Spreadsheets and comma-separated files (CSV files) or tab-separated files (TSV files)
Lightweight binary points, lines, and polygons
Multi-gigabyte satellite or aerial images
Elevation data such as grids, point clouds, or integer-based images
Databases (both servers and file databases)
Each format contains its own challenges for access and processing. When you perform analysis on data, usually you have to do some form of preprocessing first. You might clip or subset a satellite image of a large area down to just your area of interest, or you might reduce the number of points in a collection to just the ones meeting certain criteria in your data model. A good example of this type of preprocessing is the SimpleGIS example at the end of Chapter 1, Learning Geospatial Analysis with Python. The state dataset included just the state...