clean up outstanding convert

src/abstractdataframe/abstractdataframe.jl

@@ -1144,7 +1144,7 @@ _filter!_helper_astable(df::AbstractDataFrame, nti::Tables.NamedTupleIterator, f
 
 function Base.Matrix(df::AbstractDataFrame)
     T = reduce(promote_type, (eltype(v) for v in eachcol(df)))
-    return convert(Matrix{T}, df)
+    return Matrix{T}(df)
 end
 
 function Base.Matrix{T}(df::AbstractDataFrame) where T

src/dataframerow/dataframerow.jl

@@ -403,7 +403,7 @@ Base.IteratorEltype(::Type{<:DataFrameRow}) = Base.EltypeUnknown()
 function Base.Vector(dfr::DataFrameRow)
     df = parent(dfr)
     T = reduce(promote_type, (eltype(df[!, i]) for i in parentcols(index(dfr))))
-    convert(Vector{T}, dfr)
+    return Vector{T}(dfr)
 end
 Base.Vector{T}(dfr::DataFrameRow) where T =
     T[dfr[i] for i in 1:length(dfr)]

test/dataframerow.jl

@@ -279,13 +279,9 @@ end
     nt = first(Tables.namedtupleiterator(df))
     @test copy(dfr) === nt === NamedTuple{(:a, :b), Tuple{Union{Missing, Int}, Float64}}((1, 2.0))
     @test sum(skipmissing(copy(df[3, :]))) == 0
-    @test convert(Vector, dfr)::Vector{Union{Float64, Missing}} == [1.0, 2.0]
-    @test convert(Vector{Int}, dfr)::Vector{Int} == [1, 2]
     @test Vector(dfr)::Vector{Union{Float64, Missing}} == [1.0, 2.0]
     @test Vector{Int}(dfr)::Vector{Int} == [1, 2]
 
-    @test convert(Array, dfr)::Vector{Union{Float64, Missing}} == [1.0, 2.0]
-    @test convert(Array{Int}, dfr)::Vector{Int} == [1, 2]
     @test Array(dfr)::Vector{Union{Float64, Missing}} == [1.0, 2.0]
     @test Array{Int}(dfr)::Vector{Int} == [1, 2]
 
@@ -297,7 +293,6 @@ end
     dfr2 = DataFrame(c=3, d=4)[1, :]
     @test NamedTuple(dfr) == (a=1, b=2)
     @test convert(NamedTuple, dfr) == (a=1, b=2)
-    @test convert(Tuple, dfr) == (1, 2)
     @test merge(dfr) == (a=1, b=2)
     @test merge(dfr, (c=3, d=4)) == (a=1, b=2, c=3, d=4)
     @test merge((c=3, d=4), dfr) == (c=3, d=4, a=1, b=2)

test/deprecated.jl

@@ -241,4 +241,17 @@ end
     @test convert(Tuple, key) isa Tuple{Int}
 end
 
+@testset "DataFrameRow convert" begin
+    df = DataFrame(a=[1, missing, missing], b=[2.0, 3.0, 0.0])
+    dfr = DataFrameRow(df, 1, :)
+    @test convert(Vector, dfr)::Vector{Union{Float64, Missing}} == [1.0, 2.0]
+    @test convert(Vector{Int}, dfr)::Vector{Int} == [1, 2]
+    @test convert(Array, dfr)::Vector{Union{Float64, Missing}} == [1.0, 2.0]
+    @test convert(Array{Int}, dfr)::Vector{Int} == [1, 2]
+
+    dfr = DataFrame(a=1, b=2)[1, :]
+    dfr2 = DataFrame(c=3, d=4)[1, :]
+    @test convert(Tuple, dfr) == (1, 2)
+end
+
 end # module

test/iteration.jl

@@ -47,7 +47,7 @@ using Test, DataFrames
         @test isa(col, AbstractVector)
     end
 
-    @test map(x -> minimum(convert(Vector, x)), eachrow(df)) == [1, 2]
+    @test map(x -> minimum(Vector(x)), eachrow(df)) == [1, 2]
     @test map(Vector, eachrow(df)) == [[1, 2], [2, 3]]
     @test mapcols(minimum, df) == DataFrame(A = [1], B = [2])
     @test map(minimum, eachcol(df)) == [1, 2]