41–50 of 62 posts
bamboolib is a GUI for transforming and visualising pandas DataFrame objects with no to little code. Feedback is appreciated!
I think you should be much more up front that this is a commercial product, because very few things based on Jupyter and Pandas are.
This looks excellent. The ability to generate the Python code for the pandas dataframe transformations looks to be more useful than OpenRefine, TBH. How much work would it be to use Dask (and Dask-ML) as a backend? I see the OneHotEncoder button. Have you considered integration with Yellowbrick? They've probably already implemented a few of your near-future and someday roadmap items involving hyperparameter selection…
I guess that makes it easy to get started with pandas (and learn about the pandas api). I wonder how some advanced transforms such as join/union/pivot will look like?
As a non-data-scientist who does some infrequent data analysis in python, this looks amazing. But not something I think we can justify paying for with the amount of analysis I do. If this doesn't work out commercially, would you consider open-sourcing it? I am curious how many data scientists don't already have pipelines that do similar functions?
You can sign up for https://cloud.trifacta.com/ our SaaS offering for your data analysis.
This looks excellent. The ability to generate the Python code for the pandas dataframe transformations looks to be more useful than OpenRefine, TBH. How much work would it be to use Dask (and Dask-ML) as a backend? I see the OneHotEncoder button. Have you considered integration with Yellowbrick? They've probably already implemented a few of your near-future and someday roadmap items involving hyperparameter selection…
The UI is heavily inspired by the one from Trifacta/Cloud Dataprep. (i.e. histograms when selecting columns, brushing to start a transformation...) I guess that makes it easy to get started with pandas (and learn about the pandas api). I wonder how some advanced transforms such as join/union/pivot will look like?
For join in action, you can watch this video: https://www.youtube.com/watch?v=r59Q19oCMr8&t=3s
We also support pivot and melt. About union: what do you have in mind here?
This looks excellent. The ability to generate the Python code for the pandas dataframe transformations looks to be more useful than OpenRefine, TBH. How much work would it be to use Dask (and Dask-ML) as a backend? I see the OneHotEncoder button. Have you considered integration with Yellowbrick? They've probably already implemented a few of your near-future and someday roadmap items involving hyperparameter selection…
We are currently thinking about providing other dataframe libraries like dask or pyspark and similar. However, we are a little bit unsure on how to make sure that there is user demand before we implement it. It is not a complete rewrite but it would require some additional abstractions at some points in the library. And we need to check if some features might not be available any more. Would dask support be a reason to buy for you?
Great hint with yellowbrick and yes, we are considering some of those features as well if there is a useful place in the library.
In general, we are also thinking about ways how you can extend the library for yourself so that you can add your own analyses/charts of choice and then they will come up again the right point in time. In case that this is useful.
This looks excellent. The ability to generate the Python code for the pandas dataframe transformations looks to be more useful than OpenRefine, TBH. How much work would it be to use Dask (and Dask-ML) as a backend? I see the OneHotEncoder button. Have you considered integration with Yellowbrick? They've probably already implemented a few of your near-future and someday roadmap items involving hyperparameter selection…
Dask has only a subset of Pandas available.
As a non-data-scientist who does some infrequent data analysis in python, this looks amazing. But not something I think we can justify paying for with the amount of analysis I do. If this doesn't work out commercially, would you consider open-sourcing it? I am curious how many data scientists don't already have pipelines that do similar functions?
About open-sourcing: I cannot tell right now what the situation will be in the future. But I can tell you that we believe in Open-Source and technologies which dont provide a vendor lockin. This is also why we export the pandas code. So, you are always flexible with your code and you own the result of your work.
Basically, we want to strengthen people to use Open-Source software at the core but we also want to make it as user-friendly as fully proprietary solutions like Trifacta. So, you will have the best of both worlds without the vendor lockin.
We talked to many Data Scientists and some already started creating similar packages etc but they never got far because it takes a long and consistent effort to catch most of the cases. Also, it quickly becomes a software engineering challenge.
Earlier quoted context omitted.
Thank you for linking the old post because the last time some people doubted that we would actually create this :)
To be fair, last time you posted a Show HN with nothing to show.
Earlier quoted context omitted.
Thank you for your feedback! :) We also dont like software where you are restricted to whats available. Therefore, we integrated so tightly with pandas, so whenever something is not available you can add the code in the user interface or just in another cell. What do you think about this hybrid approach?
> What do you think about this hybrid approach? What I want is to be able to add new functionality to the bamboo UI via new buttons for specific functionality that you don't have. Maybe if you had a plugin architecture.
I'm sad that it's not open source, because I want to add functionality and now I can't.