{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 123,
   "id": "18888451-47ef-4ed3-ab9d-a38909dea344",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd \n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "id": "3dd6a533-bbe8-4d6d-86f4-709a9c3c902e",
   "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>price</th>\n",
       "      <th>area</th>\n",
       "      <th>bedrooms</th>\n",
       "      <th>bathrooms</th>\n",
       "      <th>stories</th>\n",
       "      <th>mainroad</th>\n",
       "      <th>guestroom</th>\n",
       "      <th>basement</th>\n",
       "      <th>hotwaterheating</th>\n",
       "      <th>airconditioning</th>\n",
       "      <th>parking</th>\n",
       "      <th>prefarea</th>\n",
       "      <th>furnishingstatus</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>13300000</td>\n",
       "      <td>7420</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>2</td>\n",
       "      <td>yes</td>\n",
       "      <td>furnished</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>12250000</td>\n",
       "      <td>8960</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>3</td>\n",
       "      <td>no</td>\n",
       "      <td>furnished</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>12250000</td>\n",
       "      <td>9960</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>2</td>\n",
       "      <td>yes</td>\n",
       "      <td>semi-furnished</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>12215000</td>\n",
       "      <td>7500</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>3</td>\n",
       "      <td>yes</td>\n",
       "      <td>furnished</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>11410000</td>\n",
       "      <td>7420</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>yes</td>\n",
       "      <td>yes</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>2</td>\n",
       "      <td>no</td>\n",
       "      <td>furnished</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      price  area  bedrooms  bathrooms  stories mainroad guestroom basement  \\\n",
       "0  13300000  7420         4          2        3      yes        no       no   \n",
       "1  12250000  8960         4          4        4      yes        no       no   \n",
       "2  12250000  9960         3          2        2      yes        no      yes   \n",
       "3  12215000  7500         4          2        2      yes        no      yes   \n",
       "4  11410000  7420         4          1        2      yes       yes      yes   \n",
       "\n",
       "  hotwaterheating airconditioning  parking prefarea furnishingstatus  \n",
       "0              no             yes        2      yes        furnished  \n",
       "1              no             yes        3       no        furnished  \n",
       "2              no              no        2      yes   semi-furnished  \n",
       "3              no             yes        3      yes        furnished  \n",
       "4              no             yes        2       no        furnished  "
      ]
     },
     "execution_count": 124,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('Housing.csv') \n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "id": "09fbe0fc-873f-49c8-bd16-38c898c69048",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "price                int64\n",
       "area                 int64\n",
       "bedrooms             int64\n",
       "bathrooms            int64\n",
       "stories              int64\n",
       "mainroad            object\n",
       "guestroom           object\n",
       "basement            object\n",
       "hotwaterheating     object\n",
       "airconditioning     object\n",
       "parking              int64\n",
       "prefarea            object\n",
       "furnishingstatus    object\n",
       "dtype: object"
      ]
     },
     "execution_count": 125,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "id": "d342e775-da46-4e64-978f-279a27548248",
   "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>price</th>\n",
       "      <th>area</th>\n",
       "      <th>bedrooms</th>\n",
       "      <th>bathrooms</th>\n",
       "      <th>stories</th>\n",
       "      <th>parking</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>5.450000e+02</td>\n",
       "      <td>545.000000</td>\n",
       "      <td>545.000000</td>\n",
       "      <td>545.000000</td>\n",
       "      <td>545.000000</td>\n",
       "      <td>545.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>4.766729e+06</td>\n",
       "      <td>5150.541284</td>\n",
       "      <td>2.965138</td>\n",
       "      <td>1.286239</td>\n",
       "      <td>1.805505</td>\n",
       "      <td>0.693578</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.870440e+06</td>\n",
       "      <td>2170.141023</td>\n",
       "      <td>0.738064</td>\n",
       "      <td>0.502470</td>\n",
       "      <td>0.867492</td>\n",
       "      <td>0.861586</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.750000e+06</td>\n",
       "      <td>1650.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>3.430000e+06</td>\n",
       "      <td>3600.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>4.340000e+06</td>\n",
       "      <td>4600.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>5.740000e+06</td>\n",
       "      <td>6360.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1.330000e+07</td>\n",
       "      <td>16200.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>3.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              price          area    bedrooms   bathrooms     stories  \\\n",
       "count  5.450000e+02    545.000000  545.000000  545.000000  545.000000   \n",
       "mean   4.766729e+06   5150.541284    2.965138    1.286239    1.805505   \n",
       "std    1.870440e+06   2170.141023    0.738064    0.502470    0.867492   \n",
       "min    1.750000e+06   1650.000000    1.000000    1.000000    1.000000   \n",
       "25%    3.430000e+06   3600.000000    2.000000    1.000000    1.000000   \n",
       "50%    4.340000e+06   4600.000000    3.000000    1.000000    2.000000   \n",
       "75%    5.740000e+06   6360.000000    3.000000    2.000000    2.000000   \n",
       "max    1.330000e+07  16200.000000    6.000000    4.000000    4.000000   \n",
       "\n",
       "          parking  \n",
       "count  545.000000  \n",
       "mean     0.693578  \n",
       "std      0.861586  \n",
       "min      0.000000  \n",
       "25%      0.000000  \n",
       "50%      0.000000  \n",
       "75%      1.000000  \n",
       "max      3.000000  "
      ]
     },
     "execution_count": 126,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "id": "0f6cdfd4-3fda-4cbf-a703-89dd592cf461",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "price               0\n",
       "area                0\n",
       "bedrooms            0\n",
       "bathrooms           0\n",
       "stories             0\n",
       "mainroad            0\n",
       "guestroom           0\n",
       "basement            0\n",
       "hotwaterheating     0\n",
       "airconditioning     0\n",
       "parking             0\n",
       "prefarea            0\n",
       "furnishingstatus    0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 127,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "id": "5db58f8a-8e2b-4088-877a-4336e2db08e0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Columns dropped: []\n",
      "Remaining columns: Index(['price', 'area', 'bedrooms', 'bathrooms', 'stories', 'mainroad',\n",
      "       'guestroom', 'basement', 'hotwaterheating', 'airconditioning',\n",
      "       'parking', 'prefarea', 'furnishingstatus'],\n",
      "      dtype='object')\n"
     ]
    }
   ],
   "source": [
    "missing_percentage = df.isnull().mean() * 100 \n",
    "threshold = 30 \n",
    "# Filter columns with more than the threshold percentage of missing values \n",
    "columns_to_drop = missing_percentage[missing_percentage > threshold].index \n",
    "# Drop the columns \n",
    "df = df.drop(columns=columns_to_drop) \n",
    "# Display the resulting dataframe after removing columns with too many missing valu \n",
    "print(f\"Columns dropped: {list(columns_to_drop)}\") \n",
    "print(f\"Remaining columns: {df.columns}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "id": "ae70ec9a-6547-48d3-aee4-fb612a83f085",
   "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>price</th>\n",
       "      <th>area</th>\n",
       "      <th>bedrooms</th>\n",
       "      <th>bathrooms</th>\n",
       "      <th>stories</th>\n",
       "      <th>mainroad</th>\n",
       "      <th>guestroom</th>\n",
       "      <th>basement</th>\n",
       "      <th>hotwaterheating</th>\n",
       "      <th>airconditioning</th>\n",
       "      <th>parking</th>\n",
       "      <th>prefarea</th>\n",
       "      <th>furnishingstatus</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>13300000</td>\n",
       "      <td>7420</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>12250000</td>\n",
       "      <td>8960</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>12250000</td>\n",
       "      <td>9960</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>12215000</td>\n",
       "      <td>7500</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>11410000</td>\n",
       "      <td>7420</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      price  area  bedrooms  bathrooms  stories  mainroad  guestroom  \\\n",
       "0  13300000  7420         4          2        3         1          0   \n",
       "1  12250000  8960         4          4        4         1          0   \n",
       "2  12250000  9960         3          2        2         1          0   \n",
       "3  12215000  7500         4          2        2         1          0   \n",
       "4  11410000  7420         4          1        2         1          1   \n",
       "\n",
       "   basement  hotwaterheating  airconditioning  parking  prefarea  \\\n",
       "0         0                0                1        2         1   \n",
       "1         0                0                1        3         0   \n",
       "2         1                0                0        2         1   \n",
       "3         1                0                1        3         1   \n",
       "4         1                0                1        2         0   \n",
       "\n",
       "   furnishingstatus  \n",
       "0                 0  \n",
       "1                 0  \n",
       "2                 1  \n",
       "3                 0  \n",
       "4                 0  "
      ]
     },
     "execution_count": 129,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.preprocessing import LabelEncoder \n",
    "label_encoder = LabelEncoder() \n",
    "for column in df.select_dtypes(include=['object']).columns:     \n",
    "    df[column] = label_encoder.fit_transform(df[column]) \n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "id": "b256da5f-aa4f-401a-9701-de9c552f6aac",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Fill missing values in  columns with mode \n",
    "for column in df.select_dtypes(include=['float64']).columns:    \n",
    "    mean_value = df[column].mean()  # Get the mode (most frequent value)    \n",
    "    df[column] = df[column].fillna(mean_value) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "id": "cc83f3f8-ffdb-4fd6-bd6d-29ce32344825",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Fill missing values in categorical columns with mode \n",
    "for column in df.select_dtypes(include=['object']).columns:    \n",
    "    mode_value = df[column].mode()[0]  # Get the mode (most frequent value)    \n",
    "    df[column] = df[column].fillna(mode_value) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "id": "e8c581bf-38c6-41d4-8b66-de34a17b996b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "price               0\n",
       "area                0\n",
       "bedrooms            0\n",
       "bathrooms           0\n",
       "stories             0\n",
       "mainroad            0\n",
       "guestroom           0\n",
       "basement            0\n",
       "hotwaterheating     0\n",
       "airconditioning     0\n",
       "parking             0\n",
       "prefarea            0\n",
       "furnishingstatus    0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 132,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "id": "47b0ed5d-ced4-48af-b610-f611573b03e3",
   "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>price</th>\n",
       "      <th>area</th>\n",
       "      <th>bedrooms</th>\n",
       "      <th>bathrooms</th>\n",
       "      <th>stories</th>\n",
       "      <th>mainroad</th>\n",
       "      <th>guestroom</th>\n",
       "      <th>basement</th>\n",
       "      <th>hotwaterheating</th>\n",
       "      <th>airconditioning</th>\n",
       "      <th>parking</th>\n",
       "      <th>prefarea</th>\n",
       "      <th>furnishingstatus</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>13300000</td>\n",
       "      <td>7420</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>12250000</td>\n",
       "      <td>8960</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>12250000</td>\n",
       "      <td>9960</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>12215000</td>\n",
       "      <td>7500</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>11410000</td>\n",
       "      <td>7420</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>540</th>\n",
       "      <td>1820000</td>\n",
       "      <td>3000</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>541</th>\n",
       "      <td>1767150</td>\n",
       "      <td>2400</td>\n",
       "      <td>3</td>\n",
       "      <td>1</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",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>542</th>\n",
       "      <td>1750000</td>\n",
       "      <td>3620</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</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>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>543</th>\n",
       "      <td>1750000</td>\n",
       "      <td>2910</td>\n",
       "      <td>3</td>\n",
       "      <td>1</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",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>544</th>\n",
       "      <td>1750000</td>\n",
       "      <td>3850</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>2</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>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>545 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        price  area  bedrooms  bathrooms  stories  mainroad  guestroom  \\\n",
       "0    13300000  7420         4          2        3         1          0   \n",
       "1    12250000  8960         4          4        4         1          0   \n",
       "2    12250000  9960         3          2        2         1          0   \n",
       "3    12215000  7500         4          2        2         1          0   \n",
       "4    11410000  7420         4          1        2         1          1   \n",
       "..        ...   ...       ...        ...      ...       ...        ...   \n",
       "540   1820000  3000         2          1        1         1          0   \n",
       "541   1767150  2400         3          1        1         0          0   \n",
       "542   1750000  3620         2          1        1         1          0   \n",
       "543   1750000  2910         3          1        1         0          0   \n",
       "544   1750000  3850         3          1        2         1          0   \n",
       "\n",
       "     basement  hotwaterheating  airconditioning  parking  prefarea  \\\n",
       "0           0                0                1        2         1   \n",
       "1           0                0                1        3         0   \n",
       "2           1                0                0        2         1   \n",
       "3           1                0                1        3         1   \n",
       "4           1                0                1        2         0   \n",
       "..        ...              ...              ...      ...       ...   \n",
       "540         1                0                0        2         0   \n",
       "541         0                0                0        0         0   \n",
       "542         0                0                0        0         0   \n",
       "543         0                0                0        0         0   \n",
       "544         0                0                0        0         0   \n",
       "\n",
       "     furnishingstatus  \n",
       "0                   0  \n",
       "1                   0  \n",
       "2                   1  \n",
       "3                   0  \n",
       "4                   0  \n",
       "..                ...  \n",
       "540                 2  \n",
       "541                 1  \n",
       "542                 2  \n",
       "543                 0  \n",
       "544                 2  \n",
       "\n",
       "[545 rows x 13 columns]"
      ]
     },
     "execution_count": 133,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "id": "d832abc8-66cd-4220-861b-943a16ab9b93",
   "metadata": {},
   "outputs": [],
   "source": [
    "def replace_outliers_with_nan(column):    \n",
    "    Q1 = column.quantile(0.25)    \n",
    "    Q3 = column.quantile(0.75)    \n",
    "    IQR = Q3 - Q1    \n",
    "    lower_bound = Q1 - 1.5 * IQR    \n",
    "    upper_bound = Q3 + 1.5 * IQR    \n",
    "    # Replace outliers with NaN    \n",
    "    return column.where((column >= lower_bound) & (column <= upper_bound), np.nan) \n",
    "# Replace outliers with NaN for each feature \n",
    "for col in df.columns:    \n",
    "    df[col] = replace_outliers_with_nan(df[col])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "id": "4a8b714c-5cf9-4250-ae63-5455539d07af",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Sum of null values in each column:\n",
      "price                15\n",
      "area                 12\n",
      "bedrooms             12\n",
      "bathrooms             1\n",
      "stories              41\n",
      "mainroad             77\n",
      "guestroom            97\n",
      "basement              0\n",
      "hotwaterheating      25\n",
      "airconditioning       0\n",
      "parking              12\n",
      "prefarea            128\n",
      "furnishingstatus      0\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "null_counts = df.isnull().sum()\n",
    "print(\"Sum of null values in each column:\")\n",
    "print(null_counts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "id": "a2412048-327f-4a23-bafe-670b1fdb96f5",
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8, 6))\n",
    "sns.histplot(df['price'], bins=15, kde=True, color='blue')\n",
    "plt.title('price Distribution')\n",
    "plt.xlabel('price')\n",
    "plt.ylabel('Frequency')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "id": "ed8b8873-fef6-4258-8088-4cc4a003ed3a",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\ghufr\\AppData\\Local\\Temp\\ipykernel_26364\\972390041.py:2: FutureWarning: \n",
      "\n",
      "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n",
      "\n",
      "  sns.countplot(x='furnishingstatus', data=df, palette='Set2')\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8, 6))\n",
    "sns.countplot(x='furnishingstatus', data=df, palette='Set2')\n",
    "plt.title('furnishingstatus Count')\n",
    "plt.xlabel('furnishingstatus')\n",
    "plt.ylabel('Count')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "id": "d14b043e-0df3-4d0f-9b02-d9295c6fdc04",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8, 6))\n",
    "sns.scatterplot(x='price', y='area', data=df, hue='furnishingstatus', palette='Set1')\n",
    "plt.title('price vs area')\n",
    "plt.xlabel('price')\n",
    "plt.ylabel('area')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "70f65023-698f-4ee0-ae94-2dff5f8a3488",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "id": "26d188c3-9b1c-4e14-a633-f59715898bbf",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\ghufr\\AppData\\Local\\Temp\\ipykernel_26364\\560274491.py:4: UserWarning: Ignoring `palette` because no `hue` variable has been assigned.\n",
      "  sns.scatterplot(x='furnishingstatus', y='price', data=df, palette='Set2')\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "required_columns = ['area', 'price']\n",
    "if all(column in df.columns for column in required_columns):\n",
    "    plt.figure(figsize=(8, 6))\n",
    "    sns.scatterplot(x='furnishingstatus', y='price', data=df, palette='Set2')\n",
    "    plt.title('Price vs furnishingstatus')\n",
    "    plt.xlabel('furnishingstatus')\n",
    "    plt.ylabel('Price')\n",
    "    plt.show()\n",
    "else:\n",
    "    print(\"One or more required columns ('furnishingstatus', 'price') are not found in the DataFrame.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "id": "541edb2f-1314-43f8-a7af-4a5b0767d220",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\ghufr\\AppData\\Local\\Temp\\ipykernel_26364\\2339366810.py:2: FutureWarning: \n",
      "\n",
      "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n",
      "\n",
      "  sns.boxplot(x='furnishingstatus', y='price', data=df, palette='Set1')\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "    plt.figure(figsize=(8, 6))\n",
    "    sns.boxplot(x='furnishingstatus', y='price', data=df, palette='Set1')\n",
    "    plt.title('Price Levels by furnishingstatus')\n",
    "    plt.xlabel('furnishingstatus')\n",
    "    plt.ylabel('Price')\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "abfc34dd-6fba-4b07-b6cb-39fe6ae78b45",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.12.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}