sample_R.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div style=\"display:block\">\n",
    "    <div style=\"width: 20%; display: inline-block; text-align: left;\">\n",
    "        <img src=\"\" style=\"height:75px; margin-left:0px\" />\n",
    "    </div>\n",
    "    <div style=\"width: 59%; display: inline-block\">\n",
    "        <h1  style=\"text-align: center\">Test</h1>\n",
    "        <div style=\"width: 100%; text-align: center; display: inline-block;\"><i>Author:</i> <strong>Test</strong> </div>\n",
    "    </div>\n",
    "    <div style=\"width: 20%; text-align: right; display: inline-block;\">\n",
    "        <div style=\"width: 100%; text-align: left; display: inline-block;\">\n",
    "            <i>Created: </i>\n",
    "            <time datetime=\"2016-08-16\" pubdate>August, 2016</time>\n",
    "        </div>\n",
    "    </div>\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Introduction\n",
    "\n",
    "This is an R Markdown document. Markdown is a simple formatting syntax for authoring HTML, PDF, and MS Word documents. For more details on using R Markdown see <http://rmarkdown.rstudio.com>.\n",
    "\n",
    "When you click the **Knit** button a document will be generated that includes both content as well as the output of any embedded R code chunks within the document. You can embed an R code chunk like this:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Section 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "     speed           dist       \n",
       " Min.   : 4.0   Min.   :  2.00  \n",
       " 1st Qu.:12.0   1st Qu.: 26.00  \n",
       " Median :15.0   Median : 36.00  \n",
       " Mean   :15.4   Mean   : 42.98  \n",
       " 3rd Qu.:19.0   3rd Qu.: 56.00  \n",
       " Max.   :25.0   Max.   :120.00  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "summary(cars)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can also embed plots, for example:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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tXXUw/eR0IksePIBs+6hbuM1yAkuAyn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\nBBASIICQAAGEBAj4f9uZIWKaakvdAAAAAElFTkSuQmCC",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot(cars)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note that the `echo = FALSE` parameter was added to the code chunk to prevent printing of the R code that generated the plot."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "R",
   "language": "R",
   "name": "ir"
  },
  "language_info": {
   "codemirror_mode": "r",
   "file_extension": ".r",
   "mimetype": "text/x-r-source",
   "name": "R",
   "pygments_lexer": "r",
   "version": "3.2.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}