try VS pygwalker

"try" is not a prefix (like watch, nice, etc) uses an overlayfs in order to be able to see and accept or reject changes to your filesystem from a command

https://github.com/binpash/try

For any shell command where a minor mistake has the potential of ruining your day, take a look at “try”, which will allow you to inspect the effects before running it against a live system: https://github.com/binpash/try

he is not running a container, he is mounting an overlay file system for each root directory on the current system, then looking at what has been added as a new layer - that's what the command is supposed to add to the running system.

Pure genius.

See https://github.com/binpash/try/blob/b2df6b650cb2b58951563174...

The most popular data visualization python library in 2023. It turns your dataframe into an interactive data exploration app like tableau/powerBI with one line of code. It provides simple drag-and-drop/chat interface for you to build charts. It can run in juypter notebook, which means you do not need to switch between your code and the visualization app. Besides, you can also build interactive spitial visualization on maps with it. And it also has Javascript and R version.

GWalkR is the R binding of Graphic-Walker, if you want to use it in python, check the python version: PyGWalker: https://github.com/Kanaries/pygwalker

+ Graphic Walker (https://github.com/Kanaries/graphic-walker): A lite embeddable component for visual analysis.

+ PyGWalker (https://github.com/Kanaries/pygwalker): turning your pandas dataframe into a Tableau-style User Interface for visual exploration.

RATH is a collection of interesting ideas that we think the next generation of data analysis software should be, so there might be many features that not well organized to be a united app. Tell me which feature you prefer and which is not. Looking forward for your ideas and advice.