blogs_stats.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.5/dist-packages/IPython/core/interactiveshell.py:2717: DtypeWarning: Columns (0) have mixed types. Specify dtype option on import or set low_memory=False.\n",
      "  interactivity=interactivity, compiler=compiler, result=result)\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import re\n",
    "posts = pd.read_csv('posts_clean.csv.gz', compression='gzip', error_bad_lines=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "## Contagens"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Postagens: 1346858\n",
      "Blogs: 144045\n",
      "Autores: 154787\n"
     ]
    }
   ],
   "source": [
    "blogs = posts[['posts.csv']].groupby(['posts.csv'])\n",
    "autores = posts[['authorID']].groupby(['authorID'])\n",
    "print('Postagens: %i' %len(posts))\n",
    "print('Blogs: %i' %len(blogs))\n",
    "print('Autores: %i' %len(autores))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "## Ano de Publicação"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "posts['date'] = pd.to_datetime(posts['published'], errors='coerce')\n",
    "posts['year'] = posts['date'].dt.year"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7fe68ca55748>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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Hh1xm2wAMzihbCtxci1+Qs9IWAE/npbBNwBmSpuTEgDOATbnvgKQFeawLhozV6BhmZtYB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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe68ca3feb8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "year = posts['year']\n",
    "year = year[year > 2000]\n",
    "year = year[year < 2018]\n",
    "year.plot.hist(bins=40)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>posts.csv</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>year</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1999.0</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000.0</th>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2001.0</th>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2002.0</th>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2003.0</th>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004.0</th>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005.0</th>\n",
       "      <td>1725</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006.0</th>\n",
       "      <td>3695</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007.0</th>\n",
       "      <td>8105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008.0</th>\n",
       "      <td>19451</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009.0</th>\n",
       "      <td>62104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010.0</th>\n",
       "      <td>149051</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011.0</th>\n",
       "      <td>408472</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012.0</th>\n",
       "      <td>305785</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013.0</th>\n",
       "      <td>137054</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014.0</th>\n",
       "      <td>79242</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015.0</th>\n",
       "      <td>65082</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016.0</th>\n",
       "      <td>89731</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017.0</th>\n",
       "      <td>17143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018.0</th>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019.0</th>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020.0</th>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021.0</th>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022.0</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023.0</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024.0</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2025.0</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2026.0</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2027.0</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2029.0</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2030.0</th>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2031.0</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2034.0</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2050.0</th>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2065.0</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2066.0</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2096.0</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2098.0</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2099.0</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2100.0</th>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2101.0</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2111.0</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2112.0</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       posts.csv\n",
       "           count\n",
       "year            \n",
       "1999.0         2\n",
       "2000.0         4\n",
       "2001.0        17\n",
       "2002.0         6\n",
       "2003.0        27\n",
       "2004.0        20\n",
       "2005.0      1725\n",
       "2006.0      3695\n",
       "2007.0      8105\n",
       "2008.0     19451\n",
       "2009.0     62104\n",
       "2010.0    149051\n",
       "2011.0    408472\n",
       "2012.0    305785\n",
       "2013.0    137054\n",
       "2014.0     79242\n",
       "2015.0     65082\n",
       "2016.0     89731\n",
       "2017.0     17143\n",
       "2018.0         9\n",
       "2019.0        24\n",
       "2020.0        40\n",
       "2021.0         6\n",
       "2022.0         1\n",
       "2023.0         1\n",
       "2024.0         2\n",
       "2025.0         5\n",
       "2026.0         2\n",
       "2027.0         1\n",
       "2029.0         1\n",
       "2030.0        12\n",
       "2031.0         2\n",
       "2034.0         1\n",
       "2050.0         6\n",
       "2065.0         1\n",
       "2066.0         1\n",
       "2096.0         1\n",
       "2098.0         1\n",
       "2099.0         5\n",
       "2100.0         3\n",
       "2101.0         2\n",
       "2111.0         1\n",
       "2112.0         1"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "posts[['posts.csv','year']].groupby(['year']).agg(['count'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "## Médias"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "def titleCount(x): \n",
    "    try:\n",
    "        return len(re.findall(r'\\w+', x['title']))\n",
    "    except:\n",
    "        return 0\n",
    "    \n",
    "def contentCount(x): \n",
    "    try:\n",
    "        return len(re.findall(r'\\w+', x['content']))\n",
    "    except:\n",
    "        return 0\n",
    "\n",
    "def wpsCount(x): \n",
    "    try:\n",
    "        return x['contentCount'] / x['content'].count(\".\")\n",
    "    except:\n",
    "        return x['contentCount']\n",
    "    \n",
    "posts['titleCount'] = posts.apply(titleCount,axis=1)\n",
    "posts['contentCount'] = posts.apply(contentCount,axis=1)\n",
    "posts['wpsCount'] = posts.apply(wpsCount,axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "#posts.to_csv('posts_count.csv.gz', compression='gzip')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4.3452457497375372"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.mean(posts['titleCount'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "245.77212965286614"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.mean(posts['contentCount'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "20.941070399005731"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.mean(posts['wpsCount'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f60e3af6cf8>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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jgJvbS5I0JgseNlX1deB1M9SfBM6coV7AZfvY1yZg0wz17cBrD7izkqSD4lCa+ixJmlCG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\ndWfYSJK6+//u4SSyt55ZiAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f60d700a5f8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "contentCount = posts['contentCount']\n",
    "contentCount = contentCount[contentCount > 1]\n",
    "contentCount = contentCount[contentCount < 1000]\n",
    "contentCount.plot.hist(bins=40)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "## Blogs mais densos"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>posts.csv</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1.717984e+18</th>\n",
       "      <td>10</td>\n",
       "      <td>59727.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2.329723e+17</th>\n",
       "      <td>10</td>\n",
       "      <td>37914.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.881441e+18</th>\n",
       "      <td>10</td>\n",
       "      <td>28846.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2.294214e+18</th>\n",
       "      <td>10</td>\n",
       "      <td>24485.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.174338e+18</th>\n",
       "      <td>10</td>\n",
       "      <td>21617.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.156788e+18</th>\n",
       "      <td>9</td>\n",
       "      <td>21231.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.636456e+18</th>\n",
       "      <td>4</td>\n",
       "      <td>19915.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.024539e+18</th>\n",
       "      <td>10</td>\n",
       "      <td>18299.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2.083401e+18</th>\n",
       "      <td>10</td>\n",
       "      <td>18166.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2.071340e+18</th>\n",
       "      <td>10</td>\n",
       "      <td>18061.9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              count     mean\n",
       "posts.csv                   \n",
       "1.717984e+18     10  59727.3\n",
       "2.329723e+17     10  37914.3\n",
       "1.881441e+18     10  28846.8\n",
       "2.294214e+18     10  24485.5\n",
       "1.174338e+18     10  21617.5\n",
       "1.156788e+18      9  21231.0\n",
       "1.636456e+18      4  19915.5\n",
       "1.024539e+18     10  18299.4\n",
       "2.083401e+18     10  18166.6\n",
       "2.071340e+18     10  18061.9"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "blogLen = posts[['posts.csv','contentCount']].groupby(['posts.csv']).agg(['count','mean'])\n",
    "blogLen['contentCount'].sort_values('mean',ascending=False).head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "## Posts mais comentados"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>title</th>\n",
       "      <th>replies</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>890168</th>\n",
       "      <td>Aprenda a usar o novo orkut!</td>\n",
       "      <td>1938.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>977144</th>\n",
       "      <td>TUDO SOBRE LÉO SANTANA</td>\n",
       "      <td>1232.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>890170</th>\n",
       "      <td>Miedi que eu respondo!</td>\n",
       "      <td>1135.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>890167</th>\n",
       "      <td>Ely Kim, o melhor dançarino do mundo</td>\n",
       "      <td>1129.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>890174</th>\n",
       "      <td>O fim do Concurso Cultural</td>\n",
       "      <td>1108.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>229670</th>\n",
       "      <td>Urgente! Publicado o Edital do Concurso da PME...</td>\n",
       "      <td>1102.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>683605</th>\n",
       "      <td>Deixe seu Recado no meu Guestbook</td>\n",
       "      <td>695.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>577225</th>\n",
       "      <td>Sorteio</td>\n",
       "      <td>553.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1248769</th>\n",
       "      <td>Need for Speed: The Run (ISO) [MediaFire] + Cr...</td>\n",
       "      <td>531.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>162174</th>\n",
       "      <td>FÓRUM 3 ANO 3 BIMESTRE 2015</td>\n",
       "      <td>528.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                     title  replies\n",
       "890168                        Aprenda a usar o novo orkut!   1938.0\n",
       "977144                              TUDO SOBRE LÉO SANTANA   1232.0\n",
       "890170                              Miedi que eu respondo!   1135.0\n",
       "890167                Ely Kim, o melhor dançarino do mundo   1129.0\n",
       "890174                          O fim do Concurso Cultural   1108.0\n",
       "229670   Urgente! Publicado o Edital do Concurso da PME...   1102.0\n",
       "683605                   Deixe seu Recado no meu Guestbook    695.0\n",
       "577225                                             Sorteio    553.0\n",
       "1248769  Need for Speed: The Run (ISO) [MediaFire] + Cr...    531.0\n",
       "162174                         FÓRUM 3 ANO 3 BIMESTRE 2015    528.0"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "posts[['title','replies']].sort_values('replies',ascending=False).head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "## Posts Auto-Reflexivos"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Posts Reflexivos: 13881\n",
      "Total de Posts: 1346858\n",
      "Percentual: 1.031000\n"
     ]
    }
   ],
   "source": [
    "posts = posts.fillna('')\n",
    "postsReflexivos = posts[posts['content'].str.contains(\"eu sinto|eu penso|eu acredito\")]\n",
    "\n",
    "print('Posts Reflexivos: %i' %len(postsReflexivos))\n",
    "print('Total de Posts: %i' %len(posts))\n",
    "print('Percentual: %f' %round(100 * len(postsReflexivos) / len(posts),3))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "## Blogs Auto-Reflexivos"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.5/dist-packages/ipykernel/__main__.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  if __name__ == '__main__':\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>blogID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1717983962433433088</th>\n",
       "      <td>8</td>\n",
       "      <td>74107.625000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>242410630245328480</th>\n",
       "      <td>8</td>\n",
       "      <td>309.375000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2299697280975917568</th>\n",
       "      <td>7</td>\n",
       "      <td>247.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>118502485184438272</th>\n",
       "      <td>7</td>\n",
       "      <td>530.428571</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1978371034383716864</th>\n",
       "      <td>7</td>\n",
       "      <td>2115.142857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2376002203817739776</th>\n",
       "      <td>7</td>\n",
       "      <td>190.857143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1661881252606013696</th>\n",
       "      <td>6</td>\n",
       "      <td>1560.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1903048977906924288</th>\n",
       "      <td>6</td>\n",
       "      <td>439.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2134748788525575936</th>\n",
       "      <td>6</td>\n",
       "      <td>4668.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1450650900147172608</th>\n",
       "      <td>6</td>\n",
       "      <td>242.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     count          mean\n",
       "blogID                                  \n",
       "1717983962433433088      8  74107.625000\n",
       "242410630245328480       8    309.375000\n",
       "2299697280975917568      7    247.000000\n",
       "118502485184438272       7    530.428571\n",
       "1978371034383716864      7   2115.142857\n",
       "2376002203817739776      7    190.857143\n",
       "1661881252606013696      6   1560.666667\n",
       "1903048977906924288      6    439.666667\n",
       "2134748788525575936      6   4668.333333\n",
       "1450650900147172608      6    242.000000"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "postsReflexivos['blogID'] = postsReflexivos['posts.csv'].astype(int).astype('str')\n",
    "groupReflex = postsReflexivos[['blogID','contentCount']].groupby(['blogID']).agg(['count','mean'])\n",
    "groupReflex['contentCount'].sort_values('count',ascending=False).head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>title</th>\n",
       "      <th>replies</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1089511</th>\n",
       "      <td>Hormonios Femininos - Travestis e Transxeuais</td>\n",
       "      <td>187</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1285737</th>\n",
       "      <td>19 de Março a 07 de Abril de 2011</td>\n",
       "      <td>177</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1333666</th>\n",
       "      <td>Dangerous Life 3° - Capítulo 6 - Confusion</td>\n",
       "      <td>166</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55916</th>\n",
       "      <td>Invasão para amiga</td>\n",
       "      <td>95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>441487</th>\n",
       "      <td>Às pessoas mais importantes da minha vida.</td>\n",
       "      <td>84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1061746</th>\n",
       "      <td></td>\n",
       "      <td>78</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>530873</th>\n",
       "      <td>fifty ♡</td>\n",
       "      <td>78</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1333661</th>\n",
       "      <td>The Apprentice - Fourteenth chapter</td>\n",
       "      <td>78</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>258971</th>\n",
       "      <td>thirty-first chapter</td>\n",
       "      <td>71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>614678</th>\n",
       "      <td>Sapatos e Homens</td>\n",
       "      <td>63</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                 title replies\n",
       "1089511  Hormonios Femininos - Travestis e Transxeuais     187\n",
       "1285737              19 de Março a 07 de Abril de 2011     177\n",
       "1333666     Dangerous Life 3° - Capítulo 6 - Confusion     166\n",
       "55916                               Invasão para amiga      95\n",
       "441487      Às pessoas mais importantes da minha vida.      84\n",
       "1061746                                                     78\n",
       "530873                                         fifty ♡      78\n",
       "1333661            The Apprentice - Fourteenth chapter      78\n",
       "258971                            thirty-first chapter      71\n",
       "614678                                Sapatos e Homens      63"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "postsReflexivos[['title','replies']].sort_values('replies',ascending=False).head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f60d6ff39e8>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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qQ1XNVNXM0qVLR/svkKQD2NiDo6rOq6rlVbUCOBP4RFW9Avgk8Fut21rgmja8qY3Tpn+i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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f60d6ff8f98>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "contentCount = postsReflexivos['contentCount']\n",
    "contentCount = contentCount[contentCount > 1]\n",
    "contentCount = contentCount[contentCount < 2000]\n",
    "contentCount.plot.hist(bins=40)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f60e18c9fd0>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f60e195e0f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "wpsCount = postsReflexivos['wpsCount']\n",
    "wpsCount = wpsCount[wpsCount > 1]\n",
    "wpsCount = wpsCount[wpsCount < 100]\n",
    "wpsCount.plot.hist(bins=40)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}