Reduce number of changes, use mapreduce for T

src/DataFramesMeta.jl

@@ -388,30 +388,33 @@ end
 
 function transform(g::GroupedDataFrame; kwargs...)
     result = DataFrame(g)
+    starts = getproperty(g, :starts)
+    ends = getproperty(g, :ends)
 
-    function spread_scalar(x::Vector, obs_in_group::Int)
+    function spread_scalar(x::AbstractVector, obs_in_group)
         if length(x) == obs_in_group 
             return x 
         else
-            throw(DimensionError("If a function returns a vector, the result " * 
+            throw("If a function returns a vector, the result " * 
                                  "must have the same length as the groups it " *
-                                 "operates on"))
+                                 "operates on")
         end
+        return x
     end
 
-    function spread_scalar(x::CategoricalArrays.CategoricalValue, obs_in_group::Int)
-        vec = CategoricalArray(fill(x, obs_in_group))
-        levels!(vec, CategoricalArrays.index(CategoricalArrays.pool(x)))
-    end
-
-    function spread_scalar(x::Any, obs_in_group::Int)
-        fill(x, obs_in_group)
+    function spread_scalar(x, obs_in_group)
+        return fill(x, obs_in_group)
     end
 
     for (k, v) in kwargs
-        result[k] = reduce(vcat, spread_scalar(v(ig), size(ig, 1)) for ig in g)
+        output_iterator = (spread_scalar(v(ig), size(ig, 1)) for ig in g)
+        T = mapreduce(eltype, promote_type, g)
+        result[k] = Vector{T}(undef, size(result, 1))
+        for (i, output) in enumerate(output_iterator)
+            result[starts[i]:ends[i], k] = output
+        end
     end
-    return result
+    result
 end
 
 function transform_helper(x, args...)