semeval_deep.ipynb

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   "source": [
    "import pandas as pd\n",
    "import re\n",
    "from nltk.corpus import stopwords\n",
    "from nltk.tokenize import word_tokenize\n",
    "from nltk.stem.snowball import SnowballStemmer\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "from nltk.corpus import wordnet\n",
    "from nltk.stem import WordNetLemmatizer \n",
    "from nltk import pos_tag ,pos_tag_sents\n",
    "import matplotlib.pyplot as plt\n",
    "from nltk import pos_tag\n",
    "from sklearn.feature_extraction.text import CountVectorizer, TfidfTransformer\n",
    "from nltk.tokenize import RegexpTokenizer\n",
    "from sklearn.model_selection import train_test_split, validation_curve\n",
    "from sklearn.preprocessing import LabelEncoder\n",
    "from scipy.sparse import vstack\n",
    "from sklearn.naive_bayes import MultinomialNB\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "from sklearn import metrics\n",
    "from sklearn.ensemble import RandomForestClassifier\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "def remove_link(content):\n",
    "    '''remove links (using map) and hashtags'''\n",
    "    a = content[:content.find('http' or 'https')]\n",
    "    a = re.sub('#\\w+', '', a)\n",
    "    return a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
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       "<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",
       "      <th>content</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>619950566786113536</td>\n",
       "      <td>neutral</td>\n",
       "      <td>Picturehouse's, Pink Floyd's, 'Roger Waters: T...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>619969366986235905</td>\n",
       "      <td>neutral</td>\n",
       "      <td>Order Go Set a Watchman in store or through ou...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>619971047195045888</td>\n",
       "      <td>negative</td>\n",
       "      <td>If these runway renovations at the airport pre...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>619974445185302528</td>\n",
       "      <td>neutral</td>\n",
       "      <td>If you could ask an onstage interview question...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>619987808317407232</td>\n",
       "      <td>positive</td>\n",
       "      <td>A portion of book sales from our Harper Lee/Go...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   id     label  \\\n",
       "0  619950566786113536   neutral   \n",
       "1  619969366986235905   neutral   \n",
       "2  619971047195045888  negative   \n",
       "3  619974445185302528   neutral   \n",
       "4  619987808317407232  positive   \n",
       "\n",
       "                                             content  \n",
       "0  Picturehouse's, Pink Floyd's, 'Roger Waters: T...  \n",
       "1  Order Go Set a Watchman in store or through ou...  \n",
       "2  If these runway renovations at the airport pre...  \n",
       "3  If you could ask an onstage interview question...  \n",
       "4  A portion of book sales from our Harper Lee/Go...  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_csv('SemEval2017-task4-dev.subtask-A.english.INPUT.txt', names = ['id', 'label', 'content'], sep ='\\t', index_col=False)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "data.content = data.content.map(remove_link)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Order Go Set a Watchman in store or through our website before Tuesday and get it half price!  @GSAWatchmanBook '"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a= data.iloc[1].content\n",
    "a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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