Learn About representing spatial relationships in Python with data about Berlin residential districts (2018) /

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...

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Bibliographic Details
Main Author:	Wolf, Levi John (Author)
Format:	eBook
Language:	English
Published:	London : SAGE Publications, Ltd., 2019.
Subjects:	Airbnb (Firm) > Statistics > Databases. Airbnb (Firm) Dwellings > Germany > Berlin > Statistics. City planning > Germany > Berlin > Statistics. Spatial analysis (Statistics) Habitations > Allemagne > Berlin > Statistiques. Analyse spatiale (Statistique) spatial analysis. City planning. Dwellings. Germany > Berlin. Databases. Statistics.
Online Access:	Connect to the full text of this electronic book

Description
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.
Physical Description:	1 online resource : illustrations
ISBN:	9781526473851 1526473852