Housing Data Set

  • Last Update:January,15,2016 Created:January,15,2016
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Title of the dataset Housing Data Set
Provenance of the dataset Housing values in suburbs of Boston in 1970s
How were the data collected/created? What was the cost? It is downloaded from UCI Machine Learning Repository official website: https://archive.ics.uci.edu/ml/datasets/Housing https://archive.ics.uci.edu/ml/machine-learning-databases/housing/ It is said that this dataset was taken from the StatLib library which is maintained at Carnegie Mellon University.
Data sharing policy Other
Data sharing policy

About data analysis and simulation

Type of data: Check all that apply. Use "Other" to specify other types so that we can include them in further updates. text number table
Variable labels of dataset (the names of the variables) RAD INDEX OF ACCESSIBILITY TO RADIAL HIGHWAYS|MEDV MEDIAN VALUE OF OWNER-OCCUPIED HOMES IN $1000 S|RM AVERAGE NUMBER OF ROOMS PER DWELLING|AGE PROPORTION OF OWNER-OCCUPIED UNITS BUILT PRIOR TO 1940|ZN PROPORTION OF RESIDENTIAL LAND ZONED FOR LOTS OVER 25 000 SQ FT |CHAS CHARLES RIVER DUMMY VARIABLE (= 1 IF TRACT BOUNDS RIVER; 0 OTHERWISE)|NOX NITRIC OXIDES CONCENTRATION (PARTS PER 10 MILLION)|PTRATIO PUPIL-TEACHER RATIO BY TOWN|LSTAT % LOWER STATUS OF THE POPULATION|CRIM PER CAPITA CRIME RATE BY TOWN|DIS WEIGHTED DISTANCES TO FIVE BOSTON EMPLOYMENT CENTRES|B 1000(BK - 0 63)^2 WHERE BK IS THE PROPORTION OF BLACKS BY TOWN|INDUS PROPORTION OF NON-RETAIL BUSINESS ACRES PER TOWN|TAX FULL-VALUE PROPERTY-TAX RATE PER $10 000
Outline of data This data includes the housing values in suburbs of Boston in 1970s. It includes not only 13 explanatory variables related to the characteristics of the house, but also 1 target variable which is the median value of owner-occupied homes in $1000's
Simulation process Regression Analysis
Expected outcome of the process (obtained knowledge, analysis results, output of tools) To predict value of homes according to expected description
Anticipation for analyses/simulations other than the typical ones provided above Find relationship between value of homes and those descriptions

Other

Comments This data is a very classic and valuable
What kind of data/tools do you wish to have? python with Numpy and Scipy.
Visualized information
Sample data

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