Redundant rendering method for DataFrames

[essenciary]

We're rendering Tables and DataFrames are tables - and the rendering methods produce the same output.

I'll remove the DataFrames renderer.

@hhaensel Lmk if I'm missing something please.

[essenciary]

Actually they are not identical on the Julia side - which is a bad thing and a good reason to have just one method.

julia> Stipple.rendertable(DATA)
OrderedDict{Symbol, AbstractVector} with 2 entries:
  :x1 => [4.79784e-6, 0.000333976, 0.000418498, 0.000479837, 0.000492418, 0.00080857, 0.000909854, 0.00118906, 0.00119842, 0.00120826  …  0.…
  :x2 => [0.107271, 0.542181, 0.143818, 0.240444, 0.945631, 0.193178, 0.825941, 0.924873, 0.339736, 0.0126997  …  0.137574, 0.0738368, 0.970…

julia> Stipple.render(DATA)
OrderedDict{String, AbstractVector} with 2 entries:
  "x1" => [4.79784e-6, 0.000333976, 0.000418498, 0.000479837, 0.000492418, 0.00080857, 0.000909854, 0.00118906, 0.00119842, 0.00120826  …  0…
  "x2" => [0.107271, 0.542181, 0.143818, 0.240444, 0.945631, 0.193178, 0.825941, 0.924873, 0.339736, 0.0126997  …  0.137574, 0.0738368, 0.97…

[hhaensel]

You are indeed missing something. rendertable() is a renderer for types that support the Tables API. As Table is not an abstract type you can determine by istable() whether a datatype supports the Tables API. But there are some generic types that should not automatically be rendred as tables. (Actually first they were and we had to close an issue)
So now, if you want to add a table renderer for a special datatype, you can do that by calling rendertable().
For may other table types render() calls rendertable() that's why the results are identical

[essenciary]

@hhaensel Thanks, I did check the code and (that's why) I still don't get it. I'm talking specifically about DataFrames. Why do we need a dedicated DataFrames renderer given that Tables.istable(df::DataFrame) === true?
Also, the results are not identical. One returns a Dict with String keys, other with Symbol keys. Basically the DataFrames renderer specializes the Tables renderer only to produce a Dict with Symbol keys. Why?

[hhaensel]

Sorry, misread on my mobile. hat you were only talking about DataFrames, my bad.

I implemented a separate method for DataFrames because I thought it should be faster than rendering via the Tables API.
Just checked that this is true:

julia> @btime Stipple.rendertable(df)
  933.333 ns (11 allocations: 720 bytes)
OrderedDict{Symbol, AbstractVector} with 2 entries:
  :a => [1, 2, 3]
  :b => ["a", "b", "c"]

julia> @btime Stipple.render(df)
  501.235 ns (10 allocations: 688 bytes)
OrderedDict{String, AbstractVector} with 2 entries:
  "a" => [1, 2, 3]
  "b" => ["a", "b", "c"]

[hhaensel]

@essenciary So I propose we leave everything as is due to speed considerations.