CTR_Optimisation_Code.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "#### Import needed libraries\n",
    "import pandas as pd\n",
    "import math, datetime\n",
    "import numpy as np\n",
    "from sklearn import preprocessing, svm\n",
    "from sklearn.model_selection import train_test_split\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib import style\n",
    "import pickle\n",
    "import re\n",
    "from sklearn.cluster import KMeans\n",
    "\n",
    "style.use('ggplot')\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('data.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "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>Page</th>\n",
       "      <th>Clicks</th>\n",
       "      <th>Impressions</th>\n",
       "      <th>CTR</th>\n",
       "      <th>Position</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>https://www.beautydiaries.gr/omorfoxamos/takal...</td>\n",
       "      <td>747</td>\n",
       "      <td>8158</td>\n",
       "      <td>9.16%</td>\n",
       "      <td>21.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>https://www.beautydiaries.gr/</td>\n",
       "      <td>683</td>\n",
       "      <td>3166</td>\n",
       "      <td>21.57%</td>\n",
       "      <td>12.21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>https://www.beautydiaries.gr/omorfoxamos/takal...</td>\n",
       "      <td>430</td>\n",
       "      <td>3785</td>\n",
       "      <td>11.36%</td>\n",
       "      <td>10.81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>https://www.beautydiaries.gr/omorfoxamos/takal...</td>\n",
       "      <td>248</td>\n",
       "      <td>8620</td>\n",
       "      <td>2.88%</td>\n",
       "      <td>29.88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>https://www.beautydiaries.gr/omorfoxamos/takal...</td>\n",
       "      <td>135</td>\n",
       "      <td>1134</td>\n",
       "      <td>11.9%</td>\n",
       "      <td>9.73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>https://www.beautydiaries.gr/beauty-news-ta-ne...</td>\n",
       "      <td>90</td>\n",
       "      <td>879</td>\n",
       "      <td>10.24%</td>\n",
       "      <td>15.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>https://www.beautydiaries.gr/beauty-news-ta-ne...</td>\n",
       "      <td>68</td>\n",
       "      <td>1172</td>\n",
       "      <td>5.8%</td>\n",
       "      <td>9.70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>https://www.beautydiaries.gr/beauty-news-ta-ne...</td>\n",
       "      <td>59</td>\n",
       "      <td>617</td>\n",
       "      <td>9.56%</td>\n",
       "      <td>8.73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>https://www.beautydiaries.gr/omorfoxamos/takal...</td>\n",
       "      <td>59</td>\n",
       "      <td>477</td>\n",
       "      <td>12.37%</td>\n",
       "      <td>16.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>https://www.beautydiaries.gr/apopsi/tade-efi/t...</td>\n",
       "      <td>51</td>\n",
       "      <td>845</td>\n",
       "      <td>6.04%</td>\n",
       "      <td>8.55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>https://www.beautydiaries.gr/oraioi-anthropoi/...</td>\n",
       "      <td>49</td>\n",
       "      <td>793</td>\n",
       "      <td>6.18%</td>\n",
       "      <td>13.74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>https://www.beautydiaries.gr/beautynews/soma/t...</td>\n",
       "      <td>49</td>\n",
       "      <td>320</td>\n",
       "      <td>15.31%</td>\n",
       "      <td>9.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>https://www.beautydiaries.gr/beauty-news-ta-ne...</td>\n",
       "      <td>47</td>\n",
       "      <td>547</td>\n",
       "      <td>8.59%</td>\n",
       "      <td>15.78</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>https://www.beautydiaries.gr/beauty-news-ta-ne...</td>\n",
       "      <td>45</td>\n",
       "      <td>316</td>\n",
       "      <td>14.24%</td>\n",
       "      <td>13.07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>https://www.beautydiaries.gr/beauty-news-ta-ne...</td>\n",
       "      <td>44</td>\n",
       "      <td>597</td>\n",
       "      <td>7.37%</td>\n",
       "      <td>20.63</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>https://www.beautydiaries.gr/omorfoxamos/takal...</td>\n",
       "      <td>40</td>\n",
       "      <td>883</td>\n",
       "      <td>4.53%</td>\n",
       "      <td>25.31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>https://www.beautydiaries.gr/omorfoxamos/beaut...</td>\n",
       "      <td>38</td>\n",
       "      <td>332</td>\n",
       "      <td>11.45%</td>\n",
       "      <td>9.62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>https://www.beautydiaries.gr/omorfoxamos/takal...</td>\n",
       "      <td>36</td>\n",
       "      <td>943</td>\n",
       "      <td>3.82%</td>\n",
       "      <td>10.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>https://www.beautydiaries.gr/omorfoxamos/oikon...</td>\n",
       "      <td>36</td>\n",
       "      <td>223</td>\n",
       "      <td>16.14%</td>\n",
       "      <td>5.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>https://www.beautydiaries.gr/beauty-news-ta-ne...</td>\n",
       "      <td>34</td>\n",
       "      <td>526</td>\n",
       "      <td>6.46%</td>\n",
       "      <td>22.83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>https://www.beautydiaries.gr/apopsi/tade-efi/c...</td>\n",
       "      <td>34</td>\n",
       "      <td>274</td>\n",
       "      <td>12.41%</td>\n",
       "      <td>17.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>https://www.beautydiaries.gr/apopsi/tade-efi/t...</td>\n",
       "      <td>31</td>\n",
       "      <td>803</td>\n",
       "      <td>3.86%</td>\n",
       "      <td>22.88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>https://www.beautydiaries.gr/beauty-news-ta-ne...</td>\n",
       "      <td>30</td>\n",
       "      <td>306</td>\n",
       "      <td>9.8%</td>\n",
       "      <td>12.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>https://www.beautydiaries.gr/omorfoxamos/takal...</td>\n",
       "      <td>29</td>\n",
       "      <td>313</td>\n",
       "      <td>9.27%</td>\n",
       "      <td>29.77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>https://www.beautydiaries.gr/beauty-news-ta-ne...</td>\n",
       "      <td>28</td>\n",
       "      <td>367</td>\n",
       "      <td>7.63%</td>\n",
       "      <td>26.47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>https://www.beautydiaries.gr/oraioi-anthropoi/...</td>\n",
       "      <td>27</td>\n",
       "      <td>604</td>\n",
       "      <td>4.47%</td>\n",
       "      <td>15.89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>https://www.beautydiaries.gr/beauty-news-ta-ne...</td>\n",
       "      <td>26</td>\n",
       "      <td>377</td>\n",
       "      <td>6.9%</td>\n",
       "      <td>14.86</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>https://www.beautydiaries.gr/diagonismos/kerdi...</td>\n",
       "      <td>25</td>\n",
       "      <td>1269</td>\n",
       "      <td>1.97%</td>\n",
       "      <td>16.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>https://www.beautydiaries.gr/omorfoxamos/takal...</td>\n",
       "      <td>25</td>\n",
       "      <td>821</td>\n",
       "      <td>3.05%</td>\n",
       "      <td>31.32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>https://www.beautydiaries.gr/omorfoxamos/oikon...</td>\n",
       "      <td>25</td>\n",
       "      <td>525</td>\n",
       "      <td>4.76%</td>\n",
       "      <td>27.43</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>970</th>\n",
       "      <td>https://www.beautydiaries.gr/2010/09/08/mια-φο...</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0%</td>\n",
       "      <td>24.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>971</th>\n",
       "      <td>https://www.beautydiaries.gr/category/xoros/</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0%</td>\n",
       "      <td>25.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>972</th>\n",
       "      <td>https://www.beautydiaries.gr/tag/cream-booster/</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0%</td>\n",
       "      <td>28.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>973</th>\n",
       "      <td>https://www.beautydiaries.gr/category/beauty-n...</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0%</td>\n",
       "      <td>29.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>974</th>\n",
       "      <td>https://www.beautydiaries.gr/category/omorfoxa...</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0%</td>\n",
       "      <td>32.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>975</th>\n",
       "      <td>https://www.beautydiaries.gr/tag/anastasia-bev...</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0%</td>\n",
       "      <td>37.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>976</th>\n",
       "      <td>https://www.beautydiaries.gr/omorfoxamos/dokim...</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0%</td>\n",
       "      <td>38.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>977</th>\n",
       "      <td>https://www.beautydiaries.gr/tag/ypnos/</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0%</td>\n",
       "      <td>40.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>978</th>\n",
       "      <td>https://www.beautydiaries.gr/tag/giogka-prosopoy/</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0%</td>\n",
       "      <td>43.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>979</th>\n",
       "      <td>https://www.beautydiaries.gr/tag/idees-gia-mak...</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0%</td>\n",
       "      <td>44.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>980</th>\n",
       "      <td>https://www.beautydiaries.gr/2015/12/28/δεν-γί...</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0%</td>\n",
       "      <td>47.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>981</th>\n",
       "      <td>https://www.beautydiaries.gr/2015/03/08/επαναφ...</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0%</td>\n",
       "      <td>49.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>982</th>\n",
       "      <td>https://www.beautydiaries.gr/tag/beauty-com/</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0%</td>\n",
       "      <td>49.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>983</th>\n",
       "      <td>https://www.beautydiaries.gr/tag/gynaikeia-filia/</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0%</td>\n",
       "      <td>49.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>984</th>\n",
       "      <td>https://www.beautydiaries.gr/tag/elaia-gia-to-...</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0%</td>\n",
       "      <td>53.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>985</th>\n",
       "      <td>https://www.beautydiaries.gr/tag/κοπλιμέντα/</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0%</td>\n",
       "      <td>70.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>986</th>\n",
       "      <td>https://www.beautydiaries.gr/tag/farsali/</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0%</td>\n",
       "      <td>76.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>987</th>\n",
       "      <td>https://www.beautydiaries.gr/tag/schima-nychion/</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0%</td>\n",
       "      <td>79.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>988</th>\n",
       "      <td>https://www.beautydiaries.gr/apopsi/tade-efi/k...</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0%</td>\n",
       "      <td>81.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>989</th>\n",
       "      <td>https://www.beautydiaries.gr/tag/gregoris-pyrp...</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0%</td>\n",
       "      <td>81.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>990</th>\n",
       "      <td>https://www.beautydiaries.gr/tag/christina-fla...</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0%</td>\n",
       "      <td>84.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>991</th>\n",
       "      <td>https://www.beautydiaries.gr/c115d1a5ec888a953...</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0%</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>992</th>\n",
       "      <td>https://www.beautydiaries.gr/tag/blog/</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0%</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>993</th>\n",
       "      <td>https://www.beautydiaries.gr/tag/sta-farmakeia/</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0%</td>\n",
       "      <td>2.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>994</th>\n",
       "      <td>https://www.beautydiaries.gr/?p=15067&amp;preview=...</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0%</td>\n",
       "      <td>2.33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>995</th>\n",
       "      <td>https://www.beautydiaries.gr/beautynews/aroma/...</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0%</td>\n",
       "      <td>3.33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>996</th>\n",
       "      <td>https://www.beautydiaries.gr/tag/wakupbeautiful/</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0%</td>\n",
       "      <td>4.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>997</th>\n",
       "      <td>https://www.beautydiaries.gr/2011/01/25/παράξε...</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0%</td>\n",
       "      <td>4.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>998</th>\n",
       "      <td>https://www.beautydiaries.gr/category/des-ta-p...</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0%</td>\n",
       "      <td>5.33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>999</th>\n",
       "      <td>https://www.beautydiaries.gr/tag/voyla-sta-nyc...</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0%</td>\n",
       "      <td>5.33</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1000 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                  Page  Clicks  Impressions  \\\n",
       "0    https://www.beautydiaries.gr/omorfoxamos/takal...     747         8158   \n",
       "1                        https://www.beautydiaries.gr/     683         3166   \n",
       "2    https://www.beautydiaries.gr/omorfoxamos/takal...     430         3785   \n",
       "3    https://www.beautydiaries.gr/omorfoxamos/takal...     248         8620   \n",
       "4    https://www.beautydiaries.gr/omorfoxamos/takal...     135         1134   \n",
       "5    https://www.beautydiaries.gr/beauty-news-ta-ne...      90          879   \n",
       "6    https://www.beautydiaries.gr/beauty-news-ta-ne...      68         1172   \n",
       "7    https://www.beautydiaries.gr/beauty-news-ta-ne...      59          617   \n",
       "8    https://www.beautydiaries.gr/omorfoxamos/takal...      59          477   \n",
       "9    https://www.beautydiaries.gr/apopsi/tade-efi/t...      51          845   \n",
       "10   https://www.beautydiaries.gr/oraioi-anthropoi/...      49          793   \n",
       "11   https://www.beautydiaries.gr/beautynews/soma/t...      49          320   \n",
       "12   https://www.beautydiaries.gr/beauty-news-ta-ne...      47          547   \n",
       "13   https://www.beautydiaries.gr/beauty-news-ta-ne...      45          316   \n",
       "14   https://www.beautydiaries.gr/beauty-news-ta-ne...      44          597   \n",
       "15   https://www.beautydiaries.gr/omorfoxamos/takal...      40          883   \n",
       "16   https://www.beautydiaries.gr/omorfoxamos/beaut...      38          332   \n",
       "17   https://www.beautydiaries.gr/omorfoxamos/takal...      36          943   \n",
       "18   https://www.beautydiaries.gr/omorfoxamos/oikon...      36          223   \n",
       "19   https://www.beautydiaries.gr/beauty-news-ta-ne...      34          526   \n",
       "20   https://www.beautydiaries.gr/apopsi/tade-efi/c...      34          274   \n",
       "21   https://www.beautydiaries.gr/apopsi/tade-efi/t...      31          803   \n",
       "22   https://www.beautydiaries.gr/beauty-news-ta-ne...      30          306   \n",
       "23   https://www.beautydiaries.gr/omorfoxamos/takal...      29          313   \n",
       "24   https://www.beautydiaries.gr/beauty-news-ta-ne...      28          367   \n",
       "25   https://www.beautydiaries.gr/oraioi-anthropoi/...      27          604   \n",
       "26   https://www.beautydiaries.gr/beauty-news-ta-ne...      26          377   \n",
       "27   https://www.beautydiaries.gr/diagonismos/kerdi...      25         1269   \n",
       "28   https://www.beautydiaries.gr/omorfoxamos/takal...      25          821   \n",
       "29   https://www.beautydiaries.gr/omorfoxamos/oikon...      25          525   \n",
       "..                                                 ...     ...          ...   \n",
       "970  https://www.beautydiaries.gr/2010/09/08/mια-φο...       0            4   \n",
       "971       https://www.beautydiaries.gr/category/xoros/       0            4   \n",
       "972    https://www.beautydiaries.gr/tag/cream-booster/       0            4   \n",
       "973  https://www.beautydiaries.gr/category/beauty-n...       0            4   \n",
       "974  https://www.beautydiaries.gr/category/omorfoxa...       0            4   \n",
       "975  https://www.beautydiaries.gr/tag/anastasia-bev...       0            4   \n",
       "976  https://www.beautydiaries.gr/omorfoxamos/dokim...       0            4   \n",
       "977            https://www.beautydiaries.gr/tag/ypnos/       0            4   \n",
       "978  https://www.beautydiaries.gr/tag/giogka-prosopoy/       0            4   \n",
       "979  https://www.beautydiaries.gr/tag/idees-gia-mak...       0            4   \n",
       "980  https://www.beautydiaries.gr/2015/12/28/δεν-γί...       0            4   \n",
       "981  https://www.beautydiaries.gr/2015/03/08/επαναφ...       0            4   \n",
       "982       https://www.beautydiaries.gr/tag/beauty-com/       0            4   \n",
       "983  https://www.beautydiaries.gr/tag/gynaikeia-filia/       0            4   \n",
       "984  https://www.beautydiaries.gr/tag/elaia-gia-to-...       0            4   \n",
       "985       https://www.beautydiaries.gr/tag/κοπλιμέντα/       0            4   \n",
       "986          https://www.beautydiaries.gr/tag/farsali/       0            4   \n",
       "987   https://www.beautydiaries.gr/tag/schima-nychion/       0            4   \n",
       "988  https://www.beautydiaries.gr/apopsi/tade-efi/k...       0            4   \n",
       "989  https://www.beautydiaries.gr/tag/gregoris-pyrp...       0            4   \n",
       "990  https://www.beautydiaries.gr/tag/christina-fla...       0            4   \n",
       "991  https://www.beautydiaries.gr/c115d1a5ec888a953...       0            3   \n",
       "992             https://www.beautydiaries.gr/tag/blog/       0            3   \n",
       "993    https://www.beautydiaries.gr/tag/sta-farmakeia/       0            3   \n",
       "994  https://www.beautydiaries.gr/?p=15067&preview=...       0            3   \n",
       "995  https://www.beautydiaries.gr/beautynews/aroma/...       0            3   \n",
       "996   https://www.beautydiaries.gr/tag/wakupbeautiful/       0            3   \n",
       "997  https://www.beautydiaries.gr/2011/01/25/παράξε...       0            3   \n",
       "998  https://www.beautydiaries.gr/category/des-ta-p...       0            3   \n",
       "999  https://www.beautydiaries.gr/tag/voyla-sta-nyc...       0            3   \n",
       "\n",
       "        CTR  Position  \n",
       "0     9.16%     21.99  \n",
       "1    21.57%     12.21  \n",
       "2    11.36%     10.81  \n",
       "3     2.88%     29.88  \n",
       "4     11.9%      9.73  \n",
       "5    10.24%     15.15  \n",
       "6      5.8%      9.70  \n",
       "7     9.56%      8.73  \n",
       "8    12.37%     16.99  \n",
       "9     6.04%      8.55  \n",
       "10    6.18%     13.74  \n",
       "11   15.31%      9.25  \n",
       "12    8.59%     15.78  \n",
       "13   14.24%     13.07  \n",
       "14    7.37%     20.63  \n",
       "15    4.53%     25.31  \n",
       "16   11.45%      9.62  \n",
       "17    3.82%     10.09  \n",
       "18   16.14%      5.08  \n",
       "19    6.46%     22.83  \n",
       "20   12.41%     17.02  \n",
       "21    3.86%     22.88  \n",
       "22     9.8%     12.08  \n",
       "23    9.27%     29.77  \n",
       "24    7.63%     26.47  \n",
       "25    4.47%     15.89  \n",
       "26     6.9%     14.86  \n",
       "27    1.97%     16.11  \n",
       "28    3.05%     31.32  \n",
       "29    4.76%     27.43  \n",
       "..      ...       ...  \n",
       "970      0%     24.25  \n",
       "971      0%     25.00  \n",
       "972      0%     28.75  \n",
       "973      0%     29.50  \n",
       "974      0%     32.00  \n",
       "975      0%     37.25  \n",
       "976      0%     38.50  \n",
       "977      0%     40.25  \n",
       "978      0%     43.50  \n",
       "979      0%     44.25  \n",
       "980      0%     47.75  \n",
       "981      0%     49.25  \n",
       "982      0%     49.75  \n",
       "983      0%     49.75  \n",
       "984      0%     53.00  \n",
       "985      0%     70.50  \n",
       "986      0%     76.75  \n",
       "987      0%     79.75  \n",
       "988      0%     81.50  \n",
       "989      0%     81.50  \n",
       "990      0%     84.75  \n",
       "991      0%      1.00  \n",
       "992      0%      1.00  \n",
       "993      0%      2.00  \n",
       "994      0%      2.33  \n",
       "995      0%      3.33  \n",
       "996      0%      4.00  \n",
       "997      0%      4.67  \n",
       "998      0%      5.33  \n",
       "999      0%      5.33  \n",
       "\n",
       "[1000 rows x 5 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Cleaning The Data\n",
    "df['CTR'] = df['CTR'].apply(lambda x: float(x.replace('%', '')))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = df[['Clicks', 'Impressions', 'Position']]\n",
    "y = df.pop('CTR')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Train Test Split \n",
    "X_train, X_test, y_train, y_test = train_test_split(\n",
    "X, y, test_size=0.33, random_state=42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Standardise The Data \n",
    "from sklearn.preprocessing import StandardScaler"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "scaler = StandardScaler()\n",
    "scaler = scaler.fit(X_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train = pd.DataFrame(scaler.transform(X_train), columns = X_train.columns, index = X_train.index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_test = pd.DataFrame(scaler.transform(X_test), columns = X_test.columns, index = X_test.index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import different Algorithms to see differences between their predictions\n",
    "from sklearn.linear_model import LinearRegression\n",
    "from sklearn.ensemble import RandomForestRegressor\n",
    "from sklearn.metrics import mean_squared_error, r2_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "Linear_regression = LinearRegression()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LinearRegression(copy_X=True, fit_intercept=True, n_jobs=None, normalize=False)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Linear_regression.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.04587699725091532"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Linear_regression.score(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-0.3732922110193282"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Linear_regression.score(X_test, y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.9940722381419709 0.9539328192628949\n"
     ]
    }
   ],
   "source": [
    "RandomForestRegressorModel = RandomForestRegressor(n_estimators=50)\n",
    "RandomForestRegressorModel.fit(X_train, y_train)\n",
    "prediction_score = RandomForestRegressorModel.score(X_train, y_train)\n",
    "test_score = RandomForestRegressorModel.score(X_test, y_test)\n",
    "\n",
    "print(prediction_score, test_score)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "ERROR:root:Internal Python error in the inspect module.\n",
      "Below is the traceback from this internal error.\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Traceback (most recent call last):\n",
      "  File \"/Users/jamesphoenix/anaconda3/lib/python3.7/site-packages/IPython/core/interactiveshell.py\", line 3325, in run_code\n",
      "    exec(code_obj, self.user_global_ns, self.user_ns)\n",
      "  File \"<ipython-input-17-e77c553189f0>\", line 13, in <module>\n",
      "    RandomForestRegressorModel.fit(X_train, y_train)\n",
      "  File \"/Users/jamesphoenix/anaconda3/lib/python3.7/site-packages/sklearn/model_selection/_search.py\", line 687, in fit\n",
      "    self._run_search(evaluate_candidates)\n",
      "  File \"/Users/jamesphoenix/anaconda3/lib/python3.7/site-packages/sklearn/model_selection/_search.py\", line 1148, in _run_search\n",
      "    evaluate_candidates(ParameterGrid(self.param_grid))\n",
      "  File \"/Users/jamesphoenix/anaconda3/lib/python3.7/site-packages/sklearn/model_selection/_search.py\", line 666, in evaluate_candidates\n",
      "    cv.split(X, y, groups)))\n",
      "  File \"/Users/jamesphoenix/anaconda3/lib/python3.7/site-packages/joblib/parallel.py\", line 924, in __call__\n",
      "    while self.dispatch_one_batch(iterator):\n",
      "  File \"/Users/jamesphoenix/anaconda3/lib/python3.7/site-packages/joblib/parallel.py\", line 759, in dispatch_one_batch\n",
      "    self._dispatch(tasks)\n",
      "  File \"/Users/jamesphoenix/anaconda3/lib/python3.7/site-packages/joblib/parallel.py\", line 716, in _dispatch\n",
      "    job = self._backend.apply_async(batch, callback=cb)\n",
      "  File \"/Users/jamesphoenix/anaconda3/lib/python3.7/site-packages/joblib/_parallel_backends.py\", line 182, in apply_async\n",
      "    result = ImmediateResult(func)\n",
      "  File \"/Users/jamesphoenix/anaconda3/lib/python3.7/site-packages/joblib/_parallel_backends.py\", line 549, in __init__\n",
      "    self.results = batch()\n",
      "  File \"/Users/jamesphoenix/anaconda3/lib/python3.7/site-packages/joblib/parallel.py\", line 225, in __call__\n",
      "    for func, args, kwargs in self.items]\n",
      "  File \"/Users/jamesphoenix/anaconda3/lib/python3.7/site-packages/joblib/parallel.py\", line 225, in <listcomp>\n",
      "    for func, args, kwargs in self.items]\n",
      "  File \"/Users/jamesphoenix/anaconda3/lib/python3.7/site-packages/sklearn/model_selection/_validation.py\", line 514, in _fit_and_score\n",
      "    estimator.fit(X_train, y_train, **fit_params)\n",
      "  File \"/Users/jamesphoenix/anaconda3/lib/python3.7/site-packages/sklearn/pipeline.py\", line 356, in fit\n",
      "    self._final_estimator.fit(Xt, y, **fit_params)\n",
      "  File \"/Users/jamesphoenix/anaconda3/lib/python3.7/site-packages/sklearn/ensemble/forest.py\", line 330, in fit\n",
      "    for i, t in enumerate(trees))\n",
      "  File \"/Users/jamesphoenix/anaconda3/lib/python3.7/site-packages/joblib/parallel.py\", line 924, in __call__\n",
      "    while self.dispatch_one_batch(iterator):\n",
      "  File \"/Users/jamesphoenix/anaconda3/lib/python3.7/site-packages/joblib/parallel.py\", line 753, in dispatch_one_batch\n",
      "    self._backend.get_nested_backend(),\n",
      "  File \"/Users/jamesphoenix/anaconda3/lib/python3.7/site-packages/joblib/_parallel_backends.py\", line 189, in get_nested_backend\n",
      "    from .parallel import get_active_backend\n",
      "  File \"<frozen importlib._bootstrap>\", line 1019, in _handle_fromlist\n",
      "KeyboardInterrupt\n",
      "\n",
      "During handling of the above exception, another exception occurred:\n",
      "\n",
      "Traceback (most recent call last):\n",
      "  File \"/Users/jamesphoenix/anaconda3/lib/python3.7/site-packages/IPython/core/interactiveshell.py\", line 2039, in showtraceback\n",
      "    stb = value._render_traceback_()\n",
      "AttributeError: 'KeyboardInterrupt' object has no attribute '_render_traceback_'\n",
      "\n",
      "During handling of the above exception, another exception occurred:\n",
      "\n",
      "Traceback (most recent call last):\n",
      "  File \"/Users/jamesphoenix/anaconda3/lib/python3.7/site-packages/IPython/core/ultratb.py\", line 1101, in get_records\n",
      "    return _fixed_getinnerframes(etb, number_of_lines_of_context, tb_offset)\n",
      "  File \"/Users/jamesphoenix/anaconda3/lib/python3.7/site-packages/IPython/core/ultratb.py\", line 319, in wrapped\n",
      "    return f(*args, **kwargs)\n",
      "  File \"/Users/jamesphoenix/anaconda3/lib/python3.7/site-packages/IPython/core/ultratb.py\", line 353, in _fixed_getinnerframes\n",
      "    records = fix_frame_records_filenames(inspect.getinnerframes(etb, context))\n",
      "  File \"/Users/jamesphoenix/anaconda3/lib/python3.7/inspect.py\", line 1502, in getinnerframes\n",
      "    frameinfo = (tb.tb_frame,) + getframeinfo(tb, context)\n",
      "  File \"/Users/jamesphoenix/anaconda3/lib/python3.7/inspect.py\", line 1460, in getframeinfo\n",
      "    filename = getsourcefile(frame) or getfile(frame)\n",
      "  File \"/Users/jamesphoenix/anaconda3/lib/python3.7/inspect.py\", line 696, in getsourcefile\n",
      "    if getattr(getmodule(object, filename), '__loader__', None) is not None:\n",
      "  File \"/Users/jamesphoenix/anaconda3/lib/python3.7/inspect.py\", line 739, in getmodule\n",
      "    f = getabsfile(module)\n",
      "  File \"/Users/jamesphoenix/anaconda3/lib/python3.7/inspect.py\", line 708, in getabsfile\n",
      "    _filename = getsourcefile(object) or getfile(object)\n",
      "  File \"/Users/jamesphoenix/anaconda3/lib/python3.7/inspect.py\", line 685, in getsourcefile\n",
      "    all_bytecode_suffixes = importlib.machinery.DEBUG_BYTECODE_SUFFIXES[:]\n",
      "KeyboardInterrupt\n"
     ]
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m"
     ]
    }
   ],
   "source": [
    "from sklearn.ensemble import RandomForestRegressor\n",
    "from sklearn.pipeline import make_pipeline\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "pipeline = make_pipeline(RandomForestRegressor(n_estimators=200))\n",
    " \n",
    "# Declare hyperparameters to tune\n",
    "hyperparameters = { 'randomforestregressor__max_features' : ['auto', 'sqrt', 'log2'],\n",
    "                  'randomforestregressor__max_depth': [5, 3, None]}\n",
    " \n",
    "# Tune model using cross-validation pipeline\n",
    "RandomForestRegressorModel = GridSearchCV(pipeline, hyperparameters, cv=5)\n",
    " \n",
    "RandomForestRegressorModel.fit(X_train, y_train)\n",
    "prediction_score = RandomForestRegressorModel.score(X_train, y_train)\n",
    "print(\"The score of prediction for RandomForestRegressorModel is: {}\".format(prediction_score))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Let's Create A Function That Combines The Predictions For X_train, X_test and also contains the index number so that we can match it back up with the original dataframe."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_list = [X_train, X_test]\n",
    "y_list = y_train, y_test\n",
    "\n",
    "RandomForestRegressorModel = RandomForestRegressor(n_estimators=50)\n",
    "\n",
    "data_dict = {\n",
    "    \n",
    "    'Indexes': [],\n",
    "    'Predictions': []    \n",
    "    \n",
    "}\n",
    "\n",
    "for x, y in zip(X_list, y_list):\n",
    "    \n",
    "    indexes = list(x.index)\n",
    "    RandomForestRegressorModel.fit(X_train, y_train)\n",
    "    predictions = RandomForestRegressorModel.predict(x)\n",
    "    \n",
    "    data_dict['Indexes'].extend(indexes)\n",
    "    data_dict['Predictions'].extend(predictions)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "------------------------------------------------------------------------------------------------------------------------"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
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       "  377,\n",
       "  526,\n",
       "  845,\n",
       "  137,\n",
       "  355,\n",
       "  365,\n",
       "  942,\n",
       "  749,\n",
       "  948,\n",
       "  829,\n",
       "  656,\n",
       "  199,\n",
       "  213,\n",
       "  408,\n",
       "  332,\n",
       "  208,\n",
       "  613,\n",
       "  78,\n",
       "  29,\n",
       "  535,\n",
       "  695,\n",
       "  557,\n",
       "  836,\n",
       "  596,\n",
       "  165,\n",
       "  918,\n",
       "  495,\n",
       "  824,\n",
       "  65,\n",
       "  141,\n",
       "  925,\n",
       "  827,\n",
       "  655,\n",
       "  331,\n",
       "  664,\n",
       "  249,\n",
       "  907,\n",
       "  708,\n",
       "  305,\n",
       "  734,\n",
       "  975,\n",
       "  49,\n",
       "  896,\n",
       "  2,\n",
       "  544,\n",
       "  350,\n",
       "  904,\n",
       "  536,\n",
       "  344,\n",
       "  994,\n",
       "  481,\n",
       "  575,\n",
       "  33,\n",
       "  31,\n",
       "  231,\n",
       "  963,\n",
       "  192,\n",
       "  333,\n",
       "  3,\n",
       "  204,\n",
       "  514,\n",
       "  799,\n",
       "  306,\n",
       "  109,\n",
       "  430,\n",
       "  77,\n",
       "  84,\n",
       "  286,\n",
       "  82,\n",
       "  991,\n",
       "  789,\n",
       "  894,\n",
       "  398,\n",
       "  323,\n",
       "  519,\n",
       "  916,\n",
       "  922,\n",
       "  5,\n",
       "  731,\n",
       "  465,\n",
       "  97,\n",
       "  266,\n",
       "  357,\n",
       "  868,\n",
       "  798,\n",
       "  380,\n",
       "  631,\n",
       "  381,\n",
       "  490,\n",
       "  118,\n",
       "  900,\n",
       "  250,\n",
       "  523,\n",
       "  9,\n",
       "  196,\n",
       "  603,\n",
       "  81,\n",
       "  783,\n",
       "  587,\n",
       "  797,\n",
       "  239,\n",
       "  290,\n",
       "  211,\n",
       "  717,\n",
       "  359,\n",
       "  449,\n",
       "  227,\n",
       "  950,\n",
       "  946,\n",
       "  796,\n",
       "  501,\n",
       "  464,\n",
       "  362,\n",
       "  468,\n",
       "  935,\n",
       "  428,\n",
       "  7,\n",
       "  155,\n",
       "  541,\n",
       "  440,\n",
       "  482,\n",
       "  422,\n",
       "  778,\n",
       "  949,\n",
       "  334,\n",
       "  576,\n",
       "  934,\n",
       "  567,\n",
       "  594,\n",
       "  530,\n",
       "  581,\n",
       "  707,\n",
       "  448,\n",
       "  453,\n",
       "  228,\n",
       "  352,\n",
       "  728,\n",
       "  212,\n",
       "  79,\n",
       "  148,\n",
       "  302,\n",
       "  628,\n",
       "  777,\n",
       "  506,\n",
       "  342,\n",
       "  485,\n",
       "  711,\n",
       "  133],\n",
       " 'Predictions': [0.0,\n",
       "  1.1499999999999992,\n",
       "  0.0,\n",
       "  0.0,\n",
       "  10.995000000000005,\n",
       "  1.311799999999999,\n",
       "  0.0,\n",
       "  0.0,\n",
       "  0.0,\n",
       "  0.0,\n",
       "  100.0,\n",
       "  4.025199999999999,\n",
       "  1.1578000000000004,\n",
       "  3.6981999999999986,\n",
       "  3.684399999999997,\n",
       "  5.574200000000002,\n",
       "  0.0,\n",
       "  0.0,\n",
       "  4.642000000000003,\n",
       "  0.0,\n",
       "  2.1681999999999992,\n",
       "  8.2076,\n",
       "  0.0,\n",
       "  1.8007999999999995,\n",
       "  0.6052000000000003,\n",
       "  7.7312,\n",
       "  0.9012000000000002,\n",
       "  6.0025999999999975,\n",
       "  1.5560000000000007,\n",
       "  2.9316000000000004,\n",
       "  6.028199999999997,\n",
       "  0.0,\n",
       "  11.542799999999998,\n",
       "  9.9272,\n",
       "  11.346400000000001,\n",
       "  3.2400000000000007,\n",
       "  0.0,\n",
       "  3.3002000000000002,\n",
       "  3.3304000000000014,\n",
       "  0.0,\n",
       "  0.8086000000000004,\n",
       "  0.0,\n",
       "  1.4980000000000002,\n",
       "  1.2088000000000008,\n",
       "  8.234000000000004,\n",
       "  0.0,\n",
       "  100.0,\n",
       "  4.853399999999997,\n",
       "  0.0,\n",
       "  0.0,\n",
       "  2.0332000000000012,\n",
       "  3.0738,\n",
       "  0.0,\n",
       "  1.1981999999999986,\n",
       "  12.661799999999996,\n",
       "  0.0,\n",
       "  0.0,\n",
       "  8.206000000000001,\n",
       "  0.0,\n",
       "  0.0,\n",
       "  2.560000000000001,\n",
       "  5.400999999999998,\n",
       "  0.0,\n",
       "  6.251199999999996,\n",
       "  0.0,\n",
       "  9.505000000000004,\n",
       "  4.159999999999997,\n",
       "  9.226399999999991,\n",
       "  0.0,\n",
       "  0.0,\n",
       "  7.009799999999998,\n",
       "  31.863799999999987,\n",
       "  0.0,\n",
       "  0.0,\n",
       "  0.0,\n",
       "  0.0,\n",
       "  0.0,\n",
       "  1.8431999999999993,\n",
       "  1.4742000000000004,\n",
       "  0.0,\n",
       "  0.0,\n",
       "  0.0,\n",
       "  0.0,\n",
       "  5.550799999999999,\n",
       "  0.0,\n",
       "  0.0,\n",
       "  0.0,\n",
       "  0.0,\n",
       "  0.0,\n",
       "  10.060599999999999,\n",
       "  14.329999999999998,\n",
       "  0.0,\n",
       "  0.0,\n",
       "  0.0,\n",
       "  7.183999999999992,\n",
       "  2.6972000000000014,\n",
       "  9.168000000000001,\n",
       "  6.149800000000002,\n",
       "  0.0,\n",
       "  8.0,\n",
       "  0.36200000000000004,\n",
       "  2.4583999999999984,\n",
       "  2.277599999999999,\n",
       "  20.9666,\n",
       "  11.093000000000007,\n",
       "  9.002799999999995,\n",
       "  2.467399999999999,\n",
       "  2.700000000000001,\n",
       "  0.0,\n",
       "  0.0,\n",
       "  17.827799999999996,\n",
       "  0.0,\n",
       "  0.0,\n",
       "  0.0,\n",
       "  0.0,\n",
       "  0.0,\n",
       "  0.0,\n",
       "  1.2707999999999995,\n",
       "  0.0,\n",
       "  0.0,\n",
       "  0.0,\n",
       "  0.0,\n",
       "  3.576199999999996,\n",
       "  10.692399999999997,\n",
       "  3.5527999999999986,\n",
       "  0.0,\n",
       "  0.0,\n",
       "  0.0,\n",
       "  3.027000000000001,\n",
       "  4.524800000000002,\n",
       "  5.730200000000002,\n",
       "  13.571599999999997,\n",
       "  0.0,\n",
       "  0.0,\n",
       "  3.457399999999999,\n",
       "  5.304399999999996,\n",
       "  0.8140000000000001,\n",
       "  5.293599999999998,\n",
       "  0.0,\n",
       "  20.9666,\n",
       "  4.370999999999997,\n",
       "  5.236000000000001,\n",
       "  0.0,\n",
       "  3.6735999999999995,\n",
       "  1.7820000000000014,\n",
       "  0.0,\n",
       "  0.0,\n",
       "  0.0,\n",
       "  0.0,\n",
       "  0.0,\n",
       "  0.0,\n",
       "  6.2870000000000035,\n",
       "  14.162399999999996,\n",
       "  3.846999999999997,\n",
       "  0.0,\n",
       "  2.569800000000001,\n",
       "  9.697000000000006,\n",
       "  1.686000000000001,\n",
       "  0.46519999999999984,\n",
       "  0.0,\n",
       "  0.0,\n",
       "  0.0,\n",
       "  0.0,\n",
       "  1.535800000000001,\n",
       "  6.252999999999999,\n",
       "  1.531,\n",
       "  9.089999999999991,\n",
       "  5.3459999999999965,\n",
       "  0.0,\n",
       "  0.0,\n",
       "  0.0,\n",
       "  1.5193999999999996,\n",
       "  3.846999999999997,\n",
       "  0.0,\n",
       "  0.0,\n",
       "  0.0,\n",
       "  0.0,\n",
       "  3.131400000000002,\n",
       "  0.0,\n",
       "  0.0,\n",
       "  4.7112000000000025,\n",
       "  0.0,\n",
       "  1.7636,\n",
       "  5.443799999999999,\n",
       "  1.5220000000000007,\n",
       "  0.0,\n",
       "  17.552,\n",
       "  2.0502000000000002,\n",
       "  0.0,\n",
       "  8.813800000000004,\n",
       "  2.2769999999999992,\n",
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       "  0.0,\n",
       "  1.8451999999999993,\n",
       "  7.2169999999999925,\n",
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       "  0.0,\n",
       "  4.913599999999999,\n",
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       "  5.383000000000003,\n",
       "  0.0,\n",
       "  1.6275999999999997,\n",
       "  0.0,\n",
       "  14.8694,\n",
       "  0.0,\n",
       "  7.189999999999991,\n",
       "  4.2352,\n",
       "  7.9834,\n",
       "  0.0,\n",
       "  10.027199999999999,\n",
       "  2.779999999999999,\n",
       "  8.0,\n",
       "  1.6654000000000002,\n",
       "  0.0,\n",
       "  2.314200000000001,\n",
       "  0.0,\n",
       "  0.0,\n",
       "  0.0,\n",
       "  0.0,\n",
       "  4.0176,\n",
       "  1.9713999999999994,\n",
       "  99.0,\n",
       "  0.0,\n",
       "  10.941999999999998,\n",
       "  0.0,\n",
       "  0.0,\n",
       "  2.699200000000001,\n",
       "  6.986399999999999,\n",
       "  3.0953999999999984,\n",
       "  2.120399999999999,\n",
       "  3.4216,\n",
       "  0.0,\n",
       "  0.0,\n",
       "  0.0,\n",
       "  5.360199999999997,\n",
       "  9.089999999999991,\n",
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       "  1.1134000000000008,\n",
       "  2.0174000000000003,\n",
       "  0.0,\n",
       "  3.892800000000004,\n",
       "  3.6731999999999987,\n",
       "  0.0,\n",
       "  9.850800000000007,\n",
       "  2.2435999999999994,\n",
       "  0.0,\n",
       "  1.6942,\n",
       "  98.0,\n",
       "  3.8499999999999965,\n",
       "  0.0,\n",
       "  1.4431999999999987,\n",
       "  7.110199999999997,\n",
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       "  0.0,\n",
       "  0.0,\n",
       "  4.347199999999997,\n",
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       "  0.0,\n",
       "  2.764799999999998,\n",
       "  1.2542000000000009,\n",
       "  3.4454000000000007,\n",
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       "  0.0,\n",
       "  0.0,\n",
       "  4.667600000000005,\n",
       "  0.5363999999999998,\n",
       "  0.0,\n",
       "  0.0,\n",
       "  0.0,\n",
       "  5.538199999999997,\n",
       "  4.401200000000002,\n",
       "  1.505,\n",
       "  4.265399999999996,\n",
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       "  0.0,\n",
       "  3.145400000000001,\n",
       "  1.9507999999999999,\n",
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       "  2.1104,\n",
       "  0.9143999999999995,\n",
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       "  13.640600000000004,\n",
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       "  2.6579999999999995,\n",
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       "  2.939999999999998,\n",
       "  64.0,\n",
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       "  3.3743999999999983,\n",
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       "  0.0,\n",
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       "  0.0,\n",
       "  8.459399999999995,\n",
       "  0.5171999999999999,\n",
       "  0.0,\n",
       "  4.2412,\n",
       "  6.053399999999997,\n",
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       "  3.7754000000000025,\n",
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       "  13.089,\n",
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       "  3.8899999999999966,\n",
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      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_dict"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "------------------------------------------------------------------------------------------------------------------------------"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Merging X_train + X_test with Y_train + Y_test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "merged_X = pd.concat([X_train, X_test])\n",
    "merged_Y = pd.concat([y_train, y_test])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "merged_df = pd.concat([merged_X, merged_Y], axis = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "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>Clicks</th>\n",
       "      <th>Impressions</th>\n",
       "      <th>Position</th>\n",
       "      <th>CTR</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>703</th>\n",
       "      <td>-0.125275</td>\n",
       "      <td>-0.237756</td>\n",
       "      <td>-0.931010</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>311</th>\n",
       "      <td>-0.100183</td>\n",
       "      <td>-0.051416</td>\n",
       "      <td>-0.256306</td>\n",
       "      <td>1.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>722</th>\n",
       "      <td>-0.125275</td>\n",
       "      <td>-0.240418</td>\n",
       "      <td>0.568934</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>629</th>\n",
       "      <td>-0.125275</td>\n",
       "      <td>-0.205812</td>\n",
       "      <td>-0.714698</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>18.618823</td>\n",
       "      <td>21.433572</td>\n",
       "      <td>0.025781</td>\n",
       "      <td>9.16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>316</th>\n",
       "      <td>-0.100183</td>\n",
       "      <td>-0.078036</td>\n",
       "      <td>-0.101023</td>\n",
       "      <td>1.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>706</th>\n",
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       "      <td>-0.237756</td>\n",
       "      <td>0.145803</td>\n",
       "      <td>0.00</td>\n",
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       "    <tr>\n",
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       "      <td>-0.125275</td>\n",
       "      <td>-0.144586</td>\n",
       "      <td>3.809544</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>872</th>\n",
       "      <td>-0.125275</td>\n",
       "      <td>-0.264376</td>\n",
       "      <td>0.491631</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>532</th>\n",
       "      <td>-0.125275</td>\n",
       "      <td>-0.125952</td>\n",
       "      <td>0.269216</td>\n",
       "      <td>0.00</td>\n",
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       "    <tr>\n",
       "      <th>477</th>\n",
       "      <td>-0.100183</td>\n",
       "      <td>-0.280348</td>\n",
       "      <td>-0.990682</td>\n",
       "      <td>100.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>404</th>\n",
       "      <td>-0.100183</td>\n",
       "      <td>-0.216460</td>\n",
       "      <td>0.517399</td>\n",
       "      <td>4.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Clicks  Impressions  Position     CTR\n",
       "703  -0.125275    -0.237756 -0.931010    0.00\n",
       "311  -0.100183    -0.051416 -0.256306    1.15\n",
       "722  -0.125275    -0.240418  0.568934    0.00\n",
       "629  -0.125275    -0.205812 -0.714698    0.00\n",
       "0    18.618823    21.433572  0.025781    9.16\n",
       "316  -0.100183    -0.078036 -0.101023    1.30\n",
       "706  -0.125275    -0.237756  0.145803    0.00\n",
       "547  -0.125275    -0.144586  3.809544    0.00\n",
       "872  -0.125275    -0.264376  0.491631    0.00\n",
       "532  -0.125275    -0.125952  0.269216    0.00\n",
       "477  -0.100183    -0.280348 -0.990682  100.00\n",
       "404  -0.100183    -0.216460  0.517399    4.00"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "merged_df.head(12)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Predicted Data For Click Through Ratio's For All Pages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "predicted_data = pd.DataFrame(data_dict)\n",
    "predicted_data.set_index(predicted_data['Indexes'], inplace = True)\n",
    "predicted_data.drop(columns=['Indexes'], inplace = True)\n",
    "predicted_data.rename(columns={\"Predictions\": \"Predicted_CTR_%\"}, inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .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></th>\n",
       "      <th>Predicted_CTR_%</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Indexes</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>703</th>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>311</th>\n",
       "      <td>1.1460</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>722</th>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>629</th>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10.9958</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>316</th>\n",
       "      <td>1.3014</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Predicted_CTR_%\n",
       "Indexes                 \n",
       "703               0.0000\n",
       "311               1.1460\n",
       "722               0.0000\n",
       "629               0.0000\n",
       "0                10.9958\n",
       "316               1.3014"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "predicted_data.head(6)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "----------------------------------------------------------------------------------------------------------------------------------------"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Merging The Original Dataframe to the predicted CTR (%)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "final_df = pd.concat([merged_df, predicted_data], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Clicks</th>\n",
       "      <th>Impressions</th>\n",
       "      <th>Position</th>\n",
       "      <th>CTR</th>\n",
       "      <th>Predicted_CTR_%</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>703</th>\n",
       "      <td>-0.125275</td>\n",
       "      <td>-0.237756</td>\n",
       "      <td>-0.931010</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>311</th>\n",
       "      <td>-0.100183</td>\n",
       "      <td>-0.051416</td>\n",
       "      <td>-0.256306</td>\n",
       "      <td>1.15</td>\n",
       "      <td>1.1460</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>722</th>\n",
       "      <td>-0.125275</td>\n",
       "      <td>-0.240418</td>\n",
       "      <td>0.568934</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>629</th>\n",
       "      <td>-0.125275</td>\n",
       "      <td>-0.205812</td>\n",
       "      <td>-0.714698</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>18.618823</td>\n",
       "      <td>21.433572</td>\n",
       "      <td>0.025781</td>\n",
       "      <td>9.16</td>\n",
       "      <td>10.9958</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>316</th>\n",
       "      <td>-0.100183</td>\n",
       "      <td>-0.078036</td>\n",
       "      <td>-0.101023</td>\n",
       "      <td>1.30</td>\n",
       "      <td>1.3014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>706</th>\n",
       "      <td>-0.125275</td>\n",
       "      <td>-0.237756</td>\n",
       "      <td>0.145803</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>547</th>\n",
       "      <td>-0.125275</td>\n",
       "      <td>-0.144586</td>\n",
       "      <td>3.809544</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>872</th>\n",
       "      <td>-0.125275</td>\n",
       "      <td>-0.264376</td>\n",
       "      <td>0.491631</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>532</th>\n",
       "      <td>-0.125275</td>\n",
       "      <td>-0.125952</td>\n",
       "      <td>0.269216</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>477</th>\n",
       "      <td>-0.100183</td>\n",
       "      <td>-0.280348</td>\n",
       "      <td>-0.990682</td>\n",
       "      <td>100.00</td>\n",
       "      <td>100.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>404</th>\n",
       "      <td>-0.100183</td>\n",
       "      <td>-0.216460</td>\n",
       "      <td>0.517399</td>\n",
       "      <td>4.00</td>\n",
       "      <td>4.0316</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172</th>\n",
       "      <td>-0.049998</td>\n",
       "      <td>0.422419</td>\n",
       "      <td>-0.765555</td>\n",
       "      <td>1.13</td>\n",
       "      <td>1.1402</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125</th>\n",
       "      <td>0.000187</td>\n",
       "      <td>0.076360</td>\n",
       "      <td>0.211578</td>\n",
       "      <td>3.70</td>\n",
       "      <td>3.7334</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>394</th>\n",
       "      <td>-0.100183</td>\n",
       "      <td>-0.211136</td>\n",
       "      <td>-1.065950</td>\n",
       "      <td>3.70</td>\n",
       "      <td>3.6526</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>420</th>\n",
       "      <td>-0.100183</td>\n",
       "      <td>-0.235094</td>\n",
       "      <td>0.557406</td>\n",
       "      <td>5.56</td>\n",
       "      <td>5.5882</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>552</th>\n",
       "      <td>-0.125275</td>\n",
       "      <td>-0.149910</td>\n",
       "      <td>-0.465837</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>903</th>\n",
       "      <td>-0.125275</td>\n",
       "      <td>-0.269700</td>\n",
       "      <td>-1.072053</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>0.050372</td>\n",
       "      <td>0.124276</td>\n",
       "      <td>0.844240</td>\n",
       "      <td>4.58</td>\n",
       "      <td>4.5556</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>939</th>\n",
       "      <td>-0.125275</td>\n",
       "      <td>-0.269700</td>\n",
       "      <td>1.667446</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>181</th>\n",
       "      <td>-0.049998</td>\n",
       "      <td>0.073698</td>\n",
       "      <td>-0.326150</td>\n",
       "      <td>2.24</td>\n",
       "      <td>2.1862</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>274</th>\n",
       "      <td>-0.075090</td>\n",
       "      <td>-0.219122</td>\n",
       "      <td>-0.428542</td>\n",
       "      <td>8.33</td>\n",
       "      <td>8.1832</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>895</th>\n",
       "      <td>-0.125275</td>\n",
       "      <td>-0.267038</td>\n",
       "      <td>0.953413</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>0.100557</td>\n",
       "      <td>0.986763</td>\n",
       "      <td>1.672192</td>\n",
       "      <td>1.89</td>\n",
       "      <td>1.7772</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>291</th>\n",
       "      <td>-0.100183</td>\n",
       "      <td>0.214784</td>\n",
       "      <td>0.208188</td>\n",
       "      <td>0.53</td>\n",
       "      <td>0.5866</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>131</th>\n",
       "      <td>0.000187</td>\n",
       "      <td>-0.112642</td>\n",
       "      <td>-0.597387</td>\n",
       "      <td>7.81</td>\n",
       "      <td>7.8568</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>300</th>\n",
       "      <td>-0.100183</td>\n",
       "      <td>0.015134</td>\n",
       "      <td>1.607774</td>\n",
       "      <td>0.89</td>\n",
       "      <td>0.9014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>424</th>\n",
       "      <td>-0.100183</td>\n",
       "      <td>-0.237756</td>\n",
       "      <td>0.381780</td>\n",
       "      <td>5.88</td>\n",
       "      <td>5.8786</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>326</th>\n",
       "      <td>-0.100183</td>\n",
       "      <td>-0.112642</td>\n",
       "      <td>-0.615696</td>\n",
       "      <td>1.56</td>\n",
       "      <td>1.5548</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>144</th>\n",
       "      <td>-0.024905</td>\n",
       "      <td>0.100318</td>\n",
       "      <td>0.028493</td>\n",
       "      <td>2.78</td>\n",
       "      <td>3.0032</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>541</th>\n",
       "      <td>-0.125275</td>\n",
       "      <td>-0.139262</td>\n",
       "      <td>1.342639</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>440</th>\n",
       "      <td>-0.100183</td>\n",
       "      <td>-0.251066</td>\n",
       "      <td>0.088843</td>\n",
       "      <td>8.33</td>\n",
       "      <td>9.2416</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>482</th>\n",
       "      <td>-0.125275</td>\n",
       "      <td>0.257376</td>\n",
       "      <td>1.697960</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>422</th>\n",
       "      <td>-0.100183</td>\n",
       "      <td>-0.237756</td>\n",
       "      <td>-0.886934</td>\n",
       "      <td>5.88</td>\n",
       "      <td>6.0128</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>778</th>\n",
       "      <td>-0.125275</td>\n",
       "      <td>-0.251066</td>\n",
       "      <td>-0.747924</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>949</th>\n",
       "      <td>-0.125275</td>\n",
       "      <td>-0.272362</td>\n",
       "      <td>-1.228015</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>334</th>\n",
       "      <td>-0.100183</td>\n",
       "      <td>-0.131276</td>\n",
       "      <td>-0.550599</td>\n",
       "      <td>1.75</td>\n",
       "      <td>1.7782</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>576</th>\n",
       "      <td>-0.125275</td>\n",
       "      <td>-0.171206</td>\n",
       "      <td>1.608452</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>934</th>\n",
       "      <td>-0.125275</td>\n",
       "      <td>-0.269700</td>\n",
       "      <td>0.948666</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>567</th>\n",
       "      <td>-0.125275</td>\n",
       "      <td>-0.163220</td>\n",
       "      <td>-0.855063</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>594</th>\n",
       "      <td>-0.125275</td>\n",
       "      <td>-0.187178</td>\n",
       "      <td>1.900710</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>530</th>\n",
       "      <td>-0.125275</td>\n",
       "      <td>-0.117966</td>\n",
       "      <td>-0.432611</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>581</th>\n",
       "      <td>-0.125275</td>\n",
       "      <td>-0.176530</td>\n",
       "      <td>1.636932</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>707</th>\n",
       "      <td>-0.125275</td>\n",
       "      <td>-0.237756</td>\n",
       "      <td>0.309902</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>448</th>\n",
       "      <td>-0.100183</td>\n",
       "      <td>-0.256390</td>\n",
       "      <td>0.006116</td>\n",
       "      <td>10.00</td>\n",
       "      <td>9.8908</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>453</th>\n",
       "      <td>-0.100183</td>\n",
       "      <td>-0.264376</td>\n",
       "      <td>-1.067985</td>\n",
       "      <td>14.29</td>\n",
       "      <td>15.7118</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>228</th>\n",
       "      <td>-0.075090</td>\n",
       "      <td>0.603435</td>\n",
       "      <td>1.866805</td>\n",
       "      <td>0.60</td>\n",
       "      <td>0.6872</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>352</th>\n",
       "      <td>-0.100183</td>\n",
       "      <td>-0.163220</td>\n",
       "      <td>-0.933722</td>\n",
       "      <td>2.22</td>\n",
       "      <td>2.2584</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>728</th>\n",
       "      <td>-0.125275</td>\n",
       "      <td>-0.243080</td>\n",
       "      <td>-1.185295</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>212</th>\n",
       "      <td>-0.049998</td>\n",
       "      <td>-0.165882</td>\n",
       "      <td>-1.030689</td>\n",
       "      <td>6.82</td>\n",
       "      <td>7.9980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>0.075465</td>\n",
       "      <td>0.214784</td>\n",
       "      <td>0.282100</td>\n",
       "      <td>4.28</td>\n",
       "      <td>4.9560</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>-0.024905</td>\n",
       "      <td>0.007148</td>\n",
       "      <td>-0.305129</td>\n",
       "      <td>3.67</td>\n",
       "      <td>4.1132</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>302</th>\n",
       "      <td>-0.100183</td>\n",
       "      <td>-0.016810</td>\n",
       "      <td>-0.061015</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.0784</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>628</th>\n",
       "      <td>-0.125275</td>\n",
       "      <td>-0.205812</td>\n",
       "      <td>-0.869303</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>777</th>\n",
       "      <td>-0.125275</td>\n",
       "      <td>-0.251066</td>\n",
       "      <td>-0.770301</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>506</th>\n",
       "      <td>-0.125275</td>\n",
       "      <td>-0.062064</td>\n",
       "      <td>0.305833</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>342</th>\n",
       "      <td>-0.100183</td>\n",
       "      <td>-0.149910</td>\n",
       "      <td>-0.341068</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.0256</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>485</th>\n",
       "      <td>-0.125275</td>\n",
       "      <td>0.196150</td>\n",
       "      <td>2.980235</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>711</th>\n",
       "      <td>-0.125275</td>\n",
       "      <td>-0.237756</td>\n",
       "      <td>3.137553</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133</th>\n",
       "      <td>0.000187</td>\n",
       "      <td>-0.133938</td>\n",
       "      <td>-0.303095</td>\n",
       "      <td>8.93</td>\n",
       "      <td>7.8694</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1000 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        Clicks  Impressions  Position     CTR  Predicted_CTR_%\n",
       "703  -0.125275    -0.237756 -0.931010    0.00           0.0000\n",
       "311  -0.100183    -0.051416 -0.256306    1.15           1.1460\n",
       "722  -0.125275    -0.240418  0.568934    0.00           0.0000\n",
       "629  -0.125275    -0.205812 -0.714698    0.00           0.0000\n",
       "0    18.618823    21.433572  0.025781    9.16          10.9958\n",
       "316  -0.100183    -0.078036 -0.101023    1.30           1.3014\n",
       "706  -0.125275    -0.237756  0.145803    0.00           0.0000\n",
       "547  -0.125275    -0.144586  3.809544    0.00           0.0000\n",
       "872  -0.125275    -0.264376  0.491631    0.00           0.0000\n",
       "532  -0.125275    -0.125952  0.269216    0.00           0.0000\n",
       "477  -0.100183    -0.280348 -0.990682  100.00         100.0000\n",
       "404  -0.100183    -0.216460  0.517399    4.00           4.0316\n",
       "172  -0.049998     0.422419 -0.765555    1.13           1.1402\n",
       "125   0.000187     0.076360  0.211578    3.70           3.7334\n",
       "394  -0.100183    -0.211136 -1.065950    3.70           3.6526\n",
       "420  -0.100183    -0.235094  0.557406    5.56           5.5882\n",
       "552  -0.125275    -0.149910 -0.465837    0.00           0.0000\n",
       "903  -0.125275    -0.269700 -1.072053    0.00           0.0000\n",
       "90    0.050372     0.124276  0.844240    4.58           4.5556\n",
       "939  -0.125275    -0.269700  1.667446    0.00           0.0000\n",
       "181  -0.049998     0.073698 -0.326150    2.24           2.1862\n",
       "274  -0.075090    -0.219122 -0.428542    8.33           8.1832\n",
       "895  -0.125275    -0.267038  0.953413    0.00           0.0000\n",
       "69    0.100557     0.986763  1.672192    1.89           1.7772\n",
       "291  -0.100183     0.214784  0.208188    0.53           0.5866\n",
       "131   0.000187    -0.112642 -0.597387    7.81           7.8568\n",
       "300  -0.100183     0.015134  1.607774    0.89           0.9014\n",
       "424  -0.100183    -0.237756  0.381780    5.88           5.8786\n",
       "326  -0.100183    -0.112642 -0.615696    1.56           1.5548\n",
       "144  -0.024905     0.100318  0.028493    2.78           3.0032\n",
       "..         ...          ...       ...     ...              ...\n",
       "541  -0.125275    -0.139262  1.342639    0.00           0.0000\n",
       "440  -0.100183    -0.251066  0.088843    8.33           9.2416\n",
       "482  -0.125275     0.257376  1.697960    0.00           0.0000\n",
       "422  -0.100183    -0.237756 -0.886934    5.88           6.0128\n",
       "778  -0.125275    -0.251066 -0.747924    0.00           0.0000\n",
       "949  -0.125275    -0.272362 -1.228015    0.00           0.0000\n",
       "334  -0.100183    -0.131276 -0.550599    1.75           1.7782\n",
       "576  -0.125275    -0.171206  1.608452    0.00           0.0000\n",
       "934  -0.125275    -0.269700  0.948666    0.00           0.0000\n",
       "567  -0.125275    -0.163220 -0.855063    0.00           0.0000\n",
       "594  -0.125275    -0.187178  1.900710    0.00           0.0000\n",
       "530  -0.125275    -0.117966 -0.432611    0.00           0.0000\n",
       "581  -0.125275    -0.176530  1.636932    0.00           0.0000\n",
       "707  -0.125275    -0.237756  0.309902    0.00           0.0000\n",
       "448  -0.100183    -0.256390  0.006116   10.00           9.8908\n",
       "453  -0.100183    -0.264376 -1.067985   14.29          15.7118\n",
       "228  -0.075090     0.603435  1.866805    0.60           0.6872\n",
       "352  -0.100183    -0.163220 -0.933722    2.22           2.2584\n",
       "728  -0.125275    -0.243080 -1.185295    0.00           0.0000\n",
       "212  -0.049998    -0.165882 -1.030689    6.82           7.9980\n",
       "79    0.075465     0.214784  0.282100    4.28           4.9560\n",
       "148  -0.024905     0.007148 -0.305129    3.67           4.1132\n",
       "302  -0.100183    -0.016810 -0.061015    1.00           1.0784\n",
       "628  -0.125275    -0.205812 -0.869303    0.00           0.0000\n",
       "777  -0.125275    -0.251066 -0.770301    0.00           0.0000\n",
       "506  -0.125275    -0.062064  0.305833    0.00           0.0000\n",
       "342  -0.100183    -0.149910 -0.341068    2.00           2.0256\n",
       "485  -0.125275     0.196150  2.980235    0.00           0.0000\n",
       "711  -0.125275    -0.237756  3.137553    0.00           0.0000\n",
       "133   0.000187    -0.133938 -0.303095    8.93           7.8694\n",
       "\n",
       "[1000 rows x 5 columns]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "final_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "final_df['CTR_Difference'] = final_df['Predicted_CTR_%'] - final_df['CTR']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "### Now let's subset on the data and remove any CTR's that were 0.00"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "final_df = final_df[final_df['CTR'] != 0.00]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "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>Clicks</th>\n",
       "      <th>Impressions</th>\n",
       "      <th>Position</th>\n",
       "      <th>CTR</th>\n",
       "      <th>Predicted_CTR_%</th>\n",
       "      <th>CTR_Difference</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>469</th>\n",
       "      <td>-0.100183</td>\n",
       "      <td>-0.277686</td>\n",
       "      <td>-1.397538</td>\n",
       "      <td>50.00</td>\n",
       "      <td>67.0000</td>\n",
       "      <td>17.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>6.097665</td>\n",
       "      <td>22.663415</td>\n",
       "      <td>0.560797</td>\n",
       "      <td>2.88</td>\n",
       "      <td>9.5460</td>\n",
       "      <td>6.6660</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>10.664500</td>\n",
       "      <td>9.792653</td>\n",
       "      <td>-0.732328</td>\n",
       "      <td>11.36</td>\n",
       "      <td>17.5800</td>\n",
       "      <td>6.2200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1.154442</td>\n",
       "      <td>1.966378</td>\n",
       "      <td>-0.885577</td>\n",
       "      <td>6.04</td>\n",
       "      <td>9.5606</td>\n",
       "      <td>3.5206</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>1.104257</td>\n",
       "      <td>1.827954</td>\n",
       "      <td>-0.533647</td>\n",
       "      <td>6.18</td>\n",
       "      <td>9.2682</td>\n",
       "      <td>3.0882</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1.581015</td>\n",
       "      <td>2.836852</td>\n",
       "      <td>-0.807597</td>\n",
       "      <td>5.80</td>\n",
       "      <td>8.4918</td>\n",
       "      <td>2.6918</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>18.618823</td>\n",
       "      <td>21.433572</td>\n",
       "      <td>0.025781</td>\n",
       "      <td>9.16</td>\n",
       "      <td>10.9958</td>\n",
       "      <td>1.8358</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>0.778055</td>\n",
       "      <td>2.227254</td>\n",
       "      <td>-0.781151</td>\n",
       "      <td>3.82</td>\n",
       "      <td>5.5824</td>\n",
       "      <td>1.7624</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>455</th>\n",
       "      <td>-0.100183</td>\n",
       "      <td>-0.267038</td>\n",
       "      <td>0.026459</td>\n",
       "      <td>16.67</td>\n",
       "      <td>18.1542</td>\n",
       "      <td>1.4842</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>453</th>\n",
       "      <td>-0.100183</td>\n",
       "      <td>-0.264376</td>\n",
       "      <td>-1.067985</td>\n",
       "      <td>14.29</td>\n",
       "      <td>15.7118</td>\n",
       "      <td>1.4218</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>0.075465</td>\n",
       "      <td>0.233418</td>\n",
       "      <td>-0.520085</td>\n",
       "      <td>4.12</td>\n",
       "      <td>5.4076</td>\n",
       "      <td>1.2876</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>0.175835</td>\n",
       "      <td>0.222770</td>\n",
       "      <td>-0.682149</td>\n",
       "      <td>6.32</td>\n",
       "      <td>7.5926</td>\n",
       "      <td>1.2726</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>0.878425</td>\n",
       "      <td>2.067534</td>\n",
       "      <td>0.250908</td>\n",
       "      <td>4.53</td>\n",
       "      <td>5.7216</td>\n",
       "      <td>1.1916</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>212</th>\n",
       "      <td>-0.049998</td>\n",
       "      <td>-0.165882</td>\n",
       "      <td>-1.030689</td>\n",
       "      <td>6.82</td>\n",
       "      <td>7.9980</td>\n",
       "      <td>1.1780</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>439</th>\n",
       "      <td>-0.100183</td>\n",
       "      <td>-0.251066</td>\n",
       "      <td>-0.832686</td>\n",
       "      <td>8.33</td>\n",
       "      <td>9.3084</td>\n",
       "      <td>0.9784</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>452</th>\n",
       "      <td>-0.100183</td>\n",
       "      <td>-0.261714</td>\n",
       "      <td>-0.193922</td>\n",
       "      <td>12.50</td>\n",
       "      <td>13.4354</td>\n",
       "      <td>0.9354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>440</th>\n",
       "      <td>-0.100183</td>\n",
       "      <td>-0.251066</td>\n",
       "      <td>0.088843</td>\n",
       "      <td>8.33</td>\n",
       "      <td>9.2416</td>\n",
       "      <td>0.9116</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1.355182</td>\n",
       "      <td>1.359443</td>\n",
       "      <td>-0.873372</td>\n",
       "      <td>9.56</td>\n",
       "      <td>10.4416</td>\n",
       "      <td>0.8816</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>0.652592</td>\n",
       "      <td>1.854574</td>\n",
       "      <td>0.086131</td>\n",
       "      <td>3.86</td>\n",
       "      <td>4.6490</td>\n",
       "      <td>0.7890</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>0.552222</td>\n",
       "      <td>1.324837</td>\n",
       "      <td>-0.387856</td>\n",
       "      <td>4.47</td>\n",
       "      <td>5.2490</td>\n",
       "      <td>0.7790</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>451</th>\n",
       "      <td>-0.100183</td>\n",
       "      <td>-0.261714</td>\n",
       "      <td>-0.566873</td>\n",
       "      <td>12.50</td>\n",
       "      <td>13.2460</td>\n",
       "      <td>0.7460</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>454</th>\n",
       "      <td>-0.100183</td>\n",
       "      <td>-0.264376</td>\n",
       "      <td>0.588599</td>\n",
       "      <td>14.29</td>\n",
       "      <td>15.0008</td>\n",
       "      <td>0.7108</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84</th>\n",
       "      <td>0.050372</td>\n",
       "      <td>2.304452</td>\n",
       "      <td>-1.333797</td>\n",
       "      <td>0.72</td>\n",
       "      <td>1.4264</td>\n",
       "      <td>0.7064</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>0.075465</td>\n",
       "      <td>0.715239</td>\n",
       "      <td>1.426722</td>\n",
       "      <td>2.13</td>\n",
       "      <td>2.8340</td>\n",
       "      <td>0.7040</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>1.054072</td>\n",
       "      <td>1.173103</td>\n",
       "      <td>-0.395316</td>\n",
       "      <td>8.59</td>\n",
       "      <td>9.2894</td>\n",
       "      <td>0.6994</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>0.075465</td>\n",
       "      <td>0.214784</td>\n",
       "      <td>0.282100</td>\n",
       "      <td>4.28</td>\n",
       "      <td>4.9560</td>\n",
       "      <td>0.6760</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>265</th>\n",
       "      <td>-0.075090</td>\n",
       "      <td>-0.195164</td>\n",
       "      <td>-0.951352</td>\n",
       "      <td>6.06</td>\n",
       "      <td>6.6844</td>\n",
       "      <td>0.6244</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>0.100557</td>\n",
       "      <td>0.776465</td>\n",
       "      <td>-1.395504</td>\n",
       "      <td>2.26</td>\n",
       "      <td>2.8560</td>\n",
       "      <td>0.5960</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>0.978795</td>\n",
       "      <td>1.306203</td>\n",
       "      <td>-0.066440</td>\n",
       "      <td>7.37</td>\n",
       "      <td>7.8870</td>\n",
       "      <td>0.5170</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158</th>\n",
       "      <td>-0.024905</td>\n",
       "      <td>-0.128614</td>\n",
       "      <td>-0.880831</td>\n",
       "      <td>6.90</td>\n",
       "      <td>7.4118</td>\n",
       "      <td>0.5118</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>22</th>\n",
       "      <td>0.627500</td>\n",
       "      <td>0.531561</td>\n",
       "      <td>-0.646210</td>\n",
       "      <td>9.80</td>\n",
       "      <td>8.8644</td>\n",
       "      <td>-0.9356</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>473</th>\n",
       "      <td>-0.100183</td>\n",
       "      <td>-0.280348</td>\n",
       "      <td>-1.329729</td>\n",
       "      <td>100.00</td>\n",
       "      <td>99.0000</td>\n",
       "      <td>-1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>471</th>\n",
       "      <td>-0.100183</td>\n",
       "      <td>-0.280348</td>\n",
       "      <td>-1.397538</td>\n",
       "      <td>100.00</td>\n",
       "      <td>99.0000</td>\n",
       "      <td>-1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>470</th>\n",
       "      <td>-0.100183</td>\n",
       "      <td>-0.280348</td>\n",
       "      <td>-1.397538</td>\n",
       "      <td>100.00</td>\n",
       "      <td>99.0000</td>\n",
       "      <td>-1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>472</th>\n",
       "      <td>-0.100183</td>\n",
       "      <td>-0.280348</td>\n",
       "      <td>-1.397538</td>\n",
       "      <td>100.00</td>\n",
       "      <td>99.0000</td>\n",
       "      <td>-1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>0.175835</td>\n",
       "      <td>-0.014148</td>\n",
       "      <td>-0.790644</td>\n",
       "      <td>11.88</td>\n",
       "      <td>10.8726</td>\n",
       "      <td>-1.0074</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133</th>\n",
       "      <td>0.000187</td>\n",
       "      <td>-0.133938</td>\n",
       "      <td>-0.303095</td>\n",
       "      <td>8.93</td>\n",
       "      <td>7.8694</td>\n",
       "      <td>-1.0606</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112</th>\n",
       "      <td>0.025280</td>\n",
       "      <td>-0.157896</td>\n",
       "      <td>-0.471262</td>\n",
       "      <td>12.77</td>\n",
       "      <td>11.5860</td>\n",
       "      <td>-1.1840</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>468</th>\n",
       "      <td>-0.100183</td>\n",
       "      <td>-0.275024</td>\n",
       "      <td>2.241791</td>\n",
       "      <td>33.33</td>\n",
       "      <td>32.1304</td>\n",
       "      <td>-1.1996</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>0.276205</td>\n",
       "      <td>0.118952</td>\n",
       "      <td>-0.394637</td>\n",
       "      <td>10.60</td>\n",
       "      <td>9.3826</td>\n",
       "      <td>-1.2174</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>0.727870</td>\n",
       "      <td>0.446377</td>\n",
       "      <td>-0.311232</td>\n",
       "      <td>12.41</td>\n",
       "      <td>11.1254</td>\n",
       "      <td>-1.2846</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>462</th>\n",
       "      <td>-0.100183</td>\n",
       "      <td>-0.272362</td>\n",
       "      <td>2.060740</td>\n",
       "      <td>25.00</td>\n",
       "      <td>23.7000</td>\n",
       "      <td>-1.3000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>0.602407</td>\n",
       "      <td>0.550195</td>\n",
       "      <td>0.553338</td>\n",
       "      <td>9.27</td>\n",
       "      <td>7.9304</td>\n",
       "      <td>-1.3396</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>0.502037</td>\n",
       "      <td>1.114539</td>\n",
       "      <td>0.394664</td>\n",
       "      <td>4.76</td>\n",
       "      <td>3.2810</td>\n",
       "      <td>-1.4790</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2.133050</td>\n",
       "      <td>2.056886</td>\n",
       "      <td>-0.438035</td>\n",
       "      <td>10.24</td>\n",
       "      <td>8.6478</td>\n",
       "      <td>-1.5922</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>222</th>\n",
       "      <td>-0.049998</td>\n",
       "      <td>-0.240418</td>\n",
       "      <td>-0.528900</td>\n",
       "      <td>18.75</td>\n",
       "      <td>17.1084</td>\n",
       "      <td>-1.6416</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>284</th>\n",
       "      <td>-0.075090</td>\n",
       "      <td>-0.251066</td>\n",
       "      <td>-0.131537</td>\n",
       "      <td>16.67</td>\n",
       "      <td>14.8870</td>\n",
       "      <td>-1.7830</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>220</th>\n",
       "      <td>-0.049998</td>\n",
       "      <td>-0.224446</td>\n",
       "      <td>0.627250</td>\n",
       "      <td>13.64</td>\n",
       "      <td>11.7290</td>\n",
       "      <td>-1.9110</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>0.451852</td>\n",
       "      <td>0.435729</td>\n",
       "      <td>-0.067118</td>\n",
       "      <td>8.52</td>\n",
       "      <td>6.5362</td>\n",
       "      <td>-1.9838</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>0.401667</td>\n",
       "      <td>0.241404</td>\n",
       "      <td>-0.731650</td>\n",
       "      <td>10.66</td>\n",
       "      <td>8.6038</td>\n",
       "      <td>-2.0562</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>0.778055</td>\n",
       "      <td>0.310615</td>\n",
       "      <td>-1.120876</td>\n",
       "      <td>16.14</td>\n",
       "      <td>14.0056</td>\n",
       "      <td>-2.1344</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>221</th>\n",
       "      <td>-0.049998</td>\n",
       "      <td>-0.227108</td>\n",
       "      <td>-0.067118</td>\n",
       "      <td>14.29</td>\n",
       "      <td>12.0720</td>\n",
       "      <td>-2.2180</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>223</th>\n",
       "      <td>-0.049998</td>\n",
       "      <td>-0.243080</td>\n",
       "      <td>-0.914057</td>\n",
       "      <td>20.00</td>\n",
       "      <td>17.7612</td>\n",
       "      <td>-2.2388</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113</th>\n",
       "      <td>0.025280</td>\n",
       "      <td>-0.181854</td>\n",
       "      <td>0.634709</td>\n",
       "      <td>15.79</td>\n",
       "      <td>13.4276</td>\n",
       "      <td>-2.3624</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>0.451852</td>\n",
       "      <td>0.353207</td>\n",
       "      <td>-0.008124</td>\n",
       "      <td>9.62</td>\n",
       "      <td>6.7740</td>\n",
       "      <td>-2.8460</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>0.125650</td>\n",
       "      <td>-0.088684</td>\n",
       "      <td>-0.379719</td>\n",
       "      <td>13.70</td>\n",
       "      <td>9.2522</td>\n",
       "      <td>-4.4478</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>0.100557</td>\n",
       "      <td>-0.109980</td>\n",
       "      <td>-0.103735</td>\n",
       "      <td>13.85</td>\n",
       "      <td>8.6944</td>\n",
       "      <td>-5.1556</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>165</th>\n",
       "      <td>-0.024905</td>\n",
       "      <td>-0.219122</td>\n",
       "      <td>-0.320725</td>\n",
       "      <td>16.67</td>\n",
       "      <td>11.0094</td>\n",
       "      <td>-5.6606</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>17.012903</td>\n",
       "      <td>8.144876</td>\n",
       "      <td>-0.637395</td>\n",
       "      <td>21.57</td>\n",
       "      <td>15.5190</td>\n",
       "      <td>-6.0510</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>0.050372</td>\n",
       "      <td>-0.208474</td>\n",
       "      <td>1.140567</td>\n",
       "      <td>25.00</td>\n",
       "      <td>14.1932</td>\n",
       "      <td>-10.8068</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>479 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        Clicks  Impressions  Position     CTR  Predicted_CTR_%  CTR_Difference\n",
       "469  -0.100183    -0.277686 -1.397538   50.00          67.0000         17.0000\n",
       "3     6.097665    22.663415  0.560797    2.88           9.5460          6.6660\n",
       "2    10.664500     9.792653 -0.732328   11.36          17.5800          6.2200\n",
       "9     1.154442     1.966378 -0.885577    6.04           9.5606          3.5206\n",
       "10    1.104257     1.827954 -0.533647    6.18           9.2682          3.0882\n",
       "6     1.581015     2.836852 -0.807597    5.80           8.4918          2.6918\n",
       "0    18.618823    21.433572  0.025781    9.16          10.9958          1.8358\n",
       "17    0.778055     2.227254 -0.781151    3.82           5.5824          1.7624\n",
       "455  -0.100183    -0.267038  0.026459   16.67          18.1542          1.4842\n",
       "453  -0.100183    -0.264376 -1.067985   14.29          15.7118          1.4218\n",
       "78    0.075465     0.233418 -0.520085    4.12           5.4076          1.2876\n",
       "55    0.175835     0.222770 -0.682149    6.32           7.5926          1.2726\n",
       "15    0.878425     2.067534  0.250908    4.53           5.7216          1.1916\n",
       "212  -0.049998    -0.165882 -1.030689    6.82           7.9980          1.1780\n",
       "439  -0.100183    -0.251066 -0.832686    8.33           9.3084          0.9784\n",
       "452  -0.100183    -0.261714 -0.193922   12.50          13.4354          0.9354\n",
       "440  -0.100183    -0.251066  0.088843    8.33           9.2416          0.9116\n",
       "7     1.355182     1.359443 -0.873372    9.56          10.4416          0.8816\n",
       "21    0.652592     1.854574  0.086131    3.86           4.6490          0.7890\n",
       "25    0.552222     1.324837 -0.387856    4.47           5.2490          0.7790\n",
       "451  -0.100183    -0.261714 -0.566873   12.50          13.2460          0.7460\n",
       "454  -0.100183    -0.264376  0.588599   14.29          15.0008          0.7108\n",
       "84    0.050372     2.304452 -1.333797    0.72           1.4264          0.7064\n",
       "77    0.075465     0.715239  1.426722    2.13           2.8340          0.7040\n",
       "12    1.054072     1.173103 -0.395316    8.59           9.2894          0.6994\n",
       "79    0.075465     0.214784  0.282100    4.28           4.9560          0.6760\n",
       "265  -0.075090    -0.195164 -0.951352    6.06           6.6844          0.6244\n",
       "70    0.100557     0.776465 -1.395504    2.26           2.8560          0.5960\n",
       "14    0.978795     1.306203 -0.066440    7.37           7.8870          0.5170\n",
       "158  -0.024905    -0.128614 -0.880831    6.90           7.4118          0.5118\n",
       "..         ...          ...       ...     ...              ...             ...\n",
       "22    0.627500     0.531561 -0.646210    9.80           8.8644         -0.9356\n",
       "473  -0.100183    -0.280348 -1.329729  100.00          99.0000         -1.0000\n",
       "471  -0.100183    -0.280348 -1.397538  100.00          99.0000         -1.0000\n",
       "470  -0.100183    -0.280348 -1.397538  100.00          99.0000         -1.0000\n",
       "472  -0.100183    -0.280348 -1.397538  100.00          99.0000         -1.0000\n",
       "57    0.175835    -0.014148 -0.790644   11.88          10.8726         -1.0074\n",
       "133   0.000187    -0.133938 -0.303095    8.93           7.8694         -1.0606\n",
       "112   0.025280    -0.157896 -0.471262   12.77          11.5860         -1.1840\n",
       "468  -0.100183    -0.275024  2.241791   33.33          32.1304         -1.1996\n",
       "42    0.276205     0.118952 -0.394637   10.60           9.3826         -1.2174\n",
       "20    0.727870     0.446377 -0.311232   12.41          11.1254         -1.2846\n",
       "462  -0.100183    -0.272362  2.060740   25.00          23.7000         -1.3000\n",
       "23    0.602407     0.550195  0.553338    9.27           7.9304         -1.3396\n",
       "29    0.502037     1.114539  0.394664    4.76           3.2810         -1.4790\n",
       "5     2.133050     2.056886 -0.438035   10.24           8.6478         -1.5922\n",
       "222  -0.049998    -0.240418 -0.528900   18.75          17.1084         -1.6416\n",
       "284  -0.075090    -0.251066 -0.131537   16.67          14.8870         -1.7830\n",
       "220  -0.049998    -0.224446  0.627250   13.64          11.7290         -1.9110\n",
       "30    0.451852     0.435729 -0.067118    8.52           6.5362         -1.9838\n",
       "36    0.401667     0.241404 -0.731650   10.66           8.6038         -2.0562\n",
       "18    0.778055     0.310615 -1.120876   16.14          14.0056         -2.1344\n",
       "221  -0.049998    -0.227108 -0.067118   14.29          12.0720         -2.2180\n",
       "223  -0.049998    -0.243080 -0.914057   20.00          17.7612         -2.2388\n",
       "113   0.025280    -0.181854  0.634709   15.79          13.4276         -2.3624\n",
       "31    0.451852     0.353207 -0.008124    9.62           6.7740         -2.8460\n",
       "65    0.125650    -0.088684 -0.379719   13.70           9.2522         -4.4478\n",
       "76    0.100557    -0.109980 -0.103735   13.85           8.6944         -5.1556\n",
       "165  -0.024905    -0.219122 -0.320725   16.67          11.0094         -5.6606\n",
       "1    17.012903     8.144876 -0.637395   21.57          15.5190         -6.0510\n",
       "97    0.050372    -0.208474  1.140567   25.00          14.1932        -10.8068\n",
       "\n",
       "[479 rows x 6 columns]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "final_df.sort_values(by='CTR_Difference', ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "final_df = final_df[['CTR', 'Predicted_CTR_%', 'CTR_Difference']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "original_data = df[['Page', 'Clicks', 'Impressions', 'Position']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "results = pd.merge(original_data, final_df, left_index=True, right_index=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "results.to_csv('results.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "results"
   ]
  }
 ],
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