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I wish Python catches up to Julia in performance. No sense rewriting a trillion lines of code for what is a really pleasant syntax & ecosystem already. But thi
by make3 3y ago
I wish Python catches up to Julia in performance. No sense rewriting a trillion lines of code for what is a really pleasant syntax & ecosystem already.
But this is a language flamewar thing, probably not a constructive comment, sorry.
- wdroz 3y agoYou can just use Polars[0] instead of Pandas and easily beat both Pandas and DataFrames.jl Pure Julia is faster than pure python, but there are non-pure python tools available in the python ecosystem for a ton of things. [0] -- https://www.pola.rs/ https://www.pola.rs/
- affinepplan 3y agoPolars definitely doesn't "easily" beat DF.jl on all tasks. Yes, I agree, on average polars is a bit faster for many of the simple workflows, but I certainly don't think that's unconditionally true. It's especially less true when you might want to do something out of the ordinary with your series --- in Julia it's trivial to just extract that as a vector and loop over it (fast!). In polars, one would have to make sure their function can be appropriately vectorized.