Resources#
Certainly, it’s impossible for this course to cover every topic, and it would be overly ambitious to think otherwise. The material we explore owes a lot to the wealth of fantastic books, tutorials, and Python programming examples available across the vast expanse of the Internet. Below, you’ll find a curated list of resources for additional learning and inspiration.
Books#
There are no required textbooks for this course. That said, these are textbooks we would recommend if you want to deepen your knowledge further:
Books related to cartography:
Cartography: Visualization of Geospatial Data, By Menno-Jan Kraak, Ferjan Ormeling, Fourth Edition, 2021
GIS Cartography A Guide to Effective Map Design, By Gretchen N. Peterson, Third Edition, 2021
A good book about colors:
The Designer’s Dictionary of Color, By Sean Adams, 2017
Books related to data analysis in Python:
Zelle (2017) Python Programming: An Introduction to Computer Science. Available at the Kumpula Campus library.
McKinney (2017) Python for Data Analysis: Data wrangling with Pandas, NumPy and iPython. Available as an e-book.
Books related to spatial data analysis in Python:
Lawhead (2015) Learning Geospatial Analysis with Python: An effective guide to geographic information systems and remote sensing analysis using Python 3, Second edition. Packt Publishing.
Westra (2016) Python Geospatial Development.
Zandbergen (2013) Python Scripting for ArcGIS. Available at Helsinki University library
Diener (2015) Python Geospatial Analysis Cookbook.
Python tutorials#
Other useful courses#
Geo-python course ## Git and GitHub tutorials
[ ]: