Best Way to Build Network Analysis App in Python with Streamlit and st-link-analysis - Easy Tutorial

☕ Buy me a Coffee: https://www.buymeacoffee.com/wjbmattingly Introducing st-link-analysis: A Game-Changer for Streamlit Now that we understand the importance of network analysis, let's explore an exciting new tool that's making it easier than ever to build network analysis applications in Streamlit: st-link-analysis. This Streamlit component allows developers to create high-quality, interactive network visualizations with just a few lines of code. Here's why it's generating so much excitement: Easy Installation: Simply install using pip Customizable Visuals: Easily style nodes and edges with different colors, icons, and labels Interactive Features: Users can zoom, pan, and interact with the network graph in real-time Streamlit Integration: Seamlessly integrates with other Streamlit components for a cohesive app experience Performance: Handles moderately sized networks (up to about 300 nodes) smoothly Video Repo: https://github.com/wjbmattingly/youtube-streamlit-link-analysis st-link-analysis repo: https://github.com/AlrasheedA/st-link-analysis?tab=readme-ov-file Join this channel to get access to perks: https://www.youtube.com/channel/UC5vr5PwcXiKX_-6NTteAlXw/join If you enjoy this video, please subscribe. ✅Be my Patron: https://www.patreon.com/WJBMattingly ✅PayPal: https://www.paypal.com/cgi-bin/webscr?cmd=_donations&business=AZ73QW52SUX8N&currency_code=USD&source=url If there's a specific video you would like to see or a tutorial series, let me know in the comments and I will try and make it. If you liked this video, check out www.PythonHumanities.com, where I have Coding Exercises, Lessons, on-site Python shells where you can experiment with code, and a text version of the material discussed here. You can follow me at: https://twitter.com/wjb_mattingly