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house_sales

house_sales

active ARFF CC0 Public Domain Visibility: public Uploaded 14-08-2019 by Sharon
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Author: https://www.kaggle.com/harlfoxem/ https://www.kaggle.com/harlfoxem/ Source: [original](https://www.kaggle.com/harlfoxem/housesalesprediction) - 2016-08-25 Please cite: This dataset contains house sale prices for King County, which includes Seattle. It includes homes sold between May 2014 and May 2015. It contains 19 house features plus the price and the id columns, along with 21613 observations. It's a great dataset for evaluating simple regression models. * Id: Unique ID for each home sold * Date: Date of the home sale * Price: Price of each home sold * Bedrooms: Number of bedrooms * Bathrooms: Number of bathrooms, where .5 accounts for a room with a toilet but no shower * Sqft_living: Square footage of the apartments interior living space * Sqft_lot: Square footage of the land space * Floors: Number of floors * Waterfront: A dummy variable for whether the apartment was overlooking the waterfront or not * View: An index from 0 to 4 of how good the view of the property was * Condition: An index from 1 to 5 on the condition of the apartment * Grade: An index from 1 to 13, where 1-3 falls short of the building construction and design, 7 has an average level of construction and design, and 11-13 have a high quality level of construction and design * Sqft_above: The square footage of the interior housing space that is above ground level. * Sqft_basement: The square footage of the interior housing space that is below ground level. * Yr_built: The year the house was initially built * Yr_renovated: The year of the house's last renovation * Zipcode: What zipcode area the house is in * Lat: Lattitude * Long: Longitude * Sqft_living15: The square footage of interior housing living space for the nearest 15 neighbors. * Sqft_lot15: The square footage of the land lots of the nearest 15 neighbors.

20 features

conditionnumeric5 unique values
0 missing
sqft_lot15numeric8689 unique values
0 missing
sqft_living15numeric777 unique values
0 missing
longnumeric752 unique values
0 missing
latnumeric5034 unique values
0 missing
zipcodenumeric70 unique values
0 missing
yr_renovatednumeric70 unique values
0 missing
yr_builtnumeric116 unique values
0 missing
sqft_basementnumeric306 unique values
0 missing
sqft_abovenumeric946 unique values
0 missing
gradenumeric12 unique values
0 missing
id (row identifier)numeric21436 unique values
0 missing
viewnumeric5 unique values
0 missing
waterfrontnumeric2 unique values
0 missing
floorsnumeric6 unique values
0 missing
sqft_lotnumeric9782 unique values
0 missing
sqft_livingnumeric1038 unique values
0 missing
bathroomsnumeric30 unique values
0 missing
bedroomsnumeric13 unique values
0 missing
pricenumeric4028 unique values
0 missing
datestring372 unique values
0 missing
Show all 20 features

62 properties

NumberOfInstances
21613
Number of instances (rows) of the dataset.
NumberOfFeatures
20
Number of attributes (columns) of the dataset.
NumberOfClasses
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
19
Number of numeric attributes.
NumberOfSymbolicFeatures
0
Number of nominal attributes.
Quartile1MutualInformation
First quartile of mutual information between the nominal attributes and the target attribute.
PercentageOfBinaryFeatures
0
Percentage of binary attributes.
PercentageOfInstancesWithMissingValues
0
Percentage of instances having missing values.
PercentageOfMissingValues
0
Percentage of missing values.
PercentageOfNumericFeatures
95
Percentage of numeric attributes.
PercentageOfSymbolicFeatures
0
Percentage of nominal attributes.
Quartile1AttributeEntropy
First quartile of entropy among attributes.
Quartile1KurtosisOfNumericAtts
0.53
First quartile of kurtosis among attributes of the numeric type.
Quartile1MeansOfNumericAtts
2.11
First quartile of means among attributes of the numeric type.
StdvNominalAttDistinctValues
Standard deviation of the number of distinct values among attributes of the nominal type.
Quartile1SkewnessOfNumericAtts
0.62
First quartile of skewness among attributes of the numeric type.
Quartile1StdDevOfNumericAtts
0.65
First quartile of standard deviation of attributes of the numeric type.
Quartile2AttributeEntropy
Second quartile (Median) of entropy among attributes.
Quartile2KurtosisOfNumericAtts
2.72
Second quartile (Median) of kurtosis among attributes of the numeric type.
Quartile2MeansOfNumericAtts
84.4
Second quartile (Median) of means among attributes of the numeric type.
Quartile2MutualInformation
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
Quartile2SkewnessOfNumericAtts
1.45
Second quartile (Median) of skewness among attributes of the numeric type.
Quartile2StdDevOfNumericAtts
29.37
Second quartile (Median) of standard deviation of attributes of the numeric type.
Quartile3AttributeEntropy
Third quartile of entropy among attributes.
Quartile3KurtosisOfNumericAtts
34.59
Third quartile of kurtosis among attributes of the numeric type.
Quartile3MeansOfNumericAtts
2079.9
Third quartile of means among attributes of the numeric type.
Quartile3MutualInformation
Third quartile of mutual information between the nominal attributes and the target attribute.
Quartile3SkewnessOfNumericAtts
4.02
Third quartile of skewness among attributes of the numeric type.
Quartile3StdDevOfNumericAtts
828.09
Third quartile of standard deviation of attributes of the numeric type.
AutoCorrelation
Average class difference between consecutive instances.
MeanMeansOfNumericAtts
35483.52
Mean of means among attributes of the numeric type.
ClassEntropy
Entropy of the target attribute values.
Dimensionality
0
Number of attributes divided by the number of instances.
EquivalentNumberOfAtts
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
MajorityClassPercentage
Percentage of instances belonging to the most frequent class.
MajorityClassSize
Number of instances belonging to the most frequent class.
MaxAttributeEntropy
Maximum entropy among attributes.
MaxKurtosisOfNumericAtts
285.08
Maximum kurtosis among attributes of the numeric type.
MaxMeansOfNumericAtts
540088.14
Maximum of means among attributes of the numeric type.
MaxMutualInformation
Maximum mutual information between the nominal attributes and the target attribute.
MaxNominalAttDistinctValues
The maximum number of distinct values among attributes of the nominal type.
MaxSkewnessOfNumericAtts
13.06
Maximum skewness among attributes of the numeric type.
MaxStdDevOfNumericAtts
367127.2
Maximum standard deviation of attributes of the numeric type.
MeanAttributeEntropy
Average entropy of the attributes.
MeanKurtosisOfNumericAtts
36.37
Mean kurtosis among attributes of the numeric type.
NumberOfBinaryFeatures
0
Number of binary attributes.
MeanMutualInformation
Average mutual information between the nominal attributes and the target attribute.
MeanNoiseToSignalRatio
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
MeanNominalAttDistinctValues
Average number of distinct values among the attributes of the nominal type.
MeanSkewnessOfNumericAtts
2.99
Mean skewness among attributes of the numeric type.
MeanStdDevOfNumericAtts
23116.64
Mean standard deviation of attributes of the numeric type.
MinAttributeEntropy
Minimal entropy among attributes.
MinKurtosisOfNumericAtts
-0.85
Minimum kurtosis among attributes of the numeric type.
MinMeansOfNumericAtts
-122.21
Minimum of means among attributes of the numeric type.
MinMutualInformation
Minimal mutual information between the nominal attributes and the target attribute.
MinNominalAttDistinctValues
The minimal number of distinct values among attributes of the nominal type.
MinSkewnessOfNumericAtts
-0.49
Minimum skewness among attributes of the numeric type.
MinStdDevOfNumericAtts
0.09
Minimum standard deviation of attributes of the numeric type.
MinorityClassPercentage
Percentage of instances belonging to the least frequent class.
MinorityClassSize
Number of instances belonging to the least frequent class.
Show all 62 properties

8 tasks

Clustering on house_sales
0 runs - estimation_procedure: 50 times Clustering
Clustering on house_sales
0 runs - estimation_procedure: 50 times Clustering
Clustering on house_sales
0 runs - estimation_procedure: 50 times Clustering
Clustering on house_sales
0 runs - estimation_procedure: 50 times Clustering
Clustering on house_sales
0 runs - estimation_procedure: 50 times Clustering
Clustering on house_sales
0 runs - estimation_procedure: 50 times Clustering
Clustering on house_sales
0 runs - estimation_procedure: 50 times Clustering
Clustering on house_sales
0 runs - estimation_procedure: 50 times Clustering
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