Project1-Parkinson'sdisease-Notebook.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "d1aba8b4",
   "metadata": {},
   "source": [
    "#                    Detecting Parkinson’s Disease with XGBoost"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8dddae66",
   "metadata": {},
   "source": [
    "## Introduction\n",
    "The goal of the project is to Predict who is likely having the Parkinson's Disease based on the features of a user. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c8b3ddeb",
   "metadata": {},
   "source": [
    "#### Steps involved in this Notebook\n",
    "\n",
    "1. Getting to know about the Data\n",
    "2. Extract New features\n",
    "3. Check distribution of target variable\n",
    "4. Understand Relationship between variables\n",
    "5. Identifying Potential Outliers\n",
    "6. Data Cleaning\n",
    "7. Model Building\n",
    "       > XGBoost classifier\n",
    "8. Feature Importances"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0b8bf879",
   "metadata": {},
   "source": [
    "#### 1. Make necessary imports:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "123e3573",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np \n",
    "import pandas as pd \n",
    "import matplotlib.pyplot as plt \n",
    "import seaborn as sns \n",
    "import os, sys\n",
    "from sklearn.preprocessing import MinMaxScaler\n",
    "from xgboost import XGBClassifier\n",
    "from sklearn.model_selection import train_test_split \n",
    "from sklearn.metrics import accuracy_score\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6eb4a4fb",
   "metadata": {},
   "source": [
    "#### 2. Now, let’s read the data into a DataFrame and get the first 5 records."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "236a04ae",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>MDVP:Fo(Hz)</th>\n",
       "      <th>MDVP:Fhi(Hz)</th>\n",
       "      <th>MDVP:Flo(Hz)</th>\n",
       "      <th>MDVP:Jitter(%)</th>\n",
       "      <th>MDVP:Jitter(Abs)</th>\n",
       "      <th>MDVP:RAP</th>\n",
       "      <th>MDVP:PPQ</th>\n",
       "      <th>Jitter:DDP</th>\n",
       "      <th>MDVP:Shimmer</th>\n",
       "      <th>...</th>\n",
       "      <th>Shimmer:DDA</th>\n",
       "      <th>NHR</th>\n",
       "      <th>HNR</th>\n",
       "      <th>status</th>\n",
       "      <th>RPDE</th>\n",
       "      <th>DFA</th>\n",
       "      <th>spread1</th>\n",
       "      <th>spread2</th>\n",
       "      <th>D2</th>\n",
       "      <th>PPE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>phon_R01_S01_1</td>\n",
       "      <td>119.992</td>\n",
       "      <td>157.302</td>\n",
       "      <td>74.997</td>\n",
       "      <td>0.00784</td>\n",
       "      <td>0.00007</td>\n",
       "      <td>0.00370</td>\n",
       "      <td>0.00554</td>\n",
       "      <td>0.01109</td>\n",
       "      <td>0.04374</td>\n",
       "      <td>...</td>\n",
       "      <td>0.06545</td>\n",
       "      <td>0.02211</td>\n",
       "      <td>21.033</td>\n",
       "      <td>1</td>\n",
       "      <td>0.414783</td>\n",
       "      <td>0.815285</td>\n",
       "      <td>-4.813031</td>\n",
       "      <td>0.266482</td>\n",
       "      <td>2.301442</td>\n",
       "      <td>0.284654</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>phon_R01_S01_2</td>\n",
       "      <td>122.400</td>\n",
       "      <td>148.650</td>\n",
       "      <td>113.819</td>\n",
       "      <td>0.00968</td>\n",
       "      <td>0.00008</td>\n",
       "      <td>0.00465</td>\n",
       "      <td>0.00696</td>\n",
       "      <td>0.01394</td>\n",
       "      <td>0.06134</td>\n",
       "      <td>...</td>\n",
       "      <td>0.09403</td>\n",
       "      <td>0.01929</td>\n",
       "      <td>19.085</td>\n",
       "      <td>1</td>\n",
       "      <td>0.458359</td>\n",
       "      <td>0.819521</td>\n",
       "      <td>-4.075192</td>\n",
       "      <td>0.335590</td>\n",
       "      <td>2.486855</td>\n",
       "      <td>0.368674</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>phon_R01_S01_3</td>\n",
       "      <td>116.682</td>\n",
       "      <td>131.111</td>\n",
       "      <td>111.555</td>\n",
       "      <td>0.01050</td>\n",
       "      <td>0.00009</td>\n",
       "      <td>0.00544</td>\n",
       "      <td>0.00781</td>\n",
       "      <td>0.01633</td>\n",
       "      <td>0.05233</td>\n",
       "      <td>...</td>\n",
       "      <td>0.08270</td>\n",
       "      <td>0.01309</td>\n",
       "      <td>20.651</td>\n",
       "      <td>1</td>\n",
       "      <td>0.429895</td>\n",
       "      <td>0.825288</td>\n",
       "      <td>-4.443179</td>\n",
       "      <td>0.311173</td>\n",
       "      <td>2.342259</td>\n",
       "      <td>0.332634</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>phon_R01_S01_4</td>\n",
       "      <td>116.676</td>\n",
       "      <td>137.871</td>\n",
       "      <td>111.366</td>\n",
       "      <td>0.00997</td>\n",
       "      <td>0.00009</td>\n",
       "      <td>0.00502</td>\n",
       "      <td>0.00698</td>\n",
       "      <td>0.01505</td>\n",
       "      <td>0.05492</td>\n",
       "      <td>...</td>\n",
       "      <td>0.08771</td>\n",
       "      <td>0.01353</td>\n",
       "      <td>20.644</td>\n",
       "      <td>1</td>\n",
       "      <td>0.434969</td>\n",
       "      <td>0.819235</td>\n",
       "      <td>-4.117501</td>\n",
       "      <td>0.334147</td>\n",
       "      <td>2.405554</td>\n",
       "      <td>0.368975</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>phon_R01_S01_5</td>\n",
       "      <td>116.014</td>\n",
       "      <td>141.781</td>\n",
       "      <td>110.655</td>\n",
       "      <td>0.01284</td>\n",
       "      <td>0.00011</td>\n",
       "      <td>0.00655</td>\n",
       "      <td>0.00908</td>\n",
       "      <td>0.01966</td>\n",
       "      <td>0.06425</td>\n",
       "      <td>...</td>\n",
       "      <td>0.10470</td>\n",
       "      <td>0.01767</td>\n",
       "      <td>19.649</td>\n",
       "      <td>1</td>\n",
       "      <td>0.417356</td>\n",
       "      <td>0.823484</td>\n",
       "      <td>-3.747787</td>\n",
       "      <td>0.234513</td>\n",
       "      <td>2.332180</td>\n",
       "      <td>0.410335</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>phon_R01_S01_6</td>\n",
       "      <td>120.552</td>\n",
       "      <td>131.162</td>\n",
       "      <td>113.787</td>\n",
       "      <td>0.00968</td>\n",
       "      <td>0.00008</td>\n",
       "      <td>0.00463</td>\n",
       "      <td>0.00750</td>\n",
       "      <td>0.01388</td>\n",
       "      <td>0.04701</td>\n",
       "      <td>...</td>\n",
       "      <td>0.06985</td>\n",
       "      <td>0.01222</td>\n",
       "      <td>21.378</td>\n",
       "      <td>1</td>\n",
       "      <td>0.415564</td>\n",
       "      <td>0.825069</td>\n",
       "      <td>-4.242867</td>\n",
       "      <td>0.299111</td>\n",
       "      <td>2.187560</td>\n",
       "      <td>0.357775</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>phon_R01_S02_1</td>\n",
       "      <td>120.267</td>\n",
       "      <td>137.244</td>\n",
       "      <td>114.820</td>\n",
       "      <td>0.00333</td>\n",
       "      <td>0.00003</td>\n",
       "      <td>0.00155</td>\n",
       "      <td>0.00202</td>\n",
       "      <td>0.00466</td>\n",
       "      <td>0.01608</td>\n",
       "      <td>...</td>\n",
       "      <td>0.02337</td>\n",
       "      <td>0.00607</td>\n",
       "      <td>24.886</td>\n",
       "      <td>1</td>\n",
       "      <td>0.596040</td>\n",
       "      <td>0.764112</td>\n",
       "      <td>-5.634322</td>\n",
       "      <td>0.257682</td>\n",
       "      <td>1.854785</td>\n",
       "      <td>0.211756</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>phon_R01_S02_2</td>\n",
       "      <td>107.332</td>\n",
       "      <td>113.840</td>\n",
       "      <td>104.315</td>\n",
       "      <td>0.00290</td>\n",
       "      <td>0.00003</td>\n",
       "      <td>0.00144</td>\n",
       "      <td>0.00182</td>\n",
       "      <td>0.00431</td>\n",
       "      <td>0.01567</td>\n",
       "      <td>...</td>\n",
       "      <td>0.02487</td>\n",
       "      <td>0.00344</td>\n",
       "      <td>26.892</td>\n",
       "      <td>1</td>\n",
       "      <td>0.637420</td>\n",
       "      <td>0.763262</td>\n",
       "      <td>-6.167603</td>\n",
       "      <td>0.183721</td>\n",
       "      <td>2.064693</td>\n",
       "      <td>0.163755</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>phon_R01_S02_3</td>\n",
       "      <td>95.730</td>\n",
       "      <td>132.068</td>\n",
       "      <td>91.754</td>\n",
       "      <td>0.00551</td>\n",
       "      <td>0.00006</td>\n",
       "      <td>0.00293</td>\n",
       "      <td>0.00332</td>\n",
       "      <td>0.00880</td>\n",
       "      <td>0.02093</td>\n",
       "      <td>...</td>\n",
       "      <td>0.03218</td>\n",
       "      <td>0.01070</td>\n",
       "      <td>21.812</td>\n",
       "      <td>1</td>\n",
       "      <td>0.615551</td>\n",
       "      <td>0.773587</td>\n",
       "      <td>-5.498678</td>\n",
       "      <td>0.327769</td>\n",
       "      <td>2.322511</td>\n",
       "      <td>0.231571</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>phon_R01_S02_4</td>\n",
       "      <td>95.056</td>\n",
       "      <td>120.103</td>\n",
       "      <td>91.226</td>\n",
       "      <td>0.00532</td>\n",
       "      <td>0.00006</td>\n",
       "      <td>0.00268</td>\n",
       "      <td>0.00332</td>\n",
       "      <td>0.00803</td>\n",
       "      <td>0.02838</td>\n",
       "      <td>...</td>\n",
       "      <td>0.04324</td>\n",
       "      <td>0.01022</td>\n",
       "      <td>21.862</td>\n",
       "      <td>1</td>\n",
       "      <td>0.547037</td>\n",
       "      <td>0.798463</td>\n",
       "      <td>-5.011879</td>\n",
       "      <td>0.325996</td>\n",
       "      <td>2.432792</td>\n",
       "      <td>0.271362</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>phon_R01_S02_5</td>\n",
       "      <td>88.333</td>\n",
       "      <td>112.240</td>\n",
       "      <td>84.072</td>\n",
       "      <td>0.00505</td>\n",
       "      <td>0.00006</td>\n",
       "      <td>0.00254</td>\n",
       "      <td>0.00330</td>\n",
       "      <td>0.00763</td>\n",
       "      <td>0.02143</td>\n",
       "      <td>...</td>\n",
       "      <td>0.03237</td>\n",
       "      <td>0.01166</td>\n",
       "      <td>21.118</td>\n",
       "      <td>1</td>\n",
       "      <td>0.611137</td>\n",
       "      <td>0.776156</td>\n",
       "      <td>-5.249770</td>\n",
       "      <td>0.391002</td>\n",
       "      <td>2.407313</td>\n",
       "      <td>0.249740</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>phon_R01_S02_6</td>\n",
       "      <td>91.904</td>\n",
       "      <td>115.871</td>\n",
       "      <td>86.292</td>\n",
       "      <td>0.00540</td>\n",
       "      <td>0.00006</td>\n",
       "      <td>0.00281</td>\n",
       "      <td>0.00336</td>\n",
       "      <td>0.00844</td>\n",
       "      <td>0.02752</td>\n",
       "      <td>...</td>\n",
       "      <td>0.04272</td>\n",
       "      <td>0.01141</td>\n",
       "      <td>21.414</td>\n",
       "      <td>1</td>\n",
       "      <td>0.583390</td>\n",
       "      <td>0.792520</td>\n",
       "      <td>-4.960234</td>\n",
       "      <td>0.363566</td>\n",
       "      <td>2.642476</td>\n",
       "      <td>0.275931</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>phon_R01_S04_1</td>\n",
       "      <td>136.926</td>\n",
       "      <td>159.866</td>\n",
       "      <td>131.276</td>\n",
       "      <td>0.00293</td>\n",
       "      <td>0.00002</td>\n",
       "      <td>0.00118</td>\n",
       "      <td>0.00153</td>\n",
       "      <td>0.00355</td>\n",
       "      <td>0.01259</td>\n",
       "      <td>...</td>\n",
       "      <td>0.01968</td>\n",
       "      <td>0.00581</td>\n",
       "      <td>25.703</td>\n",
       "      <td>1</td>\n",
       "      <td>0.460600</td>\n",
       "      <td>0.646846</td>\n",
       "      <td>-6.547148</td>\n",
       "      <td>0.152813</td>\n",
       "      <td>2.041277</td>\n",
       "      <td>0.138512</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>phon_R01_S04_2</td>\n",
       "      <td>139.173</td>\n",
       "      <td>179.139</td>\n",
       "      <td>76.556</td>\n",
       "      <td>0.00390</td>\n",
       "      <td>0.00003</td>\n",
       "      <td>0.00165</td>\n",
       "      <td>0.00208</td>\n",
       "      <td>0.00496</td>\n",
       "      <td>0.01642</td>\n",
       "      <td>...</td>\n",
       "      <td>0.02184</td>\n",
       "      <td>0.01041</td>\n",
       "      <td>24.889</td>\n",
       "      <td>1</td>\n",
       "      <td>0.430166</td>\n",
       "      <td>0.665833</td>\n",
       "      <td>-5.660217</td>\n",
       "      <td>0.254989</td>\n",
       "      <td>2.519422</td>\n",
       "      <td>0.199889</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>phon_R01_S04_3</td>\n",
       "      <td>152.845</td>\n",
       "      <td>163.305</td>\n",
       "      <td>75.836</td>\n",
       "      <td>0.00294</td>\n",
       "      <td>0.00002</td>\n",
       "      <td>0.00121</td>\n",
       "      <td>0.00149</td>\n",
       "      <td>0.00364</td>\n",
       "      <td>0.01828</td>\n",
       "      <td>...</td>\n",
       "      <td>0.03191</td>\n",
       "      <td>0.00609</td>\n",
       "      <td>24.922</td>\n",
       "      <td>1</td>\n",
       "      <td>0.474791</td>\n",
       "      <td>0.654027</td>\n",
       "      <td>-6.105098</td>\n",
       "      <td>0.203653</td>\n",
       "      <td>2.125618</td>\n",
       "      <td>0.170100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>phon_R01_S04_4</td>\n",
       "      <td>142.167</td>\n",
       "      <td>217.455</td>\n",
       "      <td>83.159</td>\n",
       "      <td>0.00369</td>\n",
       "      <td>0.00003</td>\n",
       "      <td>0.00157</td>\n",
       "      <td>0.00203</td>\n",
       "      <td>0.00471</td>\n",
       "      <td>0.01503</td>\n",
       "      <td>...</td>\n",
       "      <td>0.02316</td>\n",
       "      <td>0.00839</td>\n",
       "      <td>25.175</td>\n",
       "      <td>1</td>\n",
       "      <td>0.565924</td>\n",
       "      <td>0.658245</td>\n",
       "      <td>-5.340115</td>\n",
       "      <td>0.210185</td>\n",
       "      <td>2.205546</td>\n",
       "      <td>0.234589</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>phon_R01_S04_5</td>\n",
       "      <td>144.188</td>\n",
       "      <td>349.259</td>\n",
       "      <td>82.764</td>\n",
       "      <td>0.00544</td>\n",
       "      <td>0.00004</td>\n",
       "      <td>0.00211</td>\n",
       "      <td>0.00292</td>\n",
       "      <td>0.00632</td>\n",
       "      <td>0.02047</td>\n",
       "      <td>...</td>\n",
       "      <td>0.02908</td>\n",
       "      <td>0.01859</td>\n",
       "      <td>22.333</td>\n",
       "      <td>1</td>\n",
       "      <td>0.567380</td>\n",
       "      <td>0.644692</td>\n",
       "      <td>-5.440040</td>\n",
       "      <td>0.239764</td>\n",
       "      <td>2.264501</td>\n",
       "      <td>0.218164</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>phon_R01_S04_6</td>\n",
       "      <td>168.778</td>\n",
       "      <td>232.181</td>\n",
       "      <td>75.603</td>\n",
       "      <td>0.00718</td>\n",
       "      <td>0.00004</td>\n",
       "      <td>0.00284</td>\n",
       "      <td>0.00387</td>\n",
       "      <td>0.00853</td>\n",
       "      <td>0.03327</td>\n",
       "      <td>...</td>\n",
       "      <td>0.04322</td>\n",
       "      <td>0.02919</td>\n",
       "      <td>20.376</td>\n",
       "      <td>1</td>\n",
       "      <td>0.631099</td>\n",
       "      <td>0.605417</td>\n",
       "      <td>-2.931070</td>\n",
       "      <td>0.434326</td>\n",
       "      <td>3.007463</td>\n",
       "      <td>0.430788</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>phon_R01_S05_1</td>\n",
       "      <td>153.046</td>\n",
       "      <td>175.829</td>\n",
       "      <td>68.623</td>\n",
       "      <td>0.00742</td>\n",
       "      <td>0.00005</td>\n",
       "      <td>0.00364</td>\n",
       "      <td>0.00432</td>\n",
       "      <td>0.01092</td>\n",
       "      <td>0.05517</td>\n",
       "      <td>...</td>\n",
       "      <td>0.07413</td>\n",
       "      <td>0.03160</td>\n",
       "      <td>17.280</td>\n",
       "      <td>1</td>\n",
       "      <td>0.665318</td>\n",
       "      <td>0.719467</td>\n",
       "      <td>-3.949079</td>\n",
       "      <td>0.357870</td>\n",
       "      <td>3.109010</td>\n",
       "      <td>0.377429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>phon_R01_S05_2</td>\n",
       "      <td>156.405</td>\n",
       "      <td>189.398</td>\n",
       "      <td>142.822</td>\n",
       "      <td>0.00768</td>\n",
       "      <td>0.00005</td>\n",
       "      <td>0.00372</td>\n",
       "      <td>0.00399</td>\n",
       "      <td>0.01116</td>\n",
       "      <td>0.03995</td>\n",
       "      <td>...</td>\n",
       "      <td>0.05164</td>\n",
       "      <td>0.03365</td>\n",
       "      <td>17.153</td>\n",
       "      <td>1</td>\n",
       "      <td>0.649554</td>\n",
       "      <td>0.686080</td>\n",
       "      <td>-4.554466</td>\n",
       "      <td>0.340176</td>\n",
       "      <td>2.856676</td>\n",
       "      <td>0.322111</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>20 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              name  MDVP:Fo(Hz)  MDVP:Fhi(Hz)  MDVP:Flo(Hz)  MDVP:Jitter(%)  \\\n",
       "0   phon_R01_S01_1      119.992       157.302        74.997         0.00784   \n",
       "1   phon_R01_S01_2      122.400       148.650       113.819         0.00968   \n",
       "2   phon_R01_S01_3      116.682       131.111       111.555         0.01050   \n",
       "3   phon_R01_S01_4      116.676       137.871       111.366         0.00997   \n",
       "4   phon_R01_S01_5      116.014       141.781       110.655         0.01284   \n",
       "5   phon_R01_S01_6      120.552       131.162       113.787         0.00968   \n",
       "6   phon_R01_S02_1      120.267       137.244       114.820         0.00333   \n",
       "7   phon_R01_S02_2      107.332       113.840       104.315         0.00290   \n",
       "8   phon_R01_S02_3       95.730       132.068        91.754         0.00551   \n",
       "9   phon_R01_S02_4       95.056       120.103        91.226         0.00532   \n",
       "10  phon_R01_S02_5       88.333       112.240        84.072         0.00505   \n",
       "11  phon_R01_S02_6       91.904       115.871        86.292         0.00540   \n",
       "12  phon_R01_S04_1      136.926       159.866       131.276         0.00293   \n",
       "13  phon_R01_S04_2      139.173       179.139        76.556         0.00390   \n",
       "14  phon_R01_S04_3      152.845       163.305        75.836         0.00294   \n",
       "15  phon_R01_S04_4      142.167       217.455        83.159         0.00369   \n",
       "16  phon_R01_S04_5      144.188       349.259        82.764         0.00544   \n",
       "17  phon_R01_S04_6      168.778       232.181        75.603         0.00718   \n",
       "18  phon_R01_S05_1      153.046       175.829        68.623         0.00742   \n",
       "19  phon_R01_S05_2      156.405       189.398       142.822         0.00768   \n",
       "\n",
       "    MDVP:Jitter(Abs)  MDVP:RAP  MDVP:PPQ  Jitter:DDP  MDVP:Shimmer  ...  \\\n",
       "0            0.00007   0.00370   0.00554     0.01109       0.04374  ...   \n",
       "1            0.00008   0.00465   0.00696     0.01394       0.06134  ...   \n",
       "2            0.00009   0.00544   0.00781     0.01633       0.05233  ...   \n",
       "3            0.00009   0.00502   0.00698     0.01505       0.05492  ...   \n",
       "4            0.00011   0.00655   0.00908     0.01966       0.06425  ...   \n",
       "5            0.00008   0.00463   0.00750     0.01388       0.04701  ...   \n",
       "6            0.00003   0.00155   0.00202     0.00466       0.01608  ...   \n",
       "7            0.00003   0.00144   0.00182     0.00431       0.01567  ...   \n",
       "8            0.00006   0.00293   0.00332     0.00880       0.02093  ...   \n",
       "9            0.00006   0.00268   0.00332     0.00803       0.02838  ...   \n",
       "10           0.00006   0.00254   0.00330     0.00763       0.02143  ...   \n",
       "11           0.00006   0.00281   0.00336     0.00844       0.02752  ...   \n",
       "12           0.00002   0.00118   0.00153     0.00355       0.01259  ...   \n",
       "13           0.00003   0.00165   0.00208     0.00496       0.01642  ...   \n",
       "14           0.00002   0.00121   0.00149     0.00364       0.01828  ...   \n",
       "15           0.00003   0.00157   0.00203     0.00471       0.01503  ...   \n",
       "16           0.00004   0.00211   0.00292     0.00632       0.02047  ...   \n",
       "17           0.00004   0.00284   0.00387     0.00853       0.03327  ...   \n",
       "18           0.00005   0.00364   0.00432     0.01092       0.05517  ...   \n",
       "19           0.00005   0.00372   0.00399     0.01116       0.03995  ...   \n",
       "\n",
       "    Shimmer:DDA      NHR     HNR  status      RPDE       DFA   spread1  \\\n",
       "0       0.06545  0.02211  21.033       1  0.414783  0.815285 -4.813031   \n",
       "1       0.09403  0.01929  19.085       1  0.458359  0.819521 -4.075192   \n",
       "2       0.08270  0.01309  20.651       1  0.429895  0.825288 -4.443179   \n",
       "3       0.08771  0.01353  20.644       1  0.434969  0.819235 -4.117501   \n",
       "4       0.10470  0.01767  19.649       1  0.417356  0.823484 -3.747787   \n",
       "5       0.06985  0.01222  21.378       1  0.415564  0.825069 -4.242867   \n",
       "6       0.02337  0.00607  24.886       1  0.596040  0.764112 -5.634322   \n",
       "7       0.02487  0.00344  26.892       1  0.637420  0.763262 -6.167603   \n",
       "8       0.03218  0.01070  21.812       1  0.615551  0.773587 -5.498678   \n",
       "9       0.04324  0.01022  21.862       1  0.547037  0.798463 -5.011879   \n",
       "10      0.03237  0.01166  21.118       1  0.611137  0.776156 -5.249770   \n",
       "11      0.04272  0.01141  21.414       1  0.583390  0.792520 -4.960234   \n",
       "12      0.01968  0.00581  25.703       1  0.460600  0.646846 -6.547148   \n",
       "13      0.02184  0.01041  24.889       1  0.430166  0.665833 -5.660217   \n",
       "14      0.03191  0.00609  24.922       1  0.474791  0.654027 -6.105098   \n",
       "15      0.02316  0.00839  25.175       1  0.565924  0.658245 -5.340115   \n",
       "16      0.02908  0.01859  22.333       1  0.567380  0.644692 -5.440040   \n",
       "17      0.04322  0.02919  20.376       1  0.631099  0.605417 -2.931070   \n",
       "18      0.07413  0.03160  17.280       1  0.665318  0.719467 -3.949079   \n",
       "19      0.05164  0.03365  17.153       1  0.649554  0.686080 -4.554466   \n",
       "\n",
       "     spread2        D2       PPE  \n",
       "0   0.266482  2.301442  0.284654  \n",
       "1   0.335590  2.486855  0.368674  \n",
       "2   0.311173  2.342259  0.332634  \n",
       "3   0.334147  2.405554  0.368975  \n",
       "4   0.234513  2.332180  0.410335  \n",
       "5   0.299111  2.187560  0.357775  \n",
       "6   0.257682  1.854785  0.211756  \n",
       "7   0.183721  2.064693  0.163755  \n",
       "8   0.327769  2.322511  0.231571  \n",
       "9   0.325996  2.432792  0.271362  \n",
       "10  0.391002  2.407313  0.249740  \n",
       "11  0.363566  2.642476  0.275931  \n",
       "12  0.152813  2.041277  0.138512  \n",
       "13  0.254989  2.519422  0.199889  \n",
       "14  0.203653  2.125618  0.170100  \n",
       "15  0.210185  2.205546  0.234589  \n",
       "16  0.239764  2.264501  0.218164  \n",
       "17  0.434326  3.007463  0.430788  \n",
       "18  0.357870  3.109010  0.377429  \n",
       "19  0.340176  2.856676  0.322111  \n",
       "\n",
       "[20 rows x 24 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Read the data\n",
    "df=pd.read_csv('parkinsons.data')\n",
    "df.head(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "7429bd64",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 195 entries, 0 to 194\n",
      "Data columns (total 24 columns):\n",
      " #   Column            Non-Null Count  Dtype  \n",
      "---  ------            --------------  -----  \n",
      " 0   name              195 non-null    object \n",
      " 1   MDVP:Fo(Hz)       195 non-null    float64\n",
      " 2   MDVP:Fhi(Hz)      195 non-null    float64\n",
      " 3   MDVP:Flo(Hz)      195 non-null    float64\n",
      " 4   MDVP:Jitter(%)    195 non-null    float64\n",
      " 5   MDVP:Jitter(Abs)  195 non-null    float64\n",
      " 6   MDVP:RAP          195 non-null    float64\n",
      " 7   MDVP:PPQ          195 non-null    float64\n",
      " 8   Jitter:DDP        195 non-null    float64\n",
      " 9   MDVP:Shimmer      195 non-null    float64\n",
      " 10  MDVP:Shimmer(dB)  195 non-null    float64\n",
      " 11  Shimmer:APQ3      195 non-null    float64\n",
      " 12  Shimmer:APQ5      195 non-null    float64\n",
      " 13  MDVP:APQ          195 non-null    float64\n",
      " 14  Shimmer:DDA       195 non-null    float64\n",
      " 15  NHR               195 non-null    float64\n",
      " 16  HNR               195 non-null    float64\n",
      " 17  status            195 non-null    int64  \n",
      " 18  RPDE              195 non-null    float64\n",
      " 19  DFA               195 non-null    float64\n",
      " 20  spread1           195 non-null    float64\n",
      " 21  spread2           195 non-null    float64\n",
      " 22  D2                195 non-null    float64\n",
      " 23  PPE               195 non-null    float64\n",
      "dtypes: float64(22), int64(1), object(1)\n",
      "memory usage: 36.7+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "f91872e5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "name                0\n",
       "MDVP:Fo(Hz)         0\n",
       "MDVP:Fhi(Hz)        0\n",
       "MDVP:Flo(Hz)        0\n",
       "MDVP:Jitter(%)      0\n",
       "MDVP:Jitter(Abs)    0\n",
       "MDVP:RAP            0\n",
       "MDVP:PPQ            0\n",
       "Jitter:DDP          0\n",
       "MDVP:Shimmer        0\n",
       "MDVP:Shimmer(dB)    0\n",
       "Shimmer:APQ3        0\n",
       "Shimmer:APQ5        0\n",
       "MDVP:APQ            0\n",
       "Shimmer:DDA         0\n",
       "NHR                 0\n",
       "HNR                 0\n",
       "status              0\n",
       "RPDE                0\n",
       "DFA                 0\n",
       "spread1             0\n",
       "spread2             0\n",
       "D2                  0\n",
       "PPE                 0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "d71c8266",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Data Type</th>\n",
       "      <th>No of Levels</th>\n",
       "      <th>Levels</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>name</th>\n",
       "      <td>object</td>\n",
       "      <td>195</td>\n",
       "      <td>['phon_R01_S01_1' 'phon_R01_S01_2' 'phon_R01_S...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MDVP:Fo(Hz)</th>\n",
       "      <td>float64</td>\n",
       "      <td>195</td>\n",
       "      <td>[119.992 122.4 116.682 116.676 116.014 120.552...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MDVP:Fhi(Hz)</th>\n",
       "      <td>float64</td>\n",
       "      <td>195</td>\n",
       "      <td>[157.302 148.65 131.111 137.871 141.781 131.16...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MDVP:Flo(Hz)</th>\n",
       "      <td>float64</td>\n",
       "      <td>195</td>\n",
       "      <td>[74.997 113.819 111.555 111.366 110.655 113.78...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MDVP:Jitter(%)</th>\n",
       "      <td>float64</td>\n",
       "      <td>173</td>\n",
       "      <td>[0.00784 0.00968 0.0105 0.00997 0.01284 0.0033...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MDVP:Jitter(Abs)</th>\n",
       "      <td>float64</td>\n",
       "      <td>19</td>\n",
       "      <td>[7e-05 8e-05 9e-05 0.00011 2.9999999999999997e...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MDVP:RAP</th>\n",
       "      <td>float64</td>\n",
       "      <td>155</td>\n",
       "      <td>[0.0037 0.00465 0.0054399999999999995 0.00502 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MDVP:PPQ</th>\n",
       "      <td>float64</td>\n",
       "      <td>165</td>\n",
       "      <td>[0.00554 0.006959999999999999 0.00780999999999...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jitter:DDP</th>\n",
       "      <td>float64</td>\n",
       "      <td>180</td>\n",
       "      <td>[0.011090000000000001 0.013940000000000001 0.0...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MDVP:Shimmer</th>\n",
       "      <td>float64</td>\n",
       "      <td>188</td>\n",
       "      <td>[0.04374 0.06134 0.052329999999999995 0.054920...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MDVP:Shimmer(dB)</th>\n",
       "      <td>float64</td>\n",
       "      <td>149</td>\n",
       "      <td>[0.426 0.626 0.482 0.517 0.584 0.456 0.14 0.13...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shimmer:APQ3</th>\n",
       "      <td>float64</td>\n",
       "      <td>184</td>\n",
       "      <td>[0.02182 0.03134 0.027569999999999997 0.02924 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shimmer:APQ5</th>\n",
       "      <td>float64</td>\n",
       "      <td>189</td>\n",
       "      <td>[0.0313 0.04518 0.03858 0.04005 0.04825 0.0352...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MDVP:APQ</th>\n",
       "      <td>float64</td>\n",
       "      <td>189</td>\n",
       "      <td>[0.029710000000000004 0.043680000000000004 0.0...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shimmer:DDA</th>\n",
       "      <td>float64</td>\n",
       "      <td>189</td>\n",
       "      <td>[0.06545 0.09402999999999999 0.0827 0.08771 0....</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NHR</th>\n",
       "      <td>float64</td>\n",
       "      <td>185</td>\n",
       "      <td>[0.022109999999999998 0.01929 0.01309000000000...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HNR</th>\n",
       "      <td>float64</td>\n",
       "      <td>195</td>\n",
       "      <td>[21.033 19.085 20.651 20.644 19.649 21.378 24....</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>status</th>\n",
       "      <td>int64</td>\n",
       "      <td>2</td>\n",
       "      <td>[1 0]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RPDE</th>\n",
       "      <td>float64</td>\n",
       "      <td>195</td>\n",
       "      <td>[0.414783 0.458359 0.42989499999999997 0.43496...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DFA</th>\n",
       "      <td>float64</td>\n",
       "      <td>195</td>\n",
       "      <td>[0.815285 0.8195209999999999 0.825287999999999...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>spread1</th>\n",
       "      <td>float64</td>\n",
       "      <td>195</td>\n",
       "      <td>[-4.813031 -4.0751919999999995 -4.443179 -4.11...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>spread2</th>\n",
       "      <td>float64</td>\n",
       "      <td>194</td>\n",
       "      <td>[0.266482 0.33559 0.311173 0.33414699999999997...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>D2</th>\n",
       "      <td>float64</td>\n",
       "      <td>195</td>\n",
       "      <td>[2.3014419999999998 2.486855 2.342259 2.405554...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PPE</th>\n",
       "      <td>float64</td>\n",
       "      <td>195</td>\n",
       "      <td>[0.284654 0.368674 0.33263400000000004 0.36897...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 Data Type  No of Levels  \\\n",
       "name                object           195   \n",
       "MDVP:Fo(Hz)        float64           195   \n",
       "MDVP:Fhi(Hz)       float64           195   \n",
       "MDVP:Flo(Hz)       float64           195   \n",
       "MDVP:Jitter(%)     float64           173   \n",
       "MDVP:Jitter(Abs)   float64            19   \n",
       "MDVP:RAP           float64           155   \n",
       "MDVP:PPQ           float64           165   \n",
       "Jitter:DDP         float64           180   \n",
       "MDVP:Shimmer       float64           188   \n",
       "MDVP:Shimmer(dB)   float64           149   \n",
       "Shimmer:APQ3       float64           184   \n",
       "Shimmer:APQ5       float64           189   \n",
       "MDVP:APQ           float64           189   \n",
       "Shimmer:DDA        float64           189   \n",
       "NHR                float64           185   \n",
       "HNR                float64           195   \n",
       "status               int64             2   \n",
       "RPDE               float64           195   \n",
       "DFA                float64           195   \n",
       "spread1            float64           195   \n",
       "spread2            float64           194   \n",
       "D2                 float64           195   \n",
       "PPE                float64           195   \n",
       "\n",
       "                                                             Levels  \n",
       "name              ['phon_R01_S01_1' 'phon_R01_S01_2' 'phon_R01_S...  \n",
       "MDVP:Fo(Hz)       [119.992 122.4 116.682 116.676 116.014 120.552...  \n",
       "MDVP:Fhi(Hz)      [157.302 148.65 131.111 137.871 141.781 131.16...  \n",
       "MDVP:Flo(Hz)      [74.997 113.819 111.555 111.366 110.655 113.78...  \n",
       "MDVP:Jitter(%)    [0.00784 0.00968 0.0105 0.00997 0.01284 0.0033...  \n",
       "MDVP:Jitter(Abs)  [7e-05 8e-05 9e-05 0.00011 2.9999999999999997e...  \n",
       "MDVP:RAP          [0.0037 0.00465 0.0054399999999999995 0.00502 ...  \n",
       "MDVP:PPQ          [0.00554 0.006959999999999999 0.00780999999999...  \n",
       "Jitter:DDP        [0.011090000000000001 0.013940000000000001 0.0...  \n",
       "MDVP:Shimmer      [0.04374 0.06134 0.052329999999999995 0.054920...  \n",
       "MDVP:Shimmer(dB)  [0.426 0.626 0.482 0.517 0.584 0.456 0.14 0.13...  \n",
       "Shimmer:APQ3      [0.02182 0.03134 0.027569999999999997 0.02924 ...  \n",
       "Shimmer:APQ5      [0.0313 0.04518 0.03858 0.04005 0.04825 0.0352...  \n",
       "MDVP:APQ          [0.029710000000000004 0.043680000000000004 0.0...  \n",
       "Shimmer:DDA       [0.06545 0.09402999999999999 0.0827 0.08771 0....  \n",
       "NHR               [0.022109999999999998 0.01929 0.01309000000000...  \n",
       "HNR               [21.033 19.085 20.651 20.644 19.649 21.378 24....  \n",
       "status                                                        [1 0]  \n",
       "RPDE              [0.414783 0.458359 0.42989499999999997 0.43496...  \n",
       "DFA               [0.815285 0.8195209999999999 0.825287999999999...  \n",
       "spread1           [-4.813031 -4.0751919999999995 -4.443179 -4.11...  \n",
       "spread2           [0.266482 0.33559 0.311173 0.33414699999999997...  \n",
       "D2                [2.3014419999999998 2.486855 2.342259 2.405554...  \n",
       "PPE               [0.284654 0.368674 0.33263400000000004 0.36897...  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Inspecting the dataframe\n",
    "# This function displays the datatype,levels 0f variables and number of levels in each column of the given train dataframe.here lambda is used to pass arguments\n",
    "def inspect_data(data):\n",
    "    return pd.DataFrame({\"Data Type\":data.dtypes,\"No of Levels\":data.apply(lambda x: x.nunique(),axis=0), \"Levels\":data.apply(lambda x: str(x.unique()),axis=0)})\n",
    "inspect_data(df)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4ab2c85c",
   "metadata": {},
   "source": [
    "### Statistical Summary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "6506688a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>MDVP:Fo(Hz)</th>\n",
       "      <th>MDVP:Fhi(Hz)</th>\n",
       "      <th>MDVP:Flo(Hz)</th>\n",
       "      <th>MDVP:Jitter(%)</th>\n",
       "      <th>MDVP:Jitter(Abs)</th>\n",
       "      <th>MDVP:RAP</th>\n",
       "      <th>MDVP:PPQ</th>\n",
       "      <th>Jitter:DDP</th>\n",
       "      <th>MDVP:Shimmer</th>\n",
       "      <th>...</th>\n",
       "      <th>Shimmer:DDA</th>\n",
       "      <th>NHR</th>\n",
       "      <th>HNR</th>\n",
       "      <th>status</th>\n",
       "      <th>RPDE</th>\n",
       "      <th>DFA</th>\n",
       "      <th>spread1</th>\n",
       "      <th>spread2</th>\n",
       "      <th>D2</th>\n",
       "      <th>PPE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>195</td>\n",
       "      <td>195.000000</td>\n",
       "      <td>195.000000</td>\n",
       "      <td>195.000000</td>\n",
       "      <td>195.000000</td>\n",
       "      <td>195.000000</td>\n",
       "      <td>195.000000</td>\n",
       "      <td>195.000000</td>\n",
       "      <td>195.000000</td>\n",
       "      <td>195.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>195.000000</td>\n",
       "      <td>195.000000</td>\n",
       "      <td>195.000000</td>\n",
       "      <td>195.000000</td>\n",
       "      <td>195.000000</td>\n",
       "      <td>195.000000</td>\n",
       "      <td>195.000000</td>\n",
       "      <td>195.000000</td>\n",
       "      <td>195.000000</td>\n",
       "      <td>195.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unique</th>\n",
       "      <td>195</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>top</th>\n",
       "      <td>phon_R01_S31_2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>freq</th>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>NaN</td>\n",
       "      <td>154.228641</td>\n",
       "      <td>197.104918</td>\n",
       "      <td>116.324631</td>\n",
       "      <td>0.006220</td>\n",
       "      <td>0.000044</td>\n",
       "      <td>0.003306</td>\n",
       "      <td>0.003446</td>\n",
       "      <td>0.009920</td>\n",
       "      <td>0.029709</td>\n",
       "      <td>...</td>\n",
       "      <td>0.046993</td>\n",
       "      <td>0.024847</td>\n",
       "      <td>21.885974</td>\n",
       "      <td>0.753846</td>\n",
       "      <td>0.498536</td>\n",
       "      <td>0.718099</td>\n",
       "      <td>-5.684397</td>\n",
       "      <td>0.226510</td>\n",
       "      <td>2.381826</td>\n",
       "      <td>0.206552</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>NaN</td>\n",
       "      <td>41.390065</td>\n",
       "      <td>91.491548</td>\n",
       "      <td>43.521413</td>\n",
       "      <td>0.004848</td>\n",
       "      <td>0.000035</td>\n",
       "      <td>0.002968</td>\n",
       "      <td>0.002759</td>\n",
       "      <td>0.008903</td>\n",
       "      <td>0.018857</td>\n",
       "      <td>...</td>\n",
       "      <td>0.030459</td>\n",
       "      <td>0.040418</td>\n",
       "      <td>4.425764</td>\n",
       "      <td>0.431878</td>\n",
       "      <td>0.103942</td>\n",
       "      <td>0.055336</td>\n",
       "      <td>1.090208</td>\n",
       "      <td>0.083406</td>\n",
       "      <td>0.382799</td>\n",
       "      <td>0.090119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>NaN</td>\n",
       "      <td>88.333000</td>\n",
       "      <td>102.145000</td>\n",
       "      <td>65.476000</td>\n",
       "      <td>0.001680</td>\n",
       "      <td>0.000007</td>\n",
       "      <td>0.000680</td>\n",
       "      <td>0.000920</td>\n",
       "      <td>0.002040</td>\n",
       "      <td>0.009540</td>\n",
       "      <td>...</td>\n",
       "      <td>0.013640</td>\n",
       "      <td>0.000650</td>\n",
       "      <td>8.441000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.256570</td>\n",
       "      <td>0.574282</td>\n",
       "      <td>-7.964984</td>\n",
       "      <td>0.006274</td>\n",
       "      <td>1.423287</td>\n",
       "      <td>0.044539</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>NaN</td>\n",
       "      <td>117.572000</td>\n",
       "      <td>134.862500</td>\n",
       "      <td>84.291000</td>\n",
       "      <td>0.003460</td>\n",
       "      <td>0.000020</td>\n",
       "      <td>0.001660</td>\n",
       "      <td>0.001860</td>\n",
       "      <td>0.004985</td>\n",
       "      <td>0.016505</td>\n",
       "      <td>...</td>\n",
       "      <td>0.024735</td>\n",
       "      <td>0.005925</td>\n",
       "      <td>19.198000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.421306</td>\n",
       "      <td>0.674758</td>\n",
       "      <td>-6.450096</td>\n",
       "      <td>0.174351</td>\n",
       "      <td>2.099125</td>\n",
       "      <td>0.137451</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>NaN</td>\n",
       "      <td>148.790000</td>\n",
       "      <td>175.829000</td>\n",
       "      <td>104.315000</td>\n",
       "      <td>0.004940</td>\n",
       "      <td>0.000030</td>\n",
       "      <td>0.002500</td>\n",
       "      <td>0.002690</td>\n",
       "      <td>0.007490</td>\n",
       "      <td>0.022970</td>\n",
       "      <td>...</td>\n",
       "      <td>0.038360</td>\n",
       "      <td>0.011660</td>\n",
       "      <td>22.085000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.495954</td>\n",
       "      <td>0.722254</td>\n",
       "      <td>-5.720868</td>\n",
       "      <td>0.218885</td>\n",
       "      <td>2.361532</td>\n",
       "      <td>0.194052</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>NaN</td>\n",
       "      <td>182.769000</td>\n",
       "      <td>224.205500</td>\n",
       "      <td>140.018500</td>\n",
       "      <td>0.007365</td>\n",
       "      <td>0.000060</td>\n",
       "      <td>0.003835</td>\n",
       "      <td>0.003955</td>\n",
       "      <td>0.011505</td>\n",
       "      <td>0.037885</td>\n",
       "      <td>...</td>\n",
       "      <td>0.060795</td>\n",
       "      <td>0.025640</td>\n",
       "      <td>25.075500</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.587562</td>\n",
       "      <td>0.761881</td>\n",
       "      <td>-5.046192</td>\n",
       "      <td>0.279234</td>\n",
       "      <td>2.636456</td>\n",
       "      <td>0.252980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>NaN</td>\n",
       "      <td>260.105000</td>\n",
       "      <td>592.030000</td>\n",
       "      <td>239.170000</td>\n",
       "      <td>0.033160</td>\n",
       "      <td>0.000260</td>\n",
       "      <td>0.021440</td>\n",
       "      <td>0.019580</td>\n",
       "      <td>0.064330</td>\n",
       "      <td>0.119080</td>\n",
       "      <td>...</td>\n",
       "      <td>0.169420</td>\n",
       "      <td>0.314820</td>\n",
       "      <td>33.047000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.685151</td>\n",
       "      <td>0.825288</td>\n",
       "      <td>-2.434031</td>\n",
       "      <td>0.450493</td>\n",
       "      <td>3.671155</td>\n",
       "      <td>0.527367</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>11 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                  name  MDVP:Fo(Hz)  MDVP:Fhi(Hz)  MDVP:Flo(Hz)  \\\n",
       "count              195   195.000000    195.000000    195.000000   \n",
       "unique             195          NaN           NaN           NaN   \n",
       "top     phon_R01_S31_2          NaN           NaN           NaN   \n",
       "freq                 1          NaN           NaN           NaN   \n",
       "mean               NaN   154.228641    197.104918    116.324631   \n",
       "std                NaN    41.390065     91.491548     43.521413   \n",
       "min                NaN    88.333000    102.145000     65.476000   \n",
       "25%                NaN   117.572000    134.862500     84.291000   \n",
       "50%                NaN   148.790000    175.829000    104.315000   \n",
       "75%                NaN   182.769000    224.205500    140.018500   \n",
       "max                NaN   260.105000    592.030000    239.170000   \n",
       "\n",
       "        MDVP:Jitter(%)  MDVP:Jitter(Abs)    MDVP:RAP    MDVP:PPQ  Jitter:DDP  \\\n",
       "count       195.000000        195.000000  195.000000  195.000000  195.000000   \n",
       "unique             NaN               NaN         NaN         NaN         NaN   \n",
       "top                NaN               NaN         NaN         NaN         NaN   \n",
       "freq               NaN               NaN         NaN         NaN         NaN   \n",
       "mean          0.006220          0.000044    0.003306    0.003446    0.009920   \n",
       "std           0.004848          0.000035    0.002968    0.002759    0.008903   \n",
       "min           0.001680          0.000007    0.000680    0.000920    0.002040   \n",
       "25%           0.003460          0.000020    0.001660    0.001860    0.004985   \n",
       "50%           0.004940          0.000030    0.002500    0.002690    0.007490   \n",
       "75%           0.007365          0.000060    0.003835    0.003955    0.011505   \n",
       "max           0.033160          0.000260    0.021440    0.019580    0.064330   \n",
       "\n",
       "        MDVP:Shimmer  ...  Shimmer:DDA         NHR         HNR      status  \\\n",
       "count     195.000000  ...   195.000000  195.000000  195.000000  195.000000   \n",
       "unique           NaN  ...          NaN         NaN         NaN         NaN   \n",
       "top              NaN  ...          NaN         NaN         NaN         NaN   \n",
       "freq             NaN  ...          NaN         NaN         NaN         NaN   \n",
       "mean        0.029709  ...     0.046993    0.024847   21.885974    0.753846   \n",
       "std         0.018857  ...     0.030459    0.040418    4.425764    0.431878   \n",
       "min         0.009540  ...     0.013640    0.000650    8.441000    0.000000   \n",
       "25%         0.016505  ...     0.024735    0.005925   19.198000    1.000000   \n",
       "50%         0.022970  ...     0.038360    0.011660   22.085000    1.000000   \n",
       "75%         0.037885  ...     0.060795    0.025640   25.075500    1.000000   \n",
       "max         0.119080  ...     0.169420    0.314820   33.047000    1.000000   \n",
       "\n",
       "              RPDE         DFA     spread1     spread2          D2         PPE  \n",
       "count   195.000000  195.000000  195.000000  195.000000  195.000000  195.000000  \n",
       "unique         NaN         NaN         NaN         NaN         NaN         NaN  \n",
       "top            NaN         NaN         NaN         NaN         NaN         NaN  \n",
       "freq           NaN         NaN         NaN         NaN         NaN         NaN  \n",
       "mean      0.498536    0.718099   -5.684397    0.226510    2.381826    0.206552  \n",
       "std       0.103942    0.055336    1.090208    0.083406    0.382799    0.090119  \n",
       "min       0.256570    0.574282   -7.964984    0.006274    1.423287    0.044539  \n",
       "25%       0.421306    0.674758   -6.450096    0.174351    2.099125    0.137451  \n",
       "50%       0.495954    0.722254   -5.720868    0.218885    2.361532    0.194052  \n",
       "75%       0.587562    0.761881   -5.046192    0.279234    2.636456    0.252980  \n",
       "max       0.685151    0.825288   -2.434031    0.450493    3.671155    0.527367  \n",
       "\n",
       "[11 rows x 24 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe(include='all')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "274af133",
   "metadata": {},
   "source": [
    "### Checking for Duplicate values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "96510110",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.duplicated().sum() # displays duplicate records"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "457e1a17",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>MDVP:Fo(Hz)</th>\n",
       "      <th>MDVP:Fhi(Hz)</th>\n",
       "      <th>MDVP:Flo(Hz)</th>\n",
       "      <th>MDVP:Jitter(%)</th>\n",
       "      <th>MDVP:Jitter(Abs)</th>\n",
       "      <th>MDVP:RAP</th>\n",
       "      <th>MDVP:PPQ</th>\n",
       "      <th>Jitter:DDP</th>\n",
       "      <th>MDVP:Shimmer</th>\n",
       "      <th>...</th>\n",
       "      <th>Shimmer:DDA</th>\n",
       "      <th>NHR</th>\n",
       "      <th>HNR</th>\n",
       "      <th>status</th>\n",
       "      <th>RPDE</th>\n",
       "      <th>DFA</th>\n",
       "      <th>spread1</th>\n",
       "      <th>spread2</th>\n",
       "      <th>D2</th>\n",
       "      <th>PPE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>0 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [name, MDVP:Fo(Hz), MDVP:Fhi(Hz), MDVP:Flo(Hz), MDVP:Jitter(%), MDVP:Jitter(Abs), MDVP:RAP, MDVP:PPQ, Jitter:DDP, MDVP:Shimmer, MDVP:Shimmer(dB), Shimmer:APQ3, Shimmer:APQ5, MDVP:APQ, Shimmer:DDA, NHR, HNR, status, RPDE, DFA, spread1, spread2, D2, PPE]\n",
       "Index: []\n",
       "\n",
       "[0 rows x 24 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#checking for duplicated rows\n",
    "df[df.duplicated()]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c583aab4",
   "metadata": {},
   "source": [
    "There are no duplications in the dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "8daa00d3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "name                0\n",
       "MDVP:Fo(Hz)         0\n",
       "MDVP:Fhi(Hz)        0\n",
       "MDVP:Flo(Hz)        0\n",
       "MDVP:Jitter(%)      0\n",
       "MDVP:Jitter(Abs)    0\n",
       "MDVP:RAP            0\n",
       "MDVP:PPQ            0\n",
       "Jitter:DDP          0\n",
       "MDVP:Shimmer        0\n",
       "MDVP:Shimmer(dB)    0\n",
       "Shimmer:APQ3        0\n",
       "Shimmer:APQ5        0\n",
       "MDVP:APQ            0\n",
       "Shimmer:DDA         0\n",
       "NHR                 0\n",
       "HNR                 0\n",
       "status              0\n",
       "RPDE                0\n",
       "DFA                 0\n",
       "spread1             0\n",
       "spread2             0\n",
       "D2                  0\n",
       "PPE                 0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#checking for null values in train\n",
    "df.isnull().sum(axis=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "146abd2a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0xf0db12a088>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1800x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Visualising missing values for a sample of 250\n",
    "import missingno as msno\n",
    "\n",
    "msno.matrix(df.sample(100))\n",
    "\n",
    "#Heatmap\n",
    "#The missingno correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another:\n",
    "\n",
    "#msno.heatmap(mobp)\n",
    "\n",
    "#there are no missing values therefore nothing is displayed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "0dfb380f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0xf0dbb6ef08>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1800x720 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "msno.bar(df.sample(10))\n",
    "#no missing values\n",
    "\n",
    "#Dendrogram\n",
    "#The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap:\n",
    "\n",
    "#msno.dendrogram(mobp)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "32180105",
   "metadata": {},
   "source": [
    "### Estimating Skewness and Kurtosis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "98db391f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "MDVP:Fo(Hz)         0.591737\n",
       "MDVP:Fhi(Hz)        2.542146\n",
       "MDVP:Flo(Hz)        1.217350\n",
       "MDVP:Jitter(%)      3.084946\n",
       "MDVP:Jitter(Abs)    2.649071\n",
       "MDVP:RAP            3.360708\n",
       "MDVP:PPQ            3.073892\n",
       "Jitter:DDP          3.362058\n",
       "MDVP:Shimmer        1.666480\n",
       "MDVP:Shimmer(dB)    1.999389\n",
       "Shimmer:APQ3        1.580576\n",
       "Shimmer:APQ5        1.798697\n",
       "MDVP:APQ            2.618047\n",
       "Shimmer:DDA         1.580618\n",
       "NHR                 4.220709\n",
       "HNR                -0.514317\n",
       "status             -1.187727\n",
       "RPDE               -0.143402\n",
       "DFA                -0.033214\n",
       "spread1             0.432139\n",
       "spread2             0.144430\n",
       "D2                  0.430384\n",
       "PPE                 0.797491\n",
       "dtype: float64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.skew()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "84e76026",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "MDVP:Fo(Hz)         -0.627898\n",
       "MDVP:Fhi(Hz)         7.627241\n",
       "MDVP:Flo(Hz)         0.654615\n",
       "MDVP:Jitter(%)      12.030939\n",
       "MDVP:Jitter(Abs)    10.869043\n",
       "MDVP:RAP            14.213798\n",
       "MDVP:PPQ            11.963922\n",
       "Jitter:DDP          14.224762\n",
       "MDVP:Shimmer         3.238308\n",
       "MDVP:Shimmer(dB)     5.128193\n",
       "Shimmer:APQ3         2.720152\n",
       "Shimmer:APQ5         3.874210\n",
       "MDVP:APQ            11.163288\n",
       "Shimmer:DDA          2.720661\n",
       "NHR                 21.994974\n",
       "HNR                  0.616036\n",
       "status              -0.595518\n",
       "RPDE                -0.921781\n",
       "DFA                 -0.686152\n",
       "spread1             -0.050199\n",
       "spread2             -0.083023\n",
       "D2                   0.220334\n",
       "PPE                  0.528335\n",
       "dtype: float64"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.kurt()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "88ab59ca",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0xf0dc1ae148>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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pMRQkSY2hIElqDAVJUmMoSJIaQ0F6gJK8PsleS9VPWk68JVV6gJJ8FZivqjuWop+0nDhSkHYiySOT/HOSa5Jcl+R04HHApUku7fqcmWQhyfVJ/rhre+2Ift8a2u/xSc7plk/o9n1Nksum/BWl+1jRdwHSMncUcGtVvRggyU8BJwPPGxoBvLWq7uyeTbExyVOr6r1J3rBdvx15G/DCqvpakn0m9UWkcThSkHbuWuAFSd6Z5Ber6p4RfV6W5CrgauBJDB5W9ED8J3BOkt8C9nxw5UoPjiMFaSeq6stJng68CPizJJ8a3p7kEOCNwDOq6q7ulNAjdrS7oeXWp6peneSZwIuBzyX5+ar6xlJ+D2lcjhSknUjyOOA7VfV3wLuAw4BvAo/uuuwNfBu4J8kBDB5rus1wP4DbkzwxyR7Arw0d4/FVdUVVvQ24g/tOZS5NlSMFaeeeApyR5IfA94HfAZ4FfDLJbVX1vCRXA9cDNzE4FbTNhuF+wGnAxxk86e464FFdvzOSrGXwwKONwDVT+F7SSN6SKklqPH0kSWoMBUlSYyhIkhpDQZLUGAqSpMZQkCQ1hoIkqfl/qtXQSNZF32wAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(df['status'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "4cf11a9e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0xf0dbd58f88>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#checking for target variable\n",
    "y = df['status']\n",
    "plt.figure(1); plt.title('Johnson SU')\n",
    "sns.distplot(y, kde=False)\n",
    "plt.figure(2); plt.title('Normal')\n",
    "sns.distplot(y, kde=False)\n",
    "plt.figure(3); plt.title('Log Normal')\n",
    "sns.distplot(y, kde=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "15ab8d57",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0xf0dbdf5a08>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize = (12,10))\n",
    "sns.heatmap(df.corr(), cmap='Greens', annot = True) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "abe9cea5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 2000x400 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#checking the distribution of highly correlated features with label variable\n",
    "cols = ['NHR', 'PPE',\n",
    "       'D2', 'HNR']\n",
    "plt.figure(figsize=(20,4), dpi=100)\n",
    "i = 1\n",
    "for col in cols:\n",
    "    plt.subplot(1,11,i)\n",
    "    #sns.distplot(car['price'])\n",
    "    sns.distplot(df[col])\n",
    "    i = i+1\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f9443337",
   "metadata": {},
   "source": [
    "##### Get the features and labels from the DataFrame (dataset). The features are all the columns except ‘status’, and the labels are those in the ‘status’ column."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "d1d33fd9",
   "metadata": {},
   "outputs": [],
   "source": [
    "features=df.loc[:,df.columns!='status'].values[:,1:]\n",
    "labels=df.loc[:,'status'].values"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f9d609c4",
   "metadata": {},
   "source": [
    "###### The ‘status’ column has values 0 and 1 as labels; let’s get the counts of these labels for both- 0 and 1."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "915089cb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "147 48\n"
     ]
    }
   ],
   "source": [
    "print(labels[labels==1].shape[0], labels[labels==0].shape[0]) #We have 147 ones and 48 zeros in the status column in our dataset."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d97f3650",
   "metadata": {},
   "source": [
    "######  Initialize a MinMaxScaler and scale the features to between -1 and 1 to normalize them. The MinMaxScaler transforms features by scaling them to a given range. The fit_transform() method fits to the data and then transforms it. We don’t need to scale the labels."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "1a70c101",
   "metadata": {},
   "outputs": [],
   "source": [
    "scaler=MinMaxScaler((-1,1))\n",
    "x=scaler.fit_transform(features)\n",
    "y=labels"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c6da63cb",
   "metadata": {},
   "source": [
    "######  Now, split the dataset into training and testing sets keeping 20% of the data for testing."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "4f63fe7b",
   "metadata": {},
   "outputs": [],
   "source": [
    "x_train,x_test,y_train,y_test=train_test_split(x, y, test_size=0.2, random_state=7)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d8f8f0ce",
   "metadata": {},
   "source": [
    "Now the data is ready to deal with ML Algorithms"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f8cd1054",
   "metadata": {},
   "source": [
    "Here we are done with the EDA and data cleaning part"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "620790b0",
   "metadata": {},
   "source": [
    "####  Initialize an XGBClassifier and train the model. This classifies using eXtreme Gradient Boosting- using gradient boosting algorithms for modern data science problems. It falls under the category of Ensemble Learning in ML, where we train and predict using many models to produce one superior output."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "feabfd70",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[21:10:16] WARNING: C:/Users/Administrator/workspace/xgboost-win64_release_1.4.0/src/learner.cc:1095: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\n",
       "              colsample_bynode=1, colsample_bytree=1, gamma=0, gpu_id=-1,\n",
       "              importance_type='gain', interaction_constraints='',\n",
       "              learning_rate=0.300000012, max_delta_step=0, max_depth=6,\n",
       "              min_child_weight=1, missing=nan, monotone_constraints='()',\n",
       "              n_estimators=100, n_jobs=2, num_parallel_tree=1,\n",
       "              objective='binary:logistic', random_state=0, reg_alpha=0,\n",
       "              reg_lambda=1, scale_pos_weight=1, subsample=1,\n",
       "              tree_method='exact', use_label_encoder=True,\n",
       "              validate_parameters=1, verbosity=None)"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model=XGBClassifier()\n",
    "model.fit(x_train,y_train)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b3390b7d",
   "metadata": {},
   "source": [
    "#### 8. Finally, generate y_pred (predicted values for x_test) and calculate the accuracy for the model. Print it out."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "b90d5a45",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "94.87179487179486\n"
     ]
    }
   ],
   "source": [
    "y_pred=model.predict(x_test)\n",
    "print(accuracy_score(y_test, y_pred)*100)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d151ac93",
   "metadata": {},
   "source": [
    "<h2 style='color:blue'>Export the tested model to a pickle file</h2>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "88e7716f",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pickle\n",
    "with open('parkinson_model.pkl','wb') as f:\n",
    "    pickle.dump(model,f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c2b8f73e",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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