2013_12_26a_mpld3_nan_issue.ipynb

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     "collapsed": false,
     "input": "!date",
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     "outputs": [
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       "text": "Thu Dec 26 21:05:13 PST 2013\r\n"
      }
     ],
     "prompt_number": 1
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": "import matplotlib.pyplot as plt\nimport mpld3\nreload(mpld3)",
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 2,
       "text": "<module 'mpld3' from '/snfs2/HOME/abie/ENV_dismod/lib/python2.6/site-packages/mpld3-0.0.1-py2.6.egg/mpld3/__init__.pyc'>"
      }
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     "input": "fig = plt.figure(figsize=(12,4))\n\ny = randn(10)\ny[3] = nan\n\nplot(y, 'ks-', mec='w', mew=3, ms=10)\nmpld3.display.display_d3(fig, closefig=False, d3_url='files/d3.v3.js')",
     "language": "python",
     "metadata": {},
     "outputs": [
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pEZHW6tu3L9q1a4cZM2aIjkJEeiwjIwMHDx5EVFQUYmJi0KZNm6J5zC1atBAd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\nJiIiIiIq5v8BU9bCmDmYd1QAAAAASUVORK5CYII=\n",
       "text": "<matplotlib.figure.Figure at 0x348ad10>"
      }
     ],
     "prompt_number": 3
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": "",
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
}