NLP - 01.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# NLP - 01"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "*** Introductory Examples for the NLTK Book ***\n",
      "Loading text1, ..., text9 and sent1, ..., sent9\n",
      "Type the name of the text or sentence to view it.\n",
      "Type: 'texts()' or 'sents()' to list the materials.\n",
      "text1: Moby Dick by Herman Melville 1851\n",
      "text2: Sense and Sensibility by Jane Austen 1811\n",
      "text3: The Book of Genesis\n",
      "text4: Inaugural Address Corpus\n",
      "text5: Chat Corpus\n",
      "text6: Monty Python and the Holy Grail\n",
      "text7: Wall Street Journal\n",
      "text8: Personals Corpus\n",
      "text9: The Man Who Was Thursday by G . K . Chesterton 1908\n"
     ]
    }
   ],
   "source": [
    "from nltk.book import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def lex_div(text):\n",
    "    return len(text)/len(set(text))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def percentage(count, total):\n",
    "    return 100*count/total"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "sent1 = ['Call', 'me', 'Ishmael', '.'] "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(sent1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.0"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lex_div(sent1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "25.0"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "percentage(sent1.count('me'),len(sent1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['The',\n",
       " 'family',\n",
       " 'of',\n",
       " 'Dashwood',\n",
       " 'had',\n",
       " 'long',\n",
       " 'been',\n",
       " 'settled',\n",
       " 'in',\n",
       " 'Sussex',\n",
       " '.']"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sent2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "ex1 = ['Ritz','is', 'learning', 'nlp', 'using', 'nltk']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Ritz', 'is', 'learning', 'nlp', 'nltk', 'using']"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sorted(ex1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ex1.count('n')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['I', 'am', 'learning', 'nlp']"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "['I','am']+['learning','nlp']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Fellow',\n",
       " '-',\n",
       " 'Citizens',\n",
       " 'of',\n",
       " 'the',\n",
       " 'Senate',\n",
       " 'and',\n",
       " 'of',\n",
       " 'the',\n",
       " 'House',\n",
       " 'of',\n",
       " 'Representatives',\n",
       " ':',\n",
       " 'Call',\n",
       " 'me',\n",
       " 'Ishmael',\n",
       " '.']"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sent4 + sent1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "sent1.append(\"Maybe\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Call', 'me', 'Ishmael', '.', 'Maybe']"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sent1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'rights'"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "text4[11111]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1219"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "text4.index('rights')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['boo', '.', 'JOIN', 'PART', 'he', 'drew', 'a', 'girl', 'with']"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "text5[123:132]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['dictatorship',\n",
       " '.',\n",
       " 'A',\n",
       " 'self',\n",
       " '-',\n",
       " 'perpetuating',\n",
       " 'autocracy',\n",
       " 'in',\n",
       " 'which',\n",
       " 'the',\n",
       " 'working',\n",
       " 'classes',\n",
       " '--',\n",
       " 'WOMAN',\n",
       " ':',\n",
       " 'Oh',\n",
       " ',',\n",
       " 'there',\n",
       " 'you',\n",
       " 'go',\n",
       " ',',\n",
       " 'bringing',\n",
       " 'class',\n",
       " 'into',\n",
       " 'it']"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "text6[1500:1525]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "sent = ['1st','2nd','3rd','4th','5th','6th','7th','8th','9th','10th']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'5th'"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sent[4]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'7th'"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sent[6]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['4th', '5th']"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sent[3:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "sent[0] = 'first'\n",
    "sent[9] = 'last'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(sent)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "sent[1:9] = ['second', 'third']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['first', 'second', 'third', 'last']"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sent"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "ename": "IndexError",
     "evalue": "list index out of range",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mIndexError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-28-9d73df3f8677>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0msent\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m9\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;31mIndexError\u001b[0m: list index out of range"
     ]
    }
   ],
   "source": [
    "sent[9]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "19317"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vocab = set(text1)\n",
    "vocab_size = len(vocab)\n",
    "vocab_size"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'e'"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "name = 'Ritesh'\n",
    "name[3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Rites'"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "name[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'RiteshRitesh'"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "name*2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'RiteshK'"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "name + 'K'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Ritesh Kumar'"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "' '.join(['Ritesh', 'Kumar'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Ritesh', 'Kumar']"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "'Ritesh Kumar'.split()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "saying = ['After', 'all', 'is', 'said', 'and', 'done','more', 'is', 'said', 'than', 'done']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "tokens = set(saying)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "tokens = sorted(tokens)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['is', 'more', 'said', 'than']"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tokens[-4:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "fd = FreqDist(text1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "FreqDist({',': 18713, 'the': 13721, '.': 6862, 'of': 6536, 'and': 6024, 'a': 4569, 'to': 4542, ';': 4072, 'in': 3916, 'that': 2982, ...})"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(',', 18713),\n",
       " ('the', 13721),\n",
       " ('.', 6862),\n",
       " ('of', 6536),\n",
       " ('and', 6024),\n",
       " ('a', 4569),\n",
       " ('to', 4542),\n",
       " (';', 4072),\n",
       " ('in', 3916),\n",
       " ('that', 2982),\n",
       " (\"'\", 2684),\n",
       " ('-', 2552),\n",
       " ('his', 2459),\n",
       " ('it', 2209),\n",
       " ('I', 2124),\n",
       " ('s', 1739),\n",
       " ('is', 1695),\n",
       " ('he', 1661),\n",
       " ('with', 1659),\n",
       " ('was', 1632),\n",
       " ('as', 1620),\n",
       " ('\"', 1478),\n",
       " ('all', 1462),\n",
       " ('for', 1414),\n",
       " ('this', 1280),\n",
       " ('!', 1269),\n",
       " ('at', 1231),\n",
       " ('by', 1137),\n",
       " ('but', 1113),\n",
       " ('not', 1103),\n",
       " ('--', 1070),\n",
       " ('him', 1058),\n",
       " ('from', 1052),\n",
       " ('be', 1030),\n",
       " ('on', 1005),\n",
       " ('so', 918),\n",
       " ('whale', 906),\n",
       " ('one', 889),\n",
       " ('you', 841),\n",
       " ('had', 767),\n",
       " ('have', 760),\n",
       " ('there', 715),\n",
       " ('But', 705),\n",
       " ('or', 697),\n",
       " ('were', 680),\n",
       " ('now', 646),\n",
       " ('which', 640),\n",
       " ('?', 637),\n",
       " ('me', 627),\n",
       " ('like', 624),\n",
       " ('The', 612),\n",
       " ('their', 612),\n",
       " ('are', 586),\n",
       " ('they', 586),\n",
       " ('an', 582),\n",
       " ('some', 578),\n",
       " ('then', 571),\n",
       " ('my', 564),\n",
       " ('when', 553),\n",
       " ('upon', 538),\n",
       " ('out', 529),\n",
       " ('into', 520),\n",
       " ('man', 508),\n",
       " ('ship', 507),\n",
       " ('up', 505),\n",
       " ('more', 501),\n",
       " ('Ahab', 501),\n",
       " ('.\"', 489),\n",
       " ('no', 484),\n",
       " ('them', 471),\n",
       " ('ye', 460),\n",
       " ('what', 442),\n",
       " ('old', 436),\n",
       " ('sea', 433),\n",
       " ('would', 421),\n",
       " ('if', 421),\n",
       " ('been', 415),\n",
       " ('we', 413),\n",
       " ('other', 412),\n",
       " ('over', 403),\n",
       " ('these', 381),\n",
       " ('will', 379),\n",
       " ('its', 372),\n",
       " ('And', 369),\n",
       " ('down', 364),\n",
       " ('only', 360),\n",
       " ('such', 336),\n",
       " ('head', 335),\n",
       " ('though', 335),\n",
       " ('boat', 330),\n",
       " ('her', 329),\n",
       " ('time', 324),\n",
       " ('any', 320),\n",
       " ('who', 319),\n",
       " ('long', 318),\n",
       " ('very', 311),\n",
       " ('It', 310),\n",
       " ('than', 309),\n",
       " ('!\"', 305),\n",
       " ('about', 304),\n",
       " ('said', 302),\n",
       " (',\"', 302),\n",
       " ('yet', 300),\n",
       " ('still', 299),\n",
       " ('those', 297),\n",
       " ('before', 293),\n",
       " ('great', 293),\n",
       " ('has', 287),\n",
       " ('two', 285),\n",
       " ('t', 283),\n",
       " ('seemed', 283),\n",
       " ('must', 282),\n",
       " ('Whale', 282),\n",
       " ('most', 277),\n",
       " ('last', 277),\n",
       " ('here', 272),\n",
       " ('way', 269),\n",
       " ('do', 267),\n",
       " ('Stubb', 255),\n",
       " ('again', 254),\n",
       " ('see', 253),\n",
       " ('after', 252),\n",
       " ('?\"', 252),\n",
       " ('Queequeg', 252),\n",
       " ('little', 247),\n",
       " ('did', 246),\n",
       " ('round', 242),\n",
       " ('your', 240),\n",
       " ('whales', 237),\n",
       " ('say', 237),\n",
       " ('In', 237),\n",
       " ('three', 237),\n",
       " ('men', 236),\n",
       " ('thou', 232),\n",
       " ('He', 230),\n",
       " ('may', 230),\n",
       " ('us', 228),\n",
       " ('through', 227),\n",
       " ('every', 222),\n",
       " ('can', 220),\n",
       " ('being', 219),\n",
       " ('much', 218),\n",
       " ('off', 217),\n",
       " ('while', 216),\n",
       " ('could', 215),\n",
       " ('Captain', 215),\n",
       " ('same', 213),\n",
       " ('(', 210),\n",
       " ('first', 210),\n",
       " ('side', 208),\n",
       " ('hand', 205),\n",
       " ('own', 205),\n",
       " ('ever', 203),\n",
       " ('himself', 203),\n",
       " ('our', 199),\n",
       " ('For', 197),\n",
       " ('Starbuck', 196),\n",
       " ('never', 195),\n",
       " ('good', 192),\n",
       " ('white', 191),\n",
       " ('where', 190),\n",
       " ('deck', 189),\n",
       " ('thing', 188),\n",
       " ('how', 187),\n",
       " ('almost', 186),\n",
       " ('water', 185),\n",
       " ('too', 184),\n",
       " ('might', 183),\n",
       " ('go', 182),\n",
       " ('even', 181),\n",
       " ('should', 181),\n",
       " ('made', 178),\n",
       " ('away', 175),\n",
       " ('well', 174),\n",
       " ('What', 174),\n",
       " ('world', 173),\n",
       " ('day', 172),\n",
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       " ('whiteness', 26),\n",
       " ('country', 25),\n",
       " ('king', 25),\n",
       " ('learned', 25),\n",
       " ('carry', 25),\n",
       " ('thrown', 25),\n",
       " ('self', 25),\n",
       " ('front', 25),\n",
       " ('silent', 25),\n",
       " ('leaning', 25),\n",
       " ('believe', 25),\n",
       " ('drawn', 25),\n",
       " ('stop', 25),\n",
       " ('port', 25),\n",
       " ('gods', 25),\n",
       " ('hump', 25),\n",
       " ('cases', 25),\n",
       " ('number', 25),\n",
       " ('added', 25),\n",
       " ('supper', 25),\n",
       " ('interval', 25),\n",
       " ('duty', 25),\n",
       " ('thinking', 25),\n",
       " ('similar', 25),\n",
       " ('skull', 25),\n",
       " ('takes', 25),\n",
       " ('wife', 25),\n",
       " ('alive', 25),\n",
       " ('pilot', 25),\n",
       " ('complete', 25),\n",
       " ('Thus', 25),\n",
       " ('woe', 25),\n",
       " ('bearing', 25),\n",
       " ('friend', 25),\n",
       " ('hinted', 25),\n",
       " ('steady', 25),\n",
       " ('keel', 25),\n",
       " ('cruising', 25),\n",
       " ('fin', 25),\n",
       " ('warm', 24),\n",
       " ('grow', 24),\n",
       " ('eight', 24),\n",
       " ('dart', 24),\n",
       " ('floating', 24),\n",
       " ('seldom', 24),\n",
       " ('love', 24),\n",
       " ('bright', 24),\n",
       " ('Dutch', 24),\n",
       " ('different', 24),\n",
       " ('regular', 24),\n",
       " ('pursuit', 24),\n",
       " ('watery', 24),\n",
       " ('drop', 24),\n",
       " ('orders', 24),\n",
       " ('exactly', 24),\n",
       " ('perils', 24),\n",
       " ('became', 24),\n",
       " ('afterwards', 24),\n",
       " ('midnight', 24),\n",
       " ('swift', 24),\n",
       " ('Of', 24),\n",
       " ('First', 24),\n",
       " ('e', 24),\n",
       " ('ran', 24),\n",
       " ('aside', 24),\n",
       " ('wise', 24),\n",
       " ('beat', 24),\n",
       " ('escape', 24),\n",
       " ('circle', 24),\n",
       " ('spread', 24),\n",
       " ('thyself', 24),\n",
       " ('secret', 24),\n",
       " ('Stand', 24),\n",
       " ('remains', 24),\n",
       " ('hunt', 24),\n",
       " ('St', 24),\n",
       " ('Lakeman', 24),\n",
       " ('sword', 23),\n",
       " ('D', 23),\n",
       " ('Like', 23),\n",
       " ('shore', 23),\n",
       " ('master', 23),\n",
       " ('regarded', 23),\n",
       " ('blows', 23),\n",
       " ('striking', 23),\n",
       " ('honour', 23),\n",
       " ('fore', 23),\n",
       " ('answer', 23),\n",
       " ('following', 23),\n",
       " ('beyond', 23),\n",
       " ('spot', 23),\n",
       " ('nevertheless', 23),\n",
       " ('fiery', 23),\n",
       " ('wall', 23),\n",
       " ('lances', 23),\n",
       " ('flew', 23),\n",
       " ('higher', 23),\n",
       " ('break', 23),\n",
       " ('somewhere', 23),\n",
       " ('hot', 23),\n",
       " ('hidden', 23),\n",
       " ('during', 23),\n",
       " ('Good', 23),\n",
       " ('commanded', 23),\n",
       " ('flesh', 23),\n",
       " ('sweet', 23),\n",
       " ('instead', 23),\n",
       " ('hint', 23),\n",
       " ('headed', 23),\n",
       " ...]"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fd.most_common()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "906"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fd['whale']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fd.plot(50, cumulative=True )"
   ]
  },
  {
   "attachments": {
    "Capture.PNG": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![Capture.PNG](attachment:Capture.PNG)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "v= set(text1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "long_words = [w for w in v if len(w)>15]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['CIRCUMNAVIGATION',\n",
       " 'Physiognomically',\n",
       " 'apprehensiveness',\n",
       " 'cannibalistically',\n",
       " 'characteristically',\n",
       " 'circumnavigating',\n",
       " 'circumnavigation',\n",
       " 'circumnavigations',\n",
       " 'comprehensiveness',\n",
       " 'hermaphroditical',\n",
       " 'indiscriminately',\n",
       " 'indispensableness',\n",
       " 'irresistibleness',\n",
       " 'physiognomically',\n",
       " 'preternaturalness',\n",
       " 'responsibilities',\n",
       " 'simultaneousness',\n",
       " 'subterraneousness',\n",
       " 'supernaturalness',\n",
       " 'superstitiousness',\n",
       " 'uncomfortableness',\n",
       " 'uncompromisedness',\n",
       " 'undiscriminating',\n",
       " 'uninterpenetratingly']"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sorted(long_words)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "medium_words = [w for w in v if len(w)>9 and len(w)<15]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['ADDITIONAL',\n",
       " 'ADVENTURES',\n",
       " 'AFFGHANISTAN',\n",
       " 'APPLICATION',\n",
       " 'APPROACHING',\n",
       " 'Abominable',\n",
       " 'Accordingly',\n",
       " 'Advancement',\n",
       " 'Adventures',\n",
       " 'Affrighted',\n",
       " 'Afterwards',\n",
       " 'Aldrovandi',\n",
       " 'Aldrovandus',\n",
       " 'Alexanders',\n",
       " 'Alleghanian',\n",
       " 'Alleghanies',\n",
       " 'Ambergriese',\n",
       " 'Anacharsis',\n",
       " 'Archbishop',\n",
       " 'Archipelagoes',\n",
       " 'Arsacidean',\n",
       " 'Asphaltites',\n",
       " 'Australian',\n",
       " 'BLACKSMITH',\n",
       " 'BLACKSTONE',\n",
       " 'BREAKWATER',\n",
       " 'Babylonian',\n",
       " 'Bartholomew',\n",
       " 'Basilosaurus',\n",
       " 'Belisarius',\n",
       " 'Belshazzar',\n",
       " 'Biographical',\n",
       " 'Blacksmith',\n",
       " 'Blackstone',\n",
       " 'Blocksburg',\n",
       " 'Bonapartes',\n",
       " 'Bonneterre',\n",
       " 'Brighggians',\n",
       " 'Bulkington',\n",
       " 'CHRONICLER',\n",
       " 'COMMERCIAL',\n",
       " 'CONVERSATIONS',\n",
       " 'Californian',\n",
       " 'Canterbury',\n",
       " 'Capricornus',\n",
       " 'Champollion',\n",
       " 'Charlemagne',\n",
       " 'Chartering',\n",
       " 'Christendom',\n",
       " 'Christianity',\n",
       " 'Christians',\n",
       " 'Circassian',\n",
       " 'Circumambulate',\n",
       " 'Commanders',\n",
       " 'Commodores',\n",
       " 'Commonwealth',\n",
       " 'Concerning',\n",
       " 'Congregation',\n",
       " 'Congregational',\n",
       " 'Connecticut',\n",
       " 'Consequently',\n",
       " 'Considering',\n",
       " 'Constantine',\n",
       " 'Constantinople',\n",
       " 'Consumptive',\n",
       " 'Continents',\n",
       " 'Contrasted',\n",
       " 'Conversation',\n",
       " 'Convulsively',\n",
       " 'Copenhagen',\n",
       " 'Corinthians',\n",
       " 'Coronation',\n",
       " 'Corresponding',\n",
       " 'Counterpane',\n",
       " 'DICTIONARY',\n",
       " 'DISSECTION',\n",
       " 'DUODECIMOES',\n",
       " 'Dardanelles',\n",
       " 'Darmonodes',\n",
       " 'Decapitation',\n",
       " 'Deliberately',\n",
       " 'Delightful',\n",
       " 'Descartian',\n",
       " 'Descending',\n",
       " 'Desecrated',\n",
       " 'Desolation',\n",
       " 'Despairing',\n",
       " 'Deuteronomy',\n",
       " 'Dorchester',\n",
       " 'Dunfermline',\n",
       " 'Duodecimoes',\n",
       " 'EMBONPOINT',\n",
       " 'ERROMANGOAN',\n",
       " 'EXCHANGING',\n",
       " 'Ecclesiastes',\n",
       " 'Ellenborough',\n",
       " 'Emblazonings',\n",
       " 'Emboldened',\n",
       " 'Englishman',\n",
       " 'Englishmen',\n",
       " 'Entreaties',\n",
       " 'Equatorial',\n",
       " 'Erromanggoans',\n",
       " 'Eternities',\n",
       " 'Euroclydon',\n",
       " 'Evangelist',\n",
       " 'Evangelists',\n",
       " 'Expedition',\n",
       " 'Expeditions',\n",
       " 'FORECASTLE',\n",
       " 'Ferdinando',\n",
       " 'Floundered',\n",
       " 'Forecastle',\n",
       " 'Furthermore',\n",
       " 'Gallipagos',\n",
       " 'Geological',\n",
       " 'Greenlanders',\n",
       " 'Greenlandmen',\n",
       " 'Guernseyman',\n",
       " 'HARPOONEERS',\n",
       " 'HEREABOUTS',\n",
       " 'HORIZONTAL',\n",
       " 'Hanoverian',\n",
       " 'Hardicanutes',\n",
       " 'Harmattans',\n",
       " 'Harpooneer',\n",
       " 'Hearkening',\n",
       " 'Heidelburgh',\n",
       " 'Herculaneum',\n",
       " 'Himmalehan',\n",
       " 'Historians',\n",
       " 'Historically',\n",
       " 'Hogarthian',\n",
       " 'Hollanders',\n",
       " 'Holofernes',\n",
       " 'Hoveringly',\n",
       " 'Humiliation',\n",
       " 'Hyperborean',\n",
       " 'Immediately',\n",
       " 'Immemorial',\n",
       " 'Impenetrable',\n",
       " 'Impossible',\n",
       " 'Inquisition',\n",
       " 'Insufferable',\n",
       " 'Interweaving',\n",
       " 'Intolerably',\n",
       " 'Israelites',\n",
       " 'Kentuckian',\n",
       " 'Krusenstern',\n",
       " 'Krusensterns',\n",
       " 'LENGTHWISE',\n",
       " 'Langsdorff',\n",
       " 'Laplandish',\n",
       " 'Leuwenhoeck',\n",
       " 'Leviathanic',\n",
       " 'Leviathanism',\n",
       " 'Leviathans',\n",
       " 'Lieutenant',\n",
       " 'Loveliness',\n",
       " 'MISSIONARY',\n",
       " 'MONTGOMERY',\n",
       " 'MYSTERIOUS',\n",
       " 'Macrocephalus',\n",
       " 'Magnanimous',\n",
       " 'Manchester',\n",
       " 'Manhattoes',\n",
       " 'Massachusetts',\n",
       " 'Measurement',\n",
       " 'Mediterranean',\n",
       " 'Melancthon',\n",
       " 'Mesopotamian',\n",
       " 'Methuselah',\n",
       " 'Mississippi',\n",
       " 'Mississippies',\n",
       " 'Monongahela',\n",
       " 'Mysteriously',\n",
       " 'Mysticetus',\n",
       " 'NATURALIST',\n",
       " 'Nantucketer',\n",
       " 'Nantucketers',\n",
       " 'Nantuckois',\n",
       " 'Narragansett',\n",
       " 'Netherlands',\n",
       " 'Nevertheless',\n",
       " 'Newfoundland',\n",
       " 'Observatory',\n",
       " 'Originally',\n",
       " 'Overhearing',\n",
       " 'PARLIAMENT',\n",
       " 'PORTUGUESE',\n",
       " 'PRESIDENCY',\n",
       " 'Pannangians',\n",
       " 'Pantheistic',\n",
       " 'Pantheists',\n",
       " 'Paracelsan',\n",
       " 'Paracelsus',\n",
       " 'Parliament',\n",
       " 'Patagonian',\n",
       " 'Pedestrians',\n",
       " 'Penetrating',\n",
       " 'Philippine',\n",
       " 'Philistine',\n",
       " 'Philistines',\n",
       " 'Philologically',\n",
       " 'Philopater',\n",
       " 'Phrenologist',\n",
       " 'Physiognomist',\n",
       " 'Physiognomy',\n",
       " 'Pitchpoling',\n",
       " 'Platonists',\n",
       " 'Polynesian',\n",
       " 'Polynesians',\n",
       " 'Pontoppodan',\n",
       " 'Portuguese',\n",
       " 'Possession',\n",
       " 'Postscript',\n",
       " 'Pottowottamie',\n",
       " 'Praetorians',\n",
       " 'Presbyterian',\n",
       " 'Presbyterians',\n",
       " 'Preserving',\n",
       " 'Preternatural',\n",
       " 'Projecting',\n",
       " 'Prometheus',\n",
       " 'Protestant',\n",
       " 'Providence',\n",
       " 'Pythagoras',\n",
       " 'Pythagorean',\n",
       " 'RESPECTABLE',\n",
       " 'RICHARDSON',\n",
       " 'Remembering',\n",
       " 'Rensselaers',\n",
       " 'Republican',\n",
       " 'Respectively',\n",
       " 'Retreating',\n",
       " 'Retribution',\n",
       " 'Righteousness',\n",
       " 'Ripplingly',\n",
       " 'Rondeletius',\n",
       " 'SKRIMSHANDER',\n",
       " 'SPERMACETI',\n",
       " 'SPITZBERGEN',\n",
       " 'Sagittarius',\n",
       " 'Scandinavian',\n",
       " 'Schmerenburgh',\n",
       " 'Schoolmasters',\n",
       " 'Scriptural',\n",
       " 'Scriptures',\n",
       " 'Shakespeare',\n",
       " 'Skrimshander',\n",
       " 'Smeerenberg',\n",
       " 'Smithfield',\n",
       " 'Southerner',\n",
       " 'Specksioneer',\n",
       " 'Specksynder',\n",
       " 'Spermaceti',\n",
       " 'Spermacetti',\n",
       " 'Spitzbergen',\n",
       " 'Stammering',\n",
       " 'Straightway',\n",
       " 'Suppression',\n",
       " 'Swackhammer',\n",
       " 'TAMBOURINE',\n",
       " 'Temperance',\n",
       " 'Throttling',\n",
       " 'Throughout',\n",
       " 'Thundering',\n",
       " 'Tongatobooarrs',\n",
       " 'Tormentoto',\n",
       " 'Tranquilly',\n",
       " 'Transported',\n",
       " 'UNPUBLISHED',\n",
       " 'Ultimately',\n",
       " 'Unappalled',\n",
       " 'Uncommonly',\n",
       " 'Unconsciously',\n",
       " 'Unerringly',\n",
       " 'Unicornism',\n",
       " 'Unobserved',\n",
       " 'Unwittingly',\n",
       " 'Valparaiso',\n",
       " 'Vehemently',\n",
       " 'Venetianly',\n",
       " 'Vermonters',\n",
       " 'Versailles',\n",
       " 'Vineyarder',\n",
       " 'WHALESHIPS',\n",
       " 'Washington',\n",
       " 'Wellington',\n",
       " 'Wheelbarrow',\n",
       " 'Whirlpooles',\n",
       " 'Whitsuntide',\n",
       " 'Willoughby',\n",
       " 'Wonderfullest',\n",
       " 'Zealanders',\n",
       " '_____________',\n",
       " 'abandonedly',\n",
       " 'abandonment',\n",
       " 'abbreviate',\n",
       " 'abbreviation',\n",
       " 'abhorrence',\n",
       " 'abominable',\n",
       " 'abominated',\n",
       " 'abomination',\n",
       " 'aboriginal',\n",
       " 'aboriginally',\n",
       " 'aboriginalness',\n",
       " 'aboundingly',\n",
       " 'absolutely',\n",
       " 'absorbingly',\n",
       " 'abstemious',\n",
       " 'abstinence',\n",
       " 'abstracted',\n",
       " 'abstraction',\n",
       " 'abundantly',\n",
       " 'accelerate',\n",
       " 'accelerated',\n",
       " 'accelerating',\n",
       " 'accessible',\n",
       " 'accidental',\n",
       " 'accidentally',\n",
       " 'accommodate',\n",
       " 'accommodated',\n",
       " 'accommodation',\n",
       " 'accompanied',\n",
       " 'accompanies',\n",
       " 'accompaniments',\n",
       " 'accompanying',\n",
       " 'accomplish',\n",
       " 'accomplished',\n",
       " 'accomplishing',\n",
       " 'accomplishment',\n",
       " 'accordance',\n",
       " 'accordingly',\n",
       " 'accountable',\n",
       " 'accountants',\n",
       " 'accounting',\n",
       " 'accumulate',\n",
       " 'accumulated',\n",
       " 'accumulating',\n",
       " 'accurately',\n",
       " 'accustomed',\n",
       " 'acerbities',\n",
       " 'acknowledges',\n",
       " 'acknowledging',\n",
       " 'acquaintance',\n",
       " 'acquaintances',\n",
       " 'acquainted',\n",
       " 'acquiesced',\n",
       " 'acquiescence',\n",
       " 'additional',\n",
       " 'addressing',\n",
       " 'adequately',\n",
       " 'adhesiveness',\n",
       " 'admeasurement',\n",
       " 'admeasurements',\n",
       " 'administered',\n",
       " 'administering',\n",
       " 'admonished',\n",
       " 'admonishing',\n",
       " 'admonitions',\n",
       " 'admonitory',\n",
       " 'adolescence',\n",
       " 'advantages',\n",
       " 'adventures',\n",
       " 'adventurous',\n",
       " 'adventurously',\n",
       " 'advertised',\n",
       " 'aesthetically',\n",
       " 'aesthetics',\n",
       " 'affectionate',\n",
       " 'affectionately',\n",
       " 'affinities',\n",
       " 'affirmative',\n",
       " 'afflictions',\n",
       " 'affrighted',\n",
       " 'aforethought',\n",
       " 'afternoons',\n",
       " 'afterwards',\n",
       " 'aggregated',\n",
       " 'aggregation',\n",
       " 'aggregations',\n",
       " 'agonizingly',\n",
       " 'albatrosses',\n",
       " 'allegiance',\n",
       " 'allegorical',\n",
       " 'allowances',\n",
       " 'allurements',\n",
       " 'alluringly',\n",
       " 'alternately',\n",
       " 'alternating',\n",
       " 'altogether',\n",
       " 'amphibious',\n",
       " 'amputating',\n",
       " 'amputation',\n",
       " 'amputations',\n",
       " 'analogical',\n",
       " 'anatomical',\n",
       " 'ancestress',\n",
       " 'ancientest',\n",
       " 'annihilated',\n",
       " 'annihilating',\n",
       " 'annihilation',\n",
       " 'announcement',\n",
       " 'announcing',\n",
       " 'annuitants',\n",
       " 'anomalously',\n",
       " 'antagonistic',\n",
       " 'antecedent',\n",
       " 'antediluvian',\n",
       " 'antemosaic',\n",
       " 'antichronical',\n",
       " 'anticipated',\n",
       " 'anticipatingly',\n",
       " 'anticipation',\n",
       " 'anticipative',\n",
       " 'antiquities',\n",
       " 'apoplectic',\n",
       " 'apothecary',\n",
       " 'apotheosis',\n",
       " 'appallingly',\n",
       " 'apparelled',\n",
       " 'apparently',\n",
       " 'apparition',\n",
       " 'appearance',\n",
       " 'appearances',\n",
       " 'appellation',\n",
       " 'appellations',\n",
       " 'appellative',\n",
       " 'applicable',\n",
       " 'application',\n",
       " 'appointments',\n",
       " 'apportioned',\n",
       " 'appreciative',\n",
       " 'apprehension',\n",
       " 'apprehensions',\n",
       " 'approached',\n",
       " 'approaches',\n",
       " 'approaching',\n",
       " 'appropriate',\n",
       " 'appropriated',\n",
       " 'approvingly',\n",
       " 'approximate',\n",
       " 'archaeological',\n",
       " 'archaeologists',\n",
       " 'archangelic',\n",
       " 'archangelical',\n",
       " 'archangels',\n",
       " 'archbishopric',\n",
       " 'archipelagoes',\n",
       " 'architects',\n",
       " 'architecture',\n",
       " 'arithmetic',\n",
       " 'arrangement',\n",
       " 'articulated',\n",
       " 'artificial',\n",
       " 'artificially',\n",
       " 'artificialness',\n",
       " 'ascendency',\n",
       " 'ascertained',\n",
       " 'ascertaining',\n",
       " 'ascribable',\n",
       " 'ascriptions',\n",
       " 'aspirations',\n",
       " 'assailable',\n",
       " 'assailants',\n",
       " 'assignment',\n",
       " 'assistance',\n",
       " 'assistants',\n",
       " 'associated',\n",
       " 'associates',\n",
       " 'associations',\n",
       " 'assumption',\n",
       " 'astonished',\n",
       " 'astonishing',\n",
       " 'astonishment',\n",
       " 'astrological',\n",
       " 'astronomers',\n",
       " 'astronomical',\n",
       " 'atheistical',\n",
       " 'athwartships',\n",
       " 'atmosphere',\n",
       " 'atmospheres',\n",
       " 'atmospheric',\n",
       " 'attainable',\n",
       " 'attendance',\n",
       " 'attentively',\n",
       " 'attenuated',\n",
       " 'attestation',\n",
       " 'attraction',\n",
       " 'authenticated',\n",
       " 'authoritative',\n",
       " 'authorities',\n",
       " 'authorized',\n",
       " 'awkwardness',\n",
       " 'background',\n",
       " 'backwardly',\n",
       " 'backwoodsman',\n",
       " 'bamboozingly',\n",
       " 'bannisters',\n",
       " 'banteringly',\n",
       " 'banterings',\n",
       " 'barbarians',\n",
       " 'bashfulness',\n",
       " 'battalions',\n",
       " 'bedeadened',\n",
       " 'bedevilling',\n",
       " 'bedfellows',\n",
       " 'bedraggled',\n",
       " 'beefsteaks',\n",
       " 'befriended',\n",
       " 'befriending',\n",
       " 'benediction',\n",
       " 'benevolence',\n",
       " 'benevolent',\n",
       " 'benevolently',\n",
       " 'bequeathed',\n",
       " 'beseeching',\n",
       " 'bespattering',\n",
       " 'bespeaking',\n",
       " 'bestirring',\n",
       " 'bestreaked',\n",
       " 'bethinking',\n",
       " 'betokening',\n",
       " 'bewildered',\n",
       " 'bewildering',\n",
       " 'bewitching',\n",
       " 'bitterness',\n",
       " 'blackberrying',\n",
       " 'blacksmith',\n",
       " 'blacksmiths',\n",
       " 'blameworthy',\n",
       " 'blandishments',\n",
       " 'blanketing',\n",
       " 'blasphemer',\n",
       " 'blasphemous',\n",
       " 'blisteringly',\n",
       " 'bloodthirsty',\n",
       " 'blubbering',\n",
       " 'blundering',\n",
       " 'boatheader',\n",
       " 'boisterous',\n",
       " 'boisterously',\n",
       " 'bolstering',\n",
       " 'bookbinder',\n",
       " 'bottomless',\n",
       " 'bountifully',\n",
       " 'brawniness',\n",
       " 'breadfruit',\n",
       " 'breakfasting',\n",
       " 'breastband',\n",
       " 'breathless',\n",
       " 'breathlessly',\n",
       " 'breezeless',\n",
       " 'breezelessness',\n",
       " 'bridegroom',\n",
       " 'bridegrooms',\n",
       " 'brigandish',\n",
       " 'brightness',\n",
       " 'brilliance',\n",
       " 'brilliancy',\n",
       " 'brotherhood',\n",
       " 'bubblingly',\n",
       " 'burglaries',\n",
       " 'burstingly',\n",
       " 'butchering',\n",
       " 'butterflies',\n",
       " 'butterless',\n",
       " 'buttressed',\n",
       " 'bystanders',\n",
       " 'cabalistical',\n",
       " 'cabalistically',\n",
       " 'cabalistics',\n",
       " 'calamities',\n",
       " 'calculated',\n",
       " 'calculating',\n",
       " 'calculation',\n",
       " 'camphorated',\n",
       " 'candelabra',\n",
       " 'candidates',\n",
       " 'cannibalism',\n",
       " 'cannibally',\n",
       " 'canonicals',\n",
       " 'capricious',\n",
       " 'capriciously',\n",
       " 'capsizings',\n",
       " 'carelessly',\n",
       " 'carelessness',\n",
       " 'carnivorous',\n",
       " 'carpenters',\n",
       " 'casualties',\n",
       " 'catastrophe',\n",
       " 'caterpillar',\n",
       " 'cathedrals',\n",
       " 'cautiously',\n",
       " 'cautiousness',\n",
       " 'celebrated',\n",
       " 'celebration',\n",
       " 'cemeteries',\n",
       " 'centralization',\n",
       " 'centrepiece',\n",
       " 'cerebellum',\n",
       " 'ceremonial',\n",
       " 'ceremonies',\n",
       " 'certainties',\n",
       " 'cetological',\n",
       " 'changeless',\n",
       " 'characteristic',\n",
       " 'characterized',\n",
       " 'characterizing',\n",
       " 'characters',\n",
       " 'charitable',\n",
       " 'charmingly',\n",
       " 'chastisements',\n",
       " 'chattering',\n",
       " 'cheerfully',\n",
       " 'cheerfulness',\n",
       " 'cheeseries',\n",
       " 'cherishing',\n",
       " 'childlessness',\n",
       " 'chirography',\n",
       " 'chivalrous',\n",
       " 'christened',\n",
       " 'christenings',\n",
       " 'chronically',\n",
       " 'chronicled',\n",
       " 'chronicler',\n",
       " 'chronicles',\n",
       " 'chronometer',\n",
       " 'churchyard',\n",
       " 'circulates',\n",
       " 'circulating',\n",
       " 'circulation',\n",
       " 'circumambient',\n",
       " 'circumference',\n",
       " 'circumferences',\n",
       " 'circumpolar',\n",
       " 'circumspect',\n",
       " 'circumspection',\n",
       " 'circumspectly',\n",
       " 'circumstance',\n",
       " 'circumstanced',\n",
       " 'circumstances',\n",
       " 'circumstantial',\n",
       " 'circumventing',\n",
       " 'circumvention',\n",
       " 'civilization',\n",
       " 'classification',\n",
       " 'clattering',\n",
       " 'cleanliest',\n",
       " 'cloistered',\n",
       " 'clustering',\n",
       " 'coalescing',\n",
       " 'cobblestones',\n",
       " 'cognisable',\n",
       " 'coincident',\n",
       " 'coincidings',\n",
       " 'collateral',\n",
       " 'collectedness',\n",
       " 'collecting',\n",
       " 'collection',\n",
       " 'collectively',\n",
       " 'collegians',\n",
       " 'colonnades',\n",
       " 'colourless',\n",
       " 'combination',\n",
       " 'combinations',\n",
       " 'combinedly',\n",
       " 'comfortable',\n",
       " 'comfortably',\n",
       " 'comforters',\n",
       " 'comforting',\n",
       " 'commanders',\n",
       " 'commanding',\n",
       " 'commandingly',\n",
       " 'commandment',\n",
       " 'commentaries',\n",
       " 'commentator',\n",
       " 'commentators',\n",
       " 'commenting',\n",
       " 'commercial',\n",
       " 'commissioned',\n",
       " 'committing',\n",
       " 'commodores',\n",
       " 'commonalty',\n",
       " 'commonplaces',\n",
       " 'commotions',\n",
       " 'communicated',\n",
       " 'communicates',\n",
       " 'communicating',\n",
       " 'communication',\n",
       " 'communications',\n",
       " 'communities',\n",
       " 'compactness',\n",
       " 'companionable',\n",
       " 'companions',\n",
       " 'companionship',\n",
       " 'companionway',\n",
       " 'comparable',\n",
       " 'comparative',\n",
       " 'comparatively',\n",
       " 'comparison',\n",
       " 'compassion',\n",
       " 'compendious',\n",
       " 'compensated',\n",
       " 'competency',\n",
       " 'compilations',\n",
       " 'complacent',\n",
       " 'complained',\n",
       " 'complaints',\n",
       " 'complement',\n",
       " 'completely',\n",
       " 'completing',\n",
       " 'completion',\n",
       " 'complexion',\n",
       " 'complexioned',\n",
       " 'compliance',\n",
       " 'complicated',\n",
       " 'compliment',\n",
       " 'complimentary',\n",
       " 'complimented',\n",
       " 'compliments',\n",
       " 'compounded',\n",
       " 'comprehend',\n",
       " 'comprehended',\n",
       " 'comprehending',\n",
       " 'comprehensible',\n",
       " 'comprehension',\n",
       " 'comprehensive',\n",
       " 'comprising',\n",
       " 'compunctions',\n",
       " 'conceivable',\n",
       " 'concentrate',\n",
       " 'concentrated',\n",
       " 'concentrating',\n",
       " 'concentration',\n",
       " 'concentrations',\n",
       " 'concentred',\n",
       " 'concentric',\n",
       " 'conception',\n",
       " 'conceptions',\n",
       " 'concerning',\n",
       " 'concernment',\n",
       " 'concernments',\n",
       " 'conciliating',\n",
       " 'concluding',\n",
       " 'conclusion',\n",
       " 'concubines',\n",
       " 'concurring',\n",
       " 'concussion',\n",
       " 'concussions',\n",
       " 'condemning',\n",
       " 'condensation',\n",
       " 'condescending',\n",
       " 'condescension',\n",
       " 'conducting',\n",
       " 'confabulations',\n",
       " 'confederate',\n",
       " 'confession',\n",
       " 'confidence',\n",
       " 'confidential',\n",
       " 'confidentially',\n",
       " 'confidently',\n",
       " 'confinement',\n",
       " 'confirmation',\n",
       " 'conflagration',\n",
       " 'conflagrations',\n",
       " 'conflicting',\n",
       " 'confounded',\n",
       " 'confoundedly',\n",
       " 'confounding',\n",
       " 'confronted',\n",
       " 'congenialities',\n",
       " 'congeniality',\n",
       " 'congratulate',\n",
       " 'congregate',\n",
       " 'congregated',\n",
       " 'congregation',\n",
       " 'conjectures',\n",
       " 'conjunctures',\n",
       " 'connecting',\n",
       " 'connection',\n",
       " 'connexions',\n",
       " 'conquering',\n",
       " 'conscience',\n",
       " 'consciences',\n",
       " 'conscientious',\n",
       " 'consciously',\n",
       " 'consciousness',\n",
       " 'consecrated',\n",
       " 'consecrating',\n",
       " 'consecutive',\n",
       " 'consequence',\n",
       " 'consequences',\n",
       " 'consequent',\n",
       " 'consequently',\n",
       " 'conservatories',\n",
       " 'considerable',\n",
       " 'considerably',\n",
       " 'consideration',\n",
       " 'considerations',\n",
       " 'considered',\n",
       " 'considering',\n",
       " 'consistence',\n",
       " 'consistency',\n",
       " 'consisting',\n",
       " 'consolation',\n",
       " 'consolatory',\n",
       " 'conspicuous',\n",
       " 'conspicuously',\n",
       " 'constantly',\n",
       " 'constellation',\n",
       " 'constellations',\n",
       " 'consternation',\n",
       " 'consternations',\n",
       " 'constituents',\n",
       " 'constituting',\n",
       " 'constitution',\n",
       " 'constitutional',\n",
       " 'constrained',\n",
       " 'constrainings',\n",
       " 'constraint',\n",
       " 'constructed',\n",
       " 'construction',\n",
       " 'consulting',\n",
       " 'containing',\n",
       " 'contemplating',\n",
       " 'contemplation',\n",
       " 'contemplations',\n",
       " 'contemplative',\n",
       " 'contemporary',\n",
       " 'contemptible',\n",
       " 'contemptibly',\n",
       " 'contemptuously',\n",
       " 'contending',\n",
       " 'contentedly',\n",
       " 'contenting',\n",
       " 'contiguity',\n",
       " 'continental',\n",
       " 'continents',\n",
       " 'contingencies',\n",
       " 'contingency',\n",
       " 'contingent',\n",
       " 'continually',\n",
       " 'continuation',\n",
       " 'continuing',\n",
       " 'continuous',\n",
       " 'continuously',\n",
       " 'contortions',\n",
       " 'contraband',\n",
       " 'contracted',\n",
       " 'contracting',\n",
       " 'contraction',\n",
       " 'contradict',\n",
       " 'contradicted',\n",
       " 'contradiction',\n",
       " 'contradictory',\n",
       " 'contrasting',\n",
       " 'contrastingly',\n",
       " 'contribute',\n",
       " 'contributed',\n",
       " 'contributes',\n",
       " 'contributory',\n",
       " 'contrivance',\n",
       " 'contrivances',\n",
       " 'controllable',\n",
       " 'controlling',\n",
       " 'controversies',\n",
       " 'controverted',\n",
       " 'contusions',\n",
       " 'convalescence',\n",
       " 'convalescing',\n",
       " 'convenience',\n",
       " 'conveniences',\n",
       " 'convenient',\n",
       " 'conveniently',\n",
       " 'conventional',\n",
       " 'conversant',\n",
       " 'conversation',\n",
       " 'convertible',\n",
       " 'conveyance',\n",
       " 'convictions',\n",
       " 'convolutions',\n",
       " 'convulsive',\n",
       " 'convulsively',\n",
       " 'corkscrewed',\n",
       " 'coronation',\n",
       " 'coronations',\n",
       " 'corporeally',\n",
       " 'corpulence',\n",
       " 'corpusants',\n",
       " 'correspond',\n",
       " 'correspondence',\n",
       " 'corresponding',\n",
       " 'corresponds',\n",
       " 'corroborated',\n",
       " 'corroborative',\n",
       " 'corruption',\n",
       " 'cosmopolite',\n",
       " 'costermongers',\n",
       " 'counsellors',\n",
       " 'countenance',\n",
       " 'counteracted',\n",
       " 'counteracting',\n",
       " 'counterbalance',\n",
       " 'counterfeit',\n",
       " 'counterpane',\n",
       " 'counterpart',\n",
       " 'counterpoise',\n",
       " 'countersinkers',\n",
       " 'countersinking',\n",
       " 'countersunk',\n",
       " 'countryman',\n",
       " 'countrymen',\n",
       " 'courageous',\n",
       " 'courageousness',\n",
       " 'courteously',\n",
       " 'creativeness',\n",
       " 'credentials',\n",
       " 'credulities',\n",
       " 'creepingly',\n",
       " 'crescentic',\n",
       " 'critically',\n",
       " 'crookedness',\n",
       " 'crosslights',\n",
       " 'crucifixion',\n",
       " 'crystalline',\n",
       " 'crystallized',\n",
       " 'cudgelling',\n",
       " 'cultivated',\n",
       " 'cupbearers',\n",
       " 'curiousness',\n",
       " 'curvetting',\n",
       " 'cylindrically',\n",
       " 'cymballing',\n",
       " 'daintiness',\n",
       " 'dauntlessness',\n",
       " 'dazzlingly',\n",
       " 'deadliness',\n",
       " 'deadreckoning',\n",
       " 'decapitated',\n",
       " 'decapitating',\n",
       " 'deceitfully',\n",
       " 'deceitfulness',\n",
       " 'deciphered',\n",
       " 'decoration',\n",
       " 'dedicating',\n",
       " 'dedication',\n",
       " 'deepeningly',\n",
       " 'defendants',\n",
       " 'deferential',\n",
       " 'deficiencies',\n",
       " 'deficiency',\n",
       " 'defilements',\n",
       " 'definition',\n",
       " 'deformities',\n",
       " 'degenerated',\n",
       " 'delectable',\n",
       " 'deliberate',\n",
       " 'deliberated',\n",
       " 'deliberately',\n",
       " 'deliberating',\n",
       " 'delicately',\n",
       " 'deliciousness',\n",
       " 'delightful',\n",
       " 'delightfully',\n",
       " 'delineations',\n",
       " 'deliriously',\n",
       " 'deliverance',\n",
       " 'demigorgon',\n",
       " 'democratic',\n",
       " 'demonstrable',\n",
       " 'demonstrate',\n",
       " 'demonstrations',\n",
       " 'denominate',\n",
       " 'denominated',\n",
       " 'denominating',\n",
       " 'dentistical',\n",
       " 'denunciations',\n",
       " 'department',\n",
       " 'departments',\n",
       " 'deplorably',\n",
       " 'deprecating',\n",
       " 'deprecatory',\n",
       " 'depreciates',\n",
       " 'depression',\n",
       " 'depressions',\n",
       " 'deputation',\n",
       " 'descendants',\n",
       " 'descending',\n",
       " 'describing',\n",
       " 'description',\n",
       " 'descriptively',\n",
       " 'designated',\n",
       " 'designates',\n",
       " 'designation',\n",
       " 'desolateness',\n",
       " 'desolation',\n",
       " 'despairing',\n",
       " 'despatched',\n",
       " ...]"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sorted(medium_words)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "v2 = set(text4)\n",
    "long_words2 = [w for w in v2 if len(w)>15]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['RESPONSIBILITIES',\n",
       " 'antiphilosophists',\n",
       " 'constitutionally',\n",
       " 'contradistinction',\n",
       " 'discountenancing',\n",
       " 'disqualification',\n",
       " 'enthusiastically',\n",
       " 'instrumentalities',\n",
       " 'internationality',\n",
       " 'irresponsibility',\n",
       " 'misappropriation',\n",
       " 'misrepresentation',\n",
       " 'misunderstanding',\n",
       " 'responsibilities',\n",
       " 'sentimentalizing',\n",
       " 'transcontinental',\n",
       " 'uncharitableness',\n",
       " 'unconstitutional']"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sorted(long_words2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['!!!!!!!!!!!!!!!!',\n",
       " '!!!!!!!!!!!!!!!!!!!!!!',\n",
       " '!!!!!!!!!!!!!!!!!!!!!!!',\n",
       " '!!!!!!!!!!!!!!!!!!!!!!!!!!!',\n",
       " '!!!!!!!!!!!!!!!!!!!!!!!!!!!!',\n",
       " '!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!',\n",
       " '#talkcity_adults',\n",
       " '(((((((((((((((((',\n",
       " '((((((((((((((((((',\n",
       " '((((((((((((((((((((',\n",
       " '(((((((((((((((((((((',\n",
       " '(((((((((((((((((((((((',\n",
       " '((((((((((((((((((((((((',\n",
       " '(((((((((((((((((((((((((',\n",
       " '((((((((((((((((((((((((((',\n",
       " ')))))))))))))))))',\n",
       " ')))))))))))))))))))',\n",
       " ')))))))))))))))))))))',\n",
       " '))))))))))))))))))))))',\n",
       " '))))))))))))))))))))))))))))',\n",
       " ')))))))))))))))))))))))))))))))',\n",
       " '--------------------',\n",
       " '.(..(.vMp3 v1.7.4.).)',\n",
       " '.(..(.vMp3 vi.p.t.)..).',\n",
       " '................',\n",
       " '..................',\n",
       " '...................',\n",
       " '....................',\n",
       " '........................',\n",
       " '..............................',\n",
       " '.A.n.a.c.?.n.?.a.',\n",
       " '//www.wunderground.com/cgi-bin/findweather/getForecast?query=95953#FIR',\n",
       " '<3333333333333333',\n",
       " '<33333333333333333',\n",
       " 'BAAAAALLLLLLLLIIIIIIINNNNNNNNNNN',\n",
       " 'Bloooooooooooood',\n",
       " 'HHEEYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYY',\n",
       " 'HolocaustYourMom',\n",
       " 'Mooooooooooooooooooooooooooo',\n",
       " 'Nooooooooooooooo',\n",
       " 'WEEEEEEEEEEEEEEEEEE',\n",
       " '[[[[[[[[[[[[[[[[[[',\n",
       " ']]]]]]]]]]]]]]]]]]]]]',\n",
       " 'aaaaaaaaaaaaaaaaa',\n",
       " 'agurlwithbigguns',\n",
       " 'aiiiiiiiiiiiiiiiiiiiiiiii',\n",
       " 'anyyyyyyyyyyyyyyyyy',\n",
       " 'backfrontsidewaysandallaroundtheworld',\n",
       " 'bbbbbyyyyyyyeeeeeeeee',\n",
       " 'boooooooooooglyyyyyy',\n",
       " 'bwahahahahahahahahahaha',\n",
       " 'cooooooooookiiiiiiiiiiiieeeeeeeeeeee',\n",
       " 'eeeeeeeeewwwwwwww',\n",
       " 'grrrrrrrrrrrrrrrrr',\n",
       " 'hahahahahahahahahahahahahahahaha',\n",
       " 'heeheeheeheeheehee',\n",
       " 'heyyyyyyyyyyyyyy',\n",
       " 'http://forums.talkcity.com/tc-adults/start ',\n",
       " 'http://www.shadowbots.com',\n",
       " 'huuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuugZ',\n",
       " 'iamahotniplickme',\n",
       " 'iamahotnipwithhotnippics',\n",
       " 'iamahotnipwithpics',\n",
       " 'lllllllliiiiiiiiiikeee',\n",
       " 'llloooozzzzeeerrrrzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzz',\n",
       " 'miiiiiiiiiiiiinnnnnnnnnnneeeeeeeeee',\n",
       " 'miiiiiinnnnnnnnnneeeeeeee',\n",
       " 'mikeeeeeeeeeeeeeeeeeeeeeeeeee',\n",
       " 'mmmmmmmmiiiiiiiiinnnnnnnnneeeeeeee',\n",
       " 'muahssssssssssssssss',\n",
       " 'muahsssssssssssssssssss',\n",
       " 'niteeeeeeeeeeeeeeeeeee',\n",
       " 'ohhhhhhhhhhhhhhhh',\n",
       " 'oooooooooooglyyyyyyyy',\n",
       " 'oooooooooooooonnnnnnnnnnnneeeeeeeeeeeeeeesssssssss',\n",
       " 'raaaaaaaaaaaaaaaaaaaaaaaaaaaaa',\n",
       " 'tatatatnanaantatat',\n",
       " 'weeeeeeeeeeeeeeee',\n",
       " 'weeeeeeeeeeeeeeeeeeeeeeeeed',\n",
       " 'wheeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeee',\n",
       " 'woooooooooaaaahhhhhhhhhhhh',\n",
       " 'wooooooooooooohoooooooooooooooo',\n",
       " 'www.Wunderground.com',\n",
       " 'yuuuuuuuuuuuummmmmmmmmmmm']"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "v3 = set(text5)\n",
    "long_words3 = [w for w in v3 if len(w)>15]\n",
    "sorted(long_words3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['#14-19teens',\n",
       " '#talkcity_adults',\n",
       " '((((((((((',\n",
       " '........',\n",
       " 'Question',\n",
       " 'actually',\n",
       " 'anything',\n",
       " 'computer',\n",
       " 'cute.-ass',\n",
       " 'everyone',\n",
       " 'football',\n",
       " 'innocent',\n",
       " 'listening',\n",
       " 'remember',\n",
       " 'seriously',\n",
       " 'something',\n",
       " 'together',\n",
       " 'tomorrow',\n",
       " 'watching']"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fd = FreqDist(text5)\n",
    "sorted([w for w in set(text5) if len(w)>7 and fd[w]>7])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('more', 'is'), ('is', 'said'), ('said', 'than'), ('than', 'done')]"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(bigrams(['more', 'is', 'said', 'than', 'done']))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "United States; fellow citizens; four years; years ago; Federal\n",
      "Government; General Government; American people; Vice President; Old\n",
      "World; Almighty God; Fellow citizens; Chief Magistrate; Chief Justice;\n",
      "God bless; every citizen; Indian tribes; public debt; one another;\n",
      "foreign nations; political parties\n"
     ]
    }
   ],
   "source": [
    "text4.collocations()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
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       " 2,\n",
       " ...]"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[len(w) for w in text1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [],
   "source": [
    "fd2 = FreqDist([len(w) for w in text1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "FreqDist({3: 50223, 1: 47933, 4: 42345, 2: 38513, 5: 26597, 6: 17111, 7: 14399, 8: 9966, 9: 6428, 10: 3528, ...})"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fd2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_keys([1, 4, 2, 6, 8, 9, 11, 5, 7, 3, 10, 12, 13, 14, 16, 15, 17, 18, 20])"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fd2.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_items([(1, 47933), (4, 42345), (2, 38513), (6, 17111), (8, 9966), (9, 6428), (11, 1873), (5, 26597), (7, 14399), (3, 50223), (10, 3528), (12, 1053), (13, 567), (14, 177), (16, 22), (15, 70), (17, 12), (18, 1), (20, 1)])"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fd2.items()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fd2.max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.19255882431878046"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fd2.freq(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Business',\n",
       " 'Darkness',\n",
       " 'Loveliness',\n",
       " 'Madness',\n",
       " 'Righteousness',\n",
       " 'Unfitness',\n",
       " 'Whiteness',\n",
       " 'Witness',\n",
       " 'aboriginalness',\n",
       " 'acridness',\n",
       " 'acuteness',\n",
       " 'adhesiveness',\n",
       " 'apprehensiveness',\n",
       " 'artificialness',\n",
       " 'awfulness',\n",
       " 'awkwardness',\n",
       " 'bashfulness',\n",
       " 'bigness',\n",
       " 'bitterness',\n",
       " 'blackness',\n",
       " 'blandness',\n",
       " 'blankness',\n",
       " 'bleakness',\n",
       " 'blueness',\n",
       " 'boldness',\n",
       " 'brawniness',\n",
       " 'breezelessness',\n",
       " 'brightness',\n",
       " 'brigness',\n",
       " 'business',\n",
       " 'calmness',\n",
       " 'carelessness',\n",
       " 'cautiousness',\n",
       " 'cheerfulness',\n",
       " 'childlessness',\n",
       " 'clearness',\n",
       " 'closeness',\n",
       " 'collectedness',\n",
       " 'comfortableness',\n",
       " 'compactness',\n",
       " 'comprehensiveness',\n",
       " 'consciousness',\n",
       " 'coolness',\n",
       " 'courageousness',\n",
       " 'craziness',\n",
       " 'creativeness',\n",
       " 'crookedness',\n",
       " 'curiousness',\n",
       " 'daintiness',\n",
       " 'dampness',\n",
       " 'darkness',\n",
       " 'dauntlessness',\n",
       " 'deadliness',\n",
       " 'deceitfulness',\n",
       " 'deliciousness',\n",
       " 'desolateness',\n",
       " 'devilishness',\n",
       " 'disorderliness',\n",
       " 'divineness',\n",
       " 'dreaminess',\n",
       " 'drowsiness',\n",
       " 'eagerness',\n",
       " 'earnestness',\n",
       " 'ebonness',\n",
       " 'endlessness',\n",
       " 'enormousness',\n",
       " 'exactness',\n",
       " 'exclusiveness',\n",
       " 'expansiveness',\n",
       " 'expertness',\n",
       " 'facetiousness',\n",
       " 'faintness',\n",
       " 'faithfulness',\n",
       " 'fatness',\n",
       " 'fearfulness',\n",
       " 'fearlessness',\n",
       " 'ferociousness',\n",
       " 'fickleness',\n",
       " 'fierceness',\n",
       " 'firmness',\n",
       " 'fitness',\n",
       " 'fleetness',\n",
       " 'forgetfulness',\n",
       " 'forlornness',\n",
       " 'foulness',\n",
       " 'freshness',\n",
       " 'friendliness',\n",
       " 'gamesomeness',\n",
       " 'gentleness',\n",
       " 'genuineness',\n",
       " 'ghastliness',\n",
       " 'ghostliness',\n",
       " 'gladness',\n",
       " 'goodness',\n",
       " 'greatness',\n",
       " 'greenness',\n",
       " 'grimness',\n",
       " 'grotesqueness',\n",
       " 'guiltiness',\n",
       " 'handedness',\n",
       " 'happiness',\n",
       " 'hardness',\n",
       " 'harness',\n",
       " 'heartedness',\n",
       " 'heartlessness',\n",
       " 'heaviness',\n",
       " 'heedfulness',\n",
       " 'heinousness',\n",
       " 'hideousness',\n",
       " 'highness',\n",
       " 'holiness',\n",
       " 'honourableness',\n",
       " 'hopefulness',\n",
       " 'hugeness',\n",
       " 'humorousness',\n",
       " 'iciness',\n",
       " 'idleness',\n",
       " 'illness',\n",
       " 'immutableness',\n",
       " 'impetuousness',\n",
       " 'impiousness',\n",
       " 'indebtedness',\n",
       " 'indefiniteness',\n",
       " 'indispensableness',\n",
       " 'indistinctness',\n",
       " 'indomitableness',\n",
       " 'infantileness',\n",
       " 'inhabitiveness',\n",
       " 'inoffensiveness',\n",
       " 'intolerableness',\n",
       " 'irresistibleness',\n",
       " 'joyousness',\n",
       " 'kindness',\n",
       " 'landlessness',\n",
       " 'largeness',\n",
       " 'lightness',\n",
       " 'likeness',\n",
       " 'listlessness',\n",
       " 'liveliness',\n",
       " 'localness',\n",
       " 'loneliness',\n",
       " 'lonesomeness',\n",
       " 'loveliness',\n",
       " 'madness',\n",
       " 'manliness',\n",
       " 'maziness',\n",
       " 'meditativeness',\n",
       " 'mildness',\n",
       " 'milkiness',\n",
       " 'mindedness',\n",
       " 'mistiness',\n",
       " 'moodiness',\n",
       " 'morbidness',\n",
       " 'muffledness',\n",
       " 'muskiness',\n",
       " 'muteness',\n",
       " 'nakedness',\n",
       " 'nappishness',\n",
       " 'neatness',\n",
       " 'nervousness',\n",
       " 'noiselessness',\n",
       " 'nothingness',\n",
       " 'numbness',\n",
       " 'oneness',\n",
       " 'outlandishness',\n",
       " 'painfulness',\n",
       " 'pallidness',\n",
       " 'palpableness',\n",
       " 'passionateness',\n",
       " 'passionlessness',\n",
       " 'passiveness',\n",
       " 'peacefulness',\n",
       " 'perilousness',\n",
       " 'periodicalness',\n",
       " 'persuasiveness',\n",
       " 'pettiness',\n",
       " 'picturesqueness',\n",
       " 'plaintiveness',\n",
       " 'pleasantness',\n",
       " 'politeness',\n",
       " 'populousness',\n",
       " 'portentousness',\n",
       " 'preciousness',\n",
       " 'preternaturalness',\n",
       " 'quaintness',\n",
       " 'readiness',\n",
       " 'reasonableness',\n",
       " 'recklessness',\n",
       " 'recluseness',\n",
       " 'redness',\n",
       " 'restlessness',\n",
       " 'richness',\n",
       " 'robustness',\n",
       " 'roundness',\n",
       " 'rudeness',\n",
       " 'ruggedness',\n",
       " 'rustiness',\n",
       " 'sacredness',\n",
       " 'sadness',\n",
       " 'savageness',\n",
       " 'secludedness',\n",
       " 'sereneness',\n",
       " 'shagginess',\n",
       " 'shortness',\n",
       " 'shrewdness',\n",
       " 'shyness',\n",
       " 'sickness',\n",
       " 'simultaneousness',\n",
       " 'sleeplessness',\n",
       " 'slipperiness',\n",
       " 'slowness',\n",
       " 'smallness',\n",
       " 'snugness',\n",
       " 'softness',\n",
       " 'sordidness',\n",
       " 'spaciousness',\n",
       " 'spectralness',\n",
       " 'spotlessness',\n",
       " 'stillness',\n",
       " 'strangeness',\n",
       " 'stubbornness',\n",
       " 'subterraneousness',\n",
       " 'subtleness',\n",
       " 'suddenness',\n",
       " 'suggestiveness',\n",
       " 'superfluousness',\n",
       " 'supernaturalness',\n",
       " 'superstitiousness',\n",
       " 'sweetness',\n",
       " 'swiftness',\n",
       " 'tearlessness',\n",
       " 'tenderness',\n",
       " 'terribleness',\n",
       " 'thickness',\n",
       " 'thinness',\n",
       " 'thoughtfulness',\n",
       " 'thoughtlessness',\n",
       " 'tidiness',\n",
       " 'toughness',\n",
       " 'tremendousness',\n",
       " 'unbecomingness',\n",
       " 'uncleanliness',\n",
       " 'uncomfortableness',\n",
       " 'uncompromisedness',\n",
       " 'unconsciousness',\n",
       " 'uncouthness',\n",
       " 'unctuousness',\n",
       " 'uneasiness',\n",
       " 'uneventfulness',\n",
       " 'uniqueness',\n",
       " 'unwillingness',\n",
       " 'usefulness',\n",
       " 'vagueness',\n",
       " 'viciousness',\n",
       " 'vindictiveness',\n",
       " 'vividness',\n",
       " 'wakefulness',\n",
       " 'wantonness',\n",
       " 'weakness',\n",
       " 'weariness',\n",
       " 'whimsiness',\n",
       " 'whiteness',\n",
       " 'wickedness',\n",
       " 'wilderness',\n",
       " 'wildness',\n",
       " 'wilfulness',\n",
       " 'willingness',\n",
       " 'witness',\n",
       " 'wittiness',\n",
       " 'wonderfulness',\n",
       " 'wondrousness',\n",
       " 'woraciousness']"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sorted([w for w in set(text1) if w.endswith('ness')])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Sovereignty', 'sovereignties', 'sovereignty']"
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sorted([t for t in set(text4) if 'gnt' in t ])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['7000L',\n",
       " 'A',\n",
       " 'Abbeyland',\n",
       " 'About',\n",
       " 'Absence',\n",
       " 'Abundance',\n",
       " 'Add',\n",
       " 'Affecting',\n",
       " 'After',\n",
       " 'Again',\n",
       " 'Against',\n",
       " 'Ah',\n",
       " 'All',\n",
       " 'Allenham',\n",
       " 'Allow',\n",
       " 'Almost',\n",
       " 'Altogether',\n",
       " 'Am',\n",
       " 'Among',\n",
       " 'Amongst',\n",
       " 'An',\n",
       " 'And',\n",
       " 'Annamaria',\n",
       " 'Anne',\n",
       " 'Another',\n",
       " 'Anxiety',\n",
       " 'April',\n",
       " 'Are',\n",
       " 'As',\n",
       " 'Ashamed',\n",
       " 'Astonished',\n",
       " 'Astonishment',\n",
       " 'At',\n",
       " 'Austen',\n",
       " 'Avignon',\n",
       " 'Ay',\n",
       " 'Aye',\n",
       " 'Bad',\n",
       " 'Bartlett',\n",
       " 'Barton',\n",
       " 'Bath',\n",
       " 'Beautifully',\n",
       " 'Because',\n",
       " 'Before',\n",
       " 'Being',\n",
       " 'Believe',\n",
       " 'Benevolent',\n",
       " 'Berkeley',\n",
       " 'Besides',\n",
       " 'Betty',\n",
       " 'Between',\n",
       " 'Beyond',\n",
       " 'Biddy',\n",
       " 'Bishop',\n",
       " 'Bond',\n",
       " 'Bonomi',\n",
       " 'Born',\n",
       " 'Brandon',\n",
       " 'Bristol',\n",
       " 'Brown',\n",
       " 'Building',\n",
       " 'Buildings',\n",
       " 'Burgess',\n",
       " 'Business',\n",
       " 'But',\n",
       " 'By',\n",
       " 'Can',\n",
       " 'Careless',\n",
       " 'Careys',\n",
       " 'Cartwright',\n",
       " 'Casino',\n",
       " 'Cassino',\n",
       " 'Certainly',\n",
       " 'Chagrined',\n",
       " 'Charlotte',\n",
       " 'Choice',\n",
       " 'Christian',\n",
       " 'Christmas',\n",
       " 'Civil',\n",
       " 'Clarke',\n",
       " 'Cleveland',\n",
       " 'Cold',\n",
       " 'Colonel',\n",
       " 'Columella',\n",
       " 'Combe',\n",
       " 'Come',\n",
       " 'Common',\n",
       " 'Comparisons',\n",
       " 'Concealing',\n",
       " 'Concern',\n",
       " 'Conduit',\n",
       " 'Confess',\n",
       " 'Consider',\n",
       " 'Considering',\n",
       " 'Constantia',\n",
       " 'Continual',\n",
       " 'Conversation',\n",
       " 'Cottage',\n",
       " 'Could',\n",
       " 'Court',\n",
       " 'Courtland',\n",
       " 'Cowper',\n",
       " 'Cross',\n",
       " 'Cruel',\n",
       " 'D',\n",
       " 'Dartford',\n",
       " 'Dashwood',\n",
       " 'Dashwoods',\n",
       " 'Davies',\n",
       " 'Dawlish',\n",
       " 'Dear',\n",
       " 'Dearest',\n",
       " 'Delaford',\n",
       " 'Dennison',\n",
       " 'Depend',\n",
       " 'Design',\n",
       " 'Determined',\n",
       " 'Devonshire',\n",
       " 'Did',\n",
       " 'Disappointed',\n",
       " 'Disappointment',\n",
       " 'Do',\n",
       " 'Doctor',\n",
       " 'Does',\n",
       " 'Domestic',\n",
       " 'Don',\n",
       " 'Donavan',\n",
       " 'Dorsetshire',\n",
       " 'Down',\n",
       " 'Dr',\n",
       " 'Drury',\n",
       " 'Dullness',\n",
       " 'During',\n",
       " 'Duty',\n",
       " 'Each',\n",
       " 'Eager',\n",
       " 'Early',\n",
       " 'East',\n",
       " 'Easter',\n",
       " 'Edward',\n",
       " 'Elinor',\n",
       " 'Eliza',\n",
       " 'Elliott',\n",
       " 'Ellison',\n",
       " 'Ellisons',\n",
       " 'Encouraged',\n",
       " 'Engaged',\n",
       " 'Engagement',\n",
       " 'England',\n",
       " 'Epicurism',\n",
       " 'Esq',\n",
       " 'Esteem',\n",
       " 'Even',\n",
       " 'Every',\n",
       " 'Everybody',\n",
       " 'Excellent',\n",
       " 'Exchange',\n",
       " 'Excuse',\n",
       " 'Exert',\n",
       " 'Exeter',\n",
       " 'Extend',\n",
       " 'Extravagance',\n",
       " 'F',\n",
       " 'Fanny',\n",
       " 'Far',\n",
       " 'Farm',\n",
       " 'February',\n",
       " 'Ferrars',\n",
       " 'Few',\n",
       " 'Fifteen',\n",
       " 'Fifty',\n",
       " 'Five',\n",
       " 'Folly',\n",
       " 'For',\n",
       " 'Forgive',\n",
       " 'Fortunately',\n",
       " 'Four',\n",
       " 'Friday',\n",
       " 'From',\n",
       " 'Frosts',\n",
       " 'Gardens',\n",
       " 'Gentleman',\n",
       " 'Get',\n",
       " 'Gibson',\n",
       " 'Gilberts',\n",
       " 'Go',\n",
       " 'God',\n",
       " 'Godby',\n",
       " 'Going',\n",
       " 'Gone',\n",
       " 'Good',\n",
       " 'Gracious',\n",
       " 'Grandeur',\n",
       " 'Gray',\n",
       " 'Greatness',\n",
       " 'Grecian',\n",
       " 'Grey',\n",
       " 'Had',\n",
       " 'Half',\n",
       " 'Hamlet',\n",
       " 'Hanger',\n",
       " 'Hanover',\n",
       " 'Happy',\n",
       " 'Harley',\n",
       " 'Harris',\n",
       " 'Harry',\n",
       " 'Has',\n",
       " 'Have',\n",
       " 'Having',\n",
       " 'He',\n",
       " 'Heaven',\n",
       " 'Henry',\n",
       " 'Henshawe',\n",
       " 'Her',\n",
       " 'Here',\n",
       " 'High',\n",
       " 'His',\n",
       " 'Hitherto',\n",
       " 'Holborn',\n",
       " 'Holburn',\n",
       " 'Hon',\n",
       " 'Honiton',\n",
       " 'Hope',\n",
       " 'Hour',\n",
       " 'House',\n",
       " 'How',\n",
       " 'However',\n",
       " 'Hum',\n",
       " 'Hunters',\n",
       " 'Hush',\n",
       " 'I',\n",
       " 'If',\n",
       " 'Imagine',\n",
       " 'Impatient',\n",
       " 'Impossible',\n",
       " 'Improve',\n",
       " 'Impudence',\n",
       " 'In',\n",
       " 'Indeed',\n",
       " 'Indies',\n",
       " 'Infirmity',\n",
       " 'Inn',\n",
       " 'Instead',\n",
       " 'Invited',\n",
       " 'Is',\n",
       " 'It',\n",
       " 'James',\n",
       " 'Jane',\n",
       " 'January',\n",
       " 'Jenning',\n",
       " 'Jennings',\n",
       " 'John',\n",
       " 'Just',\n",
       " 'Kensington',\n",
       " 'Kingham',\n",
       " 'Know',\n",
       " 'Knowing',\n",
       " 'L',\n",
       " 'La',\n",
       " 'Lady',\n",
       " 'Ladyship',\n",
       " 'Lane',\n",
       " 'Last',\n",
       " 'Laughing',\n",
       " 'Law',\n",
       " 'Let',\n",
       " 'Life',\n",
       " 'Like',\n",
       " 'Little',\n",
       " 'Lodging',\n",
       " 'Lombardy',\n",
       " 'London',\n",
       " 'Long',\n",
       " 'Longstaple',\n",
       " 'Look',\n",
       " 'Lord',\n",
       " 'Luckily',\n",
       " 'Lucy',\n",
       " 'M',\n",
       " 'Ma',\n",
       " 'Mab',\n",
       " 'Madam',\n",
       " 'Magna',\n",
       " 'Mall',\n",
       " 'Mama',\n",
       " 'Mamma',\n",
       " 'Mansion',\n",
       " 'Many',\n",
       " 'March',\n",
       " 'Margaret',\n",
       " 'Marianne',\n",
       " 'Marlborough',\n",
       " 'Martha',\n",
       " 'Mary',\n",
       " 'Master',\n",
       " 'May',\n",
       " 'Me',\n",
       " 'Men',\n",
       " 'Michaelmas',\n",
       " 'Mid',\n",
       " 'Middleton',\n",
       " 'Middletons',\n",
       " 'Midsummer',\n",
       " 'Mind',\n",
       " 'Mine',\n",
       " 'Misery',\n",
       " 'Miss',\n",
       " 'Misses',\n",
       " 'Mistress',\n",
       " 'Monday',\n",
       " 'Months',\n",
       " 'More',\n",
       " 'Morton',\n",
       " 'Most',\n",
       " 'Mr',\n",
       " 'Mrs',\n",
       " 'Much',\n",
       " 'Music',\n",
       " 'Must',\n",
       " 'My',\n",
       " 'Nancy',\n",
       " 'Nay',\n",
       " 'Neither',\n",
       " 'Never',\n",
       " 'New',\n",
       " 'Newton',\n",
       " 'No',\n",
       " 'Nobody',\n",
       " 'None',\n",
       " 'Nor',\n",
       " 'Norfolk',\n",
       " 'Norland',\n",
       " 'Not',\n",
       " 'Nothing',\n",
       " 'November',\n",
       " 'Now',\n",
       " 'October',\n",
       " 'Of',\n",
       " 'Offended',\n",
       " 'Oh',\n",
       " 'On',\n",
       " 'Once',\n",
       " 'One',\n",
       " 'Only',\n",
       " 'Opportunity',\n",
       " 'Opposition',\n",
       " 'Or',\n",
       " 'Other',\n",
       " 'Others',\n",
       " 'Our',\n",
       " 'Oxford',\n",
       " 'P',\n",
       " 'Pall',\n",
       " 'Palmer',\n",
       " 'Palmers',\n",
       " 'Pardon',\n",
       " 'Park',\n",
       " 'Parliament',\n",
       " 'Parrys',\n",
       " 'Parsonage',\n",
       " 'Perhaps',\n",
       " 'Pity',\n",
       " 'Please',\n",
       " 'Pleased',\n",
       " 'Plymouth',\n",
       " 'Poor',\n",
       " 'Pope',\n",
       " 'Portman',\n",
       " 'Pratt',\n",
       " 'Pray',\n",
       " 'Precious',\n",
       " 'Preparation',\n",
       " 'Prescriptions',\n",
       " 'Priory',\n",
       " 'Queen',\n",
       " 'Quite',\n",
       " 'Rather',\n",
       " 'Reading',\n",
       " 'Really',\n",
       " 'Recollecting',\n",
       " 'Reflection',\n",
       " 'Regard',\n",
       " 'Relate',\n",
       " 'Remember',\n",
       " 'Reserved',\n",
       " 'Restless',\n",
       " 'Richard',\n",
       " 'Richardson',\n",
       " 'Richardsons',\n",
       " 'Robert',\n",
       " 'Rose',\n",
       " 'S',\n",
       " 'Sackville',\n",
       " 'Sally',\n",
       " 'Sandersons',\n",
       " 'Saturday',\n",
       " 'Scarcely',\n",
       " 'Scotland',\n",
       " 'Scott',\n",
       " 'Secrecy',\n",
       " 'Selfish',\n",
       " 'Sense',\n",
       " 'Sensibility',\n",
       " 'September',\n",
       " 'Seven',\n",
       " 'Shakespeare',\n",
       " 'Shall',\n",
       " 'Sharpe',\n",
       " 'She',\n",
       " 'Short',\n",
       " 'Should',\n",
       " 'Shyness',\n",
       " 'Simpson',\n",
       " 'Since',\n",
       " 'Sincerely',\n",
       " 'Sir',\n",
       " 'Sit',\n",
       " 'Smith',\n",
       " 'So',\n",
       " 'Some',\n",
       " 'Somehow',\n",
       " 'Somerset',\n",
       " 'Somersetshire',\n",
       " 'Something',\n",
       " 'Sometimes',\n",
       " 'Soon',\n",
       " 'Sophia',\n",
       " 'Sparks',\n",
       " 'Square',\n",
       " 'St',\n",
       " 'Stanhill',\n",
       " 'Steele',\n",
       " 'Steeles',\n",
       " 'Still',\n",
       " 'Strange',\n",
       " 'Street',\n",
       " 'Streets',\n",
       " 'Such',\n",
       " 'Sunday',\n",
       " 'Supported',\n",
       " 'Supposing',\n",
       " 'Sure',\n",
       " 'Surely',\n",
       " 'Surprised',\n",
       " 'Sussex',\n",
       " 'Take',\n",
       " 'Taylor',\n",
       " 'Tell',\n",
       " 'Temple',\n",
       " 'Thank',\n",
       " 'That',\n",
       " 'The',\n",
       " 'Their',\n",
       " 'Then',\n",
       " 'There',\n",
       " 'These',\n",
       " 'They',\n",
       " 'Think',\n",
       " 'This',\n",
       " 'Thomas',\n",
       " 'Thomson',\n",
       " 'Those',\n",
       " 'Though',\n",
       " 'Three',\n",
       " 'Thunderbolts',\n",
       " 'Thursday',\n",
       " 'Thus',\n",
       " 'Till',\n",
       " 'Time',\n",
       " 'Tis',\n",
       " 'To',\n",
       " 'Towards',\n",
       " 'Truth',\n",
       " 'Tuesday',\n",
       " 'Twice',\n",
       " 'Twill',\n",
       " 'Two',\n",
       " 'Unaccountable',\n",
       " 'Undoubtedly',\n",
       " 'Ungracious',\n",
       " 'Upon',\n",
       " 'Use',\n",
       " 'Valley',\n",
       " 'Vanity',\n",
       " 'Very',\n",
       " 'Volume',\n",
       " 'W',\n",
       " 'Wait',\n",
       " 'Walker',\n",
       " 'Want',\n",
       " 'Was',\n",
       " 'Watched',\n",
       " 'We',\n",
       " 'Wednesday',\n",
       " 'Well',\n",
       " 'Were',\n",
       " 'Westminster',\n",
       " 'Westons',\n",
       " 'Weymouth',\n",
       " 'What',\n",
       " 'Whatever',\n",
       " 'When',\n",
       " 'Whenever',\n",
       " 'Where',\n",
       " 'Whereas',\n",
       " 'Wherever',\n",
       " 'Whether',\n",
       " 'Which',\n",
       " 'While',\n",
       " 'Whitakers',\n",
       " 'Whitwell',\n",
       " 'Who',\n",
       " 'Whoever',\n",
       " 'Whom',\n",
       " 'Why',\n",
       " 'Will',\n",
       " 'William',\n",
       " 'Williams',\n",
       " 'Willing',\n",
       " 'Willoughby',\n",
       " 'Willoughbys',\n",
       " 'With',\n",
       " 'Within',\n",
       " 'Without',\n",
       " 'Would',\n",
       " 'Writing',\n",
       " 'Yes',\n",
       " 'Yet',\n",
       " 'You',\n",
       " 'Your']"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sorted([k for k in set(text2) if k.istitle()])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['29', '61']"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sorted([a for a in set(sent7) if a.isdigit()])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Stock-index',\n",
       " 'index',\n",
       " 'index-arbitrage',\n",
       " 'index-fund',\n",
       " 'index-options',\n",
       " 'index-related',\n",
       " 'indexers',\n",
       " 'indexes',\n",
       " 'stock-index']"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sorted([w for w in set(text7) if '-' and 'index' in w])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Abelmizraim',\n",
       " 'Allonbachuth',\n",
       " 'Beerlahairoi',\n",
       " 'Canaanitish',\n",
       " 'Chedorlaomer',\n",
       " 'Girgashites',\n",
       " 'Hazarmaveth',\n",
       " 'Hazezontamar',\n",
       " 'Ishmeelites',\n",
       " 'Jegarsahadutha',\n",
       " 'Jehovahjireh',\n",
       " 'Kirjatharba',\n",
       " 'Melchizedek',\n",
       " 'Mesopotamia',\n",
       " 'Peradventure',\n",
       " 'Philistines',\n",
       " 'Zaphnathpaaneah']"
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sorted([w for w in set(text3) if w.istitle() and len(w)>10])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[',', '.', '29', '61', 'Nov.', 'Pierre', 'Vinken']"
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sorted([w for w in set(sent7) if not w.islower()])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['ancient',\n",
       " 'ceiling',\n",
       " 'conceit',\n",
       " 'conceited',\n",
       " 'conceive',\n",
       " 'conscience',\n",
       " 'conscientious',\n",
       " 'conscientiously',\n",
       " 'deceitful',\n",
       " 'deceive',\n",
       " 'deceived',\n",
       " 'deceiving',\n",
       " 'deficiencies',\n",
       " 'deficiency',\n",
       " 'deficient',\n",
       " 'delicacies',\n",
       " 'excellencies',\n",
       " 'fancied',\n",
       " 'insufficiency',\n",
       " 'insufficient',\n",
       " 'legacies',\n",
       " 'perceive',\n",
       " 'perceived',\n",
       " 'perceiving',\n",
       " 'prescience',\n",
       " 'prophecies',\n",
       " 'receipt',\n",
       " 'receive',\n",
       " 'received',\n",
       " 'receiving',\n",
       " 'society',\n",
       " 'species',\n",
       " 'sufficient',\n",
       " 'sufficiently',\n",
       " 'undeceive',\n",
       " 'undeceiving']"
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sorted([w for w in set(text2) if 'cie' in w or 'cei' in w])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "260819"
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# total words in Moby Dick\n",
    "len(text1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "19317"
      ]
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# total words set in Moby Dick\n",
    "len(set(text1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "17231"
      ]
     },
     "execution_count": 106,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# total distinct word in Moby Dick\n",
    "len(set([w.lower() for w in text1]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "16948"
      ]
     },
     "execution_count": 107,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# elimination of punctuation in above \n",
    "len(set([w.lower() for w in text1 if w.isalpha()]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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