Code-Example-031-Text-PCA.ipynb

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  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "c255ac26",
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys\n",
    "import re\n",
    "import bz2\n",
    "\n",
    "regex = re.compile(\"[^a-zA-Z]\")\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "from sklearn.decomposition import PCA\n",
    "from sklearn.preprocessing import StandardScaler"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c267c31d",
   "metadata": {},
   "source": [
    "# Dataset of Australian legal case and Wikipedia Pages\n",
    "\n",
    "You should download and look at the Court-Wiki-Dataset.txt\n",
    "\n",
    "file before you begin. You’ll see that the contents are sort of a pseudo-XML, where each text document\n",
    "begins with a $<doc \\ id = ... >$ tag, and ends with $</doc>$.\n",
    "\n",
    "Note that all of the Australia legal cases begin with something like $<\\text{doc id = ‘‘AU1222’’ ...}>$\n",
    "that is, the doc id for an Australian legal case always starts with AU. You will be trying to figure out if the\n",
    "document is an Australian legal case by looking only at the contents of the document."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "c567b14d",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Line number:  100\n",
      "Line number:  200\n",
      "Line number:  300\n",
      "Line number:  400\n",
      "Line number:  500\n",
      "Line number:  600\n",
      "Line number:  700\n",
      "Line number:  800\n",
      "Line number:  800\n"
     ]
    },
    {
     "data": {
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       "<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>text</th>\n",
       "      <th>label</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>[purported, appeal, from, orders, made, by, fe...</td>\n",
       "      <td>AU11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>[bankruptcy, noticefailure, by, creditor, to, ...</td>\n",
       "      <td>AU28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>[where, documents, produced, to, commission, o...</td>\n",
       "      <td>AU29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>[leave, to, appealinterlocutory, judgmentwheth...</td>\n",
       "      <td>AU31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>[applicant, a, married, person, who, had, unde...</td>\n",
       "      <td>AU38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>795</th>\n",
       "      <td>[le, landeronle, landeron, is, a, municipality...</td>\n",
       "      <td>6292963</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>796</th>\n",
       "      <td>[saint, blaise, switzerlandsaint, blaise, is, ...</td>\n",
       "      <td>6293133</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>797</th>\n",
       "      <td>[tahirih, justice, centerthe, tahirih, justice...</td>\n",
       "      <td>6220600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>798</th>\n",
       "      <td>[the, ladies, of, grace, adieu, and, other, st...</td>\n",
       "      <td>6221345</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>799</th>\n",
       "      <td>[bring, it, on, alistair, griffin, song, bring...</td>\n",
       "      <td>6303818</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>800 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                  text    label\n",
       "0    [purported, appeal, from, orders, made, by, fe...     AU11\n",
       "1    [bankruptcy, noticefailure, by, creditor, to, ...     AU28\n",
       "2    [where, documents, produced, to, commission, o...     AU29\n",
       "3    [leave, to, appealinterlocutory, judgmentwheth...     AU31\n",
       "4    [applicant, a, married, person, who, had, unde...     AU38\n",
       "..                                                 ...      ...\n",
       "795  [le, landeronle, landeron, is, a, municipality...  6292963\n",
       "796  [saint, blaise, switzerlandsaint, blaise, is, ...  6293133\n",
       "797  [tahirih, justice, centerthe, tahirih, justice...  6220600\n",
       "798  [the, ladies, of, grace, adieu, and, other, st...  6221345\n",
       "799  [bring, it, on, alistair, griffin, song, bring...  6303818\n",
       "\n",
       "[800 rows x 2 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "file = bz2.open(\"./datasets/Court-Wiki-Dataset.txt.bz2\", \"r\")\n",
    "\n",
    "mlist = []\n",
    "\n",
    "\n",
    "count = 0 \n",
    "for line in file:\n",
    "    count +=1\n",
    "\n",
    "    line = (lambda x : (x[x.index('id=\"') + 4 : x.index('\" url=')], x[x.index('\">') + 2:][:-6]))(str(line))\n",
    "    text = np.array(regex.sub(\" \", line[1]).lower().split())\n",
    "    \n",
    "    mlist.append({'text' : text, 'label' : line[0]})\n",
    "\n",
    "\n",
    "    if(count%100==0):\n",
    "        print(\"Line number: \" , count)\n",
    "\n",
    "\n",
    "# text_list\n",
    "print(\"Line number: \" , count)\n",
    "\n",
    "\n",
    "\n",
    "data = pd.DataFrame.from_dict(mlist)\n",
    "\n",
    "data "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "96a8cc96",
   "metadata": {},
   "outputs": [
    {
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       "    .dataframe thead th {\n",
       "        text-align: right;\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>text</th>\n",
       "      <th>label</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>[purported, appeal, from, orders, made, by, fe...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>[bankruptcy, noticefailure, by, creditor, to, ...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
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       "      <th>2</th>\n",
       "      <td>[where, documents, produced, to, commission, o...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>[leave, to, appealinterlocutory, judgmentwheth...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>[applicant, a, married, person, who, had, unde...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>795</th>\n",
       "      <td>[le, landeronle, landeron, is, a, municipality...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>796</th>\n",
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       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>797</th>\n",
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       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>798</th>\n",
       "      <td>[the, ladies, of, grace, adieu, and, other, st...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>799</th>\n",
       "      <td>[bring, it, on, alistair, griffin, song, bring...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>800 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                  text  label\n",
       "0    [purported, appeal, from, orders, made, by, fe...      1\n",
       "1    [bankruptcy, noticefailure, by, creditor, to, ...      1\n",
       "2    [where, documents, produced, to, commission, o...      1\n",
       "3    [leave, to, appealinterlocutory, judgmentwheth...      1\n",
       "4    [applicant, a, married, person, who, had, unde...      1\n",
       "..                                                 ...    ...\n",
       "795  [le, landeronle, landeron, is, a, municipality...      0\n",
       "796  [saint, blaise, switzerlandsaint, blaise, is, ...      0\n",
       "797  [tahirih, justice, centerthe, tahirih, justice...      0\n",
       "798  [the, ladies, of, grace, adieu, and, other, st...      0\n",
       "799  [bring, it, on, alistair, griffin, song, bring...      0\n",
       "\n",
       "[800 rows x 2 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Convert the labels. \n",
    "# if it has AU it means it is an austrial court case report and if not it is a wikipedia article. \n",
    "\n",
    "data['label'] = data['label'].apply(lambda x: 1 if 'AU' in str(x) else 0  )\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "38647955",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[('the', 241893), ('of', 116082), ('to', 90280), ('in', 71618), ('and', 65776), ('a', 56040), ('that', 52481), ('is', 30818), ('was', 28784), ('s', 26366)]\n"
     ]
    }
   ],
   "source": [
    "# Create a Dictionary with all of the words in all documents \n",
    "# Count them up \n",
    "# Get the top 600 most common words. \n",
    "\n",
    "from collections import Counter\n",
    "my_dict=Counter()\n",
    "\n",
    "# iterate through list-string\n",
    "for item in data['text']:\n",
    "    \n",
    "    my_dict += Counter(list(item))\n",
    "    \n",
    "# Print the top 10 just for checking \n",
    "print(my_dict.most_common(10))\n",
    "\n",
    "no_features = 600 \n",
    "# We use the top no_features as our dictionary\n",
    "top_words= my_dict.most_common(no_features)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "049d3afa",
   "metadata": {},
   "outputs": [
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     "data": {
      "text/plain": [
       "('the',\n",
       " 'of',\n",
       " 'to',\n",
       " 'in',\n",
       " 'and',\n",
       " 'a',\n",
       " 'that',\n",
       " 'is',\n",
       " 'was',\n",
       " 's',\n",
       " 'for',\n",
       " 'on',\n",
       " 'by',\n",
       " 'as',\n",
       " 'it',\n",
       " 'not',\n",
       " 'be',\n",
       " 'or',\n",
       " 'at',\n",
       " 'with',\n",
       " 'an',\n",
       " 'which',\n",
       " 'he',\n",
       " 'mr',\n",
       " 'from',\n",
       " 'his',\n",
       " 'this',\n",
       " 'i',\n",
       " 'have',\n",
       " 'had',\n",
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       " 'are',\n",
       " 'x',\n",
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       " 'act',\n",
       " 'has',\n",
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       " 'tribunal',\n",
       " 'no',\n",
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       " 'evidence',\n",
       " 'applicant',\n",
       " 'other',\n",
       " 'also',\n",
       " 'they',\n",
       " 'if',\n",
       " 'under',\n",
       " 'may',\n",
       " 'but',\n",
       " 'one',\n",
       " 'first',\n",
       " 'application',\n",
       " 'their',\n",
       " 'v',\n",
       " 'such',\n",
       " 'her',\n",
       " 'said',\n",
       " 'time',\n",
       " 'xe',\n",
       " 'all',\n",
       " 'decision',\n",
       " 'did',\n",
       " 'appellant',\n",
       " 'case',\n",
       " 'will',\n",
       " 'out',\n",
       " 'whether',\n",
       " 'she',\n",
       " 'about',\n",
       " 'claim',\n",
       " 'order',\n",
       " 'those',\n",
       " 'who',\n",
       " 'so',\n",
       " 'into',\n",
       " 'these',\n",
       " 'when',\n",
       " 'two',\n",
       " 'after',\n",
       " 'part',\n",
       " 'before',\n",
       " 'should',\n",
       " 'only',\n",
       " 'new',\n",
       " 'between',\n",
       " 'some',\n",
       " 'however',\n",
       " 'than',\n",
       " 'information',\n",
       " 'being',\n",
       " 'j',\n",
       " 'respondent',\n",
       " 'xc',\n",
       " 'further',\n",
       " 'do',\n",
       " 'more',\n",
       " 'because',\n",
       " 'each',\n",
       " 'where',\n",
       " 'relevant',\n",
       " 'could',\n",
       " 'costs',\n",
       " 'him',\n",
       " 'appeal',\n",
       " 'person',\n",
       " 'can',\n",
       " 'australia',\n",
       " 'ltd',\n",
       " 'notice',\n",
       " 'what',\n",
       " 'then',\n",
       " 'reasons',\n",
       " 'relation',\n",
       " 'upon',\n",
       " 'federal',\n",
       " 'against',\n",
       " 'my',\n",
       " 'make',\n",
       " 'ms',\n",
       " 'must',\n",
       " 'proceedings',\n",
       " 'within',\n",
       " 'does',\n",
       " 'matter',\n",
       " 'given',\n",
       " 'law',\n",
       " 'them',\n",
       " 'circumstances',\n",
       " 'd',\n",
       " 'section',\n",
       " 'issue',\n",
       " 'second',\n",
       " 'question',\n",
       " 'use',\n",
       " 'respect',\n",
       " 'up',\n",
       " 'company',\n",
       " 'review',\n",
       " 'over',\n",
       " 'particular',\n",
       " 'you',\n",
       " 'fact',\n",
       " 'following',\n",
       " 'same',\n",
       " 'hearing',\n",
       " 'during',\n",
       " 'set',\n",
       " 'conduct',\n",
       " 'provided',\n",
       " 'including',\n",
       " 'xa',\n",
       " 'minister',\n",
       " 'see',\n",
       " 'both',\n",
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       " 'service',\n",
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       " 'number',\n",
       " 'basis',\n",
       " 'respondents',\n",
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       " 'parties',\n",
       " 'years',\n",
       " 'required',\n",
       " 'view',\n",
       " 'three',\n",
       " 'way',\n",
       " 'well',\n",
       " 'australian',\n",
       " 'party',\n",
       " 'subject',\n",
       " 'title',\n",
       " 'letter',\n",
       " 'reason',\n",
       " 'process',\n",
       " 'effect',\n",
       " 'period',\n",
       " 'group',\n",
       " 'am',\n",
       " 'area',\n",
       " 'statement',\n",
       " 'above',\n",
       " 'while',\n",
       " 'commissioner',\n",
       " 'found',\n",
       " 'purpose',\n",
       " 'members',\n",
       " 'submissions',\n",
       " 'having',\n",
       " 'sought',\n",
       " 'commission',\n",
       " 'june',\n",
       " 'matters',\n",
       " 'rights',\n",
       " 'considered',\n",
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       " 'without',\n",
       " 'day',\n",
       " 'honour',\n",
       " 'applicants',\n",
       " 'form',\n",
       " 'year',\n",
       " 'making',\n",
       " 'material',\n",
       " 'november',\n",
       " 'action',\n",
       " 'leave',\n",
       " 'october',\n",
       " 'line',\n",
       " 'taken',\n",
       " 'people',\n",
       " 'take',\n",
       " 'even',\n",
       " 'public',\n",
       " 'might',\n",
       " 'me',\n",
       " 'proposed',\n",
       " 'based',\n",
       " 'affidavit',\n",
       " 'through',\n",
       " 'position',\n",
       " 'c',\n",
       " 'course',\n",
       " 'access',\n",
       " 'most',\n",
       " 'consider',\n",
       " 'satisfied',\n",
       " 'right',\n",
       " 'held',\n",
       " 'determination',\n",
       " 'different',\n",
       " 'contract',\n",
       " 'member',\n",
       " 'provide',\n",
       " 'later',\n",
       " 'report',\n",
       " 'march',\n",
       " 'december',\n",
       " 'legal',\n",
       " 'union',\n",
       " 'support',\n",
       " 'issues',\n",
       " 'result',\n",
       " 'now',\n",
       " 'purposes',\n",
       " 'give',\n",
       " 'although',\n",
       " 'native',\n",
       " 'another',\n",
       " 'high',\n",
       " 'judgment',\n",
       " 'regard',\n",
       " 'r',\n",
       " 'september',\n",
       " 'necessary',\n",
       " 'since',\n",
       " 'july',\n",
       " 'until',\n",
       " 'services',\n",
       " 'interest',\n",
       " 'date',\n",
       " 'reference',\n",
       " 'full',\n",
       " 'third',\n",
       " 'cross',\n",
       " 'appropriate',\n",
       " 'limited',\n",
       " 'account',\n",
       " 'b',\n",
       " 'amount',\n",
       " 'stated',\n",
       " 'accept',\n",
       " 'business',\n",
       " 'very',\n",
       " 'point',\n",
       " 'april',\n",
       " 'filed',\n",
       " 'final',\n",
       " 'many',\n",
       " 'known',\n",
       " 'provides',\n",
       " 'clr',\n",
       " 'fca',\n",
       " 'follows',\n",
       " 'scheme',\n",
       " 'entitled',\n",
       " 'august',\n",
       " 'th',\n",
       " 'place',\n",
       " 'submitted',\n",
       " 'own',\n",
       " 'reasonable',\n",
       " 'hca',\n",
       " 'february',\n",
       " 'meeting',\n",
       " 'design',\n",
       " 'pay',\n",
       " 'consideration',\n",
       " 'available',\n",
       " 'non',\n",
       " 'interests',\n",
       " 'trade',\n",
       " 't',\n",
       " 'grounds',\n",
       " 'claimed',\n",
       " 'national',\n",
       " 'therefore',\n",
       " 'telstra',\n",
       " 'received',\n",
       " 'system',\n",
       " 'pursuant',\n",
       " 'written',\n",
       " 'january',\n",
       " 'opinion',\n",
       " 'we',\n",
       " 'exercise',\n",
       " 'xb',\n",
       " 'production',\n",
       " 'magistrate',\n",
       " 'either',\n",
       " 'dr',\n",
       " 'rules',\n",
       " 'goods',\n",
       " 'north',\n",
       " 'conclusion',\n",
       " 'clear',\n",
       " 'included',\n",
       " 'e',\n",
       " 'counsel',\n",
       " 'provision',\n",
       " 'described',\n",
       " 'site',\n",
       " 'agreed',\n",
       " 'common',\n",
       " 'harrison',\n",
       " 'called',\n",
       " 'nature',\n",
       " 'put',\n",
       " 'alleged',\n",
       " 'construction',\n",
       " 'provisions',\n",
       " 'facts',\n",
       " 'amended',\n",
       " 'visa',\n",
       " 'due',\n",
       " 'world',\n",
       " 'file',\n",
       " 'assessment',\n",
       " 'need',\n",
       " 'noted',\n",
       " 'women',\n",
       " 'prior',\n",
       " 'failed',\n",
       " 'council',\n",
       " 'rather',\n",
       " 'earlier',\n",
       " 'raised',\n",
       " 'end',\n",
       " 'breach',\n",
       " 'school',\n",
       " 'trustee',\n",
       " 'tax',\n",
       " 'states',\n",
       " 'country',\n",
       " 'four',\n",
       " 'gave',\n",
       " 'accepted',\n",
       " 'university',\n",
       " 'involved',\n",
       " 'error',\n",
       " 'authority',\n",
       " 'say',\n",
       " 'persons',\n",
       " 'community',\n",
       " 'fcr',\n",
       " 'government',\n",
       " 'document',\n",
       " 'operation',\n",
       " 'south',\n",
       " 'established',\n",
       " 'o',\n",
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       " 'words',\n",
       " 'cases',\n",
       " 'protection',\n",
       " 'statutory',\n",
       " 'took',\n",
       " 'paragraph',\n",
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       " 'ulls',\n",
       " 'became',\n",
       " 'days',\n",
       " 'trial',\n",
       " 'context',\n",
       " 'itself',\n",
       " 'term',\n",
       " 'again',\n",
       " 'amp',\n",
       " 'product',\n",
       " 'how',\n",
       " 'employment',\n",
       " 'xd',\n",
       " 'various',\n",
       " 'submission',\n",
       " 'long',\n",
       " 'management',\n",
       " 'event',\n",
       " 'dated',\n",
       " 'your',\n",
       " 're',\n",
       " 'failure',\n",
       " 'accc',\n",
       " 'says',\n",
       " 'according',\n",
       " 'motion',\n",
       " 'principles',\n",
       " 'least',\n",
       " 'team',\n",
       " 'patent',\n",
       " 'm',\n",
       " 'much',\n",
       " 'include',\n",
       " 'family',\n",
       " 'association',\n",
       " 'example',\n",
       " 'director',\n",
       " 'affairs',\n",
       " 'request',\n",
       " 'cannot',\n",
       " 'grant',\n",
       " 'applied',\n",
       " 'identified',\n",
       " 'property',\n",
       " 'finding',\n",
       " 'meaning',\n",
       " 'rule',\n",
       " 'able',\n",
       " 'justice',\n",
       " 'program',\n",
       " 'certain',\n",
       " 'related',\n",
       " 'schedule',\n",
       " 'conditions',\n",
       " 'thus',\n",
       " 'body',\n",
       " 'like',\n",
       " 'commonwealth',\n",
       " 'payment',\n",
       " 'name',\n",
       " 'concerned',\n",
       " 'city',\n",
       " 'delegate',\n",
       " 'laws',\n",
       " 'back',\n",
       " 'apply',\n",
       " 'financial',\n",
       " 'medical',\n",
       " 'products',\n",
       " 'registered',\n",
       " 'just',\n",
       " 'likely',\n",
       " 'possible',\n",
       " 'several',\n",
       " 'concerning',\n",
       " 'early',\n",
       " 'immigration',\n",
       " 'control',\n",
       " 'test',\n",
       " 'penalty',\n",
       " 'similar',\n",
       " 'sufficient',\n",
       " 'extent',\n",
       " 'united',\n",
       " 'occurred',\n",
       " 'paid',\n",
       " 'whole',\n",
       " 'findings',\n",
       " 'special',\n",
       " 'standard',\n",
       " 'otherwise',\n",
       " 'housing',\n",
       " 'down',\n",
       " 'home',\n",
       " 'jurisdiction',\n",
       " 'means',\n",
       " 'international',\n",
       " 'asked',\n",
       " 'dismissed',\n",
       " 'additional',\n",
       " 'connection',\n",
       " 'bank',\n",
       " 'history',\n",
       " 'behalf',\n",
       " 'trust',\n",
       " 'response',\n",
       " 'east',\n",
       " 'sent',\n",
       " 'granted',\n",
       " 'accordance',\n",
       " 'why',\n",
       " 'relied',\n",
       " 'committee',\n",
       " 'original',\n",
       " 'led',\n",
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       " 'mark',\n",
       " 'employees',\n",
       " 'benefit',\n",
       " 'off',\n",
       " 'contained',\n",
       " 'still',\n",
       " 'important',\n",
       " 'nor',\n",
       " 'single',\n",
       " 'series',\n",
       " 'five',\n",
       " 'lss',\n",
       " 'accordingly',\n",
       " 'best',\n",
       " 'told',\n",
       " 'cause',\n",
       " 'open',\n",
       " 'return',\n",
       " 'department',\n",
       " 'town',\n",
       " 'requirements',\n",
       " 'discretion',\n",
       " 'water',\n",
       " 'worimi',\n",
       " 'corporation',\n",
       " 'generally',\n",
       " 'primary',\n",
       " 'significant',\n",
       " 'class',\n",
       " 'argument',\n",
       " 'magistrates',\n",
       " 'substantial',\n",
       " 'questions',\n",
       " 'condition',\n",
       " 'season',\n",
       " 'nine',\n",
       " 'together',\n",
       " 'level',\n",
       " 'good',\n",
       " 'de',\n",
       " 'less',\n",
       " 'examination',\n",
       " 'income',\n",
       " 'money',\n",
       " 'professor',\n",
       " 'issued',\n",
       " 'disclosure',\n",
       " 'relating',\n",
       " 'show',\n",
       " 'value',\n",
       " 'times',\n",
       " 'co',\n",
       " 'market',\n",
       " 'left',\n",
       " 'officer',\n",
       " 'judge',\n",
       " 'life',\n",
       " 'already',\n",
       " 'concluded',\n",
       " 'price',\n",
       " 'citalopram',\n",
       " 'months',\n",
       " 'loss',\n",
       " 'code',\n",
       " 'done',\n",
       " 'traditional',\n",
       " 'million',\n",
       " 'obligation',\n",
       " 'total',\n",
       " 'practice',\n",
       " 'addition',\n",
       " 'using',\n",
       " 'far')"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Sorted List of words based on their frequencies\n",
    "my_dict_words = sorted(top_words, key=lambda k: top_words[1])\n",
    "\n",
    "# This is the order of words based on their frequencies\n",
    "# We use this order to create feature vectors for our text corpus. \n",
    "dict_words= list(zip(*my_dict_words))[0]\n",
    "\n",
    "dict_words"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "0ea7120f",
   "metadata": {},
   "outputs": [
    {
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       "      <th>4</th>\n",
       "      <td>{'applicant': 31, 'a': 87, 'married': 21, 'per...</td>\n",
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       "      <th>796</th>\n",
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       "      <th>797</th>\n",
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       "      <th>798</th>\n",
       "      <td>{'the': 122, 'ladies': 6, 'of': 75, 'grace': 6...</td>\n",
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       "    <tr>\n",
       "      <th>799</th>\n",
       "      <td>{'bring': 14, 'it': 21, 'on': 32, 'alistair': ...</td>\n",
       "      <td>0</td>\n",
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       "  </tbody>\n",
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       "<p>800 rows × 2 columns</p>\n",
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      "text/plain": [
       "                                                  text  label\n",
       "0    {'purported': 3, 'appeal': 12, 'from': 3, 'ord...      1\n",
       "1    {'bankruptcy': 21, 'noticefailure': 1, 'by': 2...      1\n",
       "2    {'where': 5, 'documents': 49, 'produced': 1, '...      1\n",
       "3    {'leave': 21, 'to': 68, 'appealinterlocutory':...      1\n",
       "4    {'applicant': 31, 'a': 87, 'married': 21, 'per...      1\n",
       "..                                                 ...    ...\n",
       "795  {'le': 25, 'landeronle': 1, 'landeron': 26, 'i...      0\n",
       "796  {'saint': 12, 'blaise': 12, 'switzerlandsaint'...      0\n",
       "797  {'tahirih': 68, 'justice': 21, 'centerthe': 1,...      0\n",
       "798  {'the': 122, 'ladies': 6, 'of': 75, 'grace': 6...      0\n",
       "799  {'bring': 14, 'it': 21, 'on': 32, 'alistair': ...      0\n",
       "\n",
       "[800 rows x 2 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['text']=data['text'].apply(lambda x:Counter(list(x)) )\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "8e8d7ca6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
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       "        18.,  13.,   7.,  14.,  18.,   3.,   0.,   7.,   8.,  16.,   1.,\n",
       "         7.,   0.,   3.,   1.,   1.,  10.,   7.,   2.,   2.,   3.,   0.,\n",
       "         7.,  11.,   3.,   4.,   3.,   0.,   9.,  23.,   1.,   5.,   6.,\n",
       "         2.,  21.,   0.,   0.,   0.,   2.,  12.,   1.,   3.,   3.,   4.,\n",
       "        12.,   0.,   4.,   0.,  14.,   2.,   2.,   0.,   1.,  12.,  11.,\n",
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       "         3.,   0.,   5.,   0.,   1.,   3.,   2.,   0.,   9.,   1.,   1.,\n",
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       "         1.,   0.,   1.,   1.,   0.,   0.,   0.,   0.,   0.,   5.,   0.,\n",
       "         1.,   0.,   3.,   0.,   0.,  11.,   0.,   1.,   0.,   2.,   1.,\n",
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       "         3.,   0.,   2.,   0.,   0.,   0.,   1.,   0.,   0.,   0.,   0.,\n",
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       "         0.,   0.,   2.,   0.,   0.,   1.,   0.,   0.,   0.,   0.,   0.,\n",
       "         3.,   0.,   0.,   0.,   0.,   0.])"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def convert_words_to_numbers(input_dict_text):\n",
    "    # get a numpy of no_features zeros \n",
    "    a = np.zeros(no_features)\n",
    "    for i in range(no_features):\n",
    "        if (dict_words[i] in input_dict_text):\n",
    "            a[i] = input_dict_text.get(dict_words[i])\n",
    "    return a\n",
    "\n",
    "\n",
    "    \n",
    "convert_words_to_numbers(data['text'][0])        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "5d2a7357",
   "metadata": {},
   "outputs": [
    {
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       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>[124.0, 56.0, 54.0, 24.0, 36.0, 28.0, 47.0, 15...</td>\n",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "      <th>798</th>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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      "text/plain": [
       "     label                                           features\n",
       "0        1  [124.0, 56.0, 54.0, 24.0, 36.0, 28.0, 47.0, 15...\n",
       "1        1  [187.0, 100.0, 79.0, 60.0, 41.0, 56.0, 43.0, 1...\n",
       "2        1  [186.0, 97.0, 77.0, 37.0, 28.0, 23.0, 57.0, 14...\n",
       "3        1  [139.0, 55.0, 68.0, 34.0, 20.0, 33.0, 43.0, 24...\n",
       "4        1  [491.0, 303.0, 193.0, 128.0, 175.0, 87.0, 74.0...\n",
       "..     ...                                                ...\n",
       "795      0  [165.0, 105.0, 27.0, 56.0, 52.0, 31.0, 4.0, 27...\n",
       "796      0  [83.0, 63.0, 10.0, 30.0, 38.0, 16.0, 2.0, 23.0...\n",
       "797      0  [173.0, 84.0, 87.0, 70.0, 115.0, 36.0, 29.0, 1...\n",
       "798      0  [122.0, 75.0, 37.0, 46.0, 57.0, 28.0, 16.0, 32...\n",
       "799      0  [60.0, 24.0, 13.0, 10.0, 19.0, 33.0, 4.0, 3.0,...\n",
       "\n",
       "[800 rows x 2 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['features']=data['text'].apply(lambda x:convert_words_to_numbers(x))\n",
    "data = data.drop(['text'], axis=1)\n",
    "\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "dbd8c4fe",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "count of Australian Court Cases 377\n"
     ]
    }
   ],
   "source": [
    "print(\"count of Australian Court Cases\", len(data[data['label'] ==1]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "c5980b35",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(800, 600)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "X = data['features'].to_numpy()\n",
    "y = data['label']\n",
    "\n",
    "X = np.array(list(map(lambda x: list(x), X)))\n",
    "X.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "f93c5a1d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(800, 3)\n",
      "[0.89824308 0.02900658 0.00710236]\n",
      "[18520.34209506  3328.13027368  1646.84722273]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([[-2.35280314e+02, -1.47833611e+02, -1.61143061e+02, ...,\n",
       "        -1.56042376e+02, -2.34614947e+02, -3.24965428e+02],\n",
       "       [ 1.34808597e+01, -6.15105490e+00,  3.07132448e-01, ...,\n",
       "        -3.41592766e+00, -3.03000609e+00,  1.52923693e+01],\n",
       "       [ 2.23070500e+01,  2.05804124e+01,  1.77344317e+01, ...,\n",
       "        -3.03360976e+00, -1.09067009e+00,  7.17173040e+00]])"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "from sklearn.decomposition import PCA\n",
    "\n",
    "\n",
    "# Use fit and transform method\n",
    "pca = PCA(n_components=3)\n",
    "pca.fit(X)\n",
    "\n",
    "transformed_data=pca.transform(X)\n",
    "print(transformed_data.shape)\n",
    "\n",
    "print(pca.explained_variance_ratio_)\n",
    "print(pca.singular_values_)\n",
    "\n",
    "\n",
    "\n",
    "transformed_data.T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "d3b97b85",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "800"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(data['label'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "a4db0ecd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(3,)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'pc2')"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plt.figure(figsize=(10,10))\n",
    "print(transformed_data[0].shape)\n",
    "plt.scatter(transformed_data.T[0], transformed_data.T[1], c=data['label'] ,  cmap='plasma')\n",
    "plt.xlabel('pc1')\n",
    "plt.ylabel('pc2')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "d8200f2b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0, 'PC3')"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# import relevant libraries for 3d graph\n",
    "from mpl_toolkits.mplot3d import Axes3D\n",
    "fig = plt.figure(figsize=(10,10))\n",
    " \n",
    "# choose projection 3d for creating a 3d graph\n",
    "axis = fig.add_subplot(111, projection='3d')\n",
    " \n",
    "axis.scatter(transformed_data.T[0],transformed_data.T[1],transformed_data.T[2], c=data['label'],cmap='plasma')\n",
    "axis.set_xlabel(\"PC1\", fontsize=10)\n",
    "axis.set_ylabel(\"PC2\", fontsize=10)\n",
    "axis.set_zlabel(\"PC3\", fontsize=10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "15e146e3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.89824308 0.02900658 0.00710236]\n"
     ]
    }
   ],
   "source": [
    "# How much variance is explained by each principal component\n",
    "print(pca.explained_variance_ratio_)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6dd73a0e",
   "metadata": {},
   "source": [
    "# Document Classification \n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "cd017c70",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.99375\n"
     ]
    }
   ],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=123)\n",
    "\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.metrics import accuracy_score\n",
    "\n",
    "model = LogisticRegression(max_iter=500, fit_intercept=True)\n",
    "model.fit(X_train,y_train)\n",
    "\n",
    "\n",
    "\n",
    "y_pred = model.predict(X_test)\n",
    "print(accuracy_score(y_test,y_pred))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "73ad4b44",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.94375\n"
     ]
    }
   ],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(transformed_data, y, test_size=0.2, random_state=123)\n",
    "\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.metrics import accuracy_score\n",
    "\n",
    "model = LogisticRegression(max_iter=500, fit_intercept=True)\n",
    "model.fit(X_train,y_train)\n",
    "\n",
    "\n",
    "\n",
    "y_pred = model.predict(X_test)\n",
    "print(accuracy_score(y_test,y_pred))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3ed8e489",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "06b6c6e6",
   "metadata": {},
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