Minor cleanup

Author: andreasnoack

src/abstractdataframe/abstractdataframe.jl

@@ -502,7 +502,7 @@ completecases!(df)
 ```
 
 """
-completecases!(df::AbstractDataFrame) = deleterows!(df, find(!completecases(df)))
+completecases!(df::AbstractDataFrame) = deleterows!(df, find(!, completecases(df)))
 
 function Base.convert(::Type{Array}, df::AbstractDataFrame)
     convert(Matrix, df)

src/abstractdataframe/show.jl

@@ -194,7 +194,7 @@ end
 #' chunkbounds = getchunkbounds(maxwidths, true)
 function getchunkbounds(maxwidths::Vector{Int},
                         splitchunks::Bool,
-                        availablewidth::Int=Base.displaysize()[2]) # -> Vector{Int}
+                        availablewidth::Int=displaysize()[2]) # -> Vector{Int}
     ncols = length(maxwidths) - 1
     rowmaxwidth = maxwidths[ncols + 1]
     if splitchunks
@@ -335,7 +335,7 @@ function showrows(io::IO,
     end
 
     rowmaxwidth = maxwidths[ncols + 1]
-    chunkbounds = getchunkbounds(maxwidths, splitchunks, Base.displaysize(io)[2])
+    chunkbounds = getchunkbounds(maxwidths, splitchunks, displaysize(io)[2])
     nchunks = length(chunkbounds) - 1
 
     for chunkindex in 1:nchunks
@@ -438,10 +438,10 @@ end
 function Base.show(io::IO,
                    df::AbstractDataFrame,
                    splitchunks::Bool = true,
-                   rowlabel::Symbol = @compat(Symbol("Row")),
+                   rowlabel::Symbol = Symbol("Row"),
                    displaysummary::Bool = true) # -> Void
     nrows = size(df, 1)
-    dsize = Base.displaysize(io)
+    dsize = displaysize(io)
     availableheight = dsize[1] - 5
     nrowssubset = fld(availableheight, 2)
     bound = min(nrowssubset - 1, nrows)
@@ -516,7 +516,7 @@ end
 function Base.showall(io::IO,
                       df::AbstractDataFrame,
                       splitchunks::Bool = false,
-                      rowlabel::Symbol = @compat(Symbol("Row")),
+                      rowlabel::Symbol = Symbol("Row"),
                       displaysummary::Bool = true) # -> Void
     rowindices1 = 1:size(df, 1)
     rowindices2 = 1:0
@@ -574,33 +574,8 @@ function showcols(io::IO, df::AbstractDataFrame) # -> Void
     metadata = DataFrame(Name = _names(df),
                          Eltype = eltypes(df),
                          Missing = colmissing(df))
-    showall(io, metadata, true, @compat(Symbol("Col #")), false)
+    showall(io, metadata, true, Symbol("Col #"), false)
     return
 end
 
 showcols(df::AbstractDataFrame) = showcols(STDOUT, df) # -> Void
-
-# using Juno
-# using Juno: Inline, LazyTree, Table, Row, strong
-
-# const SIZE = 25
-
-# function to_matrix(df::AbstractDataFrame)
-#     res = Array{Any}(size(df))
-#     for (j, col) in enumerate(columns(df)), i = 1:length(col)
-#         isassigned(col, i) && (res[i, j] = col[i])
-#     end
-#     return res
-# end
-
-# function _render(df::AbstractDataFrame)
-#     width = min(size(df, 2), SIZE)
-#     height = min(size(df, 1), SIZE)
-#     header = map(x->strong(string(x)), names(df)[1:width]')
-#     body = Juno.undefs(to_matrix(df))[1:height, 1:width]
-#     view = Table(vcat(header, body))
-#     LazyTree(Row(typeof(df), text" ", Juno.dims(size(df)...)),
-#              () -> [view])
-# end
-
-# @render Inline df::AbstractDataFrame _render(df)

src/statsmodels/contrasts.jl

@@ -292,6 +292,7 @@ function contrasts_matrix(C::HelmertCoding, baseind, n)
     mat = mat[[baseind; 1:(baseind-1); (baseind+1):end], :]
     return mat
 end
+
 """
     ContrastsCoding(mat::Matrix[, base[, levels]])