streamlit_agraph is a Streamlit custom component that allows you to create and display interactive, visual graphs within a Streamlit application. Think of it as a tool that bridges the gap between your data and a compelling, interactive network visualization.
Key Features and Use Cases
Instead of just showing a table or a simple chart, streamlit_agraph lets you render a graph with nodes (the entities) and edges (the relationships between them). This is especially useful for a variety of tasks where data connections are important:
Knowledge Graphs: Visualizing the connections between concepts, people, or events. For example, a graph showing authors and the books they've written.
Social Network Analysis: Mapping relationships between users, showing who follows whom or who is friends with whom.
Bioinformatics: Displaying protein interaction networks or gene regulatory pathways.
The component is built on top of a JavaScript library, which gives it rich interactivity. You can drag nodes around, zoom in and out, and even click on nodes to trigger actions in your Python code. It also offers a high degree of customization, allowing you to control the size, color, and labels of your nodes and edges.
This is built on top of vis.js library.
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