broadcast in DataFrames.jl

docs/src/man/getting_started.md

@@ -471,3 +471,70 @@ CSV.write(output, df)
 ```
 
 The behavior of CSV functions can be adapted via keyword arguments. For more information, see `?CSV.read` and `?CSV.write`, or checkout the online [CSV.jl documentation](https://juliadata.github.io/CSV.jl/stable/).
+
+## Broadcasting
+
+When you broadcast a function over an `AbstractDataFrame` it is treated as an `AbstractVector` of rows and each row is represented as a `DataFrameRow`:
+
+```jldoctest dataframe
+julia> df = DataFrame(A = 1:3, B = 3:-1:1)
+3×2 DataFrame
+│ Row │ A     │ B     │
+│     │ Int64 │ Int64 │
+├─────┼───────┼───────┤
+│ 1   │ 1     │ 3     │
+│ 2   │ 2     │ 2     │
+│ 3   │ 3     │ 1     │
+
+julia> identity.(df)
+3-element Array{DataFrameRow{DataFrame},1}:
+ DataFrameRow (row 1)
+A  1
+B  3
+ DataFrameRow (row 2)
+A  2
+B  2
+ DataFrameRow (row 3)
+A  3
+B  1
+
+julia> copy.(df)
+3-element Array{NamedTuple{(:A, :B),Tuple{Int64,Int64}},1}:
+ (A = 1, B = 3)
+ (A = 2, B = 2)
+ (A = 3, B = 1)
+ ```
+
+In the last example we used the `copy` function which transforms a `DataFrameRow` into a `NamedTuple`.
+
+A `DataFrameRow` is treated as a collection of values stored in its columns so you can apply to it standard functions that accept collections and also broadcast functions over it to get a vector:
+
+```jldoctest dataframe
+julia> df = DataFrame(A = 1:3, B = 3:-1:1)
+3×2 DataFrame
+│ Row │ A     │ B     │
+│     │ Int64 │ Int64 │
+├─────┼───────┼───────┤
+│ 1   │ 1     │ 3     │
+│ 2   │ 2     │ 2     │
+│ 3   │ 3     │ 1     │
+
+julia> dfr = df[1, :]
+DataFrameRow (row 1)
+A  1
+B  3
+
+julia> sum(dfr)
+4
+
+julia> string.(dfr)
+2-element Array{String,1}:
+ "1"
+ "3"
+
+julia> (row -> string.(row)).(df)
+3-element Array{Array{String,1},1}:
+ ["1", "3"]
+ ["2", "2"]
+ ["3", "1"]
+```

src/abstractdataframe/abstractdataframe.jl

@@ -223,6 +223,8 @@ Base.axes(df::AbstractDataFrame, i::Integer) = axes(df)[i]
 
 Base.ndims(::AbstractDataFrame) = 2
 
+Base.broadcastable(adf::AbstractDataFrame) = eachrow(adf)
+
 Base.getproperty(df::AbstractDataFrame, col_ind::Symbol) = getindex(df, col_ind)
 Base.setproperty!(df::AbstractDataFrame, col_ind::Symbol, x) = setindex!(df, x, col_ind)
 # Private fields are never exposed since they can conflict with column names

test/broadcasting.jl

@@ -0,0 +1,9 @@
+module TestDataFrame
+    using DataFrames, Test
+
+    @testset "broadcast DataFrame & DataFrameRow" begin
+        df = DataFrame(x=1:4, y=5:8, z=9:12)
+        @test sum.(df) == [15, 18, 21, 24]
+        @test ((row -> row .+ 1)).(df) == [i .+ [0, 4, 8] for i in 2:5]
+    end
+end

test/runtests.jl

@@ -27,6 +27,7 @@ my_tests = ["utils.jl",
             "tables.jl",
             "tabletraits.jl",
             "indexing.jl",
+            "broadcasting.jl",
             "deprecated.jl"]
 
 println("Running tests:")