IMDB_research.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###### Data Science Research Methods IMDB"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***\n",
    "\n",
    "# SussexBudgetProductions\n",
    "\n",
    "SussexBudgetProductions is one East Sussex's leading production companies, based in Brighton. We are committed to keeping our films high-end, high-impact and low-budget.\n",
    "\n",
    "## Actionable profit plan\n",
    "#### Report outline\n",
    "\n",
    "Below I have outlined an actionable profit plan in which I recommend a suitable action plan for a successful movie. Previously SussexBudgetProductions invested in creating a comedy-action-thriller with a budget of \\\\$500,000 with a gross of only 20 percent.\n",
    "In this report, I will show how we can create a high-profit, high-impact film with a budget of  \\\\$1,500,00.\n",
    "\n",
    "Brief Report Summary: \n",
    "\n",
    "**Part 1**: What data are we using?\n",
    "\n",
    "**Part 2**: Clean and filter the data set.\n",
    "\n",
    "**Part 3**: Exploratory data analysis\n",
    "\n",
    "**Part 4**: Hypothesis testing\n",
    "\n",
    "**Part 5**: Summary and recommendations"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***\n",
    "\n",
    "## Part 1: What data are we using?\n",
    "\n",
    "The IMDb (Internet Movie Database) is one of the most recognized names for its comprehensive online database collection of movies, short films and TV series. Unlike other sites, IMDb's reviews come solely from users. Thus, IMDb's biggest strength is that its scores gives us a good idea of what 'normal' consumers think of it.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "scrolled": false
   },
   "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>color</th>\n",
       "      <th>director_name</th>\n",
       "      <th>num_critic_for_reviews</th>\n",
       "      <th>duration</th>\n",
       "      <th>profit</th>\n",
       "      <th>director_facebook_likes</th>\n",
       "      <th>actor_3_facebook_likes</th>\n",
       "      <th>actor_2_name</th>\n",
       "      <th>actor_1_facebook_likes</th>\n",
       "      <th>gross</th>\n",
       "      <th>...</th>\n",
       "      <th>num_user_for_reviews</th>\n",
       "      <th>language</th>\n",
       "      <th>country</th>\n",
       "      <th>content_rating</th>\n",
       "      <th>budget</th>\n",
       "      <th>title_year</th>\n",
       "      <th>actor_2_facebook_likes</th>\n",
       "      <th>imdb_score</th>\n",
       "      <th>aspect_ratio</th>\n",
       "      <th>movie_facebook_likes</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Color</td>\n",
       "      <td>James Cameron</td>\n",
       "      <td>723.0</td>\n",
       "      <td>178.0</td>\n",
       "      <td>523505847.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>855.0</td>\n",
       "      <td>Joel David Moore</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>760505847.0</td>\n",
       "      <td>...</td>\n",
       "      <td>3054.0</td>\n",
       "      <td>English</td>\n",
       "      <td>USA</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>237000000.0</td>\n",
       "      <td>2009.0</td>\n",
       "      <td>936.0</td>\n",
       "      <td>7.9</td>\n",
       "      <td>1.8</td>\n",
       "      <td>33000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Color</td>\n",
       "      <td>Gore Verbinski</td>\n",
       "      <td>302.0</td>\n",
       "      <td>169.0</td>\n",
       "      <td>9404152.0</td>\n",
       "      <td>563.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>Orlando Bloom</td>\n",
       "      <td>40000.0</td>\n",
       "      <td>309404152.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1238.0</td>\n",
       "      <td>English</td>\n",
       "      <td>USA</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>300000000.0</td>\n",
       "      <td>2007.0</td>\n",
       "      <td>5000.0</td>\n",
       "      <td>7.1</td>\n",
       "      <td>2.4</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Color</td>\n",
       "      <td>Sam Mendes</td>\n",
       "      <td>602.0</td>\n",
       "      <td>148.0</td>\n",
       "      <td>-44925825.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>161.0</td>\n",
       "      <td>Rory Kinnear</td>\n",
       "      <td>11000.0</td>\n",
       "      <td>200074175.0</td>\n",
       "      <td>...</td>\n",
       "      <td>994.0</td>\n",
       "      <td>English</td>\n",
       "      <td>UK</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>245000000.0</td>\n",
       "      <td>2015.0</td>\n",
       "      <td>393.0</td>\n",
       "      <td>6.8</td>\n",
       "      <td>2.4</td>\n",
       "      <td>85000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Color</td>\n",
       "      <td>Christopher Nolan</td>\n",
       "      <td>813.0</td>\n",
       "      <td>164.0</td>\n",
       "      <td>198130642.0</td>\n",
       "      <td>22000.0</td>\n",
       "      <td>23000.0</td>\n",
       "      <td>Christian Bale</td>\n",
       "      <td>27000.0</td>\n",
       "      <td>448130642.0</td>\n",
       "      <td>...</td>\n",
       "      <td>2701.0</td>\n",
       "      <td>English</td>\n",
       "      <td>USA</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>250000000.0</td>\n",
       "      <td>2012.0</td>\n",
       "      <td>23000.0</td>\n",
       "      <td>8.5</td>\n",
       "      <td>2.4</td>\n",
       "      <td>164000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Doug Walker</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>131.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Rob Walker</td>\n",
       "      <td>131.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12.0</td>\n",
       "      <td>7.1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 29 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   color      director_name  num_critic_for_reviews  duration      profit  \\\n",
       "0  Color      James Cameron                   723.0     178.0 523505847.0   \n",
       "1  Color     Gore Verbinski                   302.0     169.0   9404152.0   \n",
       "2  Color         Sam Mendes                   602.0     148.0 -44925825.0   \n",
       "3  Color  Christopher Nolan                   813.0     164.0 198130642.0   \n",
       "4    NaN        Doug Walker                     NaN       NaN         NaN   \n",
       "\n",
       "   director_facebook_likes  actor_3_facebook_likes      actor_2_name  \\\n",
       "0                      0.0                   855.0  Joel David Moore   \n",
       "1                    563.0                  1000.0     Orlando Bloom   \n",
       "2                      0.0                   161.0      Rory Kinnear   \n",
       "3                  22000.0                 23000.0    Christian Bale   \n",
       "4                    131.0                     NaN        Rob Walker   \n",
       "\n",
       "   actor_1_facebook_likes       gross  ... num_user_for_reviews language  \\\n",
       "0                  1000.0 760505847.0  ...               3054.0  English   \n",
       "1                 40000.0 309404152.0  ...               1238.0  English   \n",
       "2                 11000.0 200074175.0  ...                994.0  English   \n",
       "3                 27000.0 448130642.0  ...               2701.0  English   \n",
       "4                   131.0         NaN  ...                  NaN      NaN   \n",
       "\n",
       "  country  content_rating      budget title_year  actor_2_facebook_likes  \\\n",
       "0     USA           PG-13 237000000.0     2009.0                   936.0   \n",
       "1     USA           PG-13 300000000.0     2007.0                  5000.0   \n",
       "2      UK           PG-13 245000000.0     2015.0                   393.0   \n",
       "3     USA           PG-13 250000000.0     2012.0                 23000.0   \n",
       "4     NaN             NaN         NaN        NaN                    12.0   \n",
       "\n",
       "  imdb_score aspect_ratio  movie_facebook_likes  \n",
       "0        7.9          1.8                 33000  \n",
       "1        7.1          2.4                     0  \n",
       "2        6.8          2.4                 85000  \n",
       "3        8.5          2.4                164000  \n",
       "4        7.1          NaN                     0  \n",
       "\n",
       "[5 rows x 29 columns]"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Here, I am downloading the data set which is stored in a file `movie_metadata.csv`\n",
    "#To help analyse the data, I imported a few python libraries which contain a useful set of functions\n",
    "\n",
    "myfile='movie_metadata.csv'\n",
    "import numpy as np\n",
    "from matplotlib import pyplot as plt\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "pd.set_option('display.float_format', lambda x: '%.1f' % x)\n",
    "\n",
    "myfile = 'movie_metadata.csv'\n",
    "\n",
    "#read the movie metadata file into a dataframe in pandas\n",
    "\n",
    "df = pd.read_csv(myfile,index_col=None)\n",
    "\n",
    "#As SussexBudgetProductions is commited to investing in the most profitable film\n",
    "#Need to add a profit column\n",
    "#do this by subtracting the budget from the gross\n",
    "\n",
    "df.insert(4, column='profit', value=df['gross']-df['budget'])\n",
    "\n",
    "#What does our data look like?\n",
    "\n",
    "df.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(5043, 29)"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#This means we have 5043 rows and 29 columns\n",
    "\n",
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": true
   },
   "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>movie_title</th>\n",
       "      <th>title_year</th>\n",
       "      <th>director_name</th>\n",
       "      <th>gross</th>\n",
       "      <th>budget</th>\n",
       "      <th>profit</th>\n",
       "      <th>genres</th>\n",
       "      <th>country</th>\n",
       "      <th>language</th>\n",
       "      <th>imdb_score</th>\n",
       "      <th>...</th>\n",
       "      <th>actor_3_facebook_likes</th>\n",
       "      <th>num_critic_for_reviews</th>\n",
       "      <th>movie_facebook_likes</th>\n",
       "      <th>color</th>\n",
       "      <th>plot_keywords</th>\n",
       "      <th>movie_imdb_link</th>\n",
       "      <th>aspect_ratio</th>\n",
       "      <th>facenumber_in_poster</th>\n",
       "      <th>cast_total_facebook_likes</th>\n",
       "      <th>num_voted_users</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Avatar</td>\n",
       "      <td>2009.0</td>\n",
       "      <td>James Cameron</td>\n",
       "      <td>760505847.0</td>\n",
       "      <td>237000000.0</td>\n",
       "      <td>523505847.0</td>\n",
       "      <td>Action|Adventure|Fantasy|Sci-Fi</td>\n",
       "      <td>USA</td>\n",
       "      <td>English</td>\n",
       "      <td>7.9</td>\n",
       "      <td>...</td>\n",
       "      <td>855.0</td>\n",
       "      <td>723.0</td>\n",
       "      <td>33000</td>\n",
       "      <td>Color</td>\n",
       "      <td>avatar|future|marine|native|paraplegic</td>\n",
       "      <td>http://www.imdb.com/title/tt0499549/?ref_=fn_t...</td>\n",
       "      <td>1.8</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4834</td>\n",
       "      <td>886204</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Pirates of the Caribbean: At World's End</td>\n",
       "      <td>2007.0</td>\n",
       "      <td>Gore Verbinski</td>\n",
       "      <td>309404152.0</td>\n",
       "      <td>300000000.0</td>\n",
       "      <td>9404152.0</td>\n",
       "      <td>Action|Adventure|Fantasy</td>\n",
       "      <td>USA</td>\n",
       "      <td>English</td>\n",
       "      <td>7.1</td>\n",
       "      <td>...</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>302.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Color</td>\n",
       "      <td>goddess|marriage ceremony|marriage proposal|pi...</td>\n",
       "      <td>http://www.imdb.com/title/tt0449088/?ref_=fn_t...</td>\n",
       "      <td>2.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>48350</td>\n",
       "      <td>471220</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Spectre</td>\n",
       "      <td>2015.0</td>\n",
       "      <td>Sam Mendes</td>\n",
       "      <td>200074175.0</td>\n",
       "      <td>245000000.0</td>\n",
       "      <td>-44925825.0</td>\n",
       "      <td>Action|Adventure|Thriller</td>\n",
       "      <td>UK</td>\n",
       "      <td>English</td>\n",
       "      <td>6.8</td>\n",
       "      <td>...</td>\n",
       "      <td>161.0</td>\n",
       "      <td>602.0</td>\n",
       "      <td>85000</td>\n",
       "      <td>Color</td>\n",
       "      <td>bomb|espionage|sequel|spy|terrorist</td>\n",
       "      <td>http://www.imdb.com/title/tt2379713/?ref_=fn_t...</td>\n",
       "      <td>2.4</td>\n",
       "      <td>1.0</td>\n",
       "      <td>11700</td>\n",
       "      <td>275868</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>The Dark Knight Rises</td>\n",
       "      <td>2012.0</td>\n",
       "      <td>Christopher Nolan</td>\n",
       "      <td>448130642.0</td>\n",
       "      <td>250000000.0</td>\n",
       "      <td>198130642.0</td>\n",
       "      <td>Action|Thriller</td>\n",
       "      <td>USA</td>\n",
       "      <td>English</td>\n",
       "      <td>8.5</td>\n",
       "      <td>...</td>\n",
       "      <td>23000.0</td>\n",
       "      <td>813.0</td>\n",
       "      <td>164000</td>\n",
       "      <td>Color</td>\n",
       "      <td>deception|imprisonment|lawlessness|police offi...</td>\n",
       "      <td>http://www.imdb.com/title/tt1345836/?ref_=fn_t...</td>\n",
       "      <td>2.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>106759</td>\n",
       "      <td>1144337</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Star Wars: Episode VII - The Force Awakens    ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Doug Walker</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Documentary</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.1</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://www.imdb.com/title/tt5289954/?ref_=fn_t...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>143</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 28 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                         movie_title  title_year  \\\n",
       "0                                            Avatar       2009.0   \n",
       "1          Pirates of the Caribbean: At World's End       2007.0   \n",
       "2                                           Spectre       2015.0   \n",
       "3                             The Dark Knight Rises       2012.0   \n",
       "4  Star Wars: Episode VII - The Force Awakens    ...         NaN   \n",
       "\n",
       "       director_name       gross      budget      profit  \\\n",
       "0      James Cameron 760505847.0 237000000.0 523505847.0   \n",
       "1     Gore Verbinski 309404152.0 300000000.0   9404152.0   \n",
       "2         Sam Mendes 200074175.0 245000000.0 -44925825.0   \n",
       "3  Christopher Nolan 448130642.0 250000000.0 198130642.0   \n",
       "4        Doug Walker         NaN         NaN         NaN   \n",
       "\n",
       "                            genres country language  imdb_score  ...  \\\n",
       "0  Action|Adventure|Fantasy|Sci-Fi     USA  English         7.9  ...   \n",
       "1         Action|Adventure|Fantasy     USA  English         7.1  ...   \n",
       "2        Action|Adventure|Thriller      UK  English         6.8  ...   \n",
       "3                  Action|Thriller     USA  English         8.5  ...   \n",
       "4                      Documentary     NaN      NaN         7.1  ...   \n",
       "\n",
       "  actor_3_facebook_likes  num_critic_for_reviews  movie_facebook_likes  color  \\\n",
       "0                  855.0                   723.0                 33000  Color   \n",
       "1                 1000.0                   302.0                     0  Color   \n",
       "2                  161.0                   602.0                 85000  Color   \n",
       "3                23000.0                   813.0                164000  Color   \n",
       "4                    NaN                     NaN                     0    NaN   \n",
       "\n",
       "                                       plot_keywords  \\\n",
       "0             avatar|future|marine|native|paraplegic   \n",
       "1  goddess|marriage ceremony|marriage proposal|pi...   \n",
       "2                bomb|espionage|sequel|spy|terrorist   \n",
       "3  deception|imprisonment|lawlessness|police offi...   \n",
       "4                                                NaN   \n",
       "\n",
       "                                     movie_imdb_link  aspect_ratio  \\\n",
       "0  http://www.imdb.com/title/tt0499549/?ref_=fn_t...           1.8   \n",
       "1  http://www.imdb.com/title/tt0449088/?ref_=fn_t...           2.4   \n",
       "2  http://www.imdb.com/title/tt2379713/?ref_=fn_t...           2.4   \n",
       "3  http://www.imdb.com/title/tt1345836/?ref_=fn_t...           2.4   \n",
       "4  http://www.imdb.com/title/tt5289954/?ref_=fn_t...           NaN   \n",
       "\n",
       "  facenumber_in_poster  cast_total_facebook_likes  num_voted_users  \n",
       "0                  0.0                       4834           886204  \n",
       "1                  0.0                      48350           471220  \n",
       "2                  1.0                      11700           275868  \n",
       "3                  0.0                     106759          1144337  \n",
       "4                  0.0                        143                8  \n",
       "\n",
       "[5 rows x 28 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#We want to make our data frame easier to read so I changed the order of the columns\n",
    "\n",
    "titles=['movie_title', 'title_year', 'director_name','gross', 'budget', 'profit','genres', 'country', 'language', 'imdb_score','content_rating', 'duration',\n",
    "        'director_facebook_likes','actor_1_name','actor_1_facebook_likes', 'actor_2_name','actor_2_facebook_likes', 'actor_3_name','actor_3_facebook_likes', \n",
    " 'num_critic_for_reviews', 'movie_facebook_likes','color', 'plot_keywords', 'movie_imdb_link', 'aspect_ratio', 'facenumber_in_poster', 'cast_total_facebook_likes',\n",
    "        'num_voted_users']\n",
    "\n",
    "df=df[titles] \n",
    "\n",
    "#Looking at the new data frame\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "title_year                      2002.5\n",
       "gross                       48468407.5\n",
       "budget                      39752620.4\n",
       "profit                       5844717.0\n",
       "imdb_score                         6.4\n",
       "duration                         107.2\n",
       "director_facebook_likes          686.5\n",
       "actor_1_facebook_likes          6560.0\n",
       "actor_2_facebook_likes          1651.8\n",
       "actor_3_facebook_likes           645.0\n",
       "num_critic_for_reviews           140.2\n",
       "movie_facebook_likes            7526.0\n",
       "aspect_ratio                       2.2\n",
       "facenumber_in_poster               1.4\n",
       "cast_total_facebook_likes       9699.1\n",
       "num_voted_users                83668.2\n",
       "dtype: float64"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#What data do we have so far? Let's look at averages\n",
    "#Taking the .mean() of our data frame gives us the means of all the numerical columns\n",
    "\n",
    "df.mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***\n",
    "\n",
    "## Part 2: Cleaning and filtering our data\n",
    "\n",
    "\n",
    "### 2.1 Removing Duplicates\n",
    "\n",
    "Some of the data has been duplicated for various reasons, I used the imdb link to remove these. The `movie_imdb_link` is specific to each movie so it is a good indictor if any have been duplicated."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Using drop_duplicates to remove duplicates\n",
    "\n",
    "df.drop_duplicates(subset='movie_imdb_link',inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(4919, 28)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# We can see that there were 124 movies duplicated\n",
    "\n",
    "df.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.2 Are there any missing values?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "movie_title                     0\n",
       "title_year                    106\n",
       "director_name                 102\n",
       "gross                         863\n",
       "budget                        485\n",
       "profit                       1129\n",
       "genres                          0\n",
       "country                         5\n",
       "language                       12\n",
       "imdb_score                      0\n",
       "content_rating                301\n",
       "duration                       15\n",
       "director_facebook_likes       102\n",
       "actor_1_name                    7\n",
       "actor_1_facebook_likes          7\n",
       "actor_2_name                   13\n",
       "actor_2_facebook_likes         13\n",
       "actor_3_name                   23\n",
       "actor_3_facebook_likes         23\n",
       "num_critic_for_reviews         49\n",
       "movie_facebook_likes            0\n",
       "color                          19\n",
       "plot_keywords                 152\n",
       "movie_imdb_link                 0\n",
       "aspect_ratio                  326\n",
       "facenumber_in_poster           13\n",
       "cast_total_facebook_likes       0\n",
       "num_voted_users                 0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#This gives us a summary of the missing values\n",
    "\n",
    "df.isnull().sum()"
   ]
  },
  {
   "attachments": {
    "Screenshot%202021-11-09%20at%2012.46.32.png": {
     "image/png": "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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Above, we can see that there are missing values linked to gross and budget, which then leads to missing profit values. I will also remove the missing values for content rating as this could be something to analyse later.\n",
    "\n",
    "![Screenshot%202021-11-09%20at%2012.46.32.png](attachment:Screenshot%202021-11-09%20at%2012.46.32.png)\n",
    "\n",
    "### 2.3 Removing the missing values\n",
    "\n",
    "Below, we can see that these have now been removed. Notice there are still missing values for `actor_3_name` and `actor_3_facebook_likes`, this could be because there was no actor in these films, so I will keep these values in.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "#dropna removed the missing values that are in gross, budget and content rating\n",
    "\n",
    "df.dropna(subset=['gross','budget','content_rating'], inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "movie_title                   0\n",
       "title_year                    0\n",
       "director_name                 0\n",
       "gross                         0\n",
       "budget                        0\n",
       "profit                        0\n",
       "genres                        0\n",
       "country                       0\n",
       "language                      2\n",
       "imdb_score                    0\n",
       "content_rating                0\n",
       "duration                      0\n",
       "director_facebook_likes       0\n",
       "actor_1_name                  1\n",
       "actor_1_facebook_likes        1\n",
       "actor_2_name                  2\n",
       "actor_2_facebook_likes        2\n",
       "actor_3_name                  6\n",
       "actor_3_facebook_likes        6\n",
       "num_critic_for_reviews        1\n",
       "movie_facebook_likes          0\n",
       "color                         2\n",
       "plot_keywords                21\n",
       "movie_imdb_link               0\n",
       "aspect_ratio                 55\n",
       "facenumber_in_poster          6\n",
       "cast_total_facebook_likes     0\n",
       "num_voted_users               0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#checking that these values have been removed\n",
    "\n",
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3739, 28)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#the data frame size has decreased by 1,180 rows\n",
    "\n",
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "scrolled": true
   },
   "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>movie_title</th>\n",
       "      <th>title_year</th>\n",
       "      <th>director_name</th>\n",
       "      <th>gross</th>\n",
       "      <th>budget</th>\n",
       "      <th>profit</th>\n",
       "      <th>genres</th>\n",
       "      <th>country</th>\n",
       "      <th>language</th>\n",
       "      <th>imdb_score</th>\n",
       "      <th>...</th>\n",
       "      <th>actor_3_facebook_likes</th>\n",
       "      <th>num_critic_for_reviews</th>\n",
       "      <th>movie_facebook_likes</th>\n",
       "      <th>color</th>\n",
       "      <th>plot_keywords</th>\n",
       "      <th>movie_imdb_link</th>\n",
       "      <th>aspect_ratio</th>\n",
       "      <th>facenumber_in_poster</th>\n",
       "      <th>cast_total_facebook_likes</th>\n",
       "      <th>num_voted_users</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Avatar</td>\n",
       "      <td>2009.0</td>\n",
       "      <td>James Cameron</td>\n",
       "      <td>760505847.0</td>\n",
       "      <td>237000000.0</td>\n",
       "      <td>523505847.0</td>\n",
       "      <td>Action|Adventure|Fantasy|Sci-Fi</td>\n",
       "      <td>USA</td>\n",
       "      <td>English</td>\n",
       "      <td>7.9</td>\n",
       "      <td>...</td>\n",
       "      <td>855.0</td>\n",
       "      <td>723.0</td>\n",
       "      <td>33000</td>\n",
       "      <td>Color</td>\n",
       "      <td>avatar|future|marine|native|paraplegic</td>\n",
       "      <td>http://www.imdb.com/title/tt0499549/?ref_=fn_t...</td>\n",
       "      <td>1.8</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4834</td>\n",
       "      <td>886204</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Jurassic World</td>\n",
       "      <td>2015.0</td>\n",
       "      <td>Colin Trevorrow</td>\n",
       "      <td>652177271.0</td>\n",
       "      <td>150000000.0</td>\n",
       "      <td>502177271.0</td>\n",
       "      <td>Action|Adventure|Sci-Fi|Thriller</td>\n",
       "      <td>USA</td>\n",
       "      <td>English</td>\n",
       "      <td>7.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>644.0</td>\n",
       "      <td>150000</td>\n",
       "      <td>Color</td>\n",
       "      <td>dinosaur|disaster film|experiment gone wrong|j...</td>\n",
       "      <td>http://www.imdb.com/title/tt0369610/?ref_=fn_t...</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8458</td>\n",
       "      <td>418214</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Titanic</td>\n",
       "      <td>1997.0</td>\n",
       "      <td>James Cameron</td>\n",
       "      <td>658672302.0</td>\n",
       "      <td>200000000.0</td>\n",
       "      <td>458672302.0</td>\n",
       "      <td>Drama|Romance</td>\n",
       "      <td>USA</td>\n",
       "      <td>English</td>\n",
       "      <td>7.7</td>\n",
       "      <td>...</td>\n",
       "      <td>794.0</td>\n",
       "      <td>315.0</td>\n",
       "      <td>26000</td>\n",
       "      <td>Color</td>\n",
       "      <td>artist|love|ship|titanic|wet</td>\n",
       "      <td>http://www.imdb.com/title/tt0120338/?ref_=fn_t...</td>\n",
       "      <td>2.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>45223</td>\n",
       "      <td>793059</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3024</th>\n",
       "      <td>Star Wars: Episode IV - A New Hope</td>\n",
       "      <td>1977.0</td>\n",
       "      <td>George Lucas</td>\n",
       "      <td>460935665.0</td>\n",
       "      <td>11000000.0</td>\n",
       "      <td>449935665.0</td>\n",
       "      <td>Action|Adventure|Fantasy|Sci-Fi</td>\n",
       "      <td>USA</td>\n",
       "      <td>English</td>\n",
       "      <td>8.7</td>\n",
       "      <td>...</td>\n",
       "      <td>504.0</td>\n",
       "      <td>282.0</td>\n",
       "      <td>33000</td>\n",
       "      <td>Color</td>\n",
       "      <td>death star|empire|galactic war|princess|rebellion</td>\n",
       "      <td>http://www.imdb.com/title/tt0076759/?ref_=fn_t...</td>\n",
       "      <td>2.4</td>\n",
       "      <td>1.0</td>\n",
       "      <td>13485</td>\n",
       "      <td>911097</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3080</th>\n",
       "      <td>E.T. the Extra-Terrestrial</td>\n",
       "      <td>1982.0</td>\n",
       "      <td>Steven Spielberg</td>\n",
       "      <td>434949459.0</td>\n",
       "      <td>10500000.0</td>\n",
       "      <td>424449459.0</td>\n",
       "      <td>Family|Sci-Fi</td>\n",
       "      <td>USA</td>\n",
       "      <td>English</td>\n",
       "      <td>7.9</td>\n",
       "      <td>...</td>\n",
       "      <td>548.0</td>\n",
       "      <td>215.0</td>\n",
       "      <td>34000</td>\n",
       "      <td>Color</td>\n",
       "      <td>bicyclist|boy|doll|star wars reference|voice i...</td>\n",
       "      <td>http://www.imdb.com/title/tt0083866/?ref_=fn_t...</td>\n",
       "      <td>1.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2811</td>\n",
       "      <td>281842</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2334</th>\n",
       "      <td>Steamboy</td>\n",
       "      <td>2004.0</td>\n",
       "      <td>Katsuhiro Ôtomo</td>\n",
       "      <td>410388.0</td>\n",
       "      <td>2127519898.0</td>\n",
       "      <td>-2127109510.0</td>\n",
       "      <td>Action|Adventure|Animation|Family|Sci-Fi|Thriller</td>\n",
       "      <td>Japan</td>\n",
       "      <td>Japanese</td>\n",
       "      <td>6.9</td>\n",
       "      <td>...</td>\n",
       "      <td>101.0</td>\n",
       "      <td>105.0</td>\n",
       "      <td>973</td>\n",
       "      <td>Color</td>\n",
       "      <td>19th century|ball|boy|inventor|steam</td>\n",
       "      <td>http://www.imdb.com/title/tt0348121/?ref_=fn_t...</td>\n",
       "      <td>1.9</td>\n",
       "      <td>1.0</td>\n",
       "      <td>991</td>\n",
       "      <td>13727</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2323</th>\n",
       "      <td>Princess Mononoke</td>\n",
       "      <td>1997.0</td>\n",
       "      <td>Hayao Miyazaki</td>\n",
       "      <td>2298191.0</td>\n",
       "      <td>2400000000.0</td>\n",
       "      <td>-2397701809.0</td>\n",
       "      <td>Adventure|Animation|Fantasy</td>\n",
       "      <td>Japan</td>\n",
       "      <td>Japanese</td>\n",
       "      <td>8.4</td>\n",
       "      <td>...</td>\n",
       "      <td>745.0</td>\n",
       "      <td>174.0</td>\n",
       "      <td>11000</td>\n",
       "      <td>Color</td>\n",
       "      <td>anime|cult film|forest|princess|studio ghibli</td>\n",
       "      <td>http://www.imdb.com/title/tt0119698/?ref_=fn_t...</td>\n",
       "      <td>1.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2710</td>\n",
       "      <td>221552</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3005</th>\n",
       "      <td>Fateless</td>\n",
       "      <td>2005.0</td>\n",
       "      <td>Lajos Koltai</td>\n",
       "      <td>195888.0</td>\n",
       "      <td>2500000000.0</td>\n",
       "      <td>-2499804112.0</td>\n",
       "      <td>Drama|Romance|War</td>\n",
       "      <td>Hungary</td>\n",
       "      <td>Hungarian</td>\n",
       "      <td>7.1</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>73.0</td>\n",
       "      <td>607</td>\n",
       "      <td>Color</td>\n",
       "      <td>bus|death|gay slur|hatred|jewish</td>\n",
       "      <td>http://www.imdb.com/title/tt0367082/?ref_=fn_t...</td>\n",
       "      <td>2.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11</td>\n",
       "      <td>5603</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3859</th>\n",
       "      <td>Lady Vengeance</td>\n",
       "      <td>2005.0</td>\n",
       "      <td>Chan-wook Park</td>\n",
       "      <td>211667.0</td>\n",
       "      <td>4200000000.0</td>\n",
       "      <td>-4199788333.0</td>\n",
       "      <td>Crime|Drama</td>\n",
       "      <td>South Korea</td>\n",
       "      <td>Korean</td>\n",
       "      <td>7.7</td>\n",
       "      <td>...</td>\n",
       "      <td>38.0</td>\n",
       "      <td>202.0</td>\n",
       "      <td>4000</td>\n",
       "      <td>Color</td>\n",
       "      <td>cake|christian|lesbian sex|oral sex|pregnant s...</td>\n",
       "      <td>http://www.imdb.com/title/tt0451094/?ref_=fn_t...</td>\n",
       "      <td>2.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>907</td>\n",
       "      <td>53508</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2988</th>\n",
       "      <td>The Host</td>\n",
       "      <td>2006.0</td>\n",
       "      <td>Joon-ho Bong</td>\n",
       "      <td>2201412.0</td>\n",
       "      <td>12215500000.0</td>\n",
       "      <td>-12213298588.0</td>\n",
       "      <td>Comedy|Drama|Horror|Sci-Fi</td>\n",
       "      <td>South Korea</td>\n",
       "      <td>Korean</td>\n",
       "      <td>7.0</td>\n",
       "      <td>...</td>\n",
       "      <td>74.0</td>\n",
       "      <td>363.0</td>\n",
       "      <td>7000</td>\n",
       "      <td>Color</td>\n",
       "      <td>daughter|han river|monster|river|seoul</td>\n",
       "      <td>http://www.imdb.com/title/tt0468492/?ref_=fn_t...</td>\n",
       "      <td>1.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1173</td>\n",
       "      <td>68883</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3739 rows × 28 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                              movie_title  title_year     director_name  \\\n",
       "0                                 Avatar       2009.0     James Cameron   \n",
       "29                        Jurassic World       2015.0   Colin Trevorrow   \n",
       "26                               Titanic       1997.0     James Cameron   \n",
       "3024  Star Wars: Episode IV - A New Hope       1977.0      George Lucas   \n",
       "3080          E.T. the Extra-Terrestrial       1982.0  Steven Spielberg   \n",
       "...                                   ...         ...               ...   \n",
       "2334                            Steamboy       2004.0   Katsuhiro Ôtomo   \n",
       "2323                   Princess Mononoke       1997.0    Hayao Miyazaki   \n",
       "3005                            Fateless       2005.0      Lajos Koltai   \n",
       "3859                      Lady Vengeance       2005.0    Chan-wook Park   \n",
       "2988                            The Host       2006.0      Joon-ho Bong   \n",
       "\n",
       "           gross        budget         profit  \\\n",
       "0    760505847.0   237000000.0    523505847.0   \n",
       "29   652177271.0   150000000.0    502177271.0   \n",
       "26   658672302.0   200000000.0    458672302.0   \n",
       "3024 460935665.0    11000000.0    449935665.0   \n",
       "3080 434949459.0    10500000.0    424449459.0   \n",
       "...          ...           ...            ...   \n",
       "2334    410388.0  2127519898.0  -2127109510.0   \n",
       "2323   2298191.0  2400000000.0  -2397701809.0   \n",
       "3005    195888.0  2500000000.0  -2499804112.0   \n",
       "3859    211667.0  4200000000.0  -4199788333.0   \n",
       "2988   2201412.0 12215500000.0 -12213298588.0   \n",
       "\n",
       "                                                 genres      country  \\\n",
       "0                       Action|Adventure|Fantasy|Sci-Fi          USA   \n",
       "29                     Action|Adventure|Sci-Fi|Thriller          USA   \n",
       "26                                        Drama|Romance          USA   \n",
       "3024                    Action|Adventure|Fantasy|Sci-Fi          USA   \n",
       "3080                                      Family|Sci-Fi          USA   \n",
       "...                                                 ...          ...   \n",
       "2334  Action|Adventure|Animation|Family|Sci-Fi|Thriller        Japan   \n",
       "2323                        Adventure|Animation|Fantasy        Japan   \n",
       "3005                                  Drama|Romance|War      Hungary   \n",
       "3859                                        Crime|Drama  South Korea   \n",
       "2988                         Comedy|Drama|Horror|Sci-Fi  South Korea   \n",
       "\n",
       "       language  imdb_score  ... actor_3_facebook_likes  \\\n",
       "0       English         7.9  ...                  855.0   \n",
       "29      English         7.0  ...                 1000.0   \n",
       "26      English         7.7  ...                  794.0   \n",
       "3024    English         8.7  ...                  504.0   \n",
       "3080    English         7.9  ...                  548.0   \n",
       "...         ...         ...  ...                    ...   \n",
       "2334   Japanese         6.9  ...                  101.0   \n",
       "2323   Japanese         8.4  ...                  745.0   \n",
       "3005  Hungarian         7.1  ...                    0.0   \n",
       "3859     Korean         7.7  ...                   38.0   \n",
       "2988     Korean         7.0  ...                   74.0   \n",
       "\n",
       "      num_critic_for_reviews  movie_facebook_likes  color  \\\n",
       "0                      723.0                 33000  Color   \n",
       "29                     644.0                150000  Color   \n",
       "26                     315.0                 26000  Color   \n",
       "3024                   282.0                 33000  Color   \n",
       "3080                   215.0                 34000  Color   \n",
       "...                      ...                   ...    ...   \n",
       "2334                   105.0                   973  Color   \n",
       "2323                   174.0                 11000  Color   \n",
       "3005                    73.0                   607  Color   \n",
       "3859                   202.0                  4000  Color   \n",
       "2988                   363.0                  7000  Color   \n",
       "\n",
       "                                          plot_keywords  \\\n",
       "0                avatar|future|marine|native|paraplegic   \n",
       "29    dinosaur|disaster film|experiment gone wrong|j...   \n",
       "26                         artist|love|ship|titanic|wet   \n",
       "3024  death star|empire|galactic war|princess|rebellion   \n",
       "3080  bicyclist|boy|doll|star wars reference|voice i...   \n",
       "...                                                 ...   \n",
       "2334               19th century|ball|boy|inventor|steam   \n",
       "2323      anime|cult film|forest|princess|studio ghibli   \n",
       "3005                   bus|death|gay slur|hatred|jewish   \n",
       "3859  cake|christian|lesbian sex|oral sex|pregnant s...   \n",
       "2988             daughter|han river|monster|river|seoul   \n",
       "\n",
       "                                        movie_imdb_link  aspect_ratio  \\\n",
       "0     http://www.imdb.com/title/tt0499549/?ref_=fn_t...           1.8   \n",
       "29    http://www.imdb.com/title/tt0369610/?ref_=fn_t...           2.0   \n",
       "26    http://www.imdb.com/title/tt0120338/?ref_=fn_t...           2.4   \n",
       "3024  http://www.imdb.com/title/tt0076759/?ref_=fn_t...           2.4   \n",
       "3080  http://www.imdb.com/title/tt0083866/?ref_=fn_t...           1.9   \n",
       "...                                                 ...           ...   \n",
       "2334  http://www.imdb.com/title/tt0348121/?ref_=fn_t...           1.9   \n",
       "2323  http://www.imdb.com/title/tt0119698/?ref_=fn_t...           1.9   \n",
       "3005  http://www.imdb.com/title/tt0367082/?ref_=fn_t...           2.4   \n",
       "3859  http://www.imdb.com/title/tt0451094/?ref_=fn_t...           2.4   \n",
       "2988  http://www.imdb.com/title/tt0468492/?ref_=fn_t...           1.9   \n",
       "\n",
       "     facenumber_in_poster  cast_total_facebook_likes  num_voted_users  \n",
       "0                     0.0                       4834           886204  \n",
       "29                    0.0                       8458           418214  \n",
       "26                    0.0                      45223           793059  \n",
       "3024                  1.0                      13485           911097  \n",
       "3080                  0.0                       2811           281842  \n",
       "...                   ...                        ...              ...  \n",
       "2334                  1.0                        991            13727  \n",
       "2323                  0.0                       2710           221552  \n",
       "3005                  0.0                         11             5603  \n",
       "3859                  0.0                        907            53508  \n",
       "2988                  0.0                       1173            68883  \n",
       "\n",
       "[3739 rows x 28 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#We can see that the highest profiting film is Avatar, followed by Jurassic world \n",
    "\n",
    "df.sort_values(by=['profit'],ascending=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "We can see above that the film with the highest profit was Avatar, directed by James Cameron in 2009 and took in \\\\$523,505,845. \n",
    "However, this box office hit had a budget of \\\\$237,000,000 which is not in our bracket. We are only interested in the films that have been successful under the budget of \\\\$1.5 million.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.4 What about the currency?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "#checking a country where currency is not in dollars\n",
    "#checking South Korea in a new dataframe df_testingskorea\n",
    "\n",
    "df_testingskorea=df[df.country=='South Korea']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(8, 28)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#How many films are there made in south korea?\n",
    "\n",
    "df_testingskorea.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "scrolled": true
   },
   "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>movie_title</th>\n",
       "      <th>title_year</th>\n",
       "      <th>director_name</th>\n",
       "      <th>gross</th>\n",
       "      <th>budget</th>\n",
       "      <th>profit</th>\n",
       "      <th>genres</th>\n",
       "      <th>country</th>\n",
       "      <th>language</th>\n",
       "      <th>imdb_score</th>\n",
       "      <th>...</th>\n",
       "      <th>actor_3_facebook_likes</th>\n",
       "      <th>num_critic_for_reviews</th>\n",
       "      <th>movie_facebook_likes</th>\n",
       "      <th>color</th>\n",
       "      <th>plot_keywords</th>\n",
       "      <th>movie_imdb_link</th>\n",
       "      <th>aspect_ratio</th>\n",
       "      <th>facenumber_in_poster</th>\n",
       "      <th>cast_total_facebook_likes</th>\n",
       "      <th>num_voted_users</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4105</th>\n",
       "      <td>Oldboy</td>\n",
       "      <td>2003.0</td>\n",
       "      <td>Chan-wook Park</td>\n",
       "      <td>2181290.0</td>\n",
       "      <td>3000000.0</td>\n",
       "      <td>-818710.0</td>\n",
       "      <td>Drama|Mystery|Thriller</td>\n",
       "      <td>South Korea</td>\n",
       "      <td>Korean</td>\n",
       "      <td>8.4</td>\n",
       "      <td>...</td>\n",
       "      <td>38.0</td>\n",
       "      <td>305.0</td>\n",
       "      <td>43000</td>\n",
       "      <td>Color</td>\n",
       "      <td>brother sister relationship|hypnosis|imprisonm...</td>\n",
       "      <td>http://www.imdb.com/title/tt0364569/?ref_=fn_t...</td>\n",
       "      <td>2.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>852</td>\n",
       "      <td>356181</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3255</th>\n",
       "      <td>The Good, the Bad, the Weird</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>Jee-woon Kim</td>\n",
       "      <td>128486.0</td>\n",
       "      <td>10000000.0</td>\n",
       "      <td>-9871514.0</td>\n",
       "      <td>Action|Adventure|Comedy|Western</td>\n",
       "      <td>South Korea</td>\n",
       "      <td>Korean</td>\n",
       "      <td>7.3</td>\n",
       "      <td>...</td>\n",
       "      <td>7.0</td>\n",
       "      <td>152.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Color</td>\n",
       "      <td>bounty hunter|manchuria|map|train|treasure</td>\n",
       "      <td>http://www.imdb.com/title/tt0901487/?ref_=fn_t...</td>\n",
       "      <td>2.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>569</td>\n",
       "      <td>26156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2914</th>\n",
       "      <td>Tae Guk Gi: The Brotherhood of War</td>\n",
       "      <td>2004.0</td>\n",
       "      <td>Je-kyu Kang</td>\n",
       "      <td>1110186.0</td>\n",
       "      <td>12800000.0</td>\n",
       "      <td>-11689814.0</td>\n",
       "      <td>Action|Drama|War</td>\n",
       "      <td>South Korea</td>\n",
       "      <td>Korean</td>\n",
       "      <td>8.1</td>\n",
       "      <td>...</td>\n",
       "      <td>489.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Color</td>\n",
       "      <td>1950s|archeologist|korea|korean war|soldier</td>\n",
       "      <td>http://www.imdb.com/title/tt0386064/?ref_=fn_t...</td>\n",
       "      <td>2.4</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1730</td>\n",
       "      <td>31943</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2833</th>\n",
       "      <td>The Last Godfather</td>\n",
       "      <td>2010.0</td>\n",
       "      <td>Hyung-rae Shim</td>\n",
       "      <td>163591.0</td>\n",
       "      <td>13400000.0</td>\n",
       "      <td>-13236409.0</td>\n",
       "      <td>Comedy</td>\n",
       "      <td>South Korea</td>\n",
       "      <td>English</td>\n",
       "      <td>3.6</td>\n",
       "      <td>...</td>\n",
       "      <td>385.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>502</td>\n",
       "      <td>Color</td>\n",
       "      <td>mafia|mafia boss|mafiosi|mafioso|three word title</td>\n",
       "      <td>http://www.imdb.com/title/tt1584131/?ref_=fn_t...</td>\n",
       "      <td>1.8</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2895</td>\n",
       "      <td>912</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1564</th>\n",
       "      <td>Dragon Wars: D-War</td>\n",
       "      <td>2007.0</td>\n",
       "      <td>Hyung-rae Shim</td>\n",
       "      <td>10956379.0</td>\n",
       "      <td>35000000.0</td>\n",
       "      <td>-24043621.0</td>\n",
       "      <td>Action|Drama|Fantasy|Horror|Thriller</td>\n",
       "      <td>South Korea</td>\n",
       "      <td>English</td>\n",
       "      <td>3.6</td>\n",
       "      <td>...</td>\n",
       "      <td>535.0</td>\n",
       "      <td>93.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Color</td>\n",
       "      <td>antique shop|asian dragon|dragon|korean|reporter</td>\n",
       "      <td>http://www.imdb.com/title/tt0372873/?ref_=fn_t...</td>\n",
       "      <td>2.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3274</td>\n",
       "      <td>21506</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1325</th>\n",
       "      <td>Snowpiercer</td>\n",
       "      <td>2013.0</td>\n",
       "      <td>Joon-ho Bong</td>\n",
       "      <td>4563029.0</td>\n",
       "      <td>39200000.0</td>\n",
       "      <td>-34636971.0</td>\n",
       "      <td>Action|Drama|Sci-Fi|Thriller</td>\n",
       "      <td>South Korea</td>\n",
       "      <td>English</td>\n",
       "      <td>7.0</td>\n",
       "      <td>...</td>\n",
       "      <td>398.0</td>\n",
       "      <td>488.0</td>\n",
       "      <td>58000</td>\n",
       "      <td>Color</td>\n",
       "      <td>closed ecological system|perpetual winter|popu...</td>\n",
       "      <td>http://www.imdb.com/title/tt1706620/?ref_=fn_t...</td>\n",
       "      <td>1.9</td>\n",
       "      <td>5.0</td>\n",
       "      <td>12286</td>\n",
       "      <td>181472</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3859</th>\n",
       "      <td>Lady Vengeance</td>\n",
       "      <td>2005.0</td>\n",
       "      <td>Chan-wook Park</td>\n",
       "      <td>211667.0</td>\n",
       "      <td>4200000000.0</td>\n",
       "      <td>-4199788333.0</td>\n",
       "      <td>Crime|Drama</td>\n",
       "      <td>South Korea</td>\n",
       "      <td>Korean</td>\n",
       "      <td>7.7</td>\n",
       "      <td>...</td>\n",
       "      <td>38.0</td>\n",
       "      <td>202.0</td>\n",
       "      <td>4000</td>\n",
       "      <td>Color</td>\n",
       "      <td>cake|christian|lesbian sex|oral sex|pregnant s...</td>\n",
       "      <td>http://www.imdb.com/title/tt0451094/?ref_=fn_t...</td>\n",
       "      <td>2.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>907</td>\n",
       "      <td>53508</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2988</th>\n",
       "      <td>The Host</td>\n",
       "      <td>2006.0</td>\n",
       "      <td>Joon-ho Bong</td>\n",
       "      <td>2201412.0</td>\n",
       "      <td>12215500000.0</td>\n",
       "      <td>-12213298588.0</td>\n",
       "      <td>Comedy|Drama|Horror|Sci-Fi</td>\n",
       "      <td>South Korea</td>\n",
       "      <td>Korean</td>\n",
       "      <td>7.0</td>\n",
       "      <td>...</td>\n",
       "      <td>74.0</td>\n",
       "      <td>363.0</td>\n",
       "      <td>7000</td>\n",
       "      <td>Color</td>\n",
       "      <td>daughter|han river|monster|river|seoul</td>\n",
       "      <td>http://www.imdb.com/title/tt0468492/?ref_=fn_t...</td>\n",
       "      <td>1.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1173</td>\n",
       "      <td>68883</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 28 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                              movie_title  title_year   director_name  \\\n",
       "4105                              Oldboy       2003.0  Chan-wook Park   \n",
       "3255        The Good, the Bad, the Weird       2008.0    Jee-woon Kim   \n",
       "2914  Tae Guk Gi: The Brotherhood of War       2004.0     Je-kyu Kang   \n",
       "2833                  The Last Godfather       2010.0  Hyung-rae Shim   \n",
       "1564                  Dragon Wars: D-War       2007.0  Hyung-rae Shim   \n",
       "1325                         Snowpiercer       2013.0    Joon-ho Bong   \n",
       "3859                      Lady Vengeance       2005.0  Chan-wook Park   \n",
       "2988                            The Host       2006.0    Joon-ho Bong   \n",
       "\n",
       "          gross        budget         profit  \\\n",
       "4105  2181290.0     3000000.0      -818710.0   \n",
       "3255   128486.0    10000000.0     -9871514.0   \n",
       "2914  1110186.0    12800000.0    -11689814.0   \n",
       "2833   163591.0    13400000.0    -13236409.0   \n",
       "1564 10956379.0    35000000.0    -24043621.0   \n",
       "1325  4563029.0    39200000.0    -34636971.0   \n",
       "3859   211667.0  4200000000.0  -4199788333.0   \n",
       "2988  2201412.0 12215500000.0 -12213298588.0   \n",
       "\n",
       "                                    genres      country language  imdb_score  \\\n",
       "4105                Drama|Mystery|Thriller  South Korea   Korean         8.4   \n",
       "3255       Action|Adventure|Comedy|Western  South Korea   Korean         7.3   \n",
       "2914                      Action|Drama|War  South Korea   Korean         8.1   \n",
       "2833                                Comedy  South Korea  English         3.6   \n",
       "1564  Action|Drama|Fantasy|Horror|Thriller  South Korea  English         3.6   \n",
       "1325          Action|Drama|Sci-Fi|Thriller  South Korea  English         7.0   \n",
       "3859                           Crime|Drama  South Korea   Korean         7.7   \n",
       "2988            Comedy|Drama|Horror|Sci-Fi  South Korea   Korean         7.0   \n",
       "\n",
       "      ... actor_3_facebook_likes  num_critic_for_reviews  \\\n",
       "4105  ...                   38.0                   305.0   \n",
       "3255  ...                    7.0                   152.0   \n",
       "2914  ...                  489.0                    86.0   \n",
       "2833  ...                  385.0                     4.0   \n",
       "1564  ...                  535.0                    93.0   \n",
       "1325  ...                  398.0                   488.0   \n",
       "3859  ...                   38.0                   202.0   \n",
       "2988  ...                   74.0                   363.0   \n",
       "\n",
       "      movie_facebook_likes  color  \\\n",
       "4105                 43000  Color   \n",
       "3255                     0  Color   \n",
       "2914                     0  Color   \n",
       "2833                   502  Color   \n",
       "1564                     0  Color   \n",
       "1325                 58000  Color   \n",
       "3859                  4000  Color   \n",
       "2988                  7000  Color   \n",
       "\n",
       "                                          plot_keywords  \\\n",
       "4105  brother sister relationship|hypnosis|imprisonm...   \n",
       "3255         bounty hunter|manchuria|map|train|treasure   \n",
       "2914        1950s|archeologist|korea|korean war|soldier   \n",
       "2833  mafia|mafia boss|mafiosi|mafioso|three word title   \n",
       "1564   antique shop|asian dragon|dragon|korean|reporter   \n",
       "1325  closed ecological system|perpetual winter|popu...   \n",
       "3859  cake|christian|lesbian sex|oral sex|pregnant s...   \n",
       "2988             daughter|han river|monster|river|seoul   \n",
       "\n",
       "                                        movie_imdb_link  aspect_ratio  \\\n",
       "4105  http://www.imdb.com/title/tt0364569/?ref_=fn_t...           2.4   \n",
       "3255  http://www.imdb.com/title/tt0901487/?ref_=fn_t...           2.4   \n",
       "2914  http://www.imdb.com/title/tt0386064/?ref_=fn_t...           2.4   \n",
       "2833  http://www.imdb.com/title/tt1584131/?ref_=fn_t...           1.8   \n",
       "1564  http://www.imdb.com/title/tt0372873/?ref_=fn_t...           2.4   \n",
       "1325  http://www.imdb.com/title/tt1706620/?ref_=fn_t...           1.9   \n",
       "3859  http://www.imdb.com/title/tt0451094/?ref_=fn_t...           2.4   \n",
       "2988  http://www.imdb.com/title/tt0468492/?ref_=fn_t...           1.9   \n",
       "\n",
       "     facenumber_in_poster  cast_total_facebook_likes  num_voted_users  \n",
       "4105                  0.0                        852           356181  \n",
       "3255                  0.0                        569            26156  \n",
       "2914                  2.0                       1730            31943  \n",
       "2833                  5.0                       2895              912  \n",
       "1564                  0.0                       3274            21506  \n",
       "1325                  5.0                      12286           181472  \n",
       "3859                  0.0                        907            53508  \n",
       "2988                  0.0                       1173            68883  \n",
       "\n",
       "[8 rows x 28 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_testingskorea.sort_values(by=['profit'],ascending=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As we can see, and with further investigation, the budget for 'The Host' is ₩12 billion which is equivalent to $11miliion. With this information, I have chosen to only focus on films that are in dollars so will filter through to **only analyse USA films**."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.5 Filtering by year and country\n",
    "\n",
    "As most of the movies on IMDb are in dollars, I will filter through to only use the USA movies for our exploratory step. This is not ideal but, as seen above, some of the movies are in their own currency and will skew the numbers. I also decided to only look at movies after the year 2000 as the budget would be more accurate.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2128, 28)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Taking films after the year 2000\n",
    "df=df[df.title_year>=2000]\n",
    "\n",
    "#Only taking films that are made in the USA\n",
    "df=df[df.country=='USA']\n",
    "\n",
    "#Checking the size of the new dataframe\n",
    "#We now have 2660 rows\n",
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "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>title_year</th>\n",
       "      <th>gross</th>\n",
       "      <th>budget</th>\n",
       "      <th>profit</th>\n",
       "      <th>imdb_score</th>\n",
       "      <th>duration</th>\n",
       "      <th>director_facebook_likes</th>\n",
       "      <th>actor_1_facebook_likes</th>\n",
       "      <th>actor_2_facebook_likes</th>\n",
       "      <th>actor_3_facebook_likes</th>\n",
       "      <th>num_critic_for_reviews</th>\n",
       "      <th>movie_facebook_likes</th>\n",
       "      <th>aspect_ratio</th>\n",
       "      <th>facenumber_in_poster</th>\n",
       "      <th>cast_total_facebook_likes</th>\n",
       "      <th>num_voted_users</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>2128.0</td>\n",
       "      <td>2128.0</td>\n",
       "      <td>2128.0</td>\n",
       "      <td>2128.0</td>\n",
       "      <td>2128.0</td>\n",
       "      <td>2128.0</td>\n",
       "      <td>2128.0</td>\n",
       "      <td>2128.0</td>\n",
       "      <td>2127.0</td>\n",
       "      <td>2126.0</td>\n",
       "      <td>2127.0</td>\n",
       "      <td>2128.0</td>\n",
       "      <td>2094.0</td>\n",
       "      <td>2122.0</td>\n",
       "      <td>2128.0</td>\n",
       "      <td>2128.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>2007.5</td>\n",
       "      <td>58142943.9</td>\n",
       "      <td>44388376.3</td>\n",
       "      <td>13754567.6</td>\n",
       "      <td>6.3</td>\n",
       "      <td>107.8</td>\n",
       "      <td>768.5</td>\n",
       "      <td>8812.6</td>\n",
       "      <td>2378.9</td>\n",
       "      <td>921.3</td>\n",
       "      <td>191.3</td>\n",
       "      <td>11608.5</td>\n",
       "      <td>2.1</td>\n",
       "      <td>1.5</td>\n",
       "      <td>13240.7</td>\n",
       "      <td>108742.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>4.7</td>\n",
       "      <td>74344030.2</td>\n",
       "      <td>47263547.6</td>\n",
       "      <td>52857646.6</td>\n",
       "      <td>1.0</td>\n",
       "      <td>19.4</td>\n",
       "      <td>3088.5</td>\n",
       "      <td>18932.1</td>\n",
       "      <td>5231.9</td>\n",
       "      <td>2202.8</td>\n",
       "      <td>130.8</td>\n",
       "      <td>24796.9</td>\n",
       "      <td>0.4</td>\n",
       "      <td>2.3</td>\n",
       "      <td>22812.4</td>\n",
       "      <td>148081.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>2000.0</td>\n",
       "      <td>703.0</td>\n",
       "      <td>218.0</td>\n",
       "      <td>-190641321.0</td>\n",
       "      <td>1.6</td>\n",
       "      <td>53.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>22.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>2003.0</td>\n",
       "      <td>11427606.5</td>\n",
       "      <td>12000000.0</td>\n",
       "      <td>-9999936.2</td>\n",
       "      <td>5.7</td>\n",
       "      <td>95.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>834.0</td>\n",
       "      <td>450.0</td>\n",
       "      <td>248.2</td>\n",
       "      <td>98.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2366.8</td>\n",
       "      <td>20819.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>2008.0</td>\n",
       "      <td>33923883.5</td>\n",
       "      <td>29500000.0</td>\n",
       "      <td>1939822.0</td>\n",
       "      <td>6.4</td>\n",
       "      <td>104.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>2000.0</td>\n",
       "      <td>769.0</td>\n",
       "      <td>490.0</td>\n",
       "      <td>161.0</td>\n",
       "      <td>401.0</td>\n",
       "      <td>2.4</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5009.0</td>\n",
       "      <td>56739.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>2011.0</td>\n",
       "      <td>75073078.0</td>\n",
       "      <td>60000000.0</td>\n",
       "      <td>27106851.2</td>\n",
       "      <td>7.0</td>\n",
       "      <td>117.0</td>\n",
       "      <td>213.2</td>\n",
       "      <td>14000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>745.0</td>\n",
       "      <td>254.5</td>\n",
       "      <td>14000.0</td>\n",
       "      <td>2.4</td>\n",
       "      <td>2.0</td>\n",
       "      <td>18134.2</td>\n",
       "      <td>137580.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>2016.0</td>\n",
       "      <td>760505847.0</td>\n",
       "      <td>300000000.0</td>\n",
       "      <td>523505847.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>280.0</td>\n",
       "      <td>23000.0</td>\n",
       "      <td>640000.0</td>\n",
       "      <td>137000.0</td>\n",
       "      <td>23000.0</td>\n",
       "      <td>813.0</td>\n",
       "      <td>349000.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>43.0</td>\n",
       "      <td>656730.0</td>\n",
       "      <td>1676169.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       title_year       gross      budget       profit  imdb_score  duration  \\\n",
       "count      2128.0      2128.0      2128.0       2128.0      2128.0    2128.0   \n",
       "mean       2007.5  58142943.9  44388376.3   13754567.6         6.3     107.8   \n",
       "std           4.7  74344030.2  47263547.6   52857646.6         1.0      19.4   \n",
       "min        2000.0       703.0       218.0 -190641321.0         1.6      53.0   \n",
       "25%        2003.0  11427606.5  12000000.0   -9999936.2         5.7      95.0   \n",
       "50%        2008.0  33923883.5  29500000.0    1939822.0         6.4     104.0   \n",
       "75%        2011.0  75073078.0  60000000.0   27106851.2         7.0     117.0   \n",
       "max        2016.0 760505847.0 300000000.0  523505847.0         9.0     280.0   \n",
       "\n",
       "       director_facebook_likes  actor_1_facebook_likes  \\\n",
       "count                   2128.0                  2128.0   \n",
       "mean                     768.5                  8812.6   \n",
       "std                     3088.5                 18932.1   \n",
       "min                        0.0                     0.0   \n",
       "25%                       12.0                   834.0   \n",
       "50%                       60.0                  2000.0   \n",
       "75%                      213.2                 14000.0   \n",
       "max                    23000.0                640000.0   \n",
       "\n",
       "       actor_2_facebook_likes  actor_3_facebook_likes  num_critic_for_reviews  \\\n",
       "count                  2127.0                  2126.0                  2127.0   \n",
       "mean                   2378.9                   921.3                   191.3   \n",
       "std                    5231.9                  2202.8                   130.8   \n",
       "min                       0.0                     0.0                     1.0   \n",
       "25%                     450.0                   248.2                    98.0   \n",
       "50%                     769.0                   490.0                   161.0   \n",
       "75%                    1000.0                   745.0                   254.5   \n",
       "max                  137000.0                 23000.0                   813.0   \n",
       "\n",
       "       movie_facebook_likes  aspect_ratio  facenumber_in_poster  \\\n",
       "count                2128.0        2094.0                2122.0   \n",
       "mean                11608.5           2.1                   1.5   \n",
       "std                 24796.9           0.4                   2.3   \n",
       "min                     0.0           1.3                   0.0   \n",
       "25%                     0.0           1.9                   0.0   \n",
       "50%                   401.0           2.4                   1.0   \n",
       "75%                 14000.0           2.4                   2.0   \n",
       "max                349000.0          16.0                  43.0   \n",
       "\n",
       "       cast_total_facebook_likes  num_voted_users  \n",
       "count                     2128.0           2128.0  \n",
       "mean                     13240.7         108742.3  \n",
       "std                      22812.4         148081.0  \n",
       "min                          0.0             22.0  \n",
       "25%                       2366.8          20819.8  \n",
       "50%                       5009.0          56739.0  \n",
       "75%                      18134.2         137580.2  \n",
       "max                     656730.0        1676169.0  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Checking the averages of our new filtered dataframe\n",
    "\n",
    "df.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Closer eye at the stats...\n",
    "\n",
    "Averages: **Budget**: \\\\$44,388,376 | **Gross**: \\\\$58,142,943 | **Profit**: \\\\$13,754,567 | **IMDb score**: 6.3 \n",
    "\n",
    "As we have a budget of \\\\$1,500,000, we will only focus on movies in a similar bracket. However, it is interesting to see the publics response so certain genres so I will do a short exploratory analysis keeping the higher budget productions into consideration."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***\n",
    "\n",
    "## Part 3: Exploratory Data Analysis\n",
    "\n",
    "<div class=\"alert alert-block alert-info\">\n",
    "<b>Note:</b> All following analysis is only looking at titles made in the USA after the year 2000.</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "### 3.1 Splitting into Dev and Test sets \n",
    "\n",
    "In order to make sure I was not making any assumptions about the data, I will split the data into dev and test sets. \n",
    "\n",
    "I will use 50% of the data for the exploratory data analysis and then 50% of the data for testing the hypothesis. This will help with a clearer diagnosis and a hypothesis with no p-hacking."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "title_year                     2006.5\n",
       "gross                       5052692.4\n",
       "budget                       672326.8\n",
       "profit                      4380365.5\n",
       "imdb_score                        6.5\n",
       "duration                         93.3\n",
       "director_facebook_likes         189.2\n",
       "actor_1_facebook_likes         4905.5\n",
       "actor_2_facebook_likes          478.1\n",
       "actor_3_facebook_likes          240.4\n",
       "num_critic_for_reviews           96.5\n",
       "movie_facebook_likes           2288.3\n",
       "aspect_ratio                      2.1\n",
       "facenumber_in_poster              1.2\n",
       "cast_total_facebook_likes      6039.1\n",
       "num_voted_users               22485.0\n",
       "dtype: float64"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# creating a dataframe with all the info of movies budget less than 1.5mill\n",
    "\n",
    "dfwhole_budget = df[df.budget<=1500000]\n",
    "dfwhole_budget.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "#I will set the random seed as part of my candidate number: 244788\n",
    "import random\n",
    "from numpy.random import RandomState\n",
    "\n",
    "#setting a random.seed so that the sample doesn't change each time the kernal re-runs\n",
    "random.seed(2447)\n",
    "\n",
    "df_dev = df.sample(frac=0.5, random_state=2447)\n",
    "df_test =df.loc[~df.index.isin(df_dev.index)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(2128, 28)\n",
      "(1064, 28)\n"
     ]
    }
   ],
   "source": [
    "print(df.shape)\n",
    "print(df_dev.shape) #We can see that this is half of our filtered data frame"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "### 3.2 Exploring the devepment data set\n",
    "\n",
    "Using our *development* data frame to start exploring our set. Starting with genre analysis:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-20-6e5c3a004911>:1: FutureWarning: Indexing with multiple keys (implicitly converted to a tuple of keys) will be deprecated, use a list instead.\n",
      "  genreseries=df_dev.groupby('genres')['budget','gross','profit','imdb_score'].mean()\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>budget</th>\n",
       "      <th>gross</th>\n",
       "      <th>profit</th>\n",
       "      <th>imdb_score</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>genres</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Adventure|Drama|Sci-Fi|Thriller</th>\n",
       "      <td>78000000.0</td>\n",
       "      <td>407999255.0</td>\n",
       "      <td>329999255.0</td>\n",
       "      <td>7.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Action|Adventure|Comedy|Romance|Sci-Fi</th>\n",
       "      <td>58000000.0</td>\n",
       "      <td>363024263.0</td>\n",
       "      <td>305024263.0</td>\n",
       "      <td>8.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Action|Biography|Drama|History|Thriller|War</th>\n",
       "      <td>58800000.0</td>\n",
       "      <td>350123553.0</td>\n",
       "      <td>291323553.0</td>\n",
       "      <td>7.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Action|Adventure|Fantasy|Romance</th>\n",
       "      <td>139000000.0</td>\n",
       "      <td>403706375.0</td>\n",
       "      <td>264706375.0</td>\n",
       "      <td>7.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Action|Animation|Comedy|Family|Sci-Fi</th>\n",
       "      <td>74000000.0</td>\n",
       "      <td>336029560.0</td>\n",
       "      <td>262029560.0</td>\n",
       "      <td>6.4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                 budget       gross  \\\n",
       "genres                                                                \n",
       "Adventure|Drama|Sci-Fi|Thriller              78000000.0 407999255.0   \n",
       "Action|Adventure|Comedy|Romance|Sci-Fi       58000000.0 363024263.0   \n",
       "Action|Biography|Drama|History|Thriller|War  58800000.0 350123553.0   \n",
       "Action|Adventure|Fantasy|Romance            139000000.0 403706375.0   \n",
       "Action|Animation|Comedy|Family|Sci-Fi        74000000.0 336029560.0   \n",
       "\n",
       "                                                 profit  imdb_score  \n",
       "genres                                                               \n",
       "Adventure|Drama|Sci-Fi|Thriller             329999255.0         7.3  \n",
       "Action|Adventure|Comedy|Romance|Sci-Fi      305024263.0         8.1  \n",
       "Action|Biography|Drama|History|Thriller|War 291323553.0         7.3  \n",
       "Action|Adventure|Fantasy|Romance            264706375.0         7.3  \n",
       "Action|Animation|Comedy|Family|Sci-Fi       262029560.0         6.4  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "genreseries=df_dev.groupby('genres')['budget','gross','profit','imdb_score'].mean()\n",
    "\n",
    "#Set the maximum budget to 1.5 million\n",
    "\n",
    "max_budget=1500000000\n",
    "\n",
    "top_genres = genreseries[genreseries['budget']<max_budget]\n",
    "\n",
    "#We want to present it in IMDb acending scores\n",
    "top_genres = top_genres.sort_values('profit', ascending=False)\n",
    "\n",
    "\n",
    "#Print the genres for inspection\n",
    "top_genres.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let's have a look at content rating:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-21-add56db3af29>:2: FutureWarning: Indexing with multiple keys (implicitly converted to a tuple of keys) will be deprecated, use a list instead.\n",
      "  contentseries=df_dev.groupby('content_rating')['budget','gross','profit','imdb_score'].mean()\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>budget</th>\n",
       "      <th>gross</th>\n",
       "      <th>profit</th>\n",
       "      <th>imdb_score</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>content_rating</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>PG</th>\n",
       "      <td>64928796.3</td>\n",
       "      <td>87841262.4</td>\n",
       "      <td>22912466.1</td>\n",
       "      <td>6.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>G</th>\n",
       "      <td>60909090.9</td>\n",
       "      <td>79240701.7</td>\n",
       "      <td>18331610.8</td>\n",
       "      <td>6.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PG-13</th>\n",
       "      <td>54983062.6</td>\n",
       "      <td>71018003.7</td>\n",
       "      <td>16034941.1</td>\n",
       "      <td>6.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R</th>\n",
       "      <td>26197970.4</td>\n",
       "      <td>36544790.1</td>\n",
       "      <td>10346819.8</td>\n",
       "      <td>6.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NC-17</th>\n",
       "      <td>700000.0</td>\n",
       "      <td>1141829.0</td>\n",
       "      <td>441829.0</td>\n",
       "      <td>7.2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   budget      gross     profit  imdb_score\n",
       "content_rating                                             \n",
       "PG             64928796.3 87841262.4 22912466.1         6.1\n",
       "G              60909090.9 79240701.7 18331610.8         6.2\n",
       "PG-13          54983062.6 71018003.7 16034941.1         6.2\n",
       "R              26197970.4 36544790.1 10346819.8         6.5\n",
       "NC-17            700000.0  1141829.0   441829.0         7.2"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Grouping the series by content rating\n",
    "contentseries=df_dev.groupby('content_rating')['budget','gross','profit','imdb_score'].mean()\n",
    "\n",
    "#If we had unlimited budget\n",
    "\n",
    "max_budget=1500000000\n",
    "\n",
    "top_content = contentseries[contentseries['budget']<max_budget]\n",
    "\n",
    "#We want to present it in IMDb acending scores\n",
    "top_content = top_content.sort_values('profit', ascending=False)\n",
    "\n",
    "\n",
    "#Print the genres for inspection\n",
    "top_content.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "What about films that are within our budget bracket?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-22-9cca98e895a9>:1: FutureWarning: Indexing with multiple keys (implicitly converted to a tuple of keys) will be deprecated, use a list instead.\n",
      "  sbp_genreseries=df_dev.groupby('genres')['budget','gross','profit','imdb_score'].mean()\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>budget</th>\n",
       "      <th>gross</th>\n",
       "      <th>profit</th>\n",
       "      <th>imdb_score</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>genres</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Comedy|Documentary|Drama</th>\n",
       "      <td>65000.0</td>\n",
       "      <td>11529368.0</td>\n",
       "      <td>11464368.0</td>\n",
       "      <td>7.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Action|Adventure|Animation|Comedy|Fantasy|Sci-Fi</th>\n",
       "      <td>750000.0</td>\n",
       "      <td>5518918.0</td>\n",
       "      <td>4768918.0</td>\n",
       "      <td>6.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Biography|Documentary</th>\n",
       "      <td>218.0</td>\n",
       "      <td>592014.0</td>\n",
       "      <td>591796.0</td>\n",
       "      <td>7.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Western</th>\n",
       "      <td>30000.0</td>\n",
       "      <td>243768.0</td>\n",
       "      <td>213768.0</td>\n",
       "      <td>4.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Documentary|History|Music</th>\n",
       "      <td>200000.0</td>\n",
       "      <td>215185.0</td>\n",
       "      <td>15185.0</td>\n",
       "      <td>7.5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                   budget      gross  \\\n",
       "genres                                                                 \n",
       "Comedy|Documentary|Drama                          65000.0 11529368.0   \n",
       "Action|Adventure|Animation|Comedy|Fantasy|Sci-Fi 750000.0  5518918.0   \n",
       "Biography|Documentary                               218.0   592014.0   \n",
       "Western                                           30000.0   243768.0   \n",
       "Documentary|History|Music                        200000.0   215185.0   \n",
       "\n",
       "                                                     profit  imdb_score  \n",
       "genres                                                                   \n",
       "Comedy|Documentary|Drama                         11464368.0         7.3  \n",
       "Action|Adventure|Animation|Comedy|Fantasy|Sci-Fi  4768918.0         6.9  \n",
       "Biography|Documentary                              591796.0         7.2  \n",
       "Western                                            213768.0         4.1  \n",
       "Documentary|History|Music                           15185.0         7.5  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sbp_genreseries=df_dev.groupby('genres')['budget','gross','profit','imdb_score'].mean()\n",
    "\n",
    "#Set the maximum budget to 1.5 million\n",
    "\n",
    "sbp_budget=1500000\n",
    "\n",
    "top_budget_genres =sbp_genreseries[sbp_genreseries['budget']<sbp_budget]\n",
    "\n",
    "#We want to present it in IMDb acending scores\n",
    "top_budget_genres = top_budget_genres.sort_values('profit', ascending=False)\n",
    "\n",
    "\n",
    "#Print the genres for inspection\n",
    "top_budget_genres.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-23-0757317cef3e>:2: FutureWarning: Indexing with multiple keys (implicitly converted to a tuple of keys) will be deprecated, use a list instead.\n",
      "  sbp_content_series=df_dev.groupby('content_rating')['budget','gross','profit','imdb_score'].mean()\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>budget</th>\n",
       "      <th>gross</th>\n",
       "      <th>profit</th>\n",
       "      <th>imdb_score</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>content_rating</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>NC-17</th>\n",
       "      <td>700000.0</td>\n",
       "      <td>1141829.0</td>\n",
       "      <td>441829.0</td>\n",
       "      <td>7.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Unrated</th>\n",
       "      <td>540443.6</td>\n",
       "      <td>776171.6</td>\n",
       "      <td>235728.0</td>\n",
       "      <td>7.1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 budget     gross   profit  imdb_score\n",
       "content_rating                                        \n",
       "NC-17          700000.0 1141829.0 441829.0         7.2\n",
       "Unrated        540443.6  776171.6 235728.0         7.1"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Grouping the content series\n",
    "sbp_content_series=df_dev.groupby('content_rating')['budget','gross','profit','imdb_score'].mean()\n",
    "\n",
    "sbp_budget=1500000\n",
    "\n",
    "top_budget_content =sbp_content_series[sbp_content_series['budget']<sbp_budget]\n",
    "\n",
    "#We want to present it in IMDb acending scores\n",
    "top_budget_content= top_budget_content.sort_values('profit', ascending=False)\n",
    "\n",
    "\n",
    "#Print the content for inspection\n",
    "top_budget_content.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As shown above, content rating does not give us sufficient data to analyse within our budget.\n",
    "\n",
    "#### Lets explore more about genres...\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Adventure|Family|Sci-Fi', 'Action|Adventure|Sci-Fi|Thriller',\n",
       "       'Action|Drama', 'Thriller', 'Action|Drama|History|War',\n",
       "       'Action|Adventure|Animation|Comedy|Family', 'Comedy',\n",
       "       'Crime|Drama|Thriller', 'Comedy|Romance', 'Action|Comedy|Crime',\n",
       "       'Animation|Comedy|Family|Music|Western',\n",
       "       'Crime|Drama|Horror|Thriller', 'Horror', 'Drama|Sport',\n",
       "       'Sci-Fi|Thriller', 'Biography|Drama',\n",
       "       'Crime|Drama|Mystery|Thriller', 'Action|Crime|Drama|Thriller',\n",
       "       'Horror|Mystery', 'Drama|Romance', 'Comedy|Fantasy|Romance',\n",
       "       'Action|Adventure|Fantasy|Sci-Fi|Thriller',\n",
       "       'Action|Adventure|Fantasy',\n",
       "       'Adventure|Animation|Comedy|Family|Fantasy|Music', 'Drama|Mystery',\n",
       "       'Crime|Thriller', 'Horror|Mystery|Thriller',\n",
       "       'Adventure|Family|Fantasy', 'Drama', 'Comedy|Drama',\n",
       "       'Drama|Horror|Mystery|Thriller',\n",
       "       'Adventure|Comedy|Drama|Fantasy|Musical', 'Drama|Fantasy',\n",
       "       'Mystery|Thriller', 'Drama|Mystery|Thriller',\n",
       "       'Biography|Drama|History|Thriller',\n",
       "       'Animation|Comedy|Family|Fantasy|Musical|Romance',\n",
       "       'Action|Mystery|Sci-Fi|Thriller', 'Comedy|Drama|Romance',\n",
       "       'Adventure|Animation|Family|Fantasy', 'Romance|Sci-Fi|Thriller',\n",
       "       'Comedy|Crime|Romance', 'Action|Comedy|Fantasy|Sci-Fi',\n",
       "       'Comedy|Romance|Sport', 'Action|Adventure|Family|Fantasy|Romance',\n",
       "       'Comedy|Sport', 'Horror|Thriller', 'Drama|Music|Musical|Romance',\n",
       "       'Action|Crime|Thriller', 'Drama|History|Thriller|War',\n",
       "       'Action|Comedy|Crime|Thriller',\n",
       "       'Action|Adventure|Comedy|Family|Sci-Fi', 'Comedy|Music',\n",
       "       'Biography|Drama|Sport', 'Action|Adventure|Comedy',\n",
       "       'Drama|Fantasy|Romance|Sci-Fi', 'Comedy|Crime|Drama',\n",
       "       'Comedy|Drama|Music', 'Action|Adventure',\n",
       "       'Adventure|Comedy|Crime|Family|Mystery', 'Comedy|Fantasy',\n",
       "       'Crime|Drama', 'Action|Adventure|Sci-Fi', 'Documentary|Music',\n",
       "       'Action|Adventure|Animation|Family|Fantasy|Sci-Fi',\n",
       "       'Action|Adventure|Drama|Thriller', 'Action|Comedy|Crime|Drama',\n",
       "       'Action|Drama|Sci-Fi|Thriller',\n",
       "       'Adventure|Animation|Comedy|Family|Fantasy', 'Comedy|Documentary',\n",
       "       'Comedy|Sci-Fi|Thriller', 'Comedy|Drama|Family|Fantasy',\n",
       "       'Adventure|Comedy|Family|Romance', 'Adventure|Comedy|Drama',\n",
       "       'Drama|Sci-Fi|Thriller', 'Action|Crime',\n",
       "       'Action|Comedy|Family|Fantasy', 'Drama|History|Thriller',\n",
       "       'Biography|Comedy|Documentary', 'Crime|Drama|Mystery',\n",
       "       'Action|Adventure|Animation|Family|Fantasy',\n",
       "       'Biography|Drama|Music', 'Action|Adventure|Horror|Sci-Fi|Thriller',\n",
       "       'Drama|Mystery|Romance|Thriller', 'Drama|History',\n",
       "       'Adventure|Animation|Comedy|Family|Musical',\n",
       "       'Action|Adventure|Animation|Comedy|Family|Fantasy',\n",
       "       'Adventure|Animation|Comedy|Family|Fantasy|Romance',\n",
       "       'Action|Animation|Comedy|Family', 'Horror|Musical|Sci-Fi',\n",
       "       'Action|Sci-Fi', 'Action|Comedy|Crime|Romance',\n",
       "       'Adventure|Animation|Comedy|Family', 'Drama|War',\n",
       "       'Drama|History|War', 'Drama|Thriller', 'Adventure|Biography|Drama',\n",
       "       'Action|Animation|Comedy|Crime|Family', 'Fantasy|Horror',\n",
       "       'Comedy|Crime|Mystery', 'Comedy|War',\n",
       "       'Comedy|Drama|Family|Music|Musical|Romance', 'Crime|Horror',\n",
       "       'Comedy|Horror|Romance', 'Adventure|Animation|Family|Sci-Fi',\n",
       "       'Comedy|Musical|Romance', 'Action|Crime|Sci-Fi|Thriller',\n",
       "       'Action|Adventure|Comedy|Sci-Fi|Thriller',\n",
       "       'Action|Adventure|Crime|Thriller',\n",
       "       'Action|Adventure|Comedy|Musical', 'Comedy|Horror', 'Drama|Sci-Fi',\n",
       "       'Comedy|Family', 'Comedy|Crime|Music', 'Drama|Family|Fantasy',\n",
       "       'Adventure|Comedy|Drama|Family|Mystery', 'Comedy|Drama|Sci-Fi',\n",
       "       'Biography|Comedy|Drama', 'Comedy|Crime', 'Drama|Family|Western',\n",
       "       'Adventure|Horror|Thriller', 'Drama|Western',\n",
       "       'Horror|Sci-Fi|Thriller', 'Action|Adventure|Drama',\n",
       "       'Action|Adventure|Animation|Family|Sci-Fi',\n",
       "       'Crime|Drama|Music|Romance', 'Action|Adventure|Thriller',\n",
       "       'Drama|Romance|Sci-Fi', 'Animation|Comedy|Family|Fantasy',\n",
       "       'Documentary', 'Adventure|Mystery|Thriller', 'Drama|Musical',\n",
       "       'Comedy|Family|Romance', 'Biography|Crime|Drama', 'Drama|Music',\n",
       "       'Animation|Comedy|Family|Fantasy|Music', 'Adventure|Comedy|Family',\n",
       "       'Comedy|Drama|Music|Romance', 'Biography|Drama|History|War',\n",
       "       'Adventure|Drama|Family', 'Drama|Family|Sport', 'Action',\n",
       "       'Drama|Family', 'Action|Adventure|Romance',\n",
       "       'Action|Adventure|Romance|Sci-Fi|Thriller',\n",
       "       'Biography|Drama|History', 'Adventure|Comedy|Family|Musical',\n",
       "       'Comedy|Drama|Fantasy|Romance', 'Adventure|Comedy|Mystery',\n",
       "       'Comedy|Crime|Drama|Romance', 'Drama|Mystery|Sci-Fi|Thriller',\n",
       "       'Adventure|Comedy', 'Adventure|Comedy|Family|Fantasy',\n",
       "       'Adventure|Fantasy', 'Adventure|Animation|Family|Fantasy|Musical',\n",
       "       'Action|Comedy|Sci-Fi', 'Animation|Drama|Mystery|Sci-Fi|Thriller',\n",
       "       'Action|Crime|Drama|Mystery|Thriller', 'Adventure|Drama|Fantasy',\n",
       "       'Adventure|Animation|Comedy|Family|Sci-Fi',\n",
       "       'Comedy|Family|Fantasy|Romance', 'Comedy|Horror|Thriller',\n",
       "       'Biography|Drama|Thriller', 'Comedy|Crime|Family|Romance',\n",
       "       'Action|Crime|Drama|Sci-Fi|Thriller',\n",
       "       'Action|Adventure|Family|Fantasy',\n",
       "       'Adventure|Comedy|Drama|Romance', 'Action|Comedy|Horror',\n",
       "       'Action|Adventure|Comedy|Family|Fantasy|Mystery|Sci-Fi',\n",
       "       'Action|Drama|Thriller',\n",
       "       'Action|Adventure|Animation|Comedy|Crime|Family|Fantasy',\n",
       "       'Crime|Horror|Music|Thriller', 'Action|Adventure|Horror|Sci-Fi',\n",
       "       'Crime|Mystery|Thriller', 'Drama|Fantasy|Horror|Thriller',\n",
       "       'Action|Thriller', 'Action|Comedy|Music',\n",
       "       'Action|Horror|Sci-Fi|Thriller', 'Action|Comedy|Sport',\n",
       "       'Action|Sci-Fi|Thriller', 'Documentary|Sport',\n",
       "       'Drama|Romance|Thriller', 'Action|Adventure|Fantasy|Thriller',\n",
       "       'Adventure|Animation|Family|Musical', 'Adventure',\n",
       "       'Adventure|Fantasy|Horror|Mystery|Thriller',\n",
       "       'Biography|Drama|Family|History|Sport', 'Adventure|Mystery|Sci-Fi',\n",
       "       'Action|Adventure|Comedy|Sci-Fi', 'Comedy|Documentary|Drama',\n",
       "       'Action|Adventure|Comedy|Family|Fantasy|Sci-Fi',\n",
       "       'Comedy|Drama|Romance|Sport', 'Documentary|Drama|War',\n",
       "       'Comedy|Family|Fantasy', 'Fantasy|Horror|Mystery|Thriller',\n",
       "       'Biography|Drama|Family', 'Western', 'Comedy|Crime|Sport',\n",
       "       'Animation|Drama|Family|Fantasy|Musical|Romance',\n",
       "       'Action|Adventure|Fantasy|Romance',\n",
       "       'Action|Adventure|Fantasy|Horror|Sci-Fi',\n",
       "       'Crime|Drama|Romance|Thriller',\n",
       "       'Adventure|Animation|Family|Thriller',\n",
       "       'Comedy|Drama|Family|Romance',\n",
       "       'Biography|Comedy|Drama|History|Music',\n",
       "       'Adventure|Drama|Fantasy|Romance', 'Action|Comedy',\n",
       "       'Action|Comedy|Fantasy',\n",
       "       'Action|Adventure|Animation|Comedy|Family|Sci-Fi',\n",
       "       'Drama|Horror|Sci-Fi|Thriller', 'Action|Crime|Fantasy|Thriller',\n",
       "       'Comedy|Family|Fantasy|Sport', 'Action|Adventure|Fantasy|Sci-Fi',\n",
       "       'Action|Adventure|Comedy|Romance|Thriller',\n",
       "       'Comedy|Crime|Drama|Thriller', 'Drama|Romance|Sport',\n",
       "       'Drama|Family|Fantasy|Romance',\n",
       "       'Biography|Crime|Drama|Mystery|Thriller',\n",
       "       'Action|Comedy|Crime|Drama|Thriller', 'Action|Horror|Thriller',\n",
       "       'Drama|Fantasy|Romance', 'Comedy|Drama|Family|Musical',\n",
       "       'Comedy|Romance|Sci-Fi', 'Action|Adventure|Comedy|Crime|Thriller',\n",
       "       'Adventure|Comedy|Family|Fantasy|Horror',\n",
       "       'Action|Drama|Fantasy|Romance', 'Adventure|Comedy|Horror|Sci-Fi',\n",
       "       'Biography|Drama|Music|Musical', 'Action|Drama|Fantasy|War',\n",
       "       'Drama|Horror|Thriller', 'Comedy|Drama|Fantasy|Music|Romance',\n",
       "       'Action|Adventure|Fantasy|Horror|Thriller', 'Drama|Horror',\n",
       "       'Drama|Romance|War', 'Crime|Documentary|War',\n",
       "       'Action|Adventure|Comedy|Crime', 'Drama|Musical|Romance',\n",
       "       'Action|Fantasy|Horror|Thriller',\n",
       "       'Biography|Crime|Drama|History|Romance', 'Action|Fantasy|Thriller',\n",
       "       'Adventure|Drama|Sci-Fi|Thriller', 'Drama|Romance|Western',\n",
       "       'Drama|Horror|Mystery|Sci-Fi|Thriller',\n",
       "       'Biography|Crime|Drama|History|Western',\n",
       "       'Adventure|Animation|Comedy|Family|Fantasy|Musical|Romance',\n",
       "       'Drama|Music|Romance', 'Action|Crime|Mystery|Thriller',\n",
       "       'Adventure|Comedy|Drama|Fantasy|Romance', 'Crime|Drama|Romance',\n",
       "       'Adventure|Drama|Romance', 'Action|Western',\n",
       "       'Action|Drama|History|Romance|War',\n",
       "       'Action|Adventure|Crime|Drama|Family|Fantasy|Romance|Thriller',\n",
       "       'Action|Crime|Romance|Thriller',\n",
       "       'Action|Adventure|Comedy|Family|Fantasy',\n",
       "       'Adventure|Animation|Comedy|Drama|Family|Musical',\n",
       "       'Crime|Horror|Mystery|Thriller',\n",
       "       'Comedy|Drama|Family|Fantasy|Romance',\n",
       "       'Comedy|Drama|Family|Fantasy|Sci-Fi',\n",
       "       'Adventure|Comedy|Crime|Romance', 'Comedy|Family|Sport',\n",
       "       'Adventure|Comedy|Romance', 'Adventure|Comedy|Fantasy',\n",
       "       'Fantasy|Horror|Thriller', 'Action|Crime|Drama',\n",
       "       'Biography|Drama|Romance', 'Adventure|Animation|Comedy',\n",
       "       'Biography|Drama|History|Romance',\n",
       "       'Adventure|Comedy|Family|Music|Romance',\n",
       "       'Action|Adventure|Drama|History',\n",
       "       'Drama|Music|Mystery|Romance|Thriller',\n",
       "       'Adventure|Comedy|Drama|Family|Romance',\n",
       "       'Documentary|History|Music', 'Crime|Horror|Thriller',\n",
       "       'Adventure|Drama|Sci-Fi', 'Comedy|Crime|Musical',\n",
       "       'Comedy|Drama|Romance|Thriller',\n",
       "       'Action|Adventure|Family|Mystery|Sci-Fi',\n",
       "       'Action|Drama|Fantasy|Thriller|Western', 'Action|Comedy|Romance',\n",
       "       'Comedy|Crime|Musical|Mystery', 'Drama|Fantasy|Mystery|Thriller',\n",
       "       'Action|Romance|Thriller', 'Drama|History|War|Western',\n",
       "       'Action|Adventure|Western',\n",
       "       'Action|Biography|Drama|History|Thriller|War',\n",
       "       'Adventure|Comedy|Crime|Family|Musical', 'Drama|Fantasy|Thriller',\n",
       "       'Adventure|Animation|Comedy|Drama|Family|Fantasy',\n",
       "       'Action|Animation|Comedy|Family|Sci-Fi', 'Adventure|Drama|War',\n",
       "       'Adventure|Animation|Comedy|Family|Sport', 'Comedy|Sci-Fi',\n",
       "       'Action|Drama|Fantasy|Horror|War',\n",
       "       'Comedy|Crime|Drama|Mystery|Romance', 'Action|Sci-Fi|Sport',\n",
       "       'Biography|Crime|Drama|Romance', 'Action|Mystery|Thriller',\n",
       "       'Action|Biography|Crime|Drama', 'Comedy|Drama|Family',\n",
       "       'Comedy|Crime|Drama|Romance|Thriller',\n",
       "       'Adventure|Animation|Comedy|Family|Fantasy|Musical',\n",
       "       'Biography|Comedy|Drama|History', 'Horror|Mystery|Sci-Fi|Thriller',\n",
       "       'Drama|History|Sport', 'Action|Drama|Thriller|War',\n",
       "       'Adventure|Comedy|Family|Fantasy|Horror|Mystery',\n",
       "       'Comedy|Drama|Music|Musical',\n",
       "       'Comedy|Crime|Family|Mystery|Romance|Thriller',\n",
       "       'Action|Adventure|Animation|Comedy|Fantasy|Sci-Fi',\n",
       "       'Drama|Fantasy|Music|Romance', 'Comedy|Fantasy|Musical|Sci-Fi',\n",
       "       'Adventure|Drama|Mystery',\n",
       "       'Action|Adventure|Biography|Drama|History|Thriller',\n",
       "       'Crime|Drama|Musical|Romance', 'Biography|Crime|Drama|Thriller',\n",
       "       'Action|Adventure|Drama|Thriller|War', 'Crime|Documentary',\n",
       "       'Drama|Fantasy|Sport', 'Comedy|Crime|Romance|Thriller',\n",
       "       'Adventure|Comedy|Drama|Family|Fantasy',\n",
       "       'Drama|Fantasy|Musical|Romance', 'Comedy|Drama|Musical|Romance',\n",
       "       'Crime|Thriller|War', 'Action|Adventure|Drama|Mystery',\n",
       "       'Biography|Drama|History|Thriller|War',\n",
       "       'Animation|Drama|Family|Fantasy', 'Biography|Drama|History|Sport',\n",
       "       'Adventure|Comedy|Drama|Music',\n",
       "       'Action|Crime|Mystery|Sci-Fi|Thriller', 'Documentary|Drama',\n",
       "       'Adventure|Family', 'Action|Crime|Drama|Thriller|War',\n",
       "       'Comedy|Family|Romance|Sport', 'Adventure|Comedy|Sci-Fi',\n",
       "       'Adventure|Drama', 'Crime|Drama|Fantasy|Romance',\n",
       "       'Comedy|Crime|Drama|Horror|Thriller', 'Biography|Documentary',\n",
       "       'Comedy|Crime|Thriller', 'Action|Adventure|Mystery|Sci-Fi',\n",
       "       'Action|Drama|Mystery|Sci-Fi', 'Drama|Mystery|Sci-Fi',\n",
       "       'Comedy|Family|Music|Musical',\n",
       "       'Adventure|Comedy|Family|Romance|Sci-Fi',\n",
       "       'Adventure|Drama|Thriller',\n",
       "       'Action|Adventure|Comedy|Romance|Sci-Fi',\n",
       "       'Drama|Fantasy|Mystery|Romance',\n",
       "       'Action|Adventure|Comedy|Fantasy|Thriller',\n",
       "       'Action|Crime|Sport|Thriller'], dtype=object)"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#We can see that there are many unique 'genres' in our df\n",
    "#We would like to have a look at specific genres for our title\n",
    "\n",
    "df_dev['genres'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pandas import Series\n",
    "\n",
    "#Splitting the genres\n",
    "s = df_dev['genres'].str.split('|').apply(Series, 1).stack()\n",
    "s.index = s.index.droplevel(-1)\n",
    "s.name = 'genres'\n",
    "\n",
    "#Deleting the 'genres' column from the original dataframe\n",
    "del df_dev['genres']\n",
    "\n",
    "#Adding the new genres to the data frame\n",
    "genre_df_dev = df_dev.join(s)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['Action' 'Adventure' 'Fantasy' 'Thriller' 'Romance' 'Animation' 'Comedy'\n",
      " 'Family' 'Musical' 'Sci-Fi' 'Drama' 'History' 'Sport' 'Horror' 'Crime'\n",
      " 'Mystery' 'War' 'Biography' 'Music' 'Western' 'Documentary']\n"
     ]
    }
   ],
   "source": [
    "#Now we have a new data frame called 'genre_df'\n",
    "#What are the uniquite genres in our data frame?\n",
    "\n",
    "print(genre_df_dev['genres'].unique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "scrolled": true
   },
   "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>movie_title</th>\n",
       "      <th>title_year</th>\n",
       "      <th>director_name</th>\n",
       "      <th>gross</th>\n",
       "      <th>budget</th>\n",
       "      <th>profit</th>\n",
       "      <th>country</th>\n",
       "      <th>language</th>\n",
       "      <th>imdb_score</th>\n",
       "      <th>content_rating</th>\n",
       "      <th>...</th>\n",
       "      <th>num_critic_for_reviews</th>\n",
       "      <th>movie_facebook_likes</th>\n",
       "      <th>color</th>\n",
       "      <th>plot_keywords</th>\n",
       "      <th>movie_imdb_link</th>\n",
       "      <th>aspect_ratio</th>\n",
       "      <th>facenumber_in_poster</th>\n",
       "      <th>cast_total_facebook_likes</th>\n",
       "      <th>num_voted_users</th>\n",
       "      <th>genres</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Pirates of the Caribbean: At World's End</td>\n",
       "      <td>2007.0</td>\n",
       "      <td>Gore Verbinski</td>\n",
       "      <td>309404152.0</td>\n",
       "      <td>300000000.0</td>\n",
       "      <td>9404152.0</td>\n",
       "      <td>USA</td>\n",
       "      <td>English</td>\n",
       "      <td>7.1</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>...</td>\n",
       "      <td>302.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Color</td>\n",
       "      <td>goddess|marriage ceremony|marriage proposal|pi...</td>\n",
       "      <td>http://www.imdb.com/title/tt0449088/?ref_=fn_t...</td>\n",
       "      <td>2.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>48350</td>\n",
       "      <td>471220</td>\n",
       "      <td>Action</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Pirates of the Caribbean: At World's End</td>\n",
       "      <td>2007.0</td>\n",
       "      <td>Gore Verbinski</td>\n",
       "      <td>309404152.0</td>\n",
       "      <td>300000000.0</td>\n",
       "      <td>9404152.0</td>\n",
       "      <td>USA</td>\n",
       "      <td>English</td>\n",
       "      <td>7.1</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>...</td>\n",
       "      <td>302.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Color</td>\n",
       "      <td>goddess|marriage ceremony|marriage proposal|pi...</td>\n",
       "      <td>http://www.imdb.com/title/tt0449088/?ref_=fn_t...</td>\n",
       "      <td>2.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>48350</td>\n",
       "      <td>471220</td>\n",
       "      <td>Adventure</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Pirates of the Caribbean: At World's End</td>\n",
       "      <td>2007.0</td>\n",
       "      <td>Gore Verbinski</td>\n",
       "      <td>309404152.0</td>\n",
       "      <td>300000000.0</td>\n",
       "      <td>9404152.0</td>\n",
       "      <td>USA</td>\n",
       "      <td>English</td>\n",
       "      <td>7.1</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>...</td>\n",
       "      <td>302.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Color</td>\n",
       "      <td>goddess|marriage ceremony|marriage proposal|pi...</td>\n",
       "      <td>http://www.imdb.com/title/tt0449088/?ref_=fn_t...</td>\n",
       "      <td>2.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>48350</td>\n",
       "      <td>471220</td>\n",
       "      <td>Fantasy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>The Dark Knight Rises</td>\n",
       "      <td>2012.0</td>\n",
       "      <td>Christopher Nolan</td>\n",
       "      <td>448130642.0</td>\n",
       "      <td>250000000.0</td>\n",
       "      <td>198130642.0</td>\n",
       "      <td>USA</td>\n",
       "      <td>English</td>\n",
       "      <td>8.5</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>...</td>\n",
       "      <td>813.0</td>\n",
       "      <td>164000</td>\n",
       "      <td>Color</td>\n",
       "      <td>deception|imprisonment|lawlessness|police offi...</td>\n",
       "      <td>http://www.imdb.com/title/tt1345836/?ref_=fn_t...</td>\n",
       "      <td>2.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>106759</td>\n",
       "      <td>1144337</td>\n",
       "      <td>Action</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>The Dark Knight Rises</td>\n",
       "      <td>2012.0</td>\n",
       "      <td>Christopher Nolan</td>\n",
       "      <td>448130642.0</td>\n",
       "      <td>250000000.0</td>\n",
       "      <td>198130642.0</td>\n",
       "      <td>USA</td>\n",
       "      <td>English</td>\n",
       "      <td>8.5</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>...</td>\n",
       "      <td>813.0</td>\n",
       "      <td>164000</td>\n",
       "      <td>Color</td>\n",
       "      <td>deception|imprisonment|lawlessness|police offi...</td>\n",
       "      <td>http://www.imdb.com/title/tt1345836/?ref_=fn_t...</td>\n",
       "      <td>2.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>106759</td>\n",
       "      <td>1144337</td>\n",
       "      <td>Thriller</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 28 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                 movie_title  title_year      director_name  \\\n",
       "1  Pirates of the Caribbean: At World's End       2007.0     Gore Verbinski   \n",
       "1  Pirates of the Caribbean: At World's End       2007.0     Gore Verbinski   \n",
       "1  Pirates of the Caribbean: At World's End       2007.0     Gore Verbinski   \n",
       "3                     The Dark Knight Rises       2012.0  Christopher Nolan   \n",
       "3                     The Dark Knight Rises       2012.0  Christopher Nolan   \n",
       "\n",
       "        gross      budget      profit country language  imdb_score  \\\n",
       "1 309404152.0 300000000.0   9404152.0     USA  English         7.1   \n",
       "1 309404152.0 300000000.0   9404152.0     USA  English         7.1   \n",
       "1 309404152.0 300000000.0   9404152.0     USA  English         7.1   \n",
       "3 448130642.0 250000000.0 198130642.0     USA  English         8.5   \n",
       "3 448130642.0 250000000.0 198130642.0     USA  English         8.5   \n",
       "\n",
       "  content_rating  ...  num_critic_for_reviews  movie_facebook_likes  color  \\\n",
       "1          PG-13  ...                   302.0                     0  Color   \n",
       "1          PG-13  ...                   302.0                     0  Color   \n",
       "1          PG-13  ...                   302.0                     0  Color   \n",
       "3          PG-13  ...                   813.0                164000  Color   \n",
       "3          PG-13  ...                   813.0                164000  Color   \n",
       "\n",
       "                                       plot_keywords  \\\n",
       "1  goddess|marriage ceremony|marriage proposal|pi...   \n",
       "1  goddess|marriage ceremony|marriage proposal|pi...   \n",
       "1  goddess|marriage ceremony|marriage proposal|pi...   \n",
       "3  deception|imprisonment|lawlessness|police offi...   \n",
       "3  deception|imprisonment|lawlessness|police offi...   \n",
       "\n",
       "                                     movie_imdb_link  aspect_ratio  \\\n",
       "1  http://www.imdb.com/title/tt0449088/?ref_=fn_t...           2.4   \n",
       "1  http://www.imdb.com/title/tt0449088/?ref_=fn_t...           2.4   \n",
       "1  http://www.imdb.com/title/tt0449088/?ref_=fn_t...           2.4   \n",
       "3  http://www.imdb.com/title/tt1345836/?ref_=fn_t...           2.4   \n",
       "3  http://www.imdb.com/title/tt1345836/?ref_=fn_t...           2.4   \n",
       "\n",
       "  facenumber_in_poster  cast_total_facebook_likes  num_voted_users     genres  \n",
       "1                  0.0                      48350           471220     Action  \n",
       "1                  0.0                      48350           471220  Adventure  \n",
       "1                  0.0                      48350           471220    Fantasy  \n",
       "3                  0.0                     106759          1144337     Action  \n",
       "3                  0.0                     106759          1144337   Thriller  \n",
       "\n",
       "[5 rows x 28 columns]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Exploring our new data frame \n",
    "#We can see that films come up multiple times with each genre\n",
    "\n",
    "genre_df_dev.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3109, 28)"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#As there are more than one genre per film\n",
    "#The dataframe shape has changed and increased the rows\n",
    "\n",
    "genre_df_dev.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "Let's look at the budget for each genre. I have displayed this as a box plot so we can see the broad distribution of budgets. We can see that 'Adventure' has the highest overall budget and mean."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:title={'center':'budget'}, xlabel='[genres]'>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 936x864 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Make dataframe with just genre and budget data\n",
    "genre_budgets=genre_df_dev.loc[:,['genres','budget']] \n",
    "\n",
    "#Get the frequencies\n",
    "counts=genre_budgets.groupby('genres').count().reset_index('genres')\n",
    "\n",
    "#Set the number we consider to be 'big' in terms of films made so that we can plot genres\n",
    "n=50 \n",
    "\n",
    "#Making the index by frequencies\n",
    "bigcounts=counts[counts.budget>n]['genres']\n",
    "\n",
    "#Using frequency index to make new dataframe with just 'big genres'\n",
    "biggenres_df = genre_budgets[genre_budgets.genres.isin(bigcounts)]\n",
    "biggenres_df.boxplot(by='genres',figsize=(13,12))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:title={'center':'profit'}, xlabel='[genres]'>"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAxAAAAL6CAYAAACmUbCtAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuNCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8QVMy6AAAACXBIWXMAAAsTAAALEwEAmpwYAAByl0lEQVR4nO3df5xcZX33//cnu2QDCT8ELSauQKrWTnZ7K3foD3F7m3EVBPxBe7emkyjQTKHRL2N6Y80i4y3SdtAEyV3v5dYITgRadkhpK7eCEWh2VrvSVsEfGDKlehvANf4sKGZjEhKu7x/nzGZ22U1OZmf3nHPt6/l47COTs7NzPp85Z645n3Nd1znmnBMAAAAARDEv7gAAAAAApAcFBAAAAIDIKCAAAAAAREYBAQAAACAyCggAAAAAkVFAAAAAAIiMAgIAYmRmzsxeHncccTKzFWY2coTfz/n3CACShAICACSZ2eNm9ksz22NmT5vZvWb20rjjqjOzy8xsOO44AACggACAw97inFskabGkH0nqjzmeGWNm7XHH4CsL8P0KwFs0cAAwgXNun6S/l7SsvszMTjaz283sJ2b2hJl9wMzmmdmpZjZiZm8Jn7fIzL5jZpeE/7/VzDab2QNm9gsz+6KZnTnZeo+wjoykzZJeE/aQ/GyKv19qZl8K1/NPZvZ/zOxvw9+dFQ4FypvZk5IGw9f+QLiuH4frPjl8/vOGFYW9NG8IH3/IzP7ezLaG6/uamb2q4blLzOwfwlx2mdl7Gn53fPi+PG1mOyX9ZoTNcqGZfdfMfmpmN4Sxd5jZU2b2Gw2v/SthT9KLJnl/2szsxvA1dpnZleF70t7w/pfN7Adm9n0z+yszawt/d5mZDZvZR8O4d5nZBQ2vPWRmJTP7sqS9kn7VzH493O5PmdljZvb2hudfaGY7w/fu+2b25xHeAwBIBAoIAJjAzE6QtFLSvzYs7pd0sqRflfQ6SZdI+mPn3FOS1ki6xcx+RdL/kvQN59ztDX+7WtJfSnqhpG9IumOKVU+1jpqktZL+xTm3yDl3yhR/PyDpK5JOk/QhSe+c5Dmvk5SRdL6ky8KfbLjORZJumuK1J/M2SXdJOjVc991mdlx49v1zkr4p6SWSeiX9mZmdH/7dtZJeFv6cL+nSCOv6PUnnSPqv4XrXOOf2S7pT0jsanpeT9E/OuZ9M8hqXS7pA0qvD17l4wu9vk3RQ0sslnS3pPEl/0vD735b0mILtuFFS2cys4ffvlHSFpBMl/UTSAwrel18J4/q4mXWFzy1L+lPn3ImSuiUNRngPACAZnHP88MMPP3P+R9LjkvZI+pmCg8jdkn4j/F2bpP2SljU8/08lDTX8v1/St8K/O61h+a2S7mz4/yJJhyS9NPy/U3DAesR1KDjQHz5C/GeEcZ/QsOxvJf1t+PiscF2/2vD77ZLe3fD/V0p6VlK7pBWSRiZ5j94QPv6QpH9t+N08ST+Q9LsKDrSfnPC375f06fDxdyW9qeF3V0xc14S/dROe/25J28PHvy3pe5Lmhf9/SNLbp3idQQUH7fX/vyF87XZJp4fv//ENv89Jqja8/99p+N0J4d++OPz/kKS/aPj9Skn/PGH9n5R0bfj4yXD7nhT3vs8PP/zwc6w/9EAAwGEXu+DsfoekKyV90cxerOCM83xJTzQ89wkFZ9frblZwJvnTzrn/nPC636s/cM7tkfSUpCUTnhNlHUeyRNJTzrm9k613imVLJllf/WA6isa8npM0Er7mmZKWmNnP6j+Srml43SUT4miM4ajrCp+/JFzvv0kalfQ6M/t1BcXYZ6d4jYnrbXx8pqTjJP2gIeZPKug9qPth/UHD+7zoCK/32xPeg9WSXhz+/r9LulDSE+GwttdMETMAJA4FBABM4Jw75Jz7RwU9BT2SfqrgzHzj3IUzJH1fCsbWKzjYvF3Su+z5lxwdu5qTmS1SMORn94TnHHEdCs52H8kPJJ0aDr963nob02t4vHuS9R1UMIF8VMFZ9nrcbZImzitozGuepM7wNb8naZdz7pSGnxOdcxc2xNoY2xlHyW1iLmdo/Pt3m4JhTO+U9PcumMMymR+EMU72mt9T0APxwoaYT3LOdSm6xvf2e5K+OOE9WOSce5ckOee+6px7m4IC5W5Jf3cM6wGAWFFAAMAEFnibpBdIqjnnDik4wCuZ2YnhJOirFAwRkoKz61IwF+Kjkm6vT74NXWhmPWY2X8FciH9zzo3rHYiwjh9J6gxf43mcc08oGL7zITObH57RfstRUq1I+h/h5OtFkq6XtNU5d1DSf0haYGYXmdlxkj6goGem0XIz+/1wEvKfKTgA/1cF8zCeMbO+cMJ0m5l1m1l9svTfSXq/mb3AzDolFY4SpyS9L3z+SyWtk7S14Xd/o2COxDsUFHFT+TtJ68zsJWZ2iqS++i+ccz+QdL+kG83spHCS9svM7HURYpvMPZJ+zczeGc4LOc7MftPMMuH2WW1mJzvnnpX0jIJiFQBSgQICAA77nJntUXBAV5J0qXPu0fB3BQVn5b8raVjB5NgtZrZcwYH+JWERsEHBmeirG153QMHE4ackLVcwlGUyk64j/N2gpEcl/dDMfjrF36+W9BpJ/ynprxQcZO8/Qr5bFBx8f0nSLkn7whjknPu5grkGn1LQCzKqYIhSo/+rYKz/0wrO/v++c+7Z8H14i4LJyrsU9K58SsEEcUm6TsEwpF0KDtr/5ggxNq7rYQWT0O9VMAlZYawjkr6m4H3/5yO8xi3h+h6R9HVJn1fQ41I/eL9EwTCynWFOf6/gkr7HzDn3CwWTsP9IQW/JDxXsG/Ui7J2SHjezZxRMkH/HZK8DAElkzh2tVxwA0Cwzu1XBBOEPxLDurZL+3Tl37Qy89ockvdw5l4gDXzPbImn3sbzP4WVYNzvnJr2sLgBgcvRAAIAnwiEyLwuH37xJweVO7445rBlnZmdJ+n019EpM8bzjw/svtJvZSxT0Cn1mFkIEAK9QQACAP16s4HKieyT9b0nvcs59PdaIZpiZ/aWkHZJucM7tOtrTFQyfelrBEKaapA/ObIQA4B+GMAEAAACIjB4IAAAAAJFRQAAAAACIjAICAAAAQGQUEAAAAAAio4AAAAAAEBkFBAAAAIDIKCAAAAAAREYBAQAAACAyCggAAAAAkVFAAAAAAIiMAgIAAABAZBQQAAAAACKjgAAAAAAQGQUEAAAAgMgoIAAAAABERgEBAAAAIDIKCAAAAACRUUAAAAAAiIwCAgAAAEBkFBAAAAAAIqOAAAAAABAZBQQAAACAyCggAAAAAERGAQEAAAAgMgoIAAAAAJFRQAAAAACIjAICAAAAQGQUEAAAAAAio4AAAAAAEBkFBAAAAIDIKCAAAAAAREYBAQAAACAyCggAAAAAkVFAAAAAAIiMAgIAAABAZBQQAAAAACKjgAAAAAAQGQUEAAAAgMgoIAAAAABERgEBAGg5M3uXmf3IzPaY2Wnhv78ad1wAgOkz51zcMQAAPGJmx0l6RtLvOOe+Ocnvb5U04pz7wGzHBgCYPnogAADHxMzaj/KU0yUtkPToLIQDAJhlFBAAAEmSmT1uZu83s51m9rSZfdrMFpjZCjMbMbM+M/uhpE+bWYeZ/bWZ7Q5//jpc9muSHgtf8mdmNhi+tjOzl5vZFZJWS1ofDmv6XEzpAgCadLSzSACAuWW1pPMljUr6nKQPSPonSS+WdKqkMxWcfCpK+h1Jr5bkJP1fSR9wzv1PM+uStEvSKc65g40v7py72czOFUOYACC1YuuBMLMtZvZjM9sR4blnmFnVzL5uZo+Y2YWzESMAzEE3Oee+55x7SlJJUi5c/pyka51z+51zv1RQaPyFc+7HzrmfSLpO0jvjCRkAMJviHMJ0q6Q3RXzuByT9nXPubEl/JOnjMxUUAMxx32t4/ISkJeHjnzjn9jX8bkn4+8meCwDwWGwFhHPuS5KealxmZi8zsy+Y2cNm9s9m9uv1p0s6KXx8sqTdsxgqAMwlL214fIYOt7cTL9m3W8FwpsmeezRc/g8AUixpcyBulrTWOfdtM/ttBT0Nr5f0IUn3m1lB0kJJb4gvRADw2v9nZvdI2ivpGklbp3heRdIHzOyrCgqCD0r624jr+JEk7gkBACmVmKswmdkiSedKusvMviHpk5IWh7/OSbrVOdcp6UJJf2NmiYkdADwyIOl+Sd8Nf/5qiuf9laSHJD0i6VuSvnaE505UlrTMzH5mZndPK1oAwKyL9UZyZnaWpHucc91mdpKkx5xziyd53qOS3uSc+174/+8quEHRj2c1YADwmJk9LulPnHP/FHcsAIDkSsxZfOfcM5J2mdkfSpIFXhX++klJveHyjIIbFP0klkABAACAOSzOy7hWJP2LpFeGNyjKK7gsYN7MvqngDqZvC5/+XkmXh8srki5zcXadAAAAAHNUrEOYAAAAAKRLYoYwAQAAAEg+CggAAAAAkcVyH4gXvvCF7qyzzpqVdY2OjmrhwoWzsq7Z4mNOkp95+ZiT5GdePuYk+ZmXjzlJfublY06Sn3n5mJPkZ16zmdPDDz/8U+fciyYuj6WAOOuss/TQQw/NyrqGhoa0YsWKWVnXbPExJ8nPvHzMSfIzLx9zkvzMy8ecJD/z8jEnyc+8fMxJ8jOv2czJzJ6YbDlDmAAAAABERgEBAAAAIDIKCAAAAACRUUAAAAAAiIwCAgAAAEBkFBAAAAAAIqOAAAAAABAZBQQAAACAyCggAAAAAERGAQEAAAAgMgoIAAAAAJFRQAAAAACIjAICAAAAQGQUEAAAAAAio4AAAAAAEBkFBAAAAIDIKCAAAAAAREYBAQAAACAyCggAAAAAkVFAAAAAAIiMAgIAAABAZBQQAAAAACKjgAAAAAAQGQUEAAAAgMi8LSAqlYq6u7vV29ur7u5uVSqVuEOaNh9zAgAAaDUfj5mSlFN7bGueQZVKRcViUeVyWYcOHVJbW5vy+bwkKZfLxRxdc3zMCQAAoNV8PGZKWk4t6YEws8fN7Ftm9g0ze6gVrzkdpVJJ5XJZ2WxW7e3tymazKpfLKpVKcYfWNB9zAgAAaDUfj5mSllMreyCyzrmftvD1mlar1dTT0zNuWU9Pj2q1WkwRTZ+POQEAALSaj8dMScvJyzkQmUxGw8PD45YNDw8rk8nEFNH0+ZgTAABAq/l4zJS0nMw5N/0XMdsl6WlJTtInnXM3T/KcKyRdIUmnn3768jvvvHPa653K9u3bVS6X9b73vU9Lly7Vrl27dMMNNyifz6u3t3fG1juTfMxpoj179mjRokVxh9FSPuYk+ZmXjzlJfublY06Sn3n5mJPkZ14+5eTjMVNcOWWz2Yedc+c87xfOuWn/SFoS/vsrkr4p6b8d6fnLly93M21gYMB1dXW5efPmua6uLjcwMDDj65xpPubUqFqtxh1Cy/mYk3N+5uVjTs75mZePOTnnZ14+5uScn3n5lpOPx0xx5CTpITfJsXxL5kA453aH//7YzD4j6bckfakVr92sXC6nXC6noaEhrVixIs5QWsbHnAAAAFrNx2OmJOU07TkQZrbQzE6sP5Z0nqQd031dAAAAAMnTih6I0yV9xszqrzfgnPtCC14XAAAAQMJMu4Bwzn1X0qtaEAsAAACAhPPyMq4AAAAAZgYFBAAAAIDIKCAAAAAAREYBAQAAACAyCggAAAAAkVFAAAAAAIiMAgIAAABAZBQQAAAAACKjgAAAAAAQGQUEAAAAgMgoIAAAAABERgEBAAAAIDIKCAAAAACRUUAAAAAAiIwCAgAAAEBkFBAAAAAAIqOAAAAAABAZBQQAAACAyCggAAAAAERGAQEAAAAgMgoIAAAAAJFRQAAAAACIjAICAAAAQGQUEAAAAAAio4AAAAAAEBkFBAAAAIDIKCAAAAAAREYBAQAAACAyCggAAAAAkVFAAAAAAIiMAgIAAABAZBQQAAAAACKjgAAAAAAQGQUEAAAAgMgoIAAAAABERgEBAAAAIDIKCAAAAACRUUAAAAAAiIwCAgAAAEBkFBAAAAAAIqOAAAAAABAZBQQAAACAyCggAAAAAERGAQEAAAAgMgoIAAAAAJFRQAAAAACIjAICAAAAQGQUEAAAAAAio4AAAAAAEBkFBAAAAIDIKCAAAAAAREYBAQAAACAyCggAAAAAkVFAAAAAAIiMAgIAAABAZBQQAAAAACKjgAAAAAAQGQUEAAAAgMgoIAAAAABERgEBAAAAIDIKCAAAAACRUUAAAAAAiIwCAgAAAEBkFBAAAAAAIqOAAAAAABAZBQQAAACAyCggAAAAAERGAQEAAAAgMgoIAAAAAJFRQAAAAACIjAICAAAAQGQUEAAAAAAio4AAAAAAEBkFBAAAAIDIKCAAAAAAREYBAQAAACAyCggAAAAAkVFAAAAAAIiMAgIAAABAZC0rIMyszcy+bmb3tOo1AQAAACRLK3sg1kmqtfD1AAAAACRMSwoIM+uUdJGkT7Xi9QAAAAAkU6t6IP5a0npJz7Xo9QAAAAAkkDnnpvcCZm+WdKFz7t1mtkLSnzvn3jzJ866QdIUknX766cvvvPPOaa03qj179mjRokWzsq7Z4mNOkp95+ZiT5GdePuYk+ZmXjzlJfublY06Sn3n5mJPkZ16zmVM2m33YOXfOxOWtKCA+LOmdkg5KWiDpJEn/6Jx7x1R/c84557iHHnpoWuuNamhoSCtWrJiVdc0WH3OS/MzLx5wkP/PyMSfJz7x8zEnyMy8fc5L8zMvHnCQ/85rNnMxs0gJi2kOYnHPvd851OufOkvRHkgaPVDwAAAAASC/uAwEAAAAgsvZWvphzbkjSUCtfEwAAAEBy0AMBAAAAIDIKCAAAAACRUUAAAAAAiIwCAgAAAEBkFBAAAAAAIqOAAAAAABAZBQQAAACAyCggAAAAAERGAQEAAAAgMgoIAAAAAJFRQAAAAACIjAICAAAAQGQUEAAAAAAio4AAAAAAEBkFBAAAAIDIKCAAAAAAREYBAQAAACAyCggAAAAAkVFAAAAAAIiMAgIAAABAZBQQAAAAACKjgAAAAAAQGQUEAAAAgMgoIAAAAABERgEBAAAAIDIKCAAAAACRUUAAAAAAiIwCAgAAAEBkFBAAAAAAIqOAAAAAABAZBQQAAACAyCggAAAAAERGAQEAAAAgMgoIAAAAAJFRQAAAAACIjAICAAAAQGQUEAAAAAAi87aAqFQq6u7uVm9vr7q7u1WpVOIOCUAC+dpW+JoXAMxVSWrX22Nb8wyqVCoqFosql8s6dOiQ2tralM/nJUm5XC7m6AAkha9tha95AcBclbR23cseiFKppHK5rGw2q/b2dmWzWZXLZZVKpbhDA5AgvrYVvuYFAHNV0tp1LwuIWq2mnp6ecct6enpUq9ViighAEvnaVviaFwDMVUlr170sIDKZjIaHh8ctGx4eViaTiSkiAEnka1vha14AMFclrV33soAoFovK5/OqVqs6ePCgqtWq8vm8isVi3KEBSBBf2wpf8wKAuSpp7bqXk6jrk0kKhYJqtZoymYxKpRKTBwGM42tb4WteADBXJa1d97KAkII3OpfLaWhoSCtWrIg7HAAJ5Wtb4WteADBXJald93IIEwAAAICZQQEBAAAAIDIKCAAAAACRUUAAAAAAiIwCAgAAAEBkFBAAAAAAIqOAAAAAABAZBQQAAACAyCggUqRSqai7u1u9vb3q7u5WpVKJOyQACUV7AWAu87ENTFJO3t6J2jeVSkXFYlHlclmHDh1SW1ub8vm8JMV2G3MAyUR7AWAu87ENTFpO9ECkRKlUUrlcVjabVXt7u7LZrMrlskqlUtyhAUgY2gsAc5mPbWDScqKASIlaraaenp5xy3p6elSr1WKKCEBS0V4AmMt8bAOTlhMFREpkMhkNDw+PWzY8PKxMJhNTRACSivYCwFzmYxuYtJwoIFKiWCwqn8+rWq3q4MGDqlaryufzKhaLcYcGIGFoLwDMZT62gUnLiUnUKVGfIFMoFFSr1ZTJZFQqlVI7GQjAzKG9ADCX+dgGJi0nCogUyeVyyuVyGhoa0ooVK+IOB0CC0V4AmMt8bAOTlBNDmAAAAABERgEBAAAAIDIKCAAAAACRUUAAAAAAiIwCAgAAAEBkFBAAAAAAIqOAAAAAABAZBQQAAACAyCggAAAAAERGAQEAAAAgMgoIAAAAAJFRQAAAAACIjAICAAAAQGQUEAAAAAAio4AAAAAAEJm3BUSlUlF3d7d6e3vV3d2tSqUSd0jT5mNOSBf2QQDwi6/tuq95JUV73AHMhEqlomKxqHK5rEOHDqmtrU35fF6SlMvlYo6uOT7mhHRhHwQAv/jarvuaV5J42QNRKpVULpeVzWbV3t6ubDarcrmsUqkUd2hN8zEnpAv7IAD4xdd23de8kmTaBYSZLTCzr5jZN83sUTO7rhWBTUetVlNPT8+4ZT09ParVajFFNH0+5oR0YR8EAL/42q77mleStKIHYr+k1zvnXiXp1ZLeZGa/04LXbVomk9Hw8PC4ZcPDw8pkMjFFNH0+5oR0YR8EAL/42q77mleSTLuAcIE94X+PC3/cdF93OorFovL5vKrVqg4ePKhqtap8Pq9isRhnWNPiY05IF/ZBAPCLr+26r3klSUsmUZtZm6SHJb1c0v9xzv1bK163WfUJMoVCQbVaTZlMRqVSKdUTZ3zMCenCPggAfvG1Xfc1ryQx51rXWWBmp0j6jKSCc27HhN9dIekKSTr99NOX33nnnS1b75Hs2bNHixYtmpV1zRYfc5L8zMvHnCQ/8/IxJ8nPvHzMSfIzLx9zkvzMy8ecJD/zms2cstnsw865cyYub2kBIUlmdq2kUefcR6d6zjnnnOMeeuihlq53KkNDQ1qxYsWsrGu2+JiT5GdePuYk+ZmXjzlJfublY06Sn3n5mJPkZ14+5iT5mdds5mRmkxYQrbgK04vCngeZ2fGS3iDp36f7ugAAAACSpxVzIBZLui2cBzFP0t855+5pwesCAAAASJhpFxDOuUcknd2CWAAAAAAknJd3opaC25h3d3ert7dX3d3dqlQqcYeEOYT9D3FjHwQAvySpXW/JZVyTplKpqFgsqlwu69ChQ2pra1M+n5ckLuGFGcf+h7ixDwKAX5LWrnvZA1EqlVQul5XNZtXe3q5sNqtyuaxSqRR3aJgD2P8QN/ZBAPBL0tp1LwuIWq2mnp6ecct6enpUq9ViighzCfsf4sY+CAB+SVq77mUBkclkNDw8PG7Z8PCwMplMTBG1RpLGvrWSb3n5uv9J/m0rX/m6D/q6//maF9KB/S8dktauezkHolgsKp/Pj40Tq1aryufzqe6+T9rYt1bxMS8f9z/Jz23lKx/3QV/3P1/zQjqw/6VH4tp159ys/yxfvtzNtIGBAdfV1eXmzZvnurq63MDAwIyvcyZ1dXW5wcFB55xz1WrVOefc4OCg6+rqijGq6fM1L9/2P+f83VZ19Zx84ds+6Ov+52tedb59rup8ycv3/c85f7aVc/G065IecpMcy3tbQNT5suPMmzfPHThwwDl3OKcDBw64efPmxRjV9PmaV50v+59zbKu08iUvX/c/X/Oq82X/m8iXvHzf/5zzZ1s1ms2cpiogvJwD4aOkjX1rFV/z8hHbCnHydf/zNS+kA/sfmkUBkRL1sW/ValUHDx4cG/tWLBbjDm1afM3LR2wrxMnX/c/XvJAO7H9olpeTqH1Un8xUKBRUq9WUyWRUKpVSP8nJ17x8xLZCnHzd/3zNC+nA/odmUUCkSC6XUy6X09DQkFasWBF3OC3ja14+YlshTr7uf77mhXRg/0MzGMIEAAAAIDIKCAAAAACRUUAAAAAAiIwCAgAAAEBkFBAAAAAAIqOAAAAAABAZBQQAAACAyCggAAAAAERGAQEAAAAgMgoIAAAAAJFRQAAAAACIzNsColKpqLu7W729veru7lalUok7pGnzMScAmOto2xEn9j80oz3uAGZCpVJRsVhUuVzWoUOH1NbWpnw+L0nK5XIxR9ccH3MCgLmOth1xYv9Ds7zsgSiVSiqXy8pms2pvb1c2m1W5XFapVIo7tKb5mBMAzHW07YgT+x+a5WUBUavVNDIyMq5LbmRkRLVaLe7Qmlar1dTT0zNuWU9PT6pzqqP7ND3YVoiTj/ufz207ks/n/c/H9iJJvBzCtGTJEvX19emOO+4Y65JbvXq1lixZEndoTctkMhoeHlY2mx1bNjw8rEwmE2NU00f3aXqwrRAnX/c/X9t2pIOv+5+v7UWSeNkDIUnOuSP+P22KxaLy+byq1aoOHjyoarWqfD6vYrEYd2jTQvdperCtECdf9z9f23akg6/7n6/tRZJ42QOxe/du3XrrrSoUCqrVaspkMtq4caMuu+yyuENrWr1ibsypVCqlvpL2ufvUN2wrxMnX/c/Xth3p4Ov+52t7kSRe9kBkMhl1dnZqx44d2r59u3bs2KHOzs7Ud8nlcrlxOaX9Ay4d7j5t5EP3qY/YVoiTz/ufj2070sPH/c/n9iIpvCwgfO2S8xHbKj3YVogT+x+AqGgvZp6XQ5h87ZLzEdsqPdhWiBP7H4CoaC9mnpcFhBTsPLlcTkNDQ1qxYkXc4eAI2FbpwbZCnNj/AERFezGzvBzCBAAAAGBmUECkiK83RfE1Lx+xrRAnX/c/X/MC4C9vhzD5xtebovial4/YVoiTr/ufr3kB8Bs9ECnh601RfM3LR2wrxMnX/c/XvAD4jQIiJXy9KYqvefmIbYU4+br/+ZoXAL9RQKSErzdF8TUvH7GtECdf9z9f8wLgNwqIlPD1pii+5uUjthXi5Ov+52teAPzGJOqU8PWmKL7m5SO2FeLk6/7na14A/EYBkSK+3hTF17x8xLZCnHzd/3zNC4C/GMIEAAAAIDIKCAAAAACRUUAAAAAAiIwCAgAAAEBkFBAAAAAAIqOAABBZpVJRd3e3ent71d3drUqlEndImEPY/4DW43OFZnAZVwCRVCoVFYtFlctlHTp0SG1tbcrn85LENesx49j/gNbjc4Vm0QMBIJJSqaRyuaxsNqv29nZls1mVy2WVSqW4Q8McwP4HtB6fKzSLAgJAJLVaTT09PeOW9fT0qFarxRQR5hL2P6D1+FyhWRQQKcI4RcQpk8loeHh43LLh4WFlMpmYIsKR+NZe+Lz/+batkB6ZTEbXXXfduP3vuuuu8+JzhZnFHIiUYJwi4lYsFpXP58f2wWq1qnw+T1d3AvnYXvi6//m4rZAe2WxWGzZs0IYNG7Rs2TLt3LlTfX19Wrt2bdyhIemcc7P+s3z5cjdbqtXqrK1rJnV1dbnBwUHn3OGcBgcHXVdXV4xRtZYv26qRbzkNDAy4rq4uN2/ePNfV1eUGBgbiDqllfNpWvrYXPu5/vm6rOp8+V418yaurq8sVi8Vxn6v6/33hy7ZqNJs5SXrITXIsTw9ESjBOEUmQy+WUy+U0NDSkFStWxB0OpuBre+Hj/ufrtkI61Go1ff3rX9df/dVfjX2unn32WX34wx+OOzQkHHMgUsLn8b8AWov2Ij3YVogT+x+aRQGREvXxv9VqVQcPHhwb/1ssFuMODZNgUiTiVCwWtXLlSi1dulS9vb1aunSpVq5cSXuRQLTtiBP7H5rFEKaUqE+mKxQKqtVqymQyKpVKTLJLICZFIkmCIaxIKtp2xIn9D82iByJFcrmcduzYoe3bt2vHjh18wBOKG/MgbqVSSVu3btWuXbs0ODioXbt2aevWreyDCUXbjjix/6EZFBBAizEpEnFjHwQAzCQKCKDFmJSGuLEPAgBmEgUE0GJMSkPc2AcBADOJSdRAizEpDXFjHwQAzCQKCGAG+HjDK6QL+yAAYKYwhAkAAABAZBQQAAAAACKjgAAAAAAQGQUEAAAAgMgoIAAAAABERgEBAAAAIDIKCAAAAACReVtAVCoVdXd3q7e3V93d3apUKnGHNG0+5gQAANBqHDPNLC9vJFepVFQsFlUul3Xo0CG1tbUpn89LUmrvxOpjTgAAAK3GMdPM87IHolQqqVwuK5vNqr29XdlsVuVyWaVSKe7QmlYqlbRq1SoVCgWdf/75KhQKWrVqVapzquMsQXqwrRAnX/c/X/MC4uLjcWDSeNkDUavV1NPTM25ZT0+ParVaTBFN386dO7V3797nVdOPP/543KFNC2cJ0oNthTj5uv/5mhcQJx+PA5PGyx6ITCaj4eHhccuGh4eVyWRiimj65s+fryuvvHJcNX3llVdq/vz5cYc2LZwlSA+2FeLk6/7na15AnHw8DkwaLwuIYrGofD6varWqgwcPqlqtKp/Pq1gsxh1a0w4cOKD+/v5xOfX39+vAgQNxhzYtnCVID7YV4uTr/udrXkCcfDwOTBovhzDVu30LhYJqtZoymYxKpVKqu4OXLVumiy++eFxOq1ev1t133x13aNNSP0uQzWbHlnGWIJnYVoiTr/ufr3kBcfLxODBpvCwgpGDnyeVyGhoa0ooVK+IOZ9qKxeKk42TT3s1dP0tQz6t+liDtefmIbYU4+br/+ZoXEDffjgOTZtoFhJm9VNLtkl4s6TlJNzvnPjbd18V4vlbTvublI7YV4uTr/udrXgD81ooeiIOS3uuc+5qZnSjpYTN7wDm3swWvjQa+VtO+5uUjthXi5Ov+52teAPw17UnUzrkfOOe+Fj7+haSapJdM93Wnq1AoaMGCBcpms1qwYIEKhULcIU0b1woHAP/QtgOIIklthTnnWvdiZmdJ+pKkbufcMxN+d4WkKyTp9NNPX37nnXe2bL0TfexjH9PnPvc5XXHFFXr961+vwcFB3XzzzXrLW96idevWzdh6Z9L27dtVLpf1vve9T0uXLtWuXbt0ww03KJ/Pq7e3N+7wWmLPnj1atGhR3GG0lI85SX7m5WNOkp95+ZST7227T9uqkY95+ZiT5E9ecbUV2Wz2YefcOc/7hXOuJT+SFkl6WNLvH+25y5cvdzOpo6PD3Xjjjc4556rVqnPOuRtvvNF1dHTM6HpnUldXlxscHHTOHc5pcHDQdXV1xRhVa9Xz8omPOTnnZ14+5uScn3n5lJPvbbtP26qRj3n5mJNz/uQVV1sh6SE3ybF8S+4DYWbHSfoHSXc45/6xFa85Hfv379fatWvHLVu7dq32798fU0TTx7XCAcA/tO0AokhaWzHtAsLMTFJZUs05t2n6IU1fR0eHNm/ePG7Z5s2b1dHREVNE08ddFQHAP7TtAKJIWlvRih6I10p6p6TXm9k3wp8LW/C6Tbv88svV19enTZs2ad++fdq0aZP6+vp0+eWXxxnWtHBXRQDwD207gCiS1lZM+zKuzrlhSdaCWFqmv79fknTNNddo//796ujo0Nq1a8eWpxHXCgcA/9C2A4giaW2Ft3ei7u/vV39/v1fX1eZa4QDgH9p2AFEkqa1oySRqAAAAAHMDBQQAAACAyCggAAAAAERGAQEAAAAgMgoIAAAAAJFRQAAAAACIjAICAAAAQGQUEClSqVTU3d2t3t5edXd3q1KpxB1SS/ial4/YVunh47byMSfJ37wA+MvbG8n5plKpqFgsqlwu69ChQ2pra1M+n5ekVN+x1Ne8fMS2Sg8ft5WPOUn+5gXAc865Wf9Zvny5my3VanXW1jWTurq63ODgoHPucE6Dg4Ouq6srxqimz9e86nzZ/5xjW6WJj9vKx5yc8zevOp8+V418zMvHnJzzM6/ZzEnSQ26SY3lvhzD51iVcq9U0MjIyLqeRkRHVarW4Q5uWWq2mnp6ecct6enpSn5eP2Fbp4eO28jEnyd+8gLj5dhyYNF4OYfKxS3jJkiVav369BgYGxnJatWqVlixZEndo05LJZDQ8PKxsNju2bHh4WJlMJsaoMBm2VXr4uK18zEnyNy8gTj4eByaNlz0QpVJJ5XJZ2WxW7e3tymazKpfLKpVKcYc2LWZ2xP+nUbFYVD6fV7Va1cGDB1WtVpXP51UsFuMODROwrdLDx23lY06Sv3kBcfL1ODBRJhvXNNM/Mz0HYt68ee7AgQPOucPjxA4cOODmzZs3o+udSfPmzXO333676+rqcvPmzXNdXV3u9ttvT3VOdQMDA+PyGhgYiDuklvFt7OWVV17pOjo6nCTX0dHhrrzyyrhDahnftpWPnysfc3LO37yc8+9zVedjXj7l5ONxYCPmQMyQepdwo7R3CWcyGXV2dmrHjh3avn27duzYoc7OzlTnVJfL5cblRfdiMlUqFd17773atm2bHnjgAW3btk333nsv40oTysfPlY85Sf7mBcTFx+PApPGygPCxS7hYLGrlypVaunSpent7tXTpUq1cuTLVOSFd6BJOFyYQpgfbCnHycf/z8TgwabycRF0/e1MoFFSr1ZTJZFQqlbw5qxP0KAGzi6vFpAcTCNODbYU4+br/+X4cmAiTjWua6R/uA3HsfL9WuHP+bKtGPuXk+z7ItkoPtlV6+LStGvmSl+/7n3P+bKtGSZgD4WUPhI84+4u41YfRLVy4UE8++aTOOOMMjY6O6mMf+1jcoWEC2ov0aLzHT/1MaV9fH9sKs4K2As2igEgJrhWOJHEMo0s02ov0WLJkifr6+nTHHXeMDSFZvXp16u/xg3SgrUCzvJxE7SMmBCFupVJJW7du1a5duzQ4OKhdu3Zp69atTKJOINqLdJlYkFOgY7bQVqBZ3vZAVCoVlUqlsS7hYrGY6skzuVxODz74oC644ALt379fHR0duvzyy1OdE9KFru70YAJheuzevVt/+qd/Oq5tX7NmjT75yU/GHRrmANoKNMvLAsLHqwo0XoO/Madzzz03tTkhXejqTpdcLqdcLqehoSGtWLEi7nAwhSVLlugzn/nMuLZ91apVDGHCrKGtQDO8HMLk4/XqfcwJ6UJXNzAzzOyI/weApPGygPBxqIWPOSFdcrmcLrroIl1wwQV64xvfqAsuuEAXXXQRPWAJ5ePNoXy0e/dubdiwQYVCQeeff74KhYI2bNig3bt3xx0aAEzJywLCx1uYZzIZXXfddeMOCK677rpU54R0qVQq2rp1qxYvXiwz0+LFi7V161YOTBOoPoyzv79f9913n/r7+1UsFlO/rXwsijKZjB577LFxyx577DHadgCJ5uUciPpQi/ociPpQizQP98lms9qwYYM2bNigZcuWaefOnerr69PatWvjDg1zxPr169XW1qYtW7aMG6u9fv16eiESpnHIY31cc7lcVqFQSO228nFum0TbDiCdvCwgfLyqQLVaVV9fn7Zs2TLuZkN333133KFhjhgZGdH9998/7qD09ttv13nnnRd3aJjAxyGPPhZFEm07gHTycgiTJD344IP6zne+o+eee07f+c539OCDD8Yd0rTUajVde+212rFjh7Zv364dO3bo2muvTd0BgZlN+ZPNZqf8HYDofBzG6WNRJPnTtgNJUygUtGDBAmWzWS1YsECFQiHukLziZQFRKBS0efNmXX/99dq2bZuuv/56bd68OdU7jy8HBM65KX/O7Ltnyt8hfp2dnbr00kvHXYXp0ksvVWdnZ9yhYYJisaiVK1dq6dKl6u3t1dKlS7Vy5cpUXzHLlzZwIl/zAuJUKBT08Y9/XC94wQs0b948veAFL9DHP/7xVB8HSsmaB+blEKZbbrlFGzZs0FVXXaWhoSFdddVVkqRrrrlG/f39MUfXHB/ndSBdNm7cqHXr1mnNmjV68skndcYZZ+jgwYO68cYb4w4NR+BLAe5rG+hrXkCcNm/erFNOOUUDAwNjc6b+4A/+QJs3b07tcWDi5oEd6YzwTP0sX77czSRJbnR01DnnXLVadc45Nzo66oJ000FS0z9pdWbfPXGH0HL1/c8XAwMDrqury82bN891dXW5gYGBuENqGZ+2VVdXlysWi+O2Vf3/aebr/nfllVe6jo4OJ8l1dHS4K6+8Mu6QWsanz1Ujn/Ly8XMlyX3+8593zh3eVp///OdTfYzU1dXlBgcHnXOHcxocHJzxdl3SQ26SY3kveyA6Ojq0efPmsZ4HKahGOzo6Yozq2LgjnDU86+p79fhHLprFaIAAdyxNh507d2rv3r3PO1P1+OOPxx3atPi4/1UqFd17773j7kSdz+d17rnnpnpyONIhcWe1W2jHjh264IILxv0/zZI2D8zLORCXX365+vr6tGnTJu3bt0+bNm1SX1+fLr/88rhDA4AZN3/+fF155ZXj7lx/5ZVXav78+XGHhgkary5V31blcpkhTJgVvu5/p556qq6++upxx4FXX321Tj311LhDa1rS5kt52QNRH992zTXXaP/+/ero6NDatWtTO+4NAI7FgQMH1N/fr7PPPntsXH1/f78OHDgQd2iYIGlnFTG3+Lr/3XTTTVq7dq2uvvpqPfvsszruuOO0aNEi3XTTTXGH1rSkzZfysoCQgiKiv7/fq65uAIhi2bJluvjii8fdC2f16tXcWyCB6mcVs9ns2DKuwoTZ4uv+Vx9+VSqVVKvV9Gu/9msqFoupHpaVtHuceVtAAMBcVSwWJx3XnPZhCT5K2llFzC0+738+zplKUk4UEADgmaSdqcLU2FaIE/sfmuXlJGopWTfbAAAASKJcLjfuTugUD4jCyx4Iny9LBsSpUqmMjSnNZDKpH1Pqq0qlonXr1mnhwoWSpNHRUa1bt04SbWDSNG4r5xzbCkAqeNkD4etlyYA41Qvz/v5+3Xffferv71exWKR3L4HWr1+vZ599VtLhe8o8++yzWr9+fZxhYRLr169XW1ubtmzZovvvv19btmxRW1sb2wqzhhEbaIaXPRC+XpYMiFNjYV6fwFUul1UoFDhTmjAjIyM6/fTTtWXLlrFe2Fwup5GRkbhDwwQjIyO6//77x32ubr/9dp133nlxh4Y5gBEbaJaXPRCZTEbXXXfduIr6uuuuS/1lyYA41Wo1jYyMjPtcjYyMpL4w9/Xs23vf+95xvbDvfe974w7pmJjZlD/ZbPaIvwcQDSM20CwveyCy2aw+/OEP60UvepGee+45/fSnP9WHP/xhvfvd7447NCC1lixZorVr1+rZZ5/Vc889p//4j//Q2rVrtWTJkrhDa5rPZ982bdqkc845Z+zSjJs2bYo7pGNSH3o1mbOuvlePf+SiWYxm5nR2durtb3+7TjnlFD3xxBM688wz9bOf/UydnZ1xh4Y5oPHEUH1uW19fX+pPDGHmedkDcffdd+vEE0/U8ccfr3nz5un444/XiSeeyE2UgGl4+umntXfvXv3Jn/yJPve5z+lP/uRPtHfvXj399NNxh9Y0X8++dXZ2at++fVqzZo3OO+88rVmzRvv27eOgNIEuvvhiPfPMM9q3b5/MTPv27dMzzzyjiy++OO7QMAcsWbJEfX194+a29fX1pfrEEGaHlwXEyMiI7rrrLu3atUvbt2/Xrl27dNdddzH+F5iG0dFR5XI5felLX9Lb3vY2felLX1Iul9Po6GjcoTXN1/lSGzdu1HHHHSdJY0N6jjvuOG3cuDHOsDCJarWq97///TrttNMkSaeddpre//73q1qtxhwZ5oqJvX1H6v0D6rwcwgRgZrz0pS/VI488Mu7/aZbJZDQ8PKxsNju2bHh4OPXzperDr+o9KQsXLtT111+f+mFZPphsjsajjz467nH9/43P5aAOM2H37t360z/9U11wwQXav3+/Ojo6tGbNGn3yk5+MOzQknJc9EPUxpUuXLtXrX/96LV26VG9/+9vpvgemYd68ebrhhhv005/+dGxu0Q033KB589LbjBSLRa1cuXJcW7Fy5UoVi8W4Q5s2bg6VTM65cT9dXV0aHByUc05n9t0j55wGBwfV1dU17nnATFiyZInuvvtubdu2TQ888IC2bdumu+++myFMCZWki3542QNx8cUX6+Mf/7gWLFgwbkzpO97xjrhDA1Lr+OOP1+joqA4cOCAz04EDB+Sc0wknnBB3aC3B1XsQh2KxqHw+r3K5LHfooKrVqvL5fOrn4SA9GMKUDkm76Ed6Tx0eAWNKgdYbHR3VW9/6Vu3du1fOOe3du1dvfetbUz0HolQqaevWrePmS23dupWDN8yaXC6nUqmkQqGgJ2/8fRUKBZVKJXqMMCt2796tjRs3qlAo6Pzzz1ehUNDGjRu1e/fuuEPDBEm76IeXBUStVtMrX/nKccte+cpXpn5iJBC3rq4uvfzlL9e8efP08pe/XF1dXXGHNC2+TqJGutSHm525/rMMN8OsymQy6uzsHDfcsbOzM/XzwHyUtO8rLwuIJUuWqFAojJ0ZHR0dVaFQYEwfMA2nnnqqNm7cqDVr1ujee+/VmjVrtHHjRp166qlxh9a0+iTqRj5MogaAKOpD6KrVqg4ePDyEzod5YEmaL9AKSfu+8nIOxN69e7Vnzx598IMf1LJly7Rz506tX79ebW1tcYcGpNYJJ5ygQ4cOqb+/X08++aTOOOMMLVq0KNVzIBrHn9dvuMb4cwBzRb23q1AojN1IzochdEmbL9AKSfu+8rKAeOqpp/T+979fW7ZsGftArF+/Xh/+8IfjDg1Ird27d+vWW2/Vhg0bJAWXBv2Lv/gLXXbZZfEGNg2+fnkCQFS5XE65XE5DQ0NasWJF3OG0RON8gXpe5XJZhUIhte170r6vvBzCJEnZbHbcmL7G67wDOHa+jpXlcqcA4JekzRdolSR9X3lZQHR2duqSSy4ZN6bvkksu4T4QwDT4PFYWAOCPpM0X8JGXBcTGjRt16NAhrVmzRuedd57WrFmjQ4cOaePGjXGHBqRWLpfTRRddpAsuuEBvfOMbdcEFF+iiiy5K/Rl73yba1fmaF4DW8rGt4ITXzPNyDkT9gKZUKsnMtHDhQl1//fWpP9AB4lSpVLR161YtXrxYTzzxhBYvXqytW7fq3HPPTe1ny8eJdpK/eQFoLV/biqTNF/CRlz0QUrLGiQE+WL9+vQ4cOCDp8F2bDxw4oPXr18cZ1rQk7cY8rVIqlbRq1apxN4datWpV6vMC0Fo+txUcB84sL3sgALTeyMiIXvziF2vLli1jZ6pWrVqlkZGRuENrmq8T7Xbu3KnR0dFx22rNmjV64okn4g4NQILQVqBZ3vZAAGi9q666atzZ+quuuirukKbF14l28+fPV6FQGLetCoWC5s+fH3doABKEtgLNogcCQGSbNm3SOeecM3YTm02bNsUd0rQk7cY8rXLgwAHddNNNOvvss8fyuummm8aGoAGARFuB5lFAAIiks7NTv/jFL7RmzZqxO1H/8pe/TPXlkX2daLds2TJdfPHF4/JatWqV7r777rhDA5AgtBVoFkOYAESyceNG7d27V48//riee+45Pf7449q7d2/qL4/s40S7YrGogYEB9ff367777lN/f78GBga4hCFmjY+XBpX8y4u2Il2StP/RAwHMgEqlolKpNHZGp1gspv7A9NZbb9Wzzz6rF7zgBfr5z3+uk08+WU8//bRuvfXW1Ofmm1wupwcffFAXXHCB9u/fr46ODl1++eVsJ8wKXy8N6mNevvbC+ihx+59zbtZ/li9f7mZLtVqdtXXNljP77ok7hBnhS14DAwNu6dKlbnBw0D3wwANucHDQLV261A0MDMQd2rSYmXvDG97gurq63Lx581xXV5d7wxve4Mws7tBawqe2wtd9sM6XtmIiX/Lq6upyg4ODzrnDn6vBwUHX1dUVY1TT52tedT61gY18ySuu/U/SQ26SY3mGMAEt5uu9BZxz+va3vz2uq/vb3/62gvYFSeLrPoh08PXyyL7mhXRI2v5HAQG0WNI+5K30qle9atxB6ate9aq4Q8IkarWaRkZGxo2VHRkZ8WIfRPL5enlkX/NCOiRt/6OAAFosk8nouuuuG3fwdt1113nxJfPZz35W7373u7Vnzx69+93v1mc/+9m4Q5q2JE1Ka5UlS5boPe95j0ZHR+Wc0+joqN7znvdoyZIlcYeGOaB+eeRqtaqDBw+OXR457RNzfc0L6ZC0/Y9J1ECLZbNZbdiwQRs2bNCyZcu0c+dO9fX1ae3atXGHNi1dXV368Y9/rE984hP6xCc+IUl60YtepF/5lV+JObLmJW5SWovs3btXP//5z7VgwQKZmfbt26ef//znmjePc0aYeb5OzPU1Lx8v+uGjpO1/FBBAi1WrVfX19WnLli1jH/K+vr7UX1f7JS95iR599FG9613v0oUXXqjPf/7z+sQnPqGzzz477tCa1jhXYGhoSCtWrFC5XFahUEj1F+hTTz2lk08+WQsWLJBzTgsWLNBJJ52kp556Ku7QMEfkcjnlcrmxz5UvfMvL15MovkrS/sfpKKDFarWarr322nH3Frj22mtTP/78i1/8ol772tdqy5Ytestb3qItW7bota99rb74xS/GHVrTfJ4rUCwWtWvXLg0ODmrXrl0MswDwPKVSSatWrVKhUND555+vQqGgVatWccEFHBU9EECL1Sc6ZbPZsWU+TLTbv3+/HnvsMS1evFhPPPGEFi9erMcee0z79++PO7SmLVmyRH19fbrjjjvGzr6tXr3ai7kCmzZt0jnnnKNDhw6pWq1q06ZNcYcEIGF27typ0dFRbdmyZawNXLNmjZ544om4Q5s2hmbNLAoIoMXqE53qXcL1iU4+nNHZs2ePFi1aNO7/abd3796xL8wzzzxTe/fu1Yknnhh3WNPS2dmpH//4x3r9618/tmz+/Pnq7OyMMSog/Xw7KJ0/f75e+9rXjhtX/9rXvlY/+MEP4g5tWnwdmpWk/c+LAsLMmvo7rl+PmZC0iU6ttG/fPl1wwQXj5kCk2fe//32ddtppkg63I8cdd5y+//3vxxnWtC1btkwjIyN6wQteoJ/97Gc65ZRT9PTTT2vZsmVxhwaklo8Hpfv379fWrVufd9GPgwcPxh3atPg4vy1x+99kd5eb6Z/ZvBO1L3f2bORjTs75mZcvd8B0zjlJ7txzz3UdHR1Okuvo6HDnnnuuC5qRdOro6HA33nijc+7wtrrxxhtdR0dHjFFNX0dHh1u9evW4u4avXr069XnV+dhWOOdnXj61gT7eidrXtmLevHnuwIEDzrnD2+rAgQNu3rx5MUY1PUm7E7UXPRAAZsd3v/tdbdu2bezsx6pVq+IOaVoOHDigm266SWefffbYcLObbrpJBw4ciDu0adm/f79uvvlmnXDCCWNn3/bu3as77rgj7tCA1PLxJqEHDhzQgw8++Lyz2mlvA32ci5i0/Y+rMAGIpLOzU/v27dOaNWt0/vnna82aNdq3b1+qx9UvW7Zs0iuQpH2oT0dHhzZv3jxu2ebNm9XR0RFTRED6Je1OwK3gaxuYtJuutULS9r+W9ECY2RZJb5b0Y+dcdyteE0CybNy4UevWrRu37LjjjtPGjRtjimj6isXipGNK0z7h/fLLL1dfX5+k4ABh06ZNXtzMEIhTsVjUypUrtXDhwrGLLoyOjupjH/tY3KE1zdc20Me5iEnb/1o1hOlWSTdJur1FrwcgYeoNb/2LZeHChbr++utT3SDncjk9+OCDuuCCC7R//351dHTo8ssvT3VOktTf3y9Juuaaa8byWrt27dhyANPT7MVbksbHA+26JN10rdWSsP+1ZAiTc+5LkrjFKeC5XC437gZ5af+SqVQquvfee7Vt2zY98MAD2rZtm+69915VKpW4Q5u2/v5+7du3T9VqVfv27aN4wKyqVCrjbtDow2eqVCpp69at2rVrl7Zv365du3Zp69atXpyt96ld91XS9j8mUQOY1Fy4PLKPl/oD4pa4y022SNImsWJuSdr+N2sFhJldIekKSTr99NM1NDQ0W6ue1XXNFh9zkvzLa8+ePanNqVqtTvm7y74wqlvftHDS36Up31qtpgceeEBr1qzRk08+qTPOOEO5XE61Wi1VeRxJmvfBI/ExJ8mPvK655hq95z3vkZlp3759WrRokQqFgq655hotXrw47vCadsYZZ4xdta3+ufr617+uM844w4vt5mtb4Uteidv/Jru2azM/ks6StCPKc7kPxPT4mJNzfubl0zXQG/myrTo7O92LX/xiNzg46B544AE3ODjoXvziF7vOzs64Q2sZH/dBX/a/iXzJy8dr8Dvn3MDAgFu6dOm49mLp0qVuYGAg7tBawse2wjl/8opr/xP3gQCA55s4VCsJk9OANPPxGvyS3xOOkXxJ2/9aMonazCqS/kXSK81sxMzyrXhdAJhJu3fv1oYNG8ZdA33Dhg3avXt33KEBqeXjNfgBjNeSHgjnHOU30KBSqahUKo2dJSgWi5ylSqBMJqPOzk7t2LFjbBJ1tVpN/ZlSiX0Q8UnamdJW8XVyONKhUqlo3bp1WrgwmH84Ojo6dm+mOPY/hjABLcaXTHrUz5TWt1X9TGnaL8vIPoi4+XgNfq7ahjitX79e7e3t2rJly1i7vnr1aq1fv54CAvABXzLp4euZ0lKppFWrVo3La9WqVV7kBsQlaZfRxNwyMjKi+++/f9yxxW233abzzjsvlngoIIAW40smXXw8U7pz507t3bv3eT0Qjz/+eNyhAanl6+RwoBktmUQN4LD6l0wjvmQwm+bPn69zzz133OTwc889V/Pnz487NCC1mByOOHV2duqSSy4Zt/9dcskl6uzsjCUeeiCAFisWi3rb296mffv26dlnn9Vxxx2nBQsW6JOf/GTcoWGOOHDggO644w61t7frueee02OPPaZHH32US9QC0+DDkMfptAHBLQEQl40bN2rdunVas2aNnnjiCZ155pk6dOiQNm3aFEs89EAALfbggw9qdHRUp556qiTp1FNP1ejoqB588MGYI8NkKpWKuru71dvbq+7ublUqlbhDmjYzk5nptNNOkySddtppY8sANC+Xy2nHjh3avn27duzYkariQTryzYPP7LvnaDcMRoxyuZxWrlypH/zgB3LO6Qc/+IFWrlyZ7vtAADjslltu0Q033KAf/vCHqlar+uEPf6gbbrhBt9xyS9yhYYL61Yr6+/t13333qb+/X8ViMfVFxHPPPacTTjhBxx9/vMxMxx9/vE444QQ999xzcYcGAGhCpVLR1q1btXjxYs2bN0+LFy/W1q1bY/u+ooAAWmz//v1au3btuGVr167V/v37Y4oIU2m8WlF9rkD9akVpN29e0LzXex3q/wcApE/jZVzvu+8+bdmyRe3t7Vq/fn0s8fCNArRYR0eHNm/ePG7Z5s2b1dHREVNEmMrOnTs1MDAwrgdiYGBAO3fujDu0lmj8ogFmk49DA4E4jYyM6LbbblM2m1V7e7uy2axuu+02jYyMxBIPk6iBFrv88svV19cnSVq2bJk2bdqkvr6+5/VKIH7z58/XlVdeOe662ldeeaWuueaauEObttHRUeVyOf3oRz/S6aefrtHR0bhDwhzBjQwx25qd38XcjuZRQAAt1t/fL0m65pprtH//fnV0dGjt2rVjy5EcBw4cUH9/v84+++yxO1H39/frwIEDcYc2LV1dXXrFK16hbdu2SZJ+9rOf6a1vfau+/e1vxxwZ5gJuponZdqRC4Kyr79XjH7loFqOZGfXLuA4MDIx9X8V5GVeGMAEzoL+/X/v27VO1WtW+ffsoHhJq2bJlWr169bg5EKtXr9ayZcviDm1aisWivvzlL4+bbPflL3+Z69VjVtRqNY2MjIwbwjQyMuLFzTQZmoW4bNy4UYcOHdKaNWt03nnnac2aNTp06JA2btwYSzz0QACYs4rF4qRDLXyYRF1HFz1m25IlS7R+/fqxM6VtbW1atWqVlixZEndo08LQLMSpvo+VSiWZmRYuXKjrr7+ey7gCwGzL5XJ6xSteod7eXr3xjW9Ub2+vXvGKV6T+YKBUKmnr1q3atWuXBgcHtWvXLm3dutWrwgjJNnFMug/3IGkcmlWfxFoul/lcYdYk6T4kFBAA5qxCoaDBwUF99KMf1bZt2/TRj35Ug4ODKhQKcYc2LbVaTXfddZcWLFigbDarBQsW6K677vJiCAmSb/fu3dqwYcO4oYEbNmzQ7t274w5tWmq1mnp6esYt6+np4XOFOYkCAsCcdcstt2jDhg266qqrtGDBAl111VXasGFD6m/6d8opp+jmm2/W9ddfr23btun666/XzTffrFNOOSXu0DAHZDIZdXZ2jjtT2tnZqUwmE3do05LJZDQ8PDxu2fDwcOrzAppBAQFgzvL1pn/PPPOMTjrpJJ199tlqb2/X2WefrZNOOknPPPNM3KFhDigWi8rn86pWqzp48KCq1ary+XzqJ/H7mhfQDCZRA5iz6jf9u+qqq8aW+XDTv4MHD+rGG29UoVBQrVZTJpPRjTfeqDVr1sQdGuaA+rjsxv2vVCqlfm6Rr3kBzaCAADBn+XrTv46ODm3fvn3csu3bt6e+MEJ65HI55XK5sftA+MLXvIBjRQEBYM7y9aZ/r3vd63THHXfoXe96lz7ykY/o85//vD7xiU/ovPPOizs0AIAHKCAAzGn9/f3q7+/36ozi97//fV188cXasmWLPvGJT6ijo0MXX3wxd6IGALQEk6gBwDO1Wk2LFy8et2zx4sVcbhIA0BL0QACAZ0455RR98pOf1A033KBly5Zp586det/73sdlXIFj0OzN77j7O+YCeiAAzGmVSkXd3d3q7e1Vd3e3KpVK3CFN2zPPPKNTTjll3GVcTznlFC7jChwD59yUP2f23TPl74C5gB4IAHNWpVJRsVhUuVzWoUOH1NbWpnw+L0mpvjTjVJdx/eM//uO4QwMAeIAeCABzVqlUUrlcVjabVXt7u7LZrMrlskqlUtyhTUtHR4eeeuqpcXcCfuqpp7iMKwCgJeiBADBn1Wo19fT0jFvW09OTusnGk43Vfu9736v3vve9R3wuwy0AIJmanYMjzU7bTgGBlnvVdffr5798tqm/Pevqe4/p+Scff5y+eS3XtkdzMpmMhoeHlc1mx5YNDw8rk8nEGNWxm+zLolAo6JZbbhm7v8Xll1+e+vtbAMBccaQi4Kyr79XjH7loFqN5PgoItNzPf/lsUzt2M9fhP9aCA3PbZGd0Xv/610d6btrO1tfvb5GELxoAgF+YAwFgzpjsiikDAwPq6uqSbJ66uro0MDDAlVUAADgCeiAAzGm5XE65XE5nXX2vdnCmHjhmSR+rDaD16IEAAABNa/Z+CRQPQHpRQAAAAACIjCFMwDTRfQ8AAOYSeiCAaaL7HgAAzCUUEAAAAAAio4AAAAAAEBlzIAAAsWn2zvXctR4A4kMBAQCITTN3rueu9QAQL4YwAQAAAIiMHoiYzVb3vUQXPgAAAKaPAiJms9V9L9GFDwAAgOljCBMAAACAyCggAAAAAETGECYAAFqo2bltEpenBZAOFBAAALRQM3PbJC5PCyA9GMIEAAAAIDIKCAAAAACRUUAAAAAAiIwCAgAAAEBkTKIG5jCuFgMAAI4VBQQwh3G1GAAAcKwYwgQAAAAgMgoIAAAAAJFRQAAAAACIjDkQAAAAHmn2AhlcHANRpaaA4GoxAAAAR9fMBTK4OAaORWoKCK4Wg7jN1hkdiSIWAAAkV2oKCCBus3VGR6KIBQAAycUkagAAAACR0QMBAACOiom5AOooIAAAwFH5ODGXC7SkB9sqWSgg0HInZq7Wb9x2dXN/fNuxrkuSjn1yPQAAXKAlPdhWyUIBgZb7Re0jfMgBAAA8RQEBACnga/d90z2W9FYCQGwoIAAgBXztvm+mxzLpOQGA7yggAAAAgBik9epmFBAAvJPWBhkAMLek9epmFBAAvJPWBhkAgDTgTtQAAAAAIqOAAAAAABAZBQQAAACAyCggAAAAAERGAQEAAAAgMgoIAAAAAJFxGVcAAHBUJ2au1m/cdvWx/+Ftx7oeSTr2u64DmD0UEAAA4Kh+UfsI91cBIIkhTAAAAACOAT0QwBzW9JAEiWEJAADMURQQMZutMaXBuiQO4NComSEJEsMSAACYy1pSQJjZmyR9TFKbpE855z7SitedC2ZrTKnEAdx0UewBANKACe+YadMuIMysTdL/kfRGSSOSvmpmn3XO7ZzuawNJQrEHAH7xdRgnE94x01rRA/Fbkr7jnPuuJJnZnZLeJokCAgBaxNcDHR+xrdKDYZxAc1pRQLxE0vca/j8i6bcnPsnMrpB0hSSdfvrpGhoaOuYVNfM3e/bsmbV1NetY19VsTs2sq1lsqwDbavrrasZsdt8PDS089vU04Re1j+jWNx37uvbs2aNFixYd099c9oVRLz9Xs5UT2+qwpG+rZtflY14+5iT5mVcScmpFAWGTLHPPW+DczZJulqRzzjnHHfOwji/c29RQkKaGkDS5rqY0sa5mh8XMWl5sqzFsq+mvqxm/uHr2uu9XXHpsf9M0T7fVrH2uEp6T5GdePuYk+ZmXjzlJyc/rxCd+Q4UnmvjD/zzG9WSkFSu+1cSKJteKAmJE0ksb/t8paXcLXhcAAADwVlrnq7SigPiqpFeY2VJJ35f0R5JWteB1AQBAgjR1EPKFY/ubk48/7tjXAWBWTbuAcM4dNLMrJd2n4DKuW5xzj047MgAAkBjNTDY+6+p7m/o7AMnWkvtAOOc+L+nzrXitqXBVCwAAACB+qbkTNZdaS5em38OEd3XPRve9NLt5+bqtAAD+4ERysqSmgEB6NNtdnfSubh+7733dVgAAv3AiOVkoIAAgJXztLWJiLtB6fK4wkyggACAFfO0t8rFnD+niY2HO5wozjQICAADMSb4W5sBMo4AA4CW67wEAmBkUEAC8Q/c9AAAzhwICAAAAiEkae8wpIAAAAIAYpLXHfF6sawcAAACQKhQQAAAAACKjgAAAAAAQGQUEAAAAgMiYRA0AQIv5eHdjAKijgAAAoIW4uzEA31FAJMBsXP9X4kwVAAAApi9VBYSPXcJpvf4vAAAA5qbUFBB0CQMAAADx4ypMAAAAACKjgAAAAAAQWWqGMAEAAGDu8nEubFpRQAAAACDRmAubLAxhAgAAABAZBQQAAACAyCggAAAAAERGAQEAAAAgMgoIAAAAAJFRQAAAAACIjAICAAAAQGQUEAAAAAAio4AAAAAAEBkFBAAAAIDI2uMOAAAApJeZHfn3G6b+nXOuxdEAmA30QAAAgKY556b8qVarR/w9gHSigAAAAAAQGQUEAAAAgMgoIAAAQEtVKhV1d3ert7dX3d3dqlQqcYcEoIWYRA1MExMIAeCwSqWiYrGocrmsQ4cOqa2tTfl8XpKUy+Vijg5AK9ADAUwTEwgRNzOb8ueJDW+e8nfATCiVSiqXy8pms2pvb1c2m1W5XFapVIo7NAAtQgEBACnXbBELzIRaraaenp5xy3p6elSr1WKKCECrUUAAAICWyWQyGh4eHrdseHhYmUwmpogAtBoFBAAAaJlisah8Pq9qtaqDBw+qWq0qn8+rWCzGHRqAFmESNQAAaJn6ROlCoaBaraZMJqNSqcQEasAjFBAAAKClcrmccrmchoaGtGLFirjDAdBiDGECMGc0e7WiNF6xqFAoaMGCBcpms1qwYIEKhULcIQEAPEEPBIA540hXHvLpTGmhUNDmzZu1YcMGLVu2TDt37lRfX58kqb+/P+boAABpRw8EAHjmlltu0cqVK7VlyxZddNFF2rJli1auXKlbbrkl7tAAAB6gBwIAPLN//34NDw/r05/+9NidgP/4j/9Y+/fvjzs0IDWONnTRNky+PMn3WGk2JynZeWH20QMBAJ4xM1144YXj7gR84YUXpnIuBxAXH2/Q2GxOSc8Ls48eCADwjHNOt9xyi17+8pdr2bJl2rRpk2655RYOAgAALUEBAQCe6erq0ite8Qpdc8012r9/vzo6OvTmN79Z3/72t+MODQDgAQoIAPBMsVhUsVjUtm3bxuZA5PN5lUqluEMDAESQ9PkqFBAA4BnuBAwA6Zb0y45TQACAh7gTMABgpnAVJgAAAACR0QMBYFI+XgMdAABMHz0QACbl4zXQAQDA9FFAADOgUqmou7tbvb296u7uVqVSiTuklvA1Lx+xrQDAL0lq1xnCBLRYpVJRsVhUuVwedwlNSam+Co7PeZVKpbGrFRWLxVTnI/m7rQBgrqpUKlq3bp0WLlwo55xGR0e1bt06SfG06/RAAC1WKpVULpeVzWbV3t6ubDarcrmc+mvw+5hX/UC7v79f9913n/r7+1UsFlN/tt7HbQUAc9n69evV1tamLVu26P7779eWLVvU1tam9evXxxIPBQTQYrVaTT09PeOW9fT0qFarxRRRa/iYl68H2j5uKwCYy0ZGRnT77beP+766/fbbNTIyEks8FBBAi2UyGQ0PD49bNjw8rEwmE1NEreFjXr4eaPu4rQAAyUEBAbRYsVhUPp9XtVrVwYMHVa1Wlc/nVSwW4w5tWnzMy9cDbR+3FQDMZZ2dnbr00kvHteuXXnqpOjs7Y4mHSdRAi9UnMxUKhbGJuaVSKfWTV33Mq36gXZ9sXD/QTvsQJh+3FQDMZRs3btS6deu0Zs0aPfnkkzrjjDN08OBB3XjjjbHEQwEBzIBcLqdcLqehoSGtWLEi7nBaxre8fD7Q9m1bAcBcVv9eqp/gWrhwoa6//vrYvq8oIADMaRxoAwDSIEnfV8yBAAAPJemGQwAAv9ADASAyH2+65iNuJAcAmEkUEAAi4aA0PRrvb1Hv6i6XyyoUCmwrAMC0MYQJQCS+3nTNR7VaTSMjI+OGMI2MjKT+/hZID4bQAa2XpM8VPRAAImk8KK0PYerr6+OgNIGWLFmiQqGgF7zgBZKk0dFRFQoFLVmyJObIMBfQW5kuDE1Nh6R9riggAESyZMkSrV+/XgMDA2ON16pVqzgoTaC9e/dqz549+uAHP6hly5Zp586dWr9+vdra2uIODXMAQ+jSI2kHpZha0j5XDGECEJmZHfH/SIannnpK69ev15YtW3TRRRdpy5YtWr9+vZ566qm4Q8McUKvV1NPTM25ZT08PvZUJxNDU9Eja54oCAkAku3fv1oYNG1QoFHT++eerUChow4YN2r17d9yhYRLZbFY7duzQ9u3btWPHDmWz2bhDwhyRyWQ0PDw8btnw8LAymUxMEWEqSTsoxdSS9rmigAAQSSaTUWdn57iD0s7OTg4KEqizs1OXXHKJqtWqDh48qGq1qksuuUSdnZ1xh4Y5oFgsKp/Pj9v/8vm8isVi3KFhgqQdlGJqSftcMQcCQCT1xqs+VrbeeNHVnTwbN27U2rVrdf755+vZZ5/Vcccdp+OPP16bN2+OOzTMAfXx2IVCYWxibqlUYkx9AtGup0fSPlcUEAAiyeVyevDBB3XBBRdo//796ujo0OWXX85BQUJ1dHTo1FNP1ZNPPqmXvOQlGh0djTskzCG5XE65XG5ssqcvfLtiUdIOSnFkSfpcUUAAiKRSqejee+/Vtm3bxl2t49xzz+XLJmFKpZK2bt067mod1WqVq+AA0+DrFYuSdFCK9GAOBIBIuFpHejAxEmg92kDgsGkVEGb2h2b2qJk9Z2bntCooAMnDQWl6+DAx0sym/Hliw5uP+HtgJtAGAodNtwdih6Tfl/SlFsQCIMF8OCidK5J2tY5mOOem/KlWq0f8PTATaAOBw6ZVQDjnas65x1oVDIDk8uGgdK7I5XIqlUrj7tnhw8TISqWi7u5u9fb2qru7W5VKJe6QMIfQBgKHWSvO1pjZkKQ/d849dITnXCHpCkk6/fTTl995553TXm8Ul31hVLe+aeGsrGu2+JiT5Gdee/bs0aJFi+IOo2W2b9+uv/3bv9WTTz6pM844Q+94xzvU29sbd1gt4du2qvMlr+3bt6tcLut973ufli5dql27dumGG25QPp/3Zh+kDUw+2sD08elzFcf+l81mH3bOPX+awpG6gcPi4p8UDFWa+PO2hucMSTrnaK9V/1m+fLmbLWf23TNr65otPubknJ95VavVuEOYET7m5WNOzvmTV1dXlxscHHTOHc5pcHDQdXV1xRhVa9EGpoePefmYk3P+fK4GBgbc0qVL3eDgoHvggQfc4OCgW7p0qRsYGJjR9Up6yE1yLH/Uy7g6597QqioGONoER9sw+XLHuGZgTmMCK4C5rPEqYPVL7pbL5dguz+3FZVybvVoHZt9kVWz950gTIwHMbUxgBTCVuXAcmLSTKNO9jOvvmdmIpNdIutfM7mtNWMeGg1IA8BsTWAFMZS4cBybtJMq07kTtnPuMpM+0KBYAACZV76IvFAqq1WrKZDJeXFkKAKKon0Sp3wm9fhIlrhsZTquAAAAAADCzknYShQICAJB4lUpFxWJx7OxbW1ub8vm8JNELAWBOyOVyyuVyY5Oo4+TFJGoAgN8ar0DS3t6ubDarcrkcW/c9AMxl3hYQ3LEUAPyRtCuQAMBc5uUQJrq6AcAv9SuQZLPZsWVcxhUA4uFlDwRd3QDgFy7jCgDJ4WUPBF3dAOCXpF2BpFlHu3mVbZh8edquWQ/Ab172QCTtZhsAgOnL5XLasWOHtm/frh07dqSueJDmxg2vAPjPywKCrm4AAABgZng5hMmXrm4AAAAgabwsIKRk3WwDAAAA8IWXQ5gAAAAAzAwKCAAAAACRUUAAAAAAiIwCAgAAAEBkFBAAAAAAIqOAAAAAABCZtwVEpVJRd3e3ent71d3drUqlEndImALbKj3YVogT+x+AqGgvZpaX94GoVCoqFosql8s6dOiQ2tralM/nJYmbySUM2yo92FaIk8/7X6VSUalUGrvxabFYTH1OQJx8bi8Swzk36z/Lly93M6mrq8sNDg4655yrVqvOOecGBwddV1fXjK53tpzZd0/cIbSM79uqnpMP2Fbp5Etevu5/AwMDbunSpW5wcNA98MADbnBw0C1dutQNDAzEHVpL+LL/TeRjXj7l5Gt7UTeb20rSQ26SY3kvhzDVajX19PSMW9bT06NarRZTRJgK2yo92FaIk6/7X6lUUrlcVjabVXt7u7LZrMrlskqlUtyhAanla3uRJF4WEJlMRsPDw+OWDQ8PK5PJxBTRsTOzKX+e2PDmI/4+TXzYVnMF2wpx8nX/40AHaD1f24sk8bKAKBaLyufzqlarOnjwoKrVqvL5vIrFYtyhRTZZd1H9p1qtHvH3aeLDtpor2FaIk6/7Hwc6QOv52l4kiZeTqOsTZAqFwtiktFKpxMSZBGJbpQfbCnHydf+rH+jUJ3vWD3QYwgQ0z9f2Ikm8LCCkYOfJ5XIaGhrSihUr4g4HR8C2Sg+2FeLk4/7HgQ4wM3xsL5LE2wICAIA04EAHQNp4OQcCAAAAwMyggAAAAAAQGQUEAAAAgMgoIAAAAABE5m0BUalU1N3drd7eXnV3d6tSqcQd0rT5mBMAAECr+XjMlKScvLwKU6VSUbFYHLuudltbm/L5vCSl9tJ4PuYEAADQaj4eMyUtJy97IEqlksrlsrLZrNrb25XNZlUul1N9Yx4fcwIAAGg1H4+ZkpaTlwVErVZTT0/PuGU9PT2q1WoxRTR9PuYEAADQaj4eMyUtJy8LiEwmo+Hh4XHLhoeHlclkYopo+nzMCQAAoNV8PGZKWk5eFhDFYlH5fF7ValUHDx5UtVpVPp9XsViMO7Sm+ZgTAABAq/l4zJS0nLycRF2fTFIoFFSr1ZTJZFQqlVI7cUbyMycAAIBW8/GYKWk5eVlASMEbncvlNDQ0pBUrVsQdTkv4mBMAAECr+XjMlKScvBzCBAAAAGBmUEAAAAAAiIwCAgAAAEBkFBAAAAAAIqOAAAAAABAZBQQAAACAyCggAAAAAERGAQEAAAAgMgoIAAAAAJFRQAAAAACIjAIiRSqVirq7u9Xb26vu7m5VKpW4Q2oJX/MC0Fq+thW+5gXAX+1xB4BoKpWKisWiyuWyDh06pLa2NuXzeUlSLpeLObrm+ZoXgNbyta3wNS8AfqMHIiVKpZLK5bKy2aza29uVzWZVLpdVKpXiDm1afM0LQGv52lb4mhcAv1FApEStVlNPT8+4ZT09ParVajFF1Bq+5gWgtXxtK3zNC4DfKCBSIpPJaHh4eNyy4eFhZTKZmCJqDV/zAtBavrYVvuYFwG8UEClRLBaVz+dVrVZ18OBBVatV5fN5FYvFuEObFl/zAtBavrYVvuYFwG9Mok6J+mS6QqGgWq2mTCajUqmU+kl2vuYFoLV8bSt8zQuA3yggUiSXyymXy2loaEgrVqyIO5yW8TUvAK3la1vha14A/MUQJgAAAACRUUAAAAAAiIwCAgAAAEBkFBAAAAAAIqOAAAAAABAZBQQAAACAyCggAAAAAERGAQEAAAAgMgoIAAAAAJFRQAAAAACIjAICAAAAQGQUEAAAAAAio4AAAAAAEBkFBAAAAIDIKCAAAAAAREYBAQAAACAyCggAAAAAkVFAAAAAAIiMAgIAAABAZBQQAAAAACKjgAAAAAAQGQUEAAAAgMgoIAAAAABERgEBAAAAIDIKCAAAAACRmXNu9ldq9hNJT8zS6l4o6aeztK7Z4mNOkp95+ZiT5GdePuYk+ZmXjzlJfublY06Sn3n5mJPkZ16zmdOZzrkXTVwYSwExm8zsIefcOXHH0Uo+5iT5mZePOUl+5uVjTpKfefmYk+RnXj7mJPmZl485SX7mlYScGMIEAAAAIDIKCAAAAACRzYUC4ua4A5gBPuYk+ZmXjzlJfublY06Sn3n5mJPkZ14+5iT5mZePOUl+5hV7Tt7PgQAAAADQOnOhBwIAAABAi6SmgDCz3zMzZ2a/fpTn/ZmZndDw/8+b2SkzHuD4GI4Yq5kNmVlLZ8+b2cVmtqyVrznJOiJtg/C5n2pFPGZ2lpmtavj/OWb2v6f7ug2vd8jMvmFm3zSzr5nZueHyJWb2961aTxNxfcjM/rzFr/liM7vTzP6fme0MPxu/1sp1HGHdj5vZC2djXeH6IuVqZg/OVkzNathHHw3306vMLDVt91Qa8qr/nDXN13urmV0dPm755+cI6512HmZ2mZktmYHwWsLM9kz4/2VmdlNc8TQr/P76m4b/t5vZT8zsniZe69VmdmFrI4y87vo+t8PMPjfbxzhxM7Ni2B4+Er4Pvz3F86Y8XgiPwx5r+Nz+QauOW44S+2kN6/yhmX0/fPwzM9sZ8TXWmtkl4eNbzewPGnKatSsztc/WilogJ2lY0h9J+tARnvdnkv5W0l5Jcs7F8QGPGmsrXSzpHkmRdkApaDydcwePYR2R83LO/ckxvO6RnCVplaSB8HUfkvRQi15bkn7pnHu1JJnZ+ZI+LOl1zrndkv6gFSswszbn3KFWvNY0YjBJn5F0m3Puj8Jlr5Z0uqT/iDG0louSa32bOOfOjS3Q6Br30V9R8Fk4WdK1jU9q4vMct7G8WsE591lJn23V6x2DVuRxmaQdknZPO5oEmrhvRt1XZ2CfHpXUbWbHO+d+KemNkr7f5Gu9WtI5kj4f9Q9amE9jm3CbpP9PUqkFr5t4ZvYaSW+W9F+dc/vDE1PzJ3tuhOOF1eFz6mb8pKFz7j8V7Dsysw9J2uOc+2h44uGohWy4D21uRSzTPTZJxVksM1sk6bWS8goOXmVmbWb2UTP7VliFFszsPZKWSKqaWTV83tiZz/DM3Y7w58/CZWeZWc3Mbgkr2vvN7PgWx3p8eDb0ETPbKun4cPm7zGxjw99eZmb94eN3mNlXwsr0k2bWFi7fY2al8Ezkv5rZ6RacNX+rpBvC57+ssRI1sxea2eMN67jLzD4n6X4zW2hmW8zsq2b2dTN72zHktSJcz9+b2b+b2R3hwZsmrH+PmW0ws4fN7J/M7LfC33/XzN7asB3+2YJegLGeAEkfkfS7YV7/I1znPeHfnGpmd4fv67+a2X8Jl38ozKm+jvdE3HwnSXq6IZ4d4eMFZvbpcF/7upllw+UnmNnf1bermf3bhJz/wsz+TdJrzOyD4Xu8w8xunvA+/bWZPRj+7rca4lk2MQcz+0szW9ewXUoR88tKerax4XHOfUPSsJndEK77W2a2smHbfjHM7z/M7CNmtjrcJ79lZi8Ln/ciM/uHMLevmtlrw+WnWfBZ+rqZfVJSPd9m4z8WU+XaZmZVMxuQ9K1w/Xtake9scc79WNIVkq60wMTP8yIz2x5+hr5l4ec53J//3YIzbDvCz+obzOzLZvbt+n4XfjYfDLfbg2b2ytnKrQWxP++suAVt4dca/v8KM3s4xjye911jwdnDcyTdYUE7d/wR2ov3WNCj9ogF3ynzwvfgReHv55nZd2x2e/vODPN9JPz3jHD5rWa2yYLv4g2T/P/VFrTbj5jZZ8zsBeHfDZnZ9Wb2RUnrjrDqZm2TdFH4OCepEq53yvfSzP4w3BbfNLMvmdl8SX8haWW4zVbaFN+lk3xG/8YavmfD/fmt08jnXyS9JHytI72n/yuMvWZmv2lm/xjm+1cNsdxtwff0o2Z2RcPy5x13hMtPD9fzzfCn3oM/6fFLiyyW9FPn3H5Jcs791Dm3O8zpwTCOr5jZidZwvBCFzfIZ/Em0TWwfGuIa+0xYhB5WMzvPzP7FgnboLguO4erHxB80s2FJfzitaJ1zif+R9A5J5fDxg5L+q6R3SfoHSe3h8lPDfx+X9MKGv31cwR37lis4aFgoaZGkRyWdreAM90FJrw6f/3eS3tHiWK+StCVc9l/C9Z0j6UWSvtPwt9sk9UjKSPqcpOPC5R+XdEn42El6S/h4o6QPhI9vlfQHDa81JOmc8PELJT0ePr5M0kjD+3V9PV9Jpyg4Q7swYl4rJP1cUqeCYvRfJPVMsn4n6YLw8Wck3S/pOEmvkvSNcPkJkhaEj18h6aHw8QpJ9zTEMfZ/Sf2Srg0fv77htT4UxtgR5v6f9fdykrwOSfqGpH8Pc1keLj9L0o7w8XslfTp8/OuSnpS0QNKfS/pkuLy7vl0bcn57w3pObXj8Nw3bcEjSLeHj/9awzklzCOP6WviceZL+n6TTIuyX75H0vyZZ/t8lPSCpTcEZ+icVNNArJP0sfNyh4CzddeHfrJP01+HjgYZtfoakWvj4f0v6YPj4ovD9eGGz8R/jZ3CqXFcoOAO5tGHZnobfNZ3vTP7UY5yw7Olwe12m8Z/ndkknNXzuv6OgeDsr3D9/I3zfH5a0Jfzd2yTdHf7NSTrcpr5B0j/MYF71z943FLQL0439Mkk3NXx+/jx8XNXh9v16SYWY86jHMvZdo4b2Mvz/VO3Fbkkd4eNTwn+vlfRn4ePzZmKbTcjxGwraifp7/TlJl4aP1zRsj1sVnFFtm+L/jyjo7ZWCg/H6Z2xI0sdn6rOk4Dv47xW04d/Q+O+USd9LBccOL5nwvo/tbw371vO+S/X8z+jrGt6jkyXtUviZO5Y8wn/bJN0l6U0R3tMN4eN14X5Ub+tGFLbBDTEer6BHrL58quOOrQ3vV1uYz5THLy3ahovC7fYf4Wu/TkEPxHcl/Wb4nJMUfA7Htu0krzMk6TEd3qdP04TP4Uz/aHw7dZaO3D58fIq/u1XhsV89fgXtzpcUHstJ6tPh7+PHJa1vRfxpGcKUk/TX4eM7w///qqTNLuwOdM49dZTX6JH0GefcqCSZ2T9K+l0FXd67XHCGUgq+nM5qcayvUHBAJefcI2b2SPj4JxacXf4dSd+W9EpJX1bQHblc0lfDE0/HS/px+JoHdLib62EFXbDH6oGG9+s8SW9tqGYXKDwwipDXvZK+4pwbkSQz+4aC9254wt8ekPSF8PG3JO13zj1rZt/S4ff6OEk3WTDU5JCkKGPzexQcAMs5N2jBWe+Tw9/d64IzFPvN7McKDrZGJnmNxq7g10i63cy6J1lPf7iefzezJ8L4eiR9LFy+o75dQ4cUFLh1WTNbr6BQOlVBAfu58HeV8DW+ZGYn2eHxrM/LwTn3uJn9p5mdHeb0dRd0iTarR1LFBd2YPwrPcPympGckfdU594Pwvfl/Cgo/KdiG2fDxGxT0lNRf7yQzO1FBMfT7YV73mtnT4eNWx3+svuKc2zXF75rO1zn3i5kKeArW8Ljx82ySrjez/ybpOQVnJk8Pf7fLOVfveXlU0nbnnJvwOTxZ0m1m9goFBw3HzWAO44b+mNlx04x9Kp+S9MdmdpWklZJ+6yjPP1bHmsc3wsdH+q6Zqr14REFPxd2S7g6fu0XS/1XQPq+R9Onpp/Q8E3O8TMGBiiS9RuFnXUGxs7Hh7+5y44dI3OWcOxS206c4574YLr9NwYFw3dYWxj5O+B18loLvsInDj6Z6L78s6VYz+ztJ/zjFS0/1XSo1fEadc180s/9jwXDE31dQpBzrsKbjG75vH5b0QIT3tD6871uSHm1o674r6aUKTlK9x8x+L3zeSxUcu/ynpj7ueL2kS8K8Dkn6uZm9U1Mfv0ybc26PmS1XcPyWVbCvlCT9wDn31fA5z4S5He3lxg1hivD8mXak9uFYPhO/I2mZpC+HOc1XcIK3mdeaUuILCDM7TcFO2m1mTkGV6xS8ue5YXuoIv9vf8PiQwiFGx+oIsX5dU8e6VdLbFZwB/0z4pWgKxm+/f5LnP+vCMjKMdapteFCHh6gtmPC70cawJf1359xjTeT1eT3/vZssnsaYn6v/jXPuOTOrP/9/SPqRgl6JeZL2TRXPhNgnqq8nSlzj/9C5f7Gg6/9FEdZzpOWStK/+xWlmCxScKTnHOfc9C8Y9Nm6TifvG0XL4lIKzWi9W8IUXxaOafE5H1M/Fcw3/f64hlnmSXuOC8cSHXzRotKba55uJ/1hMlas0ft+fqOl8Z5OZ/aqC/aH+pdyY02oF++/ysEh/XIf3tSj5/aWkqnPu98KDrKFWx38E0419Kv+g4MzyoKSHZ6FgjZrHpN81R2kvLlJQnL9V0v80s67wOT8ys9dL+u1w/XFq/NxP/Lwd6fPXzPOa9VlJH1Vwhvq0+sKp3kvn3FoLJupeJOkb4YmuiSb9Lg3/bmI+fxO+9h8pKFSO1S+dc68Oi4Z7FJx0vO0of9P4mZn4eWo3sxUKTpC8xjm318yGdHi/i3rcIQXvw1THLy0RfrcOSRoKTyL8fzrK8aCZ3aegkH/ItW6OZqsdqX04ls+EKShac1P8viWfrzTMgfgDSbc75850zp3lnHupgi6/r0laWz8ANbNTw+f/QtKJk7zOlyRdbMG49YWSfk/SP89irKvDOLsVdKHW/aOCCdA5Ha4Kt0v6g/AMRX2s/5lHWffEvB9XcBagHtdU7pNUCIsWhWeGo+bVc5SYjsXJCs4gPCfpnQqKFGnq7SkF27T+vq5QMC7ymWYDsODqUm0KzrhMtZ5fU3BW6TEFPS1vD5cvUzDEYjL1Rvin4TjEidujPu+gR9LPnXM/P0qon5H0JgU9Bfcd5bl1g5I6zOzy+gIz+00FQ2FWWjCn6EUKDk6+EvE1peAs/ZUNr/nq8GHje3aBpBdMM/5jMVWur2vBa0+V76wIt9FmBUMnJvvCPFnSj8MD16yko7Ubk/19fVLpZU0H2pzpxj4p59w+BfvZJzQzZ+cnaiaPxnZu0vbCgitvvdQ5V5W0XsEwmUXhcz+l4OIhf+dm/4INDyqcF6fgMz+xB/p5wjbuaTP73XDROyV98Qh/0mpbJP1FvVdrgue9l2b2MufcvznnPijppwrOzk/8boryXVp3q4ILvsg592izSYTv43sUDKfdq+m9pydLejosHn5dwVnso9muYDi5wu+Qk9Tc8UtkZvbKsIe07tUKRkwsCdt5WTD/YVyR45w73zn36gQXD630r5Jea2Yvl8bma7b8iotpKCByCg44Gv2DgsnST0p6xMy+qeBKPVJwd75tFk6irnPOfU3Bh/Yrkv5N0qecc1+fpVjPkrTIgiEu69VwgOace1rBlZPOdM59JVy2U9IHFEy4ekTBGPXFR1n3nZLeZ8HkrZcpOLvyLgsuU3mkCXV/qWCYwiMWTBr+y2PIa9Ukz23WxyVdamb/qmB4UL1CfkTSQQsmRv2PCX/zIUnnhO/RRyRd2sR6j7fwkmoKCrhLJ/kC/riCyU3fCp9zWTi06OOSXhSuvy+M9XkH/865n0m6RUHX8d2SvjrhKU+H22mzgknqR+ScO6BgXHfkg4XwYPP3JL3RgkubPqrg/RsI4/6mggPv9c65H0Z5zdB7FG4DCy5BtzZcfp2k/2bBBNbzFHxWm47/WBwh11Zc4WaqfGdSfR99VNI/KShirpviuXeE8T2k4GDu349xXRslfdjMvqzDRfxsmW7sR3ttp8PD0mZSM3ncKmlz2A7t1+TtRZukvw3boa8rmOfzs/B3n1VQTMxGgTTRexQMEXtEwUHruoh/d6mCC388ouAg8C9mJrznc86NOOc+NsWvJ3svb7BgQvwOBSdHvqmgDVsWfjZXKtp3aX39P1Jw0Dvt7RUex3xTQRE3nff0Cwp6Ih5REPu/RvibdQqG231LwaiQriaPX47FIgXDLHeGr79M0gcVnIjrD48HH9DzR17MGc65nyg4AVQJ36N/VTB/s6W4EzXQJAuuLHGcc25fWLRtl/Rr4QFy1NcYUjAZKvKlacMzkV+T9IfOuW8fY9ixS3v8SB8LxqWf7Jz7n3HHMhMsuHLM/3LO/e5Rn4wjmo330oJ7VX1LwaVIj9bjDCRS4udAAAl2goJLBh+nYMzhu46leGhGOFTqHgXzZVJ38J32+JE+ZvYZSS9TMI/LOxbcPO9din/uQ+rNxntpZm9QMIRqE8UD0oweCAAAAACRpWEOBAAAAICEoIAAAAAAEBkFBAAAAIDIKCAAYA4ys7PM7JfhpUMTw8yqZrYnvBoOACCBKCAAYO76f865V8/Ui4eXOj4mzrmspMiXNQYAzD4KCACAzOx/mtm/m9kDZlYJ750gM3uZmX3BzB42s38O71IrM7vVzP63mT1oZt81s/odk1eEvQgDkr4V3qH2BjP7angDvj8Nn7fYzL4U3ohrR8MddAEACcd9IABgjguHC/13SWcr+F74moI7y0rSzZLWOue+bWa/reAO7PV7KiyW1KPgLqeflfT34fLfktTtnNtlZldI+rlz7jfNrEPSl83sfkm/L+k+51wp7Kk4YcYTBQC0BAUEAKBH0v91zv1Skszsc+G/iySdK+kuM6s/t6Ph7+52zj0naaeZnd6w/CvOuV3h4/Mk/Zd6D4WkkyW9QtJXJW0Jb8R4t3PuG61PCwAwEyggAAA2xfJ5kn52hHkS+6d4jdEJywvOufuet1Kz/ybpIkl/Y2Y3OOdujx4yACAuzIEAAAxLeouZLQh7HS6SJOfcM5J2mdkfSpIFXnWMr32fpHeFPQ0ys18zs4VmdqakHzvnbpFUlvRfW5UMAGBm0QMBAHOcc+6rZvZZSd+U9ISCqyD9PPz1akmfMLMPSDpO0p3h86L6lKSzJH3NgnFQP5F0saQVkt5nZs9K2iPpkmknAgCYFeacizsGAMAsM7OzJN3jnOsO/7/IObfHzE6Q9CVJVzjnvhZTbEOS/tw5x+VcASCBGMIEAHPTIUknN9xI7ubw8dck/UOMxUNV0q9KejaO9QMAjo4eCAAAAACR0QMBAAAAIDIKCAAAAACRUUAAAAAAiIwCAgAAAEBkFBAAAAAAIqOAAAAAABDZ/w9rqFV4xtxhhwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 936x864 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Now looking at profit distribution per genre\n",
    "#Make dataframe with just genre and profit\n",
    "\n",
    "genre_profit=genre_df_dev.loc[:,['genres','profit']]\n",
    "\n",
    "# get frequencies\n",
    "counts1=genre_profit.groupby('genres').count().reset_index('genres')\n",
    "\n",
    "#set the number we consider to be 'big' in terms of films made so that we can plot genres\n",
    "n=50 \n",
    "\n",
    "#Making the index by frequencies\n",
    "bigcounts1=counts1[counts1.profit>n]['genres']\n",
    "biggenres1_df = genre_profit[genre_profit.genres.isin(bigcounts1)]\n",
    "biggenres1_df.boxplot(by='genres',figsize=(13,12))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Looking at number of films\n",
    "\n",
    "#Filtering through for budget less than 1.5 million\n",
    "\n",
    "genre_df_dev2 = genre_df_dev[genre_df_dev.budget<=1500000]\n",
    "genre_df_dev3 = (pd.DataFrame(genre_df_dev2.groupby('genres').movie_title.nunique())).sort_values('movie_title', ascending=False )\n",
    "\n",
    "#Looking at films with budget less than 1.5 million and an IMDb score of more than 7\n",
    "genre_df_dev4=genre_df_dev2[genre_df_dev2['imdb_score']>=7]\n",
    "genre_df_dev5 = (pd.DataFrame(genre_df_dev4.groupby('genres').movie_title.nunique())).sort_values('movie_title', ascending=False )\n",
    "\n",
    "genre_df_dev5[['movie_title']].plot.barh(stacked=True, title = 'Genres with a budget less than $1.5 million and IMDb score above 7', figsize=(8, 8),\n",
    "                                        color='darkorange');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "Looking at the table above, the most films made within our bracket are **Drama** films. We are interested in profit, so let's look more closely at that: \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "Below, is a graph showing 'genres by profit' of all USA films that were made after 2000. The **most profitable films are animation** films and **least are westerns**.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Let's look at the most profitable film per genre\n",
    "#Animation is the most profitable \n",
    "#Showing this in a bar chart\n",
    "\n",
    "genre_df_dev_prof=genre_df_dev.groupby(['genres']).mean()\n",
    "genre_df_dev_prof.sort_values('profit', ascending=False, inplace = True )\n",
    "genre_df_dev_prof[['profit']].plot.barh(stacked=True, title = 'Genres - by profit', figsize=(12, 10)\n",
    "                                       ,  color='darkcyan');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "What about films that are in our budget? And films that have a high IMDb score (above 7)?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Grouping by genres\n",
    "genre_df_dev6=genre_df_dev4.groupby(['genres']).mean()\n",
    "\n",
    "#Sorting values by profit\n",
    "genre_df_dev6.sort_values('profit', ascending=False, inplace = True )\n",
    "genre_df_dev6[['profit']].plot.barh(stacked=True, title = 'Genres with budget below $1.5 million and IMDb score above 7 - by profit', figsize=(12, 8),\n",
    "                                    color='darkcyan');\n",
    "\n",
    "#Here we can see that Mystery isthe most profitable film that has a budget of less than 1.5million dollars and IMDb score of above 7."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "Looking at the table above, the most profitable movies, with a **budget of below $1.5million** and an **IMDb score of above 7** are in the genres **Mystery**, **Comedy**  and **Crime**.\n",
    "\n",
    "As SussexBudgetProductions is interested in the most profitable and not necessarily the highest IMDb score, I broadened the data set to look only into the most profitable film that has a **budget of less than $1.5million**:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Here we can see that Horror is the most profitable film that has a budget of less than 1.5million dollars.\n",
    "\n",
    "genre_df_dev7=genre_df_dev2.groupby(['genres']).mean()\n",
    "genre_df_dev7.sort_values('profit', ascending=False, inplace = True )\n",
    "genre_df_dev7[['profit']].plot.barh(stacked=True, title = 'Genres with a budget of less than $1.5million - by profit', figsize=(12, 8),\n",
    "                                    color='darkcyan');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**War** and **Music** make a negative profit, so we will avoid these two genres. The top profiting genres are **Horror** & **Mystery**\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "scrolled": true
   },
   "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>movie_title</th>\n",
       "      <th>title_year</th>\n",
       "      <th>director_name</th>\n",
       "      <th>gross</th>\n",
       "      <th>budget</th>\n",
       "      <th>profit</th>\n",
       "      <th>country</th>\n",
       "      <th>language</th>\n",
       "      <th>imdb_score</th>\n",
       "      <th>content_rating</th>\n",
       "      <th>...</th>\n",
       "      <th>num_critic_for_reviews</th>\n",
       "      <th>movie_facebook_likes</th>\n",
       "      <th>color</th>\n",
       "      <th>plot_keywords</th>\n",
       "      <th>movie_imdb_link</th>\n",
       "      <th>aspect_ratio</th>\n",
       "      <th>facenumber_in_poster</th>\n",
       "      <th>cast_total_facebook_likes</th>\n",
       "      <th>num_voted_users</th>\n",
       "      <th>genres</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4376</th>\n",
       "      <td>May</td>\n",
       "      <td>2002.0</td>\n",
       "      <td>Lucky McKee</td>\n",
       "      <td>145540.0</td>\n",
       "      <td>500000.0</td>\n",
       "      <td>-354460.0</td>\n",
       "      <td>USA</td>\n",
       "      <td>English</td>\n",
       "      <td>6.7</td>\n",
       "      <td>R</td>\n",
       "      <td>...</td>\n",
       "      <td>114.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Color</td>\n",
       "      <td>case|doll|dry humor|friend|love</td>\n",
       "      <td>http://www.imdb.com/title/tt0303361/?ref_=fn_t...</td>\n",
       "      <td>1.9</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2489</td>\n",
       "      <td>26773</td>\n",
       "      <td>Horror</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4423</th>\n",
       "      <td>Session 9</td>\n",
       "      <td>2001.0</td>\n",
       "      <td>Brad Anderson</td>\n",
       "      <td>373967.0</td>\n",
       "      <td>1500000.0</td>\n",
       "      <td>-1126033.0</td>\n",
       "      <td>USA</td>\n",
       "      <td>English</td>\n",
       "      <td>6.5</td>\n",
       "      <td>R</td>\n",
       "      <td>...</td>\n",
       "      <td>127.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Color</td>\n",
       "      <td>abandoned asylum|abandoned hospital|asbestos|l...</td>\n",
       "      <td>http://www.imdb.com/title/tt0261983/?ref_=fn_t...</td>\n",
       "      <td>2.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>469</td>\n",
       "      <td>43839</td>\n",
       "      <td>Horror</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4423</th>\n",
       "      <td>Session 9</td>\n",
       "      <td>2001.0</td>\n",
       "      <td>Brad Anderson</td>\n",
       "      <td>373967.0</td>\n",
       "      <td>1500000.0</td>\n",
       "      <td>-1126033.0</td>\n",
       "      <td>USA</td>\n",
       "      <td>English</td>\n",
       "      <td>6.5</td>\n",
       "      <td>R</td>\n",
       "      <td>...</td>\n",
       "      <td>127.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Color</td>\n",
       "      <td>abandoned asylum|abandoned hospital|asbestos|l...</td>\n",
       "      <td>http://www.imdb.com/title/tt0261983/?ref_=fn_t...</td>\n",
       "      <td>2.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>469</td>\n",
       "      <td>43839</td>\n",
       "      <td>Mystery</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4486</th>\n",
       "      <td>Super Troopers</td>\n",
       "      <td>2001.0</td>\n",
       "      <td>Jay Chandrasekhar</td>\n",
       "      <td>18488314.0</td>\n",
       "      <td>1200000.0</td>\n",
       "      <td>17288314.0</td>\n",
       "      <td>USA</td>\n",
       "      <td>English</td>\n",
       "      <td>7.1</td>\n",
       "      <td>R</td>\n",
       "      <td>...</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Color</td>\n",
       "      <td>drugs|highway|police|state trooper|vermont</td>\n",
       "      <td>http://www.imdb.com/title/tt0247745/?ref_=fn_t...</td>\n",
       "      <td>1.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2893</td>\n",
       "      <td>76151</td>\n",
       "      <td>Mystery</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4541</th>\n",
       "      <td>Cry_Wolf</td>\n",
       "      <td>2005.0</td>\n",
       "      <td>Jeff Wadlow</td>\n",
       "      <td>10042266.0</td>\n",
       "      <td>1000000.0</td>\n",
       "      <td>9042266.0</td>\n",
       "      <td>USA</td>\n",
       "      <td>English</td>\n",
       "      <td>5.9</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>...</td>\n",
       "      <td>137.0</td>\n",
       "      <td>816</td>\n",
       "      <td>Color</td>\n",
       "      <td>e mail|game|school|serial killer|student</td>\n",
       "      <td>http://www.imdb.com/title/tt0384286/?ref_=fn_t...</td>\n",
       "      <td>2.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3155</td>\n",
       "      <td>23021</td>\n",
       "      <td>Horror</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4541</th>\n",
       "      <td>Cry_Wolf</td>\n",
       "      <td>2005.0</td>\n",
       "      <td>Jeff Wadlow</td>\n",
       "      <td>10042266.0</td>\n",
       "      <td>1000000.0</td>\n",
       "      <td>9042266.0</td>\n",
       "      <td>USA</td>\n",
       "      <td>English</td>\n",
       "      <td>5.9</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>...</td>\n",
       "      <td>137.0</td>\n",
       "      <td>816</td>\n",
       "      <td>Color</td>\n",
       "      <td>e mail|game|school|serial killer|student</td>\n",
       "      <td>http://www.imdb.com/title/tt0384286/?ref_=fn_t...</td>\n",
       "      <td>2.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3155</td>\n",
       "      <td>23021</td>\n",
       "      <td>Mystery</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4545</th>\n",
       "      <td>The Devil Inside</td>\n",
       "      <td>2012.0</td>\n",
       "      <td>William Brent Bell</td>\n",
       "      <td>53245055.0</td>\n",
       "      <td>1000000.0</td>\n",
       "      <td>52245055.0</td>\n",
       "      <td>USA</td>\n",
       "      <td>English</td>\n",
       "      <td>4.2</td>\n",
       "      <td>R</td>\n",
       "      <td>...</td>\n",
       "      <td>225.0</td>\n",
       "      <td>12000</td>\n",
       "      <td>Color</td>\n",
       "      <td>critically bashed|demonic possession|exorcism|...</td>\n",
       "      <td>http://www.imdb.com/title/tt1560985/?ref_=fn_t...</td>\n",
       "      <td>1.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>988</td>\n",
       "      <td>30570</td>\n",
       "      <td>Horror</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4571</th>\n",
       "      <td>Brigham City</td>\n",
       "      <td>2001.0</td>\n",
       "      <td>Richard Dutcher</td>\n",
       "      <td>798341.0</td>\n",
       "      <td>1000000.0</td>\n",
       "      <td>-201659.0</td>\n",
       "      <td>USA</td>\n",
       "      <td>English</td>\n",
       "      <td>7.2</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>...</td>\n",
       "      <td>12.0</td>\n",
       "      <td>100</td>\n",
       "      <td>Color</td>\n",
       "      <td>fbi agent|mormon|prayer|sheriff|utah</td>\n",
       "      <td>http://www.imdb.com/title/tt0268200/?ref_=fn_t...</td>\n",
       "      <td>1.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1107</td>\n",
       "      <td>983</td>\n",
       "      <td>Mystery</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4594</th>\n",
       "      <td>The House of the Devil</td>\n",
       "      <td>2009.0</td>\n",
       "      <td>Ti West</td>\n",
       "      <td>100659.0</td>\n",
       "      <td>900000.0</td>\n",
       "      <td>-799341.0</td>\n",
       "      <td>USA</td>\n",
       "      <td>English</td>\n",
       "      <td>6.4</td>\n",
       "      <td>R</td>\n",
       "      <td>...</td>\n",
       "      <td>238.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Color</td>\n",
       "      <td>cult film|eclipse|haunted house|lunar eclipse|...</td>\n",
       "      <td>http://www.imdb.com/title/tt1172994/?ref_=fn_t...</td>\n",
       "      <td>1.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3833</td>\n",
       "      <td>30160</td>\n",
       "      <td>Horror</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4711</th>\n",
       "      <td>Arnolds Park</td>\n",
       "      <td>2007.0</td>\n",
       "      <td>Gene Teigland</td>\n",
       "      <td>23616.0</td>\n",
       "      <td>600000.0</td>\n",
       "      <td>-576384.0</td>\n",
       "      <td>USA</td>\n",
       "      <td>English</td>\n",
       "      <td>5.6</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11</td>\n",
       "      <td>Color</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://www.imdb.com/title/tt1074931/?ref_=fn_t...</td>\n",
       "      <td>1.8</td>\n",
       "      <td>4.0</td>\n",
       "      <td>85</td>\n",
       "      <td>94</td>\n",
       "      <td>Mystery</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4758</th>\n",
       "      <td>Detention of the Dead</td>\n",
       "      <td>2012.0</td>\n",
       "      <td>Alex Craig Mann</td>\n",
       "      <td>1332.0</td>\n",
       "      <td>500000.0</td>\n",
       "      <td>-498668.0</td>\n",
       "      <td>USA</td>\n",
       "      <td>English</td>\n",
       "      <td>4.6</td>\n",
       "      <td>Not Rated</td>\n",
       "      <td>...</td>\n",
       "      <td>29.0</td>\n",
       "      <td>898</td>\n",
       "      <td>Color</td>\n",
       "      <td>based on play|blood|independent film|teenager|...</td>\n",
       "      <td>http://www.imdb.com/title/tt1865346/?ref_=fn_t...</td>\n",
       "      <td>2.4</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2251</td>\n",
       "      <td>2038</td>\n",
       "      <td>Horror</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4956</th>\n",
       "      <td>The Gallows</td>\n",
       "      <td>2015.0</td>\n",
       "      <td>Travis Cluff</td>\n",
       "      <td>22757819.0</td>\n",
       "      <td>100000.0</td>\n",
       "      <td>22657819.0</td>\n",
       "      <td>USA</td>\n",
       "      <td>English</td>\n",
       "      <td>4.2</td>\n",
       "      <td>R</td>\n",
       "      <td>...</td>\n",
       "      <td>159.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Color</td>\n",
       "      <td>breaking and entering|gallows|hanging|high sch...</td>\n",
       "      <td>http://www.imdb.com/title/tt2309260/?ref_=fn_t...</td>\n",
       "      <td>1.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>276</td>\n",
       "      <td>13521</td>\n",
       "      <td>Horror</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4964</th>\n",
       "      <td>Cheap Thrills</td>\n",
       "      <td>2013.0</td>\n",
       "      <td>E.L. Katz</td>\n",
       "      <td>59379.0</td>\n",
       "      <td>200000.0</td>\n",
       "      <td>-140621.0</td>\n",
       "      <td>USA</td>\n",
       "      <td>English</td>\n",
       "      <td>6.8</td>\n",
       "      <td>Not Rated</td>\n",
       "      <td>...</td>\n",
       "      <td>193.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Color</td>\n",
       "      <td>cocaine|extramarital affair|sex|shooting|violence</td>\n",
       "      <td>http://www.imdb.com/title/tt2389182/?ref_=fn_t...</td>\n",
       "      <td>2.4</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4729</td>\n",
       "      <td>12796</td>\n",
       "      <td>Horror</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>13 rows × 28 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                  movie_title  title_year       director_name      gross  \\\n",
       "4376                     May       2002.0         Lucky McKee   145540.0   \n",
       "4423               Session 9       2001.0       Brad Anderson   373967.0   \n",
       "4423               Session 9       2001.0       Brad Anderson   373967.0   \n",
       "4486          Super Troopers       2001.0   Jay Chandrasekhar 18488314.0   \n",
       "4541                Cry_Wolf       2005.0         Jeff Wadlow 10042266.0   \n",
       "4541                Cry_Wolf       2005.0         Jeff Wadlow 10042266.0   \n",
       "4545        The Devil Inside       2012.0  William Brent Bell 53245055.0   \n",
       "4571            Brigham City       2001.0     Richard Dutcher   798341.0   \n",
       "4594  The House of the Devil       2009.0             Ti West   100659.0   \n",
       "4711            Arnolds Park       2007.0       Gene Teigland    23616.0   \n",
       "4758   Detention of the Dead       2012.0     Alex Craig Mann     1332.0   \n",
       "4956             The Gallows       2015.0        Travis Cluff 22757819.0   \n",
       "4964           Cheap Thrills       2013.0           E.L. Katz    59379.0   \n",
       "\n",
       "        budget     profit country language  imdb_score content_rating  ...  \\\n",
       "4376  500000.0  -354460.0     USA  English         6.7              R  ...   \n",
       "4423 1500000.0 -1126033.0     USA  English         6.5              R  ...   \n",
       "4423 1500000.0 -1126033.0     USA  English         6.5              R  ...   \n",
       "4486 1200000.0 17288314.0     USA  English         7.1              R  ...   \n",
       "4541 1000000.0  9042266.0     USA  English         5.9          PG-13  ...   \n",
       "4541 1000000.0  9042266.0     USA  English         5.9          PG-13  ...   \n",
       "4545 1000000.0 52245055.0     USA  English         4.2              R  ...   \n",
       "4571 1000000.0  -201659.0     USA  English         7.2          PG-13  ...   \n",
       "4594  900000.0  -799341.0     USA  English         6.4              R  ...   \n",
       "4711  600000.0  -576384.0     USA  English         5.6          PG-13  ...   \n",
       "4758  500000.0  -498668.0     USA  English         4.6      Not Rated  ...   \n",
       "4956  100000.0 22657819.0     USA  English         4.2              R  ...   \n",
       "4964  200000.0  -140621.0     USA  English         6.8      Not Rated  ...   \n",
       "\n",
       "      num_critic_for_reviews  movie_facebook_likes  color  \\\n",
       "4376                   114.0                     0  Color   \n",
       "4423                   127.0                     0  Color   \n",
       "4423                   127.0                     0  Color   \n",
       "4486                   100.0                     0  Color   \n",
       "4541                   137.0                   816  Color   \n",
       "4541                   137.0                   816  Color   \n",
       "4545                   225.0                 12000  Color   \n",
       "4571                    12.0                   100  Color   \n",
       "4594                   238.0                     0  Color   \n",
       "4711                     NaN                    11  Color   \n",
       "4758                    29.0                   898  Color   \n",
       "4956                   159.0                     0  Color   \n",
       "4964                   193.0                     0  Color   \n",
       "\n",
       "                                          plot_keywords  \\\n",
       "4376                    case|doll|dry humor|friend|love   \n",
       "4423  abandoned asylum|abandoned hospital|asbestos|l...   \n",
       "4423  abandoned asylum|abandoned hospital|asbestos|l...   \n",
       "4486         drugs|highway|police|state trooper|vermont   \n",
       "4541           e mail|game|school|serial killer|student   \n",
       "4541           e mail|game|school|serial killer|student   \n",
       "4545  critically bashed|demonic possession|exorcism|...   \n",
       "4571               fbi agent|mormon|prayer|sheriff|utah   \n",
       "4594  cult film|eclipse|haunted house|lunar eclipse|...   \n",
       "4711                                                NaN   \n",
       "4758  based on play|blood|independent film|teenager|...   \n",
       "4956  breaking and entering|gallows|hanging|high sch...   \n",
       "4964  cocaine|extramarital affair|sex|shooting|violence   \n",
       "\n",
       "                                        movie_imdb_link  aspect_ratio  \\\n",
       "4376  http://www.imdb.com/title/tt0303361/?ref_=fn_t...           1.9   \n",
       "4423  http://www.imdb.com/title/tt0261983/?ref_=fn_t...           2.4   \n",
       "4423  http://www.imdb.com/title/tt0261983/?ref_=fn_t...           2.4   \n",
       "4486  http://www.imdb.com/title/tt0247745/?ref_=fn_t...           1.9   \n",
       "4541  http://www.imdb.com/title/tt0384286/?ref_=fn_t...           2.4   \n",
       "4541  http://www.imdb.com/title/tt0384286/?ref_=fn_t...           2.4   \n",
       "4545  http://www.imdb.com/title/tt1560985/?ref_=fn_t...           1.9   \n",
       "4571  http://www.imdb.com/title/tt0268200/?ref_=fn_t...           1.9   \n",
       "4594  http://www.imdb.com/title/tt1172994/?ref_=fn_t...           1.9   \n",
       "4711  http://www.imdb.com/title/tt1074931/?ref_=fn_t...           1.8   \n",
       "4758  http://www.imdb.com/title/tt1865346/?ref_=fn_t...           2.4   \n",
       "4956  http://www.imdb.com/title/tt2309260/?ref_=fn_t...           1.9   \n",
       "4964  http://www.imdb.com/title/tt2389182/?ref_=fn_t...           2.4   \n",
       "\n",
       "     facenumber_in_poster  cast_total_facebook_likes  num_voted_users   genres  \n",
       "4376                  1.0                       2489            26773   Horror  \n",
       "4423                  0.0                        469            43839   Horror  \n",
       "4423                  0.0                        469            43839  Mystery  \n",
       "4486                  0.0                       2893            76151  Mystery  \n",
       "4541                  0.0                       3155            23021   Horror  \n",
       "4541                  0.0                       3155            23021  Mystery  \n",
       "4545                  0.0                        988            30570   Horror  \n",
       "4571                  0.0                       1107              983  Mystery  \n",
       "4594                  0.0                       3833            30160   Horror  \n",
       "4711                  4.0                         85               94  Mystery  \n",
       "4758                  6.0                       2251             2038   Horror  \n",
       "4956                  0.0                        276            13521   Horror  \n",
       "4964                  3.0                       4729            12796   Horror  \n",
       "\n",
       "[13 rows x 28 columns]"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Looking closer at horror and mystery films\n",
    "\n",
    "genre_df_dev2[(genre_df_dev2.genres=='Horror')|(genre_df_dev2.genres=='Mystery')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "title_year                     2006.7\n",
       "gross                       3785057.2\n",
       "budget                       662829.2\n",
       "profit                      3122228.0\n",
       "imdb_score                        6.4\n",
       "duration                         93.1\n",
       "director_facebook_likes          86.7\n",
       "actor_1_facebook_likes         5565.7\n",
       "actor_2_facebook_likes          369.0\n",
       "actor_3_facebook_likes          241.7\n",
       "num_critic_for_reviews           80.2\n",
       "movie_facebook_likes           1362.4\n",
       "aspect_ratio                      2.2\n",
       "facenumber_in_poster              1.0\n",
       "cast_total_facebook_likes      6593.3\n",
       "num_voted_users               16395.6\n",
       "dtype: float64"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Looking at the averages\n",
    "#Only looking at the dev set with budget less than $1,500,000\n",
    "\n",
    "df_dev_budget = df_dev[df_dev.budget<=1500000]\n",
    "\n",
    "df_dev_budget.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The mean profit for movies that contain the genre Horror, Mystery and Animation: $7872959.928571428\n",
      "The mean profit for all genres: $3122228.0\n"
     ]
    }
   ],
   "source": [
    "#I used out data set `genre_df_dev2` as it has split the genres and only showing budget of less than 1.5million.\n",
    "#We need to group all movies containing genre Horror, Mystery and Animation in one group, this will be in a new data frame\n",
    "\n",
    "#hma_df is grouped horror, mystery and animation data frame\n",
    "\n",
    "hma_df_dev = genre_df_dev2.loc[(genre_df_dev2.genres=='Horror')|(genre_df_dev2.genres=='Mystery')|(genre_df_dev2.genres=='Animation')]\n",
    "print('The mean profit for movies that contain the genre Horror, Mystery and Animation: $'+str(hma_df_dev.profit.mean()))\n",
    "print('The mean profit for all genres: $'+str(df_dev_budget.profit.mean()))\n",
    "\n",
    "#We will be comparing this against the mean of the average movie (budget <1.5million) profit $4,380,365\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[<AxesSubplot:title={'center':'Animation'}>,\n",
       "        <AxesSubplot:title={'center':'Horror'}>],\n",
       "       [<AxesSubplot:title={'center':'Mystery'}>, <AxesSubplot:>]],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x360 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Showing our profits by histograms per genre\n",
    "\n",
    "hma_df_dev.hist(column='profit', by='genres', figsize=(12,5), bins=60)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The mean profit for movies that contain the genre Horror: $10128252.125\n",
      "The mean profit for all genres: $3122228.0\n"
     ]
    }
   ],
   "source": [
    "#Let's look more specifically at horror\n",
    "\n",
    "#We need to group all movies containing genre Horror\n",
    "\n",
    "#h_df_dev is grouped horror data frame\n",
    "\n",
    "#just selecting horro dataframe\n",
    "h_df_dev = genre_df_dev2.loc[(genre_df_dev2.genres=='Horror')]\n",
    "\n",
    "#getting the mean profit for the grouped horror data frame with budget less that 1.5mill\n",
    "print('The mean profit for movies that contain the genre Horror: $'+str(h_df_dev.profit.mean()))\n",
    "\n",
    "#getting the mean profit for the development data frame with budget less that 1.5mill\n",
    "print('The mean profit for all genres: $'+str(df_dev_budget.profit.mean()))\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***\n",
    "\n",
    "## Part 4: Hypothesis test\n",
    "\n",
    "For our hypothesis testing, we will use the `dev_test` data frame.\n",
    "\n",
    "\n",
    "**Our 2 Hypotheses:** \n",
    "\n",
    "> 1. ***If*** horror films are related to higher profit, ***then*** movies in this genre will have a higher profit than average.\n",
    "\n",
    "> 2. ***If*** more expensive films are related to higher profit, ***then*** movies that cost more than $750,000 will have a higher profit than average.\n",
    "\n",
    "<div class=\"alert alert-block alert-info\">\n",
    "<b>Note:</b> I am taking the average across the whole, unsplit dataframe i.e. all films with budget less than \\$1,500,000 (made after 2000 in the USA). \n",
    "This is \\$4,380,365. </div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "### 4.1 Our first testable hypothesis\n",
    "\n",
    "***If*** horror films are related to higher profit, ***then*** movies in this genre will have a higher profit than average (\\\\$4,380,365).\n",
    "\n",
    "In order to test this hypothesis, we will need to conduct an upper-tailed test. This is because we are hypothesising that there is an increase in profit when horror films are made.\n",
    "\n",
    "***\n",
    "\n",
    "> $H_0: μ = μ_0$ Our null hypothesis, that there is no change.\n",
    "\n",
    "> $H_1: μ > μ_0$ The research hypothesis, that **horror** films make higher profit\n",
    "\n",
    "$α =0.05$\n",
    "\n",
    "$μ_0 = $ $4,380,365 $  This is the average profit of films with budget less than $1.5million\n",
    "\n",
    "***\n",
    "The significance level ($α$) is the probability that we will reject the null hypothesis, assuming its true. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Below I will be looking at doing a one sample z-test on the group that contains the movies with horror in the genre compared with average."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1064, 28)"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#What is the size of our test set?\n",
    "\n",
    "df_test.head()\n",
    "df_test.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Splitting up our test set, similarly to what we did in the dev set\n",
    "\n",
    "t = df_test['genres'].str.split('|').apply(Series, 1).stack()\n",
    "t.index = t.index.droplevel(-1)\n",
    "t.name = 'genres'\n",
    "\n",
    "#deleting the 'genres' column from the original dataframe\n",
    "del df_test['genres']\n",
    "\n",
    "#adding the new genres to the test data frame\n",
    "genre_df_test = df_test.join(t)\n",
    "\n",
    "#only looking at films in our budget from the split genre set \n",
    "genre_df_test2 = genre_df_test[genre_df_test.budget<=1500000]\n",
    "\n",
    "#only looking at films within our budget from the whole test set\n",
    "df_test_budget = df_test[df_test.budget<=1500000]\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "title_year                     2006.3\n",
       "gross                       6443001.9\n",
       "budget                       682743.5\n",
       "profit                      5760258.3\n",
       "imdb_score                        6.5\n",
       "duration                         93.5\n",
       "director_facebook_likes         301.7\n",
       "actor_1_facebook_likes         4181.4\n",
       "actor_2_facebook_likes          597.7\n",
       "actor_3_facebook_likes          239.0\n",
       "num_critic_for_reviews          114.1\n",
       "movie_facebook_likes           3303.9\n",
       "aspect_ratio                      2.0\n",
       "facenumber_in_poster              1.3\n",
       "cast_total_facebook_likes      5431.3\n",
       "num_voted_users               29163.8\n",
       "dtype: float64"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Test set means\n",
    "df_test_budget.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The mean profit for movies that contain the genre Horror: $29028746.0\n",
      "The mean profit for all genres in the test set: $5760258.338709678\n"
     ]
    }
   ],
   "source": [
    "#Creating a test data frame with just horror\n",
    "\n",
    "h_df_test = genre_df_test2.loc[(genre_df_test2.genres=='Horror')]\n",
    "print('The mean profit for movies that contain the genre Horror: $'+str(h_df_test.profit.mean()))\n",
    "print('The mean profit for all genres in the test set: $'+str(df_test_budget.profit.mean()))\n",
    "\n",
    "#We will be comparing this against the mean of the average movie of the whole data frame (budget <1.5million) profit $4,380,365"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mean for Horror film profit from data:  29028746.0\n",
      "one tail p value from normal:  0.012919748148091603\n"
     ]
    }
   ],
   "source": [
    "from scipy import stats\n",
    "h_genres_means=h_df_test.groupby('genres')['profit'].mean()\n",
    "h_genres_std=h_df_test.groupby('genres')['profit'].std()\n",
    "h_genres_count=h_df_test.groupby('genres')['profit'].count()\n",
    "\n",
    "#here I am calculating the p value, I am taking the mean horror film value and taking away the average\n",
    "#then diving this value by the horror film standard diviation\n",
    "\n",
    "P_G = (h_genres_means['Horror']-4380366)/(h_genres_std['Horror']/np.sqrt(h_genres_count['Horror']))\n",
    "p_value_from_normal=(1-stats.norm.cdf(P_G))\n",
    "print('Mean for Horror film profit from data: ',h_genres_means['Horror'])\n",
    "print ('one tail p value from normal: ', p_value_from_normal)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Above, I conducted a z-test that is looking at the probability that our hypothesis is wrong, i.e. the null hypothesis is true. The p-value ('probability value') is a number describing how likely it is that your data would have occurred by random chance (i.e. that the null hypothesis is true).\n",
    "\n",
    "Our p value (0.0129) is less than the significance level ($α =0.05$). This indicates strong evidence that we should reject our null hypothesis. Therefore, we reject the null hypothesis and accept our first hypothesis that it will be more profitable to make a **horror film**.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4.2 Our second testable hypothesis\n",
    "\n",
    "Should we make more than one film with our budget?\n",
    "\n",
    "So, our second hypothesis: ***If*** high budget films are related to higher profit, ***then*** movies that cost more than $750,000 will have a higher profit than average (\\\\$4,380,365).\n",
    "\n",
    "Using a similar frame to above:\n",
    "\n",
    "***\n",
    "\n",
    "> $H_0: μ = μ_0$ Our null hypothesis, that there is no change.\n",
    "\n",
    "> $H_1: μ > μ_0$ The research hypothesis, that films with a budget of more than $750,000 make higher profit\n",
    "\n",
    "$μ_0 = $ $4,380,365 $  This is the average profit of films with budget less than \\\\$1.5million\n",
    "\n",
    "$α =0.05$\n",
    "\n",
    "<div class=\"alert alert-block alert-info\">\n",
    "<b>Note:</b>\n",
    "\n",
    "- *High budget*: movies that have a budget of more than \\\\$750,000 but less than \\\\$1,500,000\n",
    "- *Low budget*: movies that have a budget of less than or equal to \\\\$750,000 </div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(62, 27)\n",
      "(26, 27)\n",
      "(36, 27)\n"
     ]
    }
   ],
   "source": [
    "#df_test_budget is already looking at only the values with budget less than 1500000\n",
    "\n",
    "df_test_higherbudget = df_test_budget[df_test_budget.budget>750000]\n",
    "df_test_lowerbudget = df_test_budget[df_test_budget.budget<=750000]\n",
    "\n",
    "#Checking the numbers add up\n",
    "print(df_test_budget.shape)\n",
    "print(df_test_higherbudget.shape)\n",
    "print(df_test_lowerbudget.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "7647977.192307692\n",
      "4396905.833333333\n"
     ]
    }
   ],
   "source": [
    "#Checking the mean of each profit\n",
    "\n",
    "print(df_test_higherbudget.profit.mean())\n",
    "print(df_test_lowerbudget.profit.mean())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mean for higher budget film profit from data:  7647977.192307692\n",
      "one tail p value from normal:  0.13766528760699703\n"
     ]
    }
   ],
   "source": [
    "#Below, I will look at what the p-value is for the second hypothesis test.\n",
    "\n",
    "from scipy import stats\n",
    "higherbudget_means=df_test_higherbudget['profit'].mean()\n",
    "higherbudget_std=df_test_higherbudget['profit'].std()\n",
    "higherbudget_movie_count=df_test_higherbudget.groupby('movie_title').count()\n",
    "\n",
    "#here I am calculating the p value, I am taking the mean horror film value and taking away the average\n",
    "#then diving this value by the horror film standard diviation\n",
    "\n",
    "P_G = (higherbudget_means-4380366)/(higherbudget_std/np.sqrt(len(higherbudget_movie_count)))\n",
    "p_value_from_normal=(1-stats.norm.cdf(P_G))\n",
    "\n",
    "#Printing our stats\n",
    "print('Mean for higher budget film profit from data: ',higherbudget_means)\n",
    "print ('one tail p value from normal: ', p_value_from_normal)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Similarly to our first testable hypothesis, I conducted a z-test that is looking at the probability that our hypothesis is wrong.\n",
    "\n",
    "Our p value (0.1377) is more than the significance level ($α =0.05$). This indicates strong evidence that we should accept our null hypothesis. Therefore, we reject our first hypothesis that it will be more profitable to make just 1 film with a higher budget. We should then look into making 2 (or more) films."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "scrolled": true
   },
   "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>movie_title</th>\n",
       "      <th>title_year</th>\n",
       "      <th>director_name</th>\n",
       "      <th>gross</th>\n",
       "      <th>budget</th>\n",
       "      <th>profit</th>\n",
       "      <th>country</th>\n",
       "      <th>language</th>\n",
       "      <th>imdb_score</th>\n",
       "      <th>content_rating</th>\n",
       "      <th>...</th>\n",
       "      <th>actor_3_facebook_likes</th>\n",
       "      <th>num_critic_for_reviews</th>\n",
       "      <th>movie_facebook_likes</th>\n",
       "      <th>color</th>\n",
       "      <th>plot_keywords</th>\n",
       "      <th>movie_imdb_link</th>\n",
       "      <th>aspect_ratio</th>\n",
       "      <th>facenumber_in_poster</th>\n",
       "      <th>cast_total_facebook_likes</th>\n",
       "      <th>num_voted_users</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4793</th>\n",
       "      <td>Paranormal Activity</td>\n",
       "      <td>2007.0</td>\n",
       "      <td>Oren Peli</td>\n",
       "      <td>107917283.0</td>\n",
       "      <td>15000.0</td>\n",
       "      <td>107902283.0</td>\n",
       "      <td>USA</td>\n",
       "      <td>English</td>\n",
       "      <td>6.3</td>\n",
       "      <td>R</td>\n",
       "      <td>...</td>\n",
       "      <td>21.0</td>\n",
       "      <td>409.0</td>\n",
       "      <td>12000</td>\n",
       "      <td>Color</td>\n",
       "      <td>dark force|entity|evil force|found footage|par...</td>\n",
       "      <td>http://www.imdb.com/title/tt1179904/?ref_=fn_t...</td>\n",
       "      <td>1.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>330</td>\n",
       "      <td>184824</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4726</th>\n",
       "      <td>Open Water</td>\n",
       "      <td>2003.0</td>\n",
       "      <td>Chris Kentis</td>\n",
       "      <td>30500882.0</td>\n",
       "      <td>500000.0</td>\n",
       "      <td>30000882.0</td>\n",
       "      <td>USA</td>\n",
       "      <td>English</td>\n",
       "      <td>5.7</td>\n",
       "      <td>R</td>\n",
       "      <td>...</td>\n",
       "      <td>7.0</td>\n",
       "      <td>235.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Color</td>\n",
       "      <td>bare chested male|female full frontal nudity|h...</td>\n",
       "      <td>http://www.imdb.com/title/tt0374102/?ref_=fn_t...</td>\n",
       "      <td>1.9</td>\n",
       "      <td>1.0</td>\n",
       "      <td>67</td>\n",
       "      <td>42256</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4730</th>\n",
       "      <td>The Station Agent</td>\n",
       "      <td>2003.0</td>\n",
       "      <td>Tom McCarthy</td>\n",
       "      <td>5739376.0</td>\n",
       "      <td>500000.0</td>\n",
       "      <td>5239376.0</td>\n",
       "      <td>USA</td>\n",
       "      <td>English</td>\n",
       "      <td>7.7</td>\n",
       "      <td>R</td>\n",
       "      <td>...</td>\n",
       "      <td>587.0</td>\n",
       "      <td>154.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Color</td>\n",
       "      <td>abandoned|depot|dwarf|newfoundland new jersey|...</td>\n",
       "      <td>http://www.imdb.com/title/tt0340377/?ref_=fn_t...</td>\n",
       "      <td>1.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>24419</td>\n",
       "      <td>58260</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4855</th>\n",
       "      <td>Better Luck Tomorrow</td>\n",
       "      <td>2002.0</td>\n",
       "      <td>Justin Lin</td>\n",
       "      <td>3799339.0</td>\n",
       "      <td>250000.0</td>\n",
       "      <td>3549339.0</td>\n",
       "      <td>USA</td>\n",
       "      <td>English</td>\n",
       "      <td>7.2</td>\n",
       "      <td>R</td>\n",
       "      <td>...</td>\n",
       "      <td>13.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>661</td>\n",
       "      <td>Color</td>\n",
       "      <td>asian american|high school|overachiever|pubic ...</td>\n",
       "      <td>http://www.imdb.com/title/tt0280477/?ref_=fn_t...</td>\n",
       "      <td>1.9</td>\n",
       "      <td>1.0</td>\n",
       "      <td>139</td>\n",
       "      <td>8000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4864</th>\n",
       "      <td>Like Crazy</td>\n",
       "      <td>2011.0</td>\n",
       "      <td>Drake Doremus</td>\n",
       "      <td>3388210.0</td>\n",
       "      <td>250000.0</td>\n",
       "      <td>3138210.0</td>\n",
       "      <td>USA</td>\n",
       "      <td>English</td>\n",
       "      <td>6.7</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>...</td>\n",
       "      <td>224.0</td>\n",
       "      <td>206.0</td>\n",
       "      <td>12000</td>\n",
       "      <td>Color</td>\n",
       "      <td>girlfriend|immigration|long distance relations...</td>\n",
       "      <td>http://www.imdb.com/title/tt1758692/?ref_=fn_t...</td>\n",
       "      <td>1.8</td>\n",
       "      <td>1.0</td>\n",
       "      <td>34983</td>\n",
       "      <td>46813</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4478</th>\n",
       "      <td>Filly Brown</td>\n",
       "      <td>2012.0</td>\n",
       "      <td>Youssef Delara</td>\n",
       "      <td>2833383.0</td>\n",
       "      <td>427000.0</td>\n",
       "      <td>2406383.0</td>\n",
       "      <td>USA</td>\n",
       "      <td>English</td>\n",
       "      <td>5.7</td>\n",
       "      <td>R</td>\n",
       "      <td>...</td>\n",
       "      <td>183.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Color</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://www.imdb.com/title/tt1869425/?ref_=fn_t...</td>\n",
       "      <td>2.4</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2459</td>\n",
       "      <td>910</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4900</th>\n",
       "      <td>The Grace Card</td>\n",
       "      <td>2010.0</td>\n",
       "      <td>David G. Evans</td>\n",
       "      <td>2428241.0</td>\n",
       "      <td>200000.0</td>\n",
       "      <td>2228241.0</td>\n",
       "      <td>USA</td>\n",
       "      <td>English</td>\n",
       "      <td>6.4</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>...</td>\n",
       "      <td>16.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Color</td>\n",
       "      <td>christian film|forgiveness|hospital|pastor|police</td>\n",
       "      <td>http://www.imdb.com/title/tt1544600/?ref_=fn_t...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.0</td>\n",
       "      <td>77046</td>\n",
       "      <td>2099</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4830</th>\n",
       "      <td>Pieces of April</td>\n",
       "      <td>2003.0</td>\n",
       "      <td>Peter Hedges</td>\n",
       "      <td>2360184.0</td>\n",
       "      <td>300000.0</td>\n",
       "      <td>2060184.0</td>\n",
       "      <td>USA</td>\n",
       "      <td>English</td>\n",
       "      <td>7.1</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>...</td>\n",
       "      <td>543.0</td>\n",
       "      <td>131.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Color</td>\n",
       "      <td>apartment|oven|stove|thanksgiving|thanksgiving...</td>\n",
       "      <td>http://www.imdb.com/title/tt0311648/?ref_=fn_t...</td>\n",
       "      <td>1.9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3010</td>\n",
       "      <td>18035</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4696</th>\n",
       "      <td>Half Nelson</td>\n",
       "      <td>2006.0</td>\n",
       "      <td>Ryan Fleck</td>\n",
       "      <td>2694973.0</td>\n",
       "      <td>700000.0</td>\n",
       "      <td>1994973.0</td>\n",
       "      <td>USA</td>\n",
       "      <td>English</td>\n",
       "      <td>7.2</td>\n",
       "      <td>R</td>\n",
       "      <td>...</td>\n",
       "      <td>71.0</td>\n",
       "      <td>208.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Color</td>\n",
       "      <td>bathroom|classroom|dialectics|drugs|student</td>\n",
       "      <td>http://www.imdb.com/title/tt0468489/?ref_=fn_t...</td>\n",
       "      <td>1.9</td>\n",
       "      <td>2.0</td>\n",
       "      <td>33734</td>\n",
       "      <td>70885</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4891</th>\n",
       "      <td>Urbania</td>\n",
       "      <td>2000.0</td>\n",
       "      <td>Jon Shear</td>\n",
       "      <td>1027119.0</td>\n",
       "      <td>225000.0</td>\n",
       "      <td>802119.0</td>\n",
       "      <td>USA</td>\n",
       "      <td>English</td>\n",
       "      <td>7.0</td>\n",
       "      <td>R</td>\n",
       "      <td>...</td>\n",
       "      <td>131.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>72</td>\n",
       "      <td>Color</td>\n",
       "      <td>hot dog bun|needle|new york|rat|tourist</td>\n",
       "      <td>http://www.imdb.com/title/tt0182508/?ref_=fn_t...</td>\n",
       "      <td>1.9</td>\n",
       "      <td>1.0</td>\n",
       "      <td>964</td>\n",
       "      <td>2742</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4857</th>\n",
       "      <td>Chuck &amp; Buck</td>\n",
       "      <td>2000.0</td>\n",
       "      <td>Miguel Arteta</td>\n",
       "      <td>1050600.0</td>\n",
       "      <td>250000.0</td>\n",
       "      <td>800600.0</td>\n",
       "      <td>USA</td>\n",
       "      <td>English</td>\n",
       "      <td>6.6</td>\n",
       "      <td>R</td>\n",
       "      <td>...</td>\n",
       "      <td>129.0</td>\n",
       "      <td>59.0</td>\n",
       "      <td>170</td>\n",
       "      <td>Color</td>\n",
       "      <td>best friend|bisexuality|friend|gay kiss|sexuality</td>\n",
       "      <td>http://www.imdb.com/title/tt0200530/?ref_=fn_t...</td>\n",
       "      <td>1.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1378</td>\n",
       "      <td>4662</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4833</th>\n",
       "      <td>Wendy and Lucy</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>Kelly Reichardt</td>\n",
       "      <td>856942.0</td>\n",
       "      <td>200000.0</td>\n",
       "      <td>656942.0</td>\n",
       "      <td>USA</td>\n",
       "      <td>English</td>\n",
       "      <td>7.1</td>\n",
       "      <td>R</td>\n",
       "      <td>...</td>\n",
       "      <td>26.0</td>\n",
       "      <td>189.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Color</td>\n",
       "      <td>car|dog|flip phone|rape threat|vulnerable</td>\n",
       "      <td>http://www.imdb.com/title/tt1152850/?ref_=fn_t...</td>\n",
       "      <td>1.9</td>\n",
       "      <td>1.0</td>\n",
       "      <td>460</td>\n",
       "      <td>12241</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4858</th>\n",
       "      <td>American Desi</td>\n",
       "      <td>2001.0</td>\n",
       "      <td>Piyush Dinker Pandya</td>\n",
       "      <td>902835.0</td>\n",
       "      <td>250000.0</td>\n",
       "      <td>652835.0</td>\n",
       "      <td>USA</td>\n",
       "      <td>English</td>\n",
       "      <td>6.7</td>\n",
       "      <td>Unrated</td>\n",
       "      <td>...</td>\n",
       "      <td>51.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>133</td>\n",
       "      <td>Color</td>\n",
       "      <td>college|desi|heritage|india|indian american</td>\n",
       "      <td>http://www.imdb.com/title/tt0203289/?ref_=fn_t...</td>\n",
       "      <td>1.9</td>\n",
       "      <td>2.0</td>\n",
       "      <td>454</td>\n",
       "      <td>1489</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4738</th>\n",
       "      <td>The R.M.</td>\n",
       "      <td>2003.0</td>\n",
       "      <td>Kurt Hale</td>\n",
       "      <td>1111615.0</td>\n",
       "      <td>500000.0</td>\n",
       "      <td>611615.0</td>\n",
       "      <td>USA</td>\n",
       "      <td>English</td>\n",
       "      <td>6.0</td>\n",
       "      <td>PG</td>\n",
       "      <td>...</td>\n",
       "      <td>17.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>44</td>\n",
       "      <td>Color</td>\n",
       "      <td>latter day saints|missionary|pickup truck|poli...</td>\n",
       "      <td>http://www.imdb.com/title/tt0341540/?ref_=fn_t...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>155</td>\n",
       "      <td>651</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5033</th>\n",
       "      <td>Primer</td>\n",
       "      <td>2004.0</td>\n",
       "      <td>Shane Carruth</td>\n",
       "      <td>424760.0</td>\n",
       "      <td>7000.0</td>\n",
       "      <td>417760.0</td>\n",
       "      <td>USA</td>\n",
       "      <td>English</td>\n",
       "      <td>7.0</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>...</td>\n",
       "      <td>8.0</td>\n",
       "      <td>143.0</td>\n",
       "      <td>19000</td>\n",
       "      <td>Color</td>\n",
       "      <td>changing the future|independent film|invention...</td>\n",
       "      <td>http://www.imdb.com/title/tt0390384/?ref_=fn_t...</td>\n",
       "      <td>1.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>368</td>\n",
       "      <td>72639</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4987</th>\n",
       "      <td>Tiny Furniture</td>\n",
       "      <td>2010.0</td>\n",
       "      <td>Lena Dunham</td>\n",
       "      <td>389804.0</td>\n",
       "      <td>65000.0</td>\n",
       "      <td>324804.0</td>\n",
       "      <td>USA</td>\n",
       "      <td>English</td>\n",
       "      <td>6.3</td>\n",
       "      <td>Not Rated</td>\n",
       "      <td>...</td>\n",
       "      <td>433.0</td>\n",
       "      <td>113.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Color</td>\n",
       "      <td>adult returns home|girl with glasses|hipster|s...</td>\n",
       "      <td>http://www.imdb.com/title/tt1570989/?ref_=fn_t...</td>\n",
       "      <td>2.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2530</td>\n",
       "      <td>11816</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4899</th>\n",
       "      <td>Short Cut to Nirvana: Kumbh Mela</td>\n",
       "      <td>2004.0</td>\n",
       "      <td>Maurizio Benazzo</td>\n",
       "      <td>381225.0</td>\n",
       "      <td>200000.0</td>\n",
       "      <td>181225.0</td>\n",
       "      <td>USA</td>\n",
       "      <td>English</td>\n",
       "      <td>7.2</td>\n",
       "      <td>Unrated</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>30</td>\n",
       "      <td>Color</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://www.imdb.com/title/tt0420723/?ref_=fn_t...</td>\n",
       "      <td>1.8</td>\n",
       "      <td>0.0</td>\n",
       "      <td>66</td>\n",
       "      <td>131</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4740</th>\n",
       "      <td>Mean Creek</td>\n",
       "      <td>2004.0</td>\n",
       "      <td>Jacob Aaron Estes</td>\n",
       "      <td>603943.0</td>\n",
       "      <td>500000.0</td>\n",
       "      <td>103943.0</td>\n",
       "      <td>USA</td>\n",
       "      <td>English</td>\n",
       "      <td>7.3</td>\n",
       "      <td>R</td>\n",
       "      <td>...</td>\n",
       "      <td>595.0</td>\n",
       "      <td>126.0</td>\n",
       "      <td>1000</td>\n",
       "      <td>Color</td>\n",
       "      <td>boat|bully|dare|friend|river</td>\n",
       "      <td>http://www.imdb.com/title/tt0377091/?ref_=fn_t...</td>\n",
       "      <td>1.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2655</td>\n",
       "      <td>26407</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5042</th>\n",
       "      <td>My Date with Drew</td>\n",
       "      <td>2004.0</td>\n",
       "      <td>Jon Gunn</td>\n",
       "      <td>85222.0</td>\n",
       "      <td>1100.0</td>\n",
       "      <td>84122.0</td>\n",
       "      <td>USA</td>\n",
       "      <td>English</td>\n",
       "      <td>6.6</td>\n",
       "      <td>PG</td>\n",
       "      <td>...</td>\n",
       "      <td>16.0</td>\n",
       "      <td>43.0</td>\n",
       "      <td>456</td>\n",
       "      <td>Color</td>\n",
       "      <td>actress name in title|crush|date|four word tit...</td>\n",
       "      <td>http://www.imdb.com/title/tt0378407/?ref_=fn_t...</td>\n",
       "      <td>1.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>163</td>\n",
       "      <td>4285</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4962</th>\n",
       "      <td>The Lost Skeleton of Cadavra</td>\n",
       "      <td>2001.0</td>\n",
       "      <td>Larry Blamire</td>\n",
       "      <td>110536.0</td>\n",
       "      <td>40000.0</td>\n",
       "      <td>70536.0</td>\n",
       "      <td>USA</td>\n",
       "      <td>English</td>\n",
       "      <td>7.0</td>\n",
       "      <td>PG</td>\n",
       "      <td>...</td>\n",
       "      <td>56.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Black and White</td>\n",
       "      <td>alien|cave|husband wife relationship|monster|s...</td>\n",
       "      <td>http://www.imdb.com/title/tt0307109/?ref_=fn_t...</td>\n",
       "      <td>1.9</td>\n",
       "      <td>1.0</td>\n",
       "      <td>284</td>\n",
       "      <td>4117</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4851</th>\n",
       "      <td>Compliance</td>\n",
       "      <td>2012.0</td>\n",
       "      <td>Craig Zobel</td>\n",
       "      <td>318622.0</td>\n",
       "      <td>270000.0</td>\n",
       "      <td>48622.0</td>\n",
       "      <td>USA</td>\n",
       "      <td>English</td>\n",
       "      <td>6.4</td>\n",
       "      <td>R</td>\n",
       "      <td>...</td>\n",
       "      <td>235.0</td>\n",
       "      <td>286.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Color</td>\n",
       "      <td>authority|boss subordinate relationship|fast f...</td>\n",
       "      <td>http://www.imdb.com/title/tt1971352/?ref_=fn_t...</td>\n",
       "      <td>2.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1734</td>\n",
       "      <td>24668</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4863</th>\n",
       "      <td>November</td>\n",
       "      <td>2004.0</td>\n",
       "      <td>Greg Harrison</td>\n",
       "      <td>191309.0</td>\n",
       "      <td>150000.0</td>\n",
       "      <td>41309.0</td>\n",
       "      <td>USA</td>\n",
       "      <td>English</td>\n",
       "      <td>5.5</td>\n",
       "      <td>R</td>\n",
       "      <td>...</td>\n",
       "      <td>142.0</td>\n",
       "      <td>43.0</td>\n",
       "      <td>98</td>\n",
       "      <td>Color</td>\n",
       "      <td>female protagonist|murder|photographer|robbery...</td>\n",
       "      <td>http://www.imdb.com/title/tt0368089/?ref_=fn_t...</td>\n",
       "      <td>1.9</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1008</td>\n",
       "      <td>2787</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4979</th>\n",
       "      <td>Happy Christmas</td>\n",
       "      <td>2014.0</td>\n",
       "      <td>Joe Swanberg</td>\n",
       "      <td>30084.0</td>\n",
       "      <td>70000.0</td>\n",
       "      <td>-39916.0</td>\n",
       "      <td>USA</td>\n",
       "      <td>English</td>\n",
       "      <td>5.6</td>\n",
       "      <td>R</td>\n",
       "      <td>...</td>\n",
       "      <td>442.0</td>\n",
       "      <td>65.0</td>\n",
       "      <td>812</td>\n",
       "      <td>Color</td>\n",
       "      <td>chicago illinois|drink|drinking|filmmaker|writer</td>\n",
       "      <td>http://www.imdb.com/title/tt2955096/?ref_=fn_t...</td>\n",
       "      <td>1.9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>11642</td>\n",
       "      <td>5507</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4832</th>\n",
       "      <td>Old Joy</td>\n",
       "      <td>2006.0</td>\n",
       "      <td>Kelly Reichardt</td>\n",
       "      <td>255352.0</td>\n",
       "      <td>300000.0</td>\n",
       "      <td>-44648.0</td>\n",
       "      <td>USA</td>\n",
       "      <td>English</td>\n",
       "      <td>6.7</td>\n",
       "      <td>Unrated</td>\n",
       "      <td>...</td>\n",
       "      <td>26.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>594</td>\n",
       "      <td>Color</td>\n",
       "      <td>cell phone|male frontal nudity|oregon|sexual a...</td>\n",
       "      <td>http://www.imdb.com/title/tt0468526/?ref_=fn_t...</td>\n",
       "      <td>1.7</td>\n",
       "      <td>2.0</td>\n",
       "      <td>132</td>\n",
       "      <td>4423</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4890</th>\n",
       "      <td>Burn</td>\n",
       "      <td>2012.0</td>\n",
       "      <td>Tom Putnam</td>\n",
       "      <td>111300.0</td>\n",
       "      <td>225000.0</td>\n",
       "      <td>-113700.0</td>\n",
       "      <td>USA</td>\n",
       "      <td>English</td>\n",
       "      <td>7.5</td>\n",
       "      <td>Not Rated</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>801</td>\n",
       "      <td>Color</td>\n",
       "      <td>abandoned building|detroit michigan|firefighte...</td>\n",
       "      <td>http://www.imdb.com/title/tt1781784/?ref_=fn_t...</td>\n",
       "      <td>2.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2</td>\n",
       "      <td>575</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4901</th>\n",
       "      <td>Middle of Nowhere</td>\n",
       "      <td>2012.0</td>\n",
       "      <td>Ava DuVernay</td>\n",
       "      <td>78030.0</td>\n",
       "      <td>200000.0</td>\n",
       "      <td>-121970.0</td>\n",
       "      <td>USA</td>\n",
       "      <td>English</td>\n",
       "      <td>6.5</td>\n",
       "      <td>R</td>\n",
       "      <td>...</td>\n",
       "      <td>305.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>569</td>\n",
       "      <td>Color</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://www.imdb.com/title/tt1211890/?ref_=fn_t...</td>\n",
       "      <td>2.4</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3021</td>\n",
       "      <td>1034</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4840</th>\n",
       "      <td>Fighting Tommy Riley</td>\n",
       "      <td>2004.0</td>\n",
       "      <td>Eddie O'Flaherty</td>\n",
       "      <td>5199.0</td>\n",
       "      <td>200000.0</td>\n",
       "      <td>-194801.0</td>\n",
       "      <td>USA</td>\n",
       "      <td>English</td>\n",
       "      <td>6.6</td>\n",
       "      <td>R</td>\n",
       "      <td>...</td>\n",
       "      <td>25.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>30</td>\n",
       "      <td>Color</td>\n",
       "      <td>older man younger man relationship|punching ba...</td>\n",
       "      <td>http://www.imdb.com/title/tt0366444/?ref_=fn_t...</td>\n",
       "      <td>2.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>185</td>\n",
       "      <td>720</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4743</th>\n",
       "      <td>Civil Brand</td>\n",
       "      <td>2002.0</td>\n",
       "      <td>Neema Barnette</td>\n",
       "      <td>243347.0</td>\n",
       "      <td>500000.0</td>\n",
       "      <td>-256653.0</td>\n",
       "      <td>USA</td>\n",
       "      <td>English</td>\n",
       "      <td>5.3</td>\n",
       "      <td>R</td>\n",
       "      <td>...</td>\n",
       "      <td>469.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>86</td>\n",
       "      <td>Color</td>\n",
       "      <td>abuse of power|friendship|prison|prison guard|...</td>\n",
       "      <td>http://www.imdb.com/title/tt0326806/?ref_=fn_t...</td>\n",
       "      <td>1.9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2555</td>\n",
       "      <td>553</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4744</th>\n",
       "      <td>Lonesome Jim</td>\n",
       "      <td>2005.0</td>\n",
       "      <td>Steve Buscemi</td>\n",
       "      <td>154077.0</td>\n",
       "      <td>500000.0</td>\n",
       "      <td>-345923.0</td>\n",
       "      <td>USA</td>\n",
       "      <td>English</td>\n",
       "      <td>6.6</td>\n",
       "      <td>R</td>\n",
       "      <td>...</td>\n",
       "      <td>213.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>238</td>\n",
       "      <td>Color</td>\n",
       "      <td>bail|coma|dart board|indiana|ladder factory</td>\n",
       "      <td>http://www.imdb.com/title/tt0385056/?ref_=fn_t...</td>\n",
       "      <td>1.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1440</td>\n",
       "      <td>6884</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4595</th>\n",
       "      <td>The Perfect Host</td>\n",
       "      <td>2010.0</td>\n",
       "      <td>Nick Tomnay</td>\n",
       "      <td>48430.0</td>\n",
       "      <td>500000.0</td>\n",
       "      <td>-451570.0</td>\n",
       "      <td>USA</td>\n",
       "      <td>English</td>\n",
       "      <td>6.8</td>\n",
       "      <td>R</td>\n",
       "      <td>...</td>\n",
       "      <td>271.0</td>\n",
       "      <td>112.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Color</td>\n",
       "      <td>arm tattoo|bank robbery|cauterizing a wound|da...</td>\n",
       "      <td>http://www.imdb.com/title/tt1334553/?ref_=fn_t...</td>\n",
       "      <td>1.9</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1452</td>\n",
       "      <td>20176</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4784</th>\n",
       "      <td>Poultrygeist: Night of the Chicken Dead</td>\n",
       "      <td>2006.0</td>\n",
       "      <td>Lloyd Kaufman</td>\n",
       "      <td>23000.0</td>\n",
       "      <td>500000.0</td>\n",
       "      <td>-477000.0</td>\n",
       "      <td>USA</td>\n",
       "      <td>English</td>\n",
       "      <td>6.2</td>\n",
       "      <td>Unrated</td>\n",
       "      <td>...</td>\n",
       "      <td>49.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Color</td>\n",
       "      <td>castration|chicken|fast food|indian burial gro...</td>\n",
       "      <td>http://www.imdb.com/title/tt0462485/?ref_=fn_t...</td>\n",
       "      <td>1.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1411</td>\n",
       "      <td>5931</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4754</th>\n",
       "      <td>The Slaughter Rule</td>\n",
       "      <td>2002.0</td>\n",
       "      <td>Alex Smith</td>\n",
       "      <td>13134.0</td>\n",
       "      <td>500000.0</td>\n",
       "      <td>-486866.0</td>\n",
       "      <td>USA</td>\n",
       "      <td>English</td>\n",
       "      <td>6.1</td>\n",
       "      <td>R</td>\n",
       "      <td>...</td>\n",
       "      <td>699.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>183</td>\n",
       "      <td>Color</td>\n",
       "      <td>cheerleader|father son relationship|football c...</td>\n",
       "      <td>http://www.imdb.com/title/tt0266971/?ref_=fn_t...</td>\n",
       "      <td>2.4</td>\n",
       "      <td>2.0</td>\n",
       "      <td>35294</td>\n",
       "      <td>2004</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4757</th>\n",
       "      <td>The Living Wake</td>\n",
       "      <td>2007.0</td>\n",
       "      <td>Sol Tryon</td>\n",
       "      <td>12055.0</td>\n",
       "      <td>500000.0</td>\n",
       "      <td>-487945.0</td>\n",
       "      <td>USA</td>\n",
       "      <td>English</td>\n",
       "      <td>6.5</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>...</td>\n",
       "      <td>170.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>339</td>\n",
       "      <td>Color</td>\n",
       "      <td>artist|black comedy</td>\n",
       "      <td>http://www.imdb.com/title/tt0489212/?ref_=fn_t...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1047</td>\n",
       "      <td>739</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3950</th>\n",
       "      <td>Stake Land</td>\n",
       "      <td>2010.0</td>\n",
       "      <td>Jim Mickle</td>\n",
       "      <td>18469.0</td>\n",
       "      <td>650000.0</td>\n",
       "      <td>-631531.0</td>\n",
       "      <td>USA</td>\n",
       "      <td>English</td>\n",
       "      <td>6.5</td>\n",
       "      <td>R</td>\n",
       "      <td>...</td>\n",
       "      <td>65.0</td>\n",
       "      <td>215.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Color</td>\n",
       "      <td>canada|post apocalypse|road movie|vampire|vamp...</td>\n",
       "      <td>http://www.imdb.com/title/tt1464580/?ref_=fn_t...</td>\n",
       "      <td>2.4</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1038</td>\n",
       "      <td>34263</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4680</th>\n",
       "      <td>The Innkeepers</td>\n",
       "      <td>2011.0</td>\n",
       "      <td>Ti West</td>\n",
       "      <td>77501.0</td>\n",
       "      <td>750000.0</td>\n",
       "      <td>-672499.0</td>\n",
       "      <td>USA</td>\n",
       "      <td>English</td>\n",
       "      <td>5.5</td>\n",
       "      <td>R</td>\n",
       "      <td>...</td>\n",
       "      <td>74.0</td>\n",
       "      <td>292.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Color</td>\n",
       "      <td>bathtub|dead body in a bathtub|dead body in ba...</td>\n",
       "      <td>http://www.imdb.com/title/tt1594562/?ref_=fn_t...</td>\n",
       "      <td>2.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1252</td>\n",
       "      <td>27260</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4683</th>\n",
       "      <td>Interview with the Assassin</td>\n",
       "      <td>2002.0</td>\n",
       "      <td>Neil Burger</td>\n",
       "      <td>47329.0</td>\n",
       "      <td>750000.0</td>\n",
       "      <td>-702671.0</td>\n",
       "      <td>USA</td>\n",
       "      <td>English</td>\n",
       "      <td>6.6</td>\n",
       "      <td>R</td>\n",
       "      <td>...</td>\n",
       "      <td>21.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>163</td>\n",
       "      <td>Color</td>\n",
       "      <td>conspiracy theory|kennedy assassination|mock d...</td>\n",
       "      <td>http://www.imdb.com/title/tt0308411/?ref_=fn_t...</td>\n",
       "      <td>1.8</td>\n",
       "      <td>0.0</td>\n",
       "      <td>243</td>\n",
       "      <td>1661</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>36 rows × 27 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                   movie_title  title_year  \\\n",
       "4793                      Paranormal Activity       2007.0   \n",
       "4726                               Open Water       2003.0   \n",
       "4730                        The Station Agent       2003.0   \n",
       "4855                     Better Luck Tomorrow       2002.0   \n",
       "4864                               Like Crazy       2011.0   \n",
       "4478                              Filly Brown       2012.0   \n",
       "4900                           The Grace Card       2010.0   \n",
       "4830                          Pieces of April       2003.0   \n",
       "4696                              Half Nelson       2006.0   \n",
       "4891                                  Urbania       2000.0   \n",
       "4857                             Chuck & Buck       2000.0   \n",
       "4833                           Wendy and Lucy       2008.0   \n",
       "4858                            American Desi       2001.0   \n",
       "4738                                 The R.M.       2003.0   \n",
       "5033                                   Primer       2004.0   \n",
       "4987                           Tiny Furniture       2010.0   \n",
       "4899         Short Cut to Nirvana: Kumbh Mela       2004.0   \n",
       "4740                               Mean Creek       2004.0   \n",
       "5042                        My Date with Drew       2004.0   \n",
       "4962             The Lost Skeleton of Cadavra       2001.0   \n",
       "4851                               Compliance       2012.0   \n",
       "4863                                 November       2004.0   \n",
       "4979                          Happy Christmas       2014.0   \n",
       "4832                                  Old Joy       2006.0   \n",
       "4890                                     Burn       2012.0   \n",
       "4901                        Middle of Nowhere       2012.0   \n",
       "4840                     Fighting Tommy Riley       2004.0   \n",
       "4743                              Civil Brand       2002.0   \n",
       "4744                             Lonesome Jim       2005.0   \n",
       "4595                         The Perfect Host       2010.0   \n",
       "4784  Poultrygeist: Night of the Chicken Dead       2006.0   \n",
       "4754                       The Slaughter Rule       2002.0   \n",
       "4757                          The Living Wake       2007.0   \n",
       "3950                               Stake Land       2010.0   \n",
       "4680                           The Innkeepers       2011.0   \n",
       "4683              Interview with the Assassin       2002.0   \n",
       "\n",
       "             director_name       gross   budget      profit country language  \\\n",
       "4793             Oren Peli 107917283.0  15000.0 107902283.0     USA  English   \n",
       "4726          Chris Kentis  30500882.0 500000.0  30000882.0     USA  English   \n",
       "4730          Tom McCarthy   5739376.0 500000.0   5239376.0     USA  English   \n",
       "4855            Justin Lin   3799339.0 250000.0   3549339.0     USA  English   \n",
       "4864         Drake Doremus   3388210.0 250000.0   3138210.0     USA  English   \n",
       "4478        Youssef Delara   2833383.0 427000.0   2406383.0     USA  English   \n",
       "4900        David G. Evans   2428241.0 200000.0   2228241.0     USA  English   \n",
       "4830          Peter Hedges   2360184.0 300000.0   2060184.0     USA  English   \n",
       "4696            Ryan Fleck   2694973.0 700000.0   1994973.0     USA  English   \n",
       "4891             Jon Shear   1027119.0 225000.0    802119.0     USA  English   \n",
       "4857         Miguel Arteta   1050600.0 250000.0    800600.0     USA  English   \n",
       "4833       Kelly Reichardt    856942.0 200000.0    656942.0     USA  English   \n",
       "4858  Piyush Dinker Pandya    902835.0 250000.0    652835.0     USA  English   \n",
       "4738             Kurt Hale   1111615.0 500000.0    611615.0     USA  English   \n",
       "5033         Shane Carruth    424760.0   7000.0    417760.0     USA  English   \n",
       "4987           Lena Dunham    389804.0  65000.0    324804.0     USA  English   \n",
       "4899      Maurizio Benazzo    381225.0 200000.0    181225.0     USA  English   \n",
       "4740     Jacob Aaron Estes    603943.0 500000.0    103943.0     USA  English   \n",
       "5042              Jon Gunn     85222.0   1100.0     84122.0     USA  English   \n",
       "4962         Larry Blamire    110536.0  40000.0     70536.0     USA  English   \n",
       "4851           Craig Zobel    318622.0 270000.0     48622.0     USA  English   \n",
       "4863         Greg Harrison    191309.0 150000.0     41309.0     USA  English   \n",
       "4979          Joe Swanberg     30084.0  70000.0    -39916.0     USA  English   \n",
       "4832       Kelly Reichardt    255352.0 300000.0    -44648.0     USA  English   \n",
       "4890            Tom Putnam    111300.0 225000.0   -113700.0     USA  English   \n",
       "4901          Ava DuVernay     78030.0 200000.0   -121970.0     USA  English   \n",
       "4840      Eddie O'Flaherty      5199.0 200000.0   -194801.0     USA  English   \n",
       "4743        Neema Barnette    243347.0 500000.0   -256653.0     USA  English   \n",
       "4744         Steve Buscemi    154077.0 500000.0   -345923.0     USA  English   \n",
       "4595           Nick Tomnay     48430.0 500000.0   -451570.0     USA  English   \n",
       "4784         Lloyd Kaufman     23000.0 500000.0   -477000.0     USA  English   \n",
       "4754            Alex Smith     13134.0 500000.0   -486866.0     USA  English   \n",
       "4757             Sol Tryon     12055.0 500000.0   -487945.0     USA  English   \n",
       "3950            Jim Mickle     18469.0 650000.0   -631531.0     USA  English   \n",
       "4680               Ti West     77501.0 750000.0   -672499.0     USA  English   \n",
       "4683           Neil Burger     47329.0 750000.0   -702671.0     USA  English   \n",
       "\n",
       "      imdb_score content_rating  ...  actor_3_facebook_likes  \\\n",
       "4793         6.3              R  ...                    21.0   \n",
       "4726         5.7              R  ...                     7.0   \n",
       "4730         7.7              R  ...                   587.0   \n",
       "4855         7.2              R  ...                    13.0   \n",
       "4864         6.7          PG-13  ...                   224.0   \n",
       "4478         5.7              R  ...                   183.0   \n",
       "4900         6.4          PG-13  ...                    16.0   \n",
       "4830         7.1          PG-13  ...                   543.0   \n",
       "4696         7.2              R  ...                    71.0   \n",
       "4891         7.0              R  ...                   131.0   \n",
       "4857         6.6              R  ...                   129.0   \n",
       "4833         7.1              R  ...                    26.0   \n",
       "4858         6.7        Unrated  ...                    51.0   \n",
       "4738         6.0             PG  ...                    17.0   \n",
       "5033         7.0          PG-13  ...                     8.0   \n",
       "4987         6.3      Not Rated  ...                   433.0   \n",
       "4899         7.2        Unrated  ...                     0.0   \n",
       "4740         7.3              R  ...                   595.0   \n",
       "5042         6.6             PG  ...                    16.0   \n",
       "4962         7.0             PG  ...                    56.0   \n",
       "4851         6.4              R  ...                   235.0   \n",
       "4863         5.5              R  ...                   142.0   \n",
       "4979         5.6              R  ...                   442.0   \n",
       "4832         6.7        Unrated  ...                    26.0   \n",
       "4890         7.5      Not Rated  ...                     0.0   \n",
       "4901         6.5              R  ...                   305.0   \n",
       "4840         6.6              R  ...                    25.0   \n",
       "4743         5.3              R  ...                   469.0   \n",
       "4744         6.6              R  ...                   213.0   \n",
       "4595         6.8              R  ...                   271.0   \n",
       "4784         6.2        Unrated  ...                    49.0   \n",
       "4754         6.1              R  ...                   699.0   \n",
       "4757         6.5          PG-13  ...                   170.0   \n",
       "3950         6.5              R  ...                    65.0   \n",
       "4680         5.5              R  ...                    74.0   \n",
       "4683         6.6              R  ...                    21.0   \n",
       "\n",
       "      num_critic_for_reviews movie_facebook_likes             color  \\\n",
       "4793                   409.0                12000             Color   \n",
       "4726                   235.0                    0             Color   \n",
       "4730                   154.0                    0             Color   \n",
       "4855                    51.0                  661             Color   \n",
       "4864                   206.0                12000             Color   \n",
       "4478                    16.0                    0             Color   \n",
       "4900                    25.0                    0             Color   \n",
       "4830                   131.0                    0             Color   \n",
       "4696                   208.0                    0             Color   \n",
       "4891                    38.0                   72             Color   \n",
       "4857                    59.0                  170             Color   \n",
       "4833                   189.0                    0             Color   \n",
       "4858                     9.0                  133             Color   \n",
       "4738                     3.0                   44             Color   \n",
       "5033                   143.0                19000             Color   \n",
       "4987                   113.0                    0             Color   \n",
       "4899                    15.0                   30             Color   \n",
       "4740                   126.0                 1000             Color   \n",
       "5042                    43.0                  456             Color   \n",
       "4962                    88.0                    0   Black and White   \n",
       "4851                   286.0                    0             Color   \n",
       "4863                    43.0                   98             Color   \n",
       "4979                    65.0                  812             Color   \n",
       "4832                    88.0                  594             Color   \n",
       "4890                    22.0                  801             Color   \n",
       "4901                    37.0                  569             Color   \n",
       "4840                    13.0                   30             Color   \n",
       "4743                    11.0                   86             Color   \n",
       "4744                    81.0                  238             Color   \n",
       "4595                   112.0                    0             Color   \n",
       "4784                    88.0                    0             Color   \n",
       "4754                    17.0                  183             Color   \n",
       "4757                    28.0                  339             Color   \n",
       "3950                   215.0                    0             Color   \n",
       "4680                   292.0                    0             Color   \n",
       "4683                    31.0                  163             Color   \n",
       "\n",
       "                                          plot_keywords  \\\n",
       "4793  dark force|entity|evil force|found footage|par...   \n",
       "4726  bare chested male|female full frontal nudity|h...   \n",
       "4730  abandoned|depot|dwarf|newfoundland new jersey|...   \n",
       "4855  asian american|high school|overachiever|pubic ...   \n",
       "4864  girlfriend|immigration|long distance relations...   \n",
       "4478                                                NaN   \n",
       "4900  christian film|forgiveness|hospital|pastor|police   \n",
       "4830  apartment|oven|stove|thanksgiving|thanksgiving...   \n",
       "4696        bathroom|classroom|dialectics|drugs|student   \n",
       "4891            hot dog bun|needle|new york|rat|tourist   \n",
       "4857  best friend|bisexuality|friend|gay kiss|sexuality   \n",
       "4833          car|dog|flip phone|rape threat|vulnerable   \n",
       "4858        college|desi|heritage|india|indian american   \n",
       "4738  latter day saints|missionary|pickup truck|poli...   \n",
       "5033  changing the future|independent film|invention...   \n",
       "4987  adult returns home|girl with glasses|hipster|s...   \n",
       "4899                                                NaN   \n",
       "4740                       boat|bully|dare|friend|river   \n",
       "5042  actress name in title|crush|date|four word tit...   \n",
       "4962  alien|cave|husband wife relationship|monster|s...   \n",
       "4851  authority|boss subordinate relationship|fast f...   \n",
       "4863  female protagonist|murder|photographer|robbery...   \n",
       "4979   chicago illinois|drink|drinking|filmmaker|writer   \n",
       "4832  cell phone|male frontal nudity|oregon|sexual a...   \n",
       "4890  abandoned building|detroit michigan|firefighte...   \n",
       "4901                                                NaN   \n",
       "4840  older man younger man relationship|punching ba...   \n",
       "4743  abuse of power|friendship|prison|prison guard|...   \n",
       "4744        bail|coma|dart board|indiana|ladder factory   \n",
       "4595  arm tattoo|bank robbery|cauterizing a wound|da...   \n",
       "4784  castration|chicken|fast food|indian burial gro...   \n",
       "4754  cheerleader|father son relationship|football c...   \n",
       "4757                                artist|black comedy   \n",
       "3950  canada|post apocalypse|road movie|vampire|vamp...   \n",
       "4680  bathtub|dead body in a bathtub|dead body in ba...   \n",
       "4683  conspiracy theory|kennedy assassination|mock d...   \n",
       "\n",
       "                                        movie_imdb_link aspect_ratio  \\\n",
       "4793  http://www.imdb.com/title/tt1179904/?ref_=fn_t...          1.9   \n",
       "4726  http://www.imdb.com/title/tt0374102/?ref_=fn_t...          1.9   \n",
       "4730  http://www.imdb.com/title/tt0340377/?ref_=fn_t...          1.9   \n",
       "4855  http://www.imdb.com/title/tt0280477/?ref_=fn_t...          1.9   \n",
       "4864  http://www.imdb.com/title/tt1758692/?ref_=fn_t...          1.8   \n",
       "4478  http://www.imdb.com/title/tt1869425/?ref_=fn_t...          2.4   \n",
       "4900  http://www.imdb.com/title/tt1544600/?ref_=fn_t...          NaN   \n",
       "4830  http://www.imdb.com/title/tt0311648/?ref_=fn_t...          1.9   \n",
       "4696  http://www.imdb.com/title/tt0468489/?ref_=fn_t...          1.9   \n",
       "4891  http://www.imdb.com/title/tt0182508/?ref_=fn_t...          1.9   \n",
       "4857  http://www.imdb.com/title/tt0200530/?ref_=fn_t...          1.9   \n",
       "4833  http://www.imdb.com/title/tt1152850/?ref_=fn_t...          1.9   \n",
       "4858  http://www.imdb.com/title/tt0203289/?ref_=fn_t...          1.9   \n",
       "4738  http://www.imdb.com/title/tt0341540/?ref_=fn_t...          NaN   \n",
       "5033  http://www.imdb.com/title/tt0390384/?ref_=fn_t...          1.9   \n",
       "4987  http://www.imdb.com/title/tt1570989/?ref_=fn_t...          2.4   \n",
       "4899  http://www.imdb.com/title/tt0420723/?ref_=fn_t...          1.8   \n",
       "4740  http://www.imdb.com/title/tt0377091/?ref_=fn_t...          1.9   \n",
       "5042  http://www.imdb.com/title/tt0378407/?ref_=fn_t...          1.9   \n",
       "4962  http://www.imdb.com/title/tt0307109/?ref_=fn_t...          1.9   \n",
       "4851  http://www.imdb.com/title/tt1971352/?ref_=fn_t...          2.4   \n",
       "4863  http://www.imdb.com/title/tt0368089/?ref_=fn_t...          1.9   \n",
       "4979  http://www.imdb.com/title/tt2955096/?ref_=fn_t...          1.9   \n",
       "4832  http://www.imdb.com/title/tt0468526/?ref_=fn_t...          1.7   \n",
       "4890  http://www.imdb.com/title/tt1781784/?ref_=fn_t...          2.4   \n",
       "4901  http://www.imdb.com/title/tt1211890/?ref_=fn_t...          2.4   \n",
       "4840  http://www.imdb.com/title/tt0366444/?ref_=fn_t...          2.4   \n",
       "4743  http://www.imdb.com/title/tt0326806/?ref_=fn_t...          1.9   \n",
       "4744  http://www.imdb.com/title/tt0385056/?ref_=fn_t...          1.9   \n",
       "4595  http://www.imdb.com/title/tt1334553/?ref_=fn_t...          1.9   \n",
       "4784  http://www.imdb.com/title/tt0462485/?ref_=fn_t...          1.9   \n",
       "4754  http://www.imdb.com/title/tt0266971/?ref_=fn_t...          2.4   \n",
       "4757  http://www.imdb.com/title/tt0489212/?ref_=fn_t...          NaN   \n",
       "3950  http://www.imdb.com/title/tt1464580/?ref_=fn_t...          2.4   \n",
       "4680  http://www.imdb.com/title/tt1594562/?ref_=fn_t...          2.4   \n",
       "4683  http://www.imdb.com/title/tt0308411/?ref_=fn_t...          1.8   \n",
       "\n",
       "      facenumber_in_poster  cast_total_facebook_likes  num_voted_users  \n",
       "4793                   0.0                        330           184824  \n",
       "4726                   1.0                         67            42256  \n",
       "4730                   0.0                      24419            58260  \n",
       "4855                   1.0                        139             8000  \n",
       "4864                   1.0                      34983            46813  \n",
       "4478                   1.0                       2459              910  \n",
       "4900                   7.0                      77046             2099  \n",
       "4830                   3.0                       3010            18035  \n",
       "4696                   2.0                      33734            70885  \n",
       "4891                   1.0                        964             2742  \n",
       "4857                   0.0                       1378             4662  \n",
       "4833                   1.0                        460            12241  \n",
       "4858                   2.0                        454             1489  \n",
       "4738                   0.0                        155              651  \n",
       "5033                   0.0                        368            72639  \n",
       "4987                   0.0                       2530            11816  \n",
       "4899                   0.0                         66              131  \n",
       "4740                   0.0                       2655            26407  \n",
       "5042                   0.0                        163             4285  \n",
       "4962                   1.0                        284             4117  \n",
       "4851                   0.0                       1734            24668  \n",
       "4863                   1.0                       1008             2787  \n",
       "4979                   3.0                      11642             5507  \n",
       "4832                   2.0                        132             4423  \n",
       "4890                   0.0                          2              575  \n",
       "4901                   2.0                       3021             1034  \n",
       "4840                   0.0                        185              720  \n",
       "4743                   3.0                       2555              553  \n",
       "4744                   0.0                       1440             6884  \n",
       "4595                   1.0                       1452            20176  \n",
       "4784                   0.0                       1411             5931  \n",
       "4754                   2.0                      35294             2004  \n",
       "4757                   2.0                       1047              739  \n",
       "3950                   1.0                       1038            34263  \n",
       "4680                   0.0                       1252            27260  \n",
       "4683                   0.0                        243             1661  \n",
       "\n",
       "[36 rows x 27 columns]"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Looking at the highest budget films in the \n",
    "\n",
    "df_test_lowerbudget.sort_values(by=['profit'],ascending=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Part 5: Summary\n",
    "\n",
    "In summary, using evidence from the IMDb data set, I was interested in providing SussexBudgetProductions with some recommendations on how to spend the \\\\$1.5million investment.\n",
    "\n",
    "**What did I find?**\n",
    "\n",
    "Firstly, I only looked at the films that were made 2000 and made in the USA. This was to prevent confusion with currencies within the IMDb data frame. Analysing this data frame, I found that animation films had the highest profit in general. However, these films are expensive to make. Therefore, I the filtered through by budget and found that Horror films have the highest profit, meeting our budget criteria. Within the split development data frame I found that The mean profit for movies that contain the genre Horror: \\\\$10,128,252, compared with all genres average \\\\$4,380,365.\n",
    "\n",
    "After this exploratory step, I conducted 2 hypothesis tests:\n",
    "\n",
    "1. ***If*** horror films are related to higher profit, ***then*** movies in this genre will have a higher profit than average.\n",
    "\n",
    "2. ***If*** more expensive films are related to higher profit, ***then*** movies that cost more than $750,000 will have a higher profit than average.\n",
    "\n",
    "**What does the analysis recommened?**\n",
    "\n",
    "I proved the first hypothesis to be true and the second false. Therefore, based on the data analyses, I recommend that the SussexBudgetProductions pursue making 2 films in the genre of **horror** for the USA market. However, as this conclusion is only based upon the USA market, further analysis of other countries and languages is recommended."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Submission length is 1222\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/anaconda3/lib/python3.8/site-packages/nbformat/current.py:15: UserWarning: nbformat.current is deprecated.\n",
      "\n",
      "- use nbformat for read/write/validate public API\n",
      "- use nbformat.vX directly to composing notebooks of a particular version\n",
      "\n",
      "  warnings.warn(\"\"\"nbformat.current is deprecated.\n"
     ]
    }
   ],
   "source": [
    "##This code will word count all of the markdown cells in the notebook saved at filepath\n",
    "##Running it before providing any answers shows that the questions have a word count of 437\n",
    "\n",
    "import io\n",
    "from nbformat import current\n",
    "\n",
    "#filepath=\"/content/drive/My Drive/NLE Notebooks/assessment/assignment1.ipynb\"\n",
    "filepath=\"Report1_244788_DSRM.ipynb\"\n",
    "question_count=437\n",
    "\n",
    "with io.open(filepath, 'r', encoding='utf-8') as f:\n",
    "    nb = current.read(f, 'json')\n",
    "\n",
    "word_count = 0\n",
    "for cell in nb.worksheets[0].cells:\n",
    "    if cell.cell_type == \"markdown\":\n",
    "        word_count += len(cell['source'].replace('#', '').lstrip().split(' '))\n",
    "print(\"Submission length is {}\".format(word_count-question_count))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "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": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}