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Complex network analysis using NetworkX - Graph Theory in Python
Submitted by Himanshu Mishra (@orkohunter-himanshu) on Thursday, 1 February 2018
The workshop will be focused on the basic usage of NetworkX in manipulation of Graphs and Networks. After that, we will use NetworkX for visualization and real world network analysis.
NetworkX is a well maintained Python library for the creation, manipulation, and study of graphs and complex networks. NetworkX provides data structures for networks along with graph algorithms, generators, and drawing tools. In particular NetworkX complements Python’s scientific computing suite of SciPy/NumPy, Matplotlib, and Graphviz and can handle graphs in very large memory. NetworkX is recommended to be part of every data scientist’s toolkit.
The core algorithms that are included are implemented on very fast legacy code. Graphs are hugely flexible (nodes can be any hashable type), and there is an extensive set of native IO formats.
Python3, Jupyter Notebook
I (Himanshu Mishra) am a fourth year undergrad student at IIT Kharagpur pursuing Mathematics and Computing. I have worked on NetworkX as a Google Summer of Code 2015 student. I am currently involved as a GSoC mentor under Python Software Foundation (Timelab) where I was a GSoC 2016 student.
I am passionate about Software and Python.