{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"import pandas\n",
"\n",
"movies = pandas.read_csv(\"fandango_score_comparison.csv\")"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>FILM</th>\n",
" <th>RottenTomatoes</th>\n",
" <th>RottenTomatoes_User</th>\n",
" <th>Metacritic</th>\n",
" <th>Metacritic_User</th>\n",
" <th>IMDB</th>\n",
" <th>Fandango_Stars</th>\n",
" <th>Fandango_Ratingvalue</th>\n",
" <th>RT_norm</th>\n",
" <th>RT_user_norm</th>\n",
" <th>...</th>\n",
" <th>IMDB_norm</th>\n",
" <th>RT_norm_round</th>\n",
" <th>RT_user_norm_round</th>\n",
" <th>Metacritic_norm_round</th>\n",
" <th>Metacritic_user_norm_round</th>\n",
" <th>IMDB_norm_round</th>\n",
" <th>Metacritic_user_vote_count</th>\n",
" <th>IMDB_user_vote_count</th>\n",
" <th>Fandango_votes</th>\n",
" <th>Fandango_Difference</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>Avengers: Age of Ultron (2015)</td>\n",
" <td>74</td>\n",
" <td>86</td>\n",
" <td>66</td>\n",
" <td>7.1</td>\n",
" <td>7.8</td>\n",
" <td>5.0</td>\n",
" <td>4.5</td>\n",
" <td>3.70</td>\n",
" <td>4.30</td>\n",
" <td>...</td>\n",
" <td>3.90</td>\n",
" <td>3.5</td>\n",
" <td>4.5</td>\n",
" <td>3.5</td>\n",
" <td>3.5</td>\n",
" <td>4.0</td>\n",
" <td>1330</td>\n",
" <td>271107</td>\n",
" <td>14846</td>\n",
" <td>0.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>Cinderella (2015)</td>\n",
" <td>85</td>\n",
" <td>80</td>\n",
" <td>67</td>\n",
" <td>7.5</td>\n",
" <td>7.1</td>\n",
" <td>5.0</td>\n",
" <td>4.5</td>\n",
" <td>4.25</td>\n",
" <td>4.00</td>\n",
" <td>...</td>\n",
" <td>3.55</td>\n",
" <td>4.5</td>\n",
" <td>4.0</td>\n",
" <td>3.5</td>\n",
" <td>4.0</td>\n",
" <td>3.5</td>\n",
" <td>249</td>\n",
" <td>65709</td>\n",
" <td>12640</td>\n",
" <td>0.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>Ant-Man (2015)</td>\n",
" <td>80</td>\n",
" <td>90</td>\n",
" <td>64</td>\n",
" <td>8.1</td>\n",
" <td>7.8</td>\n",
" <td>5.0</td>\n",
" <td>4.5</td>\n",
" <td>4.00</td>\n",
" <td>4.50</td>\n",
" <td>...</td>\n",
" <td>3.90</td>\n",
" <td>4.0</td>\n",
" <td>4.5</td>\n",
" <td>3.0</td>\n",
" <td>4.0</td>\n",
" <td>4.0</td>\n",
" <td>627</td>\n",
" <td>103660</td>\n",
" <td>12055</td>\n",
" <td>0.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>Do You Believe? (2015)</td>\n",
" <td>18</td>\n",
" <td>84</td>\n",
" <td>22</td>\n",
" <td>4.7</td>\n",
" <td>5.4</td>\n",
" <td>5.0</td>\n",
" <td>4.5</td>\n",
" <td>0.90</td>\n",
" <td>4.20</td>\n",
" <td>...</td>\n",
" <td>2.70</td>\n",
" <td>1.0</td>\n",
" <td>4.0</td>\n",
" <td>1.0</td>\n",
" <td>2.5</td>\n",
" <td>2.5</td>\n",
" <td>31</td>\n",
" <td>3136</td>\n",
" <td>1793</td>\n",
" <td>0.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>Hot Tub Time Machine 2 (2015)</td>\n",
" <td>14</td>\n",
" <td>28</td>\n",
" <td>29</td>\n",
" <td>3.4</td>\n",
" <td>5.1</td>\n",
" <td>3.5</td>\n",
" <td>3.0</td>\n",
" <td>0.70</td>\n",
" <td>1.40</td>\n",
" <td>...</td>\n",
" <td>2.55</td>\n",
" <td>0.5</td>\n",
" <td>1.5</td>\n",
" <td>1.5</td>\n",
" <td>1.5</td>\n",
" <td>2.5</td>\n",
" <td>88</td>\n",
" <td>19560</td>\n",
" <td>1021</td>\n",
" <td>0.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>The Water Diviner (2015)</td>\n",
" <td>63</td>\n",
" <td>62</td>\n",
" <td>50</td>\n",
" <td>6.8</td>\n",
" <td>7.2</td>\n",
" <td>4.5</td>\n",
" <td>4.0</td>\n",
" <td>3.15</td>\n",
" <td>3.10</td>\n",
" <td>...</td>\n",
" <td>3.60</td>\n",
" <td>3.0</td>\n",
" <td>3.0</td>\n",
" <td>2.5</td>\n",
" <td>3.5</td>\n",
" <td>3.5</td>\n",
" <td>34</td>\n",
" <td>39373</td>\n",
" <td>397</td>\n",
" <td>0.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>Irrational Man (2015)</td>\n",
" <td>42</td>\n",
" <td>53</td>\n",
" <td>53</td>\n",
" <td>7.6</td>\n",
" <td>6.9</td>\n",
" <td>4.0</td>\n",
" <td>3.5</td>\n",
" <td>2.10</td>\n",
" <td>2.65</td>\n",
" <td>...</td>\n",
" <td>3.45</td>\n",
" <td>2.0</td>\n",
" <td>2.5</td>\n",
" <td>2.5</td>\n",
" <td>4.0</td>\n",
" <td>3.5</td>\n",
" <td>17</td>\n",
" <td>2680</td>\n",
" <td>252</td>\n",
" <td>0.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>Top Five (2014)</td>\n",
" <td>86</td>\n",
" <td>64</td>\n",
" <td>81</td>\n",
" <td>6.8</td>\n",
" <td>6.5</td>\n",
" <td>4.0</td>\n",
" <td>3.5</td>\n",
" <td>4.30</td>\n",
" <td>3.20</td>\n",
" <td>...</td>\n",
" <td>3.25</td>\n",
" <td>4.5</td>\n",
" <td>3.0</td>\n",
" <td>4.0</td>\n",
" <td>3.5</td>\n",
" <td>3.5</td>\n",
" <td>124</td>\n",
" <td>16876</td>\n",
" <td>3223</td>\n",
" <td>0.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>Shaun the Sheep Movie (2015)</td>\n",
" <td>99</td>\n",
" <td>82</td>\n",
" <td>81</td>\n",
" <td>8.8</td>\n",
" <td>7.4</td>\n",
" <td>4.5</td>\n",
" <td>4.0</td>\n",
" <td>4.95</td>\n",
" <td>4.10</td>\n",
" <td>...</td>\n",
" <td>3.70</td>\n",
" <td>5.0</td>\n",
" <td>4.0</td>\n",
" <td>4.0</td>\n",
" <td>4.5</td>\n",
" <td>3.5</td>\n",
" <td>62</td>\n",
" <td>12227</td>\n",
" <td>896</td>\n",
" <td>0.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>Love & Mercy (2015)</td>\n",
" <td>89</td>\n",
" <td>87</td>\n",
" <td>80</td>\n",
" <td>8.5</td>\n",
" <td>7.8</td>\n",
" <td>4.5</td>\n",
" <td>4.0</td>\n",
" <td>4.45</td>\n",
" <td>4.35</td>\n",
" <td>...</td>\n",
" <td>3.90</td>\n",
" <td>4.5</td>\n",
" <td>4.5</td>\n",
" <td>4.0</td>\n",
" <td>4.5</td>\n",
" <td>4.0</td>\n",
" <td>54</td>\n",
" <td>5367</td>\n",
" <td>864</td>\n",
" <td>0.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>Far From The Madding Crowd (2015)</td>\n",
" <td>84</td>\n",
" <td>77</td>\n",
" <td>71</td>\n",
" <td>7.5</td>\n",
" <td>7.2</td>\n",
" <td>4.5</td>\n",
" <td>4.0</td>\n",
" <td>4.20</td>\n",
" <td>3.85</td>\n",
" <td>...</td>\n",
" <td>3.60</td>\n",
" <td>4.0</td>\n",
" <td>4.0</td>\n",
" <td>3.5</td>\n",
" <td>4.0</td>\n",
" <td>3.5</td>\n",
" <td>35</td>\n",
" <td>12129</td>\n",
" <td>804</td>\n",
" <td>0.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>Black Sea (2015)</td>\n",
" <td>82</td>\n",
" <td>60</td>\n",
" <td>62</td>\n",
" <td>6.6</td>\n",
" <td>6.4</td>\n",
" <td>4.0</td>\n",
" <td>3.5</td>\n",
" <td>4.10</td>\n",
" <td>3.00</td>\n",
" <td>...</td>\n",
" <td>3.20</td>\n",
" <td>4.0</td>\n",
" <td>3.0</td>\n",
" <td>3.0</td>\n",
" <td>3.5</td>\n",
" <td>3.0</td>\n",
" <td>37</td>\n",
" <td>16547</td>\n",
" <td>218</td>\n",
" <td>0.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>Leviathan (2014)</td>\n",
" <td>99</td>\n",
" <td>79</td>\n",
" <td>92</td>\n",
" <td>7.2</td>\n",
" <td>7.7</td>\n",
" <td>4.0</td>\n",
" <td>3.5</td>\n",
" <td>4.95</td>\n",
" <td>3.95</td>\n",
" <td>...</td>\n",
" <td>3.85</td>\n",
" <td>5.0</td>\n",
" <td>4.0</td>\n",
" <td>4.5</td>\n",
" <td>3.5</td>\n",
" <td>4.0</td>\n",
" <td>145</td>\n",
" <td>22521</td>\n",
" <td>64</td>\n",
" <td>0.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>Unbroken (2014)</td>\n",
" <td>51</td>\n",
" <td>70</td>\n",
" <td>59</td>\n",
" <td>6.5</td>\n",
" <td>7.2</td>\n",
" <td>4.5</td>\n",
" <td>4.1</td>\n",
" <td>2.55</td>\n",
" <td>3.50</td>\n",
" <td>...</td>\n",
" <td>3.60</td>\n",
" <td>2.5</td>\n",
" <td>3.5</td>\n",
" <td>3.0</td>\n",
" <td>3.5</td>\n",
" <td>3.5</td>\n",
" <td>218</td>\n",
" <td>77518</td>\n",
" <td>9443</td>\n",
" <td>0.4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>The Imitation Game (2014)</td>\n",
" <td>90</td>\n",
" <td>92</td>\n",
" <td>73</td>\n",
" <td>8.2</td>\n",
" <td>8.1</td>\n",
" <td>5.0</td>\n",
" <td>4.6</td>\n",
" <td>4.50</td>\n",
" <td>4.60</td>\n",
" <td>...</td>\n",
" <td>4.05</td>\n",
" <td>4.5</td>\n",
" <td>4.5</td>\n",
" <td>3.5</td>\n",
" <td>4.0</td>\n",
" <td>4.0</td>\n",
" <td>566</td>\n",
" <td>334164</td>\n",
" <td>8055</td>\n",
" <td>0.4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>Taken 3 (2015)</td>\n",
" <td>9</td>\n",
" <td>46</td>\n",
" <td>26</td>\n",
" <td>4.6</td>\n",
" <td>6.1</td>\n",
" <td>4.5</td>\n",
" <td>4.1</td>\n",
" <td>0.45</td>\n",
" <td>2.30</td>\n",
" <td>...</td>\n",
" <td>3.05</td>\n",
" <td>0.5</td>\n",
" <td>2.5</td>\n",
" <td>1.5</td>\n",
" <td>2.5</td>\n",
" <td>3.0</td>\n",
" <td>240</td>\n",
" <td>104235</td>\n",
" <td>6757</td>\n",
" <td>0.4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>Ted 2 (2015)</td>\n",
" <td>46</td>\n",
" <td>58</td>\n",
" <td>48</td>\n",
" <td>6.5</td>\n",
" <td>6.6</td>\n",
" <td>4.5</td>\n",
" <td>4.1</td>\n",
" <td>2.30</td>\n",
" <td>2.90</td>\n",
" <td>...</td>\n",
" <td>3.30</td>\n",
" <td>2.5</td>\n",
" <td>3.0</td>\n",
" <td>2.5</td>\n",
" <td>3.5</td>\n",
" <td>3.5</td>\n",
" <td>197</td>\n",
" <td>49102</td>\n",
" <td>6437</td>\n",
" <td>0.4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>Southpaw (2015)</td>\n",
" <td>59</td>\n",
" <td>80</td>\n",
" <td>57</td>\n",
" <td>8.2</td>\n",
" <td>7.8</td>\n",
" <td>5.0</td>\n",
" <td>4.6</td>\n",
" <td>2.95</td>\n",
" <td>4.00</td>\n",
" <td>...</td>\n",
" <td>3.90</td>\n",
" <td>3.0</td>\n",
" <td>4.0</td>\n",
" <td>3.0</td>\n",
" <td>4.0</td>\n",
" <td>4.0</td>\n",
" <td>128</td>\n",
" <td>23561</td>\n",
" <td>5597</td>\n",
" <td>0.4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>Night at the Museum: Secret of the Tomb (2014)</td>\n",
" <td>50</td>\n",
" <td>58</td>\n",
" <td>47</td>\n",
" <td>5.8</td>\n",
" <td>6.3</td>\n",
" <td>4.5</td>\n",
" <td>4.1</td>\n",
" <td>2.50</td>\n",
" <td>2.90</td>\n",
" <td>...</td>\n",
" <td>3.15</td>\n",
" <td>2.5</td>\n",
" <td>3.0</td>\n",
" <td>2.5</td>\n",
" <td>3.0</td>\n",
" <td>3.0</td>\n",
" <td>103</td>\n",
" <td>50291</td>\n",
" <td>5445</td>\n",
" <td>0.4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>Pixels (2015)</td>\n",
" <td>17</td>\n",
" <td>54</td>\n",
" <td>27</td>\n",
" <td>5.3</td>\n",
" <td>5.6</td>\n",
" <td>4.5</td>\n",
" <td>4.1</td>\n",
" <td>0.85</td>\n",
" <td>2.70</td>\n",
" <td>...</td>\n",
" <td>2.80</td>\n",
" <td>1.0</td>\n",
" <td>2.5</td>\n",
" <td>1.5</td>\n",
" <td>2.5</td>\n",
" <td>3.0</td>\n",
" <td>246</td>\n",
" <td>19521</td>\n",
" <td>3886</td>\n",
" <td>0.4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>McFarland, USA (2015)</td>\n",
" <td>79</td>\n",
" <td>89</td>\n",
" <td>60</td>\n",
" <td>7.2</td>\n",
" <td>7.5</td>\n",
" <td>5.0</td>\n",
" <td>4.6</td>\n",
" <td>3.95</td>\n",
" <td>4.45</td>\n",
" <td>...</td>\n",
" <td>3.75</td>\n",
" <td>4.0</td>\n",
" <td>4.5</td>\n",
" <td>3.0</td>\n",
" <td>3.5</td>\n",
" <td>4.0</td>\n",
" <td>59</td>\n",
" <td>13769</td>\n",
" <td>3364</td>\n",
" <td>0.4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>Insidious: Chapter 3 (2015)</td>\n",
" <td>59</td>\n",
" <td>56</td>\n",
" <td>52</td>\n",
" <td>6.9</td>\n",
" <td>6.3</td>\n",
" <td>4.5</td>\n",
" <td>4.1</td>\n",
" <td>2.95</td>\n",
" <td>2.80</td>\n",
" <td>...</td>\n",
" <td>3.15</td>\n",
" <td>3.0</td>\n",
" <td>3.0</td>\n",
" <td>2.5</td>\n",
" <td>3.5</td>\n",
" <td>3.0</td>\n",
" <td>115</td>\n",
" <td>25134</td>\n",
" <td>3276</td>\n",
" <td>0.4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>The Man From U.N.C.L.E. (2015)</td>\n",
" <td>68</td>\n",
" <td>80</td>\n",
" <td>55</td>\n",
" <td>7.9</td>\n",
" <td>7.6</td>\n",
" <td>4.5</td>\n",
" <td>4.1</td>\n",
" <td>3.40</td>\n",
" <td>4.00</td>\n",
" <td>...</td>\n",
" <td>3.80</td>\n",
" <td>3.5</td>\n",
" <td>4.0</td>\n",
" <td>3.0</td>\n",
" <td>4.0</td>\n",
" <td>4.0</td>\n",
" <td>144</td>\n",
" <td>22104</td>\n",
" <td>2686</td>\n",
" <td>0.4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>Run All Night (2015)</td>\n",
" <td>60</td>\n",
" <td>59</td>\n",
" <td>59</td>\n",
" <td>7.3</td>\n",
" <td>6.6</td>\n",
" <td>4.5</td>\n",
" <td>4.1</td>\n",
" <td>3.00</td>\n",
" <td>2.95</td>\n",
" <td>...</td>\n",
" <td>3.30</td>\n",
" <td>3.0</td>\n",
" <td>3.0</td>\n",
" <td>3.0</td>\n",
" <td>3.5</td>\n",
" <td>3.5</td>\n",
" <td>141</td>\n",
" <td>50438</td>\n",
" <td>2066</td>\n",
" <td>0.4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td>Trainwreck (2015)</td>\n",
" <td>85</td>\n",
" <td>74</td>\n",
" <td>75</td>\n",
" <td>6.0</td>\n",
" <td>6.7</td>\n",
" <td>4.5</td>\n",
" <td>4.1</td>\n",
" <td>4.25</td>\n",
" <td>3.70</td>\n",
" <td>...</td>\n",
" <td>3.35</td>\n",
" <td>4.5</td>\n",
" <td>3.5</td>\n",
" <td>4.0</td>\n",
" <td>3.0</td>\n",
" <td>3.5</td>\n",
" <td>169</td>\n",
" <td>27380</td>\n",
" <td>8381</td>\n",
" <td>0.4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25</th>\n",
" <td>Selma (2014)</td>\n",
" <td>99</td>\n",
" <td>86</td>\n",
" <td>89</td>\n",
" <td>7.1</td>\n",
" <td>7.5</td>\n",
" <td>5.0</td>\n",
" <td>4.6</td>\n",
" <td>4.95</td>\n",
" <td>4.30</td>\n",
" <td>...</td>\n",
" <td>3.75</td>\n",
" <td>5.0</td>\n",
" <td>4.5</td>\n",
" <td>4.5</td>\n",
" <td>3.5</td>\n",
" <td>4.0</td>\n",
" <td>316</td>\n",
" <td>45344</td>\n",
" <td>7025</td>\n",
" <td>0.4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
" <td>Ex Machina (2015)</td>\n",
" <td>92</td>\n",
" <td>86</td>\n",
" <td>78</td>\n",
" <td>7.9</td>\n",
" <td>7.7</td>\n",
" <td>4.5</td>\n",
" <td>4.1</td>\n",
" <td>4.60</td>\n",
" <td>4.30</td>\n",
" <td>...</td>\n",
" <td>3.85</td>\n",
" <td>4.5</td>\n",
" <td>4.5</td>\n",
" <td>4.0</td>\n",
" <td>4.0</td>\n",
" <td>4.0</td>\n",
" <td>672</td>\n",
" <td>154499</td>\n",
" <td>3458</td>\n",
" <td>0.4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>27</th>\n",
" <td>Still Alice (2015)</td>\n",
" <td>88</td>\n",
" <td>85</td>\n",
" <td>72</td>\n",
" <td>7.8</td>\n",
" <td>7.5</td>\n",
" <td>4.5</td>\n",
" <td>4.1</td>\n",
" <td>4.40</td>\n",
" <td>4.25</td>\n",
" <td>...</td>\n",
" <td>3.75</td>\n",
" <td>4.5</td>\n",
" <td>4.5</td>\n",
" <td>3.5</td>\n",
" <td>4.0</td>\n",
" <td>4.0</td>\n",
" <td>153</td>\n",
" <td>57123</td>\n",
" <td>1258</td>\n",
" <td>0.4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28</th>\n",
" <td>Wild Tales (2014)</td>\n",
" <td>96</td>\n",
" <td>92</td>\n",
" <td>77</td>\n",
" <td>8.8</td>\n",
" <td>8.2</td>\n",
" <td>4.5</td>\n",
" <td>4.1</td>\n",
" <td>4.80</td>\n",
" <td>4.60</td>\n",
" <td>...</td>\n",
" <td>4.10</td>\n",
" <td>5.0</td>\n",
" <td>4.5</td>\n",
" <td>4.0</td>\n",
" <td>4.5</td>\n",
" <td>4.0</td>\n",
" <td>107</td>\n",
" <td>50285</td>\n",
" <td>235</td>\n",
" <td>0.4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
" <td>The End of the Tour (2015)</td>\n",
" <td>92</td>\n",
" <td>89</td>\n",
" <td>84</td>\n",
" <td>7.5</td>\n",
" <td>7.9</td>\n",
" <td>4.5</td>\n",
" <td>4.1</td>\n",
" <td>4.60</td>\n",
" <td>4.45</td>\n",
" <td>...</td>\n",
" <td>3.95</td>\n",
" <td>4.5</td>\n",
" <td>4.5</td>\n",
" <td>4.0</td>\n",
" <td>4.0</td>\n",
" <td>4.0</td>\n",
" <td>19</td>\n",
" <td>1320</td>\n",
" <td>121</td>\n",
" <td>0.4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>116</th>\n",
" <td>Clouds of Sils Maria (2015)</td>\n",
" <td>89</td>\n",
" <td>67</td>\n",
" <td>78</td>\n",
" <td>7.1</td>\n",
" <td>6.8</td>\n",
" <td>3.5</td>\n",
" <td>3.4</td>\n",
" <td>4.45</td>\n",
" <td>3.35</td>\n",
" <td>...</td>\n",
" <td>3.40</td>\n",
" <td>4.5</td>\n",
" <td>3.5</td>\n",
" <td>4.0</td>\n",
" <td>3.5</td>\n",
" <td>3.5</td>\n",
" <td>36</td>\n",
" <td>11392</td>\n",
" <td>162</td>\n",
" <td>0.1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>117</th>\n",
" <td>Testament of Youth (2015)</td>\n",
" <td>81</td>\n",
" <td>79</td>\n",
" <td>77</td>\n",
" <td>7.9</td>\n",
" <td>7.3</td>\n",
" <td>4.0</td>\n",
" <td>3.9</td>\n",
" <td>4.05</td>\n",
" <td>3.95</td>\n",
" <td>...</td>\n",
" <td>3.65</td>\n",
" <td>4.0</td>\n",
" <td>4.0</td>\n",
" <td>4.0</td>\n",
" <td>4.0</td>\n",
" <td>3.5</td>\n",
" <td>15</td>\n",
" <td>5495</td>\n",
" <td>127</td>\n",
" <td>0.1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>118</th>\n",
" <td>Infinitely Polar Bear (2015)</td>\n",
" <td>80</td>\n",
" <td>76</td>\n",
" <td>64</td>\n",
" <td>7.9</td>\n",
" <td>7.2</td>\n",
" <td>4.0</td>\n",
" <td>3.9</td>\n",
" <td>4.00</td>\n",
" <td>3.80</td>\n",
" <td>...</td>\n",
" <td>3.60</td>\n",
" <td>4.0</td>\n",
" <td>4.0</td>\n",
" <td>3.0</td>\n",
" <td>4.0</td>\n",
" <td>3.5</td>\n",
" <td>8</td>\n",
" <td>1062</td>\n",
" <td>124</td>\n",
" <td>0.1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>119</th>\n",
" <td>Phoenix (2015)</td>\n",
" <td>99</td>\n",
" <td>81</td>\n",
" <td>91</td>\n",
" <td>8.0</td>\n",
" <td>7.2</td>\n",
" <td>3.5</td>\n",
" <td>3.4</td>\n",
" <td>4.95</td>\n",
" <td>4.05</td>\n",
" <td>...</td>\n",
" <td>3.60</td>\n",
" <td>5.0</td>\n",
" <td>4.0</td>\n",
" <td>4.5</td>\n",
" <td>4.0</td>\n",
" <td>3.5</td>\n",
" <td>21</td>\n",
" <td>3687</td>\n",
" <td>70</td>\n",
" <td>0.1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>120</th>\n",
" <td>The Wolfpack (2015)</td>\n",
" <td>84</td>\n",
" <td>73</td>\n",
" <td>75</td>\n",
" <td>7.0</td>\n",
" <td>7.1</td>\n",
" <td>3.5</td>\n",
" <td>3.4</td>\n",
" <td>4.20</td>\n",
" <td>3.65</td>\n",
" <td>...</td>\n",
" <td>3.55</td>\n",
" <td>4.0</td>\n",
" <td>3.5</td>\n",
" <td>4.0</td>\n",
" <td>3.5</td>\n",
" <td>3.5</td>\n",
" <td>8</td>\n",
" <td>1488</td>\n",
" <td>66</td>\n",
" <td>0.1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>121</th>\n",
" <td>The Stanford Prison Experiment (2015)</td>\n",
" <td>84</td>\n",
" <td>87</td>\n",
" <td>68</td>\n",
" <td>8.5</td>\n",
" <td>7.1</td>\n",
" <td>4.0</td>\n",
" <td>3.9</td>\n",
" <td>4.20</td>\n",
" <td>4.35</td>\n",
" <td>...</td>\n",
" <td>3.55</td>\n",
" <td>4.0</td>\n",
" <td>4.5</td>\n",
" <td>3.5</td>\n",
" <td>4.5</td>\n",
" <td>3.5</td>\n",
" <td>6</td>\n",
" <td>950</td>\n",
" <td>51</td>\n",
" <td>0.1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>122</th>\n",
" <td>Tangerine (2015)</td>\n",
" <td>95</td>\n",
" <td>86</td>\n",
" <td>86</td>\n",
" <td>7.3</td>\n",
" <td>7.4</td>\n",
" <td>4.0</td>\n",
" <td>3.9</td>\n",
" <td>4.75</td>\n",
" <td>4.30</td>\n",
" <td>...</td>\n",
" <td>3.70</td>\n",
" <td>5.0</td>\n",
" <td>4.5</td>\n",
" <td>4.5</td>\n",
" <td>3.5</td>\n",
" <td>3.5</td>\n",
" <td>14</td>\n",
" <td>696</td>\n",
" <td>36</td>\n",
" <td>0.1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>123</th>\n",
" <td>Magic Mike XXL (2015)</td>\n",
" <td>62</td>\n",
" <td>64</td>\n",
" <td>60</td>\n",
" <td>5.4</td>\n",
" <td>6.3</td>\n",
" <td>4.5</td>\n",
" <td>4.4</td>\n",
" <td>3.10</td>\n",
" <td>3.20</td>\n",
" <td>...</td>\n",
" <td>3.15</td>\n",
" <td>3.0</td>\n",
" <td>3.0</td>\n",
" <td>3.0</td>\n",
" <td>2.5</td>\n",
" <td>3.0</td>\n",
" <td>52</td>\n",
" <td>11937</td>\n",
" <td>9363</td>\n",
" <td>0.1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>124</th>\n",
" <td>Home (2015)</td>\n",
" <td>45</td>\n",
" <td>65</td>\n",
" <td>55</td>\n",
" <td>7.3</td>\n",
" <td>6.7</td>\n",
" <td>4.5</td>\n",
" <td>4.4</td>\n",
" <td>2.25</td>\n",
" <td>3.25</td>\n",
" <td>...</td>\n",
" <td>3.35</td>\n",
" <td>2.5</td>\n",
" <td>3.5</td>\n",
" <td>3.0</td>\n",
" <td>3.5</td>\n",
" <td>3.5</td>\n",
" <td>177</td>\n",
" <td>41158</td>\n",
" <td>7705</td>\n",
" <td>0.1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>125</th>\n",
" <td>The Wedding Ringer (2015)</td>\n",
" <td>27</td>\n",
" <td>66</td>\n",
" <td>35</td>\n",
" <td>3.3</td>\n",
" <td>6.7</td>\n",
" <td>4.5</td>\n",
" <td>4.4</td>\n",
" <td>1.35</td>\n",
" <td>3.30</td>\n",
" <td>...</td>\n",
" <td>3.35</td>\n",
" <td>1.5</td>\n",
" <td>3.5</td>\n",
" <td>2.0</td>\n",
" <td>1.5</td>\n",
" <td>3.5</td>\n",
" <td>126</td>\n",
" <td>37292</td>\n",
" <td>6506</td>\n",
" <td>0.1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>126</th>\n",
" <td>Woman in Gold (2015)</td>\n",
" <td>52</td>\n",
" <td>81</td>\n",
" <td>51</td>\n",
" <td>7.2</td>\n",
" <td>7.4</td>\n",
" <td>4.5</td>\n",
" <td>4.4</td>\n",
" <td>2.60</td>\n",
" <td>4.05</td>\n",
" <td>...</td>\n",
" <td>3.70</td>\n",
" <td>2.5</td>\n",
" <td>4.0</td>\n",
" <td>2.5</td>\n",
" <td>3.5</td>\n",
" <td>3.5</td>\n",
" <td>72</td>\n",
" <td>17957</td>\n",
" <td>2435</td>\n",
" <td>0.1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>127</th>\n",
" <td>The Last Five Years (2015)</td>\n",
" <td>60</td>\n",
" <td>60</td>\n",
" <td>60</td>\n",
" <td>6.9</td>\n",
" <td>6.0</td>\n",
" <td>4.5</td>\n",
" <td>4.4</td>\n",
" <td>3.00</td>\n",
" <td>3.00</td>\n",
" <td>...</td>\n",
" <td>3.00</td>\n",
" <td>3.0</td>\n",
" <td>3.0</td>\n",
" <td>3.0</td>\n",
" <td>3.5</td>\n",
" <td>3.0</td>\n",
" <td>20</td>\n",
" <td>4110</td>\n",
" <td>99</td>\n",
" <td>0.1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>128</th>\n",
" <td>Mission: Impossible – Rogue Nation (2015)</td>\n",
" <td>92</td>\n",
" <td>90</td>\n",
" <td>75</td>\n",
" <td>8.0</td>\n",
" <td>7.8</td>\n",
" <td>4.5</td>\n",
" <td>4.4</td>\n",
" <td>4.60</td>\n",
" <td>4.50</td>\n",
" <td>...</td>\n",
" <td>3.90</td>\n",
" <td>4.5</td>\n",
" <td>4.5</td>\n",
" <td>4.0</td>\n",
" <td>4.0</td>\n",
" <td>4.0</td>\n",
" <td>362</td>\n",
" <td>82579</td>\n",
" <td>8357</td>\n",
" <td>0.1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>129</th>\n",
" <td>Amy (2015)</td>\n",
" <td>97</td>\n",
" <td>91</td>\n",
" <td>85</td>\n",
" <td>8.8</td>\n",
" <td>8.0</td>\n",
" <td>4.5</td>\n",
" <td>4.4</td>\n",
" <td>4.85</td>\n",
" <td>4.55</td>\n",
" <td>...</td>\n",
" <td>4.00</td>\n",
" <td>5.0</td>\n",
" <td>4.5</td>\n",
" <td>4.5</td>\n",
" <td>4.5</td>\n",
" <td>4.0</td>\n",
" <td>60</td>\n",
" <td>5630</td>\n",
" <td>729</td>\n",
" <td>0.1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>130</th>\n",
" <td>Jurassic World (2015)</td>\n",
" <td>71</td>\n",
" <td>81</td>\n",
" <td>59</td>\n",
" <td>7.0</td>\n",
" <td>7.3</td>\n",
" <td>4.5</td>\n",
" <td>4.5</td>\n",
" <td>3.55</td>\n",
" <td>4.05</td>\n",
" <td>...</td>\n",
" <td>3.65</td>\n",
" <td>3.5</td>\n",
" <td>4.0</td>\n",
" <td>3.0</td>\n",
" <td>3.5</td>\n",
" <td>3.5</td>\n",
" <td>1281</td>\n",
" <td>241807</td>\n",
" <td>34390</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>131</th>\n",
" <td>Minions (2015)</td>\n",
" <td>54</td>\n",
" <td>52</td>\n",
" <td>56</td>\n",
" <td>5.7</td>\n",
" <td>6.7</td>\n",
" <td>4.0</td>\n",
" <td>4.0</td>\n",
" <td>2.70</td>\n",
" <td>2.60</td>\n",
" <td>...</td>\n",
" <td>3.35</td>\n",
" <td>2.5</td>\n",
" <td>2.5</td>\n",
" <td>3.0</td>\n",
" <td>3.0</td>\n",
" <td>3.5</td>\n",
" <td>204</td>\n",
" <td>55895</td>\n",
" <td>14998</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>132</th>\n",
" <td>Max (2015)</td>\n",
" <td>35</td>\n",
" <td>73</td>\n",
" <td>47</td>\n",
" <td>5.9</td>\n",
" <td>7.0</td>\n",
" <td>4.5</td>\n",
" <td>4.5</td>\n",
" <td>1.75</td>\n",
" <td>3.65</td>\n",
" <td>...</td>\n",
" <td>3.50</td>\n",
" <td>2.0</td>\n",
" <td>3.5</td>\n",
" <td>2.5</td>\n",
" <td>3.0</td>\n",
" <td>3.5</td>\n",
" <td>15</td>\n",
" <td>5444</td>\n",
" <td>3412</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>133</th>\n",
" <td>Paul Blart: Mall Cop 2 (2015)</td>\n",
" <td>5</td>\n",
" <td>36</td>\n",
" <td>13</td>\n",
" <td>2.4</td>\n",
" <td>4.3</td>\n",
" <td>3.5</td>\n",
" <td>3.5</td>\n",
" <td>0.25</td>\n",
" <td>1.80</td>\n",
" <td>...</td>\n",
" <td>2.15</td>\n",
" <td>0.5</td>\n",
" <td>2.0</td>\n",
" <td>0.5</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>211</td>\n",
" <td>15004</td>\n",
" <td>3054</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>134</th>\n",
" <td>The Longest Ride (2015)</td>\n",
" <td>31</td>\n",
" <td>73</td>\n",
" <td>33</td>\n",
" <td>4.8</td>\n",
" <td>7.2</td>\n",
" <td>4.5</td>\n",
" <td>4.5</td>\n",
" <td>1.55</td>\n",
" <td>3.65</td>\n",
" <td>...</td>\n",
" <td>3.60</td>\n",
" <td>1.5</td>\n",
" <td>3.5</td>\n",
" <td>1.5</td>\n",
" <td>2.5</td>\n",
" <td>3.5</td>\n",
" <td>49</td>\n",
" <td>25214</td>\n",
" <td>2603</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>135</th>\n",
" <td>The Lazarus Effect (2015)</td>\n",
" <td>14</td>\n",
" <td>23</td>\n",
" <td>31</td>\n",
" <td>4.9</td>\n",
" <td>5.2</td>\n",
" <td>3.0</td>\n",
" <td>3.0</td>\n",
" <td>0.70</td>\n",
" <td>1.15</td>\n",
" <td>...</td>\n",
" <td>2.60</td>\n",
" <td>0.5</td>\n",
" <td>1.0</td>\n",
" <td>1.5</td>\n",
" <td>2.5</td>\n",
" <td>2.5</td>\n",
" <td>62</td>\n",
" <td>17691</td>\n",
" <td>1651</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>136</th>\n",
" <td>The Woman In Black 2 Angel of Death (2015)</td>\n",
" <td>22</td>\n",
" <td>25</td>\n",
" <td>42</td>\n",
" <td>4.4</td>\n",
" <td>4.9</td>\n",
" <td>3.0</td>\n",
" <td>3.0</td>\n",
" <td>1.10</td>\n",
" <td>1.25</td>\n",
" <td>...</td>\n",
" <td>2.45</td>\n",
" <td>1.0</td>\n",
" <td>1.5</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>2.5</td>\n",
" <td>55</td>\n",
" <td>14873</td>\n",
" <td>1333</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>137</th>\n",
" <td>Danny Collins (2015)</td>\n",
" <td>77</td>\n",
" <td>75</td>\n",
" <td>58</td>\n",
" <td>7.1</td>\n",
" <td>7.1</td>\n",
" <td>4.0</td>\n",
" <td>4.0</td>\n",
" <td>3.85</td>\n",
" <td>3.75</td>\n",
" <td>...</td>\n",
" <td>3.55</td>\n",
" <td>4.0</td>\n",
" <td>4.0</td>\n",
" <td>3.0</td>\n",
" <td>3.5</td>\n",
" <td>3.5</td>\n",
" <td>33</td>\n",
" <td>11206</td>\n",
" <td>531</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>138</th>\n",
" <td>Spare Parts (2015)</td>\n",
" <td>52</td>\n",
" <td>83</td>\n",
" <td>50</td>\n",
" <td>7.1</td>\n",
" <td>7.2</td>\n",
" <td>4.5</td>\n",
" <td>4.5</td>\n",
" <td>2.60</td>\n",
" <td>4.15</td>\n",
" <td>...</td>\n",
" <td>3.60</td>\n",
" <td>2.5</td>\n",
" <td>4.0</td>\n",
" <td>2.5</td>\n",
" <td>3.5</td>\n",
" <td>3.5</td>\n",
" <td>7</td>\n",
" <td>47377</td>\n",
" <td>450</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>139</th>\n",
" <td>Serena (2015)</td>\n",
" <td>18</td>\n",
" <td>25</td>\n",
" <td>36</td>\n",
" <td>5.3</td>\n",
" <td>5.4</td>\n",
" <td>3.0</td>\n",
" <td>3.0</td>\n",
" <td>0.90</td>\n",
" <td>1.25</td>\n",
" <td>...</td>\n",
" <td>2.70</td>\n",
" <td>1.0</td>\n",
" <td>1.5</td>\n",
" <td>2.0</td>\n",
" <td>2.5</td>\n",
" <td>2.5</td>\n",
" <td>19</td>\n",
" <td>12165</td>\n",
" <td>50</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>140</th>\n",
" <td>Inside Out (2015)</td>\n",
" <td>98</td>\n",
" <td>90</td>\n",
" <td>94</td>\n",
" <td>8.9</td>\n",
" <td>8.6</td>\n",
" <td>4.5</td>\n",
" <td>4.5</td>\n",
" <td>4.90</td>\n",
" <td>4.50</td>\n",
" <td>...</td>\n",
" <td>4.30</td>\n",
" <td>5.0</td>\n",
" <td>4.5</td>\n",
" <td>4.5</td>\n",
" <td>4.5</td>\n",
" <td>4.5</td>\n",
" <td>807</td>\n",
" <td>96252</td>\n",
" <td>15749</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>141</th>\n",
" <td>Mr. Holmes (2015)</td>\n",
" <td>87</td>\n",
" <td>78</td>\n",
" <td>67</td>\n",
" <td>7.9</td>\n",
" <td>7.4</td>\n",
" <td>4.0</td>\n",
" <td>4.0</td>\n",
" <td>4.35</td>\n",
" <td>3.90</td>\n",
" <td>...</td>\n",
" <td>3.70</td>\n",
" <td>4.5</td>\n",
" <td>4.0</td>\n",
" <td>3.5</td>\n",
" <td>4.0</td>\n",
" <td>3.5</td>\n",
" <td>33</td>\n",
" <td>7367</td>\n",
" <td>1348</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>142</th>\n",
" <td>'71 (2015)</td>\n",
" <td>97</td>\n",
" <td>82</td>\n",
" <td>83</td>\n",
" <td>7.5</td>\n",
" <td>7.2</td>\n",
" <td>3.5</td>\n",
" <td>3.5</td>\n",
" <td>4.85</td>\n",
" <td>4.10</td>\n",
" <td>...</td>\n",
" <td>3.60</td>\n",
" <td>5.0</td>\n",
" <td>4.0</td>\n",
" <td>4.0</td>\n",
" <td>4.0</td>\n",
" <td>3.5</td>\n",
" <td>60</td>\n",
" <td>24116</td>\n",
" <td>192</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>143</th>\n",
" <td>Two Days, One Night (2014)</td>\n",
" <td>97</td>\n",
" <td>78</td>\n",
" <td>89</td>\n",
" <td>8.8</td>\n",
" <td>7.4</td>\n",
" <td>3.5</td>\n",
" <td>3.5</td>\n",
" <td>4.85</td>\n",
" <td>3.90</td>\n",
" <td>...</td>\n",
" <td>3.70</td>\n",
" <td>5.0</td>\n",
" <td>4.0</td>\n",
" <td>4.5</td>\n",
" <td>4.5</td>\n",
" <td>3.5</td>\n",
" <td>123</td>\n",
" <td>24345</td>\n",
" <td>118</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>144</th>\n",
" <td>Gett: The Trial of Viviane Amsalem (2015)</td>\n",
" <td>100</td>\n",
" <td>81</td>\n",
" <td>90</td>\n",
" <td>7.3</td>\n",
" <td>7.8</td>\n",
" <td>3.5</td>\n",
" <td>3.5</td>\n",
" <td>5.00</td>\n",
" <td>4.05</td>\n",
" <td>...</td>\n",
" <td>3.90</td>\n",
" <td>5.0</td>\n",
" <td>4.0</td>\n",
" <td>4.5</td>\n",
" <td>3.5</td>\n",
" <td>4.0</td>\n",
" <td>19</td>\n",
" <td>1955</td>\n",
" <td>59</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>145</th>\n",
" <td>Kumiko, The Treasure Hunter (2015)</td>\n",
" <td>87</td>\n",
" <td>63</td>\n",
" <td>68</td>\n",
" <td>6.4</td>\n",
" <td>6.7</td>\n",
" <td>3.5</td>\n",
" <td>3.5</td>\n",
" <td>4.35</td>\n",
" <td>3.15</td>\n",
" <td>...</td>\n",
" <td>3.35</td>\n",
" <td>4.5</td>\n",
" <td>3.0</td>\n",
" <td>3.5</td>\n",
" <td>3.0</td>\n",
" <td>3.5</td>\n",
" <td>19</td>\n",
" <td>5289</td>\n",
" <td>41</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>146 rows × 22 columns</p>\n",
"</div>"
],
"text/plain": [
" FILM RottenTomatoes \\\n",
"0 Avengers: Age of Ultron (2015) 74 \n",
"1 Cinderella (2015) 85 \n",
"2 Ant-Man (2015) 80 \n",
"3 Do You Believe? (2015) 18 \n",
"4 Hot Tub Time Machine 2 (2015) 14 \n",
"5 The Water Diviner (2015) 63 \n",
"6 Irrational Man (2015) 42 \n",
"7 Top Five (2014) 86 \n",
"8 Shaun the Sheep Movie (2015) 99 \n",
"9 Love & Mercy (2015) 89 \n",
"10 Far From The Madding Crowd (2015) 84 \n",
"11 Black Sea (2015) 82 \n",
"12 Leviathan (2014) 99 \n",
"13 Unbroken (2014) 51 \n",
"14 The Imitation Game (2014) 90 \n",
"15 Taken 3 (2015) 9 \n",
"16 Ted 2 (2015) 46 \n",
"17 Southpaw (2015) 59 \n",
"18 Night at the Museum: Secret of the Tomb (2014) 50 \n",
"19 Pixels (2015) 17 \n",
"20 McFarland, USA (2015) 79 \n",
"21 Insidious: Chapter 3 (2015) 59 \n",
"22 The Man From U.N.C.L.E. (2015) 68 \n",
"23 Run All Night (2015) 60 \n",
"24 Trainwreck (2015) 85 \n",
"25 Selma (2014) 99 \n",
"26 Ex Machina (2015) 92 \n",
"27 Still Alice (2015) 88 \n",
"28 Wild Tales (2014) 96 \n",
"29 The End of the Tour (2015) 92 \n",
".. ... ... \n",
"116 Clouds of Sils Maria (2015) 89 \n",
"117 Testament of Youth (2015) 81 \n",
"118 Infinitely Polar Bear (2015) 80 \n",
"119 Phoenix (2015) 99 \n",
"120 The Wolfpack (2015) 84 \n",
"121 The Stanford Prison Experiment (2015) 84 \n",
"122 Tangerine (2015) 95 \n",
"123 Magic Mike XXL (2015) 62 \n",
"124 Home (2015) 45 \n",
"125 The Wedding Ringer (2015) 27 \n",
"126 Woman in Gold (2015) 52 \n",
"127 The Last Five Years (2015) 60 \n",
"128 Mission: Impossible – Rogue Nation (2015) 92 \n",
"129 Amy (2015) 97 \n",
"130 Jurassic World (2015) 71 \n",
"131 Minions (2015) 54 \n",
"132 Max (2015) 35 \n",
"133 Paul Blart: Mall Cop 2 (2015) 5 \n",
"134 The Longest Ride (2015) 31 \n",
"135 The Lazarus Effect (2015) 14 \n",
"136 The Woman In Black 2 Angel of Death (2015) 22 \n",
"137 Danny Collins (2015) 77 \n",
"138 Spare Parts (2015) 52 \n",
"139 Serena (2015) 18 \n",
"140 Inside Out (2015) 98 \n",
"141 Mr. Holmes (2015) 87 \n",
"142 '71 (2015) 97 \n",
"143 Two Days, One Night (2014) 97 \n",
"144 Gett: The Trial of Viviane Amsalem (2015) 100 \n",
"145 Kumiko, The Treasure Hunter (2015) 87 \n",
"\n",
" RottenTomatoes_User Metacritic Metacritic_User IMDB Fandango_Stars \\\n",
"0 86 66 7.1 7.8 5.0 \n",
"1 80 67 7.5 7.1 5.0 \n",
"2 90 64 8.1 7.8 5.0 \n",
"3 84 22 4.7 5.4 5.0 \n",
"4 28 29 3.4 5.1 3.5 \n",
"5 62 50 6.8 7.2 4.5 \n",
"6 53 53 7.6 6.9 4.0 \n",
"7 64 81 6.8 6.5 4.0 \n",
"8 82 81 8.8 7.4 4.5 \n",
"9 87 80 8.5 7.8 4.5 \n",
"10 77 71 7.5 7.2 4.5 \n",
"11 60 62 6.6 6.4 4.0 \n",
"12 79 92 7.2 7.7 4.0 \n",
"13 70 59 6.5 7.2 4.5 \n",
"14 92 73 8.2 8.1 5.0 \n",
"15 46 26 4.6 6.1 4.5 \n",
"16 58 48 6.5 6.6 4.5 \n",
"17 80 57 8.2 7.8 5.0 \n",
"18 58 47 5.8 6.3 4.5 \n",
"19 54 27 5.3 5.6 4.5 \n",
"20 89 60 7.2 7.5 5.0 \n",
"21 56 52 6.9 6.3 4.5 \n",
"22 80 55 7.9 7.6 4.5 \n",
"23 59 59 7.3 6.6 4.5 \n",
"24 74 75 6.0 6.7 4.5 \n",
"25 86 89 7.1 7.5 5.0 \n",
"26 86 78 7.9 7.7 4.5 \n",
"27 85 72 7.8 7.5 4.5 \n",
"28 92 77 8.8 8.2 4.5 \n",
"29 89 84 7.5 7.9 4.5 \n",
".. ... ... ... ... ... \n",
"116 67 78 7.1 6.8 3.5 \n",
"117 79 77 7.9 7.3 4.0 \n",
"118 76 64 7.9 7.2 4.0 \n",
"119 81 91 8.0 7.2 3.5 \n",
"120 73 75 7.0 7.1 3.5 \n",
"121 87 68 8.5 7.1 4.0 \n",
"122 86 86 7.3 7.4 4.0 \n",
"123 64 60 5.4 6.3 4.5 \n",
"124 65 55 7.3 6.7 4.5 \n",
"125 66 35 3.3 6.7 4.5 \n",
"126 81 51 7.2 7.4 4.5 \n",
"127 60 60 6.9 6.0 4.5 \n",
"128 90 75 8.0 7.8 4.5 \n",
"129 91 85 8.8 8.0 4.5 \n",
"130 81 59 7.0 7.3 4.5 \n",
"131 52 56 5.7 6.7 4.0 \n",
"132 73 47 5.9 7.0 4.5 \n",
"133 36 13 2.4 4.3 3.5 \n",
"134 73 33 4.8 7.2 4.5 \n",
"135 23 31 4.9 5.2 3.0 \n",
"136 25 42 4.4 4.9 3.0 \n",
"137 75 58 7.1 7.1 4.0 \n",
"138 83 50 7.1 7.2 4.5 \n",
"139 25 36 5.3 5.4 3.0 \n",
"140 90 94 8.9 8.6 4.5 \n",
"141 78 67 7.9 7.4 4.0 \n",
"142 82 83 7.5 7.2 3.5 \n",
"143 78 89 8.8 7.4 3.5 \n",
"144 81 90 7.3 7.8 3.5 \n",
"145 63 68 6.4 6.7 3.5 \n",
"\n",
" Fandango_Ratingvalue RT_norm RT_user_norm ... \\\n",
"0 4.5 3.70 4.30 ... \n",
"1 4.5 4.25 4.00 ... \n",
"2 4.5 4.00 4.50 ... \n",
"3 4.5 0.90 4.20 ... \n",
"4 3.0 0.70 1.40 ... \n",
"5 4.0 3.15 3.10 ... \n",
"6 3.5 2.10 2.65 ... \n",
"7 3.5 4.30 3.20 ... \n",
"8 4.0 4.95 4.10 ... \n",
"9 4.0 4.45 4.35 ... \n",
"10 4.0 4.20 3.85 ... \n",
"11 3.5 4.10 3.00 ... \n",
"12 3.5 4.95 3.95 ... \n",
"13 4.1 2.55 3.50 ... \n",
"14 4.6 4.50 4.60 ... \n",
"15 4.1 0.45 2.30 ... \n",
"16 4.1 2.30 2.90 ... \n",
"17 4.6 2.95 4.00 ... \n",
"18 4.1 2.50 2.90 ... \n",
"19 4.1 0.85 2.70 ... \n",
"20 4.6 3.95 4.45 ... \n",
"21 4.1 2.95 2.80 ... \n",
"22 4.1 3.40 4.00 ... \n",
"23 4.1 3.00 2.95 ... \n",
"24 4.1 4.25 3.70 ... \n",
"25 4.6 4.95 4.30 ... \n",
"26 4.1 4.60 4.30 ... \n",
"27 4.1 4.40 4.25 ... \n",
"28 4.1 4.80 4.60 ... \n",
"29 4.1 4.60 4.45 ... \n",
".. ... ... ... ... \n",
"116 3.4 4.45 3.35 ... \n",
"117 3.9 4.05 3.95 ... \n",
"118 3.9 4.00 3.80 ... \n",
"119 3.4 4.95 4.05 ... \n",
"120 3.4 4.20 3.65 ... \n",
"121 3.9 4.20 4.35 ... \n",
"122 3.9 4.75 4.30 ... \n",
"123 4.4 3.10 3.20 ... \n",
"124 4.4 2.25 3.25 ... \n",
"125 4.4 1.35 3.30 ... \n",
"126 4.4 2.60 4.05 ... \n",
"127 4.4 3.00 3.00 ... \n",
"128 4.4 4.60 4.50 ... \n",
"129 4.4 4.85 4.55 ... \n",
"130 4.5 3.55 4.05 ... \n",
"131 4.0 2.70 2.60 ... \n",
"132 4.5 1.75 3.65 ... \n",
"133 3.5 0.25 1.80 ... \n",
"134 4.5 1.55 3.65 ... \n",
"135 3.0 0.70 1.15 ... \n",
"136 3.0 1.10 1.25 ... \n",
"137 4.0 3.85 3.75 ... \n",
"138 4.5 2.60 4.15 ... \n",
"139 3.0 0.90 1.25 ... \n",
"140 4.5 4.90 4.50 ... \n",
"141 4.0 4.35 3.90 ... \n",
"142 3.5 4.85 4.10 ... \n",
"143 3.5 4.85 3.90 ... \n",
"144 3.5 5.00 4.05 ... \n",
"145 3.5 4.35 3.15 ... \n",
"\n",
" IMDB_norm RT_norm_round RT_user_norm_round Metacritic_norm_round \\\n",
"0 3.90 3.5 4.5 3.5 \n",
"1 3.55 4.5 4.0 3.5 \n",
"2 3.90 4.0 4.5 3.0 \n",
"3 2.70 1.0 4.0 1.0 \n",
"4 2.55 0.5 1.5 1.5 \n",
"5 3.60 3.0 3.0 2.5 \n",
"6 3.45 2.0 2.5 2.5 \n",
"7 3.25 4.5 3.0 4.0 \n",
"8 3.70 5.0 4.0 4.0 \n",
"9 3.90 4.5 4.5 4.0 \n",
"10 3.60 4.0 4.0 3.5 \n",
"11 3.20 4.0 3.0 3.0 \n",
"12 3.85 5.0 4.0 4.5 \n",
"13 3.60 2.5 3.5 3.0 \n",
"14 4.05 4.5 4.5 3.5 \n",
"15 3.05 0.5 2.5 1.5 \n",
"16 3.30 2.5 3.0 2.5 \n",
"17 3.90 3.0 4.0 3.0 \n",
"18 3.15 2.5 3.0 2.5 \n",
"19 2.80 1.0 2.5 1.5 \n",
"20 3.75 4.0 4.5 3.0 \n",
"21 3.15 3.0 3.0 2.5 \n",
"22 3.80 3.5 4.0 3.0 \n",
"23 3.30 3.0 3.0 3.0 \n",
"24 3.35 4.5 3.5 4.0 \n",
"25 3.75 5.0 4.5 4.5 \n",
"26 3.85 4.5 4.5 4.0 \n",
"27 3.75 4.5 4.5 3.5 \n",
"28 4.10 5.0 4.5 4.0 \n",
"29 3.95 4.5 4.5 4.0 \n",
".. ... ... ... ... \n",
"116 3.40 4.5 3.5 4.0 \n",
"117 3.65 4.0 4.0 4.0 \n",
"118 3.60 4.0 4.0 3.0 \n",
"119 3.60 5.0 4.0 4.5 \n",
"120 3.55 4.0 3.5 4.0 \n",
"121 3.55 4.0 4.5 3.5 \n",
"122 3.70 5.0 4.5 4.5 \n",
"123 3.15 3.0 3.0 3.0 \n",
"124 3.35 2.5 3.5 3.0 \n",
"125 3.35 1.5 3.5 2.0 \n",
"126 3.70 2.5 4.0 2.5 \n",
"127 3.00 3.0 3.0 3.0 \n",
"128 3.90 4.5 4.5 4.0 \n",
"129 4.00 5.0 4.5 4.5 \n",
"130 3.65 3.5 4.0 3.0 \n",
"131 3.35 2.5 2.5 3.0 \n",
"132 3.50 2.0 3.5 2.5 \n",
"133 2.15 0.5 2.0 0.5 \n",
"134 3.60 1.5 3.5 1.5 \n",
"135 2.60 0.5 1.0 1.5 \n",
"136 2.45 1.0 1.5 2.0 \n",
"137 3.55 4.0 4.0 3.0 \n",
"138 3.60 2.5 4.0 2.5 \n",
"139 2.70 1.0 1.5 2.0 \n",
"140 4.30 5.0 4.5 4.5 \n",
"141 3.70 4.5 4.0 3.5 \n",
"142 3.60 5.0 4.0 4.0 \n",
"143 3.70 5.0 4.0 4.5 \n",
"144 3.90 5.0 4.0 4.5 \n",
"145 3.35 4.5 3.0 3.5 \n",
"\n",
" Metacritic_user_norm_round IMDB_norm_round Metacritic_user_vote_count \\\n",
"0 3.5 4.0 1330 \n",
"1 4.0 3.5 249 \n",
"2 4.0 4.0 627 \n",
"3 2.5 2.5 31 \n",
"4 1.5 2.5 88 \n",
"5 3.5 3.5 34 \n",
"6 4.0 3.5 17 \n",
"7 3.5 3.5 124 \n",
"8 4.5 3.5 62 \n",
"9 4.5 4.0 54 \n",
"10 4.0 3.5 35 \n",
"11 3.5 3.0 37 \n",
"12 3.5 4.0 145 \n",
"13 3.5 3.5 218 \n",
"14 4.0 4.0 566 \n",
"15 2.5 3.0 240 \n",
"16 3.5 3.5 197 \n",
"17 4.0 4.0 128 \n",
"18 3.0 3.0 103 \n",
"19 2.5 3.0 246 \n",
"20 3.5 4.0 59 \n",
"21 3.5 3.0 115 \n",
"22 4.0 4.0 144 \n",
"23 3.5 3.5 141 \n",
"24 3.0 3.5 169 \n",
"25 3.5 4.0 316 \n",
"26 4.0 4.0 672 \n",
"27 4.0 4.0 153 \n",
"28 4.5 4.0 107 \n",
"29 4.0 4.0 19 \n",
".. ... ... ... \n",
"116 3.5 3.5 36 \n",
"117 4.0 3.5 15 \n",
"118 4.0 3.5 8 \n",
"119 4.0 3.5 21 \n",
"120 3.5 3.5 8 \n",
"121 4.5 3.5 6 \n",
"122 3.5 3.5 14 \n",
"123 2.5 3.0 52 \n",
"124 3.5 3.5 177 \n",
"125 1.5 3.5 126 \n",
"126 3.5 3.5 72 \n",
"127 3.5 3.0 20 \n",
"128 4.0 4.0 362 \n",
"129 4.5 4.0 60 \n",
"130 3.5 3.5 1281 \n",
"131 3.0 3.5 204 \n",
"132 3.0 3.5 15 \n",
"133 1.0 2.0 211 \n",
"134 2.5 3.5 49 \n",
"135 2.5 2.5 62 \n",
"136 2.0 2.5 55 \n",
"137 3.5 3.5 33 \n",
"138 3.5 3.5 7 \n",
"139 2.5 2.5 19 \n",
"140 4.5 4.5 807 \n",
"141 4.0 3.5 33 \n",
"142 4.0 3.5 60 \n",
"143 4.5 3.5 123 \n",
"144 3.5 4.0 19 \n",
"145 3.0 3.5 19 \n",
"\n",
" IMDB_user_vote_count Fandango_votes Fandango_Difference \n",
"0 271107 14846 0.5 \n",
"1 65709 12640 0.5 \n",
"2 103660 12055 0.5 \n",
"3 3136 1793 0.5 \n",
"4 19560 1021 0.5 \n",
"5 39373 397 0.5 \n",
"6 2680 252 0.5 \n",
"7 16876 3223 0.5 \n",
"8 12227 896 0.5 \n",
"9 5367 864 0.5 \n",
"10 12129 804 0.5 \n",
"11 16547 218 0.5 \n",
"12 22521 64 0.5 \n",
"13 77518 9443 0.4 \n",
"14 334164 8055 0.4 \n",
"15 104235 6757 0.4 \n",
"16 49102 6437 0.4 \n",
"17 23561 5597 0.4 \n",
"18 50291 5445 0.4 \n",
"19 19521 3886 0.4 \n",
"20 13769 3364 0.4 \n",
"21 25134 3276 0.4 \n",
"22 22104 2686 0.4 \n",
"23 50438 2066 0.4 \n",
"24 27380 8381 0.4 \n",
"25 45344 7025 0.4 \n",
"26 154499 3458 0.4 \n",
"27 57123 1258 0.4 \n",
"28 50285 235 0.4 \n",
"29 1320 121 0.4 \n",
".. ... ... ... \n",
"116 11392 162 0.1 \n",
"117 5495 127 0.1 \n",
"118 1062 124 0.1 \n",
"119 3687 70 0.1 \n",
"120 1488 66 0.1 \n",
"121 950 51 0.1 \n",
"122 696 36 0.1 \n",
"123 11937 9363 0.1 \n",
"124 41158 7705 0.1 \n",
"125 37292 6506 0.1 \n",
"126 17957 2435 0.1 \n",
"127 4110 99 0.1 \n",
"128 82579 8357 0.1 \n",
"129 5630 729 0.1 \n",
"130 241807 34390 0.0 \n",
"131 55895 14998 0.0 \n",
"132 5444 3412 0.0 \n",
"133 15004 3054 0.0 \n",
"134 25214 2603 0.0 \n",
"135 17691 1651 0.0 \n",
"136 14873 1333 0.0 \n",
"137 11206 531 0.0 \n",
"138 47377 450 0.0 \n",
"139 12165 50 0.0 \n",
"140 96252 15749 0.0 \n",
"141 7367 1348 0.0 \n",
"142 24116 192 0.0 \n",
"143 24345 118 0.0 \n",
"144 1955 59 0.0 \n",
"145 5289 41 0.0 \n",
"\n",
"[146 rows x 22 columns]"
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"movies"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"(array([ 12., 0., 27., 0., 0., 41., 0., 55., 0., 11.]),\n",
" array([ 3. , 3.2, 3.4, 3.6, 3.8, 4. , 4.2, 4.4, 4.6, 4.8, 5. ]),\n",
" <a list of 10 Patch objects>)"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAgcAAAFkCAYAAAC0KZhSAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nSZKK/w8Ntms3x2ABIwAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x108966128>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"import matplotlib.pyplot as plt\n",
"%matplotlib inline\n",
"\n",
"plt.hist(movies[\"Fandango_Stars\"])"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"(array([ 1., 2., 20., 14., 0., 22., 27., 20., 25., 15.]),\n",
" array([ 0.5, 0.9, 1.3, 1.7, 2.1, 2.5, 2.9, 3.3, 3.7, 4.1, 4.5]),\n",
" <a list of 10 Patch objects>)"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAgcAAAFkCAYAAAC0KZhSAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x109880668>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.hist(movies[\"Metacritic_norm_round\"])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Fandango vs Metacritic Scores\n",
"\n",
"There are no scores below a `3.0` in the Fandango reviews. The Fandango reviews also tend to center around `4.5` and `4.0`, whereas the Metacritic reviews seem to center around `3.0` and `3.5`."
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"collapsed": false,
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"4.08904109589\n",
"2.97260273973\n",
"0.540385977979\n",
"0.990960561374\n",
"4.0\n",
"3.0\n"
]
}
],
"source": [
"import numpy\n",
"\n",
"f_mean = movies[\"Fandango_Stars\"].mean()\n",
"m_mean = movies[\"Metacritic_norm_round\"].mean()\n",
"f_std = movies[\"Fandango_Stars\"].std()\n",
"m_std = movies[\"Metacritic_norm_round\"].std()\n",
"f_median = movies[\"Fandango_Stars\"].median()\n",
"m_median = movies[\"Metacritic_norm_round\"].median()\n",
"\n",
"print(f_mean)\n",
"print(m_mean)\n",
"print(f_std)\n",
"print(m_std)\n",
"print(f_median)\n",
"print(m_median)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Fandango vs Metacritic Methodology\n",
"\n",
"Fandango appears to inflate ratings and isn't transparent about how it calculates and aggregates ratings. Metacritic publishes each individual critic rating, and is transparent about how they aggregate them to get a final rating."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Fandango vs Metacritic number differences\n",
"\n",
"The median metacritic score appears higher than the mean metacritic score because a few very low reviews \"drag down\" the median. The median fandango score is lower than the mean fandango score because a few very high ratings \"drag up\" the mean.\n",
"\n",
"Fandango ratings appear clustered between `3` and `5`, and have a much narrower random than Metacritic reviews, which go from `0` to `5`.\n",
"\n",
"Fandango ratings in general appear to be higher than metacritic ratings.\n",
"\n",
"These may be due to movie studio influence on Fandango ratings, and the fact that Fandango calculates its ratings in a hidden way."
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.collections.PathCollection at 0x109aa4390>"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAgQAAAFkCAYAAABfHiNRAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nSZKwEEiSJOD/A/awyJhkEoOPAAAAAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x109989da0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.scatter(movies[\"Metacritic_norm_round\"], movies[\"Fandango_Stars\"])"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"movies[\"fm_diff\"] = numpy.abs(movies[\"Metacritic_norm_round\"] - movies[\"Fandango_Stars\"])"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>FILM</th>\n",
" <th>RottenTomatoes</th>\n",
" <th>RottenTomatoes_User</th>\n",
" <th>Metacritic</th>\n",
" <th>Metacritic_User</th>\n",
" <th>IMDB</th>\n",
" <th>Fandango_Stars</th>\n",
" <th>Fandango_Ratingvalue</th>\n",
" <th>RT_norm</th>\n",
" <th>RT_user_norm</th>\n",
" <th>...</th>\n",
" <th>RT_norm_round</th>\n",
" <th>RT_user_norm_round</th>\n",
" <th>Metacritic_norm_round</th>\n",
" <th>Metacritic_user_norm_round</th>\n",
" <th>IMDB_norm_round</th>\n",
" <th>Metacritic_user_vote_count</th>\n",
" <th>IMDB_user_vote_count</th>\n",
" <th>Fandango_votes</th>\n",
" <th>Fandango_Difference</th>\n",
" <th>fm_diff</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>Do You Believe? (2015)</td>\n",
" <td>18</td>\n",
" <td>84</td>\n",
" <td>22</td>\n",
" <td>4.7</td>\n",
" <td>5.4</td>\n",
" <td>5.0</td>\n",
" <td>4.5</td>\n",
" <td>0.90</td>\n",
" <td>4.20</td>\n",
" <td>...</td>\n",
" <td>1.0</td>\n",
" <td>4.0</td>\n",
" <td>1.0</td>\n",
" <td>2.5</td>\n",
" <td>2.5</td>\n",
" <td>31</td>\n",
" <td>3136</td>\n",
" <td>1793</td>\n",
" <td>0.5</td>\n",
" <td>4.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>85</th>\n",
" <td>Little Boy (2015)</td>\n",
" <td>20</td>\n",
" <td>81</td>\n",
" <td>30</td>\n",
" <td>5.9</td>\n",
" <td>7.4</td>\n",
" <td>4.5</td>\n",
" <td>4.3</td>\n",
" <td>1.00</td>\n",
" <td>4.05</td>\n",
" <td>...</td>\n",
" <td>1.0</td>\n",
" <td>4.0</td>\n",
" <td>1.5</td>\n",
" <td>3.0</td>\n",
" <td>3.5</td>\n",
" <td>38</td>\n",
" <td>5927</td>\n",
" <td>811</td>\n",
" <td>0.2</td>\n",
" <td>3.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>47</th>\n",
" <td>Annie (2014)</td>\n",
" <td>27</td>\n",
" <td>61</td>\n",
" <td>33</td>\n",
" <td>4.8</td>\n",
" <td>5.2</td>\n",
" <td>4.5</td>\n",
" <td>4.2</td>\n",
" <td>1.35</td>\n",
" <td>3.05</td>\n",
" <td>...</td>\n",
" <td>1.5</td>\n",
" <td>3.0</td>\n",
" <td>1.5</td>\n",
" <td>2.5</td>\n",
" <td>2.5</td>\n",
" <td>108</td>\n",
" <td>19222</td>\n",
" <td>6835</td>\n",
" <td>0.3</td>\n",
" <td>3.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>Pixels (2015)</td>\n",
" <td>17</td>\n",
" <td>54</td>\n",
" <td>27</td>\n",
" <td>5.3</td>\n",
" <td>5.6</td>\n",
" <td>4.5</td>\n",
" <td>4.1</td>\n",
" <td>0.85</td>\n",
" <td>2.70</td>\n",
" <td>...</td>\n",
" <td>1.0</td>\n",
" <td>2.5</td>\n",
" <td>1.5</td>\n",
" <td>2.5</td>\n",
" <td>3.0</td>\n",
" <td>246</td>\n",
" <td>19521</td>\n",
" <td>3886</td>\n",
" <td>0.4</td>\n",
" <td>3.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>134</th>\n",
" <td>The Longest Ride (2015)</td>\n",
" <td>31</td>\n",
" <td>73</td>\n",
" <td>33</td>\n",
" <td>4.8</td>\n",
" <td>7.2</td>\n",
" <td>4.5</td>\n",
" <td>4.5</td>\n",
" <td>1.55</td>\n",
" <td>3.65</td>\n",
" <td>...</td>\n",
" <td>1.5</td>\n",
" <td>3.5</td>\n",
" <td>1.5</td>\n",
" <td>2.5</td>\n",
" <td>3.5</td>\n",
" <td>49</td>\n",
" <td>25214</td>\n",
" <td>2603</td>\n",
" <td>0.0</td>\n",
" <td>3.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>5 rows × 23 columns</p>\n",
"</div>"
],
"text/plain": [
" FILM RottenTomatoes RottenTomatoes_User Metacritic \\\n",
"3 Do You Believe? (2015) 18 84 22 \n",
"85 Little Boy (2015) 20 81 30 \n",
"47 Annie (2014) 27 61 33 \n",
"19 Pixels (2015) 17 54 27 \n",
"134 The Longest Ride (2015) 31 73 33 \n",
"\n",
" Metacritic_User IMDB Fandango_Stars Fandango_Ratingvalue RT_norm \\\n",
"3 4.7 5.4 5.0 4.5 0.90 \n",
"85 5.9 7.4 4.5 4.3 1.00 \n",
"47 4.8 5.2 4.5 4.2 1.35 \n",
"19 5.3 5.6 4.5 4.1 0.85 \n",
"134 4.8 7.2 4.5 4.5 1.55 \n",
"\n",
" RT_user_norm ... RT_norm_round RT_user_norm_round \\\n",
"3 4.20 ... 1.0 4.0 \n",
"85 4.05 ... 1.0 4.0 \n",
"47 3.05 ... 1.5 3.0 \n",
"19 2.70 ... 1.0 2.5 \n",
"134 3.65 ... 1.5 3.5 \n",
"\n",
" Metacritic_norm_round Metacritic_user_norm_round IMDB_norm_round \\\n",
"3 1.0 2.5 2.5 \n",
"85 1.5 3.0 3.5 \n",
"47 1.5 2.5 2.5 \n",
"19 1.5 2.5 3.0 \n",
"134 1.5 2.5 3.5 \n",
"\n",
" Metacritic_user_vote_count IMDB_user_vote_count Fandango_votes \\\n",
"3 31 3136 1793 \n",
"85 38 5927 811 \n",
"47 108 19222 6835 \n",
"19 246 19521 3886 \n",
"134 49 25214 2603 \n",
"\n",
" Fandango_Difference fm_diff \n",
"3 0.5 4.0 \n",
"85 0.2 3.0 \n",
"47 0.3 3.0 \n",
"19 0.4 3.0 \n",
"134 0.0 3.0 \n",
"\n",
"[5 rows x 23 columns]"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"movies.sort_values(by=\"fm_diff\", ascending=False).head(5)"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"0.17844919073895918"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from scipy.stats import pearsonr\n",
"\n",
"r_value, p_value = pearsonr(movies[\"Fandango_Stars\"], movies[\"Metacritic_norm_round\"])\n",
"\n",
"r_value"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Fandango and Metacritic correlation\n",
"\n",
"The low correlation between Fandango and Metacritic scores indicates that Fandango scores aren't just inflated, they are fundamentally different. For whatever reason, it appears like Fandango both inflates scores overall, and inflates scores differently depending on the movie."
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"from scipy.stats import linregress\n",
"\n",
"slope, intercept, r_value, p_value, stderr_slope = linregress(movies[\"Metacritic_norm_round\"], movies[\"Fandango_Stars\"])"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"4.0917071528212032"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pred = 3 * slope + intercept\n",
"\n",
"pred"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Finding Residuals"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.collections.PathCollection at 0x10b35db00>"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"text/plain": [
"[<matplotlib.lines.Line2D at 0x10b316780>]"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"text/plain": [
"(1, 5)"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAgsAAAFkCAYAAACuFXjcAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAAPYQAAD2EBqD+naQAAIABJREFUeJzt3X+UVOWd5/H3Q9MIQoJKBNzRqAc0oo7GJjGCCggoGeec\nGEdnxo4SGZ3MZjOeZDBx50c2x8wPgnsyK+Oscc5kYCWE2Oye2dXJJBoMjaBZcRy7iR4nKqBrnHE3\ngpCQCCoNPPvHrQ5V3VVPd3VXdXVVvV/n3EN11b1V3y9Pdd9P3V8VYoxIkiSVMqbWBUiSpNHNsCBJ\nkpIMC5IkKcmwIEmSkgwLkiQpybAgSZKSDAuSJCnJsCBJkpIMC5IkKcmwIEmSksoKCyGEO0MIR/tM\nP0rMf3NuniN58x8cftmSJGmkjB3CMs8Di4CQ+/nwAPPvB87Om98vo5AkqY4MJSwcjjHuKWP+WOb8\nkiRpFBnKMQtnhRBeDyG8HEJYH0I4bYD5J4UQXg0hvBZCeCiEcO5QCpUkSbURyvmK6hDCEmAS8BJw\nCvBl4N8B58cYDxSZ/xJgJvAcMBm4A5gHnBdjfL3Ea0wBlgCvAu8MvhVJkpreeOAMYGOMcW+lnrSs\nsNBv4RAmAz8GlscY7x/E/GOBF4AHYox3lpjnE8C3hlyUJEm6Mcb4QKWebCjHLPxSjHF/CGEH2daD\nwcx/OISwfYD5XwVYv349s2bNGk55dWH58uWsWrWq1mVUnX02FvtsLPbZOF544QVuuukmyK1LK2VY\nYSGEMAmYAawb5PxjgPOBhxOzvQMwa9Ys2trahlNeXZg8ebJ9NhD7bCz22Viapc+ciu7GL/c6C18N\nIcwLIZweQpgLPEh26mRH7vF1IYSv5M3/pRDClSGEM0MIF5HtXjgdWF25FiRJUjWVu2XhVOABYAqw\nB/gBcEneQRSnUnjdhROBrwPTgZ8CXcCcGOOLwylakiSNnLLCQoyxfYDHF/b5+Xbg9iHUJUmSRgm/\nG6LG2tuT+ath2Gdjsc/GYp8ayLBOnayGEEIb0NXV1dVMB6JIkjRs3d3dzJ49G2B2jLG7Us/rlgVJ\nkpRkWJAkSUmGBUmSlGRYkCRJSYYFSZKUZFiQJElJhgVJkpRkWJAkSUmGBUmSlGRYkCRJSYYFSZKU\nZFiQJElJhgVJkpRkWJAkSUmGBUmSlGRYkCRJSYYFSZKUZFiQJElJhgVJkpRkWJAkSUmGBUmSlGRY\nkCRJSYYFSZKUZFiQJElJhgVJkpRkWJAkSUmGBUmSlGRYkCRJSYYFSZKUZFiQJElJhgVJkpRkWJAk\nSUmGBUmSlGRYkCRJSYYFSZKUZFiQJElJhgVJkpRkWJAkSUmGBUmSlFRWWAgh3BlCONpn+tEAy/xm\nCOGFEMLbIYRnQwi/NrySJUnSSBrKloXngWnA9Nx0WakZQwhzgAeAvwM+CDwEPBRCOHegF3nttdeG\nUJqkaluzZg1Lly5l7dq1tS6lqpYtW8aZZ57JrbfeWutSVAE7duzgkUceYefOnbUupT7FGAc9AXcC\n3WXMvwH4dp/7tgH3JZZpAyIQlyy5Ou7bty9Kqr1nnnkmtrZOiL2/n0BsbZ0Qt2/fXuvSKmrdunUR\nWgr6hJa4YcOGWpemIdi7d29csuTqgvFs5HVLV1dXb59tsYz1+0DTULYsnBVCeD2E8HIIYX0I4bTE\nvHOATX3u25i7fwB/zqZNT9HeftMQSpRUaXPmXE5PzzhgPfAasJ6ennFcfPHcGldWWZ/85O8Ak8jv\nEyZxww031rQuDc0nPrGUTZueIn88XbeUr9yw8BSwDFgCfBo4E3g8hDCxxPzTgTf63PdG7v4BXM2R\nI/ewcePDbjaSamzNmjX09LwNfA24ETgt9++99PS83TC7JJYtWwYcoVifcMRdEnVmx44dbNz4MEeO\n/DX54+m6pXxjy5k5xrgx78fnQwhPAz8Gfgu4f5BPE8g2kQxgOTAOgKVLlzJ16lTa29tpb28vp2RJ\nFbBly5bcrXl9HpkPQGdnZ25FW9+2bt2au1W8z82bN49oPRqel19+OXer+Hju2rWLs846a0RrqqSO\njg46OjoK7tu/f39VXqussNBXjHF/CGEHMLPELD8hOxgy31T6b20oYhXwI2AT3/zmN+t6QKV6t2DB\nAtavXw88TvYJrVe2cl20aFEtyqq4+fPn8+qrr1Kqz4ULF9agKg3VjBkzcreKj+fMmaVWXfWh2Afo\n7u5uZs+eXfHXCjEO4kN+qYVDmES2ZeHOGOO9RR7fAEyIMV6Td9//Bp6NMX6mxHO2AV3w57S0rGLx\n4kv43ve+O+QaJVXGuHHH545ZuJfsk9lW4DZaWw9x6NDB2hZXQSGMJTtmobBPeIsYD9eyNA3BRz/6\n62za9BRHjtxD73i2tHyuYdcteWFhdoyxu1LPW+51Fr4aQpgXQjg9hDAXeBA4DHTkHl8XQvhK3iL3\nAL8WQrg9hPCBEMKXgdlkv4UD+BKLF19CR8f6ckqUVCVPP/0kra2HgKXA+4GltLYe4umnn6xxZZW1\nYcO3gLfI7xPeyt2vetPRsZ7Fiy8hfzxdt5SvrC0LIYQO4HJgCrAH+AHwxRjj/8k9vhl4NcZ4S94y\n1wErgNOBncAdfY596PsabUDXgw8+yMc//vHyO5JUVWvXrqWzs5NFixY1xHEKpdx6661s3ryZhQsX\nsmbNmlqXo2HauXMnu3btYubMmQ29W7taWxaGtRuiGnrDQldXF21tbbUuR5KkujEqdkNIkqTmY1iQ\nJElJhgVJkpRkWJAkSUmGBUmSlGRYkCRJSYYFSZKUZFiQJElJhgVJkpRkWJAkSUmGBUmSlGRYkCRJ\nSYYFSZKUZFiQJElJhgVJkpRkWJAkSUmGBUmSlGRYkCRJSYYFSZKUZFiQJElJhgVJkpRkWJAkSUmG\nBUmSlGRYkCRJSYYFSZKUZFiQJElJhgVJkpRkWJAkSUmGBUmSlGRYkCRJSYYFSZKUZFiQJElJhgVJ\nkpRkWJAkSUmGBUmSlGRYkCRJSYYFSZKUZFiQJElJhgVJkpRkWJAkSUnDCgshhD8OIRwNIdydmOfm\n3DxHcv8eDSEcHM7rSpKkkTN2qAuGED4MfAp4dhCz7wfOBkLu5zjU15UkSSNrSFsWQgiTgPXA7wI/\nG8QiMca4J8a4OzftGcrrNprly5dz4YUX8oUvfKHWpVRVs/Q5d+5cJk6cyGWXXVbrUqpq1qxZtLa2\nct5559W6lKq69tprmTZtGtdff32tS6mq6dOnE0LglFNOqXUpVbVixQoWLlzIXXfdVetS6lOMsewJ\n+Abwl7nbjwF3J+a9GTgEvAq8BjwEnJuYvw2IXV1dsVE9+OCDEcZGsi0suWls/M53vlPr0iqqWfr8\n0z/90wgtffpsiStXrqx1aRX12c9+tmifd9xxR61Lq6j77ruvaJ+rV6+udWkV9du//dtF+/zkJz9Z\n69IqqrOzM4bQWtBnCK1x69attS6tKrq6unr7bItDWL+XmkKM5e0RCCHcAPwx8KEYY08I4TFge4zx\n9hLzXwLMBJ4DJgN3APOA82KMrxeZvw3o6urqoq2traza6kUIrcBE4Gtk/xWPA78PHCDGnlqWVlHN\n0+dYYBL9+3yLGA/XsrSKsk/7rEdjxowjxuPp22cIBzl69FBti6uC7u5uZs+eDTA7xthdqectazdE\nCOFU4K+Am+Ig/9rHGJ+KMa6PMT4XY3wC+A1gD/B7ZVfbAJYvXw4cJnvj3giclvv3XuBww2yqb5Y+\n586dCxyheJ9HGmaXxKxZs0j12Si7JK699lpSfTbKLonp06eT6rNRdkmsWLEi98Gkf58x9rhLogxl\nbVkIIVwD/C+yd1nvwYotZJs8jgDHxUE8YQjhfwA9McYbizzWBnTNmzePyZMnFzzW3t5Oe3v7oOsd\njS688EKee+45sj0yp+U98q/A+7ngggt49tnBHDM6ujVLnxMnTuTgwYOU6vP444/nwIEDtSmuglpb\nWzl8+DCl+hw7diw9PfW/tWjatGns3r2bUn1OnTqVN954ozbFVVAIvX++i/cJUO5W59Fo4cKFPPbY\nY5Tq84orrmDz5s21Ka4COjo66OjoKLhv//79PP7441DhLQvlng2xCfjVPvetBV4A7hpkUBgDnA88\nnJpv1apVDbkbYuHChbmV6ONkCbfXVgCuvPLKWpRVcc3S54UXXsi2bdso1edFF11Ui7IqbubMmbz4\n4ouU6vPss8+uRVkVN3fuXB566CFK9Xn55ZfXoqyKmzZtWi70FO8z2/JQ/xYtWpQLC8X7vOqqq2pR\nVsUU+wCdtxuioso+ZqHfE/Q5ZiGE8A3g9Rjjn+R+/hLwFLALOAH4j8DHyFLPi0Wer4mOWbgXmE/2\nxr2NxtuX3yx99u777dtnY+37tU/7rEfHjlko7NNjFspTiSs49k0bpwH5sfRE4OvAj4Dvkr075xQL\nCs3iO995CDgALCXb5LcUOJC7v3E0S58rV/4F8BaFfb6Vu79x3HHH7RTrM7u/caxe/bcU6zO7v3F8\n8pM3UqzP7P7GsWXLJrLrAB7rM4SDbNmyqcaV1ZlKnlpRiYkmOHWy1+c///l4wQUXxM9//vO1LqWq\nmqXPSy+9NB5//PHx0ksvrXUpVXXuuefGsWPHxnPPPbfWpVTVddddF6dOnRqvu+66WpdSVdOnT49A\nnD59eq1LqaqVK1fGK664ouFOae5r1Jw6WW3NsBtCkqRqGM27ISRJUgMzLEiSpCTDgiRJSjIsSJKk\nJMOCJElKMixIkqQkw4IkSUoyLEiSpCTDgiRJSjIsSJKkJMOCJElKMixIkqQkw4IkSUoyLEiSpCTD\ngiRJShpb6wIkSdLAYoSf/QzeeAN27y4+vfJKdV7bsCBJUo28807xlX6pQHD4cOHyra0wdeqx6ZRT\nYPv2ytdpWJAkqUKOHoV9+wZe6fc+9otf9H+OE0/MVvzTpmX/zpxZGAjyH5s8GUI4tmx3Nzz8cOX7\nMixIkpRw8ODAK/3e22++CUeOFC5/3HHHVu5Tp8LZZ8NllxWu9Hun970Pxo2rTZ8phgVJUlM5fBj2\n7h38pv8DBwqXDwGmTClcyc+a1X/F3zu95z2Fn/7rkWFBklTXYoS33hr8pv+9e7Nl8k2YcGxlP20a\nnH9+8RX/tGlZUBjbZGvPJmtXklQPenpgz57BbfrfvTs7UDDfmDFw8snHVvLTp8MFF/Tf5987TZxY\nmz7rhWFBklR1McL+/YPf9L9vX//neM97ClfwF11UetP/SSdBS8vI99moDAuSpCF5991jn/4HcwBg\nT0/h8mPHHvv0P20avP/98KEPFd/0f/LJ2a4C1YZhQZIEZKf9/fSng9/0v39//+c44YTCFf3FF5fe\n9H/CCdnuAo1+hgVJamBvvz24zf67d2dbCfpe9GfcuMIV/IwZMHdu8U3/J5+cnSaoxmNYkKQ6cuRI\ntj9/sOf9v/VW/+c46aTCT/pnn136oj/vfW/9n/an4TMsSFKN5Z/2N9BWgDffzHYX5Bs/vnAT/6xZ\nMH9+6Yv+tLbWpk/VL8OCJFXY4cPZSn0wm/53786uEJgvhGylnr+SL3Xe/9SpMGmSn/5VXYYFSRpA\njNk1/Ae76X/v3v7PMXFi4Sb+/HP++276nzLF0/40uhgWJDWlQ4eKX/SnVCB4993C5VtaCi/68yu/\nkp33X+zI/5NP9qI/qm+GBUkNIUb42c8Gf8nfn/2s/3O8972Fn/Rnz05f9MfT/tQsDAuSRq133knv\n688PBHv2FL/oT/4n/TPOKDzvv+9Ff8aPr0mb0qhnWJA0Yo4ezU77G+ym/5//vP9znHhi//P+Uxf9\n8cA/afgMC5KG5eDBwW/6f/PN7DoB+caNK1zJn3UWXHZZ6Yv+jBtXmz6lZmZYkFTgyJHC0/4G2gpw\n4ED/55gypfCT/jnnlD7y/z3v8dO/NNoZFqQGF2Pxi/6U2grw5pvZMvkmTCj89H/eeXDFFaUv+jPW\nvyxSQ/FXWqpDPT3ZSn2w5/2/807h8mPGFF70p9R5//kX/ZHUvAwL0igQY/YNfoO95O++ff2fY9Kk\nwk/6+ef89938f9JJXvRH0uAZFqQqeffd/hf9SW0JOHSocPmWlsKV/GmnZef9l7roz/HH16ZPSY1v\nWGEhhPDHwArgr2KMtyfm+03gz4AzgB3AH8UYHxnOa0sj7ejR7EI+g930v39//+eYPLkwAHz4w6Uv\n+nPiiV70R9LoMOSwEEL4MPAp4NkB5psDPAD8IfBd4BPAQyGEi2KMPyq13GuvvUZbW9tQy6sLy5Yt\nY+vWrSxcuJA1a9bUupyqWbNmDVu2bGHRokUsW7as1uUUePvtwW/637Mn+4KgfK2txz7l/9u/dfPz\nn+/ktNPG88UvXlP0oj/HHVebPitp1qxZ7Nq1i7PPPpt/+Zd/qXU5VTOa37eVtGLFCjo7O7nqqqv4\noz/6o1qXUzXN8ve2amKMZU/AJOAlYCHwGHB3Yt4NwLf73LcNuK/E/G1ABOKSJVfHffv2xUazbt26\nCC2xt89saokbNmyodWkV9cwzz8TW1gkFfba2Tojbt2+v2msePhzj7t0xPv98jJs3x9jREeM998T4\nxS/G+KlPxXjNNTHOmRPjjBkxTpoUY3a0QOF00kkxnnNOjPPmxXj99TF+5jMxfvnLMd53X4z/83/G\n+MQTMb70Uow//WmMR4/GeN999xUdz9WrV1etz1r47Gc/W7TPO+64o9alVVQt3re10NnZGUNoLegz\nhNa4devWWpdWUc3y97ZXV1dXb59tcQjr91JTiH3PkRqEEMI3gD0xxi+EEB4DtscSuyFCCD8G/kuM\n8a/z7vsycE2M8aIi87cBXfDntLSsYvHiS/je975bdo2jWQhjyfLW14B5wOPA7wNvEePh1KJ1Zdy4\n4+npGUffPltbD3Ho0MH0wnkOHBj8pv8338x2F+Q77rj+m/pLbfp/3/vKv+hPs4xns/RZqfftaDdm\nzDhiPJ6+fYZwkKNHD6UXriPN8r7t1d3dzezZswFmxxi7K/W8Ze+GCCHcAHwQ+NAgF5kOvNHnvjdy\n9ydczZEjZ7Bx41J27tzJWWedVW6po1K2OfMI2Rv3xty9N5IFwaXceuutDbGJbM2aNfT0vA38HX37\n7OlZxj33/HeuuOK3B3Xw38E+f59D6H/Rn/POK33Rn0mTqnfRn2uvvZbUeF5//fX8/d//fXVefATN\nmjWLVJ/nnXdeQ+ySSL9vl7J27dqG2CWxYsUKYuyh2HjGuJS77rqrIXZJNMvf25FQVlgIIZwK/BVw\nZczeaUMVyEYrYTmQfcRbunQpU6dOpb29nfb29mG8bO1t3bo1d2ten0fmA7B58+YRracSYoRf/KJw\npf/1rwfgPwEf6zN3O/AJ/uAPCo/cmzixcEX/q79aeivAlCmj56I/Tz75ZO5W8fF84oknRrSeatm1\na1fuVvE+d+zYMaL1VMuWLVtyt4r32dnZ2RBhobOzM3ereJ+PPvpoQ4SFRvx7m6+jo4OOjo6C+/YX\nO7K6Asr9kzsbOBnoCuGXn9VagHkhhNuA42L//Ro/Aab1uW8q/bc29LEK+BGwiW9+85sNs2Vh/vz5\nvPrqq2Sbwm7MeyR7Uy9cuLAGVfV36FD/0/5SWwHefbdw+RCWAbuBvpv5ngPu5XOfa6e9ffEvA8DE\niSPSVsXNnTuXhx56iFLjefnll9eirIqbOXMmL774IqX6PPvss2tRVsUtWLCA9evXU6rPRYsW1aKs\nilu0aBGPPfYYpfq86qqralFWxdXL39uhKvYBOm83REWVdcxCCGEicHqfu9cCLwB3xRhfKLLMBmBC\njPGavPv+N/BsjPEzReZvomMW7iVLuFuB26jmPrQYs9P+BnvJ35/+tP9zvOc96f39+Y+ddBKMH9+7\n77ewz0bb91uL8ayFZunz2DELjf2+PXbMQmGfjXvMQmO/b3uNimMWYowHyD7u/1II4QCwtzco5A5+\nfD3G+Ce5We4BtoYQbic7dbKdbAvFp9Kv9iUWL76ajo715ZRYFzZs+BY33HAjsDTv3hY2bPhWWc/z\nzjvZp//UwX+9gWDPnuwSwfnGji1c0Z9+enbef7FAcPLJ2fcDlOPpp5/k4ovn0tNzrM/W1gk8/fST\niaXqz+rVf8vv/u6/p+94rl79t7UqqSruuON2vvrVu+nb5x13lLzESl1qlvftli2bWLBgMTEe6zOE\nVrZs2VTDqiqvUn9vm92QzoYoeIIQNgM/7D0bIvfzqzHGW/LmuY7s4k2nAzuBO2KMG0s8XxvQ9eCD\nD/Lxj398WLWNdrfeeiubN2/+5Xm/R49ml/Ed7Kb/n/+8/3OecMLgjvqfOjWbdyQu+rN27Vo6Ozsb\n/nz166+/nieeeILLL7+8IQ5qLOW8885jx44dDX+dhWZ539511108+uijDX+dhb5/bxtVtbYsDDss\nVFpvWOjq6mqIizIdPDj4Tf979mRfD5xv3LiBV/y997/vfY1x0R9J0tCMit0Qylbme/cObtP/7t3Z\nNQL66j3tr3f6wAdKB4L3vrd6p/1JkjQYTR8WYoS33hr8JX/ffDNbJt/48YUr+VmzYMGC0hf9aW2t\nSauSJA1JQ4aFnp5spT6Yb/rbvTv7foB8IWQr9d5P+tOmFZ7333crwMSJfvqXJDWuuggLMWYH8w32\nkr/79vV/jkmTClf0F16YvuhPS8vI9ylJ0mg0asPCbbdlF/rpDQCH+pz229KSnc7Xu4I/9VSYPbv4\npv+TT67fi/5IklRrozYsjB8PF1xQetP/iSeOzGl/kiQ1u1EbFv7yL6EBzpyUJKnu+dlckiQlGRYk\nSVKSYUGSJCUZFiRJUpJhQZIkJRkWJElSkmFBkiQlGRYkSVKSYUGSJCUZFiRJUpJhQZIkJRkWJElS\nkmFBkiQlGRYkSVKSYUGSJCUZFiRJUpJhQZIkJRkWJElSkmFBkiQlGRYkSVKSYUGSJCUZFiRJUpJh\nQZIkJRkWJElSkmFBkiQlGRYkSVKSYUGSJCUZFiRJUpJhQZIkJRkWJElSkmFBkiQlGRYkSVKSYUGS\nJCUZFiRJUlJZYSGE8OkQwrMhhP256ckQwkcT898cQjgaQjiS+/doCOHg8MuWJEkjpdwtC/8K/CEw\nOzdtBv4hhDArscx+YHredPoQ6mxIy5Yt48wzz+TWW2+tdSlVtWbNGpYuXcratWtrXUpVrVixgoUL\nF3LXXXfVupSq2rFjB4888gg7d+6sdSlV1SzjaZ8alBjjsCZgL/A7JR67GdhX5vO1AbGrqys2qnXr\n1kVoiUDe1BI3bNhQ69Iq6plnnomtrRMK+mxtnRC3b99e69IqqrOzM4bQWtBnCK1x69attS6tovbu\n3RuXLLm6oM8lS66O+/btq3VpFdUs42mfjdVnr66urt4+2+Iw1+/503BCwhjgBuBt4JwS89wMHAJe\nBV4DHgLOHeB5Gz4sZEFhcoT1EV7L/Ts5QkutS6uoLCj077O1dUKtS6uo7A9R/z5DaK11aRW1ZMnV\nsaXlpII+W1pOikuWXF3r0iqqWcbTPhurz16jJiwA5wO/AHqAfcBHE/NeAtwEXABcDnwb+BnwK4ll\nGjos3HzzzbmBXB8h5k3fjEC85ZZbal1iRaxevTrZ5/3331/rEiviL/7iL5J9rly5stYlVsRLL72U\n7HPHjh21LrEimmU87bOx+sxXrbAwlLMhXgQuBD4C/A2wLoRwTrEZY4xPxRjXxxifizE+AfwGsAf4\nvYFeZPny5XzsYx8rmDo6OoZQ7uiydevW3K15fR6ZD8DmzZtHtJ5q2bJlS+5W8T47OztHspyqOdZH\n8T4fffTREa2nWl5++eXcreJ97tq1a0TrqZZmGU/7bIw+Ozo6+q0nly9fXpXXKjssxBgPxxhfiTF2\nxxi/CDwLfG6wywLbgZkDzbtq1Sq+/e1vF0zt7e3lljvqzJ8/P3fr8T6PZCFi4cKFI1pPtSxYsCB3\nq3ifixYtGslyquZYH8X7vOqqq0a0nmqZMWNG7lbxPmfOHPBXui40y3jaZ2P02d7e3m89uWrVqqq8\nVojZpv+hP0EIncCPY4y3DGLeMcDzwMMxxi+UmKcN6Orq6qKtrW1YtY1WIYwFJgH3kiXcrcBtwFtk\neaoxjBt3PD094+jbZ2vrIQ4dapwzaMeMGUeMx9O3zxAOcvToodoWV0Ef/eivs2nTUxw5cg+9fba0\nfI7Fiy/he9/7bq3Lq5hmGU/7bKw+e3V3dzN79myA2THG7oo9cTn7LIAVwGVkpz+eD6wEDgMLc4+v\nA76SN/+XgCuBM4GLgA7gACUOiIxNcMxCjDFu2LAhNsPZENu3b2+KsyG2bt3aFEdb79u3rynOhmiW\n8bTPxuqz16g4wBFYDbxCdgbET4BHe4NC7vHNwH/L+/lu4P/k5v+/wD8CFwzwGg0fFnrdcsst8Ywz\nzmiYgxpLuf/+++NNN93UMAc1lrJy5cp4xRVXNORBU/l27NgRH3744YY5qLGUZhlP+2ws1QoLw94N\nUWnNsBtCkqRqqNZuCL8bQpIkJRkWJElSkmFBkiQlGRYkSVKSYUGSJCUZFiRJUpJhQZIkJRkWJElS\nkmFBkiQlGRYkSVKSYUGSJCUZFiRJUpJhQZIkJRkWJElSkmFBkiQlGRYkSVKSYUGSJCUZFiRJUpJh\nQZIkJRkWJElSkmFBkiQlGRYkSVKSYUGSJCUZFiRJUpJhQZIkJRkWJElSkmFBkiQlGRYkSVKSYUGS\nJCUZFiRJUpJhQZIkJRkWJElSkmFBkiQlGRYkSVKSYUGSJCUZFiRJUpJhQZIkJRkWJElSkmFBkiQl\nGRYkSVJSWWEhhPDpEMKzIYT9uenJEMJHB1jmN0MIL4QQ3s4t+2vDK1mSJI2kcrcs/Cvwh8Ds3LQZ\n+IcQwqxiM4cQ5gAPAH8HfBB4CHgohHDukCuWJEkjqqywEGP8bozxezHGXbnpPwFvAZeUWORzwCMx\nxrtjjC/FGO8EuoHbhld2Y1izZg1Lly5l7dq1tS6lqpqlz40bN/Jnf/ZnfP/73691KVW1Y8cOHnnk\nEXbu3FnrUlQBzfL7qWGKMQ5pIgsaNwBvA+eUmOfHwGf73PdlYHvieduA2NXVFRvVM888E1tbJ0Tg\nl1Nr64R+qX1MAAALdklEQVS4ffv2WpdWUc3S565du+KUKdMK+pwyZVp85ZVXal1aRe3duzcuWXJ1\nQZ9Lllwd9+3bV+vSNATN8vvZbLq6unrHsy0Ocf1ebCr7AMcQwvkhhF8A7wL3AdfGGF8sMft04I0+\n972Ru79pzZlzOT0944D1wGvAenp6xnHxxXNrXFllNUufH/nIpezd+w75fe7d+w4f/vCcGldWWZ/4\nxFI2bXqK/D43bXqK9vabalyZhqJZfj9VGUM5G+JF4ELgI8DfAOtCCOeUsXwgSz1Nac2aNfT0vA18\nDbgROC3377309LzdMJsCm6XPjRs3snfvGxTrc+/eNxpml8SOHTvYuPFhjhz5a/L7PHLkHjZufNhd\nEnWmWX4/VTljy10gxngYeCX3Y3cI4WKyYxP+Q5HZfwJM63PfVPpvbehn+fLlTJ48ueC+9vZ22tvb\nyy15VNmyZUvu1rw+j8wHoLOzk2XLlo1gRdXRLH3+0z/9U+5W8T63bdvGlVdeOaI1VcPLL7+cu1W8\nz127dnHWWWeNaE0aumb5/Wx0HR0ddHR0FNy3f//+qrxW2WGhiDHAcSUe2wYsAv46774rc/cnrVq1\nira2tuFXN8osWLCA9evXA4+TJfleWwFYtGhRLcqquGbp8yMf+UjuVvE+58xpjF0RM2bMyN0q3ufM\nmTNHuiQNQ7P8fja6Yh+gu7u7mT17duVfrJwDHIAVwGXA6cD5wErgMLAw9/g64Ct5888BDgG3Ax8g\nO7jxHeDcxGs0/AGO2UFFkyN8M8JruX8nx9bWCbUuraKapc/s4Mb+fU6ZMq3WpVXUkiVXx5aWkwr6\nbGk5KS5ZcnWtS9MQNMvvZ7MZLQc4TssFgheBTWTXWrgqxrg59/ip5B28GGPcBrQDvwf8EPgN4JoY\n44/KfN2G8vTTT9LaeghYCrwfWEpr6yGefvrJGldWWc3S5z//8zamTBlPfp9Tpoznn/95wA1odaWj\nYz2LF19Cfp+LF19CR8f6GlemoWiW309VRohxdB1rGEJoA7q6uroacjdEvrVr19LZ2cmiRYsaev9g\ns/T5/e9/n23btjFnzpyGOE6hlJ07d7Jr1y5mzpzpcQoNoFl+P5tF3m6I2THG7ko9r2FBkqQGUa2w\n4BdJSZKkJMOCJElKMixIkqQkw4IkSUoyLEiSpCTDgiRJSjIsSJKkJMOCJElKMixIkqQkw4IkSUoy\nLEiSpCTDgiRJSjIsSJKkJMOCJElKMixIkqQkw4IkSUoyLEiSpCTDgiRJSjIsSJKkJMOCJElKMixI\nkqQkw4IkSUoyLEiSpCTDgiRJSjIsSJKkJMOCJElKMixIkqQkw4IkSUoyLEiSpCTDgiRJSjIsSJKk\nJMOCJElKMixIkqQkw4IkSUoyLEiSpCTDgiRJSjIsSJKkJMOCJElKMixIkqQkw0KNdXR01LqEEWGf\njcU+G4t9aiBlhYUQwh+HEJ4OIfw8hPBGCOHBEMLZAyxzcwjhaAjhSO7foyGEg8Mru3E0y5vXPhuL\nfTYW+9RAyt2ycDnwX4GPAIuBVuDREMKEAZbbD0zPm04v83UlSVKNjC1n5hjj1fk/hxCWAbuB2cAP\n0ovGPWVXJ0mSam64xyycAERg3wDzTQohvBpCeC2E8FAI4dxhvq4kSRohZW1ZyBdCCMBfAT+IMf4o\nMetLwC3Ac8Bk4A7gyRDCeTHG14vMPx7ghRdeGGppdWX//v10d3fXuoyqs8/GYp+NxT4bR966c3wl\nnzfEGIe2YAh/AywBLo0x/r8ylhsLvAA8EGO8s8jjnwC+NaSiJEkSwI0xxgcq9WRD2rIQQrgXuBq4\nvJygABBjPBxC2A7MLDHLRuBG4FXgnaHUJ0lSkxoPnEG2Lq2Ysrcs5ILCNcD8GOMrZb9gCGOA54GH\nY4xfKHd5SZI0ssrashBCuA9oBz4GHAghTMs9tD/G+E5unm8Ar8cY/yT385eAp4BdZAdE/keyUydX\nV6QDSZJUVeXuhvg02dkPW/rc/zvAutzt04AjeY+dCHyd7PoKPwW6gDkxxhfLLVaSJI28IR/gKEmS\nmoPfDSFJkpIMC5IkKWnEw0II4fIQwrdDCK/nvlTqY4NYZkEIoSuE8E4IYUcI4eaRqHU4yu0zhDA/\n74u2eqcjIYSpI1XzUAzly8Vyy/1mCOGFEMLbIYRnQwi/NhL1DlWzfIlaCOHTufHYn5ueDCF8dIBl\n6mosofw+63Esi8m9j4+GEO4eYL66G9N8g+mzXsc0hHBnkXVF6sKIFRnPWmxZmAj8EPh9soMlk0II\nZwDfATqBC4F7gNUhhCurV2JFlNVnTgTO4tgXbp0SY9xdnfIqpuwvFwshzAEeAP4O+CDwEDDaLwPe\nLF+i9q/AH5J938tsYDPwDyGEWcVmrtOxhDL7zKm3sSwQQvgw8Cng2QHmq9cxBQbfZ069junzwDSO\n1X1ZqRkrNp4xxppNwFHgYwPM85+B5/rc10F2nYaa1l/hPueTnUXy3lrXO8xe35fr97LEPBuAb/e5\nbxtwX63rr3CfNwP7al1rBXrdC/xOo47lIPus67EEJpFden8h8Bhwd2Leuh3TMvusyzEF7gS6y5i/\nIuNZD8csXAJs6nPfRmBODWqptgD8MITwf0MIj4YQ5ta6oCEYzJeLzaH+x7Thv0QthDAmhHADcDzZ\nH5di6n4sB9kn1PFYAl8D/jHGuHkQ89bzmJbTJ9TvmJ6V28X9cghhfQjhtMS8FRnPIX+R1AiaDrzR\n5743gPeGEI6LMb5bg5qq4f8B/x54BjiObDPalhDCxTHGH9a0skEKYdBfLlZqTKdXq7ZKKqPPcr9E\nbVQIIZxPttIcD/wCuDaWvi5K3Y5lmX3W5VgC5ILQB4EPDXKRuhzTIfRZr2P6FLCMrP5TgC8Dj4cQ\nzo8xHigyf0XGsx7CQjEh92/DXCQixrgD2JF311MhhBnAcrLNZfXgPuBc4NIhLBuon/EcVJ8xxqfI\nfrEBCCFsI/sStd8j25Q4Wr1IdnzQCcB1wLoQwrzEirSvehnLQfdZr2MZQjiVLNheGWPsGc5TMYrH\ndCh91uuYxhjzv/Ph+RDC08CPgd8C7h/k05Q9nvUQFn5CdiBHvqnAz2OMh2pQz0h6mqGteEdcKO/L\nxUqNad/0O+qU2WeBOPCXqI0KMcbDQO/3vnSHEC4GPgf8hyKz1+1Yltlnv2XrYSzJDt48GejKbRED\naAHmhRBuA46LuZ3YeepxTIfSZ4E6GtMCMcb9IYQdlK67IuNZD8csbAMW9bnvKtL7FhvFB8l2T4xq\n4diXi10RY3xtEIsUG9MrGeVjOoQ++y4/BjifOhjTPsaQ7Rorpi7HsoRUnwXqaCw3Ab9K9rfkwtz0\nDLAeuLDECrQex3QofRaoozEtEEKYBMygdN2VGc8aHMk5kWwgP0h2NPkf5H4+Lff4SuAbefOfAbxF\ndlbEB4DPAIeAxbU+KrXCfX6O7Au6ZgDnkW1S6wEW1LqXAfq8j+w7Py4nS6+90/i8eb4BfCXv5zm5\nMbw9N6ZfJvs68nNr3U+F+/xS7pfyTOAisrN4DgDn1LqfRJ8ryE7DOp3sD+dK4DCwMPf4unofyyH2\nWXdjmei94CyBRvj9HGKfdTmmwFeBebn37lzg+2RbCabkHq/K72gtdkN8iGwQY276L7n7v0F2sMl0\nsi+jAiDG+GoI4deBu4HPAv8G3Bpj7Ht052hTVp/AuNw8/w44SHbQzaIY4+MjVfAQlf3lYjHGbSGE\ndrI/2CuAncA1MX2wYK01y5eoTSPr5xSyc9CfA66Kx44uP5VspQrU7VhCmX1Sn2NZSt9P2Y3w+1lM\nsk/qd0xPJbtuwhRgD/AD4JIY4968xyv+O+oXSUmSpKR6OGZBkiTVkGFBkiQlGRYkSVKSYUGSJCUZ\nFiRJUpJhQZIkJRkWJElSkmFBkiQlGRYkSVKSYUGSJCUZFiRJUtL/B7GtDE6Kl0/3AAAAAElFTkSu\nQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x10b3167b8>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"pred_1 = 1 * slope + intercept\n",
"pred_5 = 5 * slope + intercept\n",
"plt.scatter(movies[\"Metacritic_norm_round\"], movies[\"Fandango_Stars\"])\n",
"plt.plot([1,5],[pred_1,pred_5])\n",
"plt.xlim(1,5)\n",
"plt.show()"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.4.4"
}
},
"nbformat": 4,
"nbformat_minor": 0
}