Data
ames_housing

ames_housing

active ARFF public Visibility: public Uploaded 05-06-2022 by Mine Gazioglu
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Predict sales prices of houses. The Ames Housing dataset was compiled by Dean De Cock for use in data science education.

81 features

Sale_Price (target)numeric1032 unique values
0 missing
MS_SubClassnominal16 unique values
0 missing
MS_Zoningnominal7 unique values
0 missing
Lot_Frontagenumeric129 unique values
0 missing
Lot_Areanumeric1960 unique values
0 missing
Streetnominal2 unique values
0 missing
Alleynominal3 unique values
0 missing
Lot_Shapenominal4 unique values
0 missing
Land_Contournominal4 unique values
0 missing
Utilitiesnominal3 unique values
0 missing
Lot_Confignominal5 unique values
0 missing
Land_Slopenominal3 unique values
0 missing
Neighborhoodnominal28 unique values
0 missing
Condition_1nominal9 unique values
0 missing
Condition_2nominal8 unique values
0 missing
Bldg_Typenominal5 unique values
0 missing
House_Stylenominal8 unique values
0 missing
Overall_Qualnominal10 unique values
0 missing
Overall_Condnominal9 unique values
0 missing
Year_Builtnumeric118 unique values
0 missing
Year_Remod_Addnumeric61 unique values
0 missing
Roof_Stylenominal6 unique values
0 missing
Roof_Matlnominal8 unique values
0 missing
Exterior_1stnominal16 unique values
0 missing
Exterior_2ndnominal17 unique values
0 missing
Mas_Vnr_Typenominal5 unique values
0 missing
Mas_Vnr_Areanumeric445 unique values
0 missing
Exter_Qualnominal4 unique values
0 missing
Exter_Condnominal5 unique values
0 missing
Foundationnominal6 unique values
0 missing
Bsmt_Qualnominal6 unique values
0 missing
Bsmt_Condnominal6 unique values
0 missing
Bsmt_Exposurenominal5 unique values
0 missing
BsmtFin_Type_1nominal7 unique values
0 missing
BsmtFin_SF_1numeric8 unique values
0 missing
BsmtFin_Type_2nominal7 unique values
0 missing
BsmtFin_SF_2numeric274 unique values
0 missing
Bsmt_Unf_SFnumeric1137 unique values
0 missing
Total_Bsmt_SFnumeric1058 unique values
0 missing
Heatingnominal6 unique values
0 missing
Heating_QCnominal5 unique values
0 missing
Central_Airnominal2 unique values
0 missing
Electricalnominal6 unique values
0 missing
First_Flr_SFnumeric1083 unique values
0 missing
Second_Flr_SFnumeric635 unique values
0 missing
Low_Qual_Fin_SFnumeric36 unique values
0 missing
Gr_Liv_Areanumeric1292 unique values
0 missing
Bsmt_Full_Bathnumeric4 unique values
0 missing
Bsmt_Half_Bathnumeric3 unique values
0 missing
Full_Bathnumeric5 unique values
0 missing
Half_Bathnumeric3 unique values
0 missing
Bedroom_AbvGrnumeric8 unique values
0 missing
Kitchen_AbvGrnumeric4 unique values
0 missing
Kitchen_Qualnominal5 unique values
0 missing
TotRms_AbvGrdnumeric14 unique values
0 missing
Functionalnominal8 unique values
0 missing
Fireplacesnumeric5 unique values
0 missing
Fireplace_Qunominal6 unique values
0 missing
Garage_Typenominal7 unique values
0 missing
Garage_Finishnominal4 unique values
0 missing
Garage_Carsnumeric6 unique values
0 missing
Garage_Areanumeric603 unique values
0 missing
Garage_Qualnominal6 unique values
0 missing
Garage_Condnominal6 unique values
0 missing
Paved_Drivenominal3 unique values
0 missing
Wood_Deck_SFnumeric380 unique values
0 missing
Open_Porch_SFnumeric252 unique values
0 missing
Enclosed_Porchnumeric183 unique values
0 missing
Three_season_porchnumeric31 unique values
0 missing
Screen_Porchnumeric121 unique values
0 missing
Pool_Areanumeric14 unique values
0 missing
Pool_QCnominal5 unique values
0 missing
Fencenominal5 unique values
0 missing
Misc_Featurenominal6 unique values
0 missing
Misc_Valnumeric38 unique values
0 missing
Mo_Soldnumeric12 unique values
0 missing
Year_Soldnumeric5 unique values
0 missing
Sale_Typenominal10 unique values
0 missing
Sale_Conditionnominal6 unique values
0 missing
Longitudenumeric2769 unique values
0 missing
Latitudenumeric2747 unique values
0 missing
Show all 81 features

19 properties

NumberOfInstances
2930
Number of instances (rows) of the dataset.
NumberOfFeatures
81
Number of attributes (columns) of the dataset.
NumberOfClasses
0
Number of distinct values of the target attribute (if it is nominal).
NumberOfMissingValues
0
Number of missing values in the dataset.
NumberOfInstancesWithMissingValues
0
Number of instances with at least one value missing.
NumberOfNumericFeatures
35
Number of numeric attributes.
NumberOfSymbolicFeatures
46
Number of nominal attributes.
PercentageOfBinaryFeatures
2.47
Percentage of binary attributes.
PercentageOfInstancesWithMissingValues
0
Percentage of instances having missing values.
AutoCorrelation
-43326.53
Average class difference between consecutive instances.
PercentageOfMissingValues
0
Percentage of missing values.
Dimensionality
0.03
Number of attributes divided by the number of instances.
PercentageOfNumericFeatures
43.21
Percentage of numeric attributes.
MajorityClassPercentage
Percentage of instances belonging to the most frequent class.
PercentageOfSymbolicFeatures
56.79
Percentage of nominal attributes.
MajorityClassSize
Number of instances belonging to the most frequent class.
MinorityClassPercentage
Percentage of instances belonging to the least frequent class.
MinorityClassSize
Number of instances belonging to the least frequent class.
NumberOfBinaryFeatures
2
Number of binary attributes.
Show all 19 properties

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