labellingdata.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import random\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "data=pd.read_csv('dataset_new.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "arr=np.array(data,dtype='float64')\n",
    "n_rows=arr.shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .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>Language_vocab</th>\n",
       "      <th>Memory</th>\n",
       "      <th>Speed</th>\n",
       "      <th>Visual_discrimination</th>\n",
       "      <th>Audio_Discrimination</th>\n",
       "      <th>Survey_Score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.5</td>\n",
       "      <td>0.6</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.8</td>\n",
       "      <td>0.6</td>\n",
       "      <td>0.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.6</td>\n",
       "      <td>0.7</td>\n",
       "      <td>0.8</td>\n",
       "      <td>0.9</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.6</td>\n",
       "      <td>0.4</td>\n",
       "      <td>0.3</td>\n",
       "      <td>0.3</td>\n",
       "      <td>0.4</td>\n",
       "      <td>0.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.3</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.3</td>\n",
       "      <td>0.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.7</td>\n",
       "      <td>0.6</td>\n",
       "      <td>0.7</td>\n",
       "      <td>0.8</td>\n",
       "      <td>0.9</td>\n",
       "      <td>0.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.4</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.4</td>\n",
       "      <td>0.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.8</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.8</td>\n",
       "      <td>0.9</td>\n",
       "      <td>0.6</td>\n",
       "      <td>0.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.5</td>\n",
       "      <td>0.3</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.4</td>\n",
       "      <td>0.7</td>\n",
       "      <td>0.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.6</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.4</td>\n",
       "      <td>0.6</td>\n",
       "      <td>0.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.6</td>\n",
       "      <td>0.7</td>\n",
       "      <td>0.7</td>\n",
       "      <td>0.8</td>\n",
       "      <td>0.7</td>\n",
       "      <td>0.6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Language_vocab  Memory  Speed  Visual_discrimination  Audio_Discrimination  \\\n",
       "0             0.5     0.6    0.5                    0.8                   0.6   \n",
       "1             0.6     0.7    0.8                    0.9                   0.5   \n",
       "2             0.6     0.4    0.3                    0.3                   0.4   \n",
       "3             0.3     0.5    0.2                    0.1                   0.3   \n",
       "4             0.7     0.6    0.7                    0.8                   0.9   \n",
       "5             0.4     0.1    0.0                    0.1                   0.4   \n",
       "6             0.8     1.0    0.8                    0.9                   0.6   \n",
       "7             0.5     0.3    0.5                    0.4                   0.7   \n",
       "8             0.6     0.5    0.5                    0.4                   0.6   \n",
       "9             0.6     0.7    0.7                    0.8                   0.7   \n",
       "\n",
       "   Survey_Score  \n",
       "0           0.7  \n",
       "1           0.8  \n",
       "2           0.6  \n",
       "3           0.5  \n",
       "4           0.5  \n",
       "5           0.2  \n",
       "6           0.6  \n",
       "7           0.4  \n",
       "8           0.5  \n",
       "9           0.6  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x20f92e0f808>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8,6))\n",
    "sns.heatmap(data.corr(),annot=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[3.796767634200761,\n",
       " 2.679110831912357,\n",
       " 0.8519740822605654,\n",
       " 0.36369415021960727,\n",
       " 0.23414005424875212]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "weights=[]\n",
    "for i in range(5):\n",
    "    weights.append(random.random())\n",
    "weights.sort(reverse=True)\n",
    "weights[0]*=4\n",
    "weights[1]*=3\n",
    "weights[3]*=0.75\n",
    "weights[4]*=0.5\n",
    "weights"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "def rule(a):\n",
    "    if(a<0.3):\n",
    "        return 0\n",
    "    if(a>0.4 and a<0.6):\n",
    "        return 1\n",
    "    if(a>0.7):\n",
    "        return 2\n",
    "    return -1\n",
    "labels=np.zeros((n_rows,1))\n",
    "for i in range(n_rows):\n",
    "    temp=arr[i,].tolist()\n",
    "    a=round((temp[0]*weights[0]+temp[1]*weights[1]+temp[2]*weights[2]+\n",
    "             (temp[3]+temp[4])*weights[3]+temp[5]*weights[4])/10,1)\n",
    "    b=rule(a)\n",
    "    if(b==-1):\n",
    "        if(a>=0.3 and a<=0.4):\n",
    "            if((temp[0]+temp[1])/2<0.3):\n",
    "                b=0\n",
    "            elif((temp[0]+temp[1])/2>0.4):\n",
    "                b=1\n",
    "            elif(temp[2]<0.3):\n",
    "                b=0\n",
    "            elif(temp[2]>0.4):\n",
    "                b=1\n",
    "            elif((temp[3]+temp[4])/2<0.3):\n",
    "                b=0\n",
    "            elif((temp[3]+temp[4])/2>0.4):\n",
    "                b=1\n",
    "            elif(temp[5]<0.3):\n",
    "                b=0\n",
    "            elif(temp[5]>0.4):\n",
    "                b=1\n",
    "            else:\n",
    "                b=0\n",
    "        else:\n",
    "            if((temp[0]+temp[1])/2<0.6):\n",
    "                b=1\n",
    "            elif((temp[0]+temp[1])/2>0.7):\n",
    "                b=2\n",
    "            elif(temp[2]<0.6):\n",
    "                b=1\n",
    "            elif(temp[2]>0.7):\n",
    "                b=2\n",
    "            elif((temp[3]+temp[4])/2<0.6):\n",
    "                b=1\n",
    "            elif((temp[3]+temp[4])/2>0.7):\n",
    "                b=2\n",
    "            elif(temp[5]<0.6):\n",
    "                b=1\n",
    "            elif(temp[5]>0.7):\n",
    "                b=2\n",
    "            else:\n",
    "                b=1\n",
    "    labels[i]=b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "data1=pd.concat((data,pd.DataFrame(labels,columns=['Label'])),axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "data1.to_csv('labelled_data_new.csv',index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1b4800b8ec8>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(9,8))\n",
    "sns.heatmap(data1.corr(),annot=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}