Worked on the neo4j/graph-data-science-client repository to deliver comprehensive documentation for graph visualization, focusing on the integration of the neo4j-viz library with Python environments such as notebooks and Streamlit. The contribution included creating a dedicated documentation page, adding a new navigation link, and explicitly referencing neo4j-viz to clarify its role alongside Graph Data Science examples. Using adoc for documentation, the work emphasized improving onboarding and developer experience by illustrating end-to-end workflows for graph analytics. No bugs were addressed during this period, with all efforts directed toward enhancing documentation quality and accelerating adoption of visualization tooling within the project.