Lab-2 Statistical Analysis Using Pandas Part-2.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>TV</th>\n",
       "      <th>Radio</th>\n",
       "      <th>Newspaper</th>\n",
       "      <th>Sales</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>230.1</td>\n",
       "      <td>37.8</td>\n",
       "      <td>69.2</td>\n",
       "      <td>22.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>44.5</td>\n",
       "      <td>39.3</td>\n",
       "      <td>45.1</td>\n",
       "      <td>10.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>17.2</td>\n",
       "      <td>45.9</td>\n",
       "      <td>69.3</td>\n",
       "      <td>9.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>151.5</td>\n",
       "      <td>41.3</td>\n",
       "      <td>58.5</td>\n",
       "      <td>18.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>180.8</td>\n",
       "      <td>10.8</td>\n",
       "      <td>58.4</td>\n",
       "      <td>12.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>8.7</td>\n",
       "      <td>48.9</td>\n",
       "      <td>75.0</td>\n",
       "      <td>7.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>57.5</td>\n",
       "      <td>32.8</td>\n",
       "      <td>23.5</td>\n",
       "      <td>11.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>120.2</td>\n",
       "      <td>19.6</td>\n",
       "      <td>11.6</td>\n",
       "      <td>13.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>8.6</td>\n",
       "      <td>2.1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>199.8</td>\n",
       "      <td>2.6</td>\n",
       "      <td>21.2</td>\n",
       "      <td>10.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>11</td>\n",
       "      <td>66.1</td>\n",
       "      <td>5.8</td>\n",
       "      <td>24.2</td>\n",
       "      <td>8.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>12</td>\n",
       "      <td>214.7</td>\n",
       "      <td>24.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>17.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>13</td>\n",
       "      <td>23.8</td>\n",
       "      <td>35.1</td>\n",
       "      <td>65.9</td>\n",
       "      <td>9.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>14</td>\n",
       "      <td>97.5</td>\n",
       "      <td>7.6</td>\n",
       "      <td>7.2</td>\n",
       "      <td>9.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>15</td>\n",
       "      <td>204.1</td>\n",
       "      <td>32.9</td>\n",
       "      <td>46.0</td>\n",
       "      <td>19.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>16</td>\n",
       "      <td>195.4</td>\n",
       "      <td>47.7</td>\n",
       "      <td>52.9</td>\n",
       "      <td>22.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>17</td>\n",
       "      <td>67.8</td>\n",
       "      <td>36.6</td>\n",
       "      <td>114.0</td>\n",
       "      <td>12.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>18</td>\n",
       "      <td>281.4</td>\n",
       "      <td>39.6</td>\n",
       "      <td>55.8</td>\n",
       "      <td>24.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>19</td>\n",
       "      <td>69.2</td>\n",
       "      <td>20.5</td>\n",
       "      <td>18.3</td>\n",
       "      <td>11.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>20</td>\n",
       "      <td>147.3</td>\n",
       "      <td>23.9</td>\n",
       "      <td>19.1</td>\n",
       "      <td>14.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>21</td>\n",
       "      <td>218.4</td>\n",
       "      <td>27.7</td>\n",
       "      <td>53.4</td>\n",
       "      <td>18.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>22</td>\n",
       "      <td>237.4</td>\n",
       "      <td>5.1</td>\n",
       "      <td>23.5</td>\n",
       "      <td>12.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>23</td>\n",
       "      <td>13.2</td>\n",
       "      <td>15.9</td>\n",
       "      <td>49.6</td>\n",
       "      <td>5.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>24</td>\n",
       "      <td>228.3</td>\n",
       "      <td>16.9</td>\n",
       "      <td>26.2</td>\n",
       "      <td>15.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>25</td>\n",
       "      <td>62.3</td>\n",
       "      <td>12.6</td>\n",
       "      <td>18.3</td>\n",
       "      <td>9.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>26</td>\n",
       "      <td>262.9</td>\n",
       "      <td>3.5</td>\n",
       "      <td>19.5</td>\n",
       "      <td>12.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>27</td>\n",
       "      <td>142.9</td>\n",
       "      <td>29.3</td>\n",
       "      <td>12.6</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>28</td>\n",
       "      <td>240.1</td>\n",
       "      <td>16.7</td>\n",
       "      <td>22.9</td>\n",
       "      <td>15.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>29</td>\n",
       "      <td>248.8</td>\n",
       "      <td>27.1</td>\n",
       "      <td>22.9</td>\n",
       "      <td>18.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>30</td>\n",
       "      <td>70.6</td>\n",
       "      <td>16.0</td>\n",
       "      <td>40.8</td>\n",
       "      <td>10.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>170</th>\n",
       "      <td>171</td>\n",
       "      <td>50.0</td>\n",
       "      <td>11.6</td>\n",
       "      <td>18.4</td>\n",
       "      <td>8.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>171</th>\n",
       "      <td>172</td>\n",
       "      <td>164.5</td>\n",
       "      <td>20.9</td>\n",
       "      <td>47.4</td>\n",
       "      <td>14.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172</th>\n",
       "      <td>173</td>\n",
       "      <td>19.6</td>\n",
       "      <td>20.1</td>\n",
       "      <td>17.0</td>\n",
       "      <td>7.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>173</th>\n",
       "      <td>174</td>\n",
       "      <td>168.4</td>\n",
       "      <td>7.1</td>\n",
       "      <td>12.8</td>\n",
       "      <td>11.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>174</th>\n",
       "      <td>175</td>\n",
       "      <td>222.4</td>\n",
       "      <td>3.4</td>\n",
       "      <td>13.1</td>\n",
       "      <td>11.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>175</th>\n",
       "      <td>176</td>\n",
       "      <td>276.9</td>\n",
       "      <td>48.9</td>\n",
       "      <td>41.8</td>\n",
       "      <td>27.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>176</th>\n",
       "      <td>177</td>\n",
       "      <td>248.4</td>\n",
       "      <td>30.2</td>\n",
       "      <td>20.3</td>\n",
       "      <td>20.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>177</th>\n",
       "      <td>178</td>\n",
       "      <td>170.2</td>\n",
       "      <td>7.8</td>\n",
       "      <td>35.2</td>\n",
       "      <td>11.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>178</th>\n",
       "      <td>179</td>\n",
       "      <td>276.7</td>\n",
       "      <td>2.3</td>\n",
       "      <td>23.7</td>\n",
       "      <td>11.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>179</th>\n",
       "      <td>180</td>\n",
       "      <td>165.6</td>\n",
       "      <td>10.0</td>\n",
       "      <td>17.6</td>\n",
       "      <td>12.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180</th>\n",
       "      <td>181</td>\n",
       "      <td>156.6</td>\n",
       "      <td>2.6</td>\n",
       "      <td>8.3</td>\n",
       "      <td>10.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>181</th>\n",
       "      <td>182</td>\n",
       "      <td>218.5</td>\n",
       "      <td>5.4</td>\n",
       "      <td>27.4</td>\n",
       "      <td>12.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>182</th>\n",
       "      <td>183</td>\n",
       "      <td>56.2</td>\n",
       "      <td>5.7</td>\n",
       "      <td>29.7</td>\n",
       "      <td>8.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183</th>\n",
       "      <td>184</td>\n",
       "      <td>287.6</td>\n",
       "      <td>43.0</td>\n",
       "      <td>71.8</td>\n",
       "      <td>26.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>184</th>\n",
       "      <td>185</td>\n",
       "      <td>253.8</td>\n",
       "      <td>21.3</td>\n",
       "      <td>30.0</td>\n",
       "      <td>17.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>185</th>\n",
       "      <td>186</td>\n",
       "      <td>205.0</td>\n",
       "      <td>45.1</td>\n",
       "      <td>19.6</td>\n",
       "      <td>22.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>186</th>\n",
       "      <td>187</td>\n",
       "      <td>139.5</td>\n",
       "      <td>2.1</td>\n",
       "      <td>26.6</td>\n",
       "      <td>10.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>187</th>\n",
       "      <td>188</td>\n",
       "      <td>191.1</td>\n",
       "      <td>28.7</td>\n",
       "      <td>18.2</td>\n",
       "      <td>17.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>188</th>\n",
       "      <td>189</td>\n",
       "      <td>286.0</td>\n",
       "      <td>13.9</td>\n",
       "      <td>3.7</td>\n",
       "      <td>15.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>189</th>\n",
       "      <td>190</td>\n",
       "      <td>18.7</td>\n",
       "      <td>12.1</td>\n",
       "      <td>23.4</td>\n",
       "      <td>6.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>190</th>\n",
       "      <td>191</td>\n",
       "      <td>39.5</td>\n",
       "      <td>41.1</td>\n",
       "      <td>5.8</td>\n",
       "      <td>10.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>191</th>\n",
       "      <td>192</td>\n",
       "      <td>75.5</td>\n",
       "      <td>10.8</td>\n",
       "      <td>6.0</td>\n",
       "      <td>9.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>192</th>\n",
       "      <td>193</td>\n",
       "      <td>17.2</td>\n",
       "      <td>4.1</td>\n",
       "      <td>31.6</td>\n",
       "      <td>5.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193</th>\n",
       "      <td>194</td>\n",
       "      <td>166.8</td>\n",
       "      <td>42.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>19.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>194</th>\n",
       "      <td>195</td>\n",
       "      <td>149.7</td>\n",
       "      <td>35.6</td>\n",
       "      <td>6.0</td>\n",
       "      <td>17.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>195</th>\n",
       "      <td>196</td>\n",
       "      <td>38.2</td>\n",
       "      <td>3.7</td>\n",
       "      <td>13.8</td>\n",
       "      <td>7.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196</th>\n",
       "      <td>197</td>\n",
       "      <td>94.2</td>\n",
       "      <td>4.9</td>\n",
       "      <td>8.1</td>\n",
       "      <td>9.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197</th>\n",
       "      <td>198</td>\n",
       "      <td>177.0</td>\n",
       "      <td>9.3</td>\n",
       "      <td>6.4</td>\n",
       "      <td>12.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>198</th>\n",
       "      <td>199</td>\n",
       "      <td>283.6</td>\n",
       "      <td>42.0</td>\n",
       "      <td>66.2</td>\n",
       "      <td>25.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>199</th>\n",
       "      <td>200</td>\n",
       "      <td>232.1</td>\n",
       "      <td>8.6</td>\n",
       "      <td>8.7</td>\n",
       "      <td>13.4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>200 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Unnamed: 0     TV  Radio  Newspaper  Sales\n",
       "0             1  230.1   37.8       69.2   22.1\n",
       "1             2   44.5   39.3       45.1   10.4\n",
       "2             3   17.2   45.9       69.3    9.3\n",
       "3             4  151.5   41.3       58.5   18.5\n",
       "4             5  180.8   10.8       58.4   12.9\n",
       "5             6    8.7   48.9       75.0    7.2\n",
       "6             7   57.5   32.8       23.5   11.8\n",
       "7             8  120.2   19.6       11.6   13.2\n",
       "8             9    8.6    2.1        1.0    4.8\n",
       "9            10  199.8    2.6       21.2   10.6\n",
       "10           11   66.1    5.8       24.2    8.6\n",
       "11           12  214.7   24.0        4.0   17.4\n",
       "12           13   23.8   35.1       65.9    9.2\n",
       "13           14   97.5    7.6        7.2    9.7\n",
       "14           15  204.1   32.9       46.0   19.0\n",
       "15           16  195.4   47.7       52.9   22.4\n",
       "16           17   67.8   36.6      114.0   12.5\n",
       "17           18  281.4   39.6       55.8   24.4\n",
       "18           19   69.2   20.5       18.3   11.3\n",
       "19           20  147.3   23.9       19.1   14.6\n",
       "20           21  218.4   27.7       53.4   18.0\n",
       "21           22  237.4    5.1       23.5   12.5\n",
       "22           23   13.2   15.9       49.6    5.6\n",
       "23           24  228.3   16.9       26.2   15.5\n",
       "24           25   62.3   12.6       18.3    9.7\n",
       "25           26  262.9    3.5       19.5   12.0\n",
       "26           27  142.9   29.3       12.6   15.0\n",
       "27           28  240.1   16.7       22.9   15.9\n",
       "28           29  248.8   27.1       22.9   18.9\n",
       "29           30   70.6   16.0       40.8   10.5\n",
       "..          ...    ...    ...        ...    ...\n",
       "170         171   50.0   11.6       18.4    8.4\n",
       "171         172  164.5   20.9       47.4   14.5\n",
       "172         173   19.6   20.1       17.0    7.6\n",
       "173         174  168.4    7.1       12.8   11.7\n",
       "174         175  222.4    3.4       13.1   11.5\n",
       "175         176  276.9   48.9       41.8   27.0\n",
       "176         177  248.4   30.2       20.3   20.2\n",
       "177         178  170.2    7.8       35.2   11.7\n",
       "178         179  276.7    2.3       23.7   11.8\n",
       "179         180  165.6   10.0       17.6   12.6\n",
       "180         181  156.6    2.6        8.3   10.5\n",
       "181         182  218.5    5.4       27.4   12.2\n",
       "182         183   56.2    5.7       29.7    8.7\n",
       "183         184  287.6   43.0       71.8   26.2\n",
       "184         185  253.8   21.3       30.0   17.6\n",
       "185         186  205.0   45.1       19.6   22.6\n",
       "186         187  139.5    2.1       26.6   10.3\n",
       "187         188  191.1   28.7       18.2   17.3\n",
       "188         189  286.0   13.9        3.7   15.9\n",
       "189         190   18.7   12.1       23.4    6.7\n",
       "190         191   39.5   41.1        5.8   10.8\n",
       "191         192   75.5   10.8        6.0    9.9\n",
       "192         193   17.2    4.1       31.6    5.9\n",
       "193         194  166.8   42.0        3.6   19.6\n",
       "194         195  149.7   35.6        6.0   17.3\n",
       "195         196   38.2    3.7       13.8    7.6\n",
       "196         197   94.2    4.9        8.1    9.7\n",
       "197         198  177.0    9.3        6.4   12.8\n",
       "198         199  283.6   42.0       66.2   25.5\n",
       "199         200  232.1    8.6        8.7   13.4\n",
       "\n",
       "[200 rows x 5 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#1\n",
    "df=pd.read_csv(\"https://github.com/JWarmenhoven/ISLR-python/raw/master/Notebooks/Data/Advertising.csv\")\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>TV</th>\n",
       "      <th>Radio</th>\n",
       "      <th>Newspaper</th>\n",
       "      <th>Sales</th>\n",
       "    </tr>\n",
       "  </thead>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "      <td>False</td>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "      <td>False</td>\n",
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       "      <td>False</td>\n",
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       "      <td>False</td>\n",
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       "      <td>False</td>\n",
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       "      <th>5</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "    <tr>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "      <th>9</th>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>170</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>171</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>173</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>174</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>175</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>176</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>177</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>178</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>179</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>181</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>182</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>184</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>185</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>186</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>187</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>188</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>189</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>190</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>191</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>192</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>194</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>195</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>198</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>199</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>200 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Unnamed: 0     TV  Radio  Newspaper  Sales\n",
       "0         False  False  False      False  False\n",
       "1         False  False  False      False  False\n",
       "2         False  False  False      False  False\n",
       "3         False  False  False      False  False\n",
       "4         False  False  False      False  False\n",
       "5         False  False  False      False  False\n",
       "6         False  False  False      False  False\n",
       "7         False  False  False      False  False\n",
       "8         False  False  False      False  False\n",
       "9         False  False  False      False  False\n",
       "10        False  False  False      False  False\n",
       "11        False  False  False      False  False\n",
       "12        False  False  False      False  False\n",
       "13        False  False  False      False  False\n",
       "14        False  False  False      False  False\n",
       "15        False  False  False      False  False\n",
       "16        False  False  False      False  False\n",
       "17        False  False  False      False  False\n",
       "18        False  False  False      False  False\n",
       "19        False  False  False      False  False\n",
       "20        False  False  False      False  False\n",
       "21        False  False  False      False  False\n",
       "22        False  False  False      False  False\n",
       "23        False  False  False      False  False\n",
       "24        False  False  False      False  False\n",
       "25        False  False  False      False  False\n",
       "26        False  False  False      False  False\n",
       "27        False  False  False      False  False\n",
       "28        False  False  False      False  False\n",
       "29        False  False  False      False  False\n",
       "..          ...    ...    ...        ...    ...\n",
       "170       False  False  False      False  False\n",
       "171       False  False  False      False  False\n",
       "172       False  False  False      False  False\n",
       "173       False  False  False      False  False\n",
       "174       False  False  False      False  False\n",
       "175       False  False  False      False  False\n",
       "176       False  False  False      False  False\n",
       "177       False  False  False      False  False\n",
       "178       False  False  False      False  False\n",
       "179       False  False  False      False  False\n",
       "180       False  False  False      False  False\n",
       "181       False  False  False      False  False\n",
       "182       False  False  False      False  False\n",
       "183       False  False  False      False  False\n",
       "184       False  False  False      False  False\n",
       "185       False  False  False      False  False\n",
       "186       False  False  False      False  False\n",
       "187       False  False  False      False  False\n",
       "188       False  False  False      False  False\n",
       "189       False  False  False      False  False\n",
       "190       False  False  False      False  False\n",
       "191       False  False  False      False  False\n",
       "192       False  False  False      False  False\n",
       "193       False  False  False      False  False\n",
       "194       False  False  False      False  False\n",
       "195       False  False  False      False  False\n",
       "196       False  False  False      False  False\n",
       "197       False  False  False      False  False\n",
       "198       False  False  False      False  False\n",
       "199       False  False  False      False  False\n",
       "\n",
       "[200 rows x 5 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#2\n",
    "df.isnull()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<div>\n",
       "<style scoped>\n",
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       "\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Sales Type</th>\n",
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       "  </thead>\n",
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       "      <th>8</th>\n",
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       "      <th>9</th>\n",
       "      <td>medium</td>\n",
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       "      <th>10</th>\n",
       "      <td>medium</td>\n",
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       "      <th>11</th>\n",
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       "      <td>medium</td>\n",
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       "      <th>14</th>\n",
       "      <td>high</td>\n",
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       "      <th>15</th>\n",
       "      <td>high</td>\n",
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       "      <th>16</th>\n",
       "      <td>medium</td>\n",
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       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>high</td>\n",
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       "      <th>18</th>\n",
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       "      <th>19</th>\n",
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       "      <th>20</th>\n",
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       "      <th>21</th>\n",
       "      <td>medium</td>\n",
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       "      <th>22</th>\n",
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       "      <th>25</th>\n",
       "      <td>medium</td>\n",
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       "      <th>26</th>\n",
       "      <td>high</td>\n",
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       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>high</td>\n",
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       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>high</td>\n",
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       "      <th>29</th>\n",
       "      <td>medium</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
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       "      <th>170</th>\n",
       "      <td>medium</td>\n",
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       "    <tr>\n",
       "      <th>171</th>\n",
       "      <td>medium</td>\n",
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       "    <tr>\n",
       "      <th>172</th>\n",
       "      <td>medium</td>\n",
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       "      <th>173</th>\n",
       "      <td>medium</td>\n",
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       "      <th>174</th>\n",
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       "      <th>175</th>\n",
       "      <td>high</td>\n",
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       "    <tr>\n",
       "      <th>176</th>\n",
       "      <td>high</td>\n",
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       "    <tr>\n",
       "      <th>177</th>\n",
       "      <td>medium</td>\n",
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       "    <tr>\n",
       "      <th>178</th>\n",
       "      <td>medium</td>\n",
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       "    <tr>\n",
       "      <th>179</th>\n",
       "      <td>medium</td>\n",
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       "    <tr>\n",
       "      <th>180</th>\n",
       "      <td>medium</td>\n",
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       "    <tr>\n",
       "      <th>181</th>\n",
       "      <td>medium</td>\n",
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       "    <tr>\n",
       "      <th>182</th>\n",
       "      <td>medium</td>\n",
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       "    <tr>\n",
       "      <th>183</th>\n",
       "      <td>high</td>\n",
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       "    <tr>\n",
       "      <th>184</th>\n",
       "      <td>high</td>\n",
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       "    <tr>\n",
       "      <th>185</th>\n",
       "      <td>high</td>\n",
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       "    <tr>\n",
       "      <th>186</th>\n",
       "      <td>medium</td>\n",
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       "    <tr>\n",
       "      <th>187</th>\n",
       "      <td>high</td>\n",
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       "    <tr>\n",
       "      <th>188</th>\n",
       "      <td>high</td>\n",
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       "    <tr>\n",
       "      <th>189</th>\n",
       "      <td>medium</td>\n",
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       "    <tr>\n",
       "      <th>190</th>\n",
       "      <td>medium</td>\n",
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       "      <th>191</th>\n",
       "      <td>medium</td>\n",
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       "    <tr>\n",
       "      <th>192</th>\n",
       "      <td>medium</td>\n",
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       "    <tr>\n",
       "      <th>193</th>\n",
       "      <td>high</td>\n",
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       "    <tr>\n",
       "      <th>194</th>\n",
       "      <td>high</td>\n",
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       "    <tr>\n",
       "      <th>195</th>\n",
       "      <td>medium</td>\n",
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       "      <th>196</th>\n",
       "      <td>medium</td>\n",
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       "    <tr>\n",
       "      <th>197</th>\n",
       "      <td>medium</td>\n",
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       "    <tr>\n",
       "      <th>198</th>\n",
       "      <td>high</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>199</th>\n",
       "      <td>medium</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>200 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    Sales Type\n",
       "0         high\n",
       "1       medium\n",
       "2       medium\n",
       "3         high\n",
       "4       medium\n",
       "5       medium\n",
       "6       medium\n",
       "7       medium\n",
       "8          low\n",
       "9       medium\n",
       "10      medium\n",
       "11        high\n",
       "12      medium\n",
       "13      medium\n",
       "14        high\n",
       "15        high\n",
       "16      medium\n",
       "17        high\n",
       "18      medium\n",
       "19      medium\n",
       "20        high\n",
       "21      medium\n",
       "22      medium\n",
       "23        high\n",
       "24      medium\n",
       "25      medium\n",
       "26        high\n",
       "27        high\n",
       "28        high\n",
       "29      medium\n",
       "..         ...\n",
       "170     medium\n",
       "171     medium\n",
       "172     medium\n",
       "173     medium\n",
       "174     medium\n",
       "175       high\n",
       "176       high\n",
       "177     medium\n",
       "178     medium\n",
       "179     medium\n",
       "180     medium\n",
       "181     medium\n",
       "182     medium\n",
       "183       high\n",
       "184       high\n",
       "185       high\n",
       "186     medium\n",
       "187       high\n",
       "188       high\n",
       "189     medium\n",
       "190     medium\n",
       "191     medium\n",
       "192     medium\n",
       "193       high\n",
       "194       high\n",
       "195     medium\n",
       "196     medium\n",
       "197     medium\n",
       "198       high\n",
       "199     medium\n",
       "\n",
       "[200 rows x 1 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#3\n",
    "df1=pd.DataFrame()\n",
    "df1['Sales Type']=np.select([df['Sales']>=15,(df['Sales']<15)&(df['Sales']>=5),df['Sales']<5],['high','medium','low'])\n",
    "df1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>TV</th>\n",
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       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
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       "    <tr>\n",
       "      <th>6</th>\n",
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       "      <td>57.5</td>\n",
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       "    <tr>\n",
       "      <th>7</th>\n",
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       "      <td>120.2</td>\n",
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       "      <th>8</th>\n",
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       "      <td>1.0</td>\n",
       "      <td>4.8</td>\n",
       "      <td>low</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>199.8</td>\n",
       "      <td>2.6</td>\n",
       "      <td>21.2</td>\n",
       "      <td>10.6</td>\n",
       "      <td>medium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>11</td>\n",
       "      <td>66.1</td>\n",
       "      <td>5.8</td>\n",
       "      <td>24.2</td>\n",
       "      <td>8.6</td>\n",
       "      <td>medium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>12</td>\n",
       "      <td>214.7</td>\n",
       "      <td>24.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>17.4</td>\n",
       "      <td>high</td>\n",
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       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>13</td>\n",
       "      <td>23.8</td>\n",
       "      <td>35.1</td>\n",
       "      <td>65.9</td>\n",
       "      <td>9.2</td>\n",
       "      <td>medium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>14</td>\n",
       "      <td>97.5</td>\n",
       "      <td>7.6</td>\n",
       "      <td>7.2</td>\n",
       "      <td>9.7</td>\n",
       "      <td>medium</td>\n",
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       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>15</td>\n",
       "      <td>204.1</td>\n",
       "      <td>32.9</td>\n",
       "      <td>46.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>high</td>\n",
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       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>16</td>\n",
       "      <td>195.4</td>\n",
       "      <td>47.7</td>\n",
       "      <td>52.9</td>\n",
       "      <td>22.4</td>\n",
       "      <td>high</td>\n",
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       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>17</td>\n",
       "      <td>67.8</td>\n",
       "      <td>36.6</td>\n",
       "      <td>114.0</td>\n",
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       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>18</td>\n",
       "      <td>281.4</td>\n",
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       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>19</td>\n",
       "      <td>69.2</td>\n",
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       "      <td>11.3</td>\n",
       "      <td>medium</td>\n",
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       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>20</td>\n",
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       "      <th>20</th>\n",
       "      <td>21</td>\n",
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       "      <td>53.4</td>\n",
       "      <td>18.0</td>\n",
       "      <td>high</td>\n",
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       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>22</td>\n",
       "      <td>237.4</td>\n",
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       "      <td>23.5</td>\n",
       "      <td>12.5</td>\n",
       "      <td>medium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>23</td>\n",
       "      <td>13.2</td>\n",
       "      <td>15.9</td>\n",
       "      <td>49.6</td>\n",
       "      <td>5.6</td>\n",
       "      <td>medium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>24</td>\n",
       "      <td>228.3</td>\n",
       "      <td>16.9</td>\n",
       "      <td>26.2</td>\n",
       "      <td>15.5</td>\n",
       "      <td>high</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>25</td>\n",
       "      <td>62.3</td>\n",
       "      <td>12.6</td>\n",
       "      <td>18.3</td>\n",
       "      <td>9.7</td>\n",
       "      <td>medium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>26</td>\n",
       "      <td>262.9</td>\n",
       "      <td>3.5</td>\n",
       "      <td>19.5</td>\n",
       "      <td>12.0</td>\n",
       "      <td>medium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>27</td>\n",
       "      <td>142.9</td>\n",
       "      <td>29.3</td>\n",
       "      <td>12.6</td>\n",
       "      <td>15.0</td>\n",
       "      <td>high</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>28</td>\n",
       "      <td>240.1</td>\n",
       "      <td>16.7</td>\n",
       "      <td>22.9</td>\n",
       "      <td>15.9</td>\n",
       "      <td>high</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>29</td>\n",
       "      <td>248.8</td>\n",
       "      <td>27.1</td>\n",
       "      <td>22.9</td>\n",
       "      <td>18.9</td>\n",
       "      <td>high</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>30</td>\n",
       "      <td>70.6</td>\n",
       "      <td>16.0</td>\n",
       "      <td>40.8</td>\n",
       "      <td>10.5</td>\n",
       "      <td>medium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>170</th>\n",
       "      <td>171</td>\n",
       "      <td>50.0</td>\n",
       "      <td>11.6</td>\n",
       "      <td>18.4</td>\n",
       "      <td>8.4</td>\n",
       "      <td>medium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>171</th>\n",
       "      <td>172</td>\n",
       "      <td>164.5</td>\n",
       "      <td>20.9</td>\n",
       "      <td>47.4</td>\n",
       "      <td>14.5</td>\n",
       "      <td>medium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172</th>\n",
       "      <td>173</td>\n",
       "      <td>19.6</td>\n",
       "      <td>20.1</td>\n",
       "      <td>17.0</td>\n",
       "      <td>7.6</td>\n",
       "      <td>medium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>173</th>\n",
       "      <td>174</td>\n",
       "      <td>168.4</td>\n",
       "      <td>7.1</td>\n",
       "      <td>12.8</td>\n",
       "      <td>11.7</td>\n",
       "      <td>medium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>174</th>\n",
       "      <td>175</td>\n",
       "      <td>222.4</td>\n",
       "      <td>3.4</td>\n",
       "      <td>13.1</td>\n",
       "      <td>11.5</td>\n",
       "      <td>medium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>175</th>\n",
       "      <td>176</td>\n",
       "      <td>276.9</td>\n",
       "      <td>48.9</td>\n",
       "      <td>41.8</td>\n",
       "      <td>27.0</td>\n",
       "      <td>high</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>176</th>\n",
       "      <td>177</td>\n",
       "      <td>248.4</td>\n",
       "      <td>30.2</td>\n",
       "      <td>20.3</td>\n",
       "      <td>20.2</td>\n",
       "      <td>high</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>177</th>\n",
       "      <td>178</td>\n",
       "      <td>170.2</td>\n",
       "      <td>7.8</td>\n",
       "      <td>35.2</td>\n",
       "      <td>11.7</td>\n",
       "      <td>medium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>178</th>\n",
       "      <td>179</td>\n",
       "      <td>276.7</td>\n",
       "      <td>2.3</td>\n",
       "      <td>23.7</td>\n",
       "      <td>11.8</td>\n",
       "      <td>medium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>179</th>\n",
       "      <td>180</td>\n",
       "      <td>165.6</td>\n",
       "      <td>10.0</td>\n",
       "      <td>17.6</td>\n",
       "      <td>12.6</td>\n",
       "      <td>medium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180</th>\n",
       "      <td>181</td>\n",
       "      <td>156.6</td>\n",
       "      <td>2.6</td>\n",
       "      <td>8.3</td>\n",
       "      <td>10.5</td>\n",
       "      <td>medium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>181</th>\n",
       "      <td>182</td>\n",
       "      <td>218.5</td>\n",
       "      <td>5.4</td>\n",
       "      <td>27.4</td>\n",
       "      <td>12.2</td>\n",
       "      <td>medium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>182</th>\n",
       "      <td>183</td>\n",
       "      <td>56.2</td>\n",
       "      <td>5.7</td>\n",
       "      <td>29.7</td>\n",
       "      <td>8.7</td>\n",
       "      <td>medium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183</th>\n",
       "      <td>184</td>\n",
       "      <td>287.6</td>\n",
       "      <td>43.0</td>\n",
       "      <td>71.8</td>\n",
       "      <td>26.2</td>\n",
       "      <td>high</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>184</th>\n",
       "      <td>185</td>\n",
       "      <td>253.8</td>\n",
       "      <td>21.3</td>\n",
       "      <td>30.0</td>\n",
       "      <td>17.6</td>\n",
       "      <td>high</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>185</th>\n",
       "      <td>186</td>\n",
       "      <td>205.0</td>\n",
       "      <td>45.1</td>\n",
       "      <td>19.6</td>\n",
       "      <td>22.6</td>\n",
       "      <td>high</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>186</th>\n",
       "      <td>187</td>\n",
       "      <td>139.5</td>\n",
       "      <td>2.1</td>\n",
       "      <td>26.6</td>\n",
       "      <td>10.3</td>\n",
       "      <td>medium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>187</th>\n",
       "      <td>188</td>\n",
       "      <td>191.1</td>\n",
       "      <td>28.7</td>\n",
       "      <td>18.2</td>\n",
       "      <td>17.3</td>\n",
       "      <td>high</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>188</th>\n",
       "      <td>189</td>\n",
       "      <td>286.0</td>\n",
       "      <td>13.9</td>\n",
       "      <td>3.7</td>\n",
       "      <td>15.9</td>\n",
       "      <td>high</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>189</th>\n",
       "      <td>190</td>\n",
       "      <td>18.7</td>\n",
       "      <td>12.1</td>\n",
       "      <td>23.4</td>\n",
       "      <td>6.7</td>\n",
       "      <td>medium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>190</th>\n",
       "      <td>191</td>\n",
       "      <td>39.5</td>\n",
       "      <td>41.1</td>\n",
       "      <td>5.8</td>\n",
       "      <td>10.8</td>\n",
       "      <td>medium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>191</th>\n",
       "      <td>192</td>\n",
       "      <td>75.5</td>\n",
       "      <td>10.8</td>\n",
       "      <td>6.0</td>\n",
       "      <td>9.9</td>\n",
       "      <td>medium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>192</th>\n",
       "      <td>193</td>\n",
       "      <td>17.2</td>\n",
       "      <td>4.1</td>\n",
       "      <td>31.6</td>\n",
       "      <td>5.9</td>\n",
       "      <td>medium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193</th>\n",
       "      <td>194</td>\n",
       "      <td>166.8</td>\n",
       "      <td>42.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>19.6</td>\n",
       "      <td>high</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>194</th>\n",
       "      <td>195</td>\n",
       "      <td>149.7</td>\n",
       "      <td>35.6</td>\n",
       "      <td>6.0</td>\n",
       "      <td>17.3</td>\n",
       "      <td>high</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>195</th>\n",
       "      <td>196</td>\n",
       "      <td>38.2</td>\n",
       "      <td>3.7</td>\n",
       "      <td>13.8</td>\n",
       "      <td>7.6</td>\n",
       "      <td>medium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196</th>\n",
       "      <td>197</td>\n",
       "      <td>94.2</td>\n",
       "      <td>4.9</td>\n",
       "      <td>8.1</td>\n",
       "      <td>9.7</td>\n",
       "      <td>medium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197</th>\n",
       "      <td>198</td>\n",
       "      <td>177.0</td>\n",
       "      <td>9.3</td>\n",
       "      <td>6.4</td>\n",
       "      <td>12.8</td>\n",
       "      <td>medium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>198</th>\n",
       "      <td>199</td>\n",
       "      <td>283.6</td>\n",
       "      <td>42.0</td>\n",
       "      <td>66.2</td>\n",
       "      <td>25.5</td>\n",
       "      <td>high</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>199</th>\n",
       "      <td>200</td>\n",
       "      <td>232.1</td>\n",
       "      <td>8.6</td>\n",
       "      <td>8.7</td>\n",
       "      <td>13.4</td>\n",
       "      <td>medium</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>200 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Unnamed: 0     TV  Radio  Newspaper  Sales Sales Type\n",
       "0             1  230.1   37.8       69.2   22.1       high\n",
       "1             2   44.5   39.3       45.1   10.4     medium\n",
       "2             3   17.2   45.9       69.3    9.3     medium\n",
       "3             4  151.5   41.3       58.5   18.5       high\n",
       "4             5  180.8   10.8       58.4   12.9     medium\n",
       "5             6    8.7   48.9       75.0    7.2     medium\n",
       "6             7   57.5   32.8       23.5   11.8     medium\n",
       "7             8  120.2   19.6       11.6   13.2     medium\n",
       "8             9    8.6    2.1        1.0    4.8        low\n",
       "9            10  199.8    2.6       21.2   10.6     medium\n",
       "10           11   66.1    5.8       24.2    8.6     medium\n",
       "11           12  214.7   24.0        4.0   17.4       high\n",
       "12           13   23.8   35.1       65.9    9.2     medium\n",
       "13           14   97.5    7.6        7.2    9.7     medium\n",
       "14           15  204.1   32.9       46.0   19.0       high\n",
       "15           16  195.4   47.7       52.9   22.4       high\n",
       "16           17   67.8   36.6      114.0   12.5     medium\n",
       "17           18  281.4   39.6       55.8   24.4       high\n",
       "18           19   69.2   20.5       18.3   11.3     medium\n",
       "19           20  147.3   23.9       19.1   14.6     medium\n",
       "20           21  218.4   27.7       53.4   18.0       high\n",
       "21           22  237.4    5.1       23.5   12.5     medium\n",
       "22           23   13.2   15.9       49.6    5.6     medium\n",
       "23           24  228.3   16.9       26.2   15.5       high\n",
       "24           25   62.3   12.6       18.3    9.7     medium\n",
       "25           26  262.9    3.5       19.5   12.0     medium\n",
       "26           27  142.9   29.3       12.6   15.0       high\n",
       "27           28  240.1   16.7       22.9   15.9       high\n",
       "28           29  248.8   27.1       22.9   18.9       high\n",
       "29           30   70.6   16.0       40.8   10.5     medium\n",
       "..          ...    ...    ...        ...    ...        ...\n",
       "170         171   50.0   11.6       18.4    8.4     medium\n",
       "171         172  164.5   20.9       47.4   14.5     medium\n",
       "172         173   19.6   20.1       17.0    7.6     medium\n",
       "173         174  168.4    7.1       12.8   11.7     medium\n",
       "174         175  222.4    3.4       13.1   11.5     medium\n",
       "175         176  276.9   48.9       41.8   27.0       high\n",
       "176         177  248.4   30.2       20.3   20.2       high\n",
       "177         178  170.2    7.8       35.2   11.7     medium\n",
       "178         179  276.7    2.3       23.7   11.8     medium\n",
       "179         180  165.6   10.0       17.6   12.6     medium\n",
       "180         181  156.6    2.6        8.3   10.5     medium\n",
       "181         182  218.5    5.4       27.4   12.2     medium\n",
       "182         183   56.2    5.7       29.7    8.7     medium\n",
       "183         184  287.6   43.0       71.8   26.2       high\n",
       "184         185  253.8   21.3       30.0   17.6       high\n",
       "185         186  205.0   45.1       19.6   22.6       high\n",
       "186         187  139.5    2.1       26.6   10.3     medium\n",
       "187         188  191.1   28.7       18.2   17.3       high\n",
       "188         189  286.0   13.9        3.7   15.9       high\n",
       "189         190   18.7   12.1       23.4    6.7     medium\n",
       "190         191   39.5   41.1        5.8   10.8     medium\n",
       "191         192   75.5   10.8        6.0    9.9     medium\n",
       "192         193   17.2    4.1       31.6    5.9     medium\n",
       "193         194  166.8   42.0        3.6   19.6       high\n",
       "194         195  149.7   35.6        6.0   17.3       high\n",
       "195         196   38.2    3.7       13.8    7.6     medium\n",
       "196         197   94.2    4.9        8.1    9.7     medium\n",
       "197         198  177.0    9.3        6.4   12.8     medium\n",
       "198         199  283.6   42.0       66.2   25.5       high\n",
       "199         200  232.1    8.6        8.7   13.4     medium\n",
       "\n",
       "[200 rows x 6 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#4\n",
    "data=pd.concat([df,df1],sort=False,axis=1)\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Sum:\n",
      " Sales Type\n",
      "high      16469.8\n",
      "low          13.4\n",
      "medium    12925.3\n",
      "Name: TV, dtype: float64\n",
      "\n",
      "Mean:\n",
      " Sales Type\n",
      "high      213.893506\n",
      "low         4.466667\n",
      "medium    107.710833\n",
      "Name: TV, dtype: float64\n",
      "\n",
      "Sum:\n",
      " Sales Type\n",
      "high      2720.6\n",
      "low         15.4\n",
      "medium    3374.8\n",
      "Name: Newspaper, dtype: float64\n",
      "\n",
      "Mean:\n",
      " Sales Type\n",
      "high      35.332468\n",
      "low        5.133333\n",
      "medium    28.123333\n",
      "Name: Newspaper, dtype: float64\n",
      "\n",
      "Sum:\n",
      " Sales Type\n",
      "high      2594.1\n",
      "low         53.3\n",
      "medium    2005.4\n",
      "Name: Radio, dtype: float64\n",
      "\n",
      "Mean:\n",
      " Sales Type\n",
      "high      33.689610\n",
      "low       17.766667\n",
      "medium    16.711667\n",
      "Name: Radio, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "#5\n",
    "print('Sum:\\n',data.groupby('Sales Type')['TV'].sum())\n",
    "print('\\nMean:\\n',data.groupby('Sales Type')['TV'].mean())\n",
    "print('\\nSum:\\n',data.groupby('Sales Type')['Newspaper'].sum())\n",
    "print('\\nMean:\\n',data.groupby('Sales Type')['Newspaper'].mean())\n",
    "print('\\nSum:\\n',data.groupby('Sales Type')['Radio'].sum())\n",
    "print('\\nMean:\\n',data.groupby('Sales Type')['Radio'].mean())\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>Sales Type</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>medium</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>22.1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>18.5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>NaN</td>\n",
       "      <td>4.8</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>17.4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>19.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>22.4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>24.4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>18.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>15.5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>15.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>15.9</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>18.9</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>171</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>173</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>174</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>175</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>176</th>\n",
       "      <td>27.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>177</th>\n",
       "      <td>20.2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>178</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>179</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>181</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>182</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>184</th>\n",
       "      <td>26.2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>185</th>\n",
       "      <td>17.6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>186</th>\n",
       "      <td>22.6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>187</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>188</th>\n",
       "      <td>17.3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>189</th>\n",
       "      <td>15.9</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>190</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>191</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>192</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>194</th>\n",
       "      <td>19.6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>195</th>\n",
       "      <td>17.3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>198</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>199</th>\n",
       "      <td>25.5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>200</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>200 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "Sales Type  high  low  medium\n",
       "Unnamed: 0                   \n",
       "1           22.1  NaN     NaN\n",
       "2            NaN  NaN    10.4\n",
       "3            NaN  NaN     9.3\n",
       "4           18.5  NaN     NaN\n",
       "5            NaN  NaN    12.9\n",
       "6            NaN  NaN     7.2\n",
       "7            NaN  NaN    11.8\n",
       "8            NaN  NaN    13.2\n",
       "9            NaN  4.8     NaN\n",
       "10           NaN  NaN    10.6\n",
       "11           NaN  NaN     8.6\n",
       "12          17.4  NaN     NaN\n",
       "13           NaN  NaN     9.2\n",
       "14           NaN  NaN     9.7\n",
       "15          19.0  NaN     NaN\n",
       "16          22.4  NaN     NaN\n",
       "17           NaN  NaN    12.5\n",
       "18          24.4  NaN     NaN\n",
       "19           NaN  NaN    11.3\n",
       "20           NaN  NaN    14.6\n",
       "21          18.0  NaN     NaN\n",
       "22           NaN  NaN    12.5\n",
       "23           NaN  NaN     5.6\n",
       "24          15.5  NaN     NaN\n",
       "25           NaN  NaN     9.7\n",
       "26           NaN  NaN    12.0\n",
       "27          15.0  NaN     NaN\n",
       "28          15.9  NaN     NaN\n",
       "29          18.9  NaN     NaN\n",
       "30           NaN  NaN    10.5\n",
       "...          ...  ...     ...\n",
       "171          NaN  NaN     8.4\n",
       "172          NaN  NaN    14.5\n",
       "173          NaN  NaN     7.6\n",
       "174          NaN  NaN    11.7\n",
       "175          NaN  NaN    11.5\n",
       "176         27.0  NaN     NaN\n",
       "177         20.2  NaN     NaN\n",
       "178          NaN  NaN    11.7\n",
       "179          NaN  NaN    11.8\n",
       "180          NaN  NaN    12.6\n",
       "181          NaN  NaN    10.5\n",
       "182          NaN  NaN    12.2\n",
       "183          NaN  NaN     8.7\n",
       "184         26.2  NaN     NaN\n",
       "185         17.6  NaN     NaN\n",
       "186         22.6  NaN     NaN\n",
       "187          NaN  NaN    10.3\n",
       "188         17.3  NaN     NaN\n",
       "189         15.9  NaN     NaN\n",
       "190          NaN  NaN     6.7\n",
       "191          NaN  NaN    10.8\n",
       "192          NaN  NaN     9.9\n",
       "193          NaN  NaN     5.9\n",
       "194         19.6  NaN     NaN\n",
       "195         17.3  NaN     NaN\n",
       "196          NaN  NaN     7.6\n",
       "197          NaN  NaN     9.7\n",
       "198          NaN  NaN    12.8\n",
       "199         25.5  NaN     NaN\n",
       "200          NaN  NaN    13.4\n",
       "\n",
       "[200 rows x 3 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#6\n",
    "df1=data.pivot(index='Unnamed: 0',columns='Sales Type',values='Sales')\n",
    "df1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "#7\n",
    "#Replacing every 6th row of TV and 10th row of Newspaper with NaN\n",
    "dfc=df.copy()\n",
    "for i in range(len(dfc)):\n",
    "    if((i+1)%6==0):\n",
    "        dfc['TV'][i]=np.nan\n",
    "    if((i+1)%10==0):\n",
    "        dfc['Newspaper'][i]=np.nan"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "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",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>TV</th>\n",
       "      <th>Radio</th>\n",
       "      <th>Newspaper</th>\n",
       "      <th>Sales</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>230.1</td>\n",
       "      <td>37.8</td>\n",
       "      <td>69.2</td>\n",
       "      <td>22.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>44.5</td>\n",
       "      <td>39.3</td>\n",
       "      <td>45.1</td>\n",
       "      <td>10.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>17.2</td>\n",
       "      <td>45.9</td>\n",
       "      <td>69.3</td>\n",
       "      <td>9.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>151.5</td>\n",
       "      <td>41.3</td>\n",
       "      <td>58.5</td>\n",
       "      <td>18.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>180.8</td>\n",
       "      <td>10.8</td>\n",
       "      <td>58.4</td>\n",
       "      <td>12.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>48.9</td>\n",
       "      <td>75.0</td>\n",
       "      <td>7.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>57.5</td>\n",
       "      <td>32.8</td>\n",
       "      <td>23.5</td>\n",
       "      <td>11.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>120.2</td>\n",
       "      <td>19.6</td>\n",
       "      <td>11.6</td>\n",
       "      <td>13.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>8.6</td>\n",
       "      <td>2.1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>199.8</td>\n",
       "      <td>2.6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>11</td>\n",
       "      <td>66.1</td>\n",
       "      <td>5.8</td>\n",
       "      <td>24.2</td>\n",
       "      <td>8.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>12</td>\n",
       "      <td>NaN</td>\n",
       "      <td>24.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>17.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>13</td>\n",
       "      <td>23.8</td>\n",
       "      <td>35.1</td>\n",
       "      <td>65.9</td>\n",
       "      <td>9.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>14</td>\n",
       "      <td>97.5</td>\n",
       "      <td>7.6</td>\n",
       "      <td>7.2</td>\n",
       "      <td>9.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>15</td>\n",
       "      <td>204.1</td>\n",
       "      <td>32.9</td>\n",
       "      <td>46.0</td>\n",
       "      <td>19.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>16</td>\n",
       "      <td>195.4</td>\n",
       "      <td>47.7</td>\n",
       "      <td>52.9</td>\n",
       "      <td>22.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>17</td>\n",
       "      <td>67.8</td>\n",
       "      <td>36.6</td>\n",
       "      <td>114.0</td>\n",
       "      <td>12.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>18</td>\n",
       "      <td>NaN</td>\n",
       "      <td>39.6</td>\n",
       "      <td>55.8</td>\n",
       "      <td>24.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>19</td>\n",
       "      <td>69.2</td>\n",
       "      <td>20.5</td>\n",
       "      <td>18.3</td>\n",
       "      <td>11.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>20</td>\n",
       "      <td>147.3</td>\n",
       "      <td>23.9</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>21</td>\n",
       "      <td>218.4</td>\n",
       "      <td>27.7</td>\n",
       "      <td>53.4</td>\n",
       "      <td>18.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>22</td>\n",
       "      <td>237.4</td>\n",
       "      <td>5.1</td>\n",
       "      <td>23.5</td>\n",
       "      <td>12.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>23</td>\n",
       "      <td>13.2</td>\n",
       "      <td>15.9</td>\n",
       "      <td>49.6</td>\n",
       "      <td>5.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>24</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16.9</td>\n",
       "      <td>26.2</td>\n",
       "      <td>15.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>25</td>\n",
       "      <td>62.3</td>\n",
       "      <td>12.6</td>\n",
       "      <td>18.3</td>\n",
       "      <td>9.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>26</td>\n",
       "      <td>262.9</td>\n",
       "      <td>3.5</td>\n",
       "      <td>19.5</td>\n",
       "      <td>12.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>27</td>\n",
       "      <td>142.9</td>\n",
       "      <td>29.3</td>\n",
       "      <td>12.6</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>28</td>\n",
       "      <td>240.1</td>\n",
       "      <td>16.7</td>\n",
       "      <td>22.9</td>\n",
       "      <td>15.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>29</td>\n",
       "      <td>248.8</td>\n",
       "      <td>27.1</td>\n",
       "      <td>22.9</td>\n",
       "      <td>18.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>170</th>\n",
       "      <td>171</td>\n",
       "      <td>50.0</td>\n",
       "      <td>11.6</td>\n",
       "      <td>18.4</td>\n",
       "      <td>8.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>171</th>\n",
       "      <td>172</td>\n",
       "      <td>164.5</td>\n",
       "      <td>20.9</td>\n",
       "      <td>47.4</td>\n",
       "      <td>14.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172</th>\n",
       "      <td>173</td>\n",
       "      <td>19.6</td>\n",
       "      <td>20.1</td>\n",
       "      <td>17.0</td>\n",
       "      <td>7.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>173</th>\n",
       "      <td>174</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.1</td>\n",
       "      <td>12.8</td>\n",
       "      <td>11.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>174</th>\n",
       "      <td>175</td>\n",
       "      <td>222.4</td>\n",
       "      <td>3.4</td>\n",
       "      <td>13.1</td>\n",
       "      <td>11.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>175</th>\n",
       "      <td>176</td>\n",
       "      <td>276.9</td>\n",
       "      <td>48.9</td>\n",
       "      <td>41.8</td>\n",
       "      <td>27.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>176</th>\n",
       "      <td>177</td>\n",
       "      <td>248.4</td>\n",
       "      <td>30.2</td>\n",
       "      <td>20.3</td>\n",
       "      <td>20.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>177</th>\n",
       "      <td>178</td>\n",
       "      <td>170.2</td>\n",
       "      <td>7.8</td>\n",
       "      <td>35.2</td>\n",
       "      <td>11.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>178</th>\n",
       "      <td>179</td>\n",
       "      <td>276.7</td>\n",
       "      <td>2.3</td>\n",
       "      <td>23.7</td>\n",
       "      <td>11.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>179</th>\n",
       "      <td>180</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180</th>\n",
       "      <td>181</td>\n",
       "      <td>156.6</td>\n",
       "      <td>2.6</td>\n",
       "      <td>8.3</td>\n",
       "      <td>10.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>181</th>\n",
       "      <td>182</td>\n",
       "      <td>218.5</td>\n",
       "      <td>5.4</td>\n",
       "      <td>27.4</td>\n",
       "      <td>12.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>182</th>\n",
       "      <td>183</td>\n",
       "      <td>56.2</td>\n",
       "      <td>5.7</td>\n",
       "      <td>29.7</td>\n",
       "      <td>8.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183</th>\n",
       "      <td>184</td>\n",
       "      <td>287.6</td>\n",
       "      <td>43.0</td>\n",
       "      <td>71.8</td>\n",
       "      <td>26.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>184</th>\n",
       "      <td>185</td>\n",
       "      <td>253.8</td>\n",
       "      <td>21.3</td>\n",
       "      <td>30.0</td>\n",
       "      <td>17.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>185</th>\n",
       "      <td>186</td>\n",
       "      <td>NaN</td>\n",
       "      <td>45.1</td>\n",
       "      <td>19.6</td>\n",
       "      <td>22.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>186</th>\n",
       "      <td>187</td>\n",
       "      <td>139.5</td>\n",
       "      <td>2.1</td>\n",
       "      <td>26.6</td>\n",
       "      <td>10.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>187</th>\n",
       "      <td>188</td>\n",
       "      <td>191.1</td>\n",
       "      <td>28.7</td>\n",
       "      <td>18.2</td>\n",
       "      <td>17.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>188</th>\n",
       "      <td>189</td>\n",
       "      <td>286.0</td>\n",
       "      <td>13.9</td>\n",
       "      <td>3.7</td>\n",
       "      <td>15.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>189</th>\n",
       "      <td>190</td>\n",
       "      <td>18.7</td>\n",
       "      <td>12.1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>190</th>\n",
       "      <td>191</td>\n",
       "      <td>39.5</td>\n",
       "      <td>41.1</td>\n",
       "      <td>5.8</td>\n",
       "      <td>10.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>191</th>\n",
       "      <td>192</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.8</td>\n",
       "      <td>6.0</td>\n",
       "      <td>9.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>192</th>\n",
       "      <td>193</td>\n",
       "      <td>17.2</td>\n",
       "      <td>4.1</td>\n",
       "      <td>31.6</td>\n",
       "      <td>5.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193</th>\n",
       "      <td>194</td>\n",
       "      <td>166.8</td>\n",
       "      <td>42.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>19.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>194</th>\n",
       "      <td>195</td>\n",
       "      <td>149.7</td>\n",
       "      <td>35.6</td>\n",
       "      <td>6.0</td>\n",
       "      <td>17.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>195</th>\n",
       "      <td>196</td>\n",
       "      <td>38.2</td>\n",
       "      <td>3.7</td>\n",
       "      <td>13.8</td>\n",
       "      <td>7.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196</th>\n",
       "      <td>197</td>\n",
       "      <td>94.2</td>\n",
       "      <td>4.9</td>\n",
       "      <td>8.1</td>\n",
       "      <td>9.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197</th>\n",
       "      <td>198</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.3</td>\n",
       "      <td>6.4</td>\n",
       "      <td>12.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>198</th>\n",
       "      <td>199</td>\n",
       "      <td>283.6</td>\n",
       "      <td>42.0</td>\n",
       "      <td>66.2</td>\n",
       "      <td>25.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>199</th>\n",
       "      <td>200</td>\n",
       "      <td>232.1</td>\n",
       "      <td>8.6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>200 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Unnamed: 0     TV  Radio  Newspaper  Sales\n",
       "0             1  230.1   37.8       69.2   22.1\n",
       "1             2   44.5   39.3       45.1   10.4\n",
       "2             3   17.2   45.9       69.3    9.3\n",
       "3             4  151.5   41.3       58.5   18.5\n",
       "4             5  180.8   10.8       58.4   12.9\n",
       "5             6    NaN   48.9       75.0    7.2\n",
       "6             7   57.5   32.8       23.5   11.8\n",
       "7             8  120.2   19.6       11.6   13.2\n",
       "8             9    8.6    2.1        1.0    4.8\n",
       "9            10  199.8    2.6        NaN   10.6\n",
       "10           11   66.1    5.8       24.2    8.6\n",
       "11           12    NaN   24.0        4.0   17.4\n",
       "12           13   23.8   35.1       65.9    9.2\n",
       "13           14   97.5    7.6        7.2    9.7\n",
       "14           15  204.1   32.9       46.0   19.0\n",
       "15           16  195.4   47.7       52.9   22.4\n",
       "16           17   67.8   36.6      114.0   12.5\n",
       "17           18    NaN   39.6       55.8   24.4\n",
       "18           19   69.2   20.5       18.3   11.3\n",
       "19           20  147.3   23.9        NaN   14.6\n",
       "20           21  218.4   27.7       53.4   18.0\n",
       "21           22  237.4    5.1       23.5   12.5\n",
       "22           23   13.2   15.9       49.6    5.6\n",
       "23           24    NaN   16.9       26.2   15.5\n",
       "24           25   62.3   12.6       18.3    9.7\n",
       "25           26  262.9    3.5       19.5   12.0\n",
       "26           27  142.9   29.3       12.6   15.0\n",
       "27           28  240.1   16.7       22.9   15.9\n",
       "28           29  248.8   27.1       22.9   18.9\n",
       "29           30    NaN   16.0        NaN   10.5\n",
       "..          ...    ...    ...        ...    ...\n",
       "170         171   50.0   11.6       18.4    8.4\n",
       "171         172  164.5   20.9       47.4   14.5\n",
       "172         173   19.6   20.1       17.0    7.6\n",
       "173         174    NaN    7.1       12.8   11.7\n",
       "174         175  222.4    3.4       13.1   11.5\n",
       "175         176  276.9   48.9       41.8   27.0\n",
       "176         177  248.4   30.2       20.3   20.2\n",
       "177         178  170.2    7.8       35.2   11.7\n",
       "178         179  276.7    2.3       23.7   11.8\n",
       "179         180    NaN   10.0        NaN   12.6\n",
       "180         181  156.6    2.6        8.3   10.5\n",
       "181         182  218.5    5.4       27.4   12.2\n",
       "182         183   56.2    5.7       29.7    8.7\n",
       "183         184  287.6   43.0       71.8   26.2\n",
       "184         185  253.8   21.3       30.0   17.6\n",
       "185         186    NaN   45.1       19.6   22.6\n",
       "186         187  139.5    2.1       26.6   10.3\n",
       "187         188  191.1   28.7       18.2   17.3\n",
       "188         189  286.0   13.9        3.7   15.9\n",
       "189         190   18.7   12.1        NaN    6.7\n",
       "190         191   39.5   41.1        5.8   10.8\n",
       "191         192    NaN   10.8        6.0    9.9\n",
       "192         193   17.2    4.1       31.6    5.9\n",
       "193         194  166.8   42.0        3.6   19.6\n",
       "194         195  149.7   35.6        6.0   17.3\n",
       "195         196   38.2    3.7       13.8    7.6\n",
       "196         197   94.2    4.9        8.1    9.7\n",
       "197         198    NaN    9.3        6.4   12.8\n",
       "198         199  283.6   42.0       66.2   25.5\n",
       "199         200  232.1    8.6        NaN   13.4\n",
       "\n",
       "[200 rows x 5 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
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       "      <th>TV</th>\n",
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       "      <th>6</th>\n",
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       "    <tr>\n",
       "      <th>7</th>\n",
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       "      <td>11.6</td>\n",
       "      <td>13.2</td>\n",
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       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
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       "      <td>1.0</td>\n",
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       "      <th>10</th>\n",
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       "      <th>12</th>\n",
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       "      <th>13</th>\n",
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       "      <td>97.5</td>\n",
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       "      <td>9.7</td>\n",
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       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>15</td>\n",
       "      <td>204.1</td>\n",
       "      <td>32.9</td>\n",
       "      <td>46.0</td>\n",
       "      <td>19.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>16</td>\n",
       "      <td>195.4</td>\n",
       "      <td>47.7</td>\n",
       "      <td>52.9</td>\n",
       "      <td>22.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>17</td>\n",
       "      <td>67.8</td>\n",
       "      <td>36.6</td>\n",
       "      <td>114.0</td>\n",
       "      <td>12.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>19</td>\n",
       "      <td>69.2</td>\n",
       "      <td>20.5</td>\n",
       "      <td>18.3</td>\n",
       "      <td>11.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>21</td>\n",
       "      <td>218.4</td>\n",
       "      <td>27.7</td>\n",
       "      <td>53.4</td>\n",
       "      <td>18.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>22</td>\n",
       "      <td>237.4</td>\n",
       "      <td>5.1</td>\n",
       "      <td>23.5</td>\n",
       "      <td>12.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>23</td>\n",
       "      <td>13.2</td>\n",
       "      <td>15.9</td>\n",
       "      <td>49.6</td>\n",
       "      <td>5.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>25</td>\n",
       "      <td>62.3</td>\n",
       "      <td>12.6</td>\n",
       "      <td>18.3</td>\n",
       "      <td>9.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>26</td>\n",
       "      <td>262.9</td>\n",
       "      <td>3.5</td>\n",
       "      <td>19.5</td>\n",
       "      <td>12.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>27</td>\n",
       "      <td>142.9</td>\n",
       "      <td>29.3</td>\n",
       "      <td>12.6</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>28</td>\n",
       "      <td>240.1</td>\n",
       "      <td>16.7</td>\n",
       "      <td>22.9</td>\n",
       "      <td>15.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>29</td>\n",
       "      <td>248.8</td>\n",
       "      <td>27.1</td>\n",
       "      <td>22.9</td>\n",
       "      <td>18.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>31</td>\n",
       "      <td>292.9</td>\n",
       "      <td>28.3</td>\n",
       "      <td>43.2</td>\n",
       "      <td>21.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>32</td>\n",
       "      <td>112.9</td>\n",
       "      <td>17.4</td>\n",
       "      <td>38.6</td>\n",
       "      <td>11.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>33</td>\n",
       "      <td>97.2</td>\n",
       "      <td>1.5</td>\n",
       "      <td>30.0</td>\n",
       "      <td>9.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>34</td>\n",
       "      <td>265.6</td>\n",
       "      <td>20.0</td>\n",
       "      <td>0.3</td>\n",
       "      <td>17.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>35</td>\n",
       "      <td>95.7</td>\n",
       "      <td>1.4</td>\n",
       "      <td>7.4</td>\n",
       "      <td>9.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>37</td>\n",
       "      <td>266.9</td>\n",
       "      <td>43.8</td>\n",
       "      <td>5.0</td>\n",
       "      <td>25.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>38</td>\n",
       "      <td>74.7</td>\n",
       "      <td>49.4</td>\n",
       "      <td>45.7</td>\n",
       "      <td>14.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>160</th>\n",
       "      <td>161</td>\n",
       "      <td>172.5</td>\n",
       "      <td>18.1</td>\n",
       "      <td>30.7</td>\n",
       "      <td>14.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>162</th>\n",
       "      <td>163</td>\n",
       "      <td>188.4</td>\n",
       "      <td>18.1</td>\n",
       "      <td>25.6</td>\n",
       "      <td>14.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>163</th>\n",
       "      <td>164</td>\n",
       "      <td>163.5</td>\n",
       "      <td>36.8</td>\n",
       "      <td>7.4</td>\n",
       "      <td>18.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>164</th>\n",
       "      <td>165</td>\n",
       "      <td>117.2</td>\n",
       "      <td>14.7</td>\n",
       "      <td>5.4</td>\n",
       "      <td>11.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>165</th>\n",
       "      <td>166</td>\n",
       "      <td>234.5</td>\n",
       "      <td>3.4</td>\n",
       "      <td>84.8</td>\n",
       "      <td>11.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>166</th>\n",
       "      <td>167</td>\n",
       "      <td>17.9</td>\n",
       "      <td>37.6</td>\n",
       "      <td>21.6</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>168</th>\n",
       "      <td>169</td>\n",
       "      <td>215.4</td>\n",
       "      <td>23.6</td>\n",
       "      <td>57.6</td>\n",
       "      <td>17.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>170</th>\n",
       "      <td>171</td>\n",
       "      <td>50.0</td>\n",
       "      <td>11.6</td>\n",
       "      <td>18.4</td>\n",
       "      <td>8.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>171</th>\n",
       "      <td>172</td>\n",
       "      <td>164.5</td>\n",
       "      <td>20.9</td>\n",
       "      <td>47.4</td>\n",
       "      <td>14.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172</th>\n",
       "      <td>173</td>\n",
       "      <td>19.6</td>\n",
       "      <td>20.1</td>\n",
       "      <td>17.0</td>\n",
       "      <td>7.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>174</th>\n",
       "      <td>175</td>\n",
       "      <td>222.4</td>\n",
       "      <td>3.4</td>\n",
       "      <td>13.1</td>\n",
       "      <td>11.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>175</th>\n",
       "      <td>176</td>\n",
       "      <td>276.9</td>\n",
       "      <td>48.9</td>\n",
       "      <td>41.8</td>\n",
       "      <td>27.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>176</th>\n",
       "      <td>177</td>\n",
       "      <td>248.4</td>\n",
       "      <td>30.2</td>\n",
       "      <td>20.3</td>\n",
       "      <td>20.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>177</th>\n",
       "      <td>178</td>\n",
       "      <td>170.2</td>\n",
       "      <td>7.8</td>\n",
       "      <td>35.2</td>\n",
       "      <td>11.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>178</th>\n",
       "      <td>179</td>\n",
       "      <td>276.7</td>\n",
       "      <td>2.3</td>\n",
       "      <td>23.7</td>\n",
       "      <td>11.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180</th>\n",
       "      <td>181</td>\n",
       "      <td>156.6</td>\n",
       "      <td>2.6</td>\n",
       "      <td>8.3</td>\n",
       "      <td>10.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>181</th>\n",
       "      <td>182</td>\n",
       "      <td>218.5</td>\n",
       "      <td>5.4</td>\n",
       "      <td>27.4</td>\n",
       "      <td>12.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>182</th>\n",
       "      <td>183</td>\n",
       "      <td>56.2</td>\n",
       "      <td>5.7</td>\n",
       "      <td>29.7</td>\n",
       "      <td>8.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183</th>\n",
       "      <td>184</td>\n",
       "      <td>287.6</td>\n",
       "      <td>43.0</td>\n",
       "      <td>71.8</td>\n",
       "      <td>26.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>184</th>\n",
       "      <td>185</td>\n",
       "      <td>253.8</td>\n",
       "      <td>21.3</td>\n",
       "      <td>30.0</td>\n",
       "      <td>17.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>186</th>\n",
       "      <td>187</td>\n",
       "      <td>139.5</td>\n",
       "      <td>2.1</td>\n",
       "      <td>26.6</td>\n",
       "      <td>10.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>187</th>\n",
       "      <td>188</td>\n",
       "      <td>191.1</td>\n",
       "      <td>28.7</td>\n",
       "      <td>18.2</td>\n",
       "      <td>17.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>188</th>\n",
       "      <td>189</td>\n",
       "      <td>286.0</td>\n",
       "      <td>13.9</td>\n",
       "      <td>3.7</td>\n",
       "      <td>15.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>190</th>\n",
       "      <td>191</td>\n",
       "      <td>39.5</td>\n",
       "      <td>41.1</td>\n",
       "      <td>5.8</td>\n",
       "      <td>10.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>192</th>\n",
       "      <td>193</td>\n",
       "      <td>17.2</td>\n",
       "      <td>4.1</td>\n",
       "      <td>31.6</td>\n",
       "      <td>5.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193</th>\n",
       "      <td>194</td>\n",
       "      <td>166.8</td>\n",
       "      <td>42.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>19.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>194</th>\n",
       "      <td>195</td>\n",
       "      <td>149.7</td>\n",
       "      <td>35.6</td>\n",
       "      <td>6.0</td>\n",
       "      <td>17.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>195</th>\n",
       "      <td>196</td>\n",
       "      <td>38.2</td>\n",
       "      <td>3.7</td>\n",
       "      <td>13.8</td>\n",
       "      <td>7.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196</th>\n",
       "      <td>197</td>\n",
       "      <td>94.2</td>\n",
       "      <td>4.9</td>\n",
       "      <td>8.1</td>\n",
       "      <td>9.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>198</th>\n",
       "      <td>199</td>\n",
       "      <td>283.6</td>\n",
       "      <td>42.0</td>\n",
       "      <td>66.2</td>\n",
       "      <td>25.5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>153 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Unnamed: 0     TV  Radio  Newspaper  Sales\n",
       "0             1  230.1   37.8       69.2   22.1\n",
       "1             2   44.5   39.3       45.1   10.4\n",
       "2             3   17.2   45.9       69.3    9.3\n",
       "3             4  151.5   41.3       58.5   18.5\n",
       "4             5  180.8   10.8       58.4   12.9\n",
       "6             7   57.5   32.8       23.5   11.8\n",
       "7             8  120.2   19.6       11.6   13.2\n",
       "8             9    8.6    2.1        1.0    4.8\n",
       "10           11   66.1    5.8       24.2    8.6\n",
       "12           13   23.8   35.1       65.9    9.2\n",
       "13           14   97.5    7.6        7.2    9.7\n",
       "14           15  204.1   32.9       46.0   19.0\n",
       "15           16  195.4   47.7       52.9   22.4\n",
       "16           17   67.8   36.6      114.0   12.5\n",
       "18           19   69.2   20.5       18.3   11.3\n",
       "20           21  218.4   27.7       53.4   18.0\n",
       "21           22  237.4    5.1       23.5   12.5\n",
       "22           23   13.2   15.9       49.6    5.6\n",
       "24           25   62.3   12.6       18.3    9.7\n",
       "25           26  262.9    3.5       19.5   12.0\n",
       "26           27  142.9   29.3       12.6   15.0\n",
       "27           28  240.1   16.7       22.9   15.9\n",
       "28           29  248.8   27.1       22.9   18.9\n",
       "30           31  292.9   28.3       43.2   21.4\n",
       "31           32  112.9   17.4       38.6   11.9\n",
       "32           33   97.2    1.5       30.0    9.6\n",
       "33           34  265.6   20.0        0.3   17.4\n",
       "34           35   95.7    1.4        7.4    9.5\n",
       "36           37  266.9   43.8        5.0   25.4\n",
       "37           38   74.7   49.4       45.7   14.7\n",
       "..          ...    ...    ...        ...    ...\n",
       "160         161  172.5   18.1       30.7   14.4\n",
       "162         163  188.4   18.1       25.6   14.9\n",
       "163         164  163.5   36.8        7.4   18.0\n",
       "164         165  117.2   14.7        5.4   11.9\n",
       "165         166  234.5    3.4       84.8   11.9\n",
       "166         167   17.9   37.6       21.6    8.0\n",
       "168         169  215.4   23.6       57.6   17.1\n",
       "170         171   50.0   11.6       18.4    8.4\n",
       "171         172  164.5   20.9       47.4   14.5\n",
       "172         173   19.6   20.1       17.0    7.6\n",
       "174         175  222.4    3.4       13.1   11.5\n",
       "175         176  276.9   48.9       41.8   27.0\n",
       "176         177  248.4   30.2       20.3   20.2\n",
       "177         178  170.2    7.8       35.2   11.7\n",
       "178         179  276.7    2.3       23.7   11.8\n",
       "180         181  156.6    2.6        8.3   10.5\n",
       "181         182  218.5    5.4       27.4   12.2\n",
       "182         183   56.2    5.7       29.7    8.7\n",
       "183         184  287.6   43.0       71.8   26.2\n",
       "184         185  253.8   21.3       30.0   17.6\n",
       "186         187  139.5    2.1       26.6   10.3\n",
       "187         188  191.1   28.7       18.2   17.3\n",
       "188         189  286.0   13.9        3.7   15.9\n",
       "190         191   39.5   41.1        5.8   10.8\n",
       "192         193   17.2    4.1       31.6    5.9\n",
       "193         194  166.8   42.0        3.6   19.6\n",
       "194         195  149.7   35.6        6.0   17.3\n",
       "195         196   38.2    3.7       13.8    7.6\n",
       "196         197   94.2    4.9        8.1    9.7\n",
       "198         199  283.6   42.0       66.2   25.5\n",
       "\n",
       "[153 rows x 5 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#printing df rows that have no NaN values\n",
    "dfn=dfc.dropna()\n",
    "dfn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>TV</th>\n",
       "      <th>Radio</th>\n",
       "      <th>Newspaper</th>\n",
       "      <th>Sales</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>48.9</td>\n",
       "      <td>75.0</td>\n",
       "      <td>7.2</td>\n",
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       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>199.8</td>\n",
       "      <td>2.6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.6</td>\n",
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       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>12</td>\n",
       "      <td>NaN</td>\n",
       "      <td>24.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>17.4</td>\n",
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       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>18</td>\n",
       "      <td>NaN</td>\n",
       "      <td>39.6</td>\n",
       "      <td>55.8</td>\n",
       "      <td>24.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>20</td>\n",
       "      <td>147.3</td>\n",
       "      <td>23.9</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>24</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16.9</td>\n",
       "      <td>26.2</td>\n",
       "      <td>15.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>36</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.1</td>\n",
       "      <td>8.5</td>\n",
       "      <td>12.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>40</td>\n",
       "      <td>228.0</td>\n",
       "      <td>37.7</td>\n",
       "      <td>NaN</td>\n",
       "      <td>21.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>42</td>\n",
       "      <td>NaN</td>\n",
       "      <td>33.4</td>\n",
       "      <td>38.7</td>\n",
       "      <td>17.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>48</td>\n",
       "      <td>NaN</td>\n",
       "      <td>41.5</td>\n",
       "      <td>18.5</td>\n",
       "      <td>23.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>50</td>\n",
       "      <td>66.9</td>\n",
       "      <td>11.7</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>54</td>\n",
       "      <td>NaN</td>\n",
       "      <td>46.2</td>\n",
       "      <td>58.7</td>\n",
       "      <td>21.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>60</td>\n",
       "      <td>NaN</td>\n",
       "      <td>29.5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>66</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.3</td>\n",
       "      <td>0.9</td>\n",
       "      <td>9.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>70</td>\n",
       "      <td>216.8</td>\n",
       "      <td>43.9</td>\n",
       "      <td>NaN</td>\n",
       "      <td>22.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>72</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14.3</td>\n",
       "      <td>31.7</td>\n",
       "      <td>12.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>78</td>\n",
       "      <td>NaN</td>\n",
       "      <td>28.5</td>\n",
       "      <td>14.2</td>\n",
       "      <td>14.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>80</td>\n",
       "      <td>116.0</td>\n",
       "      <td>7.7</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>84</td>\n",
       "      <td>NaN</td>\n",
       "      <td>44.5</td>\n",
       "      <td>35.6</td>\n",
       "      <td>13.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>90</td>\n",
       "      <td>NaN</td>\n",
       "      <td>47.8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>96</td>\n",
       "      <td>NaN</td>\n",
       "      <td>31.6</td>\n",
       "      <td>52.9</td>\n",
       "      <td>16.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>100</td>\n",
       "      <td>135.2</td>\n",
       "      <td>41.7</td>\n",
       "      <td>NaN</td>\n",
       "      <td>17.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101</th>\n",
       "      <td>102</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36.3</td>\n",
       "      <td>100.9</td>\n",
       "      <td>23.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107</th>\n",
       "      <td>108</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.3</td>\n",
       "      <td>23.2</td>\n",
       "      <td>8.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109</th>\n",
       "      <td>110</td>\n",
       "      <td>255.4</td>\n",
       "      <td>26.9</td>\n",
       "      <td>NaN</td>\n",
       "      <td>19.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113</th>\n",
       "      <td>114</td>\n",
       "      <td>NaN</td>\n",
       "      <td>20.6</td>\n",
       "      <td>10.7</td>\n",
       "      <td>15.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119</th>\n",
       "      <td>120</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125</th>\n",
       "      <td>126</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11.8</td>\n",
       "      <td>25.9</td>\n",
       "      <td>10.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>129</th>\n",
       "      <td>130</td>\n",
       "      <td>59.6</td>\n",
       "      <td>12.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>131</th>\n",
       "      <td>132</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.9</td>\n",
       "      <td>43.0</td>\n",
       "      <td>12.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>137</th>\n",
       "      <td>138</td>\n",
       "      <td>NaN</td>\n",
       "      <td>28.9</td>\n",
       "      <td>59.7</td>\n",
       "      <td>20.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>139</th>\n",
       "      <td>140</td>\n",
       "      <td>184.9</td>\n",
       "      <td>43.9</td>\n",
       "      <td>NaN</td>\n",
       "      <td>20.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>143</th>\n",
       "      <td>144</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.7</td>\n",
       "      <td>34.4</td>\n",
       "      <td>10.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149</th>\n",
       "      <td>150</td>\n",
       "      <td>NaN</td>\n",
       "      <td>25.8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>155</th>\n",
       "      <td>156</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11.6</td>\n",
       "      <td>5.7</td>\n",
       "      <td>3.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159</th>\n",
       "      <td>160</td>\n",
       "      <td>131.7</td>\n",
       "      <td>18.4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>161</th>\n",
       "      <td>162</td>\n",
       "      <td>NaN</td>\n",
       "      <td>35.8</td>\n",
       "      <td>49.3</td>\n",
       "      <td>13.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167</th>\n",
       "      <td>168</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.2</td>\n",
       "      <td>19.4</td>\n",
       "      <td>12.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>169</th>\n",
       "      <td>170</td>\n",
       "      <td>284.3</td>\n",
       "      <td>10.6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>173</th>\n",
       "      <td>174</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.1</td>\n",
       "      <td>12.8</td>\n",
       "      <td>11.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>179</th>\n",
       "      <td>180</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>185</th>\n",
       "      <td>186</td>\n",
       "      <td>NaN</td>\n",
       "      <td>45.1</td>\n",
       "      <td>19.6</td>\n",
       "      <td>22.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>189</th>\n",
       "      <td>190</td>\n",
       "      <td>18.7</td>\n",
       "      <td>12.1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>191</th>\n",
       "      <td>192</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.8</td>\n",
       "      <td>6.0</td>\n",
       "      <td>9.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197</th>\n",
       "      <td>198</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.3</td>\n",
       "      <td>6.4</td>\n",
       "      <td>12.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>199</th>\n",
       "      <td>200</td>\n",
       "      <td>232.1</td>\n",
       "      <td>8.6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Unnamed: 0     TV  Radio  Newspaper  Sales\n",
       "5             6    NaN   48.9       75.0    7.2\n",
       "9            10  199.8    2.6        NaN   10.6\n",
       "11           12    NaN   24.0        4.0   17.4\n",
       "17           18    NaN   39.6       55.8   24.4\n",
       "19           20  147.3   23.9        NaN   14.6\n",
       "23           24    NaN   16.9       26.2   15.5\n",
       "29           30    NaN   16.0        NaN   10.5\n",
       "35           36    NaN    4.1        8.5   12.8\n",
       "39           40  228.0   37.7        NaN   21.5\n",
       "41           42    NaN   33.4       38.7   17.1\n",
       "47           48    NaN   41.5       18.5   23.2\n",
       "49           50   66.9   11.7        NaN    9.7\n",
       "53           54    NaN   46.2       58.7   21.2\n",
       "59           60    NaN   29.5        NaN   18.4\n",
       "65           66    NaN    9.3        0.9    9.3\n",
       "69           70  216.8   43.9        NaN   22.3\n",
       "71           72    NaN   14.3       31.7   12.4\n",
       "77           78    NaN   28.5       14.2   14.2\n",
       "79           80  116.0    7.7        NaN   11.0\n",
       "83           84    NaN   44.5       35.6   13.6\n",
       "89           90    NaN   47.8        NaN   16.7\n",
       "95           96    NaN   31.6       52.9   16.9\n",
       "99          100  135.2   41.7        NaN   17.2\n",
       "101         102    NaN   36.3      100.9   23.8\n",
       "107         108    NaN    0.3       23.2    8.7\n",
       "109         110  255.4   26.9        NaN   19.8\n",
       "113         114    NaN   20.6       10.7   15.9\n",
       "119         120    NaN   16.0        NaN    6.6\n",
       "125         126    NaN   11.8       25.9   10.6\n",
       "129         130   59.6   12.0        NaN    9.7\n",
       "131         132    NaN    2.9       43.0   12.7\n",
       "137         138    NaN   28.9       59.7   20.8\n",
       "139         140  184.9   43.9        NaN   20.7\n",
       "143         144    NaN    5.7       34.4   10.4\n",
       "149         150    NaN   25.8        NaN   10.1\n",
       "155         156    NaN   11.6        5.7    3.2\n",
       "159         160  131.7   18.4        NaN   12.9\n",
       "161         162    NaN   35.8       49.3   13.3\n",
       "167         168    NaN    5.2       19.4   12.2\n",
       "169         170  284.3   10.6        NaN   15.0\n",
       "173         174    NaN    7.1       12.8   11.7\n",
       "179         180    NaN   10.0        NaN   12.6\n",
       "185         186    NaN   45.1       19.6   22.6\n",
       "189         190   18.7   12.1        NaN    6.7\n",
       "191         192    NaN   10.8        6.0    9.9\n",
       "197         198    NaN    9.3        6.4   12.8\n",
       "199         200  232.1    8.6        NaN   13.4"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#printing rows with one or more NaN values\n",
    "dfna=dfc[dfc.isna().any(axis=1)]\n",
    "dfna"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>TV</th>\n",
       "      <th>Radio</th>\n",
       "      <th>Newspaper</th>\n",
       "      <th>Sales</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>230.1</td>\n",
       "      <td>37.8</td>\n",
       "      <td>69.2</td>\n",
       "      <td>22.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
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       "      <td>39.3</td>\n",
       "      <td>45.1</td>\n",
       "      <td>10.4</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
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       "      <td>18.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>180.8</td>\n",
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       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>0.0</td>\n",
       "      <td>48.9</td>\n",
       "      <td>75.0</td>\n",
       "      <td>7.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>57.5</td>\n",
       "      <td>32.8</td>\n",
       "      <td>23.5</td>\n",
       "      <td>11.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>120.2</td>\n",
       "      <td>19.6</td>\n",
       "      <td>11.6</td>\n",
       "      <td>13.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>8.6</td>\n",
       "      <td>2.1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>199.8</td>\n",
       "      <td>2.6</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>11</td>\n",
       "      <td>66.1</td>\n",
       "      <td>5.8</td>\n",
       "      <td>24.2</td>\n",
       "      <td>8.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>12</td>\n",
       "      <td>0.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>17.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>13</td>\n",
       "      <td>23.8</td>\n",
       "      <td>35.1</td>\n",
       "      <td>65.9</td>\n",
       "      <td>9.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>14</td>\n",
       "      <td>97.5</td>\n",
       "      <td>7.6</td>\n",
       "      <td>7.2</td>\n",
       "      <td>9.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>15</td>\n",
       "      <td>204.1</td>\n",
       "      <td>32.9</td>\n",
       "      <td>46.0</td>\n",
       "      <td>19.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>16</td>\n",
       "      <td>195.4</td>\n",
       "      <td>47.7</td>\n",
       "      <td>52.9</td>\n",
       "      <td>22.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>17</td>\n",
       "      <td>67.8</td>\n",
       "      <td>36.6</td>\n",
       "      <td>114.0</td>\n",
       "      <td>12.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>18</td>\n",
       "      <td>0.0</td>\n",
       "      <td>39.6</td>\n",
       "      <td>55.8</td>\n",
       "      <td>24.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>19</td>\n",
       "      <td>69.2</td>\n",
       "      <td>20.5</td>\n",
       "      <td>18.3</td>\n",
       "      <td>11.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>20</td>\n",
       "      <td>147.3</td>\n",
       "      <td>23.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>14.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>21</td>\n",
       "      <td>218.4</td>\n",
       "      <td>27.7</td>\n",
       "      <td>53.4</td>\n",
       "      <td>18.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>22</td>\n",
       "      <td>237.4</td>\n",
       "      <td>5.1</td>\n",
       "      <td>23.5</td>\n",
       "      <td>12.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>23</td>\n",
       "      <td>13.2</td>\n",
       "      <td>15.9</td>\n",
       "      <td>49.6</td>\n",
       "      <td>5.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>24</td>\n",
       "      <td>0.0</td>\n",
       "      <td>16.9</td>\n",
       "      <td>26.2</td>\n",
       "      <td>15.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>25</td>\n",
       "      <td>62.3</td>\n",
       "      <td>12.6</td>\n",
       "      <td>18.3</td>\n",
       "      <td>9.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>26</td>\n",
       "      <td>262.9</td>\n",
       "      <td>3.5</td>\n",
       "      <td>19.5</td>\n",
       "      <td>12.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>27</td>\n",
       "      <td>142.9</td>\n",
       "      <td>29.3</td>\n",
       "      <td>12.6</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>28</td>\n",
       "      <td>240.1</td>\n",
       "      <td>16.7</td>\n",
       "      <td>22.9</td>\n",
       "      <td>15.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>29</td>\n",
       "      <td>248.8</td>\n",
       "      <td>27.1</td>\n",
       "      <td>22.9</td>\n",
       "      <td>18.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>30</td>\n",
       "      <td>0.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>170</th>\n",
       "      <td>171</td>\n",
       "      <td>50.0</td>\n",
       "      <td>11.6</td>\n",
       "      <td>18.4</td>\n",
       "      <td>8.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>171</th>\n",
       "      <td>172</td>\n",
       "      <td>164.5</td>\n",
       "      <td>20.9</td>\n",
       "      <td>47.4</td>\n",
       "      <td>14.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172</th>\n",
       "      <td>173</td>\n",
       "      <td>19.6</td>\n",
       "      <td>20.1</td>\n",
       "      <td>17.0</td>\n",
       "      <td>7.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>173</th>\n",
       "      <td>174</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.1</td>\n",
       "      <td>12.8</td>\n",
       "      <td>11.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>174</th>\n",
       "      <td>175</td>\n",
       "      <td>222.4</td>\n",
       "      <td>3.4</td>\n",
       "      <td>13.1</td>\n",
       "      <td>11.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>175</th>\n",
       "      <td>176</td>\n",
       "      <td>276.9</td>\n",
       "      <td>48.9</td>\n",
       "      <td>41.8</td>\n",
       "      <td>27.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>176</th>\n",
       "      <td>177</td>\n",
       "      <td>248.4</td>\n",
       "      <td>30.2</td>\n",
       "      <td>20.3</td>\n",
       "      <td>20.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>177</th>\n",
       "      <td>178</td>\n",
       "      <td>170.2</td>\n",
       "      <td>7.8</td>\n",
       "      <td>35.2</td>\n",
       "      <td>11.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>178</th>\n",
       "      <td>179</td>\n",
       "      <td>276.7</td>\n",
       "      <td>2.3</td>\n",
       "      <td>23.7</td>\n",
       "      <td>11.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>179</th>\n",
       "      <td>180</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180</th>\n",
       "      <td>181</td>\n",
       "      <td>156.6</td>\n",
       "      <td>2.6</td>\n",
       "      <td>8.3</td>\n",
       "      <td>10.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>181</th>\n",
       "      <td>182</td>\n",
       "      <td>218.5</td>\n",
       "      <td>5.4</td>\n",
       "      <td>27.4</td>\n",
       "      <td>12.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>182</th>\n",
       "      <td>183</td>\n",
       "      <td>56.2</td>\n",
       "      <td>5.7</td>\n",
       "      <td>29.7</td>\n",
       "      <td>8.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183</th>\n",
       "      <td>184</td>\n",
       "      <td>287.6</td>\n",
       "      <td>43.0</td>\n",
       "      <td>71.8</td>\n",
       "      <td>26.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>184</th>\n",
       "      <td>185</td>\n",
       "      <td>253.8</td>\n",
       "      <td>21.3</td>\n",
       "      <td>30.0</td>\n",
       "      <td>17.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>185</th>\n",
       "      <td>186</td>\n",
       "      <td>0.0</td>\n",
       "      <td>45.1</td>\n",
       "      <td>19.6</td>\n",
       "      <td>22.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>186</th>\n",
       "      <td>187</td>\n",
       "      <td>139.5</td>\n",
       "      <td>2.1</td>\n",
       "      <td>26.6</td>\n",
       "      <td>10.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>187</th>\n",
       "      <td>188</td>\n",
       "      <td>191.1</td>\n",
       "      <td>28.7</td>\n",
       "      <td>18.2</td>\n",
       "      <td>17.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>188</th>\n",
       "      <td>189</td>\n",
       "      <td>286.0</td>\n",
       "      <td>13.9</td>\n",
       "      <td>3.7</td>\n",
       "      <td>15.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>189</th>\n",
       "      <td>190</td>\n",
       "      <td>18.7</td>\n",
       "      <td>12.1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>190</th>\n",
       "      <td>191</td>\n",
       "      <td>39.5</td>\n",
       "      <td>41.1</td>\n",
       "      <td>5.8</td>\n",
       "      <td>10.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>191</th>\n",
       "      <td>192</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.8</td>\n",
       "      <td>6.0</td>\n",
       "      <td>9.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>192</th>\n",
       "      <td>193</td>\n",
       "      <td>17.2</td>\n",
       "      <td>4.1</td>\n",
       "      <td>31.6</td>\n",
       "      <td>5.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193</th>\n",
       "      <td>194</td>\n",
       "      <td>166.8</td>\n",
       "      <td>42.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>19.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>194</th>\n",
       "      <td>195</td>\n",
       "      <td>149.7</td>\n",
       "      <td>35.6</td>\n",
       "      <td>6.0</td>\n",
       "      <td>17.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>195</th>\n",
       "      <td>196</td>\n",
       "      <td>38.2</td>\n",
       "      <td>3.7</td>\n",
       "      <td>13.8</td>\n",
       "      <td>7.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196</th>\n",
       "      <td>197</td>\n",
       "      <td>94.2</td>\n",
       "      <td>4.9</td>\n",
       "      <td>8.1</td>\n",
       "      <td>9.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197</th>\n",
       "      <td>198</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.3</td>\n",
       "      <td>6.4</td>\n",
       "      <td>12.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>198</th>\n",
       "      <td>199</td>\n",
       "      <td>283.6</td>\n",
       "      <td>42.0</td>\n",
       "      <td>66.2</td>\n",
       "      <td>25.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>199</th>\n",
       "      <td>200</td>\n",
       "      <td>232.1</td>\n",
       "      <td>8.6</td>\n",
       "      <td>0.0</td>\n",
       "      <td>13.4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>200 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Unnamed: 0     TV  Radio  Newspaper  Sales\n",
       "0             1  230.1   37.8       69.2   22.1\n",
       "1             2   44.5   39.3       45.1   10.4\n",
       "2             3   17.2   45.9       69.3    9.3\n",
       "3             4  151.5   41.3       58.5   18.5\n",
       "4             5  180.8   10.8       58.4   12.9\n",
       "5             6    0.0   48.9       75.0    7.2\n",
       "6             7   57.5   32.8       23.5   11.8\n",
       "7             8  120.2   19.6       11.6   13.2\n",
       "8             9    8.6    2.1        1.0    4.8\n",
       "9            10  199.8    2.6        0.0   10.6\n",
       "10           11   66.1    5.8       24.2    8.6\n",
       "11           12    0.0   24.0        4.0   17.4\n",
       "12           13   23.8   35.1       65.9    9.2\n",
       "13           14   97.5    7.6        7.2    9.7\n",
       "14           15  204.1   32.9       46.0   19.0\n",
       "15           16  195.4   47.7       52.9   22.4\n",
       "16           17   67.8   36.6      114.0   12.5\n",
       "17           18    0.0   39.6       55.8   24.4\n",
       "18           19   69.2   20.5       18.3   11.3\n",
       "19           20  147.3   23.9        0.0   14.6\n",
       "20           21  218.4   27.7       53.4   18.0\n",
       "21           22  237.4    5.1       23.5   12.5\n",
       "22           23   13.2   15.9       49.6    5.6\n",
       "23           24    0.0   16.9       26.2   15.5\n",
       "24           25   62.3   12.6       18.3    9.7\n",
       "25           26  262.9    3.5       19.5   12.0\n",
       "26           27  142.9   29.3       12.6   15.0\n",
       "27           28  240.1   16.7       22.9   15.9\n",
       "28           29  248.8   27.1       22.9   18.9\n",
       "29           30    0.0   16.0        0.0   10.5\n",
       "..          ...    ...    ...        ...    ...\n",
       "170         171   50.0   11.6       18.4    8.4\n",
       "171         172  164.5   20.9       47.4   14.5\n",
       "172         173   19.6   20.1       17.0    7.6\n",
       "173         174    0.0    7.1       12.8   11.7\n",
       "174         175  222.4    3.4       13.1   11.5\n",
       "175         176  276.9   48.9       41.8   27.0\n",
       "176         177  248.4   30.2       20.3   20.2\n",
       "177         178  170.2    7.8       35.2   11.7\n",
       "178         179  276.7    2.3       23.7   11.8\n",
       "179         180    0.0   10.0        0.0   12.6\n",
       "180         181  156.6    2.6        8.3   10.5\n",
       "181         182  218.5    5.4       27.4   12.2\n",
       "182         183   56.2    5.7       29.7    8.7\n",
       "183         184  287.6   43.0       71.8   26.2\n",
       "184         185  253.8   21.3       30.0   17.6\n",
       "185         186    0.0   45.1       19.6   22.6\n",
       "186         187  139.5    2.1       26.6   10.3\n",
       "187         188  191.1   28.7       18.2   17.3\n",
       "188         189  286.0   13.9        3.7   15.9\n",
       "189         190   18.7   12.1        0.0    6.7\n",
       "190         191   39.5   41.1        5.8   10.8\n",
       "191         192    0.0   10.8        6.0    9.9\n",
       "192         193   17.2    4.1       31.6    5.9\n",
       "193         194  166.8   42.0        3.6   19.6\n",
       "194         195  149.7   35.6        6.0   17.3\n",
       "195         196   38.2    3.7       13.8    7.6\n",
       "196         197   94.2    4.9        8.1    9.7\n",
       "197         198    0.0    9.3        6.4   12.8\n",
       "198         199  283.6   42.0       66.2   25.5\n",
       "199         200  232.1    8.6        0.0   13.4\n",
       "\n",
       "[200 rows x 5 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#8\n",
    "#Filling missing values with 0\n",
    "df2=dfc.fillna(0)\n",
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>TV</th>\n",
       "      <th>Radio</th>\n",
       "      <th>Newspaper</th>\n",
       "      <th>Sales</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>230.100000</td>\n",
       "      <td>37.8</td>\n",
       "      <td>69.200000</td>\n",
       "      <td>22.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>44.500000</td>\n",
       "      <td>39.3</td>\n",
       "      <td>45.100000</td>\n",
       "      <td>10.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>17.200000</td>\n",
       "      <td>45.9</td>\n",
       "      <td>69.300000</td>\n",
       "      <td>9.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>151.500000</td>\n",
       "      <td>41.3</td>\n",
       "      <td>58.500000</td>\n",
       "      <td>18.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>180.800000</td>\n",
       "      <td>10.8</td>\n",
       "      <td>58.400000</td>\n",
       "      <td>12.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>146.010778</td>\n",
       "      <td>48.9</td>\n",
       "      <td>75.000000</td>\n",
       "      <td>7.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>57.500000</td>\n",
       "      <td>32.8</td>\n",
       "      <td>23.500000</td>\n",
       "      <td>11.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>120.200000</td>\n",
       "      <td>19.6</td>\n",
       "      <td>11.600000</td>\n",
       "      <td>13.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>8.600000</td>\n",
       "      <td>2.1</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>4.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>199.800000</td>\n",
       "      <td>2.6</td>\n",
       "      <td>31.222778</td>\n",
       "      <td>10.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>11</td>\n",
       "      <td>66.100000</td>\n",
       "      <td>5.8</td>\n",
       "      <td>24.200000</td>\n",
       "      <td>8.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>12</td>\n",
       "      <td>146.010778</td>\n",
       "      <td>24.0</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>17.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>13</td>\n",
       "      <td>23.800000</td>\n",
       "      <td>35.1</td>\n",
       "      <td>65.900000</td>\n",
       "      <td>9.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>14</td>\n",
       "      <td>97.500000</td>\n",
       "      <td>7.6</td>\n",
       "      <td>7.200000</td>\n",
       "      <td>9.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>15</td>\n",
       "      <td>204.100000</td>\n",
       "      <td>32.9</td>\n",
       "      <td>46.000000</td>\n",
       "      <td>19.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>16</td>\n",
       "      <td>195.400000</td>\n",
       "      <td>47.7</td>\n",
       "      <td>52.900000</td>\n",
       "      <td>22.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>17</td>\n",
       "      <td>67.800000</td>\n",
       "      <td>36.6</td>\n",
       "      <td>114.000000</td>\n",
       "      <td>12.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>18</td>\n",
       "      <td>146.010778</td>\n",
       "      <td>39.6</td>\n",
       "      <td>55.800000</td>\n",
       "      <td>24.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>19</td>\n",
       "      <td>69.200000</td>\n",
       "      <td>20.5</td>\n",
       "      <td>18.300000</td>\n",
       "      <td>11.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>20</td>\n",
       "      <td>147.300000</td>\n",
       "      <td>23.9</td>\n",
       "      <td>31.222778</td>\n",
       "      <td>14.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>21</td>\n",
       "      <td>218.400000</td>\n",
       "      <td>27.7</td>\n",
       "      <td>53.400000</td>\n",
       "      <td>18.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>22</td>\n",
       "      <td>237.400000</td>\n",
       "      <td>5.1</td>\n",
       "      <td>23.500000</td>\n",
       "      <td>12.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>23</td>\n",
       "      <td>13.200000</td>\n",
       "      <td>15.9</td>\n",
       "      <td>49.600000</td>\n",
       "      <td>5.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>24</td>\n",
       "      <td>146.010778</td>\n",
       "      <td>16.9</td>\n",
       "      <td>26.200000</td>\n",
       "      <td>15.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>25</td>\n",
       "      <td>62.300000</td>\n",
       "      <td>12.6</td>\n",
       "      <td>18.300000</td>\n",
       "      <td>9.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>26</td>\n",
       "      <td>262.900000</td>\n",
       "      <td>3.5</td>\n",
       "      <td>19.500000</td>\n",
       "      <td>12.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>27</td>\n",
       "      <td>142.900000</td>\n",
       "      <td>29.3</td>\n",
       "      <td>12.600000</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>28</td>\n",
       "      <td>240.100000</td>\n",
       "      <td>16.7</td>\n",
       "      <td>22.900000</td>\n",
       "      <td>15.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>29</td>\n",
       "      <td>248.800000</td>\n",
       "      <td>27.1</td>\n",
       "      <td>22.900000</td>\n",
       "      <td>18.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>30</td>\n",
       "      <td>146.010778</td>\n",
       "      <td>16.0</td>\n",
       "      <td>31.222778</td>\n",
       "      <td>10.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>170</th>\n",
       "      <td>171</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>11.6</td>\n",
       "      <td>18.400000</td>\n",
       "      <td>8.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>171</th>\n",
       "      <td>172</td>\n",
       "      <td>164.500000</td>\n",
       "      <td>20.9</td>\n",
       "      <td>47.400000</td>\n",
       "      <td>14.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172</th>\n",
       "      <td>173</td>\n",
       "      <td>19.600000</td>\n",
       "      <td>20.1</td>\n",
       "      <td>17.000000</td>\n",
       "      <td>7.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>173</th>\n",
       "      <td>174</td>\n",
       "      <td>146.010778</td>\n",
       "      <td>7.1</td>\n",
       "      <td>12.800000</td>\n",
       "      <td>11.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>174</th>\n",
       "      <td>175</td>\n",
       "      <td>222.400000</td>\n",
       "      <td>3.4</td>\n",
       "      <td>13.100000</td>\n",
       "      <td>11.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>175</th>\n",
       "      <td>176</td>\n",
       "      <td>276.900000</td>\n",
       "      <td>48.9</td>\n",
       "      <td>41.800000</td>\n",
       "      <td>27.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>176</th>\n",
       "      <td>177</td>\n",
       "      <td>248.400000</td>\n",
       "      <td>30.2</td>\n",
       "      <td>20.300000</td>\n",
       "      <td>20.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>177</th>\n",
       "      <td>178</td>\n",
       "      <td>170.200000</td>\n",
       "      <td>7.8</td>\n",
       "      <td>35.200000</td>\n",
       "      <td>11.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>178</th>\n",
       "      <td>179</td>\n",
       "      <td>276.700000</td>\n",
       "      <td>2.3</td>\n",
       "      <td>23.700000</td>\n",
       "      <td>11.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>179</th>\n",
       "      <td>180</td>\n",
       "      <td>146.010778</td>\n",
       "      <td>10.0</td>\n",
       "      <td>31.222778</td>\n",
       "      <td>12.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180</th>\n",
       "      <td>181</td>\n",
       "      <td>156.600000</td>\n",
       "      <td>2.6</td>\n",
       "      <td>8.300000</td>\n",
       "      <td>10.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>181</th>\n",
       "      <td>182</td>\n",
       "      <td>218.500000</td>\n",
       "      <td>5.4</td>\n",
       "      <td>27.400000</td>\n",
       "      <td>12.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>182</th>\n",
       "      <td>183</td>\n",
       "      <td>56.200000</td>\n",
       "      <td>5.7</td>\n",
       "      <td>29.700000</td>\n",
       "      <td>8.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183</th>\n",
       "      <td>184</td>\n",
       "      <td>287.600000</td>\n",
       "      <td>43.0</td>\n",
       "      <td>71.800000</td>\n",
       "      <td>26.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>184</th>\n",
       "      <td>185</td>\n",
       "      <td>253.800000</td>\n",
       "      <td>21.3</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>17.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>185</th>\n",
       "      <td>186</td>\n",
       "      <td>146.010778</td>\n",
       "      <td>45.1</td>\n",
       "      <td>19.600000</td>\n",
       "      <td>22.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>186</th>\n",
       "      <td>187</td>\n",
       "      <td>139.500000</td>\n",
       "      <td>2.1</td>\n",
       "      <td>26.600000</td>\n",
       "      <td>10.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>187</th>\n",
       "      <td>188</td>\n",
       "      <td>191.100000</td>\n",
       "      <td>28.7</td>\n",
       "      <td>18.200000</td>\n",
       "      <td>17.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>188</th>\n",
       "      <td>189</td>\n",
       "      <td>286.000000</td>\n",
       "      <td>13.9</td>\n",
       "      <td>3.700000</td>\n",
       "      <td>15.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>189</th>\n",
       "      <td>190</td>\n",
       "      <td>18.700000</td>\n",
       "      <td>12.1</td>\n",
       "      <td>31.222778</td>\n",
       "      <td>6.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>190</th>\n",
       "      <td>191</td>\n",
       "      <td>39.500000</td>\n",
       "      <td>41.1</td>\n",
       "      <td>5.800000</td>\n",
       "      <td>10.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>191</th>\n",
       "      <td>192</td>\n",
       "      <td>146.010778</td>\n",
       "      <td>10.8</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>9.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>192</th>\n",
       "      <td>193</td>\n",
       "      <td>17.200000</td>\n",
       "      <td>4.1</td>\n",
       "      <td>31.600000</td>\n",
       "      <td>5.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193</th>\n",
       "      <td>194</td>\n",
       "      <td>166.800000</td>\n",
       "      <td>42.0</td>\n",
       "      <td>3.600000</td>\n",
       "      <td>19.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>194</th>\n",
       "      <td>195</td>\n",
       "      <td>149.700000</td>\n",
       "      <td>35.6</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>17.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>195</th>\n",
       "      <td>196</td>\n",
       "      <td>38.200000</td>\n",
       "      <td>3.7</td>\n",
       "      <td>13.800000</td>\n",
       "      <td>7.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196</th>\n",
       "      <td>197</td>\n",
       "      <td>94.200000</td>\n",
       "      <td>4.9</td>\n",
       "      <td>8.100000</td>\n",
       "      <td>9.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197</th>\n",
       "      <td>198</td>\n",
       "      <td>146.010778</td>\n",
       "      <td>9.3</td>\n",
       "      <td>6.400000</td>\n",
       "      <td>12.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>198</th>\n",
       "      <td>199</td>\n",
       "      <td>283.600000</td>\n",
       "      <td>42.0</td>\n",
       "      <td>66.200000</td>\n",
       "      <td>25.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>199</th>\n",
       "      <td>200</td>\n",
       "      <td>232.100000</td>\n",
       "      <td>8.6</td>\n",
       "      <td>31.222778</td>\n",
       "      <td>13.4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>200 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Unnamed: 0          TV  Radio   Newspaper  Sales\n",
       "0             1  230.100000   37.8   69.200000   22.1\n",
       "1             2   44.500000   39.3   45.100000   10.4\n",
       "2             3   17.200000   45.9   69.300000    9.3\n",
       "3             4  151.500000   41.3   58.500000   18.5\n",
       "4             5  180.800000   10.8   58.400000   12.9\n",
       "5             6  146.010778   48.9   75.000000    7.2\n",
       "6             7   57.500000   32.8   23.500000   11.8\n",
       "7             8  120.200000   19.6   11.600000   13.2\n",
       "8             9    8.600000    2.1    1.000000    4.8\n",
       "9            10  199.800000    2.6   31.222778   10.6\n",
       "10           11   66.100000    5.8   24.200000    8.6\n",
       "11           12  146.010778   24.0    4.000000   17.4\n",
       "12           13   23.800000   35.1   65.900000    9.2\n",
       "13           14   97.500000    7.6    7.200000    9.7\n",
       "14           15  204.100000   32.9   46.000000   19.0\n",
       "15           16  195.400000   47.7   52.900000   22.4\n",
       "16           17   67.800000   36.6  114.000000   12.5\n",
       "17           18  146.010778   39.6   55.800000   24.4\n",
       "18           19   69.200000   20.5   18.300000   11.3\n",
       "19           20  147.300000   23.9   31.222778   14.6\n",
       "20           21  218.400000   27.7   53.400000   18.0\n",
       "21           22  237.400000    5.1   23.500000   12.5\n",
       "22           23   13.200000   15.9   49.600000    5.6\n",
       "23           24  146.010778   16.9   26.200000   15.5\n",
       "24           25   62.300000   12.6   18.300000    9.7\n",
       "25           26  262.900000    3.5   19.500000   12.0\n",
       "26           27  142.900000   29.3   12.600000   15.0\n",
       "27           28  240.100000   16.7   22.900000   15.9\n",
       "28           29  248.800000   27.1   22.900000   18.9\n",
       "29           30  146.010778   16.0   31.222778   10.5\n",
       "..          ...         ...    ...         ...    ...\n",
       "170         171   50.000000   11.6   18.400000    8.4\n",
       "171         172  164.500000   20.9   47.400000   14.5\n",
       "172         173   19.600000   20.1   17.000000    7.6\n",
       "173         174  146.010778    7.1   12.800000   11.7\n",
       "174         175  222.400000    3.4   13.100000   11.5\n",
       "175         176  276.900000   48.9   41.800000   27.0\n",
       "176         177  248.400000   30.2   20.300000   20.2\n",
       "177         178  170.200000    7.8   35.200000   11.7\n",
       "178         179  276.700000    2.3   23.700000   11.8\n",
       "179         180  146.010778   10.0   31.222778   12.6\n",
       "180         181  156.600000    2.6    8.300000   10.5\n",
       "181         182  218.500000    5.4   27.400000   12.2\n",
       "182         183   56.200000    5.7   29.700000    8.7\n",
       "183         184  287.600000   43.0   71.800000   26.2\n",
       "184         185  253.800000   21.3   30.000000   17.6\n",
       "185         186  146.010778   45.1   19.600000   22.6\n",
       "186         187  139.500000    2.1   26.600000   10.3\n",
       "187         188  191.100000   28.7   18.200000   17.3\n",
       "188         189  286.000000   13.9    3.700000   15.9\n",
       "189         190   18.700000   12.1   31.222778    6.7\n",
       "190         191   39.500000   41.1    5.800000   10.8\n",
       "191         192  146.010778   10.8    6.000000    9.9\n",
       "192         193   17.200000    4.1   31.600000    5.9\n",
       "193         194  166.800000   42.0    3.600000   19.6\n",
       "194         195  149.700000   35.6    6.000000   17.3\n",
       "195         196   38.200000    3.7   13.800000    7.6\n",
       "196         197   94.200000    4.9    8.100000    9.7\n",
       "197         198  146.010778    9.3    6.400000   12.8\n",
       "198         199  283.600000   42.0   66.200000   25.5\n",
       "199         200  232.100000    8.6   31.222778   13.4\n",
       "\n",
       "[200 rows x 5 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Filling missing values with avg of column\n",
    "df3=dfc.apply(lambda x: x.fillna(x.mean()),axis=0)\n",
    "df3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>TV</th>\n",
       "      <th>Radio</th>\n",
       "      <th>Newspaper</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>230.1</td>\n",
       "      <td>37.8</td>\n",
       "      <td>69.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>44.5</td>\n",
       "      <td>39.3</td>\n",
       "      <td>45.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>17.2</td>\n",
       "      <td>45.9</td>\n",
       "      <td>69.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>151.5</td>\n",
       "      <td>41.3</td>\n",
       "      <td>58.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>180.8</td>\n",
       "      <td>10.8</td>\n",
       "      <td>58.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>8.7</td>\n",
       "      <td>48.9</td>\n",
       "      <td>75.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>57.5</td>\n",
       "      <td>32.8</td>\n",
       "      <td>23.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>120.2</td>\n",
       "      <td>19.6</td>\n",
       "      <td>11.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>8.6</td>\n",
       "      <td>2.1</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>199.8</td>\n",
       "      <td>2.6</td>\n",
       "      <td>21.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>66.1</td>\n",
       "      <td>5.8</td>\n",
       "      <td>24.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>214.7</td>\n",
       "      <td>24.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>23.8</td>\n",
       "      <td>35.1</td>\n",
       "      <td>65.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>97.5</td>\n",
       "      <td>7.6</td>\n",
       "      <td>7.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>204.1</td>\n",
       "      <td>32.9</td>\n",
       "      <td>46.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>195.4</td>\n",
       "      <td>47.7</td>\n",
       "      <td>52.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>67.8</td>\n",
       "      <td>36.6</td>\n",
       "      <td>114.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>281.4</td>\n",
       "      <td>39.6</td>\n",
       "      <td>55.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>69.2</td>\n",
       "      <td>20.5</td>\n",
       "      <td>18.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>147.3</td>\n",
       "      <td>23.9</td>\n",
       "      <td>19.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>218.4</td>\n",
       "      <td>27.7</td>\n",
       "      <td>53.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>237.4</td>\n",
       "      <td>5.1</td>\n",
       "      <td>23.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>13.2</td>\n",
       "      <td>15.9</td>\n",
       "      <td>49.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>228.3</td>\n",
       "      <td>16.9</td>\n",
       "      <td>26.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>62.3</td>\n",
       "      <td>12.6</td>\n",
       "      <td>18.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>262.9</td>\n",
       "      <td>3.5</td>\n",
       "      <td>19.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>142.9</td>\n",
       "      <td>29.3</td>\n",
       "      <td>12.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>240.1</td>\n",
       "      <td>16.7</td>\n",
       "      <td>22.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>248.8</td>\n",
       "      <td>27.1</td>\n",
       "      <td>22.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>70.6</td>\n",
       "      <td>16.0</td>\n",
       "      <td>40.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>170</th>\n",
       "      <td>50.0</td>\n",
       "      <td>11.6</td>\n",
       "      <td>18.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>171</th>\n",
       "      <td>164.5</td>\n",
       "      <td>20.9</td>\n",
       "      <td>47.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172</th>\n",
       "      <td>19.6</td>\n",
       "      <td>20.1</td>\n",
       "      <td>17.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>173</th>\n",
       "      <td>168.4</td>\n",
       "      <td>7.1</td>\n",
       "      <td>12.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>174</th>\n",
       "      <td>222.4</td>\n",
       "      <td>3.4</td>\n",
       "      <td>13.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>175</th>\n",
       "      <td>276.9</td>\n",
       "      <td>48.9</td>\n",
       "      <td>41.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>176</th>\n",
       "      <td>248.4</td>\n",
       "      <td>30.2</td>\n",
       "      <td>20.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>177</th>\n",
       "      <td>170.2</td>\n",
       "      <td>7.8</td>\n",
       "      <td>35.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>178</th>\n",
       "      <td>276.7</td>\n",
       "      <td>2.3</td>\n",
       "      <td>23.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>179</th>\n",
       "      <td>165.6</td>\n",
       "      <td>10.0</td>\n",
       "      <td>17.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180</th>\n",
       "      <td>156.6</td>\n",
       "      <td>2.6</td>\n",
       "      <td>8.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>181</th>\n",
       "      <td>218.5</td>\n",
       "      <td>5.4</td>\n",
       "      <td>27.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>182</th>\n",
       "      <td>56.2</td>\n",
       "      <td>5.7</td>\n",
       "      <td>29.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183</th>\n",
       "      <td>287.6</td>\n",
       "      <td>43.0</td>\n",
       "      <td>71.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>184</th>\n",
       "      <td>253.8</td>\n",
       "      <td>21.3</td>\n",
       "      <td>30.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>185</th>\n",
       "      <td>205.0</td>\n",
       "      <td>45.1</td>\n",
       "      <td>19.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>186</th>\n",
       "      <td>139.5</td>\n",
       "      <td>2.1</td>\n",
       "      <td>26.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>187</th>\n",
       "      <td>191.1</td>\n",
       "      <td>28.7</td>\n",
       "      <td>18.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>188</th>\n",
       "      <td>286.0</td>\n",
       "      <td>13.9</td>\n",
       "      <td>3.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>189</th>\n",
       "      <td>18.7</td>\n",
       "      <td>12.1</td>\n",
       "      <td>23.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>190</th>\n",
       "      <td>39.5</td>\n",
       "      <td>41.1</td>\n",
       "      <td>5.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>191</th>\n",
       "      <td>75.5</td>\n",
       "      <td>10.8</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>192</th>\n",
       "      <td>17.2</td>\n",
       "      <td>4.1</td>\n",
       "      <td>31.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193</th>\n",
       "      <td>166.8</td>\n",
       "      <td>42.0</td>\n",
       "      <td>3.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>194</th>\n",
       "      <td>149.7</td>\n",
       "      <td>35.6</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>195</th>\n",
       "      <td>38.2</td>\n",
       "      <td>3.7</td>\n",
       "      <td>13.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196</th>\n",
       "      <td>94.2</td>\n",
       "      <td>4.9</td>\n",
       "      <td>8.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197</th>\n",
       "      <td>177.0</td>\n",
       "      <td>9.3</td>\n",
       "      <td>6.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>198</th>\n",
       "      <td>283.6</td>\n",
       "      <td>42.0</td>\n",
       "      <td>66.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>199</th>\n",
       "      <td>232.1</td>\n",
       "      <td>8.6</td>\n",
       "      <td>8.7</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>200 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        TV  Radio  Newspaper\n",
       "0    230.1   37.8       69.2\n",
       "1     44.5   39.3       45.1\n",
       "2     17.2   45.9       69.3\n",
       "3    151.5   41.3       58.5\n",
       "4    180.8   10.8       58.4\n",
       "5      8.7   48.9       75.0\n",
       "6     57.5   32.8       23.5\n",
       "7    120.2   19.6       11.6\n",
       "8      8.6    2.1        1.0\n",
       "9    199.8    2.6       21.2\n",
       "10    66.1    5.8       24.2\n",
       "11   214.7   24.0        4.0\n",
       "12    23.8   35.1       65.9\n",
       "13    97.5    7.6        7.2\n",
       "14   204.1   32.9       46.0\n",
       "15   195.4   47.7       52.9\n",
       "16    67.8   36.6      114.0\n",
       "17   281.4   39.6       55.8\n",
       "18    69.2   20.5       18.3\n",
       "19   147.3   23.9       19.1\n",
       "20   218.4   27.7       53.4\n",
       "21   237.4    5.1       23.5\n",
       "22    13.2   15.9       49.6\n",
       "23   228.3   16.9       26.2\n",
       "24    62.3   12.6       18.3\n",
       "25   262.9    3.5       19.5\n",
       "26   142.9   29.3       12.6\n",
       "27   240.1   16.7       22.9\n",
       "28   248.8   27.1       22.9\n",
       "29    70.6   16.0       40.8\n",
       "..     ...    ...        ...\n",
       "170   50.0   11.6       18.4\n",
       "171  164.5   20.9       47.4\n",
       "172   19.6   20.1       17.0\n",
       "173  168.4    7.1       12.8\n",
       "174  222.4    3.4       13.1\n",
       "175  276.9   48.9       41.8\n",
       "176  248.4   30.2       20.3\n",
       "177  170.2    7.8       35.2\n",
       "178  276.7    2.3       23.7\n",
       "179  165.6   10.0       17.6\n",
       "180  156.6    2.6        8.3\n",
       "181  218.5    5.4       27.4\n",
       "182   56.2    5.7       29.7\n",
       "183  287.6   43.0       71.8\n",
       "184  253.8   21.3       30.0\n",
       "185  205.0   45.1       19.6\n",
       "186  139.5    2.1       26.6\n",
       "187  191.1   28.7       18.2\n",
       "188  286.0   13.9        3.7\n",
       "189   18.7   12.1       23.4\n",
       "190   39.5   41.1        5.8\n",
       "191   75.5   10.8        6.0\n",
       "192   17.2    4.1       31.6\n",
       "193  166.8   42.0        3.6\n",
       "194  149.7   35.6        6.0\n",
       "195   38.2    3.7       13.8\n",
       "196   94.2    4.9        8.1\n",
       "197  177.0    9.3        6.4\n",
       "198  283.6   42.0       66.2\n",
       "199  232.1    8.6        8.7\n",
       "\n",
       "[200 rows x 3 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.drop('Unnamed: 0',axis=1,inplace=True)\n",
    "df4=pd.DataFrame(columns=['TV','Radio','Newspaper'])\n",
    "df4['TV']=df['TV']\n",
    "df4['Radio']=df['Radio']\n",
    "df4['Newspaper']=df['Newspaper']\n",
    "df4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn import preprocessing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <tbody>\n",
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       "      <th>1</th>\n",
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       "      <td>0.925403</td>\n",
       "      <td>0.606860</td>\n",
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       "      <th>3</th>\n",
       "      <td>0.509976</td>\n",
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       "      <td>0.217742</td>\n",
       "      <td>0.510994</td>\n",
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       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.027054</td>\n",
       "      <td>0.985887</td>\n",
       "      <td>0.656992</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.192087</td>\n",
       "      <td>0.661290</td>\n",
       "      <td>0.204046</td>\n",
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       "      <th>7</th>\n",
       "      <td>0.404126</td>\n",
       "      <td>0.395161</td>\n",
       "      <td>0.099384</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.026716</td>\n",
       "      <td>0.042339</td>\n",
       "      <td>0.006157</td>\n",
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       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.673318</td>\n",
       "      <td>0.052419</td>\n",
       "      <td>0.183817</td>\n",
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       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0.221170</td>\n",
       "      <td>0.116935</td>\n",
       "      <td>0.210202</td>\n",
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       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0.723706</td>\n",
       "      <td>0.483871</td>\n",
       "      <td>0.032542</td>\n",
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       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0.078120</td>\n",
       "      <td>0.707661</td>\n",
       "      <td>0.576957</td>\n",
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       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>0.327359</td>\n",
       "      <td>0.153226</td>\n",
       "      <td>0.060686</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>0.687859</td>\n",
       "      <td>0.663306</td>\n",
       "      <td>0.401935</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>0.658438</td>\n",
       "      <td>0.961694</td>\n",
       "      <td>0.462621</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>0.226919</td>\n",
       "      <td>0.737903</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>0.949273</td>\n",
       "      <td>0.798387</td>\n",
       "      <td>0.488127</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>0.231654</td>\n",
       "      <td>0.413306</td>\n",
       "      <td>0.158311</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>0.495773</td>\n",
       "      <td>0.481855</td>\n",
       "      <td>0.165347</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>0.736219</td>\n",
       "      <td>0.558468</td>\n",
       "      <td>0.467018</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>0.800473</td>\n",
       "      <td>0.102823</td>\n",
       "      <td>0.204046</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>0.042273</td>\n",
       "      <td>0.320565</td>\n",
       "      <td>0.433597</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>0.769699</td>\n",
       "      <td>0.340726</td>\n",
       "      <td>0.227792</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>0.208319</td>\n",
       "      <td>0.254032</td>\n",
       "      <td>0.158311</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>0.886710</td>\n",
       "      <td>0.070565</td>\n",
       "      <td>0.168865</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>0.480893</td>\n",
       "      <td>0.590726</td>\n",
       "      <td>0.108179</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>0.809604</td>\n",
       "      <td>0.336694</td>\n",
       "      <td>0.198769</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>0.839026</td>\n",
       "      <td>0.546371</td>\n",
       "      <td>0.198769</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>0.236388</td>\n",
       "      <td>0.322581</td>\n",
       "      <td>0.356201</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>170</th>\n",
       "      <td>0.166723</td>\n",
       "      <td>0.233871</td>\n",
       "      <td>0.159191</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>171</th>\n",
       "      <td>0.553940</td>\n",
       "      <td>0.421371</td>\n",
       "      <td>0.414248</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172</th>\n",
       "      <td>0.063916</td>\n",
       "      <td>0.405242</td>\n",
       "      <td>0.146878</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>173</th>\n",
       "      <td>0.567129</td>\n",
       "      <td>0.143145</td>\n",
       "      <td>0.109938</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>174</th>\n",
       "      <td>0.749746</td>\n",
       "      <td>0.068548</td>\n",
       "      <td>0.112577</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>175</th>\n",
       "      <td>0.934055</td>\n",
       "      <td>0.985887</td>\n",
       "      <td>0.364996</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>176</th>\n",
       "      <td>0.837673</td>\n",
       "      <td>0.608871</td>\n",
       "      <td>0.175901</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>177</th>\n",
       "      <td>0.573216</td>\n",
       "      <td>0.157258</td>\n",
       "      <td>0.306948</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>178</th>\n",
       "      <td>0.933378</td>\n",
       "      <td>0.046371</td>\n",
       "      <td>0.205805</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>179</th>\n",
       "      <td>0.557660</td>\n",
       "      <td>0.201613</td>\n",
       "      <td>0.152155</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180</th>\n",
       "      <td>0.527224</td>\n",
       "      <td>0.052419</td>\n",
       "      <td>0.070361</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>181</th>\n",
       "      <td>0.736557</td>\n",
       "      <td>0.108871</td>\n",
       "      <td>0.238347</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>182</th>\n",
       "      <td>0.187690</td>\n",
       "      <td>0.114919</td>\n",
       "      <td>0.258575</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183</th>\n",
       "      <td>0.970240</td>\n",
       "      <td>0.866935</td>\n",
       "      <td>0.628848</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>184</th>\n",
       "      <td>0.855935</td>\n",
       "      <td>0.429435</td>\n",
       "      <td>0.261214</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>185</th>\n",
       "      <td>0.690903</td>\n",
       "      <td>0.909274</td>\n",
       "      <td>0.169745</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>186</th>\n",
       "      <td>0.469395</td>\n",
       "      <td>0.042339</td>\n",
       "      <td>0.231310</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>187</th>\n",
       "      <td>0.643896</td>\n",
       "      <td>0.578629</td>\n",
       "      <td>0.157432</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>188</th>\n",
       "      <td>0.964829</td>\n",
       "      <td>0.280242</td>\n",
       "      <td>0.029903</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>189</th>\n",
       "      <td>0.060873</td>\n",
       "      <td>0.243952</td>\n",
       "      <td>0.203166</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>190</th>\n",
       "      <td>0.131214</td>\n",
       "      <td>0.828629</td>\n",
       "      <td>0.048373</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>191</th>\n",
       "      <td>0.252959</td>\n",
       "      <td>0.217742</td>\n",
       "      <td>0.050132</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>192</th>\n",
       "      <td>0.055800</td>\n",
       "      <td>0.082661</td>\n",
       "      <td>0.275286</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193</th>\n",
       "      <td>0.561718</td>\n",
       "      <td>0.846774</td>\n",
       "      <td>0.029024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>194</th>\n",
       "      <td>0.503889</td>\n",
       "      <td>0.717742</td>\n",
       "      <td>0.050132</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>195</th>\n",
       "      <td>0.126818</td>\n",
       "      <td>0.074597</td>\n",
       "      <td>0.118734</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196</th>\n",
       "      <td>0.316199</td>\n",
       "      <td>0.098790</td>\n",
       "      <td>0.068602</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197</th>\n",
       "      <td>0.596212</td>\n",
       "      <td>0.187500</td>\n",
       "      <td>0.053650</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>198</th>\n",
       "      <td>0.956713</td>\n",
       "      <td>0.846774</td>\n",
       "      <td>0.579595</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>199</th>\n",
       "      <td>0.782550</td>\n",
       "      <td>0.173387</td>\n",
       "      <td>0.073879</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>200 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            0         1         2\n",
       "0    0.775786  0.762097  0.605981\n",
       "1    0.148123  0.792339  0.394019\n",
       "2    0.055800  0.925403  0.606860\n",
       "3    0.509976  0.832661  0.511873\n",
       "4    0.609063  0.217742  0.510994\n",
       "5    0.027054  0.985887  0.656992\n",
       "6    0.192087  0.661290  0.204046\n",
       "7    0.404126  0.395161  0.099384\n",
       "8    0.026716  0.042339  0.006157\n",
       "9    0.673318  0.052419  0.183817\n",
       "10   0.221170  0.116935  0.210202\n",
       "11   0.723706  0.483871  0.032542\n",
       "12   0.078120  0.707661  0.576957\n",
       "13   0.327359  0.153226  0.060686\n",
       "14   0.687859  0.663306  0.401935\n",
       "15   0.658438  0.961694  0.462621\n",
       "16   0.226919  0.737903  1.000000\n",
       "17   0.949273  0.798387  0.488127\n",
       "18   0.231654  0.413306  0.158311\n",
       "19   0.495773  0.481855  0.165347\n",
       "20   0.736219  0.558468  0.467018\n",
       "21   0.800473  0.102823  0.204046\n",
       "22   0.042273  0.320565  0.433597\n",
       "23   0.769699  0.340726  0.227792\n",
       "24   0.208319  0.254032  0.158311\n",
       "25   0.886710  0.070565  0.168865\n",
       "26   0.480893  0.590726  0.108179\n",
       "27   0.809604  0.336694  0.198769\n",
       "28   0.839026  0.546371  0.198769\n",
       "29   0.236388  0.322581  0.356201\n",
       "..        ...       ...       ...\n",
       "170  0.166723  0.233871  0.159191\n",
       "171  0.553940  0.421371  0.414248\n",
       "172  0.063916  0.405242  0.146878\n",
       "173  0.567129  0.143145  0.109938\n",
       "174  0.749746  0.068548  0.112577\n",
       "175  0.934055  0.985887  0.364996\n",
       "176  0.837673  0.608871  0.175901\n",
       "177  0.573216  0.157258  0.306948\n",
       "178  0.933378  0.046371  0.205805\n",
       "179  0.557660  0.201613  0.152155\n",
       "180  0.527224  0.052419  0.070361\n",
       "181  0.736557  0.108871  0.238347\n",
       "182  0.187690  0.114919  0.258575\n",
       "183  0.970240  0.866935  0.628848\n",
       "184  0.855935  0.429435  0.261214\n",
       "185  0.690903  0.909274  0.169745\n",
       "186  0.469395  0.042339  0.231310\n",
       "187  0.643896  0.578629  0.157432\n",
       "188  0.964829  0.280242  0.029903\n",
       "189  0.060873  0.243952  0.203166\n",
       "190  0.131214  0.828629  0.048373\n",
       "191  0.252959  0.217742  0.050132\n",
       "192  0.055800  0.082661  0.275286\n",
       "193  0.561718  0.846774  0.029024\n",
       "194  0.503889  0.717742  0.050132\n",
       "195  0.126818  0.074597  0.118734\n",
       "196  0.316199  0.098790  0.068602\n",
       "197  0.596212  0.187500  0.053650\n",
       "198  0.956713  0.846774  0.579595\n",
       "199  0.782550  0.173387  0.073879\n",
       "\n",
       "[200 rows x 3 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#9\n",
    "x=df4.values\n",
    "mm=preprocessing.MinMaxScaler()\n",
    "x1=mm.fit_transform(x)\n",
    "df4=pd.DataFrame(x1)\n",
    "df4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "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>TV</th>\n",
       "      <th>Radio</th>\n",
       "      <th>Newspaper</th>\n",
       "      <th>Sales</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.775786</td>\n",
       "      <td>0.762097</td>\n",
       "      <td>0.605981</td>\n",
       "      <td>22.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.148123</td>\n",
       "      <td>0.792339</td>\n",
       "      <td>0.394019</td>\n",
       "      <td>10.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.055800</td>\n",
       "      <td>0.925403</td>\n",
       "      <td>0.606860</td>\n",
       "      <td>9.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.509976</td>\n",
       "      <td>0.832661</td>\n",
       "      <td>0.511873</td>\n",
       "      <td>18.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.609063</td>\n",
       "      <td>0.217742</td>\n",
       "      <td>0.510994</td>\n",
       "      <td>12.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.027054</td>\n",
       "      <td>0.985887</td>\n",
       "      <td>0.656992</td>\n",
       "      <td>7.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.192087</td>\n",
       "      <td>0.661290</td>\n",
       "      <td>0.204046</td>\n",
       "      <td>11.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.404126</td>\n",
       "      <td>0.395161</td>\n",
       "      <td>0.099384</td>\n",
       "      <td>13.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.026716</td>\n",
       "      <td>0.042339</td>\n",
       "      <td>0.006157</td>\n",
       "      <td>4.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.673318</td>\n",
       "      <td>0.052419</td>\n",
       "      <td>0.183817</td>\n",
       "      <td>10.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0.221170</td>\n",
       "      <td>0.116935</td>\n",
       "      <td>0.210202</td>\n",
       "      <td>8.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0.723706</td>\n",
       "      <td>0.483871</td>\n",
       "      <td>0.032542</td>\n",
       "      <td>17.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0.078120</td>\n",
       "      <td>0.707661</td>\n",
       "      <td>0.576957</td>\n",
       "      <td>9.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>0.327359</td>\n",
       "      <td>0.153226</td>\n",
       "      <td>0.060686</td>\n",
       "      <td>9.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>0.687859</td>\n",
       "      <td>0.663306</td>\n",
       "      <td>0.401935</td>\n",
       "      <td>19.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>0.658438</td>\n",
       "      <td>0.961694</td>\n",
       "      <td>0.462621</td>\n",
       "      <td>22.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>0.226919</td>\n",
       "      <td>0.737903</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>12.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>0.949273</td>\n",
       "      <td>0.798387</td>\n",
       "      <td>0.488127</td>\n",
       "      <td>24.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>0.231654</td>\n",
       "      <td>0.413306</td>\n",
       "      <td>0.158311</td>\n",
       "      <td>11.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>0.495773</td>\n",
       "      <td>0.481855</td>\n",
       "      <td>0.165347</td>\n",
       "      <td>14.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>0.736219</td>\n",
       "      <td>0.558468</td>\n",
       "      <td>0.467018</td>\n",
       "      <td>18.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>0.800473</td>\n",
       "      <td>0.102823</td>\n",
       "      <td>0.204046</td>\n",
       "      <td>12.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>0.042273</td>\n",
       "      <td>0.320565</td>\n",
       "      <td>0.433597</td>\n",
       "      <td>5.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>0.769699</td>\n",
       "      <td>0.340726</td>\n",
       "      <td>0.227792</td>\n",
       "      <td>15.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>0.208319</td>\n",
       "      <td>0.254032</td>\n",
       "      <td>0.158311</td>\n",
       "      <td>9.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>0.886710</td>\n",
       "      <td>0.070565</td>\n",
       "      <td>0.168865</td>\n",
       "      <td>12.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>0.480893</td>\n",
       "      <td>0.590726</td>\n",
       "      <td>0.108179</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>0.809604</td>\n",
       "      <td>0.336694</td>\n",
       "      <td>0.198769</td>\n",
       "      <td>15.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>0.839026</td>\n",
       "      <td>0.546371</td>\n",
       "      <td>0.198769</td>\n",
       "      <td>18.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>0.236388</td>\n",
       "      <td>0.322581</td>\n",
       "      <td>0.356201</td>\n",
       "      <td>10.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>170</th>\n",
       "      <td>0.166723</td>\n",
       "      <td>0.233871</td>\n",
       "      <td>0.159191</td>\n",
       "      <td>8.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>171</th>\n",
       "      <td>0.553940</td>\n",
       "      <td>0.421371</td>\n",
       "      <td>0.414248</td>\n",
       "      <td>14.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172</th>\n",
       "      <td>0.063916</td>\n",
       "      <td>0.405242</td>\n",
       "      <td>0.146878</td>\n",
       "      <td>7.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>173</th>\n",
       "      <td>0.567129</td>\n",
       "      <td>0.143145</td>\n",
       "      <td>0.109938</td>\n",
       "      <td>11.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>174</th>\n",
       "      <td>0.749746</td>\n",
       "      <td>0.068548</td>\n",
       "      <td>0.112577</td>\n",
       "      <td>11.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>175</th>\n",
       "      <td>0.934055</td>\n",
       "      <td>0.985887</td>\n",
       "      <td>0.364996</td>\n",
       "      <td>27.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>176</th>\n",
       "      <td>0.837673</td>\n",
       "      <td>0.608871</td>\n",
       "      <td>0.175901</td>\n",
       "      <td>20.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>177</th>\n",
       "      <td>0.573216</td>\n",
       "      <td>0.157258</td>\n",
       "      <td>0.306948</td>\n",
       "      <td>11.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>178</th>\n",
       "      <td>0.933378</td>\n",
       "      <td>0.046371</td>\n",
       "      <td>0.205805</td>\n",
       "      <td>11.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>179</th>\n",
       "      <td>0.557660</td>\n",
       "      <td>0.201613</td>\n",
       "      <td>0.152155</td>\n",
       "      <td>12.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180</th>\n",
       "      <td>0.527224</td>\n",
       "      <td>0.052419</td>\n",
       "      <td>0.070361</td>\n",
       "      <td>10.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>181</th>\n",
       "      <td>0.736557</td>\n",
       "      <td>0.108871</td>\n",
       "      <td>0.238347</td>\n",
       "      <td>12.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>182</th>\n",
       "      <td>0.187690</td>\n",
       "      <td>0.114919</td>\n",
       "      <td>0.258575</td>\n",
       "      <td>8.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183</th>\n",
       "      <td>0.970240</td>\n",
       "      <td>0.866935</td>\n",
       "      <td>0.628848</td>\n",
       "      <td>26.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>184</th>\n",
       "      <td>0.855935</td>\n",
       "      <td>0.429435</td>\n",
       "      <td>0.261214</td>\n",
       "      <td>17.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>185</th>\n",
       "      <td>0.690903</td>\n",
       "      <td>0.909274</td>\n",
       "      <td>0.169745</td>\n",
       "      <td>22.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>186</th>\n",
       "      <td>0.469395</td>\n",
       "      <td>0.042339</td>\n",
       "      <td>0.231310</td>\n",
       "      <td>10.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>187</th>\n",
       "      <td>0.643896</td>\n",
       "      <td>0.578629</td>\n",
       "      <td>0.157432</td>\n",
       "      <td>17.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>188</th>\n",
       "      <td>0.964829</td>\n",
       "      <td>0.280242</td>\n",
       "      <td>0.029903</td>\n",
       "      <td>15.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>189</th>\n",
       "      <td>0.060873</td>\n",
       "      <td>0.243952</td>\n",
       "      <td>0.203166</td>\n",
       "      <td>6.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>190</th>\n",
       "      <td>0.131214</td>\n",
       "      <td>0.828629</td>\n",
       "      <td>0.048373</td>\n",
       "      <td>10.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>191</th>\n",
       "      <td>0.252959</td>\n",
       "      <td>0.217742</td>\n",
       "      <td>0.050132</td>\n",
       "      <td>9.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>192</th>\n",
       "      <td>0.055800</td>\n",
       "      <td>0.082661</td>\n",
       "      <td>0.275286</td>\n",
       "      <td>5.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193</th>\n",
       "      <td>0.561718</td>\n",
       "      <td>0.846774</td>\n",
       "      <td>0.029024</td>\n",
       "      <td>19.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>194</th>\n",
       "      <td>0.503889</td>\n",
       "      <td>0.717742</td>\n",
       "      <td>0.050132</td>\n",
       "      <td>17.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>195</th>\n",
       "      <td>0.126818</td>\n",
       "      <td>0.074597</td>\n",
       "      <td>0.118734</td>\n",
       "      <td>7.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196</th>\n",
       "      <td>0.316199</td>\n",
       "      <td>0.098790</td>\n",
       "      <td>0.068602</td>\n",
       "      <td>9.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197</th>\n",
       "      <td>0.596212</td>\n",
       "      <td>0.187500</td>\n",
       "      <td>0.053650</td>\n",
       "      <td>12.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>198</th>\n",
       "      <td>0.956713</td>\n",
       "      <td>0.846774</td>\n",
       "      <td>0.579595</td>\n",
       "      <td>25.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>199</th>\n",
       "      <td>0.782550</td>\n",
       "      <td>0.173387</td>\n",
       "      <td>0.073879</td>\n",
       "      <td>13.4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>200 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           TV     Radio  Newspaper  Sales\n",
       "0    0.775786  0.762097   0.605981   22.1\n",
       "1    0.148123  0.792339   0.394019   10.4\n",
       "2    0.055800  0.925403   0.606860    9.3\n",
       "3    0.509976  0.832661   0.511873   18.5\n",
       "4    0.609063  0.217742   0.510994   12.9\n",
       "5    0.027054  0.985887   0.656992    7.2\n",
       "6    0.192087  0.661290   0.204046   11.8\n",
       "7    0.404126  0.395161   0.099384   13.2\n",
       "8    0.026716  0.042339   0.006157    4.8\n",
       "9    0.673318  0.052419   0.183817   10.6\n",
       "10   0.221170  0.116935   0.210202    8.6\n",
       "11   0.723706  0.483871   0.032542   17.4\n",
       "12   0.078120  0.707661   0.576957    9.2\n",
       "13   0.327359  0.153226   0.060686    9.7\n",
       "14   0.687859  0.663306   0.401935   19.0\n",
       "15   0.658438  0.961694   0.462621   22.4\n",
       "16   0.226919  0.737903   1.000000   12.5\n",
       "17   0.949273  0.798387   0.488127   24.4\n",
       "18   0.231654  0.413306   0.158311   11.3\n",
       "19   0.495773  0.481855   0.165347   14.6\n",
       "20   0.736219  0.558468   0.467018   18.0\n",
       "21   0.800473  0.102823   0.204046   12.5\n",
       "22   0.042273  0.320565   0.433597    5.6\n",
       "23   0.769699  0.340726   0.227792   15.5\n",
       "24   0.208319  0.254032   0.158311    9.7\n",
       "25   0.886710  0.070565   0.168865   12.0\n",
       "26   0.480893  0.590726   0.108179   15.0\n",
       "27   0.809604  0.336694   0.198769   15.9\n",
       "28   0.839026  0.546371   0.198769   18.9\n",
       "29   0.236388  0.322581   0.356201   10.5\n",
       "..        ...       ...        ...    ...\n",
       "170  0.166723  0.233871   0.159191    8.4\n",
       "171  0.553940  0.421371   0.414248   14.5\n",
       "172  0.063916  0.405242   0.146878    7.6\n",
       "173  0.567129  0.143145   0.109938   11.7\n",
       "174  0.749746  0.068548   0.112577   11.5\n",
       "175  0.934055  0.985887   0.364996   27.0\n",
       "176  0.837673  0.608871   0.175901   20.2\n",
       "177  0.573216  0.157258   0.306948   11.7\n",
       "178  0.933378  0.046371   0.205805   11.8\n",
       "179  0.557660  0.201613   0.152155   12.6\n",
       "180  0.527224  0.052419   0.070361   10.5\n",
       "181  0.736557  0.108871   0.238347   12.2\n",
       "182  0.187690  0.114919   0.258575    8.7\n",
       "183  0.970240  0.866935   0.628848   26.2\n",
       "184  0.855935  0.429435   0.261214   17.6\n",
       "185  0.690903  0.909274   0.169745   22.6\n",
       "186  0.469395  0.042339   0.231310   10.3\n",
       "187  0.643896  0.578629   0.157432   17.3\n",
       "188  0.964829  0.280242   0.029903   15.9\n",
       "189  0.060873  0.243952   0.203166    6.7\n",
       "190  0.131214  0.828629   0.048373   10.8\n",
       "191  0.252959  0.217742   0.050132    9.9\n",
       "192  0.055800  0.082661   0.275286    5.9\n",
       "193  0.561718  0.846774   0.029024   19.6\n",
       "194  0.503889  0.717742   0.050132   17.3\n",
       "195  0.126818  0.074597   0.118734    7.6\n",
       "196  0.316199  0.098790   0.068602    9.7\n",
       "197  0.596212  0.187500   0.053650   12.8\n",
       "198  0.956713  0.846774   0.579595   25.5\n",
       "199  0.782550  0.173387   0.073879   13.4\n",
       "\n",
       "[200 rows x 4 columns]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['TV']=df4[0]\n",
    "df['Radio']=df4[1]\n",
    "df['Newspaper']=df4[2]\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "#10\n",
    "from sklearn.model_selection import train_test_split\n",
    "X=df.drop('Sales',axis=1).values\n",
    "y=df['Sales'].values\n",
    "X_train,X_test,y_train,y_test=train_test_split(X,y,train_size=0.6,test_size=0.4,random_state=123)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "#11\n",
    "from sklearn.linear_model import LinearRegression\n",
    "model=LinearRegression().fit(X_train,y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x396 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#12\n",
    "predictions=model.predict(X_test)\n",
    "import matplotlib.pyplot as plt\n",
    "plt.scatter(y_test,predictions)\n",
    "predictions=model.predict(X_test)\n",
    "plt.xlabel('True values')\n",
    "plt.ylabel('Predictions')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MSE: 2.938932685176435\n"
     ]
    }
   ],
   "source": [
    "#MSE\n",
    "from sklearn.metrics import mean_squared_error\n",
    "mse=mean_squared_error(y_test,predictions)\n",
    "print(f\"MSE: {mse}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "R2: 0.8922433671308665\n"
     ]
    }
   ],
   "source": [
    "#R2 Score\n",
    "from sklearn.metrics import r2_score\n",
    "r2=r2_score(y_test,predictions)\n",
    "print(f\"R2: {r2}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import learning_curve\n",
    "train_sizes=[5,10,20,40,80,160]\n",
    "train_sizes,train_scores,validation_scores=learning_curve(\n",
    "estimator=LinearRegression(),\n",
    "X=df.drop('Sales',axis=1).values,\n",
    "y=df['Sales'].values, train_sizes = train_sizes,cv=5,\n",
    "scoring='neg_mean_squared_error')\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training scores:\n",
      "\n",
      " [[-0.08921326 -0.05636428 -0.05636428 -0.05636428 -0.05636428]\n",
      " [-0.78748852 -2.11312933 -2.11312933 -2.11312933 -2.11312933]\n",
      " [-1.56147651 -2.02272144 -2.02272144 -2.02272144 -2.02272144]\n",
      " [-2.10700883 -2.86430453 -2.86430453 -2.86430453 -2.86430453]\n",
      " [-1.75487601 -2.13336464 -2.58310717 -2.58310717 -2.58310717]\n",
      " [-2.71159317 -2.88969616 -3.10439608 -2.24164153 -2.82179249]]\n",
      "\n",
      " ----------------------------------------------------------------------\n",
      "\n",
      "Validation scores:\n",
      "\n",
      " [[-4.65629952 -6.8458922  -7.91218287 -7.38542573 -9.98212979]\n",
      " [-3.59597148 -5.43919623 -6.24017898 -7.61249674 -8.28740315]\n",
      " [-3.51251816 -2.3945121  -2.79555649 -4.52063037 -4.92904996]\n",
      " [-3.33525047 -2.44535335 -1.64613002 -5.3479251  -2.49645837]\n",
      " [-3.18882455 -2.39737584 -1.53789934 -5.01205052 -2.65853866]\n",
      " [-3.1365399  -2.42566776 -1.58522508 -5.42615506 -2.79114519]]\n"
     ]
    }
   ],
   "source": [
    "print('Training scores:\\n\\n',train_scores)\n",
    "print('\\n','-'*70) # separator to make the output easy to read\n",
    "print('\\nValidation scores:\\n\\n',validation_scores)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mean training scores\n",
      "\n",
      " 5      0.062934\n",
      "10     1.848001\n",
      "20     1.930472\n",
      "40     2.712845\n",
      "80     2.327512\n",
      "160    2.753824\n",
      "dtype: float64\n",
      "\n",
      " --------------------\n",
      "\n",
      "Mean validation scores\n",
      "\n",
      " 5      7.356386\n",
      "10     6.235049\n",
      "20     3.630453\n",
      "40     3.054223\n",
      "80     2.958938\n",
      "160    3.072947\n",
      "dtype: float64\n"
     ]
    }
   ],
   "source": [
    "train_scores_mean=-train_scores.mean(axis=1)\n",
    "validation_scores_mean=-validation_scores.mean(axis=1)\n",
    "print('Mean training scores\\n\\n',pd.Series(train_scores_mean,index=train_sizes))\n",
    "print('\\n','-'*20) #separator\n",
    "print('\\nMean validation scores\\n\\n',pd.Series(validation_scores_mean,index=train_sizes))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0, 10)"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x396 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "plt.style.use('seaborn')\n",
    "plt.plot(train_sizes,train_scores_mean,label='Training error')\n",
    "plt.plot(train_sizes,validation_scores_mean,label='Validation error')\n",
    "plt.ylabel('MSE',fontsize=14)\n",
    "plt.xlabel('Training set size',fontsize=14)\n",
    "plt.title('Learning curves for a linear regression model',fontsize=18,y=1.03)\n",
    "plt.legend()\n",
    "plt.ylim(0,10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}