diff --git a/ext/DimensionalDataMakie.jl b/ext/DimensionalDataMakie.jl
index ffab42dc1..d5cc8537e 100644
--- a/ext/DimensionalDataMakie.jl
+++ b/ext/DimensionalDataMakie.jl
@@ -1,6 +1,8 @@
 module DimensionalDataMakie
 
-using DimensionalData, Makie
+using DimensionalData
+using Makie
+using IntervalSets
 using DimensionalData.Dimensions, DimensionalData.LookupArrays
 
 const DD = DimensionalData
@@ -345,18 +347,18 @@ function _boxplotlike(A, attributes, labeldim)
 end
 
 # Plot type definitions. Not sure they will ever get called?
-Makie.plottype(A::AbstractDimVector) = Makie.Scatter
-Makie.plottype(A::AbstractDimMatrix) = Makie.Heatmap
-Makie.plottype(A::AbstractDimArray{<:Any,3}) = Makie.Volume
+Makie.plottype(::AbstractDimVector) = Makie.Scatter
+Makie.plottype(::AbstractDimMatrix) = Makie.Heatmap
+Makie.plottype(::AbstractDimArray{<:Any,3}) = Makie.Volume
 
 # Conversions
 function Makie.convert_arguments(t::Type{<:Makie.AbstractPlot}, A::AbstractDimMatrix)
     A1 = _prepare_for_makie(A)
-    xs, ys = map(parent, lookup(A1))
+    xs, ys = map(_lookup_to_vector, lookup(A1))
     return xs, ys, last(Makie.convert_arguments(t, parent(A1)))
 end
 function Makie.convert_arguments(t::Makie.PointBased, A::AbstractDimVector)
-    A = _prepare_for_makie(A)
+    A1 = _prepare_for_makie(A)
     xs = parent(lookup(A, 1))
     return Makie.convert_arguments(t, xs, _floatornan(parent(A)))
 end
@@ -365,24 +367,30 @@ function Makie.convert_arguments(t::Makie.PointBased, A::AbstractDimMatrix)
 end
 function Makie.convert_arguments(t::SurfaceLikeCompat, A::AbstractDimMatrix)
     A1 = _prepare_for_makie(A)
-    xs, ys = map(parent, lookup(A1))
+    xs, ys = map(_lookup_to_vector, lookup(A1))
     # the following will not work for irregular spacings, we'll need to add a check for this.
-    return first(xs)..last(xs), first(ys)..last(ys), last(Makie.convert_arguments(t, parent(A1)))
+    return xs, ys, last(Makie.convert_arguments(t, parent(A1)))
+end
+function Makie.convert_arguments(t::Makie.ImageLike, A::AbstractDimMatrix)
+    A1 = _prepare_for_makie(A)
+    xs, ys = map(_lookup_to_intervals, lookup(A))
+    # the following will not work for irregular spacings, we'll need to add a check for this.
+    return xs, ys, last(Makie.convert_arguments(t, parent(A1)))
 end
 function Makie.convert_arguments(
     t::Makie.CellGrid, A::AbstractDimMatrix
 )
     A1 = _prepare_for_makie(A)
-    xs, ys = map(parent, lookup(A1))
+    xs, ys = map(_lookup_to_axis, lookup(A1))
     return xs, ys, last(Makie.convert_arguments(t, parent(A1)))
 end
 function Makie.convert_arguments(t::Makie.VolumeLike, A::AbstractDimArray{<:Any,3}) 
     A1 = _prepare_for_makie(A)
-    xs, ys, zs = map(parent, lookup(A1))
+    xs, ys, zs = map(_lookup_to_vector, lookup(A1))
     # the following will not work for irregular spacings
-    return first(xs)..last(xs), first(ys)..last(ys), first(zs)..last(zs), last(Makie.convert_arguments(t, parent(A1)))
+    return xs, ys, zs, last(Makie.convert_arguments(t, parent(A1)))
 end
-# fallbacks with descriptive error messages
+# # fallbacks with descriptive error messages
 function Makie.convert_arguments(t::Makie.ConversionTrait, A::AbstractDimArray{<:Any,N}) where {N}
     @warn "$t not implemented for `AbstractDimArray` with $N dims, falling back to parent array type"
     return Makie.convert_arguments(t, parent(A))
@@ -512,6 +520,27 @@ function _keywords2dimpairs(x, y)
     end
 end
 
+function _lookup_to_vector(l)
+    if isintervals(l)
+        bs = intervalbounds(l)
+        x = first.(bs)
+        push!(x, last(last(bs)))
+    else
+        collect(parent(l))
+    end
+end
+
+function _lookup_to_interval(l)
+    l1 = if isnolookup(l)
+        Sampled(parent(l); order=ForwardOrdered(), sampling=Intervals(Center()), span=Regular(1))
+    elseif ispoints(l)
+        set(l, Intervals())
+    else
+        l
+    end
+    return IntervalSets.Interval(bounds(l1)...)
+end
+
 _floatornan(A::AbstractArray{<:Union{Missing,<:Real}}) = _floatornan64.(A)
 _floatornan(A::AbstractArray{<:Union{Missing,Float64}}) = _floatornan64.(A)
 _floatornan(A) = A
diff --git a/test/plotrecipes.jl b/test/plotrecipes.jl
index 27b737ec4..df59c3345 100644
--- a/test/plotrecipes.jl
+++ b/test/plotrecipes.jl
@@ -1,11 +1,17 @@
 using DimensionalData, Test, Dates
-using Plots, StatsPlots, Unitful
+using Unitful
 import Distributions
 
 using DimensionalData: Metadata, NoMetadata, ForwardOrdered, ReverseOrdered, Unordered,
     Sampled, Categorical, NoLookup, Transformed,
     Regular, Irregular, Explicit, Points, Intervals, Start, Center, End
 
+
+@testset "Plots.jl" begin
+
+using Plots
+using StatsPlots
+
 A1 = rand(Distributions.Normal(), 20)
 ref = (Ti(Sampled(1:1; order=ForwardOrdered(), span=Regular(Day(1)), sampling=Points())),)
 da1_regular = DimArray(A1, X(1:50:1000); name=:Normal, refdims=ref)
@@ -131,8 +137,6 @@ for da in (da3_regular, da3_noindex, da3_ni_r_ni, da3_c_c_c, da3_XYZ, da3_XTiZ,
     end
 end
 
-nothing
-
 # Not sure how recipes work for this
 # andrewsplot(da2)
 
@@ -159,13 +163,19 @@ nothing
 # da_im2 = DimArray(im2, (X(10:10:100), Y(10:10:100)), "Image")
 # da_im2 |> plot
 
-using CairoMakie: CairoMakie as M
-using ColorTypes
+end
+
+
 @testset "Makie" begin
 
+    using CairoMakie: CairoMakie as M
+    using ColorTypes
+
     # 1d
     A1 = rand(X('a':'e'); name=:test)
     A1m = rand([missing, (1:3.)...], X('a':'e'); name=:test)
+    A1u = rand([missing, (1:3.)...], X(1u"s":1u"s":3u"s"); name=:test)
+    A1ui = rand([missing, (1:3.)...], X(1u"s":1u"s":3u"s"; sampling=Intervals(Start())); name=:test)
     A1num = rand(X(-10:10))
     A1m .= A1
     A1m[3] = missing
@@ -174,6 +184,10 @@ using ColorTypes
     fig, ax, _ = M.plot(A1m)
     fig, ax, _ = M.plot(parent(A1m))
     M.plot!(ax, A1m)
+    fig, ax, _ = M.plot(A1u)
+    M.plot!(ax, A1u)
+    fig, ax, _ = M.plot(A1ui)
+    M.plot!(ax, A1ui)
     fig, ax, _ = M.plot(A1num)
     M.reset_limits!(ax)
     org = first(ax.finallimits.val.origin)
@@ -187,32 +201,46 @@ using ColorTypes
     M.scatter!(ax, A1m)
     fig, ax, _ = M.lines(A1)
     M.lines!(ax, A1)
+    fig, ax, _ = M.lines(A1u)
+    M.lines!(ax, A1u)
     fig, ax, _ = M.lines(A1m)
     M.lines!(ax, A1m)
     fig, ax, _ = M.scatterlines(A1)
     M.scatterlines!(ax, A1)
+    fig, ax, _ = M.scatterlines(A1u)
+    M.scatterlines!(ax, A1u)
     fig, ax, _ = M.scatterlines(A1m)
     M.scatterlines!(ax, A1m)
     fig, ax, _ = M.stairs(A1)
     M.stairs!(ax, A1)
+    fig, ax, _ = M.stairs(A1u)
+    M.stairs!(ax, A1u)
     fig, ax, _ = M.stairs(A1m)
     M.stairs!(ax, A1m)
     fig, ax, _ = M.stem(A1)
     M.stem!(ax, A1)
+    fig, ax, _ = M.stem(A1u)
+    M.stem!(ax, A1u)
     fig, ax, _ = M.stem(A1m)
     M.stem!(ax, A1m)
     fig, ax, _ = M.barplot(A1)
     M.barplot!(ax, A1)
+    fig, ax, _ = M.barplot(A1u)
+    M.barplot!(ax, A1u)
     fig, ax, _ = M.barplot(A1m)
     M.barplot!(ax, A1m)
     fig, ax, _ = M.waterfall(A1)
     M.waterfall!(ax, A1)
+    fig, ax, _ = M.waterfall(A1u)
+    M.waterfall!(ax, A1u)
     fig, ax, _ = M.waterfall(A1m)
     M.waterfall!(ax, A1m)
     # 2d
     A2 = rand(X(10:10:100), Y(['a', 'b', 'c']))
     A2r = rand(Y(10:10:100), X(['a', 'b', 'c']))
     A2m = rand([missing, (1:5)...], Y(10:10:100), X(['a', 'b', 'c']))
+    A2u = rand(Y(10u"km":10u"km":100u"km"), X(['a', 'b', 'c']))
+    A2ui = rand(Y(10u"km":10u"km":100u"km"; sampling=Intervals(Start())), X(['a', 'b', 'c']))
     A2m[3] = missing
     A2rgb = rand(RGB, X(10:10:100), Y(['a', 'b', 'c']))
 
@@ -220,6 +248,10 @@ using ColorTypes
     M.plot!(ax, A2)
     fig, ax, _ = M.plot(A2m)
     M.plot!(ax, A2m)
+    fig, ax, _ = M.plot(A2u)
+    M.plot!(ax, A2u)
+    fig, ax, _ = M.plot(A2ui)
+    M.plot!(ax, A2ui)
     fig, ax, _ = M.plot(A2rgb)
     M.plot!(ax, A2rgb)
     fig, ax, _ = M.heatmap(A2)
@@ -241,17 +273,26 @@ using ColorTypes
 
     fig, ax, _ = M.rainclouds(A2)
     M.rainclouds!(ax, A2)
-    # @test_throws ErrorException M.rainclouds(A2m) # MethodError ? missing values in data not supported
-    # @test_throws ErrorException M.rainclouds!(ax, A2m)
+    fig, ax, _ = M.rainclouds(A2u)
+    M.rainclouds!(ax, A2u)
+    @test_throws ErrorException M.rainclouds(A2m) # MethodError ? missing values in data not supported
 
     fig, ax, _ = M.surface(A2)
     M.surface!(ax, A2)
+    fig, ax, _ = M.surface(A2u)
+    M.surface!(ax, A2u)
+    fig, ax, _ = M.surface(A2ui)
+    M.surface!(ax, A2ui)
     fig, ax, _ = M.surface(A2m)
     M.surface!(ax, A2m)
     # Series also puts Categories in the legend no matter where they are
     # TODO: method series! is incomplete, we need to include the colors logic, as in series. There should not be any issue if the correct amount of colours is provided.
     fig, ax, _ = M.series(A2)
     # M.series!(ax, A2)
+    fig, ax, _ = M.series(A2u)
+    # M.series!(ax, A2u)
+    fig, ax, _ = M.series(A2ui)
+    # M.series!(ax, A2u)
     fig, ax, _ = M.series(A2r)
     # M.series!(ax, A2r)
     fig, ax, _ = M.series(A2r; labeldim=Y)
@@ -289,6 +330,7 @@ using ColorTypes
 
     # 3d, all these work with GLMakie
     A3 = rand(X(7), Z(10), Y(5))
+    A3u = rand(X((1:7)u"m"), Z((1.0:1:10.0)u"m"), Y((1:5)u"g"))
     A3m = rand([missing, (1:7)...], X(7), Z(10), Y(5))
     A3m[3] = missing
     A3rgb = rand(RGB, X(7), Z(10), Y(5))
@@ -296,14 +338,24 @@ using ColorTypes
     M.volume!(ax, A3)
     fig, ax, _ = M.volume(A3m)
     M.volume!(ax, A3m)
-    # Broken in Makie ?
+
+    # Units are broken in Makie ?
+    # fig, ax, _ = M.volume(A3u)
+    # M.volume!(ax, A3u)
+    
+    fig, ax, _ = M.volumeslices(A3)
+    M.volumeslices!(ax, A3)
+    # Need to manually specify colorrange
+    fig, ax, _ = M.volumeslices(A3m; colorrange=(1, 7))
+    M.volumeslices!(ax, A3m; colorrange=(1, 7))
+
+    # Unitful volumeslices broken in Makie ?
+    # fig, ax, _ = M.volumeslices(A3u)
+    # M.volumeslices!(ax, A3u)
+
+    # RGB volumeslices broken in Makie ?
     # fig, ax, _ = M.volumeslices(A3rgb)
     # M.volumeslices!(ax, A3rgb)
-    # fig, ax, _ = M.volumeslices(A3)
-    # M.volumeslices!(ax, A3)
-    # colorrange isn't detected here
-    # fig, ax, _ = M.volumeslices(A3m; colorrange=(1, 7))
-    # M.volumeslices!(ax, A3m; colorrange=(1, 7))
     # fig, ax, _ = M.volumeslices(A3rgb)
     # M.volumeslices!(ax, A3rgb)
     # x/y/z can be specified