Add transformation and renaming to select and select!

docs/src/lib/types.md

@@ -57,6 +57,9 @@ The `RepeatedVector` and `StackedVector` types are subtypes of `AbstractVector`
 with the exception that they are read only. Note that they are not exported and should not be constructed directly,
 but they are columns of a `DataFrame` returned by `stack` with `view=true`.
 
+The `ByRow` type is a special type used for selection operations to signal that the wrapped function should be applied
+to each element (row) of the selection.
+
 ## [The design of handling of columns of a `DataFrame`](@id man-columnhandling)
 
 When a `DataFrame` is constructed columns are copied by default. You can disable
@@ -111,6 +114,7 @@ without caution because:
 
 ```@docs
 AbstractDataFrame
+ByRow
 DataFrame
 DataFrameRow
 GroupedDataFrame

docs/src/man/getting_started.md

@@ -522,11 +522,14 @@ julia> df[in.(df.A, Ref([1, 5, 601])), :]
 │ 3   │ 601   │ 7     │ 301   │
 ```
 
-Equivalently, the `in` function can be called with a single argument to create a function object that tests whether each value belongs to the subset (partial application of `in`): `df[in([1, 5, 601]).(df.A), :]`.
+Equivalently, the `in` function can be called with a single argument to create
+a function object that tests whether each value belongs to the subset
+(partial application of `in`): `df[in([1, 5, 601]).(df.A), :]`.
 
 #### Column selection using `select` and `select!`
 
-You can also use the [`select`](@ref) and [`select!`](@ref) functions to select columns in a data frame.
+You can also use the [`select`](@ref) and [`select!`](@ref) functions to select,
+rename and transform columns in a data frame.
 
 The `select` function creates a new data frame:
 ```jldoctest dataframe
@@ -550,6 +553,27 @@ julia> select(df, r"x") # select columns containing 'x' character
 │     │ Int64 │ Int64 │
 ├─────┼───────┼───────┤
 │ 1   │ 1     │ 2     │
+
+julia> select(df, :x1 => :a1, :x2 => :a2) # rename columns
+1×2 DataFrame
+│ Row │ a1    │ a2    │
+│     │ Int64 │ Int64 │
+├─────┼───────┼───────┤
+│ 1   │ 1     │ 2     │
+
+julia> select(df, :x1, :x2 => (x -> 2x) => :x2) # transform columns
+1×2 DataFrame
+│ Row │ x1    │ x2    │
+│     │ Int64 │ Int64 │
+├─────┼───────┼───────┤
+│ 1   │ 1     │ 4     │
+
+julia> select(df, :x1, :x2 => ByRow(UInt8) => :x2) # transform columns by row
+1×2 DataFrame
+│ Row │ x1    │ x2    │
+│     │ Int64 │ UInt8 │
+├─────┼───────┼───────┤
+│ 1   │ 1     │ 0x02  │
 ```
 
 It is important to note that `select` always returns a data frame,

src/DataFrames.jl

@@ -15,6 +15,7 @@ import DataAPI.All,
 export AbstractDataFrame,
        All,
        Between,
+       ByRow,
        DataFrame,
        DataFrame!,
        DataFrameRow,
@@ -80,6 +81,7 @@ include("dataframerow/utils.jl")
 
 include("other/broadcasting.jl")
 
+include("abstractdataframe/selection.jl")
 include("abstractdataframe/iteration.jl")
 include("abstractdataframe/join.jl")
 include("abstractdataframe/reshape.jl")