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Flying Pandas - Dask, Modin and Vaex (live from London) @IanOzsvald – ianozsvald.com Ian Ozsvald Remote Pizza Python 2020

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 Interim Chief Data Scientist  19+ years experience  Team coaching & public courses – Higher Performance! Introductions By [ian]@ianozsvald[.com] Ian Ozsvald 2nd Edition M ay 2020

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 When to use Modin or Dask  A quick peek at Vaex Today’s goal By [ian]@ianozsvald[.com] Ian Ozsvald

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 10 million rows “probably fine” but needs 10s GB RAM  Probably only single core, built for in-RAM computation  Complex 10yr codebase, hard to optimise  Following tools are Pandas-like (each with differences) When does Pandas get smelly? By [ian]@ianozsvald[.com] Ian Ozsvald

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 A new “algebra” for DataFrames, reimplemented functions & Pandas fallback  Young project, drop-in replacement  Uses Ray for parallel computation  Easy to experiment with Modin By [ian]@ianozsvald[.com] Ian Ozsvald

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Modin By [ian]@ianozsvald[.com] Ian Ozsvald

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 ex Modin By [ian]@ianozsvald[.com] Ian Ozsvald https://github.com/modin-project/modin/issues/1390

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 Mature project, Array (NumPy), Bag (list-like)  Distributed dataframe for Pandas – row blocks, not cols Dask Distributed DataFrame By [ian]@ianozsvald[.com] Ian Ozsvald https://dask.readthedocs.io/en/latest/dataframe.html

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Dask – remember to “.compute()” By [ian]@ianozsvald[.com] Ian Ozsvald

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Dask – mature & rich diagnostics By [ian]@ianozsvald[.com] Ian Ozsvald groupby task-graph

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 “Slower” than Pandas but happily works for 100GBs+  Lots of docs & help on StackOverflow  Great for 1 or n machines for bigger-than-RAM tasks  Give Workers lots of RAM (else they die!) Dask Distributed DataFrame By [ian]@ianozsvald[.com] Ian Ozsvald

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 “New” project (not “Pandas”)  Memory mapped, virtual columns & lazy computation  New string dtype (RAM efficient)  See article (single laptop, billions of samples) -> Vaex By [ian]@ianozsvald[.com] Ian Ozsvald https://towardsdatascience.com/ml-impossible-train-a-1-billion-sample-model-in-20- minutes-with-vaex-and-scikit-learn-on-your-9e2968e6f385

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 Dask on Bigger Data, Modin if in RAM. See Budapest talk for smaller dataframes on Monday  See blog for my classes  I’d love a postcard if you learned something new Summary By [ian]@ianozsvald[.com] Ian Ozsvald meetup.com/PyData-Budapest