{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-03-02T21:55:14.046685Z",
     "start_time": "2017-03-02T16:55:14.036280-05:00"
    },
    "code_folding": [],
    "collapsed": false,
    "slideshow": {
     "slide_type": "notes"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{u'controls': 'true',\n",
       " u'heigh': 768,\n",
       " u'hideAddressBar': True,\n",
       " u'scroll': 'true',\n",
       " u'slideNumber': False,\n",
       " u'theme': 'beige',\n",
       " u'transition': 'fade',\n",
       " u'transition-speed': 'default',\n",
       " u'width': 1024}"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Configure some notebook settings\n",
    "from traitlets.config.manager import BaseJSONConfigManager\n",
    "path='/Users/Esh/.jupyter/nbconfig'\n",
    "cm = BaseJSONConfigManager(config_dir=path)\n",
    "cm.update('livereveal', {\n",
    "    'theme': 'beige',\n",
    "    'transition': 'fade',\n",
    "    'transition-speed':'default',\n",
    "    'controls': 'true',\n",
    "    'scroll':'true',\n",
    "    'width': 1024,\n",
    "    'heigh': 768\n",
    "})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "<h1><center>Introduction To Jupyter Notebooks</center></h1>\n",
    "<h3><center><em>(and why you should love them!)</em></center></h3>\n",
    "<h2><center>Eshin Jolly</center></h2>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "<h1><center>Overview</center></h1>\n",
    "<a href=\"#/2\"><h3>I Wanna Be Interactive</h3></a>\n",
    "<a href=\"#/3\"><h3>Lab Notebooks of the Future</h3></a>\n",
    "<a href=\"#/4\"><h3>I'm Multilingual</h3></a>\n",
    "<a href=\"#/8\"><h3>Sharing is Caring</h3></a>\n",
    "<a href=\"#/9\"><h3>Pimp My Ride</h3></a>\n",
    "<a href=\"#/10\"><h3>Tips and Tricks</h3></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "<h1><center>I Wanna Be Interactive</center></h1>\n",
    "- Interactive data analysis through code \"cells\"\n",
    "- Inline plotting\n",
    "- Access to the file system\n",
    "- \"IDE\" for analysts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-03-02T22:06:09.026305Z",
     "start_time": "2017-03-02T17:06:09.022936-05:00"
    },
    "collapsed": false,
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10\n"
     ]
    }
   ],
   "source": [
    "#Put some code here!\n",
    "x = 10\n",
    "print x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-03-02T20:17:13.989285Z",
     "start_time": "2017-03-02T15:17:13.986653-05:00"
    },
    "collapsed": false,
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [],
   "source": [
    "#Put more code here!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "<h1><center>Notebooks of the Future</center></h1>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "## Not just for code\n",
    "- Markdown, HTML, LateX integration\n",
    "- Slide shows (like this one!)\n",
    "- Keep your notes alongside your analysis routines\n",
    "- Embed images, videos, anything (it's all just HTML + javascript)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "<h1><center>I'm Multilingual!</center></h1>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "## Not just for Python!  \n",
    "- Python (multiple versions together!)\n",
    "- R\n",
    "- Matlab\n",
    "- Javascript\n",
    "- Julia\n",
    "- [30+ others](https://github.com/jupyter/jupyter/wiki/Jupyter-kernels)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# R... the master troll of statistical languages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-03-02T20:45:54.935685Z",
     "start_time": "2017-03-02T15:45:54.416610-05:00"
    },
    "collapsed": true,
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [],
   "source": [
    "%load_ext rpy2.ipython"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-03-02T20:45:56.096037Z",
     "start_time": "2017-03-02T15:45:56.072807-05:00"
    },
    "collapsed": false,
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "This is an R cell!\n",
       "[1] 1 3 5 7 9\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%R\n",
    "cat(\"This is an R cell!\\n\")\n",
    "seq(1,10,2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Matlab... because you enjoy paying for licenses"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-03-02T20:46:04.628329Z",
     "start_time": "2017-03-02T15:45:58.208601-05:00"
    },
    "collapsed": false,
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [],
   "source": [
    "%load_ext pymatbridge"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-03-02T20:46:05.834603Z",
     "start_time": "2017-03-02T15:46:05.809240-05:00"
    },
    "collapsed": false,
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "This is a matlab cell\n",
       "ans =\n",
       "     1     2     3     1     2     3\n",
       "     1     2     3     1     2     3\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%matlab\n",
    "disp('This is a matlab cell')\n",
    "repmat([1 2 3],2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# But we can talk to each other"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-03-02T20:46:07.872444Z",
     "start_time": "2017-03-02T15:46:07.864187-05:00"
    },
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Look now I'm a numpy array!\n",
      "<type 'numpy.ndarray'>\n"
     ]
    }
   ],
   "source": [
    "x = %R seq(1,10,2)\n",
    "x *= 10\n",
    "print(\"Look now I'm a numpy array!\")\n",
    "print(type(x))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "<h1><center>Sharing is Caring</center></h1>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "## Save notebooks in other formats and put them online\n",
    "- Github automatically renders jupyter notebooks\n",
    "- [Online notebook viewer](http://nbviewer.jupyter.org/)\n",
    "- Output to PDF, HTML (including javascript)\n",
    "- [Jupyterhub](https://github.com/jupyterhub/jupyterhub) code with friends!\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "<h1><center>Pimp My Ride</center></h1>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "# You can customize your notebook experience with extensions\n",
    "- Table of Contents\n",
    "- Execution time\n",
    "- Scratch Space\n",
    "- Code/Section folding\n",
    "- Look and feel (CSS+Javascript)\n",
    "- [All through notebook extensions](https://github.com/ipython-contrib/jupyter_contrib_nbextensions)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "## But be careful of yak-shaving:\n",
    "### \"Falling down an endless series of sub-tasks that prevent you from actually getting anything done\"\n",
    "<img src=\"http://zeroplayer.com/images/stuff/doNotShave.png\" align='middle' width='600' height='400'>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "<h1><center>Tips and Tricks</center></h1>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "## Lots of extra features\n",
    "- Interactive debugger (%pdb)\n",
    "- Timing code (%timeit)\n",
    "- Memory usage (%memit)\n",
    "- Profiling (%prun)\n",
    "- Development (%file, %reload)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "source": [
    "## For more...\n",
    "- [Jake Vanderplas - Data Science Handbook](https://github.com/jakevdp/PythonDataScienceHandbook)\n",
    "- [Tal Yarkoni - Intro to Data Science w/ Python](https://github.com/tyarkoni/SSI2016)\n",
    "- [Yarik - Intro to Programming for Psych/Neuro](https://github.com/dartmouth-pbs/psyc161)\n",
    "- [Awesome notebooks](https://github.com/jupyter/jupyter/wiki/A-gallery-of-interesting-Jupyter-Notebooks)\n",
    "- [Neuroimaging in Python](https://github.com/datacarpentry/python-neuroimaging-lesson)\n",
    "\n"
   ]
  }
 ],
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  "hide_input": false,
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
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  "language_info": {
   "codemirror_mode": {
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   "file_extension": ".py",
   "mimetype": "text/x-python",
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   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.11"
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  "nav_menu": {},
  "toc": {
   "navigate_menu": true,
   "number_sections": false,
   "sideBar": false,
   "threshold": 6,
   "toc_cell": false,
   "toc_section_display": "none",
   "toc_window_display": true
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  "toc_position": {
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