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Dask is a parallel-computation Python library that features scaled pandas DataFrames and allows running distributed Python code that performs fast Python based data processing.

You can easily install Dask on your platform cluster — for example, by using pip or Conda. Dask is pre-deployed in the platform's Jupyter Notebook service.

You can find examples of using Dask in the platform's tutorial Jupyter notebooks. See specifically the dask-cluster tutorial.

For more information about using Dask in the platform, see Ingesting and Preparing Data. For general information about Dask and how to use it, see the Dask documentation.

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