https://www.rottentomatoes.com/m/the_lovebirds_2020'\n\nnewkeys = ['Tenet', 'Scoob', 'The Marksman', 'Artemis Fowl', 'Lovebirds']\ndfs = []\n\nfor key in newkeys:\n    print(movie_urls[key])\n    temp = get_critic_reviews(movie_urls[key])\n    df = pd.DataFrame.from_dict(temp)\n    df['Film'] = key\n    dfs.append(df)",
    "id": "22fa8e30b0f64b598b8acd6736da276a",
    "idx": 11,
    "time": "2021-01-25T16:36:56.636Z",
    "type": "execution"
   },
   {
    "id": "22fa8e30b0f64b598b8acd6736da276a",
    "time": "2021-01-25T16:36:58.525Z",
    "type": "completion"
   },
   {
    "code": "dfs",
    "id": "9b5af4a1b7a7445cac3f9370f0090bbf",
    "idx": 12,
    "time": "2021-01-25T16:37:06.121Z",
    "type": "execution"
   },
   {
    "id": "9b5af4a1b7a7445cac3f9370f0090bbf",
    "time": "2021-01-25T16:37:06.211Z",
    "type": "completion"
   },
   {
    "code": "def get_critic_reviews(page):\n    info = [[],[],[],[],[],[],[]]\n    soup = _make_soup(page + \"reviews\")\n    print(soup)\n    pages = _get_num_pages(soup)    \n    if pages is not None:\n        for page_num in range(1,int(pages)+1):\n            soup = _make_soup(page + \"reviews?page=\" + str(page_num) + \"&sort=\")\n            c_info = _get_critic_reviews_from_page(soup)\n            \n            # accumulate review info\n            for i in range(len(c_info)):\n                info[i] = info[i] + c_info[i]\n        \n        c_info = dict()\n        keys = ['reviews', 'rating', 'fresh', 'critic', 'top_critic', 'publisher', 'date']\n        for k in range(len(keys)):\n            c_info[keys[k]] = info[k]        \n    else:\n        c_info = None        \n    return c_info",
    "id": "8e2d555ea9a54a3eb45e118bc3006d87",
    "idx": 2,
    "time": "2021-01-25T16:37:29.731Z",
    "type": "execution"
   },
   {
    "id": "8e2d555ea9a54a3eb45e118bc3006d87",
    "time": "2021-01-25T16:37:29.802Z",
    "type": "completion"
   },
   {
    "code": "#add more movies\nimport pandas as pd\n\nmovie_urls['Tenet'] = 'https://www.rottentomatoes.com/m/tenet'\nmovie_urls['Scoob'] = 'https://www.rottentomatoes.com/m/scoob'\nmovie_urls['The Marksman'] = 'https://www.rottentomatoes.com/m/the_marksman_2021'\nmovie_urls['Artemis Fowl'] = 'https://www.rottentomatoes.com/m/the_marksman_2021'\nmovie_urls['Lovebirds'] = 'https://www.rottentomatoes.com/m/the_lovebirds_2020'\n\nnewkeys = ['Tenet', 'Scoob', 'The Marksman', 'Artemis Fowl', 'Lovebirds']\ndfs = []\n\nfor key in newkeys:\n    print(movie_urls[key])\n    temp = get_critic_reviews(movie_urls[key])\n    df = pd.DataFrame.from_dict(temp)\n    df['Film'] = key\n    dfs.append(df)",
    "id": "22fa8e30b0f64b598b8acd6736da276a",
    "idx": 11,
    "time": "2021-01-25T16:37:33.285Z",
    "type": "execution"
   },
   {
    "id": "22fa8e30b0f64b598b8acd6736da276a",
    "time": "2021-01-25T16:37:37.343Z",
    "type": "completion"
   },
   {
    "code": "def get_critic_reviews(page):\n    info = [[],[],[],[],[],[],[]]\n    soup = _make_soup(page + \"reviews\")\n#     print(soup)\n    pages = _get_num_pages(soup)\n    print(pages)\n    if pages is not None:\n        for page_num in range(1,int(pages)+1):\n            soup = _make_soup(page + \"reviews?page=\" + str(page_num) + \"&sort=\")\n            c_info = _get_critic_reviews_from_page(soup)\n            \n            # accumulate review info\n            for i in range(len(c_info)):\n                info[i] = info[i] + c_info[i]\n        \n        c_info = dict()\n        keys = ['reviews', 'rating', 'fresh', 'critic', 'top_critic', 'publisher', 'date']\n        for k in range(len(keys)):\n            c_info[keys[k]] = info[k]        \n    else:\n        c_info = None        \n    return c_info",
    "id": "8e2d555ea9a54a3eb45e118bc3006d87",
    "idx": 2,
    "time": "2021-01-25T16:38:08.381Z",
    "type": "execution"
   },
   {
    "id": "8e2d555ea9a54a3eb45e118bc3006d87",
    "time": "2021-01-25T16:38:08.463Z",
    "type": "completion"
   },
   {
    "code": "#add more movies\nimport pandas as pd\n\nmovie_urls['Tenet'] = 'https://www.rottentomatoes.com/m/tenet'\nmovie_urls['Scoob'] = 'https://www.rottentomatoes.com/m/scoob'\nmovie_urls['The Marksman'] = 'https://www.rottentomatoes.com/m/the_marksman_2021'\nmovie_urls['Artemis Fowl'] = 'https://www.rottentomatoes.com/m/the_marksman_2021'\nmovie_urls['Lovebirds'] = 'https://www.rottentomatoes.com/m/the_lovebirds_2020'\n\nnewkeys = ['Tenet', 'Scoob', 'The Marksman', 'Artemis Fowl', 'Lovebirds']\ndfs = []\n\nfor key in newkeys:\n    print(movie_urls[key])\n    temp = get_critic_reviews(movie_urls[key])\n    df = pd.DataFrame.from_dict(temp)\n    df['Film'] = key\n    dfs.append(df)",
    "id": "22fa8e30b0f64b598b8acd6736da276a",
    "idx": 11,
    "time": "2021-01-25T16:38:13.734Z",
    "type": "execution"
   },
   {
    "id": "22fa8e30b0f64b598b8acd6736da276a",
    "time": "2021-01-25T16:38:16.429Z",
    "type": "completion"
   },
   {
    "code": "get_critic_reviews(movie_urls[\"Sonic\"])",
    "id": "9b5af4a1b7a7445cac3f9370f0090bbf",
    "idx": 12,
    "time": "2021-01-25T16:38:38.792Z",
    "type": "execution"
   },
   {
    "id": "9b5af4a1b7a7445cac3f9370f0090bbf",
    "time": "2021-01-25T16:38:52.063Z",
    "type": "completion"
   },
   {
    "code": "def get_critic_reviews(page):\n    info = [[],[],[],[],[],[],[]]\n    soup = _make_soup(page + \"reviews\")\n#     print(soup)\n    pages = _get_num_pages(soup)\n#     print(pages)\n    if pages is not None:\n        for page_num in range(1,int(pages)+1):\n            soup = _make_soup(page + \"reviews?page=\" + str(page_num) + \"&sort=\")\n            c_info = _get_critic_reviews_from_page(soup)\n            \n            # accumulate review info\n            for i in range(len(c_info)):\n                info[i] = info[i] + c_info[i]\n        \n        c_info = dict()\n        keys = ['reviews', 'rating', 'fresh', 'critic', 'top_critic', 'publisher', 'date']\n        for k in range(len(keys)):\n            c_info[keys[k]] = info[k]        \n    else:\n        c_info = None        \n    return c_info",
    "id": "8e2d555ea9a54a3eb45e118bc3006d87",
    "idx": 2,
    "time": "2021-01-25T16:39:43.666Z",
    "type": "execution"
   },
   {
    "id": "8e2d555ea9a54a3eb45e118bc3006d87",
    "time": "2021-01-25T16:39:43.753Z",
    "type": "completion"
   },
   {
    "code": "#add more movies\nimport pandas as pd\n\nmovie_urls['Tenet'] = 'https://www.rottentomatoes.com/m/tenet/'\nmovie_urls['Scoob'] = 'https://www.rottentomatoes.com/m/scoob/'\nmovie_urls['The Marksman'] = 'https://www.rottentomatoes.com/m/the_marksman_2021/'\nmovie_urls['Artemis Fowl'] = 'https://www.rottentomatoes.com/m/the_marksman_2021/'\nmovie_urls['Lovebirds'] = 'https://www.rottentomatoes.com/m/the_lovebirds_2020/'\n\nnewkeys = ['Tenet', 'Scoob', 'The Marksman', 'Artemis Fowl', 'Lovebirds']\ndfs = []\n\nfor key in newkeys:\n    print(movie_urls[key])\n    temp = get_critic_reviews(movie_urls[key])\n    df = pd.DataFrame.from_dict(temp)\n    df['Film'] = key\n    dfs.append(df)",
    "id": "22fa8e30b0f64b598b8acd6736da276a",
    "idx": 11,
    "time": "2021-01-25T16:39:47.308Z",
    "type": "execution"
   },
   {
    "code": "dfs",
    "id": "9b5af4a1b7a7445cac3f9370f0090bbf",
    "idx": 12,
    "time": "2021-01-25T16:39:51.046Z",
    "type": "execution"
   },
   {
    "id": "22fa8e30b0f64b598b8acd6736da276a",
    "time": "2021-01-25T16:40:39.261Z",
    "type": "completion"
   },
   {
    "id": "9b5af4a1b7a7445cac3f9370f0090bbf",
    "time": "2021-01-25T16:40:39.323Z",
    "type": "completion"
   },
   {
    "code": "new_films = pd.concat(dfs)\nnew_films",
    "id": "9b5af4a1b7a7445cac3f9370f0090bbf",
    "idx": 12,
    "time": "2021-01-25T16:46:35.036Z",
    "type": "execution"
   },
   {
    "id": "9b5af4a1b7a7445cac3f9370f0090bbf",
    "time": "2021-01-25T16:46:35.155Z",
    "type": "completion"
   },
   {
    "code": "import matplotlib.pyplot as plt\n\nfor key in newkeys:\n#     pd.to_numeric(df.Subs).plot.line()\n    df = new_films[new_films==key]\n    plt.plot(calculate_score(key), label=key)\n#     plt.plot(np.arange(len(df.index)), pd.to_numeric(df.Total).pct_change(), label = df.Name.values[0], color = colors[i])\n#     plt.axvline(x=30, color='red', linestyle='dashed',linewidth=0.5)\n    plt.ylabel('Percent Change in Subscribers by Day')\n    plt.xlabel(\"Day (0 is 1 month before Content Cop's release)\")\n    plt.legend()",
    "id": "768287d1dd5b4a3c813d1579a31b214e",
    "idx": 13,
    "time": "2021-01-25T16:47:06.094Z",
    "type": "execution"
   },
   {
    "id": "768287d1dd5b4a3c813d1579a31b214e",
    "time": "2021-01-25T16:47:06.496Z",
    "type": "completion"
   },
   {
    "code": "all_films",
    "id": "cb7d4c021a974c90ad1b658312c5d12a",
    "idx": 14,
    "time": "2021-01-25T16:47:30.137Z",
    "type": "execution"
   },
   {
    "id": "cb7d4c021a974c90ad1b658312c5d12a",
    "time": "2021-01-25T16:47:30.229Z",
    "type": "completion"
   },
   {
    "code": "import numpy as np\n\n\ndef calculate_score(film, frame):\n    df = frame[frame['Film'] == film]\n    grouped_1 = df[['date', 'score']].groupby('date').agg([sum, 'count'])\n    grouped_1.columns = grouped_1.columns.droplevel(0)\n    return grouped_1.cumsum()['sum']/grouped_1.cumsum()['count']\n\ncalculate_score(\"Wonder Woman 1984\")",
    "id": "b7543fc5990140e28811654f3dba74af",
    "idx": 8,
    "time": "2021-01-25T16:47:54.048Z",
    "type": "execution"
   },
   {
    "id": "b7543fc5990140e28811654f3dba74af",
    "time": "2021-01-25T16:47:54.143Z",
    "type": "completion"
   },
   {
    "code": "import matplotlib.pyplot as plt\n\nfor key in newkeys:\n#     pd.to_numeric(df.Subs).plot.line()\n    df = new_films[new_films==key]\n    plt.plot(calculate_score(key, new_films), label=key)\n#     plt.plot(np.arange(len(df.index)), pd.to_numeric(df.Total).pct_change(), label = df.Name.values[0], color = colors[i])\n#     plt.axvline(x=30, color='red', linestyle='dashed',linewidth=0.5)\n    plt.ylabel('Percent Change in Subscribers by Day')\n    plt.xlabel(\"Day (0 is 1 month before Content Cop's release)\")\n    plt.legend()",
    "id": "768287d1dd5b4a3c813d1579a31b214e",
    "idx": 13,
    "time": "2021-01-25T16:48:02.482Z",
    "type": "execution"
   },
   {
    "id": "768287d1dd5b4a3c813d1579a31b214e",
    "time": "2021-01-25T16:48:02.628Z",
    "type": "completion"
   },
   {
    "code": "new_films['score'] = new_films['fresh'].apply(lambda x: 1 if x == 'fresh' else 0)\nnew_films",
    "id": "f25df37cb47345e5ae1ead72417b9cbd",
    "idx": 13,
    "time": "2021-01-25T16:48:51.174Z",
    "type": "execution"
   },
   {
    "id": "f25df37cb47345e5ae1ead72417b9cbd",
    "time": "2021-01-25T16:48:51.281Z",
    "type": "completion"
   },
   {
    "code": "import matplotlib.pyplot as plt\n\nfor key in newkeys:\n#     pd.to_numeric(df.Subs).plot.line()\n    df = new_films[new_films==key]\n    plt.plot(calculate_score(key, new_films), label=key)\n#     plt.plot(np.arange(len(df.index)), pd.to_numeric(df.Total).pct_change(), label = df.Name.values[0], color = colors[i])\n#     plt.axvline(x=30, color='red', linestyle='dashed',linewidth=0.5)\n    plt.ylabel('Percent Change in Subscribers by Day')\n    plt.xlabel(\"Day (0 is 1 month before Content Cop's release)\")\n    plt.legend()",
    "id": "768287d1dd5b4a3c813d1579a31b214e",
    "idx": 14,
    "time": "2021-01-25T16:48:55.915Z",
    "type": "execution"
   },
   {
    "id": "768287d1dd5b4a3c813d1579a31b214e",
    "time": "2021-01-25T16:48:58.159Z",
    "type": "completion"
   },
   {
    "code": "new_films['date'] = pd.to_datetime(new_films['date'], format=\"%B %d, %Y\")\nnew_films = new_films.sort_values('date')",
    "id": "28d1a83a910348ba8934a7819639d756",
    "idx": 14,
    "time": "2021-01-25T16:49:56.207Z",
    "type": "execution"
   },
   {
    "id": "28d1a83a910348ba8934a7819639d756",
    "time": "2021-01-25T16:49:56.284Z",
    "type": "completion"
   },
   {
    "code": "import matplotlib.pyplot as plt\n\nfor key in newkeys:\n#     pd.to_numeric(df.Subs).plot.line()\n    df = new_films[new_films==key]\n    plt.plot(calculate_score(key, new_films), label=key)\n#     plt.plot(np.arange(len(df.index)), pd.to_numeric(df.Total).pct_change(), label = df.Name.values[0], color = colors[i])\n#     plt.axvline(x=30, color='red', linestyle='dashed',linewidth=0.5)\n    plt.ylabel('Percent Change in Subscribers by Day')\n    plt.xlabel(\"Day (0 is 1 month before Content Cop's release)\")\n    plt.legend()",
    "id": "768287d1dd5b4a3c813d1579a31b214e",
    "idx": 15,
    "time": "2021-01-25T16:49:56.802Z",
    "type": "execution"
   },
   {
    "id": "768287d1dd5b4a3c813d1579a31b214e",
    "time": "2021-01-25T16:49:57.341Z",
    "type": "completion"
   },
   {
    "code": "new_films",
    "id": "557b1997b7eb45ad88a2c779fa6d30a3",
    "idx": 15,
    "time": "2021-01-25T16:50:17.436Z",
    "type": "execution"
   },
   {
    "id": "557b1997b7eb45ad88a2c779fa6d30a3",
    "time": "2021-01-25T16:50:17.528Z",
    "type": "completion"
   },
   {
    "code": "all_films = pd.read_csv(\"all_films.csv\")\nall_films",
    "id": "cb7d4c021a974c90ad1b658312c5d12a",
    "idx": 17,
    "time": "2021-01-25T16:50:46.392Z",
    "type": "execution"
   },
   {
    "id": "cb7d4c021a974c90ad1b658312c5d12a",
    "time": "2021-01-25T16:50:46.521Z",
    "type": "completion"
   },
   {
    "code": "pd.concat(all_films, new_films)",
    "id": "0e8ce1f74d87429e8734ed645fc4ad98",
    "idx": 18,
    "time": "2021-01-25T16:50:54.950Z",
    "type": "execution"
   },
   {
    "id": "0e8ce1f74d87429e8734ed645fc4ad98",
    "time": "2021-01-25T16:50:55.034Z",
    "type": "completion"
   },
   {
    "code": "pd.concat([all_films, new_films])",
    "id": "0e8ce1f74d87429e8734ed645fc4ad98",
    "idx": 18,
    "time": "2021-01-25T16:51:04.058Z",
    "type": "execution"
   },
   {
    "id": "0e8ce1f74d87429e8734ed645fc4ad98",
    "time": "2021-01-25T16:51:04.168Z",
    "type": "completion"
   },
   {
    "code": "all_films = pd.concat([all_films, new_films])",
    "id": "0e8ce1f74d87429e8734ed645fc4ad98",
    "idx": 18,
    "time": "2021-01-25T16:51:10.672Z",
    "type": "execution"
   },
   {
    "id": "0e8ce1f74d87429e8734ed645fc4ad98",
    "time": "2021-01-25T16:51:10.747Z",
    "type": "completion"
   },
   {
    "code": "for key in movie_urls.keys():\n#     pd.to_numeric(df.Subs).plot.line()\n    df = all_films[all_films==key]\n    plt.plot(calculate_score(key, all_films), label=key)\n#     plt.plot(np.arange(len(df.index)), pd.to_numeric(df.Total).pct_change(), label = df.Name.values[0], color = colors[i])\n#     plt.axvline(x=30, color='red', linestyle='dashed',linewidth=0.5)\n    plt.ylabel('Percent Change in Subscribers by Day')\n    plt.xlabel(\"Day (0 is 1 month before Content Cop's release)\")\n    plt.legend()\n# plt.annotate('Content Cop released', xy=(30, 0.015), ha='center', size=10)\n# plt.title('The Impact of Content Cop')\n# plt.savefig('pct_cc.svg')",
    "id": "38b87d872cee42608a2da2aae2a0d985",
    "idx": 19,
    "time": "2021-01-25T16:51:34.324Z",
    "type": "execution"
   },
   {
    "id": "38b87d872cee42608a2da2aae2a0d985",
    "time": "2021-01-25T16:51:34.736Z",
    "type": "completion"
   },
   {
    "code": "all_films['date'] = pd.to_datetime(all_films['date'], format=\"%B %d, %Y\")\nall_films = all_films.sort_values('date')",
    "id": "9a24c85940a04b4f89db22e13764af47",
    "idx": 19,
    "time": "2021-01-25T16:52:10.504Z",
    "type": "execution"
   },
   {
    "id": "9a24c85940a04b4f89db22e13764af47",
    "time": "2021-01-25T16:52:10.686Z",
    "type": "completion"
   },
   {
    "code": "for key in movie_urls.keys():\n#     pd.to_numeric(df.Subs).plot.line()\n    df = all_films[all_films==key]\n    plt.plot(calculate_score(key, all_films), label=key)\n#     plt.plot(np.arange(len(df.index)), pd.to_numeric(df.Total).pct_change(), label = df.Name.values[0], color = colors[i])\n#     plt.axvline(x=30, color='red', linestyle='dashed',linewidth=0.5)\n    plt.ylabel('Percent Change in Subscribers by Day')\n    plt.xlabel(\"Day (0 is 1 month before Content Cop's release)\")\n    plt.legend()\n# plt.annotate('Content Cop released', xy=(30, 0.015), ha='center', size=10)\n# plt.title('The Impact of Content Cop')\n# plt.savefig('pct_cc.svg')",
    "id": "38b87d872cee42608a2da2aae2a0d985",
    "idx": 20,
    "time": "2021-01-25T16:52:11.426Z",
    "type": "execution"
   },
   {
    "id": "38b87d872cee42608a2da2aae2a0d985",
    "time": "2021-01-25T16:52:11.914Z",
    "type": "completion"
   },
   {
    "code": "all_films['date'] = pd.to_datetime(all_films['date'])\nall_films = all_films.sort_values('date')",
    "id": "9a24c85940a04b4f89db22e13764af47",
    "idx": 19,
    "time": "2021-01-25T16:52:53.629Z",
    "type": "execution"
   },
   {
    "id": "9a24c85940a04b4f89db22e13764af47",
    "time": "2021-01-25T16:52:53.704Z",
    "type": "completion"
   },
   {
    "code": "for key in movie_urls.keys():\n#     pd.to_numeric(df.Subs).plot.line()\n    df = all_films[all_films==key]\n    plt.plot(calculate_score(key, all_films), label=key)\n#     plt.plot(np.arange(len(df.index)), pd.to_numeric(df.Total).pct_change(), label = df.Name.values[0], color = colors[i])\n#     plt.axvline(x=30, color='red', linestyle='dashed',linewidth=0.5)\n    plt.ylabel('Percent Change in Subscribers by Day')\n    plt.xlabel(\"Day (0 is 1 month before Content Cop's release)\")\n    plt.legend()\n# plt.annotate('Content Cop released', xy=(30, 0.015), ha='center', size=10)\n# plt.title('The Impact of Content Cop')\n# plt.savefig('pct_cc.svg')",
    "id": "38b87d872cee42608a2da2aae2a0d985",
    "idx": 20,
    "time": "2021-01-25T16:52:55.815Z",
    "type": "execution"
   },
   {
    "id": "38b87d872cee42608a2da2aae2a0d985",
    "time": "2021-01-25T16:52:56.442Z",
    "type": "completion"
   },
   {
    "code": "calculate_score(\"Lovebirds\",all_films)",
    "id": "8c3d3fca7294407980c1e709032f69b3",
    "idx": 21,
    "time": "2021-01-25T16:53:43.200Z",
    "type": "execution"
   },
   {
    "id": "8c3d3fca7294407980c1e709032f69b3",
    "time": "2021-01-25T16:53:43.296Z",
    "type": "completion"
   },
   {
    "code": "dfs",
    "id": "c5a30e54c362450e8ae6e35bce30ecab",
    "idx": 22,
    "time": "2021-01-25T16:54:09.357Z",
    "type": "execution"
   },
   {
    "id": "c5a30e54c362450e8ae6e35bce30ecab",
    "time": "2021-01-25T16:54:09.532Z",
    "type": "completion"
   },
   {
    "code": "calculate_score(\"Artemis Fowl\",all_films)",
    "id": "8c3d3fca7294407980c1e709032f69b3",
    "idx": 21,
    "time": "2021-01-25T16:54:27.122Z",
    "type": "execution"
   },
   {
    "id": "8c3d3fca7294407980c1e709032f69b3",
    "time": "2021-01-25T16:54:27.215Z",
    "type": "completion"
   },
   {
    "code": "calculate_score(\"Artemis Fowl\",all_films).plot()",
    "id": "8c3d3fca7294407980c1e709032f69b3",
    "idx": 21,
    "time": "2021-01-25T16:54:38.001Z",
    "type": "execution"
   },
   {
    "id": "8c3d3fca7294407980c1e709032f69b3",
    "time": "2021-01-25T16:54:38.415Z",
    "type": "completion"
   },
   {
    "code": "#add more movies\nimport pandas as pd\n\nmovie_urls['Tenet'] = 'https://www.rottentomatoes.com/m/tenet/'\nmovie_urls['Scoob'] = 'https://www.rottentomatoes.com/m/scoob/'\nmovie_urls['The Marksman'] = 'https://www.rottentomatoes.com/m/the_marksman_2021/'\nmovie_urls['Artemis Fowl'] = 'https://www.rottentomatoes.com/m/artemis_fowl/'\nmovie_urls['Lovebirds'] = 'https://www.rottentomatoes.com/m/the_lovebirds_2020/'\n\nnewkeys = ['Tenet', 'Scoob', 'The Marksman', 'Artemis Fowl', 'Lovebirds']\ndfs = []\n\nfor key in newkeys:\n    print(movie_urls[key])\n    temp = get_critic_reviews(movie_urls[key])\n    df = pd.DataFrame.from_dict(temp)\n    df['Film'] = key\n    dfs.append(df)",
    "id": "22fa8e30b0f64b598b8acd6736da276a",
    "idx": 11,
    "time": "2021-01-25T16:55:27.487Z",
    "type": "execution"
   },
   {
    "code": "new_films = pd.concat(dfs)\nnew_films",
    "id": "9b5af4a1b7a7445cac3f9370f0090bbf",
    "idx": 12,
    "time": "2021-01-25T16:55:27.650Z",
    "type": "execution"
   },
   {
    "code": "new_films['score'] = new_films['fresh'].apply(lambda x: 1 if x == 'fresh' else 0)\nnew_films",
    "id": "f25df37cb47345e5ae1ead72417b9cbd",
    "idx": 13,
    "time": "2021-01-25T16:55:27.835Z",
    "type": "execution"
   },
   {
    "code": "new_films['date'] = pd.to_datetime(new_films['date'], format=\"%B %d, %Y\")\nnew_films = new_films.sort_values('date')",
    "id": "28d1a83a910348ba8934a7819639d756",
    "idx": 14,
    "time": "2021-01-25T16:55:28.030Z",
    "type": "execution"
   },
   {
    "code": "new_films",
    "id": "557b1997b7eb45ad88a2c779fa6d30a3",
    "idx": 15,
    "time": "2021-01-25T16:55:28.238Z",
    "type": "execution"
   },
   {
    "code": "import matplotlib.pyplot as plt\n\nfor key in newkeys:\n#     pd.to_numeric(df.Subs).plot.line()\n    df = new_films[new_films==key]\n    plt.plot(calculate_score(key, new_films), label=key)\n#     plt.plot(np.arange(len(df.index)), pd.to_numeric(df.Total).pct_change(), label = df.Name.values[0], color = colors[i])\n#     plt.axvline(x=30, color='red', linestyle='dashed',linewidth=0.5)\n    plt.ylabel('Percent Change in Subscribers by Day')\n    plt.xlabel(\"Day (0 is 1 month before Content Cop's release)\")\n    plt.legend()",
    "id": "768287d1dd5b4a3c813d1579a31b214e",
    "idx": 16,
    "time": "2021-01-25T16:55:28.802Z",
    "type": "execution"
   },
   {
    "code": "all_films = pd.read_csv(\"all_films.csv\")\nall_films",
    "id": "cb7d4c021a974c90ad1b658312c5d12a",
    "idx": 17,
    "time": "2021-01-25T16:55:30.535Z",
    "type": "execution"
   },
   {
    "code": "all_films = pd.concat([all_films, new_films])",
    "id": "0e8ce1f74d87429e8734ed645fc4ad98",
    "idx": 18,
    "time": "2021-01-25T16:55:30.815Z",
    "type": "execution"
   },
   {
    "code": "all_films['date'] = pd.to_datetime(all_films['date'])\nall_films = all_films.sort_values('date')",
    "id": "9a24c85940a04b4f89db22e13764af47",
    "idx": 19,
    "time": "2021-01-25T16:55:31.294Z",
    "type": "execution"
   },
   {
    "code": "for key in movie_urls.keys():\n#     pd.to_numeric(df.Subs).plot.line()\n    df = all_films[all_films==key]\n    plt.plot(calculate_score(key, all_films), label=key)\n#     plt.plot(np.arange(len(df.index)), pd.to_numeric(df.Total).pct_change(), label = df.Name.values[0], color = colors[i])\n#     plt.axvline(x=30, color='red', linestyle='dashed',linewidth=0.5)\n    plt.ylabel('Percent Change in Subscribers by Day')\n    plt.xlabel(\"Day (0 is 1 month before Content Cop's release)\")\n    plt.legend()\n# plt.annotate('Content Cop released', xy=(30, 0.015), ha='center', size=10)\n# plt.title('The Impact of Content Cop')\n# plt.savefig('pct_cc.svg')",
    "id": "38b87d872cee42608a2da2aae2a0d985",
    "idx": 20,
    "time": "2021-01-25T16:55:31.879Z",
    "type": "execution"
   },
   {
    "code": "calculate_score(\"Artemis Fowl\",all_films).plot()",
    "id": "8c3d3fca7294407980c1e709032f69b3",
    "idx": 21,
    "time": "2021-01-25T16:55:34.391Z",
    "type": "execution"
   },
   {
    "id": "22fa8e30b0f64b598b8acd6736da276a",
    "time": "2021-01-25T16:56:13.940Z",
    "type": "completion"
   },
   {
    "id": "9b5af4a1b7a7445cac3f9370f0090bbf",
    "time": "2021-01-25T16:56:14.001Z",
    "type": "completion"
   },
   {
    "id": "f25df37cb47345e5ae1ead72417b9cbd",
    "time": "2021-01-25T16:56:14.005Z",
    "type": "completion"
   },
   {
    "id": "28d1a83a910348ba8934a7819639d756",
    "time": "2021-01-25T16:56:14.022Z",
    "type": "completion"
   },
   {
    "id": "557b1997b7eb45ad88a2c779fa6d30a3",
    "time": "2021-01-25T16:56:14.031Z",
    "type": "completion"
   },
   {
    "id": "768287d1dd5b4a3c813d1579a31b214e",
    "time": "2021-01-25T16:56:14.431Z",
    "type": "completion"
   },
   {
    "id": "cb7d4c021a974c90ad1b658312c5d12a",
    "time": "2021-01-25T16:56:14.435Z",
    "type": "completion"
   },
   {
    "id": "0e8ce1f74d87429e8734ed645fc4ad98",
    "time": "2021-01-25T16:56:14.436Z",
    "type": "completion"
   },
   {
    "id": "9a24c85940a04b4f89db22e13764af47",
    "time": "2021-01-25T16:56:14.444Z",
    "type": "completion"
   },
   {
    "id": "38b87d872cee42608a2da2aae2a0d985",
    "time": "2021-01-25T16:56:14.986Z",
    "type": "completion"
   },
   {
    "id": "8c3d3fca7294407980c1e709032f69b3",
    "time": "2021-01-25T16:56:15.135Z",
    "type": "completion"
   },
   {
    "code": "calculate_score(\"Wonder Woman 1984\",all_films).plot()",
    "id": "c5a30e54c362450e8ae6e35bce30ecab",
    "idx": 22,
    "time": "2021-01-25T16:58:10.714Z",
    "type": "execution"
   },
   {
    "id": "c5a30e54c362450e8ae6e35bce30ecab",
    "time": "2021-01-25T16:58:11.228Z",
    "type": "completion"
   },
   {
    "code": "calculate_score(\"Mulan\",all_films).plot()",
    "id": "f621f1fe85de4ece889fcb42a4c9be45",
    "idx": 23,
    "time": "2021-01-25T16:58:34.649Z",
    "type": "execution"
   },
   {
    "id": "f621f1fe85de4ece889fcb42a4c9be45",
    "time": "2021-01-25T16:58:35.082Z",
    "type": "completion"
   },
   {
    "code": "calculate_score(\"Tenet\",all_films).plot()",
    "id": "9aa215e710244e988e051ae025606f59",
    "idx": 24,
    "time": "2021-01-25T16:58:40.851Z",
    "type": "execution"
   },
   {
    "id": "9aa215e710244e988e051ae025606f59",
    "time": "2021-01-25T16:58:41.178Z",
    "type": "completion"
   },
   {
    "code": "calculate_score(\"Birds of Prey\",all_films).plot()",
    "id": "f164a2c26f3941c68aea5f9bfc3468ed",
    "idx": 25,
    "time": "2021-01-25T17:00:48.750Z",
    "type": "execution"
   },
   {
    "id": "f164a2c26f3941c68aea5f9bfc3468ed",
    "time": "2021-01-25T17:00:49.186Z",
    "type": "completion"
   },
   {
    "code": "calculate_score(\"Lovebirds\",all_films).plot()",
    "id": "f164a2c26f3941c68aea5f9bfc3468ed",
    "idx": 25,
    "time": "2021-01-25T17:01:23.937Z",
    "type": "execution"
   },
   {
    "id": "f164a2c26f3941c68aea5f9bfc3468ed",
    "time": "2021-01-25T17:01:24.287Z",
    "type": "completion"
   },
   {
    "code": "def plot_film(film):\n    df = all_films[all_films==film]\n    plt.plot(calculate_score(film, all_films))\n    plt.axhline(y=0.75, color='yellow', linestyle='dashed',linewidth=0.5)\n    plt.axhline(y=0.6, color='red', linestyle='dashed',linewidth=0.5)",
    "id": "a939598316054d528c40aab130b5481c",
    "idx": 21,
    "time": "2021-01-25T17:04:03.192Z",
    "type": "execution"
   },
   {
    "id": "a939598316054d528c40aab130b5481c",
    "time": "2021-01-25T17:04:03.263Z",
    "type": "completion"
   },
   {
    "code": "# calculate_score(\"Artemis Fowl\",all_films).plot()\nplot_film(\"Artemis Fowl\")",
    "id": "8c3d3fca7294407980c1e709032f69b3",
    "idx": 22,
    "time": "2021-01-25T17:04:16.689Z",
    "type": "execution"
   },
   {
    "id": "8c3d3fca7294407980c1e709032f69b3",
    "time": "2021-01-25T17:04:17.342Z",
    "type": "completion"
   },
   {
    "code": "calculate_score(\"Artemis Fowl\",all_films)\n# plot_film(\"Artemis Fowl\")",
    "id": "8c3d3fca7294407980c1e709032f69b3",
    "idx": 22,
    "time": "2021-01-25T17:05:33.826Z",
    "type": "execution"
   },
   {
    "id": "8c3d3fca7294407980c1e709032f69b3",
    "time": "2021-01-25T17:05:33.916Z",
    "type": "completion"
   },
   {
    "code": "calculate_score(\"Artemis Fowl\",all_films).max()\n# plot_film(\"Artemis Fowl\")",
    "id": "8c3d3fca7294407980c1e709032f69b3",
    "idx": 22,
    "time": "2021-01-25T17:06:41.263Z",
    "type": "execution"
   },
   {
    "id": "8c3d3fca7294407980c1e709032f69b3",
    "time": "2021-01-25T17:06:41.348Z",
    "type": "completion"
   },
   {
    "code": "calculate_score(\"Artemis Fowl\",all_films).min()\n# plot_film(\"Artemis Fowl\")",
    "id": "8c3d3fca7294407980c1e709032f69b3",
    "idx": 22,
    "time": "2021-01-25T17:06:44.272Z",
    "type": "execution"
   },
   {
    "id": "8c3d3fca7294407980c1e709032f69b3",
    "time": "2021-01-25T17:06:44.354Z",
    "type": "completion"
   },
   {
    "code": "calculate_score(\"Artemis Fowl\",all_films)\n# plot_film(\"Artemis Fowl\")",
    "id": "8c3d3fca7294407980c1e709032f69b3",
    "idx": 22,
    "time": "2021-01-25T17:06:50.551Z",
    "type": "execution"
   },
   {
    "id": "8c3d3fca7294407980c1e709032f69b3",
    "time": "2021-01-25T17:06:50.647Z",
    "type": "completion"
   },
   {
    "code": "def plot_film(film):\n    df = all_films[all_films==film]\n    series = calculate_score(film, all_films)\n    plt.plot(series)\n    plt.axhline(y=0.75, color='yellow', linestyle='dashed',linewidth=0.5)\n    plt.axhline(y=0.6, color='red', linestyle='dashed',linewidth=0.5)\n    plt.ylim(series.min(), series.max())",
    "id": "a939598316054d528c40aab130b5481c",
    "idx": 21,
    "time": "2021-01-25T17:07:23.892Z",
    "type": "execution"
   },
   {
    "id": "a939598316054d528c40aab130b5481c",
    "time": "2021-01-25T17:07:23.962Z",
    "type": "completion"
   },
   {
    "code": "calculate_score(\"Artemis Fowl\",all_films)\n# plot_film(\"Artemis Fowl\")",
    "id": "8c3d3fca7294407980c1e709032f69b3",
    "idx": 22,
    "time": "2021-01-25T17:07:24.639Z",
    "type": "execution"
   },
   {
    "id": "8c3d3fca7294407980c1e709032f69b3",
    "time": "2021-01-25T17:07:24.731Z",
    "type": "completion"
   },
   {
    "code": "# calculate_score(\"Artemis Fowl\",all_films)\nplot_film(\"Artemis Fowl\")",
    "id": "8c3d3fca7294407980c1e709032f69b3",
    "idx": 22,
    "time": "2021-01-25T17:07:29.976Z",
    "type": "execution"
   },
   {
    "id": "8c3d3fca7294407980c1e709032f69b3",
    "time": "2021-01-25T17:07:30.443Z",
    "type": "completion"
   },
   {
    "code": "# calculate_score(\"Wonder Woman 1984\",all_films).plot()\nplot_film(\"Wonder Woman 1984\")",
    "id": "c5a30e54c362450e8ae6e35bce30ecab",
    "idx": 23,
    "time": "2021-01-25T17:07:43.538Z",
    "type": "execution"
   },
   {
    "id": "c5a30e54c362450e8ae6e35bce30ecab",
    "time": "2021-01-25T17:07:43.878Z",
    "type": "completion"
   },
   {
    "code": "# calculate_score(\"Mulan\",all_films).plot()\nplot_film(\"Mulan\")",
    "id": "f621f1fe85de4ece889fcb42a4c9be45",
    "idx": 24,
    "time": "2021-01-25T17:09:14.444Z",
    "type": "execution"
   },
   {
    "id": "f621f1fe85de4ece889fcb42a4c9be45",
    "time": "2021-01-25T17:09:14.799Z",
    "type": "completion"
   },
   {
    "code": "# calculate_score(\"Tenet\",all_films).plot()\nplot_film(\"Tenet\")",
    "id": "9aa215e710244e988e051ae025606f59",
    "idx": 25,
    "time": "2021-01-25T17:09:22.942Z",
    "type": "execution"
   },
   {
    "id": "9aa215e710244e988e051ae025606f59",
    "time": "2021-01-25T17:09:23.252Z",
    "type": "completion"
   },
   {
    "code": "def plot_film(film):\n    df = all_films[all_films==film]\n    series = calculate_score(film, all_films)\n    plt.plot(series)\n#     plt.axhline(y=0.75, color='yellow', linestyle='dashed',linewidth=0.5)\n#     plt.axhline(y=0.6, color='red', linestyle='dashed',linewidth=0.5)\n    ax.axhspan(0.75, 1, alpha=0.5, color='green')\n    ax.axhspan(0.6,75, alpha=0.5, color='yellow')\n    ax.axhspan(0, 0.6, alpha=0.5, color='red')\n    plt.ylim(series.min(), series.max())",
    "id": "a939598316054d528c40aab130b5481c",
    "idx": 21,
    "time": "2021-01-25T17:13:19.201Z",
    "type": "execution"
   },
   {
    "id": "a939598316054d528c40aab130b5481c",
    "time": "2021-01-25T17:13:19.293Z",
    "type": "completion"
   },
   {
    "code": "# calculate_score(\"Artemis Fowl\",all_films)\nplot_film(\"Artemis Fowl\")",
    "id": "8c3d3fca7294407980c1e709032f69b3",
    "idx": 22,
    "time": "2021-01-25T17:13:20.080Z",
    "type": "execution"
   },
   {
    "id": "8c3d3fca7294407980c1e709032f69b3",
    "time": "2021-01-25T17:13:20.413Z",
    "type": "completion"
   },
   {
    "code": "def plot_film(film):\n    df = all_films[all_films==film]\n    series = calculate_score(film, all_films)\n    plt.plot(series)\n#     plt.axhline(y=0.75, color='yellow', linestyle='dashed',linewidth=0.5)\n#     plt.axhline(y=0.6, color='red', linestyle='dashed',linewidth=0.5)\n    plt.axhspan(0.75, 1, alpha=0.5, color='green')\n    plt.axhspan(0.6,75, alpha=0.5, color='yellow')\n    plt.axhspan(0, 0.6, alpha=0.5, color='red')\n    plt.ylim(series.min(), series.max())",
    "id": "a939598316054d528c40aab130b5481c",
    "idx": 21,
    "time": "2021-01-25T17:13:28.829Z",
    "type": "execution"
   },
   {
    "id": "a939598316054d528c40aab130b5481c",
    "time": "2021-01-25T17:13:28.898Z",
    "type": "completion"
   },
   {
    "code": "# calculate_score(\"Artemis Fowl\",all_films)\nplot_film(\"Artemis Fowl\")",
    "id": "8c3d3fca7294407980c1e709032f69b3",
    "idx": 22,
    "time": "2021-01-25T17:13:29.360Z",
    "type": "execution"
   },
   {
    "id": "8c3d3fca7294407980c1e709032f69b3",
    "time": "2021-01-25T17:13:29.747Z",
    "type": "completion"
   },
   {
    "code": "# calculate_score(\"Wonder Woman 1984\",all_films).plot()\nplot_film(\"Wonder Woman 1984\")",
    "id": "c5a30e54c362450e8ae6e35bce30ecab",
    "idx": 23,
    "time": "2021-01-25T17:13:32.823Z",
    "type": "execution"
   },
   {
    "id": "c5a30e54c362450e8ae6e35bce30ecab",
    "time": "2021-01-25T17:13:33.152Z",
    "type": "completion"
   },
   {
    "code": "def plot_film(film):\n    df = all_films[all_films==film]\n    series = calculate_score(film, all_films)\n    plt.plot(series)\n    plt.axhline(y=0.75, color='yellow', linestyle='dashed',linewidth=0.5)\n    plt.axhline(y=0.6, color='red', linestyle='dashed',linewidth=0.5)\n    plt.axhspan(0.75, 1, alpha=0.5, color='green')\n    plt.axhspan(0.6,75, alpha=0.5, color='yellow')\n    plt.axhspan(0, 0.6, alpha=0.5, color='red')\n    plt.ylim(series.min(), series.max())",
    "id": "a939598316054d528c40aab130b5481c",
    "idx": 21,
    "time": "2021-01-25T17:14:05.655Z",
    "type": "execution"
   },
   {
    "id": "a939598316054d528c40aab130b5481c",
    "time": "2021-01-25T17:14:05.735Z",
    "type": "completion"
   },
   {
    "code": "# calculate_score(\"Artemis Fowl\",all_films)\nplot_film(\"Artemis Fowl\")",
    "id": "8c3d3fca7294407980c1e709032f69b3",
    "idx": 22,
    "time": "2021-01-25T17:14:06.083Z",
    "type": "execution"
   },
   {
    "id": "8c3d3fca7294407980c1e709032f69b3",
    "time": "2021-01-25T17:14:06.546Z",
    "type": "completion"
   },
   {
    "code": "# calculate_score(\"Wonder Woman 1984\",all_films).plot()\nplot_film(\"Wonder Woman 1984\")",
    "id": "c5a30e54c362450e8ae6e35bce30ecab",
    "idx": 23,
    "time": "2021-01-25T17:14:06.551Z",
    "type": "execution"
   },
   {
    "id": "c5a30e54c362450e8ae6e35bce30ecab",
    "time": "2021-01-25T17:14:06.896Z",
    "type": "completion"
   },
   {
    "code": "def plot_film(film):\n    df = all_films[all_films==film]\n    series = calculate_score(film, all_films)    \n    plt.axhline(y=0.75, color='yellow', linestyle='dashed',linewidth=0.5)\n    plt.axhline(y=0.6, color='red', linestyle='dashed',linewidth=0.5)\n    plt.axhspan(0.75, 1, alpha=0.5, color='green')\n    plt.axhspan(0.6,75, alpha=0.5, color='yellow')\n    plt.axhspan(0, 0.6, alpha=0.5, color='red')\n    plt.plot(series)\n    plt.ylim(series.min(), series.max())",
    "id": "a939598316054d528c40aab130b5481c",
    "idx": 21,
    "time": "2021-01-25T17:14:21.050Z",
    "type": "execution"
   },
   {
    "id": "a939598316054d528c40aab130b5481c",
    "time": "2021-01-25T17:14:21.143Z",
    "type": "completion"
   },
   {
    "code": "# calculate_score(\"Artemis Fowl\",all_films)\nplot_film(\"Artemis Fowl\")",
    "id": "8c3d3fca7294407980c1e709032f69b3",
    "idx": 22,
    "time": "2021-01-25T17:14:21.438Z",
    "type": "execution"
   },
   {
    "id": "8c3d3fca7294407980c1e709032f69b3",
    "time": "2021-01-25T17:14:21.722Z",
    "type": "completion"
   },
   {
    "code": "# calculate_score(\"Wonder Woman 1984\",all_films).plot()\nplot_film(\"Wonder Woman 1984\")",
    "id": "c5a30e54c362450e8ae6e35bce30ecab",
    "idx": 23,
    "time": "2021-01-25T17:14:26.067Z",
    "type": "execution"
   },
   {
    "id": "c5a30e54c362450e8ae6e35bce30ecab",
    "time": "2021-01-25T17:14:26.457Z",
    "type": "completion"
   },
   {
    "code": "def plot_film(film):\n    df = all_films[all_films==film]\n    series = calculate_score(film, all_films)\n    plt.plot(series)\n    plt.axhline(y=0.75, color='yellow', linestyle='dashed',linewidth=0.5)\n    plt.axhline(y=0.6, color='red', linestyle='dashed',linewidth=0.5)\n    plt.axhspan(0.75, 1, alpha=0.5, color='green')\n    plt.axhspan(0.6,75, alpha=0.5, color='yellow')\n    plt.axhspan(0, 0.6, alpha=0.5, color='red')\n    plt.ylim(series.min(), series.max())",
    "id": "a939598316054d528c40aab130b5481c",
    "idx": 21,
    "time": "2021-01-25T17:15:29.926Z",
    "type": "execution"
   },
   {
    "id": "a939598316054d528c40aab130b5481c",
    "time": "2021-01-25T17:15:29.994Z",
    "type": "completion"
   },
   {
    "code": "# calculate_score(\"Artemis Fowl\",all_films)\nplot_film(\"Artemis Fowl\")",
    "id": "8c3d3fca7294407980c1e709032f69b3",
    "idx": 22,
    "time": "2021-01-25T17:15:30.303Z",
    "type": "execution"
   },
   {
    "id": "8c3d3fca7294407980c1e709032f69b3",
    "time": "2021-01-25T17:15:30.617Z",
    "type": "completion"
   },
   {
    "code": "# calculate_score(\"Wonder Woman 1984\",all_films).plot()\nplot_film(\"Wonder Woman 1984\")",
    "id": "c5a30e54c362450e8ae6e35bce30ecab",
    "idx": 23,
    "time": "2021-01-25T17:15:30.775Z",
    "type": "execution"
   },
   {
    "id": "c5a30e54c362450e8ae6e35bce30ecab",
    "time": "2021-01-25T17:15:31.105Z",
    "type": "completion"
   },
   {
    "code": "def plot_film(film):\n    df = all_films[all_films==film]\n    series = calculate_score(film, all_films)\n    plt.plot(series)\n    plt.axhline(y=0.75, color='yellow', linestyle='dashed',linewidth=0.5)\n    plt.axhline(y=0.6, color='red', linestyle='dashed',linewidth=0.5)\n    plt.axhspan(0.75, 1, alpha=0.5, color='lightgreen')\n    plt.axhspan(0.6,75, alpha=0.5, color='yellow')\n    plt.axhspan(0, 0.6, alpha=0.5, color='red')\n    plt.ylim(series.min(), series.max())",
    "id": "a939598316054d528c40aab130b5481c",
    "idx": 21,
    "time": "2021-01-25T17:17:40.973Z",
    "type": "execution"
   },
   {
    "id": "a939598316054d528c40aab130b5481c",
    "time": "2021-01-25T17:17:41.050Z",
    "type": "completion"
   },
   {
    "code": "# calculate_score(\"Artemis Fowl\",all_films)\nplot_film(\"Artemis Fowl\")",
    "id": "8c3d3fca7294407980c1e709032f69b3",
    "idx": 22,
    "time": "2021-01-25T17:17:41.439Z",
    "type": "execution"
   },
   {
    "id": "8c3d3fca7294407980c1e709032f69b3",
    "time": "2021-01-25T17:17:41.807Z",
    "type": "completion"
   },
   {
    "code": "# calculate_score(\"Wonder Woman 1984\",all_films).plot()\nplot_film(\"Wonder Woman 1984\")",
    "id": "c5a30e54c362450e8ae6e35bce30ecab",
    "idx": 23,
    "time": "2021-01-25T17:17:42.268Z",
    "type": "execution"
   },
   {
    "id": "c5a30e54c362450e8ae6e35bce30ecab",
    "time": "2021-01-25T17:17:42.687Z",
    "type": "completion"
   },
   {
    "code": "def plot_film(film):\n    df = all_films[all_films==film]\n    series = calculate_score(film, all_films)\n    plt.plot(series)\n    plt.axhline(y=0.75, color='yellow', linestyle='dashed',linewidth=0.5)\n    plt.axhline(y=0.6, color='red', linestyle='dashed',linewidth=0.5)\n    plt.axhspan(0.75, 1, alpha=0.5, color='darkgreen')\n    plt.axhspan(0.6,75, alpha=0.5, color='yellow')\n    plt.axhspan(0, 0.6, alpha=0.5, color='red')\n    plt.ylim(series.min(), series.max())",
    "id": "a939598316054d528c40aab130b5481c",
    "idx": 21,
    "time": "2021-01-25T17:18:09.627Z",
    "type": "execution"
   },
   {
    "id": "a939598316054d528c40aab130b5481c",
    "time": "2021-01-25T17:18:09.696Z",
    "type": "completion"
   },
   {
    "code": "# calculate_score(\"Artemis Fowl\",all_films)\nplot_film(\"Artemis Fowl\")",
    "id": "8c3d3fca7294407980c1e709032f69b3",
    "idx": 22,
    "time": "2021-01-25T17:18:10.336Z",
    "type": "execution"
   },
   {
    "id": "8c3d3fca7294407980c1e709032f69b3",
    "time": "2021-01-25T17:18:10.724Z",
    "type": "completion"
   },
   {
    "code": "# calculate_score(\"Wonder Woman 1984\",all_films).plot()\nplot_film(\"Wonder Woman 1984\")",
    "id": "c5a30e54c362450e8ae6e35bce30ecab",
    "idx": 23,
    "time": "2021-01-25T17:18:11.328Z",
    "type": "execution"
   },
   {
    "id": "c5a30e54c362450e8ae6e35bce30ecab",
    "time": "2021-01-25T17:18:11.777Z",
    "type": "completion"
   },
   {
    "code": "def plot_film(film):\n    df = all_films[all_films==film]\n    series = calculate_score(film, all_films)\n    plt.plot(series)\n    plt.axhline(y=0.75, color='yellow', linestyle='dashed',linewidth=0.5)\n    plt.axhline(y=0.6, color='red', linestyle='dashed',linewidth=0.5)\n    plt.axhspan(0.75, 1, alpha=0.5, color='green')\n    plt.axhspan(0.6,75, alpha=0.5, color='yellow')\n    plt.axhspan(0, 0.6, alpha=0.5, color='red')\n    plt.ylim(series.min(), series.max())",
    "id": "a939598316054d528c40aab130b5481c",
    "idx": 21,
    "time": "2021-01-25T17:18:32.730Z",
    "type": "execution"
   },
   {
    "id": "a939598316054d528c40aab130b5481c",
    "time": "2021-01-25T17:18:32.799Z",
    "type": "completion"
   },
   {
    "code": "def plot_film(film):\n    df = all_films[all_films==film]\n    series = calculate_score(film, all_films)\n    plt.plot(series)\n    plt.axhline(y=0.75, color='yellow', linestyle='dashed',linewidth=0.5)\n    plt.axhline(y=0.6, color='red', linestyle='dashed',linewidth=0.5)\n    plt.axhspan(0.75, 1, alpha=0.5, color='#2ca02c)\n    plt.axhspan(0.6,75, alpha=0.5, color='yellow')\n    plt.axhspan(0, 0.6, alpha=0.5, color='red')\n    plt.ylim(series.min(), series.max())",
    "id": "a939598316054d528c40aab130b5481c",
    "idx": 21,
    "time": "2021-01-25T17:19:07.895Z",
    "type": "execution"
   },
   {
    "id": "a939598316054d528c40aab130b5481c",
    "time": "2021-01-25T17:19:08.001Z",
    "type": "completion"
   },
   {
    "code": "# calculate_score(\"Artemis Fowl\",all_films)\nplot_film(\"Artemis Fowl\")",
    "id": "8c3d3fca7294407980c1e709032f69b3",
    "idx": 22,
    "time": "2021-01-25T17:19:08.347Z",
    "type": "execution"
   },
   {
    "code": "# calculate_score(\"Wonder Woman 1984\",all_films).plot()\nplot_film(\"Wonder Woman 1984\")",
    "id": "c5a30e54c362450e8ae6e35bce30ecab",
    "idx": 23,
    "time": "2021-01-25T17:19:08.623Z",
    "type": "execution"
   },
   {
    "id": "8c3d3fca7294407980c1e709032f69b3",
    "time": "2021-01-25T17:19:08.660Z",
    "type": "completion"
   },
   {
    "id": "c5a30e54c362450e8ae6e35bce30ecab",
    "time": "2021-01-25T17:19:08.942Z",
    "type": "completion"
   },
   {
    "code": "def plot_film(film):\n    df = all_films[all_films==film]\n    series = calculate_score(film, all_films)\n    plt.plot(series)\n    plt.axhline(y=0.75, color='yellow', linestyle='dashed',linewidth=0.5)\n    plt.axhline(y=0.6, color='red', linestyle='dashed',linewidth=0.5)\n    plt.axhspan(0.75, 1, alpha=0.5, color='#2ca02c')\n    plt.axhspan(0.6,75, alpha=0.5, color='yellow')\n    plt.axhspan(0, 0.6, alpha=0.5, color='red')\n    plt.ylim(series.min(), series.max())",
    "id": "a939598316054d528c40aab130b5481c",
    "idx": 21,
    "time": "2021-01-25T17:19:13.446Z",
    "type": "execution"
   },
   {
    "id": "a939598316054d528c40aab130b5481c",
    "time": "2021-01-25T17:19:13.517Z",
    "type": "completion"
   },
   {
    "code": "# calculate_score(\"Artemis Fowl\",all_films)\nplot_film(\"Artemis Fowl\")",
    "id": "8c3d3fca7294407980c1e709032f69b3",
    "idx": 22,
    "time": "2021-01-25T17:19:14.036Z",
    "type": "execution"
   },
   {
    "code": "# calculate_score(\"Wonder Woman 1984\",all_films).plot()\nplot_film(\"Wonder Woman 1984\")",
    "id": "c5a30e54c362450e8ae6e35bce30ecab",
    "idx": 23,
    "time": "2021-01-25T17:19:14.349Z",
    "type": "execution"
   },
   {
    "id": "8c3d3fca7294407980c1e709032f69b3",
    "time": "2021-01-25T17:19:14.381Z",
    "type": "completion"
   },
   {
    "id": "c5a30e54c362450e8ae6e35bce30ecab",
    "time": "2021-01-25T17:19:14.726Z",
    "type": "completion"
   },
   {
    "code": "%config InlineBackend.figure_format = 'svg'",
    "id": "2d3d335f5b634d9686f3738ede5c2e78",
    "idx": 21,
    "time": "2021-01-25T17:19:49.466Z",
    "type": "execution"
   },
   {
    "id": "2d3d335f5b634d9686f3738ede5c2e78",
    "time": "2021-01-25T17:19:49.549Z",
    "type": "completion"
   },
   {
    "code": "def plot_film(film):\n    df = all_films[all_films==film]\n    series = calculate_score(film, all_films)\n    plt.plot(series)\n    plt.axhline(y=0.75, color='yellow', linestyle='dashed',linewidth=0.5)\n    plt.axhline(y=0.6, color='red', linestyle='dashed',linewidth=0.5)\n    plt.axhspan(0.75, 1, alpha=0.5, color='#2ca02c')\n    plt.axhspan(0.6,75, alpha=0.5, color='yellow')\n    plt.axhspan(0, 0.6, alpha=0.5, color='red')\n    plt.ylim(series.min(), series.max())",
    "id": "a939598316054d528c40aab130b5481c",
    "idx": 22,
    "time": "2021-01-25T17:19:50.028Z",
    "type": "execution"
   },
   {
    "id": "a939598316054d528c40aab130b5481c",
    "time": "2021-01-25T17:19:50.098Z",
    "type": "completion"
   },
   {
    "code": "# calculate_score(\"Artemis Fowl\",all_films)\nplot_film(\"Artemis Fowl\")",
    "id": "8c3d3fca7294407980c1e709032f69b3",
    "idx": 23,
    "time": "2021-01-25T17:19:50.922Z",
    "type": "execution"
   },
   {
    "id": "8c3d3fca7294407980c1e709032f69b3",
    "time": "2021-01-25T17:19:51.315Z",
    "type": "completion"
   },
   {
    "code": "# calculate_score(\"Wonder Woman 1984\",all_films).plot()\nplot_film(\"Wonder Woman 1984\")",
    "id": "c5a30e54c362450e8ae6e35bce30ecab",
    "idx": 24,
    "time": "2021-01-25T17:19:51.969Z",
    "type": "execution"
   },
   {
    "id": "c5a30e54c362450e8ae6e35bce30ecab",
    "time": "2021-01-25T17:19:52.375Z",
    "type": "completion"
   },
   {
    "code": "def plot_film(film):\n    df = all_films[all_films==film]\n    series = calculate_score(film, all_films)\n    plt.plot(series)\n    plt.axhline(y=0.75, color='yellow', linestyle='dashed',linewidth=0.5)\n    plt.axhline(y=0.6, color='red', linestyle='dashed',linewidth=0.5)\n    plt.axhspan(0.75, 1, alpha=0.5, color='#2ca02c')\n    plt.axhspan(0.6,75, alpha=0.5, color='yellow')\n    plt.axhspan(0, 0.6, alpha=0.5, color='red')\n    plt.ylim(series.min(), series.max())\n    plt.title(film + \" Rotten Tomatoes Score over Time\")",
    "id": "a939598316054d528c40aab130b5481c",
    "idx": 22,
    "time": "2021-01-25T17:20:25.381Z",
    "type": "execution"
   },
   {
    "id": "a939598316054d528c40aab130b5481c",
    "time": "2021-01-25T17:20:25.457Z",
    "type": "completion"
   },
   {
    "code": "# calculate_score(\"Artemis Fowl\",all_films)\nplot_film(\"Artemis Fowl\")",
    "id": "8c3d3fca7294407980c1e709032f69b3",
    "idx": 23,
    "time": "2021-01-25T17:20:25.697Z",
    "type": "execution"
   },
   {
    "id": "8c3d3fca7294407980c1e709032f69b3",
    "time": "2021-01-25T17:20:26.133Z",
    "type": "completion"
   },
   {
    "code": "# calculate_score(\"Wonder Woman 1984\",all_films).plot()\nplot_film(\"Wonder Woman 1984\")",
    "id": "c5a30e54c362450e8ae6e35bce30ecab",
    "idx": 24,
    "time": "2021-01-25T17:20:26.968Z",
    "type": "execution"
   },
   {
    "id": "c5a30e54c362450e8ae6e35bce30ecab",
    "time": "2021-01-25T17:20:27.480Z",
    "type": "completion"
   },
   {
    "code": "def plot_film(film):\n    df = all_films[all_films==film]\n    series = calculate_score(film, all_films)\n    plt.plot(series)\n    plt.axhline(y=0.75, color='yellow', linestyle='dashed',linewidth=0.5)\n    plt.axhline(y=0.6, color='red', linestyle='dashed',linewidth=0.5)\n    plt.axhspan(0.75, 1, alpha=0.5, color='#2ca02c')\n#     plt.axhspan(0.6,75, alpha=0.5, color='yellow')\n    plt.axhspan(0, 0.6, alpha=0.5, color='red')\n    plt.ylim(series.min(), series.max())\n    plt.title(film + \" Rotten Tomatoes Score over Time\")",
    "id": "a939598316054d528c40aab130b5481c",
    "idx": 22,
    "time": "2021-01-25T17:20:44.932Z",
    "type": "execution"
   },
   {
    "id": "a939598316054d528c40aab130b5481c",
    "time": "2021-01-25T17:20:45.003Z",
    "type": "completion"
   },
   {
    "code": "# calculate_score(\"Artemis Fowl\",all_films)\nplot_film(\"Artemis Fowl\")",
    "id": "8c3d3fca7294407980c1e709032f69b3",
    "idx": 23,
    "time": "2021-01-25T17:20:45.296Z",
    "type": "execution"
   },
   {
    "id": "8c3d3fca7294407980c1e709032f69b3",
    "time": "2021-01-25T17:20:45.725Z",
    "type": "completion"
   },
   {
    "code": "# calculate_score(\"Wonder Woman 1984\",all_films).plot()\nplot_film(\"Wonder Woman 1984\")",
    "id": "c5a30e54c362450e8ae6e35bce30ecab",
    "idx": 24,
    "time": "2021-01-25T17:20:45.729Z",
    "type": "execution"
   },
   {
    "id": "c5a30e54c362450e8ae6e35bce30ecab",
    "time": "2021-01-25T17:20:46.153Z",
    "type": "completion"
   },
   {
    "code": "def plot_film(film):\n    df = all_films[all_films==film]\n    series = calculate_score(film, all_films)\n    plt.plot(series)\n    plt.axhline(y=0.75, color='yellow', linestyle='dashed',linewidth=0.5)\n    plt.axhline(y=0.6, color='red', linestyle='dashed',linewidth=0.5)\n    plt.axhspan(0.75, 1, alpha=0.5, color='#2ca02c')\n    plt.axhspan(0.6,.75, alpha=0.5, color='yellow')\n    plt.axhspan(0, 0.6, alpha=0.5, color='red')\n    plt.ylim(series.min(), series.max())\n    plt.title(film + \" Rotten Tomatoes Score over Time\")",
    "id": "a939598316054d528c40aab130b5481c",
    "idx": 22,
    "time": "2021-01-25T17:21:01.059Z",
    "type": "execution"
   },
   {
    "id": "a939598316054d528c40aab130b5481c",
    "time": "2021-01-25T17:21:01.132Z",
    "type": "completion"
   },
   {
    "code": "# calculate_score(\"Artemis Fowl\",all_films)\nplot_film(\"Artemis Fowl\")",
    "id": "8c3d3fca7294407980c1e709032f69b3",
    "idx": 23,
    "time": "2021-01-25T17:21:01.353Z",
    "type": "execution"
   },
   {
    "code": "# calculate_score(\"Wonder Woman 1984\",all_films).plot()\nplot_film(\"Wonder Woman 1984\")",
    "id": "c5a30e54c362450e8ae6e35bce30ecab",
    "idx": 24,
    "time": "2021-01-25T17:21:01.882Z",
    "type": "execution"
   },
   {
    "id": "8c3d3fca7294407980c1e709032f69b3",
    "time": "2021-01-25T17:21:01.975Z",
    "type": "completion"
   },
   {
    "id": "c5a30e54c362450e8ae6e35bce30ecab",
    "time": "2021-01-25T17:21:02.344Z",
    "type": "completion"
   },
   {
    "code": "def plot_film(film):\n    df = all_films[all_films==film]\n    series = calculate_score(film, all_films)\n    plt.plot(series)\n    plt.axhline(y=0.75, color='yellow', linestyle='dashed',linewidth=0.5)\n    plt.axhline(y=0.6, color='red', linestyle='dashed',linewidth=0.5)\n    plt.axhspan(0.75, 1, alpha=0.5, color='green')\n    plt.axhspan(0.6,.75, alpha=0.5, color='yellow')\n    plt.axhspan(0, 0.6, alpha=0.5, color='red')\n    plt.ylim(series.min(), series.max())\n    plt.title(film + \" Rotten Tomatoes Score over Time\")",
    "id": "a939598316054d528c40aab130b5481c",
    "idx": 22,
    "time": "2021-01-25T17:21:10.520Z",
    "type": "execution"
   },
   {
    "id": "a939598316054d528c40aab130b5481c",
    "time": "2021-01-25T17:21:10.590Z",
    "type": "completion"
   },
   {
    "code": "# calculate_score(\"Artemis Fowl\",all_films)\nplot_film(\"Artemis Fowl\")",
    "id": "8c3d3fca7294407980c1e709032f69b3",
    "idx": 23,
    "time": "2021-01-25T17:21:10.743Z",
    "type": "execution"
   },
   {
    "code": "# calculate_score(\"Wonder Woman 1984\",all_films).plot()\nplot_film(\"Wonder Woman 1984\")",
    "id": "c5a30e54c362450e8ae6e35bce30ecab",
    "idx": 24,
    "time": "2021-01-25T17:21:10.964Z",
    "type": "execution"
   },
   {
    "id": "8c3d3fca7294407980c1e709032f69b3",
    "time": "2021-01-25T17:21:11.072Z",
    "type": "completion"
   },
   {
    "id": "c5a30e54c362450e8ae6e35bce30ecab",
    "time": "2021-01-25T17:21:11.394Z",
    "type": "completion"
   },
   {
    "code": "def plot_film(film):\n    df = all_films[all_films==film]\n    series = calculate_score(film, all_films)\n    plt.plot(series)\n    plt.axhline(y=0.75, color='yellow', linestyle='dashed',linewidth=0.5)\n    plt.axhline(y=0.6, color='red', linestyle='dashed',linewidth=0.5)\n    plt.axhspan(0.75, 1, alpha=0.5, color='lightgreen')\n    plt.axhspan(0.6,.75, alpha=0.5, color='yellow')\n    plt.axhspan(0, 0.6, alpha=0.5, color='red')\n    plt.ylim(series.min(), series.max())\n    plt.title(film + \" Rotten Tomatoes Score over Time\")",
    "id": "a939598316054d528c40aab130b5481c",
    "idx": 22,
    "time": "2021-01-25T17:21:14.950Z",
    "type": "execution"
   },
   {
    "id": "a939598316054d528c40aab130b5481c",
    "time": "2021-01-25T17:21:15.081Z",
    "type": "completion"
   },
   {
    "code": "# calculate_score(\"Artemis Fowl\",all_films)\nplot_film(\"Artemis Fowl\")",
    "id": "8c3d3fca7294407980c1e709032f69b3",
    "idx": 23,
    "time": "2021-01-25T17:21:15.121Z",
    "type": "execution"
   },
   {
    "code": "# calculate_score(\"Wonder Woman 1984\",all_films).plot()\nplot_film(\"Wonder Woman 1984\")",
    "id": "c5a30e54c362450e8ae6e35bce30ecab",
    "idx": 24,
    "time": "2021-01-25T17:21:15.256Z",
    "type": "execution"
   },
   {
    "id": "8c3d3fca7294407980c1e709032f69b3",
    "time": "2021-01-25T17:21:15.539Z",
    "type": "completion"
   },
   {
    "id": "c5a30e54c362450e8ae6e35bce30ecab",
    "time": "2021-01-25T17:21:15.747Z",
    "type": "completion"
   },
   {
    "code": "def plot_film(film):\n    df = all_films[all_films==film]\n    series = calculate_score(film, all_films)\n    plt.plot(series)\n    plt.axhline(y=0.75, color='yellow', linestyle='dashed',linewidth=0.5)\n    plt.axhline(y=0.6, color='red', linestyle='dashed',linewidth=0.5)\n    plt.axhspan(0.75, 1, alpha=0.5, color='lightgreen')\n    plt.axhspan(0.6,.75, alpha=0.5, color='yellow')\n    plt.axhspan(0, 0.6, alpha=0.5, color='salmon')\n    plt.ylim(series.min(), series.max())\n    plt.title(film + \" Rotten Tomatoes Score over Time\")",
    "id": "a939598316054d528c40aab130b5481c",
    "idx": 22,
    "time": "2021-01-25T17:21:43.750Z",
    "type": "execution"
   },
   {
    "id": "a939598316054d528c40aab130b5481c",
    "time": "2021-01-25T17:21:43.825Z",
    "type": "completion"
   },
   {
    "code": "# calculate_score(\"Artemis Fowl\",all_films)\nplot_film(\"Artemis Fowl\")",
    "id": "8c3d3fca7294407980c1e709032f69b3",
    "idx": 23,
    "time": "2021-01-25T17:21:44.127Z",
    "type": "execution"
   },
   {
    "code": "# calculate_score(\"Wonder Woman 1984\",all_films).plot()\nplot_film(\"Wonder Woman 1984\")",
    "id": "c5a30e54c362450e8ae6e35bce30ecab",
    "idx": 24,
    "time": "2021-01-25T17:21:44.575Z",
    "type": "execution"
   },
   {
    "id": "8c3d3fca7294407980c1e709032f69b3",
    "time": "2021-01-25T17:21:44.692Z",
    "type": "completion"
   },
   {
    "id": "c5a30e54c362450e8ae6e35bce30ecab",
    "time": "2021-01-25T17:21:45.043Z",
    "type": "completion"
   },
   {
    "code": "def plot_film(film):\n    df = all_films[all_films==film]\n    series = calculate_score(film, all_films)\n    plt.plot(series)\n    plt.axhline(y=0.75, color='yellow', linestyle='dashed',linewidth=0.5)\n    plt.axhline(y=0.6, color='red', linestyle='dashed',linewidth=0.5)\n    plt.axhspan(0.75, 1, alpha=0.5, color='lightgreen')\n    plt.axhspan(0.6,.75, alpha=0.5, color='lightyellow')\n    plt.axhspan(0, 0.6, alpha=0.5, color='salmon')\n    plt.ylim(series.min(), series.max())\n    plt.title(film + \" Rotten Tomatoes Score over Time\")",
    "id": "a939598316054d528c40aab130b5481c",
    "idx": 22,
    "time": "2021-01-25T17:22:14.400Z",
    "type": "execution"
   },
   {
    "id": "a939598316054d528c40aab130b5481c",
    "time": "2021-01-25T17:22:14.473Z",
    "type": "completion"
   },
   {
    "code": "# calculate_score(\"Artemis Fowl\",all_films)\nplot_film(\"Artemis Fowl\")",
    "id": "8c3d3fca7294407980c1e709032f69b3",
    "idx": 23,
    "time": "2021-01-25T17:22:14.601Z",
    "type": "execution"
   },
   {
    "code": "# calculate_score(\"Wonder Woman 1984\",all_films).plot()\nplot_film(\"Wonder Woman 1984\")",
    "id": "c5a30e54c362450e8ae6e35bce30ecab",
    "idx": 24,
    "time": "2021-01-25T17:22:14.781Z",
    "type": "execution"
   },
   {
    "id": "8c3d3fca7294407980c1e709032f69b3",
    "time": "2021-01-25T17:22:15.055Z",
    "type": "completion"
   },
   {
    "id": "c5a30e54c362450e8ae6e35bce30ecab",
    "time": "2021-01-25T17:22:15.323Z",
    "type": "completion"
   },
   {
    "code": "def plot_film(film):\n    df = all_films[all_films==film]\n    series = calculate_score(film, all_films)\n    plt.plot(series)\n    plt.axhline(y=0.75, color='yellow', linestyle='dashed',linewidth=0.5)\n    plt.axhline(y=0.6, color='red', linestyle='dashed',linewidth=0.5)\n    plt.axhspan(0.75, 1, alpha=0.5, color='lightgreen')\n    plt.axhspan(0.6,.75, alpha=0.5, color='lemonchiffon')\n    plt.axhspan(0, 0.6, alpha=0.5, color='salmon')\n    plt.ylim(series.min(), series.max())\n    plt.title(film + \" Rotten Tomatoes Score over Time\")",
    "id": "a939598316054d528c40aab130b5481c",
    "idx": 22,
    "time": "2021-01-25T17:22:33.110Z",
    "type": "execution"
   },
   {
    "id": "a939598316054d528c40aab130b5481c",
    "time": "2021-01-25T17:22:33.185Z",
    "type": "completion"
   },
   {
    "code": "# calculate_score(\"Artemis Fowl\",all_films)\nplot_film(\"Artemis Fowl\")",
    "id": "8c3d3fca7294407980c1e709032f69b3",
    "idx": 23,
    "time": "2021-01-25T17:22:33.335Z",
    "type": "execution"
   },
   {
    "id": "8c3d3fca7294407980c1e709032f69b3",
    "time": "2021-01-25T17:22:33.810Z",
    "type": "completion"
   },
   {
    "code": "def plot_film(film):\n    df = all_films[all_films==film]\n    series = calculate_score(film, all_films)\n    plt.plot(series)\n    plt.axhline(y=0.75, color='yellow', linestyle='dashed',linewidth=0.5)\n    plt.axhline(y=0.6, color='red', linestyle='dashed',linewidth=0.5)\n    plt.axhspan(0.75, 1, alpha=0.5, color='lightgreen')\n    plt.axhspan(0.6,.75, alpha=0.5, color='#F6F7A8')\n    plt.axhspan(0, 0.6, alpha=0.5, color='salmon')\n    plt.ylim(series.min(), series.max())\n    plt.title(film + \" Rotten Tomatoes Score over Time\")",
    "id": "a939598316054d528c40aab130b5481c",
    "idx": 22,
    "time": "2021-01-25T17:23:13.790Z",
    "type": "execution"
   },
   {
    "id": "a939598316054d528c40aab130b5481c",
    "time": "2021-01-25T17:23:13.862Z",
    "type": "completion"
   },
   {
    "code": "# calculate_score(\"Artemis Fowl\",all_films)\nplot_film(\"Artemis Fowl\")",
    "id": "8c3d3fca7294407980c1e709032f69b3",
    "idx": 23,
    "time": "2021-01-25T17:23:14.142Z",
    "type": "execution"
   },
   {
    "code": "# calculate_score(\"Wonder Woman 1984\",all_films).plot()\nplot_film(\"Wonder Woman 1984\")",
    "id": "c5a30e54c362450e8ae6e35bce30ecab",
    "idx": 24,
    "time": "2021-01-25T17:23:14.481Z",
    "type": "execution"
   },
   {
    "id": "8c3d3fca7294407980c1e709032f69b3",
    "time": "2021-01-25T17:23:14.721Z",
    "type": "completion"
   },
   {
    "id": "c5a30e54c362450e8ae6e35bce30ecab",
    "time": "2021-01-25T17:23:14.814Z",
    "type": "completion"
   },
   {
    "code": "# calculate_score(\"Mulan\",all_films).plot()\nplot_film(\"Mulan\")",
    "id": "f621f1fe85de4ece889fcb42a4c9be45",
    "idx": 25,
    "time": "2021-01-25T17:23:36.287Z",
    "type": "execution"
   },
   {
    "id": "f621f1fe85de4ece889fcb42a4c9be45",
    "time": "2021-01-25T17:23:36.908Z",
    "type": "completion"
   },
   {
    "code": "def plot_film(film):\n    df = all_films[all_films==film]\n    series = calculate_score(film, all_films)\n    plt.plot(series)\n    plt.axhline(y=0.75, color='yellow', linestyle='dashed',linewidth=0.5)\n    plt.axhline(y=0.6, color='red', linestyle='dashed',linewidth=0.5)\n    plt.axhspan(0.75, 1, alpha=0.5, color='lightgreen')\n    plt.axhspan(0.6,.75, alpha=0.5, color='#F6F7A8')\n    plt.axhspan(0, 0.6, alpha=0.5, color='salmon')\n    plt.ylim(series.min(), series.max())\n    plt.set_xticklabels(rotation = 45)\n    plt.title(film + \" Rotten Tomatoes Score over Time\")",
    "id": "a939598316054d528c40aab130b5481c",
    "idx": 22,
    "time": "2021-01-25T17:25:05.749Z",
    "type": "execution"
   },
   {
    "id": "a939598316054d528c40aab130b5481c",
    "time": "2021-01-25T17:25:05.819Z",
    "type": "completion"
   },
   {
    "code": "# calculate_score(\"Artemis Fowl\",all_films)\nplot_film(\"Artemis Fowl\")",
    "id": "8c3d3fca7294407980c1e709032f69b3",
    "idx": 23,
    "time": "2021-01-25T17:25:07.033Z",
    "type": "execution"
   },
   {
    "id": "8c3d3fca7294407980c1e709032f69b3",
    "time": "2021-01-25T17:25:07.474Z",
    "type": "completion"
   },
   {
    "code": "def plot_film(film):\n    df = all_films[all_films==film]\n    series = calculate_score(film, all_films)\n    plt.plot(series)\n    plt.axhline(y=0.75, color='yellow', linestyle='dashed',linewidth=0.5)\n    plt.axhline(y=0.6, color='red', linestyle='dashed',linewidth=0.5)\n    plt.axhspan(0.75, 1, alpha=0.5, color='lightgreen')\n    plt.axhspan(0.6,.75, alpha=0.5, color='#F6F7A8')\n    plt.axhspan(0, 0.6, alpha=0.5, color='salmon')\n    plt.ylim(series.min(), series.max())\n    plt.title(film + \" Rotten Tomatoes Score over Time\")",
    "id": "a939598316054d528c40aab130b5481c",
    "idx": 22,
    "time": "2021-01-25T17:25:13.218Z",
    "type": "execution"
   },
   {
    "id": "a939598316054d528c40aab130b5481c",
    "time": "2021-01-25T17:25:13.286Z",
    "type": "completion"
   },
   {
    "code": "# calculate_score(\"Artemis Fowl\",all_films)\nplot_film(\"Artemis Fowl\")",
    "id": "8c3d3fca7294407980c1e709032f69b3",
    "idx": 23,
    "time": "2021-01-25T17:25:13.368Z",
    "type": "execution"
   },
   {
    "code": "# calculate_score(\"Wonder Woman 1984\",all_films).plot()\nplot_film(\"Wonder Woman 1984\")",
    "id": "c5a30e54c362450e8ae6e35bce30ecab",
    "idx": 24,
    "time": "2021-01-25T17:25:13.512Z",
    "type": "execution"
   },
   {
    "id": "8c3d3fca7294407980c1e709032f69b3",
    "time": "2021-01-25T17:25:13.767Z",
    "type": "completion"
   },
   {
    "id": "c5a30e54c362450e8ae6e35bce30ecab",
    "time": "2021-01-25T17:25:13.991Z",
    "type": "completion"
   },
   {
    "code": "# calculate_score(\"Mulan\",all_films).plot()\nplot_film(\"Mulan\")",
    "id": "f621f1fe85de4ece889fcb42a4c9be45",
    "idx": 25,
    "time": "2021-01-25T17:25:19.724Z",
    "type": "execution"
   },
   {
    "id": "f621f1fe85de4ece889fcb42a4c9be45",
    "time": "2021-01-25T17:25:20.239Z",
    "type": "completion"
   },
   {
    "code": "# calculate_score(\"Tenet\",all_films).plot()\nplot_film(\"Tenet\")",
    "id": "9aa215e710244e988e051ae025606f59",
    "idx": 26,
    "time": "2021-01-25T17:25:20.384Z",
    "type": "execution"
   },
   {
    "id": "9aa215e710244e988e051ae025606f59",
    "time": "2021-01-25T17:25:20.823Z",
    "type": "completion"
   },
   {
    "code": "calculate_score(\"Lovebirds\",all_films).plot()",
    "id": "f164a2c26f3941c68aea5f9bfc3468ed",
    "idx": 27,
    "time": "2021-01-25T17:25:25.385Z",
    "type": "execution"
   },
   {
    "id": "f164a2c26f3941c68aea5f9bfc3468ed",
    "time": "2021-01-25T17:25:25.847Z",
    "type": "completion"
   },
   {
    "code": "plot_film(\"Lovebirds\")",
    "id": "f164a2c26f3941c68aea5f9bfc3468ed",
    "idx": 27,
    "time": "2021-01-25T17:25:33.281Z",
    "type": "execution"
   },
   {
    "id": "f164a2c26f3941c68aea5f9bfc3468ed",
    "time": "2021-01-25T17:25:33.798Z",
    "type": "completion"
   },
   {
    "code": "def plot_film(film):\n    df = all_films[all_films==film]\n    series = calculate_score(film, all_films)\n    plt.plot(series)\n    plt.axhline(y=0.75, color='yellow', linestyle='dashed',linewidth=0.5)\n    plt.axhline(y=0.6, color='red', linestyle='dashed',linewidth=0.5)\n    plt.axhspan(0.75, 1, alpha=0.5, color='lightgreen')\n    plt.axhspan(0.6,.75, alpha=0.5, color='#F6F7A8')\n    plt.axhspan(0, 0.6, alpha=0.5, color='salmon')\n    plt.ylim(series.min(), series.max())\n    plt.xticks(rotation=45, ha=\"right\")\n    plt.title(film + \" Rotten Tomatoes Score over Time\")",
    "id": "a939598316054d528c40aab130b5481c",
    "idx": 22,
    "time": "2021-01-25T17:26:38.887Z",
    "type": "execution"
   },
   {
    "id": "a939598316054d528c40aab130b5481c",
    "time": "2021-01-25T17:26:38.956Z",
    "type": "completion"
   },
   {
    "code": "# calculate_score(\"Artemis Fowl\",all_films)\nplot_film(\"Artemis Fowl\")",
    "id": "8c3d3fca7294407980c1e709032f69b3",
    "idx": 23,
    "time": "2021-01-25T17:26:39.404Z",
    "type": "execution"
   },
   {
    "id": "8c3d3fca7294407980c1e709032f69b3",
    "time": "2021-01-25T17:26:39.859Z",
    "type": "completion"
   },
   {
    "code": "# calculate_score(\"Wonder Woman 1984\",all_films).plot()\nplot_film(\"Wonder Woman 1984\")",
    "id": "c5a30e54c362450e8ae6e35bce30ecab",
    "idx": 24,
    "time": "2021-01-25T17:26:40.395Z",
    "type": "execution"
   },
   {
    "id": "c5a30e54c362450e8ae6e35bce30ecab",
    "time": "2021-01-25T17:26:41.039Z",
    "type": "completion"
   },
   {
    "code": "# calculate_score(\"Mulan\",all_films).plot()\nplot_film(\"Mulan\")",
    "id": "f621f1fe85de4ece889fcb42a4c9be45",
    "idx": 25,
    "time": "2021-01-25T17:26:45.313Z",
    "type": "execution"
   },
   {
    "code": "# calculate_score(\"Tenet\",all_films).plot()\nplot_film(\"Tenet\")",
    "id": "9aa215e710244e988e051ae025606f59",
    "idx": 26,
    "time": "2021-01-25T17:26:45.522Z",
    "type": "execution"
   },
   {
    "code": "plot_film(\"Lovebirds\")",
    "id": "f164a2c26f3941c68aea5f9bfc3468ed",
    "idx": 27,
    "time": "2021-01-25T17:26:45.693Z",
    "type": "execution"
   },
   {
    "id": "f621f1fe85de4ece889fcb42a4c9be45",
    "time": "2021-01-25T17:26:45.915Z",
    "type": "completion"
   },
   {
    "id": "9aa215e710244e988e051ae025606f59",
    "time": "2021-01-25T17:26:45.919Z",
    "type": "completion"
   },
   {
    "id": "f164a2c26f3941c68aea5f9bfc3468ed",
    "time": "2021-01-25T17:26:46.043Z",
    "type": "completion"
   },
   {
    "code": "import requests\nimport time\n\n# requirements\nfrom bs4 import BeautifulSoup\nfrom requests import TooManyRedirects\nimport re\n\ndef _make_soup(url):\n    try:\n        r = requests.get(url)\n        soup = BeautifulSoup(r.content, 'html.parser')\n    except TooManyRedirects:\n        soup = ''\n    return soup\n\n#regex patterns\npage_pat = re.compile(r'Page 1 of \\d+')\nreview_pat = re.compile(r'<div class=\\\"the_review\\\" data-qa=\\\"review-text\\\">[;a-zA-Z\\s,-.\\'\\/\\?\\[\\]\\\":\\']*</div>')\nrating_pat = re.compile(r'Original Score:\\s([A-Z](\\+|-)?|\\d(.\\d)?(\\/\\d)?)')\nfresh_pat = re.compile(r'small\\s(fresh|rotten)\\\"')\ncritic_pat = re.compile(r'\\/\\\"\\>([A-Z][a-zA-Z]+\\s[A-Z][a-zA-Z\\-]+)|([A-Z][a-zA-Z.]+\\s[A-Z].?\\s[A-Z][a-zA-Z]+)|([A-Z][a-zA-Z]+\\s[A-Z]+\\'[A-Z][a-zA-Z]+)')\npublisher_pat = re.compile(r'\\\"subtle\\\">[a-zA-Z\\s,.\\(\\)\\'\\-&;!\\/\\d+]+</em>')\ndate_pat = re.compile(r'[a-zA-Z]+\\s\\d+,\\s\\d+')",
    "id": "e766526218b9448bbc84fddcf8350cbe",
    "idx": 0,
    "time": "2021-01-25T23:51:33.216Z",
    "type": "execution"
   },
   {
    "code": "def _get_critic_reviews_from_page(soup):\n    reviews = list()\n    rating = list()\n    fresh = list()\n    critic = list()\n    top_critic = list()\n    publisher = list()\n    date = list()\n    \n    soup = str(soup)\n    review_soup = soup.split('=\"review_table')[1].split('row review_table_row')\n    review_soup.pop(0)\n\n    for review in review_soup:\n        match = re.findall(review_pat, str(review))\n        if len(match) > 0:\n            m = match[0]            \n            for iden in ['<div class=\"the_review\" data-qa=\"review-text\"> ','</div>']:\n                m = m.replace(iden,'')\n            reviews.append(m.strip('\"'))            \n            # extract rating\n            match = re.findall(rating_pat, str(review))\n            if len(match) > 0:\n                m = match[0][0]\n                if '/1' in m:\n                    sp_m = m.split('/')\n                    if sp_m[-1] == '1':\n                        sp_m[-1] = '10'\n                    m = '/'.join(sp_m)\n                rating.append(m)\n            else:\n                rating.append(None)            \n            # extract fresh indicator\n            match = re.findall(fresh_pat, str(review))\n            if len(match) > 0:\n                fresh.append(match[0])\n            else:\n                fresh.append(None)            \n            # extract critic\n            match = re.findall(critic_pat, str(review))\n            if len(match) > 0:\n                critic.append(''.join(match[0]))\n            else:\n                critic.append(None)            \n            # check if top critic\n            if '> Top Critic<' in str(review):\n                top_critic.append(1)\n            else:\n                top_critic.append(0)            \n            # extract publisher\n            match = re.findall(publisher_pat, str(review))\n            if len(match) > 0:\n                m = match[0]\n                m = m.replace('\"subtle\">', '')\n                m = m.replace('</em>','')\n                publisher.append(m)\n            else:\n                publisher.append(None)            \n            # extract date\n            match = re.findall(date_pat, str(review))\n            if len(match) > 0:\n                date.append(match[0].strip('\"'))\n            else:\n                date.append(None)\n            \n    return [reviews, rating, fresh, critic, top_critic, publisher, date]\n\ndef _get_num_pages(soup):\n    match = re.findall(page_pat,str(list(soup)))\n    if len(match) > 0:\n        match = match[0]\n        match = match.split(' of ')[-1]\n        return match\n    else:\n        return None",
    "id": "3177ae4def194e6a81c8c22695398971",
    "idx": 1,
    "time": "2021-01-25T23:51:33.227Z",
    "type": "execution"
   },
   {
    "code": "def get_critic_reviews(page):\n    info = [[],[],[],[],[],[],[]]\n    soup = _make_soup(page + \"reviews\")\n#     print(soup)\n    pages = _get_num_pages(soup)\n#     print(pages)\n    if pages is not None:\n        for page_num in range(1,int(pages)+1):\n            soup = _make_soup(page + \"reviews?page=\" + str(page_num) + \"&sort=\")\n            c_info = _get_critic_reviews_from_page(soup)\n            \n            # accumulate review info\n            for i in range(len(c_info)):\n                info[i] = info[i] + c_info[i]\n        \n        c_info = dict()\n        keys = ['reviews', 'rating', 'fresh', 'critic', 'top_critic', 'publisher', 'date']\n        for k in range(len(keys)):\n            c_info[keys[k]] = info[k]        \n    else:\n        c_info = None        \n    return c_info",
    "id": "04edfe558ec2423998eb0859ae7b1b4d",
    "idx": 2,
    "time": "2021-01-25T23:51:33.230Z",
    "type": "execution"
   },
   {
    "code": "movie_urls = {'Wonder Woman 1984': 'https://www.rottentomatoes.com/m/wonder_woman_1984/', \n              'Soul':'https://www.rottentomatoes.com/m/soul_2020/', \n              'Mulan': 'https://www.rottentomatoes.com/m/mulan_2020/',\n              'Birds of Prey': 'https://www.rottentomatoes.com/m/birds_of_prey_2020/',\n              'Sonic': 'https://www.rottentomatoes.com/m/sonic_the_hedgehog_2020/'\n             }\nmovie_urls.keys()",
    "id": "8ea7dd65ad8e41449a53059eb028b56c",
    "idx": 3,
    "time": "2021-01-25T23:51:33.234Z",
    "type": "execution"
   },
   {
    "code": "import pandas as pd\n\ndfs = []\nfor key in movie_urls.keys():\n    temp = get_critic_reviews(movie_urls[key])\n    df = pd.DataFrame.from_dict(temp)\n    df['Film'] = key\n    dfs.append(df)",
    "id": "04b78cb5b075485194f632e013f6e2e7",
    "idx": 4,
    "time": "2021-01-25T23:51:33.238Z",
    "type": "execution"
   },
   {
    "code": "all_films = pd.concat(dfs)\nall_films",
    "id": "9dfb573d4c7547c68f4a1fcaa4a62a64",
    "idx": 5,
    "time": "2021-01-25T23:51:33.242Z",
    "type": "execution"
   },
   {
    "code": "all_films['score'] = all_films['fresh'].apply(lambda x: 1 if x == 'fresh' else 0)\nall_films",
    "id": "b2655460ddf347b7ad6317d57d6c9c74",
    "idx": 6,
    "time": "2021-01-25T23:51:33.246Z",
    "type": "execution"
   },
   {
    "code": "all_films['date'] = pd.to_datetime(all_films['date'], format=\"%B %d, %Y\")\nall_films = all_films.sort_values('date')",
    "id": "f90cbc5ba5dc4d978c6ef1bef3c771bf",
    "idx": 7,
    "time": "2021-01-25T23:51:33.248Z",
    "type": "execution"
   },
   {
    "code": "import numpy as np\n\n\ndef calculate_score(film, frame):\n    df = frame[frame['Film'] == film]\n    grouped_1 = df[['date', 'score']].groupby('date').agg([sum, 'count'])\n    grouped_1.columns = grouped_1.columns.droplevel(0)\n    return grouped_1.cumsum()['sum']/grouped_1.cumsum()['count']\n\ncalculate_score(\"Wonder Woman 1984\")",
    "id": "1c4f93d3bcca40e1850500ce0ab27ead",
    "idx": 8,
    "time": "2021-01-25T23:51:33.253Z",
    "type": "execution"
   },
   {
    "code": "# calculate_score(\"Soul\").plot()\nimport matplotlib.pyplot as plt\n\nfor key in movie_urls.keys():\n#     pd.to_numeric(df.Subs).plot.line()\n    df = all_films[all_films==key]\n    plt.plot(calculate_score(key), label=key)\n#     plt.plot(np.arange(len(df.index)), pd.to_numeric(df.Total).pct_change(), label = df.Name.values[0], color = colors[i])\n#     plt.axvline(x=30, color='red', linestyle='dashed',linewidth=0.5)\n    plt.ylabel('Percent Change in Subscribers by Day')\n    plt.xlabel(\"Day (0 is 1 month before Content Cop's release)\")\n    plt.legend()\n# plt.annotate('Content Cop released', xy=(30, 0.015), ha='center', size=10)\n# plt.title('The Impact of Content Cop')\n# plt.savefig('pct_cc.svg')",
    "id": "5282402c126d480a8e20d3a8650b5b33",
    "idx": 9,
    "time": "2021-01-25T23:51:33.259Z",
    "type": "execution"
   },
   {
    "code": "# all_films.to_csv(\"all_films.csv\", index=False)",
    "id": "436946f5dbc543a9a4b64879435dbca8",
    "idx": 10,
    "time": "2021-01-25T23:51:33.261Z",
    "type": "execution"
   },
   {
    "code": "#add more movies\nimport pandas as pd\n\nmovie_urls['Tenet'] = 'https://www.rottentomatoes.com/m/tenet/'\nmovie_urls['Scoob'] = 'https://www.rottentomatoes.com/m/scoob/'\nmovie_urls['The Marksman'] = 'https://www.rottentomatoes.com/m/the_marksman_2021/'\nmovie_urls['Artemis Fowl'] = 'https://www.rottentomatoes.com/m/artemis_fowl/'\nmovie_urls['Lovebirds'] = 'https://www.rottentomatoes.com/m/the_lovebirds_2020/'\n\nnewkeys = ['Tenet', 'Scoob', 'The Marksman', 'Artemis Fowl', 'Lovebirds']\ndfs = []\n\nfor key in newkeys:\n    print(movie_urls[key])\n    temp = get_critic_reviews(movie_urls[key])\n    df = pd.DataFrame.from_dict(temp)\n    df['Film'] = key\n    dfs.append(df)",
    "id": "5428c7586a36435f8c1923bafc3ca968",
    "idx": 11,
    "time": "2021-01-25T23:51:33.264Z",
    "type": "execution"
   },
   {
    "code": "new_films = pd.concat(dfs)\nnew_films",
    "id": "8556a717af25468fb8004d0eae3d751d",
    "idx": 12,
    "time": "2021-01-25T23:51:33.268Z",
    "type": "execution"
   },
   {
    "code": "new_films['score'] = new_films['fresh'].apply(lambda x: 1 if x == 'fresh' else 0)\nnew_films",
    "id": "93fa76876e8d4c0f8412aebc9cb47935",
    "idx": 13,
    "time": "2021-01-25T23:51:33.271Z",
    "type": "execution"
   },
   {
    "code": "new_films['date'] = pd.to_datetime(new_films['date'], format=\"%B %d, %Y\")\nnew_films = new_films.sort_values('date')",
    "id": "05b49e4d479440d5b089d5b17d360896",
    "idx": 14,
    "time": "2021-01-25T23:51:33.273Z",
    "type": "execution"
   },
   {
    "code": "new_films",
    "id": "6f87adab3b0d410e81f6805b14273410",
    "idx": 15,
    "time": "2021-01-25T23:51:33.276Z",
    "type": "execution"
   },
   {
    "code": "import matplotlib.pyplot as plt\n\nfor key in newkeys:\n#     pd.to_numeric(df.Subs).plot.line()\n    df = new_films[new_films==key]\n    plt.plot(calculate_score(key, new_films), label=key)\n#     plt.plot(np.arange(len(df.index)), pd.to_numeric(df.Total).pct_change(), label = df.Name.values[0], color = colors[i])\n#     plt.axvline(x=30, color='red', linestyle='dashed',linewidth=0.5)\n    plt.ylabel('Percent Change in Subscribers by Day')\n    plt.xlabel(\"Day (0 is 1 month before Content Cop's release)\")\n    plt.legend()",
    "id": "b952a1aa8312432d895ce1aa15bacd22",
    "idx": 16,
    "time": "2021-01-25T23:51:33.278Z",
    "type": "execution"
   },
   {
    "code": "all_films = pd.read_csv(\"all_films.csv\")\nall_films",
    "id": "c1115d26f4774c7788fb0c1858f90243",
    "idx": 17,
    "time": "2021-01-25T23:51:33.283Z",
    "type": "execution"
   },
   {
    "code": "all_films = pd.concat([all_films, new_films])",
    "id": "da199b52f5074ac58c27fb5da33cabfb",
    "idx": 18,
    "time": "2021-01-25T23:51:33.286Z",
    "type": "execution"
   },
   {
    "code": "all_films['date'] = pd.to_datetime(all_films['date'])\nall_films = all_films.sort_values('date')",
    "id": "ab91beeacbf34355899cbd20f276b6ff",
    "idx": 19,
    "time": "2021-01-25T23:51:33.291Z",
    "type": "execution"
   },
   {
    "code": "for key in movie_urls.keys():\n#     pd.to_numeric(df.Subs).plot.line()\n    df = all_films[all_films==key]\n    plt.plot(calculate_score(key, all_films), label=key)\n#     plt.plot(np.arange(len(df.index)), pd.to_numeric(df.Total).pct_change(), label = df.Name.values[0], color = colors[i])\n#     plt.axvline(x=30, color='red', linestyle='dashed',linewidth=0.5)\n    plt.ylabel('Percent Change in Subscribers by Day')\n    plt.xlabel(\"Day (0 is 1 month before Content Cop's release)\")\n    plt.legend()\n# plt.annotate('Content Cop released', xy=(30, 0.015), ha='center', size=10)\n# plt.title('The Impact of Content Cop')\n# plt.savefig('pct_cc.svg')",
    "id": "5b7a2cc3ce754041a2f51ac30d184f11",
    "idx": 20,
    "time": "2021-01-25T23:51:33.296Z",
    "type": "execution"
   },
   {
    "code": "%config InlineBackend.figure_format = 'svg'",
    "id": "52f037e9877f488b8382eab7fadca779",
    "idx": 21,
    "time": "2021-01-25T23:51:33.298Z",
    "type": "execution"
   },
   {
    "code": "def plot_film(film):\n    df = all_films[all_films==film]\n    series = calculate_score(film, all_films)\n    plt.plot(series)\n    plt.axhline(y=0.75, color='yellow', linestyle='dashed',linewidth=0.5)\n    plt.axhline(y=0.6, color='red', linestyle='dashed',linewidth=0.5)\n    plt.axhspan(0.75, 1, alpha=0.5, color='lightgreen')\n    plt.axhspan(0.6,.75, alpha=0.5, color='#F6F7A8')\n    plt.axhspan(0, 0.6, alpha=0.5, color='salmon')\n    plt.ylim(series.min(), series.max())\n    plt.xticks(rotation=45, ha=\"right\")\n    plt.title(film + \" Rotten Tomatoes Score over Time\")",
    "id": "c1ba019435894a888c9905cd549b0ef7",
    "idx": 22,
    "time": "2021-01-25T23:51:33.300Z",
    "type": "execution"
   },
   {
    "code": "# calculate_score(\"Artemis Fowl\",all_films)\nplot_film(\"Artemis Fowl\")",
    "id": "ef78aef00f4449e7808156cbe19fd185",
    "idx": 23,
    "time": "2021-01-25T23:51:33.305Z",
    "type": "execution"
   },
   {
    "code": "# calculate_score(\"Wonder Woman 1984\",all_films).plot()\nplot_film(\"Wonder Woman 1984\")",
    "id": "0a404ab049dd4467b70d0d61418c3ee6",
    "idx": 24,
    "time": "2021-01-25T23:51:33.309Z",
    "type": "execution"
   },
   {
    "code": "# calculate_score(\"Mulan\",all_films).plot()\nplot_film(\"Mulan\")",
    "id": "2a43857a9ef34ea1abe592610e444bcf",
    "idx": 25,
    "time": "2021-01-25T23:51:33.311Z",
    "type": "execution"
   },
   {
    "code": "# calculate_score(\"Tenet\",all_films).plot()\nplot_film(\"Tenet\")",
    "id": "65786b7888c04290b82271e76903c656",
    "idx": 26,
    "time": "2021-01-25T23:51:33.314Z",
    "type": "execution"
   },
   {
    "code": "plot_film(\"Lovebirds\")",
    "id": "e0aaebca47bf495b843933d6a4192cd5",
    "idx": 27,
    "time": "2021-01-25T23:51:33.317Z",
    "type": "execution"
   },
   {
    "id": "e766526218b9448bbc84fddcf8350cbe",
    "time": "2021-01-25T23:51:33.442Z",
    "type": "completion"
   },
   {
    "id": "3177ae4def194e6a81c8c22695398971",
    "time": "2021-01-25T23:51:33.463Z",
    "type": "completion"
   },
   {
    "id": "04edfe558ec2423998eb0859ae7b1b4d",
    "time": "2021-01-25T23:51:33.501Z",
    "type": "completion"
   },
   {
    "id": "8ea7dd65ad8e41449a53059eb028b56c",
    "time": "2021-01-25T23:51:33.512Z",
    "type": "completion"
   },
   {
    "id": "04b78cb5b075485194f632e013f6e2e7",
    "time": "2021-01-25T23:52:33.956Z",
    "type": "completion"
   },
   {
    "id": "9dfb573d4c7547c68f4a1fcaa4a62a64",
    "time": "2021-01-25T23:52:34.020Z",
    "type": "completion"
   },
   {
    "id": "b2655460ddf347b7ad6317d57d6c9c74",
    "time": "2021-01-25T23:52:34.029Z",
    "type": "completion"
   },
   {
    "id": "f90cbc5ba5dc4d978c6ef1bef3c771bf",
    "time": "2021-01-25T23:52:34.046Z",
    "type": "completion"
   },
   {
    "id": "1c4f93d3bcca40e1850500ce0ab27ead",
    "time": "2021-01-25T23:52:34.107Z",
    "type": "completion"
   },
   {
    "id": "5282402c126d480a8e20d3a8650b5b33",
    "time": "2021-01-25T23:52:34.109Z",
    "type": "completion"
   },
   {
    "id": "436946f5dbc543a9a4b64879435dbca8",
    "time": "2021-01-25T23:52:34.154Z",
    "type": "completion"
   },
   {
    "id": "5428c7586a36435f8c1923bafc3ca968",
    "time": "2021-01-25T23:52:34.159Z",
    "type": "completion"
   },
   {
    "id": "8556a717af25468fb8004d0eae3d751d",
    "time": "2021-01-25T23:52:34.164Z",
    "type": "completion"
   },
   {
    "id": "93fa76876e8d4c0f8412aebc9cb47935",
    "time": "2021-01-25T23:52:34.174Z",
    "type": "completion"
   },
   {
    "id": "05b49e4d479440d5b089d5b17d360896",
    "time": "2021-01-25T23:52:34.182Z",
    "type": "completion"
   },
   {
    "id": "6f87adab3b0d410e81f6805b14273410",
    "time": "2021-01-25T23:52:34.185Z",
    "type": "completion"
   },
   {
    "id": "b952a1aa8312432d895ce1aa15bacd22",
    "time": "2021-01-25T23:52:34.190Z",
    "type": "completion"
   },
   {
    "id": "c1115d26f4774c7788fb0c1858f90243",
    "time": "2021-01-25T23:52:34.194Z",
    "type": "completion"
   },
   {
    "id": "da199b52f5074ac58c27fb5da33cabfb",
    "time": "2021-01-25T23:52:34.220Z",
    "type": "completion"
   },
   {
    "id": "ab91beeacbf34355899cbd20f276b6ff",
    "time": "2021-01-25T23:52:34.221Z",
    "type": "completion"
   },
   {
    "id": "5b7a2cc3ce754041a2f51ac30d184f11",
    "time": "2021-01-25T23:52:34.221Z",
    "type": "completion"
   },
   {
    "id": "52f037e9877f488b8382eab7fadca779",
    "time": "2021-01-25T23:52:34.222Z",
    "type": "completion"
   },
   {
    "id": "c1ba019435894a888c9905cd549b0ef7",
    "time": "2021-01-25T23:52:34.222Z",
    "type": "completion"
   },
   {
    "id": "ef78aef00f4449e7808156cbe19fd185",
    "time": "2021-01-25T23:52:34.222Z",
    "type": "completion"
   },
   {
    "id": "0a404ab049dd4467b70d0d61418c3ee6",
    "time": "2021-01-25T23:52:34.223Z",
    "type": "completion"
   },
   {
    "id": "2a43857a9ef34ea1abe592610e444bcf",
    "time": "2021-01-25T23:52:34.223Z",
    "type": "completion"
   },
   {
    "id": "65786b7888c04290b82271e76903c656",
    "time": "2021-01-25T23:52:34.223Z",
    "type": "completion"
   },
   {
    "id": "e0aaebca47bf495b843933d6a4192cd5",
    "time": "2021-01-25T23:52:34.224Z",
    "type": "completion"
   },
   {
    "code": "import numpy as np\n\n\ndef calculate_score(film, frame):\n    df = frame[frame['Film'] == film]\n    grouped_1 = df[['date', 'score']].groupby('date').agg([sum, 'count'])\n    grouped_1.columns = grouped_1.columns.droplevel(0)\n    return grouped_1.cumsum()['sum']/grouped_1.cumsum()['count']\n\ncalculate_score(\"Wonder Woman 1984\", all_films)",
    "id": "1c4f93d3bcca40e1850500ce0ab27ead",
    "idx": 8,
    "time": "2021-01-25T23:53:22.636Z",
    "type": "execution"
   },
   {
    "id": "1c4f93d3bcca40e1850500ce0ab27ead",
    "time": "2021-01-25T23:53:22.732Z",
    "type": "completion"
   },
   {
    "code": "# calculate_score(\"Soul\").plot()\nimport matplotlib.pyplot as plt\n\nfor key in movie_urls.keys():\n#     pd.to_numeric(df.Subs).plot.line()\n    df = all_films[all_films==key]\n    plt.plot(calculate_score(key), label=key)\n#     plt.plot(np.arange(len(df.index)), pd.to_numeric(df.Total).pct_change(), label = df.Name.values[0], color = colors[i])\n#     plt.axvline(x=30, color='red', linestyle='dashed',linewidth=0.5)\n    plt.ylabel('Percent Change in Subscribers by Day')\n    plt.xlabel(\"Day (0 is 1 month before Content Cop's release)\")\n    plt.legend()\n# plt.annotate('Content Cop released', xy=(30, 0.015), ha='center', size=10)\n# plt.title('The Impact of Content Cop')\n# plt.savefig('pct_cc.svg')",
    "id": "5282402c126d480a8e20d3a8650b5b33",
    "idx": 9,
    "time": "2021-01-25T23:53:23.418Z",
    "type": "execution"
   },
   {
    "code": "# all_films.to_csv(\"all_films.csv\", index=False)",
    "id": "436946f5dbc543a9a4b64879435dbca8",
    "idx": 10,
    "time": "2021-01-25T23:53:23.583Z",
    "type": "execution"
   },
   {
    "code": "#add more movies\nimport pandas as pd\n\nmovie_urls['Tenet'] = 'https://www.rottentomatoes.com/m/tenet/'\nmovie_urls['Scoob'] = 'https://www.rottentomatoes.com/m/scoob/'\nmovie_urls['The Marksman'] = 'https://www.rottentomatoes.com/m/the_marksman_2021/'\nmovie_urls['Artemis Fowl'] = 'https://www.rottentomatoes.com/m/artemis_fowl/'\nmovie_urls['Lovebirds'] = 'https://www.rottentomatoes.com/m/the_lovebirds_2020/'\n\nnewkeys = ['Tenet', 'Scoob', 'The Marksman', 'Artemis Fowl', 'Lovebirds']\ndfs = []\n\nfor key in newkeys:\n    print(movie_urls[key])\n    temp = get_critic_reviews(movie_urls[key])\n    df = pd.DataFrame.from_dict(temp)\n    df['Film'] = key\n    dfs.append(df)",
    "id": "5428c7586a36435f8c1923bafc3ca968",
    "idx": 11,
    "time": "2021-01-25T23:53:23.720Z",
    "type": "execution"
   },
   {
    "id": "5282402c126d480a8e20d3a8650b5b33",
    "time": "2021-01-25T23:53:23.814Z",
    "type": "completion"
   },
   {
    "code": "new_films = pd.concat(dfs)\nnew_films",
    "id": "8556a717af25468fb8004d0eae3d751d",
    "idx": 12,
    "time": "2021-01-25T23:53:23.855Z",
    "type": "execution"
   },
   {
    "id": "436946f5dbc543a9a4b64879435dbca8",
    "time": "2021-01-25T23:53:23.911Z",
    "type": "completion"
   },
   {
    "code": "new_films['score'] = new_films['fresh'].apply(lambda x: 1 if x == 'fresh' else 0)\nnew_films",
    "id": "93fa76876e8d4c0f8412aebc9cb47935",
    "idx": 13,
    "time": "2021-01-25T23:53:24.001Z",
    "type": "execution"
   },
   {
    "code": "new_films['date'] = pd.to_datetime(new_films['date'], format=\"%B %d, %Y\")\nnew_films = new_films.sort_values('date')",
    "id": "05b49e4d479440d5b089d5b17d360896",
    "idx": 14,
    "time": "2021-01-25T23:53:24.137Z",
    "type": "execution"
   },
   {
    "code": "new_films",
    "id": "6f87adab3b0d410e81f6805b14273410",
    "idx": 15,
    "time": "2021-01-25T23:53:24.269Z",
    "type": "execution"
   },
   {
    "code": "import matplotlib.pyplot as plt\n\nfor key in newkeys:\n#     pd.to_numeric(df.Subs).plot.line()\n    df = new_films[new_films==key]\n    plt.plot(calculate_score(key, new_films), label=key)\n#     plt.plot(np.arange(len(df.index)), pd.to_numeric(df.Total).pct_change(), label = df.Name.values[0], color = colors[i])\n#     plt.axvline(x=30, color='red', linestyle='dashed',linewidth=0.5)\n    plt.ylabel('Percent Change in Subscribers by Day')\n    plt.xlabel(\"Day (0 is 1 month before Content Cop's release)\")\n    plt.legend()",
    "id": "b952a1aa8312432d895ce1aa15bacd22",
    "idx": 16,
    "time": "2021-01-25T23:53:24.960Z",
    "type": "execution"
   },
   {
    "code": "all_films = pd.read_csv(\"all_films.csv\")\nall_films",
    "id": "c1115d26f4774c7788fb0c1858f90243",
    "idx": 17,
    "time": "2021-01-25T23:53:25.364Z",
    "type": "execution"
   },
   {
    "code": "all_films = pd.concat([all_films, new_films])",
    "id": "da199b52f5074ac58c27fb5da33cabfb",
    "idx": 18,
    "time": "2021-01-25T23:53:26.623Z",
    "type": "execution"
   },
   {
    "code": "all_films['date'] = pd.to_datetime(all_films['date'])\nall_films = all_films.sort_values('date')",
    "id": "ab91beeacbf34355899cbd20f276b6ff",
    "idx": 19,
    "time": "2021-01-25T23:53:26.797Z",
    "type": "execution"
   },
   {
    "code": "for key in movie_urls.keys():\n#     pd.to_numeric(df.Subs).plot.line()\n    df = all_films[all_films==key]\n    plt.plot(calculate_score(key, all_films), label=key)\n#     plt.plot(np.arange(len(df.index)), pd.to_numeric(df.Total).pct_change(), label = df.Name.values[0], color = colors[i])\n#     plt.axvline(x=30, color='red', linestyle='dashed',linewidth=0.5)\n    plt.ylabel('Percent Change in Subscribers by Day')\n    plt.xlabel(\"Day (0 is 1 month before Content Cop's release)\")\n    plt.legend()\n# plt.annotate('Content Cop released', xy=(30, 0.015), ha='center', size=10)\n# plt.title('The Impact of Content Cop')\n# plt.savefig('pct_cc.svg')",
    "id": "5b7a2cc3ce754041a2f51ac30d184f11",
    "idx": 20,
    "time": "2021-01-25T23:53:27.197Z",
    "type": "execution"
   },
   {
    "code": "%config InlineBackend.figure_format = 'svg'",
    "id": "52f037e9877f488b8382eab7fadca779",
    "idx": 21,
    "time": "2021-01-25T23:53:27.518Z",
    "type": "execution"
   },
   {
    "code": "def plot_film(film):\n    df = all_films[all_films==film]\n    series = calculate_score(film, all_films)\n    plt.plot(series)\n    plt.axhline(y=0.75, color='yellow', linestyle='dashed',linewidth=0.5)\n    plt.axhline(y=0.6, color='red', linestyle='dashed',linewidth=0.5)\n    plt.axhspan(0.75, 1, alpha=0.5, color='lightgreen')\n    plt.axhspan(0.6,.75, alpha=0.5, color='#F6F7A8')\n    plt.axhspan(0, 0.6, alpha=0.5, color='salmon')\n    plt.ylim(series.min(), series.max())\n    plt.xticks(rotation=45, ha=\"right\")\n    plt.title(film + \" Rotten Tomatoes Score over Time\")",
    "id": "c1ba019435894a888c9905cd549b0ef7",
    "idx": 22,
    "time": "2021-01-25T23:53:27.749Z",
    "type": "execution"
   },
   {
    "code": "# calculate_score(\"Artemis Fowl\",all_films)\nplot_film(\"Artemis Fowl\")",
    "id": "ef78aef00f4449e7808156cbe19fd185",
    "idx": 23,
    "time": "2021-01-25T23:53:28.411Z",
    "type": "execution"
   },
   {
    "code": "# calculate_score(\"Wonder Woman 1984\",all_films).plot()\nplot_film(\"Wonder Woman 1984\")",
    "id": "0a404ab049dd4467b70d0d61418c3ee6",
    "idx": 24,
    "time": "2021-01-25T23:53:28.865Z",
    "type": "execution"
   },
   {
    "code": "# calculate_score(\"Mulan\",all_films).plot()\nplot_film(\"Mulan\")",
    "id": "2a43857a9ef34ea1abe592610e444bcf",
    "idx": 25,
    "time": "2021-01-25T23:53:29.074Z",
    "type": "execution"
   },
   {
    "code": "# calculate_score(\"Tenet\",all_films).plot()\nplot_film(\"Tenet\")",
    "id": "65786b7888c04290b82271e76903c656",
    "idx": 26,
    "time": "2021-01-25T23:53:30.303Z",
    "type": "execution"
   },
   {
    "code": "plot_film(\"Lovebirds\")",
    "id": "e0aaebca47bf495b843933d6a4192cd5",
    "idx": 27,
    "time": "2021-01-25T23:53:30.483Z",
    "type": "execution"
   },
   {
    "id": "5428c7586a36435f8c1923bafc3ca968",
    "time": "2021-01-25T23:54:16.506Z",
    "type": "completion"
   },
   {
    "id": "8556a717af25468fb8004d0eae3d751d",
    "time": "2021-01-25T23:54:16.574Z",
    "type": "completion"
   },
   {
    "id": "93fa76876e8d4c0f8412aebc9cb47935",
    "time": "2021-01-25T23:54:16.580Z",
    "type": "completion"
   },
   {
    "id": "05b49e4d479440d5b089d5b17d360896",
    "time": "2021-01-25T23:54:16.591Z",
    "type": "completion"
   },
   {
    "id": "6f87adab3b0d410e81f6805b14273410",
    "time": "2021-01-25T23:54:16.618Z",
    "type": "completion"
   },
   {
    "id": "b952a1aa8312432d895ce1aa15bacd22",
    "time": "2021-01-25T23:54:17.052Z",
    "type": "completion"
   },
   {
    "id": "c1115d26f4774c7788fb0c1858f90243",
    "time": "2021-01-25T23:54:17.105Z",
    "type": "completion"
   },
   {
    "id": "da199b52f5074ac58c27fb5da33cabfb",
    "time": "2021-01-25T23:54:17.106Z",
    "type": "completion"
   },
   {
    "id": "ab91beeacbf34355899cbd20f276b6ff",
    "time": "2021-01-25T23:54:17.117Z",
    "type": "completion"
   },
   {
    "id": "5b7a2cc3ce754041a2f51ac30d184f11",
    "time": "2021-01-25T23:54:17.650Z",
    "type": "completion"
   },
   {
    "id": "52f037e9877f488b8382eab7fadca779",
    "time": "2021-01-25T23:54:17.651Z",
    "type": "completion"
   },
   {
    "id": "c1ba019435894a888c9905cd549b0ef7",
    "time": "2021-01-25T23:54:17.654Z",
    "type": "completion"
   },
   {
    "id": "ef78aef00f4449e7808156cbe19fd185",
    "time": "2021-01-25T23:54:17.789Z",
    "type": "completion"
   },
   {
    "id": "0a404ab049dd4467b70d0d61418c3ee6",
    "time": "2021-01-25T23:54:18.002Z",
    "type": "completion"
   },
   {
    "id": "2a43857a9ef34ea1abe592610e444bcf",
    "time": "2021-01-25T23:54:18.245Z",
    "type": "completion"
   },
   {
    "id": "65786b7888c04290b82271e76903c656",
    "time": "2021-01-25T23:54:18.426Z",
    "type": "completion"
   },
   {
    "id": "e0aaebca47bf495b843933d6a4192cd5",
    "time": "2021-01-25T23:54:18.660Z",
    "type": "completion"
   },
   {
    "code": "movie_urls.keys()",
    "id": "5c77203b73374f79834e654618454c6b",
    "idx": 28,
    "time": "2021-01-26T00:01:15.591Z",
    "type": "execution"
   },
   {
    "id": "5c77203b73374f79834e654618454c6b",
    "time": "2021-01-26T00:01:15.665Z",
    "type": "completion"
   },
   {
    "code": "plot_film(\"Scoob\")",
    "id": "3a481fd02aa84ea38fd299dcfe535da0",
    "idx": 29,
    "time": "2021-01-26T00:01:25.361Z",
    "type": "execution"
   },
   {
    "id": "3a481fd02aa84ea38fd299dcfe535da0",
    "time": "2021-01-26T00:01:25.908Z",
    "type": "completion"
   },
   {
    "code": "plot_film(\"Birds of Prey\")",
    "id": "6394cfe562784e659b5064f12cf4d5bd",
    "idx": 30,
    "time": "2021-01-26T00:01:39.020Z",
    "type": "execution"
   },
   {
    "id": "6394cfe562784e659b5064f12cf4d5bd",
    "time": "2021-01-26T00:01:39.634Z",
    "type": "completion"
   },
   {
    "code": "plot_film(\"The Marksman\")",
    "id": "fe50567c006443d49003b8d9964f7c51",
    "idx": 31,
    "time": "2021-01-26T00:02:01.792Z",
    "type": "execution"
   },
   {
    "id": "fe50567c006443d49003b8d9964f7c51",
    "time": "2021-01-26T00:02:02.414Z",
    "type": "completion"
   },
   {
    "code": "all_films.to_csv(\"new_films.csv\",index=False)",
    "id": "1bb6aaa02dcc4c139d551d168e0ec998",
    "idx": 32,
    "time": "2021-01-26T00:02:19.251Z",
    "type": "execution"
   },
   {
    "id": "1bb6aaa02dcc4c139d551d168e0ec998",
    "time": "2021-01-26T00:02:19.371Z",
    "type": "completion"
   },
   {
    "code": "movie_urls.keys()",
    "id": "2e83538edf3e4f8d8a711a00861b4787",
    "idx": 33,
    "time": "2021-01-26T00:20:04.927Z",
    "type": "execution"
   },
   {
    "id": "2e83538edf3e4f8d8a711a00861b4787",
    "time": "2021-01-26T00:20:05.028Z",
    "type": "completion"
   },
   {
    "code": "plot_film(\"Soul\")",
    "id": "8f7b56a98a6e452690e75713a765558d",
    "idx": 34,
    "time": "2021-01-26T00:20:23.743Z",
    "type": "execution"
   },
   {
    "id": "8f7b56a98a6e452690e75713a765558d",
    "time": "2021-01-26T00:20:24.235Z",
    "type": "completion"
   },
   {
    "code": "plot_film(\"Lovebirds\")",
    "id": "8f7b56a98a6e452690e75713a765558d",
    "idx": 34,
    "time": "2021-01-26T00:20:32.751Z",
    "type": "execution"
   },
   {
    "id": "8f7b56a98a6e452690e75713a765558d",
    "time": "2021-01-26T00:20:33.410Z",
    "type": "completion"
   },
   {
    "code": "plot_film(\"Sonic\")",
    "id": "8f7b56a98a6e452690e75713a765558d",
    "idx": 34,
    "time": "2021-01-26T00:20:44.355Z",
    "type": "execution"
   },
   {
    "id": "8f7b56a98a6e452690e75713a765558d",
    "time": "2021-01-26T00:20:44.987Z",
    "type": "completion"
   },
   {
    "code": "all_films[all_films[\"Film\"]==\"Sonic\"]",
    "id": "559fe0f6f2444bfc8a4127bcf693f6cc",
    "idx": 35,
    "time": "2021-01-26T00:21:14.422Z",
    "type": "execution"
   },
   {
    "id": "559fe0f6f2444bfc8a4127bcf693f6cc",
    "time": "2021-01-26T00:21:14.550Z",
    "type": "completion"
   },
   {
    "code": "all_films[all_films[\"Film\"]==\"Sonic\"].sort_values(\"date\")",
    "id": "559fe0f6f2444bfc8a4127bcf693f6cc",
    "idx": 35,
    "time": "2021-01-26T00:21:27.842Z",
    "type": "execution"
   },
   {
    "id": "559fe0f6f2444bfc8a4127bcf693f6cc",
    "time": "2021-01-26T00:21:27.995Z",
    "type": "completion"
   },
   {
    "code": "all_films[(all_films[\"Film\"]==\"Sonic\") & (all_films[\"date\"]==\"2020-02-12\")]",
    "id": "559fe0f6f2444bfc8a4127bcf693f6cc",
    "idx": 35,
    "time": "2021-01-26T00:22:07.931Z",
    "type": "execution"
   },
   {
    "id": "559fe0f6f2444bfc8a4127bcf693f6cc",
    "time": "2021-01-26T00:22:08.019Z",
    "type": "completion"
   },
   {
    "code": "movie_urls = {'Wonder Woman 1984': 'https://www.rottentomatoes.com/m/wonder_woman_1984/', \n              'Soul':'https://www.rottentomatoes.com/m/soul_2020/', \n              'Mulan': 'https://www.rottentomatoes.com/m/mulan_2020/',\n              'Birds of Prey': 'https://www.rottentomatoes.com/m/birds_of_prey_2020/',\n              'Sonic': 'https://www.rottentomatoes.com/m/sonic_the_hedgehog_2020/'\n             }\n\nmovie_urls[\"Captain Marvel\"] = \"https://www.rottentomatoes.com/m/captain_marvel/\"\nmovie_urls[\"Lion King\"] = \"https://www.rottentomatoes.com/m/the_lion_king_2019/\"\nmovie_urls[\"Aladdin\"] = \"https://www.rottentomatoes.com/m/aladdin/\"\nmovie_urls[\"Joker\"] = \"https://www.rottentomatoes.com/m/joker_2019/\"\nmovie_urls[\"Shazam!\"] = \"https://www.rottentomatoes.com/m/shazam/\"\nmovie_urls[\"Godzilla: King of the Monsters\"] = \"https://www.rottentomatoes.com/m/godzilla_king_of_the_monsters_2019/\"\nmovie_urls.keys()",
    "id": "ba75f81eae0c43879ade708c52166e21",
    "idx": 3,
    "time": "2021-01-27T00:18:07.772Z",
    "type": "execution"
   },
   {
    "id": "ba75f81eae0c43879ade708c52166e21",
    "time": "2021-01-27T00:18:07.882Z",
    "type": "completion"
   },
   {
    "code": "import requests\nimport time\n\n# requirements\nfrom bs4 import BeautifulSoup\nfrom requests import TooManyRedirects\nimport re\n\ndef _make_soup(url):\n    try:\n        r = requests.get(url)\n        soup = BeautifulSoup(r.content, 'html.parser')\n    except TooManyRedirects:\n        soup = ''\n    return soup\n\n#regex patterns\npage_pat = re.compile(r'Page 1 of \\d+')\nreview_pat = re.compile(r'<div class=\\\"the_review\\\" data-qa=\\\"review-text\\\">[;a-zA-Z\\s,-.\\'\\/\\?\\[\\]\\\":\\']*</div>')\nrating_pat = re.compile(r'Original Score:\\s([A-Z](\\+|-)?|\\d(.\\d)?(\\/\\d)?)')\nfresh_pat = re.compile(r'small\\s(fresh|rotten)\\\"')\ncritic_pat = re.compile(r'\\/\\\"\\>([A-Z][a-zA-Z]+\\s[A-Z][a-zA-Z\\-]+)|([A-Z][a-zA-Z.]+\\s[A-Z].?\\s[A-Z][a-zA-Z]+)|([A-Z][a-zA-Z]+\\s[A-Z]+\\'[A-Z][a-zA-Z]+)')\npublisher_pat = re.compile(r'\\\"subtle\\\">[a-zA-Z\\s,.\\(\\)\\'\\-&;!\\/\\d+]+</em>')\ndate_pat = re.compile(r'[a-zA-Z]+\\s\\d+,\\s\\d+')",
    "id": "c088557172df4ee88340993c0d83f871",
    "idx": 0,
    "time": "2021-01-27T00:18:15.198Z",
    "type": "execution"
   },
   {
    "code": "def _get_critic_reviews_from_page(soup):\n    reviews = list()\n    rating = list()\n    fresh = list()\n    critic = list()\n    top_critic = list()\n    publisher = list()\n    date = list()\n    \n    soup = str(soup)\n    review_soup = soup.split('=\"review_table')[1].split('row review_table_row')\n    review_soup.pop(0)\n\n    for review in review_soup:\n        match = re.findall(review_pat, str(review))\n        if len(match) > 0:\n            m = match[0]            \n            for iden in ['<div class=\"the_review\" data-qa=\"review-text\"> ','</div>']:\n                m = m.replace(iden,'')\n            reviews.append(m.strip('\"'))            \n            # extract rating\n            match = re.findall(rating_pat, str(review))\n            if len(match) > 0:\n                m = match[0][0]\n                if '/1' in m:\n                    sp_m = m.split('/')\n                    if sp_m[-1] == '1':\n                        sp_m[-1] = '10'\n                    m = '/'.join(sp_m)\n                rating.append(m)\n            else:\n                rating.append(None)            \n            # extract fresh indicator\n            match = re.findall(fresh_pat, str(review))\n            if len(match) > 0:\n                fresh.append(match[0])\n            else:\n                fresh.append(None)            \n            # extract critic\n            match = re.findall(critic_pat, str(review))\n            if len(match) > 0:\n                critic.append(''.join(match[0]))\n            else:\n                critic.append(None)            \n            # check if top critic\n            if '> Top Critic<' in str(review):\n                top_critic.append(1)\n            else:\n                top_critic.append(0)            \n            # extract publisher\n            match = re.findall(publisher_pat, str(review))\n            if len(match) > 0:\n                m = match[0]\n                m = m.replace('\"subtle\">', '')\n                m = m.replace('</em>','')\n                publisher.append(m)\n            else:\n                publisher.append(None)            \n            # extract date\n            match = re.findall(date_pat, str(review))\n            if len(match) > 0:\n                date.append(match[0].strip('\"'))\n            else:\n                date.append(None)\n            \n    return [reviews, rating, fresh, critic, top_critic, publisher, date]\n\ndef _get_num_pages(soup):\n    match = re.findall(page_pat,str(list(soup)))\n    if len(match) > 0:\n        match = match[0]\n        match = match.split(' of ')[-1]\n        return match\n    else:\n        return None",
    "id": "473f70b9197047778ba396a40a4ed7a7",
    "idx": 1,
    "time": "2021-01-27T00:18:15.200Z",
    "type": "execution"
   },
   {
    "code": "def get_critic_reviews(page):\n    info = [[],[],[],[],[],[],[]]\n    soup = _make_soup(page + \"reviews\")\n#     print(soup)\n    pages = _get_num_pages(soup)\n#     print(pages)\n    if pages is not None:\n        for page_num in range(1,int(pages)+1):\n            soup = _make_soup(page + \"reviews?page=\" + str(page_num) + \"&sort=\")\n            c_info = _get_critic_reviews_from_page(soup)\n            \n            # accumulate review info\n            for i in range(len(c_info)):\n                info[i] = info[i] + c_info[i]\n        \n        c_info = dict()\n        keys = ['reviews', 'rating', 'fresh', 'critic', 'top_critic', 'publisher', 'date']\n        for k in range(len(keys)):\n            c_info[keys[k]] = info[k]        \n    else:\n        c_info = None        \n    return c_info",
    "id": "2a164d4bc03440c287cd2aa9baee929e",
    "idx": 2,
    "time": "2021-01-27T00:18:15.202Z",
    "type": "execution"
   },
   {
    "code": "movie_urls = {'Wonder Woman 1984': 'https://www.rottentomatoes.com/m/wonder_woman_1984/', \n              'Soul':'https://www.rottentomatoes.com/m/soul_2020/', \n              'Mulan': 'https://www.rottentomatoes.com/m/mulan_2020/',\n              'Birds of Prey': 'https://www.rottentomatoes.com/m/birds_of_prey_2020/',\n              'Sonic': 'https://www.rottentomatoes.com/m/sonic_the_hedgehog_2020/'\n             }\n\nmovie_urls[\"Captain Marvel\"] = \"https://www.rottentomatoes.com/m/captain_marvel/\"\nmovie_urls[\"Lion King\"] = \"https://www.rottentomatoes.com/m/the_lion_king_2019/\"\nmovie_urls[\"Aladdin\"] = \"https://www.rottentomatoes.com/m/aladdin/\"\nmovie_urls[\"Joker\"] = \"https://www.rottentomatoes.com/m/joker_2019/\"\nmovie_urls[\"Shazam!\"] = \"https://www.rottentomatoes.com/m/shazam/\"\nmovie_urls[\"Godzilla: King of the Monsters\"] = \"https://www.rottentomatoes.com/m/godzilla_king_of_the_monsters_2019/\"\nmovie_urls.keys()",
    "id": "ba75f81eae0c43879ade708c52166e21",
    "idx": 3,
    "time": "2021-01-27T00:18:15.204Z",
    "type": "execution"
   },
   {
    "code": "import pandas as pd\n\ndfs = []\nfor key in movie_urls.keys():\n    temp = get_critic_reviews(movie_urls[key])\n    df = pd.DataFrame.from_dict(temp)\n    df['Film'] = key\n    dfs.append(df)",
    "id": "a1ef4cd89f0f41c8a9233b92ab030587",
    "idx": 4,
    "time": "2021-01-27T00:18:15.206Z",
    "type": "execution"
   },
   {
    "code": "all_films = pd.concat(dfs)\nall_films",
    "id": "0ef9e93206b741ab896dda73e440fe69",
    "idx": 5,
    "time": "2021-01-27T00:18:15.208Z",
    "type": "execution"
   },
   {
    "code": "all_films['score'] = all_films['fresh'].apply(lambda x: 1 if x == 'fresh' else 0)\nall_films",
    "id": "bd3af87003f34f009f0f49e7c7cea343",
    "idx": 6,
    "time": "2021-01-27T00:18:15.210Z",
    "type": "execution"
   },
   {
    "code": "all_films['date'] = pd.to_datetime(all_films['date'], format=\"%B %d, %Y\")\nall_films = all_films.sort_values('date')",
    "id": "59dcb1b5e4a6427482402c1d1c927436",
    "idx": 7,
    "time": "2021-01-27T00:18:15.211Z",
    "type": "execution"
   },
   {
    "code": "import numpy as np\n\n\ndef calculate_score(film, frame):\n    df = frame[frame['Film'] == film]\n    grouped_1 = df[['date', 'score']].groupby('date').agg([sum, 'count'])\n    grouped_1.columns = grouped_1.columns.droplevel(0)\n    return grouped_1.cumsum()['sum']/grouped_1.cumsum()['count']\n\ncalculate_score(\"Wonder Woman 1984\", all_films)",
    "id": "5e1cead1642b4c288daa8723c29a17c1",
    "idx": 8,
    "time": "2021-01-27T00:18:15.213Z",
    "type": "execution"
   },
   {
    "code": "# calculate_score(\"Soul\").plot()\nimport matplotlib.pyplot as plt\n\nfor key in movie_urls.keys():\n#     pd.to_numeric(df.Subs).plot.line()\n    df = all_films[all_films==key]\n    plt.plot(calculate_score(key), label=key)\n#     plt.plot(np.arange(len(df.index)), pd.to_numeric(df.Total).pct_change(), label = df.Name.values[0], color = colors[i])\n#     plt.axvline(x=30, color='red', linestyle='dashed',linewidth=0.5)\n    plt.ylabel('Percent Change in Subscribers by Day')\n    plt.xlabel(\"Day (0 is 1 month before Content Cop's release)\")\n    plt.legend()\n# plt.annotate('Content Cop released', xy=(30, 0.015), ha='center', size=10)\n# plt.title('The Impact of Content Cop')\n# plt.savefig('pct_cc.svg')",
    "id": "2df2182ab54842498ef70c9d7e8c3931",
    "idx": 9,
    "time": "2021-01-27T00:18:15.214Z",
    "type": "execution"
   },
   {
    "code": "# all_films.to_csv(\"all_films.csv\", index=False)",
    "id": "76def201162a44fe8a10a32d4dc90bc7",
    "idx": 10,
    "time": "2021-01-27T00:18:15.216Z",
    "type": "execution"
   },
   {
    "code": "#add more movies\nimport pandas as pd\n\nmovie_urls['Tenet'] = 'https://www.rottentomatoes.com/m/tenet/'\nmovie_urls['Scoob'] = 'https://www.rottentomatoes.com/m/scoob/'\nmovie_urls['The Marksman'] = 'https://www.rottentomatoes.com/m/the_marksman_2021/'\nmovie_urls['Artemis Fowl'] = 'https://www.rottentomatoes.com/m/artemis_fowl/'\nmovie_urls['Lovebirds'] = 'https://www.rottentomatoes.com/m/the_lovebirds_2020/'\n\nnewkeys = ['Tenet', 'Scoob', 'The Marksman', 'Artemis Fowl', 'Lovebirds']\ndfs = []\n\nfor key in newkeys:\n    print(movie_urls[key])\n    temp = get_critic_reviews(movie_urls[key])\n    df = pd.DataFrame.from_dict(temp)\n    df['Film'] = key\n    dfs.append(df)",
    "id": "61e72b596e6643f891e63bc4132352a6",
    "idx": 11,
    "time": "2021-01-27T00:18:15.217Z",
    "type": "execution"
   },
   {
    "code": "new_films = pd.concat(dfs)\nnew_films",
    "id": "b52a64b1f3904895853d7598c1701442",
    "idx": 12,
    "time": "2021-01-27T00:18:15.219Z",
    "type": "execution"
   },
   {
    "code": "new_films['score'] = new_films['fresh'].apply(lambda x: 1 if x == 'fresh' else 0)\nnew_films",
    "id": "df0b0a25c2ea4dada89c360d5362812e",
    "idx": 13,
    "time": "2021-01-27T00:18:15.220Z",
    "type": "execution"
   },
   {
    "code": "new_films['date'] = pd.to_datetime(new_films['date'], format=\"%B %d, %Y\")\nnew_films = new_films.sort_values('date')",
    "id": "552d587e0007467ca1d99c4d87464486",
    "idx": 14,
    "time": "2021-01-27T00:18:15.221Z",
    "type": "execution"
   },
   {
    "code": "new_films",
    "id": "17ed9fbe70db4d6ab3dbb8e037efef5b",
    "idx": 15,
    "time": "2021-01-27T00:18:15.223Z",
    "type": "execution"
   },
   {
    "code": "import matplotlib.pyplot as plt\n\nfor key in newkeys:\n#     pd.to_numeric(df.Subs).plot.line()\n    df = new_films[new_films==key]\n    plt.plot(calculate_score(key, new_films), label=key)\n#     plt.plot(np.arange(len(df.index)), pd.to_numeric(df.Total).pct_change(), label = df.Name.values[0], color = colors[i])\n#     plt.axvline(x=30, color='red', linestyle='dashed',linewidth=0.5)\n    plt.ylabel('Percent Change in Subscribers by Day')\n    plt.xlabel(\"Day (0 is 1 month before Content Cop's release)\")\n    plt.legend()",
    "id": "4c6477ce81f24006b86f338b7f371f92",
    "idx": 16,
    "time": "2021-01-27T00:18:15.225Z",
    "type": "execution"
   },
   {
    "code": "all_films = pd.read_csv(\"all_films.csv\")\nall_films",
    "id": "b5c21d498b654dbb86b5539a331743e9",
    "idx": 17,
    "time": "2021-01-27T00:18:15.227Z",
    "type": "execution"
   },
   {
    "code": "all_films = pd.concat([all_films, new_films])",
    "id": "2de1ff824f4b4a5a8a28a100b4694d6f",
    "idx": 18,
    "time": "2021-01-27T00:18:15.228Z",
    "type": "execution"
   },
   {
    "code": "all_films['date'] = pd.to_datetime(all_films['date'])\nall_films = all_films.sort_values('date')",
    "id": "c3b00c043c2c46938aaf29a975351135",
    "idx": 19,
    "time": "2021-01-27T00:18:15.228Z",
    "type": "execution"
   },
   {
    "code": "for key in movie_urls.keys():\n#     pd.to_numeric(df.Subs).plot.line()\n    df = all_films[all_films==key]\n    plt.plot(calculate_score(key, all_films), label=key)\n#     plt.plot(np.arange(len(df.index)), pd.to_numeric(df.Total).pct_change(), label = df.Name.values[0], color = colors[i])\n#     plt.axvline(x=30, color='red', linestyle='dashed',linewidth=0.5)\n    plt.ylabel('Percent Change in Subscribers by Day')\n    plt.xlabel(\"Day (0 is 1 month before Content Cop's release)\")\n    plt.legend()\n# plt.annotate('Content Cop released', xy=(30, 0.015), ha='center', size=10)\n# plt.title('The Impact of Content Cop')\n# plt.savefig('pct_cc.svg')",
    "id": "f4a2a4c0db4a466b899d078ba3a2b737",
    "idx": 20,
    "time": "2021-01-27T00:18:15.229Z",
    "type": "execution"
   },
   {
    "code": "%config InlineBackend.figure_format = 'svg'",
    "id": "8066d71185b344e68a5202b5f02658af",
    "idx": 21,
    "time": "2021-01-27T00:18:15.230Z",
    "type": "execution"
   },
   {
    "code": "def plot_film(film):\n    df = all_films[all_films==film]\n    series = calculate_score(film, all_films)\n    plt.plot(series)\n    plt.axhline(y=0.75, color='yellow', linestyle='dashed',linewidth=0.5)\n    plt.axhline(y=0.6, color='red', linestyle='dashed',linewidth=0.5)\n    plt.axhspan(0.75, 1, alpha=0.5, color='lightgreen')\n    plt.axhspan(0.6,.75, alpha=0.5, color='#F6F7A8')\n    plt.axhspan(0, 0.6, alpha=0.5, color='salmon')\n    plt.ylim(series.min(), series.max())\n    plt.xticks(rotation=45, ha=\"right\")\n    plt.title(film + \" Rotten Tomatoes Score over Time\")",
    "id": "7a774c9950fa45698183e4228404cda1",
    "idx": 22,
    "time": "2021-01-27T00:18:15.231Z",
    "type": "execution"
   },
   {
    "code": "# calculate_score(\"Artemis Fowl\",all_films)\nplot_film(\"Artemis Fowl\")",
    "id": "b7735f14cc444cfcbb9a225e52f32b96",
    "idx": 23,
    "time": "2021-01-27T00:18:15.232Z",
    "type": "execution"
   },
   {
    "code": "# calculate_score(\"Wonder Woman 1984\",all_films).plot()\nplot_film(\"Wonder Woman 1984\")",
    "id": "718d9ad72a6644f1b0512e6341e4215d",
    "idx": 24,
    "time": "2021-01-27T00:18:15.233Z",
    "type": "execution"
   },
   {
    "code": "# calculate_score(\"Mulan\",all_films).plot()\nplot_film(\"Mulan\")",
    "id": "3ee93c9b761748559d88a432bffe4673",
    "idx": 25,
    "time": "2021-01-27T00:18:15.234Z",
    "type": "execution"
   },
   {
    "code": "# calculate_score(\"Tenet\",all_films).plot()\nplot_film(\"Tenet\")",
    "id": "a2c2ec3bf43c4ea88f43267551b13aa5",
    "idx": 26,
    "time": "2021-01-27T00:18:15.235Z",
    "type": "execution"
   },
   {
    "code": "plot_film(\"Lovebirds\")",
    "id": "56ac30e5452c43a4b4d6fd823dc946cf",
    "idx": 27,
    "time": "2021-01-27T00:18:15.238Z",
    "type": "execution"
   },
   {
    "code": "movie_urls.keys()",
    "id": "ea2b9d6daa7e4c59b21dbedc2bde8446",
    "idx": 28,
    "time": "2021-01-27T00:18:15.240Z",
    "type": "execution"
   },
   {
    "code": "plot_film(\"Scoob\")",
    "id": "e0de2efc4fa8444b867726348d38bd7c",
    "idx": 29,
    "time": "2021-01-27T00:18:15.241Z",
    "type": "execution"
   },
   {
    "code": "plot_film(\"Birds of Prey\")",
    "id": "8d5262a6f57449278d48a2d966e7c6a3",
    "idx": 30,
    "time": "2021-01-27T00:18:15.243Z",
    "type": "execution"
   },
   {
    "code": "plot_film(\"The Marksman\")",
    "id": "31b7f32da2bc458f81c5bdc2427308b8",
    "idx": 31,
    "time": "2021-01-27T00:18:15.244Z",
    "type": "execution"
   },
   {
    "code": "all_films.to_csv(\"new_films.csv\",index=False)",
    "id": "59ce187c1c0f425e8d9572e7dc688abf",
    "idx": 32,
    "time": "2021-01-27T00:18:15.245Z",
    "type": "execution"
   },
   {
    "code": "movie_urls.keys()",
    "id": "e13eef2bc3684d108942ca0d5772bc3d",
    "idx": 33,
    "time": "2021-01-27T00:18:15.246Z",
    "type": "execution"
   },
   {
    "code": "plot_film(\"Sonic\")",
    "id": "5caab196d71847da906897524652f0e7",
    "idx": 34,
    "time": "2021-01-27T00:18:15.247Z",
    "type": "execution"
   },
   {
    "id": "c088557172df4ee88340993c0d83f871",
    "time": "2021-01-27T00:18:15.557Z",
    "type": "completion"
   },
   {
    "id": "473f70b9197047778ba396a40a4ed7a7",
    "time": "2021-01-27T00:18:15.562Z",
    "type": "completion"
   },
   {
    "id": "2a164d4bc03440c287cd2aa9baee929e",
    "time": "2021-01-27T00:18:15.610Z",
    "type": "completion"
   },
   {
    "id": "ba75f81eae0c43879ade708c52166e21",
    "time": "2021-01-27T00:18:15.613Z",
    "type": "completion"
   },
   {
    "code": "all_films[(all_films[\"Film\"]==\"Sonic\") & (all_films[\"date\"]==\"2020-02-12\")]",
    "id": "1ad96a7a631c410b8001bbd8c1d67709",
    "idx": 35,
    "time": "2021-01-27T00:18:23.208Z",
    "type": "execution"
   },
   {
    "code": "plot_film(\"Aladdin\")",
    "id": "e9bb416227734bad86fbd61e3ae633f3",
    "idx": 36,
    "time": "2021-01-27T00:18:28.897Z",
    "type": "execution"
   },
   {
    "id": "a1ef4cd89f0f41c8a9233b92ab030587",
    "time": "2021-01-27T00:20:49.955Z",
    "type": "completion"
   },
   {
    "id": "0ef9e93206b741ab896dda73e440fe69",
    "time": "2021-01-27T00:20:50.016Z",
    "type": "completion"
   },
   {
    "id": "bd3af87003f34f009f0f49e7c7cea343",
    "time": "2021-01-27T00:20:50.053Z",
    "type": "completion"
   },
   {
    "id": "59dcb1b5e4a6427482402c1d1c927436",
    "time": "2021-01-27T00:20:50.068Z",
    "type": "completion"
   },
   {
    "id": "5e1cead1642b4c288daa8723c29a17c1",
    "time": "2021-01-27T00:20:50.104Z",
    "type": "completion"
   },
   {
    "id": "2df2182ab54842498ef70c9d7e8c3931",
    "time": "2021-01-27T00:20:50.505Z",
    "type": "completion"
   },
   {
    "id": "76def201162a44fe8a10a32d4dc90bc7",
    "time": "2021-01-27T00:20:50.507Z",
    "type": "completion"
   },
   {
    "id": "61e72b596e6643f891e63bc4132352a6",
    "time": "2021-01-27T00:20:50.551Z",
    "type": "completion"
   },
   {
    "id": "b52a64b1f3904895853d7598c1701442",
    "time": "2021-01-27T00:20:50.553Z",
    "type": "completion"
   },
   {
    "id": "df0b0a25c2ea4dada89c360d5362812e",
    "time": "2021-01-27T00:20:50.603Z",
    "type": "completion"
   },
   {
    "id": "552d587e0007467ca1d99c4d87464486",
    "time": "2021-01-27T00:20:50.609Z",
    "type": "completion"
   },
   {
    "id": "17ed9fbe70db4d6ab3dbb8e037efef5b",
    "time": "2021-01-27T00:20:50.614Z",
    "type": "completion"
   },
   {
    "id": "4c6477ce81f24006b86f338b7f371f92",
    "time": "2021-01-27T00:20:50.657Z",
    "type": "completion"
   },
   {
    "id": "b5c21d498b654dbb86b5539a331743e9",
    "time": "2021-01-27T00:20:50.660Z",
    "type": "completion"
   },
   {
    "id": "2de1ff824f4b4a5a8a28a100b4694d6f",
    "time": "2021-01-27T00:20:50.664Z",
    "type": "completion"
   },
   {
    "id": "c3b00c043c2c46938aaf29a975351135",
    "time": "2021-01-27T00:20:50.665Z",
    "type": "completion"
   },
   {
    "id": "f4a2a4c0db4a466b899d078ba3a2b737",
    "time": "2021-01-27T00:20:50.667Z",
    "type": "completion"
   },
   {
    "id": "8066d71185b344e68a5202b5f02658af",
    "time": "2021-01-27T00:20:50.668Z",
    "type": "completion"
   },
   {
    "id": "7a774c9950fa45698183e4228404cda1",
    "time": "2021-01-27T00:20:50.711Z",
    "type": "completion"
   },
   {
    "id": "b7735f14cc444cfcbb9a225e52f32b96",
    "time": "2021-01-27T00:20:50.722Z",
    "type": "completion"
   },
   {
    "id": "718d9ad72a6644f1b0512e6341e4215d",
    "time": "2021-01-27T00:20:50.723Z",
    "type": "completion"
   },
   {
    "id": "3ee93c9b761748559d88a432bffe4673",
    "time": "2021-01-27T00:20:50.724Z",
    "type": "completion"
   },
   {
    "id": "a2c2ec3bf43c4ea88f43267551b13aa5",
    "time": "2021-01-27T00:20:50.724Z",
    "type": "completion"
   },
   {
    "id": "56ac30e5452c43a4b4d6fd823dc946cf",
    "time": "2021-01-27T00:20:50.725Z",
    "type": "completion"
   },
   {
    "id": "ea2b9d6daa7e4c59b21dbedc2bde8446",
    "time": "2021-01-27T00:20:50.725Z",
    "type": "completion"
   },
   {
    "id": "e0de2efc4fa8444b867726348d38bd7c",
    "time": "2021-01-27T00:20:50.726Z",
    "type": "completion"
   },
   {
    "id": "8d5262a6f57449278d48a2d966e7c6a3",
    "time": "2021-01-27T00:20:50.726Z",
    "type": "completion"
   },
   {
    "id": "31b7f32da2bc458f81c5bdc2427308b8",
    "time": "2021-01-27T00:20:50.726Z",
    "type": "completion"
   },
   {
    "id": "59ce187c1c0f425e8d9572e7dc688abf",
    "time": "2021-01-27T00:20:50.727Z",
    "type": "completion"
   },
   {
    "id": "e13eef2bc3684d108942ca0d5772bc3d",
    "time": "2021-01-27T00:20:50.727Z",
    "type": "completion"
   },
   {
    "id": "5caab196d71847da906897524652f0e7",
    "time": "2021-01-27T00:20:50.771Z",
    "type": "completion"
   },
   {
    "id": "1ad96a7a631c410b8001bbd8c1d67709",
    "time": "2021-01-27T00:20:50.778Z",
    "type": "completion"
   },
   {
    "id": "e9bb416227734bad86fbd61e3ae633f3",
    "time": "2021-01-27T00:20:50.779Z",
    "type": "completion"
   },
   {
    "code": "# calculate_score(\"Soul\").plot()\nimport matplotlib.pyplot as plt\n\nfor key in movie_urls.keys():\n#     pd.to_numeric(df.Subs).plot.line()\n    df = all_films[all_films==key]\n    plt.plot(calculate_score(key, all_films), label=key)\n#     plt.plot(np.arange(len(df.index)), pd.to_numeric(df.Total).pct_change(), label = df.Name.values[0], color = colors[i])\n#     plt.axvline(x=30, color='red', linestyle='dashed',linewidth=0.5)\n    plt.ylabel('Percent Change in Subscribers by Day')\n    plt.xlabel(\"Day (0 is 1 month before Content Cop's release)\")\n    plt.legend()\n# plt.annotate('Content Cop released', xy=(30, 0.015), ha='center', size=10)\n# plt.title('The Impact of Content Cop')\n# plt.savefig('pct_cc.svg')",
    "id": "2df2182ab54842498ef70c9d7e8c3931",
    "idx": 9,
    "time": "2021-01-27T00:22:18.205Z",
    "type": "execution"
   },
   {
    "id": "2df2182ab54842498ef70c9d7e8c3931",
    "time": "2021-01-27T00:22:18.970Z",
    "type": "completion"
   },
   {
    "code": "# calculate_score(\"Soul\").plot()\nimport matplotlib.pyplot as plt\n\nfor key in movie_urls.keys():\n#     pd.to_numeric(df.Subs).plot.line()\n    df = all_films[all_films==key]\n    plt.plot(calculate_score(key, all_films), label=key)\n#     plt.plot(np.arange(len(df.index)), pd.to_numeric(df.Total).pct_change(), label = df.Name.values[0], color = colors[i])\n#     plt.axvline(x=30, color='red', linestyle='dashed',linewidth=0.5)\n    plt.ylabel('Percent Change in Subscribers by Day')\n    plt.xlabel(\"Day (0 is 1 month before Content Cop's release)\")\n    plt.legend()\n# plt.annotate('Content Cop released', xy=(30, 0.015), ha='center', size=10)\n# plt.title('The Impact of Content Cop')\n# plt.savefig('pct_cc.svg')",
    "id": "2df2182ab54842498ef70c9d7e8c3931",
    "idx": 9,
    "time": "2021-01-27T00:22:46.286Z",
    "type": "execution"
   },
   {
    "code": "# all_films.to_csv(\"all_films.csv\", index=False)",
    "id": "76def201162a44fe8a10a32d4dc90bc7",
    "idx": 10,
    "time": "2021-01-27T00:22:46.288Z",
    "type": "execution"
   },
   {
    "code": "#add more movies\nimport pandas as pd\n\nmovie_urls['Tenet'] = 'https://www.rottentomatoes.com/m/tenet/'\nmovie_urls['Scoob'] = 'https://www.rottentomatoes.com/m/scoob/'\nmovie_urls['The Marksman'] = 'https://www.rottentomatoes.com/m/the_marksman_2021/'\nmovie_urls['Artemis Fowl'] = 'https://www.rottentomatoes.com/m/artemis_fowl/'\nmovie_urls['Lovebirds'] = 'https://www.rottentomatoes.com/m/the_lovebirds_2020/'\n\nnewkeys = ['Tenet', 'Scoob', 'The Marksman', 'Artemis Fowl', 'Lovebirds']\ndfs = []\n\nfor key in newkeys:\n    print(movie_urls[key])\n    temp = get_critic_reviews(movie_urls[key])\n    df = pd.DataFrame.from_dict(temp)\n    df['Film'] = key\n    dfs.append(df)",
    "id": "61e72b596e6643f891e63bc4132352a6",
    "idx": 11,
    "time": "2021-01-27T00:22:46.289Z",
    "type": "execution"
   },
   {
    "code": "new_films = pd.concat(dfs)\nnew_films",
    "id": "b52a64b1f3904895853d7598c1701442",
    "idx": 12,
    "time": "2021-01-27T00:22:46.290Z",
    "type": "execution"
   },
   {
    "code": "new_films['score'] = new_films['fresh'].apply(lambda x: 1 if x == 'fresh' else 0)\nnew_films",
    "id": "df0b0a25c2ea4dada89c360d5362812e",
    "idx": 13,
    "time": "2021-01-27T00:22:46.291Z",
    "type": "execution"
   },
   {
    "code": "new_films['date'] = pd.to_datetime(new_films['date'], format=\"%B %d, %Y\")\nnew_films = new_films.sort_values('date')",
    "id": "552d587e0007467ca1d99c4d87464486",
    "idx": 14,
    "time": "2021-01-27T00:22:46.292Z",
    "type": "execution"
   },
   {
    "code": "new_films",
    "id": "17ed9fbe70db4d6ab3dbb8e037efef5b",
    "idx": 15,
    "time": "2021-01-27T00:22:46.293Z",
    "type": "execution"
   },
   {
    "code": "import matplotlib.pyplot as plt\n\nfor key in newkeys:\n#     pd.to_numeric(df.Subs).plot.line()\n    df = new_films[new_films==key]\n    plt.plot(calculate_score(key, new_films), label=key)\n#     plt.plot(np.arange(len(df.index)), pd.to_numeric(df.Total).pct_change(), label = df.Name.values[0], color = colors[i])\n#     plt.axvline(x=30, color='red', linestyle='dashed',linewidth=0.5)\n    plt.ylabel('Percent Change in Subscribers by Day')\n    plt.xlabel(\"Day (0 is 1 month before Content Cop's release)\")\n    plt.legend()",
    "id": "4c6477ce81f24006b86f338b7f371f92",
    "idx": 16,
    "time": "2021-01-27T00:22:46.294Z",
    "type": "execution"
   },
   {
    "code": "all_films = pd.read_csv(\"all_films.csv\")\nall_films",
    "id": "b5c21d498b654dbb86b5539a331743e9",
    "idx": 17,
    "time": "2021-01-27T00:22:46.295Z",
    "type": "execution"
   },
   {
    "code": "all_films = pd.concat([all_films, new_films])",
    "id": "2de1ff824f4b4a5a8a28a100b4694d6f",
    "idx": 18,
    "time": "2021-01-27T00:22:46.296Z",
    "type": "execution"
   },
   {
    "code": "all_films['date'] = pd.to_datetime(all_films['date'])\nall_films = all_films.sort_values('date')",
    "id": "c3b00c043c2c46938aaf29a975351135",
    "idx": 19,
    "time": "2021-01-27T00:22:46.298Z",
    "type": "execution"
   },
   {
    "code": "for key in movie_urls.keys():\n#     pd.to_numeric(df.Subs).plot.line()\n    df = all_films[all_films==key]\n    plt.plot(calculate_score(key, all_films), label=key)\n#     plt.plot(np.arange(len(df.index)), pd.to_numeric(df.Total).pct_change(), label = df.Name.values[0], color = colors[i])\n#     plt.axvline(x=30, color='red', linestyle='dashed',linewidth=0.5)\n    plt.ylabel('Percent Change in Subscribers by Day')\n    plt.xlabel(\"Day (0 is 1 month before Content Cop's release)\")\n    plt.legend()\n# plt.annotate('Content Cop released', xy=(30, 0.015), ha='center', size=10)\n# plt.title('The Impact of Content Cop')\n# plt.savefig('pct_cc.svg')",
    "id": "f4a2a4c0db4a466b899d078ba3a2b737",
    "idx": 20,
    "time": "2021-01-27T00:22:46.299Z",
    "type": "execution"
   },
   {
    "code": "%config InlineBackend.figure_format = 'svg'",
    "id": "8066d71185b344e68a5202b5f02658af",
    "idx": 21,
    "time": "2021-01-27T00:22:46.300Z",
    "type": "execution"
   },
   {
    "code": "def plot_film(film):\n    df = all_films[all_films==film]\n    series = calculate_score(film, all_films)\n    plt.plot(series)\n    plt.axhline(y=0.75, color='yellow', linestyle='dashed',linewidth=0.5)\n    plt.axhline(y=0.6, color='red', linestyle='dashed',linewidth=0.5)\n    plt.axhspan(0.75, 1, alpha=0.5, color='lightgreen')\n    plt.axhspan(0.6,.75, alpha=0.5, color='#F6F7A8')\n    plt.axhspan(0, 0.6, alpha=0.5, color='salmon')\n    plt.ylim(series.min(), series.max())\n    plt.xticks(rotation=45, ha=\"right\")\n    plt.title(film + \" Rotten Tomatoes Score over Time\")",
    "id": "7a774c9950fa45698183e4228404cda1",
    "idx": 22,
    "time": "2021-01-27T00:22:46.302Z",
    "type": "execution"
   },
   {
    "code": "# calculate_score(\"Artemis Fowl\",all_films)\nplot_film(\"Artemis Fowl\")",
    "id": "b7735f14cc444cfcbb9a225e52f32b96",
    "idx": 23,
    "time": "2021-01-27T00:22:46.303Z",
    "type": "execution"
   },
   {
    "code": "# calculate_score(\"Wonder Woman 1984\",all_films).plot()\nplot_film(\"Wonder Woman 1984\")",
    "id": "718d9ad72a6644f1b0512e6341e4215d",
    "idx": 24,
    "time": "2021-01-27T00:22:46.304Z",
    "type": "execution"
   },
   {
    "code": "# calculate_score(\"Mulan\",all_films).plot()\nplot_film(\"Mulan\")",
    "id": "3ee93c9b761748559d88a432bffe4673",
    "idx": 25,
    "time": "2021-01-27T00:22:46.305Z",
    "type": "execution"
   },
   {
    "code": "# calculate_score(\"Tenet\",all_films).plot()\nplot_film(\"Tenet\")",
    "id": "a2c2ec3bf43c4ea88f43267551b13aa5",
    "idx": 26,
    "time": "2021-01-27T00:22:46.306Z",
    "type": "execution"
   },
   {
    "code": "plot_film(\"Lovebirds\")",
    "id": "56ac30e5452c43a4b4d6fd823dc946cf",
    "idx": 27,
    "time": "2021-01-27T00:22:46.307Z",
    "type": "execution"
   },
   {
    "code": "movie_urls.keys()",
    "id": "ea2b9d6daa7e4c59b21dbedc2bde8446",
    "idx": 28,
    "time": "2021-01-27T00:22:46.308Z",
    "type": "execution"
   },
   {
    "code": "plot_film(\"Scoob\")",
    "id": "e0de2efc4fa8444b867726348d38bd7c",
    "idx": 29,
    "time": "2021-01-27T00:22:46.309Z",
    "type": "execution"
   },
   {
    "code": "plot_film(\"Birds of Prey\")",
    "id": "8d5262a6f57449278d48a2d966e7c6a3",
    "idx": 30,
    "time": "2021-01-27T00:22:46.310Z",
    "type": "execution"
   },
   {
    "code": "plot_film(\"The Marksman\")",
    "id": "31b7f32da2bc458f81c5bdc2427308b8",
    "idx": 31,
    "time": "2021-01-27T00:22:46.311Z",
    "type": "execution"
   },
   {
    "code": "# all_films.to_csv(\"new_films.csv\",index=False)",
    "id": "59ce187c1c0f425e8d9572e7dc688abf",
    "idx": 32,
    "time": "2021-01-27T00:22:46.313Z",
    "type": "execution"
   },
   {
    "code": "movie_urls.keys()",
    "id": "e13eef2bc3684d108942ca0d5772bc3d",
    "idx": 33,
    "time": "2021-01-27T00:22:46.314Z",
    "type": "execution"
   },
   {
    "code": "plot_film(\"Sonic\")",
    "id": "5caab196d71847da906897524652f0e7",
    "idx": 34,
    "time": "2021-01-27T00:22:46.315Z",
    "type": "execution"
   },
   {
    "code": "all_films[(all_films[\"Film\"]==\"Sonic\") & (all_films[\"date\"]==\"2020-02-12\")]",
    "id": "1ad96a7a631c410b8001bbd8c1d67709",
    "idx": 35,
    "time": "2021-01-27T00:22:46.316Z",
    "type": "execution"
   },
   {
    "code": "plot_film(\"Aladdin\")",
    "id": "e9bb416227734bad86fbd61e3ae633f3",
    "idx": 36,
    "time": "2021-01-27T00:22:46.317Z",
    "type": "execution"
   },
   {
    "id": "2df2182ab54842498ef70c9d7e8c3931",
    "time": "2021-01-27T00:22:47.047Z",
    "type": "completion"
   },
   {
    "id": "76def201162a44fe8a10a32d4dc90bc7",
    "time": "2021-01-27T00:22:47.050Z",
    "type": "completion"
   },
   {
    "code": "plot_film(\"Lion King\")",
    "id": "24b777062e10408c86259b80b25a5ac4",
    "idx": 37,
    "time": "2021-01-27T00:22:55.588Z",
    "type": "execution"
   },
   {
    "code": "plot_film(\"Captain Marvel\")",
    "id": "c5f5b6e95e54463fa76c7144cf506bc1",
    "idx": 38,
    "time": "2021-01-27T00:23:03.027Z",
    "type": "execution"
   },
   {
    "code": "plot_film(\"Godzilla: King of the Monsters\")",
    "id": "69e596d25de54f13a7ceaec498b8d0ee",
    "idx": 39,
    "time": "2021-01-27T00:23:11.664Z",
    "type": "execution"
   },
   {
    "id": "61e72b596e6643f891e63bc4132352a6",
    "time": "2021-01-27T00:23:20.795Z",
    "type": "completion"
   },
   {
    "id": "b52a64b1f3904895853d7598c1701442",
    "time": "2021-01-27T00:23:20.843Z",
    "type": "completion"
   },
   {
    "id": "df0b0a25c2ea4dada89c360d5362812e",
    "time": "2021-01-27T00:23:20.880Z",
    "type": "completion"
   },
   {
    "id": "552d587e0007467ca1d99c4d87464486",
    "time": "2021-01-27T00:23:20.888Z",
    "type": "completion"
   },
   {
    "id": "17ed9fbe70db4d6ab3dbb8e037efef5b",
    "time": "2021-01-27T00:23:20.919Z",
    "type": "completion"
   },
   {
    "code": "plot_film(\"Joker\")",
    "id": "bdb5d1b166fb44a18595353b2786f00c",
    "idx": 40,
    "time": "2021-01-27T00:23:21.065Z",
    "type": "execution"
   },
   {
    "id": "4c6477ce81f24006b86f338b7f371f92",
    "time": "2021-01-27T00:23:21.270Z",
    "type": "completion"
   },
   {
    "id": "b5c21d498b654dbb86b5539a331743e9",
    "time": "2021-01-27T00:23:21.273Z",
    "type": "completion"
   },
   {
    "id": "2de1ff824f4b4a5a8a28a100b4694d6f",
    "time": "2021-01-27T00:23:21.306Z",
    "type": "completion"
   },
   {
    "id": "c3b00c043c2c46938aaf29a975351135",
    "time": "2021-01-27T00:23:21.308Z",
    "type": "completion"
   },
   {
    "id": "f4a2a4c0db4a466b899d078ba3a2b737",
    "time": "2021-01-27T00:23:22.180Z",
    "type": "completion"
   },
   {
    "id": "8066d71185b344e68a5202b5f02658af",
    "time": "2021-01-27T00:23:22.182Z",
    "type": "completion"
   },
   {
    "id": "7a774c9950fa45698183e4228404cda1",
    "time": "2021-01-27T00:23:22.189Z",
    "type": "completion"
   },
   {
    "id": "b7735f14cc444cfcbb9a225e52f32b96",
    "time": "2021-01-27T00:23:22.651Z",
    "type": "completion"
   },
   {
    "id": "718d9ad72a6644f1b0512e6341e4215d",
    "time": "2021-01-27T00:23:22.669Z",
    "type": "completion"
   },
   {
    "id": "3ee93c9b761748559d88a432bffe4673",
    "time": "2021-01-27T00:23:23.198Z",
    "type": "completion"
   },
   {
    "id": "a2c2ec3bf43c4ea88f43267551b13aa5",
    "time": "2021-01-27T00:23:23.226Z",
    "type": "completion"
   },
   {
    "id": "56ac30e5452c43a4b4d6fd823dc946cf",
    "time": "2021-01-27T00:23:23.381Z",
    "type": "completion"
   },
   {
    "id": "ea2b9d6daa7e4c59b21dbedc2bde8446",
    "time": "2021-01-27T00:23:23.384Z",
    "type": "completion"
   },
   {
    "id": "e0de2efc4fa8444b867726348d38bd7c",
    "time": "2021-01-27T00:23:23.811Z",
    "type": "completion"
   },
   {
    "id": "8d5262a6f57449278d48a2d966e7c6a3",
    "time": "2021-01-27T00:23:24.138Z",
    "type": "completion"
   },
   {
    "id": "31b7f32da2bc458f81c5bdc2427308b8",
    "time": "2021-01-27T00:23:24.144Z",
    "type": "completion"
   },
   {
    "id": "59ce187c1c0f425e8d9572e7dc688abf",
    "time": "2021-01-27T00:23:24.349Z",
    "type": "completion"
   },
   {
    "id": "e13eef2bc3684d108942ca0d5772bc3d",
    "time": "2021-01-27T00:23:24.352Z",
    "type": "completion"
   },
   {
    "id": "5caab196d71847da906897524652f0e7",
    "time": "2021-01-27T00:23:24.385Z",
    "type": "completion"
   },
   {
    "id": "1ad96a7a631c410b8001bbd8c1d67709",
    "time": "2021-01-27T00:23:24.619Z",
    "type": "completion"
   },
   {
    "id": "e9bb416227734bad86fbd61e3ae633f3",
    "time": "2021-01-27T00:23:24.710Z",
    "type": "completion"
   },
   {
    "id": "24b777062e10408c86259b80b25a5ac4",
    "time": "2021-01-27T00:23:24.712Z",
    "type": "completion"
   },
   {
    "id": "c5f5b6e95e54463fa76c7144cf506bc1",
    "time": "2021-01-27T00:23:24.713Z",
    "type": "completion"
   },
   {
    "id": "69e596d25de54f13a7ceaec498b8d0ee",
    "time": "2021-01-27T00:23:24.713Z",
    "type": "completion"
   },
   {
    "id": "bdb5d1b166fb44a18595353b2786f00c",
    "time": "2021-01-27T00:23:24.713Z",
    "type": "completion"
   },
   {
    "code": "plot_film(\"Shazam!\")",
    "id": "bcfc5970b6ac4539875b98b4e37650c0",
    "idx": 41,
    "time": "2021-01-27T00:23:28.974Z",
    "type": "execution"
   },
   {
    "id": "bcfc5970b6ac4539875b98b4e37650c0",
    "time": "2021-01-27T00:23:29.600Z",
    "type": "completion"
   },
   {
    "code": "plot_film(\"Lion King\")",
    "id": "24b777062e10408c86259b80b25a5ac4",
    "idx": 37,
    "time": "2021-01-27T00:24:00.233Z",
    "type": "execution"
   },
   {
    "code": "plot_film(\"Captain Marvel\")",
    "id": "c5f5b6e95e54463fa76c7144cf506bc1",
    "idx": 38,
    "time": "2021-01-27T00:24:00.599Z",
    "type": "execution"
   },
   {
    "id": "24b777062e10408c86259b80b25a5ac4",
    "time": "2021-01-27T00:24:00.900Z",
    "type": "completion"
   },
   {
    "id": "c5f5b6e95e54463fa76c7144cf506bc1",
    "time": "2021-01-27T00:24:00.918Z",
    "type": "completion"
   },
   {
    "code": "def plot_film(film):\n    df = all_films[all_films==film]\n    series = calculate_score(film, all_films)\n    plt.plot(series)\n    plt.axhline(y=0.75, color='yellow', linestyle='dashed',linewidth=0.5)\n    plt.axhline(y=0.6, color='red', linestyle='dashed',linewidth=0.5)\n    plt.axhspan(0.75, 1, alpha=0.5, color='lightgreen')\n    plt.axhspan(0.6,.75, alpha=0.5, color='#F6F7A8')\n    plt.axhspan(0, 0.6, alpha=0.5, color='salmon')\n    print(series)\n    plt.ylim(series.min(), series.max())\n    plt.xticks(rotation=45, ha=\"right\")\n    plt.title(film + \" Rotten Tomatoes Score over Time\")",
    "id": "7a774c9950fa45698183e4228404cda1",
    "idx": 22,
    "time": "2021-01-27T00:24:21.714Z",
    "type": "execution"
   },
   {
    "id": "7a774c9950fa45698183e4228404cda1",
    "time": "2021-01-27T00:24:21.787Z",
    "type": "completion"
   },
   {
    "code": "plot_film(\"Aladdin\")",
    "id": "e9bb416227734bad86fbd61e3ae633f3",
    "idx": 36,
    "time": "2021-01-27T00:24:29.231Z",
    "type": "execution"
   },
   {
    "id": "e9bb416227734bad86fbd61e3ae633f3",
    "time": "2021-01-27T00:24:29.589Z",
    "type": "completion"
   },
   {
    "code": "# all_films.to_csv(\"all_films.csv\", index=False)\nall_films = pd.concat(dfs)\nall_films['score'] = all_films['fresh'].apply(lambda x: 1 if x == 'fresh' else 0)\nall_films['date'] = pd.to_datetime(all_films['date'], format=\"%B %d, %Y\")",
    "id": "76def201162a44fe8a10a32d4dc90bc7",
    "idx": 10,
    "time": "2021-01-27T00:26:10.934Z",
    "type": "execution"
   },
   {
    "id": "76def201162a44fe8a10a32d4dc90bc7",
    "time": "2021-01-27T00:26:11.040Z",
    "type": "completion"
   },
   {
    "code": "plot_film(\"Aladdin\")",
    "id": "e9bb416227734bad86fbd61e3ae633f3",
    "idx": 36,
    "time": "2021-01-27T00:26:14.897Z",
    "type": "execution"
   },
   {
    "id": "e9bb416227734bad86fbd61e3ae633f3",
    "time": "2021-01-27T00:26:15.420Z",
    "type": "completion"
   },
   {
    "code": "all_films",
    "id": "9e15cee6f0f3427388f15a9be4260c41",
    "idx": 36,
    "time": "2021-01-27T00:26:31.217Z",
    "type": "execution"
   },
   {
    "id": "9e15cee6f0f3427388f15a9be4260c41",
    "time": "2021-01-27T00:26:31.348Z",
    "type": "completion"
   },
   {
    "code": "dfs",
    "id": "9e15cee6f0f3427388f15a9be4260c41",
    "idx": 36,
    "time": "2021-01-27T00:26:36.620Z",
    "type": "execution"
   },
   {
    "id": "9e15cee6f0f3427388f15a9be4260c41",
    "time": "2021-01-27T00:26:36.811Z",
    "type": "completion"
   },
   {
    "code": "import requests\nimport time\n\n# requirements\nfrom bs4 import BeautifulSoup\nfrom requests import TooManyRedirects\nimport re\n\ndef _make_soup(url):\n    try:\n        r = requests.get(url)\n        soup = BeautifulSoup(r.content, 'html.parser')\n    except TooManyRedirects:\n        soup = ''\n    return soup\n\n#regex patterns\npage_pat = re.compile(r'Page 1 of \\d+')\nreview_pat = re.compile(r'<div class=\\\"the_review\\\" data-qa=\\\"review-text\\\">[;a-zA-Z\\s,-.\\'\\/\\?\\[\\]\\\":\\']*</div>')\nrating_pat = re.compile(r'Original Score:\\s([A-Z](\\+|-)?|\\d(.\\d)?(\\/\\d)?)')\nfresh_pat = re.compile(r'small\\s(fresh|rotten)\\\"')\ncritic_pat = re.compile(r'\\/\\\"\\>([A-Z][a-zA-Z]+\\s[A-Z][a-zA-Z\\-]+)|([A-Z][a-zA-Z.]+\\s[A-Z].?\\s[A-Z][a-zA-Z]+)|([A-Z][a-zA-Z]+\\s[A-Z]+\\'[A-Z][a-zA-Z]+)')\npublisher_pat = re.compile(r'\\\"subtle\\\">[a-zA-Z\\s,.\\(\\)\\'\\-&;!\\/\\d+]+</em>')\ndate_pat = re.compile(r'[a-zA-Z]+\\s\\d+,\\s\\d+')",
    "id": "c088557172df4ee88340993c0d83f871",
    "idx": 0,
    "time": "2021-01-27T00:27:53.270Z",
    "type": "execution"
   },
   {
    "code": "def _get_critic_reviews_from_page(soup):\n    reviews = list()\n    rating = list()\n    fresh = list()\n    critic = list()\n    top_critic = list()\n    publisher = list()\n    date = list()\n    \n    soup = str(soup)\n    review_soup = soup.split('=\"review_table')[1].split('row review_table_row')\n    review_soup.pop(0)\n\n    for review in review_soup:\n        match = re.findall(review_pat, str(review))\n        if len(match) > 0:\n            m = match[0]            \n            for iden in ['<div class=\"the_review\" data-qa=\"review-text\"> ','</div>']:\n                m = m.replace(iden,'')\n            reviews.append(m.strip('\"'))            \n            # extract rating\n            match = re.findall(rating_pat, str(review))\n            if len(match) > 0:\n                m = match[0][0]\n                if '/1' in m:\n                    sp_m = m.split('/')\n                    if sp_m[-1] == '1':\n                        sp_m[-1] = '10'\n                    m = '/'.join(sp_m)\n                rating.append(m)\n            else:\n                rating.append(None)            \n            # extract fresh indicator\n            match = re.findall(fresh_pat, str(review))\n            if len(match) > 0:\n                fresh.append(match[0])\n            else:\n                fresh.append(None)            \n            # extract critic\n            match = re.findall(critic_pat, str(review))\n            if len(match) > 0:\n                critic.append(''.join(match[0]))\n            else:\n                critic.append(None)            \n            # check if top critic\n            if '> Top Critic<' in str(review):\n                top_critic.append(1)\n            else:\n                top_critic.append(0)            \n            # extract publisher\n            match = re.findall(publisher_pat, str(review))\n            if len(match) > 0:\n                m = match[0]\n                m = m.replace('\"subtle\">', '')\n                m = m.replace('</em>','')\n                publisher.append(m)\n            else:\n                publisher.append(None)            \n            # extract date\n            match = re.findall(date_pat, str(review))\n            if len(match) > 0:\n                date.append(match[0].strip('\"'))\n            else:\n                date.append(None)\n            \n    return [reviews, rating, fresh, critic, top_critic, publisher, date]\n\ndef _get_num_pages(soup):\n    match = re.findall(page_pat,str(list(soup)))\n    if len(match) > 0:\n        match = match[0]\n        match = match.split(' of ')[-1]\n        return match\n    else:\n        return None",
    "id": "473f70b9197047778ba396a40a4ed7a7",
    "idx": 1,
    "time": "2021-01-27T00:27:53.275Z",
    "type": "execution"
   },
   {
    "code": "def get_critic_reviews(page):\n    info = [[],[],[],[],[],[],[]]\n    soup = _make_soup(page + \"reviews\")\n#     print(soup)\n    pages = _get_num_pages(soup)\n#     print(pages)\n    if pages is not None:\n        for page_num in range(1,int(pages)+1):\n            soup = _make_soup(page + \"reviews?page=\" + str(page_num) + \"&sort=\")\n            c_info = _get_critic_reviews_from_page(soup)\n            \n            # accumulate review info\n            for i in range(len(c_info)):\n                info[i] = info[i] + c_info[i]\n        \n        c_info = dict()\n        keys = ['reviews', 'rating', 'fresh', 'critic', 'top_critic', 'publisher', 'date']\n        for k in range(len(keys)):\n            c_info[keys[k]] = info[k]        \n    else:\n        c_info = None        \n    return c_info",
    "id": "2a164d4bc03440c287cd2aa9baee929e",
    "idx": 2,
    "time": "2021-01-27T00:27:53.277Z",
    "type": "execution"
   },
   {
    "code": "movie_urls = {'Wonder Woman 1984': 'https://www.rottentomatoes.com/m/wonder_woman_1984/', \n              'Soul':'https://www.rottentomatoes.com/m/soul_2020/', \n              'Mulan': 'https://www.rottentomatoes.com/m/mulan_2020/',\n              'Birds of Prey': 'https://www.rottentomatoes.com/m/birds_of_prey_2020/',\n              'Sonic': 'https://www.rottentomatoes.com/m/sonic_the_hedgehog_2020/'\n             }\n\nmovie_urls[\"Captain Marvel\"] = \"https://www.rottentomatoes.com/m/captain_marvel/\"\nmovie_urls[\"Lion King\"] = \"https://www.rottentomatoes.com/m/the_lion_king_2019/\"\nmovie_urls[\"Aladdin\"] = \"https://www.rottentomatoes.com/m/aladdin/\"\nmovie_urls[\"Joker\"] = \"https://www.rottentomatoes.com/m/joker_2019/\"\nmovie_urls[\"Shazam!\"] = \"https://www.rottentomatoes.com/m/shazam/\"\nmovie_urls[\"Godzilla: King of the Monsters\"] = \"https://www.rottentomatoes.com/m/godzilla_king_of_the_monsters_2019/\"\n\nmovie_urls['Tenet'] = 'https://www.rottentomatoes.com/m/tenet/'\nmovie_urls['Scoob'] = 'https://www.rottentomatoes.com/m/scoob/'\nmovie_urls['The Marksman'] = 'https://www.rottentomatoes.com/m/the_marksman_2021/'\nmovie_urls['Artemis Fowl'] = 'https://www.rottentomatoes.com/m/artemis_fowl/'\nmovie_urls['Lovebirds'] = 'https://www.rottentomatoes.com/m/the_lovebirds_2020/'\n\nmovie_urls.keys()",
    "id": "ba75f81eae0c43879ade708c52166e21",
    "idx": 3,
    "time": "2021-01-27T00:27:53.279Z",
    "type": "execution"
   },
   {
    "code": "import pandas as pd\n\ndfs = []\nfor key in movie_urls.keys():\n    temp = get_critic_reviews(movie_urls[key])\n    df = pd.DataFrame.from_dict(temp)\n    df['Film'] = key\n    dfs.append(df)",
    "id": "a1ef4cd89f0f41c8a9233b92ab030587",
    "idx": 4,
    "time": "2021-01-27T00:27:53.280Z",
    "type": "execution"
   },
   {
    "code": "all_films = pd.concat(dfs)\nall_films",
    "id": "0ef9e93206b741ab896dda73e440fe69",
    "idx": 5,
    "time": "2021-01-27T00:27:53.282Z",
    "type": "execution"
   },
   {
    "code": "all_films['score'] = all_films['fresh'].apply(lambda x: 1 if x == 'fresh' else 0)\nall_films",
    "id": "bd3af87003f34f009f0f49e7c7cea343",
    "idx": 6,
    "time": "2021-01-27T00:27:53.284Z",
    "type": "execution"
   },
   {
    "code": "all_films['date'] = pd.to_datetime(all_films['date'], format=\"%B %d, %Y\")\nall_films = all_films.sort_values('date')",
    "id": "59dcb1b5e4a6427482402c1d1c927436",
    "idx": 7,
    "time": "2021-01-27T00:27:53.286Z",
    "type": "execution"
   },
   {
    "code": "import numpy as np\n\n\ndef calculate_score(film, frame):\n    df = frame[frame['Film'] == film]\n    grouped_1 = df[['date', 'score']].groupby('date').agg([sum, 'count'])\n    grouped_1.columns = grouped_1.columns.droplevel(0)\n    return grouped_1.cumsum()['sum']/grouped_1.cumsum()['count']\n\ncalculate_score(\"Wonder Woman 1984\", all_films)",
    "id": "5e1cead1642b4c288daa8723c29a17c1",
    "idx": 8,
    "time": "2021-01-27T00:27:53.288Z",
    "type": "execution"
   },
   {
    "code": "# calculate_score(\"Soul\").plot()\nimport matplotlib.pyplot as plt\n\nfor key in movie_urls.keys():\n#     pd.to_numeric(df.Subs).plot.line()\n    df = all_films[all_films==key]\n    plt.plot(calculate_score(key, all_films), label=key)\n#     plt.plot(np.arange(len(df.index)), pd.to_numeric(df.Total).pct_change(), label = df.Name.values[0], color = colors[i])\n#     plt.axvline(x=30, color='red', linestyle='dashed',linewidth=0.5)\n    plt.ylabel('Percent Change in Subscribers by Day')\n    plt.xlabel(\"Day (0 is 1 month before Content Cop's release)\")\n    plt.legend()\n# plt.annotate('Content Cop released', xy=(30, 0.015), ha='center', size=10)\n# plt.title('The Impact of Content Cop')\n# plt.savefig('pct_cc.svg')",
    "id": "2df2182ab54842498ef70c9d7e8c3931",
    "idx": 9,
    "time": "2021-01-27T00:27:53.289Z",
    "type": "execution"
   },
   {
    "code": "# all_films.to_csv(\"all_films.csv\", index=False)\nall_films = pd.concat(dfs)\nall_films['score'] = all_films['fresh'].apply(lambda x: 1 if x == 'fresh' else 0)\nall_films['date'] = pd.to_datetime(all_films['date'], format=\"%B %d, %Y\")",
    "id": "76def201162a44fe8a10a32d4dc90bc7",
    "idx": 10,
    "time": "2021-01-27T00:27:53.291Z",
    "type": "execution"
   },
   {
    "code": "# all_films = pd.read_csv(\"all_films.csv\")\nall_films",
    "id": "b5c21d498b654dbb86b5539a331743e9",
    "idx": 11,
    "time": "2021-01-27T00:27:53.293Z",
    "type": "execution"
   },
   {
    "code": "all_films = pd.concat([all_films, new_films])",
    "id": "2de1ff824f4b4a5a8a28a100b4694d6f",
    "idx": 12,
    "time": "2021-01-27T00:27:53.294Z",
    "type": "execution"
   },
   {
    "code": "all_films['date'] = pd.to_datetime(all_films['date'])\nall_films = all_films.sort_values('date')",
    "id": "c3b00c043c2c46938aaf29a975351135",
    "idx": 13,
    "time": "2021-01-27T00:27:53.296Z",
    "type": "execution"
   },
   {
    "code": "for key in movie_urls.keys():\n#     pd.to_numeric(df.Subs).plot.line()\n    df = all_films[all_films==key]\n    plt.plot(calculate_score(key, all_films), label=key)\n#     plt.plot(np.arange(len(df.index)), pd.to_numeric(df.Total).pct_change(), label = df.Name.values[0], color = colors[i])\n#     plt.axvline(x=30, color='red', linestyle='dashed',linewidth=0.5)\n    plt.ylabel('Percent Change in Subscribers by Day')\n    plt.xlabel(\"Day (0 is 1 month before Content Cop's release)\")\n    plt.legend()\n# plt.annotate('Content Cop released', xy=(30, 0.015), ha='center', size=10)\n# plt.title('The Impact of Content Cop')\n# plt.savefig('pct_cc.svg')",
    "id": "f4a2a4c0db4a466b899d078ba3a2b737",
    "idx": 14,
    "time": "2021-01-27T00:27:53.298Z",
    "type": "execution"
   },
   {
    "code": "%config InlineBackend.figure_format = 'svg'",
    "id": "8066d71185b344e68a5202b5f02658af",
    "idx": 15,
    "time": "2021-01-27T00:27:53.299Z",
    "type": "execution"
   },
   {
    "code": "def plot_film(film):\n    df = all_films[all_films==film]\n    series = calculate_score(film, all_films)\n    plt.plot(series)\n    plt.axhline(y=0.75, color='yellow', linestyle='dashed',linewidth=0.5)\n    plt.axhline(y=0.6, color='red', linestyle='dashed',linewidth=0.5)\n    plt.axhspan(0.75, 1, alpha=0.5, color='lightgreen')\n    plt.axhspan(0.6,.75, alpha=0.5, color='#F6F7A8')\n    plt.axhspan(0, 0.6, alpha=0.5, color='salmon')\n    print(series)\n    plt.ylim(series.min(), series.max())\n    plt.xticks(rotation=45, ha=\"right\")\n    plt.title(film + \" Rotten Tomatoes Score over Time\")",
    "id": "7a774c9950fa45698183e4228404cda1",
    "idx": 16,
    "time": "2021-01-27T00:27:53.300Z",
    "type": "execution"
   },
   {
    "code": "# calculate_score(\"Artemis Fowl\",all_films)\nplot_film(\"Artemis Fowl\")",
    "id": "b7735f14cc444cfcbb9a225e52f32b96",
    "idx": 17,
    "time": "2021-01-27T00:27:53.303Z",
    "type": "execution"
   },
   {
    "code": "# calculate_score(\"Wonder Woman 1984\",all_films).plot()\nplot_film(\"Wonder Woman 1984\")",
    "id": "718d9ad72a6644f1b0512e6341e4215d",
    "idx": 18,
    "time": "2021-01-27T00:27:53.307Z",
    "type": "execution"
   },
   {
    "code": "# calculate_score(\"Mulan\",all_films).plot()\nplot_film(\"Mulan\")",
    "id": "3ee93c9b761748559d88a432bffe4673",
    "idx": 19,
    "time": "2021-01-27T00:27:53.309Z",
    "type": "execution"
   },
   {
    "code": "# calculate_score(\"Tenet\",all_films).plot()\nplot_film(\"Tenet\")",
    "id": "a2c2ec3bf43c4ea88f43267551b13aa5",
    "idx": 20,
    "time": "2021-01-27T00:27:53.311Z",
    "type": "execution"
   },
   {
    "code": "plot_film(\"Lovebirds\")",
    "id": "56ac30e5452c43a4b4d6fd823dc946cf",
    "idx": 21,
    "time": "2021-01-27T00:27:53.313Z",
    "type": "execution"
   },
   {
    "code": "movie_urls.keys()",
    "id": "ea2b9d6daa7e4c59b21dbedc2bde8446",
    "idx": 22,
    "time": "2021-01-27T00:27:53.315Z",
    "type": "execution"
   },
   {
    "code": "plot_film(\"Scoob\")",
    "id": "e0de2efc4fa8444b867726348d38bd7c",
    "idx": 23,
    "time": "2021-01-27T00:27:53.317Z",
    "type": "execution"
   },
   {
    "code": "plot_film(\"Birds of Prey\")",
    "id": "8d5262a6f57449278d48a2d966e7c6a3",
    "idx": 24,
    "time": "2021-01-27T00:27:53.319Z",
    "type": "execution"
   },
   {
    "code": "plot_film(\"The Marksman\")",
    "id": "31b7f32da2bc458f81c5bdc2427308b8",
    "idx": 25,
    "time": "2021-01-27T00:27:53.322Z",
    "type": "execution"
   },
   {
    "code": "# all_films.to_csv(\"new_films.csv\",index=False)",
    "id": "59ce187c1c0f425e8d9572e7dc688abf",
    "idx": 26,
    "time": "2021-01-27T00:27:53.323Z",
    "type": "execution"
   },
   {
    "code": "movie_urls.keys()",
    "id": "e13eef2bc3684d108942ca0d5772bc3d",
    "idx": 27,
    "time": "2021-01-27T00:27:53.324Z",
    "type": "execution"
   },
   {
    "code": "plot_film(\"Sonic\")",
    "id": "5caab196d71847da906897524652f0e7",
    "idx": 28,
    "time": "2021-01-27T00:27:53.326Z",
    "type": "execution"
   },
   {
    "code": "all_films[(all_films[\"Film\"]==\"Sonic\") & (all_films[\"date\"]==\"2020-02-12\")]",
    "id": "1ad96a7a631c410b8001bbd8c1d67709",
    "idx": 29,
    "time": "2021-01-27T00:27:53.328Z",
    "type": "execution"
   },
   {
    "code": "dfs",
    "id": "9e15cee6f0f3427388f15a9be4260c41",
    "idx": 30,
    "time": "2021-01-27T00:27:53.330Z",
    "type": "execution"
   },
   {
    "code": "plot_film(\"Aladdin\")",
    "id": "e9bb416227734bad86fbd61e3ae633f3",
    "idx": 31,
    "time": "2021-01-27T00:27:53.332Z",
    "type": "execution"
   },
   {
    "code": "plot_film(\"Lion King\")",
    "id": "24b777062e10408c86259b80b25a5ac4",
    "idx": 32,
    "time": "2021-01-27T00:27:53.334Z",
    "type": "execution"
   },
   {
    "code": "plot_film(\"Captain Marvel\")",
    "id": "c5f5b6e95e54463fa76c7144cf506bc1",
    "idx": 33,
    "time": "2021-01-27T00:27:53.336Z",
    "type": "execution"
   },
   {
    "code": "plot_film(\"Godzilla: King of the Monsters\")",
    "id": "69e596d25de54f13a7ceaec498b8d0ee",
    "idx": 34,
    "time": "2021-01-27T00:27:53.337Z",
    "type": "execution"
   },
   {
    "code": "plot_film(\"Joker\")",
    "id": "bdb5d1b166fb44a18595353b2786f00c",
    "idx": 35,
    "time": "2021-01-27T00:27:53.338Z",
    "type": "execution"
   },
   {
    "code": "plot_film(\"Shazam!\")",
    "id": "bcfc5970b6ac4539875b98b4e37650c0",
    "idx": 36,
    "time": "2021-01-27T00:27:53.340Z",
    "type": "execution"
   },
   {
    "id": "c088557172df4ee88340993c0d83f871",
    "time": "2021-01-27T00:27:53.445Z",
    "type": "completion"
   },
   {
    "id": "473f70b9197047778ba396a40a4ed7a7",
    "time": "2021-01-27T00:27:53.447Z",
    "type": "completion"
   },
   {
    "id": "2a164d4bc03440c287cd2aa9baee929e",
    "time": "2021-01-27T00:27:53.456Z",
    "type": "completion"
   },
   {
    "id": "ba75f81eae0c43879ade708c52166e21",
    "time": "2021-01-27T00:27:53.462Z",
    "type": "completion"
   },
   {
    "id": "a1ef4cd89f0f41c8a9233b92ab030587",
    "time": "2021-01-27T00:30:53.739Z",
    "type": "completion"
   },
   {
    "id": "0ef9e93206b741ab896dda73e440fe69",
    "time": "2021-01-27T00:30:53.792Z",
    "type": "completion"
   },
   {
    "id": "bd3af87003f34f009f0f49e7c7cea343",
    "time": "2021-01-27T00:30:53.797Z",
    "type": "completion"
   },
   {
    "id": "59dcb1b5e4a6427482402c1d1c927436",
    "time": "2021-01-27T00:30:53.798Z",
    "type": "completion"
   },
   {
    "id": "5e1cead1642b4c288daa8723c29a17c1",
    "time": "2021-01-27T00:30:53.826Z",
    "type": "completion"
   },
   {
    "id": "2df2182ab54842498ef70c9d7e8c3931",
    "time": "2021-01-27T00:30:54.680Z",
    "type": "completion"
   },
   {
    "id": "76def201162a44fe8a10a32d4dc90bc7",
    "time": "2021-01-27T00:30:54.682Z",
    "type": "completion"
   },
   {
    "id": "b5c21d498b654dbb86b5539a331743e9",
    "time": "2021-01-27T00:30:54.817Z",
    "type": "completion"
   },
   {
    "id": "2de1ff824f4b4a5a8a28a100b4694d6f",
    "time": "2021-01-27T00:30:54.820Z",
    "type": "completion"
   },
   {
    "id": "c3b00c043c2c46938aaf29a975351135",
    "time": "2021-01-27T00:30:54.822Z",
    "type": "completion"
   },
   {
    "id": "f4a2a4c0db4a466b899d078ba3a2b737",
    "time": "2021-01-27T00:30:55.646Z",
    "type": "completion"
   },
   {
    "id": "8066d71185b344e68a5202b5f02658af",
    "time": "2021-01-27T00:30:55.788Z",
    "type": "completion"
   },
   {
    "id": "7a774c9950fa45698183e4228404cda1",
    "time": "2021-01-27T00:30:55.789Z",
    "type": "completion"
   },
   {
    "id": "b7735f14cc444cfcbb9a225e52f32b96",
    "time": "2021-01-27T00:30:55.797Z",
    "type": "completion"
   },
   {
    "id": "718d9ad72a6644f1b0512e6341e4215d",
    "time": "2021-01-27T00:30:56.044Z",
    "type": "completion"
   },
   {
    "id": "3ee93c9b761748559d88a432bffe4673",
    "time": "2021-01-27T00:30:56.204Z",
    "type": "completion"
   },
   {
    "id": "a2c2ec3bf43c4ea88f43267551b13aa5",
    "time": "2021-01-27T00:30:56.402Z",
    "type": "completion"
   },
   {
    "id": "56ac30e5452c43a4b4d6fd823dc946cf",
    "time": "2021-01-27T00:30:56.610Z",
    "type": "completion"
   },
   {
    "id": "ea2b9d6daa7e4c59b21dbedc2bde8446",
    "time": "2021-01-27T00:30:56.612Z",
    "type": "completion"
   },
   {
    "id": "e0de2efc4fa8444b867726348d38bd7c",
    "time": "2021-01-27T00:30:56.841Z",
    "type": "completion"
   },
   {
    "id": "8d5262a6f57449278d48a2d966e7c6a3",
    "time": "2021-01-27T00:30:57.075Z",
    "type": "completion"
   },
   {
    "id": "31b7f32da2bc458f81c5bdc2427308b8",
    "time": "2021-01-27T00:30:57.354Z",
    "type": "completion"
   },
   {
    "id": "59ce187c1c0f425e8d9572e7dc688abf",
    "time": "2021-01-27T00:30:57.355Z",
    "type": "completion"
   },
   {
    "id": "e13eef2bc3684d108942ca0d5772bc3d",
    "time": "2021-01-27T00:30:57.357Z",
    "type": "completion"
   },
   {
    "id": "5caab196d71847da906897524652f0e7",
    "time": "2021-01-27T00:30:57.590Z",
    "type": "completion"
   },
   {
    "id": "1ad96a7a631c410b8001bbd8c1d67709",
    "time": "2021-01-27T00:30:57.596Z",
    "type": "completion"
   },
   {
    "id": "9e15cee6f0f3427388f15a9be4260c41",
    "time": "2021-01-27T00:30:57.867Z",
    "type": "completion"
   },
   {
    "id": "e9bb416227734bad86fbd61e3ae633f3",
    "time": "2021-01-27T00:30:57.920Z",
    "type": "completion"
   },
   {
    "id": "24b777062e10408c86259b80b25a5ac4",
    "time": "2021-01-27T00:30:58.211Z",
    "type": "completion"
   },
   {
    "id": "c5f5b6e95e54463fa76c7144cf506bc1",
    "time": "2021-01-27T00:30:58.506Z",
    "type": "completion"
   },
   {
    "id": "69e596d25de54f13a7ceaec498b8d0ee",
    "time": "2021-01-27T00:30:58.826Z",
    "type": "completion"
   },
   {
    "id": "bdb5d1b166fb44a18595353b2786f00c",
    "time": "2021-01-27T00:30:59.154Z",
    "type": "completion"
   },
   {
    "id": "bcfc5970b6ac4539875b98b4e37650c0",
    "time": "2021-01-27T00:30:59.556Z",
    "type": "completion"
   },
   {
    "code": "def plot_film(film):\n    df = all_films[all_films==film]\n    series = calculate_score(film, all_films)\n    plt.plot(series)\n    plt.axhline(y=0.75, color='yellow', linestyle='dashed',linewidth=0.5)\n    plt.axhline(y=0.6, color='red', linestyle='dashed',linewidth=0.5)\n    plt.axhspan(0.75, 1, alpha=0.5, color='lightgreen')\n    plt.axhspan(0.6,.75, alpha=0.5, color='#F6F7A8')\n    plt.axhspan(0, 0.6, alpha=0.5, color='salmon')\n#     print(series)\n    plt.ylim(series.min(), series.max())\n    plt.xticks(rotation=45, ha=\"right\")\n    plt.title(film + \" Rotten Tomatoes Score over Time\")",
    "id": "7a774c9950fa45698183e4228404cda1",
    "idx": 16,
    "time": "2021-01-27T00:31:18.195Z",
    "type": "execution"
   },
   {
    "id": "7a774c9950fa45698183e4228404cda1",
    "time": "2021-01-27T00:31:18.263Z",
    "type": "completion"
   },
   {
    "code": "def plot_film(film):\n    df = all_films[all_films==film]\n    series = calculate_score(film, all_films)\n    plt.plot(series)\n    plt.axhline(y=0.75, color='yellow', linestyle='dashed',linewidth=0.5)\n    plt.axhline(y=0.6, color='red', linestyle='dashed',linewidth=0.5)\n    plt.axhspan(0.75, 1, alpha=0.5, color='lightgreen')\n    plt.axhspan(0.6,.75, alpha=0.5, color='#F6F7A8')\n    plt.axhspan(0, 0.6, alpha=0.5, color='salmon')\n#     print(series)\n    plt.ylim(series.min(), series.max())\n    plt.xticks(rotation=45, ha=\"right\")\n    plt.title(film + \" Rotten Tomatoes Score over Time\")",
    "id": "7a774c9950fa45698183e4228404cda1",
    "idx": 16,
    "time": "2021-01-27T00:31:22.588Z",
    "type": "execution"
   },
   {
    "code": "# calculate_score(\"Artemis Fowl\",all_films)\nplot_film(\"Artemis Fowl\")",
    "id": "b7735f14cc444cfcbb9a225e52f32b96",
    "idx": 17,
    "time": "2021-01-27T00:31:22.592Z",
    "type": "execution"
   },
   {
    "code": "# calculate_score(\"Wonder Woman 1984\",all_films).plot()\nplot_film(\"Wonder Woman 1984\")",
    "id": "718d9ad72a6644f1b0512e6341e4215d",
    "idx": 18,
    "time": "2021-01-27T00:31:22.597Z",
    "type": "execution"
   },
   {
    "code": "# calculate_score(\"Mulan\",all_films).plot()\nplot_film(\"Mulan\")",
    "id": "3ee93c9b761748559d88a432bffe4673",
    "idx": 19,
    "time": "2021-01-27T00:31:22.600Z",
    "type": "execution"
   },
   {
    "code": "# calculate_score(\"Tenet\",all_films).plot()\nplot_film(\"Tenet\")",
    "id": "a2c2ec3bf43c4ea88f43267551b13aa5",
    "idx": 20,
    "time": "2021-01-27T00:31:22.603Z",
    "type": "execution"
   },
   {
    "code": "plot_film(\"Lovebirds\")",
    "id": "56ac30e5452c43a4b4d6fd823dc946cf",
    "idx": 21,
    "time": "2021-01-27T00:31:22.607Z",
    "type": "execution"
   },
   {
    "code": "movie_urls.keys()",
    "id": "ea2b9d6daa7e4c59b21dbedc2bde8446",
    "idx": 22,
    "time": "2021-01-27T00:31:22.609Z",
    "type": "execution"
   },
   {
    "code": "plot_film(\"Scoob\")",
    "id": "e0de2efc4fa8444b867726348d38bd7c",
    "idx": 23,
    "time": "2021-01-27T00:31:22.612Z",
    "type": "execution"
   },
   {
    "code": "plot_film(\"Birds of Prey\")",
    "id": "8d5262a6f57449278d48a2d966e7c6a3",
    "idx": 24,
    "time": "2021-01-27T00:31:22.615Z",
    "type": "execution"
   },
   {
    "code": "plot_film(\"The Marksman\")",
    "id": "31b7f32da2bc458f81c5bdc2427308b8",
    "idx": 25,
    "time": "2021-01-27T00:31:22.617Z",
    "type": "execution"
   },
   {
    "code": "# all_films.to_csv(\"new_films.csv\",index=False)",
    "id": "59ce187c1c0f425e8d9572e7dc688abf",
    "idx": 26,
    "time": "2021-01-27T00:31:22.618Z",
    "type": "execution"
   },
   {
    "code": "movie_urls.keys()",
    "id": "e13eef2bc3684d108942ca0d5772bc3d",
    "idx": 27,
    "time": "2021-01-27T00:31:22.620Z",
    "type": "execution"
   },
   {
    "code": "plot_film(\"Sonic\")",
    "id": "5caab196d71847da906897524652f0e7",
    "idx": 28,
    "time": "2021-01-27T00:31:22.623Z",
    "type": "execution"
   },
   {
    "code": "all_films[(all_films[\"Film\"]==\"Sonic\") & (all_films[\"date\"]==\"2020-02-12\")]",
    "id": "1ad96a7a631c410b8001bbd8c1d67709",
    "idx": 29,
    "time": "2021-01-27T00:31:22.625Z",
    "type": "execution"
   },
   {
    "code": "dfs",
    "id": "9e15cee6f0f3427388f15a9be4260c41",
    "idx": 30,
    "time": "2021-01-27T00:31:22.627Z",
    "type": "execution"
   },
   {
    "code": "plot_film(\"Aladdin\")",
    "id": "e9bb416227734bad86fbd61e3ae633f3",
    "idx": 31,
    "time": "2021-01-27T00:31:22.629Z",
    "type": "execution"
   },
   {
    "code": "plot_film(\"Lion King\")",
    "id": "24b777062e10408c86259b80b25a5ac4",
    "idx": 32,
    "time": "2021-01-27T00:31:22.632Z",
    "type": "execution"
   },
   {
    "code": "plot_film(\"Captain Marvel\")",
    "id": "c5f5b6e95e54463fa76c7144cf506bc1",
    "idx": 33,
    "time": "2021-01-27T00:31:22.636Z",
    "type": "execution"
   },
   {
    "code": "plot_film(\"Godzilla: King of the Monsters\")",
    "id": "69e596d25de54f13a7ceaec498b8d0ee",
    "idx": 34,
    "time": "2021-01-27T00:31:22.639Z",
    "type": "execution"
   },
   {
    "code": "plot_film(\"Joker\")",
    "id": "bdb5d1b166fb44a18595353b2786f00c",
    "idx": 35,
    "time": "2021-01-27T00:31:22.642Z",
    "type": "execution"
   },
   {
    "code": "plot_film(\"Shazam!\")",
    "id": "bcfc5970b6ac4539875b98b4e37650c0",
    "idx": 36,
    "time": "2021-01-27T00:31:22.645Z",
    "type": "execution"
   },
   {
    "id": "7a774c9950fa45698183e4228404cda1",
    "time": "2021-01-27T00:31:22.874Z",
    "type": "completion"
   },
   {
    "id": "b7735f14cc444cfcbb9a225e52f32b96",
    "time": "2021-01-27T00:31:22.903Z",
    "type": "completion"
   },
   {
    "id": "718d9ad72a6644f1b0512e6341e4215d",
    "time": "2021-01-27T00:31:23.334Z",
    "type": "completion"
   },
   {
    "id": "3ee93c9b761748559d88a432bffe4673",
    "time": "2021-01-27T00:31:23.343Z",
    "type": "completion"
   },
   {
    "id": "a2c2ec3bf43c4ea88f43267551b13aa5",
    "time": "2021-01-27T00:31:23.813Z",
    "type": "completion"
   },
   {
    "id": "56ac30e5452c43a4b4d6fd823dc946cf",
    "time": "2021-01-27T00:31:24.129Z",
    "type": "completion"
   },
   {
    "id": "ea2b9d6daa7e4c59b21dbedc2bde8446",
    "time": "2021-01-27T00:31:24.134Z",
    "type": "completion"
   },
   {
    "id": "e0de2efc4fa8444b867726348d38bd7c",
    "time": "2021-01-27T00:31:24.164Z",
    "type": "completion"
   },
   {
    "id": "8d5262a6f57449278d48a2d966e7c6a3",
    "time": "2021-01-27T00:31:24.371Z",
    "type": "completion"
   },
   {
    "id": "31b7f32da2bc458f81c5bdc2427308b8",
    "time": "2021-01-27T00:31:24.877Z",
    "type": "completion"
   },
   {
    "id": "59ce187c1c0f425e8d9572e7dc688abf",
    "time": "2021-01-27T00:31:24.880Z",
    "type": "completion"
   },
   {
    "id": "e13eef2bc3684d108942ca0d5772bc3d",
    "time": "2021-01-27T00:31:24.882Z",
    "type": "completion"
   },
   {
    "id": "5caab196d71847da906897524652f0e7",
    "time": "2021-01-27T00:31:24.889Z",
    "type": "completion"
   },
   {
    "id": "1ad96a7a631c410b8001bbd8c1d67709",
    "time": "2021-01-27T00:31:24.898Z",
    "type": "completion"
   },
   {
    "id": "9e15cee6f0f3427388f15a9be4260c41",
    "time": "2021-01-27T00:31:25.156Z",
    "type": "completion"
   },
   {
    "id": "e9bb416227734bad86fbd61e3ae633f3",
    "time": "2021-01-27T00:31:25.438Z",
    "type": "completion"
   },
   {
    "id": "24b777062e10408c86259b80b25a5ac4",
    "time": "2021-01-27T00:31:25.682Z",
    "type": "completion"
   },
   {
    "id": "c5f5b6e95e54463fa76c7144cf506bc1",
    "time": "2021-01-27T00:31:26.229Z",
    "type": "completion"
   },
   {
    "id": "69e596d25de54f13a7ceaec498b8d0ee",
    "time": "2021-01-27T00:31:26.258Z",
    "type": "completion"
   },
   {
    "id": "bdb5d1b166fb44a18595353b2786f00c",
    "time": "2021-01-27T00:31:26.584Z",
    "type": "completion"
   },
   {
    "id": "bcfc5970b6ac4539875b98b4e37650c0",
    "time": "2021-01-27T00:31:26.923Z",
    "type": "completion"
   },
   {
    "code": "#add films\nnewkeys = [\"The Last Jedi\"]\nmovie_urls[\"The Last Jedi\"] = \"https://www.rottentomatoes.com/m/star_wars_the_last_jedi/\"\nmovie_urls[\"The Rise of Skywalker\"] = \"https://www.rottentomatoes.com/m/star_wars_the_rise_of_skywalker\"\nfor key in newkeys:\n    temp = get_critic_reviews(movie_urls[key])\n    df = pd.DataFrame.from_dict(temp)\n    df['Film'] = key\n    dfs.append(df)",
    "id": "fd721ef530024b56923a5f5561a54747",
    "idx": 36,
    "time": "2021-01-27T00:37:11.953Z",
    "type": "execution"
   },
   {
    "id": "fd721ef530024b56923a5f5561a54747",
    "time": "2021-01-27T00:37:29.118Z",
    "type": "completion"
   },
   {
    "code": "#add films\nnewkeys = [\"The Last Jedi\"]\nmovie_urls[\"The Last Jedi\"] = \"https://www.rottentomatoes.com/m/star_wars_the_last_jedi/\"\nmovie_urls[\"The Rise of Skywalker\"] = \"https://www.rottentomatoes.com/m/star_wars_the_rise_of_skywalker/\"\nfor key in newkeys:\n    temp = get_critic_reviews(movie_urls[key])\n    df = pd.DataFrame.from_dict(temp)\n    df['Film'] = key\n    dfs.append(df)",
    "id": "fd721ef530024b56923a5f5561a54747",
    "idx": 36,
    "time": "2021-01-27T00:37:58.311Z",
    "type": "execution"
   },
   {
    "id": "fd721ef530024b56923a5f5561a54747",
    "time": "2021-01-27T00:38:05.932Z",
    "type": "completion"
   },
   {
    "code": "def update():\n    all_films = pd.concat(dfs)\n    all_films['score'] = all_films['fresh'].apply(lambda x: 1 if x == 'fresh' else 0)\n    all_films['date'] = pd.to_datetime(all_films['date'], format=\"%B %d, %Y\")",
    "id": "9f0a87eebac74031a73a05c1ee48aec2",
    "idx": 37,
    "time": "2021-01-27T00:38:09.030Z",
    "type": "execution"
   },
   {
    "id": "9f0a87eebac74031a73a05c1ee48aec2",
    "time": "2021-01-27T00:38:09.101Z",
    "type": "completion"
   },
   {
    "code": "update()",
    "id": "9223c0535bc24c1681e9f4f946b40136",
    "idx": 38,
    "time": "2021-01-27T00:38:12.632Z",
    "type": "execution"
   },
   {
    "id": "9223c0535bc24c1681e9f4f946b40136",
    "time": "2021-01-27T00:38:12.729Z",
    "type": "completion"
   },
   {
    "code": "all_films",
    "id": "fcc531697e3440d0bc620808c4dc701f",
    "idx": 39,
    "time": "2021-01-27T00:38:15.107Z",
    "type": "execution"
   },
   {
    "id": "fcc531697e3440d0bc620808c4dc701f",
    "time": "2021-01-27T00:38:15.218Z",
    "type": "completion"
   },
   {
    "code": "plot_film(\"The Last Jedi\")",
    "id": "fcc531697e3440d0bc620808c4dc701f",
    "idx": 39,
    "time": "2021-01-27T00:38:22.514Z",
    "type": "execution"
   },
   {
    "id": "fcc531697e3440d0bc620808c4dc701f",
    "time": "2021-01-27T00:38:23.220Z",
    "type": "completion"
   },
   {
    "code": "all_films[\"Film\"]",
    "id": "fcc531697e3440d0bc620808c4dc701f",
    "idx": 39,
    "time": "2021-01-27T00:38:35.611Z",
    "type": "execution"
   },
   {
    "id": "fcc531697e3440d0bc620808c4dc701f",
    "time": "2021-01-27T00:38:35.950Z",
    "type": "completion"
   },
   {
    "code": "all_films[\"Film\"].unique()",
    "id": "fcc531697e3440d0bc620808c4dc701f",
    "idx": 39,
    "time": "2021-01-27T00:38:40.534Z",
    "type": "execution"
   },
   {
    "id": "fcc531697e3440d0bc620808c4dc701f",
    "time": "2021-01-27T00:38:40.610Z",
    "type": "completion"
   },
   {
    "code": "dfs",
    "id": "fcc531697e3440d0bc620808c4dc701f",
    "idx": 39,
    "time": "2021-01-27T00:38:48.635Z",
    "type": "execution"
   },
   {
    "id": "fcc531697e3440d0bc620808c4dc701f",
    "time": "2021-01-27T00:38:48.973Z",
    "type": "completion"
   },
   {
    "code": "update()",
    "id": "9223c0535bc24c1681e9f4f946b40136",
    "idx": 38,
    "time": "2021-01-27T00:39:23.674Z",
    "type": "execution"
   },
   {
    "id": "9223c0535bc24c1681e9f4f946b40136",
    "time": "2021-01-27T00:39:23.763Z",
    "type": "completion"
   },
   {
    "code": "def update():\n    all_films = pd.concat(dfs)\n    all_films['score'] = all_films['fresh'].apply(lambda x: 1 if x == 'fresh' else 0)\n    all_films['date'] = pd.to_datetime(all_films['date'], format=\"%B %d, %Y\")\n    return all_films",
    "id": "9f0a87eebac74031a73a05c1ee48aec2",
    "idx": 37,
    "time": "2021-01-27T00:39:36.028Z",
    "type": "execution"
   },
   {
    "id": "9f0a87eebac74031a73a05c1ee48aec2",
    "time": "2021-01-27T00:39:36.101Z",
    "type": "completion"
   },
   {
    "code": "update()",
    "id": "9223c0535bc24c1681e9f4f946b40136",
    "idx": 38,
    "time": "2021-01-27T00:39:36.560Z",
    "type": "execution"
   },
   {
    "id": "9223c0535bc24c1681e9f4f946b40136",
    "time": "2021-01-27T00:39:36.715Z",
    "type": "completion"
   },
   {
    "code": "all_films = update()",
    "id": "9223c0535bc24c1681e9f4f946b40136",
    "idx": 38,
    "time": "2021-01-27T00:39:43.032Z",
    "type": "execution"
   },
   {
    "id": "9223c0535bc24c1681e9f4f946b40136",
    "time": "2021-01-27T00:39:43.143Z",
    "type": "completion"
   },
   {
    "code": "all_films",
    "id": "fcc531697e3440d0bc620808c4dc701f",
    "idx": 39,
    "time": "2021-01-27T00:39:43.891Z",
    "type": "execution"
   },
   {
    "id": "fcc531697e3440d0bc620808c4dc701f",
    "time": "2021-01-27T00:39:43.981Z",
    "type": "completion"
   },
   {
    "code": "plot_film(\"The Last Jedi\")",
    "id": "fcc531697e3440d0bc620808c4dc701f",
    "idx": 39,
    "time": "2021-01-27T00:39:53.225Z",
    "type": "execution"
   },
   {
    "id": "fcc531697e3440d0bc620808c4dc701f",
    "time": "2021-01-27T00:39:54.157Z",
    "type": "completion"
   },
   {
    "code": "plot_film(\"The Rise of Skywalker\")",
    "id": "103fb05c3e304ac0bb1d036092613ed7",
    "idx": 40,
    "time": "2021-01-27T00:40:06.956Z",
    "type": "execution"
   },
   {
    "id": "103fb05c3e304ac0bb1d036092613ed7",
    "time": "2021-01-27T00:40:07.620Z",
    "type": "completion"
   },
   {
    "code": "#add films\nnewkeys = [\"The Last Jedi\", \"The Rise of Skywalker\"]\nmovie_urls[\"The Last Jedi\"] = \"https://www.rottentomatoes.com/m/star_wars_the_last_jedi/\"\nmovie_urls[\"The Rise of Skywalker\"] = \"https://www.rottentomatoes.com/m/star_wars_the_rise_of_skywalker/\"\nfor key in newkeys:\n    temp = get_critic_reviews(movie_urls[key])\n    df = pd.DataFrame.from_dict(temp)\n    df['Film'] = key\n    dfs.append(df)",
    "id": "fd721ef530024b56923a5f5561a54747",
    "idx": 36,
    "time": "2021-01-27T00:40:25.354Z",
    "type": "execution"
   },
   {
    "code": "def update():\n    all_films = pd.concat(dfs)\n    all_films['score'] = all_films['fresh'].apply(lambda x: 1 if x == 'fresh' else 0)\n    all_films['date'] = pd.to_datetime(all_films['date'], format=\"%B %d, %Y\")\n    return all_films",
    "id": "9f0a87eebac74031a73a05c1ee48aec2",
    "idx": 37,
    "time": "2021-01-27T00:40:25.816Z",
    "type": "execution"
   },
   {
    "code": "all_films = update()",
    "id": "9223c0535bc24c1681e9f4f946b40136",
    "idx": 38,
    "time": "2021-01-27T00:40:26.279Z",
    "type": "execution"
   },
   {
    "code": "plot_film(\"The Last Jedi\")",
    "id": "fcc531697e3440d0bc620808c4dc701f",
    "idx": 39,
    "time": "2021-01-27T00:40:26.767Z",
    "type": "execution"
   },
   {
    "code": "plot_film(\"The Rise of Skywalker\")",
    "id": "103fb05c3e304ac0bb1d036092613ed7",
    "idx": 40,
    "time": "2021-01-27T00:40:27.569Z",
    "type": "execution"
   },
   {
    "id": "fd721ef530024b56923a5f5561a54747",
    "time": "2021-01-27T00:40:55.300Z",
    "type": "completion"
   },
   {
    "id": "9f0a87eebac74031a73a05c1ee48aec2",
    "time": "2021-01-27T00:40:55.302Z",
    "type": "completion"
   },
   {
    "id": "9223c0535bc24c1681e9f4f946b40136",
    "time": "2021-01-27T00:40:55.331Z",
    "type": "completion"
   },
   {
    "id": "fcc531697e3440d0bc620808c4dc701f",
    "time": "2021-01-27T00:40:55.625Z",
    "type": "completion"
   },
   {
    "id": "103fb05c3e304ac0bb1d036092613ed7",
    "time": "2021-01-27T00:40:55.988Z",
    "type": "completion"
   },
   {
    "code": "import requests\nimport time\n\n# requirements\nfrom bs4 import BeautifulSoup\nfrom requests import TooManyRedirects\nimport re\n\ndef _make_soup(url):\n    try:\n        r = requests.get(url)\n        soup = BeautifulSoup(r.content, 'html.parser')\n    except TooManyRedirects:\n        soup = ''\n    return soup\n\n#regex patterns\npage_pat = re.compile(r'Page 1 of \\d+')\nreview_pat = re.compile(r'<div class=\\\"the_review\\\" data-qa=\\\"review-text\\\">[;a-zA-Z\\s,-.\\'\\/\\?\\[\\]\\\":\\']*</div>')\nrating_pat = re.compile(r'Original Score:\\s([A-Z](\\+|-)?|\\d(.\\d)?(\\/\\d)?)')\nfresh_pat = re.compile(r'small\\s(fresh|rotten)\\\"')\ncritic_pat = re.compile(r'\\/\\\"\\>([A-Z][a-zA-Z]+\\s[A-Z][a-zA-Z\\-]+)|([A-Z][a-zA-Z.]+\\s[A-Z].?\\s[A-Z][a-zA-Z]+)|([A-Z][a-zA-Z]+\\s[A-Z]+\\'[A-Z][a-zA-Z]+)')\npublisher_pat = re.compile(r'\\\"subtle\\\">[a-zA-Z\\s,.\\(\\)\\'\\-&;!\\/\\d+]+</em>')\ndate_pat = re.compile(r'[a-zA-Z]+\\s\\d+,\\s\\d+')",
    "id": "89288e81e3c34da3ac88aa62995bad09",
    "idx": 0,
    "time": "2021-01-27T18:11:34.312Z",
    "type": "execution"
   },
   {
    "code": "def _get_critic_reviews_from_page(soup):\n    reviews = list()\n    rating = list()\n    fresh = list()\n    critic = list()\n    top_critic = list()\n    publisher = list()\n    date = list()\n    \n    soup = str(soup)\n    review_soup = soup.split('=\"review_table')[1].split('row review_table_row')\n    review_soup.pop(0)\n\n    for review in review_soup:\n        match = re.findall(review_pat, str(review))\n        if len(match) > 0:\n            m = match[0]            \n            for iden in ['<div class=\"the_review\" data-qa=\"review-text\"> ','</div>']:\n                m = m.replace(iden,'')\n            reviews.append(m.strip('\"'))            \n            # extract rating\n            match = re.findall(rating_pat, str(review))\n            if len(match) > 0:\n                m = match[0][0]\n                if '/1' in m:\n                    sp_m = m.split('/')\n                    if sp_m[-1] == '1':\n                        sp_m[-1] = '10'\n                    m = '/'.join(sp_m)\n                rating.append(m)\n            else:\n                rating.append(None)            \n            # extract fresh indicator\n            match = re.findall(fresh_pat, str(review))\n            if len(match) > 0:\n                fresh.append(match[0])\n            else:\n                fresh.append(None)            \n            # extract critic\n            match = re.findall(critic_pat, str(review))\n            if len(match) > 0:\n                critic.append(''.join(match[0]))\n            else:\n                critic.append(None)            \n            # check if top critic\n            if '> Top Critic<' in str(review):\n                top_critic.append(1)\n            else:\n                top_critic.append(0)            \n            # extract publisher\n            match = re.findall(publisher_pat, str(review))\n            if len(match) > 0:\n                m = match[0]\n                m = m.replace('\"subtle\">', '')\n                m = m.replace('</em>','')\n                publisher.append(m)\n            else:\n                publisher.append(None)            \n            # extract date\n            match = re.findall(date_pat, str(review))\n            if len(match) > 0:\n                date.append(match[0].strip('\"'))\n            else:\n                date.append(None)\n            \n    return [reviews, rating, fresh, critic, top_critic, publisher, date]\n\ndef _get_num_pages(soup):\n    match = re.findall(page_pat,str(list(soup)))\n    if len(match) > 0:\n        match = match[0]\n        match = match.split(' of ')[-1]\n        return match\n    else:\n        return None",
    "id": "3cc11e69b72b4f3ba8b002b3f8ad3df7",
    "idx": 1,
    "time": "2021-01-27T18:11:34.316Z",
    "type": "execution"
   },
   {
    "code": "def get_critic_reviews(page):\n    info = [[],[],[],[],[],[],[]]\n    soup = _make_soup(page + \"reviews\")\n#     print(soup)\n    pages = _get_num_pages(soup)\n#     print(pages)\n    if pages is not None:\n        for page_num in range(1,int(pages)+1):\n            soup = _make_soup(page + \"reviews?page=\" + str(page_num) + \"&sort=\")\n            c_info = _get_critic_reviews_from_page(soup)\n            \n            # accumulate review info\n            for i in range(len(c_info)):\n                info[i] = info[i] + c_info[i]\n        \n        c_info = dict()\n        keys = ['reviews', 'rating', 'fresh', 'critic', 'top_critic', 'publisher', 'date']\n        for k in range(len(keys)):\n            c_info[keys[k]] = info[k]        \n    else:\n        c_info = None        \n    return c_info",
    "id": "24bcfe1ae80f49c89ecee6e5a56cd021",
    "idx": 2,
    "time": "2021-01-27T18:11:34.319Z",
    "type": "execution"
   },
   {
    "code": "movie_urls = {'Wonder Woman 1984': 'https://www.rottentomatoes.com/m/wonder_woman_1984/', \n              'Soul':'https://www.rottentomatoes.com/m/soul_2020/', \n              'Mulan': 'https://www.rottentomatoes.com/m/mulan_2020/',\n              'Birds of Prey': 'https://www.rottentomatoes.com/m/birds_of_prey_2020/',\n              'Sonic': 'https://www.rottentomatoes.com/m/sonic_the_hedgehog_2020/'\n             }\n\nmovie_urls[\"Captain Marvel\"] = \"https://www.rottentomatoes.com/m/captain_marvel/\"\nmovie_urls[\"Lion King\"] = \"https://www.rottentomatoes.com/m/the_lion_king_2019/\"\nmovie_urls[\"Aladdin\"] = \"https://www.rottentomatoes.com/m/aladdin/\"\nmovie_urls[\"Joker\"] = \"https://www.rottentomatoes.com/m/joker_2019/\"\nmovie_urls[\"Shazam!\"] = \"https://www.rottentomatoes.com/m/shazam/\"\nmovie_urls[\"Godzilla: King of the Monsters\"] = \"https://www.rottentomatoes.com/m/godzilla_king_of_the_monsters_2019/\"\n\nmovie_urls['Tenet'] = 'https://www.rottentomatoes.com/m/tenet/'\nmovie_urls['Scoob'] = 'https://www.rottentomatoes.com/m/scoob/'\nmovie_urls['The Marksman'] = 'https://www.rottentomatoes.com/m/the_marksman_2021/'\nmovie_urls['Artemis Fowl'] = 'https://www.rottentomatoes.com/m/artemis_fowl/'\nmovie_urls['Lovebirds'] = 'https://www.rottentomatoes.com/m/the_lovebirds_2020/'\n\nmovie_urls.keys()",
    "id": "ee4fe2e8bdff4ffb8ea1076a90682459",
    "idx": 3,
    "time": "2021-01-27T18:11:34.320Z",
    "type": "execution"
   },
   {
    "code": "import pandas as pd\n\ndfs = []\nfor key in movie_urls.keys():\n    temp = get_critic_reviews(movie_urls[key])\n    df = pd.DataFrame.from_dict(temp)\n    df['Film'] = key\n    dfs.append(df)",
    "id": "d07d041655844a71be29d3e94f4acc71",
    "idx": 4,
    "time": "2021-01-27T18:11:34.322Z",
    "type": "execution"
   },
   {
    "code": "all_films = pd.concat(dfs)\nall_films",
    "id": "377f6510105142f6a3c4e0a6e0a71788",
    "idx": 5,
    "time": "2021-01-27T18:11:34.325Z",
    "type": "execution"
   },
   {
    "code": "all_films['score'] = all_films['fresh'].apply(lambda x: 1 if x == 'fresh' else 0)\nall_films",
    "id": "9c2d8a2cdc4749a084270ef9a00880a8",
    "idx": 6,
    "time": "2021-01-27T18:11:34.328Z",
    "type": "execution"
   },
   {
    "code": "all_films['date'] = pd.to_datetime(all_films['date'], format=\"%B %d, %Y\")\nall_films = all_films.sort_values('date')",
    "id": "06a570bc5e0a4c6d8fd8d1d815ee060d",
    "idx": 7,
    "time": "2021-01-27T18:11:34.329Z",
    "type": "execution"
   },
   {
    "code": "import numpy as np\n\n\ndef calculate_score(film, frame):\n    df = frame[frame['Film'] == film]\n    grouped_1 = df[['date', 'score']].groupby('date').agg([sum, 'count'])\n    grouped_1.columns = grouped_1.columns.droplevel(0)\n    return grouped_1.cumsum()['sum']/grouped_1.cumsum()['count']\n\ncalculate_score(\"Wonder Woman 1984\", all_films)",
    "id": "13a4cefccba54a85aa1fa8f448daa972",
    "idx": 8,
    "time": "2021-01-27T18:11:34.331Z",
    "type": "execution"
   },
   {
    "code": "# calculate_score(\"Soul\").plot()\nimport matplotlib.pyplot as plt\n\nfor key in movie_urls.keys():\n#     pd.to_numeric(df.Subs).plot.line()\n    df = all_films[all_films==key]\n    plt.plot(calculate_score(key, all_films), label=key)\n#     plt.plot(np.arange(len(df.index)), pd.to_numeric(df.Total).pct_change(), label = df.Name.values[0], color = colors[i])\n#     plt.axvline(x=30, color='red', linestyle='dashed',linewidth=0.5)\n    plt.ylabel('Percent Change in Subscribers by Day')\n    plt.xlabel(\"Day (0 is 1 month before Content Cop's release)\")\n    plt.legend()\n# plt.annotate('Content Cop released', xy=(30, 0.015), ha='center', size=10)\n# plt.title('The Impact of Content Cop')\n# plt.savefig('pct_cc.svg')",
    "id": "3289e039b29344e58226cf6121ef1d4b",
    "idx": 9,
    "time": "2021-01-27T18:11:34.333Z",
    "type": "execution"
   },
   {
    "code": "# all_films.to_csv(\"all_films.csv\", index=False)\nall_films = pd.concat(dfs)\nall_films['score'] = all_films['fresh'].apply(lambda x: 1 if x == 'fresh' else 0)\nall_films['date'] = pd.to_datetime(all_films['date'], format=\"%B %d, %Y\")",
    "id": "cbaa9fc1f6c8498c88b1a3e603e3ff4e",
    "idx": 10,
    "time": "2021-01-27T18:11:34.334Z",
    "type": "execution"
   },
   {
    "code": "# all_films = pd.read_csv(\"all_films.csv\")\nall_films",
    "id": "a7879eca09b64fcf8d3321f2393aeb50",
    "idx": 11,
    "time": "2021-01-27T18:11:34.336Z",
    "type": "execution"
   },
   {
    "code": "# all_films = pd.concat([all_films, new_films])",
    "id": "54e3deb454ab47cd850c844a7fed8e17",
    "idx": 12,
    "time": "2021-01-27T18:11:34.338Z",
    "type": "execution"
   },
   {
    "code": "all_films['date'] = pd.to_datetime(all_films['date'])\nall_films = all_films.sort_values('date')",
    "id": "43c1eb91ffb14be288c5e02553bcf49a",
    "idx": 13,
    "time": "2021-01-27T18:11:34.340Z",
    "type": "execution"
   },
   {
    "code": "for key in movie_urls.keys():\n#     pd.to_numeric(df.Subs).plot.line()\n    df = all_films[all_films==key]\n    plt.plot(calculate_score(key, all_films), label=key)\n#     plt.plot(np.arange(len(df.index)), pd.to_numeric(df.Total).pct_change(), label = df.Name.values[0], color = colors[i])\n#     plt.axvline(x=30, color='red', linestyle='dashed',linewidth=0.5)\n    plt.ylabel('Percent Change in Subscribers by Day')\n    plt.xlabel(\"Day (0 is 1 month before Content Cop's release)\")\n    plt.legend()\n# plt.annotate('Content Cop released', xy=(30, 0.015), ha='center', size=10)\n# plt.title('The Impact of Content Cop')\n# plt.savefig('pct_cc.svg')",
    "id": "bbf80f5e8c9d46c382a0046a27e5b50e",
    "idx": 14,
    "time": "2021-01-27T18:11:34.341Z",
    "type": "execution"
   },
   {
    "code": "%config InlineBackend.figure_format = 'svg'",
    "id": "2401f65bb4f24c18804c01c5e8f390a2",
    "idx": 15,
    "time": "2021-01-27T18:11:34.343Z",
    "type": "execution"
   },
   {
    "code": "def plot_film(film):\n    df = all_films[all_films==film]\n    series = calculate_score(film, all_films)\n    plt.plot(series)\n    plt.axhline(y=0.75, color='yellow', linestyle='dashed',linewidth=0.5)\n    plt.axhline(y=0.6, color='red', linestyle='dashed',linewidth=0.5)\n    plt.axhspan(0.75, 1, alpha=0.5, color='lightgreen')\n    plt.axhspan(0.6,.75, alpha=0.5, color='#F6F7A8')\n    plt.axhspan(0, 0.6, alpha=0.5, color='salmon')\n#     print(series)\n    plt.ylim(series.min(), series.max())\n    plt.xticks(rotation=45, ha=\"right\")\n    plt.title(film + \" Rotten Tomatoes Score over Time\")",
    "id": "12520d752094489f8389f47cc188e820",
    "idx": 16,
    "time": "2021-01-27T18:11:34.345Z",
    "type": "execution"
   },
   {
    "code": "# calculate_score(\"Artemis Fowl\",all_films)\nplot_film(\"Artemis Fowl\")",
    "id": "29d6f017588e483b81def167923557bc",
    "idx": 17,
    "time": "2021-01-27T18:11:34.346Z",
    "type": "execution"
   },
   {
    "code": "# calculate_score(\"Wonder Woman 1984\",all_films).plot()\nplot_film(\"Wonder Woman 1984\")",
    "id": "c942d6b051b2483885e5f9437a7b7e20",
    "idx": 18,
    "time": "2021-01-27T18:11:34.348Z",
    "type": "execution"
   },
   {
    "code": "# calculate_score(\"Mulan\",all_films).plot()\nplot_film(\"Mulan\")",
    "id": "12317016b09246ca8df95dbf9d13951e",
    "idx": 19,
    "time": "2021-01-27T18:11:34.349Z",
    "type": "execution"
   },
   {
    "code": "# calculate_score(\"Tenet\",all_films).plot()\nplot_film(\"Tenet\")",
    "id": "133e84d30a9743b3b1c1a25980df5a86",
    "idx": 20,
    "time": "2021-01-27T18:11:34.351Z",
    "type": "execution"
   },
   {
    "code": "plot_film(\"Lovebirds\")",
    "id": "f9ab5f66b7ce45338b35b1229588a476",
    "idx": 21,
    "time": "2021-01-27T18:11:34.352Z",
    "type": "execution"
   },
   {
    "code": "movie_urls.keys()",
    "id": "27f54eb75fd94c4ba0c138dbeb971a4d",
    "idx": 22,
    "time": "2021-01-27T18:11:34.353Z",
    "type": "execution"
   },
   {
    "code": "plot_film(\"Scoob\")",
    "id": "b69ef826931a4f1d8828a840457148ee",
    "idx": 23,
    "time": "2021-01-27T18:11:34.354Z",
    "type": "execution"
   },
   {
    "code": "plot_film(\"Birds of Prey\")",
    "id": "3a184bcbd0034d9d8de044ba270f0cd5",
    "idx": 24,
    "time": "2021-01-27T18:11:34.356Z",
    "type": "execution"
   },
   {
    "code": "plot_film(\"The Marksman\")",
    "id": "3a1de301b938482fa8a743d89d7b5d02",
    "idx": 25,
    "time": "2021-01-27T18:11:34.357Z",
    "type": "execution"
   },
   {
    "code": "all_films.to_csv(\"all_films_v2.csv\",index=False)",
    "id": "00822b8e053743ae9b4c7a2e60fa3e88",
    "idx": 26,
    "time": "2021-01-27T18:11:34.358Z",
    "type": "execution"
   },
   {
    "code": "movie_urls.keys()",
    "id": "b6645cc8d8eb4f0284bbe56c8a994d3b",
    "idx": 27,
    "time": "2021-01-27T18:11:34.360Z",
    "type": "execution"
   },
   {
    "code": "plot_film(\"Sonic\")",
    "id": "9dea1923230549cb8a42e5954f924132",
    "idx": 28,
    "time": "2021-01-27T18:11:34.363Z",
    "type": "execution"
   },
   {
    "code": "all_films[(all_films[\"Film\"]==\"Sonic\") & (all_films[\"date\"]==\"2020-02-12\")]",
    "id": "b867a6ed94624075860908c9359d0d93",
    "idx": 29,
    "time": "2021-01-27T18:11:34.365Z",
    "type": "execution"
   },
   {
    "code": "plot_film(\"Aladdin\")",
    "id": "cf48a196a2844f70947e404b66fd6fed",
    "idx": 30,
    "time": "2021-01-27T18:11:34.366Z",
    "type": "execution"
   },
   {
    "code": "plot_film(\"Lion King\")",
    "id": "b19be89601be4f33a24cc96f4119da60",
    "idx": 31,
    "time": "2021-01-27T18:11:34.367Z",
    "type": "execution"
   },
   {
    "code": "plot_film(\"Captain Marvel\")",
    "id": "78fa33d862bb43ceaa0b5ba8fdb41a0d",
    "idx": 32,
    "time": "2021-01-27T18:11:34.369Z",
    "type": "execution"
   },
   {
    "code": "plot_film(\"Godzilla: King of the Monsters\")",
    "id": "207f804df9214ff4884b86060e87085e",
    "idx": 33,
    "time": "2021-01-27T18:11:34.370Z",
    "type": "execution"
   },
   {
    "code": "plot_film(\"Joker\")",
    "id": "dc578ba2f9d74f908b1d25b154e8f71d",
    "idx": 34,
    "time": "2021-01-27T18:11:34.372Z",
    "type": "execution"
   },
   {
    "code": "plot_film(\"Shazam!\")",
    "id": "fdd9410c2dcb47618529f48311620c7e",
    "idx": 35,
    "time": "2021-01-27T18:11:34.373Z",
    "type": "execution"
   },
   {
    "code": "#add films\nnewkeys = [\"The Last Jedi\", \"The Rise of Skywalker\"]\nmovie_urls[\"The Last Jedi\"] = \"https://www.rottentomatoes.com/m/star_wars_the_last_jedi/\"\nmovie_urls[\"The Rise of Skywalker\"] = \"https://www.rottentomatoes.com/m/star_wars_the_rise_of_skywalker/\"\nfor key in newkeys:\n    temp = get_critic_reviews(movie_urls[key])\n    df = pd.DataFrame.from_dict(temp)\n    df['Film'] = key\n    dfs.append(df)",
    "id": "a9fa7c97affe4afa8016313060e16f5a",
    "idx": 36,
    "time": "2021-01-27T18:11:34.374Z",
    "type": "execution"
   },
   {
    "code": "def update():\n    all_films = pd.concat(dfs)\n    all_films['score'] = all_films['fresh'].apply(lambda x: 1 if x == 'fresh' else 0)\n    all_films['date'] = pd.to_datetime(all_films['date'], format=\"%B %d, %Y\")\n    return all_films.drop_duplicates()",
    "id": "4d769e18b2094ba7ad0c079368076e4d",
    "idx": 37,
    "time": "2021-01-27T18:11:34.375Z",
    "type": "execution"
   },
   {
    "code": "all_films = update()",
    "id": "78d4136f2f9b4fd788b706017ddd3418",
    "idx": 38,
    "time": "2021-01-27T18:11:34.376Z",
    "type": "execution"
   },
   {
    "code": "plot_film(\"The Last Jedi\")",
    "id": "639ad268aab24db48be923276d56b453",
    "idx": 39,
    "time": "2021-01-27T18:11:34.378Z",
    "type": "execution"
   },
   {
    "code": "plot_film(\"The Rise of Skywalker\")",
    "id": "d15fc94719684dbf8a7d76044e64fe33",
    "idx": 40,
    "time": "2021-01-27T18:11:34.379Z",
    "type": "execution"
   },
   {
    "id": "89288e81e3c34da3ac88aa62995bad09",
    "time": "2021-01-27T18:11:34.584Z",
    "type": "completion"
   },
   {
    "id": "3cc11e69b72b4f3ba8b002b3f8ad3df7",
    "time": "2021-01-27T18:11:34.592Z",
    "type": "completion"
   },
   {
    "id": "24bcfe1ae80f49c89ecee6e5a56cd021",
    "time": "2021-01-27T18:11:34.656Z",
    "type": "completion"
   },
   {
    "id": "ee4fe2e8bdff4ffb8ea1076a90682459",
    "time": "2021-01-27T18:11:34.661Z",
    "type": "completion"
   },
   {
    "id": "d07d041655844a71be29d3e94f4acc71",
    "time": "2021-01-27T18:17:53.376Z",
    "type": "completion"
   },
   {
    "id": "377f6510105142f6a3c4e0a6e0a71788",
    "time": "2021-01-27T18:17:53.430Z",
    "type": "completion"
   },
   {
    "id": "9c2d8a2cdc4749a084270ef9a00880a8",
    "time": "2021-01-27T18:17:53.459Z",
    "type": "completion"
   },
   {
    "id": "06a570bc5e0a4c6d8fd8d1d815ee060d",
    "time": "2021-01-27T18:17:53.460Z",
    "type": "completion"
   },
   {
    "id": "13a4cefccba54a85aa1fa8f448daa972",
    "time": "2021-01-27T18:17:53.549Z",
    "type": "completion"
   },
   {
    "id": "3289e039b29344e58226cf6121ef1d4b",
    "time": "2021-01-27T18:17:54.612Z",
    "type": "completion"
   },
   {
    "id": "cbaa9fc1f6c8498c88b1a3e603e3ff4e",
    "time": "2021-01-27T18:17:54.617Z",
    "type": "completion"
   },
   {
    "id": "a7879eca09b64fcf8d3321f2393aeb50",
    "time": "2021-01-27T18:17:54.664Z",
    "type": "completion"
   },
   {
    "id": "54e3deb454ab47cd850c844a7fed8e17",
    "time": "2021-01-27T18:17:54.665Z",
    "type": "completion"
   },
   {
    "id": "43c1eb91ffb14be288c5e02553bcf49a",
    "time": "2021-01-27T18:17:54.666Z",
    "type": "completion"
   },
   {
    "id": "bbf80f5e8c9d46c382a0046a27e5b50e",
    "time": "2021-01-27T18:17:55.263Z",
    "type": "completion"
   },
   {
    "id": "2401f65bb4f24c18804c01c5e8f390a2",
    "time": "2021-01-27T18:17:55.265Z",
    "type": "completion"
   },
   {
    "id": "12520d752094489f8389f47cc188e820",
    "time": "2021-01-27T18:17:55.308Z",
    "type": "completion"
   },
   {
    "id": "29d6f017588e483b81def167923557bc",
    "time": "2021-01-27T18:17:55.392Z",
    "type": "completion"
   },
   {
    "id": "c942d6b051b2483885e5f9437a7b7e20",
    "time": "2021-01-27T18:17:55.586Z",
    "type": "completion"
   },
   {
    "id": "12317016b09246ca8df95dbf9d13951e",
    "time": "2021-01-27T18:17:55.928Z",
    "type": "completion"
   },
   {
    "id": "133e84d30a9743b3b1c1a25980df5a86",
    "time": "2021-01-27T18:17:56.043Z",
    "type": "completion"
   },
   {
    "id": "f9ab5f66b7ce45338b35b1229588a476",
    "time": "2021-01-27T18:17:56.238Z",
    "type": "completion"
   },
   {
    "id": "27f54eb75fd94c4ba0c138dbeb971a4d",
    "time": "2021-01-27T18:17:56.241Z",
    "type": "completion"
   },
   {
    "id": "b69ef826931a4f1d8828a840457148ee",
    "time": "2021-01-27T18:17:56.395Z",
    "type": "completion"
   },
   {
    "id": "3a184bcbd0034d9d8de044ba270f0cd5",
    "time": "2021-01-27T18:17:56.540Z",
    "type": "completion"
   },
   {
    "id": "3a1de301b938482fa8a743d89d7b5d02",
    "time": "2021-01-27T18:17:56.780Z",
    "type": "completion"
   },
   {
    "id": "00822b8e053743ae9b4c7a2e60fa3e88",
    "time": "2021-01-27T18:17:56.947Z",
    "type": "completion"
   },
   {
    "id": "b6645cc8d8eb4f0284bbe56c8a994d3b",
    "time": "2021-01-27T18:17:56.948Z",
    "type": "completion"
   },
   {
    "id": "9dea1923230549cb8a42e5954f924132",
    "time": "2021-01-27T18:17:57.161Z",
    "type": "completion"
   },
   {
    "id": "b867a6ed94624075860908c9359d0d93",
    "time": "2021-01-27T18:17:57.165Z",
    "type": "completion"
   },
   {
    "id": "cf48a196a2844f70947e404b66fd6fed",
    "time": "2021-01-27T18:17:57.456Z",
    "type": "completion"
   },
   {
    "id": "b19be89601be4f33a24cc96f4119da60",
    "time": "2021-01-27T18:17:57.651Z",
    "type": "completion"
   },
   {
    "id": "78fa33d862bb43ceaa0b5ba8fdb41a0d",
    "time": "2021-01-27T18:17:57.866Z",
    "type": "completion"
   },
   {
    "id": "207f804df9214ff4884b86060e87085e",
    "time": "2021-01-27T18:17:58.187Z",
    "type": "completion"
   },
   {
    "id": "dc578ba2f9d74f908b1d25b154e8f71d",
    "time": "2021-01-27T18:17:58.416Z",
    "type": "completion"
   },
   {
    "id": "fdd9410c2dcb47618529f48311620c7e",
    "time": "2021-01-27T18:17:58.665Z",
    "type": "completion"
   },
   {
    "id": "a9fa7c97affe4afa8016313060e16f5a",
    "time": "2021-01-27T18:18:33.556Z",
    "type": "completion"
   },
   {
    "id": "4d769e18b2094ba7ad0c079368076e4d",
    "time": "2021-01-27T18:18:33.557Z",
    "type": "completion"
   },
   {
    "id": "78d4136f2f9b4fd788b706017ddd3418",
    "time": "2021-01-27T18:18:33.597Z",
    "type": "completion"
   },
   {
    "id": "639ad268aab24db48be923276d56b453",
    "time": "2021-01-27T18:18:33.888Z",
    "type": "completion"
   },
   {
    "id": "d15fc94719684dbf8a7d76044e64fe33",
    "time": "2021-01-27T18:18:34.169Z",
    "type": "completion"
   },
   {
    "code": "import requests\nimport time\n\n# requirements\nfrom bs4 import BeautifulSoup\nfrom requests import TooManyRedirects\nimport re\n\ndef _make_soup(url):\n    try:\n        r = requests.get(url)\n        soup = BeautifulSoup(r.content, 'html.parser')\n    except TooManyRedirects:\n        soup = ''\n    return soup\n\n#regex patterns\npage_pat = re.compile(r'Page 1 of \\d+')\nreview_pat = re.compile(r'<div class=\\\"the_review\\\" data-qa=\\\"review-text\\\">[;a-zA-Z\\s,-.\\'\\/\\?\\[\\]\\\":\\']*</div>')\nrating_pat = re.compile(r'Original Score:\\s([A-Z](\\+|-)?|\\d(.\\d)?(\\/\\d)?)')\nfresh_pat = re.compile(r'small\\s(fresh|rotten)\\\"')\ncritic_pat = re.compile(r'\\/\\\"\\>([A-Z][a-zA-Z]+\\s[A-Z][a-zA-Z\\-]+)|([A-Z][a-zA-Z.]+\\s[A-Z].?\\s[A-Z][a-zA-Z]+)|([A-Z][a-zA-Z]+\\s[A-Z]+\\'[A-Z][a-zA-Z]+)')\npublisher_pat = re.compile(r'\\\"subtle\\\">[a-zA-Z\\s,.\\(\\)\\'\\-&;!\\/\\d+]+</em>')\ndate_pat = re.compile(r'[a-zA-Z]+\\s\\d+,\\s\\d+')",
    "id": "94f9bfa30c3b43e9afbd169926f1c86b",
    "idx": 0,
    "time": "2021-02-05T06:04:37.266Z",
    "type": "execution"
   },
   {
    "id": "94f9bfa30c3b43e9afbd169926f1c86b",
    "time": "2021-02-05T06:04:37.523Z",
    "type": "completion"
   },
   {
    "code": "_make_soup('https://www.rottentomatoes.com/m/wonder_woman_1984/')",
    "id": "da09a38bbe684a87ba590b6abe70cfea",
    "idx": 1,
    "time": "2021-02-05T06:04:51.601Z",
    "type": "execution"
   },
   {
    "id": "da09a38bbe684a87ba590b6abe70cfea",
    "time": "2021-02-05T06:04:53.530Z",
    "type": "completion"
   },
   {
    "code": "_make_soup('https://www.rottentomatoes.com/m/wonder_woman_1984/').find_all(\"percentage\")",
    "id": "da09a38bbe684a87ba590b6abe70cfea",
    "idx": 1,
    "time": "2021-02-05T06:06:26.088Z",
    "type": "execution"
   },
   {
    "id": "da09a38bbe684a87ba590b6abe70cfea",
    "time": "2021-02-05T06:06:26.623Z",
    "type": "completion"
   },
   {
    "code": "url = 'https://www.rottentomatoes.com/m/wonder_woman_1984/'\nrequest=urllib.request.Request(url)\nbs = BeautifulSoup(urlopen(request), \"html.parser\")\nbs",
    "id": "da09a38bbe684a87ba590b6abe70cfea",
    "idx": 1,
    "time": "2021-02-05T06:08:31.412Z",
    "type": "execution"
   },
   {
    "id": "da09a38bbe684a87ba590b6abe70cfea",
    "time": "2021-02-05T06:08:31.593Z",
    "type": "completion"
   },
   {
    "code": "from urllib.request import urlopen\nfrom bs4 import BeautifulSoup\nurl = 'https://www.rottentomatoes.com/m/wonder_woman_1984/'\nrequest=urllib.request.Request(url)\nbs = BeautifulSoup(urlopen(request), \"html.parser\")\nbs",
    "id": "da09a38bbe684a87ba590b6abe70cfea",
    "idx": 1,
    "time": "2021-02-05T06:09:10.144Z",
    "type": "execution"
   },
   {
    "id": "da09a38bbe684a87ba590b6abe70cfea",
    "time": "2021-02-05T06:09:10.225Z",
    "type": "completion"
   },
   {
    "code": "import urllib\nfrom urllib.request import urlopen\nfrom bs4 import BeautifulSoup\nurl = 'https://www.rottentomatoes.com/m/wonder_woman_1984/'\nrequest=urllib.request.Request(url)\nbs = BeautifulSoup(urlopen(request), \"html.parser\")\nbs",
    "id": "da09a38bbe684a87ba590b6abe70cfea",
    "idx": 1,
    "time": "2021-02-05T06:09:20.683Z",
    "type": "execution"
   },
   {
    "id": "da09a38bbe684a87ba590b6abe70cfea",
    "time": "2021-02-05T06:09:23.805Z",
    "type": "completion"
   },
   {
    "code": "bs.find_all(\"percentage\")",
    "id": "6ae1e126062243df90c76916b32639d7",
    "idx": 2,
    "time": "2021-02-05T06:09:33.996Z",
    "type": "execution"
   },
   {
    "id": "6ae1e126062243df90c76916b32639d7",
    "time": "2021-02-05T06:09:34.079Z",
    "type": "completion"
   },
   {
    "code": "bs.find_all(\".percentage\")",
    "id": "6ae1e126062243df90c76916b32639d7",
    "idx": 2,
    "time": "2021-02-05T06:09:42.437Z",
    "type": "execution"
   },
   {
    "id": "6ae1e126062243df90c76916b32639d7",
    "time": "2021-02-05T06:09:42.516Z",
    "type": "completion"
   },
   {
    "code": "bs.find_all(\"span\", _class=\"percentage\")",
    "id": "6ae1e126062243df90c76916b32639d7",
    "idx": 2,
    "time": "2021-02-05T06:10:17.715Z",
    "type": "execution"
   },
   {
    "id": "6ae1e126062243df90c76916b32639d7",
    "time": "2021-02-05T06:10:17.800Z",
    "type": "completion"
   },
   {
    "code": "bs.find_all(\"span\", class_=\"percentage\")",
    "id": "6ae1e126062243df90c76916b32639d7",
    "idx": 2,
    "time": "2021-02-05T06:10:28.514Z",
    "type": "execution"
   },
   {
    "id": "6ae1e126062243df90c76916b32639d7",
    "time": "2021-02-05T06:10:28.613Z",
    "type": "completion"
   },
   {
    "code": "bs.find_all(\"span\")",
    "id": "6ae1e126062243df90c76916b32639d7",
    "idx": 2,
    "time": "2021-02-05T06:10:33.163Z",
    "type": "execution"
   },
   {
    "id": "6ae1e126062243df90c76916b32639d7",
    "time": "2021-02-05T06:10:33.349Z",
    "type": "completion"
   },
   {
    "code": "bs.find_all(\"span medium\")",
    "id": "6ae1e126062243df90c76916b32639d7",
    "idx": 2,
    "time": "2021-02-05T06:11:21.464Z",
    "type": "execution"
   },
   {
    "id": "6ae1e126062243df90c76916b32639d7",
    "time": "2021-02-05T06:11:21.601Z",
    "type": "completion"
   },
   {
    "code": "bs.find_all(\"div\")",
    "id": "6ae1e126062243df90c76916b32639d7",
    "idx": 2,
    "time": "2021-02-05T06:11:53.423Z",
    "type": "execution"
   },
   {
    "id": "6ae1e126062243df90c76916b32639d7",
    "time": "2021-02-05T06:11:55.173Z",
    "type": "completion"
   },
   {
    "code": "bs.find_all(\"div\", class_=\"scores-container\")",
    "id": "6ae1e126062243df90c76916b32639d7",
    "idx": 2,
    "time": "2021-02-05T06:12:01.114Z",
    "type": "execution"
   },
   {
    "id": "6ae1e126062243df90c76916b32639d7",
    "time": "2021-02-05T06:12:01.221Z",
    "type": "completion"
   },
   {
    "code": "bs.find_all(\"div\",{\"class\":\"scores-container\"})",
    "id": "6ae1e126062243df90c76916b32639d7",
    "idx": 2,
    "time": "2021-02-05T06:12:33.911Z",
    "type": "execution"
   },
   {
    "id": "6ae1e126062243df90c76916b32639d7",
    "time": "2021-02-05T06:12:34.034Z",
    "type": "completion"
   },
   {
    "code": "movieSyn_pat = re.compile(r'movieSynopsis[a-zA-Z\\\"\\s=\\:]+>\\s+[a-zA-Z\\\"\\?\\(\\)\\s=\\:.,-\\;\\&\\']+')\nrating_pat = re.compile(r'Rating: </div>[\\s]+[a-zA-Z\\=\\-\\<\\>\\s\\\"]+\\>[A-Z\\-\\d]+')\ngenres_pat = re.compile(r'Genre: </div>[\\s]+[a-zA-Z\\=\\-\\<\\>\\s\\\"\\/\\?\\d\\&\\;\\,]+</div>')\ndir_pat = re.compile(r'Directed By: </div>[a-zA-Z\\=\\-\\<\\>\\s\\\"\\/\\?\\d\\&\\;\\,\\_]+</div>')\nwrt_pat = re.compile(r'Written By: </div>[a-zA-Z\\=\\-\\<\\>\\s\\\"\\/\\?\\d\\&\\;\\,\\_]+</div>')\ndate_pat = re.compile(r'In Theaters: </div>[a-zA-Z\\=\\-\\<\\>\\s\\\"\\/\\?\\d\\&\\;\\,\\_\\:]+</time>')\ndate2_pat = re.compile(r'\\w+\\s\\d+\\,\\s\\d+')\nboxOff_pat = re.compile(r'Box Office: </div>[\\sa-z\\<\\=\\\"\\-\\>]+.?[\\d,]+')  \nrt_pat = re.compile(r'Runtime: </div>[\\sa-zA-Z\\d\\<\\=\\\"\\-\\>]+minutes')\nstudio_pat = re.compile(r'Studio: </div>[\\sa-zA-Z\\d\\<\\=\\\"\\-\\>\\:\\/\\.]+a>\\s+</div>')   \n\n#===============\n# user functions\n#===============",
    "id": "1f4c9d5c5dfe4ce08234b488bf7f564f",
    "idx": 2,
    "time": "2021-02-05T06:15:40.953Z",
    "type": "execution"
   },
   {
    "id": "1f4c9d5c5dfe4ce08234b488bf7f564f",
    "time": "2021-02-05T06:15:41.055Z",
    "type": "completion"
   },
   {
    "code": "def get_main_page_info(page):\n    \"\"\"Scrapes info from a movie main page\n\n    Parameters\n    ----------\n    page : str\n        The url to scrape from RT\n\n    Returns\n    -------\n    dict\n        dict of scraped info with keys:\n        synopsis, rating, genre, studio, director, writer, currency,\n        box_office, runtime\n    \"\"\"\n    \n    info = dict()   \n    \n    # verbose option\n    if get_verbose_setting():\n        print('scraping main page')\n        print('scraping url: ' + page)\n    \n    # make soup\n    soup = _make_soup(page)\n    \n    if soup == '':\n        # return None when failed soup; None is easy to detect\n        return None\n        \n    else:\n        # prepare soup\n        # ignore steping through tree due to instability\n        info_html = str(soup)\n        \n        ### eat soup ###\n        \n        # get synopsis\n        match = re.findall(movieSyn_pat, info_html)\n        if len(match) > 0:\n            match = match[0].split('>')[-1].strip()\n            info['synopsis'] = match\n        else:\n            info['synopsis'] = None\n        \n        # get rating\n        match = re.findall(rating_pat, info_html)\n        if len(match) > 0:\n            match = match[0].split('>')[-1]\n            info['rating'] = match\n        else:\n            info['rating'] = None\n        \n        # get genre\n        match = re.findall(genres_pat, info_html)\n        if len(match) > 0:\n            match = match[0].replace('&amp;','and').split('>')\n            genre = list()\n            for g in match:\n                if '</a' in g:\n                    genre.append(g.replace('</a','').rstrip().lstrip())\n            info['genre'] = '|'.join(genre)\n        else:\n            info['genre'] = None\n        \n        # get director\n        match = re.findall(dir_pat, info_html)\n        if len(match) > 0:\n            match = match[0].replace('&amp;','and').split('>')\n            director = list()\n            for d in match:\n                if '</a' in d:\n                    director.append(d.replace('</a',''))\n            info['director'] = '|'.join(director)\n        else:\n            info['director'] = None\n        \n        # get director\n        match = re.findall(wrt_pat, info_html)\n        if len(match) > 0:\n            match = match[0].replace('&amp;','and').split('>')\n            writer = list()\n            for w in match:\n                if '</a' in w:\n                    writer.append(w.replace('</a',''))\n            info['writer'] = '|'.join(writer)\n        else:\n            info['writer'] = None\n        \n        # get dates\n        match = re.findall(date_pat, info_html)\n        if len(match) > 0:\n            match = re.findall(date2_pat, match[0])\n            if len(match) == 2:\n                info['theater_date'] = match[0]\n                info['dvd_date'] = match[1]\n            else:\n                #match failed\n                info['theater_date'] = None\n                info['dvd_date'] = None\n        else:\n            info['theater_date'] = None\n            info['dvd_date'] = None\n        \n        # get box_office\n        match = re.findall(boxOff_pat, info_html)\n        if len(match) > 0:\n            info['currency'] = match[0].split('>')[-1][0]\n            info['box_office'] = match[0].split('>')[-1][1:]\n        else:\n            info['currency'] = None\n            info['box_office'] = None\n        \n        # get runtime\n        match = re.findall(rt_pat, info_html)\n        if len(match) > 0:\n            info['runtime'] = match[0].split('\\n')[-1].strip()\n        else:\n            info['runtime'] = None\n        \n        # get studio\n        match = re.findall(studio_pat, info_html)\n        if len(match) > 0:\n            match = match[0].split('\">')\n            studio = list()\n            for s in match:\n                if '</a>' in s:\n                    studio.append(s.replace('</a>','').replace('</div>','').strip())\n            info['studio'] = '|'.join(studio)\n        else:\n            info['studio'] = None\n        \n        # TODO: add cast scraper\n        \n        return info",
    "id": "db51648ed5b04ae789c5af1c597047ac",
    "idx": 3,
    "time": "2021-02-05T06:15:53.008Z",
    "type": "execution"
   },
   {
    "id": "db51648ed5b04ae789c5af1c597047ac",
    "time": "2021-02-05T06:15:53.099Z",
    "type": "completion"
   },
   {
    "code": "get_main_page_info(url)",
    "id": "8a486126b26e4b898262f686ff346081",
    "idx": 4,
    "time": "2021-02-05T06:16:06.149Z",
    "type": "execution"
   },
   {
    "id": "8a486126b26e4b898262f686ff346081",
    "time": "2021-02-05T06:16:06.290Z",
    "type": "completion"
   },
   {
    "code": "def get_main_page_info(page):\n    \"\"\"Scrapes info from a movie main page\n\n    Parameters\n    ----------\n    page : str\n        The url to scrape from RT\n\n    Returns\n    -------\n    dict\n        dict of scraped info with keys:\n        synopsis, rating, genre, studio, director, writer, currency,\n        box_office, runtime\n    \"\"\"\n    \n    info = {}\n    \n    \n    # make soup\n    soup = _make_soup(page)\n    \n    if soup == '':\n        # return None when failed soup; None is easy to detect\n        return None\n        \n    else:\n        # prepare soup\n        # ignore steping through tree due to instability\n        info_html = str(soup)\n        \n        ### eat soup ###\n        \n        # get synopsis\n        match = re.findall(movieSyn_pat, info_html)\n        if len(match) > 0:\n            match = match[0].split('>')[-1].strip()\n            info['synopsis'] = match\n        else:\n            info['synopsis'] = None\n        \n        # get rating\n        match = re.findall(rating_pat, info_html)\n        if len(match) > 0:\n            match = match[0].split('>')[-1]\n            info['rating'] = match\n        else:\n            info['rating'] = None\n        \n        # get genre\n        match = re.findall(genres_pat, info_html)\n        if len(match) > 0:\n            match = match[0].replace('&amp;','and').split('>')\n            genre = list()\n            for g in match:\n                if '</a' in g:\n                    genre.append(g.replace('</a','').rstrip().lstrip())\n            info['genre'] = '|'.join(genre)\n        else:\n            info['genre'] = None\n        \n        # get director\n        match = re.findall(dir_pat, info_html)\n        if len(match) > 0:\n            match = match[0].replace('&amp;','and').split('>')\n            director = list()\n            for d in match:\n                if '</a' in d:\n                    director.append(d.replace('</a',''))\n            info['director'] = '|'.join(director)\n        else:\n            info['director'] = None\n        \n        # get director\n        match = re.findall(wrt_pat, info_html)\n        if len(match) > 0:\n            match = match[0].replace('&amp;','and').split('>')\n            writer = list()\n            for w in match:\n                if '</a' in w:\n                    writer.append(w.replace('</a',''))\n            info['writer'] = '|'.join(writer)\n        else:\n            info['writer'] = None\n        \n        # get dates\n        match = re.findall(date_pat, info_html)\n        if len(match) > 0:\n            match = re.findall(date2_pat, match[0])\n            if len(match) == 2:\n                info['theater_date'] = match[0]\n                info['dvd_date'] = match[1]\n            else:\n                #match failed\n                info['theater_date'] = None\n                info['dvd_date'] = None\n        else:\n            info['theater_date'] = None\n            info['dvd_date'] = None\n        \n        # get box_office\n        match = re.findall(boxOff_pat, info_html)\n        if len(match) > 0:\n            info['currency'] = match[0].split('>')[-1][0]\n            info['box_office'] = match[0].split('>')[-1][1:]\n        else:\n            info['currency'] = None\n            info['box_office'] = None\n        \n        # get runtime\n        match = re.findall(rt_pat, info_html)\n        if len(match) > 0:\n            info['runtime'] = match[0].split('\\n')[-1].strip()\n        else:\n            info['runtime'] = None\n        \n        # get studio\n        match = re.findall(studio_pat, info_html)\n        if len(match) > 0:\n            match = match[0].split('\">')\n            studio = list()\n            for s in match:\n                if '</a>' in s:\n                    studio.append(s.replace('</a>','').replace('</div>','').strip())\n            info['studio'] = '|'.join(studio)\n        else:\n            info['studio'] = None\n        \n        # TODO: add cast scraper\n        \n        return info",
    "id": "db51648ed5b04ae789c5af1c597047ac",
    "idx": 3,
    "time": "2021-02-05T06:16:19.682Z",
    "type": "execution"
   },
   {
    "id": "db51648ed5b04ae789c5af1c597047ac",
    "time": "2021-02-05T06:16:19.773Z",
    "type": "completion"
   },
   {
    "code": "get_main_page_info(url)",
    "id": "8a486126b26e4b898262f686ff346081",
    "idx": 4,
    "time": "2021-02-05T06:16:20.058Z",
    "type": "execution"
   },
   {
    "id": "8a486126b26e4b898262f686ff346081",
    "time": "2021-02-05T06:16:21.147Z",
    "type": "completion"
   },
   {
    "code": "bs.find(\"aggregateRating\")",
    "id": "38b4b429f0044c0b980cfa67cf08fd70",
    "idx": 6,
    "time": "2021-02-05T06:21:12.681Z",
    "type": "execution"
   },
   {
    "id": "38b4b429f0044c0b980cfa67cf08fd70",
    "time": "2021-02-05T06:21:12.798Z",
    "type": "completion"
   },
   {
    "code": "bs.find(attrs={'class': 'meter-value superPageFontColor'})",
    "id": "38b4b429f0044c0b980cfa67cf08fd70",
    "idx": 6,
    "time": "2021-02-05T06:22:29.435Z",
    "type": "execution"
   },
   {
    "id": "38b4b429f0044c0b980cfa67cf08fd70",
    "time": "2021-02-05T06:22:29.537Z",
    "type": "completion"
   },
   {
    "code": "page = urllib2.urlopen(url)\npage_html = BeautifulSoup(page, 'html.parser')",
    "id": "ce483e451b454315802c09be073f68b5",
    "idx": 7,
    "time": "2021-02-05T06:22:54.638Z",
    "type": "execution"
   },
   {
    "id": "ce483e451b454315802c09be073f68b5",
    "time": "2021-02-05T06:22:54.721Z",
    "type": "completion"
   },
   {
    "code": "import re\nimport urllib2\nfrom bs4 import BeautifulSoup\n\npage = urllib2.urlopen(url)\npage_html = BeautifulSoup(page, 'html.parser')\nbs.find(attrs={'class': 'meter-value superPageFontColor'})",
    "id": "ce483e451b454315802c09be073f68b5",
    "idx": 7,
    "time": "2021-02-05T06:23:15.537Z",
    "type": "execution"
   },
   {
    "id": "ce483e451b454315802c09be073f68b5",
    "time": "2021-02-05T06:23:15.648Z",
    "type": "completion"
   },
   {
    "code": "import re\nimport urllib2\nfrom bs4 import BeautifulSoup\n\npage = urllib2.urlopen(url)\npage_html = BeautifulSoup(page, 'html.parser')\npage_html.find(attrs={'class': 'meter-value superPageFontColor'})",
    "id": "ce483e451b454315802c09be073f68b5",
    "idx": 7,
    "time": "2021-02-05T06:23:23.889Z",
    "type": "execution"
   },
   {
    "id": "ce483e451b454315802c09be073f68b5",
    "time": "2021-02-05T06:23:24.002Z",
    "type": "completion"
   },
   {
    "code": "!pip install urllib2",
    "id": "38b4b429f0044c0b980cfa67cf08fd70",
    "idx": 6,
    "time": "2021-02-05T06:23:32.646Z",
    "type": "execution"
   },
   {
    "code": "import re\nimport urllib2\nfrom bs4 import BeautifulSoup\n\npage = urllib2.urlopen(url)\npage_html = BeautifulSoup(page, 'html.parser')\npage_html.find(attrs={'class': 'meter-value superPageFontColor'})",
    "id": "ce483e451b454315802c09be073f68b5",
    "idx": 7,
    "time": "2021-02-05T06:23:32.965Z",
    "type": "execution"
   },
   {
    "id": "38b4b429f0044c0b980cfa67cf08fd70",
    "time": "2021-02-05T06:23:35.333Z",
    "type": "completion"
   },
   {
    "id": "ce483e451b454315802c09be073f68b5",
    "time": "2021-02-05T06:23:35.361Z",
    "type": "completion"
   },
   {
    "code": "import re\nimport urllib2\nfrom bs4 import BeautifulSoup\n\npage = urllib.urlopen(url)\npage_html = BeautifulSoup(page, 'html.parser')\npage_html.find(attrs={'class': 'meter-value superPageFontColor'})",
    "id": "ce483e451b454315802c09be073f68b5",
    "idx": 7,
    "time": "2021-02-05T06:24:06.092Z",
    "type": "execution"
   },
   {
    "id": "ce483e451b454315802c09be073f68b5",
    "time": "2021-02-05T06:24:06.178Z",
    "type": "completion"
   },
   {
    "code": "import re\nimport urllib2\nfrom bs4 import BeautifulSoup\n\npage = urlopen(request)\npage_html = BeautifulSoup(page, 'html.parser')\npage_html.find(attrs={'class': 'meter-value superPageFontColor'})",
    "id": "ce483e451b454315802c09be073f68b5",
    "idx": 7,
    "time": "2021-02-05T06:24:42.285Z",
    "type": "execution"
   },
   {
    "id": "ce483e451b454315802c09be073f68b5",
    "time": "2021-02-05T06:24:42.391Z",
    "type": "completion"
   },
   {
    "code": "import re\n# import urllib2\nfrom bs4 import BeautifulSoup\n\npage = urlopen(request)\npage_html = BeautifulSoup(page, 'html.parser')\npage_html.find(attrs={'class': 'meter-value superPageFontColor'})",
    "id": "ce483e451b454315802c09be073f68b5",
    "idx": 7,
    "time": "2021-02-05T06:24:46.611Z",
    "type": "execution"
   },
   {
    "id": "ce483e451b454315802c09be073f68b5",
    "time": "2021-02-05T06:24:48.017Z",
    "type": "completion"
   },
   {
    "code": "import re\n# import urllib2\nfrom bs4 import BeautifulSoup\n\npage = urlopen(request)\npage_html = BeautifulSoup(page, 'html.parser')\npage_html.find(attrs={'class': 'meter-value superPageFontColor'})\nbs.find_all('span', class_='mop-ratings-wrap__percentage')",
    "id": "ce483e451b454315802c09be073f68b5",
    "idx": 7,
    "time": "2021-02-05T06:27:53.377Z",
    "type": "execution"
   },
   {
    "id": "ce483e451b454315802c09be073f68b5",
    "time": "2021-02-05T06:27:54.407Z",
    "type": "completion"
   },
   {
    "code": "import re\n# import urllib2\nfrom bs4 import BeautifulSoup\n\npage = urlopen(request)\npage_html = BeautifulSoup(page, 'html.parser')\npage_html.find(attrs={'class': 'meter-value superPageFontColor'})\nbs.find_all('span')",
    "id": "ce483e451b454315802c09be073f68b5",
    "idx": 7,
    "time": "2021-02-05T06:28:06.167Z",
    "type": "execution"
   },
   {
    "id": "ce483e451b454315802c09be073f68b5",
    "time": "2021-02-05T06:28:06.933Z",
    "type": "completion"
   },
   {
    "code": "import re\n# import urllib2\nfrom bs4 import BeautifulSoup\n\npage = urlopen(request)\npage_html = BeautifulSoup(page, 'html.parser')\npage_html.find(attrs={'class': 'meter-value superPageFontColor'})\nbs.find_all('div')",
    "id": "ce483e451b454315802c09be073f68b5",
    "idx": 7,
    "time": "2021-02-05T06:29:19.588Z",
    "type": "execution"
   },
   {
    "id": "ce483e451b454315802c09be073f68b5",
    "time": "2021-02-05T06:29:19.876Z",
    "type": "completion"
   },
   {
    "code": "import re\n# import urllib2\nfrom bs4 import BeautifulSoup\n\npage = urlopen(request)\npage_html = BeautifulSoup(page, 'html.parser')\npage_html.find(attrs={'class': 'meter-value superPageFontColor'})\nbs.find_all('div')",
    "id": "ce483e451b454315802c09be073f68b5",
    "idx": 7,
    "time": "2021-02-05T06:29:30.317Z",
    "type": "execution"
   },
   {
    "id": "ce483e451b454315802c09be073f68b5",
    "time": "2021-02-05T06:29:30.521Z",
    "type": "completion"
   },
   {
    "code": "import re\n# import urllib2\nfrom bs4 import BeautifulSoup\n\n# page = urlopen(request)\n# page_html = BeautifulSoup(page, 'html.parser')\n# page_html.find(attrs={'class': 'meter-value superPageFontColor'})\nbs.find_all('div')",
    "id": "ce483e451b454315802c09be073f68b5",
    "idx": 7,
    "time": "2021-02-05T06:29:53.585Z",
    "type": "execution"
   },
   {
    "id": "ce483e451b454315802c09be073f68b5",
    "time": "2021-02-05T06:29:55.935Z",
    "type": "completion"
   },
   {
    "code": "str(bs)",
    "id": "e3671c3387cc48f78e583961113b1a79",
    "idx": 8,
    "time": "2021-02-05T06:31:50.187Z",
    "type": "execution"
   },
   {
    "id": "e3671c3387cc48f78e583961113b1a79",
    "time": "2021-02-05T06:31:50.755Z",
    "type": "completion"
   },
   {
    "code": "str(bs).find(\"aggregateRating\")",
    "id": "e3671c3387cc48f78e583961113b1a79",
    "idx": 8,
    "time": "2021-02-05T06:33:43.230Z",
    "type": "execution"
   },
   {
    "id": "e3671c3387cc48f78e583961113b1a79",
    "time": "2021-02-05T06:33:43.369Z",
    "type": "completion"
   },
   {
    "code": "bs.find(\"aggregateRating\")",
    "id": "e3671c3387cc48f78e583961113b1a79",
    "idx": 8,
    "time": "2021-02-05T06:33:51.012Z",
    "type": "execution"
   },
   {
    "id": "e3671c3387cc48f78e583961113b1a79",
    "time": "2021-02-05T06:33:51.090Z",
    "type": "completion"
   },
   {
    "code": "str(bs).find(\"aggregateRatign\")",
    "id": "e3671c3387cc48f78e583961113b1a79",
    "idx": 8,
    "time": "2021-02-05T06:33:57.890Z",
    "type": "execution"
   },
   {
    "id": "e3671c3387cc48f78e583961113b1a79",
    "time": "2021-02-05T06:33:58.024Z",
    "type": "completion"
   },
   {
    "code": "str(bs).find(\"aggregateRating\")",
    "id": "e3671c3387cc48f78e583961113b1a79",
    "idx": 8,
    "time": "2021-02-05T06:34:01.754Z",
    "type": "execution"
   },
   {
    "id": "e3671c3387cc48f78e583961113b1a79",
    "time": "2021-02-05T06:34:01.877Z",
    "type": "completion"
   },
   {
    "code": "str(bs)[str(bs).find(\"aggregateRating\")]",
    "id": "e3671c3387cc48f78e583961113b1a79",
    "idx": 8,
    "time": "2021-02-05T06:34:21.006Z",
    "type": "execution"
   },
   {
    "id": "e3671c3387cc48f78e583961113b1a79",
    "time": "2021-02-05T06:34:21.192Z",
    "type": "completion"
   },
   {
    "code": "str(bs)[str(bs).find(\"aggregateRating\"):]",
    "id": "e3671c3387cc48f78e583961113b1a79",
    "idx": 8,
    "time": "2021-02-05T06:34:26.042Z",
    "type": "execution"
   },
   {
    "id": "e3671c3387cc48f78e583961113b1a79",
    "time": "2021-02-05T06:34:26.846Z",
    "type": "completion"
   },
   {
    "code": "# str(bs)[str(bs).find(\"aggregateRating\"):]",
    "id": "e3671c3387cc48f78e583961113b1a79",
    "idx": 8,
    "time": "2021-02-05T06:35:40.985Z",
    "type": "execution"
   },
   {
    "id": "e3671c3387cc48f78e583961113b1a79",
    "time": "2021-02-05T06:35:41.054Z",
    "type": "completion"
   },
   {
    "code": "import re\n# import urllib2\nfrom bs4 import BeautifulSoup\n\n# page = urlopen(request)\n# page_html = BeautifulSoup(page, 'html.parser')\n# page_html.find(attrs={'class': 'meter-value superPageFontColor'})\nbs.find_all('div')",
    "id": "ce483e451b454315802c09be073f68b5",
    "idx": 7,
    "time": "2021-02-05T06:35:43.365Z",
    "type": "execution"
   },
   {
    "id": "ce483e451b454315802c09be073f68b5",
    "time": "2021-02-05T06:35:45.901Z",
    "type": "completion"
   },
   {
    "code": "import urllib\nfrom urllib.request import urlopen\nfrom bs4 import BeautifulSoup\nurl = 'https://www.rottentomatoes.com/m/wonder_woman_1984/'\nrequest=urllib.request.Request(url)\nbs = BeautifulSoup(urlopen(request), \"html.parser\")\n# bs",
    "id": "da09a38bbe684a87ba590b6abe70cfea",
    "idx": 1,
    "time": "2021-02-05T06:36:18.527Z",
    "type": "execution"
   },
   {
    "id": "da09a38bbe684a87ba590b6abe70cfea",
    "time": "2021-02-05T06:36:20.062Z",
    "type": "completion"
   },
   {
    "code": "import re\n# import urllib2\nfrom bs4 import BeautifulSoup\n\n# page = urlopen(request)\n# page_html = BeautifulSoup(page, 'html.parser')\n# page_html.find(attrs={'class': 'meter-value superPageFontColor'})\nbs",
    "id": "ce483e451b454315802c09be073f68b5",
    "idx": 7,
    "time": "2021-02-05T06:36:26.866Z",
    "type": "execution"
   },
   {
    "id": "ce483e451b454315802c09be073f68b5",
    "time": "2021-02-05T06:36:27.732Z",
    "type": "completion"
   },
   {
    "code": "bs.find(\"score-board\")",
    "id": "244db51c894c4bc38ba069d0c1fbdf46",
    "idx": 9,
    "time": "2021-02-05T06:37:21.365Z",
    "type": "execution"
   },
   {
    "id": "244db51c894c4bc38ba069d0c1fbdf46",
    "time": "2021-02-05T06:37:21.459Z",
    "type": "completion"
   },
   {
    "code": "bs.find(\"score-board\")[\"audiencescore\"]",
    "id": "244db51c894c4bc38ba069d0c1fbdf46",
    "idx": 9,
    "time": "2021-02-05T06:38:39.159Z",
    "type": "execution"
   },
   {
    "id": "244db51c894c4bc38ba069d0c1fbdf46",
    "time": "2021-02-05T06:38:39.248Z",
    "type": "completion"
   },
   {
    "code": "int(bs.find(\"score-board\")[\"audiencescore\"])",
    "id": "244db51c894c4bc38ba069d0c1fbdf46",
    "idx": 9,
    "time": "2021-02-05T06:38:49.829Z",
    "type": "execution"
   },
   {
    "id": "244db51c894c4bc38ba069d0c1fbdf46",
    "time": "2021-02-05T06:38:49.909Z",
    "type": "completion"
   },
   {
    "code": "bs.find(\"score-board\")",
    "id": "244db51c894c4bc38ba069d0c1fbdf46",
    "idx": 9,
    "time": "2021-02-05T06:38:58.841Z",
    "type": "execution"
   },
   {
    "id": "244db51c894c4bc38ba069d0c1fbdf46",
    "time": "2021-02-05T06:38:58.919Z",
    "type": "completion"
   },
   {
    "code": "def get_score(url):\n    request=urllib.request.Request(url)\n    bs = BeautifulSoup(urlopen(request), \"html.parser\")\n    scores = bs.find(\"score-board\")\n    return [scores[\"tomatometerscore\"], scores[\"audiencescore\"]]",
    "id": "0eb3e081a03146c5ac6ff99da77f93cb",
    "idx": 2,
    "time": "2021-02-05T06:40:29.443Z",
    "type": "execution"
   },
   {
    "id": "0eb3e081a03146c5ac6ff99da77f93cb",
    "time": "2021-02-05T06:40:29.516Z",
    "type": "completion"
   },
   {
    "code": "get_score(url)",
    "id": "c607f78a3ce9480fae641c3deec5e273",
    "idx": 3,
    "time": "2021-02-05T06:40:34.234Z",
    "type": "execution"
   },
   {
    "id": "c607f78a3ce9480fae641c3deec5e273",
    "time": "2021-02-05T06:40:35.468Z",
    "type": "completion"
   },
   {
    "code": "def get_score(url):\n    request=urllib.request.Request(url)\n    bs = BeautifulSoup(urlopen(request), \"html.parser\")\n    scores = bs.find(\"score-board\")\n    return [int(scores[\"tomatometerscore\"]), int(scores[\"audiencescore\"])]",
    "id": "0eb3e081a03146c5ac6ff99da77f93cb",
    "idx": 2,
    "time": "2021-02-05T06:40:45.225Z",
    "type": "execution"
   },
   {
    "id": "0eb3e081a03146c5ac6ff99da77f93cb",
    "time": "2021-02-05T06:40:45.294Z",
    "type": "completion"
   },
   {
    "code": "get_score(url)",
    "id": "c607f78a3ce9480fae641c3deec5e273",
    "idx": 3,
    "time": "2021-02-05T06:40:45.504Z",
    "type": "execution"
   },
   {
    "id": "c607f78a3ce9480fae641c3deec5e273",
    "time": "2021-02-05T06:40:46.088Z",
    "type": "completion"
   },
   {
    "code": "!pip install git+https://github.com/akamhy/waybackpy.git",
    "id": "ea5cfa4916cf440db1e5535f95175294",
    "idx": 4,
    "time": "2021-02-05T06:41:13.861Z",
    "type": "execution"
   },
   {
    "id": "ea5cfa4916cf440db1e5535f95175294",
    "time": "2021-02-05T06:41:20.592Z",
    "type": "completion"
   },
   {
    "code": "wayback = waybackpy.Url(url, user_agent)\n\narchive = wayback.oldest()\narchive.archive_url",
    "id": "5b56df1a7d194733a16d0e401953dd00",
    "idx": 5,
    "time": "2021-02-05T06:42:29.364Z",
    "type": "execution"
   },
   {
    "id": "5b56df1a7d194733a16d0e401953dd00",
    "time": "2021-02-05T06:42:29.462Z",
    "type": "completion"
   },
   {
    "code": "import waybackpy\n\nwayback = waybackpy.Url(url, user_agent)\n\narchive = wayback.oldest()\narchive.archive_url",
    "id": "5b56df1a7d194733a16d0e401953dd00",
    "idx": 5,
    "time": "2021-02-05T06:42:46.500Z",
    "type": "execution"
   },
   {
    "id": "5b56df1a7d194733a16d0e401953dd00",
    "time": "2021-02-05T06:42:46.591Z",
    "type": "completion"
   },
   {
    "code": "import waybackpy\n\nuser_agent = \"Mozilla/5.0 (Windows NT 5.1; rv:40.0) Gecko/20100101 Firefox/40.0\"\nwayback = waybackpy.Url(url, user_agent)\n\narchive = wayback.oldest()\narchive.archive_url",
    "id": "5b56df1a7d194733a16d0e401953dd00",
    "idx": 5,
    "time": "2021-02-05T06:43:01.261Z",
    "type": "execution"
   },
   {
    "id": "5b56df1a7d194733a16d0e401953dd00",
    "time": "2021-02-05T06:43:01.972Z",
    "type": "completion"
   },
   {
    "code": "get_score('https://web.archive.org/web/20190411022605/https://www.rottentomatoes.com/m/wonder_woman_1984')",
    "id": "24c93081a522437a89158f2902d7c599",
    "idx": 6,
    "time": "2021-02-05T06:43:14.406Z",
    "type": "execution"
   },
   {
    "id": "24c93081a522437a89158f2902d7c599",
    "time": "2021-02-05T06:43:16.622Z",
    "type": "completion"
   },
   {
    "code": "wayback.near(year=2020, month=12, day=15)",
    "id": "24c93081a522437a89158f2902d7c599",
    "idx": 6,
    "time": "2021-02-05T06:44:52.165Z",
    "type": "execution"
   },
   {
    "id": "24c93081a522437a89158f2902d7c599",
    "time": "2021-02-05T06:44:52.975Z",
    "type": "completion"
   },
   {
    "code": "wayback.near(year=2020, month=12, day=15).archive_url",
    "id": "24c93081a522437a89158f2902d7c599",
    "idx": 6,
    "time": "2021-02-05T06:44:59.849Z",
    "type": "execution"
   },
   {
    "id": "24c93081a522437a89158f2902d7c599",
    "time": "2021-02-05T06:45:00.126Z",
    "type": "completion"
   },
   {
    "code": "get_score('https://web.archive.org/web/20201215185808/https://www.rottentomatoes.com/m/wonder_woman_1984')",
    "id": "438624b5da1745a3a6f94828a4d54da9",
    "idx": 7,
    "time": "2021-02-05T06:45:11.473Z",
    "type": "execution"
   },
   {
    "id": "438624b5da1745a3a6f94828a4d54da9",
    "time": "2021-02-05T06:45:13.311Z",
    "type": "completion"
   },
   {
    "code": "wayback.near(year=2020, month=12, day=16).archive_url",
    "id": "24c93081a522437a89158f2902d7c599",
    "idx": 6,
    "time": "2021-02-05T06:45:18.480Z",
    "type": "execution"
   },
   {
    "id": "24c93081a522437a89158f2902d7c599",
    "time": "2021-02-05T06:45:18.988Z",
    "type": "completion"
   },
   {
    "code": "get_score('https://web.archive.org/web/20201216005513/https://www.rottentomatoes.com/m/wonder_woman_1984')",
    "id": "438624b5da1745a3a6f94828a4d54da9",
    "idx": 7,
    "time": "2021-02-05T06:45:32.268Z",
    "type": "execution"
   },
   {
    "id": "438624b5da1745a3a6f94828a4d54da9",
    "time": "2021-02-05T06:45:34.047Z",
    "type": "completion"
   },
   {
    "code": "def get_score(url):\n    request=urllib.request.Request(url)\n    bs = BeautifulSoup(urlopen(request), \"html.parser\")\n    scores = bs.find(\"score-board\")\n    print(scores)\n    return [int(scores[\"tomatometerscore\"]), int(scores[\"audiencescore\"])]",
    "id": "0eb3e081a03146c5ac6ff99da77f93cb",
    "idx": 2,
    "time": "2021-02-05T06:46:21.393Z",
    "type": "execution"
   },
   {
    "id": "0eb3e081a03146c5ac6ff99da77f93cb",
    "time": "2021-02-05T06:46:21.461Z",
    "type": "completion"
   },
   {
    "code": "get_score('https://web.archive.org/web/20201216005513/https://www.rottentomatoes.com/m/wonder_woman_1984')",
    "id": "438624b5da1745a3a6f94828a4d54da9",
    "idx": 7,
    "time": "2021-02-05T06:46:24.501Z",
    "type": "execution"
   },
   {
    "id": "438624b5da1745a3a6f94828a4d54da9",
    "time": "2021-02-05T06:46:25.243Z",
    "type": "completion"
   },
   {
    "code": "def get_score(url):\n    request=urllib.request.Request(url)\n    bs = BeautifulSoup(urlopen(request), \"html.parser\")\n    print(bs)\n    scores = bs.find(\"score-board\")\n    print(scores)\n    return [int(scores[\"tomatometerscore\"]), int(scores[\"audiencescore\"])]",
    "id": "0eb3e081a03146c5ac6ff99da77f93cb",
    "idx": 2,
    "time": "2021-02-05T06:46:39.419Z",
    "type": "execution"
   },
   {
    "id": "0eb3e081a03146c5ac6ff99da77f93cb",
    "time": "2021-02-05T06:46:39.488Z",
    "type": "completion"
   },
   {
    "code": "get_score('https://web.archive.org/web/20201216005513/https://www.rottentomatoes.com/m/wonder_woman_1984')",
    "id": "438624b5da1745a3a6f94828a4d54da9",
    "idx": 7,
    "time": "2021-02-05T06:46:41.815Z",
    "type": "execution"
   },
   {
    "id": "438624b5da1745a3a6f94828a4d54da9",
    "time": "2021-02-05T06:46:43.112Z",
    "type": "completion"
   },
   {
    "code": "bs.find(\"span\",class_=\"mop-ratings-wrap__percentage\")",
    "id": "62d09d13aa7a48228f7d63f362c6085c",
    "idx": 8,
    "time": "2021-02-05T06:47:57.598Z",
    "type": "execution"
   },
   {
    "id": "62d09d13aa7a48228f7d63f362c6085c",
    "time": "2021-02-05T06:47:57.688Z",
    "type": "completion"
   },
   {
    "code": "bs.find(\"span\",class_=\"mop-ratings-wrap__percentage\")",
    "id": "62d09d13aa7a48228f7d63f362c6085c",
    "idx": 8,
    "time": "2021-02-05T06:48:06.745Z",
    "type": "execution"
   },
   {
    "id": "62d09d13aa7a48228f7d63f362c6085c",
    "time": "2021-02-05T06:48:06.825Z",
    "type": "completion"
   },
   {
    "code": "bs.find(\"span\", {\"class\":\"mop-ratings-wrap__percentage\"})",
    "id": "62d09d13aa7a48228f7d63f362c6085c",
    "idx": 8,
    "time": "2021-02-05T06:48:14.983Z",
    "type": "execution"
   },
   {
    "id": "62d09d13aa7a48228f7d63f362c6085c",
    "time": "2021-02-05T06:48:15.061Z",
    "type": "completion"
   },
   {
    "code": "bs.find_all(\"span\", {\"class\":\"mop-ratings-wrap__percentage\"})",
    "id": "62d09d13aa7a48228f7d63f362c6085c",
    "idx": 8,
    "time": "2021-02-05T06:48:17.765Z",
    "type": "execution"
   },
   {
    "id": "62d09d13aa7a48228f7d63f362c6085c",
    "time": "2021-02-05T06:48:17.855Z",
    "type": "completion"
   },
   {
    "code": "bs.find_all(\"section\")",
    "id": "62d09d13aa7a48228f7d63f362c6085c",
    "idx": 8,
    "time": "2021-02-05T06:48:39.990Z",
    "type": "execution"
   },
   {
    "id": "62d09d13aa7a48228f7d63f362c6085c",
    "time": "2021-02-05T06:48:40.604Z",
    "type": "completion"
   },
   {
    "code": "bs.find_all(\"section\", {\"class\":\"mop-ratings-wrap__info\"})",
    "id": "62d09d13aa7a48228f7d63f362c6085c",
    "idx": 8,
    "time": "2021-02-05T06:49:13.645Z",
    "type": "execution"
   },
   {
    "id": "62d09d13aa7a48228f7d63f362c6085c",
    "time": "2021-02-05T06:49:13.728Z",
    "type": "completion"
   },
   {
    "code": "bs.find_all(\"section\")",
    "id": "62d09d13aa7a48228f7d63f362c6085c",
    "idx": 8,
    "time": "2021-02-05T06:49:19.527Z",
    "type": "execution"
   },
   {
    "id": "62d09d13aa7a48228f7d63f362c6085c",
    "time": "2021-02-05T06:49:20.141Z",
    "type": "completion"
   },
   {
    "code": "bs.find_all(\"section\", class_=\"mop-ratings-wrap__row js-scoreboard-container\")",
    "id": "62d09d13aa7a48228f7d63f362c6085c",
    "idx": 8,
    "time": "2021-02-05T06:50:19.968Z",
    "type": "execution"
   },
   {
    "id": "62d09d13aa7a48228f7d63f362c6085c",
    "time": "2021-02-05T06:50:20.056Z",
    "type": "completion"
   },
   {
    "code": "bs",
    "id": "3aad245f44864caebf9930cff6ea06b5",
    "idx": 9,
    "time": "2021-02-05T06:50:24.517Z",
    "type": "execution"
   },
   {
    "id": "3aad245f44864caebf9930cff6ea06b5",
    "time": "2021-02-05T06:50:25.361Z",
    "type": "completion"
   },
   {
    "code": "get_score(\"https://web.archive.org/web/20201229011903/https://www.rottentomatoes.com/m/wonder_woman_1984\")",
    "id": "1a26c24c2134477d8b7e36108b63516f",
    "idx": 10,
    "time": "2021-02-05T06:52:48.009Z",
    "type": "execution"
   },
   {
    "id": "1a26c24c2134477d8b7e36108b63516f",
    "time": "2021-02-05T06:52:49.335Z",
    "type": "completion"
   },
   {
    "code": "# bs",
    "id": "3aad245f44864caebf9930cff6ea06b5",
    "idx": 9,
    "time": "2021-02-05T06:53:14.373Z",
    "type": "execution"
   },
   {
    "id": "3aad245f44864caebf9930cff6ea06b5",
    "time": "2021-02-05T06:53:14.441Z",
    "type": "completion"
   },
   {
    "code": "# get_score('https://web.archive.org/web/20201216005513/https://www.rottentomatoes.com/m/wonder_woman_1984')",
    "id": "438624b5da1745a3a6f94828a4d54da9",
    "idx": 7,
    "time": "2021-02-05T06:53:17.458Z",
    "type": "execution"
   },
   {
    "id": "438624b5da1745a3a6f94828a4d54da9",
    "time": "2021-02-05T06:53:17.527Z",
    "type": "completion"
   },
   {
    "code": "str(bs).find('<span class=\"mop-ratings-wrap__percentage\">')",
    "id": "89c681a557204bd988ae7ac7da7f8185",
    "idx": 11,
    "time": "2021-02-05T06:54:14.982Z",
    "type": "execution"
   },
   {
    "id": "89c681a557204bd988ae7ac7da7f8185",
    "time": "2021-02-05T06:54:15.112Z",
    "type": "completion"
   },
   {
    "code": "bs.find_all(\"a\")",
    "id": "60086916b39046cfb0f9546fac7da73a",
    "idx": 12,
    "time": "2021-02-05T06:54:44.569Z",
    "type": "execution"
   },
   {
    "id": "60086916b39046cfb0f9546fac7da73a",
    "time": "2021-02-05T06:54:44.845Z",
    "type": "completion"
   },
   {
    "code": "str(bs).find('aggregateRating')",
    "id": "89c681a557204bd988ae7ac7da7f8185",
    "idx": 11,
    "time": "2021-02-05T06:55:39.140Z",
    "type": "execution"
   },
   {
    "id": "89c681a557204bd988ae7ac7da7f8185",
    "time": "2021-02-05T06:55:39.265Z",
    "type": "completion"
   },
   {
    "code": "str(bs)[4345:]",
    "id": "2ef0f1c6489445858d96ddde7e60f5b1",
    "idx": 12,
    "time": "2021-02-05T06:56:02.466Z",
    "type": "execution"
   },
   {
    "id": "2ef0f1c6489445858d96ddde7e60f5b1",
    "time": "2021-02-05T06:56:03.262Z",
    "type": "completion"
   },
   {
    "code": "str(bs).find('ratingValue')",
    "id": "89c681a557204bd988ae7ac7da7f8185",
    "idx": 11,
    "time": "2021-02-05T06:56:14.192Z",
    "type": "execution"
   },
   {
    "id": "89c681a557204bd988ae7ac7da7f8185",
    "time": "2021-02-05T06:56:14.359Z",
    "type": "completion"
   },
   {
    "code": "str(bs)[4770:]",
    "id": "2ef0f1c6489445858d96ddde7e60f5b1",
    "idx": 12,
    "time": "2021-02-05T06:56:20.699Z",
    "type": "execution"
   },
   {
    "id": "2ef0f1c6489445858d96ddde7e60f5b1",
    "time": "2021-02-05T06:56:21.360Z",
    "type": "completion"
   },
   {
    "code": "str(bs)[4783:]",
    "id": "2ef0f1c6489445858d96ddde7e60f5b1",
    "idx": 12,
    "time": "2021-02-05T06:57:26.200Z",
    "type": "execution"
   },
   {
    "id": "2ef0f1c6489445858d96ddde7e60f5b1",
    "time": "2021-02-05T06:57:26.887Z",
    "type": "completion"
   },
   {
    "code": "str(bs)[4783:4789]",
    "id": "2ef0f1c6489445858d96ddde7e60f5b1",
    "idx": 12,
    "time": "2021-02-05T06:57:42.433Z",
    "type": "execution"
   },
   {
    "id": "2ef0f1c6489445858d96ddde7e60f5b1",
    "time": "2021-02-05T06:57:42.592Z",
    "type": "completion"
   },
   {
    "code": "str(bs)[4783:]",
    "id": "2ef0f1c6489445858d96ddde7e60f5b1",
    "idx": 12,
    "time": "2021-02-05T06:57:52.014Z",
    "type": "execution"
   },
   {
    "id": "2ef0f1c6489445858d96ddde7e60f5b1",
    "time": "2021-02-05T06:57:52.742Z",
    "type": "completion"
   },
   {
    "code": "str(bs)[4783:].find('ratingValue')",
    "id": "2ef0f1c6489445858d96ddde7e60f5b1",
    "idx": 12,
    "time": "2021-02-05T06:58:00.532Z",
    "type": "execution"
   },
   {
    "id": "2ef0f1c6489445858d96ddde7e60f5b1",
    "time": "2021-02-05T06:58:00.653Z",
    "type": "completion"
   },
   {
    "code": "4783+522",
    "id": "2cfe97fe13ff4c258a09576761e43105",
    "idx": 13,
    "time": "2021-02-05T06:58:08.802Z",
    "type": "execution"
   },
   {
    "id": "2cfe97fe13ff4c258a09576761e43105",
    "time": "2021-02-05T06:58:08.877Z",
    "type": "completion"
   },
   {
    "code": "str(bs)[5305:]",
    "id": "2cfe97fe13ff4c258a09576761e43105",
    "idx": 13,
    "time": "2021-02-05T06:58:16.005Z",
    "type": "execution"
   },
   {
    "id": "2cfe97fe13ff4c258a09576761e43105",
    "time": "2021-02-05T06:58:16.806Z",
    "type": "completion"
   },
   {
    "code": "str(bs)[4783:].find('aggregateRating')",
    "id": "2ef0f1c6489445858d96ddde7e60f5b1",
    "idx": 12,
    "time": "2021-02-05T06:58:43.951Z",
    "type": "execution"
   },
   {
    "id": "2ef0f1c6489445858d96ddde7e60f5b1",
    "time": "2021-02-05T06:58:44.086Z",
    "type": "completion"
   },
   {
    "code": "str(bs).find('aggregateRating')",
    "id": "2ef0f1c6489445858d96ddde7e60f5b1",
    "idx": 12,
    "time": "2021-02-05T06:58:54.304Z",
    "type": "execution"
   },
   {
    "id": "2ef0f1c6489445858d96ddde7e60f5b1",
    "time": "2021-02-05T06:58:54.432Z",
    "type": "completion"
   },
   {
    "code": "str(bs)[4345:]",
    "id": "2cfe97fe13ff4c258a09576761e43105",
    "idx": 13,
    "time": "2021-02-05T06:59:06.529Z",
    "type": "execution"
   },
   {
    "id": "2cfe97fe13ff4c258a09576761e43105",
    "time": "2021-02-05T06:59:07.222Z",
    "type": "completion"
   },
   {
    "code": "bs.find(attrs={'class': 'meter-value superPageFontColor'})",
    "id": "2fe3d216885d4ab784781fddeaea4b8e",
    "idx": 14,
    "time": "2021-02-05T07:01:55.321Z",
    "type": "execution"
   },
   {
    "id": "2fe3d216885d4ab784781fddeaea4b8e",
    "time": "2021-02-05T07:01:55.420Z",
    "type": "completion"
   },
   {
    "code": "bs.find_all(\"section\")",
    "id": "2f68c860462b4d238a75d60695fa7e33",
    "idx": 15,
    "time": "2021-02-05T07:02:15.046Z",
    "type": "execution"
   },
   {
    "id": "2f68c860462b4d238a75d60695fa7e33",
    "time": "2021-02-05T07:02:15.621Z",
    "type": "completion"
   },
   {
    "code": "bs.find_all(\"section\")[1:]",
    "id": "2f68c860462b4d238a75d60695fa7e33",
    "idx": 15,
    "time": "2021-02-05T07:02:30.234Z",
    "type": "execution"
   },
   {
    "id": "2f68c860462b4d238a75d60695fa7e33",
    "time": "2021-02-05T07:02:30.597Z",
    "type": "completion"
   },
   {
    "code": "bs.find_all(\"section\")[2:]",
    "id": "2f68c860462b4d238a75d60695fa7e33",
    "idx": 15,
    "time": "2021-02-05T07:02:37.538Z",
    "type": "execution"
   },
   {
    "id": "2f68c860462b4d238a75d60695fa7e33",
    "time": "2021-02-05T07:02:37.899Z",
    "type": "completion"
   },
   {
    "code": "bs.find_all(\"section\")[3:]",
    "id": "2f68c860462b4d238a75d60695fa7e33",
    "idx": 15,
    "time": "2021-02-05T07:02:47.338Z",
    "type": "execution"
   },
   {
    "id": "2f68c860462b4d238a75d60695fa7e33",
    "time": "2021-02-05T07:02:47.678Z",
    "type": "completion"
   },
   {
    "code": "bs.find_all(\"section\")[4:]",
    "id": "2f68c860462b4d238a75d60695fa7e33",
    "idx": 15,
    "time": "2021-02-05T07:02:51.165Z",
    "type": "execution"
   },
   {
    "id": "2f68c860462b4d238a75d60695fa7e33",
    "time": "2021-02-05T07:02:51.472Z",
    "type": "completion"
   },
   {
    "code": "site = urlopen(url)\n#site = urlopen(\"https://www.rottentomatoes.com/m/the_lord_of_the_rings_the_fellowship_of_the_ring\")\nmovie = bs(site.read(), features=\"lxml\")\nfor rating in movie.find_all('span', class_='mop-ratings-wrap__percentage'):\n    print(rating.get_text())",
    "id": "c487a9143608456d8128ec2231e2995a",
    "idx": 16,
    "time": "2021-02-05T07:05:13.578Z",
    "type": "execution"
   },
   {
    "id": "c487a9143608456d8128ec2231e2995a",
    "time": "2021-02-05T07:05:14.031Z",
    "type": "completion"
   },
   {
    "code": "site = urlopen(url)\n#site = urlopen(\"https://www.rottentomatoes.com/m/the_lord_of_the_rings_the_fellowship_of_the_ring\")\nmovie = bs(site.read(), features=\"lxml\")\nmovie.find_all('span', class_='mop-ratings-wrap__percentage')",
    "id": "c487a9143608456d8128ec2231e2995a",
    "idx": 16,
    "time": "2021-02-05T07:05:37.811Z",
    "type": "execution"
   },
   {
    "id": "c487a9143608456d8128ec2231e2995a",
    "time": "2021-02-05T07:05:38.803Z",
    "type": "completion"
   },
   {
    "code": "movie",
    "id": "365dd0da236042ee9dc2e3ad8da4f95a",
    "idx": 17,
    "time": "2021-02-05T07:05:49.906Z",
    "type": "execution"
   },
   {
    "id": "365dd0da236042ee9dc2e3ad8da4f95a",
    "time": "2021-02-05T07:05:49.981Z",
    "type": "completion"
   },
   {
    "code": "site",
    "id": "365dd0da236042ee9dc2e3ad8da4f95a",
    "idx": 17,
    "time": "2021-02-05T07:05:56.404Z",
    "type": "execution"
   },
   {
    "id": "365dd0da236042ee9dc2e3ad8da4f95a",
    "time": "2021-02-05T07:05:56.474Z",
    "type": "completion"
   },
   {
    "code": "site.read()",
    "id": "365dd0da236042ee9dc2e3ad8da4f95a",
    "idx": 17,
    "time": "2021-02-05T07:06:03.179Z",
    "type": "execution"
   },
   {
    "id": "365dd0da236042ee9dc2e3ad8da4f95a",
    "time": "2021-02-05T07:06:03.257Z",
    "type": "completion"
   },
   {
    "code": "bs",
    "id": "365dd0da236042ee9dc2e3ad8da4f95a",
    "idx": 17,
    "time": "2021-02-05T07:12:02.940Z",
    "type": "execution"
   },
   {
    "code": "import urllib\nfrom urllib.request import urlopen\nfrom bs4 import BeautifulSoup\nurl = 'https://www.rottentomatoes.com/m/wonder_woman_1984/'\nrequest=urllib.request.Request(url)\nbs = BeautifulSoup(urlopen(request), \"html.parser\")\n# bs",
    "id": "0b869188566a4a8da2e488aeb605e493",
    "idx": 0,
    "time": "2021-02-05T17:53:57.274Z",
    "type": "execution"
   },
   {
    "code": "bs.find(\"score-board\")",
    "id": "d4fa72150b554f74a94a4e2bb80d2d00",
    "idx": 1,
    "time": "2021-02-05T17:53:58.137Z",
    "type": "execution"
   },
   {
    "code": "def get_score(url):\n    request=urllib.request.Request(url)\n    bs = BeautifulSoup(urlopen(request), \"html.parser\")\n    print(bs)\n    scores = bs.find(\"score-board\")\n    print(scores)\n    return [int(scores[\"tomatometerscore\"]), int(scores[\"audiencescore\"])]",
    "id": "ea8c24808a7d4bb7848179fee03059f3",
    "idx": 2,
    "time": "2021-02-05T17:53:58.969Z",
    "type": "execution"
   },
   {
    "id": "0b869188566a4a8da2e488aeb605e493",
    "time": "2021-02-05T17:53:59.410Z",
    "type": "completion"
   },
   {
    "code": "get_score(url)",
    "id": "274ab24503294b1cba0ce92137e3012c",
    "idx": 3,
    "time": "2021-02-05T17:53:59.429Z",
    "type": "execution"
   },
   {
    "id": "d4fa72150b554f74a94a4e2bb80d2d00",
    "time": "2021-02-05T17:53:59.611Z",
    "type": "completion"
   },
   {
    "id": "ea8c24808a7d4bb7848179fee03059f3",
    "time": "2021-02-05T17:53:59.613Z",
    "type": "completion"
   },
   {
    "code": "!pip install git+https://github.com/akamhy/waybackpy.git",
    "id": "509dc6bb1b6a434885b641fbcd96f90c",
    "idx": 4,
    "time": "2021-02-05T17:54:00.560Z",
    "type": "execution"
   },
   {
    "id": "274ab24503294b1cba0ce92137e3012c",
    "time": "2021-02-05T17:54:00.773Z",
    "type": "completion"
   },
   {
    "code": "import waybackpy\n\nuser_agent = \"Mozilla/5.0 (Windows NT 5.1; rv:40.0) Gecko/20100101 Firefox/40.0\"\nwayback = waybackpy.Url(url, user_agent)\n\narchive = wayback.oldest()\narchive.archive_url",
    "id": "03c99652dc70457a8144022aab1afc92",
    "idx": 5,
    "time": "2021-02-05T17:54:01.279Z",
    "type": "execution"
   },
   {
    "id": "509dc6bb1b6a434885b641fbcd96f90c",
    "time": "2021-02-05T17:54:06.795Z",
    "type": "completion"
   },
   {
    "id": "03c99652dc70457a8144022aab1afc92",
    "time": "2021-02-05T17:54:07.619Z",
    "type": "completion"
   },
   {
    "code": "wayback.near(year=2020, month=12, day=16).archive_url",
    "id": "07413400d8ec492c81f40a44896e6e76",
    "idx": 6,
    "time": "2021-02-05T17:54:22.199Z",
    "type": "execution"
   },
   {
    "id": "07413400d8ec492c81f40a44896e6e76",
    "time": "2021-02-05T17:54:24.143Z",
    "type": "completion"
   },
   {
    "code": "get_score('https://web.archive.org/web/20201216005513/https://www.rottentomatoes.com/m/wonder_woman_1984')",
    "id": "c65ded03406a43a282b87b624165c141",
    "idx": 7,
    "time": "2021-02-05T17:54:26.286Z",
    "type": "execution"
   },
   {
    "id": "c65ded03406a43a282b87b624165c141",
    "time": "2021-02-05T17:54:28.990Z",
    "type": "completion"
   },
   {
    "code": "# get_score('https://web.archive.org/web/20201216005513/https://www.rottentomatoes.com/m/wonder_woman_1984')",
    "id": "c65ded03406a43a282b87b624165c141",
    "idx": 7,
    "time": "2021-02-05T17:54:37.858Z",
    "type": "execution"
   },
   {
    "id": "c65ded03406a43a282b87b624165c141",
    "time": "2021-02-05T17:54:37.926Z",
    "type": "completion"
   },
   {
    "code": "def criticScore(soup):\n    meter = \"meter-value superPageFontColor\"\n    score = soup.find('span', {'class': meter})\n    return score.text",
    "id": "9d12dc19220f4f8b85a8bab128ccb0ff",
    "idx": 9,
    "time": "2021-02-05T17:55:19.908Z",
    "type": "execution"
   },
   {
    "id": "9d12dc19220f4f8b85a8bab128ccb0ff",
    "time": "2021-02-05T17:55:20.014Z",
    "type": "completion"
   },
   {
    "code": "criticScore(bs)",
    "id": "953a2e2c456e43a4af66113214bcae1f",
    "idx": 10,
    "time": "2021-02-05T17:55:26.579Z",
    "type": "execution"
   },
   {
    "id": "953a2e2c456e43a4af66113214bcae1f",
    "time": "2021-02-05T17:55:26.690Z",
    "type": "completion"
   },
   {
    "code": "archived = wayback.near(year=2020, month=12, day=16).archive_url\narchived",
    "id": "07413400d8ec492c81f40a44896e6e76",
    "idx": 6,
    "time": "2021-02-05T17:55:41.724Z",
    "type": "execution"
   },
   {
    "id": "07413400d8ec492c81f40a44896e6e76",
    "time": "2021-02-05T17:55:42.301Z",
    "type": "completion"
   },
   {
    "code": "page = requests.get(url).text\nsoup = BeautifulSoup(page, 'lxml')\nsoup",
    "id": "953a2e2c456e43a4af66113214bcae1f",
    "idx": 10,
    "time": "2021-02-05T17:56:27.657Z",
    "type": "execution"
   },
   {
    "id": "953a2e2c456e43a4af66113214bcae1f",
    "time": "2021-02-05T17:56:27.733Z",
    "type": "completion"
   },
   {
    "code": "import requests\npage = requests.get(url).text\nsoup = BeautifulSoup(page, 'lxml')\nsoup",
    "id": "953a2e2c456e43a4af66113214bcae1f",
    "idx": 10,
    "time": "2021-02-05T17:56:38.156Z",
    "type": "execution"
   },
   {
    "id": "953a2e2c456e43a4af66113214bcae1f",
    "time": "2021-02-05T17:56:39.998Z",
    "type": "completion"
   },
   {
    "code": "soup.find('span', {'class': meter})",
    "id": "5a60cb9d5c9845658be9272852bfebae",
    "idx": 11,
    "time": "2021-02-05T17:56:49.452Z",
    "type": "execution"
   },
   {
    "id": "5a60cb9d5c9845658be9272852bfebae",
    "time": "2021-02-05T17:56:49.540Z",
    "type": "completion"
   },
   {
    "code": "soup.find('span', {'class': \"meter-value superPageFontColor\"})",
    "id": "5a60cb9d5c9845658be9272852bfebae",
    "idx": 11,
    "time": "2021-02-05T17:57:00.519Z",
    "type": "execution"
   },
   {
    "id": "5a60cb9d5c9845658be9272852bfebae",
    "time": "2021-02-05T17:57:00.599Z",
    "type": "completion"
   },
   {
    "code": "import requests\npage = requests.get(archived).text\nsoup = BeautifulSoup(page, 'lxml')\nsoup",
    "id": "953a2e2c456e43a4af66113214bcae1f",
    "idx": 10,
    "time": "2021-02-05T17:57:27.324Z",
    "type": "execution"
   },
   {
    "code": "soup.find('span', {'class': \"meter-value superPageFontColor\"})",
    "id": "5a60cb9d5c9845658be9272852bfebae",
    "idx": 11,
    "time": "2021-02-05T17:57:28.071Z",
    "type": "execution"
   },
   {
    "id": "953a2e2c456e43a4af66113214bcae1f",
    "time": "2021-02-05T17:57:29.430Z",
    "type": "completion"
   },
   {
    "id": "5a60cb9d5c9845658be9272852bfebae",
    "time": "2021-02-05T17:57:29.443Z",
    "type": "completion"
   },
   {
    "code": "import requests\narchived = \"http://web.archive.org/web/20181220185920/https://www.rottentomatoes.com/m/star_wars_the_last_jedi/\"\npage = requests.get(archived).text\nsoup = BeautifulSoup(page, 'lxml')\nsoup",
    "id": "953a2e2c456e43a4af66113214bcae1f",
    "idx": 10,
    "time": "2021-02-05T17:58:58.662Z",
    "type": "execution"
   },
   {
    "code": "soup.find('span', {'class': \"meter-value superPageFontColor\"})",
    "id": "5a60cb9d5c9845658be9272852bfebae",
    "idx": 11,
    "time": "2021-02-05T17:58:59.021Z",
    "type": "execution"
   },
   {
    "id": "953a2e2c456e43a4af66113214bcae1f",
    "time": "2021-02-05T17:58:59.708Z",
    "type": "completion"
   },
   {
    "id": "5a60cb9d5c9845658be9272852bfebae",
    "time": "2021-02-05T17:58:59.713Z",
    "type": "completion"
   },
   {
    "code": "soup.find('span', {'class': \"meter-value superPageFontColor\"})\ncriticScore(soup)",
    "id": "5a60cb9d5c9845658be9272852bfebae",
    "idx": 11,
    "time": "2021-02-05T17:59:18.901Z",
    "type": "execution"
   },
   {
    "id": "5a60cb9d5c9845658be9272852bfebae",
    "time": "2021-02-05T17:59:18.985Z",
    "type": "completion"
   },
   {
    "code": "soup.find('span', {'class': \"meter-value superPageFontColor\"})\nint(criticScore(soup))",
    "id": "5a60cb9d5c9845658be9272852bfebae",
    "idx": 11,
    "time": "2021-02-05T17:59:27.490Z",
    "type": "execution"
   },
   {
    "id": "5a60cb9d5c9845658be9272852bfebae",
    "time": "2021-02-05T17:59:27.574Z",
    "type": "completion"
   },
   {
    "code": "soup.find('span', {'class': \"meter-value superPageFontColor\"})\ncriticScore(soup)",
    "id": "5a60cb9d5c9845658be9272852bfebae",
    "idx": 11,
    "time": "2021-02-05T17:59:31.191Z",
    "type": "execution"
   },
   {
    "id": "5a60cb9d5c9845658be9272852bfebae",
    "time": "2021-02-05T17:59:31.286Z",
    "type": "completion"
   },
   {
    "code": "def criticScore(soup):\n    meter = \"meter-value superPageFontColor\"\n    score = soup.find('span', {'class': meter})\n    return score.text\n\ndef audienceScore(soup):\n    audience_meter = \"audience-score meter\"\n    audience_score = \"superPageFontColor\"\n\n    meter = soup.find('div', {'class': audience_meter})\n    score = meter.find('span', {'class': audience_score})\n\n    return score.text",
    "id": "9d12dc19220f4f8b85a8bab128ccb0ff",
    "idx": 9,
    "time": "2021-02-05T18:00:24.613Z",
    "type": "execution"
   },
   {
    "id": "9d12dc19220f4f8b85a8bab128ccb0ff",
    "time": "2021-02-05T18:00:24.687Z",
    "type": "completion"
   },
   {
    "code": "soup.find('span', {'class': \"meter-value superPageFontColor\"})\ncriticScore(soup)\naudienceScore(soup)",
    "id": "5a60cb9d5c9845658be9272852bfebae",
    "idx": 11,
    "time": "2021-02-05T18:00:33.832Z",
    "type": "execution"
   },
   {
    "id": "5a60cb9d5c9845658be9272852bfebae",
    "time": "2021-02-05T18:00:33.943Z",
    "type": "completion"
   },
   {
    "code": "#late 2020\ndef get_score(url):\n    request=urllib.request.Request(url)\n    bs = BeautifulSoup(urlopen(request), \"html.parser\")\n    print(bs)\n    scores = bs.find(\"score-board\")\n    print(scores)\n    return [int(scores[\"tomatometerscore\"]), int(scores[\"audiencescore\"])]",
    "id": "ea8c24808a7d4bb7848179fee03059f3",
    "idx": 2,
    "time": "2021-02-05T18:01:32.763Z",
    "type": "execution"
   },
   {
    "id": "ea8c24808a7d4bb7848179fee03059f3",
    "time": "2021-02-05T18:01:32.837Z",
    "type": "completion"
   },
   {
    "code": "#late 2020\ndef get_score(url):\n    request=urllib.request.Request(url)\n    bs = BeautifulSoup(urlopen(request), \"html.parser\")\n    scores = bs.find(\"score-board\")\n    return [int(scores[\"tomatometerscore\"]), int(scores[\"audiencescore\"])]",
    "id": "ea8c24808a7d4bb7848179fee03059f3",
    "idx": 2,
    "time": "2021-02-05T18:01:41.472Z",
    "type": "execution"
   },
   {
    "id": "ea8c24808a7d4bb7848179fee03059f3",
    "time": "2021-02-05T18:01:41.543Z",
    "type": "completion"
   },
   {
    "code": "archived = wayback.near(year=2020, month=12, day=16).archive_url\narchived",
    "id": "07413400d8ec492c81f40a44896e6e76",
    "idx": 6,
    "time": "2021-02-05T18:02:04.376Z",
    "type": "execution"
   },
   {
    "id": "07413400d8ec492c81f40a44896e6e76",
    "time": "2021-02-05T18:02:04.998Z",
    "type": "completion"
   },
   {
    "code": "import requests\narchived = \"http://web.archive.org/web/20181220185920/https://www.rottentomatoes.com/m/star_wars_the_last_jedi/\"\npage = requests.get(archived).text\nsoup = BeautifulSoup(page, 'lxml')\nsoup",
    "id": "953a2e2c456e43a4af66113214bcae1f",
    "idx": 10,
    "time": "2021-02-05T18:02:20.645Z",
    "type": "execution"
   },
   {
    "id": "953a2e2c456e43a4af66113214bcae1f",
    "time": "2021-02-05T18:02:21.812Z",
    "type": "completion"
   },
   {
    "code": "archived = wayback.near(year=2020, month=12, day=16).archive_url\narchived",
    "id": "07413400d8ec492c81f40a44896e6e76",
    "idx": 6,
    "time": "2021-02-05T18:02:29.166Z",
    "type": "execution"
   },
   {
    "id": "07413400d8ec492c81f40a44896e6e76",
    "time": "2021-02-05T18:02:29.434Z",
    "type": "completion"
   },
   {
    "code": "import requests\n# archived = \"http://web.archive.org/web/20181220185920/https://www.rottentomatoes.com/m/star_wars_the_last_jedi/\"\npage = requests.get(archived).text\nsoup = BeautifulSoup(page, 'lxml')\nsoup",
    "id": "953a2e2c456e43a4af66113214bcae1f",
    "idx": 10,
    "time": "2021-02-05T18:02:30.913Z",
    "type": "execution"
   },
   {
    "id": "953a2e2c456e43a4af66113214bcae1f",
    "time": "2021-02-05T18:02:35.657Z",
    "type": "completion"
   },
   {
    "code": "soup.find('span', {'class': \"meter-value superPageFontColor\"})\ncriticScore(soup)\naudienceScore(soup)",
    "id": "5a60cb9d5c9845658be9272852bfebae",
    "idx": 11,
    "time": "2021-02-05T18:06:10.479Z",
    "type": "execution"
   },
   {
    "id": "5a60cb9d5c9845658be9272852bfebae",
    "time": "2021-02-05T18:06:10.624Z",
    "type": "completion"
   },
   {
    "code": "soup.find_all('div', class_='mop-ratings-wrap__half')",
    "id": "68451771a8c04d44843891eeb873e794",
    "idx": 11,
    "time": "2021-02-05T18:06:19.028Z",
    "type": "execution"
   },
   {
    "id": "68451771a8c04d44843891eeb873e794",
    "time": "2021-02-05T18:06:19.141Z",
    "type": "completion"
   },
   {
    "code": "soup.find_all('div', class_='mop-ratings-wrap__half')[0].text.strip().replace('\\n', '').split(' ')[0]",
    "id": "68451771a8c04d44843891eeb873e794",
    "idx": 11,
    "time": "2021-02-05T18:06:50.015Z",
    "type": "execution"
   },
   {
    "id": "68451771a8c04d44843891eeb873e794",
    "time": "2021-02-05T18:06:50.101Z",
    "type": "completion"
   },
   {
    "code": "#2020\ndef getScore(soup):\n    temp = soup.find_all('div', class_='mop-ratings-wrap__half')\n    critic = temp[0].text.strip().replace('\\n', '').split(' ')[0]\n    audience = temp[1].text.strip().replace('\\n', '').split(' ')[0]\n    return [critic, audience]",
    "id": "68451771a8c04d44843891eeb873e794",
    "idx": 11,
    "time": "2021-02-05T18:08:26.041Z",
    "type": "execution"
   },
   {
    "id": "68451771a8c04d44843891eeb873e794",
    "time": "2021-02-05T18:08:26.114Z",
    "type": "completion"
   },
   {
    "code": "getScore(soup)",
    "id": "9bd938369a3345b784751f47f5093567",
    "idx": 12,
    "time": "2021-02-05T18:08:30.379Z",
    "type": "execution"
   },
   {
    "id": "9bd938369a3345b784751f47f5093567",
    "time": "2021-02-05T18:08:30.463Z",
    "type": "completion"
   },
   {
    "code": "\nwayback.near(year=2020, month=12, day=46).archive_url\n",
    "id": "d07f5e58927d41e29e1d3006eaa1b25d",
    "idx": 12,
    "time": "2021-02-05T18:09:59.807Z",
    "type": "execution"
   },
   {
    "id": "d07f5e58927d41e29e1d3006eaa1b25d",
    "time": "2021-02-05T18:10:02.166Z",
    "type": "completion"
   },
   {
    "code": "\nwayback.near(year=2020, month=12, day=46).archive_url\nrange(16,31)",
    "id": "d07f5e58927d41e29e1d3006eaa1b25d",
    "idx": 12,
    "time": "2021-02-05T18:10:25.826Z",
    "type": "execution"
   },
   {
    "id": "d07f5e58927d41e29e1d3006eaa1b25d",
    "time": "2021-02-05T18:10:26.166Z",
    "type": "completion"
   },
   {
    "code": "scores = []\nfor day in range(16, 32):\n    archived = wayback.near(year=2020, month=12, day=46).archive_url\n    page = requests.get(archived).text\n    soup = BeautifulSoup(page, 'lxml')\n    scores.append(getScore(soup))",
    "id": "d07f5e58927d41e29e1d3006eaa1b25d",
    "idx": 12,
    "time": "2021-02-05T18:11:38.272Z",
    "type": "execution"
   },
   {
    "code": "scores",
    "id": "417470edb4de4a0b8a289b413bad65be",
    "idx": 13,
    "time": "2021-02-05T18:11:41.178Z",
    "type": "execution"
   },
   {
    "code": "pd.DataFrame(scores)",
    "id": "c3c0a132cc0c428f8cda27b54db1ff4e",
    "idx": 14,
    "time": "2021-02-05T18:11:46.337Z",
    "type": "execution"
   },
   {
    "id": "d07f5e58927d41e29e1d3006eaa1b25d",
    "time": "2021-02-05T18:11:54.537Z",
    "type": "completion"
   },
   {
    "id": "417470edb4de4a0b8a289b413bad65be",
    "time": "2021-02-05T18:11:54.540Z",
    "type": "completion"
   },
   {
    "id": "c3c0a132cc0c428f8cda27b54db1ff4e",
    "time": "2021-02-05T18:11:54.590Z",
    "type": "completion"
   },
   {
    "code": "scores = []\nfor day in range(16, 32):\n    archived = wayback.near(year=2020, month=12, day=day).archive_url\n    page = requests.get(archived).text\n    soup = BeautifulSoup(page, 'lxml')\n    scores.append(getScore(soup))",
    "id": "d07f5e58927d41e29e1d3006eaa1b25d",
    "idx": 12,
    "time": "2021-02-05T18:12:12.121Z",
    "type": "execution"
   },
   {
    "code": "scores",
    "id": "417470edb4de4a0b8a289b413bad65be",
    "idx": 13,
    "time": "2021-02-05T18:12:13.960Z",
    "type": "execution"
   },
   {
    "code": "import pandas as pd\npd.DataFrame(scores)",
    "id": "c3c0a132cc0c428f8cda27b54db1ff4e",
    "idx": 14,
    "time": "2021-02-05T18:12:20.604Z",
    "type": "execution"
   },
   {
    "id": "d07f5e58927d41e29e1d3006eaa1b25d",
    "time": "2021-02-05T18:13:09.210Z",
    "type": "completion"
   },
   {
    "id": "417470edb4de4a0b8a289b413bad65be",
    "time": "2021-02-05T18:13:09.248Z",
    "type": "completion"
   },
   {
    "id": "c3c0a132cc0c428f8cda27b54db1ff4e",
    "time": "2021-02-05T18:13:09.249Z",
    "type": "completion"
   },
   {
    "code": "scores",
    "id": "417470edb4de4a0b8a289b413bad65be",
    "idx": 13,
    "time": "2021-02-05T18:13:23.045Z",
    "type": "execution"
   },
   {
    "id": "417470edb4de4a0b8a289b413bad65be",
    "time": "2021-02-05T18:13:23.124Z",
    "type": "completion"
   },
   {
    "code": "import pandas as pd\npd.DataFrame(scores)",
    "id": "c3c0a132cc0c428f8cda27b54db1ff4e",
    "idx": 14,
    "time": "2021-02-05T18:13:46.389Z",
    "type": "execution"
   },
   {
    "id": "c3c0a132cc0c428f8cda27b54db1ff4e",
    "time": "2021-02-05T18:13:47.010Z",
    "type": "completion"
   },
   {
    "code": "import pandas as pd\npd.DataFrame(scores, columns=[\"Critic\", \"Audience\"])",
    "id": "c3c0a132cc0c428f8cda27b54db1ff4e",
    "idx": 14,
    "time": "2021-02-05T18:14:07.809Z",
    "type": "execution"
   },
   {
    "id": "c3c0a132cc0c428f8cda27b54db1ff4e",
    "time": "2021-02-05T18:14:07.890Z",
    "type": "completion"
   },
   {
    "code": "import datetime\n\ndate1 = '2020-12-15'\ndate2 = '2021-01-18'\ndates = pd.date_range(date1, date2).tolist()\ndates",
    "id": "b5b9d1963b9d4abc8fc0034867bacbc0",
    "idx": 12,
    "time": "2021-02-05T18:16:21.900Z",
    "type": "execution"
   },
   {
    "id": "b5b9d1963b9d4abc8fc0034867bacbc0",
    "time": "2021-02-05T18:16:22.030Z",
    "type": "completion"
   },
   {
    "code": "dates[0]",
    "id": "c1697d56b87a410c8a43028394a1080e",
    "idx": 13,
    "time": "2021-02-05T18:17:35.834Z",
    "type": "execution"
   },
   {
    "id": "c1697d56b87a410c8a43028394a1080e",
    "time": "2021-02-05T18:17:35.906Z",
    "type": "completion"
   },
   {
    "code": "day(dates[0])",
    "id": "c1697d56b87a410c8a43028394a1080e",
    "idx": 13,
    "time": "2021-02-05T18:17:39.509Z",
    "type": "execution"
   },
   {
    "id": "c1697d56b87a410c8a43028394a1080e",
    "time": "2021-02-05T18:17:39.672Z",
    "type": "completion"
   },
   {
    "code": "datetime.year(dates[0])",
    "id": "c1697d56b87a410c8a43028394a1080e",
    "idx": 13,
    "time": "2021-02-05T18:17:43.634Z",
    "type": "execution"
   },
   {
    "id": "c1697d56b87a410c8a43028394a1080e",
    "time": "2021-02-05T18:17:43.713Z",
    "type": "completion"
   },
   {
    "code": "dates[0].year",
    "id": "c1697d56b87a410c8a43028394a1080e",
    "idx": 13,
    "time": "2021-02-05T18:18:00.912Z",
    "type": "execution"
   },
   {
    "id": "c1697d56b87a410c8a43028394a1080e",
    "time": "2021-02-05T18:18:00.982Z",
    "type": "completion"
   },
   {
    "code": "scores = []\nfor date in dates:\n    try:\n        archived = wayback.near(year=date.year, month=date.month, day=date.day).archive_url\n    except:\n        print(date)\n        continue\n    page = requests.get(archived).text\n    soup = BeautifulSoup(page, 'lxml')\n    scores.append(getScore(soup))",
    "id": "d07f5e58927d41e29e1d3006eaa1b25d",
    "idx": 14,
    "time": "2021-02-05T18:19:00.970Z",
    "type": "execution"
   },
   {
    "id": "d07f5e58927d41e29e1d3006eaa1b25d",
    "time": "2021-02-05T18:19:05.342Z",
    "type": "completion"
   },
   {
    "code": "scores = []\nfor date in dates:\n    try:\n        archived = wayback.near(year=date.year, month=date.month, day=date.day).archive_url\n    except:\n        print(date)\n        continue\n    page = requests.get(archived).text\n    soup = BeautifulSoup(page, 'lxml')\n    scores.append(getScore(soup) + [date])",
    "id": "d07f5e58927d41e29e1d3006eaa1b25d",
    "idx": 14,
    "time": "2021-02-05T18:19:10.332Z",
    "type": "execution"
   },
   {
    "code": "scores",
    "id": "417470edb4de4a0b8a289b413bad65be",
    "idx": 15,
    "time": "2021-02-05T18:19:11.577Z",
    "type": "execution"
   },
   {
    "id": "d07f5e58927d41e29e1d3006eaa1b25d",
    "time": "2021-02-05T18:20:39.448Z",
    "type": "completion"
   },
   {
    "id": "417470edb4de4a0b8a289b413bad65be",
    "time": "2021-02-05T18:20:39.501Z",
    "type": "completion"
   },
   {
    "code": "import pandas as pd\npd.DataFrame(scores, columns=[\"Critic\", \"Audience\", \"Date\"])",
    "id": "c3c0a132cc0c428f8cda27b54db1ff4e",
    "idx": 16,
    "time": "2021-02-05T18:21:05.741Z",
    "type": "execution"
   },
   {
    "id": "c3c0a132cc0c428f8cda27b54db1ff4e",
    "time": "2021-02-05T18:21:05.851Z",
    "type": "completion"
   },
   {
    "code": "import datetime\n\ndate1 = '2020-12-15'\ndate2 = '2021-02-05'\ndates = pd.date_range(date1, date2).tolist()\ndates",
    "id": "b5b9d1963b9d4abc8fc0034867bacbc0",
    "idx": 12,
    "time": "2021-02-05T18:21:40.923Z",
    "type": "execution"
   },
   {
    "id": "b5b9d1963b9d4abc8fc0034867bacbc0",
    "time": "2021-02-05T18:21:41.042Z",
    "type": "completion"
   },
   {
    "code": "dates[0].year",
    "id": "c1697d56b87a410c8a43028394a1080e",
    "idx": 13,
    "time": "2021-02-05T18:21:41.647Z",
    "type": "execution"
   },
   {
    "id": "c1697d56b87a410c8a43028394a1080e",
    "time": "2021-02-05T18:21:41.708Z",
    "type": "completion"
   },
   {
    "code": "scores = []\nfor date in dates:\n    try:\n        archived = wayback.near(year=date.year, month=date.month, day=date.day).archive_url\n    except:\n        print(date)\n        continue\n    page = requests.get(archived).text\n    soup = BeautifulSoup(page, 'lxml')\n    scores.append(getScore(soup) + [date])",
    "id": "d07f5e58927d41e29e1d3006eaa1b25d",
    "idx": 14,
    "time": "2021-02-05T18:21:42.498Z",
    "type": "execution"
   },
   {
    "code": "scores",
    "id": "417470edb4de4a0b8a289b413bad65be",
    "idx": 15,
    "time": "2021-02-05T18:21:45.672Z",
    "type": "execution"
   },
   {
    "code": "import pandas as pd\npd.DataFrame(scores, columns=[\"Critic\", \"Audience\", \"Date\"])",
    "id": "c3c0a132cc0c428f8cda27b54db1ff4e",
    "idx": 16,
    "time": "2021-02-05T18:21:46.166Z",
    "type": "execution"
   },
   {
    "id": "d07f5e58927d41e29e1d3006eaa1b25d",
    "time": "2021-02-05T18:23:18.375Z",
    "type": "completion"
   },
   {
    "id": "417470edb4de4a0b8a289b413bad65be",
    "time": "2021-02-05T18:23:18.383Z",
    "type": "completion"
   },
   {
    "id": "c3c0a132cc0c428f8cda27b54db1ff4e",
    "time": "2021-02-05T18:23:18.451Z",
    "type": "completion"
   },
   {
    "code": "movie_urls = {'Wonder Woman 1984': 'https://www.rottentomatoes.com/m/wonder_woman_1984/', \n              'Soul':'https://www.rottentomatoes.com/m/soul_2020/', \n              'Mulan': 'https://www.rottentomatoes.com/m/mulan_2020/',\n              'Birds of Prey': 'https://www.rottentomatoes.com/m/birds_of_prey_2020/',\n              'Sonic': 'https://www.rottentomatoes.com/m/sonic_the_hedgehog_2020/'\n             }\n\nmovie_urls[\"Captain Marvel\"] = \"https://www.rottentomatoes.com/m/captain_marvel/\"\nmovie_urls[\"Lion King\"] = \"https://www.rottentomatoes.com/m/the_lion_king_2019/\"\nmovie_urls[\"Aladdin\"] = \"https://www.rottentomatoes.com/m/aladdin/\"\nmovie_urls[\"Joker\"] = \"https://www.rottentomatoes.com/m/joker_2019/\"\nmovie_urls[\"Shazam!\"] = \"https://www.rottentomatoes.com/m/shazam/\"\nmovie_urls[\"Godzilla: King of the Monsters\"] = \"https://www.rottentomatoes.com/m/godzilla_king_of_the_monsters_2019/\"\n\nmovie_urls['Tenet'] = 'https://www.rottentomatoes.com/m/tenet/'\nmovie_urls['Scoob'] = 'https://www.rottentomatoes.com/m/scoob/'\nmovie_urls['The Marksman'] = 'https://www.rottentomatoes.com/m/the_marksman_2021/'\nmovie_urls['Artemis Fowl'] = 'https://www.rottentomatoes.com/m/artemis_fowl/'\nmovie_urls['Lovebirds'] = 'https://www.rottentomatoes.com/m/the_lovebirds_2020/'",
    "id": "e9efbc0021a14285ba4853843b2b9b0c",
    "idx": 18,
    "time": "2021-02-05T18:27:37.344Z",
    "type": "execution"
   },
   {
    "id": "e9efbc0021a14285ba4853843b2b9b0c",
    "time": "2021-02-05T18:27:37.426Z",
    "type": "completion"
   },
   {
    "code": "def build(key, date1, date2):\n    dates = pd.date_range(date1, date2).tolist()\n    wayback = waybackpy.Url(movie_urls[key], user_agent)\n    scores = []\n    for date in dates:\n        try:\n            archived = wayback.near(year=date.year, month=date.month, day=date.day).archive_url\n        except:\n            print(date)\n            continue\n        page = requests.get(archived).text\n        soup = BeautifulSoup(page, 'lxml')\n        scores.append(getScore(soup) + [date, key])\n    return scores",
    "id": "f941d1e3e3b74c2eae9bdc1e7c81db6d",
    "idx": 19,
    "time": "2021-02-05T18:28:45.569Z",
    "type": "execution"
   },
   {
    "id": "f941d1e3e3b74c2eae9bdc1e7c81db6d",
    "time": "2021-02-05T18:28:45.690Z",
    "type": "completion"
   },
   {
    "code": "build(\"Tenet\")",
    "id": "c4ed78fb6fe949558baa4f82cfacc443",
    "idx": 20,
    "time": "2021-02-05T18:28:57.554Z",
    "type": "execution"
   },
   {
    "id": "c4ed78fb6fe949558baa4f82cfacc443",
    "time": "2021-02-05T18:28:57.627Z",
    "type": "completion"
   },
   {
    "code": "build(\"Tenet\", '2020-08-21', '2021-02-05')",
    "id": "c4ed78fb6fe949558baa4f82cfacc443",
    "idx": 20,
    "time": "2021-02-05T18:30:59.247Z",
    "type": "execution"
   },
   {
    "id": "c4ed78fb6fe949558baa4f82cfacc443",
    "time": "2021-02-05T18:40:09.296Z",
    "type": "completion"
   },
   {
    "code": "date",
    "id": "c2a0c7a6589f42ee8171f2c0909c5cbf",
    "idx": 21,
    "time": "2021-02-05T18:41:08.276Z",
    "type": "execution"
   },
   {
    "id": "c2a0c7a6589f42ee8171f2c0909c5cbf",
    "time": "2021-02-05T18:41:08.354Z",
    "type": "completion"
   },
   {
    "code": "scores",
    "id": "c2a0c7a6589f42ee8171f2c0909c5cbf",
    "idx": 21,
    "time": "2021-02-05T18:41:14.864Z",
    "type": "execution"
   },
   {
    "id": "c2a0c7a6589f42ee8171f2c0909c5cbf",
    "time": "2021-02-05T18:41:14.974Z",
    "type": "completion"
   },
   {
    "code": "#2020\ndef getScore(soup):\n    temp = soup.find_all('div', class_='mop-ratings-wrap__half')\n    try:\n        critic = temp[0].text.strip().replace('\\n', '').split(' ')[0]\n        audience = temp[1].text.strip().replace('\\n', '').split(' ')[0]\n    except:\n        return [\"na\", \"na\"]\n    return [critic, audience]",
    "id": "68451771a8c04d44843891eeb873e794",
    "idx": 11,
    "time": "2021-02-05T18:42:33.227Z",
    "type": "execution"
   },
   {
    "id": "68451771a8c04d44843891eeb873e794",
    "time": "2021-02-05T18:42:33.342Z",
    "type": "completion"
   },
   {
    "code": "tenet = build(\"Tenet\", '2020-08-21', '2021-02-05')\ntenet",
    "id": "c4ed78fb6fe949558baa4f82cfacc443",
    "idx": 20,
    "time": "2021-02-05T18:42:37.871Z",
    "type": "execution"
   },
   {
    "id": "c4ed78fb6fe949558baa4f82cfacc443",
    "time": "2021-02-05T18:50:56.547Z",
    "type": "completion"
   },
   {
    "code": "pd.DataFrame(tenet, columns=[\"critic\", \"audience\", \"date\", \"film\"])",
    "id": "c2a0c7a6589f42ee8171f2c0909c5cbf",
    "idx": 21,
    "time": "2021-02-05T18:52:13.792Z",
    "type": "execution"
   },
   {
    "id": "c2a0c7a6589f42ee8171f2c0909c5cbf",
    "time": "2021-02-05T18:52:13.939Z",
    "type": "completion"
   },
   {
    "code": "#2020\ndef getScore(soup):\n    temp = soup.find_all('div', class_='mop-ratings-wrap__half')\n    try:\n        critic = temp[0].text.strip().replace('\\n', '').split(' ')[0] #2020 scraper\n        audience = temp[1].text.strip().replace('\\n', '').split(' ')[0]\n    except:\n        scores = soup.find(\"score-board\") #2021 scraper\n        return [scores[\"tomatometerscore\"], scores[\"audiencescore\"]]\n    return [critic, audience]",
    "id": "68451771a8c04d44843891eeb873e794",
    "idx": 11,
    "time": "2021-02-05T18:54:16.448Z",
    "type": "execution"
   },
   {
    "id": "68451771a8c04d44843891eeb873e794",
    "time": "2021-02-05T18:54:16.569Z",
    "type": "completion"
   },
   {
    "code": "def build(key, date1, date2):\n    dates = pd.date_range(date1, date2).tolist()\n    wayback = waybackpy.Url(movie_urls[key], user_agent)\n    scores = []\n    for date in dates:\n        try:\n            archived = wayback.near(year=date.year, month=date.month, day=date.day).archive_url\n        except:\n            print(date)\n            continue\n        page = requests.get(archived).text\n        soup = BeautifulSoup(page, 'lxml')\n        scores.append(getScore(soup) + [date, key])\n    return scores",
    "id": "f941d1e3e3b74c2eae9bdc1e7c81db6d",
    "idx": 19,
    "time": "2021-02-05T18:54:27.552Z",
    "type": "execution"
   },
   {
    "id": "f941d1e3e3b74c2eae9bdc1e7c81db6d",
    "time": "2021-02-05T18:54:27.622Z",
    "type": "completion"
   },
   {
    "code": "tenet = build(\"Tenet\", '2020-08-21', '2021-02-05')\ntenet",
    "id": "c4ed78fb6fe949558baa4f82cfacc443",
    "idx": 20,
    "time": "2021-02-05T18:54:49.230Z",
    "type": "execution"
   },
   {
    "code": "pd.DataFrame(tenet, columns=[\"critic\", \"audience\", \"date\", \"film\"])",
    "id": "c2a0c7a6589f42ee8171f2c0909c5cbf",
    "idx": 21,
    "time": "2021-02-05T18:54:49.588Z",
    "type": "execution"
   },
   {
    "code": "soup.find('span', {'class': \"meter-value superPageFontColor\"})\ncriticScore(soup)\naudienceScore(soup)",
    "id": "5a60cb9d5c9845658be9272852bfebae",
    "idx": 22,
    "time": "2021-02-05T18:54:49.990Z",
    "type": "execution"
   },
   {
    "code": "mulan = build(\"Mulan\", '2020-09-03', '2021-02-05')\nmulan",
    "id": "5a60cb9d5c9845658be9272852bfebae",
    "idx": 22,
    "time": "2021-02-05T18:56:53.154Z",
    "type": "execution"
   },
   {
    "id": "c4ed78fb6fe949558baa4f82cfacc443",
    "time": "2021-02-05T19:01:44.843Z",
    "type": "completion"
   },
   {
    "id": "c2a0c7a6589f42ee8171f2c0909c5cbf",
    "time": "2021-02-05T19:01:44.889Z",
    "type": "completion"
   },
   {
    "id": "5a60cb9d5c9845658be9272852bfebae",
    "time": "2021-02-05T19:01:44.907Z",
    "type": "completion"
   },
   {
    "id": "5a60cb9d5c9845658be9272852bfebae",
    "time": "2021-02-05T19:01:44.907Z",
    "type": "completion"
   },
   {
    "code": "mulan = build(\"Mulan\", '2020-09-03', '2021-02-05')\nmulan",
    "id": "5a60cb9d5c9845658be9272852bfebae",
    "idx": 22,
    "time": "2021-02-05T19:02:20.259Z",
    "type": "execution"
   },
   {
    "code": "soul = build(\"Soul\", '2020-11-24', '2021-02-05')\nsoul",
    "id": "48d825c309eb4c8e8c4880f55e33e687",
    "idx": 23,
    "time": "2021-02-05T19:04:22.127Z",
    "type": "execution"
   },
   {
    "code": "prey = build(\"Birds of Prey\", '2020-02-06', '2021-02-05')",
    "id": "76de90ac60254e27856f910eaa8edb90",
    "idx": 24,
    "time": "2021-02-05T19:07:50.211Z",
    "type": "execution"
   },
   {
    "code": "prey = build(\"Birds of Prey\", '2020-02-06', '2021-02-05')\nprey",
    "id": "76de90ac60254e27856f910eaa8edb90",
    "idx": 24,
    "time": "2021-02-05T19:07:53.802Z",
    "type": "execution"
   },
   {
    "code": "sonic = build(\"Sonic\", '2020-02-13', '2021-02-05')\nsonic",
    "id": "dee801f6b61f4ae894a144f277103c0c",
    "idx": 25,
    "time": "2021-02-05T19:07:56.875Z",
    "type": "execution"
   },
   {
    "id": "5a60cb9d5c9845658be9272852bfebae",
    "time": "2021-02-05T19:09:48.005Z",
    "type": "completion"
   },
   {
    "id": "48d825c309eb4c8e8c4880f55e33e687",
    "time": "2021-02-05T19:12:25.283Z",
    "type": "completion"
   },
   {
    "id": "76de90ac60254e27856f910eaa8edb90",
    "time": "2021-02-05T19:34:52.319Z",
    "type": "completion"
   },
   {
    "id": "76de90ac60254e27856f910eaa8edb90",
    "time": "2021-02-05T19:34:52.322Z",
    "type": "completion"
   },
   {
    "id": "dee801f6b61f4ae894a144f277103c0c",
    "time": "2021-02-05T19:34:52.323Z",
    "type": "completion"
   },
   {
    "code": "prey",
    "id": "20a3041a03814e4785072801b1950dfc",
    "idx": 25,
    "time": "2021-02-05T19:38:10.258Z",
    "type": "execution"
   },
   {
    "id": "20a3041a03814e4785072801b1950dfc",
    "time": "2021-02-05T19:38:10.510Z",
    "type": "completion"
   },
   {
    "code": "sonic = build(\"Sonic\", '2020-02-13', '2021-02-05')\nsonic",
    "id": "dee801f6b61f4ae894a144f277103c0c",
    "idx": 26,
    "time": "2021-02-05T19:38:27.971Z",
    "type": "execution"
   },
   {
    "id": "dee801f6b61f4ae894a144f277103c0c",
    "time": "2021-02-05T19:49:03.716Z",
    "type": "completion"
   },
   {
    "code": "arr = [tenet, mulan, sonic, prey, soul]\ndfs = []\n\nfor movie in arr:\n    dfs.append(pd.DataFrame(movie, columns=[\"critic\", \"audience\", \"date\", \"film\"]))",
    "id": "d072ac3b51094360a301688e328eac20",
    "idx": 27,
    "time": "2021-02-05T19:50:57.982Z",
    "type": "execution"
   },
   {
    "id": "d072ac3b51094360a301688e328eac20",
    "time": "2021-02-05T19:50:58.062Z",
    "type": "completion"
   },
   {
    "code": "scores",
    "id": "38e6e02a7db94662805ed2c9fb966441",
    "idx": 28,
    "time": "2021-02-05T19:51:01.219Z",
    "type": "execution"
   },
   {
    "id": "38e6e02a7db94662805ed2c9fb966441",
    "time": "2021-02-05T19:51:01.305Z",
    "type": "completion"
   },
   {
    "code": "pd.DataFrame(scores, columns=[\"critic\", \"audience\", \"date\"])",
    "id": "38e6e02a7db94662805ed2c9fb966441",
    "idx": 28,
    "time": "2021-02-05T19:51:17.613Z",
    "type": "execution"
   },
   {
    "id": "38e6e02a7db94662805ed2c9fb966441",
    "time": "2021-02-05T19:51:17.745Z",
    "type": "completion"
   },
   {
    "code": "ww = pd.DataFrame(scores, columns=[\"critic\", \"audience\", \"date\"])\nww[\"film\"] = \"Wonder Woman 1984\"\nww",
    "id": "38e6e02a7db94662805ed2c9fb966441",
    "idx": 28,
    "time": "2021-02-05T19:51:32.470Z",
    "type": "execution"
   },
   {
    "id": "38e6e02a7db94662805ed2c9fb966441",
    "time": "2021-02-05T19:51:32.645Z",
    "type": "completion"
   },
   {
    "code": "dfs.append(ww)",
    "id": "d99641eda8bb4b4689567aadfd3ce513",
    "idx": 29,
    "time": "2021-02-05T19:51:38.509Z",
    "type": "execution"
   },
   {
    "id": "d99641eda8bb4b4689567aadfd3ce513",
    "time": "2021-02-05T19:51:38.577Z",
    "type": "completion"
   },
   {
    "code": "pd.concat(dfs)",
    "id": "48350b961be5417b8729d09e6f279251",
    "idx": 30,
    "time": "2021-02-05T19:51:41.236Z",
    "type": "execution"
   },
   {
    "id": "48350b961be5417b8729d09e6f279251",
    "time": "2021-02-05T19:51:41.352Z",
    "type": "completion"
   },
   {
    "code": "pd.concat(dfs).to_csv('all_films_wayback.csv',index=False)",
    "id": "48350b961be5417b8729d09e6f279251",
    "idx": 30,
    "time": "2021-02-05T19:52:06.928Z",
    "type": "execution"
   },
   {
    "code": "!pip install git+https://github.com/akamhy/waybackpy.git",
    "id": "a99c04b0f3c4465a865ab8a8471e3cf7",
    "idx": 0,
    "time": "2021-02-06T00:06:53.729Z",
    "type": "execution"
   },
   {
    "code": "import urllib\nfrom urllib.request import urlopen\nfrom bs4 import BeautifulSoup\nimport datetime\nimport requests\nimport waybackpy\nimport pandas as pd\n\nuser_agent = \"Mozilla/5.0 (Windows NT 5.1; rv:40.0) Gecko/20100101 Firefox/40.0\"",
    "id": "8f910b3fec484a8e8fd764b15adff7ea",
    "idx": 1,
    "time": "2021-02-06T00:06:54.070Z",
    "type": "execution"
   },
   {
    "code": "#2018 scraper\ndef criticScore(soup):\n    meter = \"meter-value superPageFontColor\"\n    score = soup.find('span', {'class': meter})\n    return score.text\n\ndef audienceScore(soup):\n    audience_meter = \"audience-score meter\"\n    audience_score = \"superPageFontColor\"\n\n    meter = soup.find('div', {'class': audience_meter})\n    score = meter.find('span', {'class': audience_score})\n\n    return score.text",
    "id": "4d639c2ee5bc4c7dbd81ced6c46b85fa",
    "idx": 2,
    "time": "2021-02-06T00:06:54.521Z",
    "type": "execution"
   },
   {
    "code": "#2020-21 scraper\ndef getScore(soup):\n    temp = soup.find_all('div', class_='mop-ratings-wrap__half')\n    try:\n        critic = temp[0].text.strip().replace('\\n', '').split(' ')[0] #2020 scraper\n        audience = temp[1].text.strip().replace('\\n', '').split(' ')[0]\n    except:\n        scores = soup.find(\"score-board\") #2021 scraper\n        return [scores[\"tomatometerscore\"], scores[\"audiencescore\"]]\n    return [critic, audience]",
    "id": "3924cab5bff04f068bd5bd75046a8af2",
    "idx": 3,
    "time": "2021-02-06T00:06:55.346Z",
    "type": "execution"
   },
   {
    "code": "movie_urls = {'Wonder Woman 1984': 'https://www.rottentomatoes.com/m/wonder_woman_1984/', \n              'Soul':'https://www.rottentomatoes.com/m/soul_2020/', \n              'Mulan': 'https://www.rottentomatoes.com/m/mulan_2020/',\n              'Birds of Prey': 'https://www.rottentomatoes.com/m/birds_of_prey_2020/',\n              'Sonic': 'https://www.rottentomatoes.com/m/sonic_the_hedgehog_2020/'\n             }\n\nmovie_urls[\"Captain Marvel\"] = \"https://www.rottentomatoes.com/m/captain_marvel/\"\nmovie_urls[\"Lion King\"] = \"https://www.rottentomatoes.com/m/the_lion_king_2019/\"\nmovie_urls[\"Aladdin\"] = \"https://www.rottentomatoes.com/m/aladdin/\"\nmovie_urls[\"Joker\"] = \"https://www.rottentomatoes.com/m/joker_2019/\"\nmovie_urls[\"Shazam!\"] = \"https://www.rottentomatoes.com/m/shazam/\"\nmovie_urls[\"Godzilla: King of the Monsters\"] = \"https://www.rottentomatoes.com/m/godzilla_king_of_the_monsters_2019/\"\n\nmovie_urls['Tenet'] = 'https://www.rottentomatoes.com/m/tenet/'\nmovie_urls['Scoob'] = 'https://www.rottentomatoes.com/m/scoob/'\nmovie_urls['The Marksman'] = 'https://www.rottentomatoes.com/m/the_marksman_2021/'\nmovie_urls['Artemis Fowl'] = 'https://www.rottentomatoes.com/m/artemis_fowl/'\nmovie_urls['Lovebirds'] = 'https://www.rottentomatoes.com/m/the_lovebirds_2020/'",
    "id": "cd2ef2b795454180800ca186fb848538",
    "idx": 4,
    "time": "2021-02-06T00:06:58.146Z",
    "type": "execution"
   },
   {
    "id": "a99c04b0f3c4465a865ab8a8471e3cf7",
    "time": "2021-02-06T00:07:00.577Z",
    "type": "completion"
   },
   {
    "code": "def build(key, date1, date2):\n    dates = pd.date_range(date1, date2).tolist()\n    wayback = waybackpy.Url(movie_urls[key], user_agent)\n    scores = []\n    for date in dates:\n        try:\n            archived = wayback.near(year=date.year, month=date.month, day=date.day).archive_url\n        except:\n            print(date)\n            continue\n        page = requests.get(archived).text\n        soup = BeautifulSoup(page, 'lxml')\n        scores.append(getScore(soup) + [date, key])\n    return scores",
    "id": "b6ba369810e747bf923143e7b573f64f",
    "idx": 5,
    "time": "2021-02-06T00:07:01.149Z",
    "type": "execution"
   },
   {
    "id": "8f910b3fec484a8e8fd764b15adff7ea",
    "time": "2021-02-06T00:07:01.246Z",
    "type": "completion"
   },
   {
    "id": "4d639c2ee5bc4c7dbd81ced6c46b85fa",
    "time": "2021-02-06T00:07:01.251Z",
    "type": "completion"
   },
   {
    "id": "3924cab5bff04f068bd5bd75046a8af2",
    "time": "2021-02-06T00:07:01.275Z",
    "type": "completion"
   },
   {
    "id": "cd2ef2b795454180800ca186fb848538",
    "time": "2021-02-06T00:07:01.301Z",
    "type": "completion"
   },
   {
    "id": "b6ba369810e747bf923143e7b573f64f",
    "time": "2021-02-06T00:07:01.346Z",
    "type": "completion"
   },
   {
    "code": "captain = build(\"Joker\", '2019-09-03', '2020-09-03')\ncaptain",
    "id": "f4e02c4cf5a64ee6bb53a0e12ba33c9c",
    "idx": 6,
    "time": "2021-02-06T00:10:58.289Z",
    "type": "execution"
   },
   {
    "code": "joker = build(\"Captain Marvel\", '2019-03-06', '2020-03-06')\njoker",
    "id": "154c9387891744f59122b3c60f3cf700",
    "idx": 8,
    "time": "2021-02-06T00:13:06.385Z",
    "type": "execution"
   },
   {
    "code": "lion = build(\"Lion King\", '2019-07-11', '2020-07-11')\nlion",
    "id": "203df76a92624051b673ec5755f64f5c",
    "idx": 8,
    "time": "2021-02-06T00:16:36.975Z",
    "type": "execution"
   },
   {
    "code": "aladdin = build(\"Aladdin\", '2019-05-23', '2020-05-23')\naladdin",
    "id": "74f1d0bf696f40058df6cec13b78e712",
    "idx": 9,
    "time": "2021-02-06T00:19:33.581Z",
    "type": "execution"
   },
   {
    "code": "shazam = build(\"Shazam!\", '2019-03-24', '2020-03-24')\nshazam",
    "id": "112df8c942ae4eea8b31c43a02a7e83c",
    "idx": 10,
    "time": "2021-02-06T00:23:17.772Z",
    "type": "execution"
   },
   {
    "id": "f4e02c4cf5a64ee6bb53a0e12ba33c9c",
    "time": "2021-02-06T00:23:31.470Z",
    "type": "completion"
   },
   {
    "code": "godzilla = build(\"Godzilla: King of the Monsters\", '2019-05-31', '2020-05-31')\ngodzilla",
    "id": "e813639e6c7e46ff8df29adfec5354aa",
    "idx": 11,
    "time": "2021-02-06T00:24:45.674Z",
    "type": "execution"
   },
   {
    "code": "arr = [captain, joker, lion, aladdin, shazam, godzilla]\ndfs = []\n\nfor movie in arr:\n    dfs.append(pd.DataFrame(movie, columns=[\"critic\", \"audience\", \"date\", \"film\"]))",
    "id": "c6f3b8a951a9466385f97e3856100625",
    "idx": 12,
    "time": "2021-02-06T00:25:02.915Z",
    "type": "execution"
   },
   {
    "code": "pd.concat(dfs).to_csv('all_films_wayback_2019.csv',index=False)",
    "id": "ae4a862bf2fb432a974e4068eb88c484",
    "idx": 13,
    "time": "2021-02-06T00:25:17.340Z",
    "type": "execution"
   },
   {
    "id": "154c9387891744f59122b3c60f3cf700",
    "time": "2021-02-06T00:27:05.159Z",
    "type": "completion"
   },
   {
    "id": "203df76a92624051b673ec5755f64f5c",
    "time": "2021-02-06T00:27:05.163Z",
    "type": "completion"
   },
   {
    "id": "74f1d0bf696f40058df6cec13b78e712",
    "time": "2021-02-06T00:27:05.165Z",
    "type": "completion"
   },
   {
    "id": "112df8c942ae4eea8b31c43a02a7e83c",
    "time": "2021-02-06T00:27:05.167Z",
    "type": "completion"
   },
   {
    "id": "e813639e6c7e46ff8df29adfec5354aa",
    "time": "2021-02-06T00:27:05.167Z",
    "type": "completion"
   },
   {
    "id": "c6f3b8a951a9466385f97e3856100625",
    "time": "2021-02-06T00:27:05.168Z",
    "type": "completion"
   },
   {
    "id": "ae4a862bf2fb432a974e4068eb88c484",
    "time": "2021-02-06T00:27:05.168Z",
    "type": "completion"
   },
   {
    "code": "joker",
    "id": "4960d94b2ed7402cbbf7a57574922d2c",
    "idx": 8,
    "time": "2021-02-06T00:29:30.826Z",
    "type": "execution"
   },
   {
    "id": "4960d94b2ed7402cbbf7a57574922d2c",
    "time": "2021-02-06T00:29:30.905Z",
    "type": "completion"
   },
   {
    "code": "joker = build(\"Captain Marvel\", '2019-03-06', '2020-03-06')\njoker",
    "id": "154c9387891744f59122b3c60f3cf700",
    "idx": 7,
    "time": "2021-02-06T00:29:36.234Z",
    "type": "execution"
   },
   {
    "code": "#2018 scraper\ndef criticScore(soup):\n    meter = \"meter-value superPageFontColor\"\n    score = soup.find('span', {'class': meter})\n    return score.text\n\ndef audienceScore(soup):\n    audience_meter = \"audience-score meter\"\n    audience_score = \"superPageFontColor\"\n\n    meter = soup.find('div', {'class': audience_meter})\n    score = meter.find('span', {'class': audience_score})\n\n    return score.text\n\ndef get_score(soup):\n    critic = soup.find('span', {'class': \"meter-value superPageFontColor\"})\n    audience = soup.find('div', {'class': \"audience-score meter\"}).find('span', {'class': \"superPageFontColor\"})\n    return [critic.text, audience.text]",
    "id": "4d639c2ee5bc4c7dbd81ced6c46b85fa",
    "idx": 2,
    "time": "2021-02-06T00:31:39.342Z",
    "type": "execution"
   },
   {
    "id": "154c9387891744f59122b3c60f3cf700",
    "time": "2021-02-06T00:32:15.032Z",
    "type": "completion"
   },
   {
    "id": "4d639c2ee5bc4c7dbd81ced6c46b85fa",
    "time": "2021-02-06T00:32:15.033Z",
    "type": "completion"
   },
   {
    "code": "joker",
    "id": "4960d94b2ed7402cbbf7a57574922d2c",
    "idx": 8,
    "time": "2021-02-06T00:34:58.529Z",
    "type": "execution"
   },
   {
    "id": "4960d94b2ed7402cbbf7a57574922d2c",
    "time": "2021-02-06T00:34:58.615Z",
    "type": "completion"
   },
   {
    "code": "def build2(key, date1, date2):\n    dates = pd.date_range(date1, date2).tolist()\n    wayback = waybackpy.Url(movie_urls[key], user_agent)\n    scores = []\n    for date in dates:\n        try:\n            archived = wayback.near(year=date.year, month=date.month, day=date.day).archive_url\n        except:\n            print(date)\n            continue\n        page = requests.get(archived).text\n        soup = BeautifulSoup(page, 'lxml')\n        scores.append(get_score(soup) + [date, key])\n    return scores",
    "id": "d6d6dc5ebf1b46458efcc0ce064ccf91",
    "idx": 6,
    "time": "2021-02-06T00:35:20.760Z",
    "type": "execution"
   },
   {
    "id": "d6d6dc5ebf1b46458efcc0ce064ccf91",
    "time": "2021-02-06T00:35:20.841Z",
    "type": "completion"
   },
   {
    "code": "joker = build2(\"Captain Marvel\", '2019-03-06', '2020-03-06')\njoker",
    "id": "154c9387891744f59122b3c60f3cf700",
    "idx": 8,
    "time": "2021-02-06T00:35:24.372Z",
    "type": "execution"
   },
   {
    "id": "154c9387891744f59122b3c60f3cf700",
    "time": "2021-02-06T00:35:28.643Z",
    "type": "completion"
   },
   {
    "code": "#2018 scraper\ndef criticScore(soup):\n    meter = \"meter-value superPageFontColor\"\n    score = soup.find('span', {'class': meter})\n    return score.text\n\ndef audienceScore(soup):\n    audience_meter = \"audience-score meter\"\n    audience_score = \"superPageFontColor\"\n\n    meter = soup.find('div', {'class': audience_meter})\n    score = meter.find('span', {'class': audience_score})\n\n    return score.text\n\ndef get_score(soup):\n    critic = soup.find('span', {'class': \"meter-value superPageFontColor\"})\n    audience = soup.find('div', {'class': \"audience-score meter\"}).find('span', {'class': \"superPageFontColor\"})\n    return [critic.text, audience.text]",
    "id": "4d639c2ee5bc4c7dbd81ced6c46b85fa",
    "idx": 2,
    "time": "2021-02-06T00:35:34.954Z",
    "type": "execution"
   },
   {
    "id": "4d639c2ee5bc4c7dbd81ced6c46b85fa",
    "time": "2021-02-06T00:35:35.024Z",
    "type": "completion"
   },
   {
    "code": "joker = build2(\"Captain Marvel\", '2019-03-06', '2020-03-06')\njoker",
    "id": "154c9387891744f59122b3c60f3cf700",
    "idx": 8,
    "time": "2021-02-06T00:35:38.202Z",
    "type": "execution"
   },
   {
    "id": "154c9387891744f59122b3c60f3cf700",
    "time": "2021-02-06T00:35:39.128Z",
    "type": "completion"
   },
   {
    "code": "#2020-21 scraper\ndef getScore(soup):\n    temp = soup.find_all('div', class_='mop-ratings-wrap__half')\n    try:\n        critic = temp[0].text.strip().replace('\\n', '').split(' ')[0] #2020 scraper\n        audience = temp[1].text.strip().replace('\\n', '').split(' ')\n        if audience:\n            audience = audience[0]\n        else:\n            audience = \"Coming\"\n    except:\n        scores = soup.find(\"score-board\") #2021 scraper\n        return [scores[\"tomatometerscore\"], scores[\"audiencescore\"]]\n    return [critic, audience]",
    "id": "3924cab5bff04f068bd5bd75046a8af2",
    "idx": 3,
    "time": "2021-02-06T00:36:39.534Z",
    "type": "execution"
   },
   {
    "id": "3924cab5bff04f068bd5bd75046a8af2",
    "time": "2021-02-06T00:36:39.614Z",
    "type": "completion"
   },
   {
    "code": "joker = build(\"Captain Marvel\", '2019-03-06', '2020-03-06')\njoker",
    "id": "154c9387891744f59122b3c60f3cf700",
    "idx": 8,
    "time": "2021-02-06T00:36:45.959Z",
    "type": "execution"
   },
   {
    "id": "154c9387891744f59122b3c60f3cf700",
    "time": "2021-02-06T00:40:50.706Z",
    "type": "completion"
   },
   {
    "code": "#2020-21 scraper\ndef getScore(soup):\n    temp = soup.find_all('div', class_='mop-ratings-wrap__half')\n    try:\n        critic = temp[0].text.strip().replace('\\n', '').split(' ')[0] #2020 scraper        \n        if len(temp) > 1:\n            audience = temp[1].text.strip().replace('\\n', '').split(' ')[0]\n        else:\n            audience = \"Coming\"\n    except:\n        scores = soup.find(\"score-board\") #2021 scraper\n        return [scores[\"tomatometerscore\"], scores[\"audiencescore\"]]\n    return [critic, audience]",
    "id": "3924cab5bff04f068bd5bd75046a8af2",
    "idx": 3,
    "time": "2021-02-06T00:42:01.215Z",
    "type": "execution"
   },
   {
    "id": "3924cab5bff04f068bd5bd75046a8af2",
    "time": "2021-02-06T00:42:01.287Z",
    "type": "completion"
   },
   {
    "code": "joker = build(\"Captain Marvel\", '2019-03-06', '2020-03-06')\njoker",
    "id": "154c9387891744f59122b3c60f3cf700",
    "idx": 8,
    "time": "2021-02-06T00:42:05.013Z",
    "type": "execution"
   },
   {
    "code": "lion = build(\"Lion King\", '2019-07-11', '2020-07-11')\nlion",
    "id": "203df76a92624051b673ec5755f64f5c",
    "idx": 9,
    "time": "2021-02-06T00:42:05.269Z",
    "type": "execution"
   },
   {
    "code": "aladdin = build(\"Aladdin\", '2019-05-23', '2020-05-23')\naladdin",
    "id": "74f1d0bf696f40058df6cec13b78e712",
    "idx": 10,
    "time": "2021-02-06T00:42:06.638Z",
    "type": "execution"
   },
   {
    "code": "shazam = build(\"Shazam!\", '2019-03-24', '2020-03-24')\nshazam",
    "id": "112df8c942ae4eea8b31c43a02a7e83c",
    "idx": 11,
    "time": "2021-02-06T00:42:06.892Z",
    "type": "execution"
   },
   {
    "code": "godzilla = build(\"Godzilla: King of the Monsters\", '2019-05-31', '2020-05-31')\ngodzilla",
    "id": "e813639e6c7e46ff8df29adfec5354aa",
    "idx": 12,
    "time": "2021-02-06T00:42:07.201Z",
    "type": "execution"
   },
   {
    "code": "arr = [captain, joker, lion, aladdin, shazam, godzilla]\ndfs = []\n\nfor movie in arr:\n    dfs.append(pd.DataFrame(movie, columns=[\"critic\", \"audience\", \"date\", \"film\"]))",
    "id": "c6f3b8a951a9466385f97e3856100625",
    "idx": 13,
    "time": "2021-02-06T00:42:09.334Z",
    "type": "execution"
   },
   {
    "code": "pd.concat(dfs).to_csv('all_films_wayback_2019.csv',index=False)",
    "id": "ae4a862bf2fb432a974e4068eb88c484",
    "idx": 14,
    "time": "2021-02-06T00:49:30.508Z",
    "type": "execution"
   },
   {
    "id": "154c9387891744f59122b3c60f3cf700",
    "time": "2021-02-06T00:52:25.296Z",
    "type": "completion"
   },
   {
    "id": "203df76a92624051b673ec5755f64f5c",
    "time": "2021-02-06T01:02:39.829Z",
    "type": "completion"
   },
   {
    "id": "74f1d0bf696f40058df6cec13b78e712",
    "time": "2021-02-06T01:16:18.203Z",
    "type": "completion"
   },
   {
    "id": "112df8c942ae4eea8b31c43a02a7e83c",
    "time": "2021-02-06T01:28:04.304Z",
    "type": "completion"
   },
   {
    "id": "e813639e6c7e46ff8df29adfec5354aa",
    "time": "2021-02-06T01:38:27.540Z",
    "type": "completion"
   },
   {
    "id": "c6f3b8a951a9466385f97e3856100625",
    "time": "2021-02-06T01:38:27.546Z",
    "type": "completion"
   },
   {
    "id": "ae4a862bf2fb432a974e4068eb88c484",
    "time": "2021-02-06T01:38:27.548Z",
    "type": "completion"
   },
   {
    "code": "def getNumReviews(soup):        \n    critic = soup.find_all(\"small\", class_=\"mop-ratings-wrap__text--small\")\n    audience = soup.find_all(\"strong\", class_=\"mop-ratings-wrap__text--small\")\n    if critic:\n        critic = critic[0].text.replace(\"\\n\", '').strip()\n    else:\n        critic = soup.find_all(\"a\", class_='scoreboard__link scoreboard__link--tomatometer')\n        critic = critic[0].text\n    if audience:\n        audience = audience[1].text.replace(\"Verified Ratings: \", '')\n    else:\n        audience = soup.find_all(\"a\", class_='scoreboard__link scoreboard__link--audience')\n        if audience:\n            audience = audience[0].text\n        else:    \n            audience = \"Coming\"\n    return [critic, audience]",
    "id": "b371431973604d1f8887d84839f7d916",
    "idx": 4,
    "time": "2021-02-09T20:40:29.037Z",
    "type": "execution"
   },
   {
    "id": "b371431973604d1f8887d84839f7d916",
    "time": "2021-02-09T20:40:29.124Z",
    "type": "completion"
   },
   {
    "code": "!pip install git+https://github.com/akamhy/waybackpy.git",
    "id": "7d30b642e44340b185e47cf1c946f9bd",
    "idx": 0,
    "time": "2021-02-09T20:40:59.718Z",
    "type": "execution"
   },
   {
    "code": "import urllib\nfrom urllib.request import urlopen\nfrom bs4 import BeautifulSoup\nimport datetime\nimport requests\nimport waybackpy\nimport pandas as pd\n\nuser_agent = \"Mozilla/5.0 (Windows NT 5.1; rv:40.0) Gecko/20100101 Firefox/40.0\"",
    "id": "7609ed1133af4c1f8616c52338361de8",
    "idx": 1,
    "time": "2021-02-09T20:40:59.719Z",
    "type": "execution"
   },
   {
    "code": "#2018 scraper\ndef criticScore(soup):\n    meter = \"meter-value superPageFontColor\"\n    score = soup.find('span', {'class': meter})\n    return score.text\n\ndef audienceScore(soup):\n    audience_meter = \"audience-score meter\"\n    audience_score = \"superPageFontColor\"\n\n    meter = soup.find('div', {'class': audience_meter})\n    score = meter.find('span', {'class': audience_score})\n\n    return score.text\n\ndef get_score(soup):\n    critic = soup.find('span', {'class': \"meter-value superPageFontColor\"})\n    audience = soup.find('div', {'class': \"audience-score meter\"}).find('span', {'class': \"superPageFontColor\"})\n    return [critic.text, audience.text]",
    "id": "9a29db6cfd99428b8e8d4ee113520fe8",
    "idx": 2,
    "time": "2021-02-09T20:40:59.721Z",
    "type": "execution"
   },
   {
    "code": "#2020-21 scraper\ndef getScore(soup):\n    temp = soup.find_all('div', class_='mop-ratings-wrap__half')\n    try:\n        critic = temp[0].text.strip().replace('\\n', '').split(' ')[0] #2020 scraper        \n        if len(temp) > 1:\n            audience = temp[1].text.strip().replace('\\n', '').split(' ')[0]\n        else:\n            audience = \"Coming\"\n    except:\n        scores = soup.find(\"score-board\") #2021 scraper\n        return [scores[\"tomatometerscore\"], scores[\"audiencescore\"]]\n    return [critic, audience]",
    "id": "81aed26ff8a14daa8887f2756fd4f7dc",
    "idx": 3,
    "time": "2021-02-09T20:40:59.723Z",
    "type": "execution"
   },
   {
    "code": "def getNumReviews(soup):        \n    critic = soup.find_all(\"small\", class_=\"mop-ratings-wrap__text--small\")\n    audience = soup.find_all(\"strong\", class_=\"mop-ratings-wrap__text--small\")\n    if critic:\n        critic = critic[0].text.replace(\"\\n\", '').strip()\n    else:\n        critic = soup.find_all(\"a\", class_='scoreboard__link scoreboard__link--tomatometer')\n        critic = critic[0].text\n    if audience:\n        audience = audience[1].text.replace(\"Verified Ratings: \", '')\n    else:\n        audience = soup.find_all(\"a\", class_='scoreboard__link scoreboard__link--audience')\n        if audience:\n            audience = audience[0].text\n        else:    \n            audience = \"Coming\"\n    return [critic, audience]",
    "id": "b371431973604d1f8887d84839f7d916",
    "idx": 4,
    "time": "2021-02-09T20:40:59.724Z",
    "type": "execution"
   },
   {
    "code": "movie_urls = {'Wonder Woman 1984': 'https://www.rottentomatoes.com/m/wonder_woman_1984/', \n              'Soul':'https://www.rottentomatoes.com/m/soul_2020/', \n              'Mulan': 'https://www.rottentomatoes.com/m/mulan_2020/',\n              'Birds of Prey': 'https://www.rottentomatoes.com/m/birds_of_prey_2020/',\n              'Sonic': 'https://www.rottentomatoes.com/m/sonic_the_hedgehog_2020/'\n             }\n\nmovie_urls[\"Captain Marvel\"] = \"https://www.rottentomatoes.com/m/captain_marvel/\"\nmovie_urls[\"Lion King\"] = \"https://www.rottentomatoes.com/m/the_lion_king_2019/\"\nmovie_urls[\"Aladdin\"] = \"https://www.rottentomatoes.com/m/aladdin/\"\nmovie_urls[\"Joker\"] = \"https://www.rottentomatoes.com/m/joker_2019/\"\nmovie_urls[\"Shazam!\"] = \"https://www.rottentomatoes.com/m/shazam/\"\nmovie_urls[\"Godzilla: King of the Monsters\"] = \"https://www.rottentomatoes.com/m/godzilla_king_of_the_monsters_2019/\"\n\nmovie_urls['Tenet'] = 'https://www.rottentomatoes.com/m/tenet/'\nmovie_urls['Scoob'] = 'https://www.rottentomatoes.com/m/scoob/'\nmovie_urls['The Marksman'] = 'https://www.rottentomatoes.com/m/the_marksman_2021/'\nmovie_urls['Artemis Fowl'] = 'https://www.rottentomatoes.com/m/artemis_fowl/'\nmovie_urls['Lovebirds'] = 'https://www.rottentomatoes.com/m/the_lovebirds_2020/'",
    "id": "c91f031f53aa451ab1392a4bab7ccf52",
    "idx": 5,
    "time": "2021-02-09T20:40:59.725Z",
    "type": "execution"
   },
   {
    "code": "def build(key, date1, date2):\n    dates = pd.date_range(date1, date2).tolist()\n    wayback = waybackpy.Url(movie_urls[key], user_agent)\n    scores = []\n    for date in dates:\n        try:\n            archived = wayback.near(year=date.year, month=date.month, day=date.day).archive_url\n        except:\n            print(date)\n            continue\n        page = requests.get(archived).text\n        soup = BeautifulSoup(page, 'lxml')\n        scores.append(getScore(soup) + getNumReviews(soup) + [date, key])\n    return scores",
    "id": "46fc34f7e7114439867249bcbb6b8987",
    "idx": 6,
    "time": "2021-02-09T20:40:59.726Z",
    "type": "execution"
   },
   {
    "code": "def build2(key, date1, date2):\n    dates = pd.date_range(date1, date2).tolist()\n    wayback = waybackpy.Url(movie_urls[key], user_agent)\n    scores = []\n    for date in dates:\n        try:\n            archived = wayback.near(year=date.year, month=date.month, day=date.day).archive_url\n        except:\n            print(date)\n            continue\n        page = requests.get(archived).text\n        soup = BeautifulSoup(page, 'lxml')\n        scores.append(get_score(soup) + getNumReviews(soup) + [date, key])\n    return scores",
    "id": "c18a5a7297394918aca149c04fb981e8",
    "idx": 7,
    "time": "2021-02-09T20:40:59.727Z",
    "type": "execution"
   },
   {
    "code": "captain = build(\"Joker\", '2019-09-03', '2020-09-03')\ncaptain",
    "id": "b02e0e40d3844a88a1d316ec0b347368",
    "idx": 8,
    "time": "2021-02-09T20:40:59.729Z",
    "type": "execution"
   },
   {
    "code": "joker = build(\"Captain Marvel\", '2019-03-06', '2020-03-06')\njoker",
    "id": "edff657084474bf68f9f9bbc404acc69",
    "idx": 9,
    "time": "2021-02-09T20:40:59.731Z",
    "type": "execution"
   },
   {
    "code": "lion = build(\"Lion King\", '2019-07-11', '2020-07-11')\nlion",
    "id": "1313aaa84d1a4d2485d95114d207575f",
    "idx": 10,
    "time": "2021-02-09T20:40:59.733Z",
    "type": "execution"
   },
   {
    "code": "aladdin = build(\"Aladdin\", '2019-05-23', '2020-05-23')\naladdin",
    "id": "8a0093440c1644449753ecb046b4f238",
    "idx": 11,
    "time": "2021-02-09T20:40:59.735Z",
    "type": "execution"
   },
   {
    "code": "shazam = build(\"Shazam!\", '2019-03-24', '2020-03-24')\nshazam",
    "id": "2ad40f0cce9c429e813f99fccfe013e1",
    "idx": 12,
    "time": "2021-02-09T20:40:59.738Z",
    "type": "execution"
   },
   {
    "code": "godzilla = build(\"Godzilla: King of the Monsters\", '2019-05-31', '2020-05-31')\ngodzilla",
    "id": "002f7af4f4a743d586cba5275e83a987",
    "idx": 13,
    "time": "2021-02-09T20:40:59.741Z",
    "type": "execution"
   },
   {
    "code": "arr = [captain, joker, lion, aladdin, shazam, godzilla]\ndfs = []\n\nfor movie in arr:\n    dfs.append(pd.DataFrame(movie, columns=[\"critic\", \"audience\", \"date\", \"film\"]))",
    "id": "5c8609b1aa58466c9f23d78fb8eabc54",
    "idx": 14,
    "time": "2021-02-09T20:40:59.742Z",
    "type": "execution"
   },
   {
    "code": "pd.concat(dfs).to_csv('all_films_wayback_2019_reviews.csv',index=False)",
    "id": "acab315e59174e09806414bcc0650a0c",
    "idx": 15,
    "time": "2021-02-09T20:40:59.742Z",
    "type": "execution"
   },
   {
    "id": "7d30b642e44340b185e47cf1c946f9bd",
    "time": "2021-02-09T20:41:06.011Z",
    "type": "completion"
   },
   {
    "id": "7609ed1133af4c1f8616c52338361de8",
    "time": "2021-02-09T20:41:06.625Z",
    "type": "completion"
   },
   {
    "id": "9a29db6cfd99428b8e8d4ee113520fe8",
    "time": "2021-02-09T20:41:06.626Z",
    "type": "completion"
   },
   {
    "id": "81aed26ff8a14daa8887f2756fd4f7dc",
    "time": "2021-02-09T20:41:06.628Z",
    "type": "completion"
   },
   {
    "id": "b371431973604d1f8887d84839f7d916",
    "time": "2021-02-09T20:41:06.678Z",
    "type": "completion"
   },
   {
    "id": "c91f031f53aa451ab1392a4bab7ccf52",
    "time": "2021-02-09T20:41:06.679Z",
    "type": "completion"
   },
   {
    "id": "46fc34f7e7114439867249bcbb6b8987",
    "time": "2021-02-09T20:41:06.684Z",
    "type": "completion"
   },
   {
    "id": "c18a5a7297394918aca149c04fb981e8",
    "time": "2021-02-09T20:41:06.733Z",
    "type": "completion"
   },
   {
    "code": "arr = [captain, joker, lion, aladdin, shazam, godzilla]\ndfs = []\n\nfor movie in arr:\n    dfs.append(pd.DataFrame(movie, columns=[\"critic\", \"audience\", \"criticNum\", \"audienceNum\" \"date\", \"film\"]))",
    "id": "5c8609b1aa58466c9f23d78fb8eabc54",
    "idx": 14,
    "time": "2021-02-09T20:50:09.596Z",
    "type": "execution"
   },
   {
    "id": "b02e0e40d3844a88a1d316ec0b347368",
    "time": "2021-02-09T20:53:54.079Z",
    "type": "completion"
   },
   {
    "id": "edff657084474bf68f9f9bbc404acc69",
    "time": "2021-02-09T20:56:19.908Z",
    "type": "completion"
   },
   {
    "id": "1313aaa84d1a4d2485d95114d207575f",
    "time": "2021-02-09T20:56:19.938Z",
    "type": "completion"
   },
   {
    "id": "8a0093440c1644449753ecb046b4f238",
    "time": "2021-02-09T20:56:19.945Z",
    "type": "completion"
   },
   {
    "id": "2ad40f0cce9c429e813f99fccfe013e1",
    "time": "2021-02-09T20:56:19.947Z",
    "type": "completion"
   },
   {
    "id": "002f7af4f4a743d586cba5275e83a987",
    "time": "2021-02-09T20:56:19.949Z",
    "type": "completion"
   },
   {
    "id": "acab315e59174e09806414bcc0650a0c",
    "time": "2021-02-09T20:56:19.950Z",
    "type": "completion"
   },
   {
    "id": "5c8609b1aa58466c9f23d78fb8eabc54",
    "time": "2021-02-09T20:56:19.950Z",
    "type": "completion"
   },
   {
    "id": "5c8609b1aa58466c9f23d78fb8eabc54",
    "time": "2021-02-09T20:56:19.950Z",
    "type": "completion"
   },
   {
    "code": "def getNumReviews(soup):        \n    critic = soup.find_all(\"small\", class_=\"mop-ratings-wrap__text--small\")\n    audience = soup.find_all(\"strong\", class_=\"mop-ratings-wrap__text--small\")\n    if critic:\n        critic = critic[0].text.replace(\"\\n\", '').strip()\n    else:\n        critic = soup.find_all(\"a\", class_='scoreboard__link scoreboard__link--tomatometer')\n        critic = critic[0].text\n    if len(audience) > 1:\n        audience = audience[1].text.replace(\"Verified Ratings: \", '')\n    else:\n        audience = soup.find_all(\"a\", class_='scoreboard__link scoreboard__link--audience')\n        if audience:\n            audience = audience[0].text\n        else:    \n            audience = \"Coming\"\n    return [critic, audience]",
    "id": "b371431973604d1f8887d84839f7d916",
    "idx": 4,
    "time": "2021-02-09T21:06:07.482Z",
    "type": "execution"
   },
   {
    "id": "b371431973604d1f8887d84839f7d916",
    "time": "2021-02-09T21:06:07.561Z",
    "type": "completion"
   },
   {
    "code": "joker = build(\"Captain Marvel\", '2019-03-06', '2020-03-06')\njoker",
    "id": "edff657084474bf68f9f9bbc404acc69",
    "idx": 9,
    "time": "2021-02-09T21:06:11.723Z",
    "type": "execution"
   },
   {
    "id": "edff657084474bf68f9f9bbc404acc69",
    "time": "2021-02-09T21:07:35.299Z",
    "type": "completion"
   },
   {
    "code": "joker = build(\"Captain Marvel\", '2019-03-06', '2020-03-06')\njoker",
    "id": "edff657084474bf68f9f9bbc404acc69",
    "idx": 9,
    "time": "2021-02-09T21:09:47.194Z",
    "type": "execution"
   },
   {
    "id": "edff657084474bf68f9f9bbc404acc69",
    "time": "2021-02-09T21:19:56.498Z",
    "type": "completion"
   },
   {
    "code": "lion = build(\"Lion King\", '2019-07-11', '2020-07-11')\nlion",
    "id": "1313aaa84d1a4d2485d95114d207575f",
    "idx": 10,
    "time": "2021-02-09T21:20:49.216Z",
    "type": "execution"
   },
   {
    "code": "aladdin = build(\"Aladdin\", '2019-05-23', '2020-05-23')\naladdin",
    "id": "8a0093440c1644449753ecb046b4f238",
    "idx": 11,
    "time": "2021-02-09T21:20:49.462Z",
    "type": "execution"
   },
   {
    "code": "shazam = build(\"Shazam!\", '2019-03-24', '2020-03-24')\nshazam",
    "id": "2ad40f0cce9c429e813f99fccfe013e1",
    "idx": 12,
    "time": "2021-02-09T21:20:49.681Z",
    "type": "execution"
   },
   {
    "code": "godzilla = build(\"Godzilla: King of the Monsters\", '2019-05-31', '2020-05-31')\ngodzilla",
    "id": "002f7af4f4a743d586cba5275e83a987",
    "idx": 13,
    "time": "2021-02-09T21:20:50.023Z",
    "type": "execution"
   },
   {
    "code": "arr = [captain, joker, lion, aladdin, shazam, godzilla]\ndfs = []\n\nfor movie in arr:\n    dfs.append(pd.DataFrame(movie, columns=[\"critic\", \"audience\", \"criticNum\", \"audienceNum\" \"date\", \"film\"]))",
    "id": "5c8609b1aa58466c9f23d78fb8eabc54",
    "idx": 14,
    "time": "2021-02-09T21:20:51.868Z",
    "type": "execution"
   },
   {
    "code": "pd.concat(dfs).to_csv('all_films_wayback_2019_reviews.csv',index=False)",
    "id": "acab315e59174e09806414bcc0650a0c",
    "idx": 15,
    "time": "2021-02-09T21:20:52.596Z",
    "type": "execution"
   },
   {
    "id": "1313aaa84d1a4d2485d95114d207575f",
    "time": "2021-02-09T21:29:48.787Z",
    "type": "completion"
   },
   {
    "id": "8a0093440c1644449753ecb046b4f238",
    "time": "2021-02-09T21:39:09.524Z",
    "type": "completion"
   },
   {
    "id": "2ad40f0cce9c429e813f99fccfe013e1",
    "time": "2021-02-09T21:49:27.973Z",
    "type": "completion"
   },
   {
    "id": "002f7af4f4a743d586cba5275e83a987",
    "time": "2021-02-09T21:58:38.165Z",
    "type": "completion"
   },
   {
    "id": "5c8609b1aa58466c9f23d78fb8eabc54",
    "time": "2021-02-09T21:58:38.237Z",
    "type": "completion"
   },
   {
    "id": "acab315e59174e09806414bcc0650a0c",
    "time": "2021-02-09T21:58:38.237Z",
    "type": "completion"
   },
   {
    "code": "arr = [captain, joker, lion, aladdin, shazam, godzilla]\ndfs = []\n\nfor movie in arr:\n    dfs.append(pd.DataFrame(movie, columns=[\"critic\", \"audience\", \"criticNum\", \"audienceNum\", \"date\", \"film\"]))",
    "id": "5c8609b1aa58466c9f23d78fb8eabc54",
    "idx": 14,
    "time": "2021-02-09T22:01:21.219Z",
    "type": "execution"
   },
   {
    "id": "5c8609b1aa58466c9f23d78fb8eabc54",
    "time": "2021-02-09T22:01:21.312Z",
    "type": "completion"
   },
   {
    "code": "pd.concat(dfs).to_csv('all_films_wayback_2019_reviews.csv',index=False)",
    "id": "acab315e59174e09806414bcc0650a0c",
    "idx": 15,
    "time": "2021-02-09T22:01:25.437Z",
    "type": "execution"
   },
   {
    "id": "acab315e59174e09806414bcc0650a0c",
    "time": "2021-02-09T22:01:25.557Z",
    "type": "completion"
   }
  ],
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.6"
  }
 },
 "nbformat": 4,
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