Applied Geospatial Data Science with Python

6

Hypothesis Testing and Spatial Randomness

In Chapter 5, Exploratory Data Visualization, you started to understand the first step of exploratory spatial data analysis (ESDA), which focused on data visualization through the creation of maps derived from the New York City Airbnb dataset. During your work, you noticed that the prices of Airbnb rentals are heavily skewed across New York’s geography, with what appeared to be groups of census tracts with higher and lower values in different parts of the city. For reference, take a look at Figure 6.1, which represents New York City Airbnb prices as a choropleth map. Areas highlighted by the red circle are groupings of higher values, while areas highlighted by the blue circle are groupings of lower ...