diff --git a/src/aesthetics.jl b/src/aesthetics.jl
index 6291888b8..0cefe5c4e 100755
--- a/src/aesthetics.jl
+++ b/src/aesthetics.jl
@@ -1,11 +1,11 @@
 const NumericalOrCategoricalAesthetic =
-    Union{Nothing, Vector, Array, IndirectArray}
+    Union{Nothing, Vector, IndirectArray}
 
 const CategoricalAesthetic =
     Union{Nothing, IndirectArray}
 
 const NumericalAesthetic =
-    Union{Nothing, Matrix, Vector, Array}
+    Union{Nothing, Matrix, Vector}
 
 
 @varset Aesthetics begin
@@ -273,11 +273,7 @@ cat_aes_var!(a, b) = a
 
 function cat_aes_var!(a::AbstractArray{T}, b::AbstractArray{U}) where {T, U}
     V = promote_type(T, U)
-    if isa(a, Array{Union{Missing,T}}) || isa(b, Array{Union{Missing,U}})
-        ab = Array{Union{Missing,V}}(undef, length(a) + length(b))
-    else
-        ab = Array{V}(undef, length(a) + length(b))
-    end
+    ab = Array{V}(undef, length(a) + length(b))
     i = 1
     for x in a
         ab[i] = x
diff --git a/src/mapping.jl b/src/mapping.jl
index c0aa21906..7ded47cca 100644
--- a/src/mapping.jl
+++ b/src/mapping.jl
@@ -10,10 +10,7 @@ end
 
 Base.hash(colgroup::GroupedColumn, h::UInt64) = hash(colgroup.columns, h)
 
-function ==(a::GroupedColumn, b::GroupedColumn)
-    return (a.columns===nothing && b.columns===nothing) ||
-        (a.columns!==nothing && b.columns!==nothing && a.columns == b.columns)
-end
+==(a::GroupedColumn, b::GroupedColumn) = a.columns==b.columns
 
 Base.show(io::IO, gc::GroupedColumn) = print(io, "Column")
 
diff --git a/src/misc.jl b/src/misc.jl
index 70fc7cb36..f9a28aaf9 100644
--- a/src/misc.jl
+++ b/src/misc.jl
@@ -61,17 +61,7 @@ end
 function concrete_length(xs)
     n = 0
     for x in xs
-        if isconcrete(x)
-            n += 1
-        end
-    end
-    n
-end
-
-function concrete_length(xs::Array{Union{Missing,T}}) where T
-    n = 0
-    for i = 1:length(xs)
-        if !ismissing(xs[i]) && isconcrete(xs[i])
+        if !ismissing(x) && isconcrete(x)
             n += 1
         end
     end
@@ -136,24 +126,7 @@ function concrete_minmax(xs, xmin::T, xmax::T) where T<:Real
     end
 
     for x in xs
-        if isconcrete(x)
-            xT = convert(T, x)
-            if isnan(xmin) || xT < xmin
-                xmin = xT
-            end
-            if isnan(xmax) || xT > xmax
-                xmax = xT
-            end
-        end
-    end
-    xmin, xmax
-end
-
-
-function concrete_minmax(xs::Array{Union{Missing,TA}}, xmin::T, xmax::T) where {T<:Real, TA}
-    for i = 1:length(xs)
-        if !ismissing(xs[i])
-            x = xs[i]
+        if !ismissing(x) && isconcrete(x)
             xT = convert(T, x)
             if isnan(xmin) || xT < xmin
                 xmin = xT
@@ -169,24 +142,7 @@ end
 
 function concrete_minmax(xs, xmin::T, xmax::T) where T
     for x in xs
-        if isconcrete(x)
-            xT = convert(T, x)
-            if xT < xmin
-                xmin = xT
-            end
-            if xT > xmax
-                xmax = xT
-            end
-        end
-    end
-    xmin, xmax
-end
-
-
-function concrete_minmax(xs::Array{Union{Missing,TA}}, xmin::T, xmax::T) where {T, TA}
-    for i = 1:length(xs)
-        if !ismissing(xs[i])
-            x = xs[i]
+        if !ismissing(x) && isconcrete(x)
             xT = convert(T, x)
             if xT < xmin
                 xmin = xT
@@ -404,7 +360,7 @@ discretize_make_ia(values::CategoricalArray) =
     discretize_make_ia(values, intersect(push!(levels(values), missing), unique(values)))
 discretize_make_ia(values::CategoricalArray, ::Nothing) = discretize_make_ia(values)
 function discretize_make_ia(values::CategoricalArray{T}, levels::Vector) where {T}
-    mapping = Union{Nothing,Int}[coalesce.(indexin(CategoricalArrays.index(values.pool), levels), 0)...]
+    mapping = something(indexin(CategoricalArrays.index(values.pool), levels), 0)
     pushfirst!(mapping, coalesce(findfirst(ismissing, levels), 0))
     index = [mapping[x+1] for x in values.refs]
     any(iszero, index) && throw(ArgumentError("values not in levels encountered"))
diff --git a/src/statistics.jl b/src/statistics.jl
index c9b01b985..50b108b97 100644
--- a/src/statistics.jl
+++ b/src/statistics.jl
@@ -956,7 +956,7 @@ function apply_statistic_typed(minval::T, maxval::T, vals, size, dsize) where T
     lensize  = length(size)
     lendsize = length(dsize)
     for (i, val) in enumerate(vals)
-        (!Gadfly.isconcrete(val) || !isfinite(val)) && continue
+        (ismissing(val) || !Gadfly.isconcrete(val) || !isfinite(val)) && continue
 
         s = size[mod1(i, lensize)]
         ds = dsize[mod1(i, lendsize)]
@@ -966,21 +966,6 @@ function apply_statistic_typed(minval::T, maxval::T, vals, size, dsize) where T
     minval, maxval
 end
 
-function apply_statistic_typed(minval::T, maxval::T, vals::Array{Union{Missing,T}}, size, dsize) where T
-    lensize  = length(size)
-    lendsize = length(dsize)
-    for i = 1:length(vals)
-        ismissing(vals[i]) && continue
-
-        val = vals[i]
-        s = size[mod1(i, lensize)]
-        ds = dsize[mod1(i, lendsize)]
-
-        minval, maxval = minvalmaxval(minval, maxval, val, s, ds)
-    end
-    minval, maxval
-end
-
 function minvalmaxval(minval::T, maxval::T, val, s, ds) where T
     if val < minval || !isfinite(minval)
         minval = val
@@ -1428,7 +1413,7 @@ function apply_statistic(stat::FunctionStatistic,
     if aes.color != nothing
         func_color = aes.color
         aes.color = Array{eltype(aes.color)}(undef, length(aes.y) * stat.num_samples)
-        groups = Array{Union{Missing,Int}}(undef, length(aes.y) * stat.num_samples)
+        groups = Array{Int}(undef, length(aes.y) * stat.num_samples)
         for i in 1:length(aes.y)
             aes.color[1+(i-1)*stat.num_samples:i*stat.num_samples] .= func_color[i]
             groups[1+(i-1)*stat.num_samples:i*stat.num_samples] .= i