Resources
Contents
Resources#
In addition to our course, there are countless of excellent books, tutorials and examples related to programming in Python. Here we list some good places to look for further information.
Books#
There are no required textbooks for this course. This course uses a wide range of sources for course information and the main textbooks are given below.
Books related to data analysis in Python:
Zelle, J. (2017) Python Programming: An Introduction to Computer Science, Third edition. Franklin, Beedle & Associates. Copies of this book are available in the Kumpula Campus library.
McKinney, W. (2017) Python for Data Analysis: Data wrangling with Pandas, NumPy and iPython, Second edition. O´Reilly Media, Incorporated. Available as Ebook in here.
Lawhead, J. (2015) Learning Geospatial Analysis with Python: An effective guide to geographic information systems and remote sensing analysis using Python 3, Second edition. Packt Publishing.
Books related to spatial data analysis in Python:
Westra, E. (2016) Python Geospatial Development: Develop sophisticated mapping applications from scratch using Python 3 tools for geospatial development, Third edition. Packt Publishing.
Zandbergen, P. (2013) Python Scripting for ArcGIS, Alternate edition. ESRI press. (Available from the library
Diener, M. (2015) Python Geospatial Analysis Cookbook: Over 60 recipes to work with topology, overlays, indoor routing, and web application analysis with Python. Packt Publishing.