diff --git a/Spotify_Prediction_32116239.ipynb b/Spotify_Prediction_32116239.ipynb
new file mode 100644
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+++ b/Spotify_Prediction_32116239.ipynb
@@ -0,0 +1,2304 @@
+{
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "n3KRTQVKcRUV"
+      },
+      "source": [
+        "*Adarsh Sankar Rajesh Kumar Sangeetha - 32116239*"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "hzIqyzG8VOk_"
+      },
+      "source": [
+        "#Spotify Data Exploratory Analysis and Song Popularity Prediction\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "!pip install kaggle"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "Bvn2g95MVG_y",
+        "outputId": "cc8b10ef-2c27-40c7-9792-1da48940f775"
+      },
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Requirement already satisfied: kaggle in /usr/local/lib/python3.10/dist-packages (1.5.16)\n",
+            "Requirement already satisfied: six>=1.10 in /usr/local/lib/python3.10/dist-packages (from kaggle) (1.16.0)\n",
+            "Requirement already satisfied: certifi in /usr/local/lib/python3.10/dist-packages (from kaggle) (2023.7.22)\n",
+            "Requirement already satisfied: python-dateutil in /usr/local/lib/python3.10/dist-packages (from kaggle) (2.8.2)\n",
+            "Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from kaggle) (2.31.0)\n",
+            "Requirement already satisfied: tqdm in /usr/local/lib/python3.10/dist-packages (from kaggle) (4.66.1)\n",
+            "Requirement already satisfied: python-slugify in /usr/local/lib/python3.10/dist-packages (from kaggle) (8.0.1)\n",
+            "Requirement already satisfied: urllib3 in /usr/local/lib/python3.10/dist-packages (from kaggle) (2.0.7)\n",
+            "Requirement already satisfied: bleach in /usr/local/lib/python3.10/dist-packages (from kaggle) (6.1.0)\n",
+            "Requirement already satisfied: webencodings in /usr/local/lib/python3.10/dist-packages (from bleach->kaggle) (0.5.1)\n",
+            "Requirement already satisfied: text-unidecode>=1.3 in /usr/local/lib/python3.10/dist-packages (from python-slugify->kaggle) (1.3)\n",
+            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests->kaggle) (3.3.2)\n",
+            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->kaggle) (3.4)\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "from google.colab import files\n",
+        "\n",
+        "uploaded = files.upload()"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 74
+        },
+        "id": "22VRxA6hVXwH",
+        "outputId": "1e3da2d3-9318-4b46-a421-dc11d9645083"
+      },
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<IPython.core.display.HTML object>"
+            ],
+            "text/html": [
+              "\n",
+              "     <input type=\"file\" id=\"files-549e8a0d-850d-4c99-81b0-e649fb2501fe\" name=\"files[]\" multiple disabled\n",
+              "        style=\"border:none\" />\n",
+              "     <output id=\"result-549e8a0d-850d-4c99-81b0-e649fb2501fe\">\n",
+              "      Upload widget is only available when the cell has been executed in the\n",
+              "      current browser session. Please rerun this cell to enable.\n",
+              "      </output>\n",
+              "      <script>// Copyright 2017 Google LLC\n",
+              "//\n",
+              "// Licensed under the Apache License, Version 2.0 (the \"License\");\n",
+              "// you may not use this file except in compliance with the License.\n",
+              "// You may obtain a copy of the License at\n",
+              "//\n",
+              "//      http://www.apache.org/licenses/LICENSE-2.0\n",
+              "//\n",
+              "// Unless required by applicable law or agreed to in writing, software\n",
+              "// distributed under the License is distributed on an \"AS IS\" BASIS,\n",
+              "// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
+              "// See the License for the specific language governing permissions and\n",
+              "// limitations under the License.\n",
+              "\n",
+              "/**\n",
+              " * @fileoverview Helpers for google.colab Python module.\n",
+              " */\n",
+              "(function(scope) {\n",
+              "function span(text, styleAttributes = {}) {\n",
+              "  const element = document.createElement('span');\n",
+              "  element.textContent = text;\n",
+              "  for (const key of Object.keys(styleAttributes)) {\n",
+              "    element.style[key] = styleAttributes[key];\n",
+              "  }\n",
+              "  return element;\n",
+              "}\n",
+              "\n",
+              "// Max number of bytes which will be uploaded at a time.\n",
+              "const MAX_PAYLOAD_SIZE = 100 * 1024;\n",
+              "\n",
+              "function _uploadFiles(inputId, outputId) {\n",
+              "  const steps = uploadFilesStep(inputId, outputId);\n",
+              "  const outputElement = document.getElementById(outputId);\n",
+              "  // Cache steps on the outputElement to make it available for the next call\n",
+              "  // to uploadFilesContinue from Python.\n",
+              "  outputElement.steps = steps;\n",
+              "\n",
+              "  return _uploadFilesContinue(outputId);\n",
+              "}\n",
+              "\n",
+              "// This is roughly an async generator (not supported in the browser yet),\n",
+              "// where there are multiple asynchronous steps and the Python side is going\n",
+              "// to poll for completion of each step.\n",
+              "// This uses a Promise to block the python side on completion of each step,\n",
+              "// then passes the result of the previous step as the input to the next step.\n",
+              "function _uploadFilesContinue(outputId) {\n",
+              "  const outputElement = document.getElementById(outputId);\n",
+              "  const steps = outputElement.steps;\n",
+              "\n",
+              "  const next = steps.next(outputElement.lastPromiseValue);\n",
+              "  return Promise.resolve(next.value.promise).then((value) => {\n",
+              "    // Cache the last promise value to make it available to the next\n",
+              "    // step of the generator.\n",
+              "    outputElement.lastPromiseValue = value;\n",
+              "    return next.value.response;\n",
+              "  });\n",
+              "}\n",
+              "\n",
+              "/**\n",
+              " * Generator function which is called between each async step of the upload\n",
+              " * process.\n",
+              " * @param {string} inputId Element ID of the input file picker element.\n",
+              " * @param {string} outputId Element ID of the output display.\n",
+              " * @return {!Iterable<!Object>} Iterable of next steps.\n",
+              " */\n",
+              "function* uploadFilesStep(inputId, outputId) {\n",
+              "  const inputElement = document.getElementById(inputId);\n",
+              "  inputElement.disabled = false;\n",
+              "\n",
+              "  const outputElement = document.getElementById(outputId);\n",
+              "  outputElement.innerHTML = '';\n",
+              "\n",
+              "  const pickedPromise = new Promise((resolve) => {\n",
+              "    inputElement.addEventListener('change', (e) => {\n",
+              "      resolve(e.target.files);\n",
+              "    });\n",
+              "  });\n",
+              "\n",
+              "  const cancel = document.createElement('button');\n",
+              "  inputElement.parentElement.appendChild(cancel);\n",
+              "  cancel.textContent = 'Cancel upload';\n",
+              "  const cancelPromise = new Promise((resolve) => {\n",
+              "    cancel.onclick = () => {\n",
+              "      resolve(null);\n",
+              "    };\n",
+              "  });\n",
+              "\n",
+              "  // Wait for the user to pick the files.\n",
+              "  const files = yield {\n",
+              "    promise: Promise.race([pickedPromise, cancelPromise]),\n",
+              "    response: {\n",
+              "      action: 'starting',\n",
+              "    }\n",
+              "  };\n",
+              "\n",
+              "  cancel.remove();\n",
+              "\n",
+              "  // Disable the input element since further picks are not allowed.\n",
+              "  inputElement.disabled = true;\n",
+              "\n",
+              "  if (!files) {\n",
+              "    return {\n",
+              "      response: {\n",
+              "        action: 'complete',\n",
+              "      }\n",
+              "    };\n",
+              "  }\n",
+              "\n",
+              "  for (const file of files) {\n",
+              "    const li = document.createElement('li');\n",
+              "    li.append(span(file.name, {fontWeight: 'bold'}));\n",
+              "    li.append(span(\n",
+              "        `(${file.type || 'n/a'}) - ${file.size} bytes, ` +\n",
+              "        `last modified: ${\n",
+              "            file.lastModifiedDate ? file.lastModifiedDate.toLocaleDateString() :\n",
+              "                                    'n/a'} - `));\n",
+              "    const percent = span('0% done');\n",
+              "    li.appendChild(percent);\n",
+              "\n",
+              "    outputElement.appendChild(li);\n",
+              "\n",
+              "    const fileDataPromise = new Promise((resolve) => {\n",
+              "      const reader = new FileReader();\n",
+              "      reader.onload = (e) => {\n",
+              "        resolve(e.target.result);\n",
+              "      };\n",
+              "      reader.readAsArrayBuffer(file);\n",
+              "    });\n",
+              "    // Wait for the data to be ready.\n",
+              "    let fileData = yield {\n",
+              "      promise: fileDataPromise,\n",
+              "      response: {\n",
+              "        action: 'continue',\n",
+              "      }\n",
+              "    };\n",
+              "\n",
+              "    // Use a chunked sending to avoid message size limits. See b/62115660.\n",
+              "    let position = 0;\n",
+              "    do {\n",
+              "      const length = Math.min(fileData.byteLength - position, MAX_PAYLOAD_SIZE);\n",
+              "      const chunk = new Uint8Array(fileData, position, length);\n",
+              "      position += length;\n",
+              "\n",
+              "      const base64 = btoa(String.fromCharCode.apply(null, chunk));\n",
+              "      yield {\n",
+              "        response: {\n",
+              "          action: 'append',\n",
+              "          file: file.name,\n",
+              "          data: base64,\n",
+              "        },\n",
+              "      };\n",
+              "\n",
+              "      let percentDone = fileData.byteLength === 0 ?\n",
+              "          100 :\n",
+              "          Math.round((position / fileData.byteLength) * 100);\n",
+              "      percent.textContent = `${percentDone}% done`;\n",
+              "\n",
+              "    } while (position < fileData.byteLength);\n",
+              "  }\n",
+              "\n",
+              "  // All done.\n",
+              "  yield {\n",
+              "    response: {\n",
+              "      action: 'complete',\n",
+              "    }\n",
+              "  };\n",
+              "}\n",
+              "\n",
+              "scope.google = scope.google || {};\n",
+              "scope.google.colab = scope.google.colab || {};\n",
+              "scope.google.colab._files = {\n",
+              "  _uploadFiles,\n",
+              "  _uploadFilesContinue,\n",
+              "};\n",
+              "})(self);\n",
+              "</script> "
+            ]
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Saving kaggle.json to kaggle.json\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "!mkdir -p ~/.kaggle\n",
+        "!cp kaggle.json ~/.kaggle/\n",
+        "!chmod 600 ~/.kaggle/kaggle.json"
+      ],
+      "metadata": {
+        "id": "sDtn6G7IVkL2"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "!kaggle datasets download -d dhruvjyotiswain/spotify2016popularsongs"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "pF0ucehwVuat",
+        "outputId": "f400d456-36a1-455f-e68b-15789a9a798b"
+      },
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Downloading spotify2016popularsongs.zip to /content\n",
+            "\r  0% 0.00/97.7k [00:00<?, ?B/s]\n",
+            "\r100% 97.7k/97.7k [00:00<00:00, 60.4MB/s]\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "!unzip spotify2016popularsongs.zip"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "Sz-DcVN0VyUP",
+        "outputId": "33d99098-c638-48ae-8a56-686f49e9f1a9"
+      },
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Archive:  spotify2016popularsongs.zip\n",
+            "  inflating: data.csv                \n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "uIVRX29YMnaB"
+      },
+      "source": [
+        "Importing Libraries\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 296
+        },
+        "id": "3-JypK1xMsfn",
+        "outputId": "3e4b00bd-be14-41c1-af6a-70e86b19ffd8"
+      },
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "   acousticness  danceability  duration_ms  energy  instrumentalness  key  \\\n",
+              "0        0.0102         0.833       204600   0.434          0.021900    2   \n",
+              "1        0.1990         0.743       326933   0.359          0.006110    1   \n",
+              "2        0.0344         0.838       185707   0.412          0.000234    2   \n",
+              "3        0.6040         0.494       199413   0.338          0.510000    5   \n",
+              "4        0.1800         0.678       392893   0.561          0.512000    5   \n",
+              "\n",
+              "   liveness  loudness  mode  speechiness    tempo  time_signature  valence  \\\n",
+              "0    0.1650    -8.795     1       0.4310  150.062               4    0.286   \n",
+              "1    0.1370   -10.401     1       0.0794  160.083               4    0.588   \n",
+              "2    0.1590    -7.148     1       0.2890   75.044               4    0.173   \n",
+              "3    0.0922   -15.236     1       0.0261   86.468               4    0.230   \n",
+              "4    0.4390   -11.648     0       0.0694  174.004               4    0.904   \n",
+              "\n",
+              "   target      song_title            artist  \n",
+              "0       1        Mask Off            Future  \n",
+              "1       1         Redbone  Childish Gambino  \n",
+              "2       1    Xanny Family            Future  \n",
+              "3       1  Master Of None       Beach House  \n",
+              "4       1  Parallel Lines       Junior Boys  "
+            ],
+            "text/html": [
+              "\n",
+              "  <div id=\"df-2de4db1a-0b00-4b0d-af59-7ad8a818cd0f\" 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>duration_ms</th>\n",
+              "      <th>energy</th>\n",
+              "      <th>instrumentalness</th>\n",
+              "      <th>key</th>\n",
+              "      <th>liveness</th>\n",
+              "      <th>loudness</th>\n",
+              "      <th>mode</th>\n",
+              "      <th>speechiness</th>\n",
+              "      <th>tempo</th>\n",
+              "      <th>time_signature</th>\n",
+              "      <th>valence</th>\n",
+              "      <th>target</th>\n",
+              "      <th>song_title</th>\n",
+              "      <th>artist</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>0.0102</td>\n",
+              "      <td>0.833</td>\n",
+              "      <td>204600</td>\n",
+              "      <td>0.434</td>\n",
+              "      <td>0.021900</td>\n",
+              "      <td>2</td>\n",
+              "      <td>0.1650</td>\n",
+              "      <td>-8.795</td>\n",
+              "      <td>1</td>\n",
+              "      <td>0.4310</td>\n",
+              "      <td>150.062</td>\n",
+              "      <td>4</td>\n",
+              "      <td>0.286</td>\n",
+              "      <td>1</td>\n",
+              "      <td>Mask Off</td>\n",
+              "      <td>Future</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1</th>\n",
+              "      <td>0.1990</td>\n",
+              "      <td>0.743</td>\n",
+              "      <td>326933</td>\n",
+              "      <td>0.359</td>\n",
+              "      <td>0.006110</td>\n",
+              "      <td>1</td>\n",
+              "      <td>0.1370</td>\n",
+              "      <td>-10.401</td>\n",
+              "      <td>1</td>\n",
+              "      <td>0.0794</td>\n",
+              "      <td>160.083</td>\n",
+              "      <td>4</td>\n",
+              "      <td>0.588</td>\n",
+              "      <td>1</td>\n",
+              "      <td>Redbone</td>\n",
+              "      <td>Childish Gambino</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>0.0344</td>\n",
+              "      <td>0.838</td>\n",
+              "      <td>185707</td>\n",
+              "      <td>0.412</td>\n",
+              "      <td>0.000234</td>\n",
+              "      <td>2</td>\n",
+              "      <td>0.1590</td>\n",
+              "      <td>-7.148</td>\n",
+              "      <td>1</td>\n",
+              "      <td>0.2890</td>\n",
+              "      <td>75.044</td>\n",
+              "      <td>4</td>\n",
+              "      <td>0.173</td>\n",
+              "      <td>1</td>\n",
+              "      <td>Xanny Family</td>\n",
+              "      <td>Future</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>0.6040</td>\n",
+              "      <td>0.494</td>\n",
+              "      <td>199413</td>\n",
+              "      <td>0.338</td>\n",
+              "      <td>0.510000</td>\n",
+              "      <td>5</td>\n",
+              "      <td>0.0922</td>\n",
+              "      <td>-15.236</td>\n",
+              "      <td>1</td>\n",
+              "      <td>0.0261</td>\n",
+              "      <td>86.468</td>\n",
+              "      <td>4</td>\n",
+              "      <td>0.230</td>\n",
+              "      <td>1</td>\n",
+              "      <td>Master Of None</td>\n",
+              "      <td>Beach House</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4</th>\n",
+              "      <td>0.1800</td>\n",
+              "      <td>0.678</td>\n",
+              "      <td>392893</td>\n",
+              "      <td>0.561</td>\n",
+              "      <td>0.512000</td>\n",
+              "      <td>5</td>\n",
+              "      <td>0.4390</td>\n",
+              "      <td>-11.648</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0.0694</td>\n",
+              "      <td>174.004</td>\n",
+              "      <td>4</td>\n",
+              "      <td>0.904</td>\n",
+              "      <td>1</td>\n",
+              "      <td>Parallel Lines</td>\n",
+              "      <td>Junior Boys</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>\n",
+              "    <div class=\"colab-df-buttons\">\n",
+              "\n",
+              "  <div class=\"colab-df-container\">\n",
+              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-2de4db1a-0b00-4b0d-af59-7ad8a818cd0f')\"\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 -960 960 960\">\n",
+              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
+              "  </svg>\n",
+              "    </button>\n",
+              "\n",
+              "  <style>\n",
+              "    .colab-df-container {\n",
+              "      display:flex;\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",
+              "    .colab-df-buttons div {\n",
+              "      margin-bottom: 4px;\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-2de4db1a-0b00-4b0d-af59-7ad8a818cd0f 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-2de4db1a-0b00-4b0d-af59-7ad8a818cd0f');\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",
+              "\n",
+              "\n",
+              "<div id=\"df-c2ecfa28-677b-40cf-93df-d6c186bd17f5\">\n",
+              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-c2ecfa28-677b-40cf-93df-d6c186bd17f5')\"\n",
+              "            title=\"Suggest charts\"\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",
+              "    <g>\n",
+              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
+              "    </g>\n",
+              "</svg>\n",
+              "  </button>\n",
+              "\n",
+              "<style>\n",
+              "  .colab-df-quickchart {\n",
+              "      --bg-color: #E8F0FE;\n",
+              "      --fill-color: #1967D2;\n",
+              "      --hover-bg-color: #E2EBFA;\n",
+              "      --hover-fill-color: #174EA6;\n",
+              "      --disabled-fill-color: #AAA;\n",
+              "      --disabled-bg-color: #DDD;\n",
+              "  }\n",
+              "\n",
+              "  [theme=dark] .colab-df-quickchart {\n",
+              "      --bg-color: #3B4455;\n",
+              "      --fill-color: #D2E3FC;\n",
+              "      --hover-bg-color: #434B5C;\n",
+              "      --hover-fill-color: #FFFFFF;\n",
+              "      --disabled-bg-color: #3B4455;\n",
+              "      --disabled-fill-color: #666;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart {\n",
+              "    background-color: var(--bg-color);\n",
+              "    border: none;\n",
+              "    border-radius: 50%;\n",
+              "    cursor: pointer;\n",
+              "    display: none;\n",
+              "    fill: var(--fill-color);\n",
+              "    height: 32px;\n",
+              "    padding: 0;\n",
+              "    width: 32px;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart:hover {\n",
+              "    background-color: var(--hover-bg-color);\n",
+              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "    fill: var(--button-hover-fill-color);\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart-complete:disabled,\n",
+              "  .colab-df-quickchart-complete:disabled:hover {\n",
+              "    background-color: var(--disabled-bg-color);\n",
+              "    fill: var(--disabled-fill-color);\n",
+              "    box-shadow: none;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-spinner {\n",
+              "    border: 2px solid var(--fill-color);\n",
+              "    border-color: transparent;\n",
+              "    border-bottom-color: var(--fill-color);\n",
+              "    animation:\n",
+              "      spin 1s steps(1) infinite;\n",
+              "  }\n",
+              "\n",
+              "  @keyframes spin {\n",
+              "    0% {\n",
+              "      border-color: transparent;\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "      border-left-color: var(--fill-color);\n",
+              "    }\n",
+              "    20% {\n",
+              "      border-color: transparent;\n",
+              "      border-left-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "    }\n",
+              "    30% {\n",
+              "      border-color: transparent;\n",
+              "      border-left-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "      border-right-color: var(--fill-color);\n",
+              "    }\n",
+              "    40% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "    }\n",
+              "    60% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "    }\n",
+              "    80% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "    }\n",
+              "    90% {\n",
+              "      border-color: transparent;\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "    }\n",
+              "  }\n",
+              "</style>\n",
+              "\n",
+              "  <script>\n",
+              "    async function quickchart(key) {\n",
+              "      const quickchartButtonEl =\n",
+              "        document.querySelector('#' + key + ' button');\n",
+              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
+              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
+              "      try {\n",
+              "        const charts = await google.colab.kernel.invokeFunction(\n",
+              "            'suggestCharts', [key], {});\n",
+              "      } catch (error) {\n",
+              "        console.error('Error during call to suggestCharts:', error);\n",
+              "      }\n",
+              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
+              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
+              "    }\n",
+              "    (() => {\n",
+              "      let quickchartButtonEl =\n",
+              "        document.querySelector('#df-c2ecfa28-677b-40cf-93df-d6c186bd17f5 button');\n",
+              "      quickchartButtonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "    })();\n",
+              "  </script>\n",
+              "</div>\n",
+              "    </div>\n",
+              "  </div>\n"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 7
+        }
+      ],
+      "source": [
+        "# Importing wanted libraries\n",
+        "import pandas as pd\n",
+        "import numpy as np\n",
+        "import seaborn as sns\n",
+        "import matplotlib.pyplot as plt\n",
+        "\n",
+        "# Set the style for the plots\n",
+        "sns.set_style(\"darkgrid\")\n",
+        "\n",
+        "# Load the dataset\n",
+        "df = pd.read_csv(\"/content/data.csv\")\n",
+        "df.drop(\"Unnamed: 0\", axis=1, inplace=True)\n",
+        "df.head()"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "BM77Qi00Qcve"
+      },
+      "source": [
+        "Cleaning the Data\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "LMwJhDqIPHdt",
+        "outputId": "2947ce32-3610-4d03-d318-dc1f111e0b91"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Missing Values:\n",
+            "acousticness        0\n",
+            "danceability        0\n",
+            "duration_ms         0\n",
+            "energy              0\n",
+            "instrumentalness    0\n",
+            "key                 0\n",
+            "liveness            0\n",
+            "loudness            0\n",
+            "mode                0\n",
+            "speechiness         0\n",
+            "tempo               0\n",
+            "time_signature      0\n",
+            "valence             0\n",
+            "target              0\n",
+            "song_title          0\n",
+            "artist              0\n",
+            "dtype: int64\n"
+          ]
+        }
+      ],
+      "source": [
+        "# Data Cleaning\n",
+        "\n",
+        "# Checking for missing values\n",
+        "missing_values = df.isna().sum()\n",
+        "print(\"Missing Values:\")\n",
+        "print(missing_values)\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "Wy7xcsfnQpyI",
+        "outputId": "d015627f-6352-4fc5-e773-c59d89247c7b"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "<class 'pandas.core.frame.DataFrame'>\n",
+            "RangeIndex: 2017 entries, 0 to 2016\n",
+            "Data columns (total 16 columns):\n",
+            " #   Column            Non-Null Count  Dtype  \n",
+            "---  ------            --------------  -----  \n",
+            " 0   acousticness      2017 non-null   float64\n",
+            " 1   danceability      2017 non-null   float64\n",
+            " 2   duration_ms       2017 non-null   int64  \n",
+            " 3   energy            2017 non-null   float64\n",
+            " 4   instrumentalness  2017 non-null   float64\n",
+            " 5   key               2017 non-null   int64  \n",
+            " 6   liveness          2017 non-null   float64\n",
+            " 7   loudness          2017 non-null   float64\n",
+            " 8   mode              2017 non-null   int64  \n",
+            " 9   speechiness       2017 non-null   float64\n",
+            " 10  tempo             2017 non-null   float64\n",
+            " 11  time_signature    2017 non-null   int64  \n",
+            " 12  valence           2017 non-null   float64\n",
+            " 13  target            2017 non-null   int64  \n",
+            " 14  song_title        2017 non-null   object \n",
+            " 15  artist            2017 non-null   object \n",
+            "dtypes: float64(9), int64(5), object(2)\n",
+            "memory usage: 252.2+ KB\n",
+            "DataFrame Info:\n",
+            "None\n"
+          ]
+        }
+      ],
+      "source": [
+        "# Display information about the DataFrame\n",
+        "df_info = df.info()\n",
+        "print(\"DataFrame Info:\")\n",
+        "print(df_info)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "0Ga_6lQ5QwBx",
+        "outputId": "cc07300c-b958-417d-cf1e-49c88a1647b6"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "DataFrame Shape:\n",
+            "(2017, 16)\n"
+          ]
+        }
+      ],
+      "source": [
+        "# Display the shape of the DataFrame\n",
+        "df_shape = df.shape\n",
+        "print(\"DataFrame Shape:\")\n",
+        "print(df_shape)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "y3mfwc02Q3EB",
+        "outputId": "9d93e30d-dc3b-42a7-ba98-f4cdff7a1485"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "DataFrame Columns:\n",
+            "Index(['acousticness', 'danceability', 'duration_ms', 'energy',\n",
+            "       'instrumentalness', 'key', 'liveness', 'loudness', 'mode',\n",
+            "       'speechiness', 'tempo', 'time_signature', 'valence', 'target',\n",
+            "       'song_title', 'artist'],\n",
+            "      dtype='object')\n"
+          ]
+        }
+      ],
+      "source": [
+        "# Display the columns of the DataFrame\n",
+        "df_columns = df.columns\n",
+        "print(\"DataFrame Columns:\")\n",
+        "print(df_columns)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "bn1oL_tgQ6RT",
+        "outputId": "ace9daa1-4bed-4d80-e2c1-fd01674535fc"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "DataFrame Summary Statistics:\n",
+            "       acousticness  danceability   duration_ms       energy  \\\n",
+            "count   2017.000000   2017.000000  2.017000e+03  2017.000000   \n",
+            "mean       0.187590      0.618422  2.463062e+05     0.681577   \n",
+            "std        0.259989      0.161029  8.198181e+04     0.210273   \n",
+            "min        0.000003      0.122000  1.604200e+04     0.014800   \n",
+            "25%        0.009630      0.514000  2.000150e+05     0.563000   \n",
+            "50%        0.063300      0.631000  2.292610e+05     0.715000   \n",
+            "75%        0.265000      0.738000  2.703330e+05     0.846000   \n",
+            "max        0.995000      0.984000  1.004627e+06     0.998000   \n",
+            "\n",
+            "       instrumentalness          key     liveness     loudness         mode  \\\n",
+            "count       2017.000000  2017.000000  2017.000000  2017.000000  2017.000000   \n",
+            "mean           0.133286     5.342588     0.190844    -7.085624     0.612295   \n",
+            "std            0.273162     3.648240     0.155453     3.761684     0.487347   \n",
+            "min            0.000000     0.000000     0.018800   -33.097000     0.000000   \n",
+            "25%            0.000000     2.000000     0.092300    -8.394000     0.000000   \n",
+            "50%            0.000076     6.000000     0.127000    -6.248000     1.000000   \n",
+            "75%            0.054000     9.000000     0.247000    -4.746000     1.000000   \n",
+            "max            0.976000    11.000000     0.969000    -0.307000     1.000000   \n",
+            "\n",
+            "       speechiness        tempo  time_signature      valence       target  \n",
+            "count  2017.000000  2017.000000     2017.000000  2017.000000  2017.000000  \n",
+            "mean      0.092664   121.603272        3.968270     0.496815     0.505702  \n",
+            "std       0.089931    26.685604        0.255853     0.247195     0.500091  \n",
+            "min       0.023100    47.859000        1.000000     0.034800     0.000000  \n",
+            "25%       0.037500   100.189000        4.000000     0.295000     0.000000  \n",
+            "50%       0.054900   121.427000        4.000000     0.492000     1.000000  \n",
+            "75%       0.108000   137.849000        4.000000     0.691000     1.000000  \n",
+            "max       0.816000   219.331000        5.000000     0.992000     1.000000  \n"
+          ]
+        }
+      ],
+      "source": [
+        "# Display summary statistics of the DataFrame\n",
+        "df_describe = df.describe()\n",
+        "print(\"DataFrame Summary Statistics:\")\n",
+        "print(df_describe)"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "2aUKax0gRCA8"
+      },
+      "source": [
+        "#Analysing the Data"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "TsBOe3bnWKqv"
+      },
+      "outputs": [],
+      "source": []
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "HMS3Kov5RI2Q"
+      },
+      "source": [
+        "Top Five Most Popular Artists"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 689
+        },
+        "id": "phUVxPxVRGNb",
+        "outputId": "197a7e08-c7ed-481f-c74a-8ff127a29fd5"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Top 5 Most Popular Artists are :\n",
+            "Drake              16\n",
+            "Rick Ross          13\n",
+            "Disclosure         12\n",
+            "WALK THE MOON      10\n",
+            "Backstreet Boys    10\n",
+            "Name: artist, dtype: int64\n"
+          ]
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 1000x600 with 1 Axes>"
+            ],
+            "image/png": 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\n"
+          },
+          "metadata": {}
+        }
+      ],
+      "source": [
+        "# Top 5 most popular artists\n",
+        "top_five_artists = df['artist'].value_counts().nlargest(5)\n",
+        "print(\"Top 5 Most Popular Artists are :\")\n",
+        "print(top_five_artists)\n",
+        "\n",
+        "# Plotting a horizontal bar chart for the top 5 artists\n",
+        "plt.figure(figsize=(10, 6))\n",
+        "top_five_artists.plot(kind='barh', color='skyblue')\n",
+        "plt.title(\"Top 5 Most Popular Artists can be represented as follows :\")\n",
+        "plt.xlabel(\"Number of Songs\")\n",
+        "plt.ylabel(\"Artist\")\n",
+        "plt.show()"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "iajaiMTNRVRu"
+      },
+      "outputs": [],
+      "source": []
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "gCsEzknOSnn8"
+      },
+      "source": [
+        "Top Five Loudest Tracks"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 731
+        },
+        "id": "bJrmBUghSxEF",
+        "outputId": "6dacbf44-43f5-43ef-999f-b993dd9fc1db"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Top 5 Loudest Tracks are :\n",
+            "      loudness                   song_title\n",
+            "195     -0.307                 GodLovesUgly\n",
+            "636     -0.718      The Lion - Original Mix\n",
+            "1443    -0.787                     The Wall\n",
+            "2010    -0.935  Hey Baby - Steve Aoki Remix\n",
+            "1299    -0.994                No Absolution\n"
+          ]
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 1200x700 with 1 Axes>"
+            ],
+            "image/png": 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+          },
+          "metadata": {}
+        }
+      ],
+      "source": [
+        "# Top 5 loudest tracks\n",
+        "top_five_loudest_tracks = df[['loudness', 'song_title']].nlargest(5, 'loudness')\n",
+        "print(\"Top 5 Loudest Tracks are :\")\n",
+        "print(top_five_loudest_tracks)\n",
+        "\n",
+        "# Plotting a bar chart for the top 5 loudest tracks\n",
+        "plt.figure(figsize=(12, 7))\n",
+        "sns.barplot(x=\"loudness\", y=\"song_title\", data=top_five_loudest_tracks)\n",
+        "plt.title(\"Top 5 Loudest Tracks are as follows :\")\n",
+        "plt.xlabel(\"Loudness\")\n",
+        "plt.ylabel(\"Song Title\")\n",
+        "plt.show()\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "4OgljlCbTKX9"
+      },
+      "source": [
+        "Artist With The Most Danceable Song"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 766
+        },
+        "id": "d6duXto4TDbi",
+        "outputId": "fa79afbb-712a-4f22-848e-b4762cb7a9b4"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Top 5 Artists with Most Danceable Songs are :\n",
+            "      danceability              song_title             artist\n",
+            "1433         0.984  Flashwind - Radio Edit       Ben Remember\n",
+            "1901         0.967                SexyBack  Justin Timberlake\n",
+            "604          0.962       Check Me Out Like          Blaqstarr\n",
+            "32           0.959             Best Friend         Young Thug\n",
+            "1957         0.959            Ice Ice Baby        Vanilla Ice\n"
+          ]
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 1200x700 with 1 Axes>"
+            ],
+            "image/png": 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+          },
+          "metadata": {}
+        }
+      ],
+      "source": [
+        "# Artist with the most danceable song\n",
+        "top_five_artists_danceable_songs = df[['danceability', 'song_title', 'artist']].nlargest(5, 'danceability')\n",
+        "print(\"Top 5 Artists with Most Danceable Songs are :\")\n",
+        "print(top_five_artists_danceable_songs)\n",
+        "\n",
+        "# Plotting a bar chart for the danceability of songs by top 5 artists\n",
+        "plt.figure(figsize=(12, 7))\n",
+        "sns.barplot(x=\"danceability\", y=\"artist\", data=top_five_artists_danceable_songs)\n",
+        "plt.title(\"Artist With The Most Danceable Song can be represented as follows :\")\n",
+        "plt.xlabel(\"Danceability\")\n",
+        "plt.ylabel(\"Artist\")\n",
+        "plt.show()"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "wYhN9UOlT2ry"
+      },
+      "source": [
+        "Top Ten Instrumental Tasks"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 1000
+        },
+        "id": "yN-OGQFeT70B",
+        "outputId": "1d2d8742-004d-4ac9-8a28-a4b483a8e986"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Top 10 Instrumental Tracks are :\n",
+            "      instrumentalness                            song_title  \\\n",
+            "1313             0.976                       Senseless Order   \n",
+            "271              0.968  So Destroyed (channeling Rage Peace)   \n",
+            "1575             0.964             A Hundred Dreams from Now   \n",
+            "1619             0.958                                 Raven   \n",
+            "725              0.957                     Strandbar (disko)   \n",
+            "1546             0.956                        Almas vaggvisa   \n",
+            "1322             0.955                            Pitchblack   \n",
+            "1349             0.954                       Prismatic Abyss   \n",
+            "1661             0.954                               Yebisah   \n",
+            "121              0.952                        Chasing Heaven   \n",
+            "\n",
+            "                        artist  \n",
+            "1313        Signs of the Swarm  \n",
+            "271                Prince Rama  \n",
+            "1575                Ray Bryant  \n",
+            "1619             John Dahlbäck  \n",
+            "725                 Todd Terje  \n",
+            "1546         Jan Lundgren Trio  \n",
+            "1322  Walking Dead On Broadway  \n",
+            "1349           Aversions Crown  \n",
+            "1661               Mark Knight  \n",
+            "121                 Bassnectar  \n"
+          ]
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 800x800 with 1 Axes>"
+            ],
+            "image/png": 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\n"
+          },
+          "metadata": {}
+        }
+      ],
+      "source": [
+        "# Top 10 instrumentalness tracks\n",
+        "top_ten_instrumental_tracks = df[['instrumentalness', 'song_title', 'artist']].nlargest(10, 'instrumentalness')\n",
+        "print(\"Top 10 Instrumental Tracks are :\")\n",
+        "print(top_ten_instrumental_tracks)\n",
+        "\n",
+        "# Plotting a pie chart for the instrumentalness of the top 10 tracks\n",
+        "plt.figure(figsize=(8, 8))\n",
+        "plt.pie(x=top_ten_instrumental_tracks['instrumentalness'], autopct='%1.2f%%', labels=top_ten_instrumental_tracks['song_title'])\n",
+        "plt.title(\"Top 10 Instrumental Tracks can be represented as follows :\")\n",
+        "plt.show()\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "0RzNMgRPUUqs"
+      },
+      "source": [
+        "Top Ten Energetic Tracks"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 952
+        },
+        "id": "zLp-Vg0tURKo",
+        "outputId": "c5a372fd-5c50-47d2-b744-1c9bbd6361fe"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Top 10 Energetic Tracks are :\n",
+            "      energy           song_title\n",
+            "1299   0.998        No Absolution\n",
+            "1322   0.997           Pitchblack\n",
+            "1297   0.994    A Darkened Gospel\n",
+            "1347   0.993           Unanswered\n",
+            "1332   0.992      Beautiful Agony\n",
+            "1680   0.992             Paranoia\n",
+            "2015   0.992        First Contact\n",
+            "1328   0.991  Down into the Abyss\n",
+            "1296   0.990         Black Colors\n",
+            "1681   0.990                Hated\n"
+          ]
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 1200x700 with 1 Axes>"
+            ],
+            "image/png": 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\n"
+          },
+          "metadata": {}
+        }
+      ],
+      "source": [
+        "# Top 10 energetic tracks\n",
+        "energetic_tracks = df[['energy', 'song_title']].nlargest(10, 'energy')\n",
+        "print(\"Top 10 Energetic Tracks are :\")\n",
+        "print(energetic_tracks)\n",
+        "\n",
+        "# Defining a color palette\n",
+        "colors = sns.color_palette(\"viridis\", len(energetic_tracks))\n",
+        "\n",
+        "# Plotting a horizontal bar chart for the energy of the top 10 tracks with colorful bars\n",
+        "plt.figure(figsize=(12, 7))\n",
+        "sns.barplot(x=\"song_title\", y=\"energy\", data=energetic_tracks, palette=colors)\n",
+        "plt.title(\"Top 10 Energetic Tracks can be represented as follows :\")\n",
+        "plt.xlabel(\"Song Title\")\n",
+        "plt.ylabel(\"Energy\")\n",
+        "plt.xticks(rotation=45, ha='right')  # Rotating x-axis labels for better readability\n",
+        "plt.show()\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "f8SLd8w2U7xQ"
+      },
+      "source": [
+        "Top Ten Tracks With Most Valence"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 1000
+        },
+        "id": "7kNHprwZUoeq",
+        "outputId": "985aa2da-47f6-4f57-d11c-65f85088ca19"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Top 10 Tracks with Most Valence are:\n",
+            "      valence                                         song_title\n",
+            "460     0.992                             Abataka - Original Mix\n",
+            "912     0.975                I'm Walkin' - 2002 Digital Remaster\n",
+            "1966    0.974        To Roz Bikini (Itsy, Bitsy, Teenie, Weenie)\n",
+            "48      0.973                              Azon de ma gnin kpevi\n",
+            "207     0.973                                        Look at You\n",
+            "337     0.972  Let's Lovedance Tonight - Danny Krivit Re-edit...\n",
+            "1590    0.972                                   Jelly On A Plate\n",
+            "838     0.971  Let's Lovedance Tonight - Danny Krivit Re-edit...\n",
+            "497     0.968                               Mi Swing es Tropical\n",
+            "72      0.967                                             Spooky\n"
+          ]
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 1200x700 with 1 Axes>"
+            ],
+            "image/png": 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\n"
+          },
+          "metadata": {}
+        }
+      ],
+      "source": [
+        "# Top 10 tracks with most valence\n",
+        "trending_genre = df[['valence', 'song_title']].nlargest(10, 'valence')\n",
+        "print(\"Top 10 Tracks with Most Valence are:\")\n",
+        "print(trending_genre)\n",
+        "\n",
+        "# Defining a color palette\n",
+        "colors_valence = sns.color_palette(\"YlGnBu\", len(trending_genre))\n",
+        "\n",
+        "# Plotting a horizontal bar chart for the valence of the top 10 tracks with colorful bars\n",
+        "plt.figure(figsize=(12, 7))\n",
+        "sns.barplot(x=\"song_title\", y=\"valence\", data=trending_genre, palette=colors_valence)\n",
+        "plt.title(\"Top 10 Tracks with Most Valence can be represented as follows : \")\n",
+        "plt.xlabel(\"Song Title\")\n",
+        "plt.ylabel(\"Valence\")\n",
+        "plt.xticks(rotation=45, ha='right')  # Rotate x-axis labels for better readability\n",
+        "plt.show()"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "aH7EgmotWWrH"
+      },
+      "source": [
+        "Artists With The Most Number Of Songs - Top Five"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 784
+        },
+        "id": "N7mkG_seWOXR",
+        "outputId": "5abeb6e7-1480-49f1-8577-63f8e6c8a63c"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Top 5 Most Popular Songs are:\n",
+            "song_title\n",
+            "Jack                                    3\n",
+            "River                                   3\n",
+            "I Know There's Gonna Be (Good Times)    2\n",
+            "Forever                                 2\n",
+            "What I Might Do - Club Mix              2\n",
+            "Name: artist, dtype: int64\n"
+          ]
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 1000x700 with 1 Axes>"
+            ],
+            "image/png": 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\n"
+          },
+          "metadata": {}
+        }
+      ],
+      "source": [
+        "# Artist with most number of songs (top 5)\n",
+        "most_popular = df.groupby(\"song_title\").count().sort_values(by=\"artist\", ascending=False)[\"artist\"][:5]\n",
+        "print(\"Top 5 Most Popular Songs are:\")\n",
+        "print(most_popular)\n",
+        "\n",
+        "# Defining a color palette\n",
+        "colors_popular = sns.color_palette(\"viridis\", len(most_popular))\n",
+        "\n",
+        "# Plotting a horizontal bar chart for the most popular songs with colorful bars\n",
+        "plt.figure(figsize=(10, 7))\n",
+        "most_popular.plot(kind='barh', color=colors_popular)\n",
+        "plt.title(\"Top 5 Most Popular Songs can be represented as follows : \")\n",
+        "plt.xlabel(\"Number of Songs\")\n",
+        "plt.ylabel(\"Song Title\")\n",
+        "plt.show()"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "CNnZHUXvWzrs"
+      },
+      "source": [
+        "Songs With The Most Liveness - Top FIVE"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 613
+        },
+        "id": "X-O0Vr71Wvmu",
+        "outputId": "8dcdd24b-fded-4bfc-8d1f-b37340c843ad"
+      },
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 1000x700 with 1 Axes>"
+            ],
+            "image/png": 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dH6d06dKqWrWq9XHevHlVsmRJhYWFWZft2LFDlSpVsukVkTt37ni/jc2ZM6ckaevWrXrw4METr+dRefPm1WuvvWb9TfDBgwdlb28vX19fXb16VWfOnJH0sAdL5cqVrT0mnoaXl5defvll6+O4a3/0ep9Gcu7j+vXrVaVKFeXKlUvXr1+3/nF3d1dsbGyKhlp6e3tr48aNio6O1oYNG2Rvb68GDRrE2y42Nla7du1SgwYNVLRoUevyAgUKqFmzZvr99991584dSVKuXLl08uRJ6/1OLyVLllTZsmUVHBxsXRYbG6sNGzbI09NTWbJkkfTwfubMmVO1atWyuZ/ly5dXtmzZ4g1hTM3nKFeuXLp79+4Th7s97f389ddfVaZMmQR7ZcS1fXt7e2sPQrPZrJs3byomJkYuLi7666+/4u1ntN2/++67Nj2d3n//fWXKlMn6frJ7925FRESoadOmNvfNzs5OFStWjPdcJOadd96Rvb299fHTHLddu3bWf5tMJrVr104PHjzQnj17bLZr2LCh8ubNa3188+ZN7d27V02aNNGdO3es57px44Y8PDx05swZXb58WVLSz21KjvXotT/63la1alXFxsYqPDw8yfuW3Ha7fft2ZcqUSe+//751X3t7e7Vv3z7Jc0hS5syZZWf38Efj2NhY3bhxQ9myZVPJkiVt2l2uXLl06dKlFA3DfJJt27bJ1dXV5vWbPXt2vfvuuwoPD9c///yTomNJSX9GPu3nkpFrnz9/Pr2X/iMYIgcAwAsqPDxcBQoUUI4cOWyWxw1/evw/98WLF493jBIlSuju3bu6fv26zZCepGTOnFnt2rXT0KFD9ccff9j85zkhrq6u8vf3V3R0tI4fP65NmzZpzpw56tu3r4KCglS6dGmFh4fLzs5OxYoVs9k3f/78ypUrV7zrKVSoULzzvPzyyzbzq4SHh6tSpUrxtnv8HNWrV1ejRo3k7++vOXPmqHr16mrQoIG8vb2TnDy3atWq1v/YHzhwQC4uLqpQoYJy586tAwcOyNHRUcePH1ezZs2eeJykPH69cT90R0REpOpx44796H08e/asTpw4YR3W9rhH51tJipeXl8aOHavt27dr1apVqlevXrw2HHfMu3fvqmTJkvHWlSpVSmazWRcvXtTrr7+uPn36qEePHmrUqJGcnJzk4eGhFi1aqEyZMsmuK7V4eXnp+++/1+XLl1WwYEHt379f165dU5MmTazbnD17Vrdv3070fj4++X1qPkdt27bVunXr9NFHH6lgwYKqVauWmjRpojp16li3fdr7ee7cOTVs2PCJ20gPh9v+/PPPOn36tE2gm9BQNKPt/vH3vezZsyt//vzW95O4H7bjhgc+LqG2mZDHa0/pce3s7GyCVEnWtv/4e9/j5zp37pwsFosmTpyoiRMnJni+a9euqWDBgkk+tyk5VpzChQvbrI+bby85z1Fy2214eLjy58+v7Nmz26xP6P0hIWazWfPmzdMvv/yi8+fP2/xSJXfu3NZ/f/TRR9q9e7fatGmj4sWLq1atWmrWrJmqVKmSrPM87sKFC9ahvI+KG6584cKFZA1Rl5Siz8in+VxK7WvHi4mACQAApIm4H/wSmjA3MZkzZ5arq6tcXV1VokQJDRo0SOvXr1evXr2s2yS3l8+jvQWMMplMmjRpkg4dOqT//e9/2rFjh7744gvNnj1bS5YsifdDzaOqVKmipUuXKiwsTAcOHFCVKlVkMplUuXJl/f777ypQoIDMZnOSIVxSErtey2MTuqfWcR9lNptVq1YtdenSJcH1JUqUSPb5ChQooOrVq2v27Nk6ePCgJk+enOx9E1OtWjVt3LhRmzdv1q5du7R8+XLNnTtXw4YNU5s2bQwfPyWaNGmi7777TuvWrdMHH3ygdevWKWfOnDYBjtlsVr58+TR+/PgEj/Fo7xQpdZ+jfPnyKSgoSDt37tT27du1fft2BQQE6O2339bYsWMlpe39XLlypfz8/NSgQQP5+voqX758sre31/Tp0xPslZRW7f7x43z77bcJhuzJfZ95/FshU+u4CYnrCRcnbjLszp07q3bt2gnuExdKJPXcpuRYceJ6Bj0uOc9Rar63PMm0adM0ceJEtWrVSn379tXLL78sOzs7ffPNNzZ1lipVSuvXr9fWrVu1Y8cO/frrr/rll1/Us2dPm0n601NyPiOf5nMpI1w70h8BEwAAL6giRYpoz549unPnjs1vw0+dOmVd/6izZ8/GO8aZM2eUNWvWeD/QJkfcD4NPs68k63C9f//9V9LDes1ms86ePWszCfXVq1cVERER73qSo0iRIgle97lz5xLcvlKlSqpUqZL69eun1atXq3///goODn7iD9Vxv93dtWuXjh49qq5du0p6+IPcokWLVKBAAWXLlk3ly5d/Yq1Ghs+l9XGLFSumqKgoubu7p0JFDyf7/vLLL5UrVy6b4OVRefPmVdasWXX69Ol4606dOiU7Ozub3i25c+dWq1at1KpVK0VGRqp9+/aaPHmy9blLq/v7uKJFi8rV1VXr1q1T+/bt9euvv6pBgwY2PeGKFSumPXv2qHLlyvHCgqeVkucoc+bM8vT0lKenp8xms77++mstWbJEPXr0sPb4Sep+JlZDUt+8tmHDBhUtWlT+/v42z8mkSZOSeaUpc/bsWb3xxhvWx5GRkbpy5Yq13cX1GsqXL1+qte+nOa7ZbFZYWJhNj5y4tp/Ue1/cuRwcHJJ1ric9tyk9VnIl9vpLbrstUqSI9u7dq8jISJvAP6H3h4Rs2LBBNWrU0DfffGOzPCIiQnny5LFZli1bNnl5ecnLy0vR0dHq3bu3pk2bpo8//jhekJiUwoULJ/oeFrc+uVLyGfm0n0upee14MTEHEwAAL6g6deooNjbW+vXrcebMmSOTyRTvB/eQkBD9+eef1scXL17U5s2bVatWrSf+Nj2h4U937tzR3LlzlSdPniSDk7179yb4m+y47vtxQwXivtr70a9Ll6TZs2fbrE8JDw8PHTp0SMeOHbMuu3nzZryvXb5161a8GuPmbXr0658TUrRoURUsWFBz5sxRTEyMKleuLOnhEIVz585p/fr1qlixojJlevLv/bJmzSrJ+JC3xI6b3K/zTkiTJk0UEhKiHTt2xFsXERGhmJiYFB2vcePG6tWrl4YOHZroEER7e3vVqlVLmzdv1vnz563Lr169qjVr1qhKlSrWYPXGjRs2+2bPnl3FihWzee7S6v4mxMvLS4cOHdKKFSt048YNm+Fx0sP7GRsbq6lTp8bbNyYm5qlqTO5z9Pi9srOzs36letz9Ss79TEjDhg11/PjxBL99Me71Ffde8+jr7fDhwzp06NATj/20lixZYjMMb9GiRYqJibG+P9auXVs5cuTQ9OnTE5x/LSXDPx/1NMd99L3c8v+/8t7BwSHR4WNx8uXLp+rVq2vJkiXWwD6xcyX13KbkWCmRNWvWBNt1ctttnTp1FBMTo0WLFlnXx8bGasGCBck6v729fbz3+HXr1sWbT+rx+5M5c2aVKlVKFoslRfPzxalbt66OHDmikJAQ67KoqCgtXbpURYoUUenSpVN0LCl5n5FP87lk5NovXLig0NDQZF8LMi56MAEA8ILy9PRUjRo1NGHCBIWHh8vZ2Vm7du3S5s2b1alTp3jDGJycnOTr66sOHTooc+bM1v+o9+7d+4nnWbhwoTZt2qQ333xThQsX1r///quAgABduHBB3377bZJzFI0cOVJ3797VW2+9pddee00PHjzQwYMHtW7dOhUpUkQtW7aUJJUpU0Y+Pj5asmSJIiIiVK1aNR09elSBgYFq0KCBTS+E5OrSpYtWrVqlDz/8UO3bt1e2bNm0bNkyFSpUSDdv3rT+Vj0wMFCLFi1SgwYNVKxYMUVGRmrp0qXKkSNHoj1sHlW1alWtXbtWTk5O1jliypUrp2zZsunMmTNJfsWzJGtQN3LkSHl4eMje3l5NmzZN8TU/rmzZsrK3t9fMmTN1+/ZtZc6cWW+88Yby5cuX7GP4+vpqy5Yt6tatm3x8fFS+fHndvXtXf//9tzZs2KDNmzenqCdbzpw5k2x3kvTJJ59o9+7datu2rdq2bSt7e3stWbJE0dHR+vzzz63bNW3aVNWrV1f58uWVO3duHT16VBs2bLCZAPhp7u/169cTDIFeffVVNW/ePNH9mjRporFjx2rs2LHKnTt3vN4Z1atX17vvvqvp06fr2LFjqlWrlhwcHHTmzBmtX79egwcPVuPGjZO8P49K7nP05Zdf6tatW3rjjTdUsGBBXbhwQQsWLFDZsmWtvSKScz8Tq2HDhg3q27evWrVqpfLly+vWrVvasmWLhg0bpjJlyqhevXr69ddf1bNnT9WrV0/nz5/X4sWLVbp0aUVFRaXompPjwYMH+uCDD9SkSROdPn1av/zyi6pUqaL69etLejgX0tdff60BAwaoZcuW8vLyUt68eXXhwgVt27ZNlStX1pAhQ1J83pQe96WXXtKOHTs0cOBAubq6aseOHdq6dau6deuWrNfW0KFD1bZtW3l7e+udd95R0aJFdfXqVR06dEiXLl3SqlWrJCXvuU3usVKifPnyWrRokaZOnarixYsrb968qlmzZrLbraenpypXrqzvvvtO4eHhKl26tH799ddkB+f16tXTlClTNGjQILm5uenvv//W6tWr48175evrK0dHR1WuXFn58uXTqVOntGDBAtWtWzfZ83E9qmvXrlq7dq0++ugjdejQQS+//LKCgoJ0/vx5TZ48OdHhhQlJ6WdkSj+XjFz7wIEDtX//fib6/g8gYAIA4AVlZ2enH3/8UZMmTVJwcLACAgJUpEgRDRgwwPqtMo+qVq2aKlWqpClTpujChQsqXbq0Ro8eneTEvZUrV1ZISIiWL1+umzdvKmvWrHJ1ddWoUaOS/M26JA0YMEDr16/Xtm3brL0JChcurLZt26p79+7WCWGlhz/8v/rqqwoMDNSmTZvk6Oiojz/+2GaOppQoVKiQ5s2bp5E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+          },
+          "metadata": {}
+        }
+      ],
+      "source": [
+        "# Top 5 songs with the most liveness\n",
+        "more_liveness = df.sort_values(by=\"liveness\", ascending=False)[[\"song_title\", \"liveness\"]][:5]\n",
+        "\n",
+        "# Plot a bar chart for the liveness of the top 5 tracks\n",
+        "plt.figure(figsize=(10, 7))\n",
+        "sns.barplot(x=\"liveness\", y=\"song_title\", data=more_liveness, palette=\"magma\")\n",
+        "plt.title(\"Top 5 Songs with the Most Liveness can be represented as follows : \")\n",
+        "plt.xlabel(\"Liveness\")\n",
+        "plt.ylabel(\"Song Title\")\n",
+        "plt.show()\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "y0NvmpR3XrkM"
+      },
+      "source": [
+        "Songs with More Danceability - Top Ten"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 363
+        },
+        "id": "anRKhwNfXmUC",
+        "outputId": "ed56155d-a26f-4288-bfde-a8fe48db8ef0"
+      },
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "                  song_title  danceability\n",
+              "1433  Flashwind - Radio Edit         0.984\n",
+              "1901                SexyBack         0.967\n",
+              "604        Check Me Out Like         0.962\n",
+              "32               Best Friend         0.959\n",
+              "1957            Ice Ice Baby         0.959\n",
+              "1136                Bad Liar         0.950\n",
+              "1977                 Fuck Kd         0.947\n",
+              "138     Sippin On Some Syrup         0.944\n",
+              "623            I'm Different         0.941\n",
+              "1591      Little Green Apple         0.941"
+            ],
+            "text/html": [
+              "\n",
+              "  <div id=\"df-254b7d48-0606-46ff-b350-f3f44553d536\" 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",
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+              "\n",
+              "    .dataframe thead th {\n",
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+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>song_title</th>\n",
+              "      <th>danceability</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>1433</th>\n",
+              "      <td>Flashwind - Radio Edit</td>\n",
+              "      <td>0.984</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1901</th>\n",
+              "      <td>SexyBack</td>\n",
+              "      <td>0.967</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>604</th>\n",
+              "      <td>Check Me Out Like</td>\n",
+              "      <td>0.962</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>32</th>\n",
+              "      <td>Best Friend</td>\n",
+              "      <td>0.959</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1957</th>\n",
+              "      <td>Ice Ice Baby</td>\n",
+              "      <td>0.959</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1136</th>\n",
+              "      <td>Bad Liar</td>\n",
+              "      <td>0.950</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1977</th>\n",
+              "      <td>Fuck Kd</td>\n",
+              "      <td>0.947</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>138</th>\n",
+              "      <td>Sippin On Some Syrup</td>\n",
+              "      <td>0.944</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>623</th>\n",
+              "      <td>I'm Different</td>\n",
+              "      <td>0.941</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1591</th>\n",
+              "      <td>Little Green Apple</td>\n",
+              "      <td>0.941</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>\n",
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+              "    }\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",
+              "    .colab-df-buttons div {\n",
+              "      margin-bottom: 4px;\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-254b7d48-0606-46ff-b350-f3f44553d536 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-254b7d48-0606-46ff-b350-f3f44553d536');\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",
+              "\n",
+              "\n",
+              "<div id=\"df-6bb65756-cfa9-4333-8199-e8c81224b8d5\">\n",
+              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-6bb65756-cfa9-4333-8199-e8c81224b8d5')\"\n",
+              "            title=\"Suggest charts\"\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",
+              "    <g>\n",
+              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
+              "    </g>\n",
+              "</svg>\n",
+              "  </button>\n",
+              "\n",
+              "<style>\n",
+              "  .colab-df-quickchart {\n",
+              "      --bg-color: #E8F0FE;\n",
+              "      --fill-color: #1967D2;\n",
+              "      --hover-bg-color: #E2EBFA;\n",
+              "      --hover-fill-color: #174EA6;\n",
+              "      --disabled-fill-color: #AAA;\n",
+              "      --disabled-bg-color: #DDD;\n",
+              "  }\n",
+              "\n",
+              "  [theme=dark] .colab-df-quickchart {\n",
+              "      --bg-color: #3B4455;\n",
+              "      --fill-color: #D2E3FC;\n",
+              "      --hover-bg-color: #434B5C;\n",
+              "      --hover-fill-color: #FFFFFF;\n",
+              "      --disabled-bg-color: #3B4455;\n",
+              "      --disabled-fill-color: #666;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart {\n",
+              "    background-color: var(--bg-color);\n",
+              "    border: none;\n",
+              "    border-radius: 50%;\n",
+              "    cursor: pointer;\n",
+              "    display: none;\n",
+              "    fill: var(--fill-color);\n",
+              "    height: 32px;\n",
+              "    padding: 0;\n",
+              "    width: 32px;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart:hover {\n",
+              "    background-color: var(--hover-bg-color);\n",
+              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "    fill: var(--button-hover-fill-color);\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart-complete:disabled,\n",
+              "  .colab-df-quickchart-complete:disabled:hover {\n",
+              "    background-color: var(--disabled-bg-color);\n",
+              "    fill: var(--disabled-fill-color);\n",
+              "    box-shadow: none;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-spinner {\n",
+              "    border: 2px solid var(--fill-color);\n",
+              "    border-color: transparent;\n",
+              "    border-bottom-color: var(--fill-color);\n",
+              "    animation:\n",
+              "      spin 1s steps(1) infinite;\n",
+              "  }\n",
+              "\n",
+              "  @keyframes spin {\n",
+              "    0% {\n",
+              "      border-color: transparent;\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "      border-left-color: var(--fill-color);\n",
+              "    }\n",
+              "    20% {\n",
+              "      border-color: transparent;\n",
+              "      border-left-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "    }\n",
+              "    30% {\n",
+              "      border-color: transparent;\n",
+              "      border-left-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "      border-right-color: var(--fill-color);\n",
+              "    }\n",
+              "    40% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "    }\n",
+              "    60% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "    }\n",
+              "    80% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "    }\n",
+              "    90% {\n",
+              "      border-color: transparent;\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "    }\n",
+              "  }\n",
+              "</style>\n",
+              "\n",
+              "  <script>\n",
+              "    async function quickchart(key) {\n",
+              "      const quickchartButtonEl =\n",
+              "        document.querySelector('#' + key + ' button');\n",
+              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
+              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
+              "      try {\n",
+              "        const charts = await google.colab.kernel.invokeFunction(\n",
+              "            'suggestCharts', [key], {});\n",
+              "      } catch (error) {\n",
+              "        console.error('Error during call to suggestCharts:', error);\n",
+              "      }\n",
+              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
+              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
+              "    }\n",
+              "    (() => {\n",
+              "      let quickchartButtonEl =\n",
+              "        document.querySelector('#df-6bb65756-cfa9-4333-8199-e8c81224b8d5 button');\n",
+              "      quickchartButtonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "    })();\n",
+              "  </script>\n",
+              "</div>\n",
+              "    </div>\n",
+              "  </div>\n"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 21
+        }
+      ],
+      "source": [
+        "More_danceability = df.sort_values(by = \"danceability\",ascending=False)[[\"song_title\",\"danceability\"]][:10]\n",
+        "More_danceability"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 641
+        },
+        "id": "AATtqvmNX4c_",
+        "outputId": "47d455c1-c20e-4042-c316-5726a1c00c0a"
+      },
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 1000x700 with 1 Axes>"
+            ],
+            "image/png": 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\n"
+          },
+          "metadata": {}
+        }
+      ],
+      "source": [
+        "plt.figure(figsize=(10, 7))\n",
+        "sns.barplot(x=\"danceability\", y=\"song_title\", data=More_danceability)\n",
+        "plt.title(\"Songs with More Danceability can be represented as follows :\")\n",
+        "plt.show()"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "bKx0eSFgYPHd"
+      },
+      "source": [
+        "Songs With The Most Duration - Top Five"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 541
+        },
+        "id": "65wJQXiVYO1D",
+        "outputId": "6b0c15de-0eb5-455d-dcef-1514ac55f8b0"
+      },
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 1200x700 with 1 Axes>"
+            ],
+            "image/png": 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+          },
+          "metadata": {}
+        }
+      ],
+      "source": [
+        "# Top 5 songs with the most duration\n",
+        "most_duration = df.sort_values(by=\"duration_ms\", ascending=False)[[\"song_title\", \"duration_ms\"]][:5]\n",
+        "\n",
+        "# Plotting a bar chart for the duration of the top 5 tracks\n",
+        "plt.figure(figsize=(12, 7))\n",
+        "sns.barplot(x=\"duration_ms\", y=\"song_title\", data=most_duration, palette=\"viridis\")\n",
+        "plt.title(\"Top 5 Songs with the Most Duration can be represented as follows : \")\n",
+        "plt.xlabel(\"Duration (ms)\")\n",
+        "plt.ylabel(\"Song Title\")\n",
+        "plt.show()"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 1000
+        },
+        "id": "IPUuiuYUX7Wo",
+        "outputId": "3d8e128e-a747-4667-987b-c6295ac7a799"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Random Forest:\n",
+            "Best Model Parameters: {'rf__max_depth': None, 'rf__min_samples_leaf': 1, 'rf__min_samples_split': 2, 'rf__n_estimators': 50}\n",
+            "Cross-Validation Scores: [0.78947368 0.78018576 0.76160991 0.76397516 0.77950311]\n",
+            "Mean CV Accuracy: 0.7749495221429532\n",
+            "Accuracy on Test Set: 0.7821782178217822\n",
+            "Confusion Matrix:\n",
+            "[[158  48]\n",
+            " [ 40 158]]\n",
+            "Classification Report:\n",
+            "              precision    recall  f1-score   support\n",
+            "\n",
+            "           0       0.80      0.77      0.78       206\n",
+            "           1       0.77      0.80      0.78       198\n",
+            "\n",
+            "    accuracy                           0.78       404\n",
+            "   macro avg       0.78      0.78      0.78       404\n",
+            "weighted avg       0.78      0.78      0.78       404\n",
+            "\n"
+          ]
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 1200x500 with 3 Axes>"
+            ],
+            "image/png": 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\n"
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "/usr/local/lib/python3.10/dist-packages/sklearn/neural_network/_multilayer_perceptron.py:686: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (200) reached and the optimization hasn't converged yet.\n",
+            "  warnings.warn(\n"
+          ]
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 1800x500 with 2 Axes>"
+            ],
+            "image/png": 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+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 1800x500 with 2 Axes>"
+            ],
+            "image/png": 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+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "MLP:\n",
+            "Accuracy: 0.7351485148514851\n",
+            "Confusion Matrix:\n",
+            "[[160  46]\n",
+            " [ 61 137]]\n",
+            "Classification Report:\n",
+            "              precision    recall  f1-score   support\n",
+            "\n",
+            "           0       0.72      0.78      0.75       206\n",
+            "           1       0.75      0.69      0.72       198\n",
+            "\n",
+            "    accuracy                           0.74       404\n",
+            "   macro avg       0.74      0.73      0.73       404\n",
+            "weighted avg       0.74      0.74      0.73       404\n",
+            "\n"
+          ]
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 1800x500 with 2 Axes>"
+            ],
+            "image/png": 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+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 1800x500 with 2 Axes>"
+            ],
+            "image/png": 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+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Random Forest:\n",
+            "Accuracy: 0.7821782178217822\n",
+            "Confusion Matrix:\n",
+            "[[158  48]\n",
+            " [ 40 158]]\n",
+            "Classification Report:\n",
+            "              precision    recall  f1-score   support\n",
+            "\n",
+            "           0       0.80      0.77      0.78       206\n",
+            "           1       0.77      0.80      0.78       198\n",
+            "\n",
+            "    accuracy                           0.78       404\n",
+            "   macro avg       0.78      0.78      0.78       404\n",
+            "weighted avg       0.78      0.78      0.78       404\n",
+            "\n"
+          ]
+        }
+      ],
+      "source": [
+        "import numpy as np\n",
+        "import pandas as pd\n",
+        "from sklearn.model_selection import train_test_split, GridSearchCV, cross_val_score\n",
+        "from sklearn.ensemble import RandomForestClassifier\n",
+        "from sklearn.svm import SVC\n",
+        "from sklearn.preprocessing import StandardScaler\n",
+        "from sklearn.pipeline import Pipeline\n",
+        "from sklearn.metrics import accuracy_score, classification_report, confusion_matrix, roc_curve, auc, precision_recall_curve\n",
+        "import matplotlib.pyplot as plt\n",
+        "import seaborn as sns\n",
+        "import time\n",
+        "\n",
+        "\n",
+        "# Loading the dataset\n",
+        "df = pd.read_csv(\"/content/data.csv\")\n",
+        "df.drop(\"Unnamed: 0\", axis=1, inplace=True)\n",
+        "\n",
+        "# Defining features (X) and target variable (y)\n",
+        "X = df.drop(['target', 'song_title', 'artist'], axis=1)  # Adjust features accordingly\n",
+        "y = df['target']\n",
+        "\n",
+        "# Splitting the data into training and testing sets\n",
+        "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n",
+        "\n",
+        "# Constructing a pipeline with preprocessing and RandomForestClassifier\n",
+        "rf_pipeline = Pipeline([\n",
+        "    ('scaler', StandardScaler()),  # Standardize features\n",
+        "    ('rf', RandomForestClassifier(random_state=42))\n",
+        "])\n",
+        "\n",
+        "# Defining the parameter grid for grid search\n",
+        "rf_param_grid = {\n",
+        "    'rf__n_estimators': [50, 100, 200],\n",
+        "    'rf__max_depth': [None, 10, 20],\n",
+        "    'rf__min_samples_split': [2, 5, 10],\n",
+        "    'rf__min_samples_leaf': [1, 2, 4]\n",
+        "}\n",
+        "\n",
+        "# Initializing GridSearchCV with cross-validation for Random Forest\n",
+        "rf_grid_search = GridSearchCV(rf_pipeline, rf_param_grid, cv=5, n_jobs=-1)\n",
+        "rf_grid_search.fit(X_train, y_train)\n",
+        "\n",
+        "# Getting the best Random Forest model from grid search\n",
+        "best_rf_model = rf_grid_search.best_estimator_\n",
+        "\n",
+        "# Cross-validating the best Random Forest model\n",
+        "rf_cv_scores = cross_val_score(best_rf_model, X_train, y_train, cv=5, scoring='accuracy')\n",
+        "\n",
+        "# Making predictions on the test set using Random Forest\n",
+        "rf_predictions = best_rf_model.predict(X_test)\n",
+        "\n",
+        "# Evaluating the Random Forest model\n",
+        "rf_accuracy = accuracy_score(y_test, rf_predictions)\n",
+        "rf_conf_matrix = confusion_matrix(y_test, rf_predictions)\n",
+        "rf_class_report = classification_report(y_test, rf_predictions)\n",
+        "\n",
+        "# Printting evaluation metrics for Random Forest\n",
+        "print(\"Random Forest:\")\n",
+        "print(f\"Best Model Parameters: {rf_grid_search.best_params_}\")\n",
+        "print(f\"Cross-Validation Scores: {rf_cv_scores}\")\n",
+        "print(f\"Mean CV Accuracy: {rf_cv_scores.mean()}\")\n",
+        "print(f\"Accuracy on Test Set: {rf_accuracy}\")\n",
+        "print(f\"Confusion Matrix:\\n{rf_conf_matrix}\")\n",
+        "print(f\"Classification Report:\\n{rf_class_report}\")\n",
+        "\n",
+        "# Visualizing the confusion matrix for Random Forest\n",
+        "plt.figure(figsize=(12, 5))\n",
+        "plt.subplot(1, 2, 1)\n",
+        "sns.heatmap(rf_conf_matrix, annot=True, fmt='d', cmap='Blues', xticklabels=['Not Popular', 'Popular'],\n",
+        "            yticklabels=['Not Popular', 'Popular'])\n",
+        "plt.title('Random Forest Confusion Matrix')\n",
+        "plt.xlabel('Predicted Label')\n",
+        "plt.ylabel('True Label')\n",
+        "\n",
+        "# Visualizing feature importances for Random Forest\n",
+        "plt.subplot(1, 2, 2)\n",
+        "rf_feature_importances = best_rf_model.named_steps['rf'].feature_importances_\n",
+        "rf_features = X.columns\n",
+        "sns.barplot(x=rf_feature_importances, y=rf_features, palette='viridis')\n",
+        "plt.title('Random Forest Feature Importances')\n",
+        "plt.xlabel('Importance')\n",
+        "plt.ylabel('Feature')\n",
+        "\n",
+        "plt.tight_layout()\n",
+        "plt.show()\n",
+        "\n",
+        "# Function for model evaluation considering enhanced visualization\n",
+        "from sklearn.neural_network import MLPClassifier\n",
+        "\n",
+        "# Constructing a pipeline with preprocessing and MLPClassifier\n",
+        "mlp_pipeline_proba = Pipeline([\n",
+        "    ('scaler', StandardScaler()),  # Standardizing the features\n",
+        "    ('mlp', MLPClassifier(random_state=42))\n",
+        "])\n",
+        "\n",
+        "# Defining the parameter grid for grid search for MLP with probability estimates\n",
+        "mlp_param_grid = {\n",
+        "    'mlp__hidden_layer_sizes': [(100,), (50, 50), (20, 20, 20)],\n",
+        "    'mlp__activation': ['relu', 'tanh'],\n",
+        "    'mlp__alpha': [0.0001, 0.001, 0.01],\n",
+        "}\n",
+        "\n",
+        "# Initializing GridSearchCV with cross-validation for MLP with probability estimates\n",
+        "mlp_grid_search_proba = GridSearchCV(mlp_pipeline_proba, mlp_param_grid, cv=5, n_jobs=-1)\n",
+        "mlp_grid_search_proba.fit(X_train, y_train)\n",
+        "\n",
+        "# Getting the best MLP model with probability estimates from grid search\n",
+        "best_mlp_model_proba = mlp_grid_search_proba.best_estimator_\n",
+        "def evaluate_model_visual(model, X_train, y_train, X_test, y_test, model_name):\n",
+        "    # Predictions on the training set\n",
+        "    train_predictions = model.predict(X_train)\n",
+        "\n",
+        "    try:\n",
+        "        train_probabilities = model.predict_proba(X_train)[:, 1]\n",
+        "        fpr_train, tpr_train, _ = roc_curve(y_train, train_probabilities)\n",
+        "        precision_train, recall_train, _ = precision_recall_curve(y_train, train_probabilities)\n",
+        "\n",
+        "        # Plot ROC curve\n",
+        "        # Plot ROC curve\n",
+        "        plt.figure(figsize=(18, 5))  # Increase the width to provide more space\n",
+        "\n",
+        "# Subplotting for ROC curve\n",
+        "        plt.subplot(1, 2, 1)\n",
+        "        plt.plot(fpr_train, tpr_train, color='darkorange', lw=2, label='Training (AUC = {:.2f})'.format(auc(fpr_train, tpr_train)))\n",
+        "        plt.plot([0, 1], [0, 1], color='navy', lw=2, linestyle='--')\n",
+        "        plt.xlabel('False Positive Rate')\n",
+        "        plt.ylabel('True Positive Rate')\n",
+        "        plt.title(f'{model_name} ROC Curve (Training)')\n",
+        "        plt.legend(loc=\"lower right\")\n",
+        "\n",
+        "        # Subplotting for Precision-Recall curve\n",
+        "        plt.subplot(1, 2, 2)\n",
+        "        plt.plot(recall_train, precision_train, color='darkorange', lw=2, label='Training')\n",
+        "        plt.xlabel('Recall')\n",
+        "        plt.ylabel('Precision')\n",
+        "        plt.title(f'{model_name} Precision-Recall Curve (Training)')\n",
+        "        plt.legend(loc=\"lower right\")\n",
+        "\n",
+        "        plt.tight_layout(pad=3.0)  # Add space between subplots\n",
+        "        plt.show()\n",
+        "\n",
+        "\n",
+        "    except AttributeError:\n",
+        "        print(f\"{model_name} does not support predict_proba. Skipping ROC and Precision-Recall curves for training.\")\n",
+        "\n",
+        "    # Predictions on the test set\n",
+        "    test_predictions = model.predict(X_test)\n",
+        "\n",
+        "    try:\n",
+        "        test_probabilities = model.predict_proba(X_test)[:, 1]\n",
+        "        fpr_test, tpr_test, _ = roc_curve(y_test, test_probabilities)\n",
+        "        precision_test, recall_test, _ = precision_recall_curve(y_test, test_probabilities)\n",
+        "\n",
+        "        # Plotting ROC curve\n",
+        "        plt.figure(figsize=(18, 5))\n",
+        "\n",
+        "        plt.subplot(1, 2, 1)\n",
+        "        plt.plot(fpr_test, tpr_test, color='cornflowerblue', lw=2, label='Testing (AUC = {:.2f})'.format(auc(fpr_test, tpr_test)))\n",
+        "        plt.plot([0, 1], [0, 1], color='navy', lw=2, linestyle='--')\n",
+        "        plt.xlabel('False Positive Rate')\n",
+        "        plt.ylabel('True Positive Rate')\n",
+        "        plt.title(f'{model_name} ROC Curve (Testing)')\n",
+        "        plt.legend(loc=\"lower right\")\n",
+        "\n",
+        "        # Plotting Precision-Recall curve\n",
+        "        plt.subplot(1, 2, 2)\n",
+        "        plt.plot(recall_test, precision_test, color='cornflowerblue', lw=2, label='Testing')\n",
+        "        plt.xlabel('Recall')\n",
+        "        plt.ylabel('Precision')\n",
+        "        plt.title(f'{model_name} Precision-Recall Curve (Testing)')\n",
+        "        plt.legend(loc=\"lower right\")\n",
+        "    except AttributeError:\n",
+        "        print(f\"{model_name} does not support predict_proba. Skipping ROC and Precision-Recall curves for testing.\")\n",
+        "\n",
+        "    plt.tight_layout(pad=3.0)  # Add space between subplots\n",
+        "    plt.show()\n",
+        "\n",
+        "    # Confusion Matrix\n",
+        "    conf_matrix = confusion_matrix(y_test, test_predictions)\n",
+        "\n",
+        "    # Printing evaluation metrics\n",
+        "    accuracy = accuracy_score(y_test, test_predictions)\n",
+        "    class_report = classification_report(y_test, test_predictions)\n",
+        "\n",
+        "    print(f\"{model_name}:\")\n",
+        "    print(f\"Accuracy: {accuracy}\")\n",
+        "    print(f\"Confusion Matrix:\\n{conf_matrix}\")\n",
+        "    print(f\"Classification Report:\\n{class_report}\")\n",
+        "\n",
+        "evaluate_model_visual(best_mlp_model_proba, X_train, y_train, X_test, y_test, 'MLP')\n",
+        "\n",
+        "# Visualizing the results with probability estimates for Random Forest\n",
+        "evaluate_model_visual(best_rf_model, X_train, y_train, X_test, y_test, 'Random Forest')\n",
+        "\n",
+        "\n",
+        "\n",
+        "\n",
+        "\n",
+        "\n",
+        "\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "## ***Inference after close study on both strategies***"
+      ],
+      "metadata": {
+        "id": "XKaIA0WGbYK0"
+      }
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "**For Good Performance:**\n",
+        "\n",
+        "If we want accurate and well-rounded results, go for the Random Forest model.\n",
+        "It excels in precision and overall effectiveness.\n",
+        "\n",
+        "**For Considering Interpretability and Efficiency:**\n",
+        "\n",
+        "If we prioritize understanding the model or need efficient computing, think about the MLP model.\n",
+        "We also have to be cautious about potential instability during convergence needs attention.\n",
+        "\n",
+        "\n",
+        "\n",
+        "Our choice should match what your task needs considering the trade-offs between accuracy, stability, and interpretability, especially in the Spotify dataset context."
+      ],
+      "metadata": {
+        "id": "LDrQ0p0kZ8ps"
+      }
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "99en8uArYh1B"
+      },
+      "outputs": [],
+      "source": [
+        "|"
+      ]
+    }
+  ],
+  "metadata": {
+    "colab": {
+      "provenance": []
+    },
+    "kernelspec": {
+      "display_name": "Python 3",
+      "name": "python3"
+    },
+    "language_info": {
+      "name": "python"
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 0
+}
\ No newline at end of file