diff --git a/src/Dimensions/dimension.jl b/src/Dimensions/dimension.jl
index d048ae373..38d07a631 100644
--- a/src/Dimensions/dimension.jl
+++ b/src/Dimensions/dimension.jl
@@ -32,8 +32,7 @@ A = DimArray(zeros(3, 5, 12), (y, x, ti))
 
 # output
 
-╭─────────────────────────────╮
-│ 3×5×12 DimArray{Float64, 3} │
+┌ 3×5×12 DimArray{Float64, 3} ┐
 ├─────────────────────────────┴────────────────────────────────────────── dims ┐
   ↓ Y  Categorical{Char} ['a', 'b', 'c'] ForwardOrdered,
   → X  Sampled{Int64} 2:2:10 ForwardOrdered Regular Points,
@@ -54,8 +53,7 @@ x = A[X(2), Y(3)]
 
 # output
 
-╭─────────────────────────────────╮
-│ 12-element DimArray{Float64, 1} │
+┌ 12-element DimArray{Float64, 1} ┐
 ├─────────────────────────────────┴────────────────────────────────────── dims ┐
   ↓ Ti Sampled{DateTime} DateTime("2021-01-01T00:00:00"):Month(1):DateTime("2021-12-01T00:00:00") ForwardOrdered Regular Points
 └──────────────────────────────────────────────────────────────────────────────┘
@@ -80,8 +78,7 @@ x = A[X(Between(3, 4)), Y(At('b'))]
 
 # output
 
-╭───────────────────────────╮
-│ 1×12 DimArray{Float64, 2} │
+┌ 1×12 DimArray{Float64, 2} ┐
 ├───────────────────────────┴──────────────────────────────────────────── dims ┐
   ↓ X  Sampled{Int64} 4:2:4 ForwardOrdered Regular Points,
   → Ti Sampled{DateTime} DateTime("2021-01-01T00:00:00"):Month(1):DateTime("2021-12-01T00:00:00") ForwardOrdered Regular Points
diff --git a/src/Dimensions/primitives.jl b/src/Dimensions/primitives.jl
index 32159ecdf..cf15dfc2e 100644
--- a/src/Dimensions/primitives.jl
+++ b/src/Dimensions/primitives.jl
@@ -131,8 +131,7 @@ any combination of either.
 julia> using DimensionalData
 
 julia> A = DimArray(ones(2, 3, 2), (X, Y, Z))
-╭────────────────────────────╮
-│ 2×3×2 DimArray{Float64, 3} │
+┌ 2×3×2 DimArray{Float64, 3} ┐
 ├────────────────────── dims ┤
   ↓ X, → Y, ↗ Z
 └────────────────────────────┘
@@ -364,8 +363,7 @@ A = ones(X(2), Y(4), Z(2))
 Dimensions.swapdims(A, (Dim{:a}, Dim{:b}, Dim{:c}))
 
 # output
-╭────────────────────────────╮
-│ 2×4×2 DimArray{Float64, 3} │
+┌ 2×4×2 DimArray{Float64, 3} ┐
 ├────────────────────── dims ┤
   ↓ a, → b, ↗ c
 └────────────────────────────┘
diff --git a/src/Lookups/lookup_arrays.jl b/src/Lookups/lookup_arrays.jl
index 4d8210a50..9f69dc1cb 100644
--- a/src/Lookups/lookup_arrays.jl
+++ b/src/Lookups/lookup_arrays.jl
@@ -293,8 +293,7 @@ y = Y(Sampled([1, 4, 7, 10]; span=Regular(3), sampling=Intervals(Start())))
 A = ones(x, y)
 
 # output
-╭──────────────────────────╮
-│ 5×4 DimArray{Float64, 2} │
+┌ 5×4 DimArray{Float64, 2} ┐
 ├──────────────────────────┴───────────────────────────────────────── dims ┐
   ↓ X Sampled{Int64} 100:-20:20 ReverseOrdered Regular Intervals{Start},
   → Y Sampled{Int64} [1, 4, 7, 10] ForwardOrdered Regular Intervals{Start}
diff --git a/src/Lookups/selector.jl b/src/Lookups/selector.jl
index e421c64a1..35e5fe1e8 100644
--- a/src/Lookups/selector.jl
+++ b/src/Lookups/selector.jl
@@ -551,8 +551,7 @@ A[X(Between(15, 25)), Y(Between(4, 6.5))]
 
 # output
 
-╭────────────────────────╮
-│ 1×2 DimArray{Int64, 2} │
+┌ 1×2 DimArray{Int64, 2} ┐
 ├────────────────────────┴───────────────────────────── dims ┐
   ↓ X Sampled{Int64} 20:10:20 ForwardOrdered Regular Points,
   → Y Sampled{Int64} 5:6 ForwardOrdered Regular Points
@@ -807,8 +806,7 @@ A = DimArray([1 2 3; 4 5 6], (X(10:10:20), Y(5:7)))
 A[X(Touches(15, 25)), Y(Touches(4, 6.5))]
 
 # output
-╭────────────────────────╮
-│ 1×2 DimArray{Int64, 2} │
+┌ 1×2 DimArray{Int64, 2} ┐
 ├────────────────────────┴───────────────────────────── dims ┐
   ↓ X Sampled{Int64} 20:10:20 ForwardOrdered Regular Points,
   → Y Sampled{Int64} 5:6 ForwardOrdered Regular Points
@@ -975,8 +973,7 @@ A[X(Where(x -> x > 15)), Y(Where(x -> x in (19, 21)))]
 
 # output
 
-╭────────────────────────╮
-│ 1×2 DimArray{Int64, 2} │
+┌ 1×2 DimArray{Int64, 2} ┐
 ├────────────────────────┴────────────────────────────── dims ┐
   ↓ X Sampled{Int64} [20] ForwardOrdered Irregular Points,
   → Y Sampled{Int64} [19, 21] ForwardOrdered Irregular Points
@@ -1017,8 +1014,7 @@ A[X=All(At(10.0), At(50.0)), Ti=All(1u"s"..10u"s", 90u"s"..100u"s")]
 
 # output
 
-╭────────────────────────╮
-│ 2×4 DimArray{Int64, 2} │
+┌ 2×4 DimArray{Int64, 2} ┐
 ├────────────────────────┴─────────────────────────────────────────────── dims ┐
   ↓ X  Sampled{Float64} [10.0, 50.0] ForwardOrdered Irregular Points,
   → Ti Sampled{Unitful.Quantity{Int64, 𝐓, Unitful.FreeUnits{(s,), 𝐓, nothing}}} [1 s, 6 s, 91 s, 96 s] ForwardOrdered Irregular Points
diff --git a/src/array/array.jl b/src/array/array.jl
index b4cc08a60..d3e054c28 100644
--- a/src/array/array.jl
+++ b/src/array/array.jl
@@ -401,8 +401,7 @@ julia> x = X(10:10:100);
 julia> A = DimArray(rand(12,10), (ti, x), name="example");
 
 julia> A[X(Near([12, 35])), Ti(At(DateTime(2001,5)))]
-╭────────────────────────────────────────╮
-│ 2-element DimArray{Float64, 1} example │
+┌ 2-element DimArray{Float64, 1} example ┐
 ├────────────────────────────────────────┴────────────── dims ┐
   ↓ X Sampled{Int64} [10, 40] ForwardOrdered Irregular Points
 └─────────────────────────────────────────────────────────────┘
@@ -410,8 +409,7 @@ julia> A[X(Near([12, 35])), Ti(At(DateTime(2001,5)))]
  40  0.637077
 
 julia> A[Near(DateTime(2001, 5, 4)), Between(20, 50)]
-╭────────────────────────────────────────╮
-│ 4-element DimArray{Float64, 1} example │
+┌ 4-element DimArray{Float64, 1} example ┐
 ├────────────────────────────────────────┴──────────── dims ┐
   ↓ X Sampled{Int64} 20:10:50 ForwardOrdered Regular Points
 └───────────────────────────────────────────────────────────┘
@@ -425,8 +423,7 @@ Generator expression:
 
 ```jldoctest dimarray
 julia> DimArray((x, y) for x in X(1:3), y in Y(1:2); name = :Value)
-╭────────────────────────────────────────────╮
-│ 3×2 DimArray{Tuple{Int64, Int64}, 2} Value │
+┌ 3×2 DimArray{Tuple{Int64, Int64}, 2} Value ┐
 ├────────────────────────────────────────────┴──── dims ┐
   ↓ X Sampled{Int64} 1:3 ForwardOrdered Regular Points,
   → Y Sampled{Int64} 1:2 ForwardOrdered Regular Points
@@ -545,8 +542,7 @@ Keywords are the same as for [`DimArray`](@ref).
 julia> using DimensionalData, Random; Random.seed!(123);
 
 julia> fill(true, X(2), Y(4))
-╭───────────────────────╮
-│ 2×4 DimArray{Bool, 2} │
+┌ 2×4 DimArray{Bool, 2} ┐
 ├───────────────── dims ┤
   ↓ X, → Y
 └───────────────────────┘
@@ -578,8 +574,7 @@ Keywords are the same as for [`DimArray`](@ref).
 julia> using DimensionalData
 
 julia> rand(Bool, X(2), Y(4))
-╭───────────────────────╮
-│ 2×4 DimArray{Bool, 2} │
+┌ 2×4 DimArray{Bool, 2} ┐
 ├───────────────── dims ┤
   ↓ X, → Y
 └───────────────────────┘
@@ -587,8 +582,7 @@ julia> rand(Bool, X(2), Y(4))
  1  0  0  1
 
 julia> rand(X([:a, :b, :c]), Y(100.0:50:200.0))
-╭──────────────────────────╮
-│ 3×3 DimArray{Float64, 2} │
+┌ 3×3 DimArray{Float64, 2} ┐
 ├──────────────────────────┴──────────────────────────────────── dims ┐
   ↓ X Categorical{Symbol} [:a, :b, :c] ForwardOrdered,
   → Y Sampled{Float64} 100.0:50.0:200.0 ForwardOrdered Regular Points
@@ -621,8 +615,7 @@ Keywords are the same as for [`DimArray`](@ref).
 julia> using DimensionalData
 
 julia> zeros(Bool, X(2), Y(4))
-╭───────────────────────╮
-│ 2×4 DimArray{Bool, 2} │
+┌ 2×4 DimArray{Bool, 2} ┐
 ├───────────────── dims ┤
   ↓ X, → Y
 └───────────────────────┘
@@ -630,8 +623,7 @@ julia> zeros(Bool, X(2), Y(4))
  0  0  0  0
 
 julia> zeros(X([:a, :b, :c]), Y(100.0:50:200.0))
-╭──────────────────────────╮
-│ 3×3 DimArray{Float64, 2} │
+┌ 3×3 DimArray{Float64, 2} ┐
 ├──────────────────────────┴──────────────────────────────────── dims ┐
   ↓ X Categorical{Symbol} [:a, :b, :c] ForwardOrdered,
   → Y Sampled{Float64} 100.0:50.0:200.0 ForwardOrdered Regular Points
@@ -665,8 +657,7 @@ Keywords are the same as for [`DimArray`](@ref).
 julia> using DimensionalData
 
 julia> ones(Bool, X(2), Y(4))
-╭───────────────────────╮
-│ 2×4 DimArray{Bool, 2} │
+┌ 2×4 DimArray{Bool, 2} ┐
 ├───────────────── dims ┤
   ↓ X, → Y
 └───────────────────────┘
@@ -674,8 +665,7 @@ julia> ones(Bool, X(2), Y(4))
  1  1  1  1
 
 julia> ones(X([:a, :b, :c]), Y(100.0:50:200.0))
-╭──────────────────────────╮
-│ 3×3 DimArray{Float64, 2} │
+┌ 3×3 DimArray{Float64, 2} ┐
 ├──────────────────────────┴──────────────────────────────────── dims ┐
   ↓ X Categorical{Symbol} [:a, :b, :c] ForwardOrdered,
   → Y Sampled{Float64} 100.0:50.0:200.0 ForwardOrdered Regular Points
diff --git a/src/array/show.jl b/src/array/show.jl
index b5f099543..b6a561ce5 100644
--- a/src/array/show.jl
+++ b/src/array/show.jl
@@ -99,11 +99,9 @@ print_type(io, x) = print(io, string(nameof(typeof(x))))
 function print_top(io, mime, A)
     _, displaywidth = displaysize(io)
     blockwidth = min(displaywidth - 2, textwidth(sprint(summary, A)) + 2)
-    printstyled(io, '╭', '─'^blockwidth, '╮'; color=:light_black)
-    println(io)
-    printstyled(io, "│ "; color=:light_black)
+    printstyled(io, "┌ "; color=:light_black)
     summary(io, A)
-    printstyled(io, " │"; color=:light_black)
+    printstyled(io, " ┐"; color=:light_black)
     println(io)
     n, blockwidth = print_dims_block(io, mime, dims(A); displaywidth, blockwidth)
     lines = 2 + n
diff --git a/src/dimindices.jl b/src/dimindices.jl
index 0a80344d6..56ecd1996 100644
--- a/src/dimindices.jl
+++ b/src/dimindices.jl
@@ -76,8 +76,7 @@ are not in the same order. Or even if they are not all contained in each.
 
 ```jldoctest; setup = :(using DimensionalData, Random; Random.seed!(123))
 julia> A = rand(Y(0.0:0.3:1.0), X('a':'f'))
-╭──────────────────────────╮
-│ 4×6 DimArray{Float64, 2} │
+┌ 4×6 DimArray{Float64, 2} ┐
 ├──────────────────────────┴──────────────────────────────── dims ┐
   ↓ Y Sampled{Float64} 0.0:0.3:0.9 ForwardOrdered Regular Points,
   → X Categorical{Char} 'a':1:'f' ForwardOrdered
@@ -89,8 +88,7 @@ julia> A = rand(Y(0.0:0.3:1.0), X('a':'f'))
  0.9  0.512083  0.867547  0.136551   0.959434   0.150155  0.941133
 
 julia> di = DimIndices((X(1:2:4), Y(1:2:4)))
-╭──────────────────────────────────────────────╮
-│ 2×2 DimIndices{Tuple{X{Int64}, Y{Int64}}, 2} │
+┌ 2×2 DimIndices{Tuple{X{Int64}, Y{Int64}}, 2} ┐
 ├──────────────────────────────────────── dims ┤
   ↓ X 1:2:3,
   → Y 1:2:3
@@ -100,8 +98,7 @@ julia> di = DimIndices((X(1:2:4), Y(1:2:4)))
  3     (↓ X 3, → Y 1)   (↓ X 3, → Y 3)
 
 julia> A[di] # Index A with these indices
-╭──────────────────────────╮
-│ 2×2 DimArray{Float64, 2} │
+┌ 2×2 DimArray{Float64, 2} ┐
 ├──────────────────────────┴──────────────────────────────── dims ┐
   ↓ Y Sampled{Float64} 0.0:0.6:0.6 ForwardOrdered Regular Points,
   → X Categorical{Char} 'a':2:'c' ForwardOrdered
@@ -228,8 +225,7 @@ julia> A = rand(X(1.0:3.0:30.0), Y(1.0:5.0:30.0), Ti(1:2));
 julia> target = rand(X(1.0:10.0:30.0), Y(1.0:10.0:30.0));
 
 julia> A[DimSelectors(target; selectors=Near), Ti=2]
-╭──────────────────────────╮
-│ 3×3 DimArray{Float64, 2} │
+┌ 3×3 DimArray{Float64, 2} ┐
 ├──────────────────────────┴──────────────────────────────────────── dims ┐
   ↓ X Sampled{Float64} [1.0, 10.0, 22.0] ForwardOrdered Irregular Points,
   → Y Sampled{Float64} [1.0, 11.0, 21.0] ForwardOrdered Irregular Points
diff --git a/src/groupby.jl b/src/groupby.jl
index 6792f6d32..70f7add8b 100644
--- a/src/groupby.jl
+++ b/src/groupby.jl
@@ -253,8 +253,7 @@ julia> using DimensionalData, Dates
 julia> A = rand(X(1:0.1:20), Y(1:20), Ti(DateTime(2000):Day(3):DateTime(2003)));
 
 julia> groups = groupby(A, Ti => month) # Group by month
-╭───────────────────────────────────────────────────╮
-│ 12-element DimGroupByArray{DimArray{Float64,2},1} │
+┌ 12-element DimGroupByArray{DimArray{Float64,2},1} ┐
 ├───────────────────────────────────────────────────┴───────────── dims ┐
   ↓ Ti Sampled{Int64} [1, 2, …, 11, 12] ForwardOrdered Irregular Points
 ├───────────────────────────────────────────────────────────── metadata ┤
@@ -275,8 +274,7 @@ And take the mean:
 
 ```jldoctest groupby; setup = :(using Statistics)
 julia> groupmeans = mean.(groups) # Take the monthly mean
-╭─────────────────────────────────╮
-│ 12-element DimArray{Float64, 1} │
+┌ 12-element DimArray{Float64, 1} ┐
 ├─────────────────────────────────┴─────────────────────────────── dims ┐
   ↓ Ti Sampled{Int64} [1, 2, …, 11, 12] ForwardOrdered Irregular Points
 ├───────────────────────────────────────────────────────────── metadata ┤
@@ -305,8 +303,7 @@ Or do something else with Y:
 
 ```jldoctest groupby
 julia> groupmeans = mean.(groupby(A, Ti=>month, Y=>isodd))
-╭───────────────────────────╮
-│ 12×2 DimArray{Float64, 2} │
+┌ 12×2 DimArray{Float64, 2} ┐
 ├───────────────────────────┴────────────────────────────────────── dims ┐
   ↓ Ti Sampled{Int64} [1, 2, …, 11, 12] ForwardOrdered Irregular Points,
   → Y  Sampled{Bool} [false, true] ForwardOrdered Irregular Points
diff --git a/src/set.jl b/src/set.jl
index 1c7a2a112..dac869a29 100644
--- a/src/set.jl
+++ b/src/set.jl
@@ -41,8 +41,7 @@ julia> using DimensionalData; const DD = DimensionalData;
 julia> da = DimArray(zeros(3, 4), (custom=10.0:010.0:30.0, Z=-20:010.0:10.0));
 
 julia> set(da, ones(3, 4))
-╭──────────────────────────╮
-│ 3×4 DimArray{Float64, 2} │
+┌ 3×4 DimArray{Float64, 2} ┐
 ├──────────────────────────┴──────────────────────────────────────── dims ┐
   ↓ custom Sampled{Float64} 10.0:10.0:30.0 ForwardOrdered Regular Points,
   → Z      Sampled{Float64} -20.0:10.0:10.0 ForwardOrdered Regular Points
@@ -57,8 +56,7 @@ Change the `Dimension` wrapper type:
 
 ```jldoctest set
 julia> set(da, :Z => Ti, :custom => Z)
-╭──────────────────────────╮
-│ 3×4 DimArray{Float64, 2} │
+┌ 3×4 DimArray{Float64, 2} ┐
 ├──────────────────────────┴──────────────────────────────────── dims ┐
   ↓ Z  Sampled{Float64} 10.0:10.0:30.0 ForwardOrdered Regular Points,
   → Ti Sampled{Float64} -20.0:10.0:10.0 ForwardOrdered Regular Points
@@ -73,8 +71,7 @@ Change the lookup `Vector`:
 
 ```jldoctest set
 julia> set(da, Z => [:a, :b, :c, :d], :custom => [4, 5, 6])
-╭──────────────────────────╮
-│ 3×4 DimArray{Float64, 2} │
+┌ 3×4 DimArray{Float64, 2} ┐
 ├──────────────────────────┴──────────────────────────────────────── dims ┐
   ↓ custom Sampled{Int64} [4, 5, 6] ForwardOrdered Regular Points,
   → Z      Sampled{Symbol} [:a, :b, :c, :d] ForwardOrdered Regular Points
@@ -89,8 +86,7 @@ Change the `Lookup` type:
 
 ```jldoctest set
 julia> set(da, Z=DD.NoLookup(), custom=DD.Sampled())
-╭──────────────────────────╮
-│ 3×4 DimArray{Float64, 2} │
+┌ 3×4 DimArray{Float64, 2} ┐
 ├──────────────────────────┴──────────────────────────────────────── dims ┐
   ↓ custom Sampled{Float64} 10.0:10.0:30.0 ForwardOrdered Regular Points,
   → Z
@@ -104,8 +100,7 @@ Change the `Sampling` trait:
 
 ```jldoctest set
 julia> set(da, :custom => DD.Irregular(10, 12), Z => DD.Regular(9.9))
-╭──────────────────────────╮
-│ 3×4 DimArray{Float64, 2} │
+┌ 3×4 DimArray{Float64, 2} ┐
 ├──────────────────────────┴────────────────────────────────────────── dims ┐
   ↓ custom Sampled{Float64} 10.0:10.0:30.0 ForwardOrdered Irregular Points,
   → Z      Sampled{Float64} -20.0:10.0:10.0 ForwardOrdered Regular Points
diff --git a/src/stack/methods.jl b/src/stack/methods.jl
index 272cd2146..7e684ba84 100644
--- a/src/stack/methods.jl
+++ b/src/stack/methods.jl
@@ -72,8 +72,7 @@ julia> map(dims, axes(slices))
 → X Base.OneTo(2))
 
 julia> first(slices)
-╭──────────────╮
-│ 3×5 DimStack │
+┌ 3×5 DimStack ┐
 ├──────────────┴─────────────────────────────────── dims ┐
   ↓ Y  Sampled{Int64} 1:3 ForwardOrdered Regular Points,
   → Ti
diff --git a/src/tables.jl b/src/tables.jl
index 96a127ffa..9773a8495 100644
--- a/src/tables.jl
+++ b/src/tables.jl
@@ -65,8 +65,7 @@ To get dimension columns, you can index with `Dimension` (`X()`) or
 julia> using DimensionalData, Tables
 
 julia> a = DimArray(ones(16, 16, 3), (X, Y, Dim{:band}))
-╭──────────────────────────────╮
-│ 16×16×3 DimArray{Float64, 3} │
+┌ 16×16×3 DimArray{Float64, 3} ┐
 ├──────────────────────── dims ┤
   ↓ X, → Y, ↗ band
 └──────────────────────────────┘