{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "!bitter tweet get_all lista-tweets.csv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('untitled.txt', names=['id', 'label'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\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>label</th>\n",
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       "  <tbody>\n",
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       "      <th>0</th>\n",
       "      <td>631659865748860929</td>\n",
       "      <td>ironic</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>602202801092038656</td>\n",
       "      <td>ironic</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      "text/plain": [
       "                   id   label\n",
       "0  631659865748860929  ironic\n",
       "1  602202801092038656  ironic"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "get_text(631659865748860929)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "import json\n",
    "import os\n",
    "\n",
    "def get_text(tweetid):\n",
    "    tweetfile = 'tweets/{}.json'.format(tweetid)\n",
    "    if not os.path.exists(tweetfile):\n",
    "        return \"\"\n",
    "    return json.load(open(tweetfile))['text']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Uy que emoción! #sarcasmo #noquiero #yatienesuno :( @Cris_baoc  https://t.co/Roe4H1D4d6'"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "get_text(631659865748860929)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['text'] = df['id'].apply(get_text)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <td>Uy que emoción! #sarcasmo #noquiero #yatienesu...</td>\n",
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      "text/plain": [
       "                   id   label  \\\n",
       "0  631659865748860929  ironic   \n",
       "1  602202801092038656  ironic   \n",
       "\n",
       "                                                text  \n",
       "0  Uy que emoción! #sarcasmo #noquiero #yatienesu...  \n",
       "1                                                     "
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</table>\n",
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      "text/plain": [
       "                   id   label  \\\n",
       "0  631659865748860929  ironic   \n",
       "\n",
       "                                                text  \n",
       "0  Uy que emoción! #sarcasmo #noquiero #yatienesu...  "
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['text'] != \"\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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