{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "# Welcome to rnotebook.io!\n",
    "\n",
    "If you've never used a Notebook environment before, read on!\n",
    "\n",
    "Otherwise, here's some stuff you might want to know:\n",
    "\n",
    "* This environment is preloaded with R and over three thousand R packages.\n",
    "* You can return and edit it any time, forever.\n",
    "* This is a BETA service. We're rapidly improving it.\n",
    "\n",
    "Right now, you're using [rnotebook.io](https://rnotebook.io) without logging in. As a result, there are some restrictions on what you can do:\n",
    "\n",
    "* RAM consumption and disk space are limited.\n",
    "* There's no network access.\n",
    "\n",
    "We will start lifting these restrictions in the free and paid accounts shortly.\n",
    "\n",
    "**Please send feedback (bugs, problems, suggestions) to [ian@mutexlabs.com](mailto:ian@mutexlabs.com)**.\n",
    "\n",
    "Enjoy!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "# Getting started\n",
    "\n",
    "Notebooks let you mix code, documentation and graphics. The following cell contains the traditional 'Hello, world!' greeting. Click it, then execute it by pressing Shift-Enter."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1] \"Hello, world!\"\n"
     ]
    }
   ],
   "source": [
    "print(\"Hello, world!\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "We're working in R, so you might want to play with one of the built-in datasets. Let's check out `mtcars`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th></th><th scope=col>mpg</th><th scope=col>cyl</th><th scope=col>disp</th><th scope=col>hp</th><th scope=col>drat</th><th scope=col>wt</th><th scope=col>qsec</th><th scope=col>vs</th><th scope=col>am</th><th scope=col>gear</th><th scope=col>carb</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>Mazda RX4</th><td>21.0 </td><td>6    </td><td>160.0</td><td>110  </td><td>3.90 </td><td>2.620</td><td>16.46</td><td>0    </td><td>1    </td><td>4    </td><td>4    </td></tr>\n",
       "\t<tr><th scope=row>Mazda RX4 Wag</th><td>21.0 </td><td>6    </td><td>160.0</td><td>110  </td><td>3.90 </td><td>2.875</td><td>17.02</td><td>0    </td><td>1    </td><td>4    </td><td>4    </td></tr>\n",
       "\t<tr><th scope=row>Datsun 710</th><td>22.8 </td><td>4    </td><td>108.0</td><td> 93  </td><td>3.85 </td><td>2.320</td><td>18.61</td><td>1    </td><td>1    </td><td>4    </td><td>1    </td></tr>\n",
       "\t<tr><th scope=row>Hornet 4 Drive</th><td>21.4 </td><td>6    </td><td>258.0</td><td>110  </td><td>3.08 </td><td>3.215</td><td>19.44</td><td>1    </td><td>0    </td><td>3    </td><td>1    </td></tr>\n",
       "\t<tr><th scope=row>Hornet Sportabout</th><td>18.7 </td><td>8    </td><td>360.0</td><td>175  </td><td>3.15 </td><td>3.440</td><td>17.02</td><td>0    </td><td>0    </td><td>3    </td><td>2    </td></tr>\n",
       "\t<tr><th scope=row>Valiant</th><td>18.1 </td><td>6    </td><td>225.0</td><td>105  </td><td>2.76 </td><td>3.460</td><td>20.22</td><td>1    </td><td>0    </td><td>3    </td><td>1    </td></tr>\n",
       "\t<tr><th scope=row>Duster 360</th><td>14.3 </td><td>8    </td><td>360.0</td><td>245  </td><td>3.21 </td><td>3.570</td><td>15.84</td><td>0    </td><td>0    </td><td>3    </td><td>4    </td></tr>\n",
       "\t<tr><th scope=row>Merc 240D</th><td>24.4 </td><td>4    </td><td>146.7</td><td> 62  </td><td>3.69 </td><td>3.190</td><td>20.00</td><td>1    </td><td>0    </td><td>4    </td><td>2    </td></tr>\n",
       "\t<tr><th scope=row>Merc 230</th><td>22.8 </td><td>4    </td><td>140.8</td><td> 95  </td><td>3.92 </td><td>3.150</td><td>22.90</td><td>1    </td><td>0    </td><td>4    </td><td>2    </td></tr>\n",
       "\t<tr><th scope=row>Merc 280</th><td>19.2 </td><td>6    </td><td>167.6</td><td>123  </td><td>3.92 </td><td>3.440</td><td>18.30</td><td>1    </td><td>0    </td><td>4    </td><td>4    </td></tr>\n",
       "\t<tr><th scope=row>Merc 280C</th><td>17.8 </td><td>6    </td><td>167.6</td><td>123  </td><td>3.92 </td><td>3.440</td><td>18.90</td><td>1    </td><td>0    </td><td>4    </td><td>4    </td></tr>\n",
       "\t<tr><th scope=row>Merc 450SE</th><td>16.4 </td><td>8    </td><td>275.8</td><td>180  </td><td>3.07 </td><td>4.070</td><td>17.40</td><td>0    </td><td>0    </td><td>3    </td><td>3    </td></tr>\n",
       "\t<tr><th scope=row>Merc 450SL</th><td>17.3 </td><td>8    </td><td>275.8</td><td>180  </td><td>3.07 </td><td>3.730</td><td>17.60</td><td>0    </td><td>0    </td><td>3    </td><td>3    </td></tr>\n",
       "\t<tr><th scope=row>Merc 450SLC</th><td>15.2 </td><td>8    </td><td>275.8</td><td>180  </td><td>3.07 </td><td>3.780</td><td>18.00</td><td>0    </td><td>0    </td><td>3    </td><td>3    </td></tr>\n",
       "\t<tr><th scope=row>Cadillac Fleetwood</th><td>10.4 </td><td>8    </td><td>472.0</td><td>205  </td><td>2.93 </td><td>5.250</td><td>17.98</td><td>0    </td><td>0    </td><td>3    </td><td>4    </td></tr>\n",
       "\t<tr><th scope=row>Lincoln Continental</th><td>10.4 </td><td>8    </td><td>460.0</td><td>215  </td><td>3.00 </td><td>5.424</td><td>17.82</td><td>0    </td><td>0    </td><td>3    </td><td>4    </td></tr>\n",
       "\t<tr><th scope=row>Chrysler Imperial</th><td>14.7 </td><td>8    </td><td>440.0</td><td>230  </td><td>3.23 </td><td>5.345</td><td>17.42</td><td>0    </td><td>0    </td><td>3    </td><td>4    </td></tr>\n",
       "\t<tr><th scope=row>Fiat 128</th><td>32.4 </td><td>4    </td><td> 78.7</td><td> 66  </td><td>4.08 </td><td>2.200</td><td>19.47</td><td>1    </td><td>1    </td><td>4    </td><td>1    </td></tr>\n",
       "\t<tr><th scope=row>Honda Civic</th><td>30.4 </td><td>4    </td><td> 75.7</td><td> 52  </td><td>4.93 </td><td>1.615</td><td>18.52</td><td>1    </td><td>1    </td><td>4    </td><td>2    </td></tr>\n",
       "\t<tr><th scope=row>Toyota Corolla</th><td>33.9 </td><td>4    </td><td> 71.1</td><td> 65  </td><td>4.22 </td><td>1.835</td><td>19.90</td><td>1    </td><td>1    </td><td>4    </td><td>1    </td></tr>\n",
       "\t<tr><th scope=row>Toyota Corona</th><td>21.5 </td><td>4    </td><td>120.1</td><td> 97  </td><td>3.70 </td><td>2.465</td><td>20.01</td><td>1    </td><td>0    </td><td>3    </td><td>1    </td></tr>\n",
       "\t<tr><th scope=row>Dodge Challenger</th><td>15.5 </td><td>8    </td><td>318.0</td><td>150  </td><td>2.76 </td><td>3.520</td><td>16.87</td><td>0    </td><td>0    </td><td>3    </td><td>2    </td></tr>\n",
       "\t<tr><th scope=row>AMC Javelin</th><td>15.2 </td><td>8    </td><td>304.0</td><td>150  </td><td>3.15 </td><td>3.435</td><td>17.30</td><td>0    </td><td>0    </td><td>3    </td><td>2    </td></tr>\n",
       "\t<tr><th scope=row>Camaro Z28</th><td>13.3 </td><td>8    </td><td>350.0</td><td>245  </td><td>3.73 </td><td>3.840</td><td>15.41</td><td>0    </td><td>0    </td><td>3    </td><td>4    </td></tr>\n",
       "\t<tr><th scope=row>Pontiac Firebird</th><td>19.2 </td><td>8    </td><td>400.0</td><td>175  </td><td>3.08 </td><td>3.845</td><td>17.05</td><td>0    </td><td>0    </td><td>3    </td><td>2    </td></tr>\n",
       "\t<tr><th scope=row>Fiat X1-9</th><td>27.3 </td><td>4    </td><td> 79.0</td><td> 66  </td><td>4.08 </td><td>1.935</td><td>18.90</td><td>1    </td><td>1    </td><td>4    </td><td>1    </td></tr>\n",
       "\t<tr><th scope=row>Porsche 914-2</th><td>26.0 </td><td>4    </td><td>120.3</td><td> 91  </td><td>4.43 </td><td>2.140</td><td>16.70</td><td>0    </td><td>1    </td><td>5    </td><td>2    </td></tr>\n",
       "\t<tr><th scope=row>Lotus Europa</th><td>30.4 </td><td>4    </td><td> 95.1</td><td>113  </td><td>3.77 </td><td>1.513</td><td>16.90</td><td>1    </td><td>1    </td><td>5    </td><td>2    </td></tr>\n",
       "\t<tr><th scope=row>Ford Pantera L</th><td>15.8 </td><td>8    </td><td>351.0</td><td>264  </td><td>4.22 </td><td>3.170</td><td>14.50</td><td>0    </td><td>1    </td><td>5    </td><td>4    </td></tr>\n",
       "\t<tr><th scope=row>Ferrari Dino</th><td>19.7 </td><td>6    </td><td>145.0</td><td>175  </td><td>3.62 </td><td>2.770</td><td>15.50</td><td>0    </td><td>1    </td><td>5    </td><td>6    </td></tr>\n",
       "\t<tr><th scope=row>Maserati Bora</th><td>15.0 </td><td>8    </td><td>301.0</td><td>335  </td><td>3.54 </td><td>3.570</td><td>14.60</td><td>0    </td><td>1    </td><td>5    </td><td>8    </td></tr>\n",
       "\t<tr><th scope=row>Volvo 142E</th><td>21.4 </td><td>4    </td><td>121.0</td><td>109  </td><td>4.11 </td><td>2.780</td><td>18.60</td><td>1    </td><td>1    </td><td>4    </td><td>2    </td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lllllllllll}\n",
       "  & mpg & cyl & disp & hp & drat & wt & qsec & vs & am & gear & carb\\\\\n",
       "\\hline\n",
       "\tMazda RX4 & 21.0  & 6     & 160.0 & 110   & 3.90  & 2.620 & 16.46 & 0     & 1     & 4     & 4    \\\\\n",
       "\tMazda RX4 Wag & 21.0  & 6     & 160.0 & 110   & 3.90  & 2.875 & 17.02 & 0     & 1     & 4     & 4    \\\\\n",
       "\tDatsun 710 & 22.8  & 4     & 108.0 &  93   & 3.85  & 2.320 & 18.61 & 1     & 1     & 4     & 1    \\\\\n",
       "\tHornet 4 Drive & 21.4  & 6     & 258.0 & 110   & 3.08  & 3.215 & 19.44 & 1     & 0     & 3     & 1    \\\\\n",
       "\tHornet Sportabout & 18.7  & 8     & 360.0 & 175   & 3.15  & 3.440 & 17.02 & 0     & 0     & 3     & 2    \\\\\n",
       "\tValiant & 18.1  & 6     & 225.0 & 105   & 2.76  & 3.460 & 20.22 & 1     & 0     & 3     & 1    \\\\\n",
       "\tDuster 360 & 14.3  & 8     & 360.0 & 245   & 3.21  & 3.570 & 15.84 & 0     & 0     & 3     & 4    \\\\\n",
       "\tMerc 240D & 24.4  & 4     & 146.7 &  62   & 3.69  & 3.190 & 20.00 & 1     & 0     & 4     & 2    \\\\\n",
       "\tMerc 230 & 22.8  & 4     & 140.8 &  95   & 3.92  & 3.150 & 22.90 & 1     & 0     & 4     & 2    \\\\\n",
       "\tMerc 280 & 19.2  & 6     & 167.6 & 123   & 3.92  & 3.440 & 18.30 & 1     & 0     & 4     & 4    \\\\\n",
       "\tMerc 280C & 17.8  & 6     & 167.6 & 123   & 3.92  & 3.440 & 18.90 & 1     & 0     & 4     & 4    \\\\\n",
       "\tMerc 450SE & 16.4  & 8     & 275.8 & 180   & 3.07  & 4.070 & 17.40 & 0     & 0     & 3     & 3    \\\\\n",
       "\tMerc 450SL & 17.3  & 8     & 275.8 & 180   & 3.07  & 3.730 & 17.60 & 0     & 0     & 3     & 3    \\\\\n",
       "\tMerc 450SLC & 15.2  & 8     & 275.8 & 180   & 3.07  & 3.780 & 18.00 & 0     & 0     & 3     & 3    \\\\\n",
       "\tCadillac Fleetwood & 10.4  & 8     & 472.0 & 205   & 2.93  & 5.250 & 17.98 & 0     & 0     & 3     & 4    \\\\\n",
       "\tLincoln Continental & 10.4  & 8     & 460.0 & 215   & 3.00  & 5.424 & 17.82 & 0     & 0     & 3     & 4    \\\\\n",
       "\tChrysler Imperial & 14.7  & 8     & 440.0 & 230   & 3.23  & 5.345 & 17.42 & 0     & 0     & 3     & 4    \\\\\n",
       "\tFiat 128 & 32.4  & 4     &  78.7 &  66   & 4.08  & 2.200 & 19.47 & 1     & 1     & 4     & 1    \\\\\n",
       "\tHonda Civic & 30.4  & 4     &  75.7 &  52   & 4.93  & 1.615 & 18.52 & 1     & 1     & 4     & 2    \\\\\n",
       "\tToyota Corolla & 33.9  & 4     &  71.1 &  65   & 4.22  & 1.835 & 19.90 & 1     & 1     & 4     & 1    \\\\\n",
       "\tToyota Corona & 21.5  & 4     & 120.1 &  97   & 3.70  & 2.465 & 20.01 & 1     & 0     & 3     & 1    \\\\\n",
       "\tDodge Challenger & 15.5  & 8     & 318.0 & 150   & 2.76  & 3.520 & 16.87 & 0     & 0     & 3     & 2    \\\\\n",
       "\tAMC Javelin & 15.2  & 8     & 304.0 & 150   & 3.15  & 3.435 & 17.30 & 0     & 0     & 3     & 2    \\\\\n",
       "\tCamaro Z28 & 13.3  & 8     & 350.0 & 245   & 3.73  & 3.840 & 15.41 & 0     & 0     & 3     & 4    \\\\\n",
       "\tPontiac Firebird & 19.2  & 8     & 400.0 & 175   & 3.08  & 3.845 & 17.05 & 0     & 0     & 3     & 2    \\\\\n",
       "\tFiat X1-9 & 27.3  & 4     &  79.0 &  66   & 4.08  & 1.935 & 18.90 & 1     & 1     & 4     & 1    \\\\\n",
       "\tPorsche 914-2 & 26.0  & 4     & 120.3 &  91   & 4.43  & 2.140 & 16.70 & 0     & 1     & 5     & 2    \\\\\n",
       "\tLotus Europa & 30.4  & 4     &  95.1 & 113   & 3.77  & 1.513 & 16.90 & 1     & 1     & 5     & 2    \\\\\n",
       "\tFord Pantera L & 15.8  & 8     & 351.0 & 264   & 4.22  & 3.170 & 14.50 & 0     & 1     & 5     & 4    \\\\\n",
       "\tFerrari Dino & 19.7  & 6     & 145.0 & 175   & 3.62  & 2.770 & 15.50 & 0     & 1     & 5     & 6    \\\\\n",
       "\tMaserati Bora & 15.0  & 8     & 301.0 & 335   & 3.54  & 3.570 & 14.60 & 0     & 1     & 5     & 8    \\\\\n",
       "\tVolvo 142E & 21.4  & 4     & 121.0 & 109   & 4.11  & 2.780 & 18.60 & 1     & 1     & 4     & 2    \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "| <!--/--> | mpg | cyl | disp | hp | drat | wt | qsec | vs | am | gear | carb | \n",
       "|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n",
       "| Mazda RX4 | 21.0  | 6     | 160.0 | 110   | 3.90  | 2.620 | 16.46 | 0     | 1     | 4     | 4     | \n",
       "| Mazda RX4 Wag | 21.0  | 6     | 160.0 | 110   | 3.90  | 2.875 | 17.02 | 0     | 1     | 4     | 4     | \n",
       "| Datsun 710 | 22.8  | 4     | 108.0 |  93   | 3.85  | 2.320 | 18.61 | 1     | 1     | 4     | 1     | \n",
       "| Hornet 4 Drive | 21.4  | 6     | 258.0 | 110   | 3.08  | 3.215 | 19.44 | 1     | 0     | 3     | 1     | \n",
       "| Hornet Sportabout | 18.7  | 8     | 360.0 | 175   | 3.15  | 3.440 | 17.02 | 0     | 0     | 3     | 2     | \n",
       "| Valiant | 18.1  | 6     | 225.0 | 105   | 2.76  | 3.460 | 20.22 | 1     | 0     | 3     | 1     | \n",
       "| Duster 360 | 14.3  | 8     | 360.0 | 245   | 3.21  | 3.570 | 15.84 | 0     | 0     | 3     | 4     | \n",
       "| Merc 240D | 24.4  | 4     | 146.7 |  62   | 3.69  | 3.190 | 20.00 | 1     | 0     | 4     | 2     | \n",
       "| Merc 230 | 22.8  | 4     | 140.8 |  95   | 3.92  | 3.150 | 22.90 | 1     | 0     | 4     | 2     | \n",
       "| Merc 280 | 19.2  | 6     | 167.6 | 123   | 3.92  | 3.440 | 18.30 | 1     | 0     | 4     | 4     | \n",
       "| Merc 280C | 17.8  | 6     | 167.6 | 123   | 3.92  | 3.440 | 18.90 | 1     | 0     | 4     | 4     | \n",
       "| Merc 450SE | 16.4  | 8     | 275.8 | 180   | 3.07  | 4.070 | 17.40 | 0     | 0     | 3     | 3     | \n",
       "| Merc 450SL | 17.3  | 8     | 275.8 | 180   | 3.07  | 3.730 | 17.60 | 0     | 0     | 3     | 3     | \n",
       "| Merc 450SLC | 15.2  | 8     | 275.8 | 180   | 3.07  | 3.780 | 18.00 | 0     | 0     | 3     | 3     | \n",
       "| Cadillac Fleetwood | 10.4  | 8     | 472.0 | 205   | 2.93  | 5.250 | 17.98 | 0     | 0     | 3     | 4     | \n",
       "| Lincoln Continental | 10.4  | 8     | 460.0 | 215   | 3.00  | 5.424 | 17.82 | 0     | 0     | 3     | 4     | \n",
       "| Chrysler Imperial | 14.7  | 8     | 440.0 | 230   | 3.23  | 5.345 | 17.42 | 0     | 0     | 3     | 4     | \n",
       "| Fiat 128 | 32.4  | 4     |  78.7 |  66   | 4.08  | 2.200 | 19.47 | 1     | 1     | 4     | 1     | \n",
       "| Honda Civic | 30.4  | 4     |  75.7 |  52   | 4.93  | 1.615 | 18.52 | 1     | 1     | 4     | 2     | \n",
       "| Toyota Corolla | 33.9  | 4     |  71.1 |  65   | 4.22  | 1.835 | 19.90 | 1     | 1     | 4     | 1     | \n",
       "| Toyota Corona | 21.5  | 4     | 120.1 |  97   | 3.70  | 2.465 | 20.01 | 1     | 0     | 3     | 1     | \n",
       "| Dodge Challenger | 15.5  | 8     | 318.0 | 150   | 2.76  | 3.520 | 16.87 | 0     | 0     | 3     | 2     | \n",
       "| AMC Javelin | 15.2  | 8     | 304.0 | 150   | 3.15  | 3.435 | 17.30 | 0     | 0     | 3     | 2     | \n",
       "| Camaro Z28 | 13.3  | 8     | 350.0 | 245   | 3.73  | 3.840 | 15.41 | 0     | 0     | 3     | 4     | \n",
       "| Pontiac Firebird | 19.2  | 8     | 400.0 | 175   | 3.08  | 3.845 | 17.05 | 0     | 0     | 3     | 2     | \n",
       "| Fiat X1-9 | 27.3  | 4     |  79.0 |  66   | 4.08  | 1.935 | 18.90 | 1     | 1     | 4     | 1     | \n",
       "| Porsche 914-2 | 26.0  | 4     | 120.3 |  91   | 4.43  | 2.140 | 16.70 | 0     | 1     | 5     | 2     | \n",
       "| Lotus Europa | 30.4  | 4     |  95.1 | 113   | 3.77  | 1.513 | 16.90 | 1     | 1     | 5     | 2     | \n",
       "| Ford Pantera L | 15.8  | 8     | 351.0 | 264   | 4.22  | 3.170 | 14.50 | 0     | 1     | 5     | 4     | \n",
       "| Ferrari Dino | 19.7  | 6     | 145.0 | 175   | 3.62  | 2.770 | 15.50 | 0     | 1     | 5     | 6     | \n",
       "| Maserati Bora | 15.0  | 8     | 301.0 | 335   | 3.54  | 3.570 | 14.60 | 0     | 1     | 5     | 8     | \n",
       "| Volvo 142E | 21.4  | 4     | 121.0 | 109   | 4.11  | 2.780 | 18.60 | 1     | 1     | 4     | 2     | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "                    mpg  cyl disp  hp  drat wt    qsec  vs am gear carb\n",
       "Mazda RX4           21.0 6   160.0 110 3.90 2.620 16.46 0  1  4    4   \n",
       "Mazda RX4 Wag       21.0 6   160.0 110 3.90 2.875 17.02 0  1  4    4   \n",
       "Datsun 710          22.8 4   108.0  93 3.85 2.320 18.61 1  1  4    1   \n",
       "Hornet 4 Drive      21.4 6   258.0 110 3.08 3.215 19.44 1  0  3    1   \n",
       "Hornet Sportabout   18.7 8   360.0 175 3.15 3.440 17.02 0  0  3    2   \n",
       "Valiant             18.1 6   225.0 105 2.76 3.460 20.22 1  0  3    1   \n",
       "Duster 360          14.3 8   360.0 245 3.21 3.570 15.84 0  0  3    4   \n",
       "Merc 240D           24.4 4   146.7  62 3.69 3.190 20.00 1  0  4    2   \n",
       "Merc 230            22.8 4   140.8  95 3.92 3.150 22.90 1  0  4    2   \n",
       "Merc 280            19.2 6   167.6 123 3.92 3.440 18.30 1  0  4    4   \n",
       "Merc 280C           17.8 6   167.6 123 3.92 3.440 18.90 1  0  4    4   \n",
       "Merc 450SE          16.4 8   275.8 180 3.07 4.070 17.40 0  0  3    3   \n",
       "Merc 450SL          17.3 8   275.8 180 3.07 3.730 17.60 0  0  3    3   \n",
       "Merc 450SLC         15.2 8   275.8 180 3.07 3.780 18.00 0  0  3    3   \n",
       "Cadillac Fleetwood  10.4 8   472.0 205 2.93 5.250 17.98 0  0  3    4   \n",
       "Lincoln Continental 10.4 8   460.0 215 3.00 5.424 17.82 0  0  3    4   \n",
       "Chrysler Imperial   14.7 8   440.0 230 3.23 5.345 17.42 0  0  3    4   \n",
       "Fiat 128            32.4 4    78.7  66 4.08 2.200 19.47 1  1  4    1   \n",
       "Honda Civic         30.4 4    75.7  52 4.93 1.615 18.52 1  1  4    2   \n",
       "Toyota Corolla      33.9 4    71.1  65 4.22 1.835 19.90 1  1  4    1   \n",
       "Toyota Corona       21.5 4   120.1  97 3.70 2.465 20.01 1  0  3    1   \n",
       "Dodge Challenger    15.5 8   318.0 150 2.76 3.520 16.87 0  0  3    2   \n",
       "AMC Javelin         15.2 8   304.0 150 3.15 3.435 17.30 0  0  3    2   \n",
       "Camaro Z28          13.3 8   350.0 245 3.73 3.840 15.41 0  0  3    4   \n",
       "Pontiac Firebird    19.2 8   400.0 175 3.08 3.845 17.05 0  0  3    2   \n",
       "Fiat X1-9           27.3 4    79.0  66 4.08 1.935 18.90 1  1  4    1   \n",
       "Porsche 914-2       26.0 4   120.3  91 4.43 2.140 16.70 0  1  5    2   \n",
       "Lotus Europa        30.4 4    95.1 113 3.77 1.513 16.90 1  1  5    2   \n",
       "Ford Pantera L      15.8 8   351.0 264 4.22 3.170 14.50 0  1  5    4   \n",
       "Ferrari Dino        19.7 6   145.0 175 3.62 2.770 15.50 0  1  5    6   \n",
       "Maserati Bora       15.0 8   301.0 335 3.54 3.570 14.60 0  1  5    8   \n",
       "Volvo 142E          21.4 4   121.0 109 4.11 2.780 18.60 1  1  4    2   "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mtcars"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "You can plot things:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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6Nu/+VLo87dZcwG9/5pzMBec9565oJjD/+kuPTI645P84DZ2dljxoypcbfCwsKs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\nOkGwAwAA0In/A+IxRSjxlRneAAAAAElFTkSuQmCC",
      "text/plain": [
       "Plot with title “Histogram of mtcars$hp”"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "hist(mtcars$hp)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "In R, `ggplot2` is the defacto standard plotting packages. Let's make the same plot using `ggplot2`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "`stat_bin()` using `bins = 30`. Pick better value with `binwidth`.\n"
     ]
    },
    {
     "data": {},
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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F//4YzdoJs/usfnrv9rVUcBAGBVDPWM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\nYII=",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "library(ggplot2)\n",
    "\n",
    "qplot(mtcars$hp)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "`plotly` is another popular graphing library. Let's try it!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<iframe src=\"plotlyJupyterHTML/9eaac260a613d03943dec7e324220b37.html\" width=\"100%\" height=\"400\" id=\"igraph\" scrolling=\"no\" seamless=\"seamless\" frameBorder=\"0\"> </iframe>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "library(plotly)\n",
    "set.seed(100)\n",
    "d <- diamonds[sample(nrow(diamonds), 1000), ]\n",
    "p <- plot_ly(d, x = ~carat, y = ~price, color = ~carat,\n",
    "        size = ~carat, text = ~paste(\"Clarity: \", clarity),\n",
    "        type = \"scatter\", mode = \"markers\")\n",
    "embed_notebook(p)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>Sepal.Length</th><th scope=col>Sepal.Width</th><th scope=col>Petal.Length</th><th scope=col>Petal.Width</th><th scope=col>Species</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>5.1   </td><td>3.5   </td><td>1.4   </td><td>0.2   </td><td>setosa</td></tr>\n",
       "\t<tr><td>4.9   </td><td>3.0   </td><td>1.4   </td><td>0.2   </td><td>setosa</td></tr>\n",
       "\t<tr><td>4.7   </td><td>3.2   </td><td>1.3   </td><td>0.2   </td><td>setosa</td></tr>\n",
       "\t<tr><td>4.6   </td><td>3.1   </td><td>1.5   </td><td>0.2   </td><td>setosa</td></tr>\n",
       "\t<tr><td>5.0   </td><td>3.6   </td><td>1.4   </td><td>0.2   </td><td>setosa</td></tr>\n",
       "\t<tr><td>5.4   </td><td>3.9   </td><td>1.7   </td><td>0.4   </td><td>setosa</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lllll}\n",
       " Sepal.Length & Sepal.Width & Petal.Length & Petal.Width & Species\\\\\n",
       "\\hline\n",
       "\t 5.1    & 3.5    & 1.4    & 0.2    & setosa\\\\\n",
       "\t 4.9    & 3.0    & 1.4    & 0.2    & setosa\\\\\n",
       "\t 4.7    & 3.2    & 1.3    & 0.2    & setosa\\\\\n",
       "\t 4.6    & 3.1    & 1.5    & 0.2    & setosa\\\\\n",
       "\t 5.0    & 3.6    & 1.4    & 0.2    & setosa\\\\\n",
       "\t 5.4    & 3.9    & 1.7    & 0.4    & setosa\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "Sepal.Length | Sepal.Width | Petal.Length | Petal.Width | Species | \n",
       "|---|---|---|---|---|---|\n",
       "| 5.1    | 3.5    | 1.4    | 0.2    | setosa | \n",
       "| 4.9    | 3.0    | 1.4    | 0.2    | setosa | \n",
       "| 4.7    | 3.2    | 1.3    | 0.2    | setosa | \n",
       "| 4.6    | 3.1    | 1.5    | 0.2    | setosa | \n",
       "| 5.0    | 3.6    | 1.4    | 0.2    | setosa | \n",
       "| 5.4    | 3.9    | 1.7    | 0.4    | setosa | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "  Sepal.Length Sepal.Width Petal.Length Petal.Width Species\n",
       "1 5.1          3.5         1.4          0.2         setosa \n",
       "2 4.9          3.0         1.4          0.2         setosa \n",
       "3 4.7          3.2         1.3          0.2         setosa \n",
       "4 4.6          3.1         1.5          0.2         setosa \n",
       "5 5.0          3.6         1.4          0.2         setosa \n",
       "6 5.4          3.9         1.7          0.4         setosa "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "\n",
       "Call:\n",
       "glm(formula = y ~ x, family = binomial(link = \"logit\"))\n",
       "\n",
       "Deviance Residuals: \n",
       "    Min       1Q   Median       3Q      Max  \n",
       "-1.7368  -0.4784   0.1618   0.5249   1.6902  \n",
       "\n",
       "Coefficients:\n",
       "            Estimate Std. Error z value Pr(>|z|)  \n",
       "(Intercept) -3.56668    1.68570  -2.116   0.0344 *\n",
       "x            0.08319    0.03562   2.335   0.0195 *\n",
       "---\n",
       "Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1\n",
       "\n",
       "(Dispersion parameter for binomial family taken to be 1)\n",
       "\n",
       "    Null deviance: 27.526  on 19  degrees of freedom\n",
       "Residual deviance: 15.187  on 18  degrees of freedom\n",
       "AIC: 19.187\n",
       "\n",
       "Number of Fisher Scoring iterations: 5\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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VqJWlv79+8XBCEwMFCUvT+Z3he7yoq8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\nkAmCHQAAgEwQ7AAAAGSCYAcAACAT/wf0ZNfHXBPjEQAAAABJRU5ErkJggg==",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "head(iris)\n",
    "x = c(4,5,17,17,19,19,29,41,45,47,49,54,56,58,70,76,88,88,93,97)\n",
    "y = c(0,0,0,0,0,0,1,1,1,0,0,1,1,0,1,1,1,1,1,1)\n",
    "plot(x, y, xlim=c(0,100), ylim=c(-0.2,1.2), yaxt=\"n\")\n",
    "axis(2, at=c(0,1), labels=c(0,1), las=1)\n",
    "r = lm(y ~ x)\n",
    "abline(r)\n",
    "r = glm(y ~ x, family=binomial(link=\"logit\"))\n",
    "summary(r)\n",
    "curve(1 / (1 + exp(-(0.08319 * x - 3.56668))), add=TRUE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message in file(file, \"rt\"):\n",
      "“URL 'https://oku.edu.mie-u.ac.jp/~okumura/stat/data1.csv': status was 'Couldn't resolve host name'”"
     ]
    },
    {
     "ename": "ERROR",
     "evalue": "Error in file(file, \"rt\"): cannot open connection\n",
     "output_type": "error",
     "traceback": [
      "Error in file(file, \"rt\"): cannot open connection\nTraceback:\n",
      "1. read.csv(\"https://oku.edu.mie-u.ac.jp/~okumura/stat/data1.csv\")",
      "2. read.table(file = file, header = header, sep = sep, quote = quote, \n .     dec = dec, fill = fill, comment.char = comment.char, ...)",
      "3. file(file, \"rt\")"
     ]
    }
   ],
   "source": [
    "# That's it for now! Please play around, tell your friends, and let us know how we're doing! Tweet us at @RNotebookHQ !\n",
    "data1 = read.csv(\"https://oku.edu.mie-u.ac.jp/~okumura/stat/data1.csv\")\n",
    "head(data1)\n",
    "head(iris)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "head(iris)\n",
    "data1 = read.csv(\"https://oku.edu.mie-u.ac.jp/~okumura/stat/data1.csv\")\n",
    "head(data1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "head(iris)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>Sepal.Length</th><th scope=col>Sepal.Width</th><th scope=col>Petal.Length</th><th scope=col>Petal.Width</th><th scope=col>Species</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>5.1   </td><td>3.5   </td><td>1.4   </td><td>0.2   </td><td>setosa</td></tr>\n",
       "\t<tr><td>4.9   </td><td>3.0   </td><td>1.4   </td><td>0.2   </td><td>setosa</td></tr>\n",
       "\t<tr><td>4.7   </td><td>3.2   </td><td>1.3   </td><td>0.2   </td><td>setosa</td></tr>\n",
       "\t<tr><td>4.6   </td><td>3.1   </td><td>1.5   </td><td>0.2   </td><td>setosa</td></tr>\n",
       "\t<tr><td>5.0   </td><td>3.6   </td><td>1.4   </td><td>0.2   </td><td>setosa</td></tr>\n",
       "\t<tr><td>5.4   </td><td>3.9   </td><td>1.7   </td><td>0.4   </td><td>setosa</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lllll}\n",
       " Sepal.Length & Sepal.Width & Petal.Length & Petal.Width & Species\\\\\n",
       "\\hline\n",
       "\t 5.1    & 3.5    & 1.4    & 0.2    & setosa\\\\\n",
       "\t 4.9    & 3.0    & 1.4    & 0.2    & setosa\\\\\n",
       "\t 4.7    & 3.2    & 1.3    & 0.2    & setosa\\\\\n",
       "\t 4.6    & 3.1    & 1.5    & 0.2    & setosa\\\\\n",
       "\t 5.0    & 3.6    & 1.4    & 0.2    & setosa\\\\\n",
       "\t 5.4    & 3.9    & 1.7    & 0.4    & setosa\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "Sepal.Length | Sepal.Width | Petal.Length | Petal.Width | Species | \n",
       "|---|---|---|---|---|---|\n",
       "| 5.1    | 3.5    | 1.4    | 0.2    | setosa | \n",
       "| 4.9    | 3.0    | 1.4    | 0.2    | setosa | \n",
       "| 4.7    | 3.2    | 1.3    | 0.2    | setosa | \n",
       "| 4.6    | 3.1    | 1.5    | 0.2    | setosa | \n",
       "| 5.0    | 3.6    | 1.4    | 0.2    | setosa | \n",
       "| 5.4    | 3.9    | 1.7    | 0.4    | setosa | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "  Sepal.Length Sepal.Width Petal.Length Petal.Width Species\n",
       "1 5.1          3.5         1.4          0.2         setosa \n",
       "2 4.9          3.0         1.4          0.2         setosa \n",
       "3 4.7          3.2         1.3          0.2         setosa \n",
       "4 4.6          3.1         1.5          0.2         setosa \n",
       "5 5.0          3.6         1.4          0.2         setosa \n",
       "6 5.4          3.9         1.7          0.4         setosa "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "head(iris)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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Xmhxis0NLSgoGDKlCl0VQcAhoaGc+bM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CQ+vOMVNSAr0ewcEAUFBgUnd3BwAHBwiFBXwFvNgAACAASURBVG6s0ICWQQMLgt0A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      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot(iris[,c(2:4)], col=iris$Species)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "  Sepal.Length    Sepal.Width     Petal.Length       Petal.Width      \n",
       " Min.   :4.300   Min.   :2.000   Min.   :1.100000   Min.   :0.100000  \n",
       " 1st Qu.:5.100   1st Qu.:2.800   1st Qu.:1.575000   1st Qu.:0.300000  \n",
       " Median :5.800   Median :3.000   Median :4.350000   Median :1.300000  \n",
       " Mean   :5.825   Mean   :3.055   Mean   :3.735833   Mean   :1.183333  \n",
       " 3rd Qu.:6.400   3rd Qu.:3.300   3rd Qu.:5.100000   3rd Qu.:1.800000  \n",
       " Max.   :7.900   Max.   :4.400   Max.   :6.900000   Max.   :2.500000  \n",
       "       Species  \n",
       " setosa    :41  \n",
       " versicolor:39  \n",
       " virginica :40  \n",
       "                \n",
       "                \n",
       "                "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "# weights:  43\n",
      "initial  value 133.443616 \n",
      "iter  10 value 45.224811\n",
      "iter  20 value 8.490007\n",
      "iter  30 value 5.846245\n",
      "iter  40 value 5.814955\n",
      "iter  50 value 5.808654\n",
      "iter  60 value 5.797305\n",
      "iter  70 value 5.783923\n",
      "iter  80 value 5.780577\n",
      "iter  90 value 5.779106\n",
      "iter 100 value 5.778356\n",
      "final  value 5.778356 \n",
      "stopped after 100 iterations\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "            pred_nn1\n",
       "             setosa versicolor virginica\n",
       "  setosa          9          0         0\n",
       "  versicolor      0         11         0\n",
       "  virginica       0          0        10"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "library(nnet)\n",
    "    d=iris\n",
    "    d$Species <- as.factor(d$Species)\n",
    "    #train_test_split\n",
    "    set.seed(0)\n",
    "    sample <- sample.int(n = nrow(d), size = floor(0.80*nrow(d)), replace = F)\n",
    "    train <- d[sample, ]\n",
    "    test <- d[-sample, ]\n",
    "    summary(train)\n",
    "    #nnet\n",
    "    library(nnet)\n",
    "    nn1=nnet(Species~., size=5, data=train)\n",
    "    pred_nn1 <- predict(nn1, test,type=\"class\")\n",
    "    table(test$Species,pred_nn1)\n",
    "\n",
    "    library(caret) \n",
    "    tmp <- dummyVars(~.,data=train) \n",
    "    dummy <- as.data.frame(predict(tmp, train))\n",
    "    library(\"neuralnet\")\n",
    "    f = Species.setosa + Species.versicolor + Species.virginica~ Sepal.Length + Sepal.Width + Petal.Length + Petal.Width \n",
    "    nn2 <- neuralnet(formula = f, data = dummy)\n",
    "plot(nn2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "$call\n",
       "neuralnet(formula = f, data = dummy)\n",
       "\n",
       "$response\n",
       "    Species.setosa Species.versicolor Species.virginica\n",
       "135              0                  0                 1\n",
       "40               1                  0                 0\n",
       "56               0                  1                 0\n",
       "85               0                  1                 0\n",
       "133              0                  0                 1\n",
       "30               1                  0                 0\n",
       "130              0                  0                 1\n",
       "136              0                  0                 1\n",
       "94               0                  1                 0\n",
       "89               0                  1                 0\n",
       "9                1                  0                 0\n",
       "29               1                  0                 0\n",
       "25               1                  0                 0\n",
       "95               0                  1                 0\n",
       "53               0                  1                 0\n",
       "104              0                  0                 1\n",
       "67               0                  1                 0\n",
       "96               0                  1                 0\n",
       "131              0                  0                 1\n",
       "50               1                  0                 0\n",
       "102              0                  0                 1\n",
       "121              0                  0                 1\n",
       "28               1                  0                 0\n",
       "83               0                  1                 0\n",
       "16               1                  0                 0\n",
       "34               1                  0                 0\n",
       "48               1                  0                 0\n",
       "2                1                  0                 0\n",
       "47               1                  0                 0\n",
       "106              0                  0                 1\n",
       "41               1                  0                 0\n",
       "58               0                  1                 0\n",
       "71               0                  1                 0\n",
       "119              0                  0                 1\n",
       "22               1                  0                 0\n",
       "146              0                  0                 1\n",
       "77               0                  1                 0\n",
       "90               0                  1                 0\n",
       "13               1                  0                 0\n",
       "81               0                  1                 0\n",
       "46               1                  0                 0\n",
       "113              0                  0                 1\n",
       "70               0                  1                 0\n",
       "84               0                  1                 0\n",
       "59               0                  1                 0\n",
       "148              0                  0                 1\n",
       "127              0                  0                 1\n",
       "3                1                  0                 0\n",
       "49               1                  0                 0\n",
       "74               0                  1                 0\n",
       "108              0                  0                 1\n",
       "124              0                  0                 1\n",
       "147              0                  0                 1\n",
       "43               1                  0                 0\n",
       "24               1                  0                 0\n",
       "7                1                  0                 0\n",
       "10               1                  0                 0\n",
       "145              0                  0                 1\n",
       "99               0                  1                 0\n",
       "61               0                  1                 0\n",
       "37               1                  0                 0\n",
       "82               0                  1                 0\n",
       "26               1                  0                 0\n",
       "149              0                  0                 1\n",
       "139              0                  0                 1\n",
       "105              0                  0                 1\n",
       "116              0                  0                 1\n",
       "87               0                  1                 0\n",
       "63               0                  1                 0\n",
       "137              0                  0                 1\n",
       "118              0                  0                 1\n",
       "27               1                  0                 0\n",
       "66               0                  1                 0\n",
       "79               0                  1                 0\n",
       "88               0                  1                 0\n",
       "36               1                  0                 0\n",
       "134              0                  0                 1\n",
       "64               0                  1                 0\n",
       "86               0                  1                 0\n",
       "98               0                  1                 0\n",
       "68               0                  1                 0\n",
       "93               0                  1                 0\n",
       "144              0                  0                 1\n",
       "114              0                  0                 1\n",
       "107              0                  0                 1\n",
       "132              0                  0                 1\n",
       "112              0                  0                 1\n",
       "45               1                  0                 0\n",
       "8                1                  0                 0\n",
       "15               1                  0                 0\n",
       "140              0                  0                 1\n",
       "91               0                  1                 0\n",
       "4                1                  0                 0\n",
       "109              0                  0                 1\n",
       "65               0                  1                 0\n",
       "97               0                  1                 0\n",
       "44               1                  0                 0\n",
       "138              0                  0                 1\n",
       "78               0                  1                 0\n",
       "42               1                  0                 0\n",
       "31               1                  0                 0\n",
       "33               1                  0                 0\n",
       "17               1                  0                 0\n",
       "73               0                  1                 0\n",
       "110              0                  0                 1\n",
       "72               0                  1                 0\n",
       "142              0                  0                 1\n",
       "6                1                  0                 0\n",
       "21               1                  0                 0\n",
       "38               1                  0                 0\n",
       "115              0                  0                 1\n",
       "39               1                  0                 0\n",
       "128              0                  0                 1\n",
       "14               1                  0                 0\n",
       "126              0                  0                 1\n",
       "55               0                  1                 0\n",
       "1                1                  0                 0\n",
       "150              0                  0                 1\n",
       "117              0                  0                 1\n",
       "57               0                  1                 0\n",
       "\n",
       "$covariate\n",
       "       [,1] [,2] [,3] [,4]\n",
       "  [1,]  6.1  2.6  5.6  1.4\n",
       "  [2,]  5.1  3.4  1.5  0.2\n",
       "  [3,]  5.7  2.8  4.5  1.3\n",
       "  [4,]  5.4  3.0  4.5  1.5\n",
       "  [5,]  6.4  2.8  5.6  2.2\n",
       "  [6,]  4.7  3.2  1.6  0.2\n",
       "  [7,]  7.2  3.0  5.8  1.6\n",
       "  [8,]  7.7  3.0  6.1  2.3\n",
       "  [9,]  5.0  2.3  3.3  1.0\n",
       " [10,]  5.6  3.0  4.1  1.3\n",
       " [11,]  4.4  2.9  1.4  0.2\n",
       " [12,]  5.2  3.4  1.4  0.2\n",
       " [13,]  4.8  3.4  1.9  0.2\n",
       " [14,]  5.6  2.7  4.2  1.3\n",
       " [15,]  6.9  3.1  4.9  1.5\n",
       " [16,]  6.3  2.9  5.6  1.8\n",
       " [17,]  5.6  3.0  4.5  1.5\n",
       " [18,]  5.7  3.0  4.2  1.2\n",
       " [19,]  7.4  2.8  6.1  1.9\n",
       " [20,]  5.0  3.3  1.4  0.2\n",
       " [21,]  5.8  2.7  5.1  1.9\n",
       " [22,]  6.9  3.2  5.7  2.3\n",
       " [23,]  5.2  3.5  1.5  0.2\n",
       " [24,]  5.8  2.7  3.9  1.2\n",
       " [25,]  5.7  4.4  1.5  0.4\n",
       " [26,]  5.5  4.2  1.4  0.2\n",
       " [27,]  4.6  3.2  1.4  0.2\n",
       " [28,]  4.9  3.0  1.4  0.2\n",
       " [29,]  5.1  3.8  1.6  0.2\n",
       " [30,]  7.6  3.0  6.6  2.1\n",
       " [31,]  5.0  3.5  1.3  0.3\n",
       " [32,]  4.9  2.4  3.3  1.0\n",
       " [33,]  5.9  3.2  4.8  1.8\n",
       " [34,]  7.7  2.6  6.9  2.3\n",
       " [35,]  5.1  3.7  1.5  0.4\n",
       " [36,]  6.7  3.0  5.2  2.3\n",
       " [37,]  6.8  2.8  4.8  1.4\n",
       " [38,]  5.5  2.5  4.0  1.3\n",
       " [39,]  4.8  3.0  1.4  0.1\n",
       " [40,]  5.5  2.4  3.8  1.1\n",
       " [41,]  4.8  3.0  1.4  0.3\n",
       " [42,]  6.8  3.0  5.5  2.1\n",
       " [43,]  5.6  2.5  3.9  1.1\n",
       " [44,]  6.0  2.7  5.1  1.6\n",
       " [45,]  6.6  2.9  4.6  1.3\n",
       " [46,]  6.5  3.0  5.2  2.0\n",
       " [47,]  6.2  2.8  4.8  1.8\n",
       " [48,]  4.7  3.2  1.3  0.2\n",
       " [49,]  5.3  3.7  1.5  0.2\n",
       " [50,]  6.1  2.8  4.7  1.2\n",
       " [51,]  7.3  2.9  6.3  1.8\n",
       " [52,]  6.3  2.7  4.9  1.8\n",
       " [53,]  6.3  2.5  5.0  1.9\n",
       " [54,]  4.4  3.2  1.3  0.2\n",
       " [55,]  5.1  3.3  1.7  0.5\n",
       " [56,]  4.6  3.4  1.4  0.3\n",
       " [57,]  4.9  3.1  1.5  0.1\n",
       " [58,]  6.7  3.3  5.7  2.5\n",
       " [59,]  5.1  2.5  3.0  1.1\n",
       " [60,]  5.0  2.0  3.5  1.0\n",
       " [61,]  5.5  3.5  1.3  0.2\n",
       " [62,]  5.5  2.4  3.7  1.0\n",
       " [63,]  5.0  3.0  1.6  0.2\n",
       " [64,]  6.2  3.4  5.4  2.3\n",
       " [65,]  6.0  3.0  4.8  1.8\n",
       " [66,]  6.5  3.0  5.8  2.2\n",
       " [67,]  6.4  3.2  5.3  2.3\n",
       " [68,]  6.7  3.1  4.7  1.5\n",
       " [69,]  6.0  2.2  4.0  1.0\n",
       " [70,]  6.3  3.4  5.6  2.4\n",
       " [71,]  7.7  3.8  6.7  2.2\n",
       " [72,]  5.0  3.4  1.6  0.4\n",
       " [73,]  6.7  3.1  4.4  1.4\n",
       " [74,]  6.0  2.9  4.5  1.5\n",
       " [75,]  6.3  2.3  4.4  1.3\n",
       " [76,]  5.0  3.2  1.2  0.2\n",
       " [77,]  6.3  2.8  5.1  1.5\n",
       " [78,]  6.1  2.9  4.7  1.4\n",
       " [79,]  6.0  3.4  4.5  1.6\n",
       " [80,]  6.2  2.9  4.3  1.3\n",
       " [81,]  5.8  2.7  4.1  1.0\n",
       " [82,]  5.8  2.6  4.0  1.2\n",
       " [83,]  6.8  3.2  5.9  2.3\n",
       " [84,]  5.7  2.5  5.0  2.0\n",
       " [85,]  4.9  2.5  4.5  1.7\n",
       " [86,]  7.9  3.8  6.4  2.0\n",
       " [87,]  6.4  2.7  5.3  1.9\n",
       " [88,]  5.1  3.8  1.9  0.4\n",
       " [89,]  5.0  3.4  1.5  0.2\n",
       " [90,]  5.8  4.0  1.2  0.2\n",
       " [91,]  6.9  3.1  5.4  2.1\n",
       " [92,]  5.5  2.6  4.4  1.2\n",
       " [93,]  4.6  3.1  1.5  0.2\n",
       " [94,]  6.7  2.5  5.8  1.8\n",
       " [95,]  5.6  2.9  3.6  1.3\n",
       " [96,]  5.7  2.9  4.2  1.3\n",
       " [97,]  5.0  3.5  1.6  0.6\n",
       " [98,]  6.4  3.1  5.5  1.8\n",
       " [99,]  6.7  3.0  5.0  1.7\n",
       "[100,]  4.5  2.3  1.3  0.3\n",
       "[101,]  4.8  3.1  1.6  0.2\n",
       "[102,]  5.2  4.1  1.5  0.1\n",
       "[103,]  5.4  3.9  1.3  0.4\n",
       "[104,]  6.3  2.5  4.9  1.5\n",
       "[105,]  7.2  3.6  6.1  2.5\n",
       "[106,]  6.1  2.8  4.0  1.3\n",
       "[107,]  6.9  3.1  5.1  2.3\n",
       "[108,]  5.4  3.9  1.7  0.4\n",
       "[109,]  5.4  3.4  1.7  0.2\n",
       "[110,]  4.9  3.6  1.4  0.1\n",
       "[111,]  5.8  2.8  5.1  2.4\n",
       "[112,]  4.4  3.0  1.3  0.2\n",
       "[113,]  6.1  3.0  4.9  1.8\n",
       "[114,]  4.3  3.0  1.1  0.1\n",
       "[115,]  7.2  3.2  6.0  1.8\n",
       "[116,]  6.5  2.8  4.6  1.5\n",
       "[117,]  5.1  3.5  1.4  0.2\n",
       "[118,]  5.9  3.0  5.1  1.8\n",
       "[119,]  6.5  3.0  5.5  1.8\n",
       "[120,]  6.3  3.3  4.7  1.6\n",
       "\n",
       "$model.list\n",
       "$model.list$response\n",
       "[1] \"Species.setosa\"     \"Species.versicolor\" \"Species.virginica\" \n",
       "\n",
       "$model.list$variables\n",
       "[1] \"Sepal.Length\" \"Sepal.Width\"  \"Petal.Length\" \"Petal.Width\" \n",
       "\n",
       "\n",
       "$err.fct\n",
       "function (x, y) \n",
       "{\n",
       "    1/2 * (y - x)^2\n",
       "}\n",
       "<environment: 0x999f258>\n",
       "attr(,\"type\")\n",
       "[1] \"sse\"\n",
       "\n",
       "$act.fct\n",
       "function (x) \n",
       "{\n",
       "    1/(1 + exp(-x))\n",
       "}\n",
       "<environment: 0x999f258>\n",
       "attr(,\"type\")\n",
       "[1] \"logistic\"\n",
       "\n",
       "$linear.output\n",
       "[1] TRUE\n",
       "\n",
       "$data\n",
       "    Sepal.Length Sepal.Width Petal.Length Petal.Width Species.setosa\n",
       "135          6.1         2.6          5.6         1.4              0\n",
       "40           5.1         3.4          1.5         0.2              1\n",
       "56           5.7         2.8          4.5         1.3              0\n",
       "85           5.4         3.0          4.5         1.5              0\n",
       "133          6.4         2.8          5.6         2.2              0\n",
       "30           4.7         3.2          1.6         0.2              1\n",
       "130          7.2         3.0          5.8         1.6              0\n",
       "136          7.7         3.0          6.1         2.3              0\n",
       "94           5.0         2.3          3.3         1.0              0\n",
       "89           5.6         3.0          4.1         1.3              0\n",
       "9            4.4         2.9          1.4         0.2              1\n",
       "29           5.2         3.4          1.4         0.2              1\n",
       "25           4.8         3.4          1.9         0.2              1\n",
       "95           5.6         2.7          4.2         1.3              0\n",
       "53           6.9         3.1          4.9         1.5              0\n",
       "104          6.3         2.9          5.6         1.8              0\n",
       "67           5.6         3.0          4.5         1.5              0\n",
       "96           5.7         3.0          4.2         1.2              0\n",
       "131          7.4         2.8          6.1         1.9              0\n",
       "50           5.0         3.3          1.4         0.2              1\n",
       "102          5.8         2.7          5.1         1.9              0\n",
       "121          6.9         3.2          5.7         2.3              0\n",
       "28           5.2         3.5          1.5         0.2              1\n",
       "83           5.8         2.7          3.9         1.2              0\n",
       "16           5.7         4.4          1.5         0.4              1\n",
       "34           5.5         4.2          1.4         0.2              1\n",
       "48           4.6         3.2          1.4         0.2              1\n",
       "2            4.9         3.0          1.4         0.2              1\n",
       "47           5.1         3.8          1.6         0.2              1\n",
       "106          7.6         3.0          6.6         2.1              0\n",
       "41           5.0         3.5          1.3         0.3              1\n",
       "58           4.9         2.4          3.3         1.0              0\n",
       "71           5.9         3.2          4.8         1.8              0\n",
       "119          7.7         2.6          6.9         2.3              0\n",
       "22           5.1         3.7          1.5         0.4              1\n",
       "146          6.7         3.0          5.2         2.3              0\n",
       "77           6.8         2.8          4.8         1.4              0\n",
       "90           5.5         2.5          4.0         1.3              0\n",
       "13           4.8         3.0          1.4         0.1              1\n",
       "81           5.5         2.4          3.8         1.1              0\n",
       "46           4.8         3.0          1.4         0.3              1\n",
       "113          6.8         3.0          5.5         2.1              0\n",
       "70           5.6         2.5          3.9         1.1              0\n",
       "84           6.0         2.7          5.1         1.6              0\n",
       "59           6.6         2.9          4.6         1.3              0\n",
       "148          6.5         3.0          5.2         2.0              0\n",
       "127          6.2         2.8          4.8         1.8              0\n",
       "3            4.7         3.2          1.3         0.2              1\n",
       "49           5.3         3.7          1.5         0.2              1\n",
       "74           6.1         2.8          4.7         1.2              0\n",
       "108          7.3         2.9          6.3         1.8              0\n",
       "124          6.3         2.7          4.9         1.8              0\n",
       "147          6.3         2.5          5.0         1.9              0\n",
       "43           4.4         3.2          1.3         0.2              1\n",
       "24           5.1         3.3          1.7         0.5              1\n",
       "7            4.6         3.4          1.4         0.3              1\n",
       "10           4.9         3.1          1.5         0.1              1\n",
       "145          6.7         3.3          5.7         2.5              0\n",
       "99           5.1         2.5          3.0         1.1              0\n",
       "61           5.0         2.0          3.5         1.0              0\n",
       "37           5.5         3.5          1.3         0.2              1\n",
       "82           5.5         2.4          3.7         1.0              0\n",
       "26           5.0         3.0          1.6         0.2              1\n",
       "149          6.2         3.4          5.4         2.3              0\n",
       "139          6.0         3.0          4.8         1.8              0\n",
       "105          6.5         3.0          5.8         2.2              0\n",
       "116          6.4         3.2          5.3         2.3              0\n",
       "87           6.7         3.1          4.7         1.5              0\n",
       "63           6.0         2.2          4.0         1.0              0\n",
       "137          6.3         3.4          5.6         2.4              0\n",
       "118          7.7         3.8          6.7         2.2              0\n",
       "27           5.0         3.4          1.6         0.4              1\n",
       "66           6.7         3.1          4.4         1.4              0\n",
       "79           6.0         2.9          4.5         1.5              0\n",
       "88           6.3         2.3          4.4         1.3              0\n",
       "36           5.0         3.2          1.2         0.2              1\n",
       "134          6.3         2.8          5.1         1.5              0\n",
       "64           6.1         2.9          4.7         1.4              0\n",
       "86           6.0         3.4          4.5         1.6              0\n",
       "98           6.2         2.9          4.3         1.3              0\n",
       "68           5.8         2.7          4.1         1.0              0\n",
       "93           5.8         2.6          4.0         1.2              0\n",
       "144          6.8         3.2          5.9         2.3              0\n",
       "114          5.7         2.5          5.0         2.0              0\n",
       "107          4.9         2.5          4.5         1.7              0\n",
       "132          7.9         3.8          6.4         2.0              0\n",
       "112          6.4         2.7          5.3         1.9              0\n",
       "45           5.1         3.8          1.9         0.4              1\n",
       "8            5.0         3.4          1.5         0.2              1\n",
       "15           5.8         4.0          1.2         0.2              1\n",
       "140          6.9         3.1          5.4         2.1              0\n",
       "91           5.5         2.6          4.4         1.2              0\n",
       "4            4.6         3.1          1.5         0.2              1\n",
       "109          6.7         2.5          5.8         1.8              0\n",
       "65           5.6         2.9          3.6         1.3              0\n",
       "97           5.7         2.9          4.2         1.3              0\n",
       "44           5.0         3.5          1.6         0.6              1\n",
       "138          6.4         3.1          5.5         1.8              0\n",
       "78           6.7         3.0          5.0         1.7              0\n",
       "42           4.5         2.3          1.3         0.3              1\n",
       "31           4.8         3.1          1.6         0.2              1\n",
       "33           5.2         4.1          1.5         0.1              1\n",
       "17           5.4         3.9          1.3         0.4              1\n",
       "73           6.3         2.5          4.9         1.5              0\n",
       "110          7.2         3.6          6.1         2.5              0\n",
       "72           6.1         2.8          4.0         1.3              0\n",
       "142          6.9         3.1          5.1         2.3              0\n",
       "6            5.4         3.9          1.7         0.4              1\n",
       "21           5.4         3.4          1.7         0.2              1\n",
       "38           4.9         3.6          1.4         0.1              1\n",
       "115          5.8         2.8          5.1         2.4              0\n",
       "39           4.4         3.0          1.3         0.2              1\n",
       "128          6.1         3.0          4.9         1.8              0\n",
       "14           4.3         3.0          1.1         0.1              1\n",
       "126          7.2         3.2          6.0         1.8              0\n",
       "55           6.5         2.8          4.6         1.5              0\n",
       "1            5.1         3.5          1.4         0.2              1\n",
       "150          5.9         3.0          5.1         1.8              0\n",
       "117          6.5         3.0          5.5         1.8              0\n",
       "57           6.3         3.3          4.7         1.6              0\n",
       "    Species.versicolor Species.virginica\n",
       "135                  0                 1\n",
       "40                   0                 0\n",
       "56                   1                 0\n",
       "85                   1                 0\n",
       "133                  0                 1\n",
       "30                   0                 0\n",
       "130                  0                 1\n",
       "136                  0                 1\n",
       "94                   1                 0\n",
       "89                   1                 0\n",
       "9                    0                 0\n",
       "29                   0                 0\n",
       "25                   0                 0\n",
       "95                   1                 0\n",
       "53                   1                 0\n",
       "104                  0                 1\n",
       "67                   1                 0\n",
       "96                   1                 0\n",
       "131                  0                 1\n",
       "50                   0                 0\n",
       "102                  0                 1\n",
       "121                  0                 1\n",
       "28                   0                 0\n",
       "83                   1                 0\n",
       "16                   0                 0\n",
       "34                   0                 0\n",
       "48                   0                 0\n",
       "2                    0                 0\n",
       "47                   0                 0\n",
       "106                  0                 1\n",
       "41                   0                 0\n",
       "58                   1                 0\n",
       "71                   1                 0\n",
       "119                  0                 1\n",
       "22                   0                 0\n",
       "146                  0                 1\n",
       "77                   1                 0\n",
       "90                   1                 0\n",
       "13                   0                 0\n",
       "81                   1                 0\n",
       "46                   0                 0\n",
       "113                  0                 1\n",
       "70                   1                 0\n",
       "84                   1                 0\n",
       "59                   1                 0\n",
       "148                  0                 1\n",
       "127                  0                 1\n",
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       "\n",
       "$net.result\n",
       "$net.result[[1]]\n",
       "                 [,1]            [,2]             [,3]\n",
       "135 -0.00137437681102 0.4936497671436  0.5077048289515\n",
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       "39   1.00060968357911 0.0011342663314 -0.0017072591441\n",
       "128 -0.00139010703671 0.4936574991827  0.5077128262515\n",
       "14   1.00117300935105 0.0008573690376 -0.0019936558735\n",
       "126 -0.00139697332069 0.4936608742377  0.5077163170935\n",
       "55  -0.00125057326941 0.4935889127191  0.5076418868119\n",
       "1    1.00126377120416 0.0008127559332 -0.0020397995068\n",
       "150 -0.00139426207465 0.4936595415512  0.5077149386869\n",
       "117 -0.00139686356619 0.4936608202890  0.5077162612940\n",
       "57  -0.00119864788243 0.4935633893012  0.5076154877694\n",
       "\n",
       "\n",
       "$weights\n",
       "$weights[[1]]\n",
       "$weights[[1]][[1]]\n",
       "              [,1]\n",
       "[1,] -0.7811989145\n",
       "[2,] -0.4596197458\n",
       "[3,] -2.7342934196\n",
       "[4,]  1.7840873053\n",
       "[5,]  8.0124700109\n",
       "\n",
       "$weights[[1]][[2]]\n",
       "             [,1]            [,2]            [,3]\n",
       "[1,]  1.001449280 0.0007215709172 -0.002134112781\n",
       "[2,] -1.002850879 0.4929415769365  0.509852781491\n",
       "\n",
       "\n",
       "\n",
       "$startweights\n",
       "$startweights[[1]]\n",
       "$startweights[[1]][[1]]\n",
       "              [,1]\n",
       "[1,] -0.4248102834\n",
       "[2,] -0.4189800994\n",
       "[3,]  0.9969868609\n",
       "[4,] -0.2757780291\n",
       "[5,]  1.2560188173\n",
       "\n",
       "$startweights[[1]][[2]]\n",
       "             [,1]            [,2]          [,3]\n",
       "[1,] 0.6466743905 -0.873262111744 -0.8808717233\n",
       "[2,] 1.2993123026  0.008370959996  0.5962590166\n",
       "\n",
       "\n",
       "\n",
       "$generalized.weights\n",
       "$generalized.weights[[1]]\n",
       "                   [,1]                 [,2]                [,3]\n",
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       "24    0.604437123152955    3.595816897568414  -2.346219038941258\n",
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       "87   -0.132800912899124   -0.790037124331859   0.515487911476044\n",
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       "137  -0.000028858063925   -0.000171677598742   0.000112017175013\n",
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       "57  -0.00112854128698324  0.00073635703073253  0.00330703469982470\n",
       "\n",
       "\n",
       "$result.matrix\n",
       "                                                1\n",
       "error                            19.7467592721447\n",
       "reached.threshold                 0.0098748732251\n",
       "steps                           819.0000000000000\n",
       "Intercept.to.1layhid1            -0.7811989144552\n",
       "Sepal.Length.to.1layhid1         -0.4596197457923\n",
       "Sepal.Width.to.1layhid1          -2.7342934195619\n",
       "Petal.Length.to.1layhid1          1.7840873052702\n",
       "Petal.Width.to.1layhid1           8.0124700108805\n",
       "Intercept.to.Species.setosa       1.0014492799494\n",
       "1layhid.1.to.Species.setosa      -1.0028508787631\n",
       "Intercept.to.Species.versicolor   0.0007215709172\n",
       "1layhid.1.to.Species.versicolor   0.4929415769365\n",
       "Intercept.to.Species.virginica   -0.0021341127809\n",
       "1layhid.1.to.Species.virginica    0.5098527814907\n",
       "\n",
       "attr(,\"class\")\n",
       "[1] \"nn\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "nn2\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
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