Projects/Anime Recommendation.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import warnings\n",
    "\n",
    "# Ignore specific warning temporarily\n",
    "with warnings.catch_warnings():\n",
    "    warnings.filterwarnings(\"ignore\", message=\"Number of labels is 1.*\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Import data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>Score</th>\n",
       "      <th>Genres</th>\n",
       "      <th>Type</th>\n",
       "      <th>Episodes</th>\n",
       "      <th>Aired</th>\n",
       "      <th>Premiered</th>\n",
       "      <th>Producers</th>\n",
       "      <th>Licensors</th>\n",
       "      <th>Studios</th>\n",
       "      <th>...</th>\n",
       "      <th>Score-10</th>\n",
       "      <th>Score-9</th>\n",
       "      <th>Score-8</th>\n",
       "      <th>Score-7</th>\n",
       "      <th>Score-6</th>\n",
       "      <th>Score-5</th>\n",
       "      <th>Score-4</th>\n",
       "      <th>Score-3</th>\n",
       "      <th>Score-2</th>\n",
       "      <th>Score-1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Cowboy Bebop</td>\n",
       "      <td>8.78</td>\n",
       "      <td>Action, Adventure, Comedy, Drama, Sci-Fi, Space</td>\n",
       "      <td>TV</td>\n",
       "      <td>26</td>\n",
       "      <td>Apr 3, 1998 to Apr 24, 1999</td>\n",
       "      <td>Spring 1998</td>\n",
       "      <td>Bandai Visual</td>\n",
       "      <td>Funimation, Bandai Entertainment</td>\n",
       "      <td>Sunrise</td>\n",
       "      <td>...</td>\n",
       "      <td>229170.0</td>\n",
       "      <td>182126.0</td>\n",
       "      <td>131625.0</td>\n",
       "      <td>62330.0</td>\n",
       "      <td>20688.0</td>\n",
       "      <td>8904.0</td>\n",
       "      <td>3184.0</td>\n",
       "      <td>1357.0</td>\n",
       "      <td>741.0</td>\n",
       "      <td>1580.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Cowboy Bebop: Tengoku no Tobira</td>\n",
       "      <td>8.39</td>\n",
       "      <td>Action, Drama, Mystery, Sci-Fi, Space</td>\n",
       "      <td>Movie</td>\n",
       "      <td>1</td>\n",
       "      <td>Sep 1, 2001</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Sunrise, Bandai Visual</td>\n",
       "      <td>Sony Pictures Entertainment</td>\n",
       "      <td>Bones</td>\n",
       "      <td>...</td>\n",
       "      <td>30043.0</td>\n",
       "      <td>49201.0</td>\n",
       "      <td>49505.0</td>\n",
       "      <td>22632.0</td>\n",
       "      <td>5805.0</td>\n",
       "      <td>1877.0</td>\n",
       "      <td>577.0</td>\n",
       "      <td>221.0</td>\n",
       "      <td>109.0</td>\n",
       "      <td>379.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Trigun</td>\n",
       "      <td>8.24</td>\n",
       "      <td>Action, Sci-Fi, Adventure, Comedy, Drama, Shounen</td>\n",
       "      <td>TV</td>\n",
       "      <td>26</td>\n",
       "      <td>Apr 1, 1998 to Sep 30, 1998</td>\n",
       "      <td>Spring 1998</td>\n",
       "      <td>Victor Entertainment</td>\n",
       "      <td>Funimation, Geneon Entertainment USA</td>\n",
       "      <td>Madhouse</td>\n",
       "      <td>...</td>\n",
       "      <td>50229.0</td>\n",
       "      <td>75651.0</td>\n",
       "      <td>86142.0</td>\n",
       "      <td>49432.0</td>\n",
       "      <td>15376.0</td>\n",
       "      <td>5838.0</td>\n",
       "      <td>1965.0</td>\n",
       "      <td>664.0</td>\n",
       "      <td>316.0</td>\n",
       "      <td>533.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Witch Hunter Robin</td>\n",
       "      <td>7.27</td>\n",
       "      <td>Action, Mystery, Police, Supernatural, Drama, ...</td>\n",
       "      <td>TV</td>\n",
       "      <td>26</td>\n",
       "      <td>Jul 2, 2002 to Dec 24, 2002</td>\n",
       "      <td>Summer 2002</td>\n",
       "      <td>TV Tokyo, Bandai Visual, Dentsu, Victor Entert...</td>\n",
       "      <td>Funimation, Bandai Entertainment</td>\n",
       "      <td>Sunrise</td>\n",
       "      <td>...</td>\n",
       "      <td>2182.0</td>\n",
       "      <td>4806.0</td>\n",
       "      <td>10128.0</td>\n",
       "      <td>11618.0</td>\n",
       "      <td>5709.0</td>\n",
       "      <td>2920.0</td>\n",
       "      <td>1083.0</td>\n",
       "      <td>353.0</td>\n",
       "      <td>164.0</td>\n",
       "      <td>131.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Bouken Ou Beet</td>\n",
       "      <td>6.98</td>\n",
       "      <td>Adventure, Fantasy, Shounen, Supernatural</td>\n",
       "      <td>TV</td>\n",
       "      <td>52</td>\n",
       "      <td>Sep 30, 2004 to Sep 29, 2005</td>\n",
       "      <td>Fall 2004</td>\n",
       "      <td>TV Tokyo, Dentsu</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Toei Animation</td>\n",
       "      <td>...</td>\n",
       "      <td>312.0</td>\n",
       "      <td>529.0</td>\n",
       "      <td>1242.0</td>\n",
       "      <td>1713.0</td>\n",
       "      <td>1068.0</td>\n",
       "      <td>634.0</td>\n",
       "      <td>265.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>27.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 32 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                              Name Score  \\\n",
       "0                     Cowboy Bebop  8.78   \n",
       "1  Cowboy Bebop: Tengoku no Tobira  8.39   \n",
       "2                           Trigun  8.24   \n",
       "3               Witch Hunter Robin  7.27   \n",
       "4                   Bouken Ou Beet  6.98   \n",
       "\n",
       "                                              Genres   Type Episodes  \\\n",
       "0    Action, Adventure, Comedy, Drama, Sci-Fi, Space     TV       26   \n",
       "1              Action, Drama, Mystery, Sci-Fi, Space  Movie        1   \n",
       "2  Action, Sci-Fi, Adventure, Comedy, Drama, Shounen     TV       26   \n",
       "3  Action, Mystery, Police, Supernatural, Drama, ...     TV       26   \n",
       "4          Adventure, Fantasy, Shounen, Supernatural     TV       52   \n",
       "\n",
       "                          Aired    Premiered  \\\n",
       "0   Apr 3, 1998 to Apr 24, 1999  Spring 1998   \n",
       "1                   Sep 1, 2001      Unknown   \n",
       "2   Apr 1, 1998 to Sep 30, 1998  Spring 1998   \n",
       "3   Jul 2, 2002 to Dec 24, 2002  Summer 2002   \n",
       "4  Sep 30, 2004 to Sep 29, 2005    Fall 2004   \n",
       "\n",
       "                                           Producers  \\\n",
       "0                                      Bandai Visual   \n",
       "1                             Sunrise, Bandai Visual   \n",
       "2                               Victor Entertainment   \n",
       "3  TV Tokyo, Bandai Visual, Dentsu, Victor Entert...   \n",
       "4                                   TV Tokyo, Dentsu   \n",
       "\n",
       "                              Licensors         Studios  ...  Score-10  \\\n",
       "0      Funimation, Bandai Entertainment         Sunrise  ...  229170.0   \n",
       "1           Sony Pictures Entertainment           Bones  ...   30043.0   \n",
       "2  Funimation, Geneon Entertainment USA        Madhouse  ...   50229.0   \n",
       "3      Funimation, Bandai Entertainment         Sunrise  ...    2182.0   \n",
       "4                               Unknown  Toei Animation  ...     312.0   \n",
       "\n",
       "    Score-9   Score-8  Score-7  Score-6  Score-5  Score-4  Score-3  Score-2  \\\n",
       "0  182126.0  131625.0  62330.0  20688.0   8904.0   3184.0   1357.0    741.0   \n",
       "1   49201.0   49505.0  22632.0   5805.0   1877.0    577.0    221.0    109.0   \n",
       "2   75651.0   86142.0  49432.0  15376.0   5838.0   1965.0    664.0    316.0   \n",
       "3    4806.0   10128.0  11618.0   5709.0   2920.0   1083.0    353.0    164.0   \n",
       "4     529.0    1242.0   1713.0   1068.0    634.0    265.0     83.0     50.0   \n",
       "\n",
       "   Score-1  \n",
       "0   1580.0  \n",
       "1    379.0  \n",
       "2    533.0  \n",
       "3    131.0  \n",
       "4     27.0  \n",
       "\n",
       "[5 rows x 32 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "data = pd.read_csv('data/Anime Recommendation/anime.csv')\n",
    "\n",
    "# We only need one identifier for the animes, in this case we will use the name\n",
    "data.drop(columns = ['MAL_ID', 'English name', 'Japanese name'], inplace = True)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Explore the dataset\n",
    "* Do we have null data?\n",
    "* Are there duplicated values?\n",
    "* What type of data is each column?\n",
    "* The categorical data has levels (easy - difficult or less - more)?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. Do we have null data?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.isnull().sum().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This can also exist as a string such as 'Unknown' or 'Undefined', in data frame we can see there are some 'Unknown', lets find which features have this as categorical data, and how much it represents in percentage of the whole dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Unkwnowns in Score: 29.273431272064684%\n",
      "Unkwnowns in Genres: 0.358729074137342%\n",
      "Unkwnowns in Type: 0.21068215465208973%\n",
      "Unkwnowns in Episodes: 2.9381619405534676%\n",
      "Unkwnowns in Aired: 1.759480696959344%\n",
      "Unkwnowns in Premiered: 72.98143719394146%\n",
      "Unkwnowns in Producers: 44.379911171848306%\n",
      "Unkwnowns in Licensors: 77.53103291196902%\n",
      "Unkwnowns in Studios: 40.30862088600387%\n",
      "Unkwnowns in Source: 20.31089853091903%\n",
      "Unkwnowns in Duration: 3.160232319781346%\n",
      "Unkwnowns in Rating: 3.9175492540712904%\n",
      "Unkwnowns in Ranked: 10.033025851269787%\n",
      "Unkwnowns in Score-10: 2.4883270698098165%\n",
      "Unkwnowns in Score-9: 18.033253615761303%\n",
      "Unkwnowns in Score-8: 7.806627946703109%\n",
      "Unkwnowns in Score-7: 2.8641384808108414%\n",
      "Unkwnowns in Score-6: 2.9096913791139962%\n",
      "Unkwnowns in Score-5: 3.3253615761302813%\n",
      "Unkwnowns in Score-4: 5.563147705272748%\n",
      "Unkwnowns in Score-3: 7.442204760277873%\n",
      "Unkwnowns in Score-2: 9.093497323767224%\n",
      "Unkwnowns in Score-1: 2.6135975401434917%\n"
     ]
    }
   ],
   "source": [
    "categorical_data = data.columns[data.dtypes == object]\n",
    "unknown_cat = []\n",
    "percentages = []\n",
    "for cat in categorical_data:\n",
    "    if 'Unknown' in data[cat].unique():\n",
    "        unknown_cat.append(cat)\n",
    "        percentages.append(len(data[data[cat] == 'Unknown'])*100/len(data))\n",
    "        print(f\"Unkwnowns in {cat}: {len(data[data[cat] == 'Unknown'])*100/len(data)}%\")\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "# Combine the categories and values, then sort them by value in decreasing order\n",
    "sorted_data = sorted(zip(unknown_cat, percentages), key=lambda x: x[1], reverse=True)\n",
    "sorted_categories, sorted_values = zip(*sorted_data)\n",
    "\n",
    "# Plotting\n",
    "plt.figure(figsize=(10, 6))\n",
    "plt.barh(sorted_categories, sorted_values, color='skyblue')\n",
    "plt.xlabel('Category')\n",
    "plt.ylabel('Unknown data (%)')\n",
    "plt.title('Unknown values per feature')\n",
    "plt.gca().invert_yaxis()  # Invert y-axis to have the highest value on top\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. Are there duplicated values?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.duplicated().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. What type of data is each column?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Name             object\n",
       "Score            object\n",
       "Genres           object\n",
       "Type             object\n",
       "Episodes         object\n",
       "Aired            object\n",
       "Premiered        object\n",
       "Producers        object\n",
       "Licensors        object\n",
       "Studios          object\n",
       "Source           object\n",
       "Duration         object\n",
       "Rating           object\n",
       "Ranked           object\n",
       "Popularity        int64\n",
       "Members           int64\n",
       "Favorites         int64\n",
       "Watching          int64\n",
       "Completed         int64\n",
       "On-Hold           int64\n",
       "Dropped           int64\n",
       "Plan to Watch     int64\n",
       "Score-10         object\n",
       "Score-9          object\n",
       "Score-8          object\n",
       "Score-7          object\n",
       "Score-6          object\n",
       "Score-5          object\n",
       "Score-4          object\n",
       "Score-3          object\n",
       "Score-2          object\n",
       "Score-1          object\n",
       "dtype: object"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.dtypes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can see that numerical data (for example the scores) are objects instead of floats"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## The categorical data has levels?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Name: ['Cowboy Bebop' 'Cowboy Bebop: Tengoku no Tobira' 'Trigun' ...\n",
      " 'Higurashi no Naku Koro ni Sotsu' 'Yama no Susume: Next Summit'\n",
      " 'Scarlet Nexus']\n",
      "\n",
      "Genres: ['Action, Adventure, Comedy, Drama, Sci-Fi, Space'\n",
      " 'Action, Drama, Mystery, Sci-Fi, Space'\n",
      " 'Action, Sci-Fi, Adventure, Comedy, Drama, Shounen' ...\n",
      " 'Horror, Demons, Supernatural, Thriller' 'Sci-Fi, Space, Vampire'\n",
      " 'Adventure, Mystery, Supernatural']\n",
      "\n",
      "Type: ['TV' 'Movie' 'OVA' 'Special' 'ONA' 'Music' 'Unknown']\n",
      "\n",
      "Aired: ['Apr 3, 1998 to Apr 24, 1999' 'Sep 1, 2001' 'Apr 1, 1998 to Sep 30, 1998'\n",
      " ... 'Sep 10, 2021 to ?' 'Mar 14, 2021' 'Mar 17, 2021 to ?']\n",
      "\n",
      "Premiered: ['Spring 1998' 'Unknown' 'Summer 2002' 'Fall 2004' 'Spring 2005'\n",
      " 'Fall 2002' 'Spring 2004' 'Fall 1999' 'Fall 2001' 'Spring 2003'\n",
      " 'Fall 1995' 'Fall 1997' 'Winter 1996' 'Spring 2002' 'Winter 2005'\n",
      " 'Spring 2001' 'Spring 1999' 'Fall 2003' 'Summer 2003' 'Summer 2004'\n",
      " 'Fall 2005' 'Winter 2002' 'Summer 2005' 'Spring 1979' 'Spring 1985'\n",
      " 'Spring 1986' 'Spring 1993' 'Spring 1995' 'Spring 1996' 'Spring 1994'\n",
      " 'Winter 1994' 'Spring 2000' 'Fall 1996' 'Spring 1997' 'Winter 2004'\n",
      " 'Winter 1998' 'Summer 2001' 'Winter 1999' 'Fall 1998' 'Fall 1993'\n",
      " 'Summer 2000' 'Fall 2000' 'Winter 2003' 'Spring 1989' 'Winter 1986'\n",
      " 'Summer 1997' 'Summer 1999' 'Winter 1979' 'Winter 2001' 'Spring 1978'\n",
      " 'Winter 1973' 'Spring 1991' 'Fall 1973' 'Fall 1989' 'Fall 1994'\n",
      " 'Winter 1992' 'Fall 1979' 'Summer 1998' 'Winter 2000' 'Winter 2006'\n",
      " 'Summer 1995' 'Fall 1992' 'Summer 1985' 'Spring 1973' 'Spring 1984'\n",
      " 'Spring 1982' 'Spring 1992' 'Winter 1993' 'Summer 2006' 'Fall 1985'\n",
      " 'Winter 1991' 'Spring 1987' 'Spring 2006' 'Summer 1991' 'Winter 1987'\n",
      " 'Winter 1997' 'Winter 1995' 'Spring 1988' 'Summer 1987' 'Winter 1983'\n",
      " 'Spring 1980' 'Winter 1990' 'Spring 1976' 'Fall 1984' 'Fall 1991'\n",
      " 'Summer 1977' 'Fall 1982' 'Fall 1988' 'Summer 1994' 'Spring 1990'\n",
      " 'Fall 1986' 'Summer 1982' 'Spring 2007' 'Fall 1981' 'Summer 1984'\n",
      " 'Fall 1971' 'Fall 1977' 'Spring 1967' 'Spring 1981' 'Summer 1975'\n",
      " 'Fall 2006' 'Summer 1996' 'Fall 1978' 'Summer 1965' 'Winter 1970'\n",
      " 'Fall 1965' 'Winter 2007' 'Winter 1989' 'Fall 1974' 'Fall 1980'\n",
      " 'Winter 1976' 'Summer 2007' 'Summer 1980' 'Fall 2007' 'Summer 1983'\n",
      " 'Fall 1975' 'Spring 1977' 'Fall 1983' 'Spring 1975' 'Winter 2008'\n",
      " 'Winter 1980' 'Spring 1983' 'Winter 1974' 'Fall 1987' 'Summer 1990'\n",
      " 'Summer 1972' 'Winter 1982' 'Spring 1970' 'Fall 1972' 'Fall 1969'\n",
      " 'Summer 1981' 'Winter 1981' 'Winter 1985' 'Winter 1978' 'Winter 1975'\n",
      " 'Winter 1988' 'Fall 1966' 'Winter 1972' 'Winter 1977' 'Winter 1984'\n",
      " 'Fall 1963' 'Winter 1967' 'Spring 1972' 'Winter 1963' 'Fall 1976'\n",
      " 'Summer 1992' 'Spring 1974' 'Spring 2008' 'Spring 1968' 'Summer 1988'\n",
      " 'Winter 1969' 'Summer 1978' 'Fall 2009' 'Fall 2008' 'Summer 2008'\n",
      " 'Spring 2009' 'Summer 1986' 'Winter 1971' 'Winter 2009' 'Fall 1990'\n",
      " 'Spring 1971' 'Fall 1970' 'Fall 1968' 'Spring 2010' 'Spring 1969'\n",
      " 'Summer 2009' 'Winter 2010' 'Summer 1976' 'Summer 2010' 'Winter 1968'\n",
      " 'Summer 1979' 'Fall 2010' 'Fall 2011' 'Spring 2011' 'Winter 2011'\n",
      " 'Summer 2011' 'Spring 1965' 'Spring 2012' 'Summer 1989' 'Fall 1967'\n",
      " 'Winter 2012' 'Spring 1966' 'Fall 2013' 'Summer 1974' 'Spring 1964'\n",
      " 'Winter 1966' 'Summer 2012' 'Fall 2012' 'Summer 2013' 'Spring 2013'\n",
      " 'Winter 1964' 'Summer 1966' 'Winter 1965' 'Summer 1964' 'Winter 2013'\n",
      " 'Spring 1961' 'Summer 1962' 'Winter 2014' 'Summer 1967' 'Winter 2015'\n",
      " 'Fall 2014' 'Spring 2015' 'Spring 2014' 'Summer 2014' 'Summer 2015'\n",
      " 'Summer 2018' 'Summer 1970' 'Fall 2015' 'Spring 2017' 'Winter 2016'\n",
      " 'Spring 2016' 'Winter 2017' 'Summer 2016' 'Fall 2016' 'Spring 2018'\n",
      " 'Fall 2017' 'Winter 2019' 'Summer 2019' 'Summer 2017' 'Winter 2021'\n",
      " 'Winter 2018' 'Summer 2021' 'Spring 2019' 'Winter 2020' 'Fall 2018'\n",
      " 'Fall 2019' 'Summer 2020' 'Fall 2020' 'Spring 2020' 'Fall 2021'\n",
      " 'Spring 2021']\n",
      "\n",
      "Producers: ['Bandai Visual' 'Sunrise, Bandai Visual' 'Victor Entertainment' ...\n",
      " 'flying DOG, Hakuhodo DY Music & Pictures' 'Bandai Spirits'\n",
      " 'Bushiroad, Bit grooove promotion']\n",
      "\n",
      "Licensors: ['Funimation, Bandai Entertainment' 'Sony Pictures Entertainment'\n",
      " 'Funimation, Geneon Entertainment USA' 'Unknown'\n",
      " 'VIZ Media, Sentai Filmworks' 'VIZ Media, Discotek Media' 'Funimation'\n",
      " 'VIZ Media' 'Funimation, 4Kids Entertainment' 'Nozomi Entertainment'\n",
      " 'Geneon Entertainment USA' 'ADV Films, Netflix' 'Manga Entertainment'\n",
      " 'Media Blasters, NYAV Post' 'ADV Films, Aniplex of America'\n",
      " 'Media Blasters'\n",
      " 'Funimation, Bandai Entertainment, Geneon Entertainment USA' 'AnimEigo'\n",
      " 'ADV Films, Sentai Filmworks'\n",
      " 'Sentai Filmworks, Geneon Entertainment USA' 'ADV Films'\n",
      " 'Bandai Entertainment' 'ADV Films, Funimation'\n",
      " 'ADV Films, Discotek Media' 'Discotek Media, Geneon Entertainment USA'\n",
      " 'Sentai Filmworks' 'ADV Films, Funimation, Kadokawa Pictures USA'\n",
      " 'Nozomi Entertainment, Bandai Entertainment'\n",
      " 'Bandai Entertainment, NYAV Post'\n",
      " 'ADV Films, Sentai Filmworks, Discotek Media'\n",
      " 'Nozomi Entertainment, Geneon Entertainment USA'\n",
      " 'Funimation, Aniplex of America'\n",
      " 'Media Blasters, Geneon Entertainment USA'\n",
      " 'Media Blasters, Discotek Media, Tokyopop' '4Kids Entertainment'\n",
      " 'Funimation, Sentai Filmworks' 'Nozomi Entertainment, Maiden Japan'\n",
      " 'Central Park Media' 'GKIDS'\n",
      " 'Bandai Entertainment, Sentai Filmworks, Discotek Media'\n",
      " 'Flatiron Film Company, Geneon Entertainment USA' 'Urban Vision'\n",
      " 'Funimation, Tokyopop' 'Bandai Entertainment, Discotek Media'\n",
      " 'Walt Disney Studios, GKIDS' 'NuTech Digital'\n",
      " 'Funimation, Central Park Media'\n",
      " 'Aniplex of America, Manga Entertainment'\n",
      " 'Aniplex of America, Geneon Entertainment USA' 'Adult Source Media'\n",
      " 'Central Park Media, Discotek Media' 'SoftCel Pictures'\n",
      " 'ADV Films, Nozomi Entertainment' 'Media Blasters, SoftCel Pictures'\n",
      " 'Funimation, Synch-Point' 'Nozomi Entertainment, NYAV Post'\n",
      " 'Nelvana, NIS America, Inc., Geneon Entertainment USA'\n",
      " 'Funimation, Crunchyroll' 'Discotek Media, Tokyopop' 'Tokyopop'\n",
      " 'Bandai Visual USA' 'VIZ Media, Flatiron Film Company' 'Discotek Media'\n",
      " 'Media Blasters, Maiden Japan'\n",
      " 'ADV Films, Media Blasters, Discotek Media' 'Maiden Japan'\n",
      " 'Bandai Entertainment, Sentai Filmworks' 'Anime Midstream'\n",
      " 'Nelvana, Discotek Media' 'Nozomi Entertainment, Discotek Media'\n",
      " 'Sentai Filmworks, Synch-Point' 'Central Park Media, Maiden Japan'\n",
      " 'Sentai Filmworks, Urban Vision' 'Media Blasters, Discotek Media'\n",
      " 'Bandai Entertainment, Central Park Media'\n",
      " 'Nelvana, Discotek Media, Geneon Entertainment USA' 'Walt Disney Studios'\n",
      " 'Media Blasters, Central Park Media, Discotek Media'\n",
      " 'GKIDS, Manga Entertainment' 'Nozomi Entertainment, Central Park Media'\n",
      " 'Bandai Entertainment, Manga Entertainment'\n",
      " '4Kids Entertainment, Flatiron Film Company'\n",
      " 'VIZ Media, 4Kids Entertainment'\n",
      " '4Kids Entertainment, Warner Bros. Pictures'\n",
      " 'ADV Films, VIZ Media, DiC Entertainment'\n",
      " 'VIZ Media, Geneon Entertainment USA'\n",
      " 'Funimation, Central Park Media, Enoki Films'\n",
      " 'Discotek Media, Urban Vision' 'ADV Films, Maiden Japan'\n",
      " 'Saban Entertainment, Flatiron Film Company'\n",
      " 'Bandai Entertainment, Bandai Visual USA'\n",
      " 'ADV Films, Central Park Media, Sentai Filmworks'\n",
      " 'Funimation, Manga Entertainment'\n",
      " 'Nozomi Entertainment, Crimson Star Media'\n",
      " 'Nozomi Entertainment, Media Blasters' 'Synch-Point'\n",
      " 'Sentai Filmworks, Manga Entertainment'\n",
      " 'Nozomi Entertainment, Media Blasters, NYAV Post'\n",
      " 'Bandai Entertainment, Media Blasters' 'ADV Films, AnimEigo'\n",
      " 'Super Techno Arts' 'ADV Films, Manga Entertainment'\n",
      " 'Tokyopop, Maiden Japan' 'Kitty Media' 'Media Blasters, Kitty Media'\n",
      " 'Sony Pictures Entertainment, GKIDS' 'ADV Films, Central Park Media'\n",
      " 'Funimation, Bandai Entertainment, Kadokawa Pictures USA'\n",
      " 'Flatiron Film Company' 'ADV Films, Funimation, NYAV Post'\n",
      " 'Funimation, Media Blasters' 'ADV Films, Funimation, OLM Digital'\n",
      " 'Anchor Bay Films' 'Sentai Filmworks, Crunchyroll'\n",
      " 'Discotek Media, Manga Entertainment' \"Brain's Base, Discotek Media\"\n",
      " 'Nozomi Entertainment, Kadokawa Pictures USA' 'Bandai'\n",
      " 'Discotek Media, Bandai Visual USA' 'Funimation, Kadokawa Pictures USA'\n",
      " 'Eleven Arts, DreamWorks'\n",
      " 'Maiden Japan, Manga Entertainment, Bandai Visual USA'\n",
      " 'Geneon Universal Entertainment, Funimation'\n",
      " 'Maiden Japan, Geneon Entertainment USA' 'AnimEigo, Discotek Media'\n",
      " '4Kids Entertainment, Warner Bros. Japan'\n",
      " '4Kids Entertainment, Miramax Films' 'Saban Entertainment'\n",
      " 'ADV Films, Discotek Media, Shout! Factory'\n",
      " 'Media Blasters, Central Park Media'\n",
      " 'Funimation, Sentai Filmworks, Geneon Entertainment USA' 'Shout! Factory'\n",
      " 'Funimation, Discotek Media, Geneon Entertainment USA'\n",
      " 'ADV Films, DiC Entertainment, Flatiron Film Company'\n",
      " 'Discotek Media, Saban Entertainment'\n",
      " 'Central Park Media, Critical Mass Video'\n",
      " 'Media Blasters, Sentai Filmworks' 'Warner Bros. Japan'\n",
      " 'ADV Films, SoftCel Pictures' 'NuTech Digital, Critical Mass Video'\n",
      " 'Critical Mass Video' 'Funimation, Discotek Media'\n",
      " 'Sony Pictures Entertainment, Discotek Media'\n",
      " 'ADV Films, Central Park Media, Discotek Media'\n",
      " '4Kids Entertainment, The Pokemon Company International'\n",
      " 'Bandai Entertainment, Media Blasters, Bandai Visual USA'\n",
      " 'VIZ Media, 4Kids Entertainment, The Pokemon Company International'\n",
      " 'VIZ Media, The Pokemon Company International' 'Voyager Entertainment'\n",
      " 'Nelvana' 'Hasbro'\n",
      " 'ADV Films, Bandai Entertainment, Discotek Media, Crunchyroll'\n",
      " 'Enoki Films'\n",
      " 'Bandai Entertainment, Discotek Media, NYAV Post, Bandai Visual USA'\n",
      " 'ADV Films, Media Blasters' '4Kids Entertainment, Discotek Media'\n",
      " 'Geneon Universal Entertainment'\n",
      " 'VIZ Media, Media Blasters, Sentai Filmworks, Geneon Entertainment USA'\n",
      " 'Kadokawa Pictures USA' 'Bandai Entertainment, Maiden Japan' 'JapanAnime'\n",
      " 'Nozomi Entertainment, Bandai Visual USA' 'Enoki Films, Urban Vision'\n",
      " 'ADV Films, Bandai Entertainment, Aniplex of America'\n",
      " 'Maiden Japan, Bandai Visual USA'\n",
      " 'Bandai Entertainment, Discotek Media, Bandai Visual USA'\n",
      " 'Warner Bros. Pictures' 'NuTech Digital, Kitty Media'\n",
      " 'Media Blasters, Discotek Media, NYAV Post'\n",
      " 'Walt Disney Studios, Hasbro, Saban Entertainment'\n",
      " '4Kids Entertainment, Enoki Films, Discotek Media'\n",
      " 'Media Blasters, Discotek Media, NYAV Post, Manga Entertainment'\n",
      " 'Saban Brands' 'Pioneer LDC' 'Aniplex of America' 'Capcom'\n",
      " 'The Pokemon Company International'\n",
      " 'Sentai Filmworks, Saban Entertainment' 'ADV Films, Warner Bros. Japan'\n",
      " 'Central Park Media, NYAV Post' 'Cinelicious Pics' 'NIS America, Inc.'\n",
      " 'Central Park Media, Sentai Filmworks, Discotek Media'\n",
      " 'NuTech Digital, Central Park Media' 'NuTech Digital, Adult Source Media'\n",
      " 'Funimation, NYAV Post' 'Pied Piper'\n",
      " 'Bandai Entertainment, Sentai Filmworks, NYAV Post' 'NYAV Post'\n",
      " 'Anchor Bay Films, Manga Entertainment'\n",
      " 'Funimation, Warner Bros. Japan, GKIDS'\n",
      " 'Nozomi Entertainment, Bandai Entertainment, NYAV Post'\n",
      " 'Marvel Entertainment' '4Kids Entertainment, Nintendo of America'\n",
      " 'Funimation, Nozomi Entertainment' 'Dentsu Entertainment USA'\n",
      " 'NYAV Post, Pied Piper' 'NYAV Post, GKIDS' 'Sentai Filmworks, NYAV Post'\n",
      " 'Bandai Entertainment, Aniplex of America'\n",
      " 'NIS America, Inc., Aniplex of America' 'Konami, 4Kids Entertainment'\n",
      " 'Bandai, Sentai Filmworks' 'VIZ Media, NYAV Post' 'Eleven Arts'\n",
      " 'Cookie Jar Entertainment' 'VIZ Media, Warner Bros. Pictures' 'Active'\n",
      " 'Ketchup Entertainment' 'Discotek Media, Crunchyroll' 'Kadokawa'\n",
      " 'Funimation, Discotek Media, Crunchyroll' 'Crunchyroll' 'Netflix'\n",
      " 'Ponycan USA' 'Eleven Arts, NYAV Post' 'bilibili'\n",
      " 'Haoliners Animation League' 'Aniplex of America, Crunchyroll' 'feel.'\n",
      " 'B.CMAY PICTURES' 'Funimation, NBCUniversal Entertainment Japan'\n",
      " 'Bandai Namco Games' 'Eleven Arts, Ponycan USA'\n",
      " 'Eleven Arts, Shout! Factory' 'Warner Bros. Japan, Crunchyroll'\n",
      " 'Sentai Filmworks, Ponycan USA' 'Discotek Media, Ponycan USA'\n",
      " 'Media Bank' 'Sentai Filmworks, Kadokawa' 'iQIYI']\n",
      "\n",
      "Studios: ['Sunrise' 'Bones' 'Madhouse' ... 'Fanworks, Space Neko Company' 'OZ'\n",
      " 'Studio Kafka']\n",
      "\n",
      "Source: ['Original' 'Manga' 'Light novel' 'Game' 'Visual novel' '4-koma manga'\n",
      " 'Novel' 'Unknown' 'Other' 'Picture book' 'Web manga' 'Music' 'Radio'\n",
      " 'Book' 'Card game' 'Digital manga']\n",
      "\n",
      "Duration: ['24 min. per ep.' '1 hr. 55 min.' '25 min. per ep.' '23 min. per ep.'\n",
      " '27 min. per ep.' '24 min.' '22 min. per ep.' '1 hr. 44 min.'\n",
      " '1 hr. 27 min.' '1 hr. 22 min.' '30 min. per ep.' '1 hr. 31 min.'\n",
      " '2 hr. 4 min.' '1 hr. 45 min.' '52 min.' '1 hr. 59 min.' '2 hr.'\n",
      " '21 min. per ep.' '14 min. per ep.' '12 min. per ep.' '34 min. per ep.'\n",
      " '46 min. per ep.' '1 hr. 37 min.' '20 min. per ep.' '2 hr. 15 min.'\n",
      " '26 min. per ep.' '28 min. per ep.' '21 min.' '46 min.' '15 min. per ep.'\n",
      " '2 hr. 5 min.' '29 min. per ep.' '33 min. per ep.' '1 hr. 24 min.'\n",
      " '48 min.' '1 hr. 19 min.' '25 min.' '1 hr. 30 min.' '1 hr. 1 min.'\n",
      " '4 min. per ep.' '7 min. per ep.' '1 hr. 46 min.' '18 min. per ep.'\n",
      " '1 hr. 41 min.' '11 min. per ep.' '13 min. per ep.' '55 min.'\n",
      " '1 hr. 21 min.' '1 hr. 2 min.' '37 min. per ep.' '42 min. per ep.'\n",
      " '37 min.' '19 min.' '1 hr. 33 min.' '1 hr. 14 min.' '50 min.' '42 min.'\n",
      " '1 hr. 20 min.' '45 min. per ep.' '1 hr. 39 min.' '1 hr. 38 min.'\n",
      " '26 min.' '1 hr. 35 min.' '1 hr. 34 min.' '28 min.' '39 min. per ep.'\n",
      " '40 min.' '5 min. per ep.' '1 hr. 32 min.' '2 hr. 12 min.'\n",
      " '1 hr. 36 min.' '36 min. per ep.' '30 min.' '1 hr. 49 min.'\n",
      " '1 hr. 26 min.' '1 hr. 25 min.' '1 hr. 6 min.' '1 hr. 42 min.'\n",
      " '1 hr. 43 min.' '1 hr. 23 min.' '15 min.' '51 min.' '31 min. per ep.'\n",
      " '2 hr. 6 min.' '1 hr. 57 min.' '1 hr. 28 min.' '8 min. per ep.'\n",
      " '1 hr. 51 min.' '22 min.' '6 min.' '1 hr. 15 min.' '32 min.'\n",
      " '6 min. per ep.' '23 min.' '1 hr. 17 min.' '31 min.' '35 min. per ep.'\n",
      " '1 min. per ep.' '3 min. per ep.' '20 min.' '10 min.' '2 hr. 20 min.'\n",
      " '54 min. per ep.' '16 min. per ep.' '1 hr. 7 min.' '44 min.'\n",
      " '1 hr. 12 min.' '27 min.' '17 min.' '29 min.' '50 min. per ep.'\n",
      " '1 hr. 40 min.' '48 min. per ep.' '1 hr.' '35 min.' '1 hr. 5 min.'\n",
      " '49 min.' '17 min. per ep.' '10 min. per ep.' '33 min.' '43 min. per ep.'\n",
      " '59 min.' '9 min. per ep.' '1 hr. 11 min.' '45 min.' '41 min.'\n",
      " '1 hr. 10 min.' '11 min.' '53 min.' '32 min. per ep.' '5 min.' '47 min.'\n",
      " '4 min.' '1 hr. 58 min.' '2 hr. 1 min.' '54 min.' '1 hr. 3 min.'\n",
      " '40 min. per ep.' '1 hr. 48 min.' '1 hr. 18 min.' '47 min. per ep.'\n",
      " '2 hr. 16 min.' '43 min.' '52 min. per ep.' '56 min.' '58 min.'\n",
      " '2 hr. 19 min.' '51 min. per ep.' '2 hr. 8 min.' '2 hr. 10 min.'\n",
      " '41 min. per ep.' '58 min. per ep.' '1 hr. 50 min.' '1 hr. 47 min.'\n",
      " '12 min.' '1 hr. 13 min.' '38 min. per ep.' '1 hr. 5 min. per ep.'\n",
      " '39 min.' '1 hr. 9 min.' '1 hr. per ep.' '3 min.' '2 hr. 11 min.'\n",
      " '34 min.' '57 min.' '1 hr. 52 min.' '2 min. per ep.' '16 min.' '13 min.'\n",
      " '38 min.' '1 hr. 17 min. per ep.' '8 min.' '1 hr. 38 min. per ep.'\n",
      " '1 hr. 7 min. per ep.' '55 min. per ep.' '1 hr. 29 min.' '1 hr. 56 min.'\n",
      " '53 min. per ep.' '1 min.' '9 min.' '7 min.' '1 hr. 35 min. per ep.'\n",
      " '1 hr. 30 min. per ep.' '49 min. per ep.' '2 hr. 41 min.' '2 hr. 40 min.'\n",
      " '14 min.' '1 hr. 8 min.' '57 min. per ep.' '2 min.' '1 hr. 53 min.'\n",
      " '18 min.' '2 hr. 21 min.' '2 hr. 33 min.' '1 hr. 52 min. per ep.'\n",
      " '1 hr. 4 min.' '2 hr. 32 min.' '2 hr. 30 min.' '2 hr. 43 min.'\n",
      " '2 hr. 2 min.' '36 min.' 'Unknown' '1 hr. 16 min.' '1 hr. 54 min.'\n",
      " '44 min. per ep.' '12 sec.' '19 min. per ep.' '52 sec.' '30 sec. per ep.'\n",
      " '1 hr. 2 min. per ep.' '22 sec. per ep.' '2 hr. 3 min.' '40 sec. per ep.'\n",
      " '2 hr. 42 min.' '32 sec.' '1 hr. 14 min. per ep.' '39 sec. per ep.'\n",
      " '2 hr. 28 min.' '2 hr. 27 min.' '2 hr. 7 min.' '15 sec. per ep.'\n",
      " '30 sec.' '1 hr. 11 min. per ep.' '1 hr. 16 min. per ep.'\n",
      " '53 sec. per ep.' '38 sec.' '29 sec.' '35 sec.' '33 sec. per ep.'\n",
      " '2 hr. 36 min.' '34 sec. per ep.' '2 hr. 17 min.' '1 hr. 15 min. per ep.'\n",
      " '24 sec. per ep.' '37 sec. per ep.' '31 sec. per ep.' '29 sec. per ep.'\n",
      " '1 hr. 36 min. per ep.' '31 sec.' '41 sec.' '45 sec. per ep.'\n",
      " '35 sec. per ep.' '15 sec.' '49 sec. per ep.' '17 sec.' '54 sec.'\n",
      " '2 hr. 14 min.' '16 sec.' '41 sec. per ep.' '27 sec.' '42 sec.' '14 sec.'\n",
      " '26 sec. per ep.' '36 sec.' '37 sec.' '58 sec. per ep.'\n",
      " '1 hr. 24 min. per ep.' '50 sec.' '45 sec.' '33 sec.' '32 sec. per ep.'\n",
      " '55 sec.' '57 sec.' '16 sec. per ep.' '40 sec.' '10 sec.' '46 sec.'\n",
      " '7 sec.' '49 sec.' '39 sec.' '51 sec. per ep.' '57 sec. per ep.'\n",
      " '10 sec. per ep.' '44 sec. per ep.' '3 sec.' '2 hr. 47 min.' '25 sec.'\n",
      " '36 sec. per ep.' '20 sec. per ep.' '42 sec. per ep.' '19 sec.'\n",
      " '18 sec. per ep.' '44 sec.' '20 sec.' '51 sec.' '28 sec.'\n",
      " '46 sec. per ep.' '56 sec. per ep.' '34 sec.' '50 sec. per ep.' '58 sec.'\n",
      " '21 sec.' '13 sec.' '54 sec. per ep.' '23 sec.' '22 sec.'\n",
      " '21 sec. per ep.' '25 sec. per ep.' '12 sec. per ep.' '38 sec. per ep.'\n",
      " '14 sec. per ep.' '6 sec. per ep.' '23 sec. per ep.' '47 sec.'\n",
      " '1 hr. 9 min. per ep.' '24 sec.' '28 sec. per ep.' '43 sec. per ep.'\n",
      " '1 hr. 27 min. per ep.' '48 sec.' '6 sec.' '43 sec.' '55 sec. per ep.']\n",
      "\n",
      "Rating: ['R - 17+ (violence & profanity)' 'PG-13 - Teens 13 or older'\n",
      " 'PG - Children' 'R+ - Mild Nudity' 'G - All Ages' 'Rx - Hentai' 'Unknown']\n",
      "\n"
     ]
    }
   ],
   "source": [
    "categorical_data = data.columns[data.dtypes == object]\n",
    "for cat in categorical_data:\n",
    "    # Only intented categorical data\n",
    "    try:\n",
    "        float(data[cat][0])\n",
    "    except:\n",
    "        print(f\"{cat}: {data[cat].unique()}\")\n",
    "        print(\"\")"
   ]
  },
  {
   "attachments": {
    "image-2.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For the date data we can change them into Year, month and day in number. Nevertheless I prefer to use a 2 dimensional representations for month and day, this can represent the cyclic nature of the months and days of the weeks rather than just the number itself.\n",
    "\n",
    "![image-2.png](attachment:image-2.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally we can see that the duration can also be represented by the number of minutes. All this transformations will be done at the feautre engineering section."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0           39\n",
       "1          518\n",
       "2          201\n",
       "3         1467\n",
       "4         4369\n",
       "         ...  \n",
       "17557    13116\n",
       "17558    17562\n",
       "17559    17558\n",
       "17560    17565\n",
       "17561    17563\n",
       "Name: Popularity, Length: 17562, dtype: int64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['Popularity']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Clean dataset\n",
    "\n",
    "We have seen before that we have no nan data nor duplicated data. But we do have some features with 'unknown' data. We need to do the following:\n",
    "\n",
    "* N-Scores: \n",
    "    * First change type from string to float\n",
    "    * Impute the unknown scores by a linear interpolation.\n",
    "* Scores: (First change type from string to float) Recalculate the scores based on the information obtained.\n",
    "* Premiered and Licensors: Remove this features (More than 70% of the information is unknown)\n",
    "* Aired, keep years only since this might be the most relevant data (If we want to analyze performance of launching an Anime, months and days might be more relevant). \n",
    "* For the Duration and Rating Unknown values I took the average value. \n",
    "* For categorical data the unknown values can be a category by itself.\n",
    "* Impute the unknown ranks as the average rank (not good or bad since is in the middle) and add an unkown rank feature (1 means unknown and 0 that we have a known feature)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "# Change type of scores \n",
    "data.replace({'Score': 'Unknown'}, 'NaN', inplace = True)\n",
    "data['Score'] = data['Score'].astype(float)\n",
    "\n",
    "# All scores (1 - 10)\n",
    "score_cols = []\n",
    "for ii in range(10):\n",
    "    feature = 'Score-' + str(ii + 1)\n",
    "    score_cols.append(feature)\n",
    "    data.replace({feature: 'Unknown'}, 'NaN', inplace = True)\n",
    "    data[feature] = data[feature].astype(float)\n",
    "\n",
    "# Calculate values for unknown scores\n",
    "data.loc[:, score_cols] = data[score_cols].interpolate(method='linear', axis=1, limit_direction='both')\n",
    "\n",
    "# Recalculate the scores based on the imputated scores\n",
    "data.loc[:, 'Score'] = (data[score_cols]*(1+np.arange(10))).sum(axis = 1)/((data[score_cols]).sum(axis = 1))\n",
    "\n",
    "# Replace unknown scores to 5 (not good but not bad enough) and unknown score-i to 0 (no votes)\n",
    "data.replace({'Score': np.nan}, 5, inplace = True)\n",
    "for scorecol in score_cols:\n",
    "    data.replace({scorecol: np.nan}, 0, inplace = True)\n",
    "\n",
    "# Remove premiered and licensors features\n",
    "data.drop(columns= {'Licensors', 'Premiered'}, inplace = True)\n",
    "\n",
    "# Create OHE for categorical data\n",
    "    # First for the genres (this are separated by commas in each row we need first each genre)\n",
    "all_genres = set(genre.strip() for sublist in data['Genres'].str.split(',') for genre in sublist)\n",
    "for genre in all_genres:\n",
    "    data[genre] = data['Genres'].apply(lambda x: 1 if genre in x else 0)\n",
    "data.drop(columns = 'Genres', inplace = True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For 'Aired' feature we will use only the year. If only one year is shown we will consider this the same year of finishing. If we have something like 'Jan 23, 1992, ?' we consider '?' as still in air. We will use the current year as the last year"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Initial Year</th>\n",
       "      <th>Last Year</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1998.000000</td>\n",
       "      <td>1999.000000</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2001.000000</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1998.000000</td>\n",
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       "      <td>2005.000000</td>\n",
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       "      <td>2024.000000</td>\n",
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       "      <th>17558</th>\n",
       "      <td>2021.000000</td>\n",
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       "<p>17562 rows × 2 columns</p>\n",
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      ],
      "text/plain": [
       "       Initial Year    Last Year\n",
       "0       1998.000000  1999.000000\n",
       "1       2001.000000  2001.000000\n",
       "2       1998.000000  1998.000000\n",
       "3       2002.000000  2002.000000\n",
       "4       2004.000000  2005.000000\n",
       "...             ...          ...\n",
       "17557   2021.000000  2024.000000\n",
       "17558   2021.000000  2024.000000\n",
       "17559   2021.000000  2024.000000\n",
       "17560   2005.127166  2005.600185\n",
       "17561   2021.000000  2024.000000\n",
       "\n",
       "[17562 rows x 2 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import re\n",
    "from datetime import datetime\n",
    "# Current year\n",
    "current_year = datetime.now().year\n",
    "\n",
    "def extract_years(date_str):\n",
    "    current_year = datetime.now().year\n",
    "    date_str = date_str.replace('?', str(current_year))\n",
    "    years = re.findall(r'\\d{4}', date_str)\n",
    "    \n",
    "    if len(years) == 1:\n",
    "        return int(years[0]), int(years[0])\n",
    "    elif len(years) == 2:\n",
    "        return int(years[0]), int(years[1])\n",
    "    else:\n",
    "        return None, None  # Handle cases where no valid year is found\n",
    "    \n",
    "data['Initial Year'], data['Last Year'] = zip(*data['Aired'].apply(extract_years))\n",
    "\n",
    "data.replace({'Initial Year': np.nan}, data['Initial Year'].mean(skipna = True), inplace = True)\n",
    "data.replace({'Last Year': np.nan}, data['Last Year'].mean(skipna = True), inplace = True)\n",
    "\n",
    "data.drop(columns= 'Aired', inplace=True)\n",
    "data[['Initial Year', 'Last Year']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0        26.000000\n",
       "1         1.000000\n",
       "2        26.000000\n",
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       "           ...    \n",
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       "17559    11.525519\n",
       "17560    11.525519\n",
       "17561    11.525519\n",
       "Name: Episodes, Length: 17562, dtype: float64"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Remove Unknown values for the average value in Episodes\n",
    "data.replace({'Episodes': 'Unknown'}, 'NaN', inplace = True)\n",
    "data['Episodes'] = data['Episodes'].astype(float)\n",
    "\n",
    "data.replace({'Episodes': np.nan}, data['Episodes'].mean(skipna = True), inplace = True)\n",
    "data['Episodes']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\gilbe\\AppData\\Local\\Temp\\ipykernel_12452\\1854820143.py:32: FutureWarning: Downcasting behavior in `replace` is deprecated and will be removed in a future version. To retain the old behavior, explicitly call `result.infer_objects(copy=False)`. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`\n",
      "  data.replace({'Duration': np.nan}, data['Duration'].mean(skipna = True), inplace = True)\n"
     ]
    }
   ],
   "source": [
    "# Transform 'Duration' data into minutes only\n",
    "def convert_to_minutes(duration_str):\n",
    "    # Regular expressions to capture hours and minutes\n",
    "    hours_pattern = r'(\\d+)\\s*hr'\n",
    "    minutes_pattern = r'(\\d+)\\s*min'\n",
    "    \n",
    "    # Find hours and minutes in the string\n",
    "    hours_match = re.search(hours_pattern, duration_str)\n",
    "    minutes_match = re.search(minutes_pattern, duration_str)\n",
    "    unknown_match = re.search('Unknown', duration_str)\n",
    "\n",
    "    # Convert to minutes\n",
    "    total_minutes = 0\n",
    "    \n",
    "    if hours_match:\n",
    "        hours = int(hours_match.group(1))\n",
    "        total_minutes += hours * 60\n",
    "    \n",
    "    if minutes_match:\n",
    "        minutes = int(minutes_match.group(1))\n",
    "        total_minutes += minutes\n",
    "    if unknown_match:\n",
    "        total_minutes = np.nan\n",
    "\n",
    "    return total_minutes\n",
    "\n",
    "# Apply the function to the DataFrame\n",
    "data.loc[:, 'Duration'] = data['Duration'].apply(convert_to_minutes)\n",
    "data.loc[:, 'Duration'] = data['Duration'].astype(float)\n",
    "\n",
    "# Get unknown duration data to be the mean rank\n",
    "data.replace({'Duration': np.nan}, data['Duration'].mean(skipna = True), inplace = True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Feature engineering"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Apply OHE and get a dataset without the names of the movies "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of non binary features: 67\n"
     ]
    },
    {
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       "      <td>2</td>\n",
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       "      <td>11.525519</td>\n",
       "      <td>24.532839</td>\n",
       "      <td>17563</td>\n",
       "      <td>310</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>17562 rows × 15460 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          Score   Episodes    Duration  Popularity  Members  Favorites  \\\n",
       "0      8.740248  26.000000   24.000000          39  1251960      61971   \n",
       "1      8.390985   1.000000  115.000000         518   273145       1174   \n",
       "2      8.215289  26.000000   24.000000         201   558913      12944   \n",
       "3      7.216657  26.000000   25.000000        1467    94683        587   \n",
       "4      6.892115  52.000000   23.000000        4369    13224         18   \n",
       "...         ...        ...         ...         ...      ...        ...   \n",
       "17557  5.500000  11.525519   24.532839       13116      354          6   \n",
       "17558  5.000000  11.525519   24.532839       17562     7010         70   \n",
       "17559  5.500000  11.525519   24.532839       17558    11309         48   \n",
       "17560  5.000000  11.525519   24.532839       17565     1386          2   \n",
       "17561  5.000000  11.525519   24.532839       17563      310          0   \n",
       "\n",
       "       Watching  Completed  On-Hold  Dropped  ...  Ranked_9987.0  \\\n",
       "0        105808     718161    71513    26678  ...          False   \n",
       "1          4143     208333     1935      770  ...          False   \n",
       "2         29113     343492    25465    13925  ...          False   \n",
       "3          4300      46165     5121     5378  ...          False   \n",
       "4           642       7314      766     1108  ...          False   \n",
       "...         ...        ...      ...      ...  ...            ...   \n",
       "17557         0          0        0        0  ...          False   \n",
       "17558        14          0       14        0  ...          False   \n",
       "17559         3          0        0        0  ...          False   \n",
       "17560        13          2        2        1  ...          False   \n",
       "17561         4          0        1        1  ...          False   \n",
       "\n",
       "       Ranked_9989.0  Ranked_9991.0  Ranked_9992.0  Ranked_9993.0  \\\n",
       "0              False          False          False          False   \n",
       "1              False          False          False          False   \n",
       "2              False          False          False          False   \n",
       "3              False          False          False          False   \n",
       "4              False          False          False          False   \n",
       "...              ...            ...            ...            ...   \n",
       "17557          False          False          False          False   \n",
       "17558          False          False          False          False   \n",
       "17559          False          False          False          False   \n",
       "17560          False          False          False          False   \n",
       "17561          False          False          False          False   \n",
       "\n",
       "       Ranked_9996.0  Ranked_9997.0  Ranked_9998.0  Ranked_9999.0  \\\n",
       "0              False          False          False          False   \n",
       "1              False          False          False          False   \n",
       "2              False          False          False          False   \n",
       "3              False          False          False          False   \n",
       "4              False          False          False          False   \n",
       "...              ...            ...            ...            ...   \n",
       "17557          False          False          False          False   \n",
       "17558          False          False          False          False   \n",
       "17559          False          False          False          False   \n",
       "17560          False          False          False          False   \n",
       "17561          False          False          False          False   \n",
       "\n",
       "       Ranked_Unknown  \n",
       "0               False  \n",
       "1               False  \n",
       "2               False  \n",
       "3               False  \n",
       "4               False  \n",
       "...               ...  \n",
       "17557            True  \n",
       "17558            True  \n",
       "17559            True  \n",
       "17560            True  \n",
       "17561            True  \n",
       "\n",
       "[17562 rows x 15460 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Now the categorical data with OHE\n",
    "\n",
    "# One Hot Encoding the rest of categorical data\n",
    "columns = data.columns\n",
    "categorical_features = columns[data.dtypes == object]\n",
    "data = pd.get_dummies(data, columns = categorical_features[1:])\n",
    "\n",
    "# Creat dataset without names\n",
    "columns = data.columns\n",
    "data_model = data[columns[1:]]\n",
    "columns = data_model.columns\n",
    "print(f\"Number of non binary features: {len(columns) - len(columns[data_model.dtypes == bool])}\")\n",
    "data_model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "With this we finish cleaning the dataset with a total of 17562 rows and 15460 columns. From this, 15393 are booleans corresponding to the categorical data. We will apply PCA mainly to this features to reduce the categorical data to 33 features (just to have a total of 100 features). "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Apply PCA only to the boolean features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\gilbe\\AppData\\Local\\Temp\\ipykernel_12452\\1379511651.py:8: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  data_model.drop(columns = 'index', inplace = True)\n"
     ]
    }
   ],
   "source": [
    "# Position again the target column to the end of the data\n",
    "from sklearn.decomposition import PCA\n",
    "\n",
    "pca_enc = PCA(n_components = 33)\n",
    "pca_num = PCA(n_components = 33)\n",
    "\n",
    "data_model.reset_index(inplace = True)\n",
    "data_model.drop(columns = 'index', inplace = True)\n",
    "columns = data_model.columns\n",
    "red_cat_data = pca_enc.fit_transform(data_model[columns[data_model.dtypes == bool]])\n",
    "pca_data = pd.concat([data_model[columns[data_model.dtypes != bool]], pd.DataFrame(red_cat_data)], axis = 1)\n",
    "pca_data_np = pca_data.to_numpy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Perform standardization of the features\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "\n",
    "std_scaler = StandardScaler()\n",
    "data_std = std_scaler.fit_transform(data_model)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Customer segmentation\n",
    "\n",
    "Here we would like to get a segmentation of customers, understanding which groups exists, their size and how they are related. For this we will use a couple of techniques such as K-means, HAC and DBSCAN. To evaluate performance of the clustering we will use the silhouette score."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## K-means"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "from tqdm import tqdm\n",
    "from sklearn.cluster import KMeans\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.metrics import silhouette_score\n",
    "from sklearn.metrics import pairwise_distances\n",
    "\n",
    "distance_matrix = pairwise_distances(pca_data_np)\n",
    "np.fill_diagonal(distance_matrix, 0) # Remove computational errors of distances"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 40/40 [06:43<00:00, 10.08s/it]\n"
     ]
    },
    {
     "data": {
      "image/png": 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t7Y177rkHb731Voeei0UryNMRwV5OuJheiB/PpePJod2NXRIREZHZkYQZTCJSWFgIZ2dnFBQUGKU/y+d/XMWKny5hUDcXbH9ueLufn4iIyBQZ8vObK161gj/194ZMAk6m5CMpp8TY5RAREZkdBpZW4OFkgxGB7gCAnafZ+ZaIiKi1MbC0kgdrpurfwan6iYiIWh0DSyu5p48KdtZyJOeW4mRKvrHLISIiMisMLK3EztoKE/pWT563/MeLyC0uN3JFRERE5oOBpRU9M6oHnGyscCY1H1M+OYT4rGJjl0RERGQWGFhaUZCnI7Y/Nxw+rrZIuVGKh/51CEeuNrzqNBERETUNA0srC/BwwM7nhmNgNxcU3KzEkxuOYvvJNGOXRUREZNIYWNpAZwclvpo7FPf380KlWmDRN2fwj91xHD1ERETUTAwsbcRGIcc/pw/EvDE9AAAfRl3Bom/OoLxKbeTKiIiITA8DSxuSySS8OqEXVj3YD3KZhB2nruHJDceQX8pFEomIiAzBwNIOpt/VDV/MHgJHpRWOJd7Ag58cQnIup/AnIiJqKgaWdjIy0B3b5g2Dt7MNruaUYMonhxCTfMPYZREREZkEBpZ2FOTpiJ3zh6NfF2fcKKnA9PVHsS0mDRVVGmOXRkRE1KFJwgyGrhiyPHVHUFpRhQVfn8bui5kAAHtrOcJ7dMaonu4YFegOXzd7I1dIRETU9gz5+c3AYiRqjcCHe+Lw32MpyCnW74TbzdUOo3q6YVSgO4YFuMFBaWWkKomIiNoOA4sJ0WgELqYXYv+VbOyLzUZMch6qNLduiZVMwqDunTC6pvWlj7cTZDLJiBUTERG1DgYWE1ZcXoXDCbnYH5eN/VeykZxbqvd5kMoRL4wLwL19vSBncCEiIhPGwGJGknNLsD8uG/vicnAoIQelFdUTzwV4OOCFuwPwQIg3gwsREZkkBhYzVVBaiU2HErHxQCIKy6oAAP5u9pg/NgCTBnjDSs5BX0REZDoYWMxcYVklthxKwucHEpFfWgmguqPu82MDMGVQFygYXIiIyAQwsFiI4vIq/PtwMtb/cRU3SqpHGnXtZIvnxgTg4dCusLZicCEioo6LgcXClFZU4csjKfh0f4JuiLS3sw0WRARi6pBuRq6OiIiofgwsFupmhRpfHUvBun0JyCoqBwBs/vNdGN3T3ciVERER1WXIz28+MzAjttZy/HmEH/a/Mhb39/MCAPx2IcPIVREREbUcA4sZslHI8eCgLgCAfXHZMINGNCIisnAMLGZqqH9nWMtlSMu7ias5JcYuh4iIqEUYWMyUvdIKQ/w6AQD2x2UbuRoiIqKWYWAxY6MCqzvb7mNgISIiE8fAYsZGB1UHliNXc1FWqTZyNURERM3HwGLGglSOUDkpUVapwfGkG8Yuh4iIqNkYWMyYJEm6OVj2xfKxEBERmS4GFjM3qif7sRARkeljYDFzIwLcIJOAK1nFuJ5/09jlEBERNQsDi5lzsbPGAB8XABzeTEREpouBxQKM7ukBgI+FiIjIdDGwWADt8OYDV3JQqdYYuRoiIiLDMbBYgH5dnOFip0BReRVOp+YbuxwiIiKDMbBYALlMwsiaWW/Zj4WIiEwRA4uFGM3hzUREZMIYWCzEqEA3AMDZtALkFJcbuRoiIiLDMLBYCA8nGwR7OQGo7nxLRERkShhYLIh21lv2YyEiIlPDwGJBtP1Y9l/JhkYjjFwNERFR0zGwWJDQ7p1gby1HTnEFLqYXGrscIiKiJmNgsSDWVjIMC6jufMvRQkREZEoYWCwMV28mIiJTxMBiYUbXTCB3MjkPhWWVRq6GiIioaRhYLEy3znbwd7NHlUbgUHyuscshIiJqEgYWC8THQkREZGqaFVjWrl0LX19f2NjYICwsDMeOHWtw2zFjxkCSpDqv+++/X7eNEAJLliyBl5cXbG1tERERgStXrjSnNGoC7erN++OyIQSHNxMRUcdncGDZunUrFi1ahKVLl+LkyZPo378/IiMjkZWVVe/227dvR3p6uu51/vx5yOVyPPLII7pt3nnnHXz00UdYt24djh49Cnt7e0RGRqKsrKz5V0YNGurXGdZWMlzLv4mE7BJjl0NERHRHBgeWDz74AHPnzsXs2bMRHByMdevWwc7ODhs3bqx3e1dXV3h6eupeu3fvhp2dnS6wCCGwZs0avP7665g0aRJCQkKwZcsWXL9+HTt37mzRxVH9bK3lCPNzBcDHQkREZBoMCiwVFRWIiYlBRETErQPIZIiIiMDhw4ebdIwNGzZg2rRpsLe3BwAkJiYiIyND75jOzs4ICwtr8Jjl5eUoLCzUe5FhuHozERGZEoMCS05ODtRqNVQqld77KpUKGRkZd9z/2LFjOH/+PJ566inde9r9DDnmqlWr4OzsrHv5+PgYchmEW4Hl6NVclFWqjVwNERFR49p1lNCGDRvQr18/3HXXXS06zuLFi1FQUKB7paamtlKFliPAwwHezjYor9LgaOINY5dDRETUKIMCi5ubG+RyOTIzM/Xez8zMhKenZ6P7lpSU4Ouvv8acOXP03tfuZ8gxlUolnJyc9F5kGEmSbg1vjuVjISIi6tgMCizW1tYIDQ1FVFSU7j2NRoOoqCiEh4c3uu+3336L8vJyPPHEE3rv+/n5wdPTU++YhYWFOHr06B2PSS1zqx9L/SO8iIiIOgorQ3dYtGgRZs6cicGDB+Ouu+7CmjVrUFJSgtmzZwMAZsyYgS5dumDVqlV6+23YsAGTJ09G586d9d6XJAkLFy7EihUrEBgYCD8/P7zxxhvw9vbG5MmTm39ldEfDAtwgl0lIyC5BWl4punayM3ZJRERE9TI4sEydOhXZ2dlYsmQJMjIyMGDAAOzatUvXaTYlJQUymX7DTWxsLA4cOIDffvut3mO+8sorKCkpwdNPP438/HyMGDECu3btgo2NTTMuiZrK2VaBQd1ccDwpD/vjcvBYWDdjl0RERFQvSZjBVKeFhYVwdnZGQUEB+7MY6J9RV/D+7jhE9lHh0ycHG7scIiKyIIb8/OZaQhZOO03/wfhcVKo1Rq6GiIiofgwsFq6vtzNc7a1RXF6FUyn5xi6HiIioXgwsFk4mkzAq0A0ARwsREVHHxcBCusdC352+jhslFUauhoiIqC4GFsK43ip4OdsgLe8mZmw8isKySmOXREREpIeBheBko8B/ngqDm4M1zl8rxOxNx1FaUWXssoiIiHQYWAgA0MPdAf+eEwZnWwVikvMwd8sJLopIREQdBgML6fT2csLmP98Fe2s5DsbnYv6XJznUmYiIOgQGFtIzwMcFG2YNgdJKhqjLWVi49TTUGpOfW5CIiEwcAwvVMdS/Mz59MhQKuYSfzqbj1f+dhYahhYiIjIiBheo1JsgD/5w+CHKZhG0xaXjzhwswg1UciIjIRDGwUIMm9PXEe4+EQJKAzYeT8fauWIYWIiIyCgYWatSUgV3x98n9AADr9iVg7d54I1dERESWiIGF7uixsG54/f7eAID3fovDhgOJRq6IiIgsDQMLNclTI/3xl4ieAIC3fryIr4+lGLkiIiKyJAws1GQvjgvA06P8AQCLd5zDun0JHD1ERETtgoGFmkySJCy+txdmhHeHEMDqXy5jzubjXDCRiIjaHAMLGUSSJLz5pz5Y9WA/KK1k2Bubjfs+/APHk24YuzQiIjJjDCxkMEmSMP2ubtg5fzj83e2RUViGaZ8dwdq98e3yiEgIgbySClxKL8Tey1m4nFHY5uckIiLjkoQZTKxRWFgIZ2dnFBQUwMnJydjlWJSS8iq8vvM8dpy6BgAY1dMdHzzaH24OymYfM6uoDNfzy5BRcBMZBWVILyxDZkEZ0gvKkFFYhoyCMpRX3VrjyFouQ9T/jYaPq12Lr4eIiNqPIT+/GVioxYQQ+PZEGpZ8fx5llRp4OCrx0fSBGOrfucn7X0ovwq4LGfj1fAZiM4uatJ+rvTXUGoGCm5V4ZpQ/Ft/XuyWXQURE7YyBhYwiLrMIz315EvFZxZBJwMKInpg/NgBymVRnW41G4FRqHnadz8CvFzKRcqNU95lMAlRONlA52cDL+davns428HSygZezLTyclLBRyLHnYiae2nICzrYKHFk8DrbW8va8ZCIiagFDfn5btVNNZAF6qhzx/fPDseS7C9gWk4YPdsfhaGIu1kwdCHdHJSrVGhy9egO7LqTjtwuZyCoq1+2rtJJhdE93TOjriXG9VHC2UzTpnGN7eaBrJ1uk5d3E92euYeqQbm11eUREZERsYaE28b+YNLy+8zxuVqrh5qDEiIDO2BubjYKblbptHJVWGNfbAxP6emJUT3fYWTcvP3+6LwGrfrmMYC8n/PTiCEhS3RYdIiLqePhIiDqE+KwizP/ylF6fFDcHa4wPViGyjyeG9XCDtVXLB6rll1YgbGUUyqs02PZsOAb7urb4mERE1Pb4SIg6hAAPR+ycPxz//P0Kyqs0iOzjidDunert09ISLnbWmDygC7aeSMUXh5IYWIiIzBADC7UpW2s5XpnQq83P82R4d2w9kYpd5zOQWVgGlZNNm5+TiIjaDyeOI7PQt4szBnfvhCqNwH+PcmFGIiJzw8BCZmPmMF8AwH+PpaCi1sRyRERk+hhYyGxE9vGEh6MS2UXl+OV8urHLISKiVsTAQmbD2kqGx8Kq52HZcjjZyNUQEVFrYmAhs/LYXd1gJZMQk5yH89cKjF0OERG1EgYWMiseTja4r58XAGDL4STjFkNERK2GgYXMzsxh3QEA352+jrySCiNXQ0RErYGBhczOoG6d0MfbCeVVGmw9kWrscoiIqBUwsJDZkSQJM8N9AQD/PpwMtcbkV58gIrJ4DCxklv40wBsudgpcy7+J3y9nGbscIiJqIQYWMks2CjmmDvEBAGw+lGTcYoiIqMUYWMhsPRHWHZIEHIjPQXxW0Z13ICKiDouBhcyWj6sdxvVSAajuy0JERKaLgYXM2qya9YW2xaShqKzSuMUQEVGzMbCQWRse0Bn+7vYoqVBj+8lrxi6HiIiaiYGFzFrtIc6bDydBCA5xJiIyRQwsZPYeHNQF9tZyXM0uwcH4XGOXQ0REzcDAQmbP0UaBh0O7AqhuZSEiItPDwEIW4cmax0JRlzKReqPUuMUQEZHBGFjIIgR4OGBEgBs0Anjzhwso5IghIiKTwsBCFuO5MT0gk4A9l7Iw4R/7cTA+x9glERFREzGwkMUYFuCGb54JR/fOdrheUIbHPz+Kpd+dx80KtbFLIyKiO2BgIYsy2NcVP784Ek8M7QYA2Hw4Gfd99AdOpuQZuTIiImpMswLL2rVr4evrCxsbG4SFheHYsWONbp+fn4/58+fDy8sLSqUSPXv2xM8//6z7fNmyZZAkSe/Vq1ev5pRGdEf2SiusmNwPW/58FzydbJCYU4KH/3UI7+y6jIoqTbvUUFGlQXJuSbuci4jIHBgcWLZu3YpFixZh6dKlOHnyJPr374/IyEhkZWXVu31FRQXGjx+PpKQkbNu2DbGxsVi/fj26dOmit12fPn2Qnp6uex04cKB5V0TURKN6uuPXhaMwZWAXaATwSXQCJq09iEvphW163uv5N/Gnjw9g9LvR+Pj3K216LiIicyEJA6f+DAsLw5AhQ/Dxxx8DADQaDXx8fPDCCy/gtddeq7P9unXr8O677+Ly5ctQKBT1HnPZsmXYuXMnTp8+3aQaysvLUV5ervu6sLAQPj4+KCgogJOTkyGXQwQA+OVcOv664xzySiuhkEv4y/ieeGZUD8hlUque5/y1Avz5i+PIKrr15/eNB4IxZ4Rfq56HiMgUFBYWwtnZuUk/vw1qYamoqEBMTAwiIiJuHUAmQ0REBA4fPlzvPt9//z3Cw8Mxf/58qFQq9O3bFytXroRard/R8cqVK/D29oa/vz8ef/xxpKSkNFjHqlWr4OzsrHv5+PgYchlEddzbzwu//WU0InqrUKkWeGdXLB5ZdwiJOa332CbqUiYe/fQwsorK0VPlgKdqQspbP17Ef482/OediIgMDCw5OTlQq9VQqVR676tUKmRkZNS7z9WrV7Ft2zao1Wr8/PPPeOONN/D+++9jxYoVum3CwsLwxRdfYNeuXfjXv/6FxMREjBw5EkVFRfUec/HixSgoKNC9UlNTDbkMonq5OyqxfkYo3n04BI5KK5xMyce9H+7HP6OuoKyyZSOJthxOwtwtJ1BaocbIQDdsmzcMf7u/N54Z7Q8A+NvOc9hxKq01LoOIyCxZtfUJNBoNPDw88Nlnn0EulyM0NBTXrl3Du+++i6VLlwIA7r33Xt32ISEhCAsLQ/fu3fHNN99gzpw5dY6pVCqhVCrbunSyQJIk4ZHBPhgW4IZXtp3BwfhcvL87Dt/GpOGNB4IR0dsDktT0x0RqjcDKny9hw4FEAMC0IT54a3JfKOTV/1d4bUIv3KxQY8vhZLz07VnYKuSY0NerTa6NiMiUGdTC4ubmBrlcjszMTL33MzMz4enpWe8+Xl5e6NmzJ+Ryue693r17IyMjAxUVFfXu4+Ligp49eyI+Pt6Q8ohaTRcXW/xnThg+nDYAKiclUm6UYu6WE5j9xXFczS5u0jFuVqjx3JcxurDycmQQVj3YTxdWgOqAtGxiHzwc2hVqjcALX53C3sv1d2AnIrJkBgUWa2trhIaGIioqSveeRqNBVFQUwsPD691n+PDhiI+Ph0Zza7hoXFwcvLy8YG1tXe8+xcXFSEhIgJcX/6dJxiNJEiYN6ILf/28M5o3pAYVcQnRsNiLX7MfqXy6jpLyqwX2zi8oxbf0R/HohE9ZyGT6aPhDzxwbU2zojk0l4+6EQPBDihUq1wLP/icGhBM7CS0RUm8HDmhctWoT169dj8+bNuHTpEubNm4eSkhLMnj0bADBjxgwsXrxYt/28efNw48YNLFiwAHFxcfjpp5+wcuVKzJ8/X7fNSy+9hH379iEpKQmHDh3ClClTIJfLMX369Fa4RKKWsVda4dUJvfDrwlEYE+SOSrXAun0JGPf+Pnx3+hpuH2h3JbMIUz45iDOp+ehkp8CXc8Pwp/7ejZ5DLpPwj6kDENHbA+VVGjy1+QRikjmZHRGRlsGBZerUqXjvvfewZMkSDBgwAKdPn8auXbt0HXFTUlKQnp6u297Hxwe//vorjh8/jpCQELz44otYsGCB3hDotLQ0TJ8+HUFBQXj00UfRuXNnHDlyBO7u7q1wiUStw9/dAZtmDcHnMwajm6sdMgrLsODr05j62RHd3C2H4nPw4L8OIS3vJnw722H7c8MxxNe1ScdXyGX4+LFBGBnohtIKNWZtOobz1wra8pKIiEyGwfOwdESGjOMmag1llWp8/sdVfLw3HmWVGsgkYEJfT+y+mIlKtcDg7p3w2YzBcLWv/7FnY0orqjBz4zEcT8pDJzsFtj4Tjp4qxza4CiIi42qzeViIqJqNQo7n7w5E1P+Nwf39vKARwM/nMlCpFpjY3xv/eSqsWWEFAOysrbBx1hCEdHVGXmklHv/8aKvOB0NEZIrYwkLUCg7F5+CT6AQM9XfFc2MCIGuFGXLzSysw7bMjuJxRBG9nG3zzbDi6drJrhWqJiDoGQ35+M7AQdWDZReWY+ulhXM0pwcBuLtjx3HBjl0RE1Gr4SIjITLg7KvHZjMEAgLNpBVBrTP7/F0REzcLAQtTB+Xa2g0yqnjU3p7j8zjsQEZkhBhaiDs5KLoOHow0AIKOgzMjVEBEZBwMLkQlQOdcElkIGFiKyTAwsRCbA06l6sU+2sBCRpWJgITIBXs62ANjCQkSWi4GFyASonKofCWWyhYWILBQDC5EJ8HSufiSUzsBCRBaKgYXIBHg6VT8SyuQjISKyUAwsRCbAs9YoITOYnJqIyGAMLEQmwLOmD0tphRpF5VVGroaIqP0xsBCZAFtrOZxsrABwaDMRWSYGFiIToRvazMBCRBaIgYXIRHC2WyKyZAwsRCaCs90SkSVjYCEyEZ6c7ZaILBgDC5GJ8ORst0RkwRhYiEyEdrZbtrAQkSViYCEyEdr1hNiHhYgsEQMLkYnQDmvOLalAeZXayNUQEbUvBhYiE9HJTgFrq+q/slmF5UauhoiofTGwEJkISZKgcmI/FiKyTAwsRCbEy4mz3RKRZWJgITIh2tluM9nCQkQWhoGFyIRwtlsislQMLEQmRDu0OZ0tLERkYRhYiEyIdmgzZ7slIkvDwEJkQjjbLRFZKgYWIhOifSSUWVgGjUYYuRoiovbDwEJkQjwcbSBJQKVa4EZphbHLISJqNwwsRCbE2kqGzvYcKUREloeBhcjEaPuxcC4WIrIkDCxEJsazZrbbdLawEJEFYWAhMjFsYSEiS8TAQmRiPGtGCrEPCxFZEgYWIhOjHdrMuViIyJIwsBCZGO1st2xhISJLwsBCZGI42y0RWSIGFiITo30kVFRWhZLyKiNXQ0TUPhhYiEyMo40CDkorAGxlISLLwcBCZIJUTjVDm1vYj0UIgT9/cRyzNh3j2kRE1KExsBCZIE/n1hkplJZ3E79fzkJ0bDau5d9sjdKIiNoEAwuRCdL2Y2npbLdxmUW631/JKmpkSyIi42JgITJBXjUtLC2d7Ta2dmDJLG7RsYiI2hIDC5EJaq3ZbuMyarewMLAQUcfFwEJkglprttvYWq0q8QwsRNSBNSuwrF27Fr6+vrCxsUFYWBiOHTvW6Pb5+fmYP38+vLy8oFQq0bNnT/z8888tOiaRJWuN2W6r1BokZOkHFiE4UoiIOiaDA8vWrVuxaNEiLF26FCdPnkT//v0RGRmJrKyserevqKjA+PHjkZSUhG3btiE2Nhbr169Hly5dmn1MIkunqpntNqe4HFVqTbOOkZRbigq1BrYKOeQyCcXlVZzXhYg6LIMDywcffIC5c+di9uzZCA4Oxrp162BnZ4eNGzfWu/3GjRtx48YN7Ny5E8OHD4evry9Gjx6N/v37N/uYRJbOzV4JK5kEjQCyi8ubdQztCKGeno7w7WwHgB1viajjMiiwVFRUICYmBhEREbcOIJMhIiIChw8frnef77//HuHh4Zg/fz5UKhX69u2LlStXQq1WN/uY5eXlKCws1HsRWRKZTIKHY3UrS3OHNsfWdLgNUjkg0MMRADveElHHZVBgycnJgVqthkql0ntfpVIhIyOj3n2uXr2Kbdu2Qa1W4+eff8Ybb7yB999/HytWrGj2MVetWgVnZ2fdy8fHx5DLIDIL2snjmjvbra6FReWIQJUDACCec7EQUQfV5qOENBoNPDw88NlnnyE0NBRTp07F3/72N6xbt67Zx1y8eDEKCgp0r9TU1FasmMg0tHS2W+0cLEGejgjw0AYWtrAQUcdkZcjGbm5ukMvlyMzM1Hs/MzMTnp6e9e7j5eUFhUIBuVyue693797IyMhARUVFs46pVCqhVCoNKZ3I7KhaMBdLWaUaSTklAIAglaOuH0xcZvVIIUmSWq9QIqJWYFALi7W1NUJDQxEVFaV7T6PRICoqCuHh4fXuM3z4cMTHx0OjuTWSIS4uDl5eXrC2tm7WMYno1my3zWlhScguhkYALnYKuDsq0cPdAZIEFNysRE5xRWuXSkTUYgY/Elq0aBHWr1+PzZs349KlS5g3bx5KSkowe/ZsAMCMGTOwePFi3fbz5s3DjRs3sGDBAsTFxeGnn37CypUrMX/+/CYfk4jqakkLS+3+K5IkwUYhRzfXmpFC7MdCRB2QQY+EAGDq1KnIzs7GkiVLkJGRgQEDBmDXrl26TrMpKSmQyW7lIB8fH/z666/4y1/+gpCQEHTp0gULFizAq6++2uRjElFd2un5m7OeUGxGdV+VnjWdbQEg0MMBybmliM8qxrAebq1TJBFRKzE4sADA888/j+eff77ez6Kjo+u8Fx4ejiNHjjT7mERUl3a22/SCMoP7nWhbWIJUjrr3AjwcsedSFjveElGHxLWEiEyUh1N1x/PyKg0KblYatK92DpaetQJLYM1IIU4eR0QdEQMLkYmyUcjRyU4BwLCOt8XlVbiWfxOAfmDRDm3m5HFE1BExsBCZMG3HW0Nmu71S8zjIw1GJTvbWuvd71ASWnOJy5JVwpBARdSwMLEQmzKsZs93G1ZowrjYHpRW6uFT3i4nPZisLEXUsDCxEJqw5s93eGiHkWOezAPZjIaIOioGFyISpmjG0ub4RQlqBnKKfiDooBhYiE6Z9JGRIHxbtGkI9PesJLCptx1tOHkdEHQsDC5EJM3S22xslFcguql43SNuaUhsXQSSijoqBhciEafuwNPWRkPZxkI+rLeyVdeeNDHCvbnVJLyhDUZlhc7sQEbUlBhYiE6adnj+vtBJlleo7bt9Y/xUAcLZTwMOxekI6trIQUUfCwEJkwpxtFbBRVP81bkorS30z3N5O24+FgYWIOhIGFiITJkmSrpWlKf1YGpqDpbZAj+rPGFiIqCNhYCEycbqOt3doYRFCNKmFpQen6CeiDoiBhcjEaYc236mFJbOwHIVlVZDLJPi72ze4nW4RRA5tJqIOpO4wASIyKaomznarnX/Fz80eSit5g9tpA0ta3k2UVlTBzrrt/pkQQiC7qBxXsopxJbMIaXk3MXlgF/Tt4txm5yQi08TAQmTiPJs4221cRuMjhLQ6Oyjham+NGyUVuJpd0irhQQiBrKJyxGUW4UpmMa5kaX8tRsFN/eHTp1Lz8b95w1p8TiIyLwwsRCbOs4krNutmuL1DYAGqJ5A7lngD8VnFLQos35xIxdfHUnAlqxhFZVX1biOTgO6d7dG9sx2iY7NxNi0fZZVq2CgabgUiIsvDwEJk4jybuGLzrRFCdWe4vV1gTWBpST+WkvIqvL7zPCqqNACqg4lvZ3sEqhwQ6OGo+9Xf3R42CjmEEBjy9yjkFJfjbFoB7vJzbfa5icj8MLAQmThtYMkqKodGIyCTSXW20WiELrA0tYUFaNmqzX9cyUZFlQZdO9li/YzB8HdvvO+MJEkY3L0Tdl3IwInkGwwsRKSHo4SITJy7gxIyCajSCOSUlNe7TWpeKcoqNbC2kqF754ZHCGm1xlwsv13MBABE9vFEby+nRsOK1mDfTgCAmKS8Zp+XiMwTAwuRibOSy+BeM51+Q0ObtfOvBHo4QF5PC8zttLPdJuWWoLzqzlP+365KrcHvl7MAAOODVU3eL7R7TWBJyYNGIww+LxGZLwYWIjNwp9lu77SG0O08HJVwtLGCRgCJOSUG13MiOQ/5pZVwsVNgcE0IaYo+3s5QWsmQX1qJqzmcuI6IbmFgITIDqjsMbY6t6YvSs5Ep+WuTJEk3H0tzHgvtrnkcdHcvD1jJm/7PjLWVDP19XAAAJ/hYiIhqYWAhMgPa2W4bGtrc1DlYatP2YzG0460QQhdY7jHgcZCWtkXmRDIDCxHdwsBCZAYam+22okqDhGzDWliAWyOFDG1hicssRsqNUlhbyTAy0N2gfQFgiG/16KAYBhYiqoWBhcgMNDbbbVJuCao0Ag5KK3jXBJumCFA1b02h3RczAAAjAtxgrzR85oRB3apbWBJzSpBTXP+oJyKyPAwsRGagsU63t1ZodoAk3XmEkJa2D0tiTgmq1Jom76d9HGTI6KDanO0U6FkTltjKQkRaDCxEZsCzkRWbb81w2/THQQDg7WwLO2s5KtUCyTdKm7RPZmEZzqQVAADG9fIw6Hy1hXbnYyEi0sfAQmQGtIGlpEKNojL9xQRvtbAYFlhkMsngGW+1rSsDfFzg4dT0x0+303a8PZ50o9nHICLzwsBCZAbsrK3gaFPdX+T2fiyGzsFS262Ot03rx9LSx0Fa2hlvz18rQFml4RPXEZH5YWAhMhP1DW2+WaHWPc4xZISQlq6FpQkjhYrLq3A4IRdA84Yz19bN1Q5uDkpUqgXO1jxiIiLLxsBCZCZU9XS8jc8qhhBAZ3truDkoDT6mIXOx7I/LRoVaA9/Odrqg01zahRAB4EQyHwsREQMLkdmob2hzrAErNNdHO1IoIbsY6jus7VP7cZAho5EawoUQiag2BhYiM+FZz+RxzR0hpOXjagdrKxnKqzS4lnezwe0q9RY79GzWuW7HhRCJqDYGFiIzUd/Q5uaOENKSyyT0cL/zBHLHk26g4GYlXO2tdUGjpbgQIhHVxsBCZCZ0k8fV28LS/D4lTel4W3uxQ7ms5Y+DAC6ESET6GFiIzMStTrfV09kX3KzUjRgKbGYLC3CrH0tDHW9rL3bY0uHMt+NCiESkxcBCZCa0w5pzistRUaXBlZrWFW9nGzjZKJp93MA7zMVyOaMIaXk3obSSYWSgW7PPUx8uhEhEWgwsRGbC1d4a1vLqv9JZRWW3Rgg1s8OtVqDq1qrNQtTt/KptXRkZ6AY7a8MXO2wMF0IkIi0GFiIzIUkSPJyq51rJLCxDXEbzZ7itrXtne1jJJJRUqPUmpdNqq8dBABdCJKJbGFiIzIhnrX4sLZ2DRUshl8HPzR5A3Y636QU3ce5aASQJuLtX6wcWgAshElE1BhYiM+Kpm57/pm5Ic3PnYKnt1iKI+v1Y9tS0rgzq1gnujobPpNsUuo63XAiRyKIxsBCZEW0Ly4XrhcgrrYQkocXT5AO1O97qt7D81oaPg7RuLYRYyIUQiSwYAwuRGdG2sPxxJRsA4NvZHjYKeYuPG1DzWKn2I6HCskocuVq92GFbBhbtQogVag3OXeNCiESWioGFyIx46oY2VwCArsNqS9VuYdGOFNoXm41KtYC/u71uNty2oLcQIieQI7JYDCxEZkT7SEirpSOEtPzc7CGTqiejy64ZXtyWo4Nup30sxH4sRJaLgYXIjKhuCywtnYNFy0YhR/fO1SOF4jOLUanWYG9s9WKH97RDYOFCiETEwEJkRm4PLK3VwgKg1iKIxTh69QaKyqrQ2d4aA3xaZ7HDxnAhRCJiYCEyI9ZWMrg5WAMAFHIJvjXzp7QG7Yy3V7KKsPtiBgBgXO/WW+ywMVwIkYgYWIjMjLaVxd/NAQp56/0V13a8jcssrtV/xbPVjn8nXAiRyLI161+ztWvXwtfXFzY2NggLC8OxY8ca3PaLL76AJEl6Lxsb/WbrWbNm1dlmwoQJzSmNyOJpO962Vv8VrUCP6uOdTM7D9YIy2ChkGBHQuosdNoYLIRJZNoMDy9atW7Fo0SIsXboUJ0+eRP/+/REZGYmsrKwG93FyckJ6errulZycXGebCRMm6G3z1VdfGVoaEeHWRHEDah6htJYeHtWPl6pqOr2ODHSHrXXL53hpKi6ESGTZDF5a9YMPPsDcuXMxe/ZsAMC6devw008/YePGjXjttdfq3UeSJHh6Nt50rFQq77iNVnl5OcrLb/2DVVhY2MTqiczf83cHYGC3ThgT5N6qx7WztkLXTrZIy7sJoH2GM9emXQgxLrMYMcl5iOzTfo+jiMj4DGphqaioQExMDCIiIm4dQCZDREQEDh8+3OB+xcXF6N69O3x8fDBp0iRcuHChzjbR0dHw8PBAUFAQ5s2bh9zc3AaPt2rVKjg7O+tePj4+hlwGkVlztFFgQl/PVpnh9nba1huZBIzr5dHqx78TLoRIZLkMCiw5OTlQq9VQqfT/Z6VSqZCRkVHvPkFBQdi4cSO+++47/Oc//4FGo8GwYcOQlpam22bChAnYsmULoqKi8Pbbb2Pfvn249957oVbXv27I4sWLUVBQoHulpqYachlE1Ezajreh3Tuhs0PbLHbYGC6ESGS5DH4kZKjw8HCEh4frvh42bBh69+6NTz/9FG+99RYAYNq0abrP+/Xrh5CQEPTo0QPR0dEYN25cnWMqlUoole3/jyWRpZs6pBtikvPwl4ieRjn/7QshtkUrEhF1TAa1sLi5uUEulyMzM1Pv/czMzCb3P1EoFBg4cCDi4+Mb3Mbf3x9ubm6NbkNE7S/AwwHbnxuOYe04Oqg2LoRIZLkMCizW1tYIDQ1FVFSU7j2NRoOoqCi9VpTGqNVqnDt3Dl5eXg1uk5aWhtzc3Ea3ISLLw4UQiSyXwcOaFy1ahPXr12Pz5s24dOkS5s2bh5KSEt2ooRkzZmDx4sW67ZcvX47ffvsNV69excmTJ/HEE08gOTkZTz31FIDqDrkvv/wyjhw5gqSkJERFRWHSpEkICAhAZGRkK10mEZkL7WOhmGT2YyGyJAb3YZk6dSqys7OxZMkSZGRkYMCAAdi1a5euI25KSgpksls5KC8vD3PnzkVGRgY6deqE0NBQHDp0CMHBwQAAuVyOs2fPYvPmzcjPz4e3tzfuuecevPXWW+ynQkR16BZCTM6DEAKSdOelAVJvlOL7M9cxxNcVd/m5tnWJRNQGJCGEyS99WlhYCGdnZxQUFMDJycnY5RBRG6qo0qDfsl9RXqXBnkWjdUOtbyeEQExyHjYeTMSu8xnQCMDFToEji8exsy5RB2HIz+82HyVERNSatAshHku8gZjkG3UCS6Vag5/PpWPjgUScSSvQ2y+/tBK/nE/HlIFd27tsImohLn5IRCZH2/H2eK2Ot/mlFfgkOh4j396LBV+fxpm0AlhbyTB1sA9+XTgKL4wNAAB8eSTFKDUTUcuwhYWITE71QogJiEnOQ3xWMTYdTMT/TqahrFIDAHBzUGJGeHc8FtYNbjUT3LnYKbAm6gpOJOchNqMIQa28OCQRtS0GFiIyObUXQoz4YJ/u/d5eTpgzwg8T+3tBaaXfT0XlZIPxvVXYdSED/z2ajDcn9W3XmomoZfhIiIhMjrOdAr29qjvoSRIQ0VuFr+YOxc8vjsDDoV3rhBWtx8K6AQC2n7yG0oqqdquXiFqOLSxEZJLefTgE+69k476+XvB1s2/SPiMC3NDN1Q4pN0rx45l0PDrE/BZOLatUQ2kla9JwbyJTwhYWIjJJfbs447kxAU0OKwAgk0m6VpYvjya3VWlGc+RqLoKX7MLavVzWhMwPAwsRWZSHQ7tCIZdwJq0A581sPaJtMWnQCOCrY6kwgym2iPQwsBCRRXFzUGJC3+p1yr48aj5DnIUQOHAlBwBwLf8m4rOKjVwRUetiYCEii/PYXdWPhb47fQ1FZZVGrqZ1xGcVI6OwTPf13tgsI1ZD1PoYWIjI4gz1d4W/uz1KK9T47vR1Y5fTKv6oaV2R1fS13Xs524jVELU+BhYisjiSJOHxsO4Aqh8LmUN/jwPx1YFl6pDq1qPjSTfMpvWICGBgISIL9dCgLrC2kuFSeiFOp+Ybu5wWqajS4MjVXADAE0O7wd/NHlUagYM1IYbIHDCwEJFFcrGzxgMh5tH59mRKHkor1HBzsEZvTyeMCfIAwMdCZF4YWIjIYj1eMyfLD2euo6DUdB+f/HGlOpgMD3CDTCZhbC93AEB0XJZZPO4iAhhYiMiCDerWCb08HVFepcH2U2nGLqfZtMOZRwZWB5W7/Fxhq5Ajs7Acl9KLjFkaUathYCEii1Xd+VY7861pdr7NK6nA2ZoJ8EYEuAEAlFZyDA/oDIDDm8l8MLAQkUWbNLALbBVyxGcV43hSnrHLMdihhFwIAQR6OMDT2Ub3vrYfSzQDC5kJBhYismhONgpMGuANwDTXFzoQX91/Rfs4SGtMUPXXMcl5Jt0/h0iLgYWILJ52QcRfzmXgRkmFQfum3ijFC1+dwvIfLkKjad9HSkII7I/T9l9x0/usayc79FQ5QCOA/Vc4WohMHwMLEVm8kK4u6NfFGRVqDbbFpDZpHyEE/ns0BRPW7McPZ65j48FEvPtbbBtXqi8ptxTX8m9CIZcQ5u9a5/Ox2uHNfCxEZoCBhYgIt4Y4//doyh1bStILbmLmpuP4645zKKlQo6fKAQDwr+gE/C+m/UYbaYczh3bvBDtrqzqfa/ux7IvNbvfWH6LWxsBCRARgYn9vOCitkJRbisM1s8beTgiBbTFpuOcf+7E/LhvWVjK8fn9v/LJgFJ4fGwAAWLz9HGKSb7RLzX/cNpz5doN9O8FBaYXckgqcqxlJRGSqGFiIiADYK60wZWAXAPV3vs0qLMPcLSfw0rdnUFRWhf4+Lvj5xZF4aqQ/5DIJi8b3xIQ+nqhQa/D0lhik5ZW2ab2Vag2OJFQHq9v7r2gp5DLdZ9Gx7MdCpo2BhYiohrbz7W8XMpFVVAagulXlu9PXcM+a/dhzKQsKuYSXI4Pwv2fDEeDhoNtXJpPwwdT+6OPthNySCjy1+QSKy6varNYzqfkoKq9CJzsF+ng7N7iddrQQ+7GQqWNgISKq0dvLCYO6uaBKI/DtiTTkFpfjuS9PYsHXp5FfWok+3k744YURmD82AFbyuv982llbYf2MwXB3VOJyRhEWfHUK6jbqO6J9HDQswA1ymdTgdtp+LGfS8pFbXN4mtRC1BwYWIqJaHg/rDgDYdDAJ9/xjP345nwErmYQF4wKxc/5w9PJ0anR/bxdbrJ8xGEorGaIuZ+GdXZfbpE5th9tRDTwO0lI52SDYywmCw5vJxDGwEBHVcn+IF5xtFcgpLkduSQWCVI7YOX84/jK+JxT1tKrUZ4CPC959pD8A4NP9V/HtiaYNlW6qgpuVOJNWMx1/Ax1ua9MuhsjVm8mUMbAQEdVio5DjhbsDYKuQY96YHvj+heHo26XhPiIN+VN/b7w4LhAA8Ncd53A8qfVGDh1OyIVaI+DvZo8uLrZ33F47H8u+uOw2e0RF1NYYWIiIbvPUSH9cXB6JVyf0gtJK3uzjLBwXiPv6eaJSLfDMv2OQeqN1Rg7dmo6/8cdBWgN8XOBsq0DBzUqcTjW99ZKIAAYWIqJ6SVLDHVmbSiaT8P4jA9CvizNulFRgzubjKCpr+bo+B2o63DblcRAAWMllGNWTj4XItDGwEBG1IVtrOdbPGAwPRyXiMovxYgtHDqXeKEVSbimsZBKG1jMdf0PG1ASW6DgObybTxMBCRNTGPJ1t8PnM6pFDe2OzsfqXS80+lnY488BuLnC0UTR5v9E187Gcv1aIrMKyZp+/qbKLynE1u7jNz0OWg4GFiKgdhHR1wfuPVo8cWv9HIrY1c80h7XDmhqbjb4ibgxL9u1Z3Ho6Oa93HQlVqDc5fK8DmQ0lY8PUpjHzndwz5+x7c/f4+7LmY2arnIstVd7UsIiJqEw+EeONKZjE+jLqC13eeQ0hXZ/RUOTZ5f7VG4GC8tv9K0zrc1jYmyANn0goQHZuFRwf7GLy/Vm5xOU6m5ONkSh5OJufhbFoBblaq6932nV8vY2wvj0YntyNqCgYWIqJ2tGBcIE6m5OGPKzmY/+VJfPf88HpXWq7P2bR8FJZVwcnGCiHNGGo9tpcHPoy6gj/iclCp1jR5XhkAyC+twDu/xuJgfA6Sc+uOdnK0scKgbp2qX91d4O/ugHvX7EdcZjF+PHsdkwZ0MbheotoYWIiI2pFMJuEfUwfgvg//wJWsYiz57gLeq5lk7k60o4OG9XCrd2mAOwnp4ozO9tbILalATHIehvp3btJ+GQVlmLHxKOIyb/VJCfRw0IWTQd06oYe7A2S3taI8Pcof7/0Whw/3XMH9/byaVTORFv/0EBG1MzcHJT6cNhAyCdgWk4b/NbE/yx81j4NG9jT8cRBQHZZG9zRsMcSr2cV46F+HEJdZDJWTEp/PGIwzS+/B7kWj8fbDIZg6pBsCVY51wgoAzBruh052ClzNKcHO09ebVTORFgMLEZERhPfojIURPQEAr+88j/isoka3Ly6vwsnk6knfRgYY1uG2tjG9ama9jb1zx9tzaQV4eN1hXMu/CT83e2x7dhgiglVwtm3a6CQHpRWeHd0DAPBhVBwq1Zpm103EwEJEZCTzxwZgeEBn3KxU47kvT+JmRf0dVwHg6NVcVGkEurnaoVtnu2afc1SgG2QScDmjCNfzbza43aH4HEz77DBulFSgbxcnfPtsOHxcDT/vjHBfuDkokXrjJr490byRUUQAAwsRkdHIZRLWTB0I95pJ5ZZ9f6HBbbXzrzR1Ov6GuNhZY2C3TgCA6AZaWX4+l45Zm46jpEKNYT0646u5Q+HmoGzW+Wyt5Zg/trqV5ePfr6C8quFQRtQYBhYiIiNyd1Tiw6kDIEnA1hOp2HGq/laIW/OvtCywAMDYoIb7sXx5NBnz/3sSFWoN7u3riY2zhhg0QV19pt/VDV7ONrheUIavj7XuytVkORhYiIiMbFiAG168u3pl57/tOI/4LP0ZYq/n30RCdglkEhDeo+WBZUzN6s0H43N0LR5CCPwz6gr+tuM8hKgOGR8/Ngg2iuYv/qhlo5Bj/tgAAMDavfEoa2DOFqLGMLAQEXUAL44LRLh/Z5RWqPH8f0/q/VDXDmfuX7Pqckv18XaCh6MSpRVqHE/Mg0Yj8OYPF/H+7jgAwAt3B2DllL6tOtnbo4N90LWTLbKKyvGfI8mtdlyyHAwsREQdgFwm4cPpA+DmYI3LGUV484eLus90w5kNnI6/IZIkYUzNY6HfLmZg4dbT+OJQEgBg6cRg/N89Qa2yWnVt1lYyXSvSJ9EJKCmvatXjk/ljYCEi6iA8HG2wZupASBLw1bEUfHf6GjS1puNvjf4rWmNrHgttOZyM789ch5VMwpqpAzB7uF+rneN2Dw7qAt/OdrhRUqELSERNxcBCRNSBjAh0wws1/T3+uv0cfjyXjhslFXBQWmGAj0urnWd4oBusah752ChkWD9zMCYPbNvp863kMt3cM5/tv4rCsso2PR+ZFwYWIqIOZkFET4T5uaKkQo1FW08DAIb6dzZo7Z87cbJR4NEhPujiYosvnxqqa3FpaxP7eyPQwwEFNyux8UBiu5yTzAMDCxFRByOXSfho+kB0trdGlUYAAEY1czr+xqyc0g8HXh2L0O6dWv3YDZHLJF0ry4Y/EpFfWtFu5zY1O09dw8vfnrnjLMiWolmBZe3atfD19YWNjQ3CwsJw7NixBrf94osvIEmS3svGxkZvGyEElixZAi8vL9ja2iIiIgJXrlxpTmlERGZB5WSDf9TMzwK0Xofb27V259qmuLevJ3p5OqKovAqf7b/a7uc3BRsOJGLh1tP4NiYNE9b8gb//dBFFFv4IzeDAsnXrVixatAhLly7FyZMn0b9/f0RGRiIrq+GFtJycnJCenq57JSfrD2l755138NFHH2HdunU4evQo7O3tERkZibKyMsOviIjITIzq6Y51T4RizdQB8HOzN3Y5rUYmk7BofHUryxeHkpBbXG7kijqWT/cl4K0fq0eJ9fJ0RJVGYP0fibj7/X3YcSoNQggjV2gcBgeWDz74AHPnzsXs2bMRHByMdevWwc7ODhs3bmxwH0mS4OnpqXupVCrdZ0IIrFmzBq+//jomTZqEkJAQbNmyBdevX8fOnTubdVFEROYiso9nm3eGNYbxwSqEdHVGaYUa6/YlGLucDmPt3nis+uUyAODFuwPwy4KR2DR7CPzc7JFdVI6/bD2DRz89jAvXC4xcafszKLBUVFQgJiYGERERtw4gkyEiIgKHDx9ucL/i4mJ0794dPj4+mDRpEi5cuLVeRmJiIjIyMvSO6ezsjLCwsAaPWV5ejsLCQr0XERGZDkm61cqy5XAysgqN36IuhEB2UTnOpRVArWnfVgwhBNbsicO7v8YCABaN74lFNfPhjA3ywK6FI/HKhCDYKuQ4npSHif88gCXfnUdBqeU8JrIyZOOcnByo1Wq9FhIAUKlUuHz5cr37BAUFYePGjQgJCUFBQQHee+89DBs2DBcuXEDXrl2RkZGhO8btx9R+drtVq1bhzTffNKR0IiLqYEb3dEdo906ISc7DJ9EJWPanPu1yXrVGIPVGKRKyixGfVVzr1xIU3KwOABG9VfjXE4NadWRWQ4QQeP+3OHy8Nx4A8MqEIDw3JkBvG6WVHM+NCcDkAV2w8udL+PFsOrYcTsaPZ9PxSmQQHh3sA1krzkzcERkUWJojPDwc4eHhuq+HDRuG3r1749NPP8Vbb73VrGMuXrwYixYt0n1dWFgIHx+fFtdKRETtR5Ik/N/4nnjs86P479EUzB3ljy4utq16DiEEDsbn4lhiLhKySxCfVYzEnBJUqDUN1ATIJAl7LmVi0TdnsGbqgFZdoqC++lb/chmf1nQ+fv3+3nhqpH+D23u72OLjxwbhsbAcLP3uAq5kFeO17efw1bEUvDmpb6vO1dPRGBRY3NzcIJfLkZmZqfd+ZmYmPD09m3QMhUKBgQMHIj6+Oklq98vMzISXl5feMQcMGFDvMZRKJZTK5i11TkREHcewADcM9XfFkas3sPyHC/j7lH5wc2j5v+9CCOyLy8aaPVdwOjW/zudKKxn83R3Qw90eAR4OCPBwQA93B/i52eNwQi6e/vcJ/HDmOmwVMqx+MKRNWi+EEHjrx0vYeLB6PpqlE4ObPNPwsB5u+HnBSGw5nIw1u+NwJq0Ak9cexNTBPnh5QlCrfA87GoMCi7W1NUJDQxEVFYXJkycDADQaDaKiovD888836RhqtRrnzp3DfffdBwDw8/ODp6cnoqKidAGlsLAQR48exbx58wwpj4iITNBL9wTh4XWH8euFTOyNzcbkAd748wg/9PJ0MvhYQggciM/BP3bH4WRKPoDqmXzv7+eNXp6OunDi7WLbYMvJ2F4e+GjaQMz/70l8cyINdtZWWDoxuFWHgGs0Ast+uIAth6tHzb41uS+eHNrdoGMo5DLMGeGHif298PYvsfjfyTRsPZGKn8+nY9H4nnhyaHdYtcMjrfYiCQPHR23duhUzZ87Ep59+irvuugtr1qzBN998g8uXL0OlUmHGjBno0qULVq1aBQBYvnw5hg4dioCAAOTn5+Pdd9/Fzp07ERMTg+DgYADA22+/jdWrV2Pz5s3w8/PDG2+8gbNnz+LixYt15mypT2FhIZydnVFQUAAnJ8P/gBMRkXHtuZiJf+6Nx5larSEjAtwwZ4QfRvd0v2MLhxAChxJy8Y/dcTiRnAeguhXlyaHd8czoHnB3NLzFYfvJNCz65gwAYP7YHng5spfBx6iPRiPwt53n8dWxFEgSsGpKP0y7q1uLjxuTfANLv7+A89eqB6IEqRyx7E99EN6jc4uP3VYM+fltcB+WqVOnIjs7G0uWLEFGRgYGDBiAXbt26TrNpqSkQCa7lejy8vIwd+5cZGRkoFOnTggNDcWhQ4d0YQUAXnnlFZSUlODpp59Gfn4+RowYgV27djUprBARkemLCFZhXG8PnEzJw4YDidh1PgMH4nNwID4H/u72mD3cDw8N6gI767o/tg7XBJVjSTcAVK8M/XhYN8wb3QMeTs3/OfLgoK4orVDj9Z3nsXZvAuysrTB/bMCdd2yEWiOwePtZfHMiDZIEvPtwfzwc2rVFx9QK7e6K7+aPwNfHU/Der7GIzSzC9PVHcH+IF/52X294t3L/oPZmcAtLR8QWFiIi85J6oxSbDyVh6/FUFJVXAQCcbRV4LKwbZob7wtPZBkev5uIfe+Jw5GpNUJHL8FhYN8wb0wOqFgSV263ffxV///kSAGDJA8H484jmrWhdWlGF13ecx/ZT1yCTgH9MHYBJA9pmjp380gq8/1scvjyaDI0AbBVyzB/bA0+N9IeNQt4m52wOQ35+M7AQEVGHVVxehW9PpGLTwSSk3CgFAFjJJASqHHEpvfrRh7VchqlDfPDc2B7wcm6bVoQ1e+KwZk/1kjGrHzTsEU5OcTm2HErCliPJyC+thFwm4cNpA/BAiHeb1FrbhesFWPb9BRxPqn5M1s3VDkseCMa43h5GWZbhdgwsRERkVtQagT2XMrHhQCKOJVa3qCjkEh4d7IP5YwPa/HGHEAKrfrmMz/ZfhSQBa5rQOnI1uxifH0jE/2LSUF5VPYy6m6sdlk4Mxrjeqkb3bU1CCHx/5jpW/nwJmYXVyyCMCXLHkgeC4e/u0G511IeBhYiIzNa5tAKcTsvH2CB3dO1k127nFULgje/O4z9HUiCXSfjX44NwT5+6U3rEJN/Ap/uuYvelTGh/wvb3ccEzo/wR2cezTed1aUxxeRU+/j0eGw5cRaVaQJKALi62uuHd2l97uDvAw1HZLi0wDCxERERtQKMReGnbGWw/eQ3Wchk+nzkYo3q6Q6MR2H0pE5/tv4qYmlFKADCulweeHuWPu/xcO8QjGKC65Wf5jxcRHZvd4DYOSiv414QXfzd79PBwgL+7PQI9HFs1cDGwEBERtZEqtQYvfn0KP5/LgI1ChmdH98D3p6/jak4JgOo+NVMGdsFTI/0QqHI0crUNyykuR0JWMa7mlOh+vZpdjJQbpahvKSVJAi4tn9CqnXbbdFgzERGRJbOSy7Bm6kDcrDiBvbHZus64TjZWeGJod8wa5tui4dTtxc1BCTcHJcL89edpKa9SIyW3eq2lhOwSXM0uQUJ2MSrVGqOOMGILCxERUTOUVaqx4OtTuJJVjMfDumPqEB84KNkOYAi2sBAREbUxG4Ucnz452NhlWAzzWWSAiIiIzBYDCxEREXV4DCxERETU4TGwEBERUYfHwEJEREQdHgMLERERdXgMLERERNThMbAQERFRh8fAQkRERB0eAwsRERF1eAwsRERE1OExsBAREVGHx8BCREREHR4DCxEREXV4VsYuoDUIIQAAhYWFRq6EiIiImkr7c1v7c7wxZhFYioqKAAA+Pj5GroSIiIgMVVRUBGdn50a3kURTYk0Hp9FocP36dTg6OkKSpFY9dmFhIXx8fJCamgonJ6dWPXZHwus0H5ZwjQCv09zwOs2HIdcohEBRURG8vb0hkzXeS8UsWlhkMhm6du3apudwcnIy2z9ctfE6zYclXCPA6zQ3vE7z0dRrvFPLihY73RIREVGHx8BCREREHR4Dyx0olUosXboUSqXS2KW0KV6n+bCEawR4neaG12k+2uoazaLTLREREZk3trAQERFRh8fAQkRERB0eAwsRERF1eAwsRERE1OExsNTYv38/Jk6cCG9vb0iShJ07d+p9LoTAkiVL4OXlBVtbW0RERODKlSvGKbYF7nSds2bNgiRJeq8JEyYYp9hmWrVqFYYMGQJHR0d4eHhg8uTJiI2N1dumrKwM8+fPR+fOneHg4ICHHnoImZmZRqq4eZpynWPGjKlzP5999lkjVdw8//rXvxASEqKbhCo8PBy//PKL7nNzuJd3ukZzuI/1Wb16NSRJwsKFC3XvmcP9vF1912kO93TZsmV1rqFXr166z1v7XjKw1CgpKUH//v2xdu3aej9/55138NFHH2HdunU4evQo7O3tERkZibKysnautGXudJ0AMGHCBKSnp+teX331VTtW2HL79u3D/PnzceTIEezevRuVlZW45557UFJSotvmL3/5C3744Qd8++232LdvH65fv44HH3zQiFUbrinXCQBz587Vu5/vvPOOkSpunq5du2L16tWIiYnBiRMncPfdd2PSpEm4cOECAPO4l3e6RsD07+Ptjh8/jk8//RQhISF675vD/aytoesEzOOe9unTR+8aDhw4oPus1e+loDoAiB07dui+1mg0wtPTU7z77ru69/Lz84VSqRRfffWVESpsHbdfpxBCzJw5U0yaNMko9bSVrKwsAUDs27dPCFF97xQKhfj2229121y6dEkAEIcPHzZWmS12+3UKIcTo0aPFggULjFdUG+nUqZP4/PPPzfZeCnHrGoUwv/tYVFQkAgMDxe7du/WuzdzuZ0PXKYR53NOlS5eK/v371/tZW9xLtrA0QWJiIjIyMhAREaF7z9nZGWFhYTh8+LARK2sb0dHR8PDwQFBQEObNm4fc3Fxjl9QiBQUFAABXV1cAQExMDCorK/XuZ69evdCtWzeTvp+3X6fWl19+CTc3N/Tt2xeLFy9GaWmpMcprFWq1Gl9//TVKSkoQHh5ulvfy9mvUMqf7OH/+fNx///169w0wv7+bDV2nljnc0ytXrsDb2xv+/v54/PHHkZKSAqBt7qVZLH7Y1jIyMgAAKpVK732VSqX7zFxMmDABDz74IPz8/JCQkIC//vWvuPfee3H48GHI5XJjl2cwjUaDhQsXYvjw4ejbty+A6vtpbW0NFxcXvW1N+X7Wd50A8Nhjj6F79+7w9vbG2bNn8eqrryI2Nhbbt283YrWGO3fuHMLDw1FWVgYHBwfs2LEDwcHBOH36tNncy4auETCf+wgAX3/9NU6ePInjx4/X+cyc/m42dp2AedzTsLAwfPHFFwgKCkJ6ejrefPNNjBw5EufPn2+Te8nAQnqmTZum+32/fv0QEhKCHj16IDo6GuPGjTNiZc0zf/58nD9/Xu+5qjlq6Dqffvpp3e/79esHLy8vjBs3DgkJCejRo0d7l9lsQUFBOH36NAoKCrBt2zbMnDkT+/btM3ZZraqhawwODjab+5iamooFCxZg9+7dsLGxMXY5baYp12kO9/Tee+/V/T4kJARhYWHo3r07vvnmG9ja2rb6+fhIqAk8PT0BoE7v5szMTN1n5srf3x9ubm6Ij483dikGe/755/Hjjz9i79696Nq1q+59T09PVFRUID8/X297U72fDV1nfcLCwgDA5O6ntbU1AgICEBoailWrVqF///748MMPzepeNnSN9THV+xgTE4OsrCwMGjQIVlZWsLKywr59+/DRRx/BysoKKpXKLO7nna5TrVbX2cdU72ltLi4u6NmzJ+Lj49vk7yYDSxP4+fnB09MTUVFRuvcKCwtx9OhRvWfM5igtLQ25ubnw8vIydilNJoTA888/jx07duD333+Hn5+f3uehoaFQKBR69zM2NhYpKSkmdT/vdJ31OX36NACY1P2sj0ajQXl5udncy/por7E+pnofx40bh3PnzuH06dO61+DBg/H444/rfm8O9/NO11nf43VTvae1FRcXIyEhAV5eXm3zd7NZXXXNUFFRkTh16pQ4deqUACA++OADcerUKZGcnCyEEGL16tXCxcVFfPfdd+Ls2bNi0qRJws/PT9y8edPIlRumsessKioSL730kjh8+LBITEwUe/bsEYMGDRKBgYGirKzM2KU32bx584Szs7OIjo4W6enpuldpaalum2effVZ069ZN/P777+LEiRMiPDxchIeHG7Fqw93pOuPj48Xy5cvFiRMnRGJiovjuu++Ev7+/GDVqlJErN8xrr70m9u3bJxITE8XZs2fFa6+9JiRJEr/99psQwjzuZWPXaC73sSG3j5Yxh/tZn9rXaS739P/+7/9EdHS0SExMFAcPHhQRERHCzc1NZGVlCSFa/14ysNTYu3evAFDnNXPmTCFE9dDmN954Q6hUKqFUKsW4ceNEbGyscYtuhsaus7S0VNxzzz3C3d1dKBQK0b17dzF37lyRkZFh7LINUt/1ARCbNm3SbXPz5k3x3HPPiU6dOgk7OzsxZcoUkZ6ebryim+FO15mSkiJGjRolXF1dhVKpFAEBAeLll18WBQUFxi3cQH/+859F9+7dhbW1tXB3dxfjxo3ThRUhzONeNnaN5nIfG3J7YDGH+1mf2tdpLvd06tSpwsvLS1hbW4suXbqIqVOnivj4eN3nrX0vJSGEaF7bDBEREVH7YB8WIiIi6vAYWIiIiKjDY2AhIiKiDo+BhYiIiDo8BhYiIiLq8BhYiIiIqMNjYCEiIqIOj4GFiIiIOjwGFiILIkkSdu7cCQBISkqCJEm6NUyio6MhSVKdxcqIiDoCBhYiM5GdnY158+ahW7duUCqV8PT0RGRkJA4ePKjbJj09XW9J+I5qzJgxWLhwod57rRmoEhMT8dhjj8Hb2xs2Njbo2rUrJk2ahMuXL7f42ETUNqyMXQARtY6HHnoIFRUV2Lx5M/z9/ZGZmYmoqCjk5ubqtmnusu7mpLKyEuPHj0dQUBC2b98OLy8vpKWl4ZdffmnT1qXKykooFIo2Oz6R2Wv58kdEZGx5eXkCgIiOjm50OwBix44dQgghEhMTBQBx6tQpIcSthTH37NkjQkNDha2trQgPDxeXL1/WO8Ynn3wi/P39hUKhED179hRbtmzRfXb7MWvXtnfvXt17586dExMmTBD29vbCw8NDPPHEEyI7O1sIIcTMmTPrLOioPS7qWZhUrVaLlStXCl9fX2FjYyNCQkLEt99+2+D3QLtSeVJSUqPfq9TUVDFt2jTdwm2hoaHiyJEjTfo+aL/Xn3zyiZg4caKws7MTS5cuFUIIsXPnTjFw4EChVCqFn5+fWLZsmaisrGy0FiLias1EZqGyslI4ODiIhQsXirKysga3a0pgCQsLE9HR0eLChQti5MiRYtiwYbr9t2/fLhQKhVi7dq2IjY0V77//vpDL5eL333+v95hC1A0seXl5wt3dXSxevFhcunRJnDx5UowfP16MHTtWCCFEfn6+CA8PF3PnzhXp6ekiPT1dVFVVif/9738CgIiNjRXp6ekiPz9fCCHEihUrRK9evcSuXbtEQkKC2LRpk1AqlQ2Gt7S0NCGTycR7770nqqqq6t2mqKhI+Pv7i5EjR4o//vhDXLlyRWzdulUcOnSoSd8H7ffaw8NDbNy4USQkJIjk5GSxf/9+4eTkJL744guRkJAgfvvtN+Hr6yuWLVvW4D0jomoMLERmYtu2baJTp07CxsZGDBs2TCxevFicOXNGb5umtrBo/fTTTwKAuHnzphBCiGHDhom5c+fqHfORRx4R9913X73HFKJuYHnrrbfEPffco3eM1NRUXRgRQojRo0eLBQsW6G2jrS8vL0/3XllZmbCzs9MFCa05c+aI6dOnN/i9+vjjj4WdnZ1wdHQUY8eOFcuXLxcJCQm6zz/99FPh6OgocnNz693/Tt8HIaq/1wsXLtTbZty4cWLlypV67/373/8WXl5eDdZKRNXY6ZbITDz00EO4fv06vv/+e0yYMAHR0dEYNGgQvvjiC4OOExISovu9l5cXACArKwsAcOnSJQwfPlxv++HDh+PSpUtNPv6ZM2ewd+9eODg46F69evUCACQkJBhUa3x8PEpLSzF+/Hi9423ZsqXRY82fPx8ZGRn48ssvER4ejm+//RZ9+vTB7t27AQCnT5/GwIED4erqWu/+Tf0+DB48uM61L1++XK/WuXPnIj09HaWlpQZdO5GlYadbIjNiY2OD8ePHY/z48XjjjTfw1FNPYenSpZg1a1aTj1G7Y6gkSQAAjUbTpH1lsur/AwkhdO9VVlbqbVNcXIyJEyfi7bffrrO/NiA1VXFxMQDgp59+QpcuXfQ+UyqVje7r6OiIiRMnYuLEiVixYgUiIyOxYsUKjB8/Hra2tgbV0RB7e/s69b755pt48MEH62xrY2PTKuckMldsYSEyY8HBwSgpKWm14/Xu3VtvmDQAHDx4EMHBwQAAd3d3ANXDp7W087xoDRo0CBcuXICvry8CAgL0Xtof8NbW1lCr1Xr7WVtbA4De+8HBwVAqlUhJSalzLB8fnyZflyRJ6NWrl+57FRISgtOnT+PGjRvN+j40ZNCgQYiNja1Ta0BAgC7sEVH92MJCZAZyc3PxyCOP4M9//jNCQkLg6OiIEydO4J133sGkSZNa7Twvv/wyHn30UQwcOBARERH44YcfsH37duzZswcAYGtri6FDh2L16tXw8/NDVlYWXn/9db1jzJ8/H+vXr8f06dPxyiuvwNXVFfHx8fj666/x+eefQy6Xw9fXF0ePHkVSUhIcHBzg6uqK7t27Q5Ik/Pjjj7jvvvtga2sLR0dHvPTSS/jLX/4CjUaDESNGoKCgAAcPHoSTkxNmzpxZ5xpOnz6NpUuX4sknn0RwcDCsra2xb98+bNy4Ea+++ioAYPr06Vi5ciUmT56MVatWwcvLC6dOnYK3tzfCw8Pv+H1oyJIlS/DAAw+gW7duePjhhyGTyXDmzBmcP38eK1asaKW7RGSmjN2JhoharqysTLz22mti0KBBwtnZWdjZ2YmgoCDx+uuvi9LSUt12aEKn29qdWrVDgBMTE3Xv3Wk478WLF0V4eLiwtbUVAwYMEL/99ludYc1xcXFiypQpwsXFRdja2opevXqJhQsXCo1GI4QQIjY2VgwdOlTY2trqnX/58uXC09NTSJKkG9as0WjEmjVrRFBQkFAoFMLd3V1ERkaKffv21fu9ys7OFi+++KLo27evcHBwEI6OjqJfv37ivffeE2q1WrddUlKSeOihh4STk5Ows7MTgwcPFkePHm3y96H297q2Xbt2iWHDhglbW1vh5OQk7rrrLvHZZ5/VWysR3SIJUethMxEREVEHxIemRERE1OExsBAREVGHx8BCREREHR4DCxEREXV4DCxERETU4TGwEBERUYfHwEJEREQdHgMLERERdXgMLERERNThMbAQERFRh8fAQkRERB3e/wMAN+1rQjbVDQAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from tqdm import tqdm\n",
    "from sklearn.cluster import KMeans\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.metrics import silhouette_score\n",
    "from sklearn.metrics import pairwise_distances\n",
    "\n",
    "distance_matrix = pairwise_distances(pca_data_np)\n",
    "np.fill_diagonal(distance_matrix, 0) # Remove computational errors of distances\n",
    "\n",
    "n_clusters = np.arange(10, 50)\n",
    "silhouette = []\n",
    "for n_clust in tqdm(n_clusters):\n",
    "    sil = 0\n",
    "    for jj in range(5):\n",
    "        kmeans = KMeans(n_clusters = n_clust, init = 'k-means++')\n",
    "        kmeans.fit(pca_data_np)\n",
    "        sil += silhouette_score(distance_matrix, kmeans.labels_, metric='precomputed')\n",
    "    silhouette.append(sil/5)\n",
    "\n",
    "plt.plot(n_clusters, silhouette, label = 'Numerical data')\n",
    "plt.xlabel('Number of clusters')\n",
    "plt.ylabel('Silhouette Score')\n",
    "plt.legend()\n",
    "plt.savefig('Images/Anime Recommendation/Kmeans.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "By the silhouette score we can see that a clustering of 2 classes has a silhouette score of aproximately 0.6 which suggests that the clusters are well separated."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Hierarchical Agglomerative Clustering"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 40/40 [1:45:45<00:00, 158.65s/it]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.cluster import AgglomerativeClustering\n",
    "\n",
    "n_clusters = np.arange(10, 50)\n",
    "silhouette = []\n",
    "\n",
    "for n_clust in tqdm(n_clusters):\n",
    "    sil = 0\n",
    "    for ii in range(5):\n",
    "        HAC = AgglomerativeClustering(n_clusters = n_clust, linkage = 'ward', metric = 'euclidean')\n",
    "        HAC.fit(pca_data_np)\n",
    "        sil += silhouette_score(distance_matrix, HAC.labels_, metric='precomputed')\n",
    "    silhouette.append(sil/5)\n",
    "\n",
    "plt.plot(n_clusters, silhouette, label = 'Numerical data')\n",
    "plt.xlabel('Number of clusters')\n",
    "plt.ylabel('Silhouette Score')\n",
    "plt.legend()\n",
    "plt.savefig('Images/Anime Recommendation/HAC.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## DBSCAN \n",
    "\n",
    "Here we need to decide for an optimal N and $\\epsilon$ we will use grid search for this. But before, we will compute the maximum distance of nearest neighbors to get an idea of an optimal $\\epsilon$ and $N$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.neighbors import NearestNeighbors\n",
    "\n",
    "# Compute the k-nearest neighbors\n",
    "neigh = NearestNeighbors(n_neighbors=100)\n",
    "nbrs = neigh.fit(data_model)\n",
    "distances, indices = nbrs.kneighbors(data_model)\n",
    "\n",
    "# Sort distances\n",
    "distances = np.sort(distances, axis=0)\n",
    "\n",
    "#Plot distances\n",
    "plt.plot(distances)\n",
    "plt.ylabel('N-neighbor distance')\n",
    "plt.xlabel('Datapoint')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Lets zoom before the elbow"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Plot distances\n",
    "plt.plot(distances[:14000])\n",
    "plt.ylabel('N-neighbor distance')\n",
    "plt.xlabel('Datapoint')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can see most of the data points has neighbors with distances are below 2500, lets use a grid search to find the best parameters. Since this is a recommendation system we would like to have at least lets say 10 clusters. Otherwise we will guess we have only 2 types of customers which could by highly rare."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "eps = 1000, min_samples = 2 - Silhouette Score: -0.13829173170559794, # of labels: 183\n",
      "eps = 1000, min_samples = 3 - Silhouette Score: -0.008707086981697323, # of labels: 66\n",
      "eps = 1000, min_samples = 4 - Silhouette Score: 0.0043767133929311095, # of labels: 31\n",
      "eps = 1000, min_samples = 5 - Silhouette Score: 0.30173617395353036, # of labels: 17\n",
      "eps = 1000, min_samples = 6 - Silhouette Score: 0.26645820211303306, # of labels: 12\n",
      "eps = 1000, min_samples = 7 - Silhouette Score: 0.26539072677818576, # of labels: 11\n",
      "eps = 1250, min_samples = 2 - Silhouette Score: -0.0056483127687180015, # of labels: 163\n",
      "eps = 1250, min_samples = 3 - Silhouette Score: 0.0658254199660711, # of labels: 67\n",
      "eps = 1250, min_samples = 4 - Silhouette Score: 0.06872768523059461, # of labels: 34\n",
      "eps = 1250, min_samples = 5 - Silhouette Score: 0.2798163602723221, # of labels: 19\n",
      "eps = 1250, min_samples = 6 - Silhouette Score: 0.1960961179258615, # of labels: 14\n",
      "eps = 1500, min_samples = 2 - Silhouette Score: 0.06972864423401705, # of labels: 130\n",
      "eps = 1500, min_samples = 3 - Silhouette Score: 0.08293192565598641, # of labels: 45\n",
      "eps = 1500, min_samples = 4 - Silhouette Score: 0.07100062426504304, # of labels: 30\n",
      "eps = 1500, min_samples = 5 - Silhouette Score: 0.3334115785215427, # of labels: 25\n",
      "eps = 1500, min_samples = 6 - Silhouette Score: 0.2772615580641458, # of labels: 13\n",
      "eps = 1750, min_samples = 2 - Silhouette Score: 0.026420852080425942, # of labels: 131\n",
      "eps = 1750, min_samples = 3 - Silhouette Score: 0.05104683764351946, # of labels: 45\n",
      "eps = 1750, min_samples = 4 - Silhouette Score: 0.047255849123851106, # of labels: 21\n",
      "eps = 1750, min_samples = 5 - Silhouette Score: 0.3278502657500818, # of labels: 14\n",
      "eps = 1750, min_samples = 6 - Silhouette Score: 0.3283973049306079, # of labels: 15\n",
      "eps = 1750, min_samples = 7 - Silhouette Score: 0.3880347929414589, # of labels: 11\n",
      "eps = 1750, min_samples = 8 - Silhouette Score: 0.391738528278741, # of labels: 11\n",
      "eps = 2000, min_samples = 2 - Silhouette Score: 0.030342181274479293, # of labels: 130\n",
      "eps = 2000, min_samples = 3 - Silhouette Score: 0.04720961741252384, # of labels: 49\n",
      "eps = 2000, min_samples = 4 - Silhouette Score: 0.28731769638471427, # of labels: 31\n",
      "eps = 2000, min_samples = 5 - Silhouette Score: 0.44496080342072103, # of labels: 14\n",
      "eps = 2250, min_samples = 2 - Silhouette Score: 0.05881006775372814, # of labels: 117\n",
      "eps = 2250, min_samples = 3 - Silhouette Score: 0.2597853059278906, # of labels: 52\n",
      "eps = 2250, min_samples = 4 - Silhouette Score: 0.27234937047960367, # of labels: 25\n",
      "eps = 2250, min_samples = 5 - Silhouette Score: 0.4177232303198498, # of labels: 24\n",
      "eps = 2250, min_samples = 6 - Silhouette Score: 0.4232271997815744, # of labels: 10\n",
      "eps = 2500, min_samples = 2 - Silhouette Score: 0.017876390637775776, # of labels: 112\n",
      "eps = 2500, min_samples = 3 - Silhouette Score: 0.24362831576812205, # of labels: 44\n",
      "eps = 2500, min_samples = 4 - Silhouette Score: 0.24404622905288348, # of labels: 22\n",
      "eps = 2500, min_samples = 5 - Silhouette Score: 0.4975537106712024, # of labels: 13\n",
      "eps = 2500, min_samples = 6 - Silhouette Score: 0.44368685918153317, # of labels: 15\n",
      "eps = 2500, min_samples = 7 - Silhouette Score: 0.4209625325929098, # of labels: 12\n",
      "eps = 2750, min_samples = 2 - Silhouette Score: 0.00685966346492861, # of labels: 115\n",
      "eps = 2750, min_samples = 3 - Silhouette Score: 0.23402519463156346, # of labels: 46\n",
      "eps = 2750, min_samples = 4 - Silhouette Score: 0.23839278112177892, # of labels: 23\n",
      "eps = 2750, min_samples = 5 - Silhouette Score: 0.2390537025402517, # of labels: 14\n",
      "eps = 3000, min_samples = 2 - Silhouette Score: 0.0008508900664355, # of labels: 113\n",
      "eps = 3000, min_samples = 3 - Silhouette Score: 0.33885510746465786, # of labels: 47\n",
      "eps = 3000, min_samples = 4 - Silhouette Score: 0.21894892463492246, # of labels: 21\n",
      "eps = 3000, min_samples = 5 - Silhouette Score: 0.21971684481572665, # of labels: 14\n",
      "eps = 3250, min_samples = 2 - Silhouette Score: -0.019006971508363724, # of labels: 109\n",
      "eps = 3250, min_samples = 3 - Silhouette Score: 0.32814131578456984, # of labels: 47\n",
      "eps = 3250, min_samples = 4 - Silhouette Score: 0.33667677358282727, # of labels: 24\n",
      "eps = 3250, min_samples = 5 - Silhouette Score: 0.2368492602490881, # of labels: 18\n",
      "eps = 3250, min_samples = 6 - Silhouette Score: 0.21641614459059583, # of labels: 11\n",
      "eps = 3500, min_samples = 2 - Silhouette Score: -0.008038948648771268, # of labels: 106\n",
      "eps = 3500, min_samples = 3 - Silhouette Score: 0.3187468689706278, # of labels: 44\n",
      "eps = 3500, min_samples = 4 - Silhouette Score: 0.32410543660359753, # of labels: 24\n",
      "eps = 3500, min_samples = 5 - Silhouette Score: 0.556197071455848, # of labels: 11\n",
      "eps = 3500, min_samples = 6 - Silhouette Score: 0.24490893707267686, # of labels: 11\n",
      "eps = 3750, min_samples = 2 - Silhouette Score: -0.012071969976328718, # of labels: 110\n",
      "eps = 3750, min_samples = 3 - Silhouette Score: 0.31671626384377227, # of labels: 49\n",
      "eps = 3750, min_samples = 4 - Silhouette Score: 0.31942401638747825, # of labels: 25\n",
      "eps = 3750, min_samples = 5 - Silhouette Score: 0.5215179455629251, # of labels: 14\n",
      "eps = 3750, min_samples = 6 - Silhouette Score: 0.5556354735490054, # of labels: 12\n",
      "eps = 3750, min_samples = 7 - Silhouette Score: 0.23821781234392245, # of labels: 10\n",
      "eps = 4000, min_samples = 2 - Silhouette Score: -0.015134285618688391, # of labels: 117\n",
      "eps = 4000, min_samples = 3 - Silhouette Score: 0.31584284338561475, # of labels: 48\n",
      "eps = 4000, min_samples = 4 - Silhouette Score: 0.31634958741291147, # of labels: 25\n",
      "eps = 4000, min_samples = 5 - Silhouette Score: 0.5621449982371622, # of labels: 13\n",
      "eps = 4250, min_samples = 2 - Silhouette Score: -0.0698188959792314, # of labels: 100\n",
      "eps = 4250, min_samples = 3 - Silhouette Score: 0.5499174949217273, # of labels: 43\n",
      "eps = 4250, min_samples = 4 - Silhouette Score: 0.5534829100409168, # of labels: 25\n",
      "eps = 4500, min_samples = 2 - Silhouette Score: -0.07985547251472314, # of labels: 95\n",
      "eps = 4500, min_samples = 3 - Silhouette Score: 0.5528262034871937, # of labels: 38\n",
      "eps = 4500, min_samples = 4 - Silhouette Score: 0.5576700798124843, # of labels: 22\n",
      "eps = 4500, min_samples = 5 - Silhouette Score: 0.5574591780513246, # of labels: 18\n",
      "eps = 4500, min_samples = 6 - Silhouette Score: 0.5591251830636402, # of labels: 10\n",
      "eps = 4750, min_samples = 2 - Silhouette Score: -0.09712325866971774, # of labels: 90\n",
      "eps = 4750, min_samples = 3 - Silhouette Score: 0.5455493041677408, # of labels: 37\n",
      "eps = 4750, min_samples = 4 - Silhouette Score: 0.5535301282001955, # of labels: 17\n",
      "eps = 4750, min_samples = 5 - Silhouette Score: 0.5536219145980207, # of labels: 13\n",
      "eps = 4750, min_samples = 6 - Silhouette Score: 0.5565056312665444, # of labels: 12\n",
      "eps = 4750, min_samples = 7 - Silhouette Score: 0.5871115075233497, # of labels: 10\n",
      "eps = 5000, min_samples = 2 - Silhouette Score: -0.10022349627334474, # of labels: 94\n",
      "eps = 5000, min_samples = 3 - Silhouette Score: 0.5052263292536033, # of labels: 39\n",
      "eps = 5000, min_samples = 4 - Silhouette Score: 0.6221921793170738, # of labels: 17\n",
      "eps = 5000, min_samples = 5 - Silhouette Score: 0.6037954033150023, # of labels: 14\n",
      "eps = 5000, min_samples = 6 - Silhouette Score: 0.6016068297002991, # of labels: 11\n",
      "eps = 5000, min_samples = 7 - Silhouette Score: 0.5900209593743546, # of labels: 10\n",
      "eps = 5250, min_samples = 2 - Silhouette Score: -0.10245458524496251, # of labels: 95\n",
      "eps = 5250, min_samples = 3 - Silhouette Score: 0.4891672459859479, # of labels: 36\n",
      "eps = 5250, min_samples = 4 - Silhouette Score: 0.6385340747761705, # of labels: 17\n",
      "eps = 5250, min_samples = 5 - Silhouette Score: 0.6211016439290546, # of labels: 14\n",
      "eps = 5500, min_samples = 2 - Silhouette Score: -0.12196424620682397, # of labels: 99\n",
      "eps = 5500, min_samples = 3 - Silhouette Score: 0.4849071587771403, # of labels: 32\n",
      "eps = 5500, min_samples = 4 - Silhouette Score: 0.6181682309597557, # of labels: 17\n",
      "eps = 5500, min_samples = 5 - Silhouette Score: 0.6386643559591652, # of labels: 10\n",
      "eps = 5750, min_samples = 2 - Silhouette Score: -0.1272048075517282, # of labels: 96\n",
      "eps = 5750, min_samples = 3 - Silhouette Score: 0.4845624395485608, # of labels: 34\n",
      "eps = 5750, min_samples = 4 - Silhouette Score: 0.5882197128596384, # of labels: 16\n",
      "eps = 5750, min_samples = 5 - Silhouette Score: 0.630902062225463, # of labels: 11\n",
      "eps = 6000, min_samples = 2 - Silhouette Score: -0.14551469604830244, # of labels: 98\n",
      "eps = 6000, min_samples = 3 - Silhouette Score: 0.49202329965016955, # of labels: 29\n",
      "eps = 6000, min_samples = 4 - Silhouette Score: 0.5861077420448, # of labels: 19\n",
      "eps = 6000, min_samples = 5 - Silhouette Score: 0.6249819193305892, # of labels: 11\n",
      "eps = 6250, min_samples = 2 - Silhouette Score: -0.16663836142378574, # of labels: 94\n",
      "eps = 6250, min_samples = 3 - Silhouette Score: 0.05178938331996198, # of labels: 29\n",
      "eps = 6250, min_samples = 4 - Silhouette Score: 0.6699436039263277, # of labels: 18\n",
      "eps = 6250, min_samples = 5 - Silhouette Score: 0.6277883274421774, # of labels: 11\n",
      "eps = 6500, min_samples = 2 - Silhouette Score: -0.1744631883015595, # of labels: 93\n",
      "eps = 6500, min_samples = 3 - Silhouette Score: 0.04422347634188128, # of labels: 29\n",
      "eps = 6500, min_samples = 4 - Silhouette Score: 0.4847352688954933, # of labels: 16\n",
      "eps = 6500, min_samples = 5 - Silhouette Score: 0.6279202763084953, # of labels: 12\n",
      "eps = 6750, min_samples = 2 - Silhouette Score: -0.18189008279286326, # of labels: 90\n",
      "eps = 6750, min_samples = 3 - Silhouette Score: 0.036109965008226566, # of labels: 28\n",
      "eps = 6750, min_samples = 4 - Silhouette Score: 0.4806009863335474, # of labels: 16\n",
      "eps = 6750, min_samples = 5 - Silhouette Score: 0.6731304057823023, # of labels: 12\n",
      "eps = 7000, min_samples = 2 - Silhouette Score: -0.19547020943601517, # of labels: 95\n",
      "eps = 7000, min_samples = 3 - Silhouette Score: 0.010654651307239471, # of labels: 32\n",
      "eps = 7000, min_samples = 4 - Silhouette Score: 0.4764669551664228, # of labels: 17\n",
      "eps = 7000, min_samples = 5 - Silhouette Score: 0.4841769589185399, # of labels: 13\n",
      "eps = 7250, min_samples = 2 - Silhouette Score: -0.2093789338566423, # of labels: 91\n",
      "eps = 7250, min_samples = 3 - Silhouette Score: -0.008362860397007333, # of labels: 31\n",
      "eps = 7250, min_samples = 4 - Silhouette Score: 0.46354858662922943, # of labels: 16\n",
      "eps = 7250, min_samples = 5 - Silhouette Score: 0.4790084626924412, # of labels: 12\n",
      "eps = 7500, min_samples = 2 - Silhouette Score: -0.19870841131377381, # of labels: 86\n",
      "eps = 7500, min_samples = 3 - Silhouette Score: 0.43241556941858833, # of labels: 32\n",
      "eps = 7500, min_samples = 4 - Silhouette Score: 0.4587635989111887, # of labels: 17\n",
      "eps = 7500, min_samples = 5 - Silhouette Score: 0.47526846264218514, # of labels: 10\n",
      "eps = 7500, min_samples = 6 - Silhouette Score: 0.6899423111362524, # of labels: 10\n",
      "eps = 7750, min_samples = 2 - Silhouette Score: -0.21027854822054748, # of labels: 92\n",
      "eps = 7750, min_samples = 3 - Silhouette Score: 0.42082077547555685, # of labels: 32\n",
      "eps = 7750, min_samples = 4 - Silhouette Score: 0.44916241940364043, # of labels: 16\n",
      "eps = 7750, min_samples = 5 - Silhouette Score: 0.47417447929715484, # of labels: 10\n",
      "eps = 8000, min_samples = 2 - Silhouette Score: -0.21124122631724715, # of labels: 97\n",
      "eps = 8000, min_samples = 3 - Silhouette Score: 0.41933455936671693, # of labels: 38\n",
      "eps = 8000, min_samples = 4 - Silhouette Score: 0.4487244460097696, # of labels: 17\n",
      "eps = 8000, min_samples = 5 - Silhouette Score: 0.4608450659344587, # of labels: 11\n",
      "eps = 8250, min_samples = 2 - Silhouette Score: -0.20601753823167707, # of labels: 96\n",
      "eps = 8250, min_samples = 3 - Silhouette Score: 0.6236252450929043, # of labels: 37\n",
      "eps = 8250, min_samples = 4 - Silhouette Score: 0.460960715948873, # of labels: 17\n",
      "eps = 8250, min_samples = 5 - Silhouette Score: 0.4619786720210849, # of labels: 13\n",
      "eps = 8500, min_samples = 2 - Silhouette Score: 0.5644572782511378, # of labels: 96\n",
      "eps = 8500, min_samples = 3 - Silhouette Score: 0.6225399664604583, # of labels: 39\n",
      "eps = 8500, min_samples = 4 - Silhouette Score: 0.4574346209510163, # of labels: 15\n",
      "eps = 8500, min_samples = 5 - Silhouette Score: 0.45637369593675586, # of labels: 12\n",
      "eps = 8750, min_samples = 2 - Silhouette Score: 0.5643667165921529, # of labels: 92\n",
      "eps = 8750, min_samples = 3 - Silhouette Score: 0.6538072999109004, # of labels: 39\n",
      "eps = 8750, min_samples = 4 - Silhouette Score: 0.4566409161117697, # of labels: 20\n",
      "eps = 8750, min_samples = 5 - Silhouette Score: 0.4468928034325198, # of labels: 15\n",
      "eps = 9000, min_samples = 2 - Silhouette Score: 0.5556671578336005, # of labels: 89\n",
      "eps = 9000, min_samples = 3 - Silhouette Score: 0.6781597847518437, # of labels: 31\n",
      "eps = 9000, min_samples = 4 - Silhouette Score: 0.4563083987024144, # of labels: 17\n",
      "eps = 9000, min_samples = 5 - Silhouette Score: 0.45291521143755625, # of labels: 13\n",
      "eps = 9000, min_samples = 6 - Silhouette Score: 0.4534138509001947, # of labels: 11\n",
      "eps = 9250, min_samples = 2 - Silhouette Score: 0.5451385602276752, # of labels: 83\n",
      "eps = 9250, min_samples = 3 - Silhouette Score: 0.6712004291418108, # of labels: 27\n",
      "eps = 9250, min_samples = 4 - Silhouette Score: 0.44352111551990214, # of labels: 13\n",
      "eps = 9250, min_samples = 5 - Silhouette Score: 0.4446468174750435, # of labels: 10\n",
      "eps = 9250, min_samples = 6 - Silhouette Score: 0.4588764762060376, # of labels: 11\n",
      "eps = 9500, min_samples = 2 - Silhouette Score: 0.5449142396976786, # of labels: 77\n",
      "eps = 9500, min_samples = 3 - Silhouette Score: 0.6746486674521223, # of labels: 25\n",
      "eps = 9500, min_samples = 4 - Silhouette Score: 0.44795167514688, # of labels: 16\n",
      "eps = 9500, min_samples = 5 - Silhouette Score: 0.4298780619292158, # of labels: 10\n",
      "eps = 9750, min_samples = 2 - Silhouette Score: 0.5427278165812083, # of labels: 75\n",
      "eps = 9750, min_samples = 3 - Silhouette Score: 0.6730186344915867, # of labels: 23\n",
      "eps = 9750, min_samples = 4 - Silhouette Score: 0.44600704372279676, # of labels: 14\n",
      "eps = 10000, min_samples = 2 - Silhouette Score: 0.5419764067919883, # of labels: 78\n",
      "eps = 10000, min_samples = 3 - Silhouette Score: 0.6587342258157096, # of labels: 26\n",
      "eps = 10000, min_samples = 4 - Silhouette Score: 0.4466947063293794, # of labels: 15\n",
      "eps = 10000, min_samples = 5 - Silhouette Score: 0.4434702040461726, # of labels: 10\n",
      "eps = 10250, min_samples = 2 - Silhouette Score: 0.5408995413902963, # of labels: 77\n",
      "eps = 10250, min_samples = 3 - Silhouette Score: 0.6464305602092174, # of labels: 29\n",
      "eps = 10250, min_samples = 4 - Silhouette Score: 0.6681862511168946, # of labels: 15\n",
      "eps = 10250, min_samples = 5 - Silhouette Score: 0.44305825239624674, # of labels: 11\n",
      "eps = 10250, min_samples = 6 - Silhouette Score: 0.4528993309164628, # of labels: 11\n",
      "eps = 10500, min_samples = 2 - Silhouette Score: 0.5374645827784092, # of labels: 76\n",
      "eps = 10500, min_samples = 3 - Silhouette Score: 0.6637807305989801, # of labels: 26\n",
      "eps = 10500, min_samples = 4 - Silhouette Score: 0.6721282681446895, # of labels: 12\n",
      "eps = 10500, min_samples = 5 - Silhouette Score: 0.4372481117619613, # of labels: 13\n",
      "eps = 10500, min_samples = 6 - Silhouette Score: 0.45075295738096577, # of labels: 10\n",
      "eps = 10750, min_samples = 2 - Silhouette Score: 0.5358212026058199, # of labels: 73\n",
      "eps = 10750, min_samples = 3 - Silhouette Score: 0.6705586333097944, # of labels: 24\n",
      "eps = 10750, min_samples = 4 - Silhouette Score: 0.6718216865898415, # of labels: 12\n",
      "eps = 10750, min_samples = 5 - Silhouette Score: 0.6731958524983671, # of labels: 10\n",
      "eps = 11000, min_samples = 2 - Silhouette Score: 0.536561215535784, # of labels: 72\n",
      "eps = 11000, min_samples = 3 - Silhouette Score: 0.6678094792088629, # of labels: 24\n",
      "eps = 11000, min_samples = 4 - Silhouette Score: 0.6701266166238183, # of labels: 12\n",
      "eps = 11250, min_samples = 2 - Silhouette Score: 0.5365502154601167, # of labels: 74\n",
      "eps = 11250, min_samples = 3 - Silhouette Score: 0.6710364129908871, # of labels: 25\n",
      "eps = 11250, min_samples = 4 - Silhouette Score: 0.6696843299906499, # of labels: 12\n",
      "eps = 11500, min_samples = 2 - Silhouette Score: 0.5370120478983874, # of labels: 75\n",
      "eps = 11500, min_samples = 3 - Silhouette Score: 0.6716089791911554, # of labels: 26\n",
      "eps = 11500, min_samples = 4 - Silhouette Score: 0.670000410662901, # of labels: 14\n",
      "eps = 11750, min_samples = 2 - Silhouette Score: 0.5377397547328129, # of labels: 75\n",
      "eps = 11750, min_samples = 3 - Silhouette Score: 0.6714036346280647, # of labels: 26\n",
      "eps = 11750, min_samples = 4 - Silhouette Score: 0.6701526415790818, # of labels: 15\n",
      "eps = 11750, min_samples = 5 - Silhouette Score: 0.6777852154656617, # of labels: 10\n",
      "eps = 12000, min_samples = 2 - Silhouette Score: 0.5342200051177135, # of labels: 73\n",
      "eps = 12000, min_samples = 3 - Silhouette Score: 0.6699955363176927, # of labels: 22\n",
      "eps = 12000, min_samples = 4 - Silhouette Score: 0.6713384950754712, # of labels: 19\n",
      "eps = 12000, min_samples = 5 - Silhouette Score: 0.6745019899486043, # of labels: 11\n",
      "eps = 12250, min_samples = 2 - Silhouette Score: 0.5256445661943722, # of labels: 73\n",
      "eps = 12250, min_samples = 3 - Silhouette Score: 0.6636433095389198, # of labels: 22\n",
      "eps = 12250, min_samples = 4 - Silhouette Score: 0.6760610304980653, # of labels: 17\n",
      "eps = 12250, min_samples = 5 - Silhouette Score: 0.674494860410775, # of labels: 11\n",
      "eps = 12500, min_samples = 2 - Silhouette Score: 0.5215510449225974, # of labels: 73\n",
      "eps = 12500, min_samples = 3 - Silhouette Score: 0.6607975108452736, # of labels: 21\n",
      "eps = 12500, min_samples = 4 - Silhouette Score: 0.6720751063685825, # of labels: 14\n",
      "eps = 12750, min_samples = 2 - Silhouette Score: 0.5200808838588278, # of labels: 73\n",
      "eps = 12750, min_samples = 3 - Silhouette Score: 0.6549360352757183, # of labels: 22\n",
      "eps = 12750, min_samples = 4 - Silhouette Score: 0.6707591595538658, # of labels: 13\n",
      "eps = 12750, min_samples = 5 - Silhouette Score: 0.6716522041985825, # of labels: 10\n",
      "eps = 13000, min_samples = 2 - Silhouette Score: 0.5179014320642453, # of labels: 72\n",
      "eps = 13000, min_samples = 3 - Silhouette Score: 0.6583522122775995, # of labels: 20\n",
      "eps = 13000, min_samples = 4 - Silhouette Score: 0.6640831602541517, # of labels: 12\n",
      "eps = 13000, min_samples = 5 - Silhouette Score: 0.6713592753064332, # of labels: 10\n",
      "eps = 13250, min_samples = 2 - Silhouette Score: 0.5173473180047893, # of labels: 72\n",
      "eps = 13250, min_samples = 3 - Silhouette Score: 0.6580684880833326, # of labels: 22\n",
      "eps = 13250, min_samples = 4 - Silhouette Score: 0.6634833422241625, # of labels: 12\n",
      "eps = 13250, min_samples = 5 - Silhouette Score: 0.6686269957000708, # of labels: 10\n",
      "eps = 13500, min_samples = 2 - Silhouette Score: 0.5181800442134876, # of labels: 73\n",
      "eps = 13500, min_samples = 3 - Silhouette Score: 0.6581052664482262, # of labels: 24\n",
      "eps = 13500, min_samples = 4 - Silhouette Score: 0.6633062010196519, # of labels: 13\n",
      "eps = 13500, min_samples = 5 - Silhouette Score: 0.668519764973352, # of labels: 11\n",
      "eps = 13750, min_samples = 2 - Silhouette Score: 0.5290716972097582, # of labels: 70\n",
      "eps = 13750, min_samples = 3 - Silhouette Score: 0.6588085032206996, # of labels: 25\n",
      "eps = 13750, min_samples = 4 - Silhouette Score: 0.6618353695527533, # of labels: 13\n",
      "eps = 13750, min_samples = 5 - Silhouette Score: 0.6642342081421092, # of labels: 10\n",
      "eps = 14000, min_samples = 2 - Silhouette Score: 0.5282118298500849, # of labels: 68\n",
      "eps = 14000, min_samples = 3 - Silhouette Score: 0.661252378682183, # of labels: 24\n",
      "eps = 14000, min_samples = 4 - Silhouette Score: 0.6644904219049507, # of labels: 12\n",
      "eps = 14250, min_samples = 2 - Silhouette Score: 0.5274550432029443, # of labels: 65\n",
      "eps = 14250, min_samples = 3 - Silhouette Score: 0.6630311153030009, # of labels: 24\n",
      "eps = 14250, min_samples = 4 - Silhouette Score: 0.6629445646987033, # of labels: 14\n",
      "eps = 14500, min_samples = 2 - Silhouette Score: 0.5256622795177436, # of labels: 63\n",
      "eps = 14500, min_samples = 3 - Silhouette Score: 0.6620350181982583, # of labels: 23\n",
      "eps = 14500, min_samples = 4 - Silhouette Score: 0.6631493802934697, # of labels: 14\n",
      "eps = 14750, min_samples = 2 - Silhouette Score: 0.521489100593987, # of labels: 65\n",
      "eps = 14750, min_samples = 3 - Silhouette Score: 0.6589047763167655, # of labels: 22\n",
      "eps = 14750, min_samples = 4 - Silhouette Score: 0.6631691797530469, # of labels: 13\n",
      "eps = 14750, min_samples = 5 - Silhouette Score: 0.6630577893764894, # of labels: 10\n",
      "eps = 15000, min_samples = 2 - Silhouette Score: 0.6490484517599688, # of labels: 64\n",
      "eps = 15000, min_samples = 3 - Silhouette Score: 0.6579437340085377, # of labels: 22\n",
      "eps = 15000, min_samples = 4 - Silhouette Score: 0.6630719177749614, # of labels: 11\n",
      "eps = 15000, min_samples = 5 - Silhouette Score: 0.6622414998939838, # of labels: 11\n",
      "eps = 15250, min_samples = 2 - Silhouette Score: 0.6488049017215863, # of labels: 63\n",
      "eps = 15250, min_samples = 3 - Silhouette Score: 0.6579811397473952, # of labels: 23\n",
      "eps = 15250, min_samples = 4 - Silhouette Score: 0.6634209898246891, # of labels: 10\n",
      "eps = 15250, min_samples = 5 - Silhouette Score: 0.662746171478956, # of labels: 10\n",
      "eps = 15500, min_samples = 2 - Silhouette Score: 0.6473750530745863, # of labels: 60\n",
      "eps = 15500, min_samples = 3 - Silhouette Score: 0.6566406708125527, # of labels: 23\n",
      "eps = 15750, min_samples = 2 - Silhouette Score: 0.6471657891125213, # of labels: 61\n",
      "eps = 15750, min_samples = 3 - Silhouette Score: 0.656241071549985, # of labels: 22\n",
      "eps = 16000, min_samples = 2 - Silhouette Score: 0.6367922073645079, # of labels: 56\n",
      "eps = 16000, min_samples = 3 - Silhouette Score: 0.6496225414316986, # of labels: 19\n",
      "eps = 16000, min_samples = 4 - Silhouette Score: 0.6505913601828671, # of labels: 11\n",
      "eps = 16250, min_samples = 2 - Silhouette Score: 0.6362594307632519, # of labels: 53\n",
      "eps = 16250, min_samples = 3 - Silhouette Score: 0.6496423059472025, # of labels: 21\n",
      "eps = 16250, min_samples = 4 - Silhouette Score: 0.6501494275042222, # of labels: 11\n",
      "eps = 16500, min_samples = 2 - Silhouette Score: 0.6808060146170659, # of labels: 48\n",
      "eps = 16500, min_samples = 3 - Silhouette Score: 0.7056214450637882, # of labels: 19\n",
      "eps = 16500, min_samples = 4 - Silhouette Score: 0.7068370627101767, # of labels: 11\n",
      "eps = 16750, min_samples = 2 - Silhouette Score: 0.6809172078495156, # of labels: 52\n",
      "eps = 16750, min_samples = 3 - Silhouette Score: 0.7056214450637882, # of labels: 19\n",
      "eps = 16750, min_samples = 4 - Silhouette Score: 0.70587290302572, # of labels: 10\n",
      "Best Params: {'eps': 16500, 'min_samples': 4} with Silhouette Score: 0.7068370627101767\n"
     ]
    }
   ],
   "source": [
    "from sklearn.cluster import DBSCAN\n",
    "\n",
    "epsilons = np.arange(1000, 17000, 250)\n",
    "min_samples = np.arange(2, 10)\n",
    "\n",
    "best_score = -1\n",
    "best_params = {'eps': None, 'min_samples': None}\n",
    "\n",
    "sil_scores = np.ones((len(epsilons), len(min_samples)))*-1\n",
    "num_of_labels = np.zeros((len(epsilons), len(min_samples)))\n",
    "ii = 0\n",
    "for eps in epsilons:\n",
    "    num_labels = 20\n",
    "    jj = 0\n",
    "    for min_sample in min_samples:\n",
    "        #Increasing the number of min_sample reduces the number of labels,\n",
    "        #if we want at least 10 labels we can stop increasing min_sample \n",
    "        #if we obtain less than 10 labels.\n",
    "        if num_labels >= 10:\n",
    "            dbscan = DBSCAN(eps=eps, min_samples=min_sample, metric = 'euclidean')\n",
    "            labels = dbscan.fit_predict(pca_data_np)\n",
    "            num_labels = len(set(labels))\n",
    "            \n",
    "        if num_labels >=10:\n",
    "            num_of_labels[ii, jj] = num_labels\n",
    "            #Calculate Silhouette_score\n",
    "            score = silhouette_score(distance_matrix, labels, metric = 'precomputed')\n",
    "            sil_scores[ii, jj] = score\n",
    "            print(f\"eps = {eps}, min_samples = {min_sample} - Silhouette Score: {score}, # of labels: {len(set(labels))}\")\n",
    "\n",
    "            if score > best_score:\n",
    "                best_score = score\n",
    "                best_params['eps'] = eps\n",
    "                best_params['min_samples'] = min_sample\n",
    "        jj +=1 \n",
    "    ii+=1\n",
    "\n",
    "print(f\"Best Params: {best_params} with Silhouette Score: {best_score}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "X, Y = np.meshgrid(min_samples, epsilons)\n",
    "plt.figure(figsize=(8, 6))\n",
    "plt.pcolormesh(X, Y, sil_scores, shading='auto')\n",
    "plt.colorbar(label='Silhouette score')\n",
    "plt.xlabel('min_samples')\n",
    "plt.ylabel('epsilon size')\n",
    "plt.title('DBSCAN search')\n",
    "plt.savefig('Images/Anime Recommendation/DBSCAN.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Get positions of sil_scores greater than 0.7\n",
    "indices = np.argwhere(sil_scores > 0.7)\n",
    "\n",
    "# Get number of labels\n",
    "num_clusters = [num_of_labels[(ii[0], ii[1])] for ii in indices]\n",
    "sil_scores_dbscan = [sil_scores[(ii[0], ii[1])] for ii in indices]\n",
    "\n",
    "plt.scatter(num_clusters, sil_scores_dbscan)\n",
    "plt.xlabel('# of cluster')\n",
    "plt.ylabel('Silhouette score')\n",
    "plt.title('DBSCAN')\n",
    "plt.savefig('Images/Anime Recommendation/DBSCAN_above_07.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "DataScience",
   "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": "3.12.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}