convert_cat_features.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import sys\n",
    "import csv\n",
    "from time import strptime\n",
    "import json\n",
    "from datetime import datetime as dt\n",
    "from datetime import date\n",
    "from statistics import mean\n",
    "import math\n",
    "import pickle"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/stas/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:5: FutureWarning: Passing a negative integer is deprecated in version 1.0 and will not be supported in future version. Instead, use None to not limit the column width.\n",
      "  \"\"\"\n"
     ]
    }
   ],
   "source": [
    "csv.field_size_limit(sys.maxsize)\n",
    "np.set_printoptions(threshold=sys.maxsize)\n",
    "pd.options.display.max_columns = None\n",
    "pd.options.display.max_rows = 10000\n",
    "pd.set_option('display.max_colwidth', -1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('10 df.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "num_actors = 10\n",
    "def swap_cast(row):\n",
    "    actors = []\n",
    "    for i in range(1,num_actors+1):\n",
    "        actors.append(row[f'cast_{i}_name'])\n",
    "    not_empty_actors = [a for a in actors if not pd.isna(a)]\n",
    "    padded_actors = not_empty_actors + [np.nan] * (num_actors-len(not_empty_actors))\n",
    "    for i in range(num_actors):\n",
    "        row[f'cast_{i+1}_name'] = padded_actors[i]\n",
    "    return row"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_shifted_actors = df.copy()\n",
    "for i, row in df_shifted_actors.iterrows():\n",
    "    if i in range(0, df.shape[0], 100):\n",
    "        print(i)\n",
    "    df_shifted_actors.iloc[i] = swap_cast(row)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1\n",
      "15\n",
      "38\n",
      "78\n",
      "145\n",
      "251\n",
      "390\n",
      "542\n",
      "828\n",
      "1614\n"
     ]
    }
   ],
   "source": [
    "for i in range(1, 11):\n",
    "    print(len([a for a in df_shifted_actors[f'cast_{i}_name'] if pd.isna(a)]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 797,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_shifted_actors.to_csv('10 1 df_shifted_actors.csv', mode='w+', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 312,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_shifted_actors = pd.read_csv('10 1 df_shifted_actors.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 314,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(7536, 201)"
      ]
     },
     "execution_count": 314,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_shifted_actors.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 321,
   "metadata": {},
   "outputs": [],
   "source": [
    "ids_to_delete = []\n",
    "genre_cols = [c for c in df.columns if 'genre' in c]\n",
    "\n",
    "def to_delete(movie): \n",
    "    return not sum([1 for col in genre_cols if movie[col]]) or pd.isna(movie.overview)\n",
    "\n",
    "for i, movie in added_collection_info.iterrows():\n",
    "    if to_delete(movie):\n",
    "        ids_to_delete.append(movie.id)\n",
    "\n",
    "indexes = df_shifted_actors.loc[df_shifted_actors.id.isin(ids_to_delete)].index\n",
    "df_deleted = df_shifted_actors.drop(indexes, axis=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 323,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_deleted.to_csv('10 2 df_deleted.csv', mode='w+', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 324,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_deleted = pd.read_csv('10 2 df_deleted.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 325,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_8_actors = df_deleted.copy()\n",
    "for i in range(9, 11):\n",
    "    df_8_actors.drop([f'cast_{i}_name', f'cast_{i}_gender'], axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 326,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(7494, 197)"
      ]
     },
     "execution_count": 326,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_8_actors.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 327,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['budget',\n",
       " 'id',\n",
       " 'original_language',\n",
       " 'original_title',\n",
       " 'overview',\n",
       " 'revenue',\n",
       " 'runtime',\n",
       " 'spoken_languages',\n",
       " 'tagline',\n",
       " 'title',\n",
       " 'year',\n",
       " 'month',\n",
       " 'day',\n",
       " 'weekend',\n",
       " 'collection_name',\n",
       " 'cast_1_name',\n",
       " 'cast_1_gender',\n",
       " 'cast_2_name',\n",
       " 'cast_2_gender',\n",
       " 'cast_3_name',\n",
       " 'cast_3_gender',\n",
       " 'cast_4_name',\n",
       " 'cast_4_gender',\n",
       " 'cast_5_name',\n",
       " 'cast_5_gender',\n",
       " 'cast_6_name',\n",
       " 'cast_6_gender',\n",
       " 'cast_7_name',\n",
       " 'cast_7_gender',\n",
       " 'cast_8_name',\n",
       " 'cast_8_gender',\n",
       " 'crew__lighting__gaffer',\n",
       " 'crew__sound__boom_operator',\n",
       " 'crew__sound__dialogue_editor',\n",
       " 'crew__sound__foley',\n",
       " 'crew__sound__music',\n",
       " 'crew__sound__music_editor',\n",
       " 'crew__sound__music_supervisor',\n",
       " 'crew__sound__original_music_composer',\n",
       " 'crew__sound__sound_designer',\n",
       " 'crew__sound__sound_effects_editor',\n",
       " 'crew__sound__sound_mixer',\n",
       " 'crew__sound__sound_re_recording_mixer',\n",
       " 'crew__sound__supervising_sound_editor',\n",
       " 'crew__directing__director__1',\n",
       " 'crew__directing__first_assistant_director',\n",
       " 'crew__directing__script_supervisor',\n",
       " 'crew__directing__second_assistant_director',\n",
       " 'crew__production__associate_producer',\n",
       " 'crew__production__casting',\n",
       " 'crew__production__casting_associate',\n",
       " 'crew__production__co_producer',\n",
       " 'crew__production__executive_producer__1',\n",
       " 'crew__production__executive_producer__2',\n",
       " 'crew__production__line_producer',\n",
       " 'crew__production__location_manager',\n",
       " 'crew__production__producer__1',\n",
       " 'crew__production__producer__2',\n",
       " 'crew__production__producer__3',\n",
       " 'crew__production__production_coordinator',\n",
       " 'crew__production__production_manager',\n",
       " 'crew__production__unit_production_manager',\n",
       " 'crew__editing__editor__1',\n",
       " 'crew__costume__costume_designer',\n",
       " 'crew__costume__costume_supervisor',\n",
       " 'crew__costume__hairstylist',\n",
       " 'crew__costume__key_hair_stylist',\n",
       " 'crew__costume__makeup_artist',\n",
       " 'crew__costume__makeup_department_head',\n",
       " 'crew__costume__set_costumer',\n",
       " 'crew__crew__post_production_supervisor',\n",
       " 'crew__crew__special_effects_coordinator',\n",
       " 'crew__crew__stunt_coordinator',\n",
       " 'crew__crew__stunts',\n",
       " 'crew__crew__visual_effects_editor',\n",
       " 'crew__writing__novel',\n",
       " 'crew__writing__screenplay__1',\n",
       " 'crew__writing__story',\n",
       " 'crew__writing__writer',\n",
       " 'crew__art__art_department_coordinator',\n",
       " 'crew__art__art_direction',\n",
       " 'crew__art__construction_coordinator',\n",
       " 'crew__art__production_design',\n",
       " 'crew__art__property_master',\n",
       " 'crew__art__set_decoration',\n",
       " 'crew__art__set_designer',\n",
       " 'crew__visualeffects__special_effects_supervisor',\n",
       " 'crew__visualeffects__visual_effects_producer',\n",
       " 'crew__visualeffects__visual_effects_supervisor',\n",
       " 'crew__camera__camera_operator',\n",
       " 'crew__camera__director_of_photography',\n",
       " 'crew__camera__key_grip',\n",
       " 'crew__camera__steadicam_operator',\n",
       " 'crew__camera__still_photographer',\n",
       " 'genre__war',\n",
       " 'genre__western',\n",
       " 'genre__mystery',\n",
       " 'genre__music',\n",
       " 'genre__crime',\n",
       " 'genre__romance',\n",
       " 'genre__action',\n",
       " 'genre__adventure',\n",
       " 'genre__thriller',\n",
       " 'genre__animation',\n",
       " 'genre__family',\n",
       " 'genre__drama',\n",
       " 'genre__comedy',\n",
       " 'genre__documentary',\n",
       " 'genre__history',\n",
       " 'genre__fantasy',\n",
       " 'genre__horror',\n",
       " 'production_company_1',\n",
       " 'production_company_2',\n",
       " 'production_company_3',\n",
       " 'production_company_4',\n",
       " 'production_company_5',\n",
       " 'country__rs',\n",
       " 'country__su',\n",
       " 'country__do',\n",
       " 'country__bo',\n",
       " 'country__ph',\n",
       " 'country__pe',\n",
       " 'country__id',\n",
       " 'country__gr',\n",
       " 'country__hn',\n",
       " 'country__nl',\n",
       " 'country__ee',\n",
       " 'country__ug',\n",
       " 'country__uy',\n",
       " 'country__ir',\n",
       " 'country__lb',\n",
       " 'country__pk',\n",
       " 'country__ua',\n",
       " 'country__eg',\n",
       " 'country__is',\n",
       " 'country__co',\n",
       " 'country__sk',\n",
       " 'country__bw',\n",
       " 'country__es',\n",
       " 'country__se',\n",
       " 'country__jp',\n",
       " 'country__np',\n",
       " 'country__tw',\n",
       " 'country__ie',\n",
       " 'country__lu',\n",
       " 'country__us',\n",
       " 'country__vn',\n",
       " 'country__ro',\n",
       " 'country__mn',\n",
       " 'country__cl',\n",
       " 'country__hu',\n",
       " 'country__br',\n",
       " 'country__ae',\n",
       " 'country__kr',\n",
       " 'country__be',\n",
       " 'country__ca',\n",
       " 'country__sg',\n",
       " 'country__bg',\n",
       " 'country__de',\n",
       " 'country__pl',\n",
       " 'country__mv',\n",
       " 'country__cn',\n",
       " 'country__in',\n",
       " 'country__th',\n",
       " 'country__fr',\n",
       " 'country__ru',\n",
       " 'country__dk',\n",
       " 'country__af',\n",
       " 'country__xg',\n",
       " 'country__it',\n",
       " 'country__ge',\n",
       " 'country__tr',\n",
       " 'country__za',\n",
       " 'country__ve',\n",
       " 'country__lk',\n",
       " 'country__hr',\n",
       " 'country__ng',\n",
       " 'country__ar',\n",
       " 'country__ba',\n",
       " 'country__il',\n",
       " 'country__mx',\n",
       " 'country__bd',\n",
       " 'country__my',\n",
       " 'country__nz',\n",
       " 'country__no',\n",
       " 'country__cz',\n",
       " 'country__hk',\n",
       " 'country__au',\n",
       " 'country__gb',\n",
       " 'country__lv',\n",
       " 'country__fi',\n",
       " 'profitability',\n",
       " 'day_sin',\n",
       " 'day_cos',\n",
       " 'month_sin',\n",
       " 'month_cos',\n",
       " 'collection_exists']"
      ]
     },
     "execution_count": 327,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(df_8_actors.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 328,
   "metadata": {},
   "outputs": [],
   "source": [
    "actors = []\n",
    "for i in range(1, 9):\n",
    "    actors.extend(df_8_actors[f'cast_{i}_name'])\n",
    "all_actors = list(set(actors))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 329,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "23891"
      ]
     },
     "execution_count": 329,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(all_actors)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 304,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_real_columns(name_prefix, name_suffix, num_columns):\n",
    "    return [f'{name_prefix}{j}{name_suffix}' for j in range(1, num_columns+1)]\n",
    "\n",
    "def get_date_from_movie(movie):\n",
    "    return date(movie['year'], movie['month'], movie['day'])\n",
    "\n",
    "def get_info_df_movies_per_value_range_columns(df, columns):\n",
    "    result = {}\n",
    "    for i, row in df.iterrows():\n",
    "        if i in range(0, df.shape[0], 100):\n",
    "            print(i)\n",
    "        for col in columns:\n",
    "            value = row[col]\n",
    "            if not pd.isna(value):\n",
    "                if value in list(result.keys()):\n",
    "                    result[value]['movies'] = result[value]['movies'].append(df.iloc[[i]])\n",
    "                else:\n",
    "                    result[value] = {'movies': df.iloc[[i]]}\n",
    "    return result\n",
    "\n",
    "def calculate_info_per_previous_movies_per_value(df, info_dict, calc_budget=False, calc_movies_before=False, \n",
    "                                                 calc_experience=False, calc_profitability=False, calc_revenue=False):\n",
    "    smooth_parameter = 5\n",
    "    mean_profitability = df['profitability'].mean()\n",
    "    for value_name in info_dict:\n",
    "        value = info_dict[value_name]\n",
    "        value['avg_profit'] = {}\n",
    "        if calc_budget:\n",
    "            value['avg_budget'] = {}\n",
    "        if calc_experience:\n",
    "            value['experience'] = {}\n",
    "        if calc_profitability:\n",
    "            value['avg_profitability'] = {}\n",
    "        if calc_revenue:\n",
    "            value['avg_revenue'] = {}\n",
    "        if calc_movies_before:\n",
    "            value['movies_before'] = {}\n",
    "\n",
    "        movies = value['movies']\n",
    "        for movie_index, movie in movies.iterrows():\n",
    "            current_date = get_date_from_movie(movie)\n",
    "            str_date = str(current_date)\n",
    "            if calc_experience and str_date not in list(value['experience'].keys()):\n",
    "                value['experience'][str_date] = movie['year'] - movies.year.min()\n",
    "            if str_date not in list(value['avg_profit'].keys()):\n",
    "                movies_before = movies[movies.apply(lambda row: (date(row.year, row.month, row.day) < current_date), axis=1)]\n",
    "                if not movies_before.empty:\n",
    "                    value['avg_profit'][str_date] = get_average_profit(movies_before)\n",
    "                    if calc_movies_before:\n",
    "                        value['movies_before'][str_date] = movies_before.shape[0]\n",
    "                    if calc_revenue:\n",
    "                        value['avg_revenue'][str_date] = movies_before['revenue'].mean()                        \n",
    "                    if calc_budget:\n",
    "                        value['avg_budget'][str_date] = movies_before['budget'].mean()\n",
    "                    if calc_profitability:\n",
    "                        value['avg_profitability'][str_date] = smooth_mean_profitability(movies_before, mean_profitability, smooth_parameter)\n",
    "                    \n",
    "                    \n",
    "def get_columns_from_info_dict(df, info_dict, real_columns, new_column_prefix='', nested_info=False):\n",
    "    def get_first_key(d):\n",
    "        return d[list(d.keys())[0]]\n",
    "    \n",
    "    new_columns_data = {}\n",
    "    for index, real_column in enumerate(real_columns):\n",
    "        print(real_column)\n",
    "        root = info_dict[real_column] if nested_info else info_dict\n",
    "        info_names = [key for key in get_first_key(root).keys() if key != 'movies']\n",
    "        new_column_names = [f'{real_column}_{key}' if nested_info or len(real_columns) == 1 else f'{new_column_prefix}_{index+1}_{key}' for key in info_names] \n",
    "            \n",
    "        for new_column_name in new_column_names:\n",
    "            new_columns_data[new_column_name] = []\n",
    "\n",
    "        for movie_index, movie in df.iterrows():\n",
    "            value = movie[real_column]\n",
    "            str_date = str(get_date_from_movie(movie))\n",
    "            if pd.isna(value):\n",
    "                for col in new_column_names:\n",
    "                    new_columns_data[col].append(np.nan)\n",
    "            else:\n",
    "                for name_index, new_column_name in enumerate(new_column_names):\n",
    "                    year_info = root[value][info_names[name_index]].get(str_date, np.nan)\n",
    "                    new_columns_data[new_column_name].append(year_info)\n",
    "    return new_columns_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 305,
   "metadata": {},
   "outputs": [],
   "source": [
    "def smooth_mean(mean, counts, overall_mean, m):\n",
    "    return (counts * mean + m * overall_mean)/(counts + m)\n",
    "\n",
    "def smooth_field(df, field, overall_mean, m):\n",
    "    counts = df.shape[0]\n",
    "    mean = df[field].mean()\n",
    "    return smooth_mean(mean, counts, overall_mean, m)\n",
    "\n",
    "def smooth_mean_profitability(df, mean_profitability, m):\n",
    "    return smooth_field(df, 'profitability', mean_profitability, m)\n",
    "\n",
    "def get_average_profit(df):\n",
    "    return (df['revenue'] - df['budget']).mean()\n",
    "\n",
    "def get_actor_experience(df, year):\n",
    "    return year - df.year.min()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 335,
   "metadata": {},
   "outputs": [],
   "source": [
    "real_columns = get_real_columns('cast_', '_name', 8)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_actors_info = get_info_df_movies_per_value_range_columns(df_8_actors, real_columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 337,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_actors_info_copy = all_actors_info.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 338,
   "metadata": {},
   "outputs": [],
   "source": [
    "calculate_info_per_previous_movies_per_value(df_8_actors, all_actors_info_copy, calc_movies_before=True, calc_budget=True, calc_experience=True, calc_profitability=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 339,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "cast_1_name\n",
      "cast_2_name\n",
      "cast_3_name\n",
      "cast_4_name\n",
      "cast_5_name\n",
      "cast_6_name\n",
      "cast_7_name\n",
      "cast_8_name\n"
     ]
    }
   ],
   "source": [
    "cast_columns = get_columns_from_info_dict(df_8_actors, all_actors_info_copy, real_columns, new_column_prefix='cast')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 340,
   "metadata": {},
   "outputs": [],
   "source": [
    "added_actors_info = df_8_actors.copy()\n",
    "for column in cast_columns.keys():\n",
    "    added_actors_info[column] = cast_columns[column]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 341,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(7494, 237)"
      ]
     },
     "execution_count": 341,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "added_actors_info.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 343,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1693"
      ]
     },
     "execution_count": 343,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len([a for a in added_actors_info.cast_1_avg_budget if pd.isna(a)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 344,
   "metadata": {},
   "outputs": [],
   "source": [
    "genders = {}\n",
    "for i in range(1, 9):\n",
    "    genders[f'cast_{i}_male'] = []\n",
    "    genders[f'cast_{i}_female'] = []\n",
    "    for movie_index, movie in added_actors_info.iterrows():\n",
    "        genders[f'cast_{i}_male'].append(1 if movie[f'cast_{i}_gender'] == 2 else 0)\n",
    "        genders[f'cast_{i}_female'].append(1 if movie[f'cast_{i}_gender'] == 1 else 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 345,
   "metadata": {},
   "outputs": [],
   "source": [
    "opened_gender = added_actors_info.copy()\n",
    "for column in genders.keys():\n",
    "    opened_gender[column] = genders[column]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 346,
   "metadata": {},
   "outputs": [],
   "source": [
    "for column in [col for col in opened_gender.columns if 'gender' in col]:\n",
    "    opened_gender = opened_gender.drop(column, axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "sorted_actors = sorted(actors_movies, key=lambda actor: all_actors_info[actor]['movies'].shape[0], reverse=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 696,
   "metadata": {},
   "outputs": [],
   "source": [
    "number_of_movies_per_actor = [all_actors_info[actor]['movies'].shape[0] for actor in sorted_actors]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 697,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.893076795212766"
      ]
     },
     "execution_count": 697,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len([num for num in number_of_movies_per_actor if num <5])/len(number_of_movies_per_actor)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 347,
   "metadata": {},
   "outputs": [],
   "source": [
    "crew_columns_list = [column for column in list(opened_gender.columns) if 'crew' in column]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_crew_info = {}\n",
    "for crew_column in crew_columns_list:\n",
    "    all_crew_info[crew_column] = get_info_df_movies_per_value_range_columns(opened_gender, [crew_column])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 349,
   "metadata": {},
   "outputs": [],
   "source": [
    "for crew_column in crew_columns_list:\n",
    "    calculate_info_per_previous_movies_per_value(opened_gender, all_crew_info[crew_column], calc_movies_before=True, calc_budget=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "crew_columns = get_columns_from_info_dict(opened_gender, all_crew_info, crew_columns_list, nested_info=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 351,
   "metadata": {},
   "outputs": [],
   "source": [
    "opened_crew = opened_gender.copy()\n",
    "for column in list(crew_columns.keys()):\n",
    "    opened_crew[column] = crew_columns[column]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 352,
   "metadata": {},
   "outputs": [],
   "source": [
    "crew_extra_columns = [c for c in opened_crew.columns if 'crew' in c and ('avg' in c or 'movies_before' in c)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 353,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "4332  crew__camera__director_of_photography_avg_profit\n",
      "4332  crew__camera__director_of_photography_avg_budget\n",
      "4332  crew__camera__director_of_photography_movies_before\n",
      "4278  crew__editing__editor__1_avg_profit\n",
      "4278  crew__editing__editor__1_avg_budget\n",
      "4278  crew__editing__editor__1_movies_before\n",
      "4048  crew__directing__director__1_avg_profit\n",
      "4048  crew__directing__director__1_avg_budget\n",
      "4048  crew__directing__director__1_movies_before\n",
      "3665  crew__production__producer__1_avg_profit\n",
      "3665  crew__production__producer__1_avg_budget\n",
      "3665  crew__production__producer__1_movies_before\n",
      "3529  crew__sound__original_music_composer_avg_profit\n",
      "3529  crew__sound__original_music_composer_avg_budget\n",
      "3529  crew__sound__original_music_composer_movies_before\n",
      "3385  crew__production__casting_avg_profit\n",
      "3385  crew__production__casting_avg_budget\n",
      "3385  crew__production__casting_movies_before\n",
      "3242  crew__art__production_design_avg_profit\n",
      "3242  crew__art__production_design_avg_budget\n",
      "3242  crew__art__production_design_movies_before\n",
      "3132  crew__costume__costume_designer_avg_profit\n",
      "3132  crew__costume__costume_designer_avg_budget\n",
      "3132  crew__costume__costume_designer_movies_before\n",
      "2364  crew__art__set_decoration_avg_profit\n",
      "2364  crew__art__set_decoration_avg_budget\n",
      "2364  crew__art__set_decoration_movies_before\n",
      "2042  crew__writing__screenplay__1_avg_profit\n",
      "2042  crew__writing__screenplay__1_avg_budget\n",
      "2042  crew__writing__screenplay__1_movies_before\n",
      "1997  crew__art__art_direction_avg_profit\n",
      "1997  crew__art__art_direction_avg_budget\n",
      "1997  crew__art__art_direction_movies_before\n",
      "1890  crew__production__executive_producer__1_avg_profit\n",
      "1890  crew__production__executive_producer__1_avg_budget\n",
      "1890  crew__production__executive_producer__1_movies_before\n",
      "1692  crew__directing__script_supervisor_avg_profit\n",
      "1692  crew__directing__script_supervisor_avg_budget\n",
      "1692  crew__directing__script_supervisor_movies_before\n",
      "1559  crew__camera__still_photographer_avg_profit\n",
      "1559  crew__camera__still_photographer_avg_budget\n",
      "1559  crew__camera__still_photographer_movies_before\n",
      "1476  crew__sound__sound_re_recording_mixer_avg_profit\n",
      "1476  crew__sound__sound_re_recording_mixer_avg_budget\n",
      "1476  crew__sound__sound_re_recording_mixer_movies_before\n",
      "1323  crew__sound__supervising_sound_editor_avg_profit\n",
      "1323  crew__sound__supervising_sound_editor_avg_budget\n",
      "1323  crew__sound__supervising_sound_editor_movies_before\n",
      "1245  crew__sound__music_editor_avg_profit\n",
      "1245  crew__sound__music_editor_avg_budget\n",
      "1245  crew__sound__music_editor_movies_before\n",
      "1118  crew__crew__stunt_coordinator_avg_profit\n",
      "1118  crew__crew__stunt_coordinator_avg_budget\n",
      "1118  crew__crew__stunt_coordinator_movies_before\n",
      "1046  crew__costume__makeup_artist_avg_profit\n",
      "1046  crew__costume__makeup_artist_avg_budget\n",
      "1046  crew__costume__makeup_artist_movies_before\n",
      "970  crew__art__property_master_avg_profit\n",
      "970  crew__art__property_master_avg_budget\n",
      "970  crew__art__property_master_movies_before\n",
      "888  crew__sound__sound_effects_editor_avg_profit\n",
      "888  crew__sound__sound_effects_editor_avg_budget\n",
      "888  crew__sound__sound_effects_editor_movies_before\n",
      "868  crew__visualeffects__visual_effects_supervisor_avg_profit\n",
      "868  crew__visualeffects__visual_effects_supervisor_avg_budget\n",
      "868  crew__visualeffects__visual_effects_supervisor_movies_before\n",
      "852  crew__sound__sound_designer_avg_profit\n",
      "852  crew__sound__sound_designer_avg_budget\n",
      "852  crew__sound__sound_designer_movies_before\n",
      "819  crew__production__producer__2_avg_profit\n",
      "819  crew__production__producer__2_avg_budget\n",
      "819  crew__production__producer__2_movies_before\n",
      "778  crew__camera__steadicam_operator_avg_profit\n",
      "778  crew__camera__steadicam_operator_avg_budget\n",
      "778  crew__camera__steadicam_operator_movies_before\n",
      "773  crew__costume__costume_supervisor_avg_profit\n",
      "773  crew__costume__costume_supervisor_avg_budget\n",
      "773  crew__costume__costume_supervisor_movies_before\n",
      "751  crew__camera__camera_operator_avg_profit\n",
      "751  crew__camera__camera_operator_avg_budget\n",
      "751  crew__camera__camera_operator_movies_before\n",
      "724  crew__costume__hairstylist_avg_profit\n",
      "724  crew__costume__hairstylist_avg_budget\n",
      "724  crew__costume__hairstylist_movies_before\n",
      "701  crew__sound__dialogue_editor_avg_profit\n",
      "701  crew__sound__dialogue_editor_avg_budget\n",
      "701  crew__sound__dialogue_editor_movies_before\n",
      "694  crew__lighting__gaffer_avg_profit\n",
      "694  crew__lighting__gaffer_avg_budget\n",
      "694  crew__lighting__gaffer_movies_before\n",
      "691  crew__art__construction_coordinator_avg_profit\n",
      "691  crew__art__construction_coordinator_avg_budget\n",
      "691  crew__art__construction_coordinator_movies_before\n",
      "687  crew__sound__music_supervisor_avg_profit\n",
      "687  crew__sound__music_supervisor_avg_budget\n",
      "687  crew__sound__music_supervisor_movies_before\n",
      "647  crew__costume__makeup_department_head_avg_profit\n",
      "647  crew__costume__makeup_department_head_avg_budget\n",
      "647  crew__costume__makeup_department_head_movies_before\n",
      "619  crew__sound__music_avg_profit\n",
      "619  crew__sound__music_avg_budget\n",
      "619  crew__sound__music_movies_before\n",
      "594  crew__sound__boom_operator_avg_profit\n",
      "594  crew__sound__boom_operator_avg_budget\n",
      "594  crew__sound__boom_operator_movies_before\n",
      "592  crew__crew__special_effects_coordinator_avg_profit\n",
      "592  crew__crew__special_effects_coordinator_avg_budget\n",
      "592  crew__crew__special_effects_coordinator_movies_before\n",
      "591  crew__art__art_department_coordinator_avg_profit\n",
      "591  crew__art__art_department_coordinator_avg_budget\n",
      "591  crew__art__art_department_coordinator_movies_before\n",
      "570  crew__sound__sound_mixer_avg_profit\n",
      "570  crew__sound__sound_mixer_avg_budget\n",
      "570  crew__sound__sound_mixer_movies_before\n",
      "557  crew__sound__foley_avg_profit\n",
      "557  crew__sound__foley_avg_budget\n",
      "557  crew__sound__foley_movies_before\n",
      "537  crew__visualeffects__visual_effects_producer_avg_profit\n",
      "537  crew__visualeffects__visual_effects_producer_avg_budget\n",
      "537  crew__visualeffects__visual_effects_producer_movies_before\n",
      "516  crew__writing__writer_avg_profit\n",
      "516  crew__writing__writer_avg_budget\n",
      "516  crew__writing__writer_movies_before\n",
      "496  crew__directing__first_assistant_director_avg_profit\n",
      "496  crew__directing__first_assistant_director_avg_budget\n",
      "496  crew__directing__first_assistant_director_movies_before\n",
      "455  crew__crew__stunts_avg_profit\n",
      "455  crew__crew__stunts_avg_budget\n",
      "455  crew__crew__stunts_movies_before\n",
      "437  crew__production__casting_associate_avg_profit\n",
      "437  crew__production__casting_associate_avg_budget\n",
      "437  crew__production__casting_associate_movies_before\n",
      "434  crew__production__location_manager_avg_profit\n",
      "434  crew__production__location_manager_avg_budget\n",
      "434  crew__production__location_manager_movies_before\n",
      "432  crew__production__unit_production_manager_avg_profit\n",
      "432  crew__production__unit_production_manager_avg_budget\n",
      "432  crew__production__unit_production_manager_movies_before\n",
      "427  crew__crew__post_production_supervisor_avg_profit\n",
      "427  crew__crew__post_production_supervisor_avg_budget\n",
      "427  crew__crew__post_production_supervisor_movies_before\n",
      "422  crew__production__executive_producer__2_avg_profit\n",
      "422  crew__production__executive_producer__2_avg_budget\n",
      "422  crew__production__executive_producer__2_movies_before\n",
      "416  crew__visualeffects__special_effects_supervisor_avg_profit\n",
      "416  crew__visualeffects__special_effects_supervisor_avg_budget\n",
      "416  crew__visualeffects__special_effects_supervisor_movies_before\n",
      "404  crew__crew__visual_effects_editor_avg_profit\n",
      "404  crew__crew__visual_effects_editor_avg_budget\n",
      "404  crew__crew__visual_effects_editor_movies_before\n",
      "385  crew__camera__key_grip_avg_profit\n",
      "385  crew__camera__key_grip_avg_budget\n",
      "385  crew__camera__key_grip_movies_before\n",
      "367  crew__art__set_designer_avg_profit\n",
      "367  crew__art__set_designer_avg_budget\n",
      "367  crew__art__set_designer_movies_before\n",
      "335  crew__costume__key_hair_stylist_avg_profit\n",
      "335  crew__costume__key_hair_stylist_avg_budget\n",
      "335  crew__costume__key_hair_stylist_movies_before\n",
      "306  crew__writing__novel_avg_profit\n",
      "306  crew__writing__novel_avg_budget\n",
      "306  crew__writing__novel_movies_before\n",
      "300  crew__production__co_producer_avg_profit\n",
      "300  crew__production__co_producer_avg_budget\n",
      "300  crew__production__co_producer_movies_before\n",
      "285  crew__costume__set_costumer_avg_profit\n",
      "285  crew__costume__set_costumer_avg_budget\n",
      "285  crew__costume__set_costumer_movies_before\n",
      "268  crew__production__associate_producer_avg_profit\n",
      "268  crew__production__associate_producer_avg_budget\n",
      "268  crew__production__associate_producer_movies_before\n",
      "264  crew__production__production_coordinator_avg_profit\n",
      "264  crew__production__production_coordinator_avg_budget\n",
      "264  crew__production__production_coordinator_movies_before\n",
      "243  crew__production__producer__3_avg_profit\n",
      "243  crew__production__producer__3_avg_budget\n",
      "243  crew__production__producer__3_movies_before\n",
      "204  crew__directing__second_assistant_director_avg_profit\n",
      "204  crew__directing__second_assistant_director_avg_budget\n",
      "204  crew__directing__second_assistant_director_movies_before\n",
      "178  crew__writing__story_avg_profit\n",
      "178  crew__writing__story_avg_budget\n",
      "178  crew__writing__story_movies_before\n",
      "153  crew__production__line_producer_avg_profit\n",
      "153  crew__production__line_producer_avg_budget\n",
      "153  crew__production__line_producer_movies_before\n",
      "147  crew__production__production_manager_avg_profit\n",
      "147  crew__production__production_manager_avg_budget\n",
      "147  crew__production__production_manager_movies_before\n"
     ]
    }
   ],
   "source": [
    "crew_count = {}\n",
    "for col in crew_extra_columns:\n",
    "    crew_count[col] = len([p for p in opened_crew[col] if not pd.isna(p)])\n",
    "\n",
    "sorted_crew = sorted(crew_count, key=lambda job: crew_count[job], reverse=True)\n",
    "for job in sorted_crew:\n",
    "    print(f'{crew_count[job]}  {job}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 354,
   "metadata": {},
   "outputs": [],
   "source": [
    "jobs_to_delete = [job for job in sorted_crew if crew_count[job] < 756]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 355,
   "metadata": {},
   "outputs": [],
   "source": [
    "jobs_to_delete.extend(list(set([job.split('_avg')[0] for job in jobs_to_delete])))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 356,
   "metadata": {},
   "outputs": [],
   "source": [
    "columns_to_keep = [col for col in opened_crew.columns if col not in jobs_to_delete]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 357,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_cast_crew = opened_crew[columns_to_keep].copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 358,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_cast_crew.to_csv('11 cast_crew.csv', mode='w+', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 359,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['budget',\n",
       " 'id',\n",
       " 'original_language',\n",
       " 'original_title',\n",
       " 'overview',\n",
       " 'revenue',\n",
       " 'runtime',\n",
       " 'spoken_languages',\n",
       " 'tagline',\n",
       " 'title',\n",
       " 'year',\n",
       " 'month',\n",
       " 'day',\n",
       " 'weekend',\n",
       " 'collection_name',\n",
       " 'cast_1_name',\n",
       " 'cast_2_name',\n",
       " 'cast_3_name',\n",
       " 'cast_4_name',\n",
       " 'cast_5_name',\n",
       " 'cast_6_name',\n",
       " 'cast_7_name',\n",
       " 'cast_8_name',\n",
       " 'crew__sound__music_editor',\n",
       " 'crew__sound__original_music_composer',\n",
       " 'crew__sound__sound_designer',\n",
       " 'crew__sound__sound_effects_editor',\n",
       " 'crew__sound__sound_re_recording_mixer',\n",
       " 'crew__sound__supervising_sound_editor',\n",
       " 'crew__directing__director__1',\n",
       " 'crew__directing__script_supervisor',\n",
       " 'crew__production__casting',\n",
       " 'crew__production__executive_producer__1',\n",
       " 'crew__production__producer__1',\n",
       " 'crew__production__producer__2',\n",
       " 'crew__editing__editor__1',\n",
       " 'crew__costume__costume_designer',\n",
       " 'crew__costume__costume_supervisor',\n",
       " 'crew__costume__makeup_artist',\n",
       " 'crew__crew__stunt_coordinator',\n",
       " 'crew__writing__screenplay__1',\n",
       " 'crew__art__art_direction',\n",
       " 'crew__art__production_design',\n",
       " 'crew__art__property_master',\n",
       " 'crew__art__set_decoration',\n",
       " 'crew__visualeffects__visual_effects_supervisor',\n",
       " 'crew__camera__director_of_photography',\n",
       " 'crew__camera__steadicam_operator',\n",
       " 'crew__camera__still_photographer',\n",
       " 'genre__war',\n",
       " 'genre__western',\n",
       " 'genre__mystery',\n",
       " 'genre__music',\n",
       " 'genre__crime',\n",
       " 'genre__romance',\n",
       " 'genre__action',\n",
       " 'genre__adventure',\n",
       " 'genre__thriller',\n",
       " 'genre__animation',\n",
       " 'genre__family',\n",
       " 'genre__drama',\n",
       " 'genre__comedy',\n",
       " 'genre__documentary',\n",
       " 'genre__history',\n",
       " 'genre__fantasy',\n",
       " 'genre__horror',\n",
       " 'production_company_1',\n",
       " 'production_company_2',\n",
       " 'production_company_3',\n",
       " 'production_company_4',\n",
       " 'production_company_5',\n",
       " 'country__rs',\n",
       " 'country__su',\n",
       " 'country__do',\n",
       " 'country__bo',\n",
       " 'country__ph',\n",
       " 'country__pe',\n",
       " 'country__id',\n",
       " 'country__gr',\n",
       " 'country__hn',\n",
       " 'country__nl',\n",
       " 'country__ee',\n",
       " 'country__ug',\n",
       " 'country__uy',\n",
       " 'country__ir',\n",
       " 'country__lb',\n",
       " 'country__pk',\n",
       " 'country__ua',\n",
       " 'country__eg',\n",
       " 'country__is',\n",
       " 'country__co',\n",
       " 'country__sk',\n",
       " 'country__bw',\n",
       " 'country__es',\n",
       " 'country__se',\n",
       " 'country__jp',\n",
       " 'country__np',\n",
       " 'country__tw',\n",
       " 'country__ie',\n",
       " 'country__lu',\n",
       " 'country__us',\n",
       " 'country__vn',\n",
       " 'country__ro',\n",
       " 'country__mn',\n",
       " 'country__cl',\n",
       " 'country__hu',\n",
       " 'country__br',\n",
       " 'country__ae',\n",
       " 'country__kr',\n",
       " 'country__be',\n",
       " 'country__ca',\n",
       " 'country__sg',\n",
       " 'country__bg',\n",
       " 'country__de',\n",
       " 'country__pl',\n",
       " 'country__mv',\n",
       " 'country__cn',\n",
       " 'country__in',\n",
       " 'country__th',\n",
       " 'country__fr',\n",
       " 'country__ru',\n",
       " 'country__dk',\n",
       " 'country__af',\n",
       " 'country__xg',\n",
       " 'country__it',\n",
       " 'country__ge',\n",
       " 'country__tr',\n",
       " 'country__za',\n",
       " 'country__ve',\n",
       " 'country__lk',\n",
       " 'country__hr',\n",
       " 'country__ng',\n",
       " 'country__ar',\n",
       " 'country__ba',\n",
       " 'country__il',\n",
       " 'country__mx',\n",
       " 'country__bd',\n",
       " 'country__my',\n",
       " 'country__nz',\n",
       " 'country__no',\n",
       " 'country__cz',\n",
       " 'country__hk',\n",
       " 'country__au',\n",
       " 'country__gb',\n",
       " 'country__lv',\n",
       " 'country__fi',\n",
       " 'profitability',\n",
       " 'day_sin',\n",
       " 'day_cos',\n",
       " 'month_sin',\n",
       " 'month_cos',\n",
       " 'collection_exists',\n",
       " 'cast_1_avg_profit',\n",
       " 'cast_1_avg_budget',\n",
       " 'cast_1_experience',\n",
       " 'cast_1_avg_profitability',\n",
       " 'cast_1_movies_before',\n",
       " 'cast_2_avg_profit',\n",
       " 'cast_2_avg_budget',\n",
       " 'cast_2_experience',\n",
       " 'cast_2_avg_profitability',\n",
       " 'cast_2_movies_before',\n",
       " 'cast_3_avg_profit',\n",
       " 'cast_3_avg_budget',\n",
       " 'cast_3_experience',\n",
       " 'cast_3_avg_profitability',\n",
       " 'cast_3_movies_before',\n",
       " 'cast_4_avg_profit',\n",
       " 'cast_4_avg_budget',\n",
       " 'cast_4_experience',\n",
       " 'cast_4_avg_profitability',\n",
       " 'cast_4_movies_before',\n",
       " 'cast_5_avg_profit',\n",
       " 'cast_5_avg_budget',\n",
       " 'cast_5_experience',\n",
       " 'cast_5_avg_profitability',\n",
       " 'cast_5_movies_before',\n",
       " 'cast_6_avg_profit',\n",
       " 'cast_6_avg_budget',\n",
       " 'cast_6_experience',\n",
       " 'cast_6_avg_profitability',\n",
       " 'cast_6_movies_before',\n",
       " 'cast_7_avg_profit',\n",
       " 'cast_7_avg_budget',\n",
       " 'cast_7_experience',\n",
       " 'cast_7_avg_profitability',\n",
       " 'cast_7_movies_before',\n",
       " 'cast_8_avg_profit',\n",
       " 'cast_8_avg_budget',\n",
       " 'cast_8_experience',\n",
       " 'cast_8_avg_profitability',\n",
       " 'cast_8_movies_before',\n",
       " 'cast_1_male',\n",
       " 'cast_1_female',\n",
       " 'cast_2_male',\n",
       " 'cast_2_female',\n",
       " 'cast_3_male',\n",
       " 'cast_3_female',\n",
       " 'cast_4_male',\n",
       " 'cast_4_female',\n",
       " 'cast_5_male',\n",
       " 'cast_5_female',\n",
       " 'cast_6_male',\n",
       " 'cast_6_female',\n",
       " 'cast_7_male',\n",
       " 'cast_7_female',\n",
       " 'cast_8_male',\n",
       " 'cast_8_female',\n",
       " 'crew__sound__music_editor_avg_profit',\n",
       " 'crew__sound__music_editor_avg_budget',\n",
       " 'crew__sound__music_editor_movies_before',\n",
       " 'crew__sound__original_music_composer_avg_profit',\n",
       " 'crew__sound__original_music_composer_avg_budget',\n",
       " 'crew__sound__original_music_composer_movies_before',\n",
       " 'crew__sound__sound_designer_avg_profit',\n",
       " 'crew__sound__sound_designer_avg_budget',\n",
       " 'crew__sound__sound_designer_movies_before',\n",
       " 'crew__sound__sound_effects_editor_avg_profit',\n",
       " 'crew__sound__sound_effects_editor_avg_budget',\n",
       " 'crew__sound__sound_effects_editor_movies_before',\n",
       " 'crew__sound__sound_re_recording_mixer_avg_profit',\n",
       " 'crew__sound__sound_re_recording_mixer_avg_budget',\n",
       " 'crew__sound__sound_re_recording_mixer_movies_before',\n",
       " 'crew__sound__supervising_sound_editor_avg_profit',\n",
       " 'crew__sound__supervising_sound_editor_avg_budget',\n",
       " 'crew__sound__supervising_sound_editor_movies_before',\n",
       " 'crew__directing__director__1_avg_profit',\n",
       " 'crew__directing__director__1_avg_budget',\n",
       " 'crew__directing__director__1_movies_before',\n",
       " 'crew__directing__script_supervisor_avg_profit',\n",
       " 'crew__directing__script_supervisor_avg_budget',\n",
       " 'crew__directing__script_supervisor_movies_before',\n",
       " 'crew__production__casting_avg_profit',\n",
       " 'crew__production__casting_avg_budget',\n",
       " 'crew__production__casting_movies_before',\n",
       " 'crew__production__executive_producer__1_avg_profit',\n",
       " 'crew__production__executive_producer__1_avg_budget',\n",
       " 'crew__production__executive_producer__1_movies_before',\n",
       " 'crew__production__producer__1_avg_profit',\n",
       " 'crew__production__producer__1_avg_budget',\n",
       " 'crew__production__producer__1_movies_before',\n",
       " 'crew__production__producer__2_avg_profit',\n",
       " 'crew__production__producer__2_avg_budget',\n",
       " 'crew__production__producer__2_movies_before',\n",
       " 'crew__editing__editor__1_avg_profit',\n",
       " 'crew__editing__editor__1_avg_budget',\n",
       " 'crew__editing__editor__1_movies_before',\n",
       " 'crew__costume__costume_designer_avg_profit',\n",
       " 'crew__costume__costume_designer_avg_budget',\n",
       " 'crew__costume__costume_designer_movies_before',\n",
       " 'crew__costume__costume_supervisor_avg_profit',\n",
       " 'crew__costume__costume_supervisor_avg_budget',\n",
       " 'crew__costume__costume_supervisor_movies_before',\n",
       " 'crew__costume__makeup_artist_avg_profit',\n",
       " 'crew__costume__makeup_artist_avg_budget',\n",
       " 'crew__costume__makeup_artist_movies_before',\n",
       " 'crew__crew__stunt_coordinator_avg_profit',\n",
       " 'crew__crew__stunt_coordinator_avg_budget',\n",
       " 'crew__crew__stunt_coordinator_movies_before',\n",
       " 'crew__writing__screenplay__1_avg_profit',\n",
       " 'crew__writing__screenplay__1_avg_budget',\n",
       " 'crew__writing__screenplay__1_movies_before',\n",
       " 'crew__art__art_direction_avg_profit',\n",
       " 'crew__art__art_direction_avg_budget',\n",
       " 'crew__art__art_direction_movies_before',\n",
       " 'crew__art__production_design_avg_profit',\n",
       " 'crew__art__production_design_avg_budget',\n",
       " 'crew__art__production_design_movies_before',\n",
       " 'crew__art__property_master_avg_profit',\n",
       " 'crew__art__property_master_avg_budget',\n",
       " 'crew__art__property_master_movies_before',\n",
       " 'crew__art__set_decoration_avg_profit',\n",
       " 'crew__art__set_decoration_avg_budget',\n",
       " 'crew__art__set_decoration_movies_before',\n",
       " 'crew__visualeffects__visual_effects_supervisor_avg_profit',\n",
       " 'crew__visualeffects__visual_effects_supervisor_avg_budget',\n",
       " 'crew__visualeffects__visual_effects_supervisor_movies_before',\n",
       " 'crew__camera__director_of_photography_avg_profit',\n",
       " 'crew__camera__director_of_photography_avg_budget',\n",
       " 'crew__camera__director_of_photography_movies_before',\n",
       " 'crew__camera__steadicam_operator_avg_profit',\n",
       " 'crew__camera__steadicam_operator_avg_budget',\n",
       " 'crew__camera__steadicam_operator_movies_before',\n",
       " 'crew__camera__still_photographer_avg_profit',\n",
       " 'crew__camera__still_photographer_avg_budget',\n",
       " 'crew__camera__still_photographer_movies_before']"
      ]
     },
     "execution_count": 359,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(df_cast_crew.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 360,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('11 cast_crew.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 361,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_average_cast_movies(row, columns):\n",
    "    avgs = [row[col] for col in columns if not pd.isna(row[col])]\n",
    "    return mean(avgs) if len(avgs) else np.nan\n",
    "\n",
    "def get_avg_cast_info(df):\n",
    "    result = {'cast_avg_budget':[], 'cast_avg_profit':[], 'cast_avg_experience':[], 'cast_avg_movies_before': []}\n",
    "    budget_columns = [col for col in df.columns if 'cast_' in col and 'budget' in col]\n",
    "    profit_columns = [col for col in df.columns if 'cast_' in col and 'profit' in col]\n",
    "    experience_columns = [col for col in df.columns if 'cast_' in col and 'experience' in col]\n",
    "    movies_before_columns = [col for col in df.columns if 'cast_' in col and 'movies_before' in col]\n",
    "    cast_avg_budget, cast_avg_profit, cast_avg_experience = [], [], []\n",
    "    for i, row in df.iterrows():\n",
    "        result['cast_avg_movies_before'].append(get_average_cast_movies(row, movies_before_columns))\n",
    "        result['cast_avg_budget'].append(get_average_cast_movies(row, budget_columns))\n",
    "        result['cast_avg_profit'].append(get_average_cast_movies(row, profit_columns))\n",
    "        result['cast_avg_experience'].append(get_average_cast_movies(row, experience_columns))        \n",
    "    return result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 362,
   "metadata": {},
   "outputs": [],
   "source": [
    "avg_columns = get_avg_cast_info(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 363,
   "metadata": {},
   "outputs": [],
   "source": [
    "added_avg_columns = df.copy()\n",
    "for column in list(avg_columns.keys()):\n",
    "    added_avg_columns[column] = avg_columns[column]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 364,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['budget',\n",
       " 'id',\n",
       " 'original_language',\n",
       " 'original_title',\n",
       " 'overview',\n",
       " 'revenue',\n",
       " 'runtime',\n",
       " 'spoken_languages',\n",
       " 'tagline',\n",
       " 'title',\n",
       " 'year',\n",
       " 'month',\n",
       " 'day',\n",
       " 'weekend',\n",
       " 'collection_name',\n",
       " 'cast_1_name',\n",
       " 'cast_2_name',\n",
       " 'cast_3_name',\n",
       " 'cast_4_name',\n",
       " 'cast_5_name',\n",
       " 'cast_6_name',\n",
       " 'cast_7_name',\n",
       " 'cast_8_name',\n",
       " 'crew__sound__music_editor',\n",
       " 'crew__sound__original_music_composer',\n",
       " 'crew__sound__sound_designer',\n",
       " 'crew__sound__sound_effects_editor',\n",
       " 'crew__sound__sound_re_recording_mixer',\n",
       " 'crew__sound__supervising_sound_editor',\n",
       " 'crew__directing__director__1',\n",
       " 'crew__directing__script_supervisor',\n",
       " 'crew__production__casting',\n",
       " 'crew__production__executive_producer__1',\n",
       " 'crew__production__producer__1',\n",
       " 'crew__production__producer__2',\n",
       " 'crew__editing__editor__1',\n",
       " 'crew__costume__costume_designer',\n",
       " 'crew__costume__costume_supervisor',\n",
       " 'crew__costume__makeup_artist',\n",
       " 'crew__crew__stunt_coordinator',\n",
       " 'crew__writing__screenplay__1',\n",
       " 'crew__art__art_direction',\n",
       " 'crew__art__production_design',\n",
       " 'crew__art__property_master',\n",
       " 'crew__art__set_decoration',\n",
       " 'crew__visualeffects__visual_effects_supervisor',\n",
       " 'crew__camera__director_of_photography',\n",
       " 'crew__camera__steadicam_operator',\n",
       " 'crew__camera__still_photographer',\n",
       " 'genre__war',\n",
       " 'genre__western',\n",
       " 'genre__mystery',\n",
       " 'genre__music',\n",
       " 'genre__crime',\n",
       " 'genre__romance',\n",
       " 'genre__action',\n",
       " 'genre__adventure',\n",
       " 'genre__thriller',\n",
       " 'genre__animation',\n",
       " 'genre__family',\n",
       " 'genre__drama',\n",
       " 'genre__comedy',\n",
       " 'genre__documentary',\n",
       " 'genre__history',\n",
       " 'genre__fantasy',\n",
       " 'genre__horror',\n",
       " 'production_company_1',\n",
       " 'production_company_2',\n",
       " 'production_company_3',\n",
       " 'production_company_4',\n",
       " 'production_company_5',\n",
       " 'country__rs',\n",
       " 'country__su',\n",
       " 'country__do',\n",
       " 'country__bo',\n",
       " 'country__ph',\n",
       " 'country__pe',\n",
       " 'country__id',\n",
       " 'country__gr',\n",
       " 'country__hn',\n",
       " 'country__nl',\n",
       " 'country__ee',\n",
       " 'country__ug',\n",
       " 'country__uy',\n",
       " 'country__ir',\n",
       " 'country__lb',\n",
       " 'country__pk',\n",
       " 'country__ua',\n",
       " 'country__eg',\n",
       " 'country__is',\n",
       " 'country__co',\n",
       " 'country__sk',\n",
       " 'country__bw',\n",
       " 'country__es',\n",
       " 'country__se',\n",
       " 'country__jp',\n",
       " 'country__np',\n",
       " 'country__tw',\n",
       " 'country__ie',\n",
       " 'country__lu',\n",
       " 'country__us',\n",
       " 'country__vn',\n",
       " 'country__ro',\n",
       " 'country__mn',\n",
       " 'country__cl',\n",
       " 'country__hu',\n",
       " 'country__br',\n",
       " 'country__ae',\n",
       " 'country__kr',\n",
       " 'country__be',\n",
       " 'country__ca',\n",
       " 'country__sg',\n",
       " 'country__bg',\n",
       " 'country__de',\n",
       " 'country__pl',\n",
       " 'country__mv',\n",
       " 'country__cn',\n",
       " 'country__in',\n",
       " 'country__th',\n",
       " 'country__fr',\n",
       " 'country__ru',\n",
       " 'country__dk',\n",
       " 'country__af',\n",
       " 'country__xg',\n",
       " 'country__it',\n",
       " 'country__ge',\n",
       " 'country__tr',\n",
       " 'country__za',\n",
       " 'country__ve',\n",
       " 'country__lk',\n",
       " 'country__hr',\n",
       " 'country__ng',\n",
       " 'country__ar',\n",
       " 'country__ba',\n",
       " 'country__il',\n",
       " 'country__mx',\n",
       " 'country__bd',\n",
       " 'country__my',\n",
       " 'country__nz',\n",
       " 'country__no',\n",
       " 'country__cz',\n",
       " 'country__hk',\n",
       " 'country__au',\n",
       " 'country__gb',\n",
       " 'country__lv',\n",
       " 'country__fi',\n",
       " 'profitability',\n",
       " 'day_sin',\n",
       " 'day_cos',\n",
       " 'month_sin',\n",
       " 'month_cos',\n",
       " 'collection_exists',\n",
       " 'cast_1_avg_profit',\n",
       " 'cast_1_avg_budget',\n",
       " 'cast_1_experience',\n",
       " 'cast_1_avg_profitability',\n",
       " 'cast_1_movies_before',\n",
       " 'cast_2_avg_profit',\n",
       " 'cast_2_avg_budget',\n",
       " 'cast_2_experience',\n",
       " 'cast_2_avg_profitability',\n",
       " 'cast_2_movies_before',\n",
       " 'cast_3_avg_profit',\n",
       " 'cast_3_avg_budget',\n",
       " 'cast_3_experience',\n",
       " 'cast_3_avg_profitability',\n",
       " 'cast_3_movies_before',\n",
       " 'cast_4_avg_profit',\n",
       " 'cast_4_avg_budget',\n",
       " 'cast_4_experience',\n",
       " 'cast_4_avg_profitability',\n",
       " 'cast_4_movies_before',\n",
       " 'cast_5_avg_profit',\n",
       " 'cast_5_avg_budget',\n",
       " 'cast_5_experience',\n",
       " 'cast_5_avg_profitability',\n",
       " 'cast_5_movies_before',\n",
       " 'cast_6_avg_profit',\n",
       " 'cast_6_avg_budget',\n",
       " 'cast_6_experience',\n",
       " 'cast_6_avg_profitability',\n",
       " 'cast_6_movies_before',\n",
       " 'cast_7_avg_profit',\n",
       " 'cast_7_avg_budget',\n",
       " 'cast_7_experience',\n",
       " 'cast_7_avg_profitability',\n",
       " 'cast_7_movies_before',\n",
       " 'cast_8_avg_profit',\n",
       " 'cast_8_avg_budget',\n",
       " 'cast_8_experience',\n",
       " 'cast_8_avg_profitability',\n",
       " 'cast_8_movies_before',\n",
       " 'cast_1_male',\n",
       " 'cast_1_female',\n",
       " 'cast_2_male',\n",
       " 'cast_2_female',\n",
       " 'cast_3_male',\n",
       " 'cast_3_female',\n",
       " 'cast_4_male',\n",
       " 'cast_4_female',\n",
       " 'cast_5_male',\n",
       " 'cast_5_female',\n",
       " 'cast_6_male',\n",
       " 'cast_6_female',\n",
       " 'cast_7_male',\n",
       " 'cast_7_female',\n",
       " 'cast_8_male',\n",
       " 'cast_8_female',\n",
       " 'crew__sound__music_editor_avg_profit',\n",
       " 'crew__sound__music_editor_avg_budget',\n",
       " 'crew__sound__music_editor_movies_before',\n",
       " 'crew__sound__original_music_composer_avg_profit',\n",
       " 'crew__sound__original_music_composer_avg_budget',\n",
       " 'crew__sound__original_music_composer_movies_before',\n",
       " 'crew__sound__sound_designer_avg_profit',\n",
       " 'crew__sound__sound_designer_avg_budget',\n",
       " 'crew__sound__sound_designer_movies_before',\n",
       " 'crew__sound__sound_effects_editor_avg_profit',\n",
       " 'crew__sound__sound_effects_editor_avg_budget',\n",
       " 'crew__sound__sound_effects_editor_movies_before',\n",
       " 'crew__sound__sound_re_recording_mixer_avg_profit',\n",
       " 'crew__sound__sound_re_recording_mixer_avg_budget',\n",
       " 'crew__sound__sound_re_recording_mixer_movies_before',\n",
       " 'crew__sound__supervising_sound_editor_avg_profit',\n",
       " 'crew__sound__supervising_sound_editor_avg_budget',\n",
       " 'crew__sound__supervising_sound_editor_movies_before',\n",
       " 'crew__directing__director__1_avg_profit',\n",
       " 'crew__directing__director__1_avg_budget',\n",
       " 'crew__directing__director__1_movies_before',\n",
       " 'crew__directing__script_supervisor_avg_profit',\n",
       " 'crew__directing__script_supervisor_avg_budget',\n",
       " 'crew__directing__script_supervisor_movies_before',\n",
       " 'crew__production__casting_avg_profit',\n",
       " 'crew__production__casting_avg_budget',\n",
       " 'crew__production__casting_movies_before',\n",
       " 'crew__production__executive_producer__1_avg_profit',\n",
       " 'crew__production__executive_producer__1_avg_budget',\n",
       " 'crew__production__executive_producer__1_movies_before',\n",
       " 'crew__production__producer__1_avg_profit',\n",
       " 'crew__production__producer__1_avg_budget',\n",
       " 'crew__production__producer__1_movies_before',\n",
       " 'crew__production__producer__2_avg_profit',\n",
       " 'crew__production__producer__2_avg_budget',\n",
       " 'crew__production__producer__2_movies_before',\n",
       " 'crew__editing__editor__1_avg_profit',\n",
       " 'crew__editing__editor__1_avg_budget',\n",
       " 'crew__editing__editor__1_movies_before',\n",
       " 'crew__costume__costume_designer_avg_profit',\n",
       " 'crew__costume__costume_designer_avg_budget',\n",
       " 'crew__costume__costume_designer_movies_before',\n",
       " 'crew__costume__costume_supervisor_avg_profit',\n",
       " 'crew__costume__costume_supervisor_avg_budget',\n",
       " 'crew__costume__costume_supervisor_movies_before',\n",
       " 'crew__costume__makeup_artist_avg_profit',\n",
       " 'crew__costume__makeup_artist_avg_budget',\n",
       " 'crew__costume__makeup_artist_movies_before',\n",
       " 'crew__crew__stunt_coordinator_avg_profit',\n",
       " 'crew__crew__stunt_coordinator_avg_budget',\n",
       " 'crew__crew__stunt_coordinator_movies_before',\n",
       " 'crew__writing__screenplay__1_avg_profit',\n",
       " 'crew__writing__screenplay__1_avg_budget',\n",
       " 'crew__writing__screenplay__1_movies_before',\n",
       " 'crew__art__art_direction_avg_profit',\n",
       " 'crew__art__art_direction_avg_budget',\n",
       " 'crew__art__art_direction_movies_before',\n",
       " 'crew__art__production_design_avg_profit',\n",
       " 'crew__art__production_design_avg_budget',\n",
       " 'crew__art__production_design_movies_before',\n",
       " 'crew__art__property_master_avg_profit',\n",
       " 'crew__art__property_master_avg_budget',\n",
       " 'crew__art__property_master_movies_before',\n",
       " 'crew__art__set_decoration_avg_profit',\n",
       " 'crew__art__set_decoration_avg_budget',\n",
       " 'crew__art__set_decoration_movies_before',\n",
       " 'crew__visualeffects__visual_effects_supervisor_avg_profit',\n",
       " 'crew__visualeffects__visual_effects_supervisor_avg_budget',\n",
       " 'crew__visualeffects__visual_effects_supervisor_movies_before',\n",
       " 'crew__camera__director_of_photography_avg_profit',\n",
       " 'crew__camera__director_of_photography_avg_budget',\n",
       " 'crew__camera__director_of_photography_movies_before',\n",
       " 'crew__camera__steadicam_operator_avg_profit',\n",
       " 'crew__camera__steadicam_operator_avg_budget',\n",
       " 'crew__camera__steadicam_operator_movies_before',\n",
       " 'crew__camera__still_photographer_avg_profit',\n",
       " 'crew__camera__still_photographer_avg_budget',\n",
       " 'crew__camera__still_photographer_movies_before',\n",
       " 'cast_avg_budget',\n",
       " 'cast_avg_profit',\n",
       " 'cast_avg_experience',\n",
       " 'cast_avg_movies_before']"
      ]
     },
     "execution_count": 364,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(added_avg_columns.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 365,
   "metadata": {},
   "outputs": [],
   "source": [
    "def calc_smooth_mean(df, by, on, m):\n",
    "    mean = df[on].mean()\n",
    "    agg = df.groupby(by)[on].agg(['count', 'mean'])\n",
    "    counts = agg['count']\n",
    "    means = agg['mean']\n",
    "    smooth = (counts * means + m * mean) / (counts + m)\n",
    "    return df[by].map(smooth)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 366,
   "metadata": {},
   "outputs": [],
   "source": [
    "added_avg_columns['year_avg_profitability'] = calc_smooth_mean(added_avg_columns, by='year', on='profitability', m=5)\n",
    "added_avg_columns['year_avg_revenue'] = calc_smooth_mean(added_avg_columns, by='year', on='revenue', m=5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 367,
   "metadata": {},
   "outputs": [],
   "source": [
    "prod_comp_columns = [col for col in added_avg_columns.columns if 'production_company' in col]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 368,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0\n",
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      "7100\n",
      "7200\n",
      "7300\n",
      "7400\n"
     ]
    }
   ],
   "source": [
    "companies_info = get_info_df_movies_per_value_range_columns(added_avg_columns, prod_comp_columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 369,
   "metadata": {},
   "outputs": [],
   "source": [
    "companies_info_copy = companies_info.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 370,
   "metadata": {},
   "outputs": [],
   "source": [
    "calculate_info_per_previous_movies_per_value(added_avg_columns, companies_info_copy, calc_revenue=True, calc_profitability=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 371,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "production_company_1\n",
      "production_company_2\n",
      "production_company_3\n",
      "production_company_4\n",
      "production_company_5\n"
     ]
    }
   ],
   "source": [
    "companies_columns = get_columns_from_info_dict(added_avg_columns, companies_info_copy, prod_comp_columns, new_column_prefix='production_company')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 372,
   "metadata": {},
   "outputs": [],
   "source": [
    "added_company_info = added_avg_columns.copy()\n",
    "for column in companies_columns.keys():\n",
    "    added_company_info[column] = companies_columns[column]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 373,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.8941820122764879  production_company_5_avg_profit\n",
      "0.8941820122764879  production_company_5_avg_profitability\n",
      "0.8941820122764879  production_company_5_avg_revenue\n",
      "0.8143848412062984  production_company_4_avg_profit\n",
      "0.8143848412062984  production_company_4_avg_profitability\n",
      "0.8143848412062984  production_company_4_avg_revenue\n",
      "0.6737389911929543  production_company_3_avg_profit\n",
      "0.6737389911929543  production_company_3_avg_profitability\n",
      "0.6737389911929543  production_company_3_avg_revenue\n",
      "0.4809180677875634  production_company_2_avg_profit\n",
      "0.4809180677875634  production_company_2_avg_profitability\n",
      "0.4809180677875634  production_company_2_avg_revenue\n",
      "0.340405657859621  production_company_1_avg_profit\n",
      "0.340405657859621  production_company_1_avg_profitability\n",
      "0.340405657859621  production_company_1_avg_revenue\n"
     ]
    }
   ],
   "source": [
    "companies_cols = [col for col in added_company_info.columns if 'production_company' in col and 'avg' in col]\n",
    "companies_count = {}\n",
    "for col in companies_cols:\n",
    "    companies_count[col] = len([p for p in added_company_info[col] if pd.isna(p)])\n",
    "\n",
    "sorted_company = sorted(companies_count, key=lambda company: companies_count[company], reverse=True)\n",
    "for company in sorted_company:\n",
    "    print(f'{companies_count[company]/added_company_info.shape[0]}  {company}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 374,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8941820122764879"
      ]
     },
     "execution_count": 374,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len([a for a in added_company_info['production_company_5_avg_profit'] if pd.isna(a)])/added_company_info.shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 375,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_3_companies = added_company_info.copy()\n",
    "\n",
    "for col in [col for col in added_company_info.columns if 'production_company' in col and ('4' in col or '5' in col)]:\n",
    "    df_3_companies.drop(col, axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 376,
   "metadata": {},
   "outputs": [],
   "source": [
    "col_count = df_3_companies.groupby('collection_name')['collection_name'].count()\n",
    "for i, row in df_3_companies.iterrows():\n",
    "    collection = row['collection_name']\n",
    "    if collection and not pd.isna(collection) and col_count[collection] < 2:\n",
    "        df_3_companies.loc[i, 'collection_name'] = np.nan"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "collection_info = get_info_df_movies_per_value_range_columns(df_3_companies, ['collection_name'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 378,
   "metadata": {},
   "outputs": [],
   "source": [
    "calculate_info_per_previous_movies_per_value(df_3_companies, collection_info, calc_revenue=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 379,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "collection_name\n"
     ]
    }
   ],
   "source": [
    "collection_columns = get_columns_from_info_dict(df_3_companies, collection_info, ['collection_name'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 380,
   "metadata": {},
   "outputs": [],
   "source": [
    "added_collection_info = df_3_companies.copy()\n",
    "for column in collection_columns.keys():\n",
    "    added_collection_info[column] = collection_columns[column]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 381,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.903789698425407"
      ]
     },
     "execution_count": 381,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len([a for a in added_collection_info['collection_name_avg_revenue'] if pd.isna(a)])/added_company_info.shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 382,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8509474246063518"
      ]
     },
     "execution_count": 382,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len([a for a in added_collection_info['collection_name'] if pd.isna(a)])/df_3_companies.shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 383,
   "metadata": {},
   "outputs": [],
   "source": [
    "added_collection_info.to_csv('12 added_collection_info.csv', mode='w+', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 414,
   "metadata": {},
   "outputs": [],
   "source": [
    "added_collection_info = pd.read_csv('12 added_collection_info.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 415,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_number_days_release(row):\n",
    "    return (date(row['year'], row['month'], row['day']) - date(1900,1,1)).days"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 419,
   "metadata": {},
   "outputs": [],
   "source": [
    "added_collection_info['days_release'] = added_collection_info.apply(lambda row: get_number_days_release(row), axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 425,
   "metadata": {},
   "outputs": [],
   "source": [
    "def calculate_competition(df, window):\n",
    "    def get_genres_set(movie):\n",
    "        return set([col for col in genre_cols if movie[col]])\n",
    "    \n",
    "    def genres_coef(set1, set2):\n",
    "        return len(set1 & set2) / len(set1 | set2)\n",
    "\n",
    "    def get_concurrent_value(target, movies):\n",
    "        return sum([genres_coef(get_genres_set(target), get_genres_set(movie)) for i, movie in movies.iterrows()])\n",
    "    \n",
    "    competition = []\n",
    "    genre_cols = [c for c in df.columns if 'genre' in c]\n",
    "    for i, row in df.iterrows():\n",
    "        concurrent_movies = df[(abs(df.days_release - row['days_release']) < window)].drop(index=i)\n",
    "        competition.append(get_concurrent_value(row, concurrent_movies) if concurrent_movies.shape[0] else 0)\n",
    "    return competition"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 426,
   "metadata": {},
   "outputs": [],
   "source": [
    "added_collection_info['competition'] = calculate_competition(added_collection_info, window=7)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 427,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.2896740672961648"
      ]
     },
     "execution_count": 427,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mean(added_collection_info['competition'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 428,
   "metadata": {},
   "outputs": [
    {
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       " 2.5833333333333335,\n",
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       " 2.5833333333333335,\n",
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       " 2.5833333333333335,\n",
       " 2.5833333333333335,\n",
       " 2.5833333333333335,\n",
       " 2.5833333333333335,\n",
       " 2.5833333333333335,\n",
       " 2.5833333333333335,\n",
       " 2.5833333333333335,\n",
       " 2.5833333333333335,\n",
       " 2.5833333333333335,\n",
       " 2.5833333333333335,\n",
       " 2.5833333333333335,\n",
       " 2.5833333333333335,\n",
       " 2.5833333333333335,\n",
       " 2.583333333333333,\n",
       " 2.583333333333333,\n",
       " 2.583333333333333,\n",
       " 2.583333333333333,\n",
       " 2.583333333333333,\n",
       " 2.583333333333333,\n",
       " 2.583333333333333,\n",
       " 2.583333333333333,\n",
       " ...]"
      ]
     },
     "execution_count": 428,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sorted(added_collection_info['competition'], reverse=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 430,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.1674673071790766"
      ]
     },
     "execution_count": 430,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len([a for a in added_collection_info['competition'] if not a])/added_collection_info.shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 392,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = added_collection_info.drop(['days_release', 'collection_exists'], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 393,
   "metadata": {},
   "outputs": [],
   "source": [
    "for col in [c for c in list(df.columns) if 'gender' in c]:\n",
    "    df = df.drop(col, axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 394,
   "metadata": {},
   "outputs": [],
   "source": [
    "cols = list(df.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 395,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i, col in enumerate(cols):\n",
    "    if (col == 'id'\n",
    "       or col == 'year'\n",
    "       or col == 'month'\n",
    "       or col == 'day'\n",
    "       or col == 'collection_name'\n",
    "       or (('cast' in col or 'crew' in col) and all(w not in col for w in ['male', 'female', 'avg', 'movies_before', 'experience']))\n",
    "       or ('production_company' in col and not 'avg' in col)): \n",
    "        cols[i] = f'META__{col}'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 396,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i, col in enumerate(cols):\n",
    "    if (col == 'original_language'\n",
    "       or col == 'original_title'\n",
    "       or col == 'overview'\n",
    "       or col == 'tagline'\n",
    "       or col == 'title'): \n",
    "        cols[i] = f'PROCESS__{col}'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 397,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.columns = cols"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 398,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.to_csv('13 changed_columns.csv', mode='w+', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 431,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('13 changed_columns.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 432,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open(\"rating.txt\", \"rb\") as fp:   # Unpickling\n",
    "    ratings_list = pickle.load(fp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 433,
   "metadata": {},
   "outputs": [],
   "source": [
    "ratings = {}\n",
    "for rating_col in ['g','pg','pg-13','r','nc-17']:\n",
    "    ratings[rating_col] = [int(v==rating_col) for v in ratings_list]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 434,
   "metadata": {},
   "outputs": [],
   "source": [
    "for rating in ratings:\n",
    "    df[f'rating__{rating}'] = ratings[rating]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 435,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df.drop('PROCESS__tagline', axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 436,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.to_csv('14 ratings.csv', mode='w+', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 437,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['budget',\n",
       " 'META__id',\n",
       " 'PROCESS__original_language',\n",
       " 'PROCESS__original_title',\n",
       " 'PROCESS__overview',\n",
       " 'revenue',\n",
       " 'runtime',\n",
       " 'spoken_languages',\n",
       " 'PROCESS__title',\n",
       " 'META__year',\n",
       " 'META__month',\n",
       " 'META__day',\n",
       " 'weekend',\n",
       " 'META__collection_name',\n",
       " 'META__cast_1_name',\n",
       " 'META__cast_2_name',\n",
       " 'META__cast_3_name',\n",
       " 'META__cast_4_name',\n",
       " 'META__cast_5_name',\n",
       " 'META__cast_6_name',\n",
       " 'META__cast_7_name',\n",
       " 'META__cast_8_name',\n",
       " 'META__crew__sound__music_editor',\n",
       " 'META__crew__sound__original_music_composer',\n",
       " 'META__crew__sound__sound_designer',\n",
       " 'META__crew__sound__sound_effects_editor',\n",
       " 'META__crew__sound__sound_re_recording_mixer',\n",
       " 'META__crew__sound__supervising_sound_editor',\n",
       " 'META__crew__directing__director__1',\n",
       " 'META__crew__directing__script_supervisor',\n",
       " 'META__crew__production__casting',\n",
       " 'META__crew__production__executive_producer__1',\n",
       " 'META__crew__production__producer__1',\n",
       " 'META__crew__production__producer__2',\n",
       " 'META__crew__editing__editor__1',\n",
       " 'META__crew__costume__costume_designer',\n",
       " 'META__crew__costume__costume_supervisor',\n",
       " 'META__crew__costume__makeup_artist',\n",
       " 'META__crew__crew__stunt_coordinator',\n",
       " 'META__crew__writing__screenplay__1',\n",
       " 'META__crew__art__art_direction',\n",
       " 'META__crew__art__production_design',\n",
       " 'META__crew__art__property_master',\n",
       " 'META__crew__art__set_decoration',\n",
       " 'META__crew__visualeffects__visual_effects_supervisor',\n",
       " 'META__crew__camera__director_of_photography',\n",
       " 'META__crew__camera__steadicam_operator',\n",
       " 'META__crew__camera__still_photographer',\n",
       " 'genre__war',\n",
       " 'genre__western',\n",
       " 'genre__mystery',\n",
       " 'genre__music',\n",
       " 'genre__crime',\n",
       " 'genre__romance',\n",
       " 'genre__action',\n",
       " 'genre__adventure',\n",
       " 'genre__thriller',\n",
       " 'genre__animation',\n",
       " 'genre__family',\n",
       " 'genre__drama',\n",
       " 'genre__comedy',\n",
       " 'genre__documentary',\n",
       " 'genre__history',\n",
       " 'genre__fantasy',\n",
       " 'genre__horror',\n",
       " 'META__production_company_1',\n",
       " 'META__production_company_2',\n",
       " 'META__production_company_3',\n",
       " 'country__rs',\n",
       " 'country__su',\n",
       " 'country__do',\n",
       " 'country__bo',\n",
       " 'country__ph',\n",
       " 'country__pe',\n",
       " 'country__id',\n",
       " 'country__gr',\n",
       " 'country__hn',\n",
       " 'country__nl',\n",
       " 'country__ee',\n",
       " 'country__ug',\n",
       " 'country__uy',\n",
       " 'country__ir',\n",
       " 'country__lb',\n",
       " 'country__pk',\n",
       " 'country__ua',\n",
       " 'country__eg',\n",
       " 'country__is',\n",
       " 'country__co',\n",
       " 'country__sk',\n",
       " 'country__bw',\n",
       " 'country__es',\n",
       " 'country__se',\n",
       " 'country__jp',\n",
       " 'country__np',\n",
       " 'country__tw',\n",
       " 'country__ie',\n",
       " 'country__lu',\n",
       " 'country__us',\n",
       " 'country__vn',\n",
       " 'country__ro',\n",
       " 'country__mn',\n",
       " 'country__cl',\n",
       " 'country__hu',\n",
       " 'country__br',\n",
       " 'country__ae',\n",
       " 'country__kr',\n",
       " 'country__be',\n",
       " 'country__ca',\n",
       " 'country__sg',\n",
       " 'country__bg',\n",
       " 'country__de',\n",
       " 'country__pl',\n",
       " 'country__mv',\n",
       " 'country__cn',\n",
       " 'country__in',\n",
       " 'country__th',\n",
       " 'country__fr',\n",
       " 'country__ru',\n",
       " 'country__dk',\n",
       " 'country__af',\n",
       " 'country__xg',\n",
       " 'country__it',\n",
       " 'country__ge',\n",
       " 'country__tr',\n",
       " 'country__za',\n",
       " 'country__ve',\n",
       " 'country__lk',\n",
       " 'country__hr',\n",
       " 'country__ng',\n",
       " 'country__ar',\n",
       " 'country__ba',\n",
       " 'country__il',\n",
       " 'country__mx',\n",
       " 'country__bd',\n",
       " 'country__my',\n",
       " 'country__nz',\n",
       " 'country__no',\n",
       " 'country__cz',\n",
       " 'country__hk',\n",
       " 'country__au',\n",
       " 'country__gb',\n",
       " 'country__lv',\n",
       " 'country__fi',\n",
       " 'profitability',\n",
       " 'day_sin',\n",
       " 'day_cos',\n",
       " 'month_sin',\n",
       " 'month_cos',\n",
       " 'cast_1_avg_profit',\n",
       " 'cast_1_avg_budget',\n",
       " 'cast_1_experience',\n",
       " 'cast_1_avg_profitability',\n",
       " 'cast_1_movies_before',\n",
       " 'cast_2_avg_profit',\n",
       " 'cast_2_avg_budget',\n",
       " 'cast_2_experience',\n",
       " 'cast_2_avg_profitability',\n",
       " 'cast_2_movies_before',\n",
       " 'cast_3_avg_profit',\n",
       " 'cast_3_avg_budget',\n",
       " 'cast_3_experience',\n",
       " 'cast_3_avg_profitability',\n",
       " 'cast_3_movies_before',\n",
       " 'cast_4_avg_profit',\n",
       " 'cast_4_avg_budget',\n",
       " 'cast_4_experience',\n",
       " 'cast_4_avg_profitability',\n",
       " 'cast_4_movies_before',\n",
       " 'cast_5_avg_profit',\n",
       " 'cast_5_avg_budget',\n",
       " 'cast_5_experience',\n",
       " 'cast_5_avg_profitability',\n",
       " 'cast_5_movies_before',\n",
       " 'cast_6_avg_profit',\n",
       " 'cast_6_avg_budget',\n",
       " 'cast_6_experience',\n",
       " 'cast_6_avg_profitability',\n",
       " 'cast_6_movies_before',\n",
       " 'cast_7_avg_profit',\n",
       " 'cast_7_avg_budget',\n",
       " 'cast_7_experience',\n",
       " 'cast_7_avg_profitability',\n",
       " 'cast_7_movies_before',\n",
       " 'cast_8_avg_profit',\n",
       " 'cast_8_avg_budget',\n",
       " 'cast_8_experience',\n",
       " 'cast_8_avg_profitability',\n",
       " 'cast_8_movies_before',\n",
       " 'cast_1_male',\n",
       " 'cast_1_female',\n",
       " 'cast_2_male',\n",
       " 'cast_2_female',\n",
       " 'cast_3_male',\n",
       " 'cast_3_female',\n",
       " 'cast_4_male',\n",
       " 'cast_4_female',\n",
       " 'cast_5_male',\n",
       " 'cast_5_female',\n",
       " 'cast_6_male',\n",
       " 'cast_6_female',\n",
       " 'cast_7_male',\n",
       " 'cast_7_female',\n",
       " 'cast_8_male',\n",
       " 'cast_8_female',\n",
       " 'crew__sound__music_editor_avg_profit',\n",
       " 'crew__sound__music_editor_avg_budget',\n",
       " 'crew__sound__music_editor_movies_before',\n",
       " 'crew__sound__original_music_composer_avg_profit',\n",
       " 'crew__sound__original_music_composer_avg_budget',\n",
       " 'crew__sound__original_music_composer_movies_before',\n",
       " 'crew__sound__sound_designer_avg_profit',\n",
       " 'crew__sound__sound_designer_avg_budget',\n",
       " 'crew__sound__sound_designer_movies_before',\n",
       " 'crew__sound__sound_effects_editor_avg_profit',\n",
       " 'crew__sound__sound_effects_editor_avg_budget',\n",
       " 'crew__sound__sound_effects_editor_movies_before',\n",
       " 'crew__sound__sound_re_recording_mixer_avg_profit',\n",
       " 'crew__sound__sound_re_recording_mixer_avg_budget',\n",
       " 'crew__sound__sound_re_recording_mixer_movies_before',\n",
       " 'crew__sound__supervising_sound_editor_avg_profit',\n",
       " 'crew__sound__supervising_sound_editor_avg_budget',\n",
       " 'crew__sound__supervising_sound_editor_movies_before',\n",
       " 'crew__directing__director__1_avg_profit',\n",
       " 'crew__directing__director__1_avg_budget',\n",
       " 'crew__directing__director__1_movies_before',\n",
       " 'crew__directing__script_supervisor_avg_profit',\n",
       " 'crew__directing__script_supervisor_avg_budget',\n",
       " 'crew__directing__script_supervisor_movies_before',\n",
       " 'crew__production__casting_avg_profit',\n",
       " 'crew__production__casting_avg_budget',\n",
       " 'crew__production__casting_movies_before',\n",
       " 'crew__production__executive_producer__1_avg_profit',\n",
       " 'crew__production__executive_producer__1_avg_budget',\n",
       " 'crew__production__executive_producer__1_movies_before',\n",
       " 'crew__production__producer__1_avg_profit',\n",
       " 'crew__production__producer__1_avg_budget',\n",
       " 'crew__production__producer__1_movies_before',\n",
       " 'crew__production__producer__2_avg_profit',\n",
       " 'crew__production__producer__2_avg_budget',\n",
       " 'crew__production__producer__2_movies_before',\n",
       " 'crew__editing__editor__1_avg_profit',\n",
       " 'crew__editing__editor__1_avg_budget',\n",
       " 'crew__editing__editor__1_movies_before',\n",
       " 'crew__costume__costume_designer_avg_profit',\n",
       " 'crew__costume__costume_designer_avg_budget',\n",
       " 'crew__costume__costume_designer_movies_before',\n",
       " 'crew__costume__costume_supervisor_avg_profit',\n",
       " 'crew__costume__costume_supervisor_avg_budget',\n",
       " 'crew__costume__costume_supervisor_movies_before',\n",
       " 'crew__costume__makeup_artist_avg_profit',\n",
       " 'crew__costume__makeup_artist_avg_budget',\n",
       " 'crew__costume__makeup_artist_movies_before',\n",
       " 'crew__crew__stunt_coordinator_avg_profit',\n",
       " 'crew__crew__stunt_coordinator_avg_budget',\n",
       " 'crew__crew__stunt_coordinator_movies_before',\n",
       " 'crew__writing__screenplay__1_avg_profit',\n",
       " 'crew__writing__screenplay__1_avg_budget',\n",
       " 'crew__writing__screenplay__1_movies_before',\n",
       " 'crew__art__art_direction_avg_profit',\n",
       " 'crew__art__art_direction_avg_budget',\n",
       " 'crew__art__art_direction_movies_before',\n",
       " 'crew__art__production_design_avg_profit',\n",
       " 'crew__art__production_design_avg_budget',\n",
       " 'crew__art__production_design_movies_before',\n",
       " 'crew__art__property_master_avg_profit',\n",
       " 'crew__art__property_master_avg_budget',\n",
       " 'crew__art__property_master_movies_before',\n",
       " 'crew__art__set_decoration_avg_profit',\n",
       " 'crew__art__set_decoration_avg_budget',\n",
       " 'crew__art__set_decoration_movies_before',\n",
       " 'crew__visualeffects__visual_effects_supervisor_avg_profit',\n",
       " 'crew__visualeffects__visual_effects_supervisor_avg_budget',\n",
       " 'crew__visualeffects__visual_effects_supervisor_movies_before',\n",
       " 'crew__camera__director_of_photography_avg_profit',\n",
       " 'crew__camera__director_of_photography_avg_budget',\n",
       " 'crew__camera__director_of_photography_movies_before',\n",
       " 'crew__camera__steadicam_operator_avg_profit',\n",
       " 'crew__camera__steadicam_operator_avg_budget',\n",
       " 'crew__camera__steadicam_operator_movies_before',\n",
       " 'crew__camera__still_photographer_avg_profit',\n",
       " 'crew__camera__still_photographer_avg_budget',\n",
       " 'crew__camera__still_photographer_movies_before',\n",
       " 'cast_avg_budget',\n",
       " 'cast_avg_profit',\n",
       " 'cast_avg_experience',\n",
       " 'cast_avg_movies_before',\n",
       " 'year_avg_profitability',\n",
       " 'year_avg_revenue',\n",
       " 'production_company_1_avg_profit',\n",
       " 'production_company_1_avg_profitability',\n",
       " 'production_company_1_avg_revenue',\n",
       " 'production_company_2_avg_profit',\n",
       " 'production_company_2_avg_profitability',\n",
       " 'production_company_2_avg_revenue',\n",
       " 'production_company_3_avg_profit',\n",
       " 'production_company_3_avg_profitability',\n",
       " 'production_company_3_avg_revenue',\n",
       " 'collection_name_avg_profit',\n",
       " 'collection_name_avg_revenue',\n",
       " 'competition',\n",
       " 'rating__g',\n",
       " 'rating__pg',\n",
       " 'rating__pg-13',\n",
       " 'rating__r',\n",
       " 'rating__nc-17']"
      ]
     },
     "execution_count": 437,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(df.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('14 ratings.csv')\n",
    "# merged_plot = df.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(7494, 305)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open('keywords_info.json', 'r') as f:\n",
    "    keywords_info = json.load(f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "kw_list = [' '.join([w['name'] for w in movie['keywords']]) for movie in keywords_info]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "plot_df = pd.read_csv('plot_df.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(4520, 2)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plot_df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "merged_plot = df.merge(plot_df, how='outer', on=['META__id']).drop_duplicates('META__id')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
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     ]
    }
   ],
   "source": [
    "num_changed = 0\n",
    "for i, row in merged_plot.iterrows():\n",
    "    if not row['plot'] or pd.isna(row['plot']) or len(row['plot']) < len(row['PROCESS__overview']):\n",
    "        num_changed += 1\n",
    "        print(f'{i}, changed {num_changed}')\n",
    "        merged_plot.loc[merged_plot.META__id == row.META__id, 'plot'] = row['PROCESS__overview']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.25740592473979185"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len([y for y in merged_plot['META__year'] if y > 2012])/merged_plot.shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "merged_plot['keywords'] = kw_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "merged_plot['plot'] = merged_plot['plot'] + merged_plot['keywords']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "import gensim\n",
    "from gensim.utils import simple_preprocess\n",
    "from gensim.parsing.preprocessing import STOPWORDS\n",
    "from nltk.stem import WordNetLemmatizer\n",
    "from nltk.tokenize import sent_tokenize, RegexpTokenizer\n",
    "from nltk.corpus import stopwords\n",
    "from nltk.corpus import wordnet\n",
    "import string"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 288,
   "metadata": {},
   "outputs": [],
   "source": [
    "ps = PorterStemmer()\n",
    "wnl = WordNetLemmatizer()\n",
    "tokenizer = RegexpTokenizer(r'\\w+')\n",
    "stop_words = set(stopwords.words('english'))\n",
    "\n",
    "def get_words(text):\n",
    "    sentences = [sentence for sentence in sent_tokenize(text)]\n",
    "    return [word for sentence in sentences for word in tokenizer.tokenize(sentence)]\n",
    "\n",
    "def filter_words(words):\n",
    "    return [word for word in words if len(word) > 2 and word not in stop_words and word.isalpha() and wordnet.synsets(word)]\n",
    "\n",
    "def prepare_words(text):\n",
    "    words = filter_words(get_words(text.lower()))    \n",
    "    return [f'{wnl.lemmatize(word)} ' for word in words]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# text = merged_plot.iloc[100]['PROCESS__overview']\n",
    "text = merged_plot.iloc[100]['plot']\n",
    "print(text)\n",
    "print('\\n')\n",
    "print(prepare_words(text))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 286,
   "metadata": {},
   "outputs": [],
   "source": [
    "# keywords = [kw.split('%') for kw in merged_plot['keywords']]\n",
    "# print(mean([len(a) for a in merged_plot['keywords']]))\n",
    "# print(mean([len(a) for a in keywords]))\n",
    "\n",
    "# dictionary = gensim.corpora.Dictionary(keywords)\n",
    "# dictionary.filter_extremes(no_below=1, no_above=0.01, keep_n=100000)\n",
    "# print(len(dictionary.keys()))\n",
    "\n",
    "# bow_corpus = [dictionary.doc2bow(overview) for overview in processed_overview]\n",
    "# lda_model = gensim.models.LdaMulticore(bow_corpus, num_topics=5, id2word=dictionary, passes=5, workers=10)\n",
    "# for idx, topic in lda_model.print_topics(-1):\n",
    "#     print('Topic: {} \\nWords: {}'.format(idx, topic))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 287,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2314.621697357886\n",
      "198.0069388844409\n"
     ]
    }
   ],
   "source": [
    "processed_overview = merged_plot['plot'].map(prepare_words)\n",
    "print(mean([len(a) for a in merged_plot['plot']]))\n",
    "print(mean([len(a) for a in processed_overview]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 256,
   "metadata": {},
   "outputs": [],
   "source": [
    "# processed_overview[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 298,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10361\n"
     ]
    }
   ],
   "source": [
    "dictionary = gensim.corpora.Dictionary(processed_overview)\n",
    "dictionary.filter_extremes(no_below=10, no_above=0.5)\n",
    "print(len(dictionary.keys()))\n",
    "bow_corpus = [dictionary.doc2bow(overview) for overview in processed_overview]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "lda_model = gensim.models.LdaMulticore(bow_corpus, num_topics=30, id2word=dictionary, passes=10, workers=10)\n",
    "for idx, topic in lda_model.print_topics(-1):\n",
    "    print('Topic: {} \\nWords: {}'.format(idx, topic))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "from gensim import corpora, models"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "tfidf = models.TfidfModel(bow_corpus)\n",
    "corpus_tfidf = tfidf[bow_corpus]\n",
    "\n",
    "lda_model_tfidf = gensim.models.LdaMulticore(corpus_tfidf, num_topics=30, id2word=dictionary, passes=10, workers=10)\n",
    "for idx, topic in lda_model_tfidf.print_topics(-1):\n",
    "    print('Topic: {} Word: {}'.format(idx, topic))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "import re\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from pprint import pprint\n",
    "import gensim\n",
    "import gensim.corpora as corpora\n",
    "from gensim.utils import simple_preprocess\n",
    "from gensim.models import CoherenceModel\n",
    "import spacy\n",
    "import pyLDAvis\n",
    "import pyLDAvis.gensim  # don't skip this\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "from nltk.corpus import stopwords\n",
    "stop_words = stopwords.words('english')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "docs = [re.sub(\"\\'\", \"\", doc) for doc in merged_plot['plot']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "def sent_to_words(docs):\n",
    "    for doc in docs:\n",
    "        yield(gensim.utils.simple_preprocess(str(doc), deacc=True))  # deacc=True removes punctuations\n",
    "\n",
    "data_words = list(sent_to_words(docs))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "bigram = gensim.models.Phrases(data_words, min_count=5, threshold=100)\n",
    "trigram = gensim.models.Phrases(bigram[data_words], threshold=100)  \n",
    "\n",
    "bigram_mod = gensim.models.phrases.Phraser(bigram)\n",
    "trigram_mod = gensim.models.phrases.Phraser(trigram)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "def remove_stopwords(texts):\n",
    "    return [[word for word in simple_preprocess(str(doc)) if word not in stop_words] for doc in texts]\n",
    "\n",
    "def make_bigrams(texts):\n",
    "    return [bigram_mod[doc] for doc in texts]\n",
    "\n",
    "def make_trigrams(texts):\n",
    "    return [trigram_mod[bigram_mod[doc]] for doc in texts]\n",
    "\n",
    "def lemmatization(texts, allowed_postags=['NOUN', 'ADJ', 'VERB', 'ADV']):\n",
    "    texts_out = []\n",
    "    for sent in texts:\n",
    "        doc = nlp(\" \".join(sent)) \n",
    "        texts_out.append([token.lemma_ for token in doc if token.pos_ in allowed_postags])\n",
    "    return texts_out"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_words_nostops = remove_stopwords(data_words)\n",
    "data_words_bigrams = make_bigrams(data_words_nostops)\n",
    "nlp = spacy.load('en', disable=['parser', 'ner'])\n",
    "data_lemmatized = lemmatization(data_words_bigrams, allowed_postags=['NOUN', 'ADJ', 'VERB', 'ADV'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "id2word = corpora.Dictionary(data_lemmatized)\n",
    "texts = data_lemmatized\n",
    "corpus = [id2word.doc2bow(text) for text in texts]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "lda_model = gensim.models.ldamodel.LdaModel(corpus=corpus,\n",
    "                                           id2word=id2word,\n",
    "                                           num_topics=15,\n",
    "                                           update_every=1,\n",
    "                                           chunksize=100,\n",
    "                                           passes=15,\n",
    "                                           alpha='auto',\n",
    "                                           per_word_topics=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "lda_model.save('lga/lga_model_num15_update1_chunk100_passes_15')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "doc_lda = lda_model[corpus]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "lda_topics = lda_model.show_topics(num_topics=25, num_words=100, formatted=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Perplexity:  -10.608632001448141\n",
      "\n",
      "Coherence Score:  0.4526555243924768\n"
     ]
    }
   ],
   "source": [
    "print('\\nPerplexity: ', lda_model.log_perplexity(corpus))  # a measure of how good the model is. lower the better.\n",
    "\n",
    "coherence_model_lda = CoherenceModel(model=lda_model, texts=data_lemmatized, dictionary=id2word, coherence='c_v')\n",
    "coherence_lda = coherence_model_lda.get_coherence()\n",
    "print('\\nCoherence Score: ', coherence_lda)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{0: 'patient,rise,rabbit,toy,basement,violently,noise,trauma,tattoo',\n",
       " 1: 'police,murder,kill,money,steal,car,drug,officer,arrest,crime,man,shoot',\n",
       " 2: 'emily,murderer,victor,holly,fre,fred,belt,paul',\n",
       " 3: 'find,tell,go,leave,take,see,try,come,run,man,back',\n",
       " 4: 'animal,water,monster,dog,creature,giant,boat,cave,billy,island,village,forest,river,wood,rock',\n",
       " 5: 'driver,frankie,tire,suitcase,stephanie,trailer,overnight',\n",
       " 6: 'friend,get,make,go',\n",
       " 7: 'horse,singer,gold,unfold,railroad,ranch,irish,wallet,terrorize',\n",
       " 8: 'base,life,time,film,story,world,become,book',\n",
       " 9: '',\n",
       " 10: 'kill,use,team,force,fight,save,escape,attack,group',\n",
       " 11: 'crew,earth,ship,alien,space,planet,spacecraft,submarine',\n",
       " 12: 'family,love,mother,woman,young,child,relationship,son,live,wife,daughter,father,brother,life,old,boy,man,parent,home,marry,wedding',\n",
       " 13: 'prison,german,corruption,trial,lawyer,sentence,court,prisoner,firm,religious,japanese,activist',\n",
       " 14: 'ghost,magic,curse,evil,demon,possess,witch,king,priest,ritual,violet,spell,throne'}"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "{topic[0]: ','.join([w[0] for w in topic[1] if w[1]>0.01]) for topic in lda_topics}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/stas/anaconda3/lib/python3.7/site-packages/pyLDAvis/_prepare.py:257: FutureWarning: Sorting because non-concatenation axis is not aligned. A future version\n",
      "of pandas will change to not sort by default.\n",
      "\n",
      "To accept the future behavior, pass 'sort=False'.\n",
      "\n",
      "To retain the current behavior and silence the warning, pass 'sort=True'.\n",
      "\n",
      "  return pd.concat([default_term_info] + list(topic_dfs))\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "<link rel=\"stylesheet\" type=\"text/css\" href=\"https://cdn.rawgit.com/bmabey/pyLDAvis/files/ldavis.v1.0.0.css\">\n",
       "\n",
       "\n",
       "<div id=\"ldavis_el290721404241249709604139817506\"></div>\n",
       "<script type=\"text/javascript\">\n",
       "\n",
       "var ldavis_el290721404241249709604139817506_data = {\"mdsDat\": {\"x\": [-0.35740579298713704, -0.36170425656328875, -0.33902030985660947, -0.11116071284209378, -0.03034867666778771, -0.01682905660722495, 0.01335376045915845, 0.09100653732177874, 0.09880966088654675, 0.17196009248790423, 0.16962634169307775, 0.16717718758617445, 0.16858217799598682, 0.16855014940071275, 0.16740289769280162], \"y\": [-0.14866715354907337, -0.10167508989529812, 0.0014910381292450136, 0.24617797216400583, 0.14826650106675546, 0.2112684452011472, 0.008777797596715766, -0.11025659961281807, 0.012947995016901864, -0.049240438365198626, -0.05148372449692338, -0.041580306815677634, -0.042314697103013436, -0.04239583255045307, -0.041315906786315484], \"topics\": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15], \"cluster\": [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], \"Freq\": [39.54022216796875, 31.042686462402344, 16.119857788085938, 3.865776300430298, 2.6140151023864746, 1.9344110488891602, 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\"college\", \"kiss\", \"sexual\", \"care\", \"affair\", \"summer\", \"best_friend\", \"writer\", \"divorce\", \"reject\", \"family\", \"mother\", \"life\", \"story\", \"husband\", \"problem\", \"change\", \"father\", \"dream\", \"together\", \"good\", \"live\", \"young\", \"become\", \"year\", \"friend\", \"girl\", \"sister\", \"woman\", \"never\", \"time\", \"new\", \"son\", \"daughter\", \"day\", \"child\", \"first\", \"come\", \"make\", \"old\", \"begin\", \"home\", \"tell\", \"get\", \"go\", \"meet\", \"decide\", \"work\", \"base\", \"take\", \"find\", \"leave\", \"car\", \"drug\", \"gun\", \"gang\", \"phone\", \"rape\", \"cop\", \"fake\", \"driver\", \"diamond\", \"check\", \"cash\", \"bank\", \"gangster\", \"heist\", \"robbery\", \"pose\", \"cocaine\", \"con\", \"custody\", \"henchman\", \"foster\", \"cook\", \"frankie\", \"associate\", \"double\", \"theft\", \"policeman\", \"price\", \"justice\", \"money\", \"room\", \"steal\", \"drive\", \"beat\", \"hotel\", \"shoot\", 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\"role\", \"role\", \"rookie\", \"room\", \"room\", \"room\", \"royalty\", \"run\", \"run\", \"run\", \"runner\", \"runway\", \"russian\", \"russian\", \"ruthless\", \"sailor\", \"satellite\", \"satire\", \"save\", \"save\", \"save\", \"save\", \"save\", \"save\", \"scholarship\", \"school\", \"science\", \"scientist\", \"score\", \"score\", \"score\", \"script\", \"scroll\", \"sculptor\", \"sculpture\", \"season\", \"season\", \"sebastian\", \"secret\", \"secret\", \"secret\", \"secret\", \"secret\", \"secret\", \"see\", \"see\", \"see\", \"selene\", \"sentence\", \"sentence\", \"sequel\", \"set\", \"set\", \"set\", \"seth\", \"sexual\", \"sexy\", \"shark\", \"ship\", \"shoot\", \"shoot\", \"shoot\", \"shot\", \"shot\", \"show\", \"show\", \"show\", \"show\", \"shuttle\", \"sibling_relationship\", \"silver\", \"singer\", \"singing\", \"sister\", \"sister\", \"slave\", \"small_town\", \"solace\", \"soldier\", \"solve\", \"solve\", \"solve\", \"son\", \"son\", \"son\", \"song\", \"sonny\", \"soul\", \"soul\", \"space\", \"spacecraft\", \"spacesuit\", \"spell\", \"spirit\", \"sport\", \"spy\", \"spy\", \"stage\", \"stage\", \"stage\", \"star\", \"star\", \"star\", \"star\", \"steal\", \"steal\", \"steal\", \"steal\", \"stephanie\", \"steward\", \"storm\", \"storm\", \"storm\", \"story\", \"story\", \"story\", \"storyline\", \"student\", \"studio\", \"submarine\", \"suburb\", \"successful\", \"summer\", \"super\", \"superhero\", \"superhero_base\", \"supernatural\", \"surf\", \"surveillance\", \"survival\", \"survive\", \"survive\", \"survive\", \"suspect\", \"suspect\", \"sword\", \"system\", \"system\", \"system\", \"take\", \"take\", \"take\", \"target\", \"target\", \"target\", \"teacher\", \"team\", \"team\", \"team\", \"team\", \"tech\", \"technology\", \"tell\", \"tell\", \"tell\", \"tennis\", \"terrorist\", \"testify\", \"theater\", \"theater\", \"theater\", \"theft\", \"thing\", \"threaten\", \"threaten\", \"threaten\", \"throne\", \"tick\", \"tiger\", \"time\", \"time\", \"time\", \"time\", \"title\", \"title\", \"toast\", \"together\", \"together\", \"totally\", \"tour\", \"tour\", \"tour\", \"tour\", \"tournament\", \"tower\", \"town\", \"town\", \"town\", \"trainer\", \"training\", \"training\", \"training\", \"training\", \"trap\", \"tree\", \"tree\", \"trial\", \"trial\", \"troll\", \"troop\", \"try\", \"try\", \"try\", \"turn\", \"turn\", \"turn\", \"turn\", \"tv\", \"tv\", \"tv\", \"tyrannical\", \"undefeated\", \"undercover\", \"undercover\", \"underlie\", \"undo\", \"unicorn\", \"unit\", \"unit\", \"universe\", \"unleash\", \"unscrupulous\", \"unwanted\", \"upsetting\", \"use\", \"use\", \"use\", \"use\", \"use\", \"vacuum\", \"vampire\", \"victim\", \"victim\", \"victim\", \"victor\", \"village\", \"village\", \"village\", \"violence\", \"violence\", \"violence\", \"violence\", \"violence\", \"viral\", \"virus\", \"vivian\", \"waiter\", \"war\", \"warrior\", \"water\", \"wed\", \"wedding\", \"whale\", \"widow\", \"willy\", \"win\", \"win\", \"window\", \"window\", \"wink\", \"witch\", \"witness\", \"witness\", \"witness\", \"witness\", \"wizard\", \"wolf\", \"woman\", \"woman\", \"wood\", \"work\", \"work\", \"work\", \"world\", \"world\", \"world\", \"wrestling\", \"writer\", \"year\", \"year\", \"year\", \"yearn\", \"young\", \"young\", \"young\", \"young\"]}, \"R\": 30, \"lambda.step\": 0.01, \"plot.opts\": {\"xlab\": \"PC1\", \"ylab\": \"PC2\"}, \"topic.order\": [8, 3, 14, 6, 15, 10, 7, 5, 11, 2, 13, 9, 1, 4, 12]};\n",
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      "text/plain": [
       "PreparedData(topic_coordinates=              x         y  topics  cluster       Freq\n",
       "topic                                                \n",
       "7     -0.357406 -0.148667  1       1        39.540222\n",
       "2     -0.361704 -0.101675  2       1        31.042686\n",
       "13    -0.339020  0.001491  3       1        16.119858\n",
       "5     -0.111161  0.246178  4       1        3.865776 \n",
       "14    -0.030349  0.148267  5       1        2.614015 \n",
       "9     -0.016829  0.211268  6       1        1.934411 \n",
       "6      0.013354  0.008778  7       1        1.784143 \n",
       "4      0.091007 -0.110257  8       1        1.011806 \n",
       "10     0.098810  0.012948  9       1        0.906070 \n",
       "1      0.171960 -0.049240  10      1        0.323298 \n",
       "12     0.169626 -0.051484  11      1        0.309589 \n",
       "8      0.167177 -0.041580  12      1        0.280520 \n",
       "0      0.168582 -0.042315  13      1        0.102729 \n",
       "3      0.168550 -0.042396  14      1        0.102140 \n",
       "11     0.167403 -0.041316  15      1        0.062745 , topic_info=      Category          Freq                  Term         Total  loglift  \\\n",
       "191    Default  3506.000000   show                  3506.000000   30.0000   \n",
       "76     Default  2622.000000   film                  2622.000000   29.0000   \n",
       "1202   Default  2312.000000   murder                2312.000000   28.0000   \n",
       "373    Default  3397.000000   police                3397.000000   27.0000   \n",
       "304    Default  2813.000000   fight                 2813.000000   26.0000   \n",
       "336    Default  7238.000000   kill                  7238.000000   25.0000   \n",
       "455    Default  1628.000000   team                  1628.000000   24.0000   \n",
       "645    Default  3578.000000   base                  3578.000000   23.0000   \n",
       "225    Default  3875.000000   use                   3875.000000   22.0000   \n",
       "899    Default  1712.000000   world                 1712.000000   21.0000   \n",
       "579    Default  1356.000000   play                  1356.000000   20.0000   \n",
       "77     Default  10168.000000  find                  10168.000000  19.0000   \n",
       "351    Default  6185.000000   man                   6185.000000   18.0000   \n",
       "307    Default  2823.000000   force                 2823.000000   17.0000   \n",
       "302    Default  4808.000000   family                4808.000000   16.0000   \n",
       "281    Default  2943.000000   death                 2943.000000   15.0000   \n",
       "2112   Default  832.000000    match                 832.000000    14.0000   \n",
       "697    Default  4318.000000   love                  4318.000000   13.0000   \n",
       "993    Default  1284.000000   prison                1284.000000   12.0000   \n",
       "130    Default  992.000000    movie                 992.000000    11.0000   \n",
       "467    Default  2658.000000   attack                2658.000000   10.0000   \n",
       "140    Default  2257.000000   order                 2257.000000   9.0000    \n",
       "254    Default  4462.000000   become                4462.000000   8.0000    \n",
       "24     Default  3146.000000   car                   3146.000000   7.0000    \n",
       "90     Default  2407.000000   group                 2407.000000   6.0000    \n",
       "80     Default  2713.000000   first                 2713.000000   5.0000    \n",
       "395    Default  2128.000000   save                  2128.000000   4.0000    \n",
       "2220   Default  698.000000    win                   698.000000    3.0000    \n",
       "131    Default  1681.000000   must                  1681.000000   2.0000    \n",
       "616    Default  2337.000000   story                 2337.000000   1.0000    \n",
       "697    Topic1   4316.701660   love                  4318.015625   0.9275    \n",
       "590    Topic1   2662.820312   relationship          2664.133545   0.9274    \n",
       "602    Topic1   1545.579224   school                1546.892334   0.9270    \n",
       "2188   Topic1   1343.739380   parent                1345.052490   0.9269    \n",
       "1021   Topic1   1214.225464   thing                 1215.538574   0.9268    \n",
       "1517   Topic1   1188.530762   student               1189.843872   0.9267    \n",
       "843    Topic1   1136.217896   marry                 1137.531006   0.9267    \n",
       "1366   Topic1   1073.814209   wedding               1075.127319   0.9266    \n",
       "842    Topic1   969.658020    marriage              970.971252    0.9265    \n",
       "2377   Topic1   931.313660    feel                  932.626892    0.9264    \n",
       "6980   Topic1   905.962158    wrestling             907.275391    0.9264    \n",
       "1797   Topic1   791.262329    date                  792.575562    0.9262    \n",
       "746    Topic1   787.031311    age                   788.344543    0.9262    \n",
       "681    Topic1   769.750732    friendship            771.063965    0.9261    \n",
       "2553   Topic1   577.734131    teacher               579.047363    0.9256    \n",
       "1016   Topic1   558.927185    successful            560.256165    0.9255    \n",
       "1841   Topic1   536.334717    always                537.647949    0.9254    \n",
       "2522   Topic1   494.484467    class                 495.797668    0.9252    \n",
       "949    Topic1   438.998291    feeling               440.311493    0.9249    \n",
       "829    Topic1   428.624237    happy                 429.937439    0.9248    \n",
       "1391   Topic1   425.639587    college               426.952789    0.9248    \n",
       "1084   Topic1   460.191406    kiss                  461.644379    0.9247    \n",
       "781    Topic1   404.201569    sexual                405.514771    0.9246    \n",
       "652    Topic1   392.758942    care                  394.072144    0.9245    \n",
       "796    Topic1   361.738770    affair                363.051971    0.9242    \n",
       "3263   Topic1   355.938873    summer                357.252075    0.9242    \n",
       "257    Topic1   343.709045    best_friend           345.022247    0.9240    \n",
       "793    Topic1   337.712769    writer                339.025970    0.9240    \n",
       "2370   Topic1   329.503845    divorce               330.817047    0.9239    \n",
       "1340   Topic1   329.200989    reject                330.514191    0.9239    \n",
       "302    Topic1   4771.451660   family                4808.893555   0.9200    \n",
       "357    Topic1   2914.793457   mother                2949.519531   0.9160    \n",
       "345    Topic1   4201.048828   life                  4315.111328   0.9011    \n",
       "616    Topic1   2276.211670   story                 2337.469727   0.9013    \n",
       "102    Topic1   963.077576    husband               980.901367    0.9095    \n",
       "1817   Topic1   704.263794    problem               713.002319    0.9155    \n",
       "272    Topic1   1274.936401   change                1307.469238   0.9027    \n",
       "74     Topic1   1884.228760   father                1954.199585   0.8914    \n",
       "758    Topic1   898.927673    dream                 917.950317    0.9069    \n",
       "456    Topic1   2007.199829   together              2107.838867   0.8789    \n",
       "531    Topic1   1567.302002   good                  1634.986572   0.8856    \n",
       "347    Topic1   3100.887695   live                  3341.353271   0.8532    \n",
       "632    Topic1   2925.376709   young                 3199.599365   0.8382    \n",
       "254    Topic1   3897.024170   become                4462.521484   0.7924    \n",
       "743    Topic1   2436.756104   year                  2712.114258   0.8208    \n",
       "83     Topic1   3945.497070   friend                4619.723633   0.7701    \n",
       "1269   Topic1   2288.149658   girl                  2559.186768   0.8159    \n",
       "1838   Topic1   1384.297852   sister                1485.359009   0.8574    \n",
       "236    Topic1   3061.269287   woman                 3637.823242   0.7553    \n",
       "1204   Topic1   1129.471558   never                 1197.132202   0.8697    \n",
       "216    Topic1   3371.183105   time                  4286.443848   0.6877    \n",
       "566    Topic1   2224.721191   new                   2635.728271   0.7583    \n",
       "612    Topic1   1992.382568   son                   2317.592285   0.7767    \n",
       "280    Topic1   1709.152832   daughter              1944.230225   0.7990    \n",
       "495    Topic1   2274.160156   day                   2832.212158   0.7084    \n",
       "33     Topic1   2260.484131   child                 2820.048096   0.7067    \n",
       "80     Topic1   2182.926025   first                 2713.365967   0.7103    \n",
       "39     Topic1   3289.440430   come                  5152.589844   0.4791    \n",
       "121    Topic1   3342.611328   make                  5611.638184   0.4098    \n",
       "366    Topic1   1884.846802   old                   2405.318359   0.6840    \n",
       "18     Topic1   2634.299316   begin                 4167.069336   0.4693    \n",
       "538    Topic1   2254.092285   home                  3293.535400   0.5486    \n",
       "214    Topic1   3663.509766   tell                  7859.670410   0.1645    \n",
       "86     Topic1   3360.848145   get                   7053.352539   0.1865    \n",
       "87     Topic1   3770.218018   go                    8768.509766   0.0838    \n",
       "554    Topic1   2316.778809   meet                  3616.493896   0.4825    \n",
       "282    Topic1   2130.255127   decide                3074.890625   0.5608    \n",
       "792    Topic1   2202.899658   work                  3317.339355   0.5185    \n",
       "645    Topic1   2242.180908   base                  3578.428467   0.4604    \n",
       "212    Topic1   2701.165283   take                  8357.747070  -0.2017    \n",
       "77     Topic1   2647.776367   find                  10168.070312 -0.4177    \n",
       "116    Topic1   2452.888184   leave                 6991.101074  -0.1195    \n",
       "24     Topic2   3145.348145   car                   3146.621826   1.1694    \n",
       "1547   Topic2   1249.839966   drug                  1251.113770   1.1688    \n",
       "959    Topic2   1057.445068   gun                   1058.718872   1.1686    \n",
       "311    Topic2   949.544312    gang                  950.818115    1.1685    \n",
       "150    Topic2   719.001343    phone                 720.286316    1.1680    \n",
       "2624   Topic2   668.296997    rape                  669.570801    1.1679    \n",
       "3335   Topic2   500.272339    cop                   501.546173    1.1673    \n",
       "2765   Topic2   448.958496    fake                  450.232330    1.1670    \n",
       "290    Topic2   445.802368    driver                447.076202    1.1670    \n",
       "3871   Topic2   361.239594    diamond               362.513428    1.1663    \n",
       "3030   Topic2   348.619690    check                 349.893524    1.1662    \n",
       "2358   Topic2   319.936432    cash                  321.210266    1.1658    \n",
       "3727   Topic2   302.716461    bank                  303.990295    1.1656    \n",
       "1905   Topic2   273.088043    gangster              274.361877    1.1652    \n",
       "3621   Topic2   272.848938    heist                 274.122772    1.1651    \n",
       "1003   Topic2   237.573822    robbery               238.847656    1.1645    \n",
       "2257   Topic2   228.562027    pose                  229.835861    1.1642    \n",
       "3331   Topic2   223.412125    cocaine               224.685959    1.1641    \n",
       "4847   Topic2   218.290451    con                   219.564285    1.1640    \n",
       "4791   Topic2   212.653793    custody               213.927628    1.1638    \n",
       "3169   Topic2   211.960754    henchman              213.234589    1.1638    \n",
       "6795   Topic2   206.908783    foster                208.182617    1.1637    \n",
       "4546   Topic2   205.738602    cook                  207.012436    1.1636    \n",
       "2459   Topic2   195.639786    frankie               196.913620    1.1633    \n",
       "2564   Topic2   194.913803    associate             196.187637    1.1633    \n",
       "1897   Topic2   196.673782    double                197.962830    1.1633    \n",
       "1020   Topic2   194.324432    theft                 195.598267    1.1633    \n",
       "4047   Topic2   188.105072    policeman             189.378906    1.1631    \n",
       "4049   Topic2   188.060684    price                 189.334518    1.1631    \n",
       "6941   Topic2   180.171707    justice               181.445541    1.1628    \n",
       "129    Topic2   2515.908203   money                 2548.598633   1.1569    \n",
       "176    Topic2   1902.936035   room                  1948.337524   1.1462    \n",
       "412    Topic2   1710.454834   steal                 1774.079712   1.1333    \n",
       "289    Topic2   1549.354614   drive                 1653.995483   1.1045    \n",
       "1628   Topic2   936.140137    beat                  985.341980    1.1186    \n",
       "99     Topic2   832.008545    hotel                 875.185059    1.1192    \n",
       "401    Topic2   1784.557495   shoot                 1929.873779   1.0915    \n",
       "1288   Topic2   1227.749390   arrest                1329.180908   1.0904    \n",
       "373    Topic2   3002.847656   police                3397.069824   1.0465    \n",
       "234    Topic2   476.278564    window                500.584015    1.1200    \n",
       "81     Topic2   442.672272    floor                 464.776978    1.1211    \n",
       "250    Topic2   1182.794678   apartment             1336.369995   1.0477    \n",
       "253    Topic2   276.204407    bag                   282.062042    1.1488    \n",
       "57     Topic2   670.468628    door                  741.600586    1.0690    \n",
       "266    Topic2   491.137482    bus                   533.183533    1.0877    \n",
       "2198   Topic2   711.743408    revenge               805.394104    1.0462    \n",
       "1043   Topic2   961.483887    chase                 1155.460693   0.9860    \n",
       "404    Topic2   437.735992    shot                  470.124298    1.0984    \n",
       "427    Topic2   811.492310    threaten              964.203064    0.9974    \n",
       "351    Topic2   3899.317627   man                   6185.935547   0.7083    \n",
       "23     Topic2   2281.531250   call                  3324.968018   0.7932    \n",
       "993    Topic2   1025.587402   prison                1284.141968   0.9450    \n",
       "10     Topic2   2194.489990   arrive                3250.337158   0.7770    \n",
       "336    Topic2   4122.415527   kill                  7238.985352   0.6068    \n",
       "87     Topic2   4771.450195   go                    8768.509766   0.5613    \n",
       "393    Topic2   2194.679688   run                   3387.964844   0.7356    \n",
       "214    Topic2   4043.007568   tell                  7859.670410   0.5051    \n",
       "86     Topic2   3682.774414   get                   7053.352539   0.5200    \n",
       "116    Topic2   3571.083252   leave                 6991.101074   0.4980    \n",
       "212    Topic2   4053.381348   take                  8357.747070   0.4462    \n",
       "218    Topic2   2780.608154   try                   5485.462402   0.4904    \n",
       "77     Topic2   4273.269531   find                  10168.070312  0.3029    \n",
       "184    Topic2   2600.998291   see                   5132.941895   0.4900    \n",
       "171    Topic2   1929.316162   reveal                3319.267822   0.6272    \n",
       "225    Topic2   2019.622437   use                   3875.632324   0.5180    \n",
       "341    Topic2   1944.841553   later                 4030.438232   0.4411    \n",
       "312    Topic2   1964.161011   give                  4214.801758   0.4063    \n",
       "338    Topic2   1491.002563   know                  2852.942139   0.5209    \n",
       "315    Topic2   1275.034424   head                  2004.812378   0.7172    \n",
       "576    Topic2   1357.515991   plan                  2363.154053   0.6155    \n",
       "281    Topic2   1471.733276   death                 2943.899658   0.4765    \n",
       "14     Topic2   1409.790894   attempt               2749.993408   0.5016    \n",
       "121    Topic2   1626.890991   make                  5611.638184  -0.0684    \n",
       "318    Topic2   1450.372925   help                  4142.804199   0.1203    \n",
       "15     Topic2   1422.882324   back                  3906.315674   0.1599    \n",
       "629    Topic3   1095.420044   water                 1096.709717   1.8239    \n",
       "6707   Topic3   850.295593    vampire               851.585388    1.8236    \n",
       "1779   Topic3   800.719116    trap                  802.008911    1.8235    \n",
       "2080   Topic3   695.087036    animal                696.376831    1.8233    \n",
       "4572   Topic3   553.215210    horse                 554.505005    1.8228    \n",
       "2971   Topic3   469.509430    creature              470.799225    1.8224    \n",
       "5253   Topic3   336.711426    wood                  338.001221    1.8213    \n",
       "4252   Topic3   312.181091    forest                313.470886    1.8210    \n",
       "6562   Topic3   280.814819    hercule               282.104614    1.8205    \n",
       "3242   Topic3   266.994507    mountain              268.284302    1.8203    \n",
       "2221   Topic3   265.838165    wink                  267.127991    1.8203    \n",
       "3189   Topic3   265.423767    river                 266.713562    1.8203    \n",
       "4935   Topic3   249.938751    cat                   251.228546    1.8200    \n",
       "103    Topic3   243.369705    ice                   244.659500    1.8198    \n",
       "2654   Topic3   238.358963    bird                  239.648758    1.8197    \n",
       "313    Topic3   237.513702    gold                  238.803497    1.8197    \n",
       "7004   Topic3   236.547501    grave                 237.837296    1.8197    \n",
       "2738   Topic3   222.903732    indian                224.193527    1.8193    \n",
       "525    Topic3   220.011124    fish                  221.300919    1.8193    \n",
       "6446   Topic3   215.118942    silver                216.408737    1.8191    \n",
       "3849   Topic3   214.706818    survival              215.996613    1.8191    \n",
       "5556   Topic3   214.305344    isolate               215.606766    1.8191    \n",
       "848    Topic3   183.189499    mine                  184.479294    1.8181    \n",
       "5063   Topic3   181.227036    cage                  182.516830    1.8180    \n",
       "6540   Topic3   176.347015    epic                  177.636810    1.8178    \n",
       "984    Topic3   175.078049    ordinary              176.367844    1.8178    \n",
       "3417   Topic3   166.099335    remote                167.389130    1.8174    \n",
       "5117   Topic3   163.710861    cabin                 165.000656    1.8173    \n",
       "1243   Topic3   175.791519    tower                 177.188904    1.8172    \n",
       "7606   Topic3   161.110703    retain                162.400513    1.8171    \n",
       "1613   Topic3   960.943665    village               989.484558    1.7958    \n",
       "476    Topic3   421.631226    boat                  438.375702    1.7862    \n",
       "1430   Topic3   285.004852    hole                  292.262146    1.8000    \n",
       "1869   Topic3   506.996582    monster               535.448181    1.7705    \n",
       "737    Topic3   501.908813    tree                  539.005127    1.7538    \n",
       "5308   Topic3   304.300568    experiment            317.394867    1.7830    \n",
       "90     Topic3   1975.185547   group                 2407.386719   1.6272    \n",
       "1086   Topic3   739.238525    land                  856.954407    1.6774    \n",
       "467    Topic3   2044.605347   attack                2658.941650   1.5624    \n",
       "1697   Topic3   1391.669922   town                  1790.364868   1.5732    \n",
       "451    Topic3   1016.100403   rescue                1276.689941   1.5968    \n",
       "1650   Topic3   304.709412    farm                  325.369934    1.7595    \n",
       "2131   Topic3   697.544617    survive               880.866638    1.5918    \n",
       "395    Topic3   1348.222290   save                  2128.093994   1.3687    \n",
       "1832   Topic3   592.446838    dog                   763.260742    1.5718    \n",
       "474    Topic3   580.633484    blood                 750.380798    1.5687    \n",
       "444    Topic3   722.123352    capture               1020.574707   1.4792    \n",
       "1475   Topic3   490.941833    storm                 624.761963    1.5841    \n",
       "295    Topic3   1462.072510   escape                2742.801514   1.1960    \n",
       "336    Topic3   2727.330078   kill                  7238.985352   0.8490    \n",
       "77     Topic3   3246.053955   find                  10168.070312  0.6833    \n",
       "386    Topic3   705.729553    remain                1107.078857   1.3749    \n",
       "68     Topic3   597.745361    eye                   925.427246    1.3880    \n",
       "259    Topic3   828.731018    body                  1580.371460   1.1796    \n",
       "585    Topic3   561.211975    reach                 848.139648    1.4122    \n",
       "300    Topic3   1159.767334   fall                  2738.997314   0.9657    \n",
       "985    Topic3   638.625244    other                 1047.963745   1.3298    \n",
       "502    Topic3   1222.923828   discover              3227.090820   0.8548    \n",
       "270    Topic3   799.493408    cause                 1592.866821   1.1358    \n",
       "343    Topic3   1036.733521   lead                  2730.781982   0.8566    \n",
       "720    Topic3   1249.539917   return                4281.970215   0.5935    \n",
       "212    Topic3   1601.933594   take                  8357.747070   0.1731    \n",
       "663    Topic3   911.283020    die                   2350.564697   0.8776    \n",
       "225    Topic3   1036.664429   use                   3875.632324   0.5064    \n",
       "662    Topic3   668.819824    destroy               1174.069824   1.2624    \n",
       "307    Topic3   863.370483    force                 2823.899414   0.6401    \n",
       "187    Topic3   793.780518    set                   2241.945068   0.7868    \n",
       "318    Topic3   932.390137    help                  4142.804199   0.3337    \n",
       "15     Topic3   874.302185    back                  3906.315674   0.3282    \n",
       "116    Topic3   966.157349    leave                 6991.101074  -0.1539    \n",
       "10     Topic3   837.570923    arrive                3250.337158   0.4691    \n",
       "18     Topic3   856.984497    begin                 4167.069336   0.2436    \n",
       "14     Topic3   794.436951    attempt               2749.993408   0.5834    \n",
       "432    Topic3   797.862549    turn                  3052.350586   0.4834    \n",
       "1131   Topic4   792.252197    war                   793.562073    3.2514    \n",
       "726    Topic4   779.256348    soldier               780.566223    3.2513    \n",
       "2337   Topic4   575.790588    terrorist             577.100464    3.2507    \n",
       "2460   Topic4   391.118103    german                392.427979    3.2497    \n",
       "1846   Topic4   223.361389    british               224.671265    3.2472    \n",
       "1491   Topic4   201.764297    troop                 203.074173    3.2465    \n",
       "5298   Topic4   198.199051    ally                  199.508926    3.2464    \n",
       "656    Topic4   186.986649    chinese               188.296524    3.2460    \n",
       "2892   Topic4   180.253876    assassin              181.563751    3.2458    \n",
       "4324   Topic4   179.996002    japanese              181.305878    3.2458    \n",
       "3846   Topic4   163.350113    rebel                 164.659988    3.2450    \n",
       "4859   Topic4   160.593704    international         161.903580    3.2449    \n",
       "1365   Topic4   152.521545    ruthless              153.831421    3.2445    \n",
       "6062   Topic4   146.511429    mercenary             147.821304    3.2441    \n",
       "5143   Topic4   133.357117    nation                134.666992    3.2432    \n",
       "5629   Topic4   132.801453    rebellion             134.111328    3.2432    \n",
       "3224   Topic4   131.544571    economic              132.854446    3.2431    \n",
       "1284   Topic4   126.087265    alliance              127.397156    3.2427    \n",
       "1392   Topic4   121.857765    combat                123.167656    3.2423    \n",
       "5526   Topic4   97.272362     refugee               98.582253     3.2396    \n",
       "2724   Topic4   91.653290     assassinate           92.963181     3.2388    \n",
       "3491   Topic4   86.096695     hack                  87.406586     3.2379    \n",
       "702    Topic4   82.643570     medal                 83.953461     3.2373    \n",
       "5608   Topic4   80.786606     abroad                82.096497     3.2369    \n",
       "6011   Topic4   79.257294     frost                 80.567184     3.2366    \n",
       "1539   Topic4   77.658394     colonel               78.968285     3.2363    \n",
       "1379   Topic4   77.577087     bombing               78.886978     3.2363    \n",
       "6183   Topic4   69.495216     opposition            70.805107     3.2343    \n",
       "2613   Topic4   69.090981     nazi                  70.400871     3.2342    \n",
       "6081   Topic4   67.278954     rogue                 68.588844     3.2337    \n",
       "2304   Topic4   570.411316    government            584.409546    3.2288    \n",
       "1039   Topic4   575.214844    bomb                  591.377380    3.2253    \n",
       "1710   Topic4   102.766907    agency                105.548920    3.2263    \n",
       "1495   Topic4   142.813538    unit                  152.379120    3.1882    \n",
       "3060   Topic4   204.949356    russian               226.808548    3.1517    \n",
       "2661   Topic4   143.432648    detonate              154.029434    3.1817    \n",
       "1362   Topic4   121.786324    assassination         129.365631    3.1926    \n",
       "703    Topic4   431.684723    military              529.458923    3.0488    \n",
       "1411   Topic4   330.853912    enemy                 396.761414    3.0713    \n",
       "4776   Topic4   357.446381    spy                   436.914368    3.0523    \n",
       "2222   Topic4   755.553650    agent                 1044.792725   2.9289    \n",
       "2561   Topic4   344.511871    american              429.326538    3.0329    \n",
       "1450   Topic4   587.546326    mission               809.525879    2.9325    \n",
       "1337   Topic4   269.918793    prisoner              343.790833    3.0111    \n",
       "646    Topic4   495.218414    battle                873.251282    2.6858    \n",
       "2677   Topic4   161.001968    invasion              182.740799    3.1264    \n",
       "1677   Topic4   196.720718    recruit               249.455933    3.0155    \n",
       "455    Topic4   622.645325    team                  1628.742432   2.2914    \n",
       "859    Topic4   221.029480    political             313.830292    2.9025    \n",
       "982    Topic4   234.495300    operation             356.863770    2.8331    \n",
       "140    Topic4   599.835632    order                 2257.205322   1.9278    \n",
       "3427   Topic4   250.883255    target                478.050446    2.6083    \n",
       "307    Topic4   551.885620    force                 2823.899414   1.6205    \n",
       "1008   Topic4   377.633209    secret                1262.161133   2.0464    \n",
       "645    Topic4   563.117859    base                  3578.428467   1.4038    \n",
       "304    Topic4   423.350250    fight                 2813.795410   1.3589    \n",
       "365    Topic4   329.975372    officer               1356.695801   1.8392    \n",
       "344    Topic4   265.533447    leader                666.318665    2.3330    \n",
       "444    Topic4   269.009644    capture               1020.574707   1.9196    \n",
       "343    Topic4   327.924988    lead                  2730.781982   1.1334    \n",
       "336    Topic4   388.270935    kill                  7238.985352   0.3275    \n",
       "351    Topic4   361.565155    man                   6185.935547   0.4134    \n",
       "467    Topic4   244.641769    attack                2658.941650   0.8671    \n",
       "1118   Topic5   664.122925    ship                  665.422974    3.6423    \n",
       "1033   Topic5   541.108826    alien                 542.408875    3.6419    \n",
       "1115   Topic5   399.857605    scientist             401.157654    3.6410    \n",
       "1120   Topic5   374.513123    space                 375.813171    3.6408    \n",
       "452    Topic5   300.923889    robot                 302.223938    3.6400    \n",
       "2023   Topic5   288.831543    planet                290.131592    3.6398    \n",
       "2063   Topic5   240.816696    technology            242.116760    3.6389    \n",
       "2059   Topic5   161.636841    super                 162.936905    3.6363    \n",
       "5947   Topic5   154.675766    universe              155.975830    3.6359    \n",
       "1121   Topic5   154.428192    spacecraft            155.728256    3.6359    \n",
       "5023   Topic5   152.635727    global                153.935791    3.6358    \n",
       "2743   Topic5   152.012207    nuclear               153.312271    3.6358    \n",
       "5163   Topic5   150.195572    submarine             151.495636    3.6357    \n",
       "5919   Topic5   149.548676    kyle                  150.848740    3.6356    \n",
       "4462   Topic5   127.371674    engine                128.671738    3.6341    \n",
       "3391   Topic5   117.125893    communication         118.425980    3.6332    \n",
       "2328   Topic5   102.732506    resistance            104.032593    3.6317    \n",
       "1046   Topic5   102.250565    clone                 103.550652    3.6316    \n",
       "1954   Topic5   88.630417     core                  89.930511     3.6297    \n",
       "2860   Topic5   80.709663     laboratory            82.009750     3.6283    \n",
       "5154   Topic5   79.028961     sailor                80.329048     3.6280    \n",
       "2044   Topic5   76.433746     satellite             77.733833     3.6274    \n",
       "2747   Topic5   71.055992     science               72.356079     3.6262    \n",
       "5015   Topic5   68.723289     crystal               70.023384     3.6255    \n",
       "2851   Topic5   64.557732     genetic               65.857819     3.6243    \n",
       "3789   Topic5   61.599037     inventor              62.899128     3.6234    \n",
       "3498   Topic5   60.761059     laser                 62.061150     3.6231    \n",
       "4404   Topic5   58.550014     phenomenon            59.850105     3.6223    \n",
       "5268   Topic5   57.866451     dystopia              59.166542     3.6221    \n",
       "6797   Topic5   56.566792     liquid                57.866882     3.6216    \n",
       "1066   Topic5   599.427673    earth                 641.082153    3.5771    \n",
       "1959   Topic5   181.714142    device                193.250809    3.5827    \n",
       "1336   Topic5   128.561935    pirate                137.950851    3.5738    \n",
       "971    Topic5   305.730103    machine               363.120270    3.4723    \n",
       "1304   Topic5   501.504639    crew                  706.777283    3.3012    \n",
       "1080   Topic5   118.283836    humanity              134.124756    3.5186    \n",
       "2096   Topic5   151.222061    engineer              207.389160    3.3284    \n",
       "6812   Topic5   135.436569    brain                 180.992813    3.3543    \n",
       "1238   Topic5   222.574554    system                385.116241    3.0960    \n",
       "1951   Topic5   195.831894    computer              327.614685    3.1297    \n",
       "1079   Topic5   391.172394    human                 1033.917725   2.6723    \n",
       "662    Topic5   331.273804    destroy               1174.069824   2.3790    \n",
       "2679   Topic5   141.137878    launch                225.210571    3.1770    \n",
       "1450   Topic5   220.822311    mission               809.525879    2.3452    \n",
       "225    Topic5   380.444397    use                   3875.632324   1.3232    \n",
       "861    Topic5   224.865860    power                 957.790283    2.1952    \n",
       "276    Topic5   217.589554    crash                 882.718811    2.2439    \n",
       "899    Topic5   259.558838    world                 1712.780273   1.7574    \n",
       "489    Topic5   206.365509    control               807.500977    2.2800    \n",
       "48     Topic5   186.090759    create                670.351257    2.3627    \n",
       "279    Topic5   154.825821    damage                313.082031    2.9401    \n",
       "455    Topic5   165.812256    team                  1628.742432   1.3596    \n",
       "1072   Topic5   159.896484    fly                   821.873108    2.0072    \n",
       "448    Topic6   566.838623    evil                  568.181335    3.9430    \n",
       "1615   Topic6   371.865570    warrior               373.208252    3.9418    \n",
       "4789   Topic6   334.927948    comic                 336.270630    3.9414    \n",
       "4223   Topic6   319.746033    ghost                 321.088715    3.9412    \n",
       "4144   Topic6   265.516113    magic                 266.858795    3.9403    \n",
       "5902   Topic6   220.794266    supernatural          222.136963    3.9393    \n",
       "4126   Topic6   211.063873    demon                 212.406570    3.9390    \n",
       "4301   Topic6   197.733612    spirit                199.076309    3.9386    \n",
       "2904   Topic6   179.416962    king                  180.759659    3.9379    \n",
       "1512   Topic6   178.394714    modern                179.737411    3.9379    \n",
       "3560   Topic6   171.934494    slave                 173.277191    3.9376    \n",
       "235    Topic6   171.086288    witch                 172.428986    3.9376    \n",
       "2091   Topic6   164.202911    cure                  165.545609    3.9372    \n",
       "2915   Topic6   140.211914    sword                 141.554611    3.9358    \n",
       "4809   Topic6   136.671295    superhero_base        138.013992    3.9356    \n",
       "1034   Topic6   131.159454    ancient               132.502151    3.9352    \n",
       "4315   Topic6   128.721649    dragon                130.064346    3.9350    \n",
       "4285   Topic6   126.506584    god                   127.849304    3.9348    \n",
       "199    Topic6   107.512978    spell                 108.855698    3.9330    \n",
       "6984   Topic6   95.180008     pastor                96.522728     3.9314    \n",
       "3565   Topic6   91.642693     throne                92.985413     3.9308    \n",
       "4305   Topic6   90.440735     wolf                  91.783455     3.9306    \n",
       "1042   Topic6   84.862419     century               86.205139     3.9297    \n",
       "1250   Topic6   80.189774     unleash               81.532494     3.9288    \n",
       "2119   Topic6   79.103943     plague                80.446663     3.9285    \n",
       "3842   Topic6   195.605606    possess               199.166107    3.9273    \n",
       "6056   Topic6   69.061348     kingdom               70.404068     3.9261    \n",
       "5897   Topic6   67.029640     psychic               68.372360     3.9255    \n",
       "3305   Topic6   66.224083     knight                67.566803     3.9253    \n",
       "4556   Topic6   65.401764     entity                66.744484     3.9250    \n",
       "1101   Topic6   245.810699    priest                294.363495    3.7651    \n",
       "1305   Topic6   206.492661    curse                 262.523865    3.7053    \n",
       "4498   Topic6   144.798706    haunt                 181.168884    3.7213    \n",
       "1876   Topic6   175.755127    soul                  236.038010    3.6505    \n",
       "861    Topic6   474.679565    power                 957.790283    3.2434    \n",
       "2028   Topic6   226.136932    powerful              387.279938    3.4074    \n",
       "899    Topic6   463.734436    world                 1712.780273   2.6388    \n",
       "3405   Topic6   219.539581    hero                  486.509888    3.1496    \n",
       "646    Topic6   239.732208    battle                873.251282    2.6527    \n",
       "1058   Topic6   163.166031    defeat                402.307404    3.0429    \n",
       "1203   Topic6   187.814102    mysterious            801.872131    2.4939    \n",
       "645    Topic6   245.395233    base                  3578.428467   1.2656    \n",
       "131    Topic6   204.756271    must                  1681.562134   1.8397    \n",
       "4125   Topic6   159.923294    dark                  483.474091    2.8391    \n",
       "225    Topic6   159.959579    use                   3875.632324   0.7578    \n",
       "395    Topic6   156.035126    save                  2128.093994   1.3325    \n",
       "304    Topic6   152.420166    fight                 2813.795410   1.0297    \n",
       "2246   Topic7   354.344849    investigation         355.681366    4.0225    \n",
       "6686   Topic7   226.487000    conspiracy            227.823563    4.0203    \n",
       "3658   Topic7   225.265717    corruption            226.602280    4.0203    \n",
       "5059   Topic7   121.394890    activist              122.731461    4.0153    \n",
       "1395   Topic7   85.373604     corporate             86.710175     4.0107    \n",
       "2177   Topic7   81.539017     incredible            82.875587     4.0100    \n",
       "2267   Topic7   78.346329     surveillance          79.682899     4.0093    \n",
       "6702   Topic7   59.974709     selene                61.311287     4.0042    \n",
       "3029   Topic7   58.618256     cartel                59.954834     4.0037    \n",
       "6695   Topic7   56.452335     lycan                 57.788914     4.0028    \n",
       "4085   Topic7   56.147011     espionage             57.483589     4.0027    \n",
       "5447   Topic7   52.160324     abruptly              53.496902     4.0009    \n",
       "5866   Topic7   48.105553     gus                   49.442127     3.9988    \n",
       "4582   Topic7   44.521923     minister              45.858501     3.9967    \n",
       "7358   Topic7   38.406918     ethic                 39.743496     3.9920    \n",
       "479    Topic7   36.159702     bruce                 37.496277     3.9899    \n",
       "2640   Topic7   35.279541     testify               36.616116     3.9890    \n",
       "6872   Topic7   34.616730     raucous               35.953312     3.9883    \n",
       "2231   Topic7   34.291512     collin                35.628086     3.9880    \n",
       "5863   Topic7   32.851059     expire                34.187637     3.9864    \n",
       "6033   Topic7   32.034737     dean                  33.371311     3.9854    \n",
       "5797   Topic7   31.830429     eve                   33.167007     3.9851    \n",
       "3457   Topic7   31.481770     implicate             32.818348     3.9847    \n",
       "2885   Topic7   30.075439     tech                  31.412014     3.9828    \n",
       "6646   Topic7   28.277649     manhunt               29.614216     3.9800    \n",
       "4025   Topic7   27.367365     courtroom             28.703932     3.9785    \n",
       "3786   Topic7   26.329082     impending             27.665655     3.9767    \n",
       "6653   Topic7   25.610575     profile               26.947142     3.9754    \n",
       "6029   Topic7   25.076664     capacity              26.413237     3.9743    \n",
       "5266   Topic7   24.982672     dilemma               26.319241     3.9741    \n",
       "850    Topic7   214.345306    mystery               228.195618    3.9636    \n",
       "1025   Topic7   203.498978    trial                 234.143921    3.8860    \n",
       "1041   Topic7   504.056000    case                  733.557556    3.6510    \n",
       "1202   Topic7   1411.431274   murder                2312.857422   3.5324    \n",
       "881    Topic7   151.764496    solve                 197.871506    3.7609    \n",
       "968    Topic7   246.844604    lawyer                349.013885    3.6799    \n",
       "1802   Topic7   142.080460    firm                  187.974518    3.7463    \n",
       "1641   Topic7   475.602692    crime                 785.759399    3.5242    \n",
       "869    Topic7   159.721207    reporter              243.133377    3.6061    \n",
       "2234   Topic7   253.082077    detective             438.286560    3.4771    \n",
       "1668   Topic7   101.728607    murderer              141.735641    3.6946    \n",
       "297    Topic7   222.323822    evidence              385.999634    3.4745    \n",
       "1127   Topic7   127.269630    undercover            201.185211    3.5683    \n",
       "3657   Topic7   174.925690    corrupt               347.628113    3.3395    \n",
       "3032   Topic7   155.603485    commit                303.723114    3.3574    \n",
       "2630   Topic7   130.011078    sentence              245.326965    3.3913    \n",
       "4034   Topic7   89.786293     judge                 141.980072    3.5680    \n",
       "331    Topic7   228.007751    investigate           657.677856    2.9669    \n",
       "3348   Topic7   243.754089    killer                737.019287    2.9198    \n",
       "2579   Topic7   136.627457    court                 317.312286    3.1836    \n",
       "2217   Topic7   148.252029    victim                406.718414    3.0170    \n",
       "993    Topic7   257.396942    prison                1284.141968   2.4190    \n",
       "373    Topic7   393.064728    police                3397.069824   1.8695    \n",
       "1130   Topic7   164.661057    violence              595.815491    2.7402    \n",
       "1354   Topic7   156.016937    suspect               532.339600    2.7989    \n",
       "277    Topic7   125.543884    criminal              584.032837    2.4889    \n",
       "281    Topic7   176.632065    death                 2943.899658   1.2128    \n",
       "438    Topic7   113.720337    witness               513.707275    2.5183    \n",
       "2354   Topic8   330.311432    band                  331.669037    4.5893    \n",
       "3194   Topic8   206.677994    singer                208.035660    4.5869    \n",
       "1503   Topic8   151.695862    concert               153.053528    4.5845    \n",
       "1013   Topic8   133.092255    song                  134.449921    4.5833    \n",
       "7399   Topic8   106.430817    producer              107.788483    4.5808    \n",
       "2184   Topic8   86.899269     lily                  88.256935     4.5779    \n",
       "2212   Topic8   86.513924     studio                87.871590     4.5779    \n",
       "3793   Topic8   86.149040     marty                 87.506706     4.5778    \n",
       "2350   Topic8   68.799088     audition              70.156754     4.5739    \n",
       "6348   Topic8   64.736794     dave                  66.094460     4.5727    \n",
       "1347   Topic8   57.204277     singing               58.561951     4.5700    \n",
       "779    Topic8   43.471161     satire                44.828835     4.5627    \n",
       "3714   Topic8   35.054901     porn                  36.412575     4.5554    \n",
       "3795   Topic8   34.187359     misfit                35.545033     4.5545    \n",
       "2585   Topic8   33.207783     derek                 34.565453     4.5534    \n",
       "5404   Topic8   31.823309     script                33.180981     4.5517    \n",
       "751    Topic8   31.518744     broker                32.876415     4.5513    \n",
       "2346   Topic8   27.012993     addiction             28.370657     4.5444    \n",
       "6626   Topic8   23.989819     catherine             25.347481     4.5384    \n",
       "2381   Topic8   23.656101     guitar                25.013763     4.5376    \n",
       "744    Topic8   19.416182     academy               20.773849     4.5258    \n",
       "2880   Topic8   17.582291     sebastian             18.939955     4.5191    \n",
       "6648   Topic8   16.899319     multi                 18.256987     4.5162    \n",
       "2410   Topic8   16.887472     solace                18.245138     4.5161    \n",
       "2186   Topic8   16.709541     onstage               18.067204     4.5153    \n",
       "4235   Topic8   16.089771     royalty               17.447435     4.5124    \n",
       "3781   Topic8   15.905409     fusion                17.263075     4.5115    \n",
       "4662   Topic8   15.001346     province              16.359011     4.5068    \n",
       "5682   Topic8   14.277593     harmony               15.635255     4.5026    \n",
       "6962   Topic8   13.971333     choir                 15.328995     4.5007    \n",
       "5318   Topic8   106.891212    production            128.924789    4.4060    \n",
       "1019   Topic8   167.143143    theater               208.480133    4.3724    \n",
       "2515   Topic8   171.372635    actor                 219.471741    4.3461    \n",
       "1513   Topic8   335.743317    music                 467.771423    4.2618    \n",
       "2189   Topic8   191.262817    performance           266.879517    4.2603    \n",
       "3702   Topic8   88.848991     fame                  114.691895    4.3381    \n",
       "976    Topic8   188.782822    musical               279.590820    4.2007    \n",
       "3571   Topic8   69.948250     actress               104.172806    4.1951    \n",
       "2132   Topic8   118.420250    tour                  210.132431    4.0199    \n",
       "56     Topic8   123.596436    director              222.909744    4.0037    \n",
       "454    Topic8   197.596298    star                  424.276520    3.8293    \n",
       "2349   Topic8   159.480545    audience              329.750000    3.8670    \n",
       "76     Topic8   602.012817    film                  2622.349365   3.1219    \n",
       "1231   Topic8   149.103256    stage                 363.002625    3.7037    \n",
       "148    Topic8   215.955368    perform               664.546936    3.4694    \n",
       "55     Topic8   109.345711    direct                281.589996    3.6475    \n",
       "174    Topic8   109.373367    role                  298.289551    3.5901    \n",
       "75     Topic8   107.389381    feature               309.792847    3.5340    \n",
       "191    Topic8   340.016235    show                  3506.412354   2.2601    \n",
       "130    Topic8   178.002213    movie                 992.760498    2.8747    \n",
       "579    Topic8   189.392609    play                  1356.658691   2.6245    \n",
       "4418   Topic8   105.208191    tv                    361.683044    3.3586    \n",
       "775    Topic8   91.775352     record                474.643829    2.9502    \n",
       "2214   Topic9   237.832443    tournament            239.194336    4.6981    \n",
       "2519   Topic9   189.108688    billy                 190.471436    4.6966    \n",
       "713    Topic9   172.171555    player                173.533447    4.6959    \n",
       "2549   Topic9   160.499878    sport                 161.861771    4.6954    \n",
       "2435   Topic9   123.509766    championship          124.871658    4.6928    \n",
       "2478   Topic9   105.613899    opponent              106.975792    4.6910    \n",
       "7460   Topic9   89.236435     champion              90.598328     4.6887    \n",
       "6589   Topic9   83.452034     superhero             84.813927     4.6876    \n",
       "2565   Topic9   66.503349     basketball            67.865242     4.6835    \n",
       "2503   Topic9   65.810074     trainer               67.171967     4.6833    \n",
       "3725   Topic9   63.188671     wizard                64.550568     4.6825    \n",
       "4018   Topic9   59.965446     baseball              61.327343     4.6814    \n",
       "2432   Topic9   48.706226     boxer                 50.068123     4.6762    \n",
       "2518   Topic9   47.434250     ballet                48.796146     4.6755    \n",
       "2545   Topic9   34.025085     scholarship           35.386986     4.6646    \n",
       "1342   Topic9   28.400520     runner                29.762411     4.6570    \n",
       "4695   Topic9   27.317402     reggie                28.679293     4.6552    \n",
       "6613   Topic9   25.714184     unscrupulous          27.076077     4.6522    \n",
       "5344   Topic9   24.670073     racer                 26.031961     4.6501    \n",
       "4220   Topic9   23.137165     eagle                 24.499058     4.6466    \n",
       "4239   Topic9   22.218540     troll                 23.580433     4.6443    \n",
       "2889   Topic9   18.921000     unicorn               20.282892     4.6343    \n",
       "2136   Topic9   18.906258     viral                 20.268152     4.6343    \n",
       "2433   Topic9   18.652203     boxing                20.014093     4.6333    \n",
       "4115   Topic9   16.948841     willy                 18.310734     4.6265    \n",
       "747    Topic9   14.872009     angela                16.233904     4.6162    \n",
       "2438   Topic9   134.590485    coach                 148.074310    4.6083    \n",
       "4129   Topic9   13.384284     elve                  14.746174     4.6069    \n",
       "1919   Topic9   13.242662     richie                14.604552     4.6059    \n",
       "7043   Topic9   12.715676     payroll               14.077568     4.6021    \n",
       "2112   Topic9   668.843384    match                 832.308899    4.4852    \n",
       "657    Topic9   103.484718    compete               131.225098    4.4663    \n",
       "1860   Topic9   375.775513    game                  544.641541    4.3327    \n",
       "2065   Topic9   232.477386    title                 405.766846    4.1468    \n",
       "455    Topic9   733.392944    team                  1628.742432   3.9059    \n",
       "5328   Topic9   114.960716    competition           190.978989    4.1962    \n",
       "2220   Topic9   276.029846    win                   698.794922    3.7750    \n",
       "3254   Topic9   64.366516     season                116.435165    4.1111    \n",
       "1103   Topic9   234.931366    race                  740.353821    3.5560    \n",
       "951    Topic9   140.065216    final                 820.439026    2.9361    \n",
       "304    Topic9   225.432663    fight                 2813.795410   2.1795    \n",
       "3013   Topic9   50.723846     score                 123.789101    3.8116    \n",
       "579    Topic9   140.154556    play                  1356.658691   2.4338    \n",
       "28     Topic9   74.453964     challenge             333.173462    3.2053    \n",
       "1058   Topic9   69.042534     defeat                402.307404    2.9413    \n",
       "522    Topic9   62.330173     field                 347.711182    2.9849    \n",
       "1489   Topic9   55.993591     training              248.997055    3.2116    \n",
       "6398   Topic10  112.668503    molly                 114.056396    5.7221    \n",
       "7313   Topic10  74.612961     lgbt                  76.000854     5.7159    \n",
       "608    Topic10  57.800972     shark                 59.188869     5.7106    \n",
       "3472   Topic10  53.235538     sequel                54.623440     5.7086    \n",
       "1644   Topic10  44.571262     dialogue              45.959160     5.7037    \n",
       "6911   Topic10  42.460693     annie                 43.848591     5.7022    \n",
       "468    Topic10  33.160809     australian            34.548710     5.6934    \n",
       "1442   Topic10  29.499063     lance                 30.886955     5.6884    \n",
       "3568   Topic10  29.420486     undefeated            30.808388     5.6883    \n",
       "5992   Topic10  29.311264     brandon               30.699156     5.6881    \n",
       "6326   Topic10  28.722212     interesting           30.110104     5.6872    \n",
       "6997   Topic10  28.677429     amateur               30.065327     5.6871    \n",
       "1605   Topic10  24.280439     tiger                 25.668457     5.6788    \n",
       "6929   Topic10  24.161121     rocky                 25.549013     5.6785    \n",
       "4823   Topic10  23.944258     disabled              25.332151     5.6780    \n",
       "6930   Topic10  23.490337     rookie                24.878235     5.6769    \n",
       "1012   Topic10  22.874144     small_town            24.262035     5.6754    \n",
       "630    Topic10  22.504438     whale                 23.892330     5.6745    \n",
       "6851   Topic10  21.425606     athletic              22.813498     5.6716    \n",
       "3058   Topic10  20.735939     realization           22.123833     5.6696    \n",
       "3091   Topic10  20.676762     fisherman             22.064657     5.6694    \n",
       "3129   Topic10  20.472691     tick                  21.860584     5.6688    \n",
       "2394   Topic10  19.567802     peak                  20.955698     5.6658    \n",
       "7143   Topic10  19.297125     biker                 20.685017     5.6649    \n",
       "618    Topic10  17.667456     surf                  19.055347     5.6587    \n",
       "6402   Topic10  16.843853     poltergeist           18.231745     5.6552    \n",
       "7181   Topic10  16.286739     toast                 17.674633     5.6526    \n",
       "3394   Topic10  15.088082     dottie                16.475973     5.6464    \n",
       "4905   Topic10  14.191010     sculpture             15.578904     5.6410    \n",
       "7312   Topic10  13.563566     feud                  14.951461     5.6369    \n",
       "7658   Topic10  14.206916     chapter               23.265301     5.2411    \n",
       "2526   Topic11  121.657082    dancer                123.050125    5.7663    \n",
       "4431   Topic11  100.722778    gay                   102.115822    5.7639    \n",
       "988    Topic11  63.227238     penny                 64.620277     5.7559    \n",
       "3229   Topic11  52.002136     france                53.395180     5.7512    \n",
       "3430   Topic11  49.579651     wed                   50.972698     5.7500    \n",
       "3259   Topic11  42.508907     sibling_relationship  43.901955     5.7454    \n",
       "3236   Topic11  37.806679     jake                  39.199726     5.7415    \n",
       "1675   Topic11  37.348274     ranch                 38.741322     5.7411    \n",
       "3207   Topic11  34.146259     abortion              35.539307     5.7377    \n",
       "2701   Topic11  31.442871     robbie                32.835918     5.7343    \n",
       "5656   Topic11  29.714037     historical            31.107080     5.7319    \n",
       "756    Topic11  28.224155     dancing               29.617197     5.7295    \n",
       "2210   Topic11  26.890673     stephanie             28.283714     5.7272    \n",
       "4626   Topic11  26.508873     inspiration           27.901915     5.7265    \n",
       "6748   Topic11  25.774525     commission            27.167570     5.7250    \n",
       "3209   Topic11  24.571754     affluent              25.964798     5.7225    \n",
       "4014   Topic11  21.777527     tennis                23.170570     5.7157    \n",
       "4544   Topic11  18.880249     compose               20.273293     5.7065    \n",
       "3257   Topic11  18.856812     sexy                  20.249857     5.7064    \n",
       "4449   Topic11  18.294182     totally               19.687223     5.7043    \n",
       "3243   Topic11  18.186857     pennys                19.579899     5.7039    \n",
       "4622   Topic11  16.968861     greek                 18.361904     5.6988    \n",
       "3227   Topic11  15.596787     everyone              16.989830     5.6921    \n",
       "3272   Topic11  14.073375     waiter                15.466420     5.6833    \n",
       "6778   Topic11  13.993120     premiere              15.386163     5.6828    \n",
       "3246   Topic11  13.965240     polly                 15.358280     5.6826    \n",
       "6773   Topic11  13.583713     narrative             14.976755     5.6801    \n",
       "3270   Topic11  13.269047     unwanted              14.662089     5.6778    \n",
       "7293   Topic11  12.743870     sonny                 14.136911     5.6739    \n",
       "6777   Topic11  12.495284     pledge                13.888326     5.6720    \n",
       "659    Topic11  158.595352    dance                 537.420776    4.5573    \n",
       "4799   Topic11  42.852169     lucky                 95.300026     4.9784    \n",
       "5643   Topic11  32.483948     biological            76.587791     4.9200    \n",
       "4428   Topic11  14.769880     classmate             234.861084    3.0113    \n",
       "738    Topic12  73.319489     virus                 74.708687     5.8575    \n",
       "6490   Topic12  15.362153     indigenous            16.751352     5.7897    \n",
       "3123   Topic12  14.969583     seth                  16.358778     5.7875    \n",
       "7659   Topic12  14.825666     countdown             16.214872     5.7867    \n",
       "4771   Topic12  11.639655     remotely              13.028886     5.7635    \n",
       "7003   Topic12  11.379482     firefighter           12.768678     5.7611    \n",
       "4753   Topic12  9.857837      alpha                 11.247033     5.7444    \n",
       "7666   Topic12  7.928021      parasite              9.317218      5.7148    \n",
       "5079   Topic12  7.921782      infected              9.310977      5.7147    \n",
       "5066   Topic12  7.630448      chimp                 9.019643      5.7090    \n",
       "1991   Topic12  7.150779      hal                   8.539974      5.6987    \n",
       "1752   Topic12  6.430190      pollution             7.819389      5.6807    \n",
       "5091   Topic12  6.106236      quarantine            7.495432      5.6713    \n",
       "3422   Topic12  5.874177      shuttle               7.263376      5.6640    \n",
       "1554   Topic12  5.786269      hick                  7.175467      5.6611    \n",
       "4991   Topic12  4.186476      undo                  5.575677      5.5897    \n",
       "7421   Topic12  3.896984      runway                5.286180      5.5714    \n",
       "5086   Topic12  3.102545      platoon               4.491750      5.5063    \n",
       "3501   Topic12  2.958649      mainframe             4.347847      5.4913    \n",
       "6638   Topic12  2.800786      goggle                4.189983      5.4735    \n",
       "2430   Topic12  204.389572    bond                  309.200378    5.4623    \n",
       "2650   Topic12  44.771877     airplane              68.306602     5.4539    \n",
       "1458   Topic12  186.087158    plane                 289.847992    5.4331    \n",
       "2052   Topic12  2.225495      spacesuit             3.614697      5.3913    \n",
       "3510   Topic12  1.895510      reconstruct           3.284707      5.3265    \n",
       "5080   Topic12  20.233322     infection             35.953785     5.3014    \n",
       "2010   Topic12  1.381246      manually              2.770460      5.1803    \n",
       "5067   Topic12  4.531295      chimpanzee            9.413622      5.1451    \n",
       "2467   Topic12  25.346117     infect                53.515873     5.1289    \n",
       "2013   Topic12  1.040941      module                2.430137      5.0285    \n",
       "2694   Topic12  79.033897     pilot                 204.711227    4.9246    \n",
       "2668   Topic12  72.665894     flight                242.813507    4.6699    \n",
       "3001   Topic12  31.750862     passenger             145.466476    4.3543    \n",
       "5060   Topic12  8.653102      aircraft              97.115700     3.4583    \n",
       "2079   Topic12  9.146605      airport               172.908020    2.9369    \n",
       "3025   Topic12  5.244888      aerial                31.581810     4.0810    \n",
       "1072   Topic12  10.488916     fly                   821.873108    1.5150    \n",
       "6000   Topic12  5.374027      operative             164.089355    2.4574    \n",
       "913    Topic12  4.719728      board                 302.512634    1.7159    \n",
       "2562   Topic13  27.826954     angel                 29.250834     6.8309    \n",
       "4617   Topic13  27.679615     circus                29.103495     6.8307    \n",
       "4086   Topic13  12.649358     expand                14.073238     6.7742    \n",
       "1938   Topic13  12.150048     ape                   13.573927     6.7700    \n",
       "6894   Topic13  11.822582     fountain              13.246462     6.7671    \n",
       "6234   Topic13  6.490610      suburb                7.914490      6.6825    \n",
       "4569   Topic13  6.080450      happening             7.504333      6.6704    \n",
       "4228   Topic13  5.456045      lava                  6.879930      6.6490    \n",
       "6126   Topic13  4.683290      conscious             6.107171      6.6154    \n",
       "6828   Topic13  4.229840      lenny                 5.653719      6.5907    \n",
       "6956   Topic13  4.080606      rick                  5.504487      6.5815    \n",
       "4392   Topic13  3.173348      endeavor              4.597228      6.5102    \n",
       "6141   Topic13  3.063991      yearn                 4.487871      6.4992    \n",
       "6325   Topic13  2.912780      fiona                 4.336659      6.4828    \n",
       "6130   Topic13  2.908949      empowerment           4.332831      6.4824    \n",
       "7507   Topic13  2.699500      storyline             4.123381      6.4572    \n",
       "6131   Topic13  2.426568      glamorous             3.850447      6.4191    \n",
       "6125   Topic13  2.094040      cheque                3.517922      6.3621    \n",
       "4630   Topic13  1.925130      mortality             3.349016      6.3272    \n",
       "2073   Topic13  1.902898      vacuum                3.326778      6.3222    \n",
       "4237   Topic13  1.900283      steward               3.324162      6.3216    \n",
       "6921   Topic13  1.498702      latch                 2.922589      6.2130    \n",
       "6135   Topic13  1.437418      perpetual             2.861298      6.1924    \n",
       "7338   Topic13  1.332906      reptile               2.756785      6.1541    \n",
       "5654   Topic13  0.720429      dick                  2.144308      5.7901    \n",
       "5795   Topic13  0.453814      cornfield             1.877694      5.4607    \n",
       "6137   Topic13  0.418419      psychologically       1.842298      5.3985    \n",
       "4623   Topic13  0.376772      grown_tire            1.800651      5.3166    \n",
       "4614   Topic13  0.278112      berlin                1.701990      5.0693    \n",
       "4642   Topic13  0.188891      unheard               1.612770      4.7363    \n",
       "3402   Topic14  30.811188     grace                 32.235283     6.8414    \n",
       "3384   Topic14  27.232189     victor                28.656282     6.8356    \n",
       "4472   Topic14  27.108938     rabbit                28.533031     6.8354    \n",
       "2556   Topic14  19.984144     widow                 21.408239     6.8177    \n",
       "2902   Topic14  13.469695     ideal                 14.893789     6.7861    \n",
       "7539   Topic14  8.026186      awful                 9.450281      6.7232    \n",
       "7344   Topic14  6.067144      extent                7.491239      6.6757    \n",
       "6770   Topic14  5.131292      miraculous            6.555388      6.6416    \n",
       "6994   Topic14  2.822033      sculptor              4.246126      6.4780    \n",
       "3351   Topic14  2.718010      maverick              4.142103      6.4653    \n",
       "2911   Topic14  2.384613      scroll                3.808706      6.4183    \n",
       "4474   Topic14  2.245204      roberta               3.669297      6.3954    \n",
       "2411   Topic14  2.031502      vivian                3.455595      6.3554    \n",
       "4274   Topic14  1.304598      amazed                2.728691      6.1486    \n",
       "1027   Topic14  1.216273      underlie              2.640368      6.1114    \n",
       "5282   Topic14  0.948990      poise                 2.373083      5.9700    \n",
       "7685   Topic14  0.913876      idiot                 2.337969      5.9472    \n",
       "1029   Topic14  0.677002      upsetting             2.101094      5.7540    \n",
       "2918   Topic14  0.264580      unify                 1.688673      5.0330    \n",
       "25566  Topic14  0.028722      pooh                  1.453371      2.9626    \n",
       "27423  Topic14  0.028721      eeyore                1.453352      2.9626    \n",
       "20573  Topic14  0.028699      sparky                1.453070      2.9620    \n",
       "32657  Topic14  0.028686      bruza                 1.452879      2.9617    \n",
       "34588  Topic14  0.028686      sakhavu               1.453215      2.9615    \n",
       "18441  Topic14  0.028686      hurdle                1.453239      2.9614    \n",
       "9809   Topic14  0.028686      communism             1.453352      2.9614    \n",
       "17616  Topic14  0.028695      owl                   1.454137      2.9611    \n",
       "18775  Topic14  0.028666      brothel               1.452883      2.9610    \n",
       "31573  Topic14  0.028662      cordelia              1.452838      2.9609    \n",
       "22531  Topic14  0.028669      illusionist           1.453340      2.9608    \n",
       "15134  Topic14  0.028670      brent                 1.453427      2.9607    \n",
       "31825  Topic14  0.028677      suraj                 1.455457      2.9596    \n",
       "2535   Topic15  11.451269     miner                 12.885513     7.2558    \n",
       "3932   Topic15  10.805567     expensive             12.239813     7.2492    \n",
       "6942   Topic15  6.696304      marshal               8.130549      7.1798    \n",
       "6943   Topic15  4.921833      miller                6.356077      7.1181    \n",
       "5493   Topic15  4.201887      medieval              5.636131      7.0802    \n",
       "5473   Topic15  3.679155      handler               5.113400      7.0447    \n",
       "5488   Topic15  3.076561      labyrinth             4.510808      6.9912    \n",
       "3930   Topic15  2.786003      bath                  4.220248      6.9586    \n",
       "6938   Topic15  2.321470      fuller                3.755716      6.8928    \n",
       "653    Topic15  1.561777      carman                2.996021      6.7224    \n",
       "5470   Topic15  1.366007      feral                 2.800254      6.6560    \n",
       "5242   Topic15  0.995392      indict                2.429637      6.4815    \n",
       "6945   Topic15  0.994901      pacifist              2.429151      6.4812    \n",
       "5251   Topic15  0.894016      tyrannical            2.328259      6.4167    \n",
       "4892   Topic15  0.739559      disembody             2.173805      6.2957    \n",
       "2225   Topic15  8.102152      bug                   34.978271     5.9112    \n",
       "33865  Topic15  0.018550      vilain                1.455347      3.0113    \n",
       "15473  Topic15  0.018528      weaver                1.453819      3.0112    \n",
       "32399  Topic15  0.018515      haven                 1.453723      3.0105    \n",
       "34328  Topic15  0.018501      hoodie                1.452818      3.0104    \n",
       "24402  Topic15  0.018501      audacious             1.452837      3.0104    \n",
       "10648  Topic15  0.018510      mining                1.453589      3.0103    \n",
       "11921  Topic15  0.018498      adoptive              1.452978      3.0101    \n",
       "20548  Topic15  0.018514      expendable            1.454293      3.0101    \n",
       "24247  Topic15  0.018502      steampunk             1.453352      3.0101    \n",
       "11649  Topic15  0.018493      ripper                1.452792      3.0100    \n",
       "7736   Topic15  0.018499      slasher               1.453288      3.0100    \n",
       "21071  Topic15  0.018495      multiple_personality  1.453011      3.0099    \n",
       "9638   Topic15  0.018493      prematurely           1.452974      3.0099    \n",
       "19725  Topic15  0.018491      macbeth               1.452931      3.0098    \n",
       "7846   Topic15  0.018501      harden                1.453753      3.0098    \n",
       "32481  Topic15  0.018500      thadeous              1.453760      3.0097    \n",
       "32476  Topic15  0.018498      fabious               1.453679      3.0097    \n",
       "10552  Topic15  0.018498      physician             1.453705      3.0096    \n",
       "32429  Topic15  0.018501      are                   1.454565      3.0092    \n",
       "\n",
       "       logprob  \n",
       "191    30.0000  \n",
       "76     29.0000  \n",
       "1202   28.0000  \n",
       "373    27.0000  \n",
       "304    26.0000  \n",
       "336    25.0000  \n",
       "455    24.0000  \n",
       "645    23.0000  \n",
       "225    22.0000  \n",
       "899    21.0000  \n",
       "579    20.0000  \n",
       "77     19.0000  \n",
       "351    18.0000  \n",
       "307    17.0000  \n",
       "302    16.0000  \n",
       "281    15.0000  \n",
       "2112   14.0000  \n",
       "697    13.0000  \n",
       "993    12.0000  \n",
       "130    11.0000  \n",
       "467    10.0000  \n",
       "140    9.0000   \n",
       "254    8.0000   \n",
       "24     7.0000   \n",
       "90     6.0000   \n",
       "80     5.0000   \n",
       "395    4.0000   \n",
       "2220   3.0000   \n",
       "131    2.0000   \n",
       "616    1.0000   \n",
       "697   -4.6325   \n",
       "590   -5.1156   \n",
       "602   -5.6596   \n",
       "2188  -5.7995   \n",
       "1021  -5.9008   \n",
       "1517  -5.9222   \n",
       "843   -5.9672   \n",
       "1366  -6.0237   \n",
       "842   -6.1258   \n",
       "2377  -6.1661   \n",
       "6980  -6.1937   \n",
       "1797  -6.3291   \n",
       "746   -6.3344   \n",
       "681   -6.3566   \n",
       "2553  -6.6436   \n",
       "1016  -6.6767   \n",
       "1841  -6.7180   \n",
       "2522  -6.7992   \n",
       "949   -6.9182   \n",
       "829   -6.9421   \n",
       "1391  -6.9491   \n",
       "1084  -6.8711   \n",
       "781   -7.0008   \n",
       "652   -7.0295   \n",
       "796   -7.1118   \n",
       "3263  -7.1280   \n",
       "257   -7.1629   \n",
       "793   -7.1805   \n",
       "2370  -7.2051   \n",
       "1340  -7.2060   \n",
       "302   -4.5323   \n",
       "357   -5.0252   \n",
       "345   -4.6596   \n",
       "616   -5.2724   \n",
       "102   -6.1326   \n",
       "1817  -6.4456   \n",
       "272   -5.8521   \n",
       "74    -5.4614   \n",
       "758   -6.2015   \n",
       "456   -5.3982   \n",
       "531   -5.6456   \n",
       "347   -4.9633   \n",
       "632   -5.0215   \n",
       "254   -4.7347   \n",
       "743   -5.2043   \n",
       "83    -4.7224   \n",
       "1269  -5.2672   \n",
       "1838  -5.7698   \n",
       "236   -4.9761   \n",
       "1204  -5.9732   \n",
       "216   -4.8797   \n",
       "566   -5.2953   \n",
       "612   -5.4056   \n",
       "280   -5.5590   \n",
       "495   -5.2733   \n",
       "33    -5.2794   \n",
       "80    -5.3143   \n",
       "39    -4.9042   \n",
       "121   -4.8882   \n",
       "366   -5.4611   \n",
       "18    -5.1263   \n",
       "538   -5.2822   \n",
       "214   -4.7965   \n",
       "86    -4.8828   \n",
       "87    -4.7678   \n",
       "554   -5.2548   \n",
       "282   -5.3387   \n",
       "792   -5.3052   \n",
       "645   -5.2875   \n",
       "212   -5.1013   \n",
       "77    -5.1212   \n",
       "116   -5.1977   \n",
       "24    -4.7071   \n",
       "1547  -5.6300   \n",
       "959   -5.7971   \n",
       "311   -5.9048   \n",
       "150   -6.1829   \n",
       "2624  -6.2560   \n",
       "3335  -6.5456   \n",
       "2765  -6.6538   \n",
       "290   -6.6609   \n",
       "3871  -6.8712   \n",
       "3030  -6.9068   \n",
       "2358  -6.9926   \n",
       "3727  -7.0480   \n",
       "1905  -7.1510   \n",
       "3621  -7.1518   \n",
       "1003  -7.2903   \n",
       "2257  -7.3289   \n",
       "3331  -7.3517   \n",
       "4847  -7.3749   \n",
       "4791  -7.4011   \n",
       "3169  -7.4044   \n",
       "6795  -7.4285   \n",
       "4546  -7.4341   \n",
       "2459  -7.4845   \n",
       "2564  -7.4882   \n",
       "1897  -7.4792   \n",
       "1020  -7.4912   \n",
       "4047  -7.5238   \n",
       "4049  -7.5240   \n",
       "6941  -7.5668   \n",
       "129   -4.9304   \n",
       "176   -5.2096   \n",
       "412   -5.3162   \n",
       "289   -5.4152   \n",
       "1628  -5.9190   \n",
       "99    -6.0369   \n",
       "401   -5.2738   \n",
       "1288  -5.6478   \n",
       "373   -4.7534   \n",
       "234   -6.5948   \n",
       "81    -6.6679   \n",
       "250   -5.6851   \n",
       "253   -7.1396   \n",
       "57    -6.2528   \n",
       "266   -6.5640   \n",
       "2198  -6.1930   \n",
       "1043  -5.8923   \n",
       "404   -6.6791   \n",
       "427   -6.0619   \n",
       "351   -4.4922   \n",
       "23    -5.0282   \n",
       "993   -5.8277   \n",
       "10    -5.0670   \n",
       "336   -4.4366   \n",
       "87    -4.2903   \n",
       "393   -5.0670   \n",
       "214   -4.4560   \n",
       "86    -4.5493   \n",
       "116   -4.5801   \n",
       "212   -4.4534   \n",
       "218   -4.8303   \n",
       "77    -4.4006   \n",
       "184   -4.8971   \n",
       "171   -5.1958   \n",
       "225   -5.1501   \n",
       "341   -5.1878   \n",
       "312   -5.1779   \n",
       "338   -5.4536   \n",
       "315   -5.6100   \n",
       "576   -5.5473   \n",
       "281   -5.4666   \n",
       "14    -5.5096   \n",
       "121   -5.3663   \n",
       "318   -5.4812   \n",
       "15    -5.5003   \n",
       "629   -5.1066   \n",
       "6707  -5.3599   \n",
       "1779  -5.4199   \n",
       "2080  -5.5614   \n",
       "4572  -5.7897   \n",
       "2971  -5.9538   \n",
       "5253  -6.2862   \n",
       "4252  -6.3619   \n",
       "6562  -6.4677   \n",
       "3242  -6.5182   \n",
       "2221  -6.5226   \n",
       "3189  -6.5241   \n",
       "4935  -6.5842   \n",
       "103   -6.6109   \n",
       "2654  -6.6317   \n",
       "313   -6.6352   \n",
       "7004  -6.6393   \n",
       "2738  -6.6987   \n",
       "525   -6.7118   \n",
       "6446  -6.7343   \n",
       "3849  -6.7362   \n",
       "5556  -6.7380   \n",
       "848   -6.8949   \n",
       "5063  -6.9057   \n",
       "6540  -6.9330   \n",
       "984   -6.9402   \n",
       "3417  -6.9929   \n",
       "5117  -7.0073   \n",
       "1243  -6.9361   \n",
       "7606  -7.0234   \n",
       "1613  -5.2375   \n",
       "476   -6.0613   \n",
       "1430  -6.4529   \n",
       "1869  -5.8769   \n",
       "737   -5.8870   \n",
       "5308  -6.3874   \n",
       "90    -4.5170   \n",
       "1086  -5.4998   \n",
       "467   -4.4825   \n",
       "1697  -4.8672   \n",
       "451   -5.1817   \n",
       "1650  -6.3861   \n",
       "2131  -5.5579   \n",
       "395   -4.8989   \n",
       "1832  -5.7212   \n",
       "474   -5.7413   \n",
       "444   -5.5232   \n",
       "1475  -5.9091   \n",
       "295   -4.8178   \n",
       "336   -4.1944   \n",
       "77    -4.0202   \n",
       "386   -5.5462   \n",
       "68    -5.7123   \n",
       "259   -5.3855   \n",
       "585   -5.7753   \n",
       "300   -5.0495   \n",
       "985   -5.6461   \n",
       "502   -4.9964   \n",
       "270   -5.4215   \n",
       "343   -5.1616   \n",
       "720   -4.9749   \n",
       "212   -4.7265   \n",
       "663   -5.2906   \n",
       "225   -5.1617   \n",
       "662   -5.5999   \n",
       "307   -5.3446   \n",
       "187   -5.4286   \n",
       "318   -5.2677   \n",
       "15    -5.3320   \n",
       "116   -5.2321   \n",
       "10    -5.3749   \n",
       "18    -5.3520   \n",
       "14    -5.4278   \n",
       "432   -5.4235   \n",
       "1131  -4.0027   \n",
       "726   -4.0192   \n",
       "2337  -4.3218   \n",
       "2460  -4.7085   \n",
       "1846  -5.2688   \n",
       "1491  -5.3705   \n",
       "5298  -5.3883   \n",
       "656   -5.4465   \n",
       "2892  -5.4832   \n",
       "4324  -5.4846   \n",
       "3846  -5.5817   \n",
       "4859  -5.5987   \n",
       "1365  -5.6502   \n",
       "6062  -5.6904   \n",
       "5143  -5.7845   \n",
       "5629  -5.7887   \n",
       "3224  -5.7982   \n",
       "1284  -5.8406   \n",
       "1392  -5.8747   \n",
       "5526  -6.1000   \n",
       "2724  -6.1595   \n",
       "3491  -6.2221   \n",
       "702   -6.2630   \n",
       "5608  -6.2857   \n",
       "6011  -6.3049   \n",
       "1539  -6.3252   \n",
       "1379  -6.3263   \n",
       "6183  -6.4363   \n",
       "2613  -6.4421   \n",
       "6081  -6.4687   \n",
       "2304  -4.3312   \n",
       "1039  -4.3228   \n",
       "1710  -6.0451   \n",
       "1495  -5.7160   \n",
       "3060  -5.3548   \n",
       "2661  -5.7117   \n",
       "1362  -5.8753   \n",
       "703   -4.6099   \n",
       "1411  -4.8759   \n",
       "4776  -4.7986   \n",
       "2222  -4.0501   \n",
       "2561  -4.8354   \n",
       "1450  -4.3016   \n",
       "1337  -5.0794   \n",
       "646   -4.4726   \n",
       "2677  -5.5961   \n",
       "1677  -5.3958   \n",
       "455   -4.2436   \n",
       "859   -5.2793   \n",
       "982   -5.2201   \n",
       "140   -4.2809   \n",
       "3427  -5.1526   \n",
       "307   -4.3642   \n",
       "1008  -4.7436   \n",
       "645   -4.3441   \n",
       "304   -4.6294   \n",
       "365   -4.8785   \n",
       "344   -5.0958   \n",
       "444   -5.0828   \n",
       "343   -4.8848   \n",
       "336   -4.7159   \n",
       "351   -4.7871   \n",
       "467   -5.1778   \n",
       "1118  -3.7878   \n",
       "1033  -3.9927   \n",
       "1115  -4.2952   \n",
       "1120  -4.3607   \n",
       "452   -4.5794   \n",
       "2023  -4.6204   \n",
       "2063  -4.8022   \n",
       "2059  -5.2009   \n",
       "5947  -5.2449   \n",
       "1121  -5.2465   \n",
       "5023  -5.2582   \n",
       "2743  -5.2623   \n",
       "5163  -5.2743   \n",
       "5919  -5.2787   \n",
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       "56    -4.5201   \n",
       "454   -4.0509   \n",
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       "76    -2.9368   \n",
       "1231  -4.3325   \n",
       "148   -3.9621   \n",
       "55    -4.6426   \n",
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       "28    -4.9166   \n",
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       "1489  -5.2015   \n",
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       "1605  -5.0065   \n",
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       "659   -3.0865   \n",
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       "3123  -5.3483   \n",
       "7659  -5.3579   \n",
       "4771  -5.5999   \n",
       "7003  -5.6225   \n",
       "4753  -5.7660   \n",
       "7666  -5.9839   \n",
       "5079  -5.9847   \n",
       "5066  -6.0221   \n",
       "1991  -6.0871   \n",
       "1752  -6.1933   \n",
       "5091  -6.2450   \n",
       "3422  -6.2837   \n",
       "1554  -6.2988   \n",
       "4991  -6.6224   \n",
       "7421  -6.6941   \n",
       "5086  -6.9221   \n",
       "3501  -6.9695   \n",
       "6638  -7.0244   \n",
       "2430  -2.7343   \n",
       "2650  -4.2527   \n",
       "1458  -2.8281   \n",
       "2052  -7.2543   \n",
       "3510  -7.4148   \n",
       "5080  -5.0469   \n",
       "2010  -7.7313   \n",
       "5067  -6.5433   \n",
       "2467  -4.8217   \n",
       "2013  -8.0142   \n",
       "2694  -3.6844   \n",
       "2668  -3.7684   \n",
       "3001  -4.5964   \n",
       "5060  -5.8964   \n",
       "2079  -5.8409   \n",
       "3025  -6.3970   \n",
       "1072  -5.7040   \n",
       "6000  -6.3727   \n",
       "913   -6.5025   \n",
       "2562  -3.7237   \n",
       "4617  -3.7290   \n",
       "4086  -4.5121   \n",
       "1938  -4.5524   \n",
       "6894  -4.5797   \n",
       "6234  -5.1794   \n",
       "4569  -5.2446   \n",
       "4228  -5.3530   \n",
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       "4392  -5.8949   \n",
       "6141  -5.9300   \n",
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       "6130  -5.9819   \n",
       "7507  -6.0567   \n",
       "6131  -6.1632   \n",
       "6125  -6.3106   \n",
       "4630  -6.3947   \n",
       "2073  -6.4063   \n",
       "4237  -6.4077   \n",
       "6921  -6.6451   \n",
       "6135  -6.6869   \n",
       "7338  -6.7624   \n",
       "5654  -7.3776   \n",
       "5795  -7.8398   \n",
       "6137  -7.9210   \n",
       "4623  -8.0258   \n",
       "4614  -8.3295   \n",
       "4642  -8.7163   \n",
       "3402  -3.6161   \n",
       "3384  -3.7396   \n",
       "4472  -3.7441   \n",
       "2556  -4.0490   \n",
       "2902  -4.4435   \n",
       "7539  -4.9613   \n",
       "7344  -5.2411   \n",
       "6770  -5.4086   \n",
       "6994  -6.0065   \n",
       "3351  -6.0441   \n",
       "2911  -6.1749   \n",
       "4474  -6.2352   \n",
       "2411  -6.3352   \n",
       "4274  -6.7781   \n",
       "1027  -6.8482   \n",
       "5282  -7.0963   \n",
       "7685  -7.1340   \n",
       "1029  -7.4341   \n",
       "2918  -8.3736   \n",
       "25566 -10.5941  \n",
       "27423 -10.5941  \n",
       "20573 -10.5949  \n",
       "32657 -10.5953  \n",
       "34588 -10.5953  \n",
       "18441 -10.5953  \n",
       "9809  -10.5953  \n",
       "17616 -10.5950  \n",
       "18775 -10.5960  \n",
       "31573 -10.5962  \n",
       "22531 -10.5959  \n",
       "15134 -10.5959  \n",
       "31825 -10.5957  \n",
       "2535  -4.1186   \n",
       "3932  -4.1767   \n",
       "6942  -4.6552   \n",
       "6943  -4.9630   \n",
       "5493  -5.1212   \n",
       "5473  -5.2540   \n",
       "5488  -5.4329   \n",
       "3930  -5.5321   \n",
       "6938  -5.7145   \n",
       "653   -6.1109   \n",
       "5470  -6.2448   \n",
       "5242  -6.5613   \n",
       "6945  -6.5618   \n",
       "5251  -6.6688   \n",
       "4892  -6.8584   \n",
       "2225  -4.4646   \n",
       "33865 -10.5440  \n",
       "15473 -10.5452  \n",
       "32399 -10.5459  \n",
       "34328 -10.5466  \n",
       "24402 -10.5466  \n",
       "10648 -10.5462  \n",
       "11921 -10.5468  \n",
       "20548 -10.5459  \n",
       "24247 -10.5466  \n",
       "11649 -10.5471  \n",
       "7736  -10.5468  \n",
       "21071 -10.5470  \n",
       "9638  -10.5471  \n",
       "19725 -10.5472  \n",
       "7846  -10.5466  \n",
       "32481 -10.5467  \n",
       "32476 -10.5468  \n",
       "10552 -10.5468  \n",
       "32429 -10.5467  , token_table=      Topic      Freq                  Term\n",
       "term                                       \n",
       "3207  11     0.956687  abortion            \n",
       "5608  4      0.986644  abroad              \n",
       "5447  7      0.972019  abruptly            \n",
       "744   8      0.914611  academy             \n",
       "5059  7      0.985892  activist            \n",
       "2515  1      0.214151  actor               \n",
       "2515  8      0.779144  actor               \n",
       "3571  1      0.316781  actress             \n",
       "3571  8      0.671960  actress             \n",
       "2346  8      0.951688  addiction           \n",
       "3025  4      0.189983  aerial              \n",
       "3025  5      0.633276  aerial              \n",
       "3025  12     0.158319  aerial              \n",
       "796   1      0.997102  affair              \n",
       "3209  11     0.962842  affluent            \n",
       "746   1      0.998294  age                 \n",
       "1710  4      0.975851  agency              \n",
       "1710  7      0.018949  agency              \n",
       "2222  2      0.269910  agent               \n",
       "2222  4      0.723589  agent               \n",
       "2222  7      0.006700  agent               \n",
       "5060  5      0.895839  aircraft            \n",
       "5060  12     0.092673  aircraft            \n",
       "2650  2      0.322077  airplane            \n",
       "2650  12     0.658794  airplane            \n",
       "2079  1      0.133019  airport             \n",
       "2079  2      0.803896  airport             \n",
       "2079  12     0.052051  airport             \n",
       "1033  5      0.997403  alien               \n",
       "1284  4      0.989033  alliance            \n",
       "5298  4      0.992437  ally                \n",
       "4753  12     0.889123  alpha               \n",
       "1841  1      0.996935  always              \n",
       "6997  10     0.964566  amateur             \n",
       "4274  14     0.366476  amazed              \n",
       "2561  1      0.195655  american            \n",
       "2561  4      0.803584  american            \n",
       "1034  6      0.988663  ancient             \n",
       "2562  13     0.957238  angel               \n",
       "747   9      0.923992  angela              \n",
       "2080  3      0.998023  animal              \n",
       "6911  10     0.957842  annie               \n",
       "250   1      0.113741  apartment           \n",
       "250   2      0.885234  apartment           \n",
       "1938  13     0.884048  ape                 \n",
       "1288  2      0.923877  arrest              \n",
       "1288  7      0.075234  arrest              \n",
       "10    1      0.066762  arrive              \n",
       "10    2      0.675007  arrive              \n",
       "10    3      0.257819  arrive              \n",
       "2892  4      0.991387  assassin            \n",
       "2724  4      0.989639  assassinate         \n",
       "1362  4      0.943063  assassination       \n",
       "1362  7      0.046380  assassination       \n",
       "2564  2      0.993946  associate           \n",
       "6851  10     0.920508  athletic            \n",
       "467   2      0.138777  attack              \n",
       "467   3      0.769103  attack              \n",
       "467   4      0.092142  attack              \n",
       "14    1      0.173819  attempt             \n",
       "14    2      0.512729  attempt             \n",
       "14    3      0.288728  attempt             \n",
       "14    4      0.006545  attempt             \n",
       "14    5      0.017818  attempt             \n",
       "2349  1      0.403336  audience            \n",
       "2349  2      0.057619  audience            \n",
       "2349  3      0.009098  audience            \n",
       "2349  8      0.482183  audience            \n",
       "2349  9      0.045489  audience            \n",
       "2350  8      0.983512  audition            \n",
       "468   10     0.955173  australian          \n",
       "7539  14     0.846536  awful               \n",
       "15    1      0.411641  back                \n",
       "15    2      0.364282  back                \n",
       "15    3      0.223740  back                \n",
       "253   2      0.978508  bag                 \n",
       "253   3      0.017727  bag                 \n",
       "2518  9      0.963191  ballet              \n",
       "2354  8      0.994968  band                \n",
       "3727  2      0.996742  bank                \n",
       "645   1      0.626532  base                \n",
       "645   3      0.096690  base                \n",
       "645   4      0.157332  base                \n",
       "645   5      0.021238  base                \n",
       "645   6      0.068466  base                \n",
       "645   7      0.029342  base                \n",
       "4018  9      0.978356  baseball            \n",
       "2565  9      0.987251  basketball          \n",
       "3930  15     0.710859  bath                \n",
       "646   3      0.148869  battle              \n",
       "646   4      0.566847  battle              \n",
       "646   6      0.274835  battle              \n",
       "646   9      0.009161  battle              \n",
       "1628  1      0.002030  beat                \n",
       "1628  2      0.949924  beat                \n",
       "1628  9      0.046684  beat                \n",
       "254   1      0.873273  become              \n",
       "254   2      0.025994  become              \n",
       "254   3      0.081568  become              \n",
       "254   6      0.019048  become              \n",
       "18    1      0.632099  begin               \n",
       "18    2      0.161984  begin               \n",
       "18    3      0.205660  begin               \n",
       "257   1      0.997037  best_friend         \n",
       "7143  10     0.918539  biker               \n",
       "2519  9      0.992275  billy               \n",
       "5643  3      0.313366  biological          \n",
       "5643  5      0.248081  biological          \n",
       "5643  11     0.417821  biological          \n",
       "2654  3      0.993120  bird                \n",
       "474   2      0.223886  blood               \n",
       "474   3      0.774274  blood               \n",
       "474   6      0.001333  blood               \n",
       "913   1      0.201644  board               \n",
       "913   2      0.442957  board               \n",
       "913   3      0.165282  board               \n",
       "913   4      0.052890  board               \n",
       "913   5      0.119003  board               \n",
       "913   12     0.016528  board               \n",
       "476   2      0.036498  boat                \n",
       "476   3      0.962645  boat                \n",
       "259   2      0.475205  body                \n",
       "259   3      0.524560  body                \n",
       "1039  2      0.005073  bomb                \n",
       "1039  4      0.972306  bomb                \n",
       "1039  5      0.021983  bomb                \n",
       "1379  4      0.988756  bombing             \n",
       "2430  1      0.336351  bond                \n",
       "2430  12     0.659766  bond                \n",
       "2432  9      0.978667  boxer               \n",
       "2433  9      0.949331  boxing              \n",
       "6812  1      0.243104  brain               \n",
       "6812  5      0.745886  brain               \n",
       "5992  10     0.944651  brandon             \n",
       "1846  4      0.992561  british             \n",
       "751   8      0.973342  broker              \n",
       "479   7      0.960095  bruce               \n",
       "2225  2      0.743319  bug                 \n",
       "2225  15     0.228713  bug                 \n",
       "266   1      0.076897  bus                 \n",
       "266   2      0.920884  bus                 \n",
       "5117  3      0.993935  cabin               \n",
       "5063  3      0.991689  cage                \n",
       "23    1      0.256845  call                \n",
       "23    2      0.686322  call                \n",
       "23    3      0.051429  call                \n",
       "23    5      0.005414  call                \n",
       "6029  7      0.946495  capacity            \n",
       "444   3      0.707445  capture             \n",
       "444   4      0.263577  capture             \n",
       "444   5      0.015677  capture             \n",
       "444   6      0.011758  capture             \n",
       "24    2      0.999485  car                 \n",
       "652   1      0.997279  care                \n",
       "653   15     0.667552  carman              \n",
       "3029  7      0.984074  cartel              \n",
       "1041  2      0.310814  case                \n",
       "1041  7      0.687063  case                \n",
       "2358  2      0.996232  cash                \n",
       "4935  3      0.995110  cat                 \n",
       "6626  8      0.946840  catherine           \n",
       "270   1      0.177667  cause               \n",
       "270   2      0.271209  cause               \n",
       "270   3      0.501611  cause               \n",
       "270   5      0.048341  cause               \n",
       "1042  6      0.986020  century             \n",
       "28    1      0.690331  challenge           \n",
       "28    3      0.057027  challenge           \n",
       "28    6      0.027013  challenge           \n",
       "28    9      0.222107  challenge           \n",
       "7460  9      0.982358  champion            \n",
       "2435  9      0.993020  championship        \n",
       "272   1      0.975166  change              \n",
       "272   2      0.023710  change              \n",
       "7658  2      0.343860  chapter             \n",
       "7658  10     0.601755  chapter             \n",
       "1043  2      0.831703  chase               \n",
       "1043  3      0.167033  chase               \n",
       "3030  2      0.997446  check               \n",
       "6125  13     0.568518  cheque              \n",
       "33    1      0.801405  child               \n",
       "33    2      0.003546  child               \n",
       "33    3      0.194323  child               \n",
       "5066  12     0.886953  chimp               \n",
       "5067  3      0.424916  chimpanzee          \n",
       "5067  12     0.531145  chimpanzee          \n",
       "656   4      0.993114  chinese             \n",
       "6962  8      0.913302  choir               \n",
       "4617  13     0.962084  circus              \n",
       "2522  1      0.996374  class               \n",
       "4428  2      0.932466  classmate           \n",
       "4428  11     0.063868  classmate           \n",
       "1046  5      0.985025  clone               \n",
       "2438  1      0.081040  coach               \n",
       "2438  9      0.911704  coach               \n",
       "3331  2      0.992496  cocaine             \n",
       "1391  1      0.997768  college             \n",
       "2231  7      0.954303  collin              \n",
       "1539  4      0.987738  colonel             \n",
       "1392  4      0.990520  combat              \n",
       "39    1      0.638320  come                \n",
       "39    2      0.261616  come                \n",
       "39    3      0.099756  come                \n",
       "4789  6      0.996221  comic               \n",
       "6748  11     0.957023  commission          \n",
       "3032  1      0.141576  commit              \n",
       "3032  2      0.342417  commit              \n",
       "3032  7      0.513626  commit              \n",
       "3391  5      0.987959  communication       \n",
       "657   1      0.205753  compete             \n",
       "657   9      0.784911  compete             \n",
       "5328  1      0.392713  competition         \n",
       "5328  9      0.602160  competition         \n",
       "4544  11     0.937194  compose             \n",
       "1951  2      0.372389  computer            \n",
       "1951  5      0.598264  computer            \n",
       "1951  7      0.027471  computer            \n",
       "4847  2      0.992876  con                 \n",
       "1503  8      0.993117  concert             \n",
       "6126  13     0.818710  conscious           \n",
       "6686  7      0.991996  conspiracy          \n",
       "489   1      0.279876  control             \n",
       "489   2      0.230340  control             \n",
       "489   3      0.226625  control             \n",
       "489   5      0.255108  control             \n",
       "489   6      0.006192  control             \n",
       "4546  2      0.995109  cook                \n",
       "3335  2      0.996917  cop                 \n",
       "1954  5      0.989653  core                \n",
       "1395  7      0.980277  corporate           \n",
       "3657  2      0.494782  corrupt             \n",
       "3657  7      0.503412  corrupt             \n",
       "3658  7      0.992929  corruption          \n",
       "7659  12     0.925077  countdown           \n",
       "2579  1      0.564113  court               \n",
       "2579  7      0.431751  court               \n",
       "4025  7      0.940638  courtroom           \n",
       "276   1      0.011329  crash               \n",
       "276   2      0.594753  crash               \n",
       "276   3      0.141608  crash               \n",
       "276   5      0.246964  crash               \n",
       "276   12     0.004531  crash               \n",
       "48    1      0.487804  create              \n",
       "48    2      0.068621  create              \n",
       "48    3      0.119340  create              \n",
       "48    5      0.277466  create              \n",
       "48    6      0.044753  create              \n",
       "48    7      0.001492  create              \n",
       "2971  3      0.998302  creature            \n",
       "1304  2      0.232039  crew                \n",
       "1304  5      0.710266  crew                \n",
       "1304  8      0.056595  crew                \n",
       "1641  2      0.393250  crime               \n",
       "1641  7      0.605783  crime               \n",
       "277   2      0.782490  criminal            \n",
       "277   7      0.215741  criminal            \n",
       "5015  5      0.985385  crystal             \n",
       "2091  6      0.990664  cure                \n",
       "1305  1      0.087611  curse               \n",
       "1305  2      0.038092  curse               \n",
       "1305  3      0.083802  curse               \n",
       "1305  6      0.784691  curse               \n",
       "4791  2      0.995664  custody             \n",
       "279   1      0.092627  damage              \n",
       "279   2      0.303435  damage              \n",
       "279   3      0.070269  damage              \n",
       "279   4      0.038329  damage              \n",
       "279   5      0.495078  damage              \n",
       "659   1      0.703359  dance               \n",
       "659   11     0.295858  dance               \n",
       "2526  11     0.991466  dancer              \n",
       "756   11     0.945397  dancing             \n",
       "4125  1      0.084803  dark                \n",
       "4125  2      0.163401  dark                \n",
       "4125  3      0.419878  dark                \n",
       "4125  6      0.330938  dark                \n",
       "1797  1      0.998012  date                \n",
       "280   1      0.879011  daughter            \n",
       "280   2      0.084352  daughter            \n",
       "280   3      0.036004  daughter            \n",
       "6348  8      0.983441  dave                \n",
       "495   1      0.802906  day                 \n",
       "495   2      0.150766  day                 \n",
       "495   3      0.045901  day                 \n",
       "6033  7      0.958907  dean                \n",
       "281   1      0.172900  death               \n",
       "281   2      0.500017  death               \n",
       "281   3      0.253745  death               \n",
       "281   4      0.006114  death               \n",
       "281   6      0.007133  death               \n",
       "281   7      0.060124  death               \n",
       "282   1      0.692708  decide              \n",
       "282   2      0.216593  decide              \n",
       "282   3      0.090085  decide              \n",
       "1058  3      0.256023  defeat              \n",
       "1058  4      0.156597  defeat              \n",
       "1058  5      0.007457  defeat              \n",
       "1058  6      0.405163  defeat              \n",
       "1058  9      0.171511  defeat              \n",
       "4126  6      0.993378  demon               \n",
       "2585  8      0.954710  derek               \n",
       "662   2      0.023849  destroy             \n",
       "662   3      0.569813  destroy             \n",
       "662   4      0.100505  destroy             \n",
       "662   5      0.281925  destroy             \n",
       "662   6      0.023849  destroy             \n",
       "2234  2      0.419817  detective           \n",
       "2234  7      0.577248  detective           \n",
       "2661  4      0.928394  detonate            \n",
       "2661  5      0.058430  detonate            \n",
       "1959  4      0.051746  device              \n",
       "1959  5      0.941781  device              \n",
       "1644  10     0.979130  dialogue            \n",
       "3871  2      0.995825  diamond             \n",
       "5654  13     0.466351  dick                \n",
       "663   1      0.305459  die                 \n",
       "663   2      0.306309  die                 \n",
       "663   3      0.387566  die                 \n",
       "5266  7      0.949875  dilemma             \n",
       "55    1      0.156256  direct              \n",
       "55    2      0.127845  direct              \n",
       "55    3      0.163358  direct              \n",
       "55    4      0.159807  direct              \n",
       "55    8      0.387088  direct              \n",
       "56    1      0.296084  director            \n",
       "56    5      0.107667  director            \n",
       "56    7      0.035889  director            \n",
       "56    8      0.556279  director            \n",
       "4823  10     0.947413  disabled            \n",
       "502   1      0.216914  discover            \n",
       "502   2      0.371852  discover            \n",
       "502   3      0.378979  discover            \n",
       "502   5      0.027269  discover            \n",
       "502   6      0.001240  discover            \n",
       "502   7      0.003409  discover            \n",
       "4892  15     0.460023  disembody           \n",
       "2370  1      0.997530  divorce             \n",
       "1832  1      0.137568  dog                 \n",
       "1832  2      0.083851  dog                 \n",
       "1832  3      0.775620  dog                 \n",
       "57    1      0.017530  door                \n",
       "57    2      0.903451  door                \n",
       "57    3      0.076861  door                \n",
       "3394  10     0.910417  dottie              \n",
       "1897  2      0.995136  double              \n",
       "4315  6      0.991817  dragon              \n",
       "758   1      0.979356  dream               \n",
       "758   6      0.006536  dream               \n",
       "758   8      0.013073  dream               \n",
       "289   1      0.050786  drive               \n",
       "289   2      0.936520  drive               \n",
       "289   3      0.011487  drive               \n",
       "290   2      0.997593  driver              \n",
       "1547  2      0.999110  drug                \n",
       "5268  5      0.980284  dystopia            \n",
       "4220  9      0.938812  eagle               \n",
       "1066  5      0.934358  earth               \n",
       "1066  6      0.062394  earth               \n",
       "3224  4      0.993569  economic            \n",
       "4129  9      0.881585  elve                \n",
       "6130  13     0.692388  empowerment         \n",
       "4392  13     0.652567  endeavor            \n",
       "1411  4      0.834255  enemy               \n",
       "1411  6      0.163826  enemy               \n",
       "4462  5      0.987008  engine              \n",
       "2096  1      0.077150  engineer            \n",
       "2096  3      0.188052  engineer            \n",
       "2096  5      0.728100  engineer            \n",
       "4556  6      0.973863  entity              \n",
       "6540  3      0.990786  epic                \n",
       "295   2      0.412352  escape              \n",
       "295   3      0.533032  escape              \n",
       "295   4      0.043751  escape              \n",
       "295   5      0.010573  escape              \n",
       "4085  7      0.974191  espionage           \n",
       "7358  7      0.956131  ethic               \n",
       "5797  7      0.964814  eve                 \n",
       "3227  11     0.941740  everyone            \n",
       "297   2      0.365285  evidence            \n",
       "297   3      0.056995  evidence            \n",
       "297   7      0.575130  evidence            \n",
       "448   6      0.997921  evil                \n",
       "4086  13     0.923739  expand              \n",
       "3932  15     0.898707  expensive           \n",
       "5308  1      0.037808  experiment          \n",
       "5308  3      0.957797  experiment          \n",
       "5863  7      0.965261  expire              \n",
       "7344  14     0.800936  extent              \n",
       "68    1      0.186941  eye                 \n",
       "68    2      0.166410  eye                 \n",
       "68    3      0.646188  eye                 \n",
       "2765  2      0.997263  fake                \n",
       "300   1      0.537788  fall                \n",
       "300   2      0.038335  fall                \n",
       "300   3      0.423513  fall                \n",
       "3702  2      0.183099  fame                \n",
       "3702  8      0.775992  fame                \n",
       "3702  9      0.034876  fame                \n",
       "302   1      0.992120  family              \n",
       "302   2      0.002911  family              \n",
       "302   3      0.004575  family              \n",
       "1650  1      0.061468  farm                \n",
       "1650  3      0.937395  farm                \n",
       "74    1      0.964078  father              \n",
       "74    2      0.035309  father              \n",
       "75    1      0.597173  feature             \n",
       "75    3      0.051647  feature             \n",
       "75    8      0.345392  feature             \n",
       "2377  1      0.998256  feel                \n",
       "949   1      0.997021  feeling             \n",
       "5470  15     0.357110  feral               \n",
       "7312  10     0.936363  feud                \n",
       "522   1      0.230076  field               \n",
       "522   3      0.365246  field               \n",
       "522   4      0.224324  field               \n",
       "522   9      0.178309  field               \n",
       "304   1      0.148909  fight               \n",
       "304   2      0.325539  fight               \n",
       "304   3      0.240600  fight               \n",
       "304   4      0.150331  fight               \n",
       "304   6      0.054020  fight               \n",
       "304   9      0.079963  fight               \n",
       "76    1      0.603276  film                \n",
       "76    2      0.145290  film                \n",
       "76    3      0.018304  film                \n",
       "76    4      0.003051  film                \n",
       "76    8      0.229565  film                \n",
       "951   1      0.464386  final               \n",
       "951   2      0.173078  final               \n",
       "951   3      0.093852  final               \n",
       "951   4      0.073132  final               \n",
       "951   6      0.023158  final               \n",
       "951   9      0.170640  final               \n",
       "77    1      0.260423  find                \n",
       "77    2      0.420237  find                \n",
       "77    3      0.319235  find                \n",
       "6325  13     0.691777  fiona               \n",
       "7003  12     0.861483  firefighter         \n",
       "1802  1      0.239394  firm                \n",
       "1802  7      0.755422  firm                \n",
       "80    1      0.804536  first               \n",
       "80    2      0.050859  first               \n",
       "80    3      0.123094  first               \n",
       "80    5      0.005528  first               \n",
       "80    9      0.015847  first               \n",
       "525   3      0.994121  fish                \n",
       "3091  10     0.951748  fisherman           \n",
       "2668  1      0.177091  flight              \n",
       "2668  2      0.325353  flight              \n",
       "2668  5      0.193564  flight              \n",
       "2668  12     0.300642  flight              \n",
       "81    2      0.953145  floor               \n",
       "81    3      0.045183  floor               \n",
       "1072  1      0.223879  fly                 \n",
       "1072  3      0.566998  fly                 \n",
       "1072  5      0.194677  fly                 \n",
       "1072  6      0.001217  fly                 \n",
       "1072  12     0.012167  fly                 \n",
       "307   1      0.136690  force               \n",
       "307   2      0.339247  force               \n",
       "307   3      0.305606  force               \n",
       "307   4      0.195474  force               \n",
       "307   5      0.001416  force               \n",
       "307   6      0.021601  force               \n",
       "4252  3      0.995308  forest              \n",
       "6795  2      0.994319  foster              \n",
       "6894  13     0.905902  fountain            \n",
       "3229  11     0.973871  france              \n",
       "2459  2      0.995360  frankie             \n",
       "83    1      0.853947  friend              \n",
       "83    2      0.145680  friend              \n",
       "681   1      0.998620  friendship          \n",
       "6011  4      0.980548  frost               \n",
       "6938  15     0.532522  fuller              \n",
       "3781  8      0.926834  fusion              \n",
       "1860  1      0.174427  game                \n",
       "1860  2      0.132197  game                \n",
       "1860  9      0.690362  game                \n",
       "311   2      0.999140  gang                \n",
       "1905  2      0.995036  gangster            \n",
       "4431  11     0.989073  gay                 \n",
       "2851  5      0.986975  genetic             \n",
       "2460  4      0.996361  german              \n",
       "86    1      0.476511  get                 \n",
       "86    2      0.522163  get                 \n",
       "86    3      0.001276  get                 \n",
       "4223  6      0.996609  ghost               \n",
       "1269  1      0.894034  girl                \n",
       "1269  2      0.105502  girl                \n",
       "312   1      0.447233  give                \n",
       "312   2      0.465977  give                \n",
       "312   3      0.086362  give                \n",
       "312   6      0.000237  give                \n",
       "6131  13     0.519420  glamorous           \n",
       "5023  5      0.993921  global              \n",
       "87    1      0.429948  go                  \n",
       "87    2      0.544106  go                  \n",
       "87    3      0.025774  go                  \n",
       "4285  6      0.993357  god                 \n",
       "6638  12     0.715993  goggle              \n",
       "313   3      0.996635  gold                \n",
       "531   1      0.958418  good                \n",
       "531   2      0.040367  good                \n",
       "2304  4      0.975343  government          \n",
       "2304  5      0.008556  government          \n",
       "2304  7      0.013689  government          \n",
       "3402  14     0.961679  grace               \n",
       "7004  3      0.996480  grave               \n",
       "4622  11     0.925830  greek               \n",
       "90    1      0.031570  group               \n",
       "90    2      0.098862  group               \n",
       "90    3      0.820392  group               \n",
       "90    4      0.034477  group               \n",
       "90    8      0.014539  group               \n",
       "2381  8      0.959472  guitar              \n",
       "959   2      0.998376  gun                 \n",
       "5866  7      0.970832  gus                 \n",
       "3491  4      0.983908  hack                \n",
       "1991  12     0.819675  hal                 \n",
       "5473  15     0.782258  handler             \n",
       "4569  13     0.799538  happening           \n",
       "829   1      0.997820  happy               \n",
       "5682  8      0.895412  harmony             \n",
       "4498  1      0.071756  haunt               \n",
       "4498  2      0.121434  haunt               \n",
       "4498  6      0.800358  haunt               \n",
       "315   1      0.021947  head                \n",
       "315   2      0.635970  head                \n",
       "315   3      0.341678  head                \n",
       "3621  2      0.995904  heist               \n",
       "318   1      0.424592  help                \n",
       "318   2      0.350004  help                \n",
       "318   3      0.224968  help                \n",
       "3169  2      0.994210  henchman            \n",
       "6562  3      0.996084  hercule             \n",
       "3405  2      0.147993  hero                \n",
       "3405  3      0.045220  hero                \n",
       "3405  4      0.236378  hero                \n",
       "3405  5      0.117161  hero                \n",
       "3405  6      0.452200  hero                \n",
       "1554  12     0.836182  hick                \n",
       "5656  11     0.964411  historical          \n",
       "1430  3      0.975152  hole                \n",
       "1430  5      0.020530  hole                \n",
       "538   1      0.684371  home                \n",
       "538   2      0.274781  home                \n",
       "538   3      0.040686  home                \n",
       "4572  3      0.997286  horse               \n",
       "99    1      0.047990  hotel               \n",
       "99    2      0.950656  hotel               \n",
       "1079  3      0.567743  human               \n",
       "1079  5      0.378173  human               \n",
       "1079  6      0.053196  human               \n",
       "1080  5      0.879778  humanity            \n",
       "1080  6      0.111836  humanity            \n",
       "102   1      0.981750  husband             \n",
       "102   2      0.017331  husband             \n",
       "103   3      0.993217  ice                 \n",
       "2902  14     0.872847  ideal               \n",
       "7685  14     0.427722  idiot               \n",
       "3786  7      0.939793  impending           \n",
       "3457  7      0.944594  implicate           \n",
       "2177  7      0.989435  incredible          \n",
       "2738  3      0.994676  indian              \n",
       "5242  15     0.411584  indict              \n",
       "6490  12     0.895450  indigenous          \n",
       "2467  3      0.504523  infect              \n",
       "2467  12     0.467151  infect              \n",
       "5079  12     0.859201  infected            \n",
       "5080  3      0.389389  infection           \n",
       "5080  12     0.556270  infection           \n",
       "4626  11     0.967676  inspiration         \n",
       "6326  10     0.963132  interesting         \n",
       "4859  4      0.994419  international       \n",
       "2677  3      0.114917  invasion            \n",
       "2677  4      0.881029  invasion            \n",
       "3789  5      0.985705  inventor            \n",
       "331   2      0.396851  investigate         \n",
       "331   3      0.221993  investigate         \n",
       "331   5      0.033451  investigate         \n",
       "331   7      0.346674  investigate         \n",
       "2246  7      0.995273  investigation       \n",
       "5556  3      0.992548  isolate             \n",
       "3236  11     0.969395  jake                \n",
       "4324  4      0.992797  japanese            \n",
       "4034  1      0.359205  judge               \n",
       "4034  7      0.633892  judge               \n",
       "6941  2      0.992033  justice             \n",
       "336   2      0.569417  kill                \n",
       "336   3      0.376710  kill                \n",
       "336   4      0.053599  kill                \n",
       "3348  2      0.667554  killer              \n",
       "3348  7      0.331063  killer              \n",
       "2904  6      0.990265  king                \n",
       "6056  6      0.980057  kingdom             \n",
       "1084  1      0.996438  kiss                \n",
       "3305  6      0.976811  knight              \n",
       "338   1      0.429381  know                \n",
       "338   2      0.522618  know                \n",
       "338   3      0.035402  know                \n",
       "338   4      0.004907  know                \n",
       "338   5      0.005608  know                \n",
       "338   6      0.002103  know                \n",
       "5919  5      0.994374  kyle                \n",
       "2860  5      0.987687  laboratory          \n",
       "5488  15     0.665069  labyrinth           \n",
       "1442  10     0.938908  lance               \n",
       "1086  1      0.106190  land                \n",
       "1086  3      0.862356  land                \n",
       "1086  4      0.007002  land                \n",
       "1086  5      0.022172  land                \n",
       "3498  5      0.982902  laser               \n",
       "6921  13     0.342162  latch               \n",
       "341   1      0.402686  later               \n",
       "341   2      0.482578  later               \n",
       "341   3      0.114628  later               \n",
       "2679  3      0.204253  launch              \n",
       "2679  4      0.164291  launch              \n",
       "2679  5      0.626081  launch              \n",
       "4228  13     0.726752  lava                \n",
       "968   1      0.289387  lawyer              \n",
       "968   7      0.707708  lawyer              \n",
       "343   1      0.255238  lead                \n",
       "343   2      0.243520  lead                \n",
       "343   3      0.379745  lead                \n",
       "343   4      0.120112  lead                \n",
       "343   6      0.001465  lead                \n",
       "344   2      0.186097  leader              \n",
       "344   3      0.388703  leader              \n",
       "344   4      0.399208  leader              \n",
       "344   6      0.024013  leader              \n",
       "116   1      0.350875  leave               \n",
       "116   2      0.510792  leave               \n",
       "116   3      0.138176  leave               \n",
       "6828  13     0.707499  lenny               \n",
       "7313  10     0.986831  lgbt                \n",
       "345   1      0.973555  life                \n",
       "345   2      0.006257  life                \n",
       "345   3      0.017381  life                \n",
       "345   5      0.002549  life                \n",
       "2184  8      0.985758  lily                \n",
       "6797  5      0.985019  liquid              \n",
       "347   1      0.928067  live                \n",
       "347   2      0.017358  live                \n",
       "347   3      0.054469  live                \n",
       "697   1      0.999765  love                \n",
       "4799  2      0.535152  lucky               \n",
       "4799  11     0.451207  lucky               \n",
       "6695  7      0.969044  lycan               \n",
       "971   2      0.121172  machine             \n",
       "971   4      0.033047  machine             \n",
       "971   5      0.842696  machine             \n",
       "4144  6      0.996782  magic               \n",
       "3501  12     0.689997  mainframe           \n",
       "121   1      0.595726  make                \n",
       "121   2      0.289933  make                \n",
       "121   3      0.114049  make                \n",
       "121   5      0.000178  make                \n",
       "351   1      0.237313  man                 \n",
       "351   2      0.630301  man                 \n",
       "351   3      0.073716  man                 \n",
       "351   4      0.058520  man                 \n",
       "6646  7      0.945492  manhunt             \n",
       "2010  12     0.360951  manually            \n",
       "842   1      0.999000  marriage            \n",
       "843   1      0.998654  marry               \n",
       "6942  15     0.860950  marshal             \n",
       "3793  8      0.982782  marty               \n",
       "2112  1      0.181423  match               \n",
       "2112  3      0.014418  match               \n",
       "2112  9      0.803788  match               \n",
       "3351  14     0.724270  maverick            \n",
       "702   4      0.988643  medal               \n",
       "5493  15     0.709707  medieval            \n",
       "554   1      0.640676  meet                \n",
       "554   2      0.326283  meet                \n",
       "554   3      0.032905  meet                \n",
       "6062  4      0.994444  mercenary           \n",
       "703   4      0.815927  military            \n",
       "703   5      0.183206  military            \n",
       "6943  15     0.786649  miller              \n",
       "848   3      0.991981  mine                \n",
       "2535  15     0.853672  miner               \n",
       "4582  7      0.981279  minister            \n",
       "6770  14     0.762731  miraculous          \n",
       "3795  8      0.956533  misfit              \n",
       "1450  4      0.726351  mission             \n",
       "1450  5      0.272999  mission             \n",
       "1512  6      0.990334  modern              \n",
       "2013  12     0.411499  module              \n",
       "6398  10     0.990738  molly               \n",
       "129   1      0.012556  money               \n",
       "129   2      0.987209  money               \n",
       "1869  3      0.946870  monster             \n",
       "1869  6      0.050425  monster             \n",
       "4630  13     0.597190  mortality           \n",
       "357   1      0.988297  mother              \n",
       "357   2      0.011527  mother              \n",
       "3242  3      0.995213  mountain            \n",
       "130   1      0.670857  movie               \n",
       "130   2      0.148072  movie               \n",
       "130   8      0.179298  movie               \n",
       "6648  8      0.931150  multi               \n",
       "1202  2      0.389129  murder              \n",
       "1202  7      0.610068  murder              \n",
       "1668  2      0.275160  murderer            \n",
       "1668  7      0.719650  murderer            \n",
       "1513  1      0.280051  music               \n",
       "1513  8      0.718300  music               \n",
       "976   1      0.321899  musical             \n",
       "976   8      0.675988  musical             \n",
       "131   1      0.492399  must                \n",
       "131   2      0.093960  must                \n",
       "131   3      0.215276  must                \n",
       "131   4      0.054116  must                \n",
       "131   6      0.121910  must                \n",
       "131   7      0.022598  must                \n",
       "1203  1      0.215745  mysterious          \n",
       "1203  2      0.098519  mysterious          \n",
       "1203  3      0.405302  mysterious          \n",
       "1203  5      0.009977  mysterious          \n",
       "1203  6      0.234451  mysterious          \n",
       "1203  7      0.034918  mysterious          \n",
       "850   6      0.056969  mystery             \n",
       "850   7      0.937792  mystery             \n",
       "6773  11     0.934782  narrative           \n",
       "5143  4      0.987621  nation              \n",
       "2613  4      0.980102  nazi                \n",
       "1204  1      0.943087  never               \n",
       "1204  2      0.055967  never               \n",
       "566   1      0.844169  new                 \n",
       "566   2      0.055013  new                 \n",
       "566   3      0.059566  new                 \n",
       "566   5      0.040975  new                 \n",
       "2743  5      0.991441  nuclear             \n",
       "365   2      0.700968  officer             \n",
       "365   4      0.243238  officer             \n",
       "365   7      0.055281  officer             \n",
       "366   1      0.783680  old                 \n",
       "366   2      0.081902  old                 \n",
       "366   3      0.134286  old                 \n",
       "2186  8      0.940931  onstage             \n",
       "982   2      0.319450  operation           \n",
       "982   4      0.655712  operation           \n",
       "982   5      0.019615  operation           \n",
       "6000  3      0.914136  operative           \n",
       "6000  7      0.048754  operative           \n",
       "6000  12     0.030471  operative           \n",
       "2478  9      0.990878  opponent            \n",
       "6183  4      0.974506  opposition          \n",
       "140   1      0.147971  order               \n",
       "140   2      0.395622  order               \n",
       "140   3      0.154173  order               \n",
       "140   4      0.265815  order               \n",
       "140   5      0.015506  order               \n",
       "140   6      0.020822  order               \n",
       "984   3      0.992244  ordinary            \n",
       "985   1      0.252871  other               \n",
       "985   2      0.137409  other               \n",
       "985   3      0.609754  other               \n",
       "6945  15     0.411666  pacifist            \n",
       "7666  12     0.858625  parasite            \n",
       "2188  1      0.999218  parent              \n",
       "3001  2      0.735565  passenger           \n",
       "3001  5      0.041247  passenger           \n",
       "3001  12     0.219982  passenger           \n",
       "6984  6      0.984224  pastor              \n",
       "7043  9      0.923455  payroll             \n",
       "2394  10     0.954394  peak                \n",
       "988   11     0.974926  penny               \n",
       "3243  11     0.919310  pennys              \n",
       "148   1      0.535703  perform             \n",
       "148   2      0.067715  perform             \n",
       "148   3      0.069220  perform             \n",
       "148   8      0.325033  perform             \n",
       "2189  1      0.251050  performance         \n",
       "2189  8      0.715679  performance         \n",
       "2189  9      0.029976  performance         \n",
       "6135  13     0.349492  perpetual           \n",
       "4404  5      0.985796  phenomenon          \n",
       "150   2      0.998214  phone               \n",
       "2694  5      0.605731  pilot               \n",
       "2694  12     0.385909  pilot               \n",
       "1336  5      0.935116  pirate              \n",
       "1336  6      0.057992  pirate              \n",
       "2119  6      0.982017  plague              \n",
       "576   1      0.239934  plan                \n",
       "576   2      0.574656  plan                \n",
       "576   3      0.112985  plan                \n",
       "576   4      0.047817  plan                \n",
       "576   5      0.024543  plan                \n",
       "1458  1      0.213905  plane               \n",
       "1458  3      0.079352  plane               \n",
       "1458  5      0.062102  plane               \n",
       "1458  12     0.641716  plane               \n",
       "2023  5      0.996100  planet              \n",
       "5086  12     0.667891  platoon             \n",
       "579   1      0.718677  play                \n",
       "579   2      0.037592  play                \n",
       "579   8      0.139313  play                \n",
       "579   9      0.103195  play                \n",
       "713   9      0.991163  player              \n",
       "6777  11     0.864035  pledge              \n",
       "5282  14     0.421393  poise               \n",
       "373   2      0.883997  police              \n",
       "373   7      0.115688  police              \n",
       "4047  2      0.992719  policeman           \n",
       "859   4      0.704202  political           \n",
       "859   7      0.293152  political           \n",
       "1752  12     0.767323  pollution           \n",
       "3246  11     0.911560  polly               \n",
       "6402  10     0.932440  poltergeist         \n",
       "3714  8      0.961206  porn                \n",
       "2257  2      0.996363  pose                \n",
       "3842  3      0.010042  possess             \n",
       "3842  6      0.984103  possess             \n",
       "861   2      0.035498  power               \n",
       "861   3      0.221343  power               \n",
       "861   5      0.234916  power               \n",
       "861   6      0.495933  power               \n",
       "861   7      0.012529  power               \n",
       "2028  1      0.085210  powerful            \n",
       "2028  2      0.061971  powerful            \n",
       "2028  3      0.118777  powerful            \n",
       "2028  5      0.080045  powerful            \n",
       "2028  6      0.583557  powerful            \n",
       "2028  7      0.067135  powerful            \n",
       "6778  11     0.909908  premiere            \n",
       "4049  2      0.992952  price               \n",
       "1101  1      0.159667  priest              \n",
       "1101  6      0.835701  priest              \n",
       "993   2      0.798977  prison              \n",
       "993   7      0.200134  prison              \n",
       "1337  2      0.029087  prisoner            \n",
       "1337  3      0.174525  prisoner            \n",
       "1337  4      0.785361  prisoner            \n",
       "1337  6      0.005817  prisoner            \n",
       "1817  1      0.987374  problem             \n",
       "1817  5      0.011220  problem             \n",
       "7399  8      0.983407  producer            \n",
       "5318  1      0.069808  production          \n",
       "5318  4      0.093078  production          \n",
       "5318  8      0.829941  production          \n",
       "6653  7      0.964852  profile             \n",
       "4662  8      0.916926  province            \n",
       "5897  6      0.979928  psychic             \n",
       "5091  12     0.800488  quarantine          \n",
       "4472  14     0.946272  rabbit              \n",
       "1103  2      0.370093  race                \n",
       "1103  3      0.058080  race                \n",
       "1103  5      0.178293  race                \n",
       "1103  6      0.075640  race                \n",
       "1103  9      0.317416  race                \n",
       "5344  9      0.960358  racer               \n",
       "1675  11     0.955053  ranch               \n",
       "2624  2      0.997654  rape                \n",
       "6872  7      0.973485  raucous             \n",
       "585   1      0.071922  reach               \n",
       "585   2      0.229915  reach               \n",
       "585   3      0.661448  reach               \n",
       "585   5      0.035372  reach               \n",
       "3058  10     0.949203  realization         \n",
       "3846  4      0.989919  rebel               \n",
       "5629  4      0.991713  rebellion           \n",
       "3510  12     0.608882  reconstruct         \n",
       "775   1      0.200150  record              \n",
       "775   2      0.581489  record              \n",
       "775   5      0.023175  record              \n",
       "775   8      0.193830  record              \n",
       "1677  2      0.132288  recruit             \n",
       "1677  4      0.789719  recruit             \n",
       "1677  9      0.072157  recruit             \n",
       "5526  4      0.983950  refugee             \n",
       "4695  9      0.941446  reggie              \n",
       "1340  1      0.995419  reject              \n",
       "590   1      0.999575  relationship        \n",
       "386   1      0.161687  remain              \n",
       "386   2      0.158074  remain              \n",
       "386   3      0.637714  remain              \n",
       "386   4      0.040648  remain              \n",
       "386   5      0.000903  remain              \n",
       "3417  3      0.991701  remote              \n",
       "4771  12     0.921030  remotely            \n",
       "869   1      0.300247  reporter            \n",
       "869   3      0.037017  reporter            \n",
       "869   7      0.658075  reporter            \n",
       "7338  13     0.362741  reptile             \n",
       "451   2      0.039947  rescue              \n",
       "451   3      0.795808  rescue              \n",
       "451   4      0.094776  rescue              \n",
       "451   5      0.068145  rescue              \n",
       "2328  5      0.990074  resistance          \n",
       "7606  3      0.991376  retain              \n",
       "720   1      0.397948  return              \n",
       "720   2      0.304533  return              \n",
       "720   3      0.291922  return              \n",
       "720   4      0.000467  return              \n",
       "720   5      0.000234  return              \n",
       "720   6      0.004904  return              \n",
       "171   1      0.189801  reveal              \n",
       "171   2      0.581152  reveal              \n",
       "171   3      0.216313  reveal              \n",
       "171   5      0.007833  reveal              \n",
       "171   6      0.004519  reveal              \n",
       "171   7      0.000301  reveal              \n",
       "2198  1      0.026074  revenge             \n",
       "2198  2      0.884039  revenge             \n",
       "2198  3      0.019866  revenge             \n",
       "2198  6      0.069531  revenge             \n",
       "1919  9      0.890133  richie              \n",
       "6956  13     0.726680  rick                \n",
       "3189  3      0.993575  river               \n",
       "1003  2      0.996451  robbery             \n",
       "2701  11     0.944088  robbie              \n",
       "4474  14     0.545064  roberta             \n",
       "452   5      0.995950  robot               \n",
       "6929  10     0.939371  rocky               \n",
       "6081  4      0.976835  rogue               \n",
       "174   1      0.533039  role                \n",
       "174   2      0.097221  role                \n",
       "174   8      0.365417  role                \n",
       "6930  10     0.924503  rookie              \n",
       "176   1      0.018991  room                \n",
       "176   2      0.976730  room                \n",
       "176   3      0.003593  room                \n",
       "4235  8      0.917040  royalty             \n",
       "393   1      0.225504  run                 \n",
       "393   2      0.647882  run                 \n",
       "393   3      0.126330  run                 \n",
       "1342  9      0.940784  runner              \n",
       "7421  12     0.756690  runway              \n",
       "3060  2      0.092589  russian             \n",
       "3060  4      0.903846  russian             \n",
       "1365  4      0.994595  ruthless            \n",
       "5154  5      0.983455  sailor              \n",
       "2044  5      0.977695  satellite           \n",
       "779   8      0.959204  satire              \n",
       "395   1      0.025845  save                \n",
       "395   2      0.228843  save                \n",
       "395   3      0.633431  save                \n",
       "395   4      0.003289  save                \n",
       "395   5      0.035243  save                \n",
       "395   6      0.073305  save                \n",
       "2545  9      0.960805  scholarship         \n",
       "602   1      0.999423  school              \n",
       "2747  5      0.981258  science             \n",
       "1115  5      0.997114  scientist           \n",
       "3013  1      0.468539  score               \n",
       "3013  2      0.113096  score               \n",
       "3013  9      0.411991  score               \n",
       "5404  8      0.964408  script              \n",
       "2911  14     0.525113  scroll              \n",
       "6994  14     0.706526  sculptor            \n",
       "4905  10     0.898651  sculpture           \n",
       "3254  1      0.438012  season              \n",
       "3254  9      0.549662  season              \n",
       "2880  8      0.950372  sebastian           \n",
       "1008  1      0.407238  secret              \n",
       "1008  2      0.085568  secret              \n",
       "1008  4      0.299486  secret              \n",
       "1008  5      0.051499  secret              \n",
       "1008  6      0.106167  secret              \n",
       "1008  7      0.050707  secret              \n",
       "184   1      0.399966  see                 \n",
       "184   2      0.506727  see                 \n",
       "184   3      0.093124  see                 \n",
       "6702  7      0.978613  selene              \n",
       "2630  2      0.464686  sentence            \n",
       "2630  7      0.529905  sentence            \n",
       "3472  10     0.970279  sequel              \n",
       "187   1      0.350142  set                 \n",
       "187   2      0.295279  set                 \n",
       "187   3      0.354157  set                 \n",
       "3123  12     0.916939  seth                \n",
       "781   1      0.996265  sexual              \n",
       "3257  11     0.938278  sexy                \n",
       "608   10     0.979914  shark               \n",
       "1118  5      0.997862  ship                \n",
       "401   2      0.924931  shoot               \n",
       "401   3      0.008291  shoot               \n",
       "401   4      0.066326  shoot               \n",
       "404   2      0.931669  shot                \n",
       "404   3      0.065940  shot                \n",
       "191   1      0.527320  show                \n",
       "191   2      0.321982  show                \n",
       "191   3      0.053331  show                \n",
       "191   8      0.096965  show                \n",
       "3422  12     0.826062  shuttle             \n",
       "3259  11     0.979455  sibling_relationship\n",
       "6446  3      0.993490  silver              \n",
       "3194  8      0.995022  singer              \n",
       "1347  8      0.973328  singing             \n",
       "1838  1      0.931761  sister              \n",
       "1838  2      0.067324  sister              \n",
       "3560  6      0.992629  slave               \n",
       "1012  10     0.947983  small_town          \n",
       "2410  8      0.931755  solace              \n",
       "726   4      0.997993  soldier             \n",
       "881   1      0.096022  solve               \n",
       "881   3      0.131398  solve               \n",
       "881   7      0.768175  solve               \n",
       "612   1      0.859513  son                 \n",
       "612   2      0.048757  son                 \n",
       "612   3      0.091043  son                 \n",
       "1013  8      0.989216  song                \n",
       "7293  11     0.919578  sonny               \n",
       "1876  1      0.249960  soul                \n",
       "1876  6      0.745643  soul                \n",
       "1120  5      0.997836  space               \n",
       "1121  5      0.988902  spacecraft          \n",
       "2052  12     0.553297  spacesuit           \n",
       "199   6      0.992139  spell               \n",
       "4301  6      0.994594  spirit              \n",
       "2549  9      0.988498  sport               \n",
       "4776  2      0.178525  spy                 \n",
       "4776  4      0.817094  spy                 \n",
       "1231  1      0.366389  stage               \n",
       "1231  2      0.220384  stage               \n",
       "1231  8      0.410465  stage               \n",
       "454   1      0.424252  star                \n",
       "454   3      0.056567  star                \n",
       "454   8      0.466677  star                \n",
       "454   9      0.051853  star                \n",
       "412   2      0.963880  steal               \n",
       "412   3      0.007891  steal               \n",
       "412   5      0.007891  steal               \n",
       "412   6      0.019165  steal               \n",
       "2210  11     0.954613  stephanie           \n",
       "4237  13     0.601655  steward             \n",
       "1475  1      0.209680  storm               \n",
       "1475  2      0.003201  storm               \n",
       "1475  3      0.785899  storm               \n",
       "616   1      0.973702  story               \n",
       "616   2      0.002567  story               \n",
       "616   7      0.023530  story               \n",
       "7507  13     0.727558  storyline           \n",
       "1517  1      0.999291  student             \n",
       "2212  8      0.990081  studio              \n",
       "5163  5      0.990128  submarine           \n",
       "6234  13     0.758103  suburb              \n",
       "1016  1      0.997758  successful          \n",
       "3263  1      0.996495  summer              \n",
       "2059  5      0.994250  super               \n",
       "6589  9      0.978613  superhero           \n",
       "4809  6      0.992653  superhero_base      \n",
       "5902  6      0.994882  supernatural        \n",
       "618   10     0.944617  surf                \n",
       "2267  7      0.978880  surveillance        \n",
       "3849  3      0.995386  survival            \n",
       "2131  2      0.045410  survive             \n",
       "2131  3      0.792401  survive             \n",
       "2131  4      0.161205  survive             \n",
       "1354  2      0.704438  suspect             \n",
       "1354  7      0.293046  suspect             \n",
       "2915  6      0.989018  sword               \n",
       "1238  2      0.360930  system              \n",
       "1238  5      0.579046  system              \n",
       "1238  7      0.059722  system              \n",
       "212   1      0.323173  take                \n",
       "212   2      0.484939  take                \n",
       "212   3      0.191678  take                \n",
       "3427  2      0.414182  target              \n",
       "3427  4      0.525049  target              \n",
       "3427  7      0.058571  target              \n",
       "2553  1      0.998191  teacher             \n",
       "455   3      0.065081  team                \n",
       "455   4      0.382504  team                \n",
       "455   5      0.101919  team                \n",
       "455   9      0.450040  team                \n",
       "2885  7      0.955049  tech                \n",
       "2063  5      0.995387  technology          \n",
       "214   1      0.466177  tell                \n",
       "214   2      0.514398  tell                \n",
       "214   3      0.019339  tell                \n",
       "4014  11     0.949480  tennis              \n",
       "2337  4      0.998093  terrorist           \n",
       "2640  7      0.955863  testify             \n",
       "1019  2      0.187068  theater             \n",
       "1019  3      0.004797  theater             \n",
       "1019  8      0.801036  theater             \n",
       "1020  2      0.991829  theft               \n",
       "1021  1      0.998734  thing               \n",
       "427   1      0.124455  threaten            \n",
       "427   2      0.841109  threaten            \n",
       "427   4      0.033188  threaten            \n",
       "3565  6      0.989403  throne              \n",
       "3129  10     0.914889  tick                \n",
       "1605  10     0.935000  tiger               \n",
       "216   1      0.786433  time                \n",
       "216   2      0.149308  time                \n",
       "216   3      0.033361  time                \n",
       "216   5      0.030795  time                \n",
       "2065  1      0.423889  title               \n",
       "2065  9      0.571757  title               \n",
       "7181  10     0.905252  toast               \n",
       "456   1      0.952160  together            \n",
       "456   2      0.047442  together            \n",
       "4449  11     0.914299  totally             \n",
       "2132  1      0.309329  tour                \n",
       "2132  2      0.033312  tour                \n",
       "2132  4      0.090419  tour                \n",
       "2132  8      0.561551  tour                \n",
       "2214  9      0.995007  tournament          \n",
       "1243  3      0.993290  tower               \n",
       "1697  1      0.157510  town                \n",
       "1697  2      0.064791  town                \n",
       "1697  3      0.777495  town                \n",
       "2503  9      0.982553  trainer             \n",
       "1489  1      0.060242  training            \n",
       "1489  3      0.309241  training            \n",
       "1489  4      0.401611  training            \n",
       "1489  9      0.224902  training            \n",
       "1779  3      0.998742  trap                \n",
       "737   1      0.066790  tree                \n",
       "737   3      0.931346  tree                \n",
       "1025  6      0.123855  trial               \n",
       "1025  7      0.866988  trial               \n",
       "4239  9      0.932977  troll               \n",
       "1491  4      0.994710  troop               \n",
       "218   1      0.352568  try                 \n",
       "218   2      0.506976  try                 \n",
       "218   3      0.140371  try                 \n",
       "432   1      0.449817  turn                \n",
       "432   2      0.286337  turn                \n",
       "432   3      0.261438  turn                \n",
       "432   6      0.002293  turn                \n",
       "4418  1      0.171421  tv                  \n",
       "4418  2      0.533616  tv                  \n",
       "4418  8      0.290309  tv                  \n",
       "5251  15     0.429505  tyrannical          \n",
       "3568  10     0.941302  undefeated          \n",
       "1127  2      0.362850  undercover          \n",
       "1127  7      0.631259  undercover          \n",
       "1027  14     0.378735  underlie            \n",
       "4991  12     0.717402  undo                \n",
       "2889  9      0.936750  unicorn             \n",
       "1495  2      0.052501  unit                \n",
       "1495  4      0.938449  unit                \n",
       "5947  5      0.993744  universe            \n",
       "1250  6      0.981204  unleash             \n",
       "6613  9      0.960257  unscrupulous        \n",
       "3270  11     0.886640  unwanted            \n",
       "1029  14     0.475942  upsetting           \n",
       "225   1      0.071730  use                 \n",
       "225   2      0.521205  use                 \n",
       "225   3      0.267569  use                 \n",
       "225   5      0.098049  use                 \n",
       "225   6      0.041284  use                 \n",
       "2073  13     0.601182  vacuum              \n",
       "6707  3      0.998138  vampire             \n",
       "2217  2      0.511410  victim              \n",
       "2217  3      0.122935  victim              \n",
       "2217  7      0.363888  victim              \n",
       "3384  14     0.942202  victor              \n",
       "1613  3      0.971213  village             \n",
       "1613  4      0.025266  village             \n",
       "1613  6      0.002021  village             \n",
       "1130  2      0.505190  violence            \n",
       "1130  3      0.025176  violence            \n",
       "1130  4      0.176229  violence            \n",
       "1130  6      0.016784  violence            \n",
       "1130  7      0.276931  violence            \n",
       "2136  9      0.937431  viral               \n",
       "738   12     0.977129  virus               \n",
       "2411  14     0.578772  vivian              \n",
       "3272  11     0.905187  waiter              \n",
       "1131  4      0.998032  war                 \n",
       "1615  6      0.996763  warrior             \n",
       "629   3      0.998441  water               \n",
       "3430  11     0.980917  wed                 \n",
       "1366  1      0.998951  wedding             \n",
       "630   10     0.962652  whale               \n",
       "2556  14     0.934220  widow               \n",
       "4115  9      0.928417  willy               \n",
       "2220  1      0.603897  win                 \n",
       "2220  9      0.394966  win                 \n",
       "234   2      0.950889  window              \n",
       "234   3      0.045946  window              \n",
       "2221  3      0.995777  wink                \n",
       "235   6      0.991713  witch               \n",
       "438   1      0.075919  witness             \n",
       "438   2      0.480819  witness             \n",
       "438   3      0.221916  witness             \n",
       "438   7      0.221916  witness             \n",
       "3725  9      0.975979  wizard              \n",
       "4305  6      0.980569  wolf                \n",
       "236   1      0.841437  woman               \n",
       "236   2      0.158062  woman               \n",
       "5253  3      0.997038  wood                \n",
       "792   1      0.664086  work                \n",
       "792   2      0.324356  work                \n",
       "792   5      0.011455  work                \n",
       "899   1      0.576840  world               \n",
       "899   5      0.151800  world               \n",
       "899   6      0.270905  world               \n",
       "6980  1      0.998594  wrestling           \n",
       "793   1      0.996974  writer              \n",
       "743   1      0.898561  year                \n",
       "743   2      0.021386  year                \n",
       "743   3      0.080011  year                \n",
       "6141  13     0.668468  yearn               \n",
       "632   1      0.914177  young               \n",
       "632   2      0.012189  young               \n",
       "632   3      0.071259  young               \n",
       "632   6      0.002188  young               , R=30, lambda_step=0.01, plot_opts={'xlab': 'PC1', 'ylab': 'PC2'}, topic_order=[8, 3, 14, 6, 15, 10, 7, 5, 11, 2, 13, 9, 1, 4, 12])"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Visualize the topics\n",
    "pyLDAvis.enable_notebook()\n",
    "vis = pyLDAvis.gensim.prepare(lda_model, corpus, id2word)\n",
    "vis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(0,\n",
       "  [('patient', 0.03161468),\n",
       "   ('rise', 0.03084148),\n",
       "   ('rabbit', 0.015390237),\n",
       "   ('toy', 0.014982357),\n",
       "   ('basement', 0.013688705),\n",
       "   ('violently', 0.012183724),\n",
       "   ('noise', 0.011055235),\n",
       "   ('trauma', 0.010794966),\n",
       "   ('tattoo', 0.01078408),\n",
       "   ('toilet', 0.009999722),\n",
       "   ('banker', 0.008219323),\n",
       "   ('frighten', 0.007926155),\n",
       "   ('bleed', 0.007732194),\n",
       "   ('cartoon', 0.007349138),\n",
       "   ('troupe', 0.0073239123),\n",
       "   ('insane', 0.007187707),\n",
       "   ('shocking', 0.006932281),\n",
       "   ('tent', 0.0068267905),\n",
       "   ('paranoid', 0.0065089753),\n",
       "   ('theory', 0.006395869),\n",
       "   ('enormous', 0.0063369866),\n",
       "   ('there', 0.0063316524),\n",
       "   ('plastic', 0.006326219),\n",
       "   ('hallucination', 0.0060968064),\n",
       "   ('camera', 0.0060888007),\n",
       "   ('protector', 0.005949115),\n",
       "   ('compare', 0.005905147),\n",
       "   ('weather', 0.005831121),\n",
       "   ('elizabeth', 0.0057101534),\n",
       "   ('conference', 0.005549204),\n",
       "   ('closet', 0.0054290197),\n",
       "   ('significant', 0.0052291853),\n",
       "   ('perpetrator', 0.0051004677),\n",
       "   ('size', 0.0047261263),\n",
       "   ('prank', 0.004696487),\n",
       "   ('dirt', 0.004536494),\n",
       "   ('isolation', 0.0042154524),\n",
       "   ('coal', 0.004110992),\n",
       "   ('revert', 0.0040769232),\n",
       "   ('hysterically', 0.0036770538),\n",
       "   ('schizophrenia', 0.003330808),\n",
       "   ('hallway', 0.0030171452),\n",
       "   ('diagnosis', 0.0028892653),\n",
       "   ('rat', 0.0028603503),\n",
       "   ('mickey', 0.0028514212),\n",
       "   ('lane', 0.0026082227),\n",
       "   ('wrist', 0.0026026275),\n",
       "   ('collector', 0.0025350938),\n",
       "   ('hurricane', 0.0023018809),\n",
       "   ('compass', 0.0022785242),\n",
       "   ('outbreak', 0.0022591592),\n",
       "   ('crawl', 0.002249482),\n",
       "   ('chill', 0.0020426826),\n",
       "   ('topic', 0.0019205027),\n",
       "   ('vortex', 0.0019190505),\n",
       "   ('dose', 0.0018813424),\n",
       "   ('additionally', 0.001827492),\n",
       "   ('stepfather', 0.0016971756),\n",
       "   ('inside', 0.0015336437),\n",
       "   ('surfing', 0.0015248429),\n",
       "   ('backwards', 0.001497307),\n",
       "   ('hypnosis', 0.0014242859),\n",
       "   ('orderly', 0.0013307779),\n",
       "   ('rendition', 0.0013251232),\n",
       "   ('committed_suicide', 0.001313603),\n",
       "   ('corpse', 0.001307526),\n",
       "   ('crane', 0.001274921),\n",
       "   ('wield', 0.0012034246),\n",
       "   ('staircase', 0.0011933233),\n",
       "   ('chaotic', 0.0011881401),\n",
       "   ('duck', 0.0011231939),\n",
       "   ('scissor', 0.00095953373),\n",
       "   ('upon_learning', 0.0009381969),\n",
       "   ('severe', 0.00092631334),\n",
       "   ('emit', 0.0008402982),\n",
       "   ('tumor', 0.00083847175),\n",
       "   ('careless', 0.00082344556),\n",
       "   ('imagery', 0.00075473805),\n",
       "   ('razor', 0.0007224334),\n",
       "   ('microphone', 0.00067466166),\n",
       "   ('mimic', 0.00064135867),\n",
       "   ('roberta', 0.00063880475),\n",
       "   ('swerve', 0.0004380945),\n",
       "   ('erratically', 0.000406366),\n",
       "   ('shipwreck', 0.00028058502),\n",
       "   ('beetle', 0.00021271723),\n",
       "   ('catatonic', 0.00018682591),\n",
       "   ('lighting', 0.0001315647),\n",
       "   ('gibb', 0.00012295594),\n",
       "   ('banquet', 9.05365e-05),\n",
       "   ('cole', 8.762035e-05),\n",
       "   ('goodness', 8.7348046e-05),\n",
       "   ('alice', 1.7188571e-05),\n",
       "   ('experiment', 1.713972e-05),\n",
       "   ('sarah', 1.712438e-05),\n",
       "   ('uncle', 1.7113467e-05),\n",
       "   ('greg', 1.7113312e-05),\n",
       "   ('treatment', 1.7110035e-05),\n",
       "   ('wrestling', 1.710807e-05),\n",
       "   ('dane', 1.7106935e-05)]),\n",
       " (1,\n",
       "  [('police', 0.037543207),\n",
       "   ('murder', 0.03292167),\n",
       "   ('kill', 0.022177357),\n",
       "   ('money', 0.018240673),\n",
       "   ('steal', 0.0154193025),\n",
       "   ('car', 0.014222198),\n",
       "   ('drug', 0.013507893),\n",
       "   ('officer', 0.013078368),\n",
       "   ('arrest', 0.012659839),\n",
       "   ('crime', 0.011452309),\n",
       "   ('man', 0.011272455),\n",
       "   ('shoot', 0.011102017),\n",
       "   ('gang', 0.009574693),\n",
       "   ('case', 0.009229308),\n",
       "   ('agent', 0.008168403),\n",
       "   ('criminal', 0.007285473),\n",
       "   ('gun', 0.006813423),\n",
       "   ('violence', 0.006691843),\n",
       "   ('bond', 0.0066795466),\n",
       "   ('plan', 0.0062783696),\n",
       "   ('death', 0.006267775),\n",
       "   ('detective', 0.0061783316),\n",
       "   ('investigation', 0.005979262),\n",
       "   ('partner', 0.0056160903),\n",
       "   ('investigate', 0.005546831),\n",
       "   ('cop', 0.0054351394),\n",
       "   ('escape', 0.005333273),\n",
       "   ('revenge', 0.0053280145),\n",
       "   ('kidnap', 0.005199263),\n",
       "   ('former', 0.0050423485),\n",
       "   ('chase', 0.0050106677),\n",
       "   ('suspect', 0.0049968814),\n",
       "   ('corrupt', 0.0048095216),\n",
       "   ('evidence', 0.0047779405),\n",
       "   ('wife', 0.0047330726),\n",
       "   ('brother', 0.0045914315),\n",
       "   ('involve', 0.0044347644),\n",
       "   ('work', 0.0043021995),\n",
       "   ('reveal', 0.004211224),\n",
       "   ('track', 0.0041529206),\n",
       "   ('beat', 0.0040504276),\n",
       "   ('fake', 0.0039719334),\n",
       "   ('local', 0.0038773376),\n",
       "   ('threaten', 0.0038606352),\n",
       "   ('information', 0.003834861),\n",
       "   ('hostage', 0.0037887676),\n",
       "   ('target', 0.0037205121),\n",
       "   ('boss', 0.00371847),\n",
       "   ('commit', 0.0037143067),\n",
       "   ('victim', 0.0037097896),\n",
       "   ('force', 0.0035949093),\n",
       "   ('use', 0.003576395),\n",
       "   ('order', 0.0035470643),\n",
       "   ('diamond', 0.0035229642),\n",
       "   ('pay', 0.003390874),\n",
       "   ('cash', 0.0033530693),\n",
       "   ('heist', 0.0032157705),\n",
       "   ('identity', 0.003160236),\n",
       "   ('rip', 0.0031185006),\n",
       "   ('scene', 0.0030686304),\n",
       "   ('station', 0.0030657928),\n",
       "   ('train', 0.0030121563),\n",
       "   ('thief', 0.0029543247),\n",
       "   ('building', 0.0029205338),\n",
       "   ('gangster', 0.0029109935),\n",
       "   ('bank', 0.002881113),\n",
       "   ('box', 0.0028602886),\n",
       "   ('jail', 0.0028397806),\n",
       "   ('know', 0.002759427),\n",
       "   ('take', 0.0027330392),\n",
       "   ('undercover', 0.0027257954),\n",
       "   ('cat', 0.0027255726),\n",
       "   ('hotel', 0.0026948801),\n",
       "   ('office', 0.0026682934),\n",
       "   ('deal', 0.002633093),\n",
       "   ('violent', 0.002631525),\n",
       "   ('pursue', 0.0026097165),\n",
       "   ('security', 0.0026086736),\n",
       "   ('cocaine', 0.0025923082),\n",
       "   ('catch', 0.0025837168),\n",
       "   ('hire', 0.002569844),\n",
       "   ('hide', 0.0024889952),\n",
       "   ('situation', 0.0024724905),\n",
       "   ('release', 0.0024277822),\n",
       "   ('debt', 0.0023662522),\n",
       "   ('charge', 0.0023409026),\n",
       "   ('discover', 0.0023400835),\n",
       "   ('robbery', 0.002321892),\n",
       "   ('tape', 0.0023114905),\n",
       "   ('theft', 0.0023040276),\n",
       "   ('street', 0.0022900759),\n",
       "   ('bathtub', 0.0022326538),\n",
       "   ('con', 0.0022151773),\n",
       "   ('henchman', 0.0021918672),\n",
       "   ('help', 0.002172798),\n",
       "   ('factory', 0.002171658),\n",
       "   ('member', 0.002156568),\n",
       "   ('witness', 0.00215364),\n",
       "   ('lead', 0.0021215167),\n",
       "   ('associate', 0.0021197742)]),\n",
       " (2,\n",
       "  [('emily', 0.044979904),\n",
       "   ('murderer', 0.023220072),\n",
       "   ('victor', 0.018985512),\n",
       "   ('holly', 0.017208407),\n",
       "   ('fre', 0.01717127),\n",
       "   ('fred', 0.012525589),\n",
       "   ('belt', 0.0102788685),\n",
       "   ('paul', 0.010211044),\n",
       "   ('instructor', 0.008820879),\n",
       "   ('tenant', 0.007685751),\n",
       "   ('committed', 0.0076477467),\n",
       "   ('cellphone', 0.005949437),\n",
       "   ('smooth', 0.00508209),\n",
       "   ('dilemma', 0.004917814),\n",
       "   ('seth', 0.0043381033),\n",
       "   ('reconsider', 0.0042375354),\n",
       "   ('needle', 0.0027363948),\n",
       "   ('siren', 0.0024919063),\n",
       "   ('drunkenly', 0.0023302045),\n",
       "   ('cohort', 0.0013528856),\n",
       "   ('jeopardy', 0.0011997728),\n",
       "   ('insinuate', 0.0008750614),\n",
       "   ('pan', 0.0005326096),\n",
       "   ('initially_reluctant', 0.00012731273),\n",
       "   ('poe', 2.2860753e-05),\n",
       "   ('cal', 2.2850287e-05),\n",
       "   ('greg', 2.2824246e-05),\n",
       "   ('beret', 2.282383e-05),\n",
       "   ('hooded_figure', 2.2812917e-05),\n",
       "   ('nile', 2.2806385e-05),\n",
       "   ('aunt', 2.2797161e-05),\n",
       "   ('alice', 2.2793505e-05),\n",
       "   ('atm', 2.2777574e-05),\n",
       "   ('brent', 2.2771948e-05),\n",
       "   ('bunny', 2.2770155e-05),\n",
       "   ('rodrick', 2.275167e-05),\n",
       "   ('singh', 2.2747166e-05),\n",
       "   ('impulsively', 2.2746844e-05),\n",
       "   ('influential', 2.2746372e-05),\n",
       "   ('knack', 2.2745104e-05),\n",
       "   ('smart', 2.2744593e-05),\n",
       "   ('presidency', 2.2744523e-05),\n",
       "   ('adviser', 2.2744518e-05),\n",
       "   ('speechwriter', 2.2744502e-05),\n",
       "   ('sitter', 2.2744502e-05),\n",
       "   ('politics', 2.2744502e-05),\n",
       "   ('vlogger', 2.2743829e-05),\n",
       "   ('feign', 2.2743463e-05),\n",
       "   ('slacker', 2.2743241e-05),\n",
       "   ('licorice', 2.2743237e-05),\n",
       "   ('freeze', 2.2743086e-05),\n",
       "   ('mom', 2.2741182e-05),\n",
       "   ('louie', 2.2739954e-05),\n",
       "   ('cedric', 2.273754e-05),\n",
       "   ('swamp', 2.2737186e-05),\n",
       "   ('wilderness', 2.2736825e-05),\n",
       "   ('throat', 2.27346e-05),\n",
       "   ('sparky', 2.2733186e-05),\n",
       "   ('rust', 2.2732444e-05),\n",
       "   ('paige', 2.273124e-05),\n",
       "   ('lockjaw', 2.272847e-05),\n",
       "   ('gator', 2.272847e-05),\n",
       "   ('wyatt', 2.27276e-05),\n",
       "   ('naked', 2.272754e-05),\n",
       "   ('rowley', 2.2726766e-05),\n",
       "   ('tone', 2.2726499e-05),\n",
       "   ('zombie', 2.2726439e-05),\n",
       "   ('david', 2.2725724e-05),\n",
       "   ('agne', 2.2725648e-05),\n",
       "   ('security_guard', 2.2725275e-05),\n",
       "   ('corey', 2.2724733e-05),\n",
       "   ('lillith', 2.2724282e-05),\n",
       "   ('bindu', 2.2723745e-05),\n",
       "   ('juvenile_delinquent', 2.2723189e-05),\n",
       "   ('spark', 2.2722506e-05),\n",
       "   ('carve', 2.2722308e-05),\n",
       "   ('grade', 2.2722046e-05),\n",
       "   ('drummer', 2.2720908e-05),\n",
       "   ('fun', 2.2720204e-05),\n",
       "   ('oscar', 2.2719954e-05),\n",
       "   ('sudeep', 2.2719942e-05),\n",
       "   ('production', 2.2718816e-05),\n",
       "   ('recording', 2.271817e-05),\n",
       "   ('golf', 2.2718084e-05),\n",
       "   ('battery', 2.2717995e-05),\n",
       "   ('emilys', 2.2717648e-05),\n",
       "   ('hop', 2.2717391e-05),\n",
       "   ('subdue', 2.2717133e-05),\n",
       "   ('labor', 2.2717075e-05),\n",
       "   ('boil', 2.2716882e-05),\n",
       "   ('dodge', 2.2716878e-05),\n",
       "   ('obvious', 2.2716875e-05),\n",
       "   ('rick', 2.2716766e-05),\n",
       "   ('pageant', 2.2716724e-05),\n",
       "   ('drum', 2.2716711e-05),\n",
       "   ('reflection', 2.2716677e-05),\n",
       "   ('cloudy', 2.2716671e-05),\n",
       "   ('nicky', 2.2716671e-05),\n",
       "   ('harken', 2.271667e-05),\n",
       "   ('quite', 2.2716576e-05)]),\n",
       " (3,\n",
       "  [('find', 0.035742853),\n",
       "   ('tell', 0.02232761),\n",
       "   ('go', 0.021538844),\n",
       "   ('leave', 0.020526662),\n",
       "   ('take', 0.016492223),\n",
       "   ('see', 0.0159537),\n",
       "   ('try', 0.014273773),\n",
       "   ('come', 0.011190603),\n",
       "   ('run', 0.010933863),\n",
       "   ('man', 0.010933383),\n",
       "   ('back', 0.0108737275),\n",
       "   ('arrive', 0.009860634),\n",
       "   ('get', 0.0096629355),\n",
       "   ('later', 0.009532556),\n",
       "   ('call', 0.008484453),\n",
       "   ('night', 0.008287691),\n",
       "   ('return', 0.008238844),\n",
       "   ('away', 0.007754511),\n",
       "   ('kill', 0.0074088187),\n",
       "   ('room', 0.006793666),\n",
       "   ('begin', 0.006728295),\n",
       "   ('home', 0.006569122),\n",
       "   ('ask', 0.0065381094),\n",
       "   ('head', 0.0065380777),\n",
       "   ('look', 0.006519739),\n",
       "   ('town', 0.0064352844),\n",
       "   ('say', 0.006321983),\n",
       "   ('car', 0.0061672954),\n",
       "   ('give', 0.0059211203),\n",
       "   ('realize', 0.005691751),\n",
       "   ('die', 0.0056327647),\n",
       "   ('drive', 0.0055764355),\n",
       "   ('make', 0.005503101),\n",
       "   ('open', 0.0054408973),\n",
       "   ('body', 0.0053413413),\n",
       "   ('reveal', 0.005340816),\n",
       "   ('follow', 0.0052432274),\n",
       "   ('name', 0.0051956787),\n",
       "   ('turn', 0.0051695774),\n",
       "   ('discover', 0.005085544),\n",
       "   ('know', 0.0049255113),\n",
       "   ('dead', 0.00492435),\n",
       "   ('help', 0.004850889),\n",
       "   ('stop', 0.0047929147),\n",
       "   ('hand', 0.004613046),\n",
       "   ('break', 0.004351119),\n",
       "   ('believe', 0.0041798535),\n",
       "   ('walk', 0.004173241),\n",
       "   ('death', 0.0041418034),\n",
       "   ('appear', 0.004141754),\n",
       "   ('hide', 0.0040920004),\n",
       "   ('house', 0.00402461),\n",
       "   ('show', 0.003851797),\n",
       "   ('fall', 0.003794308),\n",
       "   ('way', 0.0036666412),\n",
       "   ('apartment', 0.0036480445),\n",
       "   ('throw', 0.0036311063),\n",
       "   ('explain', 0.0035937184),\n",
       "   ('hear', 0.0034921032),\n",
       "   ('meet', 0.003491383),\n",
       "   ('day', 0.0034665158),\n",
       "   ('meanwhile', 0.0034507106),\n",
       "   ('decide', 0.003425113),\n",
       "   ('watch', 0.0034204228),\n",
       "   ('attack', 0.0033536525),\n",
       "   ('hospital', 0.003323555),\n",
       "   ('also', 0.0032641678),\n",
       "   ('attempt', 0.0032597887),\n",
       "   ('search', 0.0032184783),\n",
       "   ('still', 0.003214583),\n",
       "   ('fire', 0.003090369),\n",
       "   ('pull', 0.003045115),\n",
       "   ('eye', 0.0030246377),\n",
       "   ('killer', 0.0030151538),\n",
       "   ('soon', 0.002950081),\n",
       "   ('woman', 0.0029448892),\n",
       "   ('hold', 0.002928925),\n",
       "   ('suddenly', 0.0028954784),\n",
       "   ('cause', 0.0028732815),\n",
       "   ('truck', 0.0028406247),\n",
       "   ('continue', 0.0028390232),\n",
       "   ('start', 0.002838137),\n",
       "   ('stay', 0.0028162403),\n",
       "   ('hit', 0.002785179),\n",
       "   ('happen', 0.002780779),\n",
       "   ('place', 0.002669156),\n",
       "   ('claim', 0.0026531208),\n",
       "   ('door', 0.0026443966),\n",
       "   ('put', 0.0026319067),\n",
       "   ('notice', 0.002611201),\n",
       "   ('cut', 0.0025584619),\n",
       "   ('chase', 0.0025397546),\n",
       "   ('pick', 0.0025250353),\n",
       "   ('miss', 0.0025026528),\n",
       "   ('enter', 0.0024405017),\n",
       "   ('eventually', 0.0024200398),\n",
       "   ('move', 0.0024130137),\n",
       "   ('rape', 0.0024009382),\n",
       "   ('let', 0.0023668406),\n",
       "   ('refuse', 0.0023660874)]),\n",
       " (4,\n",
       "  [('animal', 0.032041814),\n",
       "   ('water', 0.028332446),\n",
       "   ('monster', 0.023581592),\n",
       "   ('dog', 0.020395406),\n",
       "   ('creature', 0.01952956),\n",
       "   ('giant', 0.015298737),\n",
       "   ('boat', 0.014880377),\n",
       "   ('cave', 0.014151835),\n",
       "   ('billy', 0.013167336),\n",
       "   ('island', 0.012587303),\n",
       "   ('village', 0.012279417),\n",
       "   ('forest', 0.012224152),\n",
       "   ('river', 0.011877303),\n",
       "   ('wood', 0.0112761585),\n",
       "   ('rock', 0.010706011),\n",
       "   ('villager', 0.009784137),\n",
       "   ('fish', 0.009275274),\n",
       "   ('dragon', 0.008970698),\n",
       "   ('tree', 0.008173527),\n",
       "   ('human', 0.008065273),\n",
       "   ('flood', 0.007876582),\n",
       "   ('sail', 0.0076856357),\n",
       "   ('sea', 0.007424648),\n",
       "   ('sequel', 0.0073476927),\n",
       "   ('cabin', 0.007262131),\n",
       "   ('cage', 0.007226085),\n",
       "   ('ice', 0.006735806),\n",
       "   ('hunter', 0.0067114052),\n",
       "   ('shark', 0.006470659),\n",
       "   ('swim', 0.0064425813),\n",
       "   ('wolf', 0.0061791325),\n",
       "   ('cult', 0.005945083),\n",
       "   ('pirate', 0.005847337),\n",
       "   ('beast', 0.0055648335),\n",
       "   ('hungry', 0.005533466),\n",
       "   ('trap', 0.0054560537),\n",
       "   ('mayor', 0.005255172),\n",
       "   ('god', 0.005156641),\n",
       "   ('surface', 0.005057111),\n",
       "   ('egg', 0.0050267163),\n",
       "   ('predator', 0.00488244),\n",
       "   ('fishing', 0.0047989283),\n",
       "   ('sink', 0.004739483),\n",
       "   ('underwater', 0.0046669333),\n",
       "   ('wild', 0.0046590534),\n",
       "   ('turtle', 0.0045313626),\n",
       "   ('tribe', 0.0044832723),\n",
       "   ('winter', 0.0044649458),\n",
       "   ('australian', 0.004439406),\n",
       "   ('civilization', 0.00441267),\n",
       "   ('eat', 0.004323651),\n",
       "   ('mine', 0.0042811995),\n",
       "   ('miner', 0.004204437),\n",
       "   ('ocean', 0.004078099),\n",
       "   ('herd', 0.0039851884),\n",
       "   ('land', 0.003974783),\n",
       "   ('float', 0.003968434),\n",
       "   ('wave', 0.0037972121),\n",
       "   ('sailor', 0.0037956308),\n",
       "   ('navigate', 0.0037382166),\n",
       "   ('townspeople', 0.0036647227),\n",
       "   ('infect', 0.00346093),\n",
       "   ('clutch', 0.003399139),\n",
       "   ('treasure', 0.0033749298),\n",
       "   ('devour', 0.0032459253),\n",
       "   ('explore', 0.003238174),\n",
       "   ('group', 0.003211134),\n",
       "   ('storm', 0.0030912384),\n",
       "   ('dive', 0.0030146453),\n",
       "   ('rope', 0.002957288),\n",
       "   ('hawk', 0.002935999),\n",
       "   ('bottom', 0.002874515),\n",
       "   ('volcano', 0.0028360127),\n",
       "   ('scare', 0.00281864),\n",
       "   ('snake', 0.0028025743),\n",
       "   ('tiger', 0.0027315489),\n",
       "   ('venture', 0.0027307384),\n",
       "   ('mountain', 0.002642305),\n",
       "   ('expedition', 0.0025883554),\n",
       "   ('piece', 0.0024946146),\n",
       "   ('ape', 0.002486233),\n",
       "   ('lose', 0.0024658807),\n",
       "   ('farm', 0.0023967384),\n",
       "   ('resident', 0.0023767415),\n",
       "   ('great', 0.002330666),\n",
       "   ('drown', 0.002322268),\n",
       "   ('princess', 0.002307874),\n",
       "   ('salvage', 0.0022877348),\n",
       "   ('fend', 0.0022726855),\n",
       "   ('food', 0.0021974845),\n",
       "   ('lake', 0.0021540872),\n",
       "   ('ned', 0.0021490226),\n",
       "   ('submerge', 0.0021407169),\n",
       "   ('enslave', 0.0020727257),\n",
       "   ('machete', 0.0020628583),\n",
       "   ('overboard', 0.0020169006),\n",
       "   ('fisherman', 0.0020013107),\n",
       "   ('surf', 0.0019343649),\n",
       "   ('emperor', 0.001911803),\n",
       "   ('kit', 0.001903243)]),\n",
       " (5,\n",
       "  [('driver', 0.050144084),\n",
       "   ('frankie', 0.02794934),\n",
       "   ('tire', 0.016740408),\n",
       "   ('suitcase', 0.014261834),\n",
       "   ('stephanie', 0.011776654),\n",
       "   ('trailer', 0.010316627),\n",
       "   ('overnight', 0.010060597),\n",
       "   ('lance', 0.00871715),\n",
       "   ('cane', 0.004439696),\n",
       "   ('reggie', 0.0037474628),\n",
       "   ('injection', 0.001953781),\n",
       "   ('risky', 0.0016223117),\n",
       "   ('lap', 0.0016036718),\n",
       "   ('stereotype', 0.0013534186),\n",
       "   ('fabulous', 0.0012668581),\n",
       "   ('outrun', 0.0011611271),\n",
       "   ('leonard', 0.0008396365),\n",
       "   ('blare', 0.000770406),\n",
       "   ('jimmys', 0.0006350411),\n",
       "   ('diet', 0.0005805334),\n",
       "   ('clarence', 0.00030389288),\n",
       "   ('bartender', 0.00019901728),\n",
       "   ('uncensored', 2.4197232e-05),\n",
       "   ('quid', 2.4093535e-05),\n",
       "   ('sweet', 2.408571e-05),\n",
       "   ('cherrie', 2.4085222e-05),\n",
       "   ('havokwrestle', 2.4085222e-05),\n",
       "   ('jessicka', 2.4085222e-05),\n",
       "   ('nywc', 2.4085222e-05),\n",
       "   ('sportatorium', 2.4085222e-05),\n",
       "   ('sophie', 2.407604e-05),\n",
       "   ('griffin', 2.4062132e-05),\n",
       "   ('federal', 2.4060451e-05),\n",
       "   ('dynamite', 2.405547e-05),\n",
       "   ('motel', 2.4052712e-05),\n",
       "   ('newcomer', 2.4048304e-05),\n",
       "   ('athletic', 2.404824e-05),\n",
       "   ('sle', 2.4048222e-05),\n",
       "   ('standard', 2.4035868e-05),\n",
       "   ('nino', 2.4035811e-05),\n",
       "   ('cloakroom', 2.4029607e-05),\n",
       "   ('melissas', 2.4029607e-05),\n",
       "   ('mannequin', 2.4028157e-05),\n",
       "   ('binocular', 2.4028062e-05),\n",
       "   ('tricycle', 2.4027915e-05),\n",
       "   ('ramona', 2.4025501e-05),\n",
       "   ('collingwood', 2.4024463e-05),\n",
       "   ('lillian', 2.402272e-05),\n",
       "   ('junction', 2.4021932e-05),\n",
       "   ('ventilator', 2.4021921e-05),\n",
       "   ('rajeev', 2.4021921e-05),\n",
       "   ('encouragement', 2.4016928e-05),\n",
       "   ('expense', 2.4016514e-05),\n",
       "   ('arrangement', 2.4016412e-05),\n",
       "   ('deepen', 2.4015966e-05),\n",
       "   ('suburban', 2.4015888e-05),\n",
       "   ('ucla', 2.4015828e-05),\n",
       "   ('brood', 2.4015813e-05),\n",
       "   ('illegitimate', 2.4015813e-05),\n",
       "   ('jerrys', 2.4015808e-05),\n",
       "   ('josh', 2.4015802e-05),\n",
       "   ('sunday', 2.4015802e-05),\n",
       "   ('barterer', 2.4015802e-05),\n",
       "   ('platonically', 2.4015802e-05),\n",
       "   ('stipulate', 2.4015802e-05),\n",
       "   ('unmentione', 2.4015802e-05),\n",
       "   ('sam', 2.4015802e-05),\n",
       "   ('parking_lot', 2.400663e-05),\n",
       "   ('thereby', 2.4006587e-05),\n",
       "   ('superstar', 2.4005705e-05),\n",
       "   ('brent', 2.4004914e-05),\n",
       "   ('shannon', 2.4004567e-05),\n",
       "   ('irene', 2.4004534e-05),\n",
       "   ('somewhere', 2.400346e-05),\n",
       "   ('nurse', 2.4003399e-05),\n",
       "   ('kyle', 2.4003353e-05),\n",
       "   ('grave', 2.400306e-05),\n",
       "   ('lifeless_body', 2.4002871e-05),\n",
       "   ('bicycle', 2.4001507e-05),\n",
       "   ('janitor', 2.4001458e-05),\n",
       "   ('reincarnate', 2.400133e-05),\n",
       "   ('meat', 2.4001276e-05),\n",
       "   ('reaction', 2.4001047e-05),\n",
       "   ('induce', 2.4000896e-05),\n",
       "   ('feeding', 2.4000838e-05),\n",
       "   ('suraj', 2.4000658e-05),\n",
       "   ('spectator', 2.4000614e-05),\n",
       "   ('fracture', 2.4000594e-05),\n",
       "   ('intensely', 2.4000583e-05),\n",
       "   ('homage', 2.4000577e-05),\n",
       "   ('reserve', 2.4000574e-05),\n",
       "   ('obscure', 2.4000568e-05),\n",
       "   ('narrative', 2.4000567e-05),\n",
       "   ('diegesis', 2.4000563e-05),\n",
       "   ('scorpion', 2.4000563e-05),\n",
       "   ('chad', 2.4000563e-05),\n",
       "   ('rolling', 2.4000563e-05),\n",
       "   ('upright', 2.4000563e-05),\n",
       "   ('vibrate', 2.4000563e-05),\n",
       "   ('psychokinetic', 2.4000563e-05)]),\n",
       " (6,\n",
       "  [('friend', 0.01657588),\n",
       "   ('get', 0.01599625),\n",
       "   ('make', 0.013344735),\n",
       "   ('go', 0.011918047),\n",
       "   ('show', 0.009581636),\n",
       "   ('work', 0.00933063),\n",
       "   ('take', 0.00893307),\n",
       "   ('come', 0.008218722),\n",
       "   ('meet', 0.00813292),\n",
       "   ('tell', 0.00797341),\n",
       "   ('decide', 0.007903189),\n",
       "   ('give', 0.0077879783),\n",
       "   ('become', 0.0076535675),\n",
       "   ('want', 0.007424821),\n",
       "   ('start', 0.0072440673),\n",
       "   ('however', 0.006968587),\n",
       "   ('end', 0.006834472),\n",
       "   ('girl', 0.0065940577),\n",
       "   ('help', 0.006498122),\n",
       "   ('day', 0.006417781),\n",
       "   ('try', 0.0063117105),\n",
       "   ('sister', 0.006253156),\n",
       "   ('good', 0.006250622),\n",
       "   ('together', 0.0061772536),\n",
       "   ('first', 0.0060459096),\n",
       "   ('job', 0.0057648225),\n",
       "   ('school', 0.0057551633),\n",
       "   ('leave', 0.0057483683),\n",
       "   ('time', 0.0055753435),\n",
       "   ('play', 0.0055589965),\n",
       "   ('s', 0.005536157),\n",
       "   ('new', 0.005121212),\n",
       "   ('ask', 0.005106616),\n",
       "   ('also', 0.005009718),\n",
       "   ('later', 0.0049441974),\n",
       "   ('student', 0.0047812755),\n",
       "   ('begin', 0.0046285703),\n",
       "   ('well', 0.0043561077),\n",
       "   ('thing', 0.004277156),\n",
       "   ('night', 0.0041056746),\n",
       "   ('movie', 0.0040442115),\n",
       "   ('fight', 0.0038947377),\n",
       "   ('accept', 0.0038751105),\n",
       "   ('back', 0.003757732),\n",
       "   ('big', 0.00375387),\n",
       "   ('lose', 0.0037528786),\n",
       "   ('see', 0.003739362),\n",
       "   ('would', 0.0036939678),\n",
       "   ('turn', 0.0036867242),\n",
       "   ('much', 0.0036187766),\n",
       "   ('learn', 0.003618463),\n",
       "   ('finally', 0.0035594183),\n",
       "   ('sex', 0.0035032043),\n",
       "   ('agree', 0.00348923),\n",
       "   ('plan', 0.0033852733),\n",
       "   ('offer', 0.0033567748),\n",
       "   ('even', 0.003348409),\n",
       "   ('business', 0.003324099),\n",
       "   ('feel', 0.0032788015),\n",
       "   ('need', 0.0032677422),\n",
       "   ('party', 0.0032451956),\n",
       "   ('say', 0.003181425),\n",
       "   ('win', 0.003159728),\n",
       "   ('date', 0.003135923),\n",
       "   ('call', 0.0031018495),\n",
       "   ('kid', 0.0030839392),\n",
       "   ('soon', 0.0029976482),\n",
       "   ('perform', 0.0029847177),\n",
       "   ('spend', 0.0029602053),\n",
       "   ('eventually', 0.0029090852),\n",
       "   ('move', 0.0028735213),\n",
       "   ('film', 0.0028552809),\n",
       "   ('realize', 0.0028271),\n",
       "   ('pay', 0.0027772395),\n",
       "   ('think', 0.0027447063),\n",
       "   ('name', 0.002739912),\n",
       "   ('dance', 0.0027232878),\n",
       "   ('still', 0.002711798),\n",
       "   ('know', 0.0026806104),\n",
       "   ('invite', 0.0026546484),\n",
       "   ('never', 0.0026509387),\n",
       "   ('music', 0.002639786),\n",
       "   ('keep', 0.0026289367),\n",
       "   ('write', 0.0026001479),\n",
       "   ('bad', 0.0025364086),\n",
       "   ('refuse', 0.0025244614),\n",
       "   ('game', 0.0024859724),\n",
       "   ('meanwhile', 0.002444729),\n",
       "   ('break', 0.002360826),\n",
       "   ('convince', 0.00230748),\n",
       "   ('money', 0.0022840088),\n",
       "   ('local', 0.002278155),\n",
       "   ('year', 0.0022478383),\n",
       "   ('attempt', 0.002247523),\n",
       "   ('due', 0.0022446504),\n",
       "   ('talk', 0.0022418888),\n",
       "   ('company', 0.0022217166),\n",
       "   ('close', 0.002214882),\n",
       "   ('can', 0.0022132243),\n",
       "   ('attend', 0.0021985383)]),\n",
       " (7,\n",
       "  [('horse', 0.058228884),\n",
       "   ('singer', 0.039869044),\n",
       "   ('gold', 0.021380497),\n",
       "   ('unfold', 0.014340984),\n",
       "   ('railroad', 0.011738018),\n",
       "   ('ranch', 0.011162549),\n",
       "   ('irish', 0.011038645),\n",
       "   ('wallet', 0.010838304),\n",
       "   ('terrorize', 0.010265877),\n",
       "   ('rider', 0.009223228),\n",
       "   ('mexican', 0.0087100575),\n",
       "   ('desolate', 0.0068249297),\n",
       "   ('wage', 0.0065905084),\n",
       "   ('union', 0.006192815),\n",
       "   ('treason', 0.0060412535),\n",
       "   ('milk', 0.0052588945),\n",
       "   ('loot', 0.004916429),\n",
       "   ('testing', 0.004754452),\n",
       "   ('ethnic', 0.0038335486),\n",
       "   ('blank', 0.0037082394),\n",
       "   ('liquor', 0.0036998095),\n",
       "   ('knowing', 0.0034330636),\n",
       "   ('buck', 0.0031919612),\n",
       "   ('channel', 0.003155936),\n",
       "   ('mug', 0.0031180452),\n",
       "   ('turkish', 0.0031173036),\n",
       "   ('tavern', 0.0031027854),\n",
       "   ('windshield', 0.0030742092),\n",
       "   ('residential', 0.002926854),\n",
       "   ('neighboring', 0.0029029292),\n",
       "   ('unorthodox', 0.0028707301),\n",
       "   ('punk', 0.002733835),\n",
       "   ('besiege', 0.002577597),\n",
       "   ('arduous', 0.0025757712),\n",
       "   ('bounty', 0.0025644323),\n",
       "   ('ride', 0.0025289035),\n",
       "   ('consecutive', 0.0024181798),\n",
       "   ('beating', 0.0020403087),\n",
       "   ('intolerance', 0.0019781478),\n",
       "   ('sarcastic', 0.0018839119),\n",
       "   ('invoke', 0.0018727018),\n",
       "   ('breaker', 0.0017278992),\n",
       "   ('stamp', 0.0014988971),\n",
       "   ('spar', 0.001442076),\n",
       "   ('cart', 0.0014319376),\n",
       "   ('pete', 0.0014210186),\n",
       "   ('foretell', 0.0013943914),\n",
       "   ('brick', 0.0012457296),\n",
       "   ('approximately', 0.0011725714),\n",
       "   ('bouncer', 0.0011555833),\n",
       "   ('rodeo', 0.0009945483),\n",
       "   ('veterinarian', 0.0009052678),\n",
       "   ('enforcement', 0.00083241926),\n",
       "   ('dropping', 0.00078595604),\n",
       "   ('bluff', 0.00077345845),\n",
       "   ('troy', 0.0007169094),\n",
       "   ('indict', 0.00066194206),\n",
       "   ('rapport', 0.0006037753),\n",
       "   ('lynch', 0.0005467982),\n",
       "   ('shortcut', 0.0005081446),\n",
       "   ('doc', 0.00028518285),\n",
       "   ('entice', 0.00026254187),\n",
       "   ('relinquish', 0.0002540596),\n",
       "   ('lorraine', 0.00020653602),\n",
       "   ('payoff', 0.0002023315),\n",
       "   ('wallace', 0.00016674351),\n",
       "   ('boredom', 0.00012843277),\n",
       "   ('alonzo', 9.595042e-05),\n",
       "   ('champ', 8.071607e-05),\n",
       "   ('grandfather', 1.9424648e-05),\n",
       "   ('bold', 1.9408548e-05),\n",
       "   ('bid', 1.9396502e-05),\n",
       "   ('pennant', 1.9394813e-05),\n",
       "   ('lutie', 1.9370362e-05),\n",
       "   ('community', 1.936544e-05),\n",
       "   ('nicholl', 1.935833e-05),\n",
       "   ('brock', 1.933877e-05),\n",
       "   ('clive', 1.9337418e-05),\n",
       "   ('special', 1.9333196e-05),\n",
       "   ('experiment', 1.9332589e-05),\n",
       "   ('colt', 1.9328916e-05),\n",
       "   ('dushant', 1.9324641e-05),\n",
       "   ('albert', 1.9323385e-05),\n",
       "   ('hercule', 1.932224e-05),\n",
       "   ('emilie', 1.932184e-05),\n",
       "   ('topthorn', 1.932184e-05),\n",
       "   ('turnip', 1.932184e-05),\n",
       "   ('popper', 1.9319288e-05),\n",
       "   ('conviction', 1.9319192e-05),\n",
       "   ('musketeer', 1.9317733e-05),\n",
       "   ('settler', 1.9316121e-05),\n",
       "   ('brown', 1.9315763e-05),\n",
       "   ('pop', 1.9314226e-05),\n",
       "   ('knack', 1.9313778e-05),\n",
       "   ('brag', 1.9313122e-05),\n",
       "   ('announcement', 1.9312705e-05),\n",
       "   ('kingdom', 1.9312636e-05),\n",
       "   ('orphan', 1.9312307e-05),\n",
       "   ('boldoo', 1.9311989e-05),\n",
       "   ('byambaa', 1.9311989e-05)]),\n",
       " (8,\n",
       "  [('base', 0.028144067),\n",
       "   ('life', 0.022285894),\n",
       "   ('time', 0.0182424),\n",
       "   ('film', 0.01668467),\n",
       "   ('story', 0.016232396),\n",
       "   ('world', 0.013528381),\n",
       "   ('become', 0.01330388),\n",
       "   ('book', 0.010001533),\n",
       "   ('event', 0.009985442),\n",
       "   ('people', 0.009931008),\n",
       "   ('must', 0.009892738),\n",
       "   ('year', 0.009572369),\n",
       "   ('begin', 0.009247411),\n",
       "   ('match', 0.009015864),\n",
       "   ('live', 0.008289134),\n",
       "   ('new', 0.00797531),\n",
       "   ('face', 0.0071804593),\n",
       "   ('change', 0.006944689),\n",
       "   ('mysterious', 0.0063612275),\n",
       "   ('dream', 0.006185635),\n",
       "   ('travel', 0.0061092256),\n",
       "   ('great', 0.006006154),\n",
       "   ('death', 0.005960025),\n",
       "   ('novel', 0.005956673),\n",
       "   ('may', 0.0059464187),\n",
       "   ('first', 0.0058883717),\n",
       "   ('city', 0.005830413),\n",
       "   ('follow', 0.0056332364),\n",
       "   ('race', 0.005568344),\n",
       "   ('long', 0.0055637336),\n",
       "   ('lose', 0.0055449447),\n",
       "   ('last', 0.005329432),\n",
       "   ('set', 0.005314711),\n",
       "   ('also', 0.0050389892),\n",
       "   ('future', 0.004912452),\n",
       "   ('experience', 0.004872415),\n",
       "   ('black', 0.004842009),\n",
       "   ('lead', 0.0047025834),\n",
       "   ('real', 0.004557364),\n",
       "   ('history', 0.0044243606),\n",
       "   ('way', 0.0041479524),\n",
       "   ('struggle', 0.0040764445),\n",
       "   ('dark', 0.0040345355),\n",
       "   ('part', 0.0040095816),\n",
       "   ('true', 0.0038910122),\n",
       "   ('many', 0.0038500344),\n",
       "   ('character', 0.0037214756),\n",
       "   ('include', 0.0035550636),\n",
       "   ('young', 0.0035003521),\n",
       "   ('day', 0.0034735743),\n",
       "   ('final', 0.0034130395),\n",
       "   ('memory', 0.0033602878),\n",
       "   ('country', 0.003299707),\n",
       "   ('even', 0.0032630789),\n",
       "   ('personal', 0.0032545512),\n",
       "   ('different', 0.0032272441),\n",
       "   ('fall', 0.003224094),\n",
       "   ('seem', 0.0031307454),\n",
       "   ('present', 0.0030969314),\n",
       "   ('adventure', 0.0030863616),\n",
       "   ('fear', 0.0030646562),\n",
       "   ('title', 0.003004321),\n",
       "   ('challenge', 0.0029985434),\n",
       "   ('place', 0.0029746022),\n",
       "   ('truth', 0.0029616982),\n",
       "   ('society', 0.0029508155),\n",
       "   ('strange', 0.0029492395),\n",
       "   ('know', 0.0028572006),\n",
       "   ('strong', 0.0028299796),\n",
       "   ('tournament', 0.0028295014),\n",
       "   ('fate', 0.0028157018),\n",
       "   ('person', 0.0028053802),\n",
       "   ('encounter', 0.0028039268),\n",
       "   ('reality', 0.0027399487),\n",
       "   ('inspire', 0.0026279846),\n",
       "   ('form', 0.0026016792),\n",
       "   ('path', 0.0025739602),\n",
       "   ('journalist', 0.0025595662),\n",
       "   ('deep', 0.00255662),\n",
       "   ('self', 0.0025322372),\n",
       "   ('decision', 0.0025273352),\n",
       "   ('could', 0.0025208546),\n",
       "   ('ever', 0.0024994551),\n",
       "   ('conflict', 0.002467789),\n",
       "   ('political', 0.0024641452),\n",
       "   ('find', 0.0024114226),\n",
       "   ('mystery', 0.0024042542),\n",
       "   ('question', 0.0024002898),\n",
       "   ('would', 0.002343658),\n",
       "   ('remake', 0.002325884),\n",
       "   ('end', 0.0023222258),\n",
       "   ('suffer', 0.0023148765),\n",
       "   ('heart', 0.002276557),\n",
       "   ('voice', 0.0022511475),\n",
       "   ('small', 0.0022491661),\n",
       "   ('short', 0.0022398045),\n",
       "   ('poor', 0.0022137966),\n",
       "   ('reporter', 0.0021574511),\n",
       "   ('believe', 0.0021440664),\n",
       "   ('forever', 0.0020946944)]),\n",
       " (9,\n",
       "  [('environmental', 0.008569005),\n",
       "   ('discourage', 0.006676042),\n",
       "   ('peak', 0.006336423),\n",
       "   ('homer', 0.0045820912),\n",
       "   ('diverse', 0.004386488),\n",
       "   ('gladiator', 0.0042885314),\n",
       "   ('battlefield', 0.0040384876),\n",
       "   ('hypnotize', 0.003932384),\n",
       "   ('breach', 0.0032444051),\n",
       "   ('pearl', 0.003183539),\n",
       "   ('frontier', 0.0029266921),\n",
       "   ('basic', 0.0022584533),\n",
       "   ('randomly', 0.0021881547),\n",
       "   ('disposal', 0.0019983922),\n",
       "   ('teammate', 0.0019378661),\n",
       "   ('bowling', 0.0018083231),\n",
       "   ('manual', 0.0015224691),\n",
       "   ('burning', 0.0010292205),\n",
       "   ('transporter', 0.00090337644),\n",
       "   ('vivian', 0.0008241963),\n",
       "   ('hollow', 0.000798614),\n",
       "   ('disaster', 2.7009e-05),\n",
       "   ('global_warming', 2.7005584e-05),\n",
       "   ('recession', 2.7005584e-05),\n",
       "   ('serafin', 2.7003702e-05),\n",
       "   ('ultimate', 2.7001504e-05),\n",
       "   ('percy', 2.7000706e-05),\n",
       "   ('pompeii', 2.6991585e-05),\n",
       "   ('blaze', 2.698777e-05),\n",
       "   ('epic', 2.6987447e-05),\n",
       "   ('unwillingly', 2.6987065e-05),\n",
       "   ('cassia', 2.698702e-05),\n",
       "   ('torrent', 2.698702e-05),\n",
       "   ('magnificent', 2.698702e-05),\n",
       "   ('milo', 2.698702e-05),\n",
       "   ('betroth', 2.698702e-05),\n",
       "   ('orm', 2.6982982e-05),\n",
       "   ('aunt', 2.6978063e-05),\n",
       "   ('cosmic', 2.6974834e-05),\n",
       "   ('avenger', 2.697483e-05),\n",
       "   ('ally', 2.6974389e-05),\n",
       "   ('bounty_hunter', 2.6971593e-05),\n",
       "   ('gunman', 2.6971566e-05),\n",
       "   ('scottish', 2.697156e-05),\n",
       "   ('horseback_ride', 2.697156e-05),\n",
       "   ('infatuate', 2.697156e-05),\n",
       "   ('dream_sequence', 2.697156e-05),\n",
       "   ('conquer', 2.696959e-05),\n",
       "   ('derail', 2.6969466e-05),\n",
       "   ('warlord', 2.6969443e-05),\n",
       "   ('manuela', 2.6969237e-05),\n",
       "   ('cassie', 2.6968228e-05),\n",
       "   ('subjugation', 2.696819e-05),\n",
       "   ('alien_invasion', 2.696819e-05),\n",
       "   ('ball', 2.696711e-05),\n",
       "   ('timo', 2.6966714e-05),\n",
       "   ('network', 2.6966669e-05),\n",
       "   ('cedric', 2.6966347e-05),\n",
       "   ('dc_comic', 2.6966307e-05),\n",
       "   ('atlantis', 2.6966261e-05),\n",
       "   ('oceanic', 2.6966261e-05),\n",
       "   ('atlantean', 2.6966261e-05),\n",
       "   ('dc_extende', 2.6966261e-05),\n",
       "   ('lewt', 2.6965494e-05),\n",
       "   ('virtually', 2.6964964e-05),\n",
       "   ('softly', 2.6964919e-05),\n",
       "   ('uncle', 2.6963786e-05),\n",
       "   ('ludwig', 2.6963555e-05),\n",
       "   ('community', 2.6962702e-05),\n",
       "   ('micky', 2.69625e-05),\n",
       "   ('agne', 2.6962269e-05),\n",
       "   ('handle', 2.6962234e-05),\n",
       "   ('infinity', 2.696221e-05),\n",
       "   ('intergalactic', 2.696221e-05),\n",
       "   ('unimaginable', 2.6962196e-05),\n",
       "   ('uncertain', 2.6962187e-05),\n",
       "   ('universe', 2.6962187e-05),\n",
       "   ('valerie', 2.6961476e-05),\n",
       "   ('necessity', 2.6961237e-05),\n",
       "   ('drama', 2.6960703e-05),\n",
       "   ('mitch', 2.6960415e-05),\n",
       "   ('arnold', 2.6960359e-05),\n",
       "   ('woman_director', 2.6960179e-05),\n",
       "   ('quirky', 2.6960179e-05),\n",
       "   ('carlito', 2.6960144e-05),\n",
       "   ('cattle', 2.6959768e-05),\n",
       "   ('fiery', 2.6959506e-05),\n",
       "   ('principal', 2.6959413e-05),\n",
       "   ('convoy', 2.6959377e-05),\n",
       "   ('spark', 2.6959293e-05),\n",
       "   ('henkel', 2.6959257e-05),\n",
       "   ('jeffrie', 2.6959156e-05),\n",
       "   ('ted', 2.6959147e-05),\n",
       "   ('palm', 2.6959058e-05),\n",
       "   ('stadium', 2.6958918e-05),\n",
       "   ('mechanical', 2.695888e-05),\n",
       "   ('mall', 2.6958856e-05),\n",
       "   ('marshal', 2.695884e-05),\n",
       "   ('craze', 2.6958724e-05),\n",
       "   ('exception', 2.6958702e-05)]),\n",
       " (10,\n",
       "  [('kill', 0.017594105),\n",
       "   ('use', 0.013249645),\n",
       "   ('team', 0.012048177),\n",
       "   ('force', 0.012030523),\n",
       "   ('fight', 0.011033257),\n",
       "   ('save', 0.010627108),\n",
       "   ('escape', 0.010471622),\n",
       "   ('attack', 0.010267236),\n",
       "   ('group', 0.010090515),\n",
       "   ('order', 0.008695138),\n",
       "   ('take', 0.007787743),\n",
       "   ('rescue', 0.0075436756),\n",
       "   ('lead', 0.0075310613),\n",
       "   ('power', 0.0072659682),\n",
       "   ('destroy', 0.0071024094),\n",
       "   ('battle', 0.006568146),\n",
       "   ('capture', 0.006186314),\n",
       "   ('mission', 0.0059617166),\n",
       "   ('human', 0.005784893),\n",
       "   ('discover', 0.0057621114),\n",
       "   ('war', 0.005607986),\n",
       "   ('survive', 0.0055348286),\n",
       "   ('attempt', 0.005516673),\n",
       "   ('return', 0.005505448),\n",
       "   ('vampire', 0.005431455),\n",
       "   ('soldier', 0.0051195817),\n",
       "   ('man', 0.0051076408),\n",
       "   ('send', 0.005098983),\n",
       "   ('reveal', 0.0049946266),\n",
       "   ('help', 0.004919643),\n",
       "   ('secret', 0.004912279),\n",
       "   ('however', 0.0046625542),\n",
       "   ('plan', 0.004530016),\n",
       "   ('government', 0.0042291703),\n",
       "   ('terrorist', 0.004191253),\n",
       "   ('hero', 0.0041720686),\n",
       "   ('fly', 0.004134809),\n",
       "   ('learn', 0.004112721),\n",
       "   ('leader', 0.004094099),\n",
       "   ('allow', 0.00394732),\n",
       "   ('manage', 0.0039452133),\n",
       "   ('free', 0.0039423835),\n",
       "   ('military', 0.0038156777),\n",
       "   ('cause', 0.003803609),\n",
       "   ('trap', 0.0037393477),\n",
       "   ('protect', 0.0036309846),\n",
       "   ('find', 0.0036041194),\n",
       "   ('crash', 0.00345444),\n",
       "   ('bomb', 0.0034166935),\n",
       "   ('join', 0.0033811508),\n",
       "   ('evil', 0.0033733177),\n",
       "   ('control', 0.0033570537),\n",
       "   ('comic', 0.0033487661),\n",
       "   ('plane', 0.0032700591),\n",
       "   ('land', 0.0031393357),\n",
       "   ('remain', 0.00308232),\n",
       "   ('spy', 0.0030633232),\n",
       "   ('warrior', 0.0030602976),\n",
       "   ('create', 0.003060154),\n",
       "   ('enemy', 0.0030514323),\n",
       "   ('defeat', 0.0030233422),\n",
       "   ('member', 0.0029943576),\n",
       "   ('stop', 0.0029848686),\n",
       "   ('arrive', 0.0028622213),\n",
       "   ('make', 0.0028359494),\n",
       "   ('turn', 0.0028224455),\n",
       "   ('city', 0.0028203987),\n",
       "   ('fall', 0.0028179185),\n",
       "   ('meanwhile', 0.00279916),\n",
       "   ('weapon', 0.0027351489),\n",
       "   ('fire', 0.0027026967),\n",
       "   ('powerful', 0.0026978238),\n",
       "   ('bring', 0.0026781224),\n",
       "   ('die', 0.002662669),\n",
       "   ('scientist', 0.0025669998),\n",
       "   ('able', 0.0025606407),\n",
       "   ('train', 0.0025138254),\n",
       "   ('include', 0.0024967007),\n",
       "   ('threat', 0.0024789032),\n",
       "   ('seek', 0.0024404477),\n",
       "   ('set', 0.0024343096),\n",
       "   ('base', 0.002428192),\n",
       "   ('reach', 0.002424312),\n",
       "   ('agent', 0.0022943125),\n",
       "   ('other', 0.0022609972),\n",
       "   ('build', 0.0022378082),\n",
       "   ('robot', 0.0021625375),\n",
       "   ('machine', 0.002141095),\n",
       "   ('deadly', 0.0021210506),\n",
       "   ('system', 0.0021087457),\n",
       "   ('must', 0.0020910124),\n",
       "   ('give', 0.00204447),\n",
       "   ('explosion', 0.0020367512),\n",
       "   ('pilot', 0.0020307482),\n",
       "   ('mutant', 0.002017018),\n",
       "   ('release', 0.0020111771),\n",
       "   ('several', 0.0019814523),\n",
       "   ('dangerous', 0.0019609537),\n",
       "   ('fail', 0.0019604405),\n",
       "   ('sacrifice', 0.0019548985)]),\n",
       " (11,\n",
       "  [('crew', 0.06407831),\n",
       "   ('earth', 0.05875205),\n",
       "   ('ship', 0.055435512),\n",
       "   ('alien', 0.053227812),\n",
       "   ('space', 0.03628676),\n",
       "   ('planet', 0.027400764),\n",
       "   ('spacecraft', 0.016056186),\n",
       "   ('submarine', 0.014784161),\n",
       "   ('martian', 0.009499371),\n",
       "   ('phenomenon', 0.0070434664),\n",
       "   ('tess', 0.0069586663),\n",
       "   ('amazing', 0.006229034),\n",
       "   ('infection', 0.0058761593),\n",
       "   ('chip', 0.0053951954),\n",
       "   ('spaceship', 0.0051898025),\n",
       "   ('vessel', 0.005058794),\n",
       "   ('astronaut', 0.0045751506),\n",
       "   ('orbit', 0.00426109),\n",
       "   ('whale', 0.0040949374),\n",
       "   ('craft', 0.003183824),\n",
       "   ('jam', 0.0030967835),\n",
       "   ('station', 0.0030754704),\n",
       "   ('hole', 0.0030106448),\n",
       "   ('cannon', 0.0028604635),\n",
       "   ('captain', 0.0024921214),\n",
       "   ('grocery', 0.0024444421),\n",
       "   ('creature', 0.0023525988),\n",
       "   ('worldwide', 0.0020274918),\n",
       "   ('probe', 0.002025798),\n",
       "   ('maneuver', 0.0019894503),\n",
       "   ('cruise', 0.0019233624),\n",
       "   ('marion', 0.0018681379),\n",
       "   ('ocean', 0.0017847832),\n",
       "   ('scientist', 0.0016057882),\n",
       "   ('pod', 0.0015603595),\n",
       "   ('voyage', 0.0014410437),\n",
       "   ('infected', 0.001432886),\n",
       "   ('anchor', 0.0012472606),\n",
       "   ('aircraft', 0.0011757559),\n",
       "   ('sink', 0.0011533343),\n",
       "   ('shuttle', 0.0009943048),\n",
       "   ('chimp', 0.0009787803),\n",
       "   ('quarantine', 0.00093637366),\n",
       "   ('repair', 0.0008857416),\n",
       "   ('science', 0.00070204283),\n",
       "   ('starship', 0.00065526366),\n",
       "   ('starvation', 0.00063443603),\n",
       "   ('deck', 0.00057217287),\n",
       "   ('malfunction', 0.00054895907),\n",
       "   ('torpedo', 7.51719e-05),\n",
       "   ('gribble', 1.6368263e-05),\n",
       "   ('structure', 1.6301141e-05),\n",
       "   ('liquid', 1.6273127e-05),\n",
       "   ('interstellar', 1.6268617e-05),\n",
       "   ('hercule', 1.6265976e-05),\n",
       "   ('universe', 1.6261558e-05),\n",
       "   ('conquer', 1.6253209e-05),\n",
       "   ('meteor', 1.624453e-05),\n",
       "   ('carly', 1.6241098e-05),\n",
       "   ('dinosaur', 1.623853e-05),\n",
       "   ('alice', 1.6238144e-05),\n",
       "   ('mom', 1.6237353e-05),\n",
       "   ('milo', 1.623548e-05),\n",
       "   ('mothership', 1.623482e-05),\n",
       "   ('autobot', 1.6234007e-05),\n",
       "   ('decepticon', 1.622967e-05),\n",
       "   ('superhero', 1.622953e-05),\n",
       "   ('explorer', 1.6226473e-05),\n",
       "   ('exorcism', 1.622645e-05),\n",
       "   ('lot', 1.6226282e-05),\n",
       "   ('pillar', 1.6225677e-05),\n",
       "   ('brain', 1.6224263e-05),\n",
       "   ('collision', 1.6222879e-05),\n",
       "   ('rhoda', 1.6222288e-05),\n",
       "   ('intergalactic', 1.6222031e-05),\n",
       "   ('ella', 1.6221096e-05),\n",
       "   ('naval', 1.6217467e-05),\n",
       "   ('unlikely', 1.621736e-05),\n",
       "   ('soviet', 1.6216993e-05),\n",
       "   ('damn', 1.621695e-05),\n",
       "   ('sean', 1.6216622e-05),\n",
       "   ('disaster', 1.621478e-05),\n",
       "   ('surpass', 1.6214464e-05),\n",
       "   ('farmhouse', 1.6214086e-05),\n",
       "   ('worm', 1.6213966e-05),\n",
       "   ('cylinder', 1.6213731e-05),\n",
       "   ('subdue', 1.621372e-05),\n",
       "   ('prometheus', 1.6213493e-05),\n",
       "   ('wormhole', 1.6213422e-05),\n",
       "   ('chronicle', 1.6213173e-05),\n",
       "   ('limitation', 1.6213107e-05),\n",
       "   ('famine', 1.6213104e-05),\n",
       "   ('vika', 1.6212136e-05),\n",
       "   ('conspiracy', 1.6211892e-05),\n",
       "   ('heroism', 1.6211743e-05),\n",
       "   ('experiment', 1.6211494e-05),\n",
       "   ('samantha', 1.6210335e-05),\n",
       "   ('gigantic', 1.6209246e-05),\n",
       "   ('painting', 1.620822e-05),\n",
       "   ('colorful', 1.6207836e-05)]),\n",
       " (12,\n",
       "  [('family', 0.0471987),\n",
       "   ('love', 0.037474576),\n",
       "   ('mother', 0.027668152),\n",
       "   ('woman', 0.027471758),\n",
       "   ('young', 0.02672751),\n",
       "   ('child', 0.026168283),\n",
       "   ('relationship', 0.02526997),\n",
       "   ('son', 0.022119805),\n",
       "   ('live', 0.019990232),\n",
       "   ('wife', 0.018873598),\n",
       "   ('daughter', 0.018486232),\n",
       "   ('father', 0.0176634),\n",
       "   ('brother', 0.01532075),\n",
       "   ('life', 0.0144394655),\n",
       "   ('old', 0.01373245),\n",
       "   ('boy', 0.012966049),\n",
       "   ('man', 0.012942233),\n",
       "   ('parent', 0.012588455),\n",
       "   ('home', 0.01163523),\n",
       "   ('marry', 0.010835558),\n",
       "   ('wedding', 0.010439124),\n",
       "   ('marriage', 0.009587163),\n",
       "   ('husband', 0.009535211),\n",
       "   ('year', 0.008869021),\n",
       "   ('couple', 0.008215883),\n",
       "   ('fall', 0.006831489),\n",
       "   ('return', 0.0061573717),\n",
       "   ('age', 0.006156559),\n",
       "   ('baby', 0.005923915),\n",
       "   ('become', 0.005754949),\n",
       "   ('pregnant', 0.0053862296),\n",
       "   ('grow', 0.005168422),\n",
       "   ('together', 0.0048991633),\n",
       "   ('visit', 0.004667133),\n",
       "   ('friendship', 0.0046553896),\n",
       "   ('village', 0.0044775154),\n",
       "   ('secret', 0.0044090077),\n",
       "   ('bear', 0.00438783),\n",
       "   ('discover', 0.004185121),\n",
       "   ('come', 0.004157319),\n",
       "   ('story', 0.0041149566),\n",
       "   ('beautiful', 0.0040957276),\n",
       "   ('teenage', 0.0040533445),\n",
       "   ('sexual', 0.0039599477),\n",
       "   ('little', 0.0038317458),\n",
       "   ('affair', 0.0037864083),\n",
       "   ('law', 0.0037657723),\n",
       "   ('die', 0.0036342153),\n",
       "   ('learn', 0.0035568164),\n",
       "   ('girl', 0.0034123098),\n",
       "   ('cancer', 0.0033932521),\n",
       "   ('romance', 0.003202734),\n",
       "   ('struggle', 0.0031125133),\n",
       "   ('care', 0.0030512135),\n",
       "   ('divorce', 0.0030285064),\n",
       "   ('single', 0.0029898281),\n",
       "   ('childhood', 0.0029589494),\n",
       "   ('adopt', 0.0029260241),\n",
       "   ('rich', 0.0027949004),\n",
       "   ('raise', 0.0027079713),\n",
       "   ('sex', 0.0026191722),\n",
       "   ('comedy', 0.0025858332),\n",
       "   ('soon', 0.0025671998),\n",
       "   ('name', 0.0025528339),\n",
       "   ('move', 0.0025341187),\n",
       "   ('bill', 0.0025266786),\n",
       "   ('seek', 0.0023853448),\n",
       "   ('bring', 0.0023687237),\n",
       "   ('doctor', 0.0023445638),\n",
       "   ('wealthy', 0.0022827617),\n",
       "   ('never', 0.0022798881),\n",
       "   ('modern', 0.0022766776),\n",
       "   ('farm', 0.0022744373),\n",
       "   ('suicide', 0.0022623846),\n",
       "   ('vacation', 0.00220619),\n",
       "   ('embark', 0.0021667967),\n",
       "   ('stay', 0.0021641592),\n",
       "   ('reunite', 0.0021432415),\n",
       "   ('medical', 0.0021337639),\n",
       "   ('true', 0.0020937042),\n",
       "   ('mark', 0.0020846303),\n",
       "   ('abuse', 0.0020737988),\n",
       "   ('lie', 0.0020382295),\n",
       "   ('lover', 0.0020307605),\n",
       "   ('neighbor', 0.0019938361),\n",
       "   ('separate', 0.0019679077),\n",
       "   ('youth', 0.0019456847),\n",
       "   ('year_old', 0.0019001543),\n",
       "   ('meet', 0.0018990057),\n",
       "   ('spirit', 0.0018529934),\n",
       "   ('romantic', 0.001824699),\n",
       "   ('small', 0.001808956),\n",
       "   ('pain', 0.0017988997),\n",
       "   ('trouble', 0.0017669427),\n",
       "   ('grandmother', 0.0017647839),\n",
       "   ('pregnancy', 0.0017367081),\n",
       "   ('gift', 0.0016919147),\n",
       "   ('loss', 0.0016759309),\n",
       "   ('one', 0.0016695552),\n",
       "   ('house', 0.0016588934)]),\n",
       " (13,\n",
       "  [('prison', 0.09017999),\n",
       "   ('german', 0.027652707),\n",
       "   ('corruption', 0.023183156),\n",
       "   ('trial', 0.021282656),\n",
       "   ('lawyer', 0.020338662),\n",
       "   ('sentence', 0.018136686),\n",
       "   ('court', 0.018054338),\n",
       "   ('prisoner', 0.0149430195),\n",
       "   ('firm', 0.014854683),\n",
       "   ('religious', 0.014668492),\n",
       "   ('japanese', 0.013783788),\n",
       "   ('activist', 0.0113885775),\n",
       "   ('convict', 0.009258154),\n",
       "   ('outlaw', 0.008837264),\n",
       "   ('judge', 0.008190804),\n",
       "   ('execution', 0.007639095),\n",
       "   ('release', 0.007152931),\n",
       "   ('supermarket', 0.0065800324),\n",
       "   ('racism', 0.006534587),\n",
       "   ('colonel', 0.0061604762),\n",
       "   ('case', 0.005843532),\n",
       "   ('aircraft', 0.0058367327),\n",
       "   ('down', 0.0055181696),\n",
       "   ('danny', 0.005342063),\n",
       "   ('nazi', 0.0053344243),\n",
       "   ('korean', 0.00481025),\n",
       "   ('accuse', 0.004531313),\n",
       "   ('french', 0.0043513477),\n",
       "   ('settlement', 0.004247073),\n",
       "   ('supporter', 0.0040301583),\n",
       "   ('hatred', 0.0039982796),\n",
       "   ('catastrophe', 0.0037815133),\n",
       "   ('inmate', 0.0036089472),\n",
       "   ('transition', 0.0035566539),\n",
       "   ('brutality', 0.0035528734),\n",
       "   ('canadian', 0.0035355424),\n",
       "   ('forcibly', 0.0034311127),\n",
       "   ('discredit', 0.0034146996),\n",
       "   ('hunger', 0.003369924),\n",
       "   ('territory', 0.0033357325),\n",
       "   ('protective', 0.0032399546),\n",
       "   ('lord', 0.0031503758),\n",
       "   ('attorney', 0.0031344965),\n",
       "   ('guilty', 0.003056421),\n",
       "   ('intentionally', 0.0030348378),\n",
       "   ('drug_abuse', 0.0029865687),\n",
       "   ('testify', 0.0029188488),\n",
       "   ('manny', 0.0029108892),\n",
       "   ('envelope', 0.002896758),\n",
       "   ('catapult', 0.00286103),\n",
       "   ('charge', 0.0028008788),\n",
       "   ('rape', 0.0027883023),\n",
       "   ('parole', 0.002722689),\n",
       "   ('fury', 0.0026496388),\n",
       "   ('cell', 0.0026231764),\n",
       "   ('donor', 0.0025733623),\n",
       "   ('niece', 0.002564466),\n",
       "   ('guard', 0.0025545831),\n",
       "   ('implicate', 0.0025410005),\n",
       "   ('unnamed', 0.0025244975),\n",
       "   ('jail', 0.0025167458),\n",
       "   ('discreetly', 0.002508329),\n",
       "   ('derek', 0.0023556328),\n",
       "   ('law', 0.0023131676),\n",
       "   ('merchant', 0.002270125),\n",
       "   ('disillusioned', 0.0022583837),\n",
       "   ('repel', 0.0022173766),\n",
       "   ('punishment', 0.0021724536),\n",
       "   ('courtroom', 0.0021691378),\n",
       "   ('ferry', 0.002132219),\n",
       "   ('appeal', 0.0020498757),\n",
       "   ('jewish', 0.0020136607),\n",
       "   ('interrogation', 0.0019952327),\n",
       "   ('jury', 0.0019738511),\n",
       "   ('captivity', 0.0019266979),\n",
       "   ('legal', 0.0018724177),\n",
       "   ('bribe', 0.0018574658),\n",
       "   ('impending', 0.0018385145),\n",
       "   ('loudspeaker', 0.0018048439),\n",
       "   ('atrocity', 0.0018026779),\n",
       "   ('execute', 0.0017629707),\n",
       "   ('african', 0.0017421594),\n",
       "   ('occasional', 0.0017336837),\n",
       "   ('catholic', 0.0017015117),\n",
       "   ('plight', 0.0016684855),\n",
       "   ('narcotic', 0.0016589762),\n",
       "   ('testimony', 0.0015812581),\n",
       "   ('dealing', 0.001566052),\n",
       "   ('high_ranke', 0.0015454197),\n",
       "   ('saying', 0.0014947455),\n",
       "   ('warden', 0.0014812283),\n",
       "   ('captain', 0.001459377),\n",
       "   ('pardon', 0.001447607),\n",
       "   ('regime', 0.0014377891),\n",
       "   ('coverage', 0.0013221588),\n",
       "   ('serve', 0.001309635),\n",
       "   ('firearm', 0.001237298),\n",
       "   ('fuck', 0.0012372853),\n",
       "   ('evidence', 0.001220841),\n",
       "   ('defense', 0.0011788097)]),\n",
       " (14,\n",
       "  [('ghost', 0.039632753),\n",
       "   ('magic', 0.031131025),\n",
       "   ('curse', 0.030997865),\n",
       "   ('evil', 0.027310552),\n",
       "   ('demon', 0.025122344),\n",
       "   ('possess', 0.022739662),\n",
       "   ('witch', 0.0208684),\n",
       "   ('king', 0.018361399),\n",
       "   ('priest', 0.01727422),\n",
       "   ('ritual', 0.014722639),\n",
       "   ('violet', 0.012317419),\n",
       "   ('spell', 0.011719534),\n",
       "   ('throne', 0.010082734),\n",
       "   ('invisible', 0.009436403),\n",
       "   ('wizard', 0.007815969),\n",
       "   ('soul', 0.0076286006),\n",
       "   ('ancient', 0.007234593),\n",
       "   ('knight', 0.0070458474),\n",
       "   ('entity', 0.006950669),\n",
       "   ('salt', 0.006825693),\n",
       "   ('outnumber', 0.006381684),\n",
       "   ('dust', 0.006335077),\n",
       "   ('sword', 0.0056231255),\n",
       "   ('haunt', 0.005482021),\n",
       "   ('crown', 0.0053764777),\n",
       "   ('barne', 0.005247622),\n",
       "   ('realm', 0.005106181),\n",
       "   ('necklace', 0.0048622293),\n",
       "   ('possession', 0.004545998),\n",
       "   ('grandparent', 0.0044985847),\n",
       "   ('humble', 0.004475877),\n",
       "   ('gene', 0.004397139),\n",
       "   ('similarly', 0.004256632),\n",
       "   ('dwarf', 0.0042150654),\n",
       "   ('disastrous', 0.0041980217),\n",
       "   ('interrupted', 0.0041396646),\n",
       "   ('mirror', 0.004108282),\n",
       "   ('healing', 0.0038676052),\n",
       "   ('slay', 0.003820997),\n",
       "   ('heir', 0.0038013186),\n",
       "   ('overly', 0.003739614),\n",
       "   ('coin', 0.0035424822),\n",
       "   ('transform', 0.0034991936),\n",
       "   ('exhibit', 0.0034973281),\n",
       "   ('troll', 0.0028256944),\n",
       "   ('bubble', 0.002779416),\n",
       "   ('trance', 0.0026691402),\n",
       "   ('ghostly', 0.0025813498),\n",
       "   ('royalty', 0.0025125581),\n",
       "   ('considerable', 0.0021378428),\n",
       "   ('ruler', 0.002134438),\n",
       "   ('willy', 0.002029577),\n",
       "   ('statue', 0.0020245945),\n",
       "   ('trick', 0.0019738968),\n",
       "   ('spurn', 0.0019425137),\n",
       "   ('vanquish', 0.001933936),\n",
       "   ('ignorant', 0.0019060246),\n",
       "   ('mortally_wounde', 0.0019022735),\n",
       "   ('candy', 0.0018283993),\n",
       "   ('stone', 0.0018216406),\n",
       "   ('elve', 0.0017777174),\n",
       "   ('council', 0.0017532712),\n",
       "   ('notably', 0.0016418882),\n",
       "   ('palace', 0.0015759643),\n",
       "   ('manufacturer', 0.0015506566),\n",
       "   ('rumble', 0.0014928634),\n",
       "   ('ledge', 0.0014906834),\n",
       "   ('glory', 0.0013939075),\n",
       "   ('chocolate', 0.0013932058),\n",
       "   ('cotton', 0.001149092),\n",
       "   ('hick', 0.0010496477),\n",
       "   ('sorcery', 0.000951474),\n",
       "   ('oppress', 0.00092022),\n",
       "   ('century', 0.00088155613),\n",
       "   ('enchant', 0.00084414956),\n",
       "   ('potion', 0.00080042245),\n",
       "   ('talking', 0.00079896743),\n",
       "   ('delusional', 0.000771582),\n",
       "   ('giving', 0.0007568592),\n",
       "   ('wooden', 0.0007501743),\n",
       "   ('bucket', 0.00070236635),\n",
       "   ('stomp', 0.00063635374),\n",
       "   ('stern', 0.00063523336),\n",
       "   ('brick', 0.000604527),\n",
       "   ('pure', 0.00060178776),\n",
       "   ('summon', 0.0006016575),\n",
       "   ('ear', 0.0005750045),\n",
       "   ('paperwork', 0.0005703278),\n",
       "   ('ploy', 0.00043070974),\n",
       "   ('servant', 0.0003691797),\n",
       "   ('stagger', 0.00035030904),\n",
       "   ('merry', 0.000113416856),\n",
       "   ('radiator', 0.000100300764),\n",
       "   ('supernatural', 1.4501941e-05),\n",
       "   ('excalibur', 1.43346e-05),\n",
       "   ('mythical', 1.4306569e-05),\n",
       "   ('magical', 1.4305321e-05),\n",
       "   ('exorcism', 1.4301937e-05),\n",
       "   ('legendary', 1.4293059e-05),\n",
       "   ('castle', 1.4289694e-05)])]"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lda_topics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "topics_json = [{'topic':topic[0], 'info':[{'word': w[0], 'score': w[1]} for w in topic[1] if w[1]>0.01]} for topic in lda_topics]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open('topics_json.json', 'w') as f:\n",
    "    json.dump(str(topics_json), f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "topic_words = {str(topic[0]): ','.join([w[0] for w in topic[1] if w[1]>0.01]) for topic in lda_topics}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'0': 'patient,rise,rabbit,toy,basement,violently,noise,trauma,tattoo',\n",
       " '1': 'police,murder,kill,money,steal,car,drug,officer,arrest,crime,man,shoot',\n",
       " '2': 'emily,murderer,victor,holly,fre,fred,belt,paul',\n",
       " '3': 'find,tell,go,leave,take,see,try,come,run,man,back',\n",
       " '4': 'animal,water,monster,dog,creature,giant,boat,cave,billy,island,village,forest,river,wood,rock',\n",
       " '5': 'driver,frankie,tire,suitcase,stephanie,trailer,overnight',\n",
       " '6': 'friend,get,make,go',\n",
       " '7': 'horse,singer,gold,unfold,railroad,ranch,irish,wallet,terrorize',\n",
       " '8': 'base,life,time,film,story,world,become,book',\n",
       " '9': '',\n",
       " '10': 'kill,use,team,force,fight,save,escape,attack,group',\n",
       " '11': 'crew,earth,ship,alien,space,planet,spacecraft,submarine',\n",
       " '12': 'family,love,mother,woman,young,child,relationship,son,live,wife,daughter,father,brother,life,old,boy,man,parent,home,marry,wedding',\n",
       " '13': 'prison,german,corruption,trial,lawyer,sentence,court,prisoner,firm,religious,japanese,activist',\n",
       " '14': 'ghost,magic,curse,evil,demon,possess,witch,king,priest,ritual,violet,spell,throne'}"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "topic_words"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "topics_num = 15\n",
    "topic_columns = {f'topic_{i}':[] for i in range(topics_num)}\n",
    "topic_columns['topic_dominant'] = []\n",
    "topic_columns['topic_words'] = []\n",
    "\n",
    "for i, row in enumerate(doc_lda):\n",
    "    sorted_topics = sorted(row[0], key=lambda x: x[1], reverse=True)\n",
    "    dominant = sorted_topics[0][0]\n",
    "    topic_columns['topic_dominant'].append(dominant)\n",
    "    topic_columns['topic_words'].append(topic_words[str(dominant)])\n",
    "    row_dict = {str(topic[0]): topic[1] for topic in sorted_topics}\n",
    "    for t_index in range(topics_num):\n",
    "        topic_columns[f'topic_{t_index}'].append(row_dict.get(str(t_index), 0))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "added_topics = merged_plot.copy()\n",
    "for col in topic_columns:\n",
    "    added_topics[col] = topic_columns[col]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [],
   "source": [
    "added_topics['META__original_title'] = added_topics['PROCESS__original_title']\n",
    "added_topics['META__title'] = added_topics['PROCESS__title']\n",
    "added_topics['META__keywords'] = added_topics['keywords']\n",
    "added_topics['META__plot'] = added_topics['plot']\n",
    "added_topics['META__topic_dominant'] = added_topics['topic_dominant']\n",
    "added_topics['META__topic_words'] = added_topics['topic_words']\n",
    "\n",
    "\n",
    "added_topics = added_topics.drop(['PROCESS__original_title', 'PROCESS__overview', 'PROCESS__title', \n",
    "                                  'keywords', 'plot', 'topic_dominant', 'topic_words'], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['budget',\n",
       " 'META__id',\n",
       " 'PROCESS__original_language',\n",
       " 'revenue',\n",
       " 'runtime',\n",
       " 'spoken_languages',\n",
       " 'META__year',\n",
       " 'META__month',\n",
       " 'META__day',\n",
       " 'weekend',\n",
       " 'META__collection_name',\n",
       " 'META__cast_1_name',\n",
       " 'META__cast_2_name',\n",
       " 'META__cast_3_name',\n",
       " 'META__cast_4_name',\n",
       " 'META__cast_5_name',\n",
       " 'META__cast_6_name',\n",
       " 'META__cast_7_name',\n",
       " 'META__cast_8_name',\n",
       " 'META__crew__sound__music_editor',\n",
       " 'META__crew__sound__original_music_composer',\n",
       " 'META__crew__sound__sound_designer',\n",
       " 'META__crew__sound__sound_effects_editor',\n",
       " 'META__crew__sound__sound_re_recording_mixer',\n",
       " 'META__crew__sound__supervising_sound_editor',\n",
       " 'META__crew__directing__director__1',\n",
       " 'META__crew__directing__script_supervisor',\n",
       " 'META__crew__production__casting',\n",
       " 'META__crew__production__executive_producer__1',\n",
       " 'META__crew__production__producer__1',\n",
       " 'META__crew__production__producer__2',\n",
       " 'META__crew__editing__editor__1',\n",
       " 'META__crew__costume__costume_designer',\n",
       " 'META__crew__costume__costume_supervisor',\n",
       " 'META__crew__costume__makeup_artist',\n",
       " 'META__crew__crew__stunt_coordinator',\n",
       " 'META__crew__writing__screenplay__1',\n",
       " 'META__crew__art__art_direction',\n",
       " 'META__crew__art__production_design',\n",
       " 'META__crew__art__property_master',\n",
       " 'META__crew__art__set_decoration',\n",
       " 'META__crew__visualeffects__visual_effects_supervisor',\n",
       " 'META__crew__camera__director_of_photography',\n",
       " 'META__crew__camera__steadicam_operator',\n",
       " 'META__crew__camera__still_photographer',\n",
       " 'genre__war',\n",
       " 'genre__western',\n",
       " 'genre__mystery',\n",
       " 'genre__music',\n",
       " 'genre__crime',\n",
       " 'genre__romance',\n",
       " 'genre__action',\n",
       " 'genre__adventure',\n",
       " 'genre__thriller',\n",
       " 'genre__animation',\n",
       " 'genre__family',\n",
       " 'genre__drama',\n",
       " 'genre__comedy',\n",
       " 'genre__documentary',\n",
       " 'genre__history',\n",
       " 'genre__fantasy',\n",
       " 'genre__horror',\n",
       " 'META__production_company_1',\n",
       " 'META__production_company_2',\n",
       " 'META__production_company_3',\n",
       " 'country__rs',\n",
       " 'country__su',\n",
       " 'country__do',\n",
       " 'country__bo',\n",
       " 'country__ph',\n",
       " 'country__pe',\n",
       " 'country__id',\n",
       " 'country__gr',\n",
       " 'country__hn',\n",
       " 'country__nl',\n",
       " 'country__ee',\n",
       " 'country__ug',\n",
       " 'country__uy',\n",
       " 'country__ir',\n",
       " 'country__lb',\n",
       " 'country__pk',\n",
       " 'country__ua',\n",
       " 'country__eg',\n",
       " 'country__is',\n",
       " 'country__co',\n",
       " 'country__sk',\n",
       " 'country__bw',\n",
       " 'country__es',\n",
       " 'country__se',\n",
       " 'country__jp',\n",
       " 'country__np',\n",
       " 'country__tw',\n",
       " 'country__ie',\n",
       " 'country__lu',\n",
       " 'country__us',\n",
       " 'country__vn',\n",
       " 'country__ro',\n",
       " 'country__mn',\n",
       " 'country__cl',\n",
       " 'country__hu',\n",
       " 'country__br',\n",
       " 'country__ae',\n",
       " 'country__kr',\n",
       " 'country__be',\n",
       " 'country__ca',\n",
       " 'country__sg',\n",
       " 'country__bg',\n",
       " 'country__de',\n",
       " 'country__pl',\n",
       " 'country__mv',\n",
       " 'country__cn',\n",
       " 'country__in',\n",
       " 'country__th',\n",
       " 'country__fr',\n",
       " 'country__ru',\n",
       " 'country__dk',\n",
       " 'country__af',\n",
       " 'country__xg',\n",
       " 'country__it',\n",
       " 'country__ge',\n",
       " 'country__tr',\n",
       " 'country__za',\n",
       " 'country__ve',\n",
       " 'country__lk',\n",
       " 'country__hr',\n",
       " 'country__ng',\n",
       " 'country__ar',\n",
       " 'country__ba',\n",
       " 'country__il',\n",
       " 'country__mx',\n",
       " 'country__bd',\n",
       " 'country__my',\n",
       " 'country__nz',\n",
       " 'country__no',\n",
       " 'country__cz',\n",
       " 'country__hk',\n",
       " 'country__au',\n",
       " 'country__gb',\n",
       " 'country__lv',\n",
       " 'country__fi',\n",
       " 'profitability',\n",
       " 'day_sin',\n",
       " 'day_cos',\n",
       " 'month_sin',\n",
       " 'month_cos',\n",
       " 'cast_1_avg_profit',\n",
       " 'cast_1_avg_budget',\n",
       " 'cast_1_experience',\n",
       " 'cast_1_avg_profitability',\n",
       " 'cast_1_movies_before',\n",
       " 'cast_2_avg_profit',\n",
       " 'cast_2_avg_budget',\n",
       " 'cast_2_experience',\n",
       " 'cast_2_avg_profitability',\n",
       " 'cast_2_movies_before',\n",
       " 'cast_3_avg_profit',\n",
       " 'cast_3_avg_budget',\n",
       " 'cast_3_experience',\n",
       " 'cast_3_avg_profitability',\n",
       " 'cast_3_movies_before',\n",
       " 'cast_4_avg_profit',\n",
       " 'cast_4_avg_budget',\n",
       " 'cast_4_experience',\n",
       " 'cast_4_avg_profitability',\n",
       " 'cast_4_movies_before',\n",
       " 'cast_5_avg_profit',\n",
       " 'cast_5_avg_budget',\n",
       " 'cast_5_experience',\n",
       " 'cast_5_avg_profitability',\n",
       " 'cast_5_movies_before',\n",
       " 'cast_6_avg_profit',\n",
       " 'cast_6_avg_budget',\n",
       " 'cast_6_experience',\n",
       " 'cast_6_avg_profitability',\n",
       " 'cast_6_movies_before',\n",
       " 'cast_7_avg_profit',\n",
       " 'cast_7_avg_budget',\n",
       " 'cast_7_experience',\n",
       " 'cast_7_avg_profitability',\n",
       " 'cast_7_movies_before',\n",
       " 'cast_8_avg_profit',\n",
       " 'cast_8_avg_budget',\n",
       " 'cast_8_experience',\n",
       " 'cast_8_avg_profitability',\n",
       " 'cast_8_movies_before',\n",
       " 'cast_1_male',\n",
       " 'cast_1_female',\n",
       " 'cast_2_male',\n",
       " 'cast_2_female',\n",
       " 'cast_3_male',\n",
       " 'cast_3_female',\n",
       " 'cast_4_male',\n",
       " 'cast_4_female',\n",
       " 'cast_5_male',\n",
       " 'cast_5_female',\n",
       " 'cast_6_male',\n",
       " 'cast_6_female',\n",
       " 'cast_7_male',\n",
       " 'cast_7_female',\n",
       " 'cast_8_male',\n",
       " 'cast_8_female',\n",
       " 'crew__sound__music_editor_avg_profit',\n",
       " 'crew__sound__music_editor_avg_budget',\n",
       " 'crew__sound__music_editor_movies_before',\n",
       " 'crew__sound__original_music_composer_avg_profit',\n",
       " 'crew__sound__original_music_composer_avg_budget',\n",
       " 'crew__sound__original_music_composer_movies_before',\n",
       " 'crew__sound__sound_designer_avg_profit',\n",
       " 'crew__sound__sound_designer_avg_budget',\n",
       " 'crew__sound__sound_designer_movies_before',\n",
       " 'crew__sound__sound_effects_editor_avg_profit',\n",
       " 'crew__sound__sound_effects_editor_avg_budget',\n",
       " 'crew__sound__sound_effects_editor_movies_before',\n",
       " 'crew__sound__sound_re_recording_mixer_avg_profit',\n",
       " 'crew__sound__sound_re_recording_mixer_avg_budget',\n",
       " 'crew__sound__sound_re_recording_mixer_movies_before',\n",
       " 'crew__sound__supervising_sound_editor_avg_profit',\n",
       " 'crew__sound__supervising_sound_editor_avg_budget',\n",
       " 'crew__sound__supervising_sound_editor_movies_before',\n",
       " 'crew__directing__director__1_avg_profit',\n",
       " 'crew__directing__director__1_avg_budget',\n",
       " 'crew__directing__director__1_movies_before',\n",
       " 'crew__directing__script_supervisor_avg_profit',\n",
       " 'crew__directing__script_supervisor_avg_budget',\n",
       " 'crew__directing__script_supervisor_movies_before',\n",
       " 'crew__production__casting_avg_profit',\n",
       " 'crew__production__casting_avg_budget',\n",
       " 'crew__production__casting_movies_before',\n",
       " 'crew__production__executive_producer__1_avg_profit',\n",
       " 'crew__production__executive_producer__1_avg_budget',\n",
       " 'crew__production__executive_producer__1_movies_before',\n",
       " 'crew__production__producer__1_avg_profit',\n",
       " 'crew__production__producer__1_avg_budget',\n",
       " 'crew__production__producer__1_movies_before',\n",
       " 'crew__production__producer__2_avg_profit',\n",
       " 'crew__production__producer__2_avg_budget',\n",
       " 'crew__production__producer__2_movies_before',\n",
       " 'crew__editing__editor__1_avg_profit',\n",
       " 'crew__editing__editor__1_avg_budget',\n",
       " 'crew__editing__editor__1_movies_before',\n",
       " 'crew__costume__costume_designer_avg_profit',\n",
       " 'crew__costume__costume_designer_avg_budget',\n",
       " 'crew__costume__costume_designer_movies_before',\n",
       " 'crew__costume__costume_supervisor_avg_profit',\n",
       " 'crew__costume__costume_supervisor_avg_budget',\n",
       " 'crew__costume__costume_supervisor_movies_before',\n",
       " 'crew__costume__makeup_artist_avg_profit',\n",
       " 'crew__costume__makeup_artist_avg_budget',\n",
       " 'crew__costume__makeup_artist_movies_before',\n",
       " 'crew__crew__stunt_coordinator_avg_profit',\n",
       " 'crew__crew__stunt_coordinator_avg_budget',\n",
       " 'crew__crew__stunt_coordinator_movies_before',\n",
       " 'crew__writing__screenplay__1_avg_profit',\n",
       " 'crew__writing__screenplay__1_avg_budget',\n",
       " 'crew__writing__screenplay__1_movies_before',\n",
       " 'crew__art__art_direction_avg_profit',\n",
       " 'crew__art__art_direction_avg_budget',\n",
       " 'crew__art__art_direction_movies_before',\n",
       " 'crew__art__production_design_avg_profit',\n",
       " 'crew__art__production_design_avg_budget',\n",
       " 'crew__art__production_design_movies_before',\n",
       " 'crew__art__property_master_avg_profit',\n",
       " 'crew__art__property_master_avg_budget',\n",
       " 'crew__art__property_master_movies_before',\n",
       " 'crew__art__set_decoration_avg_profit',\n",
       " 'crew__art__set_decoration_avg_budget',\n",
       " 'crew__art__set_decoration_movies_before',\n",
       " 'crew__visualeffects__visual_effects_supervisor_avg_profit',\n",
       " 'crew__visualeffects__visual_effects_supervisor_avg_budget',\n",
       " 'crew__visualeffects__visual_effects_supervisor_movies_before',\n",
       " 'crew__camera__director_of_photography_avg_profit',\n",
       " 'crew__camera__director_of_photography_avg_budget',\n",
       " 'crew__camera__director_of_photography_movies_before',\n",
       " 'crew__camera__steadicam_operator_avg_profit',\n",
       " 'crew__camera__steadicam_operator_avg_budget',\n",
       " 'crew__camera__steadicam_operator_movies_before',\n",
       " 'crew__camera__still_photographer_avg_profit',\n",
       " 'crew__camera__still_photographer_avg_budget',\n",
       " 'crew__camera__still_photographer_movies_before',\n",
       " 'cast_avg_budget',\n",
       " 'cast_avg_profit',\n",
       " 'cast_avg_experience',\n",
       " 'cast_avg_movies_before',\n",
       " 'year_avg_profitability',\n",
       " 'year_avg_revenue',\n",
       " 'production_company_1_avg_profit',\n",
       " 'production_company_1_avg_profitability',\n",
       " 'production_company_1_avg_revenue',\n",
       " 'production_company_2_avg_profit',\n",
       " 'production_company_2_avg_profitability',\n",
       " 'production_company_2_avg_revenue',\n",
       " 'production_company_3_avg_profit',\n",
       " 'production_company_3_avg_profitability',\n",
       " 'production_company_3_avg_revenue',\n",
       " 'collection_name_avg_profit',\n",
       " 'collection_name_avg_revenue',\n",
       " 'competition',\n",
       " 'rating__g',\n",
       " 'rating__pg',\n",
       " 'rating__pg-13',\n",
       " 'rating__r',\n",
       " 'rating__nc-17',\n",
       " 'topic_0',\n",
       " 'topic_1',\n",
       " 'topic_2',\n",
       " 'topic_3',\n",
       " 'topic_4',\n",
       " 'topic_5',\n",
       " 'topic_6',\n",
       " 'topic_7',\n",
       " 'topic_8',\n",
       " 'topic_9',\n",
       " 'topic_10',\n",
       " 'topic_11',\n",
       " 'topic_12',\n",
       " 'topic_13',\n",
       " 'topic_14',\n",
       " 'META__original_title',\n",
       " 'META__title',\n",
       " 'META__keywords',\n",
       " 'META__plot',\n",
       " 'META__topic_dominant',\n",
       " 'META__topic_words']"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(added_topics.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "added_topics.to_csv('15 topics_num15_update1_chunk200_passes_15.csv', mode='w+', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['budget',\n",
       " 'META__id',\n",
       " 'PROCESS__original_language',\n",
       " 'revenue',\n",
       " 'runtime',\n",
       " 'spoken_languages',\n",
       " 'META__year',\n",
       " 'META__month',\n",
       " 'META__day',\n",
       " 'weekend',\n",
       " 'META__collection_name',\n",
       " 'META__cast_1_name',\n",
       " 'META__cast_2_name',\n",
       " 'META__cast_3_name',\n",
       " 'META__cast_4_name',\n",
       " 'META__cast_5_name',\n",
       " 'META__cast_6_name',\n",
       " 'META__cast_7_name',\n",
       " 'META__cast_8_name',\n",
       " 'META__crew__sound__music_editor',\n",
       " 'META__crew__sound__original_music_composer',\n",
       " 'META__crew__sound__sound_designer',\n",
       " 'META__crew__sound__sound_effects_editor',\n",
       " 'META__crew__sound__sound_re_recording_mixer',\n",
       " 'META__crew__sound__supervising_sound_editor',\n",
       " 'META__crew__directing__director__1',\n",
       " 'META__crew__directing__script_supervisor',\n",
       " 'META__crew__production__casting',\n",
       " 'META__crew__production__executive_producer__1',\n",
       " 'META__crew__production__producer__1',\n",
       " 'META__crew__production__producer__2',\n",
       " 'META__crew__editing__editor__1',\n",
       " 'META__crew__costume__costume_designer',\n",
       " 'META__crew__costume__costume_supervisor',\n",
       " 'META__crew__costume__makeup_artist',\n",
       " 'META__crew__crew__stunt_coordinator',\n",
       " 'META__crew__writing__screenplay__1',\n",
       " 'META__crew__art__art_direction',\n",
       " 'META__crew__art__production_design',\n",
       " 'META__crew__art__property_master',\n",
       " 'META__crew__art__set_decoration',\n",
       " 'META__crew__visualeffects__visual_effects_supervisor',\n",
       " 'META__crew__camera__director_of_photography',\n",
       " 'META__crew__camera__steadicam_operator',\n",
       " 'META__crew__camera__still_photographer',\n",
       " 'genre__war',\n",
       " 'genre__western',\n",
       " 'genre__mystery',\n",
       " 'genre__music',\n",
       " 'genre__crime',\n",
       " 'genre__romance',\n",
       " 'genre__action',\n",
       " 'genre__adventure',\n",
       " 'genre__thriller',\n",
       " 'genre__animation',\n",
       " 'genre__family',\n",
       " 'genre__drama',\n",
       " 'genre__comedy',\n",
       " 'genre__documentary',\n",
       " 'genre__history',\n",
       " 'genre__fantasy',\n",
       " 'genre__horror',\n",
       " 'META__production_company_1',\n",
       " 'META__production_company_2',\n",
       " 'META__production_company_3',\n",
       " 'country__rs',\n",
       " 'country__su',\n",
       " 'country__do',\n",
       " 'country__bo',\n",
       " 'country__ph',\n",
       " 'country__pe',\n",
       " 'country__id',\n",
       " 'country__gr',\n",
       " 'country__hn',\n",
       " 'country__nl',\n",
       " 'country__ee',\n",
       " 'country__ug',\n",
       " 'country__uy',\n",
       " 'country__ir',\n",
       " 'country__lb',\n",
       " 'country__pk',\n",
       " 'country__ua',\n",
       " 'country__eg',\n",
       " 'country__is',\n",
       " 'country__co',\n",
       " 'country__sk',\n",
       " 'country__bw',\n",
       " 'country__es',\n",
       " 'country__se',\n",
       " 'country__jp',\n",
       " 'country__np',\n",
       " 'country__tw',\n",
       " 'country__ie',\n",
       " 'country__lu',\n",
       " 'country__us',\n",
       " 'country__vn',\n",
       " 'country__ro',\n",
       " 'country__mn',\n",
       " 'country__cl',\n",
       " 'country__hu',\n",
       " 'country__br',\n",
       " 'country__ae',\n",
       " 'country__kr',\n",
       " 'country__be',\n",
       " 'country__ca',\n",
       " 'country__sg',\n",
       " 'country__bg',\n",
       " 'country__de',\n",
       " 'country__pl',\n",
       " 'country__mv',\n",
       " 'country__cn',\n",
       " 'country__in',\n",
       " 'country__th',\n",
       " 'country__fr',\n",
       " 'country__ru',\n",
       " 'country__dk',\n",
       " 'country__af',\n",
       " 'country__xg',\n",
       " 'country__it',\n",
       " 'country__ge',\n",
       " 'country__tr',\n",
       " 'country__za',\n",
       " 'country__ve',\n",
       " 'country__lk',\n",
       " 'country__hr',\n",
       " 'country__ng',\n",
       " 'country__ar',\n",
       " 'country__ba',\n",
       " 'country__il',\n",
       " 'country__mx',\n",
       " 'country__bd',\n",
       " 'country__my',\n",
       " 'country__nz',\n",
       " 'country__no',\n",
       " 'country__cz',\n",
       " 'country__hk',\n",
       " 'country__au',\n",
       " 'country__gb',\n",
       " 'country__lv',\n",
       " 'country__fi',\n",
       " 'profitability',\n",
       " 'day_sin',\n",
       " 'day_cos',\n",
       " 'month_sin',\n",
       " 'month_cos',\n",
       " 'cast_1_avg_profit',\n",
       " 'cast_1_avg_budget',\n",
       " 'cast_1_experience',\n",
       " 'cast_1_avg_profitability',\n",
       " 'cast_1_movies_before',\n",
       " 'cast_2_avg_profit',\n",
       " 'cast_2_avg_budget',\n",
       " 'cast_2_experience',\n",
       " 'cast_2_avg_profitability',\n",
       " 'cast_2_movies_before',\n",
       " 'cast_3_avg_profit',\n",
       " 'cast_3_avg_budget',\n",
       " 'cast_3_experience',\n",
       " 'cast_3_avg_profitability',\n",
       " 'cast_3_movies_before',\n",
       " 'cast_4_avg_profit',\n",
       " 'cast_4_avg_budget',\n",
       " 'cast_4_experience',\n",
       " 'cast_4_avg_profitability',\n",
       " 'cast_4_movies_before',\n",
       " 'cast_5_avg_profit',\n",
       " 'cast_5_avg_budget',\n",
       " 'cast_5_experience',\n",
       " 'cast_5_avg_profitability',\n",
       " 'cast_5_movies_before',\n",
       " 'cast_6_avg_profit',\n",
       " 'cast_6_avg_budget',\n",
       " 'cast_6_experience',\n",
       " 'cast_6_avg_profitability',\n",
       " 'cast_6_movies_before',\n",
       " 'cast_7_avg_profit',\n",
       " 'cast_7_avg_budget',\n",
       " 'cast_7_experience',\n",
       " 'cast_7_avg_profitability',\n",
       " 'cast_7_movies_before',\n",
       " 'cast_8_avg_profit',\n",
       " 'cast_8_avg_budget',\n",
       " 'cast_8_experience',\n",
       " 'cast_8_avg_profitability',\n",
       " 'cast_8_movies_before',\n",
       " 'cast_1_male',\n",
       " 'cast_1_female',\n",
       " 'cast_2_male',\n",
       " 'cast_2_female',\n",
       " 'cast_3_male',\n",
       " 'cast_3_female',\n",
       " 'cast_4_male',\n",
       " 'cast_4_female',\n",
       " 'cast_5_male',\n",
       " 'cast_5_female',\n",
       " 'cast_6_male',\n",
       " 'cast_6_female',\n",
       " 'cast_7_male',\n",
       " 'cast_7_female',\n",
       " 'cast_8_male',\n",
       " 'cast_8_female',\n",
       " 'crew__sound__music_editor_avg_profit',\n",
       " 'crew__sound__music_editor_avg_budget',\n",
       " 'crew__sound__music_editor_movies_before',\n",
       " 'crew__sound__original_music_composer_avg_profit',\n",
       " 'crew__sound__original_music_composer_avg_budget',\n",
       " 'crew__sound__original_music_composer_movies_before',\n",
       " 'crew__sound__sound_designer_avg_profit',\n",
       " 'crew__sound__sound_designer_avg_budget',\n",
       " 'crew__sound__sound_designer_movies_before',\n",
       " 'crew__sound__sound_effects_editor_avg_profit',\n",
       " 'crew__sound__sound_effects_editor_avg_budget',\n",
       " 'crew__sound__sound_effects_editor_movies_before',\n",
       " 'crew__sound__sound_re_recording_mixer_avg_profit',\n",
       " 'crew__sound__sound_re_recording_mixer_avg_budget',\n",
       " 'crew__sound__sound_re_recording_mixer_movies_before',\n",
       " 'crew__sound__supervising_sound_editor_avg_profit',\n",
       " 'crew__sound__supervising_sound_editor_avg_budget',\n",
       " 'crew__sound__supervising_sound_editor_movies_before',\n",
       " 'crew__directing__director__1_avg_profit',\n",
       " 'crew__directing__director__1_avg_budget',\n",
       " 'crew__directing__director__1_movies_before',\n",
       " 'crew__directing__script_supervisor_avg_profit',\n",
       " 'crew__directing__script_supervisor_avg_budget',\n",
       " 'crew__directing__script_supervisor_movies_before',\n",
       " 'crew__production__casting_avg_profit',\n",
       " 'crew__production__casting_avg_budget',\n",
       " 'crew__production__casting_movies_before',\n",
       " 'crew__production__executive_producer__1_avg_profit',\n",
       " 'crew__production__executive_producer__1_avg_budget',\n",
       " 'crew__production__executive_producer__1_movies_before',\n",
       " 'crew__production__producer__1_avg_profit',\n",
       " 'crew__production__producer__1_avg_budget',\n",
       " 'crew__production__producer__1_movies_before',\n",
       " 'crew__production__producer__2_avg_profit',\n",
       " 'crew__production__producer__2_avg_budget',\n",
       " 'crew__production__producer__2_movies_before',\n",
       " 'crew__editing__editor__1_avg_profit',\n",
       " 'crew__editing__editor__1_avg_budget',\n",
       " 'crew__editing__editor__1_movies_before',\n",
       " 'crew__costume__costume_designer_avg_profit',\n",
       " 'crew__costume__costume_designer_avg_budget',\n",
       " 'crew__costume__costume_designer_movies_before',\n",
       " 'crew__costume__costume_supervisor_avg_profit',\n",
       " 'crew__costume__costume_supervisor_avg_budget',\n",
       " 'crew__costume__costume_supervisor_movies_before',\n",
       " 'crew__costume__makeup_artist_avg_profit',\n",
       " 'crew__costume__makeup_artist_avg_budget',\n",
       " 'crew__costume__makeup_artist_movies_before',\n",
       " 'crew__crew__stunt_coordinator_avg_profit',\n",
       " 'crew__crew__stunt_coordinator_avg_budget',\n",
       " 'crew__crew__stunt_coordinator_movies_before',\n",
       " 'crew__writing__screenplay__1_avg_profit',\n",
       " 'crew__writing__screenplay__1_avg_budget',\n",
       " 'crew__writing__screenplay__1_movies_before',\n",
       " 'crew__art__art_direction_avg_profit',\n",
       " 'crew__art__art_direction_avg_budget',\n",
       " 'crew__art__art_direction_movies_before',\n",
       " 'crew__art__production_design_avg_profit',\n",
       " 'crew__art__production_design_avg_budget',\n",
       " 'crew__art__production_design_movies_before',\n",
       " 'crew__art__property_master_avg_profit',\n",
       " 'crew__art__property_master_avg_budget',\n",
       " 'crew__art__property_master_movies_before',\n",
       " 'crew__art__set_decoration_avg_profit',\n",
       " 'crew__art__set_decoration_avg_budget',\n",
       " 'crew__art__set_decoration_movies_before',\n",
       " 'crew__visualeffects__visual_effects_supervisor_avg_profit',\n",
       " 'crew__visualeffects__visual_effects_supervisor_avg_budget',\n",
       " 'crew__visualeffects__visual_effects_supervisor_movies_before',\n",
       " 'crew__camera__director_of_photography_avg_profit',\n",
       " 'crew__camera__director_of_photography_avg_budget',\n",
       " 'crew__camera__director_of_photography_movies_before',\n",
       " 'crew__camera__steadicam_operator_avg_profit',\n",
       " 'crew__camera__steadicam_operator_avg_budget',\n",
       " 'crew__camera__steadicam_operator_movies_before',\n",
       " 'crew__camera__still_photographer_avg_profit',\n",
       " 'crew__camera__still_photographer_avg_budget',\n",
       " 'crew__camera__still_photographer_movies_before',\n",
       " 'cast_avg_budget',\n",
       " 'cast_avg_profit',\n",
       " 'cast_avg_experience',\n",
       " 'cast_avg_movies_before',\n",
       " 'year_avg_profitability',\n",
       " 'year_avg_revenue',\n",
       " 'production_company_1_avg_profit',\n",
       " 'production_company_1_avg_profitability',\n",
       " 'production_company_1_avg_revenue',\n",
       " 'production_company_2_avg_profit',\n",
       " 'production_company_2_avg_profitability',\n",
       " 'production_company_2_avg_revenue',\n",
       " 'production_company_3_avg_profit',\n",
       " 'production_company_3_avg_profitability',\n",
       " 'production_company_3_avg_revenue',\n",
       " 'collection_name_avg_profit',\n",
       " 'collection_name_avg_revenue',\n",
       " 'competition',\n",
       " 'rating__g',\n",
       " 'rating__pg',\n",
       " 'rating__pg-13',\n",
       " 'rating__r',\n",
       " 'rating__nc-17',\n",
       " 'topic_0',\n",
       " 'topic_1',\n",
       " 'topic_2',\n",
       " 'topic_3',\n",
       " 'topic_4',\n",
       " 'topic_5',\n",
       " 'topic_6',\n",
       " 'topic_7',\n",
       " 'topic_8',\n",
       " 'topic_9',\n",
       " 'topic_10',\n",
       " 'topic_11',\n",
       " 'topic_12',\n",
       " 'topic_13',\n",
       " 'topic_14',\n",
       " 'META__original_title',\n",
       " 'META__title',\n",
       " 'META__keywords',\n",
       " 'META__plot',\n",
       " 'META__topic_dominant',\n",
       " 'META__topic_words']"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(added_topics.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.feature_selection import VarianceThreshold"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "VarianceThreshold(threshold=0.01)"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "qzf = VarianceThreshold(threshold=0.01)\n",
    "qzf.fit(added_topics[[c for c in added_topics.columns if 'topic_' in c and not 'META' in c]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [],
   "source": [
    "qzf.get_support().sum()\n",
    "added_topics_qzf = added_topics[[c for c in added_topics.columns if 'topic_' in c and not 'META' in c]].columns[[not temp for temp in qzf.get_support()]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['topic_0', 'topic_1', 'topic_2', 'topic_4', 'topic_5', 'topic_7',\n",
       "       'topic_8', 'topic_9', 'topic_11', 'topic_12', 'topic_13', 'topic_14'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "added_topics_qzf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 335,
   "metadata": {},
   "outputs": [],
   "source": [
    "def compute_coherence_values(dictionary, corpus, texts, limit, start=2, step=3):\n",
    "    coherence_values = []\n",
    "    model_list = []\n",
    "    for num_topics in range(start, limit, step):\n",
    "        print(f'num_topics: {num_topics}')\n",
    "        model = gensim.models.ldamodel.LdaModel(corpus=corpus,\n",
    "                                           id2word=id2word,\n",
    "                                           num_topics=num_topics, \n",
    "                                           random_state=100,\n",
    "                                           update_every=1,\n",
    "                                           chunksize=100,\n",
    "                                           passes=5,\n",
    "                                           alpha='auto',\n",
    "                                           per_word_topics=True)\n",
    "        model_list.append(model)\n",
    "        coherencemodel = CoherenceModel(model=model, texts=texts, dictionary=dictionary, coherence='c_v')\n",
    "        coherence_values.append(coherencemodel.get_coherence())\n",
    "\n",
    "    return model_list, coherence_values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 336,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "num_topics: 10\n",
      "num_topics: 15\n",
      "num_topics: 20\n",
      "num_topics: 25\n",
      "num_topics: 30\n",
      "num_topics: 35\n",
      "num_topics: 40\n",
      "num_topics: 45\n"
     ]
    }
   ],
   "source": [
    "model_list, coherence_values = compute_coherence_values(dictionary=id2word, corpus=corpus, texts=data_lemmatized, start=10, limit=50, step=5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 337,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Show graph\n",
    "limit=50; start=10; step=5;\n",
    "x = range(start, limit, step)\n",
    "plt.plot(x, coherence_values)\n",
    "plt.xlabel(\"Num Topics\")\n",
    "plt.ylabel(\"Coherence score\")\n",
    "plt.legend((\"coherence_values\"), loc='best')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 338,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Num Topics = 10  has Coherence Value of 0.4565\n",
      "Num Topics = 15  has Coherence Value of 0.4655\n",
      "Num Topics = 20  has Coherence Value of 0.4593\n",
      "Num Topics = 25  has Coherence Value of 0.4601\n",
      "Num Topics = 30  has Coherence Value of 0.44\n",
      "Num Topics = 35  has Coherence Value of 0.4397\n",
      "Num Topics = 40  has Coherence Value of 0.4229\n",
      "Num Topics = 45  has Coherence Value of 0.4558\n"
     ]
    }
   ],
   "source": [
    "# Print the coherence scores\n",
    "for m, cv in zip(x, coherence_values):\n",
    "    print(\"Num Topics =\", m, \" has Coherence Value of\", round(cv, 4))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 339,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "num_topics: 50\n",
      "num_topics: 55\n",
      "num_topics: 60\n",
      "num_topics: 65\n"
     ]
    }
   ],
   "source": [
    "model_list2, coherence_values2 = compute_coherence_values(dictionary=id2word, corpus=corpus, texts=data_lemmatized, start=50, limit=70, step=5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 340,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Show graph\n",
    "limit=70; start=50; step=5;\n",
    "x = range(start, limit, step)\n",
    "plt.plot(x, coherence_values2)\n",
    "plt.xlabel(\"Num Topics\")\n",
    "plt.ylabel(\"Coherence score\")\n",
    "plt.legend((\"coherence_values\"), loc='best')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 341,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Num Topics = 50  has Coherence Value of 0.4366\n",
      "Num Topics = 55  has Coherence Value of 0.445\n",
      "Num Topics = 60  has Coherence Value of 0.4321\n",
      "Num Topics = 65  has Coherence Value of 0.4286\n"
     ]
    }
   ],
   "source": [
    "# Print the coherence scores\n",
    "for m, cv in zip(x, coherence_values2):\n",
    "    print(\"Num Topics =\", m, \" has Coherence Value of\", round(cv, 4))"
   ]
  },
  {
   "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": "3.7.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}