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I wasn't able to find a clear description in the documentation of how to use the dims kwarg for the imputation methods. I think I was able to figure it out from context in the examples, but it would be good to have an unambiguous statement saying something like "If your dataset is in standard Table/DataFrame format (observations in rows, series in columns), use dims = X. If it is transposed, with observations in columns, use dims = Y."
The text was updated successfully, but these errors were encountered:
The dims kwarg has gone through a few iterations, given the inconsistent conventions within the ecosystems we're trying to interact with. That's why we started using NamedDims.jl to label them. Glad the examples helped clarify it. If you think there's a clearer way to summarize it feel free to update the docstring https://github.com/invenia/Impute.jl/blob/master/src/imputors.jl#L94.
I wasn't able to find a clear description in the documentation of how to use the
dims
kwarg for the imputation methods. I think I was able to figure it out from context in the examples, but it would be good to have an unambiguous statement saying something like "If your dataset is in standard Table/DataFrame format (observations in rows, series in columns), usedims = X
. If it is transposed, with observations in columns, usedims = Y
."The text was updated successfully, but these errors were encountered: