exploratory_text.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "from source.conversation_helper import conversation_filter\n",
    "from source.visualization_helper import init_plot_style"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "init_plot_style()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2716464, 6)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds = pd.read_csv('/Users/john/data/twitter/tweets_ec_nd_conv.csv', usecols=['id', 'screen_name', 'text', 'hashtags','num_replies', 'conversation_id'])\n",
    "ds.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(914381, 8)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "conv = conversation_filter(ds)\n",
    "conv.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# text"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "conv['textlen'] = conv.text.str.len();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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4evbsectXVFy/fp0jR47Qr1+/XC9MREQKN6sDqkGDBrcsc3Jyws/P765fVigi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\nQImIiE1SQImIiE1SQImIiE36/wAdyMGr3zaQuwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1182450f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#textlen=ds.groupby('textlen').size()\n",
    "#textlen.reset_index(inplace=True)\n",
    "fig = plt.figure()\n",
    "conv.textlen.plot.hist( bins=100)\n",
    "#plt.xscale('log')\n",
    "plt.title('number of chars in tweets')\n",
    "plt.xlabel('chars')\n",
    "plt.xlim([0, 180])\n",
    "#plt.xscale('log')\n",
    "fig.autofmt_xdate()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# hashtags"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "s = conv[\"hashtags\"].str.split(';', expand=True).stack()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "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>id</th>\n",
       "      <th>hashtags</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>838977507487547393</td>\n",
       "      <td>VoyACNCOconDNA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>838977593403666432</td>\n",
       "      <td>VoyACNCOconDNA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>838978411460767745</td>\n",
       "      <td>VoyACNCOconDNA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>838997472966021120</td>\n",
       "      <td>VoyACNCOconDNA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>838999765996224512</td>\n",
       "      <td>VoyACNCOconDNA</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   id        hashtags\n",
       "0  838977507487547393  VoyACNCOconDNA\n",
       "1  838977593403666432  VoyACNCOconDNA\n",
       "2  838978411460767745  VoyACNCOconDNA\n",
       "3  838997472966021120  VoyACNCOconDNA\n",
       "4  838999765996224512  VoyACNCOconDNA"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "i = s.index.get_level_values(0)\n",
    "s.index = s.index.droplevel(-1)\n",
    "ds_hashtags = ds[['id']].loc[i].copy()\n",
    "ds_hashtags['hashtags'] = s.values\n",
    "ds_hashtags.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.03474737747306793\n"
     ]
    }
   ],
   "source": [
    "perc = ds_hashtags.id.nunique() / ds.shape[0]\n",
    "print(perc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "ht=ds_hashtags.groupby('hashtags').size()\n",
    "top=ht.sort_values(ascending=False).head(50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x11acaaac8>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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JJBJh3LhxAAA3Nzf4+PhwebgZac3c08pP8hAT7qfWq+JKPiIyFr3mmPz9/XH48GFMnjwZ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\nAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11ed37860>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x=range(1, len(top)+1,1)\n",
    "y=top.values\n",
    "plt.scatter(x, y, marker='x')\n",
    "plt.yscale('log')\n",
    "plt.xlabel('top 50 hashtags')\n",
    "plt.ylabel('tweets')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "number of words with stop words removal: 4982412\n",
      "number of words (TF min:3): 86441\n"
     ]
    }
   ],
   "source": [
    "from nltk.corpus import stopwords\n",
    "from nltk.stem.snowball import SnowballStemmer\n",
    "from nltk.tokenize import word_tokenize\n",
    "import re\n",
    "\n",
    "use_stemmer = False\n",
    "stemmer = SnowballStemmer(\"spanish\")\n",
    "stopset = set(stopwords.words('english') + stopwords.words('spanish'))\n",
    "\n",
    "def tokenize(text):\n",
    "    text = re.sub(r\"(?:\\#|@|https?\\://)\\S+\", \"\", text)\n",
    "    text = re.sub(\"[^a-zA-Z] \",\"\",text)\n",
    "    text = re.sub(r'\\b\\w{1,2}\\b',' ',text)\n",
    "    text = re.sub(r'http[\\bs]*',' ',text)\n",
    "    tokens = word_tokenize(text)\n",
    "    if use_stemmer:\n",
    "        tokens = [stemmer.stem(t) for t in tokens]\n",
    "    return tokens\n",
    "\n",
    "words = ' '.join(conv['text'])\n",
    "\n",
    "use_stemmer=False\n",
    "word_list = tokenize(words)\n",
    "word_list = [word for word in word_list if word not in stopset]\n",
    "print(f'number of words with stop words removal: {len(word_list)}')\n",
    "\n",
    "\n",
    "wds = pd.DataFrame(word_list)\n",
    "wds.columns = ['word']\n",
    "wds=wds.word.value_counts().reset_index()\n",
    "wds.columns=['word', 'count']\n",
    "wds=wds[wds['count']>3]\n",
    "print(f'number of words (TF min:3): {len(wds)}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "wds2=wds.sort_values('count', ascending=False).head(1000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-0.5, 499.5, 299.5, -0.5)"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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MRZdUmMhHXrNIK0rlu8ffaL3/19CV6Iv0WeL/E2E5oWrlwanq6WMA7I01O1gM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\nsP06izYOYOpwoRp52U8HuXD8MTk5Uvq0+JXJCzqzaPpfjPm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umXZjit8lragcXT08r+OY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urmRdXcc42szbAuB+V2afDxhO4GncaqXRfp1romvu7aq42YuFT6jdG9ojrwx5QKsbEk7P3jAl5V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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x118421f28>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from wordcloud import WordCloud\n",
    "filtered_words = ' '.join(wds2.word)\n",
    "wordcloud = WordCloud(background_color='white', width=500, height=300).generate(filtered_words)\n",
    "plt.imshow(wordcloud)\n",
    "plt.axis(\"off\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# text analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(47728, 9)\n"
     ]
    },
    {
     "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>id</th>\n",
       "      <th>screen_name</th>\n",
       "      <th>text</th>\n",
       "      <th>hashtags</th>\n",
       "      <th>conversation_id</th>\n",
       "      <th>num_replies</th>\n",
       "      <th>num_users</th>\n",
       "      <th>num_tweets</th>\n",
       "      <th>textlen</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>838952408432717825</td>\n",
       "      <td>Denissecnco</td>\n",
       "      <td>@DnaGlobalEvents ¿cuantos ganadores van a ser?...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>838920932982992896</td>\n",
       "      <td>94</td>\n",
       "      <td>17</td>\n",
       "      <td>94</td>\n",
       "      <td>103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>839505866483183616</td>\n",
       "      <td>gene_cncowner</td>\n",
       "      <td>@DnaGlobalEvents una pregunta .Hoy dirán a la ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>838920932982992896</td>\n",
       "      <td>94</td>\n",
       "      <td>17</td>\n",
       "      <td>94</td>\n",
       "      <td>55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93</th>\n",
       "      <td>838922043160657920</td>\n",
       "      <td>holyxcnco</td>\n",
       "      <td>@DnaGlobalEvents hasta cuando se puede partici...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>838920932982992896</td>\n",
       "      <td>94</td>\n",
       "      <td>17</td>\n",
       "      <td>94</td>\n",
       "      <td>81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>838977783133048836</td>\n",
       "      <td>xbroknheartsgox</td>\n",
       "      <td>@sheeilala_ jajajaja eres de mexico no??</td>\n",
       "      <td>NaN</td>\n",
       "      <td>838970516031537152</td>\n",
       "      <td>10</td>\n",
       "      <td>2</td>\n",
       "      <td>10</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>838975825923932161</td>\n",
       "      <td>xbroknheartsgox</td>\n",
       "      <td>@sheeilala_ jajajajaja que dia eres ; hermana ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>838970516031537152</td>\n",
       "      <td>10</td>\n",
       "      <td>2</td>\n",
       "      <td>10</td>\n",
       "      <td>61</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    id      screen_name  \\\n",
       "75  838952408432717825      Denissecnco   \n",
       "89  839505866483183616    gene_cncowner   \n",
       "93  838922043160657920        holyxcnco   \n",
       "96  838977783133048836  xbroknheartsgox   \n",
       "98  838975825923932161  xbroknheartsgox   \n",
       "\n",
       "                                                 text hashtags  \\\n",
       "75  @DnaGlobalEvents ¿cuantos ganadores van a ser?...      NaN   \n",
       "89  @DnaGlobalEvents una pregunta .Hoy dirán a la ...      NaN   \n",
       "93  @DnaGlobalEvents hasta cuando se puede partici...      NaN   \n",
       "96           @sheeilala_ jajajaja eres de mexico no??      NaN   \n",
       "98  @sheeilala_ jajajajaja que dia eres ; hermana ...      NaN   \n",
       "\n",
       "       conversation_id  num_replies  num_users  num_tweets  textlen  \n",
       "75  838920932982992896           94         17          94      103  \n",
       "89  838920932982992896           94         17          94       55  \n",
       "93  838920932982992896           94         17          94       81  \n",
       "96  838970516031537152           10          2          10       40  \n",
       "98  838970516031537152           10          2          10       61  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "questions=conv[conv.text.str.endswith('?')]\n",
    "print(questions.shape)\n",
    "questions.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(40091, 9)\n"
     ]
    },
    {
     "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>id</th>\n",
       "      <th>screen_name</th>\n",
       "      <th>text</th>\n",
       "      <th>hashtags</th>\n",
       "      <th>conversation_id</th>\n",
       "      <th>num_replies</th>\n",
       "      <th>num_users</th>\n",
       "      <th>num_tweets</th>\n",
       "      <th>textlen</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>838974538574614529</td>\n",
       "      <td>xbroknheartsgox</td>\n",
       "      <td>@sheeilala_ si!!! supongo q tu tambien!!!</td>\n",
       "      <td>NaN</td>\n",
       "      <td>838970516031537152</td>\n",
       "      <td>10</td>\n",
       "      <td>2</td>\n",
       "      <td>10</td>\n",
       "      <td>41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>838975142306938880</td>\n",
       "      <td>sheeilala_</td>\n",
       "      <td>@xbroknheartsgox Siiiiiiiiiii!!!!!!</td>\n",
       "      <td>NaN</td>\n",
       "      <td>838970516031537152</td>\n",
       "      <td>10</td>\n",
       "      <td>2</td>\n",
       "      <td>10</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>218</th>\n",
       "      <td>838972229731946496</td>\n",
       "      <td>xbroknheartsgox</td>\n",
       "      <td>@pudinilla el \"awwwww\" yo lo tomaba asi como \"...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>838970636244484097</td>\n",
       "      <td>15</td>\n",
       "      <td>2</td>\n",
       "      <td>15</td>\n",
       "      <td>85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>220</th>\n",
       "      <td>838975659590418437</td>\n",
       "      <td>xbroknheartsgox</td>\n",
       "      <td>@pudinilla que bueno que sea mutuo porque imag...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>838970636244484097</td>\n",
       "      <td>15</td>\n",
       "      <td>2</td>\n",
       "      <td>15</td>\n",
       "      <td>85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>229</th>\n",
       "      <td>838978467928682496</td>\n",
       "      <td>chicade1994</td>\n",
       "      <td>@xbroknheartsgox Jajajajajajajajaja \"no tengo ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>838970636244484097</td>\n",
       "      <td>15</td>\n",
       "      <td>2</td>\n",
       "      <td>15</td>\n",
       "      <td>122</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     id      screen_name  \\\n",
       "97   838974538574614529  xbroknheartsgox   \n",
       "105  838975142306938880       sheeilala_   \n",
       "218  838972229731946496  xbroknheartsgox   \n",
       "220  838975659590418437  xbroknheartsgox   \n",
       "229  838978467928682496      chicade1994   \n",
       "\n",
       "                                                  text hashtags  \\\n",
       "97           @sheeilala_ si!!! supongo q tu tambien!!!      NaN   \n",
       "105                @xbroknheartsgox Siiiiiiiiiii!!!!!!      NaN   \n",
       "218  @pudinilla el \"awwwww\" yo lo tomaba asi como \"...      NaN   \n",
       "220  @pudinilla que bueno que sea mutuo porque imag...      NaN   \n",
       "229  @xbroknheartsgox Jajajajajajajajaja \"no tengo ...      NaN   \n",
       "\n",
       "        conversation_id  num_replies  num_users  num_tweets  textlen  \n",
       "97   838970516031537152           10          2          10       41  \n",
       "105  838970516031537152           10          2          10       35  \n",
       "218  838970636244484097           15          2          15       85  \n",
       "220  838970636244484097           15          2          15       85  \n",
       "229  838970636244484097           15          2          15      122  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "admiration=conv[conv.text.str.endswith('!')]\n",
    "print(admiration.shape)\n",
    "admiration.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(22491, 9)\n"
     ]
    },
    {
     "data": {
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       "<div>\n",
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       "    .dataframe thead tr:only-child th {\n",
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       "    }\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>id</th>\n",
       "      <th>screen_name</th>\n",
       "      <th>text</th>\n",
       "      <th>hashtags</th>\n",
       "      <th>conversation_id</th>\n",
       "      <th>num_replies</th>\n",
       "      <th>num_users</th>\n",
       "      <th>num_tweets</th>\n",
       "      <th>textlen</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>219</th>\n",
       "      <td>838973249451081728</td>\n",
       "      <td>xbroknheartsgox</td>\n",
       "      <td>@pudinilla -_- ; te odio....</td>\n",
       "      <td>NaN</td>\n",
       "      <td>838970636244484097</td>\n",
       "      <td>15</td>\n",
       "      <td>2</td>\n",
       "      <td>15</td>\n",
       "      <td>28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>237</th>\n",
       "      <td>838979377488670720</td>\n",
       "      <td>el_flacotirador</td>\n",
       "      <td>@danielg195 a cocachos aprendí...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>838959074846728192</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>247</th>\n",
       "      <td>838980024543948804</td>\n",
       "      <td>HOMBRE_AZUL_PE</td>\n",
       "      <td>@Politico_pe NO VA A HACER CASO....\\nA CIERTA ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>838977525174849536</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>113</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>271</th>\n",
       "      <td>838953611707236355</td>\n",
       "      <td>EstefyRey</td>\n",
       "      <td>@merianmadeleine @MashiRafael @viviana_bonilla...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>838926562124779520</td>\n",
       "      <td>17</td>\n",
       "      <td>3</td>\n",
       "      <td>17</td>\n",
       "      <td>105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>286</th>\n",
       "      <td>838953859477307392</td>\n",
       "      <td>a1ejandro_az</td>\n",
       "      <td>@huyrol promoción estaba en pretemporada..esto...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>837757300874051584</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>71</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     id      screen_name  \\\n",
       "219  838973249451081728  xbroknheartsgox   \n",
       "237  838979377488670720  el_flacotirador   \n",
       "247  838980024543948804   HOMBRE_AZUL_PE   \n",
       "271  838953611707236355        EstefyRey   \n",
       "286  838953859477307392     a1ejandro_az   \n",
       "\n",
       "                                                  text hashtags  \\\n",
       "219                       @pudinilla -_- ; te odio....      NaN   \n",
       "237                  @danielg195 a cocachos aprendí...      NaN   \n",
       "247  @Politico_pe NO VA A HACER CASO....\\nA CIERTA ...      NaN   \n",
       "271  @merianmadeleine @MashiRafael @viviana_bonilla...      NaN   \n",
       "286  @huyrol promoción estaba en pretemporada..esto...      NaN   \n",
       "\n",
       "        conversation_id  num_replies  num_users  num_tweets  textlen  \n",
       "219  838970636244484097           15          2          15       28  \n",
       "237  838959074846728192            2          2           2       33  \n",
       "247  838977525174849536            2          2           2      113  \n",
       "271  838926562124779520           17          3          17      105  \n",
       "286  837757300874051584            3          2           3       71  "
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "suspense=conv[conv.text.str.endswith('..')]\n",
    "print(suspense.shape)\n",
    "suspense.head()"
   ]
  }
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