Spotify_Analysis.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "C-Dx7bYyHUG3"
      },
      "source": [
        ""
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from google.colab import drive\n",
        "drive.mount(\"/content/drive\")\n",
        "import os \n",
        "os.chdir(\"/content/drive/MyDrive/Courses/cmpe 251/spotify\")\n",
        "os.listdir()"
      ],
      "metadata": {
        "id": "yXaorOH7HwsF"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "SDiWstAuHUG8"
      },
      "outputs": [],
      "source": [
        ""
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "pRyZhbn3HUG9"
      },
      "outputs": [],
      "source": [
        "import pandas as pd"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "G_boTA2GHUG-"
      },
      "outputs": [],
      "source": ["# get your spotify data from https://www.kaggle.com/vatsalmavani/music-recommendation-system-using-spotify-dataset/data","\n",
        "df=pd.read_csv('spotify_data.csv')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Xb0nkcyDHUG-",
        "outputId": "c49eabcf-eb42-4ec3-aa93-d89716bfdd15"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 169909 entries, 0 to 169908\n",
            "Data columns (total 19 columns):\n",
            " #   Column            Non-Null Count   Dtype  \n",
            "---  ------            --------------   -----  \n",
            " 0   acousticness      169909 non-null  float64\n",
            " 1   artists           169909 non-null  object \n",
            " 2   danceability      169909 non-null  float64\n",
            " 3   duration_ms       169909 non-null  int64  \n",
            " 4   energy            169909 non-null  float64\n",
            " 5   explicit          169909 non-null  int64  \n",
            " 6   id                169909 non-null  object \n",
            " 7   instrumentalness  169909 non-null  float64\n",
            " 8   key               169909 non-null  int64  \n",
            " 9   liveness          169909 non-null  float64\n",
            " 10  loudness          169909 non-null  float64\n",
            " 11  mode              169909 non-null  int64  \n",
            " 12  name              169909 non-null  object \n",
            " 13  popularity        169909 non-null  int64  \n",
            " 14  release_date      169909 non-null  object \n",
            " 15  speechiness       169909 non-null  float64\n",
            " 16  tempo             169909 non-null  float64\n",
            " 17  valence           169909 non-null  float64\n",
            " 18  year              169909 non-null  int64  \n",
            "dtypes: float64(9), int64(6), object(4)\n",
            "memory usage: 24.6+ MB\n"
          ]
        }
      ],
      "source": [
        "df.info()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "VAw3dNNAHUG_",
        "outputId": "e73ad194-8a23-43b9-9d00-26fc2e140e80"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "acousticness        0\n",
              "artists             0\n",
              "danceability        0\n",
              "duration_ms         0\n",
              "energy              0\n",
              "explicit            0\n",
              "id                  0\n",
              "instrumentalness    0\n",
              "key                 0\n",
              "liveness            0\n",
              "loudness            0\n",
              "mode                0\n",
              "name                0\n",
              "popularity          0\n",
              "release_date        0\n",
              "speechiness         0\n",
              "tempo               0\n",
              "valence             0\n",
              "year                0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ],
      "source": [
        "df.isna().sum()"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 476
        },
        "id": "iQGTBesSI07T",
        "outputId": "529f0250-3f13-42d4-abbd-f4eefe567713"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-66b918af-faac-4564-94c4-4530c8f65440\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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>acousticness</th>\n",
              "      <th>artists</th>\n",
              "      <th>danceability</th>\n",
              "      <th>duration_ms</th>\n",
              "      <th>energy</th>\n",
              "      <th>explicit</th>\n",
              "      <th>id</th>\n",
              "      <th>instrumentalness</th>\n",
              "      <th>key</th>\n",
              "      <th>liveness</th>\n",
              "      <th>loudness</th>\n",
              "      <th>mode</th>\n",
              "      <th>name</th>\n",
              "      <th>popularity</th>\n",
              "      <th>release_date</th>\n",
              "      <th>speechiness</th>\n",
              "      <th>tempo</th>\n",
              "      <th>valence</th>\n",
              "      <th>year</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0.995</td>\n",
              "      <td>['Carl Woitschach']</td>\n",
              "      <td>0.708</td>\n",
              "      <td>158648</td>\n",
              "      <td>0.1950</td>\n",
              "      <td>0</td>\n",
              "      <td>6KbQ3uYMLKb5jDxLF7wYDD</td>\n",
              "      <td>0.563</td>\n",
              "      <td>10</td>\n",
              "      <td>0.1510</td>\n",
              "      <td>-12.428</td>\n",
              "      <td>1</td>\n",
              "      <td>Singende Bataillone 1. Teil</td>\n",
              "      <td>0</td>\n",
              "      <td>1928</td>\n",
              "      <td>0.0506</td>\n",
              "      <td>118.469</td>\n",
              "      <td>0.7790</td>\n",
              "      <td>1928</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0.994</td>\n",
              "      <td>['Robert Schumann', 'Vladimir Horowitz']</td>\n",
              "      <td>0.379</td>\n",
              "      <td>282133</td>\n",
              "      <td>0.0135</td>\n",
              "      <td>0</td>\n",
              "      <td>6KuQTIu1KoTTkLXKrwlLPV</td>\n",
              "      <td>0.901</td>\n",
              "      <td>8</td>\n",
              "      <td>0.0763</td>\n",
              "      <td>-28.454</td>\n",
              "      <td>1</td>\n",
              "      <td>Fantasiestücke, Op. 111: Più tosto lento</td>\n",
              "      <td>0</td>\n",
              "      <td>1928</td>\n",
              "      <td>0.0462</td>\n",
              "      <td>83.972</td>\n",
              "      <td>0.0767</td>\n",
              "      <td>1928</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0.604</td>\n",
              "      <td>['Seweryn Goszczyński']</td>\n",
              "      <td>0.749</td>\n",
              "      <td>104300</td>\n",
              "      <td>0.2200</td>\n",
              "      <td>0</td>\n",
              "      <td>6L63VW0PibdM1HDSBoqnoM</td>\n",
              "      <td>0.000</td>\n",
              "      <td>5</td>\n",
              "      <td>0.1190</td>\n",
              "      <td>-19.924</td>\n",
              "      <td>0</td>\n",
              "      <td>Chapter 1.18 - Zamek kaniowski</td>\n",
              "      <td>0</td>\n",
              "      <td>1928</td>\n",
              "      <td>0.9290</td>\n",
              "      <td>107.177</td>\n",
              "      <td>0.8800</td>\n",
              "      <td>1928</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0.995</td>\n",
              "      <td>['Francisco Canaro']</td>\n",
              "      <td>0.781</td>\n",
              "      <td>180760</td>\n",
              "      <td>0.1300</td>\n",
              "      <td>0</td>\n",
              "      <td>6M94FkXd15sOAOQYRnWPN8</td>\n",
              "      <td>0.887</td>\n",
              "      <td>1</td>\n",
              "      <td>0.1110</td>\n",
              "      <td>-14.734</td>\n",
              "      <td>0</td>\n",
              "      <td>Bebamos Juntos - Instrumental (Remasterizado)</td>\n",
              "      <td>0</td>\n",
              "      <td>1928-09-25</td>\n",
              "      <td>0.0926</td>\n",
              "      <td>108.003</td>\n",
              "      <td>0.7200</td>\n",
              "      <td>1928</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0.990</td>\n",
              "      <td>['Frédéric Chopin', 'Vladimir Horowitz']</td>\n",
              "      <td>0.210</td>\n",
              "      <td>687733</td>\n",
              "      <td>0.2040</td>\n",
              "      <td>0</td>\n",
              "      <td>6N6tiFZ9vLTSOIxkj8qKrd</td>\n",
              "      <td>0.908</td>\n",
              "      <td>11</td>\n",
              "      <td>0.0980</td>\n",
              "      <td>-16.829</td>\n",
              "      <td>1</td>\n",
              "      <td>Polonaise-Fantaisie in A-Flat Major, Op. 61</td>\n",
              "      <td>1</td>\n",
              "      <td>1928</td>\n",
              "      <td>0.0424</td>\n",
              "      <td>62.149</td>\n",
              "      <td>0.0693</td>\n",
              "      <td>1928</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-66b918af-faac-4564-94c4-4530c8f65440')\"\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",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <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",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      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",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-66b918af-faac-4564-94c4-4530c8f65440 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-66b918af-faac-4564-94c4-4530c8f65440');\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",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "   acousticness                                   artists  ...  valence  year\n",
              "0         0.995                       ['Carl Woitschach']  ...   0.7790  1928\n",
              "1         0.994  ['Robert Schumann', 'Vladimir Horowitz']  ...   0.0767  1928\n",
              "2         0.604                   ['Seweryn Goszczyński']  ...   0.8800  1928\n",
              "3         0.995                      ['Francisco Canaro']  ...   0.7200  1928\n",
              "4         0.990  ['Frédéric Chopin', 'Vladimir Horowitz']  ...   0.0693  1928\n",
              "\n",
              "[5 rows x 19 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.columns"
      ],
      "metadata": {
        "id": "lbDqkcTMI0-d",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "4189a262-fbf1-4f7a-acb2-52b35dabeca6"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['acousticness', 'artists', 'danceability', 'duration_ms', 'energy',\n",
              "       'explicit', 'id', 'instrumentalness', 'key', 'liveness', 'loudness',\n",
              "       'mode', 'name', 'popularity', 'release_date', 'speechiness', 'tempo',\n",
              "       'valence', 'year'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 33
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sel=['acousticness', 'danceability', 'energy', 'instrumentalness', 'liveness', 'loudness','speechiness', 'tempo', 'valence']"
      ],
      "metadata": {
        "id": "Pqtyu1ysI1BM"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df2= df[sel]"
      ],
      "metadata": {
        "id": "HiMkw2v5I1ES"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df2"
      ],
      "metadata": {
        "id": "r-PWae3sI1HP",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "outputId": "33222d62-153a-47fc-a54a-354a681e52ee"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-6ad9974c-2c16-4ddf-a243-351e61e6e8a0\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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>acousticness</th>\n",
              "      <th>danceability</th>\n",
              "      <th>energy</th>\n",
              "      <th>instrumentalness</th>\n",
              "      <th>liveness</th>\n",
              "      <th>loudness</th>\n",
              "      <th>speechiness</th>\n",
              "      <th>tempo</th>\n",
              "      <th>valence</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0.9950</td>\n",
              "      <td>0.708</td>\n",
              "      <td>0.1950</td>\n",
              "      <td>0.563000</td>\n",
              "      <td>0.1510</td>\n",
              "      <td>-12.428</td>\n",
              "      <td>0.0506</td>\n",
              "      <td>118.469</td>\n",
              "      <td>0.7790</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0.9940</td>\n",
              "      <td>0.379</td>\n",
              "      <td>0.0135</td>\n",
              "      <td>0.901000</td>\n",
              "      <td>0.0763</td>\n",
              "      <td>-28.454</td>\n",
              "      <td>0.0462</td>\n",
              "      <td>83.972</td>\n",
              "      <td>0.0767</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0.6040</td>\n",
              "      <td>0.749</td>\n",
              "      <td>0.2200</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.1190</td>\n",
              "      <td>-19.924</td>\n",
              "      <td>0.9290</td>\n",
              "      <td>107.177</td>\n",
              "      <td>0.8800</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0.9950</td>\n",
              "      <td>0.781</td>\n",
              "      <td>0.1300</td>\n",
              "      <td>0.887000</td>\n",
              "      <td>0.1110</td>\n",
              "      <td>-14.734</td>\n",
              "      <td>0.0926</td>\n",
              "      <td>108.003</td>\n",
              "      <td>0.7200</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0.9900</td>\n",
              "      <td>0.210</td>\n",
              "      <td>0.2040</td>\n",
              "      <td>0.908000</td>\n",
              "      <td>0.0980</td>\n",
              "      <td>-16.829</td>\n",
              "      <td>0.0424</td>\n",
              "      <td>62.149</td>\n",
              "      <td>0.0693</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>169904</th>\n",
              "      <td>0.1730</td>\n",
              "      <td>0.875</td>\n",
              "      <td>0.4430</td>\n",
              "      <td>0.000032</td>\n",
              "      <td>0.0891</td>\n",
              "      <td>-7.461</td>\n",
              "      <td>0.1430</td>\n",
              "      <td>100.012</td>\n",
              "      <td>0.3060</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>169905</th>\n",
              "      <td>0.0167</td>\n",
              "      <td>0.719</td>\n",
              "      <td>0.3850</td>\n",
              "      <td>0.031300</td>\n",
              "      <td>0.1110</td>\n",
              "      <td>-10.907</td>\n",
              "      <td>0.0403</td>\n",
              "      <td>128.000</td>\n",
              "      <td>0.2700</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>169906</th>\n",
              "      <td>0.5380</td>\n",
              "      <td>0.514</td>\n",
              "      <td>0.5390</td>\n",
              "      <td>0.002330</td>\n",
              "      <td>0.1080</td>\n",
              "      <td>-9.332</td>\n",
              "      <td>0.1050</td>\n",
              "      <td>123.700</td>\n",
              "      <td>0.1530</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>169907</th>\n",
              "      <td>0.0714</td>\n",
              "      <td>0.646</td>\n",
              "      <td>0.7610</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.2220</td>\n",
              "      <td>-2.557</td>\n",
              "      <td>0.0385</td>\n",
              "      <td>129.916</td>\n",
              "      <td>0.4720</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>169908</th>\n",
              "      <td>0.1090</td>\n",
              "      <td>0.512</td>\n",
              "      <td>0.4280</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.1050</td>\n",
              "      <td>-7.387</td>\n",
              "      <td>0.0271</td>\n",
              "      <td>80.588</td>\n",
              "      <td>0.3660</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>169909 rows × 9 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-6ad9974c-2c16-4ddf-a243-351e61e6e8a0')\"\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",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <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",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      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",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-6ad9974c-2c16-4ddf-a243-351e61e6e8a0 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-6ad9974c-2c16-4ddf-a243-351e61e6e8a0');\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",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "        acousticness  danceability  energy  ...  speechiness    tempo  valence\n",
              "0             0.9950         0.708  0.1950  ...       0.0506  118.469   0.7790\n",
              "1             0.9940         0.379  0.0135  ...       0.0462   83.972   0.0767\n",
              "2             0.6040         0.749  0.2200  ...       0.9290  107.177   0.8800\n",
              "3             0.9950         0.781  0.1300  ...       0.0926  108.003   0.7200\n",
              "4             0.9900         0.210  0.2040  ...       0.0424   62.149   0.0693\n",
              "...              ...           ...     ...  ...          ...      ...      ...\n",
              "169904        0.1730         0.875  0.4430  ...       0.1430  100.012   0.3060\n",
              "169905        0.0167         0.719  0.3850  ...       0.0403  128.000   0.2700\n",
              "169906        0.5380         0.514  0.5390  ...       0.1050  123.700   0.1530\n",
              "169907        0.0714         0.646  0.7610  ...       0.0385  129.916   0.4720\n",
              "169908        0.1090         0.512  0.4280  ...       0.0271   80.588   0.3660\n",
              "\n",
              "[169909 rows x 9 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 37
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.cluster import KMeans\n",
        "kmeans = KMeans(n_clusters=5, random_state=0).fit(df2)\n",
        "kmeans.labels_"
      ],
      "metadata": {
        "id": "eU01ICqJI1J5",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "23089148-06d0-460f-acf9-3d8291e98ad7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([0, 1, 3, ..., 0, 0, 1], dtype=int32)"
            ]
          },
          "metadata": {},
          "execution_count": 38
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df2[\"cl\"]=kmeans.labels_"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "BvrXHLdYMdRh",
        "outputId": "6616b561-3e25-4c93-dbae-f5c93d986c3f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:1: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \"\"\"Entry point for launching an IPython kernel.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df2"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "U_ZXmnSAuQID",
        "outputId": "92d04b4e-90e7-4d5d-b041-6e8d471ac88b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-bf494543-8fc3-4227-8f10-945c87727396\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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>acousticness</th>\n",
              "      <th>danceability</th>\n",
              "      <th>energy</th>\n",
              "      <th>instrumentalness</th>\n",
              "      <th>liveness</th>\n",
              "      <th>loudness</th>\n",
              "      <th>speechiness</th>\n",
              "      <th>tempo</th>\n",
              "      <th>valence</th>\n",
              "      <th>cl</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0.9950</td>\n",
              "      <td>0.708</td>\n",
              "      <td>0.1950</td>\n",
              "      <td>0.563000</td>\n",
              "      <td>0.1510</td>\n",
              "      <td>-12.428</td>\n",
              "      <td>0.0506</td>\n",
              "      <td>118.469</td>\n",
              "      <td>0.7790</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0.9940</td>\n",
              "      <td>0.379</td>\n",
              "      <td>0.0135</td>\n",
              "      <td>0.901000</td>\n",
              "      <td>0.0763</td>\n",
              "      <td>-28.454</td>\n",
              "      <td>0.0462</td>\n",
              "      <td>83.972</td>\n",
              "      <td>0.0767</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0.6040</td>\n",
              "      <td>0.749</td>\n",
              "      <td>0.2200</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.1190</td>\n",
              "      <td>-19.924</td>\n",
              "      <td>0.9290</td>\n",
              "      <td>107.177</td>\n",
              "      <td>0.8800</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0.9950</td>\n",
              "      <td>0.781</td>\n",
              "      <td>0.1300</td>\n",
              "      <td>0.887000</td>\n",
              "      <td>0.1110</td>\n",
              "      <td>-14.734</td>\n",
              "      <td>0.0926</td>\n",
              "      <td>108.003</td>\n",
              "      <td>0.7200</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0.9900</td>\n",
              "      <td>0.210</td>\n",
              "      <td>0.2040</td>\n",
              "      <td>0.908000</td>\n",
              "      <td>0.0980</td>\n",
              "      <td>-16.829</td>\n",
              "      <td>0.0424</td>\n",
              "      <td>62.149</td>\n",
              "      <td>0.0693</td>\n",
              "      <td>1</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",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>169904</th>\n",
              "      <td>0.1730</td>\n",
              "      <td>0.875</td>\n",
              "      <td>0.4430</td>\n",
              "      <td>0.000032</td>\n",
              "      <td>0.0891</td>\n",
              "      <td>-7.461</td>\n",
              "      <td>0.1430</td>\n",
              "      <td>100.012</td>\n",
              "      <td>0.3060</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>169905</th>\n",
              "      <td>0.0167</td>\n",
              "      <td>0.719</td>\n",
              "      <td>0.3850</td>\n",
              "      <td>0.031300</td>\n",
              "      <td>0.1110</td>\n",
              "      <td>-10.907</td>\n",
              "      <td>0.0403</td>\n",
              "      <td>128.000</td>\n",
              "      <td>0.2700</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>169906</th>\n",
              "      <td>0.5380</td>\n",
              "      <td>0.514</td>\n",
              "      <td>0.5390</td>\n",
              "      <td>0.002330</td>\n",
              "      <td>0.1080</td>\n",
              "      <td>-9.332</td>\n",
              "      <td>0.1050</td>\n",
              "      <td>123.700</td>\n",
              "      <td>0.1530</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>169907</th>\n",
              "      <td>0.0714</td>\n",
              "      <td>0.646</td>\n",
              "      <td>0.7610</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.2220</td>\n",
              "      <td>-2.557</td>\n",
              "      <td>0.0385</td>\n",
              "      <td>129.916</td>\n",
              "      <td>0.4720</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>169908</th>\n",
              "      <td>0.1090</td>\n",
              "      <td>0.512</td>\n",
              "      <td>0.4280</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.1050</td>\n",
              "      <td>-7.387</td>\n",
              "      <td>0.0271</td>\n",
              "      <td>80.588</td>\n",
              "      <td>0.3660</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>169909 rows × 10 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-bf494543-8fc3-4227-8f10-945c87727396')\"\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",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <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",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      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",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-bf494543-8fc3-4227-8f10-945c87727396 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-bf494543-8fc3-4227-8f10-945c87727396');\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",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "        acousticness  danceability  energy  ...    tempo  valence  cl\n",
              "0             0.9950         0.708  0.1950  ...  118.469   0.7790   0\n",
              "1             0.9940         0.379  0.0135  ...   83.972   0.0767   1\n",
              "2             0.6040         0.749  0.2200  ...  107.177   0.8800   3\n",
              "3             0.9950         0.781  0.1300  ...  108.003   0.7200   3\n",
              "4             0.9900         0.210  0.2040  ...   62.149   0.0693   1\n",
              "...              ...           ...     ...  ...      ...      ...  ..\n",
              "169904        0.1730         0.875  0.4430  ...  100.012   0.3060   3\n",
              "169905        0.0167         0.719  0.3850  ...  128.000   0.2700   0\n",
              "169906        0.5380         0.514  0.5390  ...  123.700   0.1530   0\n",
              "169907        0.0714         0.646  0.7610  ...  129.916   0.4720   0\n",
              "169908        0.1090         0.512  0.4280  ...   80.588   0.3660   1\n",
              "\n",
              "[169909 rows x 10 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 40
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df2[df2.cl==2]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "34tBTP6gMMFD",
        "outputId": "23a763a4-4b22-4dec-b016-c32399ada8ce"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-8428f0a1-f247-4a90-891d-75097d3e64aa\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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>acousticness</th>\n",
              "      <th>danceability</th>\n",
              "      <th>energy</th>\n",
              "      <th>instrumentalness</th>\n",
              "      <th>liveness</th>\n",
              "      <th>loudness</th>\n",
              "      <th>speechiness</th>\n",
              "      <th>tempo</th>\n",
              "      <th>valence</th>\n",
              "      <th>cl</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>33</th>\n",
              "      <td>0.9870</td>\n",
              "      <td>0.238</td>\n",
              "      <td>0.0324</td>\n",
              "      <td>0.000986</td>\n",
              "      <td>0.1120</td>\n",
              "      <td>-24.361</td>\n",
              "      <td>0.0541</td>\n",
              "      <td>172.321</td>\n",
              "      <td>0.0379</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>81</th>\n",
              "      <td>0.9930</td>\n",
              "      <td>0.523</td>\n",
              "      <td>0.0867</td>\n",
              "      <td>0.124000</td>\n",
              "      <td>0.1400</td>\n",
              "      <td>-17.528</td>\n",
              "      <td>0.0707</td>\n",
              "      <td>161.687</td>\n",
              "      <td>0.6970</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>101</th>\n",
              "      <td>0.9910</td>\n",
              "      <td>0.545</td>\n",
              "      <td>0.1330</td>\n",
              "      <td>0.444000</td>\n",
              "      <td>0.1150</td>\n",
              "      <td>-20.530</td>\n",
              "      <td>0.1270</td>\n",
              "      <td>185.062</td>\n",
              "      <td>0.6910</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>114</th>\n",
              "      <td>0.9890</td>\n",
              "      <td>0.445</td>\n",
              "      <td>0.2880</td>\n",
              "      <td>0.758000</td>\n",
              "      <td>0.1110</td>\n",
              "      <td>-8.925</td>\n",
              "      <td>0.0699</td>\n",
              "      <td>205.423</td>\n",
              "      <td>0.6970</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>118</th>\n",
              "      <td>0.9900</td>\n",
              "      <td>0.518</td>\n",
              "      <td>0.4620</td>\n",
              "      <td>0.850000</td>\n",
              "      <td>0.1570</td>\n",
              "      <td>-9.632</td>\n",
              "      <td>0.3770</td>\n",
              "      <td>178.880</td>\n",
              "      <td>0.6960</td>\n",
              "      <td>2</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",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>169862</th>\n",
              "      <td>0.0962</td>\n",
              "      <td>0.535</td>\n",
              "      <td>0.6480</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.1180</td>\n",
              "      <td>-4.479</td>\n",
              "      <td>0.1590</td>\n",
              "      <td>162.084</td>\n",
              "      <td>0.5110</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>169871</th>\n",
              "      <td>0.3590</td>\n",
              "      <td>0.839</td>\n",
              "      <td>0.4540</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0755</td>\n",
              "      <td>-9.090</td>\n",
              "      <td>0.1570</td>\n",
              "      <td>159.987</td>\n",
              "      <td>0.8040</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>169874</th>\n",
              "      <td>0.5310</td>\n",
              "      <td>0.677</td>\n",
              "      <td>0.6510</td>\n",
              "      <td>0.000038</td>\n",
              "      <td>0.0956</td>\n",
              "      <td>-5.700</td>\n",
              "      <td>0.0559</td>\n",
              "      <td>171.893</td>\n",
              "      <td>0.5430</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>169879</th>\n",
              "      <td>0.1020</td>\n",
              "      <td>0.765</td>\n",
              "      <td>0.6960</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.1480</td>\n",
              "      <td>-5.181</td>\n",
              "      <td>0.0672</td>\n",
              "      <td>160.058</td>\n",
              "      <td>0.9160</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>169899</th>\n",
              "      <td>0.3710</td>\n",
              "      <td>0.623</td>\n",
              "      <td>0.7210</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.1090</td>\n",
              "      <td>-4.584</td>\n",
              "      <td>0.3390</td>\n",
              "      <td>166.637</td>\n",
              "      <td>0.7190</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>18733 rows × 10 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-8428f0a1-f247-4a90-891d-75097d3e64aa')\"\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",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <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",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      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",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-8428f0a1-f247-4a90-891d-75097d3e64aa button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-8428f0a1-f247-4a90-891d-75097d3e64aa');\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",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "        acousticness  danceability  energy  ...    tempo  valence  cl\n",
              "33            0.9870         0.238  0.0324  ...  172.321   0.0379   2\n",
              "81            0.9930         0.523  0.0867  ...  161.687   0.6970   2\n",
              "101           0.9910         0.545  0.1330  ...  185.062   0.6910   2\n",
              "114           0.9890         0.445  0.2880  ...  205.423   0.6970   2\n",
              "118           0.9900         0.518  0.4620  ...  178.880   0.6960   2\n",
              "...              ...           ...     ...  ...      ...      ...  ..\n",
              "169862        0.0962         0.535  0.6480  ...  162.084   0.5110   2\n",
              "169871        0.3590         0.839  0.4540  ...  159.987   0.8040   2\n",
              "169874        0.5310         0.677  0.6510  ...  171.893   0.5430   2\n",
              "169879        0.1020         0.765  0.6960  ...  160.058   0.9160   2\n",
              "169899        0.3710         0.623  0.7210  ...  166.637   0.7190   2\n",
              "\n",
              "[18733 rows x 10 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 43
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        ""
      ],
      "metadata": {
        "id": "eYz2dL9RMd7U"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Dimentionality Reduction"
      ],
      "metadata": {
        "id": "YLP2N6YSuc4d"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.cluster import KMeans\n",
        "\n",
        "from sklearn.decomposition import PCA\n",
        "pca = PCA(n_components=2)\n",
        "df2_2D=pca.fit_transform(df2[sel])\n",
        "\n",
        "kmeans = KMeans(n_clusters=5, random_state=0).fit(df2_2D)\n",
        "kmeans.labels_"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "V1HqIjR8Md9q",
        "outputId": "22e32026-43c0-4260-9804-225d34091629"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([0, 1, 3, ..., 0, 0, 1], dtype=int32)"
            ]
          },
          "metadata": {},
          "execution_count": 44
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df2[\"cl_pca\"]= kmeans.labels_"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "k5ytv4TkNEao",
        "outputId": "7d7807d3-c2ae-4c23-d1e2-480cc22fa961"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:1: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \"\"\"Entry point for launching an IPython kernel.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df2"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "vPXnOq67NKIh",
        "outputId": "d509a272-3d00-4099-d783-bbfd368b47cb"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-78eef15a-2e67-4ade-aebc-29f53e771c09\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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>acousticness</th>\n",
              "      <th>danceability</th>\n",
              "      <th>energy</th>\n",
              "      <th>instrumentalness</th>\n",
              "      <th>liveness</th>\n",
              "      <th>loudness</th>\n",
              "      <th>speechiness</th>\n",
              "      <th>tempo</th>\n",
              "      <th>valence</th>\n",
              "      <th>cl</th>\n",
              "      <th>cl_pca</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0.9950</td>\n",
              "      <td>0.708</td>\n",
              "      <td>0.1950</td>\n",
              "      <td>0.563000</td>\n",
              "      <td>0.1510</td>\n",
              "      <td>-12.428</td>\n",
              "      <td>0.0506</td>\n",
              "      <td>118.469</td>\n",
              "      <td>0.7790</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0.9940</td>\n",
              "      <td>0.379</td>\n",
              "      <td>0.0135</td>\n",
              "      <td>0.901000</td>\n",
              "      <td>0.0763</td>\n",
              "      <td>-28.454</td>\n",
              "      <td>0.0462</td>\n",
              "      <td>83.972</td>\n",
              "      <td>0.0767</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0.6040</td>\n",
              "      <td>0.749</td>\n",
              "      <td>0.2200</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.1190</td>\n",
              "      <td>-19.924</td>\n",
              "      <td>0.9290</td>\n",
              "      <td>107.177</td>\n",
              "      <td>0.8800</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0.9950</td>\n",
              "      <td>0.781</td>\n",
              "      <td>0.1300</td>\n",
              "      <td>0.887000</td>\n",
              "      <td>0.1110</td>\n",
              "      <td>-14.734</td>\n",
              "      <td>0.0926</td>\n",
              "      <td>108.003</td>\n",
              "      <td>0.7200</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0.9900</td>\n",
              "      <td>0.210</td>\n",
              "      <td>0.2040</td>\n",
              "      <td>0.908000</td>\n",
              "      <td>0.0980</td>\n",
              "      <td>-16.829</td>\n",
              "      <td>0.0424</td>\n",
              "      <td>62.149</td>\n",
              "      <td>0.0693</td>\n",
              "      <td>1</td>\n",
              "      <td>1</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",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>169904</th>\n",
              "      <td>0.1730</td>\n",
              "      <td>0.875</td>\n",
              "      <td>0.4430</td>\n",
              "      <td>0.000032</td>\n",
              "      <td>0.0891</td>\n",
              "      <td>-7.461</td>\n",
              "      <td>0.1430</td>\n",
              "      <td>100.012</td>\n",
              "      <td>0.3060</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>169905</th>\n",
              "      <td>0.0167</td>\n",
              "      <td>0.719</td>\n",
              "      <td>0.3850</td>\n",
              "      <td>0.031300</td>\n",
              "      <td>0.1110</td>\n",
              "      <td>-10.907</td>\n",
              "      <td>0.0403</td>\n",
              "      <td>128.000</td>\n",
              "      <td>0.2700</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>169906</th>\n",
              "      <td>0.5380</td>\n",
              "      <td>0.514</td>\n",
              "      <td>0.5390</td>\n",
              "      <td>0.002330</td>\n",
              "      <td>0.1080</td>\n",
              "      <td>-9.332</td>\n",
              "      <td>0.1050</td>\n",
              "      <td>123.700</td>\n",
              "      <td>0.1530</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>169907</th>\n",
              "      <td>0.0714</td>\n",
              "      <td>0.646</td>\n",
              "      <td>0.7610</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.2220</td>\n",
              "      <td>-2.557</td>\n",
              "      <td>0.0385</td>\n",
              "      <td>129.916</td>\n",
              "      <td>0.4720</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>169908</th>\n",
              "      <td>0.1090</td>\n",
              "      <td>0.512</td>\n",
              "      <td>0.4280</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.1050</td>\n",
              "      <td>-7.387</td>\n",
              "      <td>0.0271</td>\n",
              "      <td>80.588</td>\n",
              "      <td>0.3660</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>169909 rows × 11 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-78eef15a-2e67-4ade-aebc-29f53e771c09')\"\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",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <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",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      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",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-78eef15a-2e67-4ade-aebc-29f53e771c09 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-78eef15a-2e67-4ade-aebc-29f53e771c09');\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",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "        acousticness  danceability  energy  ...  valence  cl  cl_pca\n",
              "0             0.9950         0.708  0.1950  ...   0.7790   0       0\n",
              "1             0.9940         0.379  0.0135  ...   0.0767   1       1\n",
              "2             0.6040         0.749  0.2200  ...   0.8800   3       3\n",
              "3             0.9950         0.781  0.1300  ...   0.7200   3       3\n",
              "4             0.9900         0.210  0.2040  ...   0.0693   1       1\n",
              "...              ...           ...     ...  ...      ...  ..     ...\n",
              "169904        0.1730         0.875  0.4430  ...   0.3060   3       3\n",
              "169905        0.0167         0.719  0.3850  ...   0.2700   0       0\n",
              "169906        0.5380         0.514  0.5390  ...   0.1530   0       0\n",
              "169907        0.0714         0.646  0.7610  ...   0.4720   0       0\n",
              "169908        0.1090         0.512  0.4280  ...   0.3660   1       1\n",
              "\n",
              "[169909 rows x 11 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 46
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df2.cl.value_counts().plot(kind=\"bar\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 279
        },
        "id": "26RGwYmMNOyI",
        "outputId": "2ce12e60-0f1d-4b81-f7cd-ce09f484a843"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f17112e97d0>"
            ]
          },
          "metadata": {},
          "execution_count": 48
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df2.cl_pca.value_counts().plot(kind=\"bar\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 279
        },
        "id": "KUWDPPeWNZ-Y",
        "outputId": "c1fa3819-7a2d-4ad7-9876-d8fa9f225f23"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f170ff8e910>"
            ]
          },
          "metadata": {},
          "execution_count": 49
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df2[\"artist\"]=df.artists"
      ],
      "metadata": {
        "id": "bBUv97teNiLZ",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "2669c4c7-92e0-476f-92d4-99f9def5b055"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:1: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \"\"\"Entry point for launching an IPython kernel.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df2[\"name\"]=df.name"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "KlBG-qmdfZeb",
        "outputId": "65ca4ba0-cf07-4757-9c40-9343d618c089"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:1: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \"\"\"Entry point for launching an IPython kernel.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df2"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 834
        },
        "id": "lBDzF55Zfc5v",
        "outputId": "91167bad-4b68-4d94-c41b-f0aabba96232"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-27386a98-1f91-4cff-939c-ba632709d63f\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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>acousticness</th>\n",
              "      <th>danceability</th>\n",
              "      <th>energy</th>\n",
              "      <th>instrumentalness</th>\n",
              "      <th>liveness</th>\n",
              "      <th>loudness</th>\n",
              "      <th>speechiness</th>\n",
              "      <th>tempo</th>\n",
              "      <th>valence</th>\n",
              "      <th>cl</th>\n",
              "      <th>cl_pca</th>\n",
              "      <th>artist</th>\n",
              "      <th>name</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0.9950</td>\n",
              "      <td>0.708</td>\n",
              "      <td>0.1950</td>\n",
              "      <td>0.563000</td>\n",
              "      <td>0.1510</td>\n",
              "      <td>-12.428</td>\n",
              "      <td>0.0506</td>\n",
              "      <td>118.469</td>\n",
              "      <td>0.7790</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>['Carl Woitschach']</td>\n",
              "      <td>Singende Bataillone 1. Teil</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0.9940</td>\n",
              "      <td>0.379</td>\n",
              "      <td>0.0135</td>\n",
              "      <td>0.901000</td>\n",
              "      <td>0.0763</td>\n",
              "      <td>-28.454</td>\n",
              "      <td>0.0462</td>\n",
              "      <td>83.972</td>\n",
              "      <td>0.0767</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>['Robert Schumann', 'Vladimir Horowitz']</td>\n",
              "      <td>Fantasiestücke, Op. 111: Più tosto lento</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0.6040</td>\n",
              "      <td>0.749</td>\n",
              "      <td>0.2200</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.1190</td>\n",
              "      <td>-19.924</td>\n",
              "      <td>0.9290</td>\n",
              "      <td>107.177</td>\n",
              "      <td>0.8800</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>['Seweryn Goszczyński']</td>\n",
              "      <td>Chapter 1.18 - Zamek kaniowski</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0.9950</td>\n",
              "      <td>0.781</td>\n",
              "      <td>0.1300</td>\n",
              "      <td>0.887000</td>\n",
              "      <td>0.1110</td>\n",
              "      <td>-14.734</td>\n",
              "      <td>0.0926</td>\n",
              "      <td>108.003</td>\n",
              "      <td>0.7200</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>['Francisco Canaro']</td>\n",
              "      <td>Bebamos Juntos - Instrumental (Remasterizado)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0.9900</td>\n",
              "      <td>0.210</td>\n",
              "      <td>0.2040</td>\n",
              "      <td>0.908000</td>\n",
              "      <td>0.0980</td>\n",
              "      <td>-16.829</td>\n",
              "      <td>0.0424</td>\n",
              "      <td>62.149</td>\n",
              "      <td>0.0693</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>['Frédéric Chopin', 'Vladimir Horowitz']</td>\n",
              "      <td>Polonaise-Fantaisie in A-Flat Major, Op. 61</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",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>169904</th>\n",
              "      <td>0.1730</td>\n",
              "      <td>0.875</td>\n",
              "      <td>0.4430</td>\n",
              "      <td>0.000032</td>\n",
              "      <td>0.0891</td>\n",
              "      <td>-7.461</td>\n",
              "      <td>0.1430</td>\n",
              "      <td>100.012</td>\n",
              "      <td>0.3060</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>['DripReport', 'Tyga']</td>\n",
              "      <td>Skechers (feat. Tyga) - Remix</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>169905</th>\n",
              "      <td>0.0167</td>\n",
              "      <td>0.719</td>\n",
              "      <td>0.3850</td>\n",
              "      <td>0.031300</td>\n",
              "      <td>0.1110</td>\n",
              "      <td>-10.907</td>\n",
              "      <td>0.0403</td>\n",
              "      <td>128.000</td>\n",
              "      <td>0.2700</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>['Leon Bridges', 'Terrace Martin']</td>\n",
              "      <td>Sweeter (feat. Terrace Martin)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>169906</th>\n",
              "      <td>0.5380</td>\n",
              "      <td>0.514</td>\n",
              "      <td>0.5390</td>\n",
              "      <td>0.002330</td>\n",
              "      <td>0.1080</td>\n",
              "      <td>-9.332</td>\n",
              "      <td>0.1050</td>\n",
              "      <td>123.700</td>\n",
              "      <td>0.1530</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>['Kygo', 'Oh Wonder']</td>\n",
              "      <td>How Would I Know</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>169907</th>\n",
              "      <td>0.0714</td>\n",
              "      <td>0.646</td>\n",
              "      <td>0.7610</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.2220</td>\n",
              "      <td>-2.557</td>\n",
              "      <td>0.0385</td>\n",
              "      <td>129.916</td>\n",
              "      <td>0.4720</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>['Cash Cash', 'Andy Grammer']</td>\n",
              "      <td>I Found You</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>169908</th>\n",
              "      <td>0.1090</td>\n",
              "      <td>0.512</td>\n",
              "      <td>0.4280</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.1050</td>\n",
              "      <td>-7.387</td>\n",
              "      <td>0.0271</td>\n",
              "      <td>80.588</td>\n",
              "      <td>0.3660</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>['Ingrid Andress']</td>\n",
              "      <td>More Hearts Than Mine</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>169909 rows × 13 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-27386a98-1f91-4cff-939c-ba632709d63f')\"\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",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <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",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      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",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-27386a98-1f91-4cff-939c-ba632709d63f button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-27386a98-1f91-4cff-939c-ba632709d63f');\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",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "        acousticness  ...                                           name\n",
              "0             0.9950  ...                    Singende Bataillone 1. Teil\n",
              "1             0.9940  ...       Fantasiestücke, Op. 111: Più tosto lento\n",
              "2             0.6040  ...                 Chapter 1.18 - Zamek kaniowski\n",
              "3             0.9950  ...  Bebamos Juntos - Instrumental (Remasterizado)\n",
              "4             0.9900  ...    Polonaise-Fantaisie in A-Flat Major, Op. 61\n",
              "...              ...  ...                                            ...\n",
              "169904        0.1730  ...                  Skechers (feat. Tyga) - Remix\n",
              "169905        0.0167  ...                 Sweeter (feat. Terrace Martin)\n",
              "169906        0.5380  ...                               How Would I Know\n",
              "169907        0.0714  ...                                    I Found You\n",
              "169908        0.1090  ...                          More Hearts Than Mine\n",
              "\n",
              "[169909 rows x 13 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 52
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df2.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3CpbVIzcfkMP",
        "outputId": "c7c3781f-26f0-4aa3-983a-5288426df29d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(169909, 13)"
            ]
          },
          "metadata": {},
          "execution_count": 53
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df2[\"year\"]=df.year"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "JeT_PqtevVjv",
        "outputId": "663e94ce-246e-46a1-b8c7-9a61a80c9c43"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:1: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \"\"\"Entry point for launching an IPython kernel.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df2[\"pca1\"]=df2_2D[:,0]\n",
        "df2[\"pca2\"]=df2_2D[:,1]\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "WgN8AMBlvZ7A",
        "outputId": "690e280e-9136-426c-b626-9bfe94b82d29"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:1: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \"\"\"Entry point for launching an IPython kernel.\n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:2: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        ""
      ],
      "metadata": {
        "id": "DFl6GFpqveeM"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        ""
      ],
      "metadata": {
        "id": "B5YuRyRIvegj"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        ""
      ],
      "metadata": {
        "id": "cHBlTCtLvejs"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df2.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Rk4h-nvsvevh",
        "outputId": "c6b20aad-42ba-40dd-a5af-d770b6137eb2"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(169909, 16)"
            ]
          },
          "metadata": {},
          "execution_count": 60
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df3=df2.sample(frac=0.02)"
      ],
      "metadata": {
        "id": "-UTbR8_7gUXC"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df3.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fcrm0coIwBrf",
        "outputId": "856eae1b-4ff0-41d2-ded6-00862d9e4ce8"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(3398, 16)"
            ]
          },
          "metadata": {},
          "execution_count": 62
        }
      ]
    },
    {
      "cell_type": "code",
      "source": ["df3.to_csv(\"spotify_sample_17DEC2021.csv\")"
      ],
      "metadata": {
        "id": "URnxWYPZgZQs"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        ""
      ],
      "metadata": {
        "id": "9x26NTk4hsre"
      },
      "execution_count": null,
      "outputs": []
    }
  ],
  "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"
    },
    "colab": {
      "name": "Spotify_Analysis_for_Cmpe_251.ipynb",
      "provenance": []
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}