Most_Popular_Recommendations.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Recommendations with MovieTweetings: Most Popular Recommendation\n",
    "\n",
    "Now that you have created the necessary columns we will be using throughout the rest of the lesson on creating recommendations, let's get started with the first of our recommendations.\n",
    "\n",
    "To get started, read in the libraries and the two datasets you will be using throughout the lesson using the code below.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import tests as t\n",
    "\n",
    "%matplotlib inline\n",
    "\n",
    "# Read in the datasets\n",
    "movies = pd.read_csv('movies_clean.csv')\n",
    "reviews = pd.read_csv('reviews_clean.csv')\n",
    "del movies['Unnamed: 0']\n",
    "del reviews['Unnamed: 0']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>user_id</th>\n",
       "      <th>movie_id</th>\n",
       "      <th>rating</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>date</th>\n",
       "      <th>month_1</th>\n",
       "      <th>month_2</th>\n",
       "      <th>month_3</th>\n",
       "      <th>month_4</th>\n",
       "      <th>month_5</th>\n",
       "      <th>...</th>\n",
       "      <th>month_9</th>\n",
       "      <th>month_10</th>\n",
       "      <th>month_11</th>\n",
       "      <th>month_12</th>\n",
       "      <th>year_2013</th>\n",
       "      <th>year_2014</th>\n",
       "      <th>year_2015</th>\n",
       "      <th>year_2016</th>\n",
       "      <th>year_2017</th>\n",
       "      <th>year_2018</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>68646</td>\n",
       "      <td>10</td>\n",
       "      <td>1381620027</td>\n",
       "      <td>2013-10-12 23:20:27</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>113277</td>\n",
       "      <td>10</td>\n",
       "      <td>1379466669</td>\n",
       "      <td>2013-09-18 01:11:09</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>422720</td>\n",
       "      <td>8</td>\n",
       "      <td>1412178746</td>\n",
       "      <td>2014-10-01 15:52:26</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2</td>\n",
       "      <td>454876</td>\n",
       "      <td>8</td>\n",
       "      <td>1394818630</td>\n",
       "      <td>2014-03-14 17:37:10</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2</td>\n",
       "      <td>790636</td>\n",
       "      <td>7</td>\n",
       "      <td>1389963947</td>\n",
       "      <td>2014-01-17 13:05:47</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 23 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   user_id  movie_id  rating   timestamp                 date  month_1  \\\n",
       "0        1     68646      10  1381620027  2013-10-12 23:20:27        0   \n",
       "1        1    113277      10  1379466669  2013-09-18 01:11:09        0   \n",
       "2        2    422720       8  1412178746  2014-10-01 15:52:26        0   \n",
       "3        2    454876       8  1394818630  2014-03-14 17:37:10        0   \n",
       "4        2    790636       7  1389963947  2014-01-17 13:05:47        0   \n",
       "\n",
       "   month_2  month_3  month_4  month_5    ...      month_9  month_10  month_11  \\\n",
       "0        0        0        0        0    ...            0         1         0   \n",
       "1        0        0        0        0    ...            0         0         0   \n",
       "2        0        0        0        0    ...            0         1         0   \n",
       "3        0        0        0        0    ...            0         0         0   \n",
       "4        0        0        0        0    ...            0         0         0   \n",
       "\n",
       "   month_12  year_2013  year_2014  year_2015  year_2016  year_2017  year_2018  \n",
       "0         0          1          0          0          0          0          0  \n",
       "1         0          1          0          0          0          0          0  \n",
       "2         0          0          1          0          0          0          0  \n",
       "3         0          0          1          0          0          0          0  \n",
       "4         0          0          1          0          0          0          0  \n",
       "\n",
       "[5 rows x 23 columns]"
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   ],
   "source": [
    "reviews.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>movie_id</th>\n",
       "      <th>movie</th>\n",
       "      <th>genre</th>\n",
       "      <th>date</th>\n",
       "      <th>1800's</th>\n",
       "      <th>1900's</th>\n",
       "      <th>2000's</th>\n",
       "      <th>History</th>\n",
       "      <th>News</th>\n",
       "      <th>Horror</th>\n",
       "      <th>...</th>\n",
       "      <th>Fantasy</th>\n",
       "      <th>Romance</th>\n",
       "      <th>Game-Show</th>\n",
       "      <th>Action</th>\n",
       "      <th>Documentary</th>\n",
       "      <th>Animation</th>\n",
       "      <th>Comedy</th>\n",
       "      <th>Short</th>\n",
       "      <th>Western</th>\n",
       "      <th>Thriller</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>8</td>\n",
       "      <td>Edison Kinetoscopic Record of a Sneeze (1894)</td>\n",
       "      <td>Documentary|Short</td>\n",
       "      <td>1894</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10</td>\n",
       "      <td>La sortie des usines Lumière (1895)</td>\n",
       "      <td>Documentary|Short</td>\n",
       "      <td>1895</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>12</td>\n",
       "      <td>The Arrival of a Train (1896)</td>\n",
       "      <td>Documentary|Short</td>\n",
       "      <td>1896</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>25</td>\n",
       "      <td>The Oxford and Cambridge University Boat Race ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1895</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>91</td>\n",
       "      <td>Le manoir du diable (1896)</td>\n",
       "      <td>Short|Horror</td>\n",
       "      <td>1896</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 35 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   movie_id                                              movie  \\\n",
       "0         8      Edison Kinetoscopic Record of a Sneeze (1894)   \n",
       "1        10                La sortie des usines Lumière (1895)   \n",
       "2        12                      The Arrival of a Train (1896)   \n",
       "3        25  The Oxford and Cambridge University Boat Race ...   \n",
       "4        91                         Le manoir du diable (1896)   \n",
       "\n",
       "               genre  date  1800's  1900's  2000's  History  News  Horror  \\\n",
       "0  Documentary|Short  1894       1       0       0        0     0       0   \n",
       "1  Documentary|Short  1895       1       0       0        0     0       0   \n",
       "2  Documentary|Short  1896       1       0       0        0     0       0   \n",
       "3                NaN  1895       1       0       0        0     0       0   \n",
       "4       Short|Horror  1896       1       0       0        0     0       1   \n",
       "\n",
       "     ...     Fantasy  Romance  Game-Show  Action  Documentary  Animation  \\\n",
       "0    ...           0        0          0       0            1          0   \n",
       "1    ...           0        0          0       0            1          0   \n",
       "2    ...           0        0          0       0            1          0   \n",
       "3    ...           0        0          0       0            0          0   \n",
       "4    ...           0        0          0       0            0          0   \n",
       "\n",
       "   Comedy  Short  Western  Thriller  \n",
       "0       0      1        0         0  \n",
       "1       0      1        0         0  \n",
       "2       0      1        0         0  \n",
       "3       0      0        0         0  \n",
       "4       0      1        0         0  \n",
       "\n",
       "[5 rows x 35 columns]"
      ]
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     "execution_count": 3,
     "metadata": {},
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   ],
   "source": [
    "movies.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 1. How To Find The Most Popular Movies\n",
    "\n",
    "For this notebook, we have a single task.  The task is that no matter the user, we need to provide a list of the recommendations based on simply the most popular items.\n",
    "\n",
    "For this task, we will consider what is \"most popular\" based on the following criteria:\n",
    "\n",
    "* A movie with the highest average rating is considered best\n",
    "* With ties, movies that have more ratings are better\n",
    "* A movie must have a minimum of 5 ratings to be considered among the best movies\n",
    "* If movies are tied in their average rating and number of ratings, the ranking is determined by the movie that is the most recent rating\n",
    "\n",
    "With these criteria, the goal for this notebook is to take a **user_id** and provide back the **n_top** recommendations.  Use the function below as the scaffolding that will be used for all the future recommendations as well."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def popular_recommendations(user_id, n_top):\n",
    "    '''\n",
    "    INPUT:\n",
    "    user_id - the user_id of the individual you are making recommendations for\n",
    "    n_top - an integer of the number recommendations you want back\n",
    "    OUTPUT:\n",
    "    top_movies - a list of the n_top recommended movies by movie title in order best to worst\n",
    "    '''\n",
    "    grouped = reviews.groupby('movie_id').agg(\n",
    "    {'rating': [('ratings', 'count'),\n",
    "                ('avg_rating', 'mean')],\n",
    "     'date':[('rated_last','max')]\n",
    "    })\n",
    "    grouped.columns=grouped.columns.droplevel()\n",
    "    grouped = grouped.sort_values(by=['avg_rating','ratings','rated_last'],ascending=False)\n",
    "    grouped = grouped.loc[grouped['ratings']>5]\n",
    "    grouped = grouped.merge(movies[['movie_id','movie']],left_index=True, right_on=['movie_id'])\n",
    "    top_movies = grouped[:n_top]['movie'].tolist()\n",
    "    \n",
    "    return top_movies # a list of the n_top movies as recommended"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['MSG 2 the Messenger (2015)',\n",
       " 'Avengers: Age of Ultron Parody (2015)',\n",
       " 'Sorry to Bother You (2018)',\n",
       " 'Selam (2013)',\n",
       " \"Quiet Riot: Well Now You're Here, There's No Way Back (2014)\"]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "popular_recommendations(1, 5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Notice:** This wasn't the only way we could have determined the \"top rated\" movies.  You can imagine that in keeping track of trending news or trending social events, you would likely want to create a time window from the current time, and then pull the articles in the most recent time frame.  There are always going to be some subjective decisions to be made.  \n",
    "\n",
    "If you find that no one is paying any attention to your most popular recommendations, then it might be time to find a new way to recommend, which is what the next parts of the lesson should prepare us to do!\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Part II: Adding Filters\n",
    "\n",
    "Now that you have created a function to give back the **n_top** movies, let's make it a bit more robust.  Add arguments that will act as filters for the movie **year** and **genre**.  \n",
    "\n",
    "Use the cells below to adjust your existing function to allow for **year** and **genre** arguments as **lists** of **strings**.  Then your ending results are filtered to only movies within the lists of provided years and genres (as `or` conditions).  If no list is provided, there should be no filter applied.\n",
    "\n",
    "You can adjust other necessary inputs as necessary to retrieve the final results you are looking for!\n",
    "\n",
    "Try writing a few tests against the test function in our test function.  Below returns the top 20 movies for user 1 based on the specified year and genre filters.  Does yours return the same? \n",
    "\n",
    "```\n",
    "t.popular_recs_filtered('1', 20, ranked_movies, years=['2015', '2016', '2017', '2018'], genres=['History'])\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def recommend_filtered(user_id, n_top, years,genres):\n",
    "    '''\n",
    "    INPUT:\n",
    "    user_id - the user_id of the individual you are making recommendations for\n",
    "    n_top - an integer of the number recommendations you want back\n",
    "    OUTPUT:\n",
    "    top_movies - a list of the n_top recommended movies by movie title in order best to worst\n",
    "    '''\n",
    "    grouped = reviews.groupby('movie_id').agg(\n",
    "    {'rating': [('ratings', 'count'),\n",
    "                ('avg_rating', 'mean')],\n",
    "     'date':[('rated_last','max')]\n",
    "    })\n",
    "    grouped.columns=grouped.columns.droplevel()\n",
    "    grouped = grouped.sort_values(by=['avg_rating','ratings','rated_last'],ascending=False)\n",
    "    grouped = grouped.loc[grouped['ratings']>5]\n",
    "    grouped = grouped.merge(movies,left_index=True, right_on=['movie_id'])\n",
    "    if years:\n",
    "        grouped = grouped.loc[grouped['date'].isin(years)]\n",
    "\n",
    "    if genres:\n",
    "        grouped = grouped.loc[(grouped[genres] == 1).any(axis=1)]\n",
    "    \n",
    "    return grouped # a list of the n_top movies as recommended"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ratings</th>\n",
       "      <th>avg_rating</th>\n",
       "      <th>rated_last</th>\n",
       "      <th>movie_id</th>\n",
       "      <th>movie</th>\n",
       "      <th>genre</th>\n",
       "      <th>date</th>\n",
       "      <th>1800's</th>\n",
       "      <th>1900's</th>\n",
       "      <th>2000's</th>\n",
       "      <th>...</th>\n",
       "      <th>Fantasy</th>\n",
       "      <th>Romance</th>\n",
       "      <th>Game-Show</th>\n",
       "      <th>Action</th>\n",
       "      <th>Documentary</th>\n",
       "      <th>Animation</th>\n",
       "      <th>Comedy</th>\n",
       "      <th>Short</th>\n",
       "      <th>Western</th>\n",
       "      <th>Thriller</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>30587</th>\n",
       "      <td>35</td>\n",
       "      <td>9.200000</td>\n",
       "      <td>2018-06-22 22:19:09</td>\n",
       "      <td>6316138</td>\n",
       "      <td>Ayla: The Daughter of War (2017)</td>\n",
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       "      <td>2017</td>\n",
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       "      <th>30503</th>\n",
       "      <td>6</td>\n",
       "      <td>8.833333</td>\n",
       "      <td>2018-06-11 04:06:25</td>\n",
       "      <td>6223974</td>\n",
       "      <td>The Farthest (2017)</td>\n",
       "      <td>Documentary|History</td>\n",
       "      <td>2017</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>30862</th>\n",
       "      <td>6</td>\n",
       "      <td>8.333333</td>\n",
       "      <td>2018-03-18 13:27:52</td>\n",
       "      <td>6794424</td>\n",
       "      <td>LA 92 (2017)</td>\n",
       "      <td>Documentary|History</td>\n",
       "      <td>2017</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28997</th>\n",
       "      <td>1618</td>\n",
       "      <td>7.982695</td>\n",
       "      <td>2018-06-25 02:12:19</td>\n",
       "      <td>5013056</td>\n",
       "      <td>Dunkirk (2017)</td>\n",
       "      <td>Action|Drama|History</td>\n",
       "      <td>2017</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>30891</th>\n",
       "      <td>64</td>\n",
       "      <td>7.953125</td>\n",
       "      <td>2018-06-22 22:48:04</td>\n",
       "      <td>6878038</td>\n",
       "      <td>Taeksi Woonjunsa (2017)</td>\n",
       "      <td>Action|Drama|History</td>\n",
       "      <td>2017</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>30220</th>\n",
       "      <td>18</td>\n",
       "      <td>7.944444</td>\n",
       "      <td>2018-06-24 13:06:26</td>\n",
       "      <td>5969696</td>\n",
       "      <td>The Battleship Island (2017)</td>\n",
       "      <td>Action|Drama|History</td>\n",
       "      <td>2017</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>28273</th>\n",
       "      <td>487</td>\n",
       "      <td>7.895277</td>\n",
       "      <td>2018-06-25 02:47:00</td>\n",
       "      <td>4555426</td>\n",
       "      <td>Darkest Hour (2017)</td>\n",
       "      <td>Biography|Drama|History</td>\n",
       "      <td>2017</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>28946</th>\n",
       "      <td>11</td>\n",
       "      <td>7.363636</td>\n",
       "      <td>2018-05-29 17:22:48</td>\n",
       "      <td>4977530</td>\n",
       "      <td>Viceroy's House (2017)</td>\n",
       "      <td>Drama|History</td>\n",
       "      <td>2017</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>30569</th>\n",
       "      <td>320</td>\n",
       "      <td>7.331250</td>\n",
       "      <td>2018-06-23 11:31:29</td>\n",
       "      <td>6294822</td>\n",
       "      <td>The Post (2017)</td>\n",
       "      <td>Biography|Drama|History</td>\n",
       "      <td>2017</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>30063</th>\n",
       "      <td>78</td>\n",
       "      <td>7.256410</td>\n",
       "      <td>2018-05-27 21:41:50</td>\n",
       "      <td>5816682</td>\n",
       "      <td>Victoria and Abdul (2017)</td>\n",
       "      <td>Biography|Drama|History</td>\n",
       "      <td>2017</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>19382</th>\n",
       "      <td>70</td>\n",
       "      <td>7.214286</td>\n",
       "      <td>2018-06-05 19:32:24</td>\n",
       "      <td>1730768</td>\n",
       "      <td>The Zookeeper's Wife (2017)</td>\n",
       "      <td>Biography|Drama|History</td>\n",
       "      <td>2017</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>30187</th>\n",
       "      <td>16</td>\n",
       "      <td>7.187500</td>\n",
       "      <td>2018-06-20 05:40:57</td>\n",
       "      <td>5935704</td>\n",
       "      <td>Padmaavat (2018)</td>\n",
       "      <td>Drama|History|Romance</td>\n",
       "      <td>2018</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>28777</th>\n",
       "      <td>25</td>\n",
       "      <td>7.040000</td>\n",
       "      <td>2018-03-14 15:49:37</td>\n",
       "      <td>4882376</td>\n",
       "      <td>First They Killed My Father: A Daughter of Cam...</td>\n",
       "      <td>Biography|Drama|History</td>\n",
       "      <td>2017</td>\n",
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       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>29406</th>\n",
       "      <td>7</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>2018-05-28 06:24:27</td>\n",
       "      <td>5270948</td>\n",
       "      <td>Chappaquiddick (2017)</td>\n",
       "      <td>Drama|History|Thriller</td>\n",
       "      <td>2017</td>\n",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>30738</th>\n",
       "      <td>7</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>2018-04-07 16:05:34</td>\n",
       "      <td>6537238</td>\n",
       "      <td>Salyut-7 (2017)</td>\n",
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       "      <td>2017</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>17522</th>\n",
       "      <td>120</td>\n",
       "      <td>6.800000</td>\n",
       "      <td>2018-06-25 01:06:55</td>\n",
       "      <td>1413492</td>\n",
       "      <td>12 Strong (2018)</td>\n",
       "      <td>Action|Drama|History</td>\n",
       "      <td>2018</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>28538</th>\n",
       "      <td>36</td>\n",
       "      <td>6.388889</td>\n",
       "      <td>2018-06-17 14:13:05</td>\n",
       "      <td>4703048</td>\n",
       "      <td>6 Days (2017)</td>\n",
       "      <td>Action|Drama|History</td>\n",
       "      <td>2017</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>29270</th>\n",
       "      <td>21</td>\n",
       "      <td>6.333333</td>\n",
       "      <td>2018-04-30 02:49:17</td>\n",
       "      <td>5175450</td>\n",
       "      <td>Mark Felt: The Man Who Brought Down the White ...</td>\n",
       "      <td>Biography|Drama|History</td>\n",
       "      <td>2017</td>\n",
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       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>23962</th>\n",
       "      <td>20</td>\n",
       "      <td>6.150000</td>\n",
       "      <td>2018-03-18 21:40:48</td>\n",
       "      <td>2674454</td>\n",
       "      <td>Churchill (2017)</td>\n",
       "      <td>Biography|Drama|History</td>\n",
       "      <td>2017</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>29625</th>\n",
       "      <td>7</td>\n",
       "      <td>5.428571</td>\n",
       "      <td>2018-06-22 18:41:20</td>\n",
       "      <td>5466186</td>\n",
       "      <td>Entebbe (2018)</td>\n",
       "      <td>Crime|Drama|History</td>\n",
       "      <td>2018</td>\n",
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       "      <td>0</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "<p>20 rows × 38 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       ratings  avg_rating           rated_last  movie_id  \\\n",
       "30587       35    9.200000  2018-06-22 22:19:09   6316138   \n",
       "30503        6    8.833333  2018-06-11 04:06:25   6223974   \n",
       "30862        6    8.333333  2018-03-18 13:27:52   6794424   \n",
       "28997     1618    7.982695  2018-06-25 02:12:19   5013056   \n",
       "30891       64    7.953125  2018-06-22 22:48:04   6878038   \n",
       "30220       18    7.944444  2018-06-24 13:06:26   5969696   \n",
       "28273      487    7.895277  2018-06-25 02:47:00   4555426   \n",
       "28946       11    7.363636  2018-05-29 17:22:48   4977530   \n",
       "30569      320    7.331250  2018-06-23 11:31:29   6294822   \n",
       "30063       78    7.256410  2018-05-27 21:41:50   5816682   \n",
       "19382       70    7.214286  2018-06-05 19:32:24   1730768   \n",
       "30187       16    7.187500  2018-06-20 05:40:57   5935704   \n",
       "28777       25    7.040000  2018-03-14 15:49:37   4882376   \n",
       "29406        7    7.000000  2018-05-28 06:24:27   5270948   \n",
       "30738        7    7.000000  2018-04-07 16:05:34   6537238   \n",
       "17522      120    6.800000  2018-06-25 01:06:55   1413492   \n",
       "28538       36    6.388889  2018-06-17 14:13:05   4703048   \n",
       "29270       21    6.333333  2018-04-30 02:49:17   5175450   \n",
       "23962       20    6.150000  2018-03-18 21:40:48   2674454   \n",
       "29625        7    5.428571  2018-06-22 18:41:20   5466186   \n",
       "\n",
       "                                                   movie  \\\n",
       "30587                   Ayla: The Daughter of War (2017)   \n",
       "30503                                The Farthest (2017)   \n",
       "30862                                       LA 92 (2017)   \n",
       "28997                                     Dunkirk (2017)   \n",
       "30891                            Taeksi Woonjunsa (2017)   \n",
       "30220                       The Battleship Island (2017)   \n",
       "28273                                Darkest Hour (2017)   \n",
       "28946                             Viceroy's House (2017)   \n",
       "30569                                    The Post (2017)   \n",
       "30063                          Victoria and Abdul (2017)   \n",
       "19382                        The Zookeeper's Wife (2017)   \n",
       "30187                                   Padmaavat (2018)   \n",
       "28777  First They Killed My Father: A Daughter of Cam...   \n",
       "29406                              Chappaquiddick (2017)   \n",
       "30738                                    Salyut-7 (2017)   \n",
       "17522                                   12 Strong (2018)   \n",
       "28538                                      6 Days (2017)   \n",
       "29270  Mark Felt: The Man Who Brought Down the White ...   \n",
       "23962                                   Churchill (2017)   \n",
       "29625                                     Entebbe (2018)   \n",
       "\n",
       "                         genre  date  1800's  1900's  2000's    ...     \\\n",
       "30587        Drama|History|War  2017       0       0       1    ...      \n",
       "30503      Documentary|History  2017       0       0       1    ...      \n",
       "30862      Documentary|History  2017       0       0       1    ...      \n",
       "28997     Action|Drama|History  2017       0       0       1    ...      \n",
       "30891     Action|Drama|History  2017       0       0       1    ...      \n",
       "30220     Action|Drama|History  2017       0       0       1    ...      \n",
       "28273  Biography|Drama|History  2017       0       0       1    ...      \n",
       "28946            Drama|History  2017       0       0       1    ...      \n",
       "30569  Biography|Drama|History  2017       0       0       1    ...      \n",
       "30063  Biography|Drama|History  2017       0       0       1    ...      \n",
       "19382  Biography|Drama|History  2017       0       0       1    ...      \n",
       "30187    Drama|History|Romance  2018       0       0       1    ...      \n",
       "28777  Biography|Drama|History  2017       0       0       1    ...      \n",
       "29406   Drama|History|Thriller  2017       0       0       1    ...      \n",
       "30738     Action|Drama|History  2017       0       0       1    ...      \n",
       "17522     Action|Drama|History  2018       0       0       1    ...      \n",
       "28538     Action|Drama|History  2017       0       0       1    ...      \n",
       "29270  Biography|Drama|History  2017       0       0       1    ...      \n",
       "23962  Biography|Drama|History  2017       0       0       1    ...      \n",
       "29625      Crime|Drama|History  2018       0       0       1    ...      \n",
       "\n",
       "       Fantasy  Romance  Game-Show  Action  Documentary  Animation  Comedy  \\\n",
       "30587        0        0          0       0            0          0       0   \n",
       "30503        0        0          0       0            1          0       0   \n",
       "30862        0        0          0       0            1          0       0   \n",
       "28997        0        0          0       1            0          0       0   \n",
       "30891        0        0          0       1            0          0       0   \n",
       "30220        0        0          0       1            0          0       0   \n",
       "28273        0        0          0       0            0          0       0   \n",
       "28946        0        0          0       0            0          0       0   \n",
       "30569        0        0          0       0            0          0       0   \n",
       "30063        0        0          0       0            0          0       0   \n",
       "19382        0        0          0       0            0          0       0   \n",
       "30187        0        1          0       0            0          0       0   \n",
       "28777        0        0          0       0            0          0       0   \n",
       "29406        0        0          0       0            0          0       0   \n",
       "30738        0        0          0       1            0          0       0   \n",
       "17522        0        0          0       1            0          0       0   \n",
       "28538        0        0          0       1            0          0       0   \n",
       "29270        0        0          0       0            0          0       0   \n",
       "23962        0        0          0       0            0          0       0   \n",
       "29625        0        0          0       0            0          0       0   \n",
       "\n",
       "       Short  Western  Thriller  \n",
       "30587      0        0         0  \n",
       "30503      0        0         0  \n",
       "30862      0        0         0  \n",
       "28997      0        0         0  \n",
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       "30220      0        0         0  \n",
       "28273      0        0         0  \n",
       "28946      0        0         0  \n",
       "30569      0        0         0  \n",
       "30063      0        0         0  \n",
       "19382      0        0         0  \n",
       "30187      0        0         0  \n",
       "28777      0        0         0  \n",
       "29406      0        0         1  \n",
       "30738      0        0         0  \n",
       "17522      0        0         0  \n",
       "28538      0        0         0  \n",
       "29270      0        0         0  \n",
       "23962      0        0         0  \n",
       "29625      0        0         0  \n",
       "\n",
       "[20 rows x 38 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "recommend_filtered('1', 20, years=['2017', '2018'], genres=['History'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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