1000x faster data manipulation: vectorizing with Pandas and Numpy

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.