diff --git a/your-code/main.ipynb b/your-code/main.ipynb
index a5caf8b..fd3a237 100755
--- a/your-code/main.ipynb
+++ b/your-code/main.ipynb
@@ -12,7 +12,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 251,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -37,11 +37,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 252,
    "metadata": {},
    "outputs": [],
    "source": [
-    "websites = pd.read_csv('../data/website.csv')"
+    "websites = pd.read_csv(\"website.csv\")"
    ]
   },
   {
@@ -65,20 +65,268 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Your code here\n"
+   "execution_count": 253,
+   "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",
+       "  </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          None           None   \n",
+       "1          Apache/2.4.10         15087.0          None           None   \n",
+       "2  Microsoft-HTTPAPI/2.0           324.0          None           None   \n",
+       "3                  nginx           162.0            US             AK   \n",
+       "4                   None        124140.0            US             TX   \n",
+       "\n",
+       "      WHOIS_REGDATE WHOIS_UPDATED_DATE  ...  DIST_REMOTE_TCP_PORT  REMOTE_IPS  \\\n",
+       "0  10/10/2015 18:21               None  ...                     0           2   \n",
+       "1              None               None  ...                     7           4   \n",
+       "2              None               None  ...                     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": 253,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Your code here\n",
+    "websites.head()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Your comment here"
+   "execution_count": 254,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "URL                           object\n",
+       "URL_LENGTH                     int64\n",
+       "NUMBER_SPECIAL_CHARACTERS      int64\n",
+       "CHARSET                       object\n",
+       "SERVER                        object\n",
+       "CONTENT_LENGTH               float64\n",
+       "WHOIS_COUNTRY                 object\n",
+       "WHOIS_STATEPRO                object\n",
+       "WHOIS_REGDATE                 object\n",
+       "WHOIS_UPDATED_DATE            object\n",
+       "TCP_CONVERSATION_EXCHANGE      int64\n",
+       "DIST_REMOTE_TCP_PORT           int64\n",
+       "REMOTE_IPS                     int64\n",
+       "APP_BYTES                      int64\n",
+       "SOURCE_APP_PACKETS             int64\n",
+       "REMOTE_APP_PACKETS             int64\n",
+       "SOURCE_APP_BYTES               int64\n",
+       "REMOTE_APP_BYTES               int64\n",
+       "APP_PACKETS                    int64\n",
+       "DNS_QUERY_TIMES              float64\n",
+       "Type                           int64\n",
+       "dtype: object"
+      ]
+     },
+     "execution_count": 254,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Your comment here\n",
+    "websites.dtypes"
    ]
   },
   {
@@ -102,20 +350,444 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Your code here\n"
+   "execution_count": 255,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\carol\\AppData\\Local\\Temp\\ipykernel_17936\\3576182210.py:2: FutureWarning: The default value of numeric_only in DataFrame.corr is deprecated. In a future version, it will default to False. Select only valid columns or specify the value of numeric_only to silence this warning.\n",
+      "  websites.corr()\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>URL_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>URL_LENGTH</th>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.917986</td>\n",
+       "      <td>0.129745</td>\n",
+       "      <td>-0.038407</td>\n",
+       "      <td>-0.039839</td>\n",
+       "      <td>-0.046367</td>\n",
+       "      <td>-0.026446</td>\n",
+       "      <td>-0.042264</td>\n",
+       "      <td>-0.033779</td>\n",
+       "      <td>-0.014857</td>\n",
+       "      <td>-0.026686</td>\n",
+       "      <td>-0.042264</td>\n",
+       "      <td>-0.068582</td>\n",
+       "      <td>0.162104</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>NUMBER_SPECIAL_CHARACTERS</th>\n",
+       "      <td>0.917986</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.214225</td>\n",
+       "      <td>-0.037459</td>\n",
+       "      <td>-0.042619</td>\n",
+       "      <td>-0.047103</td>\n",
+       "      <td>-0.023914</td>\n",
+       "      <td>-0.040096</td>\n",
+       "      <td>-0.030597</td>\n",
+       "      <td>-0.014376</td>\n",
+       "      <td>-0.024098</td>\n",
+       "      <td>-0.040096</td>\n",
+       "      <td>-0.050048</td>\n",
+       "      <td>0.280897</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>CONTENT_LENGTH</th>\n",
+       "      <td>0.129745</td>\n",
+       "      <td>0.214225</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.078451</td>\n",
+       "      <td>-0.000381</td>\n",
+       "      <td>0.004774</td>\n",
+       "      <td>0.051202</td>\n",
+       "      <td>0.074142</td>\n",
+       "      <td>0.091077</td>\n",
+       "      <td>0.100094</td>\n",
+       "      <td>0.047595</td>\n",
+       "      <td>0.074142</td>\n",
+       "      <td>-0.045644</td>\n",
+       "      <td>-0.090852</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>TCP_CONVERSATION_EXCHANGE</th>\n",
+       "      <td>-0.038407</td>\n",
+       "      <td>-0.037459</td>\n",
+       "      <td>0.078451</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.555188</td>\n",
+       "      <td>0.331080</td>\n",
+       "      <td>0.457320</td>\n",
+       "      <td>0.997796</td>\n",
+       "      <td>0.990848</td>\n",
+       "      <td>0.865580</td>\n",
+       "      <td>0.458702</td>\n",
+       "      <td>0.997796</td>\n",
+       "      <td>0.349832</td>\n",
+       "      <td>-0.040202</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>DIST_REMOTE_TCP_PORT</th>\n",
+       "      <td>-0.039839</td>\n",
+       "      <td>-0.042619</td>\n",
+       "      <td>-0.000381</td>\n",
+       "      <td>0.555188</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.210188</td>\n",
+       "      <td>0.780238</td>\n",
+       "      <td>0.558612</td>\n",
+       "      <td>0.591188</td>\n",
+       "      <td>0.313359</td>\n",
+       "      <td>0.781212</td>\n",
+       "      <td>0.558612</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>-0.047103</td>\n",
+       "      <td>0.004774</td>\n",
+       "      <td>0.331080</td>\n",
+       "      <td>0.210188</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.023126</td>\n",
+       "      <td>0.361104</td>\n",
+       "      <td>0.304683</td>\n",
+       "      <td>0.171651</td>\n",
+       "      <td>0.025324</td>\n",
+       "      <td>0.361104</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>-0.023914</td>\n",
+       "      <td>0.051202</td>\n",
+       "      <td>0.457320</td>\n",
+       "      <td>0.780238</td>\n",
+       "      <td>0.023126</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.445822</td>\n",
+       "      <td>0.468999</td>\n",
+       "      <td>0.074464</td>\n",
+       "      <td>0.999992</td>\n",
+       "      <td>0.445822</td>\n",
+       "      <td>0.012221</td>\n",
+       "      <td>-0.011262</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>SOURCE_APP_PACKETS</th>\n",
+       "      <td>-0.042264</td>\n",
+       "      <td>-0.040096</td>\n",
+       "      <td>0.074142</td>\n",
+       "      <td>0.997796</td>\n",
+       "      <td>0.558612</td>\n",
+       "      <td>0.361104</td>\n",
+       "      <td>0.445822</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.989285</td>\n",
+       "      <td>0.857495</td>\n",
+       "      <td>0.447448</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.410843</td>\n",
+       "      <td>-0.034414</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>REMOTE_APP_PACKETS</th>\n",
+       "      <td>-0.033779</td>\n",
+       "      <td>-0.030597</td>\n",
+       "      <td>0.091077</td>\n",
+       "      <td>0.990848</td>\n",
+       "      <td>0.591188</td>\n",
+       "      <td>0.304683</td>\n",
+       "      <td>0.468999</td>\n",
+       "      <td>0.989285</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.880555</td>\n",
+       "      <td>0.470401</td>\n",
+       "      <td>0.989285</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>-0.014376</td>\n",
+       "      <td>0.100094</td>\n",
+       "      <td>0.865580</td>\n",
+       "      <td>0.313359</td>\n",
+       "      <td>0.171651</td>\n",
+       "      <td>0.074464</td>\n",
+       "      <td>0.857495</td>\n",
+       "      <td>0.880555</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.075328</td>\n",
+       "      <td>0.857495</td>\n",
+       "      <td>0.215285</td>\n",
+       "      <td>-0.043852</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>REMOTE_APP_BYTES</th>\n",
+       "      <td>-0.026686</td>\n",
+       "      <td>-0.024098</td>\n",
+       "      <td>0.047595</td>\n",
+       "      <td>0.458702</td>\n",
+       "      <td>0.781212</td>\n",
+       "      <td>0.025324</td>\n",
+       "      <td>0.999992</td>\n",
+       "      <td>0.447448</td>\n",
+       "      <td>0.470401</td>\n",
+       "      <td>0.075328</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.447448</td>\n",
+       "      <td>0.016215</td>\n",
+       "      <td>-0.011004</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>APP_PACKETS</th>\n",
+       "      <td>-0.042264</td>\n",
+       "      <td>-0.040096</td>\n",
+       "      <td>0.074142</td>\n",
+       "      <td>0.997796</td>\n",
+       "      <td>0.558612</td>\n",
+       "      <td>0.361104</td>\n",
+       "      <td>0.445822</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.989285</td>\n",
+       "      <td>0.857495</td>\n",
+       "      <td>0.447448</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.410843</td>\n",
+       "      <td>-0.034414</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>DNS_QUERY_TIMES</th>\n",
+       "      <td>-0.068582</td>\n",
+       "      <td>-0.050048</td>\n",
+       "      <td>-0.045644</td>\n",
+       "      <td>0.349832</td>\n",
+       "      <td>0.259942</td>\n",
+       "      <td>0.548189</td>\n",
+       "      <td>0.012221</td>\n",
+       "      <td>0.410843</td>\n",
+       "      <td>0.355716</td>\n",
+       "      <td>0.215285</td>\n",
+       "      <td>0.016215</td>\n",
+       "      <td>0.410843</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>0.280897</td>\n",
+       "      <td>-0.090852</td>\n",
+       "      <td>-0.040202</td>\n",
+       "      <td>-0.082925</td>\n",
+       "      <td>-0.078783</td>\n",
+       "      <td>-0.011262</td>\n",
+       "      <td>-0.034414</td>\n",
+       "      <td>-0.032897</td>\n",
+       "      <td>-0.043852</td>\n",
+       "      <td>-0.011004</td>\n",
+       "      <td>-0.034414</td>\n",
+       "      <td>0.068753</td>\n",
+       "      <td>1.000000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                           URL_LENGTH  NUMBER_SPECIAL_CHARACTERS  \\\n",
+       "URL_LENGTH                   1.000000                   0.917986   \n",
+       "NUMBER_SPECIAL_CHARACTERS    0.917986                   1.000000   \n",
+       "CONTENT_LENGTH               0.129745                   0.214225   \n",
+       "TCP_CONVERSATION_EXCHANGE   -0.038407                  -0.037459   \n",
+       "DIST_REMOTE_TCP_PORT        -0.039839                  -0.042619   \n",
+       "REMOTE_IPS                  -0.046367                  -0.047103   \n",
+       "APP_BYTES                   -0.026446                  -0.023914   \n",
+       "SOURCE_APP_PACKETS          -0.042264                  -0.040096   \n",
+       "REMOTE_APP_PACKETS          -0.033779                  -0.030597   \n",
+       "SOURCE_APP_BYTES            -0.014857                  -0.014376   \n",
+       "REMOTE_APP_BYTES            -0.026686                  -0.024098   \n",
+       "APP_PACKETS                 -0.042264                  -0.040096   \n",
+       "DNS_QUERY_TIMES             -0.068582                  -0.050048   \n",
+       "Type                         0.162104                   0.280897   \n",
+       "\n",
+       "                           CONTENT_LENGTH  TCP_CONVERSATION_EXCHANGE  \\\n",
+       "URL_LENGTH                       0.129745                  -0.038407   \n",
+       "NUMBER_SPECIAL_CHARACTERS        0.214225                  -0.037459   \n",
+       "CONTENT_LENGTH                   1.000000                   0.078451   \n",
+       "TCP_CONVERSATION_EXCHANGE        0.078451                   1.000000   \n",
+       "DIST_REMOTE_TCP_PORT            -0.000381                   0.555188   \n",
+       "REMOTE_IPS                       0.004774                   0.331080   \n",
+       "APP_BYTES                        0.051202                   0.457320   \n",
+       "SOURCE_APP_PACKETS               0.074142                   0.997796   \n",
+       "REMOTE_APP_PACKETS               0.091077                   0.990848   \n",
+       "SOURCE_APP_BYTES                 0.100094                   0.865580   \n",
+       "REMOTE_APP_BYTES                 0.047595                   0.458702   \n",
+       "APP_PACKETS                      0.074142                   0.997796   \n",
+       "DNS_QUERY_TIMES                 -0.045644                   0.349832   \n",
+       "Type                            -0.090852                  -0.040202   \n",
+       "\n",
+       "                           DIST_REMOTE_TCP_PORT  REMOTE_IPS  APP_BYTES  \\\n",
+       "URL_LENGTH                            -0.039839   -0.046367  -0.026446   \n",
+       "NUMBER_SPECIAL_CHARACTERS             -0.042619   -0.047103  -0.023914   \n",
+       "CONTENT_LENGTH                        -0.000381    0.004774   0.051202   \n",
+       "TCP_CONVERSATION_EXCHANGE              0.555188    0.331080   0.457320   \n",
+       "DIST_REMOTE_TCP_PORT                   1.000000    0.210188   0.780238   \n",
+       "REMOTE_IPS                             0.210188    1.000000   0.023126   \n",
+       "APP_BYTES                              0.780238    0.023126   1.000000   \n",
+       "SOURCE_APP_PACKETS                     0.558612    0.361104   0.445822   \n",
+       "REMOTE_APP_PACKETS                     0.591188    0.304683   0.468999   \n",
+       "SOURCE_APP_BYTES                       0.313359    0.171651   0.074464   \n",
+       "REMOTE_APP_BYTES                       0.781212    0.025324   0.999992   \n",
+       "APP_PACKETS                            0.558612    0.361104   0.445822   \n",
+       "DNS_QUERY_TIMES                        0.259942    0.548189   0.012221   \n",
+       "Type                                  -0.082925   -0.078783  -0.011262   \n",
+       "\n",
+       "                           SOURCE_APP_PACKETS  REMOTE_APP_PACKETS  \\\n",
+       "URL_LENGTH                          -0.042264           -0.033779   \n",
+       "NUMBER_SPECIAL_CHARACTERS           -0.040096           -0.030597   \n",
+       "CONTENT_LENGTH                       0.074142            0.091077   \n",
+       "TCP_CONVERSATION_EXCHANGE            0.997796            0.990848   \n",
+       "DIST_REMOTE_TCP_PORT                 0.558612            0.591188   \n",
+       "REMOTE_IPS                           0.361104            0.304683   \n",
+       "APP_BYTES                            0.445822            0.468999   \n",
+       "SOURCE_APP_PACKETS                   1.000000            0.989285   \n",
+       "REMOTE_APP_PACKETS                   0.989285            1.000000   \n",
+       "SOURCE_APP_BYTES                     0.857495            0.880555   \n",
+       "REMOTE_APP_BYTES                     0.447448            0.470401   \n",
+       "APP_PACKETS                          1.000000            0.989285   \n",
+       "DNS_QUERY_TIMES                      0.410843            0.355716   \n",
+       "Type                                -0.034414           -0.032897   \n",
+       "\n",
+       "                           SOURCE_APP_BYTES  REMOTE_APP_BYTES  APP_PACKETS  \\\n",
+       "URL_LENGTH                        -0.014857         -0.026686    -0.042264   \n",
+       "NUMBER_SPECIAL_CHARACTERS         -0.014376         -0.024098    -0.040096   \n",
+       "CONTENT_LENGTH                     0.100094          0.047595     0.074142   \n",
+       "TCP_CONVERSATION_EXCHANGE          0.865580          0.458702     0.997796   \n",
+       "DIST_REMOTE_TCP_PORT               0.313359          0.781212     0.558612   \n",
+       "REMOTE_IPS                         0.171651          0.025324     0.361104   \n",
+       "APP_BYTES                          0.074464          0.999992     0.445822   \n",
+       "SOURCE_APP_PACKETS                 0.857495          0.447448     1.000000   \n",
+       "REMOTE_APP_PACKETS                 0.880555          0.470401     0.989285   \n",
+       "SOURCE_APP_BYTES                   1.000000          0.075328     0.857495   \n",
+       "REMOTE_APP_BYTES                   0.075328          1.000000     0.447448   \n",
+       "APP_PACKETS                        0.857495          0.447448     1.000000   \n",
+       "DNS_QUERY_TIMES                    0.215285          0.016215     0.410843   \n",
+       "Type                              -0.043852         -0.011004    -0.034414   \n",
+       "\n",
+       "                           DNS_QUERY_TIMES      Type  \n",
+       "URL_LENGTH                       -0.068582  0.162104  \n",
+       "NUMBER_SPECIAL_CHARACTERS        -0.050048  0.280897  \n",
+       "CONTENT_LENGTH                   -0.045644 -0.090852  \n",
+       "TCP_CONVERSATION_EXCHANGE         0.349832 -0.040202  \n",
+       "DIST_REMOTE_TCP_PORT              0.259942 -0.082925  \n",
+       "REMOTE_IPS                        0.548189 -0.078783  \n",
+       "APP_BYTES                         0.012221 -0.011262  \n",
+       "SOURCE_APP_PACKETS                0.410843 -0.034414  \n",
+       "REMOTE_APP_PACKETS                0.355716 -0.032897  \n",
+       "SOURCE_APP_BYTES                  0.215285 -0.043852  \n",
+       "REMOTE_APP_BYTES                  0.016215 -0.011004  \n",
+       "APP_PACKETS                       0.410843 -0.034414  \n",
+       "DNS_QUERY_TIMES                   1.000000  0.068753  \n",
+       "Type                              0.068753  1.000000  "
+      ]
+     },
+     "execution_count": 255,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Your code here\n",
+    "websites.corr()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Your comment here"
+   "execution_count": 256,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\carol\\AppData\\Local\\Temp\\ipykernel_17936\\2539656341.py:5: FutureWarning: The default value of numeric_only in DataFrame.corr is deprecated. In a future version, it will default to False. Select only valid columns or specify the value of numeric_only to silence this warning.\n",
+      "  corr = np.abs(websites.corr())\n"
+     ]
+    },
+    {
+     "data": {
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\n",
+      "text/plain": [
+       "<Figure size 1400x1400 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Your code here\n",
+    "import matplotlib.pyplot as plt\n",
+    "import seaborn as sn\n",
+    "\n",
+    "corr = np.abs(websites.corr())\n",
+    "\n",
+    "mask = np.zeros_like(corr, dtype=bool)\n",
+    "mask[np.triu_indices_from(mask)] = True\n",
+    "\n",
+    "f, ax = plt.subplots(figsize=(14, 14))\n",
+    "cmap = sn.diverging_palette(220, 10, as_cmap=True)\n",
+    "sn.heatmap(corr, mask=mask,  vmax=1,square=True, linewidths=.5, cbar_kws={\"shrink\": .5},annot = corr)\n",
+    "\n",
+    "plt.show()"
    ]
   },
   {
@@ -133,29 +805,254 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 257,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your code here\n"
+    "# Your code here\n",
+    "websites = websites.drop([\"TCP_CONVERSATION_EXCHANGE\", \"NUMBER_SPECIAL_CHARACTERS\", \"APP_PACKETS\", \"SOURCE_APP_PACKETS\", \"APP_BYTES\"], axis = 1)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Your comment here"
+   "execution_count": 258,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\carol\\AppData\\Local\\Temp\\ipykernel_17936\\3766508873.py:3: FutureWarning: The default value of numeric_only in DataFrame.corr is deprecated. In a future version, it will default to False. Select only valid columns or specify the value of numeric_only to silence this warning.\n",
+      "  websites.corr()\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>URL_LENGTH</th>\n",
+       "      <th>CONTENT_LENGTH</th>\n",
+       "      <th>DIST_REMOTE_TCP_PORT</th>\n",
+       "      <th>REMOTE_IPS</th>\n",
+       "      <th>REMOTE_APP_PACKETS</th>\n",
+       "      <th>SOURCE_APP_BYTES</th>\n",
+       "      <th>REMOTE_APP_BYTES</th>\n",
+       "      <th>DNS_QUERY_TIMES</th>\n",
+       "      <th>Type</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>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>-0.033779</td>\n",
+       "      <td>-0.014857</td>\n",
+       "      <td>-0.026686</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>0.091077</td>\n",
+       "      <td>0.100094</td>\n",
+       "      <td>0.047595</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>0.591188</td>\n",
+       "      <td>0.313359</td>\n",
+       "      <td>0.781212</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>0.304683</td>\n",
+       "      <td>0.171651</td>\n",
+       "      <td>0.025324</td>\n",
+       "      <td>0.548189</td>\n",
+       "      <td>-0.078783</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>1.000000</td>\n",
+       "      <td>0.880555</td>\n",
+       "      <td>0.470401</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>0.880555</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.075328</td>\n",
+       "      <td>0.215285</td>\n",
+       "      <td>-0.043852</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>REMOTE_APP_BYTES</th>\n",
+       "      <td>-0.026686</td>\n",
+       "      <td>0.047595</td>\n",
+       "      <td>0.781212</td>\n",
+       "      <td>0.025324</td>\n",
+       "      <td>0.470401</td>\n",
+       "      <td>0.075328</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.016215</td>\n",
+       "      <td>-0.011004</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>0.355716</td>\n",
+       "      <td>0.215285</td>\n",
+       "      <td>0.016215</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>-0.032897</td>\n",
+       "      <td>-0.043852</td>\n",
+       "      <td>-0.011004</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",
+       "REMOTE_APP_PACKETS     -0.033779        0.091077              0.591188   \n",
+       "SOURCE_APP_BYTES       -0.014857        0.100094              0.313359   \n",
+       "REMOTE_APP_BYTES       -0.026686        0.047595              0.781212   \n",
+       "DNS_QUERY_TIMES        -0.068582       -0.045644              0.259942   \n",
+       "Type                    0.162104       -0.090852             -0.082925   \n",
+       "\n",
+       "                      REMOTE_IPS  REMOTE_APP_PACKETS  SOURCE_APP_BYTES  \\\n",
+       "URL_LENGTH             -0.046367           -0.033779         -0.014857   \n",
+       "CONTENT_LENGTH          0.004774            0.091077          0.100094   \n",
+       "DIST_REMOTE_TCP_PORT    0.210188            0.591188          0.313359   \n",
+       "REMOTE_IPS              1.000000            0.304683          0.171651   \n",
+       "REMOTE_APP_PACKETS      0.304683            1.000000          0.880555   \n",
+       "SOURCE_APP_BYTES        0.171651            0.880555          1.000000   \n",
+       "REMOTE_APP_BYTES        0.025324            0.470401          0.075328   \n",
+       "DNS_QUERY_TIMES         0.548189            0.355716          0.215285   \n",
+       "Type                   -0.078783           -0.032897         -0.043852   \n",
+       "\n",
+       "                      REMOTE_APP_BYTES  DNS_QUERY_TIMES      Type  \n",
+       "URL_LENGTH                   -0.026686        -0.068582  0.162104  \n",
+       "CONTENT_LENGTH                0.047595        -0.045644 -0.090852  \n",
+       "DIST_REMOTE_TCP_PORT          0.781212         0.259942 -0.082925  \n",
+       "REMOTE_IPS                    0.025324         0.548189 -0.078783  \n",
+       "REMOTE_APP_PACKETS            0.470401         0.355716 -0.032897  \n",
+       "SOURCE_APP_BYTES              0.075328         0.215285 -0.043852  \n",
+       "REMOTE_APP_BYTES              1.000000         0.016215 -0.011004  \n",
+       "DNS_QUERY_TIMES               0.016215         1.000000  0.068753  \n",
+       "Type                         -0.011004         0.068753  1.000000  "
+      ]
+     },
+     "execution_count": 258,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Your comment here\n",
+    "### --> I deleted every columns that had a correlation higher than 90%\n",
+    "websites.corr()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Print heatmap again\n"
+   "execution_count": 259,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\carol\\AppData\\Local\\Temp\\ipykernel_17936\\729443228.py:2: FutureWarning: The default value of numeric_only in DataFrame.corr is deprecated. In a future version, it will default to False. Select only valid columns or specify the value of numeric_only to silence this warning.\n",
+      "  corr = np.abs(websites.corr())\n"
+     ]
+    },
+    {
+     "data": {
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li3D/Fy9RSOnSpdbuCKpxbGxsVKNmRcWLH1f79x/+FyOJuuzs7JQjZxZt3bLLon3r5l3KF8ExyJsvp7Zutuy/ZfNOfZEzq8Ux6N6znfz87mne3GURbn/0dwO0af02bd+2J8I+0ZmdnZ1y5cqmPzbtsGjf9McOFSgQ/iWR+fPn0qY/3um/cbty584e4XsAEbOzs1P2LzJr+xbLf4Pbt+5RnnxfhLtO7rw5tP2dz41tm3cre84s5mNQ9quSOnTgmIaN6auj57Zr856Vat+5hflvz1ivPwdevPP30vMX/3hZPoCoLWZ/A4VVNWnSROfOndP+/fslSYGBgZo3b56aNm1q0a9WrVpq3ry50qdPryFDhihPnjz6/vvvJUmLFi2SjY2Npk+frmzZsilTpkyaNWuWrl69qm3btoW73YCAAD169Mji8W7CwFoSJUkkW9tYuu9336L9nt99JXFN8q9fN6lXUhX/uphixYql7t69NHfifNVpVUve3zb4ryFHaYmdHGVrayu/u/4W7X5378nF1SncdVxcneR39947/f1lZ2enxE6OkkKTKE2/aaiUqT1lMplUuHh+lSlfXC5uzoaMI6pK7JQ4dP/feXf/+0e4r1xcncMerzuW+3/tr+v13YgpWvLbbJ2/dVA7Dq/T3l0H9OPEmRbrZciUViev7NU53wMaNq6PWjfqpL/OXfp0A4wC/t0xcIrwGCT5/zF4W45cWZUxczotmrfC3Pb0yTMd2n9U7bu0lKu7i2xsbFSt1tf6Inc2ubq7/PeBRRFO/9//d+5YXhp957a/3NzC3w9ubi66c9ty/9+54yc7Ozs5OSc2tyVM6KCbt0/I/8E5LV0+Q926DgqTaMmcJYNu3j4hv/tnNX7iUDWo943Onf3rE40uanh9DO6+ewzu+sk1gveAq5uz7ty17H/39TFwCj0G+QvkUsNGtdSxfdjq19eq1/haOXJk0eCBY//jKKIuZ+cksrW11e07dy3a79y+K/cIzgXu7q66c9uy/+07d2VnZydn53//t1JMlSTCv4X85eoawXsgvM/iu5afA15eyfV15XKKFctG3rW/0cSxP6lVWx9926WVpNDPgYP7j6hDt9Zy+//nQPXaFZUzT/YIz38AogeSULCapEmT6uuvv9bMmaFfDNeuXasXL15YXGonSQULFgzz/HUl1KFDh/TXX3/JwcFBCRIkUIIECZQkSRK9ePFCFy+GPz/SiBEjlChRIovHiBEjwu1rLe9eJGsySf/lylkbGxs98L+vMd2/0/kTF7Rl9Vb9Mmm+qjaq9B8jjR7C7m/Te/f3u8tMJpNF+5DeY3Tl0lVt3LtCZ33/1MBRPbRs4RoFv/o8L4W0tvD253/Z//kL51HbTs3Vv9swVSpZV60adVKpcsXUvktLi/Uu/XVZX5eorepfemverKUa+8MQpc0Q+ZdjfQ4+9TF4W50G1XT29AUdO3zSor3jN71lMpl04NRmXfA9KJ+W9bVq+bqY+T4Jsz/ff84P0T/v/8ePn6hIwYoqUayqBg8aq+Ej+qhI0fwW6104f0lFClZU6RI1NGP6fP340xhlyJj2v44mSgrzb1r//j2QIEF8/ThtrDq276N7/vfDW13Jkrlr+Oi+atW8a5iKwJjIyHMQPsx/PQYyH4PQpzY2NvL3u6fuHQfqxLHTWr3id00a97MaNa1jXuXbVr1kMpl0+Mw2/X37iJq2bKhfl/2mV6+CP82gAHyWqFmFVTVv3lze3t4aP368Zs2apTp16ihevHj/uN7rPzaCg4OVO3duzZ8/P0wfF5fwf0Xp1auXOnfubNFmb2+vLdPCv1QnMj2891BBQa+UxCWxRXtip8S6fzf8P2Q/hP9tfwUFBSk4+M2H+pULV+Xk5iRbO1sFBYa9Vj8muO//QEFBQWGqnpycE4epdnrt7h3/cPonUWBgoB7ceyhJuuf/QK0bdVFs+9hKnDiRbt+6q+79v9W1qzeNGUgUdd//fuj+f6fawMk5SZjKnNfu3vGTyzu/zDq5WO7/Lr3a6tcla7V4XujcTufO/KV48eJq+Hf9NPm7aeY/nAMDg3Tl72uSpBNHTyt7zixq0rKB+rw1J0Z09++OgX+Ex+D+/4/Ba3HixlGl6uX13YiwdwW7evm66lRuqrjx4srBIb7u3PbT5Omjde3Kjf84qqjD///73/WdX/1dXJ3CVEe9dvv2Xbm9c7xcXJwUGBioe/4PzG0hISG6dOmKJOnE8TPKkCGtunT9Rrt2/mnuExgYaO5z5MgJ5cqdXd+08VHHbyOu3oluIjwGLk66G8F74M5tP7m5WvZ3fn0M7j1Qxkzp5JXSUwuW/GRe/voSpDv3zyhfri+VOUt6ubo6a+vON3PQ2draqlDhvGreqqHcnbJYfGZHV35+9xQUFCR3N8uJqF1cnXX7dvjvgVu37sjN3bK/q4uzAgMD5R9B0g8Ru2f+Wyjs58DduxG8B8L5LHZ2fv058EBS6LkqKNDyb88L5y/Kzd1FdnZ2CgwM1JXL11Szoo/F58DUGWN17er1TztIAJ8VKqFgVRUqVFD8+PE1depU/f7772EuxZOkffv2hXmeMWNGSVKuXLl04cIFubq6Km3atBaPRIkShbtNe3t7JUyY0OJhb2//6Qf3LwQFBun88fPKUyy3RXueYrl18uC/nyzxxMFTSpYymTl5J0meqZPL75ZfjE1ASaFJiJPHzqhwCcvqgMIlCujw/vDnBjpy4LgKlyhg0VakZAGdOHomzMSbLwNe6vatu7K1tVX5iqX1x+/bP+0AorjX+7/Iu/uzRAEdOhD+/j988HiY/kVLFtSJo6fN+z9O3DgKfucX2levXslkMlm8B95lMpkU297u3wwlygoMDNKJY2dUtIRlxWnREgV06MDRcNc5fPCYioY5BoUsjsFrFauWU+zYsfXr0rURxvD82XPdue2nhIkcVKxUIW38feu/G0wUFBgYqKNHTqpUqSIW7SVLFtGff4Y/N9P+/UdUsqRl/1Kli+rI4RPhTv77mslkUuzYsd8bj8lkkr39+/tEN4GBgTp25JRKlCxs0V6iVGHtj+AYHNh/RCVKWfYvWaqIjh45qaCgIF04f1GF81VQ8UKVzY/f123Wzh37VLxQZd247qsd2/aG6XP40HEtXbxaxQtVjhEJKCl0/x8+fMLizo2SVKZ0Ue3bdzDcdf7887DKlH6nf9liOnTo+HvfAwhfYGCgjh89rWIlC1m0FytRSAf3Hw13nUMHjqlYCcv+xUsV0vEjp8zH4OCfR5QydQqLz93UaVLqlu8dBQYGWqz7+nMgUaKEKl66sDasizmfA0BMRBIKVhUrViz5+PioV69eSps2bZhL7yRp6dKlmjlzps6fP68BAwZo//79ateunSSpQYMGcnZ2VpUqVbRz5079/fff2r59uzp06KDr16PmryhLpi1TxXoVVKFOeXmlTaF2A7+RazJXrfpljSSpZc9m6j2xh8U6abOkUdosaRQ3flw5JkmktFnSyCudl3n5qrmrlShxQn07uK2Sp06uAqXzq2H7+vp1zqpIHdvnaObU+ardsJpq1q+iNOlSqc/QLvJI5q4Fs5dLkrr2baexPww2918we5mSJU+q3kM6K026VKpZv4pqNaiq6T/MNffJkSuryn1dSp5eyZSnQE7NWjJZJhuTfv5+trlPvPhxlSlremXKml6SlNwrmTJlTa+kydwjZ+CfielTflGdhtVVq35VpUmfSn2HdpVHsqRaMGupJKlbv281bsqbu7bNn7VUyZJ7qM+QrkqTPpVq1a+q2g2qadoPc8x9Nm/YrgZNaqlitfJKniKZipQooM692uqP9dvNX+y69m2vvAVyKpmnhzJkSquufdqpQOE8WrVsXeTugM/A9ClzVadhddWuX1Vp06dSv6Hd5JEsqeb//xh07/etvpvy5m5dr49BvyFdlTZ9KtWuX1V1GlTTz28dg9fqNKiujeu26MH9h2GWFStZSMVLFZbn/4/RolUzdOmvK1q6IGadlyZ/P0ONfGqrYaNaSp8hjUaM6qvknh6aOT20wnfAoG76adqbOYNmTp8vzxTJNHxkH6XPkEYNG9VSo8a1NGnidHOfzl2/UclSRZQypafSpU+ttu2bqV79alq8aKW5T/+BXVWwUF6lSJFMmbNkUL8BXVS0aH4tWbw60sb+uZgyeaa8G9dSA++aSp8hjYaN6K1kyZNq1oyFkqR+A7toyk+jzf1nzVio5J4eGjqil9JnSKMG3jXVsFFNTZ4Yeve1gICXOnPmgsXj4cPHevLkqc6cuaDAwEDz/7/9ePbsue7fe6AzZy5YZT9Yy8SJP6tpk3pq3LiOMmZMqzFjBsjTM5l+nvaLJGnokJ6aOWOCuf/P035RihTJNXp0f2XMmFaNG9dRE5+6Gj/+TeWZnZ2dcmTPrBzZMyt2bDt5eCRVjuyZlSZNSnOf+PHjmftIUsqUnsqRPbM8PT0iZdyfk2lT5qiedw3VaVBNadOn1sBhPZQseVL9MmuxJKln/46aOHW4uf8vMxcruWdSDRjaXWnTp1adBtVUt2EN/Th5trnP3JmLlTixowaP7KXUabxUulwxte/cQnP+/76SpOKlCqtE6SLyTJFMRUsU1NI1s3TxwmUtttJdagFEDi7Hg9U1a9ZMw4cPD7cKSpIGDRqkRYsWqU2bNnJ3d9f8+fOVOXPoHwzx4sXTjh071KNHD1WvXl2PHz9WsmTJVLp0aSVMmDAyh/HJbFm9TQkTJ1TjTt5yck2iv89dVg/vXrp9444kycnNSW4elmXoMzf+bP7/jDkyqGz1MvK9dkt1CoROPH7n5l11qd9D7QZ+o1mbpsnvlp+WzVihBT8siryBfaZ+W7lRjokTqX3XFnJxc9aFsxfVrN63unndV1LoBLRJk79JDF2/elPN6rVXn6Fd1LBpbd25dVeDe4/WhrVbzH3s48RW595tlMIrmZ4+fabtf+xWlzZ99fjRE3OfbF9k1oJV08zP+w7tIklavnC1urcfaPCoPx+/rdygxEkS6dt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\n",
+      "text/plain": [
+       "<Figure size 1400x1400 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Print heatmap again\n",
+    "corr = np.abs(websites.corr())\n",
+    "\n",
+    "mask = np.zeros_like(corr, dtype=bool)\n",
+    "mask[np.triu_indices_from(mask)] = True\n",
+    "\n",
+    "f, ax = plt.subplots(figsize=(14, 14))\n",
+    "cmap = sn.diverging_palette(220, 10, as_cmap=True)\n",
+    "sn.heatmap(corr, mask=mask,  vmax=1,square=True, linewidths=.5, cbar_kws={\"shrink\": .5},annot = corr)\n",
+    "\n",
+    "plt.show()"
    ]
   },
   {
@@ -169,11 +1066,39 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Your code here\n"
+   "execution_count": 260,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "URL                       0\n",
+       "URL_LENGTH                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",
+       "DIST_REMOTE_TCP_PORT      0\n",
+       "REMOTE_IPS                0\n",
+       "REMOTE_APP_PACKETS        0\n",
+       "SOURCE_APP_BYTES          0\n",
+       "REMOTE_APP_BYTES          0\n",
+       "DNS_QUERY_TIMES           1\n",
+       "Type                      0\n",
+       "dtype: int64"
+      ]
+     },
+     "execution_count": 260,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Your code here\n",
+    "websites.isnull().sum()"
    ]
   },
   {
@@ -187,16 +1112,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 261,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your code here\n"
+    "# Your code here\n",
+    "websites = websites.dropna()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 262,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -214,11 +1140,39 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Examine missing values in each column\n"
+   "execution_count": 263,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "URL                     0\n",
+       "URL_LENGTH              0\n",
+       "CHARSET                 0\n",
+       "SERVER                  0\n",
+       "CONTENT_LENGTH          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",
+       "REMOTE_APP_PACKETS      0\n",
+       "SOURCE_APP_BYTES        0\n",
+       "REMOTE_APP_BYTES        0\n",
+       "DNS_QUERY_TIMES         0\n",
+       "Type                    0\n",
+       "dtype: int64"
+      ]
+     },
+     "execution_count": 263,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Examine missing values in each column\n",
+    "websites.isnull().sum()"
    ]
   },
   {
@@ -256,11 +1210,67 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 264,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array(['None', 'US', 'GB', 'UK', 'RU', 'AU', 'CA', 'PA', 'se', 'IN',\n",
+       "       \"[u'GB'; u'UK']\", 'UG', 'JP', 'SI', 'IL', 'AT', 'CN', 'BE', 'NO',\n",
+       "       'TR', 'KY', 'BR', 'SC', 'NL', 'FR', 'CZ', 'KR', 'UA', 'CH', 'HK',\n",
+       "       'United Kingdom', 'DE', 'IT', 'BS', 'SE', 'Cyprus', 'us', 'BY',\n",
+       "       'AE', 'IE', 'PH', 'UY'], dtype=object)"
+      ]
+     },
+     "execution_count": 264,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Your code here\n",
+    "websites[\"WHOIS_COUNTRY\"].unique()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 265,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your code here\n"
+    "columns = {\n",
+    "    \"Cyprus\": \"CY\",\n",
+    "    \"us\": \"US\",\n",
+    "    \"se\": \"SE\",\n",
+    "    \"United Kingdom\": \"GB\",\n",
+    "    \"[u'GB'; u'UK']\": \"GB\"\n",
+    "}\n",
+    "\n",
+    "websites[\"WHOIS_COUNTRY\"].replace(columns, inplace = True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 266,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array(['None', 'US', 'GB', 'UK', 'RU', 'AU', 'CA', 'PA', 'SE', 'IN', 'UG',\n",
+       "       'JP', 'SI', 'IL', 'AT', 'CN', 'BE', 'NO', 'TR', 'KY', 'BR', 'SC',\n",
+       "       'NL', 'FR', 'CZ', 'KR', 'UA', 'CH', 'HK', 'DE', 'IT', 'BS', 'CY',\n",
+       "       'BY', 'AE', 'IE', 'PH', 'UY'], dtype=object)"
+      ]
+     },
+     "execution_count": 266,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "websites[\"WHOIS_COUNTRY\"].unique()"
    ]
   },
   {
@@ -278,11 +1288,25 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 267,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
-    "# Your code here\n"
+    "# Your code here\n",
+    "count = pd.value_counts(websites[\"WHOIS_COUNTRY\"])\n",
+    "count.plot(kind = \"bar\", color = \"orange\")\n",
+    "plt.show()"
    ]
   },
   {
@@ -294,13 +1318,37 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 268,
    "metadata": {
     "scrolled": true
    },
    "outputs": [],
    "source": [
-    "# Your code here\n"
+    "# Your code here\n",
+    "top_countries = [\"US\", \"None\", \"CA\", \"ES\", \"AU\", \"GB\", \"PA\", \"IP\", \"IN\", \"UK\"]\n",
+    "\n",
+    "websites[\"WHOIS_COUNTRY\"] = websites[\"WHOIS_COUNTRY\"].apply(lambda x: x if x in top_countries else \"OTHER\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 269,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array(['None', 'US', 'GB', 'UK', 'OTHER', 'AU', 'CA', 'PA', 'IN'],\n",
+       "      dtype=object)"
+      ]
+     },
+     "execution_count": 269,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "websites[\"WHOIS_COUNTRY\"].unique()"
    ]
   },
   {
@@ -316,11 +1364,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 270,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your code here\n"
+    "# Your code here\n",
+    "websites.drop([\"WHOIS_STATEPRO\", \"WHOIS_REGDATE\", \"WHOIS_UPDATED_DATE\"], axis = 1, inplace = True)"
    ]
   },
   {
@@ -334,11 +1383,36 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Your code here\n"
+   "execution_count": 271,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "URL                      object\n",
+       "URL_LENGTH                int64\n",
+       "CHARSET                  object\n",
+       "SERVER                   object\n",
+       "CONTENT_LENGTH          float64\n",
+       "WHOIS_COUNTRY            object\n",
+       "DIST_REMOTE_TCP_PORT      int64\n",
+       "REMOTE_IPS                int64\n",
+       "REMOTE_APP_PACKETS        int64\n",
+       "SOURCE_APP_BYTES          int64\n",
+       "REMOTE_APP_BYTES          int64\n",
+       "DNS_QUERY_TIMES         float64\n",
+       "Type                      int64\n",
+       "dtype: object"
+      ]
+     },
+     "execution_count": 271,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Your code here\n",
+    "websites.dtypes"
    ]
   },
   {
@@ -350,11 +1424,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 272,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your code here\n"
+    "# Your code here\n",
+    "# websites[\"URL\"].value_counts().sum() --> 1781\n",
+    "\n",
+    "websites.drop(\"URL\", axis = 1, inplace = True)"
    ]
   },
   {
@@ -366,11 +1443,24 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 273,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array(['iso-8859-1', 'UTF-8', 'us-ascii', 'ISO-8859-1', 'utf-8', 'None',\n",
+       "       'windows-1251', 'ISO-8859'], dtype=object)"
+      ]
+     },
+     "execution_count": 273,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# Your code here"
+    "# Your code here\n",
+    "websites[\"CHARSET\"].unique()"
    ]
   },
   {
@@ -384,11 +1474,103 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Your code here\n"
+   "execution_count": 274,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array(['nginx', 'Apache/2.4.10', 'Microsoft-HTTPAPI/2.0', 'None',\n",
+       "       'Apache/2', 'Apache/2.2.15 (Red Hat)',\n",
+       "       'Apache/2.4.23 (Unix) OpenSSL/1.0.1e-fips mod_bwlimited/1.4',\n",
+       "       'Apache/2.2.22', 'Apache/2.4.7 (Ubuntu)', 'Apache',\n",
+       "       'Apache/2.4.12 (Unix) OpenSSL/1.0.1e-fips mod_bwlimited/1.4',\n",
+       "       'Oracle-iPlanet-Web-Server/7.0', 'nginx/1.6.2', 'Heptu web server',\n",
+       "       'Microsoft-IIS/7.5', 'nginx/1.12.0',\n",
+       "       'Apache/2.4.25 (cPanel) OpenSSL/1.0.1e-fips mod_bwlimited/1.4',\n",
+       "       'tsa_c', 'Apache/2.2.22 (Debian)', 'Apache/2.4.25',\n",
+       "       'Apache/2.4.25 (Amazon) PHP/7.0.14', 'GSE',\n",
+       "       'Apache/2.4.23 (Unix) OpenSSL/0.9.8e-fips-rhel5 mod_bwlimited/1.4',\n",
+       "       'Apache/2.4.25 (Amazon) OpenSSL/1.0.1k-fips',\n",
+       "       'Apache/2.2.22 (Ubuntu)',\n",
+       "       'Apache/2.4.18 (Unix) OpenSSL/0.9.8e-fips-rhel5 mod_bwlimited/1.4',\n",
+       "       'Apache/2.4.6 (CentOS) PHP/5.6.8', 'AmazonS3', 'ATS',\n",
+       "       'Apache/2.2.27 (CentOS)', 'CherryPy/3.6.0',\n",
+       "       'Apache/2.2.15 (CentOS)', 'KHL',\n",
+       "       'Apache/2.4.6 (CentOS) OpenSSL/1.0.1e-fips mod_fcgid/2.3.9 PHP/5.4.16 mod_jk/1.2.40',\n",
+       "       'Apache/2.2.3 (CentOS)', 'Apache/2.4', 'Apache/2.2.31 (Amazon)',\n",
+       "       'Apache/2.4.10 (Debian)', 'Apache/2.4.12 (Ubuntu)',\n",
+       "       'Apache/2.2.29 (Unix) mod_ssl/2.2.29 OpenSSL/1.0.1e-fips mod_bwlimited/1.4',\n",
+       "       'mw2232.codfw.wmnet', 'Sucuri/Cloudproxy', 'Apache/2.4.23 (Unix)',\n",
+       "       'cloudflare-nginx', 'Apache/2.0.52 (Red Hat)',\n",
+       "       'Apache/1.3.31 (Unix) PHP/4.3.9 mod_perl/1.29 rus/PL30.20',\n",
+       "       'Apache/2.2.13 (Unix) mod_ssl/2.2.13 OpenSSL/0.9.8e-fips-rhel5 mod_auth_passthrough/2.1 mod_bwlimited/1.4 PHP/5.2.10',\n",
+       "       'ATS/5.3.0', 'Apache/2.2.3 (Red Hat)', 'nginx/1.4.3',\n",
+       "       'Apache/2.2.29 (Unix) mod_ssl/2.2.29 OpenSSL/1.0.1e-fips mod_bwlimited/1.4 PHP/5.4.35',\n",
+       "       'Apache/2.2.14 (FreeBSD) mod_ssl/2.2.14 OpenSSL/0.9.8y DAV/2 PHP/5.2.12 with Suhosin-Patch',\n",
+       "       'nginx/1.8.0',\n",
+       "       'Apache/2.2.14 (Unix) mod_ssl/2.2.14 OpenSSL/0.9.8e-fips-rhel5',\n",
+       "       'Microsoft-IIS/8.0', 'Apache/2.4.18 (Ubuntu)',\n",
+       "       'Apache/2.4.6 (CentOS) OpenSSL/1.0.1e-fips PHP/5.4.16 mod_apreq2-20090110/2.8.0 mod_perl/2.0.10 Perl/v5.24.1',\n",
+       "       'Apache/2.2.20 (Unix)', 'nginx/1.11.10', 'Yippee-Ki-Yay',\n",
+       "       'mw2165.codfw.wmnet', 'Apache/2.2.23 (Amazon)', 'LiteSpeed',\n",
+       "       'Proxy Pandeiro UOL', 'openresty/1.11.2.2', 'Apache-Coyote/1.1',\n",
+       "       'mw2225.codfw.wmnet', 'nginx/1.1.19', 'Varnish',\n",
+       "       'Microsoft-IIS/8.5', 'Apache/2.4.6 (CentOS)', 'barista/5.1.3',\n",
+       "       'nginx/1.11.2', 'Apache/2.4.25 (Debian)', 'ECD (fll/0790)',\n",
+       "       'nginx/1.10.3',\n",
+       "       'Apache/2.4.25 (FreeBSD) OpenSSL/1.0.1s-freebsd PHP/5.6.30',\n",
+       "       'mw2239.codfw.wmnet', 'mw2255.codfw.wmnet',\n",
+       "       'Apache/2.2.31 (Unix) mod_ssl/2.2.31 OpenSSL/1.0.1e-fips mod_bwlimited/1.4 mod_fcgid/2.3.9',\n",
+       "       'nginx/1.13.0',\n",
+       "       'Apache/2.2.31 (Unix) mod_ssl/2.2.31 OpenSSL/0.9.8e-fips-rhel5 mod_bwlimited/1.4',\n",
+       "       'Apache/2.4.6 (CentOS) OpenSSL/1.0.1e-fips PHP/5.4.16',\n",
+       "       'nginx/1.11.3', 'lighttpd', 'mw2230.codfw.wmnet',\n",
+       "       'Apache/2.4.6 (CentOS) OpenSSL/1.0.1e-fips', 'AkamaiGHost',\n",
+       "       'PWS/8.2.0.7', 'nginx/1.2.1',\n",
+       "       'Apache/2.2.16 (Unix) mod_ssl/2.2.16 OpenSSL/0.9.8e-fips-rhel5 mod_auth_passthrough/2.1 mod_bwlimited/1.4',\n",
+       "       'Play', 'Apache/2.2.11 (Unix) PHP/5.2.6', 'Scratch Web Server',\n",
+       "       'nginx/1.4.6 (Ubuntu)', 'marrakesh 1.12.2', 'nginx/0.8.35',\n",
+       "       'squid/3.3.8', 'nginx/1.8.1', 'Nginx (OpenBSD)',\n",
+       "       'Zope/(2.13.16; python 2.6.8; linux2) ZServer/1.1',\n",
+       "       'Apache/2.2.26 (Unix) mod_ssl/2.2.26 OpenSSL/0.9.8e-fips-rhel5 mod_bwlimited/1.4 PHP/5.4.26',\n",
+       "       'Apache/2.2.21 (Unix) mod_ssl/2.2.21 OpenSSL/0.9.8e-fips-rhel5 PHP/5.3.10',\n",
+       "       'Apache/2.2.27 (Unix) OpenAM Web Agent/4.0.1-1 mod_ssl/2.2.27 OpenSSL/1.0.1p PHP/5.3.28',\n",
+       "       'Apache/2.2.32',\n",
+       "       'Apache/2.4.6 (Unix) mod_jk/1.2.37 PHP/5.5.1 OpenSSL/1.0.1g mod_fcgid/2.3.9',\n",
+       "       'mw2106.codfw.wmnet', 'Microsoft-IIS/7.0',\n",
+       "       'Aeria Games & Entertainment',\n",
+       "       'Apache/2.4.10 (Debian) PHP/5.6.30-0+deb8u1 mod_perl/2.0.9dev Perl/v5.20.2',\n",
+       "       'mw2173.codfw.wmnet',\n",
+       "       'Apache/2.4.6 (Red Hat Enterprise Linux) OpenSSL/1.0.1e-fips mod_fcgid/2.3.9 Communique/4.2.0',\n",
+       "       'Apache/2.2.15 (CentOS) DAV/2 mod_ssl/2.2.15 OpenSSL/1.0.1e-fips PHP/5.3.3',\n",
+       "       'Apache/2.4.6 (CentOS) OpenSSL/1.0.1e-fips PHP/7.0.14', 'Server',\n",
+       "       'Apache/2.4.6 (Unix) mod_jk/1.2.37', 'Cowboy',\n",
+       "       'Apache/2.2.14 (Unix) mod_ssl/2.2.14 OpenSSL/0.9.8a',\n",
+       "       'Apache/2.4.10 (Ubuntu)', 'mw2257.codfw.wmnet', 'DMS/1.0.42',\n",
+       "       'Application-Server', 'mw2177.codfw.wmnet', 'lighttpd/1.4.28',\n",
+       "       'mw2197.codfw.wmnet',\n",
+       "       'Apache/2.2.31 (FreeBSD) PHP/5.4.15 mod_ssl/2.2.31 OpenSSL/1.0.2d DAV/2',\n",
+       "       'Apache/2.2.26 (Unix) mod_ssl/2.2.26 OpenSSL/1.0.1e-fips DAV/2 mod_bwlimited/1.4',\n",
+       "       '294', 'Microsoft-IIS/6.0', 'www.lexisnexis.com  9999',\n",
+       "       'nginx/0.8.38', 'mw2238.codfw.wmnet', 'XXXXXXXXXXXXXXXXXXXXXX',\n",
+       "       'Pizza/pepperoni', 'MI', 'Roxen/5.4.98-r2', 'nginx/1.10.1',\n",
+       "       'mw2180.codfw.wmnet', 'nginx/1.9.13', 'nginx/1.7.12',\n",
+       "       'Apache/2.0.63 (Unix) mod_ssl/2.0.63 OpenSSL/0.9.8e-fips-rhel5 mod_auth_passthrough/2.1 mod_bwlimited/1.4 PHP/5.3.6',\n",
+       "       'Boston.com Frontend', 'My Arse',\n",
+       "       'Apache/2.4.17 (Unix) OpenSSL/1.0.1e-fips PHP/5.6.19',\n",
+       "       'Microsoft-IIS/7.5; litigation_essentials.lexisnexis.com  9999',\n",
+       "       'Apache/2.2.16 (Debian)'], dtype=object)"
+      ]
+     },
+     "execution_count": 274,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Your code here\n",
+    "websites[\"SERVER\"].unique()"
    ]
   },
   {
@@ -400,11 +1582,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 275,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your comment here\n"
+    "# Your comment here\n",
+    "# I would delete it. "
    ]
   },
   {
@@ -418,22 +1601,49 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 277,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your code here\n"
+    "# Your code here\n",
+    "def relabel_server(row):\n",
+    "    if \"microsoft\" in row[\"SERVER\"].lower():\n",
+    "        return \"Microsoft\"\n",
+    "    elif \"apache\" in row[\"SERVER\"].lower():\n",
+    "        return \"Apache\"\n",
+    "    elif \"nginx\" in row[\"SERVER\"].lower():\n",
+    "        return \"nginx\"\n",
+    "    else:\n",
+    "        return \"Other\"\n",
+    "    \n",
+    "websites[\"SERVER\"] = websites.apply(relabel_server, axis=1)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 278,
    "metadata": {
     "scrolled": false
    },
-   "outputs": [],
-   "source": [
-    "# Count `SERVER` value counts here\n"
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Apache       401\n",
+       "Other        220\n",
+       "Microsoft    180\n",
+       "nginx        166\n",
+       "Name: SERVER, dtype: int64"
+      ]
+     },
+     "execution_count": 278,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Count `SERVER` value counts here\n",
+    "websites[\"SERVER\"].value_counts()"
    ]
   },
   {
@@ -445,11 +1655,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 279,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your code here\n"
+    "# Your code here\n",
+    "website_dummy = pd.get_dummies(websites, columns=[\"SERVER\", \"WHOIS_COUNTRY\", \"CHARSET\"])"
    ]
   },
   {
@@ -461,11 +1672,276 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Your code here\n"
+   "execution_count": 281,
+   "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>CONTENT_LENGTH</th>\n",
+       "      <th>DIST_REMOTE_TCP_PORT</th>\n",
+       "      <th>REMOTE_IPS</th>\n",
+       "      <th>REMOTE_APP_PACKETS</th>\n",
+       "      <th>SOURCE_APP_BYTES</th>\n",
+       "      <th>REMOTE_APP_BYTES</th>\n",
+       "      <th>DNS_QUERY_TIMES</th>\n",
+       "      <th>Type</th>\n",
+       "      <th>SERVER_Apache</th>\n",
+       "      <th>...</th>\n",
+       "      <th>WHOIS_COUNTRY_UK</th>\n",
+       "      <th>WHOIS_COUNTRY_US</th>\n",
+       "      <th>CHARSET_ISO-8859</th>\n",
+       "      <th>CHARSET_ISO-8859-1</th>\n",
+       "      <th>CHARSET_None</th>\n",
+       "      <th>CHARSET_UTF-8</th>\n",
+       "      <th>CHARSET_iso-8859-1</th>\n",
+       "      <th>CHARSET_us-ascii</th>\n",
+       "      <th>CHARSET_utf-8</th>\n",
+       "      <th>CHARSET_windows-1251</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>16</td>\n",
+       "      <td>263.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>10</td>\n",
+       "      <td>1153</td>\n",
+       "      <td>832</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</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>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>16</td>\n",
+       "      <td>15087.0</td>\n",
+       "      <td>7</td>\n",
+       "      <td>4</td>\n",
+       "      <td>19</td>\n",
+       "      <td>1265</td>\n",
+       "      <td>1230</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</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>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>16</td>\n",
+       "      <td>324.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</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>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>17</td>\n",
+       "      <td>162.0</td>\n",
+       "      <td>22</td>\n",
+       "      <td>3</td>\n",
+       "      <td>37</td>\n",
+       "      <td>18784</td>\n",
+       "      <td>4380</td>\n",
+       "      <td>8.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>17</td>\n",
+       "      <td>124140.0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>5</td>\n",
+       "      <td>62</td>\n",
+       "      <td>129889</td>\n",
+       "      <td>4586</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>5 rows × 30 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   URL_LENGTH  CONTENT_LENGTH  DIST_REMOTE_TCP_PORT  REMOTE_IPS  \\\n",
+       "0          16           263.0                     0           2   \n",
+       "1          16         15087.0                     7           4   \n",
+       "2          16           324.0                     0           0   \n",
+       "3          17           162.0                    22           3   \n",
+       "4          17        124140.0                     2           5   \n",
+       "\n",
+       "   REMOTE_APP_PACKETS  SOURCE_APP_BYTES  REMOTE_APP_BYTES  DNS_QUERY_TIMES  \\\n",
+       "0                  10              1153               832              2.0   \n",
+       "1                  19              1265              1230              0.0   \n",
+       "2                   0                 0                 0              0.0   \n",
+       "3                  37             18784              4380              8.0   \n",
+       "4                  62            129889              4586              4.0   \n",
+       "\n",
+       "   Type  SERVER_Apache  ...  WHOIS_COUNTRY_UK  WHOIS_COUNTRY_US  \\\n",
+       "0     1              0  ...                 0                 0   \n",
+       "1     0              1  ...                 0                 0   \n",
+       "2     0              0  ...                 0                 0   \n",
+       "3     0              0  ...                 0                 1   \n",
+       "4     0              0  ...                 0                 1   \n",
+       "\n",
+       "   CHARSET_ISO-8859  CHARSET_ISO-8859-1  CHARSET_None  CHARSET_UTF-8  \\\n",
+       "0                 0                   0             0              0   \n",
+       "1                 0                   0             0              1   \n",
+       "2                 0                   0             0              0   \n",
+       "3                 0                   1             0              0   \n",
+       "4                 0                   0             0              1   \n",
+       "\n",
+       "   CHARSET_iso-8859-1  CHARSET_us-ascii  CHARSET_utf-8  CHARSET_windows-1251  \n",
+       "0                   1                 0              0                     0  \n",
+       "1                   0                 0              0                     0  \n",
+       "2                   0                 1              0                     0  \n",
+       "3                   0                 0              0                     0  \n",
+       "4                   0                 0              0                     0  \n",
+       "\n",
+       "[5 rows x 30 columns]"
+      ]
+     },
+     "execution_count": 281,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Your code here\n",
+    "website_dummy.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 282,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "URL_LENGTH                int64\n",
+       "CONTENT_LENGTH          float64\n",
+       "DIST_REMOTE_TCP_PORT      int64\n",
+       "REMOTE_IPS                int64\n",
+       "REMOTE_APP_PACKETS        int64\n",
+       "SOURCE_APP_BYTES          int64\n",
+       "REMOTE_APP_BYTES          int64\n",
+       "DNS_QUERY_TIMES         float64\n",
+       "Type                      int64\n",
+       "SERVER_Apache             uint8\n",
+       "SERVER_Microsoft          uint8\n",
+       "SERVER_Other              uint8\n",
+       "SERVER_nginx              uint8\n",
+       "WHOIS_COUNTRY_AU          uint8\n",
+       "WHOIS_COUNTRY_CA          uint8\n",
+       "WHOIS_COUNTRY_GB          uint8\n",
+       "WHOIS_COUNTRY_IN          uint8\n",
+       "WHOIS_COUNTRY_None        uint8\n",
+       "WHOIS_COUNTRY_OTHER       uint8\n",
+       "WHOIS_COUNTRY_PA          uint8\n",
+       "WHOIS_COUNTRY_UK          uint8\n",
+       "WHOIS_COUNTRY_US          uint8\n",
+       "CHARSET_ISO-8859          uint8\n",
+       "CHARSET_ISO-8859-1        uint8\n",
+       "CHARSET_None              uint8\n",
+       "CHARSET_UTF-8             uint8\n",
+       "CHARSET_iso-8859-1        uint8\n",
+       "CHARSET_us-ascii          uint8\n",
+       "CHARSET_utf-8             uint8\n",
+       "CHARSET_windows-1251      uint8\n",
+       "dtype: object"
+      ]
+     },
+     "execution_count": 282,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "website_dummy.dtypes"
    ]
   },
   {
@@ -479,13 +1955,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 284,
    "metadata": {},
    "outputs": [],
    "source": [
     "from sklearn.model_selection import train_test_split\n",
     "\n",
-    "# Your code here:\n"
+    "# Your code here:\n",
+    "features = website_dummy.drop(\"Type\", axis = 1)\n",
+    "target = website_dummy[\"Type\"]\n",
+    "\n",
+    "X_train, X_test, y_train, y_test = train_test_split(features, target, test_size = 0.20)"
    ]
   },
   {
@@ -499,12 +1979,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 287,
    "metadata": {},
    "outputs": [],
    "source": [
     "# Your code here:\n",
-    "\n"
+    "from sklearn.linear_model import LogisticRegression\n",
+    "\n",
+    "model = LogisticRegression()"
    ]
   },
   {
@@ -516,12 +1998,38 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 295,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\carol\\anaconda3\\lib\\site-packages\\sklearn\\linear_model\\_logistic.py:458: ConvergenceWarning: lbfgs failed to converge (status=1):\n",
+      "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
+      "\n",
+      "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
+      "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
+      "Please also refer to the documentation for alternative solver options:\n",
+      "    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n",
+      "  n_iter_i = _check_optimize_result(\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "0.9175257731958762"
+      ]
+     },
+     "execution_count": 295,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "# Your code here:\n",
-    "\n"
+    "model.fit(X_train, y_train)\n",
+    "model.score(X_test, y_test)"
    ]
   },
   {
@@ -533,12 +2041,29 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 298,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "confusion matrix :\n",
+      " [[169   5]\n",
+      " [ 11   9]]\n",
+      "accuracy score : 0.9175257731958762\n"
+     ]
+    }
+   ],
    "source": [
     "# Your code here:\n",
-    "\n"
+    "\n",
+    "from sklearn.metrics import confusion_matrix, accuracy_score\n",
+    "\n",
+    "y_pred = model.predict(X_test)\n",
+    "\n",
+    "print(f\"confusion matrix :\\n {confusion_matrix(y_test, y_pred)}\")\n",
+    "print(f\"accuracy score : {accuracy_score(y_test, y_pred)}\")"
    ]
   },
   {
@@ -550,12 +2075,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your conclusions here:\n",
-    "\n"
+    "# Your conclusions here: the model is doing pretty good! :)"
    ]
   },
   {
@@ -569,12 +2093,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": 300,
    "metadata": {},
    "outputs": [],
    "source": [
     "# Your code here:\n",
-    "\n"
+    "from sklearn.neighbors import KNeighborsClassifier\n",
+    "\n",
+    "knn = KNeighborsClassifier(n_neighbors = 3)"
    ]
   },
   {
@@ -586,12 +2112,47 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 301,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.9381443298969072"
+      ]
+     },
+     "execution_count": 301,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "# Your code here:\n",
-    "\n"
+    "knn.fit(X_train, y_train)\n",
+    "knn.score(X_test, y_test)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 303,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "confusion matrix :\n",
+      " [[169   5]\n",
+      " [  7  13]]\n",
+      "accuracy score : 0.9381443298969072\n"
+     ]
+    }
+   ],
+   "source": [
+    "y_pred = knn.predict(X_test)\n",
+    "\n",
+    "print(f\"confusion matrix :\\n {confusion_matrix(y_test, y_pred)}\")\n",
+    "print(f\"accuracy score : {accuracy_score(y_test, y_pred)}\")"
    ]
   },
   {
@@ -605,12 +2166,48 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 304,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.9432989690721649"
+      ]
+     },
+     "execution_count": 304,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "# Your code here:\n",
-    "\n"
+    "knn = KNeighborsClassifier(n_neighbors = 5)\n",
+    "knn.fit(X_train, y_train)\n",
+    "knn.score(X_test, y_test)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 305,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "confusion matrix :\n",
+      " [[171   3]\n",
+      " [  8  12]]\n",
+      "accuracy score : 0.9432989690721649\n"
+     ]
+    }
+   ],
+   "source": [
+    "y_pred = knn.predict(X_test)\n",
+    "\n",
+    "print(f\"confusion matrix :\\n {confusion_matrix(y_test, y_pred)}\")\n",
+    "print(f\"accuracy score : {accuracy_score(y_test, y_pred)}\")"
    ]
   },
   {
@@ -622,12 +2219,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 37,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your conclusions here:\n",
-    "\n"
+    "# Your conclusions here: Yes, increasing the k to 5 made the model better. "
    ]
   },
   {
@@ -645,7 +2241,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 38,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -655,9 +2251,9 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "ironhack-3.7",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
-   "name": "ironhack-3.7"
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
@@ -669,7 +2265,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.3"
+   "version": "3.10.9"
   }
  },
  "nbformat": 4,
diff --git a/data/website.csv b/your-code/website.csv
old mode 100755
new mode 100644
similarity index 100%
rename from data/website.csv
rename to your-code/website.csv