You can preview and download the dataset from this tab. The dataset is designed to be used in the GeoJSON format. You can also view and download the Codebook, which provides information on the structure, contents, and layout of the dataset.
Learn About Join Counts in Python Using Airbnb Data in Berlin Residential Districts (2018)
By: Levi John Wolf
Published: 2019 | Product: SAGE Research Methods Datasets Part 2
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 boundaries of districts, as well as information about prices for Airbnbs in each district. The dataset file is accompanied by a Teaching Guide, a Student Guide, and a How-to Guide for Python.
Prerequisites:
Understanding Spatial Relationships, Moran’s I
Data Type:
Spatial
Software Guide:
Python
Exploratory data analysis
