ydata-profiling VS visions

6. Ydata-synthetic and Ydata-profiling by YData | Github | tutorial

Send us your North ⭐️: "On the first day of Christmas, my true contributor gave to me..." a star in my GitHub tree! 🎵 If you love these projects too, star ydata-profiling or ydata-synthetic and let your friends know why you love it so much!

My suggestion start with the EDA - there are a lot of packages that automate that for you already. My usual go-to: https://github.com/ydataai/ydata-profiling.

If you're not sure about the behaviour of your data (i.e., if the original data has properties like seasonality), you can use ydata-profiling to profile your data first.

Super cool! For EDA, you could give ydata-profiling a spin sometime and speed up the process!

Hey guys,

We've been recently at the Dask Demo Day and we're hoping to launch a new feature on ydata-profiling, with the support for Dask dataframes!

We're looking for Dask Wizards to start collaborating on this feature, so if you're interested, please join us to define the roadmap of the project and start making it real

Current GitHub branch is here: https://github.com/ydataai/ydata-profiling/tree/feat/dask

Dedicated dask channel here: https://discord.gg/EHDBuSSDuy

We're looking for Dask Wizards 🧙🏻‍♂️ to start collaborating on this branch, so if you're interested, please join us to define the roadmap of the project and start making it real 🚀

This one works pretty well: https://github.com/dylan-profiler/visions

This is really cool! I'm glad there's more work going into the area - visions[1] is a similar tool which embeds the type system (user defined schema) into a traversable graph rather than encoding all type information in the trained network. We originally wrote it as the backend for pandas-profiling[2].

I'm not sure if any of the authors are on here but y'all might look into Sherlock[3] as well. They've got pre-trained models for many other semantic types than you've currently implemented.

1. https://github.com/dylan-profiler/visions