InputAnalysis.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Input Analysis\n",
    "\n",
    "This notebook contains our analysis of the input data ([MovieLens 1M](http://grouplens.org/datasets/movielens/)) to understand the basic demographic distribution before we run experiments."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Setup\n",
    "\n",
    "First, we want to load some libraries."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "Attaching package: 'dplyr'\n",
      "\n",
      "The following objects are masked from 'package:stats':\n",
      "\n",
      "    filter, lag\n",
      "\n",
      "The following objects are masked from 'package:base':\n",
      "\n",
      "    intersect, setdiff, setequal, union\n",
      "\n"
     ]
    }
   ],
   "source": [
    "library(dplyr)\n",
    "library(readr)\n",
    "library(ggplot2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "options(repr.plot.height=5)\n",
    "options(repr.matrix.max.rows=20)\n",
    "options(repr.matrix.max.columns=10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load Data\n",
    "\n",
    "We want to read the ML-1M ratings file:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "ratings = read_delim(\"data/ml-1m/ratings.dat\", delim=\":\",\n",
    "                     col_names=c(\"user\", \"item\", \"rating\", \"timestamp\"),\n",
    "                     col_types=\"i_i_i_i\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>user</th><th scope=col>item</th><th scope=col>rating</th><th scope=col>timestamp</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>1        </td><td>1193     </td><td>5        </td><td>978300760</td></tr>\n",
       "\t<tr><td>1        </td><td> 661     </td><td>3        </td><td>978302109</td></tr>\n",
       "\t<tr><td>1        </td><td> 914     </td><td>3        </td><td>978301968</td></tr>\n",
       "\t<tr><td>1        </td><td>3408     </td><td>4        </td><td>978300275</td></tr>\n",
       "\t<tr><td>1        </td><td>2355     </td><td>5        </td><td>978824291</td></tr>\n",
       "\t<tr><td>1        </td><td>1197     </td><td>3        </td><td>978302268</td></tr>\n",
       "\t<tr><td>1        </td><td>1287     </td><td>5        </td><td>978302039</td></tr>\n",
       "\t<tr><td>1        </td><td>2804     </td><td>5        </td><td>978300719</td></tr>\n",
       "\t<tr><td>1        </td><td> 594     </td><td>4        </td><td>978302268</td></tr>\n",
       "\t<tr><td>1        </td><td> 919     </td><td>4        </td><td>978301368</td></tr>\n",
       "\t<tr><td>...</td><td>...</td><td>...</td><td>...</td></tr>\n",
       "\t<tr><td>6040     </td><td>2022     </td><td>5        </td><td>956716207</td></tr>\n",
       "\t<tr><td>6040     </td><td>2028     </td><td>5        </td><td>956704519</td></tr>\n",
       "\t<tr><td>6040     </td><td>1080     </td><td>4        </td><td>957717322</td></tr>\n",
       "\t<tr><td>6040     </td><td>1089     </td><td>4        </td><td>956704996</td></tr>\n",
       "\t<tr><td>6040     </td><td>1090     </td><td>3        </td><td>956715518</td></tr>\n",
       "\t<tr><td>6040     </td><td>1091     </td><td>1        </td><td>956716541</td></tr>\n",
       "\t<tr><td>6040     </td><td>1094     </td><td>5        </td><td>956704887</td></tr>\n",
       "\t<tr><td>6040     </td><td> 562     </td><td>5        </td><td>956704746</td></tr>\n",
       "\t<tr><td>6040     </td><td>1096     </td><td>4        </td><td>956715648</td></tr>\n",
       "\t<tr><td>6040     </td><td>1097     </td><td>4        </td><td>956715569</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|llll}\n",
       " user & item & rating & timestamp\\\\\n",
       "\\hline\n",
       "\t 1         & 1193      & 5         & 978300760\\\\\n",
       "\t 1         &  661      & 3         & 978302109\\\\\n",
       "\t 1         &  914      & 3         & 978301968\\\\\n",
       "\t 1         & 3408      & 4         & 978300275\\\\\n",
       "\t 1         & 2355      & 5         & 978824291\\\\\n",
       "\t 1         & 1197      & 3         & 978302268\\\\\n",
       "\t 1         & 1287      & 5         & 978302039\\\\\n",
       "\t 1         & 2804      & 5         & 978300719\\\\\n",
       "\t 1         &  594      & 4         & 978302268\\\\\n",
       "\t 1         &  919      & 4         & 978301368\\\\\n",
       "\t ... & ... & ... & ...\\\\\n",
       "\t 6040      & 2022      & 5         & 956716207\\\\\n",
       "\t 6040      & 2028      & 5         & 956704519\\\\\n",
       "\t 6040      & 1080      & 4         & 957717322\\\\\n",
       "\t 6040      & 1089      & 4         & 956704996\\\\\n",
       "\t 6040      & 1090      & 3         & 956715518\\\\\n",
       "\t 6040      & 1091      & 1         & 956716541\\\\\n",
       "\t 6040      & 1094      & 5         & 956704887\\\\\n",
       "\t 6040      &  562      & 5         & 956704746\\\\\n",
       "\t 6040      & 1096      & 4         & 956715648\\\\\n",
       "\t 6040      & 1097      & 4         & 956715569\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "user | item | rating | timestamp | \n",
       "|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n",
       "| 1         | 1193      | 5         | 978300760 | \n",
       "| 1         |  661      | 3         | 978302109 | \n",
       "| 1         |  914      | 3         | 978301968 | \n",
       "| 1         | 3408      | 4         | 978300275 | \n",
       "| 1         | 2355      | 5         | 978824291 | \n",
       "| 1         | 1197      | 3         | 978302268 | \n",
       "| 1         | 1287      | 5         | 978302039 | \n",
       "| 1         | 2804      | 5         | 978300719 | \n",
       "| 1         |  594      | 4         | 978302268 | \n",
       "| 1         |  919      | 4         | 978301368 | \n",
       "| ... | ... | ... | ... | \n",
       "| 6040      | 2022      | 5         | 956716207 | \n",
       "| 6040      | 2028      | 5         | 956704519 | \n",
       "| 6040      | 1080      | 4         | 957717322 | \n",
       "| 6040      | 1089      | 4         | 956704996 | \n",
       "| 6040      | 1090      | 3         | 956715518 | \n",
       "| 6040      | 1091      | 1         | 956716541 | \n",
       "| 6040      | 1094      | 5         | 956704887 | \n",
       "| 6040      |  562      | 5         | 956704746 | \n",
       "| 6040      | 1096      | 4         | 956715648 | \n",
       "| 6040      | 1097      | 4         | 956715569 | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "        user item rating timestamp\n",
       "1       1    1193 5      978300760\n",
       "2       1     661 3      978302109\n",
       "3       1     914 3      978301968\n",
       "4       1    3408 4      978300275\n",
       "5       1    2355 5      978824291\n",
       "6       1    1197 3      978302268\n",
       "7       1    1287 5      978302039\n",
       "8       1    2804 5      978300719\n",
       "9       1     594 4      978302268\n",
       "10      1     919 4      978301368\n",
       "...     ...  ...  ...    ...      \n",
       "1000200 6040 2022 5      956716207\n",
       "1000201 6040 2028 5      956704519\n",
       "1000202 6040 1080 4      957717322\n",
       "1000203 6040 1089 4      956704996\n",
       "1000204 6040 1090 3      956715518\n",
       "1000205 6040 1091 1      956716541\n",
       "1000206 6040 1094 5      956704887\n",
       "1000207 6040  562 5      956704746\n",
       "1000208 6040 1096 4      956715648\n",
       "1000209 6040 1097 4      956715569"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ratings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>user</th><th scope=col>gender</th><th scope=col>age</th><th scope=col>occupation</th><th scope=col>zip</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td> 1   </td><td>F    </td><td>1    </td><td>10   </td><td>48067</td></tr>\n",
       "\t<tr><td> 2   </td><td>M    </td><td>56   </td><td>16   </td><td>70072</td></tr>\n",
       "\t<tr><td> 3   </td><td>M    </td><td>25   </td><td>15   </td><td>55117</td></tr>\n",
       "\t<tr><td> 4   </td><td>M    </td><td>45   </td><td>7    </td><td>02460</td></tr>\n",
       "\t<tr><td> 5   </td><td>M    </td><td>25   </td><td>20   </td><td>55455</td></tr>\n",
       "\t<tr><td> 6   </td><td>F    </td><td>50   </td><td>9    </td><td>55117</td></tr>\n",
       "\t<tr><td> 7   </td><td>M    </td><td>35   </td><td>1    </td><td>06810</td></tr>\n",
       "\t<tr><td> 8   </td><td>M    </td><td>25   </td><td>12   </td><td>11413</td></tr>\n",
       "\t<tr><td> 9   </td><td>M    </td><td>25   </td><td>17   </td><td>61614</td></tr>\n",
       "\t<tr><td>10   </td><td>F    </td><td>35   </td><td>1    </td><td>95370</td></tr>\n",
       "\t<tr><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td></tr>\n",
       "\t<tr><td>6031 </td><td>F    </td><td>18   </td><td>0    </td><td>45123</td></tr>\n",
       "\t<tr><td>6032 </td><td>M    </td><td>45   </td><td>7    </td><td>55108</td></tr>\n",
       "\t<tr><td>6033 </td><td>M    </td><td>50   </td><td>13   </td><td>78232</td></tr>\n",
       "\t<tr><td>6034 </td><td>M    </td><td>25   </td><td>14   </td><td>94117</td></tr>\n",
       "\t<tr><td>6035 </td><td>F    </td><td>25   </td><td>1    </td><td>78734</td></tr>\n",
       "\t<tr><td>6036 </td><td>F    </td><td>25   </td><td>15   </td><td>32603</td></tr>\n",
       "\t<tr><td>6037 </td><td>F    </td><td>45   </td><td>1    </td><td>76006</td></tr>\n",
       "\t<tr><td>6038 </td><td>F    </td><td>56   </td><td>1    </td><td>14706</td></tr>\n",
       "\t<tr><td>6039 </td><td>F    </td><td>45   </td><td>0    </td><td>01060</td></tr>\n",
       "\t<tr><td>6040 </td><td>M    </td><td>25   </td><td>6    </td><td>11106</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lllll}\n",
       " user & gender & age & occupation & zip\\\\\n",
       "\\hline\n",
       "\t  1    & F     & 1     & 10    & 48067\\\\\n",
       "\t  2    & M     & 56    & 16    & 70072\\\\\n",
       "\t  3    & M     & 25    & 15    & 55117\\\\\n",
       "\t  4    & M     & 45    & 7     & 02460\\\\\n",
       "\t  5    & M     & 25    & 20    & 55455\\\\\n",
       "\t  6    & F     & 50    & 9     & 55117\\\\\n",
       "\t  7    & M     & 35    & 1     & 06810\\\\\n",
       "\t  8    & M     & 25    & 12    & 11413\\\\\n",
       "\t  9    & M     & 25    & 17    & 61614\\\\\n",
       "\t 10    & F     & 35    & 1     & 95370\\\\\n",
       "\t ... & ... & ... & ... & ...\\\\\n",
       "\t 6031  & F     & 18    & 0     & 45123\\\\\n",
       "\t 6032  & M     & 45    & 7     & 55108\\\\\n",
       "\t 6033  & M     & 50    & 13    & 78232\\\\\n",
       "\t 6034  & M     & 25    & 14    & 94117\\\\\n",
       "\t 6035  & F     & 25    & 1     & 78734\\\\\n",
       "\t 6036  & F     & 25    & 15    & 32603\\\\\n",
       "\t 6037  & F     & 45    & 1     & 76006\\\\\n",
       "\t 6038  & F     & 56    & 1     & 14706\\\\\n",
       "\t 6039  & F     & 45    & 0     & 01060\\\\\n",
       "\t 6040  & M     & 25    & 6     & 11106\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "user | gender | age | occupation | zip | \n",
       "|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n",
       "|  1    | F     | 1     | 10    | 48067 | \n",
       "|  2    | M     | 56    | 16    | 70072 | \n",
       "|  3    | M     | 25    | 15    | 55117 | \n",
       "|  4    | M     | 45    | 7     | 02460 | \n",
       "|  5    | M     | 25    | 20    | 55455 | \n",
       "|  6    | F     | 50    | 9     | 55117 | \n",
       "|  7    | M     | 35    | 1     | 06810 | \n",
       "|  8    | M     | 25    | 12    | 11413 | \n",
       "|  9    | M     | 25    | 17    | 61614 | \n",
       "| 10    | F     | 35    | 1     | 95370 | \n",
       "| ... | ... | ... | ... | ... | \n",
       "| 6031  | F     | 18    | 0     | 45123 | \n",
       "| 6032  | M     | 45    | 7     | 55108 | \n",
       "| 6033  | M     | 50    | 13    | 78232 | \n",
       "| 6034  | M     | 25    | 14    | 94117 | \n",
       "| 6035  | F     | 25    | 1     | 78734 | \n",
       "| 6036  | F     | 25    | 15    | 32603 | \n",
       "| 6037  | F     | 45    | 1     | 76006 | \n",
       "| 6038  | F     | 56    | 1     | 14706 | \n",
       "| 6039  | F     | 45    | 0     | 01060 | \n",
       "| 6040  | M     | 25    | 6     | 11106 | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "     user gender age occupation zip  \n",
       "1     1   F      1   10         48067\n",
       "2     2   M      56  16         70072\n",
       "3     3   M      25  15         55117\n",
       "4     4   M      45  7          02460\n",
       "5     5   M      25  20         55455\n",
       "6     6   F      50  9          55117\n",
       "7     7   M      35  1          06810\n",
       "8     8   M      25  12         11413\n",
       "9     9   M      25  17         61614\n",
       "10   10   F      35  1          95370\n",
       "...  ...  ...    ... ...        ...  \n",
       "6031 6031 F      18  0          45123\n",
       "6032 6032 M      45  7          55108\n",
       "6033 6033 M      50  13         78232\n",
       "6034 6034 M      25  14         94117\n",
       "6035 6035 F      25  1          78734\n",
       "6036 6036 F      25  15         32603\n",
       "6037 6037 F      45  1          76006\n",
       "6038 6038 F      56  1          14706\n",
       "6039 6039 F      45  0          01060\n",
       "6040 6040 M      25  6          11106"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "users = read_delim(\"data/ml-1m/users.dat\", delim=\":\",\n",
    "                   col_names=c(\"user\", \"gender\", \"age\", \"occupation\", \"zip\"),\n",
    "                   col_types=\"i_c_c_c_c\") %>%\n",
    "    mutate(gender=as.factor(gender),\n",
    "           age=as.factor(age),\n",
    "           occupation=as.factor(occupation))\n",
    "users"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "item.stats = ratings %>%\n",
    "    group_by(item) %>%\n",
    "    summarize(RatingCount=n(),\n",
    "              MeanRating=mean(rating),\n",
    "              MinRating=min(rating),\n",
    "              MaxRating=max(rating)) %>%\n",
    "    mutate(PopRank=rank(-RatingCount))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>item</th><th scope=col>RatingCount</th><th scope=col>MeanRating</th><th scope=col>MinRating</th><th scope=col>MaxRating</th><th scope=col>PopRank</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td> 1      </td><td>2077    </td><td>4.146846</td><td>1       </td><td>5       </td><td>  30.0  </td></tr>\n",
       "\t<tr><td> 2      </td><td> 701    </td><td>3.201141</td><td>1       </td><td>5       </td><td> 394.5  </td></tr>\n",
       "\t<tr><td> 3      </td><td> 478    </td><td>3.016736</td><td>1       </td><td>5       </td><td> 650.0  </td></tr>\n",
       "\t<tr><td> 4      </td><td> 170    </td><td>2.729412</td><td>1       </td><td>5       </td><td>1574.0  </td></tr>\n",
       "\t<tr><td> 5      </td><td> 296    </td><td>3.006757</td><td>1       </td><td>5       </td><td>1067.0  </td></tr>\n",
       "\t<tr><td> 6      </td><td> 940    </td><td>3.878723</td><td>1       </td><td>5       </td><td> 234.0  </td></tr>\n",
       "\t<tr><td> 7      </td><td> 458    </td><td>3.410480</td><td>1       </td><td>5       </td><td> 689.5  </td></tr>\n",
       "\t<tr><td> 8      </td><td>  68    </td><td>3.014706</td><td>1       </td><td>5       </td><td>2290.0  </td></tr>\n",
       "\t<tr><td> 9      </td><td> 102    </td><td>2.656863</td><td>1       </td><td>5       </td><td>1994.0  </td></tr>\n",
       "\t<tr><td>10      </td><td> 888    </td><td>3.540541</td><td>1       </td><td>5       </td><td> 260.0  </td></tr>\n",
       "\t<tr><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td></tr>\n",
       "\t<tr><td>3943    </td><td> 96     </td><td>3.052083</td><td>1       </td><td>5       </td><td>2046.5  </td></tr>\n",
       "\t<tr><td>3944    </td><td>  9     </td><td>2.111111</td><td>1       </td><td>5       </td><td>3273.5  </td></tr>\n",
       "\t<tr><td>3945    </td><td> 43     </td><td>1.488372</td><td>1       </td><td>5       </td><td>2609.5  </td></tr>\n",
       "\t<tr><td>3946    </td><td>100     </td><td>2.260000</td><td>1       </td><td>5       </td><td>2013.0  </td></tr>\n",
       "\t<tr><td>3947    </td><td> 55     </td><td>3.472727</td><td>1       </td><td>5       </td><td>2434.5  </td></tr>\n",
       "\t<tr><td>3948    </td><td>862     </td><td>3.635731</td><td>1       </td><td>5       </td><td> 278.0  </td></tr>\n",
       "\t<tr><td>3949    </td><td>304     </td><td>4.115132</td><td>1       </td><td>5       </td><td>1037.5  </td></tr>\n",
       "\t<tr><td>3950    </td><td> 54     </td><td>3.666667</td><td>1       </td><td>5       </td><td>2449.5  </td></tr>\n",
       "\t<tr><td>3951    </td><td> 40     </td><td>3.900000</td><td>1       </td><td>5       </td><td>2663.5  </td></tr>\n",
       "\t<tr><td>3952    </td><td>388     </td><td>3.780928</td><td>1       </td><td>5       </td><td> 820.0  </td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|llllll}\n",
       " item & RatingCount & MeanRating & MinRating & MaxRating & PopRank\\\\\n",
       "\\hline\n",
       "\t  1       & 2077     & 4.146846 & 1        & 5        &   30.0  \\\\\n",
       "\t  2       &  701     & 3.201141 & 1        & 5        &  394.5  \\\\\n",
       "\t  3       &  478     & 3.016736 & 1        & 5        &  650.0  \\\\\n",
       "\t  4       &  170     & 2.729412 & 1        & 5        & 1574.0  \\\\\n",
       "\t  5       &  296     & 3.006757 & 1        & 5        & 1067.0  \\\\\n",
       "\t  6       &  940     & 3.878723 & 1        & 5        &  234.0  \\\\\n",
       "\t  7       &  458     & 3.410480 & 1        & 5        &  689.5  \\\\\n",
       "\t  8       &   68     & 3.014706 & 1        & 5        & 2290.0  \\\\\n",
       "\t  9       &  102     & 2.656863 & 1        & 5        & 1994.0  \\\\\n",
       "\t 10       &  888     & 3.540541 & 1        & 5        &  260.0  \\\\\n",
       "\t ... & ... & ... & ... & ... & ...\\\\\n",
       "\t 3943     &  96      & 3.052083 & 1        & 5        & 2046.5  \\\\\n",
       "\t 3944     &   9      & 2.111111 & 1        & 5        & 3273.5  \\\\\n",
       "\t 3945     &  43      & 1.488372 & 1        & 5        & 2609.5  \\\\\n",
       "\t 3946     & 100      & 2.260000 & 1        & 5        & 2013.0  \\\\\n",
       "\t 3947     &  55      & 3.472727 & 1        & 5        & 2434.5  \\\\\n",
       "\t 3948     & 862      & 3.635731 & 1        & 5        &  278.0  \\\\\n",
       "\t 3949     & 304      & 4.115132 & 1        & 5        & 1037.5  \\\\\n",
       "\t 3950     &  54      & 3.666667 & 1        & 5        & 2449.5  \\\\\n",
       "\t 3951     &  40      & 3.900000 & 1        & 5        & 2663.5  \\\\\n",
       "\t 3952     & 388      & 3.780928 & 1        & 5        &  820.0  \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "item | RatingCount | MeanRating | MinRating | MaxRating | PopRank | \n",
       "|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n",
       "|  1       | 2077     | 4.146846 | 1        | 5        |   30.0   | \n",
       "|  2       |  701     | 3.201141 | 1        | 5        |  394.5   | \n",
       "|  3       |  478     | 3.016736 | 1        | 5        |  650.0   | \n",
       "|  4       |  170     | 2.729412 | 1        | 5        | 1574.0   | \n",
       "|  5       |  296     | 3.006757 | 1        | 5        | 1067.0   | \n",
       "|  6       |  940     | 3.878723 | 1        | 5        |  234.0   | \n",
       "|  7       |  458     | 3.410480 | 1        | 5        |  689.5   | \n",
       "|  8       |   68     | 3.014706 | 1        | 5        | 2290.0   | \n",
       "|  9       |  102     | 2.656863 | 1        | 5        | 1994.0   | \n",
       "| 10       |  888     | 3.540541 | 1        | 5        |  260.0   | \n",
       "| ... | ... | ... | ... | ... | ... | \n",
       "| 3943     |  96      | 3.052083 | 1        | 5        | 2046.5   | \n",
       "| 3944     |   9      | 2.111111 | 1        | 5        | 3273.5   | \n",
       "| 3945     |  43      | 1.488372 | 1        | 5        | 2609.5   | \n",
       "| 3946     | 100      | 2.260000 | 1        | 5        | 2013.0   | \n",
       "| 3947     |  55      | 3.472727 | 1        | 5        | 2434.5   | \n",
       "| 3948     | 862      | 3.635731 | 1        | 5        |  278.0   | \n",
       "| 3949     | 304      | 4.115132 | 1        | 5        | 1037.5   | \n",
       "| 3950     |  54      | 3.666667 | 1        | 5        | 2449.5   | \n",
       "| 3951     |  40      | 3.900000 | 1        | 5        | 2663.5   | \n",
       "| 3952     | 388      | 3.780928 | 1        | 5        |  820.0   | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "     item RatingCount MeanRating MinRating MaxRating PopRank\n",
       "1     1   2077        4.146846   1         5           30.0 \n",
       "2     2    701        3.201141   1         5          394.5 \n",
       "3     3    478        3.016736   1         5          650.0 \n",
       "4     4    170        2.729412   1         5         1574.0 \n",
       "5     5    296        3.006757   1         5         1067.0 \n",
       "6     6    940        3.878723   1         5          234.0 \n",
       "7     7    458        3.410480   1         5          689.5 \n",
       "8     8     68        3.014706   1         5         2290.0 \n",
       "9     9    102        2.656863   1         5         1994.0 \n",
       "10   10    888        3.540541   1         5          260.0 \n",
       "...  ...  ...         ...        ...       ...       ...    \n",
       "3697 3943  96         3.052083   1         5         2046.5 \n",
       "3698 3944   9         2.111111   1         5         3273.5 \n",
       "3699 3945  43         1.488372   1         5         2609.5 \n",
       "3700 3946 100         2.260000   1         5         2013.0 \n",
       "3701 3947  55         3.472727   1         5         2434.5 \n",
       "3702 3948 862         3.635731   1         5          278.0 \n",
       "3703 3949 304         4.115132   1         5         1037.5 \n",
       "3704 3950  54         3.666667   1         5         2449.5 \n",
       "3705 3951  40         3.900000   1         5         2663.5 \n",
       "3706 3952 388         3.780928   1         5          820.0 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "item.stats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Joining, by = \"item\"\n",
      "Joining, by = \"user\"\n"
     ]
    }
   ],
   "source": [
    "user.stats = ratings %>%\n",
    "    inner_join(item.stats %>% select(item, RatingCount, PopRank)) %>%\n",
    "    group_by(user) %>%\n",
    "    summarize(RatingCount=n(),\n",
    "              MeanRating=mean(rating),\n",
    "              MinRating=min(rating),\n",
    "              MaxRating=max(rating),\n",
    "              MeanPopRank=mean(PopRank),\n",
    "              MedRatingCount=median(RatingCount),\n",
    "              AccountLifetime=max(timestamp) - min(timestamp)) %>%\n",
    "    inner_join(users)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>user</th><th scope=col>RatingCount</th><th scope=col>MeanRating</th><th scope=col>MinRating</th><th scope=col>MaxRating</th><th scope=col>MeanPopRank</th><th scope=col>MedRatingCount</th><th scope=col>AccountLifetime</th><th scope=col>gender</th><th scope=col>age</th><th scope=col>occupation</th><th scope=col>zip</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td> 1      </td><td> 53     </td><td>4.188679</td><td>3       </td><td>5       </td><td>397.9811</td><td> 53     </td><td> 524332 </td><td>F       </td><td>1       </td><td>10      </td><td>48067   </td></tr>\n",
       "\t<tr><td> 2      </td><td>129     </td><td>3.713178</td><td>1       </td><td>5       </td><td>454.5698</td><td>129     </td><td>   2050 </td><td>M       </td><td>56      </td><td>16      </td><td>70072   </td></tr>\n",
       "\t<tr><td> 3      </td><td> 51     </td><td>3.901961</td><td>1       </td><td>5       </td><td>289.4706</td><td> 51     </td><td>   1486 </td><td>M       </td><td>25      </td><td>15      </td><td>55117   </td></tr>\n",
       "\t<tr><td> 4      </td><td> 21     </td><td>4.190476</td><td>1       </td><td>5       </td><td>148.5476</td><td> 21     </td><td>    358 </td><td>M       </td><td>45      </td><td>7       </td><td>02460   </td></tr>\n",
       "\t<tr><td> 5      </td><td>198     </td><td>3.146465</td><td>1       </td><td>5       </td><td>832.9268</td><td>198     </td><td>   5513 </td><td>M       </td><td>25      </td><td>20      </td><td>55455   </td></tr>\n",
       "\t<tr><td> 6      </td><td> 71     </td><td>3.901408</td><td>1       </td><td>5       </td><td>626.2958</td><td> 71     </td><td>   2944 </td><td>F       </td><td>50      </td><td>9       </td><td>55117   </td></tr>\n",
       "\t<tr><td> 7      </td><td> 31     </td><td>4.322581</td><td>3       </td><td>5       </td><td>140.9516</td><td> 31     </td><td>    317 </td><td>M       </td><td>35      </td><td>1       </td><td>06810   </td></tr>\n",
       "\t<tr><td> 8      </td><td>139     </td><td>3.884892</td><td>2       </td><td>5       </td><td>658.2374</td><td>139     </td><td>  18354 </td><td>M       </td><td>25      </td><td>12      </td><td>11413   </td></tr>\n",
       "\t<tr><td> 9      </td><td>106     </td><td>3.735849</td><td>2       </td><td>5       </td><td>356.9528</td><td>106     </td><td>   1819 </td><td>M       </td><td>25      </td><td>17      </td><td>61614   </td></tr>\n",
       "\t<tr><td>10      </td><td>401     </td><td>4.114713</td><td>2       </td><td>5       </td><td>589.1633</td><td>401     </td><td>2414313 </td><td>F       </td><td>35      </td><td>1       </td><td>95370   </td></tr>\n",
       "\t<tr><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td></tr>\n",
       "\t<tr><td>6031    </td><td> 51     </td><td>3.666667</td><td>1       </td><td>5       </td><td>553.0588</td><td> 51     </td><td>    1485</td><td>F       </td><td>18      </td><td>0       </td><td>45123   </td></tr>\n",
       "\t<tr><td>6032    </td><td>104     </td><td>4.134615</td><td>1       </td><td>5       </td><td>564.1731</td><td>104     </td><td>    2338</td><td>M       </td><td>45      </td><td>7       </td><td>55108   </td></tr>\n",
       "\t<tr><td>6033    </td><td> 60     </td><td>3.850000</td><td>1       </td><td>5       </td><td>314.3417</td><td> 60     </td><td>     629</td><td>M       </td><td>50      </td><td>13      </td><td>78232   </td></tr>\n",
       "\t<tr><td>6034    </td><td> 21     </td><td>4.095238</td><td>2       </td><td>5       </td><td>787.2619</td><td> 21     </td><td>     617</td><td>M       </td><td>25      </td><td>14      </td><td>94117   </td></tr>\n",
       "\t<tr><td>6035    </td><td>280     </td><td>2.610714</td><td>1       </td><td>5       </td><td>794.7625</td><td>280     </td><td>    2794</td><td>F       </td><td>25      </td><td>1       </td><td>78734   </td></tr>\n",
       "\t<tr><td>6036    </td><td>888     </td><td>3.302928</td><td>1       </td><td>5       </td><td>954.6430</td><td>888     </td><td>   45847</td><td>F       </td><td>25      </td><td>15      </td><td>32603   </td></tr>\n",
       "\t<tr><td>6037    </td><td>202     </td><td>3.717822</td><td>1       </td><td>5       </td><td>561.6485</td><td>202     </td><td>   92843</td><td>F       </td><td>45      </td><td>1       </td><td>76006   </td></tr>\n",
       "\t<tr><td>6038    </td><td> 20     </td><td>3.800000</td><td>1       </td><td>5       </td><td>482.4250</td><td> 20     </td><td>   10377</td><td>F       </td><td>56      </td><td>1       </td><td>14706   </td></tr>\n",
       "\t<tr><td>6039    </td><td>123     </td><td>3.878049</td><td>2       </td><td>5       </td><td>701.7967</td><td>123     </td><td>   52871</td><td>F       </td><td>45      </td><td>0       </td><td>01060   </td></tr>\n",
       "\t<tr><td>6040    </td><td>341     </td><td>3.577713</td><td>1       </td><td>5       </td><td>719.8065</td><td>341     </td><td>41611123</td><td>M       </td><td>25      </td><td>6       </td><td>11106   </td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|llllllllllll}\n",
       " user & RatingCount & MeanRating & MinRating & MaxRating & MeanPopRank & MedRatingCount & AccountLifetime & gender & age & occupation & zip\\\\\n",
       "\\hline\n",
       "\t  1       &  53      & 4.188679 & 3        & 5        & 397.9811 &  53      &  524332  & F        & 1        & 10       & 48067   \\\\\n",
       "\t  2       & 129      & 3.713178 & 1        & 5        & 454.5698 & 129      &    2050  & M        & 56       & 16       & 70072   \\\\\n",
       "\t  3       &  51      & 3.901961 & 1        & 5        & 289.4706 &  51      &    1486  & M        & 25       & 15       & 55117   \\\\\n",
       "\t  4       &  21      & 4.190476 & 1        & 5        & 148.5476 &  21      &     358  & M        & 45       & 7        & 02460   \\\\\n",
       "\t  5       & 198      & 3.146465 & 1        & 5        & 832.9268 & 198      &    5513  & M        & 25       & 20       & 55455   \\\\\n",
       "\t  6       &  71      & 3.901408 & 1        & 5        & 626.2958 &  71      &    2944  & F        & 50       & 9        & 55117   \\\\\n",
       "\t  7       &  31      & 4.322581 & 3        & 5        & 140.9516 &  31      &     317  & M        & 35       & 1        & 06810   \\\\\n",
       "\t  8       & 139      & 3.884892 & 2        & 5        & 658.2374 & 139      &   18354  & M        & 25       & 12       & 11413   \\\\\n",
       "\t  9       & 106      & 3.735849 & 2        & 5        & 356.9528 & 106      &    1819  & M        & 25       & 17       & 61614   \\\\\n",
       "\t 10       & 401      & 4.114713 & 2        & 5        & 589.1633 & 401      & 2414313  & F        & 35       & 1        & 95370   \\\\\n",
       "\t ... & ... & ... & ... & ... & ... & ... & ... & ... & ... & ... & ...\\\\\n",
       "\t 6031     &  51      & 3.666667 & 1        & 5        & 553.0588 &  51      &     1485 & F        & 18       & 0        & 45123   \\\\\n",
       "\t 6032     & 104      & 4.134615 & 1        & 5        & 564.1731 & 104      &     2338 & M        & 45       & 7        & 55108   \\\\\n",
       "\t 6033     &  60      & 3.850000 & 1        & 5        & 314.3417 &  60      &      629 & M        & 50       & 13       & 78232   \\\\\n",
       "\t 6034     &  21      & 4.095238 & 2        & 5        & 787.2619 &  21      &      617 & M        & 25       & 14       & 94117   \\\\\n",
       "\t 6035     & 280      & 2.610714 & 1        & 5        & 794.7625 & 280      &     2794 & F        & 25       & 1        & 78734   \\\\\n",
       "\t 6036     & 888      & 3.302928 & 1        & 5        & 954.6430 & 888      &    45847 & F        & 25       & 15       & 32603   \\\\\n",
       "\t 6037     & 202      & 3.717822 & 1        & 5        & 561.6485 & 202      &    92843 & F        & 45       & 1        & 76006   \\\\\n",
       "\t 6038     &  20      & 3.800000 & 1        & 5        & 482.4250 &  20      &    10377 & F        & 56       & 1        & 14706   \\\\\n",
       "\t 6039     & 123      & 3.878049 & 2        & 5        & 701.7967 & 123      &    52871 & F        & 45       & 0        & 01060   \\\\\n",
       "\t 6040     & 341      & 3.577713 & 1        & 5        & 719.8065 & 341      & 41611123 & M        & 25       & 6        & 11106   \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "user | RatingCount | MeanRating | MinRating | MaxRating | MeanPopRank | MedRatingCount | AccountLifetime | gender | age | occupation | zip | \n",
       "|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n",
       "|  1       |  53      | 4.188679 | 3        | 5        | 397.9811 |  53      |  524332  | F        | 1        | 10       | 48067    | \n",
       "|  2       | 129      | 3.713178 | 1        | 5        | 454.5698 | 129      |    2050  | M        | 56       | 16       | 70072    | \n",
       "|  3       |  51      | 3.901961 | 1        | 5        | 289.4706 |  51      |    1486  | M        | 25       | 15       | 55117    | \n",
       "|  4       |  21      | 4.190476 | 1        | 5        | 148.5476 |  21      |     358  | M        | 45       | 7        | 02460    | \n",
       "|  5       | 198      | 3.146465 | 1        | 5        | 832.9268 | 198      |    5513  | M        | 25       | 20       | 55455    | \n",
       "|  6       |  71      | 3.901408 | 1        | 5        | 626.2958 |  71      |    2944  | F        | 50       | 9        | 55117    | \n",
       "|  7       |  31      | 4.322581 | 3        | 5        | 140.9516 |  31      |     317  | M        | 35       | 1        | 06810    | \n",
       "|  8       | 139      | 3.884892 | 2        | 5        | 658.2374 | 139      |   18354  | M        | 25       | 12       | 11413    | \n",
       "|  9       | 106      | 3.735849 | 2        | 5        | 356.9528 | 106      |    1819  | M        | 25       | 17       | 61614    | \n",
       "| 10       | 401      | 4.114713 | 2        | 5        | 589.1633 | 401      | 2414313  | F        | 35       | 1        | 95370    | \n",
       "| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | \n",
       "| 6031     |  51      | 3.666667 | 1        | 5        | 553.0588 |  51      |     1485 | F        | 18       | 0        | 45123    | \n",
       "| 6032     | 104      | 4.134615 | 1        | 5        | 564.1731 | 104      |     2338 | M        | 45       | 7        | 55108    | \n",
       "| 6033     |  60      | 3.850000 | 1        | 5        | 314.3417 |  60      |      629 | M        | 50       | 13       | 78232    | \n",
       "| 6034     |  21      | 4.095238 | 2        | 5        | 787.2619 |  21      |      617 | M        | 25       | 14       | 94117    | \n",
       "| 6035     | 280      | 2.610714 | 1        | 5        | 794.7625 | 280      |     2794 | F        | 25       | 1        | 78734    | \n",
       "| 6036     | 888      | 3.302928 | 1        | 5        | 954.6430 | 888      |    45847 | F        | 25       | 15       | 32603    | \n",
       "| 6037     | 202      | 3.717822 | 1        | 5        | 561.6485 | 202      |    92843 | F        | 45       | 1        | 76006    | \n",
       "| 6038     |  20      | 3.800000 | 1        | 5        | 482.4250 |  20      |    10377 | F        | 56       | 1        | 14706    | \n",
       "| 6039     | 123      | 3.878049 | 2        | 5        | 701.7967 | 123      |    52871 | F        | 45       | 0        | 01060    | \n",
       "| 6040     | 341      | 3.577713 | 1        | 5        | 719.8065 | 341      | 41611123 | M        | 25       | 6        | 11106    | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "     user RatingCount MeanRating MinRating MaxRating MeanPopRank MedRatingCount\n",
       "1     1    53         4.188679   3         5         397.9811     53           \n",
       "2     2   129         3.713178   1         5         454.5698    129           \n",
       "3     3    51         3.901961   1         5         289.4706     51           \n",
       "4     4    21         4.190476   1         5         148.5476     21           \n",
       "5     5   198         3.146465   1         5         832.9268    198           \n",
       "6     6    71         3.901408   1         5         626.2958     71           \n",
       "7     7    31         4.322581   3         5         140.9516     31           \n",
       "8     8   139         3.884892   2         5         658.2374    139           \n",
       "9     9   106         3.735849   2         5         356.9528    106           \n",
       "10   10   401         4.114713   2         5         589.1633    401           \n",
       "...  ...  ...         ...        ...       ...       ...         ...           \n",
       "6031 6031  51         3.666667   1         5         553.0588     51           \n",
       "6032 6032 104         4.134615   1         5         564.1731    104           \n",
       "6033 6033  60         3.850000   1         5         314.3417     60           \n",
       "6034 6034  21         4.095238   2         5         787.2619     21           \n",
       "6035 6035 280         2.610714   1         5         794.7625    280           \n",
       "6036 6036 888         3.302928   1         5         954.6430    888           \n",
       "6037 6037 202         3.717822   1         5         561.6485    202           \n",
       "6038 6038  20         3.800000   1         5         482.4250     20           \n",
       "6039 6039 123         3.878049   2         5         701.7967    123           \n",
       "6040 6040 341         3.577713   1         5         719.8065    341           \n",
       "     AccountLifetime gender age occupation zip  \n",
       "1     524332         F      1   10         48067\n",
       "2       2050         M      56  16         70072\n",
       "3       1486         M      25  15         55117\n",
       "4        358         M      45  7          02460\n",
       "5       5513         M      25  20         55455\n",
       "6       2944         F      50  9          55117\n",
       "7        317         M      35  1          06810\n",
       "8      18354         M      25  12         11413\n",
       "9       1819         M      25  17         61614\n",
       "10   2414313         F      35  1          95370\n",
       "...  ...             ...    ... ...        ...  \n",
       "6031     1485        F      18  0          45123\n",
       "6032     2338        M      45  7          55108\n",
       "6033      629        M      50  13         78232\n",
       "6034      617        M      25  14         94117\n",
       "6035     2794        F      25  1          78734\n",
       "6036    45847        F      25  15         32603\n",
       "6037    92843        F      45  1          76006\n",
       "6038    10377        F      56  1          14706\n",
       "6039    52871        F      45  0          01060\n",
       "6040 41611123        M      25  6          11106"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "user.stats"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Basic Stats\n",
    "\n",
    "How much data do we have?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>Users</th><th scope=col>Items</th><th scope=col>Ratings</th><th scope=col>Density</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>6040      </td><td>3706      </td><td>1000209   </td><td>0.04468363</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|llll}\n",
       " Users & Items & Ratings & Density\\\\\n",
       "\\hline\n",
       "\t 6040       & 3706       & 1000209    & 0.04468363\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "Users | Items | Ratings | Density | \n",
       "|---|\n",
       "| 6040       | 3706       | 1000209    | 0.04468363 | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "  Users Items Ratings Density   \n",
       "1 6040  3706  1000209 0.04468363"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data.frame(Users=nrow(user.stats),\n",
    "           Items=nrow(item.stats),\n",
    "           Ratings=nrow(ratings)) %>%\n",
    "    mutate(Density=Ratings / (Users * Items))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Start looking at demographic splits:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "ggplot(users) +\n",
    "    aes(x=gender,fill=dataset) +\n",
    "    geom_bar()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {},
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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YLVYSBFqgEpUrA6DKRINSBFClaHgRSp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\nRU5ErkJggg==",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ggplot(users) +\n",
    "    aes(x=age) +\n",
    "    geom_bar()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "What are the statistics of users per zip code?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. \n",
       "  1.000   1.000   1.000   1.756   2.000  19.000 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "zips = users %>%\n",
    "    group_by(zip) %>%\n",
    "    summarize(nusers=n())\n",
    "summary(zips$nusers)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {},
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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elqIQmJOrVZSFFabHe6WkhCok5tFlKU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",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ggplot(zips) +\n",
    "    aes(x=nusers) +\n",
    "    geom_histogram(binwidth=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Per region?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. \n",
       "  1.000   2.000   4.000   8.909   9.000 172.000 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "regions = users %>%\n",
    "    mutate(region=substr(zip, 1, 3)) %>%\n",
    "    group_by(region) %>%\n",
    "    summarize(nusers=n())\n",
    "summary(regions$nusers)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {},
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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D8/2SCk1goz6opbQnr6igZf2eACgxT9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",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ggplot(regions) +\n",
    "    aes(x=nusers) +\n",
    "    geom_histogram(binwidth=5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Per-demographic rating statistics"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Do different groups have more ratings?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Gender"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>gender</th><th scope=col>NUsers</th><th scope=col>MeanRatingCount</th><th scope=col>RCErr</th><th scope=col>MeanAvgRating</th><th scope=col>AvgRatingErr</th><th scope=col>MeanPop</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>F         </td><td>1709      </td><td>144.2013  </td><td>4.088308  </td><td>3.729465  </td><td>0.01000872</td><td>616.8265  </td></tr>\n",
       "\t<tr><td>M         </td><td>4331      </td><td>174.0404  </td><td>3.050227  </td><td>3.692145  </td><td>0.00661471</td><td>565.9058  </td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lllllll}\n",
       " gender & NUsers & MeanRatingCount & RCErr & MeanAvgRating & AvgRatingErr & MeanPop\\\\\n",
       "\\hline\n",
       "\t F          & 1709       & 144.2013   & 4.088308   & 3.729465   & 0.01000872 & 616.8265  \\\\\n",
       "\t M          & 4331       & 174.0404   & 3.050227   & 3.692145   & 0.00661471 & 565.9058  \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "gender | NUsers | MeanRatingCount | RCErr | MeanAvgRating | AvgRatingErr | MeanPop | \n",
       "|---|---|\n",
       "| F          | 1709       | 144.2013   | 4.088308   | 3.729465   | 0.01000872 | 616.8265   | \n",
       "| M          | 4331       | 174.0404   | 3.050227   | 3.692145   | 0.00661471 | 565.9058   | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "  gender NUsers MeanRatingCount RCErr    MeanAvgRating AvgRatingErr MeanPop \n",
       "1 F      1709   144.2013        4.088308 3.729465      0.01000872   616.8265\n",
       "2 M      4331   174.0404        3.050227 3.692145      0.00661471   565.9058"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "gender.stats = user.stats %>%\n",
    "    group_by(gender) %>%\n",
    "    summarize(NUsers=n(),\n",
    "              MeanRatingCount=mean(RatingCount),\n",
    "              RCErr=sd(RatingCount) / sqrt(n()),\n",
    "              MeanAvgRating=mean(MeanRating),\n",
    "              AvgRatingErr=sd(MeanRating) / sqrt(n()),\n",
    "              MeanPop=mean(MeanPopRank))\n",
    "gender.stats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {},
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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leHxBuNjY5oXZQat4bEG40NjWhdlBpX\nh8QbjY2OaF2UGleHxBuNjY5oXZQaV4fEG42NjmhdlBrXh6RQrqB3arGI1kWpMUOKRbQuSo0b\nQ7q9OnybdNLbUShX0Du1WETrotS4OqSnzcuzGgo/kB0V0booNa4O6brsDj9DuuMHsqMiWhel\nxtUhHX5+9PY/hjQionVRasyQYhGti1Lj6pBe79rt+IHsqIjWRalxdUhPry+0upzyEijKFfRO\nLRbRuig1rg5pv7/ZlLLZnfSiXMoV9E4tFtG6KDVuDEmgXEHv1GIRrYtSY4YUi2hdlBofH9JS\nCi/HNTqidVFqfHxIVwxpfETrotT4+JBuy+bmlKcGMaQOiNZFqfHxIT1eH+7cXd+d+jr6yhX0\nTi0W0booNT4+pGcPh0e/y/aGZ3+PimhdlBpXh/Ts8fbwu+YLQxoT0booNW4N6dnTFQ82jIpo\nXZQat4bELdLQiNZFqXF1SK/fI92e9G5jyhX0Ti0W0booNT4+pJdH7Zbrex61GxjRuig1Pj4k\nfo4UgGhdlBofHxLPbAhAtC5KjY8PiefaBSBaF6XGx4ekUq6gd2qxiNZFqTFDikW0LkqNGVIs\nonVRasyQYhGti1JjhhSLaF2UGjOkWETrotSYIcUiWhelxgwpFtG6KDVmSLGI1kWpMUOKRbQu\nSo0ZUiyidVFqzJBiEa2LUmOGFItoXZQaM6RYROui1JghxSJaF6XGDCkW0booNWZIsYjWRakx\nQ4pFtC5KjRlSLKJ1UWrMkGIRrYtSY4YUi2hdlBozpFhE66LUmCHFIloXpcYMKRbRuig1Zkix\niNZFqTFDikW0LkqNGVIsonVRasyQYhGti1JjhhSLaF2UGjOkWETrotRYHdJy8PqRIXVBtC5K\njeUhffjwviTlCnqnFotoXZQaM6RYROui1Fgc0vLxI0PqgmhdlBqrQ3r7Ful9SP89O+Vf8aZ3\narGI1kWp8bvTb5EWbpF6IloXpcbikN7WxJD6IVoXpcYMKRbRuig1FofEXbv+iNZFqfEPhvTp\nwQaGdGZE66LUWBzSn2c08MyGbojWRamxOqTjlCvonVosonVRasyQYhGti1JjhhSLaF2UGjOk\nWETrotSYIcUiWhelxgwpFtG6KDVmSLGI1kWpMUOKRbQuSo0ZUiyidVFqzJBiEa2LUmOGFIto\nXZQaM6RYROui1JghxSJaF6XGDCkW0booNWZIsYjWRakxQ4pFtC5KjRlSLKJ1UWrMkGIRrYtS\nY4YUi2hdlBozpFhE66LUmCHFIloXpcYMKRbRuig1ZkixiNZFqTFDikW0LkqNGVIsonVRasyQ\nYhGti1JjhhSLaF2UGjOkWETrotSYIcUiWhelxgwpFtG6KDVmSLGI1kWpMUOKRbQuSo0ZUiyi\ndVFqzJBiEa2LUmOGFItoXZQaM6RYROui1JghxSJaF6XGDCkW0booNWZIsYjWRakxQ4pFtC5K\njRlSLKJ1UWrMkGIRrYtSY4YUi2hdlBozpFhE66LUmCHFIloXpcYMKRbRuig1ZkixiNZFqTFD\nikW0LkqNGVIsonVRasyQYhGti1JjhhSLaF2UGjOkWETrotSYIcUiWhelxgwpFtG6KDVmSLGI\n1kWpMUOKRbQuSo0ZUiyidVFqzJBiEa2LUmOGFItoXZQaM6RYROui1JghxSJaF6XGDCkW0boo\nNV53SIreqcUiWpefFZpbpDBE66LUmCHFIloXpcYMKRbRuig1ZkixiNZFqTFDikW0LkqNGVIs\nonVRasyQYhGti1JjhhSLaF2UGjOkWETrotSYIcUiWhelxgwpFtG6KDVmSLGI1kWpMUOKRbQu\nSo0ZUiyidVFqzJBiEa2LUmOGFItoXZQaM6RYROui1JghxSJaF6XGDCkW0booNWZIsYjWRakx\nQ4pFtC5KjRlSLKJ1UWrMkGIRrYtSY4YUi2hdlBozpFhE66LUmCHFIloXpcYMKRbRuig1Zkix\niNZFqTFDikW0LkqNGVIsonVRasyQYhGti1JjhhSLaF2UGjOkWETrotSYIcUiWhelxgwpFtG6\nKDVmSLGI1kWpMUOKRbQuSo0ZUiyidVFqzJBiEa2LUmOGFItoXZQaM6RYROui1JghxSJaF6XG\nDCkW0booNWZIsYjWRakxQ4pFtC5KjRlSLKJ1UWrMkGIRrYtSY4YUi2hdlBozpFhE66LUmCHF\nIloXpcYMKRbRuig1ZkixiNZFqTFDikW0LkqNGVIsonVRasyQYhGti1JjhhSLaF2UGjOkWETr\notSYIcUiWhelxgwpFtG6KDVmSLGI1kWpMUOKRbQuSo0ZUiyidVFqzJBiEa2LUuOfDml5xpC6\nIFoXpcY/HNLy5w+GdG5E66LUmCHFIloXpcYMKRbRuig1Xm9I/z1T/hXAVHrdIo1sugONY7Zo\nGVLLdAcax2zRMqSW6Q40jtmiZUgt0x1oHLNFy5BapjvQOGaL9odDWuGZDSOb7kDjmC3anw7p\nb71Ps7bpDjSO2aJlSC3THWgcs0XLkFqmO9A4ZouWIbVMd6BxzBYtQ2qZ7kDjmC1ahtQy3YHG\nMVu0DKllugONY7ZoGVLLdAcax2zRMqSW6Q40jtmiZUgt0x1oHLNFy5BapjvQOGaLliG1THeg\nccwWLUNqme5A45gtWobUMt2BxjFbtAypZboDjWO2aBlSy3QHGsds0TKklukONI7ZomVILdMd\naByzRbvukGbDK17azBstQ/rXvF/t7uaNliH9a96vdnfzRsuQ/jXvV7u7eaNlSMAKGBKwAoYE\nrIAhAStgSMAKGBKwAob0t+W33pcxoeXTx8kwpL9N+mUewOt/nWb9jxRD+tukX+YBMKSLMumX\neQDLS7bLrAkzpL9N+mUeAEO6KDzW4MKQLsqkX+YBLK8rmjRhhvS3Sb/MA2BIF2XSL/MAGNJF\nmfTLPIDlw/8mxJD+NumXeQAMCcBXGBKwAoYErIAhAStgSMAKGBKwAoYErIAhAStgSMAKGBKw\nAoY0jcLXsiPCnwZD6onwp8GQeiL8DI/bsrl/mcrTdSnXT/vDcB6vyrJ7/ezV/vNnfy3bnld8\nYRhShKelvHj+68vfNvvDVF7+unv97NXnz27Ldd+LvigMKcJN2e6ftoep3ByWsyu3L1N52t+W\n5fCPxz67633RF4UhRdiUx+c7cIepbF6+Ys/35A537fa/vzOqfxbnwpAi/H4g4fBnKW938j7+\nf7XP4lyIOwJDGh1xR/h85+3gfT71z+JciDvC4eGE/cvDCbvDgwh3h398H9LN4WGHo5/FuRB3\nhPeHv1//9uvjkN4f/v78WZwLcWc4/ED27mUcj9elbB/2H4e0f7x6+4Hsp8/iXIg7SJn0NeFm\nwJAilPJw+AaIpyoMiyFF2P3+FomfsQ6LIWW43ZRyzY7GxZCAFTAkYAUMCVgBQwJWwJCAFTAk\nYAUMCVgBQwJW8P8sxX+osDB74wAAAABJRU5ErkJggg==",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ggplot(gender.stats) +\n",
    "    aes(x=gender, y=MeanRatingCount, \n",
    "        ymin=MeanRatingCount-RCErr,\n",
    "        ymax=MeanRatingCount+RCErr) +\n",
    "    geom_bar(stat=\"identity\") + geom_errorbar(width=0.2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {},
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ggplot(gender.stats) +\n",
    "    aes(x=gender, y=MeanAvgRating, \n",
    "        ymin=MeanAvgRating-AvgRatingErr,\n",
    "        ymax=MeanAvgRating+AvgRatingErr) +\n",
    "    geom_bar(stat=\"identity\") + geom_errorbar(width=0.2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, let's examine popularity preference."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {},
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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gulxv0iWXx6g0jLQ7ReKDUeKdINRIoA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\nrkJggg==",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ggplot(gender.stats) +\n",
    "    aes(x=gender, y=MeanPop) +\n",
    "    geom_bar(stat=\"identity\") +\n",
    "    ylab(\"Mean Average Popularity (lower is more popular)\") +\n",
    "    ggtitle(\"Popularity Preference by Gender\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Male users - of which there are considerably more - tend to rate more popular movies. This is expected - the dominant group's movies will, by nature, be more popular - but it does document that demographics and popularity will confound."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Age"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>age</th><th scope=col>NUsers</th><th scope=col>MeanRatingCount</th><th scope=col>RCErr</th><th scope=col>MeanAvgRating</th><th scope=col>AvgRatingErr</th><th scope=col>MeanPop</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>1          </td><td> 222       </td><td>122.5721   </td><td>9.222686   </td><td>3.621055   </td><td>0.031579911</td><td>646.8739   </td></tr>\n",
       "\t<tr><td>18         </td><td>1103       </td><td>166.3971   </td><td>5.523255   </td><td>3.620671   </td><td>0.013457093</td><td>554.2323   </td></tr>\n",
       "\t<tr><td>25         </td><td>2096       </td><td>188.7195   </td><td>4.549564   </td><td>3.667680   </td><td>0.009041619</td><td>551.3487   </td></tr>\n",
       "\t<tr><td>35         </td><td>1193       </td><td>166.8089   </td><td>5.748490   </td><td>3.743372   </td><td>0.011960702</td><td>572.7603   </td></tr>\n",
       "\t<tr><td>45         </td><td> 550       </td><td>152.0600   </td><td>8.180004   </td><td>3.770965   </td><td>0.017591735</td><td>620.9656   </td></tr>\n",
       "\t<tr><td>50         </td><td> 496       </td><td>146.1492   </td><td>8.069795   </td><td>3.795452   </td><td>0.018509621</td><td>630.7887   </td></tr>\n",
       "\t<tr><td>56         </td><td> 380       </td><td>102.0526   </td><td>6.275718   </td><td>3.834176   </td><td>0.023388193</td><td>675.8898   </td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lllllll}\n",
       " age & NUsers & MeanRatingCount & RCErr & MeanAvgRating & AvgRatingErr & MeanPop\\\\\n",
       "\\hline\n",
       "\t 1           &  222        & 122.5721    & 9.222686    & 3.621055    & 0.031579911 & 646.8739   \\\\\n",
       "\t 18          & 1103        & 166.3971    & 5.523255    & 3.620671    & 0.013457093 & 554.2323   \\\\\n",
       "\t 25          & 2096        & 188.7195    & 4.549564    & 3.667680    & 0.009041619 & 551.3487   \\\\\n",
       "\t 35          & 1193        & 166.8089    & 5.748490    & 3.743372    & 0.011960702 & 572.7603   \\\\\n",
       "\t 45          &  550        & 152.0600    & 8.180004    & 3.770965    & 0.017591735 & 620.9656   \\\\\n",
       "\t 50          &  496        & 146.1492    & 8.069795    & 3.795452    & 0.018509621 & 630.7887   \\\\\n",
       "\t 56          &  380        & 102.0526    & 6.275718    & 3.834176    & 0.023388193 & 675.8898   \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "age | NUsers | MeanRatingCount | RCErr | MeanAvgRating | AvgRatingErr | MeanPop | \n",
       "|---|---|---|---|---|---|---|\n",
       "| 1           |  222        | 122.5721    | 9.222686    | 3.621055    | 0.031579911 | 646.8739    | \n",
       "| 18          | 1103        | 166.3971    | 5.523255    | 3.620671    | 0.013457093 | 554.2323    | \n",
       "| 25          | 2096        | 188.7195    | 4.549564    | 3.667680    | 0.009041619 | 551.3487    | \n",
       "| 35          | 1193        | 166.8089    | 5.748490    | 3.743372    | 0.011960702 | 572.7603    | \n",
       "| 45          |  550        | 152.0600    | 8.180004    | 3.770965    | 0.017591735 | 620.9656    | \n",
       "| 50          |  496        | 146.1492    | 8.069795    | 3.795452    | 0.018509621 | 630.7887    | \n",
       "| 56          |  380        | 102.0526    | 6.275718    | 3.834176    | 0.023388193 | 675.8898    | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "  age NUsers MeanRatingCount RCErr    MeanAvgRating AvgRatingErr MeanPop \n",
       "1 1    222   122.5721        9.222686 3.621055      0.031579911  646.8739\n",
       "2 18  1103   166.3971        5.523255 3.620671      0.013457093  554.2323\n",
       "3 25  2096   188.7195        4.549564 3.667680      0.009041619  551.3487\n",
       "4 35  1193   166.8089        5.748490 3.743372      0.011960702  572.7603\n",
       "5 45   550   152.0600        8.180004 3.770965      0.017591735  620.9656\n",
       "6 50   496   146.1492        8.069795 3.795452      0.018509621  630.7887\n",
       "7 56   380   102.0526        6.275718 3.834176      0.023388193  675.8898"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "age.stats = user.stats %>%\n",
    "    group_by(age) %>%\n",
    "    summarize(NUsers=n(),\n",
    "              MeanRatingCount=mean(RatingCount),\n",
    "              RCErr=sd(RatingCount) / sqrt(n()),\n",
    "              MeanAvgRating=mean(MeanRating),\n",
    "              AvgRatingErr=sd(MeanRating) / sqrt(n()),\n",
    "              MeanPop=mean(MeanPopRank))\n",
    "age.stats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {},
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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0safj7ujoZPf+0lkZB2J9Um0s1wd7wb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\ne7PgAAAAAElFTkSuQmCC",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ggplot(age.stats) +\n",
    "    aes(x=age, y=MeanRatingCount, \n",
    "        ymin=MeanRatingCount-RCErr,\n",
    "        ymax=MeanRatingCount+RCErr) +\n",
    "    geom_bar(stat=\"identity\") + geom_errorbar(width=0.2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {},
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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pC0LSCZtoCkbQHJtAUkbQtIpi0gaVtA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\nAAAASUVORK5CYII=",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ggplot(age.stats) +\n",
    "    aes(x=age, y=MeanAvgRating, \n",
    "        ymin=MeanAvgRating-AvgRatingErr,\n",
    "        ymax=MeanAvgRating+AvgRatingErr) +\n",
    "    geom_bar(stat=\"identity\") + geom_errorbar(width=0.2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {},
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ggplot(age.stats) +\n",
    "    aes(x=age, y=MeanPop) +\n",
    "    geom_bar(stat=\"identity\") +\n",
    "    ylab(\"Mean Average Popularity (lower is more popular)\") +\n",
    "    ggtitle(\"Popularity Preference by Age\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We see the same issue here - dominant age brackets like more popular stuff."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## Intersections\n",
    "\n",
    "Let's look at both age and gender."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "cross.stats = user.stats %>%\n",
    "    group_by(age, gender) %>%\n",
    "    summarize(nusers=n(),\n",
    "              MeanCount=mean(RatingCount),\n",
    "              MeanAvgRating=mean(MeanRating))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {},
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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4YSSCB1BekDa7VhKIEEUleQPqBWG4YS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\nYII=",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ggplot(cross.stats) +\n",
    "    aes(x=age, y=gender, fill=nusers) +\n",
    "    geom_tile()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {},
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ggplot(cross.stats) +\n",
    "    aes(x=age, y=gender, fill=MeanCount) +\n",
    "    geom_tile()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {},
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ggplot(cross.stats) +\n",
    "    aes(x=age, y=gender, fill=MeanAvgRating) +\n",
    "    geom_tile()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "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": "3.3.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}