twitter sentment.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[nltk_data] Downloading package punkt to\n",
      "[nltk_data]     C:\\Users\\hp\\AppData\\Roaming\\nltk_data...\n",
      "[nltk_data]   Unzipping tokenizers\\punkt.zip.\n"
     ]
    }
   ],
   "source": [
    "import re\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import nltk\n",
    "nltk.download('punkt')\n",
    "data=pd.read_csv(r\"C:\\Users\\hp\\Downloads\\0000000000002747_training_twitter_x_y_train.csv\")\n",
    "data_test=pd.read_csv(r\"C:\\Users\\hp\\Downloads\\0000000000002747_test_twitter_x_test.csv\")\n",
    "df=data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(10980, 12)"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "l=[]\n",
    "for i in df['airline_sentiment']:\n",
    "    if(i=='negative'):\n",
    "        l.append(-1)\n",
    "        \n",
    "    elif(i=='neutral'):\n",
    "        l.append(0)\n",
    "        \n",
    "    else:\n",
    "        l.append(1)\n",
    "        \n",
    "y_train=np.array(l)        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = data.append(data_test, ignore_index=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\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>airline</th>\n",
       "      <th>airline_sentiment</th>\n",
       "      <th>airline_sentiment_gold</th>\n",
       "      <th>name</th>\n",
       "      <th>negativereason_gold</th>\n",
       "      <th>retweet_count</th>\n",
       "      <th>text</th>\n",
       "      <th>tweet_coord</th>\n",
       "      <th>tweet_created</th>\n",
       "      <th>tweet_id</th>\n",
       "      <th>tweet_location</th>\n",
       "      <th>user_timezone</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Southwest</td>\n",
       "      <td>negative</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ColeyGirouard</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>@SouthwestAir I am scheduled for the morning, ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-02-17 20:16:29 -0800</td>\n",
       "      <td>567900433542488064</td>\n",
       "      <td>Washington D.C.</td>\n",
       "      <td>Atlantic Time (Canada)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Southwest</td>\n",
       "      <td>positive</td>\n",
       "      <td>NaN</td>\n",
       "      <td>WalterFaddoul</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>@SouthwestAir seeing your workers time in and ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-02-23 14:36:22 -0800</td>\n",
       "      <td>569989168903819264</td>\n",
       "      <td>Indianapolis, Indiana; USA</td>\n",
       "      <td>Central Time (US &amp; Canada)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>United</td>\n",
       "      <td>positive</td>\n",
       "      <td>NaN</td>\n",
       "      <td>LocalKyle</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>@united Flew ORD to Miami and back and  had gr...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-02-18 08:46:29 -0800</td>\n",
       "      <td>568089179520954368</td>\n",
       "      <td>Illinois</td>\n",
       "      <td>Central Time (US &amp; Canada)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Southwest</td>\n",
       "      <td>negative</td>\n",
       "      <td>NaN</td>\n",
       "      <td>amccarthy19</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>@SouthwestAir @dultch97 that's horse radish 😤🐴</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-02-20 16:20:26 -0800</td>\n",
       "      <td>568928195581513728</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Atlantic Time (Canada)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>United</td>\n",
       "      <td>negative</td>\n",
       "      <td>NaN</td>\n",
       "      <td>J_Okayy</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>@united so our flight into ORD was delayed bec...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-02-19 18:13:11 -0800</td>\n",
       "      <td>568594180014014464</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Eastern Time (US &amp; Canada)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>United</td>\n",
       "      <td>negative</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bobgiolito</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>@united Why did you load us in this flying sar...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-02-22 17:58:27 -0800</td>\n",
       "      <td>569677636613439488</td>\n",
       "      <td>Los Angeles, CA</td>\n",
       "      <td>Pacific Time (US &amp; Canada)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Delta</td>\n",
       "      <td>negative</td>\n",
       "      <td>NaN</td>\n",
       "      <td>aaronkinnari</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>@JetBlue that is a stock response. Delays not ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-02-22 16:44:00 -0800</td>\n",
       "      <td>569658903044218880</td>\n",
       "      <td>Gotham</td>\n",
       "      <td>Quito</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Delta</td>\n",
       "      <td>positive</td>\n",
       "      <td>NaN</td>\n",
       "      <td>TimothySays</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>@JetBlue That'd be nice! Hoping to rack up eno...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-02-19 14:48:53 -0800</td>\n",
       "      <td>568542766860541952</td>\n",
       "      <td>Burlington, MA</td>\n",
       "      <td>Eastern Time (US &amp; Canada)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>United</td>\n",
       "      <td>negative</td>\n",
       "      <td>NaN</td>\n",
       "      <td>lindaSWC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>@united frankly worse customer service ever. P...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-02-23 23:01:11 -0800</td>\n",
       "      <td>570116209263427584</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Southwest</td>\n",
       "      <td>positive</td>\n",
       "      <td>NaN</td>\n",
       "      <td>amyums</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>@SouthwestAir yeah haha. Never been in one. It...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-02-20 12:29:46 -0800</td>\n",
       "      <td>568870144891600896</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Central Time (US &amp; Canada)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Southwest</td>\n",
       "      <td>negative</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Faultie</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>@SouthwestAir MCO-&amp;gt;DCA flight almost full o...</td>\n",
       "      <td>[38.73693556, -90.35367062]</td>\n",
       "      <td>2015-02-17 13:12:06 -0800</td>\n",
       "      <td>567793635892174848</td>\n",
       "      <td>D.C.</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Delta</td>\n",
       "      <td>neutral</td>\n",
       "      <td>NaN</td>\n",
       "      <td>tonymbove</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>@JetBlue what's the easiest way to get a ticke...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-02-23 07:20:34 -0800</td>\n",
       "      <td>569879497891303424</td>\n",
       "      <td>Cambridge, MA</td>\n",
       "      <td>Quito</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>US Airways</td>\n",
       "      <td>positive</td>\n",
       "      <td>NaN</td>\n",
       "      <td>sherrylweir</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>@USAirways - love the changes in the lounge - ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-02-19 13:09:47 -0800</td>\n",
       "      <td>568517827482685440</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Quito</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Southwest</td>\n",
       "      <td>negative</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Mselite25</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>@SouthwestAir I receive bad customer service a...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-02-18 16:58:05 -0800</td>\n",
       "      <td>568212893012860928</td>\n",
       "      <td>Rite behind my $$</td>\n",
       "      <td>Mountain Time (US &amp; Canada)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>US Airways</td>\n",
       "      <td>negative</td>\n",
       "      <td>NaN</td>\n",
       "      <td>KennethBracy</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>@USAirways you're killing me sche a flight to ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-02-21 14:59:23 -0800</td>\n",
       "      <td>569270187725160449</td>\n",
       "      <td>Where ever God puts me</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>US Airways</td>\n",
       "      <td>negative</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SyncSummit</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>@USAirways 8 weeks to refund this ticket - 037...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-02-17 14:43:33 -0800</td>\n",
       "      <td>567816651900583936</td>\n",
       "      <td>Where Music meets Visual Media</td>\n",
       "      <td>Eastern Time (US &amp; Canada)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>American</td>\n",
       "      <td>negative</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Lioninflorida</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>@AmericanAir no private msg me and will provid...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-02-22 18:48:06 -0800</td>\n",
       "      <td>569690131235340288</td>\n",
       "      <td>Fort Myers, Florida</td>\n",
       "      <td>Eastern Time (US &amp; Canada)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Delta</td>\n",
       "      <td>negative</td>\n",
       "      <td>NaN</td>\n",
       "      <td>TheBuie</td>\n",
       "      <td>NaN</td>\n",
       "      <td>22</td>\n",
       "      <td>can you not? RT @JetBlue Our fleet's on fleek....</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-02-23 10:51:54 -0800</td>\n",
       "      <td>569932678688055296</td>\n",
       "      <td>Raleigh, NC</td>\n",
       "      <td>Eastern Time (US &amp; Canada)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Delta</td>\n",
       "      <td>negative</td>\n",
       "      <td>NaN</td>\n",
       "      <td>TheRealOx</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>@JetBlue any info on why flight 704 from SJU t...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-02-23 11:18:59 -0800</td>\n",
       "      <td>569939494465462272</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Eastern Time (US &amp; Canada)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>American</td>\n",
       "      <td>negative</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Rizzilient</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>@AmericanAir, I've tried no less than 8 times ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-02-23 12:33:24 -0800</td>\n",
       "      <td>569958224968982528</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>US Airways</td>\n",
       "      <td>negative</td>\n",
       "      <td>NaN</td>\n",
       "      <td>TomFutureforall</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>@USAirways new problem...had wrong last name o...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-02-19 02:47:59 -0800</td>\n",
       "      <td>568361346464497664</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Southwest</td>\n",
       "      <td>neutral</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DoctorFox007</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>@SouthwestAir Any possible chance of SWA bring...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-02-18 11:15:31 -0800</td>\n",
       "      <td>568126682336534529</td>\n",
       "      <td>ÜT: 40.819919,-73.864869</td>\n",
       "      <td>Eastern Time (US &amp; Canada)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>US Airways</td>\n",
       "      <td>negative</td>\n",
       "      <td>NaN</td>\n",
       "      <td>chrisseifert83</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>@USAirways @AmericanAir who runs the show at t...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-02-20 13:24:08 -0800</td>\n",
       "      <td>568883826333777920</td>\n",
       "      <td>Stamford, Ct</td>\n",
       "      <td>Eastern Time (US &amp; Canada)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>United</td>\n",
       "      <td>negative</td>\n",
       "      <td>NaN</td>\n",
       "      <td>JeffPKirkland</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>@united computers are down but you stopped giv...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-02-23 19:00:44 -0800</td>\n",
       "      <td>570055700790931456</td>\n",
       "      <td>Oregon</td>\n",
       "      <td>Pacific Time (US &amp; Canada)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>United</td>\n",
       "      <td>positive</td>\n",
       "      <td>NaN</td>\n",
       "      <td>jonatzzValdez</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>@united good fly!! #United #businessFirst</td>\n",
       "      <td>[29.98445184, -95.33224657]</td>\n",
       "      <td>2015-02-20 08:07:02 -0800</td>\n",
       "      <td>568804026789138433</td>\n",
       "      <td>Mexico</td>\n",
       "      <td>Central Time (US &amp; Canada)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>United</td>\n",
       "      <td>neutral</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MusseZam</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>@united I am flying from msp to dxb, my child ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-02-17 21:54:19 -0800</td>\n",
       "      <td>567925054853496832</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Delta</td>\n",
       "      <td>negative</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Old_bauer</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>@JetBlue loves Cancelled Flightling tickets an...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-02-19 07:37:53 -0800</td>\n",
       "      <td>568434301496381441</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Eastern Time (US &amp; Canada)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>United</td>\n",
       "      <td>negative</td>\n",
       "      <td>NaN</td>\n",
       "      <td>KeenanPam</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>@united In ORD, waited 20 min after crew membe...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-02-23 20:50:48 -0800</td>\n",
       "      <td>570083397873373184</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Southwest</td>\n",
       "      <td>positive</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Salem_Eways</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>@SouthwestAir Jason (108639) at Gate #3 in SAN...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-02-19 17:38:07 -0800</td>\n",
       "      <td>568585356586586113</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>American</td>\n",
       "      <td>positive</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MarkMan23</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>@AmericanAir everything for sorted out. Thanks...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-02-23 16:47:53 -0800</td>\n",
       "      <td>570022265343123456</td>\n",
       "      <td>San Diego, CA</td>\n",
       "      <td>Pacific Time (US &amp; Canada)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14610</th>\n",
       "      <td>US Airways</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MLasichak</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>@USAirways nope not yet...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-02-24 03:05:31 -0800</td>\n",
       "      <td>570177698166923267</td>\n",
       "      <td>Crofton, Maryland</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14611</th>\n",
       "      <td>Southwest</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>joshuapromero</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>@SouthwestAir So far so good! http://t.co/16c9...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-02-18 14:56:51 -0800</td>\n",
       "      <td>568182386409607168</td>\n",
       "      <td>San Diego, CA</td>\n",
       "      <td>Pacific Time (US &amp; Canada)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14612</th>\n",
       "      <td>Southwest</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>amyegoley</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>@SouthwestAir @CBSsoxfan you get to hold? call...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-02-17 11:13:20 -0800</td>\n",
       "      <td>567763748559937536</td>\n",
       "      <td>Flowood, MS</td>\n",
       "      <td>Central Time (US &amp; Canada)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14613</th>\n",
       "      <td>Delta</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>TyrellJourdanA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>@JetBlue Really!? That's good to hear! Thanks ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-02-20 04:40:33 -0800</td>\n",
       "      <td>568752061682208768</td>\n",
       "      <td>The Eastside of the Far Side</td>\n",
       "      <td>Eastern Time (US &amp; Canada)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14614</th>\n",
       "      <td>Delta</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Old_bauer</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>@JetBlue trying to charge us $550 dollars cash...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-02-19 07:47:04 -0800</td>\n",
       "      <td>568436613384155136</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Eastern Time (US &amp; Canada)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14615</th>\n",
       "      <td>US Airways</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Shroomcam</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>@USAirways can u tell me if 5238 from clt to J...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-02-20 12:32:32 -0800</td>\n",
       "      <td>568870841120731138</td>\n",
       "      <td>Orlando</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14616</th>\n",
       "      <td>US Airways</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4ensicdds</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>@USAirways Your customer service is  non-exist...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-02-21 21:33:35 -0800</td>\n",
       "      <td>569369390178799616</td>\n",
       "      <td>Long Island, NY</td>\n",
       "      <td>Eastern Time (US &amp; Canada)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14617</th>\n",
       "      <td>Southwest</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>kalenski</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>@SouthwestAir Whoa. Thanks and that's what I w...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-02-18 15:21:32 -0800</td>\n",
       "      <td>568188595456118785</td>\n",
       "      <td>Denver</td>\n",
       "      <td>Mountain Time (US &amp; Canada)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14618</th>\n",
       "      <td>United</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>goodenufmother</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>@United THANK U! Secured room for the night Th...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-02-23 17:24:06 -0800</td>\n",
       "      <td>570031379456643072</td>\n",
       "      <td>GEM HQ (aka walk-in closet) NY</td>\n",
       "      <td>Eastern Time (US &amp; Canada)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14619</th>\n",
       "      <td>American</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>StefanNiemczyk</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>@AmericanAir I'm not sure what happened to my ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-02-24 09:36:01 -0800</td>\n",
       "      <td>570275970046775297</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Arizona</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14620</th>\n",
       "      <td>American</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>joedizzle</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>@AmericanAir pretty bad at #DFW no updates two...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-02-22 19:11:44 -0800</td>\n",
       "      <td>569696080121569280</td>\n",
       "      <td>Windermere (seattle)</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14621</th>\n",
       "      <td>US Airways</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>erickofiejones</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>@USAirways Just contaced EYEWITNESS NEWS about...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-02-17 09:20:27 -0800</td>\n",
       "      <td>567735337246806016</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Eastern Time (US &amp; Canada)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14622</th>\n",
       "      <td>Southwest</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>tonybrancato</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>@SouthwestAir thx. Make it right. Help Meagan ...</td>\n",
       "      <td>[41.19747574, -73.76926201]</td>\n",
       "      <td>2015-02-24 11:10:05 -0800</td>\n",
       "      <td>570299642887442433</td>\n",
       "      <td>Chappaqua NY</td>\n",
       "      <td>Eastern Time (US &amp; Canada)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14623</th>\n",
       "      <td>US Airways</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>scheds14</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>@USAirways I didn't Cancelled Flight my flight...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-02-18 20:25:12 -0800</td>\n",
       "      <td>568265016253628416</td>\n",
       "      <td>Phoenix, AZ</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14624</th>\n",
       "      <td>United</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Pacen8r</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>@united your \"Airserv\" contractors aren't wort...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-02-21 05:59:25 -0800</td>\n",
       "      <td>569134299024367616</td>\n",
       "      <td>Manassas, Virginia</td>\n",
       "      <td>Eastern Time (US &amp; Canada)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14625</th>\n",
       "      <td>Southwest</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>GlendaVee</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>@SouthwestAir @taylormdowns We share that valu...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-02-18 11:48:27 -0800</td>\n",
       "      <td>568134973728755712</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Pacific Time (US &amp; Canada)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14626</th>\n",
       "      <td>US Airways</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>pmj1234</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>@USAirways on hold now over 2 hrs on one phone...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-02-22 02:04:55 -0800</td>\n",
       "      <td>569437674257276930</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14627</th>\n",
       "      <td>American</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>JaJillian</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>@AmericanAir the flight I'm trying to change i...</td>\n",
       "      <td>[34.10909961, -118.32361693]</td>\n",
       "      <td>2015-02-23 08:54:12 -0800</td>\n",
       "      <td>569903058299199488</td>\n",
       "      <td>New York, NY</td>\n",
       "      <td>Eastern Time (US &amp; Canada)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14628</th>\n",
       "      <td>Delta</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ChrisDonahoe</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>@JetBlue the fact that #ChrisHasMadeUsBLUSH is...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-02-22 14:02:42 -0800</td>\n",
       "      <td>569618309357940737</td>\n",
       "      <td>Washington, D.C.</td>\n",
       "      <td>Quito</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14629</th>\n",
       "      <td>United</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>abigailedge</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>@united Did somebody say flight upgrade?</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-02-20 09:53:15 -0800</td>\n",
       "      <td>568830757730422784</td>\n",
       "      <td>Brighton, UK</td>\n",
       "      <td>London</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14630</th>\n",
       "      <td>Southwest</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>UnstoppableMika</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>@SouthwestAir how do I get my companion pass?</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-02-22 17:18:34 -0800</td>\n",
       "      <td>569667602148151296</td>\n",
       "      <td>Pennsylvania</td>\n",
       "      <td>Atlantic Time (Canada)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14631</th>\n",
       "      <td>US Airways</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>bonmotmadison</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>@USAirways tells me to talk to @AmericanAir ab...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-02-19 13:48:38 -0800</td>\n",
       "      <td>568527605063757824</td>\n",
       "      <td>Madison, WI</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14632</th>\n",
       "      <td>Delta</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>JohnFMacky</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>@JetBlue you want me to talk to the wall?</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-02-22 06:28:25 -0800</td>\n",
       "      <td>569503983623999488</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Eastern Time (US &amp; Canada)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14633</th>\n",
       "      <td>US Airways</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>laurencecharles</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>@USAirways Now, the JFK Baggage Office has act...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-02-17 19:59:01 -0800</td>\n",
       "      <td>567896040982069249</td>\n",
       "      <td>Washington, DC</td>\n",
       "      <td>Eastern Time (US &amp; Canada)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14634</th>\n",
       "      <td>American</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>avaflav13</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>@AmericanAir Least you could do would be to re...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-02-23 12:41:40 -0800</td>\n",
       "      <td>569960303514923009</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Quito</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14635</th>\n",
       "      <td>US Airways</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Anthony_Scerri</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>@USAirways Been stuck for 40+ minutes due to l...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-02-24 11:28:22 -0800</td>\n",
       "      <td>570304244001193984</td>\n",
       "      <td>Astoria, NY</td>\n",
       "      <td>Quito</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14636</th>\n",
       "      <td>US Airways</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>mttdprkr</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>@USAirways 4 hours... 4 hours... FOUR HOURS.  ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-02-17 16:47:05 -0800</td>\n",
       "      <td>567847737061941249</td>\n",
       "      <td>Vancouver, WA</td>\n",
       "      <td>Pacific Time (US &amp; Canada)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14637</th>\n",
       "      <td>Virgin America</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>miaerolinea</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>Nice RT @VirginAmerica: The man of steel might...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-02-17 15:11:02 -0800</td>\n",
       "      <td>567823564167192576</td>\n",
       "      <td>Worldwide</td>\n",
       "      <td>Caracas</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14638</th>\n",
       "      <td>American</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>GoldensPleasure</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>@AmericanAir Aww Thanks AA..DFW was on GMA up ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-02-24 09:27:28 -0800</td>\n",
       "      <td>570273819287531520</td>\n",
       "      <td>East Coast     CT.</td>\n",
       "      <td>Central Time (US &amp; Canada)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14639</th>\n",
       "      <td>United</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>suntoshi</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>@united the lounge tells us they have no pillo...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-02-21 19:43:50 -0800</td>\n",
       "      <td>569341769114128386</td>\n",
       "      <td>Bedford, Nh</td>\n",
       "      <td>Eastern Time (US &amp; Canada)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>14640 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              airline airline_sentiment airline_sentiment_gold  \\\n",
       "0           Southwest          negative                    NaN   \n",
       "1           Southwest          positive                    NaN   \n",
       "2              United          positive                    NaN   \n",
       "3           Southwest          negative                    NaN   \n",
       "4              United          negative                    NaN   \n",
       "5              United          negative                    NaN   \n",
       "6               Delta          negative                    NaN   \n",
       "7               Delta          positive                    NaN   \n",
       "8              United          negative                    NaN   \n",
       "9           Southwest          positive                    NaN   \n",
       "10          Southwest          negative                    NaN   \n",
       "11              Delta           neutral                    NaN   \n",
       "12         US Airways          positive                    NaN   \n",
       "13          Southwest          negative                    NaN   \n",
       "14         US Airways          negative                    NaN   \n",
       "15         US Airways          negative                    NaN   \n",
       "16           American          negative                    NaN   \n",
       "17              Delta          negative                    NaN   \n",
       "18              Delta          negative                    NaN   \n",
       "19           American          negative                    NaN   \n",
       "20         US Airways          negative                    NaN   \n",
       "21          Southwest           neutral                    NaN   \n",
       "22         US Airways          negative                    NaN   \n",
       "23             United          negative                    NaN   \n",
       "24             United          positive                    NaN   \n",
       "25             United           neutral                    NaN   \n",
       "26              Delta          negative                    NaN   \n",
       "27             United          negative                    NaN   \n",
       "28          Southwest          positive                    NaN   \n",
       "29           American          positive                    NaN   \n",
       "...               ...               ...                    ...   \n",
       "14610      US Airways               NaN                    NaN   \n",
       "14611       Southwest               NaN                    NaN   \n",
       "14612       Southwest               NaN                    NaN   \n",
       "14613           Delta               NaN                    NaN   \n",
       "14614           Delta               NaN                    NaN   \n",
       "14615      US Airways               NaN                    NaN   \n",
       "14616      US Airways               NaN                    NaN   \n",
       "14617       Southwest               NaN                    NaN   \n",
       "14618          United               NaN                    NaN   \n",
       "14619        American               NaN                    NaN   \n",
       "14620        American               NaN                    NaN   \n",
       "14621      US Airways               NaN                    NaN   \n",
       "14622       Southwest               NaN                    NaN   \n",
       "14623      US Airways               NaN                    NaN   \n",
       "14624          United               NaN                    NaN   \n",
       "14625       Southwest               NaN                    NaN   \n",
       "14626      US Airways               NaN                    NaN   \n",
       "14627        American               NaN                    NaN   \n",
       "14628           Delta               NaN                    NaN   \n",
       "14629          United               NaN                    NaN   \n",
       "14630       Southwest               NaN                    NaN   \n",
       "14631      US Airways               NaN                    NaN   \n",
       "14632           Delta               NaN                    NaN   \n",
       "14633      US Airways               NaN                    NaN   \n",
       "14634        American               NaN                    NaN   \n",
       "14635      US Airways               NaN                    NaN   \n",
       "14636      US Airways               NaN                    NaN   \n",
       "14637  Virgin America               NaN                    NaN   \n",
       "14638        American               NaN                    NaN   \n",
       "14639          United               NaN                    NaN   \n",
       "\n",
       "                  name negativereason_gold  retweet_count  \\\n",
       "0        ColeyGirouard                 NaN              0   \n",
       "1        WalterFaddoul                 NaN              0   \n",
       "2            LocalKyle                 NaN              0   \n",
       "3          amccarthy19                 NaN              0   \n",
       "4              J_Okayy                 NaN              0   \n",
       "5           bobgiolito                 NaN              0   \n",
       "6         aaronkinnari                 NaN              0   \n",
       "7          TimothySays                 NaN              0   \n",
       "8             lindaSWC                 NaN              1   \n",
       "9               amyums                 NaN              0   \n",
       "10             Faultie                 NaN              0   \n",
       "11           tonymbove                 NaN              0   \n",
       "12         sherrylweir                 NaN              0   \n",
       "13           Mselite25                 NaN              0   \n",
       "14        KennethBracy                 NaN              0   \n",
       "15          SyncSummit                 NaN              0   \n",
       "16       Lioninflorida                 NaN              0   \n",
       "17             TheBuie                 NaN             22   \n",
       "18           TheRealOx                 NaN              0   \n",
       "19          Rizzilient                 NaN              0   \n",
       "20     TomFutureforall                 NaN              0   \n",
       "21        DoctorFox007                 NaN              0   \n",
       "22      chrisseifert83                 NaN              0   \n",
       "23       JeffPKirkland                 NaN              0   \n",
       "24       jonatzzValdez                 NaN              0   \n",
       "25            MusseZam                 NaN              0   \n",
       "26           Old_bauer                 NaN              0   \n",
       "27           KeenanPam                 NaN              0   \n",
       "28         Salem_Eways                 NaN              0   \n",
       "29           MarkMan23                 NaN              0   \n",
       "...                ...                 ...            ...   \n",
       "14610        MLasichak                 NaN              0   \n",
       "14611    joshuapromero                 NaN              0   \n",
       "14612        amyegoley                 NaN              0   \n",
       "14613   TyrellJourdanA                 NaN              0   \n",
       "14614        Old_bauer                 NaN              1   \n",
       "14615        Shroomcam                 NaN              0   \n",
       "14616        4ensicdds                 NaN              0   \n",
       "14617         kalenski                 NaN              0   \n",
       "14618   goodenufmother                 NaN              1   \n",
       "14619   StefanNiemczyk                 NaN              0   \n",
       "14620        joedizzle                 NaN              0   \n",
       "14621   erickofiejones                 NaN              0   \n",
       "14622     tonybrancato                 NaN              0   \n",
       "14623         scheds14                 NaN              0   \n",
       "14624          Pacen8r                 NaN              1   \n",
       "14625        GlendaVee                 NaN              0   \n",
       "14626          pmj1234                 NaN              0   \n",
       "14627        JaJillian                 NaN              0   \n",
       "14628     ChrisDonahoe                 NaN              0   \n",
       "14629      abigailedge                 NaN              0   \n",
       "14630  UnstoppableMika                 NaN              0   \n",
       "14631    bonmotmadison                 NaN              0   \n",
       "14632       JohnFMacky                 NaN              0   \n",
       "14633  laurencecharles                 NaN              0   \n",
       "14634        avaflav13                 NaN              0   \n",
       "14635   Anthony_Scerri                 NaN              0   \n",
       "14636         mttdprkr                 NaN              0   \n",
       "14637      miaerolinea                 NaN              1   \n",
       "14638  GoldensPleasure                 NaN              0   \n",
       "14639         suntoshi                 NaN              0   \n",
       "\n",
       "                                                    text  \\\n",
       "0      @SouthwestAir I am scheduled for the morning, ...   \n",
       "1      @SouthwestAir seeing your workers time in and ...   \n",
       "2      @united Flew ORD to Miami and back and  had gr...   \n",
       "3         @SouthwestAir @dultch97 that's horse radish 😤🐴   \n",
       "4      @united so our flight into ORD was delayed bec...   \n",
       "5      @united Why did you load us in this flying sar...   \n",
       "6      @JetBlue that is a stock response. Delays not ...   \n",
       "7      @JetBlue That'd be nice! Hoping to rack up eno...   \n",
       "8      @united frankly worse customer service ever. P...   \n",
       "9      @SouthwestAir yeah haha. Never been in one. It...   \n",
       "10     @SouthwestAir MCO-&gt;DCA flight almost full o...   \n",
       "11     @JetBlue what's the easiest way to get a ticke...   \n",
       "12     @USAirways - love the changes in the lounge - ...   \n",
       "13     @SouthwestAir I receive bad customer service a...   \n",
       "14     @USAirways you're killing me sche a flight to ...   \n",
       "15     @USAirways 8 weeks to refund this ticket - 037...   \n",
       "16     @AmericanAir no private msg me and will provid...   \n",
       "17     can you not? RT @JetBlue Our fleet's on fleek....   \n",
       "18     @JetBlue any info on why flight 704 from SJU t...   \n",
       "19     @AmericanAir, I've tried no less than 8 times ...   \n",
       "20     @USAirways new problem...had wrong last name o...   \n",
       "21     @SouthwestAir Any possible chance of SWA bring...   \n",
       "22     @USAirways @AmericanAir who runs the show at t...   \n",
       "23     @united computers are down but you stopped giv...   \n",
       "24             @united good fly!! #United #businessFirst   \n",
       "25     @united I am flying from msp to dxb, my child ...   \n",
       "26     @JetBlue loves Cancelled Flightling tickets an...   \n",
       "27     @united In ORD, waited 20 min after crew membe...   \n",
       "28     @SouthwestAir Jason (108639) at Gate #3 in SAN...   \n",
       "29     @AmericanAir everything for sorted out. Thanks...   \n",
       "...                                                  ...   \n",
       "14610                         @USAirways nope not yet...   \n",
       "14611  @SouthwestAir So far so good! http://t.co/16c9...   \n",
       "14612  @SouthwestAir @CBSsoxfan you get to hold? call...   \n",
       "14613  @JetBlue Really!? That's good to hear! Thanks ...   \n",
       "14614  @JetBlue trying to charge us $550 dollars cash...   \n",
       "14615  @USAirways can u tell me if 5238 from clt to J...   \n",
       "14616  @USAirways Your customer service is  non-exist...   \n",
       "14617  @SouthwestAir Whoa. Thanks and that's what I w...   \n",
       "14618  @United THANK U! Secured room for the night Th...   \n",
       "14619  @AmericanAir I'm not sure what happened to my ...   \n",
       "14620  @AmericanAir pretty bad at #DFW no updates two...   \n",
       "14621  @USAirways Just contaced EYEWITNESS NEWS about...   \n",
       "14622  @SouthwestAir thx. Make it right. Help Meagan ...   \n",
       "14623  @USAirways I didn't Cancelled Flight my flight...   \n",
       "14624  @united your \"Airserv\" contractors aren't wort...   \n",
       "14625  @SouthwestAir @taylormdowns We share that valu...   \n",
       "14626  @USAirways on hold now over 2 hrs on one phone...   \n",
       "14627  @AmericanAir the flight I'm trying to change i...   \n",
       "14628  @JetBlue the fact that #ChrisHasMadeUsBLUSH is...   \n",
       "14629           @united Did somebody say flight upgrade?   \n",
       "14630      @SouthwestAir how do I get my companion pass?   \n",
       "14631  @USAirways tells me to talk to @AmericanAir ab...   \n",
       "14632          @JetBlue you want me to talk to the wall?   \n",
       "14633  @USAirways Now, the JFK Baggage Office has act...   \n",
       "14634  @AmericanAir Least you could do would be to re...   \n",
       "14635  @USAirways Been stuck for 40+ minutes due to l...   \n",
       "14636  @USAirways 4 hours... 4 hours... FOUR HOURS.  ...   \n",
       "14637  Nice RT @VirginAmerica: The man of steel might...   \n",
       "14638  @AmericanAir Aww Thanks AA..DFW was on GMA up ...   \n",
       "14639  @united the lounge tells us they have no pillo...   \n",
       "\n",
       "                        tweet_coord              tweet_created  \\\n",
       "0                               NaN  2015-02-17 20:16:29 -0800   \n",
       "1                               NaN  2015-02-23 14:36:22 -0800   \n",
       "2                               NaN  2015-02-18 08:46:29 -0800   \n",
       "3                               NaN  2015-02-20 16:20:26 -0800   \n",
       "4                               NaN  2015-02-19 18:13:11 -0800   \n",
       "5                               NaN  2015-02-22 17:58:27 -0800   \n",
       "6                               NaN  2015-02-22 16:44:00 -0800   \n",
       "7                               NaN  2015-02-19 14:48:53 -0800   \n",
       "8                               NaN  2015-02-23 23:01:11 -0800   \n",
       "9                               NaN  2015-02-20 12:29:46 -0800   \n",
       "10      [38.73693556, -90.35367062]  2015-02-17 13:12:06 -0800   \n",
       "11                              NaN  2015-02-23 07:20:34 -0800   \n",
       "12                              NaN  2015-02-19 13:09:47 -0800   \n",
       "13                              NaN  2015-02-18 16:58:05 -0800   \n",
       "14                              NaN  2015-02-21 14:59:23 -0800   \n",
       "15                              NaN  2015-02-17 14:43:33 -0800   \n",
       "16                              NaN  2015-02-22 18:48:06 -0800   \n",
       "17                              NaN  2015-02-23 10:51:54 -0800   \n",
       "18                              NaN  2015-02-23 11:18:59 -0800   \n",
       "19                              NaN  2015-02-23 12:33:24 -0800   \n",
       "20                              NaN  2015-02-19 02:47:59 -0800   \n",
       "21                              NaN  2015-02-18 11:15:31 -0800   \n",
       "22                              NaN  2015-02-20 13:24:08 -0800   \n",
       "23                              NaN  2015-02-23 19:00:44 -0800   \n",
       "24      [29.98445184, -95.33224657]  2015-02-20 08:07:02 -0800   \n",
       "25                              NaN  2015-02-17 21:54:19 -0800   \n",
       "26                              NaN  2015-02-19 07:37:53 -0800   \n",
       "27                              NaN  2015-02-23 20:50:48 -0800   \n",
       "28                              NaN  2015-02-19 17:38:07 -0800   \n",
       "29                              NaN  2015-02-23 16:47:53 -0800   \n",
       "...                             ...                        ...   \n",
       "14610                           NaN  2015-02-24 03:05:31 -0800   \n",
       "14611                           NaN  2015-02-18 14:56:51 -0800   \n",
       "14612                           NaN  2015-02-17 11:13:20 -0800   \n",
       "14613                           NaN  2015-02-20 04:40:33 -0800   \n",
       "14614                           NaN  2015-02-19 07:47:04 -0800   \n",
       "14615                           NaN  2015-02-20 12:32:32 -0800   \n",
       "14616                           NaN  2015-02-21 21:33:35 -0800   \n",
       "14617                           NaN  2015-02-18 15:21:32 -0800   \n",
       "14618                           NaN  2015-02-23 17:24:06 -0800   \n",
       "14619                           NaN  2015-02-24 09:36:01 -0800   \n",
       "14620                           NaN  2015-02-22 19:11:44 -0800   \n",
       "14621                           NaN  2015-02-17 09:20:27 -0800   \n",
       "14622   [41.19747574, -73.76926201]  2015-02-24 11:10:05 -0800   \n",
       "14623                           NaN  2015-02-18 20:25:12 -0800   \n",
       "14624                           NaN  2015-02-21 05:59:25 -0800   \n",
       "14625                           NaN  2015-02-18 11:48:27 -0800   \n",
       "14626                           NaN  2015-02-22 02:04:55 -0800   \n",
       "14627  [34.10909961, -118.32361693]  2015-02-23 08:54:12 -0800   \n",
       "14628                           NaN  2015-02-22 14:02:42 -0800   \n",
       "14629                           NaN  2015-02-20 09:53:15 -0800   \n",
       "14630                           NaN  2015-02-22 17:18:34 -0800   \n",
       "14631                           NaN  2015-02-19 13:48:38 -0800   \n",
       "14632                           NaN  2015-02-22 06:28:25 -0800   \n",
       "14633                           NaN  2015-02-17 19:59:01 -0800   \n",
       "14634                           NaN  2015-02-23 12:41:40 -0800   \n",
       "14635                           NaN  2015-02-24 11:28:22 -0800   \n",
       "14636                           NaN  2015-02-17 16:47:05 -0800   \n",
       "14637                           NaN  2015-02-17 15:11:02 -0800   \n",
       "14638                           NaN  2015-02-24 09:27:28 -0800   \n",
       "14639                           NaN  2015-02-21 19:43:50 -0800   \n",
       "\n",
       "                 tweet_id                  tweet_location  \\\n",
       "0      567900433542488064                 Washington D.C.   \n",
       "1      569989168903819264      Indianapolis, Indiana; USA   \n",
       "2      568089179520954368                        Illinois   \n",
       "3      568928195581513728                             NaN   \n",
       "4      568594180014014464                             NaN   \n",
       "5      569677636613439488                 Los Angeles, CA   \n",
       "6      569658903044218880                          Gotham   \n",
       "7      568542766860541952                  Burlington, MA   \n",
       "8      570116209263427584                             NaN   \n",
       "9      568870144891600896                             NaN   \n",
       "10     567793635892174848                            D.C.   \n",
       "11     569879497891303424                   Cambridge, MA   \n",
       "12     568517827482685440                             NaN   \n",
       "13     568212893012860928               Rite behind my $$   \n",
       "14     569270187725160449          Where ever God puts me   \n",
       "15     567816651900583936  Where Music meets Visual Media   \n",
       "16     569690131235340288             Fort Myers, Florida   \n",
       "17     569932678688055296                     Raleigh, NC   \n",
       "18     569939494465462272                             NaN   \n",
       "19     569958224968982528                             NaN   \n",
       "20     568361346464497664                             NaN   \n",
       "21     568126682336534529        ÜT: 40.819919,-73.864869   \n",
       "22     568883826333777920                    Stamford, Ct   \n",
       "23     570055700790931456                          Oregon   \n",
       "24     568804026789138433                          Mexico   \n",
       "25     567925054853496832                             NaN   \n",
       "26     568434301496381441                             NaN   \n",
       "27     570083397873373184                             NaN   \n",
       "28     568585356586586113                             NaN   \n",
       "29     570022265343123456                   San Diego, CA   \n",
       "...                   ...                             ...   \n",
       "14610  570177698166923267               Crofton, Maryland   \n",
       "14611  568182386409607168                   San Diego, CA   \n",
       "14612  567763748559937536                     Flowood, MS   \n",
       "14613  568752061682208768    The Eastside of the Far Side   \n",
       "14614  568436613384155136                             NaN   \n",
       "14615  568870841120731138                        Orlando    \n",
       "14616  569369390178799616                 Long Island, NY   \n",
       "14617  568188595456118785                          Denver   \n",
       "14618  570031379456643072  GEM HQ (aka walk-in closet) NY   \n",
       "14619  570275970046775297                             NaN   \n",
       "14620  569696080121569280            Windermere (seattle)   \n",
       "14621  567735337246806016                             NaN   \n",
       "14622  570299642887442433                    Chappaqua NY   \n",
       "14623  568265016253628416                     Phoenix, AZ   \n",
       "14624  569134299024367616              Manassas, Virginia   \n",
       "14625  568134973728755712                             NaN   \n",
       "14626  569437674257276930                             NaN   \n",
       "14627  569903058299199488                    New York, NY   \n",
       "14628  569618309357940737                Washington, D.C.   \n",
       "14629  568830757730422784                    Brighton, UK   \n",
       "14630  569667602148151296                    Pennsylvania   \n",
       "14631  568527605063757824                     Madison, WI   \n",
       "14632  569503983623999488                             NaN   \n",
       "14633  567896040982069249                  Washington, DC   \n",
       "14634  569960303514923009                             NaN   \n",
       "14635  570304244001193984                     Astoria, NY   \n",
       "14636  567847737061941249                   Vancouver, WA   \n",
       "14637  567823564167192576                       Worldwide   \n",
       "14638  570273819287531520              East Coast     CT.   \n",
       "14639  569341769114128386                     Bedford, Nh   \n",
       "\n",
       "                     user_timezone  \n",
       "0           Atlantic Time (Canada)  \n",
       "1       Central Time (US & Canada)  \n",
       "2       Central Time (US & Canada)  \n",
       "3           Atlantic Time (Canada)  \n",
       "4       Eastern Time (US & Canada)  \n",
       "5       Pacific Time (US & Canada)  \n",
       "6                            Quito  \n",
       "7       Eastern Time (US & Canada)  \n",
       "8                              NaN  \n",
       "9       Central Time (US & Canada)  \n",
       "10                             NaN  \n",
       "11                           Quito  \n",
       "12                           Quito  \n",
       "13     Mountain Time (US & Canada)  \n",
       "14                             NaN  \n",
       "15      Eastern Time (US & Canada)  \n",
       "16      Eastern Time (US & Canada)  \n",
       "17      Eastern Time (US & Canada)  \n",
       "18      Eastern Time (US & Canada)  \n",
       "19                             NaN  \n",
       "20                             NaN  \n",
       "21      Eastern Time (US & Canada)  \n",
       "22      Eastern Time (US & Canada)  \n",
       "23      Pacific Time (US & Canada)  \n",
       "24      Central Time (US & Canada)  \n",
       "25                             NaN  \n",
       "26      Eastern Time (US & Canada)  \n",
       "27                             NaN  \n",
       "28                             NaN  \n",
       "29      Pacific Time (US & Canada)  \n",
       "...                            ...  \n",
       "14610                          NaN  \n",
       "14611   Pacific Time (US & Canada)  \n",
       "14612   Central Time (US & Canada)  \n",
       "14613   Eastern Time (US & Canada)  \n",
       "14614   Eastern Time (US & Canada)  \n",
       "14615                          NaN  \n",
       "14616   Eastern Time (US & Canada)  \n",
       "14617  Mountain Time (US & Canada)  \n",
       "14618   Eastern Time (US & Canada)  \n",
       "14619                      Arizona  \n",
       "14620                          NaN  \n",
       "14621   Eastern Time (US & Canada)  \n",
       "14622   Eastern Time (US & Canada)  \n",
       "14623                          NaN  \n",
       "14624   Eastern Time (US & Canada)  \n",
       "14625   Pacific Time (US & Canada)  \n",
       "14626                          NaN  \n",
       "14627   Eastern Time (US & Canada)  \n",
       "14628                        Quito  \n",
       "14629                       London  \n",
       "14630       Atlantic Time (Canada)  \n",
       "14631                          NaN  \n",
       "14632   Eastern Time (US & Canada)  \n",
       "14633   Eastern Time (US & Canada)  \n",
       "14634                        Quito  \n",
       "14635                        Quito  \n",
       "14636   Pacific Time (US & Canada)  \n",
       "14637                      Caracas  \n",
       "14638   Central Time (US & Canada)  \n",
       "14639   Eastern Time (US & Canada)  \n",
       "\n",
       "[14640 rows x 12 columns]"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df     "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "def remove_pattern(input_txt, pattern):\n",
    "    r = re.findall(pattern, input_txt)\n",
    "    for i in r:\n",
    "        input_txt = re.sub(i, '', input_txt)\n",
    "        \n",
    "    return input_txt  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "dic=[]\n",
    "for i in df.text:    \n",
    "    dic.append(remove_pattern(i,\"@[\\w]*\"))\n",
    "     \n",
    "df['rem_@']=dic"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "#df['tidy_tweet'] = np.vectorize(remove_pattern)(df['text'], \"@[\\w]*\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "' good fly    United  businessFirst'"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['rem_@'] = df['rem_@'].str.replace(\"[^a-zA-Z]\", \" \")\n",
    "df['rem_@'][24]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['rem_@'] = df['rem_@'].apply(lambda x: ' '.join([w for w in x.split() if len(w)>3]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "from nltk.tokenize import word_tokenize\n",
    "from nltk.corpus import stopwords\n",
    "stop=stopwords.words('english')\n",
    "import string\n",
    "punctuations=list(string.punctuation)\n",
    "stop=stop+punctuations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    [scheduled, morning, days, after, fact, sure, ...\n",
       "1    [seeing, your, workers, time, time, going, abo...\n",
       "Name: rem_@, dtype: object"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tokenized_tweet = df['rem_@'].apply(lambda x: word_tokenize(x))\n",
    "tokenized_tweet[0:2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    [scheduled, morning, days, fact, sure, evening...\n",
       "1    [seeing, workers, time, time, going, beyond, l...\n",
       "Name: rem_@, dtype: object"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "tokenized_tweet=tokenized_tweet.apply(lambda m:[w for w in m if not w.lower() in stop])\n",
    "tokenized_tweet[0:2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "from nltk.corpus import wordnet\n",
    "def get_simple_pos(tag):\n",
    "    if tag.startswith('J'):\n",
    "        return wordnet.ADJ\n",
    "    elif tag.startswith('V'):\n",
    "        return wordnet.VERB\n",
    "    elif tag.startswith('N'):\n",
    "        return wordnet.NOUN\n",
    "    elif tag.startswith('R'):\n",
    "        return wordnet.ADJ\n",
    "    else:\n",
    "        return wordnet.NOUN"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[nltk_data] Downloading package wordnet to\n",
      "[nltk_data]     C:\\Users\\hp\\AppData\\Roaming\\nltk_data...\n",
      "[nltk_data]   Unzipping corpora\\wordnet.zip.\n"
     ]
    }
   ],
   "source": [
    "import nltk\n",
    "nltk.download('wordnet')\n",
    "from nltk.stem import WordNetLemmatizer\n",
    "lemmatizer=WordNetLemmatizer()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "from nltk.corpus import wordnet"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[nltk_data] Downloading package averaged_perceptron_tagger to\n",
      "[nltk_data]     C:\\Users\\hp\\AppData\\Roaming\\nltk_data...\n",
      "[nltk_data]   Unzipping taggers\\averaged_perceptron_tagger.zip.\n"
     ]
    }
   ],
   "source": [
    "nltk.download('averaged_perceptron_tagger')\n",
    "from nltk import pos_tag"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    [schedule, morning, day, fact, sure, even, fli...\n",
       "1    [see, worker, time, time, go, beyond, love, fl...\n",
       "2    [Flew, Miami, back, great, crew, service, leg,...\n",
       "Name: rem_@, dtype: object"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tokenized_tweet = tokenized_tweet.apply(lambda x: [lemmatizer.lemmatize(i,pos=get_simple_pos(pos_tag([i])[0][1])) for i in x])\n",
    "tokenized_tweet[0:3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "list"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(tokenized_tweet[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_word=[]\n",
    "for doc in tokenized_tweet:\n",
    "    all_word+=doc    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in range(len(tokenized_tweet)):\n",
    "    tokenized_tweet[i] = ' '.join(tokenized_tweet[i])\n",
    "\n",
    "df['rem_@'] = tokenized_tweet"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_words = ' '.join([text for text in df['rem_@']])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "freq=nltk.FreqDist(all_word)\n",
    "common=freq.most_common(3000)\n",
    "feat=[i[0] for i in common]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.feature_extraction.text import CountVectorizer\n",
    "count_vectorizer = CountVectorizer(max_df=0.90, min_df=2, max_features=10000)\n",
    "x_train_features = count_vectorizer.fit_transform(df['rem_@'][0:10980])\n",
    "x_train_features=x_train_features.toarray()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [],
   "source": [
    "x_test_features=count_vectorizer.transform(df['rem_@'][10980:])\n",
    "x_test_features=x_test_features.toarray()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'negative'"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(df['airline_sentiment'][0])\n",
    "df['airline_sentiment'][0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\hp\\Anaconda3\\lib\\site-packages\\sklearn\\linear_model\\logistic.py:433: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "C:\\Users\\hp\\Anaconda3\\lib\\site-packages\\sklearn\\linear_model\\logistic.py:460: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
      "  \"this warning.\", FutureWarning)\n"
     ]
    }
   ],
   "source": [
    "from sklearn.naive_bayes import GaussianNB\n",
    "clf=GaussianNB()\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "cl=LogisticRegression()\n",
    "cl.fit(x_train_features,y_train)\n",
    "ytest1=cl.predict(x_test_features)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [],
   "source": [
    "clf.fit(x_train_features,y_train)\n",
    "ytest2=clf.predict(x_test_features)\n",
    "#cl better"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'@AmericanAir after all, the plane didn’t land in identical or worse) conditions at GRK according to METARs.'"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_test['text'][1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.feature_extraction.text import TfidfVectorizer\n",
    "tfidf_vectorizer = TfidfVectorizer(max_df=0.90, min_df=2, max_features=1000, stop_words='english')\n",
    "tfidf_train = tfidf_vectorizer.fit_transform(df['rem_@'][0:10980])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [],
   "source": [
    "tfidf_test=tfidf_vectorizer.transform(df['rem_@'][10981:])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\hp\\Anaconda3\\lib\\site-packages\\sklearn\\linear_model\\logistic.py:433: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
      "  FutureWarning)\n",
      "C:\\Users\\hp\\Anaconda3\\lib\\site-packages\\sklearn\\linear_model\\logistic.py:460: FutureWarning: Default multi_class will be changed to 'auto' in 0.22. Specify the multi_class option to silence this warning.\n",
      "  \"this warning.\", FutureWarning)\n"
     ]
    }
   ],
   "source": [
    "cl.fit(tfidf_train,y_train)\n",
    "ytest3=cl.predict(tfidf_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [],
   "source": [
    "tfidf_train=tfidf_train.toarray()\n",
    "tfidf_test=tfidf_test.toarray()\n",
    "clf.fit(tfidf_train,y_train)\n",
    "ytest4=clf.predict(tfidf_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_test1=[]\n",
    "for i in ytest1:\n",
    "    if(i==-1):\n",
    "        y_test1.append('negative')\n",
    "        \n",
    "    elif(i==0):\n",
    "        y_test1.append('neutral')\n",
    "        \n",
    "    else:\n",
    "        y_test1.append('positive')\n",
    "        \n",
    "\n",
    "        \n",
    "y_test2=[]\n",
    "for i in ytest2:\n",
    "    if(i==-1):\n",
    "        y_test2.append('negative')\n",
    "        \n",
    "    elif(i==0):\n",
    "        y_test2.append('neutral')\n",
    "        \n",
    "    else:\n",
    "        y_test2.append('positive')        \n",
    "        \n",
    "        \n",
    "y_test3=[]\n",
    "for i in ytest3:\n",
    "    if(i==-1):\n",
    "        y_test3.append('negative')\n",
    "        \n",
    "    elif(i==0):\n",
    "        y_test3.append('neutral')\n",
    "        \n",
    "    else:\n",
    "        y_test3.append('positive')\n",
    "        \n",
    "        \n",
    "y_test4=[]\n",
    "for i in ytest4:\n",
    "    if(i==-1):\n",
    "        y_test4.append('negative')\n",
    "        \n",
    "    elif(i==0):\n",
    "        y_test4.append('neutral')\n",
    "        \n",
    "    else:\n",
    "        y_test4.append('positive')        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [],
   "source": [
    "np.savetxt(\"tts1.csv\",y_test1,delimiter=\",\",fmt='%s')\n",
    "np.savetxt(\"tts2.csv\",y_test2,delimiter=\",\",fmt='%s')\n",
    "np.savetxt(\"tts3.csv\",y_test3,delimiter=\",\",fmt='%s')\n",
    "np.savetxt(\"tts4.csv\",y_test4,delimiter=\",\",fmt='%s')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "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": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}