Xarray and Dask documentation explain how to load a large NetCDF dataset into Xarray with Dask backing. But what if I have a very large CSV file (> 1GB)? Is it possible to load that into an Xarray dataset through Dask? Either loading it into Xarray in a way that engages the Dask backend, or loading it as a Dask dataframe and translating that dataframe into an Xarray dataset?
I'd like to use Xarray with this dataset, because it is made up of experimental results, and I would like to index into the experimental results based on different settings of the independent variables (which I would use as dimensions).
Xarray's from_dataframe()
(http://xarray.pydata.org/en/stable/generated/xarray.Dataset.from_dataframe.html?highlight=from_dataframe) only mentions supporting Pandas DataFrames, nothing about dask.
The Dask documentation (https://examples.dask.org/xarray.html) describes only loading from a saved Xarray Dataset.