If you believe that graph and network visualization is a kind of art, this post was written for you. If you believe that it isn’t, then you should also keep reading. Since we love using graph-based methods in our work, like generating more labeled data, visualizing language acquisition and shedding light on hidden biases in language, we started a series on graph theory and network science. The first part was devoted to the theoretical background of graphs and how to deal with them using Python, while the second part was about graph databases and analytics engines. Now we turn to graph and network visualization.

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