{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "d12693c1",
   "metadata": {},
   "source": [
    "# Movie data\n",
    "\n",
    "The file 'imdb.csv' contains data about 6178 movies and TV shows, which were scraped from the website <a href=\"https://www.imdb.com/\">IMDb.com</a> (and which I downloaded from <a href=\"https://www.kaggle.com/datasets/mazenramadan/imdb-most-popular-films-and-series\">Kaggle.com</a>)\n",
    "\n",
    "Your task is to investigate what makes a good movie and write up your claims in a blog-style report, \"10 ingredients for a good movie\". You don't have to have exactly 10 (try for at least 5!). \n",
    "\n",
    "Our metric of a 'good movie' shall be the IMDb rating (base on users' votes). You may like to comment on whether this is a reliable metric.\n",
    "\n",
    "This is a blog for geeky movie enthusiasts so you can support your claims with some numbers (correlations, decriptive statistics and the like) but try to avoid jargon and use the data to support the points you are making in the text, rather than robotically reporting statistics. \n",
    "\n",
    "Below I will suggest some avenues to explore but I encourage you to investigate the data yourself - play around with plotting the relationship between different variables before you settle down to write your report.\n",
    "\n",
    "## What makes a good report?\n",
    "\n",
    "Write a (very) short introduction explaining what the data are and what you are using as a measure of movie 'quality'\n",
    "\n",
    "It's up to you to find some interesting features in the data and show them effectively using plots\n",
    "\n",
    "You should support your claims using descriptive statistics such the mean rating for different groups of movies or correlation coefficients\n",
    "\n",
    "No need to use this notebook for your report - you can start a new 'clean' one without my notes in.\n",
    "\n",
    "You might even like to start two notebooks - one for rough work (you experimenting with plotting the data, and saving any analyses you want to discuss with you tutor) and one for your final report.\n",
    "\n",
    "\n",
    "### Set up Python libraries\n",
    "\n",
    "As usual, run the code cell below to import the relevant Python libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "id": "9b95464c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Set-up Python libraries - you need to run this but you don't need to change it\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import scipy.stats as stats\n",
    "import pandas \n",
    "import seaborn as sns\n",
    "sns.set_theme()\n",
    "sns.set_style('whitegrid')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6095e938",
   "metadata": {},
   "source": [
    "### Import the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "id": "24c257a1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>Date</th>\n",
       "      <th>Rating</th>\n",
       "      <th>Votes</th>\n",
       "      <th>Genre</th>\n",
       "      <th>Duration</th>\n",
       "      <th>Type</th>\n",
       "      <th>Certificate</th>\n",
       "      <th>Episodes</th>\n",
       "      <th>Nudity</th>\n",
       "      <th>Violence</th>\n",
       "      <th>Profanity</th>\n",
       "      <th>Alcohol</th>\n",
       "      <th>Frightening</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>No Time to Die</td>\n",
       "      <td>2021</td>\n",
       "      <td>7.6</td>\n",
       "      <td>107163.0</td>\n",
       "      <td>Action, Adventure, Thriller</td>\n",
       "      <td>163.0</td>\n",
       "      <td>Film</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Mild</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>Mild</td>\n",
       "      <td>Mild</td>\n",
       "      <td>Moderate</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>The Guilty</td>\n",
       "      <td>2021</td>\n",
       "      <td>6.3</td>\n",
       "      <td>64375.0</td>\n",
       "      <td>Crime, Drama, Thriller</td>\n",
       "      <td>90.0</td>\n",
       "      <td>Film</td>\n",
       "      <td>R</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Severe</td>\n",
       "      <td>None</td>\n",
       "      <td>Moderate</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>The Many Saints of Newark</td>\n",
       "      <td>2021</td>\n",
       "      <td>6.4</td>\n",
       "      <td>27145.0</td>\n",
       "      <td>Crime, Drama</td>\n",
       "      <td>120.0</td>\n",
       "      <td>Film</td>\n",
       "      <td>R</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>Severe</td>\n",
       "      <td>Severe</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>Moderate</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Venom: Let There Be Carnage</td>\n",
       "      <td>2021</td>\n",
       "      <td>6.4</td>\n",
       "      <td>30443.0</td>\n",
       "      <td>Action, Adventure, Sci-Fi</td>\n",
       "      <td>97.0</td>\n",
       "      <td>Film</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>Mild</td>\n",
       "      <td>Moderate</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Dune</td>\n",
       "      <td>2021</td>\n",
       "      <td>8.3</td>\n",
       "      <td>84636.0</td>\n",
       "      <td>Action, Adventure, Drama</td>\n",
       "      <td>155.0</td>\n",
       "      <td>Film</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>None</td>\n",
       "      <td>Mild</td>\n",
       "      <td>Moderate</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6173</th>\n",
       "      <td>The Human Centipede II (Full Sequence)</td>\n",
       "      <td>2011</td>\n",
       "      <td>3.8</td>\n",
       "      <td>37492.0</td>\n",
       "      <td>Horror</td>\n",
       "      <td>91.0</td>\n",
       "      <td>Film</td>\n",
       "      <td>Not Rated</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Severe</td>\n",
       "      <td>Severe</td>\n",
       "      <td>Severe</td>\n",
       "      <td>Mild</td>\n",
       "      <td>Severe</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6174</th>\n",
       "      <td>Double Indemnity</td>\n",
       "      <td>1944</td>\n",
       "      <td>8.3</td>\n",
       "      <td>150448.0</td>\n",
       "      <td>Crime, Drama, Film-Noir</td>\n",
       "      <td>107.0</td>\n",
       "      <td>Film</td>\n",
       "      <td>Passed</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>Mild</td>\n",
       "      <td>None</td>\n",
       "      <td>Mild</td>\n",
       "      <td>Mild</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6175</th>\n",
       "      <td>Before the Devil Knows You're Dead</td>\n",
       "      <td>2007</td>\n",
       "      <td>7.3</td>\n",
       "      <td>100668.0</td>\n",
       "      <td>Crime, Drama, Thriller</td>\n",
       "      <td>117.0</td>\n",
       "      <td>Film</td>\n",
       "      <td>R</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Severe</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>Severe</td>\n",
       "      <td>Severe</td>\n",
       "      <td>Severe</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6176</th>\n",
       "      <td>Queen Bees</td>\n",
       "      <td>2021</td>\n",
       "      <td>6.0</td>\n",
       "      <td>887.0</td>\n",
       "      <td>Comedy, Drama, Romance</td>\n",
       "      <td>100.0</td>\n",
       "      <td>Film</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Mild</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6177</th>\n",
       "      <td>Death Race</td>\n",
       "      <td>2008</td>\n",
       "      <td>6.3</td>\n",
       "      <td>203578.0</td>\n",
       "      <td>Action, Sci-Fi, Thriller</td>\n",
       "      <td>105.0</td>\n",
       "      <td>Film</td>\n",
       "      <td>R</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Mild</td>\n",
       "      <td>Severe</td>\n",
       "      <td>Severe</td>\n",
       "      <td>Mild</td>\n",
       "      <td>Moderate</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4446 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                        Name  Date  Rating     Votes  \\\n",
       "0                             No Time to Die  2021     7.6  107163.0   \n",
       "1                                 The Guilty  2021     6.3   64375.0   \n",
       "2                  The Many Saints of Newark  2021     6.4   27145.0   \n",
       "3                Venom: Let There Be Carnage  2021     6.4   30443.0   \n",
       "4                                       Dune  2021     8.3   84636.0   \n",
       "...                                      ...   ...     ...       ...   \n",
       "6173  The Human Centipede II (Full Sequence)  2011     3.8   37492.0   \n",
       "6174                        Double Indemnity  1944     8.3  150448.0   \n",
       "6175      Before the Devil Knows You're Dead  2007     7.3  100668.0   \n",
       "6176                              Queen Bees  2021     6.0     887.0   \n",
       "6177                              Death Race  2008     6.3  203578.0   \n",
       "\n",
       "                            Genre  Duration  Type Certificate  Episodes  \\\n",
       "0     Action, Adventure, Thriller     163.0  Film       PG-13       NaN   \n",
       "1          Crime, Drama, Thriller      90.0  Film           R       NaN   \n",
       "2                    Crime, Drama     120.0  Film           R       NaN   \n",
       "3       Action, Adventure, Sci-Fi      97.0  Film       PG-13       NaN   \n",
       "4        Action, Adventure, Drama     155.0  Film       PG-13       NaN   \n",
       "...                           ...       ...   ...         ...       ...   \n",
       "6173                       Horror      91.0  Film   Not Rated       NaN   \n",
       "6174      Crime, Drama, Film-Noir     107.0  Film      Passed       NaN   \n",
       "6175       Crime, Drama, Thriller     117.0  Film           R       NaN   \n",
       "6176       Comedy, Drama, Romance     100.0  Film       PG-13       NaN   \n",
       "6177     Action, Sci-Fi, Thriller     105.0  Film           R       NaN   \n",
       "\n",
       "        Nudity  Violence Profanity   Alcohol Frightening  \n",
       "0         Mild  Moderate      Mild      Mild    Moderate  \n",
       "1         None      None    Severe      None    Moderate  \n",
       "2     Moderate    Severe    Severe  Moderate    Moderate  \n",
       "3         None  Moderate  Moderate      Mild    Moderate  \n",
       "4         None  Moderate      None      Mild    Moderate  \n",
       "...        ...       ...       ...       ...         ...  \n",
       "6173    Severe    Severe    Severe      Mild      Severe  \n",
       "6174      None      Mild      None      Mild        Mild  \n",
       "6175    Severe  Moderate    Severe    Severe      Severe  \n",
       "6176      None      None      Mild  Moderate        None  \n",
       "6177      Mild    Severe    Severe      Mild    Moderate  \n",
       "\n",
       "[4446 rows x 14 columns]"
      ]
     },
     "execution_count": 130,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "imdb=pandas.read_csv('https://raw.githubusercontent.com/jillxoreilly/StatsCourseBook/main/data/imdb.csv')\n",
    "\n",
    "# get only the movies (ignoring TV shows)\n",
    "movies=imdb[imdb['Type']=='Film']\n",
    "movies"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1b967599",
   "metadata": {},
   "source": [
    "## Where to start?\n",
    "\n",
    "Here are some myths (or truths?) for you to investigate to get you started\n",
    "\n",
    "<ol>\n",
    "<li> Movies are getting worse over time\n",
    "<li> Longer movies are better\n",
    "    <ul> <li>As well as investigating the general relationship, can you find some points of interest - for example, name cases of long movies that were also bad (certainly to be avoided!)? Are there any surprisingly long movies in the dataset? What about those that were short but sweet?</ul>\n",
    "<li> More nudity makes for a highly rated movie\n",
    "<li> Movies rated 15 are the worst!\n",
    "    <ul><li>To do this you will need to create a new column converting the US and international certificates into their closest UK equivalent - U,PG,12,15 or 18</ul>\n",
    "<li> Straight-to-TV movies have lower ratings than those shown in cinemas\n",
    "    <ul><li>The straight-to-TV movies have certificates beginning in 'TV'</ul>\n",
    "<li> Popular movies are better (you can use the number of votes as a measure of popularity of a movie, since people should only vote if they watched it - you may like to comment on whether this is a reasonabble measure of popularity or whether it may be biased)\n",
    "</ol>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "35241f53",
   "metadata": {},
   "source": [
    "## Examples:\n",
    "\n",
    "Here are a couple of examples to get you started:\n",
    "\n",
    "### Example 1: Are movies getting worse over time?\n",
    "\n",
    "According to IMDb raters, yes they are. Or to be more accurate, the number of low-rated movies increased over time, whilst a steady flow of high rated movies was also maintained."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "id": "69d08c3e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0.98, 'Movie ratings over time')"
      ]
     },
     "execution_count": 131,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.histplot(data=movies, x='Date', y='Rating')\n",
    "plt.xlim([1920,2020])\n",
    "plt.ylim([0,10])\n",
    "plt.suptitle('Movie ratings over time', fontsize=16)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0170b197",
   "metadata": {},
   "source": [
    "Rating was negatively correlated with year of release (Spearman's r = -0.29)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "id": "fe267f7a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Rating</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.298428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rating</th>\n",
       "      <td>-0.298428</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Date    Rating\n",
       "Date    1.000000 -0.298428\n",
       "Rating -0.298428  1.000000"
      ]
     },
     "execution_count": 132,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movies[['Date','Rating']].corr(method='spearman')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7fb45258",
   "metadata": {},
   "source": [
    "#### Thinking point - \n",
    "No need to put this in your blog, but you could test if that correlation would be likely to have happened due to chance (is it significant?) by bootstrapping and seeing how often you got a correlation as far from zero as r=-0.29 if you resampled the data."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1a5e97ea",
   "metadata": {},
   "source": [
    "### Example 2: Does swearing spoil a good movie?\n",
    "\n",
    "Perhaps surpisingly, yes it does. At least, movies with no swearing (Profanity) at all seem to get slightly higher ratings.\n",
    "\n",
    "In the plot below there is a small but perceptible advantage in ratings for movies with no Profanity - the average rating for a movie with no profanity was a third of one point (out of ten) higher than one with profanity!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "id": "10245f3c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "mean rating - no profanity = 6.918087318087323\n",
      "mean rating - with profanity = 6.5885078534031285\n"
     ]
    }
   ],
   "source": [
    "print('mean rating - no profanity = ' + str(movies[movies['Profanity']=='None']['Rating'].mean()))\n",
    "print('mean rating - with profanity = ' + str(movies[movies['Profanity']!='None']['Rating'].mean()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "id": "d7f01129",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Profanity', ylabel='Rating'>"
      ]
     },
     "execution_count": 134,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot ratings by 'alcohol content' of the movie\n",
    "# note that I have set the order of the violins to increasing alcohol, rather than the default order which wasn't meaningful\n",
    "sns.violinplot(data=movies, x='Profanity', y='Rating', order=['None','Mild','Moderate','Severe'])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "413e48f1",
   "metadata": {},
   "source": [
    "That said, there was an explosion in profanity from the 1960s onwards - so maybe this just reflects the fact that the old classics are the best movies!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "id": "e994d5e3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0.98, 'Distribution profanity ratings over time')"
      ]
     },
     "execution_count": 135,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set_palette('rocket')\n",
    "\n",
    "sns.kdeplot(\n",
    "    data=movies, \n",
    "    x='Date',  \n",
    "    hue='Profanity', \n",
    "    multiple='stack',\n",
    "    hue_order=['None','Mild','Moderate','Severe'])\n",
    "\n",
    "plt.suptitle('Distribution profanity ratings over time', fontsize=16)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "155d5660",
   "metadata": {},
   "source": [
    "#### By the way....\n",
    "\n",
    "Don't put this in your blog as it is too technical, but you might be interested to see it:\n",
    "\n",
    "It looks like there is only a tiny effect of Profanity on ratings, but could it have occurred due to chance?\n",
    "\n",
    "We construct a bootstrapped confidence interval for the difference in ratings between movies with and without profanity:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "id": "178f3c68",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "481\n",
      "3965\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0, 'Difference of means: no profanity- profanity')"
      ]
     },
     "execution_count": 136,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "nReps = 10000\n",
    "mDiff=np.empty(nReps)\n",
    "n1=len(movies[movies['Profanity']=='None'])\n",
    "n2=len(movies[movies['Profanity']!='None'])\n",
    "\n",
    "print(n1)\n",
    "print(n2)\n",
    "\n",
    "for i in range(nReps):\n",
    "    sample1 = movies[movies['Profanity']=='None'].sample(n1, replace=True)\n",
    "    sample2 = movies[movies['Profanity']!='None'].sample(n2, replace=True)\n",
    "    mDiff[i]= sample1['Rating'].mean()-sample2['Rating'].mean()\n",
    "    \n",
    "sns.histplot(mDiff)\n",
    "plt.xlabel('Difference of means: no profanity- profanity')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fdf1df81",
   "metadata": {},
   "source": [
    "Since the difference of means is almost always greater than ero, we can be confident that movies with no profanity really do have higher mean ratings - even if the difference is less than 0.3/10 points!"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "79ada6b0",
   "metadata": {},
   "source": [
    "## Useful information: Movie Certificates\n",
    "\n",
    "The movie certificates given are mostly US certificates but there are different schemes in use for movies shown in cinema and on TV. There are a fair few certificates in use in the database, some of which relate to only a few titles:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "id": "a6e6529b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "R            1885\n",
       "PG-13        1145\n",
       "PG            530\n",
       "None          296\n",
       "Not Rated     189\n",
       "TV-MA         109\n",
       "G              70\n",
       "Approved       42\n",
       "TV-14          35\n",
       "Passed         24\n",
       "NC-17          14\n",
       "TV-PG          13\n",
       "E              12\n",
       "(Banned)       10\n",
       "TV-G           10\n",
       "GP              6\n",
       "X               6\n",
       "TV-Y7           5\n",
       "M               3\n",
       "M/PG            2\n",
       "Name: Certificate, dtype: int64"
      ]
     },
     "execution_count": 137,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movies['Certificate'].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9beeba7f",
   "metadata": {},
   "source": [
    "\n",
    "There are also some old (pre 1968) or international certificates mixed in there\n",
    "\n",
    "To meaningfully use these data (for example to answer the question, are movies rated 15 the worst?) it would be helpful to group these into a smaller set of classifications - for example the closest UK equivalent \n",
    "\n",
    "UK movie ratings are:\n",
    "<ul>\n",
    "    <li> U - Universal - suitable for all (including young children)\n",
    "    <li> PG - Parental Guidance - may be unsuitable for very young children\n",
    "    <li> 12,15,18 - Not suitable for persons under the age of 12,15 or 18 respectively\n",
    "</ul>\n",
    "\n",
    "Alternatively, to answer the question about straight-to-TV movies, you will want to separate out those with a certificate beginning 'TV' (only ever shown on TV) from the others\n",
    "\n",
    "The meaning of certificates should be Googlable but here are my notes on the certificates used in the dataset:\n",
    "\n",
    "<ul>\n",
    "<li>TV-Y: Designed to be appropriate for all children\n",
    "<li>TV-Y7: Suitable for ages 7 and up\n",
    "<li>G: Suitable for General Audiences\n",
    "<li>TV-G: Suitable for General Audiences\n",
    "<li>PG: Parental Guidance suggested\n",
    "<li>TV-PG: Parental Guidance suggested\n",
    "<li>PG-13: Parents strongly cautioned. May be Inappropriate for ages 12 and under.\n",
    "<li>TV-14: Parents strongly cautioned. May not be suitable for ages 14 and under.\n",
    "<li>R: Restricted. May be inappropriate for ages 17 and under.\n",
    "<li>TV-MA: For Mature Audiences. May not be suitable for ages 17 and under.\n",
    "<li>NC-17: Inappropriate for ages 17 and under\n",
    "<li>M - Mature\n",
    "<li>TV-Y7 - suitable for children over 7\n",
    "<li>banned/approved/passed - pre 1968 classifications\n",
    "</ul>\n",
    "\n",
    "In reclassifying the movies you may consider excluding some cases that don't clearly fall into one category or another, for example the pre-1968 movies. \n",
    "\n",
    "There are also some remaining mysteries, for example, one certificate I was not able to understand was 'E': Google tells me that 'E' stands for educational or exempt but if I look which movies have this rating, I'm not so sure this is correct:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "id": "071f7e6c",
   "metadata": {},
   "outputs": [
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       "      <td>35374.0</td>\n",
       "      <td>Drama, Musical, Romance</td>\n",
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       "      <th>1978</th>\n",
       "      <td>The Comeback Trail</td>\n",
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       "      <td>Mild</td>\n",
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       "      <td>Dragon Rider</td>\n",
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      "text/plain": [
       "                                Name  Date  Rating     Votes  \\\n",
       "429                             Luca  2021     7.5  112694.0   \n",
       "521          Space Jam: A New Legacy  2021     4.4   56919.0   \n",
       "526                Godzilla vs. Kong  2021     6.4  176046.0   \n",
       "581            PAW Patrol: The Movie  2021     6.2    3898.0   \n",
       "851                   In the Heights  2021     7.4   35374.0   \n",
       "872   The Boss Baby: Family Business  2021     5.9   11863.0   \n",
       "1978              The Comeback Trail  2020     5.6    4961.0   \n",
       "2654     Peter Rabbit 2: The Runaway  2021     6.2    7310.0   \n",
       "2877                  Spirit Untamed  2021     5.4    2585.0   \n",
       "3156     AINBO: Spirit of the Amazon  2021     4.7     933.0   \n",
       "4814                    Dragon Rider  2020     5.6    1199.0   \n",
       "5964                    Dragon Rider  2020     5.6    1199.0   \n",
       "\n",
       "                             Genre  Duration  Type Certificate  Episodes  \\\n",
       "429   Animation, Adventure, Comedy      95.0  Film           E       NaN   \n",
       "521   Animation, Adventure, Comedy     115.0  Film           E       NaN   \n",
       "526       Action, Sci-Fi, Thriller     113.0  Film           E       NaN   \n",
       "581   Animation, Adventure, Comedy      86.0  Film           E       NaN   \n",
       "851        Drama, Musical, Romance     143.0  Film           E       NaN   \n",
       "872   Animation, Adventure, Comedy     107.0  Film           E       NaN   \n",
       "1978                 Comedy, Crime     104.0  Film           E       NaN   \n",
       "2654  Animation, Adventure, Comedy      93.0  Film           E       NaN   \n",
       "2877  Animation, Adventure, Comedy      88.0  Film           E       NaN   \n",
       "3156  Animation, Adventure, Comedy      84.0  Film           E       NaN   \n",
       "4814  Animation, Adventure, Comedy      91.0  Film           E       NaN   \n",
       "5964  Animation, Adventure, Comedy      91.0  Film           E       NaN   \n",
       "\n",
       "       Nudity  Violence Profanity  Alcohol Frightening  \n",
       "429      None      Mild      None     None        Mild  \n",
       "521      None      Mild      Mild     Mild        Mild  \n",
       "526      None  Moderate      Mild     Mild    Moderate  \n",
       "581      Mild      Mild      None     None        Mild  \n",
       "851      Mild      None      Mild     Mild        None  \n",
       "872      Mild      Mild      Mild     None        Mild  \n",
       "1978     Mild  Moderate  Moderate     Mild        Mild  \n",
       "2654     None      Mild      None     None        Mild  \n",
       "2877     None      Mild      Mild     None        Mild  \n",
       "3156  No Rate   No Rate   No Rate  No Rate     No Rate  \n",
       "4814     None      Mild      Mild     Mild        Mild  \n",
       "5964     None      Mild      Mild     Mild        Mild  "
      ]
     },
     "execution_count": 138,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movies[movies['Certificate']=='E']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0f579ca1",
   "metadata": {},
   "source": [
    "You may find this example useful in creating a new column for UK classifications:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "id": "8a215669",
   "metadata": {},
   "outputs": [],
   "source": [
    "#first, create a new column with the default value 'None'\n",
    "movies = movies.assign(classification = 'none')\n",
    "\n",
    "#np.isin to do a boolean check on every element of the array and see if it is in a different list (your list of interest)\n",
    "# use np.where to get booleans where that condition is met, assign a new value if true, or do nothing if not true\n",
    "movies['classification'] = np.where(np.isin(movies.Certificate, ['G', 'TV-G', 'TV-Y', 'TV-7']), 'U', movies.classification)\n",
    "movies['classification'] = np.where(np.isin(movies.Certificate, ['PG', 'TV-PG']), 'PG', movies.classification)\n",
    "\n",
    "\n",
    "#the syntax for this is:\n",
    "# np.where(set condition, do this if condition is met, otherwise do this)\n",
    "# np.isin(array_to_test, list of values you want to check if the element matches)\n",
    "\n",
    "#so the code is doing:\n",
    "# finding where the movie certificate is either G, TV-G, TV-Y or TV-7\n",
    "# setting the value of 'classification' to 'U' if that movie meets the condition\n",
    "# if not, it sets the value of 'classification' to itself (i.e. it does nothing)\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "id": "a636e08e",
   "metadata": {},
   "outputs": [
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       "      <th>1002</th>\n",
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       "      <th>1073</th>\n",
       "      <td>The Lion King</td>\n",
       "      <td>1994</td>\n",
       "      <td>8.5</td>\n",
       "      <td>986883.0</td>\n",
       "      <td>Animation, Adventure, Drama</td>\n",
       "      <td>88.0</td>\n",
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       "      <td>Pocahontas</td>\n",
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       "      <th>5903</th>\n",
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       "      <td>2004</td>\n",
       "      <td>6.6</td>\n",
       "      <td>188010.0</td>\n",
       "      <td>Animation, Adventure, Comedy</td>\n",
       "      <td>100.0</td>\n",
       "      <td>Film</td>\n",
       "      <td>G</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Mild</td>\n",
       "      <td>U</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5944</th>\n",
       "      <td>Chitty Chitty Bang Bang</td>\n",
       "      <td>1968</td>\n",
       "      <td>6.9</td>\n",
       "      <td>43331.0</td>\n",
       "      <td>Adventure, Family, Fantasy</td>\n",
       "      <td>144.0</td>\n",
       "      <td>Film</td>\n",
       "      <td>G</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>Mild</td>\n",
       "      <td>None</td>\n",
       "      <td>Mild</td>\n",
       "      <td>Mild</td>\n",
       "      <td>U</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6064</th>\n",
       "      <td>The Princess Diaries 2: Royal Engagement</td>\n",
       "      <td>2004</td>\n",
       "      <td>5.8</td>\n",
       "      <td>77450.0</td>\n",
       "      <td>Comedy, Family, Romance</td>\n",
       "      <td>113.0</td>\n",
       "      <td>Film</td>\n",
       "      <td>G</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>U</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>80 rows × 15 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                          Name  Date  Rating     Votes  \\\n",
       "392                              Halloweentown  1998     6.7   15617.0   \n",
       "426                         Love Strikes Twice  2021     7.2     458.0   \n",
       "889                                       Cars  2006     7.1  388952.0   \n",
       "1002                     2001: A Space Odyssey  1968     8.3  631754.0   \n",
       "1073                             The Lion King  1994     8.5  986883.0   \n",
       "...                                        ...   ...     ...       ...   \n",
       "5701                                Pocahontas  1995     6.7  177837.0   \n",
       "5803                                Robin Hood  1973     7.6  120934.0   \n",
       "5903                         The Polar Express  2004     6.6  188010.0   \n",
       "5944                   Chitty Chitty Bang Bang  1968     6.9   43331.0   \n",
       "6064  The Princess Diaries 2: Royal Engagement  2004     5.8   77450.0   \n",
       "\n",
       "                             Genre  Duration  Type Certificate  Episodes  \\\n",
       "392      Adventure, Comedy, Family      84.0  Film        TV-G       NaN   \n",
       "426       Comedy, Mystery, Romance      84.0  Film        TV-G       NaN   \n",
       "889   Animation, Adventure, Comedy     117.0  Film           G       NaN   \n",
       "1002             Adventure, Sci-Fi     149.0  Film           G       NaN   \n",
       "1073   Animation, Adventure, Drama      88.0  Film           G       NaN   \n",
       "...                            ...       ...   ...         ...       ...   \n",
       "5701   Animation, Adventure, Drama      81.0  Film           G       NaN   \n",
       "5803  Animation, Adventure, Comedy      83.0  Film           G       NaN   \n",
       "5903  Animation, Adventure, Comedy     100.0  Film           G       NaN   \n",
       "5944    Adventure, Family, Fantasy     144.0  Film           G       NaN   \n",
       "6064       Comedy, Family, Romance     113.0  Film           G       NaN   \n",
       "\n",
       "     Nudity Violence Profanity Alcohol Frightening classification  \n",
       "392    None     Mild      None    None        Mild              U  \n",
       "426    None     None      None    None        None              U  \n",
       "889    None     None      Mild    None        Mild              U  \n",
       "1002   None     Mild      None    None    Moderate              U  \n",
       "1073   None     Mild      None    None    Moderate              U  \n",
       "...     ...      ...       ...     ...         ...            ...  \n",
       "5701   None     Mild      None    None        Mild              U  \n",
       "5803   None     Mild      None    Mild        Mild              U  \n",
       "5903   None     None      None    None        Mild              U  \n",
       "5944   None     Mild      None    Mild        Mild              U  \n",
       "6064   None     None      None    None        None              U  \n",
       "\n",
       "[80 rows x 15 columns]"
      ]
     },
     "execution_count": 141,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movies[movies['classification']=='U']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5ccfd150",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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