Learn about geographically weighted models in Python using Airbnb data in Berlin residential districts (2018) /

This dataset teaches readers how to estimate and interpret a geographically weighted regression in Python. This dataset contains data related to nightly Airbnb prices in Berlin, Germany. The dataset file is accompanied by a Teaching Guide, a Student Guide, and a How-to Guide for Python.

Bibliographic Details
Main Author:	Wolf, Levi John (Author)
Format:	eBook
Language:	English
Published:	London : SAGE Publications, Ltd., 2019.
Subjects:	Airbnb (Firm) > Statistics. Airbnb (Firm) Geography > Mathematical models. Regression analysis. Python (Computer program language) > Handbooks, manuals, etc. Hospitality industry > Germany > Berlin > Statistics. Rental housing > Germany > Berlin > Statistics. Regression Analysis Géographie > Modèles mathématiques. Analyse de régression. Python (Langage de programmation) > Guides, manuels, etc. Accueil (Tourisme) > Allemagne > Berlin > Statistiques. Logement locatif > Allemagne > Berlin > Statistiques. Geography > Mathematical models Hospitality industry Python (Computer program language) Regression analysis Rental housing Germany > Berlin Handbooks and manuals Statistics
Online Access:	Connect to the full text of this electronic book

Description
Summary:	This dataset teaches readers how to estimate and interpret a geographically weighted regression in Python. This dataset contains data related to nightly Airbnb prices in Berlin, Germany. 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:	9781526499578 1526499576