I am currently using streamlit to develop an app which uses Pyvis to render some network graphs. Streamlit supports the use of Pyvis to render the plot, but not Networkx to my knowledge. Networkx graphs can though be transformed in Pyvis Graphs through the pyvis.network.from_nx() function. My problem is that the graphs are a little messy (i have about 100 nodes on the screen with very variable connectivity). Now i know Networkx has some methods to arrange the nodes neatly as in this example:
https://linuxtut.com/en/7c550010f5915ae4acdc/
But I don't know how to do that with Pyvis. I tried to read Pyvis documentation, but didn't find much on the arrangement of the nodes. Does anyone know any Pyvis native solution to arrange large number of nodes neatly?
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I have a pandas dataframe that contains 3 columns , ['source' , 'target', 'weight'].
I have created a networkx graph successfully and plotted it in the browser. The networkx graph was created using the following line of code:
Graph = nx.from_pandas_edgelist(rules,source='source',target='target').
Using the networkx library, it was easy to create the graph using only the above line of code, and setting the nodes labels, arrows that shows the sense from source to destination etc...
I want to do this using plotly dash to have an interactive plot, however, in the examples I have seen in plotly dash networkx, they always have to declare the nodes and edges manually, which will require to have a for loop over the dataframe to pass all the entries of the dataframe. In my case, I have a pretty large dataframe which will be a problem.
My question is that, is there a way that I am missing, to create the graph using dash in a simple way without the need to declare the edges and the nodes manually? a way similar to that line of code?
Graph = nx.from_pandas_edgelist(rules,source='source',target='target').
and if there is a way, can I access the nodes by their ids? and how to insert nodes labels in the graph.
Thank you in advance.
I have tries visdcc and cytoscape libraries using plotly dash. In visdcc I used a loop which took a lot of time to pass through the dataframe entries. And in cytoscape, it needs to create the nodes and edges manually, which I do not want to do, my question is, if there is a way to create the graph automatically using the dataframe as networkx and the draw option do.
Yes, it is possible to use a dataframe to create a network graph with Networkx and then render this network graph in Dash-Cytoscape (you don't have to enter nodes and edges manually). In the question I asked yesterday (here), you can find a code example to achieve this (my question was about something more specific).
I have a medium sized graph with ~400 nodes and ~6000 edges that I am trying to visualize via python. At the moment I am trying to use networkx and this is the output.
There's 2 issues:
The layout seems to be too dense and I can't make out any of the edges near the center of the graph
There's a set of nodes that are semi-bipartite (they have no edges within themselves), and I would like to place these nodes on a vertical line on the right, and all the other nodes on the left. I can't figure out how to manage this with networkx.
Any help would be appreciated, thanks!
I suggest you experiment with different engines other that dot. Consider neato, twopi or circo. The gallery section on the official graphviz site has really nice examples (300+ nodes) that you can mimic.
I have managed to create a graph using pos tagging in pyvis. But unable to find methods to extract in_degree and out_degree similar to networkx.
Converting pyvis graph to networkx seems to be a solution. Is that possible?
The pyvis package is used to visualize graphs. Instead, NetworkX is a package for the creation, manipulation, and study of the structure, dynamics, and functions of graphs. Their goals are completely different. It wouldn't make any sense to have such functions in a tools meant for visualization only.
What you can do is using NetworkX to build the graph (and manipulate it) and then convert it into the pyvis format to visualize it. You can find an example in the official docs here.
I'm trying to visualize a big data set of nodes and edges and I have two files: nodes.txt and edges.txt and I want draw a graph for them. it's got 403,394 nodes and 3,387,388 edges. good to know I generate them randomly.
So I decide using igraph python to draw it by layout and plot but when I try to draw a simple graph with few edges it works but with this huge data set it got an memory error and doesn't work right. I want some help to draw a graph from my edge list with igraph. or maybe there is some better way to do, so suggest it to me.
I use layout with Drl algorithm and use the function plot.
I'm looking for a way to visualize hierarchical data where there is a many to many relationship between parent and child - this is not a tree, but should be hierarchical like a tree. Is there a good package in R for doing this? I've looked at a few but they're either for visualizing trees or for visualizing graphs, but I'd like to visualize a graph that is also hierarchical.
I think you want to visualise a Directed Acyclic Graph (DAG). I.e. there are no cycles but each node may have multiple in-degree and out-degree. Graph libraries will usually visualise these correctly if you set the right parameters. I would recommend networkx for small/medium-sized graphs, or Gephi for large graphs (gephi is a GUI program but makes good visualisations). Networkx's Graphviz drawing backend will do a good job of drawing DAGs
https://networkx.github.io/documentation/latest/reference/algorithms.dag.html
http://gephi.github.io/