diff --git a/your-code/main.ipynb b/your-code/main.ipynb
index a5caf8b..f746874 100755
--- a/your-code/main.ipynb
+++ b/your-code/main.ipynb
@@ -12,7 +12,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 991,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -21,7 +21,22 @@
     "%matplotlib inline\n",
     "\n",
     "import numpy as np\n",
-    "import pandas as pd"
+    "import pandas as pd\n",
+    "\n",
+    "\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",
+    "# 🤖 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 "
    ]
   },
   {
@@ -37,7 +52,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 992,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "pd.set_option('display.max_columns', None) # display all columns\n",
+    "warnings.filterwarnings('ignore') # ignore warnings"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 993,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -65,20 +90,1231 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 994,
+   "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",
+       "  </tbody>\n",
+       "</table>\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",
+       "                  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",
+       "      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",
+       "   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",
+       "   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",
+       "   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  "
+      ]
+     },
+     "execution_count": 994,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "websites.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 995,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "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",
+    "# 🎯 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\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 996,
+   "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>1552</th>\n",
+       "      <td>B0_407</td>\n",
+       "      <td>87</td>\n",
+       "      <td>15</td>\n",
+       "      <td>utf-8</td>\n",
+       "      <td>Microsoft-IIS/7.5</td>\n",
+       "      <td>9083.0</td>\n",
+       "      <td>US</td>\n",
+       "      <td>va</td>\n",
+       "      <td>29/04/1994 0:00</td>\n",
+       "      <td>30/08/2013 0:00</td>\n",
+       "      <td>14</td>\n",
+       "      <td>0</td>\n",
+       "      <td>5</td>\n",
+       "      <td>1482</td>\n",
+       "      <td>20</td>\n",
+       "      <td>18</td>\n",
+       "      <td>8797</td>\n",
+       "      <td>1914</td>\n",
+       "      <td>20</td>\n",
+       "      <td>6.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>706</th>\n",
+       "      <td>B0_1318</td>\n",
+       "      <td>45</td>\n",
+       "      <td>8</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>27/09/2000 0:00</td>\n",
+       "      <td>10/10/2016 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",
+       "    <tr>\n",
+       "      <th>1583</th>\n",
+       "      <td>B0_645</td>\n",
+       "      <td>91</td>\n",
+       "      <td>14</td>\n",
+       "      <td>UTF-8</td>\n",
+       "      <td>Apache</td>\n",
+       "      <td>9406.0</td>\n",
+       "      <td>IE</td>\n",
+       "      <td>CO. DUBLIN</td>\n",
+       "      <td>11/08/2009 0:00</td>\n",
+       "      <td>4/03/2017 0:00</td>\n",
+       "      <td>13</td>\n",
+       "      <td>3</td>\n",
+       "      <td>6</td>\n",
+       "      <td>1591</td>\n",
+       "      <td>17</td>\n",
+       "      <td>15</td>\n",
+       "      <td>1936</td>\n",
+       "      <td>1931</td>\n",
+       "      <td>17</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1086</th>\n",
+       "      <td>B0_522</td>\n",
+       "      <td>56</td>\n",
+       "      <td>13</td>\n",
+       "      <td>utf-8</td>\n",
+       "      <td>Apache</td>\n",
+       "      <td>67283.0</td>\n",
+       "      <td>US</td>\n",
+       "      <td>MO</td>\n",
+       "      <td>20/05/1996 0:00</td>\n",
+       "      <td>24/10/2016 0:00</td>\n",
+       "      <td>37</td>\n",
+       "      <td>3</td>\n",
+       "      <td>5</td>\n",
+       "      <td>3050</td>\n",
+       "      <td>43</td>\n",
+       "      <td>44</td>\n",
+       "      <td>65986</td>\n",
+       "      <td>3492</td>\n",
+       "      <td>43</td>\n",
+       "      <td>6.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>617</th>\n",
+       "      <td>B0_603</td>\n",
+       "      <td>42</td>\n",
+       "      <td>8</td>\n",
+       "      <td>UTF-8</td>\n",
+       "      <td>Apache/2.2.15 (CentOS)</td>\n",
+       "      <td>94.0</td>\n",
+       "      <td>AU</td>\n",
+       "      <td>NSW</td>\n",
+       "      <td>19/08/2004 0:00</td>\n",
+       "      <td>5/07/2016 0:00</td>\n",
+       "      <td>14</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1102</td>\n",
+       "      <td>16</td>\n",
+       "      <td>8</td>\n",
+       "      <td>1015</td>\n",
+       "      <td>1248</td>\n",
+       "      <td>16</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "          URL  URL_LENGTH  NUMBER_SPECIAL_CHARACTERS   CHARSET  \\\n",
+       "1552   B0_407          87                         15     utf-8   \n",
+       "706   B0_1318          45                          8  us-ascii   \n",
+       "1583   B0_645          91                         14     UTF-8   \n",
+       "1086   B0_522          56                         13     utf-8   \n",
+       "617    B0_603          42                          8     UTF-8   \n",
+       "\n",
+       "                      SERVER  CONTENT_LENGTH WHOIS_COUNTRY WHOIS_STATEPRO  \\\n",
+       "1552       Microsoft-IIS/7.5          9083.0            US             va   \n",
+       "706    Microsoft-HTTPAPI/2.0           324.0           NaN            NaN   \n",
+       "1583                  Apache          9406.0            IE     CO. DUBLIN   \n",
+       "1086                  Apache         67283.0            US             MO   \n",
+       "617   Apache/2.2.15 (CentOS)            94.0            AU            NSW   \n",
+       "\n",
+       "        WHOIS_REGDATE WHOIS_UPDATED_DATE  TCP_CONVERSATION_EXCHANGE  \\\n",
+       "1552  29/04/1994 0:00    30/08/2013 0:00                         14   \n",
+       "706   27/09/2000 0:00    10/10/2016 0:00                          0   \n",
+       "1583  11/08/2009 0:00     4/03/2017 0:00                         13   \n",
+       "1086  20/05/1996 0:00    24/10/2016 0:00                         37   \n",
+       "617   19/08/2004 0:00     5/07/2016 0:00                         14   \n",
+       "\n",
+       "      DIST_REMOTE_TCP_PORT  REMOTE_IPS  APP_BYTES  SOURCE_APP_PACKETS  \\\n",
+       "1552                     0           5       1482                  20   \n",
+       "706                      0           0          0                   0   \n",
+       "1583                     3           6       1591                  17   \n",
+       "1086                     3           5       3050                  43   \n",
+       "617                      0           3       1102                  16   \n",
+       "\n",
+       "      REMOTE_APP_PACKETS  SOURCE_APP_BYTES  REMOTE_APP_BYTES  APP_PACKETS  \\\n",
+       "1552                  18              8797              1914           20   \n",
+       "706                    0                 0                 0            0   \n",
+       "1583                  15              1936              1931           17   \n",
+       "1086                  44             65986              3492           43   \n",
+       "617                    8              1015              1248           16   \n",
+       "\n",
+       "      DNS_QUERY_TIMES  Type  \n",
+       "1552              6.0     0  \n",
+       "706               0.0     0  \n",
+       "1583              4.0     0  \n",
+       "1086              6.0     0  \n",
+       "617               2.0     0  "
+      ]
+     },
+     "execution_count": 996,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "open_data(websites)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 997,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Type\n",
+       "0    1565\n",
+       "1     216\n",
+       "Name: count, dtype: int64"
+      ]
+     },
+     "execution_count": 997,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "websites[\"Type\"].value_counts()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 998,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "snake_columns(websites)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 999,
+   "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",
+       "  </tbody>\n",
+       "</table>\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",
+       "                  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",
+       "      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",
+       "   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",
+       "   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",
+       "   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  "
+      ]
+     },
+     "execution_count": 999,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "websites.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1000,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df = websites.copy()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1001,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "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"
+      ]
+     },
+     "execution_count": 1001,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.dtypes"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1002,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "server\n",
+       "Apache                                                       386\n",
+       "nginx                                                        211\n",
+       "Microsoft-HTTPAPI/2.0                                        113\n",
+       "cloudflare-nginx                                              94\n",
+       "Microsoft-IIS/7.5                                             51\n",
+       "                                                            ... \n",
+       "mw2103.codfw.wmnet                                             1\n",
+       "Apache/2.4.25 (Debian)                                         1\n",
+       "ECD (fll/0790)                                                 1\n",
+       "Apache/2.4.25 (FreeBSD) OpenSSL/1.0.1s-freebsd PHP/5.6.30      1\n",
+       "Apache/2.2.16 (Debian)                                         1\n",
+       "Name: count, Length: 238, dtype: int64"
+      ]
+     },
+     "execution_count": 1002,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.server.value_counts(ascending=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1003,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "whois_country\n",
+       "US                1103\n",
+       "CA                  84\n",
+       "ES                  63\n",
+       "AU                  35\n",
+       "PA                  21\n",
+       "GB                  19\n",
+       "JP                  11\n",
+       "UK                  10\n",
+       "CN                  10\n",
+       "IN                  10\n",
+       "FR                   9\n",
+       "CZ                   9\n",
+       "NL                   6\n",
+       "CH                   6\n",
+       "[u'GB'; u'UK']       5\n",
+       "KR                   5\n",
+       "PH                   4\n",
+       "BS                   4\n",
+       "ru                   4\n",
+       "AT                   4\n",
+       "HK                   3\n",
+       "us                   3\n",
+       "TR                   3\n",
+       "BE                   3\n",
+       "DE                   3\n",
+       "SC                   3\n",
+       "KY                   3\n",
+       "SE                   3\n",
+       "BR                   2\n",
+       "UY                   2\n",
+       "Cyprus               2\n",
+       "SI                   2\n",
+       "UA                   2\n",
+       "RU                   2\n",
+       "IL                   2\n",
+       "NO                   2\n",
+       "KG                   2\n",
+       "TH                   1\n",
+       "se                   1\n",
+       "LV                   1\n",
+       "LU                   1\n",
+       "United Kingdom       1\n",
+       "UG                   1\n",
+       "PK                   1\n",
+       "IT                   1\n",
+       "BY                   1\n",
+       "AE                   1\n",
+       "IE                   1\n",
+       "Name: count, dtype: int64"
+      ]
+     },
+     "execution_count": 1003,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.whois_country.value_counts(ascending=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1004,
+   "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": 1004,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.nunique().sort_values(ascending=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1005,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(1781, 21)"
+      ]
+     },
+     "execution_count": 1005,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1006,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "url                            0\n",
+       "url_length                     0\n",
+       "number_special_characters      0\n",
+       "charset                        7\n",
+       "server                       176\n",
+       "content_length               812\n",
+       "whois_country                306\n",
+       "whois_statepro               362\n",
+       "whois_regdate                127\n",
+       "whois_updated_date           139\n",
+       "tcp_conversation_exchange      0\n",
+       "dist_remote_tcp_port           0\n",
+       "remote_ips                     0\n",
+       "app_bytes                      0\n",
+       "source_app_packets             0\n",
+       "remote_app_packets             0\n",
+       "source_app_bytes               0\n",
+       "remote_app_bytes               0\n",
+       "app_packets                    0\n",
+       "dns_query_times                1\n",
+       "type                           0\n",
+       "dtype: int64"
+      ]
+     },
+     "execution_count": 1006,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.isnull().sum()  #contentlenght tiene mas de un 65 % null. nos la  cargaremos lo mas probable."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1007,
+   "metadata": {},
+   "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": 1007,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "explore_data(df)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1008,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your code here\n"
+    "\n",
+    "df.drop(columns='content_length', inplace=True)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 1009,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your comment here"
+    "df.drop(columns='url', inplace=True)"
    ]
   },
   {
@@ -102,20 +1338,133 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 1010,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0.5, 1.0, 'Disctribucion de Tipos')"
+      ]
+     },
+     "execution_count": 1010,
+     "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": [
+    "# Your code here\n",
+    "sns.countplot(data=df, x=\"type\", palette=\"Oranges\")\n",
+    "plt.xlabel(\"websites\")\n",
+    "plt.title(\"Disctribucion de Tipos\")  "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1011,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your code here\n"
+    "\n",
+    "#Ya que no hay documentacion, con esto entiendo que 0 es benigno y 1 maligno. hay bastante desbalance y probablemente tendremos que aplicar algun metodo para balancear esto, porque con essta diferencia, no considero que vayamos a tener un modelo de ml tan efectivo."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 1012,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your comment here"
+    "num = df.select_dtypes(include=\"number\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1013,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 2000x1600 with 20 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "color = '#FF8C00'\n",
+    "\n",
+    "# grid size\n",
+    "nrows, ncols = 5, 4  # adjust for your number of features\n",
+    "\n",
+    "fig, axes = plt.subplots(nrows=nrows, ncols=ncols, figsize=(20, 16))\n",
+    "\n",
+    "axes = axes.flatten()\n",
+    "\n",
+    "# Plot each numerical feature\n",
+    "for i, ax in enumerate(axes):\n",
+    "    if i >= len(num.columns):\n",
+    "        ax.set_visible(False)  # hide unesed plots\n",
+    "        continue\n",
+    "    ax.hist(num.iloc[:, i], bins=30, color=color, edgecolor='black')\n",
+    "    ax.set_title(num.columns[i])\n",
+    "\n",
+    "plt.tight_layout()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1014,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 2000x1600 with 20 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "color = '#FF8C00'\n",
+    "\n",
+    "# grid size\n",
+    "nrows, ncols = 5, 4 \n",
+    "\n",
+    "fig, axes = plt.subplots(nrows=nrows, ncols=ncols, figsize=(20, 16))\n",
+    "\n",
+    "axes = axes.flatten()\n",
+    "\n",
+    "for i, ax in enumerate(axes):\n",
+    "    if i >= len(num.columns):\n",
+    "        ax.set_visible(False)\n",
+    "        continue\n",
+    "    ax.boxplot(num.iloc[:, i].dropna(), vert=False, patch_artist=True, \n",
+    "               boxprops=dict(facecolor=color, color='black'), \n",
+    "               medianprops=dict(color='yellow'), whiskerprops=dict(color='black'), \n",
+    "               capprops=dict(color='black'), flierprops=dict(marker='o', color='red', markersize=5))\n",
+    "    ax.set_title(num.columns[i], fontsize=10)\n",
+    "    ax.tick_params(axis='x', labelsize=8)\n",
+    "\n",
+    "plt.tight_layout()\n",
+    "plt.show()"
    ]
   },
   {
@@ -133,29 +1482,148 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 1015,
+   "metadata": {},
+   "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",
+       "dtype: float64"
+      ]
+     },
+     "execution_count": 1015,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "round(num.corrwith(df[\"type\"]).sort_values(ascending=False),2)   #Miramos algunas que podríamos quitar, pero ahora no cargamos nada \n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1016,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your code here\n"
+    "num_corr = num.corr().round(2)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 1017,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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JxcfH68SJE5bJyoSEBMXFxWXI/bi4uCQ7SSpJTz31lOXne/fuWX7etm2bpMQJ9eQKJ6TESfjs2bOnOR5zQcH169d1/Phxy3ZzxwJfX1/L29F79+617I+JibGMadSoUZqv+yCVK1dOdruzs7O8vLwkyVJMkl45cuRQgwYNJNkue5CQkGBpLZ/c8/FfZs5JiRIlkp1Ql6T8+fNr7dq1mjZtmp599llFRERY2uWb395PyfPPPy9JOnHiRIYX2vxbSl0vXF1dlTNnTkmJHT/M9u/fr5iYGElSmTJlUvyd8NRTT8nb21uSrLoMNG7cWMOGDdPnn3+e7HWvXbtmteyK+Vr/Zi66yEgtW7a0dKz4d5eCffv26eLFi5JY7gAAAADAf5fR3gEAAAAAABzT7du3LT97enpafja/pRseHq6qVaum6lyXL1+2LCtgdvPmTW3dulWnTp1ScHCwzp8/rzNnzigqKspqXFqXE0iJp6dnim+8J+2UEB8fLymxoMLchr148eIpntfZ2VnFihWzFE2kVpkyZVSwYEFdunRJO3fuVJkyZSQldiyQpJo1a1rWrD969Kju3LkjDw8PBQYGKioqSq6urqpTp06arvkw5uslx/zZZUSBR8uWLbV+/Xpt375dt2/ftkxSBwUFKTQ0VD4+PpZiiidFWFiYJKlYsWJpOsb8fJcsWfKBY5Puv3z5sqXAIzM86Nzm70rS72XSrhXvvfdeqq5x6dIlm20JCQnavXu3jhw5ovPnzys4OFhnzpzRlStXHjnu9MqVK5f8/Py0fv16/fHHH+rVq5dl36pVqyRJ5cuXf2j+AAAAAMBeKCgAAAAAAGSKpO29CxcubPk5uXXvHybpMdHR0Zo0aZIWLlxoUzyQLVs2+fr6Kj4+3uqt/IxgbtWeWknfAndzc3vg2KTLQ6RFgwYNtGjRIu3cuVNvvfWWIiMjdfjwYTk5OalGjRrKnj27smfPrrt37yooKEj169e3LHfg6+trWes9oyS3BEVm8PPzs9yXv7+/Xn75ZUmytI9v2bLlE9c+/ubNm5KUpm4VSb8XD3uGkp73UbtEPIz5jfzUetTfCVLikhFff/21zpw5Y7XdYDCoRIkSevbZZy1LkKQks57fl19+WevXr9eJEyd08uRJlSpVSrGxsVq7dq0kuhMAAAAA+G+joAAAAAAAkCkOHjxo+TlpC3Tz5HrlypW1aNGiNJ+3f//+WrdunaTEdeP9/PxUunRpPfPMMypRooSMRqMmTZqU4QUFaZV0Ajdpe/fkPGx/Svz8/LRo0SLt3btXMTEx2rNnj+Li4lSuXDnlypVLklSlShXt2LFDe/bsUf369S3LMGT0cgePk7u7u/z8/LRmzRr9+eefevnllxUfH2+ZoH3hhRcy7FpJl7DITObvRVqehaQFIf8urvm3tBQfPG5Jvytr1qxRiRIl0nT8hg0b9O677yohIUG5c+dW8+bNVaFCBZUsWVKlS5eWp6enzp8//9CCgszSoEED5c6dWxEREfrjjz/04Ycfavv27QoPD5ezs7NatWpll7gAAAAAIDUoKAAAAAAAZLiYmBjLpL+Pj4/V2uSFChXS8ePHFRIS8sBzJCQk2Lxlvn//fst533jjDQ0bNizZYzN7jfjU8PT0tEwinjt3LsVxCQkJVi3f06J27drKli2boqKidPDgQe3Zs0dS4nIHZr6+vpaCgkuXLunEiROSnuyCAimxC8GaNWu0bds23b59W0eOHNHVq1dVokQJlS1bNlXncHJykiTFxsamOCYiIiIjwn0o8/ciaWeP5EybNk1Go1HVqlXT008/LYPBoISEBJ0+ffqBxyV9c79QoUIZEnNGKViwoOXnkJCQBxYUJPd7Yfz48UpISJCPj4+WLl2qPHny2Bxnz98Jrq6uatGihRYsWCB/f399+OGH2rBhg6TE73DevHntFhsAAAAAPIyTvQMAAAAAADieJUuW6OrVq5Kkdu3aWU0AVqtWTZJ07do1qy4G/zZt2jRVr15dL730kmXCff/+/Zb9r7/+erLHxcfHa/fu3VZ/txdfX19J0rZt26zWjE9q79696W5Bnz17dkvxwI4dOxQYGGh13aQ/HzlyRH/++ackyWQypWlS+b+4fEDDhg3l4eGhmJgYBQQEaM2aNZLS1p3A/GZ8SpPNsbGxOnz4cJpjS8/nVbVqVUnSqVOnFBoamuyYyMhIfffdd/rqq6+0Y8cO5cqVS6VKlZIkS6FNSszdG55++mnlzp07zfFlpqpVq1o+M39//xTHXbx4UVWqVFHTpk31888/S0rMnblg57nnnku2mECSdu7cafnZHr8TzMtynDhxQhcuXNDmzZslsdwBAAAAgP8+CgoAAAAAABlq3759+uqrryRJBQoUUNeuXa32v/zyy5a1ykeNGpVsi/fg4GD99NNPun37tqKjo1WkSBFJ/7xRLiVOvCZnypQpVh0BYmJiHuV2Hkn79u0lJb51bZ4ATer+/fsaP378I13D3Glgw4YN+vvvv+Xk5KQaNWpY9lesWFHu7u6KjY3V9OnTrY5JLWdnZ8vP9vw8k8qWLZsaN24sKXEy3fzGd1oKCooVKyZJCgoK0pUrV2z2z5o1y2qpgNQyf17R0dGpPqZ169YyGo1KSEjQuHHjki1A+eGHHxQbGyuDwaCWLVtK+ucZ+/vvvzV37txkzz1nzhxLZ4p27dql6V4eB29vb8sz+b///U/79u2zGRMfH68xY8bo7t27unDhgipUqCDJ+tlMqUvDsWPHLM++lPHPsNFofOh5K1eurOLFi0uSpk6dqrCwMLm7u6tZs2YZGgsAAAAAZDQKCgAAAAAAqRYXF6c7d+5Y/YmIiNCFCxe0adMmDRkyRF26dNHdu3fl5uam7777zmp9dClx8vD999+XJB0+fFjt27fXunXrdO3aNYWGhuq3335T586dFRERIYPBoCFDhljeXq5bt67l51GjRmnlypW6fPmywsLCtHXrVvXq1Uvff/+91fUetrZ8ZqpXr55lonTMmDEaN26cTp8+rfDwcO3cuVOdOnXSoUOHLOPT82Z7w4YNJUnHjx9XbGysypYtq5w5c1r2m9vjS9KNGzckyTIRn1pJ32hftWqVbty4ka6J9oxmnlT39/fX9evXVb58eT399NOpPr5p06aSEif+e/bsqZ07d+rGjRv6+++/NWzYME2cOFG5cuVKc1zmz+vatWvatGmTIiIidP/+/Qcekz9/fr3zzjuSpD///FO9e/fW/v37FR4ermPHjmnUqFGaPXu2JKlDhw6WyekOHTpYJtfHjBmjESNG6NixY7p586aOHTumESNGaOzYsZKkKlWqqEuXLmm+n8dh0KBBypEjh2JiYtS9e3f98MMPOnfunG7cuKHAwED17t1b69evlyS1atXK0tHB09NTFStWlCRt3rxZo0ePtnzHjh07pm+++Uavvfaa1e+BjP6dYM53YGCgTp06Zfme/duLL74oSVq+fLmkxOfP3d09Q2MBAAAAgIxmtHcAAAAAAIAnx759+ywTeQ9SpEgRTZw4UZUqVUp2f48ePRQVFaUffvhBJ06c0HvvvWczxsXFRcOHD1f9+vUt20qVKqWePXtq+vTpun79ugYOHGhzXM6cOdWuXTvL5Ov58+fl7e2d2lvMcOPHj1fXrl115MgRzZ492xKXWZs2bbR69Wrdu3fP6m3r1CpcuLCeeeYZS8eGpMsdmPn6+mrr1q2SpLx586aYl5QUK1ZMBQsW1KVLl/T999/r+++/1yuvvGKZqLaXevXqydPTU7du3ZKUtu4EUuIE7++//66tW7fq2LFjNt00qlSpotatW+vzzz9P03lr1KghZ2dnxcXFWYoExowZozZt2jzwuHfffVcRERH69ddftXHjRm3cuNFmTLNmzTRkyBDL311dXTVt2jT17dtXBw4c0Pz58zV//nyb4+rWrasJEyZY3qb/rylWrJhmzpypd999V9euXdM333yjb775xmZco0aNNHr0aKttw4cP15tvvqmoqCjNmzdP8+bNszmuTZs22rNnj0JCQqw6mGQEX19frV69WpcvX7Y8g/7+/ipcuLDVuNatW2vKlCmW7hMsdwAAAADgSUCHAgAAAADAI3FycpKHh4dKlCihli1basKECVqzZs0DJ60NBoM++OAD/fbbb2rXrp2KFSsmNzc3ubq6qnjx4nrttde0YsWKZNuz9+/fX99++61q1aolT09POTs7K2fOnCpfvrx69eqlP/74Qx9++KFy5Mgh6eFry2e2nDlzauHChRo8eLAqVKggDw8Pubu7q3Llyvrqq680ZswYxcXFSUps458e5i4FklSzZk2b/UmLDBo0aJDmTghGo1E//vijfH195e7uLnd3d925cyddsWYkV1dXS5eBpMsApJazs7OmTZumESNGqEqVKpbclC9fXoMHD9Yvv/ySrjfIn3nmGU2cOFGlS5dWtmzZlCtXLoWHhz/0OCcnJw0bNkzz5s1TixYtlC9fPrm4uMjT01O1a9fWxIkTNWXKFMuSIWZ58+bV/PnzNW7cONWrV0958uSRi4uLChUqpEaNGmnKlCmaOXOm8uTJk+Z7eZyqVKmiP//8Ux999JEqV66sXLlyyWg0Kk+ePGrYsKG++eYb/fjjjzZdTypWrKjly5erTZs2KliwoIxGo9zc3FSkSBG98MIL+vnnnzVmzBjVqVNHUmIng7QsR/Ew7du313vvvadChQrJxcVF3t7eunz5ss24IkWKWAqyvL29LfEAAAAAwH+ZISG5RfkAAAAAAMBjcf/+fUvxxbhx4/Tyyy/bNyAAmaZTp07au3evunbtqsGDB9s7HAAAAAD/UefOndPLL7+sNm3aaNiwYWk6NiwsTFOnTtWOHTt0+fJl5c2bV40bN1bfvn3TVWhOhwIAAAAAADLJnDlz9Pnnn+uPP/5Icczhw4ctP5coUeJxhAXADkJDQxUYGChJeuWVV+wcDQAAAID/qmvXrqlPnz66e/dumo+9cOGC2rZtq4ULF8rNzU2NGjWSs7O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+      "text/plain": [
+       "<Figure size 2500x1500 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "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(\"Dealing with Multicollinearity\", fontsize=20) # add title\n",
+    "plt.show()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1018,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "num.drop(columns=['tcp_conversation_exchange', 'app_packets', 'source_app_packets', 'remote_app_bytes', 'source_app_bytes'], inplace=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1019,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your comment here"
+    "num2 = num.copy()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 1020,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Print heatmap again\n"
+    "num_corr2 = num2.corr().round(2)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1021,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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ntixFjtSpUydVrVpVQUFBatSokbp27SpJOnjwoPr06aOmTZtq586dKl++vDp37mxyLWA98fHxGjBggJo3b67PPvtM33//vYKCgiRJkyZNUoMGDbR3716TKwHr4LUAkHr16qVTp07pq6++ynTN8uXLFRERkenOrgDwuDIs7K0IAMii1atXZ2mdo6Oj8ubNq5IlS6pEiRLWjQJMEBkZqR9++EEhISGKi4tTq1atNGHCBA0bNkzFixfXm2++KXt7e7MzgWzXrl07nTx5Ups3b850y9IrV66oUaNGKlWqlFasWGHbQMBGOnfurISEBB07dkyGYeipp55S8eLFZW9vr/Pnzys2NlaS5ODgIEdHx3T3Goahffv2mZENZKvExESNHTtWa9euvWdwzDAMNW3aVKNHj77nm6lATnHz5k116tRJkZGRKlCggHx8fLRx40a1atVKEydOVI8ePRQSEiIXFxetWbNGxYsXNzsZyHa8FuC/Ljg4WIsWLdKWLVtUuXJltWjRQqVKlZKdnZ3Onz+vbdu2acuWLfL09EwbtPmnN954w4RqAMgahggAAFnm7e390OfBlytXThMnTtSzzz5rpSrAtpYvX65Ro0al+zb23TcKW7ZsqePHj6thw4aaNm2a7OzY9Ak5y7x58zR+/HjVqFFDU6ZMkYeHR7rrcXFxGjhwoMLDw/XRRx+pR48e5oQCVubt7f1I92dly1PgSREXF6e9e/cqOjpaqampKliwoGrVqpVuq3cgJ/ruu+80depU+fn5afTo0XJxcZG3t3fa7wbS37sRzJkzRx07dtSoUaNMLgash9cC/Ffdfa/07sds//d9039+/PbPaxaLRYZh6MiRI7YJBYB/gSECAECWfffdd9q2bZsOHTqkvHnzqn79+ipatKgsFouio6O1c+dOxcfHy8vLS+XKldOZM2f0119/6emnn9batWv19NNPm/1/AXgkBw4c0Ouvv648efKob9++8vX1VcuWLdPeKAwMDNSYMWMUGxur8ePHq3Xr1mYnA9kqOTlZnTp10uHDh+Xk5KSaNWuqaNGikqSzZ88qLCxMSUlJqlSpkpYsWSInJyeTiwHrOHfu3CPdzxvqeNJFR0crd+7cme5Kc9eZM2d04sQJ+fr62iYMsCE/Pz9duXJFW7ZsSfuZ5/8OEaSmpqpx48bKlSuXNmzYYGYuAMAKPv7444f+wtU/jRs3LhtrACB7OZgdAAB4cvj4+Ojbb79VgwYNNGnSJOXNmzfd9Zs3b2ro0KHavHmzpkyZoueee07z58/XuHHj9OOPP3ImMJ54s2fPliTNnDlT1atXv+d648aNVapUKbVq1UrLly9niAA5jqOjo+bNm6fPPvtMGzZs0O7du9NdNwxD//vf/zRq1CgGCJCjMQSA/7pGjRqlHed0P19++aVCQkK0Z88eG5UBthMVFSVfX9/7/sxjZ2enihUrKigoyIZlgO1dunRJt2/fvu8aLy8vG9UAtjN+/HizEwDAahgiAABk2fTp0+Xq6qqvv/5aLi4u91x3cXHRhAkT1LBhQ02dOlVz5sxR9+7dtXjxYm3dupUhAjzxwsPDVbVq1QwHCO4qU6aMatSooRMnTtiwDLCdvHnzavLkyfrwww+1Z88excbGKjU1VYUKFZKPj488PT3NTgQAZLPo6Oh0jy0Wi27cuHHP8/+UkJCgiIgIJSUlWTsPMIWjo6OuXLnywHWXL1+Wo6OjDYoA20pNTdWUKVO0bNkyXbt27b5rDcNQRESEjcoA21m8eLFatWqlp556yuwUAMh2DBEAALLs0KFDqlevXoYDBHc5OTmpevXq2rlzZ9pzzz777D3fVgWeRNevX5e7u/sD1z311FNKSEiwQRFgnsKFC6tVq1ZmZwA24efnJ8MwNGPGDBUpUkR+fn5ZvtcwDK1du9aKdYD1DRs2TMHBwWmPDcNQYGCgAgMDH3hvtWrVrJkGmKZcuXI6fPiwYmJiMh2iPHv2rA4fPqzKlSvbuA6wvnnz5mnWrFmS/t51I3fu3I+0rTvwJBozZowmTpyopk2bql27dqpdu7bZSQCQbRgiAABkmaOjo+Lj4x+47v+uMQxDdnZ21soCbKZgwYI6evToA9cdPXpUHh4eNigCzJGQkCB/f3+FhITowoULsre3l5eXl3x9fdW0aVPlypXL7EQgWx07dkyGYaR9o/rYsWNZvpc305ETfPzxx+rSpYssFoukvwcr7e3tMx0uNgxDTk5OKlmypEaOHGnDUsB22rVrp08++UT9+/fX5MmTVaJEiXTXT58+rUGDBikpKYljzpAjrVixQvb29ho/fryaN2/Ojhv4T+rSpYv8/f3166+/yt/fX8WLF1fbtm3Vpk0b3hcC8MQzLHd/AwQA4AG6deum8PBwLV26NNNvUvzxxx/q0KGDnnvuOS1dulSS1KxZMzk4OGjdunW2zAWy3Weffably5dr2LBh6ty5syTJ29tbrVq10sSJEyX9vZXdmDFj1KFDB40ePdrMXMAqtm7dqqFDh+rq1av6v79KGIahYsWK6auvvuIbd8hR7p7nXqVKFeXKleuhz3f38fGxRhZgmv/78w/wX9W/f38FBgbKMAx5enoqJiZG7u7ucnV11alTp5SSkqK6detqzpw5DJUhx6latapq1KihuXPnmp0CmCopKUmBgYFasWKFgoODZbFYZG9vr/r166t9+/by9fXly1UAnkgMEQAAsmzLli1655135Orqqvfee09NmzZN29o9Li5Omzdv1pQpUxQfH6+vvvpKzZs319SpUzVz5kx17dpVQ4cONfn/AfBozp07p1atWunGjRt6+eWX9cILL2jo0KGqV6+e2rVrp23btmnNmjVydnbW6tWr7/k2EvCki4iI0GuvvaakpCS9+OKLatq0qTw9PWWxWHT27Flt3LhRoaGhyp8/v1asWCEvLy+zk4HHSmBgoCIjI9W/f3+zU4BHsmrVKhUvXlw1atQwOwUwVWpqqr777jstWLDgnuPMXFxc1KlTJw0cOFBOTk4mFQLW07hxY5UoUYIhAuAfYmJitGLFCq1cuVLR0dEyDEPu7u569dVX1a5dOxUrVszsRADIMoYIAAAPZfr06fr222/THjs4OMhisejOnTuSJIvFol69emnw4ME6d+6cGjVqJBcXF61du5YflJEjhIaGasCAAYqPj7/n20QWi0V58uTR5MmT5evra1IhYD0DBgxQQECAhg8fnrYbx/81e/ZsffXVV+rUqZNGjBhh40Lg8TZkyBD5+/vryJEjZqcAj6Rt27Zq3769WrZsqbx585qdA5guOTlZERERio6OlsVikYeHhypXrixnZ2ez0wCr+eabbzRv3jz9+uuvKlq0qNk5wGPn0KFDWr16tZYtWyaLxSLDMPT888+rW7duatCggdl5APBADBEAAB7avn379OOPP2r37t26ceOGJMnZ2Vk+Pj7q2bOnnn/+eUnS8ePHNWvWLHXv3l0VKlQwMxnIVvHx8Vq+fLlCQkIUExOj1NRUeXh4yMfHRx07duTcO+RY9erVU8GCBbVy5cr7rvPz89P169e1detWG5UBTwaGCJBTeHt7yzAMOTs7q3nz5mrbtq1q1qxpdhZgU3fu3JG9vX2W1v72229q0qSJlYsA20pKSlLPnj119uxZ9evXTxUqVFD+/PkzXc8uZfivuH37tgICArRhwwbt2rVLt2/flr29vYoVK6ZTp07JMAy98MIL+uabbxjGBPBYY4gAAPBIrl69qpSUFOXPnz/Lb6AAAJ5MVatWla+vr7755pv7rhs4cKC2bdumAwcO2CYMeEIwRICc4siRI1q+fLnWrVuXtjtTqVKl1K5dO73yyisqUKCA2YmA1Q0cOFCTJ0++7znXV69e1ahRo7Rx40b+248cx2KxaMKECZo3b949u/T9X4ZhKCIiwkZlgDnCw8O1cuVKbdy4UYmJibJYLPLy8lK7du3Utm1bFSpUSEeOHNGoUaN08OBBtWjRQl999ZXZ2QCQKYYIAAAAsqhbt26qW7eu+vTpc99148aN09atWxUQEGCjMsA2OnbsqAsXLui3336To6Njpuv+97//KXfu3FqxYoUN64DHH0MEyGmSkpIUEBCgX375RaGhoZIke3t7NWzYUG3btlX9+vUf+MES8KTy9vZWy5Yt9eWXX2b493zjxo0aM2aMLl26JEdHR/3+++8mVALW891332natGm6+/FC3rx57/vf/L1799oqDbCZCxcuaNWqVVq1apWioqJksVjk4OCghg0bqn379qpXr949/15cvnxZ9erVk4uLi/bt22dSOQA8mIPZAQCAJ0tKSop+++03RUZG6ubNm0pNTc107bBhw2xYBljfnj17VLhw4QeuO3r0qGJiYmxQBNjWu+++q969e+vTTz/V2LFj5eTkdM+aqVOn6tSpU5o6daoJhQAAW3JyclLLli3VsmVLnTt3TitXrtSGDRsUEBCg3377TYUKFVLbtm3Vtm1btrFGjvPss89q3bp1cnBw0Pjx49Oev3z5skaNGqWAgABZLBZVrVpVY8aMMbEUsI6VK1fKzs5OI0eOVOvWrTP83QDI6V566SVZLBZZLBYVL148bdeBp59+OtN7ChQoIDs7O+XLl8+GpQDw8NiJAACQZVeuXFG3bt30119/SZLu9xJiGAbfssMT74MPPlBcXFza4z179sjd3V2lS5fO9J6EhAQdPXpUXl5e2rx5sy0yAZv55ZdftHnzZm3btk2FChVSkyZNVLJkSdnb2+v8+fPavn27IiMjVbhwYTVq1Oie+xkuw38dOxHgv+Dy5cuaPXu25s+fnzZwbG9vr0aNGmnQoEEqWbKkuYFANrl69areeOMNRUZGqm3btho7dqzWrVunsWPH6sqVK8qdO7cGDRqkzp07syMHcqTnnntONWvW1A8//GB2CmCaypUrq2nTpmrXrp3q1Klz37Xx8fFydXVN28npmWeekbe3t41KAeDhsRMBACDLvv32Wx07dkyurq5q1KiRChYsKAcHXkqQc9WrV0+ffPJJ2mPDMHTx4kVdvHjxvvcZhqFevXpZOw+wuWHDhskwDFksFp0/f14LFy5Me1P8n4NlMTExWrRoUbp7DcNgiAAAcqjbt29r06ZNWr16tfbs2aM7d+7IMAy9+OKLqlWrltatW6eAgAAFBQVp9uzZqlmzptnJwCNzc3PT/Pnz1bNnT61YsUJhYWE6ffq0LBaLGjRooJEjR2ZpFzPgSeXu7n7fI86A/wIHBwd5eHg8cIBgyJAhCg4O1s6dO9N2cgKAxx2f/AAAsmzz5s1ycXHRihUrVLRoUbNzAKtr06aNXF1d075F179/f/n4+Khbt24ZrjcMQ7ly5VKJEiVUrFgxW6YCNtGvXz++SQcASBMeHq5Vq1Zpw4YNSkxMlMViSTvCoF27dmlHGLz11luaNWuWJk+erC+++EIrV640uRzIHvny5dO8efPUq1cvHThwQA4ODpo4caJatGhhdhpgdc2aNdPSpUsVHR3NkTX4z7p586YuX778wHVRUVGKj4+3QREAZB+OMwAAZFnlypVVr149zZgxw+wUwBRdu3ZVvXr11KdPH7NTgCfK8ePHdfnyZdWqVcvsFMBUHGeAnGLmzJlauXKloqKiZLFYZG9vr/r166tDhw7y9fWVnZ3dPfdYLBZVqVJF9vb22r9/vwnVgPUkJibqrbfeUnh4uF5//XUNHz7c7CTA6hITE9W1a1fFx8frnXfeUdWqVeXq6prpjpVubm62DQSs4M0339SpU6fSHp87d065c+dW/vz5M73n+vXrSkhIUMmSJbVhwwYbVAJA9mAnAgBAlnl4eOjWrVtmZwCmWbhwoSQpKSlJx48fV/ny5dOunThxQsHBwWrZsqVcXV3NSgQeS99//73WrVuniIgIs1MAANng66+/liR5eXmpXbt2atu2rQoVKnTfe5KTk2UYBkcZ4Inl5+d33+u3b9+WxWLRkiVL0rarvsswDK1du9baiYBNvfrqq7p165ZiY2MfeGyZYRj8LoAcoXPnznrnnXfSHhuGoRs3bujGjRv3vS9XrlwaNGiQtfMAIFsxRAAAyLKGDRtqxYoVOn/+PGc74j9r8+bN+vjjj1WmTBktW7Ys7flDhw5pzJgx+uabb/TFF1+ocePGJlYCjx82QAOAnKNJkybq0KGD6tWrl+VjbpycnHTw4EErlwHWc+zYsSyts1gsOn36dLrnOA4KOdH//Xt+P/wugJyiYcOGWrNmjSwWiywWi9q0aaMGDRpo4MCBmd6TK1cueXp6ytnZ2XahAJANGCIAAGTZu+++q6CgIL399tsaOnSoqlatKkdHR7OzAJs5dOiQ3n33XVkslnvOfHzmmWfUtGlT/fbbbxo4cKB++uknVaxY0aRSAAAA65k2bZrZCYDNLViwwOwE4LESGRlpdgJginLlyqX9uU2bNqpevbq8vb1NLAIA62CIAACQZe+//77y5MmjI0eOqFu3bpIkZ2fnDL9VYRiG9u3bZ+tEwKpmzpwpi8WiyZMn63//+1+6a5UqVdLUqVO1adMmvffee5o5c6amTp1qUikA4HGUP39+eXp6mp0BZJv4+HitXr1aoaGhunDhghwdHeXl5aU6derIz8+Pb9whR/Hx8TE7AQDwmBk3bpzZCQBgNYaFvYQAAFn0sFO1TKUjp3nppZdUqFChdMcYZKR9+/Y6c+aMQkJCbFQGPN6GDBkif39/HTlyxOwUINtFRUUpNDRU0dHRKl26tPz8/BQWFqZKlSrxASpytMDAQH366adKSEi4Z5tqwzBUuHBhffPNN3ruuedMKgRsY926dTp37pzeeuuttOeCgoL0zTff6LXXXlO7du1MrAMAAAD+HXYiAABk2ebNm81OAEx15coVValS5YHrvLy8GKIBgBwuPj5ew4cPV2BgYNoHqH5+fvLz89OkSZN06tQpTZs2TbVq1TK5FMh+hw8f1sCBA5WSkiJfX181btxYnp6eslgsOnv2rNavX6+9e/eqd+/eWrFihYoWLWp2MpDtUlJS9MEHHyggIEClS5dON0QQFRWlw4cPa/jw4dq5c6emTJliXiiQTapXry7DMLRy5UqVKFFC1atXz/K97FYJAMCThyECAECWFSlSxOwEwFSFChXSH3/88cB1f/75pzw8PGxQBAAww82bN9W9e3dFRkaqQIEC8vHx0caNG9OuOzs76+rVq3rrrbe0Zs0aFS9e3MRaIPvNnDlTd+7c0YgRI9SpU6d7rnfq1EkzZ87U119/rW+//ZatfpEjrVixQps2bVKJEiU0YMCAdNfat2+vIkWKaPz48dq0aZN+/vlndejQwaRSIHvcuHFDkpSampruMQAAyJkYIgAA/CuJiYk6ePCgoqOj5enpqbp16+rkyZMqVaqU2WmA1bz00kuaP3++pk+frv79+2e45ocfftDJkyd5kxAAcrAff/xRkZGR8vPz0+jRo+Xi4pLu2Kd58+Zp0qRJmjNnjubOnatRo0aZWAtkvz179qh8+fIZDhDc1adPH/3666/asWOHDcsA21m+fLny5s2rxYsXy93dPd01JycnNWjQQBUqVFDz5s31008/8fsBnnh3d6csXLhwuscAACBnYogAAPBQkpOTNXnyZC1btky3bt2S9PfWvXXr1tXw4cN15coVTZ06VWXKlDG5FMh+PXr00KpVq/Ttt99q586datiwoby8vGQYhmJiYrR9+3aFhYUpX7586tOnj9m5AAAr2bBhg9zd3fX555/LyckpwzWDBg3S+vXrtWfPHhvXAdZ3+/btLO2w8cwzz2jr1q02KAJsLyoqSrVq1bpngOCfChYsqBo1amjv3r02LAOs4//uTvkwu1XGx8dndw4AALAyhggAAFmWkpKiPn36KDg4WA4ODqpUqZJ+//33tOuJiYk6fvy4unXrptWrV7OdO3KcwoULa8aMGRoyZIgOHDiggwcPprtusVhUsGBBffPNNxz/AQA5WFRUlHx9fTMdIJAkOzs7VaxYUUFBQTYsA2yjfPnyOnTokFJSUuTgkPlbS0ePHtUzzzxjwzLAtu5u634/Dg4OMgzDBjWAbTVq1EhNmzbVRx99dN91Q4YMUXBwsHbu3GmjMgAAkB3szA4AADw5li1bpt27d+v555/X5s2btXz58nTXly5dqpYtW+rSpUuaN2+eOZGAlVWvXl3r16/X119/rfbt28vX11d169bVK6+8onHjxikgIEDVqlUzOxMAYEWOjo66cuXKA9ddvnxZjo6ONigCbGvAgAE6f/68PvvsM928eTPDNV9//bVOnTqlvn372rgOsI3SpUtr7969unz5cqZr4uPjFRYWptKlS9uwDLCNc+fO6dKlSw9cFxUVxU4EAAA8gdiJAACQZatWrVK+fPk0bdo05c2b957rzs7O+uKLLxQcHKwdO3ZoyJAhJlQC1pcrVy7973//0//+9z+zUwAAJihXrpwOHz6smJgYeXp6Zrjm7NmzOnz4sCpXrmzjOiD7jR079p7nSpQooVWrVmnHjh1q0qSJihUrply5cunChQsKCgpSZGSkqlWrpri4OBOKAet75ZVXNHLkSPXt21cTJkxQqVKl0l0/c+aMPvnkE12/fl2vvPKKOZFANnrzzTd16tSpdM8FBgaqUaNGmd5z/fp1JSQkqGTJktaNAwAA2Y4hAgBAlp04cUJ16tTJcIDgLicnJ1WpUkUhISE2LAMeLxaLRcHBwXrhhRfMTgEeCxaLRRaLxewMINu0a9dOn3zyifr376/JkyerRIkS6a6fPn1agwYNUlJSklq3bm1SJZB9Fi1aJMMwMvxv+cWLF7V06dK07dr/uSY8PFz79+/X66+/brNWwFY6dOig9evXa8+ePWrRooVKliwpLy8vSdL58+d18uRJpaamqlatWurUqZPJtcCj69y5s9555520x4Zh6MaNG7px48Z978uVK5cGDRpk7TwAAJDNGCIAAGSZYRi6ffv2A9clJiZy5iNyrLCwMC1atEhnz55VUlJSujfKLRaLbt++rcuXL+vmzZuKiIgwsRSwvj///FMXLlyQg4ODvLy87vkg9a5PP/1U77//vo3rAOtp06aNNm/erMDAQDVv3lyenp4yDEPBwcFq2bKlTp06pZSUFNWtW1ft2rUzOxd4ZP379zc7AXjs2NnZac6cOZo6dap+/vlnnTx5UidPnky77uzsrI4dO2rQoEFycOAtWDz5GjZsqDVr1qQNCLdp00YNGjTQwIEDM70nV65c8vT0lLOzs+1CAQBAtuAnWABAlpUpU0a///67rl69Kjc3twzXXL58WYcPH+bMR+RIBw4cUI8ePXTnzp37fqvaMAyVK1fOhmWA7SQlJWnOnDlasmTJPWegFi9eXG+++aY6dOiQ7vn8+fMrf/78tswErG7q1Kn67rvvtGDBAkVHR0uS4uLiFBcXJxcXF3Xr1k0DBw5ksBI5QnYNEZw4cUKXLl1SrVq1suWfB5jNyclJgwcP1sCBA3X48GFduHBBd+7ckYeHhypXrswHp8hx/vl7bps2bVS9enV5e3s/1D+D1wIAAJ4MhoV9RQEAWbRgwQJ98cUXevHFFzVp0iS5urrK29tbrVq10sSJExUfH68PPvhAu3bt0ocffqg33njD7GQgWw0YMEABAQF66aWX1K5dO+3YsUPLly/Xt99+q5SUFG3fvl0rVqzQM888o5UrV8rR0dHsZCBbJScnq3fv3goNDZXFYlHBggXl5eUli8Wis2fP6tKlSzIMQ61bt9b48ePNzgVsIjk5WREREYqOjpbFYuGDI+A+hgwZIn9/fx05csTsFACASXgtAADgycBOBACALOvUqZPWr1+voKAgNWrUSOXLl5ckHTx4UH369NGBAwcUHx+vChUqqHPnzibXAtlv//79evrppzVlyhTlypVL+fLl008//SQ7Ozs1adJETZo0Ubly5fTFF19o8eLF6tGjh9nJQLZasGCBQkJCVLZsWX3++ed67rnn0l0PCwvTp59+qjVr1qhu3bry8/MzqRSwrr179+rpp59W6dKl5ejoqCpVqqhKlSr3rDt48KAiIyPVsWNHEyoBALZw/fp1nT9//p6jzlJTU3X79m1dvHhRgYGBmjRpkomVAAAAwMNhiAAAkGWOjo6aO3euxo4dq7Vr12rv3r2SpNOnT+v06dMyDEPNmjXT6NGj5eTkZHItkP2uXLmiF154Qbly5ZIkPfvss5KkP/74Q76+vpKkLl26aM6cOdq0aRNDBMhxVq9erbx58+rHH3+Uu7v7Pddr1qypefPmqUWLFlqyZAlDBMixunbtqtatW2vChAn3XTd37lzt2rWLIQIAyIFSU1M1cuRIrVy5Unfu3HngeoYIAAAA8CRhiAAA8FDy5MmjcePGadCgQdq7d6+io6OVmpqqggULqlatWipSpIjZiYDVODk5pdue2tXVVa6urjp+/Hjac4ZhqGLFivrjjz/MSASs6syZM6pbt26GAwR3eXp6qnbt2mmDZkBOEBYWpv97EuDFixfv+/c8Pj5e4eHh99wHAMgZlixZop9//lmSlC9fPqWmpioxMVGenp5KSEjQ9evXJUnFihVTly5dzEwFAAAAHhpDBACAf8XDw0MtWrQwOwOwqSJFiujEiRPpnitWrJgiIyPTPZeamqqrV6/asAywjaeeeirtDfH7sVgsaTt2ADnB4sWLtXHjxrTHhmFo9+7d2r17933vs1gsql+/vrXzAAAm8Pf3l2EYmjBhglq1aqXly5frs88+04IFC1S0aFHt27dPH374oS5evKiXXnrJ7FwAAADgoTBEAADI1KN+COrm5pYtHcDj4vnnn9eiRYs0d+5cvfHGG7Kzs1OFChW0fPlyhYeHq3r16rp8+bL27dunwoULm50LZLtmzZpp6dKlOnDggKpWrZrhmjNnzigkJEStW7e2bRxgRR9++KFOnTqVtqvA0aNHlS9fPnl6ema43jAM5cqVSyVKlNCgQYNsmQoAsJHjx4+rbNmyatWqlSSpatWqslgsCgsLU9GiRVWjRg1Nnz5dbdq00dy5czVq1CiTiwEAAICsY4gAAJCpOnXq/Ot7DcNQRERENtYA5nvjjTe0cuVKTZo0SQcOHNC0adPUvn17/fzzz+rbt69eeOEF7d+/X9evX+cseORIgwYN0uHDh9W7d2+9//77atmypfLlyydJSkpK0o4dOzRu3Dg9/fTTeuONN+4ZRmO4DE8qT09PrVq1Ku2xt7e3fH19NXHiRBOrAABmunnzpkqWLJn2uGTJkrKzs9PRo0fTnitfvrwqVaqk/fv3m1AIAAAA/HsMEQAAMvUoZ/hy/i9yIi8vL/3www8aNWqUXF1dJUmVK1fWG2+8oR9//DFtq2svLy/169fPzFTAKlq0aKGUlBRdu3ZNY8aM0ZgxY+Tm5iZ7e3tdvXpVd+7cSbf2nxguQ06yYMECPf3002ZnAABM9NRTT+n27dtpjx0dHVW4cGH99ddf6dYVKVJEwcHBts4DAAAAHglDBACATP3fc94BSFWqVNHKlSt169attOc++ugjNW7cWOHh4cqfP7/+97//KU+ePCZWAtZx/vz5tD/fHRa7cuVKlu5luAw5iY+PT9qfY2JitGfPHsXGxsrJyUnu7u7y8fGRh4eHiYUAAGt79tlndeDAAd26dUvOzs6SpBIlSujw4cOyWCwyDEOSFBsby89BAAAAeOIwRAAAsLrvv/9ewcHBmj9/vtkpwCMZNWqUnnnmGXXu3DntjcK7atSooRo1aphUBtgGw2XA/3Pjxg2NGjVK/v7+Sk1NTXfNzs5OzZs316hRo5Q3b16TCgEA1tSsWTOFhoaqW7duGjx4sHx8fPT8888rJCREkydPVr9+/RQQEKD9+/erYsWKZucCAAAAD8XO7AAAQM53/Phx7dmzx+wM4JH5+/trxYoVZmcAj6UbN27o+vXrZmcANpGcnKxevXppzZo1srOz0wsvvKCOHTuqQ4cOqlOnjuzs7LR+/Xq99dZb9wwYAAByhvbt26tGjRo6dOiQ5s2bJ0nq2LGjcufOrTlz5qhatWr66KOPZBiGOnXqZG4sAAAA8JDYiQAAACCLUlJS5OXlZXYGYKqrV69q8uTJSkhI0JQpU9Ke37lzpwYNGqQWLVrok08+Uf78+c2LBKxs2bJlCg8PV7Vq1TRlyhQVKlQo3fULFy7ovffe0/79+7V8+XJ17NjRpFIAgLU4Ojpq3rx5+umnn+Tg8PdbrG5ubpo1a5Y++eQTRUVFydHRUV26dFG7du1MrgUAAAAeDkMEAAAAWdSsWTNt2rRJx44dU9myZc3OAWzu6tWreu2113Tq1CkVK1Ys3bVbt25Jkn799Vf98ccf+vnnn5UnTx4zMgGrW7t2rfLkyaNvv/1WBQoUuOd6oUKF9N1336lx48ZavXo1QwTA/89isXA2PHKUu0MC/1SjRg0FBATo0qVLyps3r3LlymVSHfB44rUAAIAnA0MEAAAAWeTn56dDhw7p1VdfVZ06dVS+fHnly5dPdnYZnxD1xhtv2LgQsK65c+fq1KlTatq0qT799NN011q1aqWXXnpJw4cP16ZNmzRr1iy9//77JpUC1nX8+HH5+PhkOEBwV4ECBeTj46Pw8HAblgHm+PPPP3XhwgU5ODjIy8tLJUqUyHDdp59+ymsDcrSkpCTZ2dnJwcFBTz/9tNk5gFW1bdtW7du3V8uWLZU3b94s38drAQAATwbDwtgfAMDKhgwZIn9/fx05csTsFOCReHt7yzCMtG9NGIaR4TqLxSLDMPg7jxynZcuWSkxMVEBAgBwdHTNck5SUpMaNG8vFxUWbNm2ycSFgG1WqVNGLL76o6dOn33dd//79tXPnTh04cMA2YYANJSUlac6cOVqyZIkuXbqU7lrx4sX15ptvqkOHDibVAbYTFhamRYsWKTg4WAkJCTIMQ+7u7vL19VW3bt3YwQw51t3fj52dndW8eXO1bdtWNWvWNDsLAABkE3YiAAAAyKJXXnkl08EB4L/g3LlzevHFFzMdIJAkJycnPffcc9q+fbsNywDbKl68uMLCwnTz5k25uLhkuObmzZsKCwu75+gPICdITk7WW2+9pdDQUFksFhUsWFBeXl6yWCw6e/asTp8+rREjRig8PFzjx483Oxewmq+//lqzZs1KtzW7xWJRbGysli9frtWrV2v48OEM1CBHWrVqlZYvX65169Zp1apVWr16tUqVKqV27drplVdeue+OTQAA4PHHEAEAAEAW8SY4/uvy5Mmjy5cvP3Dd9evXlTt3bhsUAeZo1qyZpk+fro8++kgTJ06Us7Nzuuu3b9/WRx99pPj4+HvOygZyggULFigkJERly5bV559/rueeey7d9bCwMH366adas2aN6tatKz8/P5NKAesJCAjQzJkzlTt3br399ttq2rSpPD09JUlnzpzRxo0bNWfOHI0ePVrPPvusqlatam4wkM3Kly+vzz77TB9//LECAgL0yy+/KDQ0VF9++aUmT56shg0bqm3btqpfvz7D+AAAPIE4zgAAYHUcZwAAOcPbb7+tHTt26KefflKlSpUyXPPnn3/q1VdfVe3atTV37lwbFwK2kZiYqNatW+vcuXMqUKCAGjZsqKJFi8owDJ05c0Zbt27VpUuXVKxYMa1cufKhzgkGngR+fn6KiYnRxo0b5e7unuGamJgYtWjRQt7e3lq6dKmNCwHr69y5sw4ePKiFCxeqWrVqGa4JCQnRG2+8oYYNG+rbb7+1cSFge+fOndPKlSu1YcMGnThxQoZhqFChQmrbtq3atm0rLy8vsxMBAEAWMUQAALA6hgiQ0xw/flxnz55VUlJSuq1LU1NTdfv2bV28eFGbN2/WkiVLTKwEst/OnTvVq1cvubm5adCgQWrYsGHah0eXL1/Wtm3bNHnyZF26dEnfffedXnrpJZOLAes5f/68Bg4cqAMHDkhS2jfs7r4uVKlSRZMnT1aRIkXMSgSspmrVqqpbt+4DPxTt27ev9u7dq3379tmoDLCdWrVqqWLFipo3b95913Xt2lV//fWXgoODbRMGPAYuX76s2bNna/78+UpNTZUk2dvbq1GjRho0aJBKlixpbiAAAHggjjMAAADIotu3b+udd97R7t2777vOYrGwXSNypHr16ql3796aPXu2RowYoREjRsjB4e9fKVJSUiT9/ff/zTffZIAAOV7hwoW1bNky7du3T3v27FFsbKxSU1NVqFAh+fj4qGbNmmYnAlbz1FNP6fr16w9cZ7FYlCtXLhsUAebIkyfPA9fkz59fSUlJNqgBzHX79m1t2rRJq1ev1p49e3Tnzh0ZhqEXX3xRtWrV0rp16xQQEKCgoCDNnj2bn5UAAHjMMUQAAACQRT/88IN27dole3t7Pfvss4qPj1dMTIxq1qyp+Ph4HT9+XHfu3FHp0qU1aNAgs3MBq/jggw9Uq1YtLVy4UHv27NHt27clSY6Ojqpatap69OihRo0amVwJ2E6NGjVUo0YNszMAm2rWrJmWLl2qAwcOZHrO+5kzZxQSEqLWrVvbNg6wkVq1aikkJEQXL17M9FiPGzduKCwsjNcJ5Gjh4eFatWqVNmzYoMTERFkslrQjDNq1a5d2hMFbb72lWbNmafLkyfriiy+0cuVKk8sBAMD9cJwBAMDqOM4AOcWrr76qI0eOaP78+fLx8dHatWv10Ucfyd/fX2XKlFF0dLT69++vP//8U8uXL1f58uXNTgas7sqVK7pz547c3NzSdiUA/ksuXbqUNkyTGc7/RU5z48YN9ezZU8ePH9f777+vli1bKl++fJKkpKQk7dixQ+PGjZPFYtHcuXOVP3/+dPe7ubmZUA1kr6ioKHXs2FEFCxbUV199pWeeeSbd9cuXL+ujjz7Svn37tHTpUpUrV86kUsA6Zs6cqZUrVyoqKkoWi0X29vaqX7++OnToIF9fX9nZ2d1zj8ViUZUqVWRvb6/9+/ebUA0AALKKIQIAgNX9/PPP2r9/v8aNG2d2CvBIatSoodKlS2v58uWSpJMnT+p///ufxowZo/bt20v6+1t3zZs3V4sWLfTll1+amQtku+nTp8vb21uNGze+77rly5dr3759Gj9+vI3KANtKTU3VlClTtGzZMl27du2+aw3DUEREhI3KANto0KCBUlJSdPHixbQjnNzc3GRvb6+rV6/qzp07md7LvxPIKT788EOdO3dO+/btk2EYevbZZ1WyZEnZ29vr/PnzOnz4sJKTk5UvXz4VLFgw3b2GYWjt2rUmlQPZw9vbW9Lfw5Lt2rVT27ZtVahQofvek5SUpFq1asnHx0ezZ8+2RSYAAPiX+KoQACBTf/zxxyPdX7FiRUlShw4d1KFDh+xIAkx1+/btdN8mLVGihBwcHHT06NG054oVK6YqVarw5jhypOnTp6tVq1YPHCLYvn27goKCGCJAjjVv3jzNmjVLkmRnZ6fcuXOnfZAK/BecP38+7c93v5ty5cqVLN3Ld1mQU/xzCMBisejo0aPpfi+4Kz4+XvHx8eme4zUDOUGTJk3UsWNH1a1bN8t/p52cnHTw4EErlwEAgOzAEAEAIFNt27b9129u8A0j5ERubm66fv162mM7Ozt5enrq+PHj6dZ5eHhk+AYi8KSZM2eObt26le65o0ePavr06Znek5CQoKCgILm4uFg7DzDNihUrZG9vr/Hjx6t58+ZydHQ0OwmwqcjISLMTANMtWLDA7ATAVMnJyQoODla9evXMTgEAAFbAEAEAIFOc3wukV758eYWFheny5csqUKCAJKlkyZLav3+/kpKS5OTkJOnvIw34QAk5wfXr1/X999+nDZQZhqE///xTf/75Z6b33P2Gadu2bW3SCJjh3Llzev755+Xn52d2CgDAJD4+Pv/qvt9++01Hjx791/cDj4s9e/YoISHB7AwAAGAlDBEAADK1ZcsWsxOAx0rr1q0VFBSkjh076v3331eLFi3k6+uroKAgDR8+XG+99ZZ+++03RUREqHr16mbnAo+sT58+unnzZtpgwIIFC1SmTBnVrVs3w/WGYShXrlwqUaKEWrdubctUwKbc3d3NTgAeG8ePH1dwcLAuXLgge3t7FSlSRC+++KIKFy5sdhrwWAoICJC/v7/69+9vdgrwSOzt7ZUvXz6zMwAAgJUwRAAAyLJRo0apbNmyev31181OAUzx8ssva/PmzdqwYYM2btyoFi1aqG3btpo5c6bWrl2bdi6qYRjq2bOnybXAo3NxcdEnn3yS9njBggWqWLGihg4damIVYD4/Pz/NmzdPZ8+eVdGiRc3OAUxx5swZDR8+XKGhoZL+3onmn0ehtWjRQsOGDVP+/PnNSgQAWFG7du20cOFC7dy5kyMNAADIgQzL3a8VAQDwALVq1VKxYsW0cuVKs1MAU23dulW3b99W8+bNJUknT57UqFGjtH//fuXPn1+9evVSly5dTK4EHh/jxo3T5s2bFRgYaHYKkC2SkpLUs2dPnT17Vv369VOFChXu+0EpR0Qhp4mLi1P79u11/vx5ubm5qV69evLy8pLFYtHZs2e1a9cuJSQkqEKFClqyZImcnZ3NTgYeG0OGDJG/v7+OHDlidgrwSFavXq1Zs2bp5MmTKl26tLy9veXq6io7O7sM1w8bNszGhQAA4FGwEwEAIMtSUlJ4ExyQ9NJLL6V7XKpUKc2bN8+cGOAJcPnyZZ07d87sDCDbODo6qlKlSgoLC9Nnn31237WGYSgiIsJGZYBtzJw5U+fPn1fLli01duzYe4YEEhMT9fHHHyswMFDz589Xnz59TCoFAFjLxx9/LMMwZLFYdPz4cR0/fjzTtYZhMEQAAMAThiECAECWNWvWTJs2bdKxY8dUtmxZs3MAAABMMWPGDM2fP1/S31u4582bN9027kBOt3XrVnl6emrcuHFydHS853qePHk0adIkNWrUSGvXrmWIAAByoH79+vHzDwAAORhDBACALPPz89OhQ4f06quvqk6dOipfvrzy5cuX6VZ1b7zxho0LAetLTk7Wjh07dOTIEV27dk137tzJdC3ftACAnGnlypWys7PTyJEj1bp1azk5OZmdBNhUXFycGjZsmOEAwV25cuVS9erVtWPHDhuWAQBs5d133zU7AQAAWBFDBACALHvzzTfTtqrbsWOHgoKCMlxnsVhkGAZDBMhxrl27pq5du+ro0aOS/v67nhm2awSAnCs2Nla1a9dW+/btzU4BTOHl5aXTp08/cN3Fixfl4eFhgyIAwOPgzp07SklJUa5cucxOAQAAj4ghAgBAlr3yyitsVYf/tKlTpyoyMlIuLi5q2rSpPD095eDAj1MA8F/j7u5+329gAznd66+/ri+++EKLFy9W586dM1yzY8cOhYeHa9CgQTauAwDYUmRkpH744QeFhIQoLi5OrVq10oQJEzRs2DAVL15cb775puzt7c3OBAAAD4l3vQEAWTZ+/HizEwBTbd68WS4uLlqzZo2KFy9udg4AwCTNmjXT0qVLFR0dLS8vL7NzAJtr0KCBQkNDNXbsWO3du1ctW7ZUyZIlZWdnpwsXLmjr1q1aunSpvLy8VLRoUQUEBKS7v2nTpiaVAwCy0/LlyzVq1CilpKSkPXd3x74DBw5oxYoVOnjwoKZNm5bpUZgAAODxxBABACDL/vjjj4daX7FiRSuVAOaIi4tTnTp1GCAAgP+4/v37KzQ0VF27dtU777yjqlWrytXVNdPdadzc3GwbCFhZ06ZN044527RpkzZt2nTPGovFopiYGH3wwQf3XDty5IgtMgEAVnTgwAGNGDFCefLkUd++feXr66uWLVumXR84cKDGjBmjLVu26Ndff1Xr1q1NrAUAAA+LIQIAQJa1bdv2oY4z4M1B5DSc6QsAkKRXX31Vt27dUmxsrIYNG3bftYZhKCIiwkZlgG3UqlXL7AQAgMlmz54tSZo5c6aqV69+z/XGjRurVKlSatWqlZYvX84QAQAATxiGCAAAWZbZdr2pqamKj4/XzZs3JUk+Pj5yd3e3ZRpgE40aNdLy5ct18eJF/o4DwH/Y6dOns7z27pa+QE6ycOFCsxMAACYLDw9X1apVMxwguKtMmTKqUaOGTpw4YcMyAACQHRgiAABk2ZYtW+57PTIyUiNGjFBMTIymTZtmoyrAdvr166ft27frzTff1Keffqpq1arJ0dHR7CwAgI1FRkaanQA8Fq5fv67z588rKSkp3cBMamqqbt++rYsXL2rz5s368ssvTawEHi/58+eXp6en2RnAI7t+/XqWhuufeuopJSQk2KAIAABkJ4YIAADZxtvbWzNmzFCjRo00bdq0B27vCzzuMvpGRUpKipKTk9W9e3dJkrOzc4bHfBiGoX379lm9EQAAwNZSU1M1cuRIrVy5Unfu3HngeoYIkNMdP35cwcHBunDhguzt7VWkSBG9+OKLKly48D1rhw4dqqFDh5pQCWSvggUL6ujRow9cd/ToUY4GBADgCcQQAQAgWxUoUEA+Pj4KDAxkiABPvBs3bjxwzd1jPAAA/01RUVEKDQ1VdHS0SpcuLT8/P4WFhalSpUpydnY2Ow+wiiVLlujnn3+WJOXLl0+pqalKTEyUp6enEhISdP36dUlSsWLF1KVLFzNTAas6c+aMhg8frtDQUEl/H2HzzwHjFi1aaNiwYcqfP79ZiYDV1K1bV8uXL9fixYvVuXPnDNcsXrxYZ8+eVYcOHWxcBwAAHhVDBAAAq7h8+bLZCcAj27x5s9kJQI7QtGlTlShRwuwMIFvFx8dr+PDhCgwMTNvG3c/PT35+fpo0aZJOnTqladOmqVatWiaXAtnP399fhmFowoQJatWqlZYvX67PPvtMCxYsUNGiRbVv3z59+OGHunjxol566SWzcwGriIuLU9euXXX+/Hm5ubmpXr168vLyksVi0dmzZ7Vr1y6tW7dOJ0+e1JIlSxgsQ47Tp08frVu3TmPHjtX+/fv1wgsvSPr7/aCNGzdq27ZtWrNmjVxcXPTmm2+aXAsAAB4WQwQAgGz1119/KTg4OMNtG4EnTZEiRbK8NjU1VXZ2dlasAR4fcXFxWrJkiUJCQhQTE6MGDRpo5MiRmjJlip599lm1aNEi3fomTZqoSZMmJtUC2e/mzZvq3r27IiMj03Zh2rhxY9p1Z2dnXb16VW+99ZbWrFmj4sWLm1gLZL/jx4+rbNmyatWqlSSpatWqslgsCgsLU9GiRVWjRg1Nnz5dbdq00dy5czVq1CiTi4HsN3PmTJ0/f14tW7bU2LFj7xkSSExM1Mcff6zAwEDNnz9fffr0MakUsI4iRYrou+++04ABA+Tv769169bJMAzt2rVLu3btksViUZ48eTR58mQGigEAeAIxRAAAyLKxY8dmeu3OnTu6dOmSgoKClJycrObNm9uwDLCdpKQkzZs3T7GxsemO7Ni6das+++wzdejQQW+//bacnJxMrASsZ/v27frggw+UmJiYtmXv3aM/tm7dqpkzZ2rfvn0aPny4yaWA9fz444+KjIyUn5+fRo8eLRcXF3l7e6ddnzdvniZNmqQ5c+bwASpypJs3b6pkyZJpj0uWLCk7O7t0Z2OXL19elSpV0v79+00oBKxv69at8vT01Lhx4+To6HjP9Tx58mjSpElq1KiR1q5dyxABcqTatWsrICBAy5cvTxswTk1NlYeHh3x8fNSxY0d5eHiYnQkAAP4FhggAAFm2aNEiGYaRtmVvZqpWrcobJMiRbt68qTfffFP79++/51ulcXFxunTpkr7//nvt3btX8+bNk4MDP2ohZzl+/LgGDBigO3fuqFOnTvL19U333/v27dvrm2++0ZIlS1S3bl01bNjQxFrAejZs2CB3d3d9/vnnmQ6NDRo0SOvXr9eePXtsXAdY31NPPaXbt2+nPXZ0dFThwoX1119/pVtXpEgRBQcH2zoPsIm4uDg1bNgwwwGCu3LlyqXq1atrx44dNiwDbMvV1VW9evVSr169zE4BAADZiHe2AQBZ1r9//0yvGYahPHnyqFy5cnr++edlGIYNywDbWLRokcLDw1W1alUNHTo03bXXXntNNWrU0MiRI7Vv3z79+OOP6t27t0mlgHXMmDFDSUlJmjZtmho3bnzP9S5duqh8+fLq0qWLFi9ezBABcqyoqCj5+vred9cZOzs7VaxYUUFBQTYsA2zj2Wef1YEDB3Tr1q20LdxLlCihw4cPp+1SI0mxsbEPHEAGnlReXl46ffr0A9ddvHiRb2IDAADgicMQAQAgy+43RAD8F/j7+6tAgQKaO3eu8uTJc8/1smXL6vvvv1eTJk20du1ahgiQ44SEhKhChQoZDhDcVaNGDVWpUuWeb6MCOYmjo6OuXLnywHWXL1++7zdUgSdVs2bNFBoaqm7dumnw4MHy8fHR888/r5CQEE2ePFn9+vVTQECA9u/fr4oVK5qdC1jF66+/ri+++EKLFy9W586dM1yzY8cOhYeHa9CgQTauA6zvfkdeZuSfxwECAIDHH0MEAAAAWXTmzBm98MILGQ4Q3PXUU0+patWq2r17tw3LANuIj49X9erVH7jOw8NDf/zxhw2KAHOUK1dOhw8fVkxMjDw9PTNcc/bsWR0+fFiVK1e2cR1gfe3bt9e6deu0b98+zZs3L+3c61mzZmnOnDmaM2eOpL93K+vUqZPJtYB1NGjQQKGhoRo7dqz27t2rli1bqmTJkrKzs9OFCxe0detWLV26VF5eXipatKgCAgLS3d+0aVOTyoHs8aAjL+/uSnN3hxqGCAAAeLIwRAAAAJBFuXLl0o0bNx647s6dO3zzFDlS/vz5dfLkyQeuO3HihAoUKGCDIsAc7dq10yeffKL+/ftr8uTJKlGiRLrrp0+f1qBBg5SUlKTWrVubVAlYj6Ojo+bNm6effvpJDg5/v7Xk5uamWbNm6ZNPPlFUVJQcHR3VpUsXtWvXzuRawDqaNm2a9gHqpk2btGnTpnvWWCwWxcTE6IMPPrjn2pEjR2yRCVhNZrtV3rlzR/Hx8dq/f7+OHDmiNm3aqEWLFjauAwAAj4ohAgAAgCwqV66cwsLCdObMGRUrVizDNefPn9fevXvZuhc5ko+Pj9atW6fffvtNTZo0yXDNpk2bdPz4cbVs2dLGdYDttGnTRps3b1ZgYKCaN28uT09PGYah4OBgtWzZUqdOnVJKSorq1q3LB6jIse4OCfxTjRo1FBAQoEuXLilv3rzKlSuXSXWA9dWqVcvsBMBUWTnycsaMGZo+fbrat29vgyIAAJCdDEtm+w0BAAAgnfXr12vQoEEqXry4RowYoRdeeCFti0ZJCg0N1ejRo3XixAmNGzdOr7zyinmxgBX8+eefatu2rSSpZ8+eeuGFF9S9e3c1bdpUvXv31rZt2zR79mylpqbqp59+YpgGOVpqaqq+++47LViwQAkJCemuubi4qFOnTho4cKCcnJxMKgQAADBfkyZNVKJEibSjbgAAwJOBIQIAAICH8MEHH2jdunUyDEPOzs4qWLCgDMNQbGysbt68KYvFohYtWmjy5MlmpwJWsW7dOg0dOlRJSUn3XLNYLHJwcNCIESP4thFytLfffltlypTR4MGDlZycrIiICEVHR8tiscjDw0OVK1eWs7Oz2ZkAAACmGzBggIKDg7V3716zUwAAwENgiAAAAOAhLV26VAsXLtSJEyfSPe/l5aUePXqoa9eu6XYoAHKaU6dOaf78+QoJCVFMTIxSU1Pl4eEhHx8fde/eXd7e3mYnAlZVvXp1eXt7a8mSJWanAABMlpCQIH9/f4WEhOjChQuyt7eXl5eX6tevr2bNmnGsB/7zXn31VZ08eVL79+83OwUAADwEhggAAAD+pbi4OF24cEF37tyRh4eHvLy8Mlx39epV3bhxI9PrAIAnS61atVSjRg19//33ZqcAAEy0detWDR06VFevXtX/fYvVMAwVK1ZMX331lSpXrmxSIWCexMRE/fjjj5o+fbqqV6/O8CUAAE8YB7MDAAAAnlQeHh7y8PB44LrPP/9c69atU0REhA2qAOv55JNPVL169QceVTBz5kzt2rVLCxYssFEZYFvt2rXTwoULtXPnTtWrV8/sHACACSIiIvTee+8pKSlJL774opo2bSpPT09ZLBadPXtWGzduVGhoqN566y2tWLGCgWLkONWrV8/0Wmpqqm7fvi3p74Ga7t272yoLAABkE4YIAAAAbIDNn5ATrFq1Snfu3HngEMH+/ft14MAB20QBJihXrpyKFy+u3r17q3Tp0vL29parq6vs7OwyXD9s2DAbFwIArO37779XUlKShg8frs6dO99zvVOnTpo9e7a++uorzZ49WyNGjDChErCeGzduPHCNp6enevfurWbNmtmgCAAAZCeOMwAAALCyIUOGyN/fX0eOHDE7BXgoX3zxha5du5b2eNWqVSpevLhq1KiR6T0JCQnasmWL3N3dFRQUZItMwOa8vb1lGEaWBsQMw+C//wCQA9WrV08FCxbUypUr77vOz89P169f19atW21UBtjGuXPnMr1mZ2en3Llzy9XV1YZFAAAgO7ETAQAAAIAMeXl5afz48WmPDcNQVFSUoqKiHnhvx44drZkGmKpfv34yDMPsDACAia5fv37fwcq7ypQpo23btlk/CLCxIkWKmJ0AAACsiCECAAAAABnq0qWL7O3tlZqaKovFovHjx6tSpUry8/PLcL1hGMqVK5dKlCih559/3sa1gO28++67ZicAAExWrlw5HTx4UMnJyXJ0dMx03dGjR1WmTBkblgEAAACPjiECAAAAABlycHBQ165d0x4vWLBANWvWVPfu3U2sAgAAMN+7776r3r1769NPP9XYsWPl5OR0z5qpU6fq1KlTmjp1qgmFgHX17dv3X99rGIZmzJiRjTUAACC7MUQAAAAAIEu2bNlidgIAAMBj4fz582rQoIF+/fVX7dmzR02aNFHJkiVlb2+v8+fPa/v27YqMjFThwoUVGhqq0NDQdPcPGzbMpHIge9w9psMwDFkslgzXZHaNY6EAAHj8GZbMXuEBAACQLYYMGSJ/f38dOXLE7BQgW1y5ckU//fSTQkJCFBsbKycnJz399NOqU6eOWrduLQ8PD7MTAQAArMrb2/ueD0jvfjD6oLdbDcPgdwM88Y4dO6bp06dr06ZNqlevnvz8/FSqVCk5OjrqwoUL2rx5s1auXKnChQvrnXfekZ2dXbr727RpY1I5AADICnYiAAAAAJBle/bs0bvvvquEhIR73iDfvXu35syZo6+//lp16tQxqRAAAMD6+vXrx7ep8Z928OBBBQQE6IMPPlDv3r3TXStfvrwaNGigevXq6b333lNiYqK6detmUikAAPg32IkAAADAytiJADnFuXPn1Lp1a12/fl0NGjSQn5+fihUrJovFoqioKP3666/asWOHXF1dtXr1anl6epqdDAAAAMAKWrVqJYvFol9//fW+61577TXFx8drw4YNNioDAADZwe7BSwAAAABAmj17tq5fv65Bgwbp+++/18svv6znnntOVapUkZ+fn2bNmqX3339f8fHxmj9/vtm5AAAAAKzk9OnTKlOmzAPXFSpUSOfOnbNBEQAAyE4cZwAAAAAgS4KCglSiRAm99dZbma7p06ePVqxYoa1bt+rjjz+2YR0AAIBtpaSkaNeuXTp79qySk5PTHfWUmpqq27dv6+LFi9q2bZu2bNliYimQ/QoUKKCIiAhZLJZMj/ZISkrSgQMHVKhQIRvXAQCAR8UQAQAAgJVxehRyitjYWDVq1OiB6ypUqKCtW7faoAgAAMAcV69eVdeuXfXXX3/dd939PmAFnmT169fXzz//rM8//1yffPKJ7O3t011PSkrSsGHDFBsbq969e5tUCQAA/i2GCAAAAKzs7bffVocOHczOAB5Z7ty5denSpQeuu3TpkpydnW1QBAAAYI7Zs2fr2LFjyps3r55//nmdPXtWf/75p/z8/JSQkKDw8HDFx8erbNmy+vLLL83OBbJd3759FRAQoMWLF2vLli2qX7++vLy8JElnz57V1q1bFRcXpzJlyqhPnz4m1wIAgIfFEAEAAEAmxo4d+0j3Dxs2TJJUpkyZLJ0VCTzuKlWqpNDQUEVGRsrb2zvDNZGRkQoPD9fzzz9v4zoAAADb2b59uxwcHPTTTz+pTJky2rhxo95//311795dFSpUUGJiogYMGKDdu3crISHB7Fwg23l6eurHH3/URx99pKNHj2rZsmVpu27c3Y2vbt26Gj9+vPLkyWNmKgAA+BcMC/vrAgAAZMjb21uGYfyr4wgMw9CRI0esUAWYJzAwUP3795eHh4eGDx+uRo0apW1beufOHW3ZskWjR4/WxYsXNXXqVDVp0sTkYgAAAOuoVq2aKlSooMWLF0v6+5vXjRs31vDhw9W5c2dJ0uXLl9WgQQP5+vpq2rRpZuYCVmOxWLRv3z7t2bNHcXFxkiQvLy/VrVtXFSpUMLkOAAD8W+xEAAAAkIn+/fubnQA8Vho3bqwOHTro559/1nvvvadcuXKpUKFCMgxD58+f1+3bt2WxWNSuXTsGCAAAQI6WkpIiDw+PtMdFihSRk5OTjh07lvZcgQIFVK1atXTPATmNYRiqWbOmatasmaX148aN0+bNmxUYGGjlMgAA8CgYIgAAAMgEQwTAvUaPHq0KFSpo7ty5OnPmjE6fPp12rXjx4nrjjTfUqVMnEwsBAACsr0CBArp8+XLaY8Mw5OXlpb/++ivdOjc3Nx06dMjWecBj6/Llyzp37pzZGQAA4AEYIgAAAADwUF577TW99tprunDhgi5cuCCLxaJChQqpcOHCZqcBAADYROXKlbVt2zadPHlSpUqVkiSVLl1au3fv1vXr15U3b15J0rFjxzgPHgAAAE8chggAAAAeQkpKinbt2qWzZ88qOTlZFosl7Vpqaqpu376tixcvatu2bdqyZYuJpYD1FSpUSIUKFTI7AwAAwObat2+vwMBAvfbaa+rXr5+6deumpk2basuWLXrvvffUrVs3bd68WSdOnFDdunXNzgUAAAAeCkMEAAAAWXT16lV17dr1ni1K/y+LxSLDMGxUBdhWUlKSduzYoZMnT+r27dv3XcuRIAAAIKfy9fVVr169NHfuXO3fv1/dunXTyy+/rFmzZmnXrl3avXu3LBaL7Ozs1LdvX7NzAQAAgIfCEAEAAEAWzZ49W8eOHVPevHn1/PPP6+zZs/rzzz/l5+enhIQEhYeHKz4+XmXLltWXX35pdi6Q7S5cuKDXX39d0dHR9113d5CGIQIAAJCTDR48WH5+frp69aokydHRUYsWLdJXX32l/fv3K3/+/OrZs6dq1aplbigAAADwkBgiAAAAyKLt27fLwcFBP/30k8qUKaONGzfq/fffV/fu3VWhQgUlJiZqwIAB2r17txISEszOBbLdxIkTde7cObm7u+uFF16Qq6sru24AAID/tHLlyqV7XKBAAX3++eeZrg8MDFRkZCTDlgAAAHisMUQAAACQRefOnVOVKlVUpkwZSVKlSpVksVi0f/9+VahQQXny5NGXX36pBg0aaOHChfLx8TG5GMhee/fuVYECBeTv7y83NzezcwAAAJ44mzZtkr+/P0MEAAAAeKzZmR0AAADwpEhJSZGHh0fa4yJFisjJyUnHjh1Le65AgQKqVq1auueAnOLatWuqWbMmAwQAAAAAAABADsYQAQAAQBYVKFBAly9fTntsGIa8vLz0119/pVvn5uamCxcu2DoPsDpvb2+dOXPG7AwAAAAAAAAAVsQQAQAAQBZVrlxZ4eHhOnnyZNpzpUuX1uHDh3X9+vW0544dO6Y8efKYkQhYVZ8+fXTkyBH9/PPPZqcAAAAAAAAAsBIHswMAAACeFO3bt1dgYKBee+019evXT926dVPTpk21ZcsWvffee+rWrZs2b96sEydOqG7dumbnAtmuQYMG+vjjjzVixAitXLlSlSpVuu/RBpz1CwAAAAAAADx5GCIAAADIIl9fX/Xq1Utz587V/v371a1bN7388suaNWuWdu3apd27d8tiscjOzk59+/Y1OxfIdufOndOiRYtksVh04MABHThwQIZh3LPOYrHIMAyGCAAAAAAAAIAnEEMEAAAAD2Hw4MHy8/PT1atXJUmOjo5atGiRvvrqK+3fv1/58+dXz549VatWLXNDASuYMGGCzp49q3z58unFF19UgQIFMhwiAAAAAICMNG3aVCVKlDA7AwAAPIBhsVgsZkcAAAAAePzVrl1bjo6OWrt2rQoUKGB2DgAAwBNnyJAh8vf315EjR8xOAR7ZnTt3FBAQoIoVK6p48eKSpO3bt2vixImKjo5WlSpV9Mknn6hcuXImlwIAgIdlZ3YAAAAAgCdDUlKSqlWrxgABAAAA8B93/fp1tW/fXoMGDVJYWJgk6cyZM+rfv7+OHz+umzdvKiQkRF27dlVMTIzJtQAA4GFxnAEAAEAm+vbtK8MwNHLkSBUqVEh9+/bN8r2GYWjGjBlWrANsr2zZsjp37pzZGQAAAABMNn/+fEVEROiZZ55RyZIlJUk//fSTkpOT1bhxY33yySdavXq1pk2bptmzZ+uzzz4zNxgAADwUhggAAAAysW3bNhmGoRs3bqQ9zirOiUdO1KNHDw0aNEirVq1SmzZtzM4BAAAAYJLAwEC5urpq6dKleuqpp9KeMwxD/fv3V5EiRdSvXz+tX79eQUFBJtcCAICHxRABAABAJsaNGydJ8vDwSPcY+K8qXLiwGjRooKFDh+qXX35R1apV5erqKkdHxwzXv/HGGzYuBAAAAGALp0+fVu3atdMGCKKjo3Xq1Cm5u7vL29s7bV2ZMmUeaiAfAAA8HhgiAAAAyMT//aY137zGf93rr78uwzBksVi0b98+hYeHZ7jOYrHIMAyGCAAAAP6P/Pnzy9PT0+wM4JEZhiE7O7u0xzt37pQk1a5dO926xMRE2dvb27QNAAA8OoYIAAAAHtKBAwd04sQJvfrqq2nPhYWFaeHChXrttddUp04dE+sA63nllVc4qgMAAOD/iIqKUmhoqKKjo1W6dGn5+fkpLCxMlSpVkrOzc7q1Q4cO1dChQ00qBbJPsWLFdPjwYaWmpsrOzk6//fabDMPQiy++mLbm4sWLCg8PV6lSpUwsBQAA/wZDBAAAAA9h/Pjxmj9/vsqWLZtuiOD48ePatGmTAgIC1KNHD3300UcmVgLWMX78eLMTAAAAHhvx8fEaPny4AgMDZbFYJEl+fn7y8/PTpEmTdOrUKU2bNk21atUyuRTIfvXq1dOcOXP0xhtv6Omnn1ZQUJBcXFzUqFEjSdK6des0ffp03bp1S82bNze5FgAAPCy7By8BAACAJK1fv17z5s2Tq6trugECSWrcuLGGDx8uNzc3zZs3T5s2bTKpEgAAAIC13bx5U927d1dAQIDc3NzUrFmztEECSXJ2dtbVq1f11ltvKSoqysRSwDr69u2rcuXKKTQ0VOvXr5ckDRkyRE899ZQk6csvv9TJkyf14osvqkePHiaWAgCAf8Ow/POnWwAAAGTq9ddf1+HDh7V69WqVLl06wzUnTpxQ69atVbVqVS1cuNDGhYBtxMXFacmSJQoJCVFMTIwaNGigkSNHasqUKSpbtqxefvllsxMBAACs6rvvvtPUqVPl5+en0aNHy8XFRd7e3mrVqpUmTpwoSZo0aZLmzJmjjh07atSoUSYXA9kvKSlJGzduVGxsrHx8fPTcc8+lXfvmm29UrFgxvfLKK7Kz47uMAAA8aTjOAAAAIItOnjyp2rVrZzpAIEmlS5dWzZo1deDAAduFATa0fft2ffDBB0pMTJTFYpFhGLpx44YkaevWrZo5c6bCw8M1fPhwk0sBAACsZ8OGDXJ3d9fnn38uJyenDNcMGjRI69ev1549e2xcB9iGk5OTWrVqleG19957z8Y1AAAgOzECCAAAkEVJSUmZvkH4T3nz5hWbPSEnOn78uAYMGKBbt26pU6dOmjlzZrq/6+3bt1fevHm1ZMkSbdmyxcRSAAAA64qKilL16tXv+/uBnZ2dKlasqJiYGBuWAQAAAI+OnQgAAACyqESJEgoLC9ONGzeUO3fuDNfcvn1b4eHhKlasmI3rAOubMWOGkpKSNG3aNDVu3Pie6126dFH58uXVpUsXLV68WA0bNjShEgAAwPocHR115cqVB667fPmyHB0dbVAE2F5YWJhmzZqlyMhI3bx5U3fu3MlwnWEY2rdvn43rAADAo2AnAgAAgCxq0aKF4uPjNWjQICUkJNxzPTExUUOGDNHly5f1v//9z4RCwLpCQkJUoUKFDAcI7qpRo4aqVKmiv/76y4ZlAAAAtlWuXDkdPnz4vrsMnD17VocPH1a5cuVsWAbYRlhYmHr06KGgoCDFxsbq2rVrunHjRob/S0xMNDsXAAA8JHYiAAAAyKKuXbtq7dq12rZtm3x9fVWjRg15eXlJks6fP5+2S0HZsmXVo0cPc2MBK4iPj1f16tUfuM7Dw0N//PGHDYoAAADM0a5dO33yySfq37+/Jk+erBIlSqS7fvr0aQ0aNEhJSUlq3bq1SZWA9cycOVMpKSlq2rSpunXrpoIFC8re3t7sLAAAkE0YIgAAAMiiXLlyad68eRozZow2bdqknTt3prtuGIYaN26s0aNHZ3rcAfAky58/v06ePPnAdSdOnFCBAgVsUAQAAGCONm3aaPPmzQoMDFTz5s3l6ekpwzAUHBysli1b6tSpU0pJSVHdunXVrl07s3OBbHfgwAEVL15c33zzjQzDMDsHAABkM4YIAAAAHkKBAgX09ddf69KlSwoJCdGFCxeUkpKiggULqmbNmipatKjZiYDV+Pj4aN26dfrtt9/UpEmTDNds2rRJx48fV8uWLW1cBwAAYFtTp07Vd999pwULFig6OlqSFBcXp7i4OLm4uKhbt24aOHAgH7AiR0pJSZG3tzd/vwEAyKEMi8ViMTsCAAAAwOPvzz//VNu2bSVJPXv21AsvvKDu3buradOm6t27t7Zt26bZs2crNTVVP/30kypWrGhyMQAAgPUlJycrIiJC0dHRslgs8vDwUOXKleXs7Gx2GmA17dq1U0pKilavXm12CgAAsAKGCAAAAP6F4OBghYSEKCYmRpUqVVK3bt20adMmPffcc/L09DQ7D7CadevWaejQoUpKSrrnmsVikYODg0aMGKH27dubUAcAAGAbe/fu1dNPP63SpUvfd93BgwcVGRmpjh072qgMsI0VK1bo008/1dSpU9W0aVOzcwAAQDZjiAAAAOAhnDlzRu+//77++OMPWSwWGYYhPz8/TZw4UR06dFBERIQmTpyoFi1amJ0KWM2pU6c0f/78tEGa1NRUeXh4yMfHR927d5e3t7fZiQAAAFbl7e2t1q1ba8KECfddN2DAAO3atUv79u2zURlgGxcuXNAXX3yhLVu2qGXLlqpevbry5cuX6fEGDBoAAPBkcTA7AAAA4Elx9epVde/eXdHR0Spbtqzq16+vuXPnpl0vUaKEDh06pCFDhqhUqVIqX768ibVA9ouMjFTZsmVVsmRJjRgxwuwcAAAAmwkLC9P//S7WxYsXtXfv3kzviY+PV3h4+D33ATmBr6+vDMOQxWLR6tWrH3iswZEjR2wTBgAAsgVDBAAAAFk0a9YsRUdHq3fv3ho0aJAMw0g3RPDll1+qatWqGjNmjH744Qd9+eWXJtYC2e/dd9+Vo6Oj1q9fb3YKAACATS1evFgbN25Me2wYhnbv3q3du3ff9z6LxaL69etbOw+wuVq1apmdAAAArIghAgAAgCzavHmzihQpkjZAkJHOnTtr0aJFOnjwoI3rAOs7f/48b4IDAID/pA8//FCnTp1K21Xg6NGjypcvnzw9PTNcbxiGcuXKpRIlSmjQoEG2TAVsYuHChWYnAAAAK2KIAAAAIItiYmL00ksvZTpAcFfZsmW1fft2G1UBtuPl5aWzZ8+anQEAAGBznp6eWrVqVdpjb29v+fr6auLEiSZWAbZz9erVR7rfzc0tWzoAAIBtMEQAAACQRS4uLoqNjX3guvPnz8vZ2dkGRYBtffbZZ+rXr58GDx6sbt26ydvbW05OTmZnAQAA2NyCBQv09NNPm50B2EydOnX+9b2GYSgiIiIbawAAgLUxRAAAAJBFlSpVUmhoqI4dO6ayZctmuCYyMlIRERGqXbu2jesA65s7d66efvpprVu3TuvWrZMkOTs7Z7g7h2EY2rdvn60TAQAAbMLHxyftzzExMdqzZ49iY2Pl5OQkd3d3+fj4yMPDw8RCIHvdPcojM46OjipcuLDs7e0VFxenxMRESZK7u7ty585ti0QAAJCNGCIAAADIotdff127du3S22+/rdGjR6d741CSQkNDNWzYMN25c0cdO3Y0qRKwnt27d9/z3M2bN00oAQAAMN+NGzc0atQo+fv7KzU1Nd01Ozs7NW/eXKNGjVLevHlNKgSyT2RkZLrHCQkJ6ty5sxISEjR06FA1bNhQjo6OadeDg4M1atQoWSwWLVq0yNa5AADgERmWB40QAgAAIM3YsWO1aNEiGYYhe3t73blzR3ny5FFqaqpu3rwpi8WiNm3aaNy4cWanAtnu3LlzD7W+SJEiVioBAAAwV3Jysrp3767w8HA5OjrKx8dHxYoVk8Vi0ZkzZ7R3716lpKSoWrVqWrRokezs7MxOBrLVmDFj9Msvv2j16tUqVapUhmtiYmLUokULNWnSRBMnTrRxIQAAeBTsRAAAAPAQhg0bpkqVKmn27Nk6fvy4JOn69euS/v7AtGfPnurcubOZiYDV/NuhgJ9//ln79+9nuAYAAOQYy5YtU3h4uKpVq6YpU6aoUKFC6a5fuHBB7733nvbv36/ly5ezUxlynE2bNsnHxyfTAQJJ8vT0VO3atbVjxw4blgEAgOzAEAEAAMBDeuWVV/TKK6/o4sWLio6OlsVikYeHh7y8vMxOAx5Le/fulb+/P0MEAAAgx1i7dq3y5Mmjb7/9VgUKFLjneqFChfTdd9+pcePGWr16NUMEyHESExPTHV+QmdTUVCUnJ9ugCAAAZCeGCAAAAP4ld3d3ubu7m50BAAAAwMaOHz8uHx+fDAcI7ipQoIB8fHwUHh5uwzLANkqUKKGQkBDFxcXJw8MjwzUnT55USEiIKlSoYOM6AADwqDiMCwAA4CFFRUXpyy+/1Kuvvqp69erJ19dXnTp10vfff69Lly6ZnQcAAADAyu7cuSMHhwd/P8vBwUFJSUk2KAJsq23btrpx44a6d++ukJCQdNdSU1O1ZcsW9ezZU8nJyRz5BwDAE4idCAAAAB7CsmXL9MUXXyg5OVkWiyXt+QsXLujAgQP68ccfNWHCBDVo0MC8SAAAAABWVbx4cYWFhenmzZtycXHJcM3NmzcVFhamYsWK2bgOsL7OnTtr586d2r59u9544w05OzurUKFCkqTz58/r9u3bslgs6tChg/z8/EyuBQAAD4udCAAAALIoJCREo0aN0p07d9SxY0f98MMP2rBhg9avX69Zs2apTZs2unbtmt5//30dO3bM7FwAAAAAVtKsWTNdvXpVH330kW7dunXP9du3b+ujjz5SfHy8mjVrZkIhYF12dnaaMWOGhg4dquLFi+vmzZs6deqUTp06pVu3bunZZ5/VhAkTNHr0aLNTAQDAv2BY/vkVOgAAAGSqV69e2rVrl6ZNm6bGjRtnuMbf31+DBw+Wn5+fvvzySxsXAo+nIUOGyN/fX0eOHDE7BQAAIFskJiaqdevWOnfunAoUKKCGDRuqaNGiMgxDZ86c0datW3Xp0iUVK1ZMK1euVN68ec1OBqwqNjZWFy5ckGEYKly4sNzd3c1OAgAAj4DjDAAAALLo8OHDqlq1aqYDBJLUsmVLzZ8//54zIQEAAADkHHny5NGiRYs0cOBAHThwQMuXL5dhGJKUduxZlSpVNHnyZAYI8J9QsGBBFSxY0OwMAACQTRgiAAAAyKKkpCR5eHg8cJ2Xl5f++usvGxQBAAAAMEvhwoW1bNky7du3T3v27FFsbKxSU1NVqFAh+fj4qGbNmmYnAgAAAP8KQwQAAABZ9Nxzz2nv3r26fv16pt8mSklJ0e+//66KFSvauA4AAACAGWrUqKEaNWqYnQEAAABkGzuzAwAAAJ4UgwcP1o0bNzRgwABduXLlnuvJycn67LPPFBsbq/fee8+EQgAAAAC2dunSJUVHR9/3fwAAAMCThJ0IAAAAsmjz5s2qWbOmdu3apYYNG6pOnToqWbKk7O3tdf78eQUHB+vSpUvy8PDQ3LlzNXfu3LR7DcPQjBkzTKwHAAAAkF1SU1M1ZcoULVu2TNeuXbvvWsMwFBERYaMyAAAA4NExRAAAAJBFM2bMkGEYkqSbN29qy5YtGa6LjY1VbGxsuufu3gcAAADgyTdv3jzNmjVLkmRnZ6fcuXPzMz8AAAByDIYIAAAAsmjcuHFmJwCmio6OVu7cueXm5nbfdWfOnNGJEyfk6+srSSpTpoxq1qxpg0IAAADbWLFihezt7TV+/Hg1b95cjo6OZicBAAAA2cawWCwWsyMAAAAAPP7Kly+vVq1aacKECfddN2DAAIWEhGjPnj02KgMAALCtqlWrqkaNGumOMAMAAAByCnYiAAAAyAZxcXG6cOGCSpcurdy5c5udA2SL6OjodI8tFotu3Lhxz/P/lJCQoIiICCUlJVk7DwAAwDTu7u5mJwAAAABWwxABAADAQ4iKitKPP/6oVq1aqVq1apKkKVOmaPbs2UpNTVWePHk0dOhQvfrqqyaXAo9u2LBhCg4OTntsGIYCAwMVGBj4wHvv/vsBAACQE/n5+WnevHk6e/asihYtanYOAAAAkK04zgAAACCLzpw5o7Zt2+ratWsaPny4Xn/9de3bt0+dO3eWJHl5een8+fOyWCxasmQJH6Liiffnn3+qS5cuuvsrw/Xr12Vvby8XF5cM1xuGIScnJ5UsWVIjR47UM888Y8tcAAAAm0lKSlLPnj119uxZ9evXTxUqVFD+/PkzXe/l5WXDOgAAAODRsBMBAABAFs2ZM0cJCQlq1aqVGjZsKElasWKFDMNQ37599d577yk0NFQ9evTQvHnzGCLAE+/ZZ5/Vnj170h57e3urRYsWmjhxoolVAAAA5nN0dFSlSpUUFhamzz777L5rDcNQRESEjcoAAACAR8cQAQAAQBbt3r1bxYoV04QJE2QYhiRp+/btkqTXXntNklS7dm1VrVpV+/btM60TsJZx48apWLFiZmcAAACYbsaMGZo/f74kyWKxKG/evGm/IwAAAABPOoYIAAAAsig2Nla+vr5pbw4eOXJEly5dUqlSpVSoUKG0dQULFtTvv/9uViZgNW3atMn02qFDhxQTE6OKFStyLjAAAMjxVq5cKTs7O40cOVKtW7eWk5OT2UkAAABAtrEzOwAAAOBJkSdPHt26dSvtcVBQkCSpTp066dZduHBBefLksWkbYCv79+/XW2+9pV27dqU99+GHH6pjx44aOHCgmjVrpunTp5tYCAAAYH2xsbGqXbu22rdvzwABAAAAchyGCAAAALKoZMmSCgsL06VLl5SSkiJ/f38ZhiFfX9+0Nfv379fBgwfl7e1tYilgHZGRkerevbuCgoJ04sQJSX8f6bF27VrZ29urZs2acnZ21rfffpt21AcAAEBO5O7uLkdHR7MzAAAAAKtgiAAAACCLXn75Zd24cUMtW7ZUkyZN9Oeff6pw4cKqV6+eJGn06NHq2bOnJKlDhw5mpgJW8cMPPygpKUlvvfWWXn31VUnSmjVrZBiGhgwZooULF2rZsmWyt7fXkiVLTK4FAACwnmbNmik0NFTR0dFmpwAAAADZzrBYLBazIwAAAJ4EFotFI0aM0PLly2WxWJQ/f35NmzZNNWvWlCQ1b95cp0+f1sCBA9WnTx+Ta4Hs99JLLylv3rz69ddfJUmpqamqXbu2EhMTtWvXLuXPn1+S1L17d/35558KDg42MxcAAMBqEhMT1bVrV8XHx+udd95R1apV5erqKgcHhwzXu7m52TYQAAAAeAQZ/1QLAACAexiGodGjR+udd95RbGysypUrp1y5cqVdHzx4sMqVK6dixYqZWAlYz8WLF1WlSpW0x4cOHdK1a9fk7e2dNkAg/f0m+bVr18xIBAAAsIlXX31Vt27dUmxsrIYNG3bftYZhKCIiwkZlAAAAwKNjiAAAAOAhFS5cWIULF77n+caNG2e4fsiQIVq3bh1vHOKJ5+bmpvj4+LTHO3bskCTVqVMn3bozZ84oX758Nm0DAACwpdOnT2d5LRvBAgAA4EnDEAEAAIAN8MYhcoLSpUsrLCxMJ06ckLu7u9auXSvDMPTSSy+lrQkICFBERIR8fX1NLAUAALCuyMhIsxMAAAAAq2GIAAAAAECWdOjQQaGhoWrVqpUcHBx069YtPfPMM/Lx8ZEk9e3bV0FBQTIMQ127djW5FgAAAAAAAMC/wRABAAAAgCx5+eWXde7cOc2YMUM3b95U2bJlNWXKlLTrZ8+elZOTk0aNGqV69eqZFwoAAGBDUVFRCg0NVXR0tEqXLi0/Pz+FhYWpUqVKcnZ2NjsPAAAAeGiGhb11AQAArGrIkCHy9/fXkSNHzE4BskVSUpKuX7+uAgUKpHv+4MGDKlu2rHLnzm1SGQAAgO3Ex8dr+PDhCgwMTDu+zM/PTxMnTtRrr72mU6dOadq0aapVq5bJpQAAAMDDsTM7AAAAAMCTxcnJ6Z4BAkmqUqUKAwQAAOA/4ebNm+revbsCAgLk5uamZs2a6Z/f1XJ2dtbVq1f11ltvKSoqysRSAAAA4OFxnAEAAACADAUEBEiS6tWrp9y5c6c9zqqmTZtaIwsAAMB0P/74oyIjI+Xn56fRo0fLxcVF3t7eadfnzZunSZMmac6cOZo7d65GjRplYi0AAADwcBgiAAAAAJChAQMGyDAMrV+/XqVKlUp7nFUc4QEAAHKqDRs2yN3dXZ9//rmcnJwyXDNo0CCtX79ee/bssXEdAAAA8GgYIgAAAACQobvn97q4uKR7DAAA8F8XFRUlX1/fTAcIJMnOzk4VK1ZUUFCQDcsAAACAR8cQAQAAAIAMLVy48L6PAQAA/qscHR115cqVB667fPmyHB0dbVAEAAAAZB+GCAAAAABk6OrVq490v5ubW7Z0AAAAPG7KlSunw4c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+      "text/plain": [
+       "<Figure size 2500x1500 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "\n",
+    "mask = np.zeros_like(num_corr2)\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_corr2, 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(\"Dealing with Multicollinearity\", fontsize=20) # add title\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1022,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(1781, 8)"
+      ]
+     },
+     "execution_count": 1022,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "num.shape"
    ]
   },
   {
@@ -169,38 +1637,100 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 1023,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "url_length                   0\n",
+       "number_special_characters    0\n",
+       "dist_remote_tcp_port         0\n",
+       "remote_ips                   0\n",
+       "app_bytes                    0\n",
+       "remote_app_packets           0\n",
+       "dns_query_times              1\n",
+       "type                         0\n",
+       "dtype: int64"
+      ]
+     },
+     "execution_count": 1023,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# Your code here\n"
+    "\n",
+    "num2.isna().sum()"
    ]
   },
   {
-   "cell_type": "markdown",
+   "cell_type": "code",
+   "execution_count": 1024,
    "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([ 2.,  0.,  8.,  4., 10.,  6., 12., 14., 20.,  9., nan])"
+      ]
+     },
+     "execution_count": 1024,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "If you remember in the previous labs, we drop a column if the column contains a high proportion of missing values. After dropping those problematic columns, we drop the rows with missing values.\n",
-    "\n",
-    "#### In the cells below, handle the missing values from the dataset. Remember to comment the rationale of your decisions."
+    "num2.dns_query_times.unique()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 1025,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "dns_query_times\n",
+       "0.0     976\n",
+       "4.0     309\n",
+       "6.0     213\n",
+       "2.0     142\n",
+       "8.0     105\n",
+       "10.0     19\n",
+       "12.0     12\n",
+       "14.0      2\n",
+       "20.0      1\n",
+       "9.0       1\n",
+       "Name: count, dtype: int64"
+      ]
+     },
+     "execution_count": 1025,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# Your code here\n"
+    "num2.dns_query_times.value_counts(ascending= False)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "If you remember in the previous labs, we drop a column if the column contains a high proportion of missing values. After dropping those problematic columns, we drop the rows with missing values.\n",
+    "\n",
+    "#### In the cells below, handle the missing values from the dataset. Remember to comment the rationale of your decisions."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 1026,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your comment here"
+    "num2 = num2.fillna(method='backfill', axis=1)\n"
    ]
   },
   {
@@ -214,11 +1744,30 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 1027,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "url_length                   0\n",
+       "number_special_characters    0\n",
+       "dist_remote_tcp_port         0\n",
+       "remote_ips                   0\n",
+       "app_bytes                    0\n",
+       "remote_app_packets           0\n",
+       "dns_query_times              0\n",
+       "type                         0\n",
+       "dtype: int64"
+      ]
+     },
+     "execution_count": 1027,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# Examine missing values in each column\n"
+    "num2.isna().sum()"
    ]
   },
   {
@@ -256,33 +1805,157 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 1028,
    "metadata": {},
-   "outputs": [],
+   "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": 1028,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# Your code here\n"
+    "df.whois_country.unique()"
    ]
   },
   {
-   "cell_type": "markdown",
+   "cell_type": "code",
+   "execution_count": 1029,
    "metadata": {},
+   "outputs": [],
    "source": [
-    "Since we have fixed the country values, can we convert this column to ordinal now?\n",
-    "\n",
-    "Not yet. If you reflect on the previous labs how we handle categorical columns, you probably remember we ended up dropping a lot of those columns because there are too many unique values. Too many unique values in a column is not desirable in machine learning because it makes prediction inaccurate. But there are workarounds under certain conditions. One of the fixable conditions is:\n",
-    "\n",
-    "#### If a limited number of values account for the majority of data, we can retain these top values and re-label all other rare values.\n",
-    "\n",
-    "The `WHOIS_COUNTRY` column happens to be this case. You can verify it by print a bar chart of the `value_counts` in the next cell to verify:"
+    "country_mapping = {\n",
+    "    'US': 'US',\n",
+    "    'SC': 'SC',\n",
+    "    'GB': 'GB',\n",
+    "    'UK': 'GB',  \n",
+    "    'RU': 'RU',\n",
+    "    'AU': 'AU',\n",
+    "    'CA': 'CA',\n",
+    "    'PA': 'PA',\n",
+    "    'se': 'SE',  \n",
+    "    'IN': 'IN',\n",
+    "    'LU': 'LU',\n",
+    "    'TH': 'TH',\n",
+    "    \"[u'GB'; u'UK']\": 'GB',  \n",
+    "    'FR': 'FR',\n",
+    "    'NL': 'NL',\n",
+    "    'UG': 'UG',\n",
+    "    'JP': 'JP',\n",
+    "    'CN': 'CN',\n",
+    "    'SE': 'SE',\n",
+    "    'SI': 'SI',\n",
+    "    'IL': 'IL',\n",
+    "    'ru': 'RU',  \n",
+    "    'KY': 'KY',\n",
+    "    'AT': 'AT',\n",
+    "    'CZ': 'CZ',\n",
+    "    'PH': 'PH',\n",
+    "    'BE': 'BE',\n",
+    "    'NO': 'NO',\n",
+    "    'TR': 'TR',\n",
+    "    'LV': 'LV',\n",
+    "    'DE': 'DE',\n",
+    "    'ES': 'ES',\n",
+    "    'BR': 'BR',\n",
+    "    'us': 'US',  # Convertir a mayúsculas\n",
+    "    'KR': 'KR',\n",
+    "    'HK': 'HK',\n",
+    "    'UA': 'UA',\n",
+    "    'CH': 'CH',\n",
+    "    'United Kingdom': 'GB',\n",
+    "    'BS': 'BS',\n",
+    "    'PK': 'PK',\n",
+    "    'IT': 'IT',\n",
+    "    'Cyprus': 'CY',\n",
+    "    'BY': 'BY',\n",
+    "    'AE': 'AE',\n",
+    "    'IE': 'IE',\n",
+    "    'UY': 'UY',\n",
+    "    'KG': 'KG'\n",
+    "}"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 1030,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your code here\n"
+    "df['whois_country'] = df['whois_country'].map(country_mapping)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1031,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "whois_country\n",
+       "US    1106\n",
+       "CA      84\n",
+       "ES      63\n",
+       "GB      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": 1031,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.whois_country.value_counts(ascending=False)\n"
    ]
   },
   {
@@ -294,13 +1967,31 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 1032,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df2 = df.copy()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1033,
    "metadata": {
     "scrolled": true
    },
    "outputs": [],
    "source": [
-    "# Your code here\n"
+    "top_10_values = df2['whois_country'].value_counts().nlargest(10).index\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1034,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df2['whois_country'] = df2['whois_country'].apply(lambda x: x if x in top_10_values else 'OTHER')"
    ]
   },
   {
@@ -316,11 +2007,210 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 1035,
    "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>charset</th>\n",
+       "      <th>server</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>16</td>\n",
+       "      <td>7</td>\n",
+       "      <td>iso-8859-1</td>\n",
+       "      <td>nginx</td>\n",
+       "      <td>OTHER</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>16</td>\n",
+       "      <td>6</td>\n",
+       "      <td>UTF-8</td>\n",
+       "      <td>Apache/2.4.10</td>\n",
+       "      <td>OTHER</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>16</td>\n",
+       "      <td>6</td>\n",
+       "      <td>us-ascii</td>\n",
+       "      <td>Microsoft-HTTPAPI/2.0</td>\n",
+       "      <td>OTHER</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>17</td>\n",
+       "      <td>6</td>\n",
+       "      <td>ISO-8859-1</td>\n",
+       "      <td>nginx</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>17</td>\n",
+       "      <td>6</td>\n",
+       "      <td>UTF-8</td>\n",
+       "      <td>NaN</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",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   url_length  number_special_characters     charset                 server  \\\n",
+       "0          16                          7  iso-8859-1                  nginx   \n",
+       "1          16                          6       UTF-8          Apache/2.4.10   \n",
+       "2          16                          6    us-ascii  Microsoft-HTTPAPI/2.0   \n",
+       "3          17                          6  ISO-8859-1                  nginx   \n",
+       "4          17                          6       UTF-8                    NaN   \n",
+       "\n",
+       "  whois_country whois_statepro     whois_regdate whois_updated_date  \\\n",
+       "0         OTHER            NaN  10/10/2015 18:21                NaN   \n",
+       "1         OTHER            NaN               NaN                NaN   \n",
+       "2         OTHER            NaN               NaN                NaN   \n",
+       "3            US             AK    7/10/1997 4:00    12/09/2013 0:45   \n",
+       "4            US             TX   12/05/1996 0:00    11/04/2017 0:00   \n",
+       "\n",
+       "   tcp_conversation_exchange  dist_remote_tcp_port  remote_ips  app_bytes  \\\n",
+       "0                          7                     0           2        700   \n",
+       "1                         17                     7           4       1230   \n",
+       "2                          0                     0           0          0   \n",
+       "3                         31                    22           3       3812   \n",
+       "4                         57                     2           5       4278   \n",
+       "\n",
+       "   source_app_packets  remote_app_packets  source_app_bytes  remote_app_bytes  \\\n",
+       "0                   9                  10              1153               832   \n",
+       "1                  17                  19              1265              1230   \n",
+       "2                   0                   0                 0                 0   \n",
+       "3                  39                  37             18784              4380   \n",
+       "4                  61                  62            129889              4586   \n",
+       "\n",
+       "   app_packets  dns_query_times  type  \n",
+       "0            9              2.0     1  \n",
+       "1           17              0.0     0  \n",
+       "2            0              0.0     0  \n",
+       "3           39              8.0     0  \n",
+       "4           61              4.0     0  "
+      ]
+     },
+     "execution_count": 1035,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# Your code here\n"
+    "df2.head()"
    ]
   },
   {
@@ -332,15 +2222,6 @@
     "Now print the `dtypes` of the data again. Besides `WHOIS_COUNTRY` which we already fixed, there should be 3 categorical columns left: `URL`, `CHARSET`, and `SERVER`."
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": 18,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Your code here\n"
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -350,11 +2231,211 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 1036,
    "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>charset</th>\n",
+       "      <th>server</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>16</td>\n",
+       "      <td>7</td>\n",
+       "      <td>iso-8859-1</td>\n",
+       "      <td>nginx</td>\n",
+       "      <td>OTHER</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>16</td>\n",
+       "      <td>6</td>\n",
+       "      <td>UTF-8</td>\n",
+       "      <td>Apache/2.4.10</td>\n",
+       "      <td>OTHER</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>16</td>\n",
+       "      <td>6</td>\n",
+       "      <td>us-ascii</td>\n",
+       "      <td>Microsoft-HTTPAPI/2.0</td>\n",
+       "      <td>OTHER</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>17</td>\n",
+       "      <td>6</td>\n",
+       "      <td>ISO-8859-1</td>\n",
+       "      <td>nginx</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>17</td>\n",
+       "      <td>6</td>\n",
+       "      <td>UTF-8</td>\n",
+       "      <td>NaN</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",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   url_length  number_special_characters     charset                 server  \\\n",
+       "0          16                          7  iso-8859-1                  nginx   \n",
+       "1          16                          6       UTF-8          Apache/2.4.10   \n",
+       "2          16                          6    us-ascii  Microsoft-HTTPAPI/2.0   \n",
+       "3          17                          6  ISO-8859-1                  nginx   \n",
+       "4          17                          6       UTF-8                    NaN   \n",
+       "\n",
+       "  whois_country whois_statepro     whois_regdate whois_updated_date  \\\n",
+       "0         OTHER            NaN  10/10/2015 18:21                NaN   \n",
+       "1         OTHER            NaN               NaN                NaN   \n",
+       "2         OTHER            NaN               NaN                NaN   \n",
+       "3            US             AK    7/10/1997 4:00    12/09/2013 0:45   \n",
+       "4            US             TX   12/05/1996 0:00    11/04/2017 0:00   \n",
+       "\n",
+       "   tcp_conversation_exchange  dist_remote_tcp_port  remote_ips  app_bytes  \\\n",
+       "0                          7                     0           2        700   \n",
+       "1                         17                     7           4       1230   \n",
+       "2                          0                     0           0          0   \n",
+       "3                         31                    22           3       3812   \n",
+       "4                         57                     2           5       4278   \n",
+       "\n",
+       "   source_app_packets  remote_app_packets  source_app_bytes  remote_app_bytes  \\\n",
+       "0                   9                  10              1153               832   \n",
+       "1                  17                  19              1265              1230   \n",
+       "2                   0                   0                 0                 0   \n",
+       "3                  39                  37             18784              4380   \n",
+       "4                  61                  62            129889              4586   \n",
+       "\n",
+       "   app_packets  dns_query_times  type  \n",
+       "0            9              2.0     1  \n",
+       "1           17              0.0     0  \n",
+       "2            0              0.0     0  \n",
+       "3           39              8.0     0  \n",
+       "4           61              4.0     0  "
+      ]
+     },
+     "execution_count": 1036,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# Your code here\n"
+    "# Ya lo he borrado al principio. Ya está hecho\n",
+    "df2.head()\n"
    ]
   },
   {
@@ -366,11 +2447,23 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 1037,
    "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": 1037,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# Your code here"
+    "df2.charset.unique()"
    ]
   },
   {
@@ -384,11 +2477,151 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 1038,
    "metadata": {},
-   "outputs": [],
+   "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": 1038,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# Your code here\n"
+    "df2.server.unique()\n"
    ]
   },
   {
@@ -400,11 +2633,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 1039,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your comment here\n"
+    "# Podría categorizarlo por servidor. Ej. Amazon, Apache, etc \n"
    ]
   },
   {
@@ -418,22 +2651,953 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 1040,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "176"
+      ]
+     },
+     "execution_count": 1040,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df2.server.isna().sum()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1041,
+   "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": 1041,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df2.server.unique()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1042,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df2['server'] = df2['server'].fillna(method='backfill')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1043,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df3 = df2.copy()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1044,
+   "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>charset</th>\n",
+       "      <th>server</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>16</td>\n",
+       "      <td>7</td>\n",
+       "      <td>iso-8859-1</td>\n",
+       "      <td>nginx</td>\n",
+       "      <td>OTHER</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>16</td>\n",
+       "      <td>6</td>\n",
+       "      <td>UTF-8</td>\n",
+       "      <td>Apache/2.4.10</td>\n",
+       "      <td>OTHER</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>16</td>\n",
+       "      <td>6</td>\n",
+       "      <td>us-ascii</td>\n",
+       "      <td>Microsoft-HTTPAPI/2.0</td>\n",
+       "      <td>OTHER</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>17</td>\n",
+       "      <td>6</td>\n",
+       "      <td>ISO-8859-1</td>\n",
+       "      <td>nginx</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>17</td>\n",
+       "      <td>6</td>\n",
+       "      <td>UTF-8</td>\n",
+       "      <td>nginx</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",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   url_length  number_special_characters     charset                 server  \\\n",
+       "0          16                          7  iso-8859-1                  nginx   \n",
+       "1          16                          6       UTF-8          Apache/2.4.10   \n",
+       "2          16                          6    us-ascii  Microsoft-HTTPAPI/2.0   \n",
+       "3          17                          6  ISO-8859-1                  nginx   \n",
+       "4          17                          6       UTF-8                  nginx   \n",
+       "\n",
+       "  whois_country whois_statepro     whois_regdate whois_updated_date  \\\n",
+       "0         OTHER            NaN  10/10/2015 18:21                NaN   \n",
+       "1         OTHER            NaN               NaN                NaN   \n",
+       "2         OTHER            NaN               NaN                NaN   \n",
+       "3            US             AK    7/10/1997 4:00    12/09/2013 0:45   \n",
+       "4            US             TX   12/05/1996 0:00    11/04/2017 0:00   \n",
+       "\n",
+       "   tcp_conversation_exchange  dist_remote_tcp_port  remote_ips  app_bytes  \\\n",
+       "0                          7                     0           2        700   \n",
+       "1                         17                     7           4       1230   \n",
+       "2                          0                     0           0          0   \n",
+       "3                         31                    22           3       3812   \n",
+       "4                         57                     2           5       4278   \n",
+       "\n",
+       "   source_app_packets  remote_app_packets  source_app_bytes  remote_app_bytes  \\\n",
+       "0                   9                  10              1153               832   \n",
+       "1                  17                  19              1265              1230   \n",
+       "2                   0                   0                 0                 0   \n",
+       "3                  39                  37             18784              4380   \n",
+       "4                  61                  62            129889              4586   \n",
+       "\n",
+       "   app_packets  dns_query_times  type  \n",
+       "0            9              2.0     1  \n",
+       "1           17              0.0     0  \n",
+       "2            0              0.0     0  \n",
+       "3           39              8.0     0  \n",
+       "4           61              4.0     0  "
+      ]
+     },
+     "execution_count": 1044,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df3.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1045,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your code here\n"
+    "df3['server'] = df3['server'].str.replace(r'/.*', '', regex=True)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 1046,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df3['server'] = df3['server'].str.replace(r'-.*', '', regex=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1047,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "server\n",
+       "Apache                711\n",
+       "nginx                 378\n",
+       "Microsoft             214\n",
+       "cloudflare            111\n",
+       "GSE                    56\n",
+       "                     ... \n",
+       "barista                 1\n",
+       "mw2190.codfw.wmnet      1\n",
+       "mw2107.codfw.wmnet      1\n",
+       "Resin                   1\n",
+       "IdeaWebServer           1\n",
+       "Name: count, Length: 108, dtype: int64"
+      ]
+     },
+     "execution_count": 1047,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df3.server.value_counts()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1048,
+   "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>charset</th>\n",
+       "      <th>server</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>16</td>\n",
+       "      <td>7</td>\n",
+       "      <td>iso-8859-1</td>\n",
+       "      <td>nginx</td>\n",
+       "      <td>OTHER</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>16</td>\n",
+       "      <td>6</td>\n",
+       "      <td>UTF-8</td>\n",
+       "      <td>Apache</td>\n",
+       "      <td>OTHER</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>16</td>\n",
+       "      <td>6</td>\n",
+       "      <td>us-ascii</td>\n",
+       "      <td>Microsoft</td>\n",
+       "      <td>OTHER</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>17</td>\n",
+       "      <td>6</td>\n",
+       "      <td>ISO-8859-1</td>\n",
+       "      <td>nginx</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>17</td>\n",
+       "      <td>6</td>\n",
+       "      <td>UTF-8</td>\n",
+       "      <td>nginx</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",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   url_length  number_special_characters     charset     server whois_country  \\\n",
+       "0          16                          7  iso-8859-1      nginx         OTHER   \n",
+       "1          16                          6       UTF-8     Apache         OTHER   \n",
+       "2          16                          6    us-ascii  Microsoft         OTHER   \n",
+       "3          17                          6  ISO-8859-1      nginx            US   \n",
+       "4          17                          6       UTF-8      nginx            US   \n",
+       "\n",
+       "  whois_statepro     whois_regdate whois_updated_date  \\\n",
+       "0            NaN  10/10/2015 18:21                NaN   \n",
+       "1            NaN               NaN                NaN   \n",
+       "2            NaN               NaN                NaN   \n",
+       "3             AK    7/10/1997 4:00    12/09/2013 0:45   \n",
+       "4             TX   12/05/1996 0:00    11/04/2017 0:00   \n",
+       "\n",
+       "   tcp_conversation_exchange  dist_remote_tcp_port  remote_ips  app_bytes  \\\n",
+       "0                          7                     0           2        700   \n",
+       "1                         17                     7           4       1230   \n",
+       "2                          0                     0           0          0   \n",
+       "3                         31                    22           3       3812   \n",
+       "4                         57                     2           5       4278   \n",
+       "\n",
+       "   source_app_packets  remote_app_packets  source_app_bytes  remote_app_bytes  \\\n",
+       "0                   9                  10              1153               832   \n",
+       "1                  17                  19              1265              1230   \n",
+       "2                   0                   0                 0                 0   \n",
+       "3                  39                  37             18784              4380   \n",
+       "4                  61                  62            129889              4586   \n",
+       "\n",
+       "   app_packets  dns_query_times  type  \n",
+       "0            9              2.0     1  \n",
+       "1           17              0.0     0  \n",
+       "2            0              0.0     0  \n",
+       "3           39              8.0     0  \n",
+       "4           61              4.0     0  "
+      ]
+     },
+     "execution_count": 1048,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df3.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1049,
    "metadata": {
     "scrolled": false
    },
    "outputs": [],
    "source": [
-    "# Count `SERVER` value counts here\n"
+    "top_server = df3.server.value_counts().head(3).index\n",
+    "df3.server=df3.server.apply(lambda x:x if x in top_server else \"OTHER\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1050,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "server\n",
+       "Apache       711\n",
+       "OTHER        478\n",
+       "nginx        378\n",
+       "Microsoft    214\n",
+       "Name: count, dtype: int64"
+      ]
+     },
+     "execution_count": 1050,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df3.server.value_counts()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1051,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "cat = df3.select_dtypes(exclude=\"number\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1052,
+   "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>app_bytes</th>\n",
+       "      <th>remote_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>16</td>\n",
+       "      <td>7</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>700</td>\n",
+       "      <td>10</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>7</td>\n",
+       "      <td>4</td>\n",
+       "      <td>1230</td>\n",
+       "      <td>19</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>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>22</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3812</td>\n",
+       "      <td>37</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>2</td>\n",
+       "      <td>5</td>\n",
+       "      <td>4278</td>\n",
+       "      <td>62</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\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",
+       "   app_bytes  remote_app_packets  dns_query_times  type  \n",
+       "0        700                  10              2.0     1  \n",
+       "1       1230                  19              0.0     0  \n",
+       "2          0                   0              0.0     0  \n",
+       "3       3812                  37              8.0     0  \n",
+       "4       4278                  62              4.0     0  "
+      ]
+     },
+     "execution_count": 1052,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "num.head()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Since we have fixed the country values, can we convert this column to ordinal now?\n",
+    "\n",
+    "Not yet. If you reflect on the previous labs how we handle categorical columns, you probably remember we ended up dropping a lot of those columns because there are too many unique values. Too many unique values in a column is not desirable in machine learning because it makes prediction inaccurate. But there are workarounds under certain conditions. One of the fixable conditions is:\n",
+    "\n",
+    "#### If a limited number of values account for the majority of data, we can retain these top values and re-label all other rare values.\n",
+    "\n",
+    "The `WHOIS_COUNTRY` column happens to be this case. You can verify it by print a bar chart of the `value_counts` in the next cell to verify:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1053,
+   "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",
+       "      <th>whois_statepro</th>\n",
+       "      <th>whois_regdate</th>\n",
+       "      <th>whois_updated_date</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",
+       "      <td>NaN</td>\n",
+       "      <td>10/10/2015 18:21</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>UTF-8</td>\n",
+       "      <td>Apache</td>\n",
+       "      <td>OTHER</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>us-ascii</td>\n",
+       "      <td>Microsoft</td>\n",
+       "      <td>OTHER</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>ISO-8859-1</td>\n",
+       "      <td>nginx</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",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>UTF-8</td>\n",
+       "      <td>nginx</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",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      charset     server whois_country whois_statepro     whois_regdate  \\\n",
+       "0  iso-8859-1      nginx         OTHER            NaN  10/10/2015 18:21   \n",
+       "1       UTF-8     Apache         OTHER            NaN               NaN   \n",
+       "2    us-ascii  Microsoft         OTHER            NaN               NaN   \n",
+       "3  ISO-8859-1      nginx            US             AK    7/10/1997 4:00   \n",
+       "4       UTF-8      nginx            US             TX   12/05/1996 0:00   \n",
+       "\n",
+       "  whois_updated_date  \n",
+       "0                NaN  \n",
+       "1                NaN  \n",
+       "2                NaN  \n",
+       "3    12/09/2013 0:45  \n",
+       "4    11/04/2017 0:00  "
+      ]
+     },
+     "execution_count": 1053,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cat.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1054,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "cat = cat.drop(columns=['whois_statepro', 'whois_regdate', 'whois_updated_date'])"
    ]
   },
   {
@@ -445,11 +3609,96 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 1055,
+   "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</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>nginx</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         OTHER\n",
+       "3  ISO-8859-1      nginx            US\n",
+       "4       UTF-8      nginx            US"
+      ]
+     },
+     "execution_count": 1055,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cat.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1056,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your code here\n"
+    "website_dummy = pd.get_dummies(cat, drop_first=True)\n",
+    "website_dummy = website_dummy.astype(int)"
    ]
   },
   {
@@ -461,11 +3710,383 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": 1057,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your code here\n"
+    "#There aren't"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1058,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "charset_ISO-8859-1      int32\n",
+       "charset_UTF-8           int32\n",
+       "charset_iso-8859-1      int32\n",
+       "charset_us-ascii        int32\n",
+       "charset_utf-8           int32\n",
+       "charset_windows-1251    int32\n",
+       "charset_windows-1252    int32\n",
+       "server_Microsoft        int32\n",
+       "server_OTHER            int32\n",
+       "server_nginx            int32\n",
+       "whois_country_CA        int32\n",
+       "whois_country_CN        int32\n",
+       "whois_country_ES        int32\n",
+       "whois_country_FR        int32\n",
+       "whois_country_GB        int32\n",
+       "whois_country_IN        int32\n",
+       "whois_country_JP        int32\n",
+       "whois_country_OTHER     int32\n",
+       "whois_country_PA        int32\n",
+       "whois_country_US        int32\n",
+       "dtype: object"
+      ]
+     },
+     "execution_count": 1058,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "website_dummy.dtypes"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1059,
+   "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>app_bytes</th>\n",
+       "      <th>remote_app_packets</th>\n",
+       "      <th>dns_query_times</th>\n",
+       "      <th>type</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_Microsoft</th>\n",
+       "      <th>server_OTHER</th>\n",
+       "      <th>server_nginx</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_GB</th>\n",
+       "      <th>whois_country_IN</th>\n",
+       "      <th>whois_country_JP</th>\n",
+       "      <th>whois_country_OTHER</th>\n",
+       "      <th>whois_country_PA</th>\n",
+       "      <th>whois_country_US</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>16.0</td>\n",
+       "      <td>7.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>700.0</td>\n",
+       "      <td>10.0</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>1.0</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",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>16.0</td>\n",
+       "      <td>6.0</td>\n",
+       "      <td>7.0</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>1230.0</td>\n",
+       "      <td>19.0</td>\n",
+       "      <td>0.0</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>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>2</th>\n",
+       "      <td>16.0</td>\n",
+       "      <td>6.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</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>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>3</th>\n",
+       "      <td>17.0</td>\n",
+       "      <td>6.0</td>\n",
+       "      <td>22.0</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>3812.0</td>\n",
+       "      <td>37.0</td>\n",
+       "      <td>8.0</td>\n",
+       "      <td>0.0</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",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>17.0</td>\n",
+       "      <td>6.0</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>4278.0</td>\n",
+       "      <td>62.0</td>\n",
+       "      <td>4.0</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>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",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   url_length  number_special_characters  dist_remote_tcp_port  remote_ips  \\\n",
+       "0        16.0                        7.0                   0.0         2.0   \n",
+       "1        16.0                        6.0                   7.0         4.0   \n",
+       "2        16.0                        6.0                   0.0         0.0   \n",
+       "3        17.0                        6.0                  22.0         3.0   \n",
+       "4        17.0                        6.0                   2.0         5.0   \n",
+       "\n",
+       "   app_bytes  remote_app_packets  dns_query_times  type  charset_ISO-8859-1  \\\n",
+       "0      700.0                10.0              2.0   1.0                   0   \n",
+       "1     1230.0                19.0              0.0   0.0                   0   \n",
+       "2        0.0                 0.0              0.0   0.0                   0   \n",
+       "3     3812.0                37.0              8.0   0.0                   1   \n",
+       "4     4278.0                62.0              4.0   0.0                   0   \n",
+       "\n",
+       "   charset_UTF-8  charset_iso-8859-1  charset_us-ascii  charset_utf-8  \\\n",
+       "0              0                   1                 0              0   \n",
+       "1              1                   0                 0              0   \n",
+       "2              0                   0                 1              0   \n",
+       "3              0                   0                 0              0   \n",
+       "4              1                   0                 0              0   \n",
+       "\n",
+       "   charset_windows-1251  charset_windows-1252  server_Microsoft  server_OTHER  \\\n",
+       "0                     0                     0                 0             0   \n",
+       "1                     0                     0                 0             0   \n",
+       "2                     0                     0                 1             0   \n",
+       "3                     0                     0                 0             0   \n",
+       "4                     0                     0                 0             0   \n",
+       "\n",
+       "   server_nginx  whois_country_CA  whois_country_CN  whois_country_ES  \\\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             1                 0                 0                 0   \n",
+       "\n",
+       "   whois_country_FR  whois_country_GB  whois_country_IN  whois_country_JP  \\\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",
+       "   whois_country_OTHER  whois_country_PA  whois_country_US  \n",
+       "0                    1                 0                 0  \n",
+       "1                    1                 0                 0  \n",
+       "2                    1                 0                 0  \n",
+       "3                    0                 0                 1  \n",
+       "4                    0                 0                 1  "
+      ]
+     },
+     "execution_count": 1059,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "merged_df = pd.concat([num2, website_dummy], axis=1)\n",
+    "merged_df.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1060,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "url_length                   float64\n",
+       "number_special_characters    float64\n",
+       "dist_remote_tcp_port         float64\n",
+       "remote_ips                   float64\n",
+       "app_bytes                    float64\n",
+       "remote_app_packets           float64\n",
+       "dns_query_times              float64\n",
+       "type                         float64\n",
+       "charset_ISO-8859-1             int32\n",
+       "charset_UTF-8                  int32\n",
+       "charset_iso-8859-1             int32\n",
+       "charset_us-ascii               int32\n",
+       "charset_utf-8                  int32\n",
+       "charset_windows-1251           int32\n",
+       "charset_windows-1252           int32\n",
+       "server_Microsoft               int32\n",
+       "server_OTHER                   int32\n",
+       "server_nginx                   int32\n",
+       "whois_country_CA               int32\n",
+       "whois_country_CN               int32\n",
+       "whois_country_ES               int32\n",
+       "whois_country_FR               int32\n",
+       "whois_country_GB               int32\n",
+       "whois_country_IN               int32\n",
+       "whois_country_JP               int32\n",
+       "whois_country_OTHER            int32\n",
+       "whois_country_PA               int32\n",
+       "whois_country_US               int32\n",
+       "dtype: object"
+      ]
+     },
+     "execution_count": 1060,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "merged_df.dtypes"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### After verifying, now let's keep the top 10 values of the column and re-label other columns with `OTHER`."
    ]
   },
   {
@@ -479,13 +4100,51 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 1061,
    "metadata": {},
    "outputs": [],
    "source": [
-    "from sklearn.model_selection import train_test_split\n",
-    "\n",
-    "# Your code here:\n"
+    "from sklearn.model_selection import train_test_split"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1062,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "y = df['type']\n",
+    "X = df.drop(columns = ['type'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1063,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "X_train, X_test, y_train, y_test = train_test_split(X,y, test_size = 0.3, random_state = 42)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1064,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "100% of our data: 1781.\n",
+      "70% for training data: 1246.\n",
+      "30% for test data: 535.\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(f'100% of our data: {len(df)}.')\n",
+    "print(f'70% for training data: {len(X_train)}.')\n",
+    "print(f'30% for test data: {len(X_test)}.')"
    ]
   },
   {
@@ -499,12 +4158,31 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "ename": "ValueError",
+     "evalue": "could not convert string to float: 'ISO-8859-1'",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[1;31mValueError\u001b[0m                                Traceback (most recent call last)",
+      "\u001b[1;32m~\\AppData\\Local\\Temp\\ipykernel_20132\\3122369064.py\u001b[0m in \u001b[0;36m?\u001b[1;34m()\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[0mmodel\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mLogisticRegression\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 2\u001b[1;33m \u001b[0mmodel\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfit\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mX_train\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0my_train\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
+      "\u001b[1;32mc:\\Users\\julyj\\anaconda3\\Lib\\site-packages\\sklearn\\base.py\u001b[0m in \u001b[0;36m?\u001b[1;34m(estimator, *args, **kwargs)\u001b[0m\n\u001b[0;32m   1470\u001b[0m                 skip_parameter_validation=(\n\u001b[0;32m   1471\u001b[0m                     \u001b[0mprefer_skip_nested_validation\u001b[0m \u001b[1;32mor\u001b[0m \u001b[0mglobal_skip_validation\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1472\u001b[0m                 \u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1473\u001b[0m             \u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1474\u001b[1;33m                 \u001b[1;32mreturn\u001b[0m \u001b[0mfit_method\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mestimator\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
+      "\u001b[1;32mc:\\Users\\julyj\\anaconda3\\Lib\\site-packages\\sklearn\\linear_model\\_logistic.py\u001b[0m in \u001b[0;36m?\u001b[1;34m(self, X, y, sample_weight)\u001b[0m\n\u001b[0;32m   1197\u001b[0m             \u001b[0m_dtype\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfloat64\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1198\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1199\u001b[0m             \u001b[0m_dtype\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m[\u001b[0m\u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfloat64\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfloat32\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1200\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1201\u001b[1;33m         X, y = self._validate_data(\n\u001b[0m\u001b[0;32m   1202\u001b[0m             \u001b[0mX\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1203\u001b[0m             \u001b[0my\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1204\u001b[0m             \u001b[0maccept_sparse\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m\"csr\"\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+      "\u001b[1;32mc:\\Users\\julyj\\anaconda3\\Lib\\site-packages\\sklearn\\base.py\u001b[0m in \u001b[0;36m?\u001b[1;34m(self, X, y, reset, validate_separately, cast_to_ndarray, **check_params)\u001b[0m\n\u001b[0;32m    646\u001b[0m                 \u001b[1;32mif\u001b[0m \u001b[1;34m\"estimator\"\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mcheck_y_params\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    647\u001b[0m                     \u001b[0mcheck_y_params\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m{\u001b[0m\u001b[1;33m**\u001b[0m\u001b[0mdefault_check_params\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mcheck_y_params\u001b[0m\u001b[1;33m}\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    648\u001b[0m                 \u001b[0my\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mcheck_array\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0my\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0minput_name\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m\"y\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mcheck_y_params\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    649\u001b[0m             \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 650\u001b[1;33m                 \u001b[0mX\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0my\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mcheck_X_y\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mX\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0my\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mcheck_params\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    651\u001b[0m             \u001b[0mout\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mX\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0my\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    652\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    653\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mno_val_X\u001b[0m \u001b[1;32mand\u001b[0m \u001b[0mcheck_params\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"ensure_2d\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;32mTrue\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+      "\u001b[1;32mc:\\Users\\julyj\\anaconda3\\Lib\\site-packages\\sklearn\\utils\\validation.py\u001b[0m in \u001b[0;36m?\u001b[1;34m(X, y, accept_sparse, accept_large_sparse, dtype, order, copy, force_all_finite, ensure_2d, allow_nd, multi_output, ensure_min_samples, ensure_min_features, y_numeric, estimator)\u001b[0m\n\u001b[0;32m   1259\u001b[0m         raise ValueError(\n\u001b[0;32m   1260\u001b[0m             \u001b[1;33mf\"\u001b[0m\u001b[1;33m{\u001b[0m\u001b[0mestimator_name\u001b[0m\u001b[1;33m}\u001b[0m\u001b[1;33m requires y to be passed, but the target y is None\u001b[0m\u001b[1;33m\"\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1261\u001b[0m         \u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1262\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1263\u001b[1;33m     X = check_array(\n\u001b[0m\u001b[0;32m   1264\u001b[0m         \u001b[0mX\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1265\u001b[0m         \u001b[0maccept_sparse\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0maccept_sparse\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1266\u001b[0m         \u001b[0maccept_large_sparse\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0maccept_large_sparse\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+      "\u001b[1;32mc:\\Users\\julyj\\anaconda3\\Lib\\site-packages\\sklearn\\utils\\validation.py\u001b[0m in \u001b[0;36m?\u001b[1;34m(array, accept_sparse, accept_large_sparse, dtype, order, copy, force_all_finite, ensure_2d, allow_nd, ensure_min_samples, ensure_min_features, estimator, input_name)\u001b[0m\n\u001b[0;32m    994\u001b[0m                         \u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    995\u001b[0m                     \u001b[0marray\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mxp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mastype\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0marray\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcopy\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mFalse\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    996\u001b[0m                 \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    997\u001b[0m                     \u001b[0marray\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0m_asarray_with_order\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0marray\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0morder\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0morder\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mdtype\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mxp\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mxp\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 998\u001b[1;33m             \u001b[1;32mexcept\u001b[0m \u001b[0mComplexWarning\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0mcomplex_warning\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    999\u001b[0m                 raise ValueError(\n\u001b[0;32m   1000\u001b[0m                     \u001b[1;34m\"Complex data not supported\\n{}\\n\"\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mformat\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0marray\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1001\u001b[0m                 \u001b[1;33m)\u001b[0m \u001b[1;32mfrom\u001b[0m \u001b[0mcomplex_warning\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+      "\u001b[1;32mc:\\Users\\julyj\\anaconda3\\Lib\\site-packages\\sklearn\\utils\\_array_api.py\u001b[0m in \u001b[0;36m?\u001b[1;34m(array, dtype, order, copy, xp)\u001b[0m\n\u001b[0;32m    517\u001b[0m         \u001b[1;31m# Use NumPy API to support order\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    518\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mcopy\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mTrue\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    519\u001b[0m             \u001b[0marray\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mnumpy\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0marray\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0marray\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0morder\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0morder\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mdtype\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    520\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 521\u001b[1;33m             \u001b[0marray\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mnumpy\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0masarray\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0marray\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0morder\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0morder\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mdtype\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    522\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    523\u001b[0m         \u001b[1;31m# At this point array is a NumPy ndarray. We convert it to an array\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    524\u001b[0m         \u001b[1;31m# container that is consistent with the input's namespace.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+      "\u001b[1;32mc:\\Users\\julyj\\anaconda3\\Lib\\site-packages\\pandas\\core\\generic.py\u001b[0m in \u001b[0;36m?\u001b[1;34m(self, dtype, copy)\u001b[0m\n\u001b[0;32m   2149\u001b[0m     def __array__(\n\u001b[0;32m   2150\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mnpt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mDTypeLike\u001b[0m \u001b[1;33m|\u001b[0m \u001b[1;32mNone\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcopy\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mbool_t\u001b[0m \u001b[1;33m|\u001b[0m \u001b[1;32mNone\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2151\u001b[0m     \u001b[1;33m)\u001b[0m \u001b[1;33m->\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mndarray\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2152\u001b[0m         \u001b[0mvalues\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_values\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 2153\u001b[1;33m         \u001b[0marr\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0masarray\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mvalues\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mdtype\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   2154\u001b[0m         if (\n\u001b[0;32m   2155\u001b[0m             \u001b[0mastype_is_view\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mvalues\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdtype\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0marr\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdtype\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2156\u001b[0m             \u001b[1;32mand\u001b[0m \u001b[0musing_copy_on_write\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+      "\u001b[1;31mValueError\u001b[0m: could not convert string to float: 'ISO-8859-1'"
+     ]
+    }
+   ],
    "source": [
-    "# Your code here:\n",
-    "\n"
+    "model = LogisticRegression()\n",
+    "model.fit(X_train, y_train)k"
    ]
   },
   {
@@ -516,7 +4194,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -533,7 +4211,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -550,7 +4228,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -569,7 +4247,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -586,7 +4264,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -605,7 +4283,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -622,7 +4300,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 37,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -645,7 +4323,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 38,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -655,9 +4333,9 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "ironhack-3.7",
+   "display_name": "base",
    "language": "python",
-   "name": "ironhack-3.7"
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
@@ -669,7 +4347,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.3"
+   "version": "3.12.4"
   }
  },
  "nbformat": 4,