Learn about join counts in Python using Airbnb data in Berlin residential districts (2018) /

This dataset teaches readers how to estimate and interpret Join Count statistics and use this information to identify whether there is clustering or dispersion in a categorical feature. This dataset contains data related to residential districts in central Berlin, Germany, and information about the...

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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. Airbnb (Firm) Spatial analysis (Statistics) Geography > Statistical methods. Autocorrelation (Statistics) Python (Computer program language) > Handbooks, manuals, etc. Hospitality industry > Germany > Berlin > Statistics. Rental housing > Germany > Berlin > Statistics. Analyse spatiale (Statistique) Géographie > Méthodes statistiques. Autocorrélation (Statistique) Python (Langage de programmation) > Guides, manuels, etc. Accueil (Tourisme) > Allemagne > Berlin > Statistiques. Logement locatif > Allemagne > Berlin > Statistiques. spatial analysis. Geography > Statistical methods Hospitality industry Python (Computer program language) Rental housing Germany > Berlin Handbooks and manuals Statistics
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Call Number	Status	Get It
Call Number:		QA278.2 .W65 2019

QA278.2 .W65 2019	Available