no_ipsrc_simulation.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   frame.number  frame.time_relative  frame.len ip.proto  \\\n",
      "0             1             0.000000        156        6   \n",
      "1             2             0.220575         66        6   \n",
      "2             3             0.537609        284        6   \n",
      "3             4             2.075699        156        6   \n",
      "4             5             2.186605         90       17   \n",
      "\n",
      "            frame.protocols         ip.dst  tcp.srcport  tcp.dstport  \\\n",
      "0  eth:ethertype:ip:tcp:tls  52.87.241.159      40767.0        443.0   \n",
      "1      eth:ethertype:ip:tcp  192.168.1.106        443.0      40767.0   \n",
      "2  eth:ethertype:ip:tcp:tls  52.87.241.159      40767.0        443.0   \n",
      "3  eth:ethertype:ip:tcp:tls  52.87.241.159      40767.0        443.0   \n",
      "4  eth:ethertype:ip:udp:ntp  192.168.1.196          NaN          NaN   \n",
      "\n",
      "   udp.srcport  udp.dstport ip.dsfield.dscp            eth.src  \\\n",
      "0          NaN          NaN               0  30:8c:fb:2f:e4:b2   \n",
      "1          NaN          NaN               0  14:cc:20:51:33:ea   \n",
      "2          NaN          NaN               0  30:8c:fb:2f:e4:b2   \n",
      "3          NaN          NaN               0  30:8c:fb:2f:e4:b2   \n",
      "4        123.0       4967.0               6  14:cc:20:51:33:ea   \n",
      "\n",
      "             eth.dst  \n",
      "0  14:cc:20:51:33:ea  \n",
      "1  30:8c:fb:2f:e4:b2  \n",
      "2  14:cc:20:51:33:ea  \n",
      "3  14:cc:20:51:33:ea  \n",
      "4  d0:52:a8:00:67:5e  \n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/deepak/.local/lib/python3.8/site-packages/IPython/core/interactiveshell.py:3062: DtypeWarning: Columns (3,11) have mixed types.Specify dtype option on import or set low_memory=False.\n",
      "  has_raised = await self.run_ast_nodes(code_ast.body, cell_name,\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(527035, 13)"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np \n",
    "import pandas as pd \n",
    "import csv\n",
    "\n",
    "df = pd.read_csv(\"16-09-27.csv\", sep='\\t', dtype={'frame.number':np.int64})\n",
    "df = df.drop(['ip.src'],axis=1)\n",
    "print(df.head(5))\n",
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "32040"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Selecting 1 of packets randomly of amazon Echo: 44:65:0d:56:cc:d3\n",
    "echo = df[df['eth.src']=='44:65:0d:56:cc:d3'].sample(n=1,random_state=1)['frame.number']\n",
    "echo_start = echo.iloc[0]-1\n",
    "echo_start"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3116"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "echo_total = len(df[df['eth.src']=='44:65:0d:56:cc:d3'])\n",
    "echo_10 = int(round(echo_total*.1))\n",
    "echo_10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1470420"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-4-5c69e15571b3>:1: UserWarning: Boolean Series key will be reindexed to match DataFrame index.\n",
      "  echo_10p = df[(echo_start):][df['eth.src']=='44:65:0d:56:cc:d3']\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>frame.number</th>\n",
       "      <th>frame.time_relative</th>\n",
       "      <th>frame.len</th>\n",
       "      <th>ip.proto</th>\n",
       "      <th>frame.protocols</th>\n",
       "      <th>ip.dst</th>\n",
       "      <th>tcp.srcport</th>\n",
       "      <th>tcp.dstport</th>\n",
       "      <th>udp.srcport</th>\n",
       "      <th>udp.dstport</th>\n",
       "      <th>ip.dsfield.dscp</th>\n",
       "      <th>eth.src</th>\n",
       "      <th>eth.dst</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>32040</th>\n",
       "      <td>32041</td>\n",
       "      <td>5742.056713</td>\n",
       "      <td>74</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp</td>\n",
       "      <td>93.184.216.34</td>\n",
       "      <td>33282.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>44:65:0d:56:cc:d3</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32043</th>\n",
       "      <td>32044</td>\n",
       "      <td>5742.169883</td>\n",
       "      <td>66</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp</td>\n",
       "      <td>93.184.216.34</td>\n",
       "      <td>33281.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>44:65:0d:56:cc:d3</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32045</th>\n",
       "      <td>32046</td>\n",
       "      <td>5742.216645</td>\n",
       "      <td>66</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp</td>\n",
       "      <td>93.184.216.34</td>\n",
       "      <td>33282.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>44:65:0d:56:cc:d3</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32046</th>\n",
       "      <td>32047</td>\n",
       "      <td>5742.217355</td>\n",
       "      <td>66</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp</td>\n",
       "      <td>93.184.216.34</td>\n",
       "      <td>33282.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>44:65:0d:56:cc:d3</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32047</th>\n",
       "      <td>32048</td>\n",
       "      <td>5742.219355</td>\n",
       "      <td>75</td>\n",
       "      <td>17</td>\n",
       "      <td>eth:ethertype:ip:udp:dns</td>\n",
       "      <td>8.8.8.8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>51224.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>0</td>\n",
       "      <td>44:65:0d:56:cc:d3</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>526866</th>\n",
       "      <td>526867</td>\n",
       "      <td>86362.621767</td>\n",
       "      <td>191</td>\n",
       "      <td>17</td>\n",
       "      <td>eth:ethertype:ip:udp:data</td>\n",
       "      <td>23.23.189.20</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>47532.0</td>\n",
       "      <td>33434.0</td>\n",
       "      <td>0</td>\n",
       "      <td>44:65:0d:56:cc:d3</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>526958</th>\n",
       "      <td>526959</td>\n",
       "      <td>86381.259183</td>\n",
       "      <td>201</td>\n",
       "      <td>17</td>\n",
       "      <td>eth:ethertype:ip:udp:data</td>\n",
       "      <td>23.23.189.20</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>49280.0</td>\n",
       "      <td>33434.0</td>\n",
       "      <td>0</td>\n",
       "      <td>44:65:0d:56:cc:d3</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>526986</th>\n",
       "      <td>526987</td>\n",
       "      <td>86389.459048</td>\n",
       "      <td>54</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp</td>\n",
       "      <td>176.32.100.25</td>\n",
       "      <td>52424.0</td>\n",
       "      <td>443.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>44:65:0d:56:cc:d3</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>526987</th>\n",
       "      <td>526988</td>\n",
       "      <td>86389.459158</td>\n",
       "      <td>95</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp:tls</td>\n",
       "      <td>176.32.100.25</td>\n",
       "      <td>52424.0</td>\n",
       "      <td>443.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>44:65:0d:56:cc:d3</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>526989</th>\n",
       "      <td>526990</td>\n",
       "      <td>86389.650181</td>\n",
       "      <td>191</td>\n",
       "      <td>17</td>\n",
       "      <td>eth:ethertype:ip:udp:data</td>\n",
       "      <td>23.23.189.20</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>47532.0</td>\n",
       "      <td>33434.0</td>\n",
       "      <td>0</td>\n",
       "      <td>44:65:0d:56:cc:d3</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>29077 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        frame.number  frame.time_relative  frame.len ip.proto  \\\n",
       "32040          32041          5742.056713         74        6   \n",
       "32043          32044          5742.169883         66        6   \n",
       "32045          32046          5742.216645         66        6   \n",
       "32046          32047          5742.217355         66        6   \n",
       "32047          32048          5742.219355         75       17   \n",
       "...              ...                  ...        ...      ...   \n",
       "526866        526867         86362.621767        191       17   \n",
       "526958        526959         86381.259183        201       17   \n",
       "526986        526987         86389.459048         54        6   \n",
       "526987        526988         86389.459158         95        6   \n",
       "526989        526990         86389.650181        191       17   \n",
       "\n",
       "                  frame.protocols         ip.dst  tcp.srcport  tcp.dstport  \\\n",
       "32040        eth:ethertype:ip:tcp  93.184.216.34      33282.0         80.0   \n",
       "32043        eth:ethertype:ip:tcp  93.184.216.34      33281.0         80.0   \n",
       "32045        eth:ethertype:ip:tcp  93.184.216.34      33282.0         80.0   \n",
       "32046        eth:ethertype:ip:tcp  93.184.216.34      33282.0         80.0   \n",
       "32047    eth:ethertype:ip:udp:dns        8.8.8.8          NaN          NaN   \n",
       "...                           ...            ...          ...          ...   \n",
       "526866  eth:ethertype:ip:udp:data   23.23.189.20          NaN          NaN   \n",
       "526958  eth:ethertype:ip:udp:data   23.23.189.20          NaN          NaN   \n",
       "526986       eth:ethertype:ip:tcp  176.32.100.25      52424.0        443.0   \n",
       "526987   eth:ethertype:ip:tcp:tls  176.32.100.25      52424.0        443.0   \n",
       "526989  eth:ethertype:ip:udp:data   23.23.189.20          NaN          NaN   \n",
       "\n",
       "        udp.srcport  udp.dstport ip.dsfield.dscp            eth.src  \\\n",
       "32040           NaN          NaN               0  44:65:0d:56:cc:d3   \n",
       "32043           NaN          NaN               0  44:65:0d:56:cc:d3   \n",
       "32045           NaN          NaN               0  44:65:0d:56:cc:d3   \n",
       "32046           NaN          NaN               0  44:65:0d:56:cc:d3   \n",
       "32047       51224.0         53.0               0  44:65:0d:56:cc:d3   \n",
       "...             ...          ...             ...                ...   \n",
       "526866      47532.0      33434.0               0  44:65:0d:56:cc:d3   \n",
       "526958      49280.0      33434.0               0  44:65:0d:56:cc:d3   \n",
       "526986          NaN          NaN               0  44:65:0d:56:cc:d3   \n",
       "526987          NaN          NaN               0  44:65:0d:56:cc:d3   \n",
       "526989      47532.0      33434.0               0  44:65:0d:56:cc:d3   \n",
       "\n",
       "                  eth.dst  \n",
       "32040   14:cc:20:51:33:ea  \n",
       "32043   14:cc:20:51:33:ea  \n",
       "32045   14:cc:20:51:33:ea  \n",
       "32046   14:cc:20:51:33:ea  \n",
       "32047   14:cc:20:51:33:ea  \n",
       "...                   ...  \n",
       "526866  14:cc:20:51:33:ea  \n",
       "526958  14:cc:20:51:33:ea  \n",
       "526986  14:cc:20:51:33:ea  \n",
       "526987  14:cc:20:51:33:ea  \n",
       "526989  14:cc:20:51:33:ea  \n",
       "\n",
       "[29077 rows x 13 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "echo_10p = df[(echo_start):][df['eth.src']=='44:65:0d:56:cc:d3']\n",
    "echo_10p"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "17417\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>frame.number</th>\n",
       "      <th>frame.time_relative</th>\n",
       "      <th>frame.len</th>\n",
       "      <th>ip.proto</th>\n",
       "      <th>frame.protocols</th>\n",
       "      <th>ip.dst</th>\n",
       "      <th>tcp.srcport</th>\n",
       "      <th>tcp.dstport</th>\n",
       "      <th>udp.srcport</th>\n",
       "      <th>udp.dstport</th>\n",
       "      <th>ip.dsfield.dscp</th>\n",
       "      <th>eth.src</th>\n",
       "      <th>eth.dst</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>32040</th>\n",
       "      <td>32041</td>\n",
       "      <td>5742.056713</td>\n",
       "      <td>74</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp</td>\n",
       "      <td>93.184.216.34</td>\n",
       "      <td>33282.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>44:65:0d:56:cc:d3</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32043</th>\n",
       "      <td>32044</td>\n",
       "      <td>5742.169883</td>\n",
       "      <td>66</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp</td>\n",
       "      <td>93.184.216.34</td>\n",
       "      <td>33281.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>44:65:0d:56:cc:d3</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32045</th>\n",
       "      <td>32046</td>\n",
       "      <td>5742.216645</td>\n",
       "      <td>66</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp</td>\n",
       "      <td>93.184.216.34</td>\n",
       "      <td>33282.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>44:65:0d:56:cc:d3</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32046</th>\n",
       "      <td>32047</td>\n",
       "      <td>5742.217355</td>\n",
       "      <td>66</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp</td>\n",
       "      <td>93.184.216.34</td>\n",
       "      <td>33282.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>44:65:0d:56:cc:d3</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32047</th>\n",
       "      <td>32048</td>\n",
       "      <td>5742.219355</td>\n",
       "      <td>75</td>\n",
       "      <td>17</td>\n",
       "      <td>eth:ethertype:ip:udp:dns</td>\n",
       "      <td>8.8.8.8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>51224.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>0</td>\n",
       "      <td>44:65:0d:56:cc:d3</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79108</th>\n",
       "      <td>79109</td>\n",
       "      <td>14493.817372</td>\n",
       "      <td>98</td>\n",
       "      <td>1</td>\n",
       "      <td>eth:ethertype:ip:icmp:data</td>\n",
       "      <td>192.168.1.1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>44:65:0d:56:cc:d3</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79110</th>\n",
       "      <td>79111</td>\n",
       "      <td>14493.822176</td>\n",
       "      <td>98</td>\n",
       "      <td>1</td>\n",
       "      <td>eth:ethertype:ip:icmp:data</td>\n",
       "      <td>192.168.1.1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>44:65:0d:56:cc:d3</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79112</th>\n",
       "      <td>79113</td>\n",
       "      <td>14493.825995</td>\n",
       "      <td>98</td>\n",
       "      <td>1</td>\n",
       "      <td>eth:ethertype:ip:icmp:data</td>\n",
       "      <td>192.168.1.1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>44:65:0d:56:cc:d3</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79114</th>\n",
       "      <td>79115</td>\n",
       "      <td>14493.829887</td>\n",
       "      <td>98</td>\n",
       "      <td>1</td>\n",
       "      <td>eth:ethertype:ip:icmp:data</td>\n",
       "      <td>192.168.1.1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>44:65:0d:56:cc:d3</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79116</th>\n",
       "      <td>79117</td>\n",
       "      <td>14493.834664</td>\n",
       "      <td>98</td>\n",
       "      <td>1</td>\n",
       "      <td>eth:ethertype:ip:icmp:data</td>\n",
       "      <td>8.8.8.8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>44:65:0d:56:cc:d3</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3116 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       frame.number  frame.time_relative  frame.len ip.proto  \\\n",
       "32040         32041          5742.056713         74        6   \n",
       "32043         32044          5742.169883         66        6   \n",
       "32045         32046          5742.216645         66        6   \n",
       "32046         32047          5742.217355         66        6   \n",
       "32047         32048          5742.219355         75       17   \n",
       "...             ...                  ...        ...      ...   \n",
       "79108         79109         14493.817372         98        1   \n",
       "79110         79111         14493.822176         98        1   \n",
       "79112         79113         14493.825995         98        1   \n",
       "79114         79115         14493.829887         98        1   \n",
       "79116         79117         14493.834664         98        1   \n",
       "\n",
       "                  frame.protocols         ip.dst  tcp.srcport  tcp.dstport  \\\n",
       "32040        eth:ethertype:ip:tcp  93.184.216.34      33282.0         80.0   \n",
       "32043        eth:ethertype:ip:tcp  93.184.216.34      33281.0         80.0   \n",
       "32045        eth:ethertype:ip:tcp  93.184.216.34      33282.0         80.0   \n",
       "32046        eth:ethertype:ip:tcp  93.184.216.34      33282.0         80.0   \n",
       "32047    eth:ethertype:ip:udp:dns        8.8.8.8          NaN          NaN   \n",
       "...                           ...            ...          ...          ...   \n",
       "79108  eth:ethertype:ip:icmp:data    192.168.1.1          NaN          NaN   \n",
       "79110  eth:ethertype:ip:icmp:data    192.168.1.1          NaN          NaN   \n",
       "79112  eth:ethertype:ip:icmp:data    192.168.1.1          NaN          NaN   \n",
       "79114  eth:ethertype:ip:icmp:data    192.168.1.1          NaN          NaN   \n",
       "79116  eth:ethertype:ip:icmp:data        8.8.8.8          NaN          NaN   \n",
       "\n",
       "       udp.srcport  udp.dstport ip.dsfield.dscp            eth.src  \\\n",
       "32040          NaN          NaN               0  44:65:0d:56:cc:d3   \n",
       "32043          NaN          NaN               0  44:65:0d:56:cc:d3   \n",
       "32045          NaN          NaN               0  44:65:0d:56:cc:d3   \n",
       "32046          NaN          NaN               0  44:65:0d:56:cc:d3   \n",
       "32047      51224.0         53.0               0  44:65:0d:56:cc:d3   \n",
       "...            ...          ...             ...                ...   \n",
       "79108          NaN          NaN               0  44:65:0d:56:cc:d3   \n",
       "79110          NaN          NaN               0  44:65:0d:56:cc:d3   \n",
       "79112          NaN          NaN               0  44:65:0d:56:cc:d3   \n",
       "79114          NaN          NaN               0  44:65:0d:56:cc:d3   \n",
       "79116          NaN          NaN               0  44:65:0d:56:cc:d3   \n",
       "\n",
       "                 eth.dst  \n",
       "32040  14:cc:20:51:33:ea  \n",
       "32043  14:cc:20:51:33:ea  \n",
       "32045  14:cc:20:51:33:ea  \n",
       "32046  14:cc:20:51:33:ea  \n",
       "32047  14:cc:20:51:33:ea  \n",
       "...                  ...  \n",
       "79108  14:cc:20:51:33:ea  \n",
       "79110  14:cc:20:51:33:ea  \n",
       "79112  14:cc:20:51:33:ea  \n",
       "79114  14:cc:20:51:33:ea  \n",
       "79116  14:cc:20:51:33:ea  \n",
       "\n",
       "[3116 rows x 13 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "echo_10pc = pd.DataFrame()\n",
    "length = len(echo_10p.index)\n",
    "print(length)\n",
    "while(length>echo_10):\n",
    "    echo_10p = echo_10p.drop(echo_10p.index[length-1])\n",
    "    length = len(echo_10p.index)\n",
    "echo_10p"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "echo_np = echo_10p.index.to_numpy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "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>frame.number</th>\n",
       "      <th>frame.time_relative</th>\n",
       "      <th>frame.len</th>\n",
       "      <th>ip.proto</th>\n",
       "      <th>frame.protocols</th>\n",
       "      <th>ip.dst</th>\n",
       "      <th>tcp.srcport</th>\n",
       "      <th>tcp.dstport</th>\n",
       "      <th>udp.srcport</th>\n",
       "      <th>udp.dstport</th>\n",
       "      <th>ip.dsfield.dscp</th>\n",
       "      <th>eth.src</th>\n",
       "      <th>eth.dst</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>32040</th>\n",
       "      <td>32041</td>\n",
       "      <td>5742.056713</td>\n",
       "      <td>75</td>\n",
       "      <td>17</td>\n",
       "      <td>eth:ethertype:ip:udp:dns</td>\n",
       "      <td>192.168.1.1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>23456.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>0</td>\n",
       "      <td>44:65:0d:56:cc:d3</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32043</th>\n",
       "      <td>32044</td>\n",
       "      <td>5742.169883</td>\n",
       "      <td>75</td>\n",
       "      <td>17</td>\n",
       "      <td>eth:ethertype:ip:udp:dns</td>\n",
       "      <td>192.168.1.1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>23456.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>0</td>\n",
       "      <td>44:65:0d:56:cc:d3</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32045</th>\n",
       "      <td>32046</td>\n",
       "      <td>5742.216645</td>\n",
       "      <td>75</td>\n",
       "      <td>17</td>\n",
       "      <td>eth:ethertype:ip:udp:dns</td>\n",
       "      <td>8.8.8.8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>23456.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>0</td>\n",
       "      <td>44:65:0d:56:cc:d3</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32046</th>\n",
       "      <td>32047</td>\n",
       "      <td>5742.217355</td>\n",
       "      <td>75</td>\n",
       "      <td>17</td>\n",
       "      <td>eth:ethertype:ip:udp:dns</td>\n",
       "      <td>8.8.8.8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>23456.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>0</td>\n",
       "      <td>44:65:0d:56:cc:d3</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32047</th>\n",
       "      <td>32048</td>\n",
       "      <td>5742.219355</td>\n",
       "      <td>75</td>\n",
       "      <td>17</td>\n",
       "      <td>eth:ethertype:ip:udp:dns</td>\n",
       "      <td>8.8.8.8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>23456.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>0</td>\n",
       "      <td>44:65:0d:56:cc:d3</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79108</th>\n",
       "      <td>79109</td>\n",
       "      <td>14493.817372</td>\n",
       "      <td>148</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp</td>\n",
       "      <td>62.210.205.141</td>\n",
       "      <td>23326.0</td>\n",
       "      <td>443.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>44:65:0d:56:cc:d3</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79110</th>\n",
       "      <td>79111</td>\n",
       "      <td>14493.822176</td>\n",
       "      <td>74</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp:tls</td>\n",
       "      <td>62.210.205.141</td>\n",
       "      <td>23325.0</td>\n",
       "      <td>443.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>44:65:0d:56:cc:d3</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79112</th>\n",
       "      <td>79113</td>\n",
       "      <td>14493.825995</td>\n",
       "      <td>148</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp</td>\n",
       "      <td>62.210.205.141</td>\n",
       "      <td>23323.0</td>\n",
       "      <td>443.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>44:65:0d:56:cc:d3</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79114</th>\n",
       "      <td>79115</td>\n",
       "      <td>14493.829887</td>\n",
       "      <td>97</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp</td>\n",
       "      <td>62.210.205.141</td>\n",
       "      <td>23325.0</td>\n",
       "      <td>443.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>44:65:0d:56:cc:d3</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79116</th>\n",
       "      <td>79117</td>\n",
       "      <td>14493.834664</td>\n",
       "      <td>296</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp</td>\n",
       "      <td>62.210.205.141</td>\n",
       "      <td>23325.0</td>\n",
       "      <td>443.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>44:65:0d:56:cc:d3</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3116 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       frame.number  frame.time_relative  frame.len ip.proto  \\\n",
       "32040         32041          5742.056713         75       17   \n",
       "32043         32044          5742.169883         75       17   \n",
       "32045         32046          5742.216645         75       17   \n",
       "32046         32047          5742.217355         75       17   \n",
       "32047         32048          5742.219355         75       17   \n",
       "...             ...                  ...        ...      ...   \n",
       "79108         79109         14493.817372        148        6   \n",
       "79110         79111         14493.822176         74        6   \n",
       "79112         79113         14493.825995        148        6   \n",
       "79114         79115         14493.829887         97        6   \n",
       "79116         79117         14493.834664        296        6   \n",
       "\n",
       "                frame.protocols          ip.dst  tcp.srcport  tcp.dstport  \\\n",
       "32040  eth:ethertype:ip:udp:dns     192.168.1.1          NaN          NaN   \n",
       "32043  eth:ethertype:ip:udp:dns     192.168.1.1          NaN          NaN   \n",
       "32045  eth:ethertype:ip:udp:dns         8.8.8.8          NaN          NaN   \n",
       "32046  eth:ethertype:ip:udp:dns         8.8.8.8          NaN          NaN   \n",
       "32047  eth:ethertype:ip:udp:dns         8.8.8.8          NaN          NaN   \n",
       "...                         ...             ...          ...          ...   \n",
       "79108      eth:ethertype:ip:tcp  62.210.205.141      23326.0        443.0   \n",
       "79110  eth:ethertype:ip:tcp:tls  62.210.205.141      23325.0        443.0   \n",
       "79112      eth:ethertype:ip:tcp  62.210.205.141      23323.0        443.0   \n",
       "79114      eth:ethertype:ip:tcp  62.210.205.141      23325.0        443.0   \n",
       "79116      eth:ethertype:ip:tcp  62.210.205.141      23325.0        443.0   \n",
       "\n",
       "       udp.srcport  udp.dstport ip.dsfield.dscp            eth.src  \\\n",
       "32040      23456.0         53.0               0  44:65:0d:56:cc:d3   \n",
       "32043      23456.0         53.0               0  44:65:0d:56:cc:d3   \n",
       "32045      23456.0         53.0               0  44:65:0d:56:cc:d3   \n",
       "32046      23456.0         53.0               0  44:65:0d:56:cc:d3   \n",
       "32047      23456.0         53.0               0  44:65:0d:56:cc:d3   \n",
       "...            ...          ...             ...                ...   \n",
       "79108          NaN          NaN               0  44:65:0d:56:cc:d3   \n",
       "79110          NaN          NaN               0  44:65:0d:56:cc:d3   \n",
       "79112          NaN          NaN               0  44:65:0d:56:cc:d3   \n",
       "79114          NaN          NaN               0  44:65:0d:56:cc:d3   \n",
       "79116          NaN          NaN               0  44:65:0d:56:cc:d3   \n",
       "\n",
       "                 eth.dst  \n",
       "32040  14:cc:20:51:33:ea  \n",
       "32043  14:cc:20:51:33:ea  \n",
       "32045  14:cc:20:51:33:ea  \n",
       "32046  14:cc:20:51:33:ea  \n",
       "32047  14:cc:20:51:33:ea  \n",
       "...                  ...  \n",
       "79108  14:cc:20:51:33:ea  \n",
       "79110  14:cc:20:51:33:ea  \n",
       "79112  14:cc:20:51:33:ea  \n",
       "79114  14:cc:20:51:33:ea  \n",
       "79116  14:cc:20:51:33:ea  \n",
       "\n",
       "[3116 rows x 13 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import random\n",
    "\n",
    "i = 0      # DNS ip = 192.168.1.1, des port 53, src port 44239, dscp 0, len 75\n",
    "while(i<echo_10):\n",
    "    while(i<2):\n",
    "        echo_10p.loc[echo_10p.iloc[i].name,['frame.len','ip.proto','frame.protocols','ip.dst','tcp.srcport','tcp.dstport','udp.srcport','udp.dstport','ip.dsfield.dscp']] = 75, 17, 'eth:ethertype:ip:udp:dns', '192.168.1.1', np.NaN, np.NaN, 23456, 53, 0\n",
    "        i+=1\n",
    "    while(i<6):\n",
    "        echo_10p.loc[echo_10p.iloc[i].name,['frame.len','ip.proto','frame.protocols','ip.dst','tcp.srcport','tcp.dstport','udp.srcport','udp.dstport','ip.dsfield.dscp']] = 75, 17, 'eth:ethertype:ip:udp:dns', '8.8.8.8', np.NaN, np.NaN, 23456, 53, 0\n",
    "        i+=1\n",
    "    rn = random.randint(1,5)           #random integer\n",
    "    if (rn==1):\n",
    "        echo_10p.loc[echo_10p.iloc[i].name,['frame.len','ip.proto','frame.protocols','ip.dst','tcp.srcport','tcp.dstport','udp.srcport','udp.dstport','ip.dsfield.dscp']] = random.choice([66,97,74,341,554,1472,148,296,774,2344]), 6, 'eth:ethertype:ip:tcp:tls', '62.210.205.141', random.choice([23323,23325,23326]), 443, np.NaN, np.NaN, 0\n",
    "    else:\n",
    "        echo_10p.loc[echo_10p.iloc[i].name,['frame.len','ip.proto','frame.protocols','ip.dst','tcp.srcport','tcp.dstport','udp.srcport','udp.dstport','ip.dsfield.dscp']] = random.choice([66,97,74,148,296]), 6, 'eth:ethertype:ip:tcp', '62.210.205.141', random.choice([23323,23325,23326]), 443, np.NaN, np.NaN, 0\n",
    "    i+=1\n",
    "    \n",
    "echo_10p"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "after_echo = echo_10p\n",
    "# inserting changed row back to overall dataframe\n",
    "# df.loc[after_echo.loc[0].]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "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>frame.number</th>\n",
       "      <th>frame.time_relative</th>\n",
       "      <th>frame.len</th>\n",
       "      <th>ip.proto</th>\n",
       "      <th>frame.protocols</th>\n",
       "      <th>ip.dst</th>\n",
       "      <th>tcp.srcport</th>\n",
       "      <th>tcp.dstport</th>\n",
       "      <th>udp.srcport</th>\n",
       "      <th>udp.dstport</th>\n",
       "      <th>ip.dsfield.dscp</th>\n",
       "      <th>eth.src</th>\n",
       "      <th>eth.dst</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>156</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp:tls</td>\n",
       "      <td>52.87.241.159</td>\n",
       "      <td>40767.0</td>\n",
       "      <td>443.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>30:8c:fb:2f:e4:b2</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>0.220575</td>\n",
       "      <td>66</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp</td>\n",
       "      <td>192.168.1.106</td>\n",
       "      <td>443.0</td>\n",
       "      <td>40767.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "      <td>30:8c:fb:2f:e4:b2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>0.537609</td>\n",
       "      <td>284</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp:tls</td>\n",
       "      <td>52.87.241.159</td>\n",
       "      <td>40767.0</td>\n",
       "      <td>443.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>30:8c:fb:2f:e4:b2</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>2.075699</td>\n",
       "      <td>156</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp:tls</td>\n",
       "      <td>52.87.241.159</td>\n",
       "      <td>40767.0</td>\n",
       "      <td>443.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>30:8c:fb:2f:e4:b2</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>2.186605</td>\n",
       "      <td>90</td>\n",
       "      <td>17</td>\n",
       "      <td>eth:ethertype:ip:udp:ntp</td>\n",
       "      <td>192.168.1.196</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>123.0</td>\n",
       "      <td>4967.0</td>\n",
       "      <td>6</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "      <td>d0:52:a8:00:67:5e</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32040</th>\n",
       "      <td>32041</td>\n",
       "      <td>5742.056713</td>\n",
       "      <td>75</td>\n",
       "      <td>17</td>\n",
       "      <td>eth:ethertype:ip:udp:dns</td>\n",
       "      <td>192.168.1.1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>23456.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>0</td>\n",
       "      <td>44:65:0d:56:cc:d3</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32041</th>\n",
       "      <td>32042</td>\n",
       "      <td>5742.125377</td>\n",
       "      <td>66</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp</td>\n",
       "      <td>192.168.1.106</td>\n",
       "      <td>443.0</td>\n",
       "      <td>40767.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "      <td>30:8c:fb:2f:e4:b2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32042</th>\n",
       "      <td>32043</td>\n",
       "      <td>5742.159399</td>\n",
       "      <td>66</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp</td>\n",
       "      <td>192.168.1.240</td>\n",
       "      <td>80.0</td>\n",
       "      <td>33281.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "      <td>44:65:0d:56:cc:d3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32043</th>\n",
       "      <td>32044</td>\n",
       "      <td>5742.169883</td>\n",
       "      <td>75</td>\n",
       "      <td>17</td>\n",
       "      <td>eth:ethertype:ip:udp:dns</td>\n",
       "      <td>192.168.1.1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>23456.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>0</td>\n",
       "      <td>44:65:0d:56:cc:d3</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32044</th>\n",
       "      <td>32045</td>\n",
       "      <td>5742.200324</td>\n",
       "      <td>74</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp</td>\n",
       "      <td>192.168.1.240</td>\n",
       "      <td>80.0</td>\n",
       "      <td>33282.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "      <td>44:65:0d:56:cc:d3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>32045 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       frame.number  frame.time_relative  frame.len ip.proto  \\\n",
       "0                 1             0.000000        156        6   \n",
       "1                 2             0.220575         66        6   \n",
       "2                 3             0.537609        284        6   \n",
       "3                 4             2.075699        156        6   \n",
       "4                 5             2.186605         90       17   \n",
       "...             ...                  ...        ...      ...   \n",
       "32040         32041          5742.056713         75       17   \n",
       "32041         32042          5742.125377         66        6   \n",
       "32042         32043          5742.159399         66        6   \n",
       "32043         32044          5742.169883         75       17   \n",
       "32044         32045          5742.200324         74        6   \n",
       "\n",
       "                frame.protocols         ip.dst  tcp.srcport  tcp.dstport  \\\n",
       "0      eth:ethertype:ip:tcp:tls  52.87.241.159      40767.0        443.0   \n",
       "1          eth:ethertype:ip:tcp  192.168.1.106        443.0      40767.0   \n",
       "2      eth:ethertype:ip:tcp:tls  52.87.241.159      40767.0        443.0   \n",
       "3      eth:ethertype:ip:tcp:tls  52.87.241.159      40767.0        443.0   \n",
       "4      eth:ethertype:ip:udp:ntp  192.168.1.196          NaN          NaN   \n",
       "...                         ...            ...          ...          ...   \n",
       "32040  eth:ethertype:ip:udp:dns    192.168.1.1          NaN          NaN   \n",
       "32041      eth:ethertype:ip:tcp  192.168.1.106        443.0      40767.0   \n",
       "32042      eth:ethertype:ip:tcp  192.168.1.240         80.0      33281.0   \n",
       "32043  eth:ethertype:ip:udp:dns    192.168.1.1          NaN          NaN   \n",
       "32044      eth:ethertype:ip:tcp  192.168.1.240         80.0      33282.0   \n",
       "\n",
       "       udp.srcport  udp.dstport ip.dsfield.dscp            eth.src  \\\n",
       "0              NaN          NaN               0  30:8c:fb:2f:e4:b2   \n",
       "1              NaN          NaN               0  14:cc:20:51:33:ea   \n",
       "2              NaN          NaN               0  30:8c:fb:2f:e4:b2   \n",
       "3              NaN          NaN               0  30:8c:fb:2f:e4:b2   \n",
       "4            123.0       4967.0               6  14:cc:20:51:33:ea   \n",
       "...            ...          ...             ...                ...   \n",
       "32040      23456.0         53.0               0  44:65:0d:56:cc:d3   \n",
       "32041          NaN          NaN               0  14:cc:20:51:33:ea   \n",
       "32042          NaN          NaN               0  14:cc:20:51:33:ea   \n",
       "32043      23456.0         53.0               0  44:65:0d:56:cc:d3   \n",
       "32044          NaN          NaN               0  14:cc:20:51:33:ea   \n",
       "\n",
       "                 eth.dst  \n",
       "0      14:cc:20:51:33:ea  \n",
       "1      30:8c:fb:2f:e4:b2  \n",
       "2      14:cc:20:51:33:ea  \n",
       "3      14:cc:20:51:33:ea  \n",
       "4      d0:52:a8:00:67:5e  \n",
       "...                  ...  \n",
       "32040  14:cc:20:51:33:ea  \n",
       "32041  30:8c:fb:2f:e4:b2  \n",
       "32042  44:65:0d:56:cc:d3  \n",
       "32043  14:cc:20:51:33:ea  \n",
       "32044  44:65:0d:56:cc:d3  \n",
       "\n",
       "[32045 rows x 13 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test = df\n",
    "i = 0\n",
    "while (i<echo_10):\n",
    "    test.loc[after_echo.iloc[i].name] = after_echo.iloc[i]\n",
    "    i+=1\n",
    "test.head(32045)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 195,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "# # write to CSV\n",
    "# test.to_csv('simulated_csv.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10503\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-11-97be0c7c33fc>:11: UserWarning: Boolean Series key will be reindexed to match DataFrame index.\n",
      "  dropcam_10p = df[(dropcam_start):][df['eth.src']=='30:8c:fb:2f:e4:b2']\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>frame.number</th>\n",
       "      <th>frame.time_relative</th>\n",
       "      <th>frame.len</th>\n",
       "      <th>ip.proto</th>\n",
       "      <th>frame.protocols</th>\n",
       "      <th>ip.dst</th>\n",
       "      <th>tcp.srcport</th>\n",
       "      <th>tcp.dstport</th>\n",
       "      <th>udp.srcport</th>\n",
       "      <th>udp.dstport</th>\n",
       "      <th>ip.dsfield.dscp</th>\n",
       "      <th>eth.src</th>\n",
       "      <th>eth.dst</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>32062</th>\n",
       "      <td>32063</td>\n",
       "      <td>5743.989610</td>\n",
       "      <td>156</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp:tls</td>\n",
       "      <td>52.87.241.159</td>\n",
       "      <td>40767.0</td>\n",
       "      <td>443.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>30:8c:fb:2f:e4:b2</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32064</th>\n",
       "      <td>32065</td>\n",
       "      <td>5745.013440</td>\n",
       "      <td>156</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp:tls</td>\n",
       "      <td>52.87.241.159</td>\n",
       "      <td>40767.0</td>\n",
       "      <td>443.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>30:8c:fb:2f:e4:b2</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32072</th>\n",
       "      <td>32073</td>\n",
       "      <td>5746.054957</td>\n",
       "      <td>156</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp:tls</td>\n",
       "      <td>52.87.241.159</td>\n",
       "      <td>40767.0</td>\n",
       "      <td>443.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>30:8c:fb:2f:e4:b2</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32083</th>\n",
       "      <td>32084</td>\n",
       "      <td>5747.078354</td>\n",
       "      <td>156</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp:tls</td>\n",
       "      <td>52.87.241.159</td>\n",
       "      <td>40767.0</td>\n",
       "      <td>443.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>30:8c:fb:2f:e4:b2</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32089</th>\n",
       "      <td>32090</td>\n",
       "      <td>5747.487942</td>\n",
       "      <td>156</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp:tls</td>\n",
       "      <td>52.87.241.159</td>\n",
       "      <td>40767.0</td>\n",
       "      <td>443.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>30:8c:fb:2f:e4:b2</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>527013</th>\n",
       "      <td>527014</td>\n",
       "      <td>86395.711516</td>\n",
       "      <td>156</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp:tls</td>\n",
       "      <td>52.87.241.159</td>\n",
       "      <td>40767.0</td>\n",
       "      <td>443.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>30:8c:fb:2f:e4:b2</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>527018</th>\n",
       "      <td>527019</td>\n",
       "      <td>86396.238686</td>\n",
       "      <td>284</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp:tls</td>\n",
       "      <td>52.87.241.159</td>\n",
       "      <td>40767.0</td>\n",
       "      <td>443.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>30:8c:fb:2f:e4:b2</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>527021</th>\n",
       "      <td>527022</td>\n",
       "      <td>86396.741598</td>\n",
       "      <td>156</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp:tls</td>\n",
       "      <td>52.87.241.159</td>\n",
       "      <td>40767.0</td>\n",
       "      <td>443.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>30:8c:fb:2f:e4:b2</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>527025</th>\n",
       "      <td>527026</td>\n",
       "      <td>86397.659465</td>\n",
       "      <td>156</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp:tls</td>\n",
       "      <td>52.87.241.159</td>\n",
       "      <td>40767.0</td>\n",
       "      <td>443.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>30:8c:fb:2f:e4:b2</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>527031</th>\n",
       "      <td>527032</td>\n",
       "      <td>86398.698987</td>\n",
       "      <td>156</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp:tls</td>\n",
       "      <td>52.87.241.159</td>\n",
       "      <td>40767.0</td>\n",
       "      <td>443.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>30:8c:fb:2f:e4:b2</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>99442 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        frame.number  frame.time_relative  frame.len ip.proto  \\\n",
       "32062          32063          5743.989610        156        6   \n",
       "32064          32065          5745.013440        156        6   \n",
       "32072          32073          5746.054957        156        6   \n",
       "32083          32084          5747.078354        156        6   \n",
       "32089          32090          5747.487942        156        6   \n",
       "...              ...                  ...        ...      ...   \n",
       "527013        527014         86395.711516        156        6   \n",
       "527018        527019         86396.238686        284        6   \n",
       "527021        527022         86396.741598        156        6   \n",
       "527025        527026         86397.659465        156        6   \n",
       "527031        527032         86398.698987        156        6   \n",
       "\n",
       "                 frame.protocols         ip.dst  tcp.srcport  tcp.dstport  \\\n",
       "32062   eth:ethertype:ip:tcp:tls  52.87.241.159      40767.0        443.0   \n",
       "32064   eth:ethertype:ip:tcp:tls  52.87.241.159      40767.0        443.0   \n",
       "32072   eth:ethertype:ip:tcp:tls  52.87.241.159      40767.0        443.0   \n",
       "32083   eth:ethertype:ip:tcp:tls  52.87.241.159      40767.0        443.0   \n",
       "32089   eth:ethertype:ip:tcp:tls  52.87.241.159      40767.0        443.0   \n",
       "...                          ...            ...          ...          ...   \n",
       "527013  eth:ethertype:ip:tcp:tls  52.87.241.159      40767.0        443.0   \n",
       "527018  eth:ethertype:ip:tcp:tls  52.87.241.159      40767.0        443.0   \n",
       "527021  eth:ethertype:ip:tcp:tls  52.87.241.159      40767.0        443.0   \n",
       "527025  eth:ethertype:ip:tcp:tls  52.87.241.159      40767.0        443.0   \n",
       "527031  eth:ethertype:ip:tcp:tls  52.87.241.159      40767.0        443.0   \n",
       "\n",
       "        udp.srcport  udp.dstport ip.dsfield.dscp            eth.src  \\\n",
       "32062           NaN          NaN               0  30:8c:fb:2f:e4:b2   \n",
       "32064           NaN          NaN               0  30:8c:fb:2f:e4:b2   \n",
       "32072           NaN          NaN               0  30:8c:fb:2f:e4:b2   \n",
       "32083           NaN          NaN               0  30:8c:fb:2f:e4:b2   \n",
       "32089           NaN          NaN               0  30:8c:fb:2f:e4:b2   \n",
       "...             ...          ...             ...                ...   \n",
       "527013          NaN          NaN               0  30:8c:fb:2f:e4:b2   \n",
       "527018          NaN          NaN               0  30:8c:fb:2f:e4:b2   \n",
       "527021          NaN          NaN               0  30:8c:fb:2f:e4:b2   \n",
       "527025          NaN          NaN               0  30:8c:fb:2f:e4:b2   \n",
       "527031          NaN          NaN               0  30:8c:fb:2f:e4:b2   \n",
       "\n",
       "                  eth.dst  \n",
       "32062   14:cc:20:51:33:ea  \n",
       "32064   14:cc:20:51:33:ea  \n",
       "32072   14:cc:20:51:33:ea  \n",
       "32083   14:cc:20:51:33:ea  \n",
       "32089   14:cc:20:51:33:ea  \n",
       "...                   ...  \n",
       "527013  14:cc:20:51:33:ea  \n",
       "527018  14:cc:20:51:33:ea  \n",
       "527021  14:cc:20:51:33:ea  \n",
       "527025  14:cc:20:51:33:ea  \n",
       "527031  14:cc:20:51:33:ea  \n",
       "\n",
       "[99442 rows x 13 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Selecting 1 of packets randomly of amazon Dropcam: 30:8c:fb:2f:e4:b2\n",
    "\n",
    "dropcam = df[df['eth.src']=='30:8c:fb:2f:e4:b2'].sample(n=1,random_state=1)['frame.number']\n",
    "dropcam\n",
    "dropcam_start = echo.iloc[0]-1\n",
    "dropcam_start\n",
    "dropcam_total = len(df[df['eth.src']=='30:8c:fb:2f:e4:b2'])\n",
    "dropcam_10 = int(round(dropcam_total*.1))\n",
    "print(dropcam_10)\n",
    "# dropcam_total\n",
    "dropcam_10p = df[(dropcam_start):][df['eth.src']=='30:8c:fb:2f:e4:b2']\n",
    "dropcam_10p\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "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>frame.number</th>\n",
       "      <th>frame.time_relative</th>\n",
       "      <th>frame.len</th>\n",
       "      <th>ip.proto</th>\n",
       "      <th>frame.protocols</th>\n",
       "      <th>ip.dst</th>\n",
       "      <th>tcp.srcport</th>\n",
       "      <th>tcp.dstport</th>\n",
       "      <th>udp.srcport</th>\n",
       "      <th>udp.dstport</th>\n",
       "      <th>ip.dsfield.dscp</th>\n",
       "      <th>eth.src</th>\n",
       "      <th>eth.dst</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>32062</th>\n",
       "      <td>32063</td>\n",
       "      <td>5743.989610</td>\n",
       "      <td>156</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp:tls</td>\n",
       "      <td>52.87.241.159</td>\n",
       "      <td>40767.0</td>\n",
       "      <td>443.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>30:8c:fb:2f:e4:b2</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32064</th>\n",
       "      <td>32065</td>\n",
       "      <td>5745.013440</td>\n",
       "      <td>156</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp:tls</td>\n",
       "      <td>52.87.241.159</td>\n",
       "      <td>40767.0</td>\n",
       "      <td>443.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>30:8c:fb:2f:e4:b2</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32072</th>\n",
       "      <td>32073</td>\n",
       "      <td>5746.054957</td>\n",
       "      <td>156</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp:tls</td>\n",
       "      <td>52.87.241.159</td>\n",
       "      <td>40767.0</td>\n",
       "      <td>443.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>30:8c:fb:2f:e4:b2</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32083</th>\n",
       "      <td>32084</td>\n",
       "      <td>5747.078354</td>\n",
       "      <td>156</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp:tls</td>\n",
       "      <td>52.87.241.159</td>\n",
       "      <td>40767.0</td>\n",
       "      <td>443.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>30:8c:fb:2f:e4:b2</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32089</th>\n",
       "      <td>32090</td>\n",
       "      <td>5747.487942</td>\n",
       "      <td>156</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp:tls</td>\n",
       "      <td>52.87.241.159</td>\n",
       "      <td>40767.0</td>\n",
       "      <td>443.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>30:8c:fb:2f:e4:b2</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89589</th>\n",
       "      <td>89590</td>\n",
       "      <td>16434.746159</td>\n",
       "      <td>156</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp:tls</td>\n",
       "      <td>52.87.241.159</td>\n",
       "      <td>40767.0</td>\n",
       "      <td>443.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>30:8c:fb:2f:e4:b2</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89591</th>\n",
       "      <td>89592</td>\n",
       "      <td>16435.774144</td>\n",
       "      <td>156</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp:tls</td>\n",
       "      <td>52.87.241.159</td>\n",
       "      <td>40767.0</td>\n",
       "      <td>443.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>30:8c:fb:2f:e4:b2</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89599</th>\n",
       "      <td>89600</td>\n",
       "      <td>16436.808227</td>\n",
       "      <td>156</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp:tls</td>\n",
       "      <td>52.87.241.159</td>\n",
       "      <td>40767.0</td>\n",
       "      <td>443.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>30:8c:fb:2f:e4:b2</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89601</th>\n",
       "      <td>89602</td>\n",
       "      <td>16436.870410</td>\n",
       "      <td>42</td>\n",
       "      <td>NaN</td>\n",
       "      <td>eth:ethertype:arp</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>30:8c:fb:2f:e4:b2</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89605</th>\n",
       "      <td>89606</td>\n",
       "      <td>16437.715172</td>\n",
       "      <td>156</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp:tls</td>\n",
       "      <td>52.87.241.159</td>\n",
       "      <td>40767.0</td>\n",
       "      <td>443.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>30:8c:fb:2f:e4:b2</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10503 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       frame.number  frame.time_relative  frame.len ip.proto  \\\n",
       "32062         32063          5743.989610        156        6   \n",
       "32064         32065          5745.013440        156        6   \n",
       "32072         32073          5746.054957        156        6   \n",
       "32083         32084          5747.078354        156        6   \n",
       "32089         32090          5747.487942        156        6   \n",
       "...             ...                  ...        ...      ...   \n",
       "89589         89590         16434.746159        156        6   \n",
       "89591         89592         16435.774144        156        6   \n",
       "89599         89600         16436.808227        156        6   \n",
       "89601         89602         16436.870410         42      NaN   \n",
       "89605         89606         16437.715172        156        6   \n",
       "\n",
       "                frame.protocols         ip.dst  tcp.srcport  tcp.dstport  \\\n",
       "32062  eth:ethertype:ip:tcp:tls  52.87.241.159      40767.0        443.0   \n",
       "32064  eth:ethertype:ip:tcp:tls  52.87.241.159      40767.0        443.0   \n",
       "32072  eth:ethertype:ip:tcp:tls  52.87.241.159      40767.0        443.0   \n",
       "32083  eth:ethertype:ip:tcp:tls  52.87.241.159      40767.0        443.0   \n",
       "32089  eth:ethertype:ip:tcp:tls  52.87.241.159      40767.0        443.0   \n",
       "...                         ...            ...          ...          ...   \n",
       "89589  eth:ethertype:ip:tcp:tls  52.87.241.159      40767.0        443.0   \n",
       "89591  eth:ethertype:ip:tcp:tls  52.87.241.159      40767.0        443.0   \n",
       "89599  eth:ethertype:ip:tcp:tls  52.87.241.159      40767.0        443.0   \n",
       "89601         eth:ethertype:arp            NaN          NaN          NaN   \n",
       "89605  eth:ethertype:ip:tcp:tls  52.87.241.159      40767.0        443.0   \n",
       "\n",
       "       udp.srcport  udp.dstport ip.dsfield.dscp            eth.src  \\\n",
       "32062          NaN          NaN               0  30:8c:fb:2f:e4:b2   \n",
       "32064          NaN          NaN               0  30:8c:fb:2f:e4:b2   \n",
       "32072          NaN          NaN               0  30:8c:fb:2f:e4:b2   \n",
       "32083          NaN          NaN               0  30:8c:fb:2f:e4:b2   \n",
       "32089          NaN          NaN               0  30:8c:fb:2f:e4:b2   \n",
       "...            ...          ...             ...                ...   \n",
       "89589          NaN          NaN               0  30:8c:fb:2f:e4:b2   \n",
       "89591          NaN          NaN               0  30:8c:fb:2f:e4:b2   \n",
       "89599          NaN          NaN               0  30:8c:fb:2f:e4:b2   \n",
       "89601          NaN          NaN             NaN  30:8c:fb:2f:e4:b2   \n",
       "89605          NaN          NaN               0  30:8c:fb:2f:e4:b2   \n",
       "\n",
       "                 eth.dst  \n",
       "32062  14:cc:20:51:33:ea  \n",
       "32064  14:cc:20:51:33:ea  \n",
       "32072  14:cc:20:51:33:ea  \n",
       "32083  14:cc:20:51:33:ea  \n",
       "32089  14:cc:20:51:33:ea  \n",
       "...                  ...  \n",
       "89589  14:cc:20:51:33:ea  \n",
       "89591  14:cc:20:51:33:ea  \n",
       "89599  14:cc:20:51:33:ea  \n",
       "89601  14:cc:20:51:33:ea  \n",
       "89605  14:cc:20:51:33:ea  \n",
       "\n",
       "[10503 rows x 13 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dropcam_10pc = pd.DataFrame()\n",
    "length = len(dropcam_10p.index)\n",
    "while(length>dropcam_10):\n",
    "    dropcam_10p = dropcam_10p.drop(dropcam_10p.index[length-1])\n",
    "    length = len(dropcam_10p.index)\n",
    "dropcam_10p"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "dropcam_np = dropcam_10p.index.to_numpy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<bound method IndexOpsMixin.to_numpy of Int64Index([32062, 32064, 32072, 32083, 32089, 32091, 32093, 32114, 32139,\n",
       "            32141,\n",
       "            ...\n",
       "            89562, 89573, 89579, 89583, 89585, 89589, 89591, 89599, 89601,\n",
       "            89605],\n",
       "           dtype='int64', length=10503)>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dropcam_np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "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>frame.number</th>\n",
       "      <th>frame.time_relative</th>\n",
       "      <th>frame.len</th>\n",
       "      <th>ip.proto</th>\n",
       "      <th>frame.protocols</th>\n",
       "      <th>ip.dst</th>\n",
       "      <th>tcp.srcport</th>\n",
       "      <th>tcp.dstport</th>\n",
       "      <th>udp.srcport</th>\n",
       "      <th>udp.dstport</th>\n",
       "      <th>ip.dsfield.dscp</th>\n",
       "      <th>eth.src</th>\n",
       "      <th>eth.dst</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>32062</th>\n",
       "      <td>32063</td>\n",
       "      <td>5743.989610</td>\n",
       "      <td>79</td>\n",
       "      <td>17</td>\n",
       "      <td>eth:ethertype:ip:udp:dns</td>\n",
       "      <td>192.168.1.1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>33486.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>0</td>\n",
       "      <td>30:8c:fb:2f:e4:b2</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32064</th>\n",
       "      <td>32065</td>\n",
       "      <td>5745.013440</td>\n",
       "      <td>79</td>\n",
       "      <td>17</td>\n",
       "      <td>eth:ethertype:ip:udp:dns</td>\n",
       "      <td>192.168.1.1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>33486.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>0</td>\n",
       "      <td>30:8c:fb:2f:e4:b2</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32072</th>\n",
       "      <td>32073</td>\n",
       "      <td>5746.054957</td>\n",
       "      <td>79</td>\n",
       "      <td>17</td>\n",
       "      <td>eth:ethertype:ip:udp:dns</td>\n",
       "      <td>8.8.8.8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>33486.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>0</td>\n",
       "      <td>30:8c:fb:2f:e4:b2</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32083</th>\n",
       "      <td>32084</td>\n",
       "      <td>5747.078354</td>\n",
       "      <td>79</td>\n",
       "      <td>17</td>\n",
       "      <td>eth:ethertype:ip:udp:dns</td>\n",
       "      <td>8.8.8.8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>33486.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>0</td>\n",
       "      <td>30:8c:fb:2f:e4:b2</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32089</th>\n",
       "      <td>32090</td>\n",
       "      <td>5747.487942</td>\n",
       "      <td>79</td>\n",
       "      <td>17</td>\n",
       "      <td>eth:ethertype:ip:udp:dns</td>\n",
       "      <td>8.8.8.8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>33486.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>0</td>\n",
       "      <td>30:8c:fb:2f:e4:b2</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89589</th>\n",
       "      <td>89590</td>\n",
       "      <td>16434.746159</td>\n",
       "      <td>66</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp:tls</td>\n",
       "      <td>158.69.38.240</td>\n",
       "      <td>45546.0</td>\n",
       "      <td>443.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>30:8c:fb:2f:e4:b2</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89591</th>\n",
       "      <td>89592</td>\n",
       "      <td>16435.774144</td>\n",
       "      <td>66</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp:tls</td>\n",
       "      <td>158.69.38.240</td>\n",
       "      <td>45546.0</td>\n",
       "      <td>443.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>30:8c:fb:2f:e4:b2</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89599</th>\n",
       "      <td>89600</td>\n",
       "      <td>16436.808227</td>\n",
       "      <td>66</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp:tls</td>\n",
       "      <td>158.69.38.240</td>\n",
       "      <td>45547.0</td>\n",
       "      <td>443.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>30:8c:fb:2f:e4:b2</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89601</th>\n",
       "      <td>89602</td>\n",
       "      <td>16436.870410</td>\n",
       "      <td>66</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp:tls</td>\n",
       "      <td>158.69.38.240</td>\n",
       "      <td>45546.0</td>\n",
       "      <td>443.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>30:8c:fb:2f:e4:b2</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89605</th>\n",
       "      <td>89606</td>\n",
       "      <td>16437.715172</td>\n",
       "      <td>66</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp:tls</td>\n",
       "      <td>158.69.38.240</td>\n",
       "      <td>45547.0</td>\n",
       "      <td>443.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>30:8c:fb:2f:e4:b2</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10503 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       frame.number  frame.time_relative  frame.len ip.proto  \\\n",
       "32062         32063          5743.989610         79       17   \n",
       "32064         32065          5745.013440         79       17   \n",
       "32072         32073          5746.054957         79       17   \n",
       "32083         32084          5747.078354         79       17   \n",
       "32089         32090          5747.487942         79       17   \n",
       "...             ...                  ...        ...      ...   \n",
       "89589         89590         16434.746159         66        6   \n",
       "89591         89592         16435.774144         66        6   \n",
       "89599         89600         16436.808227         66        6   \n",
       "89601         89602         16436.870410         66        6   \n",
       "89605         89606         16437.715172         66        6   \n",
       "\n",
       "                frame.protocols         ip.dst  tcp.srcport  tcp.dstport  \\\n",
       "32062  eth:ethertype:ip:udp:dns    192.168.1.1          NaN          NaN   \n",
       "32064  eth:ethertype:ip:udp:dns    192.168.1.1          NaN          NaN   \n",
       "32072  eth:ethertype:ip:udp:dns        8.8.8.8          NaN          NaN   \n",
       "32083  eth:ethertype:ip:udp:dns        8.8.8.8          NaN          NaN   \n",
       "32089  eth:ethertype:ip:udp:dns        8.8.8.8          NaN          NaN   \n",
       "...                         ...            ...          ...          ...   \n",
       "89589  eth:ethertype:ip:tcp:tls  158.69.38.240      45546.0        443.0   \n",
       "89591  eth:ethertype:ip:tcp:tls  158.69.38.240      45546.0        443.0   \n",
       "89599  eth:ethertype:ip:tcp:tls  158.69.38.240      45547.0        443.0   \n",
       "89601  eth:ethertype:ip:tcp:tls  158.69.38.240      45546.0        443.0   \n",
       "89605  eth:ethertype:ip:tcp:tls  158.69.38.240      45547.0        443.0   \n",
       "\n",
       "       udp.srcport  udp.dstport ip.dsfield.dscp            eth.src  \\\n",
       "32062      33486.0         53.0               0  30:8c:fb:2f:e4:b2   \n",
       "32064      33486.0         53.0               0  30:8c:fb:2f:e4:b2   \n",
       "32072      33486.0         53.0               0  30:8c:fb:2f:e4:b2   \n",
       "32083      33486.0         53.0               0  30:8c:fb:2f:e4:b2   \n",
       "32089      33486.0         53.0               0  30:8c:fb:2f:e4:b2   \n",
       "...            ...          ...             ...                ...   \n",
       "89589          NaN          NaN               0  30:8c:fb:2f:e4:b2   \n",
       "89591          NaN          NaN               0  30:8c:fb:2f:e4:b2   \n",
       "89599          NaN          NaN               0  30:8c:fb:2f:e4:b2   \n",
       "89601          NaN          NaN               0  30:8c:fb:2f:e4:b2   \n",
       "89605          NaN          NaN               0  30:8c:fb:2f:e4:b2   \n",
       "\n",
       "                 eth.dst  \n",
       "32062  14:cc:20:51:33:ea  \n",
       "32064  14:cc:20:51:33:ea  \n",
       "32072  14:cc:20:51:33:ea  \n",
       "32083  14:cc:20:51:33:ea  \n",
       "32089  14:cc:20:51:33:ea  \n",
       "...                  ...  \n",
       "89589  14:cc:20:51:33:ea  \n",
       "89591  14:cc:20:51:33:ea  \n",
       "89599  14:cc:20:51:33:ea  \n",
       "89601  14:cc:20:51:33:ea  \n",
       "89605  14:cc:20:51:33:ea  \n",
       "\n",
       "[10503 rows x 13 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#SIMULATION\n",
    "import random\n",
    "\n",
    "i = 0      # DNS ip = 192.168.1.1, des port 53, src port 33486, dscp 0, len 79, \n",
    "while(i<dropcam_10):\n",
    "    while(i<2):\n",
    "        dropcam_10p.loc[dropcam_10p.iloc[i].name,['frame.len','ip.proto','frame.protocols','ip.dst','tcp.srcport','tcp.dstport','udp.srcport','udp.dstport','ip.dsfield.dscp']] = 79, 17, 'eth:ethertype:ip:udp:dns', '192.168.1.1', np.NaN, np.NaN, 33486, 53, 0\n",
    "        i+=1\n",
    "    while(i<6):\n",
    "        dropcam_10p.loc[dropcam_10p.iloc[i].name,['frame.len','ip.proto','frame.protocols','ip.dst','tcp.srcport','tcp.dstport','udp.srcport','udp.dstport','ip.dsfield.dscp']] = 79, 17, 'eth:ethertype:ip:udp:dns', '8.8.8.8', np.NaN, np.NaN, 33486, 53, 0\n",
    "        i+=1\n",
    "    rn = random.randint(1,5)           #random integer\n",
    "    if (rn!=1):\n",
    "        dropcam_10p.loc[dropcam_10p.iloc[i].name,['frame.len','ip.proto','frame.protocols','ip.dst','tcp.srcport','tcp.dstport','udp.srcport','udp.dstport','ip.dsfield.dscp']] = 66, 6, 'eth:ethertype:ip:tcp:tls', '158.69.38.240', random.choice([45546,45547,45548]), 443, np.NaN, np.NaN, 0\n",
    "    else:\n",
    "        dropcam_10p.loc[dropcam_10p.iloc[i].name,['frame.len','ip.proto','frame.protocols','ip.dst','tcp.srcport','tcp.dstport','udp.srcport','udp.dstport','ip.dsfield.dscp']] = random.choice([156, 248, 172, 312]), 6,'192.168.1.106', '158.69.38.240', random.choice([45546,45547,45548]), 443, np.NaN, np.NaN, 0\n",
    "    i+=1\n",
    "    \n",
    "dropcam_10p"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "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>frame.number</th>\n",
       "      <th>frame.time_relative</th>\n",
       "      <th>frame.len</th>\n",
       "      <th>ip.proto</th>\n",
       "      <th>frame.protocols</th>\n",
       "      <th>ip.dst</th>\n",
       "      <th>tcp.srcport</th>\n",
       "      <th>tcp.dstport</th>\n",
       "      <th>udp.srcport</th>\n",
       "      <th>udp.dstport</th>\n",
       "      <th>ip.dsfield.dscp</th>\n",
       "      <th>eth.src</th>\n",
       "      <th>eth.dst</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>156</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp:tls</td>\n",
       "      <td>52.87.241.159</td>\n",
       "      <td>40767.0</td>\n",
       "      <td>443.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>30:8c:fb:2f:e4:b2</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>0.220575</td>\n",
       "      <td>66</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp</td>\n",
       "      <td>192.168.1.106</td>\n",
       "      <td>443.0</td>\n",
       "      <td>40767.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "      <td>30:8c:fb:2f:e4:b2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>0.537609</td>\n",
       "      <td>284</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp:tls</td>\n",
       "      <td>52.87.241.159</td>\n",
       "      <td>40767.0</td>\n",
       "      <td>443.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>30:8c:fb:2f:e4:b2</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>2.075699</td>\n",
       "      <td>156</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp:tls</td>\n",
       "      <td>52.87.241.159</td>\n",
       "      <td>40767.0</td>\n",
       "      <td>443.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>30:8c:fb:2f:e4:b2</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>2.186605</td>\n",
       "      <td>90</td>\n",
       "      <td>17</td>\n",
       "      <td>eth:ethertype:ip:udp:ntp</td>\n",
       "      <td>192.168.1.196</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>123.0</td>\n",
       "      <td>4967.0</td>\n",
       "      <td>6</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "      <td>d0:52:a8:00:67:5e</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32060</th>\n",
       "      <td>32061</td>\n",
       "      <td>5742.760900</td>\n",
       "      <td>60</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp:data</td>\n",
       "      <td>54.210.202.2</td>\n",
       "      <td>2173.0</td>\n",
       "      <td>443.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>d0:52:a8:00:67:5e</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32061</th>\n",
       "      <td>32062</td>\n",
       "      <td>5742.977143</td>\n",
       "      <td>54</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp</td>\n",
       "      <td>192.168.1.196</td>\n",
       "      <td>443.0</td>\n",
       "      <td>2173.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "      <td>d0:52:a8:00:67:5e</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32062</th>\n",
       "      <td>32063</td>\n",
       "      <td>5743.989610</td>\n",
       "      <td>79</td>\n",
       "      <td>17</td>\n",
       "      <td>eth:ethertype:ip:udp:dns</td>\n",
       "      <td>192.168.1.1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>33486.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>0</td>\n",
       "      <td>30:8c:fb:2f:e4:b2</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32063</th>\n",
       "      <td>32064</td>\n",
       "      <td>5744.194788</td>\n",
       "      <td>66</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp</td>\n",
       "      <td>192.168.1.106</td>\n",
       "      <td>443.0</td>\n",
       "      <td>40767.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "      <td>30:8c:fb:2f:e4:b2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32064</th>\n",
       "      <td>32065</td>\n",
       "      <td>5745.013440</td>\n",
       "      <td>79</td>\n",
       "      <td>17</td>\n",
       "      <td>eth:ethertype:ip:udp:dns</td>\n",
       "      <td>192.168.1.1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>33486.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>0</td>\n",
       "      <td>30:8c:fb:2f:e4:b2</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>32065 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       frame.number  frame.time_relative  frame.len ip.proto  \\\n",
       "0                 1             0.000000        156        6   \n",
       "1                 2             0.220575         66        6   \n",
       "2                 3             0.537609        284        6   \n",
       "3                 4             2.075699        156        6   \n",
       "4                 5             2.186605         90       17   \n",
       "...             ...                  ...        ...      ...   \n",
       "32060         32061          5742.760900         60        6   \n",
       "32061         32062          5742.977143         54        6   \n",
       "32062         32063          5743.989610         79       17   \n",
       "32063         32064          5744.194788         66        6   \n",
       "32064         32065          5745.013440         79       17   \n",
       "\n",
       "                 frame.protocols         ip.dst  tcp.srcport  tcp.dstport  \\\n",
       "0       eth:ethertype:ip:tcp:tls  52.87.241.159      40767.0        443.0   \n",
       "1           eth:ethertype:ip:tcp  192.168.1.106        443.0      40767.0   \n",
       "2       eth:ethertype:ip:tcp:tls  52.87.241.159      40767.0        443.0   \n",
       "3       eth:ethertype:ip:tcp:tls  52.87.241.159      40767.0        443.0   \n",
       "4       eth:ethertype:ip:udp:ntp  192.168.1.196          NaN          NaN   \n",
       "...                          ...            ...          ...          ...   \n",
       "32060  eth:ethertype:ip:tcp:data   54.210.202.2       2173.0        443.0   \n",
       "32061       eth:ethertype:ip:tcp  192.168.1.196        443.0       2173.0   \n",
       "32062   eth:ethertype:ip:udp:dns    192.168.1.1          NaN          NaN   \n",
       "32063       eth:ethertype:ip:tcp  192.168.1.106        443.0      40767.0   \n",
       "32064   eth:ethertype:ip:udp:dns    192.168.1.1          NaN          NaN   \n",
       "\n",
       "       udp.srcport  udp.dstport ip.dsfield.dscp            eth.src  \\\n",
       "0              NaN          NaN               0  30:8c:fb:2f:e4:b2   \n",
       "1              NaN          NaN               0  14:cc:20:51:33:ea   \n",
       "2              NaN          NaN               0  30:8c:fb:2f:e4:b2   \n",
       "3              NaN          NaN               0  30:8c:fb:2f:e4:b2   \n",
       "4            123.0       4967.0               6  14:cc:20:51:33:ea   \n",
       "...            ...          ...             ...                ...   \n",
       "32060          NaN          NaN               0  d0:52:a8:00:67:5e   \n",
       "32061          NaN          NaN               0  14:cc:20:51:33:ea   \n",
       "32062      33486.0         53.0               0  30:8c:fb:2f:e4:b2   \n",
       "32063          NaN          NaN               0  14:cc:20:51:33:ea   \n",
       "32064      33486.0         53.0               0  30:8c:fb:2f:e4:b2   \n",
       "\n",
       "                 eth.dst  \n",
       "0      14:cc:20:51:33:ea  \n",
       "1      30:8c:fb:2f:e4:b2  \n",
       "2      14:cc:20:51:33:ea  \n",
       "3      14:cc:20:51:33:ea  \n",
       "4      d0:52:a8:00:67:5e  \n",
       "...                  ...  \n",
       "32060  14:cc:20:51:33:ea  \n",
       "32061  d0:52:a8:00:67:5e  \n",
       "32062  14:cc:20:51:33:ea  \n",
       "32063  30:8c:fb:2f:e4:b2  \n",
       "32064  14:cc:20:51:33:ea  \n",
       "\n",
       "[32065 rows x 13 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "after_dropcam = dropcam_10p\n",
    "\n",
    "# inserting changed row back to overall dataframe\n",
    "\n",
    "# test = df\n",
    "i = 0\n",
    "while (i<dropcam_10):\n",
    "    test.loc[after_dropcam.iloc[i].name] = after_dropcam.iloc[i]\n",
    "    i+=1\n",
    "test.head(32065)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [],
   "source": [
    "# write to CSV\n",
    "# test.to_csv('simulated_csv.csv',index=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "670\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-18-a5c42d2be00c>:9: UserWarning: Boolean Series key will be reindexed to match DataFrame index.\n",
      "  printer_10p = df[(printer_start):][df['eth.src']=='70:5a:0f:e4:9b:c0']\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "       frame.number  frame.time_relative  frame.len ip.proto  \\\n",
      "32239         32240          5773.397398        140        6   \n",
      "32271         32272          5778.599311         60      NaN   \n",
      "32348         32349          5799.326245         46        2   \n",
      "32360         32361          5802.142503         46        2   \n",
      "32540         32541          5833.705364         86      NaN   \n",
      "...             ...                  ...        ...      ...   \n",
      "78957         78958         14465.656859        140        6   \n",
      "78982         78983         14470.859250         60      NaN   \n",
      "79052         79053         14484.918634         86      NaN   \n",
      "79054         79055         14485.420340         86      NaN   \n",
      "79055         79056         14485.651749         86      NaN   \n",
      "\n",
      "                              frame.protocols           ip.dst  tcp.srcport  \\\n",
      "32239                    eth:ethertype:ip:tcp     15.72.162.53      21787.0   \n",
      "32271                       eth:ethertype:arp              NaN          NaN   \n",
      "32348              eth:ethertype:ip:igmp:igmp  239.255.255.250          NaN   \n",
      "32360              eth:ethertype:ip:igmp:igmp       224.0.1.60          NaN   \n",
      "32540  eth:ethertype:ipv6:ipv6.hopopts:icmpv6              NaN          NaN   \n",
      "...                                       ...              ...          ...   \n",
      "78957                    eth:ethertype:ip:tcp     15.72.162.53      21787.0   \n",
      "78982                       eth:ethertype:arp              NaN          NaN   \n",
      "79052  eth:ethertype:ipv6:ipv6.hopopts:icmpv6              NaN          NaN   \n",
      "79054  eth:ethertype:ipv6:ipv6.hopopts:icmpv6              NaN          NaN   \n",
      "79055  eth:ethertype:ipv6:ipv6.hopopts:icmpv6              NaN          NaN   \n",
      "\n",
      "       tcp.dstport  udp.srcport  udp.dstport ip.dsfield.dscp  \\\n",
      "32239       5222.0          NaN          NaN               0   \n",
      "32271          NaN          NaN          NaN             NaN   \n",
      "32348          NaN          NaN          NaN               0   \n",
      "32360          NaN          NaN          NaN               0   \n",
      "32540          NaN          NaN          NaN             NaN   \n",
      "...            ...          ...          ...             ...   \n",
      "78957       5222.0          NaN          NaN               0   \n",
      "78982          NaN          NaN          NaN             NaN   \n",
      "79052          NaN          NaN          NaN             NaN   \n",
      "79054          NaN          NaN          NaN             NaN   \n",
      "79055          NaN          NaN          NaN             NaN   \n",
      "\n",
      "                 eth.src            eth.dst  \n",
      "32239  70:5a:0f:e4:9b:c0  14:cc:20:51:33:ea  \n",
      "32271  70:5a:0f:e4:9b:c0  14:cc:20:51:33:ea  \n",
      "32348  70:5a:0f:e4:9b:c0  01:00:5e:7f:ff:fa  \n",
      "32360  70:5a:0f:e4:9b:c0  01:00:5e:00:01:3c  \n",
      "32540  70:5a:0f:e4:9b:c0  33:33:ff:00:0e:e2  \n",
      "...                  ...                ...  \n",
      "78957  70:5a:0f:e4:9b:c0  14:cc:20:51:33:ea  \n",
      "78982  70:5a:0f:e4:9b:c0  14:cc:20:51:33:ea  \n",
      "79052  70:5a:0f:e4:9b:c0  33:33:00:01:00:03  \n",
      "79054  70:5a:0f:e4:9b:c0  33:33:ff:00:0e:e2  \n",
      "79055  70:5a:0f:e4:9b:c0  33:33:ff:e4:9b:c0  \n",
      "\n",
      "[670 rows x 13 columns]\n",
      "       frame.number  frame.time_relative  frame.len ip.proto  \\\n",
      "32239         32240          5773.397398         84       17   \n",
      "32271         32272          5778.599311         84       17   \n",
      "32348         32349          5799.326245         84       17   \n",
      "32360         32361          5802.142503         84       17   \n",
      "32540         32541          5833.705364         84       17   \n",
      "...             ...                  ...        ...      ...   \n",
      "78957         78958         14465.656859        356        6   \n",
      "78982         78983         14470.859250        140        6   \n",
      "79052         79053         14484.918634         97        6   \n",
      "79054         79055         14485.420340        140        6   \n",
      "79055         79056         14485.651749        246        6   \n",
      "\n",
      "                frame.protocols         ip.dst  tcp.srcport  tcp.dstport  \\\n",
      "32239  eth:ethertype:ip:udp:dns    192.168.1.1          NaN          NaN   \n",
      "32271  eth:ethertype:ip:udp:dns    192.168.1.1          NaN          NaN   \n",
      "32348  eth:ethertype:ip:udp:dns        8.8.8.8          NaN          NaN   \n",
      "32360  eth:ethertype:ip:udp:dns        8.8.8.8          NaN          NaN   \n",
      "32540  eth:ethertype:ip:udp:dns        8.8.8.8          NaN          NaN   \n",
      "...                         ...            ...          ...          ...   \n",
      "78957      eth:ethertype:ip:tcp  62.210.177.42      44766.0        443.0   \n",
      "78982      eth:ethertype:ip:tcp  62.210.177.42      44767.0        443.0   \n",
      "79052      eth:ethertype:ip:tcp  62.210.177.42      44765.0        443.0   \n",
      "79054      eth:ethertype:ip:tcp  62.210.177.42      44765.0        443.0   \n",
      "79055      eth:ethertype:ip:tcp  62.210.177.42      44767.0        443.0   \n",
      "\n",
      "       udp.srcport  udp.dstport ip.dsfield.dscp            eth.src  \\\n",
      "32239      44675.0         53.0               0  70:5a:0f:e4:9b:c0   \n",
      "32271      44675.0         53.0               0  70:5a:0f:e4:9b:c0   \n",
      "32348      44675.0         53.0               0  70:5a:0f:e4:9b:c0   \n",
      "32360      44675.0         53.0               0  70:5a:0f:e4:9b:c0   \n",
      "32540      44675.0         53.0               0  70:5a:0f:e4:9b:c0   \n",
      "...            ...          ...             ...                ...   \n",
      "78957          NaN          NaN               0  70:5a:0f:e4:9b:c0   \n",
      "78982          NaN          NaN               0  70:5a:0f:e4:9b:c0   \n",
      "79052          NaN          NaN               0  70:5a:0f:e4:9b:c0   \n",
      "79054          NaN          NaN               0  70:5a:0f:e4:9b:c0   \n",
      "79055          NaN          NaN               0  70:5a:0f:e4:9b:c0   \n",
      "\n",
      "                 eth.dst  \n",
      "32239  14:cc:20:51:33:ea  \n",
      "32271  14:cc:20:51:33:ea  \n",
      "32348  01:00:5e:7f:ff:fa  \n",
      "32360  01:00:5e:00:01:3c  \n",
      "32540  33:33:ff:00:0e:e2  \n",
      "...                  ...  \n",
      "78957  14:cc:20:51:33:ea  \n",
      "78982  14:cc:20:51:33:ea  \n",
      "79052  33:33:00:01:00:03  \n",
      "79054  33:33:ff:00:0e:e2  \n",
      "79055  33:33:ff:e4:9b:c0  \n",
      "\n",
      "[670 rows x 13 columns]\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>frame.number</th>\n",
       "      <th>frame.time_relative</th>\n",
       "      <th>frame.len</th>\n",
       "      <th>ip.proto</th>\n",
       "      <th>frame.protocols</th>\n",
       "      <th>ip.dst</th>\n",
       "      <th>tcp.srcport</th>\n",
       "      <th>tcp.dstport</th>\n",
       "      <th>udp.srcport</th>\n",
       "      <th>udp.dstport</th>\n",
       "      <th>ip.dsfield.dscp</th>\n",
       "      <th>eth.src</th>\n",
       "      <th>eth.dst</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>156</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp:tls</td>\n",
       "      <td>52.87.241.159</td>\n",
       "      <td>40767.0</td>\n",
       "      <td>443.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>30:8c:fb:2f:e4:b2</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>0.220575</td>\n",
       "      <td>66</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp</td>\n",
       "      <td>192.168.1.106</td>\n",
       "      <td>443.0</td>\n",
       "      <td>40767.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "      <td>30:8c:fb:2f:e4:b2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>0.537609</td>\n",
       "      <td>284</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp:tls</td>\n",
       "      <td>52.87.241.159</td>\n",
       "      <td>40767.0</td>\n",
       "      <td>443.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>30:8c:fb:2f:e4:b2</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>2.075699</td>\n",
       "      <td>156</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp:tls</td>\n",
       "      <td>52.87.241.159</td>\n",
       "      <td>40767.0</td>\n",
       "      <td>443.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>30:8c:fb:2f:e4:b2</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>2.186605</td>\n",
       "      <td>90</td>\n",
       "      <td>17</td>\n",
       "      <td>eth:ethertype:ip:udp:ntp</td>\n",
       "      <td>192.168.1.196</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>123.0</td>\n",
       "      <td>4967.0</td>\n",
       "      <td>6</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "      <td>d0:52:a8:00:67:5e</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79050</th>\n",
       "      <td>79051</td>\n",
       "      <td>14484.218542</td>\n",
       "      <td>66</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp</td>\n",
       "      <td>52.8.89.254</td>\n",
       "      <td>35792.0</td>\n",
       "      <td>5222.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>00:16:6c:ab:6b:88</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79051</th>\n",
       "      <td>79052</td>\n",
       "      <td>14484.519614</td>\n",
       "      <td>86</td>\n",
       "      <td>NaN</td>\n",
       "      <td>eth:ethertype:ipv6:ipv6.hopopts:icmpv6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>00:16:6c:ab:6b:88</td>\n",
       "      <td>33:33:00:00:00:fb</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79052</th>\n",
       "      <td>79053</td>\n",
       "      <td>14484.918634</td>\n",
       "      <td>97</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp</td>\n",
       "      <td>62.210.177.42</td>\n",
       "      <td>44765.0</td>\n",
       "      <td>443.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>70:5a:0f:e4:9b:c0</td>\n",
       "      <td>33:33:00:01:00:03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79053</th>\n",
       "      <td>79054</td>\n",
       "      <td>14484.991996</td>\n",
       "      <td>86</td>\n",
       "      <td>NaN</td>\n",
       "      <td>eth:ethertype:ipv6:ipv6.hopopts:icmpv6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>e0:76:d0:33:bb:85</td>\n",
       "      <td>33:33:ff:33:bb:85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79054</th>\n",
       "      <td>79055</td>\n",
       "      <td>14485.420340</td>\n",
       "      <td>140</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp</td>\n",
       "      <td>62.210.177.42</td>\n",
       "      <td>44765.0</td>\n",
       "      <td>443.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>70:5a:0f:e4:9b:c0</td>\n",
       "      <td>33:33:ff:00:0e:e2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>79055 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       frame.number  frame.time_relative  frame.len ip.proto  \\\n",
       "0                 1             0.000000        156        6   \n",
       "1                 2             0.220575         66        6   \n",
       "2                 3             0.537609        284        6   \n",
       "3                 4             2.075699        156        6   \n",
       "4                 5             2.186605         90       17   \n",
       "...             ...                  ...        ...      ...   \n",
       "79050         79051         14484.218542         66        6   \n",
       "79051         79052         14484.519614         86      NaN   \n",
       "79052         79053         14484.918634         97        6   \n",
       "79053         79054         14484.991996         86      NaN   \n",
       "79054         79055         14485.420340        140        6   \n",
       "\n",
       "                              frame.protocols         ip.dst  tcp.srcport  \\\n",
       "0                    eth:ethertype:ip:tcp:tls  52.87.241.159      40767.0   \n",
       "1                        eth:ethertype:ip:tcp  192.168.1.106        443.0   \n",
       "2                    eth:ethertype:ip:tcp:tls  52.87.241.159      40767.0   \n",
       "3                    eth:ethertype:ip:tcp:tls  52.87.241.159      40767.0   \n",
       "4                    eth:ethertype:ip:udp:ntp  192.168.1.196          NaN   \n",
       "...                                       ...            ...          ...   \n",
       "79050                    eth:ethertype:ip:tcp    52.8.89.254      35792.0   \n",
       "79051  eth:ethertype:ipv6:ipv6.hopopts:icmpv6            NaN          NaN   \n",
       "79052                    eth:ethertype:ip:tcp  62.210.177.42      44765.0   \n",
       "79053  eth:ethertype:ipv6:ipv6.hopopts:icmpv6            NaN          NaN   \n",
       "79054                    eth:ethertype:ip:tcp  62.210.177.42      44765.0   \n",
       "\n",
       "       tcp.dstport  udp.srcport  udp.dstport ip.dsfield.dscp  \\\n",
       "0            443.0          NaN          NaN               0   \n",
       "1          40767.0          NaN          NaN               0   \n",
       "2            443.0          NaN          NaN               0   \n",
       "3            443.0          NaN          NaN               0   \n",
       "4              NaN        123.0       4967.0               6   \n",
       "...            ...          ...          ...             ...   \n",
       "79050       5222.0          NaN          NaN               0   \n",
       "79051          NaN          NaN          NaN             NaN   \n",
       "79052        443.0          NaN          NaN               0   \n",
       "79053          NaN          NaN          NaN             NaN   \n",
       "79054        443.0          NaN          NaN               0   \n",
       "\n",
       "                 eth.src            eth.dst  \n",
       "0      30:8c:fb:2f:e4:b2  14:cc:20:51:33:ea  \n",
       "1      14:cc:20:51:33:ea  30:8c:fb:2f:e4:b2  \n",
       "2      30:8c:fb:2f:e4:b2  14:cc:20:51:33:ea  \n",
       "3      30:8c:fb:2f:e4:b2  14:cc:20:51:33:ea  \n",
       "4      14:cc:20:51:33:ea  d0:52:a8:00:67:5e  \n",
       "...                  ...                ...  \n",
       "79050  00:16:6c:ab:6b:88  14:cc:20:51:33:ea  \n",
       "79051  00:16:6c:ab:6b:88  33:33:00:00:00:fb  \n",
       "79052  70:5a:0f:e4:9b:c0  33:33:00:01:00:03  \n",
       "79053  e0:76:d0:33:bb:85  33:33:ff:33:bb:85  \n",
       "79054  70:5a:0f:e4:9b:c0  33:33:ff:00:0e:e2  \n",
       "\n",
       "[79055 rows x 13 columns]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Selecting 1 of packets randomly of amazon HP Printer: 70:5a:0f:e4:9b:c0\n",
    "printer = df[df['eth.src']=='70:5a:0f:e4:9b:c0'].sample(n=1,random_state=1)['frame.number']\n",
    "printer_start = echo.iloc[0]-1\n",
    "\n",
    "printer_total = len(df[df['eth.src']=='70:5a:0f:e4:9b:c0'])\n",
    "printer_10 = int(round(printer_total*.1))\n",
    "print(printer_10)\n",
    "\n",
    "printer_10p = df[(printer_start):][df['eth.src']=='70:5a:0f:e4:9b:c0']\n",
    "\n",
    "# printer\n",
    "printer_10pc = pd.DataFrame()\n",
    "length = len(printer_10p.index)\n",
    "while(length>printer_10):\n",
    "    printer_10p = printer_10p.drop(printer_10p.index[length-1])\n",
    "    length = len(printer_10p.index)\n",
    "print(printer_10p)\n",
    "\n",
    "\n",
    "#SIMULATION\n",
    "import random\n",
    "\n",
    "i = 0      # DNS ip = 192.168.1.1, des port 53, src port 58776, dscp 0, len 98\n",
    "while(i<printer_10):\n",
    "    while(i<2):\n",
    "        printer_10p.loc[printer_10p.iloc[i].name,['frame.len','ip.proto','frame.protocols','ip.dst','tcp.srcport','tcp.dstport','udp.srcport','udp.dstport','ip.dsfield.dscp']] = 84, 17, 'eth:ethertype:ip:udp:dns', '192.168.1.1', np.NaN, np.NaN, 44675, 53, 0\n",
    "        i+=1\n",
    "    while(i<6):\n",
    "        printer_10p.loc[printer_10p.iloc[i].name,['frame.len','ip.proto','frame.protocols','ip.dst','tcp.srcport','tcp.dstport','udp.srcport','udp.dstport','ip.dsfield.dscp']] = 84, 17, 'eth:ethertype:ip:udp:dns', '8.8.8.8', np.NaN, np.NaN, 44675, 53, 0\n",
    "        i+=1\n",
    "    rn = random.randint(1,5)           #random integer\n",
    "    if (rn==1):\n",
    "        printer_10p.loc[printer_10p.iloc[i].name,['frame.len','ip.proto','frame.protocols','ip.dst','tcp.srcport','tcp.dstport','udp.srcport','udp.dstport','ip.dsfield.dscp']] = random.choice([140,280,356]), 6, 'eth:ethertype:ip:tcp:tls','62.210.177.42', random.choice([44765,44766,44767]), 443, np.NaN, np.NaN, 0\n",
    "    else:\n",
    "        printer_10p.loc[printer_10p.iloc[i].name,['frame.len','ip.proto','frame.protocols','ip.dst','tcp.srcport','tcp.dstport','udp.srcport','udp.dstport','ip.dsfield.dscp']] = random.choice([66,97,140,280,356,246]), 6, 'eth:ethertype:ip:tcp','62.210.177.42', random.choice([44765,44766,44767]), 443, np.NaN, np.NaN, 0\n",
    "    i+=1\n",
    "    \n",
    "print(printer_10p)\n",
    "\n",
    "after_printer = printer_10p\n",
    "\n",
    "# inserting changed row back to overall dataframe\n",
    "\n",
    "# test = df\n",
    "i = 0\n",
    "while (i<printer_10):\n",
    "    test.loc[after_printer.iloc[i].name] = after_printer.iloc[i]\n",
    "    i+=1\n",
    "test.head(79055)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "printer_np = printer_10p.index.to_numpy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Int64Index([32239, 32271, 32348, 32360, 32540, 32543, 32547, 32563, 32664,\n",
      "            32694,\n",
      "            ...\n",
      "            89562, 89573, 89579, 89583, 89585, 89589, 89591, 89599, 89601,\n",
      "            89605],\n",
      "           dtype='int64', length=14289)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([32239, 32271, 32348, ..., 89599, 89601, 89605])"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# print(echo_10+dropcam_10+printer_10)\n",
    "index_array = printer_10p.index.append(echo_10p.index.append(dropcam_10p.index))\n",
    "print(index_array)\n",
    "index_array = np.array(index_array)\n",
    "# index_array = np.concatenate((index_array,echo_np))\n",
    "index_array"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "from numpy import savetxt\n",
    "savetxt('no_ipsrc_array_indices.txt',index_array)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "# write to CSV\n",
    "test.to_csv('no_ipsrc_simulated_csv.csv',index=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "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>frameNumber</th>\n",
       "      <th>timeRelative</th>\n",
       "      <th>frame.len</th>\n",
       "      <th>protocolNumber</th>\n",
       "      <th>protocolName</th>\n",
       "      <th>ipDst</th>\n",
       "      <th>srcPort</th>\n",
       "      <th>dstPort</th>\n",
       "      <th>ipDSCP</th>\n",
       "      <th>ethsrc</th>\n",
       "      <th>ethdst</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>156</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp:tls</td>\n",
       "      <td>52.87.241.159</td>\n",
       "      <td>40767.0</td>\n",
       "      <td>443.0</td>\n",
       "      <td>0</td>\n",
       "      <td>30:8c:fb:2f:e4:b2</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>0.220575</td>\n",
       "      <td>66</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp</td>\n",
       "      <td>192.168.1.106</td>\n",
       "      <td>443.0</td>\n",
       "      <td>40767.0</td>\n",
       "      <td>0</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "      <td>30:8c:fb:2f:e4:b2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>0.537609</td>\n",
       "      <td>284</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp:tls</td>\n",
       "      <td>52.87.241.159</td>\n",
       "      <td>40767.0</td>\n",
       "      <td>443.0</td>\n",
       "      <td>0</td>\n",
       "      <td>30:8c:fb:2f:e4:b2</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>2.075699</td>\n",
       "      <td>156</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp:tls</td>\n",
       "      <td>52.87.241.159</td>\n",
       "      <td>40767.0</td>\n",
       "      <td>443.0</td>\n",
       "      <td>0</td>\n",
       "      <td>30:8c:fb:2f:e4:b2</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>2.186605</td>\n",
       "      <td>90</td>\n",
       "      <td>17</td>\n",
       "      <td>eth:ethertype:ip:udp:ntp</td>\n",
       "      <td>192.168.1.196</td>\n",
       "      <td></td>\n",
       "      <td>4967.0</td>\n",
       "      <td>6</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "      <td>d0:52:a8:00:67:5e</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>527030</th>\n",
       "      <td>527031</td>\n",
       "      <td>86398.649904</td>\n",
       "      <td>42</td>\n",
       "      <td></td>\n",
       "      <td>eth:ethertype:arp</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>f4:f2:6d:93:51:f1</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>527031</th>\n",
       "      <td>527032</td>\n",
       "      <td>86398.698987</td>\n",
       "      <td>156</td>\n",
       "      <td>6.0</td>\n",
       "      <td>eth:ethertype:ip:tcp:tls</td>\n",
       "      <td>52.87.241.159</td>\n",
       "      <td>40767.0</td>\n",
       "      <td>443.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>30:8c:fb:2f:e4:b2</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>527032</th>\n",
       "      <td>527033</td>\n",
       "      <td>86398.904135</td>\n",
       "      <td>66</td>\n",
       "      <td>6.0</td>\n",
       "      <td>eth:ethertype:ip:tcp</td>\n",
       "      <td>192.168.1.106</td>\n",
       "      <td>443.0</td>\n",
       "      <td>40767.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "      <td>30:8c:fb:2f:e4:b2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>527033</th>\n",
       "      <td>527034</td>\n",
       "      <td>86399.490511</td>\n",
       "      <td>118</td>\n",
       "      <td>1.0</td>\n",
       "      <td>eth:ethertype:ip:icmp:data</td>\n",
       "      <td>192.168.1.1</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0.0</td>\n",
       "      <td>ec:1a:59:79:f4:89</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>527034</th>\n",
       "      <td>527035</td>\n",
       "      <td>86399.49063</td>\n",
       "      <td>118</td>\n",
       "      <td>1.0</td>\n",
       "      <td>eth:ethertype:ip:icmp:data</td>\n",
       "      <td>192.168.1.223</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0.0</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "      <td>ec:1a:59:79:f4:89</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>527035 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       frameNumber  timeRelative frame.len protocolNumber  \\\n",
       "0                1           0.0       156              6   \n",
       "1                2      0.220575        66              6   \n",
       "2                3      0.537609       284              6   \n",
       "3                4      2.075699       156              6   \n",
       "4                5      2.186605        90             17   \n",
       "...            ...           ...       ...            ...   \n",
       "527030      527031  86398.649904        42                  \n",
       "527031      527032  86398.698987       156            6.0   \n",
       "527032      527033  86398.904135        66            6.0   \n",
       "527033      527034  86399.490511       118            1.0   \n",
       "527034      527035   86399.49063       118            1.0   \n",
       "\n",
       "                      protocolName          ipDst  srcPort  dstPort ipDSCP  \\\n",
       "0         eth:ethertype:ip:tcp:tls  52.87.241.159  40767.0    443.0      0   \n",
       "1             eth:ethertype:ip:tcp  192.168.1.106    443.0  40767.0      0   \n",
       "2         eth:ethertype:ip:tcp:tls  52.87.241.159  40767.0    443.0      0   \n",
       "3         eth:ethertype:ip:tcp:tls  52.87.241.159  40767.0    443.0      0   \n",
       "4         eth:ethertype:ip:udp:ntp  192.168.1.196            4967.0      6   \n",
       "...                            ...            ...      ...      ...    ...   \n",
       "527030           eth:ethertype:arp                                           \n",
       "527031    eth:ethertype:ip:tcp:tls  52.87.241.159  40767.0    443.0    0.0   \n",
       "527032        eth:ethertype:ip:tcp  192.168.1.106    443.0  40767.0    0.0   \n",
       "527033  eth:ethertype:ip:icmp:data    192.168.1.1                      0.0   \n",
       "527034  eth:ethertype:ip:icmp:data  192.168.1.223                      0.0   \n",
       "\n",
       "                   ethsrc             ethdst  \n",
       "0       30:8c:fb:2f:e4:b2  14:cc:20:51:33:ea  \n",
       "1       14:cc:20:51:33:ea  30:8c:fb:2f:e4:b2  \n",
       "2       30:8c:fb:2f:e4:b2  14:cc:20:51:33:ea  \n",
       "3       30:8c:fb:2f:e4:b2  14:cc:20:51:33:ea  \n",
       "4       14:cc:20:51:33:ea  d0:52:a8:00:67:5e  \n",
       "...                   ...                ...  \n",
       "527030  f4:f2:6d:93:51:f1  14:cc:20:51:33:ea  \n",
       "527031  30:8c:fb:2f:e4:b2  14:cc:20:51:33:ea  \n",
       "527032  14:cc:20:51:33:ea  30:8c:fb:2f:e4:b2  \n",
       "527033  ec:1a:59:79:f4:89  14:cc:20:51:33:ea  \n",
       "527034  14:cc:20:51:33:ea  ec:1a:59:79:f4:89  \n",
       "\n",
       "[527035 rows x 11 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import csv\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from sklearn.utils import shuffle\n",
    "arra = []\n",
    "with open('no_ipsrc_simulated_csv.csv') as file:\n",
    "    reader = csv.reader(file, delimiter=',')\n",
    "    a = 0\n",
    "    for row in reader:\n",
    "        if(a==0):\n",
    "            a+=1\n",
    "            continue\n",
    "\n",
    "        arr = np.array(row)\n",
    "        if(arr[7]==\"\"):\n",
    "            arr[7]=arr[9]\n",
    "        if(arr[8]==\"\"):\n",
    "            arr[8]=arr[10]\n",
    "        arr = np.delete(arr,(8,9))\n",
    "        \n",
    "        arra.append(arr)\n",
    "\n",
    "file.close()\n",
    " \n",
    "\n",
    "columns = ['frameNumber','timeRelative','frame.len','protocolNumber','protocolName','ipDst','srcPort','dstPort','ipDSCP','ethsrc','ethdst']\n",
    "\n",
    "dfs = pd.DataFrame(data=arra,columns=columns)\n",
    "dfs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "arra = []\n",
    "with open('16-09-27.csv') as file:\n",
    "    reader = csv.reader(file, delimiter='\\t')\n",
    "    a = 0\n",
    "    for row in reader:\n",
    "        if(a==0):\n",
    "            a+=1\n",
    "            continue\n",
    "#         if(a==10):\n",
    "#             break\n",
    "        arr = np.array(row)\n",
    "        if(arr[7]==\"\"):\n",
    "            arr[7]=arr[9]\n",
    "        if(arr[8]==\"\"):\n",
    "            arr[8]=arr[10]\n",
    "        arr = np.delete(arr,(9,10))\n",
    "        \n",
    "        arra.append(arr)\n",
    "#         a += 1\n",
    "#     print(arr)\n",
    "#     print(ar)\n",
    "# file.close()\n",
    " \n",
    "# arra = np.array(ar)\n",
    "columns = ['frameNumber','timeRelative','frame.len','protocolNumber','protocolName','ipSrc','ipDst','srcPort','dstPort','ipDSCP','ethsrc','ethdst']\n",
    "\n",
    "df27 = pd.DataFrame(data=arra,columns=columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "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>frameNumber</th>\n",
       "      <th>timeRelative</th>\n",
       "      <th>frame.len</th>\n",
       "      <th>protocolNumber</th>\n",
       "      <th>protocolName</th>\n",
       "      <th>ipDst</th>\n",
       "      <th>srcPort</th>\n",
       "      <th>dstPort</th>\n",
       "      <th>ipDSCP</th>\n",
       "      <th>ethsrc</th>\n",
       "      <th>ethdst</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>0.000000000</td>\n",
       "      <td>156</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp:tls</td>\n",
       "      <td>52.87.241.159</td>\n",
       "      <td>40767</td>\n",
       "      <td>443</td>\n",
       "      <td>0</td>\n",
       "      <td>30:8c:fb:2f:e4:b2</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>0.220575000</td>\n",
       "      <td>66</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp</td>\n",
       "      <td>192.168.1.106</td>\n",
       "      <td>443</td>\n",
       "      <td>40767</td>\n",
       "      <td>0</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "      <td>30:8c:fb:2f:e4:b2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>0.537609000</td>\n",
       "      <td>284</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp:tls</td>\n",
       "      <td>52.87.241.159</td>\n",
       "      <td>40767</td>\n",
       "      <td>443</td>\n",
       "      <td>0</td>\n",
       "      <td>30:8c:fb:2f:e4:b2</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>2.075699000</td>\n",
       "      <td>156</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp:tls</td>\n",
       "      <td>52.87.241.159</td>\n",
       "      <td>40767</td>\n",
       "      <td>443</td>\n",
       "      <td>0</td>\n",
       "      <td>30:8c:fb:2f:e4:b2</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>2.186605000</td>\n",
       "      <td>90</td>\n",
       "      <td>17</td>\n",
       "      <td>eth:ethertype:ip:udp:ntp</td>\n",
       "      <td>192.168.1.196</td>\n",
       "      <td>123</td>\n",
       "      <td>4967</td>\n",
       "      <td>6</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "      <td>d0:52:a8:00:67:5e</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>527030</th>\n",
       "      <td>527031</td>\n",
       "      <td>86398.649904000</td>\n",
       "      <td>42</td>\n",
       "      <td></td>\n",
       "      <td>eth:ethertype:arp</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>f4:f2:6d:93:51:f1</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>527031</th>\n",
       "      <td>527032</td>\n",
       "      <td>86398.698987000</td>\n",
       "      <td>156</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp:tls</td>\n",
       "      <td>52.87.241.159</td>\n",
       "      <td>40767</td>\n",
       "      <td>443</td>\n",
       "      <td>0</td>\n",
       "      <td>30:8c:fb:2f:e4:b2</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>527032</th>\n",
       "      <td>527033</td>\n",
       "      <td>86398.904135000</td>\n",
       "      <td>66</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp</td>\n",
       "      <td>192.168.1.106</td>\n",
       "      <td>443</td>\n",
       "      <td>40767</td>\n",
       "      <td>0</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "      <td>30:8c:fb:2f:e4:b2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>527033</th>\n",
       "      <td>527034</td>\n",
       "      <td>86399.490511000</td>\n",
       "      <td>118</td>\n",
       "      <td>1</td>\n",
       "      <td>eth:ethertype:ip:icmp:data</td>\n",
       "      <td>192.168.1.1</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>ec:1a:59:79:f4:89</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>527034</th>\n",
       "      <td>527035</td>\n",
       "      <td>86399.490630000</td>\n",
       "      <td>118</td>\n",
       "      <td>1</td>\n",
       "      <td>eth:ethertype:ip:icmp:data</td>\n",
       "      <td>192.168.1.223</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "      <td>ec:1a:59:79:f4:89</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>527035 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       frameNumber     timeRelative frame.len protocolNumber  \\\n",
       "0                1      0.000000000       156              6   \n",
       "1                2      0.220575000        66              6   \n",
       "2                3      0.537609000       284              6   \n",
       "3                4      2.075699000       156              6   \n",
       "4                5      2.186605000        90             17   \n",
       "...            ...              ...       ...            ...   \n",
       "527030      527031  86398.649904000        42                  \n",
       "527031      527032  86398.698987000       156              6   \n",
       "527032      527033  86398.904135000        66              6   \n",
       "527033      527034  86399.490511000       118              1   \n",
       "527034      527035  86399.490630000       118              1   \n",
       "\n",
       "                      protocolName          ipDst srcPort dstPort ipDSCP  \\\n",
       "0         eth:ethertype:ip:tcp:tls  52.87.241.159   40767     443      0   \n",
       "1             eth:ethertype:ip:tcp  192.168.1.106     443   40767      0   \n",
       "2         eth:ethertype:ip:tcp:tls  52.87.241.159   40767     443      0   \n",
       "3         eth:ethertype:ip:tcp:tls  52.87.241.159   40767     443      0   \n",
       "4         eth:ethertype:ip:udp:ntp  192.168.1.196     123    4967      6   \n",
       "...                            ...            ...     ...     ...    ...   \n",
       "527030           eth:ethertype:arp                                         \n",
       "527031    eth:ethertype:ip:tcp:tls  52.87.241.159   40767     443      0   \n",
       "527032        eth:ethertype:ip:tcp  192.168.1.106     443   40767      0   \n",
       "527033  eth:ethertype:ip:icmp:data    192.168.1.1                      0   \n",
       "527034  eth:ethertype:ip:icmp:data  192.168.1.223                      0   \n",
       "\n",
       "                   ethsrc             ethdst  \n",
       "0       30:8c:fb:2f:e4:b2  14:cc:20:51:33:ea  \n",
       "1       14:cc:20:51:33:ea  30:8c:fb:2f:e4:b2  \n",
       "2       30:8c:fb:2f:e4:b2  14:cc:20:51:33:ea  \n",
       "3       30:8c:fb:2f:e4:b2  14:cc:20:51:33:ea  \n",
       "4       14:cc:20:51:33:ea  d0:52:a8:00:67:5e  \n",
       "...                   ...                ...  \n",
       "527030  f4:f2:6d:93:51:f1  14:cc:20:51:33:ea  \n",
       "527031  30:8c:fb:2f:e4:b2  14:cc:20:51:33:ea  \n",
       "527032  14:cc:20:51:33:ea  30:8c:fb:2f:e4:b2  \n",
       "527033  ec:1a:59:79:f4:89  14:cc:20:51:33:ea  \n",
       "527034  14:cc:20:51:33:ea  ec:1a:59:79:f4:89  \n",
       "\n",
       "[527035 rows x 11 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df27 = df27.drop(['ipSrc'], axis=1)\n",
    "df27"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "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>frameNumber</th>\n",
       "      <th>timeRelative</th>\n",
       "      <th>frame.len</th>\n",
       "      <th>protocolNumber</th>\n",
       "      <th>protocolName</th>\n",
       "      <th>ipDst</th>\n",
       "      <th>srcPort</th>\n",
       "      <th>dstPort</th>\n",
       "      <th>ipDSCP</th>\n",
       "      <th>ethsrc</th>\n",
       "      <th>ethdst</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>0.000000000</td>\n",
       "      <td>156</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp:tls</td>\n",
       "      <td>52.87.241.159</td>\n",
       "      <td>40767</td>\n",
       "      <td>443</td>\n",
       "      <td>0</td>\n",
       "      <td>30:8c:fb:2f:e4:b2</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>0.220575000</td>\n",
       "      <td>66</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp</td>\n",
       "      <td>192.168.1.106</td>\n",
       "      <td>443</td>\n",
       "      <td>40767</td>\n",
       "      <td>0</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "      <td>30:8c:fb:2f:e4:b2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>0.537609000</td>\n",
       "      <td>284</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp:tls</td>\n",
       "      <td>52.87.241.159</td>\n",
       "      <td>40767</td>\n",
       "      <td>443</td>\n",
       "      <td>0</td>\n",
       "      <td>30:8c:fb:2f:e4:b2</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>2.075699000</td>\n",
       "      <td>156</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp:tls</td>\n",
       "      <td>52.87.241.159</td>\n",
       "      <td>40767</td>\n",
       "      <td>443</td>\n",
       "      <td>0</td>\n",
       "      <td>30:8c:fb:2f:e4:b2</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>2.186605000</td>\n",
       "      <td>90</td>\n",
       "      <td>17</td>\n",
       "      <td>eth:ethertype:ip:udp:ntp</td>\n",
       "      <td>192.168.1.196</td>\n",
       "      <td>123</td>\n",
       "      <td>4967</td>\n",
       "      <td>6</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "      <td>d0:52:a8:00:67:5e</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1054065</th>\n",
       "      <td>527031</td>\n",
       "      <td>86398.649904</td>\n",
       "      <td>42</td>\n",
       "      <td></td>\n",
       "      <td>eth:ethertype:arp</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>f4:f2:6d:93:51:f1</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1054066</th>\n",
       "      <td>527032</td>\n",
       "      <td>86398.698987</td>\n",
       "      <td>156</td>\n",
       "      <td>6.0</td>\n",
       "      <td>eth:ethertype:ip:tcp:tls</td>\n",
       "      <td>52.87.241.159</td>\n",
       "      <td>40767.0</td>\n",
       "      <td>443.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>30:8c:fb:2f:e4:b2</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1054067</th>\n",
       "      <td>527033</td>\n",
       "      <td>86398.904135</td>\n",
       "      <td>66</td>\n",
       "      <td>6.0</td>\n",
       "      <td>eth:ethertype:ip:tcp</td>\n",
       "      <td>192.168.1.106</td>\n",
       "      <td>443.0</td>\n",
       "      <td>40767.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "      <td>30:8c:fb:2f:e4:b2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1054068</th>\n",
       "      <td>527034</td>\n",
       "      <td>86399.490511</td>\n",
       "      <td>118</td>\n",
       "      <td>1.0</td>\n",
       "      <td>eth:ethertype:ip:icmp:data</td>\n",
       "      <td>192.168.1.1</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0.0</td>\n",
       "      <td>ec:1a:59:79:f4:89</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1054069</th>\n",
       "      <td>527035</td>\n",
       "      <td>86399.49063</td>\n",
       "      <td>118</td>\n",
       "      <td>1.0</td>\n",
       "      <td>eth:ethertype:ip:icmp:data</td>\n",
       "      <td>192.168.1.223</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0.0</td>\n",
       "      <td>14:cc:20:51:33:ea</td>\n",
       "      <td>ec:1a:59:79:f4:89</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1054070 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        frameNumber  timeRelative frame.len protocolNumber  \\\n",
       "0                 1   0.000000000       156              6   \n",
       "1                 2   0.220575000        66              6   \n",
       "2                 3   0.537609000       284              6   \n",
       "3                 4   2.075699000       156              6   \n",
       "4                 5   2.186605000        90             17   \n",
       "...             ...           ...       ...            ...   \n",
       "1054065      527031  86398.649904        42                  \n",
       "1054066      527032  86398.698987       156            6.0   \n",
       "1054067      527033  86398.904135        66            6.0   \n",
       "1054068      527034  86399.490511       118            1.0   \n",
       "1054069      527035   86399.49063       118            1.0   \n",
       "\n",
       "                       protocolName          ipDst  srcPort  dstPort ipDSCP  \\\n",
       "0          eth:ethertype:ip:tcp:tls  52.87.241.159    40767      443      0   \n",
       "1              eth:ethertype:ip:tcp  192.168.1.106      443    40767      0   \n",
       "2          eth:ethertype:ip:tcp:tls  52.87.241.159    40767      443      0   \n",
       "3          eth:ethertype:ip:tcp:tls  52.87.241.159    40767      443      0   \n",
       "4          eth:ethertype:ip:udp:ntp  192.168.1.196      123     4967      6   \n",
       "...                             ...            ...      ...      ...    ...   \n",
       "1054065           eth:ethertype:arp                                           \n",
       "1054066    eth:ethertype:ip:tcp:tls  52.87.241.159  40767.0    443.0    0.0   \n",
       "1054067        eth:ethertype:ip:tcp  192.168.1.106    443.0  40767.0    0.0   \n",
       "1054068  eth:ethertype:ip:icmp:data    192.168.1.1                      0.0   \n",
       "1054069  eth:ethertype:ip:icmp:data  192.168.1.223                      0.0   \n",
       "\n",
       "                    ethsrc             ethdst  \n",
       "0        30:8c:fb:2f:e4:b2  14:cc:20:51:33:ea  \n",
       "1        14:cc:20:51:33:ea  30:8c:fb:2f:e4:b2  \n",
       "2        30:8c:fb:2f:e4:b2  14:cc:20:51:33:ea  \n",
       "3        30:8c:fb:2f:e4:b2  14:cc:20:51:33:ea  \n",
       "4        14:cc:20:51:33:ea  d0:52:a8:00:67:5e  \n",
       "...                    ...                ...  \n",
       "1054065  f4:f2:6d:93:51:f1  14:cc:20:51:33:ea  \n",
       "1054066  30:8c:fb:2f:e4:b2  14:cc:20:51:33:ea  \n",
       "1054067  14:cc:20:51:33:ea  30:8c:fb:2f:e4:b2  \n",
       "1054068  ec:1a:59:79:f4:89  14:cc:20:51:33:ea  \n",
       "1054069  14:cc:20:51:33:ea  ec:1a:59:79:f4:89  \n",
       "\n",
       "[1054070 rows x 11 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfj = df27.append(dfs,ignore_index=True)\n",
    "dfj"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "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>frameNumber</th>\n",
       "      <th>timeRelative</th>\n",
       "      <th>frame.len</th>\n",
       "      <th>protocolNumber</th>\n",
       "      <th>protocolName</th>\n",
       "      <th>ipDst</th>\n",
       "      <th>srcPort</th>\n",
       "      <th>dstPort</th>\n",
       "      <th>ipDSCP</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>0.000000000</td>\n",
       "      <td>156</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp:tls</td>\n",
       "      <td>52.87.241.159</td>\n",
       "      <td>40767</td>\n",
       "      <td>443</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>0.220575000</td>\n",
       "      <td>66</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp</td>\n",
       "      <td>192.168.1.106</td>\n",
       "      <td>443</td>\n",
       "      <td>40767</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>0.537609000</td>\n",
       "      <td>284</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp:tls</td>\n",
       "      <td>52.87.241.159</td>\n",
       "      <td>40767</td>\n",
       "      <td>443</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>2.075699000</td>\n",
       "      <td>156</td>\n",
       "      <td>6</td>\n",
       "      <td>eth:ethertype:ip:tcp:tls</td>\n",
       "      <td>52.87.241.159</td>\n",
       "      <td>40767</td>\n",
       "      <td>443</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>2.186605000</td>\n",
       "      <td>90</td>\n",
       "      <td>17</td>\n",
       "      <td>eth:ethertype:ip:udp:ntp</td>\n",
       "      <td>192.168.1.196</td>\n",
       "      <td>123</td>\n",
       "      <td>4967</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1054065</th>\n",
       "      <td>527031</td>\n",
       "      <td>86398.649904</td>\n",
       "      <td>42</td>\n",
       "      <td></td>\n",
       "      <td>eth:ethertype:arp</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1054066</th>\n",
       "      <td>527032</td>\n",
       "      <td>86398.698987</td>\n",
       "      <td>156</td>\n",
       "      <td>6.0</td>\n",
       "      <td>eth:ethertype:ip:tcp:tls</td>\n",
       "      <td>52.87.241.159</td>\n",
       "      <td>40767.0</td>\n",
       "      <td>443.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1054067</th>\n",
       "      <td>527033</td>\n",
       "      <td>86398.904135</td>\n",
       "      <td>66</td>\n",
       "      <td>6.0</td>\n",
       "      <td>eth:ethertype:ip:tcp</td>\n",
       "      <td>192.168.1.106</td>\n",
       "      <td>443.0</td>\n",
       "      <td>40767.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1054068</th>\n",
       "      <td>527034</td>\n",
       "      <td>86399.490511</td>\n",
       "      <td>118</td>\n",
       "      <td>1.0</td>\n",
       "      <td>eth:ethertype:ip:icmp:data</td>\n",
       "      <td>192.168.1.1</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1054069</th>\n",
       "      <td>527035</td>\n",
       "      <td>86399.49063</td>\n",
       "      <td>118</td>\n",
       "      <td>1.0</td>\n",
       "      <td>eth:ethertype:ip:icmp:data</td>\n",
       "      <td>192.168.1.223</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1054070 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        frameNumber  timeRelative frame.len protocolNumber  \\\n",
       "0                 1   0.000000000       156              6   \n",
       "1                 2   0.220575000        66              6   \n",
       "2                 3   0.537609000       284              6   \n",
       "3                 4   2.075699000       156              6   \n",
       "4                 5   2.186605000        90             17   \n",
       "...             ...           ...       ...            ...   \n",
       "1054065      527031  86398.649904        42                  \n",
       "1054066      527032  86398.698987       156            6.0   \n",
       "1054067      527033  86398.904135        66            6.0   \n",
       "1054068      527034  86399.490511       118            1.0   \n",
       "1054069      527035   86399.49063       118            1.0   \n",
       "\n",
       "                       protocolName          ipDst  srcPort  dstPort ipDSCP  \n",
       "0          eth:ethertype:ip:tcp:tls  52.87.241.159    40767      443      0  \n",
       "1              eth:ethertype:ip:tcp  192.168.1.106      443    40767      0  \n",
       "2          eth:ethertype:ip:tcp:tls  52.87.241.159    40767      443      0  \n",
       "3          eth:ethertype:ip:tcp:tls  52.87.241.159    40767      443      0  \n",
       "4          eth:ethertype:ip:udp:ntp  192.168.1.196      123     4967      6  \n",
       "...                             ...            ...      ...      ...    ...  \n",
       "1054065           eth:ethertype:arp                                          \n",
       "1054066    eth:ethertype:ip:tcp:tls  52.87.241.159  40767.0    443.0    0.0  \n",
       "1054067        eth:ethertype:ip:tcp  192.168.1.106    443.0  40767.0    0.0  \n",
       "1054068  eth:ethertype:ip:icmp:data    192.168.1.1                      0.0  \n",
       "1054069  eth:ethertype:ip:icmp:data  192.168.1.223                      0.0  \n",
       "\n",
       "[1054070 rows x 9 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "features = ['frameNumber','timeRelative','frame.len','protocolNumber','protocolName','ipDst','srcPort','dstPort','ipDSCP']\n",
    "\n",
    "\n",
    "Xj = dfj[features]\n",
    "\n",
    "y1 = dfj['ethsrc']\n",
    "\n",
    "y2 = dfj['ethdst']\n",
    "Xj"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-8-2e23010d8dcf>:5: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  Xj[col] = pd.to_numeric(Xj[col],errors='coerce')\n",
      "/home/deepak/.local/lib/python3.8/site-packages/pandas/core/indexing.py:966: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  self.obj[item] = s\n"
     ]
    }
   ],
   "source": [
    "#################PREPROCESSING######################\n",
    "\n",
    "catCols = ['frameNumber','timeRelative','frame.len','protocolNumber','srcPort','dstPort','ipDSCP']\n",
    "for col in catCols:\n",
    "    Xj[col] = pd.to_numeric(Xj[col],errors='coerce')\n",
    "\n",
    "# print(Xj.dtypes)\n",
    "\n",
    "\n",
    "textCols = ['protocolName', 'ipDst']\n",
    "\n",
    "for col in textCols:\n",
    "    Xj.loc[Xj[col]=='',[col]] = \"missing\"\n",
    "categories = [Xj[column].unique() for column in textCols]\n",
    "cat_colwise = categories\n",
    "# print(categories)\n",
    "\n",
    "# categories = [item for sublist in categories for item in sublist]\n",
    "# categories = list(set(categories))\n",
    "\n",
    "\n",
    "\n",
    "from sklearn.preprocessing import OrdinalEncoder\n",
    "from sklearn.impute import SimpleImputer\n",
    "\n",
    "imp = SimpleImputer(missing_values=np.nan,strategy='constant',fill_value=-1)\n",
    "imp.fit(Xj)\n",
    "\n",
    "\n",
    "Xt = imp.transform(Xj)\n",
    "Xju = pd.DataFrame(data=Xt,columns=features)\n",
    "\n",
    "# Xju.dtypes\n",
    "\n",
    "enc = OrdinalEncoder(dtype=np.float64)\n",
    "enc.fit(Xju)\n",
    "X_enc = enc.transform(Xju)\n",
    "Xjug = pd.DataFrame(data=X_enc,columns=features)\n",
    "\n",
    "\n",
    "from sklearn.preprocessing import LabelEncoder\n",
    "le1 = LabelEncoder()\n",
    "le1.fit(y1)\n",
    "le1.classes_\n",
    "y = le1.transform(y1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "################   ORIGINAL FILE FOR MODEL    #############\n",
    "\n",
    "features = ['frameNumber','timeRelative','frame.len','protocolNumber','protocolName','ipDst','srcPort','dstPort','ipDSCP']\n",
    "\n",
    "# print(arra)\n",
    "X27 = df27[features]\n",
    "# print(X)\n",
    "# X.head()\n",
    "y1 = df27['ethsrc']\n",
    "# print(y1)\n",
    "# y1.head()\n",
    "y2 = df27['ethdst']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-10-f1d3b4c33ac9>:3: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  X27[col] = pd.to_numeric(X27[col],errors='coerce')\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "frameNumber         int64\n",
      "timeRelative      float64\n",
      "frame.len           int64\n",
      "protocolNumber    float64\n",
      "protocolName       object\n",
      "ipDst              object\n",
      "srcPort           float64\n",
      "dstPort           float64\n",
      "ipDSCP            float64\n",
      "dtype: object\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/deepak/.local/lib/python3.8/site-packages/pandas/core/indexing.py:966: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  self.obj[item] = s\n"
     ]
    }
   ],
   "source": [
    "catCols = ['frameNumber','timeRelative','frame.len','protocolNumber','srcPort','dstPort','ipDSCP']\n",
    "for col in catCols:\n",
    "    X27[col] = pd.to_numeric(X27[col],errors='coerce')\n",
    "\n",
    "print(X27.dtypes)\n",
    "\n",
    "\n",
    "textCols = ['protocolName', 'ipDst']\n",
    "\n",
    "for col in textCols:\n",
    "    X27.loc[X27[col]=='',[col]] = \"missing\"\n",
    "# categories = [X[column].unique() for column in textCols]\n",
    "# cat_colwise = categories\n",
    "# print(categories)\n",
    "\n",
    "# categories = [item for sublist in categories for item in sublist]\n",
    "# categories = list(set(categories))\n",
    "\n",
    "\n",
    "\n",
    "# from sklearn.preprocessing import OrdinalEncoder\n",
    "from sklearn.impute import SimpleImputer\n",
    "\n",
    "imp = SimpleImputer(missing_values=np.nan,strategy='constant',fill_value=-1)\n",
    "imp.fit(X27)\n",
    "\n",
    "\n",
    "Xt = imp.transform(X27)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "X27 = pd.DataFrame(data=Xt,columns=features)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_enc = enc.transform(X27)\n",
    "X27 = pd.DataFrame(data=X_enc,columns=features)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import LabelEncoder\n",
    "le1 = LabelEncoder()\n",
    "le1.fit(y1)\n",
    "le1.classes_\n",
    "y27 = le1.transform(y1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "done\n"
     ]
    }
   ],
   "source": [
    "# START MODEL HERE!!\n",
    "##########################################################\n",
    "#################################\n",
    "#######################################\n",
    "\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "# X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.5, random_state=0)  89\n",
    "# X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, random_state=0)   90\n",
    "# X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.25, random_state=0)    0.8991643834576765\n",
    "X_train, X_test, y_train, y_test = train_test_split(X27, y27, test_size=0.3, random_state=0) \n",
    "\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "\n",
    "classifier=RandomForestClassifier() \n",
    "classifier=classifier.fit(X_train,y_train) \n",
    "predicted=classifier.predict(X_test)\n",
    "\n",
    "print('done')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pickle\n",
    "filename = 'no_ipsrc_jugaad_model.sav'\n",
    "pickle.dump(classifier,open(filename,'wb'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0., 0., 0., ..., 0., 0., 0.],\n",
       "       [0., 0., 0., ..., 0., 0., 0.],\n",
       "       [0., 0., 0., ..., 0., 0., 0.],\n",
       "       ...,\n",
       "       [0., 1., 0., ..., 0., 0., 0.],\n",
       "       [0., 0., 0., ..., 0., 0., 0.],\n",
       "       [0., 0., 0., ..., 0., 0., 0.]])"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "classifier.predict_proba(X_test)[:-33]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.07002346, 0.06981787, 0.1270703 , 0.0227309 , 0.05725067,\n",
       "       0.25066624, 0.25244818, 0.14519261, 0.00479978])"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "classifier.feature_importances_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8824632140180444"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "XJ = Xjug.iloc[527035:,:]\n",
    "classifier.score(XJ,y[527035:])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8824632140180444"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "classifier.score(XJ,y27)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9691595434838294"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "classifier.score(X27,y27)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.89816496 0.89594232 0.90038761 0.89605074 0.90060176 0.90019516\n",
      " 0.89523474 0.89759297 0.89843326 0.89938198]\n",
      "0.898198551052716\n",
      "CV\n"
     ]
    }
   ],
   "source": [
    "from sklearn.model_selection import cross_val_score\n",
    "import numpy as np\n",
    "cv = cross_val_score(classifier, X_train, y_train, cv=10)\n",
    "print(cv)\n",
    "print(np.mean(cv))\n",
    "# scores\n",
    "print(\"CV\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Confusion Matrix :\n",
      "[[9.14198706e-01 2.83205891e-04 0.00000000e+00 6.88705234e-04\n",
      "  7.80865894e-03 0.00000000e+00 3.98142004e-03 1.89681335e-04\n",
      "  1.99978950e-03 7.95228628e-03 7.75903614e-02 1.62778079e-03\n",
      "  1.56154938e-02 0.00000000e+00 2.80155642e-02 2.76110444e-02\n",
      "  2.68020305e-02 9.07354346e-03]\n",
      " [7.61324705e-05 8.92098556e-01 0.00000000e+00 0.00000000e+00\n",
      "  0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      "  0.00000000e+00 1.98807157e-03 1.07951807e-01 0.00000000e+00\n",
      "  0.00000000e+00 1.40022548e-01 0.00000000e+00 0.00000000e+00\n",
      "  0.00000000e+00 0.00000000e+00]\n",
      " [0.00000000e+00 0.00000000e+00 9.21568627e-01 0.00000000e+00\n",
      "  2.89209590e-05 3.70370370e-02 0.00000000e+00 0.00000000e+00\n",
      "  2.10504157e-04 0.00000000e+00 0.00000000e+00 2.17037439e-03\n",
      "  0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      "  0.00000000e+00 0.00000000e+00]\n",
      " [1.52264941e-04 1.41602945e-04 0.00000000e+00 8.80165289e-01\n",
      "  1.93770425e-03 0.00000000e+00 1.52621102e-02 1.89681335e-04\n",
      "  3.15756236e-04 3.97614314e-03 9.63855422e-04 0.00000000e+00\n",
      "  1.01399310e-03 0.00000000e+00 1.16731518e-02 8.00320128e-04\n",
      "  0.00000000e+00 9.55109838e-04]\n",
      " [4.75827941e-02 0.00000000e+00 3.92156863e-02 8.47107438e-02\n",
      "  9.28116956e-01 3.70370370e-02 2.76045123e-01 2.50063227e-02\n",
      "  7.63077571e-02 2.50497018e-01 9.63855422e-04 5.42593597e-02\n",
      "  2.19022511e-01 0.00000000e+00 1.13618677e-01 1.88475390e-01\n",
      "  9.03553299e-02 1.91021968e-01]\n",
      " [0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      "  1.44604795e-05 8.88888889e-01 0.00000000e+00 0.00000000e+00\n",
      "  0.00000000e+00 0.00000000e+00 0.00000000e+00 5.42593597e-04\n",
      "  2.02798621e-04 0.00000000e+00 7.78210117e-04 0.00000000e+00\n",
      "  0.00000000e+00 4.77554919e-04]\n",
      " [4.56794823e-04 0.00000000e+00 0.00000000e+00 6.88705234e-03\n",
      "  5.68296845e-03 0.00000000e+00 6.64897147e-01 4.10976227e-04\n",
      "  7.36764551e-04 0.00000000e+00 1.44578313e-03 1.62778079e-03\n",
      "  2.02798621e-03 0.00000000e+00 2.72373541e-02 3.20128051e-03\n",
      "  1.62436548e-03 1.43266476e-03]\n",
      " [7.61324705e-04 0.00000000e+00 0.00000000e+00 6.88705234e-04\n",
      "  1.01367961e-02 0.00000000e+00 5.97213006e-03 9.70820688e-01\n",
      "  2.52604989e-03 5.96421471e-03 1.44578313e-03 1.62778079e-03\n",
      "  4.46156966e-03 0.00000000e+00 8.56031128e-03 4.80192077e-03\n",
      "  2.43654822e-03 4.77554919e-03]\n",
      " [1.44651694e-03 0.00000000e+00 0.00000000e+00 3.44352617e-03\n",
      "  9.99219134e-03 0.00000000e+00 3.98142004e-03 4.10976227e-04\n",
      "  9.08535944e-01 3.18091451e-02 8.67469880e-03 5.42593597e-04\n",
      "  2.43358345e-03 0.00000000e+00 3.11284047e-03 7.60304122e-03\n",
      "  4.06091371e-03 5.25310411e-03]\n",
      " [2.28397411e-04 1.41602945e-04 0.00000000e+00 0.00000000e+00\n",
      "  1.57619227e-03 0.00000000e+00 1.32714001e-03 2.21294891e-04\n",
      "  8.42016630e-04 6.18290258e-01 1.92771084e-03 0.00000000e+00\n",
      "  1.41959035e-03 0.00000000e+00 9.33852140e-03 4.00160064e-03\n",
      "  1.82741117e-03 5.25310411e-03]\n",
      " [1.20289303e-02 2.63381478e-02 0.00000000e+00 2.06611570e-03\n",
      "  1.44604795e-05 0.00000000e+00 1.32714001e-03 3.16135559e-05\n",
      "  1.05252079e-03 5.96421471e-03 4.65542169e-01 0.00000000e+00\n",
      "  3.14337863e-02 2.36753100e-02 5.83657588e-02 6.40256102e-02\n",
      "  3.37055838e-02 1.43266476e-03]\n",
      " [1.52264941e-04 0.00000000e+00 1.96078431e-02 6.88705234e-03\n",
      "  1.35928507e-03 3.70370370e-02 1.32714001e-03 2.21294891e-04\n",
      "  5.26260394e-04 0.00000000e+00 9.63855422e-04 9.34346175e-01\n",
      "  1.21679173e-03 0.00000000e+00 0.00000000e+00 8.00320128e-04\n",
      "  6.09137056e-04 1.91021968e-03]\n",
      " [4.11115341e-03 1.41602945e-04 0.00000000e+00 5.50964187e-03\n",
      "  1.31156549e-02 0.00000000e+00 6.63570007e-03 1.04324734e-03\n",
      "  3.05231028e-03 2.18687873e-02 7.22891566e-02 2.17037439e-03\n",
      "  6.80794971e-01 0.00000000e+00 2.17898833e-02 3.20128051e-02\n",
      "  1.46192893e-02 9.07354346e-03]\n",
      " [7.61324705e-05 8.05720759e-02 1.96078431e-02 0.00000000e+00\n",
      "  0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      "  0.00000000e+00 0.00000000e+00 5.25301205e-02 0.00000000e+00\n",
      "  0.00000000e+00 8.36076663e-01 0.00000000e+00 0.00000000e+00\n",
      "  0.00000000e+00 0.00000000e+00]\n",
      " [2.74076894e-03 1.41602945e-04 0.00000000e+00 2.06611570e-03\n",
      "  1.93770425e-03 0.00000000e+00 7.29927007e-03 7.27111786e-04\n",
      "  4.21008315e-04 0.00000000e+00 3.90361446e-02 0.00000000e+00\n",
      "  6.69235449e-03 0.00000000e+00 6.63035019e-01 1.44057623e-02\n",
      "  5.48223350e-03 1.43266476e-03]\n",
      " [6.09059764e-03 0.00000000e+00 0.00000000e+00 2.06611570e-03\n",
      "  6.11678283e-03 0.00000000e+00 5.30856005e-03 1.89681335e-04\n",
      "  1.15777287e-03 1.78926441e-02 8.14457831e-02 0.00000000e+00\n",
      "  1.50070980e-02 0.00000000e+00 2.25680934e-02 5.61424570e-01\n",
      "  4.64974619e-02 6.20821394e-03]\n",
      " [8.45070423e-03 0.00000000e+00 0.00000000e+00 3.44352617e-03\n",
      "  5.94325708e-03 0.00000000e+00 3.31785003e-03 2.84522003e-04\n",
      "  9.47268709e-04 7.95228628e-03 8.43373494e-02 5.42593597e-04\n",
      "  1.62238897e-02 0.00000000e+00 2.87937743e-02 8.56342537e-02\n",
      "  7.69340102e-01 3.82043935e-03]\n",
      " [1.44651694e-03 1.41602945e-04 0.00000000e+00 1.37741047e-03\n",
      "  6.21800619e-03 0.00000000e+00 3.31785003e-03 2.52908447e-04\n",
      "  1.36827702e-03 2.58449304e-02 2.89156627e-03 5.42593597e-04\n",
      "  2.43358345e-03 2.25479143e-04 3.11284047e-03 5.20208083e-03\n",
      "  2.63959391e-03 7.57879656e-01]]\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import confusion_matrix \n",
    "from sklearn.metrics import accuracy_score \n",
    "from sklearn.metrics import classification_report\n",
    "\n",
    "print ('Confusion Matrix :') \n",
    "CM = confusion_matrix(y_test, predicted, normalize=\"pred\")\n",
    "CM_not = confusion_matrix(y_test,predicted)\n",
    "print(CM)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Report : \n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.91      0.92      0.92     13083\n",
      "           1       0.89      0.88      0.89      7147\n",
      "           2       0.92      0.84      0.88        56\n",
      "           3       0.88      0.87      0.87      1475\n",
      "           4       0.93      0.92      0.92     69636\n",
      "           5       0.89      0.83      0.86        29\n",
      "           6       0.66      0.67      0.67      1501\n",
      "           7       0.97      0.97      0.97     31530\n",
      "           8       0.91      0.91      0.91      9467\n",
      "           9       0.62      0.63      0.62       494\n",
      "          10       0.47      0.48      0.47      1994\n",
      "          11       0.93      0.93      0.93      1861\n",
      "          12       0.68      0.70      0.69      4763\n",
      "          13       0.84      0.85      0.84      4388\n",
      "          14       0.66      0.68      0.67      1244\n",
      "          15       0.56      0.57      0.57      2457\n",
      "          16       0.77      0.78      0.77      4858\n",
      "          17       0.76      0.75      0.75      2128\n",
      "\n",
      "    accuracy                           0.90    158111\n",
      "   macro avg       0.79      0.79      0.79    158111\n",
      "weighted avg       0.90      0.90      0.90    158111\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print ('Report : ') \n",
    "print (classification_report(y_test, predicted))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<sklearn.metrics._plot.confusion_matrix.ConfusionMatrixDisplay at 0x7fafdb56d550>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.cm as cm\n",
    "\n",
    "from sklearn.metrics import plot_confusion_matrix\n",
    "\n",
    "mac_to_device = {'00:16:6c:ab:6b:88':'Samsung SmartCam', '00:24:e4:11:18:a8':'Withings Smart Baby Monitor', '00:24:e4:1b:6f:96':'Withings Smart scale',\n",
    "                '08:21:ef:3b:fc:e3':'Samsung Galaxy Tab', '14:cc:20:51:33:ea':'TPLink Router', '18:b4:30:25:be:e4':'NEST Protect smoke alarm',\n",
    "                 '18:b7:9e:02:20:44':'Triby Speaker', '30:8c:fb:2f:e4:b2':'Dropcam','44:65:0d:56:cc:d3':'Amazon Echo', \n",
    "                 '50:c7:bf:00:56:39':'TP-Link Smart plug', '70:5a:0f:e4:9b:c0':'HP Printer', '70:ee:50:03:b8:ac':'Netatmo weather station', \n",
    "                 '70:ee:50:18:34:43':'Netatmo Welcome',  'd0:52:a8:00:67:5e':'Smart Things', 'e0:76:d0:33:bb:85':'PIX-STAR Photo-frame',\n",
    "                 'ec:1a:59:79:f4:89':'Belkin Wemo switch', 'ec:1a:59:83:28:11':'Belkin wemo motion sensor', 'f4:f2:6d:93:51:f1':'TP-Link Day Night Cloud camera', \n",
    "                    }\n",
    "devices = [d for d in mac_to_device.values()]\n",
    "\n",
    "# print(le1.transform(label))\n",
    "plot_confusion_matrix(classifier, X_test, y_test, normalize='true', display_labels=devices, include_values=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(141.0, 0.5, 'Truth')"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1296x648 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import seaborn as sn\n",
    "plt.figure(figsize=(18,9))\n",
    "sn.heatmap(CM, annot=True)\n",
    "plt.xlabel('Predicted')\n",
    "plt.ylabel('Truth')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "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>Samsung SmartCam</th>\n",
       "      <th>Withings Smart Baby Monitor</th>\n",
       "      <th>Withings Smart scale</th>\n",
       "      <th>Samsung Galaxy Tab</th>\n",
       "      <th>TPLink Router</th>\n",
       "      <th>NEST Protect smoke alarm</th>\n",
       "      <th>Triby Speaker</th>\n",
       "      <th>Dropcam</th>\n",
       "      <th>Amazon Echo</th>\n",
       "      <th>TP-Link Smart plug</th>\n",
       "      <th>HP Printer</th>\n",
       "      <th>Netatmo weather station</th>\n",
       "      <th>Netatmo Welcome</th>\n",
       "      <th>Smart Things</th>\n",
       "      <th>PIX-STAR Photo-frame</th>\n",
       "      <th>Belkin Wemo switch</th>\n",
       "      <th>Belkin wemo motion sensor</th>\n",
       "      <th>TP-Link Day Night Cloud camera</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Samsung SmartCam</th>\n",
       "      <td>12008</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>540</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>19</td>\n",
       "      <td>4</td>\n",
       "      <td>161</td>\n",
       "      <td>3</td>\n",
       "      <td>77</td>\n",
       "      <td>0</td>\n",
       "      <td>36</td>\n",
       "      <td>69</td>\n",
       "      <td>132</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Withings Smart Baby Monitor</th>\n",
       "      <td>1</td>\n",
       "      <td>6300</td>\n",
       "      <td>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>224</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>621</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Withings Smart scale</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>47</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <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>Samsung Galaxy Tab</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1278</td>\n",
       "      <td>134</td>\n",
       "      <td>0</td>\n",
       "      <td>23</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TPLink Router</th>\n",
       "      <td>625</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>123</td>\n",
       "      <td>64183</td>\n",
       "      <td>1</td>\n",
       "      <td>416</td>\n",
       "      <td>791</td>\n",
       "      <td>725</td>\n",
       "      <td>126</td>\n",
       "      <td>2</td>\n",
       "      <td>100</td>\n",
       "      <td>1080</td>\n",
       "      <td>0</td>\n",
       "      <td>146</td>\n",
       "      <td>471</td>\n",
       "      <td>445</td>\n",
       "      <td>400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NEST Protect smoke alarm</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>24</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Triby Speaker</th>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>393</td>\n",
       "      <td>0</td>\n",
       "      <td>1002</td>\n",
       "      <td>13</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dropcam</th>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>701</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>30709</td>\n",
       "      <td>24</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>22</td>\n",
       "      <td>0</td>\n",
       "      <td>11</td>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Amazon Echo</th>\n",
       "      <td>19</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>691</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>13</td>\n",
       "      <td>8632</td>\n",
       "      <td>16</td>\n",
       "      <td>18</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>19</td>\n",
       "      <td>20</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TP-Link Smart plug</th>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>109</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>8</td>\n",
       "      <td>311</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>9</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HP Printer</th>\n",
       "      <td>158</td>\n",
       "      <td>186</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>3</td>\n",
       "      <td>966</td>\n",
       "      <td>0</td>\n",
       "      <td>155</td>\n",
       "      <td>105</td>\n",
       "      <td>75</td>\n",
       "      <td>160</td>\n",
       "      <td>166</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Netatmo weather station</th>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>94</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1722</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Netatmo Welcome</th>\n",
       "      <td>54</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>907</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>33</td>\n",
       "      <td>29</td>\n",
       "      <td>11</td>\n",
       "      <td>150</td>\n",
       "      <td>4</td>\n",
       "      <td>3357</td>\n",
       "      <td>0</td>\n",
       "      <td>28</td>\n",
       "      <td>80</td>\n",
       "      <td>72</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Smart Things</th>\n",
       "      <td>1</td>\n",
       "      <td>569</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>109</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3708</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PIX-STAR Photo-frame</th>\n",
       "      <td>36</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>134</td>\n",
       "      <td>0</td>\n",
       "      <td>11</td>\n",
       "      <td>23</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>81</td>\n",
       "      <td>0</td>\n",
       "      <td>33</td>\n",
       "      <td>0</td>\n",
       "      <td>852</td>\n",
       "      <td>36</td>\n",
       "      <td>27</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Belkin Wemo switch</th>\n",
       "      <td>80</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>423</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>6</td>\n",
       "      <td>11</td>\n",
       "      <td>9</td>\n",
       "      <td>169</td>\n",
       "      <td>0</td>\n",
       "      <td>74</td>\n",
       "      <td>0</td>\n",
       "      <td>29</td>\n",
       "      <td>1403</td>\n",
       "      <td>229</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Belkin wemo motion sensor</th>\n",
       "      <td>111</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>411</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>9</td>\n",
       "      <td>9</td>\n",
       "      <td>4</td>\n",
       "      <td>175</td>\n",
       "      <td>1</td>\n",
       "      <td>80</td>\n",
       "      <td>0</td>\n",
       "      <td>37</td>\n",
       "      <td>214</td>\n",
       "      <td>3789</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TP-Link Day Night Cloud camera</th>\n",
       "      <td>19</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>430</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>8</td>\n",
       "      <td>13</td>\n",
       "      <td>13</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>13</td>\n",
       "      <td>13</td>\n",
       "      <td>1587</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                Samsung SmartCam  Withings Smart Baby Monitor  \\\n",
       "Samsung SmartCam                           12008                            2   \n",
       "Withings Smart Baby Monitor                    1                         6300   \n",
       "Withings Smart scale                           0                            0   \n",
       "Samsung Galaxy Tab                             2                            1   \n",
       "TPLink Router                                625                            0   \n",
       "NEST Protect smoke alarm                       0                            0   \n",
       "Triby Speaker                                  6                            0   \n",
       "Dropcam                                       10                            0   \n",
       "Amazon Echo                                   19                            0   \n",
       "TP-Link Smart plug                             3                            1   \n",
       "HP Printer                                   158                          186   \n",
       "Netatmo weather station                        2                            0   \n",
       "Netatmo Welcome                               54                            1   \n",
       "Smart Things                                   1                          569   \n",
       "PIX-STAR Photo-frame                          36                            1   \n",
       "Belkin Wemo switch                            80                            0   \n",
       "Belkin wemo motion sensor                    111                            0   \n",
       "TP-Link Day Night Cloud camera                19                            1   \n",
       "\n",
       "                                Withings Smart scale  Samsung Galaxy Tab  \\\n",
       "Samsung SmartCam                                   0                   1   \n",
       "Withings Smart Baby Monitor                        0                   0   \n",
       "Withings Smart scale                              47                   0   \n",
       "Samsung Galaxy Tab                                 0                1278   \n",
       "TPLink Router                                      2                 123   \n",
       "NEST Protect smoke alarm                           0                   0   \n",
       "Triby Speaker                                      0                  10   \n",
       "Dropcam                                            0                   1   \n",
       "Amazon Echo                                        0                   5   \n",
       "TP-Link Smart plug                                 0                   0   \n",
       "HP Printer                                         0                   3   \n",
       "Netatmo weather station                            1                  10   \n",
       "Netatmo Welcome                                    0                   8   \n",
       "Smart Things                                       1                   0   \n",
       "PIX-STAR Photo-frame                               0                   3   \n",
       "Belkin Wemo switch                                 0                   3   \n",
       "Belkin wemo motion sensor                          0                   5   \n",
       "TP-Link Day Night Cloud camera                     0                   2   \n",
       "\n",
       "                                TPLink Router  NEST Protect smoke alarm  \\\n",
       "Samsung SmartCam                          540                         0   \n",
       "Withings Smart Baby Monitor                 0                         0   \n",
       "Withings Smart scale                        2                         1   \n",
       "Samsung Galaxy Tab                        134                         0   \n",
       "TPLink Router                           64183                         1   \n",
       "NEST Protect smoke alarm                    1                        24   \n",
       "Triby Speaker                             393                         0   \n",
       "Dropcam                                   701                         0   \n",
       "Amazon Echo                               691                         0   \n",
       "TP-Link Smart plug                        109                         0   \n",
       "HP Printer                                  1                         0   \n",
       "Netatmo weather station                    94                         1   \n",
       "Netatmo Welcome                           907                         0   \n",
       "Smart Things                                0                         0   \n",
       "PIX-STAR Photo-frame                      134                         0   \n",
       "Belkin Wemo switch                        423                         0   \n",
       "Belkin wemo motion sensor                 411                         0   \n",
       "TP-Link Day Night Cloud camera            430                         0   \n",
       "\n",
       "                                Triby Speaker  Dropcam  Amazon Echo  \\\n",
       "Samsung SmartCam                            6        6           19   \n",
       "Withings Smart Baby Monitor                 0        0            0   \n",
       "Withings Smart scale                        0        0            2   \n",
       "Samsung Galaxy Tab                         23        6            3   \n",
       "TPLink Router                             416      791          725   \n",
       "NEST Protect smoke alarm                    0        0            0   \n",
       "Triby Speaker                            1002       13            7   \n",
       "Dropcam                                     9    30709           24   \n",
       "Amazon Echo                                 6       13         8632   \n",
       "TP-Link Smart plug                          2        7            8   \n",
       "HP Printer                                  2        1           10   \n",
       "Netatmo weather station                     2        7            5   \n",
       "Netatmo Welcome                            10       33           29   \n",
       "Smart Things                                0        0            0   \n",
       "PIX-STAR Photo-frame                       11       23            4   \n",
       "Belkin Wemo switch                          8        6           11   \n",
       "Belkin wemo motion sensor                   5        9            9   \n",
       "TP-Link Day Night Cloud camera              5        8           13   \n",
       "\n",
       "                                TP-Link Smart plug  HP Printer  \\\n",
       "Samsung SmartCam                                 4         161   \n",
       "Withings Smart Baby Monitor                      1         224   \n",
       "Withings Smart scale                             0           0   \n",
       "Samsung Galaxy Tab                               2           2   \n",
       "TPLink Router                                  126           2   \n",
       "NEST Protect smoke alarm                         0           0   \n",
       "Triby Speaker                                    0           3   \n",
       "Dropcam                                          3           3   \n",
       "Amazon Echo                                     16          18   \n",
       "TP-Link Smart plug                             311           4   \n",
       "HP Printer                                       3         966   \n",
       "Netatmo weather station                          0           2   \n",
       "Netatmo Welcome                                 11         150   \n",
       "Smart Things                                     0         109   \n",
       "PIX-STAR Photo-frame                             0          81   \n",
       "Belkin Wemo switch                               9         169   \n",
       "Belkin wemo motion sensor                        4         175   \n",
       "TP-Link Day Night Cloud camera                  13           6   \n",
       "\n",
       "                                Netatmo weather station  Netatmo Welcome  \\\n",
       "Samsung SmartCam                                      3               77   \n",
       "Withings Smart Baby Monitor                           0                0   \n",
       "Withings Smart scale                                  4                0   \n",
       "Samsung Galaxy Tab                                    0                5   \n",
       "TPLink Router                                       100             1080   \n",
       "NEST Protect smoke alarm                              1                1   \n",
       "Triby Speaker                                         3               10   \n",
       "Dropcam                                               3               22   \n",
       "Amazon Echo                                           1               12   \n",
       "TP-Link Smart plug                                    0                7   \n",
       "HP Printer                                            0              155   \n",
       "Netatmo weather station                            1722                6   \n",
       "Netatmo Welcome                                       4             3357   \n",
       "Smart Things                                          0                0   \n",
       "PIX-STAR Photo-frame                                  0               33   \n",
       "Belkin Wemo switch                                    0               74   \n",
       "Belkin wemo motion sensor                             1               80   \n",
       "TP-Link Day Night Cloud camera                        1               12   \n",
       "\n",
       "                                Smart Things  PIX-STAR Photo-frame  \\\n",
       "Samsung SmartCam                           0                    36   \n",
       "Withings Smart Baby Monitor              621                     0   \n",
       "Withings Smart scale                       0                     0   \n",
       "Samsung Galaxy Tab                         0                    15   \n",
       "TPLink Router                              0                   146   \n",
       "NEST Protect smoke alarm                   0                     1   \n",
       "Triby Speaker                              0                    35   \n",
       "Dropcam                                    0                    11   \n",
       "Amazon Echo                                0                     4   \n",
       "TP-Link Smart plug                         0                    12   \n",
       "HP Printer                               105                    75   \n",
       "Netatmo weather station                    0                     0   \n",
       "Netatmo Welcome                            0                    28   \n",
       "Smart Things                            3708                     0   \n",
       "PIX-STAR Photo-frame                       0                   852   \n",
       "Belkin Wemo switch                         0                    29   \n",
       "Belkin wemo motion sensor                  0                    37   \n",
       "TP-Link Day Night Cloud camera             1                     4   \n",
       "\n",
       "                                Belkin Wemo switch  Belkin wemo motion sensor  \\\n",
       "Samsung SmartCam                                69                        132   \n",
       "Withings Smart Baby Monitor                      0                          0   \n",
       "Withings Smart scale                             0                          0   \n",
       "Samsung Galaxy Tab                               2                          0   \n",
       "TPLink Router                                  471                        445   \n",
       "NEST Protect smoke alarm                         0                          0   \n",
       "Triby Speaker                                    8                          8   \n",
       "Dropcam                                         12                         12   \n",
       "Amazon Echo                                     19                         20   \n",
       "TP-Link Smart plug                              10                          9   \n",
       "HP Printer                                     160                        166   \n",
       "Netatmo weather station                          2                          3   \n",
       "Netatmo Welcome                                 80                         72   \n",
       "Smart Things                                     0                          0   \n",
       "PIX-STAR Photo-frame                            36                         27   \n",
       "Belkin Wemo switch                            1403                        229   \n",
       "Belkin wemo motion sensor                      214                       3789   \n",
       "TP-Link Day Night Cloud camera                  13                         13   \n",
       "\n",
       "                                TP-Link Day Night Cloud camera  \n",
       "Samsung SmartCam                                            19  \n",
       "Withings Smart Baby Monitor                                  0  \n",
       "Withings Smart scale                                         0  \n",
       "Samsung Galaxy Tab                                           2  \n",
       "TPLink Router                                              400  \n",
       "NEST Protect smoke alarm                                     1  \n",
       "Triby Speaker                                                3  \n",
       "Dropcam                                                     10  \n",
       "Amazon Echo                                                 11  \n",
       "TP-Link Smart plug                                          11  \n",
       "HP Printer                                                   3  \n",
       "Netatmo weather station                                      4  \n",
       "Netatmo Welcome                                             19  \n",
       "Smart Things                                                 0  \n",
       "PIX-STAR Photo-frame                                         3  \n",
       "Belkin Wemo switch                                          13  \n",
       "Belkin wemo motion sensor                                    8  \n",
       "TP-Link Day Night Cloud camera                            1587  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd# CMd = pd.DataFrame(CM, columns=devices, index=le1.classes_)\n",
    "\n",
    "CMd = pd.DataFrame(CM_not, columns=devices, index=devices)\n",
    "\n",
    "CMd.head(18)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.91419871 0.89209856 0.92156863 0.88016529 0.92811696 0.88888889\n",
      " 0.66489715 0.97082069 0.90853594 0.61829026 0.46554217 0.93434617\n",
      " 0.68079497 0.83607666 0.66303502 0.56142457 0.7693401  0.75787966] [0.9178323  0.88148874 0.83928571 0.86644068 0.9216928  0.82758621\n",
      " 0.66755496 0.97396131 0.91179888 0.62955466 0.48445336 0.92530897\n",
      " 0.70480789 0.84503191 0.68488746 0.57102157 0.7799506  0.74577068] [0.9160119  0.88676191 0.87850467 0.87324906 0.92489372 0.85714286\n",
      " 0.6662234  0.97238846 0.91016449 0.62387161 0.47480954 0.92980562\n",
      " 0.69259336 0.84053043 0.6737841  0.56618241 0.77460902 0.75177641] [13083  7147    56  1475 69636    29  1501 31530  9467   494  1994  1861\n",
      "  4763  4388  1244  2457  4858  2128]\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import precision_recall_fscore_support\n",
    "precision, recall, f1Score, support = precision_recall_fscore_support(y_test, predicted)\n",
    "print(precision, recall, f1Score, support)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.7876904824200177"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.metrics import balanced_accuracy_score\n",
    "balanced_accuracy_score(y_test, predicted)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "features = ['frameNumber','timeRelative','frame.len','protocolNumber','protocolName','ipDst','srcPort','dstPort','ipDSCP']\n",
    "\n",
    "# print(arra)\n",
    "X = dfs[features]\n",
    "# print(X)\n",
    "# X.head()\n",
    "y1 = dfs['ethsrc']\n",
    "# print(y1)\n",
    "# y1.head()\n",
    "y2 = dfs['ethdst']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-31-6c556973cbf3>:3: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  X[col] = pd.to_numeric(X[col],errors='coerce')\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "frameNumber         int64\n",
      "timeRelative      float64\n",
      "frame.len           int64\n",
      "protocolNumber    float64\n",
      "protocolName       object\n",
      "ipDst              object\n",
      "srcPort           float64\n",
      "dstPort           float64\n",
      "ipDSCP            float64\n",
      "dtype: object\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/deepak/.local/lib/python3.8/site-packages/pandas/core/indexing.py:966: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  self.obj[item] = s\n"
     ]
    }
   ],
   "source": [
    "catCols = ['frameNumber','timeRelative','frame.len','protocolNumber','srcPort','dstPort','ipDSCP']\n",
    "for col in catCols:\n",
    "    X[col] = pd.to_numeric(X[col],errors='coerce')\n",
    "\n",
    "print(X.dtypes)\n",
    "\n",
    "\n",
    "textCols = ['protocolName', 'ipDst']\n",
    "\n",
    "for col in textCols:\n",
    "    X.loc[X[col]=='',[col]] = \"missing\"\n",
    "# categories = [X[column].unique() for column in textCols]\n",
    "# cat_colwise = categories\n",
    "# print(categories)\n",
    "\n",
    "# categories = [item for sublist in categories for item in sublist]\n",
    "# categories = list(set(categories))\n",
    "\n",
    "\n",
    "\n",
    "# from sklearn.preprocessing import OrdinalEncoder\n",
    "from sklearn.impute import SimpleImputer\n",
    "\n",
    "imp = SimpleImputer(missing_values=np.nan,strategy='constant',fill_value=-1)\n",
    "imp.fit(X)\n",
    "\n",
    "\n",
    "Xt = imp.transform(X)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = pd.DataFrame(data=Xt,columns=features)\n",
    "X_enc = enc.transform(X)\n",
    "X = pd.DataFrame(data=X_enc,columns=features)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import LabelEncoder\n",
    "le1 = LabelEncoder()\n",
    "le1.fit(y1)\n",
    "le1.classes_\n",
    "y = le1.transform(y1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0.  , 0.  , 0.  , ..., 0.  , 0.  , 0.  ],\n",
       "       [0.  , 0.  , 0.  , ..., 0.  , 0.  , 0.  ],\n",
       "       [0.  , 0.  , 0.  , ..., 0.  , 0.  , 0.  ],\n",
       "       ...,\n",
       "       [0.  , 0.  , 0.  , ..., 0.  , 0.  , 0.  ],\n",
       "       [0.  , 0.  , 0.  , ..., 0.95, 0.04, 0.  ],\n",
       "       [0.  , 0.  , 0.  , ..., 0.  , 0.  , 0.  ]])"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "classifier.predict_proba(X)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 7,  4,  7, ...,  4, 15,  4])"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "predictedS=classifier.predict(X)\n",
    "predictedS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 7,  4,  7, ...,  4, 15,  4])"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "predicted27 = classifier.predict(X27)\n",
    "predicted27"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "not_matching_rows = (predicted27==predictedS)\n",
    "not_matching_rows.all()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "not_matching = np.where(not_matching_rows==False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([    11,     50,     72, ..., 526929, 526958, 526989]),)"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# print(not_matching.size())\n",
    "not_matching"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([    11,     50,     72, ..., 526929, 526958, 526989])"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "for i in not_matching:\n",
    "    not_matching = i\n",
    "    break\n",
    "not_matching"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "not_matching_list = not_matching.tolist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "46188"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(not_matching_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "from numpy import loadtxt\n",
    "array_index = loadtxt('no_ipsrc_array_indices.txt')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "14289\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([32239., 32271., 32348., ..., 89599., 89601., 89605.])"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(array_index.size)\n",
    "array_index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[32239., 32271., 32348., ..., 89599., 89601., 89605.]])"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "arr_i = np.reshape(array_index,(1,14289))\n",
    "arr_i"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[    11,     50,     72, ..., 526929, 526958, 526989]])"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "no_match = np.reshape(not_matching,(1,46188))\n",
    "no_match"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "list_index = array_index.tolist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([    0,     1,     2, ..., 46185, 46186, 46187])"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "index = np.argsort(not_matching)\n",
    "index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([    11,     50,     72, ..., 526929, 526958, 526989])"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sorted_not = not_matching[index]\n",
    "sorted_not"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 2156,  2172,  2197, ..., 19294, 19295, 19296])"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sorted_index_not = np.searchsorted(sorted_not, array_index)\n",
    "sorted_index_not"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 2094,  2095,  2096, ..., 19294, 19295, 19296])"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sorted_indices = np.unique(sorted_index_not)\n",
    "sorted_indices"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "14032"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sorted_indices.size"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9820141367485479"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sorted_indices.size/array_index.size"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "14030\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([    0,     1,     6, ..., 14287, 14288, 14289])"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "indexa = np.argsort(array_index)\n",
    "sorted_list = array_index[indexa]\n",
    "sorted_index_list = np.searchsorted(sorted_list, not_matching)\n",
    "\n",
    "sorted_indicesa = np.unique(sorted_index_list)\n",
    "print(sorted_indicesa.size)\n",
    "sorted_indicesa"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib import pyplot as plt\n",
    "plt.bar(array_index,2,width=1)\n",
    "plt.bar(not_matching,2,width=1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([32040, 32043, 32051, ..., 89599, 89601, 89605])"
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wrongly_identified = sorted_indices.tolist()\n",
    "wrongly_identified = not_matching[wrongly_identified]\n",
    "wrongly_identified"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([8, 8, 8, ..., 7, 7, 7])"
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wrongS = predictedS[wrongly_identified]\n",
    "correct27 = predicted27[wrongly_identified]\n",
    "correct27"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(wrongS, label='wrongS', marker='.', markersize='5')\n",
    "plt.plot(correct27,label='correct27', color='g')\n",
    "plt.xlabel('incorrectly identified')\n",
    "plt.ylabel('label')\n",
    "plt.yticks([0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17])\n",
    "plt.legend()\n",
    "plt.title('Comparing prediction in simulated packets')\n",
    "plt.axis([0,100,0,17])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'df' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-168-8b0f8ccee0f1>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdf27\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'timeRelative'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mdf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mloc\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mdf\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'eth.src'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m==\u001b[0m\u001b[0;34m'ec:1a:59:83:28:11'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'frame.len'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m: name 'df' is not defined"
     ]
    }
   ],
   "source": [
    "plt.plot(df27['timeRelative'],df.loc[df['eth.src']=='ec:1a:59:83:28:11','frame.len'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "metadata": {},
   "outputs": [],
   "source": [
    "unique_protocol = df27['protocolName'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[['156',\n",
       "  '284',\n",
       "  '60',\n",
       "  '172',\n",
       "  '160',\n",
       "  '123',\n",
       "  '95',\n",
       "  '140',\n",
       "  '135',\n",
       "  '139',\n",
       "  '425',\n",
       "  '211',\n",
       "  '224',\n",
       "  '97',\n",
       "  '583',\n",
       "  '1484',\n",
       "  '192',\n",
       "  '117',\n",
       "  '158',\n",
       "  '824',\n",
       "  '201',\n",
       "  '335',\n",
       "  '89',\n",
       "  '93',\n",
       "  '246',\n",
       "  '408',\n",
       "  '1514',\n",
       "  '264',\n",
       "  '316',\n",
       "  '359',\n",
       "  '471',\n",
       "  '571',\n",
       "  '380',\n",
       "  '107',\n",
       "  '396',\n",
       "  '368',\n",
       "  '219',\n",
       "  '91',\n",
       "  '103',\n",
       "  '300',\n",
       "  '336',\n",
       "  '357',\n",
       "  '1510',\n",
       "  '347',\n",
       "  '529',\n",
       "  '236',\n",
       "  '184',\n",
       "  '109',\n",
       "  '940',\n",
       "  '481',\n",
       "  '514',\n",
       "  '127',\n",
       "  '230',\n",
       "  '320',\n",
       "  '104',\n",
       "  '448',\n",
       "  '88',\n",
       "  '171',\n",
       "  '183',\n",
       "  '207',\n",
       "  '345',\n",
       "  '267',\n",
       "  '525',\n",
       "  '926',\n",
       "  '260',\n",
       "  '259',\n",
       "  '222',\n",
       "  '256',\n",
       "  '324',\n",
       "  '593',\n",
       "  '378',\n",
       "  '194',\n",
       "  '1051',\n",
       "  '308',\n",
       "  '1127',\n",
       "  '883',\n",
       "  '1367',\n",
       "  '1463',\n",
       "  '245',\n",
       "  '122',\n",
       "  '242',\n",
       "  '205',\n",
       "  '1481',\n",
       "  '162',\n",
       "  '203',\n",
       "  '263',\n",
       "  '987',\n",
       "  '976',\n",
       "  '1413',\n",
       "  '551',\n",
       "  '173',\n",
       "  '253',\n",
       "  '1469',\n",
       "  '1104',\n",
       "  '1472',\n",
       "  '124',\n",
       "  '967',\n",
       "  '1446',\n",
       "  '1468',\n",
       "  '1480',\n",
       "  '625',\n",
       "  '1258',\n",
       "  '636',\n",
       "  '984',\n",
       "  '645',\n",
       "  '962',\n",
       "  '1424',\n",
       "  '247',\n",
       "  '328',\n",
       "  '743',\n",
       "  '517',\n",
       "  '1337',\n",
       "  '268',\n",
       "  '901',\n",
       "  '543',\n",
       "  '145',\n",
       "  '1251',\n",
       "  '431',\n",
       "  '1253',\n",
       "  '228',\n",
       "  '1271',\n",
       "  '653',\n",
       "  '232',\n",
       "  '1263',\n",
       "  '296',\n",
       "  '534',\n",
       "  '144',\n",
       "  '851',\n",
       "  '459',\n",
       "  '429',\n",
       "  '825',\n",
       "  '1421',\n",
       "  '552',\n",
       "  '225',\n",
       "  '754',\n",
       "  '899',\n",
       "  '457',\n",
       "  '519',\n",
       "  '214',\n",
       "  '837',\n",
       "  '1363',\n",
       "  '229',\n",
       "  '248',\n",
       "  '567',\n",
       "  '310',\n",
       "  '266',\n",
       "  '843',\n",
       "  '451',\n",
       "  '399',\n",
       "  '817',\n",
       "  '1397',\n",
       "  '1296',\n",
       "  '243',\n",
       "  '622',\n",
       "  '287',\n",
       "  '856',\n",
       "  '639',\n",
       "  '244',\n",
       "  '249',\n",
       "  '815',\n",
       "  '254',\n",
       "  '360',\n",
       "  '748',\n",
       "  '1219',\n",
       "  '538',\n",
       "  '888',\n",
       "  '1476',\n",
       "  '112',\n",
       "  '1408',\n",
       "  '416',\n",
       "  '257',\n",
       "  '989',\n",
       "  '573',\n",
       "  '238',\n",
       "  '234',\n",
       "  '141',\n",
       "  '727',\n",
       "  '119',\n",
       "  '1303',\n",
       "  '535',\n",
       "  '759',\n",
       "  '239',\n",
       "  '855',\n",
       "  '895',\n",
       "  '999',\n",
       "  '220',\n",
       "  '714',\n",
       "  '521',\n",
       "  '569',\n",
       "  '92',\n",
       "  '85',\n",
       "  '371',\n",
       "  '180',\n",
       "  '99',\n",
       "  '397',\n",
       "  '206',\n",
       "  '251',\n",
       "  '274',\n",
       "  '548',\n",
       "  '182',\n",
       "  '189',\n",
       "  '365',\n",
       "  '1050',\n",
       "  '554',\n",
       "  '853',\n",
       "  '584',\n",
       "  '434',\n",
       "  '157',\n",
       "  '179',\n",
       "  '528',\n",
       "  '281',\n",
       "  '200',\n",
       "  '620',\n",
       "  '167',\n",
       "  '221',\n",
       "  '262',\n",
       "  '255',\n",
       "  '374',\n",
       "  '398',\n",
       "  '223',\n",
       "  '252',\n",
       "  '275',\n",
       "  '545',\n",
       "  '191',\n",
       "  '375',\n",
       "  '390',\n",
       "  '426',\n",
       "  '210',\n",
       "  '334',\n",
       "  '447',\n",
       "  '348',\n",
       "  '349',\n",
       "  '544',\n",
       "  '186',\n",
       "  '149',\n",
       "  '227',\n",
       "  '121',\n",
       "  '153',\n",
       "  '1340',\n",
       "  '511',\n",
       "  '1259',\n",
       "  '472',\n",
       "  '1099',\n",
       "  '218',\n",
       "  '1094',\n",
       "  '615',\n",
       "  '482',\n",
       "  '217',\n",
       "  '505',\n",
       "  '332',\n",
       "  '423',\n",
       "  '154',\n",
       "  '430',\n",
       "  '276',\n",
       "  '190',\n",
       "  '148',\n",
       "  '381',\n",
       "  '427',\n",
       "  '209',\n",
       "  '226',\n",
       "  '350',\n",
       "  '485',\n",
       "  '352',\n",
       "  '614',\n",
       "  '278',\n",
       "  '370',\n",
       "  '193',\n",
       "  '142',\n",
       "  '208',\n",
       "  '199',\n",
       "  '1029',\n",
       "  '111',\n",
       "  '204',\n",
       "  '164',\n",
       "  '110',\n",
       "  '250',\n",
       "  '460',\n",
       "  '314',\n",
       "  '285',\n",
       "  '1423',\n",
       "  '966',\n",
       "  '433',\n",
       "  '1053',\n",
       "  '292',\n",
       "  '361',\n",
       "  '174',\n",
       "  '916',\n",
       "  '452',\n",
       "  '711',\n",
       "  '861',\n",
       "  '588',\n",
       "  '500',\n",
       "  '647',\n",
       "  '963',\n",
       "  '195',\n",
       "  '473',\n",
       "  '155',\n",
       "  '132',\n",
       "  '894',\n",
       "  '602',\n",
       "  '927',\n",
       "  '282',\n",
       "  '1483',\n",
       "  '241',\n",
       "  '342',\n",
       "  '541',\n",
       "  '152',\n",
       "  '130',\n",
       "  '1208',\n",
       "  '213',\n",
       "  '503',\n",
       "  '810',\n",
       "  '358',\n",
       "  '237',\n",
       "  '1508',\n",
       "  '461',\n",
       "  '782',\n",
       "  '356',\n",
       "  '1228',\n",
       "  '591',\n",
       "  '1254',\n",
       "  '1450',\n",
       "  '491',\n",
       "  '857',\n",
       "  '100',\n",
       "  '439',\n",
       "  '159',\n",
       "  '632',\n",
       "  '944',\n",
       "  '504',\n",
       "  '972',\n",
       "  '353',\n",
       "  '125',\n",
       "  '1275',\n",
       "  '313',\n",
       "  '291',\n",
       "  '355',\n",
       "  '108',\n",
       "  '1273',\n",
       "  '302',\n",
       "  '113',\n",
       "  '131',\n",
       "  '1342',\n",
       "  '1173',\n",
       "  '518',\n",
       "  '609',\n",
       "  '1121',\n",
       "  '886',\n",
       "  '725',\n",
       "  '118',\n",
       "  '143',\n",
       "  '134',\n",
       "  '756',\n",
       "  '75',\n",
       "  '722',\n",
       "  '943',\n",
       "  '1222',\n",
       "  '1260',\n",
       "  '986',\n",
       "  '626',\n",
       "  '351',\n",
       "  '598',\n",
       "  '648',\n",
       "  '261',\n",
       "  '333',\n",
       "  '464',\n",
       "  '432',\n",
       "  '546',\n",
       "  '379',\n",
       "  '147',\n",
       "  '303',\n",
       "  '120',\n",
       "  '931',\n",
       "  '523',\n",
       "  '550',\n",
       "  '1034',\n",
       "  '315',\n",
       "  '524',\n",
       "  '90',\n",
       "  '337',\n",
       "  '522',\n",
       "  '558',\n",
       "  '814',\n",
       "  '480',\n",
       "  '1130',\n",
       "  '1166',\n",
       "  '294',\n",
       "  '1436',\n",
       "  '1155',\n",
       "  '317',\n",
       "  '402',\n",
       "  '377',\n",
       "  '185',\n",
       "  '290',\n",
       "  '575',\n",
       "  '446',\n",
       "  '231',\n",
       "  '406',\n",
       "  '772',\n",
       "  '570',\n",
       "  '163',\n",
       "  '331',\n",
       "  '306',\n",
       "  '202',\n",
       "  '312',\n",
       "  '418',\n",
       "  '1326',\n",
       "  '384',\n",
       "  '618',\n",
       "  '1140',\n",
       "  '586',\n",
       "  '1044',\n",
       "  '216',\n",
       "  '94',\n",
       "  '376',\n",
       "  '1256',\n",
       "  '630',\n",
       "  '496',\n",
       "  '702',\n",
       "  '616',\n",
       "  '1122',\n",
       "  '1439',\n",
       "  '115',\n",
       "  '319',\n",
       "  '270',\n",
       "  '151',\n",
       "  '96',\n",
       "  '1055',\n",
       "  '835',\n",
       "  '885',\n",
       "  '483',\n",
       "  '456',\n",
       "  '925',\n",
       "  '1344',\n",
       "  '309',\n",
       "  '1455',\n",
       "  '170',\n",
       "  '176',\n",
       "  '1056',\n",
       "  '72',\n",
       "  '951',\n",
       "  '717',\n",
       "  '1461',\n",
       "  '175',\n",
       "  '597',\n",
       "  '674',\n",
       "  '903',\n",
       "  '420',\n",
       "  '1169',\n",
       "  '1255',\n",
       "  '1200',\n",
       "  '364',\n",
       "  '1415',\n",
       "  '832',\n",
       "  '1304',\n",
       "  '474',\n",
       "  '938',\n",
       "  '670',\n",
       "  '395',\n",
       "  '1038',\n",
       "  '685',\n",
       "  '937',\n",
       "  '549',\n",
       "  '177',\n",
       "  '513',\n",
       "  '1047',\n",
       "  '1032',\n",
       "  '492',\n",
       "  '1006',\n",
       "  '212',\n",
       "  '338',\n",
       "  '61',\n",
       "  '271',\n",
       "  '385',\n",
       "  '166',\n",
       "  '84',\n",
       "  '477',\n",
       "  '323',\n",
       "  '424',\n",
       "  '272',\n",
       "  '311',\n",
       "  '327',\n",
       "  '1250',\n",
       "  '1398',\n",
       "  '1031',\n",
       "  '566',\n",
       "  '1054',\n",
       "  '872',\n",
       "  '539',\n",
       "  '790',\n",
       "  '596',\n",
       "  '165',\n",
       "  '579',\n",
       "  '1175',\n",
       "  '391',\n",
       "  '809',\n",
       "  '868',\n",
       "  '792',\n",
       "  '392',\n",
       "  '542',\n",
       "  '1247',\n",
       "  '441',\n",
       "  '1464',\n",
       "  '1316',\n",
       "  '1105',\n",
       "  '1262',\n",
       "  '1317',\n",
       "  '1444',\n",
       "  '476',\n",
       "  '443',\n",
       "  '1430',\n",
       "  '339',\n",
       "  '559',\n",
       "  '198',\n",
       "  '178',\n",
       "  '362',\n",
       "  '527',\n",
       "  '215'],\n",
       " ['66',\n",
       "  '54',\n",
       "  '188',\n",
       "  '204',\n",
       "  '60',\n",
       "  '140',\n",
       "  '74',\n",
       "  '252',\n",
       "  '1236',\n",
       "  '135',\n",
       "  '78',\n",
       "  '95',\n",
       "  '97',\n",
       "  '1484',\n",
       "  '1326',\n",
       "  '1514',\n",
       "  '62',\n",
       "  '58',\n",
       "  '265',\n",
       "  '103',\n",
       "  '1510',\n",
       "  '172',\n",
       "  '89',\n",
       "  '93',\n",
       "  '109',\n",
       "  '104',\n",
       "  '957',\n",
       "  '105',\n",
       "  '1266',\n",
       "  '1414',\n",
       "  '1424',\n",
       "  '551',\n",
       "  '517',\n",
       "  '452',\n",
       "  '428',\n",
       "  '666',\n",
       "  '799',\n",
       "  '451',\n",
       "  '354',\n",
       "  '748',\n",
       "  '121',\n",
       "  '759',\n",
       "  '160',\n",
       "  '416',\n",
       "  '383',\n",
       "  '70',\n",
       "  '146',\n",
       "  '91',\n",
       "  '408',\n",
       "  '264',\n",
       "  '268',\n",
       "  '199',\n",
       "  '267',\n",
       "  '996',\n",
       "  '332',\n",
       "  '460',\n",
       "  '247',\n",
       "  '359',\n",
       "  '348',\n",
       "  '349',\n",
       "  '256',\n",
       "  '427',\n",
       "  '248',\n",
       "  '153',\n",
       "  '218',\n",
       "  '350',\n",
       "  '345',\n",
       "  '947',\n",
       "  '173',\n",
       "  '967',\n",
       "  '1222',\n",
       "  '110',\n",
       "  '254',\n",
       "  '217',\n",
       "  '90',\n",
       "  '550',\n",
       "  '347',\n",
       "  '253',\n",
       "  '566',\n",
       "  '241',\n",
       "  '123',\n",
       "  '330',\n",
       "  '333',\n",
       "  '292',\n",
       "  '86',\n",
       "  '315',\n",
       "  '552',\n",
       "  '910',\n",
       "  '92',\n",
       "  '337',\n",
       "  '219',\n",
       "  '856',\n",
       "  '600',\n",
       "  '386',\n",
       "  '1056',\n",
       "  '760',\n",
       "  '118',\n",
       "  '521',\n",
       "  '119',\n",
       "  '131',\n",
       "  '111',\n",
       "  '503',\n",
       "  '837',\n",
       "  '94',\n",
       "  '156',\n",
       "  '351',\n",
       "  '335',\n",
       "  '392',\n",
       "  '579',\n",
       "  '198',\n",
       "  '255',\n",
       "  '423'],\n",
       " ['90'],\n",
       " ['268',\n",
       "  '75',\n",
       "  '91',\n",
       "  '288',\n",
       "  '103',\n",
       "  '76',\n",
       "  '148',\n",
       "  '80',\n",
       "  '78',\n",
       "  '82',\n",
       "  '92',\n",
       "  '88',\n",
       "  '326',\n",
       "  '332',\n",
       "  '79',\n",
       "  '284',\n",
       "  '72',\n",
       "  '530',\n",
       "  '74',\n",
       "  '443',\n",
       "  '89',\n",
       "  '217',\n",
       "  '95',\n",
       "  '86',\n",
       "  '453',\n",
       "  '104',\n",
       "  '170',\n",
       "  '542',\n",
       "  '136',\n",
       "  '405',\n",
       "  '545',\n",
       "  '395',\n",
       "  '526',\n",
       "  '96',\n",
       "  '418',\n",
       "  '153',\n",
       "  '157',\n",
       "  '554',\n",
       "  '83',\n",
       "  '499',\n",
       "  '276',\n",
       "  '280',\n",
       "  '184',\n",
       "  '147',\n",
       "  '143',\n",
       "  '127',\n",
       "  '151',\n",
       "  '81',\n",
       "  '156',\n",
       "  '85',\n",
       "  '160',\n",
       "  '173',\n",
       "  '549',\n",
       "  '533',\n",
       "  '105',\n",
       "  '205',\n",
       "  '529',\n",
       "  '483',\n",
       "  '467',\n",
       "  '87',\n",
       "  '246',\n",
       "  '536',\n",
       "  '313',\n",
       "  '247',\n",
       "  '449',\n",
       "  '398',\n",
       "  '73',\n",
       "  '301',\n",
       "  '139',\n",
       "  '285',\n",
       "  '538',\n",
       "  '431',\n",
       "  '322',\n",
       "  '375',\n",
       "  '505',\n",
       "  '164',\n",
       "  '115',\n",
       "  '543',\n",
       "  '84',\n",
       "  '310',\n",
       "  '546',\n",
       "  '248',\n",
       "  '116',\n",
       "  '373',\n",
       "  '489',\n",
       "  '77',\n",
       "  '108',\n",
       "  '244',\n",
       "  '290',\n",
       "  '541',\n",
       "  '389',\n",
       "  '528',\n",
       "  '294',\n",
       "  '68',\n",
       "  '227',\n",
       "  '234',\n",
       "  '256',\n",
       "  '346',\n",
       "  '547'],\n",
       " ['98', '118', '62'],\n",
       " ['201', '191', '55', '306'],\n",
       " ['43'],\n",
       " ['42', '60'],\n",
       " ['421',\n",
       "  '493',\n",
       "  '489',\n",
       "  '469',\n",
       "  '501',\n",
       "  '483',\n",
       "  '485',\n",
       "  '143',\n",
       "  '381',\n",
       "  '163',\n",
       "  '148',\n",
       "  '354',\n",
       "  '352',\n",
       "  '376',\n",
       "  '384',\n",
       "  '382',\n",
       "  '386',\n",
       "  '394',\n",
       "  '390'],\n",
       " ['174'],\n",
       " ['214', '146', '222', '114', '206', '170'],\n",
       " ['70',\n",
       "  '68',\n",
       "  '60',\n",
       "  '78',\n",
       "  '106',\n",
       "  '62',\n",
       "  '58',\n",
       "  '160',\n",
       "  '315',\n",
       "  '201',\n",
       "  '242',\n",
       "  '199',\n",
       "  '158',\n",
       "  '580',\n",
       "  '732',\n",
       "  '108',\n",
       "  '285',\n",
       "  '455',\n",
       "  '114',\n",
       "  '176',\n",
       "  '672',\n",
       "  '284',\n",
       "  '234',\n",
       "  '211',\n",
       "  '192',\n",
       "  '215',\n",
       "  '579',\n",
       "  '124',\n",
       "  '111',\n",
       "  '509',\n",
       "  '109',\n",
       "  '402',\n",
       "  '733',\n",
       "  '186',\n",
       "  '281',\n",
       "  '1514'],\n",
       " ['46', '54'],\n",
       " ['252',\n",
       "  '91',\n",
       "  '162',\n",
       "  '349',\n",
       "  '254',\n",
       "  '149',\n",
       "  '277',\n",
       "  '272',\n",
       "  '249',\n",
       "  '288',\n",
       "  '282',\n",
       "  '285',\n",
       "  '299',\n",
       "  '354',\n",
       "  '311',\n",
       "  '314',\n",
       "  '411',\n",
       "  '383',\n",
       "  '267',\n",
       "  '453',\n",
       "  '79',\n",
       "  '416',\n",
       "  '369'],\n",
       " ['1236', '386'],\n",
       " ['86', '90', '110'],\n",
       " ['251', '257'],\n",
       " ['785', '753'],\n",
       " ['689'],\n",
       " ['20'],\n",
       " ['139', '113', '135'],\n",
       " ['350', '342', '349', '322', '590', '347', '355'],\n",
       " ['198', '86', '78', '70'],\n",
       " ['188', '204', '140', '105', '70', '259', '198', '605', '181', '95', '606'],\n",
       " ['1266'],\n",
       " ['81',\n",
       "  '176',\n",
       "  '362',\n",
       "  '1514',\n",
       "  '103',\n",
       "  '90',\n",
       "  '1266',\n",
       "  '1036',\n",
       "  '998',\n",
       "  '1295',\n",
       "  '264',\n",
       "  '666',\n",
       "  '742',\n",
       "  '374',\n",
       "  '375',\n",
       "  '1484',\n",
       "  '1425',\n",
       "  '1060',\n",
       "  '1510',\n",
       "  '706',\n",
       "  '537',\n",
       "  '675',\n",
       "  '835',\n",
       "  '1132',\n",
       "  '485',\n",
       "  '594',\n",
       "  '717',\n",
       "  '1348',\n",
       "  '393',\n",
       "  '656',\n",
       "  '861',\n",
       "  '1285',\n",
       "  '929',\n",
       "  '1016',\n",
       "  '920',\n",
       "  '1039',\n",
       "  '699',\n",
       "  '1267',\n",
       "  '1477',\n",
       "  '601',\n",
       "  '627',\n",
       "  '810',\n",
       "  '933',\n",
       "  '862',\n",
       "  '990',\n",
       "  '500',\n",
       "  '352',\n",
       "  '1084',\n",
       "  '414',\n",
       "  '823',\n",
       "  '586',\n",
       "  '740',\n",
       "  '634',\n",
       "  '286',\n",
       "  '1196',\n",
       "  '1110',\n",
       "  '1214',\n",
       "  '1070',\n",
       "  '324',\n",
       "  '1350',\n",
       "  '498',\n",
       "  '1262',\n",
       "  '932',\n",
       "  '1494',\n",
       "  '926',\n",
       "  '170',\n",
       "  '1380',\n",
       "  '194',\n",
       "  '542',\n",
       "  '305',\n",
       "  '283'],\n",
       " ['109', '427', '1469'],\n",
       " ['70', '110'],\n",
       " ['98'],\n",
       " ['265',\n",
       "  '248',\n",
       "  '339',\n",
       "  '287',\n",
       "  '458',\n",
       "  '387',\n",
       "  '459',\n",
       "  '338',\n",
       "  '298',\n",
       "  '460',\n",
       "  '263',\n",
       "  '256',\n",
       "  '259',\n",
       "  '264',\n",
       "  '262',\n",
       "  '255',\n",
       "  '257',\n",
       "  '461',\n",
       "  '267',\n",
       "  '268',\n",
       "  '266',\n",
       "  '270',\n",
       "  '269',\n",
       "  '237',\n",
       "  '392',\n",
       "  '200',\n",
       "  '301',\n",
       "  '284',\n",
       "  '276',\n",
       "  '457',\n",
       "  '271',\n",
       "  '272',\n",
       "  '273',\n",
       "  '275',\n",
       "  '274',\n",
       "  '261',\n",
       "  '258',\n",
       "  '288',\n",
       "  '260'],\n",
       " ['331',\n",
       "  '392',\n",
       "  '248',\n",
       "  '289',\n",
       "  '545',\n",
       "  '993',\n",
       "  '650',\n",
       "  '252',\n",
       "  '379',\n",
       "  '247',\n",
       "  '246',\n",
       "  '255',\n",
       "  '347',\n",
       "  '492',\n",
       "  '898',\n",
       "  '431',\n",
       "  '1337',\n",
       "  '928'],\n",
       " ['252', '1236'],\n",
       " ['110'],\n",
       " ['98',\n",
       "  '110',\n",
       "  '286',\n",
       "  '313',\n",
       "  '308',\n",
       "  '565',\n",
       "  '109',\n",
       "  '268',\n",
       "  '106',\n",
       "  '282',\n",
       "  '96',\n",
       "  '277',\n",
       "  '97',\n",
       "  '262',\n",
       "  '95',\n",
       "  '274',\n",
       "  '104',\n",
       "  '503',\n",
       "  '107',\n",
       "  '525',\n",
       "  '99',\n",
       "  '333',\n",
       "  '332',\n",
       "  '251',\n",
       "  '301',\n",
       "  '94',\n",
       "  '422',\n",
       "  '435',\n",
       "  '457',\n",
       "  '356',\n",
       "  '292',\n",
       "  '304',\n",
       "  '103',\n",
       "  '495',\n",
       "  '444',\n",
       "  '451',\n",
       "  '522',\n",
       "  '101',\n",
       "  '218',\n",
       "  '105',\n",
       "  '551',\n",
       "  '267',\n",
       "  '559',\n",
       "  '108',\n",
       "  '476',\n",
       "  '131',\n",
       "  '460',\n",
       "  '349',\n",
       "  '296',\n",
       "  '115',\n",
       "  '511',\n",
       "  '93',\n",
       "  '258',\n",
       "  '100',\n",
       "  '317',\n",
       "  '300',\n",
       "  '355',\n",
       "  '485',\n",
       "  '348',\n",
       "  '520',\n",
       "  '354',\n",
       "  '102',\n",
       "  '365',\n",
       "  '297',\n",
       "  '373',\n",
       "  '364',\n",
       "  '372',\n",
       "  '269',\n",
       "  '556',\n",
       "  '294'],\n",
       " ['910', '880'],\n",
       " ['1236',\n",
       "  '1209',\n",
       "  '407',\n",
       "  '394',\n",
       "  '576',\n",
       "  '575',\n",
       "  '562',\n",
       "  '577',\n",
       "  '563',\n",
       "  '1208',\n",
       "  '409',\n",
       "  '1207',\n",
       "  '1223',\n",
       "  '1326',\n",
       "  '396',\n",
       "  '1237'],\n",
       " ['1266'],\n",
       " ['1514'],\n",
       " ['856', '796', '770', '783', '1514', '944', '759', '843'],\n",
       " ['83', '852'],\n",
       " ['38'],\n",
       " ['1069', '1205'],\n",
       " ['1234'],\n",
       " ['1029'],\n",
       " ['759', '786', '1049'],\n",
       " ['252', '1236'],\n",
       " ['743'],\n",
       " ['616'],\n",
       " ['1215'],\n",
       " ['252', '1236'],\n",
       " ['177', '175'],\n",
       " ['394', '250', '122', '506', '1214', '238', '138', '282', '170'],\n",
       " ['1514'],\n",
       " ['230'],\n",
       " ['252', '1236'],\n",
       " ['880'],\n",
       " ['643'],\n",
       " ['252', '1236'],\n",
       " ['252', '1236'],\n",
       " ['672', '598', '440'],\n",
       " ['59'],\n",
       " ['252', '1236'],\n",
       " ['994', '506'],\n",
       " ['71'],\n",
       " ['198', '150'],\n",
       " ['252', '1236'],\n",
       " ['1392', '77', '83', '80', '72'],\n",
       " ['646'],\n",
       " ['252', '1236'],\n",
       " ['705'],\n",
       " ['252', '1236'],\n",
       " ['435'],\n",
       " ['59']]"
      ]
     },
     "execution_count": 167,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "protocol_frame_len_unique_len = []\n",
    "protocol_frame_len_unique = []\n",
    "total_len_per_proto = []\n",
    "for p in unique_protocol:\n",
    "#     print(p)\n",
    "    pro_len = df27.loc[df27['protocolName']==p,'frame.len']#['frame.len'].unique()\n",
    "    s = pro_len.size\n",
    "    total_len_per_proto.append(s)\n",
    "    pro_len = pro_len.unique()\n",
    "    pro_len = pro_len.tolist()\n",
    "    protocol_frame_len_unique.append(pro_len)\n",
    "    protocol_frame_len_unique_len.append(len(pro_len))\n",
    "#     break\n",
    "#     protocol_frame_len += pro_len\n",
    "\n",
    "# pro_len.size\n",
    "protocol_frame_len_unique"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 166,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[518,\n",
       " 112,\n",
       " 1,\n",
       " 99,\n",
       " 3,\n",
       " 4,\n",
       " 1,\n",
       " 2,\n",
       " 19,\n",
       " 1,\n",
       " 6,\n",
       " 36,\n",
       " 2,\n",
       " 23,\n",
       " 2,\n",
       " 3,\n",
       " 2,\n",
       " 2,\n",
       " 1,\n",
       " 1,\n",
       " 3,\n",
       " 7,\n",
       " 4,\n",
       " 11,\n",
       " 1,\n",
       " 71,\n",
       " 3,\n",
       " 2,\n",
       " 1,\n",
       " 39,\n",
       " 18,\n",
       " 2,\n",
       " 1,\n",
       " 70,\n",
       " 2,\n",
       " 16,\n",
       " 1,\n",
       " 1,\n",
       " 8,\n",
       " 2,\n",
       " 1,\n",
       " 2,\n",
       " 1,\n",
       " 1,\n",
       " 3,\n",
       " 2,\n",
       " 1,\n",
       " 1,\n",
       " 1,\n",
       " 2,\n",
       " 2,\n",
       " 9,\n",
       " 1,\n",
       " 1,\n",
       " 2,\n",
       " 1,\n",
       " 1,\n",
       " 2,\n",
       " 2,\n",
       " 3,\n",
       " 1,\n",
       " 2,\n",
       " 2,\n",
       " 1,\n",
       " 2,\n",
       " 2,\n",
       " 5,\n",
       " 1,\n",
       " 2,\n",
       " 1,\n",
       " 2,\n",
       " 1,\n",
       " 1,\n",
       " None,\n",
       " None]"
      ]
     },
     "execution_count": 166,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "protocol_frame_len_unique_len"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[122684,\n",
       " 216966,\n",
       " 3707,\n",
       " 9993,\n",
       " 31082,\n",
       " 6450,\n",
       " 7870,\n",
       " 57474,\n",
       " 22747,\n",
       " 1640,\n",
       " 1286,\n",
       " 9803,\n",
       " 2853,\n",
       " 1730,\n",
       " 1329,\n",
       " 14418,\n",
       " 240,\n",
       " 582,\n",
       " 20,\n",
       " 510,\n",
       " 3382,\n",
       " 4751,\n",
       " 304,\n",
       " 132,\n",
       " 122,\n",
       " 621,\n",
       " 117,\n",
       " 1296,\n",
       " 336,\n",
       " 773,\n",
       " 781,\n",
       " 6,\n",
       " 355,\n",
       " 282,\n",
       " 124,\n",
       " 26,\n",
       " 2,\n",
       " 5,\n",
       " 34,\n",
       " 8,\n",
       " 12,\n",
       " 10,\n",
       " 2,\n",
       " 2,\n",
       " 6,\n",
       " 2,\n",
       " 14,\n",
       " 1,\n",
       " 9,\n",
       " 6,\n",
       " 10,\n",
       " 36,\n",
       " 4,\n",
       " 1,\n",
       " 4,\n",
       " 1,\n",
       " 1,\n",
       " 4,\n",
       " 2,\n",
       " 6,\n",
       " 1,\n",
       " 4,\n",
       " 4,\n",
       " 10,\n",
       " 9,\n",
       " 2,\n",
       " 14,\n",
       " 1,\n",
       " 2,\n",
       " 1,\n",
       " 8,\n",
       " 4,\n",
       " 1,\n",
       " [['156',\n",
       "   '284',\n",
       "   '60',\n",
       "   '172',\n",
       "   '160',\n",
       "   '123',\n",
       "   '95',\n",
       "   '140',\n",
       "   '135',\n",
       "   '139',\n",
       "   '425',\n",
       "   '211',\n",
       "   '224',\n",
       "   '97',\n",
       "   '583',\n",
       "   '1484',\n",
       "   '192',\n",
       "   '117',\n",
       "   '158',\n",
       "   '824',\n",
       "   '201',\n",
       "   '335',\n",
       "   '89',\n",
       "   '93',\n",
       "   '246',\n",
       "   '408',\n",
       "   '1514',\n",
       "   '264',\n",
       "   '316',\n",
       "   '359',\n",
       "   '471',\n",
       "   '571',\n",
       "   '380',\n",
       "   '107',\n",
       "   '396',\n",
       "   '368',\n",
       "   '219',\n",
       "   '91',\n",
       "   '103',\n",
       "   '300',\n",
       "   '336',\n",
       "   '357',\n",
       "   '1510',\n",
       "   '347',\n",
       "   '529',\n",
       "   '236',\n",
       "   '184',\n",
       "   '109',\n",
       "   '940',\n",
       "   '481',\n",
       "   '514',\n",
       "   '127',\n",
       "   '230',\n",
       "   '320',\n",
       "   '104',\n",
       "   '448',\n",
       "   '88',\n",
       "   '171',\n",
       "   '183',\n",
       "   '207',\n",
       "   '345',\n",
       "   '267',\n",
       "   '525',\n",
       "   '926',\n",
       "   '260',\n",
       "   '259',\n",
       "   '222',\n",
       "   '256',\n",
       "   '324',\n",
       "   '593',\n",
       "   '378',\n",
       "   '194',\n",
       "   '1051',\n",
       "   '308',\n",
       "   '1127',\n",
       "   '883',\n",
       "   '1367',\n",
       "   '1463',\n",
       "   '245',\n",
       "   '122',\n",
       "   '242',\n",
       "   '205',\n",
       "   '1481',\n",
       "   '162',\n",
       "   '203',\n",
       "   '263',\n",
       "   '987',\n",
       "   '976',\n",
       "   '1413',\n",
       "   '551',\n",
       "   '173',\n",
       "   '253',\n",
       "   '1469',\n",
       "   '1104',\n",
       "   '1472',\n",
       "   '124',\n",
       "   '967',\n",
       "   '1446',\n",
       "   '1468',\n",
       "   '1480',\n",
       "   '625',\n",
       "   '1258',\n",
       "   '636',\n",
       "   '984',\n",
       "   '645',\n",
       "   '962',\n",
       "   '1424',\n",
       "   '247',\n",
       "   '328',\n",
       "   '743',\n",
       "   '517',\n",
       "   '1337',\n",
       "   '268',\n",
       "   '901',\n",
       "   '543',\n",
       "   '145',\n",
       "   '1251',\n",
       "   '431',\n",
       "   '1253',\n",
       "   '228',\n",
       "   '1271',\n",
       "   '653',\n",
       "   '232',\n",
       "   '1263',\n",
       "   '296',\n",
       "   '534',\n",
       "   '144',\n",
       "   '851',\n",
       "   '459',\n",
       "   '429',\n",
       "   '825',\n",
       "   '1421',\n",
       "   '552',\n",
       "   '225',\n",
       "   '754',\n",
       "   '899',\n",
       "   '457',\n",
       "   '519',\n",
       "   '214',\n",
       "   '837',\n",
       "   '1363',\n",
       "   '229',\n",
       "   '248',\n",
       "   '567',\n",
       "   '310',\n",
       "   '266',\n",
       "   '843',\n",
       "   '451',\n",
       "   '399',\n",
       "   '817',\n",
       "   '1397',\n",
       "   '1296',\n",
       "   '243',\n",
       "   '622',\n",
       "   '287',\n",
       "   '856',\n",
       "   '639',\n",
       "   '244',\n",
       "   '249',\n",
       "   '815',\n",
       "   '254',\n",
       "   '360',\n",
       "   '748',\n",
       "   '1219',\n",
       "   '538',\n",
       "   '888',\n",
       "   '1476',\n",
       "   '112',\n",
       "   '1408',\n",
       "   '416',\n",
       "   '257',\n",
       "   '989',\n",
       "   '573',\n",
       "   '238',\n",
       "   '234',\n",
       "   '141',\n",
       "   '727',\n",
       "   '119',\n",
       "   '1303',\n",
       "   '535',\n",
       "   '759',\n",
       "   '239',\n",
       "   '855',\n",
       "   '895',\n",
       "   '999',\n",
       "   '220',\n",
       "   '714',\n",
       "   '521',\n",
       "   '569',\n",
       "   '92',\n",
       "   '85',\n",
       "   '371',\n",
       "   '180',\n",
       "   '99',\n",
       "   '397',\n",
       "   '206',\n",
       "   '251',\n",
       "   '274',\n",
       "   '548',\n",
       "   '182',\n",
       "   '189',\n",
       "   '365',\n",
       "   '1050',\n",
       "   '554',\n",
       "   '853',\n",
       "   '584',\n",
       "   '434',\n",
       "   '157',\n",
       "   '179',\n",
       "   '528',\n",
       "   '281',\n",
       "   '200',\n",
       "   '620',\n",
       "   '167',\n",
       "   '221',\n",
       "   '262',\n",
       "   '255',\n",
       "   '374',\n",
       "   '398',\n",
       "   '223',\n",
       "   '252',\n",
       "   '275',\n",
       "   '545',\n",
       "   '191',\n",
       "   '375',\n",
       "   '390',\n",
       "   '426',\n",
       "   '210',\n",
       "   '334',\n",
       "   '447',\n",
       "   '348',\n",
       "   '349',\n",
       "   '544',\n",
       "   '186',\n",
       "   '149',\n",
       "   '227',\n",
       "   '121',\n",
       "   '153',\n",
       "   '1340',\n",
       "   '511',\n",
       "   '1259',\n",
       "   '472',\n",
       "   '1099',\n",
       "   '218',\n",
       "   '1094',\n",
       "   '615',\n",
       "   '482',\n",
       "   '217',\n",
       "   '505',\n",
       "   '332',\n",
       "   '423',\n",
       "   '154',\n",
       "   '430',\n",
       "   '276',\n",
       "   '190',\n",
       "   '148',\n",
       "   '381',\n",
       "   '427',\n",
       "   '209',\n",
       "   '226',\n",
       "   '350',\n",
       "   '485',\n",
       "   '352',\n",
       "   '614',\n",
       "   '278',\n",
       "   '370',\n",
       "   '193',\n",
       "   '142',\n",
       "   '208',\n",
       "   '199',\n",
       "   '1029',\n",
       "   '111',\n",
       "   '204',\n",
       "   '164',\n",
       "   '110',\n",
       "   '250',\n",
       "   '460',\n",
       "   '314',\n",
       "   '285',\n",
       "   '1423',\n",
       "   '966',\n",
       "   '433',\n",
       "   '1053',\n",
       "   '292',\n",
       "   '361',\n",
       "   '174',\n",
       "   '916',\n",
       "   '452',\n",
       "   '711',\n",
       "   '861',\n",
       "   '588',\n",
       "   '500',\n",
       "   '647',\n",
       "   '963',\n",
       "   '195',\n",
       "   '473',\n",
       "   '155',\n",
       "   '132',\n",
       "   '894',\n",
       "   '602',\n",
       "   '927',\n",
       "   '282',\n",
       "   '1483',\n",
       "   '241',\n",
       "   '342',\n",
       "   '541',\n",
       "   '152',\n",
       "   '130',\n",
       "   '1208',\n",
       "   '213',\n",
       "   '503',\n",
       "   '810',\n",
       "   '358',\n",
       "   '237',\n",
       "   '1508',\n",
       "   '461',\n",
       "   '782',\n",
       "   '356',\n",
       "   '1228',\n",
       "   '591',\n",
       "   '1254',\n",
       "   '1450',\n",
       "   '491',\n",
       "   '857',\n",
       "   '100',\n",
       "   '439',\n",
       "   '159',\n",
       "   '632',\n",
       "   '944',\n",
       "   '504',\n",
       "   '972',\n",
       "   '353',\n",
       "   '125',\n",
       "   '1275',\n",
       "   '313',\n",
       "   '291',\n",
       "   '355',\n",
       "   '108',\n",
       "   '1273',\n",
       "   '302',\n",
       "   '113',\n",
       "   '131',\n",
       "   '1342',\n",
       "   '1173',\n",
       "   '518',\n",
       "   '609',\n",
       "   '1121',\n",
       "   '886',\n",
       "   '725',\n",
       "   '118',\n",
       "   '143',\n",
       "   '134',\n",
       "   '756',\n",
       "   '75',\n",
       "   '722',\n",
       "   '943',\n",
       "   '1222',\n",
       "   '1260',\n",
       "   '986',\n",
       "   '626',\n",
       "   '351',\n",
       "   '598',\n",
       "   '648',\n",
       "   '261',\n",
       "   '333',\n",
       "   '464',\n",
       "   '432',\n",
       "   '546',\n",
       "   '379',\n",
       "   '147',\n",
       "   '303',\n",
       "   '120',\n",
       "   '931',\n",
       "   '523',\n",
       "   '550',\n",
       "   '1034',\n",
       "   '315',\n",
       "   '524',\n",
       "   '90',\n",
       "   '337',\n",
       "   '522',\n",
       "   '558',\n",
       "   '814',\n",
       "   '480',\n",
       "   '1130',\n",
       "   '1166',\n",
       "   '294',\n",
       "   '1436',\n",
       "   '1155',\n",
       "   '317',\n",
       "   '402',\n",
       "   '377',\n",
       "   '185',\n",
       "   '290',\n",
       "   '575',\n",
       "   '446',\n",
       "   '231',\n",
       "   '406',\n",
       "   '772',\n",
       "   '570',\n",
       "   '163',\n",
       "   '331',\n",
       "   '306',\n",
       "   '202',\n",
       "   '312',\n",
       "   '418',\n",
       "   '1326',\n",
       "   '384',\n",
       "   '618',\n",
       "   '1140',\n",
       "   '586',\n",
       "   '1044',\n",
       "   '216',\n",
       "   '94',\n",
       "   '376',\n",
       "   '1256',\n",
       "   '630',\n",
       "   '496',\n",
       "   '702',\n",
       "   '616',\n",
       "   '1122',\n",
       "   '1439',\n",
       "   '115',\n",
       "   '319',\n",
       "   '270',\n",
       "   '151',\n",
       "   '96',\n",
       "   '1055',\n",
       "   '835',\n",
       "   '885',\n",
       "   '483',\n",
       "   '456',\n",
       "   '925',\n",
       "   '1344',\n",
       "   '309',\n",
       "   '1455',\n",
       "   '170',\n",
       "   '176',\n",
       "   '1056',\n",
       "   '72',\n",
       "   '951',\n",
       "   '717',\n",
       "   '1461',\n",
       "   '175',\n",
       "   '597',\n",
       "   '674',\n",
       "   '903',\n",
       "   '420',\n",
       "   '1169',\n",
       "   '1255',\n",
       "   '1200',\n",
       "   '364',\n",
       "   '1415',\n",
       "   '832',\n",
       "   '1304',\n",
       "   '474',\n",
       "   '938',\n",
       "   '670',\n",
       "   '395',\n",
       "   '1038',\n",
       "   '685',\n",
       "   '937',\n",
       "   '549',\n",
       "   '177',\n",
       "   '513',\n",
       "   '1047',\n",
       "   '1032',\n",
       "   '492',\n",
       "   '1006',\n",
       "   '212',\n",
       "   '338',\n",
       "   '61',\n",
       "   '271',\n",
       "   '385',\n",
       "   '166',\n",
       "   '84',\n",
       "   '477',\n",
       "   '323',\n",
       "   '424',\n",
       "   '272',\n",
       "   '311',\n",
       "   '327',\n",
       "   '1250',\n",
       "   '1398',\n",
       "   '1031',\n",
       "   '566',\n",
       "   '1054',\n",
       "   '872',\n",
       "   '539',\n",
       "   '790',\n",
       "   '596',\n",
       "   '165',\n",
       "   '579',\n",
       "   '1175',\n",
       "   '391',\n",
       "   '809',\n",
       "   '868',\n",
       "   '792',\n",
       "   '392',\n",
       "   '542',\n",
       "   '1247',\n",
       "   '441',\n",
       "   '1464',\n",
       "   '1316',\n",
       "   '1105',\n",
       "   '1262',\n",
       "   '1317',\n",
       "   '1444',\n",
       "   '476',\n",
       "   '443',\n",
       "   '1430',\n",
       "   '339',\n",
       "   '559',\n",
       "   '198',\n",
       "   '178',\n",
       "   '362',\n",
       "   '527',\n",
       "   '215'],\n",
       "  ['66',\n",
       "   '54',\n",
       "   '188',\n",
       "   '204',\n",
       "   '60',\n",
       "   '140',\n",
       "   '74',\n",
       "   '252',\n",
       "   '1236',\n",
       "   '135',\n",
       "   '78',\n",
       "   '95',\n",
       "   '97',\n",
       "   '1484',\n",
       "   '1326',\n",
       "   '1514',\n",
       "   '62',\n",
       "   '58',\n",
       "   '265',\n",
       "   '103',\n",
       "   '1510',\n",
       "   '172',\n",
       "   '89',\n",
       "   '93',\n",
       "   '109',\n",
       "   '104',\n",
       "   '957',\n",
       "   '105',\n",
       "   '1266',\n",
       "   '1414',\n",
       "   '1424',\n",
       "   '551',\n",
       "   '517',\n",
       "   '452',\n",
       "   '428',\n",
       "   '666',\n",
       "   '799',\n",
       "   '451',\n",
       "   '354',\n",
       "   '748',\n",
       "   '121',\n",
       "   '759',\n",
       "   '160',\n",
       "   '416',\n",
       "   '383',\n",
       "   '70',\n",
       "   '146',\n",
       "   '91',\n",
       "   '408',\n",
       "   '264',\n",
       "   '268',\n",
       "   '199',\n",
       "   '267',\n",
       "   '996',\n",
       "   '332',\n",
       "   '460',\n",
       "   '247',\n",
       "   '359',\n",
       "   '348',\n",
       "   '349',\n",
       "   '256',\n",
       "   '427',\n",
       "   '248',\n",
       "   '153',\n",
       "   '218',\n",
       "   '350',\n",
       "   '345',\n",
       "   '947',\n",
       "   '173',\n",
       "   '967',\n",
       "   '1222',\n",
       "   '110',\n",
       "   '254',\n",
       "   '217',\n",
       "   '90',\n",
       "   '550',\n",
       "   '347',\n",
       "   '253',\n",
       "   '566',\n",
       "   '241',\n",
       "   '123',\n",
       "   '330',\n",
       "   '333',\n",
       "   '292',\n",
       "   '86',\n",
       "   '315',\n",
       "   '552',\n",
       "   '910',\n",
       "   '92',\n",
       "   '337',\n",
       "   '219',\n",
       "   '856',\n",
       "   '600',\n",
       "   '386',\n",
       "   '1056',\n",
       "   '760',\n",
       "   '118',\n",
       "   '521',\n",
       "   '119',\n",
       "   '131',\n",
       "   '111',\n",
       "   '503',\n",
       "   '837',\n",
       "   '94',\n",
       "   '156',\n",
       "   '351',\n",
       "   '335',\n",
       "   '392',\n",
       "   '579',\n",
       "   '198',\n",
       "   '255',\n",
       "   '423'],\n",
       "  ['90'],\n",
       "  ['268',\n",
       "   '75',\n",
       "   '91',\n",
       "   '288',\n",
       "   '103',\n",
       "   '76',\n",
       "   '148',\n",
       "   '80',\n",
       "   '78',\n",
       "   '82',\n",
       "   '92',\n",
       "   '88',\n",
       "   '326',\n",
       "   '332',\n",
       "   '79',\n",
       "   '284',\n",
       "   '72',\n",
       "   '530',\n",
       "   '74',\n",
       "   '443',\n",
       "   '89',\n",
       "   '217',\n",
       "   '95',\n",
       "   '86',\n",
       "   '453',\n",
       "   '104',\n",
       "   '170',\n",
       "   '542',\n",
       "   '136',\n",
       "   '405',\n",
       "   '545',\n",
       "   '395',\n",
       "   '526',\n",
       "   '96',\n",
       "   '418',\n",
       "   '153',\n",
       "   '157',\n",
       "   '554',\n",
       "   '83',\n",
       "   '499',\n",
       "   '276',\n",
       "   '280',\n",
       "   '184',\n",
       "   '147',\n",
       "   '143',\n",
       "   '127',\n",
       "   '151',\n",
       "   '81',\n",
       "   '156',\n",
       "   '85',\n",
       "   '160',\n",
       "   '173',\n",
       "   '549',\n",
       "   '533',\n",
       "   '105',\n",
       "   '205',\n",
       "   '529',\n",
       "   '483',\n",
       "   '467',\n",
       "   '87',\n",
       "   '246',\n",
       "   '536',\n",
       "   '313',\n",
       "   '247',\n",
       "   '449',\n",
       "   '398',\n",
       "   '73',\n",
       "   '301',\n",
       "   '139',\n",
       "   '285',\n",
       "   '538',\n",
       "   '431',\n",
       "   '322',\n",
       "   '375',\n",
       "   '505',\n",
       "   '164',\n",
       "   '115',\n",
       "   '543',\n",
       "   '84',\n",
       "   '310',\n",
       "   '546',\n",
       "   '248',\n",
       "   '116',\n",
       "   '373',\n",
       "   '489',\n",
       "   '77',\n",
       "   '108',\n",
       "   '244',\n",
       "   '290',\n",
       "   '541',\n",
       "   '389',\n",
       "   '528',\n",
       "   '294',\n",
       "   '68',\n",
       "   '227',\n",
       "   '234',\n",
       "   '256',\n",
       "   '346',\n",
       "   '547'],\n",
       "  ['98', '118', '62'],\n",
       "  ['201', '191', '55', '306'],\n",
       "  ['43'],\n",
       "  ['42', '60'],\n",
       "  ['421',\n",
       "   '493',\n",
       "   '489',\n",
       "   '469',\n",
       "   '501',\n",
       "   '483',\n",
       "   '485',\n",
       "   '143',\n",
       "   '381',\n",
       "   '163',\n",
       "   '148',\n",
       "   '354',\n",
       "   '352',\n",
       "   '376',\n",
       "   '384',\n",
       "   '382',\n",
       "   '386',\n",
       "   '394',\n",
       "   '390'],\n",
       "  ['174'],\n",
       "  ['214', '146', '222', '114', '206', '170'],\n",
       "  ['70',\n",
       "   '68',\n",
       "   '60',\n",
       "   '78',\n",
       "   '106',\n",
       "   '62',\n",
       "   '58',\n",
       "   '160',\n",
       "   '315',\n",
       "   '201',\n",
       "   '242',\n",
       "   '199',\n",
       "   '158',\n",
       "   '580',\n",
       "   '732',\n",
       "   '108',\n",
       "   '285',\n",
       "   '455',\n",
       "   '114',\n",
       "   '176',\n",
       "   '672',\n",
       "   '284',\n",
       "   '234',\n",
       "   '211',\n",
       "   '192',\n",
       "   '215',\n",
       "   '579',\n",
       "   '124',\n",
       "   '111',\n",
       "   '509',\n",
       "   '109',\n",
       "   '402',\n",
       "   '733',\n",
       "   '186',\n",
       "   '281',\n",
       "   '1514'],\n",
       "  ['46', '54'],\n",
       "  ['252',\n",
       "   '91',\n",
       "   '162',\n",
       "   '349',\n",
       "   '254',\n",
       "   '149',\n",
       "   '277',\n",
       "   '272',\n",
       "   '249',\n",
       "   '288',\n",
       "   '282',\n",
       "   '285',\n",
       "   '299',\n",
       "   '354',\n",
       "   '311',\n",
       "   '314',\n",
       "   '411',\n",
       "   '383',\n",
       "   '267',\n",
       "   '453',\n",
       "   '79',\n",
       "   '416',\n",
       "   '369'],\n",
       "  ['1236', '386'],\n",
       "  ['86', '90', '110'],\n",
       "  ['251', '257'],\n",
       "  ['785', '753'],\n",
       "  ['689'],\n",
       "  ['20'],\n",
       "  ['139', '113', '135'],\n",
       "  ['350', '342', '349', '322', '590', '347', '355'],\n",
       "  ['198', '86', '78', '70'],\n",
       "  ['188', '204', '140', '105', '70', '259', '198', '605', '181', '95', '606'],\n",
       "  ['1266'],\n",
       "  ['81',\n",
       "   '176',\n",
       "   '362',\n",
       "   '1514',\n",
       "   '103',\n",
       "   '90',\n",
       "   '1266',\n",
       "   '1036',\n",
       "   '998',\n",
       "   '1295',\n",
       "   '264',\n",
       "   '666',\n",
       "   '742',\n",
       "   '374',\n",
       "   '375',\n",
       "   '1484',\n",
       "   '1425',\n",
       "   '1060',\n",
       "   '1510',\n",
       "   '706',\n",
       "   '537',\n",
       "   '675',\n",
       "   '835',\n",
       "   '1132',\n",
       "   '485',\n",
       "   '594',\n",
       "   '717',\n",
       "   '1348',\n",
       "   '393',\n",
       "   '656',\n",
       "   '861',\n",
       "   '1285',\n",
       "   '929',\n",
       "   '1016',\n",
       "   '920',\n",
       "   '1039',\n",
       "   '699',\n",
       "   '1267',\n",
       "   '1477',\n",
       "   '601',\n",
       "   '627',\n",
       "   '810',\n",
       "   '933',\n",
       "   '862',\n",
       "   '990',\n",
       "   '500',\n",
       "   '352',\n",
       "   '1084',\n",
       "   '414',\n",
       "   '823',\n",
       "   '586',\n",
       "   '740',\n",
       "   '634',\n",
       "   '286',\n",
       "   '1196',\n",
       "   '1110',\n",
       "   '1214',\n",
       "   '1070',\n",
       "   '324',\n",
       "   '1350',\n",
       "   '498',\n",
       "   '1262',\n",
       "   '932',\n",
       "   '1494',\n",
       "   '926',\n",
       "   '170',\n",
       "   '1380',\n",
       "   '194',\n",
       "   '542',\n",
       "   '305',\n",
       "   '283'],\n",
       "  ['109', '427', '1469'],\n",
       "  ['70', '110'],\n",
       "  ['98'],\n",
       "  ['265',\n",
       "   '248',\n",
       "   '339',\n",
       "   '287',\n",
       "   '458',\n",
       "   '387',\n",
       "   '459',\n",
       "   '338',\n",
       "   '298',\n",
       "   '460',\n",
       "   '263',\n",
       "   '256',\n",
       "   '259',\n",
       "   '264',\n",
       "   '262',\n",
       "   '255',\n",
       "   '257',\n",
       "   '461',\n",
       "   '267',\n",
       "   '268',\n",
       "   '266',\n",
       "   '270',\n",
       "   '269',\n",
       "   '237',\n",
       "   '392',\n",
       "   '200',\n",
       "   '301',\n",
       "   '284',\n",
       "   '276',\n",
       "   '457',\n",
       "   '271',\n",
       "   '272',\n",
       "   '273',\n",
       "   '275',\n",
       "   '274',\n",
       "   '261',\n",
       "   '258',\n",
       "   '288',\n",
       "   '260'],\n",
       "  ['331',\n",
       "   '392',\n",
       "   '248',\n",
       "   '289',\n",
       "   '545',\n",
       "   '993',\n",
       "   '650',\n",
       "   '252',\n",
       "   '379',\n",
       "   '247',\n",
       "   '246',\n",
       "   '255',\n",
       "   '347',\n",
       "   '492',\n",
       "   '898',\n",
       "   '431',\n",
       "   '1337',\n",
       "   '928'],\n",
       "  ['252', '1236'],\n",
       "  ['110'],\n",
       "  ['98',\n",
       "   '110',\n",
       "   '286',\n",
       "   '313',\n",
       "   '308',\n",
       "   '565',\n",
       "   '109',\n",
       "   '268',\n",
       "   '106',\n",
       "   '282',\n",
       "   '96',\n",
       "   '277',\n",
       "   '97',\n",
       "   '262',\n",
       "   '95',\n",
       "   '274',\n",
       "   '104',\n",
       "   '503',\n",
       "   '107',\n",
       "   '525',\n",
       "   '99',\n",
       "   '333',\n",
       "   '332',\n",
       "   '251',\n",
       "   '301',\n",
       "   '94',\n",
       "   '422',\n",
       "   '435',\n",
       "   '457',\n",
       "   '356',\n",
       "   '292',\n",
       "   '304',\n",
       "   '103',\n",
       "   '495',\n",
       "   '444',\n",
       "   '451',\n",
       "   '522',\n",
       "   '101',\n",
       "   '218',\n",
       "   '105',\n",
       "   '551',\n",
       "   '267',\n",
       "   '559',\n",
       "   '108',\n",
       "   '476',\n",
       "   '131',\n",
       "   '460',\n",
       "   '349',\n",
       "   '296',\n",
       "   '115',\n",
       "   '511',\n",
       "   '93',\n",
       "   '258',\n",
       "   '100',\n",
       "   '317',\n",
       "   '300',\n",
       "   '355',\n",
       "   '485',\n",
       "   '348',\n",
       "   '520',\n",
       "   '354',\n",
       "   '102',\n",
       "   '365',\n",
       "   '297',\n",
       "   '373',\n",
       "   '364',\n",
       "   '372',\n",
       "   '269',\n",
       "   '556',\n",
       "   '294'],\n",
       "  ['910', '880'],\n",
       "  ['1236',\n",
       "   '1209',\n",
       "   '407',\n",
       "   '394',\n",
       "   '576',\n",
       "   '575',\n",
       "   '562',\n",
       "   '577',\n",
       "   '563',\n",
       "   '1208',\n",
       "   '409',\n",
       "   '1207',\n",
       "   '1223',\n",
       "   '1326',\n",
       "   '396',\n",
       "   '1237'],\n",
       "  ['1266'],\n",
       "  ['1514'],\n",
       "  ['856', '796', '770', '783', '1514', '944', '759', '843'],\n",
       "  ['83', '852'],\n",
       "  ['38'],\n",
       "  ['1069', '1205'],\n",
       "  ['1234'],\n",
       "  ['1029'],\n",
       "  ['759', '786', '1049'],\n",
       "  ['252', '1236'],\n",
       "  ['743'],\n",
       "  ['616'],\n",
       "  ['1215'],\n",
       "  ['252', '1236'],\n",
       "  ['177', '175'],\n",
       "  ['394', '250', '122', '506', '1214', '238', '138', '282', '170'],\n",
       "  ['1514'],\n",
       "  ['230'],\n",
       "  ['252', '1236'],\n",
       "  ['880'],\n",
       "  ['643'],\n",
       "  ['252', '1236'],\n",
       "  ['252', '1236'],\n",
       "  ['672', '598', '440'],\n",
       "  ['59'],\n",
       "  ['252', '1236'],\n",
       "  ['994', '506'],\n",
       "  ['71'],\n",
       "  ['198', '150'],\n",
       "  ['252', '1236'],\n",
       "  ['1392', '77', '83', '80', '72'],\n",
       "  ['646'],\n",
       "  ['252', '1236'],\n",
       "  ['705'],\n",
       "  ['252', '1236'],\n",
       "  ['435'],\n",
       "  ['59']],\n",
       " [['156',\n",
       "   '284',\n",
       "   '60',\n",
       "   '172',\n",
       "   '160',\n",
       "   '123',\n",
       "   '95',\n",
       "   '140',\n",
       "   '135',\n",
       "   '139',\n",
       "   '425',\n",
       "   '211',\n",
       "   '224',\n",
       "   '97',\n",
       "   '583',\n",
       "   '1484',\n",
       "   '192',\n",
       "   '117',\n",
       "   '158',\n",
       "   '824',\n",
       "   '201',\n",
       "   '335',\n",
       "   '89',\n",
       "   '93',\n",
       "   '246',\n",
       "   '408',\n",
       "   '1514',\n",
       "   '264',\n",
       "   '316',\n",
       "   '359',\n",
       "   '471',\n",
       "   '571',\n",
       "   '380',\n",
       "   '107',\n",
       "   '396',\n",
       "   '368',\n",
       "   '219',\n",
       "   '91',\n",
       "   '103',\n",
       "   '300',\n",
       "   '336',\n",
       "   '357',\n",
       "   '1510',\n",
       "   '347',\n",
       "   '529',\n",
       "   '236',\n",
       "   '184',\n",
       "   '109',\n",
       "   '940',\n",
       "   '481',\n",
       "   '514',\n",
       "   '127',\n",
       "   '230',\n",
       "   '320',\n",
       "   '104',\n",
       "   '448',\n",
       "   '88',\n",
       "   '171',\n",
       "   '183',\n",
       "   '207',\n",
       "   '345',\n",
       "   '267',\n",
       "   '525',\n",
       "   '926',\n",
       "   '260',\n",
       "   '259',\n",
       "   '222',\n",
       "   '256',\n",
       "   '324',\n",
       "   '593',\n",
       "   '378',\n",
       "   '194',\n",
       "   '1051',\n",
       "   '308',\n",
       "   '1127',\n",
       "   '883',\n",
       "   '1367',\n",
       "   '1463',\n",
       "   '245',\n",
       "   '122',\n",
       "   '242',\n",
       "   '205',\n",
       "   '1481',\n",
       "   '162',\n",
       "   '203',\n",
       "   '263',\n",
       "   '987',\n",
       "   '976',\n",
       "   '1413',\n",
       "   '551',\n",
       "   '173',\n",
       "   '253',\n",
       "   '1469',\n",
       "   '1104',\n",
       "   '1472',\n",
       "   '124',\n",
       "   '967',\n",
       "   '1446',\n",
       "   '1468',\n",
       "   '1480',\n",
       "   '625',\n",
       "   '1258',\n",
       "   '636',\n",
       "   '984',\n",
       "   '645',\n",
       "   '962',\n",
       "   '1424',\n",
       "   '247',\n",
       "   '328',\n",
       "   '743',\n",
       "   '517',\n",
       "   '1337',\n",
       "   '268',\n",
       "   '901',\n",
       "   '543',\n",
       "   '145',\n",
       "   '1251',\n",
       "   '431',\n",
       "   '1253',\n",
       "   '228',\n",
       "   '1271',\n",
       "   '653',\n",
       "   '232',\n",
       "   '1263',\n",
       "   '296',\n",
       "   '534',\n",
       "   '144',\n",
       "   '851',\n",
       "   '459',\n",
       "   '429',\n",
       "   '825',\n",
       "   '1421',\n",
       "   '552',\n",
       "   '225',\n",
       "   '754',\n",
       "   '899',\n",
       "   '457',\n",
       "   '519',\n",
       "   '214',\n",
       "   '837',\n",
       "   '1363',\n",
       "   '229',\n",
       "   '248',\n",
       "   '567',\n",
       "   '310',\n",
       "   '266',\n",
       "   '843',\n",
       "   '451',\n",
       "   '399',\n",
       "   '817',\n",
       "   '1397',\n",
       "   '1296',\n",
       "   '243',\n",
       "   '622',\n",
       "   '287',\n",
       "   '856',\n",
       "   '639',\n",
       "   '244',\n",
       "   '249',\n",
       "   '815',\n",
       "   '254',\n",
       "   '360',\n",
       "   '748',\n",
       "   '1219',\n",
       "   '538',\n",
       "   '888',\n",
       "   '1476',\n",
       "   '112',\n",
       "   '1408',\n",
       "   '416',\n",
       "   '257',\n",
       "   '989',\n",
       "   '573',\n",
       "   '238',\n",
       "   '234',\n",
       "   '141',\n",
       "   '727',\n",
       "   '119',\n",
       "   '1303',\n",
       "   '535',\n",
       "   '759',\n",
       "   '239',\n",
       "   '855',\n",
       "   '895',\n",
       "   '999',\n",
       "   '220',\n",
       "   '714',\n",
       "   '521',\n",
       "   '569',\n",
       "   '92',\n",
       "   '85',\n",
       "   '371',\n",
       "   '180',\n",
       "   '99',\n",
       "   '397',\n",
       "   '206',\n",
       "   '251',\n",
       "   '274',\n",
       "   '548',\n",
       "   '182',\n",
       "   '189',\n",
       "   '365',\n",
       "   '1050',\n",
       "   '554',\n",
       "   '853',\n",
       "   '584',\n",
       "   '434',\n",
       "   '157',\n",
       "   '179',\n",
       "   '528',\n",
       "   '281',\n",
       "   '200',\n",
       "   '620',\n",
       "   '167',\n",
       "   '221',\n",
       "   '262',\n",
       "   '255',\n",
       "   '374',\n",
       "   '398',\n",
       "   '223',\n",
       "   '252',\n",
       "   '275',\n",
       "   '545',\n",
       "   '191',\n",
       "   '375',\n",
       "   '390',\n",
       "   '426',\n",
       "   '210',\n",
       "   '334',\n",
       "   '447',\n",
       "   '348',\n",
       "   '349',\n",
       "   '544',\n",
       "   '186',\n",
       "   '149',\n",
       "   '227',\n",
       "   '121',\n",
       "   '153',\n",
       "   '1340',\n",
       "   '511',\n",
       "   '1259',\n",
       "   '472',\n",
       "   '1099',\n",
       "   '218',\n",
       "   '1094',\n",
       "   '615',\n",
       "   '482',\n",
       "   '217',\n",
       "   '505',\n",
       "   '332',\n",
       "   '423',\n",
       "   '154',\n",
       "   '430',\n",
       "   '276',\n",
       "   '190',\n",
       "   '148',\n",
       "   '381',\n",
       "   '427',\n",
       "   '209',\n",
       "   '226',\n",
       "   '350',\n",
       "   '485',\n",
       "   '352',\n",
       "   '614',\n",
       "   '278',\n",
       "   '370',\n",
       "   '193',\n",
       "   '142',\n",
       "   '208',\n",
       "   '199',\n",
       "   '1029',\n",
       "   '111',\n",
       "   '204',\n",
       "   '164',\n",
       "   '110',\n",
       "   '250',\n",
       "   '460',\n",
       "   '314',\n",
       "   '285',\n",
       "   '1423',\n",
       "   '966',\n",
       "   '433',\n",
       "   '1053',\n",
       "   '292',\n",
       "   '361',\n",
       "   '174',\n",
       "   '916',\n",
       "   '452',\n",
       "   '711',\n",
       "   '861',\n",
       "   '588',\n",
       "   '500',\n",
       "   '647',\n",
       "   '963',\n",
       "   '195',\n",
       "   '473',\n",
       "   '155',\n",
       "   '132',\n",
       "   '894',\n",
       "   '602',\n",
       "   '927',\n",
       "   '282',\n",
       "   '1483',\n",
       "   '241',\n",
       "   '342',\n",
       "   '541',\n",
       "   '152',\n",
       "   '130',\n",
       "   '1208',\n",
       "   '213',\n",
       "   '503',\n",
       "   '810',\n",
       "   '358',\n",
       "   '237',\n",
       "   '1508',\n",
       "   '461',\n",
       "   '782',\n",
       "   '356',\n",
       "   '1228',\n",
       "   '591',\n",
       "   '1254',\n",
       "   '1450',\n",
       "   '491',\n",
       "   '857',\n",
       "   '100',\n",
       "   '439',\n",
       "   '159',\n",
       "   '632',\n",
       "   '944',\n",
       "   '504',\n",
       "   '972',\n",
       "   '353',\n",
       "   '125',\n",
       "   '1275',\n",
       "   '313',\n",
       "   '291',\n",
       "   '355',\n",
       "   '108',\n",
       "   '1273',\n",
       "   '302',\n",
       "   '113',\n",
       "   '131',\n",
       "   '1342',\n",
       "   '1173',\n",
       "   '518',\n",
       "   '609',\n",
       "   '1121',\n",
       "   '886',\n",
       "   '725',\n",
       "   '118',\n",
       "   '143',\n",
       "   '134',\n",
       "   '756',\n",
       "   '75',\n",
       "   '722',\n",
       "   '943',\n",
       "   '1222',\n",
       "   '1260',\n",
       "   '986',\n",
       "   '626',\n",
       "   '351',\n",
       "   '598',\n",
       "   '648',\n",
       "   '261',\n",
       "   '333',\n",
       "   '464',\n",
       "   '432',\n",
       "   '546',\n",
       "   '379',\n",
       "   '147',\n",
       "   '303',\n",
       "   '120',\n",
       "   '931',\n",
       "   '523',\n",
       "   '550',\n",
       "   '1034',\n",
       "   '315',\n",
       "   '524',\n",
       "   '90',\n",
       "   '337',\n",
       "   '522',\n",
       "   '558',\n",
       "   '814',\n",
       "   '480',\n",
       "   '1130',\n",
       "   '1166',\n",
       "   '294',\n",
       "   '1436',\n",
       "   '1155',\n",
       "   '317',\n",
       "   '402',\n",
       "   '377',\n",
       "   '185',\n",
       "   '290',\n",
       "   '575',\n",
       "   '446',\n",
       "   '231',\n",
       "   '406',\n",
       "   '772',\n",
       "   '570',\n",
       "   '163',\n",
       "   '331',\n",
       "   '306',\n",
       "   '202',\n",
       "   '312',\n",
       "   '418',\n",
       "   '1326',\n",
       "   '384',\n",
       "   '618',\n",
       "   '1140',\n",
       "   '586',\n",
       "   '1044',\n",
       "   '216',\n",
       "   '94',\n",
       "   '376',\n",
       "   '1256',\n",
       "   '630',\n",
       "   '496',\n",
       "   '702',\n",
       "   '616',\n",
       "   '1122',\n",
       "   '1439',\n",
       "   '115',\n",
       "   '319',\n",
       "   '270',\n",
       "   '151',\n",
       "   '96',\n",
       "   '1055',\n",
       "   '835',\n",
       "   '885',\n",
       "   '483',\n",
       "   '456',\n",
       "   '925',\n",
       "   '1344',\n",
       "   '309',\n",
       "   '1455',\n",
       "   '170',\n",
       "   '176',\n",
       "   '1056',\n",
       "   '72',\n",
       "   '951',\n",
       "   '717',\n",
       "   '1461',\n",
       "   '175',\n",
       "   '597',\n",
       "   '674',\n",
       "   '903',\n",
       "   '420',\n",
       "   '1169',\n",
       "   '1255',\n",
       "   '1200',\n",
       "   '364',\n",
       "   '1415',\n",
       "   '832',\n",
       "   '1304',\n",
       "   '474',\n",
       "   '938',\n",
       "   '670',\n",
       "   '395',\n",
       "   '1038',\n",
       "   '685',\n",
       "   '937',\n",
       "   '549',\n",
       "   '177',\n",
       "   '513',\n",
       "   '1047',\n",
       "   '1032',\n",
       "   '492',\n",
       "   '1006',\n",
       "   '212',\n",
       "   '338',\n",
       "   '61',\n",
       "   '271',\n",
       "   '385',\n",
       "   '166',\n",
       "   '84',\n",
       "   '477',\n",
       "   '323',\n",
       "   '424',\n",
       "   '272',\n",
       "   '311',\n",
       "   '327',\n",
       "   '1250',\n",
       "   '1398',\n",
       "   '1031',\n",
       "   '566',\n",
       "   '1054',\n",
       "   '872',\n",
       "   '539',\n",
       "   '790',\n",
       "   '596',\n",
       "   '165',\n",
       "   '579',\n",
       "   '1175',\n",
       "   '391',\n",
       "   '809',\n",
       "   '868',\n",
       "   '792',\n",
       "   '392',\n",
       "   '542',\n",
       "   '1247',\n",
       "   '441',\n",
       "   '1464',\n",
       "   '1316',\n",
       "   '1105',\n",
       "   '1262',\n",
       "   '1317',\n",
       "   '1444',\n",
       "   '476',\n",
       "   '443',\n",
       "   '1430',\n",
       "   '339',\n",
       "   '559',\n",
       "   '198',\n",
       "   '178',\n",
       "   '362',\n",
       "   '527',\n",
       "   '215'],\n",
       "  ['66',\n",
       "   '54',\n",
       "   '188',\n",
       "   '204',\n",
       "   '60',\n",
       "   '140',\n",
       "   '74',\n",
       "   '252',\n",
       "   '1236',\n",
       "   '135',\n",
       "   '78',\n",
       "   '95',\n",
       "   '97',\n",
       "   '1484',\n",
       "   '1326',\n",
       "   '1514',\n",
       "   '62',\n",
       "   '58',\n",
       "   '265',\n",
       "   '103',\n",
       "   '1510',\n",
       "   '172',\n",
       "   '89',\n",
       "   '93',\n",
       "   '109',\n",
       "   '104',\n",
       "   '957',\n",
       "   '105',\n",
       "   '1266',\n",
       "   '1414',\n",
       "   '1424',\n",
       "   '551',\n",
       "   '517',\n",
       "   '452',\n",
       "   '428',\n",
       "   '666',\n",
       "   '799',\n",
       "   '451',\n",
       "   '354',\n",
       "   '748',\n",
       "   '121',\n",
       "   '759',\n",
       "   '160',\n",
       "   '416',\n",
       "   '383',\n",
       "   '70',\n",
       "   '146',\n",
       "   '91',\n",
       "   '408',\n",
       "   '264',\n",
       "   '268',\n",
       "   '199',\n",
       "   '267',\n",
       "   '996',\n",
       "   '332',\n",
       "   '460',\n",
       "   '247',\n",
       "   '359',\n",
       "   '348',\n",
       "   '349',\n",
       "   '256',\n",
       "   '427',\n",
       "   '248',\n",
       "   '153',\n",
       "   '218',\n",
       "   '350',\n",
       "   '345',\n",
       "   '947',\n",
       "   '173',\n",
       "   '967',\n",
       "   '1222',\n",
       "   '110',\n",
       "   '254',\n",
       "   '217',\n",
       "   '90',\n",
       "   '550',\n",
       "   '347',\n",
       "   '253',\n",
       "   '566',\n",
       "   '241',\n",
       "   '123',\n",
       "   '330',\n",
       "   '333',\n",
       "   '292',\n",
       "   '86',\n",
       "   '315',\n",
       "   '552',\n",
       "   '910',\n",
       "   '92',\n",
       "   '337',\n",
       "   '219',\n",
       "   '856',\n",
       "   '600',\n",
       "   '386',\n",
       "   '1056',\n",
       "   '760',\n",
       "   '118',\n",
       "   '521',\n",
       "   '119',\n",
       "   '131',\n",
       "   '111',\n",
       "   '503',\n",
       "   '837',\n",
       "   '94',\n",
       "   '156',\n",
       "   '351',\n",
       "   '335',\n",
       "   '392',\n",
       "   '579',\n",
       "   '198',\n",
       "   '255',\n",
       "   '423'],\n",
       "  ['90'],\n",
       "  ['268',\n",
       "   '75',\n",
       "   '91',\n",
       "   '288',\n",
       "   '103',\n",
       "   '76',\n",
       "   '148',\n",
       "   '80',\n",
       "   '78',\n",
       "   '82',\n",
       "   '92',\n",
       "   '88',\n",
       "   '326',\n",
       "   '332',\n",
       "   '79',\n",
       "   '284',\n",
       "   '72',\n",
       "   '530',\n",
       "   '74',\n",
       "   '443',\n",
       "   '89',\n",
       "   '217',\n",
       "   '95',\n",
       "   '86',\n",
       "   '453',\n",
       "   '104',\n",
       "   '170',\n",
       "   '542',\n",
       "   '136',\n",
       "   '405',\n",
       "   '545',\n",
       "   '395',\n",
       "   '526',\n",
       "   '96',\n",
       "   '418',\n",
       "   '153',\n",
       "   '157',\n",
       "   '554',\n",
       "   '83',\n",
       "   '499',\n",
       "   '276',\n",
       "   '280',\n",
       "   '184',\n",
       "   '147',\n",
       "   '143',\n",
       "   '127',\n",
       "   '151',\n",
       "   '81',\n",
       "   '156',\n",
       "   '85',\n",
       "   '160',\n",
       "   '173',\n",
       "   '549',\n",
       "   '533',\n",
       "   '105',\n",
       "   '205',\n",
       "   '529',\n",
       "   '483',\n",
       "   '467',\n",
       "   '87',\n",
       "   '246',\n",
       "   '536',\n",
       "   '313',\n",
       "   '247',\n",
       "   '449',\n",
       "   '398',\n",
       "   '73',\n",
       "   '301',\n",
       "   '139',\n",
       "   '285',\n",
       "   '538',\n",
       "   '431',\n",
       "   '322',\n",
       "   '375',\n",
       "   '505',\n",
       "   '164',\n",
       "   '115',\n",
       "   '543',\n",
       "   '84',\n",
       "   '310',\n",
       "   '546',\n",
       "   '248',\n",
       "   '116',\n",
       "   '373',\n",
       "   '489',\n",
       "   '77',\n",
       "   '108',\n",
       "   '244',\n",
       "   '290',\n",
       "   '541',\n",
       "   '389',\n",
       "   '528',\n",
       "   '294',\n",
       "   '68',\n",
       "   '227',\n",
       "   '234',\n",
       "   '256',\n",
       "   '346',\n",
       "   '547'],\n",
       "  ['98', '118', '62'],\n",
       "  ['201', '191', '55', '306'],\n",
       "  ['43'],\n",
       "  ['42', '60'],\n",
       "  ['421',\n",
       "   '493',\n",
       "   '489',\n",
       "   '469',\n",
       "   '501',\n",
       "   '483',\n",
       "   '485',\n",
       "   '143',\n",
       "   '381',\n",
       "   '163',\n",
       "   '148',\n",
       "   '354',\n",
       "   '352',\n",
       "   '376',\n",
       "   '384',\n",
       "   '382',\n",
       "   '386',\n",
       "   '394',\n",
       "   '390'],\n",
       "  ['174'],\n",
       "  ['214', '146', '222', '114', '206', '170'],\n",
       "  ['70',\n",
       "   '68',\n",
       "   '60',\n",
       "   '78',\n",
       "   '106',\n",
       "   '62',\n",
       "   '58',\n",
       "   '160',\n",
       "   '315',\n",
       "   '201',\n",
       "   '242',\n",
       "   '199',\n",
       "   '158',\n",
       "   '580',\n",
       "   '732',\n",
       "   '108',\n",
       "   '285',\n",
       "   '455',\n",
       "   '114',\n",
       "   '176',\n",
       "   '672',\n",
       "   '284',\n",
       "   '234',\n",
       "   '211',\n",
       "   '192',\n",
       "   '215',\n",
       "   '579',\n",
       "   '124',\n",
       "   '111',\n",
       "   '509',\n",
       "   '109',\n",
       "   '402',\n",
       "   '733',\n",
       "   '186',\n",
       "   '281',\n",
       "   '1514'],\n",
       "  ['46', '54'],\n",
       "  ['252',\n",
       "   '91',\n",
       "   '162',\n",
       "   '349',\n",
       "   '254',\n",
       "   '149',\n",
       "   '277',\n",
       "   '272',\n",
       "   '249',\n",
       "   '288',\n",
       "   '282',\n",
       "   '285',\n",
       "   '299',\n",
       "   '354',\n",
       "   '311',\n",
       "   '314',\n",
       "   '411',\n",
       "   '383',\n",
       "   '267',\n",
       "   '453',\n",
       "   '79',\n",
       "   '416',\n",
       "   '369'],\n",
       "  ['1236', '386'],\n",
       "  ['86', '90', '110'],\n",
       "  ['251', '257'],\n",
       "  ['785', '753'],\n",
       "  ['689'],\n",
       "  ['20'],\n",
       "  ['139', '113', '135'],\n",
       "  ['350', '342', '349', '322', '590', '347', '355'],\n",
       "  ['198', '86', '78', '70'],\n",
       "  ['188', '204', '140', '105', '70', '259', '198', '605', '181', '95', '606'],\n",
       "  ['1266'],\n",
       "  ['81',\n",
       "   '176',\n",
       "   '362',\n",
       "   '1514',\n",
       "   '103',\n",
       "   '90',\n",
       "   '1266',\n",
       "   '1036',\n",
       "   '998',\n",
       "   '1295',\n",
       "   '264',\n",
       "   '666',\n",
       "   '742',\n",
       "   '374',\n",
       "   '375',\n",
       "   '1484',\n",
       "   '1425',\n",
       "   '1060',\n",
       "   '1510',\n",
       "   '706',\n",
       "   '537',\n",
       "   '675',\n",
       "   '835',\n",
       "   '1132',\n",
       "   '485',\n",
       "   '594',\n",
       "   '717',\n",
       "   '1348',\n",
       "   '393',\n",
       "   '656',\n",
       "   '861',\n",
       "   '1285',\n",
       "   '929',\n",
       "   '1016',\n",
       "   '920',\n",
       "   '1039',\n",
       "   '699',\n",
       "   '1267',\n",
       "   '1477',\n",
       "   '601',\n",
       "   '627',\n",
       "   '810',\n",
       "   '933',\n",
       "   '862',\n",
       "   '990',\n",
       "   '500',\n",
       "   '352',\n",
       "   '1084',\n",
       "   '414',\n",
       "   '823',\n",
       "   '586',\n",
       "   '740',\n",
       "   '634',\n",
       "   '286',\n",
       "   '1196',\n",
       "   '1110',\n",
       "   '1214',\n",
       "   '1070',\n",
       "   '324',\n",
       "   '1350',\n",
       "   '498',\n",
       "   '1262',\n",
       "   '932',\n",
       "   '1494',\n",
       "   '926',\n",
       "   '170',\n",
       "   '1380',\n",
       "   '194',\n",
       "   '542',\n",
       "   '305',\n",
       "   '283'],\n",
       "  ['109', '427', '1469'],\n",
       "  ['70', '110'],\n",
       "  ['98'],\n",
       "  ['265',\n",
       "   '248',\n",
       "   '339',\n",
       "   '287',\n",
       "   '458',\n",
       "   '387',\n",
       "   '459',\n",
       "   '338',\n",
       "   '298',\n",
       "   '460',\n",
       "   '263',\n",
       "   '256',\n",
       "   '259',\n",
       "   '264',\n",
       "   '262',\n",
       "   '255',\n",
       "   '257',\n",
       "   '461',\n",
       "   '267',\n",
       "   '268',\n",
       "   '266',\n",
       "   '270',\n",
       "   '269',\n",
       "   '237',\n",
       "   '392',\n",
       "   '200',\n",
       "   '301',\n",
       "   '284',\n",
       "   '276',\n",
       "   '457',\n",
       "   '271',\n",
       "   '272',\n",
       "   '273',\n",
       "   '275',\n",
       "   '274',\n",
       "   '261',\n",
       "   '258',\n",
       "   '288',\n",
       "   '260'],\n",
       "  ['331',\n",
       "   '392',\n",
       "   '248',\n",
       "   '289',\n",
       "   '545',\n",
       "   '993',\n",
       "   '650',\n",
       "   '252',\n",
       "   '379',\n",
       "   '247',\n",
       "   '246',\n",
       "   '255',\n",
       "   '347',\n",
       "   '492',\n",
       "   '898',\n",
       "   '431',\n",
       "   '1337',\n",
       "   '928'],\n",
       "  ['252', '1236'],\n",
       "  ['110'],\n",
       "  ['98',\n",
       "   '110',\n",
       "   '286',\n",
       "   '313',\n",
       "   '308',\n",
       "   '565',\n",
       "   '109',\n",
       "   '268',\n",
       "   '106',\n",
       "   '282',\n",
       "   '96',\n",
       "   '277',\n",
       "   '97',\n",
       "   '262',\n",
       "   '95',\n",
       "   '274',\n",
       "   '104',\n",
       "   '503',\n",
       "   '107',\n",
       "   '525',\n",
       "   '99',\n",
       "   '333',\n",
       "   '332',\n",
       "   '251',\n",
       "   '301',\n",
       "   '94',\n",
       "   '422',\n",
       "   '435',\n",
       "   '457',\n",
       "   '356',\n",
       "   '292',\n",
       "   '304',\n",
       "   '103',\n",
       "   '495',\n",
       "   '444',\n",
       "   '451',\n",
       "   '522',\n",
       "   '101',\n",
       "   '218',\n",
       "   '105',\n",
       "   '551',\n",
       "   '267',\n",
       "   '559',\n",
       "   '108',\n",
       "   '476',\n",
       "   '131',\n",
       "   '460',\n",
       "   '349',\n",
       "   '296',\n",
       "   '115',\n",
       "   '511',\n",
       "   '93',\n",
       "   '258',\n",
       "   '100',\n",
       "   '317',\n",
       "   '300',\n",
       "   '355',\n",
       "   '485',\n",
       "   '348',\n",
       "   '520',\n",
       "   '354',\n",
       "   '102',\n",
       "   '365',\n",
       "   '297',\n",
       "   '373',\n",
       "   '364',\n",
       "   '372',\n",
       "   '269',\n",
       "   '556',\n",
       "   '294'],\n",
       "  ['910', '880'],\n",
       "  ['1236',\n",
       "   '1209',\n",
       "   '407',\n",
       "   '394',\n",
       "   '576',\n",
       "   '575',\n",
       "   '562',\n",
       "   '577',\n",
       "   '563',\n",
       "   '1208',\n",
       "   '409',\n",
       "   '1207',\n",
       "   '1223',\n",
       "   '1326',\n",
       "   '396',\n",
       "   '1237'],\n",
       "  ['1266'],\n",
       "  ['1514'],\n",
       "  ['856', '796', '770', '783', '1514', '944', '759', '843'],\n",
       "  ['83', '852'],\n",
       "  ['38'],\n",
       "  ['1069', '1205'],\n",
       "  ['1234'],\n",
       "  ['1029'],\n",
       "  ['759', '786', '1049'],\n",
       "  ['252', '1236'],\n",
       "  ['743'],\n",
       "  ['616'],\n",
       "  ['1215'],\n",
       "  ['252', '1236'],\n",
       "  ['177', '175'],\n",
       "  ['394', '250', '122', '506', '1214', '238', '138', '282', '170'],\n",
       "  ['1514'],\n",
       "  ['230'],\n",
       "  ['252', '1236'],\n",
       "  ['880'],\n",
       "  ['643'],\n",
       "  ['252', '1236'],\n",
       "  ['252', '1236'],\n",
       "  ['672', '598', '440'],\n",
       "  ['59'],\n",
       "  ['252', '1236'],\n",
       "  ['994', '506'],\n",
       "  ['71'],\n",
       "  ['198', '150'],\n",
       "  ['252', '1236'],\n",
       "  ['1392', '77', '83', '80', '72'],\n",
       "  ['646'],\n",
       "  ['252', '1236'],\n",
       "  ['705'],\n",
       "  ['252', '1236'],\n",
       "  ['435'],\n",
       "  ['59']]]"
      ]
     },
     "execution_count": 165,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "total_len_per_proto"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 155,
   "metadata": {},
   "outputs": [],
   "source": [
    "protocols = unique_protocol.tolist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "metadata": {},
   "outputs": [],
   "source": [
    "protocol_mapping = protocols.append(protocol_frame_len_unique_len)\n",
    "protocol_mapping"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['eth:ethertype:ip:tcp:tls',\n",
       " 'eth:ethertype:ip:tcp',\n",
       " 'eth:ethertype:ip:udp:ntp',\n",
       " 'eth:ethertype:ip:udp:dns',\n",
       " 'eth:ethertype:ip:icmp:data',\n",
       " 'eth:ethertype:ip:udp:data',\n",
       " 'eth:ethertype:ip:udp:udpencap',\n",
       " 'eth:ethertype:arp',\n",
       " 'eth:ethertype:ip:udp:ssdp',\n",
       " 'eth:ethertype:ip:udp:udpencap:esp',\n",
       " 'eth:ethertype:ip:tcp:stun',\n",
       " 'eth:ethertype:ip:tcp:data',\n",
       " 'eth:ethertype:ip:igmp:igmp',\n",
       " 'eth:ethertype:ip:tcp:http',\n",
       " 'eth:ethertype:ip:tcp:http:xml',\n",
       " 'eth:ethertype:ipv6:ipv6.hopopts:icmpv6',\n",
       " 'eth:ethertype:ip:udp:nbdgm:smb:browser',\n",
       " 'eth:ethertype:ip:tcp:sip',\n",
       " 'eth:ethertype:ip:tcp:tls:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509ce:x509ce:x509ce:x509ce:x509ce:pkix1explicit:pkix1implicit:x509ce:x509ce:pkix1implicit:tls:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509ce:x509ce:x509ce:pkix1implicit:x509ce:pkix1explicit:pkix1implicit:x509ce:x509sat:x509ce:x509ce:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509ce:x509ce:logotypecertextn:x509ce:tls',\n",
       " 'eth:llc',\n",
       " 'eth:ethertype:eapol',\n",
       " 'eth:ethertype:ip:udp:dhcp',\n",
       " 'eth:ethertype:ipv6:icmpv6',\n",
       " 'eth:ethertype:ip:tcp:xmpp:xml',\n",
       " 'eth:ethertype:ip:tcp:tls:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509ce:x509ce:x509ce:x509ce:pkix1explicit:x509ce:x509ce:x509ce:pkix1implicit:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:pkix1implicit:x509ce:x509ce:x509ce:x509ce:x509sat:x509ce:x509ce:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509ce:x509ce:pkix1explicit:x509ce:x509ce:x509ce:tls',\n",
       " 'eth:ethertype:ip:tcp:tls:tls',\n",
       " 'eth:ethertype:ip:tcp:tls:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509ce:x509ce:x509ce:x509ce:x509ce:pkix1explicit:pkix1implicit:x509ce:x509ce:pkix1implicit:tls:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509ce:x509ce:x509ce:pkix1implicit:x509ce:pkix1explicit:pkix1implicit:x509ce:x509sat:x509ce:x509ce',\n",
       " 'eth:ethertype:ip:udp:classicstun',\n",
       " 'eth:ethertype:ip:icmp:ip:udp:classicstun',\n",
       " 'eth:ethertype:ip:tcp:http:urlencoded-form',\n",
       " 'eth:ethertype:ip:tcp:http:data-text-lines',\n",
       " 'eth:ethertype:ip:tcp:kip',\n",
       " 'eth:ethertype:ip:udp:nbns',\n",
       " 'eth:ethertype:ipv6:udp:dns',\n",
       " 'eth:ethertype:ip:tcp:tls:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509ce:x509ce:x509ce:x509ce:x509ce:x509ce:x509ce:pkix1explicit:pkix1implicit:x509ce:pkix1implicit:x509ce:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509ce:x509ce:x509ce:x509ce:pkix1implicit:x509ce:x509ce:pkix1explicit:pkix1explicit:tls',\n",
       " 'eth:ethertype:ip:tcp:tls:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:pkcs-1:x509ce:x509ce:x509ce:pkix1implicit:x509ce:x509ce:x509ce:x509ce:x509ce:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509ce:x509ce:x509ce:pkix1implicit:x509ce:x509ce:x509ce:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509ce:x509ce:x509ce:x509ce:x509ce:x509ce:pkix1explicit:tls',\n",
       " 'eth:ethertype:ip:tcp:tls:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509ce:x509ce:pkix1explicit:pkix1implicit:x509ce:x509ce:x509ce:x509ce:x509ce:x509ce:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509ce:x509ce:pkix1explicit:pkix1implicit:x509ce:x509ce:x509ce:x509ce:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509ce:x509ce:pkix1explicit:x509ce:x509ce:x509sat:x509sat:x509sat:x509sat:x509ce:tls',\n",
       " 'eth:ethertype:ip:tcp:tls:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509ce:x509ce:x509ce:x509ce:x509ce:x509ce:pkix1explicit:x509ce:pkix1implicit:x509ce:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509ce:x509ce:x509ce:x509ce:x509ce:x509ce:x509ce:pkix1implicit:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509ce:x509ce:x509ce:x509ce:x509ce:x509ce:pkix1implicit:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509ce:x509ce:x509ce:x509ce:x509sat:x509sat:x509sat:x509sat:tls',\n",
       " 'eth:ethertype:ip:tcp:tls:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509ce:x509ce:pkix1implicit:x509ce:x509ce:x509ce:x509ce:x509ce:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509ce:x509ce:x509ce:pkix1implicit:x509ce:x509ce:x509ce:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509ce:x509ce:x509ce:x509ce:x509ce:x509ce:pkix1explicit:tls',\n",
       " 'eth:ethertype:ip:tcp:ulp',\n",
       " 'eth:ethertype:wlan',\n",
       " 'eth:ethertype:ip:tcp:http:json',\n",
       " 'eth:ethertype:ip:tcp:tls:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509ce:x509ce:cms:cms:cms:x509ce:x509ce:x509ce:x509ce:pkix1implicit:x509ce:pkix1explicit:x509ce:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509ce:x509ce:pkix1explicit:pkix1implicit:x509ce:x509ce:x509ce:x509ce:x509ce',\n",
       " 'eth:ethertype:ip:tcp:tls:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509ce:x509ce:x509ce:x509ce:pkix1implicit:x509ce:x509ce:pkix1explicit:x509ce:x509ce:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509ce:x509ce:pkix1explicit:pkix1implicit:x509ce:x509ce:x509ce:x509ce:x509ce',\n",
       " 'eth:ethertype:ip:tcp:tls:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509ce:x509ce:x509ce:x509ce:pkix1implicit:x509ce:x509ce:pkix1explicit:x509ce:x509ce:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509ce:x509ce:pkix1explicit:x509ce:x509ce:x509ce:x509ce:x509ce',\n",
       " 'eth:ethertype:ip:tcp:mih',\n",
       " 'eth:ethertype:ip:tcp:tls:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509ce:x509ce:x509ce:x509ce:x509ce:pkix1explicit:pkix1implicit:x509ce:x509ce:pkix1implicit:tls:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509ce:x509ce:x509ce:pkix1implicit:x509ce:pkix1explicit:pkix1implicit:x509ce:x509sat:x509ce:x509ce:tls',\n",
       " 'eth:ethertype:ip:tcp:http:data:media',\n",
       " 'eth:ethertype:ip:tcp:tls:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509ce:x509ce:pkix1implicit:x509ce:x509ce:x509ce:x509ce:x509ce:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509ce:x509ce:x509ce:pkix1implicit:x509ce:x509ce:x509ce:tls',\n",
       " 'eth:ethertype:ip:tcp:ax4000',\n",
       " 'eth:ethertype:ipv6:udp:dhcpv6',\n",
       " 'eth:ethertype:ip:udp:udpencap:isakmp',\n",
       " 'eth:ethertype:ip:tcp:tls:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509ce:x509ce:x509ce:x509ce:x509ce:pkix1explicit:x509ce:x509ce:pkix1implicit:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:pkix1implicit:x509ce:x509ce:pkix1explicit:pkix1implicit:x509ce:x509ce:logotypecertextn:x509ce:x509sat:x509ce:x509ce:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509ce:x509ce:x509ce:x509ce:pkix1explicit:x509ce:logotypecertextn:pkix1implicit:x509ce:tls',\n",
       " 'eth:ethertype:data',\n",
       " 'eth:ethertype:ip:tcp:cflow',\n",
       " 'eth:ethertype:ip:tcp:tls:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509ce:ns_cert_exts:ns_cert_exts:x509ce:x509ce:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509ce:x509ce:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509ce:x509ce:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509ce:tls:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat',\n",
       " 'eth:ethertype:ip:tcp:tls:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509ce:ns_cert_exts:x509ce:x509ce:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509ce:x509ce:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509ce:x509ce:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509ce:tls',\n",
       " 'eth:ethertype:ip:tcp:wow',\n",
       " 'eth:ethertype:ip:tcp:sabp',\n",
       " 'eth:ethertype:ip:tcp:http:media',\n",
       " 'eth:ethertype:ip:tcp:http:data:data:data:data:data:data:data:data:data:data:data:data:data:data:data:data:data:data:data:data:data:data:data:data:data:data:data:data:data:data:urlencoded-form',\n",
       " 'eth:ethertype:ip:tcp:asap',\n",
       " 'eth:ethertype:ip:udp:isakmp',\n",
       " 'eth:ethertype:ip:icmp:ip:udp:udpencap',\n",
       " 'eth:ethertype:ip:icmp:ip:udp:udpencap:isakmp',\n",
       " 'eth:ethertype:ip:tcp:gearman',\n",
       " 'eth:ethertype:ip:udp:gquic',\n",
       " 'eth:ethertype:ip:tcp:http:data-text-lines:xml',\n",
       " 'eth:ethertype:ip:tcp:tfp',\n",
       " 'eth:ethertype:ip:tcp:tls:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509ce:x509ce:x509ce:x509ce:x509ce:pkix1explicit:pkix1implicit:x509ce:x509ce:pkix1implicit:tls:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509ce:x509ce:x509ce:pkix1implicit:x509ce:pkix1explicit:pkix1implicit:x509ce:x509sat:x509ce:x509ce',\n",
       " 'eth:ethertype:ip:tcp:diameter:data',\n",
       " 'eth:ethertype:ip:tcp:tls:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509sat:x509ce:x509ce:x509ce:x509ce:x509ce:pkix1explicit:pkix1implicit:x509ce:x509ce:x509ce:tls',\n",
       " 'eth:ethertype:ip:tcp:http:data:data:data:data:data:data:data:data:data:data:data:data:data:data:data:data:data:data:data:data:data:data:data:data:data:data:data:data:data:data:data:urlencoded-form',\n",
       " None,\n",
       " None,\n",
       " [518,\n",
       "  112,\n",
       "  1,\n",
       "  99,\n",
       "  3,\n",
       "  4,\n",
       "  1,\n",
       "  2,\n",
       "  19,\n",
       "  1,\n",
       "  6,\n",
       "  36,\n",
       "  2,\n",
       "  23,\n",
       "  2,\n",
       "  3,\n",
       "  2,\n",
       "  2,\n",
       "  1,\n",
       "  1,\n",
       "  3,\n",
       "  7,\n",
       "  4,\n",
       "  11,\n",
       "  1,\n",
       "  71,\n",
       "  3,\n",
       "  2,\n",
       "  1,\n",
       "  39,\n",
       "  18,\n",
       "  2,\n",
       "  1,\n",
       "  70,\n",
       "  2,\n",
       "  16,\n",
       "  1,\n",
       "  1,\n",
       "  8,\n",
       "  2,\n",
       "  1,\n",
       "  2,\n",
       "  1,\n",
       "  1,\n",
       "  3,\n",
       "  2,\n",
       "  1,\n",
       "  1,\n",
       "  1,\n",
       "  2,\n",
       "  2,\n",
       "  9,\n",
       "  1,\n",
       "  1,\n",
       "  2,\n",
       "  1,\n",
       "  1,\n",
       "  2,\n",
       "  2,\n",
       "  3,\n",
       "  1,\n",
       "  2,\n",
       "  2,\n",
       "  1,\n",
       "  2,\n",
       "  2,\n",
       "  5,\n",
       "  1,\n",
       "  2,\n",
       "  1,\n",
       "  2,\n",
       "  1,\n",
       "  1,\n",
       "  None,\n",
       "  None]]"
      ]
     },
     "execution_count": 164,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "protocols"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}