quick_look.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "import pandas as pd\n",
    "\n",
    "r = pd.read_csv( 'ratings.csv' )\n",
    "tr = pd.read_csv( 'to_read.csv' )\n",
    "b = pd.read_csv( 'books.csv' )\n",
    "\n",
    "t = pd.read_csv( 'tags.csv' )\n",
    "bt = pd.read_csv( 'book_tags.csv')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Ratings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>user_id</th>\n",
       "      <th>book_id</th>\n",
       "      <th>rating</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>258</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>4081</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>260</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2</td>\n",
       "      <td>9296</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2</td>\n",
       "      <td>2318</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   user_id  book_id  rating\n",
       "0        1      258       5\n",
       "1        2     4081       4\n",
       "2        2      260       5\n",
       "3        2     9296       5\n",
       "4        2     2318       3"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Ratings are sorted chronologically, oldest first."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5976479"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(r)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0xa82c1d0>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0xa7fedd8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "r.rating.hist( bins = 5 )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It appears that 4 is the most popular rating. There are relatively few ones and twos."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### To read\n",
    "These are the books users marked \"to read\".\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>user_id</th>\n",
       "      <th>book_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>9</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>15</td>\n",
       "      <td>398</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>15</td>\n",
       "      <td>275</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>37</td>\n",
       "      <td>7173</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>34</td>\n",
       "      <td>380</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   user_id  book_id\n",
       "0        9        8\n",
       "1       15      398\n",
       "2       15      275\n",
       "3       37     7173\n",
       "4       34      380"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tr.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "912705"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(tr)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Most books have been marked to read by somebody. Majority of the users have some books marked to read."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "9986"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(tr.book_id.unique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "48871"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(tr.user_id.unique())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Books"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>book_id</th>\n",
       "      <th>goodreads_book_id</th>\n",
       "      <th>best_book_id</th>\n",
       "      <th>work_id</th>\n",
       "      <th>books_count</th>\n",
       "      <th>isbn</th>\n",
       "      <th>isbn13</th>\n",
       "      <th>authors</th>\n",
       "      <th>original_publication_year</th>\n",
       "      <th>original_title</th>\n",
       "      <th>...</th>\n",
       "      <th>ratings_count</th>\n",
       "      <th>work_ratings_count</th>\n",
       "      <th>work_text_reviews_count</th>\n",
       "      <th>ratings_1</th>\n",
       "      <th>ratings_2</th>\n",
       "      <th>ratings_3</th>\n",
       "      <th>ratings_4</th>\n",
       "      <th>ratings_5</th>\n",
       "      <th>image_url</th>\n",
       "      <th>small_image_url</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2767052</td>\n",
       "      <td>2767052</td>\n",
       "      <td>2792775</td>\n",
       "      <td>272</td>\n",
       "      <td>439023483</td>\n",
       "      <td>9.780439e+12</td>\n",
       "      <td>Suzanne Collins</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>The Hunger Games</td>\n",
       "      <td>...</td>\n",
       "      <td>4780653</td>\n",
       "      <td>4942365</td>\n",
       "      <td>155254</td>\n",
       "      <td>66715</td>\n",
       "      <td>127936</td>\n",
       "      <td>560092</td>\n",
       "      <td>1481305</td>\n",
       "      <td>2706317</td>\n",
       "      <td>https://images.gr-assets.com/books/1447303603m...</td>\n",
       "      <td>https://images.gr-assets.com/books/1447303603s...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>4640799</td>\n",
       "      <td>491</td>\n",
       "      <td>439554934</td>\n",
       "      <td>9.780440e+12</td>\n",
       "      <td>J.K. Rowling, Mary GrandPré</td>\n",
       "      <td>1997.0</td>\n",
       "      <td>Harry Potter and the Philosopher's Stone</td>\n",
       "      <td>...</td>\n",
       "      <td>4602479</td>\n",
       "      <td>4800065</td>\n",
       "      <td>75867</td>\n",
       "      <td>75504</td>\n",
       "      <td>101676</td>\n",
       "      <td>455024</td>\n",
       "      <td>1156318</td>\n",
       "      <td>3011543</td>\n",
       "      <td>https://images.gr-assets.com/books/1474154022m...</td>\n",
       "      <td>https://images.gr-assets.com/books/1474154022s...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>41865</td>\n",
       "      <td>41865</td>\n",
       "      <td>3212258</td>\n",
       "      <td>226</td>\n",
       "      <td>316015849</td>\n",
       "      <td>9.780316e+12</td>\n",
       "      <td>Stephenie Meyer</td>\n",
       "      <td>2005.0</td>\n",
       "      <td>Twilight</td>\n",
       "      <td>...</td>\n",
       "      <td>3866839</td>\n",
       "      <td>3916824</td>\n",
       "      <td>95009</td>\n",
       "      <td>456191</td>\n",
       "      <td>436802</td>\n",
       "      <td>793319</td>\n",
       "      <td>875073</td>\n",
       "      <td>1355439</td>\n",
       "      <td>https://images.gr-assets.com/books/1361039443m...</td>\n",
       "      <td>https://images.gr-assets.com/books/1361039443s...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>2657</td>\n",
       "      <td>2657</td>\n",
       "      <td>3275794</td>\n",
       "      <td>487</td>\n",
       "      <td>61120081</td>\n",
       "      <td>9.780061e+12</td>\n",
       "      <td>Harper Lee</td>\n",
       "      <td>1960.0</td>\n",
       "      <td>To Kill a Mockingbird</td>\n",
       "      <td>...</td>\n",
       "      <td>3198671</td>\n",
       "      <td>3340896</td>\n",
       "      <td>72586</td>\n",
       "      <td>60427</td>\n",
       "      <td>117415</td>\n",
       "      <td>446835</td>\n",
       "      <td>1001952</td>\n",
       "      <td>1714267</td>\n",
       "      <td>https://images.gr-assets.com/books/1361975680m...</td>\n",
       "      <td>https://images.gr-assets.com/books/1361975680s...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>4671</td>\n",
       "      <td>4671</td>\n",
       "      <td>245494</td>\n",
       "      <td>1356</td>\n",
       "      <td>743273567</td>\n",
       "      <td>9.780743e+12</td>\n",
       "      <td>F. Scott Fitzgerald</td>\n",
       "      <td>1925.0</td>\n",
       "      <td>The Great Gatsby</td>\n",
       "      <td>...</td>\n",
       "      <td>2683664</td>\n",
       "      <td>2773745</td>\n",
       "      <td>51992</td>\n",
       "      <td>86236</td>\n",
       "      <td>197621</td>\n",
       "      <td>606158</td>\n",
       "      <td>936012</td>\n",
       "      <td>947718</td>\n",
       "      <td>https://images.gr-assets.com/books/1490528560m...</td>\n",
       "      <td>https://images.gr-assets.com/books/1490528560s...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 23 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   book_id  goodreads_book_id  best_book_id  work_id  books_count       isbn  \\\n",
       "0        1            2767052       2767052  2792775          272  439023483   \n",
       "1        2                  3             3  4640799          491  439554934   \n",
       "2        3              41865         41865  3212258          226  316015849   \n",
       "3        4               2657          2657  3275794          487   61120081   \n",
       "4        5               4671          4671   245494         1356  743273567   \n",
       "\n",
       "         isbn13                      authors  original_publication_year  \\\n",
       "0  9.780439e+12              Suzanne Collins                     2008.0   \n",
       "1  9.780440e+12  J.K. Rowling, Mary GrandPré                     1997.0   \n",
       "2  9.780316e+12              Stephenie Meyer                     2005.0   \n",
       "3  9.780061e+12                   Harper Lee                     1960.0   \n",
       "4  9.780743e+12          F. Scott Fitzgerald                     1925.0   \n",
       "\n",
       "                             original_title  \\\n",
       "0                          The Hunger Games   \n",
       "1  Harry Potter and the Philosopher's Stone   \n",
       "2                                  Twilight   \n",
       "3                     To Kill a Mockingbird   \n",
       "4                          The Great Gatsby   \n",
       "\n",
       "                         ...                         ratings_count  \\\n",
       "0                        ...                               4780653   \n",
       "1                        ...                               4602479   \n",
       "2                        ...                               3866839   \n",
       "3                        ...                               3198671   \n",
       "4                        ...                               2683664   \n",
       "\n",
       "  work_ratings_count  work_text_reviews_count  ratings_1  ratings_2  \\\n",
       "0            4942365                   155254      66715     127936   \n",
       "1            4800065                    75867      75504     101676   \n",
       "2            3916824                    95009     456191     436802   \n",
       "3            3340896                    72586      60427     117415   \n",
       "4            2773745                    51992      86236     197621   \n",
       "\n",
       "   ratings_3  ratings_4  ratings_5  \\\n",
       "0     560092    1481305    2706317   \n",
       "1     455024    1156318    3011543   \n",
       "2     793319     875073    1355439   \n",
       "3     446835    1001952    1714267   \n",
       "4     606158     936012     947718   \n",
       "\n",
       "                                           image_url  \\\n",
       "0  https://images.gr-assets.com/books/1447303603m...   \n",
       "1  https://images.gr-assets.com/books/1474154022m...   \n",
       "2  https://images.gr-assets.com/books/1361039443m...   \n",
       "3  https://images.gr-assets.com/books/1361975680m...   \n",
       "4  https://images.gr-assets.com/books/1490528560m...   \n",
       "\n",
       "                                     small_image_url  \n",
       "0  https://images.gr-assets.com/books/1447303603s...  \n",
       "1  https://images.gr-assets.com/books/1474154022s...  \n",
       "2  https://images.gr-assets.com/books/1361039443s...  \n",
       "3  https://images.gr-assets.com/books/1361975680s...  \n",
       "4  https://images.gr-assets.com/books/1490528560s...  \n",
       "\n",
       "[5 rows x 23 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "b.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Books are sorted by their popularity, as measured by number of ratings (overall, not in this dataset)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10000"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(b)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### User and book IDs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "53424"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r.user_id.max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10000"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r.book_id.max()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The IDs are contiguous."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "assert( len( r.user_id.unique()) == r.user_id.max())\n",
    "assert( len( r.book_id.unique()) == r.book_id.max())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Reviews per book"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Most books have a few hundred reviews, but some have as few as eight."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    10000.000000\n",
       "mean       597.647900\n",
       "std       1267.289788\n",
       "min          8.000000\n",
       "25%        155.000000\n",
       "50%        248.000000\n",
       "75%        503.000000\n",
       "max      22806.000000\n",
       "Name: book_id, dtype: float64"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "reviews_per_book = r.groupby( 'book_id' ).book_id.apply( lambda x: len( x ))\n",
    "reviews_per_book.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "book_id\n",
       "7803     8\n",
       "9345    11\n",
       "9486    24\n",
       "1935    33\n",
       "9315    36\n",
       "9553    41\n",
       "8181    45\n",
       "9479    48\n",
       "9260    48\n",
       "9705    50\n",
       "Name: book_id, dtype: int64"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "reviews_per_book.sort_values().head( 10 )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Reviews per user"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "All users have at least 19 reviews."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    53424.000000\n",
       "mean       111.868804\n",
       "std         26.071224\n",
       "min         19.000000\n",
       "25%         96.000000\n",
       "50%        111.000000\n",
       "75%        128.000000\n",
       "max        200.000000\n",
       "Name: user_id, dtype: float64"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "reviews_per_user = r.groupby( 'user_id' ).user_id.apply( lambda x: len( x ))\n",
    "reviews_per_user.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "user_id\n",
       "34590    19\n",
       "43675    20\n",
       "40753    21\n",
       "51725    21\n",
       "32128    21\n",
       "37640    22\n",
       "16470    22\n",
       "42736    22\n",
       "48077    22\n",
       "40299    22\n",
       "Name: user_id, dtype: int64"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "reviews_per_user.sort_values().head( 10 )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "### Tags"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tag_id</th>\n",
       "      <th>tag_name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>--1-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>--10-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>--12-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>--122-</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   tag_id tag_name\n",
       "0       0        -\n",
       "1       1     --1-\n",
       "2       2    --10-\n",
       "3       3    --12-\n",
       "4       4   --122-"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "t.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "34252"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(t)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>goodreads_book_id</th>\n",
       "      <th>tag_id</th>\n",
       "      <th>count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>30574</td>\n",
       "      <td>167697</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>11305</td>\n",
       "      <td>37174</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>11557</td>\n",
       "      <td>34173</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>8717</td>\n",
       "      <td>12986</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>33114</td>\n",
       "      <td>12716</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   goodreads_book_id  tag_id   count\n",
       "0                  1   30574  167697\n",
       "1                  1   11305   37174\n",
       "2                  1   11557   34173\n",
       "3                  1    8717   12986\n",
       "4                  1   33114   12716"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bt.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Tag applications are sorted by goodreads_book_id ASC and by count DESC."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "999912"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(bt)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let us merge tag names into tag applications."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "bt = bt.merge( t, on = 'tag_id' )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Why don't we merge book titles for good measure."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "bt = bt.merge( b[[ 'goodreads_book_id', 'title']], on = 'goodreads_book_id' )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It appears that there are some negative tag counts. Let's fix this."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    999912.000000\n",
       "mean        208.869633\n",
       "std        3501.265173\n",
       "min          -1.000000\n",
       "25%           7.000000\n",
       "50%          15.000000\n",
       "75%          40.000000\n",
       "max      596234.000000\n",
       "Name: count, dtype: float64"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bt['count'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "bt.loc[ bt['count'] < 0, 'count'] = 0"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Sample some popular book tags."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>goodreads_book_id</th>\n",
       "      <th>tag_id</th>\n",
       "      <th>count</th>\n",
       "      <th>tag_name</th>\n",
       "      <th>title</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>248904</th>\n",
       "      <td>46164</td>\n",
       "      <td>5207</td>\n",
       "      <td>386</td>\n",
       "      <td>books-i-own</td>\n",
       "      <td>Tender Is the Night</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>661994</th>\n",
       "      <td>6261522</td>\n",
       "      <td>30574</td>\n",
       "      <td>74453</td>\n",
       "      <td>to-read</td>\n",
       "      <td>The Body Finder (The Body Finder, #1)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>299800</th>\n",
       "      <td>73084</td>\n",
       "      <td>30574</td>\n",
       "      <td>2696</td>\n",
       "      <td>to-read</td>\n",
       "      <td>Heaven, Texas (Chicago Stars, #2)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10975</th>\n",
       "      <td>1232</td>\n",
       "      <td>14487</td>\n",
       "      <td>2973</td>\n",
       "      <td>historical-fiction</td>\n",
       "      <td>The Shadow of the Wind (The Cemetery of Forgot...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17200</th>\n",
       "      <td>2156</td>\n",
       "      <td>30574</td>\n",
       "      <td>220502</td>\n",
       "      <td>to-read</td>\n",
       "      <td>Persuasion</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>560394</th>\n",
       "      <td>821611</td>\n",
       "      <td>30574</td>\n",
       "      <td>104249</td>\n",
       "      <td>to-read</td>\n",
       "      <td>The Story of My Life</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36284</th>\n",
       "      <td>4865</td>\n",
       "      <td>24410</td>\n",
       "      <td>69</td>\n",
       "      <td>professional-development</td>\n",
       "      <td>How to Win Friends and Influence People</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>766394</th>\n",
       "      <td>10194514</td>\n",
       "      <td>30574</td>\n",
       "      <td>122130</td>\n",
       "      <td>to-read</td>\n",
       "      <td>Pushing the Limits (Pushing the Limits, #1)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>864774</th>\n",
       "      <td>16056862</td>\n",
       "      <td>2932</td>\n",
       "      <td>43</td>\n",
       "      <td>arranged-marriage</td>\n",
       "      <td>The Unwanted Wife (Unwanted, #1)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12114</th>\n",
       "      <td>1381</td>\n",
       "      <td>7457</td>\n",
       "      <td>14238</td>\n",
       "      <td>classics</td>\n",
       "      <td>The Odyssey</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        goodreads_book_id  tag_id   count                  tag_name  \\\n",
       "248904              46164    5207     386               books-i-own   \n",
       "661994            6261522   30574   74453                   to-read   \n",
       "299800              73084   30574    2696                   to-read   \n",
       "10975                1232   14487    2973        historical-fiction   \n",
       "17200                2156   30574  220502                   to-read   \n",
       "560394             821611   30574  104249                   to-read   \n",
       "36284                4865   24410      69  professional-development   \n",
       "766394           10194514   30574  122130                   to-read   \n",
       "864774           16056862    2932      43         arranged-marriage   \n",
       "12114                1381    7457   14238                  classics   \n",
       "\n",
       "                                                    title  \n",
       "248904                                Tender Is the Night  \n",
       "661994              The Body Finder (The Body Finder, #1)  \n",
       "299800                  Heaven, Texas (Chicago Stars, #2)  \n",
       "10975   The Shadow of the Wind (The Cemetery of Forgot...  \n",
       "17200                                          Persuasion  \n",
       "560394                               The Story of My Life  \n",
       "36284             How to Win Friends and Influence People  \n",
       "766394        Pushing the Limits (Pushing the Limits, #1)  \n",
       "864774                   The Unwanted Wife (Unwanted, #1)  \n",
       "12114                                         The Odyssey  "
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bt.sample( 10, weights = 'count')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "These are the most popular tags:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tag_name\n",
       "to-read              9983\n",
       "favorites            9881\n",
       "owned                9858\n",
       "books-i-own          9799\n",
       "currently-reading    9776\n",
       "library              9415\n",
       "owned-books          9221\n",
       "fiction              9097\n",
       "to-buy               8692\n",
       "kindle               8316\n",
       "default              8239\n",
       "ebook                8054\n",
       "my-books             7561\n",
       "audiobook            7242\n",
       "ebooks               7203\n",
       "wish-list            7192\n",
       "my-library           7000\n",
       "audiobooks           6862\n",
       "i-own                6670\n",
       "adult                6604\n",
       "Name: tag_name, dtype: int64"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tag_counts = bt.groupby( 'tag_name' ).tag_name.count().sort_values( ascending = False )\n",
    "tag_counts.head( 20 )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
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