Streamlit (Web Application in Python) - My thoughts on web frameworks in Python and R (PyWebIO vs Streamlit vs R Shiny)

In this video, I will be sharing my thoughts on comparing the following web frameworks in Python and R particularly PyWebIO, Streamlit and R Shiny. These web frameworks allow the development of simple web apps that you can use to deploy your machine learning models or for creating interactive data-drive web apps. 🌟 Download Kite for FREE https://www.kite.com/get-kite/?utm_medium=referral&utm_source=youtube&utm_campaign=dataprofessor&utm_content=description-only ⭕ Timeline 0:00 Introduction 0:40 PyWebIO and Streamlit for Python 0:52 Shiny for R 0:58 Additional web frameworks for Python (Django, Flask, CherryPy) 1:37 Available resources from YouTube on these web framework 4:26 Architecture of the libraries -- PyWebIO: input, output, session and platform -- Streamlit: input and output -- R Shiny: UI and server 8:06 Page layout 9:12 Which libraries have a navigation bar? 10:26 Gallery of example apps 12:09 Examples on using functions 16:48 Choosing the perfect web framework? ⭕ Links for this video: - How to Make a Multi-Page Web App | Streamlit #16 https://youtu.be/nSw96qUbK9o - PyWebIO https://github.com/wang0618/PyWebIO - PyWebIO documentation https://pywebio.readthedocs.io/ - Streamlit https://streamlit.io/ - Streamlit documentation https://docs.streamlit.io/ - R Shiny https://shiny.rstudio.com/ - R Shiny documentation https://docs.rstudio.com/resources/shiny/ Note: 0:28 Thanks to Akshay Arjun Sonawane for suggesting the idea of comparing PyWebIO to Streamlit. 🌟 Subscribe to this YouTube channel https://www.youtube.com/dataprofessor?sub_confirmation=1 🌟 Join the Newsletter of Data Professor http://newsletter.dataprofessor.org 🌟 Buy me a coffee https://www.buymeacoffee.com/dataprofessor ⭕ Playlist: Check out our other videos in the following playlists. ✅ Data Science 101: https://bit.ly/dataprofessor-ds101 ✅ Data Science YouTuber Podcast: https://bit.ly/datascience-youtuber-podcast ✅ Data Science Virtual Internship: https://bit.ly/dataprofessor-internship ✅ Bioinformatics: http://bit.ly/dataprofessor-bioinformatics ✅ Data Science Toolbox: https://bit.ly/dataprofessor-datasciencetoolbox ✅ Streamlit (Web App in Python): https://bit.ly/dataprofessor-streamlit ✅ Shiny (Web App in R): https://bit.ly/dataprofessor-shiny ✅ Google Colab Tips and Tricks: https://bit.ly/dataprofessor-google-colab ✅ Pandas Tips and Tricks: https://bit.ly/dataprofessor-pandas ✅ Python Data Science Project: https://bit.ly/dataprofessor-python-ds ✅ R Data Science Project: https://bit.ly/dataprofessor-r-ds ✅ Weka (No Code Machine Learning): http://bit.ly/dp-weka ⭕ Recommended Books: 🌟https://kit.co/dataprofessor ✅ Hands-On Machine Learning with Scikit-Learn : https://amzn.to/3hTKuTt ✅ Data Science from Scratch : https://amzn.to/3fO0JiZ ✅ Python Data Science Handbook : https://amzn.to/37Tvf8n ✅ R for Data Science : https://amzn.to/2YCPcgW ✅ Artificial Intelligence: The Insights You Need from Harvard Business Review: https://amzn.to/33jTdcv ✅ AI Superpowers: China, Silicon Valley, and the New World Order: https://amzn.to/3nghGrd ⭕ Stock photos, graphics and videos used on this channel: ✅ https://1.envato.market/c/2346717/628379/4662 ⭕ Follow us: ✅ Medium: http://medium.dataprofessor.org/ ✅ FaceBook: http://facebook.com/dataprofessor/ ✅ Website: http://dataprofessor.org/ (Under construction) ✅ Twitter: https://twitter.com/thedataprof/ ✅ Instagram: https://www.instagram.com/data.professor/ ✅ LinkedIn: https://www.linkedin.com/in/chanin-nantasenamat/ ✅ GitHub 1: https://github.com/dataprofessor/ ✅ GitHub 2: https://github.com/chaninlab/ ⭕ Disclaimer: Recommended books and tools are affiliate links that gives me a portion of sales at no cost to you, which will contribute to the improvement of this channel's contents. #pywebio #streamlit #rshiny #python #webapp #dataapp #66daysofdata #datascience #machinelearning #dataprofessor