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Overload makeunique to allow true/false, certain keywords (:update, :… #3373

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Overload makeunique to allow true/false, certain keywords (:update, :… #3373

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106 changes: 63 additions & 43 deletions src/abstractdataframe/abstractdataframe.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -117,9 +117,9 @@ Compat.hasproperty(df::AbstractDataFrame, s::AbstractString) = haskey(index(df),

"""
rename!(df::AbstractDataFrame, vals::AbstractVector{Symbol};
makeunique::Bool=false)
makeunique=false)
rename!(df::AbstractDataFrame, vals::AbstractVector{<:AbstractString};
makeunique::Bool=false)
makeunique=false)
rename!(df::AbstractDataFrame, (from => to)::Pair...)
rename!(df::AbstractDataFrame, d::AbstractDict)
rename!(df::AbstractDataFrame, d::AbstractVector{<:Pair})
Expand All @@ -138,7 +138,8 @@ Each name is changed at most once. Permutation of names is allowed.
of the same length as the number of columns in `df`
- `makeunique` : if `false` (the default), an error will be raised
if duplicate names are found; if `true`, duplicate names will be suffixed
with `_i` (`i` starting at 1 for the first duplicate).
with `_i` (`i` starting at 1 for the first duplicate). If a Function of two
inputs will use that function to combine the duplicate column with the original

If pairs are passed to `rename!` (as positional arguments or in a dictionary or
a vector) then:
Expand Down Expand Up @@ -197,15 +198,15 @@ julia> rename!(uppercase, df)
```
"""
function rename!(df::AbstractDataFrame, vals::AbstractVector{Symbol};
makeunique::Bool=false)
makeunique=false)
rename!(index(df), vals, makeunique=makeunique)
# renaming columns of SubDataFrame has to clean non-note metadata in its parent
_drop_all_nonnote_metadata!(parent(df))
return df
end

function rename!(df::AbstractDataFrame, vals::AbstractVector{<:AbstractString};
makeunique::Bool=false)
makeunique=false)
rename!(index(df), Symbol.(vals), makeunique=makeunique)
# renaming columns of SubDataFrame has to clean non-note metadata in its parent
_drop_all_nonnote_metadata!(parent(df))
Expand Down Expand Up @@ -261,9 +262,9 @@ end

"""
rename(df::AbstractDataFrame, vals::AbstractVector{Symbol};
makeunique::Bool=false)
makeunique=false)
rename(df::AbstractDataFrame, vals::AbstractVector{<:AbstractString};
makeunique::Bool=false)
makeunique=false)
rename(df::AbstractDataFrame, (from => to)::Pair...)
rename(df::AbstractDataFrame, d::AbstractDict)
rename(df::AbstractDataFrame, d::AbstractVector{<:Pair})
Expand Down Expand Up @@ -353,9 +354,9 @@ julia> rename(uppercase, df)
```
"""
rename(df::AbstractDataFrame, vals::AbstractVector{Symbol};
makeunique::Bool=false) = rename!(copy(df), vals, makeunique=makeunique)
makeunique=false) = rename!(copy(df), vals, makeunique=makeunique)
rename(df::AbstractDataFrame, vals::AbstractVector{<:AbstractString};
makeunique::Bool=false) = rename!(copy(df), vals, makeunique=makeunique)
makeunique=false) = rename!(copy(df), vals, makeunique=makeunique)
rename(df::AbstractDataFrame, args...) = rename!(copy(df), args...)
rename(f::Function, df::AbstractDataFrame) = rename!(f, copy(df))

Expand Down Expand Up @@ -1536,13 +1537,15 @@ end

"""
hcat(df::AbstractDataFrame...;
makeunique::Bool=false, copycols::Bool=true)
makeunique=false, copycols::Bool=true)

Horizontally concatenate data frames.

If `makeunique=false` (the default) column names of passed objects must be unique.
If `makeunique=true` then duplicate column names will be suffixed
with `_i` (`i` starting at 1 for the first duplicate).
If `makeunique` is a Function of two inputs then will use that function to combine
the left-hand values with the right-hand values in the duplicated columns.

If `copycols=true` (the default) then the `DataFrame` returned by `hcat` will
contain copied columns from the source data frames.
Expand Down Expand Up @@ -1593,24 +1596,23 @@ julia> df3.A === df1.A
true
```
"""
function Base.hcat(df::AbstractDataFrame; makeunique::Bool=false, copycols::Bool=true)
function Base.hcat(df::AbstractDataFrame; makeunique=false, copycols::Bool=true)
df = DataFrame(df, copycols=copycols)
_drop_all_nonnote_metadata!(df)
return df
end

# TODO: after deprecation remove AbstractVector methods
Base.hcat(df::AbstractDataFrame, x::AbstractVector; makeunique::Bool=false, copycols::Bool=true) =
Base.hcat(df::AbstractDataFrame, x::AbstractVector; makeunique=false, copycols::Bool=true) =
hcat!(DataFrame(df, copycols=copycols), x, makeunique=makeunique, copycols=copycols)
Base.hcat(x::AbstractVector, df::AbstractDataFrame; makeunique::Bool=false, copycols::Bool=true) =
Base.hcat(x::AbstractVector, df::AbstractDataFrame; makeunique=false, copycols::Bool=true) =
hcat!(x, df, makeunique=makeunique, copycols=copycols)
Base.hcat(df1::AbstractDataFrame, df2::AbstractDataFrame;
makeunique::Bool=false, copycols::Bool=true) =
hcat!(DataFrame(df1, copycols=copycols), df2,
makeunique=makeunique, copycols=copycols)
makeunique=false, copycols::Bool=true) =
hcat!(DataFrame(df1, copycols=copycols), df2, makeunique=makeunique, copycols=copycols)
Base.hcat(df::AbstractDataFrame, x::Union{AbstractVector, AbstractDataFrame},
y::Union{AbstractVector, AbstractDataFrame}...;
makeunique::Bool=false, copycols::Bool=true) =
makeunique=false, copycols::Bool=true) =
hcat!(hcat(df, x, makeunique=makeunique, copycols=copycols), y...,
makeunique=makeunique, copycols=copycols)

Expand Down Expand Up @@ -2869,7 +2871,8 @@ const INSERTCOLS_ARGUMENTS =
- `after` : if `true` columns are inserted after `col`
- `makeunique` : defines what to do if `name` already exists in `df`;
if it is `false` an error will be thrown; if it is `true` a new unique name will
be generated by adding a suffix
be generated by adding a suffix; if it is a Function then combines the two duplicate
column using that function to combine the left-hand value with the right-hand.
- `copycols` : whether vectors passed as columns should be copied

If `val` is an `AbstractRange` then the result of `collect(val)` is inserted.
Expand All @@ -2891,7 +2894,7 @@ const INSERTCOLS_ARGUMENTS =

"""
insertcols(df::AbstractDataFrame[, col], (name=>val)::Pair...;
after::Bool=false, makeunique::Bool=false, copycols::Bool=true)
after::Bool=false, makeunique=false, copycols::Bool=true)

Insert a column into a copy of `df` data frame using the [`insertcols!`](@ref)
function and return the newly created data frame.
Expand Down Expand Up @@ -2942,13 +2945,13 @@ julia> insertcols(df, :a, :d => 7:9, after=true)
```
"""
insertcols(df::AbstractDataFrame, args...;
after::Bool=false, makeunique::Bool=false, copycols::Bool=true) =
after::Bool=false, makeunique=false, copycols::Bool=true) =
insertcols!(copy(df), args...;
after=after, makeunique=makeunique, copycols=copycols)

"""
insertcols!(df::AbstractDataFrame[, col], (name=>val)::Pair...;
after::Bool=false, makeunique::Bool=false, copycols::Bool=true)
after::Bool=false, makeunique=false, copycols::Bool=true)

Insert a column into a data frame in place. Return the updated data frame.

Expand Down Expand Up @@ -2979,7 +2982,7 @@ julia> insertcols!(df, 1, :b => 'a':'c')
2 │ b 2
3 │ c 3

julia> insertcols!(df, 2, :c => 2:4, :c => 3:5, makeunique=true)
julia> insertcols!(df, 2, :c => 2:4, :c => 3:5, makeunique=false)
3×4 DataFrame
Row │ b c c_1 a
│ Char Int64 Int64 Int64
Expand All @@ -2999,7 +3002,9 @@ julia> insertcols!(df, :b, :d => 7:9, after=true)
```
"""
function insertcols!(df::AbstractDataFrame, col::ColumnIndex, name_cols::Pair{Symbol}...;
after::Bool=false, makeunique::Bool=false, copycols::Bool=true)
after::Bool=false, makeunique=false, copycols::Bool=true)
makeunique = _makeunique_normalize(makeunique)

if !is_column_insertion_allowed(df)
throw(ArgumentError("insertcols! is only supported for DataFrame, or for " *
"SubDataFrame created with `:` as column selector"))
Expand All @@ -3025,15 +3030,15 @@ function insertcols!(df::AbstractDataFrame, col::ColumnIndex, name_cols::Pair{Sy
"$(ncol(df)) columns at index $col_ind"))
end

if !makeunique
if makeunique == false
if !allunique(first.(name_cols))
throw(ArgumentError("Names of columns to be inserted into a data frame " *
"must be unique when `makeunique=true`"))
"must be unique when `makeunique=false`"))
end
for (n, _) in name_cols
if hasproperty(df, n)
throw(ArgumentError("Column $n is already present in the data frame " *
"which is not allowed when `makeunique=true`"))
"which is not allowed when `makeunique=false`"))
end
end
end
Expand Down Expand Up @@ -3103,19 +3108,11 @@ function insertcols!(df::AbstractDataFrame, col::ColumnIndex, name_cols::Pair{Sy
dfp[!, name] = item_new
else
if hasproperty(dfp, name)
@assert makeunique
k = 1
while true
nn = Symbol("$(name)_$k")
if !hasproperty(dfp, nn)
name = nn
break
end
k += 1
end
col_ind = insert_unique(dfp, name, col_ind, item_new, makeunique)
else
insert!(index(dfp), col_ind, name)
insert!(_columns(dfp), col_ind, item_new)
end
insert!(index(dfp), col_ind, name)
insert!(_columns(dfp), col_ind, item_new)
end
col_ind += 1
end
Expand All @@ -3134,22 +3131,22 @@ function insertcols!(df::AbstractDataFrame, col::ColumnIndex, name_cols::Pair{Sy
end

insertcols!(df::AbstractDataFrame, col::ColumnIndex, name_cols::Pair{<:AbstractString}...;
after::Bool=false, makeunique::Bool=false, copycols::Bool=true) =
after::Bool=false, makeunique=false, copycols::Bool=true) =
insertcols!(df, col, (Symbol(n) => v for (n, v) in name_cols)...,
after=after, makeunique=makeunique, copycols=copycols)

insertcols!(df::AbstractDataFrame, name_cols::Pair{Symbol}...;
after::Bool=false, makeunique::Bool=false, copycols::Bool=true) =
after::Bool=false, makeunique=false, copycols::Bool=true) =
insertcols!(df, ncol(df)+1, name_cols..., after=after,
makeunique=makeunique, copycols=copycols)

insertcols!(df::AbstractDataFrame, name_cols::Pair{<:AbstractString}...;
after::Bool=false, makeunique::Bool=false, copycols::Bool=true) =
after::Bool=false, makeunique=false, copycols::Bool=true) =
insertcols!(df, (Symbol(n) => v for (n, v) in name_cols)...,
after=after, makeunique=makeunique, copycols=copycols)

function insertcols!(df::AbstractDataFrame, col::ColumnIndex; after::Bool=false,
makeunique::Bool=false, copycols::Bool=true)
makeunique=false, copycols::Bool=true)
if col isa SymbolOrString
col_ind = Int(columnindex(df, col))
if col_ind == 0
Expand All @@ -3173,11 +3170,34 @@ function insertcols!(df::AbstractDataFrame, col::ColumnIndex; after::Bool=false,
end

function insertcols!(df::AbstractDataFrame; after::Bool=false,
makeunique::Bool=false, copycols::Bool=true)
makeunique=false, copycols::Bool=true)
_drop_all_nonnote_metadata!(parent(df))
return df
end

function insert_unique(dfp, name, col_ind, item_new, makeunique::Bool=false)
if makeunique
k = 1
while true
nn = Symbol("$(name)_$k")
if !hasproperty(dfp, nn)
name = nn
break
end
k += 1
end
insert!(index(dfp), col_ind, name)
insert!(_columns(dfp), col_ind, item_new)
end
col_ind
end

function insert_unique(dfp, name, col_ind, item_new, makeunique::Function)
# Just update by using function without adding to index
dfp[!, name] = makeunique.(dfp[!, name], item_new)
col_ind - 1
end

"""
Iterators.partition(df::AbstractDataFrame, n::Integer)

Expand Down
8 changes: 4 additions & 4 deletions src/abstractdataframe/reshape.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -723,7 +723,7 @@ Base.transpose(::AbstractDataFrame, args...; kwargs...) =
permutedims(df::AbstractDataFrame,
[src_namescol::Union{Int, Symbol, AbstractString}],
[dest_namescol::Union{Symbol, AbstractString}];
makeunique::Bool=false, strict::Bool=true)
makeunique=false, strict::Bool=true)

Turn `df` on its side such that rows become columns
and values in the column indexed by `src_namescol` become the names of new columns.
Expand Down Expand Up @@ -823,7 +823,7 @@ julia> permutedims(df2, 1, "different_name")
"""
function Base.permutedims(df::AbstractDataFrame, src_namescol::ColumnIndex,
dest_namescol::Union{Symbol, AbstractString};
makeunique::Bool=false, strict::Bool=true)
makeunique=false, strict::Bool=true)

if src_namescol isa Integer
1 <= src_namescol <= ncol(df) || throw(BoundsError(index(df), src_namescol))
Expand Down Expand Up @@ -865,7 +865,7 @@ function Base.permutedims(df::AbstractDataFrame, src_namescol::ColumnIndex,
end

function Base.permutedims(df::AbstractDataFrame, src_namescol::ColumnIndex;
makeunique::Bool=false, strict::Bool=true)
makeunique=false, strict::Bool=true)
if src_namescol isa Integer
1 <= src_namescol <= ncol(df) || throw(BoundsError(index(df), src_namescol))
dest_namescol = _names(df)[src_namescol]
Expand All @@ -883,7 +883,7 @@ function Base.permutedims(df::AbstractDataFrame)
end

function Base.permutedims(df::AbstractDataFrame, cnames::AbstractVector;
makeunique::Bool=false)
makeunique=false)
out_df = DataFrame(permutedims(Matrix(df)), cnames, makeunique=makeunique)
_copy_table_note_metadata!(out_df, df)
return out_df
Expand Down
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