Get Dynamic Bitcoin Data in REAL TIME with Python - Intro to Deephaven - LINUX OS!!! скачать в хорошем качестве

Get Dynamic Bitcoin Data in REAL TIME with Python - Intro to Deephaven - LINUX OS!!!

Today we will find a SIMPLE solution to one of the most complex data science problems - working with real-time dynamic live-streaming data! We will learn how to fetch data directly from the Coinbase cryptocurrency exchange, we will then manipulate it, reconstruct it and even plot it! (YES! a graph that keeps MOVING CONSTANTLY as new data comes in and updated within microseconds! 😱😱😱) And the best part is - no need to have any prior experience with web sockets or setting up your own server! 🤩 If you're wondering how it's even possible - allow me to introduce you to Deephaven! A very powerful open-core framework that made this entire process 100% beginner friendly! Find out more on Github: https://github.com/deephaven (Especially if you'd like to contribute to their open-source project 😉) Or alternatively you can checkout their website for more info: https://deephaven.io/ ⏰ TIMESTAMPS ⏰ -------------------------------------- 00:00 - intro 00:55 - install Deephaven and dependencies 04:12 - quickhook vs setting up your own websocket 04:50 - Coinbase data stream overview 05:25 - basic data manipulation (drop columns) 07:04 - split data (filter rows of interest) 08:18 - highlight large volume transactions 11:31 - plot dynamic data 15:31 - extract new data features 23:00 - next steps 24:10 - thanks for watching! :) 🎥 MORE DATA SCIENCE TUTORIALS OF MINE 🎥 --------------------------------------------------------------- ⭐ Pandas Basics:    • Basic Guide to Pandas! Tricks, Shortcuts, ...   ⭐ Line Graph with Pandas:    • Make Graphs with Pandas in Less Than 10 Mi...   ⭐ Plot Graphs with Matplotlib:    • Plotting Google Trends Graphs with Matplot...   🤝 Connect with me 🤝 -------------------------------------- 🔗 Github: https://github.com/mariyasha 🔗 Discord:   / discord   🔗 LinkedIn:   / mariyasha888   🔗 Twitter:   / mariyasha888   🔗 Blog: https://www.pythonsimplified.org 💳 Credits 💳 ---------------------- ⭐ Beautiful animated graphics by: mixkit.co ⭐ Beautiful icons by: flaticon.com