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Statistical plotting recipes for Plots.jl

License: Other

Julia 100.00%

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statsplots.jl's Issues

Discussion: new groupapply syntax

More bikeshedding! After fixing the syntax to plot DataFrames in #74, we need to update the groupapply syntax to match it.

Example call (as it is now on master):

grp_error = groupapply(:density, school, :MAch, group = :Sx, compute_error = (:across, :School), axis_type = :continuous, summarize = (mean, sem), bandwidth = 0.5)
plot(grp_error, linewidth = 2)

What this does is to take the :MAch column from the dataframe school, splits by :Sx, splits again by :School, computes the kernel density with bandwidth = 0.5, put back together all the schools using the functions provided in summarize to compute mean and error and then plots the traces corresponding to each:Sx.

Issues:

not compatible with the new syntax
the groupapply call gets messy pretty quiclky and the result is a bit magical

A simple solution of problem 1 would be the obvious translation:

grp_error = @df school groupapply(:density, :MAch, group = :Sx, compute_error = (:across, :School), axis_type = :continuous, summarize = (mean, sem), bandwidth = 0.5)

but problem 2 remains.

A possible proposal is to draw inspiration from the DataFramesMeta syntax (as we did with @df), in particular the @linq macro to concatenate operator. What I'd propose is something along the lines of:

@groupapply school |>
    where(:Minrty .== "Yes") |> # data selection (currently not possible, but I think it can be nice to have)
    group(:Sx) |> # split (correspons do group = :Sx in a plot call)
    compute_error(:across, :School) |> # How to split to compute error (:bootstrap or :none also possible)
    summarize(mean, sem) |> #how to summarize the traces from previous step to get estimate and error
    axis_type(:continuous) |> #define how to treat the x axis: (:binned :discrete or :continuous)
    density(:MAch, bandwidth = 0.5) |> # analysis function (in this case kernel density)
    plot(linewidth = 2) #plot command (if omitted the statistical object is returned instead)

Thoughts? In particular I'd like to understand if we're happy with a more pipeline syntax, what considerations we have about the order of the functions and whether they should be together or separate.

How to do a `groupbar` but sideways?

It's not clear if group at supports plotting the bar side ways. That is the same as barh.

@df df begin ... end no longer works

The latest (0.7.1) release caused a new issue with the @df macro

julia> using Plots, StatPlots, DataFrames

julia> @df DataFrame(x=[1,2], y=[3,4]) begin
       end

julia> @df DataFrame(x=[1,2], y=[3,4]) begin
           plot(:x, :y)
       end
ERROR: StackOverflowError:

This used to work, and was convenient for doing multiple plots.

mm not defined

Something strange is happening in Julia 0.6 with the import of Measures it seems :

using StatPlots
gr(size=(400,300))
using RDatasets
iris = dataset("datasets","iris")
@df iris corrplot([:SepalLength :SepalWidth :PetalLength :PetalWidth], grid = false)

ERROR: UndefVarError: mm not defined
Stacktrace:
 [1] macro expansion at /localhome/romain/.julia/v0.6/StatPlots/src/corrplot.jl:21 [inlined]
 [2] apply_recipe(::Dict{Symbol,Any}, ::StatPlots.CorrPlot) at /localhome/romain/.julia/v0.6/RecipesBase/src/RecipesBase.jl:287
 [3] _process_userrecipes(::Plots.Plot{Plots.GRBackend}, ::Dict{Symbol,Any}, ::Tuple{StatPlots.CorrPlot}) at /localhome/romain/.julia/v0.6/Plots/src/pipeline.jl:81
 [4] _plot!(::Plots.Plot{Plots.GRBackend}, ::Dict{Symbol,Any}, ::Tuple{StatPlots.CorrPlot}) at /localhome/romain/.julia/v0.6/Plots/src/plot.jl:175
 [5] (::RecipesBase.#kw##plot)(::Array{Any,1}, ::RecipesBase.#plot, ::StatPlots.CorrPlot) at ./<missing>:0
 [6] #corrplot#23(::Array{Any,1}, ::Function, ::Array{Float64,2}, ::Vararg{Array{Float64,2},N} where N) at /localhome/romain/.julia/v0.6/RecipesBase/src/RecipesBase.jl:363
 [7] (::StatPlots.#kw##corrplot)(::Array{Any,1}, ::StatPlots.#corrplot, ::Array{Float64,2}, ::Vararg{Array{Float64,2},N} where N) at ./<missing>:0

Caused by margin --> 1mm in corrplot (or any other recipe trying to use mm). This happens both with the tagged version and the latest checkout version.

CorrPlot does not work on DataFrames

Which kind of defeats the purpose

group= plots don't work with DataFrames master

using Plots
using StatPlots
using DataFrames
N = 100
data = DataFrame(a = rand(1:20, N), b = rand(1:20, N), c = rand(1:3, N))
scatter(data, :a, :b, group=:c)

gives

ERROR: LoadError: TypeError: typeassert: expected AbstractArray{Bool,N}, got Array{Nullable{Bool},1}
 in copy!(::Array{Array{Int64,1},1}, ::Base.Generator{Array{Nullable{Int64},1},Plots.##129#131{Array{Nullable{Int64},1}}}) at ./abstractarray.jl:477
 in _collect(::Type{Array{Int64,1}}, ::Base.Generator{Array{Nullable{Int64},1},Plots.##129#131{Array{Nullable{Int64},1}}}, ::Base.HasShape) at ./array.jl:251
 in extractGroupArgs(::Array{Nullable{Int64},1}) at /home/tamas/.julia/v0.5/Plots/src/args.jl:765
 in extractGroupArgs(::Symbol, ::DataFrames.DataFrame, ::Symbol, ::Vararg{Symbol,N}) at /home/tamas/.julia/v0.5/StatPlots/src/dataframes.jl:21
 in _preprocess_args(::Dict{Symbol,Any}, ::Tuple{DataFrames.DataFrame,Symbol,Symbol}, ::Array{RecipesBase.RecipeData,1}) at /home/tamas/.julia/v0.5/Plots/src/pipeline.jl:29
 in _process_userrecipes(::Plots.Plot{Plots.PyPlotBackend}, ::Dict{Symbol,Any}, ::Tuple{DataFrames.DataFrame,Symbol,Symbol}) at /home/tamas/.julia/v0.5/Plots/src/pipeline.jl:60
 in _plot!(::Plots.Plot{Plots.PyPlotBackend}, ::Dict{Symbol,Any}, ::Tuple{DataFrames.DataFrame,Symbol,Symbol}) at /home/tamas/.julia/v0.5/Plots/src/plot.jl:171
 in #plot#261(::Array{Any,1}, ::Function, ::DataFrames.DataFrame, ::Vararg{Any,N}) at /home/tamas/.julia/v0.5/Plots/src/plot.jl:52
 in (::Plots.#kw##plot)(::Array{Any,1}, ::Plots.#plot, ::DataFrames.DataFrame, ::Symbol, ::Vararg{Symbol,N}) at ./<missing>:0
 in #scatter#354(::Array{Any,1}, ::Function, ::DataFrames.DataFrame, ::Vararg{Any,N}) at /home/tamas/.julia/v0.5/Plots/src/Plots.jl:139
 in (::Plots.#kw##scatter)(::Array{Any,1}, ::Plots.#scatter, ::DataFrames.DataFrame, ::Vararg{Any,N}) at ./<missing>:0
 in include_from_node1(::String) at ./loading.jl:488
while loading /tmp/foo.jl, in expression starting on line 6

My Pkg.status() is

53 required packages:
 - Atom                          0.5.8
 - BenchmarkTools                0.0.6
 - CSV                           0.1.2+             master
 - Cairo                         0.2.35
 - Colors                        0.6.9
 - DataFrames                    0.8.3+             master
 - DataFramesMeta                0.1.3
 - Distributions                 0.11.1
 - Documenter                    0.8.0+             master
 - DualNumbers                   0.2.3
 - Fontconfig                    0.1.1
 - ForwardDiff                   0.3.3+             master
 - GLM                           0.6.1
 - GR                            0.18.0
 - GZip                          0.2.20
 - Gadfly                        0.5.2
 - Gallium                       0.0.4
 - IntervalSets                  0.0.2+             master
 - JuliaParser                   0.7.4
 - Klara                         0.7.1+             master
 - Lexicon                       0.1.18
 - Libz                          0.2.2
 - MacroTools                    0.3.4
 - Mamba                         0.10.0
 - Match                         0.3.0
 - MultivariateStats             0.3.1
 - NLopt                         0.3.3
 - NamedArrays                   0.5.3
 - NamedTuples                   1.0.0
 - ObjFileBase                   0.0.4
 - OffsetArrays                  0.2.12
 - Optim                         0.7.4+             master
 - PGFPlots                      1.4.3
 - Parameters                    0.6.0
 - PkgDev                        0.1.3
 - Plotly                        0.1.1
 - Plots                         0.10.3+            master
 - Primes                        0.1.2
 - ProfileView                   0.1.5
 - ProgressMeter                 0.3.3+             progress-count
 - PyPlot                        2.2.4
 - QuantEcon                     0.8.0
 - Query                         0.3.0
 - RDatasets                     0.2.0              master
 - ReverseDiff                   0.0.2
 - Rsvg                          0.0.2
 - Showoff                       0.0.7
 - Sobol                         0.2.0
 - StatPlots                     0.2.1+             master
 - StatsBase                     0.12.0
 - StatsFuns                     0.3.1+             master
 - SuiteSparse                   0.0.1
 - UnicodePlots                  0.2.2
126 additional packages:
 - AMDB                          0.0.0-             master (unregistered, dirty)
 - ASTInterpreter                0.0.4
 - AbstractTrees                 0.0.4
 - ArgParse                      0.4.0
 - AutoAligns                    0.0.0-             master (unregistered, dirty)
 - AutoHashEquals                0.0.10
 - AxisAlgorithms                0.1.5
 - BaseTestNext                  0.2.2
 - BinDeps                       0.4.5
 - Blink                         0.5.0
 - Blosc                         0.1.7
 - BufferedStreams               0.2.3
 - COFF                          0.0.2
 - CRC                           1.2.0
 - Calculus                      0.1.15
 - CategoricalArrays             0.1.0
 - CodeTools                     0.4.3
 - Codecs                        0.2.0
 - ColorBrewer                   0.3.0
 - ColorTypes                    0.2.12
 - ColorVectorSpace              0.1.12
 - Combinatorics                 0.3.2
 - Compat                        0.12.0
 - Compose                       0.4.4
 - Conda                         0.4.0
 - ContinuousTransformations     0.0.0-             master (unregistered)
 - Contour                       0.2.0
 - DSP                           0.1.1
 - DWARF                         0.1.0
 - DataArrays                    0.3.11
 - DataStreams                   0.1.2
 - DataStructures                0.5.1
 - Dates                         0.4.4
 - DebuggingUtilities            0.0.0-             master (unregistered)
 - DiffBase                      0.0.2
 - Discretizers                  0.3.1
 - Distances                     0.3.2
 - DocStringExtensions           0.3.1
 - Docile                        0.5.23
 - ELF                           0.1.0
 - FileIO                        0.2.1
 - FixedPointNumbers             0.2.1
 - FixedSizeArrays               0.2.5
 - Formatting                    0.2.0
 - FunctionWrappers              0.0.1
 - Glob                          1.1.0
 - Graphics                      0.1.3
 - Graphs                        0.7.1
 - Gtk                           0.10.4
 - GtkUtilities                  0.1.0
 - HDF5                          0.7.2
 - Hexagons                      0.0.4
 - Hiccup                        0.1.1
 - HiddenMarkovChains            0.0.0-             master (unregistered)
 - HttpCommon                    0.2.6
 - HttpParser                    0.2.0
 - HttpServer                    0.1.7
 - ImageMagick                   0.1.8
 - ImageView                     0.2.0
 - Images                        0.5.14
 - IndirectInference             0.0.0-             master (unregistered, dirty)
 - IniFile                       0.2.5
 - Interpolations                0.3.6
 - Iterators                     0.2.0
 - JLD                           0.6.8
 - JSON                          0.8.1
 - Juno                          0.2.5
 - KernelDensity                 0.3.0
 - KeyTuples                     0.0.0-             master (unregistered, dirty)
 - LMFlows                       0.0.0-             master (unregistered, dirty)
 - LNR                           0.0.2
 - LaTeXStrings                  0.2.0
 - Lazy                          0.11.5
 - LegacyStrings                 0.2.0
 - LightGraphs                   0.7.2
 - LightXML                      0.4.0
 - LineSearches                  0.1.4
 - Loess                         0.1.0
 - MachO                         0.0.4
 - MathProgBase                  0.5.10
 - MbedTLS                       0.4.2
 - Measures                      0.0.3
 - Media                         0.2.4
 - Mustache                      0.1.3
 - Mux                           0.2.2
 - NaNMath                       0.2.2
 - NativeExpm                    0.0.0-             master (unregistered, dirty)
 - NullableArrays                0.0.10
 - PDMats                        0.5.3
 - ParserCombinator              1.7.11
 - PlotThemes                    0.1.0
 - PlotUtils                     0.3.0
 - PlotlyJS                      0.5.2
 - Polynomials                   0.1.2
 - PositiveFactorizations        0.0.3
 - PosteriorAnalysis             0.0.0-             master (unregistered)
 - PyCall                        1.8.0
 - RData                         0.0.4
 - Ratios                        0.0.4
 - Reactive                      0.3.6
 - RecipesBase                   0.1.0
 - Reel                          0.2.1
 - Reexport                      0.0.3
 - Requests                      0.3.12
 - Requires                      0.3.0
 - ReverseDiffSource             0.3.0
 - Rmath                         0.1.6
 - SHA                           0.3.0
 - SIUnits                       0.1.0
 - SortingAlgorithms             0.1.0
 - StructIO                      0.0.2
 - TerminalUI                    0.0.2
 - TexExtensions                 0.0.3
 - TextDataParsing               0.0.0-             master (unregistered)
 - TextTableRows                 0.0.0-             master (unregistered, dirty)
 - TextWrap                      0.1.6
 - TikzPictures                  0.3.5
 - Tk                            0.4.0
 - URIParser                     0.1.7
 - VT100                         0.0.2
 - VideoIO                       0.1.0
 - WeakRefStrings                0.2.0
 - WebSockets                    0.2.1
 - Winston                       0.12.1
 - WoodburyMatrices              0.2.1
 - Zlib                          0.1.12

Non-Real valued distributions

The Recipe for Distributions does not work with distributions with Integer domains.
Like Distributions.Bernoulli, Distributions.BetaBinomial , etc..

Font specification with @df macro

Hello, with the introduction of the @df macro I have code that stopped working.

julia> mydata = DataFrame(a = 1:10, b = 10*rand(10), c = 10 * rand(10))
10×3 DataFrames.DataFrame
│ Row │ a  │ b        │ c         │
├─────┼────┼──────────┼───────────┤
│ 1   │ 1  │ 2.63671  │ 0.170561  │
│ 2   │ 2  │ 0.242708 │ 2.91754   │
│ 3   │ 3  │ 7.30491  │ 7.04883   │
│ 4   │ 4  │ 5.72754  │ 9.73496   │
│ 5   │ 5  │ 5.47582  │ 9.08884   │
│ 6   │ 6  │ 9.27389  │ 0.528901  │
│ 7   │ 7  │ 2.01602  │ 9.47871   │
│ 8   │ 8  │ 7.81227  │ 5.78101   │
│ 9   │ 9  │ 2.22013  │ 5.59383   │
│ 10  │ 10 │ 8.19924  │ 0.0320381 │

julia> @df mydata plot(:a, [:b :c], colour = [:red :blue])

julia> @df mydata plot(:a, [:b :c], colour = [:red :blue],xtickfont=Plots.font(16))
ERROR: syntax: malformed expression

If I specify the font as before I get a malformed expression syntax error.

Thanks

How to produce a boxplot with groups, where the groups are side-by-side

I am making a box plot grouped by a certain variable. By default the boxes appear overlapping on each other. Is there a way to have them side-by-side to avoid the overlap?

Plots export broken

#50 broke Plots exports. MWE:

using StatPlots
histogram(randn(1000))
#ERROR: UndefVarError: histogram not defined

cc @ChrisRackauckas

Violin with mean

It would be nice to have an option of adding a mean/median line to the violin plots. These lines should be "halved" if side is not equal to :both.

StatPlots DataFrame example does not seem to work

using DataFrames, Plots, StatPlots
df = DataFrame(a = 1:100, b = randn(100), c = abs(randn(100)));
julia> plot(df, :a, [:b :c])
ERROR: MethodError: Cannot `convert` an object of type Array{Float64,1} to an object of type Float64
This may have arisen from a call to the constructor Float64(...),
since type constructors fall back to convert methods.
 in discrete_value!(::Plots.Axis, ::Array{Any,1}) at /Users/tcovert/.julia/v0.5/Plots/src/axes.jl:428
 in expand_extrema!(::Plots.Subplot{Plots.PyPlotBackend}, ::Dict{Symbol,Any}) at /Users/tcovert/.julia/v0.5/Plots/src/axes.jl:294
 in _expand_subplot_extrema(::Plots.Subplot{Plots.PyPlotBackend}, ::Dict{Symbol,Any}, ::Symbol) at /Users/tcovert/.julia/v0.5/Plots/src/pipeline.jl:361
 in _process_seriesrecipe(::Plots.Plot{Plots.PyPlotBackend}, ::Dict{Symbol,Any}) at /Users/tcovert/.julia/v0.5/Plots/src/pipeline.jl:392
 in _plot!(::Plots.Plot{Plots.PyPlotBackend}, ::Dict{Symbol,Any}, ::Tuple{DataFrames.DataFrame,Symbol,Array{Symbol,2}}) at /Users/tcovert/.julia/v0.5/Plots/src/plot.jl:229
 in #plot#258(::Array{Any,1}, ::Function, ::DataFrames.DataFrame, ::Vararg{Any,N}) at /Users/tcovert/.julia/v0.5/Plots/src/plot.jl:52
 in plot(::DataFrames.DataFrame, ::Symbol, ::Vararg{Any,N}) at /Users/tcovert/.julia/v0.5/Plots/src/plot.jl:46

here is my Pkg.status():

julia> Pkg.status()
18 required packages:
 - Blink                         0.4.4
 - DataFrames                    0.7.8
 - DataFramesMeta                0.1.3
 - FixedEffectModels             0.3.0
 - Formatting                    0.2.0
 - GLM                           0.6.1
 - JLD                           0.6.6
 - LaTeX                         0.1.1
 - MixedModels                   0.5.6
 - Optim                         0.6.1
 - PDMats                        0.5.1
 - PGFPlots                      1.4.2
 - PlotlyJS                      0.5.1
 - Plots                         0.10.1
 - PyPlot                        2.2.4
 - Rsvg                          0.0.2
 - Showoff                       0.0.7
 - StatPlots                     0.2.0
69 additional packages:
 - AxisAlgorithms                0.1.5
 - BaseTestNext                  0.2.2
 - BinDeps                       0.4.5
 - Blosc                         0.1.7
 - Cairo                         0.2.35
 - Calculus                      0.1.15
 - Codecs                        0.2.0
 - ColorBrewer                   0.3.0
 - ColorTypes                    0.2.12
 - ColorVectorSpace              0.1.11
 - Colors                        0.6.9
 - Compat                        0.9.5
 - Conda                         0.4.0
 - Contour                       0.2.0
 - DataArrays                    0.3.10
 - Discretizers                  0.3.1
 - Distributions                 0.11.0
 - DocStringExtensions           0.3.0
 - FileIO                        0.2.0
 - FixedPointNumbers             0.2.1
 - FixedSizeArrays               0.2.5
 - ForwardDiff                   0.2.5
 - GZip                          0.2.20
 - Graphics                      0.1.3
 - Gtk                           0.10.4
 - HDF5                          0.7.0
 - Hiccup                        0.0.3
 - Homebrew                      0.4.1
 - HttpCommon                    0.2.6
 - HttpParser                    0.2.0
 - HttpServer                    0.1.7
 - ImageMagick                   0.1.8
 - Images                        0.5.14
 - Interpolations                0.3.6
 - Iterators                     0.2.0
 - JSON                          0.8.0
 - Juno                          0.2.5
 - KernelDensity                 0.3.0
 - LaTeXStrings                  0.2.0
 - Lazy                          0.11.4
 - LegacyStrings                 0.1.1
 - MacroTools                    0.3.2
 - MathProgBase                  0.5.7
 - MbedTLS                       0.3.0
 - Measures                      0.0.3
 - Media                         0.2.4
 - Mustache                      0.1.2
 - Mux                           0.2.2
 - NLopt                         0.3.3
 - NaNMath                       0.2.2
 - PlotThemes                    0.1.0
 - PlotUtils                     0.2.0
 - PositiveFactorizations        0.0.3
 - PyCall                        1.7.2
 - Ratios                        0.0.4
 - RecipesBase                   0.1.0
 - Reexport                      0.0.3
 - Rmath                         0.1.4
 - SHA                           0.3.0
 - SIUnits                       0.1.0
 - SortingAlgorithms             0.1.0
 - StatsBase                     0.11.1
 - StatsFuns                     0.3.1
 - TexExtensions                 0.0.3
 - TikzPictures                  0.3.5
 - URIParser                     0.1.6
 - WebSockets                    0.2.1
 - WoodburyMatrices              0.2.0
 - Zlib                          0.1.12

groupedbar not working for plotlyjs()

Just found that the stack version of the groupbar example doesn't work for plotlyjs().

using Plots, StatPlots; plotlyjs() groupedbar(rand(10,3), bar_position = :stack, bar_width=0.7)

pyplot() and gr() backend works fine (below)

using Plots, StatPlots; pyplot() groupedbar(rand(10,3), bar_position = :stack, bar_width=0.7)

Can't set groupedbar series colors

I'd like to set the color individually for each series in a grouped bar plot, e.g.

using Plots, StatPlots
Plots.gr()
data = rand(6, 3)

p1 = groupedbar(data, color = [:red, :green, :blue])

But this produces the following plot:

I've also tried substituting color for fillcolor, seriescolor, linecolor, and markercolor. It's only when I edit the series individually that I get the desired plot:

p2 = groupedbar(data)
p2.series_list[1].d[:fillcolor] = parse(Colorant, :red)
p2.series_list[2].d[:fillcolor] = parse(Colorant, :green)
p2.series_list[3].d[:fillcolor] = parse(Colorant, :blue)

Is there a way to do this that I'm not aware of? I've looked through the StatPlots readme and the groupedbar code, and I haven't been able to figure it out. Thanks!

(Also, I'm not positive if this is a StatPlots issue, so if it isn't, I'll gladly open an issue in the appropriate package.)

Plot title is out of display.

Hi, thank you for making such a brilliant package in Julia.

I encountered a problem in which I cannot see a plot title because it seems to be out of window. Here is an example:

I made this plot with corrplot(θ[:,1001:2000]', title="NUTS", markersize=1) using the GR backend but the title ("NUTS") is not displayed and small fraction of the plot is also out of display.

This is a complete reproducing script: https://gist.github.com/bicycle1885/77d7ad79fbd3fa195ff432be167812d6

violin with more series than datapoints per series causes error

julia> using StatPlots

julia> violin(randn(10,3)) # Works fine

julia> violin(randn(10,10)) # Works fine

julia> violin(randn(10,11)) 
ERROR: BoundsError: attempt to access 10-element UnitRange{Int64} at index [11]
Stacktrace:
 [1] throw_boundserror(::UnitRange{Int64}, ::Int64) at ./abstractarray.jl:434
 [2] getindex(::UnitRange{Int64}, ::Int64) at ./range.jl:477
 [3] macro expansion at /local/home/fredrikb/.julia/v0.6/StatPlots/src/violin.jl:21 [inlined]
 [4] apply_recipe(::Dict{Symbol,Any}, ::Type{Val{:violin}}, ::UnitRange{Int64}, ::Array{Float64,1}, ::Void) at /local/home/fredrikb/.julia/v0.6/RecipesBase/src/RecipesBase.jl:287
 [5] _process_seriesrecipe(::Plots.Plot{Plots.GRBackend}, ::Dict{Symbol,Any}) at /local/home/fredrikb/.julia/v0.6/Plots/src/pipeline.jl:406
 [6] _plot!(::Plots.Plot{Plots.GRBackend}, ::Dict{Symbol,Any}, ::Tuple{Array{Float64,2}}) at /local/home/fredrikb/.julia/v0.6/Plots/src/plot.jl:233
 [7] (::RecipesBase.#kw##plot)(::Array{Any,1}, ::RecipesBase.#plot, ::Array{Float64,2}) at ./<missing>:0
 [8] #violin#672(::Array{Any,1}, ::Function, ::Array{Float64,2}, ::Vararg{Array{Float64,2},N} where N) at /local/home/fredrikb/.julia/v0.6/RecipesBase/src/RecipesBase.jl:381
 [9] violin(::Array{Float64,2}, ::Vararg{Array{Float64,2},N} where N) at /local/home/fredrikb/.julia/v0.6/RecipesBase/src/RecipesBase.jl:381

Fresh install of StatPlots will not precompile

For some reason, StatPlots has suddenly stopped working for me:

julia> using StatPlots
INFO: Precompiling module StatPlots.
ERROR: LoadError: LoadError: UndefVarError: Plot not defined
 in include_from_node1(::String) at ./loading.jl:488
 in include_from_node1(::String) at /usr/local/Cellar/julia/0.5.0/lib/julia/sys.dylib:?
 in include_from_node1(::String) at ./loading.jl:488
 in include_from_node1(::String) at /usr/local/Cellar/julia/0.5.0/lib/julia/sys.dylib:?
 in macro expansion; at ./none:2 [inlined]
 in anonymous at ./<missing>:?
 in eval(::Module, ::Any) at ./boot.jl:234
 in eval(::Module, ::Any) at /usr/local/Cellar/julia/0.5.0/lib/julia/sys.dylib:?
 in process_options(::Base.JLOptions) at ./client.jl:239
 in _start() at ./client.jl:318
 in _start() at /usr/local/Cellar/julia/0.5.0/lib/julia/sys.dylib:?
while loading /Users/tcovert/.julia/v0.5/StatPlots/src/marginalhist.jl, in expression starting on line 231
while loading /Users/tcovert/.julia/v0.5/StatPlots/src/StatPlots.jl, in expression starting on line 25
ERROR: Failed to precompile StatPlots to /Users/tcovert/.julia/lib/v0.5/StatPlots.ji.
 in compilecache(::String) at ./loading.jl:593
 in require(::Symbol) at ./loading.jl:422
 in require(::Symbol) at /usr/local/Cellar/julia/0.5.0/lib/julia/sys.dylib:?

if it helps, here is my versioninfo() and Pkg.status():

julia> versioninfo()
Julia Version 0.5.0
Commit 3c9d753* (2016-09-19 18:14 UTC)
Platform Info:
  System: Darwin (x86_64-apple-darwin15.6.0)
  CPU: Intel(R) Core(TM) i7-4578U CPU @ 3.00GHz
  WORD_SIZE: 64
  BLAS: libopenblas (DYNAMIC_ARCH NO_AFFINITY Haswell)
  LAPACK: libopenblas
  LIBM: libopenlibm
  LLVM: libLLVM-3.7.1 (ORCJIT, haswell)

julia> Pkg.status()
10 required packages:
 - Blink                         0.4.4
 - DataFrames                    0.8.5
 - DataFramesMeta                0.1.3
 - JLD                           0.6.6
 - Optim                         0.6.1
 - PDMats                        0.5.1
 - PlotlyJS                      0.5.1
 - Plots                         0.10.0
 - Rsvg                          0.0.2
 - StatPlots                     0.1.1
56 additional packages:
 - AxisAlgorithms                0.1.5
 - BaseTestNext                  0.2.2
 - BinDeps                       0.4.5
 - Blosc                         0.1.7
 - Cairo                         0.2.35
 - Calculus                      0.1.15
 - Codecs                        0.2.0
 - ColorTypes                    0.2.12
 - Colors                        0.6.9
 - Compat                        0.9.4
 - DataArrays                    0.3.10
 - Distributions                 0.11.0
 - DocStringExtensions           0.2.1
 - FileIO                        0.2.0
 - FixedPointNumbers             0.2.1
 - FixedSizeArrays               0.2.5
 - ForwardDiff                   0.2.5
 - GZip                          0.2.20
 - Graphics                      0.1.3
 - Gtk                           0.10.4
 - HDF5                          0.7.0
 - Hiccup                        0.0.3
 - Homebrew                      0.4.0
 - HttpCommon                    0.2.6
 - HttpParser                    0.2.0
 - HttpServer                    0.1.7
 - Interpolations                0.3.6
 - Iterators                     0.2.0
 - JSON                          0.8.0
 - Juno                          0.2.5
 - KernelDensity                 0.3.0
 - LaTeXStrings                  0.2.0
 - Lazy                          0.11.4
 - LegacyStrings                 0.1.1
 - MacroTools                    0.3.2
 - MbedTLS                       0.3.0
 - Measures                      0.0.3
 - Media                         0.2.4
 - Mustache                      0.1.2
 - Mux                           0.2.2
 - NaNMath                       0.2.2
 - PlotThemes                    0.1.0
 - PlotUtils                     0.2.0
 - PositiveFactorizations        0.0.2
 - Ratios                        0.0.4
 - RecipesBase                   0.1.0
 - Reexport                      0.0.3
 - Rmath                         0.1.4
 - SHA                           0.3.0
 - Showoff                       0.0.7
 - SortingAlgorithms             0.1.0
 - StatsBase                     0.11.1
 - StatsFuns                     0.3.1
 - URIParser                     0.1.6
 - WebSockets                    0.2.1
 - WoodburyMatrices              0.2.0

Violine plot with not overlapping groups

Hi!
Is there a way to create grouped violin plots on a categorical x-axis, where the violins of different groups on one category do not overlap?
Similar behavior has been discussed in #56 for boxplots, but i didn't find a solution for that.

df = DataFrame(accuracy=Float64[],Cat1=String[],Cat2=String[])
for i = 1 : 100 push!(df,[rand() rand(["A"; "B"]) rand(["1" "2" "3"])]) end
violin(df,:Cat1,:accuracy,group=:Cat2,ylims=(0,1))

[Feature Request] Generate groups with a column in DataFrame

It would be great to be able to take subsets from a DataFrame to plot different lines or bar groups. So for example, if I have:

df = DataFrame(a=[1,2,3,4], b=["foo","bar","foo","bar"])

I'd like to generate a plot like so:

using StatPlots

groupedbar(df, :a, group=:b)

and get:

(this was generated by doing groupedbar([[1,3] [2,4]], lab=["foo", "bar"]))

Add support to TimeSeries

Does the package support TimeSeries? The code below produces an error.

using TimeSeries
using StatPlots

dates  = collect(Date(1999,1,1):Date(2000,12,31))
series = TimeArray(dates, rand(length(dates)))

plot(series)

A way to provide group labels for groupbar?

Is there a way to provide legend labels there separately?

I've tried what I thought was a natural thing (supplying labels=["label1", "label2"]), but that doesn't work.

Going through docs for recepies and even looking at SliceIt recepie that seems to be called here didn't help, but I'll appreciate pointers.

Improve Distributions support

It is great having support for Distributions.jl.
Unfortunately there are some bugs. For example this works fine.

plot(Gamma(1, 1), fill=(0, 0.5, :skyblue), legend=false)

But this...

plot(Gamma(0.1, 1), fill=(0, 0.5, :skyblue), legend=false)

...works fine with plotlyjs() backend but shows an empty plot with gr() backend and something weird with pyplot() backend.

This gives an error.

plot(InverseGamma(2, 1), fill=(0, 0.5, :skyblue), legend=false)

ArgumentError: start and stop must be finite, got 0.0 and Inf

In sum, seems that Distributions support could use some attention.

Keep up the great work!

density doesn't work

using RDatasets
using StatPlots

iris = dataset("datasets","iris")

density(iris, [:SepalLength, :PetalLength])

throws the following error:

LoadError: UndefVarError: isvertical not defined
while loading In[2], in expression starting on line 6

 [inlined code] from /home/dzea/.julia/v0.4/StatPlots/src/hist.jl:7
 in apply_recipe at /home/dzea/.julia/v0.4/RecipesBase/src/RecipesBase.jl:238
 in _process_seriesrecipe at /home/dzea/.julia/v0.4/Plots/src/pipeline.jl:386
 in _plot! at /home/dzea/.julia/v0.4/Plots/src/plot.jl:204
 in plot at /home/dzea/.julia/v0.4/Plots/src/plot.jl:52
 in density at /home/dzea/.julia/v0.4/Plots/src/Plots.jl:151

Discussion: syntax for plotting from a DataFrame

Issues with the current syntax for plotting from a DataFrame:

It's implemented as a user recipe, which means it doesn't play well with grouping (see #1033)
The user may be led to expecting that it is equivalent to typing the columns inside the DataFrame (which I believe it should be), but instead it is different in subtle ways, for example when trying to group by more than one column. This fails

using StatPlots, DataFrames, RDatasets
iris = RDatasets.dataset("datasets","iris")
iris[:LongSepal] = iris[:SepalLength] .> median(iris[:SepalLength])
scatter(iris, :PetalLength, :PetalWidth, group = collect(zip(:Species,:LongSepal)))

but it'd work with the columns:

scatter(iris[:PetalLength], iris[:PetalWidth], group = collect(zip(iris[:Species],iris[:LongSepal])))

other recipes also fail because the transformation from symbol to columns happens to late (see #59 ):

corrplot(iris, [:SepalLength :SepalWidth :PetalLength :PetalWidth])

it has to resort to heuristics to decide whether a symbol is a symbol or a column. For example
scatter(iris, :PetalLength, :PetalWidth, color = :blue) plots in blue, unless there is a column in iris called :blue
it has to resort to a runtime eval call

My personal preference would be for syntactically replacing symbols with columns.
Possible options:

Adding a dispatch to plot if the first argument is a DataFrame: in that case all symbols and expression are replaced by the respective columns, using the same functions we use now. It wouldn't resolve the ambiguity symbol/column + calling eval but at least wouldn't mess with the recipe system
Officialize the @with method from DataFramesMeta (a bit verbose but solves all of the above problems: group and corrplot work just fine and one can escape symbols to prevent them from becoming columns). Extra advantage: it can be used in blocks:

@with iris begin
    plt = plot(:SepalLength,:PetalWidth)
    plot!(:SepalLength,:PetalLength)
    display(plt)
end

A slight modification of @with where each symbol s is not replaced by df[s], but by
haskey(df, s) ? df[s] : s so that the user wouldn't need to escape symbols so often
Try and find a less verbose macro, though the implementation is not super straightforward. One bold possibility would be sth like:

macro plot(args...)
    :(@with $(args[1]) $(Expr(:call, :plot, Base.tail(args)...)))
end
@plot(iris, :PetalLength, :PetalWidth)

But it seems hard to get it to work with keyword arguments/ different seriestypes.

groupedbar with error bars not working with plotlyjs

The plotlyjs backend doesn't handle the groupedbar recipe with error bars correctly:

gr instead produces the expected outcome:

Integer division error for a violin plot

I'm getting an integer division error for a violin plot.

# I tried plotlyjs() and pyplot() here
violin(rand(10))

results in

DivideError: integer division error

 in cycle at /home/pawel/.julia/v0.5/Plots/src/utils.jl:240 [inlined]
 in #10 at /home/pawel/.julia/v0.5/Plots/src/utils.jl:195 [inlined]
 in Predicate at ./reduce.jl:183 [inlined]
 in mapreduce_sc_impl(::Base.Predicate{Plots.##10#11{Int64}}, ::Base.#|, ::Tuple{Array{Float64,1},Array{Float64,1}}) at ./reduce.jl:198
 in start(::Plots.SegmentsIterator) at /home/pawel/.julia/v0.5/Plots/src/utils.jl:201
 in plotly_series_shapes(::Plots.Plot{Plots.PlotlyBackend}, ::Plots.Series) at /home/pawel/.julia/v0.5/Plots/src/backends/plotly.jl:545
 in plotly_series(::Plots.Plot{Plots.PlotlyBackend}, ::Plots.Series) at /home/pawel/.julia/v0.5/Plots/src/backends/plotly.jl:383
 in plotly_series_json(::Plots.Plot{Plots.PlotlyBackend}) at /home/pawel/.julia/v0.5/Plots/src/backends/plotly.jl:594
 in html_body(::Plots.Plot{Plots.PlotlyBackend}, ::Void) at /home/pawel/.julia/v0.5/Plots/src/backends/plotly.jl:612
 in _show at /home/pawel/.julia/v0.5/Plots/src/backends/plotly.jl:639 [inlined]
 in show(::Base.AbstractIOBuffer{Array{UInt8,1}}, ::MIME{Symbol("image/svg+xml")}, ::Plots.Plot{Plots.PlotlyBackend}) at /home/pawel/.julia/v0.5/Plots/src/output.jl:171
 in show(::Base.AbstractIOBuffer{Array{UInt8,1}}, ::MIME{Symbol("text/html")}, ::Plots.Plot{Plots.PlotlyBackend}) at /home/pawel/.julia/v0.5/Plots/src/output.jl:151
 in show(::Base.AbstractIOBuffer{Array{UInt8,1}}, ::String, ::Plots.Plot{Plots.PlotlyBackend}) at ./multimedia.jl:33
 in #sprint#304(::Void, ::Function, ::Int64, ::Function, ::String, ::Vararg{Any,N}) at ./strings/io.jl:37
 in display_dict(::Plots.Plot{Plots.PlotlyBackend}) at /home/pawel/.julia/v0.5/Plots/src/output.jl:240
 in execute_request(::ZMQ.Socket, ::IJulia.Msg) at /home/pawel/.julia/v0.5/IJulia/src/execute_request.jl:200
 in eventloop(::ZMQ.Socket) at /home/pawel/.julia/v0.5/IJulia/src/eventloop.jl:8
 in (::IJulia.##9#15)() at ./task.jl:360

KernelDensity.jl plots are not working

using KernelDensity
using StatPlots; pyplot()

plot(kde(randn(1000,2)))

PyError (ccall(@pysym(:PyObject_Call), PyPtr, (PyPtr, PyPtr, PyPtr), o, arg, kw)) <class 'TypeError'>
TypeError('Length of x must be number of columns in z.',)
File "/usr/lib/python3.6/site-packages/matplotlib/init.py", line 1898, in inner
return func(ax, *args, **kwargs)
File "/usr/lib/python3.6/site-packages/matplotlib/axes/_axes.py", line 5825, in contour
contours = mcontour.QuadContourSet(self, *args, **kwargs)
File "/usr/lib/python3.6/site-packages/matplotlib/contour.py", line 864, in init
self._process_args(*args, **kwargs)
File "/usr/lib/python3.6/site-packages/matplotlib/contour.py", line 1429, in _process_args
x, y, z = self._contour_args(args, kwargs)
File "/usr/lib/python3.6/site-packages/matplotlib/contour.py", line 1508, in _contour_args
x, y, z = self._check_xyz(args[:3], kwargs)
File "/usr/lib/python3.6/site-packages/matplotlib/contour.py", line 1555, in _check_xyz
raise TypeError("Length of x must be number of columns in z.")

Color of diagonal histograms

The color of the diagonal histrograms in corrplot shouldn't simply be black. If the background is dark, black might not be a good color. The foreground color could be a good alternative, as this should contrast to the background color automatically.

Request diagnostic plots for multiple regression

Request diagnostic plots for multiple regression. Some thing like this will be helpful
https://www.andrew.cmu.edu/user/achoulde/94842/homework/regression_diagnostics.html

groupedbar with labels

bench_seq = b_learn
gbar = groupedbar(rand(5,3), labels=["a", "b", "c"])

Broken at least on plotlyjs and pyplot

groupedbar with bar_position = :stack doesn't stack in plotly backend

The version is:

StatPlots 0.5.1+ master

As you can see from the screen captures below:

gallery

This is just so I can link to pictures for the readme...

corrplot `Plots.default_gradient` missing

When I try to run the corrplot example from the documentation

M = randn(1000,4)
M[:,2] += 0.8sqrt(abs(M[:,1])) - 0.5M[:,3] + 5
M[:,3] -= 0.7M[:,1].^2 + 2

corrplot(M, label = ["x$i" for i=1:4])

I get the following error

LoadError: UndefVarError: default_gradient not defined
while loading In[1], in expression starting on line 8

 [inlined code] from /home/admin/.julia/v0.4/StatPlots/src/corrplot.jl:24
 in apply_recipe at /home/admin/.julia/v0.4/RecipesBase/src/RecipesBase.jl:238
 in _process_userrecipes at /home/admin/.julia/v0.4/Plots/src/pipeline.jl:73
 in _plot! at /home/admin/.julia/v0.4/Plots/src/plot.jl:157
 in corrplot at /home/admin/.julia/v0.4/Plots/src/recipes.jl:37
 in anonymous at no file

It seems that there is no function Plots.default_gradient (I tried the 0.8 release, master, dev versions of Plots.jl).

cornerplot

See: JuliaPlots/GraphRecipes.jl#1 (comment)

cc: @mauro3 (do you want to submit a PR?)

maringal hist with plotly

Notice that the histogram on the right is reversed from what it should be.

Code to reproduce:

using Plots; plotlyjs()

using RDatasets
iris = dataset("datasets","iris")
marginalhist(iris, :PetalLength, :PetalWidth)

Cornerplot shows no x-ticks along the bottom axis

There are no x-tick labels along the bottom plots. However, they should be there, as they are enabled in this line (as far as I understand).

Distributions.Normal plotting is broken?

I'm trying to execute the example from the README.md (after adding the missing using statements):

using Plots
using Distributions
using StatPlots
plot(Normal(3,5), fill=(0, .5,:orange))

However, instead of a plot I am getting:

julia> plot(Normal(3,5), fill=(0, .5,:orange))
ERROR: In convertToAnyVector, could not handle the argument types: (Distributions.Normal{Float64},)
 in macro expansion at /.julia/v0.5/Plots/src/series.jl:128 [inlined]
 in apply_recipe(::Dict{Symbol,Any}, ::Type{Plots.SliceIt}, ::Distributions.Normal{Float64}, ::LinSpace{Float64}, ::Void) at /.julia/v0.5/RecipesBase/src/RecipesBase.jl:238
 in _process_userrecipes(::Plots.Plot{Plots.PyPlotBackend}, ::Dict{Symbol,Any}, ::Tuple{Distributions.Normal{Float64}}) at /.julia/v0.5/Plots/src/pipeline.jl:73
 in _plot!(::Plots.Plot{Plots.PyPlotBackend}, ::Dict{Symbol,Any}, ::Tuple{Distributions.Normal{Float64}}) at /.julia/v0.5/Plots/src/plot.jl:171
 in (::Plots.#kw##plot)(::Array{Any,1}, ::Plots.#plot, ::Distributions.Normal{Float64}) at ./<missing>:0

Is there a package (or another statement) that I'm missing?

@df example does not work for me

hi,
i tried and saw

               _
   _       _ _(_)_     |  A fresh approach to technical computing
  (_)     | (_) (_)    |  Documentation: https://docs.julialang.org
   _ _   _| |_  __ _   |  Type "?help" for help.
  | | | | | | |/ _` |  |
  | | |_| | | | (_| |  |  Version 0.6.0 (2017-06-19 13:05 UTC)
 _/ |\__'_|_|_|\__'_|  |  Official http://julialang.org/ release
|__/                   |  x86_64-apple-darwin13.4.0

julia> using DataFrames, StatPlots, Query

julia> df = DataFrame(a = 1:10, b = 10*rand(10), c = 10 * rand(10))
10×3 DataFrames.DataFrame
│ Row │ a  │ b       │ c        │
├─────┼────┼─────────┼──────────┤
│ 1   │ 1  │ 8.12892 │ 3.54923  │
│ 2   │ 2  │ 4.32659 │ 2.44013  │
│ 3   │ 3  │ 2.38561 │ 1.25754  │
│ 4   │ 4  │ 6.44253 │ 3.3041   │
│ 5   │ 5  │ 9.10658 │ 2.33738  │
│ 6   │ 6  │ 5.89228 │ 6.60129  │
│ 7   │ 7  │ 1.41004 │ 6.80407  │
│ 8   │ 8  │ 6.71332 │ 6.91759  │
│ 9   │ 9  │ 8.29649 │ 7.71453  │
│ 10  │ 10 │ 8.18642 │ 0.549369 │

julia> df |>
           @where(_.a > 5) |>
           @select({_.b, d = _.c-10}) |>
           @df scatter(:b, :d)
ERROR: MethodError: no method matching @df(::Expr)
Closest candidates are:
  @df(::ANY, ::ANY) at /Users/74097/.julia/v0.6/StatPlots/src/df.jl:12

julia> Pkg.status.(["StatPlots","Query","DataFrames"])
 - StatPlots                     0.5.0
 - Query                         0.6.0              v0.7.2
 - DataFrames                    0.10.1

Violin plot and _box_halfwidth

The violin plot example doesn't work, as the const _box_halfwidth has been removed from the boxplot file.

(also the alpha values are no longer as shown)

Density: Can't set path color

using Plots
using StatPlots

density(randn(200),color=:red)
cdensity!(randn(200),color=:red)

The path for density is black, the path for cdensity is red. I'm having everything on master. Tested with:

pyplot
plotlyjs
gr

I looked into the recipe code but I can't see any difference between density and cdensity that could cause this behavior. Setting the linestyle works.

Annotations on grouped bar plots for significance

I would like to see support for more powerful bar plots, including

widening the axes (#511)
allowing for lines and annotations specifying grouped significance
easy error bars
grouped bars with control of number of bars in each group and the spacing between them

Here are some images (from today's Nature magazine) representing common graphics designs with bar plots

Composite bar plots in subplots with simple error bars:

Good example of grouped barplots:

A very basic barplot:

marginalhist has extra ylabel

marginalhist(iris, :PetalLength, :PetalWidth)

Not sure when this happened, but doesn't depend on DataFrames recipe, you would have the same issue with:
marginalhist(randn(1000), randn(1000), xlabel = :x , ylabel = :y)

The only way to get only the labels on the heatmap is:

marginalhist(randn(1000), randn(1000), xlabel = :x , ylabel = ["" :y])

Use groupedbar as a seriestype

I'd like to use groupedbar in a plot recipe of my own. However, when I set seriestype := :groupedbar, I get the following error:

ERROR: The backend must not support the series type Val{:groupedbar}, and there isn't a series recipe defined.
Stacktrace:
 [1] apply_recipe(::Dict{Symbol,Any}, ::Type{Val{:groupedbar}}, ::UnitRange{Int64}, ::Array{Float64,1}, ::Void) at /home/rcepxl10/.julia/v0.6/RecipesBase/src/RecipesBase.jl:287
 [2] _process_seriesrecipe(::Plots.Plot{Plots.GRBackend}, ::Dict{Symbol,Any}) at /home/rcepxl10/.julia/v0.6/Plots/src/pipeline.jl:406
 [3] _plot!(::Plots.Plot{Plots.GRBackend}, ::Dict{Symbol,Any}, ::Tuple{Shockdec}) at /home/rcepxl10/.julia/v0.6/Plots/src/plot.jl:231
 [4] #shockdec#155(::Array{Any,1}, ::Function) at /home/rcepxl10/.julia/v0.6/RecipesBase/src/RecipesBase.jl:363
 [5] shockdec() at /home/rcepxl10/.julia/v0.6/RecipesBase/src/RecipesBase.jl:363

As far as I can tell, the difference between groupedbar and other recipes defined in this package that can be successfully set as seriestypes (e.g. marginalhist, violin) is that it's defined using @userplot with the following function header (on master):

@recipe function f(g::GroupedBar)

Compare to marginalhist's header, which uses @shorthands and takes as its first argument a Type{Val{:marginalhist}}:

@recipe function f(::Type{Val{:marginalhist}}, plt::AbstractPlot; density = false)

I spent a little time trying to modify groupedbar to take in a Type{Val{:groupedbar}} without much success, probably because I'm still trying to grasp how recipes work on the inside. Is this functionality (setting seriestype := :groupedbar in a recipe) currently possible? If not, can I put in a request for it to be added? Am I understanding the reason groupedbar currently can't be used as a seriestype correctly?

Tree plot for Hclust

I managed to generate what I think are the beginnings of a recipe for plotting a tree with Hclust types from Clustering.jl:

using Distances
using Clustering
using StatPlots

include("hclustrecipe.jl")

m = rand(100,10)
dm = pairwise(Distances.Jaccard(), m)

clust = hclust(dm, :average)

plot(hclustplot(clust, true),seriestype=:path, color=:black,
    yaxis=nothing, grid=false, legend=false, xticks=clust.labels)

Ultimately, I want to combine this with a heatmap to generate something that looks like this:

Wondering what the next steps are - in other words where should I submit a PR? Do I add it to Clustering.jl, or somewhere in this repo?

@df : passing a symbol through a variable throws an error

This is probably just me not understanding something very simple about how Symbols are passed, but

using StatPlots, DataFrames
smallDf = DataFrame(A = rand(10),B=rand(10))
x = :A
@df smallDf histogram(x)

Throws

ERROR: ArgumentError: invalid index: Union{}[]
Stacktrace:
 [1] #create_columns_from_iterabletable#1(::TableTraitsUtils.#_default_array_factory, ::Function, ::DataFrames.DataFrame, ::Array{Union{},1}) at /localhome/romain/.julia/v0.6/TableTraitsUtils/src/TableTraitsUtils.jl:142
 [2] extract_columns_from_iterabletable(::DataFrames.DataFrame) at /localhome/romain/.julia/v0.6/StatPlots/src/df.jl:100

Whereas @df smallDf histogram(:A) or smallDf[x] work as I would expect.
This is with the latest master (also on the latest release) and julia 0.6.1.

groupedbar() doesn't work with plotlyjs

I have tested this with the fix in JuliaPlots/Plots.jl#1436 as well, but it does not seem to fix it, unfortunately.

"Missing data of type Any is not supported" for df macro.

Consider the following piece of code:

using StatPlots, DataFrames

df_any = DataFrame(Any, 0, 1)
df_array_any = DataFrame(Array{Any}(0, 1))

for i in 1:10
    push!(df_any, rand())
    push!(df_array_any, rand())
end

@df df_any plot(:x1) # Error: "Missing data of type Any is not supported"
@df df_array_any plot(:x1) # works

I'm not sure if this is related to StatPlots or DataFrames, if this is expected or an issue. I was just a little surprised.
cc: @piever

new grid behaves strangely with corrplot: only appears where there are ticks

corrplot recipe has a strange grid:

M = randn(1000,4)
M[:,2] += 0.8sqrt.(abs.(M[:,1])) - 0.5M[:,3] + 5
M[:,3] -= 0.7M[:,1].^2 + 2
corrplot(M, label = ["x$i" for i=1:4])

grouped bar plots

using StatPlots
groupedbar(rand(10,3), bar_position = :stack, bar_width=0.7, alpha=0.5)

This is the default:

using StatPlots
groupedbar(rand(10,3), bar_position = :dodge, bar_width=0.7, alpha=0.5)

Cannot plot multiple series from DataFrame

I cannot plot multiple series from a DataFrame with StatPlots. I can do it with the old Plots on my julia-0.4.6 install.

so:

using StatPlots
df = DataFrame(a = 1:100, b = randn(100), c = randn(100))
plot(df, :a, :b)

works, but

plot(df, :a, [:b :c])

doesn't, but it should, since

a = 1:100 ; b = randn(100); c = randn(100)
plot(a, [b, c])

works.