PyData 2017, held on the Microsoft campus in the summer of 2017 included a tutorial on improving performance with the library dask.
Dask Notebook!
Due to the size of the html generated for this notebook and it crashing on render, it’s best viewed directly via dask_demo.html until I see if I can reduce file from 1.9 MB.
library(htmltools)
# jupyter nbconvert --to html ~/repos/blog/notebooks/dask_demo.ipynb
# includeHTML("../../notebooks/dask_demo.html")Resources
- Notebook - https://github.com/aliciatb/blog/blob/master/notebooks/dask_demo.ipynb
- Data - available on request (1 gb)