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 "worksheets": [
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   "cells": [
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<img src=\"https://raw.github.com/sunpy/sunpy-logo/master/generated/sunpy_logo_compact_192x239.png\">\n",
      "# SunPy Demo RHESSI Workshop 13\n",
      "## Author: Steven Christe\n",
      "Email: steven.christe@nasa.gov"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "## What is SunPy?\n",
      "### A community-developed, free and open-source solar data analysis environment for Python."
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "website: [http://www.sunpy.org](http://www.sunpy.org)<br>\n",
      "docs: [http://docs.sunpy.org](http://docs.sunpy.org)<br>\n",
      "code (version control!): [https://github.com/sunpy/sunpy](https://github.com/sunpy/sunpy)"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "SunPy is built upon foundational libraries which enable scientific computing in Python which includes\n",
      "\n",
      "+ [NumPy](http://numpy.org)\n",
      "+ [SciPy](http://scipy.org)\n",
      "+ [matplotlib](http://matplotlib.org)\n",
      "\n",
      "and also (increasingly)\n",
      "\n",
      "+ [AstroPy](http://astropy.org)"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "This ipython notebook file can be found at\n",
      "\n",
      "* [ipython notebook file](https://raw.githubusercontent.com/ehsteve/ipython-notebooks/master/RHESSI%20Workshope%2013%20-%20SunPy.ipynb)\n",
      "\n",
      "or can be viewed (if you don't have ipython installed) here\n",
      "\n",
      "* [ipython notebook viewer](http://nbviewer.ipython.org/urls/raw.githubusercontent.com/ehsteve/ipython-notebooks/master/RHESSI%20Workshope%2013%20-%20SunPy.ipynb?create=1)"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Setting up the notebook for inline plots"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%matplotlib inline"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 1
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import numpy as np"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 2
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import matplotlib.pyplot as plt"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 3
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import sunpy"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 4
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "sunpy.system_info()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "==========================================================\n",
        " SunPy Installation Information\n",
        "\n",
        "==========================================================\n",
        "\n",
        "###########\n",
        " General\n",
        "###########\n",
        "Time : Friday, 04. April 2014 07:22AM UT\n",
        "System : Darwin\n",
        "Processor : i386\n",
        "Arch : 64bit\n",
        "SunPy : 0.3.2\n",
        "SunPy_git : v0.3.1-878-g5d3d14a\n",
        "OS: Mac OS X 10.9.2 (i386)\n",
        "\n",
        "\n",
        "###########\n",
        " Required Libraries \n",
        "###########\n",
        "Python: 2.7.6\n",
        "NumPy: 1.8.1\n",
        "SciPy: 0.13.3\n",
        "matplotlib: 1.3.1\n",
        "Astropy: 0.3\n",
        "Pandas: 0.13.1\n",
        "\n",
        "\n",
        "###########\n",
        " Recommended Libraries \n",
        "###########\n",
        "beautifulsoup: 4.3.1\n",
        "PyQt: 4.9.4\n",
        "SUDS: 0.4\n",
        "Sqlalchemy: 0.8.3\n",
        "Requests: 1.2.3\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stderr",
       "text": [
        "/Users/schriste/anaconda/lib/python2.7/site-packages/pytz/__init__.py:29: UserWarning: Module _imaging was already imported from /Users/schriste/anaconda/lib/python2.7/site-packages/PIL/_imaging.so, but /Users/schriste/.local/lib/python2.7/site-packages is being added to sys.path\n",
        "  from pkg_resources import resource_stream\n"
       ]
      }
     ],
     "prompt_number": 5
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "#1. Solar Images in SunPy"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "SunPy has a `Map` type that supports 2D images, it makes it simple to read data in from any filetype supported in `sunpy.io` which is currently FITS, JPEG2000 and ANA files. You can also create maps from any `(data, metadata)` pair.\n",
      "\n",
      "SunPy contains a few test data files, under the `sunpy` namespace:\n",
      "\n",
      "* `sunpy.AIA_171_IMAGE`\n",
      "* `sunpy.CALLISTO_IMAGE`\n",
      "* `sunpy.EIT_195_IMAGE`\n",
      "* `sunpy.RHESSI_EVENT_LIST`\n",
      "* `sunpy.RHESSI_IMAGE`\n",
      "\n",
      "These are all just links to FITS files contained in the SunPy distribution."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "print sunpy.AIA_171_IMAGE"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "/Users/schriste/Dropbox/Developer/python/sunpy/sunpy/data/sample/AIA20110319_105400_0171.fits\n"
       ]
      }
     ],
     "prompt_number": 6
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import sunpy.map\n",
      "\n",
      "aiamap = sunpy.map.Map(sunpy.AIA_171_IMAGE)\n",
      "aiamap"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 7,
       "text": [
        "SunPy AIAMap\n",
        "---------\n",
        "Observatory:\t SDO\n",
        "Instrument:\t AIA_3\n",
        "Detector:\t AIA\n",
        "Measurement:\t 171\n",
        "Obs Date:\t 2011-03-19T10:54:00.34\n",
        "dt:\t\t 1.999601\n",
        "Dimension:\t [1024, 1024]\n",
        "[dx, dy] =\t [2.400000, 2.400000]\n",
        "\n",
        "array([[ 0.3125, -0.0625, -0.125 , ...,  0.625 , -0.625 ,  0.    ],\n",
        "       [ 1.    ,  0.1875, -0.8125, ...,  0.625 , -0.625 ,  0.    ],\n",
        "       [-1.1875,  0.375 , -0.5   , ..., -0.125 , -0.625 , -1.1875],\n",
        "       ..., \n",
        "       [-0.625 ,  0.0625, -0.3125, ...,  0.125 ,  0.125 ,  0.125 ],\n",
        "       [ 0.5625,  0.0625,  0.5625, ..., -0.0625, -0.0625,  0.    ],\n",
        "       [ 0.5   , -0.125 ,  0.4375, ...,  0.6875,  0.6875,  0.6875]])"
       ]
      }
     ],
     "prompt_number": 7
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Maps contain both the image data and the metadata associated with the image, this metadata currently does not deviate much from the standard FITS WCS keywords, but presented in a instrument-independant manner.\n",
      "\n",
      "[Documentation on the Map Object](http://docs.sunpy.org/en/stable/api/sunpy.map.mapbase.GenericMap.html#sunpy.map.mapbase.GenericMap)"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "The data (stored in a numpy array)"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "aiamap.data"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 8,
       "text": [
        "array([[ 0.3125, -0.0625, -0.125 , ...,  0.625 , -0.625 ,  0.    ],\n",
        "       [ 1.    ,  0.1875, -0.8125, ...,  0.625 , -0.625 ,  0.    ],\n",
        "       [-1.1875,  0.375 , -0.5   , ..., -0.125 , -0.625 , -1.1875],\n",
        "       ..., \n",
        "       [-0.625 ,  0.0625, -0.3125, ...,  0.125 ,  0.125 ,  0.125 ],\n",
        "       [ 0.5625,  0.0625,  0.5625, ..., -0.0625, -0.0625,  0.    ],\n",
        "       [ 0.5   , -0.125 ,  0.4375, ...,  0.6875,  0.6875,  0.6875]])"
       ]
      }
     ],
     "prompt_number": 8
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "aiamap.data.max()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 9,
       "text": [
        "9429.125"
       ]
      }
     ],
     "prompt_number": 9
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "The standard deviation"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "aiamap.data.std()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 10,
       "text": [
        "292.43424704678557"
       ]
      }
     ],
     "prompt_number": 10
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "aiamap.data.min()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 11,
       "text": [
        "-2.0"
       ]
      }
     ],
     "prompt_number": 11
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "The original metadata (stored in a dictionary)"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "aiamap.meta"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 12,
       "text": [
        "MapMeta([('dsun_obs', 148940609626.98), ('t_obs', '2011-03-19T10:54:01.34Z'), ('tobsepoc', '1977.01.01_00:00:00_TAI'), ('simple', True), ('datavals', 16777216), ('aimgshen', 4), ('aiagp2', 0), ('aiftsid', 40960), ('comment', \"FITS (Flexible Image Transport System) format is defined in 'Astronomy  and Astrophysics', volume 376, page 359; bibcode: 2001A&A...376..359H\"), ('aihis348', 8388262), ('roi_llx2', -2147483648), ('extend', True), ('aivnmst', 453), ('aicfgdl4', 236), ('crlt_obs', -7.064078), ('aicfgdl1', 0), ('aicfgdl2', 137), ('aicfgdl3', 201), ('totvals', 16777216), ('acs_mode', 'SCIENCE'), ('isppktvn', '001.197'), ('aimshobe', 26.076), ('aimshobc', 41.099998), ('aihis860', 8388603), ('r_sun', 1608.94397), ('orb_rec', 'sdo.fds_orbit_vectors[2011.03.19_10:54:00_UTC]'), ('fid', 0), ('wave_str', '171_THIN'), ('aecdelay', 1540), ('int_time', 2.273438), ('aimshcbc', 2040.791992), ('crval1', 0.0), ('lvl_num', 1.5), ('acs_safe', 'NO'), ('aimshcbe', 2025.864014), ('aifoenfl', 1), ('y0_lf', 'nan'), ('aifdbid', 241), ('ctype2', 'HPLT-TAN'), ('ctype1', 'HPLN-TAN'), ('exptime', 1.999601), ('quallev0', 0), ('obs_vn', 2177.6711), ('aiasen', 0), ('aifcps', 10), ('cdelt1', 2.4), ('cdelt2', 2.4), ('rsun_ref', 696000000.0), ('naxis', 2), ('date-obs', '2011-03-19T10:54:00.34'), ('rsun_lf', 'nan'), ('aistate', 'CLOSED'), ('obs_vw', 30775.731671), ('datamean', 236.57), ('datarms', 294.02), ('obs_vr', -2132.568376), ('rsun_obs', 963.879683), ('aiawvlen', 7), ('instrume', 'AIA_3'), ('camera', 3), ('blank', -2147483648), ('oscnrms', 'nan'), ('oscnmean', 'nan'), ('aimgots', 1679223275), ('roi_llx1', -2147483648), ('naxis1', 1024), ('naxis2', 1024), ('datakurt', 49.56), ('aifiltyp', 0), ('acs_eclp', 'NO'), ('agt1svy', 18), ('roi_nwin', -2147483648), ('agt1svz', 10), ('aiaecenf', 1), ('checksum', 'J7qAL7o6J7oAJ7o5'), ('inst_rot', 0.102488), ('percentd', 100.0), ('acs_cgt', 'GT3'), ('bitpix', 32), ('asd_rec', 'sdo.lev0_asd_0004[:#8948067]'), ('aimgfsn', 5), ('quality', 1073741824), ('roi_sum', -2147483648), ('dataskew', 4.63), ('mpo_rec', 'sdo.master_pointing[:#116]'), ('roi_nax2', -2147483648), ('fsn', 22642033), ('roi_nax1', -2147483648), ('dsun_ref', 149597870691.0), ('aihismxb', 7), ('expsdev', 0.00016), ('aiahfsn', 22642025), ('car_rot', 2108), ('gciec_y', 'nan'), ('gciec_x', 'nan'), ('gciec_z', 'nan'), ('aimgtyp', 0), ('datasum', '3958014355'), ('cunit1', 'arcsec'), ('asqtnum', 2), ('cunit2', 'arcsec'), ('crln_obs', 315.285065), ('origin', 'SDO/JSOC-SDP'), ('roi_nay2', -2147483648), ('aihis604', 8388597), ('agt3svz', 0), ('datamin', -7), ('imscl_mp', 0.599076), ('aifrmlid', 3024), ('crval2', 0.0), ('crpix1', 512.5), ('crpix2', 512.5), ('sat_z0', 14.820671), ('telescop', 'SDO/AIA'), ('wavelnth', 171), ('isppktim', '2011-03-19T10:53:57.50Z'), ('keycomments', {'DATASUM': 'data unit checksum updated 2011-03-19T11:08:18', 'EXTEND': 'FITS dataset may contain extensions', 'NAXIS1': 'length of data axis 1', 'CHECKSUM': 'HDU checksum updated 2011-03-19T11:08:18', 'NAXIS2': 'length of data axis 2', 'NAXIS': 'number of data axes', 'SIMPLE': 'file does conform to FITS standard', 'BITPIX': 'number of bits per data pixel'}), ('datamax', 16228), ('asqfsn', 22642033), ('y0_mp', 2046.589966), ('roi_nay1', -2147483648), ('aimgshce', 2000), ('aimgotss', 5339), ('agt3svy', 2), ('aecmode', 'ON'), ('date', '2011-03-19T11:08:25'), ('aihis192', 8381297), ('img_type', 'LIGHT'), ('aiagp8', 393), ('aiagp9', 457), ('aimshcte', 2068.676025), ('aiagp5', 0), ('aiagp6', 0), ('aiagp7', 0), ('aiagp1', 0), ('aimshctc', 2054.875977), ('aiagp3', 0), ('sat_rot', -8.8e-05), ('agt4svz', 0), ('crota2', 0.0), ('aiftswth', 0), ('agt4svy', 14), ('x0_lf', 'nan'), ('recnum', 76202), ('aifwen', 204), ('hciec_z', 'nan'), ('aiagp10', 748), ('hciec_x', 'nan'), ('hciec_y', 'nan'), ('datamedn', 192), ('missvals', 0), ('aiaecti', 0), ('tobsstep', 90.0), ('asqhdr', 2170125681), ('acs_sunp', 'YES'), ('history', ''), ('waveunit', 'angstrom'), ('flat_rec', 'aia.flatfield[:#7]'), ('bzero', 0.0), ('roi_lly2', -2147483648), ('x0_mp', 2052.399902), ('roi_lly1', -2147483648), ('aiagp4', 0), ('aimshotc', 55.312), ('agt2svy', 10), ('aimshote', 69.316002), ('agt2svz', 8), ('ispsname', 'aia.lev0_isp_0011'), ('bscale', 0.0625), ('aectype', 0), ('sat_y0', -0.365593), ('detector', 'AIA')])"
       ]
      }
     ],
     "prompt_number": 12
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "aiamap.meta.keys()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 13,
       "text": [
        "['dsun_obs',\n",
        " 't_obs',\n",
        " 'tobsepoc',\n",
        " 'simple',\n",
        " 'datavals',\n",
        " 'aimgshen',\n",
        " 'aiagp2',\n",
        " 'aiftsid',\n",
        " 'comment',\n",
        " 'aihis348',\n",
        " 'roi_llx2',\n",
        " 'extend',\n",
        " 'aivnmst',\n",
        " 'aicfgdl4',\n",
        " 'crlt_obs',\n",
        " 'aicfgdl1',\n",
        " 'aicfgdl2',\n",
        " 'aicfgdl3',\n",
        " 'totvals',\n",
        " 'acs_mode',\n",
        " 'isppktvn',\n",
        " 'aimshobe',\n",
        " 'aimshobc',\n",
        " 'aihis860',\n",
        " 'r_sun',\n",
        " 'orb_rec',\n",
        " 'fid',\n",
        " 'wave_str',\n",
        " 'aecdelay',\n",
        " 'int_time',\n",
        " 'aimshcbc',\n",
        " 'crval1',\n",
        " 'lvl_num',\n",
        " 'acs_safe',\n",
        " 'aimshcbe',\n",
        " 'aifoenfl',\n",
        " 'y0_lf',\n",
        " 'aifdbid',\n",
        " 'ctype2',\n",
        " 'ctype1',\n",
        " 'exptime',\n",
        " 'quallev0',\n",
        " 'obs_vn',\n",
        " 'aiasen',\n",
        " 'aifcps',\n",
        " 'cdelt1',\n",
        " 'cdelt2',\n",
        " 'rsun_ref',\n",
        " 'naxis',\n",
        " 'date-obs',\n",
        " 'rsun_lf',\n",
        " 'aistate',\n",
        " 'obs_vw',\n",
        " 'datamean',\n",
        " 'datarms',\n",
        " 'obs_vr',\n",
        " 'rsun_obs',\n",
        " 'aiawvlen',\n",
        " 'instrume',\n",
        " 'camera',\n",
        " 'blank',\n",
        " 'oscnrms',\n",
        " 'oscnmean',\n",
        " 'aimgots',\n",
        " 'roi_llx1',\n",
        " 'naxis1',\n",
        " 'naxis2',\n",
        " 'datakurt',\n",
        " 'aifiltyp',\n",
        " 'acs_eclp',\n",
        " 'agt1svy',\n",
        " 'roi_nwin',\n",
        " 'agt1svz',\n",
        " 'aiaecenf',\n",
        " 'checksum',\n",
        " 'inst_rot',\n",
        " 'percentd',\n",
        " 'acs_cgt',\n",
        " 'bitpix',\n",
        " 'asd_rec',\n",
        " 'aimgfsn',\n",
        " 'quality',\n",
        " 'roi_sum',\n",
        " 'dataskew',\n",
        " 'mpo_rec',\n",
        " 'roi_nax2',\n",
        " 'fsn',\n",
        " 'roi_nax1',\n",
        " 'dsun_ref',\n",
        " 'aihismxb',\n",
        " 'expsdev',\n",
        " 'aiahfsn',\n",
        " 'car_rot',\n",
        " 'gciec_y',\n",
        " 'gciec_x',\n",
        " 'gciec_z',\n",
        " 'aimgtyp',\n",
        " 'datasum',\n",
        " 'cunit1',\n",
        " 'asqtnum',\n",
        " 'cunit2',\n",
        " 'crln_obs',\n",
        " 'origin',\n",
        " 'roi_nay2',\n",
        " 'aihis604',\n",
        " 'agt3svz',\n",
        " 'datamin',\n",
        " 'imscl_mp',\n",
        " 'aifrmlid',\n",
        " 'crval2',\n",
        " 'crpix1',\n",
        " 'crpix2',\n",
        " 'sat_z0',\n",
        " 'telescop',\n",
        " 'wavelnth',\n",
        " 'isppktim',\n",
        " 'keycomments',\n",
        " 'datamax',\n",
        " 'asqfsn',\n",
        " 'y0_mp',\n",
        " 'roi_nay1',\n",
        " 'aimgshce',\n",
        " 'aimgotss',\n",
        " 'agt3svy',\n",
        " 'aecmode',\n",
        " 'date',\n",
        " 'aihis192',\n",
        " 'img_type',\n",
        " 'aiagp8',\n",
        " 'aiagp9',\n",
        " 'aimshcte',\n",
        " 'aiagp5',\n",
        " 'aiagp6',\n",
        " 'aiagp7',\n",
        " 'aiagp1',\n",
        " 'aimshctc',\n",
        " 'aiagp3',\n",
        " 'sat_rot',\n",
        " 'agt4svz',\n",
        " 'crota2',\n",
        " 'aiftswth',\n",
        " 'agt4svy',\n",
        " 'x0_lf',\n",
        " 'recnum',\n",
        " 'aifwen',\n",
        " 'hciec_z',\n",
        " 'aiagp10',\n",
        " 'hciec_x',\n",
        " 'hciec_y',\n",
        " 'datamedn',\n",
        " 'missvals',\n",
        " 'aiaecti',\n",
        " 'tobsstep',\n",
        " 'asqhdr',\n",
        " 'acs_sunp',\n",
        " 'history',\n",
        " 'waveunit',\n",
        " 'flat_rec',\n",
        " 'bzero',\n",
        " 'roi_lly2',\n",
        " 'x0_mp',\n",
        " 'roi_lly1',\n",
        " 'aiagp4',\n",
        " 'aimshotc',\n",
        " 'agt2svy',\n",
        " 'aimshote',\n",
        " 'agt2svz',\n",
        " 'ispsname',\n",
        " 'bscale',\n",
        " 'aectype',\n",
        " 'sat_y0',\n",
        " 'detector']"
       ]
      }
     ],
     "prompt_number": 13
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "aiamap.meta.get('rsun_obs')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 14,
       "text": [
        "963.879683"
       ]
      }
     ],
     "prompt_number": 14
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "We also provide quick access to some key metadata values as object variables"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "print(aiamap.date, aiamap.coordinate_system, aiamap.detector, aiamap.dsun)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "('2011-03-19T10:54:00.34', {'y': 'HPLT-TAN', 'x': 'HPLN-TAN'}, 'AIA', 148940609626.98)\n"
       ]
      }
     ],
     "prompt_number": 15
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "The properties of the map provide a standard way of reading meta data. For instance the pixel scale can be accessed with the `.scale` attribute:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "aiamap.scale"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 16,
       "text": [
        "{'x': 2.4, 'y': 2.4}"
       ]
      }
     ],
     "prompt_number": 16
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "aiamap.yrange"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 17,
       "text": [
        "[-1228.8, 1228.8]"
       ]
      }
     ],
     "prompt_number": 17
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "aiamap.xrange"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 18,
       "text": [
        "[-1228.8, 1228.8]"
       ]
      }
     ],
     "prompt_number": 18
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Map provides some useful functions such as \n",
      "\n",
      "+ submap\n",
      "+ plotting\n",
      "+ resampling"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "##Playing with a map"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "aiasub = aiamap.submap([-250,50],[-550,-250])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 19
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "aiasub.xrange, aiasub.yrange"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 20,
       "text": [
        "([-249.59999999999999, 50.400000000000006],\n",
        " [-549.60000000000002, -249.60000000000002])"
       ]
      }
     ],
     "prompt_number": 20
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "fig, ax = plt.subplots(1, figsize=(7,7))\n",
      "im = aiasub.plot(axes=ax, vmin=100, vmax=aiasub.data.max())\n",
      "ax = aiasub.draw_grid(grid_spacing=5)\n",
      "cbar = plt.colorbar()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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ccYfHTlSWZaUsWZZRWVmpuM137doVffr0wQsvvICKigp8/fXXOHjwoMd5z61btyIrKwuy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iWD0xpULCNitsOlslG5LtP/v9zgx/sLnsOcJ/JC2jghiTHltDNOy6Sw69rPtSFmkNTpgnNW8NX9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\nDAAAAABJRU5ErkJggg==\n",
       "text": [
        "<matplotlib.figure.Figure at 0x10ab322d0>"
       ]
      }
     ],
     "prompt_number": 21
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "## Composite Maps\n",
      "Composite maps inherits from genericMap and can handle multiple maps and lets you plot them together."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "compmap = sunpy.map.Map(sunpy.AIA_171_IMAGE, sunpy.RHESSI_IMAGE, composite=True)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 22
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "levels = np.arange(0,50,5)\n",
      "print(levels)\n",
      "compmap.set_levels(1, levels, percent=True)\n",
      "compmap.set_alpha(1,0.5)\n",
      "compmap.set_colors(1, 'Reds_r')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "[ 0  5 10 15 20 25 30 35 40 45]\n"
       ]
      }
     ],
     "prompt_number": 23
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "ax = plt.subplot()\n",
      "compmap.plot()\n",
      "ax.axis([200, 600, -600, -200])\n",
      "plt.show()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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zMslPutvSjeJQdt5XZPcFu+tFxc3uAD+LBKC7om+cjEMm87vY1QPMux6qmOux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\nhQoVLQKqMFKhQkWLwP8D22A3x4clj6oAAAAASUVORK5CYII=\n",
       "text": [
        "<matplotlib.figure.Figure at 0x10c1e9b90>"
       ]
      }
     ],
     "prompt_number": 24
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "## Spectrograms"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from sunpy.spectra.sources.callisto import CallistoSpectrogram\n",
      "tstart, tend = \"2011-06-07T06:00:00\", \"2011-06-07T07:45:00\"\n",
      "callisto = CallistoSpectrogram.from_range(\"BIR\", tstart, tend)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 25
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "callisto.peek(vmin = 0)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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Zf7iTrD81+eBORj0D0IvOgU6ScCeddBJz5szhS1/6Es8//7zPU23t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\nLQQtJwQnnHACEO1pvPzyyznggAO49tprtyjRL3zhC3zhC19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QsJd6YPEsePkWWN0TYHjT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\n",
       "text": [
        "<sunpy.spectra.spectrogram.SpectroFigure at 0x10d04ec50>"
       ]
      },
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 26,
       "text": [
        "<matplotlib.axes.AxesSubplot at 0x112f440d0>"
       ]
      }
     ],
     "prompt_number": 26
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "callisto_nobg = callisto.subtract_bg()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 27
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "callisto_nobg.peek(vmin = 0)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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FSk5au/z81uvpQVLoy1rmcJ4SwqAE8AkoWVoK7LHKORDAjve8Dmf0OhHEAZxb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\nNNz4JXmk6+eZNFgAI6izH7Pf7yctLY3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Ca59a71xhXeML0yno/uPp2rnsCKzQrkfbxW5Z\ni3N3pv6gHkekF42xQHrlWi1/pDNvtuFV8JBu6jBNBdHMd3HsYKgV9LpGetDIeF1XS97R1P9oD5+6\n0up0A4n0NTdd/wKoN90S1D6E+iPUPPavKcJTMLdu3ZrU1FRSU1NJS0sLn8t1XaEL2/fee4+8vDxA\nxcqoqakBiCtWBhAjVoYfpYL2sM5XYWtE8p03uQnSgGdR2pF+s5dpadLnR7DtwLLIpduf9bGpBmZo\ndQm9eaNLHas0GvFw0BcRpf16+SyXOr8lbC8uQWkFfmxXuHLruqWVlgROn940IBP2W7blJIBW6niC\nVbYE6IO9rTvJ4n0CSkhLGTKtY5X2E7u1fENP728xtoa9DNu/2fwm4zJjDN2Ep+6aNd/IM70KntXO\n4/0cmRvfhkJWHLwfacD6auNBES+tTreZSFe5VQaNH7U2NAA7JED9cLhl7F9ThKciv3+/HTwhLy8v\nwmUuHlx11VUsXLiQ8vJyOnfuzD333MOcOXP44osvaN68Od26deOpp54C4OOPP+b3v/89ycnJNGvW\nLCJWxo033sigQYO48847ufzyy3nuuefCn5ZyRwrKsi+alB/lb+sWwF2GQfxm9QDuOpJd0kAJFdlU\nkWTQSQyMCmwJKZqDV1vMD6jqPM1v92ViB/zJwtZ6DyoBHEApdftR9/nFODeViKAOC00xUaQpHqRD\ncLdqwyGcP2mu8BAvj3bWkYMWz4M4P2hapZ3LUf+PJF2CHZk7CCXgUW2DGEVDU9sBuCM2yTGFxhnf\nYPN4ltGOuKbW1NSQn59PdnY2s2bNori4mMmTJ1NdXU1SUhJPPvkkp556asM22IJnrAwddRXMjQVl\nd34B+5WvEjtqlWz3RbuW/Aojzy1N105F4HbBaRaRV3fZOmzWXWGU99rIUOlSRia48JQjRtu6AD8G\nVoJ/kPqeHxXQLtMZUTG4SSuv83Zro/VVFMd3AS2+Sdbrf1CEZMD6SR9E0OgPtq04b1j5L2SLte6q\nl8B/H+ofK2Nv8LiYdG2SDrvW88gjj7By5Ur27dvHzJkzKSgo4K677uLss8/m/fff5w9/+AMfffRR\nndsXDUc1ulzj4i1gO7bbWwpKu8xCaWTWa3o4PcU419PKjGt5rRYXoqB2beZLeTNNp6tyyZeFMsk3\ny1bhbHOmwSPX2ucyUG2hzk+G1plwDupNcYR1JAflUpaFMjkMwV60y9XOxRUuScntDtaPZJXeDmsR\nUxbZcjSeertbWT99zATVGo30RdeGa+uelcCxiQDK1lx/1DRvHvPnhtLSUubMmcPEiRPDQrtjx45h\nj7Q9e/aQlZXlWrYh4GnKePvtt1V0plCIvXv38s4774Qb6PP5wp9YaboIomJl6PEbJAZDOs5X6kqc\nAhScNlER5BKTolKjERuz5KXjfEWX8J0VBl+wX9szsRfuUrTzKi1frz+NyPaJZio8NsDGXsAqCAyy\nFubKYHGmc+NJ2Na6A2Vy2GBdp2t1BSy+acC3UJ5paMxAebIVFEkW4r7VeMrYgzOutSxUCoTmILaZ\nQvpVqeUnkEB8+I7YGrPbvPrVr37FH//4Ryor7fk5bdo0RowYwW233caRI0f49NNPG7ClTngK5lmz\nZoVd0c444wxmzZrlyG/6gjmBBBL4b0dNHfzhZs+eTUZGBnl5eRQVFYXTJ0yYwJ///GcuueQS3nrr\nLcaPH8+8efMasLU2PFv94osv1pv5+PHj+ec//0lGRgbr1qkFr8LCQp599lnat28PwAMPPMA555xD\nIBAgNzc3/BXtYcOGuW7Lrqio4IorrmDr1q3hxT/3mNAp2CEp07DDd/qtNN3+K4F23CD25VSNPtwa\ng860E4ttNtUlT8p42U+lfcLH3A4rZaVdolWmadcrgYWwuB8qxGYWBPwqr7zUolmrlQX7004VOLVV\n4Yla5HPYktMgmGnZsaXNAp23wCuwlG4jrzSuY/FMIIFI1Lhs7fu06DBLiw57lvnkk0+YOXMmc+bM\n4dChQ1RWVvLTn/6U4uJi5s9XnjKXXnopEydOPGrt9lz8e+QR5YqjZ4tpw+fzMWVK7K2oixYtonXr\n1vzsZz8LC+Z77rmH1NTUiPKBQICxY8eG6bxw++23065dO26//XYefPBB/vOf/0TEy1Ca/jkoO2d3\n3D0t9PMKi3azdZQ0E0InC33CUw/+rn96yqQzhb/QuD0UTO8LU5CJsE93oa+20vuhorj9BnjcusZq\n7zrUItsS3BfZsolcNLVcmFp2hUMyL2Sc2qL8ZCuwvV/0WB7yINCFvdv4iO93EU5PFN3W3JDeGAk0\nPQSs38J6L/59FeoYk+5k3zee9SxcuJCHHnqIWbNmMXDgQB599FFGjhzJggULuPPOO8P7MBoanhrz\nbbfdRv/+/Tn33HNp0aJusfNOP/10AoFARHp9BnvmzJksXLgQULEyCgoKPAIZjUMJCLHZyjHTSs/B\n6T6n76iToDpZRH4cVBbdKrGFjrh1WTvWHHlp2LvygjgfDN9iL4qJ14IsKOgPBinvFm/DfICIn7T0\nWfyaK7D9c3Ot8xycNu4qg4e+8Il13GdFo/NZH3C12pEEBH3YWw3B9l/2Y38rUMZRt+dLH6Sfur+y\nmQYJgdyUcDTeXvzWb2G9OcVnY44OMen+7W9/43//93/57rvvSElJ4W9/+1u9eXvB0ytj1apVnHXW\nWcyZM4etW7dy2mmncffddzN16tRw2M+64vHHH6d///5MmDDBEbazYWNlTEc9deWmF8G3AfvVXAnQ\nW0NJQIDCkGxzdnutr9bSRGiJENV34JkfKq208is1vvruQF2Ii4CWB4qgmsjJv4Mfh3I0uhS6HLnS\noEu1aDJJD94ApDEppNr/YMjaFefTN7CA0pQlLQulvWYBfSG7FfTMVDsJe6Lkb3Yr9cvB+vJ2proO\nby7J0o7m+Eho1RTtWgnjlnt+SXgruIPGRm7oQse16it0CV2pEpYWAjAyNNTqawSLYx9WH/nMOL5o\nHaOGLKgb1H8jOBompQAN5pVBUsxfNIwcOTIcTTM/P59ly5ZRUlLCp59+Gt4cdzTgKZgHDBjAgw8+\nyOrVq5k4cSIzZ86kd+/ecYf89MKkSZPYsmULJSUldOzYkVtvvRU4GrEygkRsWc0vVMeCQqAqfJ1i\n2aL3hWNnyP59EZTWq37PQmxXNZ0OnJ4Wrq3F1tp1zwwvVFn1aTCuU8J8VH/yWWHVMdXqYwVt2Q2E\nyG++AoDObAcqrAkZhPwrcIQLDSPoTHu2lf3JqaBBJteyJ0licYS3AIe0OoLGURvfcOQ5OL/NHJzf\nD0xT/5c2Br1Yr06s/7GttTmmB18AMHCIeri3C7uQ6OXNYzRloxaKiPmfRUOHQvfzWpTtPmQNAAN7\nL3Ycu1+7xiKcUDu+cSC/zUrrbKpx9CpQGCWzoaPzOVFD85i/o4Hdu3fHJoqCmH7Mu3btYvXq1axd\nu5bs7Ozwol1dkZGRERaoEydOpLi4GDgasTK2oybMYsI20hXWNt4iayV1hQpwc99p9wPpPHza77B3\n8UGEO9zGeThf9+XcK3aAHmQnZPMJI92gk/os/hvnaenARn0bchqvnHaDdT4dgLe7XGPRvglFy4Aq\n/nbWzYCPD066CKjkt+MfAar47Th1ZHkZ9hdHkrE//aS7+iXDQyjB68f5hZND2nDJtwNli3aYhw97\n96IePUZc8MzxruTtXj/B3lxjuQmumKeNCbx90k/UyQqV9reTbgbgg14XAbAqfYSTLvQmbJxulX7G\nOOpbsk1EyzOw8ZnYNIKd07XzWpTTym5q1h+AVc1GOI6SzlGIJ704fYx19qxx9MCK6VEy9bIB7FgZ\ngbo0LQLfcVzM39HA0P/P3ruHSVVc68PvwDQyyDTSoIPMoK1cZMDhMqDE++QAXoNJVDAQo4kSj+Qx\nxmgCGpNIDCp4ifH4occoojEeoh6D+DMCwchFTDjKdRAREOkII45CQ2ZGGplh+vuj9upae3XV3rt7\nei7ovM/Tz967atWqVbVrV1etWrXqa1/D+PHj8dprr2WlurV2zHPmzMEFF1yACRMmIJlM4oUXXsCS\nJUtwxhlnNEng3bt3p+7nz5+fOt0k974y+kE5gbkUbksKA5LOqPtIc/Eo5U0aZg9J9zXp0CRNtG0J\nQd5FWvl9rkfcCw4A3zI3Y545RxTaV0Y0JxybqsrIFlu2bMEPf/hD/PGPf0S/fv1w++23Y+vWrYHT\nWzvmH/7wh9i9ezcKCwuxePFiTJ48GePGjcO4ceNw6aWX2pK5MHHiRJx55pnYsmUL+vTpg6eeegrT\npk3DkCFDMHToUCxfvhwPPfQQAOUrY+jQoRg+fDjGjx+f5itjzRo1fbrtttuwZMkSDBgwAG+88YbL\nn3N60Q5Bj/rygWGj1POwsc51FICEHt0ddK6pjSJOOtog0W8sC5c+H/jomOWZ2hTSCXrEGGI8KCwC\ndXozxdcAPce6+fYb5dBAxac2eTibT1I77xLAdaMUz4OA2pbtyNnToe8MoPMoKGuJ/lBe3SjvK6Gc\nBzkH0KJIBXWGdvfRE2r3IPnK6Azl1AhgR1V1QWpW0K+LQ0w+LhxHS6hhYayuO4PFJXT996TRWkS7\nS6UwR7WcUq3QN5c6i+FToPOV+h4VTtkB70NOP/WIE+j8QxHgwTcliymdHyaoi8tlLLR/4X7wQST7\n+FRfViWugHn26LXnoXnNHltLldGhQwecf/75+POf/4wnnngCzzzzDE477TScd955+Mc//uGb3mou\nt2zZMpf+VprNnXeezSVh60PJ/aDzxC0BzoKy241CmYmdBWU2RuZu3HyN7J7DwBWOHmwglOtLAh3P\nRAebgt1THMf//s65qYFeDKsForfoNKuegNa7kg8OarxlcOllr7hFOw6qg1p8e5ryIHejlJZWz6nM\nUSe8EsgfCzQsgbbTPovVmWORQS5AS5zrLlFGcoT2vkOzy4njnWTDNmg99ltI/yjDcC8Ocv0z+dAI\nQx/kSmUi6xnuY6PGcAWax4qAQ/Kn54ugKmUjXO++xeTKJai+gyLbsjXdV8by5Om+dOflvd2kfEzY\ns2cPnnvuOfzxj39EUVFRamC7YcMGXHHFFUZrNQ7rOL6ioiKngrY8XgEwCO6hw2aoBkWdzkZ2JUc7\ntK0ZSDnz+QSq8yMfw/uh9Kj83LxjRBzdgz2nQHnE4NpEUQcmWw3S/deSnE5DXw190jXAFrJrnLKW\nQZsE0h9QlRNPf1ARp/OsYeXmHvEcvA/1x9RVB6X+lOqgWxK5BqVwQLQyW5OjejAt+NawOOksCtCd\nxEYRLq/yvjkg+XMZuG9pSdvWOmXbHwzgfkfyT4/QlPLEkEsdc2vgzDPPxFVXXYUFCxagpKQkFT5y\n5EjccMMNvumtHfP111/va6cXhKb10AHK7Wc+dKdLi1zkoJ12z3EVAy1+5SP1wa9cA90Y+WiB35tc\neMqGnYB2zUmyAIgtgx7ZOeqNnncAe6Y7aelD5nmEgNjT0DsXw8DACiDG/X/QRxN15CTfFKJj6Azg\nYA/oDpnqpUjF9YLq/J1FvQ43fI7GV492DniF6oBLoEfugO6c9zj3eyg/qh/uypQsVWimQnVEaiCS\nl0wV86AVnSE0za6Z8wqKOwDcnVmSnmPZ+4xlmF9rgLfdCPRCbA0Lg7ifAuAx557eLSEKVW6erhbA\nVKi65CqQjsiVf7Xm0iH7YcaMGZgwYYIr7IUXXsCECRM81K8aVlXGsccei4kTJ3oO8RcuXIgPPghy\njHnLQqkyvg518kb6AqId5NGNm41FYN9CnCn4Tj16hiWMpuVcDi4XOQs6kclWBm2UH4H+4+A76+hP\nijq/KJTq4v9Bf3SkBgFSKg86pQRQ11XO/Qc7gK4nqc67DsAnNUDXsNNB10D5d45CfZR8RMtHvrw8\nprLyZ9kJN7Vjzga0SzQT2kzStDXQrNNPJRSF+U+HaGuhNzZxNRMf3NQC2ArVPuY3WZXxanK0L903\n8v6ec1VGeXk51q5d6wrLxH2y9e/k/vvv9zlPT+3s84LJV8Z3vvMdbNmi7Ez379+PY445BuvWrWsG\nXxntaEc7vuporsU9GxYuXIjXXnsNu3btwk033ZTq8GtraxEK2cxq02HtmL///e83Wcgf/OAH+PGP\nf4yrr746FfbnP/85df+zn/3M1an269fP9x9l5syZGDt2bMpXxsyZMy1bsrkqA9CjLtpSzcH9IdfA\nXS1MpeGilfcEOdrjOE7EUT408iA1hOO20zUS5FuYKW0CahRW4OT7Fgtn1h0uu+EiaPVAD3UtyQN2\nkTVJFFrN00Xr0kugdcwlUKqNOgD5znmAdOTUwbCi2w/gkzCwn/SO0r0pt12muifrFDkaozKYNuW0\nxvbsTEa+H4jrkQjqUPjRaaRmIp8qYag2a9JNUzquJguxH6kbw1Btcjtypcr4Atm5k8gWvXv3xogR\nI7BgwQKMGDEi1TGHw+GUBVoQBDrBpCmwOSdKJpM48cQTsXTpUvTt2zewE6OBAwdi+fLlqY0mFRUV\neP/99100aqQvO2v+UZs6Zoh43unyaZf02VxguMo48qdsy9vW0XMeprSmNDwsCvupK/x6FtyWDoA+\nc63EHU4dc6rKSV9OH9Z7cJtuEOi9hqG3w3uVQ5YdlmdO31RI/s2drqWRrZxFcHv7i8B9ag69yyjc\nLg38FgNlfFjQ3tZkVca8pG2fg8bEvJdzrsqor6/PaIQs0TqacSjPc0VFRejbt28qjHxldOvWDTNm\nzMDZZ5+dli64r4yF0M5QJGhrtA2yI+QOfXg8vyfb57ghrl6E8U6ROqC4IZ5k8MqD9NOyPAnxI9qE\nUw6SqRrK1o0vPhZCjX56sCsA7AXqegDvk6tRgvTa9zaL44uQXMdu6iBkmN8z1VsE/u80CLLtXI+E\nThnIXk7Z7vk3x3luFumCfmfyOYZcLZC2tCpj/PjxePHFF1FeXp4Wl5eXh8rKykB8fDvmjRs3pnbn\n5RLz5s3DpEmTUs/kK6N79+5Yu3YtvvWtb2HTpk0oLLT5SfbzleEFPmIMQsvhtTBl4+cX7iWHjJOy\nywVFsOeYIYxGI3ERRvzIk57sfAl7oQ9s5XbGdC/5807ZVJ6mIFueQd99S/FpLrS0fDK/1q+bpqgy\n5GGsQda3Hn74YQBIO1gkU/gqcqZMmYLTTjsNjz76aOq8q6aioaEB8+fPx5VX6p1PufeVEYPac78M\nwMeGeJMKQD7HDeG2f/kCdi0QYba8ebwtDxONlN00WuZhBSxMqk7kDkZys9kFyj1oEZRqosHwS0B7\nyUuwKx/9Vxvk9YIsr1c9eYV5xccR7D15yUV8skXQ+mgKf1P79Utjug+KICNy0zslxJBrXxlN2fn3\n8MMPY9CgQanBH61vbd26FaNHjzaubfXu3RuAsmrr06cPotEovvjiC1RWVmZ0RqBvx7xy5Uo899xz\n+Oijj1BeXo6JEyfib3/7W+AMTHj99ddRWlqaKgTQHL4yolD7VCsA9IXqZPwQtoSbVBelMOvsgk4X\nSW0AAx+/+wTs+ZRaZKKwqIEPp485Vz5ipiu5Ao1B6675z9RRJeAua5GIL4I+UJYwCm4vfrIORrG0\nVF66N8Gmh6dw+d5NfLgJYVjwGwV3J1/g8BjFaGT+lCdPW2Sg4yhCev3Z+FPZaLFX0tGfLg9PIJ2/\nqS54Xpw+GkA2qvcoCx8DVQ9RaF8Zgy28MkO2HbPpMNZXXnkF11xzDQDlC/7ll1+25nvOOefgiy++\nQFVVFS644AI8++yzGRlUBFr6HDBgAGbMmIFZs2Zh+fLl+MlPfoJTTjkFL730kmc68pWxdetW9OnT\nB3PnzgUAPP/885g4caKLNve+MjgSSP8HJn0th1yg8BpRSX2a5O0nT42FbyYwyRfz4esndxR6Z2KZ\n84sitUsQIaiTUOiZkM+eqXOieuD1KhdBTbvzKuFdh7SoSJuBKL1pgSlIHZNGL2i91Qj5diFd3hqo\ncthkIVl52mrYy13syGlbU5H8Ad3OTIiJONO7AszthcvI5YlZ8jKVaTML38zyzWQW449sO2Y6jLVD\nB91FBl/fUsYNXbp0wV/+8hf86Ec/wosvvoh33303sNy+OuYNGzbg6aefxquvvoqxY8fi1VdfRXl5\nOT7++GN87Wtfw+WXX25NO2/ePGM4ddAcl112mfWA1yee0C4RI5FI6twtb1SIZ1PjkJtGaHQnzddC\nMKe3jWy9wmxpTQb78Ag3ycdHfrTzih/ZJCE3C/BV9yiULplM6CR404mztHwzAV+VJtM9/pwQNF4z\nAQ4yX+S+JhIw+29IiKspntKFYOcjTSb94iQP28wq6MYlPzrJn96DLV+v+vCK94LtO/EDd5PABwfe\nA78gyEbHbDuMlSPI+tY///lPPPfcc5gzR7lebWxsDCyDb8d800034brrrsPdd9+NLl26pMJ79+6N\nGTNmBM6o5bEMdqsMAv+Xto0YCixhUrfs1SCDmCnZOl8ebuNDNNL6g+u06qHrIsb4UVwB9M5AQJ8m\nIg97pTjArLrgHbyJhsogZbapdWxhlFem8HoXVA/SNpp2UMr3nkA6v0xN0kzv19SmMi2rF72pb4G8\nKAAAIABJREFUHPI+U5i+k0zS8jqPwW1qmT1MI+Lty3Zh+zK7EybbYay0vtWrVy+f9S3g97//Pe69\n9158+9vfxuDBg7F9+3Z8/etfDyy3rx1zXV0dCgoK0LGjKuDhw4dx8OBBHH300YEzaWmof7KLoT6o\n3vD+eOQHVgT39KwI7lGZV0fMaTmNLY3Mi9NymGQ3pTXxIVrqTGmjQz/oLbIFSD/fkCxx6NBWOfLe\ny9JLuQjS9lvWua38CehtwJQH1W0x3Js1TB0k1xsTf5KLzxKk7HQPIR/Pm3kddKU32bjLcplk4mnk\nlmeS15SXqU2aZlf8/fN6o/qQ+ZvaFLUV4s3bCr9yuaNQHSyftXEfM7w9VYs8tju02TmZJ+Tl5eHe\n5M2+dLfn/T7QYaxTp05Fjx49MG3aNMycORP79++3bG5rOnxHzGPGjMHrr7+Orl2VW7EDBw7gggsu\nCORTtHXxOZQ/5gJo3SftTgJ0Y6IPKArVKPjIqADuTkWOaAC1OBJz8pD/wjxvQFtF0DmCJt6mDl+O\n2EguiQKnHKS/4we78o+K5MiHXqDa5aQlnTLNjqQt+QHnGnOu5JZUdiQ1TEYuP1gZZUfG61XulKtm\n4VQuen9UJl4+2enKZ9kRm+SkNPSZ8LxJdnrvUXjriGmKvpnlUy3iE1DtaTMLk+/apGow3fM/m2qk\ntxfTn4hNdio3yUPvpodTDroSX36NOvRRuHdB8j9Y4h1x0vUCoA/UaAoacmDHTCqL2267DRMmTMCc\nOXNS5nI2bNmyBQ888ABisRgaGhpSfN54441Aefp2zAcPHkx1ygBQWFiIAwcOeKTQMPnK2LBhA264\n4QZ8/vnniEajeO6551BYWNhMvjJOgNI1x6Cd+jjOgY65EthPuuvvQjnxoUUtKBrcAnUmXLnDYwjS\nFziudGj47rkoVOc0CsASJ99FAKZBHWU0BNqt54VOuqhz5R9mKfRoFdB/LFHo7a9Uph5Q6hv+JxSG\n9ipXzPhGoTvqfCZ7XJefb8XuCu3AaHUX9d28P8jZ/Rd15KMR2P9Bd/bToY+Pos4LcC8ocd0zdQzU\ncdn06/IPkD/Xwt3BSL2nfI5A68OJj+yghkDVD3WulEc59DuXC8kE/ocVhXY9yyHl4WGmzpLna+Nj\no+EgeTIBz+P/nOt5zn0Y6fJuhvJFXQZVtkonX77D94dQbWWIQ78HyNFW6kNN5HPeeeelfM8HX99S\nG02mTJmCyZMnp7QNmcDXKuPoo49OWUQAwOrVq1FQEGzF9Ac/+AEWLVrkCps8eTLuu+8+VFZW4tvf\n/jbuv//+VBz5yli3bp2xUwaC2RK2ox3taAfQeieYhEIhTJkyBaNGjcLIkSNTv6DwHTH//ve/x4QJ\nE3D88ccDUJs6nn/++UDMzznnnDRP/du2bUt5pRszZgwuvPBC3HXXXYEFfuWVV7B8uXJtec0116Ci\nosLSOX8X7p1tNDKKqvv99G8fFTR8gYtGuzDwopEQHQ5Ko6Ao9Oh6G7QZVyHoYGq3aRdZJcQYf7B7\n7keapuvc+VEhtNP9fJG2DHpkTbpAKkcE2gFNLQtzRr80Ui5xfr2gRtGfOM8Hnfv9XQB00Vk3RKHU\nHbXQp7AQ8pG+GGgaEWfqYpWPrCU/v+cgJ3EsZPd8FLrREi5BeS70oAnCJ9c0fqNlen/kopUvJtdC\nn/yzELpt0QlAnAZQdUXWPmGothlj/MgNLZ3SMwS5sMpo6S3ZhHHjxmH27Nm47LLLcNRRetQeidhm\nVm74dsynnXYaNm/ejC1btiAvLw+nnHJKk5xzDB48GAsWLMA3v/lNvPjii9i5c2cqLre+MiqhDkSL\nQp/rlg/VGMmjVTlU49ns3NO0fy/0WW1R51rlhOVD24BGoW1+CxltFMjvDzQsc557qLCGNYxvBMDl\nUOoHmnbSghtN7/tDqWJeYuGkthgH3bCjTnpaYInCPXUewvhE4fZtEYVSQ0QcOgfUIdM9ndYyEO7T\nsPkpLfudcuWHgIbN0L6ieR3SVu0h0Eeu0J9OFO4/mHJoW2DbLjtK4wX+p9ZUcF5BrBCytVTIBrkq\nJ/kCJ3Ubd8nQA+r7+CHU++sh0p7ohMWgVIHLoN5nLdT7p44pBKA/kF/BvotaJ+1OaIf7TUMudMzZ\n4Omnn0ZeXh4eeOABV/iOHTsCpQ/kxGj16tXYsWMHGhoaUs6fuSvPTPDUU0/hpptuwm9/+1tceuml\n6NRJHf2Se18ZPQAMgGoI/aH9O9CfSiF0IyNQo+GjPKI5EUp/1h/uk0D4xgrSs+4FGmqcNNQ58fxo\nRJhkacuhO60i6A6qkvENwd2wKXwz1Ko2pac/GFpQ4XxI5gS0TnCHE75Zydn1JLUuw4+LAlTnvBqq\nc/4AQCzplGUvsIc5OmogmcLQm0DIxSOg/wz5M7drpmeiicPtEJ/fBxnxNod/jraIXMlGMwGq57HQ\n7bYQWldMgww6uoy+1R5Q7T4J/S1FoNt/FKlvoAGMD30Xn8Pb4ig4mqpjzhZ+Z/r5wbdjvuqqq/Dh\nhx9i2LBhLiV2th3zKaecgsWLFwMAtm7dir/+9a8AlK8M6qS5rwzppSm4LeEyqMayCsD5UOf/taMd\n7Wi7eBPASih1yEc54dhaqozPP/8cv/vd7/DRRx/hiSeewLZt27BlyxZ84xvfCJTet2Nes2YN3nvv\nvSy9uKXjs88+w7HHHovGxkbMmDEDU6ZMAaB8ZXTv3h0dO3YM5Ctj2rRpPr4yygGcAeAUaF0tIQo1\nIn0fesRMlhLSEoBbB0hLAQqjkUKMxXFabsfJ028U6UPQJ1jTCLQS7hE3H5lI22JSp5Bemu+Qc0a2\nKbUCpYmxMAd1u4APSrQzfDo2qiuAT5LA6jygLgk93QWUKqUH40e7uciFKN9OXA+3fTCBm3ARaqA3\nftBIn0bLcoOMzdyrHdmBb/qg8yDBrjHodRkKi0O3LZq5Abrd09mSJt3/OQD6ANgCYC2C6cm90Vqq\njB/84AcYMWJEyqy4d+/euOKKKwJ3zL5WGaeeeip2787OppB8ZWzZsgV9+vTBU089hXnz5uGUU05B\naWkpSkpKUo49mtdXRjva0Y6vIg7hKN9fc2D79u2YNm1aSguQ6YY83xHzZ599hkGDBuH0009PrS7m\n5eXhlVde8WVu85Vx0003pYXl3lfGWVD/zMucZ25Puhb6JA1CAdJPuOZpOA8KI50uoFaVq6FHxXKn\nVbVIy/1TbGO8adRIcSRjvZMfbZ6ghR6+AYHTwOFLZQOjp5FstZNPA/QonNx+1gMNzmhnP5QVRgMA\nrAXqRjhli0Pv7oo7BDQaps0ItJnFBJKbysJHXYB9EwWB+Evb33bkFty1K39XBdDvgMA3VcXhbqcJ\nA301tMdD4vcfUB7mmm4K21qqjKOOOgqJhG6P27dvd1ln+MG3Y54+fToA1RnTtsVcqTWaF4/A7StD\nLozIZ9ORVn5peFjch45AHXDMI72M85IlFoCG/+nQVLOehdUz2jBSTokanMXFzgAOVgMHi6A632qH\nZq9zJVWCLAuXh/8R8Wks387bYKHhz/w+LtJ5wbZZhcuFAHy+imiANtFpYNcwuwK6HumPPgy9hZzT\n05ZsGGgAddK73jvRFLRWxzx9+nRceOGF2LVrFyZNmoS33noLTz/9dOD0vh1zRUUFYrEYPvjgA4wZ\nMwYHDhxIbTFsRzZozQ+f7J4B/WHUQNunctmKlG75E8mDW8nQzEDaHRcivfPl+XGYZimmGYqpYw3S\n2fL1AOLH68ArvVceXL5seNjCeH2a/qSC5JPrP5lCqC36NMMh/nuh10IKBb0pLAatYzblUQvVVrzP\n/cwEraVjPv/881FeXo5Vq1YBUE73jz322MDpfTvmP/zhD3jiiScQj8exfft27Nq1C1OmTMHf//73\n7KVuNUThb/NKjZtsOXmYvPdKHwS2UWQueHLQws2JLJ42DUThPkk8CqC/MgE/xvkBwP4iZ4NMD6hF\nu0pou1QyaSPTKNpcwvM3yWaS1VTOGmjbbPkeokh/pzXiSrQRRss7MFs6mzyZxtnKZAqTf0p+7523\nH5P8TW07gDZf3IX0o81ooTkKNaquhHvTFhhtBNrUDiwuysqxEqrzzs2fSmuZy40ePRp///vfXYt9\nFBYEvot/s2fPxsqVKxEOq4YyYMAAfPrpp76Md+7cia9//esYPHgwTj31VPzXf/0XAODFF1/E4MGD\n0bFjx5RNNKDs/goKCjB8+HAMHz4cP/rRj4x84/E4xo4diwEDBuD888/H/v37jXRmmF52JEMaW4OJ\niPiIIU7mRTbQdI0YaKMeeZog84/A/NFGoCxXuO2pM/rpCb2BJB96FnsMpSc/zTXQG0j4fSG0/TKV\n70SWd5TJxUHljzJZiSbG0vJymOpGnlFJdUE8pIG2jU9rIhN5vMZX2bQdic0AnoO2wolBdcjvQ1vf\nbITaAfgWVMf7lhMWc9Jvdp4pnO5rHHpKXwt1tFRu7Jhbekt2IpHA3r178dlnnyEej6d+sVgMVVVB\nbO4VfDvmo446yqW0bmhoCKRjDoVCeOihh7Bp0yasWrUKs2fPxubNm1FWVob58+fj3HPPTUvTPL4y\nStm9aXEoDvdWUx5OMJlxedHLZ65zLRDhRdCexaSethT2o4Q4Rgm+xIc8rdHCSyn04mAR1OJgF+f5\nOC3DHqhv/aBz7emw3QPoRSD61UM7syFdM5e7CG6PZBRWBGC8I6NcnKTnAignTxwxFidpKGyjeK6G\ndqxU4OTN8yWMgj+C0EiZs6UJmpfXmkYu8toGVe+j4V6APgB9zBh5sBsPve7AF6PJw9825xpzwj9w\nfjGW7r0AZQqGBnT0/UkcPHgQo0aNwrBhwzBo0CDcfvvtAICf//znKC0txdChQ3HZZZcZz0B9/PHH\nMXLkSGzZsgUjRoxI/S699FLceOONgeX27ZjPO+883H333Thw4ACWLFmC8ePHY9y4cb6Me/XqhWHD\nhgEAunbtitLSUnz88ccYOHAgBgwYEFhAieDnblUg3XuWbdXe9E/G9WDcTaQf5PRYQm5nr2H8pe6N\nRhp+kEcbcdvRMPSOuioWxv1thKH1rTVqZHwq1Eg5H2JAFnUiToT2GRKB6uii0LbZJLccwYcdeasA\nkOtYLjvX+yYYDaUFtJtIAtGEBC09R5g8fKQv8X+GMPk+NxvCJDbC/GfPEcRtrkkeiUUB5FnkEUdp\n/w/efIqhRsjUfsqh3vdZznMUqp4/Zs/E7yzo2RBvL+RfIwrlgY7oR0Nt+W46DiPf9yfRuXNnLF26\nFOvXr0dlZSWWLl2KlStX4vzzz8emTZuwYcMGDBgwAPfee29a2ptvvhk7duzA/fffjx07dqR+lZWV\nGXXMvjrmmTNnYs6cOSgrK8Pjjz+Oiy++GJMnTw6cAaDUFOvWrcOoUd4jgNz6ylgG/xNMvMCN6zPZ\nvBBEJ8hR5REXhB9gdgzEN1/QlVbGa6BXwKmjjCPVSTdA+6nvBe0PI5VXF6h6JV/MxIesI6R+lUZM\nJAf5PDb9IdbAXfdUFr6xhKeje7mAyeuA8i2Auz74bIJAbld5ntxvcT1UZ0J8IoZyxKE2LFE4NxUj\n/Wwh3K5YOZ3XM1gYzYhosZXnkxBpOLiOmOSIOfdk+sjzLWFpZPvhFhj0zC0sSkS6GmjnWbydxKAd\nGW2CcpbfdBxCp6zS0WlNhw4dwuHDhxGJRDBokN49PGrUKM8zT2+66Sb84x//cPljBoLvmPbtmDt2\n7Ijrr78e119/fSCGEnV1dbjiiivw8MMPu/w6S+TeV0ZT4WdD25Zgko+rR+ievL5RfMgJ49cEUFcP\nxELacZEL1LlVOWmITz7jAegPWc42uJ9h3kF4lSchrjT65mm5gxwuawJm/8ecF89vM6OR+ZC8nJ+t\n7rcZaLgsVYa0pmdeR1xmLoesH1vbjULrhwkkB8km6wPQuy4PQK1DFEB1xtTp92d0gF634HRkdbHX\neT4At/8Msu4ogvKVkZst2dlaZTQ2NqK8vBzbt2/HlClTXJ0yoHz+yAOlOZrqysK3Yz7ppJPSwvLy\n8vDhhx/6Mq+vr8fll1+Oq666ymPrtELufWXEoIZ6MTRt5NwcyGSlvCl5AO6DUsHCyLkSn9I7H1S+\n0ynvcn4lMm0D0nXo3MyLr9zz0ZKEn9mlVzpTuOzk+QyB8+LhXvJ5rRvwPExy8zxs4PxsFismGv5O\nJY0Xv5glzrQewrEX6s84DD1TIDpT+epZ3F5o23iiJTcIYRZfD2CD89sJg51mVjCpKoKgQ4cOWL9+\nPf7973/jggsuwLJly1BRUQEAuPvuu9GpUydMmjTJmr6prix8pX7nnXdS9wcPHsT//u//Yu/evR4p\nFJLJJK677joMGjQIN99sPneLn7OVe18ZUQAjoXqYXHSENh483HTPPyA+nTN1GNnKYnoG0o9Nol19\nhdCmTZTWmV7m91fq+ZFQaoxeTvL3nWtDPdTHVCj40a6/KLSagJfdJqtX2WjkJeuR0/ENKpIPpy8U\nzxwyzCSj7T2b0BIWHn4y51K+f7F7XudhaB8w3FbdC5Re+nkB1JLXudA+MrZkKGc6TKqM2mVrUbts\nXaD03bp1wyWXXILVq1ejoqICTz/9NF577TVfszdyZdG7d++s5PY9jNWE8vJyl6mbCStXrsS5556L\nIUOGpP417rnnHnzxxRf48Y9/jD179qBbt24YPnw4Fi5ciJdeegl33nknQqEQOnTogLvuuguXXHIJ\nAOUr44YbbsCIESMQj8cxYcIEfPTRR9ajpVR+o6HMpro5obyT4o2Ypvu8ozTprXl6rr+jDoCc8lBa\nctBDjZcvavERrJQjiNpE6hopTD7LD4imizGounkLWjcbVTJ2vQgYA9U5vw/dIS8jvpUsjyro0Q/3\nyxtzrrLctjJKnSjRAfp9UH0mkF7Psu5NkHXmVdcmXjwsaBmC8jbJmvC4+qUzyeCnr7bRcZlN7wRw\nl8cmo+0d83dN8TGoqdrfm3wY67DkP33p1uedkTZIzM/PxzHHHINEIoELLrgAd955J+rr63Hrrbdi\n+fLl6NmzpwdHtTFv/fr1WbmyAAJ0zGvWrEl1rI2NjVi9ejUee+wxbNiwIVAGrQEl78MshJ+2QP/U\ncagVLhoN0EkNtEmCpuHkk5ac4RM/U9iJUKY/FB4RPPnIg8fzk4R5nhG4t00TQoYwCuc+i2mTDOXP\nR5ElUI0/zOJqgF6X6hHzaugZ5SoAB5NQH00YqlOOwT3q5zxjTkKupzVNk2V5qAz83QC6bng5Qyyc\n6oqXn1BviecjNlm/fnXrFW8qn1daL3pTeilvUB7UxmU9c1NGWU8QNGRdQe+Cj3i96tCrDKYyRQD8\npMkd86nJt33p3s073ZXPxo0bcc0116CxsRGNjY343ve+h5///Ofo378/Dh06lDqFxHYuKQAsW7bM\nGE7qED/4qjJuvfXWVMecn5/vezps28FCqAbVH+6Pmr/8OHum+zh75vS8A5Ar+xFLHjS9J50op+Gr\n4lIu2z0P4x8H3VM48SfdXQNLB7j9HtRDj3bDyi9GL4dkNdTzJ1AaoYN50OZScXHlrjhJH0mr935T\nZ1PdxWGuL05fL8K96k3+KRQawmxp/XjbwoKm9eOVaXobjw8M8fI0clOd2HTQ1PZN6WQb9SqDfI6B\nTdGahGx0zGVlZUaNwLZt2wzUZgTtgG3wldrW87d9kF2wSddp+tjp3rYgxeNNiydhQc8XyGKGNDJ/\nmXfYEG9Ly+95R7iXxfNTWWjBRT5XKSuM96EGvquhnvfD0S1TOWJw+56m0y2i0GZXgHvkLOvHVhZT\nObwWq7zCJDifIPS5RpD1hFysh+Qasl02GOK43FGkz5C89PamtYjcIFtzuWzRtWtX64JfXl4eamqC\nldG3Y37wwQfTMuJe5m655ZZAGbUO6KXw0RzgrQOz0fJ4k75PprONCqRejucTdPHGBJKH27N+Cr2T\nLgH9IfCjnBJQHamzzX5PDbAo7JjKsaOjUrriaugP7lN32pRDfHqmMhQwuTh4PXIdMqeXtsSUTpab\n16PJdhdwvwPZ6Zt0nV56UZm/vDc9+9nG07uqETRcLi67yVY5iB7ZCya5qP5NC9ZS3jDSvyNbxytt\ny3nZsrOmkGhpJ0Z1dWn2pVnBd+ffmjVr8Nhjj6Gqqgq7du3Cf//3f2Pt2rWoq6tDba19FdbmK+NX\nv/oVhg4dimHDhmH06NGpw1ibx1fGIeeaED8TKDxkofWyFTXlYUtfDfdiiZdMfuCjUFNetM2aFm6q\nned8qI+BtvUVObT5QH4YuALAzQCieUA0DOSfBKUWKoI+a7CI8c937ougOmXiG4FaXAxBf7AJ6Dom\nWWkxiXSN8srTmOodLC5soKdn4lcN83uyvTMup9xVyZ9NOy7pnvOgsoVFfEjQJKDrj9ehiY5oigW/\nCHvmcWGk518s6AmkV853eB7nPJc5Yf0EDb3LMAvLZ/kXC76Sf08gRx1qNjv/2gJ8F//OOeccvPba\na6mNHrW1tbj44ovx5ptvejL+5JNP8Mknn2DYsGGoq6vDiBEj8PLLL6OkpCTF65FHHsGGDRvw5JNP\nIhaLYdy4cdi40dvl39SpU9GzZ09MnToVs2bNwr59+9L8ZagR/nloe/bLLQ1a/KMPhC9U0i6rWqgt\ns461xamXA1c5ZC9DqTLq4Ggk6qFN7GIsPd8EROqjCAuLwdvEr/mmspnBpkbgHRWXOYJ0VY1pum5K\nS8+megDcDunpGrPkY0pne5bgMkRFnlLNQGU2wZaOFhw5qCxRAz2g9N7bAfytyYt/xyf991vszju5\nSfk0B3z/Lj799FOEQnqFOxQKBfIu16tXL/TqpYxgua+M0tLSFE1dXZ2v2YnEK6+8guXLlwNQvjIq\nKiosjowqMuKbewQ1fQuaJogZknxmp5GgAFofSPddGI3agpqyX6YZWS9okznUQ6tiyC66QadNbacu\nhFmVw2XzU9sEUTvZwjMxZ+P3poU1qj/T9L5aPJvy5CoZKlONuJc8CqA6Lj7LoTQ8rVSvSd4yTsom\n30XMUBbOrx7pC64Err7gPD6Au64jcM/gKJzXE50u/zdDPpnhUGPL6phzBd+O+eqrr8bpp5+Oyy67\nDMlkEi+//HLKiVBQSF8Zd9xxB5599ll06dIl5UgaaGu+MtrRjna0DrYD8B/pBkFDQ+s4ym8qAm0w\nWbNmDVauXAkAOPfcczF8+PDAGdTV1aGiogK//OUv03bpzZw5E1u2bMHcuXNx6NAhfP75576+Mrp3\n7459+/alniORCOJx9z+4vyrDa8ramtPpTPP3Kwfp8kjdEIWeNoahbY6HIKXKuHmsGjW/D+D/gzKb\nex9AQ7XIK+6khwgjcBWHPL0kiOrCS/VhozfxzJTPkYBclyFI3dris1FD+eUXc37Lm6zK6Pr5Z750\ndUcf2+ZUGb6LfwBw4MABFBYW4ic/+QlKSkqwY8eOQMz9fGVMmjQpteW7U6dO6N69OwC3rwwJ8pUB\nIICvjPVQI+cY3CvXtikrTadsq/rZQPIqgD0PaX2QCW8+veWqiyp2T78CuFUR9fq+M9Rvj3NtcK6u\nFfRqd5rUjzp8zjMuZKJ65iv5XHaCaQXfVFYeFsS+2FTHfu/IVs+mcBO/oLDlKZHrPxY/fiaLGh4n\n65jTTkC6T3FbfjGo73U9/E8aCobDDR19f20Rvh3z9OnTcd9996X0uIcOHcJVV13lk8ruK4N3tgsW\nLEiNvvfs2YPDhw8DQCBfGQB8fGWcDHXSbgXUSJH0W4BuOHylnvSvCeee4iLiarMc4Fd+38CeKZ8G\nuPV+IRFn4gMDPbdkoJV56ngLoHcXkm6QwuMsbK87bj+08yJAfR91gN6gQDISj2rGiz8XiCvpTnl9\nkHUBhXH72JD48Xrh74oQt9Sd1K/yOuYymGgaWLyUw2TBYcrT7x1ySAsRWRYb/OJzAVOZ6N6kWydI\nh1cmEL/+UN/rMORKBflFopPvry3CV8c8f/58rFu3DiNGjAAAFBcXe5rJEd566y386U9/wpAhQ1Kd\n7z333IM5c+Zgy5Yt6NixI/r27YvHHnsMALBixQr8+te/TvnKePzxx1M+MLivjNtuuw0TJkzAnDlz\nfHYhFkCZ3NBLJ5lDSN9qXcTCOOph/rC8tpvS4obcZmx69uNv+ihtdJw3lSUCfd4foHpbUjG85YTV\nQvtVrtH+MVJbsOPQ26+5NQb51A1B122hQV4O+kAzrUsKp/ckIevLxg9w1xd/poXNaqSPAP14cl4y\nXl4lrQmm9F7ymPINgqD0vH7pD9jGh7cHAPh/AfLgvHOLxsNt0xzOD7465tNPPx1vv/02hg8fjnXr\n1uHzzz/HGWecgcrKypaSMWMoHfODMJshmWCi8zNt4pB6Npmfl97TZLRvMqHi5lLSvMimu42KNFGk\nm7IVsvha4NTvO+Zx1CHyoTOQrjs2nZJNkJ1otlPwXOlUvwz65SMNTanz3zRZx4x/BejsTwy1OR2z\n79/J+PHj8Z//+Z/Yv38//vCHP+Cpp57K+AST1sFiAMej3SqjHe040hBDrnTMOHhkjpg9dczJZBJX\nXnklLr/8clx++eXYunUrfvvb3+Kmm25qKfmaAF60fParMTwD7h1K+Syshj3zf/6IIV2E0fG8IiId\nDzPxzhf3fLGMy1sjeMtnzoNG3JyfM0pOXQG865BhF9QW61ongJzqF7J7QPtClrawlK+s06Dg9Wsb\ncdk2O9jQPlpuebRyncv1adNPwLZrmfDggw+iQ4cOadZguYTv13LxxRfj3Xffxfnnn99sQjQPOkD7\nyiCdYg3UmW4x6F1MIWhdKTWiIVCHU3LdMy1oRJ30/R0a2hpLafkKNL/nC47USZo2hwBm3w88DNBG\n+pKWnsOChuSRO7hiTjgt0qx0yljE+PRj6WJQJyrHoC0+qI4oDeA+N45koTIG2XhDNGTVYUpDH4ap\nrkyQdcHrh545bRjpvpNN7yLbLfVB66K1ITf70LNUU1A98jD+LVXD/K54mgTUd5ujka5eZKk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H5ocV8ZANDQ0ID58+fjyiuvTIXl3lfGTqijnv8JbaoTZHRq+wvloxTiZVqYoXgwurhzpSljPePH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\n",
       "text": [
        "<sunpy.spectra.spectrogram.SpectroFigure at 0x1129d2b90>"
       ]
      },
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 28,
       "text": [
        "<matplotlib.axes.AxesSubplot at 0x1129c0250>"
       ]
      }
     ],
     "prompt_number": 28
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "callisto_nobg.peek(vmin = 0, vmax = 40)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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JSUmpsRVEKNFgPX23201MTAyNGzcmIiKC7OzskO2V4Q/1q19ihJUYdyeaukBP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v6zpT4nOPFCJ94RkP4m7S/vifSbaQRt6/bhOKb9m6xM0pelv59A+P0pBHpg3t8sgO/knaSTeMJw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\nAElFTkSuQmCC\n",
       "text": [
        "<sunpy.spectra.spectrogram.SpectroFigure at 0x1083e6c90>"
       ]
      },
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 29,
       "text": [
        "<matplotlib.axes.AxesSubplot at 0x11299ac10>"
       ]
      }
     ],
     "prompt_number": 29
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "callisto.data"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 30,
       "text": [
        "array([[117, 117, 117, ..., 117, 116, 117],\n",
        "       [117, 116, 117, ..., 116, 116, 116],\n",
        "       [117, 116, 116, ..., 116, 116, 116],\n",
        "       ..., \n",
        "       [128, 128, 128, ..., 125, 124, 126],\n",
        "       [127, 128, 127, ..., 123, 123, 125],\n",
        "       [145, 146, 142, ..., 143, 137, 140]], dtype=uint8)"
       ]
      }
     ],
     "prompt_number": 30
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "## Lightcurves"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import sunpy.lightcurve\n",
      "evelc = sunpy.lightcurve.EVELightCurve.create('2014/01/01')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stderr",
       "text": [
        "/Users/schriste/Dropbox/Developer/python/sunpy/sunpy/lightcurve/lightcurve.py:223: RuntimeWarning: Using existing file rather than downloading, use overwrite=True to override.\n",
        "  warnings.warn(\"Using existing file rather than downloading, use overwrite=True to override.\", RuntimeWarning)\n"
       ]
      }
     ],
     "prompt_number": 31
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "evelc.data"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>XRS-B proxy</th>\n",
        "      <th>XRS-A proxy</th>\n",
        "      <th>SEM proxy</th>\n",
        "      <th>0.1-7ESPquad</th>\n",
        "      <th>17.1ESP</th>\n",
        "      <th>25.7ESP</th>\n",
        "      <th>30.4ESP</th>\n",
        "      <th>36.6ESP</th>\n",
        "      <th>darkESP</th>\n",
        "      <th>121.6MEGS-P</th>\n",
        "      <th>darkMEGS-P</th>\n",
        "      <th>q0ESP</th>\n",
        "      <th>q1ESP</th>\n",
        "      <th>q2ESP</th>\n",
        "      <th>q3ESP</th>\n",
        "      <th>CMLat</th>\n",
        "      <th>CMLon</th>\n",
        "      <th>x_cool proxy</th>\n",
        "      <th>oldXRSB proxy</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>HHMM</th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:00:00</th>\n",
        "      <td> 0.000006</td>\n",
        "      <td> 0.000000</td>\n",
        "      <td> 0.000858</td>\n",
        "      <td> 0.00196</td>\n",
        "      <td> 0.000904</td>\n",
        "      <td> 0.000547</td>\n",
        "      <td> 0.000958</td>\n",
        "      <td>-1.000000</td>\n",
        "      <td> 49.4</td>\n",
        "      <td>-1</td>\n",
        "      <td> 39.2</td>\n",
        "      <td> 0.334</td>\n",
        "      <td> 0.157</td>\n",
        "      <td> 0.351</td>\n",
        "      <td> 0.158</td>\n",
        "      <td>-28.9</td>\n",
        "      <td> -0.9</td>\n",
        "      <td> 2320</td>\n",
        "      <td> 0.000005</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:01:00</th>\n",
        "      <td> 0.000006</td>\n",
        "      <td> 0.000000</td>\n",
        "      <td> 0.000858</td>\n",
        "      <td> 0.00195</td>\n",
        "      <td> 0.000904</td>\n",
        "      <td> 0.000547</td>\n",
        "      <td> 0.000959</td>\n",
        "      <td>-1.000000</td>\n",
        "      <td> 49.4</td>\n",
        "      <td>-1</td>\n",
        "      <td> 39.2</td>\n",
        "      <td> 0.334</td>\n",
        "      <td> 0.157</td>\n",
        "      <td> 0.351</td>\n",
        "      <td> 0.158</td>\n",
        "      <td>-28.8</td>\n",
        "      <td> -0.9</td>\n",
        "      <td> 2320</td>\n",
        "      <td> 0.000005</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:02:00</th>\n",
        "      <td> 0.000006</td>\n",
        "      <td> 0.000000</td>\n",
        "      <td> 0.000857</td>\n",
        "      <td> 0.00195</td>\n",
        "      <td> 0.000903</td>\n",
        "      <td> 0.000547</td>\n",
        "      <td> 0.000957</td>\n",
        "      <td>-1.000000</td>\n",
        "      <td> 49.4</td>\n",
        "      <td>-1</td>\n",
        "      <td> 39.2</td>\n",
        "      <td> 0.334</td>\n",
        "      <td> 0.157</td>\n",
        "      <td> 0.350</td>\n",
        "      <td> 0.158</td>\n",
        "      <td>-28.7</td>\n",
        "      <td> -1.2</td>\n",
        "      <td> 2320</td>\n",
        "      <td> 0.000005</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:03:00</th>\n",
        "      <td> 0.000006</td>\n",
        "      <td> 0.000000</td>\n",
        "      <td> 0.000857</td>\n",
        "      <td> 0.00195</td>\n",
        "      <td> 0.000903</td>\n",
        "      <td> 0.000547</td>\n",
        "      <td> 0.000956</td>\n",
        "      <td>-1.000000</td>\n",
        "      <td> 49.4</td>\n",
        "      <td>-1</td>\n",
        "      <td> 39.2</td>\n",
        "      <td> 0.334</td>\n",
        "      <td> 0.157</td>\n",
        "      <td> 0.351</td>\n",
        "      <td> 0.158</td>\n",
        "      <td>-28.8</td>\n",
        "      <td> -1.0</td>\n",
        "      <td> 2330</td>\n",
        "      <td> 0.000005</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:04:00</th>\n",
        "      <td> 0.000006</td>\n",
        "      <td> 0.000000</td>\n",
        "      <td> 0.000856</td>\n",
        "      <td> 0.00194</td>\n",
        "      <td> 0.000903</td>\n",
        "      <td> 0.000547</td>\n",
        "      <td> 0.000955</td>\n",
        "      <td>-1.000000</td>\n",
        "      <td> 49.4</td>\n",
        "      <td>-1</td>\n",
        "      <td> 39.2</td>\n",
        "      <td> 0.334</td>\n",
        "      <td> 0.157</td>\n",
        "      <td> 0.351</td>\n",
        "      <td> 0.158</td>\n",
        "      <td>-28.7</td>\n",
        "      <td> -1.0</td>\n",
        "      <td> 2330</td>\n",
        "      <td> 0.000005</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:05:00</th>\n",
        "      <td> 0.000006</td>\n",
        "      <td> 0.000000</td>\n",
        "      <td> 0.000856</td>\n",
        "      <td> 0.00194</td>\n",
        "      <td> 0.000903</td>\n",
        "      <td> 0.000547</td>\n",
        "      <td> 0.000955</td>\n",
        "      <td>-1.000000</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>-1</td>\n",
        "      <td> 39.2</td>\n",
        "      <td> 0.335</td>\n",
        "      <td> 0.157</td>\n",
        "      <td> 0.350</td>\n",
        "      <td> 0.158</td>\n",
        "      <td>-28.8</td>\n",
        "      <td> -1.3</td>\n",
        "      <td> 2330</td>\n",
        "      <td> 0.000005</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:06:00</th>\n",
        "      <td> 0.000006</td>\n",
        "      <td> 0.000000</td>\n",
        "      <td> 0.000856</td>\n",
        "      <td> 0.00194</td>\n",
        "      <td> 0.000903</td>\n",
        "      <td> 0.000546</td>\n",
        "      <td> 0.000955</td>\n",
        "      <td>-1.000000</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>-1</td>\n",
        "      <td> 39.2</td>\n",
        "      <td> 0.334</td>\n",
        "      <td> 0.158</td>\n",
        "      <td> 0.351</td>\n",
        "      <td> 0.158</td>\n",
        "      <td>-28.8</td>\n",
        "      <td> -1.3</td>\n",
        "      <td> 2330</td>\n",
        "      <td> 0.000005</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:07:00</th>\n",
        "      <td> 0.000006</td>\n",
        "      <td> 0.000000</td>\n",
        "      <td> 0.000856</td>\n",
        "      <td> 0.00194</td>\n",
        "      <td> 0.000903</td>\n",
        "      <td> 0.000546</td>\n",
        "      <td> 0.000955</td>\n",
        "      <td>-1.000000</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>-1</td>\n",
        "      <td> 39.2</td>\n",
        "      <td> 0.334</td>\n",
        "      <td> 0.158</td>\n",
        "      <td> 0.350</td>\n",
        "      <td> 0.158</td>\n",
        "      <td>-28.7</td>\n",
        "      <td> -1.3</td>\n",
        "      <td> 2330</td>\n",
        "      <td> 0.000005</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:08:00</th>\n",
        "      <td> 0.000006</td>\n",
        "      <td> 0.000000</td>\n",
        "      <td> 0.000856</td>\n",
        "      <td> 0.00194</td>\n",
        "      <td> 0.000903</td>\n",
        "      <td> 0.000546</td>\n",
        "      <td> 0.000956</td>\n",
        "      <td>-1.000000</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>-1</td>\n",
        "      <td> 39.2</td>\n",
        "      <td> 0.335</td>\n",
        "      <td> 0.158</td>\n",
        "      <td> 0.350</td>\n",
        "      <td> 0.158</td>\n",
        "      <td>-28.7</td>\n",
        "      <td> -1.8</td>\n",
        "      <td> 2330</td>\n",
        "      <td> 0.000005</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:09:00</th>\n",
        "      <td> 0.000006</td>\n",
        "      <td> 0.000000</td>\n",
        "      <td> 0.000857</td>\n",
        "      <td> 0.00195</td>\n",
        "      <td> 0.000904</td>\n",
        "      <td> 0.000546</td>\n",
        "      <td> 0.000956</td>\n",
        "      <td>-1.000000</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>-1</td>\n",
        "      <td> 39.2</td>\n",
        "      <td> 0.335</td>\n",
        "      <td> 0.158</td>\n",
        "      <td> 0.349</td>\n",
        "      <td> 0.158</td>\n",
        "      <td>-28.7</td>\n",
        "      <td> -2.0</td>\n",
        "      <td> 2330</td>\n",
        "      <td> 0.000005</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:10:00</th>\n",
        "      <td> 0.000006</td>\n",
        "      <td> 0.000000</td>\n",
        "      <td> 0.000857</td>\n",
        "      <td> 0.00196</td>\n",
        "      <td> 0.000904</td>\n",
        "      <td> 0.000546</td>\n",
        "      <td> 0.000956</td>\n",
        "      <td>-1.000000</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>-1</td>\n",
        "      <td> 39.2</td>\n",
        "      <td> 0.335</td>\n",
        "      <td> 0.159</td>\n",
        "      <td> 0.349</td>\n",
        "      <td> 0.158</td>\n",
        "      <td>-28.6</td>\n",
        "      <td> -2.1</td>\n",
        "      <td> 2340</td>\n",
        "      <td> 0.000005</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:11:00</th>\n",
        "      <td> 0.000006</td>\n",
        "      <td> 0.000000</td>\n",
        "      <td> 0.000856</td>\n",
        "      <td> 0.00197</td>\n",
        "      <td> 0.000903</td>\n",
        "      <td> 0.000546</td>\n",
        "      <td> 0.000956</td>\n",
        "      <td>-1.000000</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>-1</td>\n",
        "      <td> 39.2</td>\n",
        "      <td> 0.335</td>\n",
        "      <td> 0.159</td>\n",
        "      <td> 0.349</td>\n",
        "      <td> 0.158</td>\n",
        "      <td>-28.6</td>\n",
        "      <td> -2.4</td>\n",
        "      <td> 2340</td>\n",
        "      <td> 0.000005</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:12:00</th>\n",
        "      <td> 0.000006</td>\n",
        "      <td> 0.000000</td>\n",
        "      <td> 0.000856</td>\n",
        "      <td> 0.00199</td>\n",
        "      <td> 0.000903</td>\n",
        "      <td> 0.000546</td>\n",
        "      <td> 0.000955</td>\n",
        "      <td> 0.000445</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>-1</td>\n",
        "      <td> 39.2</td>\n",
        "      <td> 0.336</td>\n",
        "      <td> 0.159</td>\n",
        "      <td> 0.348</td>\n",
        "      <td> 0.157</td>\n",
        "      <td>-28.6</td>\n",
        "      <td> -3.0</td>\n",
        "      <td> 2340</td>\n",
        "      <td> 0.000005</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:13:00</th>\n",
        "      <td> 0.000006</td>\n",
        "      <td> 0.000000</td>\n",
        "      <td> 0.000855</td>\n",
        "      <td> 0.00203</td>\n",
        "      <td> 0.000903</td>\n",
        "      <td> 0.000546</td>\n",
        "      <td> 0.000954</td>\n",
        "      <td> 0.007550</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>-1</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.338</td>\n",
        "      <td> 0.160</td>\n",
        "      <td> 0.345</td>\n",
        "      <td> 0.156</td>\n",
        "      <td>-28.6</td>\n",
        "      <td> -4.7</td>\n",
        "      <td> 2340</td>\n",
        "      <td> 0.000006</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:14:00</th>\n",
        "      <td> 0.000006</td>\n",
        "      <td> 0.000000</td>\n",
        "      <td> 0.000855</td>\n",
        "      <td> 0.00208</td>\n",
        "      <td> 0.000903</td>\n",
        "      <td> 0.000546</td>\n",
        "      <td> 0.000954</td>\n",
        "      <td> 0.013800</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>-1</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.341</td>\n",
        "      <td> 0.161</td>\n",
        "      <td> 0.343</td>\n",
        "      <td> 0.156</td>\n",
        "      <td>-28.5</td>\n",
        "      <td> -6.7</td>\n",
        "      <td> 2340</td>\n",
        "      <td> 0.000006</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:15:00</th>\n",
        "      <td> 0.000007</td>\n",
        "      <td> 0.000000</td>\n",
        "      <td> 0.000855</td>\n",
        "      <td> 0.00212</td>\n",
        "      <td> 0.000904</td>\n",
        "      <td> 0.000545</td>\n",
        "      <td> 0.000954</td>\n",
        "      <td> 0.242000</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>-1</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.341</td>\n",
        "      <td> 0.162</td>\n",
        "      <td> 0.342</td>\n",
        "      <td> 0.155</td>\n",
        "      <td>-28.5</td>\n",
        "      <td> -7.6</td>\n",
        "      <td> 2340</td>\n",
        "      <td> 0.000006</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:16:00</th>\n",
        "      <td> 0.000007</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000855</td>\n",
        "      <td> 0.00215</td>\n",
        "      <td> 0.000904</td>\n",
        "      <td> 0.000545</td>\n",
        "      <td> 0.000954</td>\n",
        "      <td> 0.537000</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>-1</td>\n",
        "      <td> 39.2</td>\n",
        "      <td> 0.342</td>\n",
        "      <td> 0.163</td>\n",
        "      <td> 0.340</td>\n",
        "      <td> 0.155</td>\n",
        "      <td>-28.3</td>\n",
        "      <td> -8.3</td>\n",
        "      <td> 2350</td>\n",
        "      <td> 0.000006</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:17:00</th>\n",
        "      <td> 0.000007</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000855</td>\n",
        "      <td> 0.00217</td>\n",
        "      <td> 0.000904</td>\n",
        "      <td> 0.000545</td>\n",
        "      <td> 0.000954</td>\n",
        "      <td> 0.597000</td>\n",
        "      <td> 49.6</td>\n",
        "      <td>-1</td>\n",
        "      <td> 39.2</td>\n",
        "      <td> 0.343</td>\n",
        "      <td> 0.164</td>\n",
        "      <td> 0.338</td>\n",
        "      <td> 0.155</td>\n",
        "      <td>-28.2</td>\n",
        "      <td> -9.5</td>\n",
        "      <td> 2350</td>\n",
        "      <td> 0.000006</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:18:00</th>\n",
        "      <td> 0.000007</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000856</td>\n",
        "      <td> 0.00218</td>\n",
        "      <td> 0.000904</td>\n",
        "      <td> 0.000545</td>\n",
        "      <td> 0.000956</td>\n",
        "      <td> 0.998000</td>\n",
        "      <td> 49.6</td>\n",
        "      <td>-1</td>\n",
        "      <td> 39.2</td>\n",
        "      <td> 0.343</td>\n",
        "      <td> 0.165</td>\n",
        "      <td> 0.337</td>\n",
        "      <td> 0.155</td>\n",
        "      <td>-28.0</td>\n",
        "      <td>-10.1</td>\n",
        "      <td> 2350</td>\n",
        "      <td> 0.000006</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:19:00</th>\n",
        "      <td> 0.000007</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000857</td>\n",
        "      <td> 0.00217</td>\n",
        "      <td> 0.000905</td>\n",
        "      <td> 0.000545</td>\n",
        "      <td> 0.000957</td>\n",
        "      <td> 0.934000</td>\n",
        "      <td> 49.6</td>\n",
        "      <td>-1</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.343</td>\n",
        "      <td> 0.165</td>\n",
        "      <td> 0.336</td>\n",
        "      <td> 0.155</td>\n",
        "      <td>-27.9</td>\n",
        "      <td>-10.3</td>\n",
        "      <td> 2350</td>\n",
        "      <td> 0.000006</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:20:00</th>\n",
        "      <td> 0.000007</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000857</td>\n",
        "      <td> 0.00217</td>\n",
        "      <td> 0.000905</td>\n",
        "      <td> 0.000545</td>\n",
        "      <td> 0.000956</td>\n",
        "      <td> 0.870000</td>\n",
        "      <td> 49.6</td>\n",
        "      <td>-1</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.343</td>\n",
        "      <td> 0.166</td>\n",
        "      <td> 0.336</td>\n",
        "      <td> 0.155</td>\n",
        "      <td>-27.9</td>\n",
        "      <td>-10.6</td>\n",
        "      <td> 2350</td>\n",
        "      <td> 0.000006</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:21:00</th>\n",
        "      <td> 0.000007</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000856</td>\n",
        "      <td> 0.00216</td>\n",
        "      <td> 0.000905</td>\n",
        "      <td> 0.000545</td>\n",
        "      <td> 0.000955</td>\n",
        "      <td> 0.808000</td>\n",
        "      <td> 49.6</td>\n",
        "      <td>-1</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.343</td>\n",
        "      <td> 0.165</td>\n",
        "      <td> 0.337</td>\n",
        "      <td> 0.155</td>\n",
        "      <td>-27.9</td>\n",
        "      <td>-10.2</td>\n",
        "      <td> 2350</td>\n",
        "      <td> 0.000006</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:22:00</th>\n",
        "      <td> 0.000007</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000855</td>\n",
        "      <td> 0.00217</td>\n",
        "      <td> 0.000905</td>\n",
        "      <td> 0.000545</td>\n",
        "      <td> 0.000953</td>\n",
        "      <td> 0.746000</td>\n",
        "      <td> 49.6</td>\n",
        "      <td>-1</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.343</td>\n",
        "      <td> 0.165</td>\n",
        "      <td> 0.337</td>\n",
        "      <td> 0.155</td>\n",
        "      <td>-27.9</td>\n",
        "      <td>-10.2</td>\n",
        "      <td> 2360</td>\n",
        "      <td> 0.000006</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:23:00</th>\n",
        "      <td> 0.000007</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000855</td>\n",
        "      <td> 0.00217</td>\n",
        "      <td> 0.000905</td>\n",
        "      <td> 0.000546</td>\n",
        "      <td> 0.000953</td>\n",
        "      <td> 0.687000</td>\n",
        "      <td> 49.6</td>\n",
        "      <td>-1</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.343</td>\n",
        "      <td> 0.165</td>\n",
        "      <td> 0.337</td>\n",
        "      <td> 0.155</td>\n",
        "      <td>-27.9</td>\n",
        "      <td>-10.2</td>\n",
        "      <td> 2360</td>\n",
        "      <td> 0.000006</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:24:00</th>\n",
        "      <td> 0.000007</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000855</td>\n",
        "      <td> 0.00216</td>\n",
        "      <td> 0.000906</td>\n",
        "      <td> 0.000546</td>\n",
        "      <td> 0.000953</td>\n",
        "      <td> 0.629000</td>\n",
        "      <td> 49.6</td>\n",
        "      <td>-1</td>\n",
        "      <td> 39.2</td>\n",
        "      <td> 0.343</td>\n",
        "      <td> 0.165</td>\n",
        "      <td> 0.337</td>\n",
        "      <td> 0.155</td>\n",
        "      <td>-28.0</td>\n",
        "      <td>-10.2</td>\n",
        "      <td> 2360</td>\n",
        "      <td> 0.000006</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:25:00</th>\n",
        "      <td> 0.000007</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000856</td>\n",
        "      <td> 0.00216</td>\n",
        "      <td> 0.000906</td>\n",
        "      <td> 0.000547</td>\n",
        "      <td> 0.000954</td>\n",
        "      <td> 0.574000</td>\n",
        "      <td> 49.6</td>\n",
        "      <td>-1</td>\n",
        "      <td> 39.2</td>\n",
        "      <td> 0.344</td>\n",
        "      <td> 0.165</td>\n",
        "      <td> 0.336</td>\n",
        "      <td> 0.155</td>\n",
        "      <td>-28.0</td>\n",
        "      <td>-10.5</td>\n",
        "      <td> 2360</td>\n",
        "      <td> 0.000006</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:26:00</th>\n",
        "      <td> 0.000007</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000856</td>\n",
        "      <td> 0.00217</td>\n",
        "      <td> 0.000906</td>\n",
        "      <td> 0.000547</td>\n",
        "      <td> 0.000954</td>\n",
        "      <td> 0.520000</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>-1</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.343</td>\n",
        "      <td> 0.165</td>\n",
        "      <td> 0.336</td>\n",
        "      <td> 0.155</td>\n",
        "      <td>-27.9</td>\n",
        "      <td>-10.5</td>\n",
        "      <td> 2360</td>\n",
        "      <td> 0.000006</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:27:00</th>\n",
        "      <td> 0.000007</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000856</td>\n",
        "      <td> 0.00218</td>\n",
        "      <td> 0.000906</td>\n",
        "      <td> 0.000547</td>\n",
        "      <td> 0.000955</td>\n",
        "      <td> 0.470000</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>-1</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.343</td>\n",
        "      <td> 0.165</td>\n",
        "      <td> 0.337</td>\n",
        "      <td> 0.155</td>\n",
        "      <td>-28.0</td>\n",
        "      <td>-10.2</td>\n",
        "      <td> 2370</td>\n",
        "      <td> 0.000006</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:28:00</th>\n",
        "      <td> 0.000007</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000856</td>\n",
        "      <td> 0.00218</td>\n",
        "      <td> 0.000906</td>\n",
        "      <td> 0.000547</td>\n",
        "      <td> 0.000955</td>\n",
        "      <td> 0.421000</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>-1</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.343</td>\n",
        "      <td> 0.165</td>\n",
        "      <td> 0.337</td>\n",
        "      <td> 0.155</td>\n",
        "      <td>-28.0</td>\n",
        "      <td>-10.3</td>\n",
        "      <td> 2370</td>\n",
        "      <td> 0.000006</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:29:00</th>\n",
        "      <td> 0.000007</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000856</td>\n",
        "      <td> 0.00219</td>\n",
        "      <td> 0.000906</td>\n",
        "      <td> 0.000548</td>\n",
        "      <td> 0.000954</td>\n",
        "      <td> 0.376000</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>-1</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.343</td>\n",
        "      <td> 0.165</td>\n",
        "      <td> 0.338</td>\n",
        "      <td> 0.154</td>\n",
        "      <td>-28.1</td>\n",
        "      <td>-10.2</td>\n",
        "      <td> 2370</td>\n",
        "      <td> 0.000006</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:30:00</th>\n",
        "      <td> 0.000007</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000856</td>\n",
        "      <td> 0.00220</td>\n",
        "      <td> 0.000906</td>\n",
        "      <td> 0.000548</td>\n",
        "      <td> 0.000954</td>\n",
        "      <td> 0.332000</td>\n",
        "      <td> 49.6</td>\n",
        "      <td>-1</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.344</td>\n",
        "      <td> 0.165</td>\n",
        "      <td> 0.337</td>\n",
        "      <td> 0.154</td>\n",
        "      <td>-28.2</td>\n",
        "      <td>-10.4</td>\n",
        "      <td> 2370</td>\n",
        "      <td> 0.000006</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:31:00</th>\n",
        "      <td> 0.000007</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000856</td>\n",
        "      <td> 0.00221</td>\n",
        "      <td> 0.000906</td>\n",
        "      <td> 0.000548</td>\n",
        "      <td> 0.000954</td>\n",
        "      <td> 0.292000</td>\n",
        "      <td> 49.6</td>\n",
        "      <td>-1</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.345</td>\n",
        "      <td> 0.164</td>\n",
        "      <td> 0.337</td>\n",
        "      <td> 0.154</td>\n",
        "      <td>-28.3</td>\n",
        "      <td>-10.6</td>\n",
        "      <td> 2370</td>\n",
        "      <td> 0.000006</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:32:00</th>\n",
        "      <td> 0.000007</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000856</td>\n",
        "      <td> 0.00222</td>\n",
        "      <td> 0.000906</td>\n",
        "      <td> 0.000548</td>\n",
        "      <td> 0.000953</td>\n",
        "      <td> 0.254000</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>-1</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.345</td>\n",
        "      <td> 0.164</td>\n",
        "      <td> 0.338</td>\n",
        "      <td> 0.154</td>\n",
        "      <td>-28.4</td>\n",
        "      <td>-10.6</td>\n",
        "      <td> 2370</td>\n",
        "      <td> 0.000006</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:33:00</th>\n",
        "      <td> 0.000007</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000856</td>\n",
        "      <td> 0.00224</td>\n",
        "      <td> 0.000906</td>\n",
        "      <td> 0.000549</td>\n",
        "      <td> 0.000953</td>\n",
        "      <td> 0.219000</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>-1</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.346</td>\n",
        "      <td> 0.164</td>\n",
        "      <td> 0.338</td>\n",
        "      <td> 0.153</td>\n",
        "      <td>-28.5</td>\n",
        "      <td>-10.9</td>\n",
        "      <td> 2380</td>\n",
        "      <td> 0.000007</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:34:00</th>\n",
        "      <td> 0.000007</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000855</td>\n",
        "      <td> 0.00226</td>\n",
        "      <td> 0.000906</td>\n",
        "      <td> 0.000549</td>\n",
        "      <td> 0.000953</td>\n",
        "      <td> 0.186000</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>-1</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.347</td>\n",
        "      <td> 0.164</td>\n",
        "      <td> 0.337</td>\n",
        "      <td> 0.152</td>\n",
        "      <td>-28.6</td>\n",
        "      <td>-12.0</td>\n",
        "      <td> 2380</td>\n",
        "      <td> 0.000007</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:35:00</th>\n",
        "      <td> 0.000007</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000856</td>\n",
        "      <td> 0.00229</td>\n",
        "      <td> 0.000906</td>\n",
        "      <td> 0.000549</td>\n",
        "      <td> 0.000954</td>\n",
        "      <td> 0.156000</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>-1</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.349</td>\n",
        "      <td> 0.164</td>\n",
        "      <td> 0.336</td>\n",
        "      <td> 0.151</td>\n",
        "      <td>-28.7</td>\n",
        "      <td>-13.0</td>\n",
        "      <td> 2380</td>\n",
        "      <td> 0.000007</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:36:00</th>\n",
        "      <td> 0.000008</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000856</td>\n",
        "      <td> 0.00231</td>\n",
        "      <td> 0.000906</td>\n",
        "      <td> 0.000549</td>\n",
        "      <td> 0.000954</td>\n",
        "      <td> 0.218000</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>-1</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.349</td>\n",
        "      <td> 0.164</td>\n",
        "      <td> 0.335</td>\n",
        "      <td> 0.151</td>\n",
        "      <td>-28.7</td>\n",
        "      <td>-13.4</td>\n",
        "      <td> 2380</td>\n",
        "      <td> 0.000007</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:37:00</th>\n",
        "      <td> 0.000008</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000857</td>\n",
        "      <td> 0.00233</td>\n",
        "      <td> 0.000907</td>\n",
        "      <td> 0.000549</td>\n",
        "      <td> 0.000955</td>\n",
        "      <td> 0.361000</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>-1</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.351</td>\n",
        "      <td> 0.164</td>\n",
        "      <td> 0.334</td>\n",
        "      <td> 0.151</td>\n",
        "      <td>-28.7</td>\n",
        "      <td>-14.1</td>\n",
        "      <td> 2380</td>\n",
        "      <td> 0.000007</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:38:00</th>\n",
        "      <td> 0.000008</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000858</td>\n",
        "      <td> 0.00236</td>\n",
        "      <td> 0.000907</td>\n",
        "      <td> 0.000549</td>\n",
        "      <td> 0.000956</td>\n",
        "      <td> 0.320000</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>-1</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.350</td>\n",
        "      <td> 0.165</td>\n",
        "      <td> 0.334</td>\n",
        "      <td> 0.151</td>\n",
        "      <td>-28.6</td>\n",
        "      <td>-14.3</td>\n",
        "      <td> 2380</td>\n",
        "      <td> 0.000007</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:39:00</th>\n",
        "      <td> 0.000008</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000859</td>\n",
        "      <td> 0.00237</td>\n",
        "      <td> 0.000907</td>\n",
        "      <td> 0.000549</td>\n",
        "      <td> 0.000958</td>\n",
        "      <td> 0.283000</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>-1</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.351</td>\n",
        "      <td> 0.164</td>\n",
        "      <td> 0.334</td>\n",
        "      <td> 0.151</td>\n",
        "      <td>-28.7</td>\n",
        "      <td>-14.1</td>\n",
        "      <td> 2390</td>\n",
        "      <td> 0.000007</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:40:00</th>\n",
        "      <td> 0.000008</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000859</td>\n",
        "      <td> 0.00238</td>\n",
        "      <td> 0.000907</td>\n",
        "      <td> 0.000550</td>\n",
        "      <td> 0.000958</td>\n",
        "      <td> 0.247000</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>-1</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.350</td>\n",
        "      <td> 0.164</td>\n",
        "      <td> 0.334</td>\n",
        "      <td> 0.151</td>\n",
        "      <td>-28.7</td>\n",
        "      <td>-13.9</td>\n",
        "      <td> 2390</td>\n",
        "      <td> 0.000007</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:41:00</th>\n",
        "      <td> 0.000008</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000859</td>\n",
        "      <td> 0.00240</td>\n",
        "      <td> 0.000907</td>\n",
        "      <td> 0.000549</td>\n",
        "      <td> 0.000957</td>\n",
        "      <td> 0.214000</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>-1</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.350</td>\n",
        "      <td> 0.164</td>\n",
        "      <td> 0.335</td>\n",
        "      <td> 0.151</td>\n",
        "      <td>-28.7</td>\n",
        "      <td>-13.5</td>\n",
        "      <td> 2390</td>\n",
        "      <td> 0.000007</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:42:00</th>\n",
        "      <td> 0.000008</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000859</td>\n",
        "      <td> 0.00241</td>\n",
        "      <td> 0.000907</td>\n",
        "      <td> 0.000549</td>\n",
        "      <td> 0.000958</td>\n",
        "      <td> 0.183000</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>-1</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.349</td>\n",
        "      <td> 0.164</td>\n",
        "      <td> 0.335</td>\n",
        "      <td> 0.152</td>\n",
        "      <td>-28.7</td>\n",
        "      <td>-13.0</td>\n",
        "      <td> 2390</td>\n",
        "      <td> 0.000007</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:43:00</th>\n",
        "      <td> 0.000008</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000860</td>\n",
        "      <td> 0.00242</td>\n",
        "      <td> 0.000908</td>\n",
        "      <td> 0.000549</td>\n",
        "      <td> 0.000960</td>\n",
        "      <td> 0.155000</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>-1</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.349</td>\n",
        "      <td> 0.164</td>\n",
        "      <td> 0.336</td>\n",
        "      <td> 0.151</td>\n",
        "      <td>-28.8</td>\n",
        "      <td>-12.8</td>\n",
        "      <td> 2390</td>\n",
        "      <td> 0.000007</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:44:00</th>\n",
        "      <td> 0.000008</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000861</td>\n",
        "      <td> 0.00243</td>\n",
        "      <td> 0.000909</td>\n",
        "      <td> 0.000550</td>\n",
        "      <td> 0.000960</td>\n",
        "      <td> 0.307000</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>-1</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.349</td>\n",
        "      <td> 0.163</td>\n",
        "      <td> 0.337</td>\n",
        "      <td> 0.151</td>\n",
        "      <td>-28.9</td>\n",
        "      <td>-12.6</td>\n",
        "      <td> 2390</td>\n",
        "      <td> 0.000007</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:45:00</th>\n",
        "      <td> 0.000008</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000861</td>\n",
        "      <td> 0.00244</td>\n",
        "      <td> 0.000909</td>\n",
        "      <td> 0.000550</td>\n",
        "      <td> 0.000961</td>\n",
        "      <td> 0.620000</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>-1</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.349</td>\n",
        "      <td> 0.163</td>\n",
        "      <td> 0.338</td>\n",
        "      <td> 0.151</td>\n",
        "      <td>-29.0</td>\n",
        "      <td>-12.1</td>\n",
        "      <td> 2400</td>\n",
        "      <td> 0.000007</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:46:00</th>\n",
        "      <td> 0.000008</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000862</td>\n",
        "      <td> 0.00244</td>\n",
        "      <td> 0.000909</td>\n",
        "      <td> 0.000550</td>\n",
        "      <td> 0.000961</td>\n",
        "      <td> 0.742000</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>-1</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.348</td>\n",
        "      <td> 0.162</td>\n",
        "      <td> 0.338</td>\n",
        "      <td> 0.152</td>\n",
        "      <td>-28.9</td>\n",
        "      <td>-11.6</td>\n",
        "      <td> 2400</td>\n",
        "      <td> 0.000007</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:47:00</th>\n",
        "      <td> 0.000008</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000862</td>\n",
        "      <td> 0.00244</td>\n",
        "      <td> 0.000909</td>\n",
        "      <td> 0.000551</td>\n",
        "      <td> 0.000961</td>\n",
        "      <td> 0.763000</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>-1</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.348</td>\n",
        "      <td> 0.163</td>\n",
        "      <td> 0.338</td>\n",
        "      <td> 0.152</td>\n",
        "      <td>-28.9</td>\n",
        "      <td>-11.6</td>\n",
        "      <td> 2400</td>\n",
        "      <td> 0.000007</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:48:00</th>\n",
        "      <td> 0.000008</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000862</td>\n",
        "      <td> 0.00244</td>\n",
        "      <td> 0.000909</td>\n",
        "      <td> 0.000551</td>\n",
        "      <td> 0.000961</td>\n",
        "      <td> 0.695000</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>-1</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.347</td>\n",
        "      <td> 0.163</td>\n",
        "      <td> 0.338</td>\n",
        "      <td> 0.152</td>\n",
        "      <td>-28.8</td>\n",
        "      <td>-11.1</td>\n",
        "      <td> 2400</td>\n",
        "      <td> 0.000007</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:49:00</th>\n",
        "      <td> 0.000008</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000863</td>\n",
        "      <td> 0.00243</td>\n",
        "      <td> 0.000909</td>\n",
        "      <td> 0.000551</td>\n",
        "      <td> 0.000962</td>\n",
        "      <td> 0.675000</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>-1</td>\n",
        "      <td> 39.2</td>\n",
        "      <td> 0.346</td>\n",
        "      <td> 0.163</td>\n",
        "      <td> 0.339</td>\n",
        "      <td> 0.152</td>\n",
        "      <td>-28.8</td>\n",
        "      <td>-10.8</td>\n",
        "      <td> 2400</td>\n",
        "      <td> 0.000007</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:50:00</th>\n",
        "      <td> 0.000008</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000864</td>\n",
        "      <td> 0.00242</td>\n",
        "      <td> 0.000910</td>\n",
        "      <td> 0.000552</td>\n",
        "      <td> 0.000965</td>\n",
        "      <td> 1.140000</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>-1</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.346</td>\n",
        "      <td> 0.162</td>\n",
        "      <td> 0.340</td>\n",
        "      <td> 0.152</td>\n",
        "      <td>-28.9</td>\n",
        "      <td>-10.3</td>\n",
        "      <td> 2400</td>\n",
        "      <td> 0.000007</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:51:00</th>\n",
        "      <td> 0.000008</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000866</td>\n",
        "      <td> 0.00241</td>\n",
        "      <td> 0.000910</td>\n",
        "      <td> 0.000552</td>\n",
        "      <td> 0.000966</td>\n",
        "      <td> 1.260000</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>-1</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.346</td>\n",
        "      <td> 0.162</td>\n",
        "      <td> 0.340</td>\n",
        "      <td> 0.152</td>\n",
        "      <td>-28.9</td>\n",
        "      <td>-10.3</td>\n",
        "      <td> 2410</td>\n",
        "      <td> 0.000007</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:52:00</th>\n",
        "      <td> 0.000008</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000865</td>\n",
        "      <td> 0.00239</td>\n",
        "      <td> 0.000910</td>\n",
        "      <td> 0.000551</td>\n",
        "      <td> 0.000966</td>\n",
        "      <td> 1.470000</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>-1</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.345</td>\n",
        "      <td> 0.162</td>\n",
        "      <td> 0.340</td>\n",
        "      <td> 0.152</td>\n",
        "      <td>-28.9</td>\n",
        "      <td>-10.0</td>\n",
        "      <td> 2410</td>\n",
        "      <td> 0.000007</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:53:00</th>\n",
        "      <td> 0.000008</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000865</td>\n",
        "      <td> 0.00238</td>\n",
        "      <td> 0.000911</td>\n",
        "      <td> 0.000551</td>\n",
        "      <td> 0.000965</td>\n",
        "      <td> 1.820000</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>-1</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.345</td>\n",
        "      <td> 0.162</td>\n",
        "      <td> 0.340</td>\n",
        "      <td> 0.152</td>\n",
        "      <td>-28.9</td>\n",
        "      <td> -9.8</td>\n",
        "      <td> 2410</td>\n",
        "      <td> 0.000007</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:54:00</th>\n",
        "      <td> 0.000008</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000865</td>\n",
        "      <td> 0.00238</td>\n",
        "      <td> 0.000911</td>\n",
        "      <td> 0.000552</td>\n",
        "      <td> 0.000966</td>\n",
        "      <td> 1.890000</td>\n",
        "      <td> 49.4</td>\n",
        "      <td>-1</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.344</td>\n",
        "      <td> 0.162</td>\n",
        "      <td> 0.341</td>\n",
        "      <td> 0.152</td>\n",
        "      <td>-28.9</td>\n",
        "      <td> -9.4</td>\n",
        "      <td> 2410</td>\n",
        "      <td> 0.000007</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:55:00</th>\n",
        "      <td> 0.000008</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000865</td>\n",
        "      <td> 0.00236</td>\n",
        "      <td> 0.000911</td>\n",
        "      <td> 0.000552</td>\n",
        "      <td> 0.000965</td>\n",
        "      <td> 1.880000</td>\n",
        "      <td> 49.4</td>\n",
        "      <td>-1</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.345</td>\n",
        "      <td> 0.162</td>\n",
        "      <td> 0.341</td>\n",
        "      <td> 0.153</td>\n",
        "      <td>-28.9</td>\n",
        "      <td> -9.3</td>\n",
        "      <td> 2420</td>\n",
        "      <td> 0.000007</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:56:00</th>\n",
        "      <td> 0.000008</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000864</td>\n",
        "      <td> 0.00235</td>\n",
        "      <td> 0.000911</td>\n",
        "      <td> 0.000552</td>\n",
        "      <td> 0.000964</td>\n",
        "      <td> 2.040000</td>\n",
        "      <td> 49.4</td>\n",
        "      <td>-1</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.344</td>\n",
        "      <td> 0.162</td>\n",
        "      <td> 0.341</td>\n",
        "      <td> 0.153</td>\n",
        "      <td>-28.8</td>\n",
        "      <td> -9.3</td>\n",
        "      <td> 2420</td>\n",
        "      <td> 0.000007</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:57:00</th>\n",
        "      <td> 0.000008</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000864</td>\n",
        "      <td> 0.00233</td>\n",
        "      <td> 0.000911</td>\n",
        "      <td> 0.000553</td>\n",
        "      <td> 0.000964</td>\n",
        "      <td> 2.250000</td>\n",
        "      <td> 49.4</td>\n",
        "      <td>-1</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.343</td>\n",
        "      <td> 0.162</td>\n",
        "      <td> 0.341</td>\n",
        "      <td> 0.154</td>\n",
        "      <td>-28.8</td>\n",
        "      <td> -8.6</td>\n",
        "      <td> 2420</td>\n",
        "      <td> 0.000007</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:58:00</th>\n",
        "      <td> 0.000008</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000864</td>\n",
        "      <td> 0.00232</td>\n",
        "      <td> 0.000910</td>\n",
        "      <td> 0.000553</td>\n",
        "      <td> 0.000963</td>\n",
        "      <td> 2.060000</td>\n",
        "      <td> 49.4</td>\n",
        "      <td>-1</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.343</td>\n",
        "      <td> 0.162</td>\n",
        "      <td> 0.342</td>\n",
        "      <td> 0.154</td>\n",
        "      <td>-28.7</td>\n",
        "      <td> -8.3</td>\n",
        "      <td> 2420</td>\n",
        "      <td> 0.000007</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:59:00</th>\n",
        "      <td> 0.000007</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000863</td>\n",
        "      <td> 0.00230</td>\n",
        "      <td> 0.000910</td>\n",
        "      <td> 0.000554</td>\n",
        "      <td> 0.000962</td>\n",
        "      <td> 1.870000</td>\n",
        "      <td> 49.4</td>\n",
        "      <td>-1</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.343</td>\n",
        "      <td> 0.162</td>\n",
        "      <td> 0.342</td>\n",
        "      <td> 0.154</td>\n",
        "      <td>-28.7</td>\n",
        "      <td> -8.2</td>\n",
        "      <td> 2430</td>\n",
        "      <td> 0.000007</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th></th>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "<p>1440 rows \u00d7 19 columns</p>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 32,
       "text": [
        "                     XRS-B proxy  XRS-A proxy  SEM proxy  0.1-7ESPquad  \\\n",
        "HHMM                                                                     \n",
        "2014-01-01 00:00:00     0.000006     0.000000   0.000858       0.00196   \n",
        "2014-01-01 00:01:00     0.000006     0.000000   0.000858       0.00195   \n",
        "2014-01-01 00:02:00     0.000006     0.000000   0.000857       0.00195   \n",
        "2014-01-01 00:03:00     0.000006     0.000000   0.000857       0.00195   \n",
        "2014-01-01 00:04:00     0.000006     0.000000   0.000856       0.00194   \n",
        "2014-01-01 00:05:00     0.000006     0.000000   0.000856       0.00194   \n",
        "2014-01-01 00:06:00     0.000006     0.000000   0.000856       0.00194   \n",
        "2014-01-01 00:07:00     0.000006     0.000000   0.000856       0.00194   \n",
        "2014-01-01 00:08:00     0.000006     0.000000   0.000856       0.00194   \n",
        "2014-01-01 00:09:00     0.000006     0.000000   0.000857       0.00195   \n",
        "2014-01-01 00:10:00     0.000006     0.000000   0.000857       0.00196   \n",
        "2014-01-01 00:11:00     0.000006     0.000000   0.000856       0.00197   \n",
        "2014-01-01 00:12:00     0.000006     0.000000   0.000856       0.00199   \n",
        "2014-01-01 00:13:00     0.000006     0.000000   0.000855       0.00203   \n",
        "2014-01-01 00:14:00     0.000006     0.000000   0.000855       0.00208   \n",
        "2014-01-01 00:15:00     0.000007     0.000000   0.000855       0.00212   \n",
        "2014-01-01 00:16:00     0.000007     0.000001   0.000855       0.00215   \n",
        "2014-01-01 00:17:00     0.000007     0.000001   0.000855       0.00217   \n",
        "2014-01-01 00:18:00     0.000007     0.000001   0.000856       0.00218   \n",
        "2014-01-01 00:19:00     0.000007     0.000001   0.000857       0.00217   \n",
        "2014-01-01 00:20:00     0.000007     0.000001   0.000857       0.00217   \n",
        "2014-01-01 00:21:00     0.000007     0.000001   0.000856       0.00216   \n",
        "2014-01-01 00:22:00     0.000007     0.000001   0.000855       0.00217   \n",
        "2014-01-01 00:23:00     0.000007     0.000001   0.000855       0.00217   \n",
        "2014-01-01 00:24:00     0.000007     0.000001   0.000855       0.00216   \n",
        "2014-01-01 00:25:00     0.000007     0.000001   0.000856       0.00216   \n",
        "2014-01-01 00:26:00     0.000007     0.000001   0.000856       0.00217   \n",
        "2014-01-01 00:27:00     0.000007     0.000001   0.000856       0.00218   \n",
        "2014-01-01 00:28:00     0.000007     0.000001   0.000856       0.00218   \n",
        "2014-01-01 00:29:00     0.000007     0.000001   0.000856       0.00219   \n",
        "2014-01-01 00:30:00     0.000007     0.000001   0.000856       0.00220   \n",
        "2014-01-01 00:31:00     0.000007     0.000001   0.000856       0.00221   \n",
        "2014-01-01 00:32:00     0.000007     0.000001   0.000856       0.00222   \n",
        "2014-01-01 00:33:00     0.000007     0.000001   0.000856       0.00224   \n",
        "2014-01-01 00:34:00     0.000007     0.000001   0.000855       0.00226   \n",
        "2014-01-01 00:35:00     0.000007     0.000001   0.000856       0.00229   \n",
        "2014-01-01 00:36:00     0.000008     0.000001   0.000856       0.00231   \n",
        "2014-01-01 00:37:00     0.000008     0.000001   0.000857       0.00233   \n",
        "2014-01-01 00:38:00     0.000008     0.000001   0.000858       0.00236   \n",
        "2014-01-01 00:39:00     0.000008     0.000001   0.000859       0.00237   \n",
        "2014-01-01 00:40:00     0.000008     0.000001   0.000859       0.00238   \n",
        "2014-01-01 00:41:00     0.000008     0.000001   0.000859       0.00240   \n",
        "2014-01-01 00:42:00     0.000008     0.000001   0.000859       0.00241   \n",
        "2014-01-01 00:43:00     0.000008     0.000001   0.000860       0.00242   \n",
        "2014-01-01 00:44:00     0.000008     0.000001   0.000861       0.00243   \n",
        "2014-01-01 00:45:00     0.000008     0.000001   0.000861       0.00244   \n",
        "2014-01-01 00:46:00     0.000008     0.000001   0.000862       0.00244   \n",
        "2014-01-01 00:47:00     0.000008     0.000001   0.000862       0.00244   \n",
        "2014-01-01 00:48:00     0.000008     0.000001   0.000862       0.00244   \n",
        "2014-01-01 00:49:00     0.000008     0.000001   0.000863       0.00243   \n",
        "2014-01-01 00:50:00     0.000008     0.000001   0.000864       0.00242   \n",
        "2014-01-01 00:51:00     0.000008     0.000001   0.000866       0.00241   \n",
        "2014-01-01 00:52:00     0.000008     0.000001   0.000865       0.00239   \n",
        "2014-01-01 00:53:00     0.000008     0.000001   0.000865       0.00238   \n",
        "2014-01-01 00:54:00     0.000008     0.000001   0.000865       0.00238   \n",
        "2014-01-01 00:55:00     0.000008     0.000001   0.000865       0.00236   \n",
        "2014-01-01 00:56:00     0.000008     0.000001   0.000864       0.00235   \n",
        "2014-01-01 00:57:00     0.000008     0.000001   0.000864       0.00233   \n",
        "2014-01-01 00:58:00     0.000008     0.000001   0.000864       0.00232   \n",
        "2014-01-01 00:59:00     0.000007     0.000001   0.000863       0.00230   \n",
        "                             ...          ...        ...           ...   \n",
        "\n",
        "                      17.1ESP   25.7ESP   30.4ESP   36.6ESP  darkESP  \\\n",
        "HHMM                                                                   \n",
        "2014-01-01 00:00:00  0.000904  0.000547  0.000958 -1.000000     49.4   \n",
        "2014-01-01 00:01:00  0.000904  0.000547  0.000959 -1.000000     49.4   \n",
        "2014-01-01 00:02:00  0.000903  0.000547  0.000957 -1.000000     49.4   \n",
        "2014-01-01 00:03:00  0.000903  0.000547  0.000956 -1.000000     49.4   \n",
        "2014-01-01 00:04:00  0.000903  0.000547  0.000955 -1.000000     49.4   \n",
        "2014-01-01 00:05:00  0.000903  0.000547  0.000955 -1.000000     49.5   \n",
        "2014-01-01 00:06:00  0.000903  0.000546  0.000955 -1.000000     49.5   \n",
        "2014-01-01 00:07:00  0.000903  0.000546  0.000955 -1.000000     49.5   \n",
        "2014-01-01 00:08:00  0.000903  0.000546  0.000956 -1.000000     49.5   \n",
        "2014-01-01 00:09:00  0.000904  0.000546  0.000956 -1.000000     49.5   \n",
        "2014-01-01 00:10:00  0.000904  0.000546  0.000956 -1.000000     49.5   \n",
        "2014-01-01 00:11:00  0.000903  0.000546  0.000956 -1.000000     49.5   \n",
        "2014-01-01 00:12:00  0.000903  0.000546  0.000955  0.000445     49.5   \n",
        "2014-01-01 00:13:00  0.000903  0.000546  0.000954  0.007550     49.5   \n",
        "2014-01-01 00:14:00  0.000903  0.000546  0.000954  0.013800     49.5   \n",
        "2014-01-01 00:15:00  0.000904  0.000545  0.000954  0.242000     49.5   \n",
        "2014-01-01 00:16:00  0.000904  0.000545  0.000954  0.537000     49.5   \n",
        "2014-01-01 00:17:00  0.000904  0.000545  0.000954  0.597000     49.6   \n",
        "2014-01-01 00:18:00  0.000904  0.000545  0.000956  0.998000     49.6   \n",
        "2014-01-01 00:19:00  0.000905  0.000545  0.000957  0.934000     49.6   \n",
        "2014-01-01 00:20:00  0.000905  0.000545  0.000956  0.870000     49.6   \n",
        "2014-01-01 00:21:00  0.000905  0.000545  0.000955  0.808000     49.6   \n",
        "2014-01-01 00:22:00  0.000905  0.000545  0.000953  0.746000     49.6   \n",
        "2014-01-01 00:23:00  0.000905  0.000546  0.000953  0.687000     49.6   \n",
        "2014-01-01 00:24:00  0.000906  0.000546  0.000953  0.629000     49.6   \n",
        "2014-01-01 00:25:00  0.000906  0.000547  0.000954  0.574000     49.6   \n",
        "2014-01-01 00:26:00  0.000906  0.000547  0.000954  0.520000     49.5   \n",
        "2014-01-01 00:27:00  0.000906  0.000547  0.000955  0.470000     49.5   \n",
        "2014-01-01 00:28:00  0.000906  0.000547  0.000955  0.421000     49.5   \n",
        "2014-01-01 00:29:00  0.000906  0.000548  0.000954  0.376000     49.5   \n",
        "2014-01-01 00:30:00  0.000906  0.000548  0.000954  0.332000     49.6   \n",
        "2014-01-01 00:31:00  0.000906  0.000548  0.000954  0.292000     49.6   \n",
        "2014-01-01 00:32:00  0.000906  0.000548  0.000953  0.254000     49.5   \n",
        "2014-01-01 00:33:00  0.000906  0.000549  0.000953  0.219000     49.5   \n",
        "2014-01-01 00:34:00  0.000906  0.000549  0.000953  0.186000     49.5   \n",
        "2014-01-01 00:35:00  0.000906  0.000549  0.000954  0.156000     49.5   \n",
        "2014-01-01 00:36:00  0.000906  0.000549  0.000954  0.218000     49.5   \n",
        "2014-01-01 00:37:00  0.000907  0.000549  0.000955  0.361000     49.5   \n",
        "2014-01-01 00:38:00  0.000907  0.000549  0.000956  0.320000     49.5   \n",
        "2014-01-01 00:39:00  0.000907  0.000549  0.000958  0.283000     49.5   \n",
        "2014-01-01 00:40:00  0.000907  0.000550  0.000958  0.247000     49.5   \n",
        "2014-01-01 00:41:00  0.000907  0.000549  0.000957  0.214000     49.5   \n",
        "2014-01-01 00:42:00  0.000907  0.000549  0.000958  0.183000     49.5   \n",
        "2014-01-01 00:43:00  0.000908  0.000549  0.000960  0.155000     49.5   \n",
        "2014-01-01 00:44:00  0.000909  0.000550  0.000960  0.307000     49.5   \n",
        "2014-01-01 00:45:00  0.000909  0.000550  0.000961  0.620000     49.5   \n",
        "2014-01-01 00:46:00  0.000909  0.000550  0.000961  0.742000     49.5   \n",
        "2014-01-01 00:47:00  0.000909  0.000551  0.000961  0.763000     49.5   \n",
        "2014-01-01 00:48:00  0.000909  0.000551  0.000961  0.695000     49.5   \n",
        "2014-01-01 00:49:00  0.000909  0.000551  0.000962  0.675000     49.5   \n",
        "2014-01-01 00:50:00  0.000910  0.000552  0.000965  1.140000     49.5   \n",
        "2014-01-01 00:51:00  0.000910  0.000552  0.000966  1.260000     49.5   \n",
        "2014-01-01 00:52:00  0.000910  0.000551  0.000966  1.470000     49.5   \n",
        "2014-01-01 00:53:00  0.000911  0.000551  0.000965  1.820000     49.5   \n",
        "2014-01-01 00:54:00  0.000911  0.000552  0.000966  1.890000     49.4   \n",
        "2014-01-01 00:55:00  0.000911  0.000552  0.000965  1.880000     49.4   \n",
        "2014-01-01 00:56:00  0.000911  0.000552  0.000964  2.040000     49.4   \n",
        "2014-01-01 00:57:00  0.000911  0.000553  0.000964  2.250000     49.4   \n",
        "2014-01-01 00:58:00  0.000910  0.000553  0.000963  2.060000     49.4   \n",
        "2014-01-01 00:59:00  0.000910  0.000554  0.000962  1.870000     49.4   \n",
        "                          ...       ...       ...       ...      ...   \n",
        "\n",
        "                     121.6MEGS-P  darkMEGS-P  q0ESP  q1ESP  q2ESP  q3ESP  \\\n",
        "HHMM                                                                       \n",
        "2014-01-01 00:00:00           -1        39.2  0.334  0.157  0.351  0.158   \n",
        "2014-01-01 00:01:00           -1        39.2  0.334  0.157  0.351  0.158   \n",
        "2014-01-01 00:02:00           -1        39.2  0.334  0.157  0.350  0.158   \n",
        "2014-01-01 00:03:00           -1        39.2  0.334  0.157  0.351  0.158   \n",
        "2014-01-01 00:04:00           -1        39.2  0.334  0.157  0.351  0.158   \n",
        "2014-01-01 00:05:00           -1        39.2  0.335  0.157  0.350  0.158   \n",
        "2014-01-01 00:06:00           -1        39.2  0.334  0.158  0.351  0.158   \n",
        "2014-01-01 00:07:00           -1        39.2  0.334  0.158  0.350  0.158   \n",
        "2014-01-01 00:08:00           -1        39.2  0.335  0.158  0.350  0.158   \n",
        "2014-01-01 00:09:00           -1        39.2  0.335  0.158  0.349  0.158   \n",
        "2014-01-01 00:10:00           -1        39.2  0.335  0.159  0.349  0.158   \n",
        "2014-01-01 00:11:00           -1        39.2  0.335  0.159  0.349  0.158   \n",
        "2014-01-01 00:12:00           -1        39.2  0.336  0.159  0.348  0.157   \n",
        "2014-01-01 00:13:00           -1        39.3  0.338  0.160  0.345  0.156   \n",
        "2014-01-01 00:14:00           -1        39.3  0.341  0.161  0.343  0.156   \n",
        "2014-01-01 00:15:00           -1        39.3  0.341  0.162  0.342  0.155   \n",
        "2014-01-01 00:16:00           -1        39.2  0.342  0.163  0.340  0.155   \n",
        "2014-01-01 00:17:00           -1        39.2  0.343  0.164  0.338  0.155   \n",
        "2014-01-01 00:18:00           -1        39.2  0.343  0.165  0.337  0.155   \n",
        "2014-01-01 00:19:00           -1        39.3  0.343  0.165  0.336  0.155   \n",
        "2014-01-01 00:20:00           -1        39.3  0.343  0.166  0.336  0.155   \n",
        "2014-01-01 00:21:00           -1        39.3  0.343  0.165  0.337  0.155   \n",
        "2014-01-01 00:22:00           -1        39.3  0.343  0.165  0.337  0.155   \n",
        "2014-01-01 00:23:00           -1        39.3  0.343  0.165  0.337  0.155   \n",
        "2014-01-01 00:24:00           -1        39.2  0.343  0.165  0.337  0.155   \n",
        "2014-01-01 00:25:00           -1        39.2  0.344  0.165  0.336  0.155   \n",
        "2014-01-01 00:26:00           -1        39.3  0.343  0.165  0.336  0.155   \n",
        "2014-01-01 00:27:00           -1        39.3  0.343  0.165  0.337  0.155   \n",
        "2014-01-01 00:28:00           -1        39.3  0.343  0.165  0.337  0.155   \n",
        "2014-01-01 00:29:00           -1        39.3  0.343  0.165  0.338  0.154   \n",
        "2014-01-01 00:30:00           -1        39.3  0.344  0.165  0.337  0.154   \n",
        "2014-01-01 00:31:00           -1        39.3  0.345  0.164  0.337  0.154   \n",
        "2014-01-01 00:32:00           -1        39.3  0.345  0.164  0.338  0.154   \n",
        "2014-01-01 00:33:00           -1        39.3  0.346  0.164  0.338  0.153   \n",
        "2014-01-01 00:34:00           -1        39.3  0.347  0.164  0.337  0.152   \n",
        "2014-01-01 00:35:00           -1        39.3  0.349  0.164  0.336  0.151   \n",
        "2014-01-01 00:36:00           -1        39.3  0.349  0.164  0.335  0.151   \n",
        "2014-01-01 00:37:00           -1        39.3  0.351  0.164  0.334  0.151   \n",
        "2014-01-01 00:38:00           -1        39.3  0.350  0.165  0.334  0.151   \n",
        "2014-01-01 00:39:00           -1        39.3  0.351  0.164  0.334  0.151   \n",
        "2014-01-01 00:40:00           -1        39.3  0.350  0.164  0.334  0.151   \n",
        "2014-01-01 00:41:00           -1        39.3  0.350  0.164  0.335  0.151   \n",
        "2014-01-01 00:42:00           -1        39.3  0.349  0.164  0.335  0.152   \n",
        "2014-01-01 00:43:00           -1        39.3  0.349  0.164  0.336  0.151   \n",
        "2014-01-01 00:44:00           -1        39.3  0.349  0.163  0.337  0.151   \n",
        "2014-01-01 00:45:00           -1        39.3  0.349  0.163  0.338  0.151   \n",
        "2014-01-01 00:46:00           -1        39.3  0.348  0.162  0.338  0.152   \n",
        "2014-01-01 00:47:00           -1        39.3  0.348  0.163  0.338  0.152   \n",
        "2014-01-01 00:48:00           -1        39.3  0.347  0.163  0.338  0.152   \n",
        "2014-01-01 00:49:00           -1        39.2  0.346  0.163  0.339  0.152   \n",
        "2014-01-01 00:50:00           -1        39.3  0.346  0.162  0.340  0.152   \n",
        "2014-01-01 00:51:00           -1        39.3  0.346  0.162  0.340  0.152   \n",
        "2014-01-01 00:52:00           -1        39.3  0.345  0.162  0.340  0.152   \n",
        "2014-01-01 00:53:00           -1        39.3  0.345  0.162  0.340  0.152   \n",
        "2014-01-01 00:54:00           -1        39.3  0.344  0.162  0.341  0.152   \n",
        "2014-01-01 00:55:00           -1        39.3  0.345  0.162  0.341  0.153   \n",
        "2014-01-01 00:56:00           -1        39.3  0.344  0.162  0.341  0.153   \n",
        "2014-01-01 00:57:00           -1        39.3  0.343  0.162  0.341  0.154   \n",
        "2014-01-01 00:58:00           -1        39.3  0.343  0.162  0.342  0.154   \n",
        "2014-01-01 00:59:00           -1        39.3  0.343  0.162  0.342  0.154   \n",
        "                             ...         ...    ...    ...    ...    ...   \n",
        "\n",
        "                     CMLat  CMLon  x_cool proxy  oldXRSB proxy  \n",
        "HHMM                                                            \n",
        "2014-01-01 00:00:00  -28.9   -0.9          2320       0.000005  \n",
        "2014-01-01 00:01:00  -28.8   -0.9          2320       0.000005  \n",
        "2014-01-01 00:02:00  -28.7   -1.2          2320       0.000005  \n",
        "2014-01-01 00:03:00  -28.8   -1.0          2330       0.000005  \n",
        "2014-01-01 00:04:00  -28.7   -1.0          2330       0.000005  \n",
        "2014-01-01 00:05:00  -28.8   -1.3          2330       0.000005  \n",
        "2014-01-01 00:06:00  -28.8   -1.3          2330       0.000005  \n",
        "2014-01-01 00:07:00  -28.7   -1.3          2330       0.000005  \n",
        "2014-01-01 00:08:00  -28.7   -1.8          2330       0.000005  \n",
        "2014-01-01 00:09:00  -28.7   -2.0          2330       0.000005  \n",
        "2014-01-01 00:10:00  -28.6   -2.1          2340       0.000005  \n",
        "2014-01-01 00:11:00  -28.6   -2.4          2340       0.000005  \n",
        "2014-01-01 00:12:00  -28.6   -3.0          2340       0.000005  \n",
        "2014-01-01 00:13:00  -28.6   -4.7          2340       0.000006  \n",
        "2014-01-01 00:14:00  -28.5   -6.7          2340       0.000006  \n",
        "2014-01-01 00:15:00  -28.5   -7.6          2340       0.000006  \n",
        "2014-01-01 00:16:00  -28.3   -8.3          2350       0.000006  \n",
        "2014-01-01 00:17:00  -28.2   -9.5          2350       0.000006  \n",
        "2014-01-01 00:18:00  -28.0  -10.1          2350       0.000006  \n",
        "2014-01-01 00:19:00  -27.9  -10.3          2350       0.000006  \n",
        "2014-01-01 00:20:00  -27.9  -10.6          2350       0.000006  \n",
        "2014-01-01 00:21:00  -27.9  -10.2          2350       0.000006  \n",
        "2014-01-01 00:22:00  -27.9  -10.2          2360       0.000006  \n",
        "2014-01-01 00:23:00  -27.9  -10.2          2360       0.000006  \n",
        "2014-01-01 00:24:00  -28.0  -10.2          2360       0.000006  \n",
        "2014-01-01 00:25:00  -28.0  -10.5          2360       0.000006  \n",
        "2014-01-01 00:26:00  -27.9  -10.5          2360       0.000006  \n",
        "2014-01-01 00:27:00  -28.0  -10.2          2370       0.000006  \n",
        "2014-01-01 00:28:00  -28.0  -10.3          2370       0.000006  \n",
        "2014-01-01 00:29:00  -28.1  -10.2          2370       0.000006  \n",
        "2014-01-01 00:30:00  -28.2  -10.4          2370       0.000006  \n",
        "2014-01-01 00:31:00  -28.3  -10.6          2370       0.000006  \n",
        "2014-01-01 00:32:00  -28.4  -10.6          2370       0.000006  \n",
        "2014-01-01 00:33:00  -28.5  -10.9          2380       0.000007  \n",
        "2014-01-01 00:34:00  -28.6  -12.0          2380       0.000007  \n",
        "2014-01-01 00:35:00  -28.7  -13.0          2380       0.000007  \n",
        "2014-01-01 00:36:00  -28.7  -13.4          2380       0.000007  \n",
        "2014-01-01 00:37:00  -28.7  -14.1          2380       0.000007  \n",
        "2014-01-01 00:38:00  -28.6  -14.3          2380       0.000007  \n",
        "2014-01-01 00:39:00  -28.7  -14.1          2390       0.000007  \n",
        "2014-01-01 00:40:00  -28.7  -13.9          2390       0.000007  \n",
        "2014-01-01 00:41:00  -28.7  -13.5          2390       0.000007  \n",
        "2014-01-01 00:42:00  -28.7  -13.0          2390       0.000007  \n",
        "2014-01-01 00:43:00  -28.8  -12.8          2390       0.000007  \n",
        "2014-01-01 00:44:00  -28.9  -12.6          2390       0.000007  \n",
        "2014-01-01 00:45:00  -29.0  -12.1          2400       0.000007  \n",
        "2014-01-01 00:46:00  -28.9  -11.6          2400       0.000007  \n",
        "2014-01-01 00:47:00  -28.9  -11.6          2400       0.000007  \n",
        "2014-01-01 00:48:00  -28.8  -11.1          2400       0.000007  \n",
        "2014-01-01 00:49:00  -28.8  -10.8          2400       0.000007  \n",
        "2014-01-01 00:50:00  -28.9  -10.3          2400       0.000007  \n",
        "2014-01-01 00:51:00  -28.9  -10.3          2410       0.000007  \n",
        "2014-01-01 00:52:00  -28.9  -10.0          2410       0.000007  \n",
        "2014-01-01 00:53:00  -28.9   -9.8          2410       0.000007  \n",
        "2014-01-01 00:54:00  -28.9   -9.4          2410       0.000007  \n",
        "2014-01-01 00:55:00  -28.9   -9.3          2420       0.000007  \n",
        "2014-01-01 00:56:00  -28.8   -9.3          2420       0.000007  \n",
        "2014-01-01 00:57:00  -28.8   -8.6          2420       0.000007  \n",
        "2014-01-01 00:58:00  -28.7   -8.3          2420       0.000007  \n",
        "2014-01-01 00:59:00  -28.7   -8.2          2430       0.000007  \n",
        "                       ...    ...           ...            ...  \n",
        "\n",
        "[1440 rows x 19 columns]"
       ]
      }
     ],
     "prompt_number": 32
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "fig = plt.figure()\n",
      "ax = evelc.data['XRS-B proxy'].plot()\n",
      "plt.show()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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BAPz5z6pXceiQf2roDAwJItIsf4YEAEyeDGRmAg89BFy44L86fMGQICLN8tec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\n0wAAAAAASUVORK5CYII=\n",
       "text": [
        "<matplotlib.figure.Figure at 0x105eaaf90>"
       ]
      }
     ],
     "prompt_number": 33
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "ax = evelc.data['17.1ESP'].plot()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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9pOLi4v76doCTotxxWvq22zLS8Xc0vfPOO/Xaa6/ps88+63Z8ypQp+uc//6lh\nw4ZpwoQJlmUFIkG547TX133xRYsW6bzzzlNaWpoCgUDYOX6/X+ecc46F6YDIUO44LYR7NcyJx072\niWAnjsXHx2vp0qW9nn/VVVf1el3gVOEtfwHAgXgpJAA4EOUOAA5EuQOAA1HuAOBAlDsAOBDlDgAO\nRLkDgAP9L3J2N9Nb/IAcAAAAAElFTkSuQmCC\n",
       "text": [
        "<matplotlib.figure.Figure at 0x1083e6390>"
       ]
      }
     ],
     "prompt_number": 34
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "We can see that the missing data in this file hasn't been properly removed. (This is probably a bug in `EVELightCurve`). We can check the header:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "evelc.meta"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 35,
       "text": [
        "['; DATA_list: 20140101_EVE_L0CS_DIODES_1m.txt\\n',\n",
        " '; DATA_list: 20140101_EVE_L0CS_DIODES_1m.txt\\n',\n",
        " '; Created: Wed Jan  1 23:59:12 2014 UTC\\n',\n",
        " '; Origin: SDO/EVE Science Processing and Operations Center, LASP/CU\\n',\n",
        " '; Units: W/m^2 for irradiance, dark is counts/(0.25s sample), quadrants are unitless, solar lat & lon are deg\\n',\n",
        " '; Source: SDO-EVE ESP and MEGS-P instruments, http://lasp.colorado.edu/eve\\n',\n",
        " '; Product: Level 0CS, 1-minute averaged SDO-EVE Solar Indices from broadband photometers\\n',\n",
        " '; Version: 3.0, code updated 2013-Feb-02\\n',\n",
        " '; Missing data: -1.00e+00\\n',\n",
        " '; Column descriptions:\\n',\n",
        " ';  HHMM: hour and minute in UT\\n',\n",
        " ';  XRS-B proxy: a model of the expected XRS-B 0.1-0.8 nm value, calculated using two-component method\\n',\n",
        " ';  XRS-A proxy: a model of the expected XRS-A value\\n',\n",
        " ';  SEM proxy: a model of the expected SEM 26-34 nm value\\n',\n",
        " ';  0.1-7ESPquad: the total irradiance over the ESP quadrant diode 0.1-7 nm\\n',\n",
        " ';  17.1ESP: ESP irradiance measurement near 17.1 nm\\n',\n",
        " ';  25.7ESP: ESP irradiance measurement near 25.7 nm\\n',\n",
        " ';  30.4ESP: ESP irradiance measurement near 30.4 nm\\n',\n",
        " ';  36.6ESP: ESP irradiance measurement near 36.6 nm\\n',\n",
        " ';  darkESP: ESP dark diode count rates (background)\\n',\n",
        " ';  121.6MEGS-P: MEGS-P irradiance measurement at H I Lyman-alpha 121.6 nm\\n',\n",
        " ';  darkMEGS-P: MEGS-P dark diode count rates (background)\\n',\n",
        " ';  q0ESP: ESP quadrant 0 fraction (q0ESP to q3ESP add up to 1.0)\\n',\n",
        " ';  q1ESP: ESP quadrant 1 fraction\\n',\n",
        " ';  q2ESP: ESP quadrant 2 fraction\\n',\n",
        " ';  q3ESP: ESP quadrant 3 fraction\\n',\n",
        " ';  CMLat: Latitude centroid of ESP quad diode irradiance at the sun in degrees\\n',\n",
        " ';  CMLon: Longitude centroid of ESP quad diode irradiance at the sun in degrees\\n',\n",
        " ';  x_cool proxy: Cool component for calculating XRS-B proxy\\n',\n",
        " ';  oldXRSB proxy: XRS-B calculated using the version 2 method\\n',\n",
        " '; Format:\\n',\n",
        " ';  YYYY DOY MO DD\\n',\n",
        " ';  HHMM XRS-B    XRS-A      SEM      0.1-7     17.1      25.7      30.4      36.6      dark      121.6     dark      q0        q1        q2        q3        CM    CM       x_cool oldXRSB\\n',\n",
        " ';       proxy    proxy     proxy     ESPquad   ESP       ESP       ESP       ESP       ESP       MEGS-P    MEGS-P    ESP       ESP       ESP       ESP       Lat   Lon      proxy  proxy\\n',\n",
        " ';---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\\n',\n",
        " ';END_OF_HEADER\\n']"
       ]
      }
     ],
     "prompt_number": 35
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from pandas import isnull\n",
      "evelc.data['17.1ESP'][evelc.data['17.1ESP'] == -1]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 36,
       "text": [
        "HHMM\n",
        "2014-01-01 17:23:00   -1\n",
        "Name: 17.1ESP, dtype: float64"
       ]
      }
     ],
     "prompt_number": 36
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "evelc.data['17.1ESP'][evelc.data['17.1ESP'] == -1] = np.nan"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 37
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "evelc.data.replace(-1, np.nan)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>XRS-B proxy</th>\n",
        "      <th>XRS-A proxy</th>\n",
        "      <th>SEM proxy</th>\n",
        "      <th>0.1-7ESPquad</th>\n",
        "      <th>17.1ESP</th>\n",
        "      <th>25.7ESP</th>\n",
        "      <th>30.4ESP</th>\n",
        "      <th>36.6ESP</th>\n",
        "      <th>darkESP</th>\n",
        "      <th>121.6MEGS-P</th>\n",
        "      <th>darkMEGS-P</th>\n",
        "      <th>q0ESP</th>\n",
        "      <th>q1ESP</th>\n",
        "      <th>q2ESP</th>\n",
        "      <th>q3ESP</th>\n",
        "      <th>CMLat</th>\n",
        "      <th>CMLon</th>\n",
        "      <th>x_cool proxy</th>\n",
        "      <th>oldXRSB proxy</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>HHMM</th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:00:00</th>\n",
        "      <td> 0.000006</td>\n",
        "      <td> 0.000000</td>\n",
        "      <td> 0.000858</td>\n",
        "      <td> 0.00196</td>\n",
        "      <td> 0.000904</td>\n",
        "      <td> 0.000547</td>\n",
        "      <td> 0.000958</td>\n",
        "      <td>      NaN</td>\n",
        "      <td> 49.4</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 39.2</td>\n",
        "      <td> 0.334</td>\n",
        "      <td> 0.157</td>\n",
        "      <td> 0.351</td>\n",
        "      <td> 0.158</td>\n",
        "      <td>-28.9</td>\n",
        "      <td> -0.9</td>\n",
        "      <td> 2320</td>\n",
        "      <td> 0.000005</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:01:00</th>\n",
        "      <td> 0.000006</td>\n",
        "      <td> 0.000000</td>\n",
        "      <td> 0.000858</td>\n",
        "      <td> 0.00195</td>\n",
        "      <td> 0.000904</td>\n",
        "      <td> 0.000547</td>\n",
        "      <td> 0.000959</td>\n",
        "      <td>      NaN</td>\n",
        "      <td> 49.4</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 39.2</td>\n",
        "      <td> 0.334</td>\n",
        "      <td> 0.157</td>\n",
        "      <td> 0.351</td>\n",
        "      <td> 0.158</td>\n",
        "      <td>-28.8</td>\n",
        "      <td> -0.9</td>\n",
        "      <td> 2320</td>\n",
        "      <td> 0.000005</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:02:00</th>\n",
        "      <td> 0.000006</td>\n",
        "      <td> 0.000000</td>\n",
        "      <td> 0.000857</td>\n",
        "      <td> 0.00195</td>\n",
        "      <td> 0.000903</td>\n",
        "      <td> 0.000547</td>\n",
        "      <td> 0.000957</td>\n",
        "      <td>      NaN</td>\n",
        "      <td> 49.4</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 39.2</td>\n",
        "      <td> 0.334</td>\n",
        "      <td> 0.157</td>\n",
        "      <td> 0.350</td>\n",
        "      <td> 0.158</td>\n",
        "      <td>-28.7</td>\n",
        "      <td> -1.2</td>\n",
        "      <td> 2320</td>\n",
        "      <td> 0.000005</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:03:00</th>\n",
        "      <td> 0.000006</td>\n",
        "      <td> 0.000000</td>\n",
        "      <td> 0.000857</td>\n",
        "      <td> 0.00195</td>\n",
        "      <td> 0.000903</td>\n",
        "      <td> 0.000547</td>\n",
        "      <td> 0.000956</td>\n",
        "      <td>      NaN</td>\n",
        "      <td> 49.4</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 39.2</td>\n",
        "      <td> 0.334</td>\n",
        "      <td> 0.157</td>\n",
        "      <td> 0.351</td>\n",
        "      <td> 0.158</td>\n",
        "      <td>-28.8</td>\n",
        "      <td>  NaN</td>\n",
        "      <td> 2330</td>\n",
        "      <td> 0.000005</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:04:00</th>\n",
        "      <td> 0.000006</td>\n",
        "      <td> 0.000000</td>\n",
        "      <td> 0.000856</td>\n",
        "      <td> 0.00194</td>\n",
        "      <td> 0.000903</td>\n",
        "      <td> 0.000547</td>\n",
        "      <td> 0.000955</td>\n",
        "      <td>      NaN</td>\n",
        "      <td> 49.4</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 39.2</td>\n",
        "      <td> 0.334</td>\n",
        "      <td> 0.157</td>\n",
        "      <td> 0.351</td>\n",
        "      <td> 0.158</td>\n",
        "      <td>-28.7</td>\n",
        "      <td>  NaN</td>\n",
        "      <td> 2330</td>\n",
        "      <td> 0.000005</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:05:00</th>\n",
        "      <td> 0.000006</td>\n",
        "      <td> 0.000000</td>\n",
        "      <td> 0.000856</td>\n",
        "      <td> 0.00194</td>\n",
        "      <td> 0.000903</td>\n",
        "      <td> 0.000547</td>\n",
        "      <td> 0.000955</td>\n",
        "      <td>      NaN</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 39.2</td>\n",
        "      <td> 0.335</td>\n",
        "      <td> 0.157</td>\n",
        "      <td> 0.350</td>\n",
        "      <td> 0.158</td>\n",
        "      <td>-28.8</td>\n",
        "      <td> -1.3</td>\n",
        "      <td> 2330</td>\n",
        "      <td> 0.000005</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:06:00</th>\n",
        "      <td> 0.000006</td>\n",
        "      <td> 0.000000</td>\n",
        "      <td> 0.000856</td>\n",
        "      <td> 0.00194</td>\n",
        "      <td> 0.000903</td>\n",
        "      <td> 0.000546</td>\n",
        "      <td> 0.000955</td>\n",
        "      <td>      NaN</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 39.2</td>\n",
        "      <td> 0.334</td>\n",
        "      <td> 0.158</td>\n",
        "      <td> 0.351</td>\n",
        "      <td> 0.158</td>\n",
        "      <td>-28.8</td>\n",
        "      <td> -1.3</td>\n",
        "      <td> 2330</td>\n",
        "      <td> 0.000005</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:07:00</th>\n",
        "      <td> 0.000006</td>\n",
        "      <td> 0.000000</td>\n",
        "      <td> 0.000856</td>\n",
        "      <td> 0.00194</td>\n",
        "      <td> 0.000903</td>\n",
        "      <td> 0.000546</td>\n",
        "      <td> 0.000955</td>\n",
        "      <td>      NaN</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 39.2</td>\n",
        "      <td> 0.334</td>\n",
        "      <td> 0.158</td>\n",
        "      <td> 0.350</td>\n",
        "      <td> 0.158</td>\n",
        "      <td>-28.7</td>\n",
        "      <td> -1.3</td>\n",
        "      <td> 2330</td>\n",
        "      <td> 0.000005</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:08:00</th>\n",
        "      <td> 0.000006</td>\n",
        "      <td> 0.000000</td>\n",
        "      <td> 0.000856</td>\n",
        "      <td> 0.00194</td>\n",
        "      <td> 0.000903</td>\n",
        "      <td> 0.000546</td>\n",
        "      <td> 0.000956</td>\n",
        "      <td>      NaN</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 39.2</td>\n",
        "      <td> 0.335</td>\n",
        "      <td> 0.158</td>\n",
        "      <td> 0.350</td>\n",
        "      <td> 0.158</td>\n",
        "      <td>-28.7</td>\n",
        "      <td> -1.8</td>\n",
        "      <td> 2330</td>\n",
        "      <td> 0.000005</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:09:00</th>\n",
        "      <td> 0.000006</td>\n",
        "      <td> 0.000000</td>\n",
        "      <td> 0.000857</td>\n",
        "      <td> 0.00195</td>\n",
        "      <td> 0.000904</td>\n",
        "      <td> 0.000546</td>\n",
        "      <td> 0.000956</td>\n",
        "      <td>      NaN</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 39.2</td>\n",
        "      <td> 0.335</td>\n",
        "      <td> 0.158</td>\n",
        "      <td> 0.349</td>\n",
        "      <td> 0.158</td>\n",
        "      <td>-28.7</td>\n",
        "      <td> -2.0</td>\n",
        "      <td> 2330</td>\n",
        "      <td> 0.000005</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:10:00</th>\n",
        "      <td> 0.000006</td>\n",
        "      <td> 0.000000</td>\n",
        "      <td> 0.000857</td>\n",
        "      <td> 0.00196</td>\n",
        "      <td> 0.000904</td>\n",
        "      <td> 0.000546</td>\n",
        "      <td> 0.000956</td>\n",
        "      <td>      NaN</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 39.2</td>\n",
        "      <td> 0.335</td>\n",
        "      <td> 0.159</td>\n",
        "      <td> 0.349</td>\n",
        "      <td> 0.158</td>\n",
        "      <td>-28.6</td>\n",
        "      <td> -2.1</td>\n",
        "      <td> 2340</td>\n",
        "      <td> 0.000005</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:11:00</th>\n",
        "      <td> 0.000006</td>\n",
        "      <td> 0.000000</td>\n",
        "      <td> 0.000856</td>\n",
        "      <td> 0.00197</td>\n",
        "      <td> 0.000903</td>\n",
        "      <td> 0.000546</td>\n",
        "      <td> 0.000956</td>\n",
        "      <td>      NaN</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 39.2</td>\n",
        "      <td> 0.335</td>\n",
        "      <td> 0.159</td>\n",
        "      <td> 0.349</td>\n",
        "      <td> 0.158</td>\n",
        "      <td>-28.6</td>\n",
        "      <td> -2.4</td>\n",
        "      <td> 2340</td>\n",
        "      <td> 0.000005</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:12:00</th>\n",
        "      <td> 0.000006</td>\n",
        "      <td> 0.000000</td>\n",
        "      <td> 0.000856</td>\n",
        "      <td> 0.00199</td>\n",
        "      <td> 0.000903</td>\n",
        "      <td> 0.000546</td>\n",
        "      <td> 0.000955</td>\n",
        "      <td> 0.000445</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 39.2</td>\n",
        "      <td> 0.336</td>\n",
        "      <td> 0.159</td>\n",
        "      <td> 0.348</td>\n",
        "      <td> 0.157</td>\n",
        "      <td>-28.6</td>\n",
        "      <td> -3.0</td>\n",
        "      <td> 2340</td>\n",
        "      <td> 0.000005</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:13:00</th>\n",
        "      <td> 0.000006</td>\n",
        "      <td> 0.000000</td>\n",
        "      <td> 0.000855</td>\n",
        "      <td> 0.00203</td>\n",
        "      <td> 0.000903</td>\n",
        "      <td> 0.000546</td>\n",
        "      <td> 0.000954</td>\n",
        "      <td> 0.007550</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.338</td>\n",
        "      <td> 0.160</td>\n",
        "      <td> 0.345</td>\n",
        "      <td> 0.156</td>\n",
        "      <td>-28.6</td>\n",
        "      <td> -4.7</td>\n",
        "      <td> 2340</td>\n",
        "      <td> 0.000006</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:14:00</th>\n",
        "      <td> 0.000006</td>\n",
        "      <td> 0.000000</td>\n",
        "      <td> 0.000855</td>\n",
        "      <td> 0.00208</td>\n",
        "      <td> 0.000903</td>\n",
        "      <td> 0.000546</td>\n",
        "      <td> 0.000954</td>\n",
        "      <td> 0.013800</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.341</td>\n",
        "      <td> 0.161</td>\n",
        "      <td> 0.343</td>\n",
        "      <td> 0.156</td>\n",
        "      <td>-28.5</td>\n",
        "      <td> -6.7</td>\n",
        "      <td> 2340</td>\n",
        "      <td> 0.000006</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:15:00</th>\n",
        "      <td> 0.000007</td>\n",
        "      <td> 0.000000</td>\n",
        "      <td> 0.000855</td>\n",
        "      <td> 0.00212</td>\n",
        "      <td> 0.000904</td>\n",
        "      <td> 0.000545</td>\n",
        "      <td> 0.000954</td>\n",
        "      <td> 0.242000</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.341</td>\n",
        "      <td> 0.162</td>\n",
        "      <td> 0.342</td>\n",
        "      <td> 0.155</td>\n",
        "      <td>-28.5</td>\n",
        "      <td> -7.6</td>\n",
        "      <td> 2340</td>\n",
        "      <td> 0.000006</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:16:00</th>\n",
        "      <td> 0.000007</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000855</td>\n",
        "      <td> 0.00215</td>\n",
        "      <td> 0.000904</td>\n",
        "      <td> 0.000545</td>\n",
        "      <td> 0.000954</td>\n",
        "      <td> 0.537000</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 39.2</td>\n",
        "      <td> 0.342</td>\n",
        "      <td> 0.163</td>\n",
        "      <td> 0.340</td>\n",
        "      <td> 0.155</td>\n",
        "      <td>-28.3</td>\n",
        "      <td> -8.3</td>\n",
        "      <td> 2350</td>\n",
        "      <td> 0.000006</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:17:00</th>\n",
        "      <td> 0.000007</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000855</td>\n",
        "      <td> 0.00217</td>\n",
        "      <td> 0.000904</td>\n",
        "      <td> 0.000545</td>\n",
        "      <td> 0.000954</td>\n",
        "      <td> 0.597000</td>\n",
        "      <td> 49.6</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 39.2</td>\n",
        "      <td> 0.343</td>\n",
        "      <td> 0.164</td>\n",
        "      <td> 0.338</td>\n",
        "      <td> 0.155</td>\n",
        "      <td>-28.2</td>\n",
        "      <td> -9.5</td>\n",
        "      <td> 2350</td>\n",
        "      <td> 0.000006</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:18:00</th>\n",
        "      <td> 0.000007</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000856</td>\n",
        "      <td> 0.00218</td>\n",
        "      <td> 0.000904</td>\n",
        "      <td> 0.000545</td>\n",
        "      <td> 0.000956</td>\n",
        "      <td> 0.998000</td>\n",
        "      <td> 49.6</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 39.2</td>\n",
        "      <td> 0.343</td>\n",
        "      <td> 0.165</td>\n",
        "      <td> 0.337</td>\n",
        "      <td> 0.155</td>\n",
        "      <td>-28.0</td>\n",
        "      <td>-10.1</td>\n",
        "      <td> 2350</td>\n",
        "      <td> 0.000006</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:19:00</th>\n",
        "      <td> 0.000007</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000857</td>\n",
        "      <td> 0.00217</td>\n",
        "      <td> 0.000905</td>\n",
        "      <td> 0.000545</td>\n",
        "      <td> 0.000957</td>\n",
        "      <td> 0.934000</td>\n",
        "      <td> 49.6</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.343</td>\n",
        "      <td> 0.165</td>\n",
        "      <td> 0.336</td>\n",
        "      <td> 0.155</td>\n",
        "      <td>-27.9</td>\n",
        "      <td>-10.3</td>\n",
        "      <td> 2350</td>\n",
        "      <td> 0.000006</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:20:00</th>\n",
        "      <td> 0.000007</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000857</td>\n",
        "      <td> 0.00217</td>\n",
        "      <td> 0.000905</td>\n",
        "      <td> 0.000545</td>\n",
        "      <td> 0.000956</td>\n",
        "      <td> 0.870000</td>\n",
        "      <td> 49.6</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.343</td>\n",
        "      <td> 0.166</td>\n",
        "      <td> 0.336</td>\n",
        "      <td> 0.155</td>\n",
        "      <td>-27.9</td>\n",
        "      <td>-10.6</td>\n",
        "      <td> 2350</td>\n",
        "      <td> 0.000006</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:21:00</th>\n",
        "      <td> 0.000007</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000856</td>\n",
        "      <td> 0.00216</td>\n",
        "      <td> 0.000905</td>\n",
        "      <td> 0.000545</td>\n",
        "      <td> 0.000955</td>\n",
        "      <td> 0.808000</td>\n",
        "      <td> 49.6</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.343</td>\n",
        "      <td> 0.165</td>\n",
        "      <td> 0.337</td>\n",
        "      <td> 0.155</td>\n",
        "      <td>-27.9</td>\n",
        "      <td>-10.2</td>\n",
        "      <td> 2350</td>\n",
        "      <td> 0.000006</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:22:00</th>\n",
        "      <td> 0.000007</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000855</td>\n",
        "      <td> 0.00217</td>\n",
        "      <td> 0.000905</td>\n",
        "      <td> 0.000545</td>\n",
        "      <td> 0.000953</td>\n",
        "      <td> 0.746000</td>\n",
        "      <td> 49.6</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.343</td>\n",
        "      <td> 0.165</td>\n",
        "      <td> 0.337</td>\n",
        "      <td> 0.155</td>\n",
        "      <td>-27.9</td>\n",
        "      <td>-10.2</td>\n",
        "      <td> 2360</td>\n",
        "      <td> 0.000006</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:23:00</th>\n",
        "      <td> 0.000007</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000855</td>\n",
        "      <td> 0.00217</td>\n",
        "      <td> 0.000905</td>\n",
        "      <td> 0.000546</td>\n",
        "      <td> 0.000953</td>\n",
        "      <td> 0.687000</td>\n",
        "      <td> 49.6</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.343</td>\n",
        "      <td> 0.165</td>\n",
        "      <td> 0.337</td>\n",
        "      <td> 0.155</td>\n",
        "      <td>-27.9</td>\n",
        "      <td>-10.2</td>\n",
        "      <td> 2360</td>\n",
        "      <td> 0.000006</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:24:00</th>\n",
        "      <td> 0.000007</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000855</td>\n",
        "      <td> 0.00216</td>\n",
        "      <td> 0.000906</td>\n",
        "      <td> 0.000546</td>\n",
        "      <td> 0.000953</td>\n",
        "      <td> 0.629000</td>\n",
        "      <td> 49.6</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 39.2</td>\n",
        "      <td> 0.343</td>\n",
        "      <td> 0.165</td>\n",
        "      <td> 0.337</td>\n",
        "      <td> 0.155</td>\n",
        "      <td>-28.0</td>\n",
        "      <td>-10.2</td>\n",
        "      <td> 2360</td>\n",
        "      <td> 0.000006</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:25:00</th>\n",
        "      <td> 0.000007</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000856</td>\n",
        "      <td> 0.00216</td>\n",
        "      <td> 0.000906</td>\n",
        "      <td> 0.000547</td>\n",
        "      <td> 0.000954</td>\n",
        "      <td> 0.574000</td>\n",
        "      <td> 49.6</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 39.2</td>\n",
        "      <td> 0.344</td>\n",
        "      <td> 0.165</td>\n",
        "      <td> 0.336</td>\n",
        "      <td> 0.155</td>\n",
        "      <td>-28.0</td>\n",
        "      <td>-10.5</td>\n",
        "      <td> 2360</td>\n",
        "      <td> 0.000006</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:26:00</th>\n",
        "      <td> 0.000007</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000856</td>\n",
        "      <td> 0.00217</td>\n",
        "      <td> 0.000906</td>\n",
        "      <td> 0.000547</td>\n",
        "      <td> 0.000954</td>\n",
        "      <td> 0.520000</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.343</td>\n",
        "      <td> 0.165</td>\n",
        "      <td> 0.336</td>\n",
        "      <td> 0.155</td>\n",
        "      <td>-27.9</td>\n",
        "      <td>-10.5</td>\n",
        "      <td> 2360</td>\n",
        "      <td> 0.000006</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:27:00</th>\n",
        "      <td> 0.000007</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000856</td>\n",
        "      <td> 0.00218</td>\n",
        "      <td> 0.000906</td>\n",
        "      <td> 0.000547</td>\n",
        "      <td> 0.000955</td>\n",
        "      <td> 0.470000</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.343</td>\n",
        "      <td> 0.165</td>\n",
        "      <td> 0.337</td>\n",
        "      <td> 0.155</td>\n",
        "      <td>-28.0</td>\n",
        "      <td>-10.2</td>\n",
        "      <td> 2370</td>\n",
        "      <td> 0.000006</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:28:00</th>\n",
        "      <td> 0.000007</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000856</td>\n",
        "      <td> 0.00218</td>\n",
        "      <td> 0.000906</td>\n",
        "      <td> 0.000547</td>\n",
        "      <td> 0.000955</td>\n",
        "      <td> 0.421000</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.343</td>\n",
        "      <td> 0.165</td>\n",
        "      <td> 0.337</td>\n",
        "      <td> 0.155</td>\n",
        "      <td>-28.0</td>\n",
        "      <td>-10.3</td>\n",
        "      <td> 2370</td>\n",
        "      <td> 0.000006</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:29:00</th>\n",
        "      <td> 0.000007</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000856</td>\n",
        "      <td> 0.00219</td>\n",
        "      <td> 0.000906</td>\n",
        "      <td> 0.000548</td>\n",
        "      <td> 0.000954</td>\n",
        "      <td> 0.376000</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.343</td>\n",
        "      <td> 0.165</td>\n",
        "      <td> 0.338</td>\n",
        "      <td> 0.154</td>\n",
        "      <td>-28.1</td>\n",
        "      <td>-10.2</td>\n",
        "      <td> 2370</td>\n",
        "      <td> 0.000006</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:30:00</th>\n",
        "      <td> 0.000007</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000856</td>\n",
        "      <td> 0.00220</td>\n",
        "      <td> 0.000906</td>\n",
        "      <td> 0.000548</td>\n",
        "      <td> 0.000954</td>\n",
        "      <td> 0.332000</td>\n",
        "      <td> 49.6</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.344</td>\n",
        "      <td> 0.165</td>\n",
        "      <td> 0.337</td>\n",
        "      <td> 0.154</td>\n",
        "      <td>-28.2</td>\n",
        "      <td>-10.4</td>\n",
        "      <td> 2370</td>\n",
        "      <td> 0.000006</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:31:00</th>\n",
        "      <td> 0.000007</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000856</td>\n",
        "      <td> 0.00221</td>\n",
        "      <td> 0.000906</td>\n",
        "      <td> 0.000548</td>\n",
        "      <td> 0.000954</td>\n",
        "      <td> 0.292000</td>\n",
        "      <td> 49.6</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.345</td>\n",
        "      <td> 0.164</td>\n",
        "      <td> 0.337</td>\n",
        "      <td> 0.154</td>\n",
        "      <td>-28.3</td>\n",
        "      <td>-10.6</td>\n",
        "      <td> 2370</td>\n",
        "      <td> 0.000006</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:32:00</th>\n",
        "      <td> 0.000007</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000856</td>\n",
        "      <td> 0.00222</td>\n",
        "      <td> 0.000906</td>\n",
        "      <td> 0.000548</td>\n",
        "      <td> 0.000953</td>\n",
        "      <td> 0.254000</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.345</td>\n",
        "      <td> 0.164</td>\n",
        "      <td> 0.338</td>\n",
        "      <td> 0.154</td>\n",
        "      <td>-28.4</td>\n",
        "      <td>-10.6</td>\n",
        "      <td> 2370</td>\n",
        "      <td> 0.000006</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:33:00</th>\n",
        "      <td> 0.000007</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000856</td>\n",
        "      <td> 0.00224</td>\n",
        "      <td> 0.000906</td>\n",
        "      <td> 0.000549</td>\n",
        "      <td> 0.000953</td>\n",
        "      <td> 0.219000</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.346</td>\n",
        "      <td> 0.164</td>\n",
        "      <td> 0.338</td>\n",
        "      <td> 0.153</td>\n",
        "      <td>-28.5</td>\n",
        "      <td>-10.9</td>\n",
        "      <td> 2380</td>\n",
        "      <td> 0.000007</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:34:00</th>\n",
        "      <td> 0.000007</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000855</td>\n",
        "      <td> 0.00226</td>\n",
        "      <td> 0.000906</td>\n",
        "      <td> 0.000549</td>\n",
        "      <td> 0.000953</td>\n",
        "      <td> 0.186000</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.347</td>\n",
        "      <td> 0.164</td>\n",
        "      <td> 0.337</td>\n",
        "      <td> 0.152</td>\n",
        "      <td>-28.6</td>\n",
        "      <td>-12.0</td>\n",
        "      <td> 2380</td>\n",
        "      <td> 0.000007</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:35:00</th>\n",
        "      <td> 0.000007</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000856</td>\n",
        "      <td> 0.00229</td>\n",
        "      <td> 0.000906</td>\n",
        "      <td> 0.000549</td>\n",
        "      <td> 0.000954</td>\n",
        "      <td> 0.156000</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.349</td>\n",
        "      <td> 0.164</td>\n",
        "      <td> 0.336</td>\n",
        "      <td> 0.151</td>\n",
        "      <td>-28.7</td>\n",
        "      <td>-13.0</td>\n",
        "      <td> 2380</td>\n",
        "      <td> 0.000007</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:36:00</th>\n",
        "      <td> 0.000008</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000856</td>\n",
        "      <td> 0.00231</td>\n",
        "      <td> 0.000906</td>\n",
        "      <td> 0.000549</td>\n",
        "      <td> 0.000954</td>\n",
        "      <td> 0.218000</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.349</td>\n",
        "      <td> 0.164</td>\n",
        "      <td> 0.335</td>\n",
        "      <td> 0.151</td>\n",
        "      <td>-28.7</td>\n",
        "      <td>-13.4</td>\n",
        "      <td> 2380</td>\n",
        "      <td> 0.000007</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:37:00</th>\n",
        "      <td> 0.000008</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000857</td>\n",
        "      <td> 0.00233</td>\n",
        "      <td> 0.000907</td>\n",
        "      <td> 0.000549</td>\n",
        "      <td> 0.000955</td>\n",
        "      <td> 0.361000</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.351</td>\n",
        "      <td> 0.164</td>\n",
        "      <td> 0.334</td>\n",
        "      <td> 0.151</td>\n",
        "      <td>-28.7</td>\n",
        "      <td>-14.1</td>\n",
        "      <td> 2380</td>\n",
        "      <td> 0.000007</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:38:00</th>\n",
        "      <td> 0.000008</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000858</td>\n",
        "      <td> 0.00236</td>\n",
        "      <td> 0.000907</td>\n",
        "      <td> 0.000549</td>\n",
        "      <td> 0.000956</td>\n",
        "      <td> 0.320000</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.350</td>\n",
        "      <td> 0.165</td>\n",
        "      <td> 0.334</td>\n",
        "      <td> 0.151</td>\n",
        "      <td>-28.6</td>\n",
        "      <td>-14.3</td>\n",
        "      <td> 2380</td>\n",
        "      <td> 0.000007</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:39:00</th>\n",
        "      <td> 0.000008</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000859</td>\n",
        "      <td> 0.00237</td>\n",
        "      <td> 0.000907</td>\n",
        "      <td> 0.000549</td>\n",
        "      <td> 0.000958</td>\n",
        "      <td> 0.283000</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.351</td>\n",
        "      <td> 0.164</td>\n",
        "      <td> 0.334</td>\n",
        "      <td> 0.151</td>\n",
        "      <td>-28.7</td>\n",
        "      <td>-14.1</td>\n",
        "      <td> 2390</td>\n",
        "      <td> 0.000007</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:40:00</th>\n",
        "      <td> 0.000008</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000859</td>\n",
        "      <td> 0.00238</td>\n",
        "      <td> 0.000907</td>\n",
        "      <td> 0.000550</td>\n",
        "      <td> 0.000958</td>\n",
        "      <td> 0.247000</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.350</td>\n",
        "      <td> 0.164</td>\n",
        "      <td> 0.334</td>\n",
        "      <td> 0.151</td>\n",
        "      <td>-28.7</td>\n",
        "      <td>-13.9</td>\n",
        "      <td> 2390</td>\n",
        "      <td> 0.000007</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:41:00</th>\n",
        "      <td> 0.000008</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000859</td>\n",
        "      <td> 0.00240</td>\n",
        "      <td> 0.000907</td>\n",
        "      <td> 0.000549</td>\n",
        "      <td> 0.000957</td>\n",
        "      <td> 0.214000</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.350</td>\n",
        "      <td> 0.164</td>\n",
        "      <td> 0.335</td>\n",
        "      <td> 0.151</td>\n",
        "      <td>-28.7</td>\n",
        "      <td>-13.5</td>\n",
        "      <td> 2390</td>\n",
        "      <td> 0.000007</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:42:00</th>\n",
        "      <td> 0.000008</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000859</td>\n",
        "      <td> 0.00241</td>\n",
        "      <td> 0.000907</td>\n",
        "      <td> 0.000549</td>\n",
        "      <td> 0.000958</td>\n",
        "      <td> 0.183000</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.349</td>\n",
        "      <td> 0.164</td>\n",
        "      <td> 0.335</td>\n",
        "      <td> 0.152</td>\n",
        "      <td>-28.7</td>\n",
        "      <td>-13.0</td>\n",
        "      <td> 2390</td>\n",
        "      <td> 0.000007</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:43:00</th>\n",
        "      <td> 0.000008</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000860</td>\n",
        "      <td> 0.00242</td>\n",
        "      <td> 0.000908</td>\n",
        "      <td> 0.000549</td>\n",
        "      <td> 0.000960</td>\n",
        "      <td> 0.155000</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.349</td>\n",
        "      <td> 0.164</td>\n",
        "      <td> 0.336</td>\n",
        "      <td> 0.151</td>\n",
        "      <td>-28.8</td>\n",
        "      <td>-12.8</td>\n",
        "      <td> 2390</td>\n",
        "      <td> 0.000007</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:44:00</th>\n",
        "      <td> 0.000008</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000861</td>\n",
        "      <td> 0.00243</td>\n",
        "      <td> 0.000909</td>\n",
        "      <td> 0.000550</td>\n",
        "      <td> 0.000960</td>\n",
        "      <td> 0.307000</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.349</td>\n",
        "      <td> 0.163</td>\n",
        "      <td> 0.337</td>\n",
        "      <td> 0.151</td>\n",
        "      <td>-28.9</td>\n",
        "      <td>-12.6</td>\n",
        "      <td> 2390</td>\n",
        "      <td> 0.000007</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:45:00</th>\n",
        "      <td> 0.000008</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000861</td>\n",
        "      <td> 0.00244</td>\n",
        "      <td> 0.000909</td>\n",
        "      <td> 0.000550</td>\n",
        "      <td> 0.000961</td>\n",
        "      <td> 0.620000</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.349</td>\n",
        "      <td> 0.163</td>\n",
        "      <td> 0.338</td>\n",
        "      <td> 0.151</td>\n",
        "      <td>-29.0</td>\n",
        "      <td>-12.1</td>\n",
        "      <td> 2400</td>\n",
        "      <td> 0.000007</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:46:00</th>\n",
        "      <td> 0.000008</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000862</td>\n",
        "      <td> 0.00244</td>\n",
        "      <td> 0.000909</td>\n",
        "      <td> 0.000550</td>\n",
        "      <td> 0.000961</td>\n",
        "      <td> 0.742000</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.348</td>\n",
        "      <td> 0.162</td>\n",
        "      <td> 0.338</td>\n",
        "      <td> 0.152</td>\n",
        "      <td>-28.9</td>\n",
        "      <td>-11.6</td>\n",
        "      <td> 2400</td>\n",
        "      <td> 0.000007</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:47:00</th>\n",
        "      <td> 0.000008</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000862</td>\n",
        "      <td> 0.00244</td>\n",
        "      <td> 0.000909</td>\n",
        "      <td> 0.000551</td>\n",
        "      <td> 0.000961</td>\n",
        "      <td> 0.763000</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.348</td>\n",
        "      <td> 0.163</td>\n",
        "      <td> 0.338</td>\n",
        "      <td> 0.152</td>\n",
        "      <td>-28.9</td>\n",
        "      <td>-11.6</td>\n",
        "      <td> 2400</td>\n",
        "      <td> 0.000007</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:48:00</th>\n",
        "      <td> 0.000008</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000862</td>\n",
        "      <td> 0.00244</td>\n",
        "      <td> 0.000909</td>\n",
        "      <td> 0.000551</td>\n",
        "      <td> 0.000961</td>\n",
        "      <td> 0.695000</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.347</td>\n",
        "      <td> 0.163</td>\n",
        "      <td> 0.338</td>\n",
        "      <td> 0.152</td>\n",
        "      <td>-28.8</td>\n",
        "      <td>-11.1</td>\n",
        "      <td> 2400</td>\n",
        "      <td> 0.000007</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:49:00</th>\n",
        "      <td> 0.000008</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000863</td>\n",
        "      <td> 0.00243</td>\n",
        "      <td> 0.000909</td>\n",
        "      <td> 0.000551</td>\n",
        "      <td> 0.000962</td>\n",
        "      <td> 0.675000</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 39.2</td>\n",
        "      <td> 0.346</td>\n",
        "      <td> 0.163</td>\n",
        "      <td> 0.339</td>\n",
        "      <td> 0.152</td>\n",
        "      <td>-28.8</td>\n",
        "      <td>-10.8</td>\n",
        "      <td> 2400</td>\n",
        "      <td> 0.000007</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:50:00</th>\n",
        "      <td> 0.000008</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000864</td>\n",
        "      <td> 0.00242</td>\n",
        "      <td> 0.000910</td>\n",
        "      <td> 0.000552</td>\n",
        "      <td> 0.000965</td>\n",
        "      <td> 1.140000</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.346</td>\n",
        "      <td> 0.162</td>\n",
        "      <td> 0.340</td>\n",
        "      <td> 0.152</td>\n",
        "      <td>-28.9</td>\n",
        "      <td>-10.3</td>\n",
        "      <td> 2400</td>\n",
        "      <td> 0.000007</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:51:00</th>\n",
        "      <td> 0.000008</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000866</td>\n",
        "      <td> 0.00241</td>\n",
        "      <td> 0.000910</td>\n",
        "      <td> 0.000552</td>\n",
        "      <td> 0.000966</td>\n",
        "      <td> 1.260000</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.346</td>\n",
        "      <td> 0.162</td>\n",
        "      <td> 0.340</td>\n",
        "      <td> 0.152</td>\n",
        "      <td>-28.9</td>\n",
        "      <td>-10.3</td>\n",
        "      <td> 2410</td>\n",
        "      <td> 0.000007</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:52:00</th>\n",
        "      <td> 0.000008</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000865</td>\n",
        "      <td> 0.00239</td>\n",
        "      <td> 0.000910</td>\n",
        "      <td> 0.000551</td>\n",
        "      <td> 0.000966</td>\n",
        "      <td> 1.470000</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.345</td>\n",
        "      <td> 0.162</td>\n",
        "      <td> 0.340</td>\n",
        "      <td> 0.152</td>\n",
        "      <td>-28.9</td>\n",
        "      <td>-10.0</td>\n",
        "      <td> 2410</td>\n",
        "      <td> 0.000007</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:53:00</th>\n",
        "      <td> 0.000008</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000865</td>\n",
        "      <td> 0.00238</td>\n",
        "      <td> 0.000911</td>\n",
        "      <td> 0.000551</td>\n",
        "      <td> 0.000965</td>\n",
        "      <td> 1.820000</td>\n",
        "      <td> 49.5</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.345</td>\n",
        "      <td> 0.162</td>\n",
        "      <td> 0.340</td>\n",
        "      <td> 0.152</td>\n",
        "      <td>-28.9</td>\n",
        "      <td> -9.8</td>\n",
        "      <td> 2410</td>\n",
        "      <td> 0.000007</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:54:00</th>\n",
        "      <td> 0.000008</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000865</td>\n",
        "      <td> 0.00238</td>\n",
        "      <td> 0.000911</td>\n",
        "      <td> 0.000552</td>\n",
        "      <td> 0.000966</td>\n",
        "      <td> 1.890000</td>\n",
        "      <td> 49.4</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.344</td>\n",
        "      <td> 0.162</td>\n",
        "      <td> 0.341</td>\n",
        "      <td> 0.152</td>\n",
        "      <td>-28.9</td>\n",
        "      <td> -9.4</td>\n",
        "      <td> 2410</td>\n",
        "      <td> 0.000007</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:55:00</th>\n",
        "      <td> 0.000008</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000865</td>\n",
        "      <td> 0.00236</td>\n",
        "      <td> 0.000911</td>\n",
        "      <td> 0.000552</td>\n",
        "      <td> 0.000965</td>\n",
        "      <td> 1.880000</td>\n",
        "      <td> 49.4</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.345</td>\n",
        "      <td> 0.162</td>\n",
        "      <td> 0.341</td>\n",
        "      <td> 0.153</td>\n",
        "      <td>-28.9</td>\n",
        "      <td> -9.3</td>\n",
        "      <td> 2420</td>\n",
        "      <td> 0.000007</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:56:00</th>\n",
        "      <td> 0.000008</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000864</td>\n",
        "      <td> 0.00235</td>\n",
        "      <td> 0.000911</td>\n",
        "      <td> 0.000552</td>\n",
        "      <td> 0.000964</td>\n",
        "      <td> 2.040000</td>\n",
        "      <td> 49.4</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.344</td>\n",
        "      <td> 0.162</td>\n",
        "      <td> 0.341</td>\n",
        "      <td> 0.153</td>\n",
        "      <td>-28.8</td>\n",
        "      <td> -9.3</td>\n",
        "      <td> 2420</td>\n",
        "      <td> 0.000007</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:57:00</th>\n",
        "      <td> 0.000008</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000864</td>\n",
        "      <td> 0.00233</td>\n",
        "      <td> 0.000911</td>\n",
        "      <td> 0.000553</td>\n",
        "      <td> 0.000964</td>\n",
        "      <td> 2.250000</td>\n",
        "      <td> 49.4</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.343</td>\n",
        "      <td> 0.162</td>\n",
        "      <td> 0.341</td>\n",
        "      <td> 0.154</td>\n",
        "      <td>-28.8</td>\n",
        "      <td> -8.6</td>\n",
        "      <td> 2420</td>\n",
        "      <td> 0.000007</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:58:00</th>\n",
        "      <td> 0.000008</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000864</td>\n",
        "      <td> 0.00232</td>\n",
        "      <td> 0.000910</td>\n",
        "      <td> 0.000553</td>\n",
        "      <td> 0.000963</td>\n",
        "      <td> 2.060000</td>\n",
        "      <td> 49.4</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.343</td>\n",
        "      <td> 0.162</td>\n",
        "      <td> 0.342</td>\n",
        "      <td> 0.154</td>\n",
        "      <td>-28.7</td>\n",
        "      <td> -8.3</td>\n",
        "      <td> 2420</td>\n",
        "      <td> 0.000007</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-01 00:59:00</th>\n",
        "      <td> 0.000007</td>\n",
        "      <td> 0.000001</td>\n",
        "      <td> 0.000863</td>\n",
        "      <td> 0.00230</td>\n",
        "      <td> 0.000910</td>\n",
        "      <td> 0.000554</td>\n",
        "      <td> 0.000962</td>\n",
        "      <td> 1.870000</td>\n",
        "      <td> 49.4</td>\n",
        "      <td>NaN</td>\n",
        "      <td> 39.3</td>\n",
        "      <td> 0.343</td>\n",
        "      <td> 0.162</td>\n",
        "      <td> 0.342</td>\n",
        "      <td> 0.154</td>\n",
        "      <td>-28.7</td>\n",
        "      <td> -8.2</td>\n",
        "      <td> 2430</td>\n",
        "      <td> 0.000007</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th></th>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "<p>1440 rows \u00d7 19 columns</p>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 38,
       "text": [
        "                     XRS-B proxy  XRS-A proxy  SEM proxy  0.1-7ESPquad  \\\n",
        "HHMM                                                                     \n",
        "2014-01-01 00:00:00     0.000006     0.000000   0.000858       0.00196   \n",
        "2014-01-01 00:01:00     0.000006     0.000000   0.000858       0.00195   \n",
        "2014-01-01 00:02:00     0.000006     0.000000   0.000857       0.00195   \n",
        "2014-01-01 00:03:00     0.000006     0.000000   0.000857       0.00195   \n",
        "2014-01-01 00:04:00     0.000006     0.000000   0.000856       0.00194   \n",
        "2014-01-01 00:05:00     0.000006     0.000000   0.000856       0.00194   \n",
        "2014-01-01 00:06:00     0.000006     0.000000   0.000856       0.00194   \n",
        "2014-01-01 00:07:00     0.000006     0.000000   0.000856       0.00194   \n",
        "2014-01-01 00:08:00     0.000006     0.000000   0.000856       0.00194   \n",
        "2014-01-01 00:09:00     0.000006     0.000000   0.000857       0.00195   \n",
        "2014-01-01 00:10:00     0.000006     0.000000   0.000857       0.00196   \n",
        "2014-01-01 00:11:00     0.000006     0.000000   0.000856       0.00197   \n",
        "2014-01-01 00:12:00     0.000006     0.000000   0.000856       0.00199   \n",
        "2014-01-01 00:13:00     0.000006     0.000000   0.000855       0.00203   \n",
        "2014-01-01 00:14:00     0.000006     0.000000   0.000855       0.00208   \n",
        "2014-01-01 00:15:00     0.000007     0.000000   0.000855       0.00212   \n",
        "2014-01-01 00:16:00     0.000007     0.000001   0.000855       0.00215   \n",
        "2014-01-01 00:17:00     0.000007     0.000001   0.000855       0.00217   \n",
        "2014-01-01 00:18:00     0.000007     0.000001   0.000856       0.00218   \n",
        "2014-01-01 00:19:00     0.000007     0.000001   0.000857       0.00217   \n",
        "2014-01-01 00:20:00     0.000007     0.000001   0.000857       0.00217   \n",
        "2014-01-01 00:21:00     0.000007     0.000001   0.000856       0.00216   \n",
        "2014-01-01 00:22:00     0.000007     0.000001   0.000855       0.00217   \n",
        "2014-01-01 00:23:00     0.000007     0.000001   0.000855       0.00217   \n",
        "2014-01-01 00:24:00     0.000007     0.000001   0.000855       0.00216   \n",
        "2014-01-01 00:25:00     0.000007     0.000001   0.000856       0.00216   \n",
        "2014-01-01 00:26:00     0.000007     0.000001   0.000856       0.00217   \n",
        "2014-01-01 00:27:00     0.000007     0.000001   0.000856       0.00218   \n",
        "2014-01-01 00:28:00     0.000007     0.000001   0.000856       0.00218   \n",
        "2014-01-01 00:29:00     0.000007     0.000001   0.000856       0.00219   \n",
        "2014-01-01 00:30:00     0.000007     0.000001   0.000856       0.00220   \n",
        "2014-01-01 00:31:00     0.000007     0.000001   0.000856       0.00221   \n",
        "2014-01-01 00:32:00     0.000007     0.000001   0.000856       0.00222   \n",
        "2014-01-01 00:33:00     0.000007     0.000001   0.000856       0.00224   \n",
        "2014-01-01 00:34:00     0.000007     0.000001   0.000855       0.00226   \n",
        "2014-01-01 00:35:00     0.000007     0.000001   0.000856       0.00229   \n",
        "2014-01-01 00:36:00     0.000008     0.000001   0.000856       0.00231   \n",
        "2014-01-01 00:37:00     0.000008     0.000001   0.000857       0.00233   \n",
        "2014-01-01 00:38:00     0.000008     0.000001   0.000858       0.00236   \n",
        "2014-01-01 00:39:00     0.000008     0.000001   0.000859       0.00237   \n",
        "2014-01-01 00:40:00     0.000008     0.000001   0.000859       0.00238   \n",
        "2014-01-01 00:41:00     0.000008     0.000001   0.000859       0.00240   \n",
        "2014-01-01 00:42:00     0.000008     0.000001   0.000859       0.00241   \n",
        "2014-01-01 00:43:00     0.000008     0.000001   0.000860       0.00242   \n",
        "2014-01-01 00:44:00     0.000008     0.000001   0.000861       0.00243   \n",
        "2014-01-01 00:45:00     0.000008     0.000001   0.000861       0.00244   \n",
        "2014-01-01 00:46:00     0.000008     0.000001   0.000862       0.00244   \n",
        "2014-01-01 00:47:00     0.000008     0.000001   0.000862       0.00244   \n",
        "2014-01-01 00:48:00     0.000008     0.000001   0.000862       0.00244   \n",
        "2014-01-01 00:49:00     0.000008     0.000001   0.000863       0.00243   \n",
        "2014-01-01 00:50:00     0.000008     0.000001   0.000864       0.00242   \n",
        "2014-01-01 00:51:00     0.000008     0.000001   0.000866       0.00241   \n",
        "2014-01-01 00:52:00     0.000008     0.000001   0.000865       0.00239   \n",
        "2014-01-01 00:53:00     0.000008     0.000001   0.000865       0.00238   \n",
        "2014-01-01 00:54:00     0.000008     0.000001   0.000865       0.00238   \n",
        "2014-01-01 00:55:00     0.000008     0.000001   0.000865       0.00236   \n",
        "2014-01-01 00:56:00     0.000008     0.000001   0.000864       0.00235   \n",
        "2014-01-01 00:57:00     0.000008     0.000001   0.000864       0.00233   \n",
        "2014-01-01 00:58:00     0.000008     0.000001   0.000864       0.00232   \n",
        "2014-01-01 00:59:00     0.000007     0.000001   0.000863       0.00230   \n",
        "                             ...          ...        ...           ...   \n",
        "\n",
        "                      17.1ESP   25.7ESP   30.4ESP   36.6ESP  darkESP  \\\n",
        "HHMM                                                                   \n",
        "2014-01-01 00:00:00  0.000904  0.000547  0.000958       NaN     49.4   \n",
        "2014-01-01 00:01:00  0.000904  0.000547  0.000959       NaN     49.4   \n",
        "2014-01-01 00:02:00  0.000903  0.000547  0.000957       NaN     49.4   \n",
        "2014-01-01 00:03:00  0.000903  0.000547  0.000956       NaN     49.4   \n",
        "2014-01-01 00:04:00  0.000903  0.000547  0.000955       NaN     49.4   \n",
        "2014-01-01 00:05:00  0.000903  0.000547  0.000955       NaN     49.5   \n",
        "2014-01-01 00:06:00  0.000903  0.000546  0.000955       NaN     49.5   \n",
        "2014-01-01 00:07:00  0.000903  0.000546  0.000955       NaN     49.5   \n",
        "2014-01-01 00:08:00  0.000903  0.000546  0.000956       NaN     49.5   \n",
        "2014-01-01 00:09:00  0.000904  0.000546  0.000956       NaN     49.5   \n",
        "2014-01-01 00:10:00  0.000904  0.000546  0.000956       NaN     49.5   \n",
        "2014-01-01 00:11:00  0.000903  0.000546  0.000956       NaN     49.5   \n",
        "2014-01-01 00:12:00  0.000903  0.000546  0.000955  0.000445     49.5   \n",
        "2014-01-01 00:13:00  0.000903  0.000546  0.000954  0.007550     49.5   \n",
        "2014-01-01 00:14:00  0.000903  0.000546  0.000954  0.013800     49.5   \n",
        "2014-01-01 00:15:00  0.000904  0.000545  0.000954  0.242000     49.5   \n",
        "2014-01-01 00:16:00  0.000904  0.000545  0.000954  0.537000     49.5   \n",
        "2014-01-01 00:17:00  0.000904  0.000545  0.000954  0.597000     49.6   \n",
        "2014-01-01 00:18:00  0.000904  0.000545  0.000956  0.998000     49.6   \n",
        "2014-01-01 00:19:00  0.000905  0.000545  0.000957  0.934000     49.6   \n",
        "2014-01-01 00:20:00  0.000905  0.000545  0.000956  0.870000     49.6   \n",
        "2014-01-01 00:21:00  0.000905  0.000545  0.000955  0.808000     49.6   \n",
        "2014-01-01 00:22:00  0.000905  0.000545  0.000953  0.746000     49.6   \n",
        "2014-01-01 00:23:00  0.000905  0.000546  0.000953  0.687000     49.6   \n",
        "2014-01-01 00:24:00  0.000906  0.000546  0.000953  0.629000     49.6   \n",
        "2014-01-01 00:25:00  0.000906  0.000547  0.000954  0.574000     49.6   \n",
        "2014-01-01 00:26:00  0.000906  0.000547  0.000954  0.520000     49.5   \n",
        "2014-01-01 00:27:00  0.000906  0.000547  0.000955  0.470000     49.5   \n",
        "2014-01-01 00:28:00  0.000906  0.000547  0.000955  0.421000     49.5   \n",
        "2014-01-01 00:29:00  0.000906  0.000548  0.000954  0.376000     49.5   \n",
        "2014-01-01 00:30:00  0.000906  0.000548  0.000954  0.332000     49.6   \n",
        "2014-01-01 00:31:00  0.000906  0.000548  0.000954  0.292000     49.6   \n",
        "2014-01-01 00:32:00  0.000906  0.000548  0.000953  0.254000     49.5   \n",
        "2014-01-01 00:33:00  0.000906  0.000549  0.000953  0.219000     49.5   \n",
        "2014-01-01 00:34:00  0.000906  0.000549  0.000953  0.186000     49.5   \n",
        "2014-01-01 00:35:00  0.000906  0.000549  0.000954  0.156000     49.5   \n",
        "2014-01-01 00:36:00  0.000906  0.000549  0.000954  0.218000     49.5   \n",
        "2014-01-01 00:37:00  0.000907  0.000549  0.000955  0.361000     49.5   \n",
        "2014-01-01 00:38:00  0.000907  0.000549  0.000956  0.320000     49.5   \n",
        "2014-01-01 00:39:00  0.000907  0.000549  0.000958  0.283000     49.5   \n",
        "2014-01-01 00:40:00  0.000907  0.000550  0.000958  0.247000     49.5   \n",
        "2014-01-01 00:41:00  0.000907  0.000549  0.000957  0.214000     49.5   \n",
        "2014-01-01 00:42:00  0.000907  0.000549  0.000958  0.183000     49.5   \n",
        "2014-01-01 00:43:00  0.000908  0.000549  0.000960  0.155000     49.5   \n",
        "2014-01-01 00:44:00  0.000909  0.000550  0.000960  0.307000     49.5   \n",
        "2014-01-01 00:45:00  0.000909  0.000550  0.000961  0.620000     49.5   \n",
        "2014-01-01 00:46:00  0.000909  0.000550  0.000961  0.742000     49.5   \n",
        "2014-01-01 00:47:00  0.000909  0.000551  0.000961  0.763000     49.5   \n",
        "2014-01-01 00:48:00  0.000909  0.000551  0.000961  0.695000     49.5   \n",
        "2014-01-01 00:49:00  0.000909  0.000551  0.000962  0.675000     49.5   \n",
        "2014-01-01 00:50:00  0.000910  0.000552  0.000965  1.140000     49.5   \n",
        "2014-01-01 00:51:00  0.000910  0.000552  0.000966  1.260000     49.5   \n",
        "2014-01-01 00:52:00  0.000910  0.000551  0.000966  1.470000     49.5   \n",
        "2014-01-01 00:53:00  0.000911  0.000551  0.000965  1.820000     49.5   \n",
        "2014-01-01 00:54:00  0.000911  0.000552  0.000966  1.890000     49.4   \n",
        "2014-01-01 00:55:00  0.000911  0.000552  0.000965  1.880000     49.4   \n",
        "2014-01-01 00:56:00  0.000911  0.000552  0.000964  2.040000     49.4   \n",
        "2014-01-01 00:57:00  0.000911  0.000553  0.000964  2.250000     49.4   \n",
        "2014-01-01 00:58:00  0.000910  0.000553  0.000963  2.060000     49.4   \n",
        "2014-01-01 00:59:00  0.000910  0.000554  0.000962  1.870000     49.4   \n",
        "                          ...       ...       ...       ...      ...   \n",
        "\n",
        "                     121.6MEGS-P  darkMEGS-P  q0ESP  q1ESP  q2ESP  q3ESP  \\\n",
        "HHMM                                                                       \n",
        "2014-01-01 00:00:00          NaN        39.2  0.334  0.157  0.351  0.158   \n",
        "2014-01-01 00:01:00          NaN        39.2  0.334  0.157  0.351  0.158   \n",
        "2014-01-01 00:02:00          NaN        39.2  0.334  0.157  0.350  0.158   \n",
        "2014-01-01 00:03:00          NaN        39.2  0.334  0.157  0.351  0.158   \n",
        "2014-01-01 00:04:00          NaN        39.2  0.334  0.157  0.351  0.158   \n",
        "2014-01-01 00:05:00          NaN        39.2  0.335  0.157  0.350  0.158   \n",
        "2014-01-01 00:06:00          NaN        39.2  0.334  0.158  0.351  0.158   \n",
        "2014-01-01 00:07:00          NaN        39.2  0.334  0.158  0.350  0.158   \n",
        "2014-01-01 00:08:00          NaN        39.2  0.335  0.158  0.350  0.158   \n",
        "2014-01-01 00:09:00          NaN        39.2  0.335  0.158  0.349  0.158   \n",
        "2014-01-01 00:10:00          NaN        39.2  0.335  0.159  0.349  0.158   \n",
        "2014-01-01 00:11:00          NaN        39.2  0.335  0.159  0.349  0.158   \n",
        "2014-01-01 00:12:00          NaN        39.2  0.336  0.159  0.348  0.157   \n",
        "2014-01-01 00:13:00          NaN        39.3  0.338  0.160  0.345  0.156   \n",
        "2014-01-01 00:14:00          NaN        39.3  0.341  0.161  0.343  0.156   \n",
        "2014-01-01 00:15:00          NaN        39.3  0.341  0.162  0.342  0.155   \n",
        "2014-01-01 00:16:00          NaN        39.2  0.342  0.163  0.340  0.155   \n",
        "2014-01-01 00:17:00          NaN        39.2  0.343  0.164  0.338  0.155   \n",
        "2014-01-01 00:18:00          NaN        39.2  0.343  0.165  0.337  0.155   \n",
        "2014-01-01 00:19:00          NaN        39.3  0.343  0.165  0.336  0.155   \n",
        "2014-01-01 00:20:00          NaN        39.3  0.343  0.166  0.336  0.155   \n",
        "2014-01-01 00:21:00          NaN        39.3  0.343  0.165  0.337  0.155   \n",
        "2014-01-01 00:22:00          NaN        39.3  0.343  0.165  0.337  0.155   \n",
        "2014-01-01 00:23:00          NaN        39.3  0.343  0.165  0.337  0.155   \n",
        "2014-01-01 00:24:00          NaN        39.2  0.343  0.165  0.337  0.155   \n",
        "2014-01-01 00:25:00          NaN        39.2  0.344  0.165  0.336  0.155   \n",
        "2014-01-01 00:26:00          NaN        39.3  0.343  0.165  0.336  0.155   \n",
        "2014-01-01 00:27:00          NaN        39.3  0.343  0.165  0.337  0.155   \n",
        "2014-01-01 00:28:00          NaN        39.3  0.343  0.165  0.337  0.155   \n",
        "2014-01-01 00:29:00          NaN        39.3  0.343  0.165  0.338  0.154   \n",
        "2014-01-01 00:30:00          NaN        39.3  0.344  0.165  0.337  0.154   \n",
        "2014-01-01 00:31:00          NaN        39.3  0.345  0.164  0.337  0.154   \n",
        "2014-01-01 00:32:00          NaN        39.3  0.345  0.164  0.338  0.154   \n",
        "2014-01-01 00:33:00          NaN        39.3  0.346  0.164  0.338  0.153   \n",
        "2014-01-01 00:34:00          NaN        39.3  0.347  0.164  0.337  0.152   \n",
        "2014-01-01 00:35:00          NaN        39.3  0.349  0.164  0.336  0.151   \n",
        "2014-01-01 00:36:00          NaN        39.3  0.349  0.164  0.335  0.151   \n",
        "2014-01-01 00:37:00          NaN        39.3  0.351  0.164  0.334  0.151   \n",
        "2014-01-01 00:38:00          NaN        39.3  0.350  0.165  0.334  0.151   \n",
        "2014-01-01 00:39:00          NaN        39.3  0.351  0.164  0.334  0.151   \n",
        "2014-01-01 00:40:00          NaN        39.3  0.350  0.164  0.334  0.151   \n",
        "2014-01-01 00:41:00          NaN        39.3  0.350  0.164  0.335  0.151   \n",
        "2014-01-01 00:42:00          NaN        39.3  0.349  0.164  0.335  0.152   \n",
        "2014-01-01 00:43:00          NaN        39.3  0.349  0.164  0.336  0.151   \n",
        "2014-01-01 00:44:00          NaN        39.3  0.349  0.163  0.337  0.151   \n",
        "2014-01-01 00:45:00          NaN        39.3  0.349  0.163  0.338  0.151   \n",
        "2014-01-01 00:46:00          NaN        39.3  0.348  0.162  0.338  0.152   \n",
        "2014-01-01 00:47:00          NaN        39.3  0.348  0.163  0.338  0.152   \n",
        "2014-01-01 00:48:00          NaN        39.3  0.347  0.163  0.338  0.152   \n",
        "2014-01-01 00:49:00          NaN        39.2  0.346  0.163  0.339  0.152   \n",
        "2014-01-01 00:50:00          NaN        39.3  0.346  0.162  0.340  0.152   \n",
        "2014-01-01 00:51:00          NaN        39.3  0.346  0.162  0.340  0.152   \n",
        "2014-01-01 00:52:00          NaN        39.3  0.345  0.162  0.340  0.152   \n",
        "2014-01-01 00:53:00          NaN        39.3  0.345  0.162  0.340  0.152   \n",
        "2014-01-01 00:54:00          NaN        39.3  0.344  0.162  0.341  0.152   \n",
        "2014-01-01 00:55:00          NaN        39.3  0.345  0.162  0.341  0.153   \n",
        "2014-01-01 00:56:00          NaN        39.3  0.344  0.162  0.341  0.153   \n",
        "2014-01-01 00:57:00          NaN        39.3  0.343  0.162  0.341  0.154   \n",
        "2014-01-01 00:58:00          NaN        39.3  0.343  0.162  0.342  0.154   \n",
        "2014-01-01 00:59:00          NaN        39.3  0.343  0.162  0.342  0.154   \n",
        "                             ...         ...    ...    ...    ...    ...   \n",
        "\n",
        "                     CMLat  CMLon  x_cool proxy  oldXRSB proxy  \n",
        "HHMM                                                            \n",
        "2014-01-01 00:00:00  -28.9   -0.9          2320       0.000005  \n",
        "2014-01-01 00:01:00  -28.8   -0.9          2320       0.000005  \n",
        "2014-01-01 00:02:00  -28.7   -1.2          2320       0.000005  \n",
        "2014-01-01 00:03:00  -28.8    NaN          2330       0.000005  \n",
        "2014-01-01 00:04:00  -28.7    NaN          2330       0.000005  \n",
        "2014-01-01 00:05:00  -28.8   -1.3          2330       0.000005  \n",
        "2014-01-01 00:06:00  -28.8   -1.3          2330       0.000005  \n",
        "2014-01-01 00:07:00  -28.7   -1.3          2330       0.000005  \n",
        "2014-01-01 00:08:00  -28.7   -1.8          2330       0.000005  \n",
        "2014-01-01 00:09:00  -28.7   -2.0          2330       0.000005  \n",
        "2014-01-01 00:10:00  -28.6   -2.1          2340       0.000005  \n",
        "2014-01-01 00:11:00  -28.6   -2.4          2340       0.000005  \n",
        "2014-01-01 00:12:00  -28.6   -3.0          2340       0.000005  \n",
        "2014-01-01 00:13:00  -28.6   -4.7          2340       0.000006  \n",
        "2014-01-01 00:14:00  -28.5   -6.7          2340       0.000006  \n",
        "2014-01-01 00:15:00  -28.5   -7.6          2340       0.000006  \n",
        "2014-01-01 00:16:00  -28.3   -8.3          2350       0.000006  \n",
        "2014-01-01 00:17:00  -28.2   -9.5          2350       0.000006  \n",
        "2014-01-01 00:18:00  -28.0  -10.1          2350       0.000006  \n",
        "2014-01-01 00:19:00  -27.9  -10.3          2350       0.000006  \n",
        "2014-01-01 00:20:00  -27.9  -10.6          2350       0.000006  \n",
        "2014-01-01 00:21:00  -27.9  -10.2          2350       0.000006  \n",
        "2014-01-01 00:22:00  -27.9  -10.2          2360       0.000006  \n",
        "2014-01-01 00:23:00  -27.9  -10.2          2360       0.000006  \n",
        "2014-01-01 00:24:00  -28.0  -10.2          2360       0.000006  \n",
        "2014-01-01 00:25:00  -28.0  -10.5          2360       0.000006  \n",
        "2014-01-01 00:26:00  -27.9  -10.5          2360       0.000006  \n",
        "2014-01-01 00:27:00  -28.0  -10.2          2370       0.000006  \n",
        "2014-01-01 00:28:00  -28.0  -10.3          2370       0.000006  \n",
        "2014-01-01 00:29:00  -28.1  -10.2          2370       0.000006  \n",
        "2014-01-01 00:30:00  -28.2  -10.4          2370       0.000006  \n",
        "2014-01-01 00:31:00  -28.3  -10.6          2370       0.000006  \n",
        "2014-01-01 00:32:00  -28.4  -10.6          2370       0.000006  \n",
        "2014-01-01 00:33:00  -28.5  -10.9          2380       0.000007  \n",
        "2014-01-01 00:34:00  -28.6  -12.0          2380       0.000007  \n",
        "2014-01-01 00:35:00  -28.7  -13.0          2380       0.000007  \n",
        "2014-01-01 00:36:00  -28.7  -13.4          2380       0.000007  \n",
        "2014-01-01 00:37:00  -28.7  -14.1          2380       0.000007  \n",
        "2014-01-01 00:38:00  -28.6  -14.3          2380       0.000007  \n",
        "2014-01-01 00:39:00  -28.7  -14.1          2390       0.000007  \n",
        "2014-01-01 00:40:00  -28.7  -13.9          2390       0.000007  \n",
        "2014-01-01 00:41:00  -28.7  -13.5          2390       0.000007  \n",
        "2014-01-01 00:42:00  -28.7  -13.0          2390       0.000007  \n",
        "2014-01-01 00:43:00  -28.8  -12.8          2390       0.000007  \n",
        "2014-01-01 00:44:00  -28.9  -12.6          2390       0.000007  \n",
        "2014-01-01 00:45:00  -29.0  -12.1          2400       0.000007  \n",
        "2014-01-01 00:46:00  -28.9  -11.6          2400       0.000007  \n",
        "2014-01-01 00:47:00  -28.9  -11.6          2400       0.000007  \n",
        "2014-01-01 00:48:00  -28.8  -11.1          2400       0.000007  \n",
        "2014-01-01 00:49:00  -28.8  -10.8          2400       0.000007  \n",
        "2014-01-01 00:50:00  -28.9  -10.3          2400       0.000007  \n",
        "2014-01-01 00:51:00  -28.9  -10.3          2410       0.000007  \n",
        "2014-01-01 00:52:00  -28.9  -10.0          2410       0.000007  \n",
        "2014-01-01 00:53:00  -28.9   -9.8          2410       0.000007  \n",
        "2014-01-01 00:54:00  -28.9   -9.4          2410       0.000007  \n",
        "2014-01-01 00:55:00  -28.9   -9.3          2420       0.000007  \n",
        "2014-01-01 00:56:00  -28.8   -9.3          2420       0.000007  \n",
        "2014-01-01 00:57:00  -28.8   -8.6          2420       0.000007  \n",
        "2014-01-01 00:58:00  -28.7   -8.3          2420       0.000007  \n",
        "2014-01-01 00:59:00  -28.7   -8.2          2430       0.000007  \n",
        "                       ...    ...           ...            ...  \n",
        "\n",
        "[1440 rows x 19 columns]"
       ]
      }
     ],
     "prompt_number": 38
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "evelc.data['17.1ESP'][evelc.data['17.1ESP'] == -1]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 39,
       "text": [
        "Series([], name: 17.1ESP, dtype: float64)"
       ]
      }
     ],
     "prompt_number": 39
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import pandas as pd\n",
      "pd.__version__"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 40,
       "text": [
        "'0.13.1'"
       ]
      }
     ],
     "prompt_number": 40
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "ax = evelc.data['17.1ESP'].plot()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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OEowxp+bo3U3aIa5A0yRx9izg4QF07my4ldEWOEkwxpyao3c3aedIAE0TQcPnevfmJMEY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\nTkSuQmCC\n",
       "text": [
        "<matplotlib.figure.Figure at 0x10c1b3e90>"
       ]
      }
     ],
     "prompt_number": 41
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "## Solar Constants"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from sunpy.sun import constants as sun"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 42
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "sun.mass"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "latex": [
        "$1.9891\\times 10^{+30} \\; \\mathrm{kg}$"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 43,
       "text": [
        "<Constant name=u'Solar mass' value=1.9891e+30 error=5e+25 units='kg' reference=u\"Allen's Astrophysical Quantities 4th Ed.\">"
       ]
      }
     ],
     "prompt_number": 43
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "type(sun.mass)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 44,
       "text": [
        "astropy.constants.constant.Constant"
       ]
      }
     ],
     "prompt_number": 44
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "print(sun.mass)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "  Name   = Solar mass\n",
        "  Value  = 1.9891e+30\n",
        "  Error  = 5e+25\n",
        "  Units  = kg\n",
        "  Reference = Allen's Astrophysical Quantities 4th Ed.\n"
       ]
      }
     ],
     "prompt_number": 45
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "(sun.mass/sun.volume).cgs"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "latex": [
        "$1.40851 \\; \\mathrm{\\frac{g}{cm^{3}}}$"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 46,
       "text": [
        "<Quantity 1.4085115422744656 g / cm3>"
       ]
      }
     ],
     "prompt_number": 46
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "sun.find('age')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 47,
       "text": [
        "['age', 'average angular size', 'average density', 'average intensity']"
       ]
      }
     ],
     "prompt_number": 47
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "sun.value('age'), sun.unit('age')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 48,
       "text": [
        "(4600000000.0, Unit(\"yr\"))"
       ]
      }
     ],
     "prompt_number": 48
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "## Searching the VSO"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from sunpy.net import vso\n",
      "client = vso.VSOClient()\n",
      "tstart, tend = '2011/6/7 05:30', '2011/6/7 6:30'"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 49
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "lasco_query = client.query(vso.attrs.Time(tstart, tend), vso.attrs.Instrument('lasco'))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 50
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "lasco_query.num_records()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 51,
       "text": [
        "8"
       ]
      }
     ],
     "prompt_number": 51
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "lasco_query.show()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Start time           End time             Source  Instrument  Type  \n",
        "----------           --------             ------  ----------  ----  \n",
        "2011-06-07 05:35:23  2011-06-07 05:35:48  SOHO    LASCO       CORONA\n",
        "2011-06-07 05:43:09  2011-06-07 05:43:29  SOHO    LASCO       CORONA\n",
        "2011-06-07 05:50:13  2011-06-07 05:50:38  SOHO    LASCO       CORONA\n",
        "2011-06-07 05:57:59  2011-06-07 05:58:18  SOHO    LASCO       CORONA\n",
        "2011-06-07 06:04:58  2011-06-07 06:05:23  SOHO    LASCO       CORONA\n",
        "2011-06-07 06:12:45  2011-06-07 06:13:04  SOHO    LASCO       CORONA\n",
        "2011-06-07 06:19:43  2011-06-07 06:20:08  SOHO    LASCO       CORONA\n",
        "2011-06-07 06:27:29  2011-06-07 06:27:48  SOHO    LASCO       CORONA\n"
       ]
      }
     ],
     "prompt_number": 52
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "now download the data"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "pathformat = '/Users/schriste/sunpy/data/{file}.fits'\n",
      "results = client.get(lasco_query, path = pathformat)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 53
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "instrument_condition = ( vso.attrs.Instrument('lasco') | vso.attrs.Detector('cor1') )\n",
      "coronagraphs = client.query(vso.attrs.Time(tstart, tend), instrument_condition)\n",
      "coronagraphs.num_records()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 54,
       "text": [
        "117"
       ]
      }
     ],
     "prompt_number": 54
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "coronagraphs.show()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Start time           End time             Source    Instrument  Type  \n",
        "----------           --------             ------    ----------  ----  \n",
        "2011-06-07 05:35:23  2011-06-07 05:35:48  SOHO      LASCO       CORONA\n",
        "2011-06-07 05:43:09  2011-06-07 05:43:29  SOHO      LASCO       CORONA\n",
        "2011-06-07 05:50:13  2011-06-07 05:50:38  SOHO      LASCO       CORONA\n",
        "2011-06-07 05:57:59  2011-06-07 05:58:18  SOHO      LASCO       CORONA\n",
        "2011-06-07 06:04:58  2011-06-07 06:05:23  SOHO      LASCO       CORONA\n",
        "2011-06-07 06:12:45  2011-06-07 06:13:04  SOHO      LASCO       CORONA\n",
        "2011-06-07 06:19:43  2011-06-07 06:20:08  SOHO      LASCO       CORONA\n",
        "2011-06-07 06:27:29  2011-06-07 06:27:48  SOHO      LASCO       CORONA\n",
        "2011-06-07 05:30:00  2011-06-07 05:30:01  STEREO_A  SECCHI      CORONA\n",
        "2011-06-07 05:30:09  2011-06-07 05:30:10  STEREO_A  SECCHI      CORONA\n",
        "2011-06-07 05:30:18  2011-06-07 05:30:19  STEREO_A  SECCHI      CORONA\n",
        "2011-06-07 05:30:25  2011-06-07 05:30:27  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 05:30:34  2011-06-07 05:30:36  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 05:30:43  2011-06-07 05:30:45  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 05:32:55  2011-06-07 05:32:57  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 05:33:04  2011-06-07 05:33:06  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 05:33:13  2011-06-07 05:33:15  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 05:35:00  2011-06-07 05:35:01  STEREO_A  SECCHI      CORONA\n",
        "2011-06-07 05:35:09  2011-06-07 05:35:10  STEREO_A  SECCHI      CORONA\n",
        "2011-06-07 05:35:18  2011-06-07 05:35:19  STEREO_A  SECCHI      CORONA\n",
        "2011-06-07 05:35:25  2011-06-07 05:35:27  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 05:35:34  2011-06-07 05:35:36  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 05:35:43  2011-06-07 05:35:45  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 05:37:56  2011-06-07 05:37:58  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 05:38:04  2011-06-07 05:38:06  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 05:38:13  2011-06-07 05:38:15  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 05:40:00  2011-06-07 05:40:01  STEREO_A  SECCHI      CORONA\n",
        "2011-06-07 05:40:09  2011-06-07 05:40:10  STEREO_A  SECCHI      CORONA\n",
        "2011-06-07 05:40:18  2011-06-07 05:40:19  STEREO_A  SECCHI      CORONA\n",
        "2011-06-07 05:40:25  2011-06-07 05:40:27  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 05:40:34  2011-06-07 05:40:36  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 05:40:43  2011-06-07 05:40:45  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 05:42:55  2011-06-07 05:42:57  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 05:43:04  2011-06-07 05:43:06  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 05:43:13  2011-06-07 05:43:15  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 05:45:00  2011-06-07 05:45:01  STEREO_A  SECCHI      CORONA\n",
        "2011-06-07 05:45:09  2011-06-07 05:45:10  STEREO_A  SECCHI      CORONA\n",
        "2011-06-07 05:45:18  2011-06-07 05:45:19  STEREO_A  SECCHI      CORONA\n",
        "2011-06-07 05:45:25  2011-06-07 05:45:27  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 05:45:34  2011-06-07 05:45:36  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 05:45:43  2011-06-07 05:45:45  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 05:47:55  2011-06-07 05:47:57  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 05:48:04  2011-06-07 05:48:06  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 05:48:13  2011-06-07 05:48:15  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 05:50:00  2011-06-07 05:50:01  STEREO_A  SECCHI      CORONA\n",
        "2011-06-07 05:50:09  2011-06-07 05:50:10  STEREO_A  SECCHI      CORONA\n",
        "2011-06-07 05:50:18  2011-06-07 05:50:19  STEREO_A  SECCHI      CORONA\n",
        "2011-06-07 05:50:25  2011-06-07 05:50:27  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 05:50:34  2011-06-07 05:50:36  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 05:50:43  2011-06-07 05:50:45  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 05:52:55  2011-06-07 05:52:57  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 05:53:04  2011-06-07 05:53:06  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 05:53:13  2011-06-07 05:53:15  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 05:55:00  2011-06-07 05:55:01  STEREO_A  SECCHI      CORONA\n",
        "2011-06-07 05:55:09  2011-06-07 05:55:10  STEREO_A  SECCHI      CORONA\n",
        "2011-06-07 05:55:18  2011-06-07 05:55:19  STEREO_A  SECCHI      CORONA\n",
        "2011-06-07 05:55:25  2011-06-07 05:55:27  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 05:55:34  2011-06-07 05:55:36  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 05:55:43  2011-06-07 05:55:45  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 05:57:55  2011-06-07 05:57:57  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 05:58:04  2011-06-07 05:58:06  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 05:58:13  2011-06-07 05:58:15  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 06:00:00  2011-06-07 06:00:01  STEREO_A  SECCHI      CORONA\n",
        "2011-06-07 06:00:09  2011-06-07 06:00:10  STEREO_A  SECCHI      CORONA\n",
        "2011-06-07 06:00:18  2011-06-07 06:00:19  STEREO_A  SECCHI      CORONA\n",
        "2011-06-07 06:00:25  2011-06-07 06:00:27  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 06:00:34  2011-06-07 06:00:36  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 06:00:43  2011-06-07 06:00:45  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 06:02:55  2011-06-07 06:02:57  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 06:03:04  2011-06-07 06:03:06  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 06:03:13  2011-06-07 06:03:15  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 06:05:00  2011-06-07 06:05:01  STEREO_A  SECCHI      CORONA\n",
        "2011-06-07 06:05:09  2011-06-07 06:05:10  STEREO_A  SECCHI      CORONA\n",
        "2011-06-07 06:05:18  2011-06-07 06:05:19  STEREO_A  SECCHI      CORONA\n",
        "2011-06-07 06:05:25  2011-06-07 06:05:27  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 06:05:34  2011-06-07 06:05:36  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 06:05:43  2011-06-07 06:05:45  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 06:07:55  2011-06-07 06:07:57  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 06:08:04  2011-06-07 06:08:06  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 06:08:13  2011-06-07 06:08:15  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 06:10:00  2011-06-07 06:10:01  STEREO_A  SECCHI      CORONA\n",
        "2011-06-07 06:10:09  2011-06-07 06:10:10  STEREO_A  SECCHI      CORONA\n",
        "2011-06-07 06:10:18  2011-06-07 06:10:19  STEREO_A  SECCHI      CORONA\n",
        "2011-06-07 06:10:25  2011-06-07 06:10:27  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 06:10:34  2011-06-07 06:10:36  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 06:10:43  2011-06-07 06:10:45  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 06:12:55  2011-06-07 06:12:57  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 06:13:04  2011-06-07 06:13:06  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 06:13:13  2011-06-07 06:13:15  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 06:15:00  2011-06-07 06:15:01  STEREO_A  SECCHI      CORONA\n",
        "2011-06-07 06:15:09  2011-06-07 06:15:10  STEREO_A  SECCHI      CORONA\n",
        "2011-06-07 06:15:18  2011-06-07 06:15:19  STEREO_A  SECCHI      CORONA\n",
        "2011-06-07 06:15:25  2011-06-07 06:15:27  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 06:15:34  2011-06-07 06:15:36  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 06:15:43  2011-06-07 06:15:45  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 06:17:55  2011-06-07 06:17:57  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 06:18:04  2011-06-07 06:18:06  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 06:18:13  2011-06-07 06:18:15  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 06:20:00  2011-06-07 06:20:01  STEREO_A  SECCHI      CORONA\n",
        "2011-06-07 06:20:09  2011-06-07 06:20:10  STEREO_A  SECCHI      CORONA\n",
        "2011-06-07 06:20:18  2011-06-07 06:20:19  STEREO_A  SECCHI      CORONA\n",
        "2011-06-07 06:20:25  2011-06-07 06:20:27  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 06:20:34  2011-06-07 06:20:36  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 06:20:43  2011-06-07 06:20:45  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 06:22:55  2011-06-07 06:22:57  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 06:23:04  2011-06-07 06:23:06  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 06:23:13  2011-06-07 06:23:15  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 06:25:00  2011-06-07 06:25:01  STEREO_A  SECCHI      CORONA\n",
        "2011-06-07 06:25:09  2011-06-07 06:25:10  STEREO_A  SECCHI      CORONA\n",
        "2011-06-07 06:25:18  2011-06-07 06:25:19  STEREO_A  SECCHI      CORONA\n",
        "2011-06-07 06:25:25  2011-06-07 06:25:27  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 06:25:34  2011-06-07 06:25:36  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 06:25:43  2011-06-07 06:25:45  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 06:27:55  2011-06-07 06:27:57  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 06:28:04  2011-06-07 06:28:06  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 06:28:13  2011-06-07 06:28:15  STEREO_B  SECCHI      CORONA\n",
        "2011-06-07 06:30:00  2011-06-07 06:30:01  STEREO_A  SECCHI      CORONA\n"
       ]
      }
     ],
     "prompt_number": 55
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "## Searching for events in the HEK"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from sunpy.net import hek\n",
      "client = hek.HEKClient()\n",
      "tstart, tend = '2011/08/09 00:00:00', '2011/08/10 00:00:00'\n",
      "result = client.query(hek.attrs.Time(tstart,tend), hek.attrs.EventType('FL')) # \u2019FL\u2019 indicates flare\n",
      "len(result)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 56,
       "text": [
        "52"
       ]
      }
     ],
     "prompt_number": 56
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "result"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 57,
       "text": [
        "[{u'SOL_standard': u'SOL2011-08-08T01:30:04L247C075',\n",
        "  u'active': u'true',\n",
        "  u'ar_compactnesscls': u'',\n",
        "  u'ar_mcintoshcls': u'',\n",
        "  u'ar_mtwilsoncls': u'',\n",
        "  u'ar_noaaclass': u'',\n",
        "  u'ar_noaanum': None,\n",
        "  u'ar_numspots': None,\n",
        "  u'ar_penumbracls': u'',\n",
        "  u'ar_polarity': None,\n",
        "  u'ar_zurichcls': u'',\n",
        "  u'area_atdiskcenter': None,\n",
        "  u'area_atdiskcenteruncert': None,\n",
        "  u'area_raw': None,\n",
        "  u'area_uncert': None,\n",
        "  u'area_unit': u'',\n",
        "  u'bound_ccnsteps': None,\n",
        "  u'bound_ccstartc1': None,\n",
        "  u'bound_ccstartc2': None,\n",
        "  u'bound_chaincode': u'',\n",
        "  u'boundbox_c1ll': -470,\n",
        "  u'boundbox_c1ur': 573,\n",
        "  u'boundbox_c2ll': -174,\n",
        "  u'boundbox_c2ur': 476,\n",
        "  u'chaincodetype': u'',\n",
        "  u'comment_count': u'0',\n",
        "  u'concept': u'Flare ',\n",
        "  u'event_c1error': 521.5,\n",
        "  u'event_c2error': 324.9,\n",
        "  u'event_clippedspatial': u'',\n",
        "  u'event_clippedtemporal': u'',\n",
        "  u'event_coord1': 51,\n",
        "  u'event_coord2': 151,\n",
        "  u'event_coord3': None,\n",
        "  u'event_coordsys': u'UTC-HPC-TOPO',\n",
        "  u'event_coordunit': u'arcsec',\n",
        "  u'event_description': u'Small flare in the lower pat of the AR. Few instants before, a coronal shock wave appears from the right part of the image.',\n",
        "  u'event_endtime': u'2011-08-10T00:00:04',\n",
        "  u'event_expires': u'',\n",
        "  u'event_importance': u'0.80000000000000004',\n",
        "  u'event_importance_num_ratings': u'1',\n",
        "  u'event_mapurl': u'',\n",
        "  u'event_maskurl': u'',\n",
        "  u'event_npixels': None,\n",
        "  u'event_peaktime': u'2011-08-09T11:55:00',\n",
        "  u'event_pixelunit': u'',\n",
        "  u'event_probability': None,\n",
        "  u'event_starttime': u'2011-08-08T01:30:04',\n",
        "  u'event_testflag': u'false',\n",
        "  u'event_title': u'Small flare in AR',\n",
        "  u'event_type': u'FL',\n",
        "  u'eventtype': u'9',\n",
        "  u'fl_efoldtime': None,\n",
        "  u'fl_efoldtimeunit': u'',\n",
        "  u'fl_fluence': None,\n",
        "  u'fl_fluenceunit': u'',\n",
        "  u'fl_goescls': u'',\n",
        "  u'fl_peakem': None,\n",
        "  u'fl_peakemunit': u'',\n",
        "  u'fl_peakflux': None,\n",
        "  u'fl_peakfluxunit': u'',\n",
        "  u'fl_peaktemp': None,\n",
        "  u'fl_peaktempunit': u'',\n",
        "  u'frm_contact': u'Scott Green',\n",
        "  u'frm_daterun': u'2011-08-11T17:26:01',\n",
        "  u'frm_humanflag': u'true',\n",
        "  u'frm_identifier': u'Annotator-build_20110621-avc',\n",
        "  u'frm_institute': u'LMSAL',\n",
        "  u'frm_name': u'asainz',\n",
        "  u'frm_paramset': u'n/a',\n",
        "  u'frm_specificid': u'',\n",
        "  u'frm_url': u'n/a',\n",
        "  u'frm_versionnumber': None,\n",
        "  u'gs_galleryid': u'pod_sainz+dalda_alberto_2011-08-11T17:26:07.457',\n",
        "  u'gs_imageurl': u'http://www.lmsal.com/hek/gallery/podimages/2011/08/11/pod_sainz%2Bdalda_alberto_2011-08-11T17%3A26%3A07.457/panorama_asainz_AIA-211_HMI-6173_20110808T222504_at_20110811T172017.jpg',\n",
        "  u'gs_movieurl': u'',\n",
        "  u'gs_thumburl': u'http://www.lmsal.com/hek/gallery/podimages/2011/08/11/pod_sainz%2Bdalda_alberto_2011-08-11T17%3A26%3A07.457/thumb/panorama_asainz_AIA-211_HMI-6173_20110808T222504_at_20110811T172017.jpg',\n",
        "  u'hcr_checked': u'true',\n",
        "  u'hgc_bbox': u'POLYGON((-146.807764 -5.167838,-79.64706 -5.630367,-69.862234 34.479115,-154.290862 35.148002,-146.807764 -5.167838))',\n",
        "  u'hgc_boundcc': u'',\n",
        "  u'hgc_coord': u'POINT(-113.8074292 15.364686)',\n",
        "  u'hgc_x': -113.8074292,\n",
        "  u'hgc_y': 15.364686,\n",
        "  u'hgs_bbox': u'POLYGON((-29.808574 -5.167838,37.35213 -5.630367,47.136956 34.479115,-37.291672 35.148002,-29.808574 -5.167838))',\n",
        "  u'hgs_boundcc': u'',\n",
        "  u'hgs_coord': u'POINT(3.1917608 15.364686)',\n",
        "  u'hgs_x': 3.1917608,\n",
        "  u'hgs_y': 15.364686,\n",
        "  u'hpc_bbox': u'POLYGON((-470 -174,573 -174,573 476,-470 476,-470 -174))',\n",
        "  u'hpc_boundcc': u'',\n",
        "  u'hpc_coord': u'POINT(51 151)',\n",
        "  u'hpc_x': 51,\n",
        "  u'hpc_y': 151,\n",
        "  u'hrc_a': 341.337688166087,\n",
        "  u'hrc_bbox': u'POLYGON((0.529988 110.315196,0.633264 253.108304,0.787746 309.716939,0.707395 44.636607,0.529988 110.315196))',\n",
        "  u'hrc_boundcc': u'',\n",
        "  u'hrc_coord': u'POINT(0.168543050299641 341.337688166087)',\n",
        "  u'hrc_r': 0.168543050299641,\n",
        "  u'intenskurt': None,\n",
        "  u'intensmax': None,\n",
        "  u'intensmean': None,\n",
        "  u'intensmedian': None,\n",
        "  u'intensmin': None,\n",
        "  u'intensskew': None,\n",
        "  u'intenstotal': None,\n",
        "  u'intensunit': u'',\n",
        "  u'intensvar': None,\n",
        "  u'kb_archivdate': u'2011-08-11T17:26:13',\n",
        "  u'kb_archivid': u'ivo://helio-informatics.org/FL211_AlbertoSainzDalda_20110811_172601',\n",
        "  u'kb_archivist': u'sainzdalda_alberto',\n",
        "  u'obs_channelid': u'211',\n",
        "  u'obs_dataprepurl': u'',\n",
        "  u'obs_firstprocessingdate': u'',\n",
        "  u'obs_includesnrt': u'',\n",
        "  u'obs_instrument': u'AIA',\n",
        "  u'obs_lastprocessingdate': u'',\n",
        "  u'obs_levelnum': None,\n",
        "  u'obs_meanwavel': 2.11e-06,\n",
        "  u'obs_observatory': u'SDO',\n",
        "  u'obs_title': u'',\n",
        "  u'obs_wavelunit': u'cm',\n",
        "  u'rasterscan': u'',\n",
        "  u'rasterscantype': u'',\n",
        "  u'refs': [{u'ref_name': u'FRM_URL',\n",
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        "  u'intensmedian': None,\n",
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        "    u'ref_url': u'http://www.cfa.harvard.edu'}],\n",
        "  u'refs_orig': u'',\n",
        "  u'revision': u'2',\n",
        "  u'skel_chaincode': u'',\n",
        "  u'skel_curvature': None,\n",
        "  u'skel_nsteps': None,\n",
        "  u'skel_startc1': None,\n",
        "  u'skel_startc2': None},\n",
        " {u'SOL_standard': u'SOL2011-08-09T23:38:25L296C073',\n",
        "  u'active': u'true',\n",
        "  u'ar_compactnesscls': u'',\n",
        "  u'ar_mcintoshcls': u'',\n",
        "  u'ar_mtwilsoncls': u'',\n",
        "  u'ar_noaaclass': u'',\n",
        "  u'ar_noaanum': None,\n",
        "  u'ar_numspots': None,\n",
        "  u'ar_penumbracls': u'',\n",
        "  u'ar_polarity': None,\n",
        "  u'ar_zurichcls': u'',\n",
        "  u'area_atdiskcenter': None,\n",
        "  u'area_atdiskcenteruncert': None,\n",
        "  u'area_raw': None,\n",
        "  u'area_uncert': None,\n",
        "  u'area_unit': u'',\n",
        "  u'bound_ccnsteps': None,\n",
        "  u'bound_ccstartc1': None,\n",
        "  u'bound_ccstartc2': None,\n",
        "  u'bound_chaincode': u'',\n",
        "  u'boundbox_c1ll': 844.8,\n",
        "  u'boundbox_c1ur': 921.6,\n",
        "  u'boundbox_c2ll': 230.4,\n",
        "  u'boundbox_c2ur': 307.2,\n",
        "  u'chaincodetype': u'',\n",
        "  u'comment_count': u'0',\n",
        "  u'concept': u'Flare ',\n",
        "  u'event_c1error': 2,\n",
        "  u'event_c2error': 2,\n",
        "  u'event_clippedspatial': u'',\n",
        "  u'event_clippedtemporal': u'',\n",
        "  u'event_coord1': 883.2,\n",
        "  u'event_coord2': 268.8,\n",
        "  u'event_coord3': None,\n",
        "  u'event_coordsys': u'UTC-HPC-TOPO',\n",
        "  u'event_coordunit': u'arcseconds',\n",
        "  u'event_description': u'',\n",
        "  u'event_endtime': u'2011-08-10T00:26:25',\n",
        "  u'event_expires': u'',\n",
        "  u'event_importance': u'',\n",
        "  u'event_importance_num_ratings': u'',\n",
        "  u'event_mapurl': u'',\n",
        "  u'event_maskurl': u'',\n",
        "  u'event_npixels': None,\n",
        "  u'event_peaktime': u'2011-08-09T23:39:25',\n",
        "  u'event_pixelunit': u'',\n",
        "  u'event_probability': None,\n",
        "  u'event_starttime': u'2011-08-09T23:38:25',\n",
        "  u'event_testflag': u'false',\n",
        "  u'event_title': u'',\n",
        "  u'event_type': u'FL',\n",
        "  u'eventtype': u'9',\n",
        "  u'fl_efoldtime': None,\n",
        "  u'fl_efoldtimeunit': u'',\n",
        "  u'fl_fluence': None,\n",
        "  u'fl_fluenceunit': u'',\n",
        "  u'fl_goescls': u'',\n",
        "  u'fl_peakem': None,\n",
        "  u'fl_peakemunit': u'',\n",
        "  u'fl_peakflux': 1286.45,\n",
        "  u'fl_peakfluxunit': u'erg/cm/cm/s',\n",
        "  u'fl_peaktemp': None,\n",
        "  u'fl_peaktempunit': u'',\n",
        "  u'frm_contact': u'Paolo C. Grigis - pgrigis@cfa.harvard.edu',\n",
        "  u'frm_daterun': u'2011-08-09T17:03:15',\n",
        "  u'frm_humanflag': u'false',\n",
        "  u'frm_identifier': u'Feature Finding Team',\n",
        "  u'frm_institute': u'SAO',\n",
        "  u'frm_name': u'Flare Detective - Trigger Module',\n",
        "  u'frm_paramset': u'DerivativeThreshold= 2.00000e+00 EndFraction= 2.50000e-01',\n",
        "  u'frm_specificid': u'',\n",
        "  u'frm_url': u'http://www.cfa.harvard.edu',\n",
        "  u'frm_versionnumber': 0.51,\n",
        "  u'gs_galleryid': u'',\n",
        "  u'gs_imageurl': u'http://sdowww.lmsal.com/sdomedia/ssw/media/ssw/ssw_client/data/ssw_service_110809_183329_98818/www/ssw_cutout_171_context_full.gif',\n",
        "  u'gs_movieurl': u'http://sdowww.lmsal.com/sdomedia/h264/2011/08/09/EDS_FlareDetective-TriggerModule_20110809T225025-20110810T011425_AIA_171_XCEN883.2YCEN268.8.mov',\n",
        "  u'gs_thumburl': u'http://sdowww.lmsal.com/sdomedia/ssw/media/ssw/ssw_client/data/ssw_service_110809_183329_98818/www/ssw_cutout_171_context_thumb.gif',\n",
        "  u'hcr_checked': u'true',\n",
        "  u'hgc_bbox': u'POLYGON((-74.120828 16.492294,-53.718762 13.979604,-54.239579 18.349724,-69.847264 20.925725,-74.120828 16.492294))',\n",
        "  u'hgc_boundcc': u'',\n",
        "  u'hgc_coord': u'POINT(-64.09589 17.868605)',\n",
        "  u'hgc_x': -64.09589,\n",
        "  u'hgc_y': 17.868605,\n",
        "  u'hgs_bbox': u'POLYGON((68.297082 16.492294,88.699148 13.979604,88.178331 18.349724,72.570646 20.925725,68.297082 16.492294))',\n",
        "  u'hgs_boundcc': u'',\n",
        "  u'hgs_coord': u'POINT(78.32202 17.868605)',\n",
        "  u'hgs_x': 78.32202,\n",
        "  u'hgs_y': 17.868605,\n",
        "  u'hpc_bbox': u'POLYGON((844.8 230.4,921.6 230.4,921.6 307.2,844.8 307.2,844.8 230.4))',\n",
        "  u'hpc_boundcc': u'',\n",
        "  u'hpc_coord': u'POINT(883.2 268.8)',\n",
        "  u'hpc_x': 883.2,\n",
        "  u'hpc_y': 268.8,\n",
        "  u'hrc_a': 286.927513064147,\n",
        "  u'hrc_bbox': u'POLYGON((0.925057 285.255119,1.003558 284.036243,1.026258 288.434949,0.949636 289.983107,0.925057 285.255119))',\n",
        "  u'hrc_boundcc': u'',\n",
        "  u'hrc_coord': u'POINT(0.975282925191807 286.927513064147)',\n",
        "  u'hrc_r': 0.975282925191807,\n",
        "  u'intenskurt': None,\n",
        "  u'intensmax': None,\n",
        "  u'intensmean': None,\n",
        "  u'intensmedian': None,\n",
        "  u'intensmin': None,\n",
        "  u'intensskew': None,\n",
        "  u'intenstotal': None,\n",
        "  u'intensunit': u'',\n",
        "  u'intensvar': None,\n",
        "  u'kb_archivdate': u'2011-08-10T00:44:34',\n",
        "  u'kb_archivid': u'ivo://helio-informatics.org/FL_FlareDetective-TriggerModule_20110810_000523_2011-08-09T23:38:25.350_1',\n",
        "  u'kb_archivist': u'flare_detective',\n",
        "  u'obs_channelid': u'171',\n",
        "  u'obs_dataprepurl': u'',\n",
        "  u'obs_firstprocessingdate': u'',\n",
        "  u'obs_includesnrt': u'',\n",
        "  u'obs_instrument': u'AIA',\n",
        "  u'obs_lastprocessingdate': u'',\n",
        "  u'obs_levelnum': None,\n",
        "  u'obs_meanwavel': 1.71e-06,\n",
        "  u'obs_observatory': u'SDO',\n",
        "  u'obs_title': u'',\n",
        "  u'obs_wavelunit': u'cm',\n",
        "  u'rasterscan': u'',\n",
        "  u'rasterscantype': u'',\n",
        "  u'refs': [{u'ref_name': u'SSW Context Thumbnail',\n",
        "    u'ref_type': u'thumbnail',\n",
        "    u'ref_url': u'http://sdowww.lmsal.com/sdomedia/ssw/media/ssw/ssw_client/data/ssw_service_110809_183329_98818/www/ssw_cutout_171_context_thumb.gif'},\n",
        "   {u'ref_name': u'SSW Context Image',\n",
        "    u'ref_type': u'image',\n",
        "    u'ref_url': u'http://sdowww.lmsal.com/sdomedia/ssw/media/ssw/ssw_client/data/ssw_service_110809_183329_98818/www/ssw_cutout_171_context_full.gif'},\n",
        "   {u'ref_name': u'SDO Movie',\n",
        "    u'ref_type': u'movie',\n",
        "    u'ref_url': u'http://sdowww.lmsal.com/sdomedia/h264/2011/08/09/EDS_FlareDetective-TriggerModule_20110809T225025-20110810T011425_AIA_171_XCEN883.2YCEN268.8.mov'},\n",
        "   {u'ref_name': u'FRM_URL',\n",
        "    u'ref_type': u'unknown',\n",
        "    u'ref_url': u'http://www.cfa.harvard.edu'}],\n",
        "  u'refs_orig': u'',\n",
        "  u'revision': u'2',\n",
        "  u'skel_chaincode': u'',\n",
        "  u'skel_curvature': None,\n",
        "  u'skel_nsteps': None,\n",
        "  u'skel_startc1': None,\n",
        "  u'skel_startc2': None}]"
       ]
      }
     ],
     "prompt_number": 57
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Filter the results of the previous result to return only those events that have the FRM \u2018SSW Latest Events\u2019"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "result = client.query(hek.attrs.Time(tstart, tend), hek.attrs.EventType('FL'), hek.attrs.FRM.Name=='SSW Latest Events')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 58
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "len(result)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 59,
       "text": [
        "9"
       ]
      }
     ],
     "prompt_number": 59
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "The following returns flares west of 50 arcseconds or those that have a peak flux above 1000.0 (the units of the flux are FRM- dependent and are described at the HEK website)"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "result = client.query(hek.attrs.Time(tstart, tend), hek.attrs.EventType('FL'), (hek.attrs.Event.Coord1>50) or (hek.attrs.FL.PeakFlux>1000.0))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 60
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "len(result)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 61,
       "text": [
        "48"
       ]
      }
     ],
     "prompt_number": 61
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "## Downloading the VSO files associated with events"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from sunpy.net import hek2vso"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 62
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "h2v = hek2vso.H2VClient()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 63
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "vso_results = h2v.translate_and_query(result[0])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 64
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "h2v.vso_client.get(vso_results[0]).wait()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "ename": "KeyboardInterrupt",
       "evalue": "",
       "output_type": "pyerr",
       "traceback": [
        "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
        "\u001b[0;32m<ipython-input-65-72e4e3caeaa5>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mh2v\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvso_client\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvso_results\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwait\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
        "\u001b[0;32m/Users/schriste/Dropbox/Developer/python/sunpy/sunpy/net/vso/vso.pyc\u001b[0m in \u001b[0;36mwait\u001b[0;34m(self, timeout, progress)\u001b[0m\n\u001b[1;32m    123\u001b[0m                 \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mprogress\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdraw\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    124\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 125\u001b[0;31m         \u001b[0;32mwhile\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mevt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwait\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtimeout\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    126\u001b[0m             \u001b[0;32mpass\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    127\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mprogress\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
        "\u001b[0;32m/Users/schriste/anaconda/python.app/Contents/lib/python2.7/threading.pyc\u001b[0m in \u001b[0;36mwait\u001b[0;34m(self, timeout)\u001b[0m\n\u001b[1;32m    618\u001b[0m         \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    619\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__flag\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 620\u001b[0;31m                 \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__cond\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwait\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtimeout\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    621\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__flag\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    622\u001b[0m         \u001b[0;32mfinally\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
        "\u001b[0;32m/Users/schriste/anaconda/python.app/Contents/lib/python2.7/threading.pyc\u001b[0m in \u001b[0;36mwait\u001b[0;34m(self, timeout)\u001b[0m\n\u001b[1;32m    356\u001b[0m                         \u001b[0;32mbreak\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    357\u001b[0m                     \u001b[0mdelay\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmin\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdelay\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0;36m2\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mremaining\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m.05\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 358\u001b[0;31m                     \u001b[0m_sleep\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdelay\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    359\u001b[0m                 \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mgotit\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    360\u001b[0m                     \u001b[0;32mif\u001b[0m \u001b[0m__debug__\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
        "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "ERROR: KeyboardInterrupt [threading]\n"
       ]
      }
     ],
     "prompt_number": 65
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "## WCS"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from sunpy import wcs"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 66
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "wcs.convert_hg_hpc(10, 53)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 67,
       "text": [
        "(100.49244115330731, 767.97438321917502)"
       ]
      }
     ],
     "prompt_number": 67
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Convert that position back to heliographic coordinates"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "wcs.convert_hpc_hg(100.49, 767.97)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 68,
       "text": [
        "(9.9996521808465175, 52.999563684874893)"
       ]
      }
     ],
     "prompt_number": 68
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Try to convert a position which is not on the Sun to HG"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "wcs.convert_hpc_hg(-1500, 0)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 69,
       "text": [
        "(nan, nan)"
       ]
      }
     ],
     "prompt_number": 69
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Convert sky coordinate to a position in HCC"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "wcs.convert_hpc_hcc(-300, 400, z=True)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 70,
       "text": [
        "(-216716967.63331246, 288956420.9477042, 594364636.2208252)"
       ]
      }
     ],
     "prompt_number": 70
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "## More References\n",
      "\n",
      "+ [Python for Data Analysis](http://shop.oreilly.com/product/0636920023784.do) by Wes McKinney is great\n",
      "+ [Lectures on scientific computing with Python](http://jrjohansson.github.io) Great lectures on scientific computing in Python"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "## Consider [contributing](http://sunpy.org/contribute/) to SunPy!\n",
      "\n",
      "+ Provide feedback on the [mailing list](https://groups.google.com/forum/#!forum/sunpy)\n",
      "+ Report [bugs](https://github.com/sunpy/sunpy/issues)\n",
      "+ Provide Code (see our [developer guide](http://sunpy.readthedocs.org/en/stable/dev.html))"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
}