Naive Bayes Spam Email Classifier - Pre-Preprocessing.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Notebook Imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from os import walk\n",
    "from os.path import join\n",
    "\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "import nltk\n",
    "from nltk.stem import PorterStemmer\n",
    "from nltk.corpus import stopwords\n",
    "from nltk.tokenize import word_tokenize\n",
    "\n",
    "from bs4 import BeautifulSoup\n",
    "from wordcloud import WordCloud\n",
    "from PIL import Image\n",
    "import numpy as np\n",
    "\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Constants"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [],
   "source": [
    "EXAMPLE_FILE = 'SpamData/01_Processing/practice_email.txt'\n",
    "\n",
    "SPAM_1_PATH = 'SpamData/01_Processing/spam_assassin_corpus/spam_1'\n",
    "SPAM_2_PATH = 'SpamData/01_Processing/spam_assassin_corpus/spam_2'\n",
    "EASY_NONSPAM_1_PATH = 'SpamData/01_Processing/spam_assassin_corpus/easy_ham_1'\n",
    "EASY_NONSPAM_2_PATH = 'SpamData/01_Processing/spam_assassin_corpus/easy_ham_2'\n",
    "\n",
    "SPAM_CAT = 1\n",
    "HAM_CAT = 0\n",
    "VOCAB_SIZE = 2500\n",
    "\n",
    "DATA_JSON_FILE = 'SpamData/01_Processing/email-text-data.json'\n",
    "WORD_ID_FILE = 'SpamData/01_Processing/word-by-id.csv'\n",
    "\n",
    "TRAINING_DATA_FILE = 'SpamData/02_Training/train-data.txt'\n",
    "TEST_DATA_FILE = 'SpamData/02_Training/test-data.txt'\n",
    "\n",
    "THUMBS_UP_FILE = 'SpamData/01_Processing/wordcloud_resources/thumbs-up.png'\n",
    "THUMBS_DOWN_FILE = 'SpamData/01_Processing/wordcloud_resources/thumbs-down.png'\n",
    "CUSTOM_FONT_FILE = 'SpamData/01_Processing/wordcloud_resources/OpenSansCondensed-Bold.ttf'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Reading Files"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "Dear Mr Still\n",
      "\n",
      "\n",
      "\n",
      "Good tidings to you and all your staff for the festive season ahead (Christmas).\n",
      "\n",
      "Now to the crux of the matter-in-hand: I am a fully qualified Santa Claus and am wondering whether you might consider me to run my own \"Santa's Grotto\" in your store.\n",
      "\n",
      "But WAIT! You're probably thinking: \"What makes him so special?\"\n",
      "\n",
      "Well, first of all, I have made several changes to the characterisation of Father Christmas. Rather than greeting the children with shouts of \"Ho, ho, ho!\" I prefer to whisper the phrase \"Dependence is not unfathomable in this cruel world we live in\". In addition, my gifts are ALL hand-made, ranging from felt hoops to vanilla-pod holders.\n",
      "\n",
      "You will note also, from the enclosed sketch, that I have radically redesigned Santa's outfit and have renamed my character \"Lord Buckles\". Would you be interested in employing me? I promise NEVER to let you down.\n",
      "\n",
      "I look forward to hearing from you.\n",
      "\n",
      "\n",
      "\n",
      "Best wishes\n",
      "\n",
      "Robin Cooper\n",
      "\n",
      "[Excerpt from the book: The Timewaster Letters by Robin Cooper]\n",
      "\n"
     ]
    }
   ],
   "source": [
    "stream = open(EXAMPLE_FILE, encoding='latin-1')\n",
    "\n",
    "is_body = False\n",
    "lines = []\n",
    "\n",
    "for line in stream: \n",
    "    if is_body:\n",
    "        lines.append(line)\n",
    "    elif line =='\\n':\n",
    "        is_body = True\n",
    "stream.close()\n",
    "\n",
    "email_body = '\\n'.join(lines)\n",
    "print(email_body)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Generator Functions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def generate_squares(N):\n",
    "    for my_number in range(N):\n",
    "        yield my_number ** 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0 -> 1 -> 4 -> "
     ]
    }
   ],
   "source": [
    "for i in generate_squares(3):\n",
    "    print(i, end = ' -> ')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Email Body Extraction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def email_body_generator(path): \n",
    "    \n",
    "    for root, dirnames, filenames in walk(path):\n",
    "        for file_name in filenames:\n",
    "            \n",
    "            filepath = join(root, file_name)\n",
    "        \n",
    "            stream = open(filepath, encoding='latin-1')\n",
    "\n",
    "            is_body = False\n",
    "            lines = []\n",
    "\n",
    "            for line in stream: \n",
    "                if is_body:\n",
    "                    lines.append(line)\n",
    "                elif line =='\\n':\n",
    "                    is_body = True\n",
    "            stream.close()\n",
    "\n",
    "            email_body = '\\n'.join(lines)\n",
    "\n",
    "            yield file_name, email_body"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "def df_from_directory(path, classification):\n",
    "    rows = []\n",
    "    row_names = []\n",
    "    \n",
    "    for file_name, email_body in email_body_generator(path):\n",
    "        rows.append({'MESSAGE': email_body, 'CATEGORY': classification})\n",
    "        row_names.append(file_name)\n",
    "        \n",
    "    return pd.DataFrame(rows, index = row_names)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>MESSAGE</th>\n",
       "      <th>CATEGORY</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>00249.5f45607c1bffe89f60ba1ec9f878039a</td>\n",
       "      <td>Dear Homeowner,\\n\\n \\n\\nInterest Rates are at ...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>00373.ebe8670ac56b04125c25100a36ab0510</td>\n",
       "      <td>ATTENTION: This is a MUST for ALL Computer Use...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>00214.1367039e50dc6b7adb0f2aa8aba83216</td>\n",
       "      <td>This is a multi-part message in MIME format.\\n...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>00210.050ffd105bd4e006771ee63cabc59978</td>\n",
       "      <td>IMPORTANT INFORMATION:\\n\\n\\n\\nThe new domain n...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>00033.9babb58d9298daa2963d4f514193d7d6</td>\n",
       "      <td>This is the bottom line.  If you can GIVE AWAY...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                                                  MESSAGE  \\\n",
       "00249.5f45607c1bffe89f60ba1ec9f878039a  Dear Homeowner,\\n\\n \\n\\nInterest Rates are at ...   \n",
       "00373.ebe8670ac56b04125c25100a36ab0510  ATTENTION: This is a MUST for ALL Computer Use...   \n",
       "00214.1367039e50dc6b7adb0f2aa8aba83216  This is a multi-part message in MIME format.\\n...   \n",
       "00210.050ffd105bd4e006771ee63cabc59978  IMPORTANT INFORMATION:\\n\\n\\n\\nThe new domain n...   \n",
       "00033.9babb58d9298daa2963d4f514193d7d6  This is the bottom line.  If you can GIVE AWAY...   \n",
       "\n",
       "                                        CATEGORY  \n",
       "00249.5f45607c1bffe89f60ba1ec9f878039a         1  \n",
       "00373.ebe8670ac56b04125c25100a36ab0510         1  \n",
       "00214.1367039e50dc6b7adb0f2aa8aba83216         1  \n",
       "00210.050ffd105bd4e006771ee63cabc59978         1  \n",
       "00033.9babb58d9298daa2963d4f514193d7d6         1  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "spam_emails = df_from_directory(SPAM_1_PATH, SPAM_CAT)\n",
    "spam_emails = spam_emails.append(df_from_directory(SPAM_2_PATH, SPAM_CAT))\n",
    "spam_emails.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1898, 2)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "spam_emails.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>MESSAGE</th>\n",
       "      <th>CATEGORY</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>00769.25bf9a767b5db0ed93f03c1637281663</td>\n",
       "      <td>\\n\\nIn a message dated 9/24/2002 11:24:58 AM, ...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>01074.8590d61ac0aeeadb58dc2f2ba776c406</td>\n",
       "      <td>Hiya, I always seem to get errors when I do an...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>02479.14365bcad3a60fcf24c5c1813f6291fb</td>\n",
       "      <td>\\n\\nI don't know how one can expect better and...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>01417.ce7b07a2114218dbac682b599785820d</td>\n",
       "      <td>Tim Peters wrote:\\n\\n&gt; I've run no experiments...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>00357.d559b71616f64ba1d1c1e61a03644fd4</td>\n",
       "      <td>At 10:34 AM -0700 on 8/28/02, Jim Whitehead wr...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                                                  MESSAGE  \\\n",
       "00769.25bf9a767b5db0ed93f03c1637281663  \\n\\nIn a message dated 9/24/2002 11:24:58 AM, ...   \n",
       "01074.8590d61ac0aeeadb58dc2f2ba776c406  Hiya, I always seem to get errors when I do an...   \n",
       "02479.14365bcad3a60fcf24c5c1813f6291fb  \\n\\nI don't know how one can expect better and...   \n",
       "01417.ce7b07a2114218dbac682b599785820d  Tim Peters wrote:\\n\\n> I've run no experiments...   \n",
       "00357.d559b71616f64ba1d1c1e61a03644fd4  At 10:34 AM -0700 on 8/28/02, Jim Whitehead wr...   \n",
       "\n",
       "                                        CATEGORY  \n",
       "00769.25bf9a767b5db0ed93f03c1637281663         0  \n",
       "01074.8590d61ac0aeeadb58dc2f2ba776c406         0  \n",
       "02479.14365bcad3a60fcf24c5c1813f6291fb         0  \n",
       "01417.ce7b07a2114218dbac682b599785820d         0  \n",
       "00357.d559b71616f64ba1d1c1e61a03644fd4         0  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ham_emails = df_from_directory(EASY_NONSPAM_1_PATH, HAM_CAT)\n",
    "ham_emails = ham_emails.append(df_from_directory(EASY_NONSPAM_2_PATH, HAM_CAT))\n",
    "ham_emails.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3901, 2)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ham_emails.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Shape of entire dataframe is  (5799, 2)\n"
     ]
    },
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>MESSAGE</th>\n",
       "      <th>CATEGORY</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>00249.5f45607c1bffe89f60ba1ec9f878039a</td>\n",
       "      <td>Dear Homeowner,\\n\\n \\n\\nInterest Rates are at ...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>00373.ebe8670ac56b04125c25100a36ab0510</td>\n",
       "      <td>ATTENTION: This is a MUST for ALL Computer Use...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>00214.1367039e50dc6b7adb0f2aa8aba83216</td>\n",
       "      <td>This is a multi-part message in MIME format.\\n...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>00210.050ffd105bd4e006771ee63cabc59978</td>\n",
       "      <td>IMPORTANT INFORMATION:\\n\\n\\n\\nThe new domain n...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>00033.9babb58d9298daa2963d4f514193d7d6</td>\n",
       "      <td>This is the bottom line.  If you can GIVE AWAY...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                                                  MESSAGE  \\\n",
       "00249.5f45607c1bffe89f60ba1ec9f878039a  Dear Homeowner,\\n\\n \\n\\nInterest Rates are at ...   \n",
       "00373.ebe8670ac56b04125c25100a36ab0510  ATTENTION: This is a MUST for ALL Computer Use...   \n",
       "00214.1367039e50dc6b7adb0f2aa8aba83216  This is a multi-part message in MIME format.\\n...   \n",
       "00210.050ffd105bd4e006771ee63cabc59978  IMPORTANT INFORMATION:\\n\\n\\n\\nThe new domain n...   \n",
       "00033.9babb58d9298daa2963d4f514193d7d6  This is the bottom line.  If you can GIVE AWAY...   \n",
       "\n",
       "                                        CATEGORY  \n",
       "00249.5f45607c1bffe89f60ba1ec9f878039a         1  \n",
       "00373.ebe8670ac56b04125c25100a36ab0510         1  \n",
       "00214.1367039e50dc6b7adb0f2aa8aba83216         1  \n",
       "00210.050ffd105bd4e006771ee63cabc59978         1  \n",
       "00033.9babb58d9298daa2963d4f514193d7d6         1  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.concat([spam_emails, ham_emails])\n",
    "print('Shape of entire dataframe is ', data.shape)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>MESSAGE</th>\n",
       "      <th>CATEGORY</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>00609.dd49926ce94a1ea328cce9b62825bc97</td>\n",
       "      <td>I'm one of the 30,000 but it's not working ver...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>00957.e0b56b117f3ec5f85e432a9d2a47801f</td>\n",
       "      <td>Damien Morton quoted:\\n\\n&gt;W3C approves HTML 4 ...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>01127.841233b48eceb74a825417d8d918abf8</td>\n",
       "      <td>On Mon, 2002-07-22 at 06:50, che wrote:\\n\\n\\n\\...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>01178.5c977dff972cd6eef64d4173b90307f0</td>\n",
       "      <td>Once upon a time, Manfred wrote :\\n\\n\\n\\n&gt; I w...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>00747.352d424267d36975a7b40b85ffd0885e</td>\n",
       "      <td>If you run Pick, and then use the \"New FTOC\" b...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                                                  MESSAGE  \\\n",
       "00609.dd49926ce94a1ea328cce9b62825bc97  I'm one of the 30,000 but it's not working ver...   \n",
       "00957.e0b56b117f3ec5f85e432a9d2a47801f  Damien Morton quoted:\\n\\n>W3C approves HTML 4 ...   \n",
       "01127.841233b48eceb74a825417d8d918abf8  On Mon, 2002-07-22 at 06:50, che wrote:\\n\\n\\n\\...   \n",
       "01178.5c977dff972cd6eef64d4173b90307f0  Once upon a time, Manfred wrote :\\n\\n\\n\\n> I w...   \n",
       "00747.352d424267d36975a7b40b85ffd0885e  If you run Pick, and then use the \"New FTOC\" b...   \n",
       "\n",
       "                                        CATEGORY  \n",
       "00609.dd49926ce94a1ea328cce9b62825bc97         0  \n",
       "00957.e0b56b117f3ec5f85e432a9d2a47801f         0  \n",
       "01127.841233b48eceb74a825417d8d918abf8         0  \n",
       "01178.5c977dff972cd6eef64d4173b90307f0         0  \n",
       "00747.352d424267d36975a7b40b85ffd0885e         0  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data Cleaning: Checking for Missing Values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# check if any message bodies are null\n",
    "data['MESSAGE'].isnull().values.any()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# check if there are empty emails\n",
    "(data.MESSAGE.str.len() == 0).any()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(data.MESSAGE.str.len() == 0).sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Locate Empty Emails"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['cmds', 'cmds', 'cmds'], dtype='object')"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[data.MESSAGE.str.len() == 0].index"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Remove System File Entries from Dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "data.drop(['cmds'], inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(5796, 2)"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Add Document IDs to Track Emails in Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "document_ids = range(0, len(data.index))\n",
    "data['DOC_ID'] = document_ids"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "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>MESSAGE</th>\n",
       "      <th>CATEGORY</th>\n",
       "      <th>FILE_NAME</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DOC_ID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>Dear Homeowner,\\n\\n \\n\\nInterest Rates are at ...</td>\n",
       "      <td>1</td>\n",
       "      <td>00249.5f45607c1bffe89f60ba1ec9f878039a</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>ATTENTION: This is a MUST for ALL Computer Use...</td>\n",
       "      <td>1</td>\n",
       "      <td>00373.ebe8670ac56b04125c25100a36ab0510</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>This is a multi-part message in MIME format.\\n...</td>\n",
       "      <td>1</td>\n",
       "      <td>00214.1367039e50dc6b7adb0f2aa8aba83216</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>IMPORTANT INFORMATION:\\n\\n\\n\\nThe new domain n...</td>\n",
       "      <td>1</td>\n",
       "      <td>00210.050ffd105bd4e006771ee63cabc59978</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>This is the bottom line.  If you can GIVE AWAY...</td>\n",
       "      <td>1</td>\n",
       "      <td>00033.9babb58d9298daa2963d4f514193d7d6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                  MESSAGE  CATEGORY  \\\n",
       "DOC_ID                                                                \n",
       "0       Dear Homeowner,\\n\\n \\n\\nInterest Rates are at ...         1   \n",
       "1       ATTENTION: This is a MUST for ALL Computer Use...         1   \n",
       "2       This is a multi-part message in MIME format.\\n...         1   \n",
       "3       IMPORTANT INFORMATION:\\n\\n\\n\\nThe new domain n...         1   \n",
       "4       This is the bottom line.  If you can GIVE AWAY...         1   \n",
       "\n",
       "                                     FILE_NAME  \n",
       "DOC_ID                                          \n",
       "0       00249.5f45607c1bffe89f60ba1ec9f878039a  \n",
       "1       00373.ebe8670ac56b04125c25100a36ab0510  \n",
       "2       00214.1367039e50dc6b7adb0f2aa8aba83216  \n",
       "3       00210.050ffd105bd4e006771ee63cabc59978  \n",
       "4       00033.9babb58d9298daa2963d4f514193d7d6  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['FILE_NAME'] = data.index\n",
    "data.set_index('DOC_ID', inplace=True)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "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>MESSAGE</th>\n",
       "      <th>CATEGORY</th>\n",
       "      <th>FILE_NAME</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DOC_ID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>5791</td>\n",
       "      <td>I'm one of the 30,000 but it's not working ver...</td>\n",
       "      <td>0</td>\n",
       "      <td>00609.dd49926ce94a1ea328cce9b62825bc97</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5792</td>\n",
       "      <td>Damien Morton quoted:\\n\\n&gt;W3C approves HTML 4 ...</td>\n",
       "      <td>0</td>\n",
       "      <td>00957.e0b56b117f3ec5f85e432a9d2a47801f</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5793</td>\n",
       "      <td>On Mon, 2002-07-22 at 06:50, che wrote:\\n\\n\\n\\...</td>\n",
       "      <td>0</td>\n",
       "      <td>01127.841233b48eceb74a825417d8d918abf8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5794</td>\n",
       "      <td>Once upon a time, Manfred wrote :\\n\\n\\n\\n&gt; I w...</td>\n",
       "      <td>0</td>\n",
       "      <td>01178.5c977dff972cd6eef64d4173b90307f0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5795</td>\n",
       "      <td>If you run Pick, and then use the \"New FTOC\" b...</td>\n",
       "      <td>0</td>\n",
       "      <td>00747.352d424267d36975a7b40b85ffd0885e</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                  MESSAGE  CATEGORY  \\\n",
       "DOC_ID                                                                \n",
       "5791    I'm one of the 30,000 but it's not working ver...         0   \n",
       "5792    Damien Morton quoted:\\n\\n>W3C approves HTML 4 ...         0   \n",
       "5793    On Mon, 2002-07-22 at 06:50, che wrote:\\n\\n\\n\\...         0   \n",
       "5794    Once upon a time, Manfred wrote :\\n\\n\\n\\n> I w...         0   \n",
       "5795    If you run Pick, and then use the \"New FTOC\" b...         0   \n",
       "\n",
       "                                     FILE_NAME  \n",
       "DOC_ID                                          \n",
       "5791    00609.dd49926ce94a1ea328cce9b62825bc97  \n",
       "5792    00957.e0b56b117f3ec5f85e432a9d2a47801f  \n",
       "5793    01127.841233b48eceb74a825417d8d918abf8  \n",
       "5794    01178.5c977dff972cd6eef64d4173b90307f0  \n",
       "5795    00747.352d424267d36975a7b40b85ffd0885e  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Save to File using Pandas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "data.to_json(DATA_JSON_FILE)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Number of Spam Messages Visualised (Charts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    3900\n",
       "1    1896\n",
       "Name: CATEGORY, dtype: int64"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.CATEGORY.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "amount_of_spam = data.CATEGORY.value_counts()[1]\n",
    "amount_of_ham = data.CATEGORY.value_counts()[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 460x460 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "category_names = ['Spam', 'Legit Mail']\n",
    "sizes = [amount_of_spam, amount_of_ham]\n",
    "custom_colors = ['#ff7675','#a29bfe']\n",
    "\n",
    "\n",
    "plt.figure(figsize=(2,2), dpi = 230)\n",
    "plt.pie(sizes, labels=category_names, textprops={'fontsize': 6}, startangle = 90, autopct = '%1.0f%%', colors = custom_colors, pctdistance = 0.8)\n",
    "\n",
    "\n",
    "#making a donut\n",
    "\n",
    "centre_circle = plt.Circle((0,0), radius = 0.6, fc = 'white')\n",
    "plt.gca().add_artist(centre_circle)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Natural Language Processing"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Download the NLTK Resources (Tokenizer & Stopwords)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[nltk_data] Downloading package punkt to\n",
      "[nltk_data]     /Users/vedantshrivastava/nltk_data...\n",
      "[nltk_data]   Package punkt is already up-to-date!\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nltk.download('punkt')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[nltk_data] Downloading package stopwords to\n",
      "[nltk_data]     /Users/vedantshrivastava/nltk_data...\n",
      "[nltk_data]   Package stopwords is already up-to-date!\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nltk.download('stopwords')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Functions for Email Processing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "def clean_msg_no_html(message, stemmer=PorterStemmer(), stop_words=set(stopwords.words('english'))):\n",
    "    \n",
    "    # remove HTML tags\n",
    "    \n",
    "    soup = BeautifulSoup(message, 'html.parser')\n",
    "    cleaned_text = soup.get_text()\n",
    "    \n",
    "    words = word_tokenize(cleaned_text.lower()) #converts to lower case and splits up individual words\n",
    "    \n",
    "    filtered_words = []\n",
    "    \n",
    "    for word in words:\n",
    "        # removes stop words and punctuation\n",
    "        if word not in stop_words and word.isalpha():\n",
    "            filtered_words.append(stemmer.stem(word))\n",
    "    \n",
    "    \n",
    "    \n",
    "    return filtered_words"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['dear',\n",
       " 'mr',\n",
       " 'still',\n",
       " 'good',\n",
       " 'tide',\n",
       " 'staff',\n",
       " 'festiv',\n",
       " 'season',\n",
       " 'ahead',\n",
       " 'christma',\n",
       " 'crux',\n",
       " 'fulli',\n",
       " 'qualifi',\n",
       " 'santa',\n",
       " 'clau',\n",
       " 'wonder',\n",
       " 'whether',\n",
       " 'might',\n",
       " 'consid',\n",
       " 'run',\n",
       " 'santa',\n",
       " 'grotto',\n",
       " 'store',\n",
       " 'wait',\n",
       " 'probabl',\n",
       " 'think',\n",
       " 'make',\n",
       " 'special',\n",
       " 'well',\n",
       " 'first',\n",
       " 'made',\n",
       " 'sever',\n",
       " 'chang',\n",
       " 'characteris',\n",
       " 'father',\n",
       " 'christma',\n",
       " 'rather',\n",
       " 'greet',\n",
       " 'children',\n",
       " 'shout',\n",
       " 'ho',\n",
       " 'ho',\n",
       " 'ho',\n",
       " 'prefer',\n",
       " 'whisper',\n",
       " 'phrase',\n",
       " 'depend',\n",
       " 'unfathom',\n",
       " 'cruel',\n",
       " 'world',\n",
       " 'live',\n",
       " 'addit',\n",
       " 'gift',\n",
       " 'rang',\n",
       " 'felt',\n",
       " 'hoop',\n",
       " 'holder',\n",
       " 'note',\n",
       " 'also',\n",
       " 'enclos',\n",
       " 'sketch',\n",
       " 'radic',\n",
       " 'redesign',\n",
       " 'santa',\n",
       " 'outfit',\n",
       " 'renam',\n",
       " 'charact',\n",
       " 'lord',\n",
       " 'buckl',\n",
       " 'would',\n",
       " 'interest',\n",
       " 'employ',\n",
       " 'promis',\n",
       " 'never',\n",
       " 'let',\n",
       " 'look',\n",
       " 'forward',\n",
       " 'hear',\n",
       " 'best',\n",
       " 'wish',\n",
       " 'robin',\n",
       " 'cooper',\n",
       " 'excerpt',\n",
       " 'book',\n",
       " 'timewast',\n",
       " 'letter',\n",
       " 'robin',\n",
       " 'cooper']"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clean_msg_no_html(email_body)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Apply Cleaning and Tokenization to all messages"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Slicing Dataframes and Series and Creating Subsets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/vedantshrivastava/opt/anaconda3/lib/python3.7/site-packages/bs4/__init__.py:357: UserWarning: \"http://www.post-gazette.com/columnists/20020905brian5\n",
      "\" looks like a URL. Beautiful Soup is not an HTTP client. You should probably use an HTTP client like requests to get the document behind the URL, and feed that document to Beautiful Soup.\n",
      "  ' that document to Beautiful Soup.' % decoded_markup\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 29.1 s, sys: 57.6 ms, total: 29.2 s\n",
      "Wall time: 29.2 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "\n",
    "#use apply() on all the messages in the dataframe\n",
    "nested_list = data.MESSAGE.apply(clean_msg_no_html)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DOC_ID\n",
       "0    [dear, homeown, interest, rate, lowest, point,...\n",
       "1    [attent, must, comput, user, packag, deal, nor...\n",
       "2    [messag, mime, format, dare, tri, find, better...\n",
       "3    [import, inform, new, domain, name, final, ava...\n",
       "4    [bottom, line, give, away, cd, free, peopl, li...\n",
       "Name: MESSAGE, dtype: object"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nested_list.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DOC_ID\n",
       "5791    [one, work, well, week, te, updat, server, syn...\n",
       "5792    [damien, morton, quot, approv, html, abl, say,...\n",
       "5793    [mon, che, wrote, that, correct, line, ad, rep...\n",
       "5794    [upon, time, manfr, wrote, would, like, instal...\n",
       "5795    [run, pick, use, new, ftoc, button, show, mess...\n",
       "Name: MESSAGE, dtype: object"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nested_list.tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Using Logic to Slice Dataframes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "doc_ids_spam = data[data.CATEGORY == 1].index\n",
    "doc_ids_ham = data[data.CATEGORY == 0].index"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Subsetting a Series with an Index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "nested_list_ham = nested_list.loc[doc_ids_ham]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3900,)"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nested_list_ham.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "nested_list_spam = nested_list.loc[doc_ids_spam]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1896,)"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nested_list_spam.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "20755"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "flat_list_ham = [item for sublist in nested_list_ham for item in sublist]\n",
    "normal_words = pd.Series(flat_list_ham).value_counts()\n",
    "\n",
    "normal_words.shape[0] #total number of unique words in the non-spam messages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "http      7561\n",
       "use       3630\n",
       "list      2878\n",
       "one       2371\n",
       "get       2284\n",
       "mail      2255\n",
       "would     2003\n",
       "like      1928\n",
       "messag    1847\n",
       "work      1798\n",
       "dtype: int64"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "normal_words[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "13284"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "flat_list_spam = [item for sublist in nested_list_spam for item in sublist]\n",
    "spammy_words = pd.Series(flat_list_spam).value_counts()\n",
    "\n",
    "spammy_words.shape[0] #total number of unique words in the spam messages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "http      3101\n",
       "email     3094\n",
       "free      2555\n",
       "click     2058\n",
       "receiv    1987\n",
       "list      1974\n",
       "get       1903\n",
       "pleas     1842\n",
       "busi      1792\n",
       "order     1743\n",
       "dtype: int64"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "spammy_words[:10]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Word Cloud of Ham and Spam Messages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 12.8 s, sys: 1.99 s, total: 14.8 s\n",
      "Wall time: 12.4 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "\n",
    "icon = Image.open(THUMBS_UP_FILE)\n",
    "image_mask = Image.new(mode='RGB', size = icon.size, color = (255,255,255))\n",
    "image_mask.paste(icon, box=icon)\n",
    "\n",
    "rgb_array = np.array(image_mask) #converts the image object to an array\n",
    "\n",
    "# Generate the text as a string for the word cloud\n",
    "ham_str = ' '.join(flat_list_ham)\n",
    "\n",
    "word_cloud = WordCloud(mask=rgb_array, background_color = 'white', max_words = 500, colormap = 'ocean', max_font_size = 2000, font_path = CUSTOM_FONT_FILE)\n",
    "word_cloud.generate(ham_str.upper())\n",
    "\n",
    "plt.figure(figsize=[16,8])\n",
    "plt.imshow(word_cloud, interpolation = 'bilinear')\n",
    "plt.axis('off')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 44.1 s, sys: 12.6 s, total: 56.7 s\n",
      "Wall time: 54.3 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "\n",
    "icon = Image.open(THUMBS_DOWN_FILE)\n",
    "image_mask = Image.new(mode='RGB', size = icon.size, color = (255,255,255))\n",
    "image_mask.paste(icon, box=icon)\n",
    "\n",
    "rgb_array = np.array(image_mask) #converts the image object to an array\n",
    "\n",
    "# Generate the text as a string for the word cloud\n",
    "spam_str = ' '.join(flat_list_spam)\n",
    "\n",
    "word_cloud = WordCloud(mask=rgb_array, background_color = 'white', max_words = 2000, colormap = 'gist_heat', max_font_size = 300, font_path = CUSTOM_FONT_FILE)\n",
    "word_cloud.generate(spam_str.upper())\n",
    "\n",
    "plt.figure(figsize=[16,8])\n",
    "plt.imshow(word_cloud, interpolation = 'bilinear')\n",
    "plt.axis('off')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Generate Vocabulary & Dictionary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "stemmed_nested_list = data.MESSAGE.apply(clean_msg_no_html)\n",
    "flat_stemmed_list = [item for sublist in stemmed_nested_list for item in sublist]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of unique words 27305\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "http     10662\n",
       "use       5017\n",
       "list      4852\n",
       "email     4370\n",
       "get       4187\n",
       "dtype: int64"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "unique_words = pd.Series(flat_stemmed_list).value_counts()\n",
    "print('Number of unique words', unique_words.shape[0])\n",
    "unique_words.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Most common words: \n",
      " http     10662\n",
      "use       5017\n",
      "list      4852\n",
      "email     4370\n",
      "get       4187\n",
      "mail      3985\n",
      "one       3905\n",
      "free      3171\n",
      "time      3090\n",
      "work      2880\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "frequent_words = unique_words[0:VOCAB_SIZE]\n",
    "print('Most common words: \\n', frequent_words[:10])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Create Vocabulary DataFrame with a WORD_ID"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "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>VOCAB_WORD</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WORD_ID</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>http</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>use</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>list</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>email</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>get</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        VOCAB_WORD\n",
       "WORD_ID           \n",
       "0             http\n",
       "1              use\n",
       "2             list\n",
       "3            email\n",
       "4              get"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "word_ids = list(range(0, VOCAB_SIZE))\n",
    "vocab = pd.DataFrame({'VOCAB_WORD': frequent_words.index.values}, index = word_ids)\n",
    "vocab.index.name = 'WORD_ID'\n",
    "vocab.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Save the Vocabulary as a CSV File"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "vocab.to_csv(WORD_ID_FILE, index_label = vocab.index.name, header= vocab.VOCAB_WORD.name)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Generate Features and a Sparse Matrix\n",
    "\n",
    "## Creating a Dataframe with one word per column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "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>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "      <th>...</th>\n",
       "      <th>7661</th>\n",
       "      <th>7662</th>\n",
       "      <th>7663</th>\n",
       "      <th>7664</th>\n",
       "      <th>7665</th>\n",
       "      <th>7666</th>\n",
       "      <th>7667</th>\n",
       "      <th>7668</th>\n",
       "      <th>7669</th>\n",
       "      <th>7670</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>dear</td>\n",
       "      <td>homeown</td>\n",
       "      <td>interest</td>\n",
       "      <td>rate</td>\n",
       "      <td>lowest</td>\n",
       "      <td>point</td>\n",
       "      <td>year</td>\n",
       "      <td>help</td>\n",
       "      <td>find</td>\n",
       "      <td>best</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>attent</td>\n",
       "      <td>must</td>\n",
       "      <td>comput</td>\n",
       "      <td>user</td>\n",
       "      <td>packag</td>\n",
       "      <td>deal</td>\n",
       "      <td>norton</td>\n",
       "      <td>systemwork</td>\n",
       "      <td>softwar</td>\n",
       "      <td>suit</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>messag</td>\n",
       "      <td>mime</td>\n",
       "      <td>format</td>\n",
       "      <td>dare</td>\n",
       "      <td>tri</td>\n",
       "      <td>find</td>\n",
       "      <td>better</td>\n",
       "      <td>annuiti</td>\n",
       "      <td>guarante</td>\n",
       "      <td>year</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>import</td>\n",
       "      <td>inform</td>\n",
       "      <td>new</td>\n",
       "      <td>domain</td>\n",
       "      <td>name</td>\n",
       "      <td>final</td>\n",
       "      <td>avail</td>\n",
       "      <td>gener</td>\n",
       "      <td>public</td>\n",
       "      <td>discount</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>bottom</td>\n",
       "      <td>line</td>\n",
       "      <td>give</td>\n",
       "      <td>away</td>\n",
       "      <td>cd</td>\n",
       "      <td>free</td>\n",
       "      <td>peopl</td>\n",
       "      <td>like</td>\n",
       "      <td>one</td>\n",
       "      <td>month</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 7671 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     0        1         2       3       4      5       6           7     \\\n",
       "0    dear  homeown  interest    rate  lowest  point    year        help   \n",
       "1  attent     must    comput    user  packag   deal  norton  systemwork   \n",
       "2  messag     mime    format    dare     tri   find  better     annuiti   \n",
       "3  import   inform       new  domain    name  final   avail       gener   \n",
       "4  bottom     line      give    away      cd   free   peopl        like   \n",
       "\n",
       "       8         9     ...  7661  7662  7663  7664  7665  7666  7667  7668  \\\n",
       "0      find      best  ...  None  None  None  None  None  None  None  None   \n",
       "1   softwar      suit  ...  None  None  None  None  None  None  None  None   \n",
       "2  guarante      year  ...  None  None  None  None  None  None  None  None   \n",
       "3    public  discount  ...  None  None  None  None  None  None  None  None   \n",
       "4       one     month  ...  None  None  None  None  None  None  None  None   \n",
       "\n",
       "   7669  7670  \n",
       "0  None  None  \n",
       "1  None  None  \n",
       "2  None  None  \n",
       "3  None  None  \n",
       "4  None  None  \n",
       "\n",
       "[5 rows x 7671 columns]"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "word_columns_df = pd.DataFrame.from_records(stemmed_nested_list.tolist())\n",
    "word_columns_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(5796, 7671)"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "word_columns_df.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Splitting the Data into Training and Testing Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train, X_test, y_train, y_test = train_test_split(word_columns_df, data.CATEGORY, test_size = 0.3, random_state = 42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of training samples: 4057\n",
      "Fraction of training set: 0.6999654934437544\n"
     ]
    }
   ],
   "source": [
    "print('Number of training samples:', X_train.shape[0])\n",
    "print('Fraction of training set:', X_train.shape[0]/word_columns_df.shape[0 ])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "      <th>...</th>\n",
       "      <th>7661</th>\n",
       "      <th>7662</th>\n",
       "      <th>7663</th>\n",
       "      <th>7664</th>\n",
       "      <th>7665</th>\n",
       "      <th>7666</th>\n",
       "      <th>7667</th>\n",
       "      <th>7668</th>\n",
       "      <th>7669</th>\n",
       "      <th>7670</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DOC_ID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>4844</td>\n",
       "      <td>thu</td>\n",
       "      <td>jul</td>\n",
       "      <td>rodent</td>\n",
       "      <td>unusu</td>\n",
       "      <td>size</td>\n",
       "      <td>wrote</td>\n",
       "      <td>appli</td>\n",
       "      <td>one</td>\n",
       "      <td>three</td>\n",
       "      <td>order</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4727</td>\n",
       "      <td>well</td>\n",
       "      <td>would</td>\n",
       "      <td>vaniti</td>\n",
       "      <td>list</td>\n",
       "      <td>forward</td>\n",
       "      <td>least</td>\n",
       "      <td>littl</td>\n",
       "      <td>pure</td>\n",
       "      <td>data</td>\n",
       "      <td>week</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5022</td>\n",
       "      <td>world</td>\n",
       "      <td>wide</td>\n",
       "      <td>word</td>\n",
       "      <td>issu</td>\n",
       "      <td>saturday</td>\n",
       "      <td>august</td>\n",
       "      <td>sent</td>\n",
       "      <td>saturday</td>\n",
       "      <td>subscrib</td>\n",
       "      <td>least</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3504</td>\n",
       "      <td>believ</td>\n",
       "      <td>spamassassin</td>\n",
       "      <td>maintain</td>\n",
       "      <td>scheme</td>\n",
       "      <td>wherebi</td>\n",
       "      <td>corpu</td>\n",
       "      <td>distribut</td>\n",
       "      <td>ie</td>\n",
       "      <td>sever</td>\n",
       "      <td>peopl</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3921</td>\n",
       "      <td>sorri</td>\n",
       "      <td>think</td>\n",
       "      <td>send</td>\n",
       "      <td>realiz</td>\n",
       "      <td>list</td>\n",
       "      <td>sender</td>\n",
       "      <td>usual</td>\n",
       "      <td>anyawi</td>\n",
       "      <td>ask</td>\n",
       "      <td>harri</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 7671 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          0             1         2       3         4       5          6     \\\n",
       "DOC_ID                                                                        \n",
       "4844       thu           jul    rodent   unusu      size   wrote      appli   \n",
       "4727      well         would    vaniti    list   forward   least      littl   \n",
       "5022     world          wide      word    issu  saturday  august       sent   \n",
       "3504    believ  spamassassin  maintain  scheme   wherebi   corpu  distribut   \n",
       "3921     sorri         think      send  realiz      list  sender      usual   \n",
       "\n",
       "            7         8      9     ...  7661  7662  7663  7664  7665  7666  \\\n",
       "DOC_ID                             ...                                       \n",
       "4844         one     three  order  ...  None  None  None  None  None  None   \n",
       "4727        pure      data   week  ...  None  None  None  None  None  None   \n",
       "5022    saturday  subscrib  least  ...  None  None  None  None  None  None   \n",
       "3504          ie     sever  peopl  ...  None  None  None  None  None  None   \n",
       "3921      anyawi       ask  harri  ...  None  None  None  None  None  None   \n",
       "\n",
       "        7667  7668  7669  7670  \n",
       "DOC_ID                          \n",
       "4844    None  None  None  None  \n",
       "4727    None  None  None  None  \n",
       "5022    None  None  None  None  \n",
       "3504    None  None  None  None  \n",
       "3921    None  None  None  None  \n",
       "\n",
       "[5 rows x 7671 columns]"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_train.index.name = X_test.index.name = 'DOC_ID'\n",
    "X_train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DOC_ID\n",
       "4844    0\n",
       "4727    0\n",
       "5022    0\n",
       "3504    0\n",
       "3921    0\n",
       "Name: CATEGORY, dtype: int64"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_train.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create a Sparse Matrix for the Training Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "word_index = pd.Index(vocab.VOCAB_WORD)\n",
    "def make_sparse_matrix(df, indexed_words, labels):\n",
    "    \"\"\"\n",
    "    Returns sparse matrix as dataframe\n",
    "    \n",
    "    df: A dataframe with words in the columns with a document id as an index (X_train or X_test)\n",
    "    indexed_words: index of words ordered by word id\n",
    "    labels: category as a series (y_train or y_test)\n",
    "    \"\"\"\n",
    "    \n",
    "    nr_rows = df.shape[0]\n",
    "    nr_cols = df.shape[1]\n",
    "    word_set = set(indexed_words)\n",
    "    dict_list = []\n",
    "    \n",
    "    for i in range(nr_rows):\n",
    "        for j in range(nr_cols):\n",
    "            \n",
    "            word = df.iat[i,j]\n",
    "            if word in word_set:\n",
    "                doc_id = df.index[i]\n",
    "                word_id = indexed_words.get_loc(word)\n",
    "                category = labels.at[doc_id]\n",
    "                \n",
    "                item = {'LABEL': category, 'DOC_ID': doc_id, 'OCCURENCE': 1, 'WORD_ID': word_id}\n",
    "                \n",
    "                dict_list.append(item)\n",
    "    \n",
    "    return pd.DataFrame(dict_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 2min 5s, sys: 178 ms, total: 2min 5s\n",
      "Wall time: 2min 5s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "sparse_train_df = make_sparse_matrix(X_train, word_index, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
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       "      <th>DOC_ID</th>\n",
       "      <th>OCCURENCE</th>\n",
       "      <th>WORD_ID</th>\n",
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       "      <td>1</td>\n",
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       "      <td>2402</td>\n",
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       "      <td>3</td>\n",
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       "      <td>1</td>\n",
       "      <td>496</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>4844</td>\n",
       "      <td>1</td>\n",
       "      <td>37</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   LABEL  DOC_ID  OCCURENCE  WORD_ID\n",
       "0      0    4844          1      395\n",
       "1      0    4844          1      494\n",
       "2      0    4844          1     2402\n",
       "3      0    4844          1      496\n",
       "4      0    4844          1       37"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sparse_train_df[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(445868, 4)"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sparse_train_df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    .dataframe tbody tr th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>LABEL</th>\n",
       "      <th>DOC_ID</th>\n",
       "      <th>OCCURENCE</th>\n",
       "      <th>WORD_ID</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>445863</td>\n",
       "      <td>1</td>\n",
       "      <td>860</td>\n",
       "      <td>1</td>\n",
       "      <td>126</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>445864</td>\n",
       "      <td>1</td>\n",
       "      <td>860</td>\n",
       "      <td>1</td>\n",
       "      <td>651</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>445865</td>\n",
       "      <td>1</td>\n",
       "      <td>860</td>\n",
       "      <td>1</td>\n",
       "      <td>518</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>445866</td>\n",
       "      <td>1</td>\n",
       "      <td>860</td>\n",
       "      <td>1</td>\n",
       "      <td>1394</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>445867</td>\n",
       "      <td>1</td>\n",
       "      <td>860</td>\n",
       "      <td>1</td>\n",
       "      <td>1078</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        LABEL  DOC_ID  OCCURENCE  WORD_ID\n",
       "445863      1     860          1      126\n",
       "445864      1     860          1      651\n",
       "445865      1     860          1      518\n",
       "445866      1     860          1     1394\n",
       "445867      1     860          1     1078"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sparse_train_df[-5:]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Combine Occurences with the Pandas groupby() Method"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "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",
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       "\n",
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       "        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></th>\n",
       "      <th></th>\n",
       "      <th>OCCURENCE</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DOC_ID</th>\n",
       "      <th>WORD_ID</th>\n",
       "      <th>LABEL</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td rowspan=\"5\" valign=\"top\">0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>15</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>18</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>24</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      OCCURENCE\n",
       "DOC_ID WORD_ID LABEL           \n",
       "0      0       1              2\n",
       "       7       1              1\n",
       "       15      1              1\n",
       "       18      1              1\n",
       "       24      1              1"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_grouped = sparse_train_df.groupby(['DOC_ID', 'WORD_ID', 'LABEL']).sum()\n",
    "train_grouped.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'http'"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vocab.at[0,'VOCAB_WORD']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "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>DOC_ID</th>\n",
       "      <th>WORD_ID</th>\n",
       "      <th>LABEL</th>\n",
       "      <th>OCCURENCE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
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       "      <td>0</td>\n",
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       "      <td>7</td>\n",
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       "      <td>1</td>\n",
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       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>18</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>24</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   DOC_ID  WORD_ID  LABEL  OCCURENCE\n",
       "0       0        0      1          2\n",
       "1       0        7      1          1\n",
       "2       0       15      1          1\n",
       "3       0       18      1          1\n",
       "4       0       24      1          1"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_grouped = train_grouped.reset_index()\n",
    "train_grouped.head() "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>DOC_ID</th>\n",
       "      <th>WORD_ID</th>\n",
       "      <th>LABEL</th>\n",
       "      <th>OCCURENCE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>265374</td>\n",
       "      <td>5795</td>\n",
       "      <td>1896</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <td>265375</td>\n",
       "      <td>5795</td>\n",
       "      <td>1908</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
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       "    <tr>\n",
       "      <td>265376</td>\n",
       "      <td>5795</td>\n",
       "      <td>2128</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>265377</td>\n",
       "      <td>5795</td>\n",
       "      <td>2300</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>265378</td>\n",
       "      <td>5795</td>\n",
       "      <td>2478</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        DOC_ID  WORD_ID  LABEL  OCCURENCE\n",
       "265374    5795     1896      0          1\n",
       "265375    5795     1908      0          2\n",
       "265376    5795     2128      0          1\n",
       "265377    5795     2300      0          1\n",
       "265378    5795     2478      0          1"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_grouped.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'welch'"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vocab.at[1908, 'VOCAB_WORD']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'If you run Pick, and then use the \"New FTOC\" button to show only\\n\\nthose messages selected by pick, then the ftoc display was considered\\n\\n\"invalid\" in the old code.  This prevented the display from being cached,\\n\\nand it meant that you could get back to the full folder display by\\n\\nclicking on the folder lablel.  That doesn\\'t work anymore.  You have\\n\\nto resort to Rescan Folder.  In fact, when you change folders you\\n\\ncontinue to have the Pick results, not the new folder contents.\\n\\nIf you go to a any folder and do Rescan, then it heals itself.\\n\\n--\\n\\nBrent Welch\\n\\nSoftware Architect, Panasas Inc\\n\\nPioneering the World\\'s Most Scalable and Agile Storage Network\\n\\nwww.panasas.com\\n\\nwelch@panasas.com\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n_______________________________________________\\n\\nExmh-workers mailing list\\n\\nExmh-workers@redhat.com\\n\\nhttps://listman.redhat.com/mailman/listinfo/exmh-workers\\n\\n\\n\\n\\n'"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.MESSAGE[5795]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(265379, 4)"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_grouped.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Save Training Data as .txt File"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [],
   "source": [
    "np.savetxt(TRAINING_DATA_FILE, train_grouped, fmt='%d')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['DOC_ID', 'WORD_ID', 'LABEL', 'OCCURENCE'], dtype='object')"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_grouped.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Create a Sparse Matrix for the Test Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th>DOC_ID</th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <td>4675</td>\n",
       "      <td>could</td>\n",
       "      <td>tri</td>\n",
       "      <td>httrack</td>\n",
       "      <td>avail</td>\n",
       "      <td>http</td>\n",
       "      <td>recurs</td>\n",
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       "      <td>...</td>\n",
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       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
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       "    <tr>\n",
       "      <td>4220</td>\n",
       "      <td>adam</td>\n",
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       "      <td>wrote</td>\n",
       "      <td>creator</td>\n",
       "      <td>didnt</td>\n",
       "      <td>say</td>\n",
       "      <td>could</td>\n",
       "      <td>without</td>\n",
       "      <td>pay</td>\n",
       "      <td>theft</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2484</td>\n",
       "      <td>gari</td>\n",
       "      <td>lawrenc</td>\n",
       "      <td>murphi</td>\n",
       "      <td>wrote</td>\n",
       "      <td>say</td>\n",
       "      <td>hello</td>\n",
       "      <td>cool</td>\n",
       "      <td>oooo</td>\n",
       "      <td>go</td>\n",
       "      <td>caus</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2418</td>\n",
       "      <td>wasnt</td>\n",
       "      <td>even</td>\n",
       "      <td>though</td>\n",
       "      <td>spellingi</td>\n",
       "      <td>oddli</td>\n",
       "      <td>familar</td>\n",
       "      <td>news</td>\n",
       "      <td>fork</td>\n",
       "      <td>randomis</td>\n",
       "      <td>letter</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
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       "    <tr>\n",
       "      <td>5110</td>\n",
       "      <td>gari</td>\n",
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       "      <td>legal</td>\n",
       "      <td>violent</td>\n",
       "      <td>action</td>\n",
       "      <td>peopl</td>\n",
       "      <td>world</td>\n",
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       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 7671 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         0        1        2          3      4        5       6        7     \\\n",
       "DOC_ID                                                                        \n",
       "4675    could      tri  httrack      avail   http   recurs    grab    stuff   \n",
       "4220     adam   beberg    wrote    creator  didnt      say   could  without   \n",
       "2484     gari  lawrenc   murphi      wrote    say    hello    cool     oooo   \n",
       "2418    wasnt     even   though  spellingi  oddli  familar    news     fork   \n",
       "5110     gari   murphi   intend       take  legal  violent  action    peopl   \n",
       "\n",
       "            8       9     ...  7661  7662  7663  7664  7665  7666  7667  7668  \\\n",
       "DOC_ID                    ...                                                   \n",
       "4675         get  pictur  ...  None  None  None  None  None  None  None  None   \n",
       "4220         pay   theft  ...  None  None  None  None  None  None  None  None   \n",
       "2484          go    caus  ...  None  None  None  None  None  None  None  None   \n",
       "2418    randomis  letter  ...  None  None  None  None  None  None  None  None   \n",
       "5110       world    away  ...  None  None  None  None  None  None  None  None   \n",
       "\n",
       "        7669  7670  \n",
       "DOC_ID              \n",
       "4675    None  None  \n",
       "4220    None  None  \n",
       "2484    None  None  \n",
       "2418    None  None  \n",
       "5110    None  None  \n",
       "\n",
       "[5 rows x 7671 columns]"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_test.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DOC_ID\n",
       "4675    0\n",
       "4220    0\n",
       "2484    0\n",
       "2418    0\n",
       "5110    0\n",
       "Name: CATEGORY, dtype: int64"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_test.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1739, 7671)"
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_test.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 55.4 s, sys: 196 ms, total: 55.6 s\n",
      "Wall time: 55.6 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "\n",
    "sparse_test_df = make_sparse_matrix(X_test, word_index, y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(188265, 4)"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sparse_test_df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "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>DOC_ID</th>\n",
       "      <th>WORD_ID</th>\n",
       "      <th>LABEL</th>\n",
       "      <th>OCCURENCE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>8</td>\n",
       "      <td>12</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>8</td>\n",
       "      <td>19</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>8</td>\n",
       "      <td>26</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   DOC_ID  WORD_ID  LABEL  OCCURENCE\n",
       "0       8        7      1          1\n",
       "1       8        8      1          1\n",
       "2       8       12      1          1\n",
       "3       8       19      1          2\n",
       "4       8       26      1          1"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_grouped = sparse_test_df.groupby(['DOC_ID', 'WORD_ID', 'LABEL']).sum().reset_index()\n",
    "test_grouped.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(110495, 4)"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_grouped.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [],
   "source": [
    "np.savetxt(TEST_DATA_FILE, test_grouped, fmt = '%d')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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