Building prediction models
When beginning to analyze data spatially, there are a few practices that will make the endeavor run more smoothly. It is always important when bringing together more than one dataset to evaluate the geometry columns. Running the following code will give you a glimpse into the SRID and data type in Figure 4.20:
SELECT Find_SRID('ch4','hisplat_la','geom');
SELECT * FROM geometry_columns 
Figure 4.20 – Reviewing the table catalog in pgAdmin
Understanding how to query datasets with SQL is the first step in introducing prediction models to the database. The execution of these properties will be expanded on as our journey continues.
Exploring the below_poverty_censustract data for Los Angeles County, I want to be able to isolate a tract and explore neighboring tracts. Location and distance might hold clues for exploring marginalized communities or populations living below the poverty line.
