doctest failure in ~/work/DataFramesMeta.jl/DataFramesMeta.jl/src/macros.jl:1884-1919 ```jldoctest julia> using DataFramesMeta julia> df = DataFrame(a = repeat(1:4, outer = 2), b = repeat(2:-1:1, outer = 4), c = 1:8); julia> @select(df, :c, :a) 8×2 DataFrame Row │ c a │ Int64 Int64 ─────┼────────────── 1 │ 1 1 2 │ 2 2 3 │ 3 3 4 │ 4 4 5 │ 5 1 6 │ 6 2 7 │ 7 3 8 │ 8 4 julia> @select df begin :c :x = :b + :c end 8×2 DataFrame Row │ c x │ Int64 Int64 ─────┼────────────── 1 │ 1 3 2 │ 2 3 3 │ 3 5 4 │ 4 5 5 │ 5 7 6 │ 6 7 7 │ 7 9 8 │ 8 9 ``` Subexpression: @select(df, :c, :a) Evaluated output: ERROR: LoadError: MethodError: no method matching fun_to_vec(::QuoteNode; gensym_names::Bool, outer_flags::NamedTuple{(Symbol("@byrow"), Symbol("@passmissing"), Symbol("@astable")), Tuple{Base.RefValue{Bool}, Base.RefValue{Bool}, Base.RefValue{Bool}}}, allow_multicol::Bool) Closest candidates are: fun_to_vec(::QuoteNode; no_dest, gensym_names, outer_flags) got unsupported keyword argument "allow_multicol" @ DataFramesMeta ~/work/DataFramesMeta.jl/DataFramesMeta.jl/src/parsing.jl:430 fun_to_vec(!Matched::Expr; gensym_names, outer_flags, no_dest, allow_multicol) @ DataFramesMeta ~/work/DataFramesMeta.jl/DataFramesMeta.jl/src/parsing.jl:322 Stacktrace: [1] kwerr(::NamedTuple{(:gensym_names, :outer_flags, :allow_multicol), Tuple{Bool, NamedTuple{(Symbol("@byrow"), Symbol("@passmissing"), Symbol("@astable")), Tuple{Base.RefValue{Bool}, Base.RefValue{Bool}, Base.RefValue{Bool}}}, Bool}}, ::Function, ::QuoteNode) @ Base ./error.jl:165 [2] (::DataFramesMeta.var"#50#51"{NamedTuple{(Symbol("@byrow"), Symbol("@passmissing"), Symbol("@astable")), Tuple{Base.RefValue{Bool}, Base.RefValue{Bool}, Base.RefValue{Bool}}}})(ex::QuoteNode) @ DataFramesMeta ./none:0 [3] iterate(::Base.Generator{Vector{Any}, DataFramesMeta.var"#50#51"{NamedTuple{(Symbol("@byrow"), Symbol("@passmissing"), Symbol("@astable")), Tuple{Base.RefValue{Bool}, Base.RefValue{Bool}, Base.RefValue{Bool}}}}}) @ Base ./generator.jl:47 [4] select_helper(::Symbol, ::QuoteNode, ::Vararg{QuoteNode}) @ DataFramesMeta ~/work/DataFramesMeta.jl/DataFramesMeta.jl/src/macros.jl:1788 [5] var"@select"(__source__::LineNumberNode, __module__::Module, x::Any, args::Vararg{Any}) @ DataFramesMeta ~/work/DataFramesMeta.jl/DataFramesMeta.jl/src/macros.jl:1922 in expression starting at none:1 Expected output: 8×2 DataFrame Row │ c a │ Int64 Int64 ─────┼────────────── 1 │ 1 1 2 │ 2 2 3 │ 3 3 4 │ 4 4 5 │ 5 1 6 │ 6 2 7 │ 7 3 8 │ 8 4 diff = Warning: Diff output requires color. 8×2 DataFrame Row │ c a │ Int64 Int64 ─────┼────────────── 1 │ 1 1 2 │ 2 2 3 │ 3 3 4 │ 4 4 5 │ 5 1 6 │ 6 2 7 │ 7 3 8 │ 8 4ERROR: LoadError: MethodError: no method matching fun_to_vec(::QuoteNode; gensym_names::Bool, outer_flags::NamedTuple{(Symbol("@byrow"), Symbol("@passmissing"), Symbol("@astable")), Tuple{Base.RefValue{Bool}, Base.RefValue{Bool}, Base.RefValue{Bool}}}, allow_multicol::Bool) Closest candidates are: fun_to_vec(::QuoteNode; no_dest, gensym_names, outer_flags) got unsupported keyword argument "allow_multicol" @ DataFramesMeta ~/work/DataFramesMeta.jl/DataFramesMeta.jl/src/parsing.jl:430 fun_to_vec(!Matched::Expr; gensym_names, outer_flags, no_dest, allow_multicol) @ DataFramesMeta ~/work/DataFramesMeta.jl/DataFramesMeta.jl/src/parsing.jl:322 Stacktrace: [1] kwerr(::NamedTuple{(:gensym_names, :outer_flags, :allow_multicol), Tuple{Bool, NamedTuple{(Symbol("@byrow"), Symbol("@passmissing"), Symbol("@astable")), Tuple{Base.RefValue{Bo

doctest failure in ~/work/DataFramesMeta.jl/DataFramesMeta.jl/src/macros.jl:1884-1919 ```jldoctest julia> using DataFramesMeta julia> df = DataFrame(a = repeat(1:4, outer = 2), b = repeat(2:-1:1, outer = 4), c = 1:8); julia> @select(df, :c, :a) 8×2 DataFrame Row │ c a │ Int64 Int64 ─────┼────────────── 1 │ 1 1 2 │ 2 2 3 │ 3 3 4 │ 4 4 5 │ 5 1 6 │ 6 2 7 │ 7 3 8 │ 8 4 julia> @select df begin :c :x = :b + :c end 8×2 DataFrame Row │ c x │ Int64 Int64 ─────┼────────────── 1 │ 1 3 2 │ 2 3 3 │ 3 5 4 │ 4 5 5 │ 5 7 6 │ 6 7 7 │ 7 9 8 │ 8 9 ``` Subexpression: @select df begin :c :x = :b + :c end Evaluated output: ERROR: LoadError: MethodError: no method matching fun_to_vec(::QuoteNode; gensym_names::Bool, outer_flags::NamedTuple{(Symbol("@byrow"), Symbol("@passmissing"), Symbol("@astable")), Tuple{Base.RefValue{Bool}, Base.RefValue{Bool}, Base.RefValue{Bool}}}, allow_multicol::Bool) Closest candidates are: fun_to_vec(::QuoteNode; no_dest, gensym_names, outer_flags) got unsupported keyword argument "allow_multicol" @ DataFramesMeta ~/work/DataFramesMeta.jl/DataFramesMeta.jl/src/parsing.jl:430 fun_to_vec(!Matched::Expr; gensym_names, outer_flags, no_dest, allow_multicol) @ DataFramesMeta ~/work/DataFramesMeta.jl/DataFramesMeta.jl/src/parsing.jl:322 Stacktrace: [1] kwerr(::NamedTuple{(:gensym_names, :outer_flags, :allow_multicol), Tuple{Bool, NamedTuple{(Symbol("@byrow"), Symbol("@passmissing"), Symbol("@astable")), Tuple{Base.RefValue{Bool}, Base.RefValue{Bool}, Base.RefValue{Bool}}}, Bool}}, ::Function, ::QuoteNode) @ Base ./error.jl:165 [2] (::DataFramesMeta.var"#50#51"{NamedTuple{(Symbol("@byrow"), Symbol("@passmissing"), Symbol("@astable")), Tuple{Base.RefValue{Bool}, Base.RefValue{Bool}, Base.RefValue{Bool}}}})(ex::QuoteNode) @ DataFramesMeta ./none:0 [3] iterate(::Base.Generator{Vector{Any}, DataFramesMeta.var"#50#51"{NamedTuple{(Symbol("@byrow"), Symbol("@passmissing"), Symbol("@astable")), Tuple{Base.RefValue{Bool}, Base.RefValue{Bool}, Base.RefValue{Bool}}}}}) @ Base ./generator.jl:47 [4] select_helper(x::Symbol, args::Expr) @ DataFramesMeta ~/work/DataFramesMeta.jl/DataFramesMeta.jl/src/macros.jl:1788 [5] var"@select"(__source__::LineNumberNode, __module__::Module, x::Any, args::Vararg{Any}) @ DataFramesMeta ~/work/DataFramesMeta.jl/DataFramesMeta.jl/src/macros.jl:1922 in expression starting at none:1 Expected output: 8×2 DataFrame Row │ c x │ Int64 Int64 ─────┼────────────── 1 │ 1 3 2 │ 2 3 3 │ 3 5 4 │ 4 5 5 │ 5 7 6 │ 6 7 7 │ 7 9 8 │ 8 9 diff = Warning: Diff output requires color. 8×2 DataFrame Row │ c x │ Int64 Int64 ─────┼────────────── 1 │ 1 3 2 │ 2 3 3 │ 3 5 4 │ 4 5 5 │ 5 7 6 │ 6 7 7 │ 7 9 8 │ 8 9ERROR: LoadError: MethodError: no method matching fun_to_vec(::QuoteNode; gensym_names::Bool, outer_flags::NamedTuple{(Symbol("@byrow"), Symbol("@passmissing"), Symbol("@astable")), Tuple{Base.RefValue{Bool}, Base.RefValue{Bool}, Base.RefValue{Bool}}}, allow_multicol::Bool) Closest candidates are: fun_to_vec(::QuoteNode; no_dest, gensym_names, outer_flags) got unsupported keyword argument "allow_multicol" @ DataFramesMeta ~/work/DataFramesMeta.jl/DataFramesMeta.jl/src/parsing.jl:430 fun_to_vec(!Matched::Expr; gensym_names, outer_flags, no_dest, allow_multicol) @ DataFramesMeta ~/work/DataFramesMeta.jl/DataFramesMeta.jl/src/parsing.jl:322 Stacktrace: [1] kwerr(::NamedTuple{(:gensym_names, :outer_flags, :allow_multicol), Tuple{Bool, NamedTuple{(Symbol("@byrow"), Symbol("@passmissing"), Symbol("@astable")), Tuple{Base.RefValu

doctest failure in ~/work/DataFramesMeta.jl/DataFramesMeta.jl/src/macros.jl:2527-2547 ```jldoctest julia> using DataFramesMeta; julia> df = DataFrame(x = 1:10, y = 10:-1:1); julia> @distinct(df, :x .+ :y) 1×2 DataFrame Row │ x y │ Int64 Int64 ─────┼─────────────── 1 │ 1 10 julia> @distinct df begin :x .+ :y end 1×2 DataFrame Row │ x y │ Int64 Int64 ─────┼─────────────── 1 │ 1 10 ``` Subexpression: @distinct(df, :x .+ :y) Evaluated output: 1×2 DataFrame Row │ x y │ Int64 Int64 ─────┼────────────── 1 │ 1 10 Expected output: 1×2 DataFrame Row │ x y │ Int64 Int64 ─────┼─────────────── 1 │ 1 10 diff = Warning: Diff output requires color. 1×2 DataFrame Row │ x y y │ Int64 Int64 ─────┼─────────────── Int64 ─────┼────────────── 1 │ 1 1 10

doctest failure in ~/work/DataFramesMeta.jl/DataFramesMeta.jl/src/macros.jl:2527-2547 ```jldoctest julia> using DataFramesMeta; julia> df = DataFrame(x = 1:10, y = 10:-1:1); julia> @distinct(df, :x .+ :y) 1×2 DataFrame Row │ x y │ Int64 Int64 ─────┼─────────────── 1 │ 1 10 julia> @distinct df begin :x .+ :y end 1×2 DataFrame Row │ x y │ Int64 Int64 ─────┼─────────────── 1 │ 1 10 ``` Subexpression: @distinct df begin :x .+ :y end Evaluated output: 1×2 DataFrame Row │ x y │ Int64 Int64 ─────┼────────────── 1 │ 1 10 Expected output: 1×2 DataFrame Row │ x y │ Int64 Int64 ─────┼─────────────── 1 │ 1 10 diff = Warning: Diff output requires color. 1×2 DataFrame Row │ x y y │ Int64 Int64 ─────┼─────────────── Int64 ─────┼────────────── 1 │ 1 1 10

doctest failure in ~/work/DataFramesMeta.jl/DataFramesMeta.jl/src/macros.jl:1315-1387 ```jldoctest julia> using DataFramesMeta, Statistics julia> d = DataFrame(x = [3, 3, 3, 2, 1, 1, 1, 2, 1, 1], n = 1:10, c = ["a", "c", "b", "e", "d", "g", "f", "i", "j", "h"]); julia> @orderby(d, -:n) 10×3 DataFrame Row │ x n c │ Int64 Int64 String ─────┼────────────────────── 1 │ 1 10 h 2 │ 1 9 j 3 │ 2 8 i 4 │ 1 7 f 5 │ 1 6 g 6 │ 1 5 d 7 │ 2 4 e 8 │ 3 3 b 9 │ 3 2 c 10 │ 3 1 a julia> @orderby(d, invperm(sortperm(:c, rev = true))) 10×3 DataFrame Row │ x n c │ Int64 Int64 String ─────┼────────────────────── 1 │ 1 9 j 2 │ 2 8 i 3 │ 1 10 h 4 │ 1 6 g 5 │ 1 7 f 6 │ 2 4 e 7 │ 1 5 d 8 │ 3 2 c 9 │ 3 3 b 10 │ 3 1 a julia> @orderby d begin :x abs.(:n .- mean(:n)) end 10×3 DataFrame Row │ x n c │ Int64 Int64 String ─────┼────────────────────── 1 │ 1 5 e 2 │ 1 6 f 3 │ 1 7 g 4 │ 1 9 i 5 │ 1 10 j 6 │ 2 4 d 7 │ 2 8 h 8 │ 3 3 c 9 │ 3 2 b 10 │ 3 1 a julia> @orderby d @byrow :x^2 10×3 DataFrame Row │ x n c │ Int64 Int64 String ─────┼────────────────────── 1 │ 1 5 e 2 │ 1 6 f 3 │ 1 7 g 4 │ 1 9 i 5 │ 1 10 j 6 │ 2 4 d 7 │ 2 8 h 8 │ 3 1 a 9 │ 3 2 b 10 │ 3 3 c ``` Subexpression: @orderby d begin :x abs.(:n .- mean(:n)) end Evaluated output: 10×3 DataFrame Row │ x n c │ Int64 Int64 String ─────┼────────────────────── 1 │ 1 5 d 2 │ 1 6 g 3 │ 1 7 f 4 │ 1 9 j 5 │ 1 10 h 6 │ 2 4 e 7 │ 2 8 i 8 │ 3 3 b 9 │ 3 2 c 10 │ 3 1 a Expected output: 10×3 DataFrame Row │ x n c │ Int64 Int64 String ─────┼────────────────────── 1 │ 1 5 e 2 │ 1 6 f 3 │ 1 7 g 4 │ 1 9 i 5 │ 1 10 j 6 │ 2 4 d 7 │ 2 8 h 8 │ 3 3 c 9 │ 3 2 b 10 │ 3 1 a diff = Warning: Diff output requires color. 10×3 DataFrame Row │ x n c │ Int64 Int64 String ─────┼────────────────────── 1 │ 1 5 e d 2 │ 1 6 f g 3 │ 1 7 g f 4 │ 1 9 i j 5 │ 1 10 j h 6 │ 2 4 d e 7 │ 2 8 h i 8 │ 3 3 c b 9 │ 3 2 b c 10 │ 3 1 a

doctest failure in ~/work/DataFramesMeta.jl/DataFramesMeta.jl/src/macros.jl:1315-1387 ```jldoctest julia> using DataFramesMeta, Statistics julia> d = DataFrame(x = [3, 3, 3, 2, 1, 1, 1, 2, 1, 1], n = 1:10, c = ["a", "c", "b", "e", "d", "g", "f", "i", "j", "h"]); julia> @orderby(d, -:n) 10×3 DataFrame Row │ x n c │ Int64 Int64 String ─────┼────────────────────── 1 │ 1 10 h 2 │ 1 9 j 3 │ 2 8 i 4 │ 1 7 f 5 │ 1 6 g 6 │ 1 5 d 7 │ 2 4 e 8 │ 3 3 b 9 │ 3 2 c 10 │ 3 1 a julia> @orderby(d, invperm(sortperm(:c, rev = true))) 10×3 DataFrame Row │ x n c │ Int64 Int64 String ─────┼────────────────────── 1 │ 1 9 j 2 │ 2 8 i 3 │ 1 10 h 4 │ 1 6 g 5 │ 1 7 f 6 │ 2 4 e 7 │ 1 5 d 8 │ 3 2 c 9 │ 3 3 b 10 │ 3 1 a julia> @orderby d begin :x abs.(:n .- mean(:n)) end 10×3 DataFrame Row │ x n c │ Int64 Int64 String ─────┼────────────────────── 1 │ 1 5 e 2 │ 1 6 f 3 │ 1 7 g 4 │ 1 9 i 5 │ 1 10 j 6 │ 2 4 d 7 │ 2 8 h 8 │ 3 3 c 9 │ 3 2 b 10 │ 3 1 a julia> @orderby d @byrow :x^2 10×3 DataFrame Row │ x n c │ Int64 Int64 String ─────┼────────────────────── 1 │ 1 5 e 2 │ 1 6 f 3 │ 1 7 g 4 │ 1 9 i 5 │ 1 10 j 6 │ 2 4 d 7 │ 2 8 h 8 │ 3 1 a 9 │ 3 2 b 10 │ 3 3 c ``` Subexpression: @orderby d @byrow :x^2 Evaluated output: 10×3 DataFrame Row │ x n c │ Int64 Int64 String ─────┼────────────────────── 1 │ 1 5 d 2 │ 1 6 g 3 │ 1 7 f 4 │ 1 9 j 5 │ 1 10 h 6 │ 2 4 e 7 │ 2 8 i 8 │ 3 1 a 9 │ 3 2 c 10 │ 3 3 b Expected output: 10×3 DataFrame Row │ x n c │ Int64 Int64 String ─────┼────────────────────── 1 │ 1 5 e 2 │ 1 6 f 3 │ 1 7 g 4 │ 1 9 i 5 │ 1 10 j 6 │ 2 4 d 7 │ 2 8 h 8 │ 3 1 a 9 │ 3 2 b 10 │ 3 3 c diff = Warning: Diff output requires color. 10×3 DataFrame Row │ x n c │ Int64 Int64 String ─────┼────────────────────── 1 │ 1 5 e d 2 │ 1 6 f g 3 │ 1 7 g f 4 │ 1 9 i j 5 │ 1 10 j h 6 │ 2 4 d e 7 │ 2 8 h i 8 │ 3 1 a 9 │ 3 2 b c 10 │ 3 3 cb

doctest failure in ~/work/DataFramesMeta.jl/DataFramesMeta.jl/src/macros.jl:1131-1205 ```jldoctest julia> using DataFramesMeta, Statistics julia> df = DataFrame(x = 1:3, y = [2, 1, 2]); julia> globalvar = [2, 1, 0]; julia> @subset!(copy(df), :x .> 1) 2×2 DataFrame Row │ x y │ Int64 Int64 ─────┼────────────── 1 │ 2 1 2 │ 3 2 julia> @subset!(copy(df), :x .> globalvar) 2×2 DataFrame Row │ x y │ Int64 Int64 ─────┼────────────── 1 │ 2 1 2 │ 3 2 julia> @subset! copy(df) begin :x .> globalvar :y .== 3 end 0×2 DataFrame julia> df = DataFrame(n = 1:20, x = [3, 3, 3, 3, 1, 1, 1, 2, 1, 1, 2, 1, 1, 2, 2, 2, 3, 1, 1, 2]); julia> g = groupby(copy(df), :x); julia> @subset!(g, :n .> mean(:n)) 8×2 DataFrame Row │ n x │ Int64 Int64 ─────┼────────────── 1 │ 12 1 2 │ 13 1 3 │ 15 2 4 │ 16 2 5 │ 17 3 6 │ 18 1 7 │ 19 1 8 │ 20 2 julia> g = groupby(copy(df), :x); julia> @subset! g begin :n .> mean(:n) :n .< 20 end 7×2 DataFrame Row │ n x │ Int64 Int64 ─────┼────────────── 1 │ 12 1 2 │ 13 1 3 │ 15 2 4 │ 16 2 5 │ 17 3 6 │ 18 1 7 │ 19 1 julia> d = DataFrame(a = [1, 2, missing], b = ["x", "y", missing]); julia> @subset!(d, :a .== 1) 1×2 DataFrame Row │ a b │ Int64? String? ─────┼───────────────── 1 │ 1 x ``` Subexpression: @subset! copy(df) begin :x .> globalvar :y .== 3 end Evaluated output: 0×2 DataFrame Row │ x y │ Int64 Int64 ─────┴────────────── Expected output: 0×2 DataFrame diff = Warning: Diff output requires color. 0×2 DataFrameDataFrame Row │ x y │ Int64 Int64 ─────┴──────────────

doctest failure in ~/work/DataFramesMeta.jl/DataFramesMeta.jl/src/macros.jl:979-1009 ```jldoctest julia> using DataFramesMeta julia> df = DataFrame(A=1:5, B=["apple", "pear", "apple", "orange", "pear"]) 5×2 DataFrame Row │ A B │ Int64 String ─────┼─────────────── 1 │ 1 apple 2 │ 2 pear 3 │ 3 apple 4 │ 4 orange 5 │ 5 pear julia> @rsubset df :A > 3 2×2 DataFrame Row │ A B │ Int64 String ─────┼─────────────── 1 │ 4 orange 2 │ 5 pear julia> @rsubset df :A > 3 || :B == "pear" 3×2 DataFrame Row │ A B │ Int64 String ─────┼─────────────── 1 │ 2 pear 2 │ 4 orange 3 │ 5 pear ``` Subexpression: @rsubset df :A > 3 || :B == "pear" Evaluated output: 3×2 DataFrame Row │ A B │ Int64 String ─────┼─────────────── 1 │ 2 pear 2 │ 4 orange 3 │ 5 pear Expected output: 3×2 DataFrame Row │ A B │ Int64 String ─────┼─────────────── 1 │ 2 pear 2 │ 4 orange 3 │ 5 pear diff = Warning: Diff output requires color. 3×2 DataFrame DataFrame Row │ A B B │ Int64 String ─────┼─────────────── String ─────┼─────────────── 1 │ 2 pear pear 2 │ 4 orange orange 3 │ 5 pear

doctest failure in ~/work/DataFramesMeta.jl/DataFramesMeta.jl/src/macros.jl:863-954 ```jldoctest julia> using DataFramesMeta, Statistics julia> df = DataFrame(x = 1:3, y = [2, 1, 2]); julia> globalvar = [2, 1, 0]; julia> @subset(df, :x .> 1) 2×2 DataFrame Row │ x y │ Int64 Int64 ─────┼────────────── 1 │ 2 1 2 │ 3 2 julia> @subset(df, :x .> globalvar) 2×2 DataFrame Row │ x y │ Int64 Int64 ─────┼────────────── 1 │ 2 1 2 │ 3 2 julia> @subset df begin :x .> globalvar :y .== 3 end 0×2 DataFrame julia> df = DataFrame(n = 1:20, x = [3, 3, 3, 3, 1, 1, 1, 2, 1, 1, 2, 1, 1, 2, 2, 2, 3, 1, 1, 2]); julia> g = groupby(df, :x); julia> @subset(g, :n .> mean(:n)) 8×2 DataFrame Row │ n x │ Int64 Int64 ─────┼────────────── 1 │ 12 1 2 │ 13 1 3 │ 15 2 4 │ 16 2 5 │ 17 3 6 │ 18 1 7 │ 19 1 8 │ 20 2 julia> @subset g begin :n .> mean(:n) :n .< 20 end 7×2 DataFrame Row │ n x │ Int64 Int64 ─────┼────────────── 1 │ 12 1 2 │ 13 1 3 │ 15 2 4 │ 16 2 5 │ 17 3 6 │ 18 1 7 │ 19 1 julia> df = DataFrame(a = [1, 2, missing], b = ["x", "y", missing]); julia> @subset(df, :a .== 1) 1×2 DataFrame Row │ a b │ Int64? String? ─────┼───────────────── 1 │ 1 x julia> @subset(df, :a .< 3; view = true) 2×2 SubDataFrame Row │ a b │ Int64? String? ─────┼───────────────── 1 │ 1 x 2 │ 2 y julia> @subset df begin :a .< 3 @kwarg view = true end 2×2 SubDataFrame Row │ a b │ Int64? String? ─────┼───────────────── 1 │ 1 x 2 │ 2 y ``` Subexpression: @subset df begin :x .> globalvar :y .== 3 end Evaluated output: 0×2 DataFrame Row │ x y │ Int64 Int64 ─────┴────────────── Expected output: 0×2 DataFrame diff = Warning: Diff output requires color. 0×2 DataFrameDataFrame Row │ x y │ Int64 Int64 ─────┴──────────────

doctest failure in ~/work/DataFramesMeta.jl/DataFramesMeta.jl/src/macros.jl:1410-1447 ```jldoctest julia> using DataFramesMeta julia> df = DataFrame(x = [8,8,-8,7,7,-7], y = [-1, 1, -2, 2, -3, 3]) 6×2 DataFrame Row │ x y │ Int64 Int64 ─────┼────────────── 1 │ 8 -1 2 │ 8 1 3 │ -8 -2 4 │ 7 2 5 │ 7 -3 6 │ -7 3 julia> @rorderby df abs(:x) (:x * :y^3) Row │ x y │ Int64 Int64 ─────┼────────────── 1 │ 7 -3 2 │ -7 3 3 │ 7 2 4 │ 8 -1 5 │ 8 1 6 │ -8 -2 julia> @rorderby df :y == 2 ? -:x : :y 6×2 DataFrame Row │ x y │ Int64 Int64 ─────┼────────────── 1 │ 7 2 2 │ 7 -3 3 │ -8 -2 4 │ 8 -1 5 │ 8 1 6 │ -7 3 ``` Subexpression: @rorderby df abs(:x) (:x * :y^3) Evaluated output: 6×2 DataFrame Row │ x y │ Int64 Int64 ─────┼────────────── 1 │ 7 -3 2 │ -7 3 3 │ 7 2 4 │ 8 -1 5 │ 8 1 6 │ -8 -2 Expected output: Row │ x y │ Int64 Int64 ─────┼────────────── 1 │ 7 -3 2 │ -7 3 3 │ 7 2 4 │ 8 -1 5 │ 8 1 6 │ -8 -2 diff = Warning: Diff output requires color. 6×2 DataFrame Row │ x y │ Int64 Int64 ─────┼────────────── 1 │ 7 -3 2 │ -7 3 3 │ 7 2 4 │ 8 -1 5 │ 8 1 6 │ -8 -2

6 docstrings not included in the manual: DataFramesMeta.get_column_expr :: Tuple{Any} DataFramesMeta.get_source_fun :: Tuple{Any} DataFramesMeta.rename_kw_to_pair :: Tuple{Expr} DataFramesMeta.@col :: Tuple{Any} DataFramesMeta.check_macro_flags_consistency :: Tuple{Any} DataFramesMeta.create_args_vector! :: Tuple{Any, Any} These are docstrings in the checked modules (configured with the modules keyword) that are not included in @docs or @autodocs blocks.

The following actions uses node12 which is deprecated and will be forced to run on node16: actions/checkout@v2. For more info: https://github.blog/changelog/2023-06-13-github-actions-all-actions-will-run-on-node16-instead-of-node12-by-default/