I am working with inference results from `Turing.jl`

. My data is uneven so I’m modeling it in the “long” format while in the Turing model, but after the inference is done, I’d like to reshape the data into a more structured shape (filling in missing values with `missing`

as needed). The Python analogue I’m more familiar with, `xarray`

, has an unstack function that you can use in conjunction with a multi-index. Is there an something like this with `InferenceObjects.jl`

/`DimesionalData.jl`

? I saw `DimensionalData.jl`

has mergedims and the inverse of that operation is exactly what I think I need.

Maybe there is also a more obvious solution I’m missing?