Module 12. Assignment

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For this assignment, I constructed an undirected social network graph utilizing Python, networkx, pandas, and plotnine. The procedure for generating the random graph and transforming the node and edge positions into DataFrames was highly effective. Once all components were configured, Plotnine facilitated the creation of a clear and well-structured visualization.

The primary difficulties I encountered pertained to the visualization and preservation of the graph. Initially, the plot failed to display in a window due to infrastructure issues, and I inadvertently attempted to execute Python code within RStudio, resulting in errors. I addressed this issue by transitioning to Python directly, modifying the graphical backend, and exporting the image as a PNG rather than attempting to display it. Subsequently, the graph was exported effectively without any issues.

Overall, I would employ this method again. It provides extensive control over the network's configuration and facilitates the creation of high-quality, publication-ready visualizations. With my Python environment now completely configured, constructing future network graphs will be considerably more straightforward.

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