`table_one` without statistics

[kapple19]

Loving the package!

I'd like the presentation of table_one with scalars.

This is similar to #59, except I note that the functionality requested there is already available with table_one, except it just has to detect that each column has just one sample, which triggers it to not present mean, median and extrema, but just the scalar values in each cell. So it would be easier to implement than #59 (in that issue, a workaround/preparatory transformation is performed on the data).

Usage example:

table_one(
    data::DimensionalData.AbstractDimStack,
    [ # rows
        :A,
        :B,
        :C,
        :D
        :E
    ],
    groupby = [ # columns
        :a
        :b
        :c
    ],
    show_total = false
)

where data[a = Begin, b = Begin, c = Begin].A isa Real, and likewise for B and C.

[jkrumbiegel]

Sorry, missed this one. I don't quite understand, can you elaborate what data[a = Begin, b = Begin, c = Begin].A isa Real means? I'm not familiar with DimensionalData

[kapple19]

That's okay 😊

TL; DR I'll come up with a DataFrames MWE in a bit, I'm on mobile rn.

That access syntax is just accessing an array dimension by a lookup value instead of dimension index.

The Begin index is defined by DimensionalData.jl as a convenience in choosing the first lookup for the specified dimension.

The .A appended implies that it's a DimStack which behaves like an dimension-indexable version of a named tuple.

It supports the Tables.jl interface and as far as I've figured, I think it gets converted to a DataFrame with the dimension values repeated across columns by the same name.

So my data has fields A, B, C, D, E, and dimensions a, b, c, but when converted into a DataFrame implicitly, it just converts all the fields and dimensions into columns.

My request is with regard to the fact that, when the data to display statistics of is scalar, just display the scalar instead of showing statistics as if it were a collection of data per subset. That's what I meant when I isa Real - it's scalar for the listed dimensions.

Hope that makes sense 😅

I'm actually happy to look into this myself if you like?