diff --git a/CleaningFunctions.py b/CleaningFunctions.py
new file mode 100644
index 0000000..ae967c3
--- /dev/null
+++ b/CleaningFunctions.py
@@ -0,0 +1,31 @@
+"""
+Each support function should have an informative name and return the partially cleaned bit of the dataset.
+"""
+import pandas as pd
+
+
+# def search(dataframe, column_to_search, condition, columns):
+    
+#     dataframe=df
+    
+#     new_df=df.loc[df[columns_to_search]condition,columns]
+    
+#     return new_df
+
+class Clean():
+    
+    def __init__(self,name):
+        self.name=name
+    
+    
+    def rename_columns(self,columns,new_names):
+        for column,name in list(zip(columns,new_names)):
+            dataframe.rename(columns={column:name},inplace=True)
+        return dataframe
+    
+# def drop_nulls(dataframe,column_to_search):
+#     # The null values in our dataframe are listed as "\N"
+#     df=dataframe
+#     df.loc[df[column_to_search]==r"\N"]
+    
+    
diff --git a/Data_Cleaning.ipynb b/Data_Cleaning(old).ipynb
similarity index 69%
rename from Data_Cleaning.ipynb
rename to Data_Cleaning(old).ipynb
index 6a63f0e..6316eb7 100644
--- a/Data_Cleaning.ipynb
+++ b/Data_Cleaning(old).ipynb
@@ -1080,7 +1080,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 21,
    "metadata": {},
    "outputs": [
     {
@@ -1182,996 +1182,34 @@
        "      <td>8.8</td>\n",
        "      <td>1547334</td>\n",
        "    </tr>\n",
-       "    <tr>\n",
-       "      <th>5</th>\n",
-       "      <td>tt0167260</td>\n",
-       "      <td>movie</td>\n",
-       "      <td>The Lord of the Rings: The Return of the King</td>\n",
-       "      <td>The Lord of the Rings: The Return of the King</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2003</td>\n",
-       "      <td>201</td>\n",
-       "      <td>Adventure,Drama,Fantasy</td>\n",
-       "      <td>8.9</td>\n",
-       "      <td>1532076</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>6</th>\n",
-       "      <td>tt1345836</td>\n",
-       "      <td>movie</td>\n",
-       "      <td>The Dark Knight Rises</td>\n",
-       "      <td>The Dark Knight Rises</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2012</td>\n",
-       "      <td>164</td>\n",
-       "      <td>Action,Thriller</td>\n",
-       "      <td>8.4</td>\n",
-       "      <td>1420142</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>7</th>\n",
-       "      <td>tt0167261</td>\n",
-       "      <td>movie</td>\n",
-       "      <td>The Lord of the Rings: The Two Towers</td>\n",
-       "      <td>The Lord of the Rings: The Two Towers</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2002</td>\n",
-       "      <td>179</td>\n",
-       "      <td>Adventure,Drama,Fantasy</td>\n",
-       "      <td>8.7</td>\n",
-       "      <td>1385789</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8</th>\n",
-       "      <td>tt0816692</td>\n",
-       "      <td>movie</td>\n",
-       "      <td>Interstellar</td>\n",
-       "      <td>Interstellar</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2014</td>\n",
-       "      <td>169</td>\n",
-       "      <td>Adventure,Drama,Sci-Fi</td>\n",
-       "      <td>8.6</td>\n",
-       "      <td>1346300</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>9</th>\n",
-       "      <td>tt1853728</td>\n",
-       "      <td>movie</td>\n",
-       "      <td>Django Unchained</td>\n",
-       "      <td>Django Unchained</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2012</td>\n",
-       "      <td>165</td>\n",
-       "      <td>Drama,Western</td>\n",
-       "      <td>8.4</td>\n",
-       "      <td>1248003</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>10</th>\n",
-       "      <td>tt0172495</td>\n",
-       "      <td>movie</td>\n",
-       "      <td>Gladiator</td>\n",
-       "      <td>Gladiator</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2000</td>\n",
-       "      <td>155</td>\n",
-       "      <td>Action,Adventure,Drama</td>\n",
-       "      <td>8.5</td>\n",
-       "      <td>1245515</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>11</th>\n",
-       "      <td>tt0372784</td>\n",
-       "      <td>movie</td>\n",
-       "      <td>Batman Begins</td>\n",
-       "      <td>Batman Begins</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2005</td>\n",
-       "      <td>140</td>\n",
-       "      <td>Action,Adventure</td>\n",
-       "      <td>8.2</td>\n",
-       "      <td>1223829</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>12</th>\n",
-       "      <td>tt0848228</td>\n",
-       "      <td>movie</td>\n",
-       "      <td>The Avengers</td>\n",
-       "      <td>The Avengers</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2012</td>\n",
-       "      <td>143</td>\n",
-       "      <td>Action,Adventure,Sci-Fi</td>\n",
-       "      <td>8.0</td>\n",
-       "      <td>1206109</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>13</th>\n",
-       "      <td>tt0361748</td>\n",
-       "      <td>movie</td>\n",
-       "      <td>Inglourious Basterds</td>\n",
-       "      <td>Inglourious Basterds</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2009</td>\n",
-       "      <td>153</td>\n",
-       "      <td>Adventure,Drama,War</td>\n",
-       "      <td>8.3</td>\n",
-       "      <td>1160855</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>14</th>\n",
-       "      <td>tt0407887</td>\n",
-       "      <td>movie</td>\n",
-       "      <td>The Departed</td>\n",
-       "      <td>The Departed</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2006</td>\n",
-       "      <td>151</td>\n",
-       "      <td>Crime,Drama,Thriller</td>\n",
-       "      <td>8.5</td>\n",
-       "      <td>1102956</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>15</th>\n",
-       "      <td>tt0482571</td>\n",
-       "      <td>movie</td>\n",
-       "      <td>The Prestige</td>\n",
-       "      <td>The Prestige</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2006</td>\n",
-       "      <td>130</td>\n",
-       "      <td>Drama,Mystery,Sci-Fi</td>\n",
-       "      <td>8.5</td>\n",
-       "      <td>1094124</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>16</th>\n",
-       "      <td>tt0993846</td>\n",
-       "      <td>movie</td>\n",
-       "      <td>The Wolf of Wall Street</td>\n",
-       "      <td>The Wolf of Wall Street</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2013</td>\n",
-       "      <td>180</td>\n",
-       "      <td>Biography,Crime,Drama</td>\n",
-       "      <td>8.2</td>\n",
-       "      <td>1068635</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>17</th>\n",
-       "      <td>tt0499549</td>\n",
-       "      <td>movie</td>\n",
-       "      <td>Avatar</td>\n",
-       "      <td>Avatar</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2009</td>\n",
-       "      <td>162</td>\n",
-       "      <td>Action,Adventure,Fantasy</td>\n",
-       "      <td>7.8</td>\n",
-       "      <td>1065648</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>18</th>\n",
-       "      <td>tt0209144</td>\n",
-       "      <td>movie</td>\n",
-       "      <td>Memento</td>\n",
-       "      <td>Memento</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2000</td>\n",
-       "      <td>113</td>\n",
-       "      <td>Mystery,Thriller</td>\n",
-       "      <td>8.4</td>\n",
-       "      <td>1052013</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>19</th>\n",
-       "      <td>tt0120689</td>\n",
-       "      <td>movie</td>\n",
-       "      <td>The Green Mile</td>\n",
-       "      <td>The Green Mile</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1999</td>\n",
-       "      <td>189</td>\n",
-       "      <td>Crime,Drama,Fantasy</td>\n",
-       "      <td>8.6</td>\n",
-       "      <td>1048833</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>20</th>\n",
-       "      <td>tt1130884</td>\n",
-       "      <td>movie</td>\n",
-       "      <td>Shutter Island</td>\n",
-       "      <td>Shutter Island</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2010</td>\n",
-       "      <td>138</td>\n",
-       "      <td>Mystery,Thriller</td>\n",
-       "      <td>8.1</td>\n",
-       "      <td>1035210</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>21</th>\n",
-       "      <td>tt0169547</td>\n",
-       "      <td>movie</td>\n",
-       "      <td>American Beauty</td>\n",
-       "      <td>American Beauty</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1999</td>\n",
-       "      <td>122</td>\n",
-       "      <td>Drama</td>\n",
-       "      <td>8.3</td>\n",
-       "      <td>1008607</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>22</th>\n",
-       "      <td>tt2015381</td>\n",
-       "      <td>movie</td>\n",
-       "      <td>Guardians of the Galaxy</td>\n",
-       "      <td>Guardians of the Galaxy</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2014</td>\n",
-       "      <td>121</td>\n",
-       "      <td>Action,Adventure,Comedy</td>\n",
-       "      <td>8.0</td>\n",
-       "      <td>979707</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>23</th>\n",
-       "      <td>tt0325980</td>\n",
-       "      <td>movie</td>\n",
-       "      <td>Pirates of the Caribbean: The Curse of the Bla...</td>\n",
-       "      <td>Pirates of the Caribbean: The Curse of the Bla...</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2003</td>\n",
-       "      <td>143</td>\n",
-       "      <td>Action,Adventure,Fantasy</td>\n",
-       "      <td>8.0</td>\n",
-       "      <td>976840</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>24</th>\n",
-       "      <td>tt0434409</td>\n",
-       "      <td>movie</td>\n",
-       "      <td>V for Vendetta</td>\n",
-       "      <td>V for Vendetta</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2005</td>\n",
-       "      <td>132</td>\n",
-       "      <td>Action,Drama,Sci-Fi</td>\n",
-       "      <td>8.2</td>\n",
-       "      <td>970118</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>25</th>\n",
-       "      <td>tt0266697</td>\n",
-       "      <td>movie</td>\n",
-       "      <td>Kill Bill: Vol. 1</td>\n",
-       "      <td>Kill Bill: Vol. 1</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2003</td>\n",
-       "      <td>111</td>\n",
-       "      <td>Action,Crime,Thriller</td>\n",
-       "      <td>8.1</td>\n",
-       "      <td>931412</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>26</th>\n",
-       "      <td>tt0910970</td>\n",
-       "      <td>movie</td>\n",
-       "      <td>WALL·E</td>\n",
-       "      <td>WALL·E</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2008</td>\n",
-       "      <td>98</td>\n",
-       "      <td>Adventure,Animation,Family</td>\n",
-       "      <td>8.4</td>\n",
-       "      <td>930323</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>27</th>\n",
-       "      <td>tt0266543</td>\n",
-       "      <td>movie</td>\n",
-       "      <td>Finding Nemo</td>\n",
-       "      <td>Finding Nemo</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2003</td>\n",
-       "      <td>100</td>\n",
-       "      <td>Adventure,Animation,Comedy</td>\n",
-       "      <td>8.1</td>\n",
-       "      <td>888997</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>28</th>\n",
-       "      <td>tt0371746</td>\n",
-       "      <td>movie</td>\n",
-       "      <td>Iron Man</td>\n",
-       "      <td>Iron Man</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2008</td>\n",
-       "      <td>126</td>\n",
-       "      <td>Action,Adventure,Sci-Fi</td>\n",
-       "      <td>7.9</td>\n",
-       "      <td>886426</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>29</th>\n",
-       "      <td>tt1049413</td>\n",
-       "      <td>movie</td>\n",
-       "      <td>Up</td>\n",
-       "      <td>Up</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2009</td>\n",
-       "      <td>96</td>\n",
-       "      <td>Adventure,Animation,Comedy</td>\n",
-       "      <td>8.2</td>\n",
-       "      <td>868602</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",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>111178</th>\n",
-       "      <td>tt0797035</td>\n",
-       "      <td>movie</td>\n",
-       "      <td>La otra copa</td>\n",
-       "      <td>La otra copa</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2006</td>\n",
-       "      <td>88</td>\n",
-       "      <td>Documentary</td>\n",
-       "      <td>6.8</td>\n",
-       "      <td>5</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>111179</th>\n",
-       "      <td>tt1325614</td>\n",
-       "      <td>movie</td>\n",
-       "      <td>Utopia</td>\n",
-       "      <td>Outopia</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2004</td>\n",
-       "      <td>85</td>\n",
-       "      <td>Fantasy,Mystery</td>\n",
-       "      <td>3.6</td>\n",
-       "      <td>5</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>111180</th>\n",
-       "      <td>tt4326536</td>\n",
-       "      <td>movie</td>\n",
-       "      <td>The Secret to My Silky Skin</td>\n",
-       "      <td>The Secret to My Silky Skin</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2014</td>\n",
-       "      <td>81</td>\n",
-       "      <td>Drama</td>\n",
-       "      <td>5.2</td>\n",
-       "      <td>5</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>111181</th>\n",
-       "      <td>tt3394556</td>\n",
-       "      <td>movie</td>\n",
-       "      <td>Robert Hainard: L'art, la nature, la pensée</td>\n",
-       "      <td>Robert Hainard: L'art, la nature, la pensée</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2013</td>\n",
-       "      <td>91</td>\n",
-       "      <td>Documentary</td>\n",
-       "      <td>8.0</td>\n",
-       "      <td>5</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>111182</th>\n",
-       "      <td>tt5994668</td>\n",
-       "      <td>movie</td>\n",
-       "      <td>Paper Dreams</td>\n",
-       "      <td>Paper Dreams</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2015</td>\n",
-       "      <td>75</td>\n",
-       "      <td>Documentary</td>\n",
-       "      <td>6.4</td>\n",
-       "      <td>5</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>111183</th>\n",
-       "      <td>tt1316047</td>\n",
-       "      <td>movie</td>\n",
-       "      <td>The Gadarene Swine</td>\n",
-       "      <td>The Gadarene Swine</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2011</td>\n",
-       "      <td>88</td>\n",
-       "      <td>Drama</td>\n",
-       "      <td>7.4</td>\n",
-       "      <td>5</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>111184</th>\n",
-       "      <td>tt4314120</td>\n",
-       "      <td>movie</td>\n",
-       "      <td>Beyond Measure</td>\n",
-       "      <td>Beyond Measure</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2015</td>\n",
-       "      <td>80</td>\n",
-       "      <td>Documentary,News</td>\n",
-       "      <td>8.2</td>\n",
-       "      <td>5</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>111185</th>\n",
-       "      <td>tt6007538</td>\n",
-       "      <td>movie</td>\n",
-       "      <td>În cãutarea tatãlui pierdut</td>\n",
-       "      <td>În cãutarea tatãlui pierdut</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2016</td>\n",
-       "      <td>61</td>\n",
-       "      <td>Documentary</td>\n",
-       "      <td>7.8</td>\n",
-       "      <td>5</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>111186</th>\n",
-       "      <td>tt1316063</td>\n",
-       "      <td>movie</td>\n",
-       "      <td>The Lost Woman</td>\n",
-       "      <td>The Lost Woman</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2009</td>\n",
-       "      <td>88</td>\n",
-       "      <td>Drama,Romance,Thriller</td>\n",
-       "      <td>7.6</td>\n",
-       "      <td>5</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>111187</th>\n",
-       "      <td>tt0388397</td>\n",
-       "      <td>movie</td>\n",
-       "      <td>Scratch</td>\n",
-       "      <td>Scratch</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2000</td>\n",
-       "      <td>90</td>\n",
-       "      <td>Horror</td>\n",
-       "      <td>5.6</td>\n",
-       "      <td>5</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>111188</th>\n",
-       "      <td>tt2082344</td>\n",
-       "      <td>movie</td>\n",
-       "      <td>The Way - Man of the White Porcelain</td>\n",
-       "      <td>Michi: Hakuji no hito</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2012</td>\n",
-       "      <td>118</td>\n",
-       "      <td>History</td>\n",
-       "      <td>6.8</td>\n",
-       "      <td>5</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>111189</th>\n",
-       "      <td>tt6005986</td>\n",
-       "      <td>movie</td>\n",
-       "      <td>Santoro O Homem e Sua Música</td>\n",
-       "      <td>Santoro O Homem e Sua Música</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2015</td>\n",
-       "      <td>75</td>\n",
-       "      <td>Documentary</td>\n",
-       "      <td>4.6</td>\n",
-       "      <td>5</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>111190</th>\n",
-       "      <td>tt0805181</td>\n",
-       "      <td>movie</td>\n",
-       "      <td>Aoi uta - Nodo jiman Seishun hen</td>\n",
-       "      <td>Aoi uta - Nodo jiman Seishun hen</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2006</td>\n",
-       "      <td>115</td>\n",
-       "      <td>Drama</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>5</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>111191</th>\n",
-       "      <td>tt0308220</td>\n",
-       "      <td>movie</td>\n",
-       "      <td>En mai, fais ce qu'il te plaît</td>\n",
-       "      <td>En mai, fais ce qu'il te plaît</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2002</td>\n",
-       "      <td>60</td>\n",
-       "      <td>Animation</td>\n",
-       "      <td>5.8</td>\n",
-       "      <td>5</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>111192</th>\n",
-       "      <td>tt1316079</td>\n",
-       "      <td>movie</td>\n",
-       "      <td>Summer People</td>\n",
-       "      <td>Summer People</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2008</td>\n",
-       "      <td>67</td>\n",
-       "      <td>Horror</td>\n",
-       "      <td>4.8</td>\n",
-       "      <td>5</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>111193</th>\n",
-       "      <td>tt3807466</td>\n",
-       "      <td>movie</td>\n",
-       "      <td>Davin</td>\n",
-       "      <td>Davin</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2014</td>\n",
-       "      <td>93</td>\n",
-       "      <td>Drama</td>\n",
-       "      <td>7.2</td>\n",
-       "      <td>5</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>111194</th>\n",
-       "      <td>tt2082226</td>\n",
-       "      <td>movie</td>\n",
-       "      <td>Cartography of Loneliness</td>\n",
-       "      <td>Cartography of Loneliness</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2011</td>\n",
-       "      <td>69</td>\n",
-       "      <td>Biography,Documentary</td>\n",
-       "      <td>6.2</td>\n",
-       "      <td>5</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>111195</th>\n",
-       "      <td>tt4314934</td>\n",
-       "      <td>movie</td>\n",
-       "      <td>Black Women in Medicine</td>\n",
-       "      <td>Black Women in Medicine</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2016</td>\n",
-       "      <td>57</td>\n",
-       "      <td>Biography,Documentary</td>\n",
-       "      <td>8.0</td>\n",
-       "      <td>5</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>111196</th>\n",
-       "      <td>tt3806844</td>\n",
-       "      <td>movie</td>\n",
-       "      <td>Noon Gun</td>\n",
-       "      <td>Noon Gun</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2015</td>\n",
-       "      <td>70</td>\n",
-       "      <td>Drama</td>\n",
-       "      <td>6.8</td>\n",
-       "      <td>5</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>111197</th>\n",
-       "      <td>tt6000692</td>\n",
-       "      <td>movie</td>\n",
-       "      <td>Clear Skies 2</td>\n",
-       "      <td>Clear Skies 2</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2009</td>\n",
-       "      <td>45</td>\n",
-       "      <td>Action,Animation,Sci-Fi</td>\n",
-       "      <td>8.2</td>\n",
-       "      <td>5</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>111198</th>\n",
-       "      <td>tt4315542</td>\n",
-       "      <td>movie</td>\n",
-       "      <td>Thunichal</td>\n",
-       "      <td>Thunichal</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2010</td>\n",
-       "      <td>115</td>\n",
-       "      <td>Action</td>\n",
-       "      <td>3.2</td>\n",
-       "      <td>5</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>111199</th>\n",
-       "      <td>tt3395746</td>\n",
-       "      <td>movie</td>\n",
-       "      <td>Yatra - Uma Viagem Externa, Interna e Secreta</td>\n",
-       "      <td>Yatra - Uma Viagem Externa, Interna e Secreta</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2014</td>\n",
-       "      <td>77</td>\n",
-       "      <td>Documentary</td>\n",
-       "      <td>8.8</td>\n",
-       "      <td>5</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>111200</th>\n",
-       "      <td>tt4316098</td>\n",
-       "      <td>movie</td>\n",
-       "      <td>La Pasión de Verónica Videla</td>\n",
-       "      <td>La Pasión de Verónica Videla</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2014</td>\n",
-       "      <td>83</td>\n",
-       "      <td>Drama</td>\n",
-       "      <td>7.2</td>\n",
-       "      <td>5</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>111201</th>\n",
-       "      <td>tt1318810</td>\n",
-       "      <td>movie</td>\n",
-       "      <td>Alicia &amp; John, el peronismo olvidado</td>\n",
-       "      <td>Alicia &amp; John, el peronismo olvidado</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2008</td>\n",
-       "      <td>90</td>\n",
-       "      <td>Documentary</td>\n",
-       "      <td>7.8</td>\n",
-       "      <td>5</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>111202</th>\n",
-       "      <td>tt4317320</td>\n",
-       "      <td>movie</td>\n",
-       "      <td>Underdoges</td>\n",
-       "      <td>Underdoges</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2016</td>\n",
-       "      <td>77</td>\n",
-       "      <td>Comedy,Drama</td>\n",
-       "      <td>4.8</td>\n",
-       "      <td>5</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>111203</th>\n",
-       "      <td>tt3806902</td>\n",
-       "      <td>movie</td>\n",
-       "      <td>For My Daughter</td>\n",
-       "      <td>For My Daughter</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2013</td>\n",
-       "      <td>96</td>\n",
-       "      <td>Drama,Family</td>\n",
-       "      <td>8.2</td>\n",
-       "      <td>5</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>111204</th>\n",
-       "      <td>tt1319621</td>\n",
-       "      <td>movie</td>\n",
-       "      <td>El fin de la espera</td>\n",
-       "      <td>El fin de la espera</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2008</td>\n",
-       "      <td>90</td>\n",
-       "      <td>Drama</td>\n",
-       "      <td>5.6</td>\n",
-       "      <td>5</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>111205</th>\n",
-       "      <td>tt1319658</td>\n",
-       "      <td>movie</td>\n",
-       "      <td>Return to Bolivia</td>\n",
-       "      <td>Return to Bolivia</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2008</td>\n",
-       "      <td>90</td>\n",
-       "      <td>Documentary</td>\n",
-       "      <td>6.6</td>\n",
-       "      <td>5</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>111206</th>\n",
-       "      <td>tt7182984</td>\n",
-       "      <td>movie</td>\n",
-       "      <td>Adieu à l'Afrique</td>\n",
-       "      <td>Adieu à l'Afrique</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2017</td>\n",
-       "      <td>87</td>\n",
-       "      <td>Documentary</td>\n",
-       "      <td>6.2</td>\n",
-       "      <td>5</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>111207</th>\n",
-       "      <td>tt7918964</td>\n",
-       "      <td>movie</td>\n",
-       "      <td>Look to the Sky</td>\n",
-       "      <td>Look to the Sky</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2017</td>\n",
-       "      <td>72</td>\n",
-       "      <td>Documentary</td>\n",
-       "      <td>9.2</td>\n",
-       "      <td>5</td>\n",
-       "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>111208 rows × 10 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
-       "           tconst titleType  \\\n",
-       "0       tt0468569     movie   \n",
-       "1       tt1375666     movie   \n",
-       "2       tt0137523     movie   \n",
-       "3       tt0133093     movie   \n",
-       "4       tt0120737     movie   \n",
-       "5       tt0167260     movie   \n",
-       "6       tt1345836     movie   \n",
-       "7       tt0167261     movie   \n",
-       "8       tt0816692     movie   \n",
-       "9       tt1853728     movie   \n",
-       "10      tt0172495     movie   \n",
-       "11      tt0372784     movie   \n",
-       "12      tt0848228     movie   \n",
-       "13      tt0361748     movie   \n",
-       "14      tt0407887     movie   \n",
-       "15      tt0482571     movie   \n",
-       "16      tt0993846     movie   \n",
-       "17      tt0499549     movie   \n",
-       "18      tt0209144     movie   \n",
-       "19      tt0120689     movie   \n",
-       "20      tt1130884     movie   \n",
-       "21      tt0169547     movie   \n",
-       "22      tt2015381     movie   \n",
-       "23      tt0325980     movie   \n",
-       "24      tt0434409     movie   \n",
-       "25      tt0266697     movie   \n",
-       "26      tt0910970     movie   \n",
-       "27      tt0266543     movie   \n",
-       "28      tt0371746     movie   \n",
-       "29      tt1049413     movie   \n",
-       "...           ...       ...   \n",
-       "111178  tt0797035     movie   \n",
-       "111179  tt1325614     movie   \n",
-       "111180  tt4326536     movie   \n",
-       "111181  tt3394556     movie   \n",
-       "111182  tt5994668     movie   \n",
-       "111183  tt1316047     movie   \n",
-       "111184  tt4314120     movie   \n",
-       "111185  tt6007538     movie   \n",
-       "111186  tt1316063     movie   \n",
-       "111187  tt0388397     movie   \n",
-       "111188  tt2082344     movie   \n",
-       "111189  tt6005986     movie   \n",
-       "111190  tt0805181     movie   \n",
-       "111191  tt0308220     movie   \n",
-       "111192  tt1316079     movie   \n",
-       "111193  tt3807466     movie   \n",
-       "111194  tt2082226     movie   \n",
-       "111195  tt4314934     movie   \n",
-       "111196  tt3806844     movie   \n",
-       "111197  tt6000692     movie   \n",
-       "111198  tt4315542     movie   \n",
-       "111199  tt3395746     movie   \n",
-       "111200  tt4316098     movie   \n",
-       "111201  tt1318810     movie   \n",
-       "111202  tt4317320     movie   \n",
-       "111203  tt3806902     movie   \n",
-       "111204  tt1319621     movie   \n",
-       "111205  tt1319658     movie   \n",
-       "111206  tt7182984     movie   \n",
-       "111207  tt7918964     movie   \n",
-       "\n",
-       "                                             primaryTitle  \\\n",
-       "0                                         The Dark Knight   \n",
-       "1                                               Inception   \n",
-       "2                                              Fight Club   \n",
-       "3                                              The Matrix   \n",
-       "4       The Lord of the Rings: The Fellowship of the Ring   \n",
-       "5           The Lord of the Rings: The Return of the King   \n",
-       "6                                   The Dark Knight Rises   \n",
-       "7                   The Lord of the Rings: The Two Towers   \n",
-       "8                                            Interstellar   \n",
-       "9                                        Django Unchained   \n",
-       "10                                              Gladiator   \n",
-       "11                                          Batman Begins   \n",
-       "12                                           The Avengers   \n",
-       "13                                   Inglourious Basterds   \n",
-       "14                                           The Departed   \n",
-       "15                                           The Prestige   \n",
-       "16                                The Wolf of Wall Street   \n",
-       "17                                                 Avatar   \n",
-       "18                                                Memento   \n",
-       "19                                         The Green Mile   \n",
-       "20                                         Shutter Island   \n",
-       "21                                        American Beauty   \n",
-       "22                                Guardians of the Galaxy   \n",
-       "23      Pirates of the Caribbean: The Curse of the Bla...   \n",
-       "24                                         V for Vendetta   \n",
-       "25                                      Kill Bill: Vol. 1   \n",
-       "26                                                 WALL·E   \n",
-       "27                                           Finding Nemo   \n",
-       "28                                               Iron Man   \n",
-       "29                                                     Up   \n",
-       "...                                                   ...   \n",
-       "111178                                       La otra copa   \n",
-       "111179                                             Utopia   \n",
-       "111180                        The Secret to My Silky Skin   \n",
-       "111181        Robert Hainard: L'art, la nature, la pensée   \n",
-       "111182                                       Paper Dreams   \n",
-       "111183                                 The Gadarene Swine   \n",
-       "111184                                     Beyond Measure   \n",
-       "111185                        În cãutarea tatãlui pierdut   \n",
-       "111186                                     The Lost Woman   \n",
-       "111187                                            Scratch   \n",
-       "111188               The Way - Man of the White Porcelain   \n",
-       "111189                       Santoro O Homem e Sua Música   \n",
-       "111190                   Aoi uta - Nodo jiman Seishun hen   \n",
-       "111191                     En mai, fais ce qu'il te plaît   \n",
-       "111192                                      Summer People   \n",
-       "111193                                              Davin   \n",
-       "111194                          Cartography of Loneliness   \n",
-       "111195                            Black Women in Medicine   \n",
-       "111196                                           Noon Gun   \n",
-       "111197                                      Clear Skies 2   \n",
-       "111198                                          Thunichal   \n",
-       "111199      Yatra - Uma Viagem Externa, Interna e Secreta   \n",
-       "111200                       La Pasión de Verónica Videla   \n",
-       "111201               Alicia & John, el peronismo olvidado   \n",
-       "111202                                         Underdoges   \n",
-       "111203                                    For My Daughter   \n",
-       "111204                                El fin de la espera   \n",
-       "111205                                  Return to Bolivia   \n",
-       "111206                                  Adieu à l'Afrique   \n",
-       "111207                                    Look to the Sky   \n",
-       "\n",
-       "                                            originalTitle  isAdult  startYear  \\\n",
-       "0                                         The Dark Knight        0       2008   \n",
-       "1                                               Inception        0       2010   \n",
-       "2                                              Fight Club        0       1999   \n",
-       "3                                              The Matrix        0       1999   \n",
-       "4       The Lord of the Rings: The Fellowship of the Ring        0       2001   \n",
-       "5           The Lord of the Rings: The Return of the King        0       2003   \n",
-       "6                                   The Dark Knight Rises        0       2012   \n",
-       "7                   The Lord of the Rings: The Two Towers        0       2002   \n",
-       "8                                            Interstellar        0       2014   \n",
-       "9                                        Django Unchained        0       2012   \n",
-       "10                                              Gladiator        0       2000   \n",
-       "11                                          Batman Begins        0       2005   \n",
-       "12                                           The Avengers        0       2012   \n",
-       "13                                   Inglourious Basterds        0       2009   \n",
-       "14                                           The Departed        0       2006   \n",
-       "15                                           The Prestige        0       2006   \n",
-       "16                                The Wolf of Wall Street        0       2013   \n",
-       "17                                                 Avatar        0       2009   \n",
-       "18                                                Memento        0       2000   \n",
-       "19                                         The Green Mile        0       1999   \n",
-       "20                                         Shutter Island        0       2010   \n",
-       "21                                        American Beauty        0       1999   \n",
-       "22                                Guardians of the Galaxy        0       2014   \n",
-       "23      Pirates of the Caribbean: The Curse of the Bla...        0       2003   \n",
-       "24                                         V for Vendetta        0       2005   \n",
-       "25                                      Kill Bill: Vol. 1        0       2003   \n",
-       "26                                                 WALL·E        0       2008   \n",
-       "27                                           Finding Nemo        0       2003   \n",
-       "28                                               Iron Man        0       2008   \n",
-       "29                                                     Up        0       2009   \n",
-       "...                                                   ...      ...        ...   \n",
-       "111178                                       La otra copa        0       2006   \n",
-       "111179                                            Outopia        0       2004   \n",
-       "111180                        The Secret to My Silky Skin        0       2014   \n",
-       "111181        Robert Hainard: L'art, la nature, la pensée        0       2013   \n",
-       "111182                                       Paper Dreams        0       2015   \n",
-       "111183                                 The Gadarene Swine        0       2011   \n",
-       "111184                                     Beyond Measure        0       2015   \n",
-       "111185                        În cãutarea tatãlui pierdut        0       2016   \n",
-       "111186                                     The Lost Woman        0       2009   \n",
-       "111187                                            Scratch        0       2000   \n",
-       "111188                              Michi: Hakuji no hito        0       2012   \n",
-       "111189                       Santoro O Homem e Sua Música        0       2015   \n",
-       "111190                   Aoi uta - Nodo jiman Seishun hen        0       2006   \n",
-       "111191                     En mai, fais ce qu'il te plaît        0       2002   \n",
-       "111192                                      Summer People        0       2008   \n",
-       "111193                                              Davin        0       2014   \n",
-       "111194                          Cartography of Loneliness        0       2011   \n",
-       "111195                            Black Women in Medicine        0       2016   \n",
-       "111196                                           Noon Gun        0       2015   \n",
-       "111197                                      Clear Skies 2        0       2009   \n",
-       "111198                                          Thunichal        0       2010   \n",
-       "111199      Yatra - Uma Viagem Externa, Interna e Secreta        0       2014   \n",
-       "111200                       La Pasión de Verónica Videla        0       2014   \n",
-       "111201               Alicia & John, el peronismo olvidado        0       2008   \n",
-       "111202                                         Underdoges        0       2016   \n",
-       "111203                                    For My Daughter        0       2013   \n",
-       "111204                                El fin de la espera        0       2008   \n",
-       "111205                                  Return to Bolivia        0       2008   \n",
-       "111206                                  Adieu à l'Afrique        0       2017   \n",
-       "111207                                    Look to the Sky        0       2017   \n",
+       "      tconst titleType                                       primaryTitle  \\\n",
+       "0  tt0468569     movie                                    The Dark Knight   \n",
+       "1  tt1375666     movie                                          Inception   \n",
+       "2  tt0137523     movie                                         Fight Club   \n",
+       "3  tt0133093     movie                                         The Matrix   \n",
+       "4  tt0120737     movie  The Lord of the Rings: The Fellowship of the Ring   \n",
        "\n",
-       "        runtimeMinutes                      genres  averageRating  numVotes  \n",
-       "0                  152          Action,Crime,Drama            9.0   2131901  \n",
-       "1                  148     Action,Adventure,Sci-Fi            8.8   1890955  \n",
-       "2                  139                       Drama            8.8   1723573  \n",
-       "3                  136               Action,Sci-Fi            8.7   1552565  \n",
-       "4                  178     Adventure,Drama,Fantasy            8.8   1547334  \n",
-       "5                  201     Adventure,Drama,Fantasy            8.9   1532076  \n",
-       "6                  164             Action,Thriller            8.4   1420142  \n",
-       "7                  179     Adventure,Drama,Fantasy            8.7   1385789  \n",
-       "8                  169      Adventure,Drama,Sci-Fi            8.6   1346300  \n",
-       "9                  165               Drama,Western            8.4   1248003  \n",
-       "10                 155      Action,Adventure,Drama            8.5   1245515  \n",
-       "11                 140            Action,Adventure            8.2   1223829  \n",
-       "12                 143     Action,Adventure,Sci-Fi            8.0   1206109  \n",
-       "13                 153         Adventure,Drama,War            8.3   1160855  \n",
-       "14                 151        Crime,Drama,Thriller            8.5   1102956  \n",
-       "15                 130        Drama,Mystery,Sci-Fi            8.5   1094124  \n",
-       "16                 180       Biography,Crime,Drama            8.2   1068635  \n",
-       "17                 162    Action,Adventure,Fantasy            7.8   1065648  \n",
-       "18                 113            Mystery,Thriller            8.4   1052013  \n",
-       "19                 189         Crime,Drama,Fantasy            8.6   1048833  \n",
-       "20                 138            Mystery,Thriller            8.1   1035210  \n",
-       "21                 122                       Drama            8.3   1008607  \n",
-       "22                 121     Action,Adventure,Comedy            8.0    979707  \n",
-       "23                 143    Action,Adventure,Fantasy            8.0    976840  \n",
-       "24                 132         Action,Drama,Sci-Fi            8.2    970118  \n",
-       "25                 111       Action,Crime,Thriller            8.1    931412  \n",
-       "26                  98  Adventure,Animation,Family            8.4    930323  \n",
-       "27                 100  Adventure,Animation,Comedy            8.1    888997  \n",
-       "28                 126     Action,Adventure,Sci-Fi            7.9    886426  \n",
-       "29                  96  Adventure,Animation,Comedy            8.2    868602  \n",
-       "...                ...                         ...            ...       ...  \n",
-       "111178              88                 Documentary            6.8         5  \n",
-       "111179              85             Fantasy,Mystery            3.6         5  \n",
-       "111180              81                       Drama            5.2         5  \n",
-       "111181              91                 Documentary            8.0         5  \n",
-       "111182              75                 Documentary            6.4         5  \n",
-       "111183              88                       Drama            7.4         5  \n",
-       "111184              80            Documentary,News            8.2         5  \n",
-       "111185              61                 Documentary            7.8         5  \n",
-       "111186              88      Drama,Romance,Thriller            7.6         5  \n",
-       "111187              90                      Horror            5.6         5  \n",
-       "111188             118                     History            6.8         5  \n",
-       "111189              75                 Documentary            4.6         5  \n",
-       "111190             115                       Drama            6.0         5  \n",
-       "111191              60                   Animation            5.8         5  \n",
-       "111192              67                      Horror            4.8         5  \n",
-       "111193              93                       Drama            7.2         5  \n",
-       "111194              69       Biography,Documentary            6.2         5  \n",
-       "111195              57       Biography,Documentary            8.0         5  \n",
-       "111196              70                       Drama            6.8         5  \n",
-       "111197              45     Action,Animation,Sci-Fi            8.2         5  \n",
-       "111198             115                      Action            3.2         5  \n",
-       "111199              77                 Documentary            8.8         5  \n",
-       "111200              83                       Drama            7.2         5  \n",
-       "111201              90                 Documentary            7.8         5  \n",
-       "111202              77                Comedy,Drama            4.8         5  \n",
-       "111203              96                Drama,Family            8.2         5  \n",
-       "111204              90                       Drama            5.6         5  \n",
-       "111205              90                 Documentary            6.6         5  \n",
-       "111206              87                 Documentary            6.2         5  \n",
-       "111207              72                 Documentary            9.2         5  \n",
+       "                                       originalTitle  isAdult  startYear  \\\n",
+       "0                                    The Dark Knight        0       2008   \n",
+       "1                                          Inception        0       2010   \n",
+       "2                                         Fight Club        0       1999   \n",
+       "3                                         The Matrix        0       1999   \n",
+       "4  The Lord of the Rings: The Fellowship of the Ring        0       2001   \n",
        "\n",
-       "[111208 rows x 10 columns]"
+       "   runtimeMinutes                   genres  averageRating  numVotes  \n",
+       "0             152       Action,Crime,Drama            9.0   2131901  \n",
+       "1             148  Action,Adventure,Sci-Fi            8.8   1890955  \n",
+       "2             139                    Drama            8.8   1723573  \n",
+       "3             136            Action,Sci-Fi            8.7   1552565  \n",
+       "4             178  Adventure,Drama,Fantasy            8.8   1547334  "
       ]
      },
-     "execution_count": 8,
+     "execution_count": 21,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2179,7 +1217,7 @@
    "source": [
     "# Sort by number of votes for most \"accurate\" ratings\n",
     "df_sorted_by_votes=df_full.sort_values(\"numVotes\",ascending=False).reset_index().drop(columns=\"index\")\n",
-    "df_sorted_by_votes"
+    "df_sorted_by_votes.head()"
    ]
   },
   {
diff --git a/Greg_notebook.ipynb b/Greg_notebook.ipynb
new file mode 100644
index 0000000..95e6df6
--- /dev/null
+++ b/Greg_notebook.ipynb
@@ -0,0 +1,724 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 136,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import math\n",
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "import seaborn as sns\n",
+    "from CleaningFunctions import Clean\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 137,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "The autoreload extension is already loaded. To reload it, use:\n",
+      "  %reload_ext autoreload\n"
+     ]
+    }
+   ],
+   "source": [
+    "%load_ext autoreload\n",
+    "%autoreload 2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 138,
+   "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>tconst</th>\n",
+       "      <th>titleType</th>\n",
+       "      <th>primaryTitle</th>\n",
+       "      <th>originalTitle</th>\n",
+       "      <th>isAdult</th>\n",
+       "      <th>startYear</th>\n",
+       "      <th>endYear</th>\n",
+       "      <th>runtimeMinutes</th>\n",
+       "      <th>genres</th>\n",
+       "      <th>title</th>\n",
+       "      <th>check</th>\n",
+       "      <th>averageRating</th>\n",
+       "      <th>numVotes</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>tt0069049</td>\n",
+       "      <td>movie</td>\n",
+       "      <td>The Other Side of the Wind</td>\n",
+       "      <td>The Other Side of the Wind</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2018</td>\n",
+       "      <td>\\N</td>\n",
+       "      <td>122</td>\n",
+       "      <td>Drama</td>\n",
+       "      <td>The Other Side of the Wind</td>\n",
+       "      <td>1</td>\n",
+       "      <td>6.9</td>\n",
+       "      <td>4989</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>tt0339736</td>\n",
+       "      <td>movie</td>\n",
+       "      <td>The Evil Within</td>\n",
+       "      <td>The Evil Within</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>\\N</td>\n",
+       "      <td>98</td>\n",
+       "      <td>Horror</td>\n",
+       "      <td>The Evil Within</td>\n",
+       "      <td>1</td>\n",
+       "      <td>5.5</td>\n",
+       "      <td>2572</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>tt0360556</td>\n",
+       "      <td>movie</td>\n",
+       "      <td>Fahrenheit 451</td>\n",
+       "      <td>Fahrenheit 451</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2018</td>\n",
+       "      <td>\\N</td>\n",
+       "      <td>100</td>\n",
+       "      <td>Drama,Sci-Fi,Thriller</td>\n",
+       "      <td>Fahrenheit 451</td>\n",
+       "      <td>1</td>\n",
+       "      <td>4.9</td>\n",
+       "      <td>15295</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>tt0365545</td>\n",
+       "      <td>movie</td>\n",
+       "      <td>Nappily Ever After</td>\n",
+       "      <td>Nappily Ever After</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2018</td>\n",
+       "      <td>\\N</td>\n",
+       "      <td>98</td>\n",
+       "      <td>Comedy,Drama,Romance</td>\n",
+       "      <td>Nappily Ever After</td>\n",
+       "      <td>1</td>\n",
+       "      <td>6.4</td>\n",
+       "      <td>6718</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>tt0369610</td>\n",
+       "      <td>movie</td>\n",
+       "      <td>Jurassic World</td>\n",
+       "      <td>Jurassic World</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2015</td>\n",
+       "      <td>\\N</td>\n",
+       "      <td>124</td>\n",
+       "      <td>Action,Adventure,Sci-Fi</td>\n",
+       "      <td>Jurassic World</td>\n",
+       "      <td>1</td>\n",
+       "      <td>7.0</td>\n",
+       "      <td>549806</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      tconst titleType                primaryTitle  \\\n",
+       "0  tt0069049     movie  The Other Side of the Wind   \n",
+       "1  tt0339736     movie             The Evil Within   \n",
+       "2  tt0360556     movie              Fahrenheit 451   \n",
+       "3  tt0365545     movie          Nappily Ever After   \n",
+       "4  tt0369610     movie              Jurassic World   \n",
+       "\n",
+       "                originalTitle  isAdult  startYear endYear  runtimeMinutes  \\\n",
+       "0  The Other Side of the Wind        0       2018      \\N             122   \n",
+       "1             The Evil Within        0       2017      \\N              98   \n",
+       "2              Fahrenheit 451        0       2018      \\N             100   \n",
+       "3          Nappily Ever After        0       2018      \\N              98   \n",
+       "4              Jurassic World        0       2015      \\N             124   \n",
+       "\n",
+       "                    genres                       title  check  averageRating  \\\n",
+       "0                    Drama  The Other Side of the Wind      1            6.9   \n",
+       "1                   Horror             The Evil Within      1            5.5   \n",
+       "2    Drama,Sci-Fi,Thriller              Fahrenheit 451      1            4.9   \n",
+       "3     Comedy,Drama,Romance          Nappily Ever After      1            6.4   \n",
+       "4  Action,Adventure,Sci-Fi              Jurassic World      1            7.0   \n",
+       "\n",
+       "   numVotes  \n",
+       "0      4989  \n",
+       "1      2572  \n",
+       "2     15295  \n",
+       "3      6718  \n",
+       "4    549806  "
+      ]
+     },
+     "execution_count": 138,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Read in data as pandas dataframe\n",
+    "\n",
+    "df=pd.read_csv(\"2016_2019_USmovies.csv\")\n",
+    "df.head()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 139,
+   "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>Title_ID</th>\n",
+       "      <th>titleType</th>\n",
+       "      <th>primaryTitle</th>\n",
+       "      <th>originalTitle</th>\n",
+       "      <th>Adult</th>\n",
+       "      <th>Release_Year</th>\n",
+       "      <th>endYear</th>\n",
+       "      <th>Runtime(Minutes)</th>\n",
+       "      <th>Genre</th>\n",
+       "      <th>Title</th>\n",
+       "      <th>Check</th>\n",
+       "      <th>Rating</th>\n",
+       "      <th>Number_of_Votes</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>tt0069049</td>\n",
+       "      <td>movie</td>\n",
+       "      <td>The Other Side of the Wind</td>\n",
+       "      <td>The Other Side of the Wind</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2018</td>\n",
+       "      <td>\\N</td>\n",
+       "      <td>122</td>\n",
+       "      <td>Drama</td>\n",
+       "      <td>The Other Side of the Wind</td>\n",
+       "      <td>1</td>\n",
+       "      <td>6.9</td>\n",
+       "      <td>4989</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>tt0339736</td>\n",
+       "      <td>movie</td>\n",
+       "      <td>The Evil Within</td>\n",
+       "      <td>The Evil Within</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>\\N</td>\n",
+       "      <td>98</td>\n",
+       "      <td>Horror</td>\n",
+       "      <td>The Evil Within</td>\n",
+       "      <td>1</td>\n",
+       "      <td>5.5</td>\n",
+       "      <td>2572</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>tt0360556</td>\n",
+       "      <td>movie</td>\n",
+       "      <td>Fahrenheit 451</td>\n",
+       "      <td>Fahrenheit 451</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2018</td>\n",
+       "      <td>\\N</td>\n",
+       "      <td>100</td>\n",
+       "      <td>Drama,Sci-Fi,Thriller</td>\n",
+       "      <td>Fahrenheit 451</td>\n",
+       "      <td>1</td>\n",
+       "      <td>4.9</td>\n",
+       "      <td>15295</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>tt0365545</td>\n",
+       "      <td>movie</td>\n",
+       "      <td>Nappily Ever After</td>\n",
+       "      <td>Nappily Ever After</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2018</td>\n",
+       "      <td>\\N</td>\n",
+       "      <td>98</td>\n",
+       "      <td>Comedy,Drama,Romance</td>\n",
+       "      <td>Nappily Ever After</td>\n",
+       "      <td>1</td>\n",
+       "      <td>6.4</td>\n",
+       "      <td>6718</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>tt0369610</td>\n",
+       "      <td>movie</td>\n",
+       "      <td>Jurassic World</td>\n",
+       "      <td>Jurassic World</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2015</td>\n",
+       "      <td>\\N</td>\n",
+       "      <td>124</td>\n",
+       "      <td>Action,Adventure,Sci-Fi</td>\n",
+       "      <td>Jurassic World</td>\n",
+       "      <td>1</td>\n",
+       "      <td>7.0</td>\n",
+       "      <td>549806</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    Title_ID titleType                primaryTitle  \\\n",
+       "0  tt0069049     movie  The Other Side of the Wind   \n",
+       "1  tt0339736     movie             The Evil Within   \n",
+       "2  tt0360556     movie              Fahrenheit 451   \n",
+       "3  tt0365545     movie          Nappily Ever After   \n",
+       "4  tt0369610     movie              Jurassic World   \n",
+       "\n",
+       "                originalTitle  Adult  Release_Year endYear  Runtime(Minutes)  \\\n",
+       "0  The Other Side of the Wind      0          2018      \\N               122   \n",
+       "1             The Evil Within      0          2017      \\N                98   \n",
+       "2              Fahrenheit 451      0          2018      \\N               100   \n",
+       "3          Nappily Ever After      0          2018      \\N                98   \n",
+       "4              Jurassic World      0          2015      \\N               124   \n",
+       "\n",
+       "                     Genre                       Title  Check  Rating  \\\n",
+       "0                    Drama  The Other Side of the Wind      1     6.9   \n",
+       "1                   Horror             The Evil Within      1     5.5   \n",
+       "2    Drama,Sci-Fi,Thriller              Fahrenheit 451      1     4.9   \n",
+       "3     Comedy,Drama,Romance          Nappily Ever After      1     6.4   \n",
+       "4  Action,Adventure,Sci-Fi              Jurassic World      1     7.0   \n",
+       "\n",
+       "   Number_of_Votes  \n",
+       "0             4989  \n",
+       "1             2572  \n",
+       "2            15295  \n",
+       "3             6718  \n",
+       "4           549806  "
+      ]
+     },
+     "execution_count": 139,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Let's clean the data and rename columns so we know what we're looking at\n",
+    "\n",
+    "columns=[\"tconst\",\"title\",\"isAdult\",\"startYear\",\"runtimeMinutes\",\"check\",\"averageRating\",\"genres\",\"numVotes\"]\n",
+    "names=[\"Title_ID\",\"Title\",\"Adult\",\"Release_Year\",\"Runtime(Minutes)\",\"Check\",\"Rating\",\"Genre\",\"Number_of_Votes\"]\n",
+    "\n",
+    "for column,name in list(zip(columns,names)):\n",
+    "    df.rename(columns={column:name},inplace=True)\n",
+    "    \n",
+    "df.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 140,
+   "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>Title_ID</th>\n",
+       "      <th>Release_Year</th>\n",
+       "      <th>Runtime(Minutes)</th>\n",
+       "      <th>Genre</th>\n",
+       "      <th>Title</th>\n",
+       "      <th>Rating</th>\n",
+       "      <th>Number_of_Votes</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>tt0069049</td>\n",
+       "      <td>2018</td>\n",
+       "      <td>122</td>\n",
+       "      <td>Drama</td>\n",
+       "      <td>The Other Side of the Wind</td>\n",
+       "      <td>6.9</td>\n",
+       "      <td>4989</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>tt0339736</td>\n",
+       "      <td>2017</td>\n",
+       "      <td>98</td>\n",
+       "      <td>Horror</td>\n",
+       "      <td>The Evil Within</td>\n",
+       "      <td>5.5</td>\n",
+       "      <td>2572</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>tt0360556</td>\n",
+       "      <td>2018</td>\n",
+       "      <td>100</td>\n",
+       "      <td>Drama,Sci-Fi,Thriller</td>\n",
+       "      <td>Fahrenheit 451</td>\n",
+       "      <td>4.9</td>\n",
+       "      <td>15295</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>tt0365545</td>\n",
+       "      <td>2018</td>\n",
+       "      <td>98</td>\n",
+       "      <td>Comedy,Drama,Romance</td>\n",
+       "      <td>Nappily Ever After</td>\n",
+       "      <td>6.4</td>\n",
+       "      <td>6718</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>tt0369610</td>\n",
+       "      <td>2015</td>\n",
+       "      <td>124</td>\n",
+       "      <td>Action,Adventure,Sci-Fi</td>\n",
+       "      <td>Jurassic World</td>\n",
+       "      <td>7.0</td>\n",
+       "      <td>549806</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    Title_ID  Release_Year  Runtime(Minutes)                    Genre  \\\n",
+       "0  tt0069049          2018               122                    Drama   \n",
+       "1  tt0339736          2017                98                   Horror   \n",
+       "2  tt0360556          2018               100    Drama,Sci-Fi,Thriller   \n",
+       "3  tt0365545          2018                98     Comedy,Drama,Romance   \n",
+       "4  tt0369610          2015               124  Action,Adventure,Sci-Fi   \n",
+       "\n",
+       "                        Title  Rating  Number_of_Votes  \n",
+       "0  The Other Side of the Wind     6.9             4989  \n",
+       "1             The Evil Within     5.5             2572  \n",
+       "2              Fahrenheit 451     4.9            15295  \n",
+       "3          Nappily Ever After     6.4             6718  \n",
+       "4              Jurassic World     7.0           549806  "
+      ]
+     },
+     "execution_count": 140,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Now to drop columns we aren't interested in or that hold irrelevant data\n",
+    "\n",
+    "df.drop(columns=[\"titleType\",\"primaryTitle\",\"originalTitle\",\"endYear\",\"Adult\",\"Check\"],inplace=True)\n",
+    "\n",
+    "df.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create binaries for the genres we're interested in for analysis later on"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 141,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "       Release_Year  Runtime(Minutes)       Rating  Number_of_Votes\n",
+      "count   2015.000000       2015.000000  2015.000000      2015.000000\n",
+      "mean    2016.715633        101.181141     5.920447     42005.702233\n",
+      "std        1.355422         15.783114     1.051272     91376.330598\n",
+      "min     2014.000000         46.000000     1.400000       984.000000\n",
+      "25%     2016.000000         90.000000     5.300000      2377.500000\n",
+      "50%     2017.000000         98.000000     6.000000      7601.000000\n",
+      "75%     2018.000000        109.000000     6.600000     36685.500000\n",
+      "max     2019.000000        209.000000    10.000000    844981.000000\n",
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "RangeIndex: 2015 entries, 0 to 2014\n",
+      "Data columns (total 7 columns):\n",
+      "Title_ID            2015 non-null object\n",
+      "Release_Year        2015 non-null int64\n",
+      "Runtime(Minutes)    2015 non-null int64\n",
+      "Genre               2015 non-null object\n",
+      "Title               2015 non-null object\n",
+      "Rating              2015 non-null float64\n",
+      "Number_of_Votes     2015 non-null int64\n",
+      "dtypes: float64(1), int64(3), object(3)\n",
+      "memory usage: 110.3+ KB\n",
+      "None\n",
+      "(2015, 7)\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Now to check our data makes sense and we have no nulls\n",
+    "print(df.describe())\n",
+    "print(df.info())\n",
+    "print(df.shape)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 142,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "df_comedy contains (101, 7) entries\n",
+      "df_drama contains (112, 7) entries\n",
+      "df_horror contains (64, 7) entries\n",
+      "df_scifi contains (4, 7) entries\n",
+      "df_action contains (7, 7) entries\n",
+      "df_romance contains (3, 7) entries\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Now split into separate databases based on genre\n",
+    "\n",
+    "df_comedy=df.loc[df[\"Genre\"]==\"Comedy\",:]\n",
+    "df_drama=df.loc[df[\"Genre\"]==\"Drama\",:]\n",
+    "df_horror=df.loc[df[\"Genre\"]==\"Horror\",:]\n",
+    "df_scifi=df.loc[df[\"Genre\"]==\"Sci-Fi\",:]\n",
+    "df_action=df.loc[df[\"Genre\"]==\"Action\",:]\n",
+    "df_romance=df.loc[df[\"Genre\"]==\"Romance\",:]\n",
+    "\n",
+    "\n",
+    "# Print shape of dataframe so we know the sample sizes\n",
+    "\n",
+    "print(\"df_comedy contains\",df_comedy.shape,\"entries\")\n",
+    "print(\"df_drama contains\",df_drama.shape,\"entries\")\n",
+    "print(\"df_horror contains\",df_horror.shape,\"entries\")\n",
+    "print(\"df_scifi contains\",df_scifi.shape,\"entries\")\n",
+    "print(\"df_action contains\",df_action.shape,\"entries\")\n",
+    "print(\"df_romance contains\",df_romance.shape,\"entries\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 144,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/flatironschool/anaconda3/envs/learn-env/lib/python3.6/site-packages/scipy/stats/stats.py:1713: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.\n",
+      "  return np.add.reduce(sorted[indexer] * weights, axis=axis) / sumval\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x1a1c188668>"
+      ]
+     },
+     "execution_count": 144,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sns.distplot(df.Rating)\n",
+    "sns.distplot(df_drama.Rating)\n",
+    "# sns.distplot(df_horror.Rating)\n",
+    "# sns.distplot(df_scifi.Rating)\n",
+    "# sns.distplot(df_action.Rating)\n",
+    "# sns.distplot(df_romance.Rating)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 150,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/flatironschool/anaconda3/envs/learn-env/lib/python3.6/site-packages/scipy/stats/stats.py:1713: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.\n",
+      "  return np.add.reduce(sorted[indexer] * weights, axis=axis) / sumval\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x1a1c43ce48>"
+      ]
+     },
+     "execution_count": 150,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sns.distplot(df.Rating)\n",
+    "sns.distplot(df_comedy.Rating)\n",
+    "sns.distplot(df_drama.Rating)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 154,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "For the population the standard deviation is: 1.051271891981967  with a median value of: 6.0  and a mean value of: 5.92044665012407\n",
+      "For Comedy the standard deviation is: 0.9587884268829868  with a median value of: 5.6  and a mean value of: 5.595049504950495\n",
+      "For Drama the standard deviation is: 0.9169218376561092  with a median value of: 6.4  and a mean value of: 6.291964285714286\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(\"For the population the standard deviation is:\",df.Rating.std(),\" with a median value of:\",df.Rating.median(),\" and a mean value of:\",df.Rating.mean())\n",
+    "\n",
+    "print(\"For Comedy the standard deviation is:\",df_comedy.Rating.std(),\" with a median value of:\",df_comedy.Rating.median(),\" and a mean value of:\",df_comedy.Rating.mean())\n",
+    "\n",
+    "print(\"For Drama the standard deviation is:\",df_drama.Rating.std(),\" with a median value of:\",df_drama.Rating.median(),\" and a mean value of:\",df_drama.Rating.mean())\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python [conda env:learn-env] *",
+   "language": "python",
+   "name": "conda-env-learn-env-py"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/libraries/CleaningFunctions.py b/libraries/CleaningFunctions.py
deleted file mode 100644
index 4cd7e3d..0000000
--- a/libraries/CleaningFunctions.py
+++ /dev/null
@@ -1,22 +0,0 @@
-"""
-Each support function should have an informative name and return the partially cleaned bit of the dataset.
-"""
-import pandas as pd
-
-
-def search(dataframe, column_to_search, condition, columns):
-    
-    dataframe=df
-    
-    new_df=df.loc[df[columns_to_search]condition,columns]
-    
-    return new_df
-
-def drop_null_rows(dataframe,columns,condition):
-    
-def drop_nulls(dataframe,column_to_search):
-    # The null values in our dataframe are listed as "\N"
-    df=dataframe
-    df.loc[df[column_to_search]==r"\N"]
-    
-