data_visualization/data_visualization.ipynb

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   "version": "3.8.0-final"
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 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd \n",
    "from scipy import stats\n",
    "pd.set_option(\"display.max_rows\", None)\n",
    "\n",
    "import plotly.graph_objects as go\n",
    "from plotly.subplots import make_subplots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": "(1460, 81)"
     },
     "metadata": {},
     "execution_count": 2
    }
   ],
   "source": [
    "# load dataset and visualize columns\n",
    "df = pd.read_csv(\"../data/raw/train.csv\")\n",
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": "                     0        1        2        3        4\nId                   1        2        3        4        5\nMSSubClass          60       20       60       70       60\nMSZoning            RL       RL       RL       RL       RL\nLotFrontage         65       80       68       60       84\nLotArea           8450     9600    11250     9550    14260\nStreet            Pave     Pave     Pave     Pave     Pave\nAlley              NaN      NaN      NaN      NaN      NaN\nLotShape           Reg      Reg      IR1      IR1      IR1\nLandContour        Lvl      Lvl      Lvl      Lvl      Lvl\nUtilities       AllPub   AllPub   AllPub   AllPub   AllPub\nLotConfig       Inside      FR2   Inside   Corner      FR2\nLandSlope          Gtl      Gtl      Gtl      Gtl      Gtl\nNeighborhood   CollgCr  Veenker  CollgCr  Crawfor  NoRidge\nCondition1        Norm    Feedr     Norm     Norm     Norm\nCondition2        Norm     Norm     Norm     Norm     Norm\nBldgType          1Fam     1Fam     1Fam     1Fam     1Fam\nHouseStyle      2Story   1Story   2Story   2Story   2Story\nOverallQual          7        6        7        7        8\nOverallCond          5        8        5        5        5\nYearBuilt         2003     1976     2001     1915     2000\nYearRemodAdd      2003     1976     2002     1970     2000\nRoofStyle        Gable    Gable    Gable    Gable    Gable\nRoofMatl       CompShg  CompShg  CompShg  CompShg  CompShg\nExterior1st    VinylSd  MetalSd  VinylSd  Wd Sdng  VinylSd\nExterior2nd    VinylSd  MetalSd  VinylSd  Wd Shng  VinylSd\nMasVnrType     BrkFace     None  BrkFace     None  BrkFace\nMasVnrArea         196        0      162        0      350\nExterQual           Gd       TA       Gd       TA       Gd\nExterCond           TA       TA       TA       TA       TA\nFoundation       PConc   CBlock    PConc   BrkTil    PConc\nBsmtQual            Gd       Gd       Gd       TA       Gd\nBsmtCond            TA       TA       TA       Gd       TA\nBsmtExposure        No       Gd       Mn       No       Av\nBsmtFinType1       GLQ      ALQ      GLQ      ALQ      GLQ\nBsmtFinSF1         706      978      486      216      655\nBsmtFinType2       Unf      Unf      Unf      Unf      Unf\nBsmtFinSF2           0        0        0        0        0\nBsmtUnfSF          150      284      434      540      490\nTotalBsmtSF        856     1262      920      756     1145\nHeating           GasA     GasA     GasA     GasA     GasA\nHeatingQC           Ex       Ex       Ex       Gd       Ex\nCentralAir           Y        Y        Y        Y        Y\nElectrical       SBrkr    SBrkr    SBrkr    SBrkr    SBrkr\n1stFlrSF           856     1262      920      961     1145\n2ndFlrSF           854        0      866      756     1053\nLowQualFinSF         0        0        0        0        0\nGrLivArea         1710     1262     1786     1717     2198\nBsmtFullBath         1        0        1        1        1\nBsmtHalfBath         0        1        0        0        0\nFullBath             2        2        2        1        2\nHalfBath             1        0        1        0        1\nBedroomAbvGr         3        3        3        3        4\nKitchenAbvGr         1        1        1        1        1\nKitchenQual         Gd       TA       Gd       Gd       Gd\nTotRmsAbvGrd         8        6        6        7        9\nFunctional         Typ      Typ      Typ      Typ      Typ\nFireplaces           0        1        1        1        1\nFireplaceQu        NaN       TA       TA       Gd       TA\nGarageType      Attchd   Attchd   Attchd   Detchd   Attchd\nGarageYrBlt       2003     1976     2001     1998     2000\nGarageFinish       RFn      RFn      RFn      Unf      RFn\nGarageCars           2        2        2        3        3\nGarageArea         548      460      608      642      836\nGarageQual          TA       TA       TA       TA       TA\nGarageCond          TA       TA       TA       TA       TA\nPavedDrive           Y        Y        Y        Y        Y\nWoodDeckSF           0      298        0        0      192\nOpenPorchSF         61        0       42       35       84\nEnclosedPorch        0        0        0      272        0\n3SsnPorch            0        0        0        0        0\nScreenPorch          0        0        0        0        0\nPoolArea             0        0        0        0        0\nPoolQC             NaN      NaN      NaN      NaN      NaN\nFence              NaN      NaN      NaN      NaN      NaN\nMiscFeature        NaN      NaN      NaN      NaN      NaN\nMiscVal              0        0        0        0        0\nMoSold               2        5        9        2       12\nYrSold            2008     2007     2008     2006     2008\nSaleType            WD       WD       WD       WD       WD\nSaleCondition   Normal   Normal   Normal  Abnorml   Normal\nSalePrice       208500   181500   223500   140000   250000",
      "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>0</th>\n      <th>1</th>\n      <th>2</th>\n      <th>3</th>\n      <th>4</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>Id</th>\n      <td>1</td>\n      <td>2</td>\n      <td>3</td>\n      <td>4</td>\n      <td>5</td>\n    </tr>\n    <tr>\n      <th>MSSubClass</th>\n      <td>60</td>\n      <td>20</td>\n      <td>60</td>\n      <td>70</td>\n      <td>60</td>\n    </tr>\n    <tr>\n      <th>MSZoning</th>\n      <td>RL</td>\n      <td>RL</td>\n      <td>RL</td>\n      <td>RL</td>\n      <td>RL</td>\n    </tr>\n    <tr>\n      <th>LotFrontage</th>\n      <td>65</td>\n      <td>80</td>\n      <td>68</td>\n      <td>60</td>\n      <td>84</td>\n    </tr>\n    <tr>\n      <th>LotArea</th>\n      <td>8450</td>\n      <td>9600</td>\n      <td>11250</td>\n      <td>9550</td>\n      <td>14260</td>\n    </tr>\n    <tr>\n      <th>Street</th>\n      <td>Pave</td>\n      <td>Pave</td>\n      <td>Pave</td>\n      <td>Pave</td>\n      <td>Pave</td>\n    </tr>\n    <tr>\n      <th>Alley</th>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>LotShape</th>\n      <td>Reg</td>\n      <td>Reg</td>\n      <td>IR1</td>\n      <td>IR1</td>\n      <td>IR1</td>\n    </tr>\n    <tr>\n      <th>LandContour</th>\n      <td>Lvl</td>\n      <td>Lvl</td>\n      <td>Lvl</td>\n      <td>Lvl</td>\n      <td>Lvl</td>\n    </tr>\n    <tr>\n      <th>Utilities</th>\n      <td>AllPub</td>\n      <td>AllPub</td>\n      <td>AllPub</td>\n      <td>AllPub</td>\n      <td>AllPub</td>\n    </tr>\n    <tr>\n      <th>LotConfig</th>\n      <td>Inside</td>\n      <td>FR2</td>\n      <td>Inside</td>\n      <td>Corner</td>\n      <td>FR2</td>\n    </tr>\n    <tr>\n      <th>LandSlope</th>\n      <td>Gtl</td>\n      <td>Gtl</td>\n      <td>Gtl</td>\n      <td>Gtl</td>\n      <td>Gtl</td>\n    </tr>\n    <tr>\n      <th>Neighborhood</th>\n      <td>CollgCr</td>\n      <td>Veenker</td>\n      <td>CollgCr</td>\n      <td>Crawfor</td>\n      <td>NoRidge</td>\n    </tr>\n    <tr>\n      <th>Condition1</th>\n      <td>Norm</td>\n      <td>Feedr</td>\n      <td>Norm</td>\n      <td>Norm</td>\n      <td>Norm</td>\n    </tr>\n    <tr>\n      <th>Condition2</th>\n      <td>Norm</td>\n      <td>Norm</td>\n      <td>Norm</td>\n      <td>Norm</td>\n      <td>Norm</td>\n    </tr>\n    <tr>\n      <th>BldgType</th>\n      <td>1Fam</td>\n      <td>1Fam</td>\n      <td>1Fam</td>\n      <td>1Fam</td>\n      <td>1Fam</td>\n    </tr>\n    <tr>\n      <th>HouseStyle</th>\n      <td>2Story</td>\n      <td>1Story</td>\n      <td>2Story</td>\n      <td>2Story</td>\n      <td>2Story</td>\n    </tr>\n    <tr>\n      <th>OverallQual</th>\n      <td>7</td>\n      <td>6</td>\n      <td>7</td>\n      <td>7</td>\n      <td>8</td>\n    </tr>\n    <tr>\n      <th>OverallCond</th>\n      <td>5</td>\n      <td>8</td>\n      <td>5</td>\n      <td>5</td>\n      <td>5</td>\n    </tr>\n    <tr>\n      <th>YearBuilt</th>\n      <td>2003</td>\n      <td>1976</td>\n      <td>2001</td>\n      <td>1915</td>\n      <td>2000</td>\n    </tr>\n    <tr>\n      <th>YearRemodAdd</th>\n      <td>2003</td>\n      <td>1976</td>\n      <td>2002</td>\n      <td>1970</td>\n      <td>2000</td>\n    </tr>\n    <tr>\n      <th>RoofStyle</th>\n      <td>Gable</td>\n      <td>Gable</td>\n      <td>Gable</td>\n      <td>Gable</td>\n      <td>Gable</td>\n    </tr>\n    <tr>\n      <th>RoofMatl</th>\n      <td>CompShg</td>\n      <td>CompShg</td>\n      <td>CompShg</td>\n      <td>CompShg</td>\n      <td>CompShg</td>\n    </tr>\n    <tr>\n      <th>Exterior1st</th>\n      <td>VinylSd</td>\n      <td>MetalSd</td>\n      <td>VinylSd</td>\n      <td>Wd Sdng</td>\n      <td>VinylSd</td>\n    </tr>\n    <tr>\n      <th>Exterior2nd</th>\n      <td>VinylSd</td>\n      <td>MetalSd</td>\n      <td>VinylSd</td>\n      <td>Wd Shng</td>\n      <td>VinylSd</td>\n    </tr>\n    <tr>\n      <th>MasVnrType</th>\n      <td>BrkFace</td>\n      <td>None</td>\n      <td>BrkFace</td>\n      <td>None</td>\n      <td>BrkFace</td>\n    </tr>\n    <tr>\n      <th>MasVnrArea</th>\n      <td>196</td>\n      <td>0</td>\n      <td>162</td>\n      <td>0</td>\n      <td>350</td>\n    </tr>\n    <tr>\n      <th>ExterQual</th>\n      <td>Gd</td>\n      <td>TA</td>\n      <td>Gd</td>\n      <td>TA</td>\n      <td>Gd</td>\n    </tr>\n    <tr>\n      <th>ExterCond</th>\n      <td>TA</td>\n      <td>TA</td>\n      <td>TA</td>\n      <td>TA</td>\n      <td>TA</td>\n    </tr>\n    <tr>\n      <th>Foundation</th>\n      <td>PConc</td>\n      <td>CBlock</td>\n      <td>PConc</td>\n      <td>BrkTil</td>\n      <td>PConc</td>\n    </tr>\n    <tr>\n      <th>BsmtQual</th>\n      <td>Gd</td>\n      <td>Gd</td>\n      <td>Gd</td>\n      <td>TA</td>\n      <td>Gd</td>\n    </tr>\n    <tr>\n      <th>BsmtCond</th>\n      <td>TA</td>\n      <td>TA</td>\n      <td>TA</td>\n      <td>Gd</td>\n      <td>TA</td>\n    </tr>\n    <tr>\n      <th>BsmtExposure</th>\n      <td>No</td>\n      <td>Gd</td>\n      <td>Mn</td>\n      <td>No</td>\n      <td>Av</td>\n    </tr>\n    <tr>\n      <th>BsmtFinType1</th>\n      <td>GLQ</td>\n      <td>ALQ</td>\n      <td>GLQ</td>\n      <td>ALQ</td>\n      <td>GLQ</td>\n    </tr>\n    <tr>\n      <th>BsmtFinSF1</th>\n      <td>706</td>\n      <td>978</td>\n      <td>486</td>\n      <td>216</td>\n      <td>655</td>\n    </tr>\n    <tr>\n      <th>BsmtFinType2</th>\n      <td>Unf</td>\n      <td>Unf</td>\n      <td>Unf</td>\n      <td>Unf</td>\n      <td>Unf</td>\n    </tr>\n    <tr>\n      <th>BsmtFinSF2</th>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>BsmtUnfSF</th>\n      <td>150</td>\n      <td>284</td>\n      <td>434</td>\n      <td>540</td>\n      <td>490</td>\n    </tr>\n    <tr>\n      <th>TotalBsmtSF</th>\n      <td>856</td>\n      <td>1262</td>\n      <td>920</td>\n      <td>756</td>\n      <td>1145</td>\n    </tr>\n    <tr>\n      <th>Heating</th>\n      <td>GasA</td>\n      <td>GasA</td>\n      <td>GasA</td>\n      <td>GasA</td>\n      <td>GasA</td>\n    </tr>\n    <tr>\n      <th>HeatingQC</th>\n      <td>Ex</td>\n      <td>Ex</td>\n      <td>Ex</td>\n      <td>Gd</td>\n      <td>Ex</td>\n    </tr>\n    <tr>\n      <th>CentralAir</th>\n      <td>Y</td>\n      <td>Y</td>\n      <td>Y</td>\n      <td>Y</td>\n      <td>Y</td>\n    </tr>\n    <tr>\n      <th>Electrical</th>\n      <td>SBrkr</td>\n      <td>SBrkr</td>\n      <td>SBrkr</td>\n      <td>SBrkr</td>\n      <td>SBrkr</td>\n    </tr>\n    <tr>\n      <th>1stFlrSF</th>\n      <td>856</td>\n      <td>1262</td>\n      <td>920</td>\n      <td>961</td>\n      <td>1145</td>\n    </tr>\n    <tr>\n      <th>2ndFlrSF</th>\n      <td>854</td>\n      <td>0</td>\n      <td>866</td>\n      <td>756</td>\n      <td>1053</td>\n    </tr>\n    <tr>\n      <th>LowQualFinSF</th>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>GrLivArea</th>\n      <td>1710</td>\n      <td>1262</td>\n      <td>1786</td>\n      <td>1717</td>\n      <td>2198</td>\n    </tr>\n    <tr>\n      <th>BsmtFullBath</th>\n      <td>1</td>\n      <td>0</td>\n      <td>1</td>\n      <td>1</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>BsmtHalfBath</th>\n      <td>0</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>FullBath</th>\n      <td>2</td>\n      <td>2</td>\n      <td>2</td>\n      <td>1</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>HalfBath</th>\n      <td>1</td>\n      <td>0</td>\n      <td>1</td>\n      <td>0</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>BedroomAbvGr</th>\n      <td>3</td>\n      <td>3</td>\n      <td>3</td>\n      <td>3</td>\n      <td>4</td>\n    </tr>\n    <tr>\n      <th>KitchenAbvGr</th>\n      <td>1</td>\n      <td>1</td>\n      <td>1</td>\n      <td>1</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>KitchenQual</th>\n      <td>Gd</td>\n      <td>TA</td>\n      <td>Gd</td>\n      <td>Gd</td>\n      <td>Gd</td>\n    </tr>\n    <tr>\n      <th>TotRmsAbvGrd</th>\n      <td>8</td>\n      <td>6</td>\n      <td>6</td>\n      <td>7</td>\n      <td>9</td>\n    </tr>\n    <tr>\n      <th>Functional</th>\n      <td>Typ</td>\n      <td>Typ</td>\n      <td>Typ</td>\n      <td>Typ</td>\n      <td>Typ</td>\n    </tr>\n    <tr>\n      <th>Fireplaces</th>\n      <td>0</td>\n      <td>1</td>\n      <td>1</td>\n      <td>1</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>FireplaceQu</th>\n      <td>NaN</td>\n      <td>TA</td>\n      <td>TA</td>\n      <td>Gd</td>\n      <td>TA</td>\n    </tr>\n    <tr>\n      <th>GarageType</th>\n      <td>Attchd</td>\n      <td>Attchd</td>\n      <td>Attchd</td>\n      <td>Detchd</td>\n      <td>Attchd</td>\n    </tr>\n    <tr>\n      <th>GarageYrBlt</th>\n      <td>2003</td>\n      <td>1976</td>\n      <td>2001</td>\n      <td>1998</td>\n      <td>2000</td>\n    </tr>\n    <tr>\n      <th>GarageFinish</th>\n      <td>RFn</td>\n      <td>RFn</td>\n      <td>RFn</td>\n      <td>Unf</td>\n      <td>RFn</td>\n    </tr>\n    <tr>\n      <th>GarageCars</th>\n      <td>2</td>\n      <td>2</td>\n      <td>2</td>\n      <td>3</td>\n      <td>3</td>\n    </tr>\n    <tr>\n      <th>GarageArea</th>\n      <td>548</td>\n      <td>460</td>\n      <td>608</td>\n      <td>642</td>\n      <td>836</td>\n    </tr>\n    <tr>\n      <th>GarageQual</th>\n      <td>TA</td>\n      <td>TA</td>\n      <td>TA</td>\n      <td>TA</td>\n      <td>TA</td>\n    </tr>\n    <tr>\n      <th>GarageCond</th>\n      <td>TA</td>\n      <td>TA</td>\n      <td>TA</td>\n      <td>TA</td>\n      <td>TA</td>\n    </tr>\n    <tr>\n      <th>PavedDrive</th>\n      <td>Y</td>\n      <td>Y</td>\n      <td>Y</td>\n      <td>Y</td>\n      <td>Y</td>\n    </tr>\n    <tr>\n      <th>WoodDeckSF</th>\n      <td>0</td>\n      <td>298</td>\n      <td>0</td>\n      <td>0</td>\n      <td>192</td>\n    </tr>\n    <tr>\n      <th>OpenPorchSF</th>\n      <td>61</td>\n      <td>0</td>\n      <td>42</td>\n      <td>35</td>\n      <td>84</td>\n    </tr>\n    <tr>\n      <th>EnclosedPorch</th>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>272</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>3SsnPorch</th>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>ScreenPorch</th>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>PoolArea</th>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>PoolQC</th>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>Fence</th>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>MiscFeature</th>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>MiscVal</th>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>MoSold</th>\n      <td>2</td>\n      <td>5</td>\n      <td>9</td>\n      <td>2</td>\n      <td>12</td>\n    </tr>\n    <tr>\n      <th>YrSold</th>\n      <td>2008</td>\n      <td>2007</td>\n      <td>2008</td>\n      <td>2006</td>\n      <td>2008</td>\n    </tr>\n    <tr>\n      <th>SaleType</th>\n      <td>WD</td>\n      <td>WD</td>\n      <td>WD</td>\n      <td>WD</td>\n      <td>WD</td>\n    </tr>\n    <tr>\n      <th>SaleCondition</th>\n      <td>Normal</td>\n      <td>Normal</td>\n      <td>Normal</td>\n      <td>Abnorml</td>\n      <td>Normal</td>\n    </tr>\n    <tr>\n      <th>SalePrice</th>\n      <td>208500</td>\n      <td>181500</td>\n      <td>223500</td>\n      <td>140000</td>\n      <td>250000</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "metadata": {},
     "execution_count": 4
    }
   ],
   "source": [
    "# preview all 81 variables for first 5 instances\n",
    "df.head().T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "plotlyServerURL": "https://plot.ly"
       },
       "data": [
        {
         "hoverinfo": "x",
         "showlegend": false,
         "type": "histogram",
         "x": [
          208500,
          181500,
          223500,
          140000,
          250000,
          143000,
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   "source": [
    "fig = make_subplots(\n",
    "    rows=2, cols=2,\n",
    "    specs=[[{}, {\"rowspan\":2}],\n",
    "           [{}, None]],\n",
    "    horizontal_spacing=0.125,\n",
    "    vertical_spacing=0.125,\n",
    "    subplot_titles=(\"Histogram\", \"Violin Plot\", \"QQ Plot\")\n",
    "        )\n",
    "# calculate the quantiles for QQ plot\n",
    "qq = stats.probplot(df[\"SalePrice\"], dist='norm', sparams=(1))\n",
    "# lowest and highest quantiles\n",
    "x = np.array([qq[0][0][0], qq[0][0][-1]]) \n",
    "\n",
    "# plotting charts\n",
    "fig.add_traces([\n",
    "    go.Histogram(x=df[\"SalePrice\"],\n",
    "                 hoverinfo=\"x\", \n",
    "                 showlegend=False),\n",
    "    go.Violin(y=df[\"SalePrice\"],\n",
    "              box_visible=True, \n",
    "              line_color=\"black\",\n",
    "              meanline_visible=True,\n",
    "              fillcolor='lightseagreen',\n",
    "              opacity=0.8,\n",
    "              showlegend=False),\n",
    "    go.Scatter(x=qq[0][0], y=qq[0][1], \n",
    "               mode='markers',\n",
    "               showlegend=False),\n",
    "    go.Scatter(x=x, y=qq[1][1] + qq[1][0]*x,\n",
    "               showlegend=False,\n",
    "               mode='lines')\n",
    "        ],\n",
    "    rows=[1, 1, 2, 2],\n",
    "    cols=[1, 2, 1, 1]\n",
    ")\n",
    "\n",
    "# Update xaxis properties\n",
    "fig.update_xaxes(title_text=\"Quantiles\", row=2, col=1)\n",
    "\n",
    "# Update yaxis properties\n",
    "fig.update_yaxes(title_text=\"Counts\", row=1, col=1)\n",
    "fig.update_yaxes(title_text=\"SalePrice\", row=1, col=2)\n",
    "fig.update_yaxes(title_text=\"SalePrice\", row=2, col=1)\n",
    "\n",
    "fig.update_layout(\n",
    "    title=dict(\n",
    "        text=\"Sale Price Distribution\",\n",
    "        font=dict(\n",
    "            family=\"Arial\",\n",
    "            size=20)),\n",
    "\tshowlegend=False,\n",
    "\twidth=800,\n",
    "\theight=500\n",
    "    )\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
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    "# most correlated features to sale price\n",
    "corr= df.corr()[\"SalePrice\"].sort_values(ascending=False)[1:]\n",
    "corr_feat= corr.index\n",
    "corr_vals= corr.values\n",
    "\n",
    "# traffic light setting for fill colour\n",
    "fill = ['lime' if x >= .50 else \"red\" for x in corr_vals]\n",
    "\n",
    "# visual table of features correlation to SalePrice \n",
    "fig = go.Figure(data=[go.Table(\n",
    "    header=dict(values=[\"Features\", \"Correlation\"],\n",
    "                fill_color='lightgrey',\n",
    "                font=dict(family=\"Arial\", size=14, color=\"black\"),\n",
    "                align='center'),\n",
    "    cells=dict(values=[corr_feat, corr_vals],\n",
    "               fill_color=[fill],\n",
    "               height=22,\n",
    "               font=dict(family=\"Arial\", size=12),\n",
    "               align='left'))]\n",
    ")\n",
    "\n",
    "fig.update_layout(title=dict(\n",
    "                        text=\"Pearson's Correlation of features to SalePrice\",\n",
    "                        font=dict(\n",
    "                            family=\"Arial\",\n",
    "                            size=20\n",
    "                            ),\n",
    "                        ),\n",
    "\t\t          showlegend=False,\n",
    "\t\t          width=900,\n",
    "\t\t          height=650\n",
    "                  )\n",
    "fig.show()"
   ]
  },
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         "title": {
          "text": "SalePrice"
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     "metadata": {}
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   ],
   "source": [
    "# plotting 4 most correlated charts\n",
    "fig = make_subplots(\n",
    "    rows=2, cols=2,\n",
    "    horizontal_spacing=0.165,\n",
    "    vertical_spacing=0.165,\n",
    "    column_widths=[10, 10] ,\n",
    "    row_heights=[10, 10]\n",
    "        )\n",
    "fig.add_traces([\n",
    "    go.Box(x= df[\"OverallQual\"], y= df[\"SalePrice\"],\n",
    "           showlegend=False),\n",
    "    go.Box(x= df[\"GarageCars\"], y= df[\"SalePrice\"],\n",
    "           showlegend=False),\n",
    "    go.Scatter(x= df[\"GrLivArea\"], y= df[\"SalePrice\"], \n",
    "               mode='markers',\n",
    "               showlegend=False),\n",
    "    go.Scatter(x= df[\"GarageArea\"], y= df[\"SalePrice\"], \n",
    "               mode='markers',\n",
    "               showlegend=False),\n",
    "        ],\n",
    "    rows=[1, 2, 1, 2],\n",
    "    cols=[1, 1, 2, 2]\n",
    ")\n",
    "\n",
    "# Update xaxis properties\n",
    "fig.update_xaxes(title_text=\"OverallQual\", row=1, col=1)\n",
    "fig.update_xaxes(title_text=\"GarageCars\", row=1, col=2)\n",
    "fig.update_xaxes(title_text=\"GrLivArea\", row=2, col=1)\n",
    "fig.update_xaxes(title_text=\"GarageArea\", range=[0, 1500], row=2, col=2)\n",
    "\n",
    "# Update yaxis properties\n",
    "fig.update_yaxes(title_text=\"SalePrice\", row=1, col=1)\n",
    "fig.update_yaxes(title_text=\"SalePrice\", row=1, col=2)\n",
    "fig.update_yaxes(title_text=\"SalePrice\", row=2, col=1)\n",
    "fig.update_yaxes(title_text=\"SalePrice\", range=[0, 800000], row=2, col=2)\n",
    "\n",
    "fig.update_layout(\n",
    "    title=dict(\n",
    "        text=\"4 Most correlated features with SalePrice\",\n",
    "        font=dict(\n",
    "            family=\"Arial\",\n",
    "            size=20)),\n",
    "\tshowlegend=False,\n",
    "\twidth=900,\n",
    "\theight=600\n",
    "    )\n",
    "\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
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   "source": [
    "# correlation of features to each other \n",
    "fig = go.Figure(data=[\n",
    "    go.Heatmap(x=df.corr().columns.tolist(),\n",
    "               y=df.corr().columns.tolist(),\n",
    "               z=df.corr().values,\n",
    "               xgap=1.25, ygap=1.25,\n",
    "               colorbar_thickness=20,\n",
    "               colorbar_ticklen=3,\n",
    "    )]\n",
    ")\n",
    "\n",
    "fig.update_layout(title=dict(\n",
    "                        text=\"Feature Correlation Heatmap\",\n",
    "                        font=dict(\n",
    "                            family=\"Arial\",\n",
    "                            size=20\n",
    "                            ),\n",
    "                        ),\n",
    "\t\t          showlegend=False,\n",
    "\t\t          width=800,\n",
    "\t\t          height=550\n",
    "                  )\n",
    "\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
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    "# total number and percent of missing variables in train df\n",
    "total_missing = df.isnull().sum().sort_index(ascending=False)[df.isnull().sum().sort_values(ascending=False) != 0]\n",
    "percent_missing = round(df.isnull().sum().sort_values(ascending = False)/len(df)*100, 2)[round(df.isnull().sum().sort_values(ascending = False)/len(df)*100,2) != 0]\n",
    "\n",
    "# df of missing variables\n",
    "missing_df = pd.concat([total_missing, percent_missing], axis=1, keys=[\"total\", \"percent\"])\n",
    "\n",
    "features = missing_df.index\n",
    "total = missing_df.total\n",
    "percent = missing_df.percent\n",
    "\n",
    "# traffic light setting for fill colour\n",
    "fill = ['red' if x >= 75.0 else \"lime\" if x <= 25.0 else \"yellow\" for x in percent]\n",
    "\n",
    "# visual table of missing variables \n",
    "fig = go.Figure(data=[go.Table(\n",
    "    header=dict(values=[\"Features\", \"Total Missing Values\", \"Percentage\"],\n",
    "                fill_color='lightgrey',\n",
    "                font=dict(family=\"Arial\", size=14, color=\"black\"),\n",
    "                align='center'),\n",
    "    cells=dict(values=[features, total, percent],\n",
    "               fill_color=[fill],\n",
    "               height=22,\n",
    "               font=dict(family=\"Arial\", size=12),\n",
    "               align='left'))]\n",
    ")\n",
    "\n",
    "fig.update_layout(title=dict(\n",
    "                        text=\"Features with missing values\",\n",
    "                        font=dict(\n",
    "                            family=\"Arial\",\n",
    "                            size=20\n",
    "                            ),\n",
    "                        ),\n",
    "\t\t          showlegend=False,\n",
    "\t\t          width=900,\n",
    "\t\t          height=650\n",
    "                  )\n",
    "\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ]
}