add compatibility to a general table type and remove DataFrames dependency

REQUIRE

@@ -7,3 +7,5 @@ Distributions
 DataFrames
 KernelDensity
 Loess
+IterableTables 0.5.0
+TableTraitsUtils 0.1.0

src/StatPlots.jl

@@ -7,6 +7,10 @@ import Plots: _cycle
 using StatsBase
 using Distributions
 using DataFrames
+import IterableTables
+import DataValues: DataValue
+import TableTraits: column_types, column_names, getiterator, isiterabletable
+import TableTraitsUtils: create_columns_from_iterabletable
 
 import KernelDensity
 import Loess

src/df.jl

@@ -9,18 +9,33 @@ If you want to avoid replacing the symbol, escape it with `^`.
 for strings and symbols respectively.
 """
 macro df(d, x)
-    esc(_df(d,x))
+    syms = Any[]
+    vars = Symbol[]
+    plot_call = _df(d, x, syms, vars)
+    compute_vars = Expr(:(=), Expr(:tuple, vars...), Expr(:call, :(StatPlots.compute_all), d, syms...))
+    esc(Expr(:block, compute_vars, plot_call))
 end
 
-_df(d, x) = x
+_df(d, x, syms, vars) = x
 
-function _df(d, x::Expr)
-    (x.head == :quote) && return :(StatPlots.select_column($d, $x))
+function _df(d, x::Expr, syms, vars)
+    if x.head == :quote
+        new_var = gensym(x.args[1])
+        push!(syms, x)
+        push!(vars, new_var)
+        return new_var
+    end
     if x.head == :call
         x.args[1] == :^ && length(x.args) == 2 && return x.args[2]
-        x.args[1] == :cols && return :(hcat((StatPlots.convert_column($d[i]) for i in $(x.args[2]))...))
+        if x.args[1] == :cols
+            range = eval(x.args[2])
+            new_vars = gensym.(string.(range))
+            append!(syms, range)
+            append!(vars, new_vars)
+            return Expr(:hcat, new_vars...)
+        end
     end
-    return Expr(x.head, _df.(d, x.args)...)
+    return Expr(x.head, (_df(d, arg, syms, vars) for arg in x.args)...)
 end
 
 function _argnames(d, x::Expr)
@@ -33,7 +48,7 @@ not_kw(x::Expr) = !(x.head in [:kw, :parameters])
 _arg2string(d, x) = stringify(x)
 function _arg2string(d, x::Expr)
     if x.head == :call && x.args[1] == :cols
-        return :(reshape([(DataFrames.names($d)[i]) for i in $(x.args[2])], 1, :))
+        return :(reshape([StatPlots.compute_name($d, i) for i in $(x.args[2])], 1, :))
     elseif x.head == :call && x.args[1] == :hcat
         return hcat(stringify.(x.args[2:end])...)
     elseif x.head == :hcat
@@ -45,18 +60,20 @@ end
 
 stringify(x) = filter(t -> t != ':', string(x))
 
-select_column(df, s) = haskey(df, s) ? convert_column(df[s]) : s
-
-convert_column(col) = col
+compute_name(df, i) = column_names(getiterator(df))[i]
 
-function convert_column(col::AbstractDataArray{T}) where T
-    try
-        convert(Array, col)
-    catch
-        error("Missing data of type $T is not supported")
-    end
+function compute_all(df, syms...)
+    isiterabletable(df) || error("Only iterable tables are supported")
+    iter = getiterator(df)
+    name2index = Dict(zip(column_names(iter), 1:length(column_names(iter))))
+    col_index = [isa(s, Integer) ? s : get(name2index, s, 0) for s in syms]
+    cols = convert(Array{Any}, collect(syms))
+    cols[col_index .!= 0] = create_columns_from_iterabletable(df, filter(t -> t != 0, col_index))[1]
+    return Tuple(convert_missing.(t) for t in cols)
 end
 
-convert_column(col::AbstractDataArray{<:AbstractString}) = convert(Array, col, "")
-convert_column(col::AbstractDataArray{Symbol}) = convert(Array, col, Symbol())
-convert_column(col::AbstractDataArray{<:Real}) = convert(Array, convert(DataArray{Float64}, col), NaN)
+convert_missing(el) = el
+convert_missing(el::DataValue{T}) where {T} = get(el, error("Missing data of type $T is not supported"))
+convert_missing(el::DataValue{<:AbstractString}) = get(el, "")
+convert_missing(el::DataValue{Symbol}) = get(el, Symbol())
+convert_missing(el::DataValue{<:Real}) = get(convert(DataValue{Float64}, el), NaN)