Graphistry aligns with the way that you work, allowing you to bring next-generation visualization and analysis into your native environment. Easily add visual analytics to your existing dashboards to extend your existing tools and workflow. Data scientists can work with Graphistry directly from within their favorite data science notebooks, and developers can leverage the developer API to build a powerful visual front-end to any application. Work the way that you want, and we'll bring the visualization.
Call the PyGraphistry library directly from Jupyter, IBM's i2 and other popular Python data science environments like DataBricks. The Pandas-based API makes it easy to load data from CSVs, Spark, SQL, graph databases, and more. Directly load your own data tables and graphs. If you have custom analytics, you can annotate the data with their output, and explore the result with Graphistry.
The REST API provides language-neutral support, and makes embedding easy with wrappers for languages such as Python and JS. Use it in a variety of ways:
Embed graph views into existing data-driven web applications, dashboards, and wikis.
Create a suite of investigation templates for interacting with various data stores, and share them directly or enrich your current tools with quick launch links.