Julia benchmark Plotly Barchart

{
 "metadata": {
  "language": "Julia",
  "name": "Julia Benchmark Plotly Barchart"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "code",
     "collapsed": true,
     "input": "# IJulia rocks! So does Plotly. Check it out\n\nusing Plotly\napi_key = \"\" # visit https://plot.ly/api to generate an API username and password\nusername = \"\"\n\nPlotly.signin(username, api_key)",
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 1
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": "# Following data taken from http://julialang.org/ frontpage \nbenchmarks = [\"fib\", \"parse_int\", \"quicksort3\", \"mandel\", \"pi_sum\", \"rand_mat_stat\", \"rand_mat_mul\"]\nplatforms = [\"Fortran\", \"Julia\", \"Python\", \"R\", \"Matlab\", \"Mathematica\", \"Javascript\", \"Go\"]\n\ndata = {\n        platforms[1] => [0.26, 5.03, 1.11, 0.86, 0.80, 0.64, 0.96],\n        platforms[2] => [0.91, 1.60, 1.14, 0.85, 1.00, 1.66, 1.01],\n        platforms[3] => [30.37, 13.95, 31.98, 14.19, 16.33, 13.52, 3.41 ],\n        platforms[4] => [411.36, 59.40, 524.29, 106.97, 15.42, 10.84, 3.98  ],\n        platforms[5] => [1992.00, 1463.16, 101.84, 64.58, 1.29, 6.61, 1.10   ],\n        platforms[6] => [64.46, 29.54, 35.74, 6.07, 1.32, 4.52, 1.16 ],\n        platforms[7] => [2.18, 2.43, 3.51, 3.49, 0.84, 3.28, 14.60],\n        platforms[8] => [1.03, 4.79, 1.25, 2.36, 1.41, 8.12, 8.51]\n        }\n\npdata = [ {\"x\"=>benchmarks,\"y\"=>data[k],\"bardir\"=>\"h\",\"type\"=>\"bar\",\"name\"=>k} for k = platforms ]\n\nlayout = {\n          \"title\"=> \"Julia benchmark comparison (smaller is better, C performance = 1.0)\",\n          \"barmode\"=> \"group\",\n          \"autosize\"=> false,\n          \"width\"=> 900,\n          \"height\"=> 900,\n          \"titlefont\"=>\n          {\n           \"family\"=> \"Open Sans\",\n           \"size\"=> 18,\n           \"color\"=> \"rgb(84, 39, 143)\"\n           },\n          \"margin\"=> {\"l\"=>160, \"pad\"=>0},\n          \"xaxis\"=> {\n                     \"title\"=> \"Benchmark log-time\",\n                     \"type\"=> \"log\"\n                     },\n          \"yaxis\"=> {\"title\"=> \"Benchmark Name\"}\n          }\n\nresponse = Plotly.plot(pdata,[\"layout\"=>layout])\n\n# Embed in an iframe within IJulia\ns = string(\"<iframe height='750' id='igraph' scrolling='no' seamless='seamless' src='\",\n            response[\"url\"],\n            \"/700/700' width='750'></iframe>\")\ndisplay(\"text/html\", s)",
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": "<iframe height='750' id='igraph' scrolling='no' seamless='seamless' src='http://plot.ly/~bpostlethwaiteb/24/700/700' width='750'></iframe>",
       "metadata": {},
       "output_type": "display_data"
      }
     ],
     "prompt_number": 13
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": "# checkout https://plot.ly/api/ for more Julia examples!\n# But to show off some other Plotly features:\nx = 1:1500\ny1 = sin(2*pi*x/1500.) + rand(1500)-0.5\ny2 = sin(2*pi*x/1500.)\n\nfish = {\"x\"=>x,\"y\"=> y1,\n\t\"type\"=>\"scatter\",\"mode\"=>\"markers\",\n\t\"marker\"=>{\"color\"=>\"rgb(0, 0, 255)\",\"opacity\"=>0.5 } }\n\nfit = {\"x\"=> x,\"y\"=> y2,\n\t\"type\"=>\"scatter\", \"mode\"=>\"markers\", \"opacity\"=>0.8,\n\t\"marker\"=>{\"color\"=>\"rgb(255, 0, 0)\"} }\n\nlayout = {\"autosize\"=> false,\n    \"width\"=> 650, \"height\"=> 550,\n    \"title\"=>\"Fish School\",\n\t\"xaxis\"=>{ \"ticks\"=> \"\",\n        \"gridcolor\"=> \"white\",\n        \"zerolinecolor\"=> \"white\",    \n        \"linecolor\"=> \"white\",\n        \"autorange\"=> false,\n        \"range\"=>[0,1500] },\n\t\"yaxis\"=>{ \"ticks\"=> \"\",\n        \"gridcolor\"=> \"white\",\n        \"zerolinecolor\"=> \"white\",\n\t\t\"linecolor\"=> \"white\",\n        \"autorange\"=> false,\n        \"range\"=>[-2.2,2.2] },\n\t\"plot_bgcolor\"=> \"rgb(245,245,247)\",\n    \"showlegend\"=> false,\n    \"hovermode\"=> \"closest\"}\n\nresponse = Plotly.plot([fish, fit],[\"layout\"=>layout])\ns = string(\"<iframe height='750' id='igraph' scrolling='no' seamless='seamless' src='\",\n            response[\"url\"],\n            \"/700/700' width='750'></iframe>\")\ndisplay(\"text/html\", s)",
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": "<iframe height='750' id='igraph' scrolling='no' seamless='seamless' src='http://plot.ly/~bpostlethwaiteb/26/700/700' width='750'></iframe>",
       "metadata": {},
       "output_type": "display_data"
      }
     ],
     "prompt_number": 15
    }
   ],
   "metadata": {}
  }
 ]
}

Concur on both points made (IJulia rocks! So does Plotly).