Boston_house_prices.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "ceb82f27",
   "metadata": {},
   "source": [
    "# Gathering data from example databases"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "3f47160a",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.datasets import load_boston\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.linear_model import LinearRegression\n",
    "import statsmodels.api as sm\n",
    "from statsmodels .stats.outliers_influence import variance_inflation_factor\n",
    "import pandas as pd \n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import numpy as np\n",
    "import math\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "8f13a6c4",
   "metadata": {},
   "outputs": [],
   "source": [
    "boston_dataset = load_boston()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "3bdb0e78",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "sklearn.utils.Bunch"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(boston_dataset)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "51749b70",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'data': array([[6.3200e-03, 1.8000e+01, 2.3100e+00, ..., 1.5300e+01, 3.9690e+02,\n",
       "         4.9800e+00],\n",
       "        [2.7310e-02, 0.0000e+00, 7.0700e+00, ..., 1.7800e+01, 3.9690e+02,\n",
       "         9.1400e+00],\n",
       "        [2.7290e-02, 0.0000e+00, 7.0700e+00, ..., 1.7800e+01, 3.9283e+02,\n",
       "         4.0300e+00],\n",
       "        ...,\n",
       "        [6.0760e-02, 0.0000e+00, 1.1930e+01, ..., 2.1000e+01, 3.9690e+02,\n",
       "         5.6400e+00],\n",
       "        [1.0959e-01, 0.0000e+00, 1.1930e+01, ..., 2.1000e+01, 3.9345e+02,\n",
       "         6.4800e+00],\n",
       "        [4.7410e-02, 0.0000e+00, 1.1930e+01, ..., 2.1000e+01, 3.9690e+02,\n",
       "         7.8800e+00]]),\n",
       " 'target': array([24. , 21.6, 34.7, 33.4, 36.2, 28.7, 22.9, 27.1, 16.5, 18.9, 15. ,\n",
       "        18.9, 21.7, 20.4, 18.2, 19.9, 23.1, 17.5, 20.2, 18.2, 13.6, 19.6,\n",
       "        15.2, 14.5, 15.6, 13.9, 16.6, 14.8, 18.4, 21. , 12.7, 14.5, 13.2,\n",
       "        13.1, 13.5, 18.9, 20. , 21. , 24.7, 30.8, 34.9, 26.6, 25.3, 24.7,\n",
       "        21.2, 19.3, 20. , 16.6, 14.4, 19.4, 19.7, 20.5, 25. , 23.4, 18.9,\n",
       "        35.4, 24.7, 31.6, 23.3, 19.6, 18.7, 16. , 22.2, 25. , 33. , 23.5,\n",
       "        19.4, 22. , 17.4, 20.9, 24.2, 21.7, 22.8, 23.4, 24.1, 21.4, 20. ,\n",
       "        20.8, 21.2, 20.3, 28. , 23.9, 24.8, 22.9, 23.9, 26.6, 22.5, 22.2,\n",
       "        23.6, 28.7, 22.6, 22. , 22.9, 25. , 20.6, 28.4, 21.4, 38.7, 43.8,\n",
       "        33.2, 27.5, 26.5, 18.6, 19.3, 20.1, 19.5, 19.5, 20.4, 19.8, 19.4,\n",
       "        21.7, 22.8, 18.8, 18.7, 18.5, 18.3, 21.2, 19.2, 20.4, 19.3, 22. ,\n",
       "        20.3, 20.5, 17.3, 18.8, 21.4, 15.7, 16.2, 18. , 14.3, 19.2, 19.6,\n",
       "        23. , 18.4, 15.6, 18.1, 17.4, 17.1, 13.3, 17.8, 14. , 14.4, 13.4,\n",
       "        15.6, 11.8, 13.8, 15.6, 14.6, 17.8, 15.4, 21.5, 19.6, 15.3, 19.4,\n",
       "        17. , 15.6, 13.1, 41.3, 24.3, 23.3, 27. , 50. , 50. , 50. , 22.7,\n",
       "        25. , 50. , 23.8, 23.8, 22.3, 17.4, 19.1, 23.1, 23.6, 22.6, 29.4,\n",
       "        23.2, 24.6, 29.9, 37.2, 39.8, 36.2, 37.9, 32.5, 26.4, 29.6, 50. ,\n",
       "        32. , 29.8, 34.9, 37. , 30.5, 36.4, 31.1, 29.1, 50. , 33.3, 30.3,\n",
       "        34.6, 34.9, 32.9, 24.1, 42.3, 48.5, 50. , 22.6, 24.4, 22.5, 24.4,\n",
       "        20. , 21.7, 19.3, 22.4, 28.1, 23.7, 25. , 23.3, 28.7, 21.5, 23. ,\n",
       "        26.7, 21.7, 27.5, 30.1, 44.8, 50. , 37.6, 31.6, 46.7, 31.5, 24.3,\n",
       "        31.7, 41.7, 48.3, 29. , 24. , 25.1, 31.5, 23.7, 23.3, 22. , 20.1,\n",
       "        22.2, 23.7, 17.6, 18.5, 24.3, 20.5, 24.5, 26.2, 24.4, 24.8, 29.6,\n",
       "        42.8, 21.9, 20.9, 44. , 50. , 36. , 30.1, 33.8, 43.1, 48.8, 31. ,\n",
       "        36.5, 22.8, 30.7, 50. , 43.5, 20.7, 21.1, 25.2, 24.4, 35.2, 32.4,\n",
       "        32. , 33.2, 33.1, 29.1, 35.1, 45.4, 35.4, 46. , 50. , 32.2, 22. ,\n",
       "        20.1, 23.2, 22.3, 24.8, 28.5, 37.3, 27.9, 23.9, 21.7, 28.6, 27.1,\n",
       "        20.3, 22.5, 29. , 24.8, 22. , 26.4, 33.1, 36.1, 28.4, 33.4, 28.2,\n",
       "        22.8, 20.3, 16.1, 22.1, 19.4, 21.6, 23.8, 16.2, 17.8, 19.8, 23.1,\n",
       "        21. , 23.8, 23.1, 20.4, 18.5, 25. , 24.6, 23. , 22.2, 19.3, 22.6,\n",
       "        19.8, 17.1, 19.4, 22.2, 20.7, 21.1, 19.5, 18.5, 20.6, 19. , 18.7,\n",
       "        32.7, 16.5, 23.9, 31.2, 17.5, 17.2, 23.1, 24.5, 26.6, 22.9, 24.1,\n",
       "        18.6, 30.1, 18.2, 20.6, 17.8, 21.7, 22.7, 22.6, 25. , 19.9, 20.8,\n",
       "        16.8, 21.9, 27.5, 21.9, 23.1, 50. , 50. , 50. , 50. , 50. , 13.8,\n",
       "        13.8, 15. , 13.9, 13.3, 13.1, 10.2, 10.4, 10.9, 11.3, 12.3,  8.8,\n",
       "         7.2, 10.5,  7.4, 10.2, 11.5, 15.1, 23.2,  9.7, 13.8, 12.7, 13.1,\n",
       "        12.5,  8.5,  5. ,  6.3,  5.6,  7.2, 12.1,  8.3,  8.5,  5. , 11.9,\n",
       "        27.9, 17.2, 27.5, 15. , 17.2, 17.9, 16.3,  7. ,  7.2,  7.5, 10.4,\n",
       "         8.8,  8.4, 16.7, 14.2, 20.8, 13.4, 11.7,  8.3, 10.2, 10.9, 11. ,\n",
       "         9.5, 14.5, 14.1, 16.1, 14.3, 11.7, 13.4,  9.6,  8.7,  8.4, 12.8,\n",
       "        10.5, 17.1, 18.4, 15.4, 10.8, 11.8, 14.9, 12.6, 14.1, 13. , 13.4,\n",
       "        15.2, 16.1, 17.8, 14.9, 14.1, 12.7, 13.5, 14.9, 20. , 16.4, 17.7,\n",
       "        19.5, 20.2, 21.4, 19.9, 19. , 19.1, 19.1, 20.1, 19.9, 19.6, 23.2,\n",
       "        29.8, 13.8, 13.3, 16.7, 12. , 14.6, 21.4, 23. , 23.7, 25. , 21.8,\n",
       "        20.6, 21.2, 19.1, 20.6, 15.2,  7. ,  8.1, 13.6, 20.1, 21.8, 24.5,\n",
       "        23.1, 19.7, 18.3, 21.2, 17.5, 16.8, 22.4, 20.6, 23.9, 22. , 11.9]),\n",
       " 'feature_names': array(['CRIM', 'ZN', 'INDUS', 'CHAS', 'NOX', 'RM', 'AGE', 'DIS', 'RAD',\n",
       "        'TAX', 'PTRATIO', 'B', 'LSTAT'], dtype='<U7'),\n",
       " 'DESCR': \".. _boston_dataset:\\n\\nBoston house prices dataset\\n---------------------------\\n\\n**Data Set Characteristics:**  \\n\\n    :Number of Instances: 506 \\n\\n    :Number of Attributes: 13 numeric/categorical predictive. Median Value (attribute 14) is usually the target.\\n\\n    :Attribute Information (in order):\\n        - CRIM     per capita crime rate by town\\n        - ZN       proportion of residential land zoned for lots over 25,000 sq.ft.\\n        - INDUS    proportion of non-retail business acres per town\\n        - CHAS     Charles River dummy variable (= 1 if tract bounds river; 0 otherwise)\\n        - NOX      nitric oxides concentration (parts per 10 million)\\n        - RM       average number of rooms per dwelling\\n        - AGE      proportion of owner-occupied units built prior to 1940\\n        - DIS      weighted distances to five Boston employment centres\\n        - RAD      index of accessibility to radial highways\\n        - TAX      full-value property-tax rate per $10,000\\n        - PTRATIO  pupil-teacher ratio by town\\n        - B        1000(Bk - 0.63)^2 where Bk is the proportion of black people by town\\n        - LSTAT    % lower status of the population\\n        - MEDV     Median value of owner-occupied homes in $1000's\\n\\n    :Missing Attribute Values: None\\n\\n    :Creator: Harrison, D. and Rubinfeld, D.L.\\n\\nThis is a copy of UCI ML housing dataset.\\nhttps://archive.ics.uci.edu/ml/machine-learning-databases/housing/\\n\\n\\nThis dataset was taken from the StatLib library which is maintained at Carnegie Mellon University.\\n\\nThe Boston house-price data of Harrison, D. and Rubinfeld, D.L. 'Hedonic\\nprices and the demand for clean air', J. Environ. Economics & Management,\\nvol.5, 81-102, 1978.   Used in Belsley, Kuh & Welsch, 'Regression diagnostics\\n...', Wiley, 1980.   N.B. Various transformations are used in the table on\\npages 244-261 of the latter.\\n\\nThe Boston house-price data has been used in many machine learning papers that address regression\\nproblems.   \\n     \\n.. topic:: References\\n\\n   - Belsley, Kuh & Welsch, 'Regression diagnostics: Identifying Influential Data and Sources of Collinearity', Wiley, 1980. 244-261.\\n   - Quinlan,R. (1993). Combining Instance-Based and Model-Based Learning. In Proceedings on the Tenth International Conference of Machine Learning, 236-243, University of Massachusetts, Amherst. Morgan Kaufmann.\\n\",\n",
       " 'filename': 'c:\\\\users\\\\shubham\\\\appdata\\\\local\\\\programs\\\\python\\\\python39\\\\lib\\\\site-packages\\\\sklearn\\\\datasets\\\\data\\\\boston_house_prices.csv'}"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "boston_dataset"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "214bb2f0",
   "metadata": {},
   "source": [
    "The Boston DataSet was orignally fetched from a research paper, you can find it [here](https://deepblue.lib.umich.edu/bitstream/handle/2027.42/22636/0000186.pdf?sequence=1&isAllowed=y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "391c9c40",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['DESCR', 'data', 'feature_names', 'filename', 'target']"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dir(boston_dataset) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "fbac12e6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      ".. _boston_dataset:\n",
      "\n",
      "Boston house prices dataset\n",
      "---------------------------\n",
      "\n",
      "**Data Set Characteristics:**  \n",
      "\n",
      "    :Number of Instances: 506 \n",
      "\n",
      "    :Number of Attributes: 13 numeric/categorical predictive. Median Value (attribute 14) is usually the target.\n",
      "\n",
      "    :Attribute Information (in order):\n",
      "        - CRIM     per capita crime rate by town\n",
      "        - ZN       proportion of residential land zoned for lots over 25,000 sq.ft.\n",
      "        - INDUS    proportion of non-retail business acres per town\n",
      "        - CHAS     Charles River dummy variable (= 1 if tract bounds river; 0 otherwise)\n",
      "        - NOX      nitric oxides concentration (parts per 10 million)\n",
      "        - RM       average number of rooms per dwelling\n",
      "        - AGE      proportion of owner-occupied units built prior to 1940\n",
      "        - DIS      weighted distances to five Boston employment centres\n",
      "        - RAD      index of accessibility to radial highways\n",
      "        - TAX      full-value property-tax rate per $10,000\n",
      "        - PTRATIO  pupil-teacher ratio by town\n",
      "        - B        1000(Bk - 0.63)^2 where Bk is the proportion of black people by town\n",
      "        - LSTAT    % lower status of the population\n",
      "        - MEDV     Median value of owner-occupied homes in $1000's\n",
      "\n",
      "    :Missing Attribute Values: None\n",
      "\n",
      "    :Creator: Harrison, D. and Rubinfeld, D.L.\n",
      "\n",
      "This is a copy of UCI ML housing dataset.\n",
      "https://archive.ics.uci.edu/ml/machine-learning-databases/housing/\n",
      "\n",
      "\n",
      "This dataset was taken from the StatLib library which is maintained at Carnegie Mellon University.\n",
      "\n",
      "The Boston house-price data of Harrison, D. and Rubinfeld, D.L. 'Hedonic\n",
      "prices and the demand for clean air', J. Environ. Economics & Management,\n",
      "vol.5, 81-102, 1978.   Used in Belsley, Kuh & Welsch, 'Regression diagnostics\n",
      "...', Wiley, 1980.   N.B. Various transformations are used in the table on\n",
      "pages 244-261 of the latter.\n",
      "\n",
      "The Boston house-price data has been used in many machine learning papers that address regression\n",
      "problems.   \n",
      "     \n",
      ".. topic:: References\n",
      "\n",
      "   - Belsley, Kuh & Welsch, 'Regression diagnostics: Identifying Influential Data and Sources of Collinearity', Wiley, 1980. 244-261.\n",
      "   - Quinlan,R. (1993). Combining Instance-Based and Model-Based Learning. In Proceedings on the Tenth International Conference of Machine Learning, 236-243, University of Massachusetts, Amherst. Morgan Kaufmann.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(boston_dataset.DESCR)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1a7b3ce5",
   "metadata": {},
   "source": [
    "# Data points and features\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "415fcda0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "numpy.ndarray"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(boston_dataset.data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "683f65ac",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(506, 13)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "boston_dataset.data.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "169b7022",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['CRIM', 'ZN', 'INDUS', 'CHAS', 'NOX', 'RM', 'AGE', 'DIS', 'RAD',\n",
       "       'TAX', 'PTRATIO', 'B', 'LSTAT'], dtype='<U7')"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "boston_dataset.feature_names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "38d15124",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([24. , 21.6, 34.7, 33.4, 36.2, 28.7, 22.9, 27.1, 16.5, 18.9, 15. ,\n",
       "       18.9, 21.7, 20.4, 18.2, 19.9, 23.1, 17.5, 20.2, 18.2, 13.6, 19.6,\n",
       "       15.2, 14.5, 15.6, 13.9, 16.6, 14.8, 18.4, 21. , 12.7, 14.5, 13.2,\n",
       "       13.1, 13.5, 18.9, 20. , 21. , 24.7, 30.8, 34.9, 26.6, 25.3, 24.7,\n",
       "       21.2, 19.3, 20. , 16.6, 14.4, 19.4, 19.7, 20.5, 25. , 23.4, 18.9,\n",
       "       35.4, 24.7, 31.6, 23.3, 19.6, 18.7, 16. , 22.2, 25. , 33. , 23.5,\n",
       "       19.4, 22. , 17.4, 20.9, 24.2, 21.7, 22.8, 23.4, 24.1, 21.4, 20. ,\n",
       "       20.8, 21.2, 20.3, 28. , 23.9, 24.8, 22.9, 23.9, 26.6, 22.5, 22.2,\n",
       "       23.6, 28.7, 22.6, 22. , 22.9, 25. , 20.6, 28.4, 21.4, 38.7, 43.8,\n",
       "       33.2, 27.5, 26.5, 18.6, 19.3, 20.1, 19.5, 19.5, 20.4, 19.8, 19.4,\n",
       "       21.7, 22.8, 18.8, 18.7, 18.5, 18.3, 21.2, 19.2, 20.4, 19.3, 22. ,\n",
       "       20.3, 20.5, 17.3, 18.8, 21.4, 15.7, 16.2, 18. , 14.3, 19.2, 19.6,\n",
       "       23. , 18.4, 15.6, 18.1, 17.4, 17.1, 13.3, 17.8, 14. , 14.4, 13.4,\n",
       "       15.6, 11.8, 13.8, 15.6, 14.6, 17.8, 15.4, 21.5, 19.6, 15.3, 19.4,\n",
       "       17. , 15.6, 13.1, 41.3, 24.3, 23.3, 27. , 50. , 50. , 50. , 22.7,\n",
       "       25. , 50. , 23.8, 23.8, 22.3, 17.4, 19.1, 23.1, 23.6, 22.6, 29.4,\n",
       "       23.2, 24.6, 29.9, 37.2, 39.8, 36.2, 37.9, 32.5, 26.4, 29.6, 50. ,\n",
       "       32. , 29.8, 34.9, 37. , 30.5, 36.4, 31.1, 29.1, 50. , 33.3, 30.3,\n",
       "       34.6, 34.9, 32.9, 24.1, 42.3, 48.5, 50. , 22.6, 24.4, 22.5, 24.4,\n",
       "       20. , 21.7, 19.3, 22.4, 28.1, 23.7, 25. , 23.3, 28.7, 21.5, 23. ,\n",
       "       26.7, 21.7, 27.5, 30.1, 44.8, 50. , 37.6, 31.6, 46.7, 31.5, 24.3,\n",
       "       31.7, 41.7, 48.3, 29. , 24. , 25.1, 31.5, 23.7, 23.3, 22. , 20.1,\n",
       "       22.2, 23.7, 17.6, 18.5, 24.3, 20.5, 24.5, 26.2, 24.4, 24.8, 29.6,\n",
       "       42.8, 21.9, 20.9, 44. , 50. , 36. , 30.1, 33.8, 43.1, 48.8, 31. ,\n",
       "       36.5, 22.8, 30.7, 50. , 43.5, 20.7, 21.1, 25.2, 24.4, 35.2, 32.4,\n",
       "       32. , 33.2, 33.1, 29.1, 35.1, 45.4, 35.4, 46. , 50. , 32.2, 22. ,\n",
       "       20.1, 23.2, 22.3, 24.8, 28.5, 37.3, 27.9, 23.9, 21.7, 28.6, 27.1,\n",
       "       20.3, 22.5, 29. , 24.8, 22. , 26.4, 33.1, 36.1, 28.4, 33.4, 28.2,\n",
       "       22.8, 20.3, 16.1, 22.1, 19.4, 21.6, 23.8, 16.2, 17.8, 19.8, 23.1,\n",
       "       21. , 23.8, 23.1, 20.4, 18.5, 25. , 24.6, 23. , 22.2, 19.3, 22.6,\n",
       "       19.8, 17.1, 19.4, 22.2, 20.7, 21.1, 19.5, 18.5, 20.6, 19. , 18.7,\n",
       "       32.7, 16.5, 23.9, 31.2, 17.5, 17.2, 23.1, 24.5, 26.6, 22.9, 24.1,\n",
       "       18.6, 30.1, 18.2, 20.6, 17.8, 21.7, 22.7, 22.6, 25. , 19.9, 20.8,\n",
       "       16.8, 21.9, 27.5, 21.9, 23.1, 50. , 50. , 50. , 50. , 50. , 13.8,\n",
       "       13.8, 15. , 13.9, 13.3, 13.1, 10.2, 10.4, 10.9, 11.3, 12.3,  8.8,\n",
       "        7.2, 10.5,  7.4, 10.2, 11.5, 15.1, 23.2,  9.7, 13.8, 12.7, 13.1,\n",
       "       12.5,  8.5,  5. ,  6.3,  5.6,  7.2, 12.1,  8.3,  8.5,  5. , 11.9,\n",
       "       27.9, 17.2, 27.5, 15. , 17.2, 17.9, 16.3,  7. ,  7.2,  7.5, 10.4,\n",
       "        8.8,  8.4, 16.7, 14.2, 20.8, 13.4, 11.7,  8.3, 10.2, 10.9, 11. ,\n",
       "        9.5, 14.5, 14.1, 16.1, 14.3, 11.7, 13.4,  9.6,  8.7,  8.4, 12.8,\n",
       "       10.5, 17.1, 18.4, 15.4, 10.8, 11.8, 14.9, 12.6, 14.1, 13. , 13.4,\n",
       "       15.2, 16.1, 17.8, 14.9, 14.1, 12.7, 13.5, 14.9, 20. , 16.4, 17.7,\n",
       "       19.5, 20.2, 21.4, 19.9, 19. , 19.1, 19.1, 20.1, 19.9, 19.6, 23.2,\n",
       "       29.8, 13.8, 13.3, 16.7, 12. , 14.6, 21.4, 23. , 23.7, 25. , 21.8,\n",
       "       20.6, 21.2, 19.1, 20.6, 15.2,  7. ,  8.1, 13.6, 20.1, 21.8, 24.5,\n",
       "       23.1, 19.7, 18.3, 21.2, 17.5, 16.8, 22.4, 20.6, 23.9, 22. , 11.9])"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "boston_dataset.target # This data is the prices of houses in Boston in thousands."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "87dbf065",
   "metadata": {},
   "source": [
    "# Exploring data with pandas Dataframes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "c633f817",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Creating dataFrame using pandas\n",
    "data = pd.DataFrame(data=boston_dataset.data, columns=boston_dataset.feature_names)\n",
    "\n",
    "# Add a column with price\n",
    "data[\"Price\"] = boston_dataset.target"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "8b97a12e",
   "metadata": {},
   "outputs": [
    {
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       "<p>506 rows × 14 columns</p>\n",
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       "        CRIM    ZN  INDUS  CHAS    NOX     RM   AGE     DIS  RAD    TAX  \\\n",
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       "..       ...   ...    ...   ...    ...    ...   ...     ...  ...    ...   \n",
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       "505  0.04741   0.0  11.93   0.0  0.573  6.030  80.8  2.5050  1.0  273.0   \n",
       "\n",
       "     PTRATIO       B  LSTAT  Price  \n",
       "0       15.3  396.90   4.98   24.0  \n",
       "1       17.8  396.90   9.14   21.6  \n",
       "2       17.8  392.83   4.03   34.7  \n",
       "3       18.7  394.63   2.94   33.4  \n",
       "4       18.7  396.90   5.33   36.2  \n",
       "..       ...     ...    ...    ...  \n",
       "501     21.0  391.99   9.67   22.4  \n",
       "502     21.0  396.90   9.08   20.6  \n",
       "503     21.0  396.90   5.64   23.9  \n",
       "504     21.0  393.45   6.48   22.0  \n",
       "505     21.0  396.90   7.88   11.9  \n",
       "\n",
       "[506 rows x 14 columns]"
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     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "6f910e7f",
   "metadata": {},
   "outputs": [
    {
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      "text/plain": [
       "      CRIM    ZN  INDUS  CHAS    NOX     RM   AGE     DIS  RAD    TAX  \\\n",
       "0  0.00632  18.0   2.31   0.0  0.538  6.575  65.2  4.0900  1.0  296.0   \n",
       "1  0.02731   0.0   7.07   0.0  0.469  6.421  78.9  4.9671  2.0  242.0   \n",
       "2  0.02729   0.0   7.07   0.0  0.469  7.185  61.1  4.9671  2.0  242.0   \n",
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       "4  0.06905   0.0   2.18   0.0  0.458  7.147  54.2  6.0622  3.0  222.0   \n",
       "\n",
       "   PTRATIO       B  LSTAT  Price  \n",
       "0     15.3  396.90   4.98   24.0  \n",
       "1     17.8  396.90   9.14   21.6  \n",
       "2     17.8  392.83   4.03   34.7  \n",
       "3     18.7  394.63   2.94   33.4  \n",
       "4     18.7  396.90   5.33   36.2  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# to print the few top rows of the datset\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "2d342b51",
   "metadata": {},
   "outputs": [
    {
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       "    <tr>\n",
       "      <th>502</th>\n",
       "      <td>0.04527</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.93</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.573</td>\n",
       "      <td>6.120</td>\n",
       "      <td>76.7</td>\n",
       "      <td>2.2875</td>\n",
       "      <td>1.0</td>\n",
       "      <td>273.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>396.90</td>\n",
       "      <td>9.08</td>\n",
       "      <td>20.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>503</th>\n",
       "      <td>0.06076</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.93</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.573</td>\n",
       "      <td>6.976</td>\n",
       "      <td>91.0</td>\n",
       "      <td>2.1675</td>\n",
       "      <td>1.0</td>\n",
       "      <td>273.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>396.90</td>\n",
       "      <td>5.64</td>\n",
       "      <td>23.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>504</th>\n",
       "      <td>0.10959</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.93</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.573</td>\n",
       "      <td>6.794</td>\n",
       "      <td>89.3</td>\n",
       "      <td>2.3889</td>\n",
       "      <td>1.0</td>\n",
       "      <td>273.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>393.45</td>\n",
       "      <td>6.48</td>\n",
       "      <td>22.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>505</th>\n",
       "      <td>0.04741</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.93</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.573</td>\n",
       "      <td>6.030</td>\n",
       "      <td>80.8</td>\n",
       "      <td>2.5050</td>\n",
       "      <td>1.0</td>\n",
       "      <td>273.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>396.90</td>\n",
       "      <td>7.88</td>\n",
       "      <td>11.9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        CRIM   ZN  INDUS  CHAS    NOX     RM   AGE     DIS  RAD    TAX  \\\n",
       "501  0.06263  0.0  11.93   0.0  0.573  6.593  69.1  2.4786  1.0  273.0   \n",
       "502  0.04527  0.0  11.93   0.0  0.573  6.120  76.7  2.2875  1.0  273.0   \n",
       "503  0.06076  0.0  11.93   0.0  0.573  6.976  91.0  2.1675  1.0  273.0   \n",
       "504  0.10959  0.0  11.93   0.0  0.573  6.794  89.3  2.3889  1.0  273.0   \n",
       "505  0.04741  0.0  11.93   0.0  0.573  6.030  80.8  2.5050  1.0  273.0   \n",
       "\n",
       "     PTRATIO       B  LSTAT  Price  \n",
       "501     21.0  391.99   9.67   22.4  \n",
       "502     21.0  396.90   9.08   20.6  \n",
       "503     21.0  396.90   5.64   23.9  \n",
       "504     21.0  393.45   6.48   22.0  \n",
       "505     21.0  396.90   7.88   11.9  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# to print the few botton rows of the datset\n",
    "data.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "f2ffdbbd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "CRIM       506\n",
       "ZN         506\n",
       "INDUS      506\n",
       "CHAS       506\n",
       "NOX        506\n",
       "RM         506\n",
       "AGE        506\n",
       "DIS        506\n",
       "RAD        506\n",
       "TAX        506\n",
       "PTRATIO    506\n",
       "B          506\n",
       "LSTAT      506\n",
       "Price      506\n",
       "dtype: int64"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# To check number of enteries per column\n",
    "data.count()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6a9991af",
   "metadata": {},
   "source": [
    "# Cleaning Data to Check Missing Values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "6022c08a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "CRIM       False\n",
       "ZN         False\n",
       "INDUS      False\n",
       "CHAS       False\n",
       "NOX        False\n",
       "RM         False\n",
       "AGE        False\n",
       "DIS        False\n",
       "RAD        False\n",
       "TAX        False\n",
       "PTRATIO    False\n",
       "B          False\n",
       "LSTAT      False\n",
       "Price      False\n",
       "dtype: bool"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.isnull(data).any()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "9138cb1a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 506 entries, 0 to 505\n",
      "Data columns (total 14 columns):\n",
      " #   Column   Non-Null Count  Dtype  \n",
      "---  ------   --------------  -----  \n",
      " 0   CRIM     506 non-null    float64\n",
      " 1   ZN       506 non-null    float64\n",
      " 2   INDUS    506 non-null    float64\n",
      " 3   CHAS     506 non-null    float64\n",
      " 4   NOX      506 non-null    float64\n",
      " 5   RM       506 non-null    float64\n",
      " 6   AGE      506 non-null    float64\n",
      " 7   DIS      506 non-null    float64\n",
      " 8   RAD      506 non-null    float64\n",
      " 9   TAX      506 non-null    float64\n",
      " 10  PTRATIO  506 non-null    float64\n",
      " 11  B        506 non-null    float64\n",
      " 12  LSTAT    506 non-null    float64\n",
      " 13  Price    506 non-null    float64\n",
      "dtypes: float64(14)\n",
      "memory usage: 55.5 KB\n"
     ]
    }
   ],
   "source": [
    "data.info() # to check whether we have null places in our dataset"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fecd7250",
   "metadata": {},
   "source": [
    "# Visualizing Data, Histogram"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "83e98c35",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,8))\n",
    "plt.hist(data['Price'], bins=75, ec='black', color='#D57E7E')\n",
    "plt.xlabel('price_in_thousands')\n",
    "plt.ylabel('numberof Houses')\n",
    "plt.title('Boston-Houses')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "a5afa076",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,8))\n",
    "sns.histplot(data['Price'], bins=75, kde=True, color='#14279B') # older version has distplot but now it has histplot\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "21a681b3",
   "metadata": {},
   "source": [
    "# To visuialize the no. of rooms available in boston"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "b9178f3f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'No. of rooms')"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,8))\n",
    "rooms = data['RM'] \n",
    "sns.histplot(rooms, bins=75, kde=True)\n",
    "plt.xlabel('Average No. of rooms')\n",
    "plt.ylabel('No. of rooms')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "adeec34e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6.284634387351779"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rooms.mean() # to get the average no. of rooms in boston"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "5463f4c2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,8))\n",
    "plt.hist(data['RAD'],rwidth=0.7, ec='black',bins=25 , color='#7851a9')\n",
    "plt.ylabel('Accesibility to highways')\n",
    "plt.xlabel('Averge No. of houses')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "860390ab",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "24.0    132\n",
       "5.0     115\n",
       "4.0     110\n",
       "3.0      38\n",
       "6.0      26\n",
       "2.0      24\n",
       "8.0      24\n",
       "1.0      20\n",
       "7.0      17\n",
       "Name: RAD, dtype: int64"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[\"RAD\"].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f4946a54",
   "metadata": {},
   "source": [
    "### RAD has index values, so we can visualize the data using bar graph"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "25bec0f2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Float64Index([24.0, 5.0, 4.0, 3.0, 6.0, 2.0, 8.0, 1.0, 7.0], dtype='float64')"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "frequency = data['RAD'].value_counts() # frequency of rooms near to the highway\n",
    "type(frequency)\n",
    "frequency.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "74dd6887",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15, 8))\n",
    "plt.bar(frequency.index, height=frequency)\n",
    "plt.xlabel('Average no. of houses')\n",
    "plt.ylabel('Accessibility to highways')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "44f574aa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0    471\n",
       "1.0     35\n",
       "Name: CHAS, dtype: int64"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['CHAS'].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4801dc42",
   "metadata": {},
   "source": [
    "# Descriptive Statistics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "5d1cd92a",
   "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>CRIM</th>\n",
       "      <th>ZN</th>\n",
       "      <th>INDUS</th>\n",
       "      <th>CHAS</th>\n",
       "      <th>NOX</th>\n",
       "      <th>RM</th>\n",
       "      <th>AGE</th>\n",
       "      <th>DIS</th>\n",
       "      <th>RAD</th>\n",
       "      <th>TAX</th>\n",
       "      <th>PTRATIO</th>\n",
       "      <th>B</th>\n",
       "      <th>LSTAT</th>\n",
       "      <th>Price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>506.000000</td>\n",
       "      <td>506.000000</td>\n",
       "      <td>506.000000</td>\n",
       "      <td>506.000000</td>\n",
       "      <td>506.000000</td>\n",
       "      <td>506.000000</td>\n",
       "      <td>506.000000</td>\n",
       "      <td>506.000000</td>\n",
       "      <td>506.000000</td>\n",
       "      <td>506.000000</td>\n",
       "      <td>506.000000</td>\n",
       "      <td>506.000000</td>\n",
       "      <td>506.000000</td>\n",
       "      <td>506.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>3.613524</td>\n",
       "      <td>11.363636</td>\n",
       "      <td>11.136779</td>\n",
       "      <td>0.069170</td>\n",
       "      <td>0.554695</td>\n",
       "      <td>6.284634</td>\n",
       "      <td>68.574901</td>\n",
       "      <td>3.795043</td>\n",
       "      <td>9.549407</td>\n",
       "      <td>408.237154</td>\n",
       "      <td>18.455534</td>\n",
       "      <td>356.674032</td>\n",
       "      <td>12.653063</td>\n",
       "      <td>22.532806</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>8.601545</td>\n",
       "      <td>23.322453</td>\n",
       "      <td>6.860353</td>\n",
       "      <td>0.253994</td>\n",
       "      <td>0.115878</td>\n",
       "      <td>0.702617</td>\n",
       "      <td>28.148861</td>\n",
       "      <td>2.105710</td>\n",
       "      <td>8.707259</td>\n",
       "      <td>168.537116</td>\n",
       "      <td>2.164946</td>\n",
       "      <td>91.294864</td>\n",
       "      <td>7.141062</td>\n",
       "      <td>9.197104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.006320</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.460000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.385000</td>\n",
       "      <td>3.561000</td>\n",
       "      <td>2.900000</td>\n",
       "      <td>1.129600</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>187.000000</td>\n",
       "      <td>12.600000</td>\n",
       "      <td>0.320000</td>\n",
       "      <td>1.730000</td>\n",
       "      <td>5.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.082045</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5.190000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.449000</td>\n",
       "      <td>5.885500</td>\n",
       "      <td>45.025000</td>\n",
       "      <td>2.100175</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>279.000000</td>\n",
       "      <td>17.400000</td>\n",
       "      <td>375.377500</td>\n",
       "      <td>6.950000</td>\n",
       "      <td>17.025000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.256510</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>9.690000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.538000</td>\n",
       "      <td>6.208500</td>\n",
       "      <td>77.500000</td>\n",
       "      <td>3.207450</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>330.000000</td>\n",
       "      <td>19.050000</td>\n",
       "      <td>391.440000</td>\n",
       "      <td>11.360000</td>\n",
       "      <td>21.200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>3.677083</td>\n",
       "      <td>12.500000</td>\n",
       "      <td>18.100000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.624000</td>\n",
       "      <td>6.623500</td>\n",
       "      <td>94.075000</td>\n",
       "      <td>5.188425</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>666.000000</td>\n",
       "      <td>20.200000</td>\n",
       "      <td>396.225000</td>\n",
       "      <td>16.955000</td>\n",
       "      <td>25.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>88.976200</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>27.740000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.871000</td>\n",
       "      <td>8.780000</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>12.126500</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>711.000000</td>\n",
       "      <td>22.000000</td>\n",
       "      <td>396.900000</td>\n",
       "      <td>37.970000</td>\n",
       "      <td>50.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             CRIM          ZN       INDUS        CHAS         NOX          RM  \\\n",
       "count  506.000000  506.000000  506.000000  506.000000  506.000000  506.000000   \n",
       "mean     3.613524   11.363636   11.136779    0.069170    0.554695    6.284634   \n",
       "std      8.601545   23.322453    6.860353    0.253994    0.115878    0.702617   \n",
       "min      0.006320    0.000000    0.460000    0.000000    0.385000    3.561000   \n",
       "25%      0.082045    0.000000    5.190000    0.000000    0.449000    5.885500   \n",
       "50%      0.256510    0.000000    9.690000    0.000000    0.538000    6.208500   \n",
       "75%      3.677083   12.500000   18.100000    0.000000    0.624000    6.623500   \n",
       "max     88.976200  100.000000   27.740000    1.000000    0.871000    8.780000   \n",
       "\n",
       "              AGE         DIS         RAD         TAX     PTRATIO           B  \\\n",
       "count  506.000000  506.000000  506.000000  506.000000  506.000000  506.000000   \n",
       "mean    68.574901    3.795043    9.549407  408.237154   18.455534  356.674032   \n",
       "std     28.148861    2.105710    8.707259  168.537116    2.164946   91.294864   \n",
       "min      2.900000    1.129600    1.000000  187.000000   12.600000    0.320000   \n",
       "25%     45.025000    2.100175    4.000000  279.000000   17.400000  375.377500   \n",
       "50%     77.500000    3.207450    5.000000  330.000000   19.050000  391.440000   \n",
       "75%     94.075000    5.188425   24.000000  666.000000   20.200000  396.225000   \n",
       "max    100.000000   12.126500   24.000000  711.000000   22.000000  396.900000   \n",
       "\n",
       "            LSTAT       Price  \n",
       "count  506.000000  506.000000  \n",
       "mean    12.653063   22.532806  \n",
       "std      7.141062    9.197104  \n",
       "min      1.730000    5.000000  \n",
       "25%      6.950000   17.025000  \n",
       "50%     11.360000   21.200000  \n",
       "75%     16.955000   25.000000  \n",
       "max     37.970000   50.000000  "
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.describe() # to get description of data(max, min, median, mean, standard, ...etc)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "16530c8f",
   "metadata": {},
   "source": [
    "## Correlation\n",
    "## $$ \\rho _{XY} = corr(X,Y) $$\n",
    "## $$ -1.0 \\leq \\rho _{XY} \\leq +1.0 $$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "77f27fc9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.6953599470715396"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['Price'].corr(data['RM'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "6f455f23",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-0.5077866855375618"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['Price'].corr(data['PTRATIO'])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "731c657c",
   "metadata": {},
   "source": [
    "# Visualizing the correlation in our dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "7b9a1bf1",
   "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>CRIM</th>\n",
       "      <th>ZN</th>\n",
       "      <th>INDUS</th>\n",
       "      <th>CHAS</th>\n",
       "      <th>NOX</th>\n",
       "      <th>RM</th>\n",
       "      <th>AGE</th>\n",
       "      <th>DIS</th>\n",
       "      <th>RAD</th>\n",
       "      <th>TAX</th>\n",
       "      <th>PTRATIO</th>\n",
       "      <th>B</th>\n",
       "      <th>LSTAT</th>\n",
       "      <th>Price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>CRIM</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.200469</td>\n",
       "      <td>0.406583</td>\n",
       "      <td>-0.055892</td>\n",
       "      <td>0.420972</td>\n",
       "      <td>-0.219247</td>\n",
       "      <td>0.352734</td>\n",
       "      <td>-0.379670</td>\n",
       "      <td>0.625505</td>\n",
       "      <td>0.582764</td>\n",
       "      <td>0.289946</td>\n",
       "      <td>-0.385064</td>\n",
       "      <td>0.455621</td>\n",
       "      <td>-0.388305</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ZN</th>\n",
       "      <td>-0.200469</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.533828</td>\n",
       "      <td>-0.042697</td>\n",
       "      <td>-0.516604</td>\n",
       "      <td>0.311991</td>\n",
       "      <td>-0.569537</td>\n",
       "      <td>0.664408</td>\n",
       "      <td>-0.311948</td>\n",
       "      <td>-0.314563</td>\n",
       "      <td>-0.391679</td>\n",
       "      <td>0.175520</td>\n",
       "      <td>-0.412995</td>\n",
       "      <td>0.360445</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INDUS</th>\n",
       "      <td>0.406583</td>\n",
       "      <td>-0.533828</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.062938</td>\n",
       "      <td>0.763651</td>\n",
       "      <td>-0.391676</td>\n",
       "      <td>0.644779</td>\n",
       "      <td>-0.708027</td>\n",
       "      <td>0.595129</td>\n",
       "      <td>0.720760</td>\n",
       "      <td>0.383248</td>\n",
       "      <td>-0.356977</td>\n",
       "      <td>0.603800</td>\n",
       "      <td>-0.483725</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CHAS</th>\n",
       "      <td>-0.055892</td>\n",
       "      <td>-0.042697</td>\n",
       "      <td>0.062938</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.091203</td>\n",
       "      <td>0.091251</td>\n",
       "      <td>0.086518</td>\n",
       "      <td>-0.099176</td>\n",
       "      <td>-0.007368</td>\n",
       "      <td>-0.035587</td>\n",
       "      <td>-0.121515</td>\n",
       "      <td>0.048788</td>\n",
       "      <td>-0.053929</td>\n",
       "      <td>0.175260</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NOX</th>\n",
       "      <td>0.420972</td>\n",
       "      <td>-0.516604</td>\n",
       "      <td>0.763651</td>\n",
       "      <td>0.091203</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.302188</td>\n",
       "      <td>0.731470</td>\n",
       "      <td>-0.769230</td>\n",
       "      <td>0.611441</td>\n",
       "      <td>0.668023</td>\n",
       "      <td>0.188933</td>\n",
       "      <td>-0.380051</td>\n",
       "      <td>0.590879</td>\n",
       "      <td>-0.427321</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RM</th>\n",
       "      <td>-0.219247</td>\n",
       "      <td>0.311991</td>\n",
       "      <td>-0.391676</td>\n",
       "      <td>0.091251</td>\n",
       "      <td>-0.302188</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.240265</td>\n",
       "      <td>0.205246</td>\n",
       "      <td>-0.209847</td>\n",
       "      <td>-0.292048</td>\n",
       "      <td>-0.355501</td>\n",
       "      <td>0.128069</td>\n",
       "      <td>-0.613808</td>\n",
       "      <td>0.695360</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AGE</th>\n",
       "      <td>0.352734</td>\n",
       "      <td>-0.569537</td>\n",
       "      <td>0.644779</td>\n",
       "      <td>0.086518</td>\n",
       "      <td>0.731470</td>\n",
       "      <td>-0.240265</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.747881</td>\n",
       "      <td>0.456022</td>\n",
       "      <td>0.506456</td>\n",
       "      <td>0.261515</td>\n",
       "      <td>-0.273534</td>\n",
       "      <td>0.602339</td>\n",
       "      <td>-0.376955</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DIS</th>\n",
       "      <td>-0.379670</td>\n",
       "      <td>0.664408</td>\n",
       "      <td>-0.708027</td>\n",
       "      <td>-0.099176</td>\n",
       "      <td>-0.769230</td>\n",
       "      <td>0.205246</td>\n",
       "      <td>-0.747881</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.494588</td>\n",
       "      <td>-0.534432</td>\n",
       "      <td>-0.232471</td>\n",
       "      <td>0.291512</td>\n",
       "      <td>-0.496996</td>\n",
       "      <td>0.249929</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RAD</th>\n",
       "      <td>0.625505</td>\n",
       "      <td>-0.311948</td>\n",
       "      <td>0.595129</td>\n",
       "      <td>-0.007368</td>\n",
       "      <td>0.611441</td>\n",
       "      <td>-0.209847</td>\n",
       "      <td>0.456022</td>\n",
       "      <td>-0.494588</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.910228</td>\n",
       "      <td>0.464741</td>\n",
       "      <td>-0.444413</td>\n",
       "      <td>0.488676</td>\n",
       "      <td>-0.381626</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TAX</th>\n",
       "      <td>0.582764</td>\n",
       "      <td>-0.314563</td>\n",
       "      <td>0.720760</td>\n",
       "      <td>-0.035587</td>\n",
       "      <td>0.668023</td>\n",
       "      <td>-0.292048</td>\n",
       "      <td>0.506456</td>\n",
       "      <td>-0.534432</td>\n",
       "      <td>0.910228</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.460853</td>\n",
       "      <td>-0.441808</td>\n",
       "      <td>0.543993</td>\n",
       "      <td>-0.468536</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PTRATIO</th>\n",
       "      <td>0.289946</td>\n",
       "      <td>-0.391679</td>\n",
       "      <td>0.383248</td>\n",
       "      <td>-0.121515</td>\n",
       "      <td>0.188933</td>\n",
       "      <td>-0.355501</td>\n",
       "      <td>0.261515</td>\n",
       "      <td>-0.232471</td>\n",
       "      <td>0.464741</td>\n",
       "      <td>0.460853</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.177383</td>\n",
       "      <td>0.374044</td>\n",
       "      <td>-0.507787</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B</th>\n",
       "      <td>-0.385064</td>\n",
       "      <td>0.175520</td>\n",
       "      <td>-0.356977</td>\n",
       "      <td>0.048788</td>\n",
       "      <td>-0.380051</td>\n",
       "      <td>0.128069</td>\n",
       "      <td>-0.273534</td>\n",
       "      <td>0.291512</td>\n",
       "      <td>-0.444413</td>\n",
       "      <td>-0.441808</td>\n",
       "      <td>-0.177383</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.366087</td>\n",
       "      <td>0.333461</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LSTAT</th>\n",
       "      <td>0.455621</td>\n",
       "      <td>-0.412995</td>\n",
       "      <td>0.603800</td>\n",
       "      <td>-0.053929</td>\n",
       "      <td>0.590879</td>\n",
       "      <td>-0.613808</td>\n",
       "      <td>0.602339</td>\n",
       "      <td>-0.496996</td>\n",
       "      <td>0.488676</td>\n",
       "      <td>0.543993</td>\n",
       "      <td>0.374044</td>\n",
       "      <td>-0.366087</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.737663</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Price</th>\n",
       "      <td>-0.388305</td>\n",
       "      <td>0.360445</td>\n",
       "      <td>-0.483725</td>\n",
       "      <td>0.175260</td>\n",
       "      <td>-0.427321</td>\n",
       "      <td>0.695360</td>\n",
       "      <td>-0.376955</td>\n",
       "      <td>0.249929</td>\n",
       "      <td>-0.381626</td>\n",
       "      <td>-0.468536</td>\n",
       "      <td>-0.507787</td>\n",
       "      <td>0.333461</td>\n",
       "      <td>-0.737663</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             CRIM        ZN     INDUS      CHAS       NOX        RM       AGE  \\\n",
       "CRIM     1.000000 -0.200469  0.406583 -0.055892  0.420972 -0.219247  0.352734   \n",
       "ZN      -0.200469  1.000000 -0.533828 -0.042697 -0.516604  0.311991 -0.569537   \n",
       "INDUS    0.406583 -0.533828  1.000000  0.062938  0.763651 -0.391676  0.644779   \n",
       "CHAS    -0.055892 -0.042697  0.062938  1.000000  0.091203  0.091251  0.086518   \n",
       "NOX      0.420972 -0.516604  0.763651  0.091203  1.000000 -0.302188  0.731470   \n",
       "RM      -0.219247  0.311991 -0.391676  0.091251 -0.302188  1.000000 -0.240265   \n",
       "AGE      0.352734 -0.569537  0.644779  0.086518  0.731470 -0.240265  1.000000   \n",
       "DIS     -0.379670  0.664408 -0.708027 -0.099176 -0.769230  0.205246 -0.747881   \n",
       "RAD      0.625505 -0.311948  0.595129 -0.007368  0.611441 -0.209847  0.456022   \n",
       "TAX      0.582764 -0.314563  0.720760 -0.035587  0.668023 -0.292048  0.506456   \n",
       "PTRATIO  0.289946 -0.391679  0.383248 -0.121515  0.188933 -0.355501  0.261515   \n",
       "B       -0.385064  0.175520 -0.356977  0.048788 -0.380051  0.128069 -0.273534   \n",
       "LSTAT    0.455621 -0.412995  0.603800 -0.053929  0.590879 -0.613808  0.602339   \n",
       "Price   -0.388305  0.360445 -0.483725  0.175260 -0.427321  0.695360 -0.376955   \n",
       "\n",
       "              DIS       RAD       TAX   PTRATIO         B     LSTAT     Price  \n",
       "CRIM    -0.379670  0.625505  0.582764  0.289946 -0.385064  0.455621 -0.388305  \n",
       "ZN       0.664408 -0.311948 -0.314563 -0.391679  0.175520 -0.412995  0.360445  \n",
       "INDUS   -0.708027  0.595129  0.720760  0.383248 -0.356977  0.603800 -0.483725  \n",
       "CHAS    -0.099176 -0.007368 -0.035587 -0.121515  0.048788 -0.053929  0.175260  \n",
       "NOX     -0.769230  0.611441  0.668023  0.188933 -0.380051  0.590879 -0.427321  \n",
       "RM       0.205246 -0.209847 -0.292048 -0.355501  0.128069 -0.613808  0.695360  \n",
       "AGE     -0.747881  0.456022  0.506456  0.261515 -0.273534  0.602339 -0.376955  \n",
       "DIS      1.000000 -0.494588 -0.534432 -0.232471  0.291512 -0.496996  0.249929  \n",
       "RAD     -0.494588  1.000000  0.910228  0.464741 -0.444413  0.488676 -0.381626  \n",
       "TAX     -0.534432  0.910228  1.000000  0.460853 -0.441808  0.543993 -0.468536  \n",
       "PTRATIO -0.232471  0.464741  0.460853  1.000000 -0.177383  0.374044 -0.507787  \n",
       "B        0.291512 -0.444413 -0.441808 -0.177383  1.000000 -0.366087  0.333461  \n",
       "LSTAT   -0.496996  0.488676  0.543993  0.374044 -0.366087  1.000000 -0.737663  \n",
       "Price    0.249929 -0.381626 -0.468536 -0.507787  0.333461 -0.737663  1.000000  "
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.corr() # correlation between in all th columns."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "71cb2969",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Actual total correlation in our dataset visually\n",
    "plt.figure(figsize=(15,8))\n",
    "sns.heatmap(data.corr())\n",
    "plt.xticks(fontsize=14)\n",
    "plt.yticks(fontsize=14)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "d9967c5f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.],\n",
       "       [0., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.],\n",
       "       [0., 0., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.],\n",
       "       [0., 0., 0., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.],\n",
       "       [0., 0., 0., 0., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.],\n",
       "       [0., 0., 0., 0., 0., 1., 1., 1., 1., 1., 1., 1., 1., 1.],\n",
       "       [0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 1., 1., 1., 1.],\n",
       "       [0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 1., 1., 1.],\n",
       "       [0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 1., 1.],\n",
       "       [0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1., 1.],\n",
       "       [0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1., 1.],\n",
       "       [0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1., 1.],\n",
       "       [0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 1.],\n",
       "       [0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1.]])"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# to filter out useless data\n",
    "mask = np.zeros_like(data.corr()) # put zeros to the values which are unnecessary i.e. corr with their own.\n",
    "tri_indices = np.triu_indices_from(mask) # to get those values which are in above triangle(above 1.00 value)\n",
    "mask[tri_indices] = True\n",
    "mask"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "8286bb5f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Actual total correlation in our dataset visually after removing useless values\n",
    "plt.figure(figsize=(20, 10))\n",
    "sns.heatmap(data.corr(), mask=mask, annot=True, annot_kws={'size':14})\n",
    "sns.set_style('white')\n",
    "plt.xticks(fontsize=14)\n",
    "plt.yticks(fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "388e0aa3",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "83076f3f",
   "metadata": {},
   "source": [
    "# Scatter plot between distance & pollution\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "22e33503",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "plt.figure(figsize=(15,8))\n",
    "y = data['NOX']\n",
    "x = data['DIS']\n",
    "\n",
    "corr_dis_nox = round(x.corr(y), 3)\n",
    "\n",
    "\n",
    "plt.scatter(x, y, alpha=0.6, s=90)\n",
    "plt.ylabel('DISTANCE', fontsize=14)\n",
    "plt.xlabel('POLLUTION', fontsize=14)\n",
    "plt.title(f'POLLUTION-DISTANCE GRAPH (Correlation is {corr_dis_nox})', fontsize=14)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "21f23c02",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x648 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set()\n",
    "sns.set_context('notebook')\n",
    "sns.set_style('whitegrid')\n",
    "sns.jointplot(x=data['DIS'], y=data['NOX'], height=9,kind='hex',color='#D98C00', joint_kws={\"alpha\":0.5})\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "cdc00120",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x648 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "corr_rad_tax =round(data['TAX'].corr(data['RAD']), 5)\n",
    "sns.set()\n",
    "sns.set_context('notebook')\n",
    "sns.set_style('whitegrid')\n",
    "sns.jointplot(x=data['TAX'], y=data['RAD'], height=9,color='#FF0075', joint_kws={\"alpha\":0.5})\n",
    "plt.title(f'{corr_rad_tax}')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "abdcf272",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.lmplot(x='TAX', y='RAD', data=data, height=8)\n",
    "plt.title(f'Correlation is {corr_rad_tax}',fontsize=15)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b2762fa0",
   "metadata": {},
   "source": [
    "# Visualizing the Prices with all other params given in the dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "4e94c695",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Price with RM\n",
    "correlation = round(data['RM'].corr(data['Price']), 4)\n",
    "plt.figure(figsize=(15,8))\n",
    "sns.scatterplot(x=data['RM'], y=data['Price'])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "49b771e8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.lmplot(x='RM', y='Price', data=data, height=8)\n",
    "plt.title(f'Corelation is {correlation}')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "b13c5204",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wall time: 0 ns\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "\n",
    "#sns.pairplot(data)\n",
    "#plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "98d83abe",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wall time: 0 ns\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "\n",
    "#sns.pairplot(data, kind='reg', plot_kws={'line_kws':{'color':'cyan'}})\n",
    "#plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3e4dea91",
   "metadata": {},
   "source": [
    "# Multivariable Regression\n",
    "## Training & testing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "c3614d81",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.2015810276679842"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Take temporary data\n",
    "prices = data['Price']\n",
    "features = data.drop('Price', axis=1)\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(features, prices,\n",
    "                                                    test_size=0.2, \n",
    "                                                    random_state=10)\n",
    "# % of training dataset\n",
    "len(X_train)/len(features)\n",
    "\n",
    "# % of testing dataset \n",
    "X_test.shape[0]/features.shape[0]\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f9c974ce",
   "metadata": {},
   "source": [
    "## Multivariable regression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "f41c351b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Intercept  36.53305138282457 \n",
      "\n",
      "RSS of Training Dataset  0.750121534530608 \n",
      "\n",
      "RSS of Testing Dataset  0.6709339839115638\n"
     ]
    },
    {
     "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>coef</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>CRIM</th>\n",
       "      <td>-0.128181</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ZN</th>\n",
       "      <td>0.063198</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INDUS</th>\n",
       "      <td>-0.007576</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CHAS</th>\n",
       "      <td>1.974515</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NOX</th>\n",
       "      <td>-16.271989</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RM</th>\n",
       "      <td>3.108456</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AGE</th>\n",
       "      <td>0.016292</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DIS</th>\n",
       "      <td>-1.483014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RAD</th>\n",
       "      <td>0.303988</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TAX</th>\n",
       "      <td>-0.012082</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PTRATIO</th>\n",
       "      <td>-0.820306</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B</th>\n",
       "      <td>0.011419</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LSTAT</th>\n",
       "      <td>-0.581626</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              coef\n",
       "CRIM     -0.128181\n",
       "ZN        0.063198\n",
       "INDUS    -0.007576\n",
       "CHAS      1.974515\n",
       "NOX     -16.271989\n",
       "RM        3.108456\n",
       "AGE       0.016292\n",
       "DIS      -1.483014\n",
       "RAD       0.303988\n",
       "TAX      -0.012082\n",
       "PTRATIO  -0.820306\n",
       "B         0.011419\n",
       "LSTAT    -0.581626"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Linear Regression\n",
    "\n",
    "reg = LinearRegression()\n",
    "reg.fit(X_train, y_train)\n",
    "\n",
    "print(\"Intercept \",reg.intercept_,'\\n')\n",
    "\n",
    "# Training data set score\n",
    "print(\"RSS of Training Dataset \",reg.score(X_train, y_train),'\\n')\n",
    "\n",
    "# Testing dataset Score\n",
    "print('RSS of Testing Dataset ',reg.score(X_test, y_test))\n",
    "\n",
    "# to check regression  the prices with other params\n",
    "pd.DataFrame(data=reg.coef_, index=X_train.columns, columns=['coef'])\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a734d1e9",
   "metadata": {},
   "source": [
    "## Data Transformation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "94068c90",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.1080984082549072"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['Price'].skew() # histograms with spike values at the edges are called skewed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "07325932",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      3.178054\n",
       "1      3.072693\n",
       "2      3.546740\n",
       "3      3.508556\n",
       "4      3.589059\n",
       "         ...   \n",
       "501    3.109061\n",
       "502    3.025291\n",
       "503    3.173878\n",
       "504    3.091042\n",
       "505    2.476538\n",
       "Name: Price, Length: 506, dtype: float64"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# TO make our data fit in our linear model, we need to pull our values closer using log() which dose'nt mislead our data\n",
    "y_log = np.log(data['Price'])\n",
    "y_log"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "d45579a1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-0.33032129530987864"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_log.skew()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "165ea3a0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,8)) \n",
    "sns.histplot(data['Price'], bins=50, kde=True)\n",
    "plt.title(f\"Show data before applying log with its skew {data['Price'].skew()}\")\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "6abff836",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,8)) \n",
    "sns.histplot(y_log, bins=50, kde=True)\n",
    "plt.title(f\"Show data after applying log with its skew {y_log.skew()}\")\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "e8d16945",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.lmplot(x='LSTAT', y='Price', data=data, height=7, scatter_kws={'alpha':0.6}, line_kws={'color':'red'})\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "eb7221ea",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "Transformed_data = features\n",
    "Transformed_data['Log'] = y_log\n",
    "sns.lmplot(x='LSTAT', y='Log', data=Transformed_data, height=7, scatter_kws={'alpha':0.6}, line_kws={'color':'red'})\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "67ace199",
   "metadata": {},
   "source": [
    "## Regression with Log Values of Price"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "0afa3f10",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.2015810276679842"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Take temporary data\n",
    "prices = np.log(data['Price'])\n",
    "features = data.drop('Price', axis=1)\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(features, prices,\n",
    "                                                    test_size=0.2, \n",
    "                                                    random_state=10)\n",
    "# % of training dataset\n",
    "len(X_train)/len(features)\n",
    "\n",
    "# % of testing dataset \n",
    "X_test.shape[0]/features.shape[0]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "bffe6b9d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Intercept  4.059943871775209 \n",
      "\n",
      "RSS of Training Dataset  0.7930234826697584 \n",
      "\n",
      "RSS of Testing Dataset  0.7446922306260745\n"
     ]
    },
    {
     "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>coef</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>CRIM</th>\n",
       "      <td>-0.010672</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ZN</th>\n",
       "      <td>0.001579</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INDUS</th>\n",
       "      <td>0.002030</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CHAS</th>\n",
       "      <td>0.080331</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NOX</th>\n",
       "      <td>-0.704068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RM</th>\n",
       "      <td>0.073404</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AGE</th>\n",
       "      <td>0.000763</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DIS</th>\n",
       "      <td>-0.047633</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RAD</th>\n",
       "      <td>0.014565</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TAX</th>\n",
       "      <td>-0.000645</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PTRATIO</th>\n",
       "      <td>-0.034795</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B</th>\n",
       "      <td>0.000516</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LSTAT</th>\n",
       "      <td>-0.031390</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             coef\n",
       "CRIM    -0.010672\n",
       "ZN       0.001579\n",
       "INDUS    0.002030\n",
       "CHAS     0.080331\n",
       "NOX     -0.704068\n",
       "RM       0.073404\n",
       "AGE      0.000763\n",
       "DIS     -0.047633\n",
       "RAD      0.014565\n",
       "TAX     -0.000645\n",
       "PTRATIO -0.034795\n",
       "B        0.000516\n",
       "LSTAT   -0.031390"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Linear Regression\n",
    "\n",
    "reg = LinearRegression()\n",
    "reg.fit(X_train, y_train)\n",
    "\n",
    "print(\"Intercept \",reg.intercept_,'\\n')\n",
    "\n",
    "# Training data set score\n",
    "print(\"RSS of Training Dataset \",reg.score(X_train, y_train),'\\n')\n",
    "\n",
    "# Testing dataset Score\n",
    "print('RSS of Testing Dataset ',reg.score(X_test, y_test))\n",
    "\n",
    "# to check regression  the prices with other params\n",
    "pd.DataFrame(data=reg.coef_, index=X_train.columns, columns=['coef'])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d33c184d",
   "metadata": {},
   "source": [
    "## P-values and Evaluating Coefficients"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "f00e470a",
   "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>coef</th>\n",
       "      <th>p-values</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>const</th>\n",
       "      <td>4.059944</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CRIM</th>\n",
       "      <td>-0.010672</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ZN</th>\n",
       "      <td>0.001579</td>\n",
       "      <td>0.0086</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INDUS</th>\n",
       "      <td>0.002030</td>\n",
       "      <td>0.4445</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CHAS</th>\n",
       "      <td>0.080331</td>\n",
       "      <td>0.0382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NOX</th>\n",
       "      <td>-0.704068</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RM</th>\n",
       "      <td>0.073404</td>\n",
       "      <td>0.0001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AGE</th>\n",
       "      <td>0.000763</td>\n",
       "      <td>0.2092</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DIS</th>\n",
       "      <td>-0.047633</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RAD</th>\n",
       "      <td>0.014565</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TAX</th>\n",
       "      <td>-0.000645</td>\n",
       "      <td>0.0001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PTRATIO</th>\n",
       "      <td>-0.034795</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B</th>\n",
       "      <td>0.000516</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LSTAT</th>\n",
       "      <td>-0.031390</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             coef  p-values\n",
       "const    4.059944    0.0000\n",
       "CRIM    -0.010672    0.0000\n",
       "ZN       0.001579    0.0086\n",
       "INDUS    0.002030    0.4445\n",
       "CHAS     0.080331    0.0382\n",
       "NOX     -0.704068    0.0000\n",
       "RM       0.073404    0.0001\n",
       "AGE      0.000763    0.2092\n",
       "DIS     -0.047633    0.0000\n",
       "RAD      0.014565    0.0000\n",
       "TAX     -0.000645    0.0001\n",
       "PTRATIO -0.034795    0.0000\n",
       "B        0.000516    0.0000\n",
       "LSTAT   -0.031390    0.0000"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x_incl_const = sm.add_constant(X_train)\n",
    "model = sm.OLS(y_train, x_incl_const)\n",
    "result = model.fit()\n",
    "\n",
    "\n",
    "# result.params\n",
    "\n",
    "pd.DataFrame({'coef':result.params, 'p-values':round(result.pvalues, 4)})\n",
    "\n",
    "# P-values are calculated to check whether the features of the dataset are statistically significant or not\n",
    "# If the p-values are > 0.05, then they are not significant i.e. they do not have much\n",
    "# impact in our target values with their existence\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "dcec08c3",
   "metadata": {},
   "outputs": [],
   "source": [
    "# INDUS & AGE are not significant"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7ea16e3a",
   "metadata": {},
   "source": [
    "## Testing for Multicollinearity\n",
    "\n",
    "$$ TAX = \\alpha _0 + \\alpha _1 CRIM + \\alpha_2 ZN + ............+\\alpha_{12} LSTAT $$\n",
    "$$ VIF_{TAX} =  \\frac{1} {(1 - R_{TAX}^2)} $$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "0940fd3c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.7145250443932485"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "variance_inflation_factor(x_incl_const.values, 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "a52d158f",
   "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>coef_name</th>\n",
       "      <th>vif</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>const</td>\n",
       "      <td>597.5487</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>CRIM</td>\n",
       "      <td>1.7145</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ZN</td>\n",
       "      <td>2.3328</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>INDUS</td>\n",
       "      <td>3.9434</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>CHAS</td>\n",
       "      <td>1.0788</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>NOX</td>\n",
       "      <td>4.4103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>RM</td>\n",
       "      <td>1.8404</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>AGE</td>\n",
       "      <td>3.3268</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>DIS</td>\n",
       "      <td>4.2229</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>RAD</td>\n",
       "      <td>7.3143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>TAX</td>\n",
       "      <td>8.5089</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>PTRATIO</td>\n",
       "      <td>1.8399</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>B</td>\n",
       "      <td>1.3387</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>LSTAT</td>\n",
       "      <td>2.8125</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   coef_name       vif\n",
       "0      const  597.5487\n",
       "1       CRIM    1.7145\n",
       "2         ZN    2.3328\n",
       "3      INDUS    3.9434\n",
       "4       CHAS    1.0788\n",
       "5        NOX    4.4103\n",
       "6         RM    1.8404\n",
       "7        AGE    3.3268\n",
       "8        DIS    4.2229\n",
       "9        RAD    7.3143\n",
       "10       TAX    8.5089\n",
       "11   PTRATIO    1.8399\n",
       "12         B    1.3387\n",
       "13     LSTAT    2.8125"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vif = []\n",
    "for i in range(len(x_incl_const.columns)):\n",
    "    result = variance_inflation_factor(x_incl_const.values, i)\n",
    "    vif.append(round(result, 4))\n",
    "\n",
    "pd.DataFrame({'coef_name':x_incl_const.columns,\n",
    "                     'vif': vif})\n",
    "\n",
    "# If VIF Testing results with values more than 10, then we have to take care of multicollinearity in our dataset\n",
    "# If not, then multicollinearity will not affect major changes in our model"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e5f9222b",
   "metadata": {},
   "source": [
    "## Model Simplification & Basiyan Informtion Criterion (BIC)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "edba7a84",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "BIC value : -139.74997769478898\n",
      "RSS value : 0.7930234826697583\n"
     ]
    }
   ],
   "source": [
    "# Orignal model with all the features\n",
    "x_incl_const = sm.add_constant(X_train)\n",
    "model = sm.OLS(y_train, x_incl_const)\n",
    "result = model.fit()\n",
    "\n",
    "orignal_coef = pd.DataFrame({'coef':result.params, 'p-values':round(result.pvalues, 4)})\n",
    "\n",
    "print(\"BIC value :\",result.bic)\n",
    "print(\"RSS value :\",result.rsquared)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "c8427ce6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "BIC value : -149.49934294224678\n",
      "RSS value : 0.7918657661852815\n"
     ]
    }
   ],
   "source": [
    "# Reducaed Model removing AGE , INDUS feature\n",
    "\n",
    "reduced_model = X_train.drop(['AGE', 'INDUS'], 1)\n",
    "\n",
    "x_incl_const = sm.add_constant(reduced_model)\n",
    "model = sm.OLS(y_train, x_incl_const)\n",
    "result = model.fit()\n",
    "\n",
    "orignal_minus_coef = pd.DataFrame({'coef':result.params, 'p-values':round(result.pvalues, 4)})\n",
    "\n",
    "print(\"BIC value :\",result.bic)\n",
    "print(\"RSS value :\",result.rsquared)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4f917448",
   "metadata": {},
   "source": [
    "## Residual and Residual Plots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "526cd969",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Modified model:  data tranforming with log and dropping two features\n",
    "prices = np.log(data['Price'])\n",
    "features = data.drop(['Price', 'INDUS', 'AGE'], axis=1)\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(features, prices,\n",
    "                                                    test_size=0.2, \n",
    "                                                    random_state=10)\n",
    "\n",
    "# StatsModel use\n",
    "\n",
    "x_incl_const = sm.add_constant(X_train)\n",
    "model = sm.OLS(y_train, x_incl_const)\n",
    "result = model.fit()\n",
    "\n",
    "# Residuals\n",
    "# residuals = y_train - result.fittedvalues   -> manual\n",
    "# result.resid\n",
    "\n",
    "# Graph of Actual vs Residual\n",
    "\n",
    "corr = round(y_train.corr(result.fittedvalues), 3)\n",
    "\n",
    "plt.figure(figsize=(15, 8))\n",
    "plt.scatter(y_train, result.fittedvalues, alpha=0.6)\n",
    "plt.plot(y_train, y_train, color='cyan', linewidth=4)\n",
    "plt.xlabel('Training Log values $y _i$ (Actual Values)', fontsize=12)\n",
    "plt.ylabel('Values Fitted in the model $ \\hat y_i $(Predicted Values)', fontsize=12)\n",
    "plt.title(f'Log Prices $y _i$ VS Predicted Prices $ \\hat y_i$ with correlation {corr}', fontsize=17)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "af126898",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Residual VS Predicted\n",
    "plt.figure(figsize=(15, 8))\n",
    "plt.scatter(result.fittedvalues, result.resid, alpha=0.6, c='blue')\n",
    "plt.xlabel('Predicted Log values $y _i$ (Actual Values)', fontsize=12)\n",
    "plt.ylabel('Residuals', fontsize=12)\n",
    "plt.title(f'Residual VS Predicted ', fontsize=17)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "f58239d3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Distribution analysis-> checking for normality in our residual values\n",
    "# A normal distribution consists of skew=0 and mean=0 of residual values\n",
    "\n",
    "resid_mean = round(result.resid.mean(), 3)\n",
    "resid_skew = round(result.resid.skew(), 3)\n",
    "\n",
    "sns.displot(result.resid, kde='true', color='navy')\n",
    "plt.title(f'Distribution of residual values with skew ({resid_skew}) & mean ({resid_mean})')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "9cc90f80",
   "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>MSE</th>\n",
       "      <th>RSS</th>\n",
       "      <th>RMSE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Modified Log Values</th>\n",
       "      <td>0.035</td>\n",
       "      <td>0.792</td>\n",
       "      <td>0.187083</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Reduced Log Values</th>\n",
       "      <td>0.068</td>\n",
       "      <td>0.592</td>\n",
       "      <td>0.260768</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Orignal Values</th>\n",
       "      <td>19.921</td>\n",
       "      <td>0.750</td>\n",
       "      <td>4.463295</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        MSE    RSS      RMSE\n",
       "Modified Log Values   0.035  0.792  0.187083\n",
       "Reduced Log Values    0.068  0.592  0.260768\n",
       "Orignal Values       19.921  0.750  4.463295"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check MSE & RSS of all the possible models\n",
    "\n",
    "#########################\n",
    "# Orignal Model\n",
    "prices = data['Price']\n",
    "features = data.drop(['Price'], axis=1)\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(features, prices,\n",
    "                                                    test_size=0.2, \n",
    "                                                    random_state=10)\n",
    "# StatsModel use\n",
    "\n",
    "x_incl_const = sm.add_constant(X_train)\n",
    "model = sm.OLS(y_train, x_incl_const)\n",
    "result = model.fit()\n",
    "\n",
    "mse_og = round(result.mse_resid, 3)\n",
    "rss_og = round(result.rsquared, 3)\n",
    "\n",
    "########################\n",
    "# Modified log model with dropping specific features\n",
    "prices = np.log(data['Price'])\n",
    "features = data.drop(['Price', 'INDUS', 'AGE'], axis=1)\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(features, prices,\n",
    "                                                    test_size=0.2, \n",
    "                                                    random_state=10)\n",
    "# StatsModel use\n",
    "\n",
    "x_incl_const = sm.add_constant(X_train)\n",
    "model = sm.OLS(y_train, x_incl_const)\n",
    "result = model.fit()\n",
    "\n",
    "mse_log = round(result.mse_resid, 3)\n",
    "rss_log = round(result.rsquared, 3)\n",
    "\n",
    "########################\n",
    "# Reduced log model with dropping some features\n",
    "prices = np.log(data['Price'])\n",
    "features = data.drop(['Price', 'INDUS', 'AGE', 'LSTAT', 'CRIM', 'ZN', 'NOX'], axis=1)\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(features, prices,\n",
    "                                                    test_size=0.2, \n",
    "                                                    random_state=10)\n",
    "# StatsModel use\n",
    "\n",
    "x_incl_const = sm.add_constant(X_train)\n",
    "model = sm.OLS(y_train, x_incl_const)\n",
    "result = model.fit()\n",
    "\n",
    "mse_log_omit = round(result.mse_resid, 3)\n",
    "rss_log_omit = round(result.rsquared, 3)\n",
    "\n",
    "\n",
    "analysis = pd.DataFrame({'MSE': [mse_log, mse_log_omit, mse_og], 'RSS':[rss_log, rss_log_omit, rss_og],\n",
    "                        'RMSE': [np.sqrt(mse_log), np.sqrt(mse_log_omit), np.sqrt(mse_og)] },\n",
    "                       index=['Modified Log Values', 'Reduced Log Values', 'Orignal Values'])\n",
    "analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cd872748",
   "metadata": {},
   "source": [
    "#### This tells us that our modified log model with specific features dropped is the best fitted for our dataset as it gives least error of 0.035 with satisfied r-squared value i.e. 0.792"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "5af766a8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " 1 std deviation is 0.18708286933869708\n",
      " 2 std deviation is 0.37416573867739417\n",
      "The Upper Bound prediction for 95% prediction interval is : $ 43613.342332399385\n",
      "The Upper Bound prediction for 95% prediction interval is : $ 20635.88690682414\n"
     ]
    }
   ],
   "source": [
    "print(' 1 std deviation is', np.sqrt(mse_log))\n",
    "print(' 2 std deviation is', 2*np.sqrt(mse_log))\n",
    "\n",
    "\n",
    "# Prediction for upper bound of $ 30000 house\n",
    "upper_bound = np.log(30000) + 2*np.sqrt(mse_log)\n",
    "print('The Upper Bound prediction for 95% prediction interval is : $', np.e**(upper_bound)) #as upper bound is in log\n",
    "\n",
    "# Prediction for lower bound of $ 30000 house\n",
    "lower_bound = np.log(30000) - 2*np.sqrt(mse_log)\n",
    "print('The Upper Bound prediction for 95% prediction interval is : $', np.e**(lower_bound)) #as lower bound is in log"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "921bc062",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "        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>CRIM</th>\n",
       "      <th>ZN</th>\n",
       "      <th>INDUS</th>\n",
       "      <th>CHAS</th>\n",
       "      <th>NOX</th>\n",
       "      <th>RM</th>\n",
       "      <th>AGE</th>\n",
       "      <th>DIS</th>\n",
       "      <th>RAD</th>\n",
       "      <th>TAX</th>\n",
       "      <th>PTRATIO</th>\n",
       "      <th>B</th>\n",
       "      <th>LSTAT</th>\n",
       "      <th>Price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.00632</td>\n",
       "      <td>18.0</td>\n",
       "      <td>2.31</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.538</td>\n",
       "      <td>6.575</td>\n",
       "      <td>65.2</td>\n",
       "      <td>4.0900</td>\n",
       "      <td>1.0</td>\n",
       "      <td>296.0</td>\n",
       "      <td>15.3</td>\n",
       "      <td>396.90</td>\n",
       "      <td>4.98</td>\n",
       "      <td>24.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.02731</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.469</td>\n",
       "      <td>6.421</td>\n",
       "      <td>78.9</td>\n",
       "      <td>4.9671</td>\n",
       "      <td>2.0</td>\n",
       "      <td>242.0</td>\n",
       "      <td>17.8</td>\n",
       "      <td>396.90</td>\n",
       "      <td>9.14</td>\n",
       "      <td>21.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.02729</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.469</td>\n",
       "      <td>7.185</td>\n",
       "      <td>61.1</td>\n",
       "      <td>4.9671</td>\n",
       "      <td>2.0</td>\n",
       "      <td>242.0</td>\n",
       "      <td>17.8</td>\n",
       "      <td>392.83</td>\n",
       "      <td>4.03</td>\n",
       "      <td>34.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.03237</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.18</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.458</td>\n",
       "      <td>6.998</td>\n",
       "      <td>45.8</td>\n",
       "      <td>6.0622</td>\n",
       "      <td>3.0</td>\n",
       "      <td>222.0</td>\n",
       "      <td>18.7</td>\n",
       "      <td>394.63</td>\n",
       "      <td>2.94</td>\n",
       "      <td>33.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.06905</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.18</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.458</td>\n",
       "      <td>7.147</td>\n",
       "      <td>54.2</td>\n",
       "      <td>6.0622</td>\n",
       "      <td>3.0</td>\n",
       "      <td>222.0</td>\n",
       "      <td>18.7</td>\n",
       "      <td>396.90</td>\n",
       "      <td>5.33</td>\n",
       "      <td>36.2</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>501</th>\n",
       "      <td>0.06263</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.93</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.573</td>\n",
       "      <td>6.593</td>\n",
       "      <td>69.1</td>\n",
       "      <td>2.4786</td>\n",
       "      <td>1.0</td>\n",
       "      <td>273.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>391.99</td>\n",
       "      <td>9.67</td>\n",
       "      <td>22.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>502</th>\n",
       "      <td>0.04527</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.93</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.573</td>\n",
       "      <td>6.120</td>\n",
       "      <td>76.7</td>\n",
       "      <td>2.2875</td>\n",
       "      <td>1.0</td>\n",
       "      <td>273.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>396.90</td>\n",
       "      <td>9.08</td>\n",
       "      <td>20.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>503</th>\n",
       "      <td>0.06076</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.93</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.573</td>\n",
       "      <td>6.976</td>\n",
       "      <td>91.0</td>\n",
       "      <td>2.1675</td>\n",
       "      <td>1.0</td>\n",
       "      <td>273.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>396.90</td>\n",
       "      <td>5.64</td>\n",
       "      <td>23.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>504</th>\n",
       "      <td>0.10959</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.93</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.573</td>\n",
       "      <td>6.794</td>\n",
       "      <td>89.3</td>\n",
       "      <td>2.3889</td>\n",
       "      <td>1.0</td>\n",
       "      <td>273.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>393.45</td>\n",
       "      <td>6.48</td>\n",
       "      <td>22.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>505</th>\n",
       "      <td>0.04741</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.93</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.573</td>\n",
       "      <td>6.030</td>\n",
       "      <td>80.8</td>\n",
       "      <td>2.5050</td>\n",
       "      <td>1.0</td>\n",
       "      <td>273.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>396.90</td>\n",
       "      <td>7.88</td>\n",
       "      <td>11.9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>506 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        CRIM    ZN  INDUS  CHAS    NOX     RM   AGE     DIS  RAD    TAX  \\\n",
       "0    0.00632  18.0   2.31   0.0  0.538  6.575  65.2  4.0900  1.0  296.0   \n",
       "1    0.02731   0.0   7.07   0.0  0.469  6.421  78.9  4.9671  2.0  242.0   \n",
       "2    0.02729   0.0   7.07   0.0  0.469  7.185  61.1  4.9671  2.0  242.0   \n",
       "3    0.03237   0.0   2.18   0.0  0.458  6.998  45.8  6.0622  3.0  222.0   \n",
       "4    0.06905   0.0   2.18   0.0  0.458  7.147  54.2  6.0622  3.0  222.0   \n",
       "..       ...   ...    ...   ...    ...    ...   ...     ...  ...    ...   \n",
       "501  0.06263   0.0  11.93   0.0  0.573  6.593  69.1  2.4786  1.0  273.0   \n",
       "502  0.04527   0.0  11.93   0.0  0.573  6.120  76.7  2.2875  1.0  273.0   \n",
       "503  0.06076   0.0  11.93   0.0  0.573  6.976  91.0  2.1675  1.0  273.0   \n",
       "504  0.10959   0.0  11.93   0.0  0.573  6.794  89.3  2.3889  1.0  273.0   \n",
       "505  0.04741   0.0  11.93   0.0  0.573  6.030  80.8  2.5050  1.0  273.0   \n",
       "\n",
       "     PTRATIO       B  LSTAT  Price  \n",
       "0       15.3  396.90   4.98   24.0  \n",
       "1       17.8  396.90   9.14   21.6  \n",
       "2       17.8  392.83   4.03   34.7  \n",
       "3       18.7  394.63   2.94   33.4  \n",
       "4       18.7  396.90   5.33   36.2  \n",
       "..       ...     ...    ...    ...  \n",
       "501     21.0  391.99   9.67   22.4  \n",
       "502     21.0  396.90   9.08   20.6  \n",
       "503     21.0  396.90   5.64   23.9  \n",
       "504     21.0  393.45   6.48   22.0  \n",
       "505     21.0  396.90   7.88   11.9  \n",
       "\n",
       "[506 rows x 14 columns]"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "043dab88",
   "metadata": {},
   "outputs": [],
   "source": [
    "## Getting module import\n",
    "import boston_valuation as val"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "370b93fa",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Upper Bound in dollar is : $ 1013800.0\n",
      "Actual estimation in dollar is : $ 840500.0\n",
      "Lower Bound in dollar is : $ 696800.0\n",
      "Interval is 68\n"
     ]
    }
   ],
   "source": [
    "val.get_price_estimate(10, 25, 25, True, False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "afb31a91",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cd46fda3",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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