From 4772f9cde0ed39dca53cbd28aab275db3b0da8be Mon Sep 17 00:00:00 2001
From: CevicX <134785214+CevicX@users.noreply.github.com>
Date: Thu, 24 Aug 2023 11:54:35 +0100
Subject: [PATCH] done

---
 your-code/main.ipynb | 1316 ++++++++++++++++++++++++++++++++++++++----
 1 file changed, 1219 insertions(+), 97 deletions(-)

diff --git a/your-code/main.ipynb b/your-code/main.ipynb
index a5caf8b..fa6a141 100755
--- a/your-code/main.ipynb
+++ b/your-code/main.ipynb
@@ -67,15 +67,274 @@
    "cell_type": "code",
    "execution_count": 3,
    "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Your code here\n"
+   "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>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10/10/2015 18:21</td>\n",
+       "      <td>NaN</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>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</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>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</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>NaN</td>\n",
+       "      <td>124140.0</td>\n",
+       "      <td>US</td>\n",
+       "      <td>TX</td>\n",
+       "      <td>12/05/1996 0:00</td>\n",
+       "      <td>11/04/2017 0:00</td>\n",
+       "      <td>...</td>\n",
+       "      <td>2</td>\n",
+       "      <td>5</td>\n",
+       "      <td>4278</td>\n",
+       "      <td>61</td>\n",
+       "      <td>62</td>\n",
+       "      <td>129889</td>\n",
+       "      <td>4586</td>\n",
+       "      <td>61</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>5 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",
+       "                  SERVER  CONTENT_LENGTH WHOIS_COUNTRY WHOIS_STATEPRO  \\\n",
+       "0                  nginx           263.0           NaN            NaN   \n",
+       "1          Apache/2.4.10         15087.0           NaN            NaN   \n",
+       "2  Microsoft-HTTPAPI/2.0           324.0           NaN            NaN   \n",
+       "3                  nginx           162.0            US             AK   \n",
+       "4                    NaN        124140.0            US             TX   \n",
+       "\n",
+       "      WHOIS_REGDATE WHOIS_UPDATED_DATE  ...  DIST_REMOTE_TCP_PORT  REMOTE_IPS  \\\n",
+       "0  10/10/2015 18:21                NaN  ...                     0           2   \n",
+       "1               NaN                NaN  ...                     7           4   \n",
+       "2               NaN                NaN  ...                     0           0   \n",
+       "3    7/10/1997 4:00    12/09/2013 0:45  ...                    22           3   \n",
+       "4   12/05/1996 0:00    11/04/2017 0:00  ...                     2           5   \n",
+       "\n",
+       "   APP_BYTES  SOURCE_APP_PACKETS  REMOTE_APP_PACKETS  SOURCE_APP_BYTES  \\\n",
+       "0        700                   9                  10              1153   \n",
+       "1       1230                  17                  19              1265   \n",
+       "2          0                   0                   0                 0   \n",
+       "3       3812                  39                  37             18784   \n",
+       "4       4278                  61                  62            129889   \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",
+       "[5 rows x 21 columns]"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Your code here\n",
+    "websites.head()"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 4,
    "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                    1774 non-null   object \n",
+      " 4   SERVER                     1605 non-null   object \n",
+      " 5   CONTENT_LENGTH             969 non-null    float64\n",
+      " 6   WHOIS_COUNTRY              1475 non-null   object \n",
+      " 7   WHOIS_STATEPRO             1419 non-null   object \n",
+      " 8   WHOIS_REGDATE              1654 non-null   object \n",
+      " 9   WHOIS_UPDATED_DATE         1642 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": 5,
+   "metadata": {},
    "outputs": [],
    "source": [
     "# Your comment here"
@@ -102,20 +361,48 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 6,
    "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Your code here\n"
+   "outputs": [
+    {
+     "data": {
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",
+      "text/plain": [
+       "<Figure size 1400x1400 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "import seaborn as sn\n",
+    "\n",
+    "corr=websites.corr(numeric_only=True)\n",
+    "\n",
+    "#Set up mask for triangle representation\n",
+    "mask = np.zeros_like(corr, dtype=bool)\n",
+    "mask[np.triu_indices_from(mask)] = True\n",
+    "\n",
+    "# Set up the matplotlib figure\n",
+    "f, ax = plt.subplots(figsize=(14, 14))\n",
+    "# Generate a custom diverging colormap\n",
+    "cmap = sn.diverging_palette(220, 10, as_cmap=True)\n",
+    "# Draw the heatmap with the mask and correct aspect ratio\n",
+    "sn.heatmap(corr, mask=mask,  vmax=1,square=True, linewidths=.5, cbar_kws={\"shrink\": .5},annot = corr)\n",
+    "\n",
+    "plt.show()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your comment here"
+    "# Your comment here\n",
+    "#TCP_CONVERSATION_EXCHANGE has the highest correlation,Source_app_packets is the second one, and Remote_app_packets is the third"
    ]
   },
   {
@@ -133,29 +420,241 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 8,
    "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Your code here\n"
+   "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>CONTENT_LENGTH</th>\n",
+       "      <th>DIST_REMOTE_TCP_PORT</th>\n",
+       "      <th>REMOTE_IPS</th>\n",
+       "      <th>APP_BYTES</th>\n",
+       "      <th>REMOTE_APP_PACKETS</th>\n",
+       "      <th>SOURCE_APP_BYTES</th>\n",
+       "      <th>DNS_QUERY_TIMES</th>\n",
+       "      <th>Type</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>URL_LENGTH</th>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.129745</td>\n",
+       "      <td>-0.039839</td>\n",
+       "      <td>-0.046367</td>\n",
+       "      <td>-0.026446</td>\n",
+       "      <td>-0.033779</td>\n",
+       "      <td>-0.014857</td>\n",
+       "      <td>-0.068582</td>\n",
+       "      <td>0.162104</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>CONTENT_LENGTH</th>\n",
+       "      <td>0.129745</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>-0.000381</td>\n",
+       "      <td>0.004774</td>\n",
+       "      <td>0.051202</td>\n",
+       "      <td>0.091077</td>\n",
+       "      <td>0.100094</td>\n",
+       "      <td>-0.045644</td>\n",
+       "      <td>-0.090852</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>DIST_REMOTE_TCP_PORT</th>\n",
+       "      <td>-0.039839</td>\n",
+       "      <td>-0.000381</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.210188</td>\n",
+       "      <td>0.780238</td>\n",
+       "      <td>0.591188</td>\n",
+       "      <td>0.313359</td>\n",
+       "      <td>0.259942</td>\n",
+       "      <td>-0.082925</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>REMOTE_IPS</th>\n",
+       "      <td>-0.046367</td>\n",
+       "      <td>0.004774</td>\n",
+       "      <td>0.210188</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.023126</td>\n",
+       "      <td>0.304683</td>\n",
+       "      <td>0.171651</td>\n",
+       "      <td>0.548189</td>\n",
+       "      <td>-0.078783</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>APP_BYTES</th>\n",
+       "      <td>-0.026446</td>\n",
+       "      <td>0.051202</td>\n",
+       "      <td>0.780238</td>\n",
+       "      <td>0.023126</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.468999</td>\n",
+       "      <td>0.074464</td>\n",
+       "      <td>0.012221</td>\n",
+       "      <td>-0.011262</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>REMOTE_APP_PACKETS</th>\n",
+       "      <td>-0.033779</td>\n",
+       "      <td>0.091077</td>\n",
+       "      <td>0.591188</td>\n",
+       "      <td>0.304683</td>\n",
+       "      <td>0.468999</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.880555</td>\n",
+       "      <td>0.355716</td>\n",
+       "      <td>-0.032897</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>SOURCE_APP_BYTES</th>\n",
+       "      <td>-0.014857</td>\n",
+       "      <td>0.100094</td>\n",
+       "      <td>0.313359</td>\n",
+       "      <td>0.171651</td>\n",
+       "      <td>0.074464</td>\n",
+       "      <td>0.880555</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.215285</td>\n",
+       "      <td>-0.043852</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>DNS_QUERY_TIMES</th>\n",
+       "      <td>-0.068582</td>\n",
+       "      <td>-0.045644</td>\n",
+       "      <td>0.259942</td>\n",
+       "      <td>0.548189</td>\n",
+       "      <td>0.012221</td>\n",
+       "      <td>0.355716</td>\n",
+       "      <td>0.215285</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.068753</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Type</th>\n",
+       "      <td>0.162104</td>\n",
+       "      <td>-0.090852</td>\n",
+       "      <td>-0.082925</td>\n",
+       "      <td>-0.078783</td>\n",
+       "      <td>-0.011262</td>\n",
+       "      <td>-0.032897</td>\n",
+       "      <td>-0.043852</td>\n",
+       "      <td>0.068753</td>\n",
+       "      <td>1.000000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                      URL_LENGTH  CONTENT_LENGTH  DIST_REMOTE_TCP_PORT  \\\n",
+       "URL_LENGTH              1.000000        0.129745             -0.039839   \n",
+       "CONTENT_LENGTH          0.129745        1.000000             -0.000381   \n",
+       "DIST_REMOTE_TCP_PORT   -0.039839       -0.000381              1.000000   \n",
+       "REMOTE_IPS             -0.046367        0.004774              0.210188   \n",
+       "APP_BYTES              -0.026446        0.051202              0.780238   \n",
+       "REMOTE_APP_PACKETS     -0.033779        0.091077              0.591188   \n",
+       "SOURCE_APP_BYTES       -0.014857        0.100094              0.313359   \n",
+       "DNS_QUERY_TIMES        -0.068582       -0.045644              0.259942   \n",
+       "Type                    0.162104       -0.090852             -0.082925   \n",
+       "\n",
+       "                      REMOTE_IPS  APP_BYTES  REMOTE_APP_PACKETS  \\\n",
+       "URL_LENGTH             -0.046367  -0.026446           -0.033779   \n",
+       "CONTENT_LENGTH          0.004774   0.051202            0.091077   \n",
+       "DIST_REMOTE_TCP_PORT    0.210188   0.780238            0.591188   \n",
+       "REMOTE_IPS              1.000000   0.023126            0.304683   \n",
+       "APP_BYTES               0.023126   1.000000            0.468999   \n",
+       "REMOTE_APP_PACKETS      0.304683   0.468999            1.000000   \n",
+       "SOURCE_APP_BYTES        0.171651   0.074464            0.880555   \n",
+       "DNS_QUERY_TIMES         0.548189   0.012221            0.355716   \n",
+       "Type                   -0.078783  -0.011262           -0.032897   \n",
+       "\n",
+       "                      SOURCE_APP_BYTES  DNS_QUERY_TIMES      Type  \n",
+       "URL_LENGTH                   -0.014857        -0.068582  0.162104  \n",
+       "CONTENT_LENGTH                0.100094        -0.045644 -0.090852  \n",
+       "DIST_REMOTE_TCP_PORT          0.313359         0.259942 -0.082925  \n",
+       "REMOTE_IPS                    0.171651         0.548189 -0.078783  \n",
+       "APP_BYTES                     0.074464         0.012221 -0.011262  \n",
+       "REMOTE_APP_PACKETS            0.880555         0.355716 -0.032897  \n",
+       "SOURCE_APP_BYTES              1.000000         0.215285 -0.043852  \n",
+       "DNS_QUERY_TIMES               0.215285         1.000000  0.068753  \n",
+       "Type                         -0.043852         0.068753  1.000000  "
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Your code here\n",
+    "websites_2=websites.drop(['APP_PACKETS','TCP_CONVERSATION_EXCHANGE','NUMBER_SPECIAL_CHARACTERS','SOURCE_APP_PACKETS','REMOTE_APP_BYTES'],axis=1)\n",
+    "corr=websites_2.corr(numeric_only=True)\n",
+    "corr"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your comment here"
+    "# Your comment here\n",
+    "#Now none of them have a high correlation(Considering it < 90%)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 10,
    "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Print heatmap again\n"
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1400x1400 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Print heatmap again\n",
+    "#Set up mask for triangle representation\n",
+    "mask = np.zeros_like(corr, dtype=bool)\n",
+    "mask[np.triu_indices_from(mask)] = True\n",
+    "\n",
+    "# Set up the matplotlib figure\n",
+    "f, ax = plt.subplots(figsize=(14, 14))\n",
+    "# Generate a custom diverging colormap\n",
+    "cmap = sn.diverging_palette(220, 10, as_cmap=True)\n",
+    "# Draw the heatmap with the mask and correct aspect ratio\n",
+    "sn.heatmap(corr, mask=mask,  vmax=1,square=True, linewidths=.5, cbar_kws={\"shrink\": .5},annot = corr)\n",
+    "\n",
+    "plt.show()"
    ]
   },
   {
@@ -169,11 +668,39 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 11,
    "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Your code here\n"
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "URL                       0\n",
+       "URL_LENGTH                0\n",
+       "CHARSET                   7\n",
+       "SERVER                  176\n",
+       "CONTENT_LENGTH          812\n",
+       "WHOIS_COUNTRY           306\n",
+       "WHOIS_STATEPRO          362\n",
+       "WHOIS_REGDATE           127\n",
+       "WHOIS_UPDATED_DATE      139\n",
+       "DIST_REMOTE_TCP_PORT      0\n",
+       "REMOTE_IPS                0\n",
+       "APP_BYTES                 0\n",
+       "REMOTE_APP_PACKETS        0\n",
+       "SOURCE_APP_BYTES          0\n",
+       "DNS_QUERY_TIMES           1\n",
+       "Type                      0\n",
+       "dtype: int64"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Your code here\n",
+    "websites_2.isna().sum()"
    ]
   },
   {
@@ -187,20 +714,45 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0.45592363840539024\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Your code here\n",
+    "print(len(websites_2[websites_2['CONTENT_LENGTH'].isna()])/len(websites_2))\n",
+    "websites_2.drop('CONTENT_LENGTH',axis=1,inplace=True)\n",
+    "websites_2.drop('URL_LENGTH',axis=1,inplace=True)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your code here\n"
+    "websites_2.dropna(subset=['WHOIS_STATEPRO'], inplace=True)\n",
+    "websites_2.dropna(subset=['WHOIS_REGDATE'], inplace=True)\n",
+    "websites_2.dropna(subset=['CHARSET'], inplace=True)\n",
+    "websites_2.dropna(subset=['SERVER'], inplace=True)\n",
+    "websites_2.dropna(subset=['DNS_QUERY_TIMES'], inplace=True)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your comment here"
+    "# Your comment here\n",
+    "#Got rid of the length there is no need for us to have it,and also got rid of the WHOIS_STATEPRO,WHOIS_REGDATE,CHARSET and SERVER nulls"
    ]
   },
   {
@@ -214,11 +766,37 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 15,
    "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Examine missing values in each column\n"
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "URL                     0\n",
+       "CHARSET                 0\n",
+       "SERVER                  0\n",
+       "WHOIS_COUNTRY           0\n",
+       "WHOIS_STATEPRO          0\n",
+       "WHOIS_REGDATE           0\n",
+       "WHOIS_UPDATED_DATE      0\n",
+       "DIST_REMOTE_TCP_PORT    0\n",
+       "REMOTE_IPS              0\n",
+       "APP_BYTES               0\n",
+       "REMOTE_APP_PACKETS      0\n",
+       "SOURCE_APP_BYTES        0\n",
+       "DNS_QUERY_TIMES         0\n",
+       "Type                    0\n",
+       "dtype: int64"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Examine missing values in each column\n",
+    "websites_2.isna().sum()"
    ]
   },
   {
@@ -256,11 +834,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your code here\n"
+    "# Your code here\n",
+    "websites_2['WHOIS_COUNTRY'].value_counts()\n",
+    "websites_2['WHOIS_COUNTRY'].replace(\"[u'GB'; u'UK']\",\"GB\",inplace=True)\n",
+    "websites_2['WHOIS_COUNTRY'].replace(\"Cyprus\",\"CY\",inplace=True)\n",
+    "websites_2['WHOIS_COUNTRY'].replace(\"us\",\"US\",inplace=True)\n",
+    "websites_2['WHOIS_COUNTRY'].replace(\"ru\",\"RU\",inplace=True)\n",
+    "websites_2['WHOIS_COUNTRY'].replace(\"se\",\"SE\",inplace=True)"
    ]
   },
   {
@@ -278,11 +862,33 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 17,
    "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Your code here\n"
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Axes: xlabel='WHOIS_COUNTRY'>"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Your code here\n",
+    "websites_2['WHOIS_COUNTRY'].value_counts().plot(kind='bar')"
    ]
   },
   {
@@ -294,13 +900,48 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "for i in websites_2['WHOIS_COUNTRY']:\n",
+    "    if websites_2['WHOIS_COUNTRY'].value_counts()[i]<8:\n",
+    "        websites_2['WHOIS_COUNTRY'].replace(i,\"Other\",inplace=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
    "metadata": {
     "scrolled": true
    },
-   "outputs": [],
-   "source": [
-    "# Your code here\n"
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "WHOIS_COUNTRY\n",
+       "US       960\n",
+       "CA        75\n",
+       "ES        63\n",
+       "Other     60\n",
+       "AU        26\n",
+       "PA        21\n",
+       "GB        18\n",
+       "JP        10\n",
+       "IN         8\n",
+       "CN         8\n",
+       "CZ         8\n",
+       "Name: count, dtype: int64"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Your code here\n",
+    "websites_2['WHOIS_COUNTRY'].value_counts()"
    ]
   },
   {
@@ -316,11 +957,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 20,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your code here\n"
+    "# Your code here\n",
+    "websites_2.drop(['WHOIS_STATEPRO', 'WHOIS_REGDATE', 'WHOIS_UPDATED_DATE'],axis=1,inplace=True)"
    ]
   },
   {
@@ -334,11 +976,34 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 21,
    "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Your code here\n"
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "URL                      object\n",
+       "CHARSET                  object\n",
+       "SERVER                   object\n",
+       "WHOIS_COUNTRY            object\n",
+       "DIST_REMOTE_TCP_PORT      int64\n",
+       "REMOTE_IPS                int64\n",
+       "APP_BYTES                 int64\n",
+       "REMOTE_APP_PACKETS        int64\n",
+       "SOURCE_APP_BYTES          int64\n",
+       "DNS_QUERY_TIMES         float64\n",
+       "Type                      int64\n",
+       "dtype: object"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Your code here\n",
+    "websites_2.dtypes"
    ]
   },
   {
@@ -350,11 +1015,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 22,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your code here\n"
+    "# Your code here\n",
+    "websites_2.drop('URL',axis=1,inplace=True)"
    ]
   },
   {
@@ -366,11 +1032,31 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Your code here"
+   "execution_count": 23,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "CHARSET\n",
+       "UTF-8           520\n",
+       "utf-8           279\n",
+       "ISO-8859-1      275\n",
+       "us-ascii         98\n",
+       "iso-8859-1       83\n",
+       "windows-1251      1\n",
+       "windows-1252      1\n",
+       "Name: count, dtype: int64"
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Your code here\n",
+    "websites_2['CHARSET'].value_counts()"
    ]
   },
   {
@@ -384,11 +1070,35 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 24,
    "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Your code here\n"
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "SERVER\n",
+       "Apache                                                                                311\n",
+       "nginx                                                                                 144\n",
+       "cloudflare-nginx                                                                       80\n",
+       "Microsoft-HTTPAPI/2.0                                                                  76\n",
+       "GSE                                                                                    49\n",
+       "                                                                                     ... \n",
+       "Apache/2.4.6 (CentOS) OpenSSL/1.0.1e-fips mod_fcgid/2.3.9 PHP/5.4.16 mod_jk/1.2.40      1\n",
+       "mw2114.codfw.wmnet                                                                      1\n",
+       "mw2199.codfw.wmnet                                                                      1\n",
+       "fbs                                                                                     1\n",
+       "Apache/2.2.16 (Debian)                                                                  1\n",
+       "Name: count, Length: 193, dtype: int64"
+      ]
+     },
+     "execution_count": 24,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Your code here\n",
+    "websites_2['SERVER'].value_counts()"
    ]
   },
   {
@@ -400,11 +1110,23 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 25,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'Change everything to a single type like:Apache/2.2.16 (Debian)= Apache'"
+      ]
+     },
+     "execution_count": 25,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# Your comment here\n"
+    "# Your comment here\n",
+    "'''Change everything to a single type like:Apache/2.2.16 (Debian)= Apache'''"
    ]
   },
   {
@@ -418,22 +1140,45 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 26,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your code here\n"
+    "# Your code here\n",
+    "websites_2['SERVER'].replace(r'.*Apache.*',\"Apache\",regex=True,inplace=True)\n",
+    "websites_2['SERVER'].replace(r'.*nginx.*',\"nginx\",regex=True,inplace=True)\n",
+    "websites_2['SERVER'].replace(r'.*Microsoft.*',\"Microsoft\",regex=True,inplace=True)\n",
+    "for i in websites_2['SERVER']:\n",
+    "    if websites_2['SERVER'].value_counts()[i]<144:\n",
+    "        websites_2['SERVER'].replace(i,\"Other\",inplace=True)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 27,
    "metadata": {
     "scrolled": false
    },
-   "outputs": [],
-   "source": [
-    "# Count `SERVER` value counts here\n"
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "SERVER\n",
+       "Apache       491\n",
+       "nginx        322\n",
+       "Other        300\n",
+       "Microsoft    144\n",
+       "Name: count, dtype: int64"
+      ]
+     },
+     "execution_count": 27,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Count `SERVER` value counts here\n",
+    "websites_2['SERVER'].value_counts()"
    ]
   },
   {
@@ -445,11 +1190,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 28,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your code here\n"
+    "# Your code here\n",
+    "websites_dummy=pd.get_dummies(websites_2)"
    ]
   },
   {
@@ -461,11 +1207,282 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": 29,
    "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Your code here\n"
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "DIST_REMOTE_TCP_PORT      int64\n",
+       "REMOTE_IPS                int64\n",
+       "APP_BYTES                 int64\n",
+       "REMOTE_APP_PACKETS        int64\n",
+       "SOURCE_APP_BYTES          int64\n",
+       "DNS_QUERY_TIMES         float64\n",
+       "Type                      int64\n",
+       "CHARSET_ISO-8859-1         bool\n",
+       "CHARSET_UTF-8              bool\n",
+       "CHARSET_iso-8859-1         bool\n",
+       "CHARSET_us-ascii           bool\n",
+       "CHARSET_utf-8              bool\n",
+       "CHARSET_windows-1251       bool\n",
+       "CHARSET_windows-1252       bool\n",
+       "SERVER_Apache              bool\n",
+       "SERVER_Microsoft           bool\n",
+       "SERVER_Other               bool\n",
+       "SERVER_nginx               bool\n",
+       "WHOIS_COUNTRY_AU           bool\n",
+       "WHOIS_COUNTRY_CA           bool\n",
+       "WHOIS_COUNTRY_CN           bool\n",
+       "WHOIS_COUNTRY_CZ           bool\n",
+       "WHOIS_COUNTRY_ES           bool\n",
+       "WHOIS_COUNTRY_GB           bool\n",
+       "WHOIS_COUNTRY_IN           bool\n",
+       "WHOIS_COUNTRY_JP           bool\n",
+       "WHOIS_COUNTRY_Other        bool\n",
+       "WHOIS_COUNTRY_PA           bool\n",
+       "WHOIS_COUNTRY_US           bool\n",
+       "dtype: object"
+      ]
+     },
+     "execution_count": 29,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Your code here\n",
+    "websites_dummy.dtypes"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "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>DIST_REMOTE_TCP_PORT</th>\n",
+       "      <th>REMOTE_IPS</th>\n",
+       "      <th>APP_BYTES</th>\n",
+       "      <th>REMOTE_APP_PACKETS</th>\n",
+       "      <th>SOURCE_APP_BYTES</th>\n",
+       "      <th>DNS_QUERY_TIMES</th>\n",
+       "      <th>Type</th>\n",
+       "      <th>CHARSET_ISO-8859-1</th>\n",
+       "      <th>CHARSET_UTF-8</th>\n",
+       "      <th>CHARSET_iso-8859-1</th>\n",
+       "      <th>...</th>\n",
+       "      <th>WHOIS_COUNTRY_CA</th>\n",
+       "      <th>WHOIS_COUNTRY_CN</th>\n",
+       "      <th>WHOIS_COUNTRY_CZ</th>\n",
+       "      <th>WHOIS_COUNTRY_ES</th>\n",
+       "      <th>WHOIS_COUNTRY_GB</th>\n",
+       "      <th>WHOIS_COUNTRY_IN</th>\n",
+       "      <th>WHOIS_COUNTRY_JP</th>\n",
+       "      <th>WHOIS_COUNTRY_Other</th>\n",
+       "      <th>WHOIS_COUNTRY_PA</th>\n",
+       "      <th>WHOIS_COUNTRY_US</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>22</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3812</td>\n",
+       "      <td>37</td>\n",
+       "      <td>18784</td>\n",
+       "      <td>8.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>...</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>6</td>\n",
+       "      <td>9</td>\n",
+       "      <td>894</td>\n",
+       "      <td>13</td>\n",
+       "      <td>838</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>...</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1189</td>\n",
+       "      <td>13</td>\n",
+       "      <td>8559</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>...</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>...</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>...</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>5 rows × 29 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    DIST_REMOTE_TCP_PORT  REMOTE_IPS  APP_BYTES  REMOTE_APP_PACKETS  \\\n",
+       "3                     22           3       3812                  37   \n",
+       "5                      6           9        894                  13   \n",
+       "6                      0           3       1189                  13   \n",
+       "7                      0           0          0                   0   \n",
+       "10                     0           0          0                   0   \n",
+       "\n",
+       "    SOURCE_APP_BYTES  DNS_QUERY_TIMES  Type  CHARSET_ISO-8859-1  \\\n",
+       "3              18784              8.0     0                True   \n",
+       "5                838              0.0     0               False   \n",
+       "6               8559              2.0     0               False   \n",
+       "7                  0              0.0     0               False   \n",
+       "10                 0              0.0     0               False   \n",
+       "\n",
+       "    CHARSET_UTF-8  CHARSET_iso-8859-1  ...  WHOIS_COUNTRY_CA  \\\n",
+       "3           False               False  ...             False   \n",
+       "5            True               False  ...             False   \n",
+       "6           False                True  ...             False   \n",
+       "7           False               False  ...             False   \n",
+       "10          False               False  ...             False   \n",
+       "\n",
+       "    WHOIS_COUNTRY_CN  WHOIS_COUNTRY_CZ  WHOIS_COUNTRY_ES  WHOIS_COUNTRY_GB  \\\n",
+       "3              False             False             False             False   \n",
+       "5              False             False             False             False   \n",
+       "6              False             False             False             False   \n",
+       "7              False             False             False             False   \n",
+       "10             False             False             False             False   \n",
+       "\n",
+       "    WHOIS_COUNTRY_IN  WHOIS_COUNTRY_JP  WHOIS_COUNTRY_Other  WHOIS_COUNTRY_PA  \\\n",
+       "3              False             False                False             False   \n",
+       "5              False             False                 True             False   \n",
+       "6              False             False                False             False   \n",
+       "7              False             False                False             False   \n",
+       "10             False             False                False             False   \n",
+       "\n",
+       "    WHOIS_COUNTRY_US  \n",
+       "3               True  \n",
+       "5              False  \n",
+       "6               True  \n",
+       "7               True  \n",
+       "10              True  \n",
+       "\n",
+       "[5 rows x 29 columns]"
+      ]
+     },
+     "execution_count": 30,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "websites_dummy.head()"
    ]
   },
   {
@@ -479,13 +1496,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 31,
    "metadata": {},
    "outputs": [],
    "source": [
     "from sklearn.model_selection import train_test_split\n",
     "\n",
-    "# Your code here:\n"
+    "# Your code here:\n",
+    "features=websites_dummy.drop('Type',axis=1)\n",
+    "labels=websites_dummy['Type']\n",
+    "X_train,X_test,y_train,y_test=train_test_split(features,labels,test_size=0.2)"
    ]
   },
   {
@@ -499,12 +1519,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 32,
    "metadata": {},
    "outputs": [],
    "source": [
     "# Your code here:\n",
-    "\n"
+    "from sklearn.linear_model import LogisticRegression\n",
+    "\n",
+    "model=LogisticRegression(max_iter=1000)"
    ]
   },
   {
@@ -516,12 +1538,26 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": 33,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<style>#sk-container-id-1 {color: black;background-color: white;}#sk-container-id-1 pre{padding: 0;}#sk-container-id-1 div.sk-toggleable {background-color: white;}#sk-container-id-1 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-1 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-1 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-1 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-1 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-1 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-1 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-1 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-1 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-1 div.sk-item {position: relative;z-index: 1;}#sk-container-id-1 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-1 div.sk-item::before, #sk-container-id-1 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-1 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-1 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-1 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-1 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-1 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-1 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-1 div.sk-label-container {text-align: center;}#sk-container-id-1 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-1 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>LogisticRegression(max_iter=1000)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" checked><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">LogisticRegression</label><div class=\"sk-toggleable__content\"><pre>LogisticRegression(max_iter=1000)</pre></div></div></div></div></div>"
+      ],
+      "text/plain": [
+       "LogisticRegression(max_iter=1000)"
+      ]
+     },
+     "execution_count": 33,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "# Your code here:\n",
-    "\n"
+    "model.fit(X_train,y_train)"
    ]
   },
   {
@@ -533,11 +1569,36 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": 34,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[[227   0]\n",
+      " [  0  25]]\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "0.9484126984126984"
+      ]
+     },
+     "execution_count": 34,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "# Your code here:\n",
+    "from sklearn.metrics import accuracy_score,confusion_matrix\n",
+    "\n",
+    "y_pred=model.predict(X_test)\n",
+    "print(confusion_matrix(y_pred,model.predict(X_test)))\n",
+    "accuracy_score(y_pred,y_test)\n",
+    "\n",
     "\n"
    ]
   },
@@ -550,7 +1611,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 35,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -569,12 +1630,28 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": 36,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<style>#sk-container-id-2 {color: black;background-color: white;}#sk-container-id-2 pre{padding: 0;}#sk-container-id-2 div.sk-toggleable {background-color: white;}#sk-container-id-2 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-2 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-2 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-2 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-2 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-2 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-2 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-2 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-2 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-2 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-2 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-2 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-2 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-2 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-2 div.sk-item {position: relative;z-index: 1;}#sk-container-id-2 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-2 div.sk-item::before, #sk-container-id-2 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-2 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-2 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-2 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-2 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-2 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-2 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-2 div.sk-label-container {text-align: center;}#sk-container-id-2 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-2 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-2\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>KNeighborsClassifier(n_neighbors=3)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-2\" type=\"checkbox\" checked><label for=\"sk-estimator-id-2\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">KNeighborsClassifier</label><div class=\"sk-toggleable__content\"><pre>KNeighborsClassifier(n_neighbors=3)</pre></div></div></div></div></div>"
+      ],
+      "text/plain": [
+       "KNeighborsClassifier(n_neighbors=3)"
+      ]
+     },
+     "execution_count": 36,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "# Your code here:\n",
-    "\n"
+    "from sklearn.neighbors import KNeighborsClassifier\n",
+    "knn = KNeighborsClassifier(n_neighbors=3)\n",
+    "knn.fit(X_train, y_train)\n"
    ]
   },
   {
@@ -586,12 +1663,33 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": 37,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[[230   0]\n",
+      " [  0  22]]\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "0.9523809523809523"
+      ]
+     },
+     "execution_count": 37,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "# Your code here:\n",
-    "\n"
+    "y_pred=knn.predict(X_test)\n",
+    "print(confusion_matrix(y_pred,knn.predict(X_test)))\n",
+    "accuracy_score(y_pred,y_test)\n"
    ]
   },
   {
@@ -605,12 +1703,36 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
+   "execution_count": 38,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[[230   0]\n",
+      " [  0  22]]\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "0.9523809523809523"
+      ]
+     },
+     "execution_count": 38,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "# Your code here:\n",
-    "\n"
+    "\n",
+    "knn = KNeighborsClassifier(n_neighbors=5)\n",
+    "knn.fit(X_train, y_train)\n",
+    "y_pred=knn.predict(X_test)\n",
+    "print(confusion_matrix(y_pred,knn.predict(X_test)))\n",
+    "accuracy_score(y_pred,y_test)"
    ]
   },
   {
@@ -622,7 +1744,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 37,
+   "execution_count": 39,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -645,7 +1767,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 38,
+   "execution_count": 40,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -655,9 +1777,9 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "ironhack-3.7",
+   "display_name": "Python 3",
    "language": "python",
-   "name": "ironhack-3.7"
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
@@ -669,7 +1791,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.3"
+   "version": "3.11.4"
   }
  },
  "nbformat": 4,