Week 2 homework.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "4b5b2bd0",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "import lucem_illud \n",
    "\n",
    "import requests \n",
    "import pandas \n",
    "import matplotlib.pyplot as plt \n",
    "import wordcloud \n",
    "import numpy as np \n",
    "import scipy \n",
    "import seaborn as sns \n",
    "import sklearn.manifold \n",
    "import json \n",
    "import urllib.parse \n",
    "\n",
    "\n",
    "import spacy\n",
    "\n",
    "\n",
    "import graphviz \n",
    "import os.path\n",
    "import zipfile\n",
    "import subprocess\n",
    "import io\n",
    "import tempfile\n",
    "import nltk\n",
    "\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6f499bcb",
   "metadata": {},
   "source": [
    "## <font color=\"red\">*Exercise 1*</font>\n",
    "\n",
    "<font color=\"red\">Construct cells immediately below this that input and interrogate a corpus relating to your anticipated final project. This could include one of the Davies corpora or some other you have constructed. Turn your text into an nltk `Text` object, and explore all of the features examined above, and others that relate to better understanding your corpus in relation to your research question. </font>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e5bd6b86",
   "metadata": {},
   "source": [
    "## <font color = \"Green\"> I use the data I had collected in the first assignment and then utilize several techniques for its preliminary analysis. These are matrimonial advertisements from a newspaper called \"The Tribune\" circulated in the northern part of India. The corpus mainly is analyzed on advertisements seeking brides and grooms in 2002 except for the last exercise where I compare 4 documents, bride seeking and grrom seeking ads from 2002, and bride seeking and groom seeking ads from 2014.</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "a74320cb",
   "metadata": {},
   "outputs": [],
   "source": [
    "import csv\n",
    "brides_wanted = []\n",
    "\n",
    "file = open('brides-wanted_2002.csv')\n",
    "\n",
    "csvreader = csv.reader(file)\n",
    "\n",
    "\n",
    "for row in csvreader:\n",
    "    brides_wanted.extend(row)\n",
    "concat_list = [' '.join([str(item) for item in brides_wanted])]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "ac82fe8b",
   "metadata": {},
   "outputs": [],
   "source": [
    "nlp = spacy.load(\"en_core_web_sm\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "714041d0",
   "metadata": {},
   "source": [
    "## <font color = \"Green\"> Tokenizing words</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "6ee27f2a",
   "metadata": {},
   "outputs": [],
   "source": [
    "def word_tokenize(word_list):\n",
    "    tokenized = []\n",
    "    # pass word list through language model.\n",
    "    doc = nlp(word_list)\n",
    "    for token in doc:\n",
    "        if not token.is_punct and len(token.text.strip()) > 0:\n",
    "            tokenized.append(token.text)\n",
    "    return tokenized"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "8c51a464",
   "metadata": {},
   "outputs": [],
   "source": [
    "def wordCounter(wordLst):\n",
    "    wordCounts = {}\n",
    "    for word in wordLst:\n",
    "        #We usually need to normalize the case\n",
    "        wLower = word.lower()\n",
    "        if wLower in wordCounts:\n",
    "            wordCounts[wLower] += 1\n",
    "        else:\n",
    "            wordCounts[wLower] = 1\n",
    "    #convert to DataFrame\n",
    "    countsForFrame = {'word' : [], 'count' : []}\n",
    "    for w, c in wordCounts.items():\n",
    "        countsForFrame['word'].append(w)\n",
    "        countsForFrame['count'].append(c)\n",
    "    return pandas.DataFrame(countsForFrame)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "f7725b99",
   "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>word</th>\n",
       "      <th>count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>note</td>\n",
       "      <td>106</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>please</td>\n",
       "      <td>226</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>do</td>\n",
       "      <td>116</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>not</td>\n",
       "      <td>230</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>send</td>\n",
       "      <td>546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>any</td>\n",
       "      <td>114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>images</td>\n",
       "      <td>106</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>photographs</td>\n",
       "      <td>108</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>with</td>\n",
       "      <td>742</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>your</td>\n",
       "      <td>128</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          word  count\n",
       "0         note    106\n",
       "1       please    226\n",
       "2           do    116\n",
       "3          not    230\n",
       "4         send    546\n",
       "5          any    114\n",
       "6       images    106\n",
       "7  photographs    108\n",
       "8         with    742\n",
       "9         your    128"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "countedWords = wordCounter(word_tokenize(concat_list[0]))\n",
    "countedWords[:10]\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "38da6ca5",
   "metadata": {},
   "source": [
    "Word counts organized in a descending order. As we see, words such as beautiful, girl, sikh, educated, tend to appear frequently."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "c9c31e26",
   "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>word</th>\n",
       "      <th>count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>for</td>\n",
       "      <td>4900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>match</td>\n",
       "      <td>3900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>girl</td>\n",
       "      <td>3364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>beautiful</td>\n",
       "      <td>2130</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>sikh</td>\n",
       "      <td>1748</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>in</td>\n",
       "      <td>1636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>family</td>\n",
       "      <td>1438</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>slim</td>\n",
       "      <td>1374</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>educated</td>\n",
       "      <td>1208</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>suitable</td>\n",
       "      <td>1122</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         word  count\n",
       "21        for   4900\n",
       "20      match   3900\n",
       "26       girl   3364\n",
       "37  beautiful   2130\n",
       "38       sikh   1748\n",
       "66         in   1636\n",
       "57     family   1438\n",
       "94       slim   1374\n",
       "52   educated   1208\n",
       "19   suitable   1122"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "countedWords.sort_values('count', ascending=False, inplace=True)\n",
    "countedWords[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "206e673a",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(111)\n",
    "plt.plot(range(len(countedWords)), countedWords['count'])\n",
    "plt.show()\n",
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(111)\n",
    "plt.plot(range(len(countedWords)), countedWords['count'])\n",
    "ax.set_yscale('log')\n",
    "ax.set_xscale('log')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "40c77722",
   "metadata": {},
   "source": [
    "## <font color = \"Green\"> As expected, the words in the corpus are in alignment with Zipf's Law.</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "eb199e92",
   "metadata": {},
   "outputs": [],
   "source": [
    "BrideText = nltk.Text(word_tokenize(concat_list[0]))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f9744f2a",
   "metadata": {},
   "source": [
    "## <font color = \"Green\"> Beautiful appears almost 2000(out of around 6000) times in ads that describe brides for prospective grooms. </font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "f1533849",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Displaying 25 of 2028 matches:\n",
      " Amritsar Cantt 8910ABOL Match for beautiful Sikh TonkKashtriya girl 23/53 gr\n",
      "cer 9874FOL Well settled match for beautiful smart convent educated from status\n",
      " Suitable alliance for Kumhar Sikh beautiful attractive girl 54 24 MA BEd dec\n",
      "iage Manglik non Manglik match for beautiful Hindu Khatri girl 27½ 54½ MSc Ho\n",
      "match preferably medico for 30/5'4 beautiful Punjabi Brahmin girl working as a \n",
      " for Bansal girl BDS intern 23/158 beautiful slim convented Email dr_sbansal@ya\n",
      "uired for July 1977/53 slim fair beautiful Sood girl BSc NonMedical MSc mathe\n",
      "sts one 9932FOL Suitable match for beautiful fair slim Khatri Arora girl 26/51\n",
      "ly on point basis Jat Sikh boy for beautiful Jat Sikh Staff Nurse girl 23/55 \n",
      "for convented 27/53 employed BDS beautiful girl Father Supreintending Enginge\n",
      "emic credentials for 26 years 54 beautiful intelligent sweetnatured US citize\n",
      " American citizen convent educated beautiful downtoearth sober Jat Sikh girl 29\n",
      "boy of status family for extremely beautiful girl converted BDS working in repu\n",
      "at Sikh medical engineer match for beautiful Jat Sikh girl 28/53 MA and doing\n",
      "r highly qualified convented smart beautiful Jat Sikh girl 28/54 MBA working \n",
      "born 54 wheatish complexion slim beautiful Sikh Ahluwalia girl BA BEd MEd Dip\n",
      "kand51@yahoocom Suitable match for beautiful Ramdasia Sikh girl August 1975/59\n",
      "nted a professional match for very beautiful attractive and slim divorcee Sikh \n",
      "ilcom Suitable match for a Mahajan beautiful slim girl MA English BEd 24/53 k\n",
      "Nadi BHP must Alliance invited for beautiful fair Dhiman girl 23½/150 BSc Compu\n",
      "l May 8 1976/555 pm/53 fair slim beautiful convented MPharma Gold Medalist wo\n",
      " Sikh match for Gursikh Arora very beautiful fair slim girl26/55 12th Compute\n",
      "I preferred 4465CEP Match for very beautiful Punjabi Khatri girl tall slim conv\n",
      " Wanted Jatt Sikh MBBS BDS boy for beautiful slim 28 years 5 feet BDS convent e\n",
      "b or have established business for beautiful slim fair homely cultured Jat Sikh\n"
     ]
    }
   ],
   "source": [
    "BrideIndex = nltk.text.ConcordanceIndex(BrideText) \n",
    "BrideIndex.print_concordance('beautiful')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "980ddc8a",
   "metadata": {},
   "source": [
    "## <font color=\"red\">*Exercise 2*</font>\n",
    "\n",
    "<font color=\"red\">Construct cells immediately below this that filter, stem and lemmatize the tokens in your corpus, and then creates plots (with titles and labels) that map the word frequency distribution, word probability distribution, and at least two conditional probability distributions that help us better understand the social and cultural game underlying the production of your corpus. Create a wordl of words (or normalized words) and add a few vague comments about what mysteries are revealed through it.</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "fbaebf15",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('for', 4734),\n",
       " ('girl', 3240),\n",
       " ('match', 2788),\n",
       " ('beautiful', 2028),\n",
       " ('Sikh', 1708),\n",
       " ('in', 1528),\n",
       " ('slim', 1330),\n",
       " ('family', 1316),\n",
       " ('fair', 1052),\n",
       " ('educated', 1050),\n",
       " ('Match', 1026),\n",
       " ('Suitable', 898),\n",
       " ('Jat', 886),\n",
       " ('well', 726),\n",
       " ('from', 716),\n",
       " ('with', 712),\n",
       " ('settled', 712),\n",
       " ('and', 682),\n",
       " ('Khatri', 652),\n",
       " ('MA', 648)]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "countsDict = {}\n",
    "for word in (word_tokenize(concat_list[0])):\n",
    "    if word in countsDict:\n",
    "        countsDict[word] += 1\n",
    "    else:\n",
    "        countsDict[word] = 1\n",
    "word_counts = sorted(countsDict.items(), key = lambda x : x[1], reverse = True)\n",
    "word_counts[:20]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "2b46e4a8",
   "metadata": {},
   "outputs": [],
   "source": [
    "#The stop list is then all words that occur before the first noun\n",
    "stop_words_freq = ['for','well', 'no', 'and','with','only','match','invited','bar','d','bam', 'alliance','invited', 'a','by',\n",
    "                   'looking','family','our', 'in','from','note','send','please','do','not','any','your','reply','they','can',\n",
    "                   'be', 'images','photographs','forwarded','due','to','technical','reasons','suitable', 'uly72/5\"','born'\n",
    "                  'ma','bed','cantt','8910abol','23/5\\x923\\x94','girl','email']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "f1f45dde",
   "metadata": {},
   "outputs": [],
   "source": [
    "cleaned_list = []\n",
    "for word in word_tokenize(concat_list[0]):\n",
    "    if word.lower() not in stop_words_freq:\n",
    "        cleaned_list.append(word)\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "c4ab611e",
   "metadata": {},
   "outputs": [],
   "source": [
    "def normalizeTokens(word_list, extra_stop=[]):\n",
    "    #We can use a generator here as we just need to iterate over it\n",
    "    normalized = []\n",
    "    if type(word_list) == list and len(word_list) == 1:\n",
    "        word_list = word_list[0]\n",
    "\n",
    "    if type(word_list) == list:\n",
    "        word_list = ' '.join([str(elem) for elem in word_list]) \n",
    "\n",
    "    doc = nlp(word_list.lower())\n",
    "    \n",
    "    # add the property of stop word to words considered as stop words\n",
    "    if len(extra_stop) > 0:\n",
    "        for stopword in extra_stop:\n",
    "            lexeme = nlp.vocab[stopword]\n",
    "            lexeme.is_stop = True\n",
    "\n",
    "    for w in doc:\n",
    "        # if it's not a stop word or punctuation mark, add it to our article\n",
    "        if w.text != '\\n' and not w.is_stop and not w.is_punct and not w.like_num and len(w.text.strip()) > 0:\n",
    "            # we add the lematized version of the word\n",
    "            normalized.append(str(w.lemma_))\n",
    "\n",
    "    return normalized"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "ec82c8cf",
   "metadata": {},
   "outputs": [],
   "source": [
    "normalized_tokens = pandas.Series(word_tokenize(concat_list[0])).apply(lambda x: normalizeTokens(x, stop_words_freq))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "17002acc",
   "metadata": {},
   "outputs": [],
   "source": [
    "normalized_token_count = normalized_tokens.apply(lambda x: len(x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "7427b9a8",
   "metadata": {},
   "outputs": [],
   "source": [
    "Brides_normalized_info = pandas.DataFrame({'normalized tokens':normalized_tokens,'normalized token counts':normalized_token_count})"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c845ce70",
   "metadata": {},
   "source": [
    "## <font color = \"Green\"> frequency distribution of words used in ads seeking grooms.</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "4074b6b2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "76242\n"
     ]
    }
   ],
   "source": [
    "bridesfdist = nltk.ConditionalFreqDist(((len(w), w) for w in normalized_tokens.sum()))\n",
    "\n",
    "#print the number of words\n",
    "print(bridesfdist.N())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9c0d3a8f",
   "metadata": {},
   "source": [
    "## <font color = \"Green\"> Out of the top 15 3 letter words, we see words such as mba, bsc, mca which shows an emphasis on education, whether it is mentioned in context of the bride or groom. We also see heavy emphasis or preference for members from ethnic communities —'jat' is a donimant ethnic community in northern india. </font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "7299f2cb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x15379e940>"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bridesfdist[3].plot(15, title = \"Counts of top 15 three letter words\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "83e20901",
   "metadata": {},
   "source": [
    "## <font color = \"Green\"> Similarly, the most widely used 4 letter word is 'sikh' which is another predominant ethnic community in northern India.</font>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "661f833a",
   "metadata": {},
   "source": [
    "## <font color = \"Green\"> Calculating the probability distribution </font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "080c757e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "sikh\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "0.14119594621875883"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bridespdist = nltk.ConditionalProbDist(bridesfdist, nltk.ELEProbDist)\n",
    "#print the most common 4 letter word and its probability\n",
    "print(bridespdist[4].max())\n",
    "(bridespdist[4].prob(bridespdist[4].max()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "62d6fdd3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "settle\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "0.06638953910727258"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#print the most common 6 letter word and its probability\n",
    "print(bridespdist[6].max())\n",
    "(bridespdist[6].prob(bridespdist[6].max()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "cb341ca4",
   "metadata": {},
   "outputs": [],
   "source": [
    "def spacy_pos(word_list):\n",
    "    tags = []\n",
    "    doc = nlp(word_list.lower())\n",
    "    for w in doc:\n",
    "        tags.append((w.text, w.tag_))\n",
    "    return tags"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "22045594",
   "metadata": {},
   "outputs": [],
   "source": [
    "normalized_tokens_POS= pandas.Series([spacy_pos(t) for t in cleaned_list])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "7d044a56",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('saraswat', FreqDist({'VBD': 138})),\n",
       " ('brahmin', FreqDist({'NN': 418})),\n",
       " ('manglik', FreqDist({'NNP': 278})),\n",
       " ('nonmanglik', FreqDist({'NNP': 116})),\n",
       " ('born', FreqDist({'VBN': 280})),\n",
       " (\"july72/5'5\", FreqDist({'NNP': 2})),\n",
       " ('ma', FreqDist({'NNP': 648})),\n",
       " ('teacher', FreqDist({'NN': 204})),\n",
       " ('army', FreqDist({'NN': 160})),\n",
       " ('school', FreqDist({'NN': 226})),\n",
       " ('amritsar', FreqDist({'NNP': 72})),\n",
       " ('beautiful', FreqDist({'JJ': 2130})),\n",
       " ('sikh', FreqDist({'NNP': 1748})),\n",
       " ('tonkkashtriya', FreqDist({'NNP': 30})),\n",
       " ('graduate', FreqDist({'NN': 308})),\n",
       " ('pgdca', FreqDist({'NNP': 176})),\n",
       " ('father', FreqDist({'NN': 742})),\n",
       " ('class', FreqDist({'NN': 86})),\n",
       " ('i', FreqDist({'PRP': 42})),\n",
       " ('officer', FreqDist({'NN': 660}))]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bridesfdist_WordtoPOS = nltk.ConditionalFreqDist(normalized_tokens_POS.sum())\n",
    "list(bridesfdist_WordtoPOS.items())[:20]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "117fcbaa",
   "metadata": {},
   "source": [
    "## <font color = \"Green\"> Calculating frequency distribution of normalized tokens based on the how these words were \n",
    "categorized as different parts of speech.</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "87c62859",
   "metadata": {},
   "outputs": [],
   "source": [
    "bridesfdist_POStoWord = nltk.ConditionalFreqDist((p, w) for w, p in normalized_tokens_POS.sum())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "227269a9",
   "metadata": {},
   "source": [
    "## <font color = \"Green\"> Words such as girl and slim do appear as most occuring nouns, however with more words such as \"email\" added to the stopwords, these results could be more insightful.</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "c600f810",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "FreqDist({'slim': 1374, 'father': 742, 'status': 742, 'officer': 660, 'contact': 596, 'marriage': 542, 'doctor': 536, 'msc': 456, 'computer': 450, 'convent': 434, ...})"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bridesfdist_POStoWord['NN']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cd9e9297",
   "metadata": {},
   "source": [
    "## <font color = \"Green\"> Among the top 20 proper nouns, 7 appear to be castes/ethnic communities, reiterating the emphasis that these ads lay of these parameters. These are 'sikh','jat','khatri','gursikh','manglik','rajput', and 'ahluwalia'- communities in northern india.</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "dc021572",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x15264a4f0>"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bridesfdist_POStoWord['NNP'].plot(20, title=\"Top 20 proper nouns\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3cc40a8f",
   "metadata": {},
   "source": [
    "## <font color = \"Green\"> The word cloud highlights words such as beautiful, slim, jat, sikh etc which are in line with the observations above.</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "ee7652e4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "wc = wordcloud.WordCloud(background_color=\"white\", max_words=100, width= 1000, height = 1000, mode ='RGBA', scale=.5).generate(' '.join(normalized_tokens.sum()))\n",
    "plt.imshow(wc)\n",
    "plt.axis(\"off\")\n",
    "plt.savefig(\"brides-wanted_word_cloud.pdf\", format = 'pdf')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f1311397",
   "metadata": {},
   "source": [
    "## <font color=\"red\">Exercise 3</font>\n",
    "\n",
    "<font color=\"red\">In the cells immediately following, perform POS tagging on a meaningful (but modest) subset of a corpus associated with your final project. Examine the list of words associated with at least three different parts of speech. Consider conditional associations (e.g., adjectives associated with nouns or adverbs with verbs of interest). What do these distributions suggest about your corpus?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "b3d11979",
   "metadata": {},
   "outputs": [],
   "source": [
    "def sent_tokenize(word_list):\n",
    "    doc = nlp(str(word_list))\n",
    "    sentences = [sent.text.strip() for sent in doc.sents]\n",
    "    return sentences"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "726853b6",
   "metadata": {},
   "outputs": [],
   "source": [
    "def tag_sents_pos(sentences):\n",
    "    \"\"\"\n",
    "    function which replicates NLTK pos tagging on sentences.\n",
    "    \"\"\"\n",
    "    new_sents = []\n",
    "    for sentence in sentences:\n",
    "        new_sent = ' '.join(sentence)\n",
    "        new_sents.append(new_sent)\n",
    "    final_string = ' '.join(new_sents)\n",
    "    doc = nlp(final_string)\n",
    "    \n",
    "    pos_sents = []\n",
    "    for sent in doc.sents:\n",
    "        pos_sent = []\n",
    "        for token in sent:\n",
    "            pos_sent.append((token.text, token.tag_))\n",
    "        pos_sents.append(pos_sent)\n",
    "    \n",
    "    return pos_sents"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "fbebcc05",
   "metadata": {},
   "outputs": [],
   "source": [
    "brides_df = pandas.read_csv('brides-wanted_2002.csv')\n",
    "brides_df['bride_info'] = pandas.read_csv('brides-wanted_2002.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "c8991970",
   "metadata": {},
   "outputs": [],
   "source": [
    "brides_df['sentences'] = brides_df['bride_info'].apply(lambda x: [word_tokenize(s) for s in sent_tokenize(x)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "dbe58e72",
   "metadata": {},
   "outputs": [],
   "source": [
    "brides_df['POS_sents'] = brides_df['sentences'].apply(lambda x: tag_sents_pos(x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "1e413b84",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1    [[(Suitable, JJ), (match, NN), (for, IN), (Sar...\n",
       "2    [[(Match, VB), (for, IN), (beautiful, JJ), (Si...\n",
       "3    [[(Well, UH), (settled, VBN), (match, NN), (fo...\n",
       "4    [[(Suitable, JJ), (alliance, NN), (for, IN), (...\n",
       "Name: POS_sents, dtype: object"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "brides_df['POS_sents'][1:5]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2b022089",
   "metadata": {},
   "source": [
    "## <font color = \"Green\"> Below I look at words which are nouns, adjectives, and adverbs </font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "26bd7f33",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('girl', 3224),\n",
       " ('match', 2012),\n",
       " ('family', 1312),\n",
       " ('marriage', 510),\n",
       " ('status', 480),\n",
       " ('officer', 434),\n",
       " ('BEd', 392),\n",
       " ('convent', 350),\n",
       " ('Alliance', 330),\n",
       " ('bar', 310),\n",
       " ('boy', 286),\n",
       " ('biodata', 272),\n",
       " ('business', 272),\n",
       " ('daughter', 244),\n",
       " ('businessman', 222),\n",
       " ('father', 220),\n",
       " ('graduate', 220),\n",
       " ('citizen', 212),\n",
       " ('MSc', 208),\n",
       " ('sale', 194)]"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "countTarget = 'NN'\n",
    "targetCounts = {}\n",
    "for entry in brides_df['POS_sents']:\n",
    "    for sentence in entry:\n",
    "        for ent, kind in sentence:\n",
    "            if kind != countTarget:\n",
    "                continue\n",
    "            elif ent in targetCounts:\n",
    "                targetCounts[ent] += 1\n",
    "            else:\n",
    "                targetCounts[ent] = 1\n",
    "sortedTargets = sorted(targetCounts.items(), key = lambda x: x[1], reverse = True)\n",
    "sortedTargets[:20]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "1140b0e6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('beautiful', 2028),\n",
       " ('fair', 1030),\n",
       " ('slim', 1022),\n",
       " ('Suitable', 888),\n",
       " ('qualified', 480),\n",
       " ('smart', 466),\n",
       " ('professional', 460),\n",
       " ('kanal', 356),\n",
       " ('good', 222),\n",
       " ('Early', 206),\n",
       " ('suitable', 200),\n",
       " ('decent', 196),\n",
       " ('tall', 176),\n",
       " ('Canadian', 170),\n",
       " ('handsome', 132),\n",
       " ('early', 124),\n",
       " ('preferred', 124),\n",
       " ('high', 120),\n",
       " ('technical', 110),\n",
       " ('American', 110)]"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "countTarget = 'JJ'\n",
    "targetCounts = {}\n",
    "for entry in brides_df['POS_sents']:\n",
    "    for sentence in entry:\n",
    "        for ent, kind in sentence:\n",
    "            if kind != countTarget:\n",
    "                continue\n",
    "            elif ent in targetCounts:\n",
    "                targetCounts[ent] += 1\n",
    "            else:\n",
    "                targetCounts[ent] = 1\n",
    "sortedTargets = sorted(targetCounts.items(), key = lambda x: x[1], reverse = True)\n",
    "sortedTargets[:20]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "2a4637af",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('well', 706),\n",
       " ('very', 308),\n",
       " ('homely', 248),\n",
       " ('not', 230),\n",
       " ('professionally', 224),\n",
       " ('preferably', 156),\n",
       " ('Professionally', 144),\n",
       " ('only', 132),\n",
       " ('highly', 126),\n",
       " ('abroad', 98),\n",
       " ('extremely', 92),\n",
       " ('slim', 78),\n",
       " ('presently', 74),\n",
       " ('fully', 64),\n",
       " ('also', 62),\n",
       " ('Only', 58),\n",
       " ('pretty', 46),\n",
       " ('newly', 36),\n",
       " ('Highly', 34),\n",
       " ('Preferably', 32)]"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "countTarget = 'RB'\n",
    "targetCounts = {}\n",
    "for entry in brides_df['POS_sents']:\n",
    "    for sentence in entry:\n",
    "        for ent, kind in sentence:\n",
    "            if kind != countTarget:\n",
    "                continue\n",
    "            elif ent in targetCounts:\n",
    "                targetCounts[ent] += 1\n",
    "            else:\n",
    "                targetCounts[ent] = 1\n",
    "sortedTargets = sorted(targetCounts.items(), key = lambda x: x[1], reverse = True)\n",
    "sortedTargets[:20]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "80bfd7ea",
   "metadata": {},
   "source": [
    "## <font color = \"Green\"> Below I look at the associations of all adverbs with the verb 'match'and all adjectives with the noun 'girl'. As we can see words such as beautiful, homely, slim, cultured, decent, fair, tall, pretty tend to be assiciated with the word girl. Similarly we see words such as only abroad, professionally, cleanshaven etc when looking for a match </font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "cdb03dd5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'Abroad', 'Professionally', 'abroad', 'cleanshaven', 'ARORA', 'Suitably', 'SIKH'}\n"
     ]
    }
   ],
   "source": [
    "NTarget = 'RB'\n",
    "Word = 'match'\n",
    "NResults = set()\n",
    "for entry in brides_df['POS_sents']:\n",
    "    for sentence in entry:\n",
    "        for (ent1, kind1),(ent2,kind2) in zip(sentence[:-1], sentence[1:]):\n",
    "            if (kind1,ent2.lower())==(NTarget,Word):\n",
    "                NResults.add(ent1.replace('\\x924\\x94',''))\n",
    "            else:\n",
    "                continue\n",
    "\n",
    "print(NResults)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "ab5d1ef3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'immigrant', 'convented', 'wheatish', 'attractive', 'Christian', 'talentedbeautiful', 'Khatri', 'Canadian', 'smart', 'decent', 'sober', 'slim', 'intelligent', 'urban', 'Goldsmith', 'SOOD', 'Himachali', 'brilliant', 'MCA24½/5', 'Ramgarhia', 'homely', 'SLIM', 'mannered', 'talented', 'natured', 'caring', 'Beautiful', 'Saini', 'beautiful', 'brilliantbeautiful', 'BDSemployed', 'staffnurse', 'Indian', 'protestant', 'coloured', 'charming', 'unmarried', 'local', 'Nurseryteacher', 'Mittal', 'vegetarian', 'pretty', 'tall', 'professional', '5\\x925\\x94', 'qualified', 'fairbeautiful', 'Bansal', 'fair', 'cultured', 'Sood'}\n"
     ]
    }
   ],
   "source": [
    "NTarget = 'JJ'\n",
    "Word = 'girl'\n",
    "NResults = set()\n",
    "for entry in brides_df['POS_sents']:\n",
    "    for sentence in entry:\n",
    "        for (ent1, kind1),(ent2,kind2) in zip(sentence[:-1], sentence[1:]):\n",
    "            if (kind1,ent2.lower())==(NTarget,Word):\n",
    "                NResults.add(ent1.replace('\\x924\\x94',''))\n",
    "            else:\n",
    "                continue\n",
    "\n",
    "print(NResults)  "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a4cfe897",
   "metadata": {},
   "source": [
    "## <font color=\"red\">*Exercise 4*</font>\n",
    "\n",
    "<font color=\"red\">Construct cells immediately below this that identify statistically significant bigrams, trigrams, quadgrams, higher-order *n*grams and skipgrams. Explore whether these collocations are idiomatic and so irreducible to the semantic sum of their component words. You can do this by examination of conditional frequencies (e.g., what else is 'united' besides the 'United States'). If these phrases are idiomatic, what do they suggest about the culture of the world producing them?\n",
    "\n",
    "<font color=\"red\">**Stretch**: In Manning and Schütze's textbook, there Section 5.3.2 explores how to use the *t*-test to find words whose co-occurance patterns best distinguish two words. Implement that and use it to explore phrases in your corpus. For instance, you could tell what words come after \"America\" much more often than after \"Iraq\"?</font> "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "58ed0af2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 76242 bigrams in the finder\n"
     ]
    }
   ],
   "source": [
    "brideBigrams = nltk.collocations.BigramCollocationFinder.from_words(normalized_tokens.sum())\n",
    "print(\"There are {} bigrams in the finder\".format(brideBigrams.N))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "3cd7391d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[('jat', 'sikh'), ('beautiful', 'slim'), ('convent', 'educate'), ('professionally', 'qualified'), ('fair', 'slim'), ('slim', 'beautiful'), ('slim', 'fair'), ('decent', 'marriage'), ('doctor', 'engineer'), ('early', 'marriage')]\n"
     ]
    }
   ],
   "source": [
    "def bigramScoring(count, wordsTuple, total):\n",
    "    return count\n",
    "\n",
    "print(brideBigrams.nbest(bigramScoring, 10))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "cfee3fdf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The first word is:  902, The second word is: 1748\n",
      "The first word is:  2130, The second word is: 1374\n",
      "The first word is:  434, The second word is: 1208\n",
      "The first word is:  378, The second word is: 574\n",
      "The first word is:  1108, The second word is: 1374\n",
      "The first word is:  1374, The second word is: 2130\n",
      "The first word is:  1374, The second word is: 1108\n",
      "The first word is:  296, The second word is: 542\n",
      "The first word is:  584, The second word is: 688\n",
      "The first word is:  362, The second word is: 542\n"
     ]
    }
   ],
   "source": [
    "birgramScores = []\n",
    "\n",
    "def bigramPrinting(count, wordsTuple, total):\n",
    "    global birgramScores\n",
    "    birgramScores.append(\"The first word is:  {}, The second word is: {}\".format(*wordsTuple))\n",
    "\n",
    "brideBigrams.nbest(bigramPrinting, 10)\n",
    "print('\\n'.join(birgramScores[:10]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "8046a911",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(('jat', 'sikh'), 6632.882677907185),\n",
       " (('professionally', 'qualified'), 2551.362283185799),\n",
       " (('convent', 'educate'), 2380.85298970808),\n",
       " (('decent', 'marriage'), 1840.818086249295),\n",
       " (('early', 'marriage'), 1657.343822920839),\n",
       " (('col', 'ahluwalia'), 1581.4824469292148),\n",
       " (('doctor', 'engineer'), 1308.3508103176405),\n",
       " (('hindu', 'khatri'), 1279.2602994703975),\n",
       " (('saraswat', 'brahmin'), 1271.3745479949437),\n",
       " (('tribune', 'chandigarh'), 1269.8478086392236),\n",
       " (('clean', 'shaven'), 1140.5878998528726),\n",
       " (('hot', 'sale'), 1090.7931099750695),\n",
       " (('fair', 'slim'), 1080.8940446074048),\n",
       " (('beautiful', 'slim'), 1063.9032926785526),\n",
       " (('gazette', 'officer'), 970.2592319906621),\n",
       " (('ma', 'english'), 938.8629972574984),\n",
       " (('contact', 'col'), 928.2356851503641),\n",
       " (('manglik', 'nonmanglik'), 920.0211469236972),\n",
       " (('fully', 'marble'), 892.1879815292702),\n",
       " (('early', 'decent'), 866.6479939942725),\n",
       " (('fair', 'complexion'), 860.7460417801556),\n",
       " (('classi', 'officer'), 809.5604016546132),\n",
       " (('mair', 'rajput'), 770.0489567748796),\n",
       " (('sharp', 'feature'), 758.5366834833112),\n",
       " (('army', 'officer'), 753.3661128450769),\n",
       " (('slim', 'fair'), 726.6449956915699),\n",
       " (('public', 'school'), 708.8849930058803),\n",
       " (('dowry', 'seeker'), 698.2049761467434),\n",
       " (('slim', 'beautiful'), 696.7810466520566),\n",
       " (('extremely', 'beautiful'), 691.9933243386229),\n",
       " (('single', 'storey'), 648.9474571150937),\n",
       " (('college', 'lecturer'), 629.6395910918183),\n",
       " (('father', 'retire'), 628.3545561522383),\n",
       " (('green', 'card'), 623.369714757456),\n",
       " (('seeker', 'excuse'), 595.7793146556296),\n",
       " (('high', 'status'), 569.3946159878137),\n",
       " (('ultra', 'modern'), 562.9139360628955),\n",
       " (('sector', '36a'), 556.0332959023143),\n",
       " (('look', 'young'), 546.8005864319501),\n",
       " (('sarswat', 'brahmin'), 532.8519551097364)]"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bigram_measures = nltk.collocations.BigramAssocMeasures()\n",
    "brideBigrams.score_ngrams(bigram_measures.likelihood_ratio)[:40]\n",
    "# other options include student_t, chi_sq, likelihood_ratio, pmi"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "49e5c4cc",
   "metadata": {},
   "source": [
    "## <font color = \"Green\"> Significant bigrams </font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "5178804f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(('jat', 'sikh'), 28.585628349954398),\n",
       " (('convent', 'educate'), 17.84347459176808),\n",
       " (('professionally', 'qualified'), 16.743256891985197),\n",
       " (('beautiful', 'slim'), 16.71568614827349),\n",
       " (('fair', 'slim'), 15.53989075849439),\n",
       " (('decent', 'marriage'), 14.415699501053782),\n",
       " (('slim', 'beautiful'), 14.371096969510113),\n",
       " (('early', 'marriage'), 14.243769335972038),\n",
       " (('doctor', 'engineer'), 14.198277701293444),\n",
       " (('hindu', 'khatri'), 13.577053198170635),\n",
       " (('slim', 'fair'), 13.48616198951734),\n",
       " (('col', 'ahluwalia'), 11.540530719661353),\n",
       " (('saraswat', 'brahmin'), 11.157247189915118),\n",
       " (('fair', 'beautiful'), 11.109188803930646),\n",
       " (('ma', 'english'), 11.062937013733855),\n",
       " (('beautiful', 'fair'), 11.02151930494138),\n",
       " (('contact', 'col'), 10.557005793849152),\n",
       " (('early', 'decent'), 10.54544864776778),\n",
       " (('slim', 'smart'), 10.517260414800258),\n",
       " (('gazette', 'officer'), 10.468384476434245)]"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "brideBigrams.score_ngrams(bigram_measures.student_t)[:20]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8164d655",
   "metadata": {},
   "source": [
    "## <font color = \"Green\"> Significant trigrams </font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "f6695d2c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(('contact', 'col', 'ahluwalia'), 10.48778386142673),\n",
       " (('early', 'decent', 'marriage'), 10.487135872735196),\n",
       " (('father', 'classi', 'officer'), 7.998407203378027),\n",
       " (('beautiful', 'fair', 'slim'), 7.930268734180016),\n",
       " (('beautiful', 'slim', 'fair'), 7.542523795674986),\n",
       " (('slim', 'fair', 'beautiful'), 7.542523795674986),\n",
       " (('father', 'gazette', 'officer'), 7.481737206100351),\n",
       " (('beautiful', 'jat', 'sikh'), 7.130983215760163),\n",
       " (('hot', 'sale', 'kanal'), 6.928009931388173),\n",
       " (('fair', 'slim', 'beautiful'), 6.700079469224024),\n",
       " (('dowry', 'seeker', 'excuse'), 6.324550473809623),\n",
       " (('professionally', 'qualified', 'settle'), 6.319704033499359),\n",
       " (('jat', 'sikh', 'parent'), 6.149893503783186),\n",
       " (('status', 'jat', 'sikh'), 5.966456215436792),\n",
       " (('jat', 'sikh', 'beautiful'), 5.903708542965451),\n",
       " (('kanal', 'double', 'storey'), 5.83087202325673),\n",
       " (('fair', 'slim', 'smart'), 5.808494029252205),\n",
       " (('beautiful', 'convent', 'educate'), 5.798005473509959),\n",
       " (('box', 'tribune', 'chandigarh'), 5.65682285762619),\n",
       " (('kanal', 'single', 'storey'), 5.6567925021806)]"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "trigram_measures = nltk.collocations.TrigramAssocMeasures()\n",
    "brideTrigrams = nltk.collocations.TrigramCollocationFinder.from_words(normalized_tokens.sum())\n",
    "brideTrigrams.score_ngrams(trigram_measures.student_t)[:20]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "14bcd1b5",
   "metadata": {},
   "source": [
    "## <font color = \"Green\">  Significant quadgrams </font>\n",
    "The focal point across all grams tends to be sikh or other ethnic communities. This is because \"col\" \"sale\"\"hot\"\"kanal\" were all part of a junk advertisement and must be removed using the stop words. Without them, sikh, jat and other communitites tend to be the focal point in a bride or groom search."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 200,
   "id": "0199d92d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(('hot', 'sale', 'kanal', 'single'), 4.4721357193362845),\n",
       " (('nri', 'contact', 'col', 'ahluwalia'), 4.472132000802409),\n",
       " (('sale', 'kanal', 'single', 'storey'), 4.242640466830353),\n",
       " (('sector', '36a', 'contact', 'col'), 4.24263963911866),\n",
       " (('sikh', 'parent', 'invite', 'correspondence'), 4.242639123735174),\n",
       " (('jat', 'sikh', 'parent', 'invite'), 4.242613568417962),\n",
       " (('professionally', 'qualified', 'jat', 'sikh'), 4.242458745286768),\n",
       " (('jat', 'sikh', 'convent', 'educate'), 4.2422010589257075),\n",
       " (('beautiful', 'slim', 'convent', 'educate'), 4.241824661288123),\n",
       " (('36a', 'contact', 'col', 'ahluwalia'), 3.9999993714322035),\n",
       " (('sector', 'contact', 'col', 'ahluwalia'), 3.9999964800203403),\n",
       " (('jat', 'sikh', 'parent', 'seek'), 3.999921927028331),\n",
       " (('single', 'storey', 'good', 'house'), 3.741657272738488),\n",
       " (('kanal', 'double', 'storey', 'sector'), 3.741656838228311),\n",
       " (('clean', 'shaven', 'jat', 'sikh'), 3.741650540825823),\n",
       " (('want', 'doctor', 'engineer', 'usa'), 3.741608114469475),\n",
       " (('corner', 'duplex', 'ultramodern', 'construction'), 3.464101614714918),\n",
       " (('fully', 'marble', 'newly', 'construct'), 3.4641016125482067),\n",
       " (('duplex', 'ultramodern', 'construction', 'kanal'), 3.464101611828596),\n",
       " (('sale', 'corner', 'duplex', 'ultramodern'), 3.4641016089764163)]"
      ]
     },
     "execution_count": 200,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from nltk.metrics.association import QuadgramAssocMeasures\n",
    "gram_measures = QuadgramAssocMeasures()\n",
    "brideQuads = nltk.collocations.QuadgramCollocationFinder.from_words(normalized_tokens.sum())\n",
    "brideQuads.score_ngrams(gram_measures.student_t)[:20]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a689345d",
   "metadata": {},
   "source": [
    " ## <font color = \"Green\">  Conditional frequency of bigrams containing the word sikh </font>\n",
    " The results show that the word Sikh tends to appear mostly with the word jat or Jatt or with other religious communities within the Sikh community, these are Grewal, and Saini. This again reiterates the presence of strong emphasis of caste and ethnicity even within the ost predominant community."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 202,
   "id": "92353a64",
   "metadata": {},
   "outputs": [],
   "source": [
    "target = 'sikh'\n",
    "\n",
    "dic = {}\n",
    "\n",
    "for bi in list(nltk.bigrams(concat_list[0].split())): \n",
    "    if target in bi: \n",
    "        if bi not in dic: \n",
    "            dic[bi] = 1\n",
    "        dic[bi] += 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 203,
   "id": "a16e08a2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{('Jat', 'sikh'): 7,\n",
       " ('sikh', 'Grewal'): 3,\n",
       " ('sikh', 'parents'): 3,\n",
       " ('sikh', 'boys'): 3,\n",
       " ('Jatt', 'sikh'): 3,\n",
       " ('sikh', 'MBBS/BDS'): 3,\n",
       " ('saini', 'sikh'): 3,\n",
       " ('sikh', 'girl'): 3}"
      ]
     },
     "execution_count": 203,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dic"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7046a60c",
   "metadata": {},
   "source": [
    "## <font color=\"red\">*Exercise 5*</font>\n",
    "\n",
    "<font color=\"red\">In the cells immediately following, perform NER on a (modest) subset of your corpus of interest. List all of the different kinds of entities tagged? What does their distribution suggest about the focus of your corpus? For a subset of your corpus, tally at least one type of named entity and calculate the Precision, Recall and F-score for the NER classification just performed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 207,
   "id": "a3176738",
   "metadata": {},
   "outputs": [],
   "source": [
    "def tag_sents_ner(sentences):\n",
    "    \"\"\"\n",
    "    function which replicates NLTK ner tagging on sentences.\n",
    "    \"\"\"\n",
    "    new_sents = []\n",
    "    for sentence in sentences:\n",
    "        new_sent = ' '.join(sentence)\n",
    "        new_sents.append(new_sent)\n",
    "    final_string = ' '.join(new_sents)\n",
    "    doc = nlp(final_string)\n",
    "    \n",
    "    pos_sents = []\n",
    "    for sent in doc.sents:\n",
    "        pos_sent = []\n",
    "        for ent in sent.ents:\n",
    "            pos_sent.append((ent.text, ent.label_))\n",
    "        pos_sents.append(pos_sent)\n",
    "    \n",
    "    return pos_sents"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 208,
   "id": "8d81e599",
   "metadata": {},
   "outputs": [],
   "source": [
    "brides_df['classified_sents'] = brides_df['sentences'].apply(lambda x: tag_sents_ner(x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 209,
   "id": "b8cc0d4d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0                                                  [[]]\n",
       "1     [[(Saraswat Brahmin Manglik, ORG), (MA, PERSON)]]\n",
       "2     [[(Sikh TonkKashtriya, PERSON), (23/53, CARD...\n",
       "3     [[(Sikh, PERSON), (27/53 MBA UGC, PRODUCT), ...\n",
       "4     [[(Kumhar Sikh, PERSON), (54, CARDINAL), (MA...\n",
       "5                                                  [[]]\n",
       "6     [[(Manglik, ORG), (Hindu, NORP), (Khatri, GPE)...\n",
       "7     [[], [(BEAUTIFUL FAIR, PERSON), (SLIM MA, PERS...\n",
       "8     [[(Brahmin Khatri, PERSON), (Saraswat Brahmin,...\n",
       "9     [[(30/5'4, CARDINAL), (Punjabi Brahmin, ORG), ...\n",
       "10    [[(BDS, ORG), (23/158, CARDINAL), (9930FOL, DA...\n",
       "11    [[(Mittal, ORG), (24/52 BPharma, CARDINAL), ...\n",
       "12    [[(24/53, CARDINAL), (BCom, GPE), (MFC PGDCA...\n",
       "13    [[(July, DATE), (1977/53, CARDINAL), (NonMed...\n",
       "14    [[(Khatri Arora, PERSON), (26/51 MA, PERSON)...\n",
       "15    [[(Khatria, PERSON), (Canada, GPE), (US, GPE),...\n",
       "16      [[(5/26 year old, DATE), (9904FOL, CARDINAL)]]\n",
       "17    [[(Canadian, NORP), (Jat Sikh, PERSON), (two, ...\n",
       "18    [[(58, CARDINAL), (24/53 MBA, PERCENT), (M...\n",
       "19    [[(Jat Sikh, PERSON), (27/53, CARDINAL), (BD...\n",
       "Name: classified_sents, dtype: object"
      ]
     },
     "execution_count": 209,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "brides_df['classified_sents'][:20]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "14c08b67",
   "metadata": {},
   "source": [
    " ## <font color = \"Green\">  Even in the list of entities tagged, \"Jat Sikh\" which are religious communities tend to have the highest count, which when combined with findings above seems believable as the focal point of the distribution of words in this corpus. </font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 212,
   "id": "5cf472f5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('Jat Sikh', 544),\n",
       " ('Khatri', 356),\n",
       " ('one', 288),\n",
       " ('Hindu', 286),\n",
       " ('MA', 242),\n",
       " ('USA', 238),\n",
       " ('NRI', 210),\n",
       " ('US', 204),\n",
       " ('India', 196),\n",
       " ('Canadian', 176),\n",
       " ('Canada', 158),\n",
       " ('Sikh', 150),\n",
       " ('English', 122),\n",
       " ('Arora', 108),\n",
       " ('two', 100),\n",
       " ('Medico', 100),\n",
       " ('Army', 94),\n",
       " ('American', 94),\n",
       " ('Gursikh', 94),\n",
       " ('MNC', 92),\n",
       " ('MBA', 92),\n",
       " ('UK', 88),\n",
       " ('Engineer', 88),\n",
       " ('Himachali', 84),\n",
       " ('PGDCA', 82),\n",
       " ('BCom', 80),\n",
       " ('Saraswat Brahmin', 78),\n",
       " ('Send', 78),\n",
       " ('25', 74),\n",
       " ('Indian', 74),\n",
       " ('5\\x924\\x94', 70),\n",
       " ('BDS', 70),\n",
       " ('Ramgarhia Sikh', 70),\n",
       " ('Email', 66),\n",
       " ('26', 66),\n",
       " ('America', 58),\n",
       " ('Ramgarhia', 56),\n",
       " ('BA', 54),\n",
       " ('Contact', 54),\n",
       " ('Ramdasia Sikh', 52),\n",
       " ('Delhi', 52),\n",
       " ('first', 52),\n",
       " ('One', 50),\n",
       " ('5\\x923\\x94', 50),\n",
       " ('MCA', 48),\n",
       " ('Manglik', 46),\n",
       " ('25/5\\x924\\x94', 46),\n",
       " ('Jatsikh', 46),\n",
       " ('Saini Sikh', 46),\n",
       " ('UGC', 46),\n",
       " ('BHP', 44),\n",
       " ('Arora Sikh', 42),\n",
       " ('23', 42),\n",
       " ('Punjabi Khatri', 40),\n",
       " ('5\\x922\\x94', 40),\n",
       " ('28', 40),\n",
       " ('8', 40),\n",
       " ('Khatri Arora', 38),\n",
       " ('Arora Khatri', 38),\n",
       " ('Ramdasia', 38),\n",
       " ('Kamboj Sikh', 38),\n",
       " ('Ludhiana', 38),\n",
       " ('24', 38),\n",
       " ('Kundli', 36),\n",
       " ('Khatri Sikh', 36),\n",
       " ('MPhil', 36),\n",
       " ('Panchkula', 36),\n",
       " ('29', 34),\n",
       " ('four', 34),\n",
       " ('26/5\\x924\\x94', 34),\n",
       " ('JatSikh', 34),\n",
       " ('Saini', 34),\n",
       " ('27/5\\x923\\x94', 32),\n",
       " ('24/5\\x924\\x94', 32),\n",
       " ('Gursikh Arora', 32),\n",
       " ('Punjabi', 32),\n",
       " ('Contact Col Ahluwalia', 32),\n",
       " ('36A', 32),\n",
       " ('Singh', 30),\n",
       " ('22', 30),\n",
       " ('25/5\\x925\\x94', 30),\n",
       " ('Sarswat', 30),\n",
       " ('Gupta', 30),\n",
       " ('5\\x925\\x94', 28),\n",
       " ('27', 28),\n",
       " ('Sikh Ahluwalia', 26),\n",
       " ('Shimla', 26),\n",
       " ('25 years', 26),\n",
       " ('23/5\\x923\\x94', 24),\n",
       " ('Visa', 24),\n",
       " ('Mobile', 24),\n",
       " ('5', 24),\n",
       " ('Apply', 24),\n",
       " ('25/5\\x923\\x94', 24),\n",
       " ('MD', 24),\n",
       " ('2', 24),\n",
       " ('26/5\\x923\\x94', 24),\n",
       " ('BTech', 24),\n",
       " ('28/5\\x924\\x94', 24),\n",
       " ('24/5\\x923\\x94', 22),\n",
       " ('IAS', 22),\n",
       " ('Caste', 22),\n",
       " ('California', 22),\n",
       " ('24/5\\x925\\x94', 22),\n",
       " ('MA Eng', 22),\n",
       " ('23/5\\x924\\x94', 22),\n",
       " ('Mohali', 22),\n",
       " ('Amritsar', 22),\n",
       " ('Punjabi Brahmin', 20),\n",
       " ('Mahajan', 20),\n",
       " ('Australia', 20),\n",
       " ('33', 20),\n",
       " ('36', 20),\n",
       " ('5\\x921\\x94', 20),\n",
       " ('five', 20),\n",
       " ('British', 20),\n",
       " ('30', 20),\n",
       " ('Two', 18),\n",
       " ('Lecturer', 18),\n",
       " ('Doaba', 18),\n",
       " ('Sandhu', 18),\n",
       " ('Qualified', 18),\n",
       " ('23 years', 18),\n",
       " ('INDIA', 18),\n",
       " ('Defence', 18),\n",
       " ('9', 18),\n",
       " ('21', 18),\n",
       " ('Govt', 18),\n",
       " ('Manglik nonManglik', 18),\n",
       " ('5\\x926\\x94', 18),\n",
       " ('26 years', 16),\n",
       " ('Punjab', 16),\n",
       " ('Correspond', 16),\n",
       " ('Singla', 16),\n",
       " ('Four', 16),\n",
       " ('Respond', 16),\n",
       " ('28/5\\x923\\x94', 16),\n",
       " ('Australian', 16),\n",
       " ('24/5\\x926\\x94', 16),\n",
       " ('Software Engineer', 16),\n",
       " ('PO', 16),\n",
       " ('Send kundli', 16),\n",
       " ('England', 16),\n",
       " ('15', 16),\n",
       " ('six', 16),\n",
       " ('USA Canada', 16),\n",
       " ('Girl', 14),\n",
       " ('Dowry', 14),\n",
       " ('22/5\\x925\\x94', 14),\n",
       " ('Punjabi Hindu', 14),\n",
       " ('1978', 14),\n",
       " ('North Indian', 14),\n",
       " ('5\\x923½\\x94', 14),\n",
       " ('MA English', 14),\n",
       " ('24/5\\x921\\x94', 14),\n",
       " ('Arora Gursikh', 14),\n",
       " ('Jat Sikh Sandhu', 14),\n",
       " ('28/5\\x925\\x94', 14),\n",
       " ('Jat Sikh Gill', 14),\n",
       " ('one year', 14),\n",
       " ('84', 14),\n",
       " ('25/5\\x921\\x94', 14),\n",
       " ('4', 14),\n",
       " ('Mair Rajput', 14),\n",
       " ('3', 14),\n",
       " ('Sikh TonkKashtriya', 12),\n",
       " ('Mittal', 12),\n",
       " ('5\\x928\\x94', 12),\n",
       " ('Suitable Jat Sikh', 12),\n",
       " ('Five', 12),\n",
       " ('27/5\\x924\\x94', 12),\n",
       " ('31', 12),\n",
       " ('Hindu Arora', 12),\n",
       " ('22/5\\x924\\x94', 12),\n",
       " ('Six', 12),\n",
       " (\"5'8\", 12),\n",
       " ('Dentist', 12),\n",
       " ('24/5\\x92', 12),\n",
       " ('27/5\\x922\\x94', 12),\n",
       " ('few years', 12),\n",
       " ('PCS', 12),\n",
       " ('10', 12),\n",
       " ('MCom', 12),\n",
       " ('Himachali Rajput', 12),\n",
       " ('1992', 12),\n",
       " ('Reply', 12),\n",
       " ('French', 12),\n",
       " ('Ahluwalia', 12),\n",
       " ('17', 12),\n",
       " ('FIRST', 12),\n",
       " ('26/5\\x922\\x94', 12),\n",
       " ('SCO', 12),\n",
       " ('ALLIANCE', 12),\n",
       " ('26/5\\x925\\x94', 12),\n",
       " (\"30/5'4\", 10),\n",
       " ('Nurse', 10),\n",
       " ('Preference', 10),\n",
       " ('Sr Defence', 10),\n",
       " ('Diploma', 10),\n",
       " ('nonManglik', 10),\n",
       " ('Medico nonMedico', 10),\n",
       " ('28 years', 10),\n",
       " ('Fashion Designing', 10),\n",
       " ('26 5\\x921\\x94', 10),\n",
       " ('kundli', 10),\n",
       " ('USMLE', 10),\n",
       " ('HinduPunjabi', 10),\n",
       " ('Suitable Gursikh', 10),\n",
       " ('30/5\\x924\\x94', 10),\n",
       " ('December', 10),\n",
       " ('25/5\\x926\\x94', 10),\n",
       " ('Garg', 10),\n",
       " ('25 5\\x923\\x94', 10),\n",
       " ('MD MS', 10),\n",
       " ('Haryana', 10),\n",
       " ('Contact Col Ahluwalia Contact', 10),\n",
       " ('7755COLHot', 10),\n",
       " ('Status', 10),\n",
       " ('Gaur Brahmin', 10),\n",
       " ('Punjabi Arora', 10),\n",
       " ('Central Govt', 10),\n",
       " ('Engineer MBA', 10),\n",
       " ('MDS', 10),\n",
       " ('MTech', 10),\n",
       " ('London', 10),\n",
       " ('26/5\\x921\\x94', 10),\n",
       " ('33/5\\x923\\x94', 10),\n",
       " ('24 years', 10),\n",
       " ('Malwa', 10),\n",
       " ('29/5\\x924\\x94', 10),\n",
       " ('BCA', 10),\n",
       " ('Lobana Sikh', 10),\n",
       " ('NTT', 10),\n",
       " ('5\\x927\\x94', 10),\n",
       " ('Chamar', 10),\n",
       " ('Maths', 10),\n",
       " ('March', 10),\n",
       " ('29/5\\x922\\x94', 10),\n",
       " ('BE Electronics', 10),\n",
       " ('Jat Sikh MBBS', 10),\n",
       " ('27½', 8),\n",
       " ('Toronto', 8),\n",
       " ('Computer Science', 8),\n",
       " ('WebDesigning', 8),\n",
       " ('NRI Contact Col Ahluwalia', 8),\n",
       " ('717', 8),\n",
       " ('Computer Engineering', 8),\n",
       " ('Goel', 8),\n",
       " ('Groom', 8),\n",
       " ('Punjabi Kumhar', 8),\n",
       " ('5\\x92/24', 8),\n",
       " ('Tonkshatri', 8),\n",
       " ('21/5\\x924\\x94', 8),\n",
       " ('the last 32 years', 8),\n",
       " ('2235CEPOL', 8),\n",
       " ('Ramgarhia Gursikh', 8),\n",
       " ('76', 8),\n",
       " ('Diploma Engineer', 8),\n",
       " ('seven years', 8),\n",
       " ('Maruti', 8),\n",
       " ('Fresno', 8),\n",
       " ('24/5\\x927\\x94', 8),\n",
       " ('154', 8),\n",
       " ('23/5\\x925\\x94', 8),\n",
       " ('Doaba Rajput', 8),\n",
       " ('MBBS', 8),\n",
       " ('23/5\\x926\\x94', 8),\n",
       " ('32/5\\x923\\x94', 8),\n",
       " ('Indian Embassy', 8),\n",
       " ('MS', 8),\n",
       " ('Saraswat', 8),\n",
       " ('Public School', 8),\n",
       " ('Medico NonMedico', 8),\n",
       " ('three', 8),\n",
       " ('New Zealand', 8),\n",
       " ('two year', 8),\n",
       " ('Tel Email', 8),\n",
       " ('28 5\\x924\\x94', 8),\n",
       " ('Khanna', 8),\n",
       " ('32', 8),\n",
       " ('Kashyap Rajput', 8),\n",
       " ('Jat Gursikh', 8),\n",
       " ('Sikh Khatri', 8),\n",
       " ('5 years', 8),\n",
       " ('1', 8),\n",
       " ('Sikh Arora', 8),\n",
       " ('Boy', 8),\n",
       " ('UGCNET', 8),\n",
       " ('Khatri Manglik', 8),\n",
       " ('monthly', 8),\n",
       " ('Canadian American', 8),\n",
       " ('MA MPhil', 8),\n",
       " ('Kashatriya', 8),\n",
       " ('Mumbai', 8),\n",
       " ('15 marla', 8),\n",
       " (\"5'4\", 8),\n",
       " (\"5'3\", 8),\n",
       " ('Write', 8),\n",
       " ('MA Hindi', 8),\n",
       " ('Tonkshatria', 8),\n",
       " ('ESTABLISHED', 8),\n",
       " ('11', 8),\n",
       " ('10 years', 8),\n",
       " ('9931FOL', 6),\n",
       " ('Khatria', 6),\n",
       " ('Dental Surgeon', 6),\n",
       " ('Attn Mr Harkishan', 6),\n",
       " ('Commerce', 6),\n",
       " ('AC', 6),\n",
       " ('USA Girl', 6),\n",
       " ('Green', 6),\n",
       " ('New Delhi', 6),\n",
       " ('Chemistry', 6),\n",
       " ('Professional', 6),\n",
       " ('Caste no', 6),\n",
       " ('22/5\\x922\\x94', 6),\n",
       " ('Green Card', 6),\n",
       " ('Science Nursing', 6),\n",
       " ('1979', 6),\n",
       " ('69', 6),\n",
       " ('35/5\\x923\\x94', 6),\n",
       " ('1977', 6),\n",
       " ('31 years', 6),\n",
       " ('Dental', 6),\n",
       " ('580', 6),\n",
       " ('255\\x924\\x94', 6),\n",
       " ('November', 6),\n",
       " ('7948FOL', 6),\n",
       " ('26/5\\x927\\x94 MSc BEd', 6),\n",
       " ('8247FOL', 6),\n",
       " ('23/5\\x921\\x94', 6),\n",
       " ('72', 6),\n",
       " ('USA Send', 6),\n",
       " ('Bookkeeping Accounting Canadian', 6),\n",
       " ('29 years old', 6),\n",
       " ('October 2002', 6),\n",
       " ('Contact AS Post', 6),\n",
       " ('George Hwy Surrey BC', 6),\n",
       " ('4Z9', 6),\n",
       " ('6536FOL', 6),\n",
       " ('Comp Lect', 6),\n",
       " ('MA History', 6),\n",
       " ('Post Graduate', 6),\n",
       " ('Jat Sikh NRI', 6),\n",
       " ('28/5\\x922\\x94', 6),\n",
       " ('Medico Engineer', 6),\n",
       " ('1973', 6),\n",
       " ('Kapurthala', 6),\n",
       " ('Sourcincing Engineering', 6),\n",
       " ('Contact Joginder', 6),\n",
       " ('982', 6),\n",
       " ('Indian Forest Service', 6),\n",
       " ('29/165/', 6),\n",
       " ('4698FOL', 6),\n",
       " ('Kurukshetra', 6),\n",
       " ('5\\x927\\x92', 6),\n",
       " ('Upper', 6),\n",
       " ('Panchkula Mohali', 6),\n",
       " ('22½/5\\x925\\x94', 6),\n",
       " ('Genuine', 6),\n",
       " ('21/5\\x926\\x94', 6),\n",
       " ('31/5\\x925\\x94', 6),\n",
       " ('1975', 6),\n",
       " ('GRE', 6),\n",
       " ('May', 6),\n",
       " (\"29/5'2\", 6),\n",
       " ('70', 6),\n",
       " ('House', 6),\n",
       " ('Belong', 6),\n",
       " ('River Hills', 6),\n",
       " ('Chd', 6),\n",
       " ('Bhatia Gursikh', 6),\n",
       " ('Computer Engineer', 6),\n",
       " ('35', 6),\n",
       " ('MA Computer', 6),\n",
       " ('Employed', 6),\n",
       " ('25/5\\x921½\\x94', 6),\n",
       " ('Sikh Kamboz', 6),\n",
       " ('Sober', 6),\n",
       " ('26/5\\x927\\x94', 6),\n",
       " ('Tel', 6),\n",
       " ('Thakur Rajput', 6),\n",
       " ('Jatt Sikh', 6),\n",
       " ('32/5\\x924\\x94', 6),\n",
       " ('26/5\\x92', 6),\n",
       " ('Medico IAS', 6),\n",
       " ('Gursikh Khatri', 6),\n",
       " ('Suitable Jat', 6),\n",
       " ('Parjapati', 6),\n",
       " ('Mazbi Sikh', 6),\n",
       " ('Hindu Khatri', 6),\n",
       " ('College Lecturer', 6),\n",
       " ('HP', 6),\n",
       " ('27 years', 6),\n",
       " ('Bank', 6),\n",
       " ('28/5\\x92', 6),\n",
       " ('73', 6),\n",
       " ('28/158', 6),\n",
       " ('23/5\\x922\\x94', 6),\n",
       " ('Maths and Science', 6),\n",
       " ('CV', 6),\n",
       " ('United Kingdom', 6),\n",
       " ('2189CEPOL', 6),\n",
       " ('1 year', 6),\n",
       " ('Punjabi Saraswat Brahmin', 6),\n",
       " ('Sharma', 6),\n",
       " ('MIT', 6),\n",
       " ('Engineers', 6),\n",
       " ('Divorcee', 6),\n",
       " ('USA Canadian', 6),\n",
       " ('22/5\\x926½\\x94', 6),\n",
       " ('Hindu Punjabi', 6),\n",
       " ('the first week of August', 6),\n",
       " ('Roman Catholic Christian', 6),\n",
       " (\"24/5'4\", 6),\n",
       " ('34/5\\x921\\x94', 6),\n",
       " ('Hindu Saini', 6),\n",
       " ('SC', 6),\n",
       " ('MBA Diploma Computers Working', 6),\n",
       " ('Jat Sikh USA', 6),\n",
       " ('24/5\\x922\\x94', 6),\n",
       " ('16', 6),\n",
       " ('Punjab Govt', 6),\n",
       " (\"25/5'6\", 6),\n",
       " ('JAT', 6),\n",
       " ('MA Economics', 6),\n",
       " ('Manglik NonManglik', 6),\n",
       " ('22 years', 6),\n",
       " ('BBA', 6),\n",
       " ('Gotra Kainth Jassal Simple', 6),\n",
       " ('Industrialist', 6),\n",
       " ('24½ years 156cms', 6),\n",
       " ('CC858OL', 6),\n",
       " ('VRS', 6),\n",
       " ('Jat Sikh Sidhu', 6),\n",
       " ('9314COL', 6),\n",
       " ('10A', 6),\n",
       " ('9743COL', 6),\n",
       " ('Saraswat Brahmin Manglik', 4),\n",
       " ('July', 4),\n",
       " ('NonMedical', 4),\n",
       " ('Family', 4),\n",
       " ('24/5\\x923\\x94 MBA', 4),\n",
       " ('Govt Officers', 4),\n",
       " ('Supreintending Engingeer', 4),\n",
       " ('2528 years', 4),\n",
       " ('3 weeks', 4),\n",
       " ('Pursuing Computer', 4),\n",
       " ('ten years', 4),\n",
       " ('25 5\\x924\\x94', 4),\n",
       " ('28/5\\x923\\x94 MA', 4),\n",
       " ('26/5\\x926\\x94', 4),\n",
       " ('10 days', 4),\n",
       " ('Dhiman', 4),\n",
       " ('Brahmin', 4),\n",
       " ('Govt Officer', 4),\n",
       " ('4372CEPOL', 4),\n",
       " ('24/5\\x923\\x92 MBA', 4),\n",
       " ('Alcohol MBBS MD', 4),\n",
       " ('2228 years', 4),\n",
       " ('NY NJ', 4),\n",
       " ('Wayne USA', 4),\n",
       " ('5\\x926\\x94 MA', 4),\n",
       " ('Ludhiana Dist', 4),\n",
       " ('4531CEPOL', 4),\n",
       " ('Asstt', 4),\n",
       " ('KHATRI', 4),\n",
       " ('30/5\\x925\\x94 BA', 4),\n",
       " ('297CEHOL', 4),\n",
       " ('PGT', 4),\n",
       " ('Computers', 4),\n",
       " ('400', 4),\n",
       " ('1999', 4),\n",
       " ('Mesa', 4),\n",
       " ('Ophthalmologist', 4),\n",
       " ('London Hospital Mother', 4),\n",
       " ('next three weeks', 4),\n",
       " ('27/5\\x923½\\x94', 4),\n",
       " ('24/157', 4),\n",
       " ('Amritdhari', 4),\n",
       " ('1625FOL', 4),\n",
       " ('Govt ETT', 4),\n",
       " ('23 5\\x924\\x94', 4),\n",
       " ('KU', 4),\n",
       " ('Addharmi', 4),\n",
       " ('Computer', 4),\n",
       " ('PSU', 4),\n",
       " ('34/5\\x924\\x94', 4),\n",
       " ('Alliance', 4),\n",
       " ('Bachelor\\x92s', 4),\n",
       " ('1561FOL', 4),\n",
       " ('Send kundli biodata', 4),\n",
       " ('18D', 4),\n",
       " ('11A', 4),\n",
       " ('Maid Rajput', 4),\n",
       " ('Software', 4),\n",
       " ('Jat Sikh Mann', 4),\n",
       " ('second', 4),\n",
       " ('three year', 4),\n",
       " ('23/5\\x923½\\x94', 4),\n",
       " ('31 5\\x922\\x94', 4),\n",
       " ('28 year', 4),\n",
       " ('5\\x922½\\x94', 4),\n",
       " ('161', 4),\n",
       " ('Graduate Hindu', 4),\n",
       " ('155', 4),\n",
       " ('24/5\\x923\\x94 BSc', 4),\n",
       " ('3017CEPOL', 4),\n",
       " ('BCom Diploma', 4),\n",
       " ('Information Technology Status', 4),\n",
       " ('6842FOL', 4),\n",
       " ('MA PGDCA', 4),\n",
       " ('Kamboj Gursikh', 4),\n",
       " ('5\\x923½\\x94 1979', 4),\n",
       " ('Agri Hons', 4),\n",
       " ('Sikh Kashyap Rajput', 4),\n",
       " ('29+/5\\x925\\x94', 4),\n",
       " ('10 + 2', 4),\n",
       " ('ALLIANCE INVITED FROM HIGH STATUS BUSINESS GURSIKH', 4),\n",
       " ('AGE 22', 4),\n",
       " ('7196FOL', 4),\n",
       " ('31 May 1973', 4),\n",
       " ('27/5\\x922½\\x94', 4),\n",
       " ('22/5\\x923\\x94', 4),\n",
       " ('nonMann Jat Sikh', 4),\n",
       " ('ALLIANCE INVITED FROM', 4),\n",
       " ('5\\x927\\x94 30', 4),\n",
       " ('1995', 4),\n",
       " ('8 weeks', 4),\n",
       " ('celestial_aria@hotmailcom', 4),\n",
       " ('5808FOL', 4),\n",
       " ('Seeks', 4),\n",
       " ('2442CEPOL', 4),\n",
       " ('Preferred', 4),\n",
       " ('Verma', 4),\n",
       " ('18', 4),\n",
       " ('Bombay', 4),\n",
       " ('Kushwaha Rajput', 4),\n",
       " ('Punjab22½/5\\x928\\x94 MBA', 4),\n",
       " ('CAT Institute', 4),\n",
       " ('UGC NET', 4),\n",
       " ('22/5\\x928\\x94', 4),\n",
       " ('21½/5\\x923½\\x94', 4),\n",
       " ('36 years', 4),\n",
       " ('Senior Bank', 4),\n",
       " ('Match', 4),\n",
       " ('Arora Khatri Sikh', 4),\n",
       " ('44', 4),\n",
       " ('10 acre', 4),\n",
       " ('Vancouver', 4),\n",
       " ('1184264th', 4),\n",
       " ('7165COL', 4),\n",
       " ('Sony', 4),\n",
       " ('Thermal Printer', 4),\n",
       " ('23/155', 4),\n",
       " ('4467FOL', 4),\n",
       " ('152', 4),\n",
       " ('Engineer USA', 4),\n",
       " ('Govt College', 4),\n",
       " ('Manglik Hindu', 4),\n",
       " ('New York', 4),\n",
       " ('1012', 4),\n",
       " ('Sidhu', 4),\n",
       " ('26/155 cm', 4),\n",
       " ('173', 4),\n",
       " ('Bathinda', 4),\n",
       " ('30/158/50', 4),\n",
       " ('H1visa', 4),\n",
       " ('Sikh Ramgarhia', 4),\n",
       " ('32½/5\\x924\\x94', 4),\n",
       " ('IPS', 4),\n",
       " ('23/165', 4),\n",
       " ('ETT', 4),\n",
       " ('D Microbiology', 4),\n",
       " ('Nai Sikh', 4),\n",
       " ('33/157 HCMS Early', 4),\n",
       " ('Arora Punjabi', 4),\n",
       " ('MBA 25½', 4),\n",
       " ('USA Preferably USA Canadian', 4),\n",
       " ('Gupta Mahajan', 4),\n",
       " ('30 years', 4),\n",
       " ('NRI MNC Civil Services Jat Sikh', 4),\n",
       " ('60', 4),\n",
       " ('77', 4),\n",
       " ('last week', 4),\n",
       " ('8941FOL', 4),\n",
       " ('5\\x924\\x94/26', 4),\n",
       " ('29 years', 4),\n",
       " ('NIFD', 4),\n",
       " ('Sikh Punjabi', 4),\n",
       " ('Bhatia', 4),\n",
       " ('one four years', 4),\n",
       " ('9519N River Bend Court', 4),\n",
       " ('four years', 4),\n",
       " ('9054FOL', 4),\n",
       " ('U R', 4),\n",
       " ('33A', 4),\n",
       " ('2204', 4),\n",
       " ('VIENNAVA USA', 4),\n",
       " ('28/5\\x926\\x94', 4),\n",
       " ('360', 4),\n",
       " ('25/5\\x927\\x94', 4),\n",
       " ('Dental College', 4),\n",
       " ('Engineer MS', 4),\n",
       " ('25/157', 4),\n",
       " ('August', 4),\n",
       " ('Medico MD MS', 4),\n",
       " ('Seek Gursikh', 4),\n",
       " ('PGDCT', 4),\n",
       " ('Sikh Tonkshatriya', 4),\n",
       " ('MA Eco', 4),\n",
       " ('Honours Chemistry', 4),\n",
       " ('5938FOL', 4),\n",
       " ('Goldsmith', 4),\n",
       " ('26½', 4),\n",
       " ('Kapurthala Punjab', 4),\n",
       " ('1½', 4),\n",
       " ('MAEnglish', 4),\n",
       " ('Patiala', 4),\n",
       " ('Jatsikh MBA', 4),\n",
       " ('alliance_2002@hotmailcom', 4),\n",
       " ('Simple', 4),\n",
       " ('GC', 4),\n",
       " ('Parjapat', 4),\n",
       " ('Sikh Weaver', 4),\n",
       " ('Librarian', 4),\n",
       " ('27/162', 4),\n",
       " ('Ramgariah Sikh', 4),\n",
       " ('27/165', 4),\n",
       " ('Embassy', 4),\n",
       " ('38', 4),\n",
       " ('27/5\\x927\\x94', 4),\n",
       " ('SikhKhatri', 4),\n",
       " ('USA Status', 4),\n",
       " ('Aggarwal', 4),\n",
       " ('1968', 4),\n",
       " ('5\\x921\\x94permanent', 4),\n",
       " ('Sarswat Mohyal Brahmin Chhibber', 4),\n",
       " ('Medico Dental', 4),\n",
       " ('Wanted Scientist University Lecturer Engineer', 4),\n",
       " ('Engineer IAS', 4),\n",
       " ('24/', 4),\n",
       " ('Mesa USA EMail', 4),\n",
       " ('NRI Punjabi', 4),\n",
       " ('Caste no bar', 4),\n",
       " ('35 years', 4),\n",
       " ('MBE', 4),\n",
       " ('Rajput', 4),\n",
       " ('32/5\\x922\\x94', 4),\n",
       " ('Punjabi Kshatriya Rajput', 4),\n",
       " ('162/25', 4),\n",
       " ('BE MBA MS', 4),\n",
       " ('1696FOL', 4),\n",
       " ('kundli biodata', 4),\n",
       " ('only one', 4),\n",
       " ('Radha Soami', 4),\n",
       " ('Mother', 4),\n",
       " ('22/165/50', 4),\n",
       " ('MBA Goyal', 4),\n",
       " ('68', 4),\n",
       " ('Gursikh Ramgarhia', 4),\n",
       " ('Dec 1974', 4),\n",
       " ('BELONGING TOWELL', 4),\n",
       " ('26½/', 4),\n",
       " ('32/5\\x926\\x94', 4),\n",
       " ('BA Hons', 4),\n",
       " ('USACanadian', 4),\n",
       " ('USA Parents', 4),\n",
       " ('27/158', 4),\n",
       " (\"28/5'2\", 4),\n",
       " ('Indian Army', 4),\n",
       " ('Himachal', 4),\n",
       " ('26/5\\x928', 4),\n",
       " ('12 acres', 4),\n",
       " ('2500', 4),\n",
       " ('SCO Sec', 4),\n",
       " ('Mehfil Contact', 4),\n",
       " ('829COL', 4),\n",
       " ('Canada Send', 4),\n",
       " ('Khatri Khukhrain', 4),\n",
       " ('2112FOL', 4),\n",
       " ('2456FOL', 4),\n",
       " ('Mair Rajput Goldsmith', 4),\n",
       " ('LIC', 4),\n",
       " ('MA Political Science', 4),\n",
       " ('1980', 4),\n",
       " ('MBA Computer', 4),\n",
       " ('PGD', 4),\n",
       " ('Textile Designing Sep', 4),\n",
       " ('Biodata', 4),\n",
       " ('Jat Sikh Sohi', 4),\n",
       " ('ComputerDiploma', 4),\n",
       " ('8472FOL', 4),\n",
       " ('8500/', 4),\n",
       " ('23½/5\\x922\\x94', 4),\n",
       " ('Punjab University Please', 4),\n",
       " ('Sarswat Brahmin', 4),\n",
       " ('26/5\\x926\\x94 MSE Computer Science', 4),\n",
       " ('London University Girl', 4),\n",
       " ('1½ year', 4),\n",
       " ('New York City', 4),\n",
       " ('3 years', 4),\n",
       " ('25/5\\x92', 4),\n",
       " ('5 year', 4),\n",
       " ('23/5\\x924\\x92\\x92', 4),\n",
       " ('sb_singh@yahoocom 4450FOL', 4),\n",
       " ('HomoeopathDoctor Computer', 4),\n",
       " ('USA Doctor Engineer', 4),\n",
       " ('Resond', 4),\n",
       " ('23 5\\x924½\\x94homely', 4),\n",
       " ('Lakeport Court', 4),\n",
       " ('San Jose', 4),\n",
       " ('29/5\\x926\\x94', 4),\n",
       " ('GPO', 4),\n",
       " ('29/163', 4),\n",
       " ('BCom Hons', 4),\n",
       " ('Graduate Sikh', 4),\n",
       " ('July\\x9173 5\\x923\\x94', 4),\n",
       " ('166', 4),\n",
       " ('nonMedico', 4),\n",
       " ('ALLIANCE INVITED', 4),\n",
       " ('MD Engineer', 4),\n",
       " ('MBA Executive', 4),\n",
       " ('1291CEPOL', 4),\n",
       " ('Punjab 29/5\\x924\\x94', 4),\n",
       " ('Delta BC', 4),\n",
       " ('2632FOL', 4),\n",
       " ('25/5\\x922\\x94', 4),\n",
       " ('few weeks', 4),\n",
       " (\"22/1/2 5'5\", 4),\n",
       " ('BCom French Foundation Diploma Computer NIIT Oracle 8', 4),\n",
       " ('Australian Ramgarhia Sikh', 4),\n",
       " ('Australian University', 4),\n",
       " ('MBBS Science Engineering IT', 4),\n",
       " ('Food Technology Send', 4),\n",
       " ('PO 2042', 4),\n",
       " ('Keperra QLD', 4),\n",
       " ('5054', 4),\n",
       " ('20/5\\x922\\x94', 4),\n",
       " ('Decent', 4),\n",
       " ('Feb 74', 4),\n",
       " ('HomeScience Postgraduate Nutrition', 4),\n",
       " ('Christian', 4),\n",
       " ('Khatris', 4),\n",
       " ('TGT', 4),\n",
       " ('Convent', 4),\n",
       " ('BE MBA', 4),\n",
       " ('Bhigas of Agricultural', 4),\n",
       " ('Suburban', 4),\n",
       " ('Amloh Suitable', 4),\n",
       " ('BCom French Foundation Diploma Computer NIIT Oracle 8i Preferred', 4),\n",
       " ('27/5\\x925½\\x94', 4),\n",
       " ('40', 4),\n",
       " ('31/5\\x922\\x94', 4),\n",
       " ('one month', 4),\n",
       " ('30 years old', 4),\n",
       " ('Sr Brahmin', 4),\n",
       " ('Proposal', 4),\n",
       " ('Diploma Computer Software Programmer', 4),\n",
       " ('50', 4),\n",
       " ('GAMS', 4),\n",
       " ('21 years', 4),\n",
       " ('Agarwal', 4),\n",
       " ('145/36A', 4),\n",
       " ('Gill', 4),\n",
       " ('Ramgarhia Dhiman', 4),\n",
       " ('ten', 4),\n",
       " ('three hundred', 4),\n",
       " ('BA Economics', 4),\n",
       " ('Hindu Kashyap Rajput', 4),\n",
       " ('Contact SCO', 4),\n",
       " ('Jat Sikh MDS BDS', 4),\n",
       " ('TonkKashtriya', 4),\n",
       " (\"5'2\", 4),\n",
       " ('Ten', 4),\n",
       " ('Amritdhari Doctor Engineer', 4),\n",
       " ('BS ComputerSc', 4),\n",
       " ('Raizada', 4),\n",
       " ('Arora Hindu', 4),\n",
       " ('155 cm', 4),\n",
       " ('PHP MySql Cold Fusion', 4),\n",
       " ('1year', 4),\n",
       " ('SCF', 4),\n",
       " ('5035COL', 4),\n",
       " ('Lobana', 4),\n",
       " ('18 acres', 4),\n",
       " ('North American', 4),\n",
       " (\"5'/24 years\", 4),\n",
       " (\"24/5'6\", 4),\n",
       " ('Contact Col Ahluwalia 145 Sector', 4),\n",
       " ('Khatri Arora Gursikh', 4),\n",
       " ('26½/5\\x922\\x94', 4),\n",
       " ('6', 4),\n",
       " ('Ramgarhia Sikh Dhiman', 4),\n",
       " ('MA Fashionand Computer Web Designing Diploma Educated', 4),\n",
       " ('MA English Kundli', 4),\n",
       " ('Manglik Nonmanglik', 4),\n",
       " ('MD Saini', 4),\n",
       " ('English Medium', 4),\n",
       " ('Urban Estate Jalandhar Ist 2nd floors 1555', 4),\n",
       " ('Contact julks@rediffmailcom', 4),\n",
       " ('4417FOL', 4),\n",
       " ('158', 4),\n",
       " ('XEN', 4),\n",
       " ('29/5\\x925\\x94', 4),\n",
       " ('Computer Engineers', 4),\n",
       " ('Principal Correspond', 4),\n",
       " ('kundli 4377FOL', 4),\n",
       " ('Army School Patiala', 4),\n",
       " ('31/5\\x923\\x94', 4),\n",
       " ('week', 4),\n",
       " ('IAS IPS', 4),\n",
       " ('Hindu Rajput', 4),\n",
       " ('23½/5\\x923½\\x94', 4),\n",
       " ('Sikh Walia', 4),\n",
       " ('26/5\\x922½\\x94', 4),\n",
       " ('Mohyal Saraswat Brahmin', 4),\n",
       " ('AirHostess', 4),\n",
       " ('Chandigarh', 4),\n",
       " ('PA', 4),\n",
       " ('IIT', 4),\n",
       " ('PO Abu Dhabi UAE', 4),\n",
       " ('630', 4),\n",
       " ('Ghumar Sikh', 4),\n",
       " (\"24/5'1\", 4),\n",
       " ('24/5', 4),\n",
       " ('8604FOL', 4),\n",
       " ('Khatri Gursikh', 4),\n",
       " ('300 sq yards', 4),\n",
       " ('7680', 4),\n",
       " ('Girls College', 4),\n",
       " ('30/5\\x92', 4),\n",
       " ('23½', 4),\n",
       " ('20', 4),\n",
       " ('25½/5\\x923\\x94', 4),\n",
       " ('Businessman', 4),\n",
       " ('May 75/5\\x923\\x94', 4),\n",
       " ('Contact Kumaria', 4),\n",
       " ('NRI Ahluwalia', 4),\n",
       " (\"21/5'4\", 4),\n",
       " ('Sikh Medico', 4),\n",
       " ('Sikh Kamboj', 4),\n",
       " ('Feb 75', 4),\n",
       " (\"26/5'2\", 4),\n",
       " (\"21+/5'2½\", 4),\n",
       " ('Bangalore', 4),\n",
       " ('Bhatra Sikh', 4),\n",
       " ('27/5\\x923\\x94 MBA UGC', 2),\n",
       " ('8768ABOL', 2),\n",
       " ('Kumhar Sikh', 2),\n",
       " ('BEAUTIFUL FAIR', 2),\n",
       " ('SLIM MA', 2),\n",
       " ('Brahmin Khatri', 2),\n",
       " ('23/158', 2),\n",
       " ('9930FOL', 2),\n",
       " ('24/5\\x922\\x94 BPharma', 2),\n",
       " ('Jain Jain Hospital', 2),\n",
       " ('Manju Hotel', 2),\n",
       " ('MFC PGDCA', 2),\n",
       " ('1977/5\\x923\\x94', 2),\n",
       " ('26/5\\x921\\x94 MA', 2),\n",
       " ('1075NEHOL', 2),\n",
       " ('5\\x92/26 year old', 2),\n",
       " ('9904FOL', 2),\n",
       " ('Ludhiana Dist Mobile', 2),\n",
       " ('29 5\\x924\\x94', 2),\n",
       " ('USA Decent', 2),\n",
       " ('BCom India', 2),\n",
       " ('Virk Shergill Email', 2),\n",
       " ('IIT MBA', 2),\n",
       " ('Med MBA', 2),\n",
       " ('South Delhi', 2),\n",
       " ('7', 2),\n",
       " ('9910FOL', 2),\n",
       " ('MDS MD MBBS BDS', 2),\n",
       " ('Brothers Engineer', 2),\n",
       " ('Sunday', 2),\n",
       " ('33 yrs/5\\x927\\x94', 2),\n",
       " ('Eight year', 2),\n",
       " ('Wellqualified', 2),\n",
       " ('inig2623@yahoocom', 2),\n",
       " ('9985FOL', 2),\n",
       " ('Jan 72', 2),\n",
       " ('August 1975/5\\x929\\x94', 2),\n",
       " ('Medicos Engineer Lecturer Military Civil', 2),\n",
       " ('MA Psy India', 2),\n",
       " ('24/5\\x923\\x94 kundli', 2),\n",
       " ('Manglik Punjabi Saraswat Brahmin', 2),\n",
       " ('24½/165', 2),\n",
       " ('Adhi Nadi', 2),\n",
       " ('23½/150', 2),\n",
       " ('2 years', 2),\n",
       " ('Gotra Rupal Daffu Preferred', 2),\n",
       " ('CASTE NO BAR APPLY', 2),\n",
       " ('Saraswat Punjabi Brahmin', 2),\n",
       " ('May 8 1976/555', 2),\n",
       " ('girl26/5\\x925\\x94 12th', 2),\n",
       " ('Arora Khatri Gursikh', 2),\n",
       " ('28/5\\x921', 2),\n",
       " ('5\\x924\\x94 23', 2),\n",
       " ('Bank Required IAS', 2),\n",
       " ('Software Engineers', 2),\n",
       " ('Contact Email', 2),\n",
       " ('Arora Gazetted', 2),\n",
       " ('2528', 2),\n",
       " ('Sikh Kenyan', 2),\n",
       " ('age 24', 2),\n",
       " ('Jat Sikh MD', 2),\n",
       " ('Gold Medalist', 2),\n",
       " ('Air Force', 2),\n",
       " ('Medical College Punjab', 2),\n",
       " ('PGDCA Public School', 2),\n",
       " ('Manglik Jat Sikh', 2),\n",
       " ('Jat Sikh Manglik', 2),\n",
       " ('ExSr Executive', 2),\n",
       " ('26 +', 2),\n",
       " ('Hindu Khatri Punjabi', 2),\n",
       " ('Chemical Engineer', 2),\n",
       " ('AGE 28', 2),\n",
       " ('LIBRARY SCIENCE0 DECENT', 2),\n",
       " ('26/5\\x923\\x94 BEd', 2),\n",
       " ('Diploma Computers Fashion Designing', 2),\n",
       " ('40 acres', 2),\n",
       " ('Contact Brij Lal', 2),\n",
       " ('one two', 2),\n",
       " ('37 year', 2),\n",
       " ('Himachali Rajput Central School', 2),\n",
       " ('Kanojia Dhobi', 2),\n",
       " ('Pooran Gursikh', 2),\n",
       " ('Lyallpur Sargodha', 2),\n",
       " ('Email GSingh43@yahoocom', 2),\n",
       " ('22½/about 152', 2),\n",
       " ('Medico Punjabi', 2),\n",
       " ('Vegetarian Teetotaller', 2),\n",
       " ('London Massi', 2),\n",
       " ('CC560OL', 2),\n",
       " ('Dixit Brahmin', 2),\n",
       " ('MCA Biodata', 2),\n",
       " ('24/ 5\\x923\\x94', 2),\n",
       " ('1977FOL', 2),\n",
       " ('Steno English Punjabi Computer', 2),\n",
       " ('1955FOL', 2),\n",
       " ('Manglik Saraswat Brahmin', 2),\n",
       " ('English Aug', 2),\n",
       " ('1960FOL', 2),\n",
       " ('Bhatia Khatri', 2),\n",
       " ('Southern California', 2),\n",
       " ('Punjabi Business', 2),\n",
       " ('many years', 2),\n",
       " ('Gursikh Parjapati MA Computer', 2),\n",
       " ('1969FOL', 2),\n",
       " ('152@hotmailcom 1652ABOL', 2),\n",
       " ('1995FOL', 2),\n",
       " ('1972FOL', 2),\n",
       " ('English Post Graduate', 2),\n",
       " ('Computers Highly', 2),\n",
       " ('Amritdhari Jatsikh', 2),\n",
       " ('twelve years', 2),\n",
       " ('5\\x922\\x94/21 years', 2),\n",
       " ('Civil Services Army', 2),\n",
       " ('1917FOL', 2),\n",
       " ('TGT HP', 2),\n",
       " ('1936FOL', 2),\n",
       " ('1899FOL', 2),\n",
       " ('1852FOL', 2),\n",
       " ('1942FOL', 2),\n",
       " ('Child Dev BEd', 2),\n",
       " ('BCOM STATUS INDUSTRIALIST FAMILY SEND', 2),\n",
       " ('Match NRI Engineer', 2),\n",
       " ('1943FOL', 2),\n",
       " ('USA Canadian Professional', 2),\n",
       " ('June 76/5\\x925\\x94+', 2),\n",
       " ('9 year old', 2),\n",
       " ('33 5\\x922\\x94', 2),\n",
       " ('249/5\\x924\\x94', 2),\n",
       " ('1916FOL', 2),\n",
       " ('Diploma Anaesthesia', 2),\n",
       " ('MBA Lecturer Engineer', 2),\n",
       " ('1940FOL', 2),\n",
       " ('23½/5\\x927\\x94', 2),\n",
       " ('1963FOL', 2),\n",
       " ('Engineer CA MBA Educated Industrialist Businessman', 2),\n",
       " ('Convent Educated MCom', 2),\n",
       " ('Abroad for Convent Educated', 2),\n",
       " ('October 16th', 2),\n",
       " ('Bank of Punjab Jalandhar', 2),\n",
       " ('2014FOL', 2),\n",
       " ('Medico PG', 2),\n",
       " ('Hindu Arora MBBS', 2),\n",
       " ('Hindu Khatri Bank', 2),\n",
       " ('37/167/56', 2),\n",
       " ('Postgraduate in Finance', 2),\n",
       " ('1981FOL', 2),\n",
       " ('5\\x9265\\x94', 2),\n",
       " ('Kamboj Kashatriya', 2),\n",
       " ('Education College', 2),\n",
       " ('72CAOL', 2),\n",
       " ('Lubana 23/5\\x925\\x94 MA', 2),\n",
       " ('1675ABOL', 2),\n",
       " ('25 plus/152', 2),\n",
       " ...]"
      ]
     },
     "execution_count": 212,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "entityCounts = {}\n",
    "for entry in brides_df['classified_sents']:\n",
    "    for sentence in entry:\n",
    "        for ent, kind in sentence:\n",
    "            if ent in entityCounts:\n",
    "                entityCounts[ent] += 1\n",
    "            else:\n",
    "                entityCounts[ent] = 1\n",
    "sortedEntities = sorted(entityCounts.items(), key = lambda x: x[1], reverse = True)\n",
    "sortedEntities"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 211,
   "id": "efd22c3d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('Jat Sikh', 544),\n",
       " ('Khatri', 340),\n",
       " ('one', 288),\n",
       " ('Hindu', 286),\n",
       " ('USA', 236),\n",
       " ('US', 204),\n",
       " ('India', 196),\n",
       " ('Canadian', 176),\n",
       " ('Canada', 158),\n",
       " ('Sikh', 128)]"
      ]
     },
     "execution_count": 211,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nonObjCounts = {}\n",
    "for entry in brides_df['classified_sents']:\n",
    "    for sentence in entry:\n",
    "        for ent, kind in sentence:\n",
    "            if kind == 'ORG':\n",
    "                continue\n",
    "            elif ent in nonObjCounts:\n",
    "                nonObjCounts[ent] += 1\n",
    "            else:\n",
    "                nonObjCounts[ent] = 1\n",
    "sortedNonObj = sorted(nonObjCounts.items(), key = lambda x: x[1], reverse = True)\n",
    "sortedNonObj[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 296,
   "id": "3668c62a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saraswat Brahmin Manglik\n",
      "PGDCA\n",
      "MA\n",
      "Manglik\n",
      "Saraswat Brahmin\n",
      "MNC\n",
      "NRI\n",
      "Punjabi Brahmin\n",
      "BDS\n",
      "Mittal\n",
      "NonMedical\n",
      "Dental Surgeon\n",
      "Attn Mr Harkishan\n",
      "MNC\n",
      "Govt Officers\n",
      "Army\n",
      "BDS\n",
      "Preference\n",
      "Ludhiana Dist Mobile\n",
      "Commerce\n",
      "USA Decent\n",
      "BCom India\n",
      "Pursuing Computer\n",
      "IAS\n",
      "MNC\n",
      "AC\n",
      "MDS MD MBBS BDS\n",
      "Brothers Engineer\n",
      "USA Girl\n",
      "Visa\n",
      "NRI\n",
      "Computer Science\n",
      "Wellqualified\n",
      "inig2623@yahoocom\n",
      "Send\n",
      "BA\n",
      "Preference\n",
      "Medicos Engineer Lecturer Military Civil\n",
      "MA Psy India\n",
      "Manglik Punjabi Saraswat Brahmin\n",
      "WebDesigning\n",
      "Computer Science\n",
      "Gotra Rupal Daffu Preferred\n",
      "Saraswat Punjabi Brahmin\n",
      "Govt Officer\n",
      "Send\n",
      "girl26/55 12th\n",
      "Punjabi\n",
      "NRI\n",
      "Bank Required IAS\n",
      "Software Engineers\n",
      "Medico\n",
      "BDS\n",
      "MNC\n",
      "Army\n",
      "Alcohol MBBS MD\n",
      "NY NJ\n",
      "Air Force\n",
      "Medical College Punjab\n",
      "BDS\n",
      "PGDCA Public School\n",
      "Manglik Jat Sikh\n",
      "BA\n",
      "ExSr Executive\n",
      "BCom\n",
      "Manglik\n",
      "Hindu Khatri Punjabi\n",
      "Asstt\n",
      "Chemical Engineer\n",
      "KHATRI\n",
      "Diploma Computers Fashion Designing\n",
      "Professional\n",
      "Contact Brij Lal\n",
      "NRI\n",
      "Contact Col Ahluwalia\n",
      "NRI Contact Col Ahluwalia\n",
      "MNC\n",
      "Himachali Rajput Central School\n",
      "PGT\n",
      "BA\n",
      "Science Nursing\n",
      "Mesa\n",
      "Ophthalmologist\n",
      "Medico\n",
      "Manglik\n",
      "London Hospital Mother\n",
      "Medico Punjabi\n",
      "BDS\n",
      "London Massi\n",
      "CC560OL\n",
      "Dixit Brahmin\n",
      "Computer Engineering\n",
      "MCA\n",
      "Saraswat Brahmin\n",
      "Steno English Punjabi Computer\n",
      "Manglik Saraswat Brahmin\n",
      "NRI\n",
      "Punjabi Hindu\n",
      "Punjabi Business\n",
      "Gursikh Parjapati MA Computer\n",
      "Punjabi Hindu\n",
      "Computers Highly\n",
      "NRI\n",
      "Singla\n",
      "Civil Services Army\n",
      "TGT HP\n",
      "BCom\n",
      "Manglik\n",
      "BHP\n",
      "Match NRI Engineer\n",
      "USA Canadian Professional\n",
      "BCom\n",
      "JatSikh\n",
      "PSU\n",
      "Sikh\n",
      "Caste\n",
      "Singla\n",
      "NRI\n",
      "Engineer CA MBA Educated Industrialist Businessman\n",
      "Abroad for Convent Educated\n",
      "Bank of Punjab Jalandhar\n",
      "Medico PG\n",
      "Alliance\n",
      "Hindu Khatri Bank\n",
      "Postgraduate in Finance\n",
      "Army\n",
      "Bachelors\n",
      "Computer Engineering\n",
      "MA\n",
      "Lecturer\n",
      "Education College\n",
      "MPhil\n",
      "USMLE\n",
      "riponch@rediffmailcom\n",
      "NonMedical\n",
      "CC586OL\n",
      "Manglik Chauhan Rajput\n",
      "MNC\n",
      "Medico\n",
      "BDS\n",
      "Army\n",
      "MNC S WE USA HIB BE Elect MBAIT\n",
      "Sydney Convent\n",
      "Parents GC\n",
      "Tele\n",
      "Dental\n",
      "Sec 28A\n",
      "Contact Col Ahluwalia\n",
      "BCom\n",
      "DDS Engineer\n",
      "HinduPunjabi\n",
      "BA\n",
      "PGDCA\n",
      "Red Cross\n",
      "mukeshprabhakar@hotmailcom\n",
      "Kaushik ManglikAntyanadi\n",
      "PGDCA\n",
      "Software\n",
      "MCA Parents\n",
      "BHP\n",
      "NRI\n",
      "Punjabi\n",
      "NRI\n",
      "USA Will\n",
      "Ivy League University\n",
      "Sandhu\n",
      "MPhil\n",
      "Govt High School\n",
      "MIS\n",
      "Medico\n",
      "USMLE\n",
      "Tayal Punjabi Aggarwal\n",
      "BSc(Home Science\n",
      "MBA Punjabi Khatrigirl\n",
      "NRI\n",
      "Fashion Designing\n",
      "MNC\n",
      "PGDCA\n",
      "Medico\n",
      "Doctorgirl\n",
      "Punchkula Mohali Contact House\n",
      "MA\n",
      "Dentist\n",
      "NRI\n",
      "Punjabi\n",
      "Bsbrli@aolcom 8454FOL\n",
      "Graduate Hindu\n",
      "Medico\n",
      "JatSikh\n",
      "BCom\n",
      "Govt College Army\n",
      "BDS\n",
      "DNB\n",
      "Institute Rs\n",
      "duplex house\n",
      "Ideal\n",
      "Contact Mobile\n",
      "Medico nonMedico\n",
      "USA Send\n",
      "NRI\n",
      "Information Technology Status\n",
      "Bookkeeping Accounting Canadian\n",
      "Contact AS Post\n",
      "Contact Email bpanesar2000@yahoocom 7050FOL\n",
      "Qualified\n",
      "Bhriguvanshi Brahmin\n",
      "BCom\n",
      "DTP Designer\n",
      "BHP\n",
      "MPhil\n",
      "UGC\n",
      "Lecturer\n",
      "UGC\n",
      "3137CEPOL\n",
      "PGDCA\n",
      "BA\n",
      "BCom\n",
      "Garg\n",
      "Asstt\n",
      "Indane Allotee\n",
      "Advocate Administrator\n",
      "Punjabi Kumhar\n",
      "ETT Preferred\n",
      "Post Graduate\n",
      "MA Eng\n",
      "Saraswat Brahmin\n",
      "Culture Stitching Fabric Painting\n",
      "Sarojini\n",
      "Yamuna Nagar135001\n",
      "Commerce\n",
      "ALLIANCE INVITED FROM HIGH STATUS BUSINESS GURSIKH\n",
      "Medico nonMedico\n",
      "BDS\n",
      "PCS\n",
      "BCom\n",
      "MNC\n",
      "22/58½\n",
      "Medico\n",
      "Medico\n",
      "BCom\n",
      "MA\n",
      "JatSikh\n",
      "Send\n",
      "Mehra Rajput\n",
      "Doaba\n",
      "ALLIANCE INVITED FROM\n",
      "Saraswat Brahmin girl22/51 MA\n",
      "NRI\n",
      "attrivijesh@rediffmailcom\n",
      "Punjab University\n",
      "Army\n",
      "Defence\n",
      "MCA BE\n",
      "CharteredAccountant Punjabi Moudgil Brahmin\n",
      "Contact Col Ahluwalia\n",
      "celestial_aria@hotmailcom\n",
      "Send\n",
      "kundli Contact\n",
      "Preferred\n",
      "SEND PICTURES\n",
      "Bansal BArch\n",
      "GE\n",
      "Govt\n",
      "Kshatriya\n",
      "Punjab22½/58 MBA\n",
      "CAT Institute\n",
      "BHP\n",
      "Manglik\n",
      "kundli\n",
      "UGC NET\n",
      "MD MS\n",
      "NRI\n",
      "Medico\n",
      "ObsGynae\n",
      "Manglik nonManglik\n",
      "Garg\n",
      "Saraswat Brahmin\n",
      "25/53 MA EnglishFather\n",
      "Army\n",
      "Jalandhar144022\n",
      "Medico Engineer\n",
      "Verma\n",
      "Sikh TonkShatriya\n",
      "Senior Bank\n",
      "Match\n",
      "BA\n",
      "MA\n",
      "BDS DDS\n",
      "General Surgeon Gynaecologist\n",
      "OrthopaeditionRadiologist\n",
      "Jagadhri Distt Yamuna\n",
      "VPO\n",
      "Sony\n",
      "Sourcincing Engineering\n",
      "MNC\n",
      "Contact Col Ahluwalia Contact\n",
      "Sony\n",
      "Sourcincing Engineering\n",
      "MNC\n",
      "Contact Col Ahluwalia Contact\n",
      "Sourcincing Engineering\n",
      "MNC\n",
      "Contact Col Ahluwalia Contact\n",
      "Contact Col Ahluwalia Contact\n",
      "Contact Col Ahluwalia Contact\n",
      "Indian Forest Service\n",
      "MNC\n",
      "Army\n",
      "USMLE\n",
      "BPharma Father\n",
      "NRI\n",
      "Saraswat Brahmin\n",
      "Manglik nonManglik\n",
      "Haryana\n",
      "Gaur Brahmin\n",
      "Kurukshetra\n",
      "USAin Hospitality Management Punjabi Agarwal Singal Gotra\n",
      "Mumbai Conference Organiser\n",
      "Agarwal Hindu\n",
      "BHP\n",
      "Medical Transcriptionist Parents\n",
      "Punjabi\n",
      "Govt College\n",
      "Upper\n",
      "Manglik Hindu\n",
      "Army\n",
      "Home Science Persuing Interior Design\n",
      "26½/51preferably Advocate\n",
      "NRI\n",
      "Computer Science BEd\n",
      "UGC\n",
      "MPhil\n",
      "Central Govt\n",
      "Hons Computer\n",
      "Computer Early\n",
      "MLE\n",
      "Engineer\n",
      "Computer and Medical Transcription\n",
      "New York University\n",
      "MA Computer Software\n",
      "Panchkula Mohali\n",
      "Punjab University College Lecturer\n",
      "Reply\n",
      "Scorpion PL Fremont\n",
      "Sidhu\n",
      "Genuine\n",
      "Saraswat Brahmin\n",
      "Kundli\n",
      "Medico Engineer\n",
      "Panjabi Saraswat Brahmin\n",
      "Army\n",
      "MDS\n",
      "Lecturer Dental College\n",
      "INDUSTRILIST\n",
      "IND AREAII CHANDIGARH MOBILE\n",
      "Bathinda\n",
      "H1visa\n",
      "BTech\n",
      "JatSikh\n",
      "Science\n",
      "JatSikh\n",
      "MA\n",
      "UGC\n",
      "IRS\n",
      "IPS\n",
      "NRI\n",
      "Khatri BTech 21/161\n",
      "BDS\n",
      "MA\n",
      "Gaur Brahmin\n",
      "Gotra\n",
      "kundli biodata 270CEHOL\n",
      "Electronics Communication Engineering\n",
      "MNC\n",
      "Defence\n",
      "Army\n",
      "GMC\n",
      "NRI\n",
      "Sraharjinder@rediffmailcom\n",
      "ETT\n",
      "Bachelors\n",
      "Computer Engineering\n",
      "Defence\n",
      "GRE\n",
      "NRI\n",
      "D Microbiology\n",
      "NRI\n",
      "Manglik\n",
      "Arora MBBS\n",
      "BHP\n",
      "CC392OL\n",
      "Punjabi Brahmin\n",
      "BHP\n",
      "JatSikh\n",
      "USA Preferably USA Canadian\n",
      "GOI Mumbai\n",
      "J&K Medical\n",
      "ComputerScience\n",
      "NewJersy\n",
      "Mohali\n",
      "BA\n",
      "BTech\n",
      "MA\n",
      "PGDCA\n",
      "BCom\n",
      "NRI MNC Civil Services Jat Sikh\n",
      "Manglik\n",
      "Civil Surgeon\n",
      "PU Chd Diploma\n",
      "aSaraswat Brahmin\n",
      "Doctors\n",
      "Panjab University\n",
      "MA\n",
      "Electronics and Communication Engineering Computer\n",
      "Khatrigirl\n",
      "High Court\n",
      "BioChemistry Hons\n",
      "MA(Eng\n",
      "NRI\n",
      "56 Engineer\n",
      "MNC\n",
      "MTech\n",
      "House\n",
      "Mohali\n",
      "BTech Distinction Software Engineer\n",
      "GRE\n",
      "NRI\n",
      "Visa\n",
      "BDS\n",
      "MD MS Engineer\n",
      "NRI\n",
      "29/55½ MA Fashion Dress Designing\n",
      "GNDU\n",
      "BAMSdoctor\n",
      "Govt Early\n",
      "Bank Innocent\n",
      "Chd Mohali\n",
      "NRI\n",
      "Genuine\n",
      "BDS\n",
      "Saraswat Brahmin\n",
      "NIFD\n",
      "Computer Science\n",
      "BHP\n",
      "Panjab\n",
      "Punjabi Protestant\n",
      "GMCH Chd Government\n",
      "NRI\n",
      "Sikh Punjabi\n",
      "Send\n",
      "UGC\n",
      "Bhatia\n",
      "MA\n",
      "9519N River Bend Court\n",
      "MBBS Engineer\n",
      "India Dec\n",
      "U R\n",
      "Sector10 Contact\n",
      "USA BASED NORTH INDIAN HINDU PROFESSIONAL PARENTS SEEK ALLIANCE FROM QUALIFIED PROFESSIONALS IN USA CANADA\n",
      "VIENNAVA USA\n",
      "JatSikh\n",
      "Medico\n",
      "Medico\n",
      "MBBS\n",
      "Aggarwal Manglik\n",
      "Suitable Engineer Doctor Army\n",
      "NRI\n",
      "BDS\n",
      "Dental College\n",
      "MNC\n",
      "MBA Finance Rajput girl26/155\n",
      "MCA\n",
      "Preference\n",
      "Medico Engineer Lecturer Military Civil\n",
      "Gursikh BE Electronics Computer\n",
      "BE Electronics Telecom\n",
      "MA Eng BEd APTECH\n",
      "JatSikh\n",
      "Sandhu\n",
      "MA\n",
      "Medico MD MS\n",
      "Amritsar Send\n",
      "Sodhi\n",
      "BCom\n",
      "NRI\n",
      "MTech\n",
      "Majha\n",
      "PGDCT\n",
      "BTech Computer Science\n",
      "Sikh Tonkshatriya\n",
      "dgm_garg2002@yahoocom\n",
      "NRI\n",
      "Contact 6436FOL\n",
      "Computer Engineer\n",
      "Resort Dowry\n",
      "Honours Chemistry\n",
      "BA\n",
      "IAS\n",
      "Baptised Gynaecology\n",
      "Contact 6448FOL\n",
      "BCom\n",
      "Punjab Government\n",
      "USA Seeks\n",
      "Marwaha Visiting India\n",
      "VPO Samrai D Jalandhar Punjab\n",
      "Indian Embassy\n",
      "Indian Embassy\n",
      "Shahwala PO\n",
      "Indian Embassy\n",
      "Indian Embassy\n",
      "Contact Col Ahluwalia\n",
      "Contact Col Ahluwalia\n",
      "Medico MD MS\n",
      "MA\n",
      "Send\n",
      "BCom\n",
      "BA\n",
      "PGDCA\n",
      "Saraswat Brahmin\n",
      "MA\n",
      "MA Eng\n",
      "Arora Punjabi\n",
      "22/53 MA Economics\n",
      "BCom Fatherbusinessman\n",
      "MA\n",
      "Doad Rajput\n",
      "23/53 MAEnglish Hons\n",
      "PGDCT\n",
      "Arena Multimedia Web Designing\n",
      "Medico CA CS Engineer\n",
      "7666BNOL\n",
      "Bookkeeping Accounting Canadian\n",
      "Contact AS Post\n",
      "Sikh Ahluwalia\n",
      "Engineering Pvt College\n",
      "MSMedicine Mumbai\n",
      "Retd Army\n",
      "MS\n",
      "MA Computer\n",
      "UGC Gotras Daffu\n",
      "IAS Medico Engineer Lecturer\n",
      "UGC Net\n",
      "Punjabi Scheduled\n",
      "PCS\n",
      "JatSikh\n",
      "NRI\n",
      "Programmer\n",
      "FashionDesigning\n",
      "NIIFT Pb Govt\n",
      "MA\n",
      "UGC\n",
      "NRI\n",
      "Army\n",
      "MNC\n",
      "Singla\n",
      "Contact Canada\n",
      "Manglik\n",
      "BA\n",
      "Send\n",
      "BHP\n",
      "kundli 7899BNOL\n",
      "Ludhiana\n",
      "BEElectronics Telecomm Lecturer Engg College\n",
      "BCA\n",
      "2959CEPOL\n",
      "PGDCA\n",
      "NRIpreferred\n",
      "MNC\n",
      "USA Girl\n",
      "SC AdDharmi\n",
      "Govt Eng Mistress\n",
      "Chd\n",
      "BA Hons MA\n",
      "Amritsar\n",
      "Contact Col Ahluwalia\n",
      "BDS\n",
      "Saraswat\n",
      "Jatsikh\n",
      "Saini\n",
      "Sikh Ahluwalia\n",
      "MA\n",
      "Public School\n",
      "Chemical\n",
      "Doaba\n",
      "NRI\n",
      "Medico NonMedico\n",
      "Punjabi\n",
      "Punjabi Khatri\n",
      "NonManglik\n",
      "NRI\n",
      "MNC\n",
      "FF\n",
      "USA Send\n",
      "Bookkeeping Accounting Canadian\n",
      "Contact AS Post\n",
      "Sendbiodata\n",
      "Graduate Hindu\n",
      "Muktsar\n",
      "Commercial Bank\n",
      "Manglik Non Manglik\n",
      "Medical Transcription\n",
      "Info Co 52/25½ Father\n",
      "jobFather\n",
      "Manglik N Manglik\n",
      "Garg BE M Tech Mech\n",
      "MS\n",
      "MA\n",
      "Garhwali Rajput\n",
      "BHP\n",
      "Army\n",
      "NTT\n",
      "Send\n",
      "NEVER MARRIED USA CITIZENDAUGHTER\n",
      "MDS ELECTRONICS ENGINEERS\n",
      "Kundli\n",
      "MA\n",
      "PGDCA\n",
      "PGDCA\n",
      "PGDCA\n",
      "MA Eng\n",
      "Khatri Manglik 23/54\n",
      "Engineer College Lecturer\n",
      "USA 6790FOL\n",
      "SikhKhatri\n",
      "BDS\n",
      "Professional Rajput\n",
      "Punjab22½/58 MBA\n",
      "CAT Institute\n",
      "Army\n",
      "Medico\n",
      "BA\n",
      "Thakur Rajput\n",
      "SRF\n",
      "Lecturer Shortly\n",
      "Sandhu\n",
      "MPhil\n",
      "USA Status\n",
      "Alliance for Postgraduate 24/160\n",
      "Amritsar\n",
      "MA\n",
      "TGT underHP Govt Caste\n",
      "BDS Doctor\n",
      "MA DSend\n",
      "kundli 1150CEHOL\n",
      "kundli biodata photo\n",
      "MCom\n",
      "26/53 MA Eng BEd Computers\n",
      "Linguaden\n",
      "SCO\n",
      "Medico IAS\n",
      "MBBS MS\n",
      "nonTrimmer\n",
      "USA Canada\n",
      "Manglik\n",
      "Jatsikh\n",
      "Medico Dental\n",
      "Wanted Scientist University Lecturer Engineer\n",
      "Medico\n",
      "Science Nursing\n",
      "Mesa USA EMail\n",
      "NRI Punjabi\n",
      "Dental\n",
      "Reply\n",
      "SC Chamar\n",
      "Send\n",
      "Manglik nonManglik Punjabi\n",
      "IGNOU Preferred\n",
      "MBE\n",
      "kundli photo\n",
      "CC469OL\n",
      "Lecturer\n",
      "Rajput\n",
      "MPhil\n",
      "JRF\n",
      "IAS\n",
      "Send\n",
      "Punjabi Kshatriya Rajput\n",
      "BE MBA MS\n",
      "Qualified\n",
      "Manglik NonManglik Mahabrahmin\n",
      "kundli biodata\n",
      "MNC\n",
      "Saraswat Brahmin\n",
      "MA Eng\n",
      "2234BN OL\n",
      "Send\n",
      "Army\n",
      "NIFD\n",
      "kundli\n",
      "MA Public Administration\n",
      "Commerce Computer\n",
      "BE Elect Hons\n",
      "Stof BE\n",
      "Computer Engineer\n",
      "MCA Project\n",
      "HFWP\n",
      "Punjabi Brahmin\n",
      "Distributed Information Technology\n",
      "CM BSc HOME SCIENCE PG IN DRESS DESIGNING PRESENTLY\n",
      "Fashion Designing\n",
      "Khukhrain\n",
      "Bank\n",
      "MNC\n",
      "USA Government University\n",
      "Saraswat Brahmin\n",
      "PGDCA\n",
      "MCA\n",
      "BA\n",
      "Sikh\n",
      "Reply\n",
      "AC\n",
      "Medico\n",
      "MBA\n",
      "BCom\n",
      "Personal and Planning Management\n",
      "MNC\n",
      "Punjabi Brahmin\n",
      "MicroBio Computer\n",
      "American International Co Contact\n",
      "Engineering College\n",
      "Kurukshetra\n",
      "Orthopaedic Hospital Jalandhar\n",
      "MA English Alliance\n",
      "Defence\n",
      "Send\n",
      "SikhRamgarhia\n",
      "BCA\n",
      "PSU Reply\n",
      "IAS\n",
      "Diploma Computer Sister\n",
      "BA Hons\n",
      "MPhil\n",
      "BCom\n",
      "Bank Contact\n",
      "MComIIdid Computer\n",
      "PbHr\n",
      "MA Eng\n",
      "Fullbiodata\n",
      "Distt Karnal\n",
      "MA\n",
      "CII\n",
      "Bathinda\n",
      "Send\n",
      "MA Englishtopper\n",
      "Saraswat Brahmin Himachali\n",
      "Saraswat Brahmin\n",
      "PGDCA\n",
      "Employed Central Government Brahmin\n",
      "PGDCA\n",
      "NRI\n",
      "Contact Mrs Parbhakar\n",
      "Army\n",
      "USA Parents\n",
      "BDS\n",
      "PbGovt\n",
      "Visa\n",
      "Male Female Marketing Executive\n",
      "IAS Defence\n",
      "Tonkashtrya\n",
      "Medico\n",
      "Sikh\n",
      "Amritsar\n",
      "NRI\n",
      "Manglik\n",
      "Non Manglik\n",
      "Amritsar\n",
      "NRI\n",
      "Rajput Himachali\n",
      "Indian Army\n",
      "Himachal\n",
      "Send\n",
      "Dhillon Jat\n",
      "PGDCA MA\n",
      "NATIONAL CHAIN OF TECHNOLOGY\n",
      "Amritsar Store Customer Care Marketing Male\n",
      "AMRITSAR\n",
      "SCO Sec\n",
      "Send\n",
      "Mahajan MA MPhil Govt\n",
      "Sandhu\n",
      "25/57 MBA Bank\n",
      "Army\n",
      "BCA MBA\n",
      "BA\n",
      "MCA\n",
      "UGC\n",
      "Visa\n",
      "NTT\n",
      "Army\n",
      "Punjabi Saraswat Brahmin\n",
      "Punjab Agricultural University\n",
      "Upper\n",
      "Raman_sharma@Rediffcom\n",
      "Saraswat Brahmin\n",
      "MA\n",
      "LIC\n",
      "ALLIANCE\n",
      "USA Canada\n",
      "Health Sciences Staff Nurse\n",
      "Please\n",
      "MIT\n",
      "Gurdaspur Amritsar\n",
      "Engineer\n",
      "Engineers\n",
      "Public School\n",
      "Govt ETT\n",
      "BA Computer\n",
      "Public School\n",
      "BCom\n",
      "Manglik NonManglik Mittal\n",
      "MA Political Science\n",
      "Kumahar Parjapat\n",
      "BCom\n",
      "MBA Computer\n",
      "Information Systems Management Working\n",
      "USA Early\n",
      "Send\n",
      "DPO Send\n",
      "Saraswat Brahmin\n",
      "Saraswat Brahmin Convent Educated\n",
      "BA\n",
      "PGD\n",
      "Textile Designing Sep\n",
      "Mohali\n",
      "BCom\n",
      "BTech\n",
      "Mother MA\n",
      "Biodata\n",
      "MA\n",
      "MA Eng PU\n",
      "Abroad India\n",
      "Email johny_714@yahoocoin\n",
      "IAS Engineer\n",
      "MBA Panjab University\n",
      "Chandigah\n",
      "Khatri\n",
      "Senior Bank\n",
      "MA Nursery\n",
      "Saraswat Brahmin\n",
      "Mandi Govindgarh Business\n",
      "Computer Science\n",
      "ComputerDiploma\n",
      "MA\n",
      "Software Technology\n",
      "Belonging\n",
      "Army\n",
      "ALLIANCE\n",
      "EXTREMELY\n",
      "Saraswat Brahmin MA\n",
      "USA Canada\n",
      "Mittal\n",
      "Khatri\n",
      "Computer Engineer\n",
      "MA\n",
      "MPhil\n",
      "Doaba\n",
      "Ex Air Force\n",
      "U R\n",
      "Britishborn University\n",
      "Genuine\n",
      "Punjabi Brahmin\n",
      "BHP\n",
      "Computer Diploma Medical Asstt\n",
      "USA Parents\n",
      "MCA\n",
      "NewZealand\n",
      "MNC Applied Canada\n",
      "BTech Computer Engg 25/55\n",
      "Hons Eng\n",
      "NRI MNC Civil Service Jat Sikh\n",
      "medico nonmedico Indian NRI\n",
      "kundli decent\n",
      "Economics\n",
      "Panipat\n",
      "Army\n",
      "MA\n",
      "MBBS\n",
      "Medico\n",
      "Goyal\n",
      "Send\n",
      "Army\n",
      "Army\n",
      "Punjab University Please\n",
      "MBA\n",
      "MNC\n",
      "MNC\n",
      "Gaur Brahmin\n",
      "PGDHFW\n",
      "MPhil\n",
      "UGC\n",
      "NRI\n",
      "Contact Col Ahluwalia\n",
      "NRI MNC Civil Services Jat Sikh\n",
      "Punjabi Brahmin\n",
      "BHP\n",
      "Army\n",
      "Ayurvedic\n",
      "Chd Send\n",
      "Medico Engineer\n",
      "MS Computer Science\n",
      "Hindu Punjabi\n",
      "MA BEdArmy School\n",
      "kundli 9173FOL\n",
      "25½/53 BE MBA Working\n",
      "Librarian of Convent School\n",
      "BCA\n",
      "MCA\n",
      "Jatsikh\n",
      "26/56 MSE Computer Science\n",
      "London University Girl\n",
      "Apply\n",
      "DAV School\n",
      "CPSU\n",
      "Army\n",
      "BHP\n",
      "Mair Rajput American\n",
      "Send\n",
      "KS\n",
      "MNC\n",
      "NIIFT Pb Govt Mohali\n",
      "Business\n",
      "MA\n",
      "NRI\n",
      "IAS BTech MBA\n",
      "MNC\n",
      "AC\n",
      "USA Visa\n",
      "Medico\n",
      "Engineers\n",
      "MA II Fine Arts\n",
      "MA\n",
      "BDS\n",
      "D Computer Engineers Please\n",
      "Medico\n",
      "MA\n",
      "IAS\n",
      "Send\n",
      "Medico\n",
      "BA\n",
      "House\n",
      "Saraswat Brahmin Punjab Government\n",
      "Near\n",
      "USA BASED NORTH INDIAN HINDU PROFESSIONAL PARENTS SEEK ALLIANCEFROM QUALIFIED PROFESSIONALS IN USA CANADA\n",
      "VIENNAVA USA\n",
      "Punjabi Gaur Brahmin\n",
      "PGDCA\n",
      "Gaur Brahmin\n",
      "HomoeopathDoctor Computer\n",
      "USA Doctor Engineer\n",
      "Lakeport Court\n",
      "ALLIANCE INVITED FOR PUNJABI BHATIA CONVENT EDUCATED GIRL\n",
      "BTech Electronics\n",
      "BHP\n",
      "MBA MS Madhyanadi Punjabi\n",
      "BHP\n",
      "Sikh Ahluwalia\n",
      "Mahajan Kankal\n",
      "Computer Engineer Bachelor or Masters\n",
      "Computer Software Engineer\n",
      "Computer Science Early\n",
      "S Sandhu Portsmouth Road Manassas VA\n",
      "BCom Advance AirTicketing\n",
      "Sikh\n",
      "University Lecturer\n",
      "Defence\n",
      "Honours Panjabi\n",
      "USA CanadianNRI\n",
      "Public School Send\n",
      "MA English Convent School\n",
      "Lecturer Bank\n",
      "Army\n",
      "NRI Amritsar\n",
      "Indian Forest Service\n",
      "Sikh\n",
      "Alliance\n",
      "Khatri girl26/53 Commerce\n",
      "MA HP State\n",
      "BCom Toronto University\n",
      "USA Canada\n",
      "ALLIANCE\n",
      "Diploma Nursery Postgraduate\n",
      "DoabaKhatri\n",
      "Visa\n",
      "GPO\n",
      "MNC\n",
      "TonkKashtri\n",
      "Pvt Ltd\n",
      "HinduPunjabi\n",
      "Medico NonMedico\n",
      "MDS\n",
      "Send\n",
      "SC\n",
      "medico nonmedico professional teetotaller\n",
      "BDS\n",
      "PCS\n",
      "MNC\n",
      "BCom\n",
      "Eng MBA Defence\n",
      "MAEng Diploma Computer Software\n",
      "BCom\n",
      "nonMedico\n",
      "BHP\n",
      "PO\n",
      "KHATRI\n",
      "HinduPunjabi\n",
      "Saraswat Brahmin\n",
      "MPhil Lecturer Engineer CA\n",
      "MA Eng\n",
      "MA\n",
      "Manglik NRI\n",
      "PostGraduate Computer Science Digital Media\n",
      "Toronto University\n",
      "MBA Computer\n",
      "ComputerDip Send\n",
      "PGDCA\n",
      "Punjab Health Systems Corporation\n",
      "Punjabi SaraswatBrahman\n",
      "30/53½ M\n",
      "ALLIANCE INVITED\n",
      "POST\n",
      "Nonmedical\n",
      "Email soniasaini1975@yahoocom\n",
      "NRI\n",
      "BCom\n",
      "JatSikh 33/54\n",
      "MA\n",
      "MCA\n",
      "BCA\n",
      "NRI\n",
      "Govt Mistress\n",
      "BScMCom\n",
      "MPhil\n",
      "MD Engineer\n",
      "NRI\n",
      "MNC\n",
      "Bakunth Resorts\n",
      "Laptop Hewlett Packard\n",
      "NTT\n",
      "Model Sr Sec School\n",
      "MCA\n",
      "UGC\n",
      "BA\n",
      "PGDCA\n",
      "MA Eng\n",
      "Public School Shimla\n",
      "9519N River Bend Court\n",
      "MBA Executive\n",
      "MNC\n",
      "BE Electronics\n",
      "MA\n",
      "Delta BC\n",
      "Medico IAS\n",
      "MDS\n",
      "GRE\n",
      "MBA\n",
      "NRI\n",
      "Medico nonmedico\n",
      "CC752OL\n",
      "IAS\n",
      "CIC\n",
      "MCA\n",
      "PGT\n",
      "Cosmetology\n",
      "Mohali\n",
      "Applied for Canadian immigration Interview\n",
      "Computer Engineering\n",
      "Engineer\n",
      "Amritsar\n",
      "BE Computer\n",
      "Sahai @hotmailcom Subhash Sahai Principal BSF Sr Sec School Kadomtala Darjeeling West Bengal\n",
      "Saraswat Brahmin\n",
      "Medico\n",
      "Manglik Brahmin\n",
      "amanat11@hotmailcom\n",
      "Amritdhari Parents\n",
      "Amritdhari Professional Doctor Engineer JSM\n",
      "BS Computer Sc\n",
      "Software Engineer\n",
      "USA PO\n",
      "Hills MI USA\n",
      "Rajput Thakur\n",
      "Textile Designing Comemercial Art\n",
      "MNC\n",
      "GPO\n",
      "Ultra Modern\n",
      "MNC Indian Company\n",
      "Saraswat Brahmin Manglik\n",
      "PGDCA\n",
      "MA\n",
      "Manglik\n",
      "Saraswat Brahmin\n",
      "MNC\n",
      "NRI\n",
      "Punjabi Brahmin\n",
      "BDS\n",
      "Mittal\n",
      "NonMedical\n",
      "Dental Surgeon\n",
      "Attn Mr Harkishan\n",
      "MNC\n",
      "Govt Officers\n",
      "Army\n",
      "BDS\n",
      "Preference\n",
      "Ludhiana Dist Mobile\n",
      "Commerce\n",
      "USA Decent\n",
      "BCom India\n",
      "Pursuing Computer\n",
      "IAS\n",
      "MNC\n",
      "AC\n",
      "MDS MD MBBS BDS\n",
      "Brothers Engineer\n",
      "USA Girl\n",
      "Visa\n",
      "NRI\n",
      "Computer Science\n",
      "Wellqualified\n",
      "inig2623@yahoocom\n",
      "Send\n",
      "BA\n",
      "Preference\n",
      "Medicos Engineer Lecturer Military Civil\n",
      "MA Psy India\n",
      "Manglik Punjabi Saraswat Brahmin\n",
      "WebDesigning\n",
      "Computer Science\n",
      "Gotra Rupal Daffu Preferred\n",
      "Saraswat Punjabi Brahmin\n",
      "Govt Officer\n",
      "Send\n",
      "girl26/55 12th\n",
      "Punjabi\n",
      "NRI\n",
      "Bank Required IAS\n",
      "Software Engineers\n",
      "Medico\n",
      "BDS\n",
      "MNC\n",
      "Army\n",
      "Alcohol MBBS MD\n",
      "NY NJ\n",
      "Air Force\n",
      "Medical College Punjab\n",
      "BDS\n",
      "PGDCA Public School\n",
      "Manglik Jat Sikh\n",
      "BA\n",
      "ExSr Executive\n",
      "BCom\n",
      "Manglik\n",
      "Hindu Khatri Punjabi\n",
      "Asstt\n",
      "Chemical Engineer\n",
      "KHATRI\n",
      "Diploma Computers Fashion Designing\n",
      "Professional\n",
      "Contact Brij Lal\n",
      "NRI\n",
      "Contact Col Ahluwalia\n",
      "NRI Contact Col Ahluwalia\n",
      "MNC\n",
      "BCom French Foundation Diploma Computer NIIT Oracle 8\n",
      "Punjabi Brahmin\n",
      "Dental Surgeon\n",
      "Attn Mr Harkishan\n",
      "Australian University\n",
      "MBBS Science Engineering IT\n",
      "Food Technology Send\n",
      "PO 2042\n",
      "Medico\n",
      "BDS\n",
      "JatSikh\n",
      "USA Girl\n",
      "Saraswat Brahmin\n",
      "MPhil\n",
      "Qualified\n",
      "MA Eng\n",
      "PGDCA\n",
      "Qualified\n",
      "Sandhu\n",
      "BCom\n",
      "UGC\n",
      "BDS\n",
      "NRI\n",
      "Medico\n",
      "HomeScience Postgraduate Nutrition\n",
      "HomeScience Postgraduate Nutrition\n",
      "Central Police\n",
      "BTech\n",
      "MBA\n",
      "BArch\n",
      "Manglik\n",
      "Bank\n",
      "TGT\n",
      "Convent\n",
      "Gazetted\n",
      "Medico\n",
      "smartBCom\n",
      "BE MBA\n",
      "PGD Textile Designing\n",
      "MA\n",
      "Indore\n",
      "IAS IRS MD MS\n",
      "WebDesigning\n",
      "Mechanical Electrical Electronics Computer Engineer\n",
      "US Citizen\n",
      "Sikh Parjapat\n",
      "Derabassi Industrial Focal Point Contact\n",
      "Tel\n",
      "Bhigas of Agricultural\n",
      "Amloh Suitable\n",
      "BDS\n",
      "4256CEPOL\n",
      "Uncle\n",
      "Punjabi\n",
      "Jatsikh\n",
      "26/56 MSE Computer Science\n",
      "London University Girl\n",
      "Apply\n",
      "Post Graduate\n",
      "USA\n",
      "BA\n",
      "MCA Jalandhar\n",
      "BCom French Foundation Diploma Computer NIIT Oracle 8i Preferred\n",
      "Panjabi Brahmin\n",
      "Send\n",
      "MPhil\n",
      "MBE\n",
      "Pioneer Institution\n",
      "MTech\n",
      "NRI\n",
      "DMC Hospital Contact\n",
      "NRI\n",
      "BCom\n",
      "Caste\n",
      "BDS Lobana\n",
      "Punjabi Brahmin\n",
      "Professional\n",
      "NRI\n",
      "doingBCom\n",
      "MT Computer\n",
      "NaiSikh\n",
      "Qualified\n",
      "UGC\n",
      "JatSikh\n",
      "Working as Research Scientist\n",
      "BCom\n",
      "PGDCA\n",
      "MIT\n",
      "NRI\n",
      "Sr Brahmin\n",
      "BMS\n",
      "Telephone Mobile\n",
      "Diploma Computer\n",
      "NRI\n",
      "MNC\n",
      "Army\n",
      "MA MPhil\n",
      "Lecturer\n",
      "NRI\n",
      "USA Canada\n",
      "JatSikh\n",
      "Rajput Chauhan Kushwaha\n",
      "BCA\n",
      "MNC Presently\n",
      "PGDCA\n",
      "Proposal\n",
      "Diploma Computer Software Programmer\n",
      "Convent\n",
      "57 MA Economics\n",
      "Contact Col Ahluwalia0172660431\n",
      "NRI\n",
      "Sikh\n",
      "Sikh TonkKyshatrya\n",
      "Dhillon\n",
      "Sikh Tank Kashtriya\n",
      "MA\n",
      "NRI\n",
      "Gaur Brahmin\n",
      "BTech\n",
      "University Engineering College Send\n",
      "MA\n",
      "Medico\n",
      "GAMS\n",
      "Agarwal\n",
      "Agarwal\n",
      "MA MPhil Music Instrumental Gold\n",
      "UGC\n",
      "Lecturer\n",
      "DAV College\n",
      "PSU Mother\n",
      "NRI\n",
      "Economics Computer\n",
      "Contact Col Ahluwalia\n",
      "Contact Col Ahluwalia\n",
      "NRI\n",
      "SCO\n",
      "Contact Col Ahluwalia\n",
      "Business Administration\n",
      "California Preference to Computer Engineer Doctor Family\n",
      "Contact Sarjit Singh\n",
      "MA\n",
      "MBA\n",
      "Punjab Govt\n",
      "Medico\n",
      "MBBS\n",
      "Medico\n",
      "NRI\n",
      "Nontrimmer\n",
      "Saraswat Brahmin\n",
      "Singla\n",
      "Punjabi Saraswat Brahmin\n",
      "Compact Movie\n",
      "JVC\n",
      "Computers British Institute\n",
      "Estate Office Sector\n",
      "Contact Col Ahluwalia Also\n",
      "Nihara Sadhupur Distt Solan Road\n",
      "BA Economics\n",
      "Visa\n",
      "Send\n",
      "Himachali Rajput\n",
      "5846FOL\n",
      "MTech\n",
      "Saraswat Brahmin\n",
      "DAV\n",
      "BTech\n",
      "Electronics Communications Permanent Engg College Lecturer Patiala\n",
      "Fair\n",
      "MA Computer\n",
      "6555BNOL\n",
      "Ludhiana Send\n",
      "MSc(Foodtech\n",
      "Research Project\n",
      "2427CEPOL\n",
      "Working PSU Management\n",
      "Hyderabad Father Central\n",
      "IAS\n",
      "celestial_aria@hotmailcom\n",
      "Wanted Scientist University Lecturer Engineer\n",
      "Yadavindra Public School Passed UGCCSIR NET\n",
      "Lecturership\n",
      "Junior Research\n",
      "Defence\n",
      "Army Medical Corps Contact\n",
      "International Public Relations\n",
      "daljit@hotmailcom\n",
      "NRI\n",
      "MNC\n",
      "BDS\n",
      "Dental College\n",
      "MNC\n",
      "USA Sisterinlaw\n",
      "Honours Chemistry\n",
      "NRI\n",
      "MA\n",
      "Govt Executive Please\n",
      "MA\n",
      "ALLIANCE INVITED FROM\n",
      "NRI\n",
      "Parents USA\n",
      "USA 5984FOL\n",
      "Saraswat Brahmin\n",
      "Illinois University USA\n",
      "Contact Col Ahluwalia\n",
      "OUTRIGHT SALE PLOT\n",
      "Contact SCO\n",
      "Non Himachalies\n",
      "Contact SCO\n",
      "Maths Science\n",
      "Visa\n",
      "NTT\n",
      "Model Sr Sec School\n",
      "MCA\n",
      "UGC\n",
      "BA\n",
      "PGDCA\n",
      "MA Eng\n",
      "Public School Shimla\n",
      "9519N River Bend Court\n",
      "MBA Executive\n",
      "MNC\n",
      "BE Electronics\n",
      "MA\n",
      "Delta BC\n",
      "Medico IAS\n",
      "MDS\n",
      "GRE\n",
      "MBA\n",
      "NRI\n",
      "Medico nonmedico\n",
      "CC752OL\n",
      "IAS\n",
      "CIC\n",
      "MCA\n",
      "PGT\n",
      "Cosmetology\n",
      "Mohali\n",
      "Applied for Canadian immigration Interview\n",
      "Computer Engineering\n",
      "Engineer\n",
      "Amritsar\n",
      "BE Computer\n",
      "Sahai @hotmailcom Subhash Sahai Principal BSF Sr Sec School Kadomtala Darjeeling West Bengal\n",
      "Saraswat Brahmin\n",
      "Medico\n",
      "Manglik Brahmin\n",
      "amanat11@hotmailcom\n",
      "Amritdhari Parents\n",
      "Amritdhari Professional Doctor Engineer JSM\n",
      "BS Computer Sc\n",
      "Software Engineer\n",
      "USA PO\n",
      "Hills MI USA\n",
      "Rajput Thakur\n",
      "Textile Designing Comemercial Art\n",
      "MNC\n",
      "GPO\n",
      "Ultra Modern\n",
      "MNC Indian Company\n",
      "Punjabi Brahmin\n",
      "BHP\n",
      "JatSikh\n",
      "USA Preferably USA Canadian\n",
      "GOI Mumbai\n",
      "J&K Medical\n",
      "ComputerScience\n",
      "NewJersy\n",
      "Mohali\n",
      "BA\n",
      "BTech\n",
      "MA\n",
      "PGDCA\n",
      "BCom\n",
      "NRI MNC Civil Services Jat Sikh\n",
      "Manglik\n",
      "Civil Surgeon\n",
      "PU Chd Diploma\n",
      "aSaraswat Brahmin\n",
      "Doctors\n",
      "Panjab University\n",
      "MA\n",
      "Electronics and Communication Engineering Computer\n",
      "Khatrigirl\n",
      "High Court\n",
      "BioChemistry Hons\n",
      "MA(Eng\n",
      "NRI\n",
      "56 Engineer\n",
      "MNC\n",
      "MTech\n",
      "House\n",
      "Mohali\n",
      "BTech Distinction Software Engineer\n",
      "GRE\n",
      "NRI\n",
      "Visa\n",
      "BDS\n",
      "MD MS Engineer\n",
      "NRI\n",
      "29/55½ MA Fashion Dress Designing\n",
      "GNDU\n",
      "BAMSdoctor\n",
      "Govt Early\n",
      "Bank Innocent\n",
      "Chd Mohali\n",
      "NRI\n",
      "Genuine\n",
      "BDS\n",
      "Saraswat Brahmin\n",
      "NIFD\n",
      "Computer Science\n",
      "BHP\n",
      "Panjab\n",
      "Punjabi Protestant\n",
      "GMCH Chd Government\n",
      "NRI\n",
      "Sikh Punjabi\n",
      "Send\n",
      "UGC\n",
      "Bhatia\n",
      "MA\n",
      "9519N River Bend Court\n",
      "MBBS Engineer\n",
      "India Dec\n",
      "U R\n",
      "Sector10 Contact\n",
      "Defence\n",
      "JAT\n",
      "TonkKashtriya\n",
      "NRI\n",
      "Sikh\n",
      "MA\n",
      "Punjabi\n",
      "BDS\n",
      "Mohyal Chhibber\n",
      "Saraswat Brahmin\n",
      "Khatri\n",
      "JatSikh\n",
      "AVAILABLE ON RENT\n",
      "Infrastructure Group\n",
      "Science Nursing\n",
      "Mesa USA EMail\n",
      "NRI Punjabi\n",
      "Dental\n",
      "Reply\n",
      "SC Chamar\n",
      "Send\n",
      "Manglik nonManglik Punjabi\n",
      "IGNOU Preferred\n",
      "MBE\n",
      "kundli photo\n",
      "CC469OL\n",
      "Lecturer\n",
      "Rajput\n",
      "MPhil\n",
      "JRF\n",
      "IAS\n",
      "Send\n",
      "Punjabi Kshatriya Rajput\n",
      "BE MBA MS\n",
      "Qualified\n",
      "Manglik NonManglik Mahabrahmin\n",
      "kundli biodata\n",
      "MNC\n",
      "Saraswat Brahmin\n",
      "MA Eng\n",
      "2234BN OL\n",
      "Send\n",
      "Army\n",
      "NIFD\n",
      "kundli\n",
      "MA Public Administration\n",
      "Commerce Computer\n",
      "BE Elect Hons\n",
      "Stof BE\n",
      "Computer Engineer\n",
      "MCA Project\n",
      "HFWP\n",
      "Punjabi Brahmin\n",
      "Distributed Information Technology\n",
      "CM BSc HOME SCIENCE PG IN DRESS DESIGNING PRESENTLY\n",
      "Fashion Designing\n",
      "Khukhrain\n",
      "Bank\n",
      "MNC\n",
      "USA Government University\n",
      "Saraswat Brahmin\n",
      "PGDCA\n",
      "MCA\n",
      "BA\n",
      "Sikh\n",
      "Reply\n",
      "AC\n",
      "Amritdhari Doctor Engineer\n",
      "BS ComputerSc\n",
      "MS\n",
      "Software Engineer\n",
      "BBC\n",
      "DCA Computer\n",
      "IPS IG Police\n",
      "MNC\n",
      "Una\n",
      "BE Electronics\n",
      "BA\n",
      "Bank\n",
      "KUNDLI\n",
      "Radhaswami Parjapat Malhi\n",
      "Software Engineering\n",
      "Kashtriya Punjabi\n",
      "Computer Master Computer Management Pune University\n",
      "Delhi Send\n",
      "Bachelor of Veterinary Science\n",
      "MA Economics\n",
      "Manglik NonManglik\n",
      "Army\n",
      "MBA\n",
      "MNC\n",
      "NRI\n",
      "Medico PG PCMS\n",
      "NonMedico\n",
      "GraduationClinical Psychology\n",
      "IPS\n",
      "NRI\n",
      "Army Air Force\n",
      "PHP MySql Cold Fusion\n",
      "SCF\n",
      "Contact Col Ahluwalia\n",
      "BDS\n",
      "Garg\n",
      "Saraswat Brahmin\n",
      "Saraswat Brahmin\n",
      "Punjabi\n",
      "MDS MD MS MCH PCS\n",
      "29/5'5 MA Dress Designing Fashion Designing\n",
      "NRI\n",
      "Manglik Dhiman\n",
      "Medico\n",
      "Army\n",
      "BBA\n",
      "USA Contact\n",
      "UGC\n",
      "Manglik\n",
      "Chandel\n",
      "MA\n",
      "USA Canada\n",
      "PCS\n",
      "IAS\n",
      "Punjabi Garg\n",
      "Mahajan Manglik\n",
      "Jaswal Rajput\n",
      "Saraswat Brahmin\n",
      "Sandhu Canada\n",
      "Contact Col Ahluwalia 145 Sector\n",
      "6000 bank\n",
      "BDS\n",
      "Garg\n",
      "Saraswat Brahmin\n",
      "Saraswat Brahmin\n",
      "Punjabi\n",
      "MDS MD MS MCH PCS\n",
      "29/5'5 MA Dress Designing Fashion Designing\n",
      "NRI\n",
      "Manglik Dhiman\n",
      "Medico\n",
      "Army\n",
      "Punjabi Kshatriya Rajput\n",
      "BE MBA MS\n",
      "Reply\n",
      "MA Eng\n",
      "Army\n",
      "NRI\n",
      "BHP\n",
      "Jatsikh\n",
      "MCA\n",
      "Sarswat Brahmin Manglik Non Manglik\n",
      "MA Economics\n",
      "NRI\n",
      "Call0181273478\n",
      "Science Nursing\n",
      "Mesa USA EMail\n",
      "Ophthalmologist\n",
      "Medico\n",
      "London Hospital Mother\n",
      "Chemistry\n",
      "Public School\n",
      "Bank Manager R(VRS\n",
      "BA\n",
      "BTech\n",
      "MTech\n",
      "Dietitics\n",
      "deepchopra@hotmailcom\n",
      "MA\n",
      "Medicose Engineer Lecturer Military Civil\n",
      "PGDCA\n",
      "NRI\n",
      "D Microbiology\n",
      "Fine Arts\n",
      "Commercial Arts PGDCA\n",
      "Send\n",
      "Contact Gee Cee Network Marketing Pvt Ltd\n",
      "info@gcnetworkindiacom\n",
      "Indian Company\n",
      "Contact Col Ahluwalia\n",
      "NRI Postgraduate\n",
      "Punjabi\n",
      "NRI\n",
      "Kurukshetra\n",
      "MA\n",
      "Sikh\n",
      "PGDCA\n",
      "Medico\n",
      "BAMS\n",
      "Saraswat Brahmin\n",
      "Engineer USA Canadian\n",
      "DOCTOR ENGINEER IAS\n",
      "KUNDLI BOX TRIBUNE\n",
      "Manglik\n",
      "B H\n",
      "Post\n",
      "NRI\n",
      "Contact Col Ahluwalia 145 Sector\n",
      "Medico\n",
      "MBA\n",
      "BCom\n",
      "Personal and Planning Management\n",
      "MNC\n",
      "Punjabi Brahmin\n",
      "MicroBio Computer\n",
      "American International Co Contact\n",
      "Engineering College\n",
      "Kurukshetra\n",
      "Orthopaedic Hospital Jalandhar\n",
      "MA English Alliance\n",
      "Defence\n",
      "Send\n",
      "SikhRamgarhia\n",
      "BCA\n",
      "PSU Reply\n",
      "IAS\n",
      "Diploma Computer Sister\n",
      "BA Hons\n",
      "MPhil\n",
      "BCom\n",
      "Bank Contact\n",
      "MComIIdid Computer\n",
      "PbHr\n",
      "MA Eng\n",
      "Fullbiodata\n",
      "Distt Karnal\n",
      "MA\n",
      "CII\n",
      "Bathinda\n",
      "Send\n",
      "MA Englishtopper\n",
      "Saraswat Brahmin Himachali\n",
      "Saraswat Brahmin\n",
      "PGDCA\n",
      "Employed Central Government Brahmin\n",
      "PGDCA\n",
      "NRI\n",
      "Contact Mrs Parbhakar\n",
      "Army\n",
      "USA Parents\n",
      "BDS\n",
      "PbGovt\n",
      "Visa\n",
      "Male Female Marketing Executive\n",
      "MD Engineer\n",
      "MA Fashionand Computer Web Designing Diploma Educated\n",
      "HinduPunjabi\n",
      "girl26/5'5 12th\n",
      "Punjabi Kumhar\n",
      "Manglik Garg\n",
      "Central Govt\n",
      "25+/51/MSc Computer\n",
      "MCA\n",
      "Sarswat Punjabi Brahmin\n",
      "English Hons\n",
      "MA\n",
      "MPhil\n",
      "UGC JRF NET\n",
      "Army\n",
      "BDS Dentist\n",
      "Dentist\n",
      "USA Younger\n",
      "Thapar Engineering College\n",
      "USA Canada Please\n",
      "Medico\n",
      "JAT\n",
      "Reply\n",
      "Scropion Place Fremont\n",
      "BSc(Home Science BEd\n",
      "Army\n",
      "PROFESSIONAL\n",
      "JAT\n",
      "Medico\n",
      "Saraswat Brahmin\n",
      "USA Send\n",
      "MNC Fatherretired Army\n",
      "Send\n",
      "kundli 1317CEHOL\n",
      "NRI\n",
      "Tycoon Running\n",
      "Biodata\n",
      "NRImatch\n",
      "Chd\n",
      "Postgraduate Politicial Science PU Chd Doing Computer\n",
      "MCA\n",
      "NRI\n",
      "MBA Send\n",
      "Himachali Jaswal Rajput\n",
      "Send\n",
      "Saraswat Brahmin\n",
      "MCA\n",
      "English Medium\n",
      "HinduKhatri\n",
      "USA Canada\n",
      "Canadianimmigrant BSc Computer Science IT\n",
      "25/53 MA\n",
      "BioTech\n",
      "Jat Sikh Dental Surgeon\n",
      "Convent School\n",
      "Adharmi\n",
      "Sikh Tonkkhastry\n",
      "BAand\n",
      "NRI\n",
      "Doaba\n",
      "UGCqualified Lecturer Engineering College\n",
      "Medico\n",
      "YRS\n",
      "ESTABLISHED\n",
      "MFC UGC NET\n",
      "Urban Estate Jalandhar Ist 2nd floors 1555\n",
      "Contact julks@rediffmailcom\n",
      "Urban Estate Jalandhar Ist 2nd floors 1555\n",
      "Contact julks@rediffmailcom\n",
      "Engineer\n",
      "MIT\n",
      "Amritdhari Doctor Engineer\n",
      "BS ComputerSc\n",
      "MS\n",
      "Software Engineer\n",
      "Saraswat Brahmin\n",
      "NRI Civil Services\n",
      "MNC\n",
      "BCom\n",
      "Army\n",
      "MNC\n",
      "BCom\n",
      "Management and Public Relations\n",
      "Army\n",
      "Qualified\n",
      "PGDCA\n",
      "MCA\n",
      "Bridegroom\n",
      "PU Chd\n",
      "XEN\n",
      "Indian Army\n",
      "B H P Contact 659 Post\n",
      "SRF Parents\n",
      "USA 4276FOL\n",
      "Qualified\n",
      "Mair Rajput Verma Punjabi\n",
      "BCom\n",
      "Send\n",
      "Kharera Pacherwal Khundia\n",
      "Send\n",
      "Sr Bank\n",
      "TonkKashtriya\n",
      "MDS MD MS\n",
      "ESTABLISHED\n",
      "UNSW SYDNEY APPLIED FOR\n",
      "28/57 MA Public AdministrationStenography Panjabi Computer Operator Preference\n",
      "Sikh Ahluwalia\n",
      "WebDesigning\n",
      "BA\n",
      "BE Electronics\n",
      "UGC\n",
      "Computer Engineers\n",
      "kundli 4377FOL\n",
      "Send kundli\n",
      "Medical\n",
      "Visa\n",
      "CC858OL\n",
      "MA\n",
      "UGC\n",
      "TGT\n",
      "Army School Patiala\n",
      "Army\n",
      "MA\n",
      "PHP MySql Cold Fusion\n",
      "SCF\n",
      "Indian Forest Service\n",
      "MNC\n",
      "Army\n",
      "Medico\n",
      "MCA Send\n",
      "Central Government\n",
      "GAMSgirl\n",
      "Garg\n",
      "PGDCA\n",
      "MCA\n",
      "Medico\n",
      "Match Brahmin\n",
      "FatherIAS\n",
      "MD MS\n",
      "Punjabi Saraswat Brahmin\n",
      "MBA UGC NET\n",
      "NRI\n",
      "Medico\n",
      "nonMedico\n",
      "PCS\n",
      "2312CEPOL\n",
      "IAS IPS\n",
      "BE MBA\n",
      "Human Resource Management\n",
      "Sr Management Executive\n",
      "VRS\n",
      "Khatri\n",
      "BDS\n",
      "IAS IPS\n",
      "Send\n",
      "USA Father\n",
      "Army\n",
      "MCA\n",
      "Amritsar One\n",
      "MSS\n",
      "NRI\n",
      "BA Economics\n",
      "NRI\n",
      "MBA\n",
      "MNC Highly\n",
      "Army\n",
      "BTech\n",
      "Army\n",
      "NRI\n",
      "CollegeLecturer\n",
      "Contact Post\n",
      "Mohali\n",
      "SDO PWD\n",
      "Hindu Rajput\n",
      "Manglik Mair Rajput\n",
      "HomoeopathDoctor Computer\n",
      "USA Doctor Engineer\n",
      "Lakeport Court\n",
      "NRI Employed\n",
      "Preference\n",
      "LDH Jalandhar Patiala\n",
      "Punjabi Hindu Saini\n",
      "Qualified\n",
      "UGC\n",
      "Hindu Punjabi\n",
      "DPM\n",
      "Manglik\n",
      "ETT School Teachress\n",
      "Saraswat Brahmin\n",
      "PunjabiSarswat Brahmin\n",
      "MPhil\n",
      "Doaba\n",
      "BDS\n",
      "WebDesigning\n",
      "Webmasters Technologies\n",
      "Delhi AmritsarDelhi Highway Properties\n",
      "Ambala Contact Ashwani Developers Dal Mandi Ambala Cantt R\n",
      "Visa\n",
      "NRI\n",
      "Information Technology Status\n",
      "Punjabi Kumhar\n",
      "Contact Col Ahluwalia\n",
      "Govt College\n",
      "MA Fashionand Computer Web Designing Diploma Educated\n",
      "MA\n",
      "UGC\n",
      "NRI\n",
      "VRS\n",
      "NRI\n",
      "Engineer\n",
      "BA\n",
      "GC\n",
      "Nov 72/162 Govt\n",
      "XEN\n",
      "CA MBA Lecturer Civil or Army\n",
      "ALLIANCE INVITED FROM HIGH STATUS BUSINESS GURSIKH\n",
      "Singla\n",
      "Kurukshetrabased MA\n",
      "kundli first instance\n",
      "MA\n",
      "Postgraduate Chemistry\n",
      "Upadhayay\n",
      "NET\n",
      "Kundli\n",
      "Mohyal Saraswat Brahmin\n",
      "Match for Chhibber Army\n",
      "AirHostess\n",
      "Medico\n",
      "MS ENT\n",
      "Proposal\n",
      "Graduate Textile Designing andComputer Diploma\n",
      "BHP\n",
      "Send\n",
      "Medico nonMedico\n",
      "kah_aman@yahoocom\n",
      "PGDCA\n",
      "NRI\n",
      "Textile Designer Computer\n",
      "Saraswat Brahmin\n",
      "BTech\n",
      "Account\n",
      "Sr Defence\n",
      "Hearing Impairments\n",
      "Army School Patiala\n",
      "Himachal\n",
      "NRI Contact Col Ahluwalia\n",
      "NRI Contact Col Ahluwalia\n",
      "NRI Contact Col Ahluwalia\n",
      "HIB\n",
      "Reply\n",
      "Punjabi Kumhar\n",
      "HINDU KHATRI\n",
      "Medico NonMedico\n",
      "MDS\n",
      "Send\n",
      "BTech\n",
      "MNC\n",
      "UGC\n",
      "MCA\n",
      "MBA\n",
      "Mohyal Saraswat Brahmin\n",
      "HinduPunjabi\n",
      "ALLIANCE\n",
      "ESTABLISHED\n",
      "Oct Nov Reply\n",
      "JalandharLudhiana\n",
      "BDS\n",
      "Computer CollegePune\n",
      "Medico\n",
      "Diploma Computer Application Tele\n",
      "MD MS IIM\n",
      "IIT\n",
      "NRI\n",
      "IAS\n",
      "Electrical Mechanical Computer Engineer\n",
      "53 Staff Nurse\n",
      "Govt\n",
      "Govt\n",
      "BDS\n",
      "Visa\n",
      "CC858OL\n",
      "NRI\n",
      "PO Abu Dhabi UAE\n",
      "Sr Defence\n",
      "IIT\n",
      "Btech\n",
      "Sr Management\n",
      "MNC\n",
      "New Delhi AC Accn\n",
      "Contact Col Ahluwalia 145 Sector 36A 7570FOL\n",
      "SC\n",
      "VRS\n",
      "celestial_aria@hotmailcom\n",
      "Send\n",
      "kundli Contact\n",
      "Preferred\n",
      "SEND PICTURES\n",
      "Bansal BArch\n",
      "GE\n",
      "Govt\n",
      "Kshatriya\n",
      "Punjab22½/58 MBA\n",
      "CAT Institute\n",
      "BHP\n",
      "Manglik\n",
      "kundli\n",
      "UGC NET\n",
      "MD MS\n",
      "NRI\n",
      "Medico\n",
      "ObsGynae\n",
      "Manglik nonManglik\n",
      "Garg\n",
      "Saraswat Brahmin\n",
      "25/53 MA EnglishFather\n",
      "Army\n",
      "Jalandhar144022\n",
      "Medico Engineer\n",
      "Verma\n",
      "Sikh TonkShatriya\n",
      "Senior Bank\n",
      "Match\n",
      "BA\n",
      "MA\n",
      "BDS DDS\n",
      "General Surgeon Gynaecologist\n",
      "OrthopaeditionRadiologist\n",
      "Jagadhri Distt Yamuna\n",
      "VPO\n",
      "Sony\n",
      "Sourcincing Engineering\n",
      "MNC\n",
      "Contact Col Ahluwalia Contact\n",
      "Sony\n",
      "Sourcincing Engineering\n",
      "MNC\n",
      "Contact Col Ahluwalia Contact\n",
      "Sourcincing Engineering\n",
      "MNC\n",
      "Contact Col Ahluwalia Contact\n",
      "Contact Col Ahluwalia Contact\n",
      "Contact Col Ahluwalia Contact\n",
      "BBA\n",
      "Manglik Non\n",
      "DoctorEngineer USA Canadian\n",
      "Medico\n",
      "BA\n",
      "Medico MPharm Engineer\n",
      "Colonel\n",
      "Punjabi\n",
      "Manglik nonManglik\n",
      "Khatri Walia\n",
      "Manglik Rattan\n",
      "Learn\n",
      "Earn Network Marketing\n",
      "Medico IAS\n",
      "MBBS MS\n",
      "nonTrimmer\n",
      "USA Canada\n",
      "Manglik\n",
      "Jatsikh\n",
      "Medico Dental\n",
      "Wanted Scientist University Lecturer Engineer\n",
      "Medico\n",
      "Punjabi Kshatriya Rajput\n",
      "BE MBA MS\n",
      "Reply\n",
      "MA Eng\n",
      "Army\n",
      "NRI\n",
      "BHP\n",
      "Jatsikh\n",
      "MCA\n",
      "Sarswat Brahmin Manglik Non Manglik\n",
      "MA Economics\n",
      "NRI\n",
      "Call0181273478\n",
      "Science Nursing\n",
      "Mesa USA EMail\n",
      "Ophthalmologist\n",
      "Medico\n",
      "London Hospital Mother\n",
      "Chemistry\n",
      "Public School\n",
      "Bank Manager R(VRS\n",
      "BA\n",
      "BTech\n",
      "MTech\n",
      "Dietitics\n",
      "deepchopra@hotmailcom\n",
      "MA\n",
      "Medicose Engineer Lecturer Military Civil\n",
      "PGDCA\n",
      "NRI\n",
      "D Microbiology\n",
      "Fine Arts\n",
      "Commercial Arts PGDCA\n",
      "Send\n",
      "Contact Gee Cee Network Marketing Pvt Ltd\n",
      "info@gcnetworkindiacom\n",
      "Indian Company\n",
      "Contact Col Ahluwalia\n",
      "MA Convent\n",
      "Urban\n",
      "USA Preferably USA Canadian\n",
      "SC\n",
      "BCom\n",
      "NTT\n",
      "ExExecutive\n",
      "NRI\n",
      "Sandhu\n",
      "PSU\n",
      "Contact MS Johal ExRegistrar\n",
      "PO Abu Dhabi UAE\n",
      "MPharmacy Clinical\n",
      "Medico\n",
      "IAS\n",
      "ALLIANCE INVITED\n",
      "Diploma Fashion Designing Decent\n",
      "Diploma Dress Designing\n",
      "MA\n",
      "ComputerDiploma\n",
      "Alliance for Manglik Anand\n",
      "Preferred\n",
      "Medico\n",
      "MBBS Punjabi\n",
      "USMLE\n",
      "Amritsar\n",
      "Amritsar\n",
      "MA\n",
      "PGCTE Computer\n",
      "3882CEPOL\n",
      "Saraswat Brahmin\n",
      "BEdPGD Textile Designing\n",
      "BA Eng\n",
      "Defence\n",
      "MSComputer Engineer\n",
      "NRI\n",
      "Contact Col Ahluwalia\n",
      "International Punjabi\n",
      "Punjabi Computer Typists 2 Designers\n",
      "Send\n",
      "BCom French Foundation Diploma Computer NIIT Oracle 8\n",
      "Punjabi Brahmin\n",
      "Dental Surgeon\n",
      "Attn Mr Harkishan\n",
      "Australian University\n",
      "MBBS Science Engineering IT\n",
      "Food Technology Send\n",
      "PO 2042\n",
      "Medico\n",
      "BDS\n",
      "JatSikh\n",
      "USA Girl\n",
      "Saraswat Brahmin\n",
      "MPhil\n",
      "Qualified\n",
      "MA Eng\n",
      "PGDCA\n",
      "Qualified\n",
      "Sandhu\n",
      "BCom\n",
      "UGC\n",
      "BDS\n",
      "NRI\n",
      "Medico\n",
      "HomeScience Postgraduate Nutrition\n",
      "HomeScience Postgraduate Nutrition\n",
      "Central Police\n",
      "BTech\n",
      "MBA\n",
      "BArch\n",
      "Manglik\n",
      "Bank\n",
      "TGT\n",
      "Convent\n",
      "Gazetted\n",
      "Medico\n",
      "smartBCom\n",
      "BE MBA\n",
      "PGD Textile Designing\n",
      "MA\n",
      "Indore\n",
      "IAS IRS MD MS\n",
      "WebDesigning\n",
      "Mechanical Electrical Electronics Computer Engineer\n",
      "US Citizen\n",
      "Sikh Parjapat\n",
      "Derabassi Industrial Focal Point Contact\n",
      "Tel\n",
      "Bhigas of Agricultural\n",
      "Amloh Suitable\n",
      "Send\n",
      "Mahajan MA MPhil Govt\n",
      "Sandhu\n",
      "25/57 MBA Bank\n",
      "Army\n",
      "BCA MBA\n",
      "BA\n",
      "MCA\n",
      "UGC\n",
      "Visa\n",
      "NTT\n",
      "Army\n",
      "Punjabi Saraswat Brahmin\n",
      "Punjab Agricultural University\n",
      "Upper\n",
      "Raman_sharma@Rediffcom\n",
      "Saraswat Brahmin\n",
      "MA\n",
      "LIC\n",
      "ALLIANCE\n",
      "USA Canada\n",
      "Health Sciences Staff Nurse\n",
      "Please\n",
      "MIT\n",
      "Gurdaspur Amritsar\n",
      "Engineer\n",
      "Engineers\n",
      "Public School\n",
      "Govt ETT\n",
      "BA Computer\n",
      "Public School\n",
      "BCom\n",
      "Manglik NonManglik Mittal\n",
      "MA Political Science\n",
      "Kumahar Parjapat\n",
      "BCom\n",
      "MBA Computer\n",
      "Information Systems Management Working\n",
      "USA Early\n",
      "Send\n",
      "DPO Send\n",
      "Saraswat Brahmin\n",
      "Saraswat Brahmin Convent Educated\n",
      "BA\n",
      "PGD\n",
      "Textile Designing Sep\n",
      "Mohali\n",
      "BCom\n",
      "BTech\n",
      "Mother MA\n",
      "Biodata\n",
      "MA\n",
      "MA Eng PU\n",
      "Abroad India\n",
      "Email johny_714@yahoocoin\n",
      "IAS Engineer\n",
      "MBA Panjab University\n",
      "Chandigah\n",
      "Khatri\n",
      "Senior Bank\n",
      "MA Nursery\n",
      "MA Convent\n",
      "Urban\n",
      "USA Preferably USA Canadian\n",
      "SC\n",
      "BCom\n",
      "NTT\n",
      "ExExecutive\n",
      "NRI\n",
      "Sandhu\n",
      "PSU\n",
      "Contact MS Johal ExRegistrar\n",
      "PO Abu Dhabi UAE\n",
      "MPharmacy Clinical\n",
      "Medico\n",
      "IAS\n",
      "ALLIANCE INVITED\n",
      "Diploma Fashion Designing Decent\n",
      "Diploma Dress Designing\n",
      "MA\n",
      "ComputerDiploma\n",
      "Alliance for Manglik Anand\n",
      "Preferred\n",
      "Medico\n",
      "MBBS Punjabi\n",
      "USMLE\n",
      "Amritsar\n",
      "Amritsar\n",
      "MA\n",
      "PGCTE Computer\n",
      "3882CEPOL\n",
      "Saraswat Brahmin\n",
      "BEdPGD Textile Designing\n",
      "BA Eng\n",
      "Defence\n",
      "MSComputer Engineer\n",
      "NRI\n",
      "Contact Col Ahluwalia\n",
      "International Punjabi\n",
      "Punjabi Computer Typists 2 Designers\n",
      "Send\n",
      "BCom\n",
      "DDS Engineer\n",
      "HinduPunjabi\n",
      "BA\n",
      "PGDCA\n",
      "Red Cross\n",
      "mukeshprabhakar@hotmailcom\n",
      "Kaushik ManglikAntyanadi\n",
      "PGDCA\n",
      "Software\n",
      "MCA Parents\n",
      "BHP\n",
      "NRI\n",
      "Punjabi\n",
      "NRI\n",
      "USA Will\n",
      "Ivy League University\n",
      "Sandhu\n",
      "MPhil\n",
      "Govt High School\n",
      "MIS\n",
      "Medico\n",
      "USMLE\n",
      "Tayal Punjabi Aggarwal\n",
      "BSc(Home Science\n",
      "MBA Punjabi Khatrigirl\n",
      "NRI\n",
      "Fashion Designing\n",
      "MNC\n",
      "PGDCA\n",
      "Medico\n",
      "Doctorgirl\n",
      "Punchkula Mohali Contact House\n",
      "MA\n",
      "Dentist\n",
      "NRI\n",
      "Punjabi\n",
      "Bsbrli@aolcom 8454FOL\n",
      "Graduate Hindu\n",
      "Medico\n",
      "JatSikh\n",
      "BCom\n",
      "Govt College Army\n",
      "BDS\n",
      "DNB\n",
      "Institute Rs\n",
      "duplex house\n",
      "Ideal\n",
      "Contact Mobile\n",
      "Indian Forest Service\n",
      "MNC\n",
      "Army\n",
      "USMLE\n",
      "BPharma Father\n",
      "NRI\n",
      "Saraswat Brahmin\n",
      "Manglik nonManglik\n",
      "Haryana\n",
      "Gaur Brahmin\n",
      "Kurukshetra\n",
      "USAin Hospitality Management Punjabi Agarwal Singal Gotra\n",
      "Mumbai Conference Organiser\n",
      "Agarwal Hindu\n",
      "BHP\n",
      "Medical Transcriptionist Parents\n",
      "Punjabi\n",
      "Govt College\n",
      "Upper\n",
      "Manglik Hindu\n",
      "Army\n",
      "Home Science Persuing Interior Design\n",
      "26½/51preferably Advocate\n",
      "NRI\n",
      "Computer Science BEd\n",
      "UGC\n",
      "MPhil\n",
      "Central Govt\n",
      "Hons Computer\n",
      "Computer Early\n",
      "MLE\n",
      "Engineer\n",
      "Computer and Medical Transcription\n",
      "New York University\n",
      "MA Computer Software\n",
      "Panchkula Mohali\n",
      "Punjab University College Lecturer\n",
      "Reply\n",
      "Scorpion PL Fremont\n",
      "Sidhu\n",
      "Genuine\n",
      "NRI\n",
      "Information Technology Status\n",
      "Punjabi Kumhar\n",
      "Contact Col Ahluwalia\n",
      "Govt College\n",
      "MA Fashionand Computer Web Designing Diploma Educated\n",
      "MA\n",
      "UGC\n",
      "NRI\n",
      "VRS\n",
      "NRI\n",
      "Engineer\n",
      "BA\n",
      "GC\n",
      "Nov 72/162 Govt\n",
      "XEN\n",
      "CA MBA Lecturer Civil or Army\n",
      "ALLIANCE INVITED FROM HIGH STATUS BUSINESS GURSIKH\n",
      "Singla\n",
      "Kurukshetrabased MA\n",
      "kundli first instance\n",
      "MA\n",
      "Postgraduate Chemistry\n",
      "Upadhayay\n",
      "NET\n",
      "Kundli\n",
      "Mohyal Saraswat Brahmin\n",
      "Match for Chhibber Army\n",
      "AirHostess\n",
      "Medico\n",
      "MS ENT\n",
      "Proposal\n",
      "Graduate Textile Designing andComputer Diploma\n",
      "BHP\n",
      "Send\n",
      "Medico nonMedico\n",
      "kah_aman@yahoocom\n",
      "PGDCA\n",
      "NRI\n",
      "Textile Designer Computer\n",
      "Saraswat Brahmin\n",
      "BTech\n",
      "Account\n",
      "Sr Defence\n",
      "Hearing Impairments\n",
      "Army School Patiala\n",
      "Himachal\n",
      "NRI Contact Col Ahluwalia\n",
      "NRI Contact Col Ahluwalia\n",
      "NRI Contact Col Ahluwalia\n",
      "Doaba SikhJat Rajput Parmar\n",
      "3944CEPOL\n",
      "BCom French Foundation Diploma Computer NIIT Oracle 8i Preferred\n",
      "MCA\n",
      "Engg College\n",
      "Army EME Engrs Signal\n",
      "Mobile No 9732FOL\n",
      "BCom\n",
      "Sidhu\n",
      "Steno Canadian American England\n",
      "Amritsar143002\n",
      "Alcohol MBBS MD\n",
      "NY NJ\n",
      "MA\n",
      "Engineers\n",
      "BHP\n",
      "Medico nonMedico\n",
      "BDS\n",
      "BTech24/160 Software Engineer\n",
      "Dental\n",
      "BDS Computer\n",
      "PCS\n",
      "Send\n",
      "Girls College\n",
      "USA Citizen\n",
      "Saraswat Brahmin\n",
      "Send\n",
      "MA\n",
      "DIG BSF\n",
      "Navy\n",
      "MCA\n",
      "Sikh MadRajdoot Sawarnkar\n",
      "BA\n",
      "Amritsar\n",
      "Tourism Company\n",
      "Mittal\n",
      "MA\n",
      "UGC\n",
      "Pb Govt Service\n",
      "MSc Computer Science\n",
      "Preference\n",
      "Ludhiana Distt Mobile 20038FOLMatch\n",
      "NTT\n",
      "Saraswat Brahmin Manglik\n",
      "Manglik nonManglik\n",
      "Send BPH Contact\n",
      "Nangal\n",
      "MDS\n",
      "NRI\n",
      "BDS\n",
      "PEC Fatherbusinessman\n",
      "NM\n",
      "Govt\n",
      "Hindu Mair Rajput American\n",
      "MA\n",
      "Infosys\n",
      "MA Economics\n",
      "UGC\n",
      "MCA\n",
      "Pursuing Computer\n",
      "NRI\n",
      "Doaba\n",
      "JatSikh\n",
      "Army\n",
      "Punjab University Please\n",
      "House\n",
      "Running Hospital\n",
      "Railway Road Sultanpur\n",
      "Medico MD MS\n",
      "MA\n",
      "Send\n",
      "BCom\n",
      "BA\n",
      "PGDCA\n",
      "Saraswat Brahmin\n",
      "MA\n",
      "MA Eng\n",
      "Arora Punjabi\n",
      "22/53 MA Economics\n",
      "BCom Fatherbusinessman\n",
      "MA\n",
      "Doad Rajput\n",
      "23/53 MAEnglish Hons\n",
      "PGDCT\n",
      "Arena Multimedia Web Designing\n",
      "Medico CA CS Engineer\n",
      "7666BNOL\n",
      "Bookkeeping Accounting Canadian\n",
      "Contact AS Post\n",
      "Sikh Ahluwalia\n",
      "Engineering Pvt College\n",
      "MSMedicine Mumbai\n",
      "Retd Army\n",
      "MS\n",
      "MA Computer\n",
      "UGC Gotras Daffu\n",
      "IAS Medico Engineer Lecturer\n",
      "UGC Net\n",
      "Punjabi Scheduled\n",
      "PCS\n",
      "JatSikh\n",
      "NRI\n",
      "Programmer\n",
      "FashionDesigning\n",
      "NIIFT Pb Govt\n",
      "MA\n",
      "UGC\n",
      "NRI\n",
      "Army\n",
      "MNC\n",
      "Singla\n",
      "Contact Canada\n",
      "Manglik\n",
      "BA\n",
      "Send\n",
      "BHP\n",
      "kundli 7899BNOL\n",
      "Ludhiana\n",
      "BEElectronics Telecomm Lecturer Engg College\n",
      "BCA\n",
      "2959CEPOL\n",
      "PGDCA\n",
      "NRIpreferred\n",
      "MNC\n",
      "USA Girl\n",
      "SC AdDharmi\n",
      "Govt Eng Mistress\n",
      "Chd\n",
      "BA Hons MA\n",
      "Amritsar\n",
      "Contact Col Ahluwalia\n",
      "USA BASED NORTH INDIAN HINDU PROFESSIONAL PARENTS SEEK ALLIANCE FROM QUALIFIED PROFESSIONALS IN USA CANADA\n",
      "VIENNAVA USA\n",
      "JatSikh\n",
      "Medico\n",
      "Medico\n",
      "MBBS\n",
      "Aggarwal Manglik\n",
      "Suitable Engineer Doctor Army\n",
      "NRI\n",
      "BDS\n",
      "Dental College\n",
      "MNC\n",
      "MBA Finance Rajput girl26/155\n",
      "MCA\n",
      "Preference\n",
      "Medico Engineer Lecturer Military Civil\n",
      "Gursikh BE Electronics Computer\n",
      "BE Electronics Telecom\n",
      "MA Eng BEd APTECH\n",
      "JatSikh\n",
      "Sandhu\n",
      "MA\n",
      "Medico MD MS\n",
      "Amritsar Send\n",
      "Sodhi\n",
      "BCom\n",
      "NRI\n",
      "MTech\n",
      "Majha\n",
      "PGDCT\n",
      "BTech Computer Science\n",
      "Sikh Tonkshatriya\n",
      "dgm_garg2002@yahoocom\n",
      "NRI\n",
      "Contact 6436FOL\n",
      "Computer Engineer\n",
      "Resort Dowry\n",
      "Honours Chemistry\n",
      "BA\n",
      "IAS\n",
      "Baptised Gynaecology\n",
      "Contact 6448FOL\n",
      "BCom\n",
      "Punjab Government\n",
      "USA Seeks\n",
      "Marwaha Visiting India\n",
      "VPO Samrai D Jalandhar Punjab\n",
      "Indian Embassy\n",
      "Indian Embassy\n",
      "Shahwala PO\n",
      "Indian Embassy\n",
      "Indian Embassy\n",
      "Contact Col Ahluwalia\n",
      "Contact Col Ahluwalia\n",
      "Yadav\n",
      "MCom\n",
      "Jat Sikh USA\n",
      "NRI\n",
      "Army\n",
      "BCom\n",
      "Medico\n",
      "MD MS\n",
      "Manglik Gaur Brahmin\n",
      "Vashist Send\n",
      "kundli biodata\n",
      "Contact India9814354475\n",
      "Maid Rajput\n",
      "Thakur Rajput\n",
      "USA Match\n",
      "Business Economics Public\n",
      "Bank Executive\n",
      "Medico\n",
      "Medical College\n",
      "Health Science university\n",
      "PGDCA Computer Teacher\n",
      "Manglik\n",
      "Arora MBBS Doctor\n",
      "BHP\n",
      "SCO Sec\n",
      "BDS\n",
      "Saraswat\n",
      "Jatsikh\n",
      "Saini\n",
      "Sikh Ahluwalia\n",
      "MA\n",
      "Public School\n",
      "Chemical\n",
      "Doaba\n",
      "NRI\n",
      "Medico NonMedico\n",
      "Punjabi\n",
      "Punjabi Khatri\n",
      "NonManglik\n",
      "NRI\n",
      "MNC\n",
      "FF\n",
      "Businessman\n",
      "MDS/\n",
      "IAS Corporate\n",
      "Manglik\n",
      "Civil Defence\n",
      "JatSikh\n",
      "NRI\n",
      "Punjabi Hindu\n",
      "ALLIANCE\n",
      "CM\n",
      "MA\n",
      "MPhil Punjabi\n",
      "Medico\n",
      "BDS\n",
      "AccountsBelongs\n",
      "MA Political Science\n",
      "NRI\n",
      "Defence\n",
      "33/5'5 MA MBA\n",
      "5'5 Service\n",
      "Medico Professional\n",
      "Postgraduate College Saharanpur\n",
      "Only USA\n",
      "PGDCA\n",
      "Medico\n",
      "Hindu Punjabi\n",
      "Diploma Computer Software Programmer\n",
      "MBA\n",
      "NRI\n",
      "IAS PCS MBA Engineer\n",
      "Manglik\n",
      "Pesticides Company Please\n",
      "SCO\n",
      "NRI\n",
      "Engineer\n",
      "MIT\n",
      "Amritdhari Doctor Engineer\n",
      "BS ComputerSc\n",
      "MS\n",
      "Software Engineer\n",
      "Saraswat Brahmin\n",
      "NRI Civil Services\n",
      "MNC\n",
      "BCom\n",
      "Army\n",
      "MNC\n",
      "BCom\n",
      "Management and Public Relations\n",
      "Army\n",
      "Qualified\n",
      "PGDCA\n",
      "MCA\n",
      "Bridegroom\n",
      "PU Chd\n",
      "XEN\n",
      "Indian Army\n",
      "B H P Contact 659 Post\n",
      "SRF Parents\n",
      "USA 4276FOL\n",
      "Qualified\n",
      "Mair Rajput Verma Punjabi\n",
      "BCom\n",
      "Send\n",
      "Kharera Pacherwal Khundia\n",
      "Send\n",
      "Sr Bank\n",
      "TonkKashtriya\n",
      "MDS MD MS\n",
      "ESTABLISHED\n",
      "UNSW SYDNEY APPLIED FOR\n",
      "28/57 MA Public AdministrationStenography Panjabi Computer Operator Preference\n",
      "Sikh Ahluwalia\n",
      "WebDesigning\n",
      "BA\n",
      "BE Electronics\n",
      "UGC\n",
      "Computer Engineers\n",
      "kundli 4377FOL\n",
      "Send kundli\n",
      "Medical\n",
      "Visa\n",
      "CC858OL\n",
      "MA\n",
      "UGC\n",
      "TGT\n",
      "Army School Patiala\n",
      "Army\n",
      "MA\n",
      "PHP MySql Cold Fusion\n",
      "SCF\n",
      "NRI\n",
      "Sikh\n",
      "Sikh TonkKyshatrya\n",
      "Dhillon\n",
      "Sikh Tank Kashtriya\n",
      "MA\n",
      "NRI\n",
      "Gaur Brahmin\n",
      "BTech\n",
      "University Engineering College Send\n",
      "MA\n",
      "Medico\n",
      "GAMS\n",
      "Agarwal\n",
      "Agarwal\n",
      "MA MPhil Music Instrumental Gold\n",
      "UGC\n",
      "Lecturer\n",
      "DAV College\n",
      "PSU Mother\n",
      "NRI\n",
      "Economics Computer\n",
      "Contact Col Ahluwalia\n",
      "Contact Col Ahluwalia\n",
      "NRI\n",
      "SCO\n",
      "Contact Col Ahluwalia\n",
      "USA Canada\n",
      "BA Hons Psychology\n",
      "India June\n",
      "BE Tech MBA\n",
      "Sr Executive\n",
      "India USA Canada\n",
      "MBBS\n",
      "Army\n",
      "Canada Cleanshaven\n",
      "UGC Caste\n",
      "MA\n",
      "28/55 MA Dress Designing Fashion Designing\n",
      "GNDU NRI\n",
      "USA Status\n",
      "Army\n",
      "MA English Theater\n",
      "Saraswat Brahmin\n",
      "MPhil\n",
      "Computer C++\n",
      "BCom\n",
      "Kundli\n",
      "Contact Sharma Gramophone\n",
      "UGC\n",
      "Adhoc Lecturer\n",
      "MA\n",
      "MA\n",
      "BBA\n",
      "Canada USA\n",
      "Diploma Textile Early\n",
      "Manglik 27\n",
      "BCom Diploma Fashion Design\n",
      "Ashok Vihar Delhi\n",
      "PGDCA\n",
      "PSU Lecturer\n",
      "BDS\n",
      "H1visa\n",
      "MA\n",
      "BHP\n",
      "PGDCA\n",
      "Saraswat Brahmin\n",
      "BA\n",
      "PGD\n",
      "Textile Designing Sep\n",
      "Saraswat Brahmin\n",
      "MCom\n",
      "MPhil\n",
      "Army Navy Air Force Mechant Navy Civil\n",
      "JatSikh\n",
      "BSN\n",
      "JatSikh\n",
      "Mesa\n",
      "NRI\n",
      "SCO\n",
      "Contact Col Ahluwalia\n",
      "Choura Bazar Ludhiana\n",
      "Contact Kumaria\n",
      "USA Send\n",
      "Bookkeeping Accounting Canadian\n",
      "Contact AS Post\n",
      "Sendbiodata\n",
      "Graduate Hindu\n",
      "Muktsar\n",
      "Commercial Bank\n",
      "Manglik Non Manglik\n",
      "Medical Transcription\n",
      "Info Co 52/25½ Father\n",
      "jobFather\n",
      "Manglik N Manglik\n",
      "Garg BE M Tech Mech\n",
      "MS\n",
      "MA\n",
      "Garhwali Rajput\n",
      "BHP\n",
      "Army\n",
      "NTT\n",
      "Send\n",
      "NEVER MARRIED USA CITIZENDAUGHTER\n",
      "MDS ELECTRONICS ENGINEERS\n",
      "Kundli\n",
      "MA\n",
      "PGDCA\n",
      "PGDCA\n",
      "PGDCA\n",
      "MA Eng\n",
      "Khatri Manglik 23/54\n",
      "Engineer College Lecturer\n",
      "USA 6790FOL\n",
      "SikhKhatri\n",
      "BDS\n",
      "Professional Rajput\n",
      "Punjab22½/58 MBA\n",
      "CAT Institute\n",
      "Army\n",
      "Medico\n",
      "BA\n",
      "Thakur Rajput\n",
      "SRF\n",
      "Lecturer Shortly\n",
      "Sandhu\n",
      "MPhil\n",
      "USA Status\n",
      "Alliance for Postgraduate 24/160\n",
      "Amritsar\n",
      "MA\n",
      "TGT underHP Govt Caste\n",
      "BDS Doctor\n",
      "MA DSend\n",
      "kundli 1150CEHOL\n",
      "kundli biodata photo\n",
      "MCom\n",
      "26/53 MA Eng BEd Computers\n",
      "Linguaden\n",
      "SCO\n",
      "Himachali Rajput Central School\n",
      "PGT\n",
      "BA\n",
      "Science Nursing\n",
      "Mesa\n",
      "Ophthalmologist\n",
      "Medico\n",
      "Manglik\n",
      "London Hospital Mother\n",
      "Medico Punjabi\n",
      "BDS\n",
      "London Massi\n",
      "CC560OL\n",
      "Dixit Brahmin\n",
      "Computer Engineering\n",
      "MCA\n",
      "Saraswat Brahmin\n",
      "Steno English Punjabi Computer\n",
      "Manglik Saraswat Brahmin\n",
      "NRI\n",
      "Punjabi Hindu\n",
      "Punjabi Business\n",
      "Gursikh Parjapati MA Computer\n",
      "Punjabi Hindu\n",
      "Computers Highly\n",
      "NRI\n",
      "Singla\n",
      "Civil Services Army\n",
      "TGT HP\n",
      "BCom\n",
      "Manglik\n",
      "BHP\n",
      "Match NRI Engineer\n",
      "USA Canadian Professional\n",
      "BCom\n",
      "JatSikh\n",
      "PSU\n",
      "Sikh\n",
      "Caste\n",
      "Singla\n",
      "NRI\n",
      "Engineer CA MBA Educated Industrialist Businessman\n",
      "Abroad for Convent Educated\n",
      "Bank of Punjab Jalandhar\n",
      "Medico PG\n",
      "Alliance\n",
      "Hindu Khatri Bank\n",
      "Postgraduate in Finance\n",
      "Army\n",
      "Bachelors\n",
      "Computer Engineering\n",
      "MA\n",
      "Lecturer\n",
      "Education College\n",
      "MPhil\n",
      "USMLE\n",
      "riponch@rediffmailcom\n",
      "NonMedical\n",
      "CC586OL\n",
      "Manglik Chauhan Rajput\n",
      "MNC\n",
      "Medico\n",
      "BDS\n",
      "Army\n",
      "MNC S WE USA HIB BE Elect MBAIT\n",
      "Sydney Convent\n",
      "Parents GC\n",
      "Tele\n",
      "Dental\n",
      "Sec 28A\n",
      "Contact Col Ahluwalia\n",
      "NRI MNC Civil Services Jat Sikh\n",
      "Punjabi Brahmin\n",
      "BHP\n",
      "Army\n",
      "Ayurvedic\n",
      "Chd Send\n",
      "Medico Engineer\n",
      "MS Computer Science\n",
      "Hindu Punjabi\n",
      "MA BEdArmy School\n",
      "kundli 9173FOL\n",
      "25½/53 BE MBA Working\n",
      "Librarian of Convent School\n",
      "BCA\n",
      "MCA\n",
      "Jatsikh\n",
      "26/56 MSE Computer Science\n",
      "London University Girl\n",
      "Apply\n",
      "DAV School\n",
      "CPSU\n",
      "Army\n",
      "BHP\n",
      "Mair Rajput American\n",
      "Send\n",
      "KS\n",
      "MNC\n",
      "NIIFT Pb Govt Mohali\n",
      "Business\n",
      "MA\n",
      "NRI\n",
      "IAS BTech MBA\n",
      "MNC\n",
      "AC\n",
      "USA Visa\n",
      "Medico\n",
      "Engineers\n",
      "MA II Fine Arts\n",
      "MA\n",
      "BDS\n",
      "D Computer Engineers Please\n",
      "Medico\n",
      "MA\n",
      "IAS\n",
      "Send\n",
      "Medico\n",
      "BA\n",
      "House\n",
      "Khatri\n",
      "Engineer Bank\n",
      "Lecturer in Management Institute\n",
      "NorthWest India\n",
      "kundli first\n",
      "NRI Ahluwalia\n",
      "Amritsar\n",
      "BCom\n",
      "Hindu Tonkashatriya\n",
      "NRI\n",
      "MD MS\n",
      "Punjabi Sarswat\n",
      "Saraswat\n",
      "PGDCA\n",
      "NRI\n",
      "NRI Postgraduate\n",
      "Punjabi\n",
      "NRI\n",
      "Kurukshetra\n",
      "MA\n",
      "Sikh\n",
      "MD Engineer\n",
      "MA Fashionand Computer Web Designing Diploma Educated\n",
      "HinduPunjabi\n",
      "girl26/5'5 12th\n",
      "Punjabi Kumhar\n",
      "Manglik Garg\n",
      "Central Govt\n",
      "25+/51/MSc Computer\n",
      "MCA\n",
      "Sarswat Punjabi Brahmin\n",
      "English Hons\n",
      "MA\n",
      "MPhil\n",
      "UGC JRF NET\n",
      "Army\n",
      "BDS Dentist\n",
      "Dentist\n",
      "USA Younger\n",
      "Thapar Engineering College\n",
      "USA Canada Please\n",
      "Medico\n",
      "JAT\n",
      "Reply\n",
      "Scropion Place Fremont\n",
      "BSc(Home Science BEd\n",
      "Army\n",
      "PROFESSIONAL\n",
      "JAT\n",
      "Medico\n",
      "Saraswat Brahmin\n",
      "USA Send\n",
      "MNC Fatherretired Army\n",
      "Send\n",
      "kundli 1317CEHOL\n",
      "NRI\n",
      "Tycoon Running\n",
      "Biodata\n",
      "NRImatch\n",
      "Chd\n",
      "Postgraduate Politicial Science PU Chd Doing Computer\n",
      "MCA\n",
      "NRI\n",
      "MBA Send\n",
      "Himachali Jaswal Rajput\n",
      "Send\n",
      "Saraswat Brahmin\n",
      "MCA\n",
      "English Medium\n",
      "HinduKhatri\n",
      "USA Canada\n",
      "Canadianimmigrant BSc Computer Science IT\n",
      "25/53 MA\n",
      "BioTech\n",
      "Jat Sikh Dental Surgeon\n",
      "Convent School\n",
      "Adharmi\n",
      "Sikh Tonkkhastry\n",
      "BAand\n",
      "NRI\n",
      "Doaba\n",
      "UGCqualified Lecturer Engineering College\n",
      "Medico\n",
      "YRS\n",
      "ESTABLISHED\n",
      "MFC UGC NET\n",
      "Urban Estate Jalandhar Ist 2nd floors 1555\n",
      "Contact julks@rediffmailcom\n",
      "Urban Estate Jalandhar Ist 2nd floors 1555\n",
      "Contact julks@rediffmailcom\n",
      "HIB\n",
      "Reply\n",
      "Punjabi Kumhar\n",
      "HINDU KHATRI\n",
      "Medico NonMedico\n",
      "MDS\n",
      "Send\n",
      "BTech\n",
      "MNC\n",
      "UGC\n",
      "MCA\n",
      "MBA\n",
      "Mohyal Saraswat Brahmin\n",
      "HinduPunjabi\n",
      "ALLIANCE\n",
      "ESTABLISHED\n",
      "Oct Nov Reply\n",
      "JalandharLudhiana\n",
      "BDS\n",
      "Computer CollegePune\n",
      "Medico\n",
      "Diploma Computer Application Tele\n",
      "MD MS IIM\n",
      "IIT\n",
      "NRI\n",
      "IAS\n",
      "Electrical Mechanical Computer Engineer\n",
      "53 Staff Nurse\n",
      "Govt\n",
      "Govt\n",
      "BDS\n",
      "Visa\n",
      "CC858OL\n",
      "NRI\n",
      "PO Abu Dhabi UAE\n",
      "Sr Defence\n",
      "IIT\n",
      "Btech\n",
      "Sr Management\n",
      "MNC\n",
      "New Delhi AC Accn\n",
      "Contact Col Ahluwalia 145 Sector 36A 7570FOL\n",
      "SC\n",
      "VRS\n",
      "BE Electronics\n",
      "PGDCA\n",
      "Sikh Tonkshatriya\n",
      "University College\n",
      "BE Electronics\n",
      "Manglik nonManglik Engineer\n",
      "MD MS\n",
      "Medico nonMedico NRI\n",
      "Businessman\n",
      "SikhKhatri\n",
      "NRI Ahluwalia\n",
      "ETT\n",
      "PGDCA\n",
      "BBA\n",
      "Manglik Non\n",
      "DoctorEngineer USA Canadian\n",
      "Medico\n",
      "BA\n",
      "Medico MPharm Engineer\n",
      "Colonel\n",
      "Punjabi\n",
      "Manglik nonManglik\n",
      "Khatri Walia\n",
      "Manglik Rattan\n",
      "Learn\n",
      "Earn Network Marketing\n",
      "Punjabi\n",
      "NRI Punjabi\n",
      "MA Computer\n",
      "Khatri\n",
      "Medico Dental\n",
      "Sikh\n",
      "USA Canadian\n",
      "NRI\n",
      "SCO\n",
      "Student Referring Agents\n",
      "USA Apply\n",
      "Asia Corpmate Infotech Comtrade Corporate Centre Cambata Building\n",
      "Doaba SikhJat Rajput Parmar\n",
      "3944CEPOL\n",
      "BCom French Foundation Diploma Computer NIIT Oracle 8i Preferred\n",
      "MCA\n",
      "Engg College\n",
      "Army EME Engrs Signal\n",
      "Mobile No 9732FOL\n",
      "BCom\n",
      "Sidhu\n",
      "Steno Canadian American England\n",
      "Amritsar143002\n",
      "Alcohol MBBS MD\n",
      "NY NJ\n",
      "MA\n",
      "Engineers\n",
      "BHP\n",
      "Medico nonMedico\n",
      "BDS\n",
      "BTech24/160 Software Engineer\n",
      "Dental\n",
      "BDS Computer\n",
      "PCS\n",
      "Send\n",
      "Girls College\n",
      "USA Citizen\n",
      "Saraswat Brahmin\n",
      "Send\n",
      "MA\n",
      "DIG BSF\n",
      "Navy\n",
      "MCA\n",
      "Sikh MadRajdoot Sawarnkar\n",
      "BA\n",
      "Amritsar\n",
      "Tourism Company\n",
      "Mittal\n",
      "MA\n",
      "UGC\n",
      "Pb Govt Service\n",
      "MSc Computer Science\n",
      "Preference\n",
      "Ludhiana Distt Mobile 20038FOLMatch\n",
      "NTT\n",
      "Saraswat Brahmin Manglik\n",
      "Manglik nonManglik\n",
      "Send BPH Contact\n",
      "Nangal\n",
      "MDS\n",
      "NRI\n",
      "BDS\n",
      "PEC Fatherbusinessman\n",
      "NM\n",
      "Govt\n",
      "Hindu Mair Rajput American\n",
      "MA\n",
      "Infosys\n",
      "MA Economics\n",
      "UGC\n",
      "MCA\n",
      "Pursuing Computer\n",
      "NRI\n",
      "Doaba\n",
      "JatSikh\n",
      "Army\n",
      "Punjab University Please\n",
      "House\n",
      "Running Hospital\n",
      "Railway Road Sultanpur\n",
      "Saraswat Brahmin\n",
      "Mandi Govindgarh Business\n",
      "Computer Science\n",
      "ComputerDiploma\n",
      "MA\n",
      "Software Technology\n",
      "Belonging\n",
      "Army\n",
      "ALLIANCE\n",
      "EXTREMELY\n",
      "Saraswat Brahmin MA\n",
      "USA Canada\n",
      "Mittal\n",
      "Khatri\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Computer Engineer\n",
      "MA\n",
      "MPhil\n",
      "Doaba\n",
      "Ex Air Force\n",
      "U R\n",
      "Britishborn University\n",
      "Genuine\n",
      "Punjabi Brahmin\n",
      "BHP\n",
      "Computer Diploma Medical Asstt\n",
      "USA Parents\n",
      "MCA\n",
      "NewZealand\n",
      "MNC Applied Canada\n",
      "BTech Computer Engg 25/55\n",
      "Hons Eng\n",
      "NRI MNC Civil Service Jat Sikh\n",
      "medico nonmedico Indian NRI\n",
      "kundli decent\n",
      "Economics\n",
      "Panipat\n",
      "Army\n",
      "MA\n",
      "MBBS\n",
      "Medico\n",
      "Goyal\n",
      "Send\n",
      "Army\n",
      "Army\n",
      "Punjab University Please\n",
      "MBA\n",
      "MNC\n",
      "MNC\n",
      "Gaur Brahmin\n",
      "PGDHFW\n",
      "MPhil\n",
      "UGC\n",
      "NRI\n",
      "Contact Col Ahluwalia\n",
      "Indian Forest Service\n",
      "MNC\n",
      "Army\n",
      "Medico\n",
      "MCA Send\n",
      "Central Government\n",
      "GAMSgirl\n",
      "Garg\n",
      "PGDCA\n",
      "MCA\n",
      "Medico\n",
      "Match Brahmin\n",
      "FatherIAS\n",
      "MD MS\n",
      "Punjabi Saraswat Brahmin\n",
      "MBA UGC NET\n",
      "NRI\n",
      "Medico\n",
      "nonMedico\n",
      "PCS\n",
      "2312CEPOL\n",
      "IAS IPS\n",
      "BE MBA\n",
      "Human Resource Management\n",
      "Sr Management Executive\n",
      "VRS\n",
      "Khatri\n",
      "BDS\n",
      "IAS IPS\n",
      "Send\n",
      "USA Father\n",
      "Army\n",
      "MCA\n",
      "Amritsar One\n",
      "MSS\n",
      "NRI\n",
      "BA Economics\n",
      "NRI\n",
      "MBA\n",
      "MNC Highly\n",
      "Army\n",
      "BTech\n",
      "Army\n",
      "NRI\n",
      "CollegeLecturer\n",
      "Contact Post\n",
      "Mohali\n",
      "SDO PWD\n",
      "Hindu Rajput\n",
      "Manglik Mair Rajput\n",
      "HomoeopathDoctor Computer\n",
      "USA Doctor Engineer\n",
      "Lakeport Court\n",
      "NRI Employed\n",
      "Preference\n",
      "LDH Jalandhar Patiala\n",
      "Punjabi Hindu Saini\n",
      "Qualified\n",
      "UGC\n",
      "Hindu Punjabi\n",
      "DPM\n",
      "Manglik\n",
      "ETT School Teachress\n",
      "Saraswat Brahmin\n",
      "PunjabiSarswat Brahmin\n",
      "MPhil\n",
      "Doaba\n",
      "BDS\n",
      "WebDesigning\n",
      "Webmasters Technologies\n",
      "Delhi AmritsarDelhi Highway Properties\n",
      "Ambala Contact Ashwani Developers Dal Mandi Ambala Cantt R\n",
      "Visa\n",
      "Khatri\n",
      "Engineer Bank\n",
      "Lecturer in Management Institute\n",
      "NorthWest India\n",
      "kundli first\n",
      "NRI Ahluwalia\n",
      "Amritsar\n",
      "BCom\n",
      "Hindu Tonkashatriya\n",
      "NRI\n",
      "MD MS\n",
      "Punjabi Sarswat\n",
      "Saraswat\n",
      "PGDCA\n",
      "NRI\n",
      "BE Electronics\n",
      "PGDCA\n",
      "Sikh Tonkshatriya\n",
      "University College\n",
      "BE Electronics\n",
      "Manglik nonManglik Engineer\n",
      "MD MS\n",
      "Medico nonMedico NRI\n",
      "Businessman\n",
      "SikhKhatri\n",
      "NRI Ahluwalia\n",
      "ETT\n",
      "PGDCA\n",
      "Medico nonMedico\n",
      "USA Send\n",
      "NRI\n",
      "Information Technology Status\n",
      "Bookkeeping Accounting Canadian\n",
      "Contact AS Post\n",
      "Contact Email bpanesar2000@yahoocom 7050FOL\n",
      "Qualified\n",
      "Bhriguvanshi Brahmin\n",
      "BCom\n",
      "DTP Designer\n",
      "BHP\n",
      "MPhil\n",
      "UGC\n",
      "Lecturer\n",
      "UGC\n",
      "3137CEPOL\n",
      "PGDCA\n",
      "BA\n",
      "BCom\n",
      "Garg\n",
      "Asstt\n",
      "Indane Allotee\n",
      "Advocate Administrator\n",
      "Punjabi Kumhar\n",
      "ETT Preferred\n",
      "Post Graduate\n",
      "MA Eng\n",
      "Saraswat Brahmin\n",
      "Culture Stitching Fabric Painting\n",
      "Sarojini\n",
      "Yamuna Nagar135001\n",
      "Commerce\n",
      "ALLIANCE INVITED FROM HIGH STATUS BUSINESS GURSIKH\n",
      "Medico nonMedico\n",
      "BDS\n",
      "PCS\n",
      "BCom\n",
      "MNC\n",
      "22/58½\n",
      "Medico\n",
      "Medico\n",
      "BCom\n",
      "MA\n",
      "JatSikh\n",
      "Send\n",
      "Mehra Rajput\n",
      "Doaba\n",
      "ALLIANCE INVITED FROM\n",
      "Saraswat Brahmin girl22/51 MA\n",
      "NRI\n",
      "attrivijesh@rediffmailcom\n",
      "Punjab University\n",
      "Army\n",
      "Defence\n",
      "MCA BE\n",
      "CharteredAccountant Punjabi Moudgil Brahmin\n",
      "Contact Col Ahluwalia\n",
      "BA Economics\n",
      "Visa\n",
      "Send\n",
      "Himachali Rajput\n",
      "5846FOL\n",
      "MTech\n",
      "Saraswat Brahmin\n",
      "DAV\n",
      "BTech\n",
      "Electronics Communications Permanent Engg College Lecturer Patiala\n",
      "Fair\n",
      "MA Computer\n",
      "6555BNOL\n",
      "Ludhiana Send\n",
      "MSc(Foodtech\n",
      "Research Project\n",
      "2427CEPOL\n",
      "Working PSU Management\n",
      "Hyderabad Father Central\n",
      "IAS\n",
      "celestial_aria@hotmailcom\n",
      "Wanted Scientist University Lecturer Engineer\n",
      "Yadavindra Public School Passed UGCCSIR NET\n",
      "Lecturership\n",
      "Junior Research\n",
      "Defence\n",
      "Army Medical Corps Contact\n",
      "International Public Relations\n",
      "daljit@hotmailcom\n",
      "NRI\n",
      "MNC\n",
      "BDS\n",
      "Dental College\n",
      "MNC\n",
      "USA Sisterinlaw\n",
      "Honours Chemistry\n",
      "NRI\n",
      "MA\n",
      "Govt Executive Please\n",
      "MA\n",
      "ALLIANCE INVITED FROM\n",
      "NRI\n",
      "Parents USA\n",
      "USA 5984FOL\n",
      "Saraswat Brahmin\n",
      "Illinois University USA\n",
      "Contact Col Ahluwalia\n",
      "OUTRIGHT SALE PLOT\n",
      "Contact SCO\n",
      "Non Himachalies\n",
      "Contact SCO\n",
      "Maths Science\n",
      "Visa\n",
      "USA Canada\n",
      "BA Hons Psychology\n",
      "India June\n",
      "BE Tech MBA\n",
      "Sr Executive\n",
      "India USA Canada\n",
      "MBBS\n",
      "Army\n",
      "Canada Cleanshaven\n",
      "UGC Caste\n",
      "MA\n",
      "28/55 MA Dress Designing Fashion Designing\n",
      "GNDU NRI\n",
      "USA Status\n",
      "Army\n",
      "MA English Theater\n",
      "Saraswat Brahmin\n",
      "MPhil\n",
      "Computer C++\n",
      "BCom\n",
      "Kundli\n",
      "Contact Sharma Gramophone\n",
      "UGC\n",
      "Adhoc Lecturer\n",
      "MA\n",
      "MA\n",
      "BBA\n",
      "Canada USA\n",
      "Diploma Textile Early\n",
      "Manglik 27\n",
      "BCom Diploma Fashion Design\n",
      "Ashok Vihar Delhi\n",
      "PGDCA\n",
      "PSU Lecturer\n",
      "BDS\n",
      "H1visa\n",
      "MA\n",
      "BHP\n",
      "PGDCA\n",
      "Saraswat Brahmin\n",
      "BA\n",
      "PGD\n",
      "Textile Designing Sep\n",
      "Saraswat Brahmin\n",
      "MCom\n",
      "MPhil\n",
      "Army Navy Air Force Mechant Navy Civil\n",
      "JatSikh\n",
      "BSN\n",
      "JatSikh\n",
      "Mesa\n",
      "NRI\n",
      "SCO\n",
      "Contact Col Ahluwalia\n",
      "Choura Bazar Ludhiana\n",
      "Contact Kumaria\n",
      "UGC\n",
      "Computer Engineers\n",
      "kundli 4377FOL\n",
      "MNC\n",
      "Army\n",
      "Engineer\n",
      "Sandhu\n",
      "MPhil Employed Government High School Teachers\n",
      "BA Hons\n",
      "NRI\n",
      "BCAMCA IGNOU\n",
      "Saraswat Brahmin\n",
      "PGDCA\n",
      "MCA\n",
      "Vashisht Brahmin\n",
      "Army\n",
      "Brahmin Bhardwaj Manglik girl35/53\n",
      "Army\n",
      "MCA\n",
      "Saini\n",
      "BDS\n",
      "ECG\n",
      "Kaithal\n",
      "Haryana\n",
      "LIC\n",
      "NRI\n",
      "USMLE\n",
      "BDS\n",
      "MA\n",
      "7800/ Permanent ETT\n",
      "Medico\n",
      "MBBSManglik\n",
      "Khatri\n",
      "MPhil\n",
      "Punjabi Bhatia\n",
      "Haryana Please\n",
      "NRI\n",
      "IAS\n",
      "MNC\n",
      "NRI\n",
      "MNC Defence\n",
      "Lakeport Court Sanjose\n",
      "Punjab\n",
      "PostGraduate\n",
      "Engineer Doctor Executive\n",
      "Army\n",
      "MA Eng\n",
      "Sandhu\n",
      "Management Information Systems Belongs\n",
      "ksingh811@yahoocom\n",
      "Jatsikh\n",
      "Mohali\n",
      "MNC\n",
      "Govt Officers\n",
      "Army\n",
      "Punjabi Brahmin\n",
      "Dental Surgeon\n",
      "Attn Mr Harkishan\n",
      "BDS\n",
      "Girls College\n",
      "BCom French Foundation Diploma Computer NIIT Oracle 8\n",
      "Sikh Punjabi\n",
      "Khatri\n",
      "Pursuing\n",
      "UGC NET\n",
      "BCom\n",
      "PGDecom\n",
      "D Biotechnology in Science Father\n",
      "31/55 Lecturer Computer Science\n",
      "Business Owner\n",
      "9519 River Bend Court\n",
      "India MSComputers USA\n",
      "Visa\n",
      "Australian University\n",
      "MBBS Science Engineering IT\n",
      "Food Technology Send\n",
      "PO 2042\n",
      "Lecturer Pvt College\n",
      "ETT Final\n",
      "Lecturer\n",
      "Amritsar 27 years/160 cmsConvent\n",
      "UGC\n",
      "Write\n",
      "MA Economics BA Math BEd(Math\n",
      "NRI\n",
      "Diploma Advertising Marketing DelhiPolytechnic Executive\n",
      "HDFC Bank\n",
      "BTech MBA\n",
      "ProfQualified\n",
      "Punjabi Brahmin\n",
      "BHP\n",
      "MS MBA BE\n",
      "MA\n",
      "NRI\n",
      "Qualified\n",
      "NRI\n",
      "Jatsikh\n",
      "New York USA Presently\n",
      "Haryana\n",
      "Send\n",
      "Software\n",
      "Saini\n",
      "Write TP\n",
      "Sr Brahmin\n",
      "Professional\n",
      "College Lecturer\n",
      "Contact 4637CEPOL\n",
      "Medico NonMedico\n",
      "Central Govt\n",
      "Bhigas of Agricultural\n",
      "Amloh Suitable\n",
      "Sector11 Contact Col Ahluwalia\n",
      "IAS Defence\n",
      "Tonkashtrya\n",
      "Medico\n",
      "Sikh\n",
      "Amritsar\n",
      "NRI\n",
      "Manglik\n",
      "Non Manglik\n",
      "Amritsar\n",
      "NRI\n",
      "Rajput Himachali\n",
      "Indian Army\n",
      "Himachal\n",
      "Send\n",
      "Dhillon Jat\n",
      "PGDCA MA\n",
      "NATIONAL CHAIN OF TECHNOLOGY\n",
      "Amritsar Store Customer Care Marketing Male\n",
      "AMRITSAR\n",
      "SCO Sec\n",
      "MNC\n",
      "Govt Officers\n",
      "Army\n",
      "Punjabi Brahmin\n",
      "Dental Surgeon\n",
      "Attn Mr Harkishan\n",
      "BDS\n",
      "Girls College\n",
      "BCom French Foundation Diploma Computer NIIT Oracle 8\n",
      "Sikh Punjabi\n",
      "Khatri\n",
      "Pursuing\n",
      "UGC NET\n",
      "BCom\n",
      "PGDecom\n",
      "D Biotechnology in Science Father\n",
      "31/55 Lecturer Computer Science\n",
      "Business Owner\n",
      "9519 River Bend Court\n",
      "India MSComputers USA\n",
      "Visa\n",
      "Australian University\n",
      "MBBS Science Engineering IT\n",
      "Food Technology Send\n",
      "PO 2042\n",
      "Lecturer Pvt College\n",
      "ETT Final\n",
      "Lecturer\n",
      "Amritsar 27 years/160 cmsConvent\n",
      "UGC\n",
      "Write\n",
      "MA Economics BA Math BEd(Math\n",
      "NRI\n",
      "Diploma Advertising Marketing DelhiPolytechnic Executive\n",
      "HDFC Bank\n",
      "BTech MBA\n",
      "ProfQualified\n",
      "Punjabi Brahmin\n",
      "BHP\n",
      "MS MBA BE\n",
      "MA\n",
      "NRI\n",
      "Qualified\n",
      "NRI\n",
      "Jatsikh\n",
      "New York USA Presently\n",
      "Haryana\n",
      "Send\n",
      "Software\n",
      "Saini\n",
      "Write TP\n",
      "Sr Brahmin\n",
      "Professional\n",
      "College Lecturer\n",
      "Contact 4637CEPOL\n",
      "Medico NonMedico\n",
      "Central Govt\n",
      "Bhigas of Agricultural\n",
      "Amloh Suitable\n",
      "Sector11 Contact Col Ahluwalia\n",
      "MA\n",
      "Delta BC\n",
      "MBA Executive\n",
      "MNC\n",
      "SoberMCom\n",
      "NIIFT Pb Govt Mohali Presently\n",
      "LLB\n",
      "MNC\n",
      "55/29/\n",
      "MNC\n",
      "Sandhu\n",
      "MPhil\n",
      "inHuman Resources\n",
      "PGI\n",
      "Manglik MBA\n",
      "Convent Educated Economics\n",
      "Jalandhar Ludhiana\n",
      "BCom\n",
      "Amritsar\n",
      "Hindu Engineer\n",
      "Engineer\n",
      "Medico PG Engineer Gursikh\n",
      "Amritsar\n",
      "Hindu Rajput\n",
      "Singla SBOP\n",
      "NRI\n",
      "SciencePostgraduate\n",
      "Manglik NonManglik\n",
      "Hindu Arorasmart\n",
      "PGDCA\n",
      "BTech\n",
      "MCA\n",
      "BTech\n",
      "ESTABLISHED\n",
      "MA\n",
      "Visa\n",
      "CC858OL\n",
      "DCH Agarwal\n",
      "Saraswat Brahmin\n",
      "Kundli\n",
      "Medico Engineer\n",
      "Panjabi Saraswat Brahmin\n",
      "Army\n",
      "MDS\n",
      "Lecturer Dental College\n",
      "INDUSTRILIST\n",
      "IND AREAII CHANDIGARH MOBILE\n",
      "Bathinda\n",
      "H1visa\n",
      "BTech\n",
      "JatSikh\n",
      "Science\n",
      "JatSikh\n",
      "MA\n",
      "UGC\n",
      "IRS\n",
      "IPS\n",
      "NRI\n",
      "Khatri BTech 21/161\n",
      "BDS\n",
      "MA\n",
      "Gaur Brahmin\n",
      "Gotra\n",
      "kundli biodata 270CEHOL\n",
      "Electronics Communication Engineering\n",
      "MNC\n",
      "Defence\n",
      "Army\n",
      "GMC\n",
      "NRI\n",
      "Sraharjinder@rediffmailcom\n",
      "ETT\n",
      "Bachelors\n",
      "Computer Engineering\n",
      "Defence\n",
      "GRE\n",
      "NRI\n",
      "D Microbiology\n",
      "NRI\n",
      "Manglik\n",
      "Arora MBBS\n",
      "BHP\n",
      "CC392OL\n",
      "Punjabi\n",
      "MA\n",
      "Manglik\n",
      "MCA\n",
      "MCom\n",
      "Arora\n",
      "Medico\n",
      "Manglik Hindu\n",
      "ALLIANCE\n",
      "SUITABLE STATUS FAMILY\n",
      "Sikh\n",
      "NRI\n",
      "Manglik Punjabi Sarswat\n",
      "Tayal\n",
      "Lecturer\n",
      "NRI\n",
      "NRI\n",
      "MA\n",
      "Delta BC\n",
      "MBA Executive\n",
      "MNC\n",
      "SoberMCom\n",
      "NIIFT Pb Govt Mohali Presently\n",
      "LLB\n",
      "MNC\n",
      "55/29/\n",
      "MNC\n",
      "Sandhu\n",
      "MPhil\n",
      "inHuman Resources\n",
      "PGI\n",
      "Manglik MBA\n",
      "Convent Educated Economics\n",
      "Jalandhar Ludhiana\n",
      "BCom\n",
      "Amritsar\n",
      "Hindu Engineer\n",
      "Engineer\n",
      "Medico PG Engineer Gursikh\n",
      "Amritsar\n",
      "Hindu Rajput\n",
      "Singla SBOP\n",
      "NRI\n",
      "SciencePostgraduate\n",
      "Manglik NonManglik\n",
      "Hindu Arorasmart\n",
      "PGDCA\n",
      "BTech\n",
      "MCA\n",
      "BTech\n",
      "ESTABLISHED\n",
      "MA\n",
      "Visa\n",
      "CC858OL\n",
      "DCH Agarwal\n",
      "Yadav\n",
      "MCom\n",
      "Jat Sikh USA\n",
      "NRI\n",
      "Army\n",
      "BCom\n",
      "Medico\n",
      "MD MS\n",
      "Manglik Gaur Brahmin\n",
      "Vashist Send\n",
      "kundli biodata\n",
      "Contact India9814354475\n",
      "Maid Rajput\n",
      "Thakur Rajput\n",
      "USA Match\n",
      "Business Economics Public\n",
      "Bank Executive\n",
      "Medico\n",
      "Medical College\n",
      "Health Science university\n",
      "PGDCA Computer Teacher\n",
      "Manglik\n",
      "Arora MBBS Doctor\n",
      "BHP\n",
      "SCO Sec\n",
      "Punjabi\n",
      "MA\n",
      "Manglik\n",
      "MCA\n",
      "MCom\n",
      "Arora\n",
      "Medico\n",
      "Manglik Hindu\n",
      "ALLIANCE\n",
      "SUITABLE STATUS FAMILY\n",
      "Sikh\n",
      "NRI\n",
      "Manglik Punjabi Sarswat\n",
      "Tayal\n",
      "Lecturer\n",
      "NRI\n",
      "NRI\n",
      "BDS\n",
      "4256CEPOL\n",
      "Uncle\n",
      "Punjabi\n",
      "Jatsikh\n",
      "26/56 MSE Computer Science\n",
      "London University Girl\n",
      "Apply\n",
      "Post Graduate\n",
      "USA\n",
      "BA\n",
      "MCA Jalandhar\n",
      "BCom French Foundation Diploma Computer NIIT Oracle 8i Preferred\n",
      "Panjabi Brahmin\n",
      "Send\n",
      "MPhil\n",
      "MBE\n",
      "Pioneer Institution\n",
      "MTech\n",
      "NRI\n",
      "DMC Hospital Contact\n",
      "NRI\n",
      "BCom\n",
      "Caste\n",
      "BDS Lobana\n",
      "Punjabi Brahmin\n",
      "Professional\n",
      "NRI\n",
      "doingBCom\n",
      "MT Computer\n",
      "NaiSikh\n",
      "Qualified\n",
      "UGC\n",
      "JatSikh\n",
      "Working as Research Scientist\n",
      "BCom\n",
      "PGDCA\n",
      "MIT\n",
      "NRI\n",
      "Sr Brahmin\n",
      "BMS\n",
      "Telephone Mobile\n",
      "Diploma Computer\n",
      "NRI\n",
      "MNC\n",
      "Army\n",
      "MA MPhil\n",
      "Lecturer\n",
      "NRI\n",
      "USA Canada\n",
      "JatSikh\n",
      "Rajput Chauhan Kushwaha\n",
      "BCA\n",
      "MNC Presently\n",
      "PGDCA\n",
      "Proposal\n",
      "Diploma Computer Software Programmer\n",
      "Convent\n",
      "57 MA Economics\n",
      "Contact Col Ahluwalia0172660431\n",
      "Businessman\n",
      "MDS/\n",
      "IAS Corporate\n",
      "Manglik\n",
      "Civil Defence\n",
      "JatSikh\n",
      "NRI\n",
      "Punjabi Hindu\n",
      "ALLIANCE\n",
      "CM\n",
      "MA\n",
      "MPhil Punjabi\n",
      "Medico\n",
      "BDS\n",
      "AccountsBelongs\n",
      "MA Political Science\n",
      "NRI\n",
      "Defence\n",
      "33/5'5 MA MBA\n",
      "5'5 Service\n",
      "Medico Professional\n",
      "Postgraduate College Saharanpur\n",
      "Only USA\n",
      "PGDCA\n",
      "Medico\n",
      "Hindu Punjabi\n",
      "Diploma Computer Software Programmer\n",
      "MBA\n",
      "NRI\n",
      "IAS PCS MBA Engineer\n",
      "Manglik\n",
      "Pesticides Company Please\n",
      "SCO\n",
      "NRI\n",
      "Defence\n",
      "JAT\n",
      "TonkKashtriya\n",
      "NRI\n",
      "Sikh\n",
      "MA\n",
      "Punjabi\n",
      "BDS\n",
      "Mohyal Chhibber\n",
      "Saraswat Brahmin\n",
      "Khatri\n",
      "JatSikh\n",
      "AVAILABLE ON RENT\n",
      "Infrastructure Group\n",
      "Saraswat\n",
      "NRI\n",
      "Saraswat\n",
      "Army\n",
      "Sikh\n",
      "MairRajput\n",
      "NRI\n",
      "BDS\n",
      "Himachali\n",
      "Marwari Agarwal Commercial\n",
      "Saraswat Brahmin\n",
      "Punjabi Gaur Barahmin Vasishat\n",
      "MLM School Yamunanagar\n",
      "AirHostess\n",
      "Nihara Sadhupul\n",
      "Bhartiya MahavirDal EyeHospital\n",
      "Mansa Punjab Contact House\n",
      "NRI\n",
      "SCO\n",
      "Punjabi\n",
      "NRI Punjabi\n",
      "MA Computer\n",
      "Khatri\n",
      "Medico Dental\n",
      "Sikh\n",
      "USA Canadian\n",
      "NRI\n",
      "SCO\n",
      "Student Referring Agents\n",
      "USA Apply\n",
      "Asia Corpmate Infotech Comtrade Corporate Centre Cambata Building\n",
      "Amritdhari Doctor Engineer\n",
      "BS ComputerSc\n",
      "MS\n",
      "Software Engineer\n",
      "BBC\n",
      "DCA Computer\n",
      "IPS IG Police\n",
      "MNC\n",
      "Una\n",
      "BE Electronics\n",
      "BA\n",
      "Bank\n",
      "KUNDLI\n",
      "Radhaswami Parjapat Malhi\n",
      "Software Engineering\n",
      "Kashtriya Punjabi\n",
      "Computer Master Computer Management Pune University\n",
      "Delhi Send\n",
      "Bachelor of Veterinary Science\n",
      "MA Economics\n",
      "Manglik NonManglik\n",
      "Army\n",
      "MBA\n",
      "MNC\n",
      "NRI\n",
      "Medico PG PCMS\n",
      "NonMedico\n",
      "GraduationClinical Psychology\n",
      "IPS\n",
      "NRI\n",
      "Army Air Force\n",
      "PHP MySql Cold Fusion\n",
      "SCF\n",
      "Contact Col Ahluwalia\n",
      "Saraswat\n",
      "NRI\n",
      "Saraswat\n",
      "Army\n",
      "Sikh\n",
      "MairRajput\n",
      "NRI\n",
      "BDS\n",
      "Himachali\n",
      "Marwari Agarwal Commercial\n",
      "Saraswat Brahmin\n",
      "Punjabi Gaur Barahmin Vasishat\n",
      "MLM School Yamunanagar\n",
      "AirHostess\n",
      "Nihara Sadhupul\n",
      "Bhartiya MahavirDal EyeHospital\n",
      "Mansa Punjab Contact House\n",
      "NRI\n",
      "SCO\n",
      "PGDCA\n",
      "Medico\n",
      "BAMS\n",
      "Saraswat Brahmin\n",
      "Engineer USA Canadian\n",
      "DOCTOR ENGINEER IAS\n",
      "KUNDLI BOX TRIBUNE\n",
      "Manglik\n",
      "B H\n",
      "Post\n",
      "NRI\n",
      "Contact Col Ahluwalia 145 Sector\n",
      "Business Administration\n",
      "California Preference to Computer Engineer Doctor Family\n",
      "Contact Sarjit Singh\n",
      "MA\n",
      "MBA\n",
      "Punjab Govt\n",
      "Medico\n",
      "MBBS\n",
      "Medico\n",
      "NRI\n",
      "Nontrimmer\n",
      "Saraswat Brahmin\n",
      "Singla\n",
      "Punjabi Saraswat Brahmin\n",
      "Compact Movie\n",
      "JVC\n",
      "Computers British Institute\n",
      "Estate Office Sector\n",
      "Contact Col Ahluwalia Also\n",
      "Nihara Sadhupur Distt Solan Road\n",
      "BBA\n",
      "USA Contact\n",
      "UGC\n",
      "Manglik\n",
      "Chandel\n",
      "MA\n",
      "USA Canada\n",
      "PCS\n",
      "IAS\n",
      "Punjabi Garg\n",
      "Mahajan Manglik\n",
      "Jaswal Rajput\n",
      "Saraswat Brahmin\n",
      "Sandhu Canada\n",
      "Contact Col Ahluwalia 145 Sector\n",
      "6000 bank\n",
      "TonkKashtri\n",
      "Pvt Ltd\n",
      "HinduPunjabi\n",
      "Medico NonMedico\n",
      "MDS\n",
      "Send\n",
      "SC\n",
      "medico nonmedico professional teetotaller\n",
      "BDS\n",
      "PCS\n",
      "MNC\n",
      "BCom\n",
      "Eng MBA Defence\n",
      "MAEng Diploma Computer Software\n",
      "BCom\n",
      "nonMedico\n",
      "BHP\n",
      "PO\n",
      "KHATRI\n",
      "HinduPunjabi\n",
      "Saraswat Brahmin\n",
      "MPhil Lecturer Engineer CA\n",
      "MA Eng\n",
      "MA\n",
      "Manglik NRI\n",
      "PostGraduate Computer Science Digital Media\n",
      "Toronto University\n",
      "MBA Computer\n",
      "ComputerDip Send\n",
      "PGDCA\n",
      "Punjab Health Systems Corporation\n",
      "Punjabi SaraswatBrahman\n",
      "30/53½ M\n",
      "ALLIANCE INVITED\n",
      "POST\n",
      "Nonmedical\n",
      "Email soniasaini1975@yahoocom\n",
      "NRI\n",
      "BCom\n",
      "JatSikh 33/54\n",
      "MA\n",
      "MCA\n",
      "BCA\n",
      "NRI\n",
      "Govt Mistress\n",
      "BScMCom\n",
      "MPhil\n",
      "MD Engineer\n",
      "NRI\n",
      "MNC\n",
      "Bakunth Resorts\n",
      "Laptop Hewlett Packard\n",
      "Saraswat Brahmin Punjab Government\n",
      "Near\n",
      "USA BASED NORTH INDIAN HINDU PROFESSIONAL PARENTS SEEK ALLIANCEFROM QUALIFIED PROFESSIONALS IN USA CANADA\n",
      "VIENNAVA USA\n",
      "Punjabi Gaur Brahmin\n",
      "PGDCA\n",
      "Gaur Brahmin\n",
      "HomoeopathDoctor Computer\n",
      "USA Doctor Engineer\n",
      "Lakeport Court\n",
      "ALLIANCE INVITED FOR PUNJABI BHATIA CONVENT EDUCATED GIRL\n",
      "BTech Electronics\n",
      "BHP\n",
      "MBA MS Madhyanadi Punjabi\n",
      "BHP\n",
      "Sikh Ahluwalia\n",
      "Mahajan Kankal\n",
      "Computer Engineer Bachelor or Masters\n",
      "Computer Software Engineer\n",
      "Computer Science Early\n",
      "S Sandhu Portsmouth Road Manassas VA\n",
      "BCom Advance AirTicketing\n",
      "Sikh\n",
      "University Lecturer\n",
      "Defence\n",
      "Honours Panjabi\n",
      "USA CanadianNRI\n",
      "Public School Send\n",
      "MA English Convent School\n",
      "Lecturer Bank\n",
      "Army\n",
      "NRI Amritsar\n",
      "Indian Forest Service\n",
      "Sikh\n",
      "Alliance\n",
      "Khatri girl26/53 Commerce\n",
      "MA HP State\n",
      "BCom Toronto University\n",
      "USA Canada\n",
      "ALLIANCE\n",
      "Diploma Nursery Postgraduate\n",
      "DoabaKhatri\n",
      "Visa\n",
      "GPO\n",
      "MNC\n",
      "UGC\n",
      "Computer Engineers\n",
      "kundli 4377FOL\n",
      "MNC\n",
      "Army\n",
      "Engineer\n",
      "Sandhu\n",
      "MPhil Employed Government High School Teachers\n",
      "BA Hons\n",
      "NRI\n",
      "BCAMCA IGNOU\n",
      "Saraswat Brahmin\n",
      "PGDCA\n",
      "MCA\n",
      "Vashisht Brahmin\n",
      "Army\n",
      "Brahmin Bhardwaj Manglik girl35/53\n",
      "Army\n",
      "MCA\n",
      "Saini\n",
      "BDS\n",
      "ECG\n",
      "Kaithal\n",
      "Haryana\n",
      "LIC\n",
      "NRI\n",
      "USMLE\n",
      "BDS\n",
      "MA\n",
      "7800/ Permanent ETT\n",
      "Medico\n",
      "MBBSManglik\n",
      "Khatri\n",
      "MPhil\n",
      "Punjabi Bhatia\n",
      "Haryana Please\n",
      "NRI\n",
      "IAS\n",
      "MNC\n",
      "NRI\n",
      "MNC Defence\n",
      "Lakeport Court Sanjose\n",
      "Punjab\n",
      "PostGraduate\n",
      "Engineer Doctor Executive\n",
      "Army\n",
      "MA Eng\n",
      "Sandhu\n",
      "Management Information Systems Belongs\n",
      "ksingh811@yahoocom\n",
      "Jatsikh\n",
      "Mohali\n"
     ]
    }
   ],
   "source": [
    "OrgCounts = {}\n",
    "for entry in brides_df['classified_sents']:\n",
    "    for sentence in entry:\n",
    "        for ent, kind in sentence:\n",
    "            if kind == 'ORG':\n",
    "                print(ent)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e0373f89",
   "metadata": {},
   "source": [
    "## <font color=\"red\">*Exercise 6*</font>\n",
    "\n",
    "<font color=\"red\">In the cells immediately following, parse a (modest) subset of your corpus of interest. How deep are the phrase structure and dependency parse trees nested? How does parse depth relate to perceived sentence complexity? What are five things you can extract from these parses for subsequent analysis? (e.g., nouns collocated in a noun phrase; adjectives that modify a noun; etc.) Capture these sets of things for a focal set of words (e.g., \"Bush\", \"Obama\", \"Trump\"). What do they reveal about the roles that these entities are perceive to play in the social world inscribed by your texts?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 214,
   "id": "03ca4cd5",
   "metadata": {},
   "outputs": [],
   "source": [
    "from spacy import displacy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 215,
   "id": "122d1405",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Looking for professionally settled Tonk Khatria boy in Canada or US for Dental Surgeon girl in India For further infoplz call in Punjab at or in Canada at Attn\n",
      "Looking ROOT Looking VERB [for, For]\n",
      "for prep Looking VERB [boy]\n",
      "professionally advmod settled VERB []\n",
      "settled amod boy NOUN [professionally]\n",
      "Tonk compound boy NOUN []\n",
      "Khatria compound boy NOUN []\n",
      "boy pobj for ADP [settled, Tonk, Khatria, in, for]\n",
      "in prep boy NOUN [Canada]\n",
      "Canada pobj in ADP [or, US]\n",
      "or cc Canada PROPN []\n",
      "US conj Canada PROPN []\n",
      "for prep boy NOUN [girl]\n",
      "Dental compound Surgeon PROPN []\n",
      "Surgeon compound girl NOUN [Dental]\n",
      "girl pobj for ADP [Surgeon, in]\n",
      "in prep girl NOUN [India]\n",
      "India pobj in ADP []\n",
      "For prep Looking VERB [call]\n",
      "further amod call NOUN []\n",
      "infoplz amod call NOUN []\n",
      "call pobj For ADP [further, infoplz, in, at, at]\n",
      "in prep call NOUN [Punjab]\n",
      "Punjab pobj in ADP []\n",
      "at prep call NOUN [or, in]\n",
      "or cc at ADP []\n",
      "in conj at ADP [Canada]\n",
      "Canada pobj in ADP []\n",
      "at prep call NOUN [Attn]\n",
      "Attn pobj at ADP []\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<span class=\"tex2jax_ignore\"><svg xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\" xml:lang=\"en\" id=\"b9ec605fae7c4c188fdfbd3ce5b11f89-0\" class=\"displacy\" width=\"3530\" height=\"497.0\" direction=\"ltr\" style=\"max-width: none; height: 497.0px; color: #000000; background: #ffffff; font-family: Arial; direction: ltr\">\n",
       "<text class=\"displacy-token\" fill=\"currentColor\" text-anchor=\"middle\" y=\"407.0\">\n",
       "    <tspan class=\"displacy-word\" fill=\"currentColor\" x=\"50\">Looking</tspan>\n",
       "    <tspan class=\"displacy-tag\" dy=\"2em\" fill=\"currentColor\" x=\"50\">VERB</tspan>\n",
       "</text>\n",
       "\n",
       "<text class=\"displacy-token\" fill=\"currentColor\" text-anchor=\"middle\" y=\"407.0\">\n",
       "    <tspan class=\"displacy-word\" fill=\"currentColor\" x=\"170\">for</tspan>\n",
       "    <tspan class=\"displacy-tag\" dy=\"2em\" fill=\"currentColor\" x=\"170\">ADP</tspan>\n",
       "</text>\n",
       "\n",
       "<text class=\"displacy-token\" fill=\"currentColor\" text-anchor=\"middle\" y=\"407.0\">\n",
       "    <tspan class=\"displacy-word\" fill=\"currentColor\" x=\"290\">professionally</tspan>\n",
       "    <tspan class=\"displacy-tag\" dy=\"2em\" fill=\"currentColor\" x=\"290\">ADV</tspan>\n",
       "</text>\n",
       "\n",
       "<text class=\"displacy-token\" fill=\"currentColor\" text-anchor=\"middle\" y=\"407.0\">\n",
       "    <tspan class=\"displacy-word\" fill=\"currentColor\" x=\"410\">settled</tspan>\n",
       "    <tspan class=\"displacy-tag\" dy=\"2em\" fill=\"currentColor\" x=\"410\">VERB</tspan>\n",
       "</text>\n",
       "\n",
       "<text class=\"displacy-token\" fill=\"currentColor\" text-anchor=\"middle\" y=\"407.0\">\n",
       "    <tspan class=\"displacy-word\" fill=\"currentColor\" x=\"530\">Tonk</tspan>\n",
       "    <tspan class=\"displacy-tag\" dy=\"2em\" fill=\"currentColor\" x=\"530\">PROPN</tspan>\n",
       "</text>\n",
       "\n",
       "<text class=\"displacy-token\" fill=\"currentColor\" text-anchor=\"middle\" y=\"407.0\">\n",
       "    <tspan class=\"displacy-word\" fill=\"currentColor\" x=\"650\">Khatria</tspan>\n",
       "    <tspan class=\"displacy-tag\" dy=\"2em\" fill=\"currentColor\" x=\"650\">PROPN</tspan>\n",
       "</text>\n",
       "\n",
       "<text class=\"displacy-token\" fill=\"currentColor\" text-anchor=\"middle\" y=\"407.0\">\n",
       "    <tspan class=\"displacy-word\" fill=\"currentColor\" x=\"770\">boy</tspan>\n",
       "    <tspan class=\"displacy-tag\" dy=\"2em\" fill=\"currentColor\" x=\"770\">NOUN</tspan>\n",
       "</text>\n",
       "\n",
       "<text class=\"displacy-token\" fill=\"currentColor\" text-anchor=\"middle\" y=\"407.0\">\n",
       "    <tspan class=\"displacy-word\" fill=\"currentColor\" x=\"890\">in</tspan>\n",
       "    <tspan class=\"displacy-tag\" dy=\"2em\" fill=\"currentColor\" x=\"890\">ADP</tspan>\n",
       "</text>\n",
       "\n",
       "<text class=\"displacy-token\" fill=\"currentColor\" text-anchor=\"middle\" y=\"407.0\">\n",
       "    <tspan class=\"displacy-word\" fill=\"currentColor\" x=\"1010\">Canada</tspan>\n",
       "    <tspan class=\"displacy-tag\" dy=\"2em\" fill=\"currentColor\" x=\"1010\">PROPN</tspan>\n",
       "</text>\n",
       "\n",
       "<text class=\"displacy-token\" fill=\"currentColor\" text-anchor=\"middle\" y=\"407.0\">\n",
       "    <tspan class=\"displacy-word\" fill=\"currentColor\" x=\"1130\">or</tspan>\n",
       "    <tspan class=\"displacy-tag\" dy=\"2em\" fill=\"currentColor\" x=\"1130\">CCONJ</tspan>\n",
       "</text>\n",
       "\n",
       "<text class=\"displacy-token\" fill=\"currentColor\" text-anchor=\"middle\" y=\"407.0\">\n",
       "    <tspan class=\"displacy-word\" fill=\"currentColor\" x=\"1250\">US</tspan>\n",
       "    <tspan class=\"displacy-tag\" dy=\"2em\" fill=\"currentColor\" x=\"1250\">PROPN</tspan>\n",
       "</text>\n",
       "\n",
       "<text class=\"displacy-token\" fill=\"currentColor\" text-anchor=\"middle\" y=\"407.0\">\n",
       "    <tspan class=\"displacy-word\" fill=\"currentColor\" x=\"1370\">for</tspan>\n",
       "    <tspan class=\"displacy-tag\" dy=\"2em\" fill=\"currentColor\" x=\"1370\">ADP</tspan>\n",
       "</text>\n",
       "\n",
       "<text class=\"displacy-token\" fill=\"currentColor\" text-anchor=\"middle\" y=\"407.0\">\n",
       "    <tspan class=\"displacy-word\" fill=\"currentColor\" x=\"1490\">Dental</tspan>\n",
       "    <tspan class=\"displacy-tag\" dy=\"2em\" fill=\"currentColor\" x=\"1490\">PROPN</tspan>\n",
       "</text>\n",
       "\n",
       "<text class=\"displacy-token\" fill=\"currentColor\" text-anchor=\"middle\" y=\"407.0\">\n",
       "    <tspan class=\"displacy-word\" fill=\"currentColor\" x=\"1610\">Surgeon</tspan>\n",
       "    <tspan class=\"displacy-tag\" dy=\"2em\" fill=\"currentColor\" x=\"1610\">PROPN</tspan>\n",
       "</text>\n",
       "\n",
       "<text class=\"displacy-token\" fill=\"currentColor\" text-anchor=\"middle\" y=\"407.0\">\n",
       "    <tspan class=\"displacy-word\" fill=\"currentColor\" x=\"1730\">girl</tspan>\n",
       "    <tspan class=\"displacy-tag\" dy=\"2em\" fill=\"currentColor\" x=\"1730\">NOUN</tspan>\n",
       "</text>\n",
       "\n",
       "<text class=\"displacy-token\" fill=\"currentColor\" text-anchor=\"middle\" y=\"407.0\">\n",
       "    <tspan class=\"displacy-word\" fill=\"currentColor\" x=\"1850\">in</tspan>\n",
       "    <tspan class=\"displacy-tag\" dy=\"2em\" fill=\"currentColor\" x=\"1850\">ADP</tspan>\n",
       "</text>\n",
       "\n",
       "<text class=\"displacy-token\" fill=\"currentColor\" text-anchor=\"middle\" y=\"407.0\">\n",
       "    <tspan class=\"displacy-word\" fill=\"currentColor\" x=\"1970\">India</tspan>\n",
       "    <tspan class=\"displacy-tag\" dy=\"2em\" fill=\"currentColor\" x=\"1970\">PROPN</tspan>\n",
       "</text>\n",
       "\n",
       "<text class=\"displacy-token\" fill=\"currentColor\" text-anchor=\"middle\" y=\"407.0\">\n",
       "    <tspan class=\"displacy-word\" fill=\"currentColor\" x=\"2090\">For</tspan>\n",
       "    <tspan class=\"displacy-tag\" dy=\"2em\" fill=\"currentColor\" x=\"2090\">ADP</tspan>\n",
       "</text>\n",
       "\n",
       "<text class=\"displacy-token\" fill=\"currentColor\" text-anchor=\"middle\" y=\"407.0\">\n",
       "    <tspan class=\"displacy-word\" fill=\"currentColor\" x=\"2210\">further</tspan>\n",
       "    <tspan class=\"displacy-tag\" dy=\"2em\" fill=\"currentColor\" x=\"2210\">ADJ</tspan>\n",
       "</text>\n",
       "\n",
       "<text class=\"displacy-token\" fill=\"currentColor\" text-anchor=\"middle\" y=\"407.0\">\n",
       "    <tspan class=\"displacy-word\" fill=\"currentColor\" x=\"2330\">infoplz</tspan>\n",
       "    <tspan class=\"displacy-tag\" dy=\"2em\" fill=\"currentColor\" x=\"2330\">ADJ</tspan>\n",
       "</text>\n",
       "\n",
       "<text class=\"displacy-token\" fill=\"currentColor\" text-anchor=\"middle\" y=\"407.0\">\n",
       "    <tspan class=\"displacy-word\" fill=\"currentColor\" x=\"2450\">call</tspan>\n",
       "    <tspan class=\"displacy-tag\" dy=\"2em\" fill=\"currentColor\" x=\"2450\">NOUN</tspan>\n",
       "</text>\n",
       "\n",
       "<text class=\"displacy-token\" fill=\"currentColor\" text-anchor=\"middle\" y=\"407.0\">\n",
       "    <tspan class=\"displacy-word\" fill=\"currentColor\" x=\"2570\">in</tspan>\n",
       "    <tspan class=\"displacy-tag\" dy=\"2em\" fill=\"currentColor\" x=\"2570\">ADP</tspan>\n",
       "</text>\n",
       "\n",
       "<text class=\"displacy-token\" fill=\"currentColor\" text-anchor=\"middle\" y=\"407.0\">\n",
       "    <tspan class=\"displacy-word\" fill=\"currentColor\" x=\"2690\">Punjab</tspan>\n",
       "    <tspan class=\"displacy-tag\" dy=\"2em\" fill=\"currentColor\" x=\"2690\">PROPN</tspan>\n",
       "</text>\n",
       "\n",
       "<text class=\"displacy-token\" fill=\"currentColor\" text-anchor=\"middle\" y=\"407.0\">\n",
       "    <tspan class=\"displacy-word\" fill=\"currentColor\" x=\"2810\">at</tspan>\n",
       "    <tspan class=\"displacy-tag\" dy=\"2em\" fill=\"currentColor\" x=\"2810\">ADP</tspan>\n",
       "</text>\n",
       "\n",
       "<text class=\"displacy-token\" fill=\"currentColor\" text-anchor=\"middle\" y=\"407.0\">\n",
       "    <tspan class=\"displacy-word\" fill=\"currentColor\" x=\"2930\">or</tspan>\n",
       "    <tspan class=\"displacy-tag\" dy=\"2em\" fill=\"currentColor\" x=\"2930\">CCONJ</tspan>\n",
       "</text>\n",
       "\n",
       "<text class=\"displacy-token\" fill=\"currentColor\" text-anchor=\"middle\" y=\"407.0\">\n",
       "    <tspan class=\"displacy-word\" fill=\"currentColor\" x=\"3050\">in</tspan>\n",
       "    <tspan class=\"displacy-tag\" dy=\"2em\" fill=\"currentColor\" x=\"3050\">ADP</tspan>\n",
       "</text>\n",
       "\n",
       "<text class=\"displacy-token\" fill=\"currentColor\" text-anchor=\"middle\" y=\"407.0\">\n",
       "    <tspan class=\"displacy-word\" fill=\"currentColor\" x=\"3170\">Canada</tspan>\n",
       "    <tspan class=\"displacy-tag\" dy=\"2em\" fill=\"currentColor\" x=\"3170\">PROPN</tspan>\n",
       "</text>\n",
       "\n",
       "<text class=\"displacy-token\" fill=\"currentColor\" text-anchor=\"middle\" y=\"407.0\">\n",
       "    <tspan class=\"displacy-word\" fill=\"currentColor\" x=\"3290\">at</tspan>\n",
       "    <tspan class=\"displacy-tag\" dy=\"2em\" fill=\"currentColor\" x=\"3290\">ADP</tspan>\n",
       "</text>\n",
       "\n",
       "<text class=\"displacy-token\" fill=\"currentColor\" text-anchor=\"middle\" y=\"407.0\">\n",
       "    <tspan class=\"displacy-word\" fill=\"currentColor\" x=\"3410\">Attn</tspan>\n",
       "    <tspan class=\"displacy-tag\" dy=\"2em\" fill=\"currentColor\" x=\"3410\">PROPN</tspan>\n",
       "</text>\n",
       "\n",
       "<g class=\"displacy-arrow\">\n",
       "    <path class=\"displacy-arc\" id=\"arrow-b9ec605fae7c4c188fdfbd3ce5b11f89-0-0\" stroke-width=\"2px\" d=\"M70,362.0 C70,302.0 145.0,302.0 145.0,362.0\" fill=\"none\" stroke=\"currentColor\"/>\n",
       "    <text dy=\"1.25em\" style=\"font-size: 0.8em; letter-spacing: 1px\">\n",
       "        <textPath xlink:href=\"#arrow-b9ec605fae7c4c188fdfbd3ce5b11f89-0-0\" class=\"displacy-label\" startOffset=\"50%\" side=\"left\" fill=\"currentColor\" text-anchor=\"middle\">prep</textPath>\n",
       "    </text>\n",
       "    <path class=\"displacy-arrowhead\" d=\"M145.0,364.0 L153.0,352.0 137.0,352.0\" fill=\"currentColor\"/>\n",
       "</g>\n",
       "\n",
       "<g class=\"displacy-arrow\">\n",
       "    <path class=\"displacy-arc\" id=\"arrow-b9ec605fae7c4c188fdfbd3ce5b11f89-0-1\" stroke-width=\"2px\" d=\"M310,362.0 C310,302.0 385.0,302.0 385.0,362.0\" fill=\"none\" stroke=\"currentColor\"/>\n",
       "    <text dy=\"1.25em\" style=\"font-size: 0.8em; letter-spacing: 1px\">\n",
       "        <textPath xlink:href=\"#arrow-b9ec605fae7c4c188fdfbd3ce5b11f89-0-1\" class=\"displacy-label\" startOffset=\"50%\" side=\"left\" fill=\"currentColor\" text-anchor=\"middle\">advmod</textPath>\n",
       "    </text>\n",
       "    <path class=\"displacy-arrowhead\" d=\"M310,364.0 L302,352.0 318,352.0\" fill=\"currentColor\"/>\n",
       "</g>\n",
       "\n",
       "<g class=\"displacy-arrow\">\n",
       "    <path class=\"displacy-arc\" id=\"arrow-b9ec605fae7c4c188fdfbd3ce5b11f89-0-2\" stroke-width=\"2px\" d=\"M430,362.0 C430,182.0 755.0,182.0 755.0,362.0\" fill=\"none\" stroke=\"currentColor\"/>\n",
       "    <text dy=\"1.25em\" style=\"font-size: 0.8em; letter-spacing: 1px\">\n",
       "        <textPath xlink:href=\"#arrow-b9ec605fae7c4c188fdfbd3ce5b11f89-0-2\" class=\"displacy-label\" startOffset=\"50%\" side=\"left\" fill=\"currentColor\" text-anchor=\"middle\">amod</textPath>\n",
       "    </text>\n",
       "    <path class=\"displacy-arrowhead\" d=\"M430,364.0 L422,352.0 438,352.0\" fill=\"currentColor\"/>\n",
       "</g>\n",
       "\n",
       "<g class=\"displacy-arrow\">\n",
       "    <path class=\"displacy-arc\" id=\"arrow-b9ec605fae7c4c188fdfbd3ce5b11f89-0-3\" stroke-width=\"2px\" d=\"M550,362.0 C550,242.0 750.0,242.0 750.0,362.0\" fill=\"none\" stroke=\"currentColor\"/>\n",
       "    <text dy=\"1.25em\" style=\"font-size: 0.8em; letter-spacing: 1px\">\n",
       "        <textPath xlink:href=\"#arrow-b9ec605fae7c4c188fdfbd3ce5b11f89-0-3\" class=\"displacy-label\" startOffset=\"50%\" side=\"left\" fill=\"currentColor\" text-anchor=\"middle\">compound</textPath>\n",
       "    </text>\n",
       "    <path class=\"displacy-arrowhead\" d=\"M550,364.0 L542,352.0 558,352.0\" fill=\"currentColor\"/>\n",
       "</g>\n",
       "\n",
       "<g class=\"displacy-arrow\">\n",
       "    <path class=\"displacy-arc\" id=\"arrow-b9ec605fae7c4c188fdfbd3ce5b11f89-0-4\" stroke-width=\"2px\" d=\"M670,362.0 C670,302.0 745.0,302.0 745.0,362.0\" fill=\"none\" stroke=\"currentColor\"/>\n",
       "    <text dy=\"1.25em\" style=\"font-size: 0.8em; letter-spacing: 1px\">\n",
       "        <textPath xlink:href=\"#arrow-b9ec605fae7c4c188fdfbd3ce5b11f89-0-4\" class=\"displacy-label\" startOffset=\"50%\" side=\"left\" fill=\"currentColor\" text-anchor=\"middle\">compound</textPath>\n",
       "    </text>\n",
       "    <path class=\"displacy-arrowhead\" d=\"M670,364.0 L662,352.0 678,352.0\" fill=\"currentColor\"/>\n",
       "</g>\n",
       "\n",
       "<g class=\"displacy-arrow\">\n",
       "    <path class=\"displacy-arc\" id=\"arrow-b9ec605fae7c4c188fdfbd3ce5b11f89-0-5\" stroke-width=\"2px\" d=\"M190,362.0 C190,122.0 760.0,122.0 760.0,362.0\" fill=\"none\" stroke=\"currentColor\"/>\n",
       "    <text dy=\"1.25em\" style=\"font-size: 0.8em; letter-spacing: 1px\">\n",
       "        <textPath xlink:href=\"#arrow-b9ec605fae7c4c188fdfbd3ce5b11f89-0-5\" class=\"displacy-label\" startOffset=\"50%\" side=\"left\" fill=\"currentColor\" text-anchor=\"middle\">pobj</textPath>\n",
       "    </text>\n",
       "    <path class=\"displacy-arrowhead\" d=\"M760.0,364.0 L768.0,352.0 752.0,352.0\" fill=\"currentColor\"/>\n",
       "</g>\n",
       "\n",
       "<g class=\"displacy-arrow\">\n",
       "    <path class=\"displacy-arc\" id=\"arrow-b9ec605fae7c4c188fdfbd3ce5b11f89-0-6\" stroke-width=\"2px\" d=\"M790,362.0 C790,302.0 865.0,302.0 865.0,362.0\" fill=\"none\" stroke=\"currentColor\"/>\n",
       "    <text dy=\"1.25em\" style=\"font-size: 0.8em; letter-spacing: 1px\">\n",
       "        <textPath xlink:href=\"#arrow-b9ec605fae7c4c188fdfbd3ce5b11f89-0-6\" class=\"displacy-label\" startOffset=\"50%\" side=\"left\" fill=\"currentColor\" text-anchor=\"middle\">prep</textPath>\n",
       "    </text>\n",
       "    <path class=\"displacy-arrowhead\" d=\"M865.0,364.0 L873.0,352.0 857.0,352.0\" fill=\"currentColor\"/>\n",
       "</g>\n",
       "\n",
       "<g class=\"displacy-arrow\">\n",
       "    <path class=\"displacy-arc\" id=\"arrow-b9ec605fae7c4c188fdfbd3ce5b11f89-0-7\" stroke-width=\"2px\" d=\"M910,362.0 C910,302.0 985.0,302.0 985.0,362.0\" fill=\"none\" stroke=\"currentColor\"/>\n",
       "    <text dy=\"1.25em\" style=\"font-size: 0.8em; letter-spacing: 1px\">\n",
       "        <textPath xlink:href=\"#arrow-b9ec605fae7c4c188fdfbd3ce5b11f89-0-7\" class=\"displacy-label\" startOffset=\"50%\" side=\"left\" fill=\"currentColor\" text-anchor=\"middle\">pobj</textPath>\n",
       "    </text>\n",
       "    <path class=\"displacy-arrowhead\" d=\"M985.0,364.0 L993.0,352.0 977.0,352.0\" fill=\"currentColor\"/>\n",
       "</g>\n",
       "\n",
       "<g class=\"displacy-arrow\">\n",
       "    <path class=\"displacy-arc\" id=\"arrow-b9ec605fae7c4c188fdfbd3ce5b11f89-0-8\" stroke-width=\"2px\" d=\"M1030,362.0 C1030,302.0 1105.0,302.0 1105.0,362.0\" fill=\"none\" stroke=\"currentColor\"/>\n",
       "    <text dy=\"1.25em\" style=\"font-size: 0.8em; letter-spacing: 1px\">\n",
       "        <textPath xlink:href=\"#arrow-b9ec605fae7c4c188fdfbd3ce5b11f89-0-8\" class=\"displacy-label\" startOffset=\"50%\" side=\"left\" fill=\"currentColor\" text-anchor=\"middle\">cc</textPath>\n",
       "    </text>\n",
       "    <path class=\"displacy-arrowhead\" d=\"M1105.0,364.0 L1113.0,352.0 1097.0,352.0\" fill=\"currentColor\"/>\n",
       "</g>\n",
       "\n",
       "<g class=\"displacy-arrow\">\n",
       "    <path class=\"displacy-arc\" id=\"arrow-b9ec605fae7c4c188fdfbd3ce5b11f89-0-9\" stroke-width=\"2px\" d=\"M1030,362.0 C1030,242.0 1230.0,242.0 1230.0,362.0\" fill=\"none\" stroke=\"currentColor\"/>\n",
       "    <text dy=\"1.25em\" style=\"font-size: 0.8em; letter-spacing: 1px\">\n",
       "        <textPath xlink:href=\"#arrow-b9ec605fae7c4c188fdfbd3ce5b11f89-0-9\" class=\"displacy-label\" startOffset=\"50%\" side=\"left\" fill=\"currentColor\" text-anchor=\"middle\">conj</textPath>\n",
       "    </text>\n",
       "    <path class=\"displacy-arrowhead\" d=\"M1230.0,364.0 L1238.0,352.0 1222.0,352.0\" fill=\"currentColor\"/>\n",
       "</g>\n",
       "\n",
       "<g class=\"displacy-arrow\">\n",
       "    <path class=\"displacy-arc\" id=\"arrow-b9ec605fae7c4c188fdfbd3ce5b11f89-0-10\" stroke-width=\"2px\" d=\"M790,362.0 C790,122.0 1360.0,122.0 1360.0,362.0\" fill=\"none\" stroke=\"currentColor\"/>\n",
       "    <text dy=\"1.25em\" style=\"font-size: 0.8em; letter-spacing: 1px\">\n",
       "        <textPath xlink:href=\"#arrow-b9ec605fae7c4c188fdfbd3ce5b11f89-0-10\" class=\"displacy-label\" startOffset=\"50%\" side=\"left\" fill=\"currentColor\" text-anchor=\"middle\">prep</textPath>\n",
       "    </text>\n",
       "    <path class=\"displacy-arrowhead\" d=\"M1360.0,364.0 L1368.0,352.0 1352.0,352.0\" fill=\"currentColor\"/>\n",
       "</g>\n",
       "\n",
       "<g class=\"displacy-arrow\">\n",
       "    <path class=\"displacy-arc\" id=\"arrow-b9ec605fae7c4c188fdfbd3ce5b11f89-0-11\" stroke-width=\"2px\" d=\"M1510,362.0 C1510,302.0 1585.0,302.0 1585.0,362.0\" fill=\"none\" stroke=\"currentColor\"/>\n",
       "    <text dy=\"1.25em\" style=\"font-size: 0.8em; letter-spacing: 1px\">\n",
       "        <textPath xlink:href=\"#arrow-b9ec605fae7c4c188fdfbd3ce5b11f89-0-11\" class=\"displacy-label\" startOffset=\"50%\" side=\"left\" fill=\"currentColor\" text-anchor=\"middle\">compound</textPath>\n",
       "    </text>\n",
       "    <path class=\"displacy-arrowhead\" d=\"M1510,364.0 L1502,352.0 1518,352.0\" fill=\"currentColor\"/>\n",
       "</g>\n",
       "\n",
       "<g class=\"displacy-arrow\">\n",
       "    <path class=\"displacy-arc\" id=\"arrow-b9ec605fae7c4c188fdfbd3ce5b11f89-0-12\" stroke-width=\"2px\" d=\"M1630,362.0 C1630,302.0 1705.0,302.0 1705.0,362.0\" fill=\"none\" stroke=\"currentColor\"/>\n",
       "    <text dy=\"1.25em\" style=\"font-size: 0.8em; letter-spacing: 1px\">\n",
       "        <textPath xlink:href=\"#arrow-b9ec605fae7c4c188fdfbd3ce5b11f89-0-12\" class=\"displacy-label\" startOffset=\"50%\" side=\"left\" fill=\"currentColor\" text-anchor=\"middle\">compound</textPath>\n",
       "    </text>\n",
       "    <path class=\"displacy-arrowhead\" d=\"M1630,364.0 L1622,352.0 1638,352.0\" fill=\"currentColor\"/>\n",
       "</g>\n",
       "\n",
       "<g class=\"displacy-arrow\">\n",
       "    <path class=\"displacy-arc\" id=\"arrow-b9ec605fae7c4c188fdfbd3ce5b11f89-0-13\" stroke-width=\"2px\" d=\"M1390,362.0 C1390,182.0 1715.0,182.0 1715.0,362.0\" fill=\"none\" stroke=\"currentColor\"/>\n",
       "    <text dy=\"1.25em\" style=\"font-size: 0.8em; letter-spacing: 1px\">\n",
       "        <textPath xlink:href=\"#arrow-b9ec605fae7c4c188fdfbd3ce5b11f89-0-13\" class=\"displacy-label\" startOffset=\"50%\" side=\"left\" fill=\"currentColor\" text-anchor=\"middle\">pobj</textPath>\n",
       "    </text>\n",
       "    <path class=\"displacy-arrowhead\" d=\"M1715.0,364.0 L1723.0,352.0 1707.0,352.0\" fill=\"currentColor\"/>\n",
       "</g>\n",
       "\n",
       "<g class=\"displacy-arrow\">\n",
       "    <path class=\"displacy-arc\" id=\"arrow-b9ec605fae7c4c188fdfbd3ce5b11f89-0-14\" stroke-width=\"2px\" d=\"M1750,362.0 C1750,302.0 1825.0,302.0 1825.0,362.0\" fill=\"none\" stroke=\"currentColor\"/>\n",
       "    <text dy=\"1.25em\" style=\"font-size: 0.8em; letter-spacing: 1px\">\n",
       "        <textPath xlink:href=\"#arrow-b9ec605fae7c4c188fdfbd3ce5b11f89-0-14\" class=\"displacy-label\" startOffset=\"50%\" side=\"left\" fill=\"currentColor\" text-anchor=\"middle\">prep</textPath>\n",
       "    </text>\n",
       "    <path class=\"displacy-arrowhead\" d=\"M1825.0,364.0 L1833.0,352.0 1817.0,352.0\" fill=\"currentColor\"/>\n",
       "</g>\n",
       "\n",
       "<g class=\"displacy-arrow\">\n",
       "    <path class=\"displacy-arc\" id=\"arrow-b9ec605fae7c4c188fdfbd3ce5b11f89-0-15\" stroke-width=\"2px\" d=\"M1870,362.0 C1870,302.0 1945.0,302.0 1945.0,362.0\" fill=\"none\" stroke=\"currentColor\"/>\n",
       "    <text dy=\"1.25em\" style=\"font-size: 0.8em; letter-spacing: 1px\">\n",
       "        <textPath xlink:href=\"#arrow-b9ec605fae7c4c188fdfbd3ce5b11f89-0-15\" class=\"displacy-label\" startOffset=\"50%\" side=\"left\" fill=\"currentColor\" text-anchor=\"middle\">pobj</textPath>\n",
       "    </text>\n",
       "    <path class=\"displacy-arrowhead\" d=\"M1945.0,364.0 L1953.0,352.0 1937.0,352.0\" fill=\"currentColor\"/>\n",
       "</g>\n",
       "\n",
       "<g class=\"displacy-arrow\">\n",
       "    <path class=\"displacy-arc\" id=\"arrow-b9ec605fae7c4c188fdfbd3ce5b11f89-0-16\" stroke-width=\"2px\" d=\"M70,362.0 C70,2.0 2090.0,2.0 2090.0,362.0\" fill=\"none\" stroke=\"currentColor\"/>\n",
       "    <text dy=\"1.25em\" style=\"font-size: 0.8em; letter-spacing: 1px\">\n",
       "        <textPath xlink:href=\"#arrow-b9ec605fae7c4c188fdfbd3ce5b11f89-0-16\" class=\"displacy-label\" startOffset=\"50%\" side=\"left\" fill=\"currentColor\" text-anchor=\"middle\">prep</textPath>\n",
       "    </text>\n",
       "    <path class=\"displacy-arrowhead\" d=\"M2090.0,364.0 L2098.0,352.0 2082.0,352.0\" fill=\"currentColor\"/>\n",
       "</g>\n",
       "\n",
       "<g class=\"displacy-arrow\">\n",
       "    <path class=\"displacy-arc\" id=\"arrow-b9ec605fae7c4c188fdfbd3ce5b11f89-0-17\" stroke-width=\"2px\" d=\"M2230,362.0 C2230,242.0 2430.0,242.0 2430.0,362.0\" fill=\"none\" stroke=\"currentColor\"/>\n",
       "    <text dy=\"1.25em\" style=\"font-size: 0.8em; letter-spacing: 1px\">\n",
       "        <textPath xlink:href=\"#arrow-b9ec605fae7c4c188fdfbd3ce5b11f89-0-17\" class=\"displacy-label\" startOffset=\"50%\" side=\"left\" fill=\"currentColor\" text-anchor=\"middle\">amod</textPath>\n",
       "    </text>\n",
       "    <path class=\"displacy-arrowhead\" d=\"M2230,364.0 L2222,352.0 2238,352.0\" fill=\"currentColor\"/>\n",
       "</g>\n",
       "\n",
       "<g class=\"displacy-arrow\">\n",
       "    <path class=\"displacy-arc\" id=\"arrow-b9ec605fae7c4c188fdfbd3ce5b11f89-0-18\" stroke-width=\"2px\" d=\"M2350,362.0 C2350,302.0 2425.0,302.0 2425.0,362.0\" fill=\"none\" stroke=\"currentColor\"/>\n",
       "    <text dy=\"1.25em\" style=\"font-size: 0.8em; letter-spacing: 1px\">\n",
       "        <textPath xlink:href=\"#arrow-b9ec605fae7c4c188fdfbd3ce5b11f89-0-18\" class=\"displacy-label\" startOffset=\"50%\" side=\"left\" fill=\"currentColor\" text-anchor=\"middle\">amod</textPath>\n",
       "    </text>\n",
       "    <path class=\"displacy-arrowhead\" d=\"M2350,364.0 L2342,352.0 2358,352.0\" fill=\"currentColor\"/>\n",
       "</g>\n",
       "\n",
       "<g class=\"displacy-arrow\">\n",
       "    <path class=\"displacy-arc\" id=\"arrow-b9ec605fae7c4c188fdfbd3ce5b11f89-0-19\" stroke-width=\"2px\" d=\"M2110,362.0 C2110,182.0 2435.0,182.0 2435.0,362.0\" fill=\"none\" stroke=\"currentColor\"/>\n",
       "    <text dy=\"1.25em\" style=\"font-size: 0.8em; letter-spacing: 1px\">\n",
       "        <textPath xlink:href=\"#arrow-b9ec605fae7c4c188fdfbd3ce5b11f89-0-19\" class=\"displacy-label\" startOffset=\"50%\" side=\"left\" fill=\"currentColor\" text-anchor=\"middle\">pobj</textPath>\n",
       "    </text>\n",
       "    <path class=\"displacy-arrowhead\" d=\"M2435.0,364.0 L2443.0,352.0 2427.0,352.0\" fill=\"currentColor\"/>\n",
       "</g>\n",
       "\n",
       "<g class=\"displacy-arrow\">\n",
       "    <path class=\"displacy-arc\" id=\"arrow-b9ec605fae7c4c188fdfbd3ce5b11f89-0-20\" stroke-width=\"2px\" d=\"M2470,362.0 C2470,302.0 2545.0,302.0 2545.0,362.0\" fill=\"none\" stroke=\"currentColor\"/>\n",
       "    <text dy=\"1.25em\" style=\"font-size: 0.8em; letter-spacing: 1px\">\n",
       "        <textPath xlink:href=\"#arrow-b9ec605fae7c4c188fdfbd3ce5b11f89-0-20\" class=\"displacy-label\" startOffset=\"50%\" side=\"left\" fill=\"currentColor\" text-anchor=\"middle\">prep</textPath>\n",
       "    </text>\n",
       "    <path class=\"displacy-arrowhead\" d=\"M2545.0,364.0 L2553.0,352.0 2537.0,352.0\" fill=\"currentColor\"/>\n",
       "</g>\n",
       "\n",
       "<g class=\"displacy-arrow\">\n",
       "    <path class=\"displacy-arc\" id=\"arrow-b9ec605fae7c4c188fdfbd3ce5b11f89-0-21\" stroke-width=\"2px\" d=\"M2590,362.0 C2590,302.0 2665.0,302.0 2665.0,362.0\" fill=\"none\" stroke=\"currentColor\"/>\n",
       "    <text dy=\"1.25em\" style=\"font-size: 0.8em; letter-spacing: 1px\">\n",
       "        <textPath xlink:href=\"#arrow-b9ec605fae7c4c188fdfbd3ce5b11f89-0-21\" class=\"displacy-label\" startOffset=\"50%\" side=\"left\" fill=\"currentColor\" text-anchor=\"middle\">pobj</textPath>\n",
       "    </text>\n",
       "    <path class=\"displacy-arrowhead\" d=\"M2665.0,364.0 L2673.0,352.0 2657.0,352.0\" fill=\"currentColor\"/>\n",
       "</g>\n",
       "\n",
       "<g class=\"displacy-arrow\">\n",
       "    <path class=\"displacy-arc\" id=\"arrow-b9ec605fae7c4c188fdfbd3ce5b11f89-0-22\" stroke-width=\"2px\" d=\"M2470,362.0 C2470,182.0 2795.0,182.0 2795.0,362.0\" fill=\"none\" stroke=\"currentColor\"/>\n",
       "    <text dy=\"1.25em\" style=\"font-size: 0.8em; letter-spacing: 1px\">\n",
       "        <textPath xlink:href=\"#arrow-b9ec605fae7c4c188fdfbd3ce5b11f89-0-22\" class=\"displacy-label\" startOffset=\"50%\" side=\"left\" fill=\"currentColor\" text-anchor=\"middle\">prep</textPath>\n",
       "    </text>\n",
       "    <path class=\"displacy-arrowhead\" d=\"M2795.0,364.0 L2803.0,352.0 2787.0,352.0\" fill=\"currentColor\"/>\n",
       "</g>\n",
       "\n",
       "<g class=\"displacy-arrow\">\n",
       "    <path class=\"displacy-arc\" id=\"arrow-b9ec605fae7c4c188fdfbd3ce5b11f89-0-23\" stroke-width=\"2px\" d=\"M2830,362.0 C2830,302.0 2905.0,302.0 2905.0,362.0\" fill=\"none\" stroke=\"currentColor\"/>\n",
       "    <text dy=\"1.25em\" style=\"font-size: 0.8em; letter-spacing: 1px\">\n",
       "        <textPath xlink:href=\"#arrow-b9ec605fae7c4c188fdfbd3ce5b11f89-0-23\" class=\"displacy-label\" startOffset=\"50%\" side=\"left\" fill=\"currentColor\" text-anchor=\"middle\">cc</textPath>\n",
       "    </text>\n",
       "    <path class=\"displacy-arrowhead\" d=\"M2905.0,364.0 L2913.0,352.0 2897.0,352.0\" fill=\"currentColor\"/>\n",
       "</g>\n",
       "\n",
       "<g class=\"displacy-arrow\">\n",
       "    <path class=\"displacy-arc\" id=\"arrow-b9ec605fae7c4c188fdfbd3ce5b11f89-0-24\" stroke-width=\"2px\" d=\"M2830,362.0 C2830,242.0 3030.0,242.0 3030.0,362.0\" fill=\"none\" stroke=\"currentColor\"/>\n",
       "    <text dy=\"1.25em\" style=\"font-size: 0.8em; letter-spacing: 1px\">\n",
       "        <textPath xlink:href=\"#arrow-b9ec605fae7c4c188fdfbd3ce5b11f89-0-24\" class=\"displacy-label\" startOffset=\"50%\" side=\"left\" fill=\"currentColor\" text-anchor=\"middle\">conj</textPath>\n",
       "    </text>\n",
       "    <path class=\"displacy-arrowhead\" d=\"M3030.0,364.0 L3038.0,352.0 3022.0,352.0\" fill=\"currentColor\"/>\n",
       "</g>\n",
       "\n",
       "<g class=\"displacy-arrow\">\n",
       "    <path class=\"displacy-arc\" id=\"arrow-b9ec605fae7c4c188fdfbd3ce5b11f89-0-25\" stroke-width=\"2px\" d=\"M3070,362.0 C3070,302.0 3145.0,302.0 3145.0,362.0\" fill=\"none\" stroke=\"currentColor\"/>\n",
       "    <text dy=\"1.25em\" style=\"font-size: 0.8em; letter-spacing: 1px\">\n",
       "        <textPath xlink:href=\"#arrow-b9ec605fae7c4c188fdfbd3ce5b11f89-0-25\" class=\"displacy-label\" startOffset=\"50%\" side=\"left\" fill=\"currentColor\" text-anchor=\"middle\">pobj</textPath>\n",
       "    </text>\n",
       "    <path class=\"displacy-arrowhead\" d=\"M3145.0,364.0 L3153.0,352.0 3137.0,352.0\" fill=\"currentColor\"/>\n",
       "</g>\n",
       "\n",
       "<g class=\"displacy-arrow\">\n",
       "    <path class=\"displacy-arc\" id=\"arrow-b9ec605fae7c4c188fdfbd3ce5b11f89-0-26\" stroke-width=\"2px\" d=\"M2470,362.0 C2470,62.0 3285.0,62.0 3285.0,362.0\" fill=\"none\" stroke=\"currentColor\"/>\n",
       "    <text dy=\"1.25em\" style=\"font-size: 0.8em; letter-spacing: 1px\">\n",
       "        <textPath xlink:href=\"#arrow-b9ec605fae7c4c188fdfbd3ce5b11f89-0-26\" class=\"displacy-label\" startOffset=\"50%\" side=\"left\" fill=\"currentColor\" text-anchor=\"middle\">prep</textPath>\n",
       "    </text>\n",
       "    <path class=\"displacy-arrowhead\" d=\"M3285.0,364.0 L3293.0,352.0 3277.0,352.0\" fill=\"currentColor\"/>\n",
       "</g>\n",
       "\n",
       "<g class=\"displacy-arrow\">\n",
       "    <path class=\"displacy-arc\" id=\"arrow-b9ec605fae7c4c188fdfbd3ce5b11f89-0-27\" stroke-width=\"2px\" d=\"M3310,362.0 C3310,302.0 3385.0,302.0 3385.0,362.0\" fill=\"none\" stroke=\"currentColor\"/>\n",
       "    <text dy=\"1.25em\" style=\"font-size: 0.8em; letter-spacing: 1px\">\n",
       "        <textPath xlink:href=\"#arrow-b9ec605fae7c4c188fdfbd3ce5b11f89-0-27\" class=\"displacy-label\" startOffset=\"50%\" side=\"left\" fill=\"currentColor\" text-anchor=\"middle\">pobj</textPath>\n",
       "    </text>\n",
       "    <path class=\"displacy-arrowhead\" d=\"M3385.0,364.0 L3393.0,352.0 3377.0,352.0\" fill=\"currentColor\"/>\n",
       "</g>\n",
       "</svg></span>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for index, row in brides_df[15:16].iterrows():\n",
    "    text = ' '.join(row['sentences'][0])\n",
    "    print(text)\n",
    "    doc = nlp(text)\n",
    "    for token in doc:\n",
    "        print(token.text, token.dep_, token.head.text, token.head.pos_,\n",
    "            [child for child in token.children])\n",
    "    displacy.render(doc,style='dep',options = {'distance':120})"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d53f6396",
   "metadata": {},
   "source": [
    "## <font color = \"Green\"> The above dependency parse tree is extremely nested because most of the sentences in these advertisements are not punctuated. However, a few insights can still be drawn for instance, for is a preposition associated with looking, and settled is an adjective modifier for boy and professionally is an adverb related to settled. Other words such as Khataria and Tonk which are proper nouns are related to the buy and rightly so because they are ethnic communities again and talk about the prospective groom here. Other relations between compound words such as dental and surgeon can also be made.</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3d3a3ccd",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "affae592",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "e0c41b65",
   "metadata": {},
   "source": [
    "## <font color=\"red\">*Exercise 7*</font>\n",
    "\n",
    "<font color=\"red\">Construct cells immediately below this that calculate the KL and $\\chi^2$ divergences, and the KS and Wasserstein distances between four separate corpora, plot these with heatmaps, and then array them in two dimensions with multidimensional scaling as above. What does this reveal about relations between the corpora? Which analysis (and divergence or distribution) distinguishes the authors or documents better?\n",
    "\n",
    "**Stretch**: Calculate the [Jensen-Shannon Divergence](https://en.wikipedia.org/wiki/Jensen–Shannon_divergence) between your four corpora. What is the relationship between the KL and JS divergences?</font> "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "52cc5ede",
   "metadata": {},
   "source": [
    " ## <font color = \"Green\"> For this exercise I consider 4 documents, bride seeking ads from 2002 and 2014, and grrom seeking ads from 2002 and 2014. </font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "id": "5dea1fa3",
   "metadata": {},
   "outputs": [],
   "source": [
    "brides_info_2002= pandas.read_csv('brides-wanted_2002.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "id": "9419114d",
   "metadata": {},
   "outputs": [],
   "source": [
    "brides_info_2002['text'] = pandas.read_csv('brides-wanted_2002.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "bfe20b85",
   "metadata": {},
   "outputs": [],
   "source": [
    "grooms_info_2002 = pandas.read_csv('grooms-wanted_2002.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "id": "34184a29",
   "metadata": {},
   "outputs": [],
   "source": [
    "grooms_info_2002['text'] = pandas.read_csv('grooms-wanted_2002.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "id": "9b60121f",
   "metadata": {},
   "outputs": [],
   "source": [
    "brides_info_2014= pandas.read_csv('brides-wanted_2014.csv')\n",
    "brides_info_2014['text']= pandas.read_csv('brides-wanted_2014.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "id": "a0f932a5",
   "metadata": {},
   "outputs": [],
   "source": [
    "grooms_info_2014= pandas.read_csv('grooms-wanted_2014.csv')\n",
    "grooms_info_2014['text']= pandas.read_csv('grooms-wanted_2014.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 181,
   "id": "a70d8d8d",
   "metadata": {},
   "outputs": [],
   "source": [
    "grooms_info_2002['tokenized_text'] = grooms_info_2002['text'].apply(lambda x: word_tokenize(str(x)))\n",
    "grooms_info_2002['normalized_tokens'] = grooms_info_2002['tokenized_text'].apply(lambda x: normalizeTokens(x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 182,
   "id": "74134ecd",
   "metadata": {},
   "outputs": [],
   "source": [
    "brides_info_2002['tokenized_text'] = brides_info_2002['text'].apply(lambda x: word_tokenize(str(x)))\n",
    "brides_info_2002['normalized_tokens'] = brides_info_2002['tokenized_text'].apply(lambda x: normalizeTokens(x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 183,
   "id": "810f7c70",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "863"
      ]
     },
     "execution_count": 183,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grWords = set(grooms_info_2002['normalized_tokens'].sum())\n",
    "brWords = set(brides_info_2002['normalized_tokens'].sum())\n",
    "overlapWords = grWords & brWords\n",
    "\n",
    "overlapWordsDict = {word: index for index, word in enumerate(overlapWords)}\n",
    "overlapWordsDict['sikh']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 184,
   "id": "2fea5c2c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.0"
      ]
     },
     "execution_count": 184,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def makeProbsArray(dfColumn, overlapDict):\n",
    "    words = dfColumn.sum()\n",
    "    countList = [0] * len(overlapDict)\n",
    "    for word in words:\n",
    "        try:\n",
    "            countList[overlapDict[word]] += 1\n",
    "        except KeyError:\n",
    "            #The word is not common so we skip it\n",
    "            pass\n",
    "    countArray = np.array(countList)\n",
    "    return countArray / countArray.sum()\n",
    "\n",
    "grProbArray = makeProbsArray(grooms_info_2002['normalized_tokens'], overlapWordsDict)\n",
    "brProbArray = makeProbsArray(brides_info_2002['normalized_tokens'], overlapWordsDict)\n",
    "grProbArray.sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 185,
   "id": "5de90cc0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.35832443060756675\n",
      "0.3409618935132953\n"
     ]
    }
   ],
   "source": [
    "gr_brDivergence = scipy.stats.entropy(grProbArray, brProbArray)\n",
    "print(gr_brDivergence)\n",
    "br_grDivergence = scipy.stats.entropy(brProbArray, grProbArray)\n",
    "print (br_grDivergence)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 186,
   "id": "748e4629",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.453935200245136\n",
      "1.9238773539101945\n"
     ]
    }
   ],
   "source": [
    "gr_brchi = scipy.stats.chisquare(grProbArray, brProbArray).statistic\n",
    "print(gr_brchi)\n",
    "br_grchi = scipy.stats.chisquare(brProbArray, grProbArray).statistic\n",
    "print(br_grchi)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 187,
   "id": "600b4ac8",
   "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>word</th>\n",
       "      <th>elementwise divergence</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>lect</td>\n",
       "      <td>4.786056e-05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>bhagat</td>\n",
       "      <td>8.148483e-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>institute</td>\n",
       "      <td>2.790041e-05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>professionally</td>\n",
       "      <td>1.007343e-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>kg</td>\n",
       "      <td>6.757860e-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>yamuna</td>\n",
       "      <td>8.148483e-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>dba</td>\n",
       "      <td>8.747980e-08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>partner</td>\n",
       "      <td>2.624394e-07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>market</td>\n",
       "      <td>1.749596e-07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>clinical</td>\n",
       "      <td>4.786056e-05</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              word  elementwise divergence\n",
       "40            lect            4.786056e-05\n",
       "41          bhagat            8.148483e-06\n",
       "42       institute            2.790041e-05\n",
       "43  professionally            1.007343e-04\n",
       "44              kg            6.757860e-06\n",
       "45          yamuna            8.148483e-06\n",
       "46             dba            8.747980e-08\n",
       "47         partner            2.624394e-07\n",
       "48          market            1.749596e-07\n",
       "49        clinical            4.786056e-05"
      ]
     },
     "execution_count": 187,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gr_brDivergence_ew = scipy.special.kl_div(grProbArray, brProbArray)\n",
    "kl_df = pandas.DataFrame(list(overlapWordsDict.keys()), columns = ['word'], index = list(overlapWordsDict.values()))\n",
    "kl_df = kl_df.sort_index()\n",
    "kl_df['elementwise divergence'] = gr_brDivergence_ew\n",
    "kl_df[40:50]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 188,
   "id": "24a1d360",
   "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>word</th>\n",
       "      <th>elementwise divergence</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>745</th>\n",
       "      <td>boy</td>\n",
       "      <td>0.047911</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>399</th>\n",
       "      <td>handsome</td>\n",
       "      <td>0.039671</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1264</th>\n",
       "      <td>son</td>\n",
       "      <td>0.017207</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>796</th>\n",
       "      <td>ma</td>\n",
       "      <td>0.006214</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1414</th>\n",
       "      <td>tall</td>\n",
       "      <td>0.006048</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          word  elementwise divergence\n",
       "745        boy                0.047911\n",
       "399   handsome                0.039671\n",
       "1264       son                0.017207\n",
       "796         ma                0.006214\n",
       "1414      tall                0.006048"
      ]
     },
     "execution_count": 188,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "kl_df.sort_values(by='elementwise divergence', ascending=False)[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 189,
   "id": "3b81a430",
   "metadata": {},
   "outputs": [],
   "source": [
    "def kl_divergence(X, Y):\n",
    "    P = X.copy()\n",
    "    Q = Y.copy()\n",
    "    P.columns = ['P']\n",
    "    Q.columns = ['Q']\n",
    "    df = Q.join(P).fillna(0)\n",
    "    p = df.iloc[:,1]\n",
    "    q = df.iloc[:,0]\n",
    "    D_kl = scipy.stats.entropy(p, q)\n",
    "    return D_kl\n",
    "\n",
    "def chi2_divergence(X,Y):\n",
    "    P = X.copy()\n",
    "    Q = Y.copy()\n",
    "    P.columns = ['P']\n",
    "    Q.columns = ['Q']\n",
    "    df = Q.join(P).fillna(0)\n",
    "    p = df.iloc[:,1]\n",
    "    q = df.iloc[:,0]\n",
    "    return scipy.stats.chisquare(p, q).statistic\n",
    "\n",
    "def Divergence(corpus1, corpus2, difference=\"KL\"):\n",
    "    \"\"\"Difference parameter can equal KL, Chi2, or Wass\"\"\"\n",
    "    freqP = nltk.FreqDist(corpus1)\n",
    "  \n",
    "    P = pandas.DataFrame(list(freqP.values()), columns = ['frequency'], index = list(freqP.keys()))\n",
    "    freqQ = nltk.FreqDist(corpus2)\n",
    "    Q = pandas.DataFrame(list(freqQ.values()), columns = ['frequency'], index = list(freqQ.keys()))\n",
    "    \n",
    "    if difference == \"KL\":\n",
    "        return kl_divergence(P, Q)\n",
    "    elif difference == \"Chi2\":\n",
    "        return chi2_divergence(P, Q)\n",
    "    elif difference == \"KS\":\n",
    "        try:\n",
    "            return scipy.stats.ks_2samp(P['frequency'], Q['frequency']).statistic\n",
    "        except:\n",
    "            return scipy.stats.ks_2samp(P['frequency'], Q['frequency'])\n",
    "    elif difference == \"Wasserstein\":\n",
    "        try:\n",
    "            return scipy.stats.wasserstein_distance(P['frequency'], Q['frequency'], u_weights=None, v_weights=None).statistic\n",
    "        except:\n",
    "            return scipy.stats.wasserstein_distance(P['frequency'], Q['frequency'], u_weights=None, v_weights=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 190,
   "id": "f5621c8e",
   "metadata": {},
   "outputs": [],
   "source": [
    "file = open('grooms-wanted_2002.csv')\n",
    "brides_wanted = []\n",
    "csvreader = csv.reader(file)\n",
    "\n",
    "\n",
    "for row in csvreader:\n",
    "    brides_wanted.extend(row)\n",
    "concat_list_1 = [' '.join([str(item) for item in brides_wanted])]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 191,
   "id": "8bb82067",
   "metadata": {},
   "outputs": [],
   "source": [
    "file = open('grooms-wanted_2014.csv')\n",
    "grooms_wanted = []\n",
    "csvreader = csv.reader(file)\n",
    "\n",
    "\n",
    "for row in csvreader:\n",
    "    grooms_wanted.extend(row)\n",
    "concat_list_2 = [' '.join([str(item) for item in grooms_wanted])]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 192,
   "id": "62ea20de",
   "metadata": {},
   "outputs": [],
   "source": [
    "file = open('brides-wanted_2014.csv')\n",
    "brides_wanted = []\n",
    "csvreader = csv.reader(file)\n",
    "\n",
    "\n",
    "for row in csvreader:\n",
    "    brides_wanted.extend(row)\n",
    "concat_list_3 = [' '.join([str(item) for item in brides_wanted])]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 217,
   "id": "b5d27003",
   "metadata": {},
   "outputs": [],
   "source": [
    "final_df = pandas.DataFrame({'info':[concat_list[0][200001:],concat_list_1[0][200020:],concat_list_2[0][5000000:],concat_list_3[0][149486000:]]})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 218,
   "id": "2fd35103",
   "metadata": {},
   "outputs": [],
   "source": [
    "final_df['tokenized_text'] = final_df['info'].apply(lambda x: word_tokenize(str(x)))\n",
    "final_df['normalized_tokens'] = final_df['tokenized_text'].apply(lambda x: normalizeTokens(str(x)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "60746132",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 221,
   "id": "04aa6720",
   "metadata": {},
   "outputs": [],
   "source": [
    "final_df['ad category'] = ['grooms wanted 2002','brides wanted 2002','grooms wanted 2014','brides wanted 2014']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "78635d20",
   "metadata": {},
   "source": [
    " ## <font color = \"Green\"> the structure of advertisements for brides and grooms tend to be similar, since they use similar sentences and this continues in ads even later on. Thus the tests that could be used are two fold. Within the same year, it might be interesting to see how similar word distributions are and hence, might be meaningful to use the chi2 or KS test, however, across years it might be interesting to see how far documents are from each other and use the KL divergence. For instance, the KS divergence between ads of grooms wnated in 2002 and brides wanted in 2014 is around .6 and 0.4 between grooms wanted in 2002 and 2014. Since these results rely on data of varying sizes and one that isn't completely clean, from a preliminary analysis, seems like different purposes for the ads solicit different tests. For instance, it might be interesting to see why ads for brides wanted in 2014 are so drastically far away from other ads across years. </font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 222,
   "id": "8c3ecadf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.0\n",
      "0.4779817464731395\n",
      "0.700281743582333\n",
      "1.5039341127251398\n",
      "0.5950828709474267\n",
      "0.0\n",
      "0.4375752498126907\n",
      "1.269592091521055\n",
      "1.0564688255703791\n",
      "0.6856264559019309\n",
      "0.0\n",
      "1.5407516706124276\n",
      "5.709507912083344\n",
      "5.709163197798809\n",
      "5.112710598937971\n",
      "0.0\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "final_df.set_index('ad category')\n",
    "measure = 'KL'\n",
    "num_of_texts = 4\n",
    "fileids_sp = list(final_df[:num_of_texts]['ad category'])\n",
    "corpora_sp = list(final_df[:num_of_texts]['normalized_tokens'])\n",
    "L = []\n",
    "for p in corpora_sp:\n",
    "    l = []\n",
    "    for q in corpora_sp:\n",
    "        l.append(Divergence(p,q, difference=measure))\n",
    "        print((Divergence(p,q, difference=measure)))\n",
    "    L.append(l)\n",
    "M = np.array(L)\n",
    "fig = plt.figure()\n",
    "div = pandas.DataFrame(M, columns = fileids_sp, index = fileids_sp)\n",
    "ax = sns.heatmap(div)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 223,
   "id": "2f246a97",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "measure = 'Chi2' #\"KL\", \"Chi2\", \"KS\", \"Wasserstein\"\n",
    "num_of_texts = 4 #The bigger this number the slower it will run, you can also try selecting your own plays\n",
    "fileids_sp = list(final_df[:num_of_texts]['ad category'])\n",
    "corpora_sp = list(final_df[:num_of_texts]['normalized_tokens'])\n",
    "\n",
    "#corpora_sp = list(brides_info_2002[1:num_of_texts+1]['normalized_tokens'])\n",
    "\n",
    "L = []\n",
    "for p in corpora_sp:\n",
    "    l = []\n",
    "    for q in corpora_sp:\n",
    "        l.append(Divergence(p,q, difference=measure))\n",
    "    L.append(l)\n",
    "M = np.array(L)\n",
    "fig = plt.figure()\n",
    "div = pandas.DataFrame(M, columns = fileids_sp, index = fileids_sp)\n",
    "ax = sns.heatmap(div)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 224,
   "id": "0b74d0f1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "measure = 'KS' #\"KL\", \"Chi2\", \"KS\", \"Wasserstein\"\n",
    "num_of_texts = 4 #The bigger this number the slower it will run, you can also try selecting your own plays\n",
    "fileids_sp = list(final_df[:num_of_texts]['ad category'])\n",
    "corpora_sp = list(final_df[:num_of_texts]['normalized_tokens'])\n",
    "\n",
    "#corpora_sp = list(brides_info_2002[1:num_of_texts+1]['normalized_tokens'])\n",
    "\n",
    "L = []\n",
    "for p in corpora_sp:\n",
    "    l = []\n",
    "    for q in corpora_sp:\n",
    "        l.append(Divergence(p,q, difference=measure))\n",
    "    L.append(l)\n",
    "M = np.array(L)\n",
    "fig = plt.figure()\n",
    "div = pandas.DataFrame(M, columns = fileids_sp, index = fileids_sp)\n",
    "ax = sns.heatmap(div)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 225,
   "id": "79619d4e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "measure = 'Wasserstein' #\"KL\", \"Chi2\", \"KS\", \"Wasserstein\"\n",
    "num_of_texts = 4 #The bigger this number the slower it will run, you can also try selecting your own plays\n",
    "fileids_sp = list(final_df[:num_of_texts]['ad category'])\n",
    "corpora_sp = list(final_df[:num_of_texts]['normalized_tokens'])\n",
    "\n",
    "#corpora_sp = list(brides_info_2002[1:num_of_texts+1]['normalized_tokens'])\n",
    "\n",
    "L = []\n",
    "for p in corpora_sp:\n",
    "    l = []\n",
    "    for q in corpora_sp:\n",
    "        l.append(Divergence(p,q, difference=measure))\n",
    "    L.append(l)\n",
    "M = np.array(L)\n",
    "fig = plt.figure()\n",
    "div = pandas.DataFrame(M, columns = fileids_sp, index = fileids_sp)\n",
    "ax = sns.heatmap(div)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c5db2e1e",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "24641fc5",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5477cbbb",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "341199cb",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1d928702",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}