After min-max.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "import re"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import glob"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "arr=[]\n",
    "path = r'C:\\Users\\HP\\Desktop\\Project\\Hierarchical Clustering\\txt_sentoken\\pos\\*.txt'\n",
    "files = glob.glob(path)\n",
    "for name in files:\n",
    "    with open(name) as f:\n",
    "     arr.append(f.read())       \n",
    "   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1000"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(arr)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "arr2=[]\n",
    "path = r'C:\\Users\\HP\\Desktop\\Project\\Hierarchical Clustering\\txt_sentoken\\neg\\*.txt'\n",
    "file = glob.glob(path)\n",
    "for name in file:\n",
    "    with open(name) as f:\n",
    "        #print(\"p\")\n",
    "        arr2.append(f.read())       \n",
    "   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1000"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(arr2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df = pd.DataFrame(arr,columns=['text'])\n",
    "n=50"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df = df.head(n)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df1 = pd.DataFrame(arr2,columns=['text'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df1 = df.head(n)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df = df.append(df1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(100, 1)"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df.reset_index(drop=True,inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th></th>\n",
       "      <th>text</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>films adapted from comic books have had plenty...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>every now and then a movie comes along from a ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>you've got mail works alot better than it dese...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>\" jaws \" is a rare film that grabs your atten...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>moviemaking is a lot like being the general ma...</td>\n",
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      "text/plain": [
       "                                                text\n",
       "0  films adapted from comic books have had plenty...\n",
       "1  every now and then a movie comes along from a ...\n",
       "2  you've got mail works alot better than it dese...\n",
       "3   \" jaws \" is a rare film that grabs your atten...\n",
       "4  moviemaking is a lot like being the general ma..."
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#remove email id\n",
    "def rem_email(col):\n",
    "    text=col[0]\n",
    "    text=re.sub(r'\\S*@\\S*\\s?',\"\",text)\n",
    "    return text\n",
    "df['text']=df[['text']].apply(rem_email,axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#removal of special characters\n",
    "def rem_special(col):\n",
    "    text=col[0]\n",
    "    text=re.sub(r'[^A-Za-z0-9]+',\" \",text)\n",
    "    return text\n",
    "df['text']=df[['text']].apply(rem_special,axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def rem_dig(col):\n",
    "    text=col[0]\n",
    "    text=re.sub(r'\\d+',\"\",text)\n",
    "    return text\n",
    "df['text']=df[['text']].apply(rem_dig,axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#conversion to lowercase\n",
    "def con_tolower(col):\n",
    "    text=col[0]\n",
    "    text=text.lower()\n",
    "    return text\n",
    "df['text']=df[['text']].apply(con_tolower,axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>text</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>films adapted from comic books have had plenty...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>every now and then a movie comes along from a ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
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       "      <td>you ve got mail works alot better than it dese...</td>\n",
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       "      <td>jaws is a rare film that grabs your attention...</td>\n",
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       "      <td>on june   a self taught idealistic yet pragmat...</td>\n",
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       "      <td>apparently director tony kaye had a major batt...</td>\n",
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       "      <td>after bloody clashes and independence won lumu...</td>\n",
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       "      <th>9</th>\n",
       "      <td>the american action film has been slowly drown...</td>\n",
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       "      <th>12</th>\n",
       "      <td>synopsis bobby garfield yelchin lives in a sma...</td>\n",
       "    </tr>\n",
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       "      <th>13</th>\n",
       "      <td>synopsis in this movie steven spielberg one of...</td>\n",
       "    </tr>\n",
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       "      <th>14</th>\n",
       "      <td>the police negotiator is the person with the e...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>plot a young man who loves heavy metal music a...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>carry on matron is the last great carry on fil...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>the ultimate match up between good and evil th...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>having not seen who framed roger rabbit in ove...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>there s something about ben stiller that makes...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                 text\n",
       "0   films adapted from comic books have had plenty...\n",
       "1   every now and then a movie comes along from a ...\n",
       "2   you ve got mail works alot better than it dese...\n",
       "3    jaws is a rare film that grabs your attention...\n",
       "4   moviemaking is a lot like being the general ma...\n",
       "5   on june   a self taught idealistic yet pragmat...\n",
       "6   apparently director tony kaye had a major batt...\n",
       "7   one of my colleagues was surprised when i told...\n",
       "8   after bloody clashes and independence won lumu...\n",
       "9   the american action film has been slowly drown...\n",
       "10  after watching rat race last week i noticed my...\n",
       "11  i ve noticed something lately that i ve never ...\n",
       "12  synopsis bobby garfield yelchin lives in a sma...\n",
       "13  synopsis in this movie steven spielberg one of...\n",
       "14  the police negotiator is the person with the e...\n",
       "15  plot a young man who loves heavy metal music a...\n",
       "16  carry on matron is the last great carry on fil...\n",
       "17  the ultimate match up between good and evil th...\n",
       "18  having not seen who framed roger rabbit in ove...\n",
       "19  there s something about ben stiller that makes..."
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from nltk.corpus import stopwords\n",
    "set1=set(stopwords.words('english'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from nltk.tokenize import word_tokenize\n",
    "def stop_words1(col):\n",
    "    text=col[0]\n",
    "    word_tokens = word_tokenize(text)\n",
    "    return word_tokens\n",
    "df['text']=df[['text']].apply(stop_words1,axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    [films, adapted, from, comic, books, have, had...\n",
       "1    [every, now, and, then, a, movie, comes, along...\n",
       "2    [you, ve, got, mail, works, alot, better, than...\n",
       "3    [jaws, is, a, rare, film, that, grabs, your, a...\n",
       "4    [moviemaking, is, a, lot, like, being, the, ge...\n",
       "Name: text, dtype: object"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['text'].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def capping(col):\n",
    "    text=col[0]\n",
    "    text_new=[]\n",
    "    for i in text:\n",
    "        if(len(i)<=2 or len(i)>=13):\n",
    "            continue\n",
    "        else:\n",
    "            text_new.append(i)\n",
    "    return text_new\n",
    "df['text']=df[['text']].apply(capping,axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0     [films, adapted, from, comic, books, have, had...\n",
       "1     [every, now, and, then, movie, comes, along, f...\n",
       "2     [you, got, mail, works, alot, better, than, de...\n",
       "3     [jaws, rare, film, that, grabs, your, attentio...\n",
       "4     [moviemaking, lot, like, being, the, general, ...\n",
       "5     [june, self, taught, idealistic, yet, pragmati...\n",
       "6     [apparently, director, tony, kaye, had, major,...\n",
       "7     [one, colleagues, was, surprised, when, told, ...\n",
       "8     [after, bloody, clashes, and, independence, wo...\n",
       "9     [the, american, action, film, has, been, slowl...\n",
       "10    [after, watching, rat, race, last, week, notic...\n",
       "11    [noticed, something, lately, that, never, thou...\n",
       "12    [synopsis, bobby, garfield, yelchin, lives, sm...\n",
       "13    [synopsis, this, movie, steven, spielberg, one...\n",
       "14    [the, police, negotiator, the, person, with, t...\n",
       "15    [plot, young, man, who, loves, heavy, metal, m...\n",
       "16    [carry, matron, the, last, great, carry, film,...\n",
       "17    [the, ultimate, match, between, good, and, evi...\n",
       "18    [having, not, seen, who, framed, roger, rabbit...\n",
       "19    [there, something, about, ben, stiller, that, ...\n",
       "20    [phil, curtolo, mel, gibson, braveheart, gave,...\n",
       "21    [one, can, not, observe, star, trek, movie, an...\n",
       "22    [fully, loaded, review, website, coming, july,...\n",
       "23    [when, bulworth, ended, allowed, myself, sigh,...\n",
       "24    [call, for, the, cliche, police, you, must, bu...\n",
       "25    [hilarious, ultra, low, budget, comedy, from, ...\n",
       "26    [for, those, who, weren, yet, born, when, the,...\n",
       "27    [the, most, common, and, many, cases, the, onl...\n",
       "28    [the, blair, witch, project, was, perhaps, one...\n",
       "29    [seen, may, home, video, rented, one, the, bes...\n",
       "                            ...                        \n",
       "70    [phil, curtolo, mel, gibson, braveheart, gave,...\n",
       "71    [one, can, not, observe, star, trek, movie, an...\n",
       "72    [fully, loaded, review, website, coming, july,...\n",
       "73    [when, bulworth, ended, allowed, myself, sigh,...\n",
       "74    [call, for, the, cliche, police, you, must, bu...\n",
       "75    [hilarious, ultra, low, budget, comedy, from, ...\n",
       "76    [for, those, who, weren, yet, born, when, the,...\n",
       "77    [the, most, common, and, many, cases, the, onl...\n",
       "78    [the, blair, witch, project, was, perhaps, one...\n",
       "79    [seen, may, home, video, rented, one, the, bes...\n",
       "80    [linda, fiorentino, disappeared, off, the, rad...\n",
       "81    [you, heard, all, the, hype, you, seen, all, t...\n",
       "82    [african, american, detective, vergil, tibbs, ...\n",
       "83    [wonder, boys, michael, douglas, plays, aged, ...\n",
       "84    [plot, derek, zoolander, male, model, also, ve...\n",
       "85    [unzipped, cinematic, portrait, isaac, mizrahi...\n",
       "86    [dora, fernanda, montenegro, sits, behind, mak...\n",
       "87    [the, event, events, upon, people, have, waite...\n",
       "88    [sometimes, movie, comes, along, that, falls, ...\n",
       "89    [that, thing, you, tom, hanks, and, directoria...\n",
       "90    [back, and, about, time, was, the, motto, for,...\n",
       "91    [dreamworks, pictures, presents, jinks, cohen,...\n",
       "92    [will, hunting, matt, damon, natural, genius, ...\n",
       "93    [there, one, thing, common, about, all, hollyw...\n",
       "94    [what, you, get, when, you, slap, together, mo...\n",
       "95    [run, tings, tings, don, run, sound, advice, f...\n",
       "96    [first, glance, appears, that, the, home, alon...\n",
       "97    [comedy, rated, runs, about, starring, john, g...\n",
       "98    [when, star, wars, came, out, some, twenty, ye...\n",
       "99    [warning, contains, what, the, matrix, rated, ...\n",
       "Name: text, Length: 100, dtype: object"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['text']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from nltk.tokenize import word_tokenize\n",
    "def stop_words1(col):\n",
    "    text=col[0]\n",
    "    word_tokens = text\n",
    "    filtered=[]\n",
    "    for i in range(0,len(word_tokens)-1):\n",
    "        temp1=word_tokens[i];\n",
    "        temp2=word_tokens[i+1];\n",
    "        if temp1 in set1 or temp2 in set1:\n",
    "            continue\n",
    "        filtered.append((temp1,temp2))\n",
    "    return filtered\n",
    "df['text']=df[['text']].apply(stop_words1,axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    [(films, adapted), (comic, books), (plenty, su...\n",
       "1    [(movie, comes), (comes, along), (suspect, stu...\n",
       "2    [(got, mail), (mail, works), (works, alot), (a...\n",
       "3    [(jaws, rare), (rare, film), (single, image), ...\n",
       "4    [(moviemaking, lot), (lot, like), (general, ma...\n",
       "Name: text, dtype: object"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['text'].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "global anst"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "anst=0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0     None\n",
       "1     None\n",
       "2     None\n",
       "3     None\n",
       "4     None\n",
       "5     None\n",
       "6     None\n",
       "7     None\n",
       "8     None\n",
       "9     None\n",
       "10    None\n",
       "11    None\n",
       "12    None\n",
       "13    None\n",
       "14    None\n",
       "15    None\n",
       "16    None\n",
       "17    None\n",
       "18    None\n",
       "19    None\n",
       "20    None\n",
       "21    None\n",
       "22    None\n",
       "23    None\n",
       "24    None\n",
       "25    None\n",
       "26    None\n",
       "27    None\n",
       "28    None\n",
       "29    None\n",
       "      ... \n",
       "70    None\n",
       "71    None\n",
       "72    None\n",
       "73    None\n",
       "74    None\n",
       "75    None\n",
       "76    None\n",
       "77    None\n",
       "78    None\n",
       "79    None\n",
       "80    None\n",
       "81    None\n",
       "82    None\n",
       "83    None\n",
       "84    None\n",
       "85    None\n",
       "86    None\n",
       "87    None\n",
       "88    None\n",
       "89    None\n",
       "90    None\n",
       "91    None\n",
       "92    None\n",
       "93    None\n",
       "94    None\n",
       "95    None\n",
       "96    None\n",
       "97    None\n",
       "98    None\n",
       "99    None\n",
       "Length: 100, dtype: object"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "set1=set()\n",
    "lst=[]\n",
    "def push_in_set(col):\n",
    "    text=col[0]\n",
    "    set1.update(text)\n",
    "    for i in text:\n",
    "        lst.append(i)\n",
    "df[['text']].apply(push_in_set,axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10636"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(set1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "22846"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(lst)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{('similar', 'aptitude'),\n",
       " ('company', 'keeps'),\n",
       " ('dick', 'tracy'),\n",
       " ('hard', 'time'),\n",
       " ('coppola', 'influence'),\n",
       " ('vader', 'skywalker'),\n",
       " ('maybe', 'two'),\n",
       " ('title', 'course'),\n",
       " ('two', 'mistakenly'),\n",
       " ('show', 'doctor'),\n",
       " ('age', 'sponge'),\n",
       " ('coup', 'comparable'),\n",
       " ('thing', 'happening'),\n",
       " ('way', 'street'),\n",
       " ('spirituality', 'shines'),\n",
       " ('drops', 'naked'),\n",
       " ('dustin', 'hoffman'),\n",
       " ('right', 'comic'),\n",
       " ('tired', 'eyes'),\n",
       " ('assembled', 'one'),\n",
       " ('head', 'literally'),\n",
       " ('dot', 'traveling'),\n",
       " ('enemy', 'chief'),\n",
       " ('strong', 'bulworth'),\n",
       " ('films', 'watch'),\n",
       " ('films', 'like'),\n",
       " ('horde', 'neo'),\n",
       " ('anway', 'chris'),\n",
       " ('former', 'belgian'),\n",
       " ('primal', 'scare'),\n",
       " ('place', 'among'),\n",
       " ('new', 'mexico'),\n",
       " ('strongly', 'disagree'),\n",
       " ('director', 'works'),\n",
       " ('usual', 'summer'),\n",
       " ('playing', 'like'),\n",
       " ('mark', 'danvers'),\n",
       " ('midnight', 'dark'),\n",
       " ('christmas', 'setting'),\n",
       " ('rudy', 'one'),\n",
       " ('world', 'gridlock'),\n",
       " ('remake', 'reservoir'),\n",
       " ('salsa', 'adventure'),\n",
       " ('kind', 'unique'),\n",
       " ('measure', 'lapaglia'),\n",
       " ('like', 'battle'),\n",
       " ('man', 'speaking'),\n",
       " ('also', 'meets'),\n",
       " ('lumumba', 'solid'),\n",
       " ('use', 'real'),\n",
       " ('leia', 'home'),\n",
       " ('coherent', 'sentences'),\n",
       " ('dirt', 'meet'),\n",
       " ('position', 'highest'),\n",
       " ('dollar', 'order'),\n",
       " ('race', 'last'),\n",
       " ('one', 'shot'),\n",
       " ('business', 'like'),\n",
       " ('black', 'comedy'),\n",
       " ('disclaimer', 'ever'),\n",
       " ('though', 'dogma'),\n",
       " ('wise', 'knock'),\n",
       " ('could', 'squeeze'),\n",
       " ('shores', 'america'),\n",
       " ('mirthless', 'widowed'),\n",
       " ('tariq', 'anway'),\n",
       " ('designer', 'julie'),\n",
       " ('fantastic', 'speech'),\n",
       " ('although', 'mcgregor'),\n",
       " ('age', 'film'),\n",
       " ('assistant', 'murphy'),\n",
       " ('free', 'time'),\n",
       " ('established', 'early'),\n",
       " ('colorful', 'periphery'),\n",
       " ('hard', 'decisions'),\n",
       " ('rather', 'well'),\n",
       " ('peaceful', 'planet'),\n",
       " ('ray', 'liotta'),\n",
       " ('although', 'often'),\n",
       " ('dead', 'alive'),\n",
       " ('although', 'director'),\n",
       " ('clueless', 'clearly'),\n",
       " ('relief', 'provides'),\n",
       " ('characters', 'moving'),\n",
       " ('many', 'others'),\n",
       " ('trying', 'break'),\n",
       " ('like', 'song'),\n",
       " ('contributes', 'commanding'),\n",
       " ('followed', 'anticlimax'),\n",
       " ('tour', 'force'),\n",
       " ('eleven', 'kids'),\n",
       " ('cases', 'racism'),\n",
       " ('eminently', 'quotable'),\n",
       " ('sully', 'whose'),\n",
       " ('anticlimaxic', 'epilogue'),\n",
       " ('rely', 'daily'),\n",
       " ('comedy', 'need'),\n",
       " ('spend', 'years'),\n",
       " ('ashbrook', 'brings'),\n",
       " ('received', 'greater'),\n",
       " ('like', 'lot'),\n",
       " ('film', 'pure'),\n",
       " ('call', 'bad'),\n",
       " ('camera', 'especially'),\n",
       " ('plays', 'guy'),\n",
       " ('mistakenly', 'accounted'),\n",
       " ('much', 'better'),\n",
       " ('run', 'sound'),\n",
       " ('lengthy', 'rap'),\n",
       " ('twists', 'essentially'),\n",
       " ('human', 'depravity'),\n",
       " ('ninja', 'turtles'),\n",
       " ('federation', 'keep'),\n",
       " ('audiences', 'fail'),\n",
       " ('directed', 'virtuoso'),\n",
       " ('real', 'estate'),\n",
       " ('played', 'superbly'),\n",
       " ('struggling', 'find'),\n",
       " ('parkers', 'tries'),\n",
       " ('simple', 'artiness'),\n",
       " ('prerelease', 'ballyhoo'),\n",
       " ('effective', 'patriarch'),\n",
       " ('going', 'see'),\n",
       " ('every', 'nuance'),\n",
       " ('plays', 'kathleen'),\n",
       " ('get', 'made'),\n",
       " ('otis', 'redding'),\n",
       " ('bathrobes', 'grady'),\n",
       " ('time', 'community'),\n",
       " ('effects', 'create'),\n",
       " ('director', 'photography'),\n",
       " ('friend', 'mine'),\n",
       " ('station', 'disaster'),\n",
       " ('language', 'film'),\n",
       " ('flying', 'ninjas'),\n",
       " ('closely', 'intertwined'),\n",
       " ('clerks', 'smith'),\n",
       " ('much', 'courtesy'),\n",
       " ('deserves', 'oscar'),\n",
       " ('cohen', 'company'),\n",
       " ('nearly', 'memorable'),\n",
       " ('jessica', 'playing'),\n",
       " ('instead', 'prison'),\n",
       " ('could', 'improve'),\n",
       " ('entire', 'day'),\n",
       " ('force', 'obi'),\n",
       " ('norman', 'jewison'),\n",
       " ('vince', 'vieluf'),\n",
       " ('understated', 'performance'),\n",
       " ('times', 'terribly'),\n",
       " ('faking', 'deep'),\n",
       " ('island', 'fictitious'),\n",
       " ('extremely', 'passionate'),\n",
       " ('boring', 'simply'),\n",
       " ('tom', 'goes'),\n",
       " ('mediocre', 'performances'),\n",
       " ('piece', 'exquisite'),\n",
       " ('series', 'loosely'),\n",
       " ('film', 'insurrection'),\n",
       " ('lumumba', 'death'),\n",
       " ('gives', 'convincing'),\n",
       " ('holidays', 'four'),\n",
       " ('fly', 'like'),\n",
       " ('berlinger', 'directs'),\n",
       " ('planet', 'called'),\n",
       " ('big', 'brother'),\n",
       " ('walsh', 'taking'),\n",
       " ('without', 'looking'),\n",
       " ('compelling', 'sometimes'),\n",
       " ('sexuality', 'language'),\n",
       " ('commercially', 'ewan'),\n",
       " ('music', 'even'),\n",
       " ('call', 'action'),\n",
       " ('general', 'impression'),\n",
       " ('senator', 'jay'),\n",
       " ('one', 'point'),\n",
       " ('trying', 'prove'),\n",
       " ('storyline', 'cliched'),\n",
       " ('socky', 'sequence'),\n",
       " ('discussing', 'everything'),\n",
       " ('nothing', 'compared'),\n",
       " ('film', 'apart'),\n",
       " ('shark', 'jaws'),\n",
       " ('independence', 'approaches'),\n",
       " ('overacting', 'like'),\n",
       " ('minutes', 'saturday'),\n",
       " ('exasperated', 'local'),\n",
       " ('short', 'inexplicable'),\n",
       " ('begins', 'ponder'),\n",
       " ('gooding', 'currently'),\n",
       " ('styles', 'especially'),\n",
       " ('rent', 'suggest'),\n",
       " ('personality', 'impaired'),\n",
       " ('linda', 'evangelista'),\n",
       " ('could', 'shortened'),\n",
       " ('whichever', 'contestant'),\n",
       " ('feed', 'group'),\n",
       " ('perfect', 'ingenuity'),\n",
       " ('unique', 'film'),\n",
       " ('kravitz', 'gives'),\n",
       " ('news', 'lot'),\n",
       " ('anti', 'rich'),\n",
       " ('neurotic', 'rock'),\n",
       " ('better', 'film'),\n",
       " ('holiday', 'music'),\n",
       " ('neglected', 'galpal'),\n",
       " ('two', 'nineties'),\n",
       " ('closely', 'hard'),\n",
       " ('chan', 'something'),\n",
       " ('tended', 'exaggerate'),\n",
       " ('strongest', 'student'),\n",
       " ('sanders', 'running'),\n",
       " ('big', 'hurry'),\n",
       " ('town', 'reunite'),\n",
       " ('dogmatic', 'loophole'),\n",
       " ('strike', 'back'),\n",
       " ('screen', 'time'),\n",
       " ('key', 'get'),\n",
       " ('spent', 'well'),\n",
       " ('much', 'pure'),\n",
       " ('fare', 'like'),\n",
       " ('junk', 'fest'),\n",
       " ('mcgregor', 'makes'),\n",
       " ('film', 'director'),\n",
       " ('back', 'gridlock'),\n",
       " ('instead', 'focuses'),\n",
       " ('martin', 'smith'),\n",
       " ('could', 'shorten'),\n",
       " ('unscrupulous', 'brother'),\n",
       " ('grisham', 'dave'),\n",
       " ('today', 'highly'),\n",
       " ('much', 'going'),\n",
       " ('word', 'though'),\n",
       " ('movie', 'presence'),\n",
       " ('smoke', 'joints'),\n",
       " ('big', 'special'),\n",
       " ('horror', 'fans'),\n",
       " ('masochism', 'slightly'),\n",
       " ('would', 'deprive'),\n",
       " ('equally', 'deft'),\n",
       " ('ridiculous', 'twinkle'),\n",
       " ('way', 'makes'),\n",
       " ('ground', 'goes'),\n",
       " ('young', 'ensemble'),\n",
       " ('thankfully', 'alda'),\n",
       " ('two', 'together'),\n",
       " ('campbell', 'paul'),\n",
       " ('billy', 'zane'),\n",
       " ('often', 'stilted'),\n",
       " ('easy', 'listening'),\n",
       " ('mostly', 'comes'),\n",
       " ('directors', 'attempts'),\n",
       " ('position', 'leadership'),\n",
       " ('things', 'curtis'),\n",
       " ('make', 'forgive'),\n",
       " ('reliant', 'moving'),\n",
       " ('march', 'walsh'),\n",
       " ('great', 'directing'),\n",
       " ('linger', 'remember'),\n",
       " ('creek', 'sanitarium'),\n",
       " ('play', 'max'),\n",
       " ('dressed', 'black'),\n",
       " ('casting', 'directors'),\n",
       " ('order', 'make'),\n",
       " ('actress', 'watch'),\n",
       " ('younger', 'fei'),\n",
       " ('lester', 'burnham'),\n",
       " ('kind', 'job'),\n",
       " ('even', 'better'),\n",
       " ('comic', 'scene'),\n",
       " ('played', 'joe'),\n",
       " ('portrayal', 'patrice'),\n",
       " ('rescuing', 'runaway'),\n",
       " ('squirrel', 'salesperson'),\n",
       " ('heavy', 'metal'),\n",
       " ('thing', 'make'),\n",
       " ('film', 'danny'),\n",
       " ('called', 'tatooine'),\n",
       " ('last', 'three'),\n",
       " ('regular', 'guy'),\n",
       " ('erica', 'young'),\n",
       " ('commanding', 'presence'),\n",
       " ('person', 'true'),\n",
       " ('political', 'quagmire'),\n",
       " ('since', 'wall'),\n",
       " ('dramatic', 'acting'),\n",
       " ('also', 'bob'),\n",
       " ('project', 'tourists'),\n",
       " ('resentment', 'towards'),\n",
       " ('often', 'identified'),\n",
       " ('beautifully', 'constructed'),\n",
       " ('light', 'one'),\n",
       " ('sharp', 'editing'),\n",
       " ('exec', 'elizabeth'),\n",
       " ('time', 'making'),\n",
       " ('wonderful', 'capturing'),\n",
       " ('future', 'filmmakers'),\n",
       " ('spielberg', 'gives'),\n",
       " ('credit', 'never'),\n",
       " ('use', 'ironic'),\n",
       " ('one', 'american'),\n",
       " ('shop', 'london'),\n",
       " ('always', 'played'),\n",
       " ('next', 'day'),\n",
       " ('place', 'watching'),\n",
       " ('feel', 'forced'),\n",
       " ('including', 'vince'),\n",
       " ('different', 'way'),\n",
       " ('like', 'see'),\n",
       " ('time', 'contrast'),\n",
       " ('thud', 'rather'),\n",
       " ('central', 'showing'),\n",
       " ('crime', 'boss'),\n",
       " ('telling', 'story'),\n",
       " ('previously', 'helmer'),\n",
       " ('number', 'interesting'),\n",
       " ('prison', 'bars'),\n",
       " ('bentley', 'performance'),\n",
       " ('fun', 'watch'),\n",
       " ('never', 'call'),\n",
       " ('make', 'movie'),\n",
       " ('improves', 'general'),\n",
       " ('nominations', 'including'),\n",
       " ('production', 'designer'),\n",
       " ('fun', 'part'),\n",
       " ('life', 'thugs'),\n",
       " ('dream', 'sequence'),\n",
       " ('soundtrack', 'manipulative'),\n",
       " ('jackie', 'could'),\n",
       " ('fox', 'insisted'),\n",
       " ('favor', 'lambeau'),\n",
       " ('right', 'times'),\n",
       " ('grossing', 'film'),\n",
       " ('clearly', 'sets'),\n",
       " ('lot', 'interesting'),\n",
       " ('underway', 'promote'),\n",
       " ('cinematic', 'portrait'),\n",
       " ('documentary', 'director'),\n",
       " ('great', 'deal'),\n",
       " ('desert', 'world'),\n",
       " ('single', 'movie'),\n",
       " ('long', 'one'),\n",
       " ('fate', 'prisoner'),\n",
       " ('crates', 'bananas'),\n",
       " ('travel', 'silver'),\n",
       " ('gritty', 'drama'),\n",
       " ('named', 'mary'),\n",
       " ('mobutu', 'colonel'),\n",
       " ('visually', 'eye'),\n",
       " ('american', 'paris'),\n",
       " ('film', 'original'),\n",
       " ('hurricane', 'film'),\n",
       " ('monkey', 'photo'),\n",
       " ('know', 'capone'),\n",
       " ('thirteen', 'lives'),\n",
       " ('story', 'propelled'),\n",
       " ('well', 'amidala'),\n",
       " ('form', 'somewhere'),\n",
       " ('never', 'answered'),\n",
       " ('run', 'member'),\n",
       " ('depravity', 'violence'),\n",
       " ('jackson', 'steals'),\n",
       " ('batman', 'blade'),\n",
       " ('wisely', 'keeps'),\n",
       " ('lawrence', 'kazdan'),\n",
       " ('whole', 'lot'),\n",
       " ('fox', 'news'),\n",
       " ('inane', 'police'),\n",
       " ('played', 'jake'),\n",
       " ('places', 'half'),\n",
       " ('sporting', 'big'),\n",
       " ('cleavage', 'dozing'),\n",
       " ('like', 'train'),\n",
       " ('entering', 'new'),\n",
       " ('eight', 'miles'),\n",
       " ('dirty', 'city'),\n",
       " ('recognize', 'every'),\n",
       " ('mena', 'suvari'),\n",
       " ('enough', 'money'),\n",
       " ('therapists', 'lambeau'),\n",
       " ('student', 'elections'),\n",
       " ('roundabout', 'way'),\n",
       " ('adult', 'fei'),\n",
       " ('music', 'building'),\n",
       " ('jay', 'silent'),\n",
       " ('unzipped', 'cinematic'),\n",
       " ('gone', 'bad'),\n",
       " ('rarely', 'loses'),\n",
       " ('hollywood', 'major'),\n",
       " ('insurrection', 'however'),\n",
       " ('retro', 'yet'),\n",
       " ('capable', 'writer'),\n",
       " ('many', 'movies'),\n",
       " ('deceptively', 'simple'),\n",
       " ('stand', 'alone'),\n",
       " ('could', 'see'),\n",
       " ('appearance', 'thankfully'),\n",
       " ('two', 'pay'),\n",
       " ('determined', 'make'),\n",
       " ('days', 'seem'),\n",
       " ('life', 'henry'),\n",
       " ('proyas', 'seems'),\n",
       " ('unlikely', 'way'),\n",
       " ('republic', 'planets'),\n",
       " ('sunglasses', 'graham'),\n",
       " ('exciting', 'also'),\n",
       " ('mixed', 'bag'),\n",
       " ('despite', 'playing'),\n",
       " ('rolling', 'stones'),\n",
       " ('nicholas', 'pileggi'),\n",
       " ('film', 'experiment'),\n",
       " ('works', 'like'),\n",
       " ('simpler', 'happier'),\n",
       " ('ready', 'abandon'),\n",
       " ('hostage', 'matter'),\n",
       " ('shots', 'makes'),\n",
       " ('long', 'dark'),\n",
       " ('fifties', 'sitcom'),\n",
       " ('comedy', 'zooms'),\n",
       " ('fast', 'emptying'),\n",
       " ('stretch', 'sleep'),\n",
       " ('still', 'check'),\n",
       " ('introverted', 'like'),\n",
       " ('action', 'flick'),\n",
       " ('like', 'directors'),\n",
       " ('finally', 'nick'),\n",
       " ('print', 'saw'),\n",
       " ('oscar', 'time'),\n",
       " ('acting', 'discoveries'),\n",
       " ('vader', 'master'),\n",
       " ('yet', 'interesting'),\n",
       " ('spend', 'ten'),\n",
       " ('ending', 'buy'),\n",
       " ('none', 'could'),\n",
       " ('fine', 'performances'),\n",
       " ('lerner', 'lara'),\n",
       " ('surreal', 'atmosphere'),\n",
       " ('quite', 'remember'),\n",
       " ('top', 'form'),\n",
       " ('mexico', 'masquerading'),\n",
       " ('rebellious', 'mary'),\n",
       " ('decisions', 'order'),\n",
       " ('sound', 'system'),\n",
       " ('one', 'first'),\n",
       " ('beauty', 'alan'),\n",
       " ('get', 'bit'),\n",
       " ('lolita', 'kevin'),\n",
       " ('minded', 'mayor'),\n",
       " ('nature', 'touch'),\n",
       " ('sits', 'behind'),\n",
       " ('much', 'resist'),\n",
       " ('cut', 'good'),\n",
       " ('commercial', 'success'),\n",
       " ('roth', 'play'),\n",
       " ('standing', 'line'),\n",
       " ('janney', 'peter'),\n",
       " ('pregnant', 'tristen'),\n",
       " ('somewhat', 'still'),\n",
       " ('take', 'roman'),\n",
       " ('norton', 'play'),\n",
       " ('thugs', 'kidnap'),\n",
       " ('picard', 'defies'),\n",
       " ('echoed', 'gridlock'),\n",
       " ('seem', 'blandly'),\n",
       " ('named', 'steven'),\n",
       " ('towering', 'transvestite'),\n",
       " ('terms', 'narration'),\n",
       " ('bit', 'involving'),\n",
       " ('constructed', 'film'),\n",
       " ('tarantino', 'smith'),\n",
       " ('completely', 'absurd'),\n",
       " ('soldier', 'truck'),\n",
       " ('classy', 'piece'),\n",
       " ('otherwise', 'memorable'),\n",
       " ('westerns', 'dance'),\n",
       " ('absolute', 'truth'),\n",
       " ('mean', 'one'),\n",
       " ('call', 'trash'),\n",
       " ('charnel', 'house'),\n",
       " ('hoax', 'everyone'),\n",
       " ('would', 'became'),\n",
       " ('thing', 'common'),\n",
       " ('man', 'next'),\n",
       " ('met', 'inspector'),\n",
       " ('half', 'dozen'),\n",
       " ('scenario', 'possible'),\n",
       " ('race', 'claims'),\n",
       " ('overnight', 'success'),\n",
       " ('well', 'anything'),\n",
       " ('another', 'sneak'),\n",
       " ('ivan', 'reitman'),\n",
       " ('urban', 'realism'),\n",
       " ('also', 'inherently'),\n",
       " ('bring', 'people'),\n",
       " ('fair', 'know'),\n",
       " ('always', 'magnetic'),\n",
       " ('bloody', 'clashes'),\n",
       " ('made', 'surrender'),\n",
       " ('film', 'however'),\n",
       " ('skillfully', 'brings'),\n",
       " ('inside', 'computer'),\n",
       " ('like', 'exqueeze'),\n",
       " ('rehab', 'time'),\n",
       " ('hometown', 'kingston'),\n",
       " ('first', 'head'),\n",
       " ('sinise', 'forrest'),\n",
       " ('community', 'college'),\n",
       " ('american', 'beauty'),\n",
       " ('nicolas', 'cage'),\n",
       " ('two', 'years'),\n",
       " ('abuse', 'permanent'),\n",
       " ('primary', 'reason'),\n",
       " ('rolling', 'clients'),\n",
       " ('city', 'utah'),\n",
       " ('fiery', 'entrance'),\n",
       " ('dora', 'fernanda'),\n",
       " ('town', 'order'),\n",
       " ('fashion', 'despite'),\n",
       " ('landed', 'ship'),\n",
       " ('play', 'someone'),\n",
       " ('hard', 'imagine'),\n",
       " ('bride', 'working'),\n",
       " ('aging', 'cop'),\n",
       " ('characters', 'strange'),\n",
       " ('greater', 'part'),\n",
       " ('holiday', 'movie'),\n",
       " ('jamaican', 'film'),\n",
       " ('acting', 'great'),\n",
       " ('original', 'shortly'),\n",
       " ('eddie', 'campbell'),\n",
       " ('role', 'drug'),\n",
       " ('atmosphere', 'awe'),\n",
       " ('boast', 'superstar'),\n",
       " ('clerical', 'job'),\n",
       " ('still', 'boorem'),\n",
       " ('television', 'writer'),\n",
       " ('syndicate', 'assassinate'),\n",
       " ('would', 'write'),\n",
       " ('adventures', 'snakes'),\n",
       " ('apprentice', 'one'),\n",
       " ('teenage', 'mutant'),\n",
       " ('family', 'heads'),\n",
       " ('toontown', 'trying'),\n",
       " ('movie', 'fails'),\n",
       " ('story', 'progresses'),\n",
       " ('like', 'losin'),\n",
       " ('block', 'bureaucracy'),\n",
       " ('month', 'box'),\n",
       " ('times', 'pollini'),\n",
       " ('movie', 'opens'),\n",
       " ('meanest', 'derek'),\n",
       " ('maintain', 'peace'),\n",
       " ('michael', 'lerner'),\n",
       " ('morals', 'etc'),\n",
       " ('hill', 'seduce'),\n",
       " ('wish', 'wonder'),\n",
       " ('good', 'guys'),\n",
       " ('pays', 'welcome'),\n",
       " ('grubby', 'fingers'),\n",
       " ('outbursts', 'homicidal'),\n",
       " ('half', 'notch'),\n",
       " ('work', 'film'),\n",
       " ('humor', 'remarkably'),\n",
       " ('detective', 'vergil'),\n",
       " ('film', 'american'),\n",
       " ('fourth', 'july'),\n",
       " ('enjoys', 'concocting'),\n",
       " ('morning', 'responds'),\n",
       " ('picture', 'designer'),\n",
       " ('smith', 'bethany'),\n",
       " ('horribly', 'disfigured'),\n",
       " ('people', 'called'),\n",
       " ('couple', 'years'),\n",
       " ('first', 'summer'),\n",
       " ('father', 'wong'),\n",
       " ('fluke', 'savant'),\n",
       " ('souls', 'include'),\n",
       " ('carter', 'burwell'),\n",
       " ('land', 'san'),\n",
       " ('film', 'still'),\n",
       " ('walk', 'eight'),\n",
       " ('genius', 'woody'),\n",
       " ('audience', 'works'),\n",
       " ('wonderful', 'job'),\n",
       " ('baby', 'yeah'),\n",
       " ('last', 'four'),\n",
       " ('bigots', 'matter'),\n",
       " ('fox', 'searchlight'),\n",
       " ('tried', 'block'),\n",
       " ('true', 'fact'),\n",
       " ('words', 'escape'),\n",
       " ('slackers', 'brian'),\n",
       " ('contained', 'percent'),\n",
       " ('cinema', 'verite'),\n",
       " ('middle', 'class'),\n",
       " ('scorsese', 'jesus'),\n",
       " ('gift', 'singled'),\n",
       " ('entitled', 'countryman'),\n",
       " ('tardis', 'outsmarting'),\n",
       " ('good', 'job'),\n",
       " ('stars', 'amidst'),\n",
       " ('work', 'still'),\n",
       " ('gordon', 'gecko'),\n",
       " ('head', 'maroon'),\n",
       " ('outdoor', 'rally'),\n",
       " ('kind', 'alien'),\n",
       " ('movie', 'based'),\n",
       " ('nina', 'feel'),\n",
       " ('original', 'inventive'),\n",
       " ('floating', 'films'),\n",
       " ('metatron', 'alan'),\n",
       " ('oscar', 'worthy'),\n",
       " ('surgeon', 'grace'),\n",
       " ('creative', 'filmmaker'),\n",
       " ('never', 'sends'),\n",
       " ('back', 'gallifrey'),\n",
       " ('stiller', 'contributes'),\n",
       " ('two', 'families'),\n",
       " ('crouching', 'tiger'),\n",
       " ('gleiberman', 'weekly'),\n",
       " ('born', 'slaves'),\n",
       " ('time', 'even'),\n",
       " ('cosmic', 'cliche'),\n",
       " ('career', 'also'),\n",
       " ('different', 'fact'),\n",
       " ('angles', 'many'),\n",
       " ('entire', 'cast'),\n",
       " ('matrix', 'man'),\n",
       " ('said', 'rant'),\n",
       " ('written', 'hall'),\n",
       " ('city', 'actually'),\n",
       " ('apartment', 'medieval'),\n",
       " ('broken', 'arrow'),\n",
       " ('airplane', 'somebody'),\n",
       " ('jackson', 'tipped'),\n",
       " ('see', 'stage'),\n",
       " ('ironic', 'contrast'),\n",
       " ('blown', 'star'),\n",
       " ('mant', 'serves'),\n",
       " ('richard', 'dreyfuss'),\n",
       " ('deserved', 'big'),\n",
       " ('spend', 'couple'),\n",
       " ('sorely', 'overlooked'),\n",
       " ('evoke', 'strong'),\n",
       " ('discoveries', 'mie'),\n",
       " ('archeologist', 'indiana'),\n",
       " ('power', 'goes'),\n",
       " ('movie', 'operation'),\n",
       " ('action', 'sequences'),\n",
       " ('pyramids', 'less'),\n",
       " ('rich', 'although'),\n",
       " ('great', 'range'),\n",
       " ('limitations', 'faced'),\n",
       " ('masseuse', 'larious'),\n",
       " ('wonie', 'jamaican'),\n",
       " ('end', 'credits'),\n",
       " ('film', 'soon'),\n",
       " ('dialogue', 'narrator'),\n",
       " ('lanai', 'chapman'),\n",
       " ('internal', 'affairs'),\n",
       " ('trek', 'generations'),\n",
       " ('unprotected', 'legs'),\n",
       " ('lot', 'shouting'),\n",
       " ('largely', 'attributed'),\n",
       " ('seemed', 'completed'),\n",
       " ('third', 'world'),\n",
       " ('keep', 'track'),\n",
       " ('book', 'chain'),\n",
       " ('well', 'souls'),\n",
       " ('ricardo', 'etc'),\n",
       " ('come', 'surprise'),\n",
       " ('combination', 'actual'),\n",
       " ('joyous', 'movie'),\n",
       " ('incidentally', 'metal'),\n",
       " ('essence', 'statement'),\n",
       " ('bobby', 'garfield'),\n",
       " ('world', 'however'),\n",
       " ('best', 'sound'),\n",
       " ('however', 'mcgregor'),\n",
       " ('brutally', 'murdered'),\n",
       " ('felt', 'sentimental'),\n",
       " ('defense', 'minister'),\n",
       " ('example', 'homer'),\n",
       " ('barton', 'fink'),\n",
       " ('oddly', 'effective'),\n",
       " ('boy', 'whose'),\n",
       " ('able', 'take'),\n",
       " ('act', 'unlike'),\n",
       " ('racer', 'racer'),\n",
       " ('clinic', 'counselor'),\n",
       " ('captain', 'actually'),\n",
       " ('much', 'younger'),\n",
       " ('ghetto', 'bulworth'),\n",
       " ('literary', 'academia'),\n",
       " ('mie', 'renier'),\n",
       " ('effective', 'pop'),\n",
       " ('funny', 'picture'),\n",
       " ('fingered', 'jay'),\n",
       " ('offensive', 'suppose'),\n",
       " ('pretty', 'good'),\n",
       " ('film', 'one'),\n",
       " ('lia', 'one'),\n",
       " ('carrey', 'thought'),\n",
       " ('family', 'gatherings'),\n",
       " ('judge', 'doom'),\n",
       " ('scratch', 'far'),\n",
       " ('honest', 'citizens'),\n",
       " ('officer', 'must'),\n",
       " ('august', 'making'),\n",
       " ('face', 'see'),\n",
       " ('beautiful', 'talented'),\n",
       " ('daughter', 'girlfriend'),\n",
       " ('lambeau', 'list'),\n",
       " ('presents', 'derek'),\n",
       " ('movie', 'allows'),\n",
       " ('actual', 'footage'),\n",
       " ('time', 'gun'),\n",
       " ('interesting', 'story'),\n",
       " ('safeties', 'centers'),\n",
       " ('someone', 'believe'),\n",
       " ('parties', 'bring'),\n",
       " ('somebody', 'else'),\n",
       " ('attempts', 'get'),\n",
       " ('member', 'criminal'),\n",
       " ('paulie', 'cicero'),\n",
       " ('slogan', 'catholicism'),\n",
       " ('role', 'life'),\n",
       " ('camp', 'factor'),\n",
       " ('awfulness', 'bulworth'),\n",
       " ('actors', 'working'),\n",
       " ('motion', 'kicking'),\n",
       " ('call', 'high'),\n",
       " ('real', 'countries'),\n",
       " ('jokes', 'exist'),\n",
       " ('films', 'norman'),\n",
       " ('spielberg', 'manages'),\n",
       " ('metal', 'god'),\n",
       " ('becomes', 'eye'),\n",
       " ('recent', 'period'),\n",
       " ('stalwart', 'saint'),\n",
       " ('next', 'einstein'),\n",
       " ('warning', 'major'),\n",
       " ('kept', 'pushing'),\n",
       " ('risk', 'course'),\n",
       " ('good', 'action'),\n",
       " ('force', 'strong'),\n",
       " ('bible', 'thumper'),\n",
       " ('mind', 'heads'),\n",
       " ('week', 'noticed'),\n",
       " ('quality', 'action'),\n",
       " ('unpaved', 'roads'),\n",
       " ('horrible', 'nightmares'),\n",
       " ('girl', 'caught'),\n",
       " ('cinque', 'language'),\n",
       " ('adrenaline', 'rush'),\n",
       " ('difficult', 'time'),\n",
       " ('parents', 'hippies'),\n",
       " ('government', 'might'),\n",
       " ('hindrance', 'enough'),\n",
       " ('good', 'direction'),\n",
       " ('deadpan', 'man'),\n",
       " ('film', 'able'),\n",
       " ('repeated', 'course'),\n",
       " ('mostly', 'laughable'),\n",
       " ('make', 'shift'),\n",
       " ('dreariness', 'victorian'),\n",
       " ('african', 'settings'),\n",
       " ('heart', 'attack'),\n",
       " ('profane', 'angels'),\n",
       " ('spielberg', 'one'),\n",
       " ('iridescent', 'performances'),\n",
       " ('making', 'duds'),\n",
       " ('never', 'aware'),\n",
       " ('joan', 'allen'),\n",
       " ('shaken', 'several'),\n",
       " ('menace', 'although'),\n",
       " ('incredible', 'sense'),\n",
       " ('film', 'becomes'),\n",
       " ('pestering', 'small'),\n",
       " ('sullen', 'apathy'),\n",
       " ('unlike', 'chewbacca'),\n",
       " ('movie', 'smart'),\n",
       " ('film', 'utilize'),\n",
       " ('district', 'attorney'),\n",
       " ('get', 'glimpse'),\n",
       " ('alone', 'viewing'),\n",
       " ('obnoxious', 'man'),\n",
       " ('start', 'wonder'),\n",
       " ('delight', 'dandy'),\n",
       " ('remaining', 'whites'),\n",
       " ('fans', 'would'),\n",
       " ('toed', 'floating'),\n",
       " ('time', 'minimum'),\n",
       " ('geniuses', 'behind'),\n",
       " ('would', 'make'),\n",
       " ('depp', 'turning'),\n",
       " ('diaz', 'character'),\n",
       " ('frame', 'frame'),\n",
       " ('framed', 'although'),\n",
       " ('wars', 'also'),\n",
       " ('groom', 'molly'),\n",
       " ('characters', 'williams'),\n",
       " ('family', 'something'),\n",
       " ('several', 'bee'),\n",
       " ('several', 'noteworthy'),\n",
       " ('everyone', 'blame'),\n",
       " ('convincing', 'charismatic'),\n",
       " ('say', 'city'),\n",
       " ('makes', 'feel'),\n",
       " ('want', 'drown'),\n",
       " ('slow', 'jock'),\n",
       " ('line', 'regarding'),\n",
       " ('paramount', 'pictures'),\n",
       " ('antics', 'john'),\n",
       " ('movies', 'would'),\n",
       " ('time', 'bringing'),\n",
       " ('best', 'film'),\n",
       " ('tough', 'spunky'),\n",
       " ('chains', 'tibbs'),\n",
       " ('likely', 'mentally'),\n",
       " ('danny', 'roman'),\n",
       " ('strictly', 'sitcom'),\n",
       " ('film', 'couple'),\n",
       " ('viable', 'threats'),\n",
       " ('cliche', 'police'),\n",
       " ('sorts', 'plays'),\n",
       " ('planet', 'skaro'),\n",
       " ('forgive', 'anyone'),\n",
       " ('used', 'well'),\n",
       " ('barry', 'sanders'),\n",
       " ('convention', 'pollini'),\n",
       " ('power', 'masse'),\n",
       " ('warning', 'spoilers'),\n",
       " ('worthwhile', 'movie'),\n",
       " ('niebaum', 'may'),\n",
       " ('gibson', 'plays'),\n",
       " ('viewer', 'moralistic'),\n",
       " ('man', 'accomplishes'),\n",
       " ('cover', 'similar'),\n",
       " ('way', 'book'),\n",
       " ('whole', 'way'),\n",
       " ('eventually', 'toontown'),\n",
       " ('lying', 'bastard'),\n",
       " ('extensive', 'use'),\n",
       " ('slept', 'days'),\n",
       " ('character', 'best'),\n",
       " ('judge', 'jury'),\n",
       " ('dominic', 'west'),\n",
       " ('job', 'actually'),\n",
       " ('boys', 'party'),\n",
       " ('outdoor', 'concert'),\n",
       " ('director', 'michael'),\n",
       " ('gun', 'smuggler'),\n",
       " ('movie', 'database'),\n",
       " ('satirical', 'cardinal'),\n",
       " ('became', 'age'),\n",
       " ('furlong', 'mother'),\n",
       " ('general', 'since'),\n",
       " ('last', 'nemesis'),\n",
       " ('performance', 'unlike'),\n",
       " ('directed', 'empire'),\n",
       " ('sci', 'violence'),\n",
       " ('still', 'seen'),\n",
       " ('old', 'chestnut'),\n",
       " ('continues', 'throughout'),\n",
       " ('shot', 'odd'),\n",
       " ('like', 'manipulation'),\n",
       " ('greater', 'respect'),\n",
       " ('characters', 'jar'),\n",
       " ('horror', 'like'),\n",
       " ('flash', 'eric'),\n",
       " ('final', 'impression'),\n",
       " ('industry', 'snap'),\n",
       " ('resolution', 'featuring'),\n",
       " ('hole', 'somebody'),\n",
       " ('burbank', 'jim'),\n",
       " ('friend', 'also'),\n",
       " ('drug', 'scene'),\n",
       " ('car', 'find'),\n",
       " ('designer', 'mizrahi'),\n",
       " ('many', 'significant'),\n",
       " ('face', 'resembles'),\n",
       " ('fare', 'nearly'),\n",
       " ('good', 'cop'),\n",
       " ('waited', 'twenty'),\n",
       " ('zoolander', 'character'),\n",
       " ('small', 'force'),\n",
       " ('white', 'town'),\n",
       " ('never', 'actually'),\n",
       " ('far', 'away'),\n",
       " ('soldier', 'story'),\n",
       " ('ponder', 'exactly'),\n",
       " ('pure', 'appetite'),\n",
       " ('used', 'super'),\n",
       " ('kung', 'tune'),\n",
       " ('affords', 'affectionate'),\n",
       " ('latter', 'klingon'),\n",
       " ('money', 'crown'),\n",
       " ('soft', 'spoken'),\n",
       " ('known', 'pioneer'),\n",
       " ('going', 'like'),\n",
       " ('introduced', 'young'),\n",
       " ('selling', 'twig'),\n",
       " ('welcome', 'change'),\n",
       " ('feelings', 'definitely'),\n",
       " ('wars', 'took'),\n",
       " ('screen', 'presence'),\n",
       " ('sympathy', 'ratty'),\n",
       " ('discount', 'book'),\n",
       " ('generated', 'one'),\n",
       " ('also', 'plays'),\n",
       " ('tracy', 'flick'),\n",
       " ('run', 'children'),\n",
       " ('may', 'home'),\n",
       " ('since', 'seen'),\n",
       " ('ironic', 'prologue'),\n",
       " ('wonders', 'ride'),\n",
       " ('kathy', 'moriarty'),\n",
       " ('referee', 'cost'),\n",
       " ('organizing', 'block'),\n",
       " ('bulworth', 'ended'),\n",
       " ('slapstick', 'intended'),\n",
       " ('thereby', 'rendering'),\n",
       " ('bounding', 'around'),\n",
       " ('goes', 'slack'),\n",
       " ('speech', 'adams'),\n",
       " ('jewison', 'classic'),\n",
       " ('huge', 'special'),\n",
       " ('trek', 'fans'),\n",
       " ('underlings', 'seem'),\n",
       " ('natural', 'genius'),\n",
       " ('named', 'quint'),\n",
       " ('action', 'film'),\n",
       " ('achingly', 'honest'),\n",
       " ('probation', 'instead'),\n",
       " ('plots', 'serve'),\n",
       " ('recruits', 'helicopter'),\n",
       " ('blatant', 'exposition'),\n",
       " ('secret', 'event'),\n",
       " ('shark', 'killer'),\n",
       " ('initial', 'success'),\n",
       " ('always', 'understated'),\n",
       " ('mining', 'town'),\n",
       " ('officer', 'sam'),\n",
       " ('ping', 'eventually'),\n",
       " ('give', 'criticism'),\n",
       " ('convenience', 'store'),\n",
       " ('catch', 'jarmusch'),\n",
       " ('gets', 'transfer'),\n",
       " ('geeks', 'revenge'),\n",
       " ('homicidal', 'violence'),\n",
       " ('two', 'aides'),\n",
       " ('alda', 'film'),\n",
       " ('better', 'cold'),\n",
       " ('blind', 'dog'),\n",
       " ('ship', 'world'),\n",
       " ('also', 'gives'),\n",
       " ('filmmaker', 'world'),\n",
       " ('resolution', 'get'),\n",
       " ('song', 'lyric'),\n",
       " ('stonecutters', 'song'),\n",
       " ('talented', 'musicians'),\n",
       " ('probably', 'never'),\n",
       " ('eddie', 'valiant'),\n",
       " ('comparing', 'scars'),\n",
       " ('money', 'witherspoon'),\n",
       " ('almost', 'pastoral'),\n",
       " ('seems', 'mistaken'),\n",
       " ('excellent', 'acting'),\n",
       " ('spiner', 'discovering'),\n",
       " ('spectacular', 'robberies'),\n",
       " ('trying', 'jump'),\n",
       " ('mentor', 'ness'),\n",
       " ('great', 'films'),\n",
       " ('best', 'audience'),\n",
       " ('rent', 'recently'),\n",
       " ('writers', 'though'),\n",
       " ('caring', 'totally'),\n",
       " ('keeps', 'ringwald'),\n",
       " ('movie', 'sinise'),\n",
       " ('phil', 'segal'),\n",
       " ('laughable', 'details'),\n",
       " ('party', 'fits'),\n",
       " ('long', 'time'),\n",
       " ('sculptures', 'stones'),\n",
       " ('example', 'acting'),\n",
       " ('guys', 'first'),\n",
       " ('nation', 'first'),\n",
       " ('amount', 'sexuality'),\n",
       " ('fellow', 'police'),\n",
       " ('temptation', 'fix'),\n",
       " ('individuals', 'enthralled'),\n",
       " ('soft', 'drinks'),\n",
       " ('times', 'find'),\n",
       " ('unzipped', 'variety'),\n",
       " ('hard', 'fans'),\n",
       " ('novelty', 'wears'),\n",
       " ('audience', 'pre'),\n",
       " ('time', 'janeane'),\n",
       " ('pretty', 'entertaining'),\n",
       " ...}"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "set1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10636"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(set1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "mat=np.zeros([df.shape[0],len(set1)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 0.,  0.,  0., ...,  0.,  0.,  0.],\n",
       "       [ 0.,  0.,  0., ...,  0.,  0.,  0.],\n",
       "       [ 0.,  0.,  0., ...,  0.,  0.,  0.],\n",
       "       ..., \n",
       "       [ 0.,  0.,  0., ...,  0.,  0.,  0.],\n",
       "       [ 0.,  0.,  0., ...,  0.,  0.,  0.],\n",
       "       [ 0.,  0.,  0., ...,  0.,  0.,  0.]])"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mat"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "d=dict()\n",
    "k=0;\n",
    "for i in set1:\n",
    "    d[i]=k\n",
    "    k=k+1\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{('similar', 'aptitude'): 0,\n",
       " ('company', 'keeps'): 1,\n",
       " ('dick', 'tracy'): 2,\n",
       " ('hard', 'time'): 3,\n",
       " ('coppola', 'influence'): 4,\n",
       " ('vader', 'skywalker'): 5,\n",
       " ('maybe', 'two'): 6,\n",
       " ('title', 'course'): 7,\n",
       " ('two', 'mistakenly'): 8,\n",
       " ('show', 'doctor'): 9,\n",
       " ('age', 'sponge'): 10,\n",
       " ('coup', 'comparable'): 11,\n",
       " ('thing', 'happening'): 12,\n",
       " ('way', 'street'): 13,\n",
       " ('spirituality', 'shines'): 14,\n",
       " ('drops', 'naked'): 15,\n",
       " ('dustin', 'hoffman'): 16,\n",
       " ('right', 'comic'): 17,\n",
       " ('tired', 'eyes'): 18,\n",
       " ('assembled', 'one'): 19,\n",
       " ('head', 'literally'): 20,\n",
       " ('dot', 'traveling'): 21,\n",
       " ('enemy', 'chief'): 22,\n",
       " ('strong', 'bulworth'): 23,\n",
       " ('films', 'watch'): 24,\n",
       " ('films', 'like'): 25,\n",
       " ('horde', 'neo'): 26,\n",
       " ('anway', 'chris'): 27,\n",
       " ('former', 'belgian'): 28,\n",
       " ('primal', 'scare'): 29,\n",
       " ('place', 'among'): 30,\n",
       " ('new', 'mexico'): 31,\n",
       " ('strongly', 'disagree'): 32,\n",
       " ('director', 'works'): 33,\n",
       " ('usual', 'summer'): 34,\n",
       " ('playing', 'like'): 35,\n",
       " ('mark', 'danvers'): 36,\n",
       " ('midnight', 'dark'): 37,\n",
       " ('christmas', 'setting'): 38,\n",
       " ('rudy', 'one'): 39,\n",
       " ('world', 'gridlock'): 40,\n",
       " ('remake', 'reservoir'): 41,\n",
       " ('salsa', 'adventure'): 42,\n",
       " ('kind', 'unique'): 43,\n",
       " ('measure', 'lapaglia'): 44,\n",
       " ('like', 'battle'): 45,\n",
       " ('man', 'speaking'): 46,\n",
       " ('also', 'meets'): 47,\n",
       " ('lumumba', 'solid'): 48,\n",
       " ('use', 'real'): 49,\n",
       " ('leia', 'home'): 50,\n",
       " ('coherent', 'sentences'): 51,\n",
       " ('dirt', 'meet'): 52,\n",
       " ('position', 'highest'): 53,\n",
       " ('dollar', 'order'): 54,\n",
       " ('race', 'last'): 55,\n",
       " ('one', 'shot'): 56,\n",
       " ('business', 'like'): 57,\n",
       " ('black', 'comedy'): 58,\n",
       " ('disclaimer', 'ever'): 59,\n",
       " ('though', 'dogma'): 60,\n",
       " ('wise', 'knock'): 61,\n",
       " ('could', 'squeeze'): 62,\n",
       " ('shores', 'america'): 63,\n",
       " ('mirthless', 'widowed'): 64,\n",
       " ('tariq', 'anway'): 65,\n",
       " ('designer', 'julie'): 66,\n",
       " ('fantastic', 'speech'): 67,\n",
       " ('although', 'mcgregor'): 68,\n",
       " ('age', 'film'): 69,\n",
       " ('assistant', 'murphy'): 70,\n",
       " ('free', 'time'): 71,\n",
       " ('established', 'early'): 72,\n",
       " ('colorful', 'periphery'): 73,\n",
       " ('hard', 'decisions'): 74,\n",
       " ('rather', 'well'): 75,\n",
       " ('peaceful', 'planet'): 76,\n",
       " ('ray', 'liotta'): 77,\n",
       " ('although', 'often'): 78,\n",
       " ('dead', 'alive'): 79,\n",
       " ('although', 'director'): 80,\n",
       " ('clueless', 'clearly'): 81,\n",
       " ('relief', 'provides'): 82,\n",
       " ('characters', 'moving'): 83,\n",
       " ('many', 'others'): 84,\n",
       " ('trying', 'break'): 85,\n",
       " ('like', 'song'): 86,\n",
       " ('contributes', 'commanding'): 87,\n",
       " ('followed', 'anticlimax'): 88,\n",
       " ('tour', 'force'): 89,\n",
       " ('eleven', 'kids'): 90,\n",
       " ('cases', 'racism'): 91,\n",
       " ('eminently', 'quotable'): 92,\n",
       " ('sully', 'whose'): 93,\n",
       " ('anticlimaxic', 'epilogue'): 94,\n",
       " ('rely', 'daily'): 95,\n",
       " ('comedy', 'need'): 96,\n",
       " ('spend', 'years'): 97,\n",
       " ('ashbrook', 'brings'): 98,\n",
       " ('received', 'greater'): 99,\n",
       " ('like', 'lot'): 100,\n",
       " ('film', 'pure'): 101,\n",
       " ('call', 'bad'): 102,\n",
       " ('camera', 'especially'): 103,\n",
       " ('plays', 'guy'): 104,\n",
       " ('mistakenly', 'accounted'): 105,\n",
       " ('much', 'better'): 106,\n",
       " ('run', 'sound'): 107,\n",
       " ('lengthy', 'rap'): 108,\n",
       " ('twists', 'essentially'): 109,\n",
       " ('human', 'depravity'): 110,\n",
       " ('ninja', 'turtles'): 111,\n",
       " ('federation', 'keep'): 112,\n",
       " ('audiences', 'fail'): 113,\n",
       " ('directed', 'virtuoso'): 114,\n",
       " ('real', 'estate'): 115,\n",
       " ('played', 'superbly'): 116,\n",
       " ('struggling', 'find'): 117,\n",
       " ('parkers', 'tries'): 118,\n",
       " ('simple', 'artiness'): 119,\n",
       " ('prerelease', 'ballyhoo'): 120,\n",
       " ('effective', 'patriarch'): 121,\n",
       " ('going', 'see'): 122,\n",
       " ('every', 'nuance'): 123,\n",
       " ('plays', 'kathleen'): 124,\n",
       " ('get', 'made'): 125,\n",
       " ('otis', 'redding'): 126,\n",
       " ('bathrobes', 'grady'): 127,\n",
       " ('time', 'community'): 128,\n",
       " ('effects', 'create'): 129,\n",
       " ('director', 'photography'): 130,\n",
       " ('friend', 'mine'): 131,\n",
       " ('station', 'disaster'): 132,\n",
       " ('language', 'film'): 133,\n",
       " ('flying', 'ninjas'): 134,\n",
       " ('closely', 'intertwined'): 135,\n",
       " ('clerks', 'smith'): 136,\n",
       " ('much', 'courtesy'): 137,\n",
       " ('deserves', 'oscar'): 138,\n",
       " ('cohen', 'company'): 139,\n",
       " ('nearly', 'memorable'): 140,\n",
       " ('jessica', 'playing'): 141,\n",
       " ('instead', 'prison'): 142,\n",
       " ('could', 'improve'): 143,\n",
       " ('entire', 'day'): 144,\n",
       " ('force', 'obi'): 145,\n",
       " ('norman', 'jewison'): 146,\n",
       " ('vince', 'vieluf'): 147,\n",
       " ('understated', 'performance'): 148,\n",
       " ('times', 'terribly'): 149,\n",
       " ('faking', 'deep'): 150,\n",
       " ('island', 'fictitious'): 151,\n",
       " ('extremely', 'passionate'): 152,\n",
       " ('boring', 'simply'): 153,\n",
       " ('tom', 'goes'): 154,\n",
       " ('mediocre', 'performances'): 155,\n",
       " ('piece', 'exquisite'): 156,\n",
       " ('series', 'loosely'): 157,\n",
       " ('film', 'insurrection'): 158,\n",
       " ('lumumba', 'death'): 159,\n",
       " ('gives', 'convincing'): 160,\n",
       " ('holidays', 'four'): 161,\n",
       " ('fly', 'like'): 162,\n",
       " ('berlinger', 'directs'): 163,\n",
       " ('planet', 'called'): 164,\n",
       " ('big', 'brother'): 165,\n",
       " ('walsh', 'taking'): 166,\n",
       " ('without', 'looking'): 167,\n",
       " ('compelling', 'sometimes'): 168,\n",
       " ('sexuality', 'language'): 169,\n",
       " ('commercially', 'ewan'): 170,\n",
       " ('music', 'even'): 171,\n",
       " ('call', 'action'): 172,\n",
       " ('general', 'impression'): 173,\n",
       " ('senator', 'jay'): 174,\n",
       " ('one', 'point'): 175,\n",
       " ('trying', 'prove'): 176,\n",
       " ('storyline', 'cliched'): 177,\n",
       " ('socky', 'sequence'): 178,\n",
       " ('discussing', 'everything'): 179,\n",
       " ('nothing', 'compared'): 180,\n",
       " ('film', 'apart'): 181,\n",
       " ('shark', 'jaws'): 182,\n",
       " ('independence', 'approaches'): 183,\n",
       " ('overacting', 'like'): 184,\n",
       " ('minutes', 'saturday'): 185,\n",
       " ('exasperated', 'local'): 186,\n",
       " ('short', 'inexplicable'): 187,\n",
       " ('begins', 'ponder'): 188,\n",
       " ('gooding', 'currently'): 189,\n",
       " ('styles', 'especially'): 190,\n",
       " ('rent', 'suggest'): 191,\n",
       " ('personality', 'impaired'): 192,\n",
       " ('linda', 'evangelista'): 193,\n",
       " ('could', 'shortened'): 194,\n",
       " ('whichever', 'contestant'): 195,\n",
       " ('feed', 'group'): 196,\n",
       " ('perfect', 'ingenuity'): 197,\n",
       " ('unique', 'film'): 198,\n",
       " ('kravitz', 'gives'): 199,\n",
       " ('news', 'lot'): 200,\n",
       " ('anti', 'rich'): 201,\n",
       " ('neurotic', 'rock'): 202,\n",
       " ('better', 'film'): 203,\n",
       " ('holiday', 'music'): 204,\n",
       " ('neglected', 'galpal'): 205,\n",
       " ('two', 'nineties'): 206,\n",
       " ('closely', 'hard'): 207,\n",
       " ('chan', 'something'): 208,\n",
       " ('tended', 'exaggerate'): 209,\n",
       " ('strongest', 'student'): 210,\n",
       " ('sanders', 'running'): 211,\n",
       " ('big', 'hurry'): 212,\n",
       " ('town', 'reunite'): 213,\n",
       " ('dogmatic', 'loophole'): 214,\n",
       " ('strike', 'back'): 215,\n",
       " ('screen', 'time'): 216,\n",
       " ('key', 'get'): 217,\n",
       " ('spent', 'well'): 218,\n",
       " ('much', 'pure'): 219,\n",
       " ('fare', 'like'): 220,\n",
       " ('junk', 'fest'): 221,\n",
       " ('mcgregor', 'makes'): 222,\n",
       " ('film', 'director'): 223,\n",
       " ('back', 'gridlock'): 224,\n",
       " ('instead', 'focuses'): 225,\n",
       " ('martin', 'smith'): 226,\n",
       " ('could', 'shorten'): 227,\n",
       " ('unscrupulous', 'brother'): 228,\n",
       " ('grisham', 'dave'): 229,\n",
       " ('today', 'highly'): 230,\n",
       " ('much', 'going'): 231,\n",
       " ('word', 'though'): 232,\n",
       " ('movie', 'presence'): 233,\n",
       " ('smoke', 'joints'): 234,\n",
       " ('big', 'special'): 235,\n",
       " ('horror', 'fans'): 236,\n",
       " ('masochism', 'slightly'): 237,\n",
       " ('would', 'deprive'): 238,\n",
       " ('equally', 'deft'): 239,\n",
       " ('ridiculous', 'twinkle'): 240,\n",
       " ('way', 'makes'): 241,\n",
       " ('ground', 'goes'): 242,\n",
       " ('young', 'ensemble'): 243,\n",
       " ('thankfully', 'alda'): 244,\n",
       " ('two', 'together'): 245,\n",
       " ('campbell', 'paul'): 246,\n",
       " ('billy', 'zane'): 247,\n",
       " ('often', 'stilted'): 248,\n",
       " ('easy', 'listening'): 249,\n",
       " ('mostly', 'comes'): 250,\n",
       " ('directors', 'attempts'): 251,\n",
       " ('position', 'leadership'): 252,\n",
       " ('things', 'curtis'): 253,\n",
       " ('make', 'forgive'): 254,\n",
       " ('reliant', 'moving'): 255,\n",
       " ('march', 'walsh'): 256,\n",
       " ('great', 'directing'): 257,\n",
       " ('linger', 'remember'): 258,\n",
       " ('creek', 'sanitarium'): 259,\n",
       " ('play', 'max'): 260,\n",
       " ('dressed', 'black'): 261,\n",
       " ('casting', 'directors'): 262,\n",
       " ('order', 'make'): 263,\n",
       " ('actress', 'watch'): 264,\n",
       " ('younger', 'fei'): 265,\n",
       " ('lester', 'burnham'): 266,\n",
       " ('kind', 'job'): 267,\n",
       " ('even', 'better'): 268,\n",
       " ('comic', 'scene'): 269,\n",
       " ('played', 'joe'): 270,\n",
       " ('portrayal', 'patrice'): 271,\n",
       " ('rescuing', 'runaway'): 272,\n",
       " ('squirrel', 'salesperson'): 273,\n",
       " ('heavy', 'metal'): 274,\n",
       " ('thing', 'make'): 275,\n",
       " ('film', 'danny'): 276,\n",
       " ('called', 'tatooine'): 277,\n",
       " ('last', 'three'): 278,\n",
       " ('regular', 'guy'): 279,\n",
       " ('erica', 'young'): 280,\n",
       " ('commanding', 'presence'): 281,\n",
       " ('person', 'true'): 282,\n",
       " ('political', 'quagmire'): 283,\n",
       " ('since', 'wall'): 284,\n",
       " ('dramatic', 'acting'): 285,\n",
       " ('also', 'bob'): 286,\n",
       " ('project', 'tourists'): 287,\n",
       " ('resentment', 'towards'): 288,\n",
       " ('often', 'identified'): 289,\n",
       " ('beautifully', 'constructed'): 290,\n",
       " ('light', 'one'): 291,\n",
       " ('sharp', 'editing'): 292,\n",
       " ('exec', 'elizabeth'): 293,\n",
       " ('time', 'making'): 294,\n",
       " ('wonderful', 'capturing'): 295,\n",
       " ('future', 'filmmakers'): 296,\n",
       " ('spielberg', 'gives'): 297,\n",
       " ('credit', 'never'): 298,\n",
       " ('use', 'ironic'): 299,\n",
       " ('one', 'american'): 300,\n",
       " ('shop', 'london'): 301,\n",
       " ('always', 'played'): 302,\n",
       " ('next', 'day'): 303,\n",
       " ('place', 'watching'): 304,\n",
       " ('feel', 'forced'): 305,\n",
       " ('including', 'vince'): 306,\n",
       " ('different', 'way'): 307,\n",
       " ('like', 'see'): 308,\n",
       " ('time', 'contrast'): 309,\n",
       " ('thud', 'rather'): 310,\n",
       " ('central', 'showing'): 311,\n",
       " ('crime', 'boss'): 312,\n",
       " ('telling', 'story'): 313,\n",
       " ('previously', 'helmer'): 314,\n",
       " ('number', 'interesting'): 315,\n",
       " ('prison', 'bars'): 316,\n",
       " ('bentley', 'performance'): 317,\n",
       " ('fun', 'watch'): 318,\n",
       " ('never', 'call'): 319,\n",
       " ('make', 'movie'): 320,\n",
       " ('improves', 'general'): 321,\n",
       " ('nominations', 'including'): 322,\n",
       " ('production', 'designer'): 323,\n",
       " ('fun', 'part'): 324,\n",
       " ('life', 'thugs'): 325,\n",
       " ('dream', 'sequence'): 326,\n",
       " ('soundtrack', 'manipulative'): 327,\n",
       " ('jackie', 'could'): 328,\n",
       " ('fox', 'insisted'): 329,\n",
       " ('favor', 'lambeau'): 330,\n",
       " ('right', 'times'): 331,\n",
       " ('grossing', 'film'): 332,\n",
       " ('clearly', 'sets'): 333,\n",
       " ('lot', 'interesting'): 334,\n",
       " ('underway', 'promote'): 335,\n",
       " ('cinematic', 'portrait'): 336,\n",
       " ('documentary', 'director'): 337,\n",
       " ('great', 'deal'): 338,\n",
       " ('desert', 'world'): 339,\n",
       " ('single', 'movie'): 340,\n",
       " ('long', 'one'): 341,\n",
       " ('fate', 'prisoner'): 342,\n",
       " ('crates', 'bananas'): 343,\n",
       " ('travel', 'silver'): 344,\n",
       " ('gritty', 'drama'): 345,\n",
       " ('named', 'mary'): 346,\n",
       " ('mobutu', 'colonel'): 347,\n",
       " ('visually', 'eye'): 348,\n",
       " ('american', 'paris'): 349,\n",
       " ('film', 'original'): 350,\n",
       " ('hurricane', 'film'): 351,\n",
       " ('monkey', 'photo'): 352,\n",
       " ('know', 'capone'): 353,\n",
       " ('thirteen', 'lives'): 354,\n",
       " ('story', 'propelled'): 355,\n",
       " ('well', 'amidala'): 356,\n",
       " ('form', 'somewhere'): 357,\n",
       " ('never', 'answered'): 358,\n",
       " ('run', 'member'): 359,\n",
       " ('depravity', 'violence'): 360,\n",
       " ('jackson', 'steals'): 361,\n",
       " ('batman', 'blade'): 362,\n",
       " ('wisely', 'keeps'): 363,\n",
       " ('lawrence', 'kazdan'): 364,\n",
       " ('whole', 'lot'): 365,\n",
       " ('fox', 'news'): 366,\n",
       " ('inane', 'police'): 367,\n",
       " ('played', 'jake'): 368,\n",
       " ('places', 'half'): 369,\n",
       " ('sporting', 'big'): 370,\n",
       " ('cleavage', 'dozing'): 371,\n",
       " ('like', 'train'): 372,\n",
       " ('entering', 'new'): 373,\n",
       " ('eight', 'miles'): 374,\n",
       " ('dirty', 'city'): 375,\n",
       " ('recognize', 'every'): 376,\n",
       " ('mena', 'suvari'): 377,\n",
       " ('enough', 'money'): 378,\n",
       " ('therapists', 'lambeau'): 379,\n",
       " ('student', 'elections'): 380,\n",
       " ('roundabout', 'way'): 381,\n",
       " ('adult', 'fei'): 382,\n",
       " ('music', 'building'): 383,\n",
       " ('jay', 'silent'): 384,\n",
       " ('unzipped', 'cinematic'): 385,\n",
       " ('gone', 'bad'): 386,\n",
       " ('rarely', 'loses'): 387,\n",
       " ('hollywood', 'major'): 388,\n",
       " ('insurrection', 'however'): 389,\n",
       " ('retro', 'yet'): 390,\n",
       " ('capable', 'writer'): 391,\n",
       " ('many', 'movies'): 392,\n",
       " ('deceptively', 'simple'): 393,\n",
       " ('stand', 'alone'): 394,\n",
       " ('could', 'see'): 395,\n",
       " ('appearance', 'thankfully'): 396,\n",
       " ('two', 'pay'): 397,\n",
       " ('determined', 'make'): 398,\n",
       " ('days', 'seem'): 399,\n",
       " ('life', 'henry'): 400,\n",
       " ('proyas', 'seems'): 401,\n",
       " ('unlikely', 'way'): 402,\n",
       " ('republic', 'planets'): 403,\n",
       " ('sunglasses', 'graham'): 404,\n",
       " ('exciting', 'also'): 405,\n",
       " ('mixed', 'bag'): 406,\n",
       " ('despite', 'playing'): 407,\n",
       " ('rolling', 'stones'): 408,\n",
       " ('nicholas', 'pileggi'): 409,\n",
       " ('film', 'experiment'): 410,\n",
       " ('works', 'like'): 411,\n",
       " ('simpler', 'happier'): 412,\n",
       " ('ready', 'abandon'): 413,\n",
       " ('hostage', 'matter'): 414,\n",
       " ('shots', 'makes'): 415,\n",
       " ('long', 'dark'): 416,\n",
       " ('fifties', 'sitcom'): 417,\n",
       " ('comedy', 'zooms'): 418,\n",
       " ('fast', 'emptying'): 419,\n",
       " ('stretch', 'sleep'): 420,\n",
       " ('still', 'check'): 421,\n",
       " ('introverted', 'like'): 422,\n",
       " ('action', 'flick'): 423,\n",
       " ('like', 'directors'): 424,\n",
       " ('finally', 'nick'): 425,\n",
       " ('print', 'saw'): 426,\n",
       " ('oscar', 'time'): 427,\n",
       " ('acting', 'discoveries'): 428,\n",
       " ('vader', 'master'): 429,\n",
       " ('yet', 'interesting'): 430,\n",
       " ('spend', 'ten'): 431,\n",
       " ('ending', 'buy'): 432,\n",
       " ('none', 'could'): 433,\n",
       " ('fine', 'performances'): 434,\n",
       " ('lerner', 'lara'): 435,\n",
       " ('surreal', 'atmosphere'): 436,\n",
       " ('quite', 'remember'): 437,\n",
       " ('top', 'form'): 438,\n",
       " ('mexico', 'masquerading'): 439,\n",
       " ('rebellious', 'mary'): 440,\n",
       " ('decisions', 'order'): 441,\n",
       " ('sound', 'system'): 442,\n",
       " ('one', 'first'): 443,\n",
       " ('beauty', 'alan'): 444,\n",
       " ('get', 'bit'): 445,\n",
       " ('lolita', 'kevin'): 446,\n",
       " ('minded', 'mayor'): 447,\n",
       " ('nature', 'touch'): 448,\n",
       " ('sits', 'behind'): 449,\n",
       " ('much', 'resist'): 450,\n",
       " ('cut', 'good'): 451,\n",
       " ('commercial', 'success'): 452,\n",
       " ('roth', 'play'): 453,\n",
       " ('standing', 'line'): 454,\n",
       " ('janney', 'peter'): 455,\n",
       " ('pregnant', 'tristen'): 456,\n",
       " ('somewhat', 'still'): 457,\n",
       " ('take', 'roman'): 458,\n",
       " ('norton', 'play'): 459,\n",
       " ('thugs', 'kidnap'): 460,\n",
       " ('picard', 'defies'): 461,\n",
       " ('echoed', 'gridlock'): 462,\n",
       " ('seem', 'blandly'): 463,\n",
       " ('named', 'steven'): 464,\n",
       " ('towering', 'transvestite'): 465,\n",
       " ('terms', 'narration'): 466,\n",
       " ('bit', 'involving'): 467,\n",
       " ('constructed', 'film'): 468,\n",
       " ('tarantino', 'smith'): 469,\n",
       " ('completely', 'absurd'): 470,\n",
       " ('soldier', 'truck'): 471,\n",
       " ('classy', 'piece'): 472,\n",
       " ('otherwise', 'memorable'): 473,\n",
       " ('westerns', 'dance'): 474,\n",
       " ('absolute', 'truth'): 475,\n",
       " ('mean', 'one'): 476,\n",
       " ('call', 'trash'): 477,\n",
       " ('charnel', 'house'): 478,\n",
       " ('hoax', 'everyone'): 479,\n",
       " ('would', 'became'): 480,\n",
       " ('thing', 'common'): 481,\n",
       " ('man', 'next'): 482,\n",
       " ('met', 'inspector'): 483,\n",
       " ('half', 'dozen'): 484,\n",
       " ('scenario', 'possible'): 485,\n",
       " ('race', 'claims'): 486,\n",
       " ('overnight', 'success'): 487,\n",
       " ('well', 'anything'): 488,\n",
       " ('another', 'sneak'): 489,\n",
       " ('ivan', 'reitman'): 490,\n",
       " ('urban', 'realism'): 491,\n",
       " ('also', 'inherently'): 492,\n",
       " ('bring', 'people'): 493,\n",
       " ('fair', 'know'): 494,\n",
       " ('always', 'magnetic'): 495,\n",
       " ('bloody', 'clashes'): 496,\n",
       " ('made', 'surrender'): 497,\n",
       " ('film', 'however'): 498,\n",
       " ('skillfully', 'brings'): 499,\n",
       " ('inside', 'computer'): 500,\n",
       " ('like', 'exqueeze'): 501,\n",
       " ('rehab', 'time'): 502,\n",
       " ('hometown', 'kingston'): 503,\n",
       " ('first', 'head'): 504,\n",
       " ('sinise', 'forrest'): 505,\n",
       " ('community', 'college'): 506,\n",
       " ('american', 'beauty'): 507,\n",
       " ('nicolas', 'cage'): 508,\n",
       " ('two', 'years'): 509,\n",
       " ('abuse', 'permanent'): 510,\n",
       " ('primary', 'reason'): 511,\n",
       " ('rolling', 'clients'): 512,\n",
       " ('city', 'utah'): 513,\n",
       " ('fiery', 'entrance'): 514,\n",
       " ('dora', 'fernanda'): 515,\n",
       " ('town', 'order'): 516,\n",
       " ('fashion', 'despite'): 517,\n",
       " ('landed', 'ship'): 518,\n",
       " ('play', 'someone'): 519,\n",
       " ('hard', 'imagine'): 520,\n",
       " ('bride', 'working'): 521,\n",
       " ('aging', 'cop'): 522,\n",
       " ('characters', 'strange'): 523,\n",
       " ('greater', 'part'): 524,\n",
       " ('holiday', 'movie'): 525,\n",
       " ('jamaican', 'film'): 526,\n",
       " ('acting', 'great'): 527,\n",
       " ('original', 'shortly'): 528,\n",
       " ('eddie', 'campbell'): 529,\n",
       " ('role', 'drug'): 530,\n",
       " ('atmosphere', 'awe'): 531,\n",
       " ('boast', 'superstar'): 532,\n",
       " ('clerical', 'job'): 533,\n",
       " ('still', 'boorem'): 534,\n",
       " ('television', 'writer'): 535,\n",
       " ('syndicate', 'assassinate'): 536,\n",
       " ('would', 'write'): 537,\n",
       " ('adventures', 'snakes'): 538,\n",
       " ('apprentice', 'one'): 539,\n",
       " ('teenage', 'mutant'): 540,\n",
       " ('family', 'heads'): 541,\n",
       " ('toontown', 'trying'): 542,\n",
       " ('movie', 'fails'): 543,\n",
       " ('story', 'progresses'): 544,\n",
       " ('like', 'losin'): 545,\n",
       " ('block', 'bureaucracy'): 546,\n",
       " ('month', 'box'): 547,\n",
       " ('times', 'pollini'): 548,\n",
       " ('movie', 'opens'): 549,\n",
       " ('meanest', 'derek'): 550,\n",
       " ('maintain', 'peace'): 551,\n",
       " ('michael', 'lerner'): 552,\n",
       " ('morals', 'etc'): 553,\n",
       " ('hill', 'seduce'): 554,\n",
       " ('wish', 'wonder'): 555,\n",
       " ('good', 'guys'): 556,\n",
       " ('pays', 'welcome'): 557,\n",
       " ('grubby', 'fingers'): 558,\n",
       " ('outbursts', 'homicidal'): 559,\n",
       " ('half', 'notch'): 560,\n",
       " ('work', 'film'): 561,\n",
       " ('humor', 'remarkably'): 562,\n",
       " ('detective', 'vergil'): 563,\n",
       " ('film', 'american'): 564,\n",
       " ('fourth', 'july'): 565,\n",
       " ('enjoys', 'concocting'): 566,\n",
       " ('morning', 'responds'): 567,\n",
       " ('picture', 'designer'): 568,\n",
       " ('smith', 'bethany'): 569,\n",
       " ('horribly', 'disfigured'): 570,\n",
       " ('people', 'called'): 571,\n",
       " ('couple', 'years'): 572,\n",
       " ('first', 'summer'): 573,\n",
       " ('father', 'wong'): 574,\n",
       " ('fluke', 'savant'): 575,\n",
       " ('souls', 'include'): 576,\n",
       " ('carter', 'burwell'): 577,\n",
       " ('land', 'san'): 578,\n",
       " ('film', 'still'): 579,\n",
       " ('walk', 'eight'): 580,\n",
       " ('genius', 'woody'): 581,\n",
       " ('audience', 'works'): 582,\n",
       " ('wonderful', 'job'): 583,\n",
       " ('baby', 'yeah'): 584,\n",
       " ('last', 'four'): 585,\n",
       " ('bigots', 'matter'): 586,\n",
       " ('fox', 'searchlight'): 587,\n",
       " ('tried', 'block'): 588,\n",
       " ('true', 'fact'): 589,\n",
       " ('words', 'escape'): 590,\n",
       " ('slackers', 'brian'): 591,\n",
       " ('contained', 'percent'): 592,\n",
       " ('cinema', 'verite'): 593,\n",
       " ('middle', 'class'): 594,\n",
       " ('scorsese', 'jesus'): 595,\n",
       " ('gift', 'singled'): 596,\n",
       " ('entitled', 'countryman'): 597,\n",
       " ('tardis', 'outsmarting'): 598,\n",
       " ('good', 'job'): 599,\n",
       " ('stars', 'amidst'): 600,\n",
       " ('work', 'still'): 601,\n",
       " ('gordon', 'gecko'): 602,\n",
       " ('head', 'maroon'): 603,\n",
       " ('outdoor', 'rally'): 604,\n",
       " ('kind', 'alien'): 605,\n",
       " ('movie', 'based'): 606,\n",
       " ('nina', 'feel'): 607,\n",
       " ('original', 'inventive'): 608,\n",
       " ('floating', 'films'): 609,\n",
       " ('metatron', 'alan'): 610,\n",
       " ('oscar', 'worthy'): 611,\n",
       " ('surgeon', 'grace'): 612,\n",
       " ('creative', 'filmmaker'): 613,\n",
       " ('never', 'sends'): 614,\n",
       " ('back', 'gallifrey'): 615,\n",
       " ('stiller', 'contributes'): 616,\n",
       " ('two', 'families'): 617,\n",
       " ('crouching', 'tiger'): 618,\n",
       " ('gleiberman', 'weekly'): 619,\n",
       " ('born', 'slaves'): 620,\n",
       " ('time', 'even'): 621,\n",
       " ('cosmic', 'cliche'): 622,\n",
       " ('career', 'also'): 623,\n",
       " ('different', 'fact'): 624,\n",
       " ('angles', 'many'): 625,\n",
       " ('entire', 'cast'): 626,\n",
       " ('matrix', 'man'): 627,\n",
       " ('said', 'rant'): 628,\n",
       " ('written', 'hall'): 629,\n",
       " ('city', 'actually'): 630,\n",
       " ('apartment', 'medieval'): 631,\n",
       " ('broken', 'arrow'): 632,\n",
       " ('airplane', 'somebody'): 633,\n",
       " ('jackson', 'tipped'): 634,\n",
       " ('see', 'stage'): 635,\n",
       " ('ironic', 'contrast'): 636,\n",
       " ('blown', 'star'): 637,\n",
       " ('mant', 'serves'): 638,\n",
       " ('richard', 'dreyfuss'): 639,\n",
       " ('deserved', 'big'): 640,\n",
       " ('spend', 'couple'): 641,\n",
       " ('sorely', 'overlooked'): 642,\n",
       " ('evoke', 'strong'): 643,\n",
       " ('discoveries', 'mie'): 644,\n",
       " ('archeologist', 'indiana'): 645,\n",
       " ('power', 'goes'): 646,\n",
       " ('movie', 'operation'): 647,\n",
       " ('action', 'sequences'): 648,\n",
       " ('pyramids', 'less'): 649,\n",
       " ('rich', 'although'): 650,\n",
       " ('great', 'range'): 651,\n",
       " ('limitations', 'faced'): 652,\n",
       " ('masseuse', 'larious'): 653,\n",
       " ('wonie', 'jamaican'): 654,\n",
       " ('end', 'credits'): 655,\n",
       " ('film', 'soon'): 656,\n",
       " ('dialogue', 'narrator'): 657,\n",
       " ('lanai', 'chapman'): 658,\n",
       " ('internal', 'affairs'): 659,\n",
       " ('trek', 'generations'): 660,\n",
       " ('unprotected', 'legs'): 661,\n",
       " ('lot', 'shouting'): 662,\n",
       " ('largely', 'attributed'): 663,\n",
       " ('seemed', 'completed'): 664,\n",
       " ('third', 'world'): 665,\n",
       " ('keep', 'track'): 666,\n",
       " ('book', 'chain'): 667,\n",
       " ('well', 'souls'): 668,\n",
       " ('ricardo', 'etc'): 669,\n",
       " ('come', 'surprise'): 670,\n",
       " ('combination', 'actual'): 671,\n",
       " ('joyous', 'movie'): 672,\n",
       " ('incidentally', 'metal'): 673,\n",
       " ('essence', 'statement'): 674,\n",
       " ('bobby', 'garfield'): 675,\n",
       " ('world', 'however'): 676,\n",
       " ('best', 'sound'): 677,\n",
       " ('however', 'mcgregor'): 678,\n",
       " ('brutally', 'murdered'): 679,\n",
       " ('felt', 'sentimental'): 680,\n",
       " ('defense', 'minister'): 681,\n",
       " ('example', 'homer'): 682,\n",
       " ('barton', 'fink'): 683,\n",
       " ('oddly', 'effective'): 684,\n",
       " ('boy', 'whose'): 685,\n",
       " ('able', 'take'): 686,\n",
       " ('act', 'unlike'): 687,\n",
       " ('racer', 'racer'): 688,\n",
       " ('clinic', 'counselor'): 689,\n",
       " ('captain', 'actually'): 690,\n",
       " ('much', 'younger'): 691,\n",
       " ('ghetto', 'bulworth'): 692,\n",
       " ('literary', 'academia'): 693,\n",
       " ('mie', 'renier'): 694,\n",
       " ('effective', 'pop'): 695,\n",
       " ('funny', 'picture'): 696,\n",
       " ('fingered', 'jay'): 697,\n",
       " ('offensive', 'suppose'): 698,\n",
       " ('pretty', 'good'): 699,\n",
       " ('film', 'one'): 700,\n",
       " ('lia', 'one'): 701,\n",
       " ('carrey', 'thought'): 702,\n",
       " ('family', 'gatherings'): 703,\n",
       " ('judge', 'doom'): 704,\n",
       " ('scratch', 'far'): 705,\n",
       " ('honest', 'citizens'): 706,\n",
       " ('officer', 'must'): 707,\n",
       " ('august', 'making'): 708,\n",
       " ('face', 'see'): 709,\n",
       " ('beautiful', 'talented'): 710,\n",
       " ('daughter', 'girlfriend'): 711,\n",
       " ('lambeau', 'list'): 712,\n",
       " ('presents', 'derek'): 713,\n",
       " ('movie', 'allows'): 714,\n",
       " ('actual', 'footage'): 715,\n",
       " ('time', 'gun'): 716,\n",
       " ('interesting', 'story'): 717,\n",
       " ('safeties', 'centers'): 718,\n",
       " ('someone', 'believe'): 719,\n",
       " ('parties', 'bring'): 720,\n",
       " ('somebody', 'else'): 721,\n",
       " ('attempts', 'get'): 722,\n",
       " ('member', 'criminal'): 723,\n",
       " ('paulie', 'cicero'): 724,\n",
       " ('slogan', 'catholicism'): 725,\n",
       " ('role', 'life'): 726,\n",
       " ('camp', 'factor'): 727,\n",
       " ('awfulness', 'bulworth'): 728,\n",
       " ('actors', 'working'): 729,\n",
       " ('motion', 'kicking'): 730,\n",
       " ('call', 'high'): 731,\n",
       " ('real', 'countries'): 732,\n",
       " ('jokes', 'exist'): 733,\n",
       " ('films', 'norman'): 734,\n",
       " ('spielberg', 'manages'): 735,\n",
       " ('metal', 'god'): 736,\n",
       " ('becomes', 'eye'): 737,\n",
       " ('recent', 'period'): 738,\n",
       " ('stalwart', 'saint'): 739,\n",
       " ('next', 'einstein'): 740,\n",
       " ('warning', 'major'): 741,\n",
       " ('kept', 'pushing'): 742,\n",
       " ('risk', 'course'): 743,\n",
       " ('good', 'action'): 744,\n",
       " ('force', 'strong'): 745,\n",
       " ('bible', 'thumper'): 746,\n",
       " ('mind', 'heads'): 747,\n",
       " ('week', 'noticed'): 748,\n",
       " ('quality', 'action'): 749,\n",
       " ('unpaved', 'roads'): 750,\n",
       " ('horrible', 'nightmares'): 751,\n",
       " ('girl', 'caught'): 752,\n",
       " ('cinque', 'language'): 753,\n",
       " ('adrenaline', 'rush'): 754,\n",
       " ('difficult', 'time'): 755,\n",
       " ('parents', 'hippies'): 756,\n",
       " ('government', 'might'): 757,\n",
       " ('hindrance', 'enough'): 758,\n",
       " ('good', 'direction'): 759,\n",
       " ('deadpan', 'man'): 760,\n",
       " ('film', 'able'): 761,\n",
       " ('repeated', 'course'): 762,\n",
       " ('mostly', 'laughable'): 763,\n",
       " ('make', 'shift'): 764,\n",
       " ('dreariness', 'victorian'): 765,\n",
       " ('african', 'settings'): 766,\n",
       " ('heart', 'attack'): 767,\n",
       " ('profane', 'angels'): 768,\n",
       " ('spielberg', 'one'): 769,\n",
       " ('iridescent', 'performances'): 770,\n",
       " ('making', 'duds'): 771,\n",
       " ('never', 'aware'): 772,\n",
       " ('joan', 'allen'): 773,\n",
       " ('shaken', 'several'): 774,\n",
       " ('menace', 'although'): 775,\n",
       " ('incredible', 'sense'): 776,\n",
       " ('film', 'becomes'): 777,\n",
       " ('pestering', 'small'): 778,\n",
       " ('sullen', 'apathy'): 779,\n",
       " ('unlike', 'chewbacca'): 780,\n",
       " ('movie', 'smart'): 781,\n",
       " ('film', 'utilize'): 782,\n",
       " ('district', 'attorney'): 783,\n",
       " ('get', 'glimpse'): 784,\n",
       " ('alone', 'viewing'): 785,\n",
       " ('obnoxious', 'man'): 786,\n",
       " ('start', 'wonder'): 787,\n",
       " ('delight', 'dandy'): 788,\n",
       " ('remaining', 'whites'): 789,\n",
       " ('fans', 'would'): 790,\n",
       " ('toed', 'floating'): 791,\n",
       " ('time', 'minimum'): 792,\n",
       " ('geniuses', 'behind'): 793,\n",
       " ('would', 'make'): 794,\n",
       " ('depp', 'turning'): 795,\n",
       " ('diaz', 'character'): 796,\n",
       " ('frame', 'frame'): 797,\n",
       " ('framed', 'although'): 798,\n",
       " ('wars', 'also'): 799,\n",
       " ('groom', 'molly'): 800,\n",
       " ('characters', 'williams'): 801,\n",
       " ('family', 'something'): 802,\n",
       " ('several', 'bee'): 803,\n",
       " ('several', 'noteworthy'): 804,\n",
       " ('everyone', 'blame'): 805,\n",
       " ('convincing', 'charismatic'): 806,\n",
       " ('say', 'city'): 807,\n",
       " ('makes', 'feel'): 808,\n",
       " ('want', 'drown'): 809,\n",
       " ('slow', 'jock'): 810,\n",
       " ('line', 'regarding'): 811,\n",
       " ('paramount', 'pictures'): 812,\n",
       " ('antics', 'john'): 813,\n",
       " ('movies', 'would'): 814,\n",
       " ('time', 'bringing'): 815,\n",
       " ('best', 'film'): 816,\n",
       " ('tough', 'spunky'): 817,\n",
       " ('chains', 'tibbs'): 818,\n",
       " ('likely', 'mentally'): 819,\n",
       " ('danny', 'roman'): 820,\n",
       " ('strictly', 'sitcom'): 821,\n",
       " ('film', 'couple'): 822,\n",
       " ('viable', 'threats'): 823,\n",
       " ('cliche', 'police'): 824,\n",
       " ('sorts', 'plays'): 825,\n",
       " ('planet', 'skaro'): 826,\n",
       " ('forgive', 'anyone'): 827,\n",
       " ('used', 'well'): 828,\n",
       " ('barry', 'sanders'): 829,\n",
       " ('convention', 'pollini'): 830,\n",
       " ('power', 'masse'): 831,\n",
       " ('warning', 'spoilers'): 832,\n",
       " ('worthwhile', 'movie'): 833,\n",
       " ('niebaum', 'may'): 834,\n",
       " ('gibson', 'plays'): 835,\n",
       " ('viewer', 'moralistic'): 836,\n",
       " ('man', 'accomplishes'): 837,\n",
       " ('cover', 'similar'): 838,\n",
       " ('way', 'book'): 839,\n",
       " ('whole', 'way'): 840,\n",
       " ('eventually', 'toontown'): 841,\n",
       " ('lying', 'bastard'): 842,\n",
       " ('extensive', 'use'): 843,\n",
       " ('slept', 'days'): 844,\n",
       " ('character', 'best'): 845,\n",
       " ('judge', 'jury'): 846,\n",
       " ('dominic', 'west'): 847,\n",
       " ('job', 'actually'): 848,\n",
       " ('boys', 'party'): 849,\n",
       " ('outdoor', 'concert'): 850,\n",
       " ('director', 'michael'): 851,\n",
       " ('gun', 'smuggler'): 852,\n",
       " ('movie', 'database'): 853,\n",
       " ('satirical', 'cardinal'): 854,\n",
       " ('became', 'age'): 855,\n",
       " ('furlong', 'mother'): 856,\n",
       " ('general', 'since'): 857,\n",
       " ('last', 'nemesis'): 858,\n",
       " ('performance', 'unlike'): 859,\n",
       " ('directed', 'empire'): 860,\n",
       " ('sci', 'violence'): 861,\n",
       " ('still', 'seen'): 862,\n",
       " ('old', 'chestnut'): 863,\n",
       " ('continues', 'throughout'): 864,\n",
       " ('shot', 'odd'): 865,\n",
       " ('like', 'manipulation'): 866,\n",
       " ('greater', 'respect'): 867,\n",
       " ('characters', 'jar'): 868,\n",
       " ('horror', 'like'): 869,\n",
       " ('flash', 'eric'): 870,\n",
       " ('final', 'impression'): 871,\n",
       " ('industry', 'snap'): 872,\n",
       " ('resolution', 'featuring'): 873,\n",
       " ('hole', 'somebody'): 874,\n",
       " ('burbank', 'jim'): 875,\n",
       " ('friend', 'also'): 876,\n",
       " ('drug', 'scene'): 877,\n",
       " ('car', 'find'): 878,\n",
       " ('designer', 'mizrahi'): 879,\n",
       " ('many', 'significant'): 880,\n",
       " ('face', 'resembles'): 881,\n",
       " ('fare', 'nearly'): 882,\n",
       " ('good', 'cop'): 883,\n",
       " ('waited', 'twenty'): 884,\n",
       " ('zoolander', 'character'): 885,\n",
       " ('small', 'force'): 886,\n",
       " ('white', 'town'): 887,\n",
       " ('never', 'actually'): 888,\n",
       " ('far', 'away'): 889,\n",
       " ('soldier', 'story'): 890,\n",
       " ('ponder', 'exactly'): 891,\n",
       " ('pure', 'appetite'): 892,\n",
       " ('used', 'super'): 893,\n",
       " ('kung', 'tune'): 894,\n",
       " ('affords', 'affectionate'): 895,\n",
       " ('latter', 'klingon'): 896,\n",
       " ('money', 'crown'): 897,\n",
       " ('soft', 'spoken'): 898,\n",
       " ('known', 'pioneer'): 899,\n",
       " ('going', 'like'): 900,\n",
       " ('introduced', 'young'): 901,\n",
       " ('selling', 'twig'): 902,\n",
       " ('welcome', 'change'): 903,\n",
       " ('feelings', 'definitely'): 904,\n",
       " ('wars', 'took'): 905,\n",
       " ('screen', 'presence'): 906,\n",
       " ('sympathy', 'ratty'): 907,\n",
       " ('discount', 'book'): 908,\n",
       " ('generated', 'one'): 909,\n",
       " ('also', 'plays'): 910,\n",
       " ('tracy', 'flick'): 911,\n",
       " ('run', 'children'): 912,\n",
       " ('may', 'home'): 913,\n",
       " ('since', 'seen'): 914,\n",
       " ('ironic', 'prologue'): 915,\n",
       " ('wonders', 'ride'): 916,\n",
       " ('kathy', 'moriarty'): 917,\n",
       " ('referee', 'cost'): 918,\n",
       " ('organizing', 'block'): 919,\n",
       " ('bulworth', 'ended'): 920,\n",
       " ('slapstick', 'intended'): 921,\n",
       " ('thereby', 'rendering'): 922,\n",
       " ('bounding', 'around'): 923,\n",
       " ('goes', 'slack'): 924,\n",
       " ('speech', 'adams'): 925,\n",
       " ('jewison', 'classic'): 926,\n",
       " ('huge', 'special'): 927,\n",
       " ('trek', 'fans'): 928,\n",
       " ('underlings', 'seem'): 929,\n",
       " ('natural', 'genius'): 930,\n",
       " ('named', 'quint'): 931,\n",
       " ('action', 'film'): 932,\n",
       " ('achingly', 'honest'): 933,\n",
       " ('probation', 'instead'): 934,\n",
       " ('plots', 'serve'): 935,\n",
       " ('recruits', 'helicopter'): 936,\n",
       " ('blatant', 'exposition'): 937,\n",
       " ('secret', 'event'): 938,\n",
       " ('shark', 'killer'): 939,\n",
       " ('initial', 'success'): 940,\n",
       " ('always', 'understated'): 941,\n",
       " ('mining', 'town'): 942,\n",
       " ('officer', 'sam'): 943,\n",
       " ('ping', 'eventually'): 944,\n",
       " ('give', 'criticism'): 945,\n",
       " ('convenience', 'store'): 946,\n",
       " ('catch', 'jarmusch'): 947,\n",
       " ('gets', 'transfer'): 948,\n",
       " ('geeks', 'revenge'): 949,\n",
       " ('homicidal', 'violence'): 950,\n",
       " ('two', 'aides'): 951,\n",
       " ('alda', 'film'): 952,\n",
       " ('better', 'cold'): 953,\n",
       " ('blind', 'dog'): 954,\n",
       " ('ship', 'world'): 955,\n",
       " ('also', 'gives'): 956,\n",
       " ('filmmaker', 'world'): 957,\n",
       " ('resolution', 'get'): 958,\n",
       " ('song', 'lyric'): 959,\n",
       " ('stonecutters', 'song'): 960,\n",
       " ('talented', 'musicians'): 961,\n",
       " ('probably', 'never'): 962,\n",
       " ('eddie', 'valiant'): 963,\n",
       " ('comparing', 'scars'): 964,\n",
       " ('money', 'witherspoon'): 965,\n",
       " ('almost', 'pastoral'): 966,\n",
       " ('seems', 'mistaken'): 967,\n",
       " ('excellent', 'acting'): 968,\n",
       " ('spiner', 'discovering'): 969,\n",
       " ('spectacular', 'robberies'): 970,\n",
       " ('trying', 'jump'): 971,\n",
       " ('mentor', 'ness'): 972,\n",
       " ('great', 'films'): 973,\n",
       " ('best', 'audience'): 974,\n",
       " ('rent', 'recently'): 975,\n",
       " ('writers', 'though'): 976,\n",
       " ('caring', 'totally'): 977,\n",
       " ('keeps', 'ringwald'): 978,\n",
       " ('movie', 'sinise'): 979,\n",
       " ('phil', 'segal'): 980,\n",
       " ('laughable', 'details'): 981,\n",
       " ('party', 'fits'): 982,\n",
       " ('long', 'time'): 983,\n",
       " ('sculptures', 'stones'): 984,\n",
       " ('example', 'acting'): 985,\n",
       " ('guys', 'first'): 986,\n",
       " ('nation', 'first'): 987,\n",
       " ('amount', 'sexuality'): 988,\n",
       " ('fellow', 'police'): 989,\n",
       " ('temptation', 'fix'): 990,\n",
       " ('individuals', 'enthralled'): 991,\n",
       " ('soft', 'drinks'): 992,\n",
       " ('times', 'find'): 993,\n",
       " ('unzipped', 'variety'): 994,\n",
       " ('hard', 'fans'): 995,\n",
       " ('novelty', 'wears'): 996,\n",
       " ('audience', 'pre'): 997,\n",
       " ('time', 'janeane'): 998,\n",
       " ('pretty', 'entertaining'): 999,\n",
       " ...}"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def count_matrix(col,k):\n",
    "    text=col\n",
    "    for i in text:\n",
    "        mat[k][d[i]]=mat[k][d[i]]+1\n",
    "k=0\n",
    "for i in df['text']:\n",
    "    #print(i)\n",
    "    count_matrix(i,k)\n",
    "    k=k+1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 0.,  0.,  0., ...,  0.,  0.,  0.],\n",
       "       [ 0.,  0.,  0., ...,  0.,  0.,  0.],\n",
       "       [ 0.,  0.,  0., ...,  0.,  0.,  0.],\n",
       "       ..., \n",
       "       [ 0.,  0.,  0., ...,  0.,  0.,  0.],\n",
       "       [ 0.,  0.,  0., ...,  0.,  0.,  0.],\n",
       "       [ 0.,  0.,  0., ...,  0.,  0.,  0.]])"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mat"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(100, 10636)"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mat.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#creating tf-idf\n",
    "total_no_of_documents=df.shape[0]\n",
    "total_no_of_words=len(set1)\n",
    "tf=np.zeros([total_no_of_documents,total_no_of_words])\n",
    "\n",
    "k=0\n",
    "for i in mat:\n",
    "    cnt=0\n",
    "    p=0\n",
    "    for j in i:\n",
    "        cnt=cnt+j\n",
    "    for j in i:\n",
    "        tf[(k,p)]=j/cnt\n",
    "        p=p+1\n",
    "    k=k+1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import math\n",
    "no_of_documents_per_word=np.zeros(total_no_of_words)\n",
    "for i in mat:\n",
    "    p=0\n",
    "    for j in i:\n",
    "        if j > 0:\n",
    "            no_of_documents_per_word[p]=no_of_documents_per_word[p]+1;\n",
    "        p=p+1;\n",
    "\n",
    "idf=np.zeros(total_no_of_words)\n",
    "k=0\n",
    "for i in no_of_documents_per_word:\n",
    "    idf[k]=math.log10(total_no_of_documents/i)\n",
    "    k=k+1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "tf_idf=np.zeros([total_no_of_documents,total_no_of_words])\n",
    "k=0;\n",
    "for i in mat:\n",
    "    p=0;\n",
    "    for j in i:\n",
    "        tf_idf[(k,p)]=idf[p]*tf[k,p];\n",
    "        p=p+1;\n",
    "    k=k+1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(100, 10636)"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tf_idf[:,0]\n",
    "tf_idf.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "for i in tf_idf:\n",
    "    for j in i:\n",
    "        if j == float('inf'):\n",
    "            print (j)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "mean_mat=np.zeros([1,tf_idf.shape[1]])\n",
    "std_mat=np.zeros([1,tf_idf.shape[1]])\n",
    "for i in range(0,tf_idf.shape[1]):\n",
    "    mean_mat[0,i]=np.mean(tf_idf[:,i])\n",
    "    std_mat[0,i]=np.std(tf_idf[:,i])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "for i in range(0,std_mat.shape[0]):\n",
    "    for j in range(0,std_mat.shape[1]):\n",
    "        if(std_mat[i,j]==0):\n",
    "            x1=i\n",
    "            y1=j\n",
    "            print(x1+' '+y1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "X=np.zeros([tf_idf.shape[0],tf_idf.shape[1]])\n",
    "for i in range(0,tf_idf.shape[0]):\n",
    "    for j in range(0,tf_idf.shape[1]):\n",
    "        X[i,j]=(tf_idf[i,j]-mean_mat[0][j])/std_mat[0][j]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-0.14285714285714285"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X[0,11]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(100, 10636)"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#creating covariance matrix\n",
    "mean_vec=np.mean(X,axis=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([  4.60742555e-17,   1.72084569e-17,   5.10702591e-17, ...,\n",
       "         1.72084569e-17,  -6.43929354e-17,   1.55431223e-17])"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mean_vec"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "cov=np.zeros([X.shape[1],X.shape[1]])\n",
    "cov= (X - mean_vec).T.dot((X - mean_vec)) / (X.shape[0]-1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 1.01010101, -0.02061431, -0.02061431, ..., -0.02061431,\n",
       "        -0.02061431, -0.02061431],\n",
       "       [-0.02061431,  1.01010101, -0.02061431, ..., -0.02061431,\n",
       "        -0.02061431, -0.02061431],\n",
       "       [-0.02061431, -0.02061431,  1.01010101, ..., -0.02061431,\n",
       "        -0.02061431, -0.02061431],\n",
       "       ..., \n",
       "       [-0.02061431, -0.02061431, -0.02061431, ...,  1.01010101,\n",
       "        -0.02061431, -0.02061431],\n",
       "       [-0.02061431, -0.02061431, -0.02061431, ..., -0.02061431,\n",
       "         1.01010101, -0.02061431],\n",
       "       [-0.02061431, -0.02061431, -0.02061431, ..., -0.02061431,\n",
       "        -0.02061431,  1.01010101]])"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cov"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from sklearn.decomposition import PCA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "eig_vals, eig_vecs = np.linalg.eig(cov)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 5.43399337e+002+0.j,  4.68097243e+002+0.j,  4.12080385e+002+0.j,\n",
       "       ..., -7.19151206e-146+0.j, -2.23027036e-156+0.j,\n",
       "        7.19408647e-157+0.j])"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "eig_vals"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[-8.92689986e-04+0.j, -1.03552495e-03+0.j, -1.01014281e-03+0.j,\n",
       "        ..., -2.68425492e-21+0.j,  1.34581196e-30+0.j,\n",
       "         2.18479447e-31+0.j],\n",
       "       [-3.27239756e-03+0.j,  4.61094436e-02+0.j,  3.26821780e-03+0.j,\n",
       "        ..., -9.88816207e-19+0.j,  3.23539478e-19+0.j,\n",
       "         2.31329843e-19+0.j],\n",
       "       [-1.04706479e-03+0.j, -1.28933749e-03+0.j, -1.36282419e-03+0.j,\n",
       "        ...,  1.73244908e-18+0.j, -2.41334911e-19+0.j,\n",
       "        -1.56835259e-19+0.j],\n",
       "       ...,\n",
       "       [-7.61604969e-04+0.j, -8.13205762e-04+0.j, -8.87670818e-04+0.j,\n",
       "        ..., -4.31304094e-19+0.j,  1.65906834e-19+0.j,\n",
       "        -4.54501700e-20+0.j],\n",
       "       [-7.55152759e-04+0.j, -8.33215410e-04+0.j, -8.77906132e-04+0.j,\n",
       "        ...,  1.02638680e-19+0.j, -5.08221127e-20+0.j,\n",
       "        -5.43230045e-20+0.j],\n",
       "       [-3.27239756e-03+0.j,  4.61094436e-02+0.j,  3.26821780e-03+0.j,\n",
       "        ...,  1.31544853e-18+0.j, -8.36510187e-20+0.j,\n",
       "        -3.30303100e-20+0.j]])"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "eig_vecs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(10068, 10068)"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "eig_vecs.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Eigen values in descending order:\n",
      "543.3993369766772\n",
      "468.0972429181595\n",
      "412.0803853680131\n",
      "379.9451930593442\n",
      "361.96817977111846\n",
      "309.2938368076643\n",
      "304.8869731139201\n",
      "293.75650013362286\n",
      "285.38078514638164\n",
      "278.1348631485955\n",
      "271.6168948549007\n",
      "250.704376338844\n",
      "242.46624173385428\n",
      "239.94164547458615\n",
      "235.1859045921373\n",
      "227.37112640298008\n",
      "221.02278367527776\n",
      "212.84965119065666\n",
      "204.7162540302542\n",
      "198.5958285730511\n",
      "190.37272230854578\n",
      "188.03029927263665\n",
      "182.10389569488186\n",
      "181.2750674849002\n",
      "180.52104987030532\n",
      "179.51348189784355\n",
      "178.9591181214446\n",
      "174.62228236106134\n",
      "171.22811913721003\n",
      "168.39933791421873\n",
      "164.2904488985874\n",
      "160.33610094505227\n",
      "157.7319057711334\n",
      "155.0738305037485\n",
      "151.64504844909797\n",
      "148.9783213333555\n",
      "144.4074726435565\n",
      "141.54394125070934\n",
      "137.64051784243463\n",
      "131.41986274421174\n",
      "126.60136478114839\n",
      "123.41095891444336\n",
      "122.14421532601585\n",
      "115.91523495024066\n",
      "113.55469228152934\n",
      "94.27674105184052\n",
      "90.29660541557243\n",
      "85.14043732543524\n",
      "68.84989189579491\n",
      "2.970173860575554e-13\n",
      "1.0846976528656746e-13\n",
      "1.0846976528656746e-13\n",
      "7.758116907956318e-14\n",
      "7.758116907956318e-14\n",
      "5.546413720504431e-14\n",
      "4.036998437818928e-14\n",
      "4.036998437818928e-14\n",
      "3.9211612011013525e-14\n",
      "3.9211612011013525e-14\n",
      "3.144110971579024e-14\n",
      "3.144110971579024e-14\n",
      "3.011915815565399e-14\n",
      "3.011915815565399e-14\n",
      "2.998470681191686e-14\n",
      "2.4954674687678647e-14\n",
      "2.4954674687678647e-14\n",
      "2.1086955701656586e-14\n",
      "2.1086955701656586e-14\n",
      "2.0306191930961126e-14\n",
      "1.959085583664448e-14\n",
      "1.926055603363422e-14\n",
      "1.926055603363422e-14\n",
      "1.922710578774065e-14\n",
      "1.922710578774065e-14\n",
      "1.8140457797281432e-14\n",
      "1.793890743625196e-14\n",
      "1.793890743625196e-14\n",
      "1.689507900297439e-14\n",
      "1.682936059894339e-14\n",
      "1.682936059894339e-14\n",
      "1.6511947251108443e-14\n",
      "1.5485811877091204e-14\n",
      "1.5485811877091204e-14\n",
      "1.5046446593769342e-14\n",
      "1.5046446593769342e-14\n",
      "1.4213774616410057e-14\n",
      "1.4054986561161016e-14\n",
      "1.4054986561161016e-14\n",
      "1.3669563025258968e-14\n",
      "1.3316562151652784e-14\n",
      "1.331096110322013e-14\n",
      "1.2457338313909252e-14\n",
      "1.240550994607452e-14\n",
      "1.240550994607452e-14\n",
      "1.211350029494696e-14\n",
      "1.211350029494696e-14\n",
      "1.1286499310404038e-14\n",
      "1.115495291686832e-14\n",
      "1.115495291686832e-14\n",
      "1.064711890819188e-14\n",
      "1.064711890819188e-14\n",
      "9.938416444782705e-15\n",
      "9.931667717585039e-15\n",
      "9.931667717585039e-15\n",
      "9.80894096430396e-15\n",
      "9.80894096430396e-15\n",
      "9.502501387699161e-15\n",
      "9.502501387699161e-15\n",
      "9.303572762159186e-15\n",
      "9.303572762159186e-15\n",
      "9.024910856129975e-15\n",
      "9.024910856129975e-15\n",
      "8.873330446845417e-15\n",
      "8.873330446845417e-15\n",
      "8.824116852998529e-15\n",
      "8.499651870943236e-15\n",
      "8.499651870943236e-15\n",
      "8.396052442612355e-15\n",
      "8.396052442612355e-15\n",
      "8.371272335812699e-15\n",
      "8.11631877197659e-15\n",
      "8.11631877197659e-15\n",
      "7.958811074401968e-15\n",
      "7.958811074401968e-15\n",
      "7.77502366558203e-15\n",
      "7.77502366558203e-15\n",
      "7.390799612309417e-15\n",
      "7.324807976264679e-15\n",
      "7.324807976264679e-15\n",
      "7.224812305552244e-15\n",
      "7.182335991402561e-15\n",
      "7.182335991402561e-15\n",
      "7.180783952999677e-15\n",
      "7.180783952999677e-15\n",
      "6.855356205817395e-15\n",
      "6.855356205817395e-15\n",
      "6.8168026958494795e-15\n",
      "6.8168026958494795e-15\n",
      "6.794456452539699e-15\n",
      "6.794456452539699e-15\n",
      "6.5480553355881276e-15\n",
      "6.5303631086441565e-15\n",
      "6.5303631086441565e-15\n",
      "6.225534914857107e-15\n",
      "5.974651760683997e-15\n",
      "5.974651760683997e-15\n",
      "5.912955492417881e-15\n",
      "5.912955492417881e-15\n",
      "5.879227608293104e-15\n",
      "5.8686893207962435e-15\n",
      "5.8686893207962435e-15\n",
      "5.796666499857303e-15\n",
      "5.796666499857303e-15\n",
      "5.766282248148833e-15\n",
      "5.766282248148833e-15\n",
      "5.680451019029331e-15\n",
      "5.680451019029331e-15\n",
      "5.560595791029222e-15\n",
      "5.560595791029222e-15\n",
      "5.460272336266115e-15\n",
      "5.460272336266115e-15\n",
      "5.3335702670405106e-15\n",
      "5.226416618728318e-15\n",
      "5.226416618728318e-15\n",
      "5.135661841495439e-15\n",
      "5.135661841495439e-15\n",
      "5.080702767128467e-15\n",
      "5.080702767128467e-15\n",
      "4.996003932448833e-15\n",
      "4.926165811803983e-15\n",
      "4.926165811803983e-15\n",
      "4.666414179232642e-15\n",
      "4.666414179232642e-15\n",
      "4.486265655758335e-15\n",
      "4.486265655758335e-15\n",
      "4.428020631014536e-15\n",
      "4.428020631014536e-15\n",
      "4.386159463318216e-15\n",
      "4.386159463318216e-15\n",
      "4.30525850672602e-15\n",
      "4.305032632932979e-15\n",
      "4.305032632932979e-15\n",
      "4.184204599381672e-15\n",
      "4.184204599381672e-15\n",
      "4.1335607491148814e-15\n",
      "4.1335607491148814e-15\n",
      "4.041076247407e-15\n",
      "3.836958673195775e-15\n",
      "3.836958673195775e-15\n",
      "3.740163674330839e-15\n",
      "3.740163674330839e-15\n",
      "3.737930657316507e-15\n",
      "3.737930657316507e-15\n",
      "3.715597768506321e-15\n",
      "3.715597768506321e-15\n",
      "3.5342190556679402e-15\n",
      "3.5342190556679402e-15\n",
      "3.459335171361535e-15\n",
      "3.3825022993843087e-15\n",
      "3.3825022993843087e-15\n",
      "3.287468842245608e-15\n",
      "3.287468842245608e-15\n",
      "3.214173168824753e-15\n",
      "3.214173168824753e-15\n",
      "3.0982985324916713e-15\n",
      "3.0982985324916713e-15\n",
      "3.0030919607033698e-15\n",
      "3.0030919607033698e-15\n",
      "3.003071546609635e-15\n",
      "3.003071546609635e-15\n",
      "2.9888829535119985e-15\n",
      "2.9772130316546653e-15\n",
      "2.8747245247111762e-15\n",
      "2.8747245247111762e-15\n",
      "2.8013885383195805e-15\n",
      "2.8013885383195805e-15\n",
      "2.7989433581233854e-15\n",
      "2.7989433581233854e-15\n",
      "2.7641084600469804e-15\n",
      "2.73193468919233e-15\n",
      "2.6836305390273665e-15\n",
      "2.6836305390273665e-15\n",
      "2.6547551506692174e-15\n",
      "2.5126087787812377e-15\n",
      "2.5126087787812377e-15\n",
      "2.363692255778726e-15\n",
      "2.363692255778726e-15\n",
      "2.3354952631576842e-15\n",
      "2.279404146979383e-15\n",
      "2.279404146979383e-15\n",
      "2.240648259911727e-15\n",
      "2.240648259911727e-15\n",
      "2.2365169865940276e-15\n",
      "2.2180743527940887e-15\n",
      "2.2180743527940887e-15\n",
      "2.164353038698037e-15\n",
      "2.164353038698037e-15\n",
      "1.9358961234438717e-15\n",
      "1.9358961234438717e-15\n",
      "1.935513121442119e-15\n",
      "1.9288890227516275e-15\n",
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      "1.6143650152624237e-109\n",
      "1.6143650152624237e-109\n",
      "1.387346631599364e-109\n",
      "1.387346631599364e-109\n",
      "1.3197901267730103e-109\n",
      "1.3197901267730103e-109\n",
      "1.3025546670822158e-109\n",
      "1.3025546670822158e-109\n",
      "1.292676159559467e-109\n",
      "1.2724975377544772e-109\n",
      "1.1276296236434788e-109\n",
      "1.1276296236434788e-109\n",
      "1.0815374514112193e-109\n",
      "1.0815374514112193e-109\n",
      "9.641559321897992e-110\n",
      "5.988444990403336e-110\n",
      "5.988444990403336e-110\n",
      "5.566783223297636e-110\n",
      "5.566783223297636e-110\n",
      "4.8979111593821793e-110\n",
      "4.8979111593821793e-110\n",
      "4.489338169077013e-110\n",
      "4.489338169077013e-110\n",
      "4.3061876007603755e-110\n",
      "4.2837191593813994e-110\n",
      "4.2837191593813994e-110\n",
      "3.8193319299835705e-110\n",
      "3.8193319299835705e-110\n",
      "2.804126963000384e-110\n",
      "2.804126963000384e-110\n",
      "2.5286641855165642e-110\n",
      "2.1946090240625828e-110\n",
      "2.1946090240625828e-110\n",
      "2.0104487550495447e-110\n",
      "1.9271495459711027e-110\n",
      "1.9271495459711027e-110\n",
      "1.2112549051767929e-110\n",
      "8.798829818648876e-111\n",
      "8.798829818648876e-111\n",
      "6.5328880089961865e-111\n",
      "6.5328880089961865e-111\n",
      "6.07647545544422e-111\n",
      "6.07647545544422e-111\n",
      "4.495352134536358e-111\n",
      "4.495352134536358e-111\n",
      "3.1128564850921406e-111\n",
      "2.222011520919589e-111\n",
      "2.11401615612506e-111\n",
      "2.11401615612506e-111\n",
      "1.98340766370371e-111\n",
      "1.98340766370371e-111\n",
      "1.9086681980865234e-111\n",
      "1.9086681980865234e-111\n",
      "1.2750976355955853e-111\n",
      "1.2750976355955853e-111\n",
      "1.2490375519204174e-111\n",
      "1.1692822587299758e-111\n",
      "1.1692822587299758e-111\n",
      "1.0743618496449223e-111\n",
      "8.369842367742754e-112\n",
      "8.369842367742754e-112\n",
      "8.301232387915309e-112\n",
      "8.301232387915309e-112\n",
      "7.562296497864101e-112\n",
      "7.562296497864101e-112\n",
      "5.017851197200222e-112\n",
      "5.017851197200222e-112\n",
      "4.755360925067073e-112\n",
      "4.0859875842524173e-112\n",
      "4.0859875842524173e-112\n",
      "4.056566837860521e-112\n",
      "3.127119211338764e-112\n",
      "3.127119211338764e-112\n",
      "2.993968016860628e-112\n",
      "2.993968016860628e-112\n",
      "2.429697983480305e-112\n",
      "2.429697983480305e-112\n",
      "2.2618952965025494e-112\n",
      "2.2618952965025494e-112\n",
      "1.3937441713116383e-112\n",
      "1.3937441713116383e-112\n",
      "1.0435913033023243e-112\n",
      "1.0435913033023243e-112\n",
      "8.313068548569179e-113\n",
      "8.313068548569179e-113\n",
      "7.69570769466997e-113\n",
      "7.69570769466997e-113\n",
      "7.508983176183194e-113\n",
      "7.508983176183194e-113\n",
      "5.298772907782219e-113\n",
      "5.298772907782219e-113\n",
      "3.9600072474756573e-113\n",
      "2.8278143648678664e-113\n",
      "1.7277103210590798e-113\n",
      "1.7277103210590798e-113\n",
      "1.0502526573835472e-113\n",
      "1.0502526573835472e-113\n",
      "6.332484698856334e-114\n",
      "6.332484698856334e-114\n",
      "5.9872855684822294e-114\n",
      "5.9872855684822294e-114\n",
      "5.7919995404898166e-114\n",
      "5.7919995404898166e-114\n",
      "5.70413797808424e-114\n",
      "5.70413797808424e-114\n",
      "4.857295630437014e-114\n",
      "4.857295630437014e-114\n",
      "3.29440801483937e-114\n",
      "3.29440801483937e-114\n",
      "3.1467975012320144e-114\n",
      "2.152316317931409e-114\n",
      "2.152316317931409e-114\n",
      "2.112910119841076e-114\n",
      "1.8176905668468153e-114\n",
      "1.8176905668468153e-114\n",
      "1.2914932166275436e-114\n",
      "3.0185638690414345e-115\n",
      "3.0185638690414345e-115\n",
      "2.9436242747398544e-115\n",
      "6.97278346956814e-116\n",
      "4.85852433129816e-122\n",
      "1.3606582605361041e-123\n",
      "1.3606582605361041e-123\n",
      "2.229363545213762e-124\n",
      "1.5197637257957658e-124\n",
      "1.5197637257957658e-124\n",
      "2.261449671897413e-125\n",
      "1.742730023322468e-125\n",
      "1.742730023322468e-125\n",
      "1.0922723803941733e-125\n",
      "1.0922723803941733e-125\n",
      "7.854237591323542e-126\n",
      "7.854237591323542e-126\n",
      "3.356998313817053e-126\n",
      "1.5277734671966168e-126\n",
      "1.2616011710354867e-126\n",
      "1.116364343220866e-126\n",
      "1.116364343220866e-126\n",
      "7.324778018704814e-127\n",
      "3.7998024370445556e-127\n",
      "1.224223022813078e-127\n",
      "5.340839948820285e-128\n",
      "5.340839948820285e-128\n",
      "3.8777762769992954e-128\n",
      "3.8777762769992954e-128\n",
      "3.44750435151397e-128\n",
      "2.4591659583789695e-128\n",
      "2.4591659583789695e-128\n",
      "1.9151184041398778e-128\n",
      "1.9151184041398778e-128\n",
      "1.729012261919256e-128\n",
      "1.289848116979535e-128\n",
      "1.289848116979535e-128\n",
      "1.0536947747366686e-128\n",
      "8.596086231661887e-129\n",
      "8.596086231661887e-129\n",
      "6.178103714217451e-129\n",
      "6.178103714217451e-129\n",
      "4.883516848338604e-129\n",
      "3.667110822615027e-129\n",
      "3.667110822615027e-129\n",
      "2.3597548898744916e-129\n",
      "1.9266255913464492e-129\n",
      "1.9266255913464492e-129\n",
      "1.173675297098384e-129\n",
      "1.173675297098384e-129\n",
      "9.718578678656478e-130\n",
      "6.862308089844355e-130\n",
      "6.862308089844355e-130\n",
      "2.044917411591316e-130\n",
      "4.622117178949163e-137\n",
      "4.622117178949163e-137\n",
      "1.951847980802653e-139\n",
      "1.578443751744216e-140\n",
      "1.3536673432968902e-140\n",
      "1.3536673432968902e-140\n",
      "3.7870624959022115e-141\n",
      "6.505192845623539e-142\n",
      "2.9017001588682866e-142\n",
      "1.5803440544179836e-142\n",
      "1.5803440544179836e-142\n",
      "3.713848969197189e-143\n",
      "1.2559994223223179e-143\n",
      "1.2559994223223179e-143\n",
      "1.0033968442838039e-143\n",
      "9.13779383315892e-144\n",
      "9.13779383315892e-144\n",
      "3.893955892761588e-144\n",
      "3.085413936251224e-145\n",
      "3.085413936251224e-145\n",
      "7.191512058415747e-146\n",
      "2.230270363711709e-156\n",
      "7.194086465238827e-157\n"
     ]
    }
   ],
   "source": [
    "eig_pairs = [(np.abs(eig_vals[i]), eig_vecs[:,i]) for i in range(len(eig_vals))]\n",
    "eig_pairs.sort(key=lambda x: x[0], reverse=True)\n",
    "print(\"Eigen values in descending order:\")\n",
    "for i in eig_pairs:\n",
    "    print(i[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10068"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "shape_=eig_vecs.shape[0]\n",
    "shape_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "projection_matrix=eig_pairs[0][1].reshape(shape_,1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[-0.00089269+0.j],\n",
       "       [-0.0032724 +0.j],\n",
       "       [-0.00104706+0.j],\n",
       "       ...,\n",
       "       [-0.0007616 +0.j],\n",
       "       [-0.00075515+0.j],\n",
       "       [-0.0032724 +0.j]])"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "projection_matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "i=1\n",
    "num=100\n",
    "while i<num:\n",
    "    projection_matrix = np.hstack((projection_matrix,eig_pairs[i][1].reshape(shape_,1)))\n",
    "    i=i+1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(10068, 100)"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "projection_matrix.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "Y = X.dot(projection_matrix)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(100, 100)"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Y.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "sq = np.square(Y)\n",
    "sq = np.sum(sq,axis=1).tolist()\n",
    "square_root = np.sqrt(sq)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([107.65544266-5.07912626e-33j, 117.82643611-1.71986553e-31j,\n",
       "        85.49123534+3.84372238e-32j,  90.97944036+1.07799580e-31j,\n",
       "        94.00075195-4.61487187e-33j,  78.20293154-2.66351383e-32j,\n",
       "        91.87944855+2.58523205e-31j,  67.2326864 -9.36028147e-32j,\n",
       "        93.77687233-1.70426251e-31j, 122.14620244+1.63847851e-31j,\n",
       "       121.90284466+6.43113670e-33j,  84.79502685-5.90478610e-32j,\n",
       "        86.53636487-1.09818986e-32j, 108.45642577-3.19531770e-31j,\n",
       "        66.92995782+6.30089255e-34j, 162.26142686-1.50779272e-31j,\n",
       "       150.61601821-1.12124578e-31j, 135.72330341+2.64787637e-32j,\n",
       "        82.67648733+2.38337187e-32j,  96.32612381+3.26099672e-33j,\n",
       "        87.55881741-1.71196391e-32j, 132.77921767-5.85917742e-32j,\n",
       "        90.39111355-4.61245910e-32j, 110.46704661-1.26810141e-31j,\n",
       "       100.11498762+3.27332625e-33j,  75.06881699+1.74611506e-32j,\n",
       "       115.92761191-1.50141900e-32j, 119.39061096-2.66425331e-31j,\n",
       "       104.1625607 -1.65618785e-31j,  93.53233087+4.74634255e-32j,\n",
       "        95.98061856-3.55405828e-32j,  81.84809009-6.75822911e-33j,\n",
       "       141.33807503-2.83887255e-31j, 107.76950861+1.16133272e-32j,\n",
       "       105.32313788-2.44831258e-32j, 115.71746919+1.58444988e-33j,\n",
       "        84.59178696+1.84579981e-33j,  77.55192789-7.26317705e-32j,\n",
       "        98.53561734+8.96985706e-32j,  93.30202226-7.51364743e-33j,\n",
       "        93.30425919-7.67978855e-32j,  64.8426654 -9.50016337e-32j,\n",
       "        88.8363351 +8.58793911e-32j,  79.74774526-1.88133054e-31j,\n",
       "        58.27325023+6.40584329e-32j,  87.95749733-2.83048704e-32j,\n",
       "        94.18125033+2.62812944e-32j, 102.20191198+1.41628639e-32j,\n",
       "        77.50035059-1.28229311e-31j,  74.67916987-1.29032257e-32j,\n",
       "       107.65544266-5.07912626e-33j, 117.82643611-1.71986553e-31j,\n",
       "        85.49123534+3.84372238e-32j,  90.97944036+1.07799580e-31j,\n",
       "        94.00075195-4.61487187e-33j,  78.20293154-2.66351383e-32j,\n",
       "        91.87944855+2.58523205e-31j,  67.2326864 -9.36028147e-32j,\n",
       "        93.77687233-1.70426251e-31j, 122.14620244+1.63847851e-31j,\n",
       "       121.90284466+6.43113670e-33j,  84.79502685-5.90478610e-32j,\n",
       "        86.53636487-1.09818986e-32j, 108.45642577-3.19531770e-31j,\n",
       "        66.92995782+6.30089255e-34j, 162.26142686-1.50779272e-31j,\n",
       "       150.61601821-1.12124578e-31j, 135.72330341+2.64787637e-32j,\n",
       "        82.67648733+2.38337187e-32j,  96.32612381+3.26099672e-33j,\n",
       "        87.55881741-1.71196391e-32j, 132.77921767-5.85917742e-32j,\n",
       "        90.39111355-4.61245910e-32j, 110.46704661-1.26810141e-31j,\n",
       "       100.11498762+3.27332625e-33j,  75.06881699+1.74611506e-32j,\n",
       "       115.92761191-1.50141900e-32j, 119.39061096-2.66425331e-31j,\n",
       "       104.1625607 -1.65618785e-31j,  93.53233087+4.74634255e-32j,\n",
       "        95.98061856-3.55405828e-32j,  81.84809009-6.75822911e-33j,\n",
       "       141.33807503-2.83887255e-31j, 107.76950861+1.16133272e-32j,\n",
       "       105.32313788-2.44831258e-32j, 115.71746919+1.58444988e-33j,\n",
       "        84.59178696+1.84579981e-33j,  77.55192789-7.26317705e-32j,\n",
       "        98.53561734+8.96985706e-32j,  93.30202226-7.51364743e-33j,\n",
       "        93.30425919-7.67978855e-32j,  64.8426654 -9.50016337e-32j,\n",
       "        88.8363351 +8.58793911e-32j,  79.74774526-1.88133054e-31j,\n",
       "        58.27325023+6.40584329e-32j,  87.95749733-2.83048704e-32j,\n",
       "        94.18125033+2.62812944e-32j, 102.20191198+1.41628639e-32j,\n",
       "        77.50035059-1.28229311e-31j,  74.67916987-1.29032257e-32j])"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "square_root"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "YY=Y/square_root[:,None]\n",
    "distance_matrix = YY.dot(YY.T)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "distance_matrix=distance_matrix.real"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 1.        , -0.02608797, -0.02006162, ..., -0.02282991,\n",
       "        -0.01884483, -0.0185314 ],\n",
       "       [-0.02608797,  1.        , -0.02282955, ..., -0.02315958,\n",
       "        -0.0195812 , -0.02287087],\n",
       "       [-0.02006162, -0.02282955,  1.        , ..., -0.01798824,\n",
       "        -0.00954033, -0.00860957],\n",
       "       ...,\n",
       "       [-0.02282991, -0.02315958, -0.01798824, ...,  1.        ,\n",
       "        -0.01638236, -0.01592119],\n",
       "       [-0.01884483, -0.0195812 , -0.00954033, ..., -0.01638236,\n",
       "         1.        , -0.00476128],\n",
       "       [-0.0185314 , -0.02287087, -0.00860957, ..., -0.01592119,\n",
       "        -0.00476128,  1.        ]])"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "distance_matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7fae430b2c88>"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(distance_matrix)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(distance_matrix, cmap='hot', interpolation='nearest')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "YYY = Y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "Z = np.zeros([99,4])\n",
    "A = np.arange(0,100)\n",
    "sz = np.ones(100)\n",
    "cnt = 0\n",
    "YYYY = YYY\n",
    "def super_recursion():\n",
    "    global YYY\n",
    "    global A\n",
    "    global sz\n",
    "    global Z\n",
    "    global cnt\n",
    "    global YYYY\n",
    "    if YYY.shape[0]==2:\n",
    "        YYYY = YYY\n",
    "    if YYY.shape[0]<=1:\n",
    "        print(YYY)\n",
    "        return ;\n",
    "    sqa = np.square(YYY)\n",
    "    sqa = np.sum(sqa,axis=1).tolist()\n",
    "    square_roota = np.sqrt(sqa)\n",
    "    YY=YYY/square_roota[:,None]\n",
    "    distance_matrixa = YY.dot(YY.T)\n",
    "    distance_matrixa = distance_matrixa.real\n",
    "    np.fill_diagonal(distance_matrixa, -np.inf)\n",
    "    i,j = np.unravel_index(distance_matrixa.argmax(),distance_matrixa.shape)\n",
    "    one = YYY[i]\n",
    "    two = YYY[j]\n",
    "    avg = (one+two)/2.0\n",
    "    Z[cnt,0] = A[i]\n",
    "    Z[cnt,1] = A[j]\n",
    "    Z[cnt,2] = distance_matrixa[i,j]\n",
    "    Z[cnt,3] = sz[i] + sz[j]\n",
    "    YYY[i] = avg\n",
    "    YYY = np.delete(YYY,[j],axis=0)\n",
    "    A[i] = cnt + 100\n",
    "    A = np.delete(A,[j],axis=0)\n",
    "    sz[i] = sz[i] + sz[j]\n",
    "    sz = np.delete(sz,[j],axis=0)\n",
    "    cnt+=1\n",
    "    #print(YYY.shape)\n",
    "    super_recursion()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[ 6.07635583e+00+0.00000000e+00j  5.79852837e+00+0.00000000e+00j\n",
      "   5.48517000e+00+0.00000000e+00j  5.21114574e+00+0.00000000e+00j\n",
      "  -7.98771362e+00+0.00000000e+00j -5.20805735e-02+0.00000000e+00j\n",
      "  -1.23506723e-01+0.00000000e+00j  5.62537332e-01+0.00000000e+00j\n",
      "   1.55890113e+00+0.00000000e+00j  1.38554017e+00+0.00000000e+00j\n",
      "  -1.79041205e+00+0.00000000e+00j -1.09303217e-02+0.00000000e+00j\n",
      "  -5.16381523e-01+0.00000000e+00j -1.18628318e+00+0.00000000e+00j\n",
      "  -7.39467831e-01+0.00000000e+00j  1.69239294e+00+0.00000000e+00j\n",
      "  -4.33334092e-01+0.00000000e+00j  2.05401388e+00+0.00000000e+00j\n",
      "   4.07794369e-01+0.00000000e+00j -1.94625659e+00+0.00000000e+00j\n",
      "   3.34480296e-01+0.00000000e+00j -6.08140745e-01+0.00000000e+00j\n",
      "  -9.89615553e-02+0.00000000e+00j -1.23803200e-01+0.00000000e+00j\n",
      "   8.03508346e-02+0.00000000e+00j -1.05967235e-01+0.00000000e+00j\n",
      "   2.18882346e-02+0.00000000e+00j  4.05937878e-01+0.00000000e+00j\n",
      "  -3.97014562e-01+0.00000000e+00j -3.05834077e-01+0.00000000e+00j\n",
      "   6.09239005e-01+0.00000000e+00j -3.71958436e-01+0.00000000e+00j\n",
      "   2.05206482e-01+0.00000000e+00j -3.83279040e-01+0.00000000e+00j\n",
      "   3.31947294e-01+0.00000000e+00j  6.83240058e-02+0.00000000e+00j\n",
      "  -1.61097175e-01+0.00000000e+00j -6.84814721e-01+0.00000000e+00j\n",
      "  -3.82828926e-01+0.00000000e+00j  9.38431314e-01+0.00000000e+00j\n",
      "   1.41029102e+00+0.00000000e+00j  5.13525756e-01+0.00000000e+00j\n",
      "   4.45242042e-02+0.00000000e+00j -1.21945717e+00+0.00000000e+00j\n",
      "  -4.40649407e-01+0.00000000e+00j -1.49774625e+00+0.00000000e+00j\n",
      "   1.54574436e-01+0.00000000e+00j  5.44430769e-01+0.00000000e+00j\n",
      "  -6.75054250e-01+0.00000000e+00j  6.07189215e-15+0.00000000e+00j\n",
      "   3.00457409e-16-1.61647090e-15j  3.00457409e-16+1.61647090e-15j\n",
      "   1.33283975e-15+3.86954402e-16j  1.33283975e-15-3.86954402e-16j\n",
      "   3.69594674e-16+0.00000000e+00j -7.01846841e-16-2.78110774e-16j\n",
      "  -7.01846841e-16+2.78110774e-16j -2.03176496e-15+6.02212473e-16j\n",
      "  -2.03176496e-15-6.02212473e-16j  5.47306527e-16+5.78586819e-16j\n",
      "   5.47306527e-16-5.78586819e-16j  8.66784273e-16+1.36509810e-15j\n",
      "   8.66784273e-16-1.36509810e-15j  1.01159837e-15+0.00000000e+00j\n",
      "   5.49736241e-16+6.89191825e-16j  5.49736241e-16-6.89191825e-16j\n",
      "  -7.44211155e-16-4.71853309e-16j -7.44211155e-16+4.71853309e-16j\n",
      "  -1.31681791e-15+0.00000000e+00j -2.19811403e-16+0.00000000e+00j\n",
      "   2.28265850e-16+6.19056782e-16j  2.28265850e-16-6.19056782e-16j\n",
      "  -3.65405778e-16-7.18159247e-16j -3.65405778e-16+7.18159247e-16j\n",
      "   1.46409216e-15+0.00000000e+00j -6.06712230e-16+1.59330233e-16j\n",
      "  -6.06712230e-16-1.59330233e-16j  8.22733478e-16+0.00000000e+00j\n",
      "   9.19860766e-17+6.23043555e-17j  9.19860766e-17-6.23043555e-17j\n",
      "  -1.09578172e-15+0.00000000e+00j  2.05403902e-16+2.30915581e-16j\n",
      "   2.05403902e-16-2.30915581e-16j  8.73653075e-16-1.14556706e-16j\n",
      "   8.73653075e-16+1.14556706e-16j  2.12658633e-16+0.00000000e+00j\n",
      "  -1.38069388e-16-1.24109703e-16j -1.38069388e-16+1.24109703e-16j\n",
      "   4.24629078e-16+0.00000000e+00j -7.81215734e-16+0.00000000e+00j\n",
      "  -1.17195754e-15+0.00000000e+00j  1.05865735e-15+0.00000000e+00j\n",
      "  -3.65512504e-16+4.13479510e-16j -3.65512504e-16-4.13479510e-16j\n",
      "   1.48305389e-15-2.58647598e-16j  1.48305389e-15+2.58647598e-16j\n",
      "   1.25891119e-16+0.00000000e+00j -1.21522695e-15-2.77009208e-16j\n",
      "  -1.21522695e-15+2.77009208e-16j -5.49940059e-16+2.44394840e-16j]]\n"
     ]
    }
   ],
   "source": [
    "super_recursion()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(99, 4)"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Z.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "for i in range(0,Z.shape[0]):\n",
    "    Z[i,2] = 1.0 - Z[i,2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "for i in range(0,Z.shape[0]):\n",
    "    if(Z[i,2]<0):\n",
    "        Z[i,2]=0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[2.00000000e+00, 5.20000000e+01, 0.00000000e+00, 2.00000000e+00],\n",
       "       [4.00000000e+00, 5.40000000e+01, 0.00000000e+00, 2.00000000e+00],\n",
       "       [2.40000000e+01, 7.40000000e+01, 0.00000000e+00, 2.00000000e+00],\n",
       "       [3.20000000e+01, 8.20000000e+01, 0.00000000e+00, 2.00000000e+00],\n",
       "       [5.00000000e+00, 5.50000000e+01, 0.00000000e+00, 2.00000000e+00],\n",
       "       [7.00000000e+00, 5.70000000e+01, 0.00000000e+00, 2.00000000e+00],\n",
       "       [1.50000000e+01, 6.50000000e+01, 0.00000000e+00, 2.00000000e+00],\n",
       "       [2.00000000e+01, 7.00000000e+01, 0.00000000e+00, 2.00000000e+00],\n",
       "       [2.10000000e+01, 7.10000000e+01, 0.00000000e+00, 2.00000000e+00],\n",
       "       [2.60000000e+01, 7.60000000e+01, 0.00000000e+00, 2.00000000e+00],\n",
       "       [2.90000000e+01, 7.90000000e+01, 0.00000000e+00, 2.00000000e+00],\n",
       "       [3.80000000e+01, 8.80000000e+01, 0.00000000e+00, 2.00000000e+00],\n",
       "       [4.30000000e+01, 9.30000000e+01, 0.00000000e+00, 2.00000000e+00],\n",
       "       [4.80000000e+01, 9.80000000e+01, 0.00000000e+00, 2.00000000e+00],\n",
       "       [4.90000000e+01, 9.90000000e+01, 0.00000000e+00, 2.00000000e+00],\n",
       "       [3.00000000e+00, 5.30000000e+01, 0.00000000e+00, 2.00000000e+00],\n",
       "       [1.80000000e+01, 6.80000000e+01, 0.00000000e+00, 2.00000000e+00],\n",
       "       [1.90000000e+01, 6.90000000e+01, 0.00000000e+00, 2.00000000e+00],\n",
       "       [2.20000000e+01, 7.20000000e+01, 0.00000000e+00, 2.00000000e+00],\n",
       "       [2.80000000e+01, 7.80000000e+01, 0.00000000e+00, 2.00000000e+00],\n",
       "       [3.30000000e+01, 8.30000000e+01, 0.00000000e+00, 2.00000000e+00],\n",
       "       [3.40000000e+01, 8.40000000e+01, 0.00000000e+00, 2.00000000e+00],\n",
       "       [3.50000000e+01, 8.50000000e+01, 0.00000000e+00, 2.00000000e+00],\n",
       "       [3.60000000e+01, 8.60000000e+01, 0.00000000e+00, 2.00000000e+00],\n",
       "       [3.70000000e+01, 8.70000000e+01, 0.00000000e+00, 2.00000000e+00],\n",
       "       [4.20000000e+01, 9.20000000e+01, 0.00000000e+00, 2.00000000e+00],\n",
       "       [1.10000000e+01, 6.10000000e+01, 1.11022302e-16, 2.00000000e+00],\n",
       "       [1.20000000e+01, 6.20000000e+01, 1.11022302e-16, 2.00000000e+00],\n",
       "       [1.30000000e+01, 6.30000000e+01, 1.11022302e-16, 2.00000000e+00],\n",
       "       [1.40000000e+01, 6.40000000e+01, 1.11022302e-16, 2.00000000e+00],\n",
       "       [3.90000000e+01, 8.90000000e+01, 1.11022302e-16, 2.00000000e+00],\n",
       "       [4.10000000e+01, 9.10000000e+01, 1.11022302e-16, 2.00000000e+00],\n",
       "       [4.40000000e+01, 9.40000000e+01, 1.11022302e-16, 2.00000000e+00],\n",
       "       [4.70000000e+01, 9.70000000e+01, 1.11022302e-16, 2.00000000e+00],\n",
       "       [8.00000000e+00, 5.80000000e+01, 2.22044605e-16, 2.00000000e+00],\n",
       "       [1.60000000e+01, 6.60000000e+01, 2.22044605e-16, 2.00000000e+00],\n",
       "       [1.70000000e+01, 6.70000000e+01, 2.22044605e-16, 2.00000000e+00],\n",
       "       [2.30000000e+01, 7.30000000e+01, 2.22044605e-16, 2.00000000e+00],\n",
       "       [4.00000000e+01, 9.00000000e+01, 2.22044605e-16, 2.00000000e+00],\n",
       "       [1.00000000e+00, 5.10000000e+01, 3.33066907e-16, 2.00000000e+00],\n",
       "       [2.50000000e+01, 7.50000000e+01, 3.33066907e-16, 2.00000000e+00],\n",
       "       [3.00000000e+01, 8.00000000e+01, 3.33066907e-16, 2.00000000e+00],\n",
       "       [3.10000000e+01, 8.10000000e+01, 3.33066907e-16, 2.00000000e+00],\n",
       "       [4.50000000e+01, 9.50000000e+01, 3.33066907e-16, 2.00000000e+00],\n",
       "       [0.00000000e+00, 5.00000000e+01, 4.44089210e-16, 2.00000000e+00],\n",
       "       [1.00000000e+01, 6.00000000e+01, 4.44089210e-16, 2.00000000e+00],\n",
       "       [4.60000000e+01, 9.60000000e+01, 4.44089210e-16, 2.00000000e+00],\n",
       "       [9.00000000e+00, 5.90000000e+01, 5.55111512e-16, 2.00000000e+00],\n",
       "       [2.70000000e+01, 7.70000000e+01, 5.55111512e-16, 2.00000000e+00],\n",
       "       [6.00000000e+00, 5.60000000e+01, 6.66133815e-16, 2.00000000e+00],\n",
       "       [1.31000000e+02, 1.32000000e+02, 9.85470966e-01, 4.00000000e+00],\n",
       "       [1.05000000e+02, 1.50000000e+02, 9.83074805e-01, 6.00000000e+00],\n",
       "       [1.51000000e+02, 1.29000000e+02, 9.87309249e-01, 8.00000000e+00],\n",
       "       [1.52000000e+02, 1.14000000e+02, 9.93555736e-01, 1.00000000e+01],\n",
       "       [1.26000000e+02, 1.23000000e+02, 9.96210483e-01, 4.00000000e+00],\n",
       "       [1.53000000e+02, 1.40000000e+02, 1.00209893e+00, 1.20000000e+01],\n",
       "       [1.55000000e+02, 1.13000000e+02, 1.00543010e+00, 1.40000000e+01],\n",
       "       [1.04000000e+02, 1.24000000e+02, 1.00641754e+00, 4.00000000e+00],\n",
       "       [1.42000000e+02, 1.12000000e+02, 1.00863775e+00, 4.00000000e+00],\n",
       "       [1.07000000e+02, 1.10000000e+02, 1.01065586e+00, 4.00000000e+00],\n",
       "       [1.00000000e+02, 1.16000000e+02, 1.01143467e+00, 4.00000000e+00],\n",
       "       [1.27000000e+02, 1.17000000e+02, 1.01167935e+00, 4.00000000e+00],\n",
       "       [1.18000000e+02, 1.30000000e+02, 1.01196278e+00, 4.00000000e+00],\n",
       "       [1.57000000e+02, 1.56000000e+02, 1.01239010e+00, 1.80000000e+01],\n",
       "       [1.01000000e+02, 1.25000000e+02, 1.01292787e+00, 4.00000000e+00],\n",
       "       [1.15000000e+02, 1.34000000e+02, 1.01444059e+00, 4.00000000e+00],\n",
       "       [1.41000000e+02, 1.43000000e+02, 1.01509725e+00, 4.00000000e+00],\n",
       "       [1.02000000e+02, 1.38000000e+02, 1.01632611e+00, 4.00000000e+00],\n",
       "       [1.49000000e+02, 1.46000000e+02, 1.01719384e+00, 4.00000000e+00],\n",
       "       [1.11000000e+02, 1.33000000e+02, 1.01808386e+00, 4.00000000e+00],\n",
       "       [1.54000000e+02, 1.58000000e+02, 1.01971712e+00, 8.00000000e+00],\n",
       "       [1.44000000e+02, 1.21000000e+02, 1.02154541e+00, 4.00000000e+00],\n",
       "       [1.28000000e+02, 1.37000000e+02, 1.02216337e+00, 4.00000000e+00],\n",
       "       [1.19000000e+02, 1.20000000e+02, 1.02328724e+00, 4.00000000e+00],\n",
       "       [1.39000000e+02, 1.09000000e+02, 1.02410230e+00, 4.00000000e+00],\n",
       "       [1.45000000e+02, 1.22000000e+02, 1.02509940e+00, 4.00000000e+00],\n",
       "       [1.60000000e+02, 1.63000000e+02, 1.02638637e+00, 2.20000000e+01],\n",
       "       [1.47000000e+02, 1.48000000e+02, 1.02686286e+00, 4.00000000e+00],\n",
       "       [1.36000000e+02, 1.08000000e+02, 1.03035369e+00, 4.00000000e+00],\n",
       "       [1.61000000e+02, 1.59000000e+02, 1.03047501e+00, 8.00000000e+00],\n",
       "       [1.06000000e+02, 1.35000000e+02, 1.03124526e+00, 4.00000000e+00],\n",
       "       [1.64000000e+02, 1.68000000e+02, 1.03258451e+00, 8.00000000e+00],\n",
       "       [1.62000000e+02, 1.66000000e+02, 1.03402888e+00, 8.00000000e+00],\n",
       "       [1.65000000e+02, 1.67000000e+02, 1.03585226e+00, 8.00000000e+00],\n",
       "       [1.74000000e+02, 1.03000000e+02, 1.04046449e+00, 6.00000000e+00],\n",
       "       [1.71000000e+02, 1.69000000e+02, 1.04191560e+00, 8.00000000e+00],\n",
       "       [1.76000000e+02, 1.70000000e+02, 1.04468980e+00, 3.00000000e+01],\n",
       "       [1.72000000e+02, 1.73000000e+02, 1.04841803e+00, 8.00000000e+00],\n",
       "       [1.77000000e+02, 1.75000000e+02, 1.05569890e+00, 8.00000000e+00],\n",
       "       [1.80000000e+02, 1.78000000e+02, 1.06550462e+00, 8.00000000e+00],\n",
       "       [1.81000000e+02, 1.79000000e+02, 1.06754054e+00, 1.60000000e+01],\n",
       "       [1.83000000e+02, 1.82000000e+02, 1.07405287e+00, 1.60000000e+01],\n",
       "       [1.85000000e+02, 1.84000000e+02, 1.08857623e+00, 1.40000000e+01],\n",
       "       [1.88000000e+02, 1.87000000e+02, 1.11061542e+00, 1.60000000e+01],\n",
       "       [1.86000000e+02, 1.90000000e+02, 1.12642222e+00, 4.60000000e+01],\n",
       "       [1.92000000e+02, 1.89000000e+02, 1.16355732e+00, 2.20000000e+01],\n",
       "       [1.91000000e+02, 1.93000000e+02, 1.20828845e+00, 3.20000000e+01],\n",
       "       [1.94000000e+02, 1.96000000e+02, 1.42264403e+00, 7.80000000e+01],\n",
       "       [1.95000000e+02, 1.97000000e+02, 1.82859146e+00, 1.00000000e+02]])"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Z"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2.0    52.0   2.0\n",
      "4.0    54.0   2.0\n",
      "24.0    74.0   2.0\n",
      "32.0    82.0   2.0\n",
      "5.0    55.0   2.0\n",
      "7.0    57.0   2.0\n",
      "15.0    65.0   2.0\n",
      "20.0    70.0   2.0\n",
      "21.0    71.0   2.0\n",
      "26.0    76.0   2.0\n",
      "29.0    79.0   2.0\n",
      "38.0    88.0   2.0\n",
      "43.0    93.0   2.0\n",
      "48.0    98.0   2.0\n",
      "49.0    99.0   2.0\n",
      "3.0    53.0   2.0\n",
      "18.0    68.0   2.0\n",
      "19.0    69.0   2.0\n",
      "22.0    72.0   2.0\n",
      "28.0    78.0   2.0\n",
      "33.0    83.0   2.0\n",
      "34.0    84.0   2.0\n",
      "35.0    85.0   2.0\n",
      "36.0    86.0   2.0\n",
      "37.0    87.0   2.0\n",
      "42.0    92.0   2.0\n",
      "11.0    61.0   2.0\n",
      "12.0    62.0   2.0\n",
      "13.0    63.0   2.0\n",
      "14.0    64.0   2.0\n",
      "39.0    89.0   2.0\n",
      "41.0    91.0   2.0\n",
      "44.0    94.0   2.0\n",
      "47.0    97.0   2.0\n",
      "8.0    58.0   2.0\n",
      "16.0    66.0   2.0\n",
      "17.0    67.0   2.0\n",
      "23.0    73.0   2.0\n",
      "40.0    90.0   2.0\n",
      "1.0    51.0   2.0\n",
      "25.0    75.0   2.0\n",
      "30.0    80.0   2.0\n",
      "31.0    81.0   2.0\n",
      "45.0    95.0   2.0\n",
      "0.0    50.0   2.0\n",
      "10.0    60.0   2.0\n",
      "46.0    96.0   2.0\n",
      "9.0    59.0   2.0\n",
      "27.0    77.0   2.0\n",
      "6.0    56.0   2.0\n",
      "131.0    132.0   4.0\n",
      "105.0    150.0   6.0\n",
      "151.0    129.0   8.0\n",
      "152.0    114.0   10.0\n",
      "126.0    123.0   4.0\n",
      "153.0    140.0   12.0\n",
      "155.0    113.0   14.0\n",
      "104.0    124.0   4.0\n",
      "142.0    112.0   4.0\n",
      "107.0    110.0   4.0\n",
      "100.0    116.0   4.0\n",
      "127.0    117.0   4.0\n",
      "118.0    130.0   4.0\n",
      "157.0    156.0   18.0\n",
      "101.0    125.0   4.0\n",
      "115.0    134.0   4.0\n",
      "141.0    143.0   4.0\n",
      "102.0    138.0   4.0\n",
      "149.0    146.0   4.0\n",
      "111.0    133.0   4.0\n",
      "154.0    158.0   8.0\n",
      "144.0    121.0   4.0\n",
      "128.0    137.0   4.0\n",
      "119.0    120.0   4.0\n",
      "139.0    109.0   4.0\n",
      "145.0    122.0   4.0\n",
      "160.0    163.0   22.0\n",
      "147.0    148.0   4.0\n",
      "136.0    108.0   4.0\n",
      "161.0    159.0   8.0\n",
      "106.0    135.0   4.0\n",
      "164.0    168.0   8.0\n",
      "162.0    166.0   8.0\n",
      "165.0    167.0   8.0\n",
      "174.0    103.0   6.0\n",
      "171.0    169.0   8.0\n",
      "176.0    170.0   30.0\n",
      "172.0    173.0   8.0\n",
      "177.0    175.0   8.0\n",
      "180.0    178.0   8.0\n",
      "181.0    179.0   16.0\n",
      "183.0    182.0   16.0\n",
      "185.0    184.0   14.0\n",
      "188.0    187.0   16.0\n",
      "186.0    190.0   46.0\n",
      "192.0    189.0   22.0\n",
      "191.0    193.0   32.0\n",
      "194.0    196.0   78.0\n",
      "195.0    197.0   100.0\n"
     ]
    }
   ],
   "source": [
    "for i in range(0,Z.shape[0]):\n",
    "    print(\"{}    {}   {}\".format(Z[i,0],Z[i,1],Z[i,3]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from matplotlib import pyplot as plt\n",
    "from scipy.cluster.hierarchy import dendrogram, linkage"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 2., 52.,  0.,  2.])"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Z[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 2160x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(30,8))\n",
    "plt.title('Hierarchical Clustering Dendrogram')\n",
    "plt.xlabel('sample index')\n",
    "plt.ylabel('distance')\n",
    "dendrogram(\n",
    "    Z,\n",
    "    leaf_rotation=90.,  # rotates the x axis labels\n",
    "   # leaf_font_size=8.,  # font size for the x axis labels\n",
    ")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 6.07635583e+00+0.00000000e+00j,  5.79852837e+00+0.00000000e+00j,\n",
       "         5.48517000e+00+0.00000000e+00j,  5.21114574e+00+0.00000000e+00j,\n",
       "        -7.98771362e+00+0.00000000e+00j, -5.20805735e-02+0.00000000e+00j,\n",
       "        -1.23506723e-01+0.00000000e+00j,  5.62537332e-01+0.00000000e+00j,\n",
       "         1.55890113e+00+0.00000000e+00j,  1.38554017e+00+0.00000000e+00j,\n",
       "        -1.79041205e+00+0.00000000e+00j, -1.09303217e-02+0.00000000e+00j,\n",
       "        -5.16381523e-01+0.00000000e+00j, -1.18628318e+00+0.00000000e+00j,\n",
       "        -7.39467831e-01+0.00000000e+00j,  1.69239294e+00+0.00000000e+00j,\n",
       "        -4.33334092e-01+0.00000000e+00j,  2.05401388e+00+0.00000000e+00j,\n",
       "         4.07794369e-01+0.00000000e+00j, -1.94625659e+00+0.00000000e+00j,\n",
       "         3.34480296e-01+0.00000000e+00j, -6.08140745e-01+0.00000000e+00j,\n",
       "        -9.89615553e-02+0.00000000e+00j, -1.23803200e-01+0.00000000e+00j,\n",
       "         8.03508346e-02+0.00000000e+00j, -1.05967235e-01+0.00000000e+00j,\n",
       "         2.18882346e-02+0.00000000e+00j,  4.05937878e-01+0.00000000e+00j,\n",
       "        -3.97014562e-01+0.00000000e+00j, -3.05834077e-01+0.00000000e+00j,\n",
       "         6.09239005e-01+0.00000000e+00j, -3.71958436e-01+0.00000000e+00j,\n",
       "         2.05206482e-01+0.00000000e+00j, -3.83279040e-01+0.00000000e+00j,\n",
       "         3.31947294e-01+0.00000000e+00j,  6.83240058e-02+0.00000000e+00j,\n",
       "        -1.61097175e-01+0.00000000e+00j, -6.84814721e-01+0.00000000e+00j,\n",
       "        -3.82828926e-01+0.00000000e+00j,  9.38431314e-01+0.00000000e+00j,\n",
       "         1.41029102e+00+0.00000000e+00j,  5.13525756e-01+0.00000000e+00j,\n",
       "         4.45242042e-02+0.00000000e+00j, -1.21945717e+00+0.00000000e+00j,\n",
       "        -4.40649407e-01+0.00000000e+00j, -1.49774625e+00+0.00000000e+00j,\n",
       "         1.54574436e-01+0.00000000e+00j,  5.44430769e-01+0.00000000e+00j,\n",
       "        -6.75054250e-01+0.00000000e+00j,  6.07189215e-15+0.00000000e+00j,\n",
       "         3.00457409e-16-1.61647090e-15j,  3.00457409e-16+1.61647090e-15j,\n",
       "         1.33283975e-15+3.86954402e-16j,  1.33283975e-15-3.86954402e-16j,\n",
       "         3.69594674e-16+0.00000000e+00j, -7.01846841e-16-2.78110774e-16j,\n",
       "        -7.01846841e-16+2.78110774e-16j, -2.03176496e-15+6.02212473e-16j,\n",
       "        -2.03176496e-15-6.02212473e-16j,  5.47306527e-16+5.78586819e-16j,\n",
       "         5.47306527e-16-5.78586819e-16j,  8.66784273e-16+1.36509810e-15j,\n",
       "         8.66784273e-16-1.36509810e-15j,  1.01159837e-15+0.00000000e+00j,\n",
       "         5.49736241e-16+6.89191825e-16j,  5.49736241e-16-6.89191825e-16j,\n",
       "        -7.44211155e-16-4.71853309e-16j, -7.44211155e-16+4.71853309e-16j,\n",
       "        -1.31681791e-15+0.00000000e+00j, -2.19811403e-16+0.00000000e+00j,\n",
       "         2.28265850e-16+6.19056782e-16j,  2.28265850e-16-6.19056782e-16j,\n",
       "        -3.65405778e-16-7.18159247e-16j, -3.65405778e-16+7.18159247e-16j,\n",
       "         1.46409216e-15+0.00000000e+00j, -6.06712230e-16+1.59330233e-16j,\n",
       "        -6.06712230e-16-1.59330233e-16j,  8.22733478e-16+0.00000000e+00j,\n",
       "         9.19860766e-17+6.23043555e-17j,  9.19860766e-17-6.23043555e-17j,\n",
       "        -1.09578172e-15+0.00000000e+00j,  2.05403902e-16+2.30915581e-16j,\n",
       "         2.05403902e-16-2.30915581e-16j,  8.73653075e-16-1.14556706e-16j,\n",
       "         8.73653075e-16+1.14556706e-16j,  2.12658633e-16+0.00000000e+00j,\n",
       "        -1.38069388e-16-1.24109703e-16j, -1.38069388e-16+1.24109703e-16j,\n",
       "         4.24629078e-16+0.00000000e+00j, -7.81215734e-16+0.00000000e+00j,\n",
       "        -1.17195754e-15+0.00000000e+00j,  1.05865735e-15+0.00000000e+00j,\n",
       "        -3.65512504e-16+4.13479510e-16j, -3.65512504e-16-4.13479510e-16j,\n",
       "         1.48305389e-15-2.58647598e-16j,  1.48305389e-15+2.58647598e-16j,\n",
       "         1.25891119e-16+0.00000000e+00j, -1.21522695e-15-2.77009208e-16j,\n",
       "        -1.21522695e-15+2.77009208e-16j, -5.49940059e-16+2.44394840e-16j],\n",
       "       [-2.95305853e+00+0.00000000e+00j, -2.84430217e+00+0.00000000e+00j,\n",
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       "        -1.07094521e-15+0.00000000e+00j,  3.94721589e-17+0.00000000e+00j,\n",
       "        -9.92642146e-17+0.00000000e+00j,  1.08504921e-16+0.00000000e+00j,\n",
       "         4.69403637e-16-6.05922570e-16j,  4.69403637e-16+6.05922570e-16j,\n",
       "         5.10173026e-16-1.20509389e-16j,  5.10173026e-16+1.20509389e-16j,\n",
       "        -4.32403543e-16+0.00000000e+00j,  6.11004252e-16+1.20318023e-15j,\n",
       "         6.11004252e-16-1.20318023e-15j,  3.46554001e-16+3.76656070e-16j]])"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "YYYY"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0.96006141, 0.94636114, 1.07982797, 1.07777953, 1.07669744,\n",
       "        1.12370467, 1.07791544, 1.15792736, 1.07712764, 1.07395878,\n",
       "        1.0734487 , 1.08027932, 1.07979417, 1.07451343, 1.15405797,\n",
       "        0.54897461, 0.58751728, 0.63613308, 1.08025253, 1.07783396,\n",
       "        1.07802055, 0.64548464, 1.07667446, 1.0751847 , 1.07656382,\n",
       "        1.14237975, 0.94871412, 1.07433096, 1.07389077, 1.0768686 ,\n",
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       "        1.0734053 , 1.08038274, 1.12367132, 0.96928465, 1.07705253,\n",
       "        1.0781226 , 1.15642805, 1.07865075, 1.08176996, 1.15430983,\n",
       "        1.07817225, 1.0763021 , 0.96602077, 1.1234476 , 1.15316366,\n",
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       "        1.0734487 , 1.08027932, 1.07979417, 1.07451343, 1.15405797,\n",
       "        0.54897461, 0.58751728, 0.63613308, 1.08025253, 1.07783396,\n",
       "        1.07802055, 0.64548464, 1.07667446, 1.0751847 , 1.07656382,\n",
       "        1.14237975, 0.94871412, 1.07433096, 1.07389077, 1.0768686 ,\n",
       "        1.07453774, 1.08052167, 0.61718716, 1.07485955, 0.96061167,\n",
       "        1.0734053 , 1.08038274, 1.12367132, 0.96928465, 1.07705253,\n",
       "        1.0781226 , 1.15642805, 1.07865075, 1.08176996, 1.15430983,\n",
       "        1.07817225, 1.0763021 , 0.96602077, 1.1234476 , 1.15316366],\n",
       "       [1.18701892, 1.21051864, 0.88907122, 0.8847024 , 0.88275223,\n",
       "        1.00878845, 0.88484191, 1.09149829, 0.88273774, 0.85581931,\n",
       "        0.8565919 , 0.88823427, 0.88798754, 0.86935028, 1.08487032,\n",
       "        1.30063955, 1.27636156, 1.24388572, 0.89343174, 0.87787105,\n",
       "        0.88853038, 1.24040273, 0.88651112, 0.86601752, 0.87555487,\n",
       "        1.06185021, 1.2060081 , 0.85747304, 0.87303056, 0.88218   ,\n",
       "        0.88384139, 0.89289848, 1.25742353, 0.86959422, 1.18457509,\n",
       "        0.86283205, 0.88912691, 1.00841734, 1.17112546, 0.88329324,\n",
       "        0.88341341, 1.08956535, 0.8877627 , 0.8944717 , 1.07384838,\n",
       "        0.88749061, 0.88299946, 1.17710446, 1.0099555 , 1.08940095,\n",
       "        1.18701892, 1.21051864, 0.88907122, 0.8847024 , 0.88275223,\n",
       "        1.00878845, 0.88484191, 1.09149829, 0.88273774, 0.85581931,\n",
       "        0.8565919 , 0.88823427, 0.88798754, 0.86935028, 1.08487032,\n",
       "        1.30063955, 1.27636156, 1.24388572, 0.89343174, 0.87787105,\n",
       "        0.88853038, 1.24040273, 0.88651112, 0.86601752, 0.87555487,\n",
       "        1.06185021, 1.2060081 , 0.85747304, 0.87303056, 0.88218   ,\n",
       "        0.88384139, 0.89289848, 1.25742353, 0.86959422, 1.18457509,\n",
       "        0.86283205, 0.88912691, 1.00841734, 1.17112546, 0.88329324,\n",
       "        0.88341341, 1.08956535, 0.8877627 , 0.8944717 , 1.07384838,\n",
       "        0.88749061, 0.88299946, 1.17710446, 1.0099555 , 1.08940095]])"
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sqa = np.square(YYYY)\n",
    "sqa = np.sum(sqa,axis=1).tolist()\n",
    "square_roota = np.sqrt(sqa)\n",
    "YY=YYYY/square_roota[:,None]\n",
    "\n",
    "sqa1 = np.square(Y)\n",
    "sqa1 = np.sum(sqa1,axis=1).tolist()\n",
    "square_roota1 = np.sqrt(sqa1)\n",
    "YY1=Y/square_roota1[:,None]\n",
    "\n",
    "cluster_distance = YY.dot(YY1.T)\n",
    "cluster_distance = cluster_distance.real\n",
    "cluster_distance = 1 - cluster_distance\n",
    "cluster_distance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "sum1 = 0\n",
    "sum2 = 0\n",
    "cnt1 = 0\n",
    "cnt2 = 0\n",
    "arr = np.zeros(100)\n",
    "for i in range(0,100):\n",
    "    d1 = cluster_distance[0][i]\n",
    "    d2 = cluster_distance[1][i]\n",
    "    \n",
    "    if d1<=d2:\n",
    "        sum1+=d1\n",
    "        cnt1+=1\n",
    "        arr[i] = 0\n",
    "    else:\n",
    "        sum2+=d2\n",
    "        cnt2+=1\n",
    "        arr[i] = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "r1 = np.sqrt(sum1/cnt1)\n",
    "r2 = np.sqrt(sum2/cnt2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8937332589962359"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9596822129470908"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "22"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cnt1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "78"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cnt2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "c=0;\n",
    "for i in range(50,100):\n",
    "    if(arr[i]==0):\n",
    "        c=c+1\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "11"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "c"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "label=pd.DataFrame(arr)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "frame_with_labels= pd.concat([df,label],axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>0.0</td>\n",
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       "      <th>17</th>\n",
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       "      <th>27</th>\n",
       "      <td>[(outrageous, previews), (bulworth, one), (one...</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>[(booming, introduction), (introduction, music...</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>[(huge, fan), (fan, jeff), (jeff, bridges), (b...</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>[(plot, dude), (driving, cross), (cross, count...</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>[(may, consider), (consider, portions), (follo...</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>[(ultra, low), (low, budget), (extremely, inve...</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>[(told, several), (several, people), (old, fas...</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>[(eight, years), (release, disney), (decided, ...</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>[(umptenth, time), (time, also), (also, comple...</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>[(strong, language), (language, sexual), (sexu...</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>[(outrageous, previews), (bulworth, one), (one...</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>[(booming, introduction), (introduction, music...</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>[(huge, fan), (fan, jeff), (jeff, bridges), (b...</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>[(martin, scorsese), (scorsese, triumphant), (...</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>[(yet, born), (rock, rolled), (rolled, around)...</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82</th>\n",
       "      <td>[(success, particular), (particular, film), (f...</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>[(marie, charlotte), (charlotte, rampling), (r...</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84</th>\n",
       "      <td>[(big, courtroom), (courtroom, thrillers), (al...</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>[(vannesa, kensington), (kensington, austin), ...</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>86</th>\n",
       "      <td>[(funniest, carry), (carry, movies), (medical,...</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87</th>\n",
       "      <td>[(film, recent), (conflicted, feelings), (feel...</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>[(summer, movie), (movie, season), (season, al...</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>[(scene, early), (early, soul), (soul, food), ...</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>[(let, face), (million, plus), (plus, smash), ...</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>91</th>\n",
       "      <td>[(word, rest), (stressed, since), (action, sce...</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92</th>\n",
       "      <td>[(larry, flynt), (flynt, self), (self, proclai...</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93</th>\n",
       "      <td>[(good, thriller), (thriller, action), (action...</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>[(well, know), (stallone, years), (years, old)...</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>[(steve, soderbergh), (soderbergh, sex), (sex,...</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>[(one, thing), (thing, common), (hollywood, ma...</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>[(alien, marked), (death, suicide), (popular, ...</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>[(life, beautiful), (beautiful, rare), (rare, ...</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>[(indian, runner), (courier, became), (danger,...</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>100 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                 text    0\n",
       "0   [(rather, mary), (mary, railly), (railly, step...  0.0\n",
       "1   [(look, back), (sort, decision), (better, wors...  0.0\n",
       "2   [(must, tough), (tough, mob), (mob, boss), (as...  1.0\n",
       "3   [(capsule, earthy), (earthy, experimental), (e...  1.0\n",
       "4   [(jim, henson), (henson, passed), (passed, awa...  1.0\n",
       "5   [(movie, steven), (steven, spielberg), (spielb...  1.0\n",
       "6   [(quiz, show), (show, almost), (almost, perfec...  1.0\n",
       "7   [(first, thing), (cold, placed), (placed, minn...  1.0\n",
       "8   [(plot, group), (group, asbestos), (asbestos, ...  1.0\n",
       "9   [(coen, brothers), (homer, odyssey), (tale, th...  1.0\n",
       "10  [(many, children), (children, films), (films, ...  1.0\n",
       "11  [(last, entries), (long, running), (running, c...  1.0\n",
       "12  [(ingredients, neophyte), (neophyte, lawyer), ...  1.0\n",
       "13  [(talented, screenwriter), (make, feel), (feel...  1.0\n",
       "14  [(highly, built), (truman, show), (reviews, bo...  1.0\n",
       "15  [(enjoy, science), (science, fiction), (often,...  0.0\n",
       "16  [(good, long), (good, old), (old, fashioned), ...  0.0\n",
       "17  [(dangerous, beauty), (beauty, really), (reall...  0.0\n",
       "18  [(happy, bastard), (bastard, quick), (quick, m...  1.0\n",
       "19  [(type, motion), (motion, picture), (often, se...  1.0\n",
       "20  [(plot, dude), (driving, cross), (cross, count...  1.0\n",
       "21  [(may, consider), (consider, portions), (follo...  0.0\n",
       "22  [(ultra, low), (low, budget), (extremely, inve...  1.0\n",
       "23  [(told, several), (several, people), (old, fas...  1.0\n",
       "24  [(eight, years), (release, disney), (decided, ...  1.0\n",
       "25  [(umptenth, time), (time, also), (also, comple...  1.0\n",
       "26  [(strong, language), (language, sexual), (sexu...  0.0\n",
       "27  [(outrageous, previews), (bulworth, one), (one...  1.0\n",
       "28  [(booming, introduction), (introduction, music...  1.0\n",
       "29  [(huge, fan), (fan, jeff), (jeff, bridges), (b...  1.0\n",
       "..                                                ...  ...\n",
       "70  [(plot, dude), (driving, cross), (cross, count...  1.0\n",
       "71  [(may, consider), (consider, portions), (follo...  0.0\n",
       "72  [(ultra, low), (low, budget), (extremely, inve...  1.0\n",
       "73  [(told, several), (several, people), (old, fas...  1.0\n",
       "74  [(eight, years), (release, disney), (decided, ...  1.0\n",
       "75  [(umptenth, time), (time, also), (also, comple...  1.0\n",
       "76  [(strong, language), (language, sexual), (sexu...  0.0\n",
       "77  [(outrageous, previews), (bulworth, one), (one...  1.0\n",
       "78  [(booming, introduction), (introduction, music...  1.0\n",
       "79  [(huge, fan), (fan, jeff), (jeff, bridges), (b...  1.0\n",
       "80  [(martin, scorsese), (scorsese, triumphant), (...  1.0\n",
       "81  [(yet, born), (rock, rolled), (rolled, around)...  1.0\n",
       "82  [(success, particular), (particular, film), (f...  0.0\n",
       "83  [(marie, charlotte), (charlotte, rampling), (r...  1.0\n",
       "84  [(big, courtroom), (courtroom, thrillers), (al...  0.0\n",
       "85  [(vannesa, kensington), (kensington, austin), ...  1.0\n",
       "86  [(funniest, carry), (carry, movies), (medical,...  1.0\n",
       "87  [(film, recent), (conflicted, feelings), (feel...  1.0\n",
       "88  [(summer, movie), (movie, season), (season, al...  0.0\n",
       "89  [(scene, early), (early, soul), (soul, food), ...  1.0\n",
       "90  [(let, face), (million, plus), (plus, smash), ...  1.0\n",
       "91  [(word, rest), (stressed, since), (action, sce...  1.0\n",
       "92  [(larry, flynt), (flynt, self), (self, proclai...  1.0\n",
       "93  [(good, thriller), (thriller, action), (action...  1.0\n",
       "94  [(well, know), (stallone, years), (years, old)...  1.0\n",
       "95  [(steve, soderbergh), (soderbergh, sex), (sex,...  1.0\n",
       "96  [(one, thing), (thing, common), (hollywood, ma...  1.0\n",
       "97  [(alien, marked), (death, suicide), (popular, ...  0.0\n",
       "98  [(life, beautiful), (beautiful, rare), (rare, ...  1.0\n",
       "99  [(indian, runner), (courier, became), (danger,...  1.0\n",
       "\n",
       "[100 rows x 2 columns]"
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "frame_with_labels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#min max\n",
    "lst = []\n",
    "for i in range(0,100):\n",
    "    lst.append([i])\n",
    "\n",
    "\n",
    "\n",
    "Z = np.zeros([99,4])\n",
    "A = np.arange(0,100)\n",
    "sz = np.ones(100)\n",
    "cnt = 0\n",
    "def min_max_rec():\n",
    "    tlst=[]\n",
    "    global Z\n",
    "    global cnt\n",
    "    global A\n",
    "    global sz\n",
    "    for i in range(0,len(lst)):\n",
    "        for j in range(i+1,len(lst)):\n",
    "            tem1=lst[i]\n",
    "            tem2=lst[j]\n",
    "            tem3=[]\n",
    "            for item1 in range(0,len(tem1)):\n",
    "                for item2 in range(0,len(tem2)):\n",
    "                    tem3.append(distance_matrix[tem1[item1]][tem2[item2]])\n",
    "            tem3.sort()\n",
    "            avg=(tem3[0]+tem3[len(tem3)-1])/2\n",
    "            tlst.append((avg,i,j))\n",
    "    tlst.sort()\n",
    "    new_cluster=[]\n",
    "    frst_clus=tlst[0][1]\n",
    "    scnd_clus=tlst[0][2]\n",
    "    Z[cnt,0]=A[frst_clus]\n",
    "    Z[cnt,1]=A[scnd_clus]\n",
    "    Z[cnt,2]=tlst[0][0]\n",
    "    Z[cnt,3]=sz[frst_clus]+sz[scnd_clus]\n",
    "    new_cluster=lst[frst_clus]+lst[scnd_clus]\n",
    "    lst.pop(scnd_clus)\n",
    "    lst[frst_clus]=new_cluster\n",
    "    \n",
    "    #lst.append(new_cluster)\n",
    "    \n",
    "    print(lst)\n",
    "    A[frst_clus] = cnt + 100\n",
    "    A = np.delete(A,[scnd_clus],axis=0)\n",
    "    sz[frst_clus] = sz[frst_clus] + sz[scnd_clus]\n",
    "    sz = np.delete(sz,[scnd_clus],axis=0)\n",
    "    cnt+=1\n",
    "    if len(lst)==1:\n",
    "        return;\n",
    "    min_max_rec()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[0], [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15, 44], [16], [17], [18], [19], [20], [21], [22], [23], [24], [25], [26], [27], [28], [29], [30], [31], [32], [33], [34], [35], [36], [37], [38], [39], [40], [41], [42], [43], [45], [46], [47], [48], [49], [50], [51], [52], [53], [54], [55], [56], [57], [58], [59], [60], [61], [62], [63], [64], [65], [66], [67], [68], [69], [70], [71], [72], [73], [74], [75], [76], [77], [78], [79], [80], [81], [82], [83], [84], [85], [86], [87], [88], [89], [90], [91], [92], [93], [94], [95], [96], [97], [98], [99]]\n",
      "[[0], [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15, 44], [16], [17], [18], [19], [20], [21], [22], [23], [24], [25], [26], [27], [28], [29], [30], [31], [32], [33], [34], [35], [36], [37], [38], [39], [40], [41], [42], [43], [45], [46], [47], [48], [49], [50], [51], [52], [53], [54], [55], [56], [57], [58], [59], [60], [61], [62], [63], [64], [65, 94], [66], [67], [68], [69], [70], [71], [72], [73], [74], [75], [76], [77], [78], [79], [80], [81], [82], [83], [84], [85], [86], [87], [88], [89], [90], [91], [92], [93], [95], [96], [97], [98], [99]]\n",
      "[[0], [1], [2], [3], [4], [5], [6], [7, 16], [8], [9], [10], [11], [12], [13], [14], [15, 44], [17], [18], [19], [20], [21], [22], [23], [24], [25], [26], [27], [28], [29], [30], [31], [32], [33], [34], [35], [36], [37], [38], [39], [40], [41], [42], [43], [45], [46], [47], [48], [49], [50], [51], [52], [53], [54], [55], [56], [57], [58], [59], [60], [61], [62], [63], [64], [65, 94], [66], [67], [68], [69], [70], [71], [72], [73], [74], [75], [76], [77], [78], [79], [80], [81], [82], [83], [84], [85], [86], [87], [88], [89], [90], [91], [92], [93], [95], [96], [97], [98], [99]]\n",
      "[[0], [1], [2], [3], [4], [5], [6], [7, 16], [8], [9], [10], [11], [12], [13], [14], [15, 44], [17], [18], [19], [20], [21], [22], [23], [24], [25], [26], [27], [28], [29], [30], [31], [32], [33], [34], [35], [36], [37], [38], [39], [40], [41], [42], [43], [45], [46], [47], [48], [49], [50], [51], [52], [53], [54], [55], [56], [57, 66], [58], [59], [60], [61], [62], [63], [64], [65, 94], [67], [68], [69], [70], [71], [72], [73], [74], [75], [76], [77], [78], [79], [80], [81], [82], [83], [84], [85], [86], [87], [88], [89], [90], [91], [92], [93], [95], [96], [97], [98], [99]]\n",
      "[[0], [1], [2], [3], [4], [5], [6], [7, 16], [8], [9], [10], [11], [12], [13], [14], [15, 44, 32], [17], [18], [19], [20], [21], [22], [23], [24], [25], [26], [27], [28], [29], [30], [31], [33], [34], [35], [36], [37], [38], [39], [40], [41], [42], [43], [45], [46], [47], [48], [49], [50], [51], [52], [53], [54], [55], [56], [57, 66], [58], [59], [60], [61], [62], [63], [64], [65, 94], [67], [68], [69], [70], [71], [72], [73], [74], [75], [76], [77], [78], [79], [80], [81], [82], [83], [84], [85], [86], [87], [88], [89], [90], [91], [92], [93], [95], [96], [97], [98], [99]]\n",
      "[[0], [1], [2], [3], [4], [5], [6], [7, 16], [8], [9], [10], [11], [12], [13], [14], [15, 44, 32], [17], [18], [19], [20], [21], [22], [23], [24], [25], [26], [27], [28], [29], [30], [31], [33], [34], [35], [36], [37], [38], [39], [40], [41], [42], [43], [45], [46], [47], [48], [49], [50], [51], [52], [53], [54], [55], [56], [57, 66], [58], [59], [60], [61], [62], [63], [64], [65, 94, 82], [67], [68], [69], [70], [71], [72], [73], [74], [75], [76], [77], [78], [79], [80], [81], [83], [84], [85], [86], [87], [88], [89], [90], [91], [92], [93], [95], [96], [97], [98], [99]]\n",
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      "[[0, 1, 9, 15, 44, 32, 17, 21, 27, 10, 35, 23, 33, 13, 28, 24, 38, 8, 29, 40, 22, 20, 11, 49, 2, 3, 4, 7, 16, 26, 34, 47, 19, 46, 39, 30, 6, 45, 42, 12, 36, 18, 31, 43, 5, 37, 48, 25, 14], [41], [50, 51, 59, 65, 94, 82, 67, 71, 77, 60, 85, 73, 83, 63, 78, 74, 88, 58, 79, 90, 72, 70, 61, 99, 52, 53, 54, 57, 66, 76, 84, 97, 69, 96, 89, 80, 56, 95, 92, 62, 86, 68, 81, 93, 55, 87, 98, 75, 64], [91]]\n",
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      "[[0, 1, 9, 15, 44, 32, 17, 21, 27, 10, 35, 23, 33, 13, 28, 24, 38, 8, 29, 40, 22, 20, 11, 49, 2, 3, 4, 7, 16, 26, 34, 47, 19, 46, 39, 30, 6, 45, 42, 12, 36, 18, 31, 43, 5, 37, 48, 25, 14, 41], [50, 51, 59, 65, 94, 82, 67, 71, 77, 60, 85, 73, 83, 63, 78, 74, 88, 58, 79, 90, 72, 70, 61, 99, 52, 53, 54, 57, 66, 76, 84, 97, 69, 96, 89, 80, 56, 95, 92, 62, 86, 68, 81, 93, 55, 87, 98, 75, 64, 91]]\n",
      "[[0, 1, 9, 15, 44, 32, 17, 21, 27, 10, 35, 23, 33, 13, 28, 24, 38, 8, 29, 40, 22, 20, 11, 49, 2, 3, 4, 7, 16, 26, 34, 47, 19, 46, 39, 30, 6, 45, 42, 12, 36, 18, 31, 43, 5, 37, 48, 25, 14, 41, 50, 51, 59, 65, 94, 82, 67, 71, 77, 60, 85, 73, 83, 63, 78, 74, 88, 58, 79, 90, 72, 70, 61, 99, 52, 53, 54, 57, 66, 76, 84, 97, 69, 96, 89, 80, 56, 95, 92, 62, 86, 68, 81, 93, 55, 87, 98, 75, 64, 91]]\n"
     ]
    }
   ],
   "source": [
    "min_max_rec()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "for i in range(0,Z.shape[0]):\n",
    "    Z[i,2] = 1 - Z[i,2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "mn=Z[0,2]\n",
    "for i in range(0,Z.shape[0]):\n",
    "    if(Z[i,2]<mn):\n",
    "        mn=Z[i,2]\n",
    "mn=abs(mn)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "for i in range(0,Z.shape[0]):\n",
    "    Z[i,2]=Z[i,2]+mn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 15.        ,  44.        ,   1.56485262,   2.        ],\n",
       "       [ 65.        ,  94.        ,   1.56485262,   2.        ],\n",
       "       [  7.        ,  16.        ,   1.55691107,   2.        ],\n",
       "       [ 57.        ,  66.        ,   1.55691107,   2.        ],\n",
       "       [100.        ,  32.        ,   1.55409706,   3.        ],\n",
       "       [101.        ,  82.        ,   1.55409706,   3.        ],\n",
       "       [104.        ,  17.        ,   1.55293135,   4.        ],\n",
       "       [105.        ,  67.        ,   1.55293135,   4.        ],\n",
       "       [106.        ,  21.        ,   1.55161357,   5.        ],\n",
       "       [107.        ,  71.        ,   1.55161357,   5.        ],\n",
       "       [  9.        , 108.        ,   1.54974923,   6.        ],\n",
       "       [ 59.        , 109.        ,   1.54974923,   6.        ],\n",
       "       [  1.        , 110.        ,   1.54957016,   7.        ],\n",
       "       [ 51.        , 111.        ,   1.54957016,   7.        ],\n",
       "       [112.        ,  27.        ,   1.54914151,   8.        ],\n",
       "       [113.        ,  77.        ,   1.54914151,   8.        ],\n",
       "       [114.        ,  10.        ,   1.54911442,   9.        ],\n",
       "       [115.        ,  60.        ,   1.54911442,   9.        ],\n",
       "       [116.        ,  35.        ,   1.54823279,  10.        ],\n",
       "       [117.        ,  85.        ,   1.54823279,  10.        ],\n",
       "       [102.        ,  26.        ,   1.54793806,   3.        ],\n",
       "       [103.        ,  76.        ,   1.54793806,   3.        ],\n",
       "       [118.        ,  23.        ,   1.54687515,  11.        ],\n",
       "       [119.        ,  73.        ,   1.54687515,  11.        ],\n",
       "       [  0.        , 122.        ,   1.54602476,  12.        ],\n",
       "       [ 50.        , 123.        ,   1.54602476,  12.        ],\n",
       "       [124.        ,  33.        ,   1.54586148,  13.        ],\n",
       "       [125.        ,  83.        ,   1.54586148,  13.        ],\n",
       "       [126.        ,  13.        ,   1.54584695,  14.        ],\n",
       "       [127.        ,  63.        ,   1.54584695,  14.        ],\n",
       "       [128.        ,  28.        ,   1.54555322,  15.        ],\n",
       "       [129.        ,  78.        ,   1.54555322,  15.        ],\n",
       "       [120.        ,  34.        ,   1.54544501,   4.        ],\n",
       "       [121.        ,  84.        ,   1.54544501,   4.        ],\n",
       "       [132.        ,  47.        ,   1.54450583,   5.        ],\n",
       "       [133.        ,  97.        ,   1.54450583,   5.        ],\n",
       "       [130.        ,  24.        ,   1.54406356,  16.        ],\n",
       "       [131.        ,  74.        ,   1.54406356,  16.        ],\n",
       "       [136.        ,  38.        ,   1.54386801,  17.        ],\n",
       "       [137.        ,  88.        ,   1.54386801,  17.        ],\n",
       "       [134.        ,  19.        ,   1.54348656,   6.        ],\n",
       "       [135.        ,  69.        ,   1.54348656,   6.        ],\n",
       "       [138.        ,   8.        ,   1.54308203,  18.        ],\n",
       "       [139.        ,  58.        ,   1.54308203,  18.        ],\n",
       "       [140.        ,  46.        ,   1.54270508,   7.        ],\n",
       "       [141.        ,  96.        ,   1.54270508,   7.        ],\n",
       "       [144.        ,  39.        ,   1.54265548,   8.        ],\n",
       "       [145.        ,  89.        ,   1.54265548,   8.        ],\n",
       "       [142.        ,  29.        ,   1.54263785,  19.        ],\n",
       "       [143.        ,  79.        ,   1.54263785,  19.        ],\n",
       "       [146.        ,  30.        ,   1.542599  ,   9.        ],\n",
       "       [147.        ,  80.        ,   1.542599  ,   9.        ],\n",
       "       [  4.        , 150.        ,   1.54248292,  10.        ],\n",
       "       [ 54.        , 151.        ,   1.54248292,  10.        ],\n",
       "       [148.        ,  40.        ,   1.5423559 ,  20.        ],\n",
       "       [149.        ,  90.        ,   1.5423559 ,  20.        ],\n",
       "       [152.        ,   6.        ,   1.54214833,  11.        ],\n",
       "       [153.        ,  56.        ,   1.54214833,  11.        ],\n",
       "       [  3.        , 156.        ,   1.54203081,  12.        ],\n",
       "       [ 53.        , 157.        ,   1.54203081,  12.        ],\n",
       "       [154.        ,  22.        ,   1.54200478,  21.        ],\n",
       "       [155.        ,  72.        ,   1.54200478,  21.        ],\n",
       "       [158.        ,  45.        ,   1.54160325,  13.        ],\n",
       "       [159.        ,  95.        ,   1.54160325,  13.        ],\n",
       "       [162.        ,  42.        ,   1.54132909,  14.        ],\n",
       "       [163.        ,  92.        ,   1.54132909,  14.        ],\n",
       "       [160.        ,  20.        ,   1.54121513,  22.        ],\n",
       "       [161.        ,  70.        ,   1.54121513,  22.        ],\n",
       "       [164.        ,  12.        ,   1.54092893,  15.        ],\n",
       "       [165.        ,  62.        ,   1.54092893,  15.        ],\n",
       "       [168.        ,  36.        ,   1.54063387,  16.        ],\n",
       "       [169.        ,  86.        ,   1.54063387,  16.        ],\n",
       "       [  2.        , 170.        ,   1.54060647,  17.        ],\n",
       "       [ 52.        , 171.        ,   1.54060647,  17.        ],\n",
       "       [166.        ,  11.        ,   1.54059065,  23.        ],\n",
       "       [167.        ,  61.        ,   1.54059065,  23.        ],\n",
       "       [172.        ,  18.        ,   1.53997803,  18.        ],\n",
       "       [173.        ,  68.        ,   1.53997803,  18.        ],\n",
       "       [176.        ,  31.        ,   1.53957597,  19.        ],\n",
       "       [177.        ,  81.        ,   1.53957597,  19.        ],\n",
       "       [178.        ,  43.        ,   1.53928076,  20.        ],\n",
       "       [179.        ,  93.        ,   1.53928076,  20.        ],\n",
       "       [180.        ,   5.        ,   1.53895401,  21.        ],\n",
       "       [181.        ,  55.        ,   1.53895401,  21.        ],\n",
       "       [182.        ,  37.        ,   1.53883053,  22.        ],\n",
       "       [183.        ,  87.        ,   1.53883053,  22.        ],\n",
       "       [184.        ,  48.        ,   1.53875999,  23.        ],\n",
       "       [185.        ,  98.        ,   1.53875999,  23.        ],\n",
       "       [186.        ,  25.        ,   1.53785746,  24.        ],\n",
       "       [187.        ,  75.        ,   1.53785746,  24.        ],\n",
       "       [174.        ,  49.        ,   1.53731032,  24.        ],\n",
       "       [175.        ,  99.        ,   1.53731032,  24.        ],\n",
       "       [188.        ,  14.        ,   1.53578138,  25.        ],\n",
       "       [189.        ,  64.        ,   1.53578138,  25.        ],\n",
       "       [190.        , 192.        ,   1.53493008,  49.        ],\n",
       "       [191.        , 193.        ,   1.53493008,  49.        ],\n",
       "       [194.        ,  41.        ,   1.53463553,  50.        ],\n",
       "       [195.        ,  91.        ,   1.53463553,  50.        ],\n",
       "       [196.        , 197.        ,   1.04323508, 100.        ]])"
      ]
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Z"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from matplotlib import pyplot as plt\n",
    "from scipy.cluster.hierarchy import dendrogram, linkage"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([15.        , 44.        ,  1.56485262,  2.        ])"
      ]
     },
     "execution_count": 107,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Z[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<Figure size 2736x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(38,10))\n",
    "plt.title('Hierarchical Clustering Dendrogram')\n",
    "plt.xlabel('sample index')\n",
    "plt.ylabel('distance')\n",
    "dendrogram(\n",
    "    Z,\n",
    "    leaf_rotation=90.,  # rotates the x axis labels\n",
    "    leaf_font_size=8.,  # font size for the x axis labels\n",
    "    orientation='top',\n",
    ")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#min max with outer boundary 1.25 radius\n",
    "lst = []\n",
    "for i in range(0,100):\n",
    "    lst.append([i])\n",
    "\n",
    "\n",
    "\n",
    "Z = np.zeros([99,4])\n",
    "A = np.arange(0,100)\n",
    "sz = np.ones(100)\n",
    "cnt = 0\n",
    "def min_max_rec_1():\n",
    "    tlst=[]\n",
    "    global Z\n",
    "    global cnt\n",
    "    global A\n",
    "    global sz\n",
    "    for i in range(0,len(lst)):\n",
    "        for j in range(i+1,len(lst)):\n",
    "            \n",
    "            tem1=lst[i]\n",
    "            tem2=lst[j]\n",
    "            \n",
    "            temp1=[]\n",
    "            if len(tem1)>=3:\n",
    "                sm1=np.zeros(100);\n",
    "                for ii in tem1:\n",
    "                    sm1=sm1+Y[ii]    \n",
    "                sm1=sm1/len(tem1)\n",
    "                rad1=0\n",
    "                dis1=[]\n",
    "                for ii in tem1:\n",
    "                    dis1.append(sum((Y[ii]-sm1)*(Y[ii]-sm1)))\n",
    "                    rad1=rad1+dis1[len(dis1)-1]                \n",
    "                rad1=rad1/len(tem1)\n",
    "                for ii in range(0,len(tem1)):\n",
    "                    if dis1[ii] > 1.25*rad1:\n",
    "                        temp1.append(tem1[ii])\n",
    "            else:\n",
    "                temp1=tem1\n",
    "                    \n",
    "            temp2=[]\n",
    "            if len(tem2)>=3:\n",
    "                sm2=np.zeros(100);\n",
    "                for ii in tem2:\n",
    "                    sm2=sm2+Y[ii]    \n",
    "                sm2=sm2/len(tem2)\n",
    "                rad2=0\n",
    "                dis2=[]\n",
    "                for ii in tem2:\n",
    "                    dis2.append(sum((Y[ii]-sm2)*(Y[ii]-sm2)))\n",
    "                    rad2=rad2+dis2[len(dis2)-1]                \n",
    "                rad2=rad2/len(tem2)\n",
    "                for ii in range(0,len(tem2)):\n",
    "                    if dis2[ii] > 1.25*rad2:\n",
    "                        temp2.append(tem2[ii])\n",
    "            else:\n",
    "                temp2=tem2\n",
    "                \n",
    "            \n",
    "            tem3=[]\n",
    "            for item1 in range(0,len(temp1)):\n",
    "                for item2 in range(0,len(temp2)):\n",
    "                    tem3.append(distance_matrix[temp1[item1]][temp2[item2]])\n",
    "            tem3.sort()\n",
    "            avg=(tem3[0]+tem3[len(tem3)-1])/2\n",
    "            tlst.append((avg,i,j))\n",
    "            \n",
    "    tlst.sort()\n",
    "    new_cluster=[]\n",
    "    frst_clus=tlst[0][1]\n",
    "    scnd_clus=tlst[0][2]\n",
    "    Z[cnt,0]=A[frst_clus]\n",
    "    Z[cnt,1]=A[scnd_clus]\n",
    "    Z[cnt,2]=tlst[0][0]\n",
    "    Z[cnt,3]=sz[frst_clus]+sz[scnd_clus]\n",
    "    new_cluster=lst[frst_clus]+lst[scnd_clus]\n",
    "    lst.pop(scnd_clus)\n",
    "    lst[frst_clus]=new_cluster\n",
    "    \n",
    "    #lst.append(new_cluster)\n",
    "    \n",
    "    print(lst)\n",
    "    A[frst_clus] = cnt + 100\n",
    "    A = np.delete(A,[scnd_clus],axis=0)\n",
    "    sz[frst_clus] = sz[frst_clus] + sz[scnd_clus]\n",
    "    sz = np.delete(sz,[scnd_clus],axis=0)\n",
    "    cnt+=1\n",
    "    if len(lst)==1:\n",
    "        return;\n",
    "    min_max_rec_1()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[0], [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15, 44], [16], [17], [18], [19], [20], [21], [22], [23], [24], [25], [26], [27], [28], [29], [30], [31], [32], [33], [34], [35], [36], [37], [38], [39], [40], [41], [42], [43], [45], [46], [47], [48], [49], [50], [51], [52], [53], [54], [55], [56], [57], [58], [59], [60], [61], [62], [63], [64], [65], [66], [67], [68], [69], [70], [71], [72], [73], [74], [75], [76], [77], [78], [79], [80], [81], [82], [83], [84], [85], [86], [87], [88], [89], [90], [91], [92], [93], [94], [95], [96], [97], [98], [99]]\n",
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      "[[0, 2, 5, 7, 16, 14, 15, 44, 32, 41, 91, 64, 49, 99, 25, 75, 37, 87, 55, 43, 93, 48, 98, 18, 68, 31, 81, 20, 70, 11, 61, 52, 12, 62, 86, 8, 58, 42, 92, 3, 53, 19, 69, 29, 79, 6, 56, 40, 90, 30, 80, 4, 54, 45, 95, 67, 71], [1, 17, 24, 36, 65, 94, 82, 57, 66, 50, 47, 97, 74, 22, 72, 46, 96, 21, 39, 89, 23, 73, 51, 33, 83, 38, 88, 27, 77, 9, 35, 85, 13, 63], [10], [26], [28], [34], [59], [60], [76], [78], [84]]\n",
      "[[0, 2, 5, 7, 16, 14, 15, 44, 32, 41, 91, 64, 49, 99, 25, 75, 37, 87, 55, 43, 93, 48, 98, 18, 68, 31, 81, 20, 70, 11, 61, 52, 12, 62, 86, 8, 58, 42, 92, 3, 53, 19, 69, 29, 79, 6, 56, 40, 90, 30, 80, 4, 54, 45, 95, 67, 71, 59], [1, 17, 24, 36, 65, 94, 82, 57, 66, 50, 47, 97, 74, 22, 72, 46, 96, 21, 39, 89, 23, 73, 51, 33, 83, 38, 88, 27, 77, 9, 35, 85, 13, 63], [10], [26], [28], [34], [60], [76], [78], [84]]\n",
      "[[0, 2, 5, 7, 16, 14, 15, 44, 32, 41, 91, 64, 49, 99, 25, 75, 37, 87, 55, 43, 93, 48, 98, 18, 68, 31, 81, 20, 70, 11, 61, 52, 12, 62, 86, 8, 58, 42, 92, 3, 53, 19, 69, 29, 79, 6, 56, 40, 90, 30, 80, 4, 54, 45, 95, 67, 71, 59], [1, 17, 24, 36, 65, 94, 82, 57, 66, 50, 47, 97, 74, 22, 72, 46, 96, 21, 39, 89, 23, 73, 51, 33, 83, 38, 88, 27, 77, 9, 35, 85, 13, 63, 26], [10], [28], [34], [60], [76], [78], [84]]\n",
      "[[0, 2, 5, 7, 16, 14, 15, 44, 32, 41, 91, 64, 49, 99, 25, 75, 37, 87, 55, 43, 93, 48, 98, 18, 68, 31, 81, 20, 70, 11, 61, 52, 12, 62, 86, 8, 58, 42, 92, 3, 53, 19, 69, 29, 79, 6, 56, 40, 90, 30, 80, 4, 54, 45, 95, 67, 71, 59], [1, 17, 24, 36, 65, 94, 82, 57, 66, 50, 47, 97, 74, 22, 72, 46, 96, 21, 39, 89, 23, 73, 51, 33, 83, 38, 88, 27, 77, 9, 35, 85, 13, 63, 26, 76], [10], [28], [34], [60], [78], [84]]\n",
      "[[0, 2, 5, 7, 16, 14, 15, 44, 32, 41, 91, 64, 49, 99, 25, 75, 37, 87, 55, 43, 93, 48, 98, 18, 68, 31, 81, 20, 70, 11, 61, 52, 12, 62, 86, 8, 58, 42, 92, 3, 53, 19, 69, 29, 79, 6, 56, 40, 90, 30, 80, 4, 54, 45, 95, 67, 71, 59], [1, 17, 24, 36, 65, 94, 82, 57, 66, 50, 47, 97, 74, 22, 72, 46, 96, 21, 39, 89, 23, 73, 51, 33, 83, 38, 88, 27, 77, 9, 35, 85, 13, 63, 26, 76, 34], [10], [28], [60], [78], [84]]\n",
      "[[0, 2, 5, 7, 16, 14, 15, 44, 32, 41, 91, 64, 49, 99, 25, 75, 37, 87, 55, 43, 93, 48, 98, 18, 68, 31, 81, 20, 70, 11, 61, 52, 12, 62, 86, 8, 58, 42, 92, 3, 53, 19, 69, 29, 79, 6, 56, 40, 90, 30, 80, 4, 54, 45, 95, 67, 71, 59], [1, 17, 24, 36, 65, 94, 82, 57, 66, 50, 47, 97, 74, 22, 72, 46, 96, 21, 39, 89, 23, 73, 51, 33, 83, 38, 88, 27, 77, 9, 35, 85, 13, 63, 26, 76, 34, 84], [10], [28], [60], [78]]\n",
      "[[0, 2, 5, 7, 16, 14, 15, 44, 32, 41, 91, 64, 49, 99, 25, 75, 37, 87, 55, 43, 93, 48, 98, 18, 68, 31, 81, 20, 70, 11, 61, 52, 12, 62, 86, 8, 58, 42, 92, 3, 53, 19, 69, 29, 79, 6, 56, 40, 90, 30, 80, 4, 54, 45, 95, 67, 71, 59], [1, 17, 24, 36, 65, 94, 82, 57, 66, 50, 47, 97, 74, 22, 72, 46, 96, 21, 39, 89, 23, 73, 51, 33, 83, 38, 88, 27, 77, 9, 35, 85, 13, 63, 26, 76, 34, 84, 10], [28], [60], [78]]\n",
      "[[0, 2, 5, 7, 16, 14, 15, 44, 32, 41, 91, 64, 49, 99, 25, 75, 37, 87, 55, 43, 93, 48, 98, 18, 68, 31, 81, 20, 70, 11, 61, 52, 12, 62, 86, 8, 58, 42, 92, 3, 53, 19, 69, 29, 79, 6, 56, 40, 90, 30, 80, 4, 54, 45, 95, 67, 71, 59], [1, 17, 24, 36, 65, 94, 82, 57, 66, 50, 47, 97, 74, 22, 72, 46, 96, 21, 39, 89, 23, 73, 51, 33, 83, 38, 88, 27, 77, 9, 35, 85, 13, 63, 26, 76, 34, 84, 10, 28], [60], [78]]\n",
      "[[0, 2, 5, 7, 16, 14, 15, 44, 32, 41, 91, 64, 49, 99, 25, 75, 37, 87, 55, 43, 93, 48, 98, 18, 68, 31, 81, 20, 70, 11, 61, 52, 12, 62, 86, 8, 58, 42, 92, 3, 53, 19, 69, 29, 79, 6, 56, 40, 90, 30, 80, 4, 54, 45, 95, 67, 71, 59], [1, 17, 24, 36, 65, 94, 82, 57, 66, 50, 47, 97, 74, 22, 72, 46, 96, 21, 39, 89, 23, 73, 51, 33, 83, 38, 88, 27, 77, 9, 35, 85, 13, 63, 26, 76, 34, 84, 10, 28, 78], [60]]\n",
      "[[0, 2, 5, 7, 16, 14, 15, 44, 32, 41, 91, 64, 49, 99, 25, 75, 37, 87, 55, 43, 93, 48, 98, 18, 68, 31, 81, 20, 70, 11, 61, 52, 12, 62, 86, 8, 58, 42, 92, 3, 53, 19, 69, 29, 79, 6, 56, 40, 90, 30, 80, 4, 54, 45, 95, 67, 71, 59, 60], [1, 17, 24, 36, 65, 94, 82, 57, 66, 50, 47, 97, 74, 22, 72, 46, 96, 21, 39, 89, 23, 73, 51, 33, 83, 38, 88, 27, 77, 9, 35, 85, 13, 63, 26, 76, 34, 84, 10, 28, 78]]\n",
      "[[0, 2, 5, 7, 16, 14, 15, 44, 32, 41, 91, 64, 49, 99, 25, 75, 37, 87, 55, 43, 93, 48, 98, 18, 68, 31, 81, 20, 70, 11, 61, 52, 12, 62, 86, 8, 58, 42, 92, 3, 53, 19, 69, 29, 79, 6, 56, 40, 90, 30, 80, 4, 54, 45, 95, 67, 71, 59, 60, 1, 17, 24, 36, 65, 94, 82, 57, 66, 50, 47, 97, 74, 22, 72, 46, 96, 21, 39, 89, 23, 73, 51, 33, 83, 38, 88, 27, 77, 9, 35, 85, 13, 63, 26, 76, 34, 84, 10, 28, 78]]\n"
     ]
    }
   ],
   "source": [
    "min_max_rec_1()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "for i in range(0,Z.shape[0]):\n",
    "    Z[i,2] = 1 - Z[i,2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "mn=Z[0,2]\n",
    "for i in range(0,Z.shape[0]):\n",
    "    if(Z[i,2]<mn):\n",
    "        mn=Z[i,2]\n",
    "mn=abs(mn)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "for i in range(0,Z.shape[0]):\n",
    "    Z[i,2]=Z[i,2]+mn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<Figure size 2736x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(38,10))\n",
    "plt.title('Hierarchical Clustering Dendrogram')\n",
    "plt.xlabel('sample index')\n",
    "plt.ylabel('distance')\n",
    "dendrogram(\n",
    "    Z,\n",
    "    leaf_rotation=90.,  # rotates the x axis labels\n",
    "    leaf_font_size=8.,  # font size for the x axis labels\n",
    "    orientation='top',\n",
    ")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
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