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Making Pandas Fly (PyDataAmsterdam 2020)

3d644406158b4d440111903db1f62622?s=47 ianozsvald
June 18, 2020

Making Pandas Fly (PyDataAmsterdam 2020)

Another variant of the recent talks, this one focuses on making Pandas faster by digging into NumPy, using my `dtype_diet` memory-saving tool and understanding what's going on with some of Pandas' low level functions. See https://ianozsvald.com/ for more.



June 18, 2020

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    Ozsvald PyDataAmsterdam 2020
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    Team coaching & public courses – Higher Performance! Introductions By [ian]@ianozsvald[.com] Ian Ozsvald 2nd Edition!
  3.  All volunteers – go say thank you in #lobby

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  6. NumPy vs Pandas overhead (ser.sum()) By [ian]@ianozsvald[.com] Ian Ozsvald 25

    files, 83 functions Very few NumPy calls! Thanks!
  7. Overhead... By [ian]@ianozsvald[.com] Ian Ozsvald

  8. Overhead with ser.values.sum() By [ian]@ianozsvald[.com] Ian Ozsvald 18 files, 51

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  9. Is Pandas unnecessarily slow? By [ian]@ianozsvald[.com] Ian Ozsvald Missing? The

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  10. Is Pandas unnecessarily slow – NO! By [ian]@ianozsvald[.com] Ian Ozsvald

    https://github.com/pandas-dev/pandas/issues/34773 - the truth is a bit complicated!
  11.  Install optional (but great!) Pandas dependencies – bottleneck –

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  12.  Mistakes slow us down (PAY ATTENTION!) – Try nullable

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  13.  Make it right then make it fast  Think

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