OpenML
NYC-Housing-Data-2003-2019

NYC-Housing-Data-2003-2019

active ARFF Database: Open Database, Contents: Database Contents Visibility: public Uploaded 24-03-2022 by Dustin Carrion
0 likes downloaded by 0 people , 0 total downloads 0 issues 0 downvotes
  • Computer Systems Machine Learning
Issue #Downvotes for this reason By


Loading wiki
Help us complete this description Edit
Context This dataset is created for the prediction of future New York Housing Price based on the past 17 years of record. Content Please check the details under the column description. Acknowledgements New York City Department of Finance Open Source Data. If there is any violation, I am willing to delete the dataset. Inspiration DDL of Schol Project

10 features

BOROUGHnumeric5 unique values
0 missing
NEIGHBORHOODstring516 unique values
0 missing
BUILDING_CLASS_CATEGORYstring145 unique values
0 missing
ADDRESSstring993579 unique values
0 missing
ZIP_CODEnumeric241 unique values
16 missing
LAND_SQUARE_FEETnumeric19163 unique values
17227 missing
GROSS_SQUARE_FEETnumeric22617 unique values
17226 missing
YEAR_BUILTnumeric208 unique values
6027 missing
SALE_PRICEnumeric96347 unique values
0 missing
SALE_DATEstring6207 unique values
0 missing

19 properties

1600202
Number of instances (rows) of the dataset.
10
Number of attributes (columns) of the dataset.
Number of distinct values of the target attribute (if it is nominal).
40496
Number of missing values in the dataset.
22877
Number of instances with at least one value missing.
6
Number of numeric attributes.
0
Number of nominal attributes.
0
Number of attributes divided by the number of instances.
60
Percentage of numeric attributes.
Percentage of instances belonging to the most frequent class.
0
Percentage of nominal attributes.
Number of instances belonging to the most frequent class.
Percentage of instances belonging to the least frequent class.
Number of instances belonging to the least frequent class.
0
Number of binary attributes.
0
Percentage of binary attributes.
1.43
Percentage of instances having missing values.
Average class difference between consecutive instances.
0.25
Percentage of missing values.

0 tasks

Define a new task