Dask is a library that's used for distributing computing across multiple threads, processes, or even computers in order to effectively perform computation at a huge scale. This can greatly improve performance and throughput, even if you are working on a single laptop computer. Dask provides replacements for most of the data structures from the Python scientific stack, such as NumPy arrays and Pandas DataFrames. These replacements have very similar interfaces, but under the hood, they are built for distributed computing so that they can be shared between multiple threads, processes, or computers. In many cases, switching to Dask is as simple as changing the import statement, and possibly adding a couple of extra method calls to start concurrent computations.
In this recipe, we will learn how to use Dask to do some simple computations on a DataFrame.
