Update README

Update README, LICENSE, add link to documentation, removed unnecessary files
johnmyleswhite · May 27, 2015 · be3dd14 · be3dd14
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diff --git a/LICENSE.md b/LICENSE.md
@@ -1,6 +1,6 @@
 The Vega.jl package is licensed under the MIT "Expat" License:
 
-> Copyright (c) 2015: John Myles White.
+> Copyright (c) 2015: John Myles White and Randy Zwitch.
 >
 > Permission is hereby granted, free of charge, to any person obtaining
 > a copy of this software and associated documentation files (the

diff --git a/README.md b/README.md
@@ -2,13 +2,9 @@ Vega.jl
 =======
 [![Build Status](https://travis-ci.org/johnmyleswhite/Vega.jl.svg?branch=master)](https://travis-ci.org/johnmyleswhite/Vega.jl)
 
-# NOTICE
-
-**5/20/2015: This package is being revived by [Randy Zwitch](https://github.com/randyzwitch) for v0.4. Its reliability is still in flux, but should work in Jupyter Notebook and from the REPL**
-
 # Introduction
 
-A Julia package for creating the simplest kinds of Vega visualizations. We currently support barebones versions of the following:
+A Julia package for creating Vega visualizations. We currently support barebones versions of the following:
 
 * Area plots
 * Bar plots/Histograms
@@ -20,109 +16,11 @@ In addition, this package wraps Vega's pseudo-type system inside of Julia types.
 
 # Installation
 
-This package depends upon [Vega.js](https://github.com/trifacta/vega) from Trifacta and is provided automatically within Vega.jl. If you want to upgrade the library yourself, be sure that the file structure remains the same (and, submit a pull request here!)
+This package depends upon [Vega.js](https://github.com/trifacta/vega) from Trifacta and is provided automatically within Vega.jl. If you want to upgrade the library yourself, be sure that the file structure remains the same.
 
 	Pkg.add("Vega")
 	using Vega
 
-# Usage Examples
-
-The current API provides some convenience wrappers around Vega for generating standard kinds of plots. These are described below. If you have any issues with the examples, please try checking out master for `Distributions`, `Grid`, `Optim` and `KernelDensity`. While these packages aren't requirements to use Vega.jl, they are used for generating data to plot in the examples.
-
-	using Distributions
-	using Vega
-
-	plot(x = [1, 2, 3, 4, 5],
-		 y = [1, 2, 3, 2, 1],
-		 kind = :bar)
-
-![Example 1](content/demo1.jpg)
-
-	srand(1)
-	plot(x = [1:20],
-		 y = rand(20),
-		 kind = :bar)
-
-![Example 2](content/demo2.jpg)
-
-	plot(x = [1:20],
-		 y = rand(20),
-		 group = vcat([1 for i in 1:10], [2 for i in 1:10]),
-		 kind = :bar)
-
-![Example 3](content/demo3.jpg)
-
-	plot(x = [1:100, 1:100],
-		 y = [[1:100] + randn(100), 3.0 + 1.5 * [1:100] + randn(100)],
-		 group = [[1 for i in 1:100], [2 for i in 1:100]],
-		 kind = :line)
-
-![Example 4](content/demo4.jpg)
-
-	d1 = MultivariateNormal([0.0, 0.0], [1.0 0.9; 0.9 1.0])
-	d2 = MultivariateNormal([10.0, 10.0], [4.0 0.5; 0.5 4.0])
-	points = vcat(rand(d1, 500)', rand(d2, 500)')
-	x = points[:, 1]
-	y = points[:, 2]
-	plot(x = x, y = y,
-		 group = vcat(ones(Int, 500), ones(Int, 500) + 1),
-		 kind = :scatter)
-
-![Example 5](content/demo5.jpg)
-
-	using KernelDensity
-	x = rand(Gamma(1.0, 1.0), 1_000_000)
-	k = kde(x)
-	plot(x = k.x, y = k.density, kind = :area)
-
-![Example 6](content/demo6.jpg)
-
-	x = rand(Beta(3.0, 2.0), 1_000_000)
-	k = kde(x)
-	plot(x = k.x, y = k.density, kind = :area)
-
-![Example 7](content/demo7.jpg)
-
-	n = 30
-	x = Array(Int, n^2)
-	y = Array(Int, n^2)
-	color = Array(Int, n^2)
-	t = 0
-	for i in 1:n
-	    for j in 1:n
-	        t += 1
-	        x[t] = i
-	        y[t] = j
-	        color[t] = Int(rand() > 0.5)
-	    end
-	end
-	heatmap(x = x, y = y, group = color)
-
-![Example 8](content/heatmap.png)
-
-	fruit = ["peaches", "plums", "blueberries", "strawberries", "bananas"]
-	bushels = [100, 32, 180, 46, 21]
-	plot(x = fruit, y = bushels, kind = :pie)
-
-![Example 9](content/pie.png)
-
-	plot(x = fruit, y = bushels, kind = :donut)
-
-![Example 10](content/donut.png)
-
-	x = rand(Gamma(3.0, 1.0), 1_000_000)
-	v = histogram(x = x, relativefreq = true)
-	hidelegend!(v)
-![Example 11](content/histogram.png)
+# Documentation
 
-	using DataFrames, JSON
-	df = DataFrame()
-	for p in JSON.parse(readall(Pkg.dir("Vega", "deps/vega/examples/data/population.json")))
-	    df = vcat(df, DataFrame(;[symbol(k)=>v for (k,v) in p]...))
-	end
-	pop1900 = df[df[:year] .== 1900, :];
-	x = pop1900[:people]
-	y = pop1900[:age]
-	group = pop1900[:sex]
-	popchart(x = x, y = y, group = group)
-![Example 12](content/popchart.png)
+For documentation of the current functionality of this package, please see the [documentation](http://johnmyleswhite.github.io/Vega.jl/)
diff --git a/REQUIRE b/REQUIRE
@@ -1,2 +1,2 @@
-julia 0.3
+julia 0.4-
 JSON
diff --git a/_site/REQUIRE b/_site/REQUIRE
@@ -0,0 +1,2 @@
+julia 0.4-
+JSON
diff --git a/content/demo1.jpg b/content/demo1.jpg
diff --git a/content/demo2.jpg b/content/demo2.jpg
diff --git a/content/demo3.jpg b/content/demo3.jpg
diff --git a/content/demo4.jpg b/content/demo4.jpg
diff --git a/content/demo5.jpg b/content/demo5.jpg
diff --git a/content/demo6.jpg b/content/demo6.jpg
diff --git a/content/demo7.jpg b/content/demo7.jpg
diff --git a/content/donut.png b/content/donut.png
diff --git a/content/heatmap.png b/content/heatmap.png
diff --git a/content/histogram.png b/content/histogram.png
diff --git a/content/pie.png b/content/pie.png
diff --git a/content/popchart.png b/content/popchart.png
diff --git a/demo.jl b/demo.jl