Anamoly_detection_using_ml.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "_l0pUXfyqhSy"
   },
   "source": [
    "## Importing libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "id": "4rg1l7ToqK2G"
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "e7xzgGOow8Wo"
   },
   "source": [
    "### loading dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "id": "fma6JbZPqm8G"
   },
   "outputs": [],
   "source": [
    "data1 = pd.read_csv('mainSimulationAccessTraces.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "id": "woAj5rYp1-uI"
   },
   "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>sourceID</th>\n",
       "      <th>sourceAddress</th>\n",
       "      <th>sourceType</th>\n",
       "      <th>sourceLocation</th>\n",
       "      <th>destinationServiceAddress</th>\n",
       "      <th>destinationServiceType</th>\n",
       "      <th>destinationLocation</th>\n",
       "      <th>accessedNodeAddress</th>\n",
       "      <th>accessedNodeType</th>\n",
       "      <th>operation</th>\n",
       "      <th>value</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>normality</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>lightcontrol2</td>\n",
       "      <td>/agent2/lightcontrol2</td>\n",
       "      <td>/lightControler</td>\n",
       "      <td>BedroomParents</td>\n",
       "      <td>/agent2/lightcontrol2</td>\n",
       "      <td>/lightControler</td>\n",
       "      <td>BedroomParents</td>\n",
       "      <td>/agent2/lightcontrol2</td>\n",
       "      <td>/lightControler</td>\n",
       "      <td>registerService</td>\n",
       "      <td>none</td>\n",
       "      <td>1520031600000</td>\n",
       "      <td>normal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>lightcontrol3</td>\n",
       "      <td>/agent3/lightcontrol3</td>\n",
       "      <td>/lightControler</td>\n",
       "      <td>Dinningroom</td>\n",
       "      <td>/agent3/lightcontrol3</td>\n",
       "      <td>/lightControler</td>\n",
       "      <td>Dinningroom</td>\n",
       "      <td>/agent3/lightcontrol3</td>\n",
       "      <td>/lightControler</td>\n",
       "      <td>registerService</td>\n",
       "      <td>none</td>\n",
       "      <td>1520031603269</td>\n",
       "      <td>normal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>lightcontrol1</td>\n",
       "      <td>/agent1/lightcontrol1</td>\n",
       "      <td>/lightControler</td>\n",
       "      <td>BedroomChildren</td>\n",
       "      <td>/agent1/lightcontrol1</td>\n",
       "      <td>/lightControler</td>\n",
       "      <td>BedroomChildren</td>\n",
       "      <td>/agent1/lightcontrol1</td>\n",
       "      <td>/lightControler</td>\n",
       "      <td>registerService</td>\n",
       "      <td>none</td>\n",
       "      <td>1520031603279</td>\n",
       "      <td>normal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>lightcontrol4</td>\n",
       "      <td>/agent4/lightcontrol4</td>\n",
       "      <td>/lightControler</td>\n",
       "      <td>Kitchen</td>\n",
       "      <td>/agent4/lightcontrol4</td>\n",
       "      <td>/lightControler</td>\n",
       "      <td>Kitchen</td>\n",
       "      <td>/agent4/lightcontrol4</td>\n",
       "      <td>/lightControler</td>\n",
       "      <td>registerService</td>\n",
       "      <td>none</td>\n",
       "      <td>1520031603290</td>\n",
       "      <td>normal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>movement4</td>\n",
       "      <td>/agent4/movement4</td>\n",
       "      <td>/movementSensor</td>\n",
       "      <td>Kitchen</td>\n",
       "      <td>/agent4/movement4</td>\n",
       "      <td>/movementSensor</td>\n",
       "      <td>Kitchen</td>\n",
       "      <td>/agent4/movement4</td>\n",
       "      <td>/movementSensor</td>\n",
       "      <td>registerService</td>\n",
       "      <td>none</td>\n",
       "      <td>1520031603464</td>\n",
       "      <td>normal</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>357947</th>\n",
       "      <td>lightcontrol23</td>\n",
       "      <td>/agent23/lightcontrol23</td>\n",
       "      <td>/lightControler</td>\n",
       "      <td>room_4</td>\n",
       "      <td>/agent23/tempin23</td>\n",
       "      <td>/sensorService</td>\n",
       "      <td>room_4</td>\n",
       "      <td>/agent23/tempin23</td>\n",
       "      <td>/sensorService</td>\n",
       "      <td>read</td>\n",
       "      <td>20.3479</td>\n",
       "      <td>1520117997001</td>\n",
       "      <td>normal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>357948</th>\n",
       "      <td>washingmachine2</td>\n",
       "      <td>/agent11/washingmachine2</td>\n",
       "      <td>/washingService</td>\n",
       "      <td>Watterroom</td>\n",
       "      <td>/agent11/battery4</td>\n",
       "      <td>/batteryService</td>\n",
       "      <td>Watterroom</td>\n",
       "      <td>/agent11/battery4/charge</td>\n",
       "      <td>/basic/number</td>\n",
       "      <td>read</td>\n",
       "      <td>9</td>\n",
       "      <td>1520117997339</td>\n",
       "      <td>normal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>357949</th>\n",
       "      <td>washingmachine2</td>\n",
       "      <td>/agent11/washingmachine2</td>\n",
       "      <td>/washingService</td>\n",
       "      <td>Watterroom</td>\n",
       "      <td>/agent11/battery4</td>\n",
       "      <td>/batteryService</td>\n",
       "      <td>Watterroom</td>\n",
       "      <td>/agent11/battery4/charging</td>\n",
       "      <td>/basic/text</td>\n",
       "      <td>read</td>\n",
       "      <td>true</td>\n",
       "      <td>1520117997401</td>\n",
       "      <td>normal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>357950</th>\n",
       "      <td>lightcontrol28</td>\n",
       "      <td>/agent28/lightcontrol28</td>\n",
       "      <td>/lightControler</td>\n",
       "      <td>room_9</td>\n",
       "      <td>/agent28/movement28</td>\n",
       "      <td>/movementSensor</td>\n",
       "      <td>room_9</td>\n",
       "      <td>/agent28/movement28/movement</td>\n",
       "      <td>/derived/boolean</td>\n",
       "      <td>read</td>\n",
       "      <td>0</td>\n",
       "      <td>1520117998907</td>\n",
       "      <td>normal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>357951</th>\n",
       "      <td>lightcontrol28</td>\n",
       "      <td>/agent28/lightcontrol28</td>\n",
       "      <td>/lightControler</td>\n",
       "      <td>room_9</td>\n",
       "      <td>/agent28/tempin28</td>\n",
       "      <td>/sensorService</td>\n",
       "      <td>room_9</td>\n",
       "      <td>/agent28/tempin28</td>\n",
       "      <td>/sensorService</td>\n",
       "      <td>read</td>\n",
       "      <td>20.4131</td>\n",
       "      <td>1520117999000</td>\n",
       "      <td>normal</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>357952 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               sourceID             sourceAddress       sourceType  \\\n",
       "0         lightcontrol2     /agent2/lightcontrol2  /lightControler   \n",
       "1         lightcontrol3     /agent3/lightcontrol3  /lightControler   \n",
       "2         lightcontrol1     /agent1/lightcontrol1  /lightControler   \n",
       "3         lightcontrol4     /agent4/lightcontrol4  /lightControler   \n",
       "4             movement4         /agent4/movement4  /movementSensor   \n",
       "...                 ...                       ...              ...   \n",
       "357947   lightcontrol23   /agent23/lightcontrol23  /lightControler   \n",
       "357948  washingmachine2  /agent11/washingmachine2  /washingService   \n",
       "357949  washingmachine2  /agent11/washingmachine2  /washingService   \n",
       "357950   lightcontrol28   /agent28/lightcontrol28  /lightControler   \n",
       "357951   lightcontrol28   /agent28/lightcontrol28  /lightControler   \n",
       "\n",
       "         sourceLocation destinationServiceAddress destinationServiceType  \\\n",
       "0        BedroomParents     /agent2/lightcontrol2        /lightControler   \n",
       "1           Dinningroom     /agent3/lightcontrol3        /lightControler   \n",
       "2       BedroomChildren     /agent1/lightcontrol1        /lightControler   \n",
       "3               Kitchen     /agent4/lightcontrol4        /lightControler   \n",
       "4               Kitchen         /agent4/movement4        /movementSensor   \n",
       "...                 ...                       ...                    ...   \n",
       "357947           room_4         /agent23/tempin23         /sensorService   \n",
       "357948       Watterroom         /agent11/battery4        /batteryService   \n",
       "357949       Watterroom         /agent11/battery4        /batteryService   \n",
       "357950           room_9       /agent28/movement28        /movementSensor   \n",
       "357951           room_9         /agent28/tempin28         /sensorService   \n",
       "\n",
       "       destinationLocation           accessedNodeAddress  accessedNodeType  \\\n",
       "0           BedroomParents         /agent2/lightcontrol2   /lightControler   \n",
       "1              Dinningroom         /agent3/lightcontrol3   /lightControler   \n",
       "2          BedroomChildren         /agent1/lightcontrol1   /lightControler   \n",
       "3                  Kitchen         /agent4/lightcontrol4   /lightControler   \n",
       "4                  Kitchen             /agent4/movement4   /movementSensor   \n",
       "...                    ...                           ...               ...   \n",
       "357947              room_4             /agent23/tempin23    /sensorService   \n",
       "357948          Watterroom      /agent11/battery4/charge     /basic/number   \n",
       "357949          Watterroom    /agent11/battery4/charging       /basic/text   \n",
       "357950              room_9  /agent28/movement28/movement  /derived/boolean   \n",
       "357951              room_9             /agent28/tempin28    /sensorService   \n",
       "\n",
       "              operation    value      timestamp normality  \n",
       "0       registerService     none  1520031600000    normal  \n",
       "1       registerService     none  1520031603269    normal  \n",
       "2       registerService     none  1520031603279    normal  \n",
       "3       registerService     none  1520031603290    normal  \n",
       "4       registerService     none  1520031603464    normal  \n",
       "...                 ...      ...            ...       ...  \n",
       "357947             read  20.3479  1520117997001    normal  \n",
       "357948             read        9  1520117997339    normal  \n",
       "357949             read     true  1520117997401    normal  \n",
       "357950             read        0  1520117998907    normal  \n",
       "357951             read  20.4131  1520117999000    normal  \n",
       "\n",
       "[357952 rows x 13 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "b0XKmeo6wa_H"
   },
   "source": [
    "### Preprocessing and cleaning the dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "lGxDVty_u29h",
    "outputId": "ed7b0054-4363-455c-f7fc-6ec25d2257f6"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 357952 entries, 0 to 357951\n",
      "Data columns (total 13 columns):\n",
      " #   Column                     Non-Null Count   Dtype \n",
      "---  ------                     --------------   ----- \n",
      " 0   sourceID                   357952 non-null  object\n",
      " 1   sourceAddress              357952 non-null  object\n",
      " 2   sourceType                 357952 non-null  object\n",
      " 3   sourceLocation             357952 non-null  object\n",
      " 4   destinationServiceAddress  357952 non-null  object\n",
      " 5   destinationServiceType     357952 non-null  object\n",
      " 6   destinationLocation        357952 non-null  object\n",
      " 7   accessedNodeAddress        357952 non-null  object\n",
      " 8   accessedNodeType           357804 non-null  object\n",
      " 9   operation                  357952 non-null  object\n",
      " 10  value                      355902 non-null  object\n",
      " 11  timestamp                  357952 non-null  int64 \n",
      " 12  normality                  357952 non-null  object\n",
      "dtypes: int64(1), object(12)\n",
      "memory usage: 35.5+ MB\n"
     ]
    }
   ],
   "source": [
    "data1.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "6oqMMfkgwaet",
    "outputId": "80d65998-9bed-404a-dfee-e262d0f45502"
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "c5_hLHV-qnND",
    "outputId": "e43ee691-3287-4054-eb58-b42a4dd9fbf8"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    /lightControler\n",
       "1    /lightControler\n",
       "2    /lightControler\n",
       "3    /lightControler\n",
       "4    /movementSensor\n",
       "5     /sensorService\n",
       "6    /movementSensor\n",
       "7     /sensorService\n",
       "8     /sensorService\n",
       "9    /movementSensor\n",
       "Name: accessedNodeType, dtype: object"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data1['accessedNodeType'].head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "kQKWnttnqnOC",
    "outputId": "fb4cb5cc-649e-46d1-e60c-fa385b471ea9"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "/sensorService      130155\n",
       "/derived/boolean     94725\n",
       "/basic/number        90016\n",
       "/basic/text          42433\n",
       "/thermostat            313\n",
       "/basic/composed        100\n",
       "/lightControler         23\n",
       "/movementSensor         22\n",
       "/batteryService          6\n",
       "/doorLockService         5\n",
       "/washingService          3\n",
       "/smartPhone              3\n",
       "Name: accessedNodeType, dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data1['accessedNodeType'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "1MiMRi6JqnUn",
    "outputId": "64dec5c1-afff-430c-bd6f-c90415c8a798"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False    357804\n",
       "True        148\n",
       "Name: accessedNodeType, dtype: int64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "data1['accessedNodeType'].isnull().value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "kA1nLnJPzSUR",
    "outputId": "b449610a-1644-4e30-f98e-69ab1be2b5ed"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Garage             39501\n",
       "Watterroom         38369\n",
       "Entrance           38220\n",
       "Bathroom           28461\n",
       "Showerroom         28315\n",
       "Kitchen            18963\n",
       "Dinningroom        13430\n",
       "BedroomChildren    12836\n",
       "room_6             11642\n",
       "Bedroom            11009\n",
       "BedroomParents     10946\n",
       "room_8             10798\n",
       "room_9             10752\n",
       "Livingroom         10621\n",
       "room_2             10607\n",
       "room_1             10602\n",
       "room_3             10597\n",
       "room_5             10596\n",
       "room_4             10572\n",
       "room_7             10558\n",
       "room_10            10557\n",
       "Name: sourceLocation, dtype: int64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "data1.sourceLocation.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "id": "0jQmaq08Avkn"
   },
   "outputs": [],
   "source": [
    "df1 = data1.dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "hOzN4-8PqnVf",
    "outputId": "2d66b180-3249-4174-9314-6e440b667b55"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 355902 entries, 0 to 357951\n",
      "Data columns (total 13 columns):\n",
      " #   Column                     Non-Null Count   Dtype \n",
      "---  ------                     --------------   ----- \n",
      " 0   sourceID                   355902 non-null  object\n",
      " 1   sourceAddress              355902 non-null  object\n",
      " 2   sourceType                 355902 non-null  object\n",
      " 3   sourceLocation             355902 non-null  object\n",
      " 4   destinationServiceAddress  355902 non-null  object\n",
      " 5   destinationServiceType     355902 non-null  object\n",
      " 6   destinationLocation        355902 non-null  object\n",
      " 7   accessedNodeAddress        355902 non-null  object\n",
      " 8   accessedNodeType           355902 non-null  object\n",
      " 9   operation                  355902 non-null  object\n",
      " 10  value                      355902 non-null  object\n",
      " 11  timestamp                  355902 non-null  int64 \n",
      " 12  normality                  355902 non-null  object\n",
      "dtypes: int64(1), object(12)\n",
      "memory usage: 38.0+ MB\n"
     ]
    }
   ],
   "source": [
    "df1 = pd.DataFrame(df1)\n",
    "df1.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "dpRdXhnJ1EEy",
    "outputId": "12f51120-08f5-4824-c87b-b14537b3e734"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['1', '0', 'false', 'true', '10', '5', '2', '4', '6', '7',\n",
       "       ...\n",
       "       '1.52121734717E12',\n",
       "       'org.ds2os.vsl.core.utils.AddressParameters@61ba9b2b',\n",
       "       'org.ds2os.vsl.core.utils.AddressParameters@2c82b391',\n",
       "       '1.521217447122E12', '1.521216923287E12', '1.521217446778E12',\n",
       "       '1.521220297057E12', '1.521220308496E12', '1.521220325816E12',\n",
       "       '1.521225180883E12'],\n",
       "      dtype='object', length=10623)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1['value'].value_counts().index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "pnJGyi0AqnaS",
    "outputId": "0dd94965-6a7d-47ac-a492-eec5c75d4ed0"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1                    57047\n",
       "0                    50282\n",
       "false                25966\n",
       "true                 14460\n",
       "10                    9635\n",
       "                     ...  \n",
       "1.521217446778E12        1\n",
       "1.521220297057E12        1\n",
       "1.521220308496E12        1\n",
       "1.521220325816E12        1\n",
       "1.521225180883E12        1\n",
       "Name: value, Length: 10623, dtype: int64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1['value'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "id": "j4nF2Ji-qnef"
   },
   "outputs": [],
   "source": [
    "df1.loc[df1.value=='twenty',\"value\"] = '20.0'\n",
    "df1.loc[df1.value=='false',\"value\"] = '0'\n",
    "df1.loc[df1.value=='true',\"value\"] = '1'\n",
    "df1.loc[df1.value=='none',\"value\"] = '0'\n",
    "df1.loc[df1.value=='0',\"value\"] = '0.0'\n",
    "df1['value'] = df1['value'].fillna(value='60.0')\n",
    "df1 = df1.drop(df1.index[df1.value.str.contains(\"org.*\")])\n",
    "df1.value = df1.value.astype(float)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "mS_utFq7qnfg",
    "outputId": "5a544084-e278-4d5b-c93d-60b1e0d3686a"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.000000e+00    76624\n",
       "1.000000e+00    71507\n",
       "1.000000e+01     9635\n",
       "5.000000e+00     8487\n",
       "2.000000e+00     8438\n",
       "                ...  \n",
       "3.857174e+01        1\n",
       "1.521218e+12        1\n",
       "1.521218e+12        1\n",
       "1.521217e+12        1\n",
       "1.521225e+12        1\n",
       "Name: value, Length: 10606, dtype: int64"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1['value'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "uGVC_QV9AFup",
    "outputId": "f65c7344-5417-4acc-9dd7-6354067e4615"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "sourceID\n",
      "sourceAddress\n",
      "sourceType\n",
      "sourceLocation\n",
      "destinationServiceAddress\n",
      "destinationServiceType\n",
      "destinationLocation\n",
      "accessedNodeAddress\n",
      "accessedNodeType\n",
      "operation\n",
      "value\n",
      "timestamp\n",
      "normality\n"
     ]
    }
   ],
   "source": [
    "for i in df1.columns:\n",
    "  print(i)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "lXZ08oXN2I6t"
   },
   "source": [
    "### Plotting Graphs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "id": "cB5GKCU1qnkN"
   },
   "outputs": [],
   "source": [
    "from matplotlib import pyplot as plt\n",
    "import random"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "xkXiB2aK2U1p"
   },
   "source": [
    "#### counting the number of source locations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 465
    },
    "id": "K9xWzKEE11hs",
    "outputId": "90205043-f6d3-41fb-bf21-a692709b331a"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,5))\n",
    "ax=plt.subplot(111)\n",
    "plt.bar(df1.sourceLocation.value_counts().index, df1.sourceLocation.value_counts().values)\n",
    "plt.grid()\n",
    "plt.ylabel('Number of Occurrences', fontsize=20)\n",
    "plt.xlabel('Source Location', fontsize=20)\n",
    "plt.xticks(rotation=90,fontsize=15)\n",
    "plt.yticks(fontsize=15)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Garage             39499\n",
       "Watterroom         38268\n",
       "Entrance           36437\n",
       "Showerroom         28315\n",
       "Bathroom           28313\n",
       "Kitchen            18946\n",
       "Dinningroom        13426\n",
       "BedroomChildren    12833\n",
       "room_6             11642\n",
       "Bedroom            11009\n",
       "BedroomParents     10946\n",
       "room_8             10798\n",
       "room_9             10752\n",
       "Livingroom         10620\n",
       "room_2             10606\n",
       "room_1             10601\n",
       "room_3             10597\n",
       "room_5             10596\n",
       "room_4             10572\n",
       "room_7             10558\n",
       "room_10            10557\n",
       "Name: sourceLocation, dtype: int64"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.sourceLocation.value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "BhPqkqC_11ix",
    "outputId": "0abf7443-6235-40fa-9083-a0fc78a851e3"
   },
   "source": [
    "### counting the number of source type"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 471
    },
    "id": "ZKKUqKS811mz",
    "outputId": "6a4e9f9a-3550-4603-aff3-86b167f19b28"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,5))\n",
    "ax=plt.subplot(111)\n",
    "plt.bar(df1.sourceType.value_counts().index, df1.sourceType.value_counts().values)\n",
    "plt.grid()\n",
    "plt.ylabel('Number of Occurrences', fontsize=20)\n",
    "plt.xlabel('Source Type', fontsize=20)\n",
    "plt.xticks(rotation=90,fontsize=15)\n",
    "plt.yticks(fontsize=15)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "8Z7zfKFZ11nx",
    "outputId": "15d78edf-f61c-4eac-b356-9d28fcc3b08a"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/lightControler     135775\n",
      "/sensorService       85196\n",
      "/batteryService      81251\n",
      "/washingService      47738\n",
      "/thermostat           4200\n",
      "/movementSensor       1301\n",
      "/doorLockService       330\n",
      "/smartPhone            100\n",
      "Name: sourceType, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "print(df1.sourceType.value_counts())\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### counting the number of destination service type"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 471
    },
    "id": "z59y-odc11rm",
    "outputId": "7a05bbb5-370c-4d9e-88b7-0f86717e14af"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,5))\n",
    "ax=plt.subplot(111)\n",
    "plt.bar(df1.destinationServiceType.value_counts().index, df1.destinationServiceType.value_counts().values)\n",
    "plt.grid()\n",
    "plt.ylabel('Number of Occurrences', fontsize=20)\n",
    "plt.xlabel('Destination Service Type', fontsize=20)\n",
    "plt.xticks(rotation=90,fontsize=15)\n",
    "plt.yticks(fontsize=15)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "HGLI4oXF11sw",
    "outputId": "4a71d8ec-248c-4b21-9276-f037b45d9417"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "/sensorService      130313\n",
       "/batteryService     128871\n",
       "/movementSensor      93645\n",
       "/lightControler       1694\n",
       "/doorLockService      1043\n",
       "/thermostat            319\n",
       "/washingService          3\n",
       "/smartPhone              3\n",
       "Name: destinationServiceType, dtype: int64"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.destinationServiceType.value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### counting the number of destination location"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 464
    },
    "id": "Is09QsGK11v5",
    "outputId": "2fd64830-62e4-4a96-d0cd-81f353640ef9"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,5))\n",
    "ax=plt.subplot(111)\n",
    "plt.bar(df1.destinationLocation.value_counts().index, df1.destinationLocation.value_counts().values)\n",
    "plt.grid()\n",
    "plt.ylabel('Number of Occurrences', fontsize=20)\n",
    "plt.xlabel('Destination Location', fontsize=20)\n",
    "plt.xticks(rotation=90,fontsize=15)\n",
    "plt.yticks(fontsize=15)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "51pyHOAX11w0",
    "outputId": "3164cb3a-e434-41c1-c5c5-80165d451c7b"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Garage             57026\n",
       "Entrance           54448\n",
       "Watterroom         38408\n",
       "Kitchen            19363\n",
       "BedroomChildren    12768\n",
       "Bathroom           12681\n",
       "BedroomParents     10938\n",
       "room_9             10843\n",
       "room_2             10828\n",
       "room_1             10805\n",
       "Showerroom         10800\n",
       "Livingroom         10781\n",
       "Dinningroom        10759\n",
       "room_6             10741\n",
       "room_3             10732\n",
       "room_4             10708\n",
       "room_5             10687\n",
       "room_8             10651\n",
       "room_7             10649\n",
       "room_10            10648\n",
       "Bedroom            10627\n",
       "Name: destinationLocation, dtype: int64"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.destinationLocation.value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### counting the number of Accessed Node type"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 471
    },
    "id": "zp8wDJ6Q110Q",
    "outputId": "305d3d8e-e3c5-4265-f3f0-5f3d20340efe"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,5))\n",
    "ax=plt.subplot(111)\n",
    "plt.bar(df1.accessedNodeType.value_counts().index, df1.accessedNodeType.value_counts().values)\n",
    "plt.grid()\n",
    "plt.ylabel('Number of Occurrences', fontsize=20)\n",
    "plt.xlabel('Accessed Node Type', fontsize=20)\n",
    "plt.xticks(rotation=90,fontsize=15)\n",
    "plt.yticks(fontsize=15)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "vcw3YQXr1135",
    "outputId": "9da209ad-99d7-4a09-9dc7-ff84438eff9c"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "/sensorService      130155\n",
       "/derived/boolean     94725\n",
       "/basic/number        90010\n",
       "/basic/text          40626\n",
       "/thermostat            313\n",
       "/lightControler         23\n",
       "/movementSensor         22\n",
       "/batteryService          6\n",
       "/doorLockService         5\n",
       "/washingService          3\n",
       "/smartPhone              3\n",
       "Name: accessedNodeType, dtype: int64"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.accessedNodeType.value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### counting the number of operations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 448
    },
    "id": "zDV254sw115B",
    "outputId": "09c302c1-d2b5-4f72-a9d4-a7cb020b918d"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,5))\n",
    "ax=plt.subplot(111)\n",
    "plt.bar(df1.operation.value_counts().index, df1.operation.value_counts().values)\n",
    "plt.grid()\n",
    "plt.ylabel('Number of Occurrences', fontsize=20)\n",
    "plt.xlabel('Operations', fontsize=20)\n",
    "plt.xticks(rotation=90,fontsize=15)\n",
    "plt.yticks(fontsize=15)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "q_OE11pD116F",
    "outputId": "fdf4e860-4132-4a43-aff3-1c4638bb8cde"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "read               246259\n",
       "write              109548\n",
       "registerService        84\n",
       "Name: operation, dtype: int64"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.operation.value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### counting the number of normality"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 572
    },
    "id": "SRa-Zipk118d",
    "outputId": "f74ee6f5-b1cb-48ff-8de5-0f4e1cb6e25a"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,5))\n",
    "plt.bar(df1.normality.value_counts().index, df1.normality.value_counts().values)\n",
    "plt.grid()\n",
    "plt.ylabel('Number of Occurrences', fontsize=20)\n",
    "plt.xlabel('Normality', fontsize=20)\n",
    "plt.xticks(rotation=90,fontsize=15)\n",
    "plt.yticks(fontsize=15)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "RwU3Ll81119m",
    "outputId": "75ef91bf-719b-46cf-8236-4a42470ffbb9"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "normal                           347918\n",
       "anomalous(DoSattack)               4000\n",
       "anomalous(scan)                    1531\n",
       "anomalous(malitiousControl)         889\n",
       "anomalous(malitiousOperation)       657\n",
       "anomalous(spying)                   532\n",
       "anomalous(dataProbing)              242\n",
       "anomalous(wrongSetUp)               122\n",
       "Name: normality, dtype: int64"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.normality.value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "EwPBa_nINYCW"
   },
   "source": [
    "## Feature Extraction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 355891 entries, 0 to 357951\n",
      "Data columns (total 13 columns):\n",
      " #   Column                     Non-Null Count   Dtype  \n",
      "---  ------                     --------------   -----  \n",
      " 0   sourceID                   355891 non-null  object \n",
      " 1   sourceAddress              355891 non-null  object \n",
      " 2   sourceType                 355891 non-null  object \n",
      " 3   sourceLocation             355891 non-null  object \n",
      " 4   destinationServiceAddress  355891 non-null  object \n",
      " 5   destinationServiceType     355891 non-null  object \n",
      " 6   destinationLocation        355891 non-null  object \n",
      " 7   accessedNodeAddress        355891 non-null  object \n",
      " 8   accessedNodeType           355891 non-null  object \n",
      " 9   operation                  355891 non-null  object \n",
      " 10  value                      355891 non-null  float64\n",
      " 11  timestamp                  355891 non-null  int64  \n",
      " 12  normality                  355891 non-null  object \n",
      "dtypes: float64(1), int64(1), object(11)\n",
      "memory usage: 38.0+ MB\n"
     ]
    }
   ],
   "source": [
    "df1.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Dropping irrelavant columns\n",
    "timestamp doesnt provide any vital info hence dropping it"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "df1 = df1.drop(['timestamp'],axis=1)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 355891 entries, 0 to 357951\n",
      "Data columns (total 12 columns):\n",
      " #   Column                     Non-Null Count   Dtype  \n",
      "---  ------                     --------------   -----  \n",
      " 0   sourceID                   355891 non-null  object \n",
      " 1   sourceAddress              355891 non-null  object \n",
      " 2   sourceType                 355891 non-null  object \n",
      " 3   sourceLocation             355891 non-null  object \n",
      " 4   destinationServiceAddress  355891 non-null  object \n",
      " 5   destinationServiceType     355891 non-null  object \n",
      " 6   destinationLocation        355891 non-null  object \n",
      " 7   accessedNodeAddress        355891 non-null  object \n",
      " 8   accessedNodeType           355891 non-null  object \n",
      " 9   operation                  355891 non-null  object \n",
      " 10  value                      355891 non-null  float64\n",
      " 11  normality                  355891 non-null  object \n",
      "dtypes: float64(1), object(11)\n",
      "memory usage: 35.3+ MB\n"
     ]
    }
   ],
   "source": [
    "df1.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['normal', 'normal', 'normal', ..., 'normal', 'normal', 'normal'],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.iloc[:,11].values"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### using inbuilt preprocessing methods such as label encoding we will scale the data "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import LabelEncoder\n",
    "le = LabelEncoder()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "x0 = le.fit_transform(df1.iloc[:,0].values)\n",
    "x1 = le.fit_transform(df1.iloc[:,1].values)\n",
    "x2 = le.fit_transform(df1.iloc[:,2].values)\n",
    "x3 = le.fit_transform(df1.iloc[:,3].values)\n",
    "x4 = le.fit_transform(df1.iloc[:,4].values)\n",
    "x5 = le.fit_transform(df1.iloc[:,5].values)\n",
    "x6 = le.fit_transform(df1.iloc[:,6].values)\n",
    "x7 = le.fit_transform(df1.iloc[:,7].values)\n",
    "x8 = le.fit_transform(df1.iloc[:,8].values)\n",
    "x9 = le.fit_transform(df1.iloc[:,9].values)\n",
    "x10 = le.fit_transform(df1.iloc[:,10].values)\n",
    "y = le.fit_transform(df1.iloc[:,11].values)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### joining all x values together"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "x = list(zip(x0,x1,x2,x3,x4,x5,x6,x7,x8,x9,x10))\n",
    "y = list(y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(21, 30, 2, 3, 29, 2, 3, 57, 5, 1, 0),\n",
       " (32, 70, 2, 4, 67, 2, 4, 132, 5, 1, 0),\n",
       " (15, 1, 2, 2, 0, 2, 2, 0, 5, 1, 0),\n",
       " (33, 77, 2, 7, 72, 2, 7, 142, 5, 1, 0),\n",
       " (55, 78, 3, 7, 73, 3, 7, 144, 6, 1, 0),\n",
       " (66, 34, 4, 3, 31, 4, 3, 62, 7, 1, 0),\n",
       " (43, 32, 3, 3, 30, 3, 3, 59, 6, 1, 0),\n",
       " (78, 79, 4, 7, 74, 4, 7, 147, 7, 1, 0),\n",
       " (61, 4, 4, 2, 2, 4, 2, 5, 7, 1, 0),\n",
       " (37, 2, 3, 2, 1, 3, 2, 2, 6, 1, 0),\n",
       " (54, 71, 3, 4, 68, 3, 4, 134, 6, 1, 0),\n",
       " (77, 73, 4, 4, 70, 4, 4, 138, 7, 1, 0),\n",
       " (56, 83, 3, 6, 78, 3, 6, 156, 6, 1, 0),\n",
       " (34, 82, 2, 6, 77, 2, 6, 154, 5, 1, 0),\n",
       " (79, 84, 4, 6, 79, 4, 6, 159, 7, 1, 0),\n",
       " (77, 73, 4, 4, 70, 4, 4, 138, 7, 2, 5490),\n",
       " (54, 71, 3, 4, 68, 3, 4, 136, 3, 2, 1),\n",
       " (57, 86, 3, 0, 81, 3, 0, 162, 6, 1, 0),\n",
       " (35, 85, 2, 0, 80, 2, 0, 160, 5, 1, 0),\n",
       " (54, 71, 3, 4, 68, 3, 4, 135, 0, 2, 10031),\n",
       " (38, 7, 3, 8, 5, 3, 8, 10, 6, 1, 0),\n",
       " (80, 87, 4, 0, 82, 4, 0, 165, 7, 1, 0),\n",
       " (61, 4, 4, 2, 2, 4, 2, 5, 7, 2, 3417),\n",
       " (77, 73, 4, 4, 70, 4, 4, 138, 7, 2, 4114),\n",
       " (39, 12, 3, 10, 11, 3, 10, 22, 6, 1, 0),\n",
       " (16, 6, 2, 8, 4, 2, 8, 8, 5, 1, 0),\n",
       " (78, 79, 4, 7, 74, 4, 7, 147, 7, 2, 4549),\n",
       " (17, 11, 2, 10, 10, 2, 10, 20, 5, 1, 0),\n",
       " (41, 22, 3, 1, 22, 3, 1, 45, 6, 1, 0),\n",
       " (18, 19, 2, 5, 18, 2, 5, 37, 5, 1, 0),\n",
       " (43, 32, 3, 3, 30, 3, 3, 61, 3, 2, 1),\n",
       " (43, 32, 3, 3, 30, 3, 3, 60, 0, 2, 10032),\n",
       " (66, 34, 4, 3, 31, 4, 3, 62, 7, 2, 3211),\n",
       " (61, 4, 4, 2, 2, 4, 2, 5, 7, 2, 5031),\n",
       " (40, 20, 3, 5, 19, 3, 5, 39, 6, 1, 0),\n",
       " (19, 21, 2, 1, 21, 2, 1, 43, 5, 1, 0),\n",
       " (21, 30, 2, 3, 30, 3, 3, 61, 3, 0, 1),\n",
       " (15, 1, 2, 2, 1, 3, 2, 4, 3, 0, 0),\n",
       " (33, 77, 2, 7, 73, 3, 7, 146, 3, 0, 0),\n",
       " (21, 30, 2, 3, 29, 2, 3, 58, 3, 2, 1),\n",
       " (42, 25, 3, 9, 26, 3, 9, 52, 6, 1, 0),\n",
       " (32, 70, 2, 4, 68, 3, 4, 136, 3, 0, 1),\n",
       " (20, 24, 2, 9, 25, 2, 9, 50, 5, 1, 0),\n",
       " (77, 73, 4, 4, 70, 4, 4, 138, 7, 2, 9775),\n",
       " (78, 79, 4, 7, 74, 4, 7, 147, 7, 2, 7104),\n",
       " (32, 70, 2, 4, 67, 2, 4, 133, 3, 2, 1),\n",
       " (62, 8, 4, 8, 7, 4, 8, 14, 7, 1, 0),\n",
       " (61, 4, 4, 2, 2, 4, 2, 5, 7, 2, 6783),\n",
       " (66, 34, 4, 3, 31, 4, 3, 62, 7, 2, 2562),\n",
       " (63, 13, 4, 10, 12, 4, 10, 25, 7, 1, 0),\n",
       " (33, 77, 2, 7, 73, 3, 7, 146, 3, 0, 0),\n",
       " (21, 30, 2, 3, 30, 3, 3, 61, 3, 0, 1),\n",
       " (18, 19, 2, 5, 19, 3, 5, 41, 3, 0, 0),\n",
       " (15, 1, 2, 2, 1, 3, 2, 4, 3, 0, 0),\n",
       " (77, 73, 4, 4, 70, 4, 4, 138, 7, 2, 2745),\n",
       " (78, 79, 4, 7, 74, 4, 7, 147, 7, 2, 9129),\n",
       " (32, 70, 2, 4, 68, 3, 4, 136, 3, 0, 1),\n",
       " (19, 21, 2, 1, 22, 3, 1, 47, 3, 0, 0),\n",
       " (64, 23, 4, 1, 24, 4, 1, 49, 7, 1, 0),\n",
       " (61, 4, 4, 2, 2, 4, 2, 5, 7, 2, 3635),\n",
       " (66, 34, 4, 3, 31, 4, 3, 62, 7, 2, 6820),\n",
       " (21, 30, 2, 3, 30, 3, 3, 61, 3, 0, 1),\n",
       " (33, 77, 2, 7, 73, 3, 7, 146, 3, 0, 0),\n",
       " (15, 1, 2, 2, 1, 3, 2, 4, 3, 0, 0),\n",
       " (77, 73, 4, 4, 70, 4, 4, 138, 7, 2, 5398),\n",
       " (78, 79, 4, 7, 74, 4, 7, 147, 7, 2, 6084),\n",
       " (80, 87, 4, 0, 82, 4, 0, 165, 7, 2, 2967),\n",
       " (32, 70, 2, 4, 68, 3, 4, 136, 3, 0, 1),\n",
       " (18, 19, 2, 5, 19, 3, 5, 41, 3, 0, 0),\n",
       " (17, 11, 2, 10, 11, 3, 10, 24, 3, 0, 0),\n",
       " (61, 4, 4, 2, 2, 4, 2, 5, 7, 2, 4168),\n",
       " (16, 6, 2, 8, 5, 3, 8, 12, 3, 0, 0),\n",
       " (66, 34, 4, 3, 31, 4, 3, 62, 7, 2, 8068),\n",
       " (19, 21, 2, 1, 22, 3, 1, 47, 3, 0, 0),\n",
       " (33, 77, 2, 7, 73, 3, 7, 146, 3, 0, 0),\n",
       " (35, 85, 2, 0, 81, 3, 0, 164, 3, 0, 0),\n",
       " (21, 30, 2, 3, 30, 3, 3, 61, 3, 0, 1),\n",
       " (15, 1, 2, 2, 1, 3, 2, 4, 3, 0, 0),\n",
       " (77, 73, 4, 4, 70, 4, 4, 138, 7, 2, 6372),\n",
       " (32, 70, 2, 4, 68, 3, 4, 136, 3, 0, 1),\n",
       " (78, 79, 4, 7, 74, 4, 7, 147, 7, 2, 2948),\n",
       " (80, 87, 4, 0, 82, 4, 0, 165, 7, 2, 6757),\n",
       " (18, 19, 2, 5, 19, 3, 5, 41, 3, 0, 0),\n",
       " (61, 4, 4, 2, 2, 4, 2, 5, 7, 2, 6484),\n",
       " (17, 11, 2, 10, 11, 3, 10, 24, 3, 0, 0),\n",
       " (44, 37, 3, 11, 34, 3, 11, 67, 6, 1, 0),\n",
       " (16, 6, 2, 8, 5, 3, 8, 12, 3, 0, 0),\n",
       " (19, 21, 2, 1, 22, 3, 1, 47, 3, 0, 0),\n",
       " (21, 30, 2, 3, 30, 3, 3, 61, 3, 0, 1),\n",
       " (33, 77, 2, 7, 73, 3, 7, 146, 3, 0, 0),\n",
       " (79, 84, 4, 6, 79, 4, 6, 159, 7, 2, 2613),\n",
       " (66, 34, 4, 3, 31, 4, 3, 62, 7, 2, 6955),\n",
       " (15, 1, 2, 2, 1, 3, 2, 4, 3, 0, 0),\n",
       " (77, 73, 4, 4, 70, 4, 4, 138, 7, 2, 9356),\n",
       " (32, 70, 2, 4, 68, 3, 4, 136, 3, 0, 1),\n",
       " (18, 19, 2, 5, 19, 3, 5, 41, 3, 0, 0),\n",
       " (80, 87, 4, 0, 82, 4, 0, 165, 7, 2, 1992),\n",
       " (78, 79, 4, 7, 74, 4, 7, 147, 7, 2, 1235),\n",
       " (65, 26, 4, 9, 27, 4, 9, 55, 7, 1, 0),\n",
       " (61, 4, 4, 2, 2, 4, 2, 5, 7, 2, 4169),\n",
       " (56, 83, 3, 6, 78, 3, 6, 158, 3, 2, 1),\n",
       " (17, 11, 2, 10, 11, 3, 10, 24, 3, 0, 0),\n",
       " (21, 30, 2, 3, 30, 3, 3, 61, 3, 0, 1),\n",
       " (19, 21, 2, 1, 22, 3, 1, 47, 3, 0, 0),\n",
       " (16, 6, 2, 8, 5, 3, 8, 12, 3, 0, 0),\n",
       " (66, 34, 4, 3, 31, 4, 3, 62, 7, 2, 1989),\n",
       " (34, 82, 2, 6, 78, 3, 6, 158, 3, 0, 1),\n",
       " (35, 85, 2, 0, 81, 3, 0, 164, 3, 0, 0),\n",
       " (77, 73, 4, 4, 70, 4, 4, 138, 7, 2, 99),\n",
       " (18, 19, 2, 5, 19, 3, 5, 41, 3, 0, 0),\n",
       " (79, 84, 4, 6, 79, 4, 6, 159, 7, 2, 9058),\n",
       " (56, 83, 3, 6, 78, 3, 6, 157, 0, 2, 10033),\n",
       " (67, 38, 4, 11, 35, 4, 11, 70, 7, 1, 0),\n",
       " (22, 36, 2, 11, 33, 2, 11, 65, 5, 1, 0),\n",
       " (15, 1, 2, 2, 1, 3, 2, 4, 3, 0, 0),\n",
       " (33, 77, 2, 7, 73, 3, 7, 146, 3, 0, 0),\n",
       " (34, 82, 2, 6, 77, 2, 6, 155, 3, 2, 1),\n",
       " (32, 70, 2, 4, 68, 3, 4, 136, 3, 0, 1),\n",
       " (45, 41, 3, 13, 38, 3, 13, 75, 6, 1, 0),\n",
       " (80, 87, 4, 0, 82, 4, 0, 165, 7, 2, 4886),\n",
       " (78, 79, 4, 7, 74, 4, 7, 147, 7, 2, 7740),\n",
       " (61, 4, 4, 2, 2, 4, 2, 5, 7, 2, 8690),\n",
       " (68, 42, 4, 13, 39, 4, 13, 78, 7, 1, 0),\n",
       " (66, 34, 4, 3, 31, 4, 3, 62, 7, 2, 1517),\n",
       " (79, 84, 4, 6, 79, 4, 6, 159, 7, 2, 1033),\n",
       " (19, 21, 2, 1, 22, 3, 1, 47, 3, 0, 0),\n",
       " (21, 30, 2, 3, 30, 3, 3, 61, 3, 0, 1),\n",
       " (16, 6, 2, 8, 5, 3, 8, 12, 3, 0, 0),\n",
       " (33, 77, 2, 7, 73, 3, 7, 146, 3, 0, 0),\n",
       " (77, 73, 4, 4, 70, 4, 4, 138, 7, 2, 2887),\n",
       " (15, 1, 2, 2, 1, 3, 2, 4, 3, 0, 0),\n",
       " (35, 85, 2, 0, 81, 3, 0, 164, 3, 0, 0),\n",
       " (17, 11, 2, 10, 11, 3, 10, 24, 3, 0, 0),\n",
       " (32, 70, 2, 4, 68, 3, 4, 136, 3, 0, 1),\n",
       " (18, 19, 2, 5, 19, 3, 5, 41, 3, 0, 0),\n",
       " (64, 23, 4, 1, 24, 4, 1, 49, 7, 2, 7940),\n",
       " (34, 82, 2, 6, 78, 3, 6, 158, 3, 0, 1),\n",
       " (21, 30, 2, 3, 30, 3, 3, 61, 3, 0, 1),\n",
       " (33, 77, 2, 7, 73, 3, 7, 146, 3, 0, 0),\n",
       " (16, 6, 2, 8, 5, 3, 8, 12, 3, 0, 0),\n",
       " (19, 21, 2, 1, 22, 3, 1, 47, 3, 0, 0),\n",
       " (32, 70, 2, 4, 68, 3, 4, 136, 3, 0, 1),\n",
       " (17, 11, 2, 10, 11, 3, 10, 24, 3, 0, 0),\n",
       " (61, 4, 4, 2, 2, 4, 2, 5, 7, 2, 3506),\n",
       " (78, 79, 4, 7, 74, 4, 7, 147, 7, 2, 8927),\n",
       " (77, 73, 4, 4, 70, 4, 4, 138, 7, 2, 961),\n",
       " (79, 84, 4, 6, 79, 4, 6, 159, 7, 2, 4377),\n",
       " (80, 87, 4, 0, 82, 4, 0, 165, 7, 2, 9035),\n",
       " (66, 34, 4, 3, 31, 4, 3, 62, 7, 2, 719),\n",
       " (63, 13, 4, 10, 12, 4, 10, 25, 7, 2, 4527),\n",
       " (18, 19, 2, 5, 19, 3, 5, 41, 3, 0, 0),\n",
       " (35, 85, 2, 0, 81, 3, 0, 164, 3, 0, 0),\n",
       " (15, 1, 2, 2, 1, 3, 2, 4, 3, 0, 0),\n",
       " (46, 44, 3, 14, 41, 3, 14, 81, 6, 1, 0),\n",
       " (23, 40, 2, 13, 37, 2, 13, 73, 5, 1, 0),\n",
       " (64, 23, 4, 1, 24, 4, 1, 49, 7, 2, 8130),\n",
       " (34, 82, 2, 6, 78, 3, 6, 158, 3, 0, 1),\n",
       " (16, 6, 2, 8, 5, 3, 8, 12, 3, 0, 0),\n",
       " (80, 87, 4, 0, 82, 4, 0, 165, 7, 2, 1408),\n",
       " (61, 4, 4, 2, 2, 4, 2, 5, 7, 2, 7583),\n",
       " (78, 79, 4, 7, 74, 4, 7, 147, 7, 2, 2902),\n",
       " (79, 84, 4, 6, 79, 4, 6, 159, 7, 2, 5631),\n",
       " (77, 73, 4, 4, 70, 4, 4, 138, 7, 2, 4976),\n",
       " (21, 30, 2, 3, 30, 3, 3, 61, 3, 0, 1),\n",
       " (19, 21, 2, 1, 22, 3, 1, 47, 3, 0, 0),\n",
       " (62, 8, 4, 8, 7, 4, 8, 14, 7, 2, 5038),\n",
       " (33, 77, 2, 7, 73, 3, 7, 146, 3, 0, 0),\n",
       " (32, 70, 2, 4, 68, 3, 4, 136, 3, 0, 1),\n",
       " (18, 19, 2, 5, 19, 3, 5, 41, 3, 0, 0),\n",
       " (17, 11, 2, 10, 11, 3, 10, 24, 3, 0, 0),\n",
       " (35, 85, 2, 0, 81, 3, 0, 164, 3, 0, 0),\n",
       " (15, 1, 2, 2, 1, 3, 2, 4, 3, 0, 0),\n",
       " (66, 34, 4, 3, 31, 4, 3, 62, 7, 2, 5328),\n",
       " (63, 13, 4, 10, 12, 4, 10, 25, 7, 2, 728),\n",
       " (24, 43, 2, 14, 40, 2, 14, 79, 5, 1, 0),\n",
       " (25, 46, 2, 15, 43, 2, 15, 85, 5, 1, 0),\n",
       " (70, 48, 4, 15, 45, 4, 15, 90, 7, 1, 0),\n",
       " (16, 6, 2, 8, 5, 3, 8, 12, 3, 0, 0),\n",
       " (69, 45, 4, 14, 42, 4, 14, 84, 7, 1, 0),\n",
       " (47, 47, 3, 15, 44, 3, 15, 87, 6, 1, 0),\n",
       " (34, 82, 2, 6, 78, 3, 6, 158, 3, 0, 1),\n",
       " (77, 73, 4, 4, 70, 4, 4, 138, 7, 2, 9005),\n",
       " (79, 84, 4, 6, 79, 4, 6, 159, 7, 2, 1546),\n",
       " (64, 23, 4, 1, 24, 4, 1, 49, 7, 2, 3345),\n",
       " (61, 4, 4, 2, 2, 4, 2, 5, 7, 2, 9530),\n",
       " (78, 79, 4, 7, 74, 4, 7, 147, 7, 2, 1280),\n",
       " (62, 8, 4, 8, 7, 4, 8, 14, 7, 2, 5309),\n",
       " (57, 86, 3, 0, 81, 3, 0, 164, 3, 2, 1),\n",
       " (26, 49, 2, 16, 46, 2, 16, 91, 5, 1, 0),\n",
       " (48, 50, 3, 16, 47, 3, 16, 93, 6, 1, 0),\n",
       " (80, 87, 4, 0, 82, 4, 0, 165, 7, 2, 2021),\n",
       " (72, 55, 4, 17, 52, 4, 17, 103, 7, 1, 0),\n",
       " (21, 30, 2, 3, 30, 3, 3, 61, 3, 0, 1),\n",
       " (33, 77, 2, 7, 73, 3, 7, 146, 3, 0, 0),\n",
       " (19, 21, 2, 1, 22, 3, 1, 47, 3, 0, 0),\n",
       " (15, 1, 2, 2, 1, 3, 2, 4, 3, 0, 0),\n",
       " (35, 85, 2, 0, 81, 3, 0, 164, 3, 0, 0),\n",
       " (17, 11, 2, 10, 11, 3, 10, 24, 3, 0, 0),\n",
       " (32, 70, 2, 4, 68, 3, 4, 136, 3, 0, 1),\n",
       " (66, 34, 4, 3, 31, 4, 3, 62, 7, 2, 6436),\n",
       " (20, 24, 2, 9, 26, 3, 9, 54, 3, 0, 0),\n",
       " (18, 19, 2, 5, 19, 3, 5, 41, 3, 0, 0),\n",
       " (21, 30, 2, 3, 30, 3, 3, 61, 3, 0, 1),\n",
       " (16, 6, 2, 8, 5, 3, 8, 12, 3, 0, 0),\n",
       " (34, 82, 2, 6, 78, 3, 6, 158, 3, 0, 1),\n",
       " (15, 1, 2, 2, 1, 3, 2, 4, 3, 0, 0),\n",
       " (19, 21, 2, 1, 22, 3, 1, 47, 3, 0, 0),\n",
       " (27, 53, 2, 17, 50, 2, 17, 98, 5, 1, 0),\n",
       " (71, 51, 4, 16, 48, 4, 16, 96, 7, 1, 0),\n",
       " (50, 57, 3, 18, 54, 3, 18, 106, 6, 1, 0),\n",
       " (63, 13, 4, 10, 12, 4, 10, 25, 7, 2, 9505),\n",
       " (77, 73, 4, 4, 70, 4, 4, 138, 7, 2, 6103),\n",
       " (75, 64, 4, 20, 61, 4, 20, 121, 7, 1, 0),\n",
       " (49, 54, 3, 17, 51, 3, 17, 100, 6, 1, 0),\n",
       " (57, 86, 3, 0, 81, 3, 0, 163, 0, 2, 10034),\n",
       " (73, 58, 4, 18, 55, 4, 18, 109, 7, 1, 0),\n",
       " (64, 23, 4, 1, 24, 4, 1, 49, 7, 2, 3796),\n",
       " (61, 4, 4, 2, 2, 4, 2, 5, 7, 2, 4368),\n",
       " (17, 11, 2, 10, 11, 3, 10, 24, 3, 0, 0),\n",
       " (32, 70, 2, 4, 68, 3, 4, 136, 3, 0, 1),\n",
       " (51, 60, 3, 19, 57, 3, 19, 112, 6, 1, 0),\n",
       " (79, 84, 4, 6, 79, 4, 6, 159, 7, 2, 9334),\n",
       " (33, 77, 2, 7, 73, 3, 7, 146, 3, 0, 0),\n",
       " (28, 56, 2, 18, 53, 2, 18, 104, 5, 1, 0),\n",
       " (74, 61, 4, 19, 58, 4, 19, 115, 7, 1, 0),\n",
       " (62, 8, 4, 8, 7, 4, 8, 14, 7, 2, 3521),\n",
       " (35, 85, 2, 0, 81, 3, 0, 164, 3, 0, 1),\n",
       " (29, 59, 2, 19, 56, 2, 19, 110, 5, 1, 0),\n",
       " (78, 79, 4, 7, 74, 4, 7, 147, 7, 2, 9131),\n",
       " (31, 65, 2, 12, 62, 2, 12, 122, 5, 1, 0),\n",
       " (53, 66, 3, 12, 63, 3, 12, 124, 6, 1, 0),\n",
       " (80, 87, 4, 0, 82, 4, 0, 165, 7, 2, 6303),\n",
       " (70, 48, 4, 15, 45, 4, 15, 90, 7, 2, 2590),\n",
       " (30, 62, 2, 20, 59, 2, 20, 116, 5, 1, 0),\n",
       " (52, 63, 3, 20, 60, 3, 20, 118, 6, 1, 0),\n",
       " (76, 67, 4, 12, 64, 4, 12, 127, 7, 1, 0),\n",
       " (1, 81, 0, 6, 76, 0, 6, 151, 2, 1, 0),\n",
       " (21, 30, 2, 3, 30, 3, 3, 61, 3, 0, 1),\n",
       " (66, 34, 4, 3, 31, 4, 3, 62, 7, 2, 4015),\n",
       " (35, 85, 2, 0, 80, 2, 0, 161, 3, 2, 1),\n",
       " (2, 75, 0, 7, 71, 0, 7, 139, 2, 1, 0),\n",
       " (5, 16, 0, 5, 15, 0, 5, 30, 2, 1, 0),\n",
       " (4, 15, 0, 5, 14, 0, 5, 27, 2, 1, 0),\n",
       " (0, 80, 0, 6, 75, 0, 6, 148, 2, 1, 0),\n",
       " (18, 19, 2, 5, 19, 3, 5, 41, 3, 0, 0),\n",
       " (34, 82, 2, 6, 78, 3, 6, 158, 3, 0, 1),\n",
       " (6, 68, 1, 4, 65, 1, 4, 128, 4, 1, 0),\n",
       " (3, 9, 0, 10, 8, 0, 10, 15, 2, 1, 0),\n",
       " (19, 21, 2, 1, 22, 3, 1, 47, 3, 0, 0),\n",
       " (7, 5, 1, 8, 3, 1, 8, 6, 4, 1, 0),\n",
       " (20, 24, 2, 9, 26, 3, 9, 54, 3, 0, 0),\n",
       " (15, 1, 2, 2, 1, 3, 2, 4, 3, 0, 0),\n",
       " (8, 17, 1, 5, 16, 1, 5, 33, 4, 1, 0),\n",
       " (61, 4, 4, 2, 2, 4, 2, 5, 7, 2, 433),\n",
       " (16, 6, 2, 8, 5, 3, 8, 12, 3, 0, 0),\n",
       " (63, 13, 4, 10, 12, 4, 10, 25, 7, 2, 6904),\n",
       " (10, 39, 1, 13, 36, 1, 13, 71, 4, 1, 0),\n",
       " (9, 35, 1, 11, 32, 1, 11, 63, 4, 1, 0),\n",
       " (33, 77, 2, 7, 73, 3, 7, 146, 3, 0, 0),\n",
       " (12, 10, 6, 10, 9, 6, 10, 18, 9, 1, 0),\n",
       " (32, 70, 2, 4, 68, 3, 4, 136, 3, 0, 1),\n",
       " (77, 73, 4, 4, 70, 4, 4, 138, 7, 2, 785),\n",
       " (11, 69, 6, 4, 66, 6, 4, 130, 9, 1, 0),\n",
       " (64, 23, 4, 1, 24, 4, 1, 49, 7, 2, 3372),\n",
       " (17, 11, 2, 10, 11, 3, 10, 24, 3, 0, 0),\n",
       " (21, 30, 2, 3, 30, 3, 3, 61, 3, 0, 1),\n",
       " (79, 84, 4, 6, 79, 4, 6, 159, 7, 2, 9557),\n",
       " (18, 19, 2, 5, 19, 3, 5, 41, 3, 0, 0),\n",
       " (34, 82, 2, 6, 78, 3, 6, 158, 3, 0, 1),\n",
       " (62, 8, 4, 8, 7, 4, 8, 14, 7, 2, 1346),\n",
       " (13, 18, 6, 5, 17, 6, 5, 35, 9, 1, 0),\n",
       " (81, 88, 7, 0, 83, 7, 0, 166, 10, 1, 0),\n",
       " (82, 14, 7, 10, 13, 7, 10, 26, 10, 1, 0),\n",
       " (14, 52, 6, 17, 49, 6, 17, 97, 9, 1, 0),\n",
       " (83, 27, 7, 9, 28, 7, 9, 56, 10, 1, 0),\n",
       " (78, 79, 4, 7, 74, 4, 7, 147, 7, 2, 3802),\n",
       " (19, 21, 2, 1, 22, 3, 1, 47, 3, 0, 0),\n",
       " (70, 48, 4, 15, 45, 4, 15, 90, 7, 2, 1638),\n",
       " (68, 42, 4, 13, 39, 4, 13, 78, 7, 2, 4523),\n",
       " (35, 85, 2, 0, 81, 3, 0, 164, 3, 0, 1),\n",
       " (22, 36, 2, 11, 34, 3, 11, 69, 3, 0, 0),\n",
       " (15, 1, 2, 2, 1, 3, 2, 4, 3, 0, 0),\n",
       " (67, 38, 4, 11, 35, 4, 11, 70, 7, 2, 7786),\n",
       " (20, 24, 2, 9, 26, 3, 9, 54, 3, 0, 0),\n",
       " (65, 26, 4, 9, 27, 4, 9, 55, 7, 2, 4549),\n",
       " (66, 34, 4, 3, 31, 4, 3, 62, 7, 2, 1841),\n",
       " (80, 87, 4, 0, 82, 4, 0, 165, 7, 2, 5522),\n",
       " (61, 4, 4, 2, 2, 4, 2, 5, 7, 2, 6364),\n",
       " (16, 6, 2, 8, 5, 3, 8, 12, 3, 0, 0),\n",
       " (63, 13, 4, 10, 12, 4, 10, 25, 7, 2, 7225),\n",
       " (33, 77, 2, 7, 73, 3, 7, 146, 3, 0, 0),\n",
       " (14, 52, 6, 17, 35, 4, 11, 70, 7, 0, 7786),\n",
       " (14, 52, 6, 17, 39, 4, 13, 78, 7, 0, 4523),\n",
       " (14, 52, 6, 17, 45, 4, 15, 90, 7, 0, 1638),\n",
       " (24, 43, 2, 14, 41, 3, 14, 83, 3, 0, 0),\n",
       " (14, 52, 6, 17, 49, 6, 17, 97, 9, 2, 1),\n",
       " (32, 70, 2, 4, 68, 3, 4, 136, 3, 0, 1),\n",
       " (17, 11, 2, 10, 11, 3, 10, 24, 3, 0, 0),\n",
       " (21, 30, 2, 3, 30, 3, 3, 61, 3, 0, 1),\n",
       " (77, 73, 4, 4, 70, 4, 4, 138, 7, 2, 7731),\n",
       " (64, 23, 4, 1, 24, 4, 1, 49, 7, 2, 7809),\n",
       " (79, 84, 4, 6, 79, 4, 6, 159, 7, 2, 3615),\n",
       " (34, 82, 2, 6, 78, 3, 6, 158, 3, 0, 1),\n",
       " (18, 19, 2, 5, 19, 3, 5, 41, 3, 0, 0),\n",
       " (13, 18, 6, 5, 24, 4, 1, 49, 7, 0, 7809),\n",
       " (62, 8, 4, 8, 7, 4, 8, 14, 7, 2, 9129),\n",
       " (11, 69, 6, 4, 2, 4, 2, 5, 7, 0, 6364),\n",
       " (11, 69, 6, 4, 31, 4, 3, 62, 7, 0, 1841),\n",
       " (13, 18, 6, 5, 27, 4, 9, 55, 7, 0, 4549),\n",
       " (9, 35, 1, 11, 32, 1, 11, 64, 1, 2, 0),\n",
       " (13, 18, 6, 5, 17, 6, 5, 35, 9, 2, 1),\n",
       " (11, 69, 6, 4, 70, 4, 4, 138, 7, 0, 7731),\n",
       " (12, 10, 6, 10, 7, 4, 8, 14, 7, 0, 9129),\n",
       " (11, 69, 6, 4, 74, 4, 7, 147, 7, 0, 3802),\n",
       " (10, 39, 1, 13, 36, 1, 13, 72, 1, 2, 0),\n",
       " (12, 10, 6, 10, 12, 4, 10, 25, 7, 0, 7225),\n",
       " (78, 79, 4, 7, 74, 4, 7, 147, 7, 2, 6954),\n",
       " (70, 48, 4, 15, 45, 4, 15, 90, 7, 2, 9441),\n",
       " (11, 69, 6, 4, 79, 4, 6, 159, 7, 0, 3615),\n",
       " (23, 40, 2, 13, 38, 3, 13, 77, 3, 0, 0),\n",
       " (19, 21, 2, 1, 22, 3, 1, 47, 3, 0, 0),\n",
       " (68, 42, 4, 13, 39, 4, 13, 78, 7, 2, 1421),\n",
       " (8, 17, 1, 5, 16, 1, 5, 34, 1, 2, 0),\n",
       " (12, 10, 6, 10, 9, 6, 10, 18, 9, 2, 1),\n",
       " (11, 69, 6, 4, 82, 4, 0, 165, 7, 0, 5522),\n",
       " (65, 26, 4, 9, 27, 4, 9, 55, 7, 2, 498),\n",
       " (66, 34, 4, 3, 31, 4, 3, 62, 7, 2, 2888),\n",
       " (20, 24, 2, 9, 26, 3, 9, 54, 3, 0, 0),\n",
       " (15, 1, 2, 2, 1, 3, 2, 4, 3, 0, 0),\n",
       " (67, 38, 4, 11, 35, 4, 11, 70, 7, 2, 8456),\n",
       " (35, 85, 2, 0, 81, 3, 0, 164, 3, 0, 1),\n",
       " (11, 69, 6, 4, 66, 6, 4, 130, 9, 2, 1),\n",
       " (22, 36, 2, 11, 34, 3, 11, 69, 3, 0, 0),\n",
       " (80, 87, 4, 0, 82, 4, 0, 165, 7, 2, 5936),\n",
       " (61, 4, 4, 2, 2, 4, 2, 5, 7, 2, 5325),\n",
       " (63, 13, 4, 10, 12, 4, 10, 25, 7, 2, 7490),\n",
       " (33, 77, 2, 7, 73, 3, 7, 146, 3, 0, 0),\n",
       " (16, 6, 2, 8, 5, 3, 8, 12, 3, 0, 0),\n",
       " (7, 5, 1, 8, 3, 1, 8, 7, 1, 2, 0),\n",
       " (21, 30, 2, 3, 30, 3, 3, 61, 3, 0, 1),\n",
       " (77, 73, 4, 4, 70, 4, 4, 138, 7, 2, 3019),\n",
       " (64, 23, 4, 1, 24, 4, 1, 49, 7, 2, 8697),\n",
       " (17, 11, 2, 10, 11, 3, 10, 24, 3, 0, 0),\n",
       " (79, 84, 4, 6, 79, 4, 6, 159, 7, 2, 5542),\n",
       " (18, 19, 2, 5, 19, 3, 5, 41, 3, 0, 0),\n",
       " (3, 9, 0, 10, 8, 0, 10, 16, 0, 0, 23),\n",
       " (62, 8, 4, 8, 7, 4, 8, 14, 7, 2, 6200),\n",
       " (34, 82, 2, 6, 78, 3, 6, 158, 3, 0, 1),\n",
       " (32, 70, 2, 4, 68, 3, 4, 136, 3, 0, 1),\n",
       " (24, 43, 2, 14, 41, 3, 14, 83, 3, 0, 0),\n",
       " (6, 68, 1, 4, 65, 1, 4, 129, 1, 2, 0),\n",
       " (70, 48, 4, 15, 45, 4, 15, 90, 7, 2, 5026),\n",
       " (78, 79, 4, 7, 74, 4, 7, 147, 7, 2, 5547),\n",
       " (19, 21, 2, 1, 22, 3, 1, 47, 3, 0, 0),\n",
       " (68, 42, 4, 13, 39, 4, 13, 78, 7, 2, 1504),\n",
       " (23, 40, 2, 13, 38, 3, 13, 77, 3, 0, 0),\n",
       " (8, 17, 1, 5, 16, 1, 5, 34, 1, 0, 0),\n",
       " (10, 39, 1, 13, 36, 1, 13, 72, 1, 0, 0),\n",
       " (82, 14, 7, 10, 8, 0, 10, 16, 0, 0, 23),\n",
       " (9, 35, 1, 11, 32, 1, 11, 64, 1, 0, 0),\n",
       " (67, 38, 4, 11, 35, 4, 11, 70, 7, 2, 10014),\n",
       " (66, 34, 4, 3, 31, 4, 3, 62, 7, 2, 2098),\n",
       " (0, 80, 0, 6, 75, 0, 6, 149, 0, 0, 23),\n",
       " (20, 24, 2, 9, 26, 3, 9, 54, 3, 0, 0),\n",
       " (3, 9, 0, 10, 8, 0, 10, 17, 1, 0, 0),\n",
       " (35, 85, 2, 0, 81, 3, 0, 164, 3, 0, 1),\n",
       " (65, 26, 4, 9, 27, 4, 9, 55, 7, 2, 788),\n",
       " (7, 5, 1, 8, 3, 1, 8, 7, 1, 0, 0),\n",
       " (15, 1, 2, 2, 1, 3, 2, 4, 3, 0, 0),\n",
       " (82, 14, 7, 10, 8, 0, 10, 17, 1, 0, 0),\n",
       " (33, 77, 2, 7, 73, 3, 7, 146, 3, 0, 0),\n",
       " (82, 14, 7, 10, 8, 0, 10, 16, 0, 0, 23),\n",
       " (22, 36, 2, 11, 34, 3, 11, 69, 3, 0, 0),\n",
       " (61, 4, 4, 2, 2, 4, 2, 5, 7, 2, 8874),\n",
       " (80, 87, 4, 0, 82, 4, 0, 165, 7, 2, 800),\n",
       " (63, 13, 4, 10, 12, 4, 10, 25, 7, 2, 875),\n",
       " (82, 14, 7, 10, 8, 0, 10, 16, 0, 2, 22),\n",
       " (16, 6, 2, 8, 5, 3, 8, 12, 3, 0, 0),\n",
       " (3, 9, 0, 10, 8, 0, 10, 16, 0, 0, 22),\n",
       " (4, 15, 0, 5, 14, 0, 5, 28, 0, 0, 23),\n",
       " (21, 30, 2, 3, 30, 3, 3, 61, 3, 0, 1),\n",
       " (82, 14, 7, 10, 8, 0, 10, 16, 0, 0, 22),\n",
       " (17, 11, 2, 10, 11, 3, 10, 24, 3, 0, 0),\n",
       " (79, 84, 4, 6, 79, 4, 6, 159, 7, 2, 6176),\n",
       " (5, 16, 0, 5, 15, 0, 5, 31, 0, 0, 23),\n",
       " (3, 9, 0, 10, 8, 0, 10, 16, 0, 0, 22),\n",
       " (0, 80, 0, 6, 75, 0, 6, 150, 1, 0, 0),\n",
       " (64, 23, 4, 1, 24, 4, 1, 49, 7, 2, 3040),\n",
       " (77, 73, 4, 4, 70, 4, 4, 138, 7, 2, 6082),\n",
       " (34, 82, 2, 6, 78, 3, 6, 158, 3, 0, 1),\n",
       " (18, 19, 2, 5, 19, 3, 5, 41, 3, 0, 0),\n",
       " (32, 70, 2, 4, 68, 3, 4, 136, 3, 0, 1),\n",
       " (62, 8, 4, 8, 7, 4, 8, 14, 7, 2, 6933),\n",
       " (24, 43, 2, 14, 41, 3, 14, 83, 3, 0, 0),\n",
       " (2, 75, 0, 7, 71, 0, 7, 140, 0, 0, 23),\n",
       " (6, 68, 1, 4, 65, 1, 4, 129, 1, 0, 0),\n",
       " (83, 27, 7, 9, 14, 0, 5, 28, 0, 0, 23),\n",
       " (0, 80, 0, 6, 75, 0, 6, 149, 0, 0, 23),\n",
       " (19, 21, 2, 1, 22, 3, 1, 47, 3, 0, 0),\n",
       " (70, 48, 4, 15, 45, 4, 15, 90, 7, 2, 8110),\n",
       " (78, 79, 4, 7, 74, 4, 7, 147, 7, 2, 5304),\n",
       " (68, 42, 4, 13, 39, 4, 13, 78, 7, 2, 2103),\n",
       " (83, 27, 7, 9, 15, 0, 5, 31, 0, 0, 23),\n",
       " (4, 15, 0, 5, 14, 0, 5, 29, 1, 0, 0),\n",
       " (4, 15, 0, 5, 14, 0, 5, 28, 0, 0, 23),\n",
       " (83, 27, 7, 9, 14, 0, 5, 29, 1, 0, 0),\n",
       " (5, 16, 0, 5, 15, 0, 5, 32, 1, 0, 0),\n",
       " (81, 88, 7, 0, 75, 0, 6, 149, 0, 0, 23),\n",
       " (23, 40, 2, 13, 38, 3, 13, 77, 3, 0, 0),\n",
       " (81, 88, 7, 0, 71, 0, 7, 140, 0, 0, 23),\n",
       " (83, 27, 7, 9, 14, 0, 5, 28, 0, 0, 23),\n",
       " (1, 81, 0, 6, 76, 0, 6, 152, 0, 0, 23),\n",
       " (83, 27, 7, 9, 14, 0, 5, 28, 0, 2, 22),\n",
       " (2, 75, 0, 7, 71, 0, 7, 141, 1, 0, 0),\n",
       " (67, 38, 4, 11, 35, 4, 11, 70, 7, 2, 9642),\n",
       " (81, 88, 7, 0, 75, 0, 6, 150, 1, 0, 0),\n",
       " (20, 24, 2, 9, 26, 3, 9, 54, 3, 0, 0),\n",
       " (3, 9, 0, 10, 8, 0, 10, 16, 0, 0, 22),\n",
       " (35, 85, 2, 0, 81, 3, 0, 164, 3, 0, 1),\n",
       " (65, 26, 4, 9, 27, 4, 9, 55, 7, 2, 6352),\n",
       " (15, 1, 2, 2, 1, 3, 2, 4, 3, 0, 0),\n",
       " (83, 27, 7, 9, 14, 0, 5, 28, 0, 0, 22),\n",
       " (81, 88, 7, 0, 75, 0, 6, 149, 0, 0, 23),\n",
       " (3, 9, 0, 10, 8, 0, 10, 17, 1, 0, 0),\n",
       " (66, 34, 4, 3, 31, 4, 3, 62, 7, 2, 10002),\n",
       " (4, 15, 0, 5, 14, 0, 5, 28, 0, 0, 22),\n",
       " (33, 77, 2, 7, 73, 3, 7, 146, 3, 0, 0),\n",
       " (22, 36, 2, 11, 34, 3, 11, 69, 3, 0, 0),\n",
       " (81, 88, 7, 0, 75, 0, 6, 149, 0, 2, 22),\n",
       " (76, 67, 4, 12, 64, 4, 12, 127, 7, 2, 5998),\n",
       " (61, 4, 4, 2, 2, 4, 2, 5, 7, 2, 3119),\n",
       " (63, 13, 4, 10, 12, 4, 10, 25, 7, 2, 8037),\n",
       " (80, 87, 4, 0, 82, 4, 0, 165, 7, 2, 8395),\n",
       " (16, 6, 2, 8, 5, 3, 8, 12, 3, 0, 0),\n",
       " (81, 88, 7, 0, 75, 0, 6, 149, 0, 0, 22),\n",
       " (82, 14, 7, 10, 8, 0, 10, 17, 1, 0, 0),\n",
       " (0, 80, 0, 6, 75, 0, 6, 149, 0, 0, 22),\n",
       " (79, 84, 4, 6, 79, 4, 6, 159, 7, 2, 5822),\n",
       " (21, 30, 2, 3, 30, 3, 3, 61, 3, 0, 1),\n",
       " (17, 11, 2, 10, 11, 3, 10, 24, 3, 0, 0),\n",
       " (82, 14, 7, 10, 8, 0, 10, 16, 0, 0, 22),\n",
       " (82, 14, 7, 10, 8, 0, 10, 16, 0, 2, 21),\n",
       " (1, 81, 0, 6, 76, 0, 6, 153, 1, 0, 0),\n",
       " (82, 14, 7, 10, 8, 0, 10, 16, 0, 0, 21),\n",
       " (3, 9, 0, 10, 8, 0, 10, 16, 0, 0, 21),\n",
       " (5, 16, 0, 5, 15, 0, 5, 31, 0, 0, 23),\n",
       " (18, 19, 2, 5, 19, 3, 5, 41, 3, 0, 0),\n",
       " (77, 73, 4, 4, 70, 4, 4, 138, 7, 2, 2661),\n",
       " (2, 75, 0, 7, 71, 0, 7, 140, 0, 0, 23),\n",
       " (32, 70, 2, 4, 68, 3, 4, 136, 3, 0, 1),\n",
       " (34, 82, 2, 6, 78, 3, 6, 158, 3, 0, 1),\n",
       " (62, 8, 4, 8, 7, 4, 8, 14, 7, 2, 8078),\n",
       " (0, 80, 0, 6, 75, 0, 6, 149, 0, 0, 22),\n",
       " (0, 80, 0, 6, 75, 0, 6, 150, 1, 0, 0),\n",
       " (64, 23, 4, 1, 24, 4, 1, 49, 7, 2, 6323),\n",
       " (24, 43, 2, 14, 41, 3, 14, 83, 3, 0, 0),\n",
       " (1, 81, 0, 6, 76, 0, 6, 152, 0, 0, 23),\n",
       " (19, 21, 2, 1, 22, 3, 1, 47, 3, 0, 0),\n",
       " (30, 62, 2, 20, 60, 3, 20, 120, 3, 0, 0),\n",
       " (4, 15, 0, 5, 14, 0, 5, 28, 0, 0, 22),\n",
       " (4, 15, 0, 5, 14, 0, 5, 29, 1, 0, 0),\n",
       " (68, 42, 4, 13, 39, 4, 13, 78, 7, 2, 2875),\n",
       " (78, 79, 4, 7, 74, 4, 7, 147, 7, 2, 4123),\n",
       " (70, 48, 4, 15, 45, 4, 15, 90, 7, 2, 6730),\n",
       " (23, 40, 2, 13, 38, 3, 13, 77, 3, 0, 0),\n",
       " (5, 16, 0, 5, 15, 0, 5, 31, 0, 0, 23),\n",
       " (5, 16, 0, 5, 15, 0, 5, 32, 1, 0, 0),\n",
       " (65, 26, 4, 9, 27, 4, 9, 55, 7, 2, 8026),\n",
       " (67, 38, 4, 11, 35, 4, 11, 70, 7, 2, 4499),\n",
       " (15, 1, 2, 2, 1, 3, 2, 4, 3, 0, 0),\n",
       " (66, 34, 4, 3, 31, 4, 3, 62, 7, 2, 6196),\n",
       " (3, 9, 0, 10, 8, 0, 10, 16, 0, 0, 21),\n",
       " (20, 24, 2, 9, 26, 3, 9, 54, 3, 0, 0),\n",
       " (33, 77, 2, 7, 73, 3, 7, 146, 3, 0, 0),\n",
       " (83, 27, 7, 9, 14, 0, 5, 29, 1, 0, 0),\n",
       " (3, 9, 0, 10, 8, 0, 10, 17, 1, 0, 0),\n",
       " (35, 85, 2, 0, 81, 3, 0, 164, 3, 0, 1),\n",
       " (2, 75, 0, 7, 71, 0, 7, 140, 0, 0, 23),\n",
       " (83, 27, 7, 9, 14, 0, 5, 28, 0, 0, 22),\n",
       " (2, 75, 0, 7, 71, 0, 7, 141, 1, 0, 0),\n",
       " (22, 36, 2, 11, 34, 3, 11, 69, 3, 0, 0),\n",
       " (83, 27, 7, 9, 14, 0, 5, 28, 0, 2, 21),\n",
       " (83, 27, 7, 9, 14, 0, 5, 28, 0, 0, 21),\n",
       " (4, 15, 0, 5, 14, 0, 5, 28, 0, 0, 21),\n",
       " (74, 61, 4, 19, 58, 4, 19, 115, 7, 2, 9215),\n",
       " (61, 4, 4, 2, 2, 4, 2, 5, 7, 2, 8042),\n",
       " (75, 64, 4, 20, 61, 4, 20, 121, 7, 2, 3608),\n",
       " (16, 6, 2, 8, 5, 3, 8, 12, 3, 0, 0),\n",
       " (63, 13, 4, 10, 12, 4, 10, 25, 7, 2, 174),\n",
       " (80, 87, 4, 0, 82, 4, 0, 165, 7, 2, 6774),\n",
       " (76, 67, 4, 12, 64, 4, 12, 127, 7, 2, 6011),\n",
       " (81, 88, 7, 0, 75, 0, 6, 150, 1, 0, 0),\n",
       " (79, 84, 4, 6, 79, 4, 6, 159, 7, 2, 1207),\n",
       " (21, 30, 2, 3, 30, 3, 3, 61, 3, 0, 1),\n",
       " (17, 11, 2, 10, 11, 3, 10, 24, 3, 0, 0),\n",
       " (81, 88, 7, 0, 75, 0, 6, 149, 0, 0, 22),\n",
       " (73, 58, 4, 18, 55, 4, 18, 109, 7, 2, 607),\n",
       " (81, 88, 7, 0, 75, 0, 6, 149, 0, 2, 21),\n",
       " (0, 80, 0, 6, 75, 0, 6, 149, 0, 0, 21),\n",
       " (81, 88, 7, 0, 75, 0, 6, 149, 0, 0, 21),\n",
       " (71, 51, 4, 16, 48, 4, 16, 96, 7, 2, 9939),\n",
       " (82, 14, 7, 10, 8, 0, 10, 17, 1, 0, 0),\n",
       " (18, 19, 2, 5, 19, 3, 5, 41, 3, 0, 0),\n",
       " (32, 70, 2, 4, 68, 3, 4, 136, 3, 0, 1),\n",
       " (27, 53, 2, 17, 51, 3, 17, 102, 3, 0, 0),\n",
       " (77, 73, 4, 4, 70, 4, 4, 138, 7, 2, 5910),\n",
       " (82, 14, 7, 10, 8, 0, 10, 16, 0, 0, 21),\n",
       " (34, 82, 2, 6, 78, 3, 6, 158, 3, 0, 1),\n",
       " (82, 14, 7, 10, 8, 0, 10, 16, 0, 2, 20),\n",
       " (82, 14, 7, 10, 8, 0, 10, 16, 0, 0, 20),\n",
       " (62, 8, 4, 8, 7, 4, 8, 14, 7, 2, 1501),\n",
       " (3, 9, 0, 10, 8, 0, 10, 16, 0, 0, 20),\n",
       " (1, 81, 0, 6, 76, 0, 6, 152, 0, 0, 23),\n",
       " (1, 81, 0, 6, 76, 0, 6, 153, 1, 0, 0),\n",
       " (0, 80, 0, 6, 75, 0, 6, 149, 0, 0, 21),\n",
       " (64, 23, 4, 1, 24, 4, 1, 49, 7, 2, 7023),\n",
       " (0, 80, 0, 6, 75, 0, 6, 150, 1, 0, 0),\n",
       " (24, 43, 2, 14, 41, 3, 14, 83, 3, 0, 0),\n",
       " (72, 55, 4, 17, 52, 4, 17, 103, 7, 2, 8411),\n",
       " (26, 49, 2, 16, 47, 3, 16, 95, 3, 0, 0),\n",
       " (19, 21, 2, 1, 22, 3, 1, 47, 3, 0, 0),\n",
       " (4, 15, 0, 5, 14, 0, 5, 28, 0, 0, 21),\n",
       " (4, 15, 0, 5, 14, 0, 5, 29, 1, 0, 0),\n",
       " (68, 42, 4, 13, 39, 4, 13, 78, 7, 2, 9263),\n",
       " (78, 79, 4, 7, 74, 4, 7, 147, 7, 2, 5665),\n",
       " (69, 45, 4, 14, 42, 4, 14, 84, 7, 2, 4016),\n",
       " (23, 40, 2, 13, 38, 3, 13, 77, 3, 0, 0),\n",
       " (70, 48, 4, 15, 45, 4, 15, 90, 7, 2, 8375),\n",
       " (5, 16, 0, 5, 15, 0, 5, 31, 0, 0, 23),\n",
       " (30, 62, 2, 20, 60, 3, 20, 120, 3, 0, 0),\n",
       " (5, 16, 0, 5, 15, 0, 5, 32, 1, 0, 0),\n",
       " (31, 65, 2, 12, 63, 3, 12, 126, 3, 0, 0),\n",
       " (15, 1, 2, 2, 1, 3, 2, 4, 3, 0, 0),\n",
       " (29, 59, 2, 19, 57, 3, 19, 114, 3, 0, 0),\n",
       " (65, 26, 4, 9, 27, 4, 9, 55, 7, 2, 8199),\n",
       " (67, 38, 4, 11, 35, 4, 11, 70, 7, 2, 8181),\n",
       " (66, 34, 4, 3, 31, 4, 3, 62, 7, 2, 8642),\n",
       " (35, 85, 2, 0, 81, 3, 0, 164, 3, 0, 1),\n",
       " (33, 77, 2, 7, 73, 3, 7, 146, 3, 0, 0),\n",
       " (20, 24, 2, 9, 26, 3, 9, 54, 3, 0, 0),\n",
       " (3, 9, 0, 10, 8, 0, 10, 16, 0, 0, 20),\n",
       " (2, 75, 0, 7, 71, 0, 7, 140, 0, 0, 23),\n",
       " (3, 9, 0, 10, 8, 0, 10, 17, 1, 0, 0),\n",
       " (2, 75, 0, 7, 71, 0, 7, 141, 1, 0, 0),\n",
       " (22, 36, 2, 11, 34, 3, 11, 69, 3, 0, 0),\n",
       " (83, 27, 7, 9, 14, 0, 5, 29, 1, 0, 0),\n",
       " (83, 27, 7, 9, 14, 0, 5, 28, 0, 0, 21),\n",
       " (83, 27, 7, 9, 14, 0, 5, 28, 0, 2, 20),\n",
       " (4, 15, 0, 5, 14, 0, 5, 28, 0, 0, 20),\n",
       " (83, 27, 7, 9, 14, 0, 5, 28, 0, 0, 20),\n",
       " (28, 56, 2, 18, 54, 3, 18, 108, 3, 0, 0),\n",
       " (74, 61, 4, 19, 58, 4, 19, 115, 7, 2, 9872),\n",
       " (61, 4, 4, 2, 2, 4, 2, 5, 7, 2, 5802),\n",
       " (75, 64, 4, 20, 61, 4, 20, 121, 7, 2, 875),\n",
       " (16, 6, 2, 8, 5, 3, 8, 12, 3, 0, 0),\n",
       " (80, 87, 4, 0, 82, 4, 0, 165, 7, 2, 3577),\n",
       " (63, 13, 4, 10, 12, 4, 10, 25, 7, 2, 5768),\n",
       " (76, 67, 4, 12, 64, 4, 12, 127, 7, 2, 883),\n",
       " (21, 30, 2, 3, 30, 3, 3, 61, 3, 0, 1),\n",
       " (79, 84, 4, 6, 79, 4, 6, 159, 7, 2, 8568),\n",
       " (17, 11, 2, 10, 11, 3, 10, 24, 3, 0, 0),\n",
       " (73, 58, 4, 18, 55, 4, 18, 109, 7, 2, 8504),\n",
       " (81, 88, 7, 0, 75, 0, 6, 150, 1, 0, 0),\n",
       " (81, 88, 7, 0, 75, 0, 6, 149, 0, 0, 21),\n",
       " (81, 88, 7, 0, 75, 0, 6, 149, 0, 2, 20),\n",
       " (0, 80, 0, 6, 75, 0, 6, 149, 0, 0, 20),\n",
       " (71, 51, 4, 16, 48, 4, 16, 96, 7, 2, 4843),\n",
       " (77, 73, 4, 4, 70, 4, 4, 138, 7, 2, 6122),\n",
       " (18, 19, 2, 5, 19, 3, 5, 41, 3, 0, 0),\n",
       " (32, 70, 2, 4, 68, 3, 4, 136, 3, 0, 1),\n",
       " (81, 88, 7, 0, 75, 0, 6, 149, 0, 0, 20),\n",
       " (82, 14, 7, 10, 8, 0, 10, 17, 1, 0, 0),\n",
       " (62, 8, 4, 8, 7, 4, 8, 14, 7, 2, 4101),\n",
       " (34, 82, 2, 6, 78, 3, 6, 158, 3, 0, 1),\n",
       " (25, 46, 2, 15, 44, 3, 15, 89, 3, 0, 0),\n",
       " (82, 14, 7, 10, 8, 0, 10, 16, 0, 0, 20),\n",
       " (1, 81, 0, 6, 76, 0, 6, 152, 0, 0, 23),\n",
       " (82, 14, 7, 10, 8, 0, 10, 16, 0, 2, 18),\n",
       " (64, 23, 4, 1, 24, 4, 1, 49, 7, 2, 5048),\n",
       " (24, 43, 2, 14, 41, 3, 14, 83, 3, 0, 0),\n",
       " (0, 80, 0, 6, 75, 0, 6, 149, 0, 0, 20),\n",
       " (3, 9, 0, 10, 8, 0, 10, 16, 0, 0, 18),\n",
       " (27, 53, 2, 17, 51, 3, 17, 102, 3, 0, 0),\n",
       " (0, 80, 0, 6, 75, 0, 6, 150, 1, 0, 0),\n",
       " (72, 55, 4, 17, 52, 4, 17, 103, 7, 2, 7306),\n",
       " (82, 14, 7, 10, 8, 0, 10, 16, 0, 0, 18),\n",
       " (1, 81, 0, 6, 76, 0, 6, 153, 1, 0, 0),\n",
       " (19, 21, 2, 1, 22, 3, 1, 47, 3, 0, 0),\n",
       " (4, 15, 0, 5, 14, 0, 5, 28, 0, 0, 20),\n",
       " (4, 15, 0, 5, 14, 0, 5, 29, 1, 0, 0),\n",
       " (26, 49, 2, 16, 47, 3, 16, 95, 3, 0, 0),\n",
       " (78, 79, 4, 7, 74, 4, 7, 147, 7, 2, 8681),\n",
       " (69, 45, 4, 14, 42, 4, 14, 84, 7, 2, 6879),\n",
       " (23, 40, 2, 13, 38, 3, 13, 77, 3, 0, 0),\n",
       " (68, 42, 4, 13, 39, 4, 13, 78, 7, 2, 2442),\n",
       " (70, 48, 4, 15, 45, 4, 15, 90, 7, 2, 1023),\n",
       " (30, 62, 2, 20, 60, 3, 20, 120, 3, 0, 0),\n",
       " (5, 16, 0, 5, 15, 0, 5, 31, 0, 0, 23),\n",
       " (5, 16, 0, 5, 15, 0, 5, 32, 1, 0, 0),\n",
       " (15, 1, 2, 2, 1, 3, 2, 4, 3, 0, 0),\n",
       " (67, 38, 4, 11, 35, 4, 11, 70, 7, 2, 2417),\n",
       " (31, 65, 2, 12, 63, 3, 12, 126, 3, 0, 0),\n",
       " (65, 26, 4, 9, 27, 4, 9, 55, 7, 2, 728),\n",
       " (66, 34, 4, 3, 31, 4, 3, 62, 7, 2, 9058),\n",
       " (33, 77, 2, 7, 73, 3, 7, 146, 3, 0, 0),\n",
       " (20, 24, 2, 9, 26, 3, 9, 54, 3, 0, 0),\n",
       " (29, 59, 2, 19, 57, 3, 19, 114, 3, 0, 0),\n",
       " (35, 85, 2, 0, 81, 3, 0, 164, 3, 0, 1),\n",
       " (3, 9, 0, 10, 8, 0, 10, 16, 0, 0, 18),\n",
       " (22, 36, 2, 11, 34, 3, 11, 69, 3, 0, 0),\n",
       " (2, 75, 0, 7, 71, 0, 7, 140, 0, 0, 23),\n",
       " (2, 75, 0, 7, 71, 0, 7, 141, 1, 0, 0),\n",
       " (3, 9, 0, 10, 8, 0, 10, 17, 1, 0, 0),\n",
       " (83, 27, 7, 9, 14, 0, 5, 29, 1, 0, 0),\n",
       " (83, 27, 7, 9, 14, 0, 5, 28, 0, 0, 20),\n",
       " (83, 27, 7, 9, 14, 0, 5, 28, 0, 2, 18),\n",
       " (4, 15, 0, 5, 14, 0, 5, 28, 0, 0, 18),\n",
       " (83, 27, 7, 9, 14, 0, 5, 28, 0, 0, 18),\n",
       " (74, 61, 4, 19, 58, 4, 19, 115, 7, 2, 933),\n",
       " (28, 56, 2, 18, 54, 3, 18, 108, 3, 0, 0),\n",
       " (61, 4, 4, 2, 2, 4, 2, 5, 7, 2, 2173),\n",
       " (75, 64, 4, 20, 61, 4, 20, 121, 7, 2, 8381),\n",
       " (16, 6, 2, 8, 5, 3, 8, 12, 3, 0, 0),\n",
       " (80, 87, 4, 0, 82, 4, 0, 165, 7, 2, 3586),\n",
       " (63, 13, 4, 10, 12, 4, 10, 25, 7, 2, 7825),\n",
       " (76, 67, 4, 12, 64, 4, 12, 127, 7, 2, 6567),\n",
       " (21, 30, 2, 3, 30, 3, 3, 61, 3, 0, 1),\n",
       " (79, 84, 4, 6, 79, 4, 6, 159, 7, 2, 5105),\n",
       " (17, 11, 2, 10, 11, 3, 10, 24, 3, 0, 0),\n",
       " (73, 58, 4, 18, 55, 4, 18, 109, 7, 2, 3771),\n",
       " (18, 19, 2, 5, 19, 3, 5, 41, 3, 0, 0),\n",
       " (32, 70, 2, 4, 68, 3, 4, 136, 3, 0, 1),\n",
       " (81, 88, 7, 0, 75, 0, 6, 150, 1, 0, 0),\n",
       " (81, 88, 7, 0, 75, 0, 6, 149, 0, 0, 20),\n",
       " (81, 88, 7, 0, 75, 0, 6, 149, 0, 2, 18),\n",
       " (77, 73, 4, 4, 70, 4, 4, 138, 7, 2, 6009),\n",
       " (62, 8, 4, 8, 7, 4, 8, 14, 7, 2, 3309),\n",
       " (71, 51, 4, 16, 48, 4, 16, 96, 7, 2, 5627),\n",
       " (34, 82, 2, 6, 78, 3, 6, 158, 3, 0, 1),\n",
       " (81, 88, 7, 0, 75, 0, 6, 149, 0, 0, 18),\n",
       " (0, 80, 0, 6, 75, 0, 6, 149, 0, 0, 18),\n",
       " (25, 46, 2, 15, 44, 3, 15, 89, 3, 0, 0),\n",
       " (64, 23, 4, 1, 24, 4, 1, 49, 7, 2, 8719),\n",
       " (24, 43, 2, 14, 41, 3, 14, 83, 3, 0, 0),\n",
       " (0, 80, 0, 6, 75, 0, 6, 149, 0, 0, 18),\n",
       " (72, 55, 4, 17, 52, 4, 17, 103, 7, 2, 8976),\n",
       " (82, 14, 7, 10, 8, 0, 10, 17, 1, 0, 0),\n",
       " (1, 81, 0, 6, 76, 0, 6, 152, 0, 0, 23),\n",
       " (27, 53, 2, 17, 51, 3, 17, 102, 3, 0, 0),\n",
       " (82, 14, 7, 10, 8, 0, 10, 16, 0, 0, 18),\n",
       " (82, 14, 7, 10, 8, 0, 10, 16, 0, 2, 12),\n",
       " (0, 80, 0, 6, 75, 0, 6, 150, 1, 0, 0),\n",
       " (1, 81, 0, 6, 76, 0, 6, 153, 1, 0, 0),\n",
       " (19, 21, 2, 1, 22, 3, 1, 47, 3, 0, 0),\n",
       " (3, 9, 0, 10, 8, 0, 10, 16, 0, 0, 12),\n",
       " (82, 14, 7, 10, 8, 0, 10, 16, 0, 0, 12),\n",
       " (4, 15, 0, 5, 14, 0, 5, 28, 0, 0, 18),\n",
       " (4, 15, 0, 5, 14, 0, 5, 29, 1, 0, 0),\n",
       " (26, 49, 2, 16, 47, 3, 16, 95, 3, 0, 0),\n",
       " (78, 79, 4, 7, 74, 4, 7, 147, 7, 2, 5956),\n",
       " (69, 45, 4, 14, 42, 4, 14, 84, 7, 2, 9443),\n",
       " (23, 40, 2, 13, 38, 3, 13, 77, 3, 0, 0),\n",
       " (68, 42, 4, 13, 39, 4, 13, 78, 7, 2, 5357),\n",
       " (70, 48, 4, 15, 45, 4, 15, 90, 7, 2, 4088),\n",
       " (30, 62, 2, 20, 60, 3, 20, 120, 3, 0, 0),\n",
       " (5, 16, 0, 5, 15, 0, 5, 31, 0, 0, 23),\n",
       " (5, 16, 0, 5, 15, 0, 5, 32, 1, 0, 0),\n",
       " (15, 1, 2, 2, 1, 3, 2, 4, 3, 0, 0),\n",
       " (67, 38, 4, 11, 35, 4, 11, 70, 7, 2, 4961),\n",
       " (31, 65, 2, 12, 63, 3, 12, 126, 3, 0, 0),\n",
       " (65, 26, 4, 9, 27, 4, 9, 55, 7, 2, 9060),\n",
       " (66, 34, 4, 3, 31, 4, 3, 62, 7, 2, 1235),\n",
       " (20, 24, 2, 9, 26, 3, 9, 54, 3, 0, 0),\n",
       " (33, 77, 2, 7, 73, 3, 7, 146, 3, 0, 0),\n",
       " (29, 59, 2, 19, 57, 3, 19, 114, 3, 0, 0),\n",
       " (35, 85, 2, 0, 81, 3, 0, 164, 3, 0, 1),\n",
       " (22, 36, 2, 11, 34, 3, 11, 69, 3, 0, 0),\n",
       " (2, 75, 0, 7, 71, 0, 7, 140, 0, 0, 23),\n",
       " (2, 75, 0, 7, 71, 0, 7, 141, 1, 0, 0),\n",
       " (3, 9, 0, 10, 8, 0, 10, 16, 0, 0, 12),\n",
       " (3, 9, 0, 10, 8, 0, 10, 17, 1, 0, 0),\n",
       " (83, 27, 7, 9, 14, 0, 5, 29, 1, 0, 0),\n",
       " (74, 61, 4, 19, 58, 4, 19, 115, 7, 2, 465),\n",
       " (83, 27, 7, 9, 14, 0, 5, 28, 0, 0, 18),\n",
       " (83, 27, 7, 9, 14, 0, 5, 28, 0, 2, 12),\n",
       " (4, 15, 0, 5, 14, 0, 5, 28, 0, 0, 12),\n",
       " (83, 27, 7, 9, 14, 0, 5, 28, 0, 0, 12),\n",
       " (28, 56, 2, 18, 54, 3, 18, 108, 3, 0, 0),\n",
       " (61, 4, 4, 2, 2, 4, 2, 5, 7, 2, 8595),\n",
       " (16, 6, 2, 8, 5, 3, 8, 12, 3, 0, 0),\n",
       " (80, 87, 4, 0, 82, 4, 0, 165, 7, 2, 4719),\n",
       " (75, 64, 4, 20, 61, 4, 20, 121, 7, 2, 9860),\n",
       " (63, 13, 4, 10, 12, 4, 10, 25, 7, 2, 6721),\n",
       " (76, 67, 4, 12, 64, 4, 12, 127, 7, 2, 4581),\n",
       " (21, 30, 2, 3, 30, 3, 3, 61, 3, 0, 1),\n",
       " (73, 58, 4, 18, 55, 4, 18, 109, 7, 2, 3498),\n",
       " (79, 84, 4, 6, 79, 4, 6, 159, 7, 2, 7276),\n",
       " (17, 11, 2, 10, 11, 3, 10, 24, 3, 0, 0),\n",
       " (18, 19, 2, 5, 19, 3, 5, 41, 3, 0, 0),\n",
       " (32, 70, 2, 4, 68, 3, 4, 136, 3, 0, 1),\n",
       " (77, 73, 4, 4, 70, 4, 4, 138, 7, 2, 8960),\n",
       " (62, 8, 4, 8, 7, 4, 8, 14, 7, 2, 9192),\n",
       " (71, 51, 4, 16, 48, 4, 16, 96, 7, 2, 1693),\n",
       " (34, 82, 2, 6, 78, 3, 6, 158, 3, 0, 1),\n",
       " (81, 88, 7, 0, 75, 0, 6, 150, 1, 0, 0),\n",
       " (81, 88, 7, 0, 75, 0, 6, 149, 0, 0, 18),\n",
       " (81, 88, 7, 0, 75, 0, 6, 149, 0, 2, 12),\n",
       " (0, 80, 0, 6, 75, 0, 6, 149, 0, 0, 12),\n",
       " (64, 23, 4, 1, 24, 4, 1, 49, 7, 2, 8064),\n",
       " (81, 88, 7, 0, 75, 0, 6, 149, 0, 0, 12),\n",
       " (25, 46, 2, 15, 44, 3, 15, 89, 3, 0, 0),\n",
       " (24, 43, 2, 14, 41, 3, 14, 83, 3, 0, 0),\n",
       " (72, 55, 4, 17, 52, 4, 17, 103, 7, 2, 6419),\n",
       " (27, 53, 2, 17, 51, 3, 17, 102, 3, 0, 0),\n",
       " (0, 80, 0, 6, 75, 0, 6, 149, 0, 0, 12),\n",
       " (1, 81, 0, 6, 76, 0, 6, 152, 0, 0, 23),\n",
       " (1, 81, 0, 6, 76, 0, 6, 153, 1, 0, 0),\n",
       " (0, 80, 0, 6, 75, 0, 6, 150, 1, 0, 0),\n",
       " (19, 21, 2, 1, 22, 3, 1, 47, 3, 0, 0),\n",
       " (82, 14, 7, 10, 8, 0, 10, 17, 1, 0, 0),\n",
       " (82, 14, 7, 10, 8, 0, 10, 16, 0, 0, 12),\n",
       " (82, 14, 7, 10, 8, 0, 10, 16, 0, 2, 9),\n",
       " (3, 9, 0, 10, 8, 0, 10, 16, 0, 0, 9),\n",
       " (82, 14, 7, 10, 8, 0, 10, 16, 0, 0, 9),\n",
       " (4, 15, 0, 5, 14, 0, 5, 28, 0, 0, 12),\n",
       " (4, 15, 0, 5, 14, 0, 5, 29, 1, 0, 0),\n",
       " (26, 49, 2, 16, 47, 3, 16, 95, 3, 0, 0),\n",
       " (78, 79, 4, 7, 74, 4, 7, 147, 7, 2, 4409),\n",
       " (23, 40, 2, 13, 38, 3, 13, 77, 3, 0, 0),\n",
       " (69, 45, 4, 14, 42, 4, 14, 84, 7, 2, 9880),\n",
       " (68, 42, 4, 13, 39, 4, 13, 78, 7, 2, 497),\n",
       " (70, 48, 4, 15, 45, 4, 15, 90, 7, 2, 8949),\n",
       " (30, 62, 2, 20, 60, 3, 20, 120, 3, 0, 0),\n",
       " (5, 16, 0, 5, 15, 0, 5, 31, 0, 0, 23),\n",
       " (5, 16, 0, 5, 15, 0, 5, 32, 1, 0, 0),\n",
       " (15, 1, 2, 2, 1, 3, 2, 4, 3, 0, 0),\n",
       " (67, 38, 4, 11, 35, 4, 11, 70, 7, 2, 4352),\n",
       " (31, 65, 2, 12, 63, 3, 12, 126, 3, 0, 0),\n",
       " (66, 34, 4, 3, 31, 4, 3, 62, 7, 2, 2929),\n",
       " (65, 26, 4, 9, 27, 4, 9, 55, 7, 2, 6406),\n",
       " (20, 24, 2, 9, 26, 3, 9, 54, 3, 0, 0),\n",
       " (33, 77, 2, 7, 73, 3, 7, 146, 3, 0, 0),\n",
       " (29, 59, 2, 19, 57, 3, 19, 114, 3, 0, 0),\n",
       " (35, 85, 2, 0, 81, 3, 0, 164, 3, 0, 1),\n",
       " (2, 75, 0, 7, 71, 0, 7, 140, 0, 0, 23),\n",
       " (22, 36, 2, 11, 34, 3, 11, 69, 3, 0, 0),\n",
       " (2, 75, 0, 7, 71, 0, 7, 141, 1, 0, 0),\n",
       " (3, 9, 0, 10, 8, 0, 10, 16, 0, 0, 9),\n",
       " (3, 9, 0, 10, 8, 0, 10, 17, 1, 0, 0),\n",
       " (74, 61, 4, 19, 58, 4, 19, 115, 7, 2, 2673),\n",
       " (83, 27, 7, 9, 14, 0, 5, 29, 1, 0, 0),\n",
       " (83, 27, 7, 9, 14, 0, 5, 28, 0, 0, 12),\n",
       " (28, 56, 2, 18, 54, 3, 18, 108, 3, 0, 0),\n",
       " (83, 27, 7, 9, 14, 0, 5, 28, 0, 2, 9),\n",
       " (4, 15, 0, 5, 14, 0, 5, 28, 0, 0, 9),\n",
       " (83, 27, 7, 9, 14, 0, 5, 28, 0, 0, 9),\n",
       " (61, 4, 4, 2, 2, 4, 2, 5, 7, 2, 1102),\n",
       " (16, 6, 2, 8, 5, 3, 8, 12, 3, 0, 0),\n",
       " (80, 87, 4, 0, 82, 4, 0, 165, 7, 2, 1544),\n",
       " (75, 64, 4, 20, 61, 4, 20, 121, 7, 2, 1176),\n",
       " (76, 67, 4, 12, 64, 4, 12, 127, 7, 2, 3388),\n",
       " (63, 13, 4, 10, 12, 4, 10, 25, 7, 2, 7783),\n",
       " (21, 30, 2, 3, 30, 3, 3, 61, 3, 0, 1),\n",
       " (79, 84, 4, 6, 79, 4, 6, 159, 7, 2, 5435),\n",
       " (17, 11, 2, 10, 11, 3, 10, 24, 3, 0, 0),\n",
       " (73, 58, 4, 18, 55, 4, 18, 109, 7, 2, 8186),\n",
       " (18, 19, 2, 5, 19, 3, 5, 41, 3, 0, 0),\n",
       " (32, 70, 2, 4, 68, 3, 4, 136, 3, 0, 1),\n",
       " (77, 73, 4, 4, 70, 4, 4, 138, 7, 2, 9692),\n",
       " (62, 8, 4, 8, 7, 4, 8, 14, 7, 2, 2942),\n",
       " (71, 51, 4, 16, 48, 4, 16, 96, 7, 2, 9512),\n",
       " (34, 82, 2, 6, 78, 3, 6, 158, 3, 0, 1),\n",
       " (81, 88, 7, 0, 75, 0, 6, 150, 1, 0, 0),\n",
       " (64, 23, 4, 1, 24, 4, 1, 49, 7, 2, 9191),\n",
       " (81, 88, 7, 0, 75, 0, 6, 149, 0, 0, 12),\n",
       " (25, 46, 2, 15, 44, 3, 15, 89, 3, 0, 0),\n",
       " (81, 88, 7, 0, 75, 0, 6, 149, 0, 2, 9),\n",
       " (0, 80, 0, 6, 75, 0, 6, 149, 0, 0, 9),\n",
       " (81, 88, 7, 0, 75, 0, 6, 149, 0, 0, 9),\n",
       " (24, 43, 2, 14, 41, 3, 14, 83, 3, 0, 0),\n",
       " (72, 55, 4, 17, 52, 4, 17, 103, 7, 2, 3898),\n",
       " (27, 53, 2, 17, 51, 3, 17, 102, 3, 0, 0),\n",
       " (1, 81, 0, 6, 76, 0, 6, 152, 0, 0, 23),\n",
       " (0, 80, 0, 6, 75, 0, 6, 149, 0, 0, 9),\n",
       " (0, 80, 0, 6, 75, 0, 6, 150, 1, 0, 0),\n",
       " (1, 81, 0, 6, 76, 0, 6, 153, 1, 0, 0),\n",
       " (19, 21, 2, 1, 22, 3, 1, 47, 3, 0, 0),\n",
       " (82, 14, 7, 10, 8, 0, 10, 17, 1, 0, 0),\n",
       " (82, 14, 7, 10, 8, 0, 10, 16, 0, 0, 9),\n",
       " (82, 14, 7, 10, 8, 0, 10, 16, 0, 2, 7),\n",
       " (82, 14, 7, 10, 8, 0, 10, 16, 0, 0, 7),\n",
       " (3, 9, 0, 10, 8, 0, 10, 16, 0, 0, 7),\n",
       " (4, 15, 0, 5, 14, 0, 5, 28, 0, 0, 9),\n",
       " (78, 79, 4, 7, 74, 4, 7, 147, 7, 2, 9082),\n",
       " (26, 49, 2, 16, 47, 3, 16, 95, 3, 0, 0),\n",
       " (4, 15, 0, 5, 14, 0, 5, 29, 1, 0, 0),\n",
       " (23, 40, 2, 13, 38, 3, 13, 77, 3, 0, 0),\n",
       " (69, 45, 4, 14, 42, 4, 14, 84, 7, 2, 8796),\n",
       " (68, 42, 4, 13, 39, 4, 13, 78, 7, 2, 1777),\n",
       " (70, 48, 4, 15, 45, 4, 15, 90, 7, 2, 6672),\n",
       " (30, 62, 2, 20, 60, 3, 20, 120, 3, 0, 0),\n",
       " (5, 16, 0, 5, 15, 0, 5, 31, 0, 0, 23),\n",
       " (5, 16, 0, 5, 15, 0, 5, 32, 1, 0, 0),\n",
       " (15, 1, 2, 2, 1, 3, 2, 4, 3, 0, 0),\n",
       " (67, 38, 4, 11, 35, 4, 11, 70, 7, 2, 9808),\n",
       " (31, 65, 2, 12, 63, 3, 12, 126, 3, 0, 0),\n",
       " (66, 34, 4, 3, 31, 4, 3, 62, 7, 2, 5789),\n",
       " (65, 26, 4, 9, 27, 4, 9, 55, 7, 2, 2312),\n",
       " (20, 24, 2, 9, 26, 3, 9, 54, 3, 0, 0),\n",
       " (33, 77, 2, 7, 73, 3, 7, 146, 3, 0, 0),\n",
       " (29, 59, 2, 19, 57, 3, 19, 114, 3, 0, 0),\n",
       " (35, 85, 2, 0, 81, 3, 0, 164, 3, 0, 1),\n",
       " (2, 75, 0, 7, 71, 0, 7, 140, 0, 0, 23),\n",
       " (2, 75, 0, 7, 71, 0, 7, 141, 1, 0, 0),\n",
       " (22, 36, 2, 11, 34, 3, 11, 69, 3, 0, 0),\n",
       " (3, 9, 0, 10, 8, 0, 10, 16, 0, 0, 7),\n",
       " (3, 9, 0, 10, 8, 0, 10, 17, 1, 0, 0),\n",
       " (74, 61, 4, 19, 58, 4, 19, 115, 7, 2, 470),\n",
       " (28, 56, 2, 18, 54, 3, 18, 108, 3, 0, 0),\n",
       " (83, 27, 7, 9, 14, 0, 5, 29, 1, 0, 0),\n",
       " (83, 27, 7, 9, 14, 0, 5, 28, 0, 0, 9),\n",
       " (83, 27, 7, 9, 14, 0, 5, 28, 0, 2, 7),\n",
       " (61, 4, 4, 2, 2, 4, 2, 5, 7, 2, 6937),\n",
       " (4, 15, 0, 5, 14, 0, 5, 28, 0, 0, 7),\n",
       " (16, 6, 2, 8, 5, 3, 8, 12, 3, 0, 0),\n",
       " (83, 27, 7, 9, 14, 0, 5, 28, 0, 0, 7),\n",
       " (80, 87, 4, 0, 82, 4, 0, 165, 7, 2, 660),\n",
       " (63, 13, 4, 10, 12, 4, 10, 25, 7, 2, 8589),\n",
       " (75, 64, 4, 20, 61, 4, 20, 121, 7, 2, 1604),\n",
       " (76, 67, 4, 12, 64, 4, 12, 127, 7, 2, 3460),\n",
       " (21, 30, 2, 3, 30, 3, 3, 61, 3, 0, 1),\n",
       " (79, 84, 4, 6, 79, 4, 6, 159, 7, 2, 3666),\n",
       " (17, 11, 2, 10, 11, 3, 10, 24, 3, 0, 0),\n",
       " (73, 58, 4, 18, 55, 4, 18, 109, 7, 2, 61),\n",
       " (18, 19, 2, 5, 19, 3, 5, 41, 3, 0, 0),\n",
       " (32, 70, 2, 4, 68, 3, 4, 136, 3, 0, 1),\n",
       " (77, 73, 4, 4, 70, 4, 4, 138, 7, 2, 5376),\n",
       " (62, 8, 4, 8, 7, 4, 8, 14, 7, 2, 1006),\n",
       " (71, 51, 4, 16, 48, 4, 16, 96, 7, 2, 8281),\n",
       " (34, 82, 2, 6, 78, 3, 6, 158, 3, 0, 1),\n",
       " (64, 23, 4, 1, 24, 4, 1, 49, 7, 2, 7812),\n",
       " (25, 46, 2, 15, 44, 3, 15, 89, 3, 0, 0),\n",
       " (24, 43, 2, 14, 41, 3, 14, 83, 3, 0, 0),\n",
       " (81, 88, 7, 0, 75, 0, 6, 150, 1, 0, 0),\n",
       " (81, 88, 7, 0, 75, 0, 6, 149, 0, 0, 9),\n",
       " (81, 88, 7, 0, 75, 0, 6, 149, 0, 2, 7),\n",
       " (0, 80, 0, 6, 75, 0, 6, 149, 0, 0, 7),\n",
       " (81, 88, 7, 0, 75, 0, 6, 149, 0, 0, 7),\n",
       " (72, 55, 4, 17, 52, 4, 17, 103, 7, 2, 614),\n",
       " (27, 53, 2, 17, 51, 3, 17, 102, 3, 0, 0),\n",
       " (0, 80, 0, 6, 75, 0, 6, 149, 0, 0, 7),\n",
       " (1, 81, 0, 6, 76, 0, 6, 152, 0, 0, 23),\n",
       " (19, 21, 2, 1, 22, 3, 1, 47, 3, 0, 0),\n",
       " (0, 80, 0, 6, 75, 0, 6, 150, 1, 0, 0),\n",
       " (1, 81, 0, 6, 76, 0, 6, 153, 1, 0, 0),\n",
       " (82, 14, 7, 10, 8, 0, 10, 17, 1, 0, 0),\n",
       " (78, 79, 4, 7, 74, 4, 7, 147, 7, 2, 5890),\n",
       " (26, 49, 2, 16, 47, 3, 16, 95, 3, 0, 0),\n",
       " (82, 14, 7, 10, 8, 0, 10, 16, 0, 0, 7),\n",
       " (82, 14, 7, 10, 8, 0, 10, 16, 0, 2, 2),\n",
       " (23, 40, 2, 13, 38, 3, 13, 77, 3, 0, 0),\n",
       " (69, 45, 4, 14, 42, 4, 14, 84, 7, 2, 7059),\n",
       " (82, 14, 7, 10, 8, 0, 10, 16, 0, 0, 2),\n",
       " (4, 15, 0, 5, 14, 0, 5, 28, 0, 0, 7),\n",
       " (3, 9, 0, 10, 8, 0, 10, 16, 0, 0, 2),\n",
       " (68, 42, 4, 13, 39, 4, 13, 78, 7, 2, 9639),\n",
       " (70, 48, 4, 15, 45, 4, 15, 90, 7, 2, 340),\n",
       " (4, 15, 0, 5, 14, 0, 5, 29, 1, 0, 0),\n",
       " (30, 62, 2, 20, 60, 3, 20, 120, 3, 0, 0),\n",
       " (5, 16, 0, 5, 15, 0, 5, 31, 0, 0, 23),\n",
       " (5, 16, 0, 5, 15, 0, 5, 32, 1, 0, 0),\n",
       " (15, 1, 2, 2, 1, 3, 2, 4, 3, 0, 0),\n",
       " (67, 38, 4, 11, 35, 4, 11, 70, 7, 2, 4559),\n",
       " (31, 65, 2, 12, 63, 3, 12, 126, 3, 0, 0),\n",
       " (66, 34, 4, 3, 31, 4, 3, 62, 7, 2, 9630),\n",
       " (65, 26, 4, 9, 27, 4, 9, 55, 7, 2, 8318),\n",
       " (20, 24, 2, 9, 26, 3, 9, 54, 3, 0, 0),\n",
       " (33, 77, 2, 7, 73, 3, 7, 146, 3, 0, 0),\n",
       " (29, 59, 2, 19, 57, 3, 19, 114, 3, 0, 0),\n",
       " (35, 85, 2, 0, 81, 3, 0, 164, 3, 0, 1),\n",
       " (3, 9, 0, 10, 8, 0, 10, 16, 0, 0, 2),\n",
       " (2, 75, 0, 7, 71, 0, 7, 140, 0, 0, 23),\n",
       " (22, 36, 2, 11, 34, 3, 11, 69, 3, 0, 0),\n",
       " (3, 9, 0, 10, 8, 0, 10, 17, 1, 0, 0),\n",
       " (74, 61, 4, 19, 58, 4, 19, 115, 7, 2, 8353),\n",
       " (2, 75, 0, 7, 71, 0, 7, 141, 1, 0, 0),\n",
       " (28, 56, 2, 18, 54, 3, 18, 108, 3, 0, 0),\n",
       " (61, 4, 4, 2, 2, 4, 2, 5, 7, 2, 329),\n",
       " (16, 6, 2, 8, 5, 3, 8, 12, 3, 0, 0),\n",
       " (83, 27, 7, 9, 14, 0, 5, 29, 1, 0, 0),\n",
       " (80, 87, 4, 0, 82, 4, 0, 165, 7, 2, 285),\n",
       " (83, 27, 7, 9, 14, 0, 5, 28, 0, 0, 7),\n",
       " (83, 27, 7, 9, 14, 0, 5, 28, 0, 2, 2),\n",
       " (83, 27, 7, 9, 14, 0, 5, 28, 0, 0, 2),\n",
       " (4, 15, 0, 5, 14, 0, 5, 28, 0, 0, 2),\n",
       " (63, 13, 4, 10, 12, 4, 10, 25, 7, 2, 2337),\n",
       " (75, 64, 4, 20, 61, 4, 20, 121, 7, 2, 9445),\n",
       " (76, 67, 4, 12, 64, 4, 12, 127, 7, 2, 1193),\n",
       " (21, 30, 2, 3, 30, 3, 3, 61, 3, 0, 1),\n",
       " (79, 84, 4, 6, 79, 4, 6, 159, 7, 2, 9653),\n",
       " (17, 11, 2, 10, 11, 3, 10, 24, 3, 0, 0),\n",
       " (73, 58, 4, 18, 55, 4, 18, 109, 7, 2, 2292),\n",
       " (18, 19, 2, 5, 19, 3, 5, 41, 3, 0, 0),\n",
       " (32, 70, 2, 4, 68, 3, 4, 136, 3, 0, 1),\n",
       " (77, 73, 4, 4, 70, 4, 4, 138, 7, 2, 1753),\n",
       " (62, 8, 4, 8, 7, 4, 8, 14, 7, 2, 3352),\n",
       " (71, 51, 4, 16, 48, 4, 16, 96, 7, 2, 3355),\n",
       " (34, 82, 2, 6, 78, 3, 6, 158, 3, 0, 1),\n",
       " (64, 23, 4, 1, 24, 4, 1, 49, 7, 2, 5929),\n",
       " (25, 46, 2, 15, 44, 3, 15, 89, 3, 0, 0),\n",
       " (24, 43, 2, 14, 41, 3, 14, 83, 3, 0, 0),\n",
       " (81, 88, 7, 0, 75, 0, 6, 150, 1, 0, 0),\n",
       " (81, 88, 7, 0, 75, 0, 6, 149, 0, 0, 7),\n",
       " (81, 88, 7, 0, 75, 0, 6, 149, 0, 2, 2),\n",
       " (81, 88, 7, 0, 75, 0, 6, 149, 0, 0, 2),\n",
       " (0, 80, 0, 6, 75, 0, 6, 149, 0, 0, 2),\n",
       " (72, 55, 4, 17, 52, 4, 17, 103, 7, 2, 7321),\n",
       " (27, 53, 2, 17, 51, 3, 17, 102, 3, 0, 0),\n",
       " (1, 81, 0, 6, 76, 0, 6, 152, 0, 0, 23),\n",
       " (19, 21, 2, 1, 22, 3, 1, 47, 3, 0, 0),\n",
       " (1, 81, 0, 6, 76, 0, 6, 153, 1, 0, 0),\n",
       " (0, 80, 0, 6, 75, 0, 6, 149, 0, 0, 2),\n",
       " (0, 80, 0, 6, 75, 0, 6, 150, 1, 0, 0),\n",
       " (78, 79, 4, 7, 74, 4, 7, 147, 7, 2, 5864),\n",
       " (23, 40, 2, 13, 38, 3, 13, 77, 3, 0, 0),\n",
       " (26, 49, 2, 16, 47, 3, 16, 95, 3, 0, 0),\n",
       " (82, 14, 7, 10, 8, 0, 10, 17, 1, 0, 0),\n",
       " (82, 14, 7, 10, 8, 0, 10, 16, 0, 0, 2),\n",
       " (82, 14, 7, 10, 8, 0, 10, 16, 0, 2, 1),\n",
       " (69, 45, 4, 14, 42, 4, 14, 84, 7, 2, 7603),\n",
       " (70, 48, 4, 15, 45, 4, 15, 90, 7, 2, 2514),\n",
       " (68, 42, 4, 13, 39, 4, 13, 78, 7, 2, 4878),\n",
       " (4, 15, 0, 5, 14, 0, 5, 28, 0, 0, 2),\n",
       " (82, 14, 7, 10, 8, 0, 10, 16, 0, 0, 1),\n",
       " (30, 62, 2, 20, 60, 3, 20, 120, 3, 0, 0),\n",
       " (3, 9, 0, 10, 8, 0, 10, 16, 0, 0, 1),\n",
       " (4, 15, 0, 5, 14, 0, 5, 29, 1, 0, 0),\n",
       " (5, 16, 0, 5, 15, 0, 5, 31, 0, 0, 23),\n",
       " (5, 16, 0, 5, 15, 0, 5, 32, 1, 0, 0),\n",
       " (15, 1, 2, 2, 1, 3, 2, 4, 3, 0, 0),\n",
       " (67, 38, 4, 11, 35, 4, 11, 70, 7, 2, 1166),\n",
       " (31, 65, 2, 12, 63, 3, 12, 126, 3, 0, 0),\n",
       " (66, 34, 4, 3, 31, 4, 3, 62, 7, 2, 9337),\n",
       " (65, 26, 4, 9, 27, 4, 9, 55, 7, 2, 4433),\n",
       " (20, 24, 2, 9, 26, 3, 9, 54, 3, 0, 0),\n",
       " (29, 59, 2, 19, 57, 3, 19, 114, 3, 0, 0),\n",
       " (33, 77, 2, 7, 73, 3, 7, 146, 3, 0, 0),\n",
       " (35, 85, 2, 0, 81, 3, 0, 164, 3, 0, 1),\n",
       " (74, 61, 4, 19, 58, 4, 19, 115, 7, 2, 9781),\n",
       " (3, 9, 0, 10, 8, 0, 10, 16, 0, 0, 1),\n",
       " (2, 75, 0, 7, 71, 0, 7, 140, 0, 0, 23),\n",
       " (22, 36, 2, 11, 34, 3, 11, 69, 3, 0, 0),\n",
       " (3, 9, 0, 10, 8, 0, 10, 17, 1, 0, 0),\n",
       " (2, 75, 0, 7, 71, 0, 7, 141, 1, 0, 0),\n",
       " (28, 56, 2, 18, 54, 3, 18, 108, 3, 0, 0),\n",
       " (61, 4, 4, 2, 2, 4, 2, 5, 7, 2, 1065),\n",
       " (16, 6, 2, 8, 5, 3, 8, 12, 3, 0, 0),\n",
       " (80, 87, 4, 0, 82, 4, 0, 165, 7, 2, 807),\n",
       " (83, 27, 7, 9, 14, 0, 5, 29, 1, 0, 0),\n",
       " (83, 27, 7, 9, 14, 0, 5, 28, 0, 0, 2),\n",
       " (63, 13, 4, 10, 12, 4, 10, 25, 7, 2, 2067),\n",
       " (83, 27, 7, 9, 14, 0, 5, 28, 0, 2, 1),\n",
       " (83, 27, 7, 9, 14, 0, 5, 28, 0, 0, 1),\n",
       " (75, 64, 4, 20, 61, 4, 20, 121, 7, 2, 5456),\n",
       " (4, 15, 0, 5, 14, 0, 5, 28, 0, 0, 1),\n",
       " (76, 67, 4, 12, 64, 4, 12, 127, 7, 2, 8379),\n",
       " (21, 30, 2, 3, 30, 3, 3, 61, 3, 0, 1),\n",
       " (79, 84, 4, 6, 79, 4, 6, 159, 7, 2, 8170),\n",
       " (17, 11, 2, 10, 11, 3, 10, 24, 3, 0, 0),\n",
       " (73, 58, 4, 18, 55, 4, 18, 109, 7, 2, 9182),\n",
       " (18, 19, 2, 5, 19, 3, 5, 41, 3, 0, 0),\n",
       " (32, 70, 2, 4, 68, 3, 4, 136, 3, 0, 1),\n",
       " (77, 73, 4, 4, 70, 4, 4, 138, 7, 2, 7514),\n",
       " (62, 8, 4, 8, 7, 4, 8, 14, 7, 2, 1679),\n",
       " (71, 51, 4, 16, 48, 4, 16, 96, 7, 2, 3922),\n",
       " (34, 82, 2, 6, 78, 3, 6, 158, 3, 0, 1),\n",
       " (64, 23, 4, 1, 24, 4, 1, 49, 7, 2, 893),\n",
       " (25, 46, 2, 15, 44, 3, 15, 89, 3, 0, 0),\n",
       " (24, 43, 2, 14, 41, 3, 14, 83, 3, 0, 0),\n",
       " (81, 88, 7, 0, 75, 0, 6, 150, 1, 0, 0),\n",
       " (81, 88, 7, 0, 75, 0, 6, 149, 0, 0, 2),\n",
       " (81, 88, 7, 0, 75, 0, 6, 149, 0, 2, 1),\n",
       " (81, 88, 7, 0, 75, 0, 6, 149, 0, 0, 1),\n",
       " (72, 55, 4, 17, 52, 4, 17, 103, 7, 2, 8666),\n",
       " (0, 80, 0, 6, 75, 0, 6, 149, 0, 0, 1),\n",
       " (27, 53, 2, 17, 51, 3, 17, 102, 3, 0, 0),\n",
       " (19, 21, 2, 1, 22, 3, 1, 47, 3, 0, 0),\n",
       " (1, 81, 0, 6, 76, 0, 6, 152, 0, 0, 23),\n",
       " (1, 81, 0, 6, 76, 0, 6, 153, 1, 0, 0),\n",
       " (0, 80, 0, 6, 75, 0, 6, 149, 0, 0, 1),\n",
       " (0, 80, 0, 6, 75, 0, 6, 150, 1, 0, 0),\n",
       " (78, 79, 4, 7, 74, 4, 7, 147, 7, 2, 7453),\n",
       " (23, 40, 2, 13, 38, 3, 13, 77, 3, 0, 0),\n",
       " (26, 49, 2, 16, 47, 3, 16, 95, 3, 0, 0),\n",
       " (70, 48, 4, 15, 45, 4, 15, 90, 7, 2, 8899),\n",
       " (68, 42, 4, 13, 39, 4, 13, 78, 7, 2, 9038),\n",
       " (69, 45, 4, 14, 42, 4, 14, 84, 7, 2, 5501),\n",
       " (82, 14, 7, 10, 8, 0, 10, 17, 1, 0, 0),\n",
       " (4, 15, 0, 5, 14, 0, 5, 28, 0, 0, 1),\n",
       " (82, 14, 7, 10, 8, 0, 10, 16, 0, 0, 1),\n",
       " ...]"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
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       " 7,\n",
       " 7,\n",
       " 7,\n",
       " ...]"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The shape of x is:  (355891, 11)\n",
      "The shape of y is:  (355891,)\n"
     ]
    }
   ],
   "source": [
    "x = np.array(x)\n",
    "y = np.array(y)\n",
    "print(\"The shape of x is: \",x.shape)\n",
    "print(\"The shape of y is: \",y.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### labels of output"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['anomalous(DoSattack)', 'anomalous(dataProbing)',\n",
       "       'anomalous(malitiousControl)', 'anomalous(malitiousOperation)',\n",
       "       'anomalous(scan)', 'anomalous(spying)', 'anomalous(wrongSetUp)',\n",
       "       'normal'], dtype=object)"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "le.classes_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0])"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "le.transform(['anomalous(DoSattack)'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([7, 7, 7, ..., 7, 7, 7])"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "y = y.reshape(-1,1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(355891, 1)"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### we will create a new dataset that will contain the information in required format"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[   7,   21,   30, ...,    5,    1,    0],\n",
       "       [   7,   32,   70, ...,    5,    1,    0],\n",
       "       [   7,   15,    1, ...,    5,    1,    0],\n",
       "       ...,\n",
       "       [   7,   82,   14, ...,    1,    0,    1],\n",
       "       [   7,   30,   62, ...,    3,    0,    0],\n",
       "       [   7,   30,   62, ...,    7,    0, 9156]], dtype=int64)"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset = np.concatenate((y,x),axis=1)\n",
    "dataseta"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
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      "text/plain": [
       "        0   1   2   3   4   5   6   7    8   9   10    11\n",
       "0        7  21  30   2   3  29   2   3   57   5   1     0\n",
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       "...     ..  ..  ..  ..  ..  ..  ..  ..  ...  ..  ..   ...\n",
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       "\n",
       "[355891 rows x 12 columns]"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset = pd.DataFrame(dataset)\n",
    "dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "dataset.to_csv('dataset.csv',index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Now we have our dataset in the required format here on we will apply ML algorithms"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### loading appropriate dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
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       "        Unnamed: 0  0   1   2  3   4   5  6   7    8  9  10    11\n",
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       "...            ... ..  ..  .. ..  ..  .. ..  ..  ... ..  ..   ...\n",
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       "\n",
       "[355891 rows x 13 columns]"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_csv('dataset.csv')\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "data.drop(columns = \"Unnamed: 0\", inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
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       "      <td>67</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>132</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>7</td>\n",
       "      <td>15</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>7</td>\n",
       "      <td>33</td>\n",
       "      <td>77</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>72</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>142</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>7</td>\n",
       "      <td>55</td>\n",
       "      <td>78</td>\n",
       "      <td>3</td>\n",
       "      <td>7</td>\n",
       "      <td>73</td>\n",
       "      <td>3</td>\n",
       "      <td>7</td>\n",
       "      <td>144</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   0   1   2  3  4   5  6  7    8  9  10  11\n",
       "0  7  21  30  2  3  29  2  3   57  5   1   0\n",
       "1  7  32  70  2  4  67  2  4  132  5   1   0\n",
       "2  7  15   1  2  2   0  2  2    0  5   1   0\n",
       "3  7  33  77  2  7  72  2  7  142  5   1   0\n",
       "4  7  55  78  3  7  73  3  7  144  6   1   0"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[  21,   30,    2, ...,    5,    1,    0],\n",
       "       [  32,   70,    2, ...,    5,    1,    0],\n",
       "       [  15,    1,    2, ...,    5,    1,    0],\n",
       "       ...,\n",
       "       [  82,   14,    7, ...,    1,    0,    1],\n",
       "       [  30,   62,    2, ...,    3,    0,    0],\n",
       "       [  30,   62,    2, ...,    7,    0, 9156]], dtype=int64)"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y = data.iloc[:,0].values\n",
    "X = data.iloc[:,1:].values\n",
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([7, 7, 7, ..., 7, 7, 7], dtype=int64)"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Splitting the dataset into training and testing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "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": 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": 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": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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