added prerequisites

preface.qmd

@@ -27,6 +27,18 @@ Another unique feature of the book is that it is part of a wider community.
 *Geocomputation with Python* is a sister project of [Geocomputation with R](https://r.geocompx.org/), a book on geographic data analysis, visualization, and modeling using the R programming language that has 60+ contributors and an active community, not least in the associated [Discord group](https://discord.gg/PMztXYgNxp).
 Links with the vibrant 'R-spatial' community, and other communities such as [GeoRust](https://georust.org/) and [JuliaGeo](https://juliageo.org/), lead to many opportunities for mutual benefit across open source ecosystems.
 
+## Prerequisites
+
+We assume that the reader is: 
+
+* familiar with the Python language, 
+* is capable of running Python code and install Python packages, and 
+* is familiar with the `numpy` and `pandas` packages for working with data in Python. 
+
+From that starting point on, the book introduces the topic of working with *spatial data* in Python, through dedicated third-party packages---most importantly `geopandas` and `rasterio`. 
+
+We also assume familiarity with theoretical concepts of geographic data and GIS, such as coordinate systems, projections, spatial layer file formats, etc., which is necessary for understanding the reasoning of the examples.
+
 ## Code and sample data
 
 To run the code examples, you can [download](https:/geocompx/geocompy/zipball/master) the ZIP file of the GitHub [repository](https:/geocompx/geocompy/). In the ZIP file, the `ipynb` directory contains the source files of the chapters in Jupyter Notebook format, the `data` directory contains the sample data files, and the `output` directory contains the files created in code examples (some of which are also used as inputs in other code sections). Place them together as follows to run the code: