![]() I specified the edges between the CEO and two team leads, and team leads and their corresponding staff. ![]() Next, by going through a for loop, I created eight nodes for each name and added the corresponding position of the individual in the organisation as labels. I created a list of eight names starting from A to H, and the list of all the positions held in the company. To create a plain organogram using graphviz package, I start with initializing a graph object say f as graphviz.Digraph(filename), where filename is the name of the output file created. I am going to depict this by reconstructing the organogram created using NetworkX in the previous post, but using graphviz in this post. In this post, I am going to share how the graphviz package not only overcomes those limitations, but also offers much more flexibility options for graph visualisation. In my previous post, I pointed out the different limitations of graph visualisation with the NetworkX package, such as limited options for node shapes, limitation for getting unique shape and bounding box (bbox) attributes for individual nodes, etc. But in graphviz, a node can only be defined as a string. For example, in the NetworkX package, the node can be defined as any hashable object (except None). However, there are some key differences as well. This package allows to create both undirected and directed graphs using the DOT language.Ĭonstructing the Graph or DiGraph object using graphviz is similar to that using NetworkX in the sense that one needs to simply define the nodes and edges of the graph object and assign the attributes accordingly. The graphviz package, which works under Python 3.7+ in Python, provides a pure-Python interface to this software. ![]() Graphviz is an open-source graph visualisation software.
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