https://github.com/ericmjl/nxviz

Visualization Package for NetworkX
https://github.com/ericmjl/nxviz

network network-visualization networkx visualization

Last synced: 7 days ago
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Visualization Package for NetworkX

• Host: GitHub
• URL: https://github.com/ericmjl/nxviz
• Owner: ericmjl
• License: mit
• Created: 2016-07-15T14:55:02.000Z (over 8 years ago)
• Default Branch: master
• Last Pushed: 2024-09-03T21:17:45.000Z (4 months ago)
• Last Synced: 2024-12-12T16:02:34.581Z (14 days ago)
• Topics: network, network-visualization, networkx, visualization
• Language: Python
• Homepage: https://ericmjl.github.io/nxviz
• Size: 3.6 MB
• Stars: 458
• Watchers: 23
• Forks: 88
• Open Issues: 42
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# nxviz: Composable and rational network visualizations in matplotlib

`nxviz` is a package for building _rational_ network visualizations

using matplotlib as a backend.

Inspired heavily by the principles espoused in the grammar of graphics,

nxviz provides ways to _compose_ a graph visualization together

by adhering to the following recipe:

1. Prioritize node placement, mapping data to position and visual properties,

2. Draw in edges, mapping data to visual properties,

3. Add in annotations and highlights on the graph.

`nxviz` is simultaneously a data visualization research project,

art project,

and declarative data visualization tool.

We hope you enjoy using it to build beautiful graph visualizations.

## Installation

### Official Releases

`nxviz` is available on PyPI:

```bash

pip install nxviz

```

It's also available on conda-forge:

```bash

conda install -c conda-forge nxviz

```

### Pre-releases

Pre-releases are done by installing directly from git:

```bash

pip install git+https://github.com/ericmjl/nxviz.git

```

## Quickstart

To make a Circos plot:

```python

# We assume you have a graph G that is a NetworkX graph object.

# In this example, all nodes possess the "group" and "value" node attributes

# where "group" is categorical and "value" is continuous,

# and all edges have the "edge_value" node attribute as well.

import nxviz as nv

ax = nv.circos(

    G,

    group_by="group",

    sort_by="value",

    node_color_by="group",

    edge_alpha_by="edge_value"

)

nv.annotate.circos_group(G, group_by="group")

```

![](images/circos.png)

For more examples, including other plots that can be made,

please see the examples gallery on the docs.