examples/notebooks/Part 5 - Rich Display System.ipynb

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  "name": ""
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 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "IPython's Rich Display System"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "In Python, objects can declare their textual representation using the `__repr__` method.  IPython expands on this idea and allows objects to declare other, richer representations including:\n",
      "\n",
      "* HTML\n",
      "* JSON\n",
      "* PNG\n",
      "* JPEG\n",
      "* SVG\n",
      "* LaTeX\n",
      "\n",
      "A single object can declare some or all of these representations; all are handled by IPython's *display system*. This Notebook shows how you can use this display system to incorporate a broad range of content into your Notebooks."
     ]
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Basic display imports"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "The `display` function is a general purpose tool for displaying different representations of objects. Think of it as `print` for these rich representations."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from IPython.display import display"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 8
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "A few points:\n",
      "\n",
      "* Calling `display` on an object will send **all** possible representations to the Notebook.\n",
      "* These representations are stored in the Notebook document.\n",
      "* In general the Notebook will use the richest available representation.\n",
      "\n",
      "If you want to display a particular representation, there are specific functions for that:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from IPython.display import display_pretty, display_html, display_jpeg, display_png, display_json, display_latex, display_svg"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 11
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Images"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "To work with images (JPEG, PNG) use the `Image` class."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from IPython.display import Image"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 2
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "i = Image(filename='logo/logo.png')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 5
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Returning an `Image` object from an expression will automatically display it:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "i"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
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       "prompt_number": 6,
       "text": [
        "<IPython.core.display.Image at 0x107ea26d0>"
       ]
      }
     ],
     "prompt_number": 6
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Or you can pass it to `display`:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "display(i)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "display_data",
       "png": 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       "text": [
        "<IPython.core.display.Image at 0x107ea26d0>"
       ]
      }
     ],
     "prompt_number": 9
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "An image can also be displayed from raw data or a url"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "Image(url='http://python.org/images/python-logo.gif')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<img src=\"http://python.org/images/python-logo.gif\" />"
       ],
       "output_type": "pyout",
       "prompt_number": 2,
       "text": [
        "<IPython.core.display.Image at 0x1060e7410>"
       ]
      }
     ],
     "prompt_number": 2
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "SVG images are also supported out of the box (since modern browsers do a good job of rendering them):"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from IPython.display import SVG\n",
      "SVG(filename='python-logo.svg')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 3,
       "svg": [
        "<svg height=\"115.02pt\" id=\"svg2\" inkscape:version=\"0.43\" sodipodi:docbase=\"/home/sdeibel\" sodipodi:docname=\"logo-python-generic.svg\" sodipodi:version=\"0.32\" version=\"1.0\" width=\"388.84pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:cc=\"http://web.resource.org/cc/\" xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:inkscape=\"http://www.inkscape.org/namespaces/inkscape\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\" xmlns:sodipodi=\"http://inkscape.sourceforge.net/DTD/sodipodi-0.dtd\" xmlns:svg=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n",
        "  <metadata id=\"metadata2193\">\n",
        "    <rdf:RDF>\n",
        "      <cc:Work rdf:about=\"\">\n",
        "        <dc:format>image/svg+xml</dc:format>\n",
        "        <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n",
        "      </cc:Work>\n",
        "    </rdf:RDF>\n",
        "  </metadata>\n",
        "  <sodipodi:namedview bordercolor=\"#666666\" borderopacity=\"1.0\" id=\"base\" inkscape:current-layer=\"svg2\" inkscape:cx=\"243.02499\" inkscape:cy=\"71.887497\" inkscape:pageopacity=\"0.0\" inkscape:pageshadow=\"2\" inkscape:window-height=\"543\" inkscape:window-width=\"791\" inkscape:window-x=\"0\" inkscape:window-y=\"0\" inkscape:zoom=\"1.4340089\" pagecolor=\"#ffffff\"/>\n",
        "  <defs id=\"defs4\">\n",
        "    <linearGradient id=\"linearGradient2795\">\n",
        "      <stop id=\"stop2797\" offset=\"0\" style=\"stop-color:#b8b8b8;stop-opacity:0.49803922\"/>\n",
        "      <stop id=\"stop2799\" offset=\"1\" style=\"stop-color:#7f7f7f;stop-opacity:0\"/>\n",
        "    </linearGradient>\n",
        "    <linearGradient id=\"linearGradient2787\">\n",
        "      <stop id=\"stop2789\" offset=\"0\" style=\"stop-color:#7f7f7f;stop-opacity:0.5\"/>\n",
        "      <stop id=\"stop2791\" offset=\"1\" style=\"stop-color:#7f7f7f;stop-opacity:0\"/>\n",
        "    </linearGradient>\n",
        "    <linearGradient id=\"linearGradient3676\">\n",
        "      <stop id=\"stop3678\" offset=\"0\" style=\"stop-color:#b2b2b2;stop-opacity:0.5\"/>\n",
        "      <stop id=\"stop3680\" offset=\"1\" style=\"stop-color:#b3b3b3;stop-opacity:0\"/>\n",
        "    </linearGradient>\n",
        "    <linearGradient id=\"linearGradient3236\">\n",
        "      <stop id=\"stop3244\" offset=\"0\" style=\"stop-color:#f4f4f4;stop-opacity:1\"/>\n",
        "      <stop id=\"stop3240\" offset=\"1\" style=\"stop-color:#ffffff;stop-opacity:1\"/>\n",
        "    </linearGradient>\n",
        "    <linearGradient id=\"linearGradient4671\">\n",
        "      <stop id=\"stop4673\" offset=\"0\" style=\"stop-color:#ffd43b;stop-opacity:1\"/>\n",
        "      <stop id=\"stop4675\" offset=\"1\" style=\"stop-color:#ffe873;stop-opacity:1\"/>\n",
        "    </linearGradient>\n",
        "    <linearGradient id=\"linearGradient4689\">\n",
        "      <stop id=\"stop4691\" offset=\"0\" style=\"stop-color:#5a9fd4;stop-opacity:1\"/>\n",
        "      <stop id=\"stop4693\" offset=\"1\" style=\"stop-color:#306998;stop-opacity:1\"/>\n",
        "    </linearGradient>\n",
        "    <linearGradient gradientTransform=\"translate(100.2702,99.61116)\" gradientUnits=\"userSpaceOnUse\" id=\"linearGradient2987\" x1=\"224.23996\" x2=\"-65.308502\" xlink:href=\"#linearGradient4671\" y1=\"144.75717\" y2=\"144.75717\"/>\n",
        "    <linearGradient gradientTransform=\"translate(100.2702,99.61116)\" gradientUnits=\"userSpaceOnUse\" id=\"linearGradient2990\" x1=\"172.94208\" x2=\"26.670298\" xlink:href=\"#linearGradient4689\" y1=\"77.475983\" y2=\"76.313133\"/>\n",
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        "  </g>\n",
        "</svg>"
       ],
       "text": [
        "<IPython.core.display.SVG at 0x10fb998d0>"
       ]
      }
     ],
     "prompt_number": 3
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Links to local files"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "If we want to create a link to one of them, we can call use the `FileLink` object."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from IPython.display import FileLink, FileLinks\n",
      "FileLink('Part 1 - Running Code.ipynb')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<a href='files/Part 1 - Running Code.ipynb' target='_blank'>Part 1 - Running Code.ipynb</a><br>"
       ],
       "output_type": "pyout",
       "prompt_number": 2,
       "text": [
        "/home/bgranger/Documents/ipython/examples/notebooks/Part 1 - Running Code.ipynb"
       ]
      }
     ],
     "prompt_number": 2
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Alternatively, if we want to link to all of the files in a directory, we can use the `FileLinks` object, passing `'.'` to indicate that we want links generated for the current working directory. Note that if there were other directories under the current directory, `FileLinks` would work in a recursive manner creating links to files in all sub-directories as well."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "FileLinks('.')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "./<br>\n",
        "&nbsp;&nbsp;<a href='files/./Animations Using clear_output.ipynb' target='_blank'>Animations Using clear_output.ipynb</a><br>\n",
        "&nbsp;&nbsp;<a href='files/./Custom Display Logic.ipynb' target='_blank'>Custom Display Logic.ipynb</a><br>\n",
        "&nbsp;&nbsp;<a href='files/./SymPy Examples.ipynb' target='_blank'>SymPy Examples.ipynb</a><br>\n",
        "&nbsp;&nbsp;<a href='files/./Part 2 - Basic Output.ipynb' target='_blank'>Part 2 - Basic Output.ipynb</a><br>\n",
        "&nbsp;&nbsp;<a href='files/./Frontend-Kernel Model.ipynb' target='_blank'>Frontend-Kernel Model.ipynb</a><br>\n",
        "&nbsp;&nbsp;<a href='files/./Part 5 - Rich Display System.ipynb' target='_blank'>Part 5 - Rich Display System.ipynb</a><br>\n",
        "&nbsp;&nbsp;<a href='files/./animation.m4v' target='_blank'>animation.m4v</a><br>\n",
        "&nbsp;&nbsp;<a href='files/./Trapezoid Rule.ipynb' target='_blank'>Trapezoid Rule.ipynb</a><br>\n",
        "&nbsp;&nbsp;<a href='files/./Part 4 - Markdown Cells.ipynb' target='_blank'>Part 4 - Markdown Cells.ipynb</a><br>\n",
        "&nbsp;&nbsp;<a href='files/./R Magics.ipynb' target='_blank'>R Magics.ipynb</a><br>\n",
        "&nbsp;&nbsp;<a href='files/./Part 1 - Running Code.ipynb' target='_blank'>Part 1 - Running Code.ipynb</a><br>\n",
        "&nbsp;&nbsp;<a href='files/./Typesetting Math Using MathJax.ipynb' target='_blank'>Typesetting Math Using MathJax.ipynb</a><br>\n",
        "&nbsp;&nbsp;<a href='files/./Part 3 - Pylab and Matplotlib.ipynb' target='_blank'>Part 3 - Pylab and Matplotlib.ipynb</a><br>\n",
        "&nbsp;&nbsp;<a href='files/./Script Magics.ipynb' target='_blank'>Script Magics.ipynb</a><br>\n",
        "&nbsp;&nbsp;<a href='files/./Octave Magic.ipynb' target='_blank'>Octave Magic.ipynb</a><br>\n",
        "&nbsp;&nbsp;<a href='files/./Cell Magics.ipynb' target='_blank'>Cell Magics.ipynb</a><br>\n",
        "&nbsp;&nbsp;<a href='files/./python-logo.svg' target='_blank'>python-logo.svg</a><br>\n",
        "&nbsp;&nbsp;<a href='files/./Data Publication API.ipynb' target='_blank'>Data Publication API.ipynb</a><br>\n",
        "&nbsp;&nbsp;<a href='files/./Progress Bars.ipynb' target='_blank'>Progress Bars.ipynb</a><br>\n",
        "&nbsp;&nbsp;<a href='files/./Cython Magics.ipynb' target='_blank'>Cython Magics.ipynb</a><br>"
       ],
       "output_type": "pyout",
       "prompt_number": 3,
       "text": [
        "./\n",
        "  Animations Using clear_output.ipynb\n",
        "  Custom Display Logic.ipynb\n",
        "  SymPy Examples.ipynb\n",
        "  Part 2 - Basic Output.ipynb\n",
        "  Frontend-Kernel Model.ipynb\n",
        "  Part 5 - Rich Display System.ipynb\n",
        "  animation.m4v\n",
        "  Trapezoid Rule.ipynb\n",
        "  Part 4 - Markdown Cells.ipynb\n",
        "  R Magics.ipynb\n",
        "  Part 1 - Running Code.ipynb\n",
        "  Typesetting Math Using MathJax.ipynb\n",
        "  Part 3 - Pylab and Matplotlib.ipynb\n",
        "  Script Magics.ipynb\n",
        "  Octave Magic.ipynb\n",
        "  Cell Magics.ipynb\n",
        "  python-logo.svg\n",
        "  Data Publication API.ipynb\n",
        "  Progress Bars.ipynb\n",
        "  Cython Magics.ipynb"
       ]
      }
     ],
     "prompt_number": 3
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Embedded vs Non-embedded Images"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "By default, image data is embedded in the Notebook document so that the images can be viewed offline. However it is also possible to tell the `Image` class to only store a *link* to the image. Let's see how this works using a webcam at Berkeley."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from IPython.display import Image\n",
      "\n",
      "# by default Image data are embedded\n",
      "Embed      = Image(    'http://scienceview.berkeley.edu/view/images/newview.jpg')\n",
      "\n",
      "# if kwarg `url` is given, the embedding is assumed to be false\n",
      "SoftLinked = Image(url='http://scienceview.berkeley.edu/view/images/newview.jpg')\n",
      "\n",
      "# In each case, embed can be specified explicitly with the `embed` kwarg\n",
      "# ForceEmbed = Image(url='http://scienceview.berkeley.edu/view/images/newview.jpg', embed=True)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 4
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Here is the embedded version. Note that this image was pulled from the webcam when this code cell was originally run and stored in the Notebook. Unless we rerun this cell, this is not todays image."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "Embed"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
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+lASoKhSUc4oCA1M0AM+tDNAHPGaG6oAbsVCc1RQpNAmhAZoE0KLm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JsEjY4wSD5ZrN0s+s9D9PaXqHQ/Ul3rd9ds/i313vAgg+nw8Rs7qAQSuMHO0epxzknJKK/3Nc1D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\n3prgmYlQfpOQMHkmuDVMI//Z\n",
       "output_type": "pyout",
       "prompt_number": 5,
       "text": [
        "<IPython.core.display.Image at 0x10fb99b50>"
       ]
      }
     ],
     "prompt_number": 5
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Here is today's image from same webcam at Berkeley, (refreshed every minutes, if you reload the notebook), visible only with an active internet connection, that should be different from the previous one. Notebooks saved with this kind of image will be lighter and always reflect the current version of the source, but the image won't display offline."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "SoftLinked"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<img src=\"http://scienceview.berkeley.edu/view/images/newview.jpg\" />"
       ],
       "output_type": "pyout",
       "prompt_number": 6,
       "text": [
        "<IPython.core.display.Image at 0x10fb99b10>"
       ]
      }
     ],
     "prompt_number": 6
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Of course, if you re-run this Notebook, the two images will be the same again."
     ]
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Audio"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "IPython makes it easy to work with sounds interactively. The `Audio` display class allows you to create an audio control that is embedded in the Notebook. The interface is analogous to the interface of the `Image` display class. All audio formats supported by the browser can be used. Note that no single format is presently supported in all browsers."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from IPython.display import Audio\n",
      "Audio(url=\"http://www.nch.com.au/acm/8k16bitpcm.wav\")"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "\n",
        "                <audio controls=\"controls\" >\n",
        "                    <source src=\"http://www.nch.com.au/acm/8k16bitpcm.wav\" type=\"audio/x-wav\" />\n",
        "                    Your browser does not support the audio element.\n",
        "                </audio>\n",
        "              "
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 7,
       "text": [
        "<IPython.lib.display.Audio at 0x111346750>"
       ]
      }
     ],
     "prompt_number": 7
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "A Numpy array can be auralized automatically. The Audio class normalizes and encodes the data and embed the result in the Notebook.\n",
      "\n",
      "For instance, when two sine waves with almost the same frequency are superimposed a phenomena known as [beats](https://en.wikipedia.org/wiki/Beat_%28acoustics%29) occur. This can be auralised as follows"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import numpy as np\n",
      "max_time = 3\n",
      "f1 = 220.0\n",
      "f2 = 224.0\n",
      "rate = 8000.0\n",
      "L = 3\n",
      "times = np.linspace(0,L,rate*L)\n",
      "signal = np.sin(2*np.pi*f1*times) + np.sin(2*np.pi*f2*times)\n",
      "\n",
      "Audio(data=signal, rate=rate)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "\n",
        "                <audio controls=\"controls\" >\n",
        "                    <source 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\" type=\"audio/wav\" />\n",
        "                    Your browser does not support the audio element.\n",
        "                </audio>\n",
        "              "
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 8,
       "text": [
        "<IPython.lib.display.Audio at 0x111353e10>"
       ]
      }
     ],
     "prompt_number": 8
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Video"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "More exotic objects can also be displayed, as long as their representation supports the IPython display protocol.  For example, videos hosted externally on YouTube are easy to load (and writing a similar wrapper for other hosted content is trivial):"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from IPython.display import YouTubeVideo\n",
      "# a talk about IPython at Sage Days at U. Washington, Seattle.\n",
      "# Video credit: William Stein.\n",
      "YouTubeVideo('1j_HxD4iLn8')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "\n",
        "            <iframe\n",
        "                width=\"400\"\n",
        "                height=\"300\"\n",
        "                src=\"http://www.youtube.com/embed/1j_HxD4iLn8\"\n",
        "                frameborder=\"0\"\n",
        "                allowfullscreen\n",
        "            ></iframe>\n",
        "        "
       ],
       "output_type": "pyout",
       "prompt_number": 7,
       "text": [
        "<IPython.lib.display.YouTubeVideo at 0x10fba2190>"
       ]
      }
     ],
     "prompt_number": 7
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Using the nascent video capabilities of modern browsers, you may also be able to display local\n",
      "videos.  At the moment this doesn't work very well in all browsers, so it may or may not work for you;\n",
      "we will continue testing this and looking for ways to make it more robust.  \n",
      "\n",
      "The following cell loads a local file called  `animation.m4v`, encodes the raw video as base64 for http\n",
      "transport, and uses the HTML5 video tag to load it. On Chrome 15 it works correctly, displaying a control\n",
      "bar at the bottom with a play/pause button and a location slider."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from IPython.display import HTML\n",
      "from base64 import b64encode\n",
      "video = open(\"animation.m4v\", \"rb\").read()\n",
      "video_encoded = b64encode(video)\n",
      "video_tag = '<video controls alt=\"test\" src=\"data:video/x-m4v;base64,{0}\">'.format(video_encoded)\n",
      "HTML(data=video_tag)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<video controls alt=\"test\" src=\"data:video/x-m4v;base64,AAAAHGZ0eXBNNFYgAAACAGlzb21pc28yYXZjMQAAAAhmcmVlAAAqiW1kYXQAAAKMBgX//4jcRem9\n",
        "5tlIt5Ys2CDZI+7veDI2NCAtIGNvcmUgMTE4IC0gSC4yNjQvTVBFRy00IEFWQyBjb2RlYyAtIENv\n",
        "cHlsZWZ0IDIwMDMtMjAxMSAtIGh0dHA6Ly93d3cudmlkZW9sYW4ub3JnL3gyNjQuaHRtbCAtIG9w\n",
        "dGlvbnM6IGNhYmFjPTEgcmVmPTMgZGVibG9jaz0xOjA6MCBhbmFseXNlPTB4MzoweDExMyBtZT1o\n",
        "ZXggc3VibWU9NyBwc3k9MSBwc3lfcmQ9MS4wMDowLjAwIG1peGVkX3JlZj0xIG1lX3JhbmdlPTE2\n",
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        "\">"
       ],
       "output_type": "pyout",
       "prompt_number": 8,
       "text": [
        "<IPython.core.display.HTML at 0x10fba28d0>"
       ]
      }
     ],
     "prompt_number": 8
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "HTML"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Python objects can declare HTML representations that will be displayed in the Notebook. If you have some HTML you want to display, simply use the `HTML` class."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from IPython.display import HTML"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 3
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "s = \"\"\"<table>\n",
      "<tr>\n",
      "<th>Header 1</th>\n",
      "<th>Header 2</th>\n",
      "</tr>\n",
      "<tr>\n",
      "<td>row 1, cell 1</td>\n",
      "<td>row 1, cell 2</td>\n",
      "</tr>\n",
      "<tr>\n",
      "<td>row 2, cell 1</td>\n",
      "<td>row 2, cell 2</td>\n",
      "</tr>\n",
      "</table>\"\"\""
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 4
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "h = HTML(s); h"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<table>\n",
        "<tr>\n",
        "<th>Header 1</th>\n",
        "<th>Header 2</th>\n",
        "</tr>\n",
        "<tr>\n",
        "<td>row 1, cell 1</td>\n",
        "<td>row 1, cell 2</td>\n",
        "</tr>\n",
        "<tr>\n",
        "<td>row 2, cell 1</td>\n",
        "<td>row 2, cell 2</td>\n",
        "</tr>\n",
        "</table>"
       ],
       "output_type": "pyout",
       "prompt_number": 5,
       "text": [
        "<IPython.core.display.HTML at 0x1087a0c10>"
       ]
      }
     ],
     "prompt_number": 5
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Pandas makes use of this capability to allow `DataFrames` to be represented as HTML tables."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import pandas"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 6
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "By default, `DataFrames` will be represented as text; to enable HTML representations we need to set a print option:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "pandas.core.format.set_printoptions(notebook_repr_html=True)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 9
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Here is a small amount of stock data for APPL:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%%file data.csv\n",
      "Date,Open,High,Low,Close,Volume,Adj Close\n",
      "2012-06-01,569.16,590.00,548.50,584.00,14077000,581.50\n",
      "2012-05-01,584.90,596.76,522.18,577.73,18827900,575.26\n",
      "2012-04-02,601.83,644.00,555.00,583.98,28759100,581.48\n",
      "2012-03-01,548.17,621.45,516.22,599.55,26486000,596.99\n",
      "2012-02-01,458.41,547.61,453.98,542.44,22001000,540.12\n",
      "2012-01-03,409.40,458.24,409.00,456.48,12949100,454.53"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Writing data.csv\n"
       ]
      }
     ],
     "prompt_number": 11
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Read this as into a `DataFrame`:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df = pandas.read_csv('data.csv')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 12
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "And view the HTML representation:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\">\n",
        "  <thead>\n",
        "    <tr>\n",
        "      <th></th>\n",
        "      <th>Date</th>\n",
        "      <th>Open</th>\n",
        "      <th>High</th>\n",
        "      <th>Low</th>\n",
        "      <th>Close</th>\n",
        "      <th>Volume</th>\n",
        "      <th>Adj Close</th>\n",
        "    </tr>\n",
        "    </thead>\n",
        "    <tbody>\n",
        "    <tr>\n",
        "      <td><strong>0</strong></td>\n",
        "      <td> 2012-06-01</td>\n",
        "      <td> 569.16</td>\n",
        "      <td> 590.00</td>\n",
        "      <td> 548.50</td>\n",
        "      <td> 584.00</td>\n",
        "      <td> 14077000</td>\n",
        "      <td> 581.50</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <td><strong>1</strong></td>\n",
        "      <td> 2012-05-01</td>\n",
        "      <td> 584.90</td>\n",
        "      <td> 596.76</td>\n",
        "      <td> 522.18</td>\n",
        "      <td> 577.73</td>\n",
        "      <td> 18827900</td>\n",
        "      <td> 575.26</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <td><strong>2</strong></td>\n",
        "      <td> 2012-04-02</td>\n",
        "      <td> 601.83</td>\n",
        "      <td> 644.00</td>\n",
        "      <td> 555.00</td>\n",
        "      <td> 583.98</td>\n",
        "      <td> 28759100</td>\n",
        "      <td> 581.48</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <td><strong>3</strong></td>\n",
        "      <td> 2012-03-01</td>\n",
        "      <td> 548.17</td>\n",
        "      <td> 621.45</td>\n",
        "      <td> 516.22</td>\n",
        "      <td> 599.55</td>\n",
        "      <td> 26486000</td>\n",
        "      <td> 596.99</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <td><strong>4</strong></td>\n",
        "      <td> 2012-02-01</td>\n",
        "      <td> 458.41</td>\n",
        "      <td> 547.61</td>\n",
        "      <td> 453.98</td>\n",
        "      <td> 542.44</td>\n",
        "      <td> 22001000</td>\n",
        "      <td> 540.12</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <td><strong>5</strong></td>\n",
        "      <td> 2012-01-03</td>\n",
        "      <td> 409.40</td>\n",
        "      <td> 458.24</td>\n",
        "      <td> 409.00</td>\n",
        "      <td> 456.48</td>\n",
        "      <td> 12949100</td>\n",
        "      <td> 454.53</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "output_type": "pyout",
       "prompt_number": 14,
       "text": [
        "         Date    Open    High     Low   Close    Volume  Adj Close\n",
        "0  2012-06-01  569.16  590.00  548.50  584.00  14077000     581.50\n",
        "1  2012-05-01  584.90  596.76  522.18  577.73  18827900     575.26\n",
        "2  2012-04-02  601.83  644.00  555.00  583.98  28759100     581.48\n",
        "3  2012-03-01  548.17  621.45  516.22  599.55  26486000     596.99\n",
        "4  2012-02-01  458.41  547.61  453.98  542.44  22001000     540.12\n",
        "5  2012-01-03  409.40  458.24  409.00  456.48  12949100     454.53"
       ]
      }
     ],
     "prompt_number": 14
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "External sites"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "You can even embed an entire page from another site in an iframe; for example this is today's Wikipedia\n",
      "page for mobile users:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from IPython.display import HTML\n",
      "HTML('<iframe src=http://en.mobile.wikipedia.org/?useformat=mobile width=700 height=350></iframe>')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<iframe src=http://en.mobile.wikipedia.org/?useformat=mobile width=700 height=350></iframe>"
       ],
       "output_type": "pyout",
       "prompt_number": 9,
       "text": [
        "<IPython.core.display.HTML at 0x1094900d0>"
       ]
      }
     ],
     "prompt_number": 9
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "LaTeX"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "And we also support the display of mathematical expressions typeset in LaTeX, which is rendered\n",
      "in the browser thanks to the [MathJax library](http://mathjax.org)."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from IPython.display import Math\n",
      "Math(r'F(k) = \\int_{-\\infty}^{\\infty} f(x) e^{2\\pi i k} dx')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "latex": [
        "$$F(k) = \\int_{-\\infty}^{\\infty} f(x) e^{2\\pi i k} dx$$"
       ],
       "output_type": "pyout",
       "prompt_number": 10,
       "text": [
        "<IPython.core.display.Math at 0x10fba26d0>"
       ]
      }
     ],
     "prompt_number": 10
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "With the `Latex` class, you have to include the delimiters yourself.  This allows you to use other LaTeX modes such as `eqnarray`:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from IPython.display import Latex\n",
      "Latex(r\"\"\"\\begin{eqnarray}\n",
      "\\nabla \\times \\vec{\\mathbf{B}} -\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{E}}}{\\partial t} & = \\frac{4\\pi}{c}\\vec{\\mathbf{j}} \\\\\n",
      "\\nabla \\cdot \\vec{\\mathbf{E}} & = 4 \\pi \\rho \\\\\n",
      "\\nabla \\times \\vec{\\mathbf{E}}\\, +\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{B}}}{\\partial t} & = \\vec{\\mathbf{0}} \\\\\n",
      "\\nabla \\cdot \\vec{\\mathbf{B}} & = 0 \n",
      "\\end{eqnarray}\"\"\")"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "latex": [
        "\\begin{eqnarray}\n",
        "\\nabla \\times \\vec{\\mathbf{B}} -\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{E}}}{\\partial t} & = \\frac{4\\pi}{c}\\vec{\\mathbf{j}} \\\\\n",
        "\\nabla \\cdot \\vec{\\mathbf{E}} & = 4 \\pi \\rho \\\\\n",
        "\\nabla \\times \\vec{\\mathbf{E}}\\, +\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{B}}}{\\partial t} & = \\vec{\\mathbf{0}} \\\\\n",
        "\\nabla \\cdot \\vec{\\mathbf{B}} & = 0 \n",
        "\\end{eqnarray}"
       ],
       "output_type": "pyout",
       "prompt_number": 11,
       "text": [
        "<IPython.core.display.Latex at 0x10fba2c10>"
       ]
      }
     ],
     "prompt_number": 11
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Or you can enter latex directly with the `%%latex` cell magic:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%%latex\n",
      "\\begin{aligned}\n",
      "\\nabla \\times \\vec{\\mathbf{B}} -\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{E}}}{\\partial t} & = \\frac{4\\pi}{c}\\vec{\\mathbf{j}} \\\\\n",
      "\\nabla \\cdot \\vec{\\mathbf{E}} & = 4 \\pi \\rho \\\\\n",
      "\\nabla \\times \\vec{\\mathbf{E}}\\, +\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{B}}}{\\partial t} & = \\vec{\\mathbf{0}} \\\\\n",
      "\\nabla \\cdot \\vec{\\mathbf{B}} & = 0\n",
      "\\end{aligned}"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "latex": [
        "\\begin{aligned}\n",
        "\\nabla \\times \\vec{\\mathbf{B}} -\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{E}}}{\\partial t} & = \\frac{4\\pi}{c}\\vec{\\mathbf{j}} \\\\\n",
        "\\nabla \\cdot \\vec{\\mathbf{E}} & = 4 \\pi \\rho \\\\\n",
        "\\nabla \\times \\vec{\\mathbf{E}}\\, +\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{B}}}{\\partial t} & = \\vec{\\mathbf{0}} \\\\\n",
        "\\nabla \\cdot \\vec{\\mathbf{B}} & = 0\n",
        "\\end{aligned}"
       ],
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.Latex at 0x10a617c90>"
       ]
      }
     ],
     "prompt_number": 12
    }
   ],
   "metadata": {}
  }
 ]
}