The following are suggested books, papers, websites and other resources relating to Social Network Analysis and Python.
Hanneman, R. A., & Riddle, M. (2005). Introduction to social network methods. http://faculty.ucr.edu/~hanneman/nettext/
Note: Thorough, clear and accessible coverage of the fundamentals of Social Network Analysis, with lots of data and code (Netdraw) examples.
Scott, J. (2017). Social Network Analysis. https://uk.sagepub.com/en-gb/eur/social-network-analysis/book249668
Note: Essential introduction to the topic, in particular the sociological and anthropological origins of Social Network Analysis.
Scott, J., & Carrington, P. J. (2011). The SAGE Handbook of Social Network Analysis. hhttps://uk.sagepub.com/en-gb/eur/the-sage-handbook-of-social-network-analysis/book232753
Note: Covers wide-ranging approaches to and applications of Social Network Analysis.
Brooker, P. (2020). Programming with Python for Social Scientists. London: SAGE Publications Ltd.
Note: One of the best (and few) introductions to computational methods for social science research; mixes theoretical and practical content very well.
Downey, A. (2015). Think Python: How to Think Like a Computer Scientist. Needham, Massachusetts: Green Tea Press. http://greenteapress.com/thinkpython2
Note: A thorough and clear account of the main features of Python.
King's College London (2019). Code Camp. https://github.com/kingsgeocomp/code-camp
Note: A brilliant set of notebooks and lessons for learning the fundamentals of Python.
VanderPlas, J. (2016). Python Data Science Handbook: Essential Tools for Working with Data. https://jakevdp.github.io/PythonDataScienceHandbook/
Note: An in-depth treatment of core data science tasks in Python - calculations, data frames, visualisation and machine learning.