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by ritchie46 1611 days ago
The to numpy conversion is free if you don't have missing data. Which is most of the cases if you send it over to a ML library.

If its not zero copy. It is still not a big deal. Pandas make a lot more copies internally. I truly wouldn't worry about that single copy if you have a order of magnitude speedup overall.
1 comments
mrtranscendence 1611 days ago
I stand corrected. The conversion felt relatively slow to me, but it was a large dataset and there were definitely missing values. Overall the benefits to speed and API cleanliness might be worth it, though it feels a bit gross to convert Spark to pandas to Polars to NumPy to DMatrix.

That said, it’s so much better than pandas for data manip that I’ll probably still try to use it.

Are you the author? If so, thanks for being so responsive on GitHub. You fixed basically every issue I had almost immediately back when I was learning Polars. It was awesome.

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ritchie46 1611 days ago
Yep, Thats me. Glad to help. :) There still room for parallelization when converting to a matrix. I will take a look. Haven't given that conversion any effort yet because that's often a one time conversion at the end of a pipeline.

But I will improve it. ;)

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