Code.ipynb

{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Importing Modules"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import seaborn as sns\n",
    "import pandas as pd\n",
    "import numpy as  np\n",
    "import matplotlib.pyplot as plt\n"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Importing the dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_test = pd.read_csv('data/laptops_test.csv', sep = ',') # test data\n",
    "df = pd.read_csv('data/laptops_train.csv', sep = ',') # train data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Manufacturer</th>\n",
       "      <th>Model Name</th>\n",
       "      <th>Category</th>\n",
       "      <th>Screen Size</th>\n",
       "      <th>Screen</th>\n",
       "      <th>CPU</th>\n",
       "      <th>RAM</th>\n",
       "      <th>Storage</th>\n",
       "      <th>GPU</th>\n",
       "      <th>Operating System</th>\n",
       "      <th>Operating System Version</th>\n",
       "      <th>Weight</th>\n",
       "      <th>Price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Apple</td>\n",
       "      <td>MacBook Pro</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>13.3\"</td>\n",
       "      <td>IPS Panel Retina Display 2560x1600</td>\n",
       "      <td>Intel Core i5 2.3GHz</td>\n",
       "      <td>8GB</td>\n",
       "      <td>128GB SSD</td>\n",
       "      <td>Intel Iris Plus Graphics 640</td>\n",
       "      <td>macOS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.37kg</td>\n",
       "      <td>11912523.48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Apple</td>\n",
       "      <td>Macbook Air</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>13.3\"</td>\n",
       "      <td>1440x900</td>\n",
       "      <td>Intel Core i5 1.8GHz</td>\n",
       "      <td>8GB</td>\n",
       "      <td>128GB Flash Storage</td>\n",
       "      <td>Intel HD Graphics 6000</td>\n",
       "      <td>macOS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.34kg</td>\n",
       "      <td>7993374.48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>HP</td>\n",
       "      <td>250 G6</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>15.6\"</td>\n",
       "      <td>Full HD 1920x1080</td>\n",
       "      <td>Intel Core i5 7200U 2.5GHz</td>\n",
       "      <td>8GB</td>\n",
       "      <td>256GB SSD</td>\n",
       "      <td>Intel HD Graphics 620</td>\n",
       "      <td>No OS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.86kg</td>\n",
       "      <td>5112900.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Apple</td>\n",
       "      <td>MacBook Pro</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>15.4\"</td>\n",
       "      <td>IPS Panel Retina Display 2880x1800</td>\n",
       "      <td>Intel Core i7 2.7GHz</td>\n",
       "      <td>16GB</td>\n",
       "      <td>512GB SSD</td>\n",
       "      <td>AMD Radeon Pro 455</td>\n",
       "      <td>macOS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.83kg</td>\n",
       "      <td>22563005.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Apple</td>\n",
       "      <td>MacBook Pro</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>13.3\"</td>\n",
       "      <td>IPS Panel Retina Display 2560x1600</td>\n",
       "      <td>Intel Core i5 3.1GHz</td>\n",
       "      <td>8GB</td>\n",
       "      <td>256GB SSD</td>\n",
       "      <td>Intel Iris Plus Graphics 650</td>\n",
       "      <td>macOS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.37kg</td>\n",
       "      <td>16037611.20</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Manufacturer   Model Name   Category Screen Size  \\\n",
       "0        Apple  MacBook Pro  Ultrabook       13.3\"   \n",
       "1        Apple  Macbook Air  Ultrabook       13.3\"   \n",
       "2           HP       250 G6   Notebook       15.6\"   \n",
       "3        Apple  MacBook Pro  Ultrabook       15.4\"   \n",
       "4        Apple  MacBook Pro  Ultrabook       13.3\"   \n",
       "\n",
       "                               Screen                         CPU   RAM  \\\n",
       "0  IPS Panel Retina Display 2560x1600        Intel Core i5 2.3GHz   8GB   \n",
       "1                            1440x900        Intel Core i5 1.8GHz   8GB   \n",
       "2                   Full HD 1920x1080  Intel Core i5 7200U 2.5GHz   8GB   \n",
       "3  IPS Panel Retina Display 2880x1800        Intel Core i7 2.7GHz  16GB   \n",
       "4  IPS Panel Retina Display 2560x1600        Intel Core i5 3.1GHz   8GB   \n",
       "\n",
       "               Storage                           GPU Operating System  \\\n",
       "0            128GB SSD  Intel Iris Plus Graphics 640            macOS   \n",
       "1  128GB Flash Storage        Intel HD Graphics 6000            macOS   \n",
       "2            256GB SSD         Intel HD Graphics 620            No OS   \n",
       "3            512GB SSD            AMD Radeon Pro 455            macOS   \n",
       "4            256GB SSD  Intel Iris Plus Graphics 650            macOS   \n",
       "\n",
       "  Operating System Version  Weight        Price  \n",
       "0                      NaN  1.37kg  11912523.48  \n",
       "1                      NaN  1.34kg   7993374.48  \n",
       "2                      NaN  1.86kg   5112900.00  \n",
       "3                      NaN  1.83kg  22563005.40  \n",
       "4                      NaN  1.37kg  16037611.20  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 977 entries, 0 to 976\n",
      "Data columns (total 13 columns):\n",
      " #   Column                    Non-Null Count  Dtype  \n",
      "---  ------                    --------------  -----  \n",
      " 0   Manufacturer              977 non-null    object \n",
      " 1   Model Name                977 non-null    object \n",
      " 2   Category                  977 non-null    object \n",
      " 3   Screen Size               977 non-null    object \n",
      " 4   Screen                    977 non-null    object \n",
      " 5   CPU                       977 non-null    object \n",
      " 6   RAM                       977 non-null    object \n",
      " 7    Storage                  977 non-null    object \n",
      " 8   GPU                       977 non-null    object \n",
      " 9   Operating System          977 non-null    object \n",
      " 10  Operating System Version  841 non-null    object \n",
      " 11  Weight                    977 non-null    object \n",
      " 12  Price                     977 non-null    float64\n",
      "dtypes: float64(1), object(12)\n",
      "memory usage: 99.4+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 325 entries, 0 to 324\n",
      "Data columns (total 13 columns):\n",
      " #   Column                    Non-Null Count  Dtype  \n",
      "---  ------                    --------------  -----  \n",
      " 0   Manufacturer              325 non-null    object \n",
      " 1   Model Name                325 non-null    object \n",
      " 2   Category                  325 non-null    object \n",
      " 3   Screen Size               325 non-null    object \n",
      " 4   Screen                    325 non-null    object \n",
      " 5   CPU                       325 non-null    object \n",
      " 6   RAM                       325 non-null    object \n",
      " 7    Storage                  325 non-null    object \n",
      " 8   GPU                       325 non-null    object \n",
      " 9   Operating System          325 non-null    object \n",
      " 10  Operating System Version  291 non-null    object \n",
      " 11  Weight                    325 non-null    object \n",
      " 12  Price                     325 non-null    float64\n",
      "dtypes: float64(1), object(12)\n",
      "memory usage: 33.1+ KB\n"
     ]
    }
   ],
   "source": [
    "df_test.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>unique_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Manufacturer</th>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Model Name</th>\n",
       "      <td>488</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Category</th>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Screen Size</th>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Screen</th>\n",
       "      <td>38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CPU</th>\n",
       "      <td>106</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RAM</th>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Storage</th>\n",
       "      <td>36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GPU</th>\n",
       "      <td>98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Operating System</th>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Operating System Version</th>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Weight</th>\n",
       "      <td>166</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Price</th>\n",
       "      <td>639</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          unique_count\n",
       "Manufacturer                        19\n",
       "Model Name                         488\n",
       "Category                             6\n",
       "Screen Size                         18\n",
       "Screen                              38\n",
       "CPU                                106\n",
       "RAM                                  8\n",
       " Storage                            36\n",
       "GPU                                 98\n",
       "Operating System                     7\n",
       "Operating System Version             4\n",
       "Weight                             166\n",
       "Price                              639"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# To know the distinct occurence\n",
    "dict = {}\n",
    "\n",
    "for i in list(df.columns):\n",
    "    dict[i] = df[i].value_counts().shape[0]\n",
    "\n",
    "pd.DataFrame(dict, index = ['unique_count']).transpose()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.duplicated().sum()\n",
    "# 0 coming so no rows identically same"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Removing GB\n",
    "df[\"RAM\"] = df[\"RAM\"].str.replace(\"GB\", \"\")\n",
    "df_test[\"RAM\"] = df[\"RAM\"].str.replace(\"GB\",\"\")\n",
    "df[\"RAM\"]= df[\"RAM\"].astype(\"int32\")\n",
    "df_test[\"RAM\"]= df_test[\"RAM\"].astype(\"int32\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Manufacturer</th>\n",
       "      <th>Model Name</th>\n",
       "      <th>Category</th>\n",
       "      <th>Screen Size</th>\n",
       "      <th>Screen</th>\n",
       "      <th>CPU</th>\n",
       "      <th>RAM</th>\n",
       "      <th>Storage</th>\n",
       "      <th>GPU</th>\n",
       "      <th>Operating System</th>\n",
       "      <th>Operating System Version</th>\n",
       "      <th>Weight</th>\n",
       "      <th>Price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Apple</td>\n",
       "      <td>MacBook Pro</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>13.3\"</td>\n",
       "      <td>IPS Panel Retina Display 2560x1600</td>\n",
       "      <td>Intel Core i5 2.3GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>128GB SSD</td>\n",
       "      <td>Intel Iris Plus Graphics 640</td>\n",
       "      <td>macOS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.37kg</td>\n",
       "      <td>11912523.48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Apple</td>\n",
       "      <td>Macbook Air</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>13.3\"</td>\n",
       "      <td>1440x900</td>\n",
       "      <td>Intel Core i5 1.8GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>128GB Flash Storage</td>\n",
       "      <td>Intel HD Graphics 6000</td>\n",
       "      <td>macOS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.34kg</td>\n",
       "      <td>7993374.48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>HP</td>\n",
       "      <td>250 G6</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>15.6\"</td>\n",
       "      <td>Full HD 1920x1080</td>\n",
       "      <td>Intel Core i5 7200U 2.5GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>256GB SSD</td>\n",
       "      <td>Intel HD Graphics 620</td>\n",
       "      <td>No OS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.86kg</td>\n",
       "      <td>5112900.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Apple</td>\n",
       "      <td>MacBook Pro</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>15.4\"</td>\n",
       "      <td>IPS Panel Retina Display 2880x1800</td>\n",
       "      <td>Intel Core i7 2.7GHz</td>\n",
       "      <td>16</td>\n",
       "      <td>512GB SSD</td>\n",
       "      <td>AMD Radeon Pro 455</td>\n",
       "      <td>macOS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.83kg</td>\n",
       "      <td>22563005.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Apple</td>\n",
       "      <td>MacBook Pro</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>13.3\"</td>\n",
       "      <td>IPS Panel Retina Display 2560x1600</td>\n",
       "      <td>Intel Core i5 3.1GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>256GB SSD</td>\n",
       "      <td>Intel Iris Plus Graphics 650</td>\n",
       "      <td>macOS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.37kg</td>\n",
       "      <td>16037611.20</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Manufacturer   Model Name   Category Screen Size  \\\n",
       "0        Apple  MacBook Pro  Ultrabook       13.3\"   \n",
       "1        Apple  Macbook Air  Ultrabook       13.3\"   \n",
       "2           HP       250 G6   Notebook       15.6\"   \n",
       "3        Apple  MacBook Pro  Ultrabook       15.4\"   \n",
       "4        Apple  MacBook Pro  Ultrabook       13.3\"   \n",
       "\n",
       "                               Screen                         CPU  RAM  \\\n",
       "0  IPS Panel Retina Display 2560x1600        Intel Core i5 2.3GHz    8   \n",
       "1                            1440x900        Intel Core i5 1.8GHz    8   \n",
       "2                   Full HD 1920x1080  Intel Core i5 7200U 2.5GHz    8   \n",
       "3  IPS Panel Retina Display 2880x1800        Intel Core i7 2.7GHz   16   \n",
       "4  IPS Panel Retina Display 2560x1600        Intel Core i5 3.1GHz    8   \n",
       "\n",
       "               Storage                           GPU Operating System  \\\n",
       "0            128GB SSD  Intel Iris Plus Graphics 640            macOS   \n",
       "1  128GB Flash Storage        Intel HD Graphics 6000            macOS   \n",
       "2            256GB SSD         Intel HD Graphics 620            No OS   \n",
       "3            512GB SSD            AMD Radeon Pro 455            macOS   \n",
       "4            256GB SSD  Intel Iris Plus Graphics 650            macOS   \n",
       "\n",
       "  Operating System Version  Weight        Price  \n",
       "0                      NaN  1.37kg  11912523.48  \n",
       "1                      NaN  1.34kg   7993374.48  \n",
       "2                      NaN  1.86kg   5112900.00  \n",
       "3                      NaN  1.83kg  22563005.40  \n",
       "4                      NaN  1.37kg  16037611.20  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Manufacturer                0.000000\n",
       "Model Name                  0.000000\n",
       "Category                    0.000000\n",
       "Screen Size                 0.000000\n",
       "Screen                      0.000000\n",
       "CPU                         0.000000\n",
       "RAM                         0.000000\n",
       " Storage                    0.000000\n",
       "GPU                         0.000000\n",
       "Operating System            0.000000\n",
       "Operating System Version    0.139202\n",
       "Weight                      0.000000\n",
       "Price                       0.000000\n",
       "dtype: float64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(df.isnull().sum()/len(df))\n",
    "# OS version not returning 0 so need to fill some rows"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Filling vacant rows for our models to work properly\n",
    "\n",
    "df['Operating System Version']=df['Operating System Version'].fillna(df['Operating System Version'].mode()[0])\n",
    "df_test['Operating System Version']=df_test['Operating System Version'].fillna(df_test['Operating System Version'].mode()[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>RAM</th>\n",
       "      <th>Price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>977.000000</td>\n",
       "      <td>9.770000e+02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>8.528147</td>\n",
       "      <td>1.001899e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>4.997487</td>\n",
       "      <td>6.306430e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.706375e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>4.000000</td>\n",
       "      <td>5.326308e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>8.000000</td>\n",
       "      <td>8.527428e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>8.000000</td>\n",
       "      <td>1.311570e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>32.000000</td>\n",
       "      <td>5.423231e+07</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              RAM         Price\n",
       "count  977.000000  9.770000e+02\n",
       "mean     8.528147  1.001899e+07\n",
       "std      4.997487  6.306430e+06\n",
       "min      2.000000  1.706375e+06\n",
       "25%      4.000000  5.326308e+06\n",
       "50%      8.000000  8.527428e+06\n",
       "75%      8.000000  1.311570e+07\n",
       "max     32.000000  5.423231e+07"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Manufacturer                 object\n",
       "Model Name                   object\n",
       "Category                     object\n",
       "Screen Size                  object\n",
       "Screen                       object\n",
       "CPU                          object\n",
       "RAM                           int32\n",
       " Storage                     object\n",
       "GPU                          object\n",
       "Operating System             object\n",
       "Operating System Version     object\n",
       "Weight                       object\n",
       "Price                       float64\n",
       "dtype: object"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "# removing kgs from weight and then making weights into data type\n",
    "# making the price into numeric data type\n",
    "\n",
    "df['Weight'].replace(to_replace='kg', value='', regex=True, inplace=True)\n",
    "df_test['Weight'].replace(to_replace='kg', value='', regex=True, inplace=True)\n",
    "df_test['Weight'].replace(to_replace='s', value='', regex=True, inplace=True)\n",
    "\n",
    "df['Weight'] = df['Weight'].astype(\"float64\")\n",
    "df_test['Weight'] = df_test['Weight'].astype(\"float64\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Manufacturer</th>\n",
       "      <th>Model Name</th>\n",
       "      <th>Category</th>\n",
       "      <th>Screen Size</th>\n",
       "      <th>Screen</th>\n",
       "      <th>CPU</th>\n",
       "      <th>RAM</th>\n",
       "      <th>Storage</th>\n",
       "      <th>GPU</th>\n",
       "      <th>Operating System</th>\n",
       "      <th>Operating System Version</th>\n",
       "      <th>Weight</th>\n",
       "      <th>Price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Apple</td>\n",
       "      <td>MacBook Pro</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>13.3\"</td>\n",
       "      <td>IPS Panel Retina Display 2560x1600</td>\n",
       "      <td>Intel Core i5 2.3GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>128GB SSD</td>\n",
       "      <td>Intel Iris Plus Graphics 640</td>\n",
       "      <td>macOS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.37</td>\n",
       "      <td>11912523.48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Apple</td>\n",
       "      <td>Macbook Air</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>13.3\"</td>\n",
       "      <td>1440x900</td>\n",
       "      <td>Intel Core i5 1.8GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>128GB Flash Storage</td>\n",
       "      <td>Intel HD Graphics 6000</td>\n",
       "      <td>macOS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.34</td>\n",
       "      <td>7993374.48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>HP</td>\n",
       "      <td>250 G6</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>15.6\"</td>\n",
       "      <td>Full HD 1920x1080</td>\n",
       "      <td>Intel Core i5 7200U 2.5GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>256GB SSD</td>\n",
       "      <td>Intel HD Graphics 620</td>\n",
       "      <td>No OS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.86</td>\n",
       "      <td>5112900.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Apple</td>\n",
       "      <td>MacBook Pro</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>15.4\"</td>\n",
       "      <td>IPS Panel Retina Display 2880x1800</td>\n",
       "      <td>Intel Core i7 2.7GHz</td>\n",
       "      <td>16</td>\n",
       "      <td>512GB SSD</td>\n",
       "      <td>AMD Radeon Pro 455</td>\n",
       "      <td>macOS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.83</td>\n",
       "      <td>22563005.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Apple</td>\n",
       "      <td>MacBook Pro</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>13.3\"</td>\n",
       "      <td>IPS Panel Retina Display 2560x1600</td>\n",
       "      <td>Intel Core i5 3.1GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>256GB SSD</td>\n",
       "      <td>Intel Iris Plus Graphics 650</td>\n",
       "      <td>macOS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.37</td>\n",
       "      <td>16037611.20</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Manufacturer   Model Name   Category Screen Size  \\\n",
       "0        Apple  MacBook Pro  Ultrabook       13.3\"   \n",
       "1        Apple  Macbook Air  Ultrabook       13.3\"   \n",
       "2           HP       250 G6   Notebook       15.6\"   \n",
       "3        Apple  MacBook Pro  Ultrabook       15.4\"   \n",
       "4        Apple  MacBook Pro  Ultrabook       13.3\"   \n",
       "\n",
       "                               Screen                         CPU  RAM  \\\n",
       "0  IPS Panel Retina Display 2560x1600        Intel Core i5 2.3GHz    8   \n",
       "1                            1440x900        Intel Core i5 1.8GHz    8   \n",
       "2                   Full HD 1920x1080  Intel Core i5 7200U 2.5GHz    8   \n",
       "3  IPS Panel Retina Display 2880x1800        Intel Core i7 2.7GHz   16   \n",
       "4  IPS Panel Retina Display 2560x1600        Intel Core i5 3.1GHz    8   \n",
       "\n",
       "               Storage                           GPU Operating System  \\\n",
       "0            128GB SSD  Intel Iris Plus Graphics 640            macOS   \n",
       "1  128GB Flash Storage        Intel HD Graphics 6000            macOS   \n",
       "2            256GB SSD         Intel HD Graphics 620            No OS   \n",
       "3            512GB SSD            AMD Radeon Pro 455            macOS   \n",
       "4            256GB SSD  Intel Iris Plus Graphics 650            macOS   \n",
       "\n",
       "  Operating System Version  Weight        Price  \n",
       "0                       10    1.37  11912523.48  \n",
       "1                       10    1.34   7993374.48  \n",
       "2                       10    1.86   5112900.00  \n",
       "3                       10    1.83  22563005.40  \n",
       "4                       10    1.37  16037611.20  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Manufacturer</th>\n",
       "      <th>Model Name</th>\n",
       "      <th>Category</th>\n",
       "      <th>Screen Size</th>\n",
       "      <th>Screen</th>\n",
       "      <th>CPU</th>\n",
       "      <th>RAM</th>\n",
       "      <th>Storage</th>\n",
       "      <th>GPU</th>\n",
       "      <th>Operating System</th>\n",
       "      <th>Operating System Version</th>\n",
       "      <th>Weight</th>\n",
       "      <th>Price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>HP</td>\n",
       "      <td>15-bs053od (i7-7500U/6GB/1TB/W10)</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>15.6\"</td>\n",
       "      <td>1366x768</td>\n",
       "      <td>Intel Core i7 7500U 2.7GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>1TB HDD</td>\n",
       "      <td>Intel HD Graphics 620</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>2.04</td>\n",
       "      <td>5148468.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Asus</td>\n",
       "      <td>Rog GL753VE-DS74</td>\n",
       "      <td>Gaming</td>\n",
       "      <td>17.3\"</td>\n",
       "      <td>Full HD 1920x1080</td>\n",
       "      <td>Intel Core i7 7700HQ 2.8GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>256GB SSD +  1TB HDD</td>\n",
       "      <td>Nvidia GeForce GTX 1050 Ti</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>2.99</td>\n",
       "      <td>15552108.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Dell</td>\n",
       "      <td>Inspiron 7579</td>\n",
       "      <td>2 in 1 Convertible</td>\n",
       "      <td>15.6\"</td>\n",
       "      <td>IPS Panel Full HD / Touchscreen 1920x1080</td>\n",
       "      <td>Intel Core i7 7500U 2.7GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>512GB SSD</td>\n",
       "      <td>Intel HD Graphics 620</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>2.19</td>\n",
       "      <td>11550708.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Toshiba</td>\n",
       "      <td>Portege Z30-C-1CV</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>13.3\"</td>\n",
       "      <td>Full HD 1920x1080</td>\n",
       "      <td>Intel Core i5 6200U 2.3GHz</td>\n",
       "      <td>16</td>\n",
       "      <td>128GB SSD</td>\n",
       "      <td>Intel HD Graphics 520</td>\n",
       "      <td>Windows</td>\n",
       "      <td>7</td>\n",
       "      <td>1.20</td>\n",
       "      <td>10625940.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Lenovo</td>\n",
       "      <td>IdeaPad 320-15ABR</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>15.6\"</td>\n",
       "      <td>Full HD 1920x1080</td>\n",
       "      <td>AMD A12-Series 9720P 3.6GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>256GB SSD</td>\n",
       "      <td>AMD Radeon 530</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>2.20</td>\n",
       "      <td>4881708.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Manufacturer                         Model Name            Category  \\\n",
       "0           HP  15-bs053od (i7-7500U/6GB/1TB/W10)            Notebook   \n",
       "1         Asus                   Rog GL753VE-DS74              Gaming   \n",
       "2         Dell                      Inspiron 7579  2 in 1 Convertible   \n",
       "3      Toshiba                  Portege Z30-C-1CV            Notebook   \n",
       "4       Lenovo                  IdeaPad 320-15ABR            Notebook   \n",
       "\n",
       "  Screen Size                                     Screen  \\\n",
       "0       15.6\"                                   1366x768   \n",
       "1       17.3\"                          Full HD 1920x1080   \n",
       "2       15.6\"  IPS Panel Full HD / Touchscreen 1920x1080   \n",
       "3       13.3\"                          Full HD 1920x1080   \n",
       "4       15.6\"                          Full HD 1920x1080   \n",
       "\n",
       "                           CPU  RAM               Storage  \\\n",
       "0   Intel Core i7 7500U 2.7GHz    8               1TB HDD   \n",
       "1  Intel Core i7 7700HQ 2.8GHz    8  256GB SSD +  1TB HDD   \n",
       "2   Intel Core i7 7500U 2.7GHz    8             512GB SSD   \n",
       "3   Intel Core i5 6200U 2.3GHz   16             128GB SSD   \n",
       "4  AMD A12-Series 9720P 3.6GHz    8             256GB SSD   \n",
       "\n",
       "                          GPU Operating System Operating System Version  \\\n",
       "0       Intel HD Graphics 620          Windows                       10   \n",
       "1  Nvidia GeForce GTX 1050 Ti          Windows                       10   \n",
       "2       Intel HD Graphics 620          Windows                       10   \n",
       "3       Intel HD Graphics 520          Windows                        7   \n",
       "4              AMD Radeon 530          Windows                       10   \n",
       "\n",
       "   Weight       Price  \n",
       "0    2.04   5148468.0  \n",
       "1    2.99  15552108.0  \n",
       "2    2.19  11550708.0  \n",
       "3    1.20  10625940.0  \n",
       "4    2.20   4881708.0  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_test.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "df[\"Screen Size\"] = df[\"Screen Size\"].str.replace(\"\\\"\",\"\")\n",
    "# df_test[\"Screen Size\"] = df_test[\"Screen Size\"].str.replace('\"',\"\")\n",
    "df['Screen Size'] = df['Screen Size'].astype(\"float64\")\n",
    "# df_test['Screen Size'] = df_test['Screen Size'].astype(\"float64\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Manufacturer</th>\n",
       "      <th>Model Name</th>\n",
       "      <th>Category</th>\n",
       "      <th>Screen Size</th>\n",
       "      <th>Screen</th>\n",
       "      <th>CPU</th>\n",
       "      <th>RAM</th>\n",
       "      <th>Storage</th>\n",
       "      <th>GPU</th>\n",
       "      <th>Operating System</th>\n",
       "      <th>Operating System Version</th>\n",
       "      <th>Weight</th>\n",
       "      <th>Price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>HP</td>\n",
       "      <td>15-bs053od (i7-7500U/6GB/1TB/W10)</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>15.6\"</td>\n",
       "      <td>1366x768</td>\n",
       "      <td>Intel Core i7 7500U 2.7GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>1TB HDD</td>\n",
       "      <td>Intel HD Graphics 620</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>2.04</td>\n",
       "      <td>5148468.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Asus</td>\n",
       "      <td>Rog GL753VE-DS74</td>\n",
       "      <td>Gaming</td>\n",
       "      <td>17.3\"</td>\n",
       "      <td>Full HD 1920x1080</td>\n",
       "      <td>Intel Core i7 7700HQ 2.8GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>256GB SSD +  1TB HDD</td>\n",
       "      <td>Nvidia GeForce GTX 1050 Ti</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>2.99</td>\n",
       "      <td>15552108.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Dell</td>\n",
       "      <td>Inspiron 7579</td>\n",
       "      <td>2 in 1 Convertible</td>\n",
       "      <td>15.6\"</td>\n",
       "      <td>IPS Panel Full HD / Touchscreen 1920x1080</td>\n",
       "      <td>Intel Core i7 7500U 2.7GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>512GB SSD</td>\n",
       "      <td>Intel HD Graphics 620</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>2.19</td>\n",
       "      <td>11550708.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Toshiba</td>\n",
       "      <td>Portege Z30-C-1CV</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>13.3\"</td>\n",
       "      <td>Full HD 1920x1080</td>\n",
       "      <td>Intel Core i5 6200U 2.3GHz</td>\n",
       "      <td>16</td>\n",
       "      <td>128GB SSD</td>\n",
       "      <td>Intel HD Graphics 520</td>\n",
       "      <td>Windows</td>\n",
       "      <td>7</td>\n",
       "      <td>1.20</td>\n",
       "      <td>10625940.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Lenovo</td>\n",
       "      <td>IdeaPad 320-15ABR</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>15.6\"</td>\n",
       "      <td>Full HD 1920x1080</td>\n",
       "      <td>AMD A12-Series 9720P 3.6GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>256GB SSD</td>\n",
       "      <td>AMD Radeon 530</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>2.20</td>\n",
       "      <td>4881708.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Manufacturer                         Model Name            Category  \\\n",
       "0           HP  15-bs053od (i7-7500U/6GB/1TB/W10)            Notebook   \n",
       "1         Asus                   Rog GL753VE-DS74              Gaming   \n",
       "2         Dell                      Inspiron 7579  2 in 1 Convertible   \n",
       "3      Toshiba                  Portege Z30-C-1CV            Notebook   \n",
       "4       Lenovo                  IdeaPad 320-15ABR            Notebook   \n",
       "\n",
       "  Screen Size                                     Screen  \\\n",
       "0       15.6\"                                   1366x768   \n",
       "1       17.3\"                          Full HD 1920x1080   \n",
       "2       15.6\"  IPS Panel Full HD / Touchscreen 1920x1080   \n",
       "3       13.3\"                          Full HD 1920x1080   \n",
       "4       15.6\"                          Full HD 1920x1080   \n",
       "\n",
       "                           CPU  RAM               Storage  \\\n",
       "0   Intel Core i7 7500U 2.7GHz    8               1TB HDD   \n",
       "1  Intel Core i7 7700HQ 2.8GHz    8  256GB SSD +  1TB HDD   \n",
       "2   Intel Core i7 7500U 2.7GHz    8             512GB SSD   \n",
       "3   Intel Core i5 6200U 2.3GHz   16             128GB SSD   \n",
       "4  AMD A12-Series 9720P 3.6GHz    8             256GB SSD   \n",
       "\n",
       "                          GPU Operating System Operating System Version  \\\n",
       "0       Intel HD Graphics 620          Windows                       10   \n",
       "1  Nvidia GeForce GTX 1050 Ti          Windows                       10   \n",
       "2       Intel HD Graphics 620          Windows                       10   \n",
       "3       Intel HD Graphics 520          Windows                        7   \n",
       "4              AMD Radeon 530          Windows                       10   \n",
       "\n",
       "   Weight       Price  \n",
       "0    2.04   5148468.0  \n",
       "1    2.99  15552108.0  \n",
       "2    2.19  11550708.0  \n",
       "3    1.20  10625940.0  \n",
       "4    2.20   4881708.0  "
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_test.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_test[\"Screen Size\"] = df_test[\"Screen Size\"].str.replace('\"',\"\")\n",
    "df_test['Screen Size'] = df_test['Screen Size'].astype(\"float64\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>Manufacturer</th>\n",
       "      <th>Model Name</th>\n",
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       "      <th>Screen Size</th>\n",
       "      <th>Screen</th>\n",
       "      <th>CPU</th>\n",
       "      <th>RAM</th>\n",
       "      <th>Storage</th>\n",
       "      <th>GPU</th>\n",
       "      <th>Operating System</th>\n",
       "      <th>Operating System Version</th>\n",
       "      <th>Weight</th>\n",
       "      <th>Price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>HP</td>\n",
       "      <td>15-bs053od (i7-7500U/6GB/1TB/W10)</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>15.6</td>\n",
       "      <td>1366x768</td>\n",
       "      <td>Intel Core i7 7500U 2.7GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>1TB HDD</td>\n",
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       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>2.04</td>\n",
       "      <td>5148468.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Asus</td>\n",
       "      <td>Rog GL753VE-DS74</td>\n",
       "      <td>Gaming</td>\n",
       "      <td>17.3</td>\n",
       "      <td>Full HD 1920x1080</td>\n",
       "      <td>Intel Core i7 7700HQ 2.8GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>256GB SSD +  1TB HDD</td>\n",
       "      <td>Nvidia GeForce GTX 1050 Ti</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>2.99</td>\n",
       "      <td>15552108.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Dell</td>\n",
       "      <td>Inspiron 7579</td>\n",
       "      <td>2 in 1 Convertible</td>\n",
       "      <td>15.6</td>\n",
       "      <td>IPS Panel Full HD / Touchscreen 1920x1080</td>\n",
       "      <td>Intel Core i7 7500U 2.7GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>512GB SSD</td>\n",
       "      <td>Intel HD Graphics 620</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>2.19</td>\n",
       "      <td>11550708.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Toshiba</td>\n",
       "      <td>Portege Z30-C-1CV</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>13.3</td>\n",
       "      <td>Full HD 1920x1080</td>\n",
       "      <td>Intel Core i5 6200U 2.3GHz</td>\n",
       "      <td>16</td>\n",
       "      <td>128GB SSD</td>\n",
       "      <td>Intel HD Graphics 520</td>\n",
       "      <td>Windows</td>\n",
       "      <td>7</td>\n",
       "      <td>1.20</td>\n",
       "      <td>10625940.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Lenovo</td>\n",
       "      <td>IdeaPad 320-15ABR</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>15.6</td>\n",
       "      <td>Full HD 1920x1080</td>\n",
       "      <td>AMD A12-Series 9720P 3.6GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>256GB SSD</td>\n",
       "      <td>AMD Radeon 530</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>2.20</td>\n",
       "      <td>4881708.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Manufacturer                         Model Name            Category  \\\n",
       "0           HP  15-bs053od (i7-7500U/6GB/1TB/W10)            Notebook   \n",
       "1         Asus                   Rog GL753VE-DS74              Gaming   \n",
       "2         Dell                      Inspiron 7579  2 in 1 Convertible   \n",
       "3      Toshiba                  Portege Z30-C-1CV            Notebook   \n",
       "4       Lenovo                  IdeaPad 320-15ABR            Notebook   \n",
       "\n",
       "   Screen Size                                     Screen  \\\n",
       "0         15.6                                   1366x768   \n",
       "1         17.3                          Full HD 1920x1080   \n",
       "2         15.6  IPS Panel Full HD / Touchscreen 1920x1080   \n",
       "3         13.3                          Full HD 1920x1080   \n",
       "4         15.6                          Full HD 1920x1080   \n",
       "\n",
       "                           CPU  RAM               Storage  \\\n",
       "0   Intel Core i7 7500U 2.7GHz    8               1TB HDD   \n",
       "1  Intel Core i7 7700HQ 2.8GHz    8  256GB SSD +  1TB HDD   \n",
       "2   Intel Core i7 7500U 2.7GHz    8             512GB SSD   \n",
       "3   Intel Core i5 6200U 2.3GHz   16             128GB SSD   \n",
       "4  AMD A12-Series 9720P 3.6GHz    8             256GB SSD   \n",
       "\n",
       "                          GPU Operating System Operating System Version  \\\n",
       "0       Intel HD Graphics 620          Windows                       10   \n",
       "1  Nvidia GeForce GTX 1050 Ti          Windows                       10   \n",
       "2       Intel HD Graphics 620          Windows                       10   \n",
       "3       Intel HD Graphics 520          Windows                        7   \n",
       "4              AMD Radeon 530          Windows                       10   \n",
       "\n",
       "   Weight       Price  \n",
       "0    2.04   5148468.0  \n",
       "1    2.99  15552108.0  \n",
       "2    2.19  11550708.0  \n",
       "3    1.20  10625940.0  \n",
       "4    2.20   4881708.0  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "df_test.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Manufacturer</th>\n",
       "      <th>Model Name</th>\n",
       "      <th>Category</th>\n",
       "      <th>Screen Size</th>\n",
       "      <th>Screen</th>\n",
       "      <th>CPU</th>\n",
       "      <th>RAM</th>\n",
       "      <th>Storage</th>\n",
       "      <th>GPU</th>\n",
       "      <th>Operating System</th>\n",
       "      <th>Operating System Version</th>\n",
       "      <th>Weight</th>\n",
       "      <th>Price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Apple</td>\n",
       "      <td>MacBook Pro</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>13.3</td>\n",
       "      <td>IPS Panel Retina Display 2560x1600</td>\n",
       "      <td>Intel Core i5 2.3GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>128GB SSD</td>\n",
       "      <td>Intel Iris Plus Graphics 640</td>\n",
       "      <td>macOS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.37</td>\n",
       "      <td>11912523.48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Apple</td>\n",
       "      <td>Macbook Air</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>13.3</td>\n",
       "      <td>1440x900</td>\n",
       "      <td>Intel Core i5 1.8GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>128GB Flash Storage</td>\n",
       "      <td>Intel HD Graphics 6000</td>\n",
       "      <td>macOS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.34</td>\n",
       "      <td>7993374.48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>HP</td>\n",
       "      <td>250 G6</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>15.6</td>\n",
       "      <td>Full HD 1920x1080</td>\n",
       "      <td>Intel Core i5 7200U 2.5GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>256GB SSD</td>\n",
       "      <td>Intel HD Graphics 620</td>\n",
       "      <td>No OS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.86</td>\n",
       "      <td>5112900.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Apple</td>\n",
       "      <td>MacBook Pro</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>15.4</td>\n",
       "      <td>IPS Panel Retina Display 2880x1800</td>\n",
       "      <td>Intel Core i7 2.7GHz</td>\n",
       "      <td>16</td>\n",
       "      <td>512GB SSD</td>\n",
       "      <td>AMD Radeon Pro 455</td>\n",
       "      <td>macOS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.83</td>\n",
       "      <td>22563005.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Apple</td>\n",
       "      <td>MacBook Pro</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>13.3</td>\n",
       "      <td>IPS Panel Retina Display 2560x1600</td>\n",
       "      <td>Intel Core i5 3.1GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>256GB SSD</td>\n",
       "      <td>Intel Iris Plus Graphics 650</td>\n",
       "      <td>macOS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.37</td>\n",
       "      <td>16037611.20</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Manufacturer   Model Name   Category  Screen Size  \\\n",
       "0        Apple  MacBook Pro  Ultrabook         13.3   \n",
       "1        Apple  Macbook Air  Ultrabook         13.3   \n",
       "2           HP       250 G6   Notebook         15.6   \n",
       "3        Apple  MacBook Pro  Ultrabook         15.4   \n",
       "4        Apple  MacBook Pro  Ultrabook         13.3   \n",
       "\n",
       "                               Screen                         CPU  RAM  \\\n",
       "0  IPS Panel Retina Display 2560x1600        Intel Core i5 2.3GHz    8   \n",
       "1                            1440x900        Intel Core i5 1.8GHz    8   \n",
       "2                   Full HD 1920x1080  Intel Core i5 7200U 2.5GHz    8   \n",
       "3  IPS Panel Retina Display 2880x1800        Intel Core i7 2.7GHz   16   \n",
       "4  IPS Panel Retina Display 2560x1600        Intel Core i5 3.1GHz    8   \n",
       "\n",
       "               Storage                           GPU Operating System  \\\n",
       "0            128GB SSD  Intel Iris Plus Graphics 640            macOS   \n",
       "1  128GB Flash Storage        Intel HD Graphics 6000            macOS   \n",
       "2            256GB SSD         Intel HD Graphics 620            No OS   \n",
       "3            512GB SSD            AMD Radeon Pro 455            macOS   \n",
       "4            256GB SSD  Intel Iris Plus Graphics 650            macOS   \n",
       "\n",
       "  Operating System Version  Weight        Price  \n",
       "0                       10    1.37  11912523.48  \n",
       "1                       10    1.34   7993374.48  \n",
       "2                       10    1.86   5112900.00  \n",
       "3                       10    1.83  22563005.40  \n",
       "4                       10    1.37  16037611.20  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 977 entries, 0 to 976\n",
      "Data columns (total 13 columns):\n",
      " #   Column                    Non-Null Count  Dtype  \n",
      "---  ------                    --------------  -----  \n",
      " 0   Manufacturer              977 non-null    object \n",
      " 1   Model Name                977 non-null    object \n",
      " 2   Category                  977 non-null    object \n",
      " 3   Screen Size               977 non-null    float64\n",
      " 4   Screen                    977 non-null    object \n",
      " 5   CPU                       977 non-null    object \n",
      " 6   RAM                       977 non-null    int32  \n",
      " 7    Storage                  977 non-null    object \n",
      " 8   GPU                       977 non-null    object \n",
      " 9   Operating System          977 non-null    object \n",
      " 10  Operating System Version  977 non-null    object \n",
      " 11  Weight                    977 non-null    float64\n",
      " 12  Price                     977 non-null    float64\n",
      "dtypes: float64(3), int32(1), object(9)\n",
      "memory usage: 95.5+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 325 entries, 0 to 324\n",
      "Data columns (total 13 columns):\n",
      " #   Column                    Non-Null Count  Dtype  \n",
      "---  ------                    --------------  -----  \n",
      " 0   Manufacturer              325 non-null    object \n",
      " 1   Model Name                325 non-null    object \n",
      " 2   Category                  325 non-null    object \n",
      " 3   Screen Size               325 non-null    float64\n",
      " 4   Screen                    325 non-null    object \n",
      " 5   CPU                       325 non-null    object \n",
      " 6   RAM                       325 non-null    int32  \n",
      " 7    Storage                  325 non-null    object \n",
      " 8   GPU                       325 non-null    object \n",
      " 9   Operating System          325 non-null    object \n",
      " 10  Operating System Version  325 non-null    object \n",
      " 11  Weight                    325 non-null    float64\n",
      " 12  Price                     325 non-null    float64\n",
      "dtypes: float64(3), int32(1), object(9)\n",
      "memory usage: 31.9+ KB\n"
     ]
    }
   ],
   "source": [
    "df_test.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\aasad\\AppData\\Local\\Temp/ipykernel_1752/941010651.py:1: UserWarning: \n",
      "\n",
      "`distplot` is a deprecated function and will be removed in seaborn v0.14.0.\n",
      "\n",
      "Please adapt your code to use either `displot` (a figure-level function with\n",
      "similar flexibility) or `histplot` (an axes-level function for histograms).\n",
      "\n",
      "For a guide to updating your code to use the new functions, please see\n",
      "https://gist.github.com/mwaskom/de44147ed2974457ad6372750bbe5751\n",
      "\n",
      "  sns.distplot(df[\"Price\"])\n"
     ]
    },
    {
     "ename": "OptionError",
     "evalue": "\"No such keys(s): 'mode.use_inf_as_null'\"",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mOptionError\u001b[0m                               Traceback (most recent call last)",
      "\u001b[1;32m~\\AppData\\Local\\Temp/ipykernel_1752/941010651.py\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0msns\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdistplot\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdf\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m\"Price\"\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;32mc:\\Users\\aasad\\AppData\\Local\\Programs\\Python\\Python39\\lib\\site-packages\\seaborn\\distributions.py\u001b[0m in \u001b[0;36mdistplot\u001b[1;34m(a, bins, hist, kde, rug, fit, hist_kws, kde_kws, rug_kws, fit_kws, color, vertical, norm_hist, axlabel, label, ax, x)\u001b[0m\n\u001b[0;32m   2509\u001b[0m     \u001b[1;32mif\u001b[0m \u001b[0mkde\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2510\u001b[0m         \u001b[0mkde_color\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mkde_kws\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpop\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"color\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcolor\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 2511\u001b[1;33m         \u001b[0mkdeplot\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m**\u001b[0m\u001b[1;33m{\u001b[0m\u001b[0maxis\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0ma\u001b[0m\u001b[1;33m}\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0max\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0max\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcolor\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mkde_color\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkde_kws\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   2512\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mkde_color\u001b[0m \u001b[1;33m!=\u001b[0m \u001b[0mcolor\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2513\u001b[0m             \u001b[0mkde_kws\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m\"color\"\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mkde_color\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mc:\\Users\\aasad\\AppData\\Local\\Programs\\Python\\Python39\\lib\\site-packages\\seaborn\\distributions.py\u001b[0m in \u001b[0;36mkdeplot\u001b[1;34m(data, x, y, hue, weights, palette, hue_order, hue_norm, color, fill, multiple, common_norm, common_grid, cumulative, bw_method, bw_adjust, warn_singular, log_scale, levels, thresh, gridsize, cut, clip, legend, cbar, cbar_ax, cbar_kws, ax, **kwargs)\u001b[0m\n\u001b[0;32m   1715\u001b[0m         \u001b[0mplot_kws\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mkwargs\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcopy\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1716\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1717\u001b[1;33m         p.plot_univariate_density(\n\u001b[0m\u001b[0;32m   1718\u001b[0m             \u001b[0mmultiple\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mmultiple\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1719\u001b[0m             \u001b[0mcommon_norm\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mcommon_norm\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mc:\\Users\\aasad\\AppData\\Local\\Programs\\Python\\Python39\\lib\\site-packages\\seaborn\\distributions.py\u001b[0m in \u001b[0;36mplot_univariate_density\u001b[1;34m(self, multiple, common_norm, common_grid, warn_singular, fill, color, legend, estimate_kws, **plot_kws)\u001b[0m\n\u001b[0;32m    935\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    936\u001b[0m         \u001b[1;31m# Do the computation\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 937\u001b[1;33m         densities = self._compute_univariate_density(\n\u001b[0m\u001b[0;32m    938\u001b[0m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdata_variable\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    939\u001b[0m             \u001b[0mcommon_norm\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mc:\\Users\\aasad\\AppData\\Local\\Programs\\Python\\Python39\\lib\\site-packages\\seaborn\\distributions.py\u001b[0m in \u001b[0;36m_compute_univariate_density\u001b[1;34m(self, data_variable, common_norm, common_grid, estimate_kws, log_scale, warn_singular)\u001b[0m\n\u001b[0;32m    327\u001b[0m         \u001b[0mdensities\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m{\u001b[0m\u001b[1;33m}\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    328\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 329\u001b[1;33m         \u001b[1;32mfor\u001b[0m \u001b[0msub_vars\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msub_data\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0miter_data\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"hue\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfrom_comp_data\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mTrue\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    330\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    331\u001b[0m             \u001b[1;31m# Extract the data points from this sub set and remove nulls\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mc:\\Users\\aasad\\AppData\\Local\\Programs\\Python\\Python39\\lib\\site-packages\\seaborn\\_oldcore.py\u001b[0m in \u001b[0;36miter_data\u001b[1;34m(self, grouping_vars, reverse, from_comp_data, by_facet, allow_empty, dropna)\u001b[0m\n\u001b[0;32m   1026\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1027\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mfrom_comp_data\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1028\u001b[1;33m             \u001b[0mdata\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcomp_data\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1029\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1030\u001b[0m             \u001b[0mdata\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mplot_data\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mc:\\Users\\aasad\\AppData\\Local\\Programs\\Python\\Python39\\lib\\site-packages\\seaborn\\_oldcore.py\u001b[0m in \u001b[0;36mcomp_data\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m   1117\u001b[0m                 \u001b[0mgrouped\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mplot_data\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mvar\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mgroupby\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mconverters\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mvar\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msort\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mFalse\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1118\u001b[0m                 \u001b[1;32mfor\u001b[0m \u001b[0mconverter\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0morig\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mgrouped\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1119\u001b[1;33m                     \u001b[1;32mwith\u001b[0m \u001b[0mpd\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0moption_context\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'mode.use_inf_as_null'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;32mTrue\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1120\u001b[0m                         \u001b[0morig\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0morig\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdropna\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1121\u001b[0m                         \u001b[1;32mif\u001b[0m \u001b[0mvar\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mvar_levels\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mc:\\Users\\aasad\\AppData\\Local\\Programs\\Python\\Python39\\lib\\site-packages\\pandas\\_config\\config.py\u001b[0m in \u001b[0;36m__enter__\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m    439\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    440\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0m__enter__\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m->\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 441\u001b[1;33m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mundo\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m[\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mpat\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0m_get_option\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mpat\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msilent\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mTrue\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mpat\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mval\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mops\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    442\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    443\u001b[0m         \u001b[1;32mfor\u001b[0m \u001b[0mpat\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mval\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mops\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mc:\\Users\\aasad\\AppData\\Local\\Programs\\Python\\Python39\\lib\\site-packages\\pandas\\_config\\config.py\u001b[0m in \u001b[0;36m<listcomp>\u001b[1;34m(.0)\u001b[0m\n\u001b[0;32m    439\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    440\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0m__enter__\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m->\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 441\u001b[1;33m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mundo\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m[\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mpat\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0m_get_option\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mpat\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msilent\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mTrue\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mpat\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mval\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mops\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    442\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    443\u001b[0m         \u001b[1;32mfor\u001b[0m \u001b[0mpat\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mval\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mops\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mc:\\Users\\aasad\\AppData\\Local\\Programs\\Python\\Python39\\lib\\site-packages\\pandas\\_config\\config.py\u001b[0m in \u001b[0;36m_get_option\u001b[1;34m(pat, silent)\u001b[0m\n\u001b[0;32m    133\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    134\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0m_get_option\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mpat\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mstr\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msilent\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mbool\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mFalse\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m->\u001b[0m \u001b[0mAny\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 135\u001b[1;33m     \u001b[0mkey\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0m_get_single_key\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mpat\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msilent\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    136\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    137\u001b[0m     \u001b[1;31m# walk the nested dict\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mc:\\Users\\aasad\\AppData\\Local\\Programs\\Python\\Python39\\lib\\site-packages\\pandas\\_config\\config.py\u001b[0m in \u001b[0;36m_get_single_key\u001b[1;34m(pat, silent)\u001b[0m\n\u001b[0;32m    119\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0msilent\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    120\u001b[0m             \u001b[0m_warn_if_deprecated\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mpat\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 121\u001b[1;33m         \u001b[1;32mraise\u001b[0m \u001b[0mOptionError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34mf\"No such keys(s): {repr(pat)}\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    122\u001b[0m     \u001b[1;32mif\u001b[0m \u001b[0mlen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkeys\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m>\u001b[0m \u001b[1;36m1\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    123\u001b[0m         \u001b[1;32mraise\u001b[0m \u001b[0mOptionError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"Pattern matched multiple keys\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mOptionError\u001b[0m: \"No such keys(s): 'mode.use_inf_as_null'\""
     ]
    },
    {
     "data": {
      "image/png": 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qQBa1JI3ZcOGyS4BbllZeAODko3bbBtxaVc+NOp5FLUnj9wrgqeEKjMeyDfhQ14NJksZouPzvD5K8D5YWNEvy+iPbh/PVr2JpfaCRLGpJepmOsSjb+4Grh4tB7eWFT7faBtxcHS+78/I8SWqcI2pJapxFLUmNs6glqXEWtSQ1zqKWpMZZ1JLUOItakhr3f4YpueZ3PFXPAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(df[\"Price\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['Ips'] = df['Screen'].apply(lambda x:1 if 'IPS' in x else 0)\n",
    "df_test['Ips'] = df_test['Screen'].apply(lambda x:1 if 'IPS' in x else 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Manufacturer</th>\n",
       "      <th>Model Name</th>\n",
       "      <th>Category</th>\n",
       "      <th>Screen Size</th>\n",
       "      <th>Screen</th>\n",
       "      <th>CPU</th>\n",
       "      <th>RAM</th>\n",
       "      <th>Storage</th>\n",
       "      <th>GPU</th>\n",
       "      <th>Operating System</th>\n",
       "      <th>Operating System Version</th>\n",
       "      <th>Weight</th>\n",
       "      <th>Price</th>\n",
       "      <th>Ips</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Apple</td>\n",
       "      <td>MacBook Pro</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>13.3</td>\n",
       "      <td>IPS Panel Retina Display 2560x1600</td>\n",
       "      <td>Intel Core i5 2.3GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>128GB SSD</td>\n",
       "      <td>Intel Iris Plus Graphics 640</td>\n",
       "      <td>macOS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.37</td>\n",
       "      <td>11912523.48</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Apple</td>\n",
       "      <td>Macbook Air</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>13.3</td>\n",
       "      <td>1440x900</td>\n",
       "      <td>Intel Core i5 1.8GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>128GB Flash Storage</td>\n",
       "      <td>Intel HD Graphics 6000</td>\n",
       "      <td>macOS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.34</td>\n",
       "      <td>7993374.48</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>HP</td>\n",
       "      <td>250 G6</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>15.6</td>\n",
       "      <td>Full HD 1920x1080</td>\n",
       "      <td>Intel Core i5 7200U 2.5GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>256GB SSD</td>\n",
       "      <td>Intel HD Graphics 620</td>\n",
       "      <td>No OS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.86</td>\n",
       "      <td>5112900.00</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Apple</td>\n",
       "      <td>MacBook Pro</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>15.4</td>\n",
       "      <td>IPS Panel Retina Display 2880x1800</td>\n",
       "      <td>Intel Core i7 2.7GHz</td>\n",
       "      <td>16</td>\n",
       "      <td>512GB SSD</td>\n",
       "      <td>AMD Radeon Pro 455</td>\n",
       "      <td>macOS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.83</td>\n",
       "      <td>22563005.40</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Apple</td>\n",
       "      <td>MacBook Pro</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>13.3</td>\n",
       "      <td>IPS Panel Retina Display 2560x1600</td>\n",
       "      <td>Intel Core i5 3.1GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>256GB SSD</td>\n",
       "      <td>Intel Iris Plus Graphics 650</td>\n",
       "      <td>macOS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.37</td>\n",
       "      <td>16037611.20</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Manufacturer   Model Name   Category  Screen Size  \\\n",
       "0        Apple  MacBook Pro  Ultrabook         13.3   \n",
       "1        Apple  Macbook Air  Ultrabook         13.3   \n",
       "2           HP       250 G6   Notebook         15.6   \n",
       "3        Apple  MacBook Pro  Ultrabook         15.4   \n",
       "4        Apple  MacBook Pro  Ultrabook         13.3   \n",
       "\n",
       "                               Screen                         CPU  RAM  \\\n",
       "0  IPS Panel Retina Display 2560x1600        Intel Core i5 2.3GHz    8   \n",
       "1                            1440x900        Intel Core i5 1.8GHz    8   \n",
       "2                   Full HD 1920x1080  Intel Core i5 7200U 2.5GHz    8   \n",
       "3  IPS Panel Retina Display 2880x1800        Intel Core i7 2.7GHz   16   \n",
       "4  IPS Panel Retina Display 2560x1600        Intel Core i5 3.1GHz    8   \n",
       "\n",
       "               Storage                           GPU Operating System  \\\n",
       "0            128GB SSD  Intel Iris Plus Graphics 640            macOS   \n",
       "1  128GB Flash Storage        Intel HD Graphics 6000            macOS   \n",
       "2            256GB SSD         Intel HD Graphics 620            No OS   \n",
       "3            512GB SSD            AMD Radeon Pro 455            macOS   \n",
       "4            256GB SSD  Intel Iris Plus Graphics 650            macOS   \n",
       "\n",
       "  Operating System Version  Weight        Price  Ips  \n",
       "0                       10    1.37  11912523.48    1  \n",
       "1                       10    1.34   7993374.48    0  \n",
       "2                       10    1.86   5112900.00    0  \n",
       "3                       10    1.83  22563005.40    1  \n",
       "4                       10    1.37  16037611.20    1  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "        vertical-align: top;\n",
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       "\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>Manufacturer</th>\n",
       "      <th>Model Name</th>\n",
       "      <th>Category</th>\n",
       "      <th>Screen Size</th>\n",
       "      <th>Screen</th>\n",
       "      <th>CPU</th>\n",
       "      <th>RAM</th>\n",
       "      <th>Storage</th>\n",
       "      <th>GPU</th>\n",
       "      <th>Operating System</th>\n",
       "      <th>Operating System Version</th>\n",
       "      <th>Weight</th>\n",
       "      <th>Price</th>\n",
       "      <th>Ips</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>HP</td>\n",
       "      <td>15-bs053od (i7-7500U/6GB/1TB/W10)</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>15.6</td>\n",
       "      <td>1366x768</td>\n",
       "      <td>Intel Core i7 7500U 2.7GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>1TB HDD</td>\n",
       "      <td>Intel HD Graphics 620</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>2.04</td>\n",
       "      <td>5148468.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Asus</td>\n",
       "      <td>Rog GL753VE-DS74</td>\n",
       "      <td>Gaming</td>\n",
       "      <td>17.3</td>\n",
       "      <td>Full HD 1920x1080</td>\n",
       "      <td>Intel Core i7 7700HQ 2.8GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>256GB SSD +  1TB HDD</td>\n",
       "      <td>Nvidia GeForce GTX 1050 Ti</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>2.99</td>\n",
       "      <td>15552108.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Dell</td>\n",
       "      <td>Inspiron 7579</td>\n",
       "      <td>2 in 1 Convertible</td>\n",
       "      <td>15.6</td>\n",
       "      <td>IPS Panel Full HD / Touchscreen 1920x1080</td>\n",
       "      <td>Intel Core i7 7500U 2.7GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>512GB SSD</td>\n",
       "      <td>Intel HD Graphics 620</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>2.19</td>\n",
       "      <td>11550708.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Toshiba</td>\n",
       "      <td>Portege Z30-C-1CV</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>13.3</td>\n",
       "      <td>Full HD 1920x1080</td>\n",
       "      <td>Intel Core i5 6200U 2.3GHz</td>\n",
       "      <td>16</td>\n",
       "      <td>128GB SSD</td>\n",
       "      <td>Intel HD Graphics 520</td>\n",
       "      <td>Windows</td>\n",
       "      <td>7</td>\n",
       "      <td>1.20</td>\n",
       "      <td>10625940.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Lenovo</td>\n",
       "      <td>IdeaPad 320-15ABR</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>15.6</td>\n",
       "      <td>Full HD 1920x1080</td>\n",
       "      <td>AMD A12-Series 9720P 3.6GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>256GB SSD</td>\n",
       "      <td>AMD Radeon 530</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>2.20</td>\n",
       "      <td>4881708.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Manufacturer                         Model Name            Category  \\\n",
       "0           HP  15-bs053od (i7-7500U/6GB/1TB/W10)            Notebook   \n",
       "1         Asus                   Rog GL753VE-DS74              Gaming   \n",
       "2         Dell                      Inspiron 7579  2 in 1 Convertible   \n",
       "3      Toshiba                  Portege Z30-C-1CV            Notebook   \n",
       "4       Lenovo                  IdeaPad 320-15ABR            Notebook   \n",
       "\n",
       "   Screen Size                                     Screen  \\\n",
       "0         15.6                                   1366x768   \n",
       "1         17.3                          Full HD 1920x1080   \n",
       "2         15.6  IPS Panel Full HD / Touchscreen 1920x1080   \n",
       "3         13.3                          Full HD 1920x1080   \n",
       "4         15.6                          Full HD 1920x1080   \n",
       "\n",
       "                           CPU  RAM               Storage  \\\n",
       "0   Intel Core i7 7500U 2.7GHz    8               1TB HDD   \n",
       "1  Intel Core i7 7700HQ 2.8GHz    8  256GB SSD +  1TB HDD   \n",
       "2   Intel Core i7 7500U 2.7GHz    8             512GB SSD   \n",
       "3   Intel Core i5 6200U 2.3GHz   16             128GB SSD   \n",
       "4  AMD A12-Series 9720P 3.6GHz    8             256GB SSD   \n",
       "\n",
       "                          GPU Operating System Operating System Version  \\\n",
       "0       Intel HD Graphics 620          Windows                       10   \n",
       "1  Nvidia GeForce GTX 1050 Ti          Windows                       10   \n",
       "2       Intel HD Graphics 620          Windows                       10   \n",
       "3       Intel HD Graphics 520          Windows                        7   \n",
       "4              AMD Radeon 530          Windows                       10   \n",
       "\n",
       "   Weight       Price  Ips  \n",
       "0    2.04   5148468.0    0  \n",
       "1    2.99  15552108.0    0  \n",
       "2    2.19  11550708.0    1  \n",
       "3    1.20  10625940.0    0  \n",
       "4    2.20   4881708.0    0  "
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_test.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "new = df['Screen'].str.split('x',n=1,expand=True)\n",
    "new_test = df_test['Screen'].str.split('x',n=1,expand=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Manufacturer</th>\n",
       "      <th>Model Name</th>\n",
       "      <th>Category</th>\n",
       "      <th>Screen Size</th>\n",
       "      <th>Screen</th>\n",
       "      <th>CPU</th>\n",
       "      <th>RAM</th>\n",
       "      <th>Storage</th>\n",
       "      <th>GPU</th>\n",
       "      <th>Operating System</th>\n",
       "      <th>Operating System Version</th>\n",
       "      <th>Weight</th>\n",
       "      <th>Price</th>\n",
       "      <th>Ips</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Apple</td>\n",
       "      <td>MacBook Pro</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>13.3</td>\n",
       "      <td>IPS Panel Retina Display 2560x1600</td>\n",
       "      <td>Intel Core i5 2.3GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>128GB SSD</td>\n",
       "      <td>Intel Iris Plus Graphics 640</td>\n",
       "      <td>macOS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.37</td>\n",
       "      <td>11912523.48</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Apple</td>\n",
       "      <td>Macbook Air</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>13.3</td>\n",
       "      <td>1440x900</td>\n",
       "      <td>Intel Core i5 1.8GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>128GB Flash Storage</td>\n",
       "      <td>Intel HD Graphics 6000</td>\n",
       "      <td>macOS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.34</td>\n",
       "      <td>7993374.48</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>HP</td>\n",
       "      <td>250 G6</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>15.6</td>\n",
       "      <td>Full HD 1920x1080</td>\n",
       "      <td>Intel Core i5 7200U 2.5GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>256GB SSD</td>\n",
       "      <td>Intel HD Graphics 620</td>\n",
       "      <td>No OS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.86</td>\n",
       "      <td>5112900.00</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Apple</td>\n",
       "      <td>MacBook Pro</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>15.4</td>\n",
       "      <td>IPS Panel Retina Display 2880x1800</td>\n",
       "      <td>Intel Core i7 2.7GHz</td>\n",
       "      <td>16</td>\n",
       "      <td>512GB SSD</td>\n",
       "      <td>AMD Radeon Pro 455</td>\n",
       "      <td>macOS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.83</td>\n",
       "      <td>22563005.40</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Apple</td>\n",
       "      <td>MacBook Pro</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>13.3</td>\n",
       "      <td>IPS Panel Retina Display 2560x1600</td>\n",
       "      <td>Intel Core i5 3.1GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>256GB SSD</td>\n",
       "      <td>Intel Iris Plus Graphics 650</td>\n",
       "      <td>macOS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.37</td>\n",
       "      <td>16037611.20</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Manufacturer   Model Name   Category  Screen Size  \\\n",
       "0        Apple  MacBook Pro  Ultrabook         13.3   \n",
       "1        Apple  Macbook Air  Ultrabook         13.3   \n",
       "2           HP       250 G6   Notebook         15.6   \n",
       "3        Apple  MacBook Pro  Ultrabook         15.4   \n",
       "4        Apple  MacBook Pro  Ultrabook         13.3   \n",
       "\n",
       "                               Screen                         CPU  RAM  \\\n",
       "0  IPS Panel Retina Display 2560x1600        Intel Core i5 2.3GHz    8   \n",
       "1                            1440x900        Intel Core i5 1.8GHz    8   \n",
       "2                   Full HD 1920x1080  Intel Core i5 7200U 2.5GHz    8   \n",
       "3  IPS Panel Retina Display 2880x1800        Intel Core i7 2.7GHz   16   \n",
       "4  IPS Panel Retina Display 2560x1600        Intel Core i5 3.1GHz    8   \n",
       "\n",
       "               Storage                           GPU Operating System  \\\n",
       "0            128GB SSD  Intel Iris Plus Graphics 640            macOS   \n",
       "1  128GB Flash Storage        Intel HD Graphics 6000            macOS   \n",
       "2            256GB SSD         Intel HD Graphics 620            No OS   \n",
       "3            512GB SSD            AMD Radeon Pro 455            macOS   \n",
       "4            256GB SSD  Intel Iris Plus Graphics 650            macOS   \n",
       "\n",
       "  Operating System Version  Weight        Price  Ips  \n",
       "0                       10    1.37  11912523.48    1  \n",
       "1                       10    1.34   7993374.48    0  \n",
       "2                       10    1.86   5112900.00    0  \n",
       "3                       10    1.83  22563005.40    1  \n",
       "4                       10    1.37  16037611.20    1  "
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['X_res'] = new[0]\n",
    "df['Y_res'] = new[1]\n",
    "\n",
    "df_test['X_res'] = new_test[0]\n",
    "df_test['Y_res'] = new_test[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th>Screen</th>\n",
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       "      <th>Price</th>\n",
       "      <th>Ips</th>\n",
       "      <th>X_res</th>\n",
       "      <th>Y_res</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Apple</td>\n",
       "      <td>MacBook Pro</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>13.3</td>\n",
       "      <td>IPS Panel Retina Display 2560x1600</td>\n",
       "      <td>Intel Core i5 2.3GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>128GB SSD</td>\n",
       "      <td>Intel Iris Plus Graphics 640</td>\n",
       "      <td>macOS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.37</td>\n",
       "      <td>11912523.48</td>\n",
       "      <td>1</td>\n",
       "      <td>IPS Panel Retina Display 2560</td>\n",
       "      <td>1600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Apple</td>\n",
       "      <td>Macbook Air</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>13.3</td>\n",
       "      <td>1440x900</td>\n",
       "      <td>Intel Core i5 1.8GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>128GB Flash Storage</td>\n",
       "      <td>Intel HD Graphics 6000</td>\n",
       "      <td>macOS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.34</td>\n",
       "      <td>7993374.48</td>\n",
       "      <td>0</td>\n",
       "      <td>1440</td>\n",
       "      <td>900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>HP</td>\n",
       "      <td>250 G6</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>15.6</td>\n",
       "      <td>Full HD 1920x1080</td>\n",
       "      <td>Intel Core i5 7200U 2.5GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>256GB SSD</td>\n",
       "      <td>Intel HD Graphics 620</td>\n",
       "      <td>No OS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.86</td>\n",
       "      <td>5112900.00</td>\n",
       "      <td>0</td>\n",
       "      <td>Full HD 1920</td>\n",
       "      <td>1080</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Apple</td>\n",
       "      <td>MacBook Pro</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>15.4</td>\n",
       "      <td>IPS Panel Retina Display 2880x1800</td>\n",
       "      <td>Intel Core i7 2.7GHz</td>\n",
       "      <td>16</td>\n",
       "      <td>512GB SSD</td>\n",
       "      <td>AMD Radeon Pro 455</td>\n",
       "      <td>macOS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.83</td>\n",
       "      <td>22563005.40</td>\n",
       "      <td>1</td>\n",
       "      <td>IPS Panel Retina Display 2880</td>\n",
       "      <td>1800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Apple</td>\n",
       "      <td>MacBook Pro</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>13.3</td>\n",
       "      <td>IPS Panel Retina Display 2560x1600</td>\n",
       "      <td>Intel Core i5 3.1GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>256GB SSD</td>\n",
       "      <td>Intel Iris Plus Graphics 650</td>\n",
       "      <td>macOS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.37</td>\n",
       "      <td>16037611.20</td>\n",
       "      <td>1</td>\n",
       "      <td>IPS Panel Retina Display 2560</td>\n",
       "      <td>1600</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Manufacturer   Model Name   Category  Screen Size  \\\n",
       "0        Apple  MacBook Pro  Ultrabook         13.3   \n",
       "1        Apple  Macbook Air  Ultrabook         13.3   \n",
       "2           HP       250 G6   Notebook         15.6   \n",
       "3        Apple  MacBook Pro  Ultrabook         15.4   \n",
       "4        Apple  MacBook Pro  Ultrabook         13.3   \n",
       "\n",
       "                               Screen                         CPU  RAM  \\\n",
       "0  IPS Panel Retina Display 2560x1600        Intel Core i5 2.3GHz    8   \n",
       "1                            1440x900        Intel Core i5 1.8GHz    8   \n",
       "2                   Full HD 1920x1080  Intel Core i5 7200U 2.5GHz    8   \n",
       "3  IPS Panel Retina Display 2880x1800        Intel Core i7 2.7GHz   16   \n",
       "4  IPS Panel Retina Display 2560x1600        Intel Core i5 3.1GHz    8   \n",
       "\n",
       "               Storage                           GPU Operating System  \\\n",
       "0            128GB SSD  Intel Iris Plus Graphics 640            macOS   \n",
       "1  128GB Flash Storage        Intel HD Graphics 6000            macOS   \n",
       "2            256GB SSD         Intel HD Graphics 620            No OS   \n",
       "3            512GB SSD            AMD Radeon Pro 455            macOS   \n",
       "4            256GB SSD  Intel Iris Plus Graphics 650            macOS   \n",
       "\n",
       "  Operating System Version  Weight        Price  Ips  \\\n",
       "0                       10    1.37  11912523.48    1   \n",
       "1                       10    1.34   7993374.48    0   \n",
       "2                       10    1.86   5112900.00    0   \n",
       "3                       10    1.83  22563005.40    1   \n",
       "4                       10    1.37  16037611.20    1   \n",
       "\n",
       "                           X_res Y_res  \n",
       "0  IPS Panel Retina Display 2560  1600  \n",
       "1                           1440   900  \n",
       "2                   Full HD 1920  1080  \n",
       "3  IPS Panel Retina Display 2880  1800  \n",
       "4  IPS Panel Retina Display 2560  1600  "
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Manufacturer</th>\n",
       "      <th>Model Name</th>\n",
       "      <th>Category</th>\n",
       "      <th>Screen Size</th>\n",
       "      <th>Screen</th>\n",
       "      <th>CPU</th>\n",
       "      <th>RAM</th>\n",
       "      <th>Storage</th>\n",
       "      <th>GPU</th>\n",
       "      <th>Operating System</th>\n",
       "      <th>Operating System Version</th>\n",
       "      <th>Weight</th>\n",
       "      <th>Price</th>\n",
       "      <th>Ips</th>\n",
       "      <th>X_res</th>\n",
       "      <th>Y_res</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>HP</td>\n",
       "      <td>15-bs053od (i7-7500U/6GB/1TB/W10)</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>15.6</td>\n",
       "      <td>1366x768</td>\n",
       "      <td>Intel Core i7 7500U 2.7GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>1TB HDD</td>\n",
       "      <td>Intel HD Graphics 620</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>2.04</td>\n",
       "      <td>5148468.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1366</td>\n",
       "      <td>768</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Asus</td>\n",
       "      <td>Rog GL753VE-DS74</td>\n",
       "      <td>Gaming</td>\n",
       "      <td>17.3</td>\n",
       "      <td>Full HD 1920x1080</td>\n",
       "      <td>Intel Core i7 7700HQ 2.8GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>256GB SSD +  1TB HDD</td>\n",
       "      <td>Nvidia GeForce GTX 1050 Ti</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>2.99</td>\n",
       "      <td>15552108.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Full HD 1920</td>\n",
       "      <td>1080</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Dell</td>\n",
       "      <td>Inspiron 7579</td>\n",
       "      <td>2 in 1 Convertible</td>\n",
       "      <td>15.6</td>\n",
       "      <td>IPS Panel Full HD / Touchscreen 1920x1080</td>\n",
       "      <td>Intel Core i7 7500U 2.7GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>512GB SSD</td>\n",
       "      <td>Intel HD Graphics 620</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>2.19</td>\n",
       "      <td>11550708.0</td>\n",
       "      <td>1</td>\n",
       "      <td>IPS Panel Full HD / Touchscreen 1920</td>\n",
       "      <td>1080</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Toshiba</td>\n",
       "      <td>Portege Z30-C-1CV</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>13.3</td>\n",
       "      <td>Full HD 1920x1080</td>\n",
       "      <td>Intel Core i5 6200U 2.3GHz</td>\n",
       "      <td>16</td>\n",
       "      <td>128GB SSD</td>\n",
       "      <td>Intel HD Graphics 520</td>\n",
       "      <td>Windows</td>\n",
       "      <td>7</td>\n",
       "      <td>1.20</td>\n",
       "      <td>10625940.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Full HD 1920</td>\n",
       "      <td>1080</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Lenovo</td>\n",
       "      <td>IdeaPad 320-15ABR</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>15.6</td>\n",
       "      <td>Full HD 1920x1080</td>\n",
       "      <td>AMD A12-Series 9720P 3.6GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>256GB SSD</td>\n",
       "      <td>AMD Radeon 530</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>2.20</td>\n",
       "      <td>4881708.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Full HD 1920</td>\n",
       "      <td>1080</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Manufacturer                         Model Name            Category  \\\n",
       "0           HP  15-bs053od (i7-7500U/6GB/1TB/W10)            Notebook   \n",
       "1         Asus                   Rog GL753VE-DS74              Gaming   \n",
       "2         Dell                      Inspiron 7579  2 in 1 Convertible   \n",
       "3      Toshiba                  Portege Z30-C-1CV            Notebook   \n",
       "4       Lenovo                  IdeaPad 320-15ABR            Notebook   \n",
       "\n",
       "   Screen Size                                     Screen  \\\n",
       "0         15.6                                   1366x768   \n",
       "1         17.3                          Full HD 1920x1080   \n",
       "2         15.6  IPS Panel Full HD / Touchscreen 1920x1080   \n",
       "3         13.3                          Full HD 1920x1080   \n",
       "4         15.6                          Full HD 1920x1080   \n",
       "\n",
       "                           CPU  RAM               Storage  \\\n",
       "0   Intel Core i7 7500U 2.7GHz    8               1TB HDD   \n",
       "1  Intel Core i7 7700HQ 2.8GHz    8  256GB SSD +  1TB HDD   \n",
       "2   Intel Core i7 7500U 2.7GHz    8             512GB SSD   \n",
       "3   Intel Core i5 6200U 2.3GHz   16             128GB SSD   \n",
       "4  AMD A12-Series 9720P 3.6GHz    8             256GB SSD   \n",
       "\n",
       "                          GPU Operating System Operating System Version  \\\n",
       "0       Intel HD Graphics 620          Windows                       10   \n",
       "1  Nvidia GeForce GTX 1050 Ti          Windows                       10   \n",
       "2       Intel HD Graphics 620          Windows                       10   \n",
       "3       Intel HD Graphics 520          Windows                        7   \n",
       "4              AMD Radeon 530          Windows                       10   \n",
       "\n",
       "   Weight       Price  Ips                                 X_res Y_res  \n",
       "0    2.04   5148468.0    0                                  1366   768  \n",
       "1    2.99  15552108.0    0                          Full HD 1920  1080  \n",
       "2    2.19  11550708.0    1  IPS Panel Full HD / Touchscreen 1920  1080  \n",
       "3    1.20  10625940.0    0                          Full HD 1920  1080  \n",
       "4    2.20   4881708.0    0                          Full HD 1920  1080  "
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_test.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Cleaning the X component of the resolution\n",
    "df['X_res'] = df['X_res'].str.replace(',','').str.findall(r'(\\d+\\.?\\d+)').apply(lambda x:x[0])\n",
    "df_test['X_res'] = df_test['X_res'].str.replace(',','').str.findall(r'(\\d+\\.?\\d+)').apply(lambda x:x[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Manufacturer</th>\n",
       "      <th>Model Name</th>\n",
       "      <th>Category</th>\n",
       "      <th>Screen Size</th>\n",
       "      <th>Screen</th>\n",
       "      <th>CPU</th>\n",
       "      <th>RAM</th>\n",
       "      <th>Storage</th>\n",
       "      <th>GPU</th>\n",
       "      <th>Operating System</th>\n",
       "      <th>Operating System Version</th>\n",
       "      <th>Weight</th>\n",
       "      <th>Price</th>\n",
       "      <th>Ips</th>\n",
       "      <th>X_res</th>\n",
       "      <th>Y_res</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Apple</td>\n",
       "      <td>MacBook Pro</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>13.3</td>\n",
       "      <td>IPS Panel Retina Display 2560x1600</td>\n",
       "      <td>Intel Core i5 2.3GHz</td>\n",
       "      <td>8</td>\n",
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       "      <td>2560</td>\n",
       "      <td>1600</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Apple</td>\n",
       "      <td>Macbook Air</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>13.3</td>\n",
       "      <td>1440x900</td>\n",
       "      <td>Intel Core i5 1.8GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>128GB Flash Storage</td>\n",
       "      <td>Intel HD Graphics 6000</td>\n",
       "      <td>macOS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.34</td>\n",
       "      <td>7993374.48</td>\n",
       "      <td>0</td>\n",
       "      <td>1440</td>\n",
       "      <td>900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>HP</td>\n",
       "      <td>250 G6</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>15.6</td>\n",
       "      <td>Full HD 1920x1080</td>\n",
       "      <td>Intel Core i5 7200U 2.5GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>256GB SSD</td>\n",
       "      <td>Intel HD Graphics 620</td>\n",
       "      <td>No OS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.86</td>\n",
       "      <td>5112900.00</td>\n",
       "      <td>0</td>\n",
       "      <td>1920</td>\n",
       "      <td>1080</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Apple</td>\n",
       "      <td>MacBook Pro</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>15.4</td>\n",
       "      <td>IPS Panel Retina Display 2880x1800</td>\n",
       "      <td>Intel Core i7 2.7GHz</td>\n",
       "      <td>16</td>\n",
       "      <td>512GB SSD</td>\n",
       "      <td>AMD Radeon Pro 455</td>\n",
       "      <td>macOS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.83</td>\n",
       "      <td>22563005.40</td>\n",
       "      <td>1</td>\n",
       "      <td>2880</td>\n",
       "      <td>1800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Apple</td>\n",
       "      <td>MacBook Pro</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>13.3</td>\n",
       "      <td>IPS Panel Retina Display 2560x1600</td>\n",
       "      <td>Intel Core i5 3.1GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>256GB SSD</td>\n",
       "      <td>Intel Iris Plus Graphics 650</td>\n",
       "      <td>macOS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.37</td>\n",
       "      <td>16037611.20</td>\n",
       "      <td>1</td>\n",
       "      <td>2560</td>\n",
       "      <td>1600</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Manufacturer   Model Name   Category  Screen Size  \\\n",
       "0        Apple  MacBook Pro  Ultrabook         13.3   \n",
       "1        Apple  Macbook Air  Ultrabook         13.3   \n",
       "2           HP       250 G6   Notebook         15.6   \n",
       "3        Apple  MacBook Pro  Ultrabook         15.4   \n",
       "4        Apple  MacBook Pro  Ultrabook         13.3   \n",
       "\n",
       "                               Screen                         CPU  RAM  \\\n",
       "0  IPS Panel Retina Display 2560x1600        Intel Core i5 2.3GHz    8   \n",
       "1                            1440x900        Intel Core i5 1.8GHz    8   \n",
       "2                   Full HD 1920x1080  Intel Core i5 7200U 2.5GHz    8   \n",
       "3  IPS Panel Retina Display 2880x1800        Intel Core i7 2.7GHz   16   \n",
       "4  IPS Panel Retina Display 2560x1600        Intel Core i5 3.1GHz    8   \n",
       "\n",
       "               Storage                           GPU Operating System  \\\n",
       "0            128GB SSD  Intel Iris Plus Graphics 640            macOS   \n",
       "1  128GB Flash Storage        Intel HD Graphics 6000            macOS   \n",
       "2            256GB SSD         Intel HD Graphics 620            No OS   \n",
       "3            512GB SSD            AMD Radeon Pro 455            macOS   \n",
       "4            256GB SSD  Intel Iris Plus Graphics 650            macOS   \n",
       "\n",
       "  Operating System Version  Weight        Price  Ips X_res Y_res  \n",
       "0                       10    1.37  11912523.48    1  2560  1600  \n",
       "1                       10    1.34   7993374.48    0  1440   900  \n",
       "2                       10    1.86   5112900.00    0  1920  1080  \n",
       "3                       10    1.83  22563005.40    1  2880  1800  \n",
       "4                       10    1.37  16037611.20    1  2560  1600  "
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Manufacturer</th>\n",
       "      <th>Model Name</th>\n",
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       "      <th>Screen Size</th>\n",
       "      <th>Screen</th>\n",
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       "      <th>Operating System Version</th>\n",
       "      <th>Weight</th>\n",
       "      <th>Price</th>\n",
       "      <th>Ips</th>\n",
       "      <th>X_res</th>\n",
       "      <th>Y_res</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>HP</td>\n",
       "      <td>15-bs053od (i7-7500U/6GB/1TB/W10)</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>15.6</td>\n",
       "      <td>1366x768</td>\n",
       "      <td>Intel Core i7 7500U 2.7GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>1TB HDD</td>\n",
       "      <td>Intel HD Graphics 620</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>2.04</td>\n",
       "      <td>5148468.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1366</td>\n",
       "      <td>768</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Asus</td>\n",
       "      <td>Rog GL753VE-DS74</td>\n",
       "      <td>Gaming</td>\n",
       "      <td>17.3</td>\n",
       "      <td>Full HD 1920x1080</td>\n",
       "      <td>Intel Core i7 7700HQ 2.8GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>256GB SSD +  1TB HDD</td>\n",
       "      <td>Nvidia GeForce GTX 1050 Ti</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>2.99</td>\n",
       "      <td>15552108.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1920</td>\n",
       "      <td>1080</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Dell</td>\n",
       "      <td>Inspiron 7579</td>\n",
       "      <td>2 in 1 Convertible</td>\n",
       "      <td>15.6</td>\n",
       "      <td>IPS Panel Full HD / Touchscreen 1920x1080</td>\n",
       "      <td>Intel Core i7 7500U 2.7GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>512GB SSD</td>\n",
       "      <td>Intel HD Graphics 620</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>2.19</td>\n",
       "      <td>11550708.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1920</td>\n",
       "      <td>1080</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Toshiba</td>\n",
       "      <td>Portege Z30-C-1CV</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>13.3</td>\n",
       "      <td>Full HD 1920x1080</td>\n",
       "      <td>Intel Core i5 6200U 2.3GHz</td>\n",
       "      <td>16</td>\n",
       "      <td>128GB SSD</td>\n",
       "      <td>Intel HD Graphics 520</td>\n",
       "      <td>Windows</td>\n",
       "      <td>7</td>\n",
       "      <td>1.20</td>\n",
       "      <td>10625940.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1920</td>\n",
       "      <td>1080</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Lenovo</td>\n",
       "      <td>IdeaPad 320-15ABR</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>15.6</td>\n",
       "      <td>Full HD 1920x1080</td>\n",
       "      <td>AMD A12-Series 9720P 3.6GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>256GB SSD</td>\n",
       "      <td>AMD Radeon 530</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>2.20</td>\n",
       "      <td>4881708.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1920</td>\n",
       "      <td>1080</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Manufacturer                         Model Name            Category  \\\n",
       "0           HP  15-bs053od (i7-7500U/6GB/1TB/W10)            Notebook   \n",
       "1         Asus                   Rog GL753VE-DS74              Gaming   \n",
       "2         Dell                      Inspiron 7579  2 in 1 Convertible   \n",
       "3      Toshiba                  Portege Z30-C-1CV            Notebook   \n",
       "4       Lenovo                  IdeaPad 320-15ABR            Notebook   \n",
       "\n",
       "   Screen Size                                     Screen  \\\n",
       "0         15.6                                   1366x768   \n",
       "1         17.3                          Full HD 1920x1080   \n",
       "2         15.6  IPS Panel Full HD / Touchscreen 1920x1080   \n",
       "3         13.3                          Full HD 1920x1080   \n",
       "4         15.6                          Full HD 1920x1080   \n",
       "\n",
       "                           CPU  RAM               Storage  \\\n",
       "0   Intel Core i7 7500U 2.7GHz    8               1TB HDD   \n",
       "1  Intel Core i7 7700HQ 2.8GHz    8  256GB SSD +  1TB HDD   \n",
       "2   Intel Core i7 7500U 2.7GHz    8             512GB SSD   \n",
       "3   Intel Core i5 6200U 2.3GHz   16             128GB SSD   \n",
       "4  AMD A12-Series 9720P 3.6GHz    8             256GB SSD   \n",
       "\n",
       "                          GPU Operating System Operating System Version  \\\n",
       "0       Intel HD Graphics 620          Windows                       10   \n",
       "1  Nvidia GeForce GTX 1050 Ti          Windows                       10   \n",
       "2       Intel HD Graphics 620          Windows                       10   \n",
       "3       Intel HD Graphics 520          Windows                        7   \n",
       "4              AMD Radeon 530          Windows                       10   \n",
       "\n",
       "   Weight       Price  Ips X_res Y_res  \n",
       "0    2.04   5148468.0    0  1366   768  \n",
       "1    2.99  15552108.0    0  1920  1080  \n",
       "2    2.19  11550708.0    1  1920  1080  \n",
       "3    1.20  10625940.0    0  1920  1080  \n",
       "4    2.20   4881708.0    0  1920  1080  "
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_test.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['X_res'] = df['X_res'].astype('int')\n",
    "df['Y_res'] = df['Y_res'].astype('int')\n",
    "\n",
    "df_test['X_res'] = df_test['X_res'].astype('int')\n",
    "df_test['Y_res'] = df_test['Y_res'].astype('int')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>1600</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Apple</td>\n",
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       "      <td>13.3</td>\n",
       "      <td>1440x900</td>\n",
       "      <td>Intel Core i5 1.8GHz</td>\n",
       "      <td>8</td>\n",
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       "      <td>Intel HD Graphics 6000</td>\n",
       "      <td>macOS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.34</td>\n",
       "      <td>7993374.48</td>\n",
       "      <td>0</td>\n",
       "      <td>1440</td>\n",
       "      <td>900</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>HP</td>\n",
       "      <td>250 G6</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>15.6</td>\n",
       "      <td>Full HD 1920x1080</td>\n",
       "      <td>Intel Core i5 7200U 2.5GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>256GB SSD</td>\n",
       "      <td>Intel HD Graphics 620</td>\n",
       "      <td>No OS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.86</td>\n",
       "      <td>5112900.00</td>\n",
       "      <td>0</td>\n",
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       "      <td>1080</td>\n",
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       "      <th>3</th>\n",
       "      <td>Apple</td>\n",
       "      <td>MacBook Pro</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>15.4</td>\n",
       "      <td>IPS Panel Retina Display 2880x1800</td>\n",
       "      <td>Intel Core i7 2.7GHz</td>\n",
       "      <td>16</td>\n",
       "      <td>512GB SSD</td>\n",
       "      <td>AMD Radeon Pro 455</td>\n",
       "      <td>macOS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.83</td>\n",
       "      <td>22563005.40</td>\n",
       "      <td>1</td>\n",
       "      <td>2880</td>\n",
       "      <td>1800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Apple</td>\n",
       "      <td>MacBook Pro</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>13.3</td>\n",
       "      <td>IPS Panel Retina Display 2560x1600</td>\n",
       "      <td>Intel Core i5 3.1GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>256GB SSD</td>\n",
       "      <td>Intel Iris Plus Graphics 650</td>\n",
       "      <td>macOS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.37</td>\n",
       "      <td>16037611.20</td>\n",
       "      <td>1</td>\n",
       "      <td>2560</td>\n",
       "      <td>1600</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Manufacturer   Model Name   Category  Screen Size  \\\n",
       "0        Apple  MacBook Pro  Ultrabook         13.3   \n",
       "1        Apple  Macbook Air  Ultrabook         13.3   \n",
       "2           HP       250 G6   Notebook         15.6   \n",
       "3        Apple  MacBook Pro  Ultrabook         15.4   \n",
       "4        Apple  MacBook Pro  Ultrabook         13.3   \n",
       "\n",
       "                               Screen                         CPU  RAM  \\\n",
       "0  IPS Panel Retina Display 2560x1600        Intel Core i5 2.3GHz    8   \n",
       "1                            1440x900        Intel Core i5 1.8GHz    8   \n",
       "2                   Full HD 1920x1080  Intel Core i5 7200U 2.5GHz    8   \n",
       "3  IPS Panel Retina Display 2880x1800        Intel Core i7 2.7GHz   16   \n",
       "4  IPS Panel Retina Display 2560x1600        Intel Core i5 3.1GHz    8   \n",
       "\n",
       "               Storage                           GPU Operating System  \\\n",
       "0            128GB SSD  Intel Iris Plus Graphics 640            macOS   \n",
       "1  128GB Flash Storage        Intel HD Graphics 6000            macOS   \n",
       "2            256GB SSD         Intel HD Graphics 620            No OS   \n",
       "3            512GB SSD            AMD Radeon Pro 455            macOS   \n",
       "4            256GB SSD  Intel Iris Plus Graphics 650            macOS   \n",
       "\n",
       "  Operating System Version  Weight        Price  Ips  X_res  Y_res  \n",
       "0                       10    1.37  11912523.48    1   2560   1600  \n",
       "1                       10    1.34   7993374.48    0   1440    900  \n",
       "2                       10    1.86   5112900.00    0   1920   1080  \n",
       "3                       10    1.83  22563005.40    1   2880   1800  \n",
       "4                       10    1.37  16037611.20    1   2560   1600  "
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>Asus</td>\n",
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       "      <td>10</td>\n",
       "      <td>2.99</td>\n",
       "      <td>15552108.0</td>\n",
       "      <td>0</td>\n",
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       "      <td>1080</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Dell</td>\n",
       "      <td>Inspiron 7579</td>\n",
       "      <td>2 in 1 Convertible</td>\n",
       "      <td>15.6</td>\n",
       "      <td>IPS Panel Full HD / Touchscreen 1920x1080</td>\n",
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       "      <td>2.19</td>\n",
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       "      <td>Toshiba</td>\n",
       "      <td>Portege Z30-C-1CV</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>13.3</td>\n",
       "      <td>Full HD 1920x1080</td>\n",
       "      <td>Intel Core i5 6200U 2.3GHz</td>\n",
       "      <td>16</td>\n",
       "      <td>128GB SSD</td>\n",
       "      <td>Intel HD Graphics 520</td>\n",
       "      <td>Windows</td>\n",
       "      <td>7</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Lenovo</td>\n",
       "      <td>IdeaPad 320-15ABR</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>15.6</td>\n",
       "      <td>Full HD 1920x1080</td>\n",
       "      <td>AMD A12-Series 9720P 3.6GHz</td>\n",
       "      <td>8</td>\n",
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       "</div>"
      ],
      "text/plain": [
       "  Manufacturer                         Model Name            Category  \\\n",
       "0           HP  15-bs053od (i7-7500U/6GB/1TB/W10)            Notebook   \n",
       "1         Asus                   Rog GL753VE-DS74              Gaming   \n",
       "2         Dell                      Inspiron 7579  2 in 1 Convertible   \n",
       "3      Toshiba                  Portege Z30-C-1CV            Notebook   \n",
       "4       Lenovo                  IdeaPad 320-15ABR            Notebook   \n",
       "\n",
       "   Screen Size                                     Screen  \\\n",
       "0         15.6                                   1366x768   \n",
       "1         17.3                          Full HD 1920x1080   \n",
       "2         15.6  IPS Panel Full HD / Touchscreen 1920x1080   \n",
       "3         13.3                          Full HD 1920x1080   \n",
       "4         15.6                          Full HD 1920x1080   \n",
       "\n",
       "                           CPU  RAM               Storage  \\\n",
       "0   Intel Core i7 7500U 2.7GHz    8               1TB HDD   \n",
       "1  Intel Core i7 7700HQ 2.8GHz    8  256GB SSD +  1TB HDD   \n",
       "2   Intel Core i7 7500U 2.7GHz    8             512GB SSD   \n",
       "3   Intel Core i5 6200U 2.3GHz   16             128GB SSD   \n",
       "4  AMD A12-Series 9720P 3.6GHz    8             256GB SSD   \n",
       "\n",
       "                          GPU Operating System Operating System Version  \\\n",
       "0       Intel HD Graphics 620          Windows                       10   \n",
       "1  Nvidia GeForce GTX 1050 Ti          Windows                       10   \n",
       "2       Intel HD Graphics 620          Windows                       10   \n",
       "3       Intel HD Graphics 520          Windows                        7   \n",
       "4              AMD Radeon 530          Windows                       10   \n",
       "\n",
       "   Weight       Price  Ips  X_res  Y_res  \n",
       "0    2.04   5148468.0    0   1366    768  \n",
       "1    2.99  15552108.0    0   1920   1080  \n",
       "2    2.19  11550708.0    1   1920   1080  \n",
       "3    1.20  10625940.0    0   1920   1080  \n",
       "4    2.20   4881708.0    0   1920   1080  "
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_test.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 977 entries, 0 to 976\n",
      "Data columns (total 16 columns):\n",
      " #   Column                    Non-Null Count  Dtype  \n",
      "---  ------                    --------------  -----  \n",
      " 0   Manufacturer              977 non-null    object \n",
      " 1   Model Name                977 non-null    object \n",
      " 2   Category                  977 non-null    object \n",
      " 3   Screen Size               977 non-null    float64\n",
      " 4   Screen                    977 non-null    object \n",
      " 5   CPU                       977 non-null    object \n",
      " 6   RAM                       977 non-null    int32  \n",
      " 7    Storage                  977 non-null    object \n",
      " 8   GPU                       977 non-null    object \n",
      " 9   Operating System          977 non-null    object \n",
      " 10  Operating System Version  977 non-null    object \n",
      " 11  Weight                    977 non-null    float64\n",
      " 12  Price                     977 non-null    float64\n",
      " 13  Ips                       977 non-null    int64  \n",
      " 14  X_res                     977 non-null    int32  \n",
      " 15  Y_res                     977 non-null    int32  \n",
      "dtypes: float64(3), int32(3), int64(1), object(9)\n",
      "memory usage: 110.8+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 325 entries, 0 to 324\n",
      "Data columns (total 16 columns):\n",
      " #   Column                    Non-Null Count  Dtype  \n",
      "---  ------                    --------------  -----  \n",
      " 0   Manufacturer              325 non-null    object \n",
      " 1   Model Name                325 non-null    object \n",
      " 2   Category                  325 non-null    object \n",
      " 3   Screen Size               325 non-null    float64\n",
      " 4   Screen                    325 non-null    object \n",
      " 5   CPU                       325 non-null    object \n",
      " 6   RAM                       325 non-null    int32  \n",
      " 7    Storage                  325 non-null    object \n",
      " 8   GPU                       325 non-null    object \n",
      " 9   Operating System          325 non-null    object \n",
      " 10  Operating System Version  325 non-null    object \n",
      " 11  Weight                    325 non-null    float64\n",
      " 12  Price                     325 non-null    float64\n",
      " 13  Ips                       325 non-null    int64  \n",
      " 14  X_res                     325 non-null    int32  \n",
      " 15  Y_res                     325 non-null    int32  \n",
      "dtypes: float64(3), int32(3), int64(1), object(9)\n",
      "memory usage: 36.9+ KB\n"
     ]
    }
   ],
   "source": [
    "df_test.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Screen Size    0.075152\n",
       "RAM            0.764005\n",
       "Weight         0.224415\n",
       "Price          1.000000\n",
       "Ips            0.234718\n",
       "X_res          0.579901\n",
       "Y_res          0.577594\n",
       "Name: Price, dtype: float64"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.corr(numeric_only=True)['Price']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['ppi'] = (((df['X_res']**2) + (df['Y_res']**2))**0.5/df['Screen Size']).astype('float')\n",
    "df_test['ppi'] = (((df_test['X_res']**2) + (df_test['Y_res']**2))**0.5/df_test['Screen Size']).astype('float')\n",
    "# finding dpi or ppi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Screen Size    0.075152\n",
       "RAM            0.764005\n",
       "Weight         0.224415\n",
       "Price          1.000000\n",
       "Ips            0.234718\n",
       "X_res          0.579901\n",
       "Y_res          0.577594\n",
       "ppi            0.499022\n",
       "Name: Price, dtype: float64"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.corr(numeric_only=True)['Price']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.drop(columns=['Screen'],inplace=True)\n",
    "df_test.drop(columns=['Screen'],inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\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>Manufacturer</th>\n",
       "      <th>Model Name</th>\n",
       "      <th>Category</th>\n",
       "      <th>Screen Size</th>\n",
       "      <th>CPU</th>\n",
       "      <th>RAM</th>\n",
       "      <th>Storage</th>\n",
       "      <th>GPU</th>\n",
       "      <th>Operating System</th>\n",
       "      <th>Operating System Version</th>\n",
       "      <th>Weight</th>\n",
       "      <th>Price</th>\n",
       "      <th>Ips</th>\n",
       "      <th>X_res</th>\n",
       "      <th>Y_res</th>\n",
       "      <th>ppi</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Apple</td>\n",
       "      <td>MacBook Pro</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>13.3</td>\n",
       "      <td>Intel Core i5 2.3GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>128GB SSD</td>\n",
       "      <td>Intel Iris Plus Graphics 640</td>\n",
       "      <td>macOS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.37</td>\n",
       "      <td>11912523.48</td>\n",
       "      <td>1</td>\n",
       "      <td>2560</td>\n",
       "      <td>1600</td>\n",
       "      <td>226.983005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Apple</td>\n",
       "      <td>Macbook Air</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>13.3</td>\n",
       "      <td>Intel Core i5 1.8GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>128GB Flash Storage</td>\n",
       "      <td>Intel HD Graphics 6000</td>\n",
       "      <td>macOS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.34</td>\n",
       "      <td>7993374.48</td>\n",
       "      <td>0</td>\n",
       "      <td>1440</td>\n",
       "      <td>900</td>\n",
       "      <td>127.677940</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>HP</td>\n",
       "      <td>250 G6</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>15.6</td>\n",
       "      <td>Intel Core i5 7200U 2.5GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>256GB SSD</td>\n",
       "      <td>Intel HD Graphics 620</td>\n",
       "      <td>No OS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.86</td>\n",
       "      <td>5112900.00</td>\n",
       "      <td>0</td>\n",
       "      <td>1920</td>\n",
       "      <td>1080</td>\n",
       "      <td>141.211998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Apple</td>\n",
       "      <td>MacBook Pro</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>15.4</td>\n",
       "      <td>Intel Core i7 2.7GHz</td>\n",
       "      <td>16</td>\n",
       "      <td>512GB SSD</td>\n",
       "      <td>AMD Radeon Pro 455</td>\n",
       "      <td>macOS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.83</td>\n",
       "      <td>22563005.40</td>\n",
       "      <td>1</td>\n",
       "      <td>2880</td>\n",
       "      <td>1800</td>\n",
       "      <td>220.534624</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Apple</td>\n",
       "      <td>MacBook Pro</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>13.3</td>\n",
       "      <td>Intel Core i5 3.1GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>256GB SSD</td>\n",
       "      <td>Intel Iris Plus Graphics 650</td>\n",
       "      <td>macOS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.37</td>\n",
       "      <td>16037611.20</td>\n",
       "      <td>1</td>\n",
       "      <td>2560</td>\n",
       "      <td>1600</td>\n",
       "      <td>226.983005</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Manufacturer   Model Name   Category  Screen Size  \\\n",
       "0        Apple  MacBook Pro  Ultrabook         13.3   \n",
       "1        Apple  Macbook Air  Ultrabook         13.3   \n",
       "2           HP       250 G6   Notebook         15.6   \n",
       "3        Apple  MacBook Pro  Ultrabook         15.4   \n",
       "4        Apple  MacBook Pro  Ultrabook         13.3   \n",
       "\n",
       "                          CPU  RAM              Storage  \\\n",
       "0        Intel Core i5 2.3GHz    8            128GB SSD   \n",
       "1        Intel Core i5 1.8GHz    8  128GB Flash Storage   \n",
       "2  Intel Core i5 7200U 2.5GHz    8            256GB SSD   \n",
       "3        Intel Core i7 2.7GHz   16            512GB SSD   \n",
       "4        Intel Core i5 3.1GHz    8            256GB SSD   \n",
       "\n",
       "                            GPU Operating System Operating System Version  \\\n",
       "0  Intel Iris Plus Graphics 640            macOS                       10   \n",
       "1        Intel HD Graphics 6000            macOS                       10   \n",
       "2         Intel HD Graphics 620            No OS                       10   \n",
       "3            AMD Radeon Pro 455            macOS                       10   \n",
       "4  Intel Iris Plus Graphics 650            macOS                       10   \n",
       "\n",
       "   Weight        Price  Ips  X_res  Y_res         ppi  \n",
       "0    1.37  11912523.48    1   2560   1600  226.983005  \n",
       "1    1.34   7993374.48    0   1440    900  127.677940  \n",
       "2    1.86   5112900.00    0   1920   1080  141.211998  \n",
       "3    1.83  22563005.40    1   2880   1800  220.534624  \n",
       "4    1.37  16037611.20    1   2560   1600  226.983005  "
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Manufacturer</th>\n",
       "      <th>Model Name</th>\n",
       "      <th>Category</th>\n",
       "      <th>Screen Size</th>\n",
       "      <th>CPU</th>\n",
       "      <th>RAM</th>\n",
       "      <th>Storage</th>\n",
       "      <th>GPU</th>\n",
       "      <th>Operating System</th>\n",
       "      <th>Operating System Version</th>\n",
       "      <th>Weight</th>\n",
       "      <th>Price</th>\n",
       "      <th>Ips</th>\n",
       "      <th>X_res</th>\n",
       "      <th>Y_res</th>\n",
       "      <th>ppi</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>HP</td>\n",
       "      <td>15-bs053od (i7-7500U/6GB/1TB/W10)</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>15.6</td>\n",
       "      <td>Intel Core i7 7500U 2.7GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>1TB HDD</td>\n",
       "      <td>Intel HD Graphics 620</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>2.04</td>\n",
       "      <td>5148468.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1366</td>\n",
       "      <td>768</td>\n",
       "      <td>100.454670</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Asus</td>\n",
       "      <td>Rog GL753VE-DS74</td>\n",
       "      <td>Gaming</td>\n",
       "      <td>17.3</td>\n",
       "      <td>Intel Core i7 7700HQ 2.8GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>256GB SSD +  1TB HDD</td>\n",
       "      <td>Nvidia GeForce GTX 1050 Ti</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>2.99</td>\n",
       "      <td>15552108.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1920</td>\n",
       "      <td>1080</td>\n",
       "      <td>127.335675</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Dell</td>\n",
       "      <td>Inspiron 7579</td>\n",
       "      <td>2 in 1 Convertible</td>\n",
       "      <td>15.6</td>\n",
       "      <td>Intel Core i7 7500U 2.7GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>512GB SSD</td>\n",
       "      <td>Intel HD Graphics 620</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>2.19</td>\n",
       "      <td>11550708.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1920</td>\n",
       "      <td>1080</td>\n",
       "      <td>141.211998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Toshiba</td>\n",
       "      <td>Portege Z30-C-1CV</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>13.3</td>\n",
       "      <td>Intel Core i5 6200U 2.3GHz</td>\n",
       "      <td>16</td>\n",
       "      <td>128GB SSD</td>\n",
       "      <td>Intel HD Graphics 520</td>\n",
       "      <td>Windows</td>\n",
       "      <td>7</td>\n",
       "      <td>1.20</td>\n",
       "      <td>10625940.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1920</td>\n",
       "      <td>1080</td>\n",
       "      <td>165.632118</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Lenovo</td>\n",
       "      <td>IdeaPad 320-15ABR</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>15.6</td>\n",
       "      <td>AMD A12-Series 9720P 3.6GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>256GB SSD</td>\n",
       "      <td>AMD Radeon 530</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>2.20</td>\n",
       "      <td>4881708.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1920</td>\n",
       "      <td>1080</td>\n",
       "      <td>141.211998</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Manufacturer                         Model Name            Category  \\\n",
       "0           HP  15-bs053od (i7-7500U/6GB/1TB/W10)            Notebook   \n",
       "1         Asus                   Rog GL753VE-DS74              Gaming   \n",
       "2         Dell                      Inspiron 7579  2 in 1 Convertible   \n",
       "3      Toshiba                  Portege Z30-C-1CV            Notebook   \n",
       "4       Lenovo                  IdeaPad 320-15ABR            Notebook   \n",
       "\n",
       "   Screen Size                          CPU  RAM               Storage  \\\n",
       "0         15.6   Intel Core i7 7500U 2.7GHz    8               1TB HDD   \n",
       "1         17.3  Intel Core i7 7700HQ 2.8GHz    8  256GB SSD +  1TB HDD   \n",
       "2         15.6   Intel Core i7 7500U 2.7GHz    8             512GB SSD   \n",
       "3         13.3   Intel Core i5 6200U 2.3GHz   16             128GB SSD   \n",
       "4         15.6  AMD A12-Series 9720P 3.6GHz    8             256GB SSD   \n",
       "\n",
       "                          GPU Operating System Operating System Version  \\\n",
       "0       Intel HD Graphics 620          Windows                       10   \n",
       "1  Nvidia GeForce GTX 1050 Ti          Windows                       10   \n",
       "2       Intel HD Graphics 620          Windows                       10   \n",
       "3       Intel HD Graphics 520          Windows                        7   \n",
       "4              AMD Radeon 530          Windows                       10   \n",
       "\n",
       "   Weight       Price  Ips  X_res  Y_res         ppi  \n",
       "0    2.04   5148468.0    0   1366    768  100.454670  \n",
       "1    2.99  15552108.0    0   1920   1080  127.335675  \n",
       "2    2.19  11550708.0    1   1920   1080  141.211998  \n",
       "3    1.20  10625940.0    0   1920   1080  165.632118  \n",
       "4    2.20   4881708.0    0   1920   1080  141.211998  "
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_test.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.drop(columns=['Screen Size','X_res','Y_res'],inplace=True)\n",
    "df_test.drop(columns=['Screen Size','X_res','Y_res'],inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\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>Manufacturer</th>\n",
       "      <th>Model Name</th>\n",
       "      <th>Category</th>\n",
       "      <th>CPU</th>\n",
       "      <th>RAM</th>\n",
       "      <th>Storage</th>\n",
       "      <th>GPU</th>\n",
       "      <th>Operating System</th>\n",
       "      <th>Operating System Version</th>\n",
       "      <th>Weight</th>\n",
       "      <th>Price</th>\n",
       "      <th>Ips</th>\n",
       "      <th>ppi</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Apple</td>\n",
       "      <td>MacBook Pro</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>Intel Core i5 2.3GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>128GB SSD</td>\n",
       "      <td>Intel Iris Plus Graphics 640</td>\n",
       "      <td>macOS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.37</td>\n",
       "      <td>11912523.48</td>\n",
       "      <td>1</td>\n",
       "      <td>226.983005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Apple</td>\n",
       "      <td>Macbook Air</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>Intel Core i5 1.8GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>128GB Flash Storage</td>\n",
       "      <td>Intel HD Graphics 6000</td>\n",
       "      <td>macOS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.34</td>\n",
       "      <td>7993374.48</td>\n",
       "      <td>0</td>\n",
       "      <td>127.677940</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>HP</td>\n",
       "      <td>250 G6</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>Intel Core i5 7200U 2.5GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>256GB SSD</td>\n",
       "      <td>Intel HD Graphics 620</td>\n",
       "      <td>No OS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.86</td>\n",
       "      <td>5112900.00</td>\n",
       "      <td>0</td>\n",
       "      <td>141.211998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Apple</td>\n",
       "      <td>MacBook Pro</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>Intel Core i7 2.7GHz</td>\n",
       "      <td>16</td>\n",
       "      <td>512GB SSD</td>\n",
       "      <td>AMD Radeon Pro 455</td>\n",
       "      <td>macOS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.83</td>\n",
       "      <td>22563005.40</td>\n",
       "      <td>1</td>\n",
       "      <td>220.534624</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Apple</td>\n",
       "      <td>MacBook Pro</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>Intel Core i5 3.1GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>256GB SSD</td>\n",
       "      <td>Intel Iris Plus Graphics 650</td>\n",
       "      <td>macOS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.37</td>\n",
       "      <td>16037611.20</td>\n",
       "      <td>1</td>\n",
       "      <td>226.983005</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Manufacturer   Model Name   Category                         CPU  RAM  \\\n",
       "0        Apple  MacBook Pro  Ultrabook        Intel Core i5 2.3GHz    8   \n",
       "1        Apple  Macbook Air  Ultrabook        Intel Core i5 1.8GHz    8   \n",
       "2           HP       250 G6   Notebook  Intel Core i5 7200U 2.5GHz    8   \n",
       "3        Apple  MacBook Pro  Ultrabook        Intel Core i7 2.7GHz   16   \n",
       "4        Apple  MacBook Pro  Ultrabook        Intel Core i5 3.1GHz    8   \n",
       "\n",
       "               Storage                           GPU Operating System  \\\n",
       "0            128GB SSD  Intel Iris Plus Graphics 640            macOS   \n",
       "1  128GB Flash Storage        Intel HD Graphics 6000            macOS   \n",
       "2            256GB SSD         Intel HD Graphics 620            No OS   \n",
       "3            512GB SSD            AMD Radeon Pro 455            macOS   \n",
       "4            256GB SSD  Intel Iris Plus Graphics 650            macOS   \n",
       "\n",
       "  Operating System Version  Weight        Price  Ips         ppi  \n",
       "0                       10    1.37  11912523.48    1  226.983005  \n",
       "1                       10    1.34   7993374.48    0  127.677940  \n",
       "2                       10    1.86   5112900.00    0  141.211998  \n",
       "3                       10    1.83  22563005.40    1  220.534624  \n",
       "4                       10    1.37  16037611.20    1  226.983005  "
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Manufacturer</th>\n",
       "      <th>Model Name</th>\n",
       "      <th>Category</th>\n",
       "      <th>CPU</th>\n",
       "      <th>RAM</th>\n",
       "      <th>Storage</th>\n",
       "      <th>GPU</th>\n",
       "      <th>Operating System</th>\n",
       "      <th>Operating System Version</th>\n",
       "      <th>Weight</th>\n",
       "      <th>Price</th>\n",
       "      <th>Ips</th>\n",
       "      <th>ppi</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>HP</td>\n",
       "      <td>15-bs053od (i7-7500U/6GB/1TB/W10)</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>Intel Core i7 7500U 2.7GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>1TB HDD</td>\n",
       "      <td>Intel HD Graphics 620</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>2.04</td>\n",
       "      <td>5148468.0</td>\n",
       "      <td>0</td>\n",
       "      <td>100.454670</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Asus</td>\n",
       "      <td>Rog GL753VE-DS74</td>\n",
       "      <td>Gaming</td>\n",
       "      <td>Intel Core i7 7700HQ 2.8GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>256GB SSD +  1TB HDD</td>\n",
       "      <td>Nvidia GeForce GTX 1050 Ti</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>2.99</td>\n",
       "      <td>15552108.0</td>\n",
       "      <td>0</td>\n",
       "      <td>127.335675</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Dell</td>\n",
       "      <td>Inspiron 7579</td>\n",
       "      <td>2 in 1 Convertible</td>\n",
       "      <td>Intel Core i7 7500U 2.7GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>512GB SSD</td>\n",
       "      <td>Intel HD Graphics 620</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>2.19</td>\n",
       "      <td>11550708.0</td>\n",
       "      <td>1</td>\n",
       "      <td>141.211998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Toshiba</td>\n",
       "      <td>Portege Z30-C-1CV</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>Intel Core i5 6200U 2.3GHz</td>\n",
       "      <td>16</td>\n",
       "      <td>128GB SSD</td>\n",
       "      <td>Intel HD Graphics 520</td>\n",
       "      <td>Windows</td>\n",
       "      <td>7</td>\n",
       "      <td>1.20</td>\n",
       "      <td>10625940.0</td>\n",
       "      <td>0</td>\n",
       "      <td>165.632118</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Lenovo</td>\n",
       "      <td>IdeaPad 320-15ABR</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>AMD A12-Series 9720P 3.6GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>256GB SSD</td>\n",
       "      <td>AMD Radeon 530</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>2.20</td>\n",
       "      <td>4881708.0</td>\n",
       "      <td>0</td>\n",
       "      <td>141.211998</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Manufacturer                         Model Name            Category  \\\n",
       "0           HP  15-bs053od (i7-7500U/6GB/1TB/W10)            Notebook   \n",
       "1         Asus                   Rog GL753VE-DS74              Gaming   \n",
       "2         Dell                      Inspiron 7579  2 in 1 Convertible   \n",
       "3      Toshiba                  Portege Z30-C-1CV            Notebook   \n",
       "4       Lenovo                  IdeaPad 320-15ABR            Notebook   \n",
       "\n",
       "                           CPU  RAM               Storage  \\\n",
       "0   Intel Core i7 7500U 2.7GHz    8               1TB HDD   \n",
       "1  Intel Core i7 7700HQ 2.8GHz    8  256GB SSD +  1TB HDD   \n",
       "2   Intel Core i7 7500U 2.7GHz    8             512GB SSD   \n",
       "3   Intel Core i5 6200U 2.3GHz   16             128GB SSD   \n",
       "4  AMD A12-Series 9720P 3.6GHz    8             256GB SSD   \n",
       "\n",
       "                          GPU Operating System Operating System Version  \\\n",
       "0       Intel HD Graphics 620          Windows                       10   \n",
       "1  Nvidia GeForce GTX 1050 Ti          Windows                       10   \n",
       "2       Intel HD Graphics 620          Windows                       10   \n",
       "3       Intel HD Graphics 520          Windows                        7   \n",
       "4              AMD Radeon 530          Windows                       10   \n",
       "\n",
       "   Weight       Price  Ips         ppi  \n",
       "0    2.04   5148468.0    0  100.454670  \n",
       "1    2.99  15552108.0    0  127.335675  \n",
       "2    2.19  11550708.0    1  141.211998  \n",
       "3    1.20  10625940.0    0  165.632118  \n",
       "4    2.20   4881708.0    0  141.211998  "
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_test.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "CPU\n",
       "Intel Core i5 7200U 2.5GHz     151\n",
       "Intel Core i7 7700HQ 2.8GHz    123\n",
       "Intel Core i7 7500U 2.7GHz     103\n",
       "Intel Core i7 8550U 1.8GHz      71\n",
       "Intel Core i5 8250U 1.6GHz      71\n",
       "                              ... \n",
       "Intel Core i7 2.9GHz             1\n",
       "AMD E-Series 7110 1.8GHz         1\n",
       "Intel Core i5 2.9GHz             1\n",
       "Intel Core M m3 1.2GHz           1\n",
       "Intel Core i5 7200U 2.70GHz      1\n",
       "Name: count, Length: 106, dtype: int64"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# EDA on CPU\n",
    "df[\"CPU\"].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "CPU\n",
       "Intel Core i5 7200U 2.5GHz              39\n",
       "Intel Core i5 6200U 2.3GHz              36\n",
       "Intel Core i7 6500U 2.5GHz              33\n",
       "Intel Core i7 6700HQ 2.6GHz             32\n",
       "Intel Core i7 7500U 2.7GHz              30\n",
       "Intel Core i7 7700HQ 2.8GHz             23\n",
       "Intel Core i3 7100U 2.4GHz              11\n",
       "Intel Celeron Dual Core N3050 1.6GHz    10\n",
       "Intel Core i7 6600U 2.6GHz              10\n",
       "Intel Core i5 6300U 2.4GHz               8\n",
       "Intel Celeron Dual Core N3060 1.6GHz     8\n",
       "Intel Core i3 6006U 2GHz                 7\n",
       "Intel Core i3 6100U 2.3GHz               7\n",
       "Intel Core i3 6006U 2.0GHz               6\n",
       "Intel Core i7 6820HK 2.7GHz              4\n",
       "Intel Pentium Quad Core N3710 1.6GHz     3\n",
       "Intel Core M 6Y30 0.9GHz                 3\n",
       "Intel Core i5 6300HQ 2.3GHz              3\n",
       "Intel Atom x5-Z8550 1.44GHz              3\n",
       "AMD A9-Series 9410 2.9GHz                3\n",
       "Intel Core i5 7300HQ 2.5GHz              3\n",
       "Intel Celeron Dual Core N3350 1.1GHz     3\n",
       "Intel Celeron Dual Core 3205U 1.5GHz     2\n",
       "AMD A12-Series 9720P 3.6GHz              2\n",
       "Intel Celeron Dual Core N3350 2GHz       2\n",
       "Intel Core M 6Y75 1.2GHz                 2\n",
       "Intel Core i7 8550U 1.8GHz               2\n",
       "Intel Core i7 6500U 2.50GHz              2\n",
       "AMD A6-Series 9220 2.5GHz                2\n",
       "Intel Atom X5-Z8350 1.44GHz              2\n",
       "AMD A8-Series 7410 2.2GHz                2\n",
       "Intel Pentium Quad Core N3700 1.6GHz     2\n",
       "Intel Core i7 6820HQ 2.7GHz              2\n",
       "Intel Core M 1.1GHz                      2\n",
       "AMD E-Series 9000 2.2GHz                 1\n",
       "Intel Core i5 7200U 2.7GHz               1\n",
       "Intel Core i5 7Y54 1.2GHz                1\n",
       "Intel Core i5 1.6GHz                     1\n",
       "AMD A12-Series 9720P 2.7GHz              1\n",
       "Intel Core i7 7Y75 1.3GHz                1\n",
       "Intel Core M 1.2GHz                      1\n",
       "Intel Pentium Quad Core N4200 1.1GHz     1\n",
       "Samsung Cortex A72&A53 2.0GHz            1\n",
       "Intel Core i5 8250U 1.6GHz               1\n",
       "AMD A6-Series A6-9220 2.5GHz             1\n",
       "AMD E-Series 7110 1.8GHz                 1\n",
       "Intel Pentium Dual Core 4405Y 1.5GHz     1\n",
       "AMD A9-Series 9420 3GHz                  1\n",
       "Intel Core M 6Y54 1.1GHz                 1\n",
       "Intel Core i7 7560U 2.4GHz               1\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_test[\"CPU\"].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['CPU Name'] = df['CPU'].apply(lambda x:\" \".join(x.split()[0:3]))\n",
    "df_test['CPU Name'] = df_test['CPU'].apply(lambda x:\" \".join(x.split()[0:3]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Manufacturer</th>\n",
       "      <th>Model Name</th>\n",
       "      <th>Category</th>\n",
       "      <th>CPU</th>\n",
       "      <th>RAM</th>\n",
       "      <th>Storage</th>\n",
       "      <th>GPU</th>\n",
       "      <th>Operating System</th>\n",
       "      <th>Operating System Version</th>\n",
       "      <th>Weight</th>\n",
       "      <th>Price</th>\n",
       "      <th>Ips</th>\n",
       "      <th>ppi</th>\n",
       "      <th>CPU Name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Apple</td>\n",
       "      <td>MacBook Pro</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>Intel Core i5 2.3GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>128GB SSD</td>\n",
       "      <td>Intel Iris Plus Graphics 640</td>\n",
       "      <td>macOS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.37</td>\n",
       "      <td>11912523.48</td>\n",
       "      <td>1</td>\n",
       "      <td>226.983005</td>\n",
       "      <td>Intel Core i5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Apple</td>\n",
       "      <td>Macbook Air</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>Intel Core i5 1.8GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>128GB Flash Storage</td>\n",
       "      <td>Intel HD Graphics 6000</td>\n",
       "      <td>macOS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.34</td>\n",
       "      <td>7993374.48</td>\n",
       "      <td>0</td>\n",
       "      <td>127.677940</td>\n",
       "      <td>Intel Core i5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>HP</td>\n",
       "      <td>250 G6</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>Intel Core i5 7200U 2.5GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>256GB SSD</td>\n",
       "      <td>Intel HD Graphics 620</td>\n",
       "      <td>No OS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.86</td>\n",
       "      <td>5112900.00</td>\n",
       "      <td>0</td>\n",
       "      <td>141.211998</td>\n",
       "      <td>Intel Core i5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Apple</td>\n",
       "      <td>MacBook Pro</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>Intel Core i7 2.7GHz</td>\n",
       "      <td>16</td>\n",
       "      <td>512GB SSD</td>\n",
       "      <td>AMD Radeon Pro 455</td>\n",
       "      <td>macOS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.83</td>\n",
       "      <td>22563005.40</td>\n",
       "      <td>1</td>\n",
       "      <td>220.534624</td>\n",
       "      <td>Intel Core i7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Apple</td>\n",
       "      <td>MacBook Pro</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>Intel Core i5 3.1GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>256GB SSD</td>\n",
       "      <td>Intel Iris Plus Graphics 650</td>\n",
       "      <td>macOS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.37</td>\n",
       "      <td>16037611.20</td>\n",
       "      <td>1</td>\n",
       "      <td>226.983005</td>\n",
       "      <td>Intel Core i5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Manufacturer   Model Name   Category                         CPU  RAM  \\\n",
       "0        Apple  MacBook Pro  Ultrabook        Intel Core i5 2.3GHz    8   \n",
       "1        Apple  Macbook Air  Ultrabook        Intel Core i5 1.8GHz    8   \n",
       "2           HP       250 G6   Notebook  Intel Core i5 7200U 2.5GHz    8   \n",
       "3        Apple  MacBook Pro  Ultrabook        Intel Core i7 2.7GHz   16   \n",
       "4        Apple  MacBook Pro  Ultrabook        Intel Core i5 3.1GHz    8   \n",
       "\n",
       "               Storage                           GPU Operating System  \\\n",
       "0            128GB SSD  Intel Iris Plus Graphics 640            macOS   \n",
       "1  128GB Flash Storage        Intel HD Graphics 6000            macOS   \n",
       "2            256GB SSD         Intel HD Graphics 620            No OS   \n",
       "3            512GB SSD            AMD Radeon Pro 455            macOS   \n",
       "4            256GB SSD  Intel Iris Plus Graphics 650            macOS   \n",
       "\n",
       "  Operating System Version  Weight        Price  Ips         ppi  \\\n",
       "0                       10    1.37  11912523.48    1  226.983005   \n",
       "1                       10    1.34   7993374.48    0  127.677940   \n",
       "2                       10    1.86   5112900.00    0  141.211998   \n",
       "3                       10    1.83  22563005.40    1  220.534624   \n",
       "4                       10    1.37  16037611.20    1  226.983005   \n",
       "\n",
       "        CPU Name  \n",
       "0  Intel Core i5  \n",
       "1  Intel Core i5  \n",
       "2  Intel Core i5  \n",
       "3  Intel Core i7  \n",
       "4  Intel Core i5  "
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Manufacturer</th>\n",
       "      <th>Model Name</th>\n",
       "      <th>Category</th>\n",
       "      <th>CPU</th>\n",
       "      <th>RAM</th>\n",
       "      <th>Storage</th>\n",
       "      <th>GPU</th>\n",
       "      <th>Operating System</th>\n",
       "      <th>Operating System Version</th>\n",
       "      <th>Weight</th>\n",
       "      <th>Price</th>\n",
       "      <th>Ips</th>\n",
       "      <th>ppi</th>\n",
       "      <th>CPU Name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>HP</td>\n",
       "      <td>15-bs053od (i7-7500U/6GB/1TB/W10)</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>Intel Core i7 7500U 2.7GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>1TB HDD</td>\n",
       "      <td>Intel HD Graphics 620</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>2.04</td>\n",
       "      <td>5148468.0</td>\n",
       "      <td>0</td>\n",
       "      <td>100.454670</td>\n",
       "      <td>Intel Core i7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Asus</td>\n",
       "      <td>Rog GL753VE-DS74</td>\n",
       "      <td>Gaming</td>\n",
       "      <td>Intel Core i7 7700HQ 2.8GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>256GB SSD +  1TB HDD</td>\n",
       "      <td>Nvidia GeForce GTX 1050 Ti</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>2.99</td>\n",
       "      <td>15552108.0</td>\n",
       "      <td>0</td>\n",
       "      <td>127.335675</td>\n",
       "      <td>Intel Core i7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Dell</td>\n",
       "      <td>Inspiron 7579</td>\n",
       "      <td>2 in 1 Convertible</td>\n",
       "      <td>Intel Core i7 7500U 2.7GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>512GB SSD</td>\n",
       "      <td>Intel HD Graphics 620</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>2.19</td>\n",
       "      <td>11550708.0</td>\n",
       "      <td>1</td>\n",
       "      <td>141.211998</td>\n",
       "      <td>Intel Core i7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Toshiba</td>\n",
       "      <td>Portege Z30-C-1CV</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>Intel Core i5 6200U 2.3GHz</td>\n",
       "      <td>16</td>\n",
       "      <td>128GB SSD</td>\n",
       "      <td>Intel HD Graphics 520</td>\n",
       "      <td>Windows</td>\n",
       "      <td>7</td>\n",
       "      <td>1.20</td>\n",
       "      <td>10625940.0</td>\n",
       "      <td>0</td>\n",
       "      <td>165.632118</td>\n",
       "      <td>Intel Core i5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Lenovo</td>\n",
       "      <td>IdeaPad 320-15ABR</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>AMD A12-Series 9720P 3.6GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>256GB SSD</td>\n",
       "      <td>AMD Radeon 530</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>2.20</td>\n",
       "      <td>4881708.0</td>\n",
       "      <td>0</td>\n",
       "      <td>141.211998</td>\n",
       "      <td>AMD A12-Series 9720P</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Manufacturer                         Model Name            Category  \\\n",
       "0           HP  15-bs053od (i7-7500U/6GB/1TB/W10)            Notebook   \n",
       "1         Asus                   Rog GL753VE-DS74              Gaming   \n",
       "2         Dell                      Inspiron 7579  2 in 1 Convertible   \n",
       "3      Toshiba                  Portege Z30-C-1CV            Notebook   \n",
       "4       Lenovo                  IdeaPad 320-15ABR            Notebook   \n",
       "\n",
       "                           CPU  RAM               Storage  \\\n",
       "0   Intel Core i7 7500U 2.7GHz    8               1TB HDD   \n",
       "1  Intel Core i7 7700HQ 2.8GHz    8  256GB SSD +  1TB HDD   \n",
       "2   Intel Core i7 7500U 2.7GHz    8             512GB SSD   \n",
       "3   Intel Core i5 6200U 2.3GHz   16             128GB SSD   \n",
       "4  AMD A12-Series 9720P 3.6GHz    8             256GB SSD   \n",
       "\n",
       "                          GPU Operating System Operating System Version  \\\n",
       "0       Intel HD Graphics 620          Windows                       10   \n",
       "1  Nvidia GeForce GTX 1050 Ti          Windows                       10   \n",
       "2       Intel HD Graphics 620          Windows                       10   \n",
       "3       Intel HD Graphics 520          Windows                        7   \n",
       "4              AMD Radeon 530          Windows                       10   \n",
       "\n",
       "   Weight       Price  Ips         ppi              CPU Name  \n",
       "0    2.04   5148468.0    0  100.454670         Intel Core i7  \n",
       "1    2.99  15552108.0    0  127.335675         Intel Core i7  \n",
       "2    2.19  11550708.0    1  141.211998         Intel Core i7  \n",
       "3    1.20  10625940.0    0  165.632118         Intel Core i5  \n",
       "4    2.20   4881708.0    0  141.211998  AMD A12-Series 9720P  "
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_test.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "def fetch_processor(text):\n",
    "    if text == 'Intel Core i7' or text == 'Intel Core i5' or text == 'Intel Core i3':\n",
    "        return text\n",
    "    else:\n",
    "        if text.split()[0] == 'Intel':\n",
    "            return 'Other Intel Processor'\n",
    "        else:\n",
    "            return 'AMD Processor'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['CPU Brand'] = df['CPU Name'].apply(fetch_processor)\n",
    "df_test['CPU Brand'] = df_test['CPU Name'].apply(fetch_processor)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Manufacturer</th>\n",
       "      <th>Model Name</th>\n",
       "      <th>Category</th>\n",
       "      <th>CPU</th>\n",
       "      <th>RAM</th>\n",
       "      <th>Storage</th>\n",
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       "      <th>Operating System</th>\n",
       "      <th>Operating System Version</th>\n",
       "      <th>Weight</th>\n",
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       "      <th>Ips</th>\n",
       "      <th>ppi</th>\n",
       "      <th>CPU Name</th>\n",
       "      <th>CPU Brand</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Apple</td>\n",
       "      <td>MacBook Pro</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>Intel Core i5 2.3GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>128GB SSD</td>\n",
       "      <td>Intel Iris Plus Graphics 640</td>\n",
       "      <td>macOS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.37</td>\n",
       "      <td>11912523.48</td>\n",
       "      <td>1</td>\n",
       "      <td>226.983005</td>\n",
       "      <td>Intel Core i5</td>\n",
       "      <td>Intel Core i5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Apple</td>\n",
       "      <td>Macbook Air</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>Intel Core i5 1.8GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>128GB Flash Storage</td>\n",
       "      <td>Intel HD Graphics 6000</td>\n",
       "      <td>macOS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.34</td>\n",
       "      <td>7993374.48</td>\n",
       "      <td>0</td>\n",
       "      <td>127.677940</td>\n",
       "      <td>Intel Core i5</td>\n",
       "      <td>Intel Core i5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>HP</td>\n",
       "      <td>250 G6</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>Intel Core i5 7200U 2.5GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>256GB SSD</td>\n",
       "      <td>Intel HD Graphics 620</td>\n",
       "      <td>No OS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.86</td>\n",
       "      <td>5112900.00</td>\n",
       "      <td>0</td>\n",
       "      <td>141.211998</td>\n",
       "      <td>Intel Core i5</td>\n",
       "      <td>Intel Core i5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Apple</td>\n",
       "      <td>MacBook Pro</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>Intel Core i7 2.7GHz</td>\n",
       "      <td>16</td>\n",
       "      <td>512GB SSD</td>\n",
       "      <td>AMD Radeon Pro 455</td>\n",
       "      <td>macOS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.83</td>\n",
       "      <td>22563005.40</td>\n",
       "      <td>1</td>\n",
       "      <td>220.534624</td>\n",
       "      <td>Intel Core i7</td>\n",
       "      <td>Intel Core i7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Apple</td>\n",
       "      <td>MacBook Pro</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>Intel Core i5 3.1GHz</td>\n",
       "      <td>8</td>\n",
       "      <td>256GB SSD</td>\n",
       "      <td>Intel Iris Plus Graphics 650</td>\n",
       "      <td>macOS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.37</td>\n",
       "      <td>16037611.20</td>\n",
       "      <td>1</td>\n",
       "      <td>226.983005</td>\n",
       "      <td>Intel Core i5</td>\n",
       "      <td>Intel Core i5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Manufacturer   Model Name   Category                         CPU  RAM  \\\n",
       "0        Apple  MacBook Pro  Ultrabook        Intel Core i5 2.3GHz    8   \n",
       "1        Apple  Macbook Air  Ultrabook        Intel Core i5 1.8GHz    8   \n",
       "2           HP       250 G6   Notebook  Intel Core i5 7200U 2.5GHz    8   \n",
       "3        Apple  MacBook Pro  Ultrabook        Intel Core i7 2.7GHz   16   \n",
       "4        Apple  MacBook Pro  Ultrabook        Intel Core i5 3.1GHz    8   \n",
       "\n",
       "               Storage                           GPU Operating System  \\\n",
       "0            128GB SSD  Intel Iris Plus Graphics 640            macOS   \n",
       "1  128GB Flash Storage        Intel HD Graphics 6000            macOS   \n",
       "2            256GB SSD         Intel HD Graphics 620            No OS   \n",
       "3            512GB SSD            AMD Radeon Pro 455            macOS   \n",
       "4            256GB SSD  Intel Iris Plus Graphics 650            macOS   \n",
       "\n",
       "  Operating System Version  Weight        Price  Ips         ppi  \\\n",
       "0                       10    1.37  11912523.48    1  226.983005   \n",
       "1                       10    1.34   7993374.48    0  127.677940   \n",
       "2                       10    1.86   5112900.00    0  141.211998   \n",
       "3                       10    1.83  22563005.40    1  220.534624   \n",
       "4                       10    1.37  16037611.20    1  226.983005   \n",
       "\n",
       "        CPU Name      CPU Brand  \n",
       "0  Intel Core i5  Intel Core i5  \n",
       "1  Intel Core i5  Intel Core i5  \n",
       "2  Intel Core i5  Intel Core i5  \n",
       "3  Intel Core i7  Intel Core i7  \n",
       "4  Intel Core i5  Intel Core i5  "
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='CPU Brand'>"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df['CPU Brand'].value_counts().plot(kind='bar')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(x=df['CPU Brand'],y=df['Price'])\n",
    "plt.xticks(rotation='vertical')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.drop(columns=['CPU','CPU Name'],inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_test.drop(columns=['CPU','CPU Name'],inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Manufacturer</th>\n",
       "      <th>Model Name</th>\n",
       "      <th>Category</th>\n",
       "      <th>RAM</th>\n",
       "      <th>Storage</th>\n",
       "      <th>GPU</th>\n",
       "      <th>Operating System</th>\n",
       "      <th>Operating System Version</th>\n",
       "      <th>Weight</th>\n",
       "      <th>Price</th>\n",
       "      <th>Ips</th>\n",
       "      <th>ppi</th>\n",
       "      <th>CPU Brand</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Apple</td>\n",
       "      <td>MacBook Pro</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>8</td>\n",
       "      <td>128GB SSD</td>\n",
       "      <td>Intel Iris Plus Graphics 640</td>\n",
       "      <td>macOS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.37</td>\n",
       "      <td>11912523.48</td>\n",
       "      <td>1</td>\n",
       "      <td>226.983005</td>\n",
       "      <td>Intel Core i5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Apple</td>\n",
       "      <td>Macbook Air</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>8</td>\n",
       "      <td>128GB Flash Storage</td>\n",
       "      <td>Intel HD Graphics 6000</td>\n",
       "      <td>macOS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.34</td>\n",
       "      <td>7993374.48</td>\n",
       "      <td>0</td>\n",
       "      <td>127.677940</td>\n",
       "      <td>Intel Core i5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>HP</td>\n",
       "      <td>250 G6</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>8</td>\n",
       "      <td>256GB SSD</td>\n",
       "      <td>Intel HD Graphics 620</td>\n",
       "      <td>No OS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.86</td>\n",
       "      <td>5112900.00</td>\n",
       "      <td>0</td>\n",
       "      <td>141.211998</td>\n",
       "      <td>Intel Core i5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Apple</td>\n",
       "      <td>MacBook Pro</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>16</td>\n",
       "      <td>512GB SSD</td>\n",
       "      <td>AMD Radeon Pro 455</td>\n",
       "      <td>macOS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.83</td>\n",
       "      <td>22563005.40</td>\n",
       "      <td>1</td>\n",
       "      <td>220.534624</td>\n",
       "      <td>Intel Core i7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Apple</td>\n",
       "      <td>MacBook Pro</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>8</td>\n",
       "      <td>256GB SSD</td>\n",
       "      <td>Intel Iris Plus Graphics 650</td>\n",
       "      <td>macOS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.37</td>\n",
       "      <td>16037611.20</td>\n",
       "      <td>1</td>\n",
       "      <td>226.983005</td>\n",
       "      <td>Intel Core i5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Manufacturer   Model Name   Category  RAM              Storage  \\\n",
       "0        Apple  MacBook Pro  Ultrabook    8            128GB SSD   \n",
       "1        Apple  Macbook Air  Ultrabook    8  128GB Flash Storage   \n",
       "2           HP       250 G6   Notebook    8            256GB SSD   \n",
       "3        Apple  MacBook Pro  Ultrabook   16            512GB SSD   \n",
       "4        Apple  MacBook Pro  Ultrabook    8            256GB SSD   \n",
       "\n",
       "                            GPU Operating System Operating System Version  \\\n",
       "0  Intel Iris Plus Graphics 640            macOS                       10   \n",
       "1        Intel HD Graphics 6000            macOS                       10   \n",
       "2         Intel HD Graphics 620            No OS                       10   \n",
       "3            AMD Radeon Pro 455            macOS                       10   \n",
       "4  Intel Iris Plus Graphics 650            macOS                       10   \n",
       "\n",
       "   Weight        Price  Ips         ppi      CPU Brand  \n",
       "0    1.37  11912523.48    1  226.983005  Intel Core i5  \n",
       "1    1.34   7993374.48    0  127.677940  Intel Core i5  \n",
       "2    1.86   5112900.00    0  141.211998  Intel Core i5  \n",
       "3    1.83  22563005.40    1  220.534624  Intel Core i7  \n",
       "4    1.37  16037611.20    1  226.983005  Intel Core i5  "
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Manufacturer</th>\n",
       "      <th>Model Name</th>\n",
       "      <th>Category</th>\n",
       "      <th>RAM</th>\n",
       "      <th>Storage</th>\n",
       "      <th>GPU</th>\n",
       "      <th>Operating System</th>\n",
       "      <th>Operating System Version</th>\n",
       "      <th>Weight</th>\n",
       "      <th>Price</th>\n",
       "      <th>Ips</th>\n",
       "      <th>ppi</th>\n",
       "      <th>CPU Brand</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>HP</td>\n",
       "      <td>15-bs053od (i7-7500U/6GB/1TB/W10)</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>8</td>\n",
       "      <td>1TB HDD</td>\n",
       "      <td>Intel HD Graphics 620</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>2.04</td>\n",
       "      <td>5148468.0</td>\n",
       "      <td>0</td>\n",
       "      <td>100.454670</td>\n",
       "      <td>Intel Core i7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Asus</td>\n",
       "      <td>Rog GL753VE-DS74</td>\n",
       "      <td>Gaming</td>\n",
       "      <td>8</td>\n",
       "      <td>256GB SSD +  1TB HDD</td>\n",
       "      <td>Nvidia GeForce GTX 1050 Ti</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>2.99</td>\n",
       "      <td>15552108.0</td>\n",
       "      <td>0</td>\n",
       "      <td>127.335675</td>\n",
       "      <td>Intel Core i7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Dell</td>\n",
       "      <td>Inspiron 7579</td>\n",
       "      <td>2 in 1 Convertible</td>\n",
       "      <td>8</td>\n",
       "      <td>512GB SSD</td>\n",
       "      <td>Intel HD Graphics 620</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>2.19</td>\n",
       "      <td>11550708.0</td>\n",
       "      <td>1</td>\n",
       "      <td>141.211998</td>\n",
       "      <td>Intel Core i7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Toshiba</td>\n",
       "      <td>Portege Z30-C-1CV</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>16</td>\n",
       "      <td>128GB SSD</td>\n",
       "      <td>Intel HD Graphics 520</td>\n",
       "      <td>Windows</td>\n",
       "      <td>7</td>\n",
       "      <td>1.20</td>\n",
       "      <td>10625940.0</td>\n",
       "      <td>0</td>\n",
       "      <td>165.632118</td>\n",
       "      <td>Intel Core i5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Lenovo</td>\n",
       "      <td>IdeaPad 320-15ABR</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>8</td>\n",
       "      <td>256GB SSD</td>\n",
       "      <td>AMD Radeon 530</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>2.20</td>\n",
       "      <td>4881708.0</td>\n",
       "      <td>0</td>\n",
       "      <td>141.211998</td>\n",
       "      <td>AMD Processor</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Manufacturer                         Model Name            Category  RAM  \\\n",
       "0           HP  15-bs053od (i7-7500U/6GB/1TB/W10)            Notebook    8   \n",
       "1         Asus                   Rog GL753VE-DS74              Gaming    8   \n",
       "2         Dell                      Inspiron 7579  2 in 1 Convertible    8   \n",
       "3      Toshiba                  Portege Z30-C-1CV            Notebook   16   \n",
       "4       Lenovo                  IdeaPad 320-15ABR            Notebook    8   \n",
       "\n",
       "                Storage                         GPU Operating System  \\\n",
       "0               1TB HDD       Intel HD Graphics 620          Windows   \n",
       "1  256GB SSD +  1TB HDD  Nvidia GeForce GTX 1050 Ti          Windows   \n",
       "2             512GB SSD       Intel HD Graphics 620          Windows   \n",
       "3             128GB SSD       Intel HD Graphics 520          Windows   \n",
       "4             256GB SSD              AMD Radeon 530          Windows   \n",
       "\n",
       "  Operating System Version  Weight       Price  Ips         ppi      CPU Brand  \n",
       "0                       10    2.04   5148468.0    0  100.454670  Intel Core i7  \n",
       "1                       10    2.99  15552108.0    0  127.335675  Intel Core i7  \n",
       "2                       10    2.19  11550708.0    1  141.211998  Intel Core i7  \n",
       "3                        7    1.20  10625940.0    0  165.632118  Intel Core i5  \n",
       "4                       10    2.20   4881708.0    0  141.211998  AMD Processor  "
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_test.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='RAM'>"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df['RAM'].value_counts().plot(kind='bar')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='RAM'>"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_test['RAM'].value_counts().plot(kind='bar')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYIAAAEUCAYAAAAmxTHXAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjQuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8rg+JYAAAACXBIWXMAAAsTAAALEwEAmpwYAAAWiklEQVR4nO3df5SdBX3n8feHEEIUFSvZhvIrVLEWRUHnoC5dy6LugrVwjtI1uIq6ulktqD3rNqdoF3+09mhctVqqNgoK6oIWPW70gJYVq+IqGGhAEHWjrZKpUwKRH1EWDXz3j/uMTi43mSEzz9x787xf58y5z+/74ZDMJ8/vVBWSpO7aZ9gBJEnDZRFIUsdZBJLUcRaBJHWcRSBJHWcRSFLHjWURJLkgya1JbpzDsu9Osqn5+V6SOxYhoiSNjYzjfQRJngFsBy6qqic8iPVeDRxXVf+ptXCSNGbGco+gqr4CbJs5Lcmjk3w+ybVJvprkcQNWPQO4eFFCStKY2HfYARbQeuCVVfV/kzwVeB9w0vTMJEcARwJXDimfJI2kvaIIkhwA/Gvgb5NMT17Wt9hq4NKqum8xs0nSqNsrioDeIa47qurY3SyzGjhrceJI0vgYy3ME/arqLuAfk/wBQHqeND2/OV/wSODrQ4ooSSNrLIsgycX0fqn/VpItSV4O/Efg5UmuB24CTpuxymrgkhrHS6QkqWVjefmoJGnhjOUegSRp4VgEktRxY3fV0EEHHVSrVq0adgxJGivXXnvtbVW1YtC8sSuCVatWsXHjxmHHkKSxkuSHu5rnoSFJ6jiLQJI6ziKQpI6zCCSp4ywCSeo4i0CSOs4ikKSOG7v7CCRpb7Z27VqmpqZYuXIl69atW5TvtAgkaYRMTU0xOTm5qN/poSFJ6rjWiiDJ/kmuSXJ9kpuSvHnAMi9NsjXJpubnFW3lkSQN1uahoXuBk6pqe5KlwFVJLq+qb/Qt94mqOrvFHJKk3WitCJq3gW1vRpc2P74FR5JGTKvnCJIsSbIJuBW4oqquHrDY85PckOTSJIe1mUeS9ECtFkFV3VdVxwKHAscneULfIp8FVlXVE4ErgAsHbSfJmiQbk2zcunVrm5ElqXMW5aqhqroD+BJwct/026vq3mb0Q8BTdrH++qqaqKqJFSsGvldBkrSH2rxqaEWSA5vh5cCzge/0LXPwjNFTgZvbyiNJGqzNq4YOBi5MsoRe4Xyyqj6X5C3AxqraALwmyanADmAb8NIW80iSBmjzqqEbgOMGTD93xvA5wDltZZAkzc47iyWp4ywCSeo4i0CSOs4ikKSOswgkqeMsAknqOItAkjrOIpCkjrMIJKnjLAJJ6jiLQJI6ziKQpI6zCCSp4ywCSeo4i0CSOs4ikKSOswgkqeMsAknqOItAkjrOIpCkjmutCJLsn+SaJNcnuSnJmwcssyzJJ5JsTnJ1klVt5ZEkDbZvi9u+FzipqrYnWQpcleTyqvrGjGVeDvykqh6TZDXwduAFLWaSpFa96U1vmtf627Zt++XnfLb1YNZtbY+gerY3o0ubn+pb7DTgwmb4UuCZSdJWJknSA7V6jiDJkiSbgFuBK6rq6r5FDgFuAaiqHcCdwKMGbGdNko1JNm7durXNyJLUOa0WQVXdV1XHAocCxyd5wh5uZ31VTVTVxIoVKxY0oyR13aJcNVRVdwBfAk7umzUJHAaQZF/gEcDti5FJktTT5lVDK5Ic2AwvB54NfKdvsQ3AS5rh04Erq6r/PIIkqUVtXjV0MHBhkiX0CueTVfW5JG8BNlbVBuB84KNJNgPbgNUt5pEkDdBaEVTVDcBxA6afO2P4/wF/0FYGSdLsvLNYkjrOIpCkjrMIJKnjLAJJ6jiLQJI6ziKQpI6zCCSp4ywCSeo4i0CSOs4ikKSOswgkqeMsAknqOItAkjrOIpCkjmvzfQSSNDLWrl3L1NQUK1euZN26dcOOM1IsAkmdMDU1xeTk5LBjjCQPDUlSx1kEktRxFoEkdZxFIEkd11oRJDksyZeSfDvJTUleO2CZE5PcmWRT83PuoG1JktrT5lVDO4DXVdV1SR4GXJvkiqr6dt9yX62q57aYQ5K0G63tEVTVj6vqumb4buBm4JC2vk+StGcW5RxBklXAccDVA2Y/Pcn1SS5P8vhdrL8mycYkG7du3dpmVEkaqmXLlrF8+XKWLVu2aN/Z+g1lSQ4APgX8UVXd1Tf7OuCIqtqe5DnAZ4Cj+rdRVeuB9QATExPVbmJJGp5jjjlm0b+z1T2CJEvplcDHq+rT/fOr6q6q2t4MXwYsTXJQm5kkSTtr86qhAOcDN1fVu3axzMpmOZIc3+S5va1MkqQHavPQ0AnAi4FvJdnUTHs9cDhAVX0AOB14VZIdwD3A6qry0I8kLaLWiqCqrgIyyzLnAee1lUGSNDvvLJakjrMIJKnjLAJJ6jiLQJI6ziKQpI6zCCSp4ywCSeo4i0CSOs4ikKSOswgkqeMsAknqOItAkjrOIpCkjrMIJKnjLAJJ6jiLQJI6ziKQpI6zCCSp4ywCSeo4i0CSOm5ORZDksUm+mOTGZvyJSf50lnUOS/KlJN9OclOS1w5YJknem2RzkhuSPHnP/jMkSXtqrnsEHwTOAX4BUFU3AKtnWWcH8LqqOhp4GnBWkqP7ljkFOKr5WQO8f455JEkLZK5F8JCquqZv2o7drVBVP66q65rhu4GbgUP6FjsNuKh6vgEcmOTgOWaSJC2AuRbBbUkeDRRAktOBH8/1S5KsAo4Dru6bdQhwy4zxLTywLEiyJsnGJBu3bt0616+VJM3BvnNc7ixgPfC4JJPAPwIvmsuKSQ4APgX8UVXdtSchq2p98/1MTEzUnmxDkjTYnIqgqn4APCvJQ4F9mkM9s0qylF4JfLyqPj1gkUngsBnjhzbTJGknN7/1ynmt//Nt9/zycz7b+u03nDSvHKNorlcN/UWSA6vqp1V1d5JHJvnzWdYJcD5wc1W9axeLbQDObK4eehpwZ1XN+ZCTJGn+5nqO4JSqumN6pKp+AjxnlnVOAF4MnJRkU/PznCSvTPLKZpnLgB8Am+ldmfSHDyq9JGne5nqOYEmSZVV1L0CS5cCy3a1QVVcBmWWZonf+QZI0JHMtgo8DX0zy4Wb8ZcCF7USSJC2muZ4sfnuSG4BnNpP+rKq+0F4sSdJimeseAVV1OXB5i1kkSUOw2yJIclVV/U6Su2luJpueRe8Q/8NbTSdp5K1du5apqSlWrlzJunXrhh1He2C3RVBVv9N8Pmxx4kgaN1NTU0xOevvPOJv18tEkS5J8ZzHCSJIW36xFUFX3Ad9Ncvgi5JEkLbK5nix+JHBTkmuAn05PrKpTW0klSVo0cy2C/95qCknS0Mx21dD+wCuBxwDfAs6vqt2+h0DS+Hnri07f43W33Xpn73Pqx/Pazhs+duker6v5me0cwYXABL0SOAV4Z+uJJEmLarZDQ0dX1TEASc4H+t9SJkkac7PtEfxiesBDQpK0d5ptj+BJSabfKhZgeTPuncWStJeY7c7iJYsVRJI0HHN+6JwkDbL/kn12+tT4sQgkzctxj/JRZOPOCpekjrMIJKnjWiuCJBckuTXJjbuYf2KSO2e82P7ctrJIknatzXMEHwHOAy7azTJfrarntphBkjSL1vYIquorwLa2ti9JWhjDPkfw9CTXJ7k8yeOHnEWSOmmYl49eBxxRVduTPAf4DHDUoAWTrAHWABx+uO/HkaSFNLQ9gqq6q6q2N8OXAUuTHLSLZddX1URVTaxYsWJRc0rS3m5oRZBkZZI0w8c3WW4fVh5J6qrWDg0luRg4ETgoyRbgjcBSgKr6AHA68KokO4B7gNVVVW3lkSQN1loRVNUZs8w/j97lpZKkIRr2VUOSpCGzCCSp4ywCSeo4i0CSOs4ikKSOswgkqeMsAknqOItAkjrOIpCkjvPl9dIIW7t2LVNTU6xcuZJ169YNO472UhaBNMKmpqaYnJwcdgzt5Tw0JEkdZxFIUsdZBJLUcRaBJHWcRSBJHWcRSFLHefmopE541P6P2OlTv2IRSOqEs4974bAjjCyLQJ3kHbvSr7R2jiDJBUluTXLjLuYnyXuTbE5yQ5Int5VF6jd9x+7U1NSwo0hD1+YewUeA84CLdjH/FOCo5uepwPubT2mvcd7rPjuv9e+47ae//NzTbZ39zt+fVwbt/Vorgqr6SpJVu1nkNOCiqirgG0kOTHJwVf24rUzae3z5Gb87r/Xv2XcJJNyzZcseb+t3v/LleWWQRsUwLx89BLhlxviWZtoDJFmTZGOSjVu3bl2UcJLUFWNxH0FVra+qiaqaWLFixbDjSNJeZZhXDU0Ch80YP7SZJrXuwKqdPqUuG2YRbADOTnIJvZPEd3p+QIvlRffdP+wI0shorQiSXAycCByUZAvwRmApQFV9ALgMeA6wGfgZ8LK2skiSdq3Nq4bOmGV+AWe19f2SpLkZi5PFkqT2WASS1HE+a0gaYQ/d7+E7fUptsAikEXbCo5837AjqAA8NSVLHWQSS1HEWgSR1nEUgSR1nEUhSx1kEktRxFoEkdZxFIEkdZxFIUsdZBJLUcRaBJHWcRSBJHedD57Sg1q5dy9TUFCtXrmTdunXDjiNpDiwCLaipqSkmJyeHHUPSg+ChIUnqOItAkjqu1UNDSU4G3gMsAT5UVW/rm/9S4B3A9LGE86rqQ21m0u6d8FcnzGv9/e7Yj33Yh1vuuGVe2/raq782rxyS5q61IkiyBPhr4NnAFuCbSTZU1bf7Fv1EVZ3dVg5J0u61uUdwPLC5qn4AkOQS4DSgvwg0B16NI6ktbZ4jOAS4Zcb4lmZav+cnuSHJpUkOG7ShJGuSbEyycevWrW1kHXnTV+NMTU0NO8pu1UOK+x96P/WQGnYUSXM07MtHPwtcXFX3JvkvwIXASf0LVdV6YD3AxMTEWP6G+dFbjpnX+ju2/RqwLzu2/XBe2zr83G/NK8dsfnHCL1rdvqSF1+YewSQw81/4h/Krk8IAVNXtVXVvM/oh4Ckt5pEkDdBmEXwTOCrJkUn2A1YDG2YukOTgGaOnAje3mEeSNEBrh4aqakeSs4Ev0Lt89IKquinJW4CNVbUBeE2SU4EdwDbgpW3lGXcH7X8/sKP5lKSF0+o5gqq6DLisb9q5M4bPAc5pM8Pe4r898Y5hR5C0l/LOYknqOItAkjrOIpCkjrMIJKnjLAJJ6jiLQJI6ziKQpI6zCCSp44b90Lmh8/HOkrqu80Xgy9Yldd3YF8FT/viiea3/sNvuZgnwo9vunte2rn3HmfPKIUnD4jkCSeo4i0CSOm7sDw3N1/37PXSnT0nqms4XwU+P+nfDjiBJQ+WhIUnqOItAkjrOIpCkjrMIJKnjLAJJ6rhWiyDJyUm+m2Rzkj8ZMH9Zkk80869OsqrNPJKkB2qtCJIsAf4aOAU4GjgjydF9i70c+ElVPQZ4N/D2tvJIkgZrc4/geGBzVf2gqn4OXAKc1rfMacCFzfClwDOTpMVMkqQ+qap2NpycDpxcVa9oxl8MPLWqzp6xzI3NMlua8e83y9zWt601wJpm9LeA7y5w3IOA22ZdavjMubDMuXDGISN0O+cRVbVi0IyxuLO4qtYD69vafpKNVTXR1vYXijkXljkXzjhkBHPuSpuHhiaBw2aMH9pMG7hMkn2BRwC3t5hJktSnzSL4JnBUkiOT7AesBjb0LbMBeEkzfDpwZbV1rEqSNFBrh4aqakeSs4EvAEuAC6rqpiRvATZW1QbgfOCjSTYD2+iVxTC0dthpgZlzYZlz4YxDRjDnQK2dLJYkjQfvLJakjrMIJKnjLAJJ6rhOFkGSxyV5ZpID+qafPKxMs0ly0bAzDJLkqUke3gwvT/LmJJ9N8vYkjxh2PoAk+yU5M8mzmvEXJjkvyVlJlg47nxZPkn817AyjqHMni5O8BjgLuBk4FnhtVf2vZt51VfXkIcajydF/mW2AfwtcCVBVpy56qF1IchPwpOYqsfXAz2geF9JMf95QAwJJPk7vCrmHAHcABwCfppcxVfWSXa+tuUjyqKoaqXuAkvxa/yTgWuA4ev/fty1+qgdqnsv2Cnr3Wn2+qr42Y96fVtWft51hLO4sXmD/GXhKVW1vnnZ6aZJVVfUeen9QRsGhwLeBDwFFL9cE8M5hhtqFfapqRzM8MaNIr0qyaUiZ+h1TVU9sblqcBH6jqu5L8jHg+iFn20mzd3UOvT8Dl1fV/5wx731V9YdDC/erHG8D/kdV3ZZkAvgkcH+zd3VmVX15uAl/6Tbgh33TDgGuo/f36jcXPdFgf0PvHynXAO9N8uWq+q/NvOcBrRdBFw8N7VNV2wGq6p+AE4FTkryL0SmCCXr/cnkDcGdV/T1wT1V9eYT+kk27McnLmuHrm18MJHks8IvhxdrJPs1NjQ+j9xdu+pDVMmDUDg19mN6fw08Bq5N8KsmyZt7ThhdrJ78343lg7wBe0DxB+NmM1j9W/pjec8lOraojq+pIYEszPColAHB8Vb2wqv4SeCpwQJJPN//fF+V3UheL4F+SHDs90pTCc+k95OmYYYWaqarur6p3Ay8D3pDkPEZ37+0VwO82Dww8Gvh6kh8AH2zmjYLzge8Am+iV698m+SC9u98vGWKuQR5dVX9SVZ9pDgFeB1yZ5FHDDjbDvs3eFcDyqvomQFV9j165joSqeie9P4PnJnlXkofR2xMYNftND1TVjqpaQ29P9Up6hzFb18VzBIcCO6pqasC8E2YenxsVSX4POKGqXj/sLLvSHNI4kl5hbamqfxlypJ0k+Q2AqvrnJAcCzwJ+VFXXDDVYnyQ3A4+vqvtnTHspvX/dHlBVRwwr27QkrwZ+H3gb8AzgkfTOuZwE/GZVvXiI8QZKcirwemBVVa0cdp6ZmkOUH6uqz/dNfwXw/qpqfa+1c0UgjbIk64C/q6r/3Tf9ZOCvquqo4STbWZITgVcBj6VX/rcAn6H3KJkdu1xxkSV5HL3zAlcD99Hb47oxycn9v3iHKcnxQFXVN5sXeJ0MfKeqLluU77cIpPGQ5GVV9eFh59idUco4DlcIAiR5I703Oe4LXEHvPMGX6J1z+UJVvbX1DBaBNB6S/KiqDh92jt0ZpYxJvgU8feYVgsBHq+o9Sf6hqo4bbsKeJuex9M6vTAGHVtVdSZYDV1fVE9vOMKonIKVOSnLDrmYBv76YWXZlHDI2drpCsDmcdWmSIxidKwShd87yPuBnSb5fVXcBVNU9Se6fZd0FYRFIo+XXgX8P/KRveoD/s/hxBhqHjNBcIVhVm6B3hWCS5wIXMCJXCDZ+nuQhVfUz4CnTE5s78y0CqYM+R+/qoE39M5L8/aKnGWwcMgKcCex04ro5kX1mkr8ZTqSBnlFV90Lv0vEZ05fyqxd3tcpzBJLUcV28oUySNINFIEkdZxFIc5DkviSbktzYPGb7wL75m5Jc0jftI0l+1jzaYHraXyapJActUnRpVhaBNDf3VNWxVfUEYBu9G5UASPLbwBLg3yR5aN96m4HTmuX2ofcYhsnFiSzNjUUgPXhfp/fYgmlnAB8F/o7ml/4MlwAvaIZPBL5G35Us0rBZBNKD0LxE5JnAzJcHvYDeL/yL6ZXCTN8DViR5ZDNv1J52KlkE0hwtb160M0XvhqorAJr3L9xWVT8CvggcN+DNWJ8GVtN7hsxXFy2xNEcWgTQ391TVscD04wmmzxGcATwuyT8B3wceDjy/b91PAH8GXNF3w5A0EiwC6UFoHgPwGuB1zVvP/gO9V2GuqqpV9M4RnNG3zg/pvRDnfYscV5oTHzEhPUhV9Q/Ng9fOASar6p9nzP4KcHSSg/vWGaVHGkg78RETktRxHhqSpI6zCCSp4ywCSeo4i0CSOs4ikKSOswgkqeMsAknqOItAkjru/wO79MA1RzmHTwAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(x=df['RAM'],y=df['Price'])\n",
    "plt.xticks(rotation='vertical')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       " Storage\n",
       "256GB SSD                        318\n",
       "1TB HDD                          171\n",
       "512GB SSD                         91\n",
       "500GB HDD                         79\n",
       "128GB SSD +  1TB HDD              71\n",
       "128GB SSD                         62\n",
       "256GB SSD +  1TB HDD              52\n",
       "32GB Flash Storage                29\n",
       "2TB HDD                           14\n",
       "512GB SSD +  1TB HDD              13\n",
       "1TB SSD                           11\n",
       "256GB SSD +  2TB HDD              10\n",
       "64GB Flash Storage                 9\n",
       "16GB Flash Storage                 6\n",
       "256GB Flash Storage                5\n",
       "32GB SSD                           5\n",
       "128GB Flash Storage                4\n",
       "1GB SSD                            4\n",
       "256GB SSD +  256GB SSD             2\n",
       "16GB SSD                           2\n",
       "1TB SSD +  1TB HDD                 2\n",
       "512GB SSD +  2TB HDD               2\n",
       "128GB SSD +  2TB HDD               2\n",
       "512GB SSD +  512GB SSD             1\n",
       "512GB SSD +  256GB SSD             1\n",
       "64GB SSD                           1\n",
       "64GB Flash Storage +  1TB HDD      1\n",
       "256GB SSD +  500GB HDD             1\n",
       "1TB HDD +  1TB HDD                 1\n",
       "32GB HDD                           1\n",
       "1TB Hybrid                         1\n",
       "512GB Flash Storage                1\n",
       "128GB HDD                          1\n",
       "240GB SSD                          1\n",
       "8GB SSD                            1\n",
       "508GB Hybrid                       1\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\" Storage\"].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [],
   "source": [
    "df[' Storage'] = df[' Storage'].astype(str).replace('\\.0', '', regex=True)\n",
    "df[\" Storage\"] = df[\" Storage\"].str.replace('GB', '')\n",
    "df[\" Storage\"] = df[\" Storage\"].str.replace('TB', '000')\n",
    "new = df[\" Storage\"].str.split(\"+\", n = 1, expand = True)\n",
    "\n",
    "df[\"first\"]= new[0]\n",
    "df[\"first\"]=df[\"first\"].str.strip()\n",
    "\n",
    "df[\"second\"]= new[1]\n",
    "\n",
    "df[\"Layer1HDD\"] = df[\"first\"].apply(lambda x: 1 if \"HDD\" in x else 0)\n",
    "df[\"Layer1SSD\"] = df[\"first\"].apply(lambda x: 1 if \"SSD\" in x else 0)\n",
    "df[\"Layer1Hybrid\"] = df[\"first\"].apply(lambda x: 1 if \"Hybrid\" in x else 0)\n",
    "df[\"Layer1Flash_Storage\"] = df[\"first\"].apply(lambda x: 1 if \"Flash Storage\" in x else 0)\n",
    "\n",
    "df['first'] = df['first'].str.replace(r'\\D', \"\",regex=True)\n",
    "\n",
    "df[\"second\"].fillna(\"0\", inplace = True)\n",
    "\n",
    "df[\"Layer2HDD\"] = df[\"second\"].apply(lambda x: 1 if \"HDD\" in x else 0)\n",
    "df[\"Layer2SSD\"] = df[\"second\"].apply(lambda x: 1 if \"SSD\" in x else 0)\n",
    "df[\"Layer2Hybrid\"] = df[\"second\"].apply(lambda x: 1 if \"Hybrid\" in x else 0)\n",
    "df[\"Layer2Flash_Storage\"] = df[\"second\"].apply(lambda x: 1 if \"Flash Storage\" in x else 0)\n",
    "\n",
    "df['second'] = df['second'].str.replace(r'\\D', '',regex=True)\n",
    "# df[\"first\"] = df[\"first\"].str.replace(r\"[^0-9]+\", \"\")\n",
    "# df[\"second\"] = df[\"second\"].str.replace(r\"[^0-9]+\", \"\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Manufacturer</th>\n",
       "      <th>Model Name</th>\n",
       "      <th>Category</th>\n",
       "      <th>RAM</th>\n",
       "      <th>Storage</th>\n",
       "      <th>GPU</th>\n",
       "      <th>Operating System</th>\n",
       "      <th>Operating System Version</th>\n",
       "      <th>Weight</th>\n",
       "      <th>Price</th>\n",
       "      <th>...</th>\n",
       "      <th>first</th>\n",
       "      <th>second</th>\n",
       "      <th>Layer1HDD</th>\n",
       "      <th>Layer1SSD</th>\n",
       "      <th>Layer1Hybrid</th>\n",
       "      <th>Layer1Flash_Storage</th>\n",
       "      <th>Layer2HDD</th>\n",
       "      <th>Layer2SSD</th>\n",
       "      <th>Layer2Hybrid</th>\n",
       "      <th>Layer2Flash_Storage</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>268</th>\n",
       "      <td>HP</td>\n",
       "      <td>Probook 470</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>8</td>\n",
       "      <td>1000 HDD</td>\n",
       "      <td>Nvidia GeForce 930MX</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>2.50</td>\n",
       "      <td>9052056.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>886</th>\n",
       "      <td>Dell</td>\n",
       "      <td>Vostro 3568</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>4</td>\n",
       "      <td>1000 HDD</td>\n",
       "      <td>AMD Radeon R5 M420X</td>\n",
       "      <td>Linux</td>\n",
       "      <td>10</td>\n",
       "      <td>2.18</td>\n",
       "      <td>4052084.4</td>\n",
       "      <td>...</td>\n",
       "      <td>1000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>652</th>\n",
       "      <td>Dell</td>\n",
       "      <td>XPS 13</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>8</td>\n",
       "      <td>256 SSD</td>\n",
       "      <td>Intel UHD Graphics 620</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>1.20</td>\n",
       "      <td>12892510.8</td>\n",
       "      <td>...</td>\n",
       "      <td>256</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>938</th>\n",
       "      <td>Dell</td>\n",
       "      <td>Latitude 7480</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>8</td>\n",
       "      <td>256 SSD</td>\n",
       "      <td>Intel HD Graphics 620</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>1.36</td>\n",
       "      <td>14573988.0</td>\n",
       "      <td>...</td>\n",
       "      <td>256</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>HP</td>\n",
       "      <td>ProBook 450</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>8</td>\n",
       "      <td>256 SSD</td>\n",
       "      <td>Nvidia GeForce 930MX</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>2.10</td>\n",
       "      <td>7816068.0</td>\n",
       "      <td>...</td>\n",
       "      <td>256</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Apple</td>\n",
       "      <td>MacBook Pro</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>16</td>\n",
       "      <td>512 SSD</td>\n",
       "      <td>AMD Radeon Pro 455</td>\n",
       "      <td>macOS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.83</td>\n",
       "      <td>22563005.4</td>\n",
       "      <td>...</td>\n",
       "      <td>512</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>496</th>\n",
       "      <td>Lenovo</td>\n",
       "      <td>Ideapad 520-15IKBR</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>8</td>\n",
       "      <td>256 SSD</td>\n",
       "      <td>Intel UHD Graphics 620</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>2.17</td>\n",
       "      <td>7993018.8</td>\n",
       "      <td>...</td>\n",
       "      <td>256</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>162</th>\n",
       "      <td>Dell</td>\n",
       "      <td>Inspiron 3576</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>8</td>\n",
       "      <td>256 SSD</td>\n",
       "      <td>AMD Radeon 520</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>2.13</td>\n",
       "      <td>6473376.0</td>\n",
       "      <td>...</td>\n",
       "      <td>256</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>Asus</td>\n",
       "      <td>E402WA-GA010T (E2-6110/2GB/32GB/W10)</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>2</td>\n",
       "      <td>32 Flash Storage</td>\n",
       "      <td>AMD Radeon R2</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>1.65</td>\n",
       "      <td>1769508.0</td>\n",
       "      <td>...</td>\n",
       "      <td>32</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>567</th>\n",
       "      <td>Fujitsu</td>\n",
       "      <td>Lifebook A557</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>8</td>\n",
       "      <td>1000 HDD</td>\n",
       "      <td>Intel HD Graphics 620</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>2.20</td>\n",
       "      <td>6571188.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10 rows × 23 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    Manufacturer                            Model Name   Category  RAM  \\\n",
       "268           HP                           Probook 470   Notebook    8   \n",
       "886         Dell                           Vostro 3568   Notebook    4   \n",
       "652         Dell                                XPS 13  Ultrabook    8   \n",
       "938         Dell                         Latitude 7480  Ultrabook    8   \n",
       "39            HP                           ProBook 450   Notebook    8   \n",
       "3          Apple                           MacBook Pro  Ultrabook   16   \n",
       "496       Lenovo                    Ideapad 520-15IKBR   Notebook    8   \n",
       "162         Dell                         Inspiron 3576   Notebook    8   \n",
       "31          Asus  E402WA-GA010T (E2-6110/2GB/32GB/W10)   Notebook    2   \n",
       "567      Fujitsu                         Lifebook A557   Notebook    8   \n",
       "\n",
       "              Storage                     GPU Operating System  \\\n",
       "268          1000 HDD   Nvidia GeForce 930MX           Windows   \n",
       "886          1000 HDD     AMD Radeon R5 M420X            Linux   \n",
       "652           256 SSD  Intel UHD Graphics 620          Windows   \n",
       "938           256 SSD   Intel HD Graphics 620          Windows   \n",
       "39            256 SSD   Nvidia GeForce 930MX           Windows   \n",
       "3             512 SSD      AMD Radeon Pro 455            macOS   \n",
       "496           256 SSD  Intel UHD Graphics 620          Windows   \n",
       "162           256 SSD          AMD Radeon 520          Windows   \n",
       "31   32 Flash Storage           AMD Radeon R2          Windows   \n",
       "567          1000 HDD   Intel HD Graphics 620          Windows   \n",
       "\n",
       "    Operating System Version  Weight       Price  ...  first  second  \\\n",
       "268                       10    2.50   9052056.0  ...   1000       0   \n",
       "886                       10    2.18   4052084.4  ...   1000       0   \n",
       "652                       10    1.20  12892510.8  ...    256       0   \n",
       "938                       10    1.36  14573988.0  ...    256       0   \n",
       "39                        10    2.10   7816068.0  ...    256       0   \n",
       "3                         10    1.83  22563005.4  ...    512       0   \n",
       "496                       10    2.17   7993018.8  ...    256       0   \n",
       "162                       10    2.13   6473376.0  ...    256       0   \n",
       "31                        10    1.65   1769508.0  ...     32       0   \n",
       "567                       10    2.20   6571188.0  ...   1000       0   \n",
       "\n",
       "    Layer1HDD Layer1SSD Layer1Hybrid  Layer1Flash_Storage  Layer2HDD  \\\n",
       "268         1         0            0                    0          0   \n",
       "886         1         0            0                    0          0   \n",
       "652         0         1            0                    0          0   \n",
       "938         0         1            0                    0          0   \n",
       "39          0         1            0                    0          0   \n",
       "3           0         1            0                    0          0   \n",
       "496         0         1            0                    0          0   \n",
       "162         0         1            0                    0          0   \n",
       "31          0         0            0                    1          0   \n",
       "567         1         0            0                    0          0   \n",
       "\n",
       "     Layer2SSD  Layer2Hybrid  Layer2Flash_Storage  \n",
       "268          0             0                    0  \n",
       "886          0             0                    0  \n",
       "652          0             0                    0  \n",
       "938          0             0                    0  \n",
       "39           0             0                    0  \n",
       "3            0             0                    0  \n",
       "496          0             0                    0  \n",
       "162          0             0                    0  \n",
       "31           0             0                    0  \n",
       "567          0             0                    0  \n",
       "\n",
       "[10 rows x 23 columns]"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.sample(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [],
   "source": [
    "df[\"first\"] = df[\"first\"].astype(int)\n",
    "df[\"second\"] = df[\"second\"].astype(int)\n",
    "\n",
    "df[\"HDD\"]=(df[\"first\"]*df[\"Layer1HDD\"]+df[\"second\"]*df[\"Layer2HDD\"])\n",
    "df[\"SSD\"]=(df[\"first\"]*df[\"Layer1SSD\"]+df[\"second\"]*df[\"Layer2SSD\"])\n",
    "df[\"Hybrid\"]=(df[\"first\"]*df[\"Layer1Hybrid\"]+df[\"second\"]*df[\"Layer2Hybrid\"])\n",
    "df[\"Flash_Storage\"]=(df[\"first\"]*df[\"Layer1Flash_Storage\"]+df[\"second\"]*df[\"Layer2Flash_Storage\"])\n",
    "\n",
    "df.drop(columns=['first', 'second', 'Layer1HDD', 'Layer1SSD', 'Layer1Hybrid',\n",
    "       'Layer1Flash_Storage', 'Layer2HDD', 'Layer2SSD', 'Layer2Hybrid',\n",
    "       'Layer2Flash_Storage'],inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Manufacturer</th>\n",
       "      <th>Model Name</th>\n",
       "      <th>Category</th>\n",
       "      <th>RAM</th>\n",
       "      <th>GPU</th>\n",
       "      <th>Operating System</th>\n",
       "      <th>Operating System Version</th>\n",
       "      <th>Weight</th>\n",
       "      <th>Price</th>\n",
       "      <th>Ips</th>\n",
       "      <th>ppi</th>\n",
       "      <th>CPU Brand</th>\n",
       "      <th>HDD</th>\n",
       "      <th>SSD</th>\n",
       "      <th>Hybrid</th>\n",
       "      <th>Flash_Storage</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Apple</td>\n",
       "      <td>MacBook Pro</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>8</td>\n",
       "      <td>Intel Iris Plus Graphics 640</td>\n",
       "      <td>macOS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.37</td>\n",
       "      <td>11912523.48</td>\n",
       "      <td>1</td>\n",
       "      <td>226.983005</td>\n",
       "      <td>Intel Core i5</td>\n",
       "      <td>0</td>\n",
       "      <td>128</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Apple</td>\n",
       "      <td>Macbook Air</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>8</td>\n",
       "      <td>Intel HD Graphics 6000</td>\n",
       "      <td>macOS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.34</td>\n",
       "      <td>7993374.48</td>\n",
       "      <td>0</td>\n",
       "      <td>127.677940</td>\n",
       "      <td>Intel Core i5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>128</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>HP</td>\n",
       "      <td>250 G6</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>8</td>\n",
       "      <td>Intel HD Graphics 620</td>\n",
       "      <td>No OS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.86</td>\n",
       "      <td>5112900.00</td>\n",
       "      <td>0</td>\n",
       "      <td>141.211998</td>\n",
       "      <td>Intel Core i5</td>\n",
       "      <td>0</td>\n",
       "      <td>256</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Apple</td>\n",
       "      <td>MacBook Pro</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>16</td>\n",
       "      <td>AMD Radeon Pro 455</td>\n",
       "      <td>macOS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.83</td>\n",
       "      <td>22563005.40</td>\n",
       "      <td>1</td>\n",
       "      <td>220.534624</td>\n",
       "      <td>Intel Core i7</td>\n",
       "      <td>0</td>\n",
       "      <td>512</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Apple</td>\n",
       "      <td>MacBook Pro</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>8</td>\n",
       "      <td>Intel Iris Plus Graphics 650</td>\n",
       "      <td>macOS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.37</td>\n",
       "      <td>16037611.20</td>\n",
       "      <td>1</td>\n",
       "      <td>226.983005</td>\n",
       "      <td>Intel Core i5</td>\n",
       "      <td>0</td>\n",
       "      <td>256</td>\n",
       "      <td>0</td>\n",
       "      <td>0</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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>972</th>\n",
       "      <td>Dell</td>\n",
       "      <td>Alienware 17</td>\n",
       "      <td>Gaming</td>\n",
       "      <td>32</td>\n",
       "      <td>Nvidia GeForce GTX 1070</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>4.42</td>\n",
       "      <td>24897600.00</td>\n",
       "      <td>0</td>\n",
       "      <td>127.335675</td>\n",
       "      <td>Intel Core i7</td>\n",
       "      <td>1000</td>\n",
       "      <td>256</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>973</th>\n",
       "      <td>Toshiba</td>\n",
       "      <td>Tecra A40-C-1DF</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>8</td>\n",
       "      <td>Intel HD Graphics 520</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>1.95</td>\n",
       "      <td>10492560.00</td>\n",
       "      <td>0</td>\n",
       "      <td>157.350512</td>\n",
       "      <td>Intel Core i5</td>\n",
       "      <td>0</td>\n",
       "      <td>256</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>974</th>\n",
       "      <td>Asus</td>\n",
       "      <td>Rog Strix</td>\n",
       "      <td>Gaming</td>\n",
       "      <td>16</td>\n",
       "      <td>Nvidia GeForce GTX 1060</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>2.73</td>\n",
       "      <td>18227710.80</td>\n",
       "      <td>0</td>\n",
       "      <td>127.335675</td>\n",
       "      <td>Intel Core i7</td>\n",
       "      <td>1000</td>\n",
       "      <td>256</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>975</th>\n",
       "      <td>HP</td>\n",
       "      <td>Probook 450</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>8</td>\n",
       "      <td>Nvidia GeForce 930MX</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>2.04</td>\n",
       "      <td>8705268.00</td>\n",
       "      <td>1</td>\n",
       "      <td>141.211998</td>\n",
       "      <td>Intel Core i5</td>\n",
       "      <td>1000</td>\n",
       "      <td>128</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>976</th>\n",
       "      <td>Lenovo</td>\n",
       "      <td>ThinkPad T460</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>4</td>\n",
       "      <td>Intel HD Graphics 520</td>\n",
       "      <td>Windows</td>\n",
       "      <td>7</td>\n",
       "      <td>1.70</td>\n",
       "      <td>8909784.00</td>\n",
       "      <td>0</td>\n",
       "      <td>111.935204</td>\n",
       "      <td>Intel Core i5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>508</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>977 rows × 16 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    Manufacturer       Model Name   Category  RAM  \\\n",
       "0          Apple      MacBook Pro  Ultrabook    8   \n",
       "1          Apple      Macbook Air  Ultrabook    8   \n",
       "2             HP           250 G6   Notebook    8   \n",
       "3          Apple      MacBook Pro  Ultrabook   16   \n",
       "4          Apple      MacBook Pro  Ultrabook    8   \n",
       "..           ...              ...        ...  ...   \n",
       "972         Dell     Alienware 17     Gaming   32   \n",
       "973      Toshiba  Tecra A40-C-1DF   Notebook    8   \n",
       "974         Asus        Rog Strix     Gaming   16   \n",
       "975           HP      Probook 450   Notebook    8   \n",
       "976       Lenovo    ThinkPad T460   Notebook    4   \n",
       "\n",
       "                              GPU Operating System Operating System Version  \\\n",
       "0    Intel Iris Plus Graphics 640            macOS                       10   \n",
       "1          Intel HD Graphics 6000            macOS                       10   \n",
       "2           Intel HD Graphics 620            No OS                       10   \n",
       "3              AMD Radeon Pro 455            macOS                       10   \n",
       "4    Intel Iris Plus Graphics 650            macOS                       10   \n",
       "..                            ...              ...                      ...   \n",
       "972       Nvidia GeForce GTX 1070          Windows                       10   \n",
       "973         Intel HD Graphics 520          Windows                       10   \n",
       "974       Nvidia GeForce GTX 1060          Windows                       10   \n",
       "975          Nvidia GeForce 930MX          Windows                       10   \n",
       "976         Intel HD Graphics 520          Windows                        7   \n",
       "\n",
       "     Weight        Price  Ips         ppi      CPU Brand   HDD  SSD  Hybrid  \\\n",
       "0      1.37  11912523.48    1  226.983005  Intel Core i5     0  128       0   \n",
       "1      1.34   7993374.48    0  127.677940  Intel Core i5     0    0       0   \n",
       "2      1.86   5112900.00    0  141.211998  Intel Core i5     0  256       0   \n",
       "3      1.83  22563005.40    1  220.534624  Intel Core i7     0  512       0   \n",
       "4      1.37  16037611.20    1  226.983005  Intel Core i5     0  256       0   \n",
       "..      ...          ...  ...         ...            ...   ...  ...     ...   \n",
       "972    4.42  24897600.00    0  127.335675  Intel Core i7  1000  256       0   \n",
       "973    1.95  10492560.00    0  157.350512  Intel Core i5     0  256       0   \n",
       "974    2.73  18227710.80    0  127.335675  Intel Core i7  1000  256       0   \n",
       "975    2.04   8705268.00    1  141.211998  Intel Core i5  1000  128       0   \n",
       "976    1.70   8909784.00    0  111.935204  Intel Core i5     0    0     508   \n",
       "\n",
       "     Flash_Storage  \n",
       "0                0  \n",
       "1              128  \n",
       "2                0  \n",
       "3                0  \n",
       "4                0  \n",
       "..             ...  \n",
       "972              0  \n",
       "973              0  \n",
       "974              0  \n",
       "975              0  \n",
       "976              0  \n",
       "\n",
       "[977 rows x 16 columns]"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.drop(columns=[\" Storage\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Manufacturer</th>\n",
       "      <th>Model Name</th>\n",
       "      <th>Category</th>\n",
       "      <th>RAM</th>\n",
       "      <th>GPU</th>\n",
       "      <th>Operating System</th>\n",
       "      <th>Operating System Version</th>\n",
       "      <th>Weight</th>\n",
       "      <th>Price</th>\n",
       "      <th>Ips</th>\n",
       "      <th>ppi</th>\n",
       "      <th>CPU Brand</th>\n",
       "      <th>HDD</th>\n",
       "      <th>SSD</th>\n",
       "      <th>Hybrid</th>\n",
       "      <th>Flash_Storage</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>HP</td>\n",
       "      <td>15-bs053od (i7-7500U/6GB/1TB/W10)</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>8</td>\n",
       "      <td>Intel HD Graphics 620</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>2.04</td>\n",
       "      <td>5148468.0</td>\n",
       "      <td>0</td>\n",
       "      <td>100.454670</td>\n",
       "      <td>Intel Core i7</td>\n",
       "      <td>1000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Asus</td>\n",
       "      <td>Rog GL753VE-DS74</td>\n",
       "      <td>Gaming</td>\n",
       "      <td>8</td>\n",
       "      <td>Nvidia GeForce GTX 1050 Ti</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>2.99</td>\n",
       "      <td>15552108.0</td>\n",
       "      <td>0</td>\n",
       "      <td>127.335675</td>\n",
       "      <td>Intel Core i7</td>\n",
       "      <td>1000</td>\n",
       "      <td>256</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Dell</td>\n",
       "      <td>Inspiron 7579</td>\n",
       "      <td>2 in 1 Convertible</td>\n",
       "      <td>8</td>\n",
       "      <td>Intel HD Graphics 620</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>2.19</td>\n",
       "      <td>11550708.0</td>\n",
       "      <td>1</td>\n",
       "      <td>141.211998</td>\n",
       "      <td>Intel Core i7</td>\n",
       "      <td>0</td>\n",
       "      <td>512</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Toshiba</td>\n",
       "      <td>Portege Z30-C-1CV</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>16</td>\n",
       "      <td>Intel HD Graphics 520</td>\n",
       "      <td>Windows</td>\n",
       "      <td>7</td>\n",
       "      <td>1.20</td>\n",
       "      <td>10625940.0</td>\n",
       "      <td>0</td>\n",
       "      <td>165.632118</td>\n",
       "      <td>Intel Core i5</td>\n",
       "      <td>0</td>\n",
       "      <td>128</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Lenovo</td>\n",
       "      <td>IdeaPad 320-15ABR</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>8</td>\n",
       "      <td>AMD Radeon 530</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>2.20</td>\n",
       "      <td>4881708.0</td>\n",
       "      <td>0</td>\n",
       "      <td>141.211998</td>\n",
       "      <td>AMD Processor</td>\n",
       "      <td>0</td>\n",
       "      <td>256</td>\n",
       "      <td>0</td>\n",
       "      <td>0</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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>320</th>\n",
       "      <td>Lenovo</td>\n",
       "      <td>Yoga 500-14ISK</td>\n",
       "      <td>2 in 1 Convertible</td>\n",
       "      <td>8</td>\n",
       "      <td>Intel HD Graphics 520</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>1.80</td>\n",
       "      <td>5673096.0</td>\n",
       "      <td>1</td>\n",
       "      <td>157.350512</td>\n",
       "      <td>Intel Core i7</td>\n",
       "      <td>0</td>\n",
       "      <td>128</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>321</th>\n",
       "      <td>Lenovo</td>\n",
       "      <td>Yoga 900-13ISK</td>\n",
       "      <td>2 in 1 Convertible</td>\n",
       "      <td>4</td>\n",
       "      <td>Intel HD Graphics 520</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>1.30</td>\n",
       "      <td>13329108.0</td>\n",
       "      <td>1</td>\n",
       "      <td>276.053530</td>\n",
       "      <td>Intel Core i7</td>\n",
       "      <td>0</td>\n",
       "      <td>512</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>322</th>\n",
       "      <td>Lenovo</td>\n",
       "      <td>IdeaPad 100S-14IBR</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>8</td>\n",
       "      <td>Intel HD Graphics</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>1.50</td>\n",
       "      <td>2036268.0</td>\n",
       "      <td>0</td>\n",
       "      <td>111.935204</td>\n",
       "      <td>Other Intel Processor</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>323</th>\n",
       "      <td>HP</td>\n",
       "      <td>15-AC110nv (i7-6500U/6GB/1TB/Radeon</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>8</td>\n",
       "      <td>AMD Radeon R5 M330</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>2.19</td>\n",
       "      <td>6793488.0</td>\n",
       "      <td>0</td>\n",
       "      <td>100.454670</td>\n",
       "      <td>Intel Core i7</td>\n",
       "      <td>1000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>324</th>\n",
       "      <td>Asus</td>\n",
       "      <td>X553SA-XX031T (N3050/4GB/500GB/W10)</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>8</td>\n",
       "      <td>Intel HD Graphics</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>2.20</td>\n",
       "      <td>3281148.0</td>\n",
       "      <td>0</td>\n",
       "      <td>100.454670</td>\n",
       "      <td>Other Intel Processor</td>\n",
       "      <td>500</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>325 rows × 16 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    Manufacturer                           Model Name            Category  \\\n",
       "0             HP    15-bs053od (i7-7500U/6GB/1TB/W10)            Notebook   \n",
       "1           Asus                     Rog GL753VE-DS74              Gaming   \n",
       "2           Dell                        Inspiron 7579  2 in 1 Convertible   \n",
       "3        Toshiba                    Portege Z30-C-1CV            Notebook   \n",
       "4         Lenovo                    IdeaPad 320-15ABR            Notebook   \n",
       "..           ...                                  ...                 ...   \n",
       "320       Lenovo                       Yoga 500-14ISK  2 in 1 Convertible   \n",
       "321       Lenovo                       Yoga 900-13ISK  2 in 1 Convertible   \n",
       "322       Lenovo                   IdeaPad 100S-14IBR            Notebook   \n",
       "323           HP  15-AC110nv (i7-6500U/6GB/1TB/Radeon            Notebook   \n",
       "324         Asus  X553SA-XX031T (N3050/4GB/500GB/W10)            Notebook   \n",
       "\n",
       "     RAM                         GPU Operating System  \\\n",
       "0      8       Intel HD Graphics 620          Windows   \n",
       "1      8  Nvidia GeForce GTX 1050 Ti          Windows   \n",
       "2      8       Intel HD Graphics 620          Windows   \n",
       "3     16       Intel HD Graphics 520          Windows   \n",
       "4      8              AMD Radeon 530          Windows   \n",
       "..   ...                         ...              ...   \n",
       "320    8       Intel HD Graphics 520          Windows   \n",
       "321    4       Intel HD Graphics 520          Windows   \n",
       "322    8           Intel HD Graphics          Windows   \n",
       "323    8          AMD Radeon R5 M330          Windows   \n",
       "324    8           Intel HD Graphics          Windows   \n",
       "\n",
       "    Operating System Version  Weight       Price  Ips         ppi  \\\n",
       "0                         10    2.04   5148468.0    0  100.454670   \n",
       "1                         10    2.99  15552108.0    0  127.335675   \n",
       "2                         10    2.19  11550708.0    1  141.211998   \n",
       "3                          7    1.20  10625940.0    0  165.632118   \n",
       "4                         10    2.20   4881708.0    0  141.211998   \n",
       "..                       ...     ...         ...  ...         ...   \n",
       "320                       10    1.80   5673096.0    1  157.350512   \n",
       "321                       10    1.30  13329108.0    1  276.053530   \n",
       "322                       10    1.50   2036268.0    0  111.935204   \n",
       "323                       10    2.19   6793488.0    0  100.454670   \n",
       "324                       10    2.20   3281148.0    0  100.454670   \n",
       "\n",
       "                 CPU Brand   HDD  SSD  Hybrid  Flash_Storage  \n",
       "0            Intel Core i7  1000    0       0              0  \n",
       "1            Intel Core i7  1000  256       0              0  \n",
       "2            Intel Core i7     0  512       0              0  \n",
       "3            Intel Core i5     0  128       0              0  \n",
       "4            AMD Processor     0  256       0              0  \n",
       "..                     ...   ...  ...     ...            ...  \n",
       "320          Intel Core i7     0  128       0              0  \n",
       "321          Intel Core i7     0  512       0              0  \n",
       "322  Other Intel Processor     0    0       0             64  \n",
       "323          Intel Core i7  1000    0       0              0  \n",
       "324  Other Intel Processor   500    0       0              0  \n",
       "\n",
       "[325 rows x 16 columns]"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_test[' Storage'] = df_test[' Storage'].astype(str).replace('\\.0', '', regex=True)\n",
    "df_test[\" Storage\"] = df_test[\" Storage\"].str.replace('GB', '')\n",
    "df_test[\" Storage\"] = df_test[\" Storage\"].str.replace('TB', '000')\n",
    "new = df_test[\" Storage\"].str.split(\"+\", n = 1, expand = True)\n",
    "\n",
    "df_test[\"first\"]= new[0]\n",
    "df_test[\"first\"]=df_test[\"first\"].str.strip()\n",
    "\n",
    "df_test[\"second\"]= new[1]\n",
    "\n",
    "df_test[\"Layer1HDD\"] = df_test[\"first\"].apply(lambda x: 1 if \"HDD\" in x else 0)\n",
    "df_test[\"Layer1SSD\"] = df_test[\"first\"].apply(lambda x: 1 if \"SSD\" in x else 0)\n",
    "df_test[\"Layer1Hybrid\"] = df_test[\"first\"].apply(lambda x: 1 if \"Hybrid\" in x else 0)\n",
    "df_test[\"Layer1Flash_Storage\"] = df_test[\"first\"].apply(lambda x: 1 if \"Flash Storage\" in x else 0)\n",
    "\n",
    "df_test['first'] = df_test['first'].str.replace(r'\\D', \"\",regex=True)\n",
    "\n",
    "df_test[\"second\"].fillna(\"0\", inplace = True)\n",
    "\n",
    "df_test[\"Layer2HDD\"] = df_test[\"second\"].apply(lambda x: 1 if \"HDD\" in x else 0)\n",
    "df_test[\"Layer2SSD\"] = df_test[\"second\"].apply(lambda x: 1 if \"SSD\" in x else 0)\n",
    "df_test[\"Layer2Hybrid\"] = df_test[\"second\"].apply(lambda x: 1 if \"Hybrid\" in x else 0)\n",
    "df_test[\"Layer2Flash_Storage\"] = df_test[\"second\"].apply(lambda x: 1 if \"Flash Storage\" in x else 0)\n",
    "\n",
    "df_test['second'] = df_test['second'].str.replace(r'\\D', '',regex=True)\n",
    "# df[\"first\"] = df[\"first\"].str.replace(r\"[^0-9]+\", \"\")\n",
    "# df[\"second\"] = df[\"second\"].str.replace(r\"[^0-9]+\", \"\")\n",
    "df_test[\"first\"] = df_test[\"first\"].astype(int)\n",
    "df_test[\"second\"] = df_test[\"second\"].astype(int)\n",
    "\n",
    "df_test[\"HDD\"]=(df_test[\"first\"]*df_test[\"Layer1HDD\"]+df_test[\"second\"]*df_test[\"Layer2HDD\"])\n",
    "df_test[\"SSD\"]=(df_test[\"first\"]*df_test[\"Layer1SSD\"]+df_test[\"second\"]*df_test[\"Layer2SSD\"])\n",
    "df_test[\"Hybrid\"]=(df_test[\"first\"]*df_test[\"Layer1Hybrid\"]+df_test[\"second\"]*df_test[\"Layer2Hybrid\"])\n",
    "df_test[\"Flash_Storage\"]=(df_test[\"first\"]*df_test[\"Layer1Flash_Storage\"]+df_test[\"second\"]*df_test[\"Layer2Flash_Storage\"])\n",
    "\n",
    "df_test.drop(columns=['first', 'second', 'Layer1HDD', 'Layer1SSD', 'Layer1Hybrid',\n",
    "       'Layer1Flash_Storage', 'Layer2HDD', 'Layer2SSD', 'Layer2Hybrid',\n",
    "       'Layer2Flash_Storage'],inplace=True)\n",
    "\n",
    "df_test.drop(columns=[\" Storage\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "RAM              0.764005\n",
       "Weight           0.224415\n",
       "Price            1.000000\n",
       "Ips              0.234718\n",
       "ppi              0.499022\n",
       "HDD             -0.088832\n",
       "SSD              0.670753\n",
       "Hybrid          -0.011725\n",
       "Flash_Storage   -0.037147\n",
       "Name: Price, dtype: float64"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.corr(numeric_only=True)['Price']\n",
    "#to find correlaion between every attribte with price"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.drop(columns=[\"Hybrid\",\"Flash_Storage\"],inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_test.drop(columns=[\"Hybrid\",\"Flash_Storage\"],inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "        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>Manufacturer</th>\n",
       "      <th>Model Name</th>\n",
       "      <th>Category</th>\n",
       "      <th>RAM</th>\n",
       "      <th>Storage</th>\n",
       "      <th>GPU</th>\n",
       "      <th>Operating System</th>\n",
       "      <th>Operating System Version</th>\n",
       "      <th>Weight</th>\n",
       "      <th>Price</th>\n",
       "      <th>Ips</th>\n",
       "      <th>ppi</th>\n",
       "      <th>CPU Brand</th>\n",
       "      <th>HDD</th>\n",
       "      <th>SSD</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>939</th>\n",
       "      <td>Dell</td>\n",
       "      <td>Alienware 17</td>\n",
       "      <td>Gaming</td>\n",
       "      <td>16</td>\n",
       "      <td>512 SSD +  1000 HDD</td>\n",
       "      <td>Nvidia GeForce GTX 1080</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>4.36</td>\n",
       "      <td>24524136.00</td>\n",
       "      <td>0</td>\n",
       "      <td>169.780899</td>\n",
       "      <td>Intel Core i7</td>\n",
       "      <td>1000</td>\n",
       "      <td>512</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>Apple</td>\n",
       "      <td>MacBook Air</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>8</td>\n",
       "      <td>256 Flash Storage</td>\n",
       "      <td>Intel HD Graphics 6000</td>\n",
       "      <td>Mac OS</td>\n",
       "      <td>X</td>\n",
       "      <td>1.35</td>\n",
       "      <td>8874216.00</td>\n",
       "      <td>0</td>\n",
       "      <td>127.677940</td>\n",
       "      <td>Intel Core i5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>920</th>\n",
       "      <td>Dell</td>\n",
       "      <td>Vostro 3568</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>4</td>\n",
       "      <td>1000 HDD</td>\n",
       "      <td>AMD Radeon R5 M420</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>2.18</td>\n",
       "      <td>6090931.08</td>\n",
       "      <td>0</td>\n",
       "      <td>100.454670</td>\n",
       "      <td>Intel Core i5</td>\n",
       "      <td>1000</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>531</th>\n",
       "      <td>Toshiba</td>\n",
       "      <td>Satellite Pro</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>8</td>\n",
       "      <td>500 HDD</td>\n",
       "      <td>Intel HD Graphics 620</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>2.00</td>\n",
       "      <td>7647120.00</td>\n",
       "      <td>1</td>\n",
       "      <td>141.211998</td>\n",
       "      <td>Intel Core i5</td>\n",
       "      <td>500</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Apple</td>\n",
       "      <td>MacBook Pro</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>8</td>\n",
       "      <td>128 SSD</td>\n",
       "      <td>Intel Iris Plus Graphics 640</td>\n",
       "      <td>macOS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.37</td>\n",
       "      <td>11912523.48</td>\n",
       "      <td>1</td>\n",
       "      <td>226.983005</td>\n",
       "      <td>Intel Core i5</td>\n",
       "      <td>0</td>\n",
       "      <td>128</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>466</th>\n",
       "      <td>Acer</td>\n",
       "      <td>Aspire 5</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>4</td>\n",
       "      <td>500 HDD</td>\n",
       "      <td>Nvidia GeForce GTX 940MX</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>2.20</td>\n",
       "      <td>4170348.00</td>\n",
       "      <td>0</td>\n",
       "      <td>100.454670</td>\n",
       "      <td>Intel Core i3</td>\n",
       "      <td>500</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>470</th>\n",
       "      <td>HP</td>\n",
       "      <td>Spectre x360</td>\n",
       "      <td>2 in 1 Convertible</td>\n",
       "      <td>8</td>\n",
       "      <td>512 SSD</td>\n",
       "      <td>Intel UHD Graphics 620</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>1.29</td>\n",
       "      <td>17775108.00</td>\n",
       "      <td>1</td>\n",
       "      <td>331.264236</td>\n",
       "      <td>Intel Core i7</td>\n",
       "      <td>0</td>\n",
       "      <td>512</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>865</th>\n",
       "      <td>HP</td>\n",
       "      <td>Probook 450</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>4</td>\n",
       "      <td>500 HDD</td>\n",
       "      <td>Intel HD Graphics 520</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>2.07</td>\n",
       "      <td>8091720.00</td>\n",
       "      <td>0</td>\n",
       "      <td>141.211998</td>\n",
       "      <td>Intel Core i5</td>\n",
       "      <td>500</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>277</th>\n",
       "      <td>Acer</td>\n",
       "      <td>Aspire A515-51G</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>8</td>\n",
       "      <td>1000 HDD</td>\n",
       "      <td>Nvidia GeForce MX130</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>2.20</td>\n",
       "      <td>6624540.00</td>\n",
       "      <td>1</td>\n",
       "      <td>141.211998</td>\n",
       "      <td>Intel Core i7</td>\n",
       "      <td>1000</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>761</th>\n",
       "      <td>Dell</td>\n",
       "      <td>Latitude 7280</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>16</td>\n",
       "      <td>256 SSD</td>\n",
       "      <td>Intel HD Graphics 620</td>\n",
       "      <td>Windows</td>\n",
       "      <td>10</td>\n",
       "      <td>1.18</td>\n",
       "      <td>16530228.00</td>\n",
       "      <td>0</td>\n",
       "      <td>176.232574</td>\n",
       "      <td>Intel Core i7</td>\n",
       "      <td>0</td>\n",
       "      <td>256</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Manufacturer       Model Name            Category  RAM  \\\n",
       "939         Dell     Alienware 17              Gaming   16   \n",
       "34         Apple      MacBook Air           Ultrabook    8   \n",
       "920         Dell      Vostro 3568            Notebook    4   \n",
       "531      Toshiba    Satellite Pro            Notebook    8   \n",
       "0          Apple      MacBook Pro           Ultrabook    8   \n",
       "466         Acer         Aspire 5            Notebook    4   \n",
       "470           HP     Spectre x360  2 in 1 Convertible    8   \n",
       "865           HP      Probook 450            Notebook    4   \n",
       "277         Acer  Aspire A515-51G            Notebook    8   \n",
       "761         Dell    Latitude 7280           Ultrabook   16   \n",
       "\n",
       "                 Storage                           GPU Operating System  \\\n",
       "939  512 SSD +  1000 HDD       Nvidia GeForce GTX 1080          Windows   \n",
       "34     256 Flash Storage        Intel HD Graphics 6000           Mac OS   \n",
       "920             1000 HDD            AMD Radeon R5 M420          Windows   \n",
       "531              500 HDD         Intel HD Graphics 620          Windows   \n",
       "0                128 SSD  Intel Iris Plus Graphics 640            macOS   \n",
       "466              500 HDD      Nvidia GeForce GTX 940MX          Windows   \n",
       "470              512 SSD        Intel UHD Graphics 620          Windows   \n",
       "865              500 HDD         Intel HD Graphics 520          Windows   \n",
       "277             1000 HDD          Nvidia GeForce MX130          Windows   \n",
       "761              256 SSD         Intel HD Graphics 620          Windows   \n",
       "\n",
       "    Operating System Version  Weight        Price  Ips         ppi  \\\n",
       "939                       10    4.36  24524136.00    0  169.780899   \n",
       "34                         X    1.35   8874216.00    0  127.677940   \n",
       "920                       10    2.18   6090931.08    0  100.454670   \n",
       "531                       10    2.00   7647120.00    1  141.211998   \n",
       "0                         10    1.37  11912523.48    1  226.983005   \n",
       "466                       10    2.20   4170348.00    0  100.454670   \n",
       "470                       10    1.29  17775108.00    1  331.264236   \n",
       "865                       10    2.07   8091720.00    0  141.211998   \n",
       "277                       10    2.20   6624540.00    1  141.211998   \n",
       "761                       10    1.18  16530228.00    0  176.232574   \n",
       "\n",
       "         CPU Brand   HDD  SSD  \n",
       "939  Intel Core i7  1000  512  \n",
       "34   Intel Core i5     0    0  \n",
       "920  Intel Core i5  1000    0  \n",
       "531  Intel Core i5   500    0  \n",
       "0    Intel Core i5     0  128  \n",
       "466  Intel Core i3   500    0  \n",
       "470  Intel Core i7     0  512  \n",
       "865  Intel Core i5   500    0  \n",
       "277  Intel Core i7  1000    0  \n",
       "761  Intel Core i7     0  256  "
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.sample(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.drop(columns=[\" Storage\"],inplace=True)\n",
    "df_test.drop(columns=[\" Storage\"], inplace=True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "GPU\n",
       "Intel HD Graphics 620             225\n",
       "Intel HD Graphics 520              98\n",
       "Intel UHD Graphics 620             66\n",
       "Nvidia GeForce GTX 1050            57\n",
       "AMD Radeon 530                     37\n",
       "                                 ... \n",
       "Nvidia GeForce GTX 960<U+039C>      1\n",
       "Intel Graphics 620                  1\n",
       "Nvidia GeForce GTX 960              1\n",
       "AMD Radeon R5 520                   1\n",
       "AMD Radeon R9 M385                  1\n",
       "Name: count, Length: 98, dtype: int64"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['GPU'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['GPU Brand'] = df['GPU'].apply(lambda x:x.split()[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Manufacturer</th>\n",
       "      <th>Model Name</th>\n",
       "      <th>Category</th>\n",
       "      <th>RAM</th>\n",
       "      <th>GPU</th>\n",
       "      <th>Operating System</th>\n",
       "      <th>Operating System Version</th>\n",
       "      <th>Weight</th>\n",
       "      <th>Price</th>\n",
       "      <th>Ips</th>\n",
       "      <th>ppi</th>\n",
       "      <th>CPU Brand</th>\n",
       "      <th>HDD</th>\n",
       "      <th>SSD</th>\n",
       "      <th>GPU Brand</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Apple</td>\n",
       "      <td>MacBook Pro</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>8</td>\n",
       "      <td>Intel Iris Plus Graphics 640</td>\n",
       "      <td>macOS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.37</td>\n",
       "      <td>11912523.48</td>\n",
       "      <td>1</td>\n",
       "      <td>226.983005</td>\n",
       "      <td>Intel Core i5</td>\n",
       "      <td>0</td>\n",
       "      <td>128</td>\n",
       "      <td>Intel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Apple</td>\n",
       "      <td>Macbook Air</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>8</td>\n",
       "      <td>Intel HD Graphics 6000</td>\n",
       "      <td>macOS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.34</td>\n",
       "      <td>7993374.48</td>\n",
       "      <td>0</td>\n",
       "      <td>127.677940</td>\n",
       "      <td>Intel Core i5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Intel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>HP</td>\n",
       "      <td>250 G6</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>8</td>\n",
       "      <td>Intel HD Graphics 620</td>\n",
       "      <td>No OS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.86</td>\n",
       "      <td>5112900.00</td>\n",
       "      <td>0</td>\n",
       "      <td>141.211998</td>\n",
       "      <td>Intel Core i5</td>\n",
       "      <td>0</td>\n",
       "      <td>256</td>\n",
       "      <td>Intel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Apple</td>\n",
       "      <td>MacBook Pro</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>16</td>\n",
       "      <td>AMD Radeon Pro 455</td>\n",
       "      <td>macOS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.83</td>\n",
       "      <td>22563005.40</td>\n",
       "      <td>1</td>\n",
       "      <td>220.534624</td>\n",
       "      <td>Intel Core i7</td>\n",
       "      <td>0</td>\n",
       "      <td>512</td>\n",
       "      <td>AMD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Apple</td>\n",
       "      <td>MacBook Pro</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>8</td>\n",
       "      <td>Intel Iris Plus Graphics 650</td>\n",
       "      <td>macOS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.37</td>\n",
       "      <td>16037611.20</td>\n",
       "      <td>1</td>\n",
       "      <td>226.983005</td>\n",
       "      <td>Intel Core i5</td>\n",
       "      <td>0</td>\n",
       "      <td>256</td>\n",
       "      <td>Intel</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Manufacturer   Model Name   Category  RAM                           GPU  \\\n",
       "0        Apple  MacBook Pro  Ultrabook    8  Intel Iris Plus Graphics 640   \n",
       "1        Apple  Macbook Air  Ultrabook    8        Intel HD Graphics 6000   \n",
       "2           HP       250 G6   Notebook    8         Intel HD Graphics 620   \n",
       "3        Apple  MacBook Pro  Ultrabook   16            AMD Radeon Pro 455   \n",
       "4        Apple  MacBook Pro  Ultrabook    8  Intel Iris Plus Graphics 650   \n",
       "\n",
       "  Operating System Operating System Version  Weight        Price  Ips  \\\n",
       "0            macOS                       10    1.37  11912523.48    1   \n",
       "1            macOS                       10    1.34   7993374.48    0   \n",
       "2            No OS                       10    1.86   5112900.00    0   \n",
       "3            macOS                       10    1.83  22563005.40    1   \n",
       "4            macOS                       10    1.37  16037611.20    1   \n",
       "\n",
       "          ppi      CPU Brand  HDD  SSD GPU Brand  \n",
       "0  226.983005  Intel Core i5    0  128     Intel  \n",
       "1  127.677940  Intel Core i5    0    0     Intel  \n",
       "2  141.211998  Intel Core i5    0  256     Intel  \n",
       "3  220.534624  Intel Core i7    0  512       AMD  \n",
       "4  226.983005  Intel Core i5    0  256     Intel  "
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_test['GPU Brand'] = df_test['GPU'].apply(lambda x:x.split()[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "GPU Brand\n",
       "Intel     525\n",
       "Nvidia    310\n",
       "AMD       142\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"GPU Brand\"].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "GPU Brand\n",
       "Intel     197\n",
       "Nvidia     89\n",
       "AMD        38\n",
       "ARM         1\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_test[\"GPU Brand\"].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df[df['GPU Brand'] != 'ARM']\n",
    "df_test = df_test[df_test['GPU Brand'] != 'ARM']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(x=df['GPU Brand'],y=df['Price'],estimator=np.median)\n",
    "plt.xticks(rotation='vertical')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.drop(columns=['GPU'],inplace=True)\n",
    "df_test.drop(columns=['GPU'],inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Manufacturer</th>\n",
       "      <th>Model Name</th>\n",
       "      <th>Category</th>\n",
       "      <th>RAM</th>\n",
       "      <th>Operating System</th>\n",
       "      <th>Operating System Version</th>\n",
       "      <th>Weight</th>\n",
       "      <th>Price</th>\n",
       "      <th>Ips</th>\n",
       "      <th>ppi</th>\n",
       "      <th>CPU Brand</th>\n",
       "      <th>HDD</th>\n",
       "      <th>SSD</th>\n",
       "      <th>GPU Brand</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Apple</td>\n",
       "      <td>MacBook Pro</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>8</td>\n",
       "      <td>macOS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.37</td>\n",
       "      <td>11912523.48</td>\n",
       "      <td>1</td>\n",
       "      <td>226.983005</td>\n",
       "      <td>Intel Core i5</td>\n",
       "      <td>0</td>\n",
       "      <td>128</td>\n",
       "      <td>Intel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Apple</td>\n",
       "      <td>Macbook Air</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>8</td>\n",
       "      <td>macOS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.34</td>\n",
       "      <td>7993374.48</td>\n",
       "      <td>0</td>\n",
       "      <td>127.677940</td>\n",
       "      <td>Intel Core i5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Intel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>HP</td>\n",
       "      <td>250 G6</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>8</td>\n",
       "      <td>No OS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.86</td>\n",
       "      <td>5112900.00</td>\n",
       "      <td>0</td>\n",
       "      <td>141.211998</td>\n",
       "      <td>Intel Core i5</td>\n",
       "      <td>0</td>\n",
       "      <td>256</td>\n",
       "      <td>Intel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Apple</td>\n",
       "      <td>MacBook Pro</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>16</td>\n",
       "      <td>macOS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.83</td>\n",
       "      <td>22563005.40</td>\n",
       "      <td>1</td>\n",
       "      <td>220.534624</td>\n",
       "      <td>Intel Core i7</td>\n",
       "      <td>0</td>\n",
       "      <td>512</td>\n",
       "      <td>AMD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Apple</td>\n",
       "      <td>MacBook Pro</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>8</td>\n",
       "      <td>macOS</td>\n",
       "      <td>10</td>\n",
       "      <td>1.37</td>\n",
       "      <td>16037611.20</td>\n",
       "      <td>1</td>\n",
       "      <td>226.983005</td>\n",
       "      <td>Intel Core i5</td>\n",
       "      <td>0</td>\n",
       "      <td>256</td>\n",
       "      <td>Intel</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Manufacturer   Model Name   Category  RAM Operating System  \\\n",
       "0        Apple  MacBook Pro  Ultrabook    8            macOS   \n",
       "1        Apple  Macbook Air  Ultrabook    8            macOS   \n",
       "2           HP       250 G6   Notebook    8            No OS   \n",
       "3        Apple  MacBook Pro  Ultrabook   16            macOS   \n",
       "4        Apple  MacBook Pro  Ultrabook    8            macOS   \n",
       "\n",
       "  Operating System Version  Weight        Price  Ips         ppi  \\\n",
       "0                       10    1.37  11912523.48    1  226.983005   \n",
       "1                       10    1.34   7993374.48    0  127.677940   \n",
       "2                       10    1.86   5112900.00    0  141.211998   \n",
       "3                       10    1.83  22563005.40    1  220.534624   \n",
       "4                       10    1.37  16037611.20    1  226.983005   \n",
       "\n",
       "       CPU Brand  HDD  SSD GPU Brand  \n",
       "0  Intel Core i5    0  128     Intel  \n",
       "1  Intel Core i5    0    0     Intel  \n",
       "2  Intel Core i5    0  256     Intel  \n",
       "3  Intel Core i7    0  512       AMD  \n",
       "4  Intel Core i5    0  256     Intel  "
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Operating System\n",
       "Windows      837\n",
       "No OS         52\n",
       "Linux         48\n",
       "Chrome OS     22\n",
       "macOS         13\n",
       "Mac OS         4\n",
       "Android        1\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"Operating System\"].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(x= df[\"Operating System\"],y=df[\"Price\"])\n",
    "plt.xticks(rotation=\"vertical\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.drop(columns=[\"Operating System Version\",\"Model Name\"], inplace=True)\n",
    "df_test.drop(columns=[\"Operating System Version\",\"Model Name\"], inplace=True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(df.corr(numeric_only=True))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Manufacturer</th>\n",
       "      <th>Category</th>\n",
       "      <th>RAM</th>\n",
       "      <th>Operating System</th>\n",
       "      <th>Weight</th>\n",
       "      <th>Price</th>\n",
       "      <th>Ips</th>\n",
       "      <th>ppi</th>\n",
       "      <th>CPU Brand</th>\n",
       "      <th>HDD</th>\n",
       "      <th>SSD</th>\n",
       "      <th>GPU Brand</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Apple</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>8</td>\n",
       "      <td>macOS</td>\n",
       "      <td>1.37</td>\n",
       "      <td>11912523.48</td>\n",
       "      <td>1</td>\n",
       "      <td>226.983005</td>\n",
       "      <td>Intel Core i5</td>\n",
       "      <td>0</td>\n",
       "      <td>128</td>\n",
       "      <td>Intel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Apple</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>8</td>\n",
       "      <td>macOS</td>\n",
       "      <td>1.34</td>\n",
       "      <td>7993374.48</td>\n",
       "      <td>0</td>\n",
       "      <td>127.677940</td>\n",
       "      <td>Intel Core i5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Intel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>HP</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>8</td>\n",
       "      <td>No OS</td>\n",
       "      <td>1.86</td>\n",
       "      <td>5112900.00</td>\n",
       "      <td>0</td>\n",
       "      <td>141.211998</td>\n",
       "      <td>Intel Core i5</td>\n",
       "      <td>0</td>\n",
       "      <td>256</td>\n",
       "      <td>Intel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Apple</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>16</td>\n",
       "      <td>macOS</td>\n",
       "      <td>1.83</td>\n",
       "      <td>22563005.40</td>\n",
       "      <td>1</td>\n",
       "      <td>220.534624</td>\n",
       "      <td>Intel Core i7</td>\n",
       "      <td>0</td>\n",
       "      <td>512</td>\n",
       "      <td>AMD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Apple</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>8</td>\n",
       "      <td>macOS</td>\n",
       "      <td>1.37</td>\n",
       "      <td>16037611.20</td>\n",
       "      <td>1</td>\n",
       "      <td>226.983005</td>\n",
       "      <td>Intel Core i5</td>\n",
       "      <td>0</td>\n",
       "      <td>256</td>\n",
       "      <td>Intel</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Manufacturer   Category  RAM Operating System  Weight        Price  Ips  \\\n",
       "0        Apple  Ultrabook    8            macOS    1.37  11912523.48    1   \n",
       "1        Apple  Ultrabook    8            macOS    1.34   7993374.48    0   \n",
       "2           HP   Notebook    8            No OS    1.86   5112900.00    0   \n",
       "3        Apple  Ultrabook   16            macOS    1.83  22563005.40    1   \n",
       "4        Apple  Ultrabook    8            macOS    1.37  16037611.20    1   \n",
       "\n",
       "          ppi      CPU Brand  HDD  SSD GPU Brand  \n",
       "0  226.983005  Intel Core i5    0  128     Intel  \n",
       "1  127.677940  Intel Core i5    0    0     Intel  \n",
       "2  141.211998  Intel Core i5    0  256     Intel  \n",
       "3  220.534624  Intel Core i7    0  512       AMD  \n",
       "4  226.983005  Intel Core i5    0  256     Intel  "
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Manufacturer</th>\n",
       "      <th>Category</th>\n",
       "      <th>RAM</th>\n",
       "      <th>Operating System</th>\n",
       "      <th>Weight</th>\n",
       "      <th>Price</th>\n",
       "      <th>Ips</th>\n",
       "      <th>ppi</th>\n",
       "      <th>CPU Brand</th>\n",
       "      <th>HDD</th>\n",
       "      <th>SSD</th>\n",
       "      <th>GPU Brand</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>HP</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>8</td>\n",
       "      <td>Windows</td>\n",
       "      <td>2.04</td>\n",
       "      <td>5148468.0</td>\n",
       "      <td>0</td>\n",
       "      <td>100.454670</td>\n",
       "      <td>Intel Core i7</td>\n",
       "      <td>1000</td>\n",
       "      <td>0</td>\n",
       "      <td>Intel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Asus</td>\n",
       "      <td>Gaming</td>\n",
       "      <td>8</td>\n",
       "      <td>Windows</td>\n",
       "      <td>2.99</td>\n",
       "      <td>15552108.0</td>\n",
       "      <td>0</td>\n",
       "      <td>127.335675</td>\n",
       "      <td>Intel Core i7</td>\n",
       "      <td>1000</td>\n",
       "      <td>256</td>\n",
       "      <td>Nvidia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Dell</td>\n",
       "      <td>2 in 1 Convertible</td>\n",
       "      <td>8</td>\n",
       "      <td>Windows</td>\n",
       "      <td>2.19</td>\n",
       "      <td>11550708.0</td>\n",
       "      <td>1</td>\n",
       "      <td>141.211998</td>\n",
       "      <td>Intel Core i7</td>\n",
       "      <td>0</td>\n",
       "      <td>512</td>\n",
       "      <td>Intel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Toshiba</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>16</td>\n",
       "      <td>Windows</td>\n",
       "      <td>1.20</td>\n",
       "      <td>10625940.0</td>\n",
       "      <td>0</td>\n",
       "      <td>165.632118</td>\n",
       "      <td>Intel Core i5</td>\n",
       "      <td>0</td>\n",
       "      <td>128</td>\n",
       "      <td>Intel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Lenovo</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>8</td>\n",
       "      <td>Windows</td>\n",
       "      <td>2.20</td>\n",
       "      <td>4881708.0</td>\n",
       "      <td>0</td>\n",
       "      <td>141.211998</td>\n",
       "      <td>AMD Processor</td>\n",
       "      <td>0</td>\n",
       "      <td>256</td>\n",
       "      <td>AMD</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Manufacturer            Category  RAM Operating System  Weight       Price  \\\n",
       "0           HP            Notebook    8          Windows    2.04   5148468.0   \n",
       "1         Asus              Gaming    8          Windows    2.99  15552108.0   \n",
       "2         Dell  2 in 1 Convertible    8          Windows    2.19  11550708.0   \n",
       "3      Toshiba            Notebook   16          Windows    1.20  10625940.0   \n",
       "4       Lenovo            Notebook    8          Windows    2.20   4881708.0   \n",
       "\n",
       "   Ips         ppi      CPU Brand   HDD  SSD GPU Brand  \n",
       "0    0  100.454670  Intel Core i7  1000    0     Intel  \n",
       "1    0  127.335675  Intel Core i7  1000  256    Nvidia  \n",
       "2    1  141.211998  Intel Core i7     0  512     Intel  \n",
       "3    0  165.632118  Intel Core i5     0  128     Intel  \n",
       "4    0  141.211998  AMD Processor     0  256       AMD  "
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_test.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [],
   "source": [
    "data= pd.concat([df, df_test], ignore_index= True, join= 'inner') # the parameter ignore index reset the index of the generated dataframe.\n",
    "X = data.drop(columns=['Price'])\n",
    "y = np.log(data['Price'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Manufacturer</th>\n",
       "      <th>Category</th>\n",
       "      <th>RAM</th>\n",
       "      <th>Operating System</th>\n",
       "      <th>Weight</th>\n",
       "      <th>Ips</th>\n",
       "      <th>ppi</th>\n",
       "      <th>CPU Brand</th>\n",
       "      <th>HDD</th>\n",
       "      <th>SSD</th>\n",
       "      <th>GPU Brand</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Apple</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>8</td>\n",
       "      <td>macOS</td>\n",
       "      <td>1.37</td>\n",
       "      <td>1</td>\n",
       "      <td>226.983005</td>\n",
       "      <td>Intel Core i5</td>\n",
       "      <td>0</td>\n",
       "      <td>128</td>\n",
       "      <td>Intel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Apple</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>8</td>\n",
       "      <td>macOS</td>\n",
       "      <td>1.34</td>\n",
       "      <td>0</td>\n",
       "      <td>127.677940</td>\n",
       "      <td>Intel Core i5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Intel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>HP</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>8</td>\n",
       "      <td>No OS</td>\n",
       "      <td>1.86</td>\n",
       "      <td>0</td>\n",
       "      <td>141.211998</td>\n",
       "      <td>Intel Core i5</td>\n",
       "      <td>0</td>\n",
       "      <td>256</td>\n",
       "      <td>Intel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Apple</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>16</td>\n",
       "      <td>macOS</td>\n",
       "      <td>1.83</td>\n",
       "      <td>1</td>\n",
       "      <td>220.534624</td>\n",
       "      <td>Intel Core i7</td>\n",
       "      <td>0</td>\n",
       "      <td>512</td>\n",
       "      <td>AMD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Apple</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>8</td>\n",
       "      <td>macOS</td>\n",
       "      <td>1.37</td>\n",
       "      <td>1</td>\n",
       "      <td>226.983005</td>\n",
       "      <td>Intel Core i5</td>\n",
       "      <td>0</td>\n",
       "      <td>256</td>\n",
       "      <td>Intel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1296</th>\n",
       "      <td>Lenovo</td>\n",
       "      <td>2 in 1 Convertible</td>\n",
       "      <td>8</td>\n",
       "      <td>Windows</td>\n",
       "      <td>1.80</td>\n",
       "      <td>1</td>\n",
       "      <td>157.350512</td>\n",
       "      <td>Intel Core i7</td>\n",
       "      <td>0</td>\n",
       "      <td>128</td>\n",
       "      <td>Intel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1297</th>\n",
       "      <td>Lenovo</td>\n",
       "      <td>2 in 1 Convertible</td>\n",
       "      <td>4</td>\n",
       "      <td>Windows</td>\n",
       "      <td>1.30</td>\n",
       "      <td>1</td>\n",
       "      <td>276.053530</td>\n",
       "      <td>Intel Core i7</td>\n",
       "      <td>0</td>\n",
       "      <td>512</td>\n",
       "      <td>Intel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1298</th>\n",
       "      <td>Lenovo</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>8</td>\n",
       "      <td>Windows</td>\n",
       "      <td>1.50</td>\n",
       "      <td>0</td>\n",
       "      <td>111.935204</td>\n",
       "      <td>Other Intel Processor</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Intel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1299</th>\n",
       "      <td>HP</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>8</td>\n",
       "      <td>Windows</td>\n",
       "      <td>2.19</td>\n",
       "      <td>0</td>\n",
       "      <td>100.454670</td>\n",
       "      <td>Intel Core i7</td>\n",
       "      <td>1000</td>\n",
       "      <td>0</td>\n",
       "      <td>AMD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1300</th>\n",
       "      <td>Asus</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>8</td>\n",
       "      <td>Windows</td>\n",
       "      <td>2.20</td>\n",
       "      <td>0</td>\n",
       "      <td>100.454670</td>\n",
       "      <td>Other Intel Processor</td>\n",
       "      <td>500</td>\n",
       "      <td>0</td>\n",
       "      <td>Intel</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1301 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Manufacturer            Category  RAM Operating System  Weight  Ips  \\\n",
       "0           Apple           Ultrabook    8            macOS    1.37    1   \n",
       "1           Apple           Ultrabook    8            macOS    1.34    0   \n",
       "2              HP            Notebook    8            No OS    1.86    0   \n",
       "3           Apple           Ultrabook   16            macOS    1.83    1   \n",
       "4           Apple           Ultrabook    8            macOS    1.37    1   \n",
       "...           ...                 ...  ...              ...     ...  ...   \n",
       "1296       Lenovo  2 in 1 Convertible    8          Windows    1.80    1   \n",
       "1297       Lenovo  2 in 1 Convertible    4          Windows    1.30    1   \n",
       "1298       Lenovo            Notebook    8          Windows    1.50    0   \n",
       "1299           HP            Notebook    8          Windows    2.19    0   \n",
       "1300         Asus            Notebook    8          Windows    2.20    0   \n",
       "\n",
       "             ppi              CPU Brand   HDD  SSD GPU Brand  \n",
       "0     226.983005          Intel Core i5     0  128     Intel  \n",
       "1     127.677940          Intel Core i5     0    0     Intel  \n",
       "2     141.211998          Intel Core i5     0  256     Intel  \n",
       "3     220.534624          Intel Core i7     0  512       AMD  \n",
       "4     226.983005          Intel Core i5     0  256     Intel  \n",
       "...          ...                    ...   ...  ...       ...  \n",
       "1296  157.350512          Intel Core i7     0  128     Intel  \n",
       "1297  276.053530          Intel Core i7     0  512     Intel  \n",
       "1298  111.935204  Other Intel Processor     0    0     Intel  \n",
       "1299  100.454670          Intel Core i7  1000    0       AMD  \n",
       "1300  100.454670  Other Intel Processor   500    0     Intel  \n",
       "\n",
       "[1301 rows x 11 columns]"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "X_train,X_test,y_train,y_test = train_test_split(X,y,test_size=0.2,random_state=2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.compose import ColumnTransformer\n",
    "from sklearn.pipeline import Pipeline\n",
    "from sklearn.preprocessing import OneHotEncoder\n",
    "from sklearn.metrics import r2_score,mean_absolute_error\n",
    "from sklearn.linear_model import LinearRegression,Ridge,Lasso\n",
    "from sklearn.neighbors import KNeighborsRegressor\n",
    "from sklearn.tree import DecisionTreeRegressor\n",
    "from sklearn.ensemble import RandomForestRegressor,GradientBoostingRegressor,AdaBoostRegressor,ExtraTreesRegressor\n",
    "from sklearn.svm import SVR\n",
    "from xgboost import XGBRegressor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Manufacturer</th>\n",
       "      <th>Category</th>\n",
       "      <th>RAM</th>\n",
       "      <th>Operating System</th>\n",
       "      <th>Weight</th>\n",
       "      <th>Ips</th>\n",
       "      <th>ppi</th>\n",
       "      <th>CPU Brand</th>\n",
       "      <th>HDD</th>\n",
       "      <th>SSD</th>\n",
       "      <th>GPU Brand</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>550</th>\n",
       "      <td>Lenovo</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>4</td>\n",
       "      <td>Windows</td>\n",
       "      <td>2.20</td>\n",
       "      <td>0</td>\n",
       "      <td>141.211998</td>\n",
       "      <td>Intel Core i3</td>\n",
       "      <td>0</td>\n",
       "      <td>128</td>\n",
       "      <td>Intel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>980</th>\n",
       "      <td>Toshiba</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>16</td>\n",
       "      <td>Windows</td>\n",
       "      <td>1.20</td>\n",
       "      <td>0</td>\n",
       "      <td>165.632118</td>\n",
       "      <td>Intel Core i5</td>\n",
       "      <td>0</td>\n",
       "      <td>128</td>\n",
       "      <td>Intel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>860</th>\n",
       "      <td>Lenovo</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>8</td>\n",
       "      <td>Windows</td>\n",
       "      <td>2.30</td>\n",
       "      <td>1</td>\n",
       "      <td>141.211998</td>\n",
       "      <td>Intel Core i5</td>\n",
       "      <td>1000</td>\n",
       "      <td>0</td>\n",
       "      <td>Intel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>Asus</td>\n",
       "      <td>Gaming</td>\n",
       "      <td>8</td>\n",
       "      <td>Windows</td>\n",
       "      <td>2.45</td>\n",
       "      <td>0</td>\n",
       "      <td>141.211998</td>\n",
       "      <td>AMD Processor</td>\n",
       "      <td>1000</td>\n",
       "      <td>0</td>\n",
       "      <td>AMD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>418</th>\n",
       "      <td>Dell</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>8</td>\n",
       "      <td>Windows</td>\n",
       "      <td>2.14</td>\n",
       "      <td>0</td>\n",
       "      <td>100.454670</td>\n",
       "      <td>Intel Core i5</td>\n",
       "      <td>1000</td>\n",
       "      <td>0</td>\n",
       "      <td>Intel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>466</th>\n",
       "      <td>Acer</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>4</td>\n",
       "      <td>Windows</td>\n",
       "      <td>2.20</td>\n",
       "      <td>0</td>\n",
       "      <td>100.454670</td>\n",
       "      <td>Intel Core i3</td>\n",
       "      <td>500</td>\n",
       "      <td>0</td>\n",
       "      <td>Nvidia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>299</th>\n",
       "      <td>Asus</td>\n",
       "      <td>Ultrabook</td>\n",
       "      <td>16</td>\n",
       "      <td>Windows</td>\n",
       "      <td>1.63</td>\n",
       "      <td>0</td>\n",
       "      <td>141.211998</td>\n",
       "      <td>Intel Core i7</td>\n",
       "      <td>0</td>\n",
       "      <td>512</td>\n",
       "      <td>Nvidia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>493</th>\n",
       "      <td>Acer</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>8</td>\n",
       "      <td>Windows</td>\n",
       "      <td>2.20</td>\n",
       "      <td>0</td>\n",
       "      <td>100.454670</td>\n",
       "      <td>AMD Processor</td>\n",
       "      <td>1000</td>\n",
       "      <td>0</td>\n",
       "      <td>AMD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>527</th>\n",
       "      <td>Lenovo</td>\n",
       "      <td>Notebook</td>\n",
       "      <td>8</td>\n",
       "      <td>No OS</td>\n",
       "      <td>2.20</td>\n",
       "      <td>0</td>\n",
       "      <td>100.454670</td>\n",
       "      <td>Intel Core i3</td>\n",
       "      <td>2000</td>\n",
       "      <td>0</td>\n",
       "      <td>Nvidia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1192</th>\n",
       "      <td>Dell</td>\n",
       "      <td>2 in 1 Convertible</td>\n",
       "      <td>8</td>\n",
       "      <td>Windows</td>\n",
       "      <td>1.60</td>\n",
       "      <td>1</td>\n",
       "      <td>165.632118</td>\n",
       "      <td>Intel Core i5</td>\n",
       "      <td>0</td>\n",
       "      <td>256</td>\n",
       "      <td>Intel</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1040 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Manufacturer            Category  RAM Operating System  Weight  Ips  \\\n",
       "550        Lenovo            Notebook    4          Windows    2.20    0   \n",
       "980       Toshiba            Notebook   16          Windows    1.20    0   \n",
       "860        Lenovo            Notebook    8          Windows    2.30    1   \n",
       "90           Asus              Gaming    8          Windows    2.45    0   \n",
       "418          Dell            Notebook    8          Windows    2.14    0   \n",
       "...           ...                 ...  ...              ...     ...  ...   \n",
       "466          Acer            Notebook    4          Windows    2.20    0   \n",
       "299          Asus           Ultrabook   16          Windows    1.63    0   \n",
       "493          Acer            Notebook    8          Windows    2.20    0   \n",
       "527        Lenovo            Notebook    8            No OS    2.20    0   \n",
       "1192         Dell  2 in 1 Convertible    8          Windows    1.60    1   \n",
       "\n",
       "             ppi      CPU Brand   HDD  SSD GPU Brand  \n",
       "550   141.211998  Intel Core i3     0  128     Intel  \n",
       "980   165.632118  Intel Core i5     0  128     Intel  \n",
       "860   141.211998  Intel Core i5  1000    0     Intel  \n",
       "90    141.211998  AMD Processor  1000    0       AMD  \n",
       "418   100.454670  Intel Core i5  1000    0     Intel  \n",
       "...          ...            ...   ...  ...       ...  \n",
       "466   100.454670  Intel Core i3   500    0    Nvidia  \n",
       "299   141.211998  Intel Core i7     0  512    Nvidia  \n",
       "493   100.454670  AMD Processor  1000    0       AMD  \n",
       "527   100.454670  Intel Core i3  2000    0    Nvidia  \n",
       "1192  165.632118  Intel Core i5     0  256     Intel  \n",
       "\n",
       "[1040 rows x 11 columns]"
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_train"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Using Random Forest"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "R2 score 0.8682001965951774\n",
      "MAE 0.1625021390776729\n"
     ]
    }
   ],
   "source": [
    "step1 = ColumnTransformer(transformers=[\n",
    "    ('col_tnf',OneHotEncoder(sparse=False,drop='first'),[0,1,3,7,10])\n",
    "],remainder='passthrough')\n",
    "\n",
    "step2 = RandomForestRegressor(n_estimators=125, random_state=3,max_samples=0.64,\n",
    "                              max_features=0.74,\n",
    "                              max_depth=75, criterion=\"friedman_mse\")\n",
    "\n",
    "pipe = Pipeline([\n",
    "    ('step1',step1),\n",
    "    ('step2',step2), \n",
    "])\n",
    "\n",
    "pipe.fit(X_train,y_train)\n",
    "\n",
    "y_pred = pipe.predict(X_test)\n",
    "\n",
    "print('R2 score',r2_score(y_test,y_pred))\n",
    "print('MAE',mean_absolute_error(y_test,y_pred))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "GPU Brand\n",
       "Intel     722\n",
       "Nvidia    399\n",
       "AMD       180\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[\"GPU Brand\"].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pickle\n",
    "\n",
    "pickle.dump(data,open('data.pkl','wb'))\n",
    "pickle.dump(pipe,open('pipe.pkl','wb'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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