Since we announced that #Shiny for #Python is generally available, we have been continuously expanding its features and capabilities.
This post by Winston Chang summarizes the latest additions:
• Introducing data grid/data table, a new, fast-scrolling data table output.
• Better-looking sidebars that span the full height of the application.
Check out the blog post with video clips and images: https://posit.co/blog/shiny-for-python-0-4-0/
Been trying to go through one of my #R #Shiny apps to convert it all to a more proper #golem format - a lot of work! Hoping this change should make the move from ShinyApps to self-hosting a whole lot easier though! 🤞
Hopefully have it in a position to share at some point this week when I get a chance to finish it off!
Right - planning my first #FPL + #R guide. As we’re gonna be starting pre-season prep tomorrow (hopefully!) it’ll all be relevant pre-season data for now.
First things first will be how to download FPL player data into R! Then:
Option A - how to then bring in previous years’ FPL stats and get all that into a spreadsheet (plus make some plots in R)
Option B - how to look at ownership % to see the initial template team across everyone pre-season
Any thoughts?
Got a few initial blog posts I’ve been writing up but thought I’d sound out the interest!
If anyone’s got any sort of #dataanalysis or #r #rprogramming topics/questions they’d like answered, please send them on!
Posit
DataMonkeys_FPL