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Book Cover
Author Wolf, Levi John, author

Title Learn About representing spatial relationships in Python with data about Berlin residential districts (2018) / Levi John Wolf
Published London : SAGE Publications, Ltd., 2019
Online access available from:
Sage Research Methods Datasets    View Resource Record  


Description 1 online resource : illustrations
Summary This dataset contains residential districts in central Berlin, Germany. The dataset contains information about the boundaries of districts as well as information about prices and minimum tenancy lengths for Airbnbs in each district. The example shows how to construct a few different kinds of spatial weights matrices, mathematical objects that represent the spatial relationships between observations used in many other spatial analysis methods, and so will only focus on the information about district boundaries. The dataset file is accompanied by a Teaching Guide, a Student Guide, and a How-to Guide for Python
Notes Description based on XML content
Subject Airbnb (Firm) -- Statistics -- Databases
Airbnb (Firm)
City planning -- Germany -- Berlin -- Statistics
Dwellings -- Germany -- Berlin -- Statistics
Spatial analysis (Statistics)
City planning.
Spatial analysis (Statistics)
Germany -- Berlin.
Genre/Form Databases.
Form Electronic book
ISBN 1526473852