safaribooks_online.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pyspark import SparkConf, SparkContext\n",
    "import collections\n",
    "\n",
    "conf = SparkConf().setMaster('local').setAppName('RatingsHistogram')\n",
    "sc = SparkContext(conf = conf)\n",
    "\n",
    "lines = sc.textFile('u.data')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['196\\t242\\t3\\t881250949', '186\\t302\\t3\\t891717742', '22\\t377\\t1\\t878887116']"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lines.take(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "ratings = lines.map(lambda x: x.split()[2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['3', '3', '1', '2', '1', '4']"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ratings.take(6)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "results = ratings.countByValue()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "defaultdict(int, {'1': 6110, '2': 11370, '3': 27145, '4': 34174, '5': 21201})"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1 6110\n",
      "2 11370\n",
      "3 27145\n",
      "4 34174\n",
      "5 21201\n"
     ]
    }
   ],
   "source": [
    "sortedResults = collections.OrderedDict(sorted(results.items()))\n",
    "for key, value in sortedResults.items():\n",
    "    print('%s %i' % (key, value))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "sc.stop()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pyspark import SparkConf, SparkContext\n",
    "\n",
    "conf = SparkConf().setMaster('local').setAppName('FriendsByAge')\n",
    "sc = SparkContext(conf = conf)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "def parseLine(line):\n",
    "    fields = line.split(',')\n",
    "    age = int(fields[2])\n",
    "    numFriends = int(fields[3])\n",
    "    \n",
    "    return (age, numFriends)\n",
    "\n",
    "lines = sc.textFile('fakefriends.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['0,Will,33,385', '1,Jean-Luc,26,2', '2,Hugh,55,221']"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lines.take(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(33, 385), (26, 2), (55, 221)]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rdd = lines.map(parseLine)\n",
    "rdd.take(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(33, (3904, 12)), (26, (4115, 17)), (55, (3842, 13))]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "totalsByAge = rdd.mapValues(lambda x: (x, 1)).reduceByKey(lambda x, y: (x[0] + y[0], x[1] + y[1]))\n",
    "totalsByAge.take(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(33, 325.3333333333333), (26, 242.05882352941177), (55, 295.53846153846155)]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "averagesByAge = totalsByAge.mapValues(lambda x: (x[0] / x[1]))\n",
    "averagesByAge.take(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(33, 325.3333333333333)\n",
      "(26, 242.05882352941177)\n",
      "(55, 295.53846153846155)\n",
      "(40, 250.8235294117647)\n",
      "(68, 269.6)\n",
      "(59, 220.0)\n",
      "(37, 249.33333333333334)\n",
      "(54, 278.0769230769231)\n",
      "(38, 193.53333333333333)\n",
      "(27, 228.125)\n",
      "(53, 222.85714285714286)\n",
      "(57, 258.8333333333333)\n",
      "(56, 306.6666666666667)\n",
      "(43, 230.57142857142858)\n",
      "(36, 246.6)\n",
      "(22, 206.42857142857142)\n",
      "(35, 211.625)\n",
      "(45, 309.53846153846155)\n",
      "(60, 202.71428571428572)\n",
      "(67, 214.625)\n",
      "(19, 213.27272727272728)\n",
      "(30, 235.8181818181818)\n",
      "(51, 302.14285714285717)\n",
      "(25, 197.45454545454547)\n",
      "(21, 350.875)\n",
      "(42, 303.5)\n",
      "(49, 184.66666666666666)\n",
      "(48, 281.4)\n",
      "(50, 254.6)\n",
      "(39, 169.28571428571428)\n",
      "(32, 207.9090909090909)\n",
      "(58, 116.54545454545455)\n",
      "(64, 281.3333333333333)\n",
      "(31, 267.25)\n",
      "(52, 340.6363636363636)\n",
      "(24, 233.8)\n",
      "(20, 165.0)\n",
      "(62, 220.76923076923077)\n",
      "(41, 268.55555555555554)\n",
      "(44, 282.1666666666667)\n",
      "(69, 235.2)\n",
      "(65, 298.2)\n",
      "(61, 256.22222222222223)\n",
      "(28, 209.1)\n",
      "(66, 276.44444444444446)\n",
      "(46, 223.69230769230768)\n",
      "(29, 215.91666666666666)\n",
      "(18, 343.375)\n",
      "(47, 233.22222222222223)\n",
      "(34, 245.5)\n",
      "(63, 384.0)\n",
      "(23, 246.3)\n"
     ]
    }
   ],
   "source": [
    "results = averagesByAge.collect()\n",
    "for result in results:\n",
    "    print(result)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "sc.stop()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['ITE00100554,18000101,TMAX,-75,,,E,',\n",
       " 'ITE00100554,18000101,TMIN,-148,,,E,',\n",
       " 'GM000010962,18000101,PRCP,0,,,E,']"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from pyspark import SparkConf, SparkContext\n",
    "\n",
    "conf = SparkConf().setMaster('local').setAppName('minTemperatures')\n",
    "sc = SparkContext(conf = conf)\n",
    "\n",
    "def parseLine(line):\n",
    "    fields = line.split(',')\n",
    "    stationID = fields[0]\n",
    "    entryType = fields[2]\n",
    "    temperature = float(fields[3]) * 0.1 * (9.0/5.0) + 32.0\n",
    "    return (stationID, entryType, temperature)\n",
    "\n",
    "lines = sc.textFile('1800.csv')\n",
    "lines.take(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('ITE00100554', 'TMAX', 18.5),\n",
       " ('ITE00100554', 'TMIN', 5.359999999999999),\n",
       " ('GM000010962', 'PRCP', 32.0)]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "parsedLines = lines.map(parseLine)\n",
    "parsedLines.take(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('ITE00100554', 'TMIN', 5.359999999999999),\n",
       " ('EZE00100082', 'TMIN', 7.699999999999999),\n",
       " ('ITE00100554', 'TMIN', 9.5)]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "minTemps = parsedLines.filter(lambda x: 'TMIN' in x[1])\n",
    "minTemps.take(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('ITE00100554', 5.359999999999999),\n",
       " ('EZE00100082', 7.699999999999999),\n",
       " ('ITE00100554', 9.5)]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stationTemps = minTemps.map(lambda x: (x[0], x[2]))\n",
    "stationTemps.take(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "730"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stationTemps.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('ITE00100554', 5.359999999999999), ('EZE00100082', 7.699999999999999)]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "minTemps = stationTemps.reduceByKey(lambda x, y: min(x, y))\n",
    "minTemps.collect()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ITE00100554\t5.36F\n",
      "EZE00100082\t7.70F\n"
     ]
    }
   ],
   "source": [
    "results = minTemps.collect()\n",
    "for result in results: \n",
    "    print(result[0] + '\\t{:.2f}F'.format(result[1]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "sc.stop()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pyspark import SparkConf, SparkContext\n",
    "\n",
    "conf = SparkConf().setMaster('local').setAppName('maxTemperatures')\n",
    "sc = SparkContext(conf = conf)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['ITE00100554,18000101,TMAX,-75,,,E,',\n",
       " 'ITE00100554,18000101,TMIN,-148,,,E,',\n",
       " 'GM000010962,18000101,PRCP,0,,,E,']"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def parseLine(line):\n",
    "    fields = line.split(',')\n",
    "    stationID = fields[0]\n",
    "    entryType = fields[2]\n",
    "    temperature = float(fields[3]) * 0.1 * (9.0/5.0) + 32\n",
    "    \n",
    "    return (stationID, entryType, temperature)\n",
    "lines = sc.textFile('1800.csv')\n",
    "lines.take(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('ITE00100554', 'TMAX', 18.5),\n",
       " ('ITE00100554', 'TMIN', 5.359999999999999),\n",
       " ('GM000010962', 'PRCP', 32.0)]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "parsedLines = lines.map(parseLine)\n",
    "parsedLines.take(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('ITE00100554', 'TMAX', 18.5),\n",
       " ('EZE00100082', 'TMAX', 16.52),\n",
       " ('ITE00100554', 'TMAX', 21.2)]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "maxTemps = parsedLines.filter(lambda x: 'TMAX' in x[1])\n",
    "maxTemps.take(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('ITE00100554', 18.5), ('EZE00100082', 16.52), ('ITE00100554', 21.2)]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stationTemps = maxTemps.map(lambda x: (x[0], x[2]))\n",
    "stationTemps.take(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('ITE00100554', 90.14000000000001), ('EZE00100082', 90.14000000000001)]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "maxTemps = stationTemps.reduceByKey(lambda x, y: max(x, y))\n",
    "maxTemps.take(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ITE00100554\t90.14F\n",
      "EZE00100082\t90.14F\n"
     ]
    }
   ],
   "source": [
    "results = maxTemps.collect()\n",
    "for result in results:\n",
    "    print(result[0] + '\\t{:.2f}F'.format(result[1]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "sc.stop()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['The quick red fox jumped over the lazy brown dogs']"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from pyspark import SparkConf, SparkContext\n",
    "conf = SparkConf().setMaster('local').setAppName('RedFox')\n",
    "sc = SparkContext(conf = conf)\n",
    "\n",
    "lines = sc.textFile('redfox.txt')\n",
    "lines.collect()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['THE QUICK RED FOX JUMPED OVER THE LAZY BROWN DOGS']"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rageCaps = lines.map(lambda x: x.upper())\n",
    "rageCaps.collect()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['The',\n",
       " 'quick',\n",
       " 'red',\n",
       " 'fox',\n",
       " 'jumped',\n",
       " 'over',\n",
       " 'the',\n",
       " 'lazy',\n",
       " 'brown',\n",
       " 'dogs']"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "words = lines.flatMap(lambda x: x.split())\n",
    "words.collect()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "sc.stop()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pyspark import SparkConf, SparkContext\n",
    "conf = SparkConf().setMaster('local').setAppName('WordCount')\n",
    "sc = SparkContext(conf = conf)\n",
    "\n",
    "input = sc.textFile('book.txt')\n",
    "words = input.flatMap(lambda x: x.split())\n",
    "wordCounts = words.countByValue()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Self-Employment: 1\n",
      "Building 5\n",
      "an 172\n",
      "Internet 13\n",
      "Business 19\n",
      "of 941\n",
      "One 12\n",
      "Achieving 1\n",
      "Financial 3\n",
      "and 901\n",
      "Personal 3\n",
      "Freedom 7\n",
      "through 55\n",
      "a 1148\n",
      "Lifestyle 5\n",
      "Technology 2\n",
      "By 9\n",
      "Frank 10\n",
      "Kane 7\n",
      "Copyright 1\n",
      "2015 3\n",
      "Kane. 1\n",
      "All 13\n",
      "rights 3\n",
      "reserved 2\n",
      "worldwide. 2\n",
      "CONTENTS 1\n",
      "Disclaimer 1\n",
      "Preface 1\n",
      "Part 2\n",
      "I: 2\n",
      "Making 5\n",
      "the 1176\n",
      "Big 1\n",
      "Decision 1\n",
      "Overcoming 1\n",
      "Inertia 1\n",
      "Fear 1\n",
      "Failure 1\n",
      "Career 1\n",
      "Indoctrination 2\n",
      "The 88\n",
      "Carrot 1\n",
      "on 399\n",
      "Stick 2\n",
      "Ego 1\n",
      "Protection 1\n",
      "Your 62\n",
      "Employer 2\n",
      "as 297\n",
      "Security 2\n",
      "Blanket 1\n",
      "Why 3\n",
      "it�s 28\n",
      "Worth 1\n",
      "it 311\n",
      "Unlimited 2\n",
      "Growth 4\n",
      "Potential 1\n",
      "Investing 3\n",
      "in 552\n",
      "Yourself, 1\n",
      "Not 7\n",
      "Someone 2\n",
      "Else 1\n",
      "No 14\n",
      "Dependencies 1\n",
      "Commute 1\n",
      "to 1789\n",
      "Live 3\n",
      "Where 2\n",
      "You 144\n",
      "Want 5\n",
      "Work 4\n",
      "When 31\n",
      "How 29\n",
      "Is 17\n",
      "Self-Employment 1\n",
      "for 500\n",
      "You? 1\n",
      "Flowchart: 1\n",
      "Should 3\n",
      "I 322\n",
      "Even 35\n",
      "Consider 5\n",
      "Self-Employment? 2\n",
      "Having 2\n",
      "Safety 2\n",
      "Net 2\n",
      "Planning 3\n",
      "Health 2\n",
      "Care 2\n",
      "Self-Assessment 1\n",
      "Quiz 1\n",
      "PART 5\n",
      "II: 2\n",
      "Happen 1\n",
      "Designing 1\n",
      "Fallacy 1\n",
      "Introducing 1\n",
      "Ideal 1\n",
      "Case 1\n",
      "Study: 1\n",
      "Sundog 20\n",
      "Software 12\n",
      "Other 4\n",
      "Ideas 2\n",
      "Key 1\n",
      "Points 1\n",
      "Evaluating 1\n",
      "Idea 1\n",
      "Writing 4\n",
      "Plan 4\n",
      "Description 2\n",
      "Vision 2\n",
      "Definition 1\n",
      "Market 2\n",
      "Product 2\n",
      "Organization 1\n",
      "Management 2\n",
      "Marketing 5\n",
      "Sales 2\n",
      "Strategy 1\n",
      "your 1339\n",
      "Reality 1\n",
      "Check 4\n",
      "Employment 1\n",
      "Agreement 1\n",
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      "Obtaining 1\n",
      "Licenses 1\n",
      "Tax 2\n",
      "Launching 2\n",
      "Product, 1\n",
      "Measuring 1\n",
      "Results 1\n",
      "Risk 1\n",
      "Mitigation 1\n",
      "Don't 22\n",
      "Have 9\n",
      "Go 7\n",
      "It 42\n",
      "Alone 1\n",
      "Pulling 1\n",
      "Trigger 1\n",
      "Final 1\n",
      "Checklist 1\n",
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      "Boss 1\n",
      "III: 2\n",
      "Last 1\n",
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      "Fire 1\n",
      "Website 2\n",
      "Basics 5\n",
      "Public 1\n",
      "Relations 1\n",
      "Online 8\n",
      "Advertising 3\n",
      "Offline 1\n",
      "Search 6\n",
      "Engine 2\n",
      "Optimization 3\n",
      "Landing 4\n",
      "Page 2\n",
      "Importance 1\n",
      "Email 5\n",
      "Campaigns 1\n",
      "Using 5\n",
      "Social 2\n",
      "Networks 1\n",
      "Measure 1\n",
      "Act 2\n",
      "Interpreting 1\n",
      "Metrics 2\n",
      "Tracking 1\n",
      "Closing 1\n",
      "Avoiding 2\n",
      "Pitfalls 1\n",
      "Beware 5\n",
      "Leeches 1\n",
      "Well-Meaning 1\n",
      "Advice 1\n",
      "Hiring 3\n",
      "Salespeople 1\n",
      "Pressure 1\n",
      "Hire 1\n",
      "Misleading 1\n",
      "Statistics 4\n",
      "Finding 4\n",
      "Time 2\n",
      "People 4\n",
      "Compounding 1\n",
      "Effect 1\n",
      "Adapting 1\n",
      "New 6\n",
      "Life 2\n",
      "Survivor's 1\n",
      "Guilt 1\n",
      "Letting 1\n",
      "Fixed 1\n",
      "Schedules 1\n",
      "Little 1\n",
      "Recommended 1\n",
      "Reading 1\n",
      "Acknowledgments 1\n",
      "About 4\n",
      "Author 1\n",
      "DISCLAIMER 1\n",
      "What 38\n",
      "you 1267\n",
      "do 156\n",
      "with 292\n",
      "career 18\n",
      "is 531\n",
      "own 114\n",
      "decision. 1\n",
      "This 57\n",
      "book 31\n",
      "tells 4\n",
      "how 127\n",
      "improved 2\n",
      "my 199\n",
      "life 21\n",
      "by 109\n",
      "quitting 8\n",
      "job, 24\n",
      "creating 14\n",
      "sustainable 3\n",
      "growing 9\n",
      "income 17\n",
      "self-employment. 10\n",
      "learned 10\n",
      "along 10\n",
      "way 42\n",
      "could 44\n",
      "help 42\n",
      "same. 1\n",
      "But 38\n",
      "no 60\n",
      "matter 10\n",
      "much 78\n",
      "advice 34\n",
      "or 267\n",
      "many 63\n",
      "stories 3\n",
      "give 31\n",
      "you, 31\n",
      "end 39\n",
      "success 12\n",
      "relies 5\n",
      "preparation, 1\n",
      "planning, 2\n",
      "skillset, 1\n",
      "talents, 2\n",
      "determination, 1\n",
      "little 27\n",
      "bit 8\n",
      "luck. 1\n",
      "can't 22\n",
      "all 109\n",
      "that 641\n",
      "you. 53\n",
      "If 237\n",
      "this 208\n",
      "gives 5\n",
      "confidence 1\n",
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      "out 138\n",
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      "great. 2\n",
      "responsibly, 2\n",
      "realize 10\n",
      "failure 1\n",
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      "real 27\n",
      "possibility 3\n",
      "must 28\n",
      "plan 43\n",
      "for. 9\n",
      "blame 1\n",
      "me 26\n",
      "decisions 5\n",
      "make; 1\n",
      "they 192\n",
      "are 391\n",
      "ultimately 7\n",
      "own. 14\n",
      "Now, 4\n",
      "adventure. 1\n",
      "PREFACE 1\n",
      "Three 2\n",
      "years 23\n",
      "ago, 3\n",
      "worked 16\n",
      "big 36\n",
      "company. 11\n",
      "did 12\n",
      "everything 8\n",
      "good 67\n",
      "American 4\n",
      "employee 6\n",
      "supposed 4\n",
      "do. 15\n",
      "hard. 3\n",
      "devoted 1\n",
      "thoughts 2\n",
      "making 14\n",
      "company 83\n",
      "even 68\n",
      "more 187\n",
      "successful. 3\n",
      "commuted 1\n",
      "hour 12\n",
      "each 18\n",
      "way, 7\n",
      "without 39\n",
      "complaint. 1\n",
      "50 4\n",
      "hours 33\n",
      "every 28\n",
      "week 17\n",
      "at 189\n",
      "minimum. 3\n",
      "And 14\n",
      "when 69\n",
      "got 23\n",
      "home, 8\n",
      "let 17\n",
      "them 108\n",
      "page 30\n",
      "2 4\n",
      "AM 4\n",
      "if 174\n",
      "something 50\n",
      "needed 7\n",
      "attention 14\n",
      "which 36\n",
      "happened 3\n",
      "pretty 18\n",
      "often. 2\n",
      "Over 2\n",
      "years, 4\n",
      "was 84\n",
      "rewarded 1\n",
      "responsibility, 2\n",
      "money 62\n",
      "although 5\n",
      "never 26\n",
      "seemed 2\n",
      "be 347\n",
      "quite 5\n",
      "enough. 3\n",
      "considered 4\n",
      "role-model 1\n",
      "software 33\n",
      "development 15\n",
      "manager, 2\n",
      "felt 4\n",
      "At 24\n",
      "home 14\n",
      "however, 10\n",
      "marriage 1\n",
      "under 7\n",
      "stress, 1\n",
      "kids 5\n",
      "hardly 2\n",
      "knew 6\n",
      "me, 3\n",
      "prescription 2\n",
      "sleep 3\n",
      "aids 2\n",
      "order 31\n",
      "combat 1\n",
      "extreme 2\n",
      "stress 8\n",
      "under. 1\n",
      "My 16\n",
      "family 19\n",
      "wasn't 5\n",
      "happy 13\n",
      "living 17\n",
      "part 25\n",
      "country 4\n",
      "we 18\n",
      "lived 2\n",
      "in, 6\n",
      "weren't 1\n",
      "me. 5\n",
      "But, 12\n",
      "secondary 1\n",
      "duty 2\n",
      "employer, 6\n",
      "provider 2\n",
      "family. 3\n",
      "doing 38\n",
      "what 177\n",
      "thought 4\n",
      "had 23\n",
      "faced 4\n",
      "ultimatum 1\n",
      "from 161\n",
      "them. 35\n",
      "A 39\n",
      "few 38\n",
      "weeks 1\n",
      "later, 4\n",
      "quit 19\n",
      "job. 19\n",
      "walked 1\n",
      "away 12\n",
      "about 181\n",
      "million 6\n",
      "dollars� 1\n",
      "worth 32\n",
      "stock 7\n",
      "grants 2\n",
      "so, 24\n",
      "it. 62\n",
      "made 12\n",
      "decision 7\n",
      "try 40\n",
      "working 52\n",
      "myself 9\n",
      "before 66\n",
      "seeking 6\n",
      "another 23\n",
      "traditional 9\n",
      "Today, 2\n",
      "run 15\n",
      "home. 4\n",
      "have 299\n",
      "employees 8\n",
      "worry 8\n",
      "about, 5\n",
      "revenue 33\n",
      "stream 7\n",
      "matches 1\n",
      "anything 18\n",
      "ever 9\n",
      "successful 14\n",
      "senior 3\n",
      "manager 7\n",
      "tech 5\n",
      "now 23\n",
      "live 17\n",
      "someplace 7\n",
      "lower 12\n",
      "cost 35\n",
      "living, 4\n",
      "don't 97\n",
      "eat 3\n",
      "much, 6\n",
      "commuting 4\n",
      "costs 14\n",
      "deal 6\n",
      "with� 1\n",
      "so 101\n",
      "get 116\n",
      "keep 35\n",
      "money. 12\n",
      "entire 15\n",
      "happy, 1\n",
      "we're 6\n",
      "closer 2\n",
      "than 92\n",
      "we've 4\n",
      "been. 1\n",
      "anymore. 1\n",
      "growth, 3\n",
      "saying 4\n",
      "wrong 9\n",
      "thing 23\n",
      "some 111\n",
      "executive. 1\n",
      "commute 7\n",
      "meetings. 2\n",
      "office 17\n",
      "9 5\n",
      "AM, 1\n",
      "nor 1\n",
      "any 60\n",
      "artificial 2\n",
      "requirement 1\n",
      "work 114\n",
      "set 25\n",
      "number 34\n",
      "day, 7\n",
      "week. 4\n",
      "write 6\n",
      "receive 10\n",
      "performance 9\n",
      "reviews. 1\n",
      "fire 4\n",
      "anyone. 2\n",
      "Nobody 6\n",
      "can 319\n",
      "nobody 7\n",
      "lay 2\n",
      "off. 3\n",
      "take 52\n",
      "longer, 2\n",
      "because 27\n",
      "level 7\n",
      "basically 11\n",
      "zero. 2\n",
      "I'm 25\n",
      "43 1\n",
      "old, 1\n",
      "sure 65\n",
      "retirement 2\n",
      "feel 23\n",
      "like 66\n",
      "except 2\n",
      "not 169\n",
      "too 24\n",
      "old 6\n",
      "enjoy 10\n",
      "it, 26\n",
      "broke. 1\n",
      "telling 3\n",
      "gloat. 1\n",
      "maybe 6\n",
      "you're 159\n",
      "three 6\n",
      "ago. 1\n",
      "Maybe 13\n",
      "knows 5\n",
      "only 77\n",
      "reward 5\n",
      "hard 39\n",
      "going 53\n",
      "heart 1\n",
      "attack 1\n",
      "but 192\n",
      "trapped 2\n",
      "salary 2\n",
      "responsibilities. 2\n",
      "You've 7\n",
      "accepted 3\n",
      "society's 1\n",
      "expectations 4\n",
      "focusing 5\n",
      "entirely 13\n",
      "until 15\n",
      "65 1\n",
      "point 20\n",
      "hope 5\n",
      "you'll 67\n",
      "enough 51\n",
      "saved 6\n",
      "actually 32\n",
      "retire, 1\n",
      "health 28\n",
      "left 6\n",
      "here 11\n",
      "tell 13\n",
      "there 82\n",
      "path. 3\n",
      "Taking 3\n",
      "isn't 22\n",
      "easy, 4\n",
      "means 27\n",
      "personal 43\n",
      "financial 12\n",
      "freedom 23\n",
      "possible. 12\n",
      "while 38\n",
      "minimizing 2\n",
      "risks 3\n",
      "process. 7\n",
      "shares 5\n",
      "I've 23\n",
      "way. 3\n",
      "rich 6\n",
      "this, 10\n",
      "need 166\n",
      "developer. 1\n",
      "smarts 1\n",
      "tenacity 1\n",
      "self-sufficient, 1\n",
      "read 12\n",
      "may 106\n",
      "just 131\n",
      "save 5\n",
      "life, 3\n",
      "ways 19\n",
      "one. 8\n",
      "MAKING 4\n",
      "THE 18\n",
      "BIG 1\n",
      "DECISION 1\n",
      "OVERCOMING 1\n",
      "INERTIA 1\n",
      "first 26\n",
      "step 3\n",
      "toward 11\n",
      "self-employment 38\n",
      "want 99\n",
      "you've 49\n",
      "spent 13\n",
      "professional 13\n",
      "someone 57\n",
      "else, 5\n",
      "scary 4\n",
      "proposition. 1\n",
      "familiar 4\n",
      "comfortable, 1\n",
      "easiest 2\n",
      "continue 7\n",
      "current 18\n",
      "Discarding 1\n",
      "striking 1\n",
      "bold 1\n",
      "psyche 1\n",
      "rebel 1\n",
      "against 12\n",
      "change 17\n",
      "magnitude, 1\n",
      "find 76\n",
      "justify 1\n",
      "trying 24\n",
      "It's 46\n",
      "therefore 2\n",
      "surprising 1\n",
      "self-employed 17\n",
      "individuals 3\n",
      "were 38\n",
      "forced 6\n",
      "into 75\n",
      "their 117\n",
      "situation. 5\n",
      "ones 15\n",
      "become 13\n",
      "talk 27\n",
      "lot 54\n",
      "result, 3\n",
      "motivated 3\n",
      "achieve 8\n",
      "According 5\n",
      "2012 7\n",
      "Freelance 4\n",
      "Industry 4\n",
      "Report, 2\n",
      "29% 2\n",
      "freelancers 9\n",
      "fell 1\n",
      "necessity, 1\n",
      "after 29\n",
      "being 29\n",
      "laid 1\n",
      "off 17\n",
      "downsized. 1\n",
      "better 40\n",
      "transition 3\n",
      "terms. 3\n",
      "start 39\n",
      "planning 8\n",
      "up 155\n",
      "new 143\n",
      "business 261\n",
      "day 56\n",
      "ensure 13\n",
      "flowing 2\n",
      "yourself. 13\n",
      "will 220\n",
      "arm 1\n",
      "details 3\n",
      "make 88\n",
      "happen, 4\n",
      "decide 19\n",
      "effort 18\n",
      "taking. 2\n",
      "Before 3\n",
      "self-employed, 9\n",
      "understand 30\n",
      "forces 3\n",
      "come 26\n",
      "terms 11\n",
      "them, 15\n",
      "reasons 1\n",
      "why 18\n",
      "overcome 2\n",
      "That's 18\n",
      "about: 1\n",
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      "both 11\n",
      "imagined, 1\n",
      "still 62\n",
      "goal 14\n",
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      "done, 3\n",
      "we'll 1\n",
      "self-assessment 2\n",
      "see 46\n",
      "really 39\n",
      "position 9\n",
      "leap 2\n",
      "FEAR 1\n",
      "OF 16\n",
      "FAILURE 1\n",
      "paycheck 7\n",
      "puts 2\n",
      "food 2\n",
      "table 2\n",
      "roof 1\n",
      "over 58\n",
      "head 2\n",
      "reliably. 1\n",
      "idea 44\n",
      "giving 15\n",
      "quickly 12\n",
      "brings 3\n",
      "images 6\n",
      "starving 1\n",
      "house 7\n",
      "getting 28\n",
      "foreclosed. 1\n",
      "risk, 1\n",
      "proper 3\n",
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      "making, 1\n",
      "risk 12\n",
      "minimize. 1\n",
      "responsibilities 8\n",
      "should 63\n",
      "job 43\n",
      "until: 1\n",
      "* 22\n",
      "safety 4\n",
      "net 10\n",
      "place, 2\n",
      "fast 4\n",
      "rules 4\n",
      "low 8\n",
      "willing 11\n",
      "those 63\n",
      "reserves 5\n",
      "returning 1\n",
      "workplace 2\n",
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      "side 24\n",
      "proven 1\n",
      "viable 6\n",
      "So, 14\n",
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      "case, 10\n",
      "things 34\n",
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      "Bureau 2\n",
      "Labor 2\n",
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      "US 14\n",
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      "(SBA), 1\n",
      "50% 5\n",
      "businesses 31\n",
      "survive 2\n",
      "least 31\n",
      "five 5\n",
      "years. 9\n",
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      "think 37\n",
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      "employer 25\n",
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      "now, 6\n",
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      "4.6 1\n",
      "Does 2\n",
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      "employee. 2\n",
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      "\"strongly 1\n",
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      "Freelancers 1\n",
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      "22 1\n",
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      "workers, 3\n",
      "web 28\n",
      "developers, 5\n",
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      "fancy 2\n",
      "education 2\n",
      "lots 7\n",
      "connections 6\n",
      "advantage 11\n",
      "millions 2\n",
      "who 85\n",
      "managed 4\n",
      "full 18\n",
      "time 165\n",
      "earn 16\n",
      "living. 3\n",
      "CAREER 1\n",
      "INDOCTRINATION 1\n",
      "spend 42\n",
      "most 61\n",
      "waking 2\n",
      "possible 10\n",
      "somebody 2\n",
      "else 14\n",
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      "Well, 2\n",
      "raised 2\n",
      "believe 15\n",
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      "We'll 4\n",
      "external 2\n",
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      "barrier 2\n",
      "probably 76\n",
      "internal 1\n",
      "do! 1\n",
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      "usually 14\n",
      "religious 1\n",
      "cults 1\n",
      "brainwashing. 1\n",
      "taught 3\n",
      "beliefs 1\n",
      "questioning 1\n",
      "Just 11\n",
      "question 8\n",
      "responsible 4\n",
      "member 2\n",
      "society? 1\n",
      "common 8\n",
      "indoctrination 1\n",
      "instill 1\n",
      "ideas 19\n",
      "youth 1\n",
      "people 122\n",
      "authority. 1\n",
      "That�s 2\n",
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      "up, 4\n",
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      "track 7\n",
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      "school, 1\n",
      "told 5\n",
      "parents 2\n",
      "teachers 1\n",
      "grades 1\n",
      "college. 2\n",
      "In 41\n",
      "college, 1\n",
      "would 32\n",
      "graduated. 1\n",
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      "loyalty 2\n",
      "employer. 3\n",
      "It�s 6\n",
      "result 17\n",
      "lifestyle 29\n",
      "choice 5\n",
      "indoctrinated 1\n",
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      "age. 1\n",
      "Once 23\n",
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      "world, 5\n",
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      "promotion, 3\n",
      "fired. 1\n",
      "been 24\n",
      "busy 2\n",
      "following 8\n",
      "path, 1\n",
      "haven't 6\n",
      "consider 20\n",
      "alternatives. 2\n",
      "Meanwhile, 1\n",
      "picked 2\n",
      "children, 1\n",
      "mortgage, 1\n",
      "student 3\n",
      "loan 7\n",
      "debt 4\n",
      "steady 2\n",
      "seems 5\n",
      "terrifying, 1\n",
      "barely 1\n",
      "meet 8\n",
      "demands. 1\n",
      "bills 7\n",
      "pay 43\n",
      "mouths 1\n",
      "feed, 1\n",
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      "don�t 10\n",
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      "self-employed. 10\n",
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      "C-suite. 1\n",
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      "labor 2\n",
      "amass 3\n",
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      "executives 1\n",
      "bunch 7\n",
      "Wall 1\n",
      "Street 1\n",
      "trade 6\n",
      "portion 3\n",
      "profits 3\n",
      "create. 2\n",
      "faceless 1\n",
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      "thousands 7\n",
      "dollars 14\n",
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      "plan, 8\n",
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      "either. 5\n",
      "skills, 4\n",
      "people, 7\n",
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      "personally 7\n",
      "across 9\n",
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      "derail 1\n",
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      "failing 1\n",
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      "unnecessary. 1\n",
      "hinges 1\n",
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      "parts 4\n",
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      "screw 1\n",
      "doing, 4\n",
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      "politics\" 1\n",
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      "larger 11\n",
      "team 4\n",
      "on, 9\n",
      "sound 5\n",
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      "I'll 3\n",
      "honest: 1\n",
      "scares 1\n",
      "confident 3\n",
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      "disturbing 2\n",
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      "sitting 2\n",
      "rush-hour 1\n",
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      "kiss 1\n",
      "goodbye 1\n",
      "Census 1\n",
      "Bureau, 1\n",
      "spends 2\n",
      "minutes 2\n",
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      "relaxing 1\n",
      "recharging 1\n",
      "however 8\n",
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      "dealing 5\n",
      "traffic 28\n",
      "huge 12\n",
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    },
    {
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      "amazed 3\n",
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      "Jose, 1\n",
      "California 1\n",
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      "higher 8\n",
      "average6. 1\n",
      "six-figure 1\n",
      "Silicon 6\n",
      "Valley, 3\n",
      "engineer 3\n",
      "Austin, 1\n",
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      "discretionary 1\n",
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      "mention 7\n",
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      "housing 2\n",
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      "somewhere 1\n",
      "nicer 1\n",
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      "days 7\n",
      "conducted 1\n",
      "online. 6\n",
      "fact, 5\n",
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      "wherever 3\n",
      "want, 4\n",
      "perhaps 9\n",
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      "kind 5\n",
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      "changes 2\n",
      "kick 1\n",
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      "billionaire, 1\n",
      "INTRODUCING 1\n",
      "astute 1\n",
      "say, 1\n",
      "\"Only 1\n",
      "survive? 1\n",
      "Didn't 1\n",
      "earlier 2\n",
      "more?\" 1\n",
      "did. 2\n",
      "Both 2\n",
      "statements 2\n",
      "true 1\n",
      "businesses. 5\n",
      "designed 6\n",
      "fast, 1\n",
      "above 2\n",
      "else. 6\n",
      "contrast, 4\n",
      "exists 1\n",
      "sole 6\n",
      "purpose 3\n",
      "family-owned 1\n",
      "restaurants, 1\n",
      "barber 1\n",
      "shops, 1\n",
      "cleaners, 1\n",
      "landscapers, 1\n",
      "roofing 1\n",
      "companies, 2\n",
      "freelancers, 2\n",
      "selling 31\n",
      "crafts 1\n",
      "imported 1\n",
      "goods 8\n",
      "employs 1\n",
      "Google 53\n",
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      "love 4\n",
      "terms, 5\n",
      "be, 7\n",
      "surrounded 1\n",
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      "it; 4\n",
      "options 4\n",
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      "responsibility 1\n",
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      "managing 2\n",
      "others, 7\n",
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      "location. 1\n",
      "IDEAL 1\n",
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      "earlier. 2\n",
      "start. 4\n",
      "review 4\n",
      "fullest. 1\n",
      "minimal 3\n",
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      "can. 6\n",
      "ideal 1\n",
      "digital 10\n",
      "front, 2\n",
      "indefinitely 2\n",
      "distribution, 3\n",
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      "largely 6\n",
      "automated 9\n",
      "targeted 14\n",
      "ads 46\n",
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      "conversions. 1\n",
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      "production 1\n",
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      "reasonable 6\n",
      "bootstrap 2\n",
      "using 19\n",
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      "Investors 1\n",
      "generally 5\n",
      "interested 11\n",
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      "anyhow 3\n",
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      "Bank 1\n",
      "loans 2\n",
      "difficult 7\n",
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      "anyhow. 4\n",
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      "Self-funding 1\n",
      "forward. 3\n",
      "news 10\n",
      "modern 1\n",
      "outlay 2\n",
      "often, 1\n",
      "website, 13\n",
      "computer, 2\n",
      "connection 1\n",
      "plus 3\n",
      "talked 6\n",
      "dependencies. 1\n",
      "Of 3\n",
      "course, 1\n",
      "base 4\n",
      "way? 2\n",
      "example 3\n",
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      "Will 10\n",
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      "temporary 2\n",
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      "Instead 3\n",
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      "losing 2\n",
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      "life. 4\n",
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      "suburbs, 1\n",
      "presence 5\n",
      "counts. 1\n",
      "First 3\n",
      "violates 1\n",
      "tenet 1\n",
      "\"unlimited 1\n",
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      "messages 6\n",
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      "hopefully 6\n",
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      "& 2\n",
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      "to, 7\n",
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      "To 6\n",
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      "global, 3\n",
      "replaced 1\n",
      "remotely. 1\n",
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      "STUDY: 1\n",
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      "empty 2\n",
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      "LLC, 3\n",
      "advantages 1\n",
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      "additional 6\n",
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      "licenses 8\n",
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      "automatically 10\n",
      "download 3\n",
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      "campaigns 10\n",
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      "Since 5\n",
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      "list 18\n",
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      "IDEAS 2\n",
      "developer 2\n",
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      "staff: 1\n",
      "Selling 2\n",
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      "decent 4\n",
      "unique 10\n",
      "sites 10\n",
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      "Etsy. 1\n",
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      "account, 8\n",
      "popularity 1\n",
      "metric 3\n",
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      "Again, 2\n",
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      "saw 4\n",
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      "underserved 3\n",
      "book, 5\n",
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      "novel. 1\n",
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      "tuition 1\n",
      "increasingly 2\n",
      "expensive, 1\n",
      "turning 5\n",
      "courses 2\n",
      "Coursera, 2\n",
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      "General 1\n",
      "Assembly. 1\n",
      "instructors 1\n",
      "courses, 1\n",
      "cases 2\n",
      "instructional 2\n",
      "videos 1\n",
      "platforms 3\n",
      "streams. 1\n",
      "Some 10\n",
      "content 14\n",
      "creation. 2\n",
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      "stuff. 1\n",
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      "art 2\n",
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      "painting 1\n",
      "wall 5\n",
      "price. 1\n",
      "empty. 1\n",
      "spend, 1\n",
      "artisans 1\n",
      "fits 1\n",
      "tastes 1\n",
      "among 4\n",
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      "art. 1\n",
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      "potentially 3\n",
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      "watch 3\n",
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      "importantly 1\n",
      "creatively. 2\n",
      "ragged 1\n",
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      "responsibilities, 1\n",
      "pressed 1\n",
      "conjure 1\n",
      "original 2\n",
      "ideas. 2\n",
      "leaning 2\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "bit. 1\n",
      "Also, 4\n",
      "vigilant 1\n",
      "unsolved 1\n",
      "problems 12\n",
      "encounter 2\n",
      "searched 4\n",
      "unavailable 1\n",
      "find? 1\n",
      "waste 5\n",
      "you'd 7\n",
      "back? 2\n",
      "opportunities 7\n",
      "fill 5\n",
      "eventually 3\n",
      "excited 4\n",
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      "POINTS 1\n",
      "EVALUATING 1\n",
      "IDEA 1\n",
      "reasons: 1\n",
      "one, 3\n",
      "evaluates 1\n",
      "eliminate 3\n",
      "worst 2\n",
      "Two, 1\n",
      "validates 2\n",
      "help. 5\n",
      "easier 8\n",
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      "keeps 4\n",
      "low, 1\n",
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      "agreement, 2\n",
      "won�t 3\n",
      "violate 1\n",
      "well? 1\n",
      "manufactured 1\n",
      "developed, 1\n",
      "PR, 3\n",
      "further. 1\n",
      "wish. 1\n",
      "worse, 1\n",
      "billed 1\n",
      "hourly 3\n",
      "Products 1\n",
      "information 17\n",
      "limit, 1\n",
      "fixed 3\n",
      "quantity. 1\n",
      "niche? 1\n",
      "observation 1\n",
      "realistic 9\n",
      "3D 2\n",
      "clouds 2\n",
      "produce 4\n",
      "simulators 3\n",
      "games. 2\n",
      "Yet, 1\n",
      "deep 1\n",
      "pockets 1\n",
      "behind 3\n",
      "solutions 2\n",
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      "yes, 1\n",
      "bills. 2\n",
      "Estimating 1\n",
      "sizes 2\n",
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      "keyword 3\n",
      "tool 4\n",
      "AdWords, 6\n",
      "useful 8\n",
      "measuring 6\n",
      "trends 10\n",
      "overall 1\n",
      "topic. 2\n",
      "key 4\n",
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      "grossly 2\n",
      "overestimate 2\n",
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      "hard-earned 1\n",
      "competitors 4\n",
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      "initially, 2\n",
      "term? 1\n",
      "yours, 4\n",
      "projections. 1\n",
      "field 2\n",
      "unto 1\n",
      "itself, 5\n",
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      "Use 8\n",
      "discover 4\n",
      "doing. 6\n",
      "estimating 1\n",
      "guess. 2\n",
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      "relevant 26\n",
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      "primarily 3\n",
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      "plenty 1\n",
      "Make 15\n",
      "budgets 1\n",
      "disposable 1\n",
      "purchase 10\n",
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      "orders 2\n",
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      "insulating 1\n",
      "economic 4\n",
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      "recent 2\n",
      "simulation 4\n",
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      "stagnant 1\n",
      "Canada, 1\n",
      "Europe 1\n",
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      "globally, 1\n",
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      "Understanding 2\n",
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      "especially 5\n",
      "cost? 1\n",
      "problem. 6\n",
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      "demos 1\n",
      "salesperson 5\n",
      "everywhere 1\n",
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      "demographics 1\n",
      "Facebook? 1\n",
      "websites 25\n",
      "advertise 6\n",
      "on? 3\n",
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      "expense 5\n",
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      "allow 6\n",
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      "yours 4\n",
      "details. 2\n",
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      "website. 10\n",
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      "encourage 3\n",
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      "LLC 3\n",
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      "50/50 2\n",
      "determine 6\n",
      "Otherwise 1\n",
      "clean 2\n",
      "mess 2\n",
      "incurred 1\n",
      "setting 6\n",
      "Florida: 1\n",
      "Setting 1\n",
      "state: 1\n",
      "$125 1\n",
      "�Business 1\n",
      "Receipt� 1\n",
      "filing: 1\n",
      "$82.50 1\n",
      "Fees 1\n",
      "widely 4\n",
      "municipality, 1\n",
      "$500 1\n",
      "obtained 1\n",
      "web, 2\n",
      "city 4\n",
      "hall. 1\n",
      "Certain 1\n",
      "trades, 1\n",
      "electricians, 1\n",
      "they�ll 1\n",
      "total 4\n",
      "costs, 1\n",
      "consultation. 1\n",
      "corporation 1\n",
      "Federal 1\n",
      "Identification 1\n",
      "Number 2\n",
      "(FEIN) 1\n",
      "point. 4\n",
      "security 4\n",
      "irs.gov. 1\n",
      "licenses, 1\n",
      "it! 1\n",
      "must. 1\n",
      "accountant. 2\n",
      "development, 3\n",
      "R&D 1\n",
      "US. 1\n",
      "helped 1\n",
      "standpoint, 3\n",
      "differently 1\n",
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      "crucial 5\n",
      "taxable. 1\n",
      "quarter 3\n",
      "recommends, 1\n",
      "payroll 1\n",
      "W2 2\n",
      "forms. 1\n",
      "stresses 1\n",
      "realistically 2\n",
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      "initially 3\n",
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      "contracting 3\n",
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      "IRS 2\n",
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      "tracking 3\n",
      "tax-deductible. 1\n",
      "includes 3\n",
      "deductions 2\n",
      "business-related 1\n",
      "(including 1\n",
      "trips 1\n",
      "car,) 1\n",
      "utility 1\n",
      "repairs 1\n",
      "contains 2\n",
      "receipts 1\n",
      "keeping, 1\n",
      "Quickbooks 3\n",
      "bookkeeping. 1\n",
      "fairly 3\n",
      "use, 1\n",
      "teach 2\n",
      "properly, 1\n",
      "him 2\n",
      "flow, 1\n",
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      "invoices, 1\n",
      "activities 2\n",
      "with) 2\n",
      "LAUNCHING 1\n",
      "PRODUCT, 1\n",
      "MEASURING 1\n",
      "RESULTS 1\n",
      "peoples' 2\n",
      "hands! 1\n",
      "validation 1\n",
      "turn 7\n",
      "form 6\n",
      "employed, 1\n",
      "best; 1\n",
      "splash, 1\n",
      "\"soft 1\n",
      "launch\" 1\n",
      "subset 1\n",
      "represent? 1\n",
      "geographic 1\n",
      "announce 2\n",
      "extrapolate 1\n",
      "launching, 1\n",
      "define 2\n",
      "be. 2\n",
      "spinning 1\n",
      "metrics 19\n",
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      "making. 1\n",
      "visited 5\n",
      "bots 1\n",
      "clicking 4\n",
      "Analytics 10\n",
      "tools, 1\n",
      "distracting 1\n",
      "misleading 2\n",
      "deeply 1\n",
      "version 3\n",
      "livelihood 2\n",
      "said 5\n",
      "$11,000 1\n",
      "lose. 1\n",
      "(A 1\n",
      "nuance 1\n",
      "versus 1\n",
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      "Costs 3\n",
      "sunk 1\n",
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      "Ongoing, 1\n",
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      "count.) 1\n",
      "previous 2\n",
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      "basics 2\n",
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      "helpful 1\n",
      "language 3\n",
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      "ready 3\n",
      "yet. 3\n",
      "necessarily 3\n",
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      "It. 2\n",
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      "Putting 1\n",
      "driving 4\n",
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      "(in 1\n",
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      "publish 5\n",
      "networks, 2\n",
      "LinkedIn 9\n",
      "groups, 1\n",
      "issue 3\n",
      "editors 7\n",
      "product's 2\n",
      "website? 1\n",
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      "site 19\n",
      "placement? 1\n",
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      "support? 1\n",
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      "easily. 1\n",
      "Odds 2\n",
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      "into. 3\n",
      "revenue! 1\n",
      "return 11\n",
      "continuing 1\n",
      "option. 2\n",
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      "Bear 1\n",
      "publicity 3\n",
      "burst 1\n",
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      "down. 2\n",
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      "double-down 1\n",
      "steady. 1\n",
      "cycle 1\n",
      "big-ticket 2\n",
      "Such 1\n",
      "recommending 1\n",
      "leading 4\n",
      "push. 1\n",
      "monitor 2\n",
      "announced 1\n",
      "feedback. 1\n",
      "mentions 1\n",
      "recommended. 2\n",
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      "reviews? 1\n",
      "channel 3\n",
      "address. 3\n",
      "Alerts 1\n",
      "publicly 2\n",
      "met 5\n",
      "online, 4\n",
      "harsh 1\n",
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      "regardless 3\n",
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      "constructive. 1\n",
      "resist 1\n",
      "they're 4\n",
      "reacting 1\n",
      "inflammatory 1\n",
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      "merit, 2\n",
      "behalf. 2\n",
      "thankful 2\n",
      "noticed 1\n",
      "trolls! 1\n",
      "accomplishment. 1\n",
      "matter; 1\n",
      "vote 1\n",
      "wallets 1\n",
      "overwhelmingly 1\n",
      "negative, 1\n",
      "refinement. 1\n",
      "damage 1\n",
      "inadequate 1\n",
      "constrained, 1\n",
      "keeping 4\n",
      "quiet 1\n",
      "peers 2\n",
      "publicizing 1\n"
     ]
    },
    {
     "name": "stdout",
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     "text": [
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      "expected 4\n",
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      "emergency 2\n",
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      "real-world 1\n",
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      "relocation 1\n",
      "tricky, 1\n",
      "crazy, 1\n",
      "disposing 1\n",
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      "contingency 1\n",
      "execute 4\n",
      "enter 2\n",
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      "aspects. 1\n",
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      "ALONE 1\n",
      "Transitioning 1\n",
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      "habits. 1\n",
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      "Every 4\n",
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      "notes, 2\n",
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      "fostering 1\n",
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      "consultations 1\n",
      "designers, 1\n",
      "accountants, 1\n",
      "lawyers, 1\n",
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      "program 1\n",
      "plunge. 1\n",
      "locale 1\n",
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      "proceeding 1\n",
      "accepting 1\n",
      "investments 1\n",
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      "meetup.com 1\n",
      "regularly 1\n",
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      "OPEN 1\n",
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      "contradicts 1\n",
      "another. 1\n",
      "Everyone's 1\n",
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      "distraction. 1\n",
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      "weigh 1\n",
      "similarity 1\n",
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      "signed 3\n",
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      "retain 4\n",
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      "uncommon 1\n",
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      "trademarks, 2\n",
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      "moment 2\n",
      "burn 3\n",
      "obtaining 1\n",
      "deductibles. 1\n",
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      "explored 1\n",
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      "date 1\n",
      "checkups, 1\n",
      "exams, 2\n",
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      "TELLING 1\n",
      "BOSS 1\n",
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      "welcomes 1\n",
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      "gone 1\n",
      "adventure, 1\n",
      "appreciates 1\n",
      "restate 1\n",
      "importance 3\n",
      "maintaining 5\n",
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      "suffer 1\n",
      "experimenting 2\n",
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      "managers 1\n",
      "appeal 2\n",
      "feelings 2\n",
      "goes, 1\n",
      "private 1\n",
      "means, 1\n",
      "say. 1\n",
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      "upon. 1\n",
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      "incentives 1\n",
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      "inequities 1\n",
      "retention 1\n",
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      "who's 1\n",
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      "genuinely 3\n",
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      "chaos 2\n",
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      "frustrations 1\n",
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      "belongings, 1\n",
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      "appeasing 1\n",
      "executives, 1\n",
      "fearing 1\n",
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      "politics. 1\n",
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      "hard, 1\n",
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      "effort. 3\n",
      "final 2\n",
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      "fuel 1\n",
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      "bits 1\n",
      "permanent 1\n",
      "FUELING 1\n",
      "FIRE 1\n",
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      "offering! 1\n",
      "grabbing 1\n",
      "bare 1\n",
      "exposure 2\n",
      "shying 1\n",
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      "effectiveness. 2\n",
      "BUILDING 2\n",
      "WEBSITE 1\n",
      "Unless 3\n",
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      "cornerstone 1\n",
      "efforts, 3\n",
      "attracts 1\n",
      "repelling 1\n",
      "complexity 1\n",
      "situations, 1\n",
      "storefronts 1\n",
      "Etsy, 1\n",
      "cares 1\n",
      "referrals 3\n",
      "profiles 1\n",
      "avoid. 1\n",
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      "accordingly. 3\n",
      "modern. 1\n",
      "\"modern\" 1\n",
      "immortalize 1\n",
      "heavily 1\n",
      "adapt 2\n",
      "seamlessly 1\n",
      "mobile 8\n",
      "tablet 3\n",
      "devices. 2\n",
      "Conventional 1\n",
      "anymore, 1\n",
      "seconds 2\n",
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      "emulate, 1\n",
      "credits 1\n",
      "built 4\n",
      "looking. 1\n",
      "budget, 1\n",
      "prices. 1\n",
      "maintainable 1\n",
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      "blog 8\n",
      "(SEO) 1\n",
      "basis. 4\n",
      "SEO? 1\n",
      "answers. 1\n",
      "(LPO?) 1\n",
      "perform 3\n",
      "action 16\n",
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      "others? 1\n",
      "LPO, 1\n",
      "sign. 1\n",
      "mobile? 1\n",
      "\"responsive\"? 1\n",
      "integrated 2\n",
      "platform? 1\n",
      "securing 1\n",
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      "publicize 1\n",
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      "Often 1\n",
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      "(be 1\n",
      "afoul 1\n",
      "that� 1\n",
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      "onto 1\n",
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      "time� 1\n",
      "Wordpress 2\n",
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      "(SEO). 1\n",
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      "SEO\" 1\n",
      "Yoast, 1\n",
      "15% 1\n",
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      "85% 1\n",
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      "practices 1\n",
      "\"organic 1\n",
      "traffic\"� 1\n",
      "Update 1\n",
      "doubt 1\n",
      "engines 4\n",
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      "below. 1\n",
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      "directories 1\n",
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      "\"link 2\n",
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      "his 5\n",
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      "decline 2\n",
      "pessimistic, 1\n",
      "promise 1\n",
      "perpetuity, 1\n",
      "discontinue 1\n",
      "explicitly 1\n",
      "time-bound 1\n",
      "provide. 1\n",
      "evolving 1\n",
      "PEOPLE 1\n",
      "accomplishing 2\n",
      "hired 1\n",
      "presumption 1\n",
      "ahead. 1\n",
      "successfully, 1\n",
      "lot. 1\n",
      "routine 1\n",
      "tasks, 1\n",
      "Elance 1\n",
      "ratings 1\n",
      "contractor, 1\n",
      "Start 1\n",
      "small, 2\n",
      "well-defined 1\n",
      "strict 1\n",
      "losing. 1\n",
      "expectations, 1\n",
      "permits. 1\n",
      "Take 2\n",
      "flexible 1\n",
      "committing 1\n",
      "projects. 1\n",
      "contract! 1\n",
      "boilerplate 1\n",
      "needs. 1\n",
      "deliverables, 1\n",
      "due, 1\n",
      "made, 1\n",
      "owns 1\n",
      "property, 1\n",
      "performed. 1\n",
      "headache 1\n",
      "W9 1\n",
      "1099 1\n",
      "We've 1\n",
      "established 1\n",
      "assumes 1\n",
      "viable. 1\n",
      "ideas? 1\n",
      "one! 1\n",
      "needs, 1\n",
      "gates 1\n",
      "running. 1\n",
      "lunch. 2\n",
      "conversation. 1\n",
      "Send 1\n",
      "survey. 1\n",
      "\"what 1\n",
      "night?\" 1\n",
      "ones? 1\n",
      "kits 1\n",
      "sells� 1\n",
      "realizing 1\n",
      "add-ons 1\n",
      "game. 1\n",
      "enthusiasts. 1\n",
      "derivative 1\n",
      "$100,000 3\n",
      "revenue� 1\n",
      "up-front 1\n",
      "manufacturing, 1\n",
      "mostly 2\n",
      "cheaply. 1\n",
      "considered? 1\n",
      "re-packaging 1\n",
      "systems. 1\n",
      "weekend 3\n",
      "caffeine-fueled 1\n",
      "coding 1\n",
      "generating 1\n",
      "$1000 1\n",
      "$1,800 1\n",
      "rate! 1\n",
      "company�s 1\n",
      "cast 1\n",
      "stone 1\n",
      "risking 1\n",
      "days; 1\n",
      "business! 1\n",
      "pivoting 1\n",
      "COMPOUNDING 1\n",
      "EFFECT 1\n",
      "genius 1\n",
      "mentality 1\n",
      "year� 2\n",
      "done; 1\n",
      "smashing 1\n",
      "older 1\n",
      "diligence, 1\n",
      "forcing 1\n",
      "wealth. 1\n",
      "Increasing 1\n",
      "20% 3\n",
      "easier. 1\n",
      "get-rich-quick 1\n",
      "scheme. 1\n",
      "solo-preneurs 1\n",
      "rare. 1\n",
      "support, 1\n",
      "automate. 1\n",
      "promoting 1\n",
      "hitting 1\n",
      "flow� 1\n",
      "freedom� 1\n",
      "achieved. 1\n",
      "reasonably 1\n",
      "imagine. 1\n",
      "2010 1\n",
      "Nobel 1\n",
      "laureate 1\n",
      "Daniel 1\n",
      "Kahneman 1\n",
      "$75,000 2\n",
      "happiness. 1\n",
      "Earning 1\n",
      "achievable 1\n",
      "goal� 1\n",
      "ADAPTING 1\n",
      "NEW 1\n",
      "LIFE 1\n",
      "Successfully 1\n",
      "transitioning 1\n",
      "successfully. 1\n",
      "to! 1\n",
      "existed. 1\n",
      "transitions 1\n",
      "expect. 1\n",
      "SURVIVOR'S 1\n",
      "GUILT 1\n",
      "denial. 1\n",
      "decades 1\n",
      "virtuous 1\n",
      "threw 1\n",
      "Were 1\n",
      "wasted? 1\n",
      "believe, 1\n",
      "suspect 1\n",
      "reminds 1\n",
      "fondly. 1\n",
      "all-consumed 1\n",
      "careers. 1\n",
      "changed 1\n",
      "gloating. 2\n",
      "all� 1\n",
      "wasted. 1\n",
      "refined 1\n",
      "regret 1\n",
      "continued 1\n",
      "learn. 1\n",
      "Second, 1\n",
      "Answer 1\n",
      "too, 1\n",
      "hearing 1\n",
      "guilty 3\n",
      "feet 1\n",
      "bedroom 1\n",
      "drained 1\n",
      "clock 1\n",
      "says 1\n",
      "PM. 2\n",
      "breakfast 1\n",
      "luxuries, 1\n",
      "cheating 1\n",
      "first-world-problems; 1\n",
      "zero-world-problems. 1\n",
      "LETTING 1\n",
      "FIXED 1\n",
      "SCHEDULES 1\n",
      "workaholic 1\n",
      "8-plus-hour-day 1\n",
      "particularly 1\n",
      "tough 1\n",
      "days. 1\n",
      "minutes, 1\n",
      "filling 2\n",
      "expects 1\n",
      "continuously 1\n",
      "longer; 1\n",
      "restriction. 1\n",
      "productive, 1\n",
      "(like 1\n",
      "product,) 1\n",
      "recharge. 1\n",
      "review. 1\n",
      "met, 1\n",
      "productive. 1\n",
      "menial 1\n",
      "low. 1\n",
      "bookkeeping 1\n",
      "LITTLE 1\n",
      "Freed 1\n",
      "burdens 1\n",
      "commuting, 1\n",
      "demands 1\n",
      "rejected 1\n",
      "notion 1\n",
      "non-stop 1\n",
      "pursuit 1\n",
      "undefined 1\n",
      "\"retirement.\" 1\n",
      "retirement! 1\n",
      "beach 1\n",
      "boring 1\n",
      "(I 1\n",
      "days). 1\n",
      "rewarding 1\n",
      "enjoy. 1\n",
      "passed 1\n",
      "thought, 1\n",
      "busy? 1\n",
      "offer? 1\n",
      "pleasure? 1\n",
      "intimately 1\n",
      "interesting? 1\n",
      "change. 1\n",
      "constructed 1\n",
      "anywhere. 1\n",
      "reader 1\n",
      "achieves 1\n",
      "wish 1\n",
      "luck 1\n",
      "journey! 1\n",
      "you! 1\n",
      "RECOMMENDED 1\n",
      "READING 1\n",
      "mentioned, 1\n",
      "topics 1\n",
      "Ferriss, 1\n",
      "Timothy. 1\n",
      "4-Hour 1\n",
      "Workweek: 1\n",
      "Escape 1\n",
      "9-5, 1\n",
      "Anywhere, 1\n",
      "Join 1\n",
      "Rich. 1\n",
      "Harmony, 1\n",
      "2009. 1\n",
      "Mohammed, 1\n",
      "Rafi. 1\n",
      "Windfall: 1\n",
      "Companies 1\n",
      "Price 1\n",
      "Grow. 1\n",
      "Harper 1\n",
      "Business, 2\n",
      "2010. 1\n",
      "Reis, 1\n",
      "Eric. 1\n",
      "Startup: 1\n",
      "Today�s 1\n",
      "Entrepreneurs 1\n",
      "Continuous 1\n",
      "Innovation 1\n",
      "Create 1\n",
      "Radically 1\n",
      "Businesses. 1\n",
      "Crown 1\n",
      "2011. 2\n",
      "Rumsey, 1\n",
      "Deborah 1\n",
      "J. 1\n",
      "Dummies. 1\n",
      "Dummies, 1\n",
      "Shelton, 1\n",
      "Hal. 1\n",
      "Plan: 1\n",
      "Pro 1\n",
      "Shares 1\n",
      "Step-By-Step 1\n",
      "Guide 1\n",
      "Creating 1\n",
      "Gets 1\n",
      "Results. 1\n",
      "Summit 1\n",
      "Press, 1\n",
      "2014. 4\n",
      "ACKNOWLEDGMENTS 1\n",
      "owes 1\n",
      "colleagues 1\n",
      "graciously 1\n",
      "volunteered 1\n",
      "meticulous 1\n",
      "edits 1\n",
      "draft. 1\n",
      "thank-you 1\n",
      "Aaron 2\n",
      "Dykstra, 1\n",
      "notes. 1\n",
      "Aaron�s 1\n",
      "ranged 1\n",
      "stylistic 1\n",
      "improvements, 1\n",
      "improving 1\n",
      "continuity 1\n",
      "thanks 1\n",
      "encouragement 1\n",
      "anecdotes 1\n",
      "scenarios. 1\n",
      "Michal 3\n",
      "Bryc 1\n",
      "spotted 1\n",
      "pages. 1\n",
      "thank 1\n",
      "acknowledge 1\n",
      "wife 2\n",
      "daughters. 2\n",
      "Living 1\n",
      "nearly 1\n",
      "enjoyable 1\n",
      "ABOUT 1\n",
      "AUTHOR 1\n",
      "produces 1\n",
      "virtual-reality 1\n",
      "clouds. 1\n",
      "Frank's 1\n",
      "41, 1\n",
      "electrical 1\n",
      "Massachusetts 1\n",
      "Dartmouth, 1\n",
      "Sierra 1\n",
      "California, 1\n",
      "Glass 1\n",
      "Studios 1\n",
      "Boston. 1\n",
      "nine 1\n",
      "Amazon.com 1\n",
      "progressed 1\n",
      "personalization, 1\n",
      "recommendation, 1\n",
      "technologies. 1\n",
      "IMDb.com, 1\n",
      "subsidiary 1\n",
      "Amazon. 1\n",
      "circumstances 1\n",
      "IMDb 1\n",
      "2012, 1\n",
      "lives 1\n",
      "enjoys 1\n",
      "hanging 1\n",
      "parks, 1\n",
      "Star 1\n",
      "Trek 1\n",
      "memorabilia, 1\n",
      "himself 1\n",
      "person. 1\n",
      "Impact 1\n",
      "Requirments 1\n",
      "Success 1\n",
      "Projects, 1\n",
      "IAG 1\n",
      "Consulting. 1\n",
      "�Your 1\n",
      "realize�, 1\n",
      "Reuters, 1\n",
      "May 1\n",
      "27, 1\n",
      "http://www.reuters.com/article/2014/05/27/us-usa-commute-costs-idUSKBN0E721M20140527 1\n",
      "�How 1\n",
      "Times 1\n",
      "Crash 1\n",
      "Car?�, 1\n",
      "Forbes, 1\n",
      "http://www.forbes.com/sites/moneybuilder/2011/07/27/how-many-times-will-you-crash-your-car/ 1\n",
      "National 1\n",
      "Council, 1\n",
      "2011 1\n",
      "Brookings 1\n",
      "Institution, 1\n",
      "Council 1\n",
      "Community 1\n",
      "Economic 1\n",
      "Research, 1\n",
      "http://tgeonetta.com/cost-of-living-vs-salary-best-cities-for-software-developers-and-engineers/ 1\n",
      "47 1\n",
      "hours�, 1\n",
      "Washington 1\n",
      "Post, 1\n",
      "September 1\n",
      "2, 1\n",
      "http://www.apa.org/helpcenter/workplace-stress.aspx 1\n",
      "�Stress� 1\n",
      "Work�, 1\n",
      "DHHS 1\n",
      "(NIOSH) 1\n",
      "Publication 1\n",
      "99-101. 1\n",
      "http://www.cdc.gov/niosh/docs/99-101/ 1\n",
      "http://www.businessinsider.com/startup-odds-of-success-2013-5 1\n",
      "12 1\n",
      "exception� 1\n",
      "treated 1\n",
      "separately 1\n",
      "state� 1\n",
      "13 1\n",
      "tricking 1\n",
      "Analytics. 1\n",
      "--------------- 2\n",
      "------------------------------------------------------------ 2\n"
     ]
    }
   ],
   "source": [
    "for word, count in wordCounts.items():\n",
    "    cleanWord = word.encode('ascii', 'ignore')\n",
    "    if (cleanWord):\n",
    "        print(word, count)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "sc.stop()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "self 111\n",
      "employment 75\n",
      "building 33\n",
      "an 178\n",
      "internet 26\n",
      "business 383\n",
      "of 970\n",
      "one 100\n",
      "achieving 1\n",
      "financial 17\n",
      "and 934\n",
      "personal 48\n",
      "freedom 41\n",
      "through 57\n",
      "a 1191\n",
      "lifestyle 44\n",
      "technology 11\n",
      "by 122\n",
      "frank 11\n",
      "kane 10\n",
      "copyright 3\n",
      "2015 4\n",
      "all 137\n",
      "rights 3\n",
      "reserved 2\n",
      "worldwide 4\n",
      "contents 1\n",
      "disclaimer 2\n",
      "preface 2\n",
      "part 33\n",
      "i 387\n",
      "making 25\n",
      "the 1292\n",
      "big 42\n",
      "decision 12\n",
      "overcoming 2\n",
      "inertia 2\n",
      "fear 3\n",
      "failure 3\n",
      "career 31\n",
      "indoctrination 5\n",
      "carrot 4\n",
      "on 428\n",
      "stick 6\n",
      "ego 3\n",
      "protection 7\n",
      "your 1420\n",
      "employer 44\n",
      "as 343\n",
      "security 8\n",
      "blanket 2\n",
      "why 25\n",
      "it 649\n",
      "s 391\n",
      "worth 39\n",
      "unlimited 6\n",
      "growth 39\n",
      "potential 38\n",
      "investing 16\n",
      "in 616\n",
      "yourself 78\n",
      "not 203\n",
      "someone 62\n",
      "else 33\n",
      "no 76\n",
      "dependencies 6\n",
      "commute 14\n",
      "to 1828\n",
      "live 25\n",
      "where 53\n",
      "you 1878\n",
      "want 122\n",
      "work 144\n",
      "when 102\n",
      "how 163\n",
      "is 560\n",
      "for 537\n",
      "flowchart 4\n",
      "should 69\n",
      "even 104\n",
      "consider 26\n",
      "having 30\n",
      "safety 7\n",
      "net 13\n",
      "planning 16\n",
      "health 35\n",
      "care 24\n",
      "assessment 4\n",
      "quiz 4\n",
      "ii 2\n",
      "happen 13\n",
      "designing 4\n",
      "fallacy 2\n",
      "introducing 3\n",
      "ideal 3\n",
      "case 26\n",
      "study 4\n",
      "sundog 24\n",
      "software 60\n",
      "other 78\n",
      "ideas 27\n",
      "key 6\n",
      "points 5\n",
      "evaluating 4\n",
      "idea 60\n",
      "writing 15\n",
      "plan 64\n",
      "description 7\n",
      "vision 6\n",
      "definition 4\n",
      "market 66\n",
      "product 182\n",
      "organization 2\n",
      "management 14\n",
      "marketing 42\n",
      "sales 80\n",
      "strategy 7\n",
      "reality 11\n",
      "check 15\n",
      "agreement 8\n",
      "developing 21\n",
      "side 30\n",
      "naming 2\n",
      "obtaining 3\n",
      "licenses 12\n",
      "tax 29\n",
      "launching 11\n",
      "measuring 9\n",
      "results 25\n",
      "risk 18\n",
      "mitigation 2\n",
      "don 133\n",
      "t 301\n",
      "have 321\n",
      "go 45\n",
      "alone 9\n",
      "pulling 2\n",
      "trigger 3\n",
      "final 4\n",
      "checklist 3\n",
      "telling 5\n",
      "boss 9\n",
      "iii 2\n",
      "last 10\n",
      "fueling 2\n",
      "fire 6\n",
      "website 109\n",
      "basics 12\n",
      "public 4\n",
      "relations 4\n",
      "online 50\n",
      "advertising 41\n",
      "offline 2\n",
      "search 56\n",
      "engine 13\n",
      "optimization 15\n",
      "landing 19\n",
      "page 42\n",
      "importance 5\n",
      "email 33\n",
      "campaigns 23\n",
      "using 25\n",
      "social 36\n",
      "networks 16\n",
      "measure 27\n",
      "act 11\n",
      "interpreting 2\n",
      "metrics 23\n",
      "tracking 5\n",
      "closing 4\n",
      "avoiding 5\n",
      "pitfalls 2\n",
      "beware 10\n",
      "leeches 2\n",
      "well 66\n",
      "meaning 5\n",
      "advice 44\n",
      "hiring 17\n",
      "salespeople 5\n",
      "pressure 2\n",
      "hire 20\n",
      "misleading 5\n",
      "statistics 11\n",
      "finding 17\n",
      "time 255\n",
      "people 145\n",
      "compounding 2\n",
      "effect 4\n",
      "adapting 2\n",
      "new 153\n",
      "life 31\n",
      "survivor 2\n",
      "guilt 2\n",
      "letting 4\n",
      "fixed 5\n",
      "schedules 2\n",
      "little 29\n",
      "recommended 5\n",
      "reading 9\n",
      "acknowledgments 2\n",
      "about 202\n",
      "author 2\n",
      "what 229\n",
      "do 207\n",
      "with 315\n",
      "own 140\n",
      "this 280\n",
      "book 39\n",
      "tells 4\n",
      "improved 2\n",
      "my 215\n",
      "quitting 10\n",
      "job 90\n",
      "creating 16\n",
      "sustainable 3\n",
      "growing 12\n",
      "income 24\n",
      "learned 11\n",
      "along 10\n",
      "way 55\n",
      "could 46\n",
      "help 50\n",
      "same 29\n",
      "but 242\n",
      "matter 13\n",
      "much 90\n",
      "or 278\n",
      "many 71\n",
      "stories 3\n",
      "give 31\n",
      "end 49\n",
      "success 24\n",
      "relies 5\n",
      "preparation 1\n",
      "skillset 1\n",
      "talents 3\n",
      "determination 1\n",
      "bit 9\n",
      "luck 2\n",
      "can 376\n",
      "that 747\n",
      "if 411\n",
      "gives 5\n",
      "confidence 1\n",
      "strike 1\n",
      "out 161\n",
      "great 19\n",
      "responsibly 3\n",
      "realize 14\n",
      "very 58\n",
      "real 31\n",
      "possibility 3\n",
      "must 29\n",
      "blame 1\n",
      "me 34\n",
      "decisions 5\n",
      "make 108\n",
      "they 234\n",
      "are 424\n",
      "ultimately 9\n",
      "now 48\n",
      "adventure 4\n",
      "three 8\n",
      "years 38\n",
      "ago 4\n",
      "worked 16\n",
      "company 122\n",
      "did 16\n",
      "everything 12\n",
      "good 72\n",
      "american 4\n",
      "employee 10\n",
      "supposed 4\n",
      "hard 47\n",
      "devoted 1\n",
      "thoughts 2\n",
      "more 200\n",
      "successful 27\n",
      "commuted 1\n",
      "hour 19\n",
      "each 18\n",
      "without 40\n",
      "complaint 1\n",
      "50 16\n",
      "hours 35\n",
      "every 32\n",
      "week 25\n",
      "at 220\n",
      "minimum 9\n",
      "got 23\n",
      "home 27\n",
      "let 32\n",
      "them 166\n",
      "2 5\n",
      "am 12\n",
      "something 56\n",
      "needed 12\n",
      "attention 20\n",
      "which 37\n",
      "happened 3\n",
      "pretty 18\n",
      "often 26\n",
      "over 62\n",
      "was 85\n",
      "rewarded 1\n",
      "responsibility 3\n",
      "money 86\n",
      "although 10\n",
      "never 27\n",
      "seemed 2\n",
      "be 369\n",
      "quite 5\n",
      "enough 59\n",
      "considered 6\n",
      "role 1\n",
      "model 5\n",
      "development 19\n",
      "manager 9\n",
      "felt 4\n",
      "however 36\n",
      "marriage 1\n",
      "under 8\n",
      "stress 12\n",
      "kids 7\n",
      "hardly 2\n",
      "knew 6\n",
      "prescription 2\n",
      "sleep 5\n",
      "aids 2\n",
      "order 32\n",
      "combat 1\n",
      "extreme 2\n",
      "family 26\n",
      "wasn 5\n",
      "happy 15\n",
      "living 27\n",
      "country 6\n",
      "we 43\n",
      "lived 3\n",
      "weren 2\n",
      "secondary 1\n",
      "duty 2\n",
      "provider 2\n",
      "doing 51\n",
      "thought 5\n",
      "had 29\n",
      "faced 4\n",
      "ultimatum 1\n",
      "from 166\n",
      "few 40\n",
      "weeks 1\n",
      "later 22\n",
      "quit 21\n",
      "walked 1\n",
      "away 19\n",
      "million 6\n",
      "dollars 20\n",
      "stock 9\n",
      "grants 2\n",
      "so 143\n",
      "made 13\n",
      "try 47\n",
      "working 58\n",
      "myself 13\n",
      "before 70\n",
      "seeking 6\n",
      "another 26\n",
      "traditional 10\n",
      "today 11\n",
      "run 27\n",
      "employees 10\n",
      "worry 8\n",
      "revenue 44\n",
      "stream 9\n",
      "matches 1\n",
      "anything 23\n",
      "ever 10\n",
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      "drops 1\n",
      "congratulate 1\n",
      "completed 1\n",
      "critical 1\n",
      "dropping 2\n",
      "boost 1\n",
      "appealing 1\n",
      "abandon 1\n",
      "engagement 1\n",
      "attracting 1\n",
      "rise 1\n",
      "malicious 2\n",
      "block 1\n",
      "originated 1\n",
      "balance 2\n",
      "sources 2\n",
      "influence 2\n",
      "digging 2\n",
      "referral 1\n",
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      "tag 1\n",
      "events 2\n",
      "polluted 2\n",
      "referrer 5\n",
      "spam13 1\n",
      "tricks 1\n",
      "junk 1\n",
      "skepticism 1\n",
      "ring 3\n",
      "drove 1\n",
      "legitimate 1\n",
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      "affected 1\n",
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      "hardest 1\n",
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      "despite 2\n",
      "doubling 1\n",
      "stable 1\n",
      "overspend 1\n",
      "requiring 1\n",
      "dries 1\n",
      "indicator 1\n",
      "crm 3\n",
      "salesforce 1\n",
      "zoho 1\n",
      "driven 1\n",
      "leads 7\n",
      "added 1\n",
      "signs 1\n",
      "reminding 1\n",
      "reminders 2\n",
      "nudge 2\n",
      "nudges 1\n",
      "economy 3\n",
      "gross 1\n",
      "domestic 1\n",
      "predators 2\n",
      "unprepared 1\n",
      "fortune 1\n",
      "willingness 1\n",
      "scam 1\n",
      "recently 2\n",
      "directors 1\n",
      "partners 2\n",
      "divorce 1\n",
      "transferred 1\n",
      "contributing 1\n",
      "contingencies 1\n",
      "divorced 1\n",
      "maker 1\n",
      "acquirers 1\n",
      "complement 1\n",
      "knowledge 2\n",
      "council 3\n",
      "beast 1\n",
      "cut 2\n",
      "unsure 1\n",
      "challenges 1\n",
      "unsolicited 1\n",
      "bears 1\n",
      "repeating 1\n",
      "testified 1\n",
      "convinced 1\n",
      "relied 1\n",
      "tens 1\n",
      "furthermore 1\n",
      "distinction 1\n",
      "identified 1\n",
      "asked 1\n",
      "repeatedly 1\n",
      "fortunate 1\n",
      "originally 1\n",
      "his 5\n",
      "agreed 1\n",
      "burdened 1\n",
      "spot 1\n",
      "mainly 1\n",
      "manipulation 1\n",
      "ineffective 1\n",
      "ulterior 1\n",
      "motive 1\n",
      "negotiating 1\n",
      "scammer 1\n",
      "maximizes 1\n",
      "questionable 1\n",
      "ramp 1\n",
      "handed 1\n",
      "prospecting 1\n",
      "outsourced 1\n",
      "emailing 1\n",
      "qualified 1\n",
      "independence 1\n",
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      "dilemma 1\n",
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      "employ 1\n",
      "flows 1\n",
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      "variations 1\n",
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      "variation 2\n",
      "seasonal 1\n",
      "cycles 1\n",
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      "susceptible 1\n",
      "outliers 1\n",
      "analyzing 1\n",
      "dummies 3\n",
      "deviation 1\n",
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      "saturate 1\n",
      "provides 1\n",
      "metaphorical 1\n",
      "supporting 1\n",
      "adopt 1\n",
      "mindset 1\n",
      "conservatively 1\n",
      "104 1\n",
      "312 1\n",
      "mindful 1\n",
      "reserve 1\n",
      "outsourcing 3\n",
      "bankrupt 1\n",
      "automation 1\n",
      "automating 2\n",
      "sink 1\n",
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      "decline 2\n",
      "pessimistic 1\n",
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      "explicitly 1\n",
      "evolving 1\n",
      "accomplishing 2\n",
      "hired 1\n",
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      "elance 1\n",
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      "strict 1\n",
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      "deliverables 1\n",
      "owns 1\n",
      "performed 1\n",
      "headache 1\n",
      "w9 1\n",
      "1099 1\n",
      "assumes 1\n",
      "gates 1\n",
      "survey 1\n",
      "kits 1\n",
      "realizing 1\n",
      "ons 1\n",
      "derivative 1\n",
      "mostly 2\n",
      "cheaply 1\n",
      "packaging 1\n",
      "weekend 3\n",
      "caffeine 1\n",
      "fueled 1\n",
      "coding 1\n",
      "generating 1\n",
      "1000 1\n",
      "800 1\n",
      "cast 1\n",
      "stone 1\n",
      "risking 1\n",
      "pivoting 1\n",
      "genius 1\n",
      "mentality 1\n",
      "smashing 1\n",
      "older 1\n",
      "diligence 1\n",
      "forcing 1\n",
      "increasing 1\n",
      "scheme 1\n",
      "solo 1\n",
      "preneurs 1\n",
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      "hitting 1\n",
      "reasonably 1\n",
      "nobel 1\n",
      "laureate 1\n",
      "daniel 1\n",
      "kahneman 1\n",
      "75 2\n",
      "happiness 1\n",
      "achievable 1\n",
      "existed 1\n",
      "transitions 1\n",
      "denial 1\n",
      "decades 1\n",
      "virtuous 1\n",
      "threw 1\n",
      "suspect 1\n",
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      "fondly 1\n",
      "consumed 1\n",
      "gloating 2\n",
      "refined 1\n",
      "regret 1\n",
      "continued 1\n",
      "hearing 1\n",
      "guilty 3\n",
      "feet 1\n",
      "drained 1\n",
      "clock 1\n",
      "pm 2\n",
      "breakfast 1\n",
      "luxuries 1\n",
      "cheating 1\n",
      "workaholic 1\n",
      "particularly 1\n",
      "tough 1\n",
      "filling 2\n",
      "expects 1\n",
      "continuously 1\n",
      "restriction 1\n",
      "recharge 1\n",
      "menial 1\n",
      "freed 1\n",
      "burdens 1\n",
      "rejected 1\n",
      "notion 1\n",
      "pursuit 1\n",
      "undefined 1\n",
      "beach 1\n",
      "boring 1\n",
      "rewarding 1\n",
      "passed 1\n",
      "pleasure 1\n",
      "intimately 1\n",
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      "topics 1\n",
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      "workweek 1\n",
      "harmony 1\n",
      "2009 1\n",
      "harper 1\n",
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      "continuous 1\n",
      "innovation 1\n",
      "radically 1\n",
      "crown 1\n",
      "2011 4\n",
      "rumsey 1\n",
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      "j 1\n",
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      "owes 1\n",
      "colleagues 1\n",
      "graciously 1\n",
      "volunteered 1\n",
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      "thank 2\n",
      "aaron 3\n",
      "dykstra 1\n",
      "ranged 1\n",
      "stylistic 1\n",
      "improvements 1\n",
      "continuity 1\n",
      "thanks 1\n",
      "encouragement 1\n",
      "anecdotes 1\n",
      "scenarios 1\n",
      "michal 3\n",
      "bryc 1\n",
      "spotted 1\n",
      "acknowledge 1\n",
      "wife 2\n",
      "daughters 2\n",
      "nearly 1\n",
      "enjoyable 1\n",
      "produces 1\n",
      "electrical 1\n",
      "massachusetts 1\n",
      "dartmouth 1\n",
      "sierra 1\n",
      "glass 1\n",
      "studios 1\n",
      "boston 1\n",
      "nine 1\n",
      "progressed 1\n",
      "personalization 1\n",
      "recommendation 1\n",
      "imdb 2\n",
      "subsidiary 1\n",
      "lives 1\n",
      "enjoys 1\n",
      "parks 1\n",
      "star 1\n",
      "trek 1\n",
      "memorabilia 1\n",
      "himself 1\n",
      "requirments 1\n",
      "iag 1\n",
      "consulting 1\n",
      "reuters 2\n",
      "27 3\n",
      "05 1\n",
      "usa 1\n",
      "iduskbn0e721m20140527 1\n",
      "crash 2\n",
      "forbes 2\n",
      "moneybuilder 1\n",
      "07 1\n",
      "national 1\n",
      "brookings 1\n",
      "institution 1\n",
      "tgeonetta 1\n",
      "vs 1\n",
      "47 1\n",
      "washington 1\n",
      "september 1\n",
      "apa 1\n",
      "org 1\n",
      "helpcenter 1\n",
      "aspx 1\n",
      "dhhs 1\n",
      "niosh 2\n",
      "99 2\n",
      "101 2\n",
      "cdc 1\n",
      "docs 1\n",
      "businessinsider 1\n",
      "12 1\n",
      "treated 1\n",
      "13 1\n",
      "tricking 1\n"
     ]
    }
   ],
   "source": [
    "import re\n",
    "from pyspark import SparkConf, SparkContext\n",
    "\n",
    "def normalizeWords(text):\n",
    "    return re.compile(r'\\W+', re.UNICODE).split(text.lower())\n",
    "\n",
    "conf = SparkConf().setMaster('local').setAppName('WordCount')\n",
    "sc = SparkContext(conf = conf)\n",
    "input = sc.textFile('book.txt')\n",
    "words = input.flatMap(normalizeWords)\n",
    "wordCounts = words.countByValue()\n",
    "for word, count in wordCounts.items():\n",
    "    cleanWord = word.encode('ascii', 'ignore')\n",
    "    if cleanWord:\n",
    "        print(word, count)    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "sc.stop()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pyspark import SparkConf, SparkContext\n",
    "import re\n",
    "\n",
    "def normalizeWords(text):\n",
    "    return re.compile(r'\\W+', re.UNICODE).split(text.lower())\n",
    "\n",
    "conf = SparkConf().setMaster('local').setAppName('WordCount')\n",
    "sc = SparkContext(conf = conf)\n",
    "input = sc.textFile('book.txt')\n",
    "words = input.flatMap(normalizeWords)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['self',\n",
       " 'employment',\n",
       " 'building',\n",
       " 'an',\n",
       " 'internet',\n",
       " 'business',\n",
       " 'of',\n",
       " 'one',\n",
       " 'achieving',\n",
       " 'financial']"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "words.take(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('self', 111),\n",
       " ('employment', 75),\n",
       " ('building', 33),\n",
       " ('an', 178),\n",
       " ('internet', 26),\n",
       " ('business', 383),\n",
       " ('of', 970),\n",
       " ('one', 100),\n",
       " ('achieving', 1),\n",
       " ('financial', 17)]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wordCounts = words.map(lambda x: (x, 1)).reduceByKey(lambda x, y: x+y)\n",
    "wordCounts.take(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(1, 'achieving'),\n",
       " (1, 'contents'),\n",
       " (1, 'preparation'),\n",
       " (1, 'skillset'),\n",
       " (1, 'determination'),\n",
       " (1, 'confidence'),\n",
       " (1, 'strike'),\n",
       " (1, 'blame'),\n",
       " (1, 'devoted'),\n",
       " (1, 'commuted')]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wordCountsSorted = wordCounts.map(lambda x: (x[1], x[0])).sortByKey()\n",
    "wordCountsSorted.take(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "achieving:\t\t1\n",
      "contents:\t\t1\n",
      "preparation:\t\t1\n",
      "skillset:\t\t1\n",
      "determination:\t\t1\n",
      "confidence:\t\t1\n",
      "strike:\t\t1\n",
      "blame:\t\t1\n",
      "devoted:\t\t1\n",
      "commuted:\t\t1\n",
      "complaint:\t\t1\n",
      "rewarded:\t\t1\n",
      "role:\t\t1\n",
      "marriage:\t\t1\n",
      "combat:\t\t1\n",
      "secondary:\t\t1\n",
      "ultimatum:\t\t1\n",
      "weeks:\t\t1\n",
      "walked:\t\t1\n",
      "matches:\t\t1\n",
      "nor:\t\t1\n",
      "requirement:\t\t1\n",
      "43:\t\t1\n",
      "broke:\t\t1\n",
      "gloat:\t\t1\n",
      "heart:\t\t1\n",
      "attack:\t\t1\n",
      "65:\t\t1\n",
      "retire:\t\t1\n",
      "smarts:\t\t1\n",
      "tenacity:\t\t1\n",
      "discarding:\t\t1\n",
      "bold:\t\t1\n",
      "psyche:\t\t1\n",
      "rebel:\t\t1\n",
      "magnitude:\t\t1\n",
      "justify:\t\t1\n",
      "surprising:\t\t1\n",
      "fell:\t\t1\n",
      "laid:\t\t1\n",
      "downsized:\t\t1\n",
      "imagined:\t\t1\n",
      "pursuing:\t\t1\n",
      "roof:\t\t1\n",
      "starving:\t\t1\n",
      "foreclosed:\t\t1\n",
      "returning:\t\t1\n",
      "prototyped:\t\t1\n",
      "proven:\t\t1\n",
      "quits:\t\t1\n",
      "sba:\t\t1\n",
      "tenure:\t\t1\n",
      "secure:\t\t1\n",
      "28:\t\t1\n",
      "moderately:\t\t1\n",
      "americans:\t\t1\n",
      "representing:\t\t1\n",
      "14:\t\t1\n",
      "fringe:\t\t1\n",
      "internal:\t\t1\n",
      "religious:\t\t1\n",
      "cults:\t\t1\n",
      "brainwashing:\t\t1\n",
      "beliefs:\t\t1\n",
      "questioning:\t\t1\n",
      "instill:\t\t1\n",
      "youth:\t\t1\n",
      "grew:\t\t1\n",
      "teachers:\t\t1\n",
      "grades:\t\t1\n",
      "graduated:\t\t1\n",
      "absorbed:\t\t1\n",
      "culture:\t\t1\n",
      "promotes:\t\t1\n",
      "indoctrinated:\t\t1\n",
      "landed:\t\t1\n",
      "children:\t\t1\n",
      "terrifying:\t\t1\n",
      "barely:\t\t1\n",
      "mouths:\t\t1\n",
      "fulfill:\t\t1\n",
      "thrust:\t\t1\n",
      "foam:\t\t1\n",
      "cup:\t\t1\n",
      "ramen:\t\t1\n",
      "noodles:\t\t1\n",
      "desire:\t\t1\n",
      "alternate:\t\t1\n",
      "paths:\t\t1\n",
      "commensurate:\t\t1\n",
      "struggling:\t\t1\n",
      "spin:\t\t1\n",
      "banking:\t\t1\n",
      "impacts:\t\t1\n",
      "materially:\t\t1\n",
      "rationally:\t\t1\n",
      "tiny:\t\t1\n",
      "proceeds:\t\t1\n",
      "answered:\t\t1\n",
      "aversion:\t\t1\n",
      "awards:\t\t1\n",
      "wondered:\t\t1\n",
      "chasing:\t\t1\n",
      "proverbial:\t\t1\n",
      "doubting:\t\t1\n",
      "thrived:\t\t1\n",
      "dead:\t\t1\n",
      "difficulty:\t\t1\n",
      "promoted:\t\t1\n",
      "lobbying:\t\t1\n",
      "quantify:\t\t1\n",
      "mitigate:\t\t1\n",
      "suite:\t\t1\n",
      "attaining:\t\t1\n",
      "millionaire:\t\t1\n",
      "liked:\t\t1\n",
      "respected:\t\t1\n",
      "formed:\t\t1\n",
      "bonds:\t\t1\n",
      "president:\t\t1\n",
      "respect:\t\t1\n",
      "guts:\t\t1\n",
      "miles:\t\t1\n",
      "minded:\t\t1\n",
      "multiple:\t\t1\n",
      "filled:\t\t1\n",
      "accomplishments:\t\t1\n",
      "withhold:\t\t1\n",
      "specialist:\t\t1\n",
      "marketer:\t\t1\n",
      "paralegal:\t\t1\n",
      "arranging:\t\t1\n",
      "hassle:\t\t1\n",
      "switch:\t\t1\n",
      "super:\t\t1\n",
      "cheapest:\t\t1\n",
      "hats:\t\t1\n",
      "css:\t\t1\n",
      "similarly:\t\t1\n",
      "hopes:\t\t1\n",
      "happier:\t\t1\n",
      "passive:\t\t1\n",
      "beautiful:\t\t1\n",
      "disproportionate:\t\t1\n",
      "smarter:\t\t1\n",
      "promote:\t\t1\n",
      "ratio:\t\t1\n",
      "presumably:\t\t1\n",
      "faceless:\t\t1\n",
      "fruits:\t\t1\n",
      "returns:\t\t1\n",
      "401:\t\t1\n",
      "k:\t\t1\n",
      "cooperation:\t\t1\n",
      "committed:\t\t1\n",
      "de:\t\t1\n",
      "prioritize:\t\t1\n",
      "warning:\t\t1\n",
      "teammates:\t\t1\n",
      "derail:\t\t1\n",
      "frustrating:\t\t1\n",
      "failing:\t\t1\n",
      "inaction:\t\t1\n",
      "20081:\t\t1\n",
      "68:\t\t1\n",
      "hinges:\t\t1\n",
      "fault:\t\t1\n",
      "screw:\t\t1\n",
      "scares:\t\t1\n",
      "mile:\t\t1\n",
      "years2:\t\t1\n",
      "17:\t\t1\n",
      "years3:\t\t1\n",
      "lifetime:\t\t1\n",
      "killed:\t\t1\n",
      "motor:\t\t1\n",
      "vehicle:\t\t1\n",
      "1124:\t\t1\n",
      "injury:\t\t1\n",
      "draining:\t\t1\n",
      "hallway:\t\t1\n",
      "rush:\t\t1\n",
      "kiss:\t\t1\n",
      "goodbye:\t\t1\n",
      "relaxing:\t\t1\n",
      "recharging:\t\t1\n",
      "hobbies:\t\t1\n",
      "reliever:\t\t1\n",
      "gas:\t\t1\n",
      "parking:\t\t1\n",
      "tolls:\t\t1\n",
      "fares:\t\t1\n",
      "chances:\t\t1\n",
      "san:\t\t1\n",
      "jose:\t\t1\n",
      "area5:\t\t1\n",
      "49:\t\t1\n",
      "average6:\t\t1\n",
      "six:\t\t1\n",
      "austin:\t\t1\n",
      "texas:\t\t1\n",
      "discretionary:\t\t1\n",
      "do7:\t\t1\n",
      "nicer:\t\t1\n",
      "conducted:\t\t1\n",
      "desirable:\t\t1\n",
      "opens:\t\t1\n",
      "kick:\t\t1\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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      "person:\t\t19\n",
      "doesn:\t\t19\n",
      "show:\t\t19\n",
      "physical:\t\t19\n",
      "com:\t\t19\n",
      "hire:\t\t20\n",
      "attention:\t\t20\n",
      "dollars:\t\t20\n",
      "ones:\t\t20\n",
      "terms:\t\t20\n",
      "around:\t\t20\n",
      "usually:\t\t20\n",
      "aren:\t\t20\n",
      "ask:\t\t20\n",
      "term:\t\t20\n",
      "sort:\t\t20\n",
      "contractors:\t\t20\n",
      "services:\t\t20\n",
      "benefits:\t\t20\n",
      "example:\t\t20\n",
      "niche:\t\t20\n",
      "facebook:\t\t20\n",
      "developing:\t\t21\n",
      "quit:\t\t21\n",
      "costs:\t\t21\n",
      "spent:\t\t21\n",
      "place:\t\t21\n",
      "available:\t\t21\n",
      "grow:\t\t21\n",
      "down:\t\t21\n",
      "different:\t\t21\n",
      "whether:\t\t21\n",
      "action:\t\t21\n",
      "click:\t\t21\n",
      "campaign:\t\t21\n",
      "later:\t\t22\n",
      "focus:\t\t22\n",
      "learn:\t\t22\n",
      "paying:\t\t22\n",
      "extra:\t\t22\n",
      "problem:\t\t22\n",
      "found:\t\t22\n",
      "able:\t\t22\n",
      "list:\t\t22\n",
      "name:\t\t22\n",
      "campaigns:\t\t23\n",
      "metrics:\t\t23\n",
      "got:\t\t23\n",
      "anything:\t\t23\n",
      "off:\t\t23\n",
      "feel:\t\t23\n",
      "already:\t\t23\n",
      "us:\t\t23\n",
      "say:\t\t23\n",
      "10:\t\t23\n",
      "months:\t\t23\n",
      "paid:\t\t23\n",
      "remember:\t\t23\n",
      "care:\t\t24\n",
      "sundog:\t\t24\n",
      "income:\t\t24\n",
      "success:\t\t24\n",
      "result:\t\t24\n",
      "world:\t\t24\n",
      "000:\t\t24\n",
      "insurance:\t\t24\n",
      "right:\t\t24\n",
      "build:\t\t24\n",
      "provide:\t\t24\n",
      "needs:\t\t24\n",
      "data:\t\t24\n",
      "launch:\t\t24\n",
      "making:\t\t25\n",
      "why:\t\t25\n",
      "live:\t\t25\n",
      "results:\t\t25\n",
      "using:\t\t25\n",
      "week:\t\t25\n",
      "been:\t\t25\n",
      "trying:\t\t25\n",
      "less:\t\t25\n",
      "information:\t\t25\n",
      "internet:\t\t26\n",
      "consider:\t\t26\n",
      "case:\t\t26\n",
      "often:\t\t26\n",
      "family:\t\t26\n",
      "another:\t\t26\n",
      "set:\t\t26\n",
      "effort:\t\t26\n",
      "whatever:\t\t26\n",
      "perhaps:\t\t26\n",
      "likely:\t\t26\n",
      "ideas:\t\t27\n",
      "measure:\t\t27\n",
      "successful:\t\t27\n",
      "home:\t\t27\n",
      "never:\t\t27\n",
      "living:\t\t27\n",
      "run:\t\t27\n",
      "isn:\t\t27\n",
      "full:\t\t27\n",
      "initial:\t\t27\n",
      "similar:\t\t27\n",
      "relevant:\t\t27\n",
      "because:\t\t28\n",
      "too:\t\t28\n",
      "done:\t\t28\n",
      "look:\t\t28\n",
      "___:\t\t28\n",
      "tax:\t\t29\n",
      "little:\t\t29\n",
      "same:\t\t29\n",
      "must:\t\t29\n",
      "had:\t\t29\n",
      "thing:\t\t29\n",
      "office:\t\t29\n",
      "here:\t\t29\n",
      "offer:\t\t29\n",
      "having:\t\t30\n",
      "side:\t\t30\n",
      "m:\t\t30\n",
      "means:\t\t30\n",
      "possible:\t\t30\n",
      "come:\t\t30\n",
      "does:\t\t30\n",
      "large:\t\t30\n",
      "account:\t\t30\n",
      "adwords:\t\t30\n",
      "career:\t\t31\n",
      "life:\t\t31\n",
      "give:\t\t31\n",
      "real:\t\t31\n",
      "getting:\t\t31\n",
      "least:\t\t31\n",
      "sell:\t\t31\n",
      "companies:\t\t31\n",
      "websites:\t\t31\n",
      "every:\t\t32\n",
      "let:\t\t32\n",
      "order:\t\t32\n",
      "actually:\t\t32\n",
      "easy:\t\t32\n",
      "talk:\t\t32\n",
      "being:\t\t32\n",
      "release:\t\t32\n",
      "building:\t\t33\n",
      "part:\t\t33\n",
      "else:\t\t33\n",
      "email:\t\t33\n",
      "after:\t\t33\n",
      "traffic:\t\t33\n",
      "selling:\t\t33\n",
      "me:\t\t34\n",
      "back:\t\t34\n",
      "per:\t\t34\n",
      "health:\t\t35\n",
      "hours:\t\t35\n",
      "understand:\t\t35\n",
      "web:\t\t35\n",
      "free:\t\t35\n",
      "specific:\t\t35\n",
      "social:\t\t36\n",
      "however:\t\t36\n",
      "would:\t\t36\n",
      "its:\t\t36\n",
      "which:\t\t37\n",
      "point:\t\t37\n",
      "instead:\t\t37\n",
      "others:\t\t37\n",
      "potential:\t\t38\n",
      "years:\t\t38\n",
      "employed:\t\t38\n",
      "things:\t\t38\n",
      "expenses:\t\t38\n",
      "site:\t\t38\n",
      "worth:\t\t39\n",
      "growth:\t\t39\n",
      "book:\t\t39\n",
      "were:\t\t39\n",
      "won:\t\t39\n",
      "local:\t\t39\n",
      "without:\t\t40\n",
      "few:\t\t40\n",
      "has:\t\t40\n",
      "freedom:\t\t41\n",
      "advertising:\t\t41\n",
      "number:\t\t41\n",
      "customer:\t\t41\n",
      "big:\t\t42\n",
      "marketing:\t\t42\n",
      "page:\t\t42\n",
      "keep:\t\t42\n",
      "really:\t\t42\n",
      "we:\t\t43\n",
      "while:\t\t43\n",
      "spend:\t\t43\n",
      "such:\t\t43\n",
      "press:\t\t43\n",
      "lifestyle:\t\t44\n",
      "employer:\t\t44\n",
      "advice:\t\t44\n",
      "revenue:\t\t44\n",
      "start:\t\t44\n",
      "best:\t\t44\n",
      "go:\t\t45\n",
      "pay:\t\t45\n",
      "create:\t\t45\n",
      "could:\t\t46\n",
      "hard:\t\t47\n",
      "try:\t\t47\n",
      "small:\t\t47\n",
      "businesses:\t\t47\n",
      "long:\t\t47\n",
      "personal:\t\t48\n",
      "now:\t\t48\n",
      "see:\t\t48\n",
      "end:\t\t49\n",
      "better:\t\t49\n",
      "year:\t\t49\n",
      "online:\t\t50\n",
      "help:\t\t50\n",
      "doing:\t\t51\n",
      "first:\t\t51\n",
      "know:\t\t52\n",
      "where:\t\t53\n",
      "cost:\t\t53\n",
      "way:\t\t55\n",
      "take:\t\t55\n",
      "going:\t\t55\n",
      "lot:\t\t55\n",
      "search:\t\t56\n",
      "something:\t\t56\n",
      "through:\t\t57\n",
      "very:\t\t58\n",
      "working:\t\t58\n",
      "think:\t\t58\n",
      "important:\t\t58\n",
      "use:\t\t58\n",
      "enough:\t\t59\n",
      "once:\t\t59\n",
      "then:\t\t59\n",
      "software:\t\t60\n",
      "idea:\t\t60\n",
      "someone:\t\t62\n",
      "over:\t\t62\n",
      "any:\t\t62\n",
      "google:\t\t63\n",
      "plan:\t\t64\n",
      "sure:\t\t65\n",
      "still:\t\t65\n",
      "market:\t\t66\n",
      "well:\t\t66\n",
      "products:\t\t67\n",
      "those:\t\t68\n",
      "should:\t\t69\n",
      "before:\t\t70\n",
      "most:\t\t70\n",
      "might:\t\t70\n",
      "ad:\t\t70\n",
      "many:\t\t71\n",
      "good:\t\t72\n",
      "day:\t\t73\n",
      "employment:\t\t75\n",
      "ads:\t\t75\n",
      "no:\t\t76\n",
      "probably:\t\t76\n",
      "yourself:\t\t78\n",
      "other:\t\t78\n",
      "like:\t\t78\n",
      "only:\t\t79\n",
      "into:\t\t79\n",
      "sales:\t\t80\n",
      "find:\t\t81\n",
      "these:\t\t82\n",
      "was:\t\t85\n",
      "money:\t\t86\n",
      "who:\t\t88\n",
      "job:\t\t90\n",
      "much:\t\t90\n",
      "also:\t\t91\n",
      "than:\t\t92\n",
      "ve:\t\t95\n",
      "one:\t\t100\n",
      "when:\t\t102\n",
      "even:\t\t104\n",
      "may:\t\t107\n",
      "make:\t\t108\n",
      "website:\t\t109\n",
      "self:\t\t111\n",
      "ll:\t\t114\n",
      "some:\t\t121\n",
      "by:\t\t122\n",
      "want:\t\t122\n",
      "company:\t\t122\n",
      "their:\t\t122\n",
      "get:\t\t123\n",
      "customers:\t\t123\n",
      "don:\t\t133\n",
      "all:\t\t137\n",
      "own:\t\t140\n",
      "just:\t\t142\n",
      "so:\t\t143\n",
      "work:\t\t144\n",
      "people:\t\t145\n",
      "new:\t\t153\n",
      "out:\t\t161\n",
      "there:\t\t162\n",
      "how:\t\t163\n",
      "them:\t\t166\n",
      "from:\t\t166\n",
      "need:\t\t174\n",
      "up:\t\t177\n",
      "an:\t\t178\n",
      "product:\t\t182\n",
      "more:\t\t200\n",
      "about:\t\t202\n",
      "not:\t\t203\n",
      "do:\t\t207\n",
      "re:\t\t214\n",
      "my:\t\t215\n",
      "at:\t\t220\n",
      "what:\t\t229\n",
      "will:\t\t231\n",
      "they:\t\t234\n",
      "but:\t\t242\n",
      "time:\t\t255\n",
      "or:\t\t278\n",
      "this:\t\t280\n",
      "t:\t\t301\n",
      "with:\t\t315\n",
      "have:\t\t321\n",
      "as:\t\t343\n",
      "be:\t\t369\n",
      "can:\t\t376\n",
      "business:\t\t383\n",
      "i:\t\t387\n",
      "s:\t\t391\n",
      "if:\t\t411\n",
      "are:\t\t424\n",
      "on:\t\t428\n",
      "for:\t\t537\n",
      "is:\t\t560\n",
      "in:\t\t616\n",
      "it:\t\t649\n",
      "that:\t\t747\n",
      "and:\t\t934\n",
      "of:\t\t970\n",
      "a:\t\t1191\n",
      "the:\t\t1292\n",
      "your:\t\t1420\n",
      "to:\t\t1828\n",
      "you:\t\t1878\n"
     ]
    }
   ],
   "source": [
    "results = wordCountsSorted.collect()\n",
    "for result in results:\n",
    "    count = str(result[0])\n",
    "    word = result[1].encode('ascii', 'ignore')\n",
    "    if (word):\n",
    "        print(word.decode() + ':\\t\\t' + count)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "sc.stop()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pyspark import SparkConf, SparkContext\n",
    "\n",
    "conf = SparkConf().setMaster('local').setAppName('SpendByCustomer')\n",
    "sc = SparkContext(conf = conf)\n",
    "\n",
    "def parseLine(line):\n",
    "    fields = line.split(',')\n",
    "    return (int(fields[0]), float(fields[2]))\n",
    "\n",
    "lines = sc.textFile('customer-orders.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['44,8602,37.19', '35,5368,65.89', '2,3391,40.64']"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lines.take(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(44, 37.19), (35, 65.89), (2, 40.64)]"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rdd = lines.map(parseLine)\n",
    "rdd.take(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(44, 4756.8899999999985), (35, 5155.419999999999), (2, 5994.59)]"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "totalByCustomer = rdd.reduceByKey(lambda x, y: x+y)\n",
    "totalByCustomer.take(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(44, 4756.8899999999985)\n",
      "(35, 5155.419999999999)\n",
      "(2, 5994.59)\n",
      "(47, 4316.299999999999)\n",
      "(29, 5032.529999999999)\n",
      "(91, 4642.259999999999)\n",
      "(70, 5368.249999999999)\n",
      "(85, 5503.43)\n",
      "(53, 4945.299999999999)\n",
      "(14, 4735.030000000001)\n",
      "(51, 4975.22)\n",
      "(42, 5696.840000000003)\n",
      "(79, 3790.570000000001)\n",
      "(50, 4517.27)\n",
      "(20, 4836.859999999999)\n",
      "(15, 5413.510000000001)\n",
      "(5, 4561.069999999999)\n",
      "(48, 4384.33)\n",
      "(31, 4765.05)\n",
      "(4, 4815.050000000002)\n",
      "(36, 4278.049999999997)\n",
      "(57, 4628.4)\n",
      "(12, 4664.589999999998)\n",
      "(22, 5019.449999999999)\n",
      "(54, 6065.389999999999)\n",
      "(0, 5524.949999999998)\n",
      "(88, 4830.549999999999)\n",
      "(86, 4908.81)\n",
      "(13, 4367.62)\n",
      "(40, 5186.429999999999)\n",
      "(98, 4297.260000000001)\n",
      "(55, 5298.090000000002)\n",
      "(95, 4876.840000000002)\n",
      "(61, 5497.479999999998)\n",
      "(27, 4915.889999999999)\n",
      "(78, 4524.509999999999)\n",
      "(83, 4635.799999999997)\n",
      "(6, 5397.879999999998)\n",
      "(26, 5250.4)\n",
      "(75, 4178.500000000001)\n",
      "(25, 5057.610000000001)\n",
      "(71, 5995.660000000003)\n",
      "(39, 6193.109999999999)\n",
      "(60, 5040.709999999999)\n",
      "(97, 5977.189999999995)\n",
      "(7, 4755.070000000001)\n",
      "(21, 4707.41)\n",
      "(69, 5123.010000000001)\n",
      "(37, 4735.200000000002)\n",
      "(1, 4958.600000000001)\n",
      "(64, 5288.689999999996)\n",
      "(82, 4812.489999999998)\n",
      "(72, 5337.44)\n",
      "(99, 4172.289999999998)\n",
      "(34, 5330.8)\n",
      "(73, 6206.199999999999)\n",
      "(49, 4394.599999999999)\n",
      "(8, 5517.240000000001)\n",
      "(46, 5963.109999999999)\n",
      "(23, 4042.6499999999987)\n",
      "(19, 5059.4299999999985)\n",
      "(65, 5140.3499999999985)\n",
      "(80, 4727.860000000001)\n",
      "(16, 4979.06)\n",
      "(9, 5322.649999999999)\n",
      "(18, 4921.27)\n",
      "(59, 5642.89)\n",
      "(74, 4647.129999999999)\n",
      "(30, 4990.72)\n",
      "(56, 4701.019999999999)\n",
      "(90, 5290.409999999998)\n",
      "(68, 6375.449999999997)\n",
      "(11, 5152.290000000002)\n",
      "(10, 4819.700000000001)\n",
      "(41, 5637.62)\n",
      "(58, 5437.7300000000005)\n",
      "(87, 5206.4)\n",
      "(17, 5032.679999999999)\n",
      "(33, 5254.659999999998)\n",
      "(62, 5253.3200000000015)\n",
      "(92, 5379.280000000002)\n",
      "(76, 4904.209999999999)\n",
      "(66, 4681.919999999999)\n",
      "(43, 5368.83)\n",
      "(52, 5245.059999999999)\n",
      "(77, 4327.729999999999)\n",
      "(81, 5112.709999999999)\n",
      "(84, 4652.939999999999)\n",
      "(3, 4659.63)\n",
      "(93, 5265.750000000001)\n",
      "(89, 4851.479999999999)\n",
      "(45, 3309.38)\n",
      "(24, 5259.920000000003)\n",
      "(96, 3924.230000000001)\n",
      "(67, 4505.79)\n",
      "(63, 5415.150000000001)\n",
      "(94, 4475.569999999999)\n",
      "(32, 5496.050000000004)\n",
      "(38, 4898.460000000002)\n",
      "(28, 5000.709999999998)\n"
     ]
    }
   ],
   "source": [
    "results = totalByCustomer.collect()\n",
    "for result in results:\n",
    "    print(result)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "sc.stop()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pyspark import SparkConf, SparkContext\n",
    "\n",
    "conf = SparkConf().setMaster('local').setAppName('SpendByCustomerSorted')\n",
    "sc = SparkContext(conf = conf)\n",
    "\n",
    "def parseLine(line):\n",
    "    fields = line.split(',')\n",
    "    return (int(fields[0]), float(fields[2]))\n",
    "\n",
    "lines = sc.textFile('customer-orders.csv')\n",
    "rdd = lines.map(parseLine)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(44, 37.19), (35, 65.89), (2, 40.64)]"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rdd.take(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(44, 4756.8899999999985), (35, 5155.419999999999), (2, 5994.59)]"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "totalByCustomer = rdd.reduceByKey(lambda x, y: x + y)\n",
    "totalByCustomer.take(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(4756.8899999999985, 44), (5155.419999999999, 35), (5994.59, 2)]"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "flipped = totalByCustomer.map(lambda x: (x[1], x[0]))\n",
    "flipped.take(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(3309.38, 45), (3790.570000000001, 79), (3924.230000000001, 96)]"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "totalByCustomerSorted = flipped.sortByKey()\n",
    "totalByCustomerSorted.take(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(3309.38, 45)\n",
      "(3790.570000000001, 79)\n",
      "(3924.230000000001, 96)\n",
      "(4042.6499999999987, 23)\n",
      "(4172.289999999998, 99)\n",
      "(4178.500000000001, 75)\n",
      "(4278.049999999997, 36)\n",
      "(4297.260000000001, 98)\n",
      "(4316.299999999999, 47)\n",
      "(4327.729999999999, 77)\n",
      "(4367.62, 13)\n",
      "(4384.33, 48)\n",
      "(4394.599999999999, 49)\n",
      "(4475.569999999999, 94)\n",
      "(4505.79, 67)\n",
      "(4517.27, 50)\n",
      "(4524.509999999999, 78)\n",
      "(4561.069999999999, 5)\n",
      "(4628.4, 57)\n",
      "(4635.799999999997, 83)\n",
      "(4642.259999999999, 91)\n",
      "(4647.129999999999, 74)\n",
      "(4652.939999999999, 84)\n",
      "(4659.63, 3)\n",
      "(4664.589999999998, 12)\n",
      "(4681.919999999999, 66)\n",
      "(4701.019999999999, 56)\n",
      "(4707.41, 21)\n",
      "(4727.860000000001, 80)\n",
      "(4735.030000000001, 14)\n",
      "(4735.200000000002, 37)\n",
      "(4755.070000000001, 7)\n",
      "(4756.8899999999985, 44)\n",
      "(4765.05, 31)\n",
      "(4812.489999999998, 82)\n",
      "(4815.050000000002, 4)\n",
      "(4819.700000000001, 10)\n",
      "(4830.549999999999, 88)\n",
      "(4836.859999999999, 20)\n",
      "(4851.479999999999, 89)\n",
      "(4876.840000000002, 95)\n",
      "(4898.460000000002, 38)\n",
      "(4904.209999999999, 76)\n",
      "(4908.81, 86)\n",
      "(4915.889999999999, 27)\n",
      "(4921.27, 18)\n",
      "(4945.299999999999, 53)\n",
      "(4958.600000000001, 1)\n",
      "(4975.22, 51)\n",
      "(4979.06, 16)\n",
      "(4990.72, 30)\n",
      "(5000.709999999998, 28)\n",
      "(5019.449999999999, 22)\n",
      "(5032.529999999999, 29)\n",
      "(5032.679999999999, 17)\n",
      "(5040.709999999999, 60)\n",
      "(5057.610000000001, 25)\n",
      "(5059.4299999999985, 19)\n",
      "(5112.709999999999, 81)\n",
      "(5123.010000000001, 69)\n",
      "(5140.3499999999985, 65)\n",
      "(5152.290000000002, 11)\n",
      "(5155.419999999999, 35)\n",
      "(5186.429999999999, 40)\n",
      "(5206.4, 87)\n",
      "(5245.059999999999, 52)\n",
      "(5250.4, 26)\n",
      "(5253.3200000000015, 62)\n",
      "(5254.659999999998, 33)\n",
      "(5259.920000000003, 24)\n",
      "(5265.750000000001, 93)\n",
      "(5288.689999999996, 64)\n",
      "(5290.409999999998, 90)\n",
      "(5298.090000000002, 55)\n",
      "(5322.649999999999, 9)\n",
      "(5330.8, 34)\n",
      "(5337.44, 72)\n",
      "(5368.249999999999, 70)\n",
      "(5368.83, 43)\n",
      "(5379.280000000002, 92)\n",
      "(5397.879999999998, 6)\n",
      "(5413.510000000001, 15)\n",
      "(5415.150000000001, 63)\n",
      "(5437.7300000000005, 58)\n",
      "(5496.050000000004, 32)\n",
      "(5497.479999999998, 61)\n",
      "(5503.43, 85)\n",
      "(5517.240000000001, 8)\n",
      "(5524.949999999998, 0)\n",
      "(5637.62, 41)\n",
      "(5642.89, 59)\n",
      "(5696.840000000003, 42)\n",
      "(5963.109999999999, 46)\n",
      "(5977.189999999995, 97)\n",
      "(5994.59, 2)\n",
      "(5995.660000000003, 71)\n",
      "(6065.389999999999, 54)\n",
      "(6193.109999999999, 39)\n",
      "(6206.199999999999, 73)\n",
      "(6375.449999999997, 68)\n"
     ]
    }
   ],
   "source": [
    "results = totalByCustomerSorted.collect()\n",
    "for result in results:\n",
    "    print(result)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [],
   "source": [
    "sc.stop()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['196\\t242\\t3\\t881250949', '186\\t302\\t3\\t891717742', '22\\t377\\t1\\t878887116']"
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from pyspark import SparkConf, SparkContext\n",
    "\n",
    "conf = SparkConf().setMaster('local').setAppName('RatingsHistogram')\n",
    "sc = SparkContext(conf = conf)\n",
    "\n",
    "lines = sc.textFile('u.data')\n",
    "lines.take(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['3', '3', '1']"
      ]
     },
     "execution_count": 103,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ratings = lines.map(lambda x: x.split()[2])\n",
    "ratings.take(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "defaultdict(int, {'1': 6110, '2': 11370, '3': 27145, '4': 34174, '5': 21201})"
      ]
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result = ratings.countByValue()\n",
    "result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1 6110\n",
      "2 11370\n",
      "3 27145\n",
      "4 34174\n",
      "5 21201\n"
     ]
    }
   ],
   "source": [
    "import collections\n",
    "sortedResults = collections.OrderedDict(sorted(result.items()))\n",
    "for key, value in sortedResults.items():\n",
    "    print('%s %i' % (key, value))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [],
   "source": [
    "sc.stop()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['196\\t242\\t3\\t881250949', '186\\t302\\t3\\t891717742', '22\\t377\\t1\\t878887116']"
      ]
     },
     "execution_count": 112,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from pyspark import SparkConf, SparkContext\n",
    "conf = SparkConf().setMaster('local').setAppName('PopularMovies')\n",
    "sc = SparkContext(conf = conf)\n",
    "\n",
    "lines = sc.textFile('u.data')\n",
    "lines.take(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(242, 1), (302, 1), (377, 1)]"
      ]
     },
     "execution_count": 122,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movies = lines.map(lambda x: (int(x.split()[1]), 1))\n",
    "movies.take(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(242, 117), (302, 297), (377, 13)]"
      ]
     },
     "execution_count": 123,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movieCounts = movies.reduceByKey(lambda x, y: x + y)\n",
    "movieCounts.take(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(117, 242), (297, 302), (13, 377)]"
      ]
     },
     "execution_count": 130,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "flipped = movieCounts.map(lambda x: (x[1], x[0]))\n",
    "flipped.take(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(1, 1348), (1, 1320), (1, 1492)]"
      ]
     },
     "execution_count": 131,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sortedMovies = flipped.sortByKey()\n",
    "sortedMovies.take(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1, 1348)\n",
      "(1, 1320)\n",
      "(1, 1492)\n",
      "(1, 1364)\n",
      "(1, 1493)\n",
      "(1, 830)\n",
      "(1, 1498)\n",
      "(1, 814)\n",
      "(1, 1520)\n",
      "(1, 711)\n",
      "(1, 1373)\n",
      "(1, 1309)\n",
      "(1, 857)\n",
      "(1, 1236)\n",
      "(1, 1310)\n",
      "(1, 1536)\n",
      "(1, 1582)\n",
      "(1, 1343)\n",
      "(1, 1457)\n",
      "(1, 1543)\n",
      "(1, 599)\n",
      "(1, 1458)\n",
      "(1, 1561)\n",
      "(1, 1533)\n",
      "(1, 1565)\n",
      "(1, 1563)\n",
      "(1, 1156)\n",
      "(1, 1505)\n",
      "(1, 852)\n",
      "(1, 1557)\n",
      "(1, 1562)\n",
      "(1, 1586)\n",
      "(1, 1476)\n",
      "(1, 1580)\n",
      "(1, 1363)\n",
      "(1, 1339)\n",
      "(1, 1566)\n",
      "(1, 1349)\n",
      "(1, 1447)\n",
      "(1, 1235)\n",
      "(1, 1587)\n",
      "(1, 677)\n",
      "(1, 1571)\n",
      "(1, 1575)\n",
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      "(1, 1616)\n",
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      "(1, 1596)\n",
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      "(1, 1525)\n",
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      "(1, 1601)\n",
      "(1, 1583)\n",
      "(1, 1624)\n",
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      "(1, 1614)\n",
      "(1, 1570)\n",
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      "(1, 1572)\n",
      "(1, 1653)\n",
      "(1, 1452)\n",
      "(1, 1595)\n",
      "(1, 1548)\n",
      "(1, 1655)\n",
      "(1, 1654)\n",
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      "(1, 1657)\n",
      "(1, 1650)\n",
      "(1, 1660)\n",
      "(1, 1661)\n",
      "(1, 1515)\n",
      "(1, 1621)\n",
      "(1, 1632)\n",
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      "(1, 1647)\n",
      "(1, 1581)\n",
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      "(1, 1613)\n",
      "(1, 1130)\n",
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      "(1, 1494)\n",
      "(1, 1673)\n",
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      "(1, 1577)\n",
      "(1, 1666)\n",
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      "(1, 1567)\n",
      "(1, 1122)\n",
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      "(1, 1625)\n",
      "(1, 1665)\n",
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      "(1, 1636)\n",
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      "(2, 1550)\n",
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      "(2, 1290)\n",
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      "(2, 1590)\n",
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      "(2, 957)\n",
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      "(2, 600)\n",
      "(2, 1585)\n",
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      "(2, 1502)\n",
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      "(2, 1491)\n",
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      "(2, 1629)\n",
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      "(2, 1611)\n",
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      "(5, 439)\n",
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      "(5, 1392)\n",
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      "(5, 1470)\n",
      "(5, 1406)\n",
      "(5, 1501)\n",
      "(5, 1333)\n",
      "(5, 1138)\n",
      "(5, 920)\n",
      "(5, 1592)\n",
      "(5, 1496)\n",
      "(5, 1597)\n",
      "(5, 1431)\n",
      "(5, 666)\n",
      "(5, 1511)\n",
      "(5, 1440)\n",
      "(5, 799)\n",
      "(5, 1509)\n",
      "(6, 927)\n",
      "(6, 1216)\n",
      "(6, 1383)\n",
      "(6, 1164)\n",
      "(6, 1250)\n",
      "(6, 1322)\n",
      "(6, 867)\n",
      "(6, 1328)\n",
      "(6, 1241)\n",
      "(6, 1212)\n",
      "(6, 1386)\n",
      "(6, 1213)\n",
      "(6, 1083)\n",
      "(6, 1368)\n",
      "(6, 1466)\n",
      "(6, 1247)\n",
      "(6, 1388)\n",
      "(6, 1405)\n",
      "(6, 706)\n",
      "(6, 668)\n",
      "(6, 1534)\n",
      "(6, 1454)\n",
      "(6, 891)\n",
      "(6, 1395)\n",
      "(6, 1591)\n",
      "(6, 1237)\n",
      "(6, 296)\n",
      "(6, 1512)\n",
      "(6, 1287)\n",
      "(6, 1412)\n",
      "(6, 1468)\n",
      "(6, 1355)\n",
      "(6, 1326)\n",
      "(6, 1598)\n",
      "(6, 438)\n",
      "(6, 1205)\n",
      "(6, 1474)\n",
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      "(66, 452)\n",
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      "(66, 790)\n",
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      "(66, 207)\n",
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      "(76, 778)\n",
      "(77, 295)\n",
      "(77, 676)\n",
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      "(78, 287)\n",
      "(78, 736)\n",
      "(79, 658)\n",
      "(79, 44)\n",
      "(79, 696)\n",
      "(79, 710)\n",
      "(79, 584)\n",
      "(80, 930)\n",
      "(80, 312)\n",
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      "(80, 530)\n",
      "(80, 45)\n",
      "(80, 519)\n",
      "(81, 51)\n",
      "(81, 32)\n",
      "(81, 604)\n",
      "(81, 873)\n",
      "(81, 49)\n",
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      "(81, 420)\n",
      "(82, 625)\n",
      "(82, 662)\n",
      "(82, 640)\n",
      "(82, 823)\n",
      "(82, 717)\n",
      "(82, 152)\n",
      "(82, 63)\n",
      "(83, 59)\n",
      "(83, 825)\n",
      "(84, 21)\n",
      "(84, 781)\n",
      "(85, 465)\n",
      "(85, 280)\n",
      "(85, 425)\n",
      "(85, 448)\n",
      "(85, 924)\n",
      "(86, 5)\n",
      "(86, 673)\n",
      "(86, 720)\n",
      "(86, 864)\n",
      "(86, 792)\n",
      "(86, 988)\n",
      "(87, 715)\n",
      "(87, 305)\n",
      "(87, 39)\n",
      "(87, 386)\n",
      "(87, 689)\n",
      "(88, 661)\n",
      "(89, 201)\n",
      "(89, 518)\n",
      "(89, 10)\n",
      "(89, 642)\n",
      "(89, 399)\n",
      "(90, 3)\n",
      "(90, 1039)\n",
      "(90, 506)\n",
      "(90, 652)\n",
      "(90, 458)\n",
      "(91, 338)\n",
      "(91, 52)\n",
      "(91, 831)\n",
      "(91, 517)\n",
      "(91, 693)\n",
      "(91, 636)\n",
      "(92, 212)\n",
      "(92, 163)\n",
      "(92, 17)\n",
      "(92, 744)\n",
      "(92, 578)\n",
      "(92, 549)\n",
      "(93, 576)\n",
      "(93, 430)\n",
      "(93, 820)\n",
      "(93, 412)\n",
      "(93, 1011)\n",
      "(93, 529)\n",
      "(95, 477)\n",
      "(95, 131)\n",
      "(95, 90)\n",
      "(96, 919)\n",
      "(96, 755)\n",
      "(96, 306)\n",
      "(96, 290)\n",
      "(97, 33)\n",
      "(97, 126)\n",
      "(97, 429)\n",
      "(97, 356)\n",
      "(98, 1014)\n",
      "(98, 507)\n",
      "(98, 155)\n",
      "(99, 436)\n",
      "(100, 381)\n",
      "(100, 665)\n",
      "(100, 682)\n",
      "(100, 1012)\n",
      "(101, 232)\n",
      "(101, 264)\n",
      "(101, 378)\n",
      "(101, 404)\n",
      "(101, 926)\n",
      "(101, 708)\n",
      "(101, 159)\n",
      "(102, 317)\n",
      "(102, 554)\n",
      "(102, 699)\n",
      "(102, 747)\n",
      "(103, 67)\n",
      "(104, 54)\n",
      "(104, 478)\n",
      "(104, 709)\n",
      "(104, 92)\n",
      "(104, 928)\n",
      "(105, 136)\n",
      "(106, 122)\n",
      "(106, 421)\n",
      "(106, 162)\n",
      "(106, 895)\n",
      "(107, 679)\n",
      "(108, 470)\n",
      "(109, 225)\n",
      "(110, 81)\n",
      "(111, 219)\n",
      "(111, 382)\n",
      "(112, 815)\n",
      "(112, 408)\n",
      "(112, 93)\n",
      "(112, 316)\n",
      "(113, 331)\n",
      "(114, 29)\n",
      "(114, 214)\n",
      "(114, 292)\n",
      "(115, 65)\n",
      "(115, 762)\n",
      "(115, 659)\n",
      "(115, 123)\n",
      "(116, 184)\n",
      "(116, 663)\n",
      "(116, 380)\n",
      "(116, 192)\n",
      "(117, 242)\n",
      "(117, 48)\n",
      "(117, 449)\n",
      "(118, 169)\n",
      "(119, 746)\n",
      "(119, 631)\n",
      "(119, 866)\n",
      "(120, 217)\n",
      "(120, 38)\n",
      "(120, 521)\n",
      "(121, 509)\n",
      "(121, 447)\n",
      "(121, 510)\n",
      "(121, 428)\n",
      "(121, 528)\n",
      "(121, 170)\n",
      "(122, 504)\n",
      "(123, 501)\n",
      "(124, 246)\n",
      "(124, 526)\n",
      "(124, 750)\n",
      "(124, 520)\n",
      "(124, 343)\n",
      "(124, 190)\n",
      "(124, 233)\n",
      "(125, 485)\n",
      "(125, 178)\n",
      "(125, 324)\n",
      "(125, 116)\n",
      "(126, 346)\n",
      "(126, 473)\n",
      "(127, 198)\n",
      "(127, 62)\n",
      "(127, 291)\n",
      "(127, 596)\n",
      "(127, 157)\n",
      "(127, 260)\n",
      "(128, 241)\n",
      "(128, 756)\n",
      "(128, 325)\n",
      "(128, 53)\n",
      "(128, 73)\n",
      "(128, 148)\n",
      "(128, 482)\n",
      "(129, 531)\n",
      "(129, 129)\n",
      "(129, 418)\n",
      "(129, 72)\n",
      "(130, 109)\n",
      "(130, 249)\n",
      "(131, 2)\n",
      "(131, 657)\n",
      "(132, 243)\n",
      "(133, 47)\n",
      "(134, 68)\n",
      "(134, 303)\n",
      "(134, 1047)\n",
      "(134, 213)\n",
      "(136, 879)\n",
      "(136, 223)\n",
      "(136, 205)\n",
      "(136, 270)\n",
      "(137, 1016)\n",
      "(137, 559)\n",
      "(137, 177)\n",
      "(137, 347)\n",
      "(137, 705)\n",
      "(137, 94)\n",
      "(137, 735)\n",
      "(138, 484)\n",
      "(138, 87)\n",
      "(142, 231)\n",
      "(143, 332)\n",
      "(143, 91)\n",
      "(143, 358)\n",
      "(145, 455)\n",
      "(145, 310)\n",
      "(146, 281)\n",
      "(147, 293)\n",
      "(147, 654)\n",
      "(148, 1028)\n",
      "(148, 462)\n",
      "(148, 156)\n",
      "(148, 42)\n",
      "(149, 304)\n",
      "(149, 55)\n",
      "(149, 763)\n",
      "(150, 86)\n",
      "(150, 239)\n",
      "(151, 164)\n",
      "(151, 77)\n",
      "(151, 550)\n",
      "(152, 498)\n",
      "(153, 431)\n",
      "(153, 660)\n",
      "(154, 31)\n",
      "(155, 690)\n",
      "(156, 240)\n",
      "(157, 193)\n",
      "(157, 685)\n",
      "(157, 150)\n",
      "(158, 252)\n",
      "(158, 472)\n",
      "(160, 248)\n",
      "(160, 476)\n",
      "(160, 315)\n",
      "(161, 227)\n",
      "(162, 443)\n",
      "(162, 410)\n",
      "(162, 66)\n",
      "(162, 259)\n",
      "(162, 285)\n",
      "(163, 411)\n",
      "(164, 739)\n",
      "(164, 692)\n",
      "(164, 523)\n",
      "(165, 199)\n",
      "(166, 226)\n",
      "(168, 319)\n",
      "(168, 582)\n",
      "(169, 321)\n",
      "(169, 684)\n",
      "(169, 628)\n",
      "(170, 451)\n",
      "(170, 367)\n",
      "(170, 402)\n",
      "(170, 188)\n",
      "(171, 229)\n",
      "(171, 137)\n",
      "(171, 218)\n",
      "(171, 133)\n",
      "(171, 433)\n",
      "(171, 651)\n",
      "(172, 255)\n",
      "(172, 99)\n",
      "(173, 511)\n",
      "(174, 432)\n",
      "(174, 154)\n",
      "(174, 24)\n",
      "(175, 327)\n",
      "(175, 58)\n",
      "(175, 326)\n",
      "(176, 845)\n",
      "(176, 83)\n",
      "(177, 283)\n",
      "(178, 419)\n",
      "(178, 591)\n",
      "(179, 480)\n",
      "(179, 479)\n",
      "(179, 566)\n",
      "(180, 514)\n",
      "(180, 751)\n",
      "(180, 732)\n",
      "(182, 23)\n",
      "(182, 203)\n",
      "(183, 14)\n",
      "(184, 13)\n",
      "(185, 147)\n",
      "(187, 124)\n",
      "(188, 307)\n",
      "(189, 340)\n",
      "(190, 274)\n",
      "(191, 209)\n",
      "(192, 393)\n",
      "(193, 284)\n",
      "(194, 474)\n",
      "(194, 298)\n",
      "(195, 527)\n",
      "(197, 250)\n",
      "(198, 272)\n",
      "(198, 134)\n",
      "(199, 230)\n",
      "(200, 208)\n",
      "(201, 515)\n",
      "(201, 403)\n",
      "(202, 588)\n",
      "(206, 200)\n",
      "(206, 597)\n",
      "(206, 211)\n",
      "(208, 385)\n",
      "(208, 175)\n",
      "(209, 603)\n",
      "(209, 4)\n",
      "(209, 187)\n",
      "(211, 271)\n",
      "(212, 215)\n",
      "(213, 88)\n",
      "(215, 508)\n",
      "(216, 435)\n",
      "(217, 235)\n",
      "(218, 322)\n",
      "(219, 95)\n",
      "(219, 427)\n",
      "(219, 678)\n",
      "(219, 8)\n",
      "(220, 71)\n",
      "(220, 161)\n",
      "(221, 471)\n",
      "(221, 179)\n",
      "(221, 180)\n",
      "(222, 143)\n",
      "(223, 273)\n",
      "(226, 182)\n",
      "(227, 265)\n",
      "(227, 655)\n",
      "(230, 568)\n",
      "(230, 301)\n",
      "(231, 496)\n",
      "(232, 282)\n",
      "(236, 11)\n",
      "(239, 197)\n",
      "(239, 185)\n",
      "(240, 245)\n",
      "(240, 323)\n",
      "(241, 194)\n",
      "(243, 144)\n",
      "(243, 483)\n",
      "(244, 228)\n",
      "(244, 125)\n",
      "(246, 132)\n",
      "(247, 153)\n",
      "(250, 475)\n",
      "(251, 196)\n",
      "(251, 333)\n",
      "(251, 186)\n",
      "(251, 70)\n",
      "(254, 546)\n",
      "(255, 268)\n",
      "(256, 97)\n",
      "(256, 238)\n",
      "(259, 135)\n",
      "(259, 289)\n",
      "(261, 82)\n",
      "(264, 357)\n",
      "(267, 12)\n",
      "(267, 742)\n",
      "(268, 275)\n",
      "(272, 111)\n",
      "(275, 89)\n",
      "(276, 191)\n",
      "(276, 28)\n",
      "(280, 234)\n",
      "(280, 202)\n",
      "(283, 64)\n",
      "(284, 176)\n",
      "(290, 216)\n",
      "(291, 183)\n",
      "(293, 118)\n",
      "(293, 15)\n",
      "(293, 25)\n",
      "(295, 328)\n",
      "(295, 96)\n",
      "(297, 302)\n",
      "(297, 22)\n",
      "(298, 318)\n",
      "(298, 276)\n",
      "(299, 9)\n",
      "(300, 423)\n",
      "(301, 195)\n",
      "(303, 257)\n",
      "(315, 269)\n",
      "(316, 748)\n",
      "(316, 168)\n",
      "(321, 69)\n",
      "(324, 173)\n",
      "(326, 151)\n",
      "(331, 210)\n",
      "(336, 79)\n",
      "(344, 405)\n",
      "(350, 204)\n",
      "(350, 313)\n",
      "(365, 222)\n",
      "(367, 172)\n",
      "(378, 117)\n",
      "(384, 237)\n",
      "(390, 98)\n",
      "(392, 7)\n",
      "(394, 56)\n",
      "(413, 127)\n",
      "(420, 174)\n",
      "(429, 121)\n",
      "(431, 300)\n",
      "(452, 1)\n",
      "(478, 288)\n",
      "(481, 286)\n",
      "(485, 294)\n",
      "(507, 181)\n",
      "(508, 100)\n",
      "(509, 258)\n",
      "(583, 50)\n"
     ]
    }
   ],
   "source": [
    "results = sortedMovies.collect()\n",
    "for result in results:\n",
    "    print(result)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "metadata": {},
   "outputs": [],
   "source": [
    "sc.stop()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pyspark import SparkConf, SparkContext\n",
    "\n",
    "def loadMovieNames():\n",
    "    movieNames = {}\n",
    "    with open('u.item', encoding = \"ISO-8859-1\") as f:\n",
    "        for line in f:\n",
    "            fields = line.split('|')\n",
    "            movieNames[int(fields[0])] = fields[1]\n",
    "    return movieNames\n",
    "\n",
    "conf = SparkConf().setMaster('local').setAppName('PopularMovies')\n",
    "sc = SparkContext(conf = conf)\n",
    "nameDict = sc.broadcast(loadMovieNames())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(242, 1), (302, 1), (377, 1)]"
      ]
     },
     "execution_count": 141,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lines = sc.textFile('u.data')\n",
    "movies = lines.map(lambda x: (int(x.split()[1]), 1))\n",
    "movies.take(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(242, 117), (302, 297), (377, 13)]"
      ]
     },
     "execution_count": 143,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movieCounts = movies.reduceByKey(lambda x, y:x + y )\n",
    "movieCounts.take(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(117, 242), (297, 302), (13, 377)]"
      ]
     },
     "execution_count": 145,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "flipped = movieCounts.map(lambda x: (x[1], x[0]))\n",
    "flipped.take(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(1, 1348), (1, 1320), (1, 1492)]"
      ]
     },
     "execution_count": 146,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sortedMovies = flipped.sortByKey()\n",
    "sortedMovies.take(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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