Pietro Vertechi

The similarity with `@.` (esp. "things inside `$()` are protected from broadcasting") is quite beautiful. It's also consistent with the fact that broadcast works already for tables: ```julia julia> t...

Consider how best to optimize `@apply` for grouped data. Ideally, the macro should keep track of anything that happens during the grouping and only select the columns that are used.

Regarding the distributed table support, we're missing a method for `view(::DTable, i)` and either broadcasting or indexing on `Dagger.DArray` EDIT: all row-wise operation should automatically use `delayedmap` in the distributed...

Related to this, think how to handle "grouped data".

Similarly, see if it's easy to implement `usekey` behavior generally when grouping.

One related thing: I believe the PropertyAccessible interface should also be useful for matlab style struct arrays (see [here](https://github.com/piever/StructArrays.jl) for a julia 1.0 compatible implementation). There seems to be a...

I see, so the idea is that if there is no `x` data, it should be default to a constant variable equal to 1? See #66

Thanks for reporting. The problem may come from StatsBase though (edges and weights seem incorrect): ```julia julia> using StatsBase julia> fit(Histogram, fill(1.5, 5)) Histogram{Int64,1,Tuple{StepRangeLen{Float64,Base.TwicePrecision{Float64},Base.TwicePrecision{Float64}}}} edges: 2.5:2.0:4.5 weights: [0] closed: left...

Here is the issue in StatsBase https://github.com/JuliaStats/StatsBase.jl/issues/456. Things should work here as soon as StatsBase implements a fix for the "mono valued vector" here (we rely on StatsBase for histogram...

Thanks for fixing this! I think it's important to have the weights of the histogram sum to the correct value (before they were `0`). There may be issues due to...