Jupyter Magics Tutorial

[2017-05-29] Jupyter Magics Tutorial.ipynb

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      "cell_type": "markdown",
      "source": "# What are magics?\n\nMagics are a way to talk to the Jupyter notebook itself and lets to interface with elements outside the kernel."
    },
    {
      "metadata": {
        "heading_collapsed": true
      },
      "cell_type": "markdown",
      "source": "# Some Must-Know Examples\n\nlisting magics, bash, timing, latex and HTML"
    },
    {
      "metadata": {
        "heading_collapsed": true,
        "hidden": true
      },
      "cell_type": "markdown",
      "source": "## `lsmagic`\n\nTells you what magics you have available"
    },
    {
      "metadata": {
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      },
      "cell_type": "code",
      "source": "% lsmagic",
      "execution_count": null,
      "outputs": []
    },
    {
      "metadata": {
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      },
      "cell_type": "markdown",
      "source": "## `!`\n\nLets you run shell commands, e.g. get the version of Pandas"
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    {
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      "cell_type": "code",
      "source": "! pip freeze | grep pandas",
      "execution_count": null,
      "outputs": []
    },
    {
      "metadata": {
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        "hidden": true
      },
      "cell_type": "markdown",
      "source": "## `%time`\n\nWill time whatever you evaluate"
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      },
      "cell_type": "code",
      "source": "%time\n\nfor i in range(0, 1000000000):\n    continue",
      "execution_count": null,
      "outputs": []
    },
    {
      "metadata": {
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      "cell_type": "markdown",
      "source": "## `%%bash`\n\nLets you run bash in a subprocess"
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      "cell_type": "code",
      "source": "%%bash\nfor i in a b c;\ndo\necho $i\ndone",
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      "outputs": []
    },
    {
      "metadata": {
        "heading_collapsed": true,
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      "cell_type": "markdown",
      "source": "## `%%latex`\n\nLets you render LaTeX inline"
    },
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        "trusted": true,
        "collapsed": false
      },
      "cell_type": "code",
      "source": "%%latex\n\\begin{align}\na = \\frac{a}{b} && b = \\frac{1}{3} && c = \\frac{1}{4} \\\\\na && b && c \\\\\n1 && 2 && 3 \\\\\n\\end{align}",
      "execution_count": null,
      "outputs": []
    },
    {
      "metadata": {
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      },
      "cell_type": "markdown",
      "source": "## `%%HTML`\n\nLets you render inline HTML, including iFrames"
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        "hidden": true,
        "trusted": true,
        "collapsed": false
      },
      "cell_type": "code",
      "source": "%%HTML\n<img src=\"https://media.giphy.com/media/l1KtYs7ZpeBskCQus/giphy.gif\" />",
      "execution_count": null,
      "outputs": []
    },
    {
      "metadata": {
        "heading_collapsed": true
      },
      "cell_type": "markdown",
      "source": "# Loading External Magics\n\nWith a quick example of R"
    },
    {
      "metadata": {
        "hidden": true,
        "trusted": true,
        "collapsed": false
      },
      "cell_type": "code",
      "source": "%load_ext rmagic",
      "execution_count": null,
      "outputs": []
    },
    {
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        "hidden": true,
        "trusted": true,
        "collapsed": false
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      "cell_type": "code",
      "source": "%%R\nX <- runif(10)\nY <- runif(10)",
      "execution_count": null,
      "outputs": []
    },
    {
      "metadata": {
        "hidden": true,
        "trusted": true,
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      "cell_type": "code",
      "source": "%R plot(X, Y)",
      "execution_count": null,
      "outputs": []
    },
    {
      "metadata": {
        "heading_collapsed": true
      },
      "cell_type": "markdown",
      "source": "# Combining Magics\n\nWith a couple quick examples"
    },
    {
      "metadata": {
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        "hidden": true
      },
      "cell_type": "markdown",
      "source": "## A Simple Example with Bash & Python"
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      },
      "cell_type": "code",
      "source": "!wget -O - 'http://www.sfgate.com' > sfgate.html",
      "execution_count": null,
      "outputs": []
    },
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        "hidden": true,
        "trusted": true,
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      },
      "cell_type": "code",
      "source": "%matplotlib inline \n\nimport matplotlib.pyplot as plt\nfrom wordcloud import WordCloud, STOPWORDS\nimport nltk\n\ndata = open(\"sfgate.html\",'r').read()\ntext = nltk.clean_html(data)\ncleaned = nltk.word_tokenize(text.lower())\nwordlist = [x for x in cleaned if (len(x)>=2 and x.isalpha())]\nwordcloud = WordCloud(stopwords=STOPWORDS, background_color='white').generate(\" \".join(wordlist))\nplt.figure(figsize=(15,10))\nplt.imshow(wordcloud)\nplt.axis('off')\nplt.show()",
      "execution_count": null,
      "outputs": []
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    {
      "metadata": {
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        "trusted": true,
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      "cell_type": "code",
      "source": "!rm 'sfgate.html'",
      "execution_count": null,
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    {
      "metadata": {
        "heading_collapsed": true,
        "hidden": true
      },
      "cell_type": "markdown",
      "source": "## Mixing Languages"
    },
    {
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        "hidden": true,
        "trusted": true,
        "collapsed": false
      },
      "cell_type": "code",
      "source": "import numpy as np\nX = np.array([4.5, 6.3, 9.1])\nX.mean()",
      "execution_count": null,
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    },
    {
      "metadata": {
        "hidden": true,
        "trusted": true,
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      },
      "cell_type": "code",
      "source": "%Rpush X\n%R mean(X)",
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