data_processing_and_preparation.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Preprocessing Data and Preparing Train and VAl for Pytorch"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "from tqdm import tqdm\n",
    "\n",
    "import re\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from nltk.corpus import stopwords\n",
    "from nltk.stem import SnowballStemmer\n",
    "from string import punctuation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "tqdm.pandas()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(159571, 8)\n"
     ]
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>comment_text</th>\n",
       "      <th>toxic</th>\n",
       "      <th>severe_toxic</th>\n",
       "      <th>obscene</th>\n",
       "      <th>threat</th>\n",
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       "      <td>0000997932d777bf</td>\n",
       "      <td>Explanation\\nWhy the edits made under my usern...</td>\n",
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       "      <td>D'aww! He matches this background colour I'm s...</td>\n",
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       "      <td>000113f07ec002fd</td>\n",
       "      <td>Hey man, I'm really not trying to edit war. It...</td>\n",
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       "      <th>3</th>\n",
       "      <td>0001b41b1c6bb37e</td>\n",
       "      <td>\"\\nMore\\nI can't make any real suggestions on ...</td>\n",
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       "      <th>4</th>\n",
       "      <td>0001d958c54c6e35</td>\n",
       "      <td>You, sir, are my hero. Any chance you remember...</td>\n",
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      ],
      "text/plain": [
       "                 id                                       comment_text  toxic  \\\n",
       "0  0000997932d777bf  Explanation\\nWhy the edits made under my usern...      0   \n",
       "1  000103f0d9cfb60f  D'aww! He matches this background colour I'm s...      0   \n",
       "2  000113f07ec002fd  Hey man, I'm really not trying to edit war. It...      0   \n",
       "3  0001b41b1c6bb37e  \"\\nMore\\nI can't make any real suggestions on ...      0   \n",
       "4  0001d958c54c6e35  You, sir, are my hero. Any chance you remember...      0   \n",
       "\n",
       "   severe_toxic  obscene  threat  insult  identity_hate  \n",
       "0             0        0       0       0              0  \n",
       "1             0        0       0       0              0  \n",
       "2             0        0       0       0              0  \n",
       "3             0        0       0       0              0  \n",
       "4             0        0       0       0              0  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train = pd.read_csv(\"data/toxic_competition_data/train.csv\")\n",
    "print(train.shape)\n",
    "train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>comment_text</th>\n",
       "      <th>toxic</th>\n",
       "      <th>severe_toxic</th>\n",
       "      <th>obscene</th>\n",
       "      <th>threat</th>\n",
       "      <th>insult</th>\n",
       "      <th>identity_hate</th>\n",
       "    </tr>\n",
       "  </thead>\n",
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       "      <th>0</th>\n",
       "      <td>0002bcb3da6cb337</td>\n",
       "      <td>COCKSUCKER BEFORE YOU PISS AROUND ON MY WORK</td>\n",
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       "      <th>1</th>\n",
       "      <td>0020e7119b96eeeb</td>\n",
       "      <td>Stupid peace of shit stop deleting my stuff as...</td>\n",
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       "      <th>2</th>\n",
       "      <td>006e87872c8b370c</td>\n",
       "      <td>you are a stupid fuck \\n\\nand your mother's cu...</td>\n",
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       "      <th>3</th>\n",
       "      <td>01208d2b76624130</td>\n",
       "      <td>Hi \\n\\nIm a fucking bitch.\\n\\n50.180.208.181</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
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       "      <td>1</td>\n",
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       "      <th>4</th>\n",
       "      <td>018663f910e0bfe6</td>\n",
       "      <td>What a motherfucking piece of crap those fuckh...</td>\n",
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      ],
      "text/plain": [
       "                 id                                       comment_text  toxic  \\\n",
       "0  0002bcb3da6cb337       COCKSUCKER BEFORE YOU PISS AROUND ON MY WORK      1   \n",
       "1  0020e7119b96eeeb  Stupid peace of shit stop deleting my stuff as...      1   \n",
       "2  006e87872c8b370c  you are a stupid fuck \\n\\nand your mother's cu...      1   \n",
       "3  01208d2b76624130       Hi \\n\\nIm a fucking bitch.\\n\\n50.180.208.181      1   \n",
       "4  018663f910e0bfe6  What a motherfucking piece of crap those fuckh...      1   \n",
       "\n",
       "   severe_toxic  obscene  threat  insult  identity_hate  \n",
       "0             1        1       0       1              0  \n",
       "1             1        1       0       1              0  \n",
       "2             1        1       0       1              0  \n",
       "3             1        1       0       1              0  \n",
       "4             1        1       0       1              0  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = train.loc[(train.severe_toxic == 1) & (train.obscene == 1), :].reset_index(drop=True)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# train = train[[\"comment_text\", \"toxic\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
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     "text": [
      "(153164, 2)\n"
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       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>comment_text</th>\n",
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       "      <td>Yo bitch Ja Rule is more succesful then you'll...</td>\n",
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       "      <th>1</th>\n",
       "      <td>0000247867823ef7</td>\n",
       "      <td>== From RfC == \\n\\n The title is fine as it is...</td>\n",
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       "      <th>2</th>\n",
       "      <td>00013b17ad220c46</td>\n",
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       "      <td>I don't anonymously edit articles at all.</td>\n",
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      "text/plain": [
       "                 id                                       comment_text\n",
       "0  00001cee341fdb12  Yo bitch Ja Rule is more succesful then you'll...\n",
       "1  0000247867823ef7  == From RfC == \\n\\n The title is fine as it is...\n",
       "2  00013b17ad220c46  \" \\n\\n == Sources == \\n\\n * Zawe Ashton on Lap...\n",
       "3  00017563c3f7919a  :If you have a look back at the source, the in...\n",
       "4  00017695ad8997eb          I don't anonymously edit articles at all."
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test = pd.read_csv(\"data/toxic_competition_data/test.csv\")\n",
    "print(test.shape)\n",
    "test.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "id               0\n",
       "comment_text     0\n",
       "toxic            0\n",
       "severe_toxic     0\n",
       "obscene          0\n",
       "threat           0\n",
       "insult           0\n",
       "identity_hate    0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "id              0\n",
       "comment_text    0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "replace_ip=re.compile(r'([0-9]+)(?:\\.[0-9]+){3}',)\n",
    "def text_to_wordlist(text, remove_stopwords=True, stem_words=False, replace_ip=replace_ip):\n",
    "    # Clean the text, with the option to remove stopwords and to stem words.\n",
    "    # Convert words to lower case and split them\n",
    "    text = text.lower().split()\n",
    "\n",
    "    # Optionally, remove stop words\n",
    "    if remove_stopwords:\n",
    "        stops = set(stopwords.words(\"english\"))\n",
    "        text = [w for w in text if not w in stops]\n",
    "    \n",
    "    text = \" \".join(text)\n",
    "\n",
    "    #Replace IP address\n",
    "    text=replace_ip.sub('',text)\n",
    "    \n",
    "    # Optionally, shorten words to their stems\n",
    "    if stem_words:\n",
    "        text = text.split()\n",
    "        stemmer = SnowballStemmer('english')\n",
    "        stemmed_words = [stemmer.stem(word) for word in text]\n",
    "        text = \" \".join(stemmed_words)\n",
    "    \n",
    "    # Return a list of words\n",
    "    return(text)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 159571/159571 [00:23<00:00, 6911.94it/s]\n"
     ]
    }
   ],
   "source": [
    "train[\"comment_text\"] = train.comment_text.progress_apply(text_to_wordlist)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    144277\n",
       "1     15294\n",
       "Name: toxic, dtype: int64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.toxic.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    157976\n",
       "1      1595\n",
       "Name: severe_toxic, dtype: int64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.severe_toxic.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((143613, 8), (15958, 8))"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train, val = train_test_split(train, test_size=0.1, shuffle=True) #, stratify=train[['toxic']])\n",
    "train.shape, val.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "train.to_csv(\"data/toxic_competition_data/train_torch.csv\", encoding=\"utf-8\", index=False)\n",
    "val.to_csv(\"data/toxic_competition_data/test_torch.csv\", encoding=\"utf-8\", index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['id', 'comment_text', 'toxic', 'severe_toxic', 'obscene', 'threat',\n",
       "       'insult', 'identity_hate'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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