multiple y axis range

gistfile1.txt

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   "cells": [
    {
     "cell_type": "code",
     "collapsed": false,
     "input": "import plotly\npp = plotly.plotly('IPython.Demo', '1fw3zw2o13')",
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 1
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": "import numpy as np\nimport pandas as pd\n\ndates = pd.date_range(start='11/1/2008', end='7/31/2012', freq='M')\n\nc = ['#fbb4ae',\n'#b3cde3',\n'#ccebc5',\n'#decbe4',] \n\nprograms = ['USCG', 'COPPS', 'NOVA', 'WSC', 'CSA']\n\nband_width = 22\n\nSMA = [{'name': 'USCG',\n    'x': pd.date_range(start='2/1/2009', end='5/1/2009', freq='M'),\n    'y': np.ones(100)*5,\n    'mode':'lines',\n    'line':{'color': c[0], 'width': band_width},\n    \"yaxis\": \"yaxis2\"\n},\n{'name': 'USCG',\n    'x': pd.date_range(start='1/1/2010', end='7/1/2010', freq='M'),\n    'y': np.ones(100)*5,\n    'mode':'lines',\n    'line':{'color': c[0], 'width': band_width},\n    \"yaxis\": \"yaxis2\"\n},\n{'name': 'USCG',\n    'x': pd.date_range(start='11/1/2010', end='6/1/2011', freq='M'),\n    'y': np.ones(100)*5,\n    'mode':'lines',\n    'line':{'color': c[0], 'width': band_width},\n},\n{'name': 'USCG',\n    'x': pd.date_range(start='1/1/2012', end='3/1/2012', freq='M'),\n    'y': np.ones(100)*5,\n    'mode':'lines',\n    'line':{'color': c[0], 'width': band_width},\n    \"yaxis\": \"yaxis2\"\n}\n,{'name': 'COPPS',\n    'x': pd.date_range(start='10/1/2009', end='12/31/2009', freq='M'),\n    'y': np.ones(100)*4,\n    'mode':'lines',\n    'line':{'color': c[1], 'width': band_width},\n    \"yaxis\": \"yaxis2\"\n},\n{'name': 'NOVA',\n    'x': pd.date_range(start='11/1/2010', end='8/1/2012', freq='M'),\n    'y': np.ones(100)*3,\n    'mode':'lines',\n    'line':{'color': c[2], 'width': band_width},\n    \"yaxis\": \"yaxis2\"\n},\n{'name': 'WSC',\n    'x': pd.date_range(start='12/1/2010', end='8/1/2012', freq='M'),\n    'y': np.ones(100)*2,\n    'mode':'lines',\n    'line':{'color': c[3], 'width': band_width},\n    \"yaxis\": \"yaxis2\"\n},\n{'name': 'CSA',\n    'x': pd.date_range(start='2/1/2011', end='8/1/2012', freq='M'),\n    'y': np.ones(100)*1,\n    'mode':'lines',\n    'line':{'color': c[3], 'width': band_width},\n    \"yaxis\": \"yaxis2\"\n}]\n\nsma_dates = pd.date_range(start='11/1/2008', end='7/31/2012', freq='12M')\n\nestimates = [{'x': sma_dates, 'y': np.array([0, -0.04, 0.16, -0.67]), 'name': 'Passenger'}]\n#estimates = [{'x': range(4), 'y': [0, -0.04, 0.16, -0.67], 'name': 'Passenger', \n#'marker':{'color':'rgb(111, 168, 220)'},\n#'error_y': {'type': 'data', 'array': [0, 0.08, 0.08, 0.08], 'visible': True, 'color': 'rgb(67, 67, 67)'}}]\n\n# data = [{'x': [1]*2, 'y': [1]*2, \"type\": \"line\"},\n#         {'x': [1]*2, 'y': [2]*2, \"type\": \"line\"}]\n\nlayout = {\n   \"yaxis2\":{\n      'showgrid': False,\n      'zeroline': False,\n      'ticks': '',\n      \"showticklabels\" : False,\n      \"overlaying\":\"y\",\n\n   }, \n\n   \"yaxis\":{\n      \"range\": [0, 6],            \n      \"title\": \"Speed change from initial season\",\n      \"titlefont\":{\n         \"color\": '#1f77b4'\n      },\n      \"tickfont\":{\n         \"color\": '#1f77b4'\n      },\n      'showgrid': False,\n      'zeroline': False\n   },  \n    \"xaxis\": {'showgrid':False,'zeroline':False, \n                    'title': 'Date',\n                    'range': [dates[0], dates[-1]]},\n\n   \"title\": \"\",\n   'showlegend': False\n}\n\n\npp.iplot(SMA, layout=layout) \n\n",
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": "<iframe height=\"500\" id=\"igraph\" scrolling=\"no\" seamless=\"seamless\" src=\"https://plot.ly/~IPython.Demo/510/600/450\" width=\"650\"></iframe>",
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 2,
       "text": "<IPython.core.display.HTML at 0x10073c810>"
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     "prompt_number": 2
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     "cell_type": "code",
     "collapsed": false,
     "input": "",
     "language": "python",
     "metadata": {},
     "outputs": []
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