Project - Housing Prices¶

Purpose/Goal:¶

To use the given data to create a regression algorithm that will accurately predict the prices of homes.

# Read in Libraries

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline
from sklearn.cross_validation import train_test_split as tts
from sklearn import linear_model
from sklearn.metrics import mean_squared_error, r2_score
import seaborn as sns

C:\Users\nwerner\AppData\Local\Continuum\Anaconda2\lib\site-packages\sklearn\cross_validation.py:41: DeprecationWarning: This module was deprecated in version 0.18 in favor of the model_selection module into which all the refactored classes and functions are moved. Also note that the interface of the new CV iterators are different from that of this module. This module will be removed in 0.20.
  "This module will be removed in 0.20.", DeprecationWarning)

# Read in Data

dfTrain = pd.read_csv('train.csv') # 1460 entries, 0 to 1459
dfTest = pd.read_csv('test.csv') # 1459 entries, 1460 to 2918
df = dfTrain.append(dfTest)

print len(dfTrain), len(dfTest), len(df)

1460 1459 2919

df.head()

df.tail()

df.describe()

df.corr()

corr = df.corr()

fig, ax = plt.subplots(figsize=(15,15))
sns.heatmap(corr, xticklabels = corr.columns.values, yticklabels = corr.columns.values, ax=ax)

<matplotlib.axes._subplots.AxesSubplot at 0x1fab8c50>

print corr['SalePrice'].sort_values(ascending=False)[:5], '\n'
print corr['SalePrice'].sort_values(ascending=False)[-5:]

SalePrice      1.000000
OverallQual    0.790982
GrLivArea      0.708624
GarageCars     0.640409
GarageArea     0.623431
Name: SalePrice, dtype: float64

YrSold          -0.028923
OverallCond     -0.077856
MSSubClass      -0.084284
EnclosedPorch   -0.128578
KitchenAbvGr    -0.135907
Name: SalePrice, dtype: float64

df.info()

<class 'pandas.core.frame.DataFrame'>
Int64Index: 2919 entries, 0 to 1458
Data columns (total 81 columns):
1stFlrSF         2919 non-null int64
2ndFlrSF         2919 non-null int64
3SsnPorch        2919 non-null int64
Alley            198 non-null object
BedroomAbvGr     2919 non-null int64
BldgType         2919 non-null object
BsmtCond         2837 non-null object
BsmtExposure     2837 non-null object
BsmtFinSF1       2918 non-null float64
BsmtFinSF2       2918 non-null float64
BsmtFinType1     2840 non-null object
BsmtFinType2     2839 non-null object
BsmtFullBath     2917 non-null float64
BsmtHalfBath     2917 non-null float64
BsmtQual         2838 non-null object
BsmtUnfSF        2918 non-null float64
CentralAir       2919 non-null object
Condition1       2919 non-null object
Condition2       2919 non-null object
Electrical       2918 non-null object
EnclosedPorch    2919 non-null int64
ExterCond        2919 non-null object
ExterQual        2919 non-null object
Exterior1st      2918 non-null object
Exterior2nd      2918 non-null object
Fence            571 non-null object
FireplaceQu      1499 non-null object
Fireplaces       2919 non-null int64
Foundation       2919 non-null object
FullBath         2919 non-null int64
Functional       2917 non-null object
GarageArea       2918 non-null float64
GarageCars       2918 non-null float64
GarageCond       2760 non-null object
GarageFinish     2760 non-null object
GarageQual       2760 non-null object
GarageType       2762 non-null object
GarageYrBlt      2760 non-null float64
GrLivArea        2919 non-null int64
HalfBath         2919 non-null int64
Heating          2919 non-null object
HeatingQC        2919 non-null object
HouseStyle       2919 non-null object
Id               2919 non-null int64
KitchenAbvGr     2919 non-null int64
KitchenQual      2918 non-null object
LandContour      2919 non-null object
LandSlope        2919 non-null object
LotArea          2919 non-null int64
LotConfig        2919 non-null object
LotFrontage      2433 non-null float64
LotShape         2919 non-null object
LowQualFinSF     2919 non-null int64
MSSubClass       2919 non-null int64
MSZoning         2915 non-null object
MasVnrArea       2896 non-null float64
MasVnrType       2895 non-null object
MiscFeature      105 non-null object
MiscVal          2919 non-null int64
MoSold           2919 non-null int64
Neighborhood     2919 non-null object
OpenPorchSF      2919 non-null int64
OverallCond      2919 non-null int64
OverallQual      2919 non-null int64
PavedDrive       2919 non-null object
PoolArea         2919 non-null int64
PoolQC           10 non-null object
RoofMatl         2919 non-null object
RoofStyle        2919 non-null object
SaleCondition    2919 non-null object
SalePrice        1460 non-null float64
SaleType         2918 non-null object
ScreenPorch      2919 non-null int64
Street           2919 non-null object
TotRmsAbvGrd     2919 non-null int64
TotalBsmtSF      2918 non-null float64
Utilities        2917 non-null object
WoodDeckSF       2919 non-null int64
YearBuilt        2919 non-null int64
YearRemodAdd     2919 non-null int64
YrSold           2919 non-null int64
dtypes: float64(12), int64(26), object(43)
memory usage: 1.8+ MB

df = df.drop_duplicates()
print len(df) # No Duplicates

2919

Null / Odd Value Hunting¶

for col in df:
    print col,np.sort(df[col].unique()), '\n'

# MSSubCLass - No 150 Value
# MSZoning - No 'A', 'I', 'RP'
# Alley - Hard Code: nan = 0, Grvl = 1, Pave = 2
# MasVnrArea - fillNan with 0 & convert to INTs
# BsmtQual, BsmtCond, BsmtExposure, BsmtFinType1, BsmtFinSF1, BsmtFinType2, BsmtFinSF2, BsmtUnfSF - guessing 'nan' equals No Basement
# Electrical - has nulls (not sure how to fill them)
# MiscVal -  will have to predict house price and then add on that feature afterwards

1stFlrSF [ 334  372  407 ..., 3820 4692 5095]

2ndFlrSF [   0  110  125  144  167  180  182  185  192  208  213  218  220  224  228
  240  245  252  272  297  299  304  308  312  316  319  320  322  325  328
  330  332  336  341  343  348  349  351  356  358  360  363  368  370  371
  375  376  378  380  384  390  396  400  403  406  408  412  420  423  424
  425  428  430  432  434  436  438  439  441  442  444  445  448  450  453
  454  455  456  457  462  464  465  466  467  468  472  473  475  476  477
  482  486  488  492  493  494  495  496  498  499  500  501  502  504  505
  510  511  512  514  516  517  518  520  521  523  524  525  526  527  528
  530  531  532  533  534  536  537  539  540  541  544  545  546  547  548
  549  550  551  552  554  556  557  558  560  561  563  564  566  567  568
  570  571  573  574  576  580  581  582  583  584  585  586  587  588  589
  590  591  592  594  595  596  600  601  602  604  605  606  608  610  611
  612  614  615  616  620  622  623  624  625  626  628  629  630  631  634
  636  638  639  640  642  644  645  646  648  649  650  651  653  656  658
  659  660  661  662  663  664  665  668  670  671  672  673  674  676  677
  678  679  680  682  683  684  685  686  687  688  689  690  691  694  695
  697  698  700  701  702  703  704  707  708  709  711  712  713  714  715
  716  717  718  720  725  726  727  728  729  730  732  734  735  736  738
  739  741  742  743  744  745  747  748  750  752  753  754  755  756  757
  760  761  762  764  765  766  767  768  769  770  772  775  776  778  779
  780  782  783  784  785  786  787  788  790  792  793  794  795  796  797
  798  800  804  806  807  808  809  810  811  812  813  814  815  816  817
  818  821  823  825  826  827  828  829  830  831  832  833  834  836  838
  839  840  841  842  843  844  845  846  848  850  851  854  855  857  858
  860  861  862  863  864  866  867  868  869  870  871  872  873  874  875
  876  878  880  881  882  883  884  885  886  887  888  890  892  893  895
  896  897  898  899  900  901  902  903  904  908  910  912  913  914  915
  916  917  918  919  920  923  924  925  926  927  928  929  930  932  933
  936  939  940  941  942  943  950  954  955  956  957  959  960  966  967
  971  972  973  975  976  977  978  979  980  981  983  984  985  988  989
  990  992  994  995  998 1000 1001 1004 1005 1007 1008 1012 1015 1017 1020
 1028 1029 1031 1032 1036 1037 1038 1039 1040 1042 1044 1045 1048 1051 1053
 1054 1060 1061 1063 1066 1067 1070 1072 1074 1075 1080 1081 1087 1088 1089
 1092 1093 1096 1097 1098 1099 1100 1101 1103 1104 1106 1111 1112 1114 1116
 1120 1121 1122 1124 1126 1128 1129 1131 1133 1134 1139 1140 1141 1142 1150
 1151 1152 1157 1158 1160 1162 1164 1168 1169 1171 1174 1175 1177 1178 1182
 1185 1189 1194 1196 1198 1200 1203 1208 1209 1215 1216 1218 1221 1230 1232
 1234 1237 1238 1240 1242 1243 1246 1248 1250 1254 1257 1259 1274 1275 1276
 1277 1281 1285 1286 1288 1295 1296 1304 1306 1309 1312 1315 1319 1320 1321
 1323 1325 1330 1332 1335 1336 1340 1342 1345 1347 1349 1357 1358 1360 1362
 1368 1369 1370 1371 1377 1384 1392 1402 1405 1407 1414 1420 1426 1427 1440
 1479 1518 1519 1523 1538 1540 1567 1589 1611 1619 1629 1721 1778 1788 1796
 1818 1836 1862 1872 2065]

3SsnPorch [  0  23  86  96 120 130 140 144 150 153 162 168 174 176 180 182 196 216
 219 224 225 238 245 255 290 304 320 323 360 407 508]

Alley [nan 'Grvl' 'Pave']

BedroomAbvGr [0 1 2 3 4 5 6 8]

BldgType ['1Fam' '2fmCon' 'Duplex' 'Twnhs' 'TwnhsE']

BsmtCond [nan 'Fa' 'Gd' 'Po' 'TA']

BsmtExposure [nan 'Av' 'Gd' 'Mn' 'No']

BsmtFinSF1 [  0.00000000e+00   2.00000000e+00   1.60000000e+01   2.00000000e+01
   2.40000000e+01   2.50000000e+01   2.70000000e+01   2.80000000e+01
   3.20000000e+01   3.30000000e+01   3.50000000e+01   3.60000000e+01
   4.00000000e+01   4.10000000e+01   4.20000000e+01   4.80000000e+01
   4.90000000e+01   5.00000000e+01   5.10000000e+01   5.20000000e+01
   5.30000000e+01   5.40000000e+01   5.50000000e+01   5.60000000e+01
   5.70000000e+01   6.00000000e+01   6.30000000e+01   6.40000000e+01
   6.50000000e+01   6.80000000e+01   7.00000000e+01   7.20000000e+01
   7.30000000e+01   7.50000000e+01   7.60000000e+01   7.70000000e+01
   7.80000000e+01   8.00000000e+01   8.10000000e+01   8.50000000e+01
   8.80000000e+01   9.40000000e+01   9.60000000e+01   1.00000000e+02
   1.04000000e+02   1.08000000e+02   1.10000000e+02   1.11000000e+02
   1.13000000e+02   1.14000000e+02   1.16000000e+02   1.19000000e+02
   1.20000000e+02   1.21000000e+02   1.22000000e+02   1.25000000e+02
   1.26000000e+02   1.28000000e+02   1.29000000e+02   1.30000000e+02
   1.31000000e+02   1.32000000e+02   1.33000000e+02   1.34000000e+02
   1.38000000e+02   1.40000000e+02   1.41000000e+02   1.43000000e+02
   1.44000000e+02   1.48000000e+02   1.49000000e+02   1.50000000e+02
   1.52000000e+02   1.54000000e+02   1.55000000e+02   1.56000000e+02
   1.62000000e+02   1.65000000e+02   1.67000000e+02   1.68000000e+02
   1.69000000e+02   1.70000000e+02   1.72000000e+02   1.73000000e+02
   1.75000000e+02   1.76000000e+02   1.79000000e+02   1.80000000e+02
   1.81000000e+02   1.82000000e+02   1.85000000e+02   1.86000000e+02
   1.87000000e+02   1.88000000e+02   1.89000000e+02   1.90000000e+02
   1.91000000e+02   1.92000000e+02   1.93000000e+02   1.94000000e+02
   1.96000000e+02   1.97000000e+02   1.98000000e+02   2.00000000e+02
   2.01000000e+02   2.03000000e+02   2.04000000e+02   2.05000000e+02
   2.06000000e+02   2.07000000e+02   2.08000000e+02   2.09000000e+02
   2.10000000e+02   2.12000000e+02   2.13000000e+02   2.15000000e+02
   2.16000000e+02   2.18000000e+02   2.19000000e+02   2.20000000e+02
   2.21000000e+02   2.22000000e+02   2.23000000e+02   2.24000000e+02
   2.25000000e+02   2.26000000e+02   2.28000000e+02   2.30000000e+02
   2.31000000e+02   2.34000000e+02   2.36000000e+02   2.38000000e+02
   2.39000000e+02   2.40000000e+02   2.41000000e+02   2.42000000e+02
   2.44000000e+02   2.46000000e+02   2.47000000e+02   2.48000000e+02
   2.49000000e+02   2.50000000e+02   2.51000000e+02   2.52000000e+02
   2.54000000e+02   2.56000000e+02   2.57000000e+02   2.58000000e+02
   2.59000000e+02   2.60000000e+02   2.61000000e+02   2.62000000e+02
   2.63000000e+02   2.64000000e+02   2.66000000e+02   2.67000000e+02
   2.70000000e+02   2.71000000e+02   2.73000000e+02   2.74000000e+02
   2.75000000e+02   2.76000000e+02   2.78000000e+02   2.79000000e+02
   2.80000000e+02   2.81000000e+02   2.82000000e+02   2.83000000e+02
   2.84000000e+02   2.85000000e+02   2.86000000e+02   2.88000000e+02
   2.90000000e+02   2.92000000e+02   2.94000000e+02   2.96000000e+02
   2.97000000e+02   2.98000000e+02   2.99000000e+02   3.00000000e+02
   3.01000000e+02   3.05000000e+02   3.06000000e+02   3.08000000e+02
   3.09000000e+02   3.10000000e+02   3.11000000e+02   3.12000000e+02
   3.14000000e+02   3.15000000e+02   3.16000000e+02   3.17000000e+02
   3.18000000e+02   3.19000000e+02   3.20000000e+02   3.21000000e+02
   3.22000000e+02   3.24000000e+02   3.26000000e+02   3.28000000e+02
   3.29000000e+02   3.30000000e+02   3.31000000e+02   3.32000000e+02
   3.34000000e+02   3.35000000e+02   3.36000000e+02   3.37000000e+02
   3.38000000e+02   3.39000000e+02   3.40000000e+02   3.41000000e+02
   3.42000000e+02   3.43000000e+02   3.44000000e+02   3.46000000e+02
   3.47000000e+02   3.48000000e+02   3.49000000e+02   3.50000000e+02
   3.51000000e+02   3.52000000e+02   3.53000000e+02   3.54000000e+02
   3.55000000e+02   3.56000000e+02   3.58000000e+02   3.60000000e+02
   3.61000000e+02   3.62000000e+02   3.63000000e+02   3.64000000e+02
   3.65000000e+02   3.66000000e+02   3.68000000e+02   3.69000000e+02
   3.70000000e+02   3.71000000e+02   3.72000000e+02   3.73000000e+02
   3.74000000e+02   3.75000000e+02   3.76000000e+02   3.77000000e+02
   3.78000000e+02   3.79000000e+02   3.80000000e+02   3.81000000e+02
   3.82000000e+02   3.83000000e+02   3.84000000e+02   3.85000000e+02
   3.86000000e+02   3.87000000e+02   3.88000000e+02   3.89000000e+02
   3.90000000e+02   3.92000000e+02   3.93000000e+02   3.94000000e+02
   3.97000000e+02   3.98000000e+02   3.99000000e+02   4.00000000e+02
   4.02000000e+02   4.03000000e+02   4.04000000e+02   4.05000000e+02
   4.06000000e+02   4.08000000e+02   4.10000000e+02   4.12000000e+02
   4.14000000e+02   4.15000000e+02   4.16000000e+02   4.17000000e+02
   4.19000000e+02   4.20000000e+02   4.21000000e+02   4.22000000e+02
   4.23000000e+02   4.24000000e+02   4.25000000e+02   4.26000000e+02
   4.27000000e+02   4.28000000e+02   4.29000000e+02   4.30000000e+02
   4.32000000e+02   4.33000000e+02   4.34000000e+02   4.35000000e+02
   4.36000000e+02   4.37000000e+02   4.38000000e+02   4.39000000e+02
   4.40000000e+02   4.41000000e+02   4.42000000e+02   4.43000000e+02
   4.44000000e+02   4.45000000e+02   4.48000000e+02   4.50000000e+02
   4.52000000e+02   4.53000000e+02   4.54000000e+02   4.55000000e+02
   4.56000000e+02   4.57000000e+02   4.58000000e+02   4.59000000e+02
   4.60000000e+02   4.62000000e+02   4.64000000e+02   4.65000000e+02
   4.66000000e+02   4.67000000e+02   4.68000000e+02   4.69000000e+02
   4.71000000e+02   4.72000000e+02   4.74000000e+02   4.75000000e+02
   4.76000000e+02   4.77000000e+02   4.80000000e+02   4.81000000e+02
   4.82000000e+02   4.83000000e+02   4.84000000e+02   4.85000000e+02
   4.86000000e+02   4.88000000e+02   4.89000000e+02   4.90000000e+02
   4.91000000e+02   4.92000000e+02   4.93000000e+02   4.94000000e+02
   4.95000000e+02   4.96000000e+02   4.97000000e+02   4.98000000e+02
   5.00000000e+02   5.01000000e+02   5.02000000e+02   5.03000000e+02
   5.04000000e+02   5.05000000e+02   5.06000000e+02   5.07000000e+02
   5.09000000e+02   5.10000000e+02   5.12000000e+02   5.13000000e+02
   5.14000000e+02   5.15000000e+02   5.16000000e+02   5.18000000e+02
   5.20000000e+02   5.21000000e+02   5.22000000e+02   5.23000000e+02
   5.24000000e+02   5.26000000e+02   5.27000000e+02   5.28000000e+02
   5.31000000e+02   5.32000000e+02   5.33000000e+02   5.34000000e+02
   5.35000000e+02   5.36000000e+02   5.37000000e+02   5.38000000e+02
   5.39000000e+02   5.40000000e+02   5.43000000e+02   5.44000000e+02
   5.46000000e+02   5.47000000e+02   5.48000000e+02   5.49000000e+02
   5.50000000e+02   5.51000000e+02   5.52000000e+02   5.53000000e+02
   5.54000000e+02   5.56000000e+02   5.57000000e+02   5.59000000e+02
   5.60000000e+02   5.62000000e+02   5.64000000e+02   5.65000000e+02
   5.66000000e+02   5.67000000e+02   5.68000000e+02   5.69000000e+02
   5.70000000e+02   5.72000000e+02   5.73000000e+02   5.74000000e+02
   5.75000000e+02   5.76000000e+02   5.77000000e+02   5.78000000e+02
   5.79000000e+02   5.80000000e+02   5.83000000e+02   5.84000000e+02
   5.85000000e+02   5.86000000e+02   5.87000000e+02   5.88000000e+02
   5.90000000e+02   5.92000000e+02   5.93000000e+02   5.94000000e+02
   5.95000000e+02   5.96000000e+02   5.99000000e+02   6.00000000e+02
   6.01000000e+02   6.02000000e+02   6.03000000e+02   6.04000000e+02
   6.05000000e+02   6.06000000e+02   6.07000000e+02   6.08000000e+02
   6.09000000e+02   6.11000000e+02   6.12000000e+02   6.14000000e+02
   6.15000000e+02   6.16000000e+02   6.17000000e+02   6.19000000e+02
   6.20000000e+02   6.21000000e+02   6.22000000e+02   6.23000000e+02
   6.24000000e+02   6.25000000e+02   6.26000000e+02   6.30000000e+02
   6.31000000e+02   6.32000000e+02   6.33000000e+02   6.34000000e+02
   6.36000000e+02   6.37000000e+02   6.38000000e+02   6.39000000e+02
   6.41000000e+02   6.42000000e+02   6.43000000e+02   6.44000000e+02
   6.45000000e+02   6.46000000e+02   6.47000000e+02   6.48000000e+02
   6.49000000e+02   6.50000000e+02   6.51000000e+02   6.52000000e+02
   6.54000000e+02   6.55000000e+02   6.56000000e+02   6.58000000e+02
   6.59000000e+02   6.60000000e+02   6.61000000e+02   6.62000000e+02
   6.63000000e+02   6.64000000e+02   6.66000000e+02   6.68000000e+02
   6.69000000e+02   6.70000000e+02   6.71000000e+02   6.72000000e+02
   6.73000000e+02   6.74000000e+02   6.78000000e+02   6.79000000e+02
   6.80000000e+02   6.81000000e+02   6.82000000e+02   6.83000000e+02
   6.84000000e+02   6.85000000e+02   6.86000000e+02   6.87000000e+02
   6.88000000e+02   6.89000000e+02   6.90000000e+02   6.91000000e+02
   6.92000000e+02   6.94000000e+02   6.95000000e+02   6.96000000e+02
   6.97000000e+02   6.98000000e+02   6.99000000e+02   7.00000000e+02
   7.01000000e+02   7.02000000e+02   7.04000000e+02   7.05000000e+02
   7.06000000e+02   7.08000000e+02   7.09000000e+02   7.10000000e+02
   7.12000000e+02   7.13000000e+02   7.14000000e+02   7.16000000e+02
   7.17000000e+02   7.18000000e+02   7.19000000e+02   7.20000000e+02
   7.22000000e+02   7.24000000e+02   7.25000000e+02   7.26000000e+02
   7.27000000e+02   7.28000000e+02   7.29000000e+02   7.31000000e+02
   7.32000000e+02   7.33000000e+02   7.34000000e+02   7.35000000e+02
   7.36000000e+02   7.37000000e+02   7.38000000e+02   7.39000000e+02
   7.40000000e+02   7.41000000e+02   7.42000000e+02   7.44000000e+02
   7.45000000e+02   7.46000000e+02   7.47000000e+02   7.48000000e+02
   7.49000000e+02   7.50000000e+02   7.51000000e+02   7.55000000e+02
   7.56000000e+02   7.58000000e+02   7.59000000e+02   7.60000000e+02
   7.62000000e+02   7.63000000e+02   7.64000000e+02   7.65000000e+02
   7.66000000e+02   7.67000000e+02   7.69000000e+02   7.70000000e+02
   7.71000000e+02   7.72000000e+02   7.73000000e+02   7.74000000e+02
   7.75000000e+02   7.76000000e+02   7.77000000e+02   7.78000000e+02
   7.79000000e+02   7.80000000e+02   7.81000000e+02   7.82000000e+02
   7.83000000e+02   7.84000000e+02   7.85000000e+02   7.86000000e+02
   7.87000000e+02   7.88000000e+02   7.89000000e+02   7.90000000e+02
   7.91000000e+02   7.92000000e+02   7.93000000e+02   7.94000000e+02
   7.95000000e+02   7.96000000e+02   7.97000000e+02   7.99000000e+02
   8.00000000e+02   8.03000000e+02   8.04000000e+02   8.06000000e+02
   8.08000000e+02   8.09000000e+02   8.10000000e+02   8.11000000e+02
   8.12000000e+02   8.13000000e+02   8.14000000e+02   8.16000000e+02
   8.19000000e+02   8.20000000e+02   8.21000000e+02   8.22000000e+02
   8.24000000e+02   8.26000000e+02   8.27000000e+02   8.28000000e+02
   8.30000000e+02   8.31000000e+02   8.32000000e+02   8.33000000e+02
   8.36000000e+02   8.37000000e+02   8.38000000e+02   8.40000000e+02
   8.41000000e+02   8.42000000e+02   8.44000000e+02   8.46000000e+02
   8.47000000e+02   8.48000000e+02   8.50000000e+02   8.51000000e+02
   8.52000000e+02   8.53000000e+02   8.54000000e+02   8.56000000e+02
   8.59000000e+02   8.60000000e+02   8.62000000e+02   8.63000000e+02
   8.64000000e+02   8.65000000e+02   8.66000000e+02   8.67000000e+02
   8.70000000e+02   8.71000000e+02   8.72000000e+02   8.73000000e+02
   8.74000000e+02   8.76000000e+02   8.80000000e+02   8.81000000e+02
   8.83000000e+02   8.85000000e+02   8.88000000e+02   8.90000000e+02
   8.92000000e+02   8.93000000e+02   8.94000000e+02   8.95000000e+02
   8.96000000e+02   8.97000000e+02   8.99000000e+02   9.00000000e+02
   9.01000000e+02   9.02000000e+02   9.03000000e+02   9.04000000e+02
   9.05000000e+02   9.06000000e+02   9.08000000e+02   9.09000000e+02
   9.10000000e+02   9.12000000e+02   9.13000000e+02   9.14000000e+02
   9.15000000e+02   9.16000000e+02   9.18000000e+02   9.19000000e+02
   9.20000000e+02   9.22000000e+02   9.23000000e+02   9.24000000e+02
   9.25000000e+02   9.26000000e+02   9.29000000e+02   9.30000000e+02
   9.31000000e+02   9.32000000e+02   9.35000000e+02   9.36000000e+02
   9.37000000e+02   9.38000000e+02   9.39000000e+02   9.41000000e+02
   9.43000000e+02   9.44000000e+02   9.45000000e+02   9.46000000e+02
   9.49000000e+02   9.50000000e+02   9.51000000e+02   9.52000000e+02
   9.53000000e+02   9.54000000e+02   9.55000000e+02   9.56000000e+02
   9.58000000e+02   9.60000000e+02   9.62000000e+02   9.64000000e+02
   9.65000000e+02   9.67000000e+02   9.68000000e+02   9.69000000e+02
   9.70000000e+02   9.73000000e+02   9.75000000e+02   9.76000000e+02
   9.78000000e+02   9.80000000e+02   9.82000000e+02   9.83000000e+02
   9.84000000e+02   9.85000000e+02   9.86000000e+02   9.87000000e+02
   9.88000000e+02   9.90000000e+02   9.91000000e+02   9.94000000e+02
   9.96000000e+02   9.98000000e+02   1.00000000e+03   1.00100000e+03
   1.00200000e+03   1.00300000e+03   1.00400000e+03   1.00500000e+03
   1.01000000e+03   1.01100000e+03   1.01200000e+03   1.01300000e+03
   1.01400000e+03   1.01500000e+03   1.01600000e+03   1.01800000e+03
   1.02100000e+03   1.02200000e+03   1.02300000e+03   1.02400000e+03
   1.02600000e+03   1.02700000e+03   1.02900000e+03   1.03000000e+03
   1.03200000e+03   1.03300000e+03   1.03400000e+03   1.03500000e+03
   1.03600000e+03   1.03700000e+03   1.03800000e+03   1.03900000e+03
   1.04000000e+03   1.04400000e+03   1.04600000e+03   1.04700000e+03
   1.04800000e+03   1.05100000e+03   1.05300000e+03   1.05600000e+03
   1.05900000e+03   1.06400000e+03   1.06500000e+03   1.07000000e+03
   1.07100000e+03   1.07300000e+03   1.07400000e+03   1.07500000e+03
   1.07800000e+03   1.07900000e+03   1.08000000e+03   1.08200000e+03
   1.08400000e+03   1.08500000e+03   1.08600000e+03   1.08700000e+03
   1.08800000e+03   1.09000000e+03   1.09200000e+03   1.09400000e+03
   1.09600000e+03   1.09700000e+03   1.09800000e+03   1.10100000e+03
   1.10400000e+03   1.10600000e+03   1.11000000e+03   1.11100000e+03
   1.11200000e+03   1.11500000e+03   1.11600000e+03   1.11800000e+03
   1.12100000e+03   1.12200000e+03   1.12400000e+03   1.12600000e+03
   1.12700000e+03   1.12800000e+03   1.12900000e+03   1.13600000e+03
   1.13700000e+03   1.13800000e+03   1.14100000e+03   1.14200000e+03
   1.14800000e+03   1.14900000e+03   1.15000000e+03   1.15100000e+03
   1.15200000e+03   1.15300000e+03   1.15400000e+03   1.15700000e+03
   1.15800000e+03   1.15900000e+03   1.16200000e+03   1.16300000e+03
   1.16500000e+03   1.17000000e+03   1.17200000e+03   1.17300000e+03
   1.17800000e+03   1.18000000e+03   1.18100000e+03   1.18200000e+03
   1.18600000e+03   1.18800000e+03   1.19100000e+03   1.19400000e+03
   1.19600000e+03   1.19800000e+03   1.20000000e+03   1.20100000e+03
   1.20400000e+03   1.20600000e+03   1.21300000e+03   1.21600000e+03
   1.21800000e+03   1.21900000e+03   1.22000000e+03   1.22300000e+03
   1.22400000e+03   1.22500000e+03   1.23000000e+03   1.23100000e+03
   1.23200000e+03   1.23400000e+03   1.23600000e+03   1.23700000e+03
   1.23800000e+03   1.23900000e+03   1.24300000e+03   1.24600000e+03
   1.24700000e+03   1.24900000e+03   1.25200000e+03   1.25800000e+03
   1.25900000e+03   1.26000000e+03   1.26100000e+03   1.26200000e+03
   1.27000000e+03   1.27100000e+03   1.27400000e+03   1.27700000e+03
   1.28000000e+03   1.28200000e+03   1.28300000e+03   1.28500000e+03
   1.28800000e+03   1.29000000e+03   1.29400000e+03   1.29800000e+03
   1.30000000e+03   1.30200000e+03   1.30400000e+03   1.30800000e+03
   1.30900000e+03   1.31200000e+03   1.31400000e+03   1.31900000e+03
   1.32000000e+03   1.32400000e+03   1.32800000e+03   1.32900000e+03
   1.33000000e+03   1.33200000e+03   1.33300000e+03   1.33400000e+03
   1.33600000e+03   1.33700000e+03   1.33800000e+03   1.34100000e+03
   1.34600000e+03   1.35000000e+03   1.35100000e+03   1.35800000e+03
   1.35900000e+03   1.36000000e+03   1.36100000e+03   1.36900000e+03
   1.37300000e+03   1.37500000e+03   1.38300000e+03   1.38600000e+03
   1.38700000e+03   1.39000000e+03   1.39200000e+03   1.39800000e+03
   1.40000000e+03   1.40600000e+03   1.41000000e+03   1.41200000e+03
   1.41400000e+03   1.41600000e+03   1.42000000e+03   1.42200000e+03
   1.43000000e+03   1.43300000e+03   1.43600000e+03   1.44000000e+03
   1.44100000e+03   1.44300000e+03   1.44500000e+03   1.44700000e+03
   1.45500000e+03   1.45600000e+03   1.46000000e+03   1.46400000e+03
   1.47000000e+03   1.47400000e+03   1.47600000e+03   1.47800000e+03
   1.48000000e+03   1.50000000e+03   1.50500000e+03   1.51300000e+03
   1.51800000e+03   1.53100000e+03   1.53800000e+03   1.54000000e+03
   1.55700000e+03   1.55800000e+03   1.56200000e+03   1.56400000e+03
   1.56700000e+03   1.57100000e+03   1.57200000e+03   1.57300000e+03
   1.57600000e+03   1.59300000e+03   1.60600000e+03   1.61900000e+03
   1.63200000e+03   1.63600000e+03   1.64000000e+03   1.64600000e+03
   1.66000000e+03   1.68200000e+03   1.68400000e+03   1.69600000e+03
   1.72100000e+03   1.72800000e+03   1.73200000e+03   1.73300000e+03
   1.75800000e+03   1.76700000e+03   1.81000000e+03   1.81200000e+03
   1.83600000e+03   1.88000000e+03   1.90400000e+03   1.96500000e+03
   1.97200000e+03   2.08500000e+03   2.09600000e+03   2.14600000e+03
   2.15800000e+03   2.18800000e+03   2.25700000e+03   2.26000000e+03
   2.28800000e+03   4.01000000e+03   5.64400000e+03              nan]

BsmtFinSF2 [    0.     6.    12.    28.    32.    35.    38.    40.    41.    42.
    46.    48.    52.    60.    63.    64.    66.    68.    72.    76.
    78.    80.    81.    92.    93.    95.    96.   102.   105.   106.
   108.   110.   113.   116.   117.   119.   120.   121.   123.   125.
   127.   128.   132.   136.   138.   139.   144.   147.   149.   150.
   153.   154.   156.   159.   162.   163.   165.   167.   168.   169.
   173.   174.   175.   177.   180.   181.   182.   184.   186.   193.
   196.   201.   202.   206.   208.   210.   211.   215.   216.   219.
   227.   228.   230.   232.   239.   240.   243.   247.   250.   252.
   258.   259.   262.   263.   264.   270.   273.   276.   278.   279.
   281.   284.   286.   287.   288.   290.   294.   297.   306.   308.
   311.   319.   321.   324.   334.   336.   337.   344.   345.   350.
   351.   352.   354.   360.   362.   364.   373.   374.   375.   377.
   380.   382.   387.   391.   393.   396.   398.   400.   402.   404.
   411.   417.   419.   420.   432.   435.   438.   441.   442.   448.
   449.   450.   453.   456.   465.   466.   468.   469.   472.   474.
   479.   480.   483.   486.   488.   491.   492.   495.   497.   499.
   500.   506.   507.   512.   522.   529.   530.   531.   532.   539.
   543.   544.   546.   547.   551.   555.   557.   580.   590.   596.
   600.   604.   606.   608.   612.   613.   619.   620.   622.   624.
   627.   630.   634.   645.   661.   668.   670.   679.   682.   684.
   688.   690.   691.   692.   694.   712.   713.   722.   723.   748.
   750.   755.   761.   764.   768.   774.   791.   799.   811.   820.
   823.   826.   829.   831.   841.   842.   850.   852.   859.   869.
   872.   873.   875.   884.   891.   904.   906.   912.   915.   955.
   956.   972.   981.   982.  1020.  1029.  1031.  1037.  1039.  1057.
  1061.  1063.  1073.  1080.  1083.  1085.  1120.  1127.  1164.  1393.
  1474.  1526.    nan]

BsmtFinType1 [nan 'ALQ' 'BLQ' 'GLQ' 'LwQ' 'Rec' 'Unf']

BsmtFinType2 [nan 'ALQ' 'BLQ' 'GLQ' 'LwQ' 'Rec' 'Unf']

BsmtFullBath [  0.   1.   2.   3.  nan]

BsmtHalfBath [  0.   1.   2.  nan]

BsmtQual [nan 'Ex' 'Fa' 'Gd' 'TA']

BsmtUnfSF [    0.    14.    15. ...,  2153.  2336.    nan]

CentralAir ['N' 'Y']

Condition1 ['Artery' 'Feedr' 'Norm' 'PosA' 'PosN' 'RRAe' 'RRAn' 'RRNe' 'RRNn']

Condition2 ['Artery' 'Feedr' 'Norm' 'PosA' 'PosN' 'RRAe' 'RRAn' 'RRNn']

Electrical [nan 'FuseA' 'FuseF' 'FuseP' 'Mix' 'SBrkr']

EnclosedPorch [   0   16   18   19   20   23   24   25   26   28   30   32   34   35   36
   37   39   40   41   42   43   44   45   48   50   51   52   54   55   56
   57   60   64   66   67   68   70   72   75   77   78   80   81   84   86
   87   88   90   91   92   94   96   98   99  100  101  102  104  105  108
  109  112  113  114  115  116  117  120  121  122  123  126  128  129  130
  132  133  134  135  136  137  138  139  140  143  144  145  148  150  154
  156  158  160  161  162  164  165  167  168  169  170  172  174  175  176
  177  180  183  184  185  186  189  190  192  194  196  198  200  202  203
  204  205  207  208  209  210  211  212  213  214  216  218  219  220  221
  222  224  225  226  228  230  231  234  236  238  239  240  242  244  246
  248  249  252  254  256  259  260  264  265  268  272  275  280  286  288
  290  291  293  294  296  301  318  324  330  334  364  368  386  429  432
  552  584 1012]

ExterCond ['Ex' 'Fa' 'Gd' 'Po' 'TA']

ExterQual ['Ex' 'Fa' 'Gd' 'TA']

Exterior1st [nan 'AsbShng' 'AsphShn' 'BrkComm' 'BrkFace' 'CBlock' 'CemntBd' 'HdBoard'
 'ImStucc' 'MetalSd' 'Plywood' 'Stone' 'Stucco' 'VinylSd' 'Wd Sdng'
 'WdShing']

Exterior2nd [nan 'AsbShng' 'AsphShn' 'Brk Cmn' 'BrkFace' 'CBlock' 'CmentBd' 'HdBoard'
 'ImStucc' 'MetalSd' 'Other' 'Plywood' 'Stone' 'Stucco' 'VinylSd' 'Wd Sdng'
 'Wd Shng']

Fence [nan 'GdPrv' 'GdWo' 'MnPrv' 'MnWw']

FireplaceQu [nan 'Ex' 'Fa' 'Gd' 'Po' 'TA']

Fireplaces [0 1 2 3 4]

Foundation ['BrkTil' 'CBlock' 'PConc' 'Slab' 'Stone' 'Wood']

FullBath [0 1 2 3 4]

Functional [nan 'Maj1' 'Maj2' 'Min1' 'Min2' 'Mod' 'Sev' 'Typ']

GarageArea [    0.   100.   160.   162.   164.   180.   184.   185.   186.   189.
   192.   195.   198.   200.   205.   207.   208.   209.   210.   213.
   215.   216.   217.   220.   224.   225.   226.   228.   230.   231.
   234.   240.   242.   244.   246.   248.   249.   250.   252.   253.
   254.   255.   256.   257.   258.   260.   261.   263.   264.   265.
   266.   267.   270.   271.   272.   273.   275.   276.   280.   281.
   282.   283.   284.   286.   287.   288.   290.   292.   293.   294.
   295.   296.   297.   299.   300.   301.   303.   304.   305.   306.
   307.   308.   309.   310.   311.   312.   313.   315.   316.   317.
   318.   319.   320.   322.   323.   324.   325.   326.   327.   328.
   330.   331.   332.   336.   338.   340.   342.   343.   344.   345.
   349.   350.   351.   352.   353.   354.   355.   356.   357.   358.
   360.   363.   364.   365.   366.   367.   368.   369.   370.   371.
   372.   373.   374.   375.   377.   378.   379.   380.   384.   386.
   388.   389.   390.   392.   393.   394.   396.   397.   398.   399.
   400.   401.   402.   403.   404.   405.   406.   408.   409.   410.
   412.   413.   414.   416.   418.   420.   422.   423.   424.   425.
   426.   427.   428.   429.   430.   431.   432.   433.   434.   435.
   436.   437.   438.   439.   440.   441.   442.   443.   444.   445.
   447.   449.   450.   451.   452.   453.   454.   455.   456.   457.
   458.   459.   460.   461.   462.   463.   464.   465.   466.   467.
   468.   469.   470.   471.   472.   473.   474.   475.   476.   477.
   478.   479.   480.   481.   482.   483.   484.   485.   486.   487.
   488.   489.   490.   492.   493.   494.   495.   496.   497.   498.
   499.   500.   501.   502.   504.   505.   506.   508.   509.   510.
   511.   512.   513.   514.   515.   516.   517.   518.   520.   521.
   522.   523.   524.   525.   526.   527.   528.   529.   530.   531.
   532.   533.   534.   535.   538.   539.   540.   541.   542.   543.
   544.   545.   546.   548.   549.   550.   551.   552.   554.   555.
   556.   557.   558.   559.   560.   561.   562.   564.   565.   566.
   567.   568.   569.   570.   571.   572.   573.   574.   575.   576.
   577.   578.   579.   580.   581.   582.   583.   584.   585.   586.
   588.   590.   591.   592.   594.   595.   596.   597.   598.   599.
   600.   601.   602.   603.   604.   605.   606.   608.   609.   610.
   611.   612.   613.   614.   615.   616.   617.   618.   619.   620.
   621.   622.   623.   624.   625.   626.   627.   628.   630.   631.
   632.   636.   638.   639.   640.   641.   642.   644.   645.   646.
   647.   648.   649.   650.   656.   658.   660.   662.   663.   665.
   666.   667.   668.   670.   671.   672.   673.   674.   675.   676.
   678.   680.   682.   683.   684.   685.   686.   687.   688.   689.
   690.   691.   692.   693.   694.   696.   698.   700.   701.   702.
   704.   706.   708.   711.   712.   713.   714.   715.   716.   719.
   720.   721.   722.   724.   725.   726.   728.   729.   730.   732.
   736.   738.   739.   740.   741.   744.   746.   747.   748.   749.
   750.   751.   752.   753.   754.   756.   757.   758.   760.   762.
   765.   766.   768.   770.   772.   773.   774.   776.   779.   780.
   782.   783.   784.   786.   787.   788.   789.   791.   792.   795.
   796.   800.   803.   804.   806.   807.   808.   810.   811.   812.
   813.   814.   815.   816.   818.   820.   824.   825.   826.   828.
   830.   831.   832.   833.   834.   836.   839.   840.   841.   842.
   843.   844.   845.   846.   848.   850.   851.   852.   853.   856.
   857.   858.   859.   860.   862.   864.   865.   866.   868.   869.
   870.   871.   872.   874.   876.   878.   880.   884.   885.   886.
   888.   889.   890.   892.   894.   895.   896.   898.   899.   900.
   902.   904.   905.   907.   908.   912.   916.   920.   923.   924.
   925.   927.   928.   932.   933.   936.   938.   944.   947.   949.
   954.   958.   959.   962.   963.   968.   972.   983.   984.   995.
  1003.  1008.  1014.  1017.  1020.  1025.  1040.  1041.  1043.  1052.
  1053.  1069.  1085.  1092.  1105.  1110.  1134.  1138.  1150.  1154.
  1166.  1174.  1184.  1200.  1220.  1231.  1248.  1314.  1348.  1356.
  1390.  1418.  1488.    nan]

GarageCars [  0.   1.   2.   3.   4.   5.  nan]

GarageCond [nan 'Ex' 'Fa' 'Gd' 'Po' 'TA']

GarageFinish [nan 'Fin' 'RFn' 'Unf']

GarageQual [nan 'Ex' 'Fa' 'Gd' 'Po' 'TA']

GarageType [nan '2Types' 'Attchd' 'Basment' 'BuiltIn' 'CarPort' 'Detchd']

GarageYrBlt [ 1895.  1896.  1900.  1906.  1908.  1910.  1914.  1915.  1916.  1917.
  1918.  1919.  1920.  1921.  1922.  1923.  1924.  1925.  1926.  1927.
  1928.  1929.  1930.  1931.  1932.  1933.  1934.  1935.  1936.  1937.
  1938.  1939.  1940.  1941.  1942.  1943.  1945.  1946.  1947.  1948.
  1949.  1950.  1951.  1952.  1953.  1954.  1955.  1956.  1957.  1958.
  1959.  1960.  1961.  1962.  1963.  1964.  1965.  1966.  1967.  1968.
  1969.  1970.  1971.  1972.  1973.  1974.  1975.  1976.  1977.  1978.
  1979.  1980.  1981.  1982.  1983.  1984.  1985.  1986.  1987.  1988.
  1989.  1990.  1991.  1992.  1993.  1994.  1995.  1996.  1997.  1998.
  1999.  2000.  2001.  2002.  2003.  2004.  2005.  2006.  2007.  2008.
  2009.  2010.  2207.    nan]

GrLivArea [ 334  407  438 ..., 4676 5095 5642]

HalfBath [0 1 2]

Heating ['Floor' 'GasA' 'GasW' 'Grav' 'OthW' 'Wall']

HeatingQC ['Ex' 'Fa' 'Gd' 'Po' 'TA']

HouseStyle ['1.5Fin' '1.5Unf' '1Story' '2.5Fin' '2.5Unf' '2Story' 'SFoyer' 'SLvl']

Id [   1    2    3 ..., 2917 2918 2919]

KitchenAbvGr [0 1 2 3]

KitchenQual [nan 'Ex' 'Fa' 'Gd' 'TA']

LandContour ['Bnk' 'HLS' 'Low' 'Lvl']

LandSlope ['Gtl' 'Mod' 'Sev']

LotArea [  1300   1470   1476 ..., 159000 164660 215245]

LotConfig ['Corner' 'CulDSac' 'FR2' 'FR3' 'Inside']

LotFrontage [  21.   22.   24.   25.   26.   28.   30.   31.   32.   33.   34.   35.
   36.   37.   38.   39.   40.   41.   42.   43.   44.   45.   46.   47.
   48.   49.   50.   51.   52.   53.   54.   55.   56.   57.   58.   59.
   60.   61.   62.   63.   64.   65.   66.   67.   68.   69.   70.   71.
   72.   73.   74.   75.   76.   77.   78.   79.   80.   81.   82.   83.
   84.   85.   86.   87.   88.   89.   90.   91.   92.   93.   94.   95.
   96.   97.   98.   99.  100.  101.  102.  103.  104.  105.  106.  107.
  108.  109.  110.  111.  112.  113.  114.  115.  116.  117.  118.  119.
  120.  121.  122.  123.  124.  125.  126.  128.  129.  130.  131.  133.
  134.  135.  136.  137.  138.  140.  141.  144.  149.  150.  152.  153.
  155.  160.  168.  174.  182.  195.  200.  313.   nan]

LotShape ['IR1' 'IR2' 'IR3' 'Reg']

LowQualFinSF [   0   53   80  108  114  120  140  144  156  205  232  234  259  312  360
  362  371  384  390  392  397  420  431  436  450  473  479  481  512  513
  514  515  528  572  697 1064]

MSSubClass [ 20  30  40  45  50  60  70  75  80  85  90 120 150 160 180 190]

MSZoning [nan 'C (all)' 'FV' 'RH' 'RL' 'RM']

MasVnrArea [  0.00000000e+00   1.00000000e+00   3.00000000e+00   1.10000000e+01
   1.40000000e+01   1.60000000e+01   1.80000000e+01   2.00000000e+01
   2.20000000e+01   2.30000000e+01   2.40000000e+01   2.70000000e+01
   2.80000000e+01   3.00000000e+01   3.10000000e+01   3.20000000e+01
   3.40000000e+01   3.60000000e+01   3.80000000e+01   3.90000000e+01
   4.00000000e+01   4.10000000e+01   4.20000000e+01   4.40000000e+01
   4.50000000e+01   4.60000000e+01   4.70000000e+01   4.80000000e+01
   5.00000000e+01   5.10000000e+01   5.20000000e+01   5.30000000e+01
   5.40000000e+01   5.60000000e+01   5.70000000e+01   5.80000000e+01
   6.00000000e+01   6.20000000e+01   6.30000000e+01   6.40000000e+01
   6.50000000e+01   6.60000000e+01   6.70000000e+01   6.80000000e+01
   6.90000000e+01   7.00000000e+01   7.20000000e+01   7.40000000e+01
   7.50000000e+01   7.60000000e+01   8.00000000e+01   8.10000000e+01
   8.20000000e+01   8.40000000e+01   8.50000000e+01   8.60000000e+01
   8.70000000e+01   8.80000000e+01   8.90000000e+01   9.00000000e+01
   9.10000000e+01   9.20000000e+01   9.40000000e+01   9.50000000e+01
   9.60000000e+01   9.70000000e+01   9.80000000e+01   9.90000000e+01
   1.00000000e+02   1.01000000e+02   1.02000000e+02   1.04000000e+02
   1.05000000e+02   1.06000000e+02   1.08000000e+02   1.09000000e+02
   1.10000000e+02   1.12000000e+02   1.13000000e+02   1.14000000e+02
   1.15000000e+02   1.16000000e+02   1.17000000e+02   1.18000000e+02
   1.19000000e+02   1.20000000e+02   1.21000000e+02   1.22000000e+02
   1.23000000e+02   1.24000000e+02   1.25000000e+02   1.26000000e+02
   1.27000000e+02   1.28000000e+02   1.30000000e+02   1.32000000e+02
   1.34000000e+02   1.35000000e+02   1.36000000e+02   1.37000000e+02
   1.38000000e+02   1.40000000e+02   1.41000000e+02   1.42000000e+02
   1.43000000e+02   1.44000000e+02   1.45000000e+02   1.46000000e+02
   1.47000000e+02   1.48000000e+02   1.49000000e+02   1.50000000e+02
   1.51000000e+02   1.53000000e+02   1.54000000e+02   1.56000000e+02
   1.57000000e+02   1.58000000e+02   1.60000000e+02   1.61000000e+02
   1.62000000e+02   1.63000000e+02   1.64000000e+02   1.65000000e+02
   1.66000000e+02   1.67000000e+02   1.68000000e+02   1.69000000e+02
   1.70000000e+02   1.71000000e+02   1.72000000e+02   1.74000000e+02
   1.75000000e+02   1.76000000e+02   1.77000000e+02   1.78000000e+02
   1.79000000e+02   1.80000000e+02   1.82000000e+02   1.83000000e+02
   1.84000000e+02   1.86000000e+02   1.87000000e+02   1.88000000e+02
   1.89000000e+02   1.90000000e+02   1.92000000e+02   1.94000000e+02
   1.96000000e+02   1.97000000e+02   1.98000000e+02   1.99000000e+02
   2.00000000e+02   2.02000000e+02   2.03000000e+02   2.04000000e+02
   2.05000000e+02   2.06000000e+02   2.07000000e+02   2.08000000e+02
   2.09000000e+02   2.10000000e+02   2.12000000e+02   2.14000000e+02
   2.15000000e+02   2.16000000e+02   2.17000000e+02   2.18000000e+02
   2.19000000e+02   2.20000000e+02   2.21000000e+02   2.22000000e+02
   2.23000000e+02   2.24000000e+02   2.25000000e+02   2.26000000e+02
   2.27000000e+02   2.28000000e+02   2.29000000e+02   2.30000000e+02
   2.32000000e+02   2.33000000e+02   2.34000000e+02   2.35000000e+02
   2.36000000e+02   2.37000000e+02   2.38000000e+02   2.40000000e+02
   2.42000000e+02   2.43000000e+02   2.44000000e+02   2.45000000e+02
   2.46000000e+02   2.47000000e+02   2.48000000e+02   2.50000000e+02
   2.51000000e+02   2.52000000e+02   2.53000000e+02   2.54000000e+02
   2.55000000e+02   2.56000000e+02   2.57000000e+02   2.58000000e+02
   2.59000000e+02   2.60000000e+02   2.61000000e+02   2.62000000e+02
   2.63000000e+02   2.64000000e+02   2.65000000e+02   2.66000000e+02
   2.68000000e+02   2.70000000e+02   2.72000000e+02   2.74000000e+02
   2.75000000e+02   2.76000000e+02   2.78000000e+02   2.79000000e+02
   2.80000000e+02   2.81000000e+02   2.83000000e+02   2.84000000e+02
   2.85000000e+02   2.86000000e+02   2.87000000e+02   2.88000000e+02
   2.89000000e+02   2.90000000e+02   2.91000000e+02   2.92000000e+02
   2.93000000e+02   2.94000000e+02   2.95000000e+02   2.96000000e+02
   2.97000000e+02   2.98000000e+02   2.99000000e+02   3.00000000e+02
   3.02000000e+02   3.04000000e+02   3.05000000e+02   3.06000000e+02
   3.08000000e+02   3.09000000e+02   3.10000000e+02   3.12000000e+02
   3.15000000e+02   3.18000000e+02   3.20000000e+02   3.22000000e+02
   3.23000000e+02   3.24000000e+02   3.27000000e+02   3.28000000e+02
   3.32000000e+02   3.33000000e+02   3.35000000e+02   3.36000000e+02
   3.37000000e+02   3.38000000e+02   3.40000000e+02   3.42000000e+02
   3.44000000e+02   3.48000000e+02   3.50000000e+02   3.51000000e+02
   3.52000000e+02   3.53000000e+02   3.55000000e+02   3.56000000e+02
   3.59000000e+02   3.60000000e+02   3.61000000e+02   3.62000000e+02
   3.64000000e+02   3.65000000e+02   3.66000000e+02   3.68000000e+02
   3.70000000e+02   3.71000000e+02   3.72000000e+02   3.75000000e+02
   3.76000000e+02   3.78000000e+02   3.79000000e+02   3.80000000e+02
   3.81000000e+02   3.82000000e+02   3.83000000e+02   3.85000000e+02
   3.87000000e+02   3.88000000e+02   3.91000000e+02   3.94000000e+02
   3.96000000e+02   3.97000000e+02   3.99000000e+02   4.00000000e+02
   4.02000000e+02   4.05000000e+02   4.06000000e+02   4.08000000e+02
   4.10000000e+02   4.12000000e+02   4.15000000e+02   4.18000000e+02
   4.20000000e+02   4.22000000e+02   4.23000000e+02   4.24000000e+02
   4.25000000e+02   4.26000000e+02   4.28000000e+02   4.30000000e+02
   4.32000000e+02   4.34000000e+02   4.35000000e+02   4.36000000e+02
   4.38000000e+02   4.40000000e+02   4.42000000e+02   4.43000000e+02
   4.44000000e+02   4.48000000e+02   4.50000000e+02   4.51000000e+02
   4.52000000e+02   4.56000000e+02   4.59000000e+02   4.64000000e+02
   4.66000000e+02   4.68000000e+02   4.70000000e+02   4.72000000e+02
   4.73000000e+02   4.79000000e+02   4.80000000e+02   4.81000000e+02
   4.91000000e+02   4.92000000e+02   4.95000000e+02   5.00000000e+02
   5.01000000e+02   5.02000000e+02   5.04000000e+02   5.06000000e+02
   5.09000000e+02   5.10000000e+02   5.13000000e+02   5.14000000e+02
   5.15000000e+02   5.18000000e+02   5.19000000e+02   5.22000000e+02
   5.25000000e+02   5.26000000e+02   5.28000000e+02   5.30000000e+02
   5.32000000e+02   5.41000000e+02   5.49000000e+02   5.50000000e+02
   5.54000000e+02   5.62000000e+02   5.64000000e+02   5.67000000e+02
   5.68000000e+02   5.71000000e+02   5.72000000e+02   5.73000000e+02
   5.76000000e+02   5.79000000e+02   5.84000000e+02   5.94000000e+02
   6.00000000e+02   6.03000000e+02   6.04000000e+02   6.15000000e+02
   6.16000000e+02   6.21000000e+02   6.30000000e+02   6.32000000e+02
   6.34000000e+02   6.40000000e+02   6.47000000e+02   6.50000000e+02
   6.51000000e+02   6.52000000e+02   6.53000000e+02   6.57000000e+02
   6.60000000e+02   6.62000000e+02   6.64000000e+02   6.68000000e+02
   6.73000000e+02   6.74000000e+02   6.80000000e+02   6.92000000e+02
   7.05000000e+02   7.10000000e+02   7.14000000e+02   7.24000000e+02
   7.26000000e+02   7.30000000e+02   7.31000000e+02   7.34000000e+02
   7.38000000e+02   7.48000000e+02   7.54000000e+02   7.60000000e+02
   7.62000000e+02   7.66000000e+02   7.68000000e+02   7.71000000e+02
   7.72000000e+02   7.88000000e+02   7.96000000e+02   8.16000000e+02
   8.60000000e+02   8.70000000e+02   8.77000000e+02   8.86000000e+02
   8.94000000e+02   9.02000000e+02   9.21000000e+02   9.22000000e+02
   9.45000000e+02   9.70000000e+02   9.75000000e+02   1.03100000e+03
   1.04700000e+03   1.05000000e+03   1.09500000e+03   1.11000000e+03
   1.11500000e+03   1.12900000e+03   1.15900000e+03   1.17000000e+03
   1.22400000e+03   1.29000000e+03   1.37800000e+03   1.60000000e+03
              nan]

MasVnrType [nan 'BrkCmn' 'BrkFace' 'None' 'Stone']

MiscFeature [nan 'Gar2' 'Othr' 'Shed' 'TenC']

MiscVal [    0    54    80   300   350   400   420   450   455   460   480   490
   500   560   600   620   650   700   750   800   900  1000  1150  1200
  1300  1400  1500  1512  2000  2500  3000  3500  4500  6500  8300 12500
 15500 17000]

MoSold [ 1  2  3  4  5  6  7  8  9 10 11 12]

Neighborhood ['Blmngtn' 'Blueste' 'BrDale' 'BrkSide' 'ClearCr' 'CollgCr' 'Crawfor'
 'Edwards' 'Gilbert' 'IDOTRR' 'MeadowV' 'Mitchel' 'NAmes' 'NPkVill'
 'NWAmes' 'NoRidge' 'NridgHt' 'OldTown' 'SWISU' 'Sawyer' 'SawyerW'
 'Somerst' 'StoneBr' 'Timber' 'Veenker']

OpenPorchSF [  0   4   6   8  10  11  12  15  16  17  18  20  21  22  23  24  25  26
  27  28  29  30  31  32  33  34  35  36  37  38  39  40  41  42  43  44
  45  46  47  48  49  50  51  52  53  54  55  56  57  58  59  60  61  62
  63  64  65  66  67  68  69  70  72  73  74  75  76  77  78  80  81  82
  83  84  85  86  87  88  89  90  91  92  93  94  95  96  97  98  99 100
 101 102 103 104 105 106 107 108 110 111 112 113 114 115 116 117 118 119
 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137
 138 139 140 141 142 144 146 148 150 151 152 153 154 155 156 158 159 160
 162 164 165 166 168 169 170 171 172 173 174 175 176 177 178 180 182 183
 184 185 187 188 189 190 191 192 193 194 195 197 198 199 200 201 203 204
 205 207 208 210 211 213 214 215 216 217 222 224 225 226 228 229 230 231
 234 235 236 238 240 241 243 244 245 246 247 250 251 252 253 254 256 258
 260 262 263 265 266 267 273 274 276 278 282 285 287 288 291 292 299 304
 312 319 324 341 364 365 368 372 382 406 418 444 484 502 523 547 570 742]

OverallCond [1 2 3 4 5 6 7 8 9]

OverallQual [ 1  2  3  4  5  6  7  8  9 10]

PavedDrive ['N' 'P' 'Y']

PoolArea [  0 144 228 368 444 480 512 519 555 561 576 648 738 800]

PoolQC [nan 'Ex' 'Fa' 'Gd']

RoofMatl ['ClyTile' 'CompShg' 'Membran' 'Metal' 'Roll' 'Tar&Grv' 'WdShake' 'WdShngl']

RoofStyle ['Flat' 'Gable' 'Gambrel' 'Hip' 'Mansard' 'Shed']

SaleCondition ['Abnorml' 'AdjLand' 'Alloca' 'Family' 'Normal' 'Partial']

SalePrice [  34900.   35311.   37900.   39300.   40000.   52000.   52500.   55000.
   55993.   58500.   60000.   61000.   62383.   64500.   66500.   67000.
   68400.   68500.   72500.   73000.   75000.   75500.   76000.   76500.
   78000.   79000.   79500.   79900.   80000.   80500.   81000.   82000.
   82500.   83000.   83500.   84000.   84500.   84900.   85000.   85400.
   85500.   86000.   87000.   87500.   88000.   89000.   89471.   89500.
   90000.   90350.   91000.   91300.   91500.   92000.   92900.   93000.
   93500.   94000.   94500.   94750.   95000.   96500.   97000.   97500.
   98000.   98300.   98600.   99500.   99900.  100000.  101000.  101800.
  102000.  102776.  103000.  103200.  103600.  104000.  104900.  105000.
  105500.  105900.  106000.  106250.  106500.  107000.  107400.  107500.
  107900.  108000.  108480.  108500.  108959.  109000.  109008.  109500.
  109900.  110000.  110500.  111000.  111250.  112000.  112500.  113000.
  114500.  114504.  115000.  116000.  116050.  116500.  116900.  117000.
  117500.  118000.  118400.  118500.  118858.  118964.  119000.  119200.
  119500.  119750.  119900.  120000.  120500.  121000.  121500.  121600.
  122000.  122500.  122900.  123000.  123500.  123600.  124000.  124500.
  124900.  125000.  125500.  126000.  126175.  126500.  127000.  127500.
  128000.  128200.  128500.  128900.  128950.  129000.  129500.  129900.
  130000.  130250.  130500.  131000.  131400.  131500.  132000.  132250.
  132500.  133000.  133500.  133700.  133900.  134000.  134432.  134450.
  134500.  134800.  134900.  135000.  135500.  135750.  135900.  135960.
  136000.  136500.  136900.  136905.  137000.  137450.  137500.  137900.
  138000.  138500.  138800.  138887.  139000.  139400.  139500.  139600.
  139900.  139950.  140000.  140200.  141000.  141500.  142000.  142125.
  142500.  142600.  142953.  143000.  143250.  143500.  143750.  143900.
  144000.  144152.  144500.  144900.  145000.  145250.  145500.  145900.
  146000.  146500.  146800.  147000.  147400.  147500.  148000.  148500.
  148800.  149000.  149300.  149350.  149500.  149700.  149900.  150000.
  150500.  150750.  150900.  151000.  151400.  151500.  152000.  153000.
  153337.  153500.  153575.  153900.  154000.  154300.  154500.  154900.
  155000.  155835.  155900.  156000.  156500.  156932.  157000.  157500.
  157900.  158000.  158500.  158900.  159000.  159434.  159500.  159895.
  159950.  160000.  160200.  161000.  161500.  161750.  162000.  162500.
  162900.  163000.  163500.  163900.  163990.  164000.  164500.  164700.
  164900.  164990.  165000.  165150.  165400.  165500.  165600.  166000.
  167000.  167240.  167500.  167900.  168000.  168500.  169000.  169500.
  169900.  169990.  170000.  171000.  171500.  171750.  171900.  172000.
  172400.  172500.  172785.  173000.  173500.  173733.  173900.  174000.
  174500.  174900.  175000.  175500.  175900.  176000.  176432.  176485.
  176500.  177000.  177500.  178000.  178400.  178740.  178900.  179000.
  179200.  179400.  179500.  179540.  179600.  179665.  179900.  180000.
  180500.  181000.  181134.  181500.  181900.  182000.  182900.  183000.
  183200.  183500.  183900.  184000.  184100.  184750.  184900.  185000.
  185500.  185750.  185850.  185900.  186000.  186500.  186700.  187000.
  187100.  187500.  187750.  188000.  188500.  188700.  189000.  189950.
  190000.  191000.  192000.  192140.  192500.  193000.  193500.  193879.
  194000.  194201.  194500.  194700.  195000.  195400.  196000.  196500.
  197000.  197500.  197900.  198500.  198900.  199900.  200000.  200100.
  200141.  200500.  200624.  201000.  201800.  202500.  202665.  202900.
  203000.  204000.  204750.  204900.  205000.  205950.  206000.  206300.
  206900.  207000.  207500.  208300.  208500.  208900.  209500.  210000.
  211000.  212000.  212900.  213000.  213250.  213490.  213500.  214000.
  214500.  214900.  215000.  215200.  216000.  216500.  216837.  217000.
  217500.  218000.  219210.  219500.  220000.  221000.  221500.  222000.
  222500.  223000.  223500.  224000.  224500.  224900.  225000.  226000.
  226700.  227000.  227680.  227875.  228000.  228500.  228950.  229000.
  229456.  230000.  230500.  231500.  232000.  232600.  233000.  233170.
  233230.  234000.  235000.  235128.  236000.  236500.  237000.  237500.
  238000.  239000.  239500.  239686.  239799.  239900.  240000.  241000.
  241500.  242000.  243000.  244000.  244400.  244600.  245000.  245350.
  245500.  246578.  248000.  248328.  248900.  249700.  250000.  250580.
  251000.  252000.  252678.  253000.  253293.  254000.  254900.  255000.
  255500.  255900.  256000.  256300.  257000.  257500.  258000.  259000.
  259500.  260000.  260400.  261500.  262000.  262280.  262500.  263000.
  263435.  264132.  264561.  265000.  265900.  265979.  266000.  266500.
  267000.  268000.  269500.  269790.  270000.  271000.  271900.  272000.
  274000.  274300.  274725.  274900.  274970.  275000.  275500.  276000.
  277000.  277500.  278000.  279500.  280000.  281000.  281213.  282922.
  283463.  284000.  285000.  286000.  287000.  287090.  289000.  290000.
  293077.  294000.  295000.  295493.  297000.  299800.  301000.  301500.
  302000.  303477.  305000.  305900.  306000.  307000.  309000.  310000.
  311500.  311872.  312500.  313000.  314813.  315000.  315500.  315750.
  316600.  317000.  318000.  318061.  319000.  319900.  320000.  324000.
  325000.  325300.  325624.  326000.  328000.  328900.  333168.  335000.
  336000.  337000.  337500.  339750.  340000.  341000.  342643.  345000.
  348000.  350000.  354000.  359100.  360000.  361919.  367294.  369900.
  370878.  372402.  372500.  374000.  375000.  377426.  377500.  378500.
  380000.  381000.  383970.  385000.  386250.  392000.  392500.  394432.
  394617.  395000.  395192.  402000.  402861.  403000.  410000.  412500.
  415298.  423000.  424870.  426000.  430000.  437154.  438780.  440000.
  446261.  451950.  465000.  466500.  475000.  485000.  501837.  538000.
  555000.  556581.  582933.  611657.  625000.  745000.  755000.      nan]

SaleType [nan 'COD' 'CWD' 'Con' 'ConLD' 'ConLI' 'ConLw' 'New' 'Oth' 'WD']

ScreenPorch [  0  40  53  60  63  64  80  84  88  90  92  94  95  99 100 104 108 109
 110 111 112 113 115 116 117 119 120 121 122 123 126 128 130 135 138 140
 141 142 143 144 145 147 148 150 152 153 154 155 156 160 161 162 163 164
 165 166 168 170 171 174 175 176 178 180 182 184 185 189 190 192 195 196
 197 198 200 201 204 208 210 216 217 220 221 222 224 225 227 228 231 233
 234 240 252 255 256 259 260 263 264 265 266 270 271 273 276 280 287 288
 291 312 322 342 348 374 385 396 410 440 480 490 576]

Street ['Grvl' 'Pave']

TotRmsAbvGrd [ 2  3  4  5  6  7  8  9 10 11 12 13 14 15]

TotalBsmtSF [    0.   105.   160. ...,  5095.  6110.    nan]

Utilities [nan 'AllPub' 'NoSeWa']

WoodDeckSF [   0    4   12   14   16   20   22   23   24   25   26   27   28   30   32
   33   35   36   38   40   42   44   45   48   49   50   51   52   53   54
   55   56   57   58   60   63   64   66   68   70   71   72   73   74   75
   76   77   78   80   81   84   85   86   87   88   89   90   92   94   95
   96   97   98   99  100  102  103  104  105  106  108  110  112  113  114
  115  116  117  118  119  120  121  122  123  124  125  126  127  128  129
  130  131  132  133  134  135  136  138  139  140  141  142  143  144  145
  146  147  148  149  150  152  153  154  155  156  157  158  159  160  161
  162  164  165  166  167  168  169  170  171  172  173  174  175  176  177
  178  179  180  181  182  183  184  185  186  187  188  189  190  191  192
  193  194  195  196  197  198  199  200  201  202  203  204  205  206  207
  208  209  210  211  212  213  214  215  216  218  219  220  221  222  224
  225  226  227  228  229  230  231  232  233  234  235  236  237  238  239
  240  241  242  243  244  245  246  247  248  250  252  253  255  256  257
  259  260  261  262  263  264  265  266  268  269  270  272  274  275  276
  277  278  279  280  282  283  284  285  286  287  288  289  290  291  292
  294  295  296  297  298  300  301  302  303  304  305  306  307  308  309
  311  312  314  315  316  318  319  320  321  322  324  325  326  327  328
  329  330  331  333  335  336  339  340  342  344  345  349  351  352  353
  354  355  356  358  360  361  362  364  365  366  367  370  371  375  379
  380  382  384  385  386  390  392  393  394  400  402  403  404  405  406
  407  409  411  413  414  416  418  421  424  426  428  431  432  436  439
  441  444  448  450  453  455  460  462  466  467  468  474  476  483  486
  490  495  496  500  501  502  503  509  511  517  519  520  521  530  536
  546  550  574  576  586  631  635  641  646  657  668  670  684  690  728
  736  857  870 1424]

YearBuilt [1872 1875 1879 1880 1882 1885 1890 1892 1893 1895 1896 1898 1900 1901 1902
 1904 1905 1906 1907 1908 1910 1911 1912 1913 1914 1915 1916 1917 1918 1919
 1920 1921 1922 1923 1924 1925 1926 1927 1928 1929 1930 1931 1932 1934 1935
 1936 1937 1938 1939 1940 1941 1942 1945 1946 1947 1948 1949 1950 1951 1952
 1953 1954 1955 1956 1957 1958 1959 1960 1961 1962 1963 1964 1965 1966 1967
 1968 1969 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982
 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997
 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010]

YearRemodAdd [1950 1951 1952 1953 1954 1955 1956 1957 1958 1959 1960 1961 1962 1963 1964
 1965 1966 1967 1968 1969 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979
 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994
 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
 2010]

YrSold [2006 2007 2008 2009 2010]

nulls = pd.DataFrame(df.isnull().sum().sort_values(ascending=False)[:40])
nulls.columns = ['Null Count']
nulls.index.name = 'Feature'
nulls

categoricals = df.select_dtypes(exclude=[np.number])
categoricals.describe()

# Filling Null Values

# Alley
df.Alley.fillna('None', inplace=True) # Assuming Null values means no alley access

# BsmtCond
df.BsmtCond.fillna('None', inplace=True) # Assuming Null values means no basement

# BsmtExposure
df.BsmtExposure.fillna('None', inplace=True) # Assuming Null values means no basement

# BsmtFinSF1 & BsmtFinSF2
df.BsmtFinSF1.fillna(0, inplace=True) # Assuming Null values means no basement
df.BsmtFinSF2.fillna(0, inplace=True) # Assuming Null values means no basement

# BsmtFinType1 & BsmtFinType2
df.BsmtFinType1.fillna('None', inplace=True) # Assuming Null values means no basement
df.BsmtFinType2.fillna('None', inplace=True) # Assuming Null values means no basement

# BsmtFullBath & BsmtHalfBath
df.BsmtFullBath.fillna(0,inplace=True) # Assuming Null values means no basement
df.BsmtHalfBath.fillna(0,inplace=True) # Assuming Null values means no basement

# BsmtQual
df.BsmtQual.fillna('None', inplace=True) # Assuming Null values means no basement

# BsmtUnfSF
df.BsmtUnfSF.fillna(0, inplace=True) # Assuming Null values means no basement

# Electrical
print df.Electrical.value_counts(), '\n' # Has 1 Missing Value
df.Electrical.fillna('SBrkr', inplace=True) # Fill in with most common value

# Exterior1st & Exterior2nd
print df.Exterior1st.value_counts(), '\n'
print df.Exterior2nd.value_counts(), '\n'
df.Exterior1st.fillna('VinylSd', inplace=True) # Fill in with most common value
df.Exterior2nd.fillna('VinylSd', inplace=True) # Fill in with most common value

# Fence
df.Fence.fillna('None', inplace=True) # Assuming Null values means no fence

# FireplaceQu
df.FireplaceQu.fillna('None', inplace=True) # Assuming Null values means no fireplace

# Functional
print df.Functional.value_counts(), '\n'
df.Functional.fillna('Typ',inplace=True)

# GarageArea & GarageCars
df.GarageArea.fillna(0,inplace=True) # Assuming Null values means no garage
df.GarageCars.fillna(0,inplace=True) # Assuming Null values means no garage

# GarageCond, GarageFinish, GarageQual, GarageType
df.GarageCond.fillna('None', inplace=True) # Assuming Null values means no garage
df.GarageFinish.fillna('None', inplace=True) # Assuming Null values means no garage
df.GarageQual.fillna('None', inplace=True) # Assuming Null values means no garage
df.GarageType.fillna('None', inplace=True) # Assuming Null values means no garage

# GarageYrBlt
df.GarageYrBlt.fillna(0,inplace=True) # Assuming Null values means no garage. Therefore making the value here very old and therefore less valuable

# KitchenQual
print df[df.KitchenAbvGr==0]['KitchenQual'], '\n' # Check kitchen quality values for homes without kitchens above ground
print df.KitchenQual.value_counts(), '\n'
df.KitchenQual.fillna('TA',inplace=True) # Fill with most common value

# LotFrontage
df.LotFrontage.fillna(0,inplace=True) # Assuming Null values means no front lot

# MasVnrArea & MasVnrType
df.MasVnrType.fillna('None',inplace=True) # Assuming Null values means no masonary veneer
df.MasVnrArea.fillna(0,inplace=True) # Assuming Null values means no masonary veneer

# MiscFeature
df.MiscFeature.fillna('None',inplace=True) # Assuming Null values means no misc feature

# MSZoning
print df.MSZoning.value_counts(), '\n'
df.MSZoning.fillna('RL',inplace=True) # Fill with most common value

# PoolQC
df.PoolQC.fillna('None', inplace=True) # Assuming Null values means no pool

# SaleType
print df.SaleType.value_counts(), '\n'
df.SaleType.fillna('WD',inplace=True) # Fill with most common value

# TotalBsmtSF
df.TotalBsmtSF.fillna(0,inplace=True) # Assuming Null values mean no basement

# Utilities
print df.Utilities.value_counts(), '\n'
df.Utilities.fillna('AllPub',inplace=True) # Fill in with most common value

SBrkr    2671
FuseA     188
FuseF      50
FuseP       8
Mix         1
Name: Electrical, dtype: int64

VinylSd    1025
MetalSd     450
HdBoard     442
Wd Sdng     411
Plywood     221
CemntBd     126
BrkFace      87
WdShing      56
AsbShng      44
Stucco       43
BrkComm       6
AsphShn       2
Stone         2
CBlock        2
ImStucc       1
Name: Exterior1st, dtype: int64

VinylSd    1014
MetalSd     447
HdBoard     406
Wd Sdng     391
Plywood     270
CmentBd     126
Wd Shng      81
BrkFace      47
Stucco       47
AsbShng      38
Brk Cmn      22
ImStucc      15
Stone         6
AsphShn       4
CBlock        3
Other         1
Name: Exterior2nd, dtype: int64

Typ     2717
Min2      70
Min1      65
Mod       35
Maj1      19
Maj2       9
Sev        2
Name: Functional, dtype: int64

954     TA
1127    TA
1399    TA
Name: KitchenQual, dtype: object

TA    1492
Gd    1151
Ex     205
Fa      70
Name: KitchenQual, dtype: int64

RL         2265
RM          460
FV          139
RH           26
C (all)      25
Name: MSZoning, dtype: int64

WD       2525
New       239
COD        87
ConLD      26
CWD        12
ConLI       9
ConLw       8
Oth         7
Con         5
Name: SaleType, dtype: int64

AllPub    2916
NoSeWa       1
Name: Utilities, dtype: int64

# Personal Preference - Making all floats ints

df.MasVnrArea = map(int,df.MasVnrArea)
df.GarageYrBlt = map(int,df.GarageYrBlt)
df.LotFrontage = map(int,df.LotFrontage)
df.GarageArea = map(int,df.GarageArea)
df.GarageCars = map(int,df.GarageCars)
df.BsmtUnfSF = map(int,df.BsmtUnfSF)
df.BsmtHalfBath = map(int,df.BsmtHalfBath)
df.BsmtFullBath = map(int,df.BsmtFullBath)
df.TotalBsmtSF = map(int,df.TotalBsmtSF)
df.BsmtFinSF1 = map(int,df.BsmtFinSF1)
df.BsmtFinSF2 = map(int,df.BsmtFinSF2)

df.info()

<class 'pandas.core.frame.DataFrame'>
Int64Index: 2919 entries, 0 to 1458
Data columns (total 81 columns):
1stFlrSF         2919 non-null int64
2ndFlrSF         2919 non-null int64
3SsnPorch        2919 non-null int64
Alley            2919 non-null object
BedroomAbvGr     2919 non-null int64
BldgType         2919 non-null object
BsmtCond         2919 non-null object
BsmtExposure     2919 non-null object
BsmtFinSF1       2919 non-null int64
BsmtFinSF2       2919 non-null int64
BsmtFinType1     2919 non-null object
BsmtFinType2     2919 non-null object
BsmtFullBath     2919 non-null int64
BsmtHalfBath     2919 non-null int64
BsmtQual         2919 non-null object
BsmtUnfSF        2919 non-null int64
CentralAir       2919 non-null object
Condition1       2919 non-null object
Condition2       2919 non-null object
Electrical       2919 non-null object
EnclosedPorch    2919 non-null int64
ExterCond        2919 non-null object
ExterQual        2919 non-null object
Exterior1st      2919 non-null object
Exterior2nd      2919 non-null object
Fence            2919 non-null object
FireplaceQu      2919 non-null object
Fireplaces       2919 non-null int64
Foundation       2919 non-null object
FullBath         2919 non-null int64
Functional       2919 non-null object
GarageArea       2919 non-null int64
GarageCars       2919 non-null int64
GarageCond       2919 non-null object
GarageFinish     2919 non-null object
GarageQual       2919 non-null object
GarageType       2919 non-null object
GarageYrBlt      2919 non-null int64
GrLivArea        2919 non-null int64
HalfBath         2919 non-null int64
Heating          2919 non-null object
HeatingQC        2919 non-null object
HouseStyle       2919 non-null object
Id               2919 non-null int64
KitchenAbvGr     2919 non-null int64
KitchenQual      2919 non-null object
LandContour      2919 non-null object
LandSlope        2919 non-null object
LotArea          2919 non-null int64
LotConfig        2919 non-null object
LotFrontage      2919 non-null int64
LotShape         2919 non-null object
LowQualFinSF     2919 non-null int64
MSSubClass       2919 non-null int64
MSZoning         2919 non-null object
MasVnrArea       2919 non-null int64
MasVnrType       2919 non-null object
MiscFeature      2919 non-null object
MiscVal          2919 non-null int64
MoSold           2919 non-null int64
Neighborhood     2919 non-null object
OpenPorchSF      2919 non-null int64
OverallCond      2919 non-null int64
OverallQual      2919 non-null int64
PavedDrive       2919 non-null object
PoolArea         2919 non-null int64
PoolQC           2919 non-null object
RoofMatl         2919 non-null object
RoofStyle        2919 non-null object
SaleCondition    2919 non-null object
SalePrice        1460 non-null float64
SaleType         2919 non-null object
ScreenPorch      2919 non-null int64
Street           2919 non-null object
TotRmsAbvGrd     2919 non-null int64
TotalBsmtSF      2919 non-null int64
Utilities        2919 non-null object
WoodDeckSF       2919 non-null int64
YearBuilt        2919 non-null int64
YearRemodAdd     2919 non-null int64
YrSold           2919 non-null int64
dtypes: float64(1), int64(37), object(43)
memory usage: 1.8+ MB

# Categoricals Missing MSSubClass Feature since it is an int. Similar to an area code

categoricalCols = list(categoricals.columns)
categoricalCols.append('MSSubClass')
categoricalCols

['Alley',
 'BldgType',
 'BsmtCond',
 'BsmtExposure',
 'BsmtFinType1',
 'BsmtFinType2',
 'BsmtQual',
 'CentralAir',
 'Condition1',
 'Condition2',
 'Electrical',
 'ExterCond',
 'ExterQual',
 'Exterior1st',
 'Exterior2nd',
 'Fence',
 'FireplaceQu',
 'Foundation',
 'Functional',
 'GarageCond',
 'GarageFinish',
 'GarageQual',
 'GarageType',
 'Heating',
 'HeatingQC',
 'HouseStyle',
 'KitchenQual',
 'LandContour',
 'LandSlope',
 'LotConfig',
 'LotShape',
 'MSZoning',
 'MasVnrType',
 'MiscFeature',
 'Neighborhood',
 'PavedDrive',
 'PoolQC',
 'RoofMatl',
 'RoofStyle',
 'SaleCondition',
 'SaleType',
 'Street',
 'Utilities',
 'MSSubClass']

# GetDummies

df = pd.get_dummies(df,columns=categoricalCols,drop_first=True)
df.head(15)

import statsmodels.api as sm

dfTrain = df[0:1459]
dfFinalTest = df[1460:]
dfFinalTest = sm.add_constant(dfFinalTest.drop(['SalePrice'],axis=1)) # Need constant for linear regression models
dfyTrain = dfTrain['SalePrice']
#dfXTrain = dfTrain.drop(['SalePrice'],axis=1)
dfXTrain = sm.add_constant(dfTrain.drop(['SalePrice','Id'],axis=1)) # Need constant for linear regression models

C:\Users\nwerner\AppData\Local\Continuum\Anaconda2\lib\site-packages\statsmodels\compat\pandas.py:56: FutureWarning: The pandas.core.datetools module is deprecated and will be removed in a future version. Please use the pandas.tseries module instead.
  from pandas.core import datetools

Normalizing SalePrice¶

print 'Skew is:', dfyTrain.skew()
plt.hist(dfyTrain)
plt.show()

Skew is: 1.88176004682

target = np.log(dfyTrain)
print 'Skew is:', target.skew()
plt.hist(target)
plt.show()

Skew is: 0.120694014457

Model Time¶

X_train, X_test, y_train, y_test = tts(dfXTrain,target,train_size=0.8, random_state=69)
X_train.shape, y_train.shape, X_test.shape, y_test.shape

((1167, 274), (1167L,), (292, 274), (292L,))

#X_Train_const = sm.add_constant(X_train)

#est_price = sm.OLS(y_train, X_Train_const).fit()
#est_price.summary()

est_price = sm.OLS(target, dfXTrain).fit()
est_price.summary()

C:\Users\nwerner\AppData\Local\Continuum\Anaconda2\lib\site-packages\statsmodels\base\model.py:1036: RuntimeWarning: invalid value encountered in divide
  return self.params / self.bse
C:\Users\nwerner\AppData\Local\Continuum\Anaconda2\lib\site-packages\scipy\stats\_distn_infrastructure.py:879: RuntimeWarning: invalid value encountered in greater
  return (self.a < x) & (x < self.b)
C:\Users\nwerner\AppData\Local\Continuum\Anaconda2\lib\site-packages\scipy\stats\_distn_infrastructure.py:879: RuntimeWarning: invalid value encountered in less
  return (self.a < x) & (x < self.b)
C:\Users\nwerner\AppData\Local\Continuum\Anaconda2\lib\site-packages\scipy\stats\_distn_infrastructure.py:1818: RuntimeWarning: invalid value encountered in less_equal
  cond2 = cond0 & (x <= self.a)

y_pred_OLS = est_price.predict(dfXTrain)

rmse_OLS = mean_squared_error(target, y_pred_OLS)**0.5
r2_OLS = r2_score(target, y_pred_OLS)

print 'RMSE:', rmse_OLS
print 'R2 Score:', r2_OLS

RMSE: 0.0934055998265
R2 Score: 0.945317934136

# Linear Regression

linreg = linear_model.LinearRegression()
linreg.fit(X_train, y_train)

y_pred_lin = linreg.predict(X_test)

rmse_lin = mean_squared_error(y_test, y_pred_lin)**0.5
r2_lin = r2_score(y_test, y_pred_lin)

print 'RMSE:', rmse_lin
print 'R2 Score:', r2_lin

RMSE: 0.193812161543
R2 Score: 0.75166313022

plt.scatter(y_pred_lin, y_test, alpha=0.75)
plt.plot([11,13], [11,13], 'r--')
plt.xlabel('Predicted Price (Natural Log)')
plt.ylabel('Actual Price (Natural Log)')
plt.title('Linear Regression Model')
overlay = 'R^2 is: {}\nRMSE is: {}'.format(r2_lin, rmse_lin)
plt.annotate(s=overlay, xy=(12.1, 11.1))
plt.show()

print 'Estimated Intercept Coefficient:', linreg.intercept_
pd.DataFrame(zip(X_train.columns, linreg.coef_), columns=['Features', 'Estimated Coefficients'])

Estimated Intercept Coefficient: 9.28593348031

# Ridge Regression

ridgereg = linear_model.Ridge()
ridgereg.fit(X_train, y_train)

y_pred_ridge = ridgereg.predict(X_test)

rmse_ridge = mean_squared_error(y_test, y_pred_ridge)**0.5
r2_ridge = r2_score(y_test, y_pred_ridge)

print 'RMSE:', rmse_ridge
print 'R2 Score:', r2_ridge

RMSE: 0.125338089334
R2 Score: 0.896140723647

plt.scatter(y_pred_ridge, y_test, alpha=0.75)
plt.plot([11,13], [11,13], 'r--')
plt.xlabel('Predicted Price (Natural Log)')
plt.ylabel('Actual Price (Natural Log)')
plt.title('Ridge Regression Model')
overlay = 'R^2 is: {}\nRMSE is: {}'.format(r2_ridge, rmse_ridge)
plt.annotate(s=overlay, xy=(12.1, 11.1))
plt.show()

# Lasso Regression

lassoreg = linear_model.Lasso()
lassoreg.fit(X_train, y_train)

y_pred_lasso = lassoreg.predict(X_test)

rmse_lasso = mean_squared_error(y_test, y_pred_lasso)**0.5
r2_lasso = r2_score(y_test, y_pred_lasso)

#print 'R^2 is:', lassoreg.score(X_test, y_test)
print 'RMSE:', rmse_lasso
print 'R2 Score:', r2_lasso

RMSE: 0.180619478801
R2 Score: 0.784320771285

plt.scatter(y_pred_lasso, y_test, alpha=0.75)
plt.plot([11,13], [11,13], 'r--')
plt.xlabel('Predicted Price (Natural Log)')
plt.ylabel('Actual Price (Natural Log)')
plt.title('Lasso Regression Model')
overlay = 'R^2 is: {}\nRMSE is: {}'.format(r2_lasso, rmse_lasso)
plt.annotate(s=overlay, xy=(12.1, 11.1))
plt.show()

Make Submission¶

# Create Submission DataFrame per Algorithm

submission_OLS = pd.DataFrame()
submission_lin = pd.DataFrame()
submission_ridge = pd.DataFrame()
submission_lasso = pd.DataFrame()

# Include 'Id' Column in submission per Algorithm

submission_OLS['Id'] = dfFinalTest.Id
submission_lin['Id'] = dfFinalTest.Id
submission_ridge['Id'] = dfFinalTest.Id
submission_lasso['Id'] = dfFinalTest.Id

# Make Predictions without 'Id' Column per Algorithm

predictions_OLS = est_price.predict(dfFinalTest.drop(['Id'],axis=1))
predictions_lin = linreg.predict(dfFinalTest.drop(['Id'],axis=1))
predictions_ridge = ridgereg.predict(dfFinalTest.drop(['Id'],axis=1))
predictions_lasso = lassoreg.predict(dfFinalTest.drop(['Id'],axis=1))

# Convert prediction back out of natural log per Algorithm

final_predictions_OLS = np.exp(predictions_OLS)
final_predictions_lin = np.exp(predictions_lin)
final_predictions_ridge = np.exp(predictions_ridge)
final_predictions_lasso = np.exp(predictions_lasso)

# Place predictions in submission DataFrame per Algorithm

submission_OLS['SalePrice'] = final_predictions_OLS
submission_lin['SalePrice'] = final_predictions_lin
submission_ridge['SalePrice'] = final_predictions_ridge
submission_lasso['SalePrice'] = final_predictions_lasso

# Convert DataFrame to CSV per Algorithm

submission_OLS.to_csv('submission_OLS.csv', index=False)
submission_lin.to_csv('submission_lin.csv', index=False)
submission_ridge.to_csv('submission_ridge.csv', index=False)
submission_lasso.to_csv('submission_lasso.csv', index=False)

	1stFlrSF	2ndFlrSF	3SsnPorch	BedroomAbvGr	BsmtFinSF1	BsmtFinSF2	BsmtFullBath	BsmtHalfBath	BsmtUnfSF	EnclosedPorch	...	OverallQual	PoolArea	SalePrice	ScreenPorch	TotRmsAbvGrd	TotalBsmtSF	WoodDeckSF	YearBuilt	YearRemodAdd	YrSold
count	2919.000000	2919.000000	2919.000000	2919.000000	2918.000000	2918.000000	2917.000000	2917.000000	2918.000000	2919.000000	...	2919.000000	2919.000000	1460.000000	2919.000000	2919.000000	2918.000000	2919.000000	2919.000000	2919.000000	2919.000000
mean	1159.581706	336.483727	2.602261	2.860226	441.423235	49.582248	0.429894	0.061364	560.772104	23.098321	...	6.089072	2.251799	180921.195890	16.062350	6.451524	1051.777587	93.709832	1971.312778	1984.264474	2007.792737
std	392.362079	428.701456	25.188169	0.822693	455.610826	169.205611	0.524736	0.245687	439.543659	64.244246	...	1.409947	35.663946	79442.502883	56.184365	1.569379	440.766258	126.526589	30.291442	20.894344	1.314964
min	334.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	...	1.000000	0.000000	34900.000000	0.000000	2.000000	0.000000	0.000000	1872.000000	1950.000000	2006.000000
25%	876.000000	0.000000	0.000000	2.000000	0.000000	0.000000	0.000000	0.000000	220.000000	0.000000	...	5.000000	0.000000	129975.000000	0.000000	5.000000	793.000000	0.000000	1953.500000	1965.000000	2007.000000
50%	1082.000000	0.000000	0.000000	3.000000	368.500000	0.000000	0.000000	0.000000	467.000000	0.000000	...	6.000000	0.000000	163000.000000	0.000000	6.000000	989.500000	0.000000	1973.000000	1993.000000	2008.000000
75%	1387.500000	704.000000	0.000000	3.000000	733.000000	0.000000	1.000000	0.000000	805.500000	0.000000	...	7.000000	0.000000	214000.000000	0.000000	7.000000	1302.000000	168.000000	2001.000000	2004.000000	2009.000000
max	5095.000000	2065.000000	508.000000	8.000000	5644.000000	1526.000000	3.000000	2.000000	2336.000000	1012.000000	...	10.000000	800.000000	755000.000000	576.000000	15.000000	6110.000000	1424.000000	2010.000000	2010.000000	2010.000000

	1stFlrSF	2ndFlrSF	3SsnPorch	BedroomAbvGr	BsmtFinSF1	BsmtFinSF2	BsmtFullBath	BsmtHalfBath	BsmtUnfSF	EnclosedPorch	...	OverallQual	PoolArea	SalePrice	ScreenPorch	TotRmsAbvGrd	TotalBsmtSF	WoodDeckSF	YearBuilt	YearRemodAdd	YrSold
1stFlrSF	1.000000	-0.249823	0.044086	0.108418	0.458092	0.084330	0.261816	0.011074	0.296600	-0.065796	...	0.479152	0.121900	0.605852	0.098381	0.391782	0.801670	0.227347	0.310814	0.242245	-0.013442
2ndFlrSF	-0.249823	1.000000	-0.032458	0.503506	-0.162301	-0.097744	-0.161468	-0.060282	-0.000376	0.054645	...	0.245596	0.044503	0.319334	0.011070	0.584586	-0.205665	0.089922	0.017588	0.158985	-0.019229
3SsnPorch	0.044086	-0.032458	1.000000	-0.048279	0.050908	-0.023279	0.027378	0.026861	-0.005810	-0.032822	...	0.018715	-0.006525	0.044584	-0.029546	-0.025764	0.037892	-0.003935	0.015958	0.037433	0.022560
BedroomAbvGr	0.108418	0.503506	-0.048279	1.000000	-0.113547	-0.031223	-0.155200	0.018848	0.183259	0.049940	...	0.073075	0.036544	0.168213	0.007254	0.669737	0.053393	0.031644	-0.053101	-0.021912	-0.020453
BsmtFinSF1	0.458092	-0.162301	0.050908	-0.113547	1.000000	-0.055045	0.638847	0.078361	-0.477404	-0.099712	...	0.281810	0.084462	0.386420	0.096823	0.052141	0.536467	0.223492	0.279581	0.152126	0.022556
BsmtFinSF2	0.084330	-0.097744	-0.023279	-0.031223	-0.055045	1.000000	0.162835	0.099485	-0.238241	0.032740	...	-0.042771	0.044524	-0.011378	0.063302	-0.048423	0.089410	0.098399	-0.027595	-0.062153	0.008883
BsmtFullBath	0.261816	-0.161468	0.027378	-0.155200	0.638847	0.162835	1.000000	-0.148832	-0.398678	-0.068393	...	0.164543	0.043970	0.227122	0.053119	-0.038916	0.325623	0.186107	0.211580	0.134947	0.045255
BsmtHalfBath	0.011074	-0.060282	0.026861	0.018848	0.078361	0.099485	-0.148832	1.000000	-0.107121	-0.009675	...	-0.040732	0.066851	-0.016844	0.042069	-0.049610	0.012396	0.051549	-0.030282	-0.046285	-0.020028
BsmtUnfSF	0.296600	-0.000376	-0.005810	0.183259	-0.477404	-0.238241	-0.398678	-0.107121	1.000000	0.005006	...	0.275175	-0.032273	0.214479	-0.049158	0.247505	0.412285	-0.039302	0.130473	0.165175	-0.038015
EnclosedPorch	-0.065796	0.054645	-0.032822	0.049940	-0.099712	0.032740	-0.068393	-0.009675	0.005006	1.000000	...	-0.139256	0.092534	-0.128578	-0.064377	0.015345	-0.085510	-0.119114	-0.374073	-0.220456	-0.001134
Fireplaces	0.407545	0.169991	0.018852	0.086793	0.293089	0.065625	0.169580	0.039265	0.004814	0.000971	...	0.390753	0.099123	0.466929	0.169784	0.311260	0.332953	0.227608	0.170680	0.134157	-0.006752
FullBath	0.373077	0.402865	0.015192	0.356125	0.081525	-0.075432	-0.018815	-0.047046	0.273207	-0.118983	...	0.528483	0.028091	0.560664	-0.015910	0.527337	0.327762	0.181266	0.471169	0.457980	-0.004882
GarageArea	0.492011	0.128570	0.029440	0.073912	0.310449	0.003139	0.184738	-0.021445	0.164409	-0.106417	...	0.565122	0.053049	0.623431	0.062389	0.328687	0.486067	0.238075	0.480735	0.376765	-0.013451
GarageCars	0.440540	0.182452	0.023383	0.092876	0.255482	-0.014827	0.161709	-0.033462	0.180099	-0.132846	...	0.600744	0.030424	0.640409	0.043112	0.358053	0.437997	0.240715	0.538074	0.426022	-0.022918
GarageYrBlt	0.260450	0.086094	0.020699	-0.045364	0.194270	-0.068549	0.150492	-0.058379	0.171588	-0.300751	...	0.571803	-0.014467	0.486362	-0.062320	0.162684	0.348408	0.222584	0.834812	0.652365	-0.004543
GrLivArea	0.562538	0.655085	0.006268	0.517058	0.211669	-0.017872	0.060531	-0.043947	0.233988	0.003274	...	0.575126	0.135441	0.708624	0.086284	0.808354	0.445276	0.251017	0.242666	0.316972	-0.026919
HalfBath	-0.104141	0.611362	-0.023417	0.245318	-0.007311	-0.032448	-0.033468	-0.058438	-0.035803	-0.081978	...	0.272668	0.001424	0.284108	0.035622	0.345572	-0.055718	0.116701	0.269743	0.211430	0.001587
Id	-0.008678	-0.022252	-0.046538	0.003074	-0.016947	0.018251	0.000145	0.010387	-0.014453	0.021609	...	-0.029771	0.014332	-0.021917	0.022208	-0.029368	-0.024924	-0.007056	-0.016581	-0.050438	-0.256050
KitchenAbvGr	0.076071	0.069032	-0.021462	0.241182	-0.086354	-0.037779	-0.017931	-0.064916	0.064987	0.027639	...	-0.159325	-0.013116	-0.135907	-0.056573	0.294569	-0.038959	-0.087399	-0.137614	-0.142431	0.035173
LotArea	0.332460	0.031515	0.015995	0.132801	0.194031	0.084059	0.128349	0.026292	0.021362	0.020974	...	0.100541	0.093708	0.263843	0.054375	0.213802	0.254138	0.158045	0.024128	0.021612	-0.024234
LotFrontage	0.458247	0.026545	0.028289	0.234892	0.219408	0.047431	0.113245	-0.025629	0.113714	0.011509	...	0.217645	0.174119	0.351799	0.075858	0.349513	0.354822	0.122070	0.122811	0.091557	-0.007917
LowQualFinSF	-0.012704	0.017803	-0.004545	0.070365	-0.066028	-0.004923	-0.047099	-0.013500	0.046913	0.087212	...	-0.048393	0.035177	-0.025606	0.006835	0.102059	-0.023359	-0.015622	-0.144191	-0.060371	-0.002257
MSSubClass	-0.248641	0.309309	-0.037529	-0.008796	-0.064311	-0.072530	0.009950	-0.001878	-0.125994	-0.020867	...	0.033638	-0.003080	-0.084284	-0.049181	0.040509	-0.219965	-0.017654	0.034409	0.043315	-0.015028
MasVnrArea	0.395834	0.121014	0.013612	0.078126	0.303490	-0.015645	0.141593	0.015006	0.090163	-0.111499	...	0.432947	0.004512	0.477493	0.065209	0.278228	0.397240	0.166200	0.314051	0.196875	-0.018510
MiscVal	0.093062	-0.005299	-0.000788	0.000245	0.093295	-0.005139	-0.004629	0.036902	-0.010492	0.008654	...	0.005562	0.011921	-0.021190	0.007067	0.060903	0.084002	0.056883	-0.010886	-0.003124	0.008445
MoSold	0.040143	0.014185	0.027391	0.055997	-0.000942	-0.009593	-0.003568	0.023014	0.022607	-0.020976	...	0.030405	-0.042230	0.046432	0.028535	0.045137	0.017888	0.018120	0.013938	0.017693	-0.153895
OpenPorchSF	0.238502	0.185387	-0.009392	0.086212	0.124163	-0.005876	0.081265	-0.034917	0.119764	-0.059672	...	0.298084	0.064212	0.315856	0.047777	0.238156	0.245521	0.038457	0.198554	0.242182	-0.037377
OverallCond	-0.157418	0.005494	0.043739	-0.008477	-0.050418	0.041501	-0.042133	0.084181	-0.138202	0.071044	...	-0.093847	-0.016876	-0.077856	0.043713	-0.092027	-0.174002	0.020123	-0.368477	0.047654	0.030102
OverallQual	0.479152	0.245596	0.018715	0.073075	0.281810	-0.042771	0.164543	-0.040732	0.275175	-0.139256	...	1.000000	0.030740	0.790982	0.042910	0.389761	0.549294	0.255317	0.597554	0.571532	-0.019614
PoolArea	0.121900	0.044503	-0.006525	0.036544	0.084462	0.044524	0.043970	0.066851	-0.032273	0.092534	...	0.030740	1.000000	0.092404	0.026319	0.072061	0.072216	0.094231	0.002304	-0.011407	-0.052816
SalePrice	0.605852	0.319334	0.044584	0.168213	0.386420	-0.011378	0.227122	-0.016844	0.214479	-0.128578	...	0.790982	0.092404	1.000000	0.111447	0.533723	0.613581	0.324413	0.522897	0.507101	-0.028923
ScreenPorch	0.098381	0.011070	-0.029546	0.007254	0.096823	0.063302	0.053119	0.042069	-0.049158	-0.064377	...	0.042910	0.026319	0.111447	1.000000	0.032324	0.075363	-0.052134	-0.041046	-0.046878	-0.006634
TotRmsAbvGrd	0.391782	0.584586	-0.025764	0.669737	0.052141	-0.048423	-0.038916	-0.049610	0.247505	0.015345	...	0.389761	0.072061	0.533723	0.032324	1.000000	0.282126	0.156543	0.114280	0.198250	-0.032354
TotalBsmtSF	0.801670	-0.205665	0.037892	0.053393	0.536467	0.089410	0.325623	0.012396	0.412285	-0.085510	...	0.549294	0.072216	0.613581	0.075363	0.282126	1.000000	0.229600	0.408515	0.298107	-0.011184
WoodDeckSF	0.227347	0.089922	-0.003935	0.031644	0.223492	0.098399	0.186107	0.051549	-0.039302	-0.119114	...	0.255317	0.094231	0.324413	-0.052134	0.156543	0.229600	1.000000	0.229426	0.218513	-0.000180
YearBuilt	0.310814	0.017588	0.015958	-0.053101	0.279581	-0.027595	0.211580	-0.030282	0.130473	-0.374073	...	0.597554	0.002304	0.522897	-0.041046	0.114280	0.408515	0.229426	1.000000	0.612235	-0.012344
YearRemodAdd	0.242245	0.158985	0.037433	-0.021912	0.152126	-0.062153	0.134947	-0.046285	0.165175	-0.220456	...	0.571532	-0.011407	0.507101	-0.046878	0.198250	0.298107	0.218513	0.612235	1.000000	0.033203
YrSold	-0.013442	-0.019229	0.022560	-0.020453	0.022556	0.008883	0.045255	-0.020028	-0.038015	-0.001134	...	-0.019614	-0.052816	-0.028923	-0.006634	-0.032354	-0.011184	-0.000180	-0.012344	0.033203	1.000000

Dep. Variable:	SalePrice	R-squared:	0.945
Model:	OLS	Adj. R-squared:	0.933
Method:	Least Squares	F-statistic:	78.55
Date:	Sun, 11 Mar 2018	Prob (F-statistic):	0.00
Time:	15:57:56	Log-Likelihood:	1388.8
No. Observations:	1459	AIC:	-2250.
Df Residuals:	1195	BIC:	-854.2
Df Model:	263
Covariance Type:	nonrobust

Omnibus:	395.732	Durbin-Watson:	1.925
Prob(Omnibus):	0.000	Jarque-Bera (JB):	5634.954
Skew:	-0.857	Prob(JB):	0.00
Kurtosis:	12.474	Cond. No.	1.30e+16

	Features	Estimated Coefficients
0	const	8.742466e-12
1	1stFlrSF	2.063752e-05
2	2ndFlrSF	3.331042e-05
3	3SsnPorch	3.413177e-04
4	BedroomAbvGr	1.312744e-02
5	BsmtFinSF1	5.463368e-05
6	BsmtFinSF2	3.186460e-05
7	BsmtFullBath	2.723053e-02
8	BsmtHalfBath	1.792452e-02
9	BsmtUnfSF	8.191365e-06
10	EnclosedPorch	1.518203e-04
11	Fireplaces	9.869554e-03
12	FullBath	1.361272e-02
13	GarageArea	1.389872e-04
14	GarageCars	2.277805e-02
15	GarageYrBlt	1.250351e-04
16	GrLivArea	1.818444e-04
17	HalfBath	3.129251e-02
18	KitchenAbvGr	-1.949635e-02
19	LotArea	3.143372e-06
20	LotFrontage	-2.497678e-05
21	LowQualFinSF	1.278963e-04
22	MasVnrArea	4.733941e-05
23	MiscVal	2.343580e-06
24	MoSold	-3.505495e-04
25	OpenPorchSF	1.093257e-05
26	OverallCond	3.479756e-02
27	OverallQual	4.127441e-02
28	PoolArea	4.940483e-03
29	ScreenPorch	3.054257e-04
...	...	...
244	SaleCondition_AdjLand	9.445715e-02
245	SaleCondition_Alloca	-1.197131e-02
246	SaleCondition_Family	1.600923e-02
247	SaleCondition_Normal	4.799301e-02
248	SaleCondition_Partial	9.378706e-03
249	SaleType_CWD	9.967190e-02
250	SaleType_Con	3.461150e-02
251	SaleType_ConLD	8.578715e-02
252	SaleType_ConLI	-7.662338e-02
253	SaleType_ConLw	1.342122e-02
254	SaleType_New	5.267556e-02
255	SaleType_Oth	6.203358e-02
256	SaleType_WD	-2.200300e-02
257	Street_Pave	2.881701e-02
258	Utilities_NoSeWa	-3.439280e-01
259	MSSubClass_30	-3.079691e-02
260	MSSubClass_40	9.658902e-02
261	MSSubClass_45	-2.657223e-01
262	MSSubClass_50	1.763725e-02
263	MSSubClass_60	-4.863564e-02
264	MSSubClass_70	-8.369859e-03
265	MSSubClass_75	-3.426370e-02
266	MSSubClass_80	-7.726157e-02
267	MSSubClass_85	-4.149958e-02
268	MSSubClass_90	-2.269921e-02
269	MSSubClass_120	-8.155566e-03
270	MSSubClass_150	0.000000e+00
271	MSSubClass_160	-1.305526e-01
272	MSSubClass_180	-4.782924e-02
273	MSSubClass_190	5.588236e-04

	1stFlrSF	2ndFlrSF	Alley	BedroomAbvGr	BldgType	BsmtCond	BsmtExposure	BsmtFinSF1	...	SaleType	Street	TotRmsAbvGrd	TotalBsmtSF	Utilities	WoodDeckSF	YearBuilt	YearRemodAdd	YrSold
0	856	854	NaN	3	1Fam	TA	No	706.0	...	WD	Pave	8	856.0	AllPub	0	2003	2003	2008
1	1262	0	NaN	3	1Fam	TA	Gd	978.0	...	WD	Pave	6	1262.0	AllPub	298	1976	1976	2007
2	920	866	NaN	3	1Fam	TA	Mn	486.0	...	WD	Pave	6	920.0	AllPub	0	2001	2002	2008
3	961	756	NaN	3	1Fam	Gd	No	216.0	...	WD	Pave	7	756.0	AllPub	0	1915	1970	2006
4	1145	1053	NaN	4	1Fam	TA	Av	655.0	...	WD	Pave	9	1145.0	AllPub	192	2000	2000	2008

	1stFlrSF	2ndFlrSF	Alley	BedroomAbvGr	BldgType	BsmtCond	BsmtExposure	BsmtFinSF1	...	SaleType	Street	TotRmsAbvGrd	TotalBsmtSF	Utilities	WoodDeckSF	YearBuilt	YearRemodAdd	YrSold
1454	546	546	NaN	3	Twnhs	TA	No	0.0	...	WD	Pave	5	546.0	AllPub	0	1970	1970	2006
1455	546	546	NaN	3	TwnhsE	TA	No	252.0	...	WD	Pave	6	546.0	AllPub	0	1970	1970	2006
1456	1224	0	NaN	4	1Fam	TA	No	1224.0	...	WD	Pave	7	1224.0	AllPub	474	1960	1996	2006
1457	970	0	NaN	3	1Fam	TA	Av	337.0	...	WD	Pave	6	912.0	AllPub	80	1992	1992	2006
1458	996	1004	NaN	3	1Fam	TA	Av	758.0	...	WD	Pave	9	996.0	AllPub	190	1993	1994	2006

	Null Count
Feature
PoolQC	2909
MiscFeature	2814
Alley	2721
Fence	2348
SalePrice	1459
FireplaceQu	1420
LotFrontage	486
GarageFinish	159
GarageCond	159
GarageQual	159
GarageYrBlt	159
GarageType	157
BsmtCond	82
BsmtExposure	82
BsmtQual	81
BsmtFinType2	80
BsmtFinType1	79
MasVnrType	24
MasVnrArea	23
MSZoning	4
BsmtFullBath	2
BsmtHalfBath	2
Utilities	2
Functional	2
Electrical	1
Exterior2nd	1
KitchenQual	1
Exterior1st	1
GarageCars	1
TotalBsmtSF	1
GarageArea	1
BsmtUnfSF	1
BsmtFinSF2	1
BsmtFinSF1	1
SaleType	1
Condition2	0
FullBath	0
2ndFlrSF	0
3SsnPorch	0
BedroomAbvGr	0

	Alley	BldgType	BsmtCond	BsmtExposure	BsmtFinType1	BsmtFinType2	BsmtQual	CentralAir	Condition1	Condition2	...	MiscFeature	Neighborhood	PavedDrive	PoolQC	RoofMatl	RoofStyle	SaleCondition	SaleType	Street	Utilities
count	198	2919	2837	2837	2840	2839	2838	2919	2919	2919	...	105	2919	2919	10	2919	2919	2919	2918	2919	2917
unique	2	5	4	4	6	6	4	2	9	8	...	4	25	3	3	8	6	6	9	2	2
top	Grvl	1Fam	TA	No	Unf	Unf	TA	Y	Norm	Norm	...	Shed	NAmes	Y	Ex	CompShg	Gable	Normal	WD	Pave	AllPub
freq	120	2425	2606	1904	851	2493	1283	2723	2511	2889	...	95	443	2641	4	2876	2310	2402	2525	2907	2916

	coef	std err	t	P>\|t\|	[0.025	0.975]
const	7.4586	4.860	1.535	0.125	-2.076	16.993
1stFlrSF	6.452e-05	2.97e-05	2.175	0.030	6.33e-06	0.000
2ndFlrSF	5.946e-05	2.51e-05	2.366	0.018	1.01e-05	0.000
3SsnPorch	0.0002	0.000	1.590	0.112	-3.8e-05	0.000
BedroomAbvGr	0.0052	0.006	0.803	0.422	-0.007	0.018
BsmtFinSF1	5.1e-05	1.33e-05	3.841	0.000	2.5e-05	7.7e-05
BsmtFinSF2	4.169e-05	2.74e-05	1.522	0.128	-1.21e-05	9.54e-05
BsmtFullBath	0.0230	0.009	2.528	0.012	0.005	0.041
BsmtHalfBath	0.0039	0.014	0.280	0.780	-0.023	0.031
BsmtUnfSF	-6.318e-06	1.27e-05	-0.497	0.619	-3.12e-05	1.86e-05
EnclosedPorch	0.0001	5.75e-05	2.128	0.034	9.55e-06	0.000
Fireplaces	0.0130	0.012	1.103	0.270	-0.010	0.036
FullBath	0.0239	0.010	2.347	0.019	0.004	0.044
GarageArea	0.0001	3.62e-05	3.609	0.000	5.95e-05	0.000
GarageCars	0.0193	0.010	1.847	0.065	-0.001	0.040
GarageYrBlt	-0.0003	0.000	-1.174	0.241	-0.001	0.000
GrLivArea	0.0002	2.64e-05	6.209	0.000	0.000	0.000
HalfBath	0.0265	0.010	2.745	0.006	0.008	0.045
KitchenAbvGr	-0.0476	0.028	-1.684	0.092	-0.103	0.008
LotArea	2.99e-06	5e-07	5.977	0.000	2.01e-06	3.97e-06
LotFrontage	1.927e-05	0.000	0.182	0.855	-0.000	0.000
LowQualFinSF	3.976e-05	6.43e-05	0.619	0.536	-8.63e-05	0.000
MasVnrArea	1.947e-05	2.66e-05	0.731	0.465	-3.28e-05	7.17e-05
MiscVal	-1.689e-05	2.91e-05	-0.581	0.561	-7.39e-05	4.01e-05
MoSold	-0.0007	0.001	-0.623	0.533	-0.003	0.002
OpenPorchSF	4.124e-05	5.35e-05	0.771	0.441	-6.37e-05	0.000
OverallCond	0.0346	0.004	8.597	0.000	0.027	0.043
OverallQual	0.0383	0.005	8.135	0.000	0.029	0.048
PoolArea	0.0015	0.001	1.418	0.156	-0.001	0.004
ScreenPorch	0.0003	5.73e-05	4.756	0.000	0.000	0.000
TotRmsAbvGrd	0.0031	0.004	0.698	0.486	-0.006	0.012
TotalBsmtSF	8.638e-05	1.87e-05	4.610	0.000	4.96e-05	0.000
WoodDeckSF	9.296e-05	2.73e-05	3.411	0.001	3.95e-05	0.000
YearBuilt	0.0018	0.000	4.754	0.000	0.001	0.003
YearRemodAdd	0.0009	0.000	3.398	0.001	0.000	0.001
YrSold	-0.0026	0.002	-1.085	0.278	-0.007	0.002
Alley_None	-0.0083	0.019	-0.428	0.669	-0.046	0.030
Alley_Pave	0.0238	0.028	0.836	0.403	-0.032	0.080
BldgType_2fmCon	-0.0604	0.125	-0.483	0.629	-0.306	0.185
BldgType_Duplex	-0.0101	0.017	-0.596	0.551	-0.043	0.023
BldgType_Twnhs	-0.0260	0.071	-0.364	0.716	-0.166	0.114
BldgType_TwnhsE	-0.0025	0.068	-0.037	0.970	-0.136	0.131
BsmtCond_Gd	0.0305	0.024	1.257	0.209	-0.017	0.078
BsmtCond_None	0.0491	0.056	0.878	0.380	-0.061	0.159
BsmtCond_Po	0.2671	0.138	1.933	0.053	-0.004	0.538
BsmtCond_TA	0.0306	0.020	1.562	0.119	-0.008	0.069
BsmtExposure_Gd	0.0323	0.014	2.329	0.020	0.005	0.059
BsmtExposure_Mn	-0.0046	0.014	-0.333	0.739	-0.032	0.023
BsmtExposure_No	-0.0106	0.010	-1.060	0.290	-0.030	0.009
BsmtExposure_None	-0.0528	0.105	-0.503	0.615	-0.259	0.153
BsmtFinType1_BLQ	6.401e-05	0.013	0.005	0.996	-0.025	0.025
BsmtFinType1_GLQ	0.0119	0.012	1.025	0.305	-0.011	0.035
BsmtFinType1_LwQ	-0.0285	0.017	-1.654	0.098	-0.062	0.005
BsmtFinType1_None	0.0491	0.056	0.878	0.380	-0.061	0.159
BsmtFinType1_Rec	-0.0048	0.014	-0.347	0.729	-0.032	0.022
BsmtFinType1_Unf	-0.0131	0.013	-0.979	0.328	-0.039	0.013
BsmtFinType2_BLQ	-0.0843	0.035	-2.430	0.015	-0.152	-0.016
BsmtFinType2_GLQ	-0.0176	0.043	-0.409	0.682	-0.102	0.067
BsmtFinType2_LwQ	-0.0439	0.034	-1.293	0.196	-0.111	0.023
BsmtFinType2_None	-0.1437	0.114	-1.258	0.209	-0.368	0.080
BsmtFinType2_Rec	-0.0405	0.033	-1.243	0.214	-0.104	0.023
BsmtFinType2_Unf	-0.0321	0.035	-0.926	0.355	-0.100	0.036
BsmtQual_Fa	-0.0135	0.030	-0.458	0.647	-0.071	0.044
BsmtQual_Gd	-0.0291	0.015	-1.906	0.057	-0.059	0.001
BsmtQual_None	0.0491	0.056	0.878	0.380	-0.061	0.159
BsmtQual_TA	-0.0281	0.019	-1.473	0.141	-0.065	0.009
CentralAir_Y	0.0607	0.018	3.399	0.001	0.026	0.096
Condition1_Feedr	0.0396	0.023	1.720	0.086	-0.006	0.085
Condition1_Norm	0.0895	0.019	4.640	0.000	0.052	0.127
Condition1_PosA	0.0534	0.046	1.172	0.242	-0.036	0.143
Condition1_PosN	0.0975	0.034	2.837	0.005	0.030	0.165
Condition1_RRAe	-0.0360	0.042	-0.864	0.388	-0.118	0.046
Condition1_RRAn	0.0578	0.032	1.814	0.070	-0.005	0.120
Condition1_RRNe	0.0158	0.080	0.197	0.844	-0.141	0.173
Condition1_RRNn	0.0724	0.059	1.227	0.220	-0.043	0.188
Condition2_Feedr	0.2249	0.121	1.853	0.064	-0.013	0.463
Condition2_Norm	0.1684	0.110	1.536	0.125	-0.047	0.384
Condition2_PosA	0.3833	0.179	2.143	0.032	0.032	0.734
Condition2_PosN	-0.6976	0.139	-5.028	0.000	-0.970	-0.425
Condition2_RRAe	-0.6496	0.333	-1.953	0.051	-1.302	0.003
Condition2_RRAn	0.0738	0.156	0.473	0.637	-0.233	0.380
Condition2_RRNn	0.1650	0.138	1.197	0.231	-0.105	0.435
Electrical_FuseF	-0.0210	0.027	-0.789	0.430	-0.073	0.031
Electrical_FuseP	-0.1094	0.086	-1.276	0.202	-0.278	0.059
Electrical_Mix	-0.2564	0.205	-1.252	0.211	-0.658	0.145
Electrical_SBrkr	-0.0238	0.014	-1.720	0.086	-0.051	0.003
ExterCond_Fa	-0.0852	0.083	-1.030	0.303	-0.248	0.077
ExterCond_Gd	-0.0593	0.079	-0.751	0.453	-0.214	0.096
ExterCond_Po	0.0031	0.145	0.021	0.983	-0.282	0.288
ExterCond_TA	-0.0392	0.079	-0.498	0.618	-0.194	0.115
ExterQual_Fa	0.0192	0.056	0.344	0.731	-0.090	0.129
ExterQual_Gd	-0.0020	0.022	-0.093	0.926	-0.045	0.041
ExterQual_TA	0.0012	0.024	0.050	0.960	-0.047	0.049
Exterior1st_AsphShn	-0.0421	0.151	-0.279	0.780	-0.339	0.254
Exterior1st_BrkComm	-0.2792	0.130	-2.150	0.032	-0.534	-0.024
Exterior1st_BrkFace	0.0689	0.059	1.169	0.243	-0.047	0.184
Exterior1st_CBlock	-0.0341	0.063	-0.540	0.589	-0.158	0.090
Exterior1st_CemntBd	-0.1235	0.087	-1.413	0.158	-0.295	0.048
Exterior1st_HdBoard	-0.0288	0.060	-0.480	0.631	-0.146	0.089
Exterior1st_ImStucc	-0.0089	0.129	-0.068	0.945	-0.263	0.245
Exterior1st_MetalSd	0.0241	0.068	0.355	0.723	-0.109	0.157
Exterior1st_Plywood	-0.0196	0.059	-0.332	0.740	-0.135	0.096
Exterior1st_Stone	0.0236	0.112	0.211	0.833	-0.196	0.243
Exterior1st_Stucco	-0.0047	0.065	-0.073	0.942	-0.132	0.123
Exterior1st_VinylSd	-0.0175	0.062	-0.284	0.776	-0.139	0.104
Exterior1st_Wd Sdng	-0.0620	0.057	-1.081	0.280	-0.174	0.051
Exterior1st_WdShing	-0.0112	0.062	-0.181	0.856	-0.132	0.110
Exterior2nd_AsphShn	0.0891	0.102	0.871	0.384	-0.112	0.290
Exterior2nd_Brk Cmn	0.1153	0.095	1.216	0.224	-0.071	0.301
Exterior2nd_BrkFace	-0.0089	0.061	-0.146	0.884	-0.129	0.111
Exterior2nd_CBlock	-0.0341	0.063	-0.540	0.589	-0.158	0.090
Exterior2nd_CmentBd	0.1782	0.086	2.074	0.038	0.010	0.347
Exterior2nd_HdBoard	0.0447	0.058	0.776	0.438	-0.068	0.158
Exterior2nd_ImStucc	0.0550	0.067	0.827	0.408	-0.075	0.186
Exterior2nd_MetalSd	0.0229	0.066	0.347	0.729	-0.107	0.153
Exterior2nd_Other	-0.0633	0.124	-0.510	0.610	-0.307	0.180
Exterior2nd_Plywood	0.0410	0.056	0.734	0.463	-0.069	0.151
Exterior2nd_Stone	-0.0140	0.079	-0.176	0.860	-0.170	0.142
Exterior2nd_Stucco	0.0484	0.063	0.773	0.440	-0.074	0.171
Exterior2nd_VinylSd	0.0563	0.059	0.948	0.343	-0.060	0.173
Exterior2nd_Wd Sdng	0.0859	0.055	1.554	0.121	-0.023	0.194
Exterior2nd_Wd Shng	0.0408	0.058	0.707	0.480	-0.072	0.154
Fence_GdWo	-0.0292	0.023	-1.290	0.197	-0.073	0.015
Fence_MnPrv	0.0016	0.018	0.086	0.931	-0.034	0.038
Fence_MnWw	-0.0068	0.038	-0.181	0.857	-0.081	0.067
Fence_None	0.0116	0.017	0.689	0.491	-0.021	0.045
FireplaceQu_Fa	-0.0075	0.032	-0.237	0.813	-0.069	0.054
FireplaceQu_Gd	0.0166	0.024	0.679	0.497	-0.031	0.065
FireplaceQu_None	-0.0009	0.029	-0.032	0.974	-0.057	0.055
FireplaceQu_Po	0.0293	0.036	0.806	0.420	-0.042	0.101
FireplaceQu_TA	0.0177	0.025	0.696	0.487	-0.032	0.068
Foundation_CBlock	0.0120	0.015	0.813	0.417	-0.017	0.041
Foundation_PConc	0.0312	0.016	1.966	0.050	5.77e-05	0.062
Foundation_Slab	-0.0368	0.046	-0.798	0.425	-0.127	0.054
Foundation_Stone	0.0790	0.053	1.503	0.133	-0.024	0.182
Foundation_Wood	-0.1140	0.068	-1.684	0.092	-0.247	0.019
Functional_Maj2	-0.2645	0.066	-3.996	0.000	-0.394	-0.135
Functional_Min1	0.0143	0.040	0.359	0.720	-0.064	0.092
Functional_Min2	-0.0056	0.040	-0.139	0.889	-0.085	0.074
Functional_Mod	-0.0888	0.049	-1.820	0.069	-0.185	0.007
Functional_Sev	-0.3126	0.136	-2.292	0.022	-0.580	-0.045
Functional_Typ	0.0336	0.035	0.963	0.336	-0.035	0.102
GarageCond_Fa	0.2698	0.160	1.684	0.092	-0.044	0.584
GarageCond_Gd	0.2913	0.167	1.745	0.081	-0.036	0.619
GarageCond_None	-0.1505	0.139	-1.083	0.279	-0.423	0.122
GarageCond_Po	0.3659	0.175	2.096	0.036	0.023	0.708
GarageCond_TA	0.2925	0.159	1.841	0.066	-0.019	0.604
GarageFinish_None	-0.1505	0.139	-1.083	0.279	-0.423	0.122
GarageFinish_RFn	0.0011	0.009	0.120	0.905	-0.017	0.019
GarageFinish_Unf	-0.0103	0.011	-0.919	0.358	-0.032	0.012
GarageQual_Fa	-0.3951	0.139	-2.841	0.005	-0.668	-0.122
GarageQual_Gd	-0.3368	0.143	-2.355	0.019	-0.617	-0.056
GarageQual_None	-0.1505	0.139	-1.083	0.279	-0.423	0.122
GarageQual_Po	-0.3337	0.182	-1.831	0.067	-0.691	0.024
GarageQual_TA	-0.3463	0.138	-2.514	0.012	-0.617	-0.076
GarageType_Attchd	0.1280	0.051	2.534	0.011	0.029	0.227
GarageType_Basment	0.1238	0.059	2.103	0.036	0.008	0.239
GarageType_BuiltIn	0.1186	0.053	2.250	0.025	0.015	0.222
GarageType_CarPort	0.1670	0.068	2.457	0.014	0.034	0.300
GarageType_Detchd	0.1281	0.051	2.536	0.011	0.029	0.227
GarageType_None	-0.1505	0.139	-1.083	0.279	-0.423	0.122
Heating_GasA	0.1364	0.117	1.164	0.245	-0.094	0.366
Heating_GasW	0.1939	0.121	1.606	0.109	-0.043	0.431
Heating_Grav	-0.0503	0.129	-0.389	0.698	-0.304	0.203
Heating_OthW	0.1320	0.145	0.914	0.361	-0.151	0.416
Heating_Wall	0.2089	0.136	1.534	0.125	-0.058	0.476
HeatingQC_Fa	-0.0256	0.022	-1.180	0.238	-0.068	0.017
HeatingQC_Gd	-0.0196	0.009	-2.063	0.039	-0.038	-0.001
HeatingQC_Po	-0.0870	0.122	-0.713	0.476	-0.326	0.152
HeatingQC_TA	-0.0320	0.009	-3.368	0.001	-0.051	-0.013
HouseStyle_1.5Unf	0.2237	0.113	1.972	0.049	0.001	0.446
HouseStyle_1Story	-0.0051	0.041	-0.124	0.901	-0.085	0.075
HouseStyle_2.5Fin	-0.0404	0.082	-0.493	0.622	-0.201	0.120
HouseStyle_2.5Unf	0.0900	0.077	1.173	0.241	-0.061	0.241
HouseStyle_2Story	0.0107	0.037	0.285	0.776	-0.063	0.084
HouseStyle_SFoyer	-0.0130	0.054	-0.240	0.811	-0.120	0.093
HouseStyle_SLvl	0.0468	0.063	0.737	0.461	-0.078	0.171
KitchenQual_Fa	-0.0548	0.029	-1.914	0.056	-0.111	0.001
KitchenQual_Gd	-0.0661	0.016	-4.150	0.000	-0.097	-0.035
KitchenQual_TA	-0.0675	0.018	-3.755	0.000	-0.103	-0.032
LandContour_HLS	0.0287	0.024	1.207	0.228	-0.018	0.075
LandContour_Low	-0.0214	0.030	-0.717	0.473	-0.080	0.037
LandContour_Lvl	0.0248	0.017	1.451	0.147	-0.009	0.058
LandSlope_Mod	0.0317	0.018	1.720	0.086	-0.004	0.068
LandSlope_Sev	-0.1991	0.052	-3.810	0.000	-0.302	-0.097
LotConfig_CulDSac	0.0229	0.015	1.542	0.123	-0.006	0.052
LotConfig_FR2	-0.0397	0.018	-2.166	0.031	-0.076	-0.004
LotConfig_FR3	-0.0913	0.058	-1.584	0.114	-0.204	0.022
LotConfig_Inside	-0.0194	0.008	-2.411	0.016	-0.035	-0.004
LotShape_IR2	0.0235	0.019	1.219	0.223	-0.014	0.061
LotShape_IR3	0.0281	0.040	0.696	0.486	-0.051	0.107
LotShape_Reg	0.0086	0.008	1.150	0.250	-0.006	0.023
MSZoning_FV	0.4789	0.056	8.579	0.000	0.369	0.588
MSZoning_RH	0.4375	0.055	7.926	0.000	0.329	0.546
MSZoning_RL	0.4442	0.048	9.320	0.000	0.351	0.538
MSZoning_RM	0.4021	0.045	8.976	0.000	0.314	0.490
MasVnrType_BrkFace	0.0445	0.031	1.420	0.156	-0.017	0.106
MasVnrType_None	0.0346	0.032	1.095	0.274	-0.027	0.097
MasVnrType_Stone	0.0557	0.033	1.678	0.094	-0.009	0.121
MiscFeature_None	-0.3066	0.461	-0.665	0.506	-1.211	0.598
MiscFeature_Othr	-0.2894	0.422	-0.686	0.493	-1.117	0.538
MiscFeature_Shed	-0.2948	0.441	-0.668	0.504	-1.160	0.571
MiscFeature_TenC	-0.2998	0.455	-0.659	0.510	-1.193	0.593
Neighborhood_Blueste	0.0243	0.091	0.266	0.790	-0.155	0.204
Neighborhood_BrDale	-0.0192	0.054	-0.356	0.722	-0.125	0.086
Neighborhood_BrkSide	0.0066	0.044	0.150	0.881	-0.080	0.093
Neighborhood_ClearCr	0.0286	0.043	0.669	0.503	-0.055	0.112
Neighborhood_CollgCr	-0.0155	0.033	-0.464	0.643	-0.081	0.050
Neighborhood_Crawfor	0.1033	0.040	2.605	0.009	0.026	0.181
Neighborhood_Edwards	-0.0814	0.037	-2.194	0.028	-0.154	-0.009
Neighborhood_Gilbert	-0.0076	0.035	-0.215	0.830	-0.077	0.062
Neighborhood_IDOTRR	-0.0196	0.050	-0.392	0.695	-0.118	0.078
Neighborhood_MeadowV	-0.1449	0.056	-2.567	0.010	-0.256	-0.034
Neighborhood_Mitchel	-0.0543	0.038	-1.442	0.149	-0.128	0.020
Neighborhood_NAmes	-0.0405	0.036	-1.120	0.263	-0.111	0.030
Neighborhood_NPkVill	-9.05e-05	0.064	-0.001	0.999	-0.126	0.126
Neighborhood_NWAmes	-0.0399	0.037	-1.081	0.280	-0.112	0.033
Neighborhood_NoRidge	0.0437	0.039	1.123	0.262	-0.033	0.120
Neighborhood_NridgHt	0.0832	0.034	2.410	0.016	0.015	0.151
Neighborhood_OldTown	-0.0448	0.045	-1.003	0.316	-0.133	0.043
Neighborhood_SWISU	-0.0088	0.045	-0.196	0.845	-0.096	0.079
Neighborhood_Sawyer	-0.0277	0.037	-0.740	0.459	-0.101	0.046
Neighborhood_SawyerW	0.0017	0.036	0.046	0.963	-0.069	0.072
Neighborhood_Somerst	0.0252	0.042	0.608	0.543	-0.056	0.107
Neighborhood_StoneBr	0.1444	0.038	3.776	0.000	0.069	0.219
Neighborhood_Timber	0.0083	0.037	0.222	0.825	-0.065	0.081
Neighborhood_Veenker	0.0490	0.048	1.019	0.308	-0.045	0.143
PavedDrive_P	-0.0118	0.026	-0.460	0.645	-0.062	0.039
PavedDrive_Y	0.0112	0.016	0.705	0.481	-0.020	0.043
PoolQC_Fa	-0.1550	0.188	-0.826	0.409	-0.523	0.213
PoolQC_Gd	0.0164	0.170	0.096	0.923	-0.317	0.349
PoolQC_None	0.7255	0.572	1.269	0.205	-0.396	1.847
RoofMatl_CompShg	2.4966	0.241	10.361	0.000	2.024	2.969
RoofMatl_Membran	2.9315	0.286	10.245	0.000	2.370	3.493
RoofMatl_Metal	2.7836	0.285	9.771	0.000	2.225	3.343
RoofMatl_Roll	2.4899	0.268	9.286	0.000	1.964	3.016
RoofMatl_Tar&Grv	2.5244	0.259	9.755	0.000	2.017	3.032
RoofMatl_WdShake	2.4350	0.252	9.678	0.000	1.941	2.929
RoofMatl_WdShngl	2.5513	0.245	10.417	0.000	2.071	3.032
RoofStyle_Gable	0.0139	0.085	0.164	0.869	-0.152	0.180
RoofStyle_Gambrel	-0.0133	0.093	-0.143	0.886	-0.195	0.169
RoofStyle_Hip	0.0150	0.085	0.176	0.860	-0.152	0.182
RoofStyle_Mansard	0.0661	0.099	0.671	0.503	-0.127	0.259
RoofStyle_Shed	0.5501	0.176	3.127	0.002	0.205	0.895
SaleCondition_AdjLand	0.1137	0.067	1.700	0.089	-0.017	0.245
SaleCondition_Alloca	0.0372	0.042	0.896	0.371	-0.044	0.119
SaleCondition_Family	0.0140	0.028	0.502	0.615	-0.041	0.069
SaleCondition_Normal	0.0599	0.013	4.500	0.000	0.034	0.086
SaleCondition_Partial	0.0095	0.068	0.140	0.889	-0.124	0.143
SaleType_CWD	0.0582	0.059	0.987	0.324	-0.057	0.174
SaleType_Con	0.0991	0.080	1.233	0.218	-0.059	0.257
SaleType_ConLD	0.1384	0.045	3.052	0.002	0.049	0.227
SaleType_ConLI	-0.0335	0.053	-0.633	0.527	-0.137	0.070
SaleType_ConLw	0.0075	0.056	0.135	0.893	-0.102	0.117
SaleType_New	0.0780	0.071	1.101	0.271	-0.061	0.217
SaleType_Oth	0.0469	0.066	0.707	0.480	-0.083	0.177
SaleType_WD	-0.0141	0.019	-0.736	0.462	-0.052	0.024
Street_Pave	0.0973	0.057	1.693	0.091	-0.015	0.210
Utilities_NoSeWa	-0.2753	0.131	-2.109	0.035	-0.531	-0.019
MSSubClass_30	-0.0578	0.022	-2.661	0.008	-0.100	-0.015
MSSubClass_40	-0.0926	0.080	-1.151	0.250	-0.251	0.065
MSSubClass_45	-0.2325	0.115	-2.022	0.043	-0.458	-0.007
MSSubClass_50	0.0065	0.040	0.163	0.871	-0.072	0.085
MSSubClass_60	-0.0384	0.035	-1.086	0.278	-0.108	0.031
MSSubClass_70	0.0112	0.038	0.295	0.768	-0.063	0.086
MSSubClass_75	-0.0544	0.075	-0.729	0.466	-0.201	0.092
MSSubClass_80	-0.0577	0.058	-0.993	0.321	-0.172	0.056
MSSubClass_85	-0.0048	0.049	-0.098	0.922	-0.101	0.091
MSSubClass_90	-0.0101	0.017	-0.596	0.551	-0.043	0.023
MSSubClass_120	-0.0473	0.067	-0.706	0.480	-0.179	0.084
MSSubClass_150	0	0	nan	nan	0	0
MSSubClass_160	-0.1498	0.081	-1.860	0.063	-0.308	0.008
MSSubClass_180	-0.0672	0.090	-0.743	0.457	-0.245	0.110
MSSubClass_190	0.0388	0.128	0.303	0.762	-0.213	0.290

Housing Prices Predictions

Project - Housing Prices¶

Purpose/Goal:¶

Null / Odd Value Hunting¶

Normalizing SalePrice¶

Model Time¶

Make Submission¶