Data
Housing-Prices-in-London

Housing-Prices-in-London

active ARFF CC0: Public Domain Visibility: public Uploaded 23-03-2022 by Dustin Carrion
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Content This dataset comprises of various house listings in London and neighbouring region. It also encompasses the parameters listed below, the definitions of which are quite self-explanatory. Property Name Price House Type - Contains one of the following types of houses (House, Flat/Apartment, New Development, Duplex, Penthouse, Studio, Bungalow, Mews) Area in sq ft No. of Bedrooms No. of Bathrooms No. of Receptions Location City/County - Includes London, Essex, Middlesex, Hertfordshire, Kent, and Surrey. Postal Code Inspiration This dataset has various parameters for each house listing which can be used to conduct Exploratory Data Analysis. It can also be used to predict the house prices in various regions of London by means of Regression Analysis or other learning methods.

11 features

Unnamed:_0numeric3480 unique values
0 missing
Property_Namestring2380 unique values
0 missing
Pricenumeric536 unique values
0 missing
House_Typestring8 unique values
0 missing
Area_in_sq_ftnumeric2034 unique values
0 missing
No._of_Bedroomsnumeric11 unique values
0 missing
No._of_Bathroomsnumeric11 unique values
0 missing
No._of_Receptionsnumeric11 unique values
0 missing
Locationstring656 unique values
962 missing
City/Countystring57 unique values
0 missing
Postal_Codestring2845 unique values
0 missing

19 properties

3480
Number of instances (rows) of the dataset.
11
Number of attributes (columns) of the dataset.
Number of distinct values of the target attribute (if it is nominal).
962
Number of missing values in the dataset.
962
Number of instances with at least one value missing.
6
Number of numeric attributes.
0
Number of nominal attributes.
0
Percentage of binary attributes.
27.64
Percentage of instances having missing values.
2.51
Percentage of missing values.
Average class difference between consecutive instances.
54.55
Percentage of numeric attributes.
0
Number of attributes divided by the number of instances.
0
Percentage of nominal attributes.
Percentage of instances belonging to the most frequent class.
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.

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