Untitled1.ipynb

{
 "cells": [
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "#Referencing Variables in Markdown"
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "Import the extension in Javascript"
  },
  {
   "metadata": {
    "collapsed": false,
    "trusted": true
   },
   "cell_type": "code",
   "source": "import IPython\nIPython.html.nbextensions.install_nbextension('https://raw.githubusercontent.com/ipython-contrib/IPython-notebook-extensions/3.x/usability/python-markdown/main.js')",
   "execution_count": 31,
   "outputs": [
    {
     "output_type": "stream",
     "text": "downloading https://raw.githubusercontent.com/ipython-contrib/IPython-notebook-extensions/3.x/usability/python-markdown/main.js to /tmp/tmpvxpksb6c/main.js\ncopying /tmp/tmpvxpksb6c/main.js -> /usr/local/share/jupyter/nbextensions/main.js\n",
     "name": "stdout"
    }
   ]
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "Load it into the Javascript"
  },
  {
   "metadata": {
    "collapsed": false,
    "trusted": true
   },
   "cell_type": "code",
   "source": "%%javascript\nIPython.load_extensions('main')",
   "execution_count": 32,
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "application/javascript": "IPython.load_extensions('main')",
      "text/plain": "<IPython.core.display.Javascript object>"
     },
     "metadata": {}
    }
   ]
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "Create a variable and reference as \\{ \\{ test \\} \\} (No spaces!)"
  },
  {
   "metadata": {
    "collapsed": true,
    "trusted": true
   },
   "cell_type": "code",
   "source": "a = 214 + 123424 + 1234234",
   "execution_count": 33,
   "outputs": []
  },
  {
   "metadata": {
    "variables": {
     "a": "1357872"
    }
   },
   "cell_type": "markdown",
   "source": "THere are {{a}} in the Boston region who are this and that and so on. "
  },
  {
   "metadata": {
    "collapsed": false,
    "trusted": true
   },
   "cell_type": "code",
   "source": "import pandas as pd\n\ndata = (12304 + 12345)/23\ndata",
   "execution_count": 34,
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": "1071.695652173913"
     },
     "metadata": {},
     "execution_count": 34
    }
   ]
  },
  {
   "metadata": {
    "variables": {
     "data": "1071.695652173913"
    }
   },
   "cell_type": "markdown",
   "source": "I'm explaining that the amount of people in this area amount to {{data}} amount of etc."
  },
  {
   "metadata": {
    "trusted": true,
    "collapsed": true
   },
   "cell_type": "code",
   "source": "my_analysis = 34 * 14 +13 / 24;\n",
   "execution_count": 35,
   "outputs": []
  },
  {
   "metadata": {
    "variables": {
     "my_analysis": "476.5416666666667"
    }
   },
   "cell_type": "markdown",
   "source": "I found that my reuslt is {{my_analysis}}"
  },
  {
   "metadata": {
    "trusted": true,
    "collapsed": false
   },
   "cell_type": "code",
   "source": "%%javascript\nIPython.load_extensions(\"gist\")",
   "execution_count": 30,
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "application/javascript": "IPython.load_extensions(\"gist\")",
      "text/plain": "<IPython.core.display.Javascript object>"
     },
     "metadata": {}
    }
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "name": "python3",
   "display_name": "Python 3",
   "language": "python"
  },
  "language_info": {
   "mimetype": "text/x-python",
   "pygments_lexer": "ipython3",
   "name": "python",
   "nbconvert_exporter": "python",
   "version": "3.4.2",
   "codemirror_mode": {
    "version": 3,
    "name": "ipython"
   },
   "file_extension": ".py"
  },
  "gist_id": "f279cc8d7ad2d52e9a35"
 },
 "nbformat": 4,
 "nbformat_minor": 0
}