Convert Ip to Num.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import socket, struct\n",
    "from binascii import hexlify\n",
    "\n",
    "def ConvertIptoNum(ip):\n",
    "    try:\n",
    "        #convert decimal dotted quad string to long integer\n",
    "        return struct.unpack('>L',socket.inet_aton(ip))[0]\n",
    "    except Exception:\n",
    "        return int(hexlify(socket.inet_pton(socket.AF_INET6, ip)), 16)\n",
    "     "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "a = '192.186.0.1'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [],
   "source": [
    "s = ConvertIptoNum(a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3233415169"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3233415168.9999"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s-"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "normalized = min_max_scaler.fit_transform(s)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "float(normalized[0][0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Open the csv file ( category-risk-numeric.csv)\n",
    "## loop ma ghumauni\n",
    "### take src-ip as ip\n",
    "## each ip address line ra ConvertIptoNum(ip) walla function ma pathauni\n",
    "## arko csv ma gareni huncha src-ip as ip => , risk-factor, categories save garne\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Next time hamiharuu le new model ma train garna ko lagi pani yo function call bhayera matrai save garnu paryo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "processed 0 rows\n"
     ]
    }
   ],
   "source": [
    "import csv\n",
    "\n",
    "with open('all-neumeric.csv', 'w') as outfile:\n",
    "     c = csv.writer(outfile)\n",
    "     counter = 0\n",
    "     with open('category_risk_factor_to_neumeric.csv.csv','rb') as f:\n",
    "         for row in csv.reader(f, delimiter=','):\n",
    "            counter = counter + 1\n",
    "            mod_row = []\n",
    "            if counter != 1:\n",
    "                for cell in row[0]:\n",
    "                    print(row[0])\n",
    "                    ConvertIptoNum(row[0])\n",
    "            else:\n",
    "                for cell in row:\n",
    "                    mod_row.append(cell)\n",
    "            c.writerow(mod_row)\n",
    "\n",
    "print \"processed {} rows\".format(counter)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('category_risk_factor_to_neumeric.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "import csv\n",
    "with open('category_risk_factor_to_neumeric.csv', 'r') as f:\n",
    "    reader = csv.reader(f)\n",
    "    your_list = list(reader)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
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       " ['173.234.159.195', '1.0', '0'],\n",
       " ['157.37.235.242', '1.0', '1'],\n",
       " ['183.89.27.156', '1.0', '2'],\n",
       " ['171.217.98.88', '1.0', '1'],\n",
       " ['185.31.165.145', '1.0', '1'],\n",
       " ['123.12.192.100', '1.0', '2'],\n",
       " ['49.49.148.248', '1.0', '0'],\n",
       " ['86.167.53.248', '1.0', '1'],\n",
       " ['124.148.199.230', '1.0', '0'],\n",
       " ['83.203.157.151', '1.0', '1'],\n",
       " ['138.59.25.18', '1.0', '1'],\n",
       " ['117.203.219.119', '5.7', '2'],\n",
       " ['175.131.213.96', '1.0', '2'],\n",
       " ['36.230.206.165', '1.0', '2'],\n",
       " ['183.53.78.156', '1.0', '0'],\n",
       " ['178.130.41.85', '1.0', '0'],\n",
       " ['112.221.73.141', '1.0', '1'],\n",
       " ['178.69.32.198', '1.0', '0'],\n",
       " ['178.115.129.115', '1.0', '1'],\n",
       " ['220.173.179.75', '1.0', '1'],\n",
       " ['79.130.54.168', '1.0', '0'],\n",
       " ['91.140.91.193', '1.4', '2'],\n",
       " ['171.90.203.244', '1.0', '1'],\n",
       " ['178.70.111.20', '1.0', '2'],\n",
       " ['31.24.217.131', '1.0', '1'],\n",
       " ['116.212.19.74', '1.0', '0'],\n",
       " ['77.227.29.89', '1.0', '1'],\n",
       " ['61.239.100.38', '1.0', '1'],\n",
       " ['111.242.22.223', '5.7', '2'],\n",
       " ['182.138.188.97', '1.0', '1'],\n",
       " ['161.142.103.59', '1.0', '1'],\n",
       " ['14.223.167.218', '1.0', '0'],\n",
       " ['112.148.18.186', '1.51325678497', '1'],\n",
       " ['182.64.75.111', '5.7', '2'],\n",
       " ['129.208.155.224', '1.0', '2'],\n",
       " ['182.128.48.180', '1.0', '1'],\n",
       " ['101.80.155.103', '1.0', '1'],\n",
       " ['69.202.233.114', '1.0', '0'],\n",
       " ['183.253.130.87', '1.0', '1'],\n",
       " ['2.50.180.157', '5.7', '2'],\n",
       " ['151.0.88.85', '1.0', '2'],\n",
       " ['91.140.4.189', '1.0', '2'],\n",
       " ['169.0.78.61', '1.0', '1'],\n",
       " ['62.48.115.178', '1.0', '1'],\n",
       " ['130.180.209.226', '1.0', '0'],\n",
       " ['31.148.139.136', '1.0', '0'],\n",
       " ['213.144.20.156', '1.0', '1'],\n",
       " ['91.146.164.173', '1.0', '0'],\n",
       " ['1.233.25.103', '1.0', '1'],\n",
       " ['175.19.229.22', '1.0', '0'],\n",
       " ['103.42.210.72', '1.4', '2'],\n",
       " ['94.50.230.29', '1.0', '1'],\n",
       " ['112.134.39.109', '5.7', '2'],\n",
       " ['187.190.251.201', '5.7', '2'],\n",
       " ['176.51.90.163', '1.0', '2'],\n",
       " ['14.204.65.10', '1.0', '0'],\n",
       " ['13.114.205.93', '1.0', '1'],\n",
       " ['80.90.224.143', '1.0', '1'],\n",
       " ['119.134.151.108', '1.0', '0'],\n",
       " ['43.224.156.130', '1.4', '2'],\n",
       " ['113.27.19.6', '1.0', '1'],\n",
       " ['113.124.246.140', '1.0', '1'],\n",
       " ['91.92.245.192', '1.0', '1'],\n",
       " ['91.107.96.14', '1.0', '0'],\n",
       " ['67.164.111.93', '1.0', '1'],\n",
       " ['117.150.94.18', '1.0', '1'],\n",
       " ['82.207.27.146', '1.0', '0'],\n",
       " ['77.98.29.198', '1.0', '1'],\n",
       " ['113.53.255.67', '1.0', '0'],\n",
       " ['119.94.108.231', '1.0', '1'],\n",
       " ['73.31.113.128', '1.0', '1'],\n",
       " ['178.48.154.249', '1.0', '0'],\n",
       " ['202.129.29.3', '1.0', '1'],\n",
       " ['60.208.230.36', '1.0', '0'],\n",
       " ...]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "your_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "213.230.102.14\n",
      "here\n",
      "192.168.1.8\n"
     ]
    }
   ],
   "source": [
    "import csv\n",
    "with open('firewall_logs_with_risk_factors.csv', 'r') as f:\n",
    "    reader = csv.reader(f)\n",
    "    your_list = list(reader)\n",
    "    print(your_list[1][2])\n",
    "    print(\"here\")\n",
    "    print(your_list[1][3])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1971"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(your_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "import csv\n",
    "with open('firewall_logs_with_risk_factors.csv', 'r') as f:\n",
    "    reader = csv.reader(f)\n",
    "    your_list = list(reader)\n",
    "    i = 1\n",
    "    naya_ip=[]\n",
    "    \n",
    "    counter = 0\n",
    "    for i in range(1,8874):\n",
    "        #your_list[i][0]    \n",
    "        #print(your_list[i][0])\n",
    "        new_ip_src=ConvertIptoNum(your_list[i][2])\n",
    "        new_ip_dst=ConvertIptoNum(your_list[i][3])\n",
    "        \n",
    "        #naya_ip.append(new_ip)\n",
    "        with open('firewall_log_numeric_all.csv','a') as w:\n",
    "            counter = counter + 1\n",
    "            c = csv.writer(w)\n",
    "            value = [your_list[i][0],your_list[i][1],new_ip_src,new_ip_dst,your_list[i][4],your_list[i][5],your_list[i][6],your_list[i][7],your_list[i][8],your_list[i][9]]\n",
    "            c = c.writerow(value)\n",
    "            \n",
    "      "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "def min_max_normalzation(x):\n",
    "    return (x-0/1-0)\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1596927275.0"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "min_max_normalzation(1596927275.0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('ALL_NEUMERIX.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "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>src-ip</th>\n",
       "      <th>risk-factor</th>\n",
       "      <th>categories</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2390872136</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>584179858</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2087885482</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3584858198</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1596927275</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>3537787762</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2499489289</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>3232235784</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>624000638</td>\n",
       "      <td>5.7</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1937727665</td>\n",
       "      <td>-99999.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>770826095</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>1741136134</td>\n",
       "      <td>8.6</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>701774523</td>\n",
       "      <td>-99999.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>3232235778</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>3580044050</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>995991159</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>1856733178</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2031107992</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>1497369295</td>\n",
       "      <td>5.7</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>1342433871</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>693811825</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>630064787</td>\n",
       "      <td>5.7</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>1730546718</td>\n",
       "      <td>4.3</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>1914893240</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>1975959884</td>\n",
       "      <td>5.7</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>1886908382</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>96319801</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>96319801</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>1968255870</td>\n",
       "      <td>5.7</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>1758417666</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2629</th>\n",
       "      <td>1337266823</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2630</th>\n",
       "      <td>3554860876</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2631</th>\n",
       "      <td>2038704261</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2632</th>\n",
       "      <td>2972286333</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2633</th>\n",
       "      <td>1959692712</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2634</th>\n",
       "      <td>2946421586</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2635</th>\n",
       "      <td>3065447813</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2636</th>\n",
       "      <td>1760955246</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2637</th>\n",
       "      <td>1319458441</td>\n",
       "      <td>5.7</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2638</th>\n",
       "      <td>3015694972</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2639</th>\n",
       "      <td>3119781866</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2640</th>\n",
       "      <td>1887824055</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2641</th>\n",
       "      <td>1562587635</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2642</th>\n",
       "      <td>1558849178</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2643</th>\n",
       "      <td>1776421368</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2644</th>\n",
       "      <td>1982003042</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2645</th>\n",
       "      <td>1813930486</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2646</th>\n",
       "      <td>3068402501</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2647</th>\n",
       "      <td>3179077159</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2648</th>\n",
       "      <td>3039599016</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2649</th>\n",
       "      <td>3533097410</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2650</th>\n",
       "      <td>3286510146</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2651</th>\n",
       "      <td>1731810268</td>\n",
       "      <td>5.7</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2652</th>\n",
       "      <td>1379165293</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2653</th>\n",
       "      <td>2535009425</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2654</th>\n",
       "      <td>1938176329</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2655</th>\n",
       "      <td>3395695235</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2656</th>\n",
       "      <td>1382423349</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2657</th>\n",
       "      <td>39318190</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2658</th>\n",
       "      <td>3156443785</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2659 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          src-ip  risk-factor  categories\n",
       "0     2390872136          1.0           0\n",
       "1      584179858          1.0           0\n",
       "2     2087885482          1.0           0\n",
       "3     3584858198          1.0           0\n",
       "4     1596927275          1.0           0\n",
       "5     3537787762          1.0           0\n",
       "6     2499489289          1.0           0\n",
       "7     3232235784          1.0           0\n",
       "8      624000638          5.7           2\n",
       "9     1937727665     -99999.0           0\n",
       "10     770826095          1.0           0\n",
       "11    1741136134          8.6           2\n",
       "12     701774523     -99999.0           0\n",
       "13    3232235778          1.0           0\n",
       "14    3580044050          1.0           0\n",
       "15     995991159          1.0           0\n",
       "16    1856733178          1.0           0\n",
       "17    2031107992          1.0           0\n",
       "18    1497369295          5.7           2\n",
       "19    1342433871          1.0           0\n",
       "20     693811825          1.0           0\n",
       "21     630064787          5.7           2\n",
       "22    1730546718          4.3           2\n",
       "23    1914893240          1.0           0\n",
       "24    1975959884          5.7           2\n",
       "25    1886908382          1.0           0\n",
       "26      96319801          1.0           0\n",
       "27      96319801          1.0           0\n",
       "28    1968255870          5.7           2\n",
       "29    1758417666          1.0           0\n",
       "...          ...          ...         ...\n",
       "2629  1337266823          1.0           0\n",
       "2630  3554860876          1.0           0\n",
       "2631  2038704261          1.0           0\n",
       "2632  2972286333          1.0           0\n",
       "2633  1959692712          1.0           0\n",
       "2634  2946421586          1.0           0\n",
       "2635  3065447813          1.0           0\n",
       "2636  1760955246          1.0           0\n",
       "2637  1319458441          5.7           2\n",
       "2638  3015694972          1.0           0\n",
       "2639  3119781866          1.0           0\n",
       "2640  1887824055          1.0           0\n",
       "2641  1562587635          1.0           0\n",
       "2642  1558849178          1.0           0\n",
       "2643  1776421368          1.0           0\n",
       "2644  1982003042          1.0           0\n",
       "2645  1813930486          1.0           0\n",
       "2646  3068402501          1.0           0\n",
       "2647  3179077159          1.0           0\n",
       "2648  3039599016          1.0           0\n",
       "2649  3533097410          1.0           0\n",
       "2650  3286510146          1.0           0\n",
       "2651  1731810268          5.7           2\n",
       "2652  1379165293          1.0           0\n",
       "2653  2535009425          1.0           0\n",
       "2654  1938176329          1.0           0\n",
       "2655  3395695235          1.0           0\n",
       "2656  1382423349          1.0           0\n",
       "2657    39318190          1.0           0\n",
       "2658  3156443785          1.0           0\n",
       "\n",
       "[2659 rows x 3 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['src-ip'] = pd.to_numeric(df['src-ip'], errors='coerce')\n",
    "\n",
    "#df['src-ip'] = df['src-ip'].apply(pd.to_numeric)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>src-ip</th>\n",
       "      <th>risk-factor</th>\n",
       "      <th>categories</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2.390872e+09</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5.841799e+08</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2.087885e+09</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3.584858e+09</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1.596927e+09</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>3.537788e+09</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2.499489e+09</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>3.232236e+09</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>6.240006e+08</td>\n",
       "      <td>5.7</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1.937728e+09</td>\n",
       "      <td>-99999.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>7.708261e+08</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>1.741136e+09</td>\n",
       "      <td>8.6</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>7.017745e+08</td>\n",
       "      <td>-99999.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>3.232236e+09</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>3.580044e+09</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>9.959912e+08</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>1.856733e+09</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2.031108e+09</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>1.497369e+09</td>\n",
       "      <td>5.7</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>1.342434e+09</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>6.938118e+08</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>6.300648e+08</td>\n",
       "      <td>5.7</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>1.730547e+09</td>\n",
       "      <td>4.3</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>1.914893e+09</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>1.975960e+09</td>\n",
       "      <td>5.7</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>1.886908e+09</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>9.631980e+07</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>9.631980e+07</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>1.968256e+09</td>\n",
       "      <td>5.7</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>1.758418e+09</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2629</th>\n",
       "      <td>1.337267e+09</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2630</th>\n",
       "      <td>3.554861e+09</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2631</th>\n",
       "      <td>2.038704e+09</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2632</th>\n",
       "      <td>2.972286e+09</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2633</th>\n",
       "      <td>1.959693e+09</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2634</th>\n",
       "      <td>2.946422e+09</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2635</th>\n",
       "      <td>3.065448e+09</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2636</th>\n",
       "      <td>1.760955e+09</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2637</th>\n",
       "      <td>1.319458e+09</td>\n",
       "      <td>5.7</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2638</th>\n",
       "      <td>3.015695e+09</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2639</th>\n",
       "      <td>3.119782e+09</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2640</th>\n",
       "      <td>1.887824e+09</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2641</th>\n",
       "      <td>1.562588e+09</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2642</th>\n",
       "      <td>1.558849e+09</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2643</th>\n",
       "      <td>1.776421e+09</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2644</th>\n",
       "      <td>1.982003e+09</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2645</th>\n",
       "      <td>1.813930e+09</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2646</th>\n",
       "      <td>3.068403e+09</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2647</th>\n",
       "      <td>3.179077e+09</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2648</th>\n",
       "      <td>3.039599e+09</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2649</th>\n",
       "      <td>3.533097e+09</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2650</th>\n",
       "      <td>3.286510e+09</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2651</th>\n",
       "      <td>1.731810e+09</td>\n",
       "      <td>5.7</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2652</th>\n",
       "      <td>1.379165e+09</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2653</th>\n",
       "      <td>2.535009e+09</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2654</th>\n",
       "      <td>1.938176e+09</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2655</th>\n",
       "      <td>3.395695e+09</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2656</th>\n",
       "      <td>1.382423e+09</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2657</th>\n",
       "      <td>3.931819e+07</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2658</th>\n",
       "      <td>3.156444e+09</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2659 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            src-ip  risk-factor  categories\n",
       "0     2.390872e+09          1.0           0\n",
       "1     5.841799e+08          1.0           0\n",
       "2     2.087885e+09          1.0           0\n",
       "3     3.584858e+09          1.0           0\n",
       "4     1.596927e+09          1.0           0\n",
       "5     3.537788e+09          1.0           0\n",
       "6     2.499489e+09          1.0           0\n",
       "7     3.232236e+09          1.0           0\n",
       "8     6.240006e+08          5.7           2\n",
       "9     1.937728e+09     -99999.0           0\n",
       "10    7.708261e+08          1.0           0\n",
       "11    1.741136e+09          8.6           2\n",
       "12    7.017745e+08     -99999.0           0\n",
       "13    3.232236e+09          1.0           0\n",
       "14    3.580044e+09          1.0           0\n",
       "15    9.959912e+08          1.0           0\n",
       "16    1.856733e+09          1.0           0\n",
       "17    2.031108e+09          1.0           0\n",
       "18    1.497369e+09          5.7           2\n",
       "19    1.342434e+09          1.0           0\n",
       "20    6.938118e+08          1.0           0\n",
       "21    6.300648e+08          5.7           2\n",
       "22    1.730547e+09          4.3           2\n",
       "23    1.914893e+09          1.0           0\n",
       "24    1.975960e+09          5.7           2\n",
       "25    1.886908e+09          1.0           0\n",
       "26    9.631980e+07          1.0           0\n",
       "27    9.631980e+07          1.0           0\n",
       "28    1.968256e+09          5.7           2\n",
       "29    1.758418e+09          1.0           0\n",
       "...            ...          ...         ...\n",
       "2629  1.337267e+09          1.0           0\n",
       "2630  3.554861e+09          1.0           0\n",
       "2631  2.038704e+09          1.0           0\n",
       "2632  2.972286e+09          1.0           0\n",
       "2633  1.959693e+09          1.0           0\n",
       "2634  2.946422e+09          1.0           0\n",
       "2635  3.065448e+09          1.0           0\n",
       "2636  1.760955e+09          1.0           0\n",
       "2637  1.319458e+09          5.7           2\n",
       "2638  3.015695e+09          1.0           0\n",
       "2639  3.119782e+09          1.0           0\n",
       "2640  1.887824e+09          1.0           0\n",
       "2641  1.562588e+09          1.0           0\n",
       "2642  1.558849e+09          1.0           0\n",
       "2643  1.776421e+09          1.0           0\n",
       "2644  1.982003e+09          1.0           0\n",
       "2645  1.813930e+09          1.0           0\n",
       "2646  3.068403e+09          1.0           0\n",
       "2647  3.179077e+09          1.0           0\n",
       "2648  3.039599e+09          1.0           0\n",
       "2649  3.533097e+09          1.0           0\n",
       "2650  3.286510e+09          1.0           0\n",
       "2651  1.731810e+09          5.7           2\n",
       "2652  1.379165e+09          1.0           0\n",
       "2653  2.535009e+09          1.0           0\n",
       "2654  1.938176e+09          1.0           0\n",
       "2655  3.395695e+09          1.0           0\n",
       "2656  1.382423e+09          1.0           0\n",
       "2657  3.931819e+07          1.0           0\n",
       "2658  3.156444e+09          1.0           0\n",
       "\n",
       "[2659 rows x 3 columns]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.dropna(inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn import preprocessing\n",
    "\n",
    "x = df.values #returns a numpy array\n",
    "min_max_scaler = preprocessing.MinMaxScaler()\n",
    "x_scaled = min_max_scaler.fit_transform(x)\n",
    "df = pd.DataFrame(x_scaled)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    float64\n",
       "1    float64\n",
       "2    float64\n",
       "dtype: object"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.to_csv(\"Final-Normalized-Neumeric.csv\", index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.to_csv(\"what-happened-to-this2.csv\",index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv(\"what-happened-to-this2.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.drop_duplicates(keep = \"first\").to_csv(\"Final_Data_Set(9:00pm).csv\", index = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv(\"Final_Data_Set(9:00pm).csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "df[:1000].to_csv(\"Test_K_mean.data\",index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv(\"Final-Normalized-Neumeric.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2658"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "df[:1500].to_csv(\"Final-Normalized-Neumeric-Train(1500).csv\", index = False)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
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