add fix (#397) #540
Annotations
8 errors, 11 warnings, and 1 notice
|
src/macros.jl#L2532
doctest failure in ~/work/DataFramesMeta.jl/DataFramesMeta.jl/src/macros.jl:2532-2552
```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
|
|
src/macros.jl#L2532
doctest failure in ~/work/DataFramesMeta.jl/DataFramesMeta.jl/src/macros.jl:2532-2552
```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
|
|
src/macros.jl#L862
doctest failure in ~/work/DataFramesMeta.jl/DataFramesMeta.jl/src/macros.jl:862-953
```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
─────┴──────────────
|
|
src/macros.jl#L978
doctest failure in ~/work/DataFramesMeta.jl/DataFramesMeta.jl/src/macros.jl:978-1008
```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
|
|
src/macros.jl#L1314
doctest failure in ~/work/DataFramesMeta.jl/DataFramesMeta.jl/src/macros.jl:1314-1386
```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
|
|
src/macros.jl#L1314
doctest failure in ~/work/DataFramesMeta.jl/DataFramesMeta.jl/src/macros.jl:1314-1386
```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
|
|
src/macros.jl#L1409
doctest failure in ~/work/DataFramesMeta.jl/DataFramesMeta.jl/src/macros.jl:1409-1446
```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
|
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src/macros.jl#L1130
doctest failure in ~/work/DataFramesMeta.jl/DataFramesMeta.jl/src/macros.jl:1130-1204
```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
─────┴──────────────
|
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../../../.julia/packages/Documenter/bYYzK/src/Utilities/Utilities.jl#L34
6 docstrings not included in the manual:
DataFramesMeta.get_source_fun :: Tuple{Any}
DataFramesMeta.get_column_expr :: Tuple{Any}
DataFramesMeta.create_args_vector! :: Tuple{Any, Any}
DataFramesMeta.rename_kw_to_pair :: Tuple{Expr}
DataFramesMeta.@col :: Tuple{Any}
DataFramesMeta.check_macro_flags_consistency :: Tuple{Any}
These are docstrings in the checked modules (configured with the modules keyword)
that are not included in @docs or @autodocs blocks.
|
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../../../.julia/packages/Documenter/bYYzK/src/Documenter.jl#L800
removing `stable` and linking `stable` to `v0.15.2`.
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../../../.julia/packages/Documenter/bYYzK/src/Documenter.jl#L800
removing `v0.15` and linking `v0.15` to `v0.15.2`.
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../../../.julia/packages/Documenter/bYYzK/src/Documenter.jl#L800
removing `v0.14` and linking `v0.14` to `v0.14.2`.
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../../../.julia/packages/Documenter/bYYzK/src/Documenter.jl#L800
removing `v0.13` and linking `v0.13` to `v0.13.0`.
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../../../.julia/packages/Documenter/bYYzK/src/Documenter.jl#L800
removing `v0.11` and linking `v0.11` to `v0.11.0`.
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../../../.julia/packages/Documenter/bYYzK/src/Documenter.jl#L800
removing `v0.10` and linking `v0.10` to `v0.10.0`.
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../../../.julia/packages/Documenter/bYYzK/src/Documenter.jl#L800
removing `v0.9` and linking `v0.9` to `v0.9.1`.
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../../../.julia/packages/Documenter/bYYzK/src/Documenter.jl#L800
removing `v0.8` and linking `v0.8` to `v0.8.0`.
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../../../.julia/packages/Documenter/bYYzK/src/Documenter.jl#L800
removing `v0.7` and linking `v0.7` to `v0.7.1`.
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Consider using `julia-actions/cache` to speed up runs https://github.com/julia-actions/cache. To ignore, set input `ignore-no-cache: true`
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