From Data Science at Scale with Python and Dask by Jesse C. Daniel

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If you’re doing data analysis using Pandas, NumPy, or Scikit, you know about THE WALL. At some point, you need to introduce parallelism to your system to handle larger-scale data or analytics tasks. The problem with THE WALL is that it can require you to rewrite your code, redesign your system, or start all over using an unfamiliar technology like Spark or Flink.

Dask is a native parallel analytics tool designed to integrate seamlessly with the libraries you’re already using, including Pandas, NumPy, and Scikit-Learn. With Dask you can crunch and work with huge datasets, just using the tools you already use. And Data Science at Scale with Python and Dask is your guide to using Dask for your data projects without changing the way you work! Find out more in the slide deck below.

slideshare-crunching-data-with-dask