Chapter 11: Exploratory Spatial Data Analysis¶

Part II — Geographic Data Science

Learning Objectives¶

By the end of this chapter you will be able to:

• Detect spatial patterns and clusters (Moran's I)
• Distinguish between global and local spatial autocorrelation
• Interpret LISA maps for simulation initialization

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# Standard imports
import numpy as np
import pandas as pd
import geopandas as gpd
import matplotlib.pyplot as plt
import libpysal
import esda

# Standard imports import numpy as np import pandas as pd import geopandas as gpd import matplotlib.pyplot as plt import libpysal import esda

11.1 Global Spatial Autocorrelation¶

TODO: write content.

In [ ]:

# Code for section: Global Spatial Autocorrelation

# Code for section: Global Spatial Autocorrelation

11.2 Local Indicators of Spatial Association (LISA)¶

TODO: write content.

In [ ]:

# Code for section: Local Indicators of Spatial Association (LISA)

# Code for section: Local Indicators of Spatial Association (LISA)

Exercises¶

TODO: write content.

Summary¶

TODO: summarise key takeaways.

Further Reading¶

• TODO: add references.