Exploration_Clustering_E.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 sister. 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[2]\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": {
      "text/html": [
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       "\n",
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       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>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>Chase Atlantic</td>\n",
       "      <td>7cYEt1pqMgXJdq00hAwVpT</td>\n",
       "      <td>electropop,modern rock,pop,rock</td>\n",
       "      <td>72</td>\n",
       "      <td>spotify:artist:7cYEt1pqMgXJdq00hAwVpT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Kontra K</td>\n",
       "      <td>4lDiJcOJ2GLCK6p9q5BgfK</td>\n",
       "      <td>christlicher rap,german hip hop</td>\n",
       "      <td>74</td>\n",
       "      <td>spotify:artist:4lDiJcOJ2GLCK6p9q5BgfK</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Sabrina Carpenter</td>\n",
       "      <td>74KM79TiuVKeVCqs8QtB0B</td>\n",
       "      <td>dance pop,electropop,pop,pop dance,post-teen p...</td>\n",
       "      <td>76</td>\n",
       "      <td>spotify:artist:74KM79TiuVKeVCqs8QtB0B</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Marshmello</td>\n",
       "      <td>64KEffDW9EtZ1y2vBYgq8T</td>\n",
       "      <td>brostep,edm,pop,pop dance,progressive electro ...</td>\n",
       "      <td>88</td>\n",
       "      <td>spotify:artist:64KEffDW9EtZ1y2vBYgq8T</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>SXTN</td>\n",
       "      <td>0tMFcqLXhtm1Gep20iuIR3</td>\n",
       "      <td>deep german hip hop,frauenrap,german hip hop</td>\n",
       "      <td>60</td>\n",
       "      <td>spotify:artist:0tMFcqLXhtm1Gep20iuIR3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Ariana Grande</td>\n",
       "      <td>66CXWjxzNUsdJxJ2JdwvnR</td>\n",
       "      <td>pop,post-teen pop</td>\n",
       "      <td>98</td>\n",
       "      <td>spotify:artist:66CXWjxzNUsdJxJ2JdwvnR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Juice WRLD</td>\n",
       "      <td>4MCBfE4596Uoi2O4DtmEMz</td>\n",
       "      <td>chicago rap,melodic rap</td>\n",
       "      <td>97</td>\n",
       "      <td>spotify:artist:4MCBfE4596Uoi2O4DtmEMz</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Ufo361</td>\n",
       "      <td>5pVRwX5ZQR7hfJ18w8ZYkl</td>\n",
       "      <td>german cloud rap,german hip hop</td>\n",
       "      <td>78</td>\n",
       "      <td>spotify:artist:5pVRwX5ZQR7hfJ18w8ZYkl</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Pop Smoke</td>\n",
       "      <td>0eDvMgVFoNV3TpwtrVCoTj</td>\n",
       "      <td>brooklyn drill</td>\n",
       "      <td>93</td>\n",
       "      <td>spotify:artist:0eDvMgVFoNV3TpwtrVCoTj</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>BLACKPINK</td>\n",
       "      <td>41MozSoPIsD1dJM0CLPjZF</td>\n",
       "      <td>k-pop,k-pop girl group</td>\n",
       "      <td>89</td>\n",
       "      <td>spotify:artist:41MozSoPIsD1dJM0CLPjZF</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Jamule</td>\n",
       "      <td>4sVieJlKgpZ2k9ESNS5IdN</td>\n",
       "      <td>german hip hop,german trap</td>\n",
       "      <td>71</td>\n",
       "      <td>spotify:artist:4sVieJlKgpZ2k9ESNS5IdN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>CÉLINE</td>\n",
       "      <td>5ZYOlPpI9FZu2uIPkTB0UA</td>\n",
       "      <td>frauenrap,german hip hop,german pop</td>\n",
       "      <td>66</td>\n",
       "      <td>spotify:artist:5ZYOlPpI9FZu2uIPkTB0UA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>KC Rebell</td>\n",
       "      <td>5p7mWeX4RlvqBCxylfiXdE</td>\n",
       "      <td>german drill,german hip hop</td>\n",
       "      <td>74</td>\n",
       "      <td>spotify:artist:5p7mWeX4RlvqBCxylfiXdE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Juju</td>\n",
       "      <td>4sg4no0TXdsrM1s4SVUwNF</td>\n",
       "      <td>frauenrap,german hip hop,german pop</td>\n",
       "      <td>68</td>\n",
       "      <td>spotify:artist:4sg4no0TXdsrM1s4SVUwNF</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Dua Lipa</td>\n",
       "      <td>6M2wZ9GZgrQXHCFfjv46we</td>\n",
       "      <td>dance pop,pop,pop dance,uk pop</td>\n",
       "      <td>93</td>\n",
       "      <td>spotify:artist:6M2wZ9GZgrQXHCFfjv46we</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Justin Bieber</td>\n",
       "      <td>1uNFoZAHBGtllmzznpCI3s</td>\n",
       "      <td>canadian pop,pop,post-teen pop</td>\n",
       "      <td>96</td>\n",
       "      <td>spotify:artist:1uNFoZAHBGtllmzznpCI3s</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Harry Styles</td>\n",
       "      <td>6KImCVD70vtIoJWnq6nGn3</td>\n",
       "      <td>pop,post-teen pop</td>\n",
       "      <td>90</td>\n",
       "      <td>spotify:artist:6KImCVD70vtIoJWnq6nGn3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Apache 207</td>\n",
       "      <td>1qQLhymHXFPtP5U8KNKsm6</td>\n",
       "      <td>german hip hop</td>\n",
       "      <td>75</td>\n",
       "      <td>spotify:artist:1qQLhymHXFPtP5U8KNKsm6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>iann dior</td>\n",
       "      <td>6ASri4ePR7RlsvIQgWPJpS</td>\n",
       "      <td>melodic rap,pop rap</td>\n",
       "      <td>88</td>\n",
       "      <td>spotify:artist:6ASri4ePR7RlsvIQgWPJpS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Loredana</td>\n",
       "      <td>2Im8m4STDBosjfmb5hmP80</td>\n",
       "      <td>frauenrap,german hip hop,kosovan pop,romanian pop</td>\n",
       "      <td>74</td>\n",
       "      <td>spotify:artist:2Im8m4STDBosjfmb5hmP80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Nura</td>\n",
       "      <td>3gkbRDj7pkIylWVBpRfrQf</td>\n",
       "      <td>frauenrap,german hip hop,german pop</td>\n",
       "      <td>55</td>\n",
       "      <td>spotify:artist:3gkbRDj7pkIylWVBpRfrQf</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Bring Me The Horizon</td>\n",
       "      <td>1Ffb6ejR6Fe5IamqA5oRUF</td>\n",
       "      <td>melodic metalcore,metalcore,rock,uk metalcore</td>\n",
       "      <td>81</td>\n",
       "      <td>spotify:artist:1Ffb6ejR6Fe5IamqA5oRUF</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Sam Smith</td>\n",
       "      <td>2wY79sveU1sp5g7SokKOiI</td>\n",
       "      <td>dance pop,pop,post-teen pop,uk pop</td>\n",
       "      <td>89</td>\n",
       "      <td>spotify:artist:2wY79sveU1sp5g7SokKOiI</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Doja Cat</td>\n",
       "      <td>5cj0lLjcoR7YOSnhnX0Po5</td>\n",
       "      <td>dance pop,pop</td>\n",
       "      <td>86</td>\n",
       "      <td>spotify:artist:5cj0lLjcoR7YOSnhnX0Po5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>blackbear</td>\n",
       "      <td>2cFrymmkijnjDg9SS92EPM</td>\n",
       "      <td>electropop,pop,pop rap</td>\n",
       "      <td>87</td>\n",
       "      <td>spotify:artist:2cFrymmkijnjDg9SS92EPM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Mahogany Lox</td>\n",
       "      <td>1wG6KrT3zgutFeiCddBivH</td>\n",
       "      <td>teen pop</td>\n",
       "      <td>50</td>\n",
       "      <td>spotify:artist:1wG6KrT3zgutFeiCddBivH</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Madison Beer</td>\n",
       "      <td>2kRfqPViCqYdSGhYSM9R0Q</td>\n",
       "      <td>dance pop,electropop,pop,pop dance,post-teen pop</td>\n",
       "      <td>81</td>\n",
       "      <td>spotify:artist:2kRfqPViCqYdSGhYSM9R0Q</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Selena Gomez</td>\n",
       "      <td>0C8ZW7ezQVs4URX5aX7Kqx</td>\n",
       "      <td>dance pop,pop,pop dance,post-teen pop</td>\n",
       "      <td>86</td>\n",
       "      <td>spotify:artist:0C8ZW7ezQVs4URX5aX7Kqx</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Ali Gatie</td>\n",
       "      <td>4rTv3Ejc7hKMtmoBOK1B4T</td>\n",
       "      <td>canadian hip hop,pop</td>\n",
       "      <td>78</td>\n",
       "      <td>spotify:artist:4rTv3Ejc7hKMtmoBOK1B4T</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Twenty One Pilots</td>\n",
       "      <td>3YQKmKGau1PzlVlkL1iodx</td>\n",
       "      <td>modern rock,rock</td>\n",
       "      <td>84</td>\n",
       "      <td>spotify:artist:3YQKmKGau1PzlVlkL1iodx</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>Lewis Capaldi</td>\n",
       "      <td>4GNC7GD6oZMSxPGyXy4MNB</td>\n",
       "      <td>pop,uk pop</td>\n",
       "      <td>86</td>\n",
       "      <td>spotify:artist:4GNC7GD6oZMSxPGyXy4MNB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>Samra</td>\n",
       "      <td>6h1s4i4XKIYv4ErDelLDN0</td>\n",
       "      <td>german hip hop</td>\n",
       "      <td>79</td>\n",
       "      <td>spotify:artist:6h1s4i4XKIYv4ErDelLDN0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>Post Malone</td>\n",
       "      <td>246dkjvS1zLTtiykXe5h60</td>\n",
       "      <td>dfw rap,melodic rap,rap</td>\n",
       "      <td>92</td>\n",
       "      <td>spotify:artist:246dkjvS1zLTtiykXe5h60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>Jack &amp; Jack</td>\n",
       "      <td>1INuLZXjjVbcJRyWvD1iSq</td>\n",
       "      <td>dance pop,pop,post-teen pop,social media pop,t...</td>\n",
       "      <td>67</td>\n",
       "      <td>spotify:artist:1INuLZXjjVbcJRyWvD1iSq</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>Tobu</td>\n",
       "      <td>1feoGrmmD8QmNqtK2Gdwy8</td>\n",
       "      <td>gaming edm</td>\n",
       "      <td>59</td>\n",
       "      <td>spotify:artist:1feoGrmmD8QmNqtK2Gdwy8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>Taylor Swift</td>\n",
       "      <td>06HL4z0CvFAxyc27GXpf02</td>\n",
       "      <td>pop</td>\n",
       "      <td>98</td>\n",
       "      <td>spotify:artist:06HL4z0CvFAxyc27GXpf02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>Katja Krasavice</td>\n",
       "      <td>0lFLP59V4TY3XgnrkFIwxK</td>\n",
       "      <td>frauenrap</td>\n",
       "      <td>63</td>\n",
       "      <td>spotify:artist:0lFLP59V4TY3XgnrkFIwxK</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>Khalid</td>\n",
       "      <td>6LuN9FCkKOj5PcnpouEgny</td>\n",
       "      <td>alternative r&amp;b,pop</td>\n",
       "      <td>90</td>\n",
       "      <td>spotify:artist:6LuN9FCkKOj5PcnpouEgny</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>The Weeknd</td>\n",
       "      <td>1Xyo4u8uXC1ZmMpatF05PJ</td>\n",
       "      <td>canadian contemporary r&amp;b,canadian pop,pop</td>\n",
       "      <td>94</td>\n",
       "      <td>spotify:artist:1Xyo4u8uXC1ZmMpatF05PJ</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>Halsey</td>\n",
       "      <td>26VFTg2z8YR0cCuwLzESi2</td>\n",
       "      <td>dance pop,electropop,etherpop,indie poptimism,...</td>\n",
       "      <td>88</td>\n",
       "      <td>spotify:artist:26VFTg2z8YR0cCuwLzESi2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>BTS</td>\n",
       "      <td>3Nrfpe0tUJi4K4DXYWgMUX</td>\n",
       "      <td>k-pop,k-pop boy group</td>\n",
       "      <td>97</td>\n",
       "      <td>spotify:artist:3Nrfpe0tUJi4K4DXYWgMUX</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>Lady Gaga</td>\n",
       "      <td>1HY2Jd0NmPuamShAr6KMms</td>\n",
       "      <td>dance pop,pop,pop dance</td>\n",
       "      <td>88</td>\n",
       "      <td>spotify:artist:1HY2Jd0NmPuamShAr6KMms</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>Lil Tecca</td>\n",
       "      <td>4Ga1P7PMIsmqEZqhYZQgDo</td>\n",
       "      <td>melodic rap,rap,trap</td>\n",
       "      <td>81</td>\n",
       "      <td>spotify:artist:4Ga1P7PMIsmqEZqhYZQgDo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>DaBaby</td>\n",
       "      <td>4r63FhuTkUYltbVAg5TQnk</td>\n",
       "      <td>north carolina hip hop,rap</td>\n",
       "      <td>93</td>\n",
       "      <td>spotify:artist:4r63FhuTkUYltbVAg5TQnk</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>Billie Eilish</td>\n",
       "      <td>6qqNVTkY8uBg9cP3Jd7DAH</td>\n",
       "      <td>electropop,pop</td>\n",
       "      <td>92</td>\n",
       "      <td>spotify:artist:6qqNVTkY8uBg9cP3Jd7DAH</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>Miley Cyrus</td>\n",
       "      <td>5YGY8feqx7naU7z4HrwZM6</td>\n",
       "      <td>dance pop,pop,pop dance,post-teen pop</td>\n",
       "      <td>91</td>\n",
       "      <td>spotify:artist:5YGY8feqx7naU7z4HrwZM6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>The Chainsmokers</td>\n",
       "      <td>69GGBxA162lTqCwzJG5jLp</td>\n",
       "      <td>dance pop,edm,electropop,pop,pop dance,tropica...</td>\n",
       "      <td>84</td>\n",
       "      <td>spotify:artist:69GGBxA162lTqCwzJG5jLp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>Tones And I</td>\n",
       "      <td>2NjfBq1NflQcKSeiDooVjY</td>\n",
       "      <td>australian pop</td>\n",
       "      <td>81</td>\n",
       "      <td>spotify:artist:2NjfBq1NflQcKSeiDooVjY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>Drake</td>\n",
       "      <td>3TVXtAsR1Inumwj472S9r4</td>\n",
       "      <td>canadian hip hop,canadian pop,hip hop,pop rap,...</td>\n",
       "      <td>97</td>\n",
       "      <td>spotify:artist:3TVXtAsR1Inumwj472S9r4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>Katy Perry</td>\n",
       "      <td>6jJ0s89eD6GaHleKKya26X</td>\n",
       "      <td>dance pop,pop,pop dance,post-teen pop</td>\n",
       "      <td>86</td>\n",
       "      <td>spotify:artist:6jJ0s89eD6GaHleKKya26X</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>Austin Mahone</td>\n",
       "      <td>04abdnqPQe2N4fjztDea6z</td>\n",
       "      <td>dance pop,pop,post-teen pop,viral pop</td>\n",
       "      <td>64</td>\n",
       "      <td>spotify:artist:04abdnqPQe2N4fjztDea6z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>Alec Benjamin</td>\n",
       "      <td>5IH6FPUwQTxPSXurCrcIov</td>\n",
       "      <td>electropop,pop</td>\n",
       "      <td>79</td>\n",
       "      <td>spotify:artist:5IH6FPUwQTxPSXurCrcIov</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>24kGoldn</td>\n",
       "      <td>6fWVd57NKTalqvmjRd2t8Z</td>\n",
       "      <td>cali rap</td>\n",
       "      <td>88</td>\n",
       "      <td>spotify:artist:6fWVd57NKTalqvmjRd2t8Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>Riverdale Cast</td>\n",
       "      <td>3famqI9bxiwLcAjRq3HuYl</td>\n",
       "      <td>post-teen pop,social media pop</td>\n",
       "      <td>60</td>\n",
       "      <td>spotify:artist:3famqI9bxiwLcAjRq3HuYl</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>Camila Cabello</td>\n",
       "      <td>4nDoRrQiYLoBzwC5BhVJzF</td>\n",
       "      <td>dance pop,electropop,pop,pop dance,post-teen pop</td>\n",
       "      <td>85</td>\n",
       "      <td>spotify:artist:4nDoRrQiYLoBzwC5BhVJzF</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    name                      id  \\\n",
       "0         Chase Atlantic  7cYEt1pqMgXJdq00hAwVpT   \n",
       "1               Kontra K  4lDiJcOJ2GLCK6p9q5BgfK   \n",
       "2      Sabrina Carpenter  74KM79TiuVKeVCqs8QtB0B   \n",
       "3             Marshmello  64KEffDW9EtZ1y2vBYgq8T   \n",
       "4                   SXTN  0tMFcqLXhtm1Gep20iuIR3   \n",
       "5          Ariana Grande  66CXWjxzNUsdJxJ2JdwvnR   \n",
       "6             Juice WRLD  4MCBfE4596Uoi2O4DtmEMz   \n",
       "7                 Ufo361  5pVRwX5ZQR7hfJ18w8ZYkl   \n",
       "8              Pop Smoke  0eDvMgVFoNV3TpwtrVCoTj   \n",
       "9              BLACKPINK  41MozSoPIsD1dJM0CLPjZF   \n",
       "10                Jamule  4sVieJlKgpZ2k9ESNS5IdN   \n",
       "11                CÉLINE  5ZYOlPpI9FZu2uIPkTB0UA   \n",
       "12             KC Rebell  5p7mWeX4RlvqBCxylfiXdE   \n",
       "13                  Juju  4sg4no0TXdsrM1s4SVUwNF   \n",
       "14              Dua Lipa  6M2wZ9GZgrQXHCFfjv46we   \n",
       "15         Justin Bieber  1uNFoZAHBGtllmzznpCI3s   \n",
       "16          Harry Styles  6KImCVD70vtIoJWnq6nGn3   \n",
       "17            Apache 207  1qQLhymHXFPtP5U8KNKsm6   \n",
       "18             iann dior  6ASri4ePR7RlsvIQgWPJpS   \n",
       "19              Loredana  2Im8m4STDBosjfmb5hmP80   \n",
       "20                  Nura  3gkbRDj7pkIylWVBpRfrQf   \n",
       "21  Bring Me The Horizon  1Ffb6ejR6Fe5IamqA5oRUF   \n",
       "22             Sam Smith  2wY79sveU1sp5g7SokKOiI   \n",
       "23              Doja Cat  5cj0lLjcoR7YOSnhnX0Po5   \n",
       "24             blackbear  2cFrymmkijnjDg9SS92EPM   \n",
       "25          Mahogany Lox  1wG6KrT3zgutFeiCddBivH   \n",
       "26          Madison Beer  2kRfqPViCqYdSGhYSM9R0Q   \n",
       "27          Selena Gomez  0C8ZW7ezQVs4URX5aX7Kqx   \n",
       "28             Ali Gatie  4rTv3Ejc7hKMtmoBOK1B4T   \n",
       "29     Twenty One Pilots  3YQKmKGau1PzlVlkL1iodx   \n",
       "30         Lewis Capaldi  4GNC7GD6oZMSxPGyXy4MNB   \n",
       "31                 Samra  6h1s4i4XKIYv4ErDelLDN0   \n",
       "32           Post Malone  246dkjvS1zLTtiykXe5h60   \n",
       "33           Jack & Jack  1INuLZXjjVbcJRyWvD1iSq   \n",
       "34                  Tobu  1feoGrmmD8QmNqtK2Gdwy8   \n",
       "35          Taylor Swift  06HL4z0CvFAxyc27GXpf02   \n",
       "36       Katja Krasavice  0lFLP59V4TY3XgnrkFIwxK   \n",
       "37                Khalid  6LuN9FCkKOj5PcnpouEgny   \n",
       "38            The Weeknd  1Xyo4u8uXC1ZmMpatF05PJ   \n",
       "39                Halsey  26VFTg2z8YR0cCuwLzESi2   \n",
       "40                   BTS  3Nrfpe0tUJi4K4DXYWgMUX   \n",
       "41             Lady Gaga  1HY2Jd0NmPuamShAr6KMms   \n",
       "42             Lil Tecca  4Ga1P7PMIsmqEZqhYZQgDo   \n",
       "43                DaBaby  4r63FhuTkUYltbVAg5TQnk   \n",
       "44         Billie Eilish  6qqNVTkY8uBg9cP3Jd7DAH   \n",
       "45           Miley Cyrus  5YGY8feqx7naU7z4HrwZM6   \n",
       "46      The Chainsmokers  69GGBxA162lTqCwzJG5jLp   \n",
       "47           Tones And I  2NjfBq1NflQcKSeiDooVjY   \n",
       "48                 Drake  3TVXtAsR1Inumwj472S9r4   \n",
       "49            Katy Perry  6jJ0s89eD6GaHleKKya26X   \n",
       "50         Austin Mahone  04abdnqPQe2N4fjztDea6z   \n",
       "51         Alec Benjamin  5IH6FPUwQTxPSXurCrcIov   \n",
       "52              24kGoldn  6fWVd57NKTalqvmjRd2t8Z   \n",
       "53        Riverdale Cast  3famqI9bxiwLcAjRq3HuYl   \n",
       "54        Camila Cabello  4nDoRrQiYLoBzwC5BhVJzF   \n",
       "\n",
       "                                               genres  popularity  \\\n",
       "0                     electropop,modern rock,pop,rock          72   \n",
       "1                     christlicher rap,german hip hop          74   \n",
       "2   dance pop,electropop,pop,pop dance,post-teen p...          76   \n",
       "3   brostep,edm,pop,pop dance,progressive electro ...          88   \n",
       "4        deep german hip hop,frauenrap,german hip hop          60   \n",
       "5                                   pop,post-teen pop          98   \n",
       "6                             chicago rap,melodic rap          97   \n",
       "7                     german cloud rap,german hip hop          78   \n",
       "8                                      brooklyn drill          93   \n",
       "9                              k-pop,k-pop girl group          89   \n",
       "10                         german hip hop,german trap          71   \n",
       "11                frauenrap,german hip hop,german pop          66   \n",
       "12                        german drill,german hip hop          74   \n",
       "13                frauenrap,german hip hop,german pop          68   \n",
       "14                     dance pop,pop,pop dance,uk pop          93   \n",
       "15                     canadian pop,pop,post-teen pop          96   \n",
       "16                                  pop,post-teen pop          90   \n",
       "17                                     german hip hop          75   \n",
       "18                                melodic rap,pop rap          88   \n",
       "19  frauenrap,german hip hop,kosovan pop,romanian pop          74   \n",
       "20                frauenrap,german hip hop,german pop          55   \n",
       "21      melodic metalcore,metalcore,rock,uk metalcore          81   \n",
       "22                 dance pop,pop,post-teen pop,uk pop          89   \n",
       "23                                      dance pop,pop          86   \n",
       "24                             electropop,pop,pop rap          87   \n",
       "25                                           teen pop          50   \n",
       "26   dance pop,electropop,pop,pop dance,post-teen pop          81   \n",
       "27              dance pop,pop,pop dance,post-teen pop          86   \n",
       "28                               canadian hip hop,pop          78   \n",
       "29                                   modern rock,rock          84   \n",
       "30                                         pop,uk pop          86   \n",
       "31                                     german hip hop          79   \n",
       "32                            dfw rap,melodic rap,rap          92   \n",
       "33  dance pop,pop,post-teen pop,social media pop,t...          67   \n",
       "34                                         gaming edm          59   \n",
       "35                                                pop          98   \n",
       "36                                          frauenrap          63   \n",
       "37                                alternative r&b,pop          90   \n",
       "38         canadian contemporary r&b,canadian pop,pop          94   \n",
       "39  dance pop,electropop,etherpop,indie poptimism,...          88   \n",
       "40                              k-pop,k-pop boy group          97   \n",
       "41                            dance pop,pop,pop dance          88   \n",
       "42                               melodic rap,rap,trap          81   \n",
       "43                         north carolina hip hop,rap          93   \n",
       "44                                     electropop,pop          92   \n",
       "45              dance pop,pop,pop dance,post-teen pop          91   \n",
       "46  dance pop,edm,electropop,pop,pop dance,tropica...          84   \n",
       "47                                     australian pop          81   \n",
       "48  canadian hip hop,canadian pop,hip hop,pop rap,...          97   \n",
       "49              dance pop,pop,pop dance,post-teen pop          86   \n",
       "50              dance pop,pop,post-teen pop,viral pop          64   \n",
       "51                                     electropop,pop          79   \n",
       "52                                           cali rap          88   \n",
       "53                     post-teen pop,social media pop          60   \n",
       "54   dance pop,electropop,pop,pop dance,post-teen pop          85   \n",
       "\n",
       "                                      uri  \n",
       "0   spotify:artist:7cYEt1pqMgXJdq00hAwVpT  \n",
       "1   spotify:artist:4lDiJcOJ2GLCK6p9q5BgfK  \n",
       "2   spotify:artist:74KM79TiuVKeVCqs8QtB0B  \n",
       "3   spotify:artist:64KEffDW9EtZ1y2vBYgq8T  \n",
       "4   spotify:artist:0tMFcqLXhtm1Gep20iuIR3  \n",
       "5   spotify:artist:66CXWjxzNUsdJxJ2JdwvnR  \n",
       "6   spotify:artist:4MCBfE4596Uoi2O4DtmEMz  \n",
       "7   spotify:artist:5pVRwX5ZQR7hfJ18w8ZYkl  \n",
       "8   spotify:artist:0eDvMgVFoNV3TpwtrVCoTj  \n",
       "9   spotify:artist:41MozSoPIsD1dJM0CLPjZF  \n",
       "10  spotify:artist:4sVieJlKgpZ2k9ESNS5IdN  \n",
       "11  spotify:artist:5ZYOlPpI9FZu2uIPkTB0UA  \n",
       "12  spotify:artist:5p7mWeX4RlvqBCxylfiXdE  \n",
       "13  spotify:artist:4sg4no0TXdsrM1s4SVUwNF  \n",
       "14  spotify:artist:6M2wZ9GZgrQXHCFfjv46we  \n",
       "15  spotify:artist:1uNFoZAHBGtllmzznpCI3s  \n",
       "16  spotify:artist:6KImCVD70vtIoJWnq6nGn3  \n",
       "17  spotify:artist:1qQLhymHXFPtP5U8KNKsm6  \n",
       "18  spotify:artist:6ASri4ePR7RlsvIQgWPJpS  \n",
       "19  spotify:artist:2Im8m4STDBosjfmb5hmP80  \n",
       "20  spotify:artist:3gkbRDj7pkIylWVBpRfrQf  \n",
       "21  spotify:artist:1Ffb6ejR6Fe5IamqA5oRUF  \n",
       "22  spotify:artist:2wY79sveU1sp5g7SokKOiI  \n",
       "23  spotify:artist:5cj0lLjcoR7YOSnhnX0Po5  \n",
       "24  spotify:artist:2cFrymmkijnjDg9SS92EPM  \n",
       "25  spotify:artist:1wG6KrT3zgutFeiCddBivH  \n",
       "26  spotify:artist:2kRfqPViCqYdSGhYSM9R0Q  \n",
       "27  spotify:artist:0C8ZW7ezQVs4URX5aX7Kqx  \n",
       "28  spotify:artist:4rTv3Ejc7hKMtmoBOK1B4T  \n",
       "29  spotify:artist:3YQKmKGau1PzlVlkL1iodx  \n",
       "30  spotify:artist:4GNC7GD6oZMSxPGyXy4MNB  \n",
       "31  spotify:artist:6h1s4i4XKIYv4ErDelLDN0  \n",
       "32  spotify:artist:246dkjvS1zLTtiykXe5h60  \n",
       "33  spotify:artist:1INuLZXjjVbcJRyWvD1iSq  \n",
       "34  spotify:artist:1feoGrmmD8QmNqtK2Gdwy8  \n",
       "35  spotify:artist:06HL4z0CvFAxyc27GXpf02  \n",
       "36  spotify:artist:0lFLP59V4TY3XgnrkFIwxK  \n",
       "37  spotify:artist:6LuN9FCkKOj5PcnpouEgny  \n",
       "38  spotify:artist:1Xyo4u8uXC1ZmMpatF05PJ  \n",
       "39  spotify:artist:26VFTg2z8YR0cCuwLzESi2  \n",
       "40  spotify:artist:3Nrfpe0tUJi4K4DXYWgMUX  \n",
       "41  spotify:artist:1HY2Jd0NmPuamShAr6KMms  \n",
       "42  spotify:artist:4Ga1P7PMIsmqEZqhYZQgDo  \n",
       "43  spotify:artist:4r63FhuTkUYltbVAg5TQnk  \n",
       "44  spotify:artist:6qqNVTkY8uBg9cP3Jd7DAH  \n",
       "45  spotify:artist:5YGY8feqx7naU7z4HrwZM6  \n",
       "46  spotify:artist:69GGBxA162lTqCwzJG5jLp  \n",
       "47  spotify:artist:2NjfBq1NflQcKSeiDooVjY  \n",
       "48  spotify:artist:3TVXtAsR1Inumwj472S9r4  \n",
       "49  spotify:artist:6jJ0s89eD6GaHleKKya26X  \n",
       "50  spotify:artist:04abdnqPQe2N4fjztDea6z  \n",
       "51  spotify:artist:5IH6FPUwQTxPSXurCrcIov  \n",
       "52  spotify:artist:6fWVd57NKTalqvmjRd2t8Z  \n",
       "53  spotify:artist:3famqI9bxiwLcAjRq3HuYl  \n",
       "54  spotify:artist:4nDoRrQiYLoBzwC5BhVJzF  "
      ]
     },
     "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": {
      "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>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>Swim</td>\n",
       "      <td>Chase Atlantic</td>\n",
       "      <td>3M0lSi5WW79CXQamgSBIjx</td>\n",
       "      <td>Chase Atlantic</td>\n",
       "      <td>228786</td>\n",
       "      <td>74</td>\n",
       "      <td>0.666</td>\n",
       "      <td>0.542</td>\n",
       "      <td>8</td>\n",
       "      <td>-6.429</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0392</td>\n",
       "      <td>0.2700</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0765</td>\n",
       "      <td>0.0771</td>\n",
       "      <td>120.134</td>\n",
       "      <td>short term</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>WHAT TO DO? (feat. Don Toliver)</td>\n",
       "      <td>JACKBOYS</td>\n",
       "      <td>4AO1XhrgJczQ9bNVxdfKQe</td>\n",
       "      <td>JACKBOYS</td>\n",
       "      <td>250141</td>\n",
       "      <td>75</td>\n",
       "      <td>0.643</td>\n",
       "      <td>0.594</td>\n",
       "      <td>9</td>\n",
       "      <td>-5.191</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0312</td>\n",
       "      <td>0.0695</td>\n",
       "      <td>0.000015</td>\n",
       "      <td>0.1150</td>\n",
       "      <td>0.1950</td>\n",
       "      <td>118.037</td>\n",
       "      <td>short term</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Twingo</td>\n",
       "      <td>Twingo</td>\n",
       "      <td>0SkGIhZtmDJ5ggyeDsCNkf</td>\n",
       "      <td>Fynn Kliemann</td>\n",
       "      <td>186984</td>\n",
       "      <td>62</td>\n",
       "      <td>0.619</td>\n",
       "      <td>0.638</td>\n",
       "      <td>2</td>\n",
       "      <td>-5.754</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0906</td>\n",
       "      <td>0.2970</td>\n",
       "      <td>0.000001</td>\n",
       "      <td>0.4400</td>\n",
       "      <td>0.3600</td>\n",
       "      <td>141.967</td>\n",
       "      <td>short term</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Your Man</td>\n",
       "      <td>Nectar</td>\n",
       "      <td>6Vgtvd7I5yopJdBuxqjBd2</td>\n",
       "      <td>Joji</td>\n",
       "      <td>163758</td>\n",
       "      <td>76</td>\n",
       "      <td>0.785</td>\n",
       "      <td>0.818</td>\n",
       "      <td>7</td>\n",
       "      <td>-8.711</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0990</td>\n",
       "      <td>0.6240</td>\n",
       "      <td>0.149000</td>\n",
       "      <td>0.1490</td>\n",
       "      <td>0.0503</td>\n",
       "      <td>117.980</td>\n",
       "      <td>short term</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Into It</td>\n",
       "      <td>Chase Atlantic</td>\n",
       "      <td>4HwDCXsMBC7SUdp2WT4MZP</td>\n",
       "      <td>Chase Atlantic</td>\n",
       "      <td>196767</td>\n",
       "      <td>73</td>\n",
       "      <td>0.518</td>\n",
       "      <td>0.572</td>\n",
       "      <td>10</td>\n",
       "      <td>-6.706</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0416</td>\n",
       "      <td>0.0503</td>\n",
       "      <td>0.000024</td>\n",
       "      <td>0.1290</td>\n",
       "      <td>0.2910</td>\n",
       "      <td>130.053</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>Cyber Sex</td>\n",
       "      <td>Hot Pink</td>\n",
       "      <td>1ghvzmzpx2nnrbx7wtpMgo</td>\n",
       "      <td>Doja Cat</td>\n",
       "      <td>165733</td>\n",
       "      <td>75</td>\n",
       "      <td>0.917</td>\n",
       "      <td>0.657</td>\n",
       "      <td>8</td>\n",
       "      <td>-5.716</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0921</td>\n",
       "      <td>0.3180</td>\n",
       "      <td>0.000004</td>\n",
       "      <td>0.0754</td>\n",
       "      <td>0.8180</td>\n",
       "      <td>131.030</td>\n",
       "      <td>long term</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>Tongue Tied (with YUNGBLUD &amp; blackbear)</td>\n",
       "      <td>Tongue Tied (with YUNGBLUD &amp; blackbear)</td>\n",
       "      <td>7jzldCBnJjpJM3epzJ85KE</td>\n",
       "      <td>Marshmello</td>\n",
       "      <td>186024</td>\n",
       "      <td>68</td>\n",
       "      <td>0.628</td>\n",
       "      <td>0.821</td>\n",
       "      <td>1</td>\n",
       "      <td>-2.721</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0525</td>\n",
       "      <td>0.0208</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.4260</td>\n",
       "      <td>0.4650</td>\n",
       "      <td>93.001</td>\n",
       "      <td>long term</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>147</th>\n",
       "      <td>Smaller Than This</td>\n",
       "      <td>Smaller Than This</td>\n",
       "      <td>29A7Zz30FbIbvlnHHaJdIx</td>\n",
       "      <td>Sara Kays</td>\n",
       "      <td>208655</td>\n",
       "      <td>37</td>\n",
       "      <td>0.566</td>\n",
       "      <td>0.369</td>\n",
       "      <td>1</td>\n",
       "      <td>-9.181</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0249</td>\n",
       "      <td>0.7930</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.1090</td>\n",
       "      <td>0.2050</td>\n",
       "      <td>105.994</td>\n",
       "      <td>long term</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>Falling</td>\n",
       "      <td>Falling</td>\n",
       "      <td>4TnjEaWOeW0eKTKIEvJyCa</td>\n",
       "      <td>Trevor Daniel</td>\n",
       "      <td>159381</td>\n",
       "      <td>87</td>\n",
       "      <td>0.785</td>\n",
       "      <td>0.431</td>\n",
       "      <td>10</td>\n",
       "      <td>-8.756</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0364</td>\n",
       "      <td>0.1230</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0887</td>\n",
       "      <td>0.2360</td>\n",
       "      <td>127.085</td>\n",
       "      <td>long term</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149</th>\n",
       "      <td>Lights Up</td>\n",
       "      <td>Fine Line</td>\n",
       "      <td>4jAIqgrPjKLTY9Gbez25Qb</td>\n",
       "      <td>Harry Styles</td>\n",
       "      <td>172213</td>\n",
       "      <td>83</td>\n",
       "      <td>0.575</td>\n",
       "      <td>0.621</td>\n",
       "      <td>10</td>\n",
       "      <td>-8.165</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0320</td>\n",
       "      <td>0.0392</td>\n",
       "      <td>0.004500</td>\n",
       "      <td>0.1410</td>\n",
       "      <td>0.2700</td>\n",
       "      <td>101.987</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  \\\n",
       "0                                       Swim   \n",
       "1            WHAT TO DO? (feat. Don Toliver)   \n",
       "2                                     Twingo   \n",
       "3                                   Your Man   \n",
       "4                                    Into It   \n",
       "..                                       ...   \n",
       "145                                Cyber Sex   \n",
       "146  Tongue Tied (with YUNGBLUD & blackbear)   \n",
       "147                        Smaller Than This   \n",
       "148                                  Falling   \n",
       "149                                Lights Up   \n",
       "\n",
       "                                       album                track_id  \\\n",
       "0                             Chase Atlantic  3M0lSi5WW79CXQamgSBIjx   \n",
       "1                                   JACKBOYS  4AO1XhrgJczQ9bNVxdfKQe   \n",
       "2                                     Twingo  0SkGIhZtmDJ5ggyeDsCNkf   \n",
       "3                                     Nectar  6Vgtvd7I5yopJdBuxqjBd2   \n",
       "4                             Chase Atlantic  4HwDCXsMBC7SUdp2WT4MZP   \n",
       "..                                       ...                     ...   \n",
       "145                                 Hot Pink  1ghvzmzpx2nnrbx7wtpMgo   \n",
       "146  Tongue Tied (with YUNGBLUD & blackbear)  7jzldCBnJjpJM3epzJ85KE   \n",
       "147                        Smaller Than This  29A7Zz30FbIbvlnHHaJdIx   \n",
       "148                                  Falling  4TnjEaWOeW0eKTKIEvJyCa   \n",
       "149                                Fine Line  4jAIqgrPjKLTY9Gbez25Qb   \n",
       "\n",
       "             artist  duration  popularity  danceability  energy  key  \\\n",
       "0    Chase Atlantic    228786          74         0.666   0.542    8   \n",
       "1          JACKBOYS    250141          75         0.643   0.594    9   \n",
       "2     Fynn Kliemann    186984          62         0.619   0.638    2   \n",
       "3              Joji    163758          76         0.785   0.818    7   \n",
       "4    Chase Atlantic    196767          73         0.518   0.572   10   \n",
       "..              ...       ...         ...           ...     ...  ...   \n",
       "145        Doja Cat    165733          75         0.917   0.657    8   \n",
       "146      Marshmello    186024          68         0.628   0.821    1   \n",
       "147       Sara Kays    208655          37         0.566   0.369    1   \n",
       "148   Trevor Daniel    159381          87         0.785   0.431   10   \n",
       "149    Harry Styles    172213          83         0.575   0.621   10   \n",
       "\n",
       "     loudness  mode  speechiness  acousticness  instrumentalness  liveness  \\\n",
       "0      -6.429     1       0.0392        0.2700          0.000000    0.0765   \n",
       "1      -5.191     0       0.0312        0.0695          0.000015    0.1150   \n",
       "2      -5.754     0       0.0906        0.2970          0.000001    0.4400   \n",
       "3      -8.711     1       0.0990        0.6240          0.149000    0.1490   \n",
       "4      -6.706     0       0.0416        0.0503          0.000024    0.1290   \n",
       "..        ...   ...          ...           ...               ...       ...   \n",
       "145    -5.716     1       0.0921        0.3180          0.000004    0.0754   \n",
       "146    -2.721     0       0.0525        0.0208          0.000000    0.4260   \n",
       "147    -9.181     1       0.0249        0.7930          0.000000    0.1090   \n",
       "148    -8.756     0       0.0364        0.1230          0.000000    0.0887   \n",
       "149    -8.165     0       0.0320        0.0392          0.004500    0.1410   \n",
       "\n",
       "     valence    tempo   Timeframe  \n",
       "0     0.0771  120.134  short term  \n",
       "1     0.1950  118.037  short term  \n",
       "2     0.3600  141.967  short term  \n",
       "3     0.0503  117.980  short term  \n",
       "4     0.2910  130.053  short term  \n",
       "..       ...      ...         ...  \n",
       "145   0.8180  131.030   long term  \n",
       "146   0.4650   93.001   long term  \n",
       "147   0.2050  105.994   long term  \n",
       "148   0.2360  127.085   long term  \n",
       "149   0.2700  101.987   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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       "    .dataframe tbody tr th {\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>0.66304</td>\n",
       "      <td>0.63300</td>\n",
       "      <td>5.86</td>\n",
       "      <td>-6.61438</td>\n",
       "      <td>0.60</td>\n",
       "      <td>0.092126</td>\n",
       "      <td>0.251583</td>\n",
       "      <td>0.005209</td>\n",
       "      <td>0.170326</td>\n",
       "      <td>0.471144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>medium term</th>\n",
       "      <td>0.68136</td>\n",
       "      <td>0.62924</td>\n",
       "      <td>5.18</td>\n",
       "      <td>-6.76458</td>\n",
       "      <td>0.58</td>\n",
       "      <td>0.095004</td>\n",
       "      <td>0.226746</td>\n",
       "      <td>0.004104</td>\n",
       "      <td>0.138608</td>\n",
       "      <td>0.420542</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>short term</th>\n",
       "      <td>0.64564</td>\n",
       "      <td>0.62832</td>\n",
       "      <td>5.60</td>\n",
       "      <td>-7.24246</td>\n",
       "      <td>0.58</td>\n",
       "      <td>0.112892</td>\n",
       "      <td>0.255412</td>\n",
       "      <td>0.004633</td>\n",
       "      <td>0.147266</td>\n",
       "      <td>0.402806</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             danceability   energy   key  loudness  mode  speechiness  \\\n",
       "Timeframe                                                               \n",
       "long term         0.66304  0.63300  5.86  -6.61438  0.60     0.092126   \n",
       "medium term       0.68136  0.62924  5.18  -6.76458  0.58     0.095004   \n",
       "short term        0.64564  0.62832  5.60  -7.24246  0.58     0.112892   \n",
       "\n",
       "             acousticness  instrumentalness  liveness   valence  \n",
       "Timeframe                                                        \n",
       "long term        0.251583          0.005209  0.170326  0.471144  \n",
       "medium term      0.226746          0.004104  0.138608  0.420542  \n",
       "short term       0.255412          0.004633  0.147266  0.402806  "
      ]
     },
     "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)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
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       "    }\n",
       "\n",
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       "        text-align: right;\n",
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       "</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>0.663040</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>medium term</td>\n",
       "      <td>danceability</td>\n",
       "      <td>0.681360</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>short term</td>\n",
       "      <td>danceability</td>\n",
       "      <td>0.645640</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>long term</td>\n",
       "      <td>energy</td>\n",
       "      <td>0.633000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>medium term</td>\n",
       "      <td>energy</td>\n",
       "      <td>0.629240</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>short term</td>\n",
       "      <td>energy</td>\n",
       "      <td>0.628320</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>long term</td>\n",
       "      <td>key</td>\n",
       "      <td>5.860000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>medium term</td>\n",
       "      <td>key</td>\n",
       "      <td>5.180000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>short term</td>\n",
       "      <td>key</td>\n",
       "      <td>5.600000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>long term</td>\n",
       "      <td>loudness</td>\n",
       "      <td>-6.614380</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>medium term</td>\n",
       "      <td>loudness</td>\n",
       "      <td>-6.764580</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>short term</td>\n",
       "      <td>loudness</td>\n",
       "      <td>-7.242460</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>long term</td>\n",
       "      <td>mode</td>\n",
       "      <td>0.600000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>medium term</td>\n",
       "      <td>mode</td>\n",
       "      <td>0.580000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>short term</td>\n",
       "      <td>mode</td>\n",
       "      <td>0.580000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>long term</td>\n",
       "      <td>speechiness</td>\n",
       "      <td>0.092126</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>medium term</td>\n",
       "      <td>speechiness</td>\n",
       "      <td>0.095004</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>short term</td>\n",
       "      <td>speechiness</td>\n",
       "      <td>0.112892</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>long term</td>\n",
       "      <td>acousticness</td>\n",
       "      <td>0.251583</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>medium term</td>\n",
       "      <td>acousticness</td>\n",
       "      <td>0.226746</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>short term</td>\n",
       "      <td>acousticness</td>\n",
       "      <td>0.255412</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>long term</td>\n",
       "      <td>instrumentalness</td>\n",
       "      <td>0.005209</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>medium term</td>\n",
       "      <td>instrumentalness</td>\n",
       "      <td>0.004104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>short term</td>\n",
       "      <td>instrumentalness</td>\n",
       "      <td>0.004633</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>long term</td>\n",
       "      <td>liveness</td>\n",
       "      <td>0.170326</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>medium term</td>\n",
       "      <td>liveness</td>\n",
       "      <td>0.138608</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>short term</td>\n",
       "      <td>liveness</td>\n",
       "      <td>0.147266</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>long term</td>\n",
       "      <td>valence</td>\n",
       "      <td>0.471144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>medium term</td>\n",
       "      <td>valence</td>\n",
       "      <td>0.420542</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>short term</td>\n",
       "      <td>valence</td>\n",
       "      <td>0.402806</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Timeframe     audio_feature      mean\n",
       "0     long term      danceability  0.663040\n",
       "1   medium term      danceability  0.681360\n",
       "2    short term      danceability  0.645640\n",
       "3     long term            energy  0.633000\n",
       "4   medium term            energy  0.629240\n",
       "5    short term            energy  0.628320\n",
       "6     long term               key  5.860000\n",
       "7   medium term               key  5.180000\n",
       "8    short term               key  5.600000\n",
       "9     long term          loudness -6.614380\n",
       "10  medium term          loudness -6.764580\n",
       "11   short term          loudness -7.242460\n",
       "12    long term              mode  0.600000\n",
       "13  medium term              mode  0.580000\n",
       "14   short term              mode  0.580000\n",
       "15    long term       speechiness  0.092126\n",
       "16  medium term       speechiness  0.095004\n",
       "17   short term       speechiness  0.112892\n",
       "18    long term      acousticness  0.251583\n",
       "19  medium term      acousticness  0.226746\n",
       "20   short term      acousticness  0.255412\n",
       "21    long term  instrumentalness  0.005209\n",
       "22  medium term  instrumentalness  0.004104\n",
       "23   short term  instrumentalness  0.004633\n",
       "24    long term          liveness  0.170326\n",
       "25  medium term          liveness  0.138608\n",
       "26   short term          liveness  0.147266\n",
       "27    long term           valence  0.471144\n",
       "28  medium term           valence  0.420542\n",
       "29   short term           valence  0.402806"
      ]
     },
     "execution_count": 13,
     "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": 14,
   "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": 15,
   "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": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cluster_feat = audio_features[:-1]\n",
    "cluster_feat"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "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": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\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": 17,
   "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": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 18,
     "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": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "n_cluster = 8\n",
    "km = KMeans(n_clusters = n_cluster, max_iter = 10000, random_state=13).fit(X)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_pred = km.predict(X)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(150,)"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_pred.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "top_tracks[\"cluster\"] = X_pred"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "                               track_name             artist\n",
      "0                                   Swim     Chase Atlantic\n",
      "1        WHAT TO DO? (feat. Don Toliver)           JACKBOYS\n",
      "4                                Into It     Chase Atlantic\n",
      "7                                Friends     Chase Atlantic\n",
      "25      Consume (feat. Goon Des Garcons)     Chase Atlantic\n",
      "28                             Triggered     Chase Atlantic\n",
      "40   Jenny (I Wanna Ruin Our Friendship)     Studio Killers\n",
      "44                        Ayo Technology         Kynda Gray\n",
      "72                       Einsam zu zweit         Simon Will\n",
      "99                             Lights Up       Harry Styles\n",
      "107                           Don’t Play             Halsey\n",
      "109                            gone girl          iann dior\n",
      "119                          Reflections  The Neighbourhood\n",
      "121                             emotions          iann dior\n",
      "136                                 Easy       Kyd the Band\n",
      "148                              Falling      Trevor Daniel \n",
      "\n",
      "\n",
      "                                      track_name                artist\n",
      "11                                        Ozone        Chase Atlantic\n",
      "17                        Be Kind (with Halsey)            Marshmello\n",
      "19                            Seve - Radio Edit             Tez Cadey\n",
      "23                                WEISSER RAUCH                FOURTY\n",
      "26                                      Falling        Chase Atlantic\n",
      "30                                        Proud            Marshmello\n",
      "31                                       Lonely                Tujamo\n",
      "33                                       Cassie        Chase Atlantic\n",
      "34                                    Mistletoe         Justin Bieber\n",
      "35                                       Breath                 pluko\n",
      "49                     Merry Christmas Everyone       Shakin' Stevens\n",
      "74                                      Ballin'  Digital Farm Animals\n",
      "75                                me & ur ghost             blackbear\n",
      "79                             Level of Concern     Twenty One Pilots\n",
      "80   Still Be Friends (feat. Tory Lanez & Tyga)                G-Eazy\n",
      "81                                      ROYALTY                 ILIRA\n",
      "85                                     Birthday            Anne-Marie\n",
      "90                              I Can't Stop Me     Sabrina Carpenter\n",
      "94                                 Eenie Meenie         Sean Kingston\n",
      "95                                    Not Today     Twenty One Pilots\n",
      "116                               Rot Wie Rubin           Louis Fuego\n",
      "123                                     Hi Babe                  Juju\n",
      "133                    Mmm Yeah (feat. Pitbull)         Austin Mahone\n",
      "134                                     Bye Bye                  Juju\n",
      "137                                   Play Date      Melanie Martinez\n",
      "139                               Alone, Pt. II           Alan Walker\n",
      "145                                   Cyber Sex              Doja Cat \n",
      "\n",
      "\n",
      "                                    track_name             artist\n",
      "5                                Du willst es           Kontra K\n",
      "6                                      Leaked           Lil Tjay\n",
      "9                                    Emotions             Ufo361\n",
      "14                               Shit Changed             Ufo361\n",
      "15                                        WOW       Zara Larsson\n",
      "20                  Tiefschwarz (feat. Samra)           Kontra K\n",
      "29                                     Hyänen               Vega\n",
      "36                                   Bläulich         Apache 207\n",
      "41               Mood Swings (feat. Lil Tjay)          Pop Smoke\n",
      "89                                       Tusa            KAROL G\n",
      "96                                        Why  Sabrina Carpenter\n",
      "114                                      2002               Sido\n",
      "124                                   Love Me          Lil Tecca\n",
      "127                                    Sue Me  Sabrina Carpenter\n",
      "140                               Made 4 Love               SXTN\n",
      "143  All Roads Lead Home (Hobbs & Shaw Remix)          Ohana Bam \n",
      "\n",
      "\n",
      "   track_name artist\n",
      "3   Your Man   Joji \n",
      "\n",
      "\n",
      "                                   track_name              artist\n",
      "2                                     Twingo       Fynn Kliemann\n",
      "8                  VALENTINO - Imanbek Remix            24kGoldn\n",
      "13                                 Hollywood           LA Vision\n",
      "42                             Feliz Navidad      José Feliciano\n",
      "68                                Summer 16'  Sebastian Olzanski\n",
      "128                              Upside Down             A*Teens\n",
      "132                                 Obsessed        Mariah Carey\n",
      "146  Tongue Tied (with YUNGBLUD & blackbear)          Marshmello \n",
      "\n",
      "\n",
      "                          track_name          artist\n",
      "10                Smaller Than This       Sara Kays\n",
      "18              Lose You To Love Me    Selena Gomez\n",
      "24                               23  Chase Atlantic\n",
      "37   Rudolph The Red-Nosed Reindeer  Helene Fischer\n",
      "45                           willow    Taylor Swift\n",
      "47                          Überall          CÉLINE\n",
      "71                          Control        Zoe Wees\n",
      "97                 Forgotten Ghosts      Jadu Heart\n",
      "106                      To Die For       Sam Smith\n",
      "120              Moral of the Story            Ashe\n",
      "135                          Savage          Bahari \n",
      "\n",
      "\n",
      "                         track_name       artist\n",
      "48  Rudolph The Red-Nosed Reindeer  Dean Martin\n",
      "60               Angels 'N' Demons   Fantom Blu \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": 24,
   "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>-0.737240</td>\n",
       "      <td>5.482400</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-1.918965</td>\n",
       "      <td>5.045205</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3.466219</td>\n",
       "      <td>5.717972</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-6.804125</td>\n",
       "      <td>14.493647</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-1.139544</td>\n",
       "      <td>4.065245</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         D1         D2  label\n",
       "0 -0.737240   5.482400      1\n",
       "1 -1.918965   5.045205      1\n",
       "2  3.466219   5.717972      5\n",
       "3 -6.804125  14.493647      4\n",
       "4 -1.139544   4.065245      1"
      ]
     },
     "execution_count": 24,
     "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": 25,
   "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": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.5160901289554739\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([0.23196155, 0.38447019, 0.51609013])"
      ]
     },
     "execution_count": 26,
     "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": 27,
   "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": 28,
   "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>-36.391468</td>\n",
       "      <td>212.011520</td>\n",
       "      <td>143.227844</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>11.109424</td>\n",
       "      <td>427.900116</td>\n",
       "      <td>2.280091</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>615.950684</td>\n",
       "      <td>-196.722839</td>\n",
       "      <td>-107.548912</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-8.540461</td>\n",
       "      <td>-59.122952</td>\n",
       "      <td>630.807251</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>306.044891</td>\n",
       "      <td>128.735092</td>\n",
       "      <td>204.142395</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           D1          D2          D3  label\n",
       "0  -36.391468  212.011520  143.227844      1\n",
       "1   11.109424  427.900116    2.280091      1\n",
       "2  615.950684 -196.722839 -107.548912      5\n",
       "3   -8.540461  -59.122952  630.807251      4\n",
       "4  306.044891  128.735092  204.142395      1"
      ]
     },
     "execution_count": 28,
     "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": 29,
   "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": 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>label</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.143631</td>\n",
       "      <td>0.147085</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-0.092131</td>\n",
       "      <td>0.114810</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.058886</td>\n",
       "      <td>-0.375405</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.200553</td>\n",
       "      <td>0.004567</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-0.030382</td>\n",
       "      <td>0.094666</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         D1        D2  label\n",
       "0  0.143631  0.147085      1\n",
       "1 -0.092131  0.114810      1\n",
       "2  0.058886 -0.375405      5\n",
       "3  0.200553  0.004567      4\n",
       "4 -0.030382  0.094666      1"
      ]
     },
     "execution_count": 30,
     "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": 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": [
    "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": 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>0.056870</td>\n",
       "      <td>0.000668</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.056870</td>\n",
       "      <td>-0.005843</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.057665</td>\n",
       "      <td>-0.314264</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.056871</td>\n",
       "      <td>-0.017565</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.056870</td>\n",
       "      <td>-0.012844</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         D1        D2  label\n",
       "0  0.056870  0.000668      1\n",
       "1  0.056870 -0.005843      1\n",
       "2  0.057665 -0.314264      5\n",
       "3  0.056871 -0.017565      4\n",
       "4  0.056870 -0.012844      1"
      ]
     },
     "execution_count": 32,
     "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": 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_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": 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>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>0.666</td>\n",
       "      <td>0.542</td>\n",
       "      <td>8</td>\n",
       "      <td>-6.429</td>\n",
       "      <td>0.0392</td>\n",
       "      <td>0.2700</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0765</td>\n",
       "      <td>0.0771</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.643</td>\n",
       "      <td>0.594</td>\n",
       "      <td>9</td>\n",
       "      <td>-5.191</td>\n",
       "      <td>0.0312</td>\n",
       "      <td>0.0695</td>\n",
       "      <td>0.000015</td>\n",
       "      <td>0.1150</td>\n",
       "      <td>0.1950</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.619</td>\n",
       "      <td>0.638</td>\n",
       "      <td>2</td>\n",
       "      <td>-5.754</td>\n",
       "      <td>0.0906</td>\n",
       "      <td>0.2970</td>\n",
       "      <td>0.000001</td>\n",
       "      <td>0.4400</td>\n",
       "      <td>0.3600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.785</td>\n",
       "      <td>0.818</td>\n",
       "      <td>7</td>\n",
       "      <td>-8.711</td>\n",
       "      <td>0.0990</td>\n",
       "      <td>0.6240</td>\n",
       "      <td>0.149000</td>\n",
       "      <td>0.1490</td>\n",
       "      <td>0.0503</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.518</td>\n",
       "      <td>0.572</td>\n",
       "      <td>10</td>\n",
       "      <td>-6.706</td>\n",
       "      <td>0.0416</td>\n",
       "      <td>0.0503</td>\n",
       "      <td>0.000024</td>\n",
       "      <td>0.1290</td>\n",
       "      <td>0.2910</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>0.917</td>\n",
       "      <td>0.657</td>\n",
       "      <td>8</td>\n",
       "      <td>-5.716</td>\n",
       "      <td>0.0921</td>\n",
       "      <td>0.3180</td>\n",
       "      <td>0.000004</td>\n",
       "      <td>0.0754</td>\n",
       "      <td>0.8180</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>0.628</td>\n",
       "      <td>0.821</td>\n",
       "      <td>1</td>\n",
       "      <td>-2.721</td>\n",
       "      <td>0.0525</td>\n",
       "      <td>0.0208</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.4260</td>\n",
       "      <td>0.4650</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>147</th>\n",
       "      <td>0.566</td>\n",
       "      <td>0.369</td>\n",
       "      <td>1</td>\n",
       "      <td>-9.181</td>\n",
       "      <td>0.0249</td>\n",
       "      <td>0.7930</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.1090</td>\n",
       "      <td>0.2050</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>0.785</td>\n",
       "      <td>0.431</td>\n",
       "      <td>10</td>\n",
       "      <td>-8.756</td>\n",
       "      <td>0.0364</td>\n",
       "      <td>0.1230</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0887</td>\n",
       "      <td>0.2360</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149</th>\n",
       "      <td>0.575</td>\n",
       "      <td>0.621</td>\n",
       "      <td>10</td>\n",
       "      <td>-8.165</td>\n",
       "      <td>0.0320</td>\n",
       "      <td>0.0392</td>\n",
       "      <td>0.004500</td>\n",
       "      <td>0.1410</td>\n",
       "      <td>0.2700</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           0.666   0.542    8    -6.429       0.0392        0.2700   \n",
       "1           0.643   0.594    9    -5.191       0.0312        0.0695   \n",
       "2           0.619   0.638    2    -5.754       0.0906        0.2970   \n",
       "3           0.785   0.818    7    -8.711       0.0990        0.6240   \n",
       "4           0.518   0.572   10    -6.706       0.0416        0.0503   \n",
       "..            ...     ...  ...       ...          ...           ...   \n",
       "145         0.917   0.657    8    -5.716       0.0921        0.3180   \n",
       "146         0.628   0.821    1    -2.721       0.0525        0.0208   \n",
       "147         0.566   0.369    1    -9.181       0.0249        0.7930   \n",
       "148         0.785   0.431   10    -8.756       0.0364        0.1230   \n",
       "149         0.575   0.621   10    -8.165       0.0320        0.0392   \n",
       "\n",
       "     instrumentalness  liveness  valence  \n",
       "0            0.000000    0.0765   0.0771  \n",
       "1            0.000015    0.1150   0.1950  \n",
       "2            0.000001    0.4400   0.3600  \n",
       "3            0.149000    0.1490   0.0503  \n",
       "4            0.000024    0.1290   0.2910  \n",
       "..                ...       ...      ...  \n",
       "145          0.000004    0.0754   0.8180  \n",
       "146          0.000000    0.4260   0.4650  \n",
       "147          0.000000    0.1090   0.2050  \n",
       "148          0.000000    0.0887   0.2360  \n",
       "149          0.004500    0.1410   0.2700  \n",
       "\n",
       "[150 rows x 9 columns]"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#average song feature per cluster (what are our clusters representing?)\n",
    "df_cluster"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_cluster[\"cluster\"] = X_pred\n",
    "df_cluster.drop([\"key\",\"loudness\"],axis = 1,inplace = True)"
   ]
  },
  {
   "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>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>0.783409</td>\n",
       "      <td>0.520409</td>\n",
       "      <td>0.136200</td>\n",
       "      <td>0.147486</td>\n",
       "      <td>0.000851</td>\n",
       "      <td>0.130286</td>\n",
       "      <td>0.366000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>0.608478</td>\n",
       "      <td>0.629261</td>\n",
       "      <td>0.053548</td>\n",
       "      <td>0.129898</td>\n",
       "      <td>0.003043</td>\n",
       "      <td>0.134891</td>\n",
       "      <td>0.258804</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>0.667000</td>\n",
       "      <td>0.722800</td>\n",
       "      <td>0.060400</td>\n",
       "      <td>0.175155</td>\n",
       "      <td>0.002065</td>\n",
       "      <td>0.116067</td>\n",
       "      <td>0.606222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>0.690333</td>\n",
       "      <td>0.659333</td>\n",
       "      <td>0.252208</td>\n",
       "      <td>0.276746</td>\n",
       "      <td>0.002131</td>\n",
       "      <td>0.097542</td>\n",
       "      <td>0.380375</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>0.785000</td>\n",
       "      <td>0.818000</td>\n",
       "      <td>0.099000</td>\n",
       "      <td>0.624000</td>\n",
       "      <td>0.149000</td>\n",
       "      <td>0.149000</td>\n",
       "      <td>0.050300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5</td>\n",
       "      <td>0.679214</td>\n",
       "      <td>0.707071</td>\n",
       "      <td>0.051671</td>\n",
       "      <td>0.166687</td>\n",
       "      <td>0.000933</td>\n",
       "      <td>0.423000</td>\n",
       "      <td>0.575429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>6</td>\n",
       "      <td>0.515062</td>\n",
       "      <td>0.434875</td>\n",
       "      <td>0.052069</td>\n",
       "      <td>0.674125</td>\n",
       "      <td>0.000273</td>\n",
       "      <td>0.142175</td>\n",
       "      <td>0.250075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>7</td>\n",
       "      <td>0.528000</td>\n",
       "      <td>0.315000</td>\n",
       "      <td>0.049533</td>\n",
       "      <td>0.313067</td>\n",
       "      <td>0.000025</td>\n",
       "      <td>0.211133</td>\n",
       "      <td>0.701000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   cluster  danceability    energy  speechiness  acousticness  \\\n",
       "0        0      0.783409  0.520409     0.136200      0.147486   \n",
       "1        1      0.608478  0.629261     0.053548      0.129898   \n",
       "2        2      0.667000  0.722800     0.060400      0.175155   \n",
       "3        3      0.690333  0.659333     0.252208      0.276746   \n",
       "4        4      0.785000  0.818000     0.099000      0.624000   \n",
       "5        5      0.679214  0.707071     0.051671      0.166687   \n",
       "6        6      0.515062  0.434875     0.052069      0.674125   \n",
       "7        7      0.528000  0.315000     0.049533      0.313067   \n",
       "\n",
       "   instrumentalness  liveness   valence  \n",
       "0          0.000851  0.130286  0.366000  \n",
       "1          0.003043  0.134891  0.258804  \n",
       "2          0.002065  0.116067  0.606222  \n",
       "3          0.002131  0.097542  0.380375  \n",
       "4          0.149000  0.149000  0.050300  \n",
       "5          0.000933  0.423000  0.575429  \n",
       "6          0.000273  0.142175  0.250075  \n",
       "7          0.000025  0.211133  0.701000  "
      ]
     },
     "execution_count": 36,
     "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": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x720 with 8 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 = [str(x) for x in range(1,8)]\n",
    "\n",
    "for row in range(0, len(df_radar.index)):\n",
    "    make_radar(row=row, title=\"test\", \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
}