diff --git a/your-code/main.ipynb b/your-code/main.ipynb
index a5caf8b..9a5ba57 100755
--- a/your-code/main.ipynb
+++ b/your-code/main.ipynb
@@ -12,16 +12,67 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 34,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Import your libraries:\n",
+    "# 📚 Basic Libraries\n",
+    "import numpy as np # operaciones matemáticas (numerical python)\n",
+    "import pandas as pd # manipulación de datos\n",
+    "import warnings # nobody likes warnings\n",
+    "\n",
+    "# 📊 Visualizations\n",
+    "import matplotlib.pyplot as plt\n",
+    "import seaborn as sns\n",
     "\n",
-    "%matplotlib inline\n",
+    "# 🤖 Machine Learning\n",
+    "from sklearn.model_selection import train_test_split\n",
+    "from sklearn.linear_model import LogisticRegression \n",
+    "from sklearn.metrics import roc_curve, confusion_matrix, ConfusionMatrixDisplay\n",
+    "from sklearn.metrics import classification_report"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# ⚙️ Settings\n",
+    "pd.set_option('display.max_columns', None) # display all columns\n",
+    "warnings.filterwarnings('ignore') # ignore warnings"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# 🔧 Basic functions\n",
+    "def snake_columns(data): \n",
+    "    \"\"\"\n",
+    "    returns the columns in snake case\n",
+    "    \"\"\"\n",
+    "    data.columns = [column.lower().replace(' ', '_') for column in data.columns]\n",
+    "    \n",
+    "def open_data(data): # returns shape, data types & shows a small sample\n",
+    "    print(f\"Data shape is {data.shape}.\")\n",
+    "    print()\n",
+    "    print(data.dtypes)\n",
+    "    print()\n",
+    "    print(\"Data row sample and full columns:\")\n",
+    "    return data.sample(5)\n",
     "\n",
-    "import numpy as np\n",
-    "import pandas as pd"
+    "# 🎯 Specific functions\n",
+    "def explore_data(data): # sum & returns duplicates, NaN & empty spaces\n",
+    "    duplicate_rows = data.duplicated().sum()\n",
+    "    nan_values = data.isna().sum()\n",
+    "    empty_spaces = data.eq(' ').sum()\n",
+    "    import pandas as pd\n",
+    "    exploration = pd.DataFrame({\"NaN\": nan_values, \"EmptySpaces\": empty_spaces}) # New dataframe with the results\n",
+    "    print(f\"There are {data.duplicated().sum()} duplicate rows. Also;\")\n",
+    "    return exploration"
    ]
   },
   {
@@ -37,7 +88,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -65,20 +116,1281 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 40,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Data shape is (1781, 21).\n",
+      "\n",
+      "URL                           object\n",
+      "URL_LENGTH                     int64\n",
+      "NUMBER_SPECIAL_CHARACTERS      int64\n",
+      "CHARSET                       object\n",
+      "SERVER                        object\n",
+      "CONTENT_LENGTH               float64\n",
+      "WHOIS_COUNTRY                 object\n",
+      "WHOIS_STATEPRO                object\n",
+      "WHOIS_REGDATE                 object\n",
+      "WHOIS_UPDATED_DATE            object\n",
+      "TCP_CONVERSATION_EXCHANGE      int64\n",
+      "DIST_REMOTE_TCP_PORT           int64\n",
+      "REMOTE_IPS                     int64\n",
+      "APP_BYTES                      int64\n",
+      "SOURCE_APP_PACKETS             int64\n",
+      "REMOTE_APP_PACKETS             int64\n",
+      "SOURCE_APP_BYTES               int64\n",
+      "REMOTE_APP_BYTES               int64\n",
+      "APP_PACKETS                    int64\n",
+      "DNS_QUERY_TIMES              float64\n",
+      "Type                           int64\n",
+      "dtype: object\n",
+      "\n",
+      "Data row sample and full columns:\n"
+     ]
+    },
+    {
+     "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>URL</th>\n",
+       "      <th>URL_LENGTH</th>\n",
+       "      <th>NUMBER_SPECIAL_CHARACTERS</th>\n",
+       "      <th>CHARSET</th>\n",
+       "      <th>SERVER</th>\n",
+       "      <th>CONTENT_LENGTH</th>\n",
+       "      <th>WHOIS_COUNTRY</th>\n",
+       "      <th>WHOIS_STATEPRO</th>\n",
+       "      <th>WHOIS_REGDATE</th>\n",
+       "      <th>WHOIS_UPDATED_DATE</th>\n",
+       "      <th>TCP_CONVERSATION_EXCHANGE</th>\n",
+       "      <th>DIST_REMOTE_TCP_PORT</th>\n",
+       "      <th>REMOTE_IPS</th>\n",
+       "      <th>APP_BYTES</th>\n",
+       "      <th>SOURCE_APP_PACKETS</th>\n",
+       "      <th>REMOTE_APP_PACKETS</th>\n",
+       "      <th>SOURCE_APP_BYTES</th>\n",
+       "      <th>REMOTE_APP_BYTES</th>\n",
+       "      <th>APP_PACKETS</th>\n",
+       "      <th>DNS_QUERY_TIMES</th>\n",
+       "      <th>Type</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1338</th>\n",
+       "      <td>B0_79</td>\n",
+       "      <td>68</td>\n",
+       "      <td>11</td>\n",
+       "      <td>UTF-8</td>\n",
+       "      <td>nginx</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>US</td>\n",
+       "      <td>Arizona</td>\n",
+       "      <td>26/01/2006 21:09</td>\n",
+       "      <td>11/04/2017 23:16</td>\n",
+       "      <td>48</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>4896</td>\n",
+       "      <td>52</td>\n",
+       "      <td>58</td>\n",
+       "      <td>73318</td>\n",
+       "      <td>5200</td>\n",
+       "      <td>52</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>868</th>\n",
+       "      <td>B0_2009</td>\n",
+       "      <td>49</td>\n",
+       "      <td>11</td>\n",
+       "      <td>UTF-8</td>\n",
+       "      <td>Apache</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>25</td>\n",
+       "      <td>6</td>\n",
+       "      <td>11</td>\n",
+       "      <td>1662</td>\n",
+       "      <td>25</td>\n",
+       "      <td>12</td>\n",
+       "      <td>799</td>\n",
+       "      <td>1662</td>\n",
+       "      <td>25</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>139</th>\n",
+       "      <td>B0_2266</td>\n",
+       "      <td>29</td>\n",
+       "      <td>8</td>\n",
+       "      <td>UTF-8</td>\n",
+       "      <td>Apache/2.4.25</td>\n",
+       "      <td>6813.0</td>\n",
+       "      <td>US</td>\n",
+       "      <td>Texas</td>\n",
+       "      <td>23/05/2006 0:00</td>\n",
+       "      <td>13/07/2016 0:00</td>\n",
+       "      <td>17</td>\n",
+       "      <td>9</td>\n",
+       "      <td>10</td>\n",
+       "      <td>1249</td>\n",
+       "      <td>17</td>\n",
+       "      <td>15</td>\n",
+       "      <td>1062</td>\n",
+       "      <td>1249</td>\n",
+       "      <td>17</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>303</th>\n",
+       "      <td>B0_717</td>\n",
+       "      <td>35</td>\n",
+       "      <td>7</td>\n",
+       "      <td>UTF-8</td>\n",
+       "      <td>GSE</td>\n",
+       "      <td>8813.0</td>\n",
+       "      <td>US</td>\n",
+       "      <td>CA</td>\n",
+       "      <td>31/07/2000 0:00</td>\n",
+       "      <td>29/06/2016 0:00</td>\n",
+       "      <td>41</td>\n",
+       "      <td>6</td>\n",
+       "      <td>4</td>\n",
+       "      <td>4769</td>\n",
+       "      <td>45</td>\n",
+       "      <td>42</td>\n",
+       "      <td>69898</td>\n",
+       "      <td>5119</td>\n",
+       "      <td>45</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>500</th>\n",
+       "      <td>B0_915</td>\n",
+       "      <td>39</td>\n",
+       "      <td>9</td>\n",
+       "      <td>ISO-8859-1</td>\n",
+       "      <td>nginx/1.12.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>CA</td>\n",
+       "      <td>SK</td>\n",
+       "      <td>19/10/2005 0:00</td>\n",
+       "      <td>18/10/2016 0:00</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "          URL  URL_LENGTH  NUMBER_SPECIAL_CHARACTERS     CHARSET  \\\n",
+       "1338    B0_79          68                         11       UTF-8   \n",
+       "868   B0_2009          49                         11       UTF-8   \n",
+       "139   B0_2266          29                          8       UTF-8   \n",
+       "303    B0_717          35                          7       UTF-8   \n",
+       "500    B0_915          39                          9  ISO-8859-1   \n",
+       "\n",
+       "             SERVER  CONTENT_LENGTH WHOIS_COUNTRY WHOIS_STATEPRO  \\\n",
+       "1338          nginx             NaN            US        Arizona   \n",
+       "868          Apache             NaN           NaN            NaN   \n",
+       "139   Apache/2.4.25          6813.0            US          Texas   \n",
+       "303             GSE          8813.0            US             CA   \n",
+       "500    nginx/1.12.0             NaN            CA             SK   \n",
+       "\n",
+       "         WHOIS_REGDATE WHOIS_UPDATED_DATE  TCP_CONVERSATION_EXCHANGE  \\\n",
+       "1338  26/01/2006 21:09   11/04/2017 23:16                         48   \n",
+       "868                NaN                NaN                         25   \n",
+       "139    23/05/2006 0:00    13/07/2016 0:00                         17   \n",
+       "303    31/07/2000 0:00    29/06/2016 0:00                         41   \n",
+       "500    19/10/2005 0:00    18/10/2016 0:00                          0   \n",
+       "\n",
+       "      DIST_REMOTE_TCP_PORT  REMOTE_IPS  APP_BYTES  SOURCE_APP_PACKETS  \\\n",
+       "1338                     0           3       4896                  52   \n",
+       "868                      6          11       1662                  25   \n",
+       "139                      9          10       1249                  17   \n",
+       "303                      6           4       4769                  45   \n",
+       "500                      0           0          0                   0   \n",
+       "\n",
+       "      REMOTE_APP_PACKETS  SOURCE_APP_BYTES  REMOTE_APP_BYTES  APP_PACKETS  \\\n",
+       "1338                  58             73318              5200           52   \n",
+       "868                   12               799              1662           25   \n",
+       "139                   15              1062              1249           17   \n",
+       "303                   42             69898              5119           45   \n",
+       "500                    0                 0                 0            0   \n",
+       "\n",
+       "      DNS_QUERY_TIMES  Type  \n",
+       "1338              4.0     0  \n",
+       "868               0.0     0  \n",
+       "139               0.0     0  \n",
+       "303               4.0     0  \n",
+       "500               0.0     0  "
+      ]
+     },
+     "execution_count": 40,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "open_data(websites)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Se trata de un dataframe con 1781 filas y 21 columnas"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Hay dos tipos de datos: numéricos (enteros y decimales) y objetos (texto).\n",
+    "# En cuanto a la target, como primera aproximación sugerimos que la columna donde se ve si la url es maligna o no es la de 'Type'.\n",
+    "# En cuanto a las columnas que son object"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Hacemos una copia y empezamos a explorar el dataframe\n",
+    "df = websites.copy()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "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>url</th>\n",
+       "      <th>url_length</th>\n",
+       "      <th>number_special_characters</th>\n",
+       "      <th>charset</th>\n",
+       "      <th>server</th>\n",
+       "      <th>content_length</th>\n",
+       "      <th>whois_country</th>\n",
+       "      <th>whois_statepro</th>\n",
+       "      <th>whois_regdate</th>\n",
+       "      <th>whois_updated_date</th>\n",
+       "      <th>tcp_conversation_exchange</th>\n",
+       "      <th>dist_remote_tcp_port</th>\n",
+       "      <th>remote_ips</th>\n",
+       "      <th>app_bytes</th>\n",
+       "      <th>source_app_packets</th>\n",
+       "      <th>remote_app_packets</th>\n",
+       "      <th>source_app_bytes</th>\n",
+       "      <th>remote_app_bytes</th>\n",
+       "      <th>app_packets</th>\n",
+       "      <th>dns_query_times</th>\n",
+       "      <th>type</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>M0_109</td>\n",
+       "      <td>16</td>\n",
+       "      <td>7</td>\n",
+       "      <td>iso-8859-1</td>\n",
+       "      <td>nginx</td>\n",
+       "      <td>263.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10/10/2015 18:21</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>7</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>700</td>\n",
+       "      <td>9</td>\n",
+       "      <td>10</td>\n",
+       "      <td>1153</td>\n",
+       "      <td>832</td>\n",
+       "      <td>9</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>B0_2314</td>\n",
+       "      <td>16</td>\n",
+       "      <td>6</td>\n",
+       "      <td>UTF-8</td>\n",
+       "      <td>Apache/2.4.10</td>\n",
+       "      <td>15087.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>17</td>\n",
+       "      <td>7</td>\n",
+       "      <td>4</td>\n",
+       "      <td>1230</td>\n",
+       "      <td>17</td>\n",
+       "      <td>19</td>\n",
+       "      <td>1265</td>\n",
+       "      <td>1230</td>\n",
+       "      <td>17</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>B0_911</td>\n",
+       "      <td>16</td>\n",
+       "      <td>6</td>\n",
+       "      <td>us-ascii</td>\n",
+       "      <td>Microsoft-HTTPAPI/2.0</td>\n",
+       "      <td>324.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>B0_113</td>\n",
+       "      <td>17</td>\n",
+       "      <td>6</td>\n",
+       "      <td>ISO-8859-1</td>\n",
+       "      <td>nginx</td>\n",
+       "      <td>162.0</td>\n",
+       "      <td>US</td>\n",
+       "      <td>AK</td>\n",
+       "      <td>7/10/1997 4:00</td>\n",
+       "      <td>12/09/2013 0:45</td>\n",
+       "      <td>31</td>\n",
+       "      <td>22</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3812</td>\n",
+       "      <td>39</td>\n",
+       "      <td>37</td>\n",
+       "      <td>18784</td>\n",
+       "      <td>4380</td>\n",
+       "      <td>39</td>\n",
+       "      <td>8.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>B0_403</td>\n",
+       "      <td>17</td>\n",
+       "      <td>6</td>\n",
+       "      <td>UTF-8</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>124140.0</td>\n",
+       "      <td>US</td>\n",
+       "      <td>TX</td>\n",
+       "      <td>12/05/1996 0:00</td>\n",
+       "      <td>11/04/2017 0:00</td>\n",
+       "      <td>57</td>\n",
+       "      <td>2</td>\n",
+       "      <td>5</td>\n",
+       "      <td>4278</td>\n",
+       "      <td>61</td>\n",
+       "      <td>62</td>\n",
+       "      <td>129889</td>\n",
+       "      <td>4586</td>\n",
+       "      <td>61</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>0</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>1776</th>\n",
+       "      <td>M4_48</td>\n",
+       "      <td>194</td>\n",
+       "      <td>16</td>\n",
+       "      <td>UTF-8</td>\n",
+       "      <td>Apache</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>ES</td>\n",
+       "      <td>Barcelona</td>\n",
+       "      <td>17/09/2008 0:00</td>\n",
+       "      <td>2/09/2016 0:00</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>186</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1777</th>\n",
+       "      <td>M4_41</td>\n",
+       "      <td>198</td>\n",
+       "      <td>17</td>\n",
+       "      <td>UTF-8</td>\n",
+       "      <td>Apache</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>ES</td>\n",
+       "      <td>Barcelona</td>\n",
+       "      <td>17/09/2008 0:00</td>\n",
+       "      <td>2/09/2016 0:00</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>124</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1778</th>\n",
+       "      <td>B0_162</td>\n",
+       "      <td>201</td>\n",
+       "      <td>34</td>\n",
+       "      <td>utf-8</td>\n",
+       "      <td>Apache/2.2.16 (Debian)</td>\n",
+       "      <td>8904.0</td>\n",
+       "      <td>US</td>\n",
+       "      <td>FL</td>\n",
+       "      <td>15/02/1999 0:00</td>\n",
+       "      <td>15/07/2015 0:00</td>\n",
+       "      <td>83</td>\n",
+       "      <td>2</td>\n",
+       "      <td>6</td>\n",
+       "      <td>6631</td>\n",
+       "      <td>87</td>\n",
+       "      <td>89</td>\n",
+       "      <td>132181</td>\n",
+       "      <td>6945</td>\n",
+       "      <td>87</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1779</th>\n",
+       "      <td>B0_1152</td>\n",
+       "      <td>234</td>\n",
+       "      <td>34</td>\n",
+       "      <td>ISO-8859-1</td>\n",
+       "      <td>cloudflare-nginx</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>US</td>\n",
+       "      <td>CA</td>\n",
+       "      <td>1/04/1998 0:00</td>\n",
+       "      <td>9/12/2016 0:00</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1780</th>\n",
+       "      <td>B0_676</td>\n",
+       "      <td>249</td>\n",
+       "      <td>40</td>\n",
+       "      <td>utf-8</td>\n",
+       "      <td>Microsoft-IIS/8.5</td>\n",
+       "      <td>24435.0</td>\n",
+       "      <td>US</td>\n",
+       "      <td>Wisconsin</td>\n",
+       "      <td>14/11/2008 0:00</td>\n",
+       "      <td>20/11/2013 0:00</td>\n",
+       "      <td>19</td>\n",
+       "      <td>6</td>\n",
+       "      <td>11</td>\n",
+       "      <td>2314</td>\n",
+       "      <td>25</td>\n",
+       "      <td>28</td>\n",
+       "      <td>3039</td>\n",
+       "      <td>2776</td>\n",
+       "      <td>25</td>\n",
+       "      <td>6.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>1781 rows × 21 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "          url  url_length  number_special_characters     charset  \\\n",
+       "0      M0_109          16                          7  iso-8859-1   \n",
+       "1     B0_2314          16                          6       UTF-8   \n",
+       "2      B0_911          16                          6    us-ascii   \n",
+       "3      B0_113          17                          6  ISO-8859-1   \n",
+       "4      B0_403          17                          6       UTF-8   \n",
+       "...       ...         ...                        ...         ...   \n",
+       "1776    M4_48         194                         16       UTF-8   \n",
+       "1777    M4_41         198                         17       UTF-8   \n",
+       "1778   B0_162         201                         34       utf-8   \n",
+       "1779  B0_1152         234                         34  ISO-8859-1   \n",
+       "1780   B0_676         249                         40       utf-8   \n",
+       "\n",
+       "                      server  content_length whois_country whois_statepro  \\\n",
+       "0                      nginx           263.0           NaN            NaN   \n",
+       "1              Apache/2.4.10         15087.0           NaN            NaN   \n",
+       "2      Microsoft-HTTPAPI/2.0           324.0           NaN            NaN   \n",
+       "3                      nginx           162.0            US             AK   \n",
+       "4                        NaN        124140.0            US             TX   \n",
+       "...                      ...             ...           ...            ...   \n",
+       "1776                  Apache             NaN            ES      Barcelona   \n",
+       "1777                  Apache             NaN            ES      Barcelona   \n",
+       "1778  Apache/2.2.16 (Debian)          8904.0            US             FL   \n",
+       "1779        cloudflare-nginx             NaN            US             CA   \n",
+       "1780       Microsoft-IIS/8.5         24435.0            US      Wisconsin   \n",
+       "\n",
+       "         whois_regdate whois_updated_date  tcp_conversation_exchange  \\\n",
+       "0     10/10/2015 18:21                NaN                          7   \n",
+       "1                  NaN                NaN                         17   \n",
+       "2                  NaN                NaN                          0   \n",
+       "3       7/10/1997 4:00    12/09/2013 0:45                         31   \n",
+       "4      12/05/1996 0:00    11/04/2017 0:00                         57   \n",
+       "...                ...                ...                        ...   \n",
+       "1776   17/09/2008 0:00     2/09/2016 0:00                          0   \n",
+       "1777   17/09/2008 0:00     2/09/2016 0:00                          0   \n",
+       "1778   15/02/1999 0:00    15/07/2015 0:00                         83   \n",
+       "1779    1/04/1998 0:00     9/12/2016 0:00                          0   \n",
+       "1780   14/11/2008 0:00    20/11/2013 0:00                         19   \n",
+       "\n",
+       "      dist_remote_tcp_port  remote_ips  app_bytes  source_app_packets  \\\n",
+       "0                        0           2        700                   9   \n",
+       "1                        7           4       1230                  17   \n",
+       "2                        0           0          0                   0   \n",
+       "3                       22           3       3812                  39   \n",
+       "4                        2           5       4278                  61   \n",
+       "...                    ...         ...        ...                 ...   \n",
+       "1776                     0           0          0                   0   \n",
+       "1777                     0           0          0                   0   \n",
+       "1778                     2           6       6631                  87   \n",
+       "1779                     0           0          0                   0   \n",
+       "1780                     6          11       2314                  25   \n",
+       "\n",
+       "      remote_app_packets  source_app_bytes  remote_app_bytes  app_packets  \\\n",
+       "0                     10              1153               832            9   \n",
+       "1                     19              1265              1230           17   \n",
+       "2                      0                 0                 0            0   \n",
+       "3                     37             18784              4380           39   \n",
+       "4                     62            129889              4586           61   \n",
+       "...                  ...               ...               ...          ...   \n",
+       "1776                   3               186                 0            0   \n",
+       "1777                   2               124                 0            0   \n",
+       "1778                  89            132181              6945           87   \n",
+       "1779                   0                 0                 0            0   \n",
+       "1780                  28              3039              2776           25   \n",
+       "\n",
+       "      dns_query_times  type  \n",
+       "0                 2.0     1  \n",
+       "1                 0.0     0  \n",
+       "2                 0.0     0  \n",
+       "3                 8.0     0  \n",
+       "4                 4.0     0  \n",
+       "...               ...   ...  \n",
+       "1776              0.0     1  \n",
+       "1777              0.0     1  \n",
+       "1778              4.0     0  \n",
+       "1779              0.0     0  \n",
+       "1780              6.0     0  \n",
+       "\n",
+       "[1781 rows x 21 columns]"
+      ]
+     },
+     "execution_count": 44,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Una vez tenemos la copia, homogeneizamos y chequeamos el estado del dataframe\n",
+    "snake_columns(df)\n",
+    "df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "There are 0 duplicate rows. Also;\n"
+     ]
+    },
+    {
+     "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>NaN</th>\n",
+       "      <th>EmptySpaces</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>url</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>url_length</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>number_special_characters</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>charset</th>\n",
+       "      <td>7</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>server</th>\n",
+       "      <td>176</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>content_length</th>\n",
+       "      <td>812</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>whois_country</th>\n",
+       "      <td>306</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>whois_statepro</th>\n",
+       "      <td>362</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>whois_regdate</th>\n",
+       "      <td>127</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>whois_updated_date</th>\n",
+       "      <td>139</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tcp_conversation_exchange</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>dist_remote_tcp_port</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>remote_ips</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>app_bytes</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>source_app_packets</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>remote_app_packets</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>source_app_bytes</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>remote_app_bytes</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>app_packets</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>dns_query_times</th>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>type</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                           NaN  EmptySpaces\n",
+       "url                          0            0\n",
+       "url_length                   0            0\n",
+       "number_special_characters    0            0\n",
+       "charset                      7            0\n",
+       "server                     176            0\n",
+       "content_length             812            0\n",
+       "whois_country              306            0\n",
+       "whois_statepro             362            0\n",
+       "whois_regdate              127            0\n",
+       "whois_updated_date         139            0\n",
+       "tcp_conversation_exchange    0            0\n",
+       "dist_remote_tcp_port         0            0\n",
+       "remote_ips                   0            0\n",
+       "app_bytes                    0            0\n",
+       "source_app_packets           0            0\n",
+       "remote_app_packets           0            0\n",
+       "source_app_bytes             0            0\n",
+       "remote_app_bytes             0            0\n",
+       "app_packets                  0            0\n",
+       "dns_query_times              1            0\n",
+       "type                         0            0"
+      ]
+     },
+     "execution_count": 46,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# A continuación, revisamos duplicados, Nans y espacios en blanco:\n",
+    "explore_data(df)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your code here\n"
+    "# Podemos ver que las columnas con valores nulos son las categóricas (texto)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "URL                          1781\n",
+       "WHOIS_REGDATE                 890\n",
+       "SOURCE_APP_BYTES              885\n",
+       "APP_BYTES                     825\n",
+       "REMOTE_APP_BYTES              822\n",
+       "CONTENT_LENGTH                637\n",
+       "WHOIS_UPDATED_DATE            593\n",
+       "SERVER                        238\n",
+       "WHOIS_STATEPRO                181\n",
+       "URL_LENGTH                    142\n",
+       "REMOTE_APP_PACKETS            116\n",
+       "APP_PACKETS                   113\n",
+       "SOURCE_APP_PACKETS            113\n",
+       "TCP_CONVERSATION_EXCHANGE     103\n",
+       "DIST_REMOTE_TCP_PORT           66\n",
+       "WHOIS_COUNTRY                  48\n",
+       "NUMBER_SPECIAL_CHARACTERS      31\n",
+       "REMOTE_IPS                     18\n",
+       "DNS_QUERY_TIMES                10\n",
+       "CHARSET                         8\n",
+       "Type                            2\n",
+       "dtype: int64"
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Exploramos los valores unicos de cada categoría:\n",
+    "df.nunique().sort_values(ascending=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([1, 0])"
+      ]
+     },
+     "execution_count": 30,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Como podemos ver, 'type' tiene unicamente dos valores unicos. Seguimos explorando:\n",
+    "df.Type.unique()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Type\n",
+       "0    1565\n",
+       "1     216\n",
+       "Name: count, dtype: int64"
+      ]
+     },
+     "execution_count": 32,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Vemos que son booleanos, por lo que determinamos que es esta columna la que determinará si la URL es maliciosa o no.\n",
+    "# Seguimos explorando:\n",
+    "df.Type.value_counts()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Vemos que hay muchos más 0s que 1s, lo que sugiere que los 0 se utilicen para determinar que la URL no es maligna (False)\n",
+    "# Mientras que los 1s indicaran que la URL es maliciosa (True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "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>count</th>\n",
+       "      <th>mean</th>\n",
+       "      <th>std</th>\n",
+       "      <th>min</th>\n",
+       "      <th>25%</th>\n",
+       "      <th>50%</th>\n",
+       "      <th>75%</th>\n",
+       "      <th>max</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>url_length</th>\n",
+       "      <td>1781.0</td>\n",
+       "      <td>56.961258</td>\n",
+       "      <td>27.555586</td>\n",
+       "      <td>16.0</td>\n",
+       "      <td>39.0</td>\n",
+       "      <td>49.0</td>\n",
+       "      <td>68.0</td>\n",
+       "      <td>249.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>number_special_characters</th>\n",
+       "      <td>1781.0</td>\n",
+       "      <td>11.111735</td>\n",
+       "      <td>4.549896</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>8.0</td>\n",
+       "      <td>10.0</td>\n",
+       "      <td>13.0</td>\n",
+       "      <td>43.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>content_length</th>\n",
+       "      <td>969.0</td>\n",
+       "      <td>11726.927761</td>\n",
+       "      <td>36391.809051</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>324.0</td>\n",
+       "      <td>1853.0</td>\n",
+       "      <td>11323.0</td>\n",
+       "      <td>649263.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>tcp_conversation_exchange</th>\n",
+       "      <td>1781.0</td>\n",
+       "      <td>16.261089</td>\n",
+       "      <td>40.500975</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>7.0</td>\n",
+       "      <td>22.0</td>\n",
+       "      <td>1194.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>dist_remote_tcp_port</th>\n",
+       "      <td>1781.0</td>\n",
+       "      <td>5.472768</td>\n",
+       "      <td>21.807327</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>708.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>remote_ips</th>\n",
+       "      <td>1781.0</td>\n",
+       "      <td>3.060640</td>\n",
+       "      <td>3.386975</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>17.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>app_bytes</th>\n",
+       "      <td>1781.0</td>\n",
+       "      <td>2982.339135</td>\n",
+       "      <td>56050.574748</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>672.0</td>\n",
+       "      <td>2328.0</td>\n",
+       "      <td>2362906.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>source_app_packets</th>\n",
+       "      <td>1781.0</td>\n",
+       "      <td>18.540146</td>\n",
+       "      <td>41.627173</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>8.0</td>\n",
+       "      <td>26.0</td>\n",
+       "      <td>1198.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>remote_app_packets</th>\n",
+       "      <td>1781.0</td>\n",
+       "      <td>18.746210</td>\n",
+       "      <td>46.397969</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>9.0</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>1284.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>source_app_bytes</th>\n",
+       "      <td>1781.0</td>\n",
+       "      <td>15892.545761</td>\n",
+       "      <td>69861.929888</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>579.0</td>\n",
+       "      <td>9806.0</td>\n",
+       "      <td>2060012.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>remote_app_bytes</th>\n",
+       "      <td>1781.0</td>\n",
+       "      <td>3155.598540</td>\n",
+       "      <td>56053.780246</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>735.0</td>\n",
+       "      <td>2701.0</td>\n",
+       "      <td>2362906.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>app_packets</th>\n",
+       "      <td>1781.0</td>\n",
+       "      <td>18.540146</td>\n",
+       "      <td>41.627173</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>8.0</td>\n",
+       "      <td>26.0</td>\n",
+       "      <td>1198.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>dns_query_times</th>\n",
+       "      <td>1780.0</td>\n",
+       "      <td>2.263483</td>\n",
+       "      <td>2.930853</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>20.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>type</th>\n",
+       "      <td>1781.0</td>\n",
+       "      <td>0.121280</td>\n",
+       "      <td>0.326544</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                            count          mean           std   min    25%  \\\n",
+       "url_length                 1781.0     56.961258     27.555586  16.0   39.0   \n",
+       "number_special_characters  1781.0     11.111735      4.549896   5.0    8.0   \n",
+       "content_length              969.0  11726.927761  36391.809051   0.0  324.0   \n",
+       "tcp_conversation_exchange  1781.0     16.261089     40.500975   0.0    0.0   \n",
+       "dist_remote_tcp_port       1781.0      5.472768     21.807327   0.0    0.0   \n",
+       "remote_ips                 1781.0      3.060640      3.386975   0.0    0.0   \n",
+       "app_bytes                  1781.0   2982.339135  56050.574748   0.0    0.0   \n",
+       "source_app_packets         1781.0     18.540146     41.627173   0.0    0.0   \n",
+       "remote_app_packets         1781.0     18.746210     46.397969   0.0    0.0   \n",
+       "source_app_bytes           1781.0  15892.545761  69861.929888   0.0    0.0   \n",
+       "remote_app_bytes           1781.0   3155.598540  56053.780246   0.0    0.0   \n",
+       "app_packets                1781.0     18.540146     41.627173   0.0    0.0   \n",
+       "dns_query_times            1780.0      2.263483      2.930853   0.0    0.0   \n",
+       "type                       1781.0      0.121280      0.326544   0.0    0.0   \n",
+       "\n",
+       "                              50%      75%        max  \n",
+       "url_length                   49.0     68.0      249.0  \n",
+       "number_special_characters    10.0     13.0       43.0  \n",
+       "content_length             1853.0  11323.0   649263.0  \n",
+       "tcp_conversation_exchange     7.0     22.0     1194.0  \n",
+       "dist_remote_tcp_port          0.0      5.0      708.0  \n",
+       "remote_ips                    2.0      5.0       17.0  \n",
+       "app_bytes                   672.0   2328.0  2362906.0  \n",
+       "source_app_packets            8.0     26.0     1198.0  \n",
+       "remote_app_packets            9.0     25.0     1284.0  \n",
+       "source_app_bytes            579.0   9806.0  2060012.0  \n",
+       "remote_app_bytes            735.0   2701.0  2362906.0  \n",
+       "app_packets                   8.0     26.0     1198.0  \n",
+       "dns_query_times               0.0      4.0       20.0  \n",
+       "type                          0.0      0.0        1.0  "
+      ]
+     },
+     "execution_count": 48,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Sacamos las estadísticas descriptivas\n",
+    "df.describe().T"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# En este caso no podemos obtener mucha información de la estadísitca descriptiva"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 50,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Axes: xlabel='type', ylabel='count'>"
+      ]
+     },
+     "execution_count": 50,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sns.countplot(data=df, x=\"type\", palette=\"Oranges\")"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your comment here"
+    "# Los datos están muy desbalanceados. Más adelante exploraremos cómo solucionar esto."
    ]
   },
   {
@@ -102,20 +1414,68 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 60,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "type                         1.00\n",
+       "number_special_characters    0.28\n",
+       "url_length                   0.16\n",
+       "dns_query_times              0.07\n",
+       "remote_app_bytes            -0.01\n",
+       "app_bytes                   -0.01\n",
+       "remote_app_packets          -0.03\n",
+       "source_app_packets          -0.03\n",
+       "app_packets                 -0.03\n",
+       "tcp_conversation_exchange   -0.04\n",
+       "source_app_bytes            -0.04\n",
+       "remote_ips                  -0.08\n",
+       "dist_remote_tcp_port        -0.08\n",
+       "content_length              -0.09\n",
+       "dtype: float64"
+      ]
+     },
+     "execution_count": 60,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# Your code here\n"
+    "# Para poder hacer la matriz de correlación unicamente con las columnas numéricas, definimos estas columnas:\n",
+    "cat = df.select_dtypes(exclude=\"number\")\n",
+    "num = df.select_dtypes(include=\"number\")\n",
+    "round(num.corrwith(num[\"type\"]).sort_values(ascending=False),2)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 66,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 2500x1500 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
-    "# Your comment here"
+    "num_corr = num.corr().round(2)\n",
+    "mask = np.zeros_like(num_corr)\n",
+    "mask[np.triu_indices_from(mask)] = True # optional, to hide repeat half of the matrix\n",
+    "\n",
+    "f, ax = plt.subplots(figsize=(25, 15))\n",
+    "sns.set(font_scale=1.5) # increase font size\n",
+    "\n",
+    "ax = sns.heatmap(num_corr, mask=mask, annot=True, annot_kws={\"size\": 12}, linewidths=.5, cmap=\"coolwarm\", fmt=\".2f\", ax=ax) # round to 2 decimal places\n",
+    "ax.set_title(\"Chequear Multicolinearidad\", fontsize=20) \n",
+    "plt.show()"
    ]
   },
   {
@@ -133,29 +1493,307 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 68,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Index(['url_length', 'number_special_characters', 'content_length',\n",
+       "       'tcp_conversation_exchange', 'dist_remote_tcp_port', 'remote_ips',\n",
+       "       'app_bytes', 'source_app_packets', 'remote_app_packets',\n",
+       "       'source_app_bytes', 'remote_app_bytes', 'app_packets',\n",
+       "       'dns_query_times', 'type'],\n",
+       "      dtype='object')"
+      ]
+     },
+     "execution_count": 68,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# Your code here\n"
+    "num.columns"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 72,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your comment here"
+    "# Como nos explica en el script, quitamos las tres columnas con más colinearidad.\n",
+    "# app_packets, tcp_conversation_exchange, app_bytes, source_app_packets\n",
+    "# Eliminando estas cuatro columnas eliminamos casi toda la multicolinearidad\n",
+    "num.drop(columns=['app_packets','tcp_conversation_exchange','app_bytes','source_app_packets'], inplace=True)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 74,
    "metadata": {},
-   "outputs": [],
+   "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>url_length</th>\n",
+       "      <th>number_special_characters</th>\n",
+       "      <th>content_length</th>\n",
+       "      <th>dist_remote_tcp_port</th>\n",
+       "      <th>remote_ips</th>\n",
+       "      <th>remote_app_packets</th>\n",
+       "      <th>source_app_bytes</th>\n",
+       "      <th>remote_app_bytes</th>\n",
+       "      <th>dns_query_times</th>\n",
+       "      <th>type</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>16</td>\n",
+       "      <td>7</td>\n",
+       "      <td>263.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>10</td>\n",
+       "      <td>1153</td>\n",
+       "      <td>832</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>16</td>\n",
+       "      <td>6</td>\n",
+       "      <td>15087.0</td>\n",
+       "      <td>7</td>\n",
+       "      <td>4</td>\n",
+       "      <td>19</td>\n",
+       "      <td>1265</td>\n",
+       "      <td>1230</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>16</td>\n",
+       "      <td>6</td>\n",
+       "      <td>324.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>17</td>\n",
+       "      <td>6</td>\n",
+       "      <td>162.0</td>\n",
+       "      <td>22</td>\n",
+       "      <td>3</td>\n",
+       "      <td>37</td>\n",
+       "      <td>18784</td>\n",
+       "      <td>4380</td>\n",
+       "      <td>8.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>17</td>\n",
+       "      <td>6</td>\n",
+       "      <td>124140.0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>5</td>\n",
+       "      <td>62</td>\n",
+       "      <td>129889</td>\n",
+       "      <td>4586</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>0</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>1776</th>\n",
+       "      <td>194</td>\n",
+       "      <td>16</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>186</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1777</th>\n",
+       "      <td>198</td>\n",
+       "      <td>17</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>124</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1778</th>\n",
+       "      <td>201</td>\n",
+       "      <td>34</td>\n",
+       "      <td>8904.0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>6</td>\n",
+       "      <td>89</td>\n",
+       "      <td>132181</td>\n",
+       "      <td>6945</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1779</th>\n",
+       "      <td>234</td>\n",
+       "      <td>34</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1780</th>\n",
+       "      <td>249</td>\n",
+       "      <td>40</td>\n",
+       "      <td>24435.0</td>\n",
+       "      <td>6</td>\n",
+       "      <td>11</td>\n",
+       "      <td>28</td>\n",
+       "      <td>3039</td>\n",
+       "      <td>2776</td>\n",
+       "      <td>6.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>1781 rows × 10 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      url_length  number_special_characters  content_length  \\\n",
+       "0             16                          7           263.0   \n",
+       "1             16                          6         15087.0   \n",
+       "2             16                          6           324.0   \n",
+       "3             17                          6           162.0   \n",
+       "4             17                          6        124140.0   \n",
+       "...          ...                        ...             ...   \n",
+       "1776         194                         16             NaN   \n",
+       "1777         198                         17             NaN   \n",
+       "1778         201                         34          8904.0   \n",
+       "1779         234                         34             NaN   \n",
+       "1780         249                         40         24435.0   \n",
+       "\n",
+       "      dist_remote_tcp_port  remote_ips  remote_app_packets  source_app_bytes  \\\n",
+       "0                        0           2                  10              1153   \n",
+       "1                        7           4                  19              1265   \n",
+       "2                        0           0                   0                 0   \n",
+       "3                       22           3                  37             18784   \n",
+       "4                        2           5                  62            129889   \n",
+       "...                    ...         ...                 ...               ...   \n",
+       "1776                     0           0                   3               186   \n",
+       "1777                     0           0                   2               124   \n",
+       "1778                     2           6                  89            132181   \n",
+       "1779                     0           0                   0                 0   \n",
+       "1780                     6          11                  28              3039   \n",
+       "\n",
+       "      remote_app_bytes  dns_query_times  type  \n",
+       "0                  832              2.0     1  \n",
+       "1                 1230              0.0     0  \n",
+       "2                    0              0.0     0  \n",
+       "3                 4380              8.0     0  \n",
+       "4                 4586              4.0     0  \n",
+       "...                ...              ...   ...  \n",
+       "1776                 0              0.0     1  \n",
+       "1777                 0              0.0     1  \n",
+       "1778              6945              4.0     0  \n",
+       "1779                 0              0.0     0  \n",
+       "1780              2776              6.0     0  \n",
+       "\n",
+       "[1781 rows x 10 columns]"
+      ]
+     },
+     "execution_count": 74,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "num"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 76,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 2500x1500 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
-    "# Print heatmap again\n"
+    "num_corr = num.corr().round(2)\n",
+    "mask = np.zeros_like(num_corr)\n",
+    "mask[np.triu_indices_from(mask)] = True # optional, to hide repeat half of the matrix\n",
+    "\n",
+    "f, ax = plt.subplots(figsize=(25, 15))\n",
+    "sns.set(font_scale=1.5) # increase font size\n",
+    "\n",
+    "ax = sns.heatmap(num_corr, mask=mask, annot=True, annot_kws={\"size\": 12}, linewidths=.5, cmap=\"coolwarm\", fmt=\".2f\", ax=ax) # round to 2 decimal places\n",
+    "ax.set_title(\"Chequear Multicolinearidad\", fontsize=20) \n",
+    "plt.show()"
    ]
   },
   {
@@ -169,11 +1807,117 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 78,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "There are 131 duplicate rows. Also;\n"
+     ]
+    },
+    {
+     "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>NaN</th>\n",
+       "      <th>EmptySpaces</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>url_length</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>number_special_characters</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>content_length</th>\n",
+       "      <td>812</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>dist_remote_tcp_port</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>remote_ips</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>remote_app_packets</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>source_app_bytes</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>remote_app_bytes</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>dns_query_times</th>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>type</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                           NaN  EmptySpaces\n",
+       "url_length                   0            0\n",
+       "number_special_characters    0            0\n",
+       "content_length             812            0\n",
+       "dist_remote_tcp_port         0            0\n",
+       "remote_ips                   0            0\n",
+       "remote_app_packets           0            0\n",
+       "source_app_bytes             0            0\n",
+       "remote_app_bytes             0            0\n",
+       "dns_query_times              1            0\n",
+       "type                         0            0"
+      ]
+     },
+     "execution_count": 78,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# Your code here\n"
+    "explore_data(num)"
    ]
   },
   {
@@ -187,20 +1931,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 80,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your code here\n"
+    "# Eliminamos la columna de 'content_lenght' ya que tiene un gran porcentaje de valores nulos\n",
+    "num.drop(columns=['content_length'], inplace=True)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 82,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your comment here"
+    "# En cuanot a la columna de 'dns_query_times', rellenamos el valor nulo con el metodo backfill\n",
+    "num['dns_query_times'].fillna(method='ffill', inplace=True)"
    ]
   },
   {
@@ -214,11 +1960,112 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 84,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "There are 345 duplicate rows. Also;\n"
+     ]
+    },
+    {
+     "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>NaN</th>\n",
+       "      <th>EmptySpaces</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>url_length</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>number_special_characters</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>dist_remote_tcp_port</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>remote_ips</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>remote_app_packets</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>source_app_bytes</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>remote_app_bytes</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>dns_query_times</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>type</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                           NaN  EmptySpaces\n",
+       "url_length                   0            0\n",
+       "number_special_characters    0            0\n",
+       "dist_remote_tcp_port         0            0\n",
+       "remote_ips                   0            0\n",
+       "remote_app_packets           0            0\n",
+       "source_app_bytes             0            0\n",
+       "remote_app_bytes             0            0\n",
+       "dns_query_times              0            0\n",
+       "type                         0            0"
+      ]
+     },
+     "execution_count": 84,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# Examine missing values in each column\n"
+    "# Examine missing values in each column\n",
+    "explore_data(num)"
    ]
   },
   {
@@ -256,11 +2103,158 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 86,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Index(['url', 'charset', 'server', 'whois_country', 'whois_statepro',\n",
+       "       'whois_regdate', 'whois_updated_date'],\n",
+       "      dtype='object')"
+      ]
+     },
+     "execution_count": 86,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cat.columns"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 88,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([nan, 'US', 'SC', 'GB', 'UK', 'RU', 'AU', 'CA', 'PA', 'se', 'IN',\n",
+       "       'LU', 'TH', \"[u'GB'; u'UK']\", 'FR', 'NL', 'UG', 'JP', 'CN', 'SE',\n",
+       "       'SI', 'IL', 'ru', 'KY', 'AT', 'CZ', 'PH', 'BE', 'NO', 'TR', 'LV',\n",
+       "       'DE', 'ES', 'BR', 'us', 'KR', 'HK', 'UA', 'CH', 'United Kingdom',\n",
+       "       'BS', 'PK', 'IT', 'Cyprus', 'BY', 'AE', 'IE', 'UY', 'KG'],\n",
+       "      dtype=object)"
+      ]
+     },
+     "execution_count": 88,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cat['whois_country'].unique()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 90,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your code here\n"
+    "# LO QUE TENGO : LO QUE QUIERO\n",
+    "country_mapping = {\n",
+    "    'nan': None,         # Valores nulos o faltantes\n",
+    "    'US': 'US',          # Estados Unidos\n",
+    "    'us': 'US',          # Estados Unidos (en minúsculas)\n",
+    "    'SC': 'SC',          # Seychelles\n",
+    "    'GB': 'UK',          # Reino Unido\n",
+    "    'UK': 'UK',          # Reino Unido (variación)\n",
+    "    \"[u'GB'; u'UK']\": 'UK',  # Reino Unido (otra variación)\n",
+    "    'United Kingdom': 'UK',  # Reino Unido (nombre completo)\n",
+    "    'RU': 'RU',          # Rusia\n",
+    "    'ru': 'RU',          # Rusia (en minúsculas)\n",
+    "    'AU': 'AU',          # Australia\n",
+    "    'CA': 'CA',          # Canadá\n",
+    "    'PA': 'PA',          # Panamá\n",
+    "    'se': 'SE',          # Suecia (en minúsculas)\n",
+    "    'SE': 'SE',          # Suecia\n",
+    "    'IN': 'IN',          # India\n",
+    "    'LU': 'LU',          # Luxemburgo\n",
+    "    'TH': 'TH',          # Tailandia\n",
+    "    'FR': 'FR',          # Francia\n",
+    "    'NL': 'NL',          # Países Bajos\n",
+    "    'UG': 'UG',          # Uganda\n",
+    "    'JP': 'JP',          # Japón\n",
+    "    'CN': 'CN',          # China\n",
+    "    'SI': 'SI',          # Eslovenia\n",
+    "    'IL': 'IL',          # Israel\n",
+    "    'KY': 'KY',          # Islas Caimán\n",
+    "    'AT': 'AT',          # Austria\n",
+    "    'CZ': 'CZ',          # República Checa\n",
+    "    'PH': 'PH',          # Filipinas\n",
+    "    'BE': 'BE',          # Bélgica\n",
+    "    'NO': 'NO',          # Noruega\n",
+    "    'TR': 'TR',          # Turquía\n",
+    "    'LV': 'LV',          # Letonia\n",
+    "    'DE': 'DE',          # Alemania\n",
+    "    'ES': 'ES',          # España\n",
+    "    'BR': 'BR',          # Brasil\n",
+    "    'KR': 'KR',          # Corea del Sur\n",
+    "    'HK': 'HK',          # Hong Kong\n",
+    "    'UA': 'UA',          # Ucrania\n",
+    "    'CH': 'CH',          # Suiza\n",
+    "    'BS': 'BS',          # Bahamas\n",
+    "    'PK': 'PK',          # Pakistán\n",
+    "    'IT': 'IT',          # Italia\n",
+    "    'Cyprus': 'CY',      # Chipre (nombre completo)\n",
+    "    'BY': 'BY',          # Bielorrusia\n",
+    "    'AE': 'AE',          # Emiratos Árabes Unidos\n",
+    "    'IE': 'IE',          # Irlanda\n",
+    "    'UY': 'UY',          # Uruguay\n",
+    "    'KG': 'KG'           # Kirguistán\n",
+    "}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 94,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "49"
+      ]
+     },
+     "execution_count": 94,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "len(country_mapping)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 96,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "cat['whois_country'] = cat['whois_country'].map(country_mapping)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 98,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "42"
+      ]
+     },
+     "execution_count": 98,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cat['whois_country'].nunique()"
    ]
   },
   {
@@ -278,11 +2272,65 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 100,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "whois_country\n",
+       "US    1106\n",
+       "CA      84\n",
+       "ES      63\n",
+       "UK      35\n",
+       "AU      35\n",
+       "PA      21\n",
+       "JP      11\n",
+       "CN      10\n",
+       "IN      10\n",
+       "FR       9\n",
+       "CZ       9\n",
+       "CH       6\n",
+       "NL       6\n",
+       "RU       6\n",
+       "KR       5\n",
+       "AT       4\n",
+       "BS       4\n",
+       "PH       4\n",
+       "SE       4\n",
+       "KY       3\n",
+       "TR       3\n",
+       "DE       3\n",
+       "HK       3\n",
+       "SC       3\n",
+       "BE       3\n",
+       "NO       2\n",
+       "UA       2\n",
+       "UY       2\n",
+       "CY       2\n",
+       "SI       2\n",
+       "KG       2\n",
+       "IL       2\n",
+       "BR       2\n",
+       "TH       1\n",
+       "PK       1\n",
+       "IT       1\n",
+       "UG       1\n",
+       "BY       1\n",
+       "AE       1\n",
+       "IE       1\n",
+       "LV       1\n",
+       "LU       1\n",
+       "Name: count, dtype: int64"
+      ]
+     },
+     "execution_count": 100,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# Your code here\n"
+    "cat['whois_country'].value_counts()"
    ]
   },
   {
@@ -294,13 +2342,46 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 104,
    "metadata": {
     "scrolled": true
    },
    "outputs": [],
    "source": [
-    "# Your code here\n"
+    "top_10_values = cat['whois_country'].value_counts().head(10).index\n",
+    "cat['whois_country'] = cat['whois_country'].apply(lambda x: x if x in top_10_values else 'other')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 108,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "whois_country\n",
+       "US       1106\n",
+       "other     397\n",
+       "CA         84\n",
+       "ES         63\n",
+       "UK         35\n",
+       "AU         35\n",
+       "PA         21\n",
+       "JP         11\n",
+       "IN         10\n",
+       "CN         10\n",
+       "FR          9\n",
+       "Name: count, dtype: int64"
+      ]
+     },
+     "execution_count": 108,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cat['whois_country'].value_counts()"
    ]
   },
   {
@@ -316,11 +2397,54 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 114,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Index(['url', 'charset', 'server', 'whois_country', 'whois_statepro',\n",
+       "       'whois_regdate', 'whois_updated_date'],\n",
+       "      dtype='object')"
+      ]
+     },
+     "execution_count": 114,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cat.columns"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 116,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your code here\n"
+    "# Your code here\n",
+    "cat.drop(columns=['whois_statepro','whois_regdate','whois_updated_date'], inplace=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 118,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Index(['url', 'charset', 'server', 'whois_country'], dtype='object')"
+      ]
+     },
+     "execution_count": 118,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cat.columns"
    ]
   },
   {
@@ -334,11 +2458,26 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 122,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "url              object\n",
+       "charset          object\n",
+       "server           object\n",
+       "whois_country    object\n",
+       "dtype: object"
+      ]
+     },
+     "execution_count": 122,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# Your code here\n"
+    "cat.dtypes"
    ]
   },
   {
@@ -350,11 +2489,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 126,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your code here\n"
+    "cat.drop(columns='url', inplace=True)"
    ]
   },
   {
@@ -366,11 +2505,43 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 128,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array(['iso-8859-1', 'UTF-8', 'us-ascii', 'ISO-8859-1', 'utf-8', nan,\n",
+       "       'windows-1251', 'ISO-8859', 'windows-1252'], dtype=object)"
+      ]
+     },
+     "execution_count": 128,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# Your code here"
+    "cat.charset.unique()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 130,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "8"
+      ]
+     },
+     "execution_count": 130,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cat.charset.nunique()"
    ]
   },
   {
@@ -384,11 +2555,171 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 132,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "238"
+      ]
+     },
+     "execution_count": 132,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# Your code here\n"
+    "cat.server.nunique()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 134,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array(['nginx', 'Apache/2.4.10', 'Microsoft-HTTPAPI/2.0', nan, 'Apache/2',\n",
+       "       'nginx/1.10.1', 'Apache', 'Apache/2.2.15 (Red Hat)',\n",
+       "       'Apache/2.4.23 (Unix) OpenSSL/1.0.1e-fips mod_bwlimited/1.4',\n",
+       "       'openresty/1.11.2.1', 'Apache/2.2.22', 'Apache/2.4.7 (Ubuntu)',\n",
+       "       'nginx/1.12.0',\n",
+       "       'Apache/2.4.12 (Unix) OpenSSL/1.0.1e-fips mod_bwlimited/1.4',\n",
+       "       'Oracle-iPlanet-Web-Server/7.0', 'cloudflare-nginx', 'nginx/1.6.2',\n",
+       "       'openresty', 'Heptu web server', 'Pepyaka/1.11.3', 'nginx/1.8.0',\n",
+       "       'nginx/1.10.1 + Phusion Passenger 5.0.30',\n",
+       "       'Apache/2.2.29 (Amazon)', 'Microsoft-IIS/7.5', 'LiteSpeed',\n",
+       "       'Apache/2.4.25 (cPanel) OpenSSL/1.0.1e-fips mod_bwlimited/1.4',\n",
+       "       'tsa_c', 'Apache/2.2.0 (Fedora)', 'Apache/2.2.22 (Debian)',\n",
+       "       'Apache/2.2.15 (CentOS)', 'Apache/2.4.25',\n",
+       "       'Apache/2.4.25 (Amazon) PHP/7.0.14', 'GSE',\n",
+       "       'Apache/2.4.23 (Unix) OpenSSL/0.9.8e-fips-rhel5 mod_bwlimited/1.4',\n",
+       "       'Apache/2.4.25 (Amazon) OpenSSL/1.0.1k-fips',\n",
+       "       'Apache/2.2.22 (Ubuntu)', 'Tengine',\n",
+       "       'Apache/2.4.18 (Unix) OpenSSL/0.9.8e-fips-rhel5 mod_bwlimited/1.4',\n",
+       "       'Apache/2.4.10 (Debian)', 'Apache/2.4.6 (CentOS) PHP/5.6.8',\n",
+       "       'Sun-ONE-Web-Server/6.1',\n",
+       "       'Apache/2.4.18 (Unix) OpenSSL/1.0.2e Communique/4.1.10',\n",
+       "       'AmazonS3',\n",
+       "       'Apache/1.3.37 (Unix) mod_perl/1.29 mod_ssl/2.8.28 OpenSSL/0.9.7e-p1',\n",
+       "       'ATS', 'Apache/2.2.27 (CentOS)',\n",
+       "       'Apache/2.2.29 (Unix) mod_ssl/2.2.29 OpenSSL/1.0.1e-fips DAV/2 mod_bwlimited/1.4',\n",
+       "       'CherryPy/3.6.0', 'Server', 'KHL',\n",
+       "       'Apache/2.4.6 (CentOS) OpenSSL/1.0.1e-fips mod_fcgid/2.3.9 PHP/5.4.16 mod_jk/1.2.40',\n",
+       "       'Apache/2.2.3 (CentOS)', 'Apache/2.4',\n",
+       "       'Apache/1.3.27 (Unix)  (Red-Hat/Linux) mod_perl/1.26 PHP/4.3.3 FrontPage/5.0.2 mod_ssl/2.8.12 OpenSSL/0.9.6b',\n",
+       "       'mw2114.codfw.wmnet',\n",
+       "       'Apache/2.2.31 (Unix) mod_ssl/2.2.31 OpenSSL/1.0.1e-fips mod_bwlimited/1.4 mod_perl/2.0.8 Perl/v5.10.1',\n",
+       "       'Apache/1.3.34 (Unix) PHP/4.4.4', 'Apache/2.2.31 (Amazon)',\n",
+       "       'Jetty(9.0.z-SNAPSHOT)', 'Apache/2.2.31 (CentOS)',\n",
+       "       'Apache/2.4.12 (Ubuntu)', 'HTTPDaemon',\n",
+       "       'Apache/2.2.29 (Unix) mod_ssl/2.2.29 OpenSSL/1.0.1e-fips mod_bwlimited/1.4',\n",
+       "       'MediaFire', 'DOSarrest', 'mw2232.codfw.wmnet',\n",
+       "       'Sucuri/Cloudproxy', 'Apache/2.4.23 (Unix)', 'nginx/0.7.65',\n",
+       "       'mw2260.codfw.wmnet', 'Apache/2.2.32', 'mw2239.codfw.wmnet',\n",
+       "       'DPS/1.1.8', 'Apache/2.0.52 (Red Hat)',\n",
+       "       'Apache/2.2.25 (Unix) mod_ssl/2.2.25 OpenSSL/0.9.8e-fips-rhel5 mod_bwlimited/1.4',\n",
+       "       'Apache/1.3.31 (Unix) PHP/4.3.9 mod_perl/1.29 rus/PL30.20',\n",
+       "       'Apache/2.2.13 (Unix) mod_ssl/2.2.13 OpenSSL/0.9.8e-fips-rhel5 mod_auth_passthrough/2.1 mod_bwlimited/1.4 PHP/5.2.10',\n",
+       "       'nginx/1.1.19', 'ATS/5.3.0', 'Apache/2.2.3 (Red Hat)',\n",
+       "       'nginx/1.4.3',\n",
+       "       'Apache/2.2.29 (Unix) mod_ssl/2.2.29 OpenSSL/1.0.1e-fips mod_bwlimited/1.4 PHP/5.4.35',\n",
+       "       'Apache/2.2.14 (FreeBSD) mod_ssl/2.2.14 OpenSSL/0.9.8y DAV/2 PHP/5.2.12 with Suhosin-Patch',\n",
+       "       'Apache/2.2.14 (Unix) mod_ssl/2.2.14 OpenSSL/0.9.8e-fips-rhel5',\n",
+       "       'Apache/1.3.39 (Unix) PHP/5.2.5 mod_auth_passthrough/1.8 mod_bwlimited/1.4 mod_log_bytes/1.2 mod_gzip/1.3.26.1a FrontPage/5.0.2.2635 DAV/1.0.3 mod_ssl/2.8.30 OpenSSL/0.9.7a',\n",
+       "       'SSWS', 'Microsoft-IIS/8.0', 'Apache/2.4.18 (Ubuntu)',\n",
+       "       'Apache/2.4.6 (CentOS) OpenSSL/1.0.1e-fips PHP/5.4.16 mod_apreq2-20090110/2.8.0 mod_perl/2.0.10 Perl/v5.24.1',\n",
+       "       'Apache/2.2.20 (Unix)', 'YouTubeFrontEnd', 'nginx/1.11.3',\n",
+       "       'nginx/1.11.2', 'nginx/1.10.0 (Ubuntu)', 'nginx/1.8.1',\n",
+       "       'nginx/1.11.10', 'Squeegit/1.2.5 (3_sir)',\n",
+       "       'Virtuoso/07.20.3217 (Linux) i686-generic-linux-glibc212-64  VDB',\n",
+       "       'Apache-Coyote/1.1', 'Yippee-Ki-Yay', 'mw2165.codfw.wmnet',\n",
+       "       'mw2192.codfw.wmnet', 'Apache/2.2.23 (Amazon)',\n",
+       "       'nginx/1.4.6 (Ubuntu)', 'nginx + Phusion Passenger',\n",
+       "       'Proxy Pandeiro UOL', 'mw2231.codfw.wmnet', 'openresty/1.11.2.2',\n",
+       "       'mw2109.codfw.wmnet', 'nginx/0.8.54', 'Apache/2.4.6',\n",
+       "       'mw2225.codfw.wmnet', 'Apache/1.3.27 (Unix) PHP/4.4.1',\n",
+       "       'mw2236.codfw.wmnet', 'mw2101.codfw.wmnet', 'Varnish',\n",
+       "       'Resin/3.1.8', 'mw2164.codfw.wmnet', 'Microsoft-IIS/8.5',\n",
+       "       'mw2242.codfw.wmnet',\n",
+       "       'Apache/2.4.6 (CentOS) OpenSSL/1.0.1e-fips PHP/5.5.38',\n",
+       "       'mw2175.codfw.wmnet', 'mw2107.codfw.wmnet', 'mw2190.codfw.wmnet',\n",
+       "       'Apache/2.4.6 (CentOS)', 'nginx/1.13.0', 'barista/5.1.3',\n",
+       "       'mw2103.codfw.wmnet', 'Apache/2.4.25 (Debian)', 'ECD (fll/0790)',\n",
+       "       'Pagely Gateway/1.5.1', 'nginx/1.10.3',\n",
+       "       'Apache/2.4.25 (FreeBSD) OpenSSL/1.0.1s-freebsd PHP/5.6.30',\n",
+       "       'mw2097.codfw.wmnet', 'mw2233.codfw.wmnet', 'fbs',\n",
+       "       'mw2199.codfw.wmnet', 'mw2255.codfw.wmnet', 'mw2228.codfw.wmnet',\n",
+       "       'Apache/2.2.31 (Unix) mod_ssl/2.2.31 OpenSSL/1.0.1e-fips mod_bwlimited/1.4 mod_fcgid/2.3.9',\n",
+       "       'gunicorn/19.7.1',\n",
+       "       'Apache/2.2.31 (Unix) mod_ssl/2.2.31 OpenSSL/0.9.8e-fips-rhel5 mod_bwlimited/1.4',\n",
+       "       'Apache/2.4.6 (CentOS) OpenSSL/1.0.1e-fips PHP/5.4.16',\n",
+       "       'mw2241.codfw.wmnet',\n",
+       "       'Apache/1.3.33 (Unix) mod_ssl/2.8.24 OpenSSL/0.9.7e-p1 PHP/4.4.8',\n",
+       "       'lighttpd', 'mw2230.codfw.wmnet',\n",
+       "       'Apache/2.4.6 (CentOS) OpenSSL/1.0.1e-fips', 'AkamaiGHost',\n",
+       "       'mw2240.codfw.wmnet', 'nginx/1.10.2', 'PWS/8.2.0.7', 'nginx/1.2.1',\n",
+       "       'nxfps',\n",
+       "       'Apache/2.2.16 (Unix) mod_ssl/2.2.16 OpenSSL/0.9.8e-fips-rhel5 mod_auth_passthrough/2.1 mod_bwlimited/1.4',\n",
+       "       'Play', 'mw2185.codfw.wmnet',\n",
+       "       'Apache/2.4.10 (Unix) OpenSSL/1.0.1k',\n",
+       "       'Apache/Not telling (Unix) AuthTDS/1.1',\n",
+       "       'Apache/2.2.11 (Unix) PHP/5.2.6', 'Scratch Web Server',\n",
+       "       'marrakesh 1.12.2', 'nginx/0.8.35', 'mw2182.codfw.wmnet',\n",
+       "       'squid/3.3.8', 'nginx/1.10.0', 'Nginx (OpenBSD)',\n",
+       "       'Zope/(2.13.16; python 2.6.8; linux2) ZServer/1.1',\n",
+       "       'Apache/2.2.26 (Unix) mod_ssl/2.2.26 OpenSSL/0.9.8e-fips-rhel5 mod_bwlimited/1.4 PHP/5.4.26',\n",
+       "       'Apache/2.2.21 (Unix) mod_ssl/2.2.21 OpenSSL/0.9.8e-fips-rhel5 PHP/5.3.10',\n",
+       "       'Apache/2.2.27 (Unix) OpenAM Web Agent/4.0.1-1 mod_ssl/2.2.27 OpenSSL/1.0.1p PHP/5.3.28',\n",
+       "       'mw2104.codfw.wmnet', '.V01 Apache', 'mw2110.codfw.wmnet',\n",
+       "       'Apache/2.4.6 (Unix) mod_jk/1.2.37 PHP/5.5.1 OpenSSL/1.0.1g mod_fcgid/2.3.9',\n",
+       "       'mw2176.codfw.wmnet', 'mw2187.codfw.wmnet', 'mw2106.codfw.wmnet',\n",
+       "       'Microsoft-IIS/7.0',\n",
+       "       'Apache/1.3.42 Ben-SSL/1.60 (Unix) mod_gzip/1.3.26.1a mod_fastcgi/2.4.6 mod_throttle/3.1.2 Chili!Soft-ASP/3.6.2 FrontPage/5.0.2.2635 mod_perl/1.31 PHP/4.4.9',\n",
+       "       'Aeria Games & Entertainment', 'nginx/1.6.3 + Phusion Passenger',\n",
+       "       'Apache/2.4.10 (Debian) PHP/5.6.30-0+deb8u1 mod_perl/2.0.9dev Perl/v5.20.2',\n",
+       "       'mw2173.codfw.wmnet',\n",
+       "       'Apache/2.4.6 (Red Hat Enterprise Linux) OpenSSL/1.0.1e-fips mod_fcgid/2.3.9 Communique/4.2.0',\n",
+       "       'Apache/2.2.15 (CentOS) DAV/2 mod_ssl/2.2.15 OpenSSL/1.0.1e-fips PHP/5.3.3',\n",
+       "       'Apache/2.4.6 (CentOS) OpenSSL/1.0.1e-fips PHP/7.0.14',\n",
+       "       'mw2198.codfw.wmnet', 'mw2172.codfw.wmnet', 'nginx/1.2.6',\n",
+       "       'Apache/2.4.6 (Unix) mod_jk/1.2.37',\n",
+       "       'Apache/2.4.25 (Unix) OpenSSL/1.0.1e-fips mod_bwlimited/1.4',\n",
+       "       'nginx/1.4.4', 'Cowboy', 'mw2113.codfw.wmnet',\n",
+       "       'Apache/2.2.14 (Unix) mod_ssl/2.2.14 OpenSSL/0.9.8a',\n",
+       "       'Apache/2.4.10 (Ubuntu)', 'mw2224.codfw.wmnet',\n",
+       "       'mw2171.codfw.wmnet', 'mw2257.codfw.wmnet', 'mw2226.codfw.wmnet',\n",
+       "       'DMS/1.0.42', 'nginx/1.6.3', 'Application-Server',\n",
+       "       'Apache/2.4.6 (CentOS) mod_fcgid/2.3.9 PHP/5.6.30',\n",
+       "       'mw2177.codfw.wmnet', 'lighttpd/1.4.28', 'mw2197.codfw.wmnet',\n",
+       "       'Apache/2.2.31 (FreeBSD) PHP/5.4.15 mod_ssl/2.2.31 OpenSSL/1.0.2d DAV/2',\n",
+       "       'Apache/2.2.26 (Unix) mod_ssl/2.2.26 OpenSSL/1.0.1e-fips DAV/2 mod_bwlimited/1.4',\n",
+       "       'Apache/2.2.24 (Unix) DAV/2 PHP/5.3.26 mod_ssl/2.2.24 OpenSSL/0.9.8y',\n",
+       "       'mw2178.codfw.wmnet', '294', 'Microsoft-IIS/6.0', 'nginx/1.7.4',\n",
+       "       'Apache/2.2.22 (Debian) mod_python/3.3.1 Python/2.7.3 mod_ssl/2.2.22 OpenSSL/1.0.1t',\n",
+       "       'Apache/2.4.16 (Ubuntu)', 'www.lexisnexis.com  9999',\n",
+       "       'nginx/0.8.38', 'mw2238.codfw.wmnet', 'Pizza/pepperoni',\n",
+       "       'XXXXXXXXXXXXXXXXXXXXXX', 'MI', 'Roxen/5.4.98-r2',\n",
+       "       'Apache/2.2.31 (Unix) mod_ssl/2.2.31 OpenSSL/1.0.1e-fips mod_bwlimited/1.4',\n",
+       "       'nginx/1.9.13', 'mw2180.codfw.wmnet', 'Apache/2.2.14 (Ubuntu)',\n",
+       "       'ebay server', 'nginx/0.8.55', 'Apache/2.2.10 (Linux/SUSE)',\n",
+       "       'nginx/1.7.12',\n",
+       "       'Apache/2.0.63 (Unix) mod_ssl/2.0.63 OpenSSL/0.9.8e-fips-rhel5 mod_auth_passthrough/2.1 mod_bwlimited/1.4 PHP/5.3.6',\n",
+       "       'Boston.com Frontend', 'My Arse', 'IdeaWebServer/v0.80',\n",
+       "       'Apache/2.4.17 (Unix) OpenSSL/1.0.1e-fips PHP/5.6.19',\n",
+       "       'Microsoft-IIS/7.5; litigation_essentials.lexisnexis.com  9999',\n",
+       "       'Apache/2.2.16 (Debian)'], dtype=object)"
+      ]
+     },
+     "execution_count": 134,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cat.server.unique()"
    ]
   },
   {
@@ -404,7 +2735,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your comment here\n"
+    "# Vemos que aparecen varios servidores, pero lo que tienen en común es que aparece el nombre del mismo con un formato determinado:\n",
+    "# Nombre /.\n",
+    "# Por ello, aplicaría regex para separar el nombre "
    ]
   },
   {
@@ -418,22 +2751,217 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 142,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your code here\n"
+    "import re\n",
+    "\n",
+    "regex = r\"^[^/]+\"\n",
+    "cat['server'] = cat['server'].apply(lambda x: re.match(regex, str(x)).group(0) if isinstance(x, str) and re.match(regex, str(x)) else x)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
-   "metadata": {
-    "scrolled": false
-   },
+   "execution_count": 144,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array(['nginx', 'Apache', 'Microsoft-HTTPAPI', nan, 'openresty',\n",
+       "       'Oracle-iPlanet-Web-Server', 'cloudflare-nginx',\n",
+       "       'Heptu web server', 'Pepyaka', 'Microsoft-IIS', 'LiteSpeed',\n",
+       "       'tsa_c', 'GSE', 'Tengine', 'Sun-ONE-Web-Server', 'AmazonS3', 'ATS',\n",
+       "       'CherryPy', 'Server', 'KHL', 'mw2114.codfw.wmnet',\n",
+       "       'Jetty(9.0.z-SNAPSHOT)', 'HTTPDaemon', 'MediaFire', 'DOSarrest',\n",
+       "       'mw2232.codfw.wmnet', 'Sucuri', 'mw2260.codfw.wmnet',\n",
+       "       'mw2239.codfw.wmnet', 'DPS', 'SSWS', 'YouTubeFrontEnd', 'Squeegit',\n",
+       "       'Virtuoso', 'Apache-Coyote', 'Yippee-Ki-Yay', 'mw2165.codfw.wmnet',\n",
+       "       'mw2192.codfw.wmnet', 'nginx + Phusion Passenger',\n",
+       "       'Proxy Pandeiro UOL', 'mw2231.codfw.wmnet', 'mw2109.codfw.wmnet',\n",
+       "       'mw2225.codfw.wmnet', 'mw2236.codfw.wmnet', 'mw2101.codfw.wmnet',\n",
+       "       'Varnish', 'Resin', 'mw2164.codfw.wmnet', 'mw2242.codfw.wmnet',\n",
+       "       'mw2175.codfw.wmnet', 'mw2107.codfw.wmnet', 'mw2190.codfw.wmnet',\n",
+       "       'barista', 'mw2103.codfw.wmnet', 'ECD (fll', 'Pagely Gateway',\n",
+       "       'mw2097.codfw.wmnet', 'mw2233.codfw.wmnet', 'fbs',\n",
+       "       'mw2199.codfw.wmnet', 'mw2255.codfw.wmnet', 'mw2228.codfw.wmnet',\n",
+       "       'gunicorn', 'mw2241.codfw.wmnet', 'lighttpd', 'mw2230.codfw.wmnet',\n",
+       "       'AkamaiGHost', 'mw2240.codfw.wmnet', 'PWS', 'nxfps', 'Play',\n",
+       "       'mw2185.codfw.wmnet', 'Scratch Web Server', 'marrakesh 1.12.2',\n",
+       "       'mw2182.codfw.wmnet', 'squid', 'Nginx (OpenBSD)', 'Zope',\n",
+       "       'mw2104.codfw.wmnet', '.V01 Apache', 'mw2110.codfw.wmnet',\n",
+       "       'mw2176.codfw.wmnet', 'mw2187.codfw.wmnet', 'mw2106.codfw.wmnet',\n",
+       "       'Aeria Games & Entertainment', 'mw2173.codfw.wmnet',\n",
+       "       'mw2198.codfw.wmnet', 'mw2172.codfw.wmnet', 'Cowboy',\n",
+       "       'mw2113.codfw.wmnet', 'mw2224.codfw.wmnet', 'mw2171.codfw.wmnet',\n",
+       "       'mw2257.codfw.wmnet', 'mw2226.codfw.wmnet', 'DMS',\n",
+       "       'Application-Server', 'mw2177.codfw.wmnet', 'mw2197.codfw.wmnet',\n",
+       "       'mw2178.codfw.wmnet', '294', 'www.lexisnexis.com  9999',\n",
+       "       'mw2238.codfw.wmnet', 'Pizza', 'XXXXXXXXXXXXXXXXXXXXXX', 'MI',\n",
+       "       'Roxen', 'mw2180.codfw.wmnet', 'ebay server',\n",
+       "       'Boston.com Frontend', 'My Arse', 'IdeaWebServer'], dtype=object)"
+      ]
+     },
+     "execution_count": 144,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cat.server.unique()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 146,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "server\n",
+       "Apache                622\n",
+       "nginx                 337\n",
+       "Microsoft-HTTPAPI     113\n",
+       "cloudflare-nginx       94\n",
+       "Microsoft-IIS          85\n",
+       "                     ... \n",
+       "mw2103.codfw.wmnet      1\n",
+       "barista                 1\n",
+       "mw2190.codfw.wmnet      1\n",
+       "mw2107.codfw.wmnet      1\n",
+       "IdeaWebServer           1\n",
+       "Name: count, Length: 110, dtype: int64"
+      ]
+     },
+     "execution_count": 146,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cat.server.value_counts()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 148,
+   "metadata": {},
    "outputs": [],
    "source": [
-    "# Count `SERVER` value counts here\n"
+    "top_3_values = cat['server'].value_counts().head(3).index\n",
+    "cat['server'] = cat['server'].apply(lambda x: x if x in top_3_values else 'other')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 150,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "server\n",
+       "other                709\n",
+       "Apache               622\n",
+       "nginx                337\n",
+       "Microsoft-HTTPAPI    113\n",
+       "Name: count, dtype: int64"
+      ]
+     },
+     "execution_count": 150,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Count `SERVER` value counts here\n",
+    "cat.server.value_counts()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 152,
+   "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>charset</th>\n",
+       "      <th>server</th>\n",
+       "      <th>whois_country</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>iso-8859-1</td>\n",
+       "      <td>nginx</td>\n",
+       "      <td>other</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>UTF-8</td>\n",
+       "      <td>Apache</td>\n",
+       "      <td>other</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>us-ascii</td>\n",
+       "      <td>Microsoft-HTTPAPI</td>\n",
+       "      <td>other</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>ISO-8859-1</td>\n",
+       "      <td>nginx</td>\n",
+       "      <td>US</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>UTF-8</td>\n",
+       "      <td>other</td>\n",
+       "      <td>US</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      charset             server whois_country\n",
+       "0  iso-8859-1              nginx         other\n",
+       "1       UTF-8             Apache         other\n",
+       "2    us-ascii  Microsoft-HTTPAPI         other\n",
+       "3  ISO-8859-1              nginx            US\n",
+       "4       UTF-8              other            US"
+      ]
+     },
+     "execution_count": 152,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cat.head()"
    ]
   },
   {
@@ -445,11 +2973,459 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 162,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your code here\n"
+    "import pandas as pd\n",
+    "website_dummy = pd.get_dummies(cat, columns=['charset','server','whois_country'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 164,
+   "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>charset_ISO-8859</th>\n",
+       "      <th>charset_ISO-8859-1</th>\n",
+       "      <th>charset_UTF-8</th>\n",
+       "      <th>charset_iso-8859-1</th>\n",
+       "      <th>charset_us-ascii</th>\n",
+       "      <th>charset_utf-8</th>\n",
+       "      <th>charset_windows-1251</th>\n",
+       "      <th>charset_windows-1252</th>\n",
+       "      <th>server_Apache</th>\n",
+       "      <th>server_Microsoft-HTTPAPI</th>\n",
+       "      <th>server_nginx</th>\n",
+       "      <th>server_other</th>\n",
+       "      <th>whois_country_AU</th>\n",
+       "      <th>whois_country_CA</th>\n",
+       "      <th>whois_country_CN</th>\n",
+       "      <th>whois_country_ES</th>\n",
+       "      <th>whois_country_FR</th>\n",
+       "      <th>whois_country_IN</th>\n",
+       "      <th>whois_country_JP</th>\n",
+       "      <th>whois_country_PA</th>\n",
+       "      <th>whois_country_UK</th>\n",
+       "      <th>whois_country_US</th>\n",
+       "      <th>whois_country_other</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <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>1776</th>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1777</th>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1778</th>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1779</th>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1780</th>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>1781 rows × 23 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      charset_ISO-8859  charset_ISO-8859-1  charset_UTF-8  charset_iso-8859-1  \\\n",
+       "0                False               False          False                True   \n",
+       "1                False               False           True               False   \n",
+       "2                False               False          False               False   \n",
+       "3                False                True          False               False   \n",
+       "4                False               False           True               False   \n",
+       "...                ...                 ...            ...                 ...   \n",
+       "1776             False               False           True               False   \n",
+       "1777             False               False           True               False   \n",
+       "1778             False               False          False               False   \n",
+       "1779             False                True          False               False   \n",
+       "1780             False               False          False               False   \n",
+       "\n",
+       "      charset_us-ascii  charset_utf-8  charset_windows-1251  \\\n",
+       "0                False          False                 False   \n",
+       "1                False          False                 False   \n",
+       "2                 True          False                 False   \n",
+       "3                False          False                 False   \n",
+       "4                False          False                 False   \n",
+       "...                ...            ...                   ...   \n",
+       "1776             False          False                 False   \n",
+       "1777             False          False                 False   \n",
+       "1778             False           True                 False   \n",
+       "1779             False          False                 False   \n",
+       "1780             False           True                 False   \n",
+       "\n",
+       "      charset_windows-1252  server_Apache  server_Microsoft-HTTPAPI  \\\n",
+       "0                    False          False                     False   \n",
+       "1                    False           True                     False   \n",
+       "2                    False          False                      True   \n",
+       "3                    False          False                     False   \n",
+       "4                    False          False                     False   \n",
+       "...                    ...            ...                       ...   \n",
+       "1776                 False           True                     False   \n",
+       "1777                 False           True                     False   \n",
+       "1778                 False           True                     False   \n",
+       "1779                 False          False                     False   \n",
+       "1780                 False          False                     False   \n",
+       "\n",
+       "      server_nginx  server_other  whois_country_AU  whois_country_CA  \\\n",
+       "0             True         False             False             False   \n",
+       "1            False         False             False             False   \n",
+       "2            False         False             False             False   \n",
+       "3             True         False             False             False   \n",
+       "4            False          True             False             False   \n",
+       "...            ...           ...               ...               ...   \n",
+       "1776         False         False             False             False   \n",
+       "1777         False         False             False             False   \n",
+       "1778         False         False             False             False   \n",
+       "1779         False          True             False             False   \n",
+       "1780         False          True             False             False   \n",
+       "\n",
+       "      whois_country_CN  whois_country_ES  whois_country_FR  whois_country_IN  \\\n",
+       "0                False             False             False             False   \n",
+       "1                False             False             False             False   \n",
+       "2                False             False             False             False   \n",
+       "3                False             False             False             False   \n",
+       "4                False             False             False             False   \n",
+       "...                ...               ...               ...               ...   \n",
+       "1776             False              True             False             False   \n",
+       "1777             False              True             False             False   \n",
+       "1778             False             False             False             False   \n",
+       "1779             False             False             False             False   \n",
+       "1780             False             False             False             False   \n",
+       "\n",
+       "      whois_country_JP  whois_country_PA  whois_country_UK  whois_country_US  \\\n",
+       "0                False             False             False             False   \n",
+       "1                False             False             False             False   \n",
+       "2                False             False             False             False   \n",
+       "3                False             False             False              True   \n",
+       "4                False             False             False              True   \n",
+       "...                ...               ...               ...               ...   \n",
+       "1776             False             False             False             False   \n",
+       "1777             False             False             False             False   \n",
+       "1778             False             False             False              True   \n",
+       "1779             False             False             False              True   \n",
+       "1780             False             False             False              True   \n",
+       "\n",
+       "      whois_country_other  \n",
+       "0                    True  \n",
+       "1                    True  \n",
+       "2                    True  \n",
+       "3                   False  \n",
+       "4                   False  \n",
+       "...                   ...  \n",
+       "1776                False  \n",
+       "1777                False  \n",
+       "1778                False  \n",
+       "1779                False  \n",
+       "1780                False  \n",
+       "\n",
+       "[1781 rows x 23 columns]"
+      ]
+     },
+     "execution_count": 164,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "website_dummy"
    ]
   },
   {
@@ -461,11 +3437,1739 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": 166,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "RangeIndex: 1781 entries, 0 to 1780\n",
+      "Data columns (total 23 columns):\n",
+      " #   Column                    Non-Null Count  Dtype\n",
+      "---  ------                    --------------  -----\n",
+      " 0   charset_ISO-8859          1781 non-null   bool \n",
+      " 1   charset_ISO-8859-1        1781 non-null   bool \n",
+      " 2   charset_UTF-8             1781 non-null   bool \n",
+      " 3   charset_iso-8859-1        1781 non-null   bool \n",
+      " 4   charset_us-ascii          1781 non-null   bool \n",
+      " 5   charset_utf-8             1781 non-null   bool \n",
+      " 6   charset_windows-1251      1781 non-null   bool \n",
+      " 7   charset_windows-1252      1781 non-null   bool \n",
+      " 8   server_Apache             1781 non-null   bool \n",
+      " 9   server_Microsoft-HTTPAPI  1781 non-null   bool \n",
+      " 10  server_nginx              1781 non-null   bool \n",
+      " 11  server_other              1781 non-null   bool \n",
+      " 12  whois_country_AU          1781 non-null   bool \n",
+      " 13  whois_country_CA          1781 non-null   bool \n",
+      " 14  whois_country_CN          1781 non-null   bool \n",
+      " 15  whois_country_ES          1781 non-null   bool \n",
+      " 16  whois_country_FR          1781 non-null   bool \n",
+      " 17  whois_country_IN          1781 non-null   bool \n",
+      " 18  whois_country_JP          1781 non-null   bool \n",
+      " 19  whois_country_PA          1781 non-null   bool \n",
+      " 20  whois_country_UK          1781 non-null   bool \n",
+      " 21  whois_country_US          1781 non-null   bool \n",
+      " 22  whois_country_other       1781 non-null   bool \n",
+      "dtypes: bool(23)\n",
+      "memory usage: 40.1 KB\n"
+     ]
+    }
+   ],
+   "source": [
+    "website_dummy.info()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 170,
+   "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>charset_ISO-8859</th>\n",
+       "      <th>charset_ISO-8859-1</th>\n",
+       "      <th>charset_UTF-8</th>\n",
+       "      <th>charset_iso-8859-1</th>\n",
+       "      <th>charset_us-ascii</th>\n",
+       "      <th>charset_utf-8</th>\n",
+       "      <th>charset_windows-1251</th>\n",
+       "      <th>charset_windows-1252</th>\n",
+       "      <th>server_Apache</th>\n",
+       "      <th>server_Microsoft-HTTPAPI</th>\n",
+       "      <th>server_nginx</th>\n",
+       "      <th>server_other</th>\n",
+       "      <th>whois_country_AU</th>\n",
+       "      <th>whois_country_CA</th>\n",
+       "      <th>whois_country_CN</th>\n",
+       "      <th>whois_country_ES</th>\n",
+       "      <th>whois_country_FR</th>\n",
+       "      <th>whois_country_IN</th>\n",
+       "      <th>whois_country_JP</th>\n",
+       "      <th>whois_country_PA</th>\n",
+       "      <th>whois_country_UK</th>\n",
+       "      <th>whois_country_US</th>\n",
+       "      <th>whois_country_other</th>\n",
+       "      <th>type</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>0</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",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1776</th>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1777</th>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1778</th>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1779</th>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1780</th>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>1781 rows × 24 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      charset_ISO-8859  charset_ISO-8859-1  charset_UTF-8  charset_iso-8859-1  \\\n",
+       "0                False               False          False                True   \n",
+       "1                False               False           True               False   \n",
+       "2                False               False          False               False   \n",
+       "3                False                True          False               False   \n",
+       "4                False               False           True               False   \n",
+       "...                ...                 ...            ...                 ...   \n",
+       "1776             False               False           True               False   \n",
+       "1777             False               False           True               False   \n",
+       "1778             False               False          False               False   \n",
+       "1779             False                True          False               False   \n",
+       "1780             False               False          False               False   \n",
+       "\n",
+       "      charset_us-ascii  charset_utf-8  charset_windows-1251  \\\n",
+       "0                False          False                 False   \n",
+       "1                False          False                 False   \n",
+       "2                 True          False                 False   \n",
+       "3                False          False                 False   \n",
+       "4                False          False                 False   \n",
+       "...                ...            ...                   ...   \n",
+       "1776             False          False                 False   \n",
+       "1777             False          False                 False   \n",
+       "1778             False           True                 False   \n",
+       "1779             False          False                 False   \n",
+       "1780             False           True                 False   \n",
+       "\n",
+       "      charset_windows-1252  server_Apache  server_Microsoft-HTTPAPI  \\\n",
+       "0                    False          False                     False   \n",
+       "1                    False           True                     False   \n",
+       "2                    False          False                      True   \n",
+       "3                    False          False                     False   \n",
+       "4                    False          False                     False   \n",
+       "...                    ...            ...                       ...   \n",
+       "1776                 False           True                     False   \n",
+       "1777                 False           True                     False   \n",
+       "1778                 False           True                     False   \n",
+       "1779                 False          False                     False   \n",
+       "1780                 False          False                     False   \n",
+       "\n",
+       "      server_nginx  server_other  whois_country_AU  whois_country_CA  \\\n",
+       "0             True         False             False             False   \n",
+       "1            False         False             False             False   \n",
+       "2            False         False             False             False   \n",
+       "3             True         False             False             False   \n",
+       "4            False          True             False             False   \n",
+       "...            ...           ...               ...               ...   \n",
+       "1776         False         False             False             False   \n",
+       "1777         False         False             False             False   \n",
+       "1778         False         False             False             False   \n",
+       "1779         False          True             False             False   \n",
+       "1780         False          True             False             False   \n",
+       "\n",
+       "      whois_country_CN  whois_country_ES  whois_country_FR  whois_country_IN  \\\n",
+       "0                False             False             False             False   \n",
+       "1                False             False             False             False   \n",
+       "2                False             False             False             False   \n",
+       "3                False             False             False             False   \n",
+       "4                False             False             False             False   \n",
+       "...                ...               ...               ...               ...   \n",
+       "1776             False              True             False             False   \n",
+       "1777             False              True             False             False   \n",
+       "1778             False             False             False             False   \n",
+       "1779             False             False             False             False   \n",
+       "1780             False             False             False             False   \n",
+       "\n",
+       "      whois_country_JP  whois_country_PA  whois_country_UK  whois_country_US  \\\n",
+       "0                False             False             False             False   \n",
+       "1                False             False             False             False   \n",
+       "2                False             False             False             False   \n",
+       "3                False             False             False              True   \n",
+       "4                False             False             False              True   \n",
+       "...                ...               ...               ...               ...   \n",
+       "1776             False             False             False             False   \n",
+       "1777             False             False             False             False   \n",
+       "1778             False             False             False              True   \n",
+       "1779             False             False             False              True   \n",
+       "1780             False             False             False              True   \n",
+       "\n",
+       "      whois_country_other  type  \n",
+       "0                    True     1  \n",
+       "1                    True     0  \n",
+       "2                    True     0  \n",
+       "3                   False     0  \n",
+       "4                   False     0  \n",
+       "...                   ...   ...  \n",
+       "1776                False     1  \n",
+       "1777                False     1  \n",
+       "1778                False     0  \n",
+       "1779                False     0  \n",
+       "1780                False     0  \n",
+       "\n",
+       "[1781 rows x 24 columns]"
+      ]
+     },
+     "execution_count": 170,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "website_dummy['type'] = df.type\n",
+    "website_dummy"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 186,
+   "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>charset_ISO-8859</th>\n",
+       "      <th>charset_ISO-8859-1</th>\n",
+       "      <th>charset_UTF-8</th>\n",
+       "      <th>charset_iso-8859-1</th>\n",
+       "      <th>charset_us-ascii</th>\n",
+       "      <th>charset_utf-8</th>\n",
+       "      <th>charset_windows-1251</th>\n",
+       "      <th>charset_windows-1252</th>\n",
+       "      <th>server_Apache</th>\n",
+       "      <th>server_Microsoft-HTTPAPI</th>\n",
+       "      <th>server_nginx</th>\n",
+       "      <th>server_other</th>\n",
+       "      <th>whois_country_AU</th>\n",
+       "      <th>whois_country_CA</th>\n",
+       "      <th>whois_country_CN</th>\n",
+       "      <th>whois_country_ES</th>\n",
+       "      <th>whois_country_FR</th>\n",
+       "      <th>whois_country_IN</th>\n",
+       "      <th>whois_country_JP</th>\n",
+       "      <th>whois_country_PA</th>\n",
+       "      <th>whois_country_UK</th>\n",
+       "      <th>whois_country_US</th>\n",
+       "      <th>whois_country_other</th>\n",
+       "      <th>type</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
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+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>0</td>\n",
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+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
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+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
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+       "      <td>0</td>\n",
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+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
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+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
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+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
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+       "      <td>0</td>\n",
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+       "      <td>0</td>\n",
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+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
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+       "      <td>1</td>\n",
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+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
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+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1776</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1777</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1778</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1779</th>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1780</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>1781 rows × 24 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      charset_ISO-8859  charset_ISO-8859-1  charset_UTF-8  charset_iso-8859-1  \\\n",
+       "0                    0                   0              0                   1   \n",
+       "1                    0                   0              1                   0   \n",
+       "2                    0                   0              0                   0   \n",
+       "3                    0                   1              0                   0   \n",
+       "4                    0                   0              1                   0   \n",
+       "...                ...                 ...            ...                 ...   \n",
+       "1776                 0                   0              1                   0   \n",
+       "1777                 0                   0              1                   0   \n",
+       "1778                 0                   0              0                   0   \n",
+       "1779                 0                   1              0                   0   \n",
+       "1780                 0                   0              0                   0   \n",
+       "\n",
+       "      charset_us-ascii  charset_utf-8  charset_windows-1251  \\\n",
+       "0                    0              0                     0   \n",
+       "1                    0              0                     0   \n",
+       "2                    1              0                     0   \n",
+       "3                    0              0                     0   \n",
+       "4                    0              0                     0   \n",
+       "...                ...            ...                   ...   \n",
+       "1776                 0              0                     0   \n",
+       "1777                 0              0                     0   \n",
+       "1778                 0              1                     0   \n",
+       "1779                 0              0                     0   \n",
+       "1780                 0              1                     0   \n",
+       "\n",
+       "      charset_windows-1252  server_Apache  server_Microsoft-HTTPAPI  \\\n",
+       "0                        0              0                         0   \n",
+       "1                        0              1                         0   \n",
+       "2                        0              0                         1   \n",
+       "3                        0              0                         0   \n",
+       "4                        0              0                         0   \n",
+       "...                    ...            ...                       ...   \n",
+       "1776                     0              1                         0   \n",
+       "1777                     0              1                         0   \n",
+       "1778                     0              1                         0   \n",
+       "1779                     0              0                         0   \n",
+       "1780                     0              0                         0   \n",
+       "\n",
+       "      server_nginx  server_other  whois_country_AU  whois_country_CA  \\\n",
+       "0                1             0                 0                 0   \n",
+       "1                0             0                 0                 0   \n",
+       "2                0             0                 0                 0   \n",
+       "3                1             0                 0                 0   \n",
+       "4                0             1                 0                 0   \n",
+       "...            ...           ...               ...               ...   \n",
+       "1776             0             0                 0                 0   \n",
+       "1777             0             0                 0                 0   \n",
+       "1778             0             0                 0                 0   \n",
+       "1779             0             1                 0                 0   \n",
+       "1780             0             1                 0                 0   \n",
+       "\n",
+       "      whois_country_CN  whois_country_ES  whois_country_FR  whois_country_IN  \\\n",
+       "0                    0                 0                 0                 0   \n",
+       "1                    0                 0                 0                 0   \n",
+       "2                    0                 0                 0                 0   \n",
+       "3                    0                 0                 0                 0   \n",
+       "4                    0                 0                 0                 0   \n",
+       "...                ...               ...               ...               ...   \n",
+       "1776                 0                 1                 0                 0   \n",
+       "1777                 0                 1                 0                 0   \n",
+       "1778                 0                 0                 0                 0   \n",
+       "1779                 0                 0                 0                 0   \n",
+       "1780                 0                 0                 0                 0   \n",
+       "\n",
+       "      whois_country_JP  whois_country_PA  whois_country_UK  whois_country_US  \\\n",
+       "0                    0                 0                 0                 0   \n",
+       "1                    0                 0                 0                 0   \n",
+       "2                    0                 0                 0                 0   \n",
+       "3                    0                 0                 0                 1   \n",
+       "4                    0                 0                 0                 1   \n",
+       "...                ...               ...               ...               ...   \n",
+       "1776                 0                 0                 0                 0   \n",
+       "1777                 0                 0                 0                 0   \n",
+       "1778                 0                 0                 0                 1   \n",
+       "1779                 0                 0                 0                 1   \n",
+       "1780                 0                 0                 0                 1   \n",
+       "\n",
+       "      whois_country_other  type  \n",
+       "0                       1     1  \n",
+       "1                       1     0  \n",
+       "2                       1     0  \n",
+       "3                       0     0  \n",
+       "4                       0     0  \n",
+       "...                   ...   ...  \n",
+       "1776                    0     1  \n",
+       "1777                    0     1  \n",
+       "1778                    0     0  \n",
+       "1779                    0     0  \n",
+       "1780                    0     0  \n",
+       "\n",
+       "[1781 rows x 24 columns]"
+      ]
+     },
+     "execution_count": 186,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# lo convertimos todo a integer\n",
+    "website_dummy = website_dummy.astype(int)\n",
+    "website_dummy"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 196,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your code here\n"
+    "num.drop(columns='type', inplace=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 198,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "num.reset_index(inplace=True)\n",
+    "website_dummy.reset_index(inplace=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 204,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(1781, 9)"
+      ]
+     },
+     "execution_count": 204,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "num.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 206,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(1781, 25)"
+      ]
+     },
+     "execution_count": 206,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "website_dummy.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 208,
+   "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>index</th>\n",
+       "      <th>charset_ISO-8859</th>\n",
+       "      <th>charset_ISO-8859-1</th>\n",
+       "      <th>charset_UTF-8</th>\n",
+       "      <th>charset_iso-8859-1</th>\n",
+       "      <th>charset_us-ascii</th>\n",
+       "      <th>charset_utf-8</th>\n",
+       "      <th>charset_windows-1251</th>\n",
+       "      <th>charset_windows-1252</th>\n",
+       "      <th>server_Apache</th>\n",
+       "      <th>server_Microsoft-HTTPAPI</th>\n",
+       "      <th>server_nginx</th>\n",
+       "      <th>server_other</th>\n",
+       "      <th>whois_country_AU</th>\n",
+       "      <th>whois_country_CA</th>\n",
+       "      <th>whois_country_CN</th>\n",
+       "      <th>whois_country_ES</th>\n",
+       "      <th>whois_country_FR</th>\n",
+       "      <th>whois_country_IN</th>\n",
+       "      <th>whois_country_JP</th>\n",
+       "      <th>whois_country_PA</th>\n",
+       "      <th>whois_country_UK</th>\n",
+       "      <th>whois_country_US</th>\n",
+       "      <th>whois_country_other</th>\n",
+       "      <th>type</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   index  charset_ISO-8859  charset_ISO-8859-1  charset_UTF-8  \\\n",
+       "0      0                 0                   0              0   \n",
+       "\n",
+       "   charset_iso-8859-1  charset_us-ascii  charset_utf-8  charset_windows-1251  \\\n",
+       "0                   1                 0              0                     0   \n",
+       "\n",
+       "   charset_windows-1252  server_Apache  server_Microsoft-HTTPAPI  \\\n",
+       "0                     0              0                         0   \n",
+       "\n",
+       "   server_nginx  server_other  whois_country_AU  whois_country_CA  \\\n",
+       "0             1             0                 0                 0   \n",
+       "\n",
+       "   whois_country_CN  whois_country_ES  whois_country_FR  whois_country_IN  \\\n",
+       "0                 0                 0                 0                 0   \n",
+       "\n",
+       "   whois_country_JP  whois_country_PA  whois_country_UK  whois_country_US  \\\n",
+       "0                 0                 0                 0                 0   \n",
+       "\n",
+       "   whois_country_other  type  \n",
+       "0                    1     1  "
+      ]
+     },
+     "execution_count": 208,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "website_dummy.head(1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 216,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": [
+    "# Juntamos nuestro dataframe con las columnas categoricas codificadas con los dummies con el dataframe de las columnas numericas\n",
+    "df_final = num.merge(website_dummy, on='index', how='inner')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 222,
+   "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>url_length</th>\n",
+       "      <th>number_special_characters</th>\n",
+       "      <th>dist_remote_tcp_port</th>\n",
+       "      <th>remote_ips</th>\n",
+       "      <th>remote_app_packets</th>\n",
+       "      <th>source_app_bytes</th>\n",
+       "      <th>remote_app_bytes</th>\n",
+       "      <th>dns_query_times</th>\n",
+       "      <th>charset_ISO-8859</th>\n",
+       "      <th>charset_ISO-8859-1</th>\n",
+       "      <th>charset_UTF-8</th>\n",
+       "      <th>charset_iso-8859-1</th>\n",
+       "      <th>charset_us-ascii</th>\n",
+       "      <th>charset_utf-8</th>\n",
+       "      <th>charset_windows-1251</th>\n",
+       "      <th>charset_windows-1252</th>\n",
+       "      <th>server_Apache</th>\n",
+       "      <th>server_Microsoft-HTTPAPI</th>\n",
+       "      <th>server_nginx</th>\n",
+       "      <th>server_other</th>\n",
+       "      <th>whois_country_AU</th>\n",
+       "      <th>whois_country_CA</th>\n",
+       "      <th>whois_country_CN</th>\n",
+       "      <th>whois_country_ES</th>\n",
+       "      <th>whois_country_FR</th>\n",
+       "      <th>whois_country_IN</th>\n",
+       "      <th>whois_country_JP</th>\n",
+       "      <th>whois_country_PA</th>\n",
+       "      <th>whois_country_UK</th>\n",
+       "      <th>whois_country_US</th>\n",
+       "      <th>whois_country_other</th>\n",
+       "      <th>type</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>16</td>\n",
+       "      <td>7</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>10</td>\n",
+       "      <td>1153</td>\n",
+       "      <td>832</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>16</td>\n",
+       "      <td>6</td>\n",
+       "      <td>7</td>\n",
+       "      <td>4</td>\n",
+       "      <td>19</td>\n",
+       "      <td>1265</td>\n",
+       "      <td>1230</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>16</td>\n",
+       "      <td>6</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>17</td>\n",
+       "      <td>6</td>\n",
+       "      <td>22</td>\n",
+       "      <td>3</td>\n",
+       "      <td>37</td>\n",
+       "      <td>18784</td>\n",
+       "      <td>4380</td>\n",
+       "      <td>8.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>17</td>\n",
+       "      <td>6</td>\n",
+       "      <td>2</td>\n",
+       "      <td>5</td>\n",
+       "      <td>62</td>\n",
+       "      <td>129889</td>\n",
+       "      <td>4586</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</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",
+       "      <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>1776</th>\n",
+       "      <td>194</td>\n",
+       "      <td>16</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>186</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1777</th>\n",
+       "      <td>198</td>\n",
+       "      <td>17</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>124</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1778</th>\n",
+       "      <td>201</td>\n",
+       "      <td>34</td>\n",
+       "      <td>2</td>\n",
+       "      <td>6</td>\n",
+       "      <td>89</td>\n",
+       "      <td>132181</td>\n",
+       "      <td>6945</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1779</th>\n",
+       "      <td>234</td>\n",
+       "      <td>34</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1780</th>\n",
+       "      <td>249</td>\n",
+       "      <td>40</td>\n",
+       "      <td>6</td>\n",
+       "      <td>11</td>\n",
+       "      <td>28</td>\n",
+       "      <td>3039</td>\n",
+       "      <td>2776</td>\n",
+       "      <td>6.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>1781 rows × 32 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      url_length  number_special_characters  dist_remote_tcp_port  remote_ips  \\\n",
+       "0             16                          7                     0           2   \n",
+       "1             16                          6                     7           4   \n",
+       "2             16                          6                     0           0   \n",
+       "3             17                          6                    22           3   \n",
+       "4             17                          6                     2           5   \n",
+       "...          ...                        ...                   ...         ...   \n",
+       "1776         194                         16                     0           0   \n",
+       "1777         198                         17                     0           0   \n",
+       "1778         201                         34                     2           6   \n",
+       "1779         234                         34                     0           0   \n",
+       "1780         249                         40                     6          11   \n",
+       "\n",
+       "      remote_app_packets  source_app_bytes  remote_app_bytes  dns_query_times  \\\n",
+       "0                     10              1153               832              2.0   \n",
+       "1                     19              1265              1230              0.0   \n",
+       "2                      0                 0                 0              0.0   \n",
+       "3                     37             18784              4380              8.0   \n",
+       "4                     62            129889              4586              4.0   \n",
+       "...                  ...               ...               ...              ...   \n",
+       "1776                   3               186                 0              0.0   \n",
+       "1777                   2               124                 0              0.0   \n",
+       "1778                  89            132181              6945              4.0   \n",
+       "1779                   0                 0                 0              0.0   \n",
+       "1780                  28              3039              2776              6.0   \n",
+       "\n",
+       "      charset_ISO-8859  charset_ISO-8859-1  charset_UTF-8  charset_iso-8859-1  \\\n",
+       "0                    0                   0              0                   1   \n",
+       "1                    0                   0              1                   0   \n",
+       "2                    0                   0              0                   0   \n",
+       "3                    0                   1              0                   0   \n",
+       "4                    0                   0              1                   0   \n",
+       "...                ...                 ...            ...                 ...   \n",
+       "1776                 0                   0              1                   0   \n",
+       "1777                 0                   0              1                   0   \n",
+       "1778                 0                   0              0                   0   \n",
+       "1779                 0                   1              0                   0   \n",
+       "1780                 0                   0              0                   0   \n",
+       "\n",
+       "      charset_us-ascii  charset_utf-8  charset_windows-1251  \\\n",
+       "0                    0              0                     0   \n",
+       "1                    0              0                     0   \n",
+       "2                    1              0                     0   \n",
+       "3                    0              0                     0   \n",
+       "4                    0              0                     0   \n",
+       "...                ...            ...                   ...   \n",
+       "1776                 0              0                     0   \n",
+       "1777                 0              0                     0   \n",
+       "1778                 0              1                     0   \n",
+       "1779                 0              0                     0   \n",
+       "1780                 0              1                     0   \n",
+       "\n",
+       "      charset_windows-1252  server_Apache  server_Microsoft-HTTPAPI  \\\n",
+       "0                        0              0                         0   \n",
+       "1                        0              1                         0   \n",
+       "2                        0              0                         1   \n",
+       "3                        0              0                         0   \n",
+       "4                        0              0                         0   \n",
+       "...                    ...            ...                       ...   \n",
+       "1776                     0              1                         0   \n",
+       "1777                     0              1                         0   \n",
+       "1778                     0              1                         0   \n",
+       "1779                     0              0                         0   \n",
+       "1780                     0              0                         0   \n",
+       "\n",
+       "      server_nginx  server_other  whois_country_AU  whois_country_CA  \\\n",
+       "0                1             0                 0                 0   \n",
+       "1                0             0                 0                 0   \n",
+       "2                0             0                 0                 0   \n",
+       "3                1             0                 0                 0   \n",
+       "4                0             1                 0                 0   \n",
+       "...            ...           ...               ...               ...   \n",
+       "1776             0             0                 0                 0   \n",
+       "1777             0             0                 0                 0   \n",
+       "1778             0             0                 0                 0   \n",
+       "1779             0             1                 0                 0   \n",
+       "1780             0             1                 0                 0   \n",
+       "\n",
+       "      whois_country_CN  whois_country_ES  whois_country_FR  whois_country_IN  \\\n",
+       "0                    0                 0                 0                 0   \n",
+       "1                    0                 0                 0                 0   \n",
+       "2                    0                 0                 0                 0   \n",
+       "3                    0                 0                 0                 0   \n",
+       "4                    0                 0                 0                 0   \n",
+       "...                ...               ...               ...               ...   \n",
+       "1776                 0                 1                 0                 0   \n",
+       "1777                 0                 1                 0                 0   \n",
+       "1778                 0                 0                 0                 0   \n",
+       "1779                 0                 0                 0                 0   \n",
+       "1780                 0                 0                 0                 0   \n",
+       "\n",
+       "      whois_country_JP  whois_country_PA  whois_country_UK  whois_country_US  \\\n",
+       "0                    0                 0                 0                 0   \n",
+       "1                    0                 0                 0                 0   \n",
+       "2                    0                 0                 0                 0   \n",
+       "3                    0                 0                 0                 1   \n",
+       "4                    0                 0                 0                 1   \n",
+       "...                ...               ...               ...               ...   \n",
+       "1776                 0                 0                 0                 0   \n",
+       "1777                 0                 0                 0                 0   \n",
+       "1778                 0                 0                 0                 1   \n",
+       "1779                 0                 0                 0                 1   \n",
+       "1780                 0                 0                 0                 1   \n",
+       "\n",
+       "      whois_country_other  type  \n",
+       "0                       1     1  \n",
+       "1                       1     0  \n",
+       "2                       1     0  \n",
+       "3                       0     0  \n",
+       "4                       0     0  \n",
+       "...                   ...   ...  \n",
+       "1776                    0     1  \n",
+       "1777                    0     1  \n",
+       "1778                    0     0  \n",
+       "1779                    0     0  \n",
+       "1780                    0     0  \n",
+       "\n",
+       "[1781 rows x 32 columns]"
+      ]
+     },
+     "execution_count": 222,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_final.drop(columns='index')"
    ]
   },
   {
@@ -479,13 +5183,656 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 230,
    "metadata": {},
    "outputs": [],
    "source": [
     "from sklearn.model_selection import train_test_split\n",
     "\n",
-    "# Your code here:\n"
+    "y = df_final['type']\n",
+    "X = df_final.drop(columns=['type'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 236,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0       1\n",
+       "1       0\n",
+       "2       0\n",
+       "3       0\n",
+       "4       0\n",
+       "       ..\n",
+       "1776    1\n",
+       "1777    1\n",
+       "1778    0\n",
+       "1779    0\n",
+       "1780    0\n",
+       "Name: type, Length: 1781, dtype: int64"
+      ]
+     },
+     "execution_count": 236,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "y"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 238,
+   "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>index</th>\n",
+       "      <th>url_length</th>\n",
+       "      <th>number_special_characters</th>\n",
+       "      <th>dist_remote_tcp_port</th>\n",
+       "      <th>remote_ips</th>\n",
+       "      <th>remote_app_packets</th>\n",
+       "      <th>source_app_bytes</th>\n",
+       "      <th>remote_app_bytes</th>\n",
+       "      <th>dns_query_times</th>\n",
+       "      <th>charset_ISO-8859</th>\n",
+       "      <th>charset_ISO-8859-1</th>\n",
+       "      <th>charset_UTF-8</th>\n",
+       "      <th>charset_iso-8859-1</th>\n",
+       "      <th>charset_us-ascii</th>\n",
+       "      <th>charset_utf-8</th>\n",
+       "      <th>charset_windows-1251</th>\n",
+       "      <th>charset_windows-1252</th>\n",
+       "      <th>server_Apache</th>\n",
+       "      <th>server_Microsoft-HTTPAPI</th>\n",
+       "      <th>server_nginx</th>\n",
+       "      <th>server_other</th>\n",
+       "      <th>whois_country_AU</th>\n",
+       "      <th>whois_country_CA</th>\n",
+       "      <th>whois_country_CN</th>\n",
+       "      <th>whois_country_ES</th>\n",
+       "      <th>whois_country_FR</th>\n",
+       "      <th>whois_country_IN</th>\n",
+       "      <th>whois_country_JP</th>\n",
+       "      <th>whois_country_PA</th>\n",
+       "      <th>whois_country_UK</th>\n",
+       "      <th>whois_country_US</th>\n",
+       "      <th>whois_country_other</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0</td>\n",
+       "      <td>16</td>\n",
+       "      <td>7</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>10</td>\n",
+       "      <td>1153</td>\n",
+       "      <td>832</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1</td>\n",
+       "      <td>16</td>\n",
+       "      <td>6</td>\n",
+       "      <td>7</td>\n",
+       "      <td>4</td>\n",
+       "      <td>19</td>\n",
+       "      <td>1265</td>\n",
+       "      <td>1230</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2</td>\n",
+       "      <td>16</td>\n",
+       "      <td>6</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>3</td>\n",
+       "      <td>17</td>\n",
+       "      <td>6</td>\n",
+       "      <td>22</td>\n",
+       "      <td>3</td>\n",
+       "      <td>37</td>\n",
+       "      <td>18784</td>\n",
+       "      <td>4380</td>\n",
+       "      <td>8.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>4</td>\n",
+       "      <td>17</td>\n",
+       "      <td>6</td>\n",
+       "      <td>2</td>\n",
+       "      <td>5</td>\n",
+       "      <td>62</td>\n",
+       "      <td>129889</td>\n",
+       "      <td>4586</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</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",
+       "      <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>1776</th>\n",
+       "      <td>1776</td>\n",
+       "      <td>194</td>\n",
+       "      <td>16</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>186</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1777</th>\n",
+       "      <td>1777</td>\n",
+       "      <td>198</td>\n",
+       "      <td>17</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>124</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1778</th>\n",
+       "      <td>1778</td>\n",
+       "      <td>201</td>\n",
+       "      <td>34</td>\n",
+       "      <td>2</td>\n",
+       "      <td>6</td>\n",
+       "      <td>89</td>\n",
+       "      <td>132181</td>\n",
+       "      <td>6945</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1779</th>\n",
+       "      <td>1779</td>\n",
+       "      <td>234</td>\n",
+       "      <td>34</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1780</th>\n",
+       "      <td>1780</td>\n",
+       "      <td>249</td>\n",
+       "      <td>40</td>\n",
+       "      <td>6</td>\n",
+       "      <td>11</td>\n",
+       "      <td>28</td>\n",
+       "      <td>3039</td>\n",
+       "      <td>2776</td>\n",
+       "      <td>6.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>1781 rows × 32 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      index  url_length  number_special_characters  dist_remote_tcp_port  \\\n",
+       "0         0          16                          7                     0   \n",
+       "1         1          16                          6                     7   \n",
+       "2         2          16                          6                     0   \n",
+       "3         3          17                          6                    22   \n",
+       "4         4          17                          6                     2   \n",
+       "...     ...         ...                        ...                   ...   \n",
+       "1776   1776         194                         16                     0   \n",
+       "1777   1777         198                         17                     0   \n",
+       "1778   1778         201                         34                     2   \n",
+       "1779   1779         234                         34                     0   \n",
+       "1780   1780         249                         40                     6   \n",
+       "\n",
+       "      remote_ips  remote_app_packets  source_app_bytes  remote_app_bytes  \\\n",
+       "0              2                  10              1153               832   \n",
+       "1              4                  19              1265              1230   \n",
+       "2              0                   0                 0                 0   \n",
+       "3              3                  37             18784              4380   \n",
+       "4              5                  62            129889              4586   \n",
+       "...          ...                 ...               ...               ...   \n",
+       "1776           0                   3               186                 0   \n",
+       "1777           0                   2               124                 0   \n",
+       "1778           6                  89            132181              6945   \n",
+       "1779           0                   0                 0                 0   \n",
+       "1780          11                  28              3039              2776   \n",
+       "\n",
+       "      dns_query_times  charset_ISO-8859  charset_ISO-8859-1  charset_UTF-8  \\\n",
+       "0                 2.0                 0                   0              0   \n",
+       "1                 0.0                 0                   0              1   \n",
+       "2                 0.0                 0                   0              0   \n",
+       "3                 8.0                 0                   1              0   \n",
+       "4                 4.0                 0                   0              1   \n",
+       "...               ...               ...                 ...            ...   \n",
+       "1776              0.0                 0                   0              1   \n",
+       "1777              0.0                 0                   0              1   \n",
+       "1778              4.0                 0                   0              0   \n",
+       "1779              0.0                 0                   1              0   \n",
+       "1780              6.0                 0                   0              0   \n",
+       "\n",
+       "      charset_iso-8859-1  charset_us-ascii  charset_utf-8  \\\n",
+       "0                      1                 0              0   \n",
+       "1                      0                 0              0   \n",
+       "2                      0                 1              0   \n",
+       "3                      0                 0              0   \n",
+       "4                      0                 0              0   \n",
+       "...                  ...               ...            ...   \n",
+       "1776                   0                 0              0   \n",
+       "1777                   0                 0              0   \n",
+       "1778                   0                 0              1   \n",
+       "1779                   0                 0              0   \n",
+       "1780                   0                 0              1   \n",
+       "\n",
+       "      charset_windows-1251  charset_windows-1252  server_Apache  \\\n",
+       "0                        0                     0              0   \n",
+       "1                        0                     0              1   \n",
+       "2                        0                     0              0   \n",
+       "3                        0                     0              0   \n",
+       "4                        0                     0              0   \n",
+       "...                    ...                   ...            ...   \n",
+       "1776                     0                     0              1   \n",
+       "1777                     0                     0              1   \n",
+       "1778                     0                     0              1   \n",
+       "1779                     0                     0              0   \n",
+       "1780                     0                     0              0   \n",
+       "\n",
+       "      server_Microsoft-HTTPAPI  server_nginx  server_other  whois_country_AU  \\\n",
+       "0                            0             1             0                 0   \n",
+       "1                            0             0             0                 0   \n",
+       "2                            1             0             0                 0   \n",
+       "3                            0             1             0                 0   \n",
+       "4                            0             0             1                 0   \n",
+       "...                        ...           ...           ...               ...   \n",
+       "1776                         0             0             0                 0   \n",
+       "1777                         0             0             0                 0   \n",
+       "1778                         0             0             0                 0   \n",
+       "1779                         0             0             1                 0   \n",
+       "1780                         0             0             1                 0   \n",
+       "\n",
+       "      whois_country_CA  whois_country_CN  whois_country_ES  whois_country_FR  \\\n",
+       "0                    0                 0                 0                 0   \n",
+       "1                    0                 0                 0                 0   \n",
+       "2                    0                 0                 0                 0   \n",
+       "3                    0                 0                 0                 0   \n",
+       "4                    0                 0                 0                 0   \n",
+       "...                ...               ...               ...               ...   \n",
+       "1776                 0                 0                 1                 0   \n",
+       "1777                 0                 0                 1                 0   \n",
+       "1778                 0                 0                 0                 0   \n",
+       "1779                 0                 0                 0                 0   \n",
+       "1780                 0                 0                 0                 0   \n",
+       "\n",
+       "      whois_country_IN  whois_country_JP  whois_country_PA  whois_country_UK  \\\n",
+       "0                    0                 0                 0                 0   \n",
+       "1                    0                 0                 0                 0   \n",
+       "2                    0                 0                 0                 0   \n",
+       "3                    0                 0                 0                 0   \n",
+       "4                    0                 0                 0                 0   \n",
+       "...                ...               ...               ...               ...   \n",
+       "1776                 0                 0                 0                 0   \n",
+       "1777                 0                 0                 0                 0   \n",
+       "1778                 0                 0                 0                 0   \n",
+       "1779                 0                 0                 0                 0   \n",
+       "1780                 0                 0                 0                 0   \n",
+       "\n",
+       "      whois_country_US  whois_country_other  \n",
+       "0                    0                    1  \n",
+       "1                    0                    1  \n",
+       "2                    0                    1  \n",
+       "3                    1                    0  \n",
+       "4                    1                    0  \n",
+       "...                ...                  ...  \n",
+       "1776                 0                    0  \n",
+       "1777                 0                    0  \n",
+       "1778                 1                    0  \n",
+       "1779                 1                    0  \n",
+       "1780                 1                    0  \n",
+       "\n",
+       "[1781 rows x 32 columns]"
+      ]
+     },
+     "execution_count": 238,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "X"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 232,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 234,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "100% of our data: 1781.\n",
+      "80% for training data: 1424.\n",
+      "20% for test data: 357.\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(f'100% of our data: {len(df)}.')\n",
+    "print(f'80% for training data: {len(X_train)}.')\n",
+    "print(f'20% for test data: {len(X_test)}.')"
    ]
   },
   {
@@ -499,12 +5846,430 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 282,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<style>#sk-container-id-2 {\n",
+       "  /* Definition of color scheme common for light and dark mode */\n",
+       "  --sklearn-color-text: black;\n",
+       "  --sklearn-color-line: gray;\n",
+       "  /* Definition of color scheme for unfitted estimators */\n",
+       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
+       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
+       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
+       "  --sklearn-color-unfitted-level-3: chocolate;\n",
+       "  /* Definition of color scheme for fitted estimators */\n",
+       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
+       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
+       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
+       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
+       "\n",
+       "  /* Specific color for light theme */\n",
+       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
+       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
+       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
+       "  --sklearn-color-icon: #696969;\n",
+       "\n",
+       "  @media (prefers-color-scheme: dark) {\n",
+       "    /* Redefinition of color scheme for dark theme */\n",
+       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
+       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
+       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
+       "    --sklearn-color-icon: #878787;\n",
+       "  }\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 pre {\n",
+       "  padding: 0;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 input.sk-hidden--visually {\n",
+       "  border: 0;\n",
+       "  clip: rect(1px 1px 1px 1px);\n",
+       "  clip: rect(1px, 1px, 1px, 1px);\n",
+       "  height: 1px;\n",
+       "  margin: -1px;\n",
+       "  overflow: hidden;\n",
+       "  padding: 0;\n",
+       "  position: absolute;\n",
+       "  width: 1px;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-dashed-wrapped {\n",
+       "  border: 1px dashed var(--sklearn-color-line);\n",
+       "  margin: 0 0.4em 0.5em 0.4em;\n",
+       "  box-sizing: border-box;\n",
+       "  padding-bottom: 0.4em;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-container {\n",
+       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
+       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
+       "     so we also need the `!important` here to be able to override the\n",
+       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
+       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
+       "  display: inline-block !important;\n",
+       "  position: relative;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-text-repr-fallback {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       "div.sk-parallel-item,\n",
+       "div.sk-serial,\n",
+       "div.sk-item {\n",
+       "  /* draw centered vertical line to link estimators */\n",
+       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
+       "  background-size: 2px 100%;\n",
+       "  background-repeat: no-repeat;\n",
+       "  background-position: center center;\n",
+       "}\n",
+       "\n",
+       "/* Parallel-specific style estimator block */\n",
+       "\n",
+       "#sk-container-id-2 div.sk-parallel-item::after {\n",
+       "  content: \"\";\n",
+       "  width: 100%;\n",
+       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
+       "  flex-grow: 1;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-parallel {\n",
+       "  display: flex;\n",
+       "  align-items: stretch;\n",
+       "  justify-content: center;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  position: relative;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-parallel-item {\n",
+       "  display: flex;\n",
+       "  flex-direction: column;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-parallel-item:first-child::after {\n",
+       "  align-self: flex-end;\n",
+       "  width: 50%;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-parallel-item:last-child::after {\n",
+       "  align-self: flex-start;\n",
+       "  width: 50%;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-parallel-item:only-child::after {\n",
+       "  width: 0;\n",
+       "}\n",
+       "\n",
+       "/* Serial-specific style estimator block */\n",
+       "\n",
+       "#sk-container-id-2 div.sk-serial {\n",
+       "  display: flex;\n",
+       "  flex-direction: column;\n",
+       "  align-items: center;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  padding-right: 1em;\n",
+       "  padding-left: 1em;\n",
+       "}\n",
+       "\n",
+       "\n",
+       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
+       "clickable and can be expanded/collapsed.\n",
+       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
+       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
+       "*/\n",
+       "\n",
+       "/* Pipeline and ColumnTransformer style (default) */\n",
+       "\n",
+       "#sk-container-id-2 div.sk-toggleable {\n",
+       "  /* Default theme specific background. It is overwritten whether we have a\n",
+       "  specific estimator or a Pipeline/ColumnTransformer */\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "}\n",
+       "\n",
+       "/* Toggleable label */\n",
+       "#sk-container-id-2 label.sk-toggleable__label {\n",
+       "  cursor: pointer;\n",
+       "  display: block;\n",
+       "  width: 100%;\n",
+       "  margin-bottom: 0;\n",
+       "  padding: 0.5em;\n",
+       "  box-sizing: border-box;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 label.sk-toggleable__label-arrow:before {\n",
+       "  /* Arrow on the left of the label */\n",
+       "  content: \"▸\";\n",
+       "  float: left;\n",
+       "  margin-right: 0.25em;\n",
+       "  color: var(--sklearn-color-icon);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 label.sk-toggleable__label-arrow:hover:before {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "}\n",
+       "\n",
+       "/* Toggleable content - dropdown */\n",
+       "\n",
+       "#sk-container-id-2 div.sk-toggleable__content {\n",
+       "  max-height: 0;\n",
+       "  max-width: 0;\n",
+       "  overflow: hidden;\n",
+       "  text-align: left;\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-toggleable__content.fitted {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-toggleable__content pre {\n",
+       "  margin: 0.2em;\n",
+       "  border-radius: 0.25em;\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-toggleable__content.fitted pre {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
+       "  /* Expand drop-down */\n",
+       "  max-height: 200px;\n",
+       "  max-width: 100%;\n",
+       "  overflow: auto;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
+       "  content: \"▾\";\n",
+       "}\n",
+       "\n",
+       "/* Pipeline/ColumnTransformer-specific style */\n",
+       "\n",
+       "#sk-container-id-2 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Estimator-specific style */\n",
+       "\n",
+       "/* Colorize estimator box */\n",
+       "#sk-container-id-2 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-label label.sk-toggleable__label,\n",
+       "#sk-container-id-2 div.sk-label label {\n",
+       "  /* The background is the default theme color */\n",
+       "  color: var(--sklearn-color-text-on-default-background);\n",
+       "}\n",
+       "\n",
+       "/* On hover, darken the color of the background */\n",
+       "#sk-container-id-2 div.sk-label:hover label.sk-toggleable__label {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Label box, darken color on hover, fitted */\n",
+       "#sk-container-id-2 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Estimator label */\n",
+       "\n",
+       "#sk-container-id-2 div.sk-label label {\n",
+       "  font-family: monospace;\n",
+       "  font-weight: bold;\n",
+       "  display: inline-block;\n",
+       "  line-height: 1.2em;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-label-container {\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       "/* Estimator-specific */\n",
+       "#sk-container-id-2 div.sk-estimator {\n",
+       "  font-family: monospace;\n",
+       "  border: 1px dotted var(--sklearn-color-border-box);\n",
+       "  border-radius: 0.25em;\n",
+       "  box-sizing: border-box;\n",
+       "  margin-bottom: 0.5em;\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-estimator.fitted {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "/* on hover */\n",
+       "#sk-container-id-2 div.sk-estimator:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-estimator.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
+       "\n",
+       "/* Common style for \"i\" and \"?\" */\n",
+       "\n",
+       ".sk-estimator-doc-link,\n",
+       "a:link.sk-estimator-doc-link,\n",
+       "a:visited.sk-estimator-doc-link {\n",
+       "  float: right;\n",
+       "  font-size: smaller;\n",
+       "  line-height: 1em;\n",
+       "  font-family: monospace;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  border-radius: 1em;\n",
+       "  height: 1em;\n",
+       "  width: 1em;\n",
+       "  text-decoration: none !important;\n",
+       "  margin-left: 1ex;\n",
+       "  /* unfitted */\n",
+       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-unfitted-level-1);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link.fitted,\n",
+       "a:link.sk-estimator-doc-link.fitted,\n",
+       "a:visited.sk-estimator-doc-link.fitted {\n",
+       "  /* fitted */\n",
+       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-fitted-level-1);\n",
+       "}\n",
+       "\n",
+       "/* On hover */\n",
+       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
+       ".sk-estimator-doc-link:hover,\n",
+       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
+       ".sk-estimator-doc-link:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
+       ".sk-estimator-doc-link.fitted:hover,\n",
+       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
+       ".sk-estimator-doc-link.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "/* Span, style for the box shown on hovering the info icon */\n",
+       ".sk-estimator-doc-link span {\n",
+       "  display: none;\n",
+       "  z-index: 9999;\n",
+       "  position: relative;\n",
+       "  font-weight: normal;\n",
+       "  right: .2ex;\n",
+       "  padding: .5ex;\n",
+       "  margin: .5ex;\n",
+       "  width: min-content;\n",
+       "  min-width: 20ex;\n",
+       "  max-width: 50ex;\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  box-shadow: 2pt 2pt 4pt #999;\n",
+       "  /* unfitted */\n",
+       "  background: var(--sklearn-color-unfitted-level-0);\n",
+       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link.fitted span {\n",
+       "  /* fitted */\n",
+       "  background: var(--sklearn-color-fitted-level-0);\n",
+       "  border: var(--sklearn-color-fitted-level-3);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link:hover span {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
+       "\n",
+       "#sk-container-id-2 a.estimator_doc_link {\n",
+       "  float: right;\n",
+       "  font-size: 1rem;\n",
+       "  line-height: 1em;\n",
+       "  font-family: monospace;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  border-radius: 1rem;\n",
+       "  height: 1rem;\n",
+       "  width: 1rem;\n",
+       "  text-decoration: none;\n",
+       "  /* unfitted */\n",
+       "  color: var(--sklearn-color-unfitted-level-1);\n",
+       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 a.estimator_doc_link.fitted {\n",
+       "  /* fitted */\n",
+       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-fitted-level-1);\n",
+       "}\n",
+       "\n",
+       "/* On hover */\n",
+       "#sk-container-id-2 a.estimator_doc_link:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 a.estimator_doc_link.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-3);\n",
+       "}\n",
+       "</style><div id=\"sk-container-id-2\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>LogisticRegression()</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-2\" type=\"checkbox\" checked><label for=\"sk-estimator-id-2\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;LogisticRegression<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.linear_model.LogisticRegression.html\">?<span>Documentation for LogisticRegression</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>LogisticRegression()</pre></div> </div></div></div></div>"
+      ],
+      "text/plain": [
+       "LogisticRegression()"
+      ]
+     },
+     "execution_count": 282,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# Your code here:\n",
-    "\n"
+    "model = LogisticRegression()\n",
+    "model.fit(X_train, y_train)"
    ]
   },
   {
@@ -516,12 +6281,50 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": 284,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "20% for test prediction data: 357.\n",
+      "              precision    recall  f1-score   support\n",
+      "\n",
+      "           0       0.90      0.98      0.94       306\n",
+      "           1       0.76      0.37      0.50        51\n",
+      "\n",
+      "    accuracy                           0.89       357\n",
+      "   macro avg       0.83      0.68      0.72       357\n",
+      "weighted avg       0.88      0.89      0.88       357\n",
+      "\n"
+     ]
+    }
+   ],
    "source": [
     "# Your code here:\n",
-    "\n"
+    "predictions = model.predict(X_test)\n",
+    "print(f'20% for test prediction data: {len(predictions)}.')\n",
+    "print(classification_report(y_test, predictions))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 286,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Test data accuracy:  0.8935574229691877\n",
+      "Train data accuracy:  0.8890449438202247\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(\"Test data accuracy: \",model.score(X_test,y_test))\n",
+    "print(\"Train data accuracy: \", model.score(X_train, y_train))"
    ]
   },
   {
@@ -533,12 +6336,36 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": 244,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 800x600 with 0 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
-    "# Your code here:\n",
-    "\n"
+    "cm = confusion_matrix(y_test, predictions)\n",
+    "disp = ConfusionMatrixDisplay(confusion_matrix=cm)\n",
+    "plt.figure(figsize=(8, 6))\n",
+    "disp.plot(cmap='Oranges')  \n",
+    "plt.grid(True)\n",
+    "plt.show()"
    ]
   },
   {
@@ -554,8 +6381,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your conclusions here:\n",
-    "\n"
+    "# Podemos ver que tiene una precisión de 0.9 para predecir las páginas que no son fraudulentas (0), mientras que únicamente tiene\n",
+    "# una precisión del 0.76 para las páginas que si lo son (1)"
    ]
   },
   {
@@ -569,12 +6396,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": 260,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your code here:\n",
-    "\n"
+    "from sklearn.neighbors import KNeighborsClassifier\n",
+    "\n",
+    "model = KNeighborsClassifier(n_neighbors=3)\n",
+    "model = model.fit(X_train, y_train)"
    ]
   },
   {
@@ -586,12 +6415,81 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": 262,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "              precision    recall  f1-score   support\n",
+      "\n",
+      "           0       0.94      0.99      0.96       306\n",
+      "           1       0.91      0.63      0.74        51\n",
+      "\n",
+      "    accuracy                           0.94       357\n",
+      "   macro avg       0.93      0.81      0.85       357\n",
+      "weighted avg       0.94      0.94      0.93       357\n",
+      "\n"
+     ]
+    }
+   ],
    "source": [
-    "# Your code here:\n",
-    "\n"
+    "predictions = model.predict(X_test)\n",
+    "print(classification_report(y_test, predictions))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 264,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Test data accuracy:  0.938375350140056\n",
+      "Train data accuracy:  0.9550561797752809\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(\"Test data accuracy: \",model.score(X_test,y_test))\n",
+    "print(\"Train data accuracy: \", model.score(X_train, y_train))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 266,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 800x600 with 0 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "cm = confusion_matrix(y_test, predictions)\n",
+    "disp = ConfusionMatrixDisplay(confusion_matrix=cm)\n",
+    "plt.figure(figsize=(8, 6))\n",
+    "disp.plot(cmap='Oranges')  \n",
+    "plt.grid(True)\n",
+    "plt.show()"
    ]
   },
   {
@@ -605,12 +6503,83 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
+   "execution_count": 270,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "              precision    recall  f1-score   support\n",
+      "\n",
+      "           0       0.94      0.99      0.96       306\n",
+      "           1       0.89      0.61      0.72        51\n",
+      "\n",
+      "    accuracy                           0.93       357\n",
+      "   macro avg       0.91      0.80      0.84       357\n",
+      "weighted avg       0.93      0.93      0.93       357\n",
+      "\n"
+     ]
+    }
+   ],
    "source": [
-    "# Your code here:\n",
-    "\n"
+    "model = KNeighborsClassifier(n_neighbors=5)\n",
+    "model = model.fit(X_train, y_train)\n",
+    "predictions = model.predict(X_test)\n",
+    "print(classification_report(y_test, predictions))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 272,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Test data accuracy:  0.9327731092436975\n",
+      "Train data accuracy:  0.9459269662921348\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(\"Test data accuracy: \",model.score(X_test,y_test))\n",
+    "print(\"Train data accuracy: \", model.score(X_train, y_train))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 274,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 800x600 with 0 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "cm = confusion_matrix(y_test, predictions)\n",
+    "disp = ConfusionMatrixDisplay(confusion_matrix=cm)\n",
+    "plt.figure(figsize=(8, 6))\n",
+    "disp.plot(cmap='Oranges')  \n",
+    "plt.grid(True)\n",
+    "plt.show()"
    ]
   },
   {
@@ -626,8 +6595,85 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your conclusions here:\n",
-    "\n"
+    "# Train-data accuracy con k=3: 0.95\n",
+    "# Train-data accuracy con k=5: 0.94\n",
+    "# La confusión matrix empeora un poco al incrementar la k a 5\n",
+    "# La accuracy score también empeora un poco al incrementar esta misma k"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# La confusion matrix muestra que hay muchos true negatives bien predichos, mientras que hay pocos true positives bien predichos. \n",
+    "# Esto se debe a que hay mucho inbalance en los datos con los que hemos alimentado el modelo.\n",
+    "# Como se puede ver, tenemos 1565 datos negativos (0), mientras que sólo tenemos 216 datos positivos (1)\n",
+    "# Más adelante veremos técnicas para contrarrestar este inbalance."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 288,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "type\n",
+       "0    1565\n",
+       "1     216\n",
+       "Name: count, dtype: int64"
+      ]
+     },
+     "execution_count": 288,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.type.value_counts()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 322,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "1781"
+      ]
+     },
+     "execution_count": 322,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "len(y)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 324,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "1781"
+      ]
+     },
+     "execution_count": 324,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "len(X)"
    ]
   },
   {
@@ -645,19 +6691,579 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 38,
+   "execution_count": 290,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your code here"
+    "from sklearn.preprocessing import RobustScaler"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 292,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 294,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "scaler = RobustScaler()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 296,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "X_train_scaled = scaler.fit_transform(X_train)\n",
+    "X_test_scaled = scaler.transform(X_test)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 298,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<style>#sk-container-id-3 {\n",
+       "  /* Definition of color scheme common for light and dark mode */\n",
+       "  --sklearn-color-text: black;\n",
+       "  --sklearn-color-line: gray;\n",
+       "  /* Definition of color scheme for unfitted estimators */\n",
+       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
+       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
+       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
+       "  --sklearn-color-unfitted-level-3: chocolate;\n",
+       "  /* Definition of color scheme for fitted estimators */\n",
+       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
+       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
+       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
+       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
+       "\n",
+       "  /* Specific color for light theme */\n",
+       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
+       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
+       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
+       "  --sklearn-color-icon: #696969;\n",
+       "\n",
+       "  @media (prefers-color-scheme: dark) {\n",
+       "    /* Redefinition of color scheme for dark theme */\n",
+       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
+       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
+       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
+       "    --sklearn-color-icon: #878787;\n",
+       "  }\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 pre {\n",
+       "  padding: 0;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 input.sk-hidden--visually {\n",
+       "  border: 0;\n",
+       "  clip: rect(1px 1px 1px 1px);\n",
+       "  clip: rect(1px, 1px, 1px, 1px);\n",
+       "  height: 1px;\n",
+       "  margin: -1px;\n",
+       "  overflow: hidden;\n",
+       "  padding: 0;\n",
+       "  position: absolute;\n",
+       "  width: 1px;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-dashed-wrapped {\n",
+       "  border: 1px dashed var(--sklearn-color-line);\n",
+       "  margin: 0 0.4em 0.5em 0.4em;\n",
+       "  box-sizing: border-box;\n",
+       "  padding-bottom: 0.4em;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-container {\n",
+       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
+       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
+       "     so we also need the `!important` here to be able to override the\n",
+       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
+       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
+       "  display: inline-block !important;\n",
+       "  position: relative;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-text-repr-fallback {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       "div.sk-parallel-item,\n",
+       "div.sk-serial,\n",
+       "div.sk-item {\n",
+       "  /* draw centered vertical line to link estimators */\n",
+       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
+       "  background-size: 2px 100%;\n",
+       "  background-repeat: no-repeat;\n",
+       "  background-position: center center;\n",
+       "}\n",
+       "\n",
+       "/* Parallel-specific style estimator block */\n",
+       "\n",
+       "#sk-container-id-3 div.sk-parallel-item::after {\n",
+       "  content: \"\";\n",
+       "  width: 100%;\n",
+       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
+       "  flex-grow: 1;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-parallel {\n",
+       "  display: flex;\n",
+       "  align-items: stretch;\n",
+       "  justify-content: center;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  position: relative;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-parallel-item {\n",
+       "  display: flex;\n",
+       "  flex-direction: column;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-parallel-item:first-child::after {\n",
+       "  align-self: flex-end;\n",
+       "  width: 50%;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-parallel-item:last-child::after {\n",
+       "  align-self: flex-start;\n",
+       "  width: 50%;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-parallel-item:only-child::after {\n",
+       "  width: 0;\n",
+       "}\n",
+       "\n",
+       "/* Serial-specific style estimator block */\n",
+       "\n",
+       "#sk-container-id-3 div.sk-serial {\n",
+       "  display: flex;\n",
+       "  flex-direction: column;\n",
+       "  align-items: center;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  padding-right: 1em;\n",
+       "  padding-left: 1em;\n",
+       "}\n",
+       "\n",
+       "\n",
+       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
+       "clickable and can be expanded/collapsed.\n",
+       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
+       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
+       "*/\n",
+       "\n",
+       "/* Pipeline and ColumnTransformer style (default) */\n",
+       "\n",
+       "#sk-container-id-3 div.sk-toggleable {\n",
+       "  /* Default theme specific background. It is overwritten whether we have a\n",
+       "  specific estimator or a Pipeline/ColumnTransformer */\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "}\n",
+       "\n",
+       "/* Toggleable label */\n",
+       "#sk-container-id-3 label.sk-toggleable__label {\n",
+       "  cursor: pointer;\n",
+       "  display: block;\n",
+       "  width: 100%;\n",
+       "  margin-bottom: 0;\n",
+       "  padding: 0.5em;\n",
+       "  box-sizing: border-box;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 label.sk-toggleable__label-arrow:before {\n",
+       "  /* Arrow on the left of the label */\n",
+       "  content: \"▸\";\n",
+       "  float: left;\n",
+       "  margin-right: 0.25em;\n",
+       "  color: var(--sklearn-color-icon);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 label.sk-toggleable__label-arrow:hover:before {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "}\n",
+       "\n",
+       "/* Toggleable content - dropdown */\n",
+       "\n",
+       "#sk-container-id-3 div.sk-toggleable__content {\n",
+       "  max-height: 0;\n",
+       "  max-width: 0;\n",
+       "  overflow: hidden;\n",
+       "  text-align: left;\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-toggleable__content.fitted {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-toggleable__content pre {\n",
+       "  margin: 0.2em;\n",
+       "  border-radius: 0.25em;\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-toggleable__content.fitted pre {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
+       "  /* Expand drop-down */\n",
+       "  max-height: 200px;\n",
+       "  max-width: 100%;\n",
+       "  overflow: auto;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
+       "  content: \"▾\";\n",
+       "}\n",
+       "\n",
+       "/* Pipeline/ColumnTransformer-specific style */\n",
+       "\n",
+       "#sk-container-id-3 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Estimator-specific style */\n",
+       "\n",
+       "/* Colorize estimator box */\n",
+       "#sk-container-id-3 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-label label.sk-toggleable__label,\n",
+       "#sk-container-id-3 div.sk-label label {\n",
+       "  /* The background is the default theme color */\n",
+       "  color: var(--sklearn-color-text-on-default-background);\n",
+       "}\n",
+       "\n",
+       "/* On hover, darken the color of the background */\n",
+       "#sk-container-id-3 div.sk-label:hover label.sk-toggleable__label {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Label box, darken color on hover, fitted */\n",
+       "#sk-container-id-3 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Estimator label */\n",
+       "\n",
+       "#sk-container-id-3 div.sk-label label {\n",
+       "  font-family: monospace;\n",
+       "  font-weight: bold;\n",
+       "  display: inline-block;\n",
+       "  line-height: 1.2em;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-label-container {\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       "/* Estimator-specific */\n",
+       "#sk-container-id-3 div.sk-estimator {\n",
+       "  font-family: monospace;\n",
+       "  border: 1px dotted var(--sklearn-color-border-box);\n",
+       "  border-radius: 0.25em;\n",
+       "  box-sizing: border-box;\n",
+       "  margin-bottom: 0.5em;\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-estimator.fitted {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "/* on hover */\n",
+       "#sk-container-id-3 div.sk-estimator:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-estimator.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
+       "\n",
+       "/* Common style for \"i\" and \"?\" */\n",
+       "\n",
+       ".sk-estimator-doc-link,\n",
+       "a:link.sk-estimator-doc-link,\n",
+       "a:visited.sk-estimator-doc-link {\n",
+       "  float: right;\n",
+       "  font-size: smaller;\n",
+       "  line-height: 1em;\n",
+       "  font-family: monospace;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  border-radius: 1em;\n",
+       "  height: 1em;\n",
+       "  width: 1em;\n",
+       "  text-decoration: none !important;\n",
+       "  margin-left: 1ex;\n",
+       "  /* unfitted */\n",
+       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-unfitted-level-1);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link.fitted,\n",
+       "a:link.sk-estimator-doc-link.fitted,\n",
+       "a:visited.sk-estimator-doc-link.fitted {\n",
+       "  /* fitted */\n",
+       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-fitted-level-1);\n",
+       "}\n",
+       "\n",
+       "/* On hover */\n",
+       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
+       ".sk-estimator-doc-link:hover,\n",
+       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
+       ".sk-estimator-doc-link:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
+       ".sk-estimator-doc-link.fitted:hover,\n",
+       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
+       ".sk-estimator-doc-link.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "/* Span, style for the box shown on hovering the info icon */\n",
+       ".sk-estimator-doc-link span {\n",
+       "  display: none;\n",
+       "  z-index: 9999;\n",
+       "  position: relative;\n",
+       "  font-weight: normal;\n",
+       "  right: .2ex;\n",
+       "  padding: .5ex;\n",
+       "  margin: .5ex;\n",
+       "  width: min-content;\n",
+       "  min-width: 20ex;\n",
+       "  max-width: 50ex;\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  box-shadow: 2pt 2pt 4pt #999;\n",
+       "  /* unfitted */\n",
+       "  background: var(--sklearn-color-unfitted-level-0);\n",
+       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link.fitted span {\n",
+       "  /* fitted */\n",
+       "  background: var(--sklearn-color-fitted-level-0);\n",
+       "  border: var(--sklearn-color-fitted-level-3);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link:hover span {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
+       "\n",
+       "#sk-container-id-3 a.estimator_doc_link {\n",
+       "  float: right;\n",
+       "  font-size: 1rem;\n",
+       "  line-height: 1em;\n",
+       "  font-family: monospace;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  border-radius: 1rem;\n",
+       "  height: 1rem;\n",
+       "  width: 1rem;\n",
+       "  text-decoration: none;\n",
+       "  /* unfitted */\n",
+       "  color: var(--sklearn-color-unfitted-level-1);\n",
+       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 a.estimator_doc_link.fitted {\n",
+       "  /* fitted */\n",
+       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-fitted-level-1);\n",
+       "}\n",
+       "\n",
+       "/* On hover */\n",
+       "#sk-container-id-3 a.estimator_doc_link:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 a.estimator_doc_link.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-3);\n",
+       "}\n",
+       "</style><div id=\"sk-container-id-3\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>LogisticRegression()</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-3\" type=\"checkbox\" checked><label for=\"sk-estimator-id-3\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;LogisticRegression<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.linear_model.LogisticRegression.html\">?<span>Documentation for LogisticRegression</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>LogisticRegression()</pre></div> </div></div></div></div>"
+      ],
+      "text/plain": [
+       "LogisticRegression()"
+      ]
+     },
+     "execution_count": 298,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "model = LogisticRegression()\n",
+    "model.fit(X_train_scaled, y_train)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 302,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "predictions = model.predict(X_test_scaled)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 306,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "20% for test prediction data: 357.\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(f'20% for test prediction data: {len(predictions)}.')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 308,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "              precision    recall  f1-score   support\n",
+      "\n",
+      "           0       0.92      0.99      0.96       306\n",
+      "           1       0.93      0.51      0.66        51\n",
+      "\n",
+      "    accuracy                           0.92       357\n",
+      "   macro avg       0.93      0.75      0.81       357\n",
+      "weighted avg       0.92      0.92      0.91       357\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(classification_report(y_test, predictions))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 316,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Test data accuracy:  0.9243697478991597\n",
+      "Train data accuracy:  0.9396067415730337\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(\"Test data accuracy: \",model.score(X_test_scaled,y_test))\n",
+    "print(\"Train data accuracy: \", model.score(X_train_scaled, y_train))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 320,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 800x600 with 0 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "cm = confusion_matrix(y_test, predictions)\n",
+    "disp = ConfusionMatrixDisplay(confusion_matrix=cm)\n",
+    "plt.figure(figsize=(8, 6))\n",
+    "disp.plot(cmap='Oranges')  \n",
+    "plt.grid(True)\n",
+    "plt.show()"
    ]
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "ironhack-3.7",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
-   "name": "ironhack-3.7"
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
@@ -669,9 +7275,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.3"
+   "version": "3.12.4"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 2
+ "nbformat_minor": 4
 }