all tests fixed

src/draw.jl

@@ -65,20 +65,20 @@ function Makie.SpecApi.Axis(plot::GGPlot)
             # if there is a specified column transformation, use it
             # otherwise use cat_inseq for string-like columns and as_is for everything else
             if haskey(geom.column_transformations, aes)
-                plottable_data = geom.column_transformations[aes](aes, plot_data)
+                plottable_data = geom.column_transformations[aes](aes, [aes_dict[a]], plot_data)
             elseif eltype(plot_data[!, aes_dict[a]]) <: Union{AbstractString, AbstractChar}
-                plottable_data = cat_inseq(aes, plot_data)
+                plottable_data = cat_inseq(aes, [aes_dict[a]], plot_data)
             else
-                plottable_data = as_is(aes, plot_data)
+                plottable_data = as_is(aes, [aes_dict[a]], plot_data)
             end
 
             # if the transform has a label associated with it, pass that into axis_options
-            if !isnothing(plottable_data.label_target)
-                axis_options[label_target] = plottable_data.label_function(plottable_data.raw)
+            if !isnothing(plottable_data[aes].label_target)
+                axis_options[plottable_data[aes].label_target] = plottable_data[aes].label_function(plottable_data[aes].raw)
             end
 
             # add the transformed data to list to eventually be passed to the plots kwargs
-            push!(visual_optional_aes, aes => plottable_data.makie_function(plottable_data.raw))
+            push!(visual_optional_aes, aes => plottable_data[aes].makie_function(plottable_data[aes].raw))
         end
 
         # which ones were given as arguments? 
@@ -111,18 +111,18 @@ function Makie.SpecApi.Axis(plot::GGPlot)
             # if there is a specified column transformation, use it
             # otherwise use cat_inseq for string-like columns and as_is for everything else
             if haskey(geom.column_transformations, aes)
-                plottable_data = geom.column_transformations[aes](aes_dict[a], plot_data)
+                plottable_data = geom.column_transformations[aes](aes, [aes_dict[a]], plot_data)
             elseif eltype(plot_data[!, aes_dict[a]]) <: Union{AbstractString, AbstractChar}
-                plottable_data = cat_inseq(aes_dict[a], plot_data)
+                plottable_data = cat_inseq(aes, [aes_dict[a]], plot_data)
             else
-                plottable_data = as_is(aes_dict[a], plot_data)
+                plottable_data = as_is(aes, [aes_dict[a]], plot_data)
             end
 
             # if the transform has a label associated with it, pass that into axis_options
-            if !isnothing(plottable_data[aes_dict[a]].label_target)
-                axis_options[plottable_data[aes_dict[a]].label_target] = plottable_data[aes_dict[a]].label_function(plottable_data[aes_dict[a]].raw)
+            if !isnothing(plottable_data[aes].label_target)
+                axis_options[plottable_data[aes].label_target] = plottable_data[aes].label_function(plottable_data[aes].raw)
             end
-            push!(visual_args_list, plottable_data[aes_dict[a]].makie_function(plottable_data[aes_dict[a]].raw))
+            push!(visual_args_list, plottable_data[aes].makie_function(plottable_data[aes].raw))
         end
 
         args = Tuple([geom.visual, visual_args_list...])

src/geoms/geom_text.jl

@@ -1,2 +1,4 @@
-geom_text = geom_template("geom_text", ["x", "y"], :Text)
-geom_label = geom_template("geom_text", ["x", "y"], :Text)
+geom_text = geom_template("geom_text", ["x", "y"], :Text; 
+    column_transformations = Dict{Symbol, Function}(:text => verbatim))
+geom_label = geom_template("geom_label", ["x", "y"], :Text; 
+    column_transformations = Dict{Symbol, Function}(:text => verbatim))

src/transforms.jl

@@ -17,10 +17,10 @@ end
 # simplest one is as_is, which just gets a column 
 # exactly as it is in the DataFrame
 
-function as_is(target::Symbol, data::DataFrame)
+function as_is(target::Symbol, source::Vector{Symbol}, data::DataFrame)
     return Dict{Symbol, PlottableData}(
         target => PlottableData(
-            data[!, target],           # get the column out of the dataframe
+            data[!, source[1]],           # get the column out of the dataframe
             identity,                  # do nothing to it
             nothing,            
             nothing                   
@@ -31,10 +31,10 @@ end
 # verbatim has a similar goal, but for String columns
 
 function convert_to(type::Type)
-    return function(target::Symbol, data::DataFrame)
+    return function(target::Symbol, source::Vector{Symbol}, data::DataFrame)
         return Dict{Symbol, PlottableData}(
             target => PlottableData(
-                type.(data[!, target]),
+                type.(data[!, source[1]]),
                 identity,
                 nothing,
                 nothing
@@ -45,10 +45,10 @@ end
 
 verbatim = convert_to(String)
 
-function number_on_axis(target::Symbol, data::DataFrame)
+function number_on_axis(target::Symbol, source::Vector{Symbol}, data::DataFrame)
     return Dict{Symbol, PlottableData}(
         target => PlottableData(
-            data[!, target],                    # get the column out of the dataframe
+            data[!, source[1]],                    # get the column out of the dataframe
             identity,                           # do nothing to it
             Symbol(String(target) * "ticks"),   # the axis label it will have, e.g. :xticks
             Makie.automatic                     # calculate those ticks automatically
@@ -60,48 +60,53 @@ end
 
 # categorical array handling options for String columns
 
-function cat_inorder(target::Symbol, data::DataFrame)
-    cat_column = data[!, target]
+function cat_inorder(target::Symbol, source::Vector{Symbol}, data::DataFrame)
+    cat_column = data[!, source[1]]
     cat_array = CategoricalArray(cat_column,
         levels = unique(cat_column),
         ordered = true)
+
+    label_target = target == :x ? :xticks :
+                   target == :y ? :yticks : 
+                   nothing
+
     return Dict{Symbol, PlottableData}(
         target => PlottableData(
             cat_array,
             x -> levelcode.(x),
-            Symbol(String(target) * "ticks"),
+            label_target,
             x -> (1:length(levels(x)), levels(x))
         )
     )    
 end
 
-function cat_inseq(target::Symbol, data::DataFrame)
-    cat_array = CategoricalArray(data[!, target])
+function cat_inseq(target::Symbol, source::Vector{Symbol}, data::DataFrame)
+    cat_array = CategoricalArray(data[!, source[1]])
+
+    label_target = target == :x ? :xticks :
+                   target == :y ? :yticks : 
+                   nothing
+
     return Dict{Symbol, PlottableData}(
         target => PlottableData(
             cat_array,
             x -> levelcode.(x),
-            Symbol(String(target) * "ticks"),
+            label_target,
             x -> (1:length(levels(x)), levels(x))
         )
     )      
 end
 
 # kernel density estimation for geom_contour
 
-function kernel_density_2d(x::Symbol, y::Symbol, data::DataFrame)
+function kernel_density_2d(target::Symbol, source::Vector{Symbol}, data::DataFrame)
 
-    k = kde((data[!, x], data[!, y]))
+    k = kde((data[!, source[1]], data[!, source[2]]))
 
     return Dict{Symbol, PlottableData}(
-        :x => PlottableData(k.x, identity, 
-            :xticks,
-            Makie.automatic),
-        :y => PlottableData(k.y, identity, 
-            :yticks,
-            Makie.automatic),
-        :z => PlottableData(k.density, identity, 
-            :zticks,
-            Makie.automatic)
+        target => PlottableData(k.density, 
+            identity, 
+            nothing,
+            nothing)
     )
 end