Spotify_Songs_Suggestion_Model.ipynb

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  "metadata": {
    "colab": {
      "name": "Spotify Songs Suggestion Model.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/DinDin23/Spotify-Songs-Suggestion-Model/blob/main/Spotify_Songs_Suggestion_Model.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "n7CFK0vovSNF"
      },
      "source": [
        "# Spotify Suggestion Model V1"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "QK7_salHtjAo"
      },
      "source": [
        "## Infrastructure"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0qdIGCbJiiqQ"
      },
      "source": [
        "import sys\n",
        "!{sys.executable} -m pip install spotipy"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "66Ln0z2NilEK"
      },
      "source": [
        "username = \"dineshsp\"\n",
        "cid = \"b858cb986e874b8ca3e1a437a81b3dcd\" \n",
        "secret = \"8d7a73e652544e20b5b8ccebe4d8f03c\"\n",
        "good_playlist_id = \"61BmnG6d7ifmj8Dr5tuCBK\"\n",
        "bad_playlist_id = \"53FPslFSIAGvVyERcNG4J3\"\n",
        "source_playlist_id = \"5ghFHvZmV4FDK5YLeZQRu9\""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Zv-9hy3IimF4"
      },
      "source": [
        "import spotipy\n",
        "import spotipy.util as util\n",
        "from spotipy.oauth2 import SpotifyClientCredentials\n",
        "\n",
        "import pandas as pd\n",
        "from statistics import mean, stdev\n",
        "from sklearn.model_selection import StratifiedKFold\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.model_selection import cross_val_score\n",
        "from sklearn.metrics import accuracy_score, mean_squared_error, r2_score\n",
        "from sklearn.neighbors import KNeighborsClassifier\n",
        "from sklearn.tree import DecisionTreeClassifier\n",
        "from sklearn.ensemble import RandomForestClassifier\n",
        "from sklearn.ensemble import AdaBoostClassifier\n",
        "from sklearn.ensemble import GradientBoostingClassifier\n",
        "from sklearn.linear_model import LinearRegression"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "DzcmdM3xtoWp"
      },
      "source": [
        "## Data Collection"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4yjbU7XGis6h"
      },
      "source": [
        "sp_cred = SpotifyClientCredentials(\n",
        "    client_id=cid,\n",
        "    client_secret=secret\n",
        ")\n",
        "sp = spotipy.Spotify(client_credentials_manager=sp_cred)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MlI1GrsRi3l3"
      },
      "source": [
        "good_playlist = sp.user_playlist(username, good_playlist_id)\n",
        "good_tracks = good_playlist[\"tracks\"]\n",
        "good_songs = good_tracks[\"items\"]\n",
        "\n",
        "while good_tracks['next']:\n",
        "    good_tracks = sp.next(good_tracks)\n",
        "    for item in good_tracks[\"items\"]:\n",
        "        good_songs.append(item)\n",
        "\n",
        "good_ids = []\n",
        "for i in range(len(good_songs)):\n",
        "    good_ids.append(good_songs[i]['track']['id'])\n",
        "print(good_songs)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tmxlK5lqjXu5"
      },
      "source": [
        "bad_playlist = sp.user_playlist(username, bad_playlist_id)\n",
        "bad_tracks = bad_playlist[\"tracks\"]\n",
        "bad_songs = bad_tracks[\"items\"]\n",
        "\n",
        "while bad_tracks['next']:\n",
        "    bad_tracks = sp.next(bad_tracks)\n",
        "    for item in bad_tracks[\"items\"]:\n",
        "        bad_songs.append(item)\n",
        "\n",
        "bad_ids = []\n",
        "for i in range(len(bad_songs)):\n",
        "    bad_ids.append(bad_songs[i]['track']['id'])\n",
        "print(len(bad_ids))\n",
        "print(bad_ids)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "22yVFnRptZTM"
      },
      "source": [
        "source_playlist = sp.user_playlist(username, source_playlist_id)\n",
        "source_tracks = source_playlist[\"tracks\"]\n",
        "source_songs = source_tracks[\"items\"]\n",
        "\n",
        "while source_tracks['next']:\n",
        "    source_tracks = sp.next(source_tracks)\n",
        "    for item in source_tracks[\"items\"]:\n",
        "        source_songs.append(item)\n",
        "\n",
        "source_ids = []\n",
        "for i in range(len(source_songs)):\n",
        "    if source_songs[i]['track'] != None:\n",
        "      source_ids.append(source_songs[i]['track']['id'])\n",
        "print(len(source_ids))\n",
        "print(source_ids)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "N7VQZzZ8jJ9D"
      },
      "source": [
        "training_features = []\n",
        "\n",
        "for i in range(0, len(good_ids), 50):\n",
        "    audio_features = sp.audio_features(good_ids[i : i + 50])\n",
        "    for track in audio_features:\n",
        "        training_features.append(track)\n",
        "        training_features[-1]['target'] = 1\n",
        "\n",
        "for i in range(0, len(bad_ids), 50):\n",
        "    audio_features = sp.audio_features(bad_ids[i : i + 50])\n",
        "    for track in audio_features:\n",
        "        training_features.append(track)\n",
        "        training_features[-1]['target'] = 0\n",
        "\n",
        "print(len(training_features))\n",
        "print(training_features)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Qfv8qNtJt1bR"
      },
      "source": [
        "source_features = []\n",
        "for i in range(0, len(source_ids), 50):\n",
        "    audio_features = sp.audio_features(source_ids[i : i + 50])\n",
        "    for track in audio_features:\n",
        "        source_features.append(track)\n",
        "        source_features[-1]['target'] = 0  \n",
        "\n",
        "print(len(source_features))\n",
        "print(source_features)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "0dLN8eo3uiQV"
      },
      "source": [
        "## Data Preparation"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mXJC5u2EkvBx"
      },
      "source": [
        "trainingData = pd.DataFrame(training_features)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Y5mJO335pN6t",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 661
        },
        "outputId": "91639c95-6235-4336-b1ca-19d48460cc70"
      },
      "source": [
        "trainingData"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "      <td>https://api.spotify.com/v1/audio-analysis/5QTx...</td>\n",
              "      <td>308120</td>\n",
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              "<p>349 rows × 19 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-935d9b9b-4d6f-44ce-8bef-81d8dfe268b0')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
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              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
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              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
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              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-935d9b9b-4d6f-44ce-8bef-81d8dfe268b0 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
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              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-935d9b9b-4d6f-44ce-8bef-81d8dfe268b0');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
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              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "     danceability  energy  key  ...  duration_ms  time_signature  target\n",
              "0           0.482   0.786    7  ...       323000               4       1\n",
              "1           0.377   0.681    7  ...       285133               4       1\n",
              "2           0.333   0.927    9  ...       308120               4       1\n",
              "3           0.316   0.320    9  ...       250933               3       1\n",
              "4           0.341   0.293    9  ...       249213               4       1\n",
              "..            ...     ...  ...  ...          ...             ...     ...\n",
              "344         0.567   0.463    6  ...       496173               4       0\n",
              "345         0.554   0.498    9  ...       190067               4       0\n",
              "346         0.598   0.252    2  ...       238307               4       0\n",
              "347         0.621   0.601    6  ...       163636               5       0\n",
              "348         0.687   0.684    0  ...       107207               4       0\n",
              "\n",
              "[349 rows x 19 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tnmUDrrhkzSv"
      },
      "source": [
        "train, test = train_test_split(trainingData, test_size = 0.15)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tzjJXNrwk2b4"
      },
      "source": [
        "target_features = [\"danceability\", \"loudness\", \"valence\", \"energy\", \"instrumentalness\", \"acousticness\", \"key\", \"speechiness\", \"duration_ms\"]\n",
        "\n",
        "x_train = train[target_features]\n",
        "y_train = train[\"target\"]\n",
        "x_test = test[target_features]\n",
        "y_test = test[\"target\"]"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "CIc_1Sb_pPOf",
        "outputId": "05e9a7a4-e9a4-4637-c577-3237ce30b2c0"
      },
      "source": [
        "x_train"
      ],
      "execution_count": null,
      "outputs": [
        {
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              "  "
            ],
            "text/plain": [
              "     danceability  loudness  valence  ...  key  speechiness  duration_ms\n",
              "247         0.735    -2.939    0.369  ...    6       0.0441       157777\n",
              "32          0.436    -3.375    0.459  ...    9       0.0341       240533\n",
              "301         0.692    -8.465    0.463  ...   10       0.3300       292987\n",
              "169         0.769    -5.591    0.612  ...    1       0.0786       216946\n",
              "99          0.313    -6.215    0.300  ...    0       0.0355       431093\n",
              "..            ...       ...      ...  ...  ...          ...          ...\n",
              "235         0.931    -9.127    0.376  ...    1       0.4120       179405\n",
              "56          0.329    -8.465    0.323  ...    3       0.0296       419933\n",
              "2           0.333    -8.550    0.385  ...    9       0.0733       308120\n",
              "8           0.392    -9.961    0.228  ...    0       0.0536       354320\n",
              "200         0.582    -6.131    0.155  ...    7       0.0467       219840\n",
              "\n",
              "[296 rows x 9 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jBIgqGofpS9m"
      },
      "source": [
        "y_train"
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      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
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        "id": "UTJHfAmopUvQ",
        "outputId": "735cde37-d37f-475c-a632-f8fe7c70e933"
      },
      "source": [
        "x_test"
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      "execution_count": null,
      "outputs": [
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              "      <th>195</th>\n",
              "      <td>0.846</td>\n",
              "      <td>-8.059</td>\n",
              "      <td>0.441</td>\n",
              "      <td>0.538</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.027200</td>\n",
              "      <td>1</td>\n",
              "      <td>0.0576</td>\n",
              "      <td>208160</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>183</th>\n",
              "      <td>0.721</td>\n",
              "      <td>-6.847</td>\n",
              "      <td>0.614</td>\n",
              "      <td>0.766</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.091300</td>\n",
              "      <td>7</td>\n",
              "      <td>0.3240</td>\n",
              "      <td>175294</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>259</th>\n",
              "      <td>0.624</td>\n",
              "      <td>-4.261</td>\n",
              "      <td>0.141</td>\n",
              "      <td>0.659</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.246000</td>\n",
              "      <td>4</td>\n",
              "      <td>0.2550</td>\n",
              "      <td>176328</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>330</th>\n",
              "      <td>0.886</td>\n",
              "      <td>-8.054</td>\n",
              "      <td>0.408</td>\n",
              "      <td>0.479</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.077000</td>\n",
              "      <td>4</td>\n",
              "      <td>0.3340</td>\n",
              "      <td>158692</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>196</th>\n",
              "      <td>0.473</td>\n",
              "      <td>-6.474</td>\n",
              "      <td>0.615</td>\n",
              "      <td>0.461</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.149000</td>\n",
              "      <td>6</td>\n",
              "      <td>0.3330</td>\n",
              "      <td>234213</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>69</th>\n",
              "      <td>0.456</td>\n",
              "      <td>-3.551</td>\n",
              "      <td>0.532</td>\n",
              "      <td>0.863</td>\n",
              "      <td>0.053800</td>\n",
              "      <td>0.133000</td>\n",
              "      <td>3</td>\n",
              "      <td>0.0894</td>\n",
              "      <td>301227</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>121</th>\n",
              "      <td>0.463</td>\n",
              "      <td>-7.950</td>\n",
              "      <td>0.550</td>\n",
              "      <td>0.943</td>\n",
              "      <td>0.213000</td>\n",
              "      <td>0.030300</td>\n",
              "      <td>10</td>\n",
              "      <td>0.0419</td>\n",
              "      <td>375307</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>275</th>\n",
              "      <td>0.729</td>\n",
              "      <td>-8.060</td>\n",
              "      <td>0.683</td>\n",
              "      <td>0.687</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.010800</td>\n",
              "      <td>8</td>\n",
              "      <td>0.2500</td>\n",
              "      <td>179831</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>101</th>\n",
              "      <td>0.446</td>\n",
              "      <td>-5.004</td>\n",
              "      <td>0.595</td>\n",
              "      <td>0.970</td>\n",
              "      <td>0.000275</td>\n",
              "      <td>0.007540</td>\n",
              "      <td>9</td>\n",
              "      <td>0.0508</td>\n",
              "      <td>363587</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>92</th>\n",
              "      <td>0.511</td>\n",
              "      <td>-6.962</td>\n",
              "      <td>0.543</td>\n",
              "      <td>0.820</td>\n",
              "      <td>0.000006</td>\n",
              "      <td>0.004670</td>\n",
              "      <td>6</td>\n",
              "      <td>0.0490</td>\n",
              "      <td>310067</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>94</th>\n",
              "      <td>0.362</td>\n",
              "      <td>-5.664</td>\n",
              "      <td>0.491</td>\n",
              "      <td>0.961</td>\n",
              "      <td>0.000009</td>\n",
              "      <td>0.024000</td>\n",
              "      <td>2</td>\n",
              "      <td>0.0857</td>\n",
              "      <td>153840</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>37</th>\n",
              "      <td>0.389</td>\n",
              "      <td>-12.226</td>\n",
              "      <td>0.366</td>\n",
              "      <td>0.487</td>\n",
              "      <td>0.000751</td>\n",
              "      <td>0.073600</td>\n",
              "      <td>2</td>\n",
              "      <td>0.0332</td>\n",
              "      <td>223373</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>63</th>\n",
              "      <td>0.649</td>\n",
              "      <td>-7.127</td>\n",
              "      <td>0.676</td>\n",
              "      <td>0.811</td>\n",
              "      <td>0.009060</td>\n",
              "      <td>0.003910</td>\n",
              "      <td>7</td>\n",
              "      <td>0.0269</td>\n",
              "      <td>355400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>340</th>\n",
              "      <td>0.763</td>\n",
              "      <td>-6.405</td>\n",
              "      <td>0.349</td>\n",
              "      <td>0.726</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.259000</td>\n",
              "      <td>1</td>\n",
              "      <td>0.2820</td>\n",
              "      <td>126346</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>261</th>\n",
              "      <td>0.845</td>\n",
              "      <td>-5.283</td>\n",
              "      <td>0.329</td>\n",
              "      <td>0.601</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.020500</td>\n",
              "      <td>1</td>\n",
              "      <td>0.1610</td>\n",
              "      <td>242013</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>224</th>\n",
              "      <td>0.751</td>\n",
              "      <td>-8.862</td>\n",
              "      <td>0.900</td>\n",
              "      <td>0.638</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.213000</td>\n",
              "      <td>7</td>\n",
              "      <td>0.2680</td>\n",
              "      <td>150047</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>173</th>\n",
              "      <td>0.921</td>\n",
              "      <td>-8.443</td>\n",
              "      <td>0.287</td>\n",
              "      <td>0.467</td>\n",
              "      <td>0.000238</td>\n",
              "      <td>0.014900</td>\n",
              "      <td>1</td>\n",
              "      <td>0.1190</td>\n",
              "      <td>191252</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>213</th>\n",
              "      <td>0.884</td>\n",
              "      <td>-7.442</td>\n",
              "      <td>0.342</td>\n",
              "      <td>0.559</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.023600</td>\n",
              "      <td>0</td>\n",
              "      <td>0.1200</td>\n",
              "      <td>232959</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>168</th>\n",
              "      <td>0.763</td>\n",
              "      <td>-7.312</td>\n",
              "      <td>0.250</td>\n",
              "      <td>0.572</td>\n",
              "      <td>0.001180</td>\n",
              "      <td>0.493000</td>\n",
              "      <td>11</td>\n",
              "      <td>0.0595</td>\n",
              "      <td>190472</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>148</th>\n",
              "      <td>0.873</td>\n",
              "      <td>-7.300</td>\n",
              "      <td>0.529</td>\n",
              "      <td>0.500</td>\n",
              "      <td>0.000010</td>\n",
              "      <td>0.114000</td>\n",
              "      <td>10</td>\n",
              "      <td>0.6790</td>\n",
              "      <td>161384</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>285</th>\n",
              "      <td>0.402</td>\n",
              "      <td>-9.139</td>\n",
              "      <td>0.315</td>\n",
              "      <td>0.483</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.329000</td>\n",
              "      <td>1</td>\n",
              "      <td>0.3450</td>\n",
              "      <td>231027</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>262</th>\n",
              "      <td>0.651</td>\n",
              "      <td>-5.153</td>\n",
              "      <td>0.594</td>\n",
              "      <td>0.833</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.020100</td>\n",
              "      <td>1</td>\n",
              "      <td>0.0847</td>\n",
              "      <td>254877</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>127</th>\n",
              "      <td>0.547</td>\n",
              "      <td>-3.146</td>\n",
              "      <td>0.901</td>\n",
              "      <td>0.987</td>\n",
              "      <td>0.006190</td>\n",
              "      <td>0.001910</td>\n",
              "      <td>8</td>\n",
              "      <td>0.0839</td>\n",
              "      <td>178627</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>271</th>\n",
              "      <td>0.760</td>\n",
              "      <td>-7.283</td>\n",
              "      <td>0.545</td>\n",
              "      <td>0.517</td>\n",
              "      <td>0.000001</td>\n",
              "      <td>0.234000</td>\n",
              "      <td>9</td>\n",
              "      <td>0.1100</td>\n",
              "      <td>215189</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>233</th>\n",
              "      <td>0.769</td>\n",
              "      <td>-4.064</td>\n",
              "      <td>0.490</td>\n",
              "      <td>0.627</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.394000</td>\n",
              "      <td>7</td>\n",
              "      <td>0.2620</td>\n",
              "      <td>164038</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>338</th>\n",
              "      <td>0.484</td>\n",
              "      <td>-8.701</td>\n",
              "      <td>0.137</td>\n",
              "      <td>0.541</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.027600</td>\n",
              "      <td>7</td>\n",
              "      <td>0.0370</td>\n",
              "      <td>169286</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>51</th>\n",
              "      <td>0.667</td>\n",
              "      <td>-9.339</td>\n",
              "      <td>0.657</td>\n",
              "      <td>0.655</td>\n",
              "      <td>0.000894</td>\n",
              "      <td>0.049100</td>\n",
              "      <td>2</td>\n",
              "      <td>0.0367</td>\n",
              "      <td>506400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>273</th>\n",
              "      <td>0.789</td>\n",
              "      <td>-7.942</td>\n",
              "      <td>0.343</td>\n",
              "      <td>0.524</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.212000</td>\n",
              "      <td>1</td>\n",
              "      <td>0.2730</td>\n",
              "      <td>147600</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>201</th>\n",
              "      <td>0.452</td>\n",
              "      <td>-7.848</td>\n",
              "      <td>0.365</td>\n",
              "      <td>0.559</td>\n",
              "      <td>0.000002</td>\n",
              "      <td>0.048100</td>\n",
              "      <td>6</td>\n",
              "      <td>0.0453</td>\n",
              "      <td>209480</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>97</th>\n",
              "      <td>0.469</td>\n",
              "      <td>-5.072</td>\n",
              "      <td>0.377</td>\n",
              "      <td>0.875</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.068500</td>\n",
              "      <td>4</td>\n",
              "      <td>0.0952</td>\n",
              "      <td>203533</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>317</th>\n",
              "      <td>0.804</td>\n",
              "      <td>-8.018</td>\n",
              "      <td>0.342</td>\n",
              "      <td>0.632</td>\n",
              "      <td>0.000134</td>\n",
              "      <td>0.001860</td>\n",
              "      <td>10</td>\n",
              "      <td>0.0726</td>\n",
              "      <td>217027</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>212</th>\n",
              "      <td>0.604</td>\n",
              "      <td>-5.979</td>\n",
              "      <td>0.287</td>\n",
              "      <td>0.673</td>\n",
              "      <td>0.000033</td>\n",
              "      <td>0.026800</td>\n",
              "      <td>1</td>\n",
              "      <td>0.0545</td>\n",
              "      <td>197573</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>104</th>\n",
              "      <td>0.263</td>\n",
              "      <td>-5.871</td>\n",
              "      <td>0.411</td>\n",
              "      <td>0.882</td>\n",
              "      <td>0.001110</td>\n",
              "      <td>0.000654</td>\n",
              "      <td>9</td>\n",
              "      <td>0.0681</td>\n",
              "      <td>520293</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>177</th>\n",
              "      <td>0.765</td>\n",
              "      <td>-5.566</td>\n",
              "      <td>0.434</td>\n",
              "      <td>0.688</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.633000</td>\n",
              "      <td>4</td>\n",
              "      <td>0.0841</td>\n",
              "      <td>229573</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>98</th>\n",
              "      <td>0.456</td>\n",
              "      <td>-6.856</td>\n",
              "      <td>0.428</td>\n",
              "      <td>0.915</td>\n",
              "      <td>0.000002</td>\n",
              "      <td>0.034400</td>\n",
              "      <td>11</td>\n",
              "      <td>0.0769</td>\n",
              "      <td>259800</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>286</th>\n",
              "      <td>0.722</td>\n",
              "      <td>-6.943</td>\n",
              "      <td>0.544</td>\n",
              "      <td>0.510</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.498000</td>\n",
              "      <td>6</td>\n",
              "      <td>0.0540</td>\n",
              "      <td>196429</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>95</th>\n",
              "      <td>0.610</td>\n",
              "      <td>-6.046</td>\n",
              "      <td>0.819</td>\n",
              "      <td>0.824</td>\n",
              "      <td>0.000002</td>\n",
              "      <td>0.013600</td>\n",
              "      <td>4</td>\n",
              "      <td>0.0534</td>\n",
              "      <td>210133</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>105</th>\n",
              "      <td>0.263</td>\n",
              "      <td>-6.189</td>\n",
              "      <td>0.504</td>\n",
              "      <td>0.922</td>\n",
              "      <td>0.001320</td>\n",
              "      <td>0.000029</td>\n",
              "      <td>9</td>\n",
              "      <td>0.0982</td>\n",
              "      <td>408853</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>279</th>\n",
              "      <td>0.800</td>\n",
              "      <td>-5.144</td>\n",
              "      <td>0.367</td>\n",
              "      <td>0.578</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.003810</td>\n",
              "      <td>4</td>\n",
              "      <td>0.0485</td>\n",
              "      <td>204665</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>347</th>\n",
              "      <td>0.621</td>\n",
              "      <td>-5.616</td>\n",
              "      <td>0.457</td>\n",
              "      <td>0.601</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.052200</td>\n",
              "      <td>6</td>\n",
              "      <td>0.1480</td>\n",
              "      <td>163636</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>209</th>\n",
              "      <td>0.880</td>\n",
              "      <td>-8.280</td>\n",
              "      <td>0.333</td>\n",
              "      <td>0.428</td>\n",
              "      <td>0.000051</td>\n",
              "      <td>0.149000</td>\n",
              "      <td>9</td>\n",
              "      <td>0.2060</td>\n",
              "      <td>172800</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>82</th>\n",
              "      <td>0.502</td>\n",
              "      <td>-5.175</td>\n",
              "      <td>0.259</td>\n",
              "      <td>0.890</td>\n",
              "      <td>0.011700</td>\n",
              "      <td>0.000147</td>\n",
              "      <td>4</td>\n",
              "      <td>0.0364</td>\n",
              "      <td>292880</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>204</th>\n",
              "      <td>0.852</td>\n",
              "      <td>-7.286</td>\n",
              "      <td>0.656</td>\n",
              "      <td>0.553</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.055900</td>\n",
              "      <td>1</td>\n",
              "      <td>0.1870</td>\n",
              "      <td>205879</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>45</th>\n",
              "      <td>0.295</td>\n",
              "      <td>-6.696</td>\n",
              "      <td>0.228</td>\n",
              "      <td>0.584</td>\n",
              "      <td>0.218000</td>\n",
              "      <td>0.000385</td>\n",
              "      <td>9</td>\n",
              "      <td>0.0345</td>\n",
              "      <td>271280</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>161</th>\n",
              "      <td>0.813</td>\n",
              "      <td>-5.541</td>\n",
              "      <td>0.547</td>\n",
              "      <td>0.808</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.006930</td>\n",
              "      <td>2</td>\n",
              "      <td>0.2860</td>\n",
              "      <td>192132</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>236</th>\n",
              "      <td>0.606</td>\n",
              "      <td>-4.269</td>\n",
              "      <td>0.307</td>\n",
              "      <td>0.775</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.262000</td>\n",
              "      <td>5</td>\n",
              "      <td>0.0671</td>\n",
              "      <td>228147</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>267</th>\n",
              "      <td>0.728</td>\n",
              "      <td>-3.585</td>\n",
              "      <td>0.890</td>\n",
              "      <td>0.727</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.012800</td>\n",
              "      <td>2</td>\n",
              "      <td>0.2060</td>\n",
              "      <td>171467</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>339</th>\n",
              "      <td>0.753</td>\n",
              "      <td>-5.943</td>\n",
              "      <td>0.745</td>\n",
              "      <td>0.652</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.444000</td>\n",
              "      <td>10</td>\n",
              "      <td>0.0753</td>\n",
              "      <td>123560</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>41</th>\n",
              "      <td>0.684</td>\n",
              "      <td>-12.590</td>\n",
              "      <td>0.784</td>\n",
              "      <td>0.481</td>\n",
              "      <td>0.000066</td>\n",
              "      <td>0.475000</td>\n",
              "      <td>2</td>\n",
              "      <td>0.0384</td>\n",
              "      <td>250000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>263</th>\n",
              "      <td>0.708</td>\n",
              "      <td>-4.825</td>\n",
              "      <td>0.895</td>\n",
              "      <td>0.840</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.138000</td>\n",
              "      <td>7</td>\n",
              "      <td>0.1810</td>\n",
              "      <td>193108</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
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            "text/plain": [
              "     danceability  loudness  valence  ...  key  speechiness  duration_ms\n",
              "158         0.776    -9.143    0.294  ...    0       0.2820       161000\n",
              "298         0.639    -8.145    0.235  ...   10       0.2670       193341\n",
              "299         0.647    -6.023    0.577  ...    6       0.1370       182338\n",
              "195         0.846    -8.059    0.441  ...    1       0.0576       208160\n",
              "183         0.721    -6.847    0.614  ...    7       0.3240       175294\n",
              "259         0.624    -4.261    0.141  ...    4       0.2550       176328\n",
              "330         0.886    -8.054    0.408  ...    4       0.3340       158692\n",
              "196         0.473    -6.474    0.615  ...    6       0.3330       234213\n",
              "69          0.456    -3.551    0.532  ...    3       0.0894       301227\n",
              "121         0.463    -7.950    0.550  ...   10       0.0419       375307\n",
              "275         0.729    -8.060    0.683  ...    8       0.2500       179831\n",
              "101         0.446    -5.004    0.595  ...    9       0.0508       363587\n",
              "92          0.511    -6.962    0.543  ...    6       0.0490       310067\n",
              "94          0.362    -5.664    0.491  ...    2       0.0857       153840\n",
              "37          0.389   -12.226    0.366  ...    2       0.0332       223373\n",
              "63          0.649    -7.127    0.676  ...    7       0.0269       355400\n",
              "340         0.763    -6.405    0.349  ...    1       0.2820       126346\n",
              "261         0.845    -5.283    0.329  ...    1       0.1610       242013\n",
              "224         0.751    -8.862    0.900  ...    7       0.2680       150047\n",
              "173         0.921    -8.443    0.287  ...    1       0.1190       191252\n",
              "213         0.884    -7.442    0.342  ...    0       0.1200       232959\n",
              "168         0.763    -7.312    0.250  ...   11       0.0595       190472\n",
              "148         0.873    -7.300    0.529  ...   10       0.6790       161384\n",
              "285         0.402    -9.139    0.315  ...    1       0.3450       231027\n",
              "262         0.651    -5.153    0.594  ...    1       0.0847       254877\n",
              "127         0.547    -3.146    0.901  ...    8       0.0839       178627\n",
              "271         0.760    -7.283    0.545  ...    9       0.1100       215189\n",
              "233         0.769    -4.064    0.490  ...    7       0.2620       164038\n",
              "338         0.484    -8.701    0.137  ...    7       0.0370       169286\n",
              "51          0.667    -9.339    0.657  ...    2       0.0367       506400\n",
              "273         0.789    -7.942    0.343  ...    1       0.2730       147600\n",
              "201         0.452    -7.848    0.365  ...    6       0.0453       209480\n",
              "97          0.469    -5.072    0.377  ...    4       0.0952       203533\n",
              "317         0.804    -8.018    0.342  ...   10       0.0726       217027\n",
              "212         0.604    -5.979    0.287  ...    1       0.0545       197573\n",
              "104         0.263    -5.871    0.411  ...    9       0.0681       520293\n",
              "177         0.765    -5.566    0.434  ...    4       0.0841       229573\n",
              "98          0.456    -6.856    0.428  ...   11       0.0769       259800\n",
              "286         0.722    -6.943    0.544  ...    6       0.0540       196429\n",
              "95          0.610    -6.046    0.819  ...    4       0.0534       210133\n",
              "105         0.263    -6.189    0.504  ...    9       0.0982       408853\n",
              "279         0.800    -5.144    0.367  ...    4       0.0485       204665\n",
              "347         0.621    -5.616    0.457  ...    6       0.1480       163636\n",
              "209         0.880    -8.280    0.333  ...    9       0.2060       172800\n",
              "82          0.502    -5.175    0.259  ...    4       0.0364       292880\n",
              "204         0.852    -7.286    0.656  ...    1       0.1870       205879\n",
              "45          0.295    -6.696    0.228  ...    9       0.0345       271280\n",
              "161         0.813    -5.541    0.547  ...    2       0.2860       192132\n",
              "236         0.606    -4.269    0.307  ...    5       0.0671       228147\n",
              "267         0.728    -3.585    0.890  ...    2       0.2060       171467\n",
              "339         0.753    -5.943    0.745  ...   10       0.0753       123560\n",
              "41          0.684   -12.590    0.784  ...    2       0.0384       250000\n",
              "263         0.708    -4.825    0.895  ...    7       0.1810       193108\n",
              "\n",
              "[53 rows x 9 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xb5berAfpZp9"
      },
      "source": [
        "y_test"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "312pbWMAumua"
      },
      "source": [
        "## Model Evaluation"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "JsxXC3SflL22"
      },
      "source": [
        "linreg = LinearRegression()\n",
        "linreg.fit(x_train, y_train)\n",
        "linreg_pred = linreg.predict(x_test)\n",
        "\n",
        "print('Mean squared error: %.2f' % mean_squared_error(y_test, linreg_pred))\n",
        "linreg_pred"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qTbTf3rfkMPd"
      },
      "source": [
        "knn = KNeighborsClassifier(3)\n",
        "knn.fit(x_train, y_train)\n",
        "knn_pred = knn.predict(x_test)\n",
        "\n",
        "score = accuracy_score(y_test, knn_pred) * 100\n",
        "print(\"Accuracy using Knn Tree: \", round(score, 2), \"%\")\n",
        "print('Mean squared error: %.2f' % mean_squared_error(y_test, knn_pred))"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0Pdd6mChlGv0"
      },
      "source": [
        "dtc = DecisionTreeClassifier(min_samples_split=100)\n",
        "dtc.fit(x_train, y_train)\n",
        "dtc_pred = dtc.predict(x_test)\n",
        "\n",
        "score = accuracy_score(y_test, dtc_pred) * 100\n",
        "print(\"Accuracy using Decision Tree: \", round(score, 2), \"%\")\n",
        "print('Mean squared error: %.2f' % mean_squared_error(y_test, dtc_pred))"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IHRTAVzSpd9T"
      },
      "source": [
        "rfc = RandomForestClassifier(n_jobs=1, random_state=1)\n",
        "rfc.fit(x_train, y_train)\n",
        "rfc_pred = rfc.predict(x_test)\n",
        "\n",
        "score = accuracy_score(y_test, rfc_pred) * 100\n",
        "print(\"Accuracy using Random Forest: \", round(score, 2), \"%\")\n",
        "print('Mean squared error: %.2f' % mean_squared_error(y_test, rfc_pred))"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "AFjnkJKJlhrO"
      },
      "source": [
        "ada = AdaBoostClassifier(n_estimators=100)\n",
        "ada.fit(x_train, y_train)\n",
        "ada_pred = ada.predict(x_test)\n",
        "\n",
        "score = accuracy_score(y_test, ada_pred) * 100\n",
        "print(\"Accuracy using Ada Boost: \", round(score, 2), \"%\")\n",
        "print('Mean squared error: %.2f' % mean_squared_error(y_test, ada_pred))"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Qs9ABJuAlirT"
      },
      "source": [
        "gbc = GradientBoostingClassifier(n_estimators=100, learning_rate=.1, max_depth=1, random_state=2)\n",
        "gbc.fit(x_train, y_train)\n",
        "gbc_pred = gbc.predict(x_test)\n",
        "\n",
        "score = accuracy_score(y_test, gbc_pred) * 100\n",
        "print(\"Accuracy using Gradient Boost: \", round(score, 2), \"%\")\n",
        "print('Mean squared error: %.2f' % mean_squared_error(y_test, gbc_pred))"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "iRHAcWzNsiyc"
      },
      "source": [
        "model = ada"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7zQVW9tqtd0A"
      },
      "source": [
        "## Generate Predictions"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_1OTu_cFo3qR"
      },
      "source": [
        "sourceData = pd.DataFrame(source_features)\n",
        "sourceData = sourceData[target_features]"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "7p6y4tcWo6xp",
        "outputId": "eed8495d-0a2f-4b7a-ac0d-3d2864ae63e9"
      },
      "source": [
        "sourceData"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "\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>danceability</th>\n",
              "      <th>loudness</th>\n",
              "      <th>valence</th>\n",
              "      <th>energy</th>\n",
              "      <th>instrumentalness</th>\n",
              "      <th>acousticness</th>\n",
              "      <th>key</th>\n",
              "      <th>speechiness</th>\n",
              "      <th>duration_ms</th>\n",
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              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
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              "    <tr>\n",
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              "    <tr>\n",
              "      <th>3</th>\n",
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              "      <td>0.655</td>\n",
              "      <td>0.704</td>\n",
              "      <td>0.000488</td>\n",
              "      <td>0.1880</td>\n",
              "      <td>7</td>\n",
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              "    <tr>\n",
              "      <th>4</th>\n",
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              "      <td>0.678</td>\n",
              "      <td>0.816</td>\n",
              "      <td>0.018100</td>\n",
              "      <td>0.1680</td>\n",
              "      <td>2</td>\n",
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              "    <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",
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              "    <tr>\n",
              "      <th>173</th>\n",
              "      <td>0.572</td>\n",
              "      <td>-8.190</td>\n",
              "      <td>0.662</td>\n",
              "      <td>0.759</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0303</td>\n",
              "      <td>10</td>\n",
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              "    <tr>\n",
              "      <th>174</th>\n",
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              "      <td>0.061600</td>\n",
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              "      <td>1</td>\n",
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              "      <td>261001</td>\n",
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              "    <tr>\n",
              "      <th>175</th>\n",
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              "      <td>180000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>176</th>\n",
              "      <td>0.838</td>\n",
              "      <td>-6.525</td>\n",
              "      <td>0.971</td>\n",
              "      <td>0.919</td>\n",
              "      <td>0.000125</td>\n",
              "      <td>0.0533</td>\n",
              "      <td>2</td>\n",
              "      <td>0.0445</td>\n",
              "      <td>264000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>177</th>\n",
              "      <td>0.710</td>\n",
              "      <td>-7.904</td>\n",
              "      <td>0.654</td>\n",
              "      <td>0.661</td>\n",
              "      <td>0.000007</td>\n",
              "      <td>0.6500</td>\n",
              "      <td>1</td>\n",
              "      <td>0.0461</td>\n",
              "      <td>213205</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>178 rows × 9 columns</p>\n",
              "</div>\n",
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              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
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              "\n",
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              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
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              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "     danceability  loudness  valence  ...  key  speechiness  duration_ms\n",
              "0           0.511   -10.407    0.498  ...    0       0.0429       393667\n",
              "1           0.454    -4.126    0.488  ...    5       0.0831       154133\n",
              "2           0.535   -11.159    0.917  ...    2       0.0319       158573\n",
              "3           0.298    -9.905    0.655  ...    7       0.0366       302120\n",
              "4           0.660    -6.610    0.678  ...    2       0.0299       263040\n",
              "..            ...       ...      ...  ...  ...          ...          ...\n",
              "173         0.572    -8.190    0.662  ...   10       0.0583       207849\n",
              "174         0.683    -7.721    0.290  ...    1       0.0286       261001\n",
              "175         0.798    -4.534    0.782  ...    5       0.0251       180000\n",
              "176         0.838    -6.525    0.971  ...    2       0.0445       264000\n",
              "177         0.710    -7.904    0.654  ...    1       0.0461       213205\n",
              "\n",
              "[178 rows x 9 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 34
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "kYpvHxkVpcYZ"
      },
      "source": [
        "pred = model.predict(sourceData)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "oIe54z9npnog",
        "outputId": "62f42da1-7682-4ab7-eff5-4e094663f2fb"
      },
      "source": [
        "source_playlist_songs = source_playlist['tracks']['items']\n",
        "\n",
        "print(\"ACCEPTED\")\n",
        "\n",
        "i = 0\n",
        "for prediction in pred:\n",
        "    if prediction == 1:\n",
        "        song_title = source_playlist_songs[i + 1]['track']['name']\n",
        "        artist_name = source_playlist_songs[i + 1]['track']['artists'][0]['name']\n",
        "        print (\"Song: \" + song_title + \", By: \"+ artist_name)\n",
        "    i = i + 1\n",
        "\n",
        "\n",
        "print(\"REJECTED\")\n",
        "\n",
        "i = 0\n",
        "for prediction in pred:\n",
        "    if prediction == 0:\n",
        "        song_title = source_playlist_songs[i + 1]['track']['name']\n",
        "        artist_name = source_playlist_songs[i + 1]['track']['artists'][0]['name']\n",
        "        print (\"Song: \" + song_title + \", By: \"+ artist_name)\n",
        "    i = i + 1"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "ACCEPTED\n",
            "Song: Shout, By: Tears For Fears\n",
            "Song: Fully Alive, By: Flyleaf\n",
            "Song: Broken, By: Tears For Fears\n",
            "Song: Head Over Heels / Broken, By: Tears For Fears\n",
            "Song: Don't You (Forget About Me), By: Simple Minds\n",
            "Song: Animal, By: Def Leppard\n",
            "Song: Mad World (Feat. Michael Andrews), By: Gary Jules\n",
            "Song: Thing For You, By: Randall Bramblett\n",
            "Song: More Than This, By: Roxy Music\n",
            "Song: cherry blossom, By: slenderbodies\n",
            "Song: out 4 a breather, By: dad sports\n",
            "Song: Two Hearts, By: Zola Blood\n",
            "Song: Nightfall, By: Mimi Page\n",
            "Song: Secunda, By: Jeremy Soule\n",
            "Song: The World Retreats, By: David O'Dowda\n",
            "Song: Atlas - From “The Hunger Games: Catching Fire” Soundtrack, By: Coldplay\n",
            "Song: Weird Fishes/ Arpeggi, By: Radiohead\n",
            "Song: Tur, By: Marco Egeberg\n",
            "Song: With you, By: Cécile Corbel\n",
            "Song: Exploration, By: Bruno Coulais\n",
            "Song: Broken Sleep, By: Agnes Obel\n",
            "Song: Midnight, By: Coldplay\n",
            "Song: Blood Pressurize, By: RemoteTreeChildren\n",
            "Song: Under The Pressure, By: The War On Drugs\n",
            "Song: Round and Round, By: Ratt\n",
            "Song: Everybody Wants To Rule The World, By: Tears For Fears\n",
            "Song: Eminence Front, By: The Who\n",
            "Song: Grab as Much (as you can), By: The Black Angels\n",
            "Song: Take on Me, By: a-ha\n",
            "Song: Metal Gods, By: Judas Priest\n",
            "Song: Wake Me Up Before You Go-Go, By: Wham!\n",
            "Song: Mad World, By: Tears For Fears\n",
            "Song: Hysteria, By: Def Leppard\n",
            "Song: Who Are You, By: The Who\n",
            "Song: Helter Skelter - Live, By: U2\n",
            "Song: Pale Shelter - 2nd Single Version, By: Tears For Fears\n",
            "Song: Another One Bites The Dust - Remastered 2011, By: Queen\n",
            "Song: Armageddon It, By: Def Leppard\n",
            "Song: Careless Whisper, By: George Michael\n",
            "Song: Strangers, By: Roosevelt\n",
            "Song: Photograph, By: Def Leppard\n",
            "Song: Walk This Way, By: Aerosmith\n",
            "Song: Where The Streets Have No Name - Remastered, By: U2\n",
            "Song: Helter Skelter - Outtake - 1975, By: Aerosmith\n",
            "Song: Dancing Queen, By: ABBA\n",
            "Song: BoJack's Theme, By: Patrick Carney\n",
            "Song: Cold Cold Man, By: Saint Motel\n",
            "Song: A Horse with No Name, By: Patrick Carney\n",
            "Song: Back in the 90's, By: Grouplove\n",
            "Song: Stars (Live at Montreux), By: Nina Simone\n",
            "Song: A Horse with No Name, By: America\n",
            "Song: Hallway, By: Jesse Novak\n",
            "Song: I Will Always Think of You, By: Jane Krakowski\n",
            "Song: BoJack's Theme (Full Length), By: Patrick Carney\n",
            "Song: Mr. Peanutbutter's House Theme, By: Jesse Novak\n",
            "Song: Fragments of Time (feat. Todd Edwards), By: Daft Punk\n",
            "Song: For the Damaged Coda, By: Blonde Redhead\n",
            "Song: It’s A Beautiful World, By: Noel Gallagher's High Flying Birds\n",
            "Song: There She Goes, By: Circa Waves\n",
            "Song: Love Song, By: 311\n",
            "Song: Everlong, By: Estrada\n",
            "Song: Give It Time, By: Hoops\n",
            "Song: Far Behind, By: Candlebox\n",
            "Song: Secret Smile, By: Semisonic\n",
            "Song: Familiar, By: Agnes Obel\n",
            "Song: Strawberita, By: Remo Drive\n",
            "Song: The Girl, By: Hellberg\n",
            "Song: Acetone, By: Landon Conrath\n",
            "Song: Paint California, By: NoMBe\n",
            "Song: Night Sky, By: CHVRCHES\n",
            "Song: Entertainment, By: Phoenix\n",
            "Song: And She Was, By: Talking Heads\n",
            "Song: Dreamland, By: Glass Animals\n",
            "Song: You Took The Words Right Out of My Mouth (Hot Summer Night), By: Meat Loaf\n",
            "Song: Move On Up, By: Curtis Mayfield\n",
            "Song: In Too Deep, By: Sum 41\n",
            "Song: Learn to Fly, By: Foo Fighters\n",
            "Song: Even Flow, By: Pearl Jam\n",
            "Song: Daughter - Live, By: Pearl Jam\n",
            "Song: The Rockafeller Skank, By: Fatboy Slim\n",
            "Song: Your Woman, By: White Town\n",
            "Song: Making A Fire, By: Foo Fighters\n",
            "Song: Luv(sic.) pt3 (feat. Shing02), By: Nujabes\n",
            "Song: No Rain, By: Blind Melon\n",
            "Song: Never Let You Go - 2008 Remaster, By: Third Eye Blind\n",
            "Song: Flagpole Sitta, By: Harvey Danger\n",
            "Song: What Happened To Us?, By: Shura\n",
            "Song: Centipede - 12\" Version, By: Rebbie Jackson\n",
            "Song: Swing Swing, By: ayokay\n",
            "Song: Is It Any Wonder?, By: Keane\n",
            "Song: Take A Picture, By: Filter\n",
            "Song: Fire In The Sky, By: Anderson .Paak\n",
            "Song: Senior Skip Day, By: Mac Miller\n",
            "Song: Pride (In The Name Of Love) - Remastered 2009, By: U2\n",
            "Song: Halfway Up, By: The Brook & The Bluff\n",
            "Song: Is It True, By: Tame Impala\n",
            "Song: Is It True, By: Tame Impala\n",
            "Song: Misnomer, By: The Brook & The Bluff\n",
            "Song: Everything Is Just a Mess, By: The Brook & The Bluff\n",
            "Song: Shelby, By: The Brook & The Bluff\n",
            "Song: Off the Lawn, By: The Brook & The Bluff\n",
            "Song: Pastels, By: The Brook & The Bluff\n",
            "Song: Hallways, By: The Brook & The Bluff\n",
            "Song: Halfway Up - Lonely Version, By: The Brook & The Bluff\n",
            "Song: Rush, By: The Brook & The Bluff\n",
            "Song: In The Waiting Line, By: Zero 7\n",
            "Song: Horizon, By: Nujabes\n",
            "Song: Lovesong - 2010 Remaster, By: The Cure\n",
            "Song: Close To You, By: Dayglow\n",
            "Song: All About You (feat. Foster The People), By: The Knocks\n",
            "Song: Underneath My Skin, By: The Band CAMINO\n",
            "Song: Little Sheets, By: The Brook & The Bluff\n",
            "Song: We Cut the Night, By: AaRON\n",
            "Song: Moonsong, By: Adrian Von Ziegler\n",
            "Song: The Boys Of Summer, By: Don Henley\n",
            "Song: Kahlil Gibran, By: STRFKR\n",
            "Song: Call Me, By: Blondie\n",
            "Song: Do You Believe In Love, By: Huey Lewis & The News\n",
            "Song: Tubthumping, By: Chumbawamba\n",
            "Song: Your Love, By: The Outfield\n",
            "Song: wading through the wetlands, By: santpoort\n",
            "Song: Search for More, By: From Indian Lakes\n",
            "Song: F.O.M.O., By: Your Neighbors\n",
            "Song: Lovesong, By: Adele\n",
            "Song: Gone!, By: Rightfield\n",
            "Song: If Only for Tonight, By: Vacation Manor\n",
            "Song: On My Knees, By: RÜFÜS DU SOL\n",
            "Song: Senegal, By: j. pastel\n",
            "REJECTED\n",
            "Song: Butterflies, By: Michael Jackson\n",
            "Song: Bake Sale (feat. Travis Scott), By: Wiz Khalifa\n",
            "Song: Don't You (Forget About Me), By: David Cook\n",
            "Song: CASINO, By: Ashton Travis\n",
            "Song: favorable colours, By: slenderbodies\n",
            "Song: Outside, By: Weston Estate\n",
            "Song: Diamonds and Rust, By: Judas Priest\n",
            "Song: Secrets, By: The Weeknd\n",
            "Song: Mo Money Mo Problems (feat. Puff Daddy & Mase) - 2014 Remaster, By: The Notorious B.I.G.\n",
            "Song: Worst Behavior, By: Drake\n",
            "Song: Neck Of The Woods, By: Birdman\n",
            "Song: Mob Ties, By: Drake\n",
            "Song: Sagittarius, By: 88GLAM\n",
            "Song: floating high, By: B-Side\n",
            "Song: The Difference, By: Flume\n",
            "Song: Napkins, By: RIZ LA VIE\n",
            "Song: SUNDOWN, By: Jack Harlow\n",
            "Song: Honey, By: Rook Monroe\n",
            "Song: Waka Waka (This Time for Africa) [The Official 2010 FIFA World Cup (TM) Song] (feat. Freshlyground), By: Shakira\n",
            "Song: Solar Power, By: Lorde\n",
            "Song: Ocean Avenue, By: Yellowcard\n",
            "Song: Essence (feat. Tems), By: WizKid\n",
            "Song: Fire for You, By: Cannons\n",
            "Song: Ain't No Rest for the Wicked, By: Cage The Elephant\n",
            "Song: Take My Breath, By: The Weeknd\n",
            "Song: Tighten Up, By: Piano Tribute Players\n",
            "Song: Skin and Bones, By: Cage The Elephant\n",
            "Song: The Moment, By: THEY.\n",
            "Song: family ties (with Kendrick Lamar), By: Baby Keem\n",
            "Song: Rich N****z, By: J. Cole\n",
            "Song: durag activity (with Travis Scott), By: Baby Keem\n",
            "Song: N 2 Deep, By: Drake\n",
            "Song: Ghostface Killers (feat. Travis Scott), By: 21 Savage\n",
            "Song: Medication, By: Juicy J\n",
            "Song: We Major, By: Kanye West\n",
            "Song: Mi Gna (feat. Hayko) - Maître Gims Remix, By: GIMS\n",
            "Song: Chelsea Dagger, By: The Fratellis\n",
            "Song: Bambi, By: Hippo Campus\n",
            "Song: Reality In Motion - GUM Remix, By: Tame Impala\n",
            "Song: Black Mambo, By: Glass Animals\n",
            "Song: Stoked, By: Weston Estate\n",
            "Song: Big Poppa - 2005 Remaster, By: The Notorious B.I.G.\n",
            "Song: Take Back the Night, By: Justin Timberlake\n",
            "Song: Hot Blooded, By: Foreigner\n",
            "Song: The Way You Make Me Feel - 2012 Remaster, By: Michael Jackson\n",
            "Song: EAT SPIT! (feat. Royal & the Serpent), By: Slush Puppy\n",
            "Song: Feelings, By: LEO ISLO\n",
            "Song: Chicken, By: Your Neighbors\n",
            "Song: Jolie, By: Rook Monroe\n",
            "Song: summer nights, By: The Millennial Club\n"
          ]
        }
      ]
    }
  ]
}