Add broadcasting of AbstractDataFrame

src/other/broadcasting.jl

@@ -128,36 +128,41 @@ function Base.Broadcast.broadcast_unalias(dest::AbstractDataFrame, src)
     src
 end
 
+function _broadcast_unalias_helper(dest, scol, src, col2, wascopied)
+    # col1 can be checked till col2 point as we are writing broadcasting
+    # results from 1 to ncol
+    # we go downwards because aliasing when col1 == col2 is most probable
+    for col1 in col2:-1:1
+        dcol = dest[col1]
+        if Base.mightalias(dcol, scol)
+            if src isa SubDataFrame
+                if !wascopied
+                    src =SubDataFrame(copy(parent(src), copycols=false),
+                                      index(src), rows(src))
+                end
+                parentidx = parentcols(index(src), col2)
+                parent(src)[parentidx] = Base.unaliascopy(parent(src)[parentidx])
+
+            else
+                if !wascopied
+                    src = copy(src, copycols=false)
+                end
+                src[col2] = Base.unaliascopy(scol)
+            end
+            return src, true
+        end
+    end
+    return src, wascopied
+end
+
 function Base.Broadcast.broadcast_unalias(dest::AbstractDataFrame, src::AbstractDataFrame)
     if size(dest, 2) != size(src, 2)
         throw(ArgumentError("Dimension mismatch in broadcasting."))
     end
-    # col2 can be checked from col1 point as we are writing broadcasting
-    # results from 1 to ncol
     wascopied = false
-    for col1 in axes(dest, 2)
-        for col2 in col1:ncol(src)
-            dcol = dest[col1]
-            scol = src[col2]
-            if Base.mightalias(dcol, scol)
-                if src isa SubDataFrame
-                    if !wascopied
-                        src = SubDataFrame(copy(parent(src), copycols=false),
-                                           index(src), rows(src))
-                        wascopied = true
-                    end
-                    parentidx = parentcols(index(src), col2)
-                    parent(src)[parentidx] = Base.unaliascopy(parent(src)[parentidx])
-                else
-                    if !wascopied
-                        src = copy(src, copycols=false)
-                        wascopied = true
-                    end
-                    src[col2] = Base.unaliascopy(scol)
-                end
-                break
-            end
-        end
+    for col2 in axes(dest, 2)
+        scol = src[col2]
+        src, wascopied = _broadcast_unalias_helper(dest, scol, src, col2, wascopied)
     end
     src
 end

test/broadcasting.jl

@@ -841,4 +841,33 @@ end
     @test df == DataFrame(dfm)
 end
 
+@testset "test common cases" begin
+    m = rand(1000, 10)
+    df = DataFrame(m)
+    @test df .+ 1 == DataFrame(m .+ 1)
+    @test df .+ transpose(1:10) == DataFrame(m .+ transpose(1:10))
+    @test df .+ (1:1000) == DataFrame(m .+ (1:1000))
+    @test df .+ m == DataFrame(m .+ m)
+    @test m .+ df == DataFrame(m .+ m)
+    @test df .+ df == DataFrame(m .+ m)
+
+    df .+= 1
+    m .+= 1
+    @test df == DataFrame(m)
+    df .+= transpose(1:10)
+    m .+= transpose(1:10)
+    @test df == DataFrame(m)
+    df .+= (1:1000)
+    m .+= (1:1000)
+    @test df == DataFrame(m)
+    df .+= df
+    m .+= m
+    @test df == DataFrame(m)
+    df2 = copy(df)
+    m2 = copy(m)
+    df .+= df .+ df2 .+ m2 .+ 1
+    m .+= m .+ df2 .+ m2 .+ 1
+    @test df == DataFrame(m)
+end
+
 end # module