diff --git a/examples/meetup/iheartplots.gif b/examples/meetup/iheartplots.gif
index aa74961a..8ff623db 100644
Binary files a/examples/meetup/iheartplots.gif and b/examples/meetup/iheartplots.gif differ
diff --git a/examples/meetup/nnet.ipynb b/examples/meetup/nnet.ipynb
index ef43d4b4..62d36781 100644
--- a/examples/meetup/nnet.ipynb
+++ b/examples/meetup/nnet.ipynb
@@ -2,71 +2,11 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": null,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "INFO: Recompiling stale cache file /home/tom/.julia/lib/v0.4/OnlineStats.ji for module OnlineStats.\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "  0.544174 seconds (2.08 M allocations: 156.080 MB, 2.81% gc time)\n",
-      "\n",
-      "\n",
-      "\n",
-      "maxabs(β - coef(o)) for\n",
-      "\n",
-      "glm:      0.006636741266573876\n",
-      "sgd:      NaN\n",
-      "proxgrad: 0.010237129356885588\n",
-      "rda:      1.4318993623506318\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "WARNING: Base.FloatingPoint is deprecated, use AbstractFloat instead.\n",
-      "  likely near /home/tom/.julia/v0.4/Qwt/src/widgets.jl:5\n",
-      "WARNING: Base.String is deprecated, use AbstractString instead.\n",
-      "  likely near /home/tom/.julia/v0.4/Glob/src/Glob.jl:13\n",
-      "WARNING: Base.Uint32 is deprecated, use UInt32 instead.\n",
-      "  likely near /home/tom/.julia/v0.4/Glob/src/Glob.jl:13\n",
-      "WARNING: Base.String is deprecated, use AbstractString instead.\n",
-      "  likely near /home/tom/.julia/v0.4/Glob/src/Glob.jl:13\n",
-      "WARNING: Base.String is deprecated, use AbstractString instead.\n",
-      "  likely near /home/tom/.julia/v0.4/Glob/src/Glob.jl:18\n",
-      "WARNING: Base.String is deprecated, use AbstractString instead.\n",
-      "  likely near /home/tom/.julia/v0.4/Glob/src/Glob.jl:18\n",
-      "WARNING: Base.String is deprecated, use AbstractString instead.\n",
-      "  likely near /home/tom/.julia/v0.4/Glob/src/Glob.jl:21\n",
-      "WARNING: Base.String is deprecated, use AbstractString instead.\n",
-      "  likely near /home/tom/.julia/v0.4/Glob/src/Glob.jl:21\n",
-      "WARNING: Base.String is deprecated, use AbstractString instead.\n",
-      "  likely near /home/tom/.julia/v0.4/Glob/src/Glob.jl:45\n",
-      "WARNING: Base.String is deprecated, use AbstractString instead.\n",
-      "  likely near /home/tom/.julia/v0.4/Glob/src/Glob.jl:120\n",
-      "WARNING: Base.String is deprecated, use AbstractString instead.\n",
-      "  likely near /home/tom/.julia/v0.4/Glob/src/Glob.jl:191\n",
-      "WARNING: Base.String is deprecated, use AbstractString instead.\n",
-      "  likely near /home/tom/.julia/v0.4/Glob/src/Glob.jl:274\n",
-      "WARNING: Base.String is deprecated, use AbstractString instead.\n",
-      "  likely near /home/tom/.julia/v0.4/Glob/src/Glob.jl:336\n",
-      "WARNING: Base.String is deprecated, use AbstractString instead.\n",
-      "  likely near /home/tom/.julia/v0.4/Glob/src/Glob.jl:338\n",
-      "WARNING: Base.String is deprecated, use AbstractString instead.\n",
-      "  likely near /home/tom/.julia/v0.4/Glob/src/Glob.jl:346\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "using Plots, DataFrames, OnlineStats, OnlineAI\n",
     "default(size=(500,300))\n",
@@ -77,35 +17,21 @@
    "cell_type": "code",
    "execution_count": 4,
    "metadata": {
-    "collapsed": false
+    "collapsed": false,
+    "scrolled": false
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "(xmeta,ymeta) = (nothing,nothing)"
-     ]
-    },
-    {
-     "ename": "BoundsError",
-     "evalue": "BoundsError: attempt to access 0-element Array{Any,1}\n  at index [0]",
-     "output_type": "error",
-     "traceback": [
-      "BoundsError: attempt to access 0-element Array{Any,1}\n  at index [0]",
-      ""
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n"
+      "(xmeta,ymeta) = (nothing,nothing)\n"
      ]
     }
    ],
    "source": [
-    "p = plot(10)"
+    "using Plots; gadfly()\n",
+    "p = plot(10);"
    ]
   },
   {
diff --git a/examples/meetup/slides_20151028.ipynb b/examples/meetup/slides_20151028.ipynb
index 3a615aaa..a0ad47bb 100644
--- a/examples/meetup/slides_20151028.ipynb
+++ b/examples/meetup/slides_20151028.ipynb
@@ -388,7 +388,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 6,
    "metadata": {
     "collapsed": false,
     "slideshow": {
@@ -400,7 +400,8 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[Plots.jl] Initializing backend: gadfly"
+      "(xmeta,ymeta) = (nothing,nothing)\n",
+      "(xmeta,ymeta) = (nothing,nothing)\n"
      ]
     }
    ],
@@ -412,7 +413,7 @@
     "\n",
     "# create parametric functions\n",
     "fx(u) = 1.6sin(u)^3\n",
-    "fy(u) = 0.1 + 1.5cos(u) - 0.6cos(2u) - 0.25cos(3u) - cos(4u)/8\n",
+    "fy(u) = 0.3 + 1.5cos(u) - 0.6cos(2u) - 0.25cos(3u) - cos(4u)/8\n",
     "\n",
     "# plot and annotate\n",
     "p = plot(fx, fy, 0, 2π, line=(5,:darkred), xlim=(-2,2), ylim=(-2,2))\n",
@@ -421,7 +422,177 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 7,
+   "metadata": {
+    "collapsed": false,
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/svg+xml": [
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+       "<svg xmlns=\"http://www.w3.org/2000/svg\"\n",
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+       "     xmlns:gadfly=\"http://www.gadflyjl.org/ns\"\n",
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+       "     width=\"158.73mm\" height=\"132.28mm\" viewBox=\"0 0 158.73 132.28\"\n",
+       "     stroke=\"none\"\n",
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",
+      "image/svg+xml": [],
+      "text/plain": [
+       "Plot{Plots.GadflyPackage() n=1}"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "p"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
    "metadata": {
     "collapsed": false,
     "slideshow": {
@@ -433,39 +604,65 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "\n"
+      "(xmeta,ymeta) = (nothing,nothing)\n",
+      "(xmeta,ymeta) = (nothing,nothing)\n",
+      "(xmeta,ymeta) = (nothing,nothing)\n",
+      "(xmeta,ymeta) = (nothing,nothing)\n",
+      "(xmeta,ymeta) = (nothing,nothing)\n",
+      "(xmeta,ymeta) = (nothing,nothing)\n",
+      "(xmeta,ymeta) = (nothing,nothing)\n",
+      "(xmeta,ymeta) = (nothing,nothing)\n",
+      "(xmeta,ymeta) = (nothing,nothing)\n",
+      "(xmeta,ymeta) = (nothing,nothing)\n",
+      "(xmeta,ymeta) = (nothing,nothing)\n",
+      "(xmeta,ymeta) = (nothing,nothing)\n",
+      "(xmeta,ymeta) = (nothing,nothing)\n",
+      "(xmeta,ymeta) = (nothing,nothing)\n",
+      "(xmeta,ymeta) = (nothing,nothing)\n",
+      "(xmeta,ymeta) = (nothing,nothing)\n",
+      "(xmeta,ymeta) = (nothing,nothing)\n",
+      "(xmeta,ymeta) = (nothing,nothing)\n",
+      "(xmeta,ymeta) = (nothing,nothing)\n",
+      "(xmeta,ymeta) = (nothing,nothing)\n",
+      "(xmeta,ymeta) = (nothing,nothing)\n",
+      "(xmeta,ymeta) = (nothing,nothing)\n",
+      "(xmeta,ymeta) = (nothing,nothing)\n",
+      "(xmeta,ymeta) = (nothing,nothing)\n",
+      "(xmeta,ymeta) = (nothing,nothing)\n",
+      "(xmeta,ymeta) = (nothing,nothing)\n",
+      "(xmeta,ymeta) = (nothing,nothing)\n",
+      "(xmeta,ymeta) = (nothing,nothing)\n",
+      "(xmeta,ymeta) = (nothing,nothing)\n",
+      "(xmeta,ymeta) = (nothing,nothing)\n",
+      "(xmeta,ymeta) = (nothing,nothing)\n",
+      "(xmeta,ymeta) = (nothing,nothing)\n",
+      "(xmeta,ymeta) = (nothing,nothing)\n",
+      "(xmeta,ymeta) = (nothing,nothing)\n",
+      "(xmeta,ymeta) = (nothing,nothing)\n",
+      "(xmeta,ymeta) = (nothing,nothing)\n",
+      "(xmeta,ymeta) = (nothing,nothing)\n",
+      "(xmeta,ymeta) = (nothing,nothing)\n",
+      "(xmeta,ymeta) = (nothing,nothing)\n",
+      "(xmeta,ymeta) = (nothing,nothing)\n",
+      "(xmeta,ymeta) = (nothing,nothing)\n",
+      "(xmeta,ymeta) = (nothing,nothing)\n",
+      "(xmeta,ymeta) = (nothing,nothing)\n",
+      "(xmeta,ymeta) = (nothing,nothing)\n",
+      "(xmeta,ymeta) = (nothing,nothing)\n",
+      "(xmeta,ymeta) = (nothing,nothing)\n",
+      "(xmeta,ymeta) = (nothing,nothing)\n",
+      "(xmeta,ymeta) = (nothing,nothing)\n",
+      "(xmeta,ymeta) = (nothing,nothing)\n",
+      "(xmeta,ymeta) = (nothing,nothing)\n",
+      "(xmeta,ymeta) = (nothing,nothing)\n",
+      "(xmeta,ymeta) = (nothing,nothing)\n"
      ]
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "Plot{Plots.GadflyPackage() n=1}"
-      ]
-     },
-     "execution_count": 2,
-     "metadata": {},
-     "output_type": "execute_result"
     }
    ],
-   "source": [
-    "p"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {
-    "collapsed": false,
-    "slideshow": {
-     "slide_type": "slide"
-    }
-   },
-   "outputs": [],
    "source": [
     "# use the same parametric functions to create a custom marker shape\n",
     "us = linspace(0, 2π, 100)\n",
-    "heart = Shape([(fx(u), -fy(u)) for u in us])\n",
+    "heart = Shape([(fx(u), fy(u)) for u in us])\n",
     "\n",
     "# generate some data\n",
     "n = 50\n",
@@ -475,7 +672,7 @@
     "title!(\"Let me count the ways...\")\n",
     "\n",
     "# add a new series\n",
-    "scatter!(zeros(0),zeros(0), z=0:n, marker=(heart,15,:reds))\n",
+    "scatter!(1, z=1:n, marker=(heart,15,:reds))\n",
     "\n",
     "# animations!\n",
     "anim = Animation()\n",
@@ -495,7 +692,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 9,
    "metadata": {
     "collapsed": false,
     "slideshow": {
@@ -513,13 +710,13 @@
     {
      "data": {
       "text/html": [
-       "<img src=\"iheartplots.gif?0.35511351462964247>\" />"
+       "<img src=\"iheartplots.gif?0.180000369927116>\" />"
       ],
       "text/plain": [
        "Plots.AnimatedGif(\"/home/tom/.julia/v0.4/Plots/examples/meetup/iheartplots.gif\")"
       ]
      },
-     "execution_count": 4,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -592,7 +789,7 @@
  "metadata": {
   "celltoolbar": "Slideshow",
   "kernelspec": {
-   "display_name": "Julia 0.4.0-rc4",
+   "display_name": "Julia 0.4.0",
    "language": "julia",
    "name": "julia-0.4"
   },
diff --git a/src/backends/immerse.jl b/src/backends/immerse.jl
index 14a6699a..5b520c50 100644
--- a/src/backends/immerse.jl
+++ b/src/backends/immerse.jl
@@ -80,7 +80,9 @@ end
 
 function Base.setindex!(plt::Plot{ImmersePackage}, xy::Tuple, i::Integer)
   for mapping in getGadflyMappings(plt, i)
+    # @show "before",i xy mapping[:x] mapping[:y]
     mapping[:x], mapping[:y] = xy
+    # @show "after",i xy mapping[:x] mapping[:y]
   end
   plt
 end
diff --git a/src/plot.jl b/src/plot.jl
index aceb6002..3bef2888 100644
--- a/src/plot.jl
+++ b/src/plot.jl
@@ -111,7 +111,7 @@ function plot!(plt::Plot, args...; kw...)
   kwList, xmeta, ymeta = createKWargsList(plt, groupargs..., args...; d...)
   
   # if we were able to extract guide information from the series inputs, then update the plot
-  @show xmeta, ymeta
+  # @show xmeta, ymeta
   updateDictWithMeta(d, plt.initargs, xmeta, true)
   updateDictWithMeta(d, plt.initargs, ymeta, false)
 
@@ -225,7 +225,7 @@ typealias FuncOrFuncs @compat(Union{Function, AVec{Function}})
 convertToAnyVector(v::@compat(Void); kw...) = Any[nothing], nothing
 
 # fixed number of blank series
-convertToAnyVector(n::Integer; kw...) = Any[zero(0) for i in 1:n], nothing
+convertToAnyVector(n::Integer; kw...) = Any[zeros(0) for i in 1:n], nothing
 
 # numeric vector
 convertToAnyVector{T<:Real}(v::AVec{T}; kw...) = Any[v], nothing
diff --git a/src/utils.jl b/src/utils.jl
index 5d4e14d0..461ac05f 100644
--- a/src/utils.jl
+++ b/src/utils.jl
@@ -290,7 +290,9 @@ end
 
 # used in updating an existing series
 
-extendUnitRange(v::UnitRange{Int}, n::Int = 1) = minimum(v):maximum(v)+n
+extendUnitRange(v::UnitRange{Int}, n::Int = 1) = isempty(v) ? (1:n) : (minimum(v):maximum(v)+n)
+extendSeriesData{T}(v::Range{T}, z::Real) = extendSeriesData(float(collect(v)), z)
+extendSeriesData{T}(v::Range{T}, z::AVec) = extendSeriesData(float(collect(v)), z)
 extendSeriesData{T}(v::AVec{T}, z::Real) = (push!(v, convert(T, z)); v)
 extendSeriesData{T}(v::AVec{T}, z::AVec) = (append!(v, convert(Vector{T}, z)); v)