Rath VS dtale

Big fan of D3.js and now there is Observable Plot! I am building several data visualization software for exploratory data analysis:

RATH, auto exploratory data analysis: https://github.com/Kanaries/Rath

GraphicWalker, embeddable data exploration component: https://github.com/Kanaries/graphic-walker

They are using vega-lite for now. But there is a limit of building more fancy and customized visualizations. It seems Plot has a more flexible layer based visualization system that can support larger design space.

Is Plot stable enough now to migrate from vega-lite based system to Plot based? Are there any large milestone or roadmap of Plot in future?

By gaining knowledge of the Business Intelligence once the information is captured from all areas in the business, you can set strategies and define what are the strengths and weaknesses of the business.

I am also working on an Awesome Open Source project named: RATH. Check it out on GitHub!

I'm considering https://github.com/Kanaries/Rath, which seems to be an OSS version of Tableau. Has anyone used it for this type of thing?

Ah, there’s a really nice profiler implemented in one of their other projects here (AGPLv3): https://github.com/Kanaries/Rath/tree/master/packages/rath-c...

There’s a lot of really nice features in this other tool, the author’s thought of everything: https://github.com/Kanaries/Rath

Don't forget to check out my GitHub project:https://github.com/Kanaries/Rath We are also having a website for RATH now!

RATH is an Open Source Automated Data Analysis and Visualization tool that can help you uncover insights and patterns in your data quickly and efficiently. Check out RATH Source Code on GitHub and Free RATH Playground.

[D-Tale](https://github.com/man-group/dtale) has recently released version 3.2.0 on pypi & conda-forge: ``` pip install -U dtale conda install dtale -c conda-forge ``` But if you want to take it one step further you can now integrate it with [ArcticDB](https://github.com/man-group/ArcticDB): ``` pip install -U dtale[arcticdb] ``` This allows you the ability to navigate your libraries of datasets saved to your ArcticDB database! But the best part is that all the reads are occuring directly against ArcticDB so some of the memory constraints you may have been hit with before are now a thing of the past. Here's a full write up how to use this functionality along with a quick demo: https://github.com/man-group/dtale/blob/master/docs/arcticdb/ARCTICDB\_INTEGRATION.md Hope this helps & please support open-source by throwing your star on the [repo](https://github.com/man-group/dtale). Thanks! 🙏

I've looked into external tooling, libs such as dtale, which feel overly complicated for my use case (but I'm open to alternatives). What I would like to have instead is something akin to Spyder's variable viewer, which allows sorting by column. VSCode goes a step further and also provides the ability to filter the dataframe.

D-Tale: A Python library that provides an interactive web-based interface for data exploration and analysis.

Try this: https://github.com/man-group/dtale

https://github.com/man-group/dtale

I find that I'm actually a lot faster using basic Pandas methods to get the data I want in exactly the form I want it.

If I really want to show everything, I just use:

'''

Just added "Time Series Analysis" in v1.60.1 of D-Tale on pypi & conda-forge: pip install -U dtale conda install dtale -c conda-forge This feature provides a quick and easy way to visualize the usage of the following time series analysis function in statsmodels:

Your data is stored in memory so the size of your dataframe is limited to the memory of your machine. That being said we’ve allowed users to swap out the machanism which stores the data so you can use something like Redis or Shelve to allieviate memory. Here’s some documentation: https://github.com/man-group/dtale/blob/master/docs/GLOBAL_STATE.md