Series attribute to show empty bins as 0.

src/arg_desc.jl

@@ -42,6 +42,7 @@ const _arg_desc = KW(
 :arrow             	=> "nothing (no arrows), Bool (if true, default arrows), Arrow object, or arg(s) that could be style or head length/widths.  Defines arrowheads that should be displayed at the end of path line segments (just before a NaN and the last non-NaN point).  Used in quiverplot, streamplot, or similar.",
 :normalize         	=> "Bool or Symbol. Histogram normalization mode. Possible values are: false/:none (no normalization, default), true/:pdf (normalize to a discrete Probability Density Function, where the total area of the bins is 1), :probability (bin heights sum to 1) and :density (the area of each bin, rather than the height, is equal to the counts - useful for uneven bin sizes).",
 :weights           	=> "AbstractVector. Used in histogram types for weighted counts.",
+:show_empty_bins    => "Bool. Whether empty bins in a 2D histogram are colored as 0 (true), or transparent (the default).",
 :contours          	=> "Bool. Add contours to the side-grids of 3D plots?  Used in surface/wireframe.",
 :contour_labels         => "Bool. Show labels at the contour lines?",
 :match_dimensions  	=> "Bool. For heatmap types... should the first dimension of a matrix (rows) correspond to the first dimension of the plot (x-axis)?  The default is false, which matches the behavior of Matplotlib, Plotly, and others.  Note: when passing a function for z, the function should still map `(x,y) -> z`.",

src/args.jl

@@ -272,6 +272,7 @@ const _series_defaults = KW(
     :arrow             => nothing,   # allows for adding arrows to line/path... call `arrow(args...)`
     :normalize         => false,     # do we want a normalized histogram?
     :weights           => nothing,   # optional weights for histograms (1D and 2D)
+    :show_empty_bins   => false,     # should empty bins in 2D histogram be colored as zero (otherwise they are transparent)
     :contours          => false,     # add contours to 3d surface and wireframe plots
     :contour_labels    => false,
     :match_dimensions  => false,     # do rows match x (true) or y (false) for heatmap/image/spy? see issue 196
@@ -574,6 +575,7 @@ add_aliases(:xerror, :xerr, :xerrorbar)
 add_aliases(:yerror, :yerr, :yerrorbar, :err, :errorbar)
 add_aliases(:quiver, :velocity, :quiver2d, :gradient, :vectorfield)
 add_aliases(:normalize, :norm, :normed, :normalized)
+add_aliases(:show_empty_bins, :showemptybins, :showempty, :show_empty, :show_zeros, :showzeros)
 add_aliases(:aspect_ratio, :aspectratio, :axis_ratio, :axisratio, :ratio)
 add_aliases(:match_dimensions, :transpose, :transpose_z)
 add_aliases(:subplot, :sp, :subplt, :splt)

src/backends.jl

@@ -234,7 +234,7 @@ const _base_supported_args = [
     :subplot_index,
     :discrete_values,
     :projection,
-
+    :show_empty_bins
 ]
 
 function merge_with_base_supported(v::AVec)

src/examples.jl

@@ -129,6 +129,16 @@ PlotExample("Histogram2D",
     end)]
 ),
 
+PlotExample("Histogram2D (complex values)",
+    "",
+    [:(begin
+        n = 10_000
+        x = exp.(0.1randn(n) .+ randn(n).*(im))
+        histogram2d(x, nbins=(20,40), show_empty_bins=true,
+                    normed=true, aspect_ratio=1)
+    end)]
+),
+
 PlotExample("Line types",
     "",
     [:(begin

src/recipes.jl

@@ -755,12 +755,14 @@ end
     edge_x, edge_y, weights = x, y, z.surf
 
     float_weights = float(weights)
-    if float_weights === weights
-        float_weights = deepcopy(float_weights)
-    end
-    for (i, c) in enumerate(float_weights)
-        if c == 0
-            float_weights[i] = NaN
+    if !plotattributes[:show_empty_bins]
+        if float_weights === weights
+            float_weights = deepcopy(float_weights)
+        end
+        for (i, c) in enumerate(float_weights)
+            if c == 0
+                float_weights[i] = NaN
+            end
         end
     end