Exploratory_Data_Analysis-Laptop_Pricing.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Importing Required Libraries\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from scipy import stats\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Import the dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "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>Unnamed: 0.1</th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>Manufacturer</th>\n",
       "      <th>Category</th>\n",
       "      <th>GPU</th>\n",
       "      <th>OS</th>\n",
       "      <th>CPU_core</th>\n",
       "      <th>Screen_Size_inch</th>\n",
       "      <th>CPU_frequency</th>\n",
       "      <th>RAM_GB</th>\n",
       "      <th>Storage_GB_SSD</th>\n",
       "      <th>Weight_pounds</th>\n",
       "      <th>Price</th>\n",
       "      <th>Price-binned</th>\n",
       "      <th>Screen-Full_HD</th>\n",
       "      <th>Screen-IPS_panel</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Acer</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>14.0</td>\n",
       "      <td>0.551724</td>\n",
       "      <td>8</td>\n",
       "      <td>256</td>\n",
       "      <td>3.52800</td>\n",
       "      <td>978</td>\n",
       "      <td>Low</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Dell</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>15.6</td>\n",
       "      <td>0.689655</td>\n",
       "      <td>4</td>\n",
       "      <td>256</td>\n",
       "      <td>4.85100</td>\n",
       "      <td>634</td>\n",
       "      <td>Low</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>Dell</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>15.6</td>\n",
       "      <td>0.931034</td>\n",
       "      <td>8</td>\n",
       "      <td>256</td>\n",
       "      <td>4.85100</td>\n",
       "      <td>946</td>\n",
       "      <td>Low</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>Dell</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>13.3</td>\n",
       "      <td>0.551724</td>\n",
       "      <td>8</td>\n",
       "      <td>128</td>\n",
       "      <td>2.69010</td>\n",
       "      <td>1244</td>\n",
       "      <td>Low</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>HP</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>15.6</td>\n",
       "      <td>0.620690</td>\n",
       "      <td>8</td>\n",
       "      <td>256</td>\n",
       "      <td>4.21155</td>\n",
       "      <td>837</td>\n",
       "      <td>Low</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0.1  Unnamed: 0 Manufacturer  Category  GPU  OS  CPU_core  \\\n",
       "0             0           0         Acer         4    2   1         5   \n",
       "1             1           1         Dell         3    1   1         3   \n",
       "2             2           2         Dell         3    1   1         7   \n",
       "3             3           3         Dell         4    2   1         5   \n",
       "4             4           4           HP         4    2   1         7   \n",
       "\n",
       "   Screen_Size_inch  CPU_frequency  RAM_GB  Storage_GB_SSD  Weight_pounds  \\\n",
       "0              14.0       0.551724       8             256        3.52800   \n",
       "1              15.6       0.689655       4             256        4.85100   \n",
       "2              15.6       0.931034       8             256        4.85100   \n",
       "3              13.3       0.551724       8             128        2.69010   \n",
       "4              15.6       0.620690       8             256        4.21155   \n",
       "\n",
       "   Price Price-binned  Screen-Full_HD  Screen-IPS_panel  \n",
       "0    978          Low               0                 1  \n",
       "1    634          Low               1                 0  \n",
       "2    946          Low               1                 0  \n",
       "3   1244          Low               0                 1  \n",
       "4    837          Low               1                 0  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# The functions below will download the dataset\n",
    "\n",
    "import asyncio\n",
    "import aiohttp\n",
    "\n",
    "async def download(url, filename):\n",
    "    async with aiohttp.ClientSession() as session:\n",
    "        async with session.get(url) as response:\n",
    "            if response.status == 200:\n",
    "                with open(filename, 'wb') as f:\n",
    "                    f.write(await response.read())\n",
    "                    \n",
    "                    \n",
    "file_path= \"https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBMDeveloperSkillsNetwork-DA0101EN-Coursera/laptop_pricing_dataset_mod2.csv\"\n",
    "\n",
    "await download(file_path, \"laptops.csv\")\n",
    "file_name=\"laptops.csv\"\n",
    "\n",
    "# Import the file to a pandas dataframe.\n",
    "df = pd.read_csv(file_name, header=0)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Task 1 - Visualize individual feature patterns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Continuous valued features\n",
    "\n",
    "##### Generate regression plots for each of the parameters \"CPU_frequency\", \"Screen_Size_inch\" and \"Weight_pounds\" against \"Price\". Also, print the value of correlation of each feature with \"Price\"."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.0, 3974.15)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# CPU_frequency plot\n",
    "\n",
    "sns.regplot(x=\"CPU_frequency\", y=\"Price\", data=df)\n",
    "plt.ylim(0,)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.0, 3974.15)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Screen_Size_inch plot\n",
    "\n",
    "sns.regplot(x=\"Screen_Size_inch\", y=\"Price\", data=df)\n",
    "plt.ylim(0,)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.0, 3974.15)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Weight_pounds plot\n",
    "\n",
    "sns.regplot(x=\"Weight_pounds\", y=\"Price\", data=df)\n",
    "plt.ylim(0,)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Correlation of Price and CPU_frequency is                 CPU_frequency     Price\n",
      "CPU_frequency       1.000000  0.366666\n",
      "Price               0.366666  1.000000\n",
      "Correlation of Price and Screen_Size_inch is                    Screen_Size_inch     Price\n",
      "Screen_Size_inch          1.000000 -0.110644\n",
      "Price                    -0.110644  1.000000\n",
      "Correlation of Price and Weight_pounds is                 Weight_pounds     Price\n",
      "Weight_pounds       1.000000 -0.050312\n",
      "Price              -0.050312  1.000000\n"
     ]
    }
   ],
   "source": [
    "# Correlation values of the three attributes with Price\n",
    "\n",
    "for param in [\"CPU_frequency\", \"Screen_Size_inch\",\"Weight_pounds\"]:\n",
    "    print(f\"Correlation of Price and {param} is \", df[[param,\"Price\"]].corr())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Categorical features\n",
    "\n",
    "##### Generate Box plots for the different feature that hold categorical values. These features would be \"Category\", \"GPU\", \"OS\", \"CPU_core\", \"RAM_GB\", \"Storage_GB_SSD\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Category', ylabel='Price'>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Category Box plot\n",
    "\n",
    "sns.boxplot(x=\"Category\", y=\"Price\", data=df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='GPU', ylabel='Price'>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# GPU Box plot\n",
    "\n",
    "sns.boxplot(x=\"GPU\", y=\"Price\", data=df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='OS', ylabel='Price'>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# OS Box plot\n",
    "\n",
    "sns.boxplot(x=\"OS\", y=\"Price\", data=df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='CPU_core', ylabel='Price'>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# CPU_core Box plot\n",
    "\n",
    "sns.boxplot(x=\"CPU_core\", y=\"Price\", data=df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='RAM_GB', ylabel='Price'>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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RAAAwPQIRAAAwPQIRAAAwPQIRAAAwPQIRAAAwPQIRAAAwPQIRAAAwPQIRAAAwPQIRAAAwPQIRAAAwPQIRAAAwPQIRAAAwvSZGFwAA16qiokIlJSVGl3FFMTExCgoKMroMAFeJQASgwSkpKdG4ceOMLuOKsrOz1b59e6PLAHCVCEQAGpyYmBhlZ2d75FhHjx7VnDlz9MQTTyg2NtYjx5S+rRFAw0EgAtDgBAUFeXz0JTY2lhEdwMSYVA0AAEyPQAQAAEyPQAQAAEyPQAQAAEyPQAQAAEyPQAQAAEyPQAQAAEyPQAQAAEyPQAQAAEyPQAQAAEyPQAQAAEyPQAQAAEyPQAQAAEyPQAQAAEyPQAQAAEzP0EA0d+5c3XrrrWrRooXCw8N1zz336MCBA259evfuLR8fH7fX+PHj3fqUlJQoJSVFTZs2VXh4uKZOnaoLFy649dm2bZtuvvlmBQYGql27dlq+fHldnx4AAGggDA1E27dvV1pamnbt2qXc3FxVVVWpf//+OnPmjFu/hx9+WMePH3e95s2b52qrrq5WSkqKzp8/r507d2rFihVavny5nnrqKVef4uJipaSkqE+fPiooKNCkSZP00EMPaePGjfV2rgAAwHs1MfLNN2zY4La9fPlyhYeHa8+ePUpKSnLtb9q0qaxW6yWPsWnTJu3fv18ffPCBIiIidNNNN+npp5/W9OnTNXPmTAUEBGjp0qWKi4vT/PnzJUmdOnXSjh07tGDBAiUnJ9fdCQIAgAbBq+YQlZeXS5LCwsLc9ufk5KhVq1bq0qWLZsyYobNnz7ra8vPzlZCQoIiICNe+5ORkORwOFRUVufr069fP7ZjJycnKz8+/ZB2VlZVyOBxuLwAA0HgZOkL0XTU1NZo0aZJ69eqlLl26uPY/8MADio2NVVRUlAoLCzV9+nQdOHBA7733niTJbre7hSFJrm273X7FPg6HQ+fOnVNwcLBb29y5c5WZmenxcwQAAN7JawJRWlqa9u3bpx07drjtHzdunOvvCQkJioyMVN++fXX48GG1bdu2TmqZMWOGpkyZ4tp2OByKjo6uk/cCAADG84pLZhMnTtTatWu1detWtW7d+op9e/ToIUk6dOiQJMlqtaq0tNStT+127byjy/UJCQm5aHRIkgIDAxUSEuL2AgAAjZehgcjpdGrixIlatWqVtmzZori4uB/8moKCAklSZGSkJMlms2nv3r06ceKEq09ubq5CQkLUuXNnV5/Nmze7HSc3N1c2m81DZwIAABoyQwNRWlqa3njjDa1cuVItWrSQ3W6X3W7XuXPnJEmHDx/W008/rT179ujvf/+7/vrXv2rUqFFKSkpSYmKiJKl///7q3LmzRo4cqc8//1wbN25Uenq60tLSFBgYKEkaP368jhw5omnTpunLL79UVlaW3n77bU2ePNmwcwcAAN7D0EC0ZMkSlZeXq3fv3oqMjHS93nrrLUlSQECAPvjgA/Xv318dO3bUY489piFDhmjNmjWuY/j5+Wnt2rXy8/OTzWbTiBEjNGrUKM2aNcvVJy4uTuvWrVNubq66du2q+fPn6+WXX+aWewAAIMngSdVOp/OK7dHR0dq+ffsPHic2Nlbr16+/Yp/evXvrs88+u6b6AACAOXjFpGoAAAAjEYgAAIDpEYgAAIDpEYgAAIDpEYgAAIDpEYgAAIDpEYgAAIDpec3DXQEAMCPfcyeNLqHBqYvvGYEIAAADBRfnGV0CRCACAMBQ5+KSVBMcanQZDYrvuZMeD5IEIgAADFQTHKqaZq2MLsP0mFQNAABMj0AEAABMj0AEAABM70cFovPnz+vAgQO6cOGCp+oBAACod9cViM6ePauxY8eqadOmio+PV0lJiSTpkUce0bPPPuvRAgEAAOradQWiGTNm6PPPP9e2bdsUFBTk2t+vXz+99dZbHisOAACgPlzXbferV6/WW2+9pZ49e8rHx8e1Pz4+XocPH/ZYcQAAAPXhukaIvvnmG4WHh1+0/8yZM24BCQAAoCG4rkB0yy23aN26da7t2hD08ssvy2azeaYyAACAenJdl8yeeeYZDRw4UPv379eFCxe0cOFC7d+/Xzt37tT27ds9XSMAAECduq4Rottvv10FBQW6cOGCEhIStGnTJoWHhys/P1/du3f3dI0AAAB16rqfZda2bVu99NJLnqwFAADAENc1QrR+/Xpt3Ljxov0bN27U+++//6OLAgAAqE/XFYgef/xxVVdXX7Tf6XTq8ccf/9FFAQAA1KfrCkRfffWVOnfufNH+jh076tChQz+6KAAAgPp0XYHIYrHoyJEjF+0/dOiQmjVr9qOLAgAAqE/XFYjuvvtuTZo0yW1V6kOHDumxxx7Tr371K48VBwAAUB+uKxDNmzdPzZo1U8eOHRUXF6e4uDh16tRJLVu21B//+EdP1wgAAFCnruu2e4vFop07dyo3N1eff/65goODlZiYqKSkJE/XBwAAUOeuex0iHx8f9e/fX/379/dkPQCAOnbo0CEVFxd75Fhnz571+od6t23bVk2bNvXIseLi4tSuXTuPHAve5aoD0aJFizRu3DgFBQVp0aJFV+z7+9///kcXBgCoGy+88II+//xzo8tokLp27aqFCxcaXQbqwFUHogULFmj48OEKCgrSggULLtvPx8eHQAQAXuyRRx5hhOg6xcXFeeQ48D5XHYi++z+Pp/5HAgDUv3bt2nHZB/iea77LrKqqSm3bttUXX3xRF/UAAADUu2sORP7+/qqoqKiLWgAAAAxxXesQpaWl6bnnntOFCxc8XQ8AAEC9u67b7j/++GNt3rxZmzZtUkJCwkWP63jvvfc8UhwAAEB9uK5AFBoaqiFDhni6FgAAAENcUyCqqanR888/r4MHD+r8+fO68847NXPmTAUHB9dVfQAAAHXumuYQzZkzR3/4wx/UvHlz/fSnP9WiRYuUlpZWV7UBAADUi2sKRK+99pqysrK0ceNGrV69WmvWrFFOTo5qamqu683nzp2rW2+9VS1atFB4eLjuueceHThwwK1PRUWF0tLS1LJlSzVv3lxDhgxRaWmpW5+SkhKlpKSoadOmCg8P19SpUy+a8L1t2zbdfPPNCgwMVLt27bR8+fLrqhkAADQ+1xSISkpKdNddd7m2+/XrJx8fHx07duy63nz79u1KS0vTrl27lJubq6qqKvXv319nzpxx9Zk8ebLWrFmjd955R9u3b9exY8d07733utqrq6uVkpKi8+fPa+fOnVqxYoWWL1+up556ytWnuLhYKSkp6tOnjwoKCjRp0iQ99NBD2rhx43XVDQAAGpdrmkN04cIFBQUFue3z9/dXVVXVdb35hg0b3LaXL1+u8PBw7dmzR0lJSSovL9eyZcu0cuVK3XnnnZKkV199VZ06ddKuXbvUs2dPbdq0Sfv379cHH3ygiIgI3XTTTXr66ac1ffp0zZw5UwEBAVq6dKni4uI0f/58SVKnTp20Y8cOLViwQMnJyRfVVVlZqcrKSte2w+G4rvMDAAANwzUFIqfTqQcffFCBgYGufRUVFRo/frzbrffXe9t9eXm5JCksLEyStGfPHlVVValfv36uPh07dlRMTIzy8/PVs2dP5efnKyEhQREREa4+ycnJSk1NVVFRkbp166b8/Hy3Y9T2mTRp0iXrmDt3rjIzM6/rHAAAQMNzTYFo9OjRF+0bMWKERwqpqanRpEmT1KtXL3Xp0kWSZLfbFRAQoNDQULe+ERERstvtrj7fDUO17bVtV+rjcDh07ty5i+6SmzFjhqZMmeLadjgcio6O/vEnCQAAvNI1BaJXX321rupQWlqa9u3bpx07dtTZe1ytwMBAt1EwAADQuF3Xozs8beLEiVq7dq22bt2q1q1bu/ZbrVadP39eJ0+edOtfWloqq9Xq6vP9u85qt3+oT0hICGsoAQAAYwOR0+nUxIkTtWrVKm3ZskVxcXFu7d27d5e/v782b97s2nfgwAGVlJTIZrNJkmw2m/bu3asTJ064+uTm5iokJESdO3d29fnuMWr71B4DAACY23U9usNT0tLStHLlSv3P//yPWrRo4ZrzY7FYFBwcLIvForFjx2rKlCkKCwtTSEiIHnnkEdlsNvXs2VOS1L9/f3Xu3FkjR47UvHnzZLfblZ6errS0NNdlr/Hjx+vFF1/UtGnTNGbMGG3ZskVvv/221q1bZ9i5AwAA72HoCNGSJUtUXl6u3r17KzIy0vV66623XH0WLFigQYMGaciQIUpKSpLVanW7i83Pz09r166Vn5+fbDabRowYoVGjRmnWrFmuPnFxcVq3bp1yc3PVtWtXzZ8/Xy+//PIlb7kHAADmY+gIkdPp/ME+QUFBWrx4sRYvXnzZPrGxsVq/fv0Vj9O7d2999tln11wjAABo/LxiUjUAAICRCEQAAMD0CEQAAMD0CEQAAMD0CEQAAMD0CEQAAMD0CEQAAMD0CEQAAMD0CEQAAMD0CEQAAMD0DH10BwDzKC0tVXl5udFlXOTo0aNuf3oji8WiiIgIo8sAGjUCEYA6V1paqhEjR6nqfKXRpVzWnDlzjC7hsvwDAvXG668RioA6RCACUOfKy8tVdb5S59r8QjVBFqPLaVB8K8qlI9tVXl5OIALqEIEIQL2pCbKoplkro8sAgIswqRoAAJgegQgAAJgegQgAAJgegQgAAJgegQgAAJged5kBAGAg3wrvW7DU29XF94xABACAASwWi/wDAqUj240upUHyDwiUxeK5dc0IRAAAGCAiIkJvvP6aVz7SRvr2cTZz5szRE088odjYWKPLuYinH2lDIAIAwCARERFevwJ5bGys2rdvb3QZdY5J1QAAwPQIRAAAwPS4ZGYS1dXVKiwsVFlZmcLCwpSYmCg/Pz+jywIAwCsQiEwgLy9PWVlZstvtrn1Wq1UTJkxQUlKSgZUBAOAdCESNXF5enjIyMtSzZ0/dd999CgwMVGVlpT766CNlZGQoMzOTUAQAMD0CUSNWXV2trKwstW/fXsXFxcrPz3e1Wa1WtW/fXkuWLFGvXr24fAYAMDUmVTdihYWFstvtOnjwoNq0aaPFixdr/fr1Wrx4sdq0aaODBw/q+PHjKiwsNLpUAAAMRSBqxP73f/9XkvTzn/9cs2fPVnx8vJo2bar4+HjNnj1bP//5z936AQBgVgSiRuzkyZOSpDvuuEO+vu4fta+vr26//Xa3fgAAmBWBqBELDQ2VJH344Yeqqalxa6upqdGOHTvc+gEAYFYEokasVatWkqTdu3crPT1dRUVFOnv2rIqKipSenq7du3e79QMAwKy4y6wRS0xMlNVqlcVi0eHDh5WWluZqs1qt6tChgxwOhxITEw2sEgAA4xGIGjE/Pz9NmDDBtQ7RsGHD3NYh2rVrlzIzM7nlHgBgegSiRi4pKUmZmZnKyspyW4coMjKSRRkBAPg/BCITSEpKUq9evXiWGQAAl0EgMgk/Pz9169bN6DIAAPBK3GUGAABMz9BAlJeXp8GDBysqKko+Pj5avXq1W/uDDz4oHx8ft9eAAQPc+pSVlWn48OEKCQlRaGioxo4dq9OnT7v1KSws1B133KGgoCBFR0dr3rx5dX1qAACgATE0EJ05c0Zdu3bV4sWLL9tnwIABOn78uOv1X//1X27tw4cPV1FRkXJzc7V27Vrl5eVp3LhxrnaHw6H+/fsrNjZWe/bs0fPPP6+ZM2cqOzu7zs4LAAA0LIbOIRo4cKAGDhx4xT6BgYGyWq2XbPviiy+0YcMGffzxx7rlllskSS+88ILuuusu/fGPf1RUVJRycnJ0/vx5vfLKKwoICFB8fLwKCgr0pz/9yS04fVdlZaUqKytd2w6H4zrPEAAANAReP4do27ZtCg8PV4cOHZSamqp//etfrrb8/HyFhoa6wpAk9evXT76+vq5VmPPz85WUlKSAgABXn+TkZB04cED//ve/L/mec+fOlcVicb2io6Pr6OwAAIA38OpANGDAAL322mvavHmznnvuOW3fvl0DBw5UdXW1JMlutys8PNzta5o0aaKwsDDZ7XZXn4iICLc+tdu1fb5vxowZKi8vd72+/vprT58aAADwIl592/2wYcNcf09ISFBiYqLatm2rbdu2qW/fvnX2voGBgQoMDKyz4wMAAO/i1SNE39emTRu1atVKhw4dkvTt87hOnDjh1ufChQsqKytzzTuyWq0qLS1161O7fbm5SQAAwFwaVCD6xz/+oX/961+KjIyUJNlsNp08eVJ79uxx9dmyZYtqamrUo0cPV5+8vDxVVVW5+uTm5qpDhw76yU9+Ur8nAAAAvJKhgej06dMqKChQQUGBJKm4uFgFBQUqKSnR6dOnNXXqVO3atUt///vftXnzZt19991q166dkpOTJUmdOnXSgAED9PDDD+ujjz7S3/72N02cOFHDhg1TVFSUJOmBBx5QQECAxo4dq6KiIr311ltauHChpkyZYtRpG6K6ulqfffaZNm/erM8++8w1DwsAABg8h+iTTz5Rnz59XNu1IWX06NFasmSJCgsLtWLFCp08eVJRUVHq37+/nn76abf5PTk5OZo4caL69u0rX19fDRkyRIsWLXK1WywWbdq0SWlpaerevbtatWqlp5566rK33DdGeXl5ysrKcptEbrVaNWHCBB7uCgCADA5EvXv3ltPpvGz7xo0bf/AYYWFhWrly5RX7JCYm6sMPP7zm+hqDvLw8ZWRkyGaz6cknn1RcXJyKi4uVk5OjjIwMnngPAIAa2BwiXJvq6mplZWXJZrMpMzNT58+fV35+vs6fP6/MzEzZbDYtWbKEy2cAANPz6tvu8eMUFhbKbrdr8ODBGjly5EWXzAYNGqSdO3eqsLBQ3bp1M7BSAACMRSBqxMrKyiRJL730km677baLLpm9/PLLbv2AuuZ77qTRJTQ4fM+A+kEgasRCQ0Mlfbuo5ezZs+Xr++0V0vj4eM2ePVuPPvqo9u7d6+oH1LXg4jyjSwCASyIQAag35+KSVBMcanQZDYrvuZMESaAeEIgasZMnT0qS9u3bp/T0dA0fPtztktm+ffvc+gF1rSY4VDXNWhldBgBchEDUiIWFhUmSHnroIa1Zs0ZpaWmutsjISD300EN66aWXXP0AADArAlEjlpiYKKvVqqKiIr3++uvat2+fysrKFBYWpi5duigjI0ORkZFKTEw0ulQAAAzFOkSNmJ+fnyZMmKD8/HxlZGQoICBANptNAQEBysjIUH5+vlJTU+Xn52d0qQAAGIoRokYuKSlJmZmZysrKuuiSGatUAwDwLQKRCSQlJalXr14qLCx0XTJLTExkZAgAgP9DIDIJPz8/VqMGAOAymEMEAABMj0AEAABMj0AEAABMj0AEAABMj0AEAABMj0AEAABMj0AEAABMj0AEAABMj0AEAABMj0AEAABMj0AEAABMj0AEAABMj0AEAABMj0AEAABMr4nRBQAwD9+KcqNLaHD4ngH1g0AEoM5ZLBb5BwRKR7YbXUqD5B8QKIvFYnQZQKNGIAJQ5yIiIvTG66+pvNz7RjuOHj2qOXPm6IknnlBsbKzR5VySxWJRRESE0WXAy1VUVKikpMRjxzt69Kjbn54SExOjoKAgjx7TEwhEAOpFRESEV/9Sj42NVfv27Y0uA7huJSUlGjdunMePO2fOHI8eLzs72yv/XyMQeTFPp/264q1pHwDMJCYmRtnZ2UaX8YNiYmKMLuGSCERerK7Svqd5a9oHADMJCgriZ/GPQCDyYp5O+3U1V8Jb0z4AAFeLQOTF6irtM1cCAAB3LMwIAABMj0AEAABMj0AEAABMj0AEAABMj0AEAABMj0AEAABMz9BAlJeXp8GDBysqKko+Pj5avXq1W7vT6dRTTz2lyMhIBQcHq1+/fvrqq6/c+pSVlWn48OEKCQlRaGioxo4dq9OnT7v1KSws1B133KGgoCBFR0dr3rx5dX1qAACgATE0EJ05c0Zdu3bV4sWLL9k+b948LVq0SEuXLtXu3bvVrFkzJScnq6KiwtVn+PDhKioqUm5urtauXau8vDy31Z0dDof69++v2NhY7dmzR88//7xmzpzZIJY3BwAA9cPQhRkHDhyogQMHXrLN6XTqz3/+s9LT03X33XdLkl577TVFRERo9erVGjZsmL744gtt2LBBH3/8sW655RZJ0gsvvKC77rpLf/zjHxUVFaWcnBydP39er7zyigICAhQfH6+CggL96U9/ahCPxYB34LlyANC4ee1K1cXFxbLb7erXr59rn8ViUY8ePZSfn69hw4YpPz9foaGhrjAkSf369ZOvr692796tX//618rPz1dSUpICAgJcfZKTk/Xcc8/p3//+t37yk59c9N6VlZWqrKx0bTscjjo6SzQUPFcOABo3rw1EdrtdkhQREeG2PyIiwtVmt9sVHh7u1t6kSROFhYW59YmLi7voGLVtlwpEc+fOVWZmpmdOBI0Cz5UDgMbNawORkWbMmKEpU6a4th0Oh6Kjow2sCEbjuXIA0Lh57W33VqtVklRaWuq2v7S01NVmtVp14sQJt/YLFy6orKzMrc+ljvHd9/i+wMBAhYSEuL0AAEDj5bWBKC4uTlarVZs3b3btczgc2r17t2w2myTJZrPp5MmT2rNnj6vPli1bVFNTox49erj65OXlqaqqytUnNzdXHTp0uOTlMgAAYD6GXjI7ffq0Dh065NouLi5WQUGBwsLCFBMTo0mTJmn27Nm68cYbFRcXpyeffFJRUVG65557JEmdOnXSgAED9PDDD2vp0qWqqqrSxIkTNWzYMEVFRUmSHnjgAWVmZmrs2LGaPn269u3bp4ULF2rBggV1ck6lpaUqLy+vk2P/WEePHnX70xtZLJaL5o0BAFDXDA1En3zyifr06eParp23M3r0aC1fvlzTpk3TmTNnNG7cOJ08eVK33367NmzY4HZbcU5OjiZOnKi+ffvK19dXQ4YM0aJFi1ztFotFmzZtUlpamrp3765WrVrpqaeeqpM7hkpLSzVi5ChVna/84c4GmjNnjtElXJZ/QKDeeP01QhEAoF4ZGoh69+4tp9N52XYfHx/NmjVLs2bNumyfsLAwrVy58orvk5iYqA8//PC667xa5eXlqjpfqXNtfqGaIEudv19j41tRLh3ZrvLycgIRAKBecZdZHagJsqimWSujywAAAFfJaydVAwAA1BcCEQAAMD0umdUB33MnjS6hQeL7BgAwCoGoDgQX5xldAgAAuAYEojpwLi5JNcGhRpfR4PieO+nxMOmt60KxJhQAeBcCUR2oCQ7lLjMv0BDWhWJNKADwDgQiNFqsC3X9WBMKgNkQiNDosS4UAOCHcNs9AAAwPQIRAAAwPS6ZodFjfaNrx/cMgNkQiNDosS4UAOCHEIjQ6LEu1LWrizWhAMCbEYjQ6LEuFADghzCpGgAAmB6BCAAAmB6XzNDo+VZ437PMvB3fMwBmQyBCo2WxWOQfECgd2W50KQ2Sf0CgLBYeeQLAHAhEdYB/XV8fT3/fIiIi9Mbrr3nkafeVlZWy2+0eqOpbx48f1yuvvKIxY8YoMjLSY8e1Wq0KDAz0yLF42j0AMyEQeRAjEj+ep0clIiIiPPJL/eDBg3XyZPpXXnnFo8fLzs5W+/btPXpMADADApEHeXJEoi4cPXpUc+bM0RNPPKHY2Fijy7kkbx2ViImJUXZ2ttFl/KCYmBijSwCABolA5GGeGpGoS7GxsYwiXKOgoCC+ZwDQiHHbPQAAMD1GiAA0OBUVFSopKfHIsY4ePer2p6fExMQoKCjIo8cEUHcIRAAanJKSEo0bN86jx/T0pHkmuAMNC4EIQIPTECa5M8EdaFgIRAAaHCa5A/A0JlUDAADTIxABAADTIxABAADTIxABAADTIxABAADTIxABAADTIxABAADTIxABAADTIxABAADTIxABAADTIxABAADTIxABAADT8+qHu86cOVOZmZlu+zp06KAvv/xSklRRUaHHHntMb775piorK5WcnKysrCxFRES4+peUlCg1NVVbt25V8+bNNXr0aM2dO1dNmnj1qUv69vxKSko8dryjR4+6/ekpMTExCgoK8ugxAQCoT16fCuLj4/XBBx+4tr8bZCZPnqx169bpnXfekcVi0cSJE3Xvvffqb3/7mySpurpaKSkpslqt2rlzp44fP65Ro0bJ399fzzzzTL2fy7UqKSnRuHHjPH7cOXPmePR42dnZPHkcANCg+TidTqfRRVzOzJkztXr1ahUUFFzUVl5erhtuuEErV67U0KFDJUlffvmlOnXqpPz8fPXs2VPvv/++Bg0apGPHjrlGjZYuXarp06frm2++UUBAwFXV4XA4ZLFYVF5erpCQEI+d3w/x9AhRXWGECADgja7l97fXjxB99dVXioqKUlBQkGw2m+bOnauYmBjt2bNHVVVV6tevn6tvx44dFRMT4wpE+fn5SkhIcLuElpycrNTUVBUVFalbt26XfM/KykpVVla6th0OR92d4BUEBQUx8gIAQD3w6knVPXr00PLly7VhwwYtWbJExcXFuuOOO3Tq1CnZ7XYFBAQoNDTU7WsiIiJkt9slSXa73S0M1bbXtl3O3LlzZbFYXK/o6GjPnhgAAPAqXj1CNHDgQNffExMT1aNHD8XGxurtt99WcHBwnb3vjBkzNGXKFNe2w+EgFAEA0Ih59QjR94WGhqp9+/Y6dOiQrFarzp8/r5MnT7r1KS0tldVqlSRZrVaVlpZe1F7bdjmBgYEKCQlxewEAgMarQQWi06dP6/Dhw4qMjFT37t3l7++vzZs3u9oPHDigkpIS2Ww2SZLNZtPevXt14sQJV5/c3FyFhISoc+fO9V4/AADwTl59yew///M/NXjwYMXGxurYsWPKyMiQn5+f7r//flksFo0dO1ZTpkxRWFiYQkJC9Mgjj8hms6lnz56SpP79+6tz584aOXKk5s2bJ7vdrvT0dKWlpSkwMNDgswMAAN7CqwPRP/7xD91///3617/+pRtuuEG33367du3apRtuuEGStGDBAvn6+mrIkCFuCzPW8vPz09q1a5WamiqbzaZmzZpp9OjRmjVrllGnBAAAvJBXr0PkLYxahwgAAFy/a/n93aDmEAEAANQFAhEAADA9AhEAADA9AhEAADA9AhEAADA9AhEAADA9r16HyFvUrkxg1FPvAQDAtav9vX01KwwRiK7CqVOnJIkHvAIA0ACdOnVKFovlin1YmPEq1NTU6NixY2rRooV8fHyMLue6ORwORUdH6+uvv2aBSYPxWXgPPgvvwufhPRrDZ+F0OnXq1ClFRUXJ1/fKs4QYIboKvr6+at26tdFleExISEiD/Y+7seGz8B58Ft6Fz8N7NPTP4odGhmoxqRoAAJgegQgAAJgegchEAgMDlZGRocDAQKNLMT0+C+/BZ+Fd+Dy8h9k+CyZVAwAA02OECAAAmB6BCAAAmB6BCAAAmB6BCAAAmB6ByGSeffZZ+fj4aNKkSUaXYlr//Oc/NWLECLVs2VLBwcFKSEjQJ598YnRZplNdXa0nn3xScXFxCg4OVtu2bfX0009f1TOP8OPk5eVp8ODBioqKko+Pj1avXu1qq6qq0vTp05WQkKBmzZopKipKo0aN0rFjx4wruBG70mdR64svvtCvfvUrWSwWNWvWTLfeeqtKSkrqv9g6RiAykY8//lh/+ctflJiYaHQppvXvf/9bvXr1kr+/v95//33t379f8+fP109+8hOjSzOd5557TkuWLNGLL76oL774Qs8995zmzZunF154wejSGr0zZ86oa9euWrx48UVtZ8+e1aeffqonn3xSn376qd577z0dOHBAv/rVrwyotPG70mchSYcPH9btt9+ujh07atu2bSosLNSTTz6poKCgeq607nHbvUmcPn1aN998s7KysjR79mzddNNN+vOf/2x0Wabz+OOP629/+5s+/PBDo0sxvUGDBikiIkLLli1z7RsyZIiCg4P1xhtvGFiZufj4+GjVqlW65557Ltvn448/1s9//nMdPXpUMTEx9VecyVzqsxg2bJj8/f31+uuvG1dYPWGEyCTS0tKUkpKifv36GV2Kqf31r3/VLbfcot/85jcKDw9Xt27d9NJLLxldlinddttt2rx5sw4ePChJ+vzzz7Vjxw4NHDjQ4MrwfeXl5fLx8VFoaKjRpZhKTU2N1q1bp/bt2ys5OVnh4eHq0aPHJS+rNQYEIhN488039emnn2ru3LlGl2J6R44c0ZIlS3TjjTdq48aNSk1N1e9//3utWLHC6NJM5/HHH9ewYcPUsWNH+fv7q1u3bpo0aZKGDx9udGn4joqKCk2fPl33339/g37AaEN04sQJnT59Ws8++6wGDBigTZs26de//rXuvfdebd++3ejyPI6n3TdyX3/9tR599FHl5uY2ymu+DU1NTY1uueUWPfPMM5Kkbt26ad++fVq6dKlGjx5tcHXm8vbbbysnJ0crV65UfHy8CgoKNGnSJEVFRfFZeImqqir99re/ldPp1JIlS4wux3RqamokSXfffbcmT54sSbrpppu0c+dOLV26VL/4xS+MLM/jCESN3J49e3TixAndfPPNrn3V1dXKy8vTiy++qMrKSvn5+RlYoblERkaqc+fObvs6deqkd99916CKzGvq1KmuUSJJSkhI0NGjRzV37lwCkReoDUNHjx7Vli1bGB0yQKtWrdSkSZNL/szasWOHQVXVHQJRI9e3b1/t3bvXbd9//Md/qGPHjpo+fTphqJ716tVLBw4ccNt38OBBxcbGGlSReZ09e1a+vu6zBvz8/Fz/KoZxasPQV199pa1bt6ply5ZGl2RKAQEBuvXWW03zM4tA1Mi1aNFCXbp0cdvXrFkztWzZ8qL9qHuTJ0/WbbfdpmeeeUa//e1v9dFHHyk7O1vZ2dlGl2Y6gwcP1pw5cxQTE6P4+Hh99tln+tOf/qQxY8YYXVqjd/r0aR06dMi1XVxcrIKCAoWFhSkyMlJDhw7Vp59+qrVr16q6ulp2u12SFBYWpoCAAKPKbpSu9FnExMRo6tSpuu+++5SUlKQ+ffpow4YNWrNmjbZt22Zc0XXFCdP5xS9+4Xz00UeNLsO01qxZ4+zSpYszMDDQ2bFjR2d2drbRJZmSw+FwPvroo86YmBhnUFCQs02bNs4nnnjCWVlZaXRpjd7WrVudki56jR492llcXHzJNknOrVu3Gl16o3Olz6LWsmXLnO3atXMGBQU5u3bt6ly9erVxBdch1iECAACmx233AADA9AhEAADA9AhEAADA9AhEAADA9AhEAADA9AhEAADA9AhEAADA9AhEAADA9AhEAADA9AhEALzSgw8+KB8fH/n4+Mjf319xcXGaNm2aKioq3Pr94x//UEBAwGWfzVd7jF27drntr6ysVMuWLeXj43NNz2XaunWrBg0apBtuuEFBQUFq27at7rvvPuXl5bn6bNu2zfW+Pj4+Cg4OVnx8PM+sA7wYgQiA1xowYICOHz+uI0eOaMGCBfrLX/6ijIwMtz7Lly/Xb3/7WzkcDu3evfuSx4mOjtarr77qtm/VqlVq3rz5NdWTlZWlvn37qmXLlnrrrbd04MABrVq1SrfddpsmT558Uf8DBw7o+PHj2r9/v373u98pNTVVmzdvvqb3BFA/CEQAvFZgYKCsVquio6N1zz33qF+/fsrNzXW1O51Ovfrqqxo5cqQeeOABLVu27JLHGT16tN58802dO3fOte+VV17R6NGjr7qWkpISTZo0SZMmTdKKFSt05513KjY2VomJiXr00Uf1ySefXPQ14eHhslqtiouL0+9//3vFxcXp008/vYbvAID6QiAC0CDs27dPO3fuVEBAgGvf1q1bdfbsWfXr108jRozQm2++qTNnzlz0td27d9fPfvYzvfvuu5K+DTd5eXkaOXLkVb//u+++q6qqKk2bNu2S7T4+Ppf9WqfTqQ0bNqikpEQ9evS46vcEUH8IRAC81tq1a9W8eXMFBQUpISFBJ06c0NSpU13ty5Yt07Bhw+Tn56cuXbqoTZs2eueddy55rDFjxuiVV16R9O1ltrvuuks33HDDVddy8OBBhYSEyGq1uva9++67at68ueu1d+9et69p3bq1mjdvroCAAKWkpCgjI0NJSUnX8i0AUE+aGF0AAFxOnz59tGTJEp05c0YLFixQkyZNNGTIEEnSyZMn9d5772nHjh2u/iNGjNCyZcv04IMPXnSsESNG6PHHH9eRI0e0fPlyLVq06Jrr+f4oUHJysgoKCvTPf/5TvXv3VnV1tVv7hx9+qBYtWqiyslIfffSRJk6cqLCwMKWmpl7zewOoWwQiAF6rWbNmateunaRv5/x07dpVy5Yt09ixY7Vy5UpVVFS4XYJyOp2qqanRwYMH1b59e7djtWzZUoMGDdLYsWNVUVGhgQMH6tSpU1ddy4033qjy8nLZ7XbXKFHz5s3Vrl07NWly6R+lcXFxCg0NlSTFx8dr9+7dmjNnDoEI8EJcMgPQIPj6+uoPf/iD0tPTde7cOS1btkyPPfaYCgoKXK/PP/9cd9xxh+vS2PeNGTNG27Zt06hRo+Tn53dN7z906FD5+/vrueeeu+5z8PPzc5vYDcB7MEIEoMH4zW9+o6lTp2rx4sX69NNPlZOTo44dO7r1uf/++zVr1izNnj37opGbAQMG6JtvvlFISMg1v3dMTIzmz5+vRx99VGVlZXrwwQcVFxensrIyvfHGG5J0Ucg6ceKEKioqXJfMXn/9dQ0dOvSa3xtA3WOECECD0aRJE02cOFEzZszQz372s4vCkCT9+te/1okTJ7R+/fqL2nx8fNSqVSu3O9WuxSOPPKJNmzbpm2++0dChQ3XjjTfqrrvuUnFxsTZs2KCEhAS3/h06dFBkZKTatWun6dOn63e/+51eeOGF63pvAHXLx+l0Oo0uAgAAwEiMEAEAANMjEAGApGeeecZtTaHvvgYOHGh0eQDqGJfMAEBSWVmZysrKLtkWHBysn/70p/VcEYD6RCACAACmxyUzAABgegQiAABgegQiAABgegQiAABgegQiAABgegQiAABgegQiAABgev8P4zI8f8I3Z98AAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# RAM_GB Box plot\n",
    "\n",
    "sns.boxplot(x=\"RAM_GB\", y=\"Price\", data=df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Storage_GB_SSD', ylabel='Price'>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Storage_GB_SSD Box plot\n",
    "\n",
    "sns.boxplot(x=\"Storage_GB_SSD\", y=\"Price\", data=df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Task 2 - Descriptive Statistical Analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Generate the statistical description of all the features being used in the data set. Include \"object\" data types as well."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "       Unnamed: 0.1  Unnamed: 0    Category         GPU          OS  \\\n",
      "count    238.000000  238.000000  238.000000  238.000000  238.000000   \n",
      "mean     118.500000  118.500000    3.205882    2.151261    1.058824   \n",
      "std       68.848868   68.848868    0.776533    0.638282    0.235790   \n",
      "min        0.000000    0.000000    1.000000    1.000000    1.000000   \n",
      "25%       59.250000   59.250000    3.000000    2.000000    1.000000   \n",
      "50%      118.500000  118.500000    3.000000    2.000000    1.000000   \n",
      "75%      177.750000  177.750000    4.000000    3.000000    1.000000   \n",
      "max      237.000000  237.000000    5.000000    3.000000    2.000000   \n",
      "\n",
      "         CPU_core  Screen_Size_inch  CPU_frequency      RAM_GB  \\\n",
      "count  238.000000        238.000000     238.000000  238.000000   \n",
      "mean     5.630252         14.688655       0.813822    7.882353   \n",
      "std      1.241787          1.166045       0.141860    2.482603   \n",
      "min      3.000000         12.000000       0.413793    4.000000   \n",
      "25%      5.000000         14.000000       0.689655    8.000000   \n",
      "50%      5.000000         15.000000       0.862069    8.000000   \n",
      "75%      7.000000         15.600000       0.931034    8.000000   \n",
      "max      7.000000         17.300000       1.000000   16.000000   \n",
      "\n",
      "       Storage_GB_SSD  Weight_pounds        Price  Screen-Full_HD  \\\n",
      "count      238.000000     238.000000   238.000000      238.000000   \n",
      "mean       245.781513       4.106221  1462.344538        0.676471   \n",
      "std         34.765316       1.078442   574.607699        0.468809   \n",
      "min        128.000000       1.786050   527.000000        0.000000   \n",
      "25%        256.000000       3.246863  1066.500000        0.000000   \n",
      "50%        256.000000       4.106221  1333.000000        1.000000   \n",
      "75%        256.000000       4.851000  1777.000000        1.000000   \n",
      "max        256.000000       7.938000  3810.000000        1.000000   \n",
      "\n",
      "       Screen-IPS_panel  \n",
      "count        238.000000  \n",
      "mean           0.323529  \n",
      "std            0.468809  \n",
      "min            0.000000  \n",
      "25%            0.000000  \n",
      "50%            0.000000  \n",
      "75%            1.000000  \n",
      "max            1.000000  \n",
      "       Manufacturer Price-binned\n",
      "count           238          238\n",
      "unique           11            3\n",
      "top            Dell          Low\n",
      "freq             71          160\n"
     ]
    }
   ],
   "source": [
    "print(df.describe())\n",
    "print(df.describe(include=['object']))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Task 3 - GroupBy and Pivot Tables"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Group the parameters \"GPU\", \"CPU_core\" and \"Price\" to make a pivot table and visualize this connection using the pcolor plot."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   GPU  CPU_core        Price\n",
      "0    1         3   769.250000\n",
      "1    1         5   998.500000\n",
      "2    1         7  1167.941176\n",
      "3    2         3   785.076923\n",
      "4    2         5  1462.197674\n",
      "5    2         7  1744.621622\n",
      "6    3         3   784.000000\n",
      "7    3         5  1220.680000\n",
      "8    3         7  1945.097561\n"
     ]
    }
   ],
   "source": [
    "# Create the group\n",
    "\n",
    "df_gptest = df[['GPU','CPU_core','Price']]\n",
    "grouped_test1 = df_gptest.groupby(['GPU','CPU_core'],as_index=False).mean()\n",
    "print(grouped_test1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "               Price                          \n",
      "CPU_core           3            5            7\n",
      "GPU                                           \n",
      "1         769.250000   998.500000  1167.941176\n",
      "2         785.076923  1462.197674  1744.621622\n",
      "3         784.000000  1220.680000  1945.097561\n"
     ]
    }
   ],
   "source": [
    "# Create the Pivot table\n",
    "\n",
    "grouped_pivot = grouped_test1.pivot(index='GPU',columns='CPU_core')\n",
    "print(grouped_pivot)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.colorbar.Colorbar at 0x26fc27ab620>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create the Plot\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "im = ax.pcolor(grouped_pivot, cmap='RdBu')\n",
    "\n",
    "#label names\n",
    "row_labels = grouped_pivot.columns.levels[1]\n",
    "col_labels = grouped_pivot.index\n",
    "\n",
    "#move ticks and labels to the center\n",
    "ax.set_xticks(np.arange(grouped_pivot.shape[1]) + 0.5, minor=False)\n",
    "ax.set_yticks(np.arange(grouped_pivot.shape[0]) + 0.5, minor=False)\n",
    "\n",
    "#insert labels\n",
    "ax.set_xticklabels(row_labels, minor=False)\n",
    "ax.set_yticklabels(col_labels, minor=False)\n",
    "\n",
    "fig.colorbar(im)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Task 4 - Pearson Correlation and p-values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RAM_GB\n",
      "The Pearson Correlation Coefficient for  RAM_GB  is 0.5492972971857841  with a P-value of P = 3.681560628842973e-20\n",
      "CPU_frequency\n",
      "The Pearson Correlation Coefficient for  CPU_frequency  is 0.36666555892588615  with a P-value of P = 5.502463350713219e-09\n",
      "Storage_GB_SSD\n",
      "The Pearson Correlation Coefficient for  Storage_GB_SSD  is 0.24342075521810302  with a P-value of P = 0.00014898923191723976\n",
      "Screen_Size_inch\n",
      "The Pearson Correlation Coefficient for  Screen_Size_inch  is -0.11064420817118273  with a P-value of P = 0.0885339784683062\n",
      "Weight_pounds\n",
      "The Pearson Correlation Coefficient for  Weight_pounds  is -0.05031225837751551  with a P-value of P = 0.43976938534338894\n",
      "CPU_core\n",
      "The Pearson Correlation Coefficient for  CPU_core  is 0.4593977773355115  with a P-value of P = 7.912950127009359e-14\n",
      "OS\n",
      "The Pearson Correlation Coefficient for  OS  is -0.22172980114827384  with a P-value of P = 0.000569664255924674\n",
      "GPU\n",
      "The Pearson Correlation Coefficient for  GPU  is 0.28829819888814273  with a P-value of P = 6.166949698364437e-06\n",
      "Category\n",
      "The Pearson Correlation Coefficient for  Category  is 0.2862427558126413  with a P-value of P = 7.225696235806605e-06\n"
     ]
    }
   ],
   "source": [
    "for param in ['RAM_GB','CPU_frequency','Storage_GB_SSD','Screen_Size_inch','Weight_pounds','CPU_core','OS','GPU','Category']:\n",
    "    pearson_coef, p_value = stats.pearsonr(df[param], df['Price'])\n",
    "    print(param)\n",
    "    print(\"The Pearson Correlation Coefficient for \",param,\" is\", pearson_coef, \" with a P-value of P =\", p_value)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": ".venv",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.13.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}