From 8b23cb1d0b3bc114a5a44a3716243b53e6d56efb Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Eduardo=20Ferra=CC=81n=20Gea?= <edferrangea@gmail.com>
Date: Wed, 2 Jun 2021 09:35:33 +0200
Subject: [PATCH] me quede en el challenge 5

---
 .../.ipynb_checkpoints/main-checkpoint.ipynb  | 1988 +++++++++++++++++
 your-code/main.ipynb                          | 1391 +++++++++++-
 2 files changed, 3339 insertions(+), 40 deletions(-)
 create mode 100755 your-code/.ipynb_checkpoints/main-checkpoint.ipynb

diff --git a/your-code/.ipynb_checkpoints/main-checkpoint.ipynb b/your-code/.ipynb_checkpoints/main-checkpoint.ipynb
new file mode 100755
index 0000000..8f51d95
--- /dev/null
+++ b/your-code/.ipynb_checkpoints/main-checkpoint.ipynb
@@ -0,0 +1,1988 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Before your start:\n",
+    "- Read the README.md file\n",
+    "- Comment as much as you can and use the resources in the README.md file\n",
+    "- Happy learning!"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 65,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Collecting seaborn\n",
+      "  Downloading seaborn-0.11.1-py3-none-any.whl (285 kB)\n",
+      "\u001b[K     |████████████████████████████████| 285 kB 8.3 MB/s eta 0:00:01\n",
+      "\u001b[?25hRequirement already satisfied: scipy>=1.0 in /Users/usuario/opt/anaconda3/envs/clase/lib/python3.8/site-packages (from seaborn) (1.6.3)\n",
+      "Requirement already satisfied: numpy>=1.15 in /Users/usuario/opt/anaconda3/envs/clase/lib/python3.8/site-packages (from seaborn) (1.20.3)\n",
+      "Requirement already satisfied: pandas>=0.23 in /Users/usuario/opt/anaconda3/envs/clase/lib/python3.8/site-packages (from seaborn) (1.2.4)\n",
+      "Requirement already satisfied: matplotlib>=2.2 in /Users/usuario/opt/anaconda3/envs/clase/lib/python3.8/site-packages (from seaborn) (3.4.2)\n",
+      "Requirement already satisfied: pytz>=2017.3 in /Users/usuario/opt/anaconda3/envs/clase/lib/python3.8/site-packages (from pandas>=0.23->seaborn) (2021.1)\n",
+      "Requirement already satisfied: python-dateutil>=2.7.3 in /Users/usuario/opt/anaconda3/envs/clase/lib/python3.8/site-packages (from pandas>=0.23->seaborn) (2.8.1)\n",
+      "Requirement already satisfied: pillow>=6.2.0 in /Users/usuario/opt/anaconda3/envs/clase/lib/python3.8/site-packages (from matplotlib>=2.2->seaborn) (8.2.0)\n",
+      "Requirement already satisfied: kiwisolver>=1.0.1 in /Users/usuario/opt/anaconda3/envs/clase/lib/python3.8/site-packages (from matplotlib>=2.2->seaborn) (1.3.1)\n",
+      "Requirement already satisfied: pyparsing>=2.2.1 in /Users/usuario/opt/anaconda3/envs/clase/lib/python3.8/site-packages (from matplotlib>=2.2->seaborn) (2.4.7)\n",
+      "Requirement already satisfied: cycler>=0.10 in /Users/usuario/opt/anaconda3/envs/clase/lib/python3.8/site-packages (from matplotlib>=2.2->seaborn) (0.10.0)\n",
+      "Requirement already satisfied: six>=1.5 in /Users/usuario/opt/anaconda3/envs/clase/lib/python3.8/site-packages (from python-dateutil>=2.7.3->pandas>=0.23->seaborn) (1.15.0)\n",
+      "Installing collected packages: seaborn\n",
+      "Successfully installed seaborn-0.11.1\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Import your libraries:\n",
+    "#!pip install matplotlib\n",
+    "#!pip install seaborn\n",
+    "%matplotlib inline\n",
+    "\n",
+    "import numpy as np\n",
+    "import pandas as pd\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "In this lab, we will explore a dataset that describes websites with different features and labels them either benign or malicious . We will use supervised learning algorithms to figure out what feature patterns malicious websites are likely to have and use our model to predict malicious websites.\n",
+    "\n",
+    "# Challenge 1 - Explore The Dataset\n",
+    "\n",
+    "Let's start by exploring the dataset. First load the data file:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "websites = pd.read_csv('../website.csv')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Explore the data from an bird's-eye view.\n",
+    "\n",
+    "You should already been very familiar with the procedures now so we won't provide the instructions step by step. Reflect on what you did in the previous labs and explore the dataset.\n",
+    "\n",
+    "Things you'll be looking for:\n",
+    "\n",
+    "* What the dataset looks like?\n",
+    "* What are the data types?\n",
+    "* Which columns contain the features of the websites?\n",
+    "* Which column contains the feature we will predict? What is the code standing for benign vs malicious websites?\n",
+    "* Do we need to transform any of the columns from categorical to ordinal values? If so what are these columns?\n",
+    "\n",
+    "Feel free to add additional cells for your explorations. Make sure to comment what you find out."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "metadata": {},
+   "outputs": [
+    {
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+       "</div>"
+      ],
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+       "        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",
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+       "\n",
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+       "0                                               nginx           263.0   \n",
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+       "4                                                None        124140.0   \n",
+       "..                                                ...             ...   \n",
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+       "\n",
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+       "0           None           None  10/10/2015 18:21               None  ...   \n",
+       "1           None           None              None               None  ...   \n",
+       "2           None           None              None               None  ...   \n",
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+       "4             US             TX   12/05/1996 0:00    11/04/2017 0:00  ...   \n",
+       "..           ...            ...               ...                ...  ...   \n",
+       "75            US       Kentucky   11/01/1997 0:00    30/04/2015 0:00  ...   \n",
+       "76            US             MD   11/06/2000 0:00     3/03/2017 0:00  ...   \n",
+       "77            CA             ON  13/02/2002 19:55   23/02/2017 17:46  ...   \n",
+       "78            PA         PANAMA   19/12/2007 0:00    21/11/2016 0:00  ...   \n",
+       "79          None           None    6/11/1997 0:00     6/11/2016 0:00  ...   \n",
+       "\n",
+       "    DIST_REMOTE_TCP_PORT  REMOTE_IPS  APP_BYTES  SOURCE_APP_PACKETS  \\\n",
+       "0                      0           2        700                   9   \n",
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+       "    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",
+       "75                   0                 0                 0            0   \n",
+       "76                   0                 0                 0            0   \n",
+       "77                   0                 0                 0            0   \n",
+       "78                   0                 0                 0            0   \n",
+       "79                  19              6226              1856           19   \n",
+       "\n",
+       "    DNS_QUERY_TIMES  Type  \n",
+       "0               2.0     1  \n",
+       "1               0.0     0  \n",
+       "2               0.0     0  \n",
+       "3               8.0     0  \n",
+       "4               4.0     0  \n",
+       "..              ...   ...  \n",
+       "75              0.0     0  \n",
+       "76              0.0     0  \n",
+       "77              0.0     0  \n",
+       "78              0.0     0  \n",
+       "79              6.0     0  \n",
+       "\n",
+       "[80 rows x 21 columns]"
+      ]
+     },
+     "execution_count": 52,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Your code here\n",
+    "\n",
+    "websites.head(80)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(1781, 21)"
+      ]
+     },
+     "execution_count": 30,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "websites.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "RangeIndex: 1781 entries, 0 to 1780\n",
+      "Data columns (total 21 columns):\n",
+      " #   Column                     Non-Null Count  Dtype  \n",
+      "---  ------                     --------------  -----  \n",
+      " 0   URL                        1781 non-null   object \n",
+      " 1   URL_LENGTH                 1781 non-null   int64  \n",
+      " 2   NUMBER_SPECIAL_CHARACTERS  1781 non-null   int64  \n",
+      " 3   CHARSET                    1781 non-null   object \n",
+      " 4   SERVER                     1780 non-null   object \n",
+      " 5   CONTENT_LENGTH             969 non-null    float64\n",
+      " 6   WHOIS_COUNTRY              1781 non-null   object \n",
+      " 7   WHOIS_STATEPRO             1781 non-null   object \n",
+      " 8   WHOIS_REGDATE              1781 non-null   object \n",
+      " 9   WHOIS_UPDATED_DATE         1781 non-null   object \n",
+      " 10  TCP_CONVERSATION_EXCHANGE  1781 non-null   int64  \n",
+      " 11  DIST_REMOTE_TCP_PORT       1781 non-null   int64  \n",
+      " 12  REMOTE_IPS                 1781 non-null   int64  \n",
+      " 13  APP_BYTES                  1781 non-null   int64  \n",
+      " 14  SOURCE_APP_PACKETS         1781 non-null   int64  \n",
+      " 15  REMOTE_APP_PACKETS         1781 non-null   int64  \n",
+      " 16  SOURCE_APP_BYTES           1781 non-null   int64  \n",
+      " 17  REMOTE_APP_BYTES           1781 non-null   int64  \n",
+      " 18  APP_PACKETS                1781 non-null   int64  \n",
+      " 19  DNS_QUERY_TIMES            1780 non-null   float64\n",
+      " 20  Type                       1781 non-null   int64  \n",
+      "dtypes: float64(2), int64(12), object(7)\n",
+      "memory usage: 292.3+ KB\n"
+     ]
+    }
+   ],
+   "source": [
+    "websites.info()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "814"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "websites.isna().sum().sum()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "URL                            0\n",
+       "URL_LENGTH                     0\n",
+       "NUMBER_SPECIAL_CHARACTERS      0\n",
+       "CHARSET                        0\n",
+       "SERVER                         1\n",
+       "CONTENT_LENGTH               812\n",
+       "WHOIS_COUNTRY                  0\n",
+       "WHOIS_STATEPRO                 0\n",
+       "WHOIS_REGDATE                  0\n",
+       "WHOIS_UPDATED_DATE             0\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": 31,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "websites.isnull().sum(axis = 0)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 54,
+   "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>APP_BYTES</th>\n",
+       "      <th>REMOTE_IPS</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>M0_109</td>\n",
+       "      <td>700</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>B0_2314</td>\n",
+       "      <td>1230</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>B0_911</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>B0_113</td>\n",
+       "      <td>3812</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>B0_403</td>\n",
+       "      <td>4278</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1776</th>\n",
+       "      <td>M4_48</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1777</th>\n",
+       "      <td>M4_41</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1778</th>\n",
+       "      <td>B0_162</td>\n",
+       "      <td>6631</td>\n",
+       "      <td>6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1779</th>\n",
+       "      <td>B0_1152</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1780</th>\n",
+       "      <td>B0_676</td>\n",
+       "      <td>2314</td>\n",
+       "      <td>11</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>1781 rows × 3 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "          URL  APP_BYTES  REMOTE_IPS\n",
+       "0      M0_109        700           2\n",
+       "1     B0_2314       1230           4\n",
+       "2      B0_911          0           0\n",
+       "3      B0_113       3812           3\n",
+       "4      B0_403       4278           5\n",
+       "...       ...        ...         ...\n",
+       "1776    M4_48          0           0\n",
+       "1777    M4_41          0           0\n",
+       "1778   B0_162       6631           6\n",
+       "1779  B0_1152          0           0\n",
+       "1780   B0_676       2314          11\n",
+       "\n",
+       "[1781 rows x 3 columns]"
+      ]
+     },
+     "execution_count": 54,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "websites[[\"URL\",\"APP_BYTES\",\"REMOTE_IPS\"][:100]]\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df = websites.select_dtypes(include=['int64', 'float64'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 58,
+   "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>CONTENT_LENGTH</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>263.0</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>15087.0</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>324.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
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+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>17</td>\n",
+       "      <td>6</td>\n",
+       "      <td>162.0</td>\n",
+       "      <td>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>124140.0</td>\n",
+       "      <td>57</td>\n",
+       "      <td>2</td>\n",
+       "      <td>5</td>\n",
+       "      <td>4278</td>\n",
+       "      <td>61</td>\n",
+       "      <td>62</td>\n",
+       "      <td>129889</td>\n",
+       "      <td>4586</td>\n",
+       "      <td>61</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1776</th>\n",
+       "      <td>194</td>\n",
+       "      <td>16</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>186</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1777</th>\n",
+       "      <td>198</td>\n",
+       "      <td>17</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>2</td>\n",
+       "      <td>124</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1778</th>\n",
+       "      <td>201</td>\n",
+       "      <td>34</td>\n",
+       "      <td>8904.0</td>\n",
+       "      <td>83</td>\n",
+       "      <td>2</td>\n",
+       "      <td>6</td>\n",
+       "      <td>6631</td>\n",
+       "      <td>87</td>\n",
+       "      <td>89</td>\n",
+       "      <td>132181</td>\n",
+       "      <td>6945</td>\n",
+       "      <td>87</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1779</th>\n",
+       "      <td>234</td>\n",
+       "      <td>34</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1780</th>\n",
+       "      <td>249</td>\n",
+       "      <td>40</td>\n",
+       "      <td>24435.0</td>\n",
+       "      <td>19</td>\n",
+       "      <td>6</td>\n",
+       "      <td>11</td>\n",
+       "      <td>2314</td>\n",
+       "      <td>25</td>\n",
+       "      <td>28</td>\n",
+       "      <td>3039</td>\n",
+       "      <td>2776</td>\n",
+       "      <td>25</td>\n",
+       "      <td>6.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>1781 rows × 14 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      URL_LENGTH  NUMBER_SPECIAL_CHARACTERS  CONTENT_LENGTH  \\\n",
+       "0             16                          7           263.0   \n",
+       "1             16                          6         15087.0   \n",
+       "2             16                          6           324.0   \n",
+       "3             17                          6           162.0   \n",
+       "4             17                          6        124140.0   \n",
+       "...          ...                        ...             ...   \n",
+       "1776         194                         16             NaN   \n",
+       "1777         198                         17             NaN   \n",
+       "1778         201                         34          8904.0   \n",
+       "1779         234                         34             NaN   \n",
+       "1780         249                         40         24435.0   \n",
+       "\n",
+       "      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",
+       "1776                          0                     0           0          0   \n",
+       "1777                          0                     0           0          0   \n",
+       "1778                         83                     2           6       6631   \n",
+       "1779                          0                     0           0          0   \n",
+       "1780                         19                     6          11       2314   \n",
+       "\n",
+       "      SOURCE_APP_PACKETS  REMOTE_APP_PACKETS  SOURCE_APP_BYTES  \\\n",
+       "0                      9                  10              1153   \n",
+       "1                     17                  19              1265   \n",
+       "2                      0                   0                 0   \n",
+       "3                     39                  37             18784   \n",
+       "4                     61                  62            129889   \n",
+       "...                  ...                 ...               ...   \n",
+       "1776                   0                   3               186   \n",
+       "1777                   0                   2               124   \n",
+       "1778                  87                  89            132181   \n",
+       "1779                   0                   0                 0   \n",
+       "1780                  25                  28              3039   \n",
+       "\n",
+       "      REMOTE_APP_BYTES  APP_PACKETS  DNS_QUERY_TIMES  Type  \n",
+       "0                  832            9              2.0     1  \n",
+       "1                 1230           17              0.0     0  \n",
+       "2                    0            0              0.0     0  \n",
+       "3                 4380           39              8.0     0  \n",
+       "4                 4586           61              4.0     0  \n",
+       "...                ...          ...              ...   ...  \n",
+       "1776                 0            0              0.0     1  \n",
+       "1777                 0            0              0.0     1  \n",
+       "1778              6945           87              4.0     0  \n",
+       "1779                 0            0              0.0     0  \n",
+       "1780              2776           25              6.0     0  \n",
+       "\n",
+       "[1781 rows x 14 columns]"
+      ]
+     },
+     "execution_count": 58,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Your comment here\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Next, evaluate if the columns in this dataset are strongly correlated.\n",
+    "\n",
+    "In the Mushroom supervised learning lab we did recently, we mentioned we are concerned if our dataset has strongly correlated columns because if it is the case we need to choose certain ML algorithms instead of others. We need to evaluate this for our dataset now.\n",
+    "\n",
+    "Luckily, most of the columns in this dataset are ordinal which makes things a lot easier for us. In the next cells below, evaluate the level of collinearity of the data.\n",
+    "\n",
+    "We provide some general directions for you to consult in order to complete this step:\n",
+    "\n",
+    "1. You will create a correlation matrix using the numeric columns in the dataset.\n",
+    "\n",
+    "1. Create a heatmap using `seaborn` to visualize which columns have high collinearity.\n",
+    "\n",
+    "1. Comment on which columns you might need to remove due to high collinearity."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 70,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import seaborn as sns\n",
+    "import matplotlib.pyplot as plt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 71,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sns.heatmap(df.corr());"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 68,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Your code here\n",
+    "\n",
+    "plt.figure(figsize=(16, 6))\n",
+    "heatmap = sns.heatmap(df.corr(), vmin=-1, vmax=1, annot=True, cmap='BrBG')\n",
+    "heatmap.set_title('Correlation Heatmap', fontdict={'fontsize':18}, pad=12);\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 62,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Your comment here"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Challenge 2 - Remove Column Collinearity.\n",
+    "\n",
+    "From the heatmap you created, you should have seen at least 3 columns that can be removed due to high collinearity. Remove these columns from the dataset.\n",
+    "\n",
+    "Note that you should remove as few columns as you can. You don't have to remove all the columns at once. But instead, try removing one column, then produce the heatmap again to determine if additional columns should be removed. As long as the dataset no longer contains columns that are correlated for over 90%, you can stop. Also, keep in mind when two columns have high collinearity, you only need to remove one of them but not both.\n",
+    "\n",
+    "In the cells below, remove as few columns as you can to eliminate the high collinearity in the dataset. Make sure to comment on your way so that the instructional team can learn about your thinking process which allows them to give feedback. At the end, print the heatmap again."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 72,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Your code here\n",
+    "\n",
+    "df=df.drop(columns=['SOURCE_APP_PACKETS', 'SOURCE_APP_BYTES', \n",
+    "                    'TCP_CONVERSATION_EXCHANGE', 'REMOTE_APP_BYTES'], axis=1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Your comment here"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 74,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Print heatmap again\n",
+    "plt.figure(figsize=(16, 6))\n",
+    "heatmap = sns.heatmap(df.corr(), vmin=-1, vmax=1, annot=True, cmap='BrBG')\n",
+    "heatmap.set_title('Correlation Heatmap', fontdict={'fontsize':18}, pad=12);\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Challenge 3 - Handle Missing Values\n",
+    "\n",
+    "The next step would be handling missing values. **We start by examining the number of missing values in each column, which you will do in the next cell.**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 75,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "CONTENT_LENGTH     812\n",
+       "DNS_QUERY_TIMES      1\n",
+       "dtype: int64"
+      ]
+     },
+     "execution_count": 75,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Your code here\n",
+    "nan_cols=df.isna().sum()\n",
+    "\n",
+    "nan_cols[nan_cols>0]\n"
+   ]
+  },
+  {
+   "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": 77,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Your code here\n",
+    "df.DNS_QUERY_TIMES=df.DNS_QUERY_TIMES.fillna(df.DNS_QUERY_TIMES.mean())\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 79,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "CONTENT_LENGTH    812\n",
+       "dtype: int64"
+      ]
+     },
+     "execution_count": 79,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nan_cols=df.isna().sum()\n",
+    "\n",
+    "nan_cols[nan_cols>0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 81,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df.CONTENT_LENGTH=df.CONTENT_LENGTH.fillna(df.CONTENT_LENGTH.mean())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Your comment here\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Again, examine the number of missing values in each column. \n",
+    "\n",
+    "If all cleaned, proceed. Otherwise, go back and do more cleaning."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 83,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Series([], dtype: int64)"
+      ]
+     },
+     "execution_count": 83,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Examine missing values in each column\n",
+    "nan_cols=df.isna().sum()\n",
+    "\n",
+    "nan_cols[nan_cols>0]\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Challenge 4 - Handle `WHOIS_*` Categorical Data"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "There are several categorical columns we need to handle. These columns are:\n",
+    "\n",
+    "* `URL`\n",
+    "* `CHARSET`\n",
+    "* `SERVER`\n",
+    "* `WHOIS_COUNTRY`\n",
+    "* `WHOIS_STATEPRO`\n",
+    "* `WHOIS_REGDATE`\n",
+    "* `WHOIS_UPDATED_DATE`\n",
+    "\n",
+    "How to handle string columns is always case by case. Let's start by working on `WHOIS_COUNTRY`. Your steps are:\n",
+    "\n",
+    "1. List out the unique values of `WHOIS_COUNTRY`.\n",
+    "1. Consolidate the country values with consistent country codes. For example, the following values refer to the same country and should use consistent country code:\n",
+    "    * `CY` and `Cyprus`\n",
+    "    * `US` and `us`\n",
+    "    * `SE` and `se`\n",
+    "    * `GB`, `United Kingdom`, and `[u'GB'; u'UK']`\n",
+    "\n",
+    "#### In the cells below, fix the country values as intructed above."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 85,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "US                1103\n",
+       "None               306\n",
+       "CA                  84\n",
+       "ES                  63\n",
+       "AU                  35\n",
+       "PA                  21\n",
+       "GB                  19\n",
+       "JP                  11\n",
+       "CN                  10\n",
+       "UK                  10\n",
+       "IN                  10\n",
+       "CZ                   9\n",
+       "FR                   9\n",
+       "CH                   6\n",
+       "NL                   6\n",
+       "[u'GB'; u'UK']       5\n",
+       "KR                   5\n",
+       "PH                   4\n",
+       "AT                   4\n",
+       "ru                   4\n",
+       "BS                   4\n",
+       "us                   3\n",
+       "DE                   3\n",
+       "SE                   3\n",
+       "KY                   3\n",
+       "SC                   3\n",
+       "HK                   3\n",
+       "TR                   3\n",
+       "BE                   3\n",
+       "KG                   2\n",
+       "Cyprus               2\n",
+       "IL                   2\n",
+       "SI                   2\n",
+       "BR                   2\n",
+       "UY                   2\n",
+       "NO                   2\n",
+       "RU                   2\n",
+       "UA                   2\n",
+       "PK                   1\n",
+       "United Kingdom       1\n",
+       "TH                   1\n",
+       "UG                   1\n",
+       "LV                   1\n",
+       "LU                   1\n",
+       "IE                   1\n",
+       "se                   1\n",
+       "BY                   1\n",
+       "AE                   1\n",
+       "IT                   1\n",
+       "Name: WHOIS_COUNTRY, dtype: int64"
+      ]
+     },
+     "execution_count": 85,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Your code here\n",
+    "websites.WHOIS_COUNTRY.value_counts()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 87,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "websites.WHOIS_COUNTRY=websites.WHOIS_COUNTRY.replace('Cyprus', 'CY')\n",
+    "websites.WHOIS_COUNTRY=websites.WHOIS_COUNTRY.replace('us', 'US')\n",
+    "websites.WHOIS_COUNTRY=websites.WHOIS_COUNTRY.replace('se', 'SE')\n",
+    "websites.WHOIS_COUNTRY=websites.WHOIS_COUNTRY.replace('United Kingdom', 'GB')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "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": 94,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Your code here\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "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`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 99,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "ename": "TypeError",
+     "evalue": "'dict' object is not callable",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
+      "\u001b[0;32m<ipython-input-99-06051b85b8fe>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;31m# Your code here\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mdict\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdict\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mwebsites\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'WHOIS_COUNTRY'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalue_counts\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mhead\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m10\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
+      "\u001b[0;31mTypeError\u001b[0m: 'dict' object is not callable"
+     ]
+    }
+   ],
+   "source": [
+    "# Your code here\n",
+    "dict = dict (websites['WHOIS_COUNTRY'].value_counts().head(10))\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 100,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'US': 1106,\n",
+       " 'None': 306,\n",
+       " 'CA': 84,\n",
+       " 'ES': 63,\n",
+       " 'AU': 35,\n",
+       " 'PA': 21,\n",
+       " 'GB': 20,\n",
+       " 'JP': 11,\n",
+       " 'CN': 10,\n",
+       " 'IN': 10}"
+      ]
+     },
+     "execution_count": 100,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "dict"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 103,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "websites['WHOIS_COUNTRY']=websites['WHOIS_COUNTRY'].apply(lambda x: 'OTHER' if x not in dict else x)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 102,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "US       1106\n",
+       "None      306\n",
+       "OTHER     115\n",
+       "CA         84\n",
+       "ES         63\n",
+       "AU         35\n",
+       "PA         21\n",
+       "GB         20\n",
+       "JP         11\n",
+       "IN         10\n",
+       "CN         10\n",
+       "Name: WHOIS_COUNTRY, dtype: int64"
+      ]
+     },
+     "execution_count": 102,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "websites['WHOIS_COUNTRY'].value_counts()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now since `WHOIS_COUNTRY` has been re-labelled, we don't need `WHOIS_STATEPRO` any more because the values of the states or provinces may not be relevant any more. We'll drop this column.\n",
+    "\n",
+    "In addition, we will also drop `WHOIS_REGDATE` and `WHOIS_UPDATED_DATE`. These are the registration and update dates of the website domains. Not of our concerns.\n",
+    "\n",
+    "#### In the next cell, drop `['WHOIS_STATEPRO', 'WHOIS_REGDATE', 'WHOIS_UPDATED_DATE']`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 104,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "websites=websites.drop(columns=['WHOIS_REGDATE','WHOIS_UPDATED_DATE'])\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 105,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "websites=websites.drop(columns=['WHOIS_STATEPRO'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Your code here\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Challenge 5 - Handle Remaining Categorical Data & Convert to Ordinal\n",
+    "\n",
+    "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": 107,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Your code here\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### `URL` is easy. We'll simply drop it because it has too many unique values that there's no way for us to consolidate."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Your code here\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Print the unique value counts of `CHARSET`. You see there are only a few unique values. So we can keep it as it is."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Your code here"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "`SERVER` is a little more complicated. Print its unique values and think about how you can consolidate those values.\n",
+    "\n",
+    "#### Before you think of your own solution, don't read the instructions that come next."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Your code here\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "![Think Hard](../think-hard.jpg)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Your comment here\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Although there are so many unique values in the `SERVER` column, there are actually only 3 main server types: `Microsoft`, `Apache`, and `nginx`. Just check if each `SERVER` value contains any of those server types and re-label them. For `SERVER` values that don't contain any of those substrings, label with `Other`.\n",
+    "\n",
+    "At the end, your `SERVER` column should only contain 4 unique values: `Microsoft`, `Apache`, `nginx`, and `Other`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Your code here\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "scrolled": false
+   },
+   "outputs": [],
+   "source": [
+    "# Count `SERVER` value counts here\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "OK, all our categorical data are fixed now. **Let's convert them to ordinal data using Pandas' `get_dummies` function ([documentation](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.get_dummies.html)).** Make sure you drop the categorical columns by passing `drop_first=True` to `get_dummies` as we don't need them any more. **Also, assign the data with dummy values to a new variable `website_dummy`.**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Your code here\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now, inspect `website_dummy` to make sure the data and types are intended - there shouldn't be any categorical columns at this point."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Your code here\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Challenge 6 - Modeling, Prediction, and Evaluation\n",
+    "\n",
+    "We'll start off this section by splitting the data to train and test. **Name your 4 variables `X_train`, `X_test`, `y_train`, and `y_test`. Select 80% of the data for training and 20% for testing.**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from sklearn.model_selection import train_test_split\n",
+    "\n",
+    "# Your code here:\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### In this lab, we will try two different models and compare our results.\n",
+    "\n",
+    "The first model we will use in this lab is logistic regression. We have previously learned about logistic regression as a classification algorithm. In the cell below, load `LogisticRegression` from scikit-learn and initialize the model."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Your code here:\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Next, fit the model to our training data. We have already separated our data into 4 parts. Use those in your model."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Your code here:\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "finally, import `confusion_matrix` and `accuracy_score` from `sklearn.metrics` and fit our testing data. Assign the fitted data to `y_pred` and print the confusion matrix as well as the accuracy score"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Your code here:\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "What are your thoughts on the performance of the model? Write your conclusions below."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Your conclusions here:\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Our second algorithm is is K-Nearest Neighbors. \n",
+    "\n",
+    "Though is it not required, we will fit a model using the training data and then test the performance of the model using the testing data. Start by loading `KNeighborsClassifier` from scikit-learn and then initializing and fitting the model. We'll start off with a model where k=3."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Your code here:\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "To test your model, compute the predicted values for the testing sample and print the confusion matrix as well as the accuracy score."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Your code here:\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### We'll create another K-Nearest Neighbors model with k=5. \n",
+    "\n",
+    "Initialize and fit the model below and print the confusion matrix and the accuracy score."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Your code here:\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Did you see an improvement in the confusion matrix when increasing k to 5? Did you see an improvement in the accuracy score? Write your conclusions below."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Your conclusions here:\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Bonus Challenge - Feature Scaling\n",
+    "\n",
+    "Problem-solving in machine learning is iterative. You can improve your model prediction with various techniques (there is a sweetspot for the time you spend and the improvement you receive though). Now you've completed only one iteration of ML analysis. There are more iterations you can conduct to make improvements. In order to be able to do that, you will need deeper knowledge in statistics and master more data analysis techniques. In this bootcamp, we don't have time to achieve that advanced goal. But you will make constant efforts after the bootcamp to eventually get there.\n",
+    "\n",
+    "However, now we do want you to learn one of the advanced techniques which is called *feature scaling*. The idea of feature scaling is to standardize/normalize the range of independent variables or features of the data. This can make the outliers more apparent so that you can remove them. This step needs to happen during Challenge 6 after you split the training and test data because you don't want to split the data again which makes it impossible to compare your results with and without feature scaling. For general concepts about feature scaling, click [here](https://en.wikipedia.org/wiki/Feature_scaling). To read deeper, click [here](https://medium.com/greyatom/why-how-and-when-to-scale-your-features-4b30ab09db5e).\n",
+    "\n",
+    "In the next cell, attempt to improve your model prediction accuracy by means of feature scaling. A library you can utilize is `sklearn.preprocessing.RobustScaler` ([documentation](https://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.RobustScaler.html)). You'll use the `RobustScaler` to fit and transform your `X_train`, then transform `X_test`. You will use logistic regression to fit and predict your transformed data and obtain the accuracy score in the same way. Compare the accuracy score with your normalized data with the previous accuracy data. Is there an improvement?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Your code here"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/your-code/main.ipynb b/your-code/main.ipynb
index 8a1bbee..8f51d95 100755
--- a/your-code/main.ipynb
+++ b/your-code/main.ipynb
@@ -12,16 +12,40 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 65,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Collecting seaborn\n",
+      "  Downloading seaborn-0.11.1-py3-none-any.whl (285 kB)\n",
+      "\u001b[K     |████████████████████████████████| 285 kB 8.3 MB/s eta 0:00:01\n",
+      "\u001b[?25hRequirement already satisfied: scipy>=1.0 in /Users/usuario/opt/anaconda3/envs/clase/lib/python3.8/site-packages (from seaborn) (1.6.3)\n",
+      "Requirement already satisfied: numpy>=1.15 in /Users/usuario/opt/anaconda3/envs/clase/lib/python3.8/site-packages (from seaborn) (1.20.3)\n",
+      "Requirement already satisfied: pandas>=0.23 in /Users/usuario/opt/anaconda3/envs/clase/lib/python3.8/site-packages (from seaborn) (1.2.4)\n",
+      "Requirement already satisfied: matplotlib>=2.2 in /Users/usuario/opt/anaconda3/envs/clase/lib/python3.8/site-packages (from seaborn) (3.4.2)\n",
+      "Requirement already satisfied: pytz>=2017.3 in /Users/usuario/opt/anaconda3/envs/clase/lib/python3.8/site-packages (from pandas>=0.23->seaborn) (2021.1)\n",
+      "Requirement already satisfied: python-dateutil>=2.7.3 in /Users/usuario/opt/anaconda3/envs/clase/lib/python3.8/site-packages (from pandas>=0.23->seaborn) (2.8.1)\n",
+      "Requirement already satisfied: pillow>=6.2.0 in /Users/usuario/opt/anaconda3/envs/clase/lib/python3.8/site-packages (from matplotlib>=2.2->seaborn) (8.2.0)\n",
+      "Requirement already satisfied: kiwisolver>=1.0.1 in /Users/usuario/opt/anaconda3/envs/clase/lib/python3.8/site-packages (from matplotlib>=2.2->seaborn) (1.3.1)\n",
+      "Requirement already satisfied: pyparsing>=2.2.1 in /Users/usuario/opt/anaconda3/envs/clase/lib/python3.8/site-packages (from matplotlib>=2.2->seaborn) (2.4.7)\n",
+      "Requirement already satisfied: cycler>=0.10 in /Users/usuario/opt/anaconda3/envs/clase/lib/python3.8/site-packages (from matplotlib>=2.2->seaborn) (0.10.0)\n",
+      "Requirement already satisfied: six>=1.5 in /Users/usuario/opt/anaconda3/envs/clase/lib/python3.8/site-packages (from python-dateutil>=2.7.3->pandas>=0.23->seaborn) (1.15.0)\n",
+      "Installing collected packages: seaborn\n",
+      "Successfully installed seaborn-0.11.1\n"
+     ]
+    }
+   ],
    "source": [
     "# Import your libraries:\n",
-    "\n",
+    "#!pip install matplotlib\n",
+    "#!pip install seaborn\n",
     "%matplotlib inline\n",
     "\n",
     "import numpy as np\n",
-    "import pandas as pd"
+    "import pandas as pd\n"
    ]
   },
   {
@@ -37,7 +61,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -65,11 +89,977 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 52,
+   "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>...</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>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>10/10/2015 18:21</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</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>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</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>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</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>...</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>None</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>...</td>\n",
+       "      <td>2</td>\n",
+       "      <td>5</td>\n",
+       "      <td>4278</td>\n",
+       "      <td>61</td>\n",
+       "      <td>62</td>\n",
+       "      <td>129889</td>\n",
+       "      <td>4586</td>\n",
+       "      <td>61</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>75</th>\n",
+       "      <td>B0_1125</td>\n",
+       "      <td>26</td>\n",
+       "      <td>6</td>\n",
+       "      <td>utf-8</td>\n",
+       "      <td>nginx</td>\n",
+       "      <td>2688.0</td>\n",
+       "      <td>US</td>\n",
+       "      <td>Kentucky</td>\n",
+       "      <td>11/01/1997 0:00</td>\n",
+       "      <td>30/04/2015 0:00</td>\n",
+       "      <td>...</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>76</th>\n",
+       "      <td>B0_1205</td>\n",
+       "      <td>26</td>\n",
+       "      <td>7</td>\n",
+       "      <td>UTF-8</td>\n",
+       "      <td>cloudflare-nginx</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>US</td>\n",
+       "      <td>MD</td>\n",
+       "      <td>11/06/2000 0:00</td>\n",
+       "      <td>3/03/2017 0:00</td>\n",
+       "      <td>...</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>77</th>\n",
+       "      <td>B0_1321</td>\n",
+       "      <td>26</td>\n",
+       "      <td>6</td>\n",
+       "      <td>UTF-8</td>\n",
+       "      <td>nginx</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>CA</td>\n",
+       "      <td>ON</td>\n",
+       "      <td>13/02/2002 19:55</td>\n",
+       "      <td>23/02/2017 17:46</td>\n",
+       "      <td>...</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>78</th>\n",
+       "      <td>B0_1374</td>\n",
+       "      <td>26</td>\n",
+       "      <td>6</td>\n",
+       "      <td>iso-8859-1</td>\n",
+       "      <td>Apache</td>\n",
+       "      <td>199.0</td>\n",
+       "      <td>PA</td>\n",
+       "      <td>PANAMA</td>\n",
+       "      <td>19/12/2007 0:00</td>\n",
+       "      <td>21/11/2016 0:00</td>\n",
+       "      <td>...</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>79</th>\n",
+       "      <td>B0_159</td>\n",
+       "      <td>26</td>\n",
+       "      <td>6</td>\n",
+       "      <td>UTF-8</td>\n",
+       "      <td>Apache/2.4.25 (cPanel) OpenSSL/1.0.1e-fips mod...</td>\n",
+       "      <td>3548.0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>6/11/1997 0:00</td>\n",
+       "      <td>6/11/2016 0:00</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1378</td>\n",
+       "      <td>19</td>\n",
+       "      <td>19</td>\n",
+       "      <td>6226</td>\n",
+       "      <td>1856</td>\n",
+       "      <td>19</td>\n",
+       "      <td>6.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>80 rows × 21 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        URL  URL_LENGTH  NUMBER_SPECIAL_CHARACTERS     CHARSET  \\\n",
+       "0    M0_109          16                          7  iso-8859-1   \n",
+       "1   B0_2314          16                          6       UTF-8   \n",
+       "2    B0_911          16                          6    us-ascii   \n",
+       "3    B0_113          17                          6  ISO-8859-1   \n",
+       "4    B0_403          17                          6       UTF-8   \n",
+       "..      ...         ...                        ...         ...   \n",
+       "75  B0_1125          26                          6       utf-8   \n",
+       "76  B0_1205          26                          7       UTF-8   \n",
+       "77  B0_1321          26                          6       UTF-8   \n",
+       "78  B0_1374          26                          6  iso-8859-1   \n",
+       "79   B0_159          26                          6       UTF-8   \n",
+       "\n",
+       "                                               SERVER  CONTENT_LENGTH  \\\n",
+       "0                                               nginx           263.0   \n",
+       "1                                       Apache/2.4.10         15087.0   \n",
+       "2                               Microsoft-HTTPAPI/2.0           324.0   \n",
+       "3                                               nginx           162.0   \n",
+       "4                                                None        124140.0   \n",
+       "..                                                ...             ...   \n",
+       "75                                              nginx          2688.0   \n",
+       "76                                   cloudflare-nginx             NaN   \n",
+       "77                                              nginx             NaN   \n",
+       "78                                             Apache           199.0   \n",
+       "79  Apache/2.4.25 (cPanel) OpenSSL/1.0.1e-fips mod...          3548.0   \n",
+       "\n",
+       "   WHOIS_COUNTRY WHOIS_STATEPRO     WHOIS_REGDATE WHOIS_UPDATED_DATE  ...  \\\n",
+       "0           None           None  10/10/2015 18:21               None  ...   \n",
+       "1           None           None              None               None  ...   \n",
+       "2           None           None              None               None  ...   \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",
+       "75            US       Kentucky   11/01/1997 0:00    30/04/2015 0:00  ...   \n",
+       "76            US             MD   11/06/2000 0:00     3/03/2017 0:00  ...   \n",
+       "77            CA             ON  13/02/2002 19:55   23/02/2017 17:46  ...   \n",
+       "78            PA         PANAMA   19/12/2007 0:00    21/11/2016 0:00  ...   \n",
+       "79          None           None    6/11/1997 0:00     6/11/2016 0:00  ...   \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",
+       "75                     0           0          0                   0   \n",
+       "76                     0           0          0                   0   \n",
+       "77                     0           0          0                   0   \n",
+       "78                     0           0          0                   0   \n",
+       "79                     0           1       1378                  19   \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",
+       "75                   0                 0                 0            0   \n",
+       "76                   0                 0                 0            0   \n",
+       "77                   0                 0                 0            0   \n",
+       "78                   0                 0                 0            0   \n",
+       "79                  19              6226              1856           19   \n",
+       "\n",
+       "    DNS_QUERY_TIMES  Type  \n",
+       "0               2.0     1  \n",
+       "1               0.0     0  \n",
+       "2               0.0     0  \n",
+       "3               8.0     0  \n",
+       "4               4.0     0  \n",
+       "..              ...   ...  \n",
+       "75              0.0     0  \n",
+       "76              0.0     0  \n",
+       "77              0.0     0  \n",
+       "78              0.0     0  \n",
+       "79              6.0     0  \n",
+       "\n",
+       "[80 rows x 21 columns]"
+      ]
+     },
+     "execution_count": 52,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Your code here\n",
+    "\n",
+    "websites.head(80)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(1781, 21)"
+      ]
+     },
+     "execution_count": 30,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "websites.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "RangeIndex: 1781 entries, 0 to 1780\n",
+      "Data columns (total 21 columns):\n",
+      " #   Column                     Non-Null Count  Dtype  \n",
+      "---  ------                     --------------  -----  \n",
+      " 0   URL                        1781 non-null   object \n",
+      " 1   URL_LENGTH                 1781 non-null   int64  \n",
+      " 2   NUMBER_SPECIAL_CHARACTERS  1781 non-null   int64  \n",
+      " 3   CHARSET                    1781 non-null   object \n",
+      " 4   SERVER                     1780 non-null   object \n",
+      " 5   CONTENT_LENGTH             969 non-null    float64\n",
+      " 6   WHOIS_COUNTRY              1781 non-null   object \n",
+      " 7   WHOIS_STATEPRO             1781 non-null   object \n",
+      " 8   WHOIS_REGDATE              1781 non-null   object \n",
+      " 9   WHOIS_UPDATED_DATE         1781 non-null   object \n",
+      " 10  TCP_CONVERSATION_EXCHANGE  1781 non-null   int64  \n",
+      " 11  DIST_REMOTE_TCP_PORT       1781 non-null   int64  \n",
+      " 12  REMOTE_IPS                 1781 non-null   int64  \n",
+      " 13  APP_BYTES                  1781 non-null   int64  \n",
+      " 14  SOURCE_APP_PACKETS         1781 non-null   int64  \n",
+      " 15  REMOTE_APP_PACKETS         1781 non-null   int64  \n",
+      " 16  SOURCE_APP_BYTES           1781 non-null   int64  \n",
+      " 17  REMOTE_APP_BYTES           1781 non-null   int64  \n",
+      " 18  APP_PACKETS                1781 non-null   int64  \n",
+      " 19  DNS_QUERY_TIMES            1780 non-null   float64\n",
+      " 20  Type                       1781 non-null   int64  \n",
+      "dtypes: float64(2), int64(12), object(7)\n",
+      "memory usage: 292.3+ KB\n"
+     ]
+    }
+   ],
+   "source": [
+    "websites.info()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "814"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "websites.isna().sum().sum()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "URL                            0\n",
+       "URL_LENGTH                     0\n",
+       "NUMBER_SPECIAL_CHARACTERS      0\n",
+       "CHARSET                        0\n",
+       "SERVER                         1\n",
+       "CONTENT_LENGTH               812\n",
+       "WHOIS_COUNTRY                  0\n",
+       "WHOIS_STATEPRO                 0\n",
+       "WHOIS_REGDATE                  0\n",
+       "WHOIS_UPDATED_DATE             0\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": 31,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "websites.isnull().sum(axis = 0)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 54,
+   "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>APP_BYTES</th>\n",
+       "      <th>REMOTE_IPS</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>M0_109</td>\n",
+       "      <td>700</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>B0_2314</td>\n",
+       "      <td>1230</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>B0_911</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>B0_113</td>\n",
+       "      <td>3812</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>B0_403</td>\n",
+       "      <td>4278</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1776</th>\n",
+       "      <td>M4_48</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1777</th>\n",
+       "      <td>M4_41</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1778</th>\n",
+       "      <td>B0_162</td>\n",
+       "      <td>6631</td>\n",
+       "      <td>6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1779</th>\n",
+       "      <td>B0_1152</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1780</th>\n",
+       "      <td>B0_676</td>\n",
+       "      <td>2314</td>\n",
+       "      <td>11</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>1781 rows × 3 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "          URL  APP_BYTES  REMOTE_IPS\n",
+       "0      M0_109        700           2\n",
+       "1     B0_2314       1230           4\n",
+       "2      B0_911          0           0\n",
+       "3      B0_113       3812           3\n",
+       "4      B0_403       4278           5\n",
+       "...       ...        ...         ...\n",
+       "1776    M4_48          0           0\n",
+       "1777    M4_41          0           0\n",
+       "1778   B0_162       6631           6\n",
+       "1779  B0_1152          0           0\n",
+       "1780   B0_676       2314          11\n",
+       "\n",
+       "[1781 rows x 3 columns]"
+      ]
+     },
+     "execution_count": 54,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "websites[[\"URL\",\"APP_BYTES\",\"REMOTE_IPS\"][:100]]\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your code here\n"
+    "df = websites.select_dtypes(include=['int64', 'float64'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 58,
+   "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>CONTENT_LENGTH</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>263.0</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>15087.0</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>324.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>17</td>\n",
+       "      <td>6</td>\n",
+       "      <td>162.0</td>\n",
+       "      <td>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>124140.0</td>\n",
+       "      <td>57</td>\n",
+       "      <td>2</td>\n",
+       "      <td>5</td>\n",
+       "      <td>4278</td>\n",
+       "      <td>61</td>\n",
+       "      <td>62</td>\n",
+       "      <td>129889</td>\n",
+       "      <td>4586</td>\n",
+       "      <td>61</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1776</th>\n",
+       "      <td>194</td>\n",
+       "      <td>16</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>186</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1777</th>\n",
+       "      <td>198</td>\n",
+       "      <td>17</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>2</td>\n",
+       "      <td>124</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1778</th>\n",
+       "      <td>201</td>\n",
+       "      <td>34</td>\n",
+       "      <td>8904.0</td>\n",
+       "      <td>83</td>\n",
+       "      <td>2</td>\n",
+       "      <td>6</td>\n",
+       "      <td>6631</td>\n",
+       "      <td>87</td>\n",
+       "      <td>89</td>\n",
+       "      <td>132181</td>\n",
+       "      <td>6945</td>\n",
+       "      <td>87</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1779</th>\n",
+       "      <td>234</td>\n",
+       "      <td>34</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1780</th>\n",
+       "      <td>249</td>\n",
+       "      <td>40</td>\n",
+       "      <td>24435.0</td>\n",
+       "      <td>19</td>\n",
+       "      <td>6</td>\n",
+       "      <td>11</td>\n",
+       "      <td>2314</td>\n",
+       "      <td>25</td>\n",
+       "      <td>28</td>\n",
+       "      <td>3039</td>\n",
+       "      <td>2776</td>\n",
+       "      <td>25</td>\n",
+       "      <td>6.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>1781 rows × 14 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      URL_LENGTH  NUMBER_SPECIAL_CHARACTERS  CONTENT_LENGTH  \\\n",
+       "0             16                          7           263.0   \n",
+       "1             16                          6         15087.0   \n",
+       "2             16                          6           324.0   \n",
+       "3             17                          6           162.0   \n",
+       "4             17                          6        124140.0   \n",
+       "...          ...                        ...             ...   \n",
+       "1776         194                         16             NaN   \n",
+       "1777         198                         17             NaN   \n",
+       "1778         201                         34          8904.0   \n",
+       "1779         234                         34             NaN   \n",
+       "1780         249                         40         24435.0   \n",
+       "\n",
+       "      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",
+       "1776                          0                     0           0          0   \n",
+       "1777                          0                     0           0          0   \n",
+       "1778                         83                     2           6       6631   \n",
+       "1779                          0                     0           0          0   \n",
+       "1780                         19                     6          11       2314   \n",
+       "\n",
+       "      SOURCE_APP_PACKETS  REMOTE_APP_PACKETS  SOURCE_APP_BYTES  \\\n",
+       "0                      9                  10              1153   \n",
+       "1                     17                  19              1265   \n",
+       "2                      0                   0                 0   \n",
+       "3                     39                  37             18784   \n",
+       "4                     61                  62            129889   \n",
+       "...                  ...                 ...               ...   \n",
+       "1776                   0                   3               186   \n",
+       "1777                   0                   2               124   \n",
+       "1778                  87                  89            132181   \n",
+       "1779                   0                   0                 0   \n",
+       "1780                  25                  28              3039   \n",
+       "\n",
+       "      REMOTE_APP_BYTES  APP_PACKETS  DNS_QUERY_TIMES  Type  \n",
+       "0                  832            9              2.0     1  \n",
+       "1                 1230           17              0.0     0  \n",
+       "2                    0            0              0.0     0  \n",
+       "3                 4380           39              8.0     0  \n",
+       "4                 4586           61              4.0     0  \n",
+       "...                ...          ...              ...   ...  \n",
+       "1776                 0            0              0.0     1  \n",
+       "1777                 0            0              0.0     1  \n",
+       "1778              6945           87              4.0     0  \n",
+       "1779                 0            0              0.0     0  \n",
+       "1780              2776           25              6.0     0  \n",
+       "\n",
+       "[1781 rows x 14 columns]"
+      ]
+     },
+     "execution_count": 58,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df"
    ]
   },
   {
@@ -78,7 +1068,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your comment here"
+    "# Your comment here\n"
    ]
   },
   {
@@ -102,16 +1092,65 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 70,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your code here\n"
+    "import seaborn as sns\n",
+    "import matplotlib.pyplot as plt"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 71,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sns.heatmap(df.corr());"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 68,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Your code here\n",
+    "\n",
+    "plt.figure(figsize=(16, 6))\n",
+    "heatmap = sns.heatmap(df.corr(), vmin=-1, vmax=1, annot=True, cmap='BrBG')\n",
+    "heatmap.set_title('Correlation Heatmap', fontdict={'fontsize':18}, pad=12);\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 62,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -133,11 +1172,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 72,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your code here\n"
+    "# Your code here\n",
+    "\n",
+    "df=df.drop(columns=['SOURCE_APP_PACKETS', 'SOURCE_APP_BYTES', \n",
+    "                    'TCP_CONVERSATION_EXCHANGE', 'REMOTE_APP_BYTES'], axis=1)"
    ]
   },
   {
@@ -151,11 +1193,27 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Print heatmap again\n"
+   "execution_count": 74,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Print heatmap again\n",
+    "plt.figure(figsize=(16, 6))\n",
+    "heatmap = sns.heatmap(df.corr(), vmin=-1, vmax=1, annot=True, cmap='BrBG')\n",
+    "heatmap.set_title('Correlation Heatmap', fontdict={'fontsize':18}, pad=12);\n"
    ]
   },
   {
@@ -169,11 +1227,27 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Your code here\n"
+   "execution_count": 75,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "CONTENT_LENGTH     812\n",
+       "DNS_QUERY_TIMES      1\n",
+       "dtype: int64"
+      ]
+     },
+     "execution_count": 75,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Your code here\n",
+    "nan_cols=df.isna().sum()\n",
+    "\n",
+    "nan_cols[nan_cols>0]\n"
    ]
   },
   {
@@ -187,11 +1261,44 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 77,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your code here\n"
+    "# Your code here\n",
+    "df.DNS_QUERY_TIMES=df.DNS_QUERY_TIMES.fillna(df.DNS_QUERY_TIMES.mean())\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 79,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "CONTENT_LENGTH    812\n",
+       "dtype: int64"
+      ]
+     },
+     "execution_count": 79,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nan_cols=df.isna().sum()\n",
+    "\n",
+    "nan_cols[nan_cols>0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 81,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df.CONTENT_LENGTH=df.CONTENT_LENGTH.fillna(df.CONTENT_LENGTH.mean())"
    ]
   },
   {
@@ -200,7 +1307,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your comment here"
+    "# Your comment here\n"
    ]
   },
   {
@@ -214,11 +1321,26 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Examine missing values in each column\n"
+   "execution_count": 83,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Series([], dtype: int64)"
+      ]
+     },
+     "execution_count": 83,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Examine missing values in each column\n",
+    "nan_cols=df.isna().sum()\n",
+    "\n",
+    "nan_cols[nan_cols>0]\n",
+    "\n"
    ]
   },
   {
@@ -256,13 +1378,93 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 85,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "US                1103\n",
+       "None               306\n",
+       "CA                  84\n",
+       "ES                  63\n",
+       "AU                  35\n",
+       "PA                  21\n",
+       "GB                  19\n",
+       "JP                  11\n",
+       "CN                  10\n",
+       "UK                  10\n",
+       "IN                  10\n",
+       "CZ                   9\n",
+       "FR                   9\n",
+       "CH                   6\n",
+       "NL                   6\n",
+       "[u'GB'; u'UK']       5\n",
+       "KR                   5\n",
+       "PH                   4\n",
+       "AT                   4\n",
+       "ru                   4\n",
+       "BS                   4\n",
+       "us                   3\n",
+       "DE                   3\n",
+       "SE                   3\n",
+       "KY                   3\n",
+       "SC                   3\n",
+       "HK                   3\n",
+       "TR                   3\n",
+       "BE                   3\n",
+       "KG                   2\n",
+       "Cyprus               2\n",
+       "IL                   2\n",
+       "SI                   2\n",
+       "BR                   2\n",
+       "UY                   2\n",
+       "NO                   2\n",
+       "RU                   2\n",
+       "UA                   2\n",
+       "PK                   1\n",
+       "United Kingdom       1\n",
+       "TH                   1\n",
+       "UG                   1\n",
+       "LV                   1\n",
+       "LU                   1\n",
+       "IE                   1\n",
+       "se                   1\n",
+       "BY                   1\n",
+       "AE                   1\n",
+       "IT                   1\n",
+       "Name: WHOIS_COUNTRY, dtype: int64"
+      ]
+     },
+     "execution_count": 85,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Your code here\n",
+    "websites.WHOIS_COUNTRY.value_counts()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 87,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your code here\n"
+    "websites.WHOIS_COUNTRY=websites.WHOIS_COUNTRY.replace('Cyprus', 'CY')\n",
+    "websites.WHOIS_COUNTRY=websites.WHOIS_COUNTRY.replace('us', 'US')\n",
+    "websites.WHOIS_COUNTRY=websites.WHOIS_COUNTRY.replace('se', 'SE')\n",
+    "websites.WHOIS_COUNTRY=websites.WHOIS_COUNTRY.replace('United Kingdom', 'GB')"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -278,13 +1480,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 94,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your code here\n"
+    "# Your code here\n",
+    "\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -294,13 +1504,95 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 99,
    "metadata": {
     "scrolled": true
    },
+   "outputs": [
+    {
+     "ename": "TypeError",
+     "evalue": "'dict' object is not callable",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
+      "\u001b[0;32m<ipython-input-99-06051b85b8fe>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;31m# Your code here\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mdict\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdict\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mwebsites\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'WHOIS_COUNTRY'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalue_counts\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mhead\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m10\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
+      "\u001b[0;31mTypeError\u001b[0m: 'dict' object is not callable"
+     ]
+    }
+   ],
+   "source": [
+    "# Your code here\n",
+    "dict = dict (websites['WHOIS_COUNTRY'].value_counts().head(10))\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 100,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'US': 1106,\n",
+       " 'None': 306,\n",
+       " 'CA': 84,\n",
+       " 'ES': 63,\n",
+       " 'AU': 35,\n",
+       " 'PA': 21,\n",
+       " 'GB': 20,\n",
+       " 'JP': 11,\n",
+       " 'CN': 10,\n",
+       " 'IN': 10}"
+      ]
+     },
+     "execution_count": 100,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "dict"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 103,
+   "metadata": {},
    "outputs": [],
    "source": [
-    "# Your code here\n"
+    "websites['WHOIS_COUNTRY']=websites['WHOIS_COUNTRY'].apply(lambda x: 'OTHER' if x not in dict else x)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 102,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "US       1106\n",
+       "None      306\n",
+       "OTHER     115\n",
+       "CA         84\n",
+       "ES         63\n",
+       "AU         35\n",
+       "PA         21\n",
+       "GB         20\n",
+       "JP         11\n",
+       "IN         10\n",
+       "CN         10\n",
+       "Name: WHOIS_COUNTRY, dtype: int64"
+      ]
+     },
+     "execution_count": 102,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "websites['WHOIS_COUNTRY'].value_counts()"
    ]
   },
   {
@@ -314,6 +1606,25 @@
     "#### In the next cell, drop `['WHOIS_STATEPRO', 'WHOIS_REGDATE', 'WHOIS_UPDATED_DATE']`."
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 104,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "websites=websites.drop(columns=['WHOIS_REGDATE','WHOIS_UPDATED_DATE'])\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 105,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "websites=websites.drop(columns=['WHOIS_STATEPRO'])"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -334,7 +1645,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 107,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -669,7 +1980,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.6"
+   "version": "3.8.5"
   }
  },
  "nbformat": 4,