1000x faster data manipulation: vectorizing with Pandas and Numpy
Автор: PyGotham 2019
Загружено: 2019-10-23
Просмотров: 61238
Описание:
Speaker: Nathan Cheever
The data transformation code you're writing is correct, but potentially
1000x slower than it needs to be! In this talk, we will go over multiple
ways to enhance a data transformation workflow with Pandas and Numpy by
showing how to replace slower, perhaps more familiar, ways of operating on
Pandas data frames with faster-vectorized solutions to common use cases
like:
if-else logic in applied row-wise functions
dictionary lookups with conditional logic
Date comparisons and calculations
Regex and string column manipulation
and others! ...
without needing a beefier computer, writing Cython, or other libraries
outside the Pandas ecosystem.
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