Exploration_Clustering_T.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Clustering and Exploration\n",
    "\n",
    "This notebook follows the same structure as 'Exploration_Clustering_M.ipynb' and was not created for me, but my girlfriend. It is therefore not commented/described much. \n",
    "\n",
    "If you want comments or a notebook that is easier to follow check out the one mentioned above."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import spotipy\n",
    "from spotipy.oauth2 import SpotifyClientCredentials\n",
    "import spotipy.util as util\n",
    "from pathlib import Path\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from spotifuncs import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "path = Path(\"C:/Users/ms101/OneDrive/DataScience_ML/projects/spotify_app\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open(path / \"client_s.txt\") as f:\n",
    "    content = f.readlines()\n",
    "content = [x.strip() for x in content]\n",
    "\n",
    "client_id = content[0]\n",
    "client_secret = content[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open(path / \"usernames.txt\") as f:\n",
    "    usernames = f.readlines()\n",
    "usernames = [x.strip() for x in usernames]\n",
    "\n",
    "username = usernames[1]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "scope = \"user-library-read user-read-recently-played user-top-read playlist-modify-public playlist-read-private playlist-read-collaborative\"\n",
    "\n",
    "redirect_uri = \"https://developer.spotify.com/dashboard/applications/4a4e029d299a4241873db8300038bf0a\"\n",
    "\n",
    "client_credentials_manager = SpotifyClientCredentials(client_id=client_id, \n",
    "                                                      client_secret=client_secret)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "sp = authenticate(redirect_uri, client_credentials_manager, username, scope, client_id, client_secret)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\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>id</th>\n",
       "      <th>genres</th>\n",
       "      <th>popularity</th>\n",
       "      <th>uri</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Emancipator</td>\n",
       "      <td>6HCnsY0Rxi3cg53xreoAIm</td>\n",
       "      <td>downtempo,electronica,livetronica,trip hop</td>\n",
       "      <td>62</td>\n",
       "      <td>spotify:artist:6HCnsY0Rxi3cg53xreoAIm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Element Of Crime</td>\n",
       "      <td>3FweAJRBCbUOGR6jULfaRi</td>\n",
       "      <td>german indie,german pop,german rock,liedermacher</td>\n",
       "      <td>50</td>\n",
       "      <td>spotify:artist:3FweAJRBCbUOGR6jULfaRi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Mac Miller</td>\n",
       "      <td>4LLpKhyESsyAXpc4laK94U</td>\n",
       "      <td>hip hop,pittsburgh rap,rap</td>\n",
       "      <td>85</td>\n",
       "      <td>spotify:artist:4LLpKhyESsyAXpc4laK94U</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Dmitri Kitayenko</td>\n",
       "      <td>3Nfbf48vyOcRJmK5dXoPHg</td>\n",
       "      <td></td>\n",
       "      <td>35</td>\n",
       "      <td>spotify:artist:3Nfbf48vyOcRJmK5dXoPHg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Arctic Monkeys</td>\n",
       "      <td>7Ln80lUS6He07XvHI8qqHH</td>\n",
       "      <td>garage rock,modern rock,permanent wave,rock,sh...</td>\n",
       "      <td>86</td>\n",
       "      <td>spotify:artist:7Ln80lUS6He07XvHI8qqHH</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>257ers</td>\n",
       "      <td>6ihLfpY3cmdGyWEnItn30w</td>\n",
       "      <td>antideutsche,deep german hip hop,german hip ho...</td>\n",
       "      <td>62</td>\n",
       "      <td>spotify:artist:6ihLfpY3cmdGyWEnItn30w</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>86</th>\n",
       "      <td>Eminem</td>\n",
       "      <td>7dGJo4pcD2V6oG8kP0tJRR</td>\n",
       "      <td>detroit hip hop,hip hop,rap</td>\n",
       "      <td>93</td>\n",
       "      <td>spotify:artist:7dGJo4pcD2V6oG8kP0tJRR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87</th>\n",
       "      <td>MEUTE</td>\n",
       "      <td>1z5xbcOeFRQXBVDpvRPh8H</td>\n",
       "      <td>german dance,hamburg electronic,livetronica</td>\n",
       "      <td>53</td>\n",
       "      <td>spotify:artist:1z5xbcOeFRQXBVDpvRPh8H</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>Max Herre</td>\n",
       "      <td>7IpWQKu80qQvyer3LO6SW3</td>\n",
       "      <td>german alternative rap,german hip hop,german pop</td>\n",
       "      <td>53</td>\n",
       "      <td>spotify:artist:7IpWQKu80qQvyer3LO6SW3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>Hozier</td>\n",
       "      <td>2FXC3k01G6Gw61bmprjgqS</td>\n",
       "      <td>irish singer-songwriter,modern rock,pop</td>\n",
       "      <td>80</td>\n",
       "      <td>spotify:artist:2FXC3k01G6Gw61bmprjgqS</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>90 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                name                      id  \\\n",
       "0        Emancipator  6HCnsY0Rxi3cg53xreoAIm   \n",
       "1   Element Of Crime  3FweAJRBCbUOGR6jULfaRi   \n",
       "2         Mac Miller  4LLpKhyESsyAXpc4laK94U   \n",
       "3   Dmitri Kitayenko  3Nfbf48vyOcRJmK5dXoPHg   \n",
       "4     Arctic Monkeys  7Ln80lUS6He07XvHI8qqHH   \n",
       "..               ...                     ...   \n",
       "85            257ers  6ihLfpY3cmdGyWEnItn30w   \n",
       "86            Eminem  7dGJo4pcD2V6oG8kP0tJRR   \n",
       "87             MEUTE  1z5xbcOeFRQXBVDpvRPh8H   \n",
       "88         Max Herre  7IpWQKu80qQvyer3LO6SW3   \n",
       "89            Hozier  2FXC3k01G6Gw61bmprjgqS   \n",
       "\n",
       "                                               genres  popularity  \\\n",
       "0          downtempo,electronica,livetronica,trip hop          62   \n",
       "1    german indie,german pop,german rock,liedermacher          50   \n",
       "2                          hip hop,pittsburgh rap,rap          85   \n",
       "3                                                              35   \n",
       "4   garage rock,modern rock,permanent wave,rock,sh...          86   \n",
       "..                                                ...         ...   \n",
       "85  antideutsche,deep german hip hop,german hip ho...          62   \n",
       "86                        detroit hip hop,hip hop,rap          93   \n",
       "87        german dance,hamburg electronic,livetronica          53   \n",
       "88   german alternative rap,german hip hop,german pop          53   \n",
       "89            irish singer-songwriter,modern rock,pop          80   \n",
       "\n",
       "                                      uri  \n",
       "0   spotify:artist:6HCnsY0Rxi3cg53xreoAIm  \n",
       "1   spotify:artist:3FweAJRBCbUOGR6jULfaRi  \n",
       "2   spotify:artist:4LLpKhyESsyAXpc4laK94U  \n",
       "3   spotify:artist:3Nfbf48vyOcRJmK5dXoPHg  \n",
       "4   spotify:artist:7Ln80lUS6He07XvHI8qqHH  \n",
       "..                                    ...  \n",
       "85  spotify:artist:6ihLfpY3cmdGyWEnItn30w  \n",
       "86  spotify:artist:7dGJo4pcD2V6oG8kP0tJRR  \n",
       "87  spotify:artist:1z5xbcOeFRQXBVDpvRPh8H  \n",
       "88  spotify:artist:7IpWQKu80qQvyer3LO6SW3  \n",
       "89  spotify:artist:2FXC3k01G6Gw61bmprjgqS  \n",
       "\n",
       "[90 rows x 5 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top_tracks_short = sp.current_user_top_tracks(limit = 50,offset=0,time_range='short_term')\n",
    "top_tracks_med = sp.current_user_top_tracks(limit = 50,offset=0,time_range='medium_term')\n",
    "top_tracks_long = sp.current_user_top_tracks(limit = 50,offset=0,time_range='long_term')\n",
    "\n",
    "#combine the top_tracks\n",
    "top_tracks_short_df = append_audio_features(create_df_top_songs(top_tracks_short),sp)\n",
    "top_tracks_med_df = append_audio_features(create_df_top_songs(top_tracks_med),sp)\n",
    "top_tracks_long_df = append_audio_features(create_df_top_songs(top_tracks_long),sp)\n",
    "\n",
    "top_tracks_short_df[\"Timeframe\"] = \"short term\"\n",
    "top_tracks_med_df[\"Timeframe\"] = \"medium term\"\n",
    "top_tracks_long_df[\"Timeframe\"] = \"long term\"\n",
    "\n",
    "top_tracks = pd.concat([top_tracks_short_df, top_tracks_med_df, top_tracks_long_df])\n",
    "top_tracks = top_tracks.reset_index(drop = True)\n",
    "\n",
    "top_artists_long = sp.current_user_top_artists(limit = 50, time_range = \"long_term\")\n",
    "top_artists_med = sp.current_user_top_artists(limit = 50, time_range = \"medium_term\")\n",
    "top_artists_short = sp.current_user_top_artists(limit = 50, time_range = \"short_term\")\n",
    "\n",
    "\n",
    "artists_short_df = top_artists_from_API(top_artists_short)\n",
    "artists_med_df = top_artists_from_API(top_artists_med)\n",
    "artists_long_df = top_artists_from_API(top_artists_long)\n",
    "\n",
    "\n",
    "artists_df = pd.concat([artists_short_df,artists_med_df,artists_long_df])\n",
    "artists_df[\"genres\"] = artists_df[\"genres\"].apply(lambda x: \",\".join(x))\n",
    "artists_df.drop_duplicates().reset_index(drop = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>track_name</th>\n",
       "      <th>album</th>\n",
       "      <th>track_id</th>\n",
       "      <th>artist</th>\n",
       "      <th>duration</th>\n",
       "      <th>popularity</th>\n",
       "      <th>danceability</th>\n",
       "      <th>energy</th>\n",
       "      <th>key</th>\n",
       "      <th>loudness</th>\n",
       "      <th>mode</th>\n",
       "      <th>speechiness</th>\n",
       "      <th>acousticness</th>\n",
       "      <th>instrumentalness</th>\n",
       "      <th>liveness</th>\n",
       "      <th>valence</th>\n",
       "      <th>tempo</th>\n",
       "      <th>Timeframe</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Time for Space</td>\n",
       "      <td>Baralku</td>\n",
       "      <td>3dJXvBddoH1AGLpKvmbYDA</td>\n",
       "      <td>Emancipator</td>\n",
       "      <td>433613</td>\n",
       "      <td>56</td>\n",
       "      <td>0.610</td>\n",
       "      <td>0.313</td>\n",
       "      <td>5</td>\n",
       "      <td>-13.138</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0323</td>\n",
       "      <td>0.3900</td>\n",
       "      <td>0.840000</td>\n",
       "      <td>0.0899</td>\n",
       "      <td>0.0870</td>\n",
       "      <td>80.009</td>\n",
       "      <td>short term</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Márquez: Danzón No.2</td>\n",
       "      <td>Música Clásica Esencial: México</td>\n",
       "      <td>4IM73PUWb5Y07VcFOsUlhE</td>\n",
       "      <td>Arturo Márquez</td>\n",
       "      <td>585693</td>\n",
       "      <td>24</td>\n",
       "      <td>0.330</td>\n",
       "      <td>0.267</td>\n",
       "      <td>2</td>\n",
       "      <td>-19.607</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0511</td>\n",
       "      <td>0.8560</td>\n",
       "      <td>0.782000</td>\n",
       "      <td>0.1270</td>\n",
       "      <td>0.2350</td>\n",
       "      <td>102.855</td>\n",
       "      <td>short term</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Take Some Time - Emancipator Remix</td>\n",
       "      <td>Take Some Time (Emancipator Remix)</td>\n",
       "      <td>28M2ugvRSIa4MIKmiiwNao</td>\n",
       "      <td>Wilderado</td>\n",
       "      <td>290428</td>\n",
       "      <td>42</td>\n",
       "      <td>0.545</td>\n",
       "      <td>0.596</td>\n",
       "      <td>5</td>\n",
       "      <td>-8.216</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0289</td>\n",
       "      <td>0.0249</td>\n",
       "      <td>0.025200</td>\n",
       "      <td>0.2190</td>\n",
       "      <td>0.1820</td>\n",
       "      <td>95.002</td>\n",
       "      <td>short term</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Greenland</td>\n",
       "      <td>Safe In the Steep Cliffs</td>\n",
       "      <td>2SPTGg9SC5MT1FwNX4IYfx</td>\n",
       "      <td>Emancipator</td>\n",
       "      <td>191066</td>\n",
       "      <td>58</td>\n",
       "      <td>0.593</td>\n",
       "      <td>0.398</td>\n",
       "      <td>4</td>\n",
       "      <td>-13.301</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0295</td>\n",
       "      <td>0.0273</td>\n",
       "      <td>0.827000</td>\n",
       "      <td>0.2310</td>\n",
       "      <td>0.0989</td>\n",
       "      <td>98.728</td>\n",
       "      <td>short term</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Frosty The Snowman - Remastered 2006</td>\n",
       "      <td>Bing Crosby - Christmas Classics</td>\n",
       "      <td>35MqcEIVZ7svbBpRt4N30g</td>\n",
       "      <td>Bing Crosby</td>\n",
       "      <td>133413</td>\n",
       "      <td>66</td>\n",
       "      <td>0.519</td>\n",
       "      <td>0.368</td>\n",
       "      <td>7</td>\n",
       "      <td>-11.622</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0796</td>\n",
       "      <td>0.6170</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0859</td>\n",
       "      <td>0.8540</td>\n",
       "      <td>160.370</td>\n",
       "      <td>short term</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>145</th>\n",
       "      <td>Smek - Rey&amp;Kjavik Remix</td>\n",
       "      <td>Smek (Rey&amp;Kjavik Remix)</td>\n",
       "      <td>1PyfWp1rg8omX2DOtg65pR</td>\n",
       "      <td>Ÿuma</td>\n",
       "      <td>366006</td>\n",
       "      <td>54</td>\n",
       "      <td>0.892</td>\n",
       "      <td>0.281</td>\n",
       "      <td>2</td>\n",
       "      <td>-13.880</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0435</td>\n",
       "      <td>0.8560</td>\n",
       "      <td>0.878000</td>\n",
       "      <td>0.1950</td>\n",
       "      <td>0.0433</td>\n",
       "      <td>99.984</td>\n",
       "      <td>long term</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>It's All Theatre</td>\n",
       "      <td>MAKTUB</td>\n",
       "      <td>0vW9cGyvGU9xCreJzs8caE</td>\n",
       "      <td>Satori</td>\n",
       "      <td>238016</td>\n",
       "      <td>22</td>\n",
       "      <td>0.778</td>\n",
       "      <td>0.375</td>\n",
       "      <td>1</td>\n",
       "      <td>-13.180</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0484</td>\n",
       "      <td>0.5460</td>\n",
       "      <td>0.785000</td>\n",
       "      <td>0.0959</td>\n",
       "      <td>0.3330</td>\n",
       "      <td>120.987</td>\n",
       "      <td>long term</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>147</th>\n",
       "      <td>Baby Girl</td>\n",
       "      <td>Baby Girl</td>\n",
       "      <td>6DNTJAvdyDwkmiPm2Wl8At</td>\n",
       "      <td>Bryce Vine</td>\n",
       "      <td>145371</td>\n",
       "      <td>56</td>\n",
       "      <td>0.860</td>\n",
       "      <td>0.592</td>\n",
       "      <td>2</td>\n",
       "      <td>-8.606</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0861</td>\n",
       "      <td>0.1660</td>\n",
       "      <td>0.000609</td>\n",
       "      <td>0.2760</td>\n",
       "      <td>0.6210</td>\n",
       "      <td>107.016</td>\n",
       "      <td>long term</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>Will We Ever Carry On</td>\n",
       "      <td>Chances</td>\n",
       "      <td>2AMAh0IXu1Wwwdw3Jzojqt</td>\n",
       "      <td>Luke Marzec</td>\n",
       "      <td>254549</td>\n",
       "      <td>18</td>\n",
       "      <td>0.638</td>\n",
       "      <td>0.293</td>\n",
       "      <td>0</td>\n",
       "      <td>-15.712</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0337</td>\n",
       "      <td>0.5550</td>\n",
       "      <td>0.505000</td>\n",
       "      <td>0.1110</td>\n",
       "      <td>0.2260</td>\n",
       "      <td>81.802</td>\n",
       "      <td>long term</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149</th>\n",
       "      <td>Uma Vida</td>\n",
       "      <td>Uma Vida</td>\n",
       "      <td>46qMKSFypTgW2Yk5dRyWgN</td>\n",
       "      <td>Gerra G</td>\n",
       "      <td>399183</td>\n",
       "      <td>16</td>\n",
       "      <td>0.757</td>\n",
       "      <td>0.829</td>\n",
       "      <td>2</td>\n",
       "      <td>-7.263</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0454</td>\n",
       "      <td>0.1860</td>\n",
       "      <td>0.631000</td>\n",
       "      <td>0.1040</td>\n",
       "      <td>0.6140</td>\n",
       "      <td>97.987</td>\n",
       "      <td>long term</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>150 rows × 18 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                               track_name                               album  \\\n",
       "0                          Time for Space                             Baralku   \n",
       "1                    Márquez: Danzón No.2     Música Clásica Esencial: México   \n",
       "2      Take Some Time - Emancipator Remix  Take Some Time (Emancipator Remix)   \n",
       "3                               Greenland            Safe In the Steep Cliffs   \n",
       "4    Frosty The Snowman - Remastered 2006    Bing Crosby - Christmas Classics   \n",
       "..                                    ...                                 ...   \n",
       "145               Smek - Rey&Kjavik Remix             Smek (Rey&Kjavik Remix)   \n",
       "146                      It's All Theatre                              MAKTUB   \n",
       "147                             Baby Girl                           Baby Girl   \n",
       "148                 Will We Ever Carry On                             Chances   \n",
       "149                              Uma Vida                            Uma Vida   \n",
       "\n",
       "                   track_id          artist  duration  popularity  \\\n",
       "0    3dJXvBddoH1AGLpKvmbYDA     Emancipator    433613          56   \n",
       "1    4IM73PUWb5Y07VcFOsUlhE  Arturo Márquez    585693          24   \n",
       "2    28M2ugvRSIa4MIKmiiwNao       Wilderado    290428          42   \n",
       "3    2SPTGg9SC5MT1FwNX4IYfx     Emancipator    191066          58   \n",
       "4    35MqcEIVZ7svbBpRt4N30g     Bing Crosby    133413          66   \n",
       "..                      ...             ...       ...         ...   \n",
       "145  1PyfWp1rg8omX2DOtg65pR            Ÿuma    366006          54   \n",
       "146  0vW9cGyvGU9xCreJzs8caE          Satori    238016          22   \n",
       "147  6DNTJAvdyDwkmiPm2Wl8At      Bryce Vine    145371          56   \n",
       "148  2AMAh0IXu1Wwwdw3Jzojqt     Luke Marzec    254549          18   \n",
       "149  46qMKSFypTgW2Yk5dRyWgN         Gerra G    399183          16   \n",
       "\n",
       "     danceability  energy  key  loudness  mode  speechiness  acousticness  \\\n",
       "0           0.610   0.313    5   -13.138     0       0.0323        0.3900   \n",
       "1           0.330   0.267    2   -19.607     0       0.0511        0.8560   \n",
       "2           0.545   0.596    5    -8.216     1       0.0289        0.0249   \n",
       "3           0.593   0.398    4   -13.301     0       0.0295        0.0273   \n",
       "4           0.519   0.368    7   -11.622     1       0.0796        0.6170   \n",
       "..            ...     ...  ...       ...   ...          ...           ...   \n",
       "145         0.892   0.281    2   -13.880     1       0.0435        0.8560   \n",
       "146         0.778   0.375    1   -13.180     1       0.0484        0.5460   \n",
       "147         0.860   0.592    2    -8.606     1       0.0861        0.1660   \n",
       "148         0.638   0.293    0   -15.712     0       0.0337        0.5550   \n",
       "149         0.757   0.829    2    -7.263     1       0.0454        0.1860   \n",
       "\n",
       "     instrumentalness  liveness  valence    tempo   Timeframe  \n",
       "0            0.840000    0.0899   0.0870   80.009  short term  \n",
       "1            0.782000    0.1270   0.2350  102.855  short term  \n",
       "2            0.025200    0.2190   0.1820   95.002  short term  \n",
       "3            0.827000    0.2310   0.0989   98.728  short term  \n",
       "4            0.000000    0.0859   0.8540  160.370  short term  \n",
       "..                ...       ...      ...      ...         ...  \n",
       "145          0.878000    0.1950   0.0433   99.984   long term  \n",
       "146          0.785000    0.0959   0.3330  120.987   long term  \n",
       "147          0.000609    0.2760   0.6210  107.016   long term  \n",
       "148          0.505000    0.1110   0.2260   81.802   long term  \n",
       "149          0.631000    0.1040   0.6140   97.987   long term  \n",
       "\n",
       "[150 rows x 18 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top_tracks.drop_duplicates()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['danceability',\n",
       " 'energy',\n",
       " 'key',\n",
       " 'loudness',\n",
       " 'mode',\n",
       " 'speechiness',\n",
       " 'acousticness',\n",
       " 'instrumentalness',\n",
       " 'liveness',\n",
       " 'valence']"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(top_tracks_short_df.columns[6:-2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "audio_features = list(top_tracks_short_df.columns[6:-2])\n",
    "audio_features.append(\"Timeframe\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
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       "    }\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>danceability</th>\n",
       "      <th>energy</th>\n",
       "      <th>key</th>\n",
       "      <th>loudness</th>\n",
       "      <th>mode</th>\n",
       "      <th>speechiness</th>\n",
       "      <th>acousticness</th>\n",
       "      <th>instrumentalness</th>\n",
       "      <th>liveness</th>\n",
       "      <th>valence</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Timeframe</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>long term</th>\n",
       "      <td>0.68168</td>\n",
       "      <td>0.464146</td>\n",
       "      <td>5.60</td>\n",
       "      <td>-10.52928</td>\n",
       "      <td>0.44</td>\n",
       "      <td>0.089780</td>\n",
       "      <td>0.427003</td>\n",
       "      <td>0.232752</td>\n",
       "      <td>0.143908</td>\n",
       "      <td>0.366074</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>medium term</th>\n",
       "      <td>0.69172</td>\n",
       "      <td>0.499178</td>\n",
       "      <td>5.40</td>\n",
       "      <td>-11.24320</td>\n",
       "      <td>0.46</td>\n",
       "      <td>0.067410</td>\n",
       "      <td>0.379048</td>\n",
       "      <td>0.420345</td>\n",
       "      <td>0.129594</td>\n",
       "      <td>0.332924</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>short term</th>\n",
       "      <td>0.61538</td>\n",
       "      <td>0.487878</td>\n",
       "      <td>4.76</td>\n",
       "      <td>-10.25580</td>\n",
       "      <td>0.38</td>\n",
       "      <td>0.083654</td>\n",
       "      <td>0.389676</td>\n",
       "      <td>0.258441</td>\n",
       "      <td>0.151214</td>\n",
       "      <td>0.384346</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             danceability    energy   key  loudness  mode  speechiness  \\\n",
       "Timeframe                                                                \n",
       "long term         0.68168  0.464146  5.60 -10.52928  0.44     0.089780   \n",
       "medium term       0.69172  0.499178  5.40 -11.24320  0.46     0.067410   \n",
       "short term        0.61538  0.487878  4.76 -10.25580  0.38     0.083654   \n",
       "\n",
       "             acousticness  instrumentalness  liveness   valence  \n",
       "Timeframe                                                        \n",
       "long term        0.427003          0.232752  0.143908  0.366074  \n",
       "medium term      0.379048          0.420345  0.129594  0.332924  \n",
       "short term       0.389676          0.258441  0.151214  0.384346  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "audio_overtime_df = top_tracks[audio_features].groupby(\"Timeframe\").mean()\n",
    "audio_overtime_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "audio_overtime_df.reset_index(inplace = True)\n",
    "df_loud_key = audio_overtime_df[[\"loudness\",\"key\"]] #for better viz these need to be plotted seperately\n",
    "df_loud_key.set_index(pd.Index([\"long term\", \"medium term\", \"short term\"]), inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "audio_overtime_df.drop([\"loudness\",\"key\"], axis = 1, inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "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>Timeframe</th>\n",
       "      <th>audio_feature</th>\n",
       "      <th>mean</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>long term</td>\n",
       "      <td>danceability</td>\n",
       "      <td>0.681680</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>medium term</td>\n",
       "      <td>danceability</td>\n",
       "      <td>0.691720</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>short term</td>\n",
       "      <td>danceability</td>\n",
       "      <td>0.615380</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>long term</td>\n",
       "      <td>energy</td>\n",
       "      <td>0.464146</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>medium term</td>\n",
       "      <td>energy</td>\n",
       "      <td>0.499178</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>short term</td>\n",
       "      <td>energy</td>\n",
       "      <td>0.487878</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>long term</td>\n",
       "      <td>mode</td>\n",
       "      <td>0.440000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>medium term</td>\n",
       "      <td>mode</td>\n",
       "      <td>0.460000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>short term</td>\n",
       "      <td>mode</td>\n",
       "      <td>0.380000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>long term</td>\n",
       "      <td>speechiness</td>\n",
       "      <td>0.089780</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>medium term</td>\n",
       "      <td>speechiness</td>\n",
       "      <td>0.067410</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>short term</td>\n",
       "      <td>speechiness</td>\n",
       "      <td>0.083654</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>long term</td>\n",
       "      <td>acousticness</td>\n",
       "      <td>0.427003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>medium term</td>\n",
       "      <td>acousticness</td>\n",
       "      <td>0.379048</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>short term</td>\n",
       "      <td>acousticness</td>\n",
       "      <td>0.389676</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>long term</td>\n",
       "      <td>instrumentalness</td>\n",
       "      <td>0.232752</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>medium term</td>\n",
       "      <td>instrumentalness</td>\n",
       "      <td>0.420345</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>short term</td>\n",
       "      <td>instrumentalness</td>\n",
       "      <td>0.258441</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>long term</td>\n",
       "      <td>liveness</td>\n",
       "      <td>0.143908</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>medium term</td>\n",
       "      <td>liveness</td>\n",
       "      <td>0.129594</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>short term</td>\n",
       "      <td>liveness</td>\n",
       "      <td>0.151214</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>long term</td>\n",
       "      <td>valence</td>\n",
       "      <td>0.366074</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>medium term</td>\n",
       "      <td>valence</td>\n",
       "      <td>0.332924</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>short term</td>\n",
       "      <td>valence</td>\n",
       "      <td>0.384346</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Timeframe     audio_feature      mean\n",
       "0     long term      danceability  0.681680\n",
       "1   medium term      danceability  0.691720\n",
       "2    short term      danceability  0.615380\n",
       "3     long term            energy  0.464146\n",
       "4   medium term            energy  0.499178\n",
       "5    short term            energy  0.487878\n",
       "6     long term              mode  0.440000\n",
       "7   medium term              mode  0.460000\n",
       "8    short term              mode  0.380000\n",
       "9     long term       speechiness  0.089780\n",
       "10  medium term       speechiness  0.067410\n",
       "11   short term       speechiness  0.083654\n",
       "12    long term      acousticness  0.427003\n",
       "13  medium term      acousticness  0.379048\n",
       "14   short term      acousticness  0.389676\n",
       "15    long term  instrumentalness  0.232752\n",
       "16  medium term  instrumentalness  0.420345\n",
       "17   short term  instrumentalness  0.258441\n",
       "18    long term          liveness  0.143908\n",
       "19  medium term          liveness  0.129594\n",
       "20   short term          liveness  0.151214\n",
       "21    long term           valence  0.366074\n",
       "22  medium term           valence  0.332924\n",
       "23   short term           valence  0.384346"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plot_df = pd.melt(audio_overtime_df, id_vars = \"Timeframe\",\n",
    "                           var_name = \"audio_feature\", value_name = \"mean\")\n",
    "plot_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#%matplotlib inline\n",
    "sns.catplot(data = plot_df, kind = \"bar\", x = \"Timeframe\",\n",
    "            y = \"mean\", hue = \"audio_feature\"\n",
    ")\n",
    "fig = plt.gcf()\n",
    "fig.set_size_inches(10, 5)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['danceability',\n",
       " 'energy',\n",
       " 'key',\n",
       " 'loudness',\n",
       " 'mode',\n",
       " 'speechiness',\n",
       " 'acousticness',\n",
       " 'instrumentalness',\n",
       " 'liveness',\n",
       " 'valence']"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cluster_feat = audio_features[:-1]\n",
    "cluster_feat"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[<AxesSubplot:title={'center':'danceability'}>,\n",
       "        <AxesSubplot:title={'center':'energy'}>,\n",
       "        <AxesSubplot:title={'center':'key'}>],\n",
       "       [<AxesSubplot:title={'center':'loudness'}>,\n",
       "        <AxesSubplot:title={'center':'speechiness'}>,\n",
       "        <AxesSubplot:title={'center':'acousticness'}>],\n",
       "       [<AxesSubplot:title={'center':'instrumentalness'}>,\n",
       "        <AxesSubplot:title={'center':'liveness'}>,\n",
       "        <AxesSubplot:title={'center':'valence'}>]], dtype=object)"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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CXJDkxcCNwLNHE54kSVLvlkzaquojwEIdQRzif41bt8gvE/381UJaib3UWwDHDzMWSZKk1eqpT5skSZIkaTRM2iRJkiSpw0zaJEmSJKnDTNokSZIkqcNM2iRJkiSpw0zaJEmSRizJMUk+nGR7kuuSvKJdfliSS5Nc394eOupYJQ1fL/O0SZImyGLTdUgaqd3Apqq6OsnBwFVJLgXOAC6rqi1JNgObgVeNME5JI+CVNkmSpBGrqp1VdXV7/w5gO3A0cDJwbrvZucApIwlQ0kh5pU2SJKlDkqwDHgNcAUxV1U5oErskRy6yz0ZgI8DU1BQzMzM9PdfUAbBp/e4+RP09vT733szOzvblOIOwVGzbbvlG359z/dH3W3KbcX7Nhm3PZ76fn/9Bl8+kTZIkqSOSHAS8B3hlVd2epKf9qmorsBVgw4YNNT093dN+bzzvIs7e1t/TwR2n9vbcezMzM0OvZRi2pWI7YwBN0Ht5Tcf5NRu2Pe/RpvW7+/b578fnfm9sHilJktQBSfajSdjOq6oL28W3JjmqXX8UsGtU8UkaHZM2SZKkEUtzSe0twPaqeu2cVRcDp7f3TwcuGnZskkbP5pGSJEmj9yTgNGBbkmvaZWcCW4ALkrwYuBF49mjCkzRKJm2SJEkjVlUfARbrwHb8MGOR1D02j5QkSZKkDlsyaUtyTJIPJ9me5Lokr2iXH5bk0iTXt7eHDj5cSZIkSVpbernSthvYVFWPAJ4I/FqSRwKbgcuq6ljgsvaxJEmSJKmPlkzaqmpnVV3d3r8D2A4cDZwMnNtudi5wyoBilCRJkqQ1a1kDkSRZBzwGuAKYqqqd0CR2SY5cZJ+NwEaAqampZc0W3rXZ0/tp2GXbdss3+n7MTesXXt7P2eW7ZH65JumzOTs7O+oQJEmStIiek7YkB9FM+PjKqrq9mU5kaVW1FdgKsGHDhlrObOhdmz29n4Zdtj0zvw9DP2eX75L55Rr0zPfDNEkJqCRJ0qTpafTIJPvRJGznVdWF7eJbkxzVrj8K2DWYECVJkiRp7epl9MgAbwG2V9Vr56y6GDi9vX86cFH/w5OklUny1iS7klw7Z9lZSW5Jck37d+IoY5QkSepFL1fangScBvzMvBOdLcBTk1wPPLV9LEldcQ5wwgLLX1dVx7V/HxhyTJIkScu2ZMejqvoIsFgHtuP7G44k9UdVXd4OniRJkjTWJm+0CEnau5cleQFwJc0clLfN32A1o96OynJGpO3y6K7jOvrsG8+7Zw+BqQMWXt6rxUboXY2VfpYneTRn9d+6Pgx+tmn97u8bRG3HlpNWfUx9v368T/P5Pg2OSZukteRPgdcA1d6eDbxo/karGfV2VJYzIu0wR5NdrkkafbaLZVnpqLeTPJqzJI2DnkaPlKRJUFW3VtVdVXU38Cbg8aOOSZIkaSkmbZLWjD3TlLSeCVy72LaSJEld0a12G5LUJ0neCUwDhye5GXg1MJ3kOJrmkTuAl4wqPkmSpF6ZtEmaSFX1vAUWv2XogUiSOmmlA3HMHyRFGgabR0qSJElSh5m0SZIkdUCStybZleTaOcvOSnJLkmvavxNHGaOk0TBpkyRJ6oZzgBMWWP66qjqu/fvAkGOS1AH2aZNWyEkpJUn9VFWXJ1k36jgkdY9JmyRJUre9LMkLgCuBTVV12/wNkmwENgJMTU0xMzPT04GnDmgG1uia+XH1Wp7lWGm5R/Ga9VL+2dnZZb1OgyjDYs+/3NgGbU/Z+/leDrp8Jm2SJEnd9afAa2imKnkNcDbwovkbVdVWYCvAhg0banp6uqeDv/G8izh7W/dOBzet3/19ce04dbrvz7HSESDnxzYMvZR/ZmaGXt93WHn592axOJcb26DtKXs/38tBfEbnsk+bJElSR1XVrVV1V1XdDbwJePyoY5I0fCZtkiRJHZXkqDkPnwlcu9i2kiZX966HS5IkrUFJ3glMA4cnuRl4NTCd5Dia5pE7gJeMKj5Jo7Nk0pbkrcAzgF1V9ah22VnArwJfbjc70yFoJUmSVq6qnrfA4rcMPRBJndPLlbZzgD8C3jZv+euq6g/6HpEkSZIkMZgplsbRkn3aqupy4GtDiEWSJEmSNM9q+rQtOWcIrHzeEOjenA79NOyyDXM+ka7O+bJawyjXqD7vs7OzI3leSZIkLW2lSVtPc4bAyucNge7N6dBPwy7bIObiWMwo5i8ZhmGUa9BzfCxmUn8ckSRJmgQrGvLfOUMkSZIkaThWlLQ5Z4gkSZIkDUcvQ/47Z4gkSZIkjciSSZtzhkiSJEnS6KyoeaQkSZIkaThM2iRJkiSpw0zaJEmSJKnDTNokTaQkb02yK8m1c5YdluTSJNe3t4eOMkZJkqRemLRJmlTnACfMW7YZuKyqjgUuax9LkiR1mkmbpIlUVZcDX5u3+GTg3Pb+ucApw4xJkiRpJZYc8l+SJshUVe0EqKqdSY5caKMkG4GNAFNTU8zMzAwvwhWanZ3tOc5N63cPNphVmDqg2/EtRxfLstLP8nI+X5Kk/jNpk6R5qmorsBVgw4YNNT09PdqAejAzM0OvcZ6x+ZLBBrMKm9bv5uxtk/GvqYtl2XHq9Ir2W87nS5LUfzaPlLSW3JrkKID2dteI45EkSVqSSZukteRi4PT2/unARSOMRZIkqScmbZImUpJ3Ah8DHp7k5iQvBrYAT01yPfDU9rEkdYJTlUhajEmbpIlUVc+rqqOqar+qemBVvaWqvlpVx1fVse3t/NElJWmUzsGpSiQtoFs9pCVJ32ddj4OGbFq/u9MDjEhaWlVdnmTdvMUnA9Pt/XOBGeBVw4tKUheYtEmSJHXXQKcq6eLUFHDPuAYx5cRKyz2K16yX8i93ao5BlGGx51/NtCGDfK37+V4OeloUkzZJkqQxt9KpSt543kWdm5oC7jllxkqnq9iblbZOGMV0Hr2Uf7lTcwyidcZica5m2pBBtiLp53s5iM/oXEv2abNTrCRJ0sg4VYmkngYiOQc7xUqSJI2CU5VIWjppq6rLgfkjrJ1M0xmW9vaU/oYlSZK0tjhViaTFrLQRZ0+dYmHlHWNhdZ0Wu27YZRtmh9mudmperWGUa1Sf99nZ2ZE8ryTpe6rqeYusOn6ogUjqnIH3olxpx1hYXafFrht22YY5FPgoOugOwzDKNehOrIuZ1B9HJEmSJsFKJ9e2U6wkSZIkDcFKkzY7xUqSJEnSEPQy5L+dYiVJkiRpRJbsoGOn2OFbN8T+Z+qWQbz3O7ac1PdjSpIkaXgmb7QISRoRf3DRWuSPTZI0eCvt0yZJkiRJGgKTNkmSJEnqMJM2SZIkSeowkzZJkiRJ6jAHIpEkSZI6rJcBfzat380ZDog1sbzSJkmSJEkdZtImSZIkSR1m0iZJkiRJHWafNklrTpIdwB3AXcDuqtow2ogkSZIWZ9Imaa16clV9ZdRBSJIkLcXmkZIkSZLUYV5pk7QWFfChJAX8eVVtnbsyyUZgI8DU1BQzMzM9HXTT+t19DrN3UweM9vn7ZVLKAd0sS6+f5flmZ2cX3XcQZVxpnJI0qdZU0tbLHBfD4lwa0kg9qaq+mORI4NIkn6mqy/esbJO4rQAbNmyo6enpng46yu/0pvW7OXvb+Ffpk1IO6GZZdpw6vaL9ZmZmWOx7MIjP/UrjnGT2xZXWtm79N5GkIaiqL7a3u5K8F3g8cPne95KkkbMvrrRGrapPW5IdSbYluSbJlf0KSpIGJcmBSQ7ecx/4WeDa0UYlSZK0uH5cafNXH0njZAp4bxJo6sB3VNUHRxuSJC1pIH1xu9j3Eu4Z1xvPu6jvz7Fp/cr2G5fXbBQWe5+mDlj5e7jS96kX/XzNBt0X1+aRktaUqvoc8OhRxyFJyzSQvrhvPO+izvW9hG72Cd2jq7F1NS7obmz9jGvQfXFXG+Vef/WBlf/yA3sfrWolRv3rw1xd+DVkUCa1bONarl6+Q7Ozs4MPRNLIrXRALgfPGj374kpr22qTtr3+6gMr/+UH9j5a1Up06R9OV39x6IdJLdu4lquXX34cXluSuqvtf/sDVXXHnL64vzvisCQN0aoGIpn7qw+w51cfSZIk9c8U8JEknwI+AVxiX1xpbVnxZQN/9ZEkSRo8++JKWk1bL0dgkyRJkqQBW3HS5q8+kiRJkjR4q+rTJkmSJEkaLJM2SZIkSeowkzZJkiRJ6jCTNkmSJEnqMJM2SZIkSeowkzZJkiRJ6jCTNkmSJEnqMJM2SZIkSeowkzZJkiRJ6rB9Rx3AYtZtvoRN63dzxuZLRh2KJEmSJI2MV9okSZIkqcNM2iRJkiSpw0zaJEmSJKnDTNokSZIkqcNM2iRJkiSpw1aVtCU5Iclnk9yQZHO/gpKkQbHekjSOrLuktW3FSVuSfYA/Bp4OPBJ4XpJH9iswSeo36y1J48i6S9JqrrQ9Hrihqj5XVd8GzgdO7k9YkjQQ1luSxpF1l7TGpapWtmPyLOCEqvqV9vFpwBOq6mXzttsIbGwfPhz47DKe5nDgKysKsPss2/iZ1HJBU7YDq+qIUQcySEOqt0ZlUj6fk1IOsCzD8mDrrlXVW119b7saF3Q3tq7GBd2NbVRxLbve2ncVT5YFlt0jA6yqrcDWFT1BcmVVbVjJvl1n2cbPpJYLvlu2daOOYwgGXm+NyqR8PielHGBZ1FdL1l0rrbe6+t52NS7obmxdjQu6G1tX41rIappH3gwcM+fxA4Evri4cSRoo6y1J48i6S1rjVpO0fRI4NslDkuwPPBe4uD9hSdJAWG9JGkfWXdIat+LmkVW1O8nLgL8F9gHeWlXX9S2yxlg1T1omyzZ+JrVcMNll+64h1VujMinv4aSUAyyL+mTAdVdX39uuxgXdja2rcUF3Y+tqXPew4oFIJEmSJEmDt6rJtSVJkiRJg2XSJkmSJEkd1omkLckJST6b5IYkmxdYf2qST7d/H03y6FHEuVxLlWvOdo9Lclc7D8tY6KVsSaaTXJPkuiT/MOwYV6qHz+P9kvx1kk+1ZXvhKOJcriRvTbIrybWLrE+SP2zL/ekkjx12jNq7SaorJ6l+nKT6cFLrP91Tr9/BYUtyTJIPJ9nefsZeMeqY5kqyT5J/SvL+UccyV5JDkrw7yWfa1+4nRh0TQJL/0r6P1yZ5Z5J7jzCWe5wHJTksyaVJrm9vDx1VfEuqqpH+0XSo/VfgocD+wKeAR87b5ieBQ9v7TweuGHXc/SjXnO3+HvgA8KxRx93H9+wQ4J+BB7WPjxx13H0s25nA77f3jwC+Buw/6th7KNtPA48Frl1k/YnA39DMB/TEcfieraW/SaorJ6l+nKT6cJLrP/+W/16PMLajgMe29w8G/qUrsbUx/VfgHcD7Rx3LvLjOBX6lvb8/cEgHYjoa+DxwQPv4AuCMEcZzj/Mg4P8Am9v7m/fUb13868KVtscDN1TV56rq28D5wMlzN6iqj1bVbe3Dj9PMT9J1S5ar9XLgPcCuYQa3Sr2U7ZeBC6vqRoCqGpfy9VK2Ag5OEuAgmpOW3cMNc/mq6nKaWBdzMvC2anwcOCTJUcOJTj2YpLpykurHSaoPJ7b+0z30+h0cuqraWVVXt/fvALbTnPyPXJIHAicBbx51LHMluS9NQvIWgKr6dlV9faRBfc++wAFJ9gXuwwjnF1zkPOhkmoSX9vaUYca0HF1I2o4Gbprz+Gb2/uV8Mc3VgK5bslxJjgaeCfzZEOPqh17esx8GDk0yk+SqJC8YWnSr00vZ/gh4BE3Fsw14RVXdPZzwBmq530UN1yTVlZNUP05SfbiW67+1Zizq+yTrgMcAV4w4lD1eD/wm0LXP/EOBLwN/0TbdfHOSA0cdVFXdAvwBcCOwE/hGVX1otFHdw1RV7YTmBwPgyBHHs6guJG1ZYNmC8xAkeTLNicirBhpRf/RSrtcDr6qquwYfTl/1UrZ9gR+n+UXqacD/TPLDgw6sD3op29OAa4AHAMcBf9T+yjXuev4uaiQmqa6cpPpxkurDtVz/rTWdr++THERzpf2VVXV7B+J5BrCrqq4adSwL2Jem2d+fVtVjgDtpmvqNVNs/7GTgITR1xoFJnj/aqMZXF5K2m4Fj5jx+IAtcOk3yYzSXo0+uqq8OKbbV6KVcG4Dzk+wAngX8SZJThhLd6vRStpuBD1bVnVX1FeByoLODIszRS9leSNPUqarqBpr22j8ypPgGqafvokZmkurKSaofJ6k+XMv131rT6fo+yX40Cdt5VXXhqONpPQn4+bZOOh/4mSRvH21I33UzcHNV7bki+W6aJG7UngJ8vqq+XFXfAS6k6XvdJbfu6QrS3na1+XonkrZPAscmeUiS/YHnAhfP3SDJg2je6NOq6l9GEONKLFmuqnpIVa2rqnU0X7D/XFXvG3qky7dk2YCLgP+QZN8k9wGeQNMuvet6KduNwPEASaaAhwOfG2qUg3Ex8II0nkjTjGHnqIPSd01SXTlJ9eMk1Ydruf5ba3p5r0ei7S/5FmB7Vb121PHsUVW/VVUPbOuk5wJ/X1WduGpUVV8Cbkry8HbR8TSDH43ajcATk9ynfV+Pp3t138XA6e3902nq607ad9QBVNXuJC8D/pZmNKO3VtV1SV7arv8z4LeBH6T5pRVgd1VtGFXMveixXGOpl7JV1fYkHwQ+TdP2+81VteBQ813S4/v2GuCcJNtompi8qv31vNOSvBOYBg5PcjPwamA/+G65PkAzguQNwDdpflFXR0xSXTlJ9eMk1YeTXP/p+y32Xo84rD2eBJwGbEtyTbvszKr6wOhCGgsvB85rk/DP0YH/4VV1RZJ3A1fTDFj0T8DWUcWzyHnQFuCCJC+mSTKfPar4lpKqTjVhliRJkiTN0YXmkZIkSZKkRZi0SZIkSVKHmbRJkiRJUoeZtEmSJElSh5m0SZIkSVKHmbRJkiRJUoeZtEmSJElSh5m0SZIkSVKHmbRJkiRJUoeZtEmSJElSh5m0SZIkSVKHmbRJkiRJUoeZtEmSJElSh5m0TagkO5I8pc/HPCPJR/p5TEkaliTnJPlfe1k/m+Shw4xJkpYjyXVJpkcdh4Zv31EHIElSF1TVQaOOQZL2SHIOcHNV/Y89y6rqR0cXkUbJK22SJEmS1GEmbRMuyb2SvD7JF9u/1ye5V7vuHs0dk1SSh7X3fzDJxUluT/IJ4IcW2PalSa5PcluSP06SOetflGR7u+5vkzy4XZ4kr0uyK8k3knw6yaPadScm+eckdyS5JclvDPglkjRgSV7Vfp/vSPLZJMcnOSvJu5O8q11+dZJHz9nnAUnek+TLST6f5NfnrPuBJJuT/GuSrya5IMlhc9b/VJKPJvl6kpuSnDEnnEOTXNI+5xVJfmjOfnPrv3PaOm2xbX8kyaVJvtaW6Tlz1i1YjyU5PMn727i+luQfk/h/WOqYOfXLHe13+Zlz1v1qe26zZ91j2+WPSDLTfr+vS/Lzc/aZSfIrcx5/9/xrsXOiJBuBU4HfTNN0+6/b7b/b/SXJPknOnBPrVUmOadd5jjZh/Gcx+f478ETgOODRwOOB/7G3Heb4Y+DfgaOAF7V/8z0DeFx77OcATwNIcgpwJvALwBHAPwLvbPf5WeCngR8GDgF+Cfhqu+4twEuq6mDgUcDf9xirpA5K8nDgZcDj2u/104Ad7eqTgb8CDgPeAbwvyX5tIvPXwKeAo4HjgVcmeVq7368DpwD/EXgAcBtNfUWSBwF/A7yRpu45DrhmTkjPA34HOBS4Afi9vYS/4LZJDgQubWM+st3uT5Lsaba0WD22Cbi5jWuKpo6svTy/pNH4V+A/APejqQPenuSoJM8GzgJeANwX+Hngq0n2o6mzPkRTJ7wcOK+t/5ay4DlRVW0FzgP+T1UdVFU/t8C+/5Wm/jmxjedFwDfnrPccbYKYtE2+U4HfrapdVfVlmsrntKV2SrIP8IvAb1fVnVV1LXDuAptuqaqvV9WNwIdpTpAAXgL8f1W1vap2A/8bOK79Jec7wMHAjwBpt9nZ7vcd4JFJ7ltVt1XV1SstuKROuAu4F833er+q2lFV/9quu6qq3l1V3wFeC9yb5kemxwFHVNXvVtW3q+pzwJuA57b7vQT471V1c1V9i+Yk6llJ9qWp8/6uqt5ZVd+pqq9W1TVz4rmwqj7R1kvn8b06ayGLbfsMYEdV/UVV7W7rqfcAz2rXL1aPfYfmR7AHt7H9Y1WZtEkdU1V/VVVfrKq7q+pdwPU0P3r/Ck0S9clq3FBVX6Cptw6iOSf6dlX9PfB+moRqKXs7J1rKrwD/o6o+28bzqar66pz1nqNNEJO2yfcA4AtzHn+hXbaUI2gGqrlp3r7zfWnO/W/SVFoADwbe0DYT+DrwNSDA0W1l9kc0v4zfmmRrkvu2+/0izS9GX0jyD0l+oodYJXVUVd0AvJImsdqV5Pwke+qgm+ZsdzfNVagH0NQfD9hTf7R1yJk0V6do1793zrrtNMnhFHAMza/ki1mszlrOtg8GnjAvvlOB+7frF6vH/i/NFbsPJflcks17eW5JI5LkBUmumfP9fhRwOIvXLw8AbmrrsT2+QNNSYK+WOCdaykrrO8/RxpBJ2+T7Is2Xc48HtcsA7gTus2dFkvvP2e7LwG6aCmHuvr26ieYS+iFz/g6oqo8CVNUfVtWPAz9Kcwn+v7XLP1lVJ9M0L3gfcMEynlNSB1XVO6rqp2jqogJ+v1313fqlbRL5QJr66Sbg8/Pqj4Or6sR285uAp89bf++quqVd9339bwfgJuAf5j3/QVX1n9ryLliPVdUdVbWpqh4K/BzwX5McP+BYJS1De7XpTTTNun+wqg4BrqVJaharX74IHJPv76P6IOCW9v73nW/xvR94gMXPiVi6+fRK6zvP0caQSdvkeyfwP5IckeRw4LeBt7frPgX8aJLjktyb5pdwAKrqLuBC4Kwk90nySOD0ZTzvnwG/taePR5L7tW3BSfK4JE9o24DfSdNv7q4k+yc5Ncn92uZSt9P8ei5pTCV5eJKfSTMA0r8D/8b3vtc/nuQX2maNrwS+BXwc+ARwe5oBTA5oO9s/Ksnj2v3+DPi9OR3nj0hycrvuPOApSZ6TZN80Ayod1+divR/44SSntX3w9mvrtUfsrR5L8owkD0uSOcut46RuOZAmWfoyQJIX0lxpA3gz8BtJfrwdsONhbT10Bc35zG+29cE0zQ8z57f7XQP8Qns+9TDgxXuebLFzonb1rcDe5o58M/CaJMe28fxYkh/soYyeo40hk7bJ97+AK4FPA9uAq9tlVNW/AL8L/B1Ne+35E2e/jOZS+peAc4C/6PVJq+q9NL+mn5/kdppfqZ7err4vza9Yt9E0H/gq8AftutOAHe0+LwWe33NJJXXRvYAtwFdo6pIjaZo6AlxE08n9Nprv/i+0fb3uojnhOQ74fLvvm2kGBQB4A3AxTTPDO2gSvScAtH03TqQZ9ONrNCdL3x2Vsh+q6g6azvrPpfmF/Us09d292k0Wq8eOpalvZ4GPAX9SVTP9jE3S6lTVPwNn03xHbwXWA/+vXfdXNAMSvQO4g+Zq02FV9W2aQUmeTlNf/Qnwgqr6THvY1wHfbo93Ls2PS3vs7ZzoLTR9yL6e5H0LhPtamqtdH6JJot4CHNBDGT1HG0OxD7QkadiSnAU8rKr8py9J0hK80iZJkiRJHWbSJkmSJEkdZvNISZIkSeowr7RJkiRJUoeZtEmSJElSh+07zCc7/PDDa926dQM7/p133smBBx44sOP3m/EO3rjFPMp4r7rqqq9U1REjefIOG3S9NSzj9l3Ym0kqC1ie1bLuuqfl1Fvj9Pkbl1jHJU4w1kFZKtaV1FtDTdrWrVvHlVdeObDjz8zMMD09PbDj95vxDt64xTzKeJN8YSRP3HGDrreGZdy+C3szSWUBy7Na1l33tJx6a5w+f+MS67jECcY6KEvFupJ6y+aRkiRJktRhJm2SJEmS1GEmbZIkSZLUYSZtkiRJktRhJm2SJEmS1GFDHT1SGoV1my8ZyHF3bDlpIMdV75K8FXgGsKuqHtUuOwx4F7AO2AE8p6pua9f9FvBi4C7g16vqb/sZzyA+a37OJA3Stlu+wRl9rrust6T+80qbpHF2DnDCvGWbgcuq6ljgsvYxSR4JPBf40XafP0myz/BClSRJWhmTNkljq6ouB742b/HJwLnt/XOBU+YsP7+qvlVVnwduAB4/jDglSZJWw+aRkibNVFXtBKiqnUmObJcfDXx8znY3t8vuIclGYCPA1NQUMzMzPT3xpvW7Vxjy4np97qXMzs727VijNkllAcsjSVqaSZuktSILLKuFNqyqrcBWgA0bNtT09HRPT9DvfiEAO07t7bmXMjMzQ6/l6LpJKgtYHknS0mweKWnS3JrkKID2dle7/GbgmDnbPRD44pBjkyRJWjaTNkmT5mLg9Pb+6cBFc5Y/N8m9kjwEOBb4xAjikyRJWhabR0oaW0neCUwDhye5GXg1sAW4IMmLgRuBZwNU1XVJLgD+GdgN/FpV3TWSwCVJkpbBpE3S2Kqq5y2y6vhFtv894PcGF5EkSVL/2TxSkiRJkjrMpE2SJEmSOsykTZIkSZI6zKRNkiRJkjrMpE2SJEmSOsykTZIkSZI6zKRNkiRJkjrMpE2SJEmSOsykTZIkSZI6zKRNkiRJkjrMpE2SJEmSOsykTZIkSZI6zKRNkiRJkjrMpE2SJEmSOsykTZIkSZI6zKRNkiRJkjrMpE2SJEmSOsykTZIkSZI6bMmkLcm9k3wiyaeSXJfkd9rlhyW5NMn17e2hgw9XkiRp8ni+JWlvernS9i3gZ6rq0cBxwAlJnghsBi6rqmOBy9rHktQJSf5Le+JzbZJ3tidEnvxI6irPtyQtasmkrRqz7cP92r8CTgbObZefC5wyiAAlabmSHA38OrChqh4F7AM8F09+JHWU51uS9mbfXjZKsg9wFfAw4I+r6ookU1W1E6CqdiY5cpF9NwIbAaamppiZmelL4AuZnZ0d6PH7zXgHb3Z2lk3r7xrIsQfxWozja9xh+wIHJPkOcB/gi8BvAdPt+nOBGeBVowhOkuYbxfnW1AGwaf3ufoT/XYP6PzYu/yPHJU4w1kEZRKypqt43Tg4B3gu8HPhIVR0yZ91tVbXXpkYbNmyoK6+8cmWR9mBmZobp6emBHb/fjHfwZmZmOOODdw7k2Du2nNT3Y47yNU5yVVVtGMmTD0CSVwC/B/wb8KGqOjXJ13upt+ad/Pz4+eef39NzbrvlG/0I/fusP/p+fTnO7OwsBx10UF+ONWqTVBawPKv15Cc/eaLqLhju+dYbz7uIs7f19Bt+zwbx/xHG5zxkXOIEYx2UpWJdyTnXsr6lVfX1JDPACcCtSY5qf/U5Cti1nGNJ0qC0fdVOBh4CfB34qyTP73X/qtoKbIXm5KfXfxJnbL5kuaEuacepvT33Usbpn91SJqksYHl0T55vSZqvl9Ejj2h/8SHJAcBTgM8AFwOnt5udDlw0oBglabmeAny+qr5cVd8BLgR+kvbkB8CTH0ld4vmWpL3p5UrbUcC5bTvrHwAuqKr3J/kYcEGSFwM3As8eYJzqoHWDuKowoCYVWnNuBJ6Y5D40zSOPB64E7qQ56dmCJz+SusXzLUmLWjJpq6pPA49ZYPlXaU6EJKlT2s777wauBnYD/0TT3PEgPPmR1EGeb0nam/72PJWkjqiqVwOvnrf4W3jyI0mSxkwvk2tLkiRJkkbEpE2SJEmSOsykTZIkSZI6zKRNkiRJkjrMpE2SJEmSOsykTZIkSZI6zKRNkiRJkjrMpE2SJEmSOszJtdUp6zZf0tfjbVq/Gz/mkiRJGmdeaZMkSZKkDjNpkyRJkqQOM2mTJEmSpA4zaZMkSZKkDjNpkyRJkqQOM2mTJEmSpA4zaZMkSZKkDjNpkyRJkqQOM2mTJEmSpA4zaZMkSZKkDtt31AFI42rd5kv6fsxzTjiw78dcq5IcArwZeBRQwIuAzwLvAtYBO4DnVNVto4lQkiSpN15pkzSp3gB8sKp+BHg0sB3YDFxWVccCl7WPJUmSOs2kTdLESXJf4KeBtwBU1ber6uvAycC57WbnAqeMIj5JkqTlsHmkpEn0UODLwF8keTRwFfAKYKqqdgJU1c4kRy60c5KNwEaAqakpZmZmenrSTet3rz7yeXp97qXMzs727VijNkllAcsjSVqaSZukSbQv8Fjg5VV1RZI3sIymkFW1FdgKsGHDhpqenu5pvzMG0M9xx6m9PfdSZmZm6LUcXTdJZQHLo8kziD7fO7ac1PdjSuPE5pGSJtHNwM1VdUX7+N00SdytSY4CaG93jSg+SZKknpm0SZo4VfUl4KYkD28XHQ/8M3AxcHq77HTgohGEJ0mStCw2j5Q0qV4OnJdkf+BzwAtpfqi6IMmLgRuBZ48wPkmSpJ6YtEmaSFV1DbBhgVXHDzkUSZKkVVmyeWSSY5J8OMn2JNcleUW7/LAklya5vr09dPDhSpIkTR7PtyTtTS992nYDm6rqEcATgV9L8kicpFaSJKlfPN+StKglk7aq2llVV7f37wC2A0fjJLWSJEl94fmWpL1ZVp+2JOuAxwBXMOBJaldi3Cb0HPd4BzGRcL9NHTAece4xbp8JSVL/DfN8a1z+T87MzIzN/8hxiROMdVAGEWvPSVuSg4D3AK+sqtuT9LTfSiepXYlxm9Bz3OMdxETC/bZp/W7O3jY+4+2cc8KBY/WZkCT117DPt9543kVj8X9yx6nTY3PeNC5xgrEOyiBi7WmetiT70VQg51XVhe1iJ6mVJEnqE8+3JC2ml9EjA7wF2F5Vr52zyklqJUmS+sDzLUl708v18CcBpwHbklzTLjsT2IKT1EqSJPWD51uSFrVk0lZVHwEWa1DtJLWSJEmr5PmWpL3pqU+bJEmSJGk0TNokSZIkqcNM2iRJkiSpw0zaJEmSJKnDTNokSZIkqcNM2iRJkiSpw0zaJEmSJKnDTNokSZIkqcNM2iRJkiSpw0zaJEmSJKnDTNokTawk+yT5pyTvbx8fluTSJNe3t4eOOkZJkqSlmLRJmmSvALbPebwZuKyqjgUuax9LkiR1mkmbpImU5IHAScCb5yw+GTi3vX8ucMqQw5IkSVq2fUcdgCQNyOuB3wQOnrNsqqp2AlTVziRHLrRjko3ARoCpqSlmZmZ6esJN63evItyF9frcS5mdne3bsUZtksoClkeShm3d5kv6fswdW07q+zHnMmmTNHGSPAPYVVVXJZle7v5VtRXYCrBhw4aanu7tEGcM4p/Aqb0991JmZmbotRxdN0llAcsjSVqaSZukSfQk4OeTnAjcG7hvkrcDtyY5qr3KdhSwa6RRSpIk9cA+bZImTlX9VlU9sKrWAc8F/r6qng9cDJzebnY6cNGIQpQkSeqZV9okrSVbgAuSvBi4EXj2iOORJE2Ybbd8o+/N5QfdX0rdZ9ImaaJV1Qww097/KnD8KOORJElaLptHSpIkSVKHeaVtjejH0Kab1u8eyOh4kiRJ0kL2nMOu9fNQr7RJkiRJUoeZtEmSJElSh5m0SZIkSVKH2adNkiRJnbZu8yV979PkMPoaJ15pkyRJkqQOM2mTJEmSpA4zaZMkSZKkDrNPm9Qh2275Rt/nILHNviRJGoZ+zAushS15pS3JW5PsSnLtnGWHJbk0yfXt7aGDDVOSJGmyec4laTG9NI88Bzhh3rLNwGVVdSxwWftYkiRJK3cOnnNJWsCSSVtVXQ58bd7ik4Fz2/vnAqf0NyxJkqS1xXMuSYtZaZ+2qaraCVBVO5McudiGSTYCGwGmpqaYmZlZ4VMubXZ2dqDH77dhxrtp/e5VH2PqgP4cZ5jGLeZBxDtO3wlJ0j30dM610vOtcfo/2e9YB/X/cRCv6RvPu6ivxwNYf/T9+n4uOsjPUtc/q3Nfx0Gc4w98IJKq2gpsBdiwYUNNT08P7LlmZmYY5PH7bZjx9mNwi03rd3P2tvEau2bcYh5EvDtOne7r8SRJ3bPS8603nnfR2Pyf7Pf/yEH9fxyX13THqdN9Pxft92Bqc3X9nG7u52kQ5/grHfL/1iRHAbS3u/oXkiRJklqec0la8ZW2i4HTgS3tbf+v2UqSJMlzrgEZ1PD0m9YP5LBa43oZ8v+dwMeAhye5OcmLaSqOpya5Hnhq+1iSJEkr5DmXpMUseaWtqp63yKrj+xyLJGmefv0SvGn97u/2NXDCdambPOeStJiV9mmTpM5KckySDyfZnuS6JK9olztJrSRJGjsmbZIm0W5gU1U9Angi8GtJHomT1EqSpDFk0iZp4lTVzqq6ur1/B7AdOBonqZUkSWOou5MdSFIfJFkHPAa4ggFPUtvlST/nTko67hOuD2LS0lGyPJKkpZi0SZpYSQ4C3gO8sqpuT9LTfiudpHaQk4qu1txJScd9wvVBTFo6SpZHkrQUm0dKmkhJ9qNJ2M6rqgvbxU5SK0mSxo5Jm6SJk+aS2luA7VX12jmr9kxSC05SK0mSxoTNIyVNoicBpwHbklzTLjuTZlLaC9oJa28Enj2a8CRJknpn0iZp4lTVR4DFOrA5Sa0kSRorJm2SJEnSGrNu8yVsWr+704No6Xvs0yZJkiRJHWbSJkmSJEkdZtImSZIkSR1mn7ZVWreKdsCLtSPeseWk1YQkSZIkaYJ4pU2SJEmSOsykTZIkSZI6zKRNkiRJkjrMpE2SJEmSOsykTZIkSZI6zKRNkiRJkjrMIf87aDXTCEiSJEmaLF5pkyRJkqQOM2mTJEmSpA4zaZMkSZKkDutsn7aV9OvatH43Z+xlvx1bTlpNSJI0Ecal36x1tiRJDa+0SZIkSVKHdfZKmyRpbVvsiuBSrSr2ZlBX71Zz9XKx8nilUZK0h0mbJEkdNIhmrINIBOfHuZqkeg8TVkn6fqtqHpnkhCSfTXJDks39CkqSBsV6S9I4su6S1rYVJ21J9gH+GHg68EjgeUke2a/AJKnfrLckjSPrLkmraR75eOCGqvocQJLzgZOBf+5HYJI0ANZba9y4jJwpzWPdJa1xq2keeTRw05zHN7fLJKmrrLckjSPrLmmNS1WtbMfk2cDTqupX2senAY+vqpfP224jsLF9+HDgsysPd0mHA18Z4PH7zXgHb9xiHmW8D66qI0b03EPR0XprWMbtu7A3k1QWsDyrZd3Fquqtcfr8jUus4xInGOugLBXrsuut1TSPvBk4Zs7jBwJfnL9RVW0Ftq7ieXqW5Mqq2jCM5+oH4x28cYt53OIdQ52rt4Zlkj5bk1QWsDzqyZJ110rrrXF6v8Yl1nGJE4x1UAYR62qaR34SODbJQ5LsDzwXuLg/YUnSQFhvSRpH1l3SGrfiK21VtTvJy4C/BfYB3lpV1/UtMknqM+stSePIukvSqibXrqoPAB/oUyz9MG7NmYx38MYt5nGLd+x0sN4alkn6bE1SWcDyqAcDrLvG6f0al1jHJU4w1kHpe6wrHohEkiRJkjR4q+nTJkmSJEkasLFP2pL83ySfSfLpJO9Ncki7fF2Sf0tyTfv3ZyMO9bsWi7ld91tJbkjy2SRPG2GY35Xk2UmuS3J3kg1zlnfyNV4s3nZd517f+ZKcleSWOa/riaOOSeMhyQntZ/uGJJsXWP8jST6W5FtJfmMUMS5HD+U5ta1HP53ko0kePYo4e9VDeU5uy3JNkiuT/NQo4uzFUmWZs93jktyV5FnDjE/31MPnL0n+sF3/6SSP7Wicnfnej9P3oJdYk0y39c91Sf5h2DG2MSz1/t8vyV8n+VQb5wtHEWcby1uT7Epy7SLr+/udqqqx/gN+Fti3vf/7wO+399cB1446vmXG/EjgU8C9gIcA/wrs04F4H0Ez58sMsGHO8k6+xnuJt5Ov7wLxnwX8xqjj8G+8/mgGJ/hX4KHA/u1n/ZHztjkSeBzwe13/jPVYnp8EDm3vPx24YtRxr7I8B/G9bgs/Bnxm1HGvtCxztvt7mn5Yzxp13Gv5r8fP34nA3wABnjiK79M4fe/H6XvQ4+t6CPDPwIPax0d2NM4z+d558xHA14D9R/S6/jTwWBY5F+73d2rsr7RV1Yeqanf78OM0c5d02l5iPhk4v6q+VVWfB24AHj+KGOeqqu1VNTaTC+8l3k6+vlKfPB64oao+V1XfBs6n+cx/V1XtqqpPAt8ZRYDL1Et5PlpVt7UPu17/91Ke2Wr/0wMHAl3tdL5kWVovB94D7BpmcFpQL+/ZycDbqvFx4JAkR3Utzg5978fpe9BLrL8MXFhVN0Lz/2LIMUJvcRZwcJLQ/ND1NWA3I1BVl7fPv5i+fqfGPmmb50U0Ge0eD0nyT0n+Icl/GFVQS5gb89HATXPW3dwu67JxeI33GKfX92XtpfS3Jjl01MFoLIzT57sXyy3Pi/n++r9reipPkmcm+QxwCc3/hy5asixJjgaeCXSi2bx6+vx1oQ4Zp+/9OH0Penldfxg4NMlMkquSvGBo0X1PL3H+EU2Lqi8C24BXVNXdwwlv2fr6nVrVkP/DkuTvgPsvsOq/V9VF7Tb/nSbTPq9dt5PmEu9Xk/w48L4kP1pVt3c45iyw/VB+ae0l3gWM7DVeYbwje33n21v8wJ8Cr6GJ7TXA2XT35E3d0ZnPd5/0XJ4kT6Y5eetsHzB6LE9VvRd4b5Kfpvn+P2XQga1AL2V5PfCqqrqr+UFcI9bLe9aFOmScvvfj9D3oJdZ9gR8HjgcOAD6W5ONV9S+DDm6OXuJ8GnAN8DPADwGXJvnHYZ3fL1Nfv1NjkbRV1V7/aSU5HXgGcPyepiVV9S3gW+39q5L8K82vCFcOOFza51x2zDQZ+DFzNnsgzS8JA7dUvIvsM7LXeCXxMsLXd75e40/yJuD9Aw5Hk6Ezn+8+6ak8SX4MeDPw9Kr66pBiW4llvT9VdXmSH0pyeFV9ZeDRLU8vZdkAnN+eqB4OnJhkd1W9bygRar5e3rMu1CHj9L0fp+9Br+//V6rqTuDOJJcDjwaGmbT1EucLgS3tufMNST4P/AjwieGEuCx9/U6NffPIJCcArwJ+vqq+OWf5EUn2ae8/FDgW+Nxoovx+i8UMXAw8N8m9kjyEJuYufgiBbr/GixiL13dee+dnAguOSiTN80ng2CQPSbI/8Fyaz/y4WrI8SR4EXAicNuRfg1eil/I8rO2nQTvK2P5AFxPRJctSVQ+pqnVVtQ54N/CfTdhGqpf64WLgBe2Id08EvlFVO7sWZ4e+9+P0Pejl/b8I+A9J9k1yH+AJwPYOxnkjzdVAkkzRDDzX1XPPvn6nxuJK2xL+iGY0wEvb/3Ufr6qX0ozo8rtJdgN3AS+tqr11FhymBWOuquuSXEAzes9u4Neq6q4Rxgk0fSyAN9KM0nNJkmuq6ml09DVeLN6uvr4L+D9JjqO5hL4DeMlIo9FYqKrdSV4G/C3NCFxvbT/zL23X/1mS+9NcCb8vcHeSV9KMzNW5ZiW9lAf4beAHgT9p69LdVbVhsWOOUo/l+UWaf/DfAf4N+KU5LTE6o8eyqEN6fM8+QDPa3Q3AN2muaHQxzk5878fpe9BLrFW1PckHgU8DdwNvrqqh/mjc42v6GuCcJNtomh++alStEZK8E5gGDk9yM/BqYL85sfb1O5UO/j+QJEmSJLXGvnmkJEmSJE0ykzZJkiRJ6jCTNkmSJEnqMJM2SZIkSeowkzZJkiRJ6jCTNkmSJEnqMJM2SZIkSeowkzZJkiRJ6jCTNkmSJEnqMJM2SZIkSeowkzZJkiRJ6jCTNkmSJEnqMJM2SZIkSeowkzZJkiRJ6jCTtiFLcl2S6VHH0VVJ1iWpJPuOOhZJo5FkR5KnJDkzyZtHHY8kDVKS6SQ3jzoOdZsnxkNWVT+6mv2TnAU8rKqe35+IBivJGcCvVNVPjToWSeOlqv73qGOQJKkLvNI2YdLwfZUkSZImhCf3Qzan2c9ZSS5I8rYkd7TNJjfM2e5VSW5p1302yfFJTgDOBH4pyWyST7XbziT5vST/D/gm8NA9zzPneGcleXt7f08TxBcmuSnJbUlemuRxST6d5OtJ/mhe3C9Ksr3d9m+TPHjOumr3v75d/8dt8vgI4M+An2jj/Xq7/UlJ/inJ7e3zn7WX12smyWuS/L/2tfhQksPnrH9iko+2MX9qbtPTJGck+Vy73+eTnNouf1iSf0jyjSRfSfKu5b+TkgZtXr31wSQvm7f+U0l+ob3/I0kuTfK1ts58zpztzmnrpUva+uCKJD80Z/3e9j0xyT+3+92S5Dfa5YcneX9b93wtyT/6g5m0tiXZnOTd85a9Ickftudc29u65HNJXrKX4zwgyXuSfLk9f/n1OeuWOn88JsmF7b5fnXs+t7dzOXWf/2BG6+eB84FDgIuBPwJI8nDgZcDjqupg4GnAjqr6IPC/gXdV1UFV9eg5xzoN2AgcDHyhx+d/AnAs8EvA64H/DjwF+FHgOUn+YxvPKTTJ4i8ARwD/CLxz3rGeATwOeDTwHOBpVbUdeCnwsTbeQ9pt7wRe0Jb7JOA/tc+xmF8GXggcCewP7DlpOhq4BPhfwGHt8vckOSLJgcAfAk9vX8OfBK5pj/ca4EPAocADgTcu+UpJGrV3AM/b8yDJI4EHA5e03/dL222ObLf7kyRzm6M/D/gdmu/9DcDvtcdZat+3AC9p65FHAX/fLt8E3ExTJ07R1JHV3yJLGjPvBE5Mcl+AJPvQnBO9A9hFc650X5pzmtcleez8A7Q//vw18CngaOB44JVJnjZns8XOH/cB3k9zHriu3f/8dt0pLH0upw4zaRutj1TVB6rqLuAvaRIegLuAewGPTLJfVe2oqn9d4ljnVNV1VbW7qr7T4/O/pqr+vao+RJNIvbOqdlXVLTRf5se0270E+P+qantV7aZJHI+b9wvNlqr6elXdCHwYOG6xJ62qmaraVlV3V9WnaSqN/7iXOP+iqv6lqv4NuGDOsZ8PfKB9De+uqkuBK4ET2/V3A49KckBV7ayq69rl36E52XtAW/6PLPlKSRq19/L99c6pwIVV9S2aE6EdVfUXbR14NfAe4Flz9r+wqj7R1mHn8b16ZKl9v0NTF9+3qm5r1+9ZfhTw4Kr6TlX9Y1WZtElrWFV9AbgaOKVd9DPAN6vq41V1SVX9azX+gebH4/+wwGEeBxxRVb9bVd+uqs8BbwKeO2ebxc4fHw88APhvVXXnvHOcXs7l1GEmbaP1pTn3vwncO8m+VXUD8ErgLGBXkvOTPGCJY920gue/dc79f1vg8UHt/QcDb2ibAX0d+BoQml9w9phfloNYRJInJPlwe+n+GzRX4w5fbPu9HPvBwLP3xNXG9lPAUVV1J80VxJcCO9tmUT/S7vebbfyfaJsVvGgvzy2pA6rqDpor63tOXJ5Lk3xBUxc8YV5dcCpw/zmH2Fs9srd9f5Hmh6AvtM2qf6Jd/n9prth9qG3qtLlPRZU03ua2Cvjl9jFJnp7k421z6q/T1CsLnfs8GHjAvDrpTJor+nsseP4IHAN8oU3KFjruUudy6jCTto6qqne0Iy4+mKbJze/vWbXYLvMe3wncZ87j+7NyN9E0Dzpkzt8BVfXRHvZdKN530FzOP6aq7kfT7y0rjOsv58V1YFVtAaiqv62qp9L8Gv4Zml+qqKovVdWvVtUDaH55+pMkD1vB80sarncCz2sTpwNorupDUxf8w7y64KCq+k89HHOv+1bVJ6vqZJqmk++judpPVd1RVZuq6qHAzwH/NcnxfS2tpHH0V8B0kgcCzwTekeReNFfw/wCYaruLfICFz31uAj4/r046uKpOXGDbhfZ9UBaeNmk153LqAJO2Dkry8CQ/037J/53mqtdd7epbgXU9dHi/Bnhukv3aDqrPWmL7vfkz4Lf29PFIcr8kz+5x31uBBybZf86yg4GvVdW/J3k8zS9RK/F24OeSPC3JPknunWaukwcmmUry821/lW8Bs7SvYZJnt5UpwG00ieVdCz6DpC75AM0PWb9L07f37nb5+4EfTnJaW+ftl2ZgpUf0cMxF902yf5JTk9yvbXZ+O9+rR56RZlCjzFluPSKtcVX1ZWAG+Aua5Gs7TX/8ewFfBnYneTrws4sc4hPA7WkGpDugPb95VJLH9fD0nwB2AluSHNieFz2pXbeaczl1gElbN90L2AJ8heYS+JE0l8ah+QUH4KtJrl5g3z3+J/BDNEnJ79Benl+JqnovzZW+85PcDlwLPL3H3f8euA74UpKvtMv+M/C7Se4Afpv2l+sVxHUTcDLNa/Nlml+R/hvN5/oHaAYK+CJNE4D/2D4vNO3Fr0gyS3PF7xVV9fmVxCBpeNr+axfSDJj0jjnL76A5AXouzXf+SzR11r16OOZS+54G7GjrvpfS9KWFZhCnv6P5QehjwJ9U1cyqCihpUryDOfVUW8/8Os35zm00P1ZfvNCObT+1n6Ppd/t5mnPBNwP3W+pJ5+z7MOBGmsGSfqldt5pzOXVA7DctSZIkSd3llTZJkiRJ6jCTNkmSJEnqMJM2SZIkSeowkzZJkiRJ6rCF5nEYmMMPP7zWrVvX07Z33nknBx544GAD6pNxihWMd9DGNd6rrrrqK1V1xKjj6Zrl1FuTZtw+y/20Vss+juW27rqnufXWOL6nMJ5xj2PMYNzDtJpzrqEmbevWrePKK6/saduZmRmmp6cHG1CfjFOsYLyDNq7xJvnCqGPpouXUW5Nm3D7L/bRWyz6O5bbuuqe59dY4vqcwnnGPY8xg3MO0mnMum0dKkiRJUoeZtEmSJElSh5m0SZIkSVKHmbRJkiRJUoeZtEmaSEkOSfLuJJ9Jsj3JTyQ5LMmlSa5vbw8ddZySJElLGerokcux7ZZvcMbmS/p6zB1bTurr8SR12huAD1bVs5LsD9wHOBO4rKq2JNkMbAZe1a8nXNfnOgustyRpUPpdZ29av5szNl9iva2B8EqbpImT5L7ATwNvAaiqb1fV14GTgXPbzc4FThlFfJIkScvR2SttkrQKDwW+DPxFkkcDVwGvAKaqaidAVe1McuRCOyfZCGwEmJqaYmZmpqcn3bR+9+ojn6fX5x6E2dnZkT7/KK3Vsq/VcktS15m0SZpE+wKPBV5eVVckeQNNU8ieVNVWYCvAhg0bqtfJO/vdpBtgx6m9PfcgjOPEpf2yVsu+VsvdBUmOAd4G3B+4G9haVW9IchbwqzQ/RAGcWVUfGE2UkkbFpE3SJLoZuLmqrmgfv5smabs1yVHtVbajgF0ji1CSvt9uYFNVXZ3kYOCqJJe2615XVX8wwtgkjZhJm6SJU1VfSnJTkodX1WeB44F/bv9OB7a0txeNMMyeOLiJtDa0Tbf3NN++I8l24OjRRiWpK0zaJE2qlwPntSNHfg54Ic3gSxckeTFwI/DsEcYnSQtKsg54DHAF8CTgZUleAFxJczXutgX2WbAv7lL9FLfd8o3+Bg+sP/p+qz7G/LgHEeem9f093tQBTd/mcesXOq59Wccx7tXEbNImaSJV1TXAhgVWHT/kUCSpZ0kOAt4DvLKqbk/yp8BrgGpvzwZeNH+/xfriLtVPsat9cefHPYg4+23T+t2cvW3fkfZFXolx7cs6jnGvJmaH/JckSeqAJPvRJGznVdWFAFV1a1XdVVV3A28CHj/KGCWNhkmbJEnSiCUJzdyS26vqtXOWHzVns2cC1w47Nkmj11PzyCT/BfgVmkvz22j6htwHeBewDtgBPGehNtaSJEla0pOA04BtSa5pl50JPC/JcTTnYDuAl4wiOEmjtWTSluRo4NeBR1bVvyW5AHgu8EjgsqrakmQzzXDarxpotJIkSROoqj4CZIFVzskmqefmkfsCByTZl+YK2xeBk4Fz2/XnAqf0PTpJkiRJWuOWvNJWVbck+QOa4bH/DfhQVX0oyVQ7pwjtRLVHLrT/YkPQLmXPsKn9NKhhQcdtyFHjHSzjlSRJUj/10jzyUJqrag8Bvg78VZLn9/oEiw1Bu5Q3nncRZ2/r74wEgxqCddyGHDXewTJeSZIk9VMvzSOfAny+qr5cVd8BLgR+Erh1z4hG7e2uwYUpSZIkSWtTL0nbjcATk9ynHY72eGA7cDFwervN6cBFgwlRkiRJktauXvq0XZHk3cDVwG7gn2iaOx4EXJDkxTSJ3bMHGagkSZIkrUU9dRqrqlcDr563+Fs0V90kSZIkSQPS65D/kiRJkqQRMGmTJEmSpA4zaZMkSZKkDjNpkyRJkqQO6+/s1ZLUEUl2AHcAdwG7q2pDksOAdwHrgB3Ac6rqtlHFKEmS1AuvtEmaZE+uquOqakP7eDNwWVUdC1zWPpYkSeo0kzZJa8nJwLnt/XOBU0YXiiRJUm9sHilpUhXwoSQF/HlVbQWmqmonQFXtTHLkQjsm2QhsBJiammJmZqanJ9y0fnc/4h64XsszOzvb87aTZq2Wfa2WW5K6zqRN0qR6UlV9sU3MLk3ymV53bBO8rQAbNmyo6enpnvY7Y/MlK4lz6HacOt3TdjMzM/Ra9kmzVsu+VsstSV1n80hJE6mqvtje7gLeCzweuDXJUQDt7a7RRShJktQbkzZJEyfJgUkO3nMf+FngWuBi4PR2s9OBi0YToSRJUu9sHilpEk0B700CTT33jqr6YJJPAhckeTFwI/DsEcYoSd+V5BjgbcD9gbuBrVX1BqcqkQQmbZImUFV9Dnj0Asu/Chw//IgkaUm7gU1VdXXbUuCqJJcCZ9BMVbIlyWaaqUpeNcI4JY2AzSMlSZJGrKp2VtXV7f07gO3A0ThViSS80iZJktQpSdYBjwGuYJVTlSw1jcMgpirpx7QR8+MehylVpg5o4hy3aTPGdaqPcYx7NTGbtEmSJHVEkoOA9wCvrKrb2765S1psqpKlpnEYxFQlvU4rsjfz4x6HKVU2rd/N2dv27Uv5h2lcp/oYx7hXE7PNIyVJkjogyX40Cdt5VXVhu9ipSiSZtEmSJI1amktqbwG2V9Vr56xyqhJJNo+UJEnqgCcBpwHbklzTLjsT2IJTlUhrnkmbJEnSiFXVR4DFOrA5VYm0xpm0SZIkqW/W9WHQkE3rd4/F4CPSsNinTZIkSZI6zKRNkiRJkjrMpE2SJEmSOqynpC3JIUneneQzSbYn+YkkhyW5NMn17e2hgw5WkiRJktaaXq+0vQH4YFX9CPBoYDuwGbisqo4FLmsfS5IkSZL6aMmkLcl9gZ+mmfCRqvp2VX0dOBk4t93sXOCUwYQoSZIkSWtXL0P+PxT4MvAXSR4NXAW8Apiqqp0AVbUzyZEL7ZxkI7ARYGpqipmZmZ4CmzqgGe61n3p97uWanZ0d2LEHwXgHy3i7I8k+wJXALVX1jCSHAe8C1gE7gOdU1W2ji1CSJGlpvSRt+wKPBV5eVVckeQPLaApZVVuBrQAbNmyo6enpnvZ743kXcfa2/k4jt+PU3p57uWZmZui1XF1gvINlvJ3yCprm3PdtH+9p1r0lyeb28atGFZwkSVIveunTdjNwc1Vd0T5+N00Sd2uSowDa212DCVGSli/JA4GTgDfPWWyzbkmSNHaWvJRVVV9KclOSh1fVZ4HjgX9u/04HtrS3Fw00UklantcDvwkcPGfZQJt197tJ96D0Wp5Jbjq7lLVa9rVabknqul7bH74cOC/J/sDngBfSXKW7IMmLgRuBZw8mRElaniTPAHZV1VVJppe7/0qbdZ+x+ZLlPtVI9NpUfMKbzu7VWi37Wi23JHVdT0lbVV0DbFhg1fF9jUaS+uNJwM8nORG4N3DfJG+nbdbdXmWzWbckSRoLvc7TJkljo6p+q6oeWFXrgOcCf19VzwcupmnODTbrliRJY8KkTdJasgV4apLrgae2jyVJkjqtv2PqS1LHVNUMMNPe/yo265YkSWPGpE2SJEnqk3UDGJRqx5aT+n5MjRebR0qSJElSh5m0SZIkSVKHmbRJkiR1QJK3JtmV5No5y85KckuSa9q/E0cZo6TRMGmTJEnqhnOAExZY/rqqOq79+8CQY5LUASZtkiRJHVBVlwNfG3UckrrH0SMlSZK67WVJXgBcCWyqqtvmb5BkI7ARYGpqipmZGQBmZ2e/e38hm9bvHkC4qzd1QHdjW8wgY97be7haS31Gumoc415NzCZtkiRJ3fWnwGuAam/PBl40f6Oq2gpsBdiwYUNNT08Dzcn+nvsLOWMAw9P3w6b1uzl723idpg4y5h2nTg/kuLD0Z6SrxjHu1cRs80hJkqSOqqpbq+quqrobeBPw+FHHJGn4TNokSZI6KslRcx4+E7h2sW0lTa7xuu4sSZI0oZK8E5gGDk9yM/BqYDrJcTTNI3cALxlVfJJGx6RNkiSpA6rqeQssfsvQA9GasK7tz7hp/e6+9W3cseWkvhxH92TzSEmSJEnqMJM2SZIkSeowkzZJkiRJ6jCTNkkTJ8m9k3wiyaeSXJfkd9rlhyW5NMn17e2ho45VkiRpKSZtkibRt4CfqapHA8cBJyR5IrAZuKyqjgUuax9LkiR1mkmbpIlTjdn24X7tXwEnA+e2y88FThl+dJIkScvjkP+SJlKSfYCrgIcBf1xVVySZqqqdAFW1M8mRi+y7EdgIMDU1xczMTE/PuWn97n6EPnC9lmd2drbnbSfNWi37Wi23JHWdSZukiVRVdwHHJTkEeG+SRy1j363AVoANGzbU9PR0T/v1a56bQdtx6nRP283MzNBr2SfNWi37Wi23JHVdz80jk+yT5J+SvL99bId+SZ1XVV8HZoATgFuTHAXQ3u4aXWSSJEm9WU6ftlcA2+c8tkO/pE5KckR7hY0kBwBPAT4DXAyc3m52OnDRSAKUJElahp6StiQPBE4C3jxnsR36JXXVUcCHk3wa+CRwaVW9H9gCPDXJ9cBT28eSJEmd1mufttcDvwkcPGfZQDv0Tx3Q/079g+pcPW4dt413sIx39Krq08BjFlj+VeD44UckSZK0cksmbUmeAeyqqquSTC/3CVbaof+N513E2dv6O05Kr53vl2vcOm4b72AZryRJkvqpl6zoScDPJzkRuDdw3yRvp+3Q315ls0O/JEmSJA3Akn3aquq3quqBVbUOeC7w91X1fOzQL0mSJEkDt5zRI+ezQ78kSZIkDdiyOo1V1QzNfEd26JckSZKkIVjNlTZJkiRJ0oCZtEmSJHVAkrcm2ZXk2jnLDktyaZLr29tDRxmjpNEwaZMkSeqGc4AT5i3bDFxWVccCl7WPJa0xJm2SJEkdUFWXA1+bt/hk4Nz2/rnAKcOMSVI39Hf2akmSJPXTVFXtBGjnxj1yoY2SbAQ2AkxNTTEzMwPA7Ozsd+8vZNP63X0Otz+mDuhubIsZZMx7ew9Xak+s/Yz7jef1fwaw9Uffb8HlS322u2g1MZu0SZIkjbmq2gpsBdiwYUNNT08Dzcn+nvsLOWPzJUOIbvk2rd/N2dvG6zR1kDHvOHW678fc8953/bVerOxLfba7aDUx2zxSkiSpu25NchRAe7trxPFIGgGTNkmSpO66GDi9vX860P/2Z5I6z6RNkiSpA5K8E/gY8PAkNyd5MbAFeGqS64Gnto8lrTHdbcAqSZK0hlTV8xZZdfxQA5HUOSZtkiZOkmOAtwH3B+4GtlbVG5IcBrwLWAfsAJ5TVbeNKk5JknqxrqMDxmh4bB4paRLtBjZV1SOAJwK/luSROEmtJEkaQyZtkiZOVe2sqqvb+3cA24GjcZJaSZI0hmweKWmiJVkHPAa4glVOUruUcZkIttfyjOPEpf2yVsu+VsstSV1n0iZpYiU5CHgP8Mqquj1JT/stNkntUro6Se18vU7SOo4Tl/bLWi37Wi23JHWdzSMlTaQk+9EkbOdV1YXtYieplSRJY8ekTdLESXNJ7S3A9qp67ZxVTlIrSZLGjs0jJU2iJwGnAduSXNMuO5NmUtoL2glrbwSePZrwJEmSemfSJmniVNVHgMU6sDlJrSRJGis2j5QkSZKkDjNpkyRJkqQOM2mTJEmSpA4zaZMkSZKkDjNpkyRJkqQOW3L0yCTHAG8D7g/cDWytqjckOQx4F7AO2AE8p6puG1yokqR+WLf5kp6227R+N2f0uO2OLSetJiRJkrQXvQz5vxvYVFVXJzkYuCrJpcAZwGVVtSXJZmAz8KrBhSp1y2Invss50Z3PE19JkiTNt2TzyKraWVVXt/fvALYDRwMnA+e2m50LnDKgGCVJkiRpzVrW5NpJ1gGPAa4ApqpqJzSJXZIjF9lnI7ARYGpqipmZmZ6ea+qA5opFP/X63Ms1Ozs7sGMPgvH2x2Kfz9V8dt943kWrCWlB64++317Xd/X1lSRJUqPnpC3JQcB7gFdW1e1JetqvqrYCWwE2bNhQ09PTPe33xvMu4uxty8opl7Tj1N6ee7lmZmbotVxdYLz9sVgTyE3rd/f9s7saS33uu/r6SpIkqdHTmWWS/WgStvOq6sJ28a1Jjmqvsh0F7BpUkJIkSWtZkh3AHcBdwO6q2jDaiCQN05J92tJcUnsLsL2qXjtn1cXA6e3904H+t+uSJEnSHk+uquNM2KS1p5crbU8CTgO2JbmmXXYmsAW4IMmLgRuBZw8kQkmSJElaw5ZM2qrqI8BiHdiO7284kiRJWkABH0pSwJ+3YwZ812IDvy012FS/B33rl0EMSDdo4xgzdD/uxT6/4ziQ2mpi7s5oCZLUR0neCjwD2FVVj2qXHQa8C1gH7ACeU1W3jSpGSVqGJ1XVF9vRui9N8pmqunzPysUGfltqsKmVzis6aF0b1KsX4xgzdD/uxQZUG8eB1FYT85J92iRpTJ0DnDBv2Wbgsqo6FrisfSxJnVdVX2xvdwHvBR4/2ogkDZNJm6SJ1P4C/bV5i08Gzm3vnwucMsyYJGklkhyY5OA994GfBa4dbVSShqm710Ilqf+mqmonQDtdyZELbbRY35CldLlPwEosp5/DuPUrWMo49pXoh7Va7jEwBby3nSN3X+AdVfXB0YYkaZhM2iRpnsX6hiylq31DVmo5/RyWmsR93IxjX4l+WKvl7rqq+hzw6FHHIWl0bB4paS25NclRAO3trhHHI0mStCSTNklrycXA6e3904GLRhiLJElST0zaJE2kJO8EPgY8PMnNSV4MbAGemuR64KntY0mSpE6zT5ukiVRVz1tk1fFDDUSSJGmVvNImSZIkSR3mlTZJkiRJnbRukZGZN63f3alRm3dsOWmgx/dKmyRJkiR1mEmbJEmSJHWYSZskSZIkdZh92tQpC7VbXm2b5UG3MZYkSZIGyaRNktRJi3U+Xw1/xJEkjSObR0qSJElSh3mlTZK0aoO4KiZJkhpeaZMkSZKkDjNpkyRJkqQOs3lkB9n5XpIGo9f6dbmj1lrHSpIGySttkiRJktRhXmnTijnwgCSNl6Xq7ZXMi+lVRkkaPK+0SZIkSVKHrepKW5ITgDcA+wBvrqotfYlqQAZ1ZWglv0xqeLwiqLnGrd6Sus5+2MNh3SWtbSu+0pZkH+CPgacDjwSel+SR/QpMkvrNekvSOLLukrSa5pGPB26oqs9V1beB84GT+xOWJA2E9ZakcWTdJa1xqaqV7Zg8Czihqn6lfXwa8ISqetm87TYCG9uHDwc+2+NTHA58ZUXBDd84xQrGO2jjGu+Dq+qIUQczSEOotybNuH2W+2mtln0cy23dxV7rrXF8T2E84x7HmMG4h2nF51yr6dOWBZbdIwOsqq3A1mUfPLmyqjasJLBhG6dYwXgHzXg7baD11qRZY5+N77NWy75Wyz0Glqy7Fqu3xvU9Hce4xzFmMO5hWk3Mq2keeTNwzJzHDwS+uIrjSdKgWW9JGkfWXdIat5qk7ZPAsUkekmR/4LnAxf0JS5IGwnpL0jiy7pLWuBU3j6yq3UleBvwtzfCzb62q6/oW2Xg1TRqnWMF4B814O2oI9dakWTOfjQWs1bKv1XJ32irrrnF9T8cx7nGMGYx7mFYc84oHIpEkSZIkDd5qmkdKkiRJkgbMpE2SJEmSOmykSVuSE5J8NskNSTYvsD5J/rBd/+kkjx1FnHPiWSreU9s4P53ko0kePYo458Sz13jnbPe4JHe188CMTC/xJplOck2S65L8w7BjnBfLUp+H+yX56ySfauN94SjibGN5a5JdSa5dZH2nvmsannGr1/pp3OrIfhq3+lZLG7dzqjamsax/xrXuGMfv/Tida82JaTDnXFU1kj+ajrT/CjwU2B/4FPDIeducCPwNzfwkTwSu6Hi8Pwkc2t5/etfjnbPd3wMfAJ7V5XiBQ4B/Bh7UPj6y4/GeCfx+e/8I4GvA/iOK96eBxwLXLrK+M981/4b6uRirem3YZZ+z3cjryBG8752pb/3r23vaqXp+XOufca07xvF7P27nWnNiGsg51yivtD0euKGqPldV3wbOB06et83JwNuq8XHgkCRHDTvQ1pLxVtVHq+q29uHHaeZRGZVeXl+AlwPvAXYNM7gF9BLvLwMXVtWNAFU1yph7ibeAg5MEOIimItk93DDbQKoub59/MV36rml4xq1e66dxqyP7adzqWy1t3M6pYHzrn3GtO8bxez9W51rfDWhA51yjTNqOBm6a8/jmdtlytxmW5cbyYposelSWjDfJ0cAzgT8bYlyL6eX1/WHg0CQzSa5K8oKhRXdPvcT7R8AjaCZA3Qa8oqruHk54y9al75qGZ9zqtX4atzqyn8atvtXSxu2cCsa3/hnXumMcv/eTdq61x4q+iyuep60PssCy+fMP9LLNsPQcS5In01QuPzXQiPaul3hfD7yqqu5qfqAYqV7i3Rf4ceB44ADgY0k+XlX/MujgFtBLvE8DrgF+Bvgh4NIk/1hVtw84tpXo0ndNwzNu9Vo/jVsd2U/jVt9qaeN2TgXjW/+Ma90xjt/7STvX2mNF38VRJm03A8fMefxAmix5udsMS0+xJPkx4M3A06vqq0OKbSG9xLsBOL+tUA4HTkyyu6reN5QIv1+vn4evVNWdwJ1JLgceDYyiMukl3hcCW6ppwHxDks8DPwJ8YjghLkuXvmsannGr1/pp3OrIfhq3+lZLG7dzKhjf+mdc645x/N5P2rnWHiv7Lo6ig17bCW9f4HPAQ/he58IfnbfNSXx/R71PdDzeBwE3AD85qjiXE++87c9htAOR9PL6PgK4rN32PsC1wKM6HO+fAme196eAW4DDR/gar2PxTrGd+a75N9TPxFjVa8Mu+7ztR1pHjuB970x961/f3tNO1fPjWv+Ma90xjt/7cTzXmhNX38+5Rnalrap2J3kZ8Lc0o8O8taquS/LSdv2f0Yy4cyLNF/abNNl0l+P9beAHgT9pf13ZXVUbOhxvZ/QSb1VtT/JB4NPA3cCbq2rB4VS7EC/wGuCcJNtovpivqqqvjCLeJO8EpoHDk9wMvBrYb06snfmuaXjGrV7rp3GrI/tp3OpbLW3czqnamMay/hnXumMcv/fjdq61x6DOudJmfJIkSZKkDhrp5NqSJEmSpL0zaZMkSZKkDjNpkyRJkqQOM2mTJEmSpA4zaZMkSZKkDjNpkyRJkqQOM2mTJEmSpA77/wGyKNb90i+HPAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1080x720 with 9 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_cluster = top_tracks[cluster_feat].drop(\"mode\",axis = 1)\n",
    "df_cluster.hist(figsize= (15,10))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.cluster import KMeans\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "\n",
    "X = np.array(df_cluster)\n",
    "scaler = StandardScaler()\n",
    "scaler.fit(X)\n",
    "X = scaler.transform(X)\n",
    "\n",
    "\n",
    "ss_dist = []\n",
    "for k in range(1,21):\n",
    "    km = KMeans(n_clusters=k,max_iter = 10000 ,random_state=13)\n",
    "    km = km.fit(X)\n",
    "    ss_dist.append(km.inertia_)\n",
    "    \n",
    "plt.plot(range(1,21), ss_dist, 'bx-')\n",
    "plt.xlabel('k')\n",
    "plt.ylabel('Sum of squared distances')\n",
    "plt.title('Elbow Method For Optimal k')\n",
    "plt.show()\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x216 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.metrics import silhouette_score\n",
    "kmeans_per_k = [KMeans(n_clusters=k, random_state=42).fit(X)\n",
    "                for k in range(1, 10)]\n",
    "silhouette_scores = [silhouette_score(X, model.labels_)\n",
    "                     for model in kmeans_per_k[1:]]\n",
    "plt.figure(figsize=(8, 3))\n",
    "sns.lineplot(x = range(2, 10), y = silhouette_scores,marker=\"o\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "n_cluster = 6\n",
    "km = KMeans(n_clusters = n_cluster, max_iter = 10000, random_state=13).fit(X)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_pred = km.predict(X)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(150,)"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_pred.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "top_tracks[\"cluster\"] = X_pred"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "                                             track_name              artist\n",
      "0                                       Time for Space         Emancipator\n",
      "3                                            Greenland         Emancipator\n",
      "5           Soon It Will Be Cold Enough to Build Fires         Emancipator\n",
      "6                                               Джадуа          Jah Khalib\n",
      "19                                          Nevergreen         Emancipator\n",
      "22   Falling Rain and Light - Moby's Seas of Light ...                Moby\n",
      "28                                      Tangerine Sour         Emancipator\n",
      "34                                        Santa Teresa  Oceanvs Orientalis\n",
      "44                                               Insan       Yousef Kekhia\n",
      "51                                       The Finishing             Stavroz\n",
      "55                    Lost Minds Office - Original Mix             Maguera\n",
      "56                              Huldra - Other Version               Gidge\n",
      "59                                          Easy Field          Stereoclip\n",
      "60                                    It's All Theatre              Satori\n",
      "64                                                Blóð     Janus Rasmussen\n",
      "65                                             Fragile           Kora (CA)\n",
      "66                                               Kylie         Kerala Dust\n",
      "67                                                 Niv                Geju\n",
      "69                  Zippelonika - Mente Orgánica Remix         JPattersson\n",
      "71                              Scheune - Original Mix       FEATHERED SUN\n",
      "75                                               Bulbo       FEATHERED SUN\n",
      "79                                            My Click       Aaron Ahrends\n",
      "87                               We Are Facing the Sun        Sascha Funke\n",
      "89                                               Solar         Viken Arman\n",
      "95                                         By the Pool       Palomo Wendel\n",
      "97                    Too Many Questions - Soble Remix               Yamil\n",
      "109                                        Part Eleven    Paul Kalkbrenner\n",
      "133                       Napauken - Jpattersson Remix              Shkoon\n",
      "134                                       Worlds Apart                 Ash\n",
      "139                                  Echo of the Woods               Giolì\n",
      "145                            Smek - Rey&Kjavik Remix                Ÿuma \n",
      "\n",
      "\n",
      "                                    track_name               artist\n",
      "7                          Пряталась в ванной      Mari Kraimbrery\n",
      "9                              A Child's Tale             Bukahara\n",
      "10                           Zapatos de Baile     Michael Zanabili\n",
      "11                                        505       Arctic Monkeys\n",
      "12                                   Goodness          Emancipator\n",
      "16                                Delmenhorst     Element Of Crime\n",
      "18                                 Coco L'Eau           Egor Kreed\n",
      "21                                 goosebumps         Travis Scott\n",
      "23                  Ochi Chernye (Очи Черные)  Mikhail Shufutinsky\n",
      "25          Новая сила киски (feat. FEARMUCH)       SHLAKOBLOCHINA\n",
      "26                           Кто тебе сказал?               Rakhim\n",
      "33                                 Borboletas          Maple Syrup\n",
      "47   Why'd You Only Call Me When You're High?       Arctic Monkeys\n",
      "49                             Double in Love          Alle Farben\n",
      "54                       Bind You to My Spell            Moderator\n",
      "62                               Words Remain            Moderator\n",
      "72                              Don't You Say    Fritz Kalkbrenner\n",
      "74                                    Way Out         Ellen Allien\n",
      "77                         Wakka Flocka Flame               Dardan\n",
      "78                          Ain't No Sunshine                Yamil\n",
      "83                     Если ты меня не любишь                MOLLY\n",
      "86                                 We Love It            Outasight\n",
      "93                       Who - Single Version         Modeselektor\n",
      "94                                Summer Wine        Alex Kapranos\n",
      "98                                 Had Enough               G-Eazy\n",
      "104                       Was du Liebe nennst                Bausa\n",
      "122                                Bella ciao          Mike Singer\n",
      "125                     Don's City of Boredom                NUGAT\n",
      "131                                      Home                Dotan\n",
      "135             Aufstehn! (feat. CeeLo Green)                Seeed\n",
      "136                              Cool Me Down             Margaret\n",
      "137               Sie Is Geladen (feat. Nura)                Seeed\n",
      "147                                 Baby Girl           Bryce Vine\n",
      "149                                  Uma Vida              Gerra G \n",
      "\n",
      "\n",
      "                               track_name         artist\n",
      "27                         Traum - Remix    KazOnDaBeat\n",
      "30                     Под одним солнцем       Endspiel\n",
      "31                                Джанго       Endspiel\n",
      "39                      Phía Sau Đôi Mắt  Anh bạn Thành\n",
      "46                               Over Me      Moglebaum\n",
      "57                              Bläulich     Apache 207\n",
      "61                                  Snub         FLOHIO\n",
      "112                        Lass Sie Gehn          Seeed\n",
      "114  Lass Das Licht An (feat. Deichkind)          Seeed\n",
      "124                           Chill Maaa         Mosh36\n",
      "132                              The End       Monolink\n",
      "140                               Navajo         Masego\n",
      "141                          Kleines Rad          Bausa \n",
      "\n",
      "\n",
      "                                             track_name         artist\n",
      "8    Como Fue (feat. Beny Moré & The Charlie Sepulv...     Jon Secada\n",
      "37                    Lily Moon - Isaac Chambers Remix      Wildlight\n",
      "121          Comets (feat. Natalia Doco) - HUGEL Remix  Freddy Verano \n",
      "\n",
      "\n",
      "                                track_name              artist\n",
      "2      Take Some Time - Emancipator Remix           Wilderado\n",
      "4    Frosty The Snowman - Remastered 2006         Bing Crosby\n",
      "17                              Self Care          Mac Miller\n",
      "20                  Wenn der Winter kommt    Element Of Crime\n",
      "24              Ты словно целая вселенная          Jah Khalib\n",
      "29           Running Nights - Jugende RMX                MVCA\n",
      "32               C'est Pas La Mer A Boire       Blank & Jones\n",
      "35                 We Might As Well Dance   Madeleine Peyroux\n",
      "38                        Galopa, Murieta       Mercedes Sosa\n",
      "40           Colour - Thousand Island Mix          Pete Josef\n",
      "41                         You Inspire Me            FM LAETI\n",
      "42                       Do I Wanna Know?      Arctic Monkeys\n",
      "43       La Cancion Mas Hermosa del Mundo      Joaquín Sabina\n",
      "50                                 Wealth        Modeselektor\n",
      "52                Hundertquadratmeterherz  Oliver Jahn & Band\n",
      "58                              Drop Dead   Holly Humberstone\n",
      "63                      Keiner hat gesagt     Herman van Veen\n",
      "70                                  Drugs               Uffie\n",
      "80                        Grüne Papageien               Maxim\n",
      "82                                 Havana           Dalliance\n",
      "85                   Villa Auf Der Klippe           Max Herre\n",
      "88                         Facing the Sun   Fritz Kalkbrenner\n",
      "91                               SBCNCSLY        Black Coffee\n",
      "92                             Grey Goose          Apache 207\n",
      "96                                Thunder             Catnapp\n",
      "102                 Welcome to Wonderland        Anson Seabra\n",
      "106                            What A Day               Seeed\n",
      "110                                 Maria         Kerala Dust\n",
      "113                        Wonderful Life         Katie Melua\n",
      "115                       Don't Be A Fool      Gregory Porter\n",
      "116                  The Shape - Acoustic      Nico de Andrea\n",
      "117                     Million Years Ago               Adele\n",
      "119                        Painting Greys          Emmit Fenn\n",
      "120                    When We Were Young               Adele\n",
      "127                          Dans La Peau                 Ash\n",
      "129                             Madrugada               Chigo\n",
      "130                     On the Road Again     Deep Dive Corp.\n",
      "138               Different Kind of Blues               IAMJJ\n",
      "142             أثبت مكانك Ethbat Makanak            Cairokee \n",
      "\n",
      "\n",
      " Empty DataFrame\n",
      "Columns: [track_name, artist]\n",
      "Index: [] \n",
      "\n"
     ]
    }
   ],
   "source": [
    "for i in range(1,n_cluster+1):\n",
    "    print(\"\\n\",top_tracks[[\"track_name\",\"artist\"]][top_tracks[\"cluster\"] == i].drop_duplicates(), \"\\n\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "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>D1</th>\n",
       "      <th>D2</th>\n",
       "      <th>label</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-3.496974</td>\n",
       "      <td>-7.713355</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.271112</td>\n",
       "      <td>-9.189069</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-1.726395</td>\n",
       "      <td>-2.530624</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-4.915655</td>\n",
       "      <td>-8.010592</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1.207951</td>\n",
       "      <td>-4.665074</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         D1        D2  label\n",
       "0 -3.496974 -7.713355      1\n",
       "1  0.271112 -9.189069      0\n",
       "2 -1.726395 -2.530624      5\n",
       "3 -4.915655 -8.010592      1\n",
       "4  1.207951 -4.665074      5"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.manifold import TSNE\n",
    "tsne = TSNE(n_components=2, perplexity=50, n_iter=5000, random_state=13)\n",
    "tsne_results = tsne.fit_transform(X)\n",
    "\n",
    "df_tsne = pd.DataFrame(tsne_results)\n",
    "df_tsne.columns = ['D1', 'D2']\n",
    "df_tsne['label'] = km.labels_\n",
    "df_tsne.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.scatterplot(data = df_tsne, x = \"D1\", y = \"D2\", hue = \"label\", style = \"label\",\n",
    "                palette = \"tab10\")\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.5963059235780717\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([0.32546198, 0.46638515, 0.59630592])"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.decomposition import PCA\n",
    "pca = PCA(n_components=3, random_state=123)\n",
    "pca_results = pca.fit_transform(X)\n",
    "print(pca.explained_variance_ratio_.sum())\n",
    "pca.explained_variance_ratio_.cumsum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "not enough variance explained for sensible visualisation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "tsne3 = TSNE(n_components=3, n_iter=5000, random_state=13, perplexity=50)\n",
    "tsne_results = tsne3.fit_transform(X)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "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>D1</th>\n",
       "      <th>D2</th>\n",
       "      <th>D3</th>\n",
       "      <th>label</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-237.591034</td>\n",
       "      <td>161.595535</td>\n",
       "      <td>346.141113</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>340.236206</td>\n",
       "      <td>-242.617966</td>\n",
       "      <td>381.628113</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>56.284706</td>\n",
       "      <td>36.985207</td>\n",
       "      <td>133.397125</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-2.818033</td>\n",
       "      <td>173.954224</td>\n",
       "      <td>379.865356</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>258.651123</td>\n",
       "      <td>-73.710220</td>\n",
       "      <td>201.420166</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           D1          D2          D3  label\n",
       "0 -237.591034  161.595535  346.141113      1\n",
       "1  340.236206 -242.617966  381.628113      0\n",
       "2   56.284706   36.985207  133.397125      5\n",
       "3   -2.818033  173.954224  379.865356      1\n",
       "4  258.651123  -73.710220  201.420166      5"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_tsne3 = pd.DataFrame(tsne_results)\n",
    "df_tsne3.columns = ['D1', 'D2', 'D3']\n",
    "df_tsne3['label'] = km.labels_\n",
    "df_tsne3.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from mpl_toolkits.mplot3d import Axes3D\n",
    "\n",
    "fig = plt.figure()\n",
    "ax = Axes3D(fig)\n",
    "\n",
    "ax.scatter(df_tsne3['D1'], df_tsne3['D2'], df_tsne3['D3'],\n",
    "           c=df_tsne3['label'], cmap='tab10')\n",
    "\n",
    "ax.set_xlabel('D1')\n",
    "ax.set_ylabel('D2')\n",
    "ax.set_zlabel('D3')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "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>D1</th>\n",
       "      <th>D2</th>\n",
       "      <th>label</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.373538</td>\n",
       "      <td>0.308508</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.576781</td>\n",
       "      <td>-0.121932</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-0.208547</td>\n",
       "      <td>0.048933</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.174499</td>\n",
       "      <td>0.341598</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.022695</td>\n",
       "      <td>-0.319739</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         D1        D2  label\n",
       "0  0.373538  0.308508      1\n",
       "1  0.576781 -0.121932      0\n",
       "2 -0.208547  0.048933      5\n",
       "3  0.174499  0.341598      1\n",
       "4  0.022695 -0.319739      5"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.decomposition import KernelPCA\n",
    "rbf_pca = KernelPCA(n_components=2, kernel = \"rbf\", gamma = 0.04)\n",
    "rbf_pca_results = rbf_pca.fit_transform(X)\n",
    "\n",
    "df_rbf_pca = pd.DataFrame(rbf_pca_results)\n",
    "df_rbf_pca.columns = ['D1', 'D2']\n",
    "df_rbf_pca['label'] = km.labels_\n",
    "df_rbf_pca.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.scatterplot(data = df_rbf_pca, x = \"D1\", y = \"D2\", hue = \"label\", style = \"label\",\n",
    "                palette = \"tab10\")\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "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>D1</th>\n",
       "      <th>D2</th>\n",
       "      <th>label</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-0.098264</td>\n",
       "      <td>0.065934</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-0.085719</td>\n",
       "      <td>-0.118785</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.117471</td>\n",
       "      <td>0.035686</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-0.086505</td>\n",
       "      <td>0.083059</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-0.022563</td>\n",
       "      <td>0.010626</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         D1        D2  label\n",
       "0 -0.098264  0.065934      1\n",
       "1 -0.085719 -0.118785      0\n",
       "2  0.117471  0.035686      5\n",
       "3 -0.086505  0.083059      1\n",
       "4 -0.022563  0.010626      5"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.manifold import LocallyLinearEmbedding\n",
    "lle = LocallyLinearEmbedding(n_components=2, n_neighbors=5)\n",
    "lle_results = lle.fit_transform(X)\n",
    "\n",
    "df_lle = pd.DataFrame(lle_results)\n",
    "df_lle.columns = ['D1', 'D2']\n",
    "df_lle['label'] = km.labels_\n",
    "df_lle.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.scatterplot(data = df_lle, x = \"D1\", y = \"D2\", hue = \"label\", style = \"label\",\n",
    "                palette = \"tab10\")\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "that did not work well.\n",
    "t-sne seems to be a good solution for visualisation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "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>danceability</th>\n",
       "      <th>energy</th>\n",
       "      <th>key</th>\n",
       "      <th>loudness</th>\n",
       "      <th>speechiness</th>\n",
       "      <th>acousticness</th>\n",
       "      <th>instrumentalness</th>\n",
       "      <th>liveness</th>\n",
       "      <th>valence</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.610</td>\n",
       "      <td>0.313</td>\n",
       "      <td>5</td>\n",
       "      <td>-13.138</td>\n",
       "      <td>0.0323</td>\n",
       "      <td>0.3900</td>\n",
       "      <td>0.840000</td>\n",
       "      <td>0.0899</td>\n",
       "      <td>0.0870</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.330</td>\n",
       "      <td>0.267</td>\n",
       "      <td>2</td>\n",
       "      <td>-19.607</td>\n",
       "      <td>0.0511</td>\n",
       "      <td>0.8560</td>\n",
       "      <td>0.782000</td>\n",
       "      <td>0.1270</td>\n",
       "      <td>0.2350</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.545</td>\n",
       "      <td>0.596</td>\n",
       "      <td>5</td>\n",
       "      <td>-8.216</td>\n",
       "      <td>0.0289</td>\n",
       "      <td>0.0249</td>\n",
       "      <td>0.025200</td>\n",
       "      <td>0.2190</td>\n",
       "      <td>0.1820</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.593</td>\n",
       "      <td>0.398</td>\n",
       "      <td>4</td>\n",
       "      <td>-13.301</td>\n",
       "      <td>0.0295</td>\n",
       "      <td>0.0273</td>\n",
       "      <td>0.827000</td>\n",
       "      <td>0.2310</td>\n",
       "      <td>0.0989</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.519</td>\n",
       "      <td>0.368</td>\n",
       "      <td>7</td>\n",
       "      <td>-11.622</td>\n",
       "      <td>0.0796</td>\n",
       "      <td>0.6170</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0859</td>\n",
       "      <td>0.8540</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>145</th>\n",
       "      <td>0.892</td>\n",
       "      <td>0.281</td>\n",
       "      <td>2</td>\n",
       "      <td>-13.880</td>\n",
       "      <td>0.0435</td>\n",
       "      <td>0.8560</td>\n",
       "      <td>0.878000</td>\n",
       "      <td>0.1950</td>\n",
       "      <td>0.0433</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>0.778</td>\n",
       "      <td>0.375</td>\n",
       "      <td>1</td>\n",
       "      <td>-13.180</td>\n",
       "      <td>0.0484</td>\n",
       "      <td>0.5460</td>\n",
       "      <td>0.785000</td>\n",
       "      <td>0.0959</td>\n",
       "      <td>0.3330</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>147</th>\n",
       "      <td>0.860</td>\n",
       "      <td>0.592</td>\n",
       "      <td>2</td>\n",
       "      <td>-8.606</td>\n",
       "      <td>0.0861</td>\n",
       "      <td>0.1660</td>\n",
       "      <td>0.000609</td>\n",
       "      <td>0.2760</td>\n",
       "      <td>0.6210</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>0.638</td>\n",
       "      <td>0.293</td>\n",
       "      <td>0</td>\n",
       "      <td>-15.712</td>\n",
       "      <td>0.0337</td>\n",
       "      <td>0.5550</td>\n",
       "      <td>0.505000</td>\n",
       "      <td>0.1110</td>\n",
       "      <td>0.2260</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149</th>\n",
       "      <td>0.757</td>\n",
       "      <td>0.829</td>\n",
       "      <td>2</td>\n",
       "      <td>-7.263</td>\n",
       "      <td>0.0454</td>\n",
       "      <td>0.1860</td>\n",
       "      <td>0.631000</td>\n",
       "      <td>0.1040</td>\n",
       "      <td>0.6140</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>150 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     danceability  energy  key  loudness  speechiness  acousticness  \\\n",
       "0           0.610   0.313    5   -13.138       0.0323        0.3900   \n",
       "1           0.330   0.267    2   -19.607       0.0511        0.8560   \n",
       "2           0.545   0.596    5    -8.216       0.0289        0.0249   \n",
       "3           0.593   0.398    4   -13.301       0.0295        0.0273   \n",
       "4           0.519   0.368    7   -11.622       0.0796        0.6170   \n",
       "..            ...     ...  ...       ...          ...           ...   \n",
       "145         0.892   0.281    2   -13.880       0.0435        0.8560   \n",
       "146         0.778   0.375    1   -13.180       0.0484        0.5460   \n",
       "147         0.860   0.592    2    -8.606       0.0861        0.1660   \n",
       "148         0.638   0.293    0   -15.712       0.0337        0.5550   \n",
       "149         0.757   0.829    2    -7.263       0.0454        0.1860   \n",
       "\n",
       "     instrumentalness  liveness  valence  \n",
       "0            0.840000    0.0899   0.0870  \n",
       "1            0.782000    0.1270   0.2350  \n",
       "2            0.025200    0.2190   0.1820  \n",
       "3            0.827000    0.2310   0.0989  \n",
       "4            0.000000    0.0859   0.8540  \n",
       "..                ...       ...      ...  \n",
       "145          0.878000    0.1950   0.0433  \n",
       "146          0.785000    0.0959   0.3330  \n",
       "147          0.000609    0.2760   0.6210  \n",
       "148          0.505000    0.1110   0.2260  \n",
       "149          0.631000    0.1040   0.6140  \n",
       "\n",
       "[150 rows x 9 columns]"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#average song feature per cluster (what are our clusters representing?)\n",
    "df_cluster"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_cluster[\"cluster\"] = X_pred\n",
    "df_cluster.drop([\"key\",\"loudness\"],axis = 1,inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "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>cluster</th>\n",
       "      <th>danceability</th>\n",
       "      <th>energy</th>\n",
       "      <th>speechiness</th>\n",
       "      <th>acousticness</th>\n",
       "      <th>instrumentalness</th>\n",
       "      <th>liveness</th>\n",
       "      <th>valence</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>0.438100</td>\n",
       "      <td>0.218525</td>\n",
       "      <td>0.042895</td>\n",
       "      <td>0.857450</td>\n",
       "      <td>0.345440</td>\n",
       "      <td>0.120925</td>\n",
       "      <td>0.296975</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>0.732784</td>\n",
       "      <td>0.451097</td>\n",
       "      <td>0.047668</td>\n",
       "      <td>0.399987</td>\n",
       "      <td>0.826486</td>\n",
       "      <td>0.134781</td>\n",
       "      <td>0.213470</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>0.718250</td>\n",
       "      <td>0.683389</td>\n",
       "      <td>0.065694</td>\n",
       "      <td>0.153585</td>\n",
       "      <td>0.186484</td>\n",
       "      <td>0.139478</td>\n",
       "      <td>0.598111</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>0.741538</td>\n",
       "      <td>0.549769</td>\n",
       "      <td>0.311385</td>\n",
       "      <td>0.262523</td>\n",
       "      <td>0.023684</td>\n",
       "      <td>0.128723</td>\n",
       "      <td>0.444769</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>0.708000</td>\n",
       "      <td>0.494667</td>\n",
       "      <td>0.060333</td>\n",
       "      <td>0.301333</td>\n",
       "      <td>0.012830</td>\n",
       "      <td>0.655000</td>\n",
       "      <td>0.372333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5</td>\n",
       "      <td>0.632756</td>\n",
       "      <td>0.445512</td>\n",
       "      <td>0.068941</td>\n",
       "      <td>0.438829</td>\n",
       "      <td>0.025081</td>\n",
       "      <td>0.126117</td>\n",
       "      <td>0.290202</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   cluster  danceability    energy  speechiness  acousticness  \\\n",
       "0        0      0.438100  0.218525     0.042895      0.857450   \n",
       "1        1      0.732784  0.451097     0.047668      0.399987   \n",
       "2        2      0.718250  0.683389     0.065694      0.153585   \n",
       "3        3      0.741538  0.549769     0.311385      0.262523   \n",
       "4        4      0.708000  0.494667     0.060333      0.301333   \n",
       "5        5      0.632756  0.445512     0.068941      0.438829   \n",
       "\n",
       "   instrumentalness  liveness   valence  \n",
       "0          0.345440  0.120925  0.296975  \n",
       "1          0.826486  0.134781  0.213470  \n",
       "2          0.186484  0.139478  0.598111  \n",
       "3          0.023684  0.128723  0.444769  \n",
       "4          0.012830  0.655000  0.372333  \n",
       "5          0.025081  0.126117  0.290202  "
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_radar = df_cluster.groupby(\"cluster\").mean().reset_index()\n",
    "df_radar"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "# https://python-graph-gallery.com/392-use-faceting-for-radar-chart/\n",
    "from math import pi, ceil\n",
    "\n",
    "def make_radar(row, title, color, dframe, num_clusters):\n",
    "    # number of variable\n",
    "    categories=list(dframe)[1:]\n",
    "    N = len(categories)\n",
    "    \n",
    "    # What will be the angle of each axis in the plot? (we divide the plot / number of variable)\n",
    "    angles = [n / float(N) * 2 * pi for n in range(N)]\n",
    "    angles += angles[:1]\n",
    "    # Initialise the radar plot\n",
    "    ax = plt.subplot(2,ceil(num_clusters/2),row+1, polar=True)\n",
    "    \n",
    "    # If you want the first axis to be on top:\n",
    "    ax.set_theta_offset(pi / 2)\n",
    "    ax.set_theta_direction(-1)\n",
    "\n",
    "    # Draw one axe per variable + add labels labels yet\n",
    "    plt.xticks(angles[:-1], categories, color='grey', size=12)\n",
    "\n",
    "    # Draw ylabels\n",
    "    ax.set_rlabel_position(0)\n",
    "    plt.yticks([0.2,0.4,0.6,0.8], [\"0.2\",\"0.4\",\"0.6\",\"0.8\"], color=\"grey\", size=8)\n",
    "    plt.ylim(0,1)\n",
    "\n",
    "    # Ind1\n",
    "    values=dframe.loc[row].drop('cluster').values.flatten().tolist()\n",
    "    values += values[:1]\n",
    "    ax.plot(angles, values, color=color, linewidth=2, linestyle='solid')\n",
    "    ax.fill(angles, values, color=color, alpha=0.4)\n",
    "\n",
    "    # Add a title\n",
    "    plt.title(title, size=16, color=color, y=1.06)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x720 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "dark"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (20,10))\n",
    "my_palette = plt.cm.get_cmap(\"tab10\", len(df_radar.index))\n",
    "title_list = [\"acoustic\", \"instrumental dance\",\"dance\",\"dance again\",\"live dance\",\"acoustic chill\"]\n",
    "\n",
    "for row in range(0, len(df_radar.index)):\n",
    "    make_radar(row=row, title= title_list[row], \n",
    "               color=my_palette(row), dframe=df_radar, num_clusters=len(df_radar.index))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}