Xarray and PythonCall.jl

In the Python ecosystem Xarray is by far the most popular package for working with multidimensional labelled arrays. The main data structures it provides are:

• DataArray, analagous to DimArray.

• Dataset, analagous to DimStack.

DimensionalData integrates with PythonCall.jl to allow converting these Xarray types to their DimensionalData equivalent:

import PythonCall: pyconvert

my_dimarray = pyconvert(DimArray, my_dataarray)

my_dimstack = pyconvert(DimStack, my_dataset)

Note that:

• The current implementation will make a copy of the underlying arrays.

• Python stores arrays in row-major order whereas Julia stores them in column-major order, hence the dimensions on a converted DimArray will be in reverse order from the original DataArray. This is done to ensure that the 'fast axis' to iterate over is the same dimension in both Julia and Python.