{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 캐글뽀개기 10월 What's Cooking 발표자 이상열\n",
    "## https://www.kaggle.com/c/whats-cooking/\n",
    "![](https://kaggle2.blob.core.windows.net/competitions/kaggle/4526/logos/front_page.png)\n",
    "\n",
    "- Use recipe ingredients to categorize the cuisine\n",
    "- Picture yourself strolling through your local, open-air market... What do you see? What do you smell? What will you make for dinner tonight?\n",
    "- If you're in Northern California, you'll be walking past the inevitable bushels of leafy greens, spiked with dark purple kale and the bright pinks and yellows of chard. Across the world in South Korea, mounds of bright red kimchi greet you, while the smell of the sea draws your attention to squids squirming nearby. India’s market is perhaps the most colorful, awash in the rich hues and aromas of dozens of spices: turmeric, star anise, poppy seeds, and garam masala as far as the eye can see.\n",
    "- Some of our strongest geographic and cultural associations are tied to a region's local foods. This playground competitions asks you to predict the category of a dish's cuisine given a list of its ingredients. \n",
    "\n",
    "- 재료의 목록을 보고 요리의 범주(국가)를 예측하는 문제. \n",
    "\n",
    "- http://www.yummly.com/\n",
    "\n",
    "<img src=\"yummly_c.jpg\" alt=\"alt text\" title=\"Title\"/>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "~~~~\n",
    "json 형태 파일\n",
    "{\n",
    " \"id\": 24717,\n",
    " \"cuisine\": \"indian\",\n",
    " \"ingredients\": [\n",
    "     \"tumeric\",\n",
    "     \"vegetable stock\",\n",
    "     \"tomatoes\",\n",
    "     \"garam masala\",\n",
    "     \"naan\",\n",
    "     \"red lentils\",\n",
    "     \"red chili peppers\",\n",
    "     \"onions\",\n",
    "     \"spinach\",\n",
    "     \"sweet potatoes\"\n",
    " ]\n",
    " },\n",
    "~~~~\n",
    "\n",
    "- train.json - the training set containing recipes id, type of cuisine, and list of ingredients\n",
    "- test.json - the test set containing recipes id, and list of ingredients\n",
    "- sample_submission.csv - a sample submission file in the correct format\n",
    "\n",
    "- 평가방법 (Submissions are evaluated on the categorization accuracy (the percent of dishes that you correctly classify).\n",
    "![](https://docs.wso2.com/download/attachments/47520050/Multiclass_Classification_Matrix_Definition.png?version=1&modificationDate=1441305075000&api=v2)\n",
    "![](https://docs.wso2.com/download/attachments/47520050/Multi_Class_Classification.png?version=2&modificationDate=1441304458000&api=v2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "set.seed(2310)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "  바이너리 버전을 이용할 수 있습니다 (그리고 설치되어질 것입니다)\n",
      "  그러나 소스 버전은 추후에 제공될 것입니다:\n",
      "     binary source\n",
      "repr    0.3    0.4\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message:\n",
      "In download.file(url, destfile, method, mode = \"wb\", ...): cannot open: HTTP status was '400 Bad Request'Warning message:\n",
      "In download.packages(pkgs, destdir = tmpd, available = available, : download of package 'rzmq' failed"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "package 'repr' successfully unpacked and MD5 sums checked\n",
      "package 'IRkernel' successfully unpacked and MD5 sums checked\n",
      "package 'IRdisplay' successfully unpacked and MD5 sums checked\n",
      "\n",
      "The downloaded binary packages are in\n",
      "\tC:\\Users\\syleeie\\RtmpKcFXpv\\downloaded_packages\n"
     ]
    }
   ],
   "source": [
    "install.packages(c('rzmq','repr','IRkernel','IRdisplay'), repos = 'http://irkernel.github.io/')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "IRkernel::installspec()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "also installing the dependencies 'memoise', 'mime', 'bitops', 'Rcpp', 'crayon', 'praise', 'evaluate', 'formatR', 'highr', 'markdown', 'yaml', 'htmltools', 'caTools', 'R.methodsS3', 'R.oo', 'R.utils', 'R.cache', 'curl', 'plyr', 'testthat', 'knitr', 'rmarkdown', 'R.rsp'\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "package 'memoise' successfully unpacked and MD5 sums checked\n",
      "package 'mime' successfully unpacked and MD5 sums checked\n",
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      "package 'R.rsp' successfully unpacked and MD5 sums checked\n",
      "package 'jsonlite' successfully unpacked and MD5 sums checked\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message:\n",
      ": cannot remove prior installation of package 'jsonlite'"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "The downloaded binary packages are in\n",
      "\tC:\\Users\\syleeie\\RtmpKcFXpv\\downloaded_packages\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "also installing the dependencies 'colorspace', 'RColorBrewer', 'dichromat', 'munsell', 'labeling', 'chron', 'gtable', 'reshape2', 'scales', 'proto', 'assertthat', 'R6', 'magrittr', 'lazyeval', 'DBI', 'RSQLite', 'RMySQL', 'RPostgreSQL', 'data.table', 'microbenchmark', 'ggplot2', 'Lahman', 'nycflights13'\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "package 'colorspace' successfully unpacked and MD5 sums checked\n",
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      "package 'ggplot2' successfully unpacked and MD5 sums checked\n",
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      "package 'nycflights13' successfully unpacked and MD5 sums checked\n",
      "package 'dplyr' successfully unpacked and MD5 sums checked\n",
      "\n",
      "The downloaded binary packages are in\n",
      "\tC:\\Users\\syleeie\\RtmpKcFXpv\\downloaded_packages\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "also installing the dependencies 'zoo', 'SparseM', 'MatrixModels', 'Formula', 'latticeExtra', 'acepack', 'gridExtra', 'sp', 'mvtnorm', 'TH.data', 'sandwich', 'quantreg', 'Hmisc', 'mapproj', 'maps', 'hexbin', 'maptools', 'multcomp'\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "package 'zoo' successfully unpacked and MD5 sums checked\n",
      "package 'SparseM' successfully unpacked and MD5 sums checked\n",
      "package 'MatrixModels' successfully unpacked and MD5 sums checked\n",
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      "package 'gridExtra' successfully unpacked and MD5 sums checked\n",
      "package 'sp' successfully unpacked and MD5 sums checked\n",
      "package 'mvtnorm' successfully unpacked and MD5 sums checked\n",
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      "package 'sandwich' successfully unpacked and MD5 sums checked\n",
      "package 'quantreg' successfully unpacked and MD5 sums checked\n",
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      "package 'mapproj' successfully unpacked and MD5 sums checked\n",
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      "package 'hexbin' successfully unpacked and MD5 sums checked\n",
      "package 'maptools' successfully unpacked and MD5 sums checked\n",
      "package 'multcomp' successfully unpacked and MD5 sums checked\n",
      "package 'ggplot2' successfully unpacked and MD5 sums checked\n",
      "\n",
      "The downloaded binary packages are in\n",
      "\tC:\\Users\\syleeie\\RtmpKcFXpv\\downloaded_packages\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message:\n",
      ": dependencies 'Rcampdf', 'Rgraphviz', 'Rpoppler', 'tm.lexicon.GeneralInquirer' are not availablealso installing the dependencies 'NLP', 'slam', 'filehash', 'SnowballC', 'XML'\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "package 'NLP' successfully unpacked and MD5 sums checked\n",
      "package 'slam' successfully unpacked and MD5 sums checked\n",
      "package 'filehash' successfully unpacked and MD5 sums checked\n",
      "package 'SnowballC' successfully unpacked and MD5 sums checked\n",
      "package 'XML' successfully unpacked and MD5 sums checked\n",
      "package 'tm' successfully unpacked and MD5 sums checked\n",
      "\n",
      "The downloaded binary packages are in\n",
      "\tC:\\Users\\syleeie\\RtmpKcFXpv\\downloaded_packages\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message:\n",
      ": dependency 'rPython' is not availablealso installing the dependencies 'numDeriv', 'minqa', 'nloptr', 'profileModel', 'plotrix', 'lava', 'pbkrtest', 'iterators', 'lme4', 'brglm', 'gtools', 'plotmo', 'TeachingDemos', 'prodlim', 'combinat', 'modeltools', 'strucchange', 'coin', 'car', 'foreach', 'BradleyTerry2', 'e1071', 'earth', 'fastICA', 'gam', 'ipred', 'kernlab', 'klaR', 'ellipse', 'mda', 'mlbench', 'party', 'pls', 'pROC', 'proxy', 'randomForest', 'RANN', 'spls', 'subselect', 'pamr', 'superpc', 'Cubist'\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "package 'numDeriv' successfully unpacked and MD5 sums checked\n",
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      "package 'spls' successfully unpacked and MD5 sums checked\n",
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      "package 'pamr' successfully unpacked and MD5 sums checked\n",
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      "package 'Cubist' successfully unpacked and MD5 sums checked\n",
      "package 'caret' successfully unpacked and MD5 sums checked\n",
      "\n",
      "The downloaded binary packages are in\n",
      "\tC:\\Users\\syleeie\\RtmpKcFXpv\\downloaded_packages\n",
      "package 'rpart.plot' successfully unpacked and MD5 sums checked\n",
      "\n",
      "The downloaded binary packages are in\n",
      "\tC:\\Users\\syleeie\\RtmpKcFXpv\\downloaded_packages\n",
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      "\n",
      "The downloaded binary packages are in\n",
      "\tC:\\Users\\syleeie\\RtmpKcFXpv\\downloaded_packages\n"
     ]
    }
   ],
   "source": [
    "install.packages(\"jsonlite\", dependencies=T, repos='http://cran.rstudio.com/') \n",
    "install.packages(\"dplyr\", dependencies=T, repos='http://cran.rstudio.com/') \n",
    "install.packages(\"ggplot2\", dependencies=T, repos='http://cran.rstudio.com/') \n",
    "install.packages(\"tm\", dependencies=T, repos='http://cran.rstudio.com/') \n",
    "install.packages(\"caret\", dependencies=T, repos='http://cran.rstudio.com/') \n",
    "install.packages(\"rpart.plot\", dependencies=T, repos='http://cran.rstudio.com/') \n",
    "install.packages(\"SnowballC\", dependencies=T, repos='http://cran.rstudio.com/') "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "ename": "ERROR",
     "evalue": "Error in library(jsonlite): there is no package called 'jsonlite'\n",
     "output_type": "error",
     "traceback": [
      "Error in library(jsonlite): there is no package called 'jsonlite'\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "Attaching package: 'dplyr'\n",
      "\n",
      "The following objects are masked from 'package:stats':\n",
      "\n",
      "    filter, lag\n",
      "\n",
      "The following objects are masked from 'package:base':\n",
      "\n",
      "    intersect, setdiff, setequal, union\n",
      "\n",
      "Loading required package: NLP\n",
      "\n",
      "Attaching package: 'NLP'\n",
      "\n",
      "The following object is masked from 'package:ggplot2':\n",
      "\n",
      "    annotate\n",
      "\n",
      "Loading required package: lattice\n"
     ]
    }
   ],
   "source": [
    "library(jsonlite)\n",
    "library(dplyr)\n",
    "library(ggplot2)\n",
    "library(tm) # For NLP; creating bag-of-words\n",
    "library(caret)\n",
    "library(rpart)\n",
    "library(rpart.plot)\n",
    "library(SnowballC)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "load(\"json.Rdata\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<ol class=list-inline>\n",
       "\t<li>\"test\"</li>\n",
       "\t<li>\"train\"</li>\n",
       "</ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item \"test\"\n",
       "\\item \"train\"\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. \"test\"\n",
       "2. \"train\"\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "[1] \"test\"  \"train\""
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ls()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th></th><th scope=col>id</th><th scope=col>cuisine</th><th scope=col>ingredients</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>1</th><td>10259</td><td>greek</td><td>romaine lettuce, black olives, grape tomatoes, garlic, pepper, purple onion, seasoning, garbanzo beans, feta cheese crumbles</td></tr>\n",
       "\t<tr><th scope=row>2</th><td>25693</td><td>southern_us</td><td>plain flour, ground pepper, salt, tomatoes, ground black pepper, thyme, eggs, green tomatoes, yellow corn meal, milk, vegetable oil</td></tr>\n",
       "\t<tr><th scope=row>3</th><td>20130</td><td>filipino</td><td>eggs, pepper, salt, mayonaise, cooking oil, green chilies, grilled chicken breasts, garlic powder, yellow onion, soy sauce, butter, chicken livers</td></tr>\n",
       "\t<tr><th scope=row>4</th><td>22213</td><td>indian</td><td>water, vegetable oil, wheat, salt</td></tr>\n",
       "\t<tr><th scope=row>5</th><td>13162</td><td>indian</td><td>black pepper, shallots, cornflour, cayenne pepper, onions, garlic paste, milk, butter, salt, lemon juice, water, chili powder, passata, oil, ground cumin, boneless chicken skinless thigh, garam masala, double cream, natural yogurt, bay leaf</td></tr>\n",
       "\t<tr><th scope=row>6</th><td>6602</td><td>jamaican</td><td>plain flour, sugar, butter, eggs, fresh ginger root, salt, ground cinnamon, milk, vanilla extract, ground ginger, powdered sugar, baking powder</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lll}\n",
       "  & id & cuisine & ingredients\\\\\n",
       "\\hline\n",
       "\t1 & 10259 & greek & romaine lettuce, black olives, grape tomatoes, garlic, pepper, purple onion, seasoning, garbanzo beans, feta cheese crumbles\\\\\n",
       "\t2 & 25693 & southern_us & plain flour, ground pepper, salt, tomatoes, ground black pepper, thyme, eggs, green tomatoes, yellow corn meal, milk, vegetable oil\\\\\n",
       "\t3 & 20130 & filipino & eggs, pepper, salt, mayonaise, cooking oil, green chilies, grilled chicken breasts, garlic powder, yellow onion, soy sauce, butter, chicken livers\\\\\n",
       "\t4 & 22213 & indian & water, vegetable oil, wheat, salt\\\\\n",
       "\t5 & 13162 & indian & black pepper, shallots, cornflour, cayenne pepper, onions, garlic paste, milk, butter, salt, lemon juice, water, chili powder, passata, oil, ground cumin, boneless chicken skinless thigh, garam masala, double cream, natural yogurt, bay leaf\\\\\n",
       "\t6 & 6602 & jamaican & plain flour, sugar, butter, eggs, fresh ginger root, salt, ground cinnamon, milk, vanilla extract, ground ginger, powdered sugar, baking powder\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "     id     cuisine\n",
       "1 10259       greek\n",
       "2 25693 southern_us\n",
       "3 20130    filipino\n",
       "4 22213      indian\n",
       "5 13162      indian\n",
       "6  6602    jamaican\n",
       "                                                                                                                                                                                                                                       ingredients\n",
       "1                                                                                                                     romaine lettuce, black olives, grape tomatoes, garlic, pepper, purple onion, seasoning, garbanzo beans, feta cheese crumbles\n",
       "2                                                                                                              plain flour, ground pepper, salt, tomatoes, ground black pepper, thyme, eggs, green tomatoes, yellow corn meal, milk, vegetable oil\n",
       "3                                                                                               eggs, pepper, salt, mayonaise, cooking oil, green chilies, grilled chicken breasts, garlic powder, yellow onion, soy sauce, butter, chicken livers\n",
       "4                                                                                                                                                                                                                water, vegetable oil, wheat, salt\n",
       "5 black pepper, shallots, cornflour, cayenne pepper, onions, garlic paste, milk, butter, salt, lemon juice, water, chili powder, passata, oil, ground cumin, boneless chicken skinless thigh, garam masala, double cream, natural yogurt, bay leaf\n",
       "6                                                                                                  plain flour, sugar, butter, eggs, fresh ginger root, salt, ground cinnamon, milk, vanilla extract, ground ginger, powdered sugar, baking powder"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "head(train)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "~~~~\n",
    "ID 요리 재료\n",
    "1 10259 그리스어로 메인 양상추, 블랙 올리브, 포도, 토마토, 마늘, 고추, 보라색 양파, 조미료, garbanzo 콩, 죽은 태아의 치즈는 잘게\n",
    "2 25693 southern_us 일반 밀가루, 후추, 소금, 토마토, 지상 후추, 타임, 계란, 녹색 토마토, 노란 옥수수 가루, 우유, 식물성 기름\n",
    "3 20130 필리핀 계란, 후추, 소금, mayonaise, 기름, 녹색 고추, 구운 닭 가슴살, 마늘 분말, 노란 양파, 간장, 버터, 닭의 간 요리\n",
    "4 22213 인도 물, 식물성 기름, 밀가루, 소금\n",
    "5 13162 인도 후추, 골파, 옥수수 가루, 카이엔 고추, 양파, 마늘 페이스트, 우유, 버터, 소금, 레몬 주스, 물, 고추 가루, passata, 오일, 지상 커 민, 뼈없는 닭 껍질을 벗기는 허벅지, 가람 마살라, 더블 크림, 천연 요구르트, 베이 리프\n",
    "6 6602 자메이카 일반 밀가루, 설탕, 버터, 계란, 신선한 생강 뿌리, 소금, 분말 계피, 우유, 바닐라 추출물, 지상 생강, 가루 설탕, 베이킹 파우더\n",
    "~~~~"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th></th><th scope=col>id</th><th scope=col>ingredients</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>1</th><td>18009</td><td>baking powder, eggs, all-purpose flour, raisins, milk, white sugar</td></tr>\n",
       "\t<tr><th scope=row>2</th><td>28583</td><td>sugar, egg yolks, corn starch, cream of tartar, bananas, vanilla wafers, milk, vanilla extract, toasted pecans, egg whites, light rum</td></tr>\n",
       "\t<tr><th scope=row>3</th><td>41580</td><td>sausage links, fennel bulb, fronds, olive oil, cuban peppers, onions</td></tr>\n",
       "\t<tr><th scope=row>4</th><td>29752</td><td>meat cuts, file powder, smoked sausage, okra, shrimp, andouille sausage, water, paprika, hot sauce, garlic cloves, browning, lump crab meat, vegetable oil, all-purpose flour, freshly ground pepper, flat leaf parsley, boneless chicken skinless thigh, dried thyme, white rice, yellow onion, ham</td></tr>\n",
       "\t<tr><th scope=row>5</th><td>35687</td><td>ground black pepper, salt, sausage casings, leeks, parmigiano reggiano cheese, cornmeal, water, extra-virgin olive oil</td></tr>\n",
       "\t<tr><th scope=row>6</th><td>38527</td><td>baking powder, all-purpose flour, peach slices, corn starch, heavy cream, lemon juice, unsalted butter, salt, white sugar</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|ll}\n",
       "  & id & ingredients\\\\\n",
       "\\hline\n",
       "\t1 & 18009 & baking powder, eggs, all-purpose flour, raisins, milk, white sugar\\\\\n",
       "\t2 & 28583 & sugar, egg yolks, corn starch, cream of tartar, bananas, vanilla wafers, milk, vanilla extract, toasted pecans, egg whites, light rum\\\\\n",
       "\t3 & 41580 & sausage links, fennel bulb, fronds, olive oil, cuban peppers, onions\\\\\n",
       "\t4 & 29752 & meat cuts, file powder, smoked sausage, okra, shrimp, andouille sausage, water, paprika, hot sauce, garlic cloves, browning, lump crab meat, vegetable oil, all-purpose flour, freshly ground pepper, flat leaf parsley, boneless chicken skinless thigh, dried thyme, white rice, yellow onion, ham\\\\\n",
       "\t5 & 35687 & ground black pepper, salt, sausage casings, leeks, parmigiano reggiano cheese, cornmeal, water, extra-virgin olive oil\\\\\n",
       "\t6 & 38527 & baking powder, all-purpose flour, peach slices, corn starch, heavy cream, lemon juice, unsalted butter, salt, white sugar\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "     id\n",
       "1 18009\n",
       "2 28583\n",
       "3 41580\n",
       "4 29752\n",
       "5 35687\n",
       "6 38527\n",
       "                                                                                                                                                                                                                                                                                           ingredients\n",
       "1                                                                                                                                                                                                                                   baking powder, eggs, all-purpose flour, raisins, milk, white sugar\n",
       "2                                                                                                                                                                sugar, egg yolks, corn starch, cream of tartar, bananas, vanilla wafers, milk, vanilla extract, toasted pecans, egg whites, light rum\n",
       "3                                                                                                                                                                                                                                 sausage links, fennel bulb, fronds, olive oil, cuban peppers, onions\n",
       "4 meat cuts, file powder, smoked sausage, okra, shrimp, andouille sausage, water, paprika, hot sauce, garlic cloves, browning, lump crab meat, vegetable oil, all-purpose flour, freshly ground pepper, flat leaf parsley, boneless chicken skinless thigh, dried thyme, white rice, yellow onion, ham\n",
       "5                                                                                                                                                                               ground black pepper, salt, sausage casings, leeks, parmigiano reggiano cheese, cornmeal, water, extra-virgin olive oil\n",
       "6                                                                                                                                                                            baking powder, all-purpose flour, peach slices, corn starch, heavy cream, lemon juice, unsalted butter, salt, white sugar"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "head(test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "~~~~\n",
    "ID 성분\n",
    "1 18009 베이킹 파우더, 계란, 다목적 밀가루, 건포도, 우유, 백설탕\n",
    "2 28583 설탕, 달걀 노른자, 옥수수 전분, 치석, 바나나, 바닐라 웨이퍼, 우유, 바닐라 추출물, 구운 피칸, 달걀 흰자의 크림, 라이트 럼\n",
    "3 41580 소시지 링크, 회향 전구, 잎, 올리브 오일, 쿠바 고추, 양파\n",
    "4 29752 고기 인하, 파일 가루, 훈제 소시지, 오크라, 새우, andouille 소시지, 물, 파프리카, 핫 소스, 다진 마늘, 갈색, 덩어리 게 고기, 식물성 기름, 다목적 밀가루, 갓 지상 후추, 평면 잎 파슬리, 뼈없는 닭 껍질을 벗기는 허벅지, 말린 백리향, 흰 쌀, 노란 양파, 햄\n",
    "5 35687 지상 후추, 소금, 소시지 케이싱, 부추, 파르 미자의 reggiano 치즈, 옥수수 가루, 물, 엑스트라 버진 올리브 오일\n",
    "6 38527 베이킹 파우더, 다목적 밀가루, 복숭아 조각, 옥수수 전분, 무거운 크림, 레몬 주스, 무염 버터, 소금, 흰 설탕\n",
    "~~~~"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 데이터 전처리 필요\n",
    "- 트윗이나 다른 텍스트 데이터처럼 태그나 url이나 불필요한 자료가 없기 때문에 스페이스 기준으로 추출만 하면 됨.\n",
    "- 모두 소문자이기 때문에 따로 전처리 할 필요는 없고... 불용어 제거할 필요도 없음 (명사 단어만 있기 때문에)\n",
    "- 재료가 ,로 구분되어 있으니 이것만 제외해서 나눠주면 되고 문제는 단어를 몇개까지 매트릭스에 집어넣을것인가..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "sample_sub <- read.csv('sample_submission.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th></th><th scope=col>id</th><th scope=col>cuisine</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>1</th><td>35203</td><td>italian</td></tr>\n",
       "\t<tr><th scope=row>2</th><td>17600</td><td>italian</td></tr>\n",
       "\t<tr><th scope=row>3</th><td>35200</td><td>italian</td></tr>\n",
       "\t<tr><th scope=row>4</th><td>17602</td><td>italian</td></tr>\n",
       "\t<tr><th scope=row>5</th><td>17605</td><td>italian</td></tr>\n",
       "\t<tr><th scope=row>6</th><td>17604</td><td>italian</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|ll}\n",
       "  & id & cuisine\\\\\n",
       "\\hline\n",
       "\t1 & 35203 & italian\\\\\n",
       "\t2 & 17600 & italian\\\\\n",
       "\t3 & 35200 & italian\\\\\n",
       "\t4 & 17602 & italian\\\\\n",
       "\t5 & 17605 & italian\\\\\n",
       "\t6 & 17604 & italian\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "     id cuisine\n",
       "1 35203 italian\n",
       "2 17600 italian\n",
       "3 35200 italian\n",
       "4 17602 italian\n",
       "5 17605 italian\n",
       "6 17604 italian"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "head(sample_sub)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "ingredients <- Corpus(VectorSource(c(train$ingredients,test$ingredients)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<<VCorpus>>\n",
       "Metadata:  corpus specific: 0, document level (indexed): 0\n",
       "Content:  documents: 49718"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ingredients"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message:\n",
      "In read.dcf(file.path(p, \"DESCRIPTION\"), c(\"Package\", \"Version\")): 압축된 파일 'C:/Anaconda/R/library/jsonlite/DESCRIPTION'를 열 수 없습니다.  그 이유는 아마도 'No such file or directory'입니다Warning message:\n",
      "In find.package(if (is.null(package)) loadedNamespaces() else package, : there is no package called 'jsonlite'"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "<table width=\"100%\" summary=\"page for Corpus {tm}\"><tr><td>Corpus {tm}</td><td align=\"right\">R Documentation</td></tr></table>\n",
       "\n",
       "<h2>Corpora</h2>\n",
       "\n",
       "<h3>Description</h3>\n",
       "\n",
       "<p>Representing and computing on corpora.\n",
       "</p>\n",
       "\n",
       "\n",
       "<h3>Details</h3>\n",
       "\n",
       "<p><EM>Corpora</EM> are collections of documents containing (natural language)\n",
       "text. In packages which employ the infrastructure provided by package\n",
       "<span class=\"pkg\">tm</span>, such corpora are represented via the virtual S3 class\n",
       "<code>Corpus</code>: such packages then provide S3 corpus classes extending the\n",
       "virtual base class (such as <code>VCorpus</code> provided by package <span class=\"pkg\">tm</span>\n",
       "itself).\n",
       "</p>\n",
       "<p>All extension classes must provide accessors to extract subsets\n",
       "(<code>[</code>), individual documents (<code>[[</code>), and metadata\n",
       "(<code>meta</code>). The function <code>length</code> must return the number\n",
       "of documents, and <code>as.list</code> must construct a list holding the\n",
       "documents.\n",
       "</p>\n",
       "<p>A corpus can have two types of metadata (accessible via <code>meta</code>).\n",
       "<EM>Corpus metadata</EM> contains corpus specific metadata in form of tag-value\n",
       "pairs. <EM>Document level metadata</EM> contains document specific metadata but\n",
       "is stored in the corpus as a data frame. Document level metadata is typically\n",
       "used for semantic reasons (e.g., classifications of documents form an own\n",
       "entity due to some high-level information like the range of possible values)\n",
       "or for performance reasons (single access instead of extracting metadata of\n",
       "each document).\n",
       "</p>\n",
       "\n",
       "\n",
       "<h3>See Also</h3>\n",
       "\n",
       "<p><code>VCorpus</code>, and <code>PCorpus</code> for the corpora classes\n",
       "provided by package <span class=\"pkg\">tm</span>.\n",
       "</p>\n",
       "<p><code>DCorpus</code> for a distributed corpus class provided by\n",
       "package <span class=\"pkg\">tm.plugin.dc</span>.\n",
       "</p>\n",
       "\n",
       "<hr><div align=\"center\">[Package <em>tm</em> version 0.6-2 ]</div>"
      ],
      "text/latex": [
       "\\inputencoding{utf8}\n",
       "\\HeaderA{Corpus}{Corpora}{Corpus}\n",
       "%\n",
       "\\begin{Description}\\relax\n",
       "Representing and computing on corpora.\n",
       "\\end{Description}\n",
       "%\n",
       "\\begin{Details}\\relax\n",
       "\\emph{Corpora} are collections of documents containing (natural language)\n",
       "text. In packages which employ the infrastructure provided by package\n",
       "\\pkg{tm}, such corpora are represented via the virtual S3 class\n",
       "\\code{Corpus}: such packages then provide S3 corpus classes extending the\n",
       "virtual base class (such as \\code{\\LinkA{VCorpus}{VCorpus}} provided by package \\pkg{tm}\n",
       "itself).\n",
       "\n",
       "All extension classes must provide accessors to extract subsets\n",
       "(\\code{\\LinkA{[}{[}}), individual documents (\\code{\\LinkA{[[}{[[}}), and metadata\n",
       "(\\code{\\LinkA{meta}{meta}}). The function \\code{\\LinkA{length}{length}} must return the number\n",
       "of documents, and \\code{\\LinkA{as.list}{as.list}} must construct a list holding the\n",
       "documents.\n",
       "\n",
       "A corpus can have two types of metadata (accessible via \\code{\\LinkA{meta}{meta}}).\n",
       "\\emph{Corpus metadata} contains corpus specific metadata in form of tag-value\n",
       "pairs. \\emph{Document level metadata} contains document specific metadata but\n",
       "is stored in the corpus as a data frame. Document level metadata is typically\n",
       "used for semantic reasons (e.g., classifications of documents form an own\n",
       "entity due to some high-level information like the range of possible values)\n",
       "or for performance reasons (single access instead of extracting metadata of\n",
       "each document).\n",
       "\\end{Details}\n",
       "%\n",
       "\\begin{SeeAlso}\\relax\n",
       "\\code{\\LinkA{VCorpus}{VCorpus}}, and \\code{\\LinkA{PCorpus}{PCorpus}} for the corpora classes\n",
       "provided by package \\pkg{tm}.\n",
       "\n",
       "\\code{\\LinkA{DCorpus}{DCorpus}} for a distributed corpus class provided by\n",
       "package \\pkg{tm.plugin.dc}.\n",
       "\\end{SeeAlso}"
      ],
      "text/plain": [
       "Corpus                   package:tm                    R Documentation\n",
       "\n",
       "_\bC_\bo_\br_\bp_\bo_\br_\ba\n",
       "\n",
       "_\bD_\be_\bs_\bc_\br_\bi_\bp_\bt_\bi_\bo_\bn:\n",
       "\n",
       "     Representing and computing on corpora.\n",
       "\n",
       "_\bD_\be_\bt_\ba_\bi_\bl_\bs:\n",
       "\n",
       "     _Corpora_ are collections of documents containing (natural\n",
       "     language) text. In packages which employ the infrastructure\n",
       "     provided by package 'tm', such corpora are represented via the\n",
       "     virtual S3 class 'Corpus': such packages then provide S3 corpus\n",
       "     classes extending the virtual base class (such as 'VCorpus'\n",
       "     provided by package 'tm' itself).\n",
       "\n",
       "     All extension classes must provide accessors to extract subsets\n",
       "     ('['), individual documents ('[['), and metadata ('meta'). The\n",
       "     function 'length' must return the number of documents, and\n",
       "     'as.list' must construct a list holding the documents.\n",
       "\n",
       "     A corpus can have two types of metadata (accessible via 'meta').\n",
       "     _Corpus metadata_ contains corpus specific metadata in form of\n",
       "     tag-value pairs. _Document level metadata_ contains document\n",
       "     specific metadata but is stored in the corpus as a data frame.\n",
       "     Document level metadata is typically used for semantic reasons\n",
       "     (e.g., classifications of documents form an own entity due to some\n",
       "     high-level information like the range of possible values) or for\n",
       "     performance reasons (single access instead of extracting metadata\n",
       "     of each document).\n",
       "\n",
       "_\bS_\be_\be _\bA_\bl_\bs_\bo:\n",
       "\n",
       "     'VCorpus', and 'PCorpus' for the corpora classes provided by\n",
       "     package 'tm'.\n",
       "\n",
       "     'DCorpus' for a distributed corpus class provided by package\n",
       "     'tm.plugin.dc'.\n"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "?Corpus #tm package Corpus~"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "ingredients <- tm_map(ingredients, stemDocument)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<<VCorpus>>\n",
       "Metadata:  corpus specific: 0, document level (indexed): 0\n",
       "Content:  documents: 49718"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ingredients"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "ingredientsDTM <- DocumentTermMatrix(ingredients)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message:\n",
      "In read.dcf(file.path(p, \"DESCRIPTION\"), c(\"Package\", \"Version\")): 압축된 파일 'C:/Anaconda/R/library/jsonlite/DESCRIPTION'를 열 수 없습니다.  그 이유는 아마도 'No such file or directory'입니다Warning message:\n",
      "In find.package(if (is.null(package)) loadedNamespaces() else package, : there is no package called 'jsonlite'"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "<table width=\"100%\" summary=\"page for TermDocumentMatrix {tm}\"><tr><td>TermDocumentMatrix {tm}</td><td align=\"right\">R Documentation</td></tr></table>\n",
       "\n",
       "<h2>Term-Document Matrix</h2>\n",
       "\n",
       "<h3>Description</h3>\n",
       "\n",
       "<p>Constructs or coerces to a term-document matrix or a document-term matrix.\n",
       "</p>\n",
       "\n",
       "\n",
       "<h3>Usage</h3>\n",
       "\n",
       "<pre>\n",
       "TermDocumentMatrix(x, control = list())\n",
       "DocumentTermMatrix(x, control = list())\n",
       "as.TermDocumentMatrix(x, ...)\n",
       "as.DocumentTermMatrix(x, ...)\n",
       "</pre>\n",
       "\n",
       "\n",
       "<h3>Arguments</h3>\n",
       "\n",
       "<table summary=\"R argblock\">\n",
       "<tr valign=\"top\"><td><code>x</code></td>\n",
       "<td>\n",
       "<p>a corpus for the constructors and either a term-document\n",
       "matrix or a document-term matrix or a simple\n",
       "triplet matrix (package <span class=\"pkg\">slam</span>) or a term\n",
       "frequency vector for the coercing functions.</p>\n",
       "</td></tr>\n",
       "<tr valign=\"top\"><td><code>control</code></td>\n",
       "<td>\n",
       "<p>a named list of control options. There are local\n",
       "options which are evaluated for each document and global options\n",
       "which are evaluated once for the constructed matrix. Available local\n",
       "options are documented in <code>termFreq</code> and are internally\n",
       "delegated to a <code>termFreq</code> call. Available global options\n",
       "are:\n",
       "</p>\n",
       "\n",
       "<dl>\n",
       "<dt><code>bounds</code></dt><dd><p>A list with a tag <code>global</code> whose value\n",
       "must be an integer vector of length 2. Terms that appear in less\n",
       "documents than the lower bound <code>bounds$global[1]</code> or in\n",
       "more documents than the upper bound <code>bounds$global[2]</code> are\n",
       "discarded. Defaults to <code>list(global = c(1, Inf))</code> (i.e., every\n",
       "term will be used).</p>\n",
       "</dd>\n",
       "<dt><code>weighting</code></dt><dd><p>A weighting function capable of handling a\n",
       "<code>TermDocumentMatrix</code>. It defaults to <code>weightTf</code> for term\n",
       "frequency weighting. Available weighting functions shipped with\n",
       "the <span class=\"pkg\">tm</span> package are <code>weightTf</code>,\n",
       "<code>weightTfIdf</code>, <code>weightBin</code>, and\n",
       "<code>weightSMART</code>.</p>\n",
       "</dd>\n",
       "</dl>\n",
       "</td></tr>\n",
       "<tr valign=\"top\"><td><code>...</code></td>\n",
       "<td>\n",
       "<p>the additional argument <code>weighting</code> (typically a\n",
       "<code>WeightFunction</code>) is allowed when coercing a\n",
       "simple triplet matrix to a term-document or document-term matrix.</p>\n",
       "</td></tr>\n",
       "</table>\n",
       "\n",
       "\n",
       "<h3>Value</h3>\n",
       "\n",
       "<p>An object of class <code>TermDocumentMatrix</code> or class\n",
       "<code>DocumentTermMatrix</code> (both inheriting from a\n",
       "simple triplet matrix in package <span class=\"pkg\">slam</span>)\n",
       "containing a sparse term-document matrix or document-term matrix. The\n",
       "attribute <code>Weighting</code> contains the weighting applied to the\n",
       "matrix.\n",
       "</p>\n",
       "\n",
       "\n",
       "<h3>See Also</h3>\n",
       "\n",
       "<p><code>termFreq</code> for available local control options.\n",
       "</p>\n",
       "\n",
       "\n",
       "<h3>Examples</h3>\n",
       "\n",
       "<pre>\n",
       "data(\"crude\")\n",
       "tdm &lt;- TermDocumentMatrix(crude,\n",
       "                          control = list(removePunctuation = TRUE,\n",
       "                                         stopwords = TRUE))\n",
       "dtm &lt;- DocumentTermMatrix(crude,\n",
       "                          control = list(weighting =\n",
       "                                         function(x)\n",
       "                                         weightTfIdf(x, normalize =\n",
       "                                                     FALSE),\n",
       "                                         stopwords = TRUE))\n",
       "inspect(tdm[202:205, 1:5])\n",
       "inspect(tdm[c(\"price\", \"texas\"), c(\"127\", \"144\", \"191\", \"194\")])\n",
       "inspect(dtm[1:5, 273:276])\n",
       "</pre>\n",
       "\n",
       "<hr><div align=\"center\">[Package <em>tm</em> version 0.6-2 ]</div>"
      ],
      "text/latex": [
       "\\inputencoding{utf8}\n",
       "\\HeaderA{TermDocumentMatrix}{Term-Document Matrix}{TermDocumentMatrix}\n",
       "\\aliasA{as.DocumentTermMatrix}{TermDocumentMatrix}{as.DocumentTermMatrix}\n",
       "\\aliasA{as.TermDocumentMatrix}{TermDocumentMatrix}{as.TermDocumentMatrix}\n",
       "\\aliasA{DocumentTermMatrix}{TermDocumentMatrix}{DocumentTermMatrix}\n",
       "%\n",
       "\\begin{Description}\\relax\n",
       "Constructs or coerces to a term-document matrix or a document-term matrix.\n",
       "\\end{Description}\n",
       "%\n",
       "\\begin{Usage}\n",
       "\\begin{verbatim}\n",
       "TermDocumentMatrix(x, control = list())\n",
       "DocumentTermMatrix(x, control = list())\n",
       "as.TermDocumentMatrix(x, ...)\n",
       "as.DocumentTermMatrix(x, ...)\n",
       "\\end{verbatim}\n",
       "\\end{Usage}\n",
       "%\n",
       "\\begin{Arguments}\n",
       "\\begin{ldescription}\n",
       "\\item[\\code{x}] a corpus for the constructors and either a term-document\n",
       "matrix or a document-term matrix or a \\LinkA{simple\n",
       "    triplet matrix}{simple\n",
       "    triplet matrix} (package \\pkg{slam}) or a \\LinkA{term\n",
       "    frequency vector}{termFreq} for the coercing functions.\n",
       "\\item[\\code{control}] a named list of control options. There are local\n",
       "options which are evaluated for each document and global options\n",
       "which are evaluated once for the constructed matrix. Available local\n",
       "options are documented in \\code{\\LinkA{termFreq}{termFreq}} and are internally\n",
       "delegated to a \\code{\\LinkA{termFreq}{termFreq}} call. Available global options\n",
       "are:\n",
       "\\begin{description}\n",
       "\n",
       "\\item[\\code{bounds}] A list with a tag \\code{global} whose value\n",
       "must be an integer vector of length 2. Terms that appear in less\n",
       "documents than the lower bound \\code{bounds\\$global[1]} or in\n",
       "more documents than the upper bound \\code{bounds\\$global[2]} are\n",
       "discarded. Defaults to \\code{list(global = c(1, Inf))} (i.e., every\n",
       "term will be used).\n",
       "\\item[\\code{weighting}] A weighting function capable of handling a\n",
       "\\code{TermDocumentMatrix}. It defaults to \\code{weightTf} for term\n",
       "frequency weighting. Available weighting functions shipped with\n",
       "the \\pkg{tm} package are \\code{\\LinkA{weightTf}{weightTf}},\n",
       "\\code{\\LinkA{weightTfIdf}{weightTfIdf}}, \\code{\\LinkA{weightBin}{weightBin}}, and\n",
       "\\code{\\LinkA{weightSMART}{weightSMART}}.\n",
       "\n",
       "\\end{description}\n",
       "\n",
       "\\item[\\code{...}] the additional argument \\code{weighting} (typically a\n",
       "\\code{\\LinkA{WeightFunction}{WeightFunction}}) is allowed when coercing a\n",
       "simple triplet matrix to a term-document or document-term matrix.\n",
       "\\end{ldescription}\n",
       "\\end{Arguments}\n",
       "%\n",
       "\\begin{Value}\n",
       "An object of class \\code{TermDocumentMatrix} or class\n",
       "\\code{DocumentTermMatrix} (both inheriting from a\n",
       "\\LinkA{simple triplet matrix}{simple triplet matrix} in package \\pkg{slam})\n",
       "containing a sparse term-document matrix or document-term matrix. The\n",
       "attribute \\code{Weighting} contains the weighting applied to the\n",
       "matrix.\n",
       "\\end{Value}\n",
       "%\n",
       "\\begin{SeeAlso}\\relax\n",
       "\\code{\\LinkA{termFreq}{termFreq}} for available local control options.\n",
       "\\end{SeeAlso}\n",
       "%\n",
       "\\begin{Examples}\n",
       "\\begin{ExampleCode}\n",
       "data(\"crude\")\n",
       "tdm <- TermDocumentMatrix(crude,\n",
       "                          control = list(removePunctuation = TRUE,\n",
       "                                         stopwords = TRUE))\n",
       "dtm <- DocumentTermMatrix(crude,\n",
       "                          control = list(weighting =\n",
       "                                         function(x)\n",
       "                                         weightTfIdf(x, normalize =\n",
       "                                                     FALSE),\n",
       "                                         stopwords = TRUE))\n",
       "inspect(tdm[202:205, 1:5])\n",
       "inspect(tdm[c(\"price\", \"texas\"), c(\"127\", \"144\", \"191\", \"194\")])\n",
       "inspect(dtm[1:5, 273:276])\n",
       "\\end{ExampleCode}\n",
       "\\end{Examples}"
      ],
      "text/plain": [
       "TermDocumentMatrix             package:tm              R Documentation\n",
       "\n",
       "_\bT_\be_\br_\bm-_\bD_\bo_\bc_\bu_\bm_\be_\bn_\bt _\bM_\ba_\bt_\br_\bi_\bx\n",
       "\n",
       "_\bD_\be_\bs_\bc_\br_\bi_\bp_\bt_\bi_\bo_\bn:\n",
       "\n",
       "     Constructs or coerces to a term-document matrix or a document-term\n",
       "     matrix.\n",
       "\n",
       "_\bU_\bs_\ba_\bg_\be:\n",
       "\n",
       "     TermDocumentMatrix(x, control = list())\n",
       "     DocumentTermMatrix(x, control = list())\n",
       "     as.TermDocumentMatrix(x, ...)\n",
       "     as.DocumentTermMatrix(x, ...)\n",
       "     \n",
       "_\bA_\br_\bg_\bu_\bm_\be_\bn_\bt_\bs:\n",
       "\n",
       "       x: a corpus for the constructors and either a term-document\n",
       "          matrix or a document-term matrix or a simple triplet matrix\n",
       "          (package 'slam') or a term frequency vector for the coercing\n",
       "          functions.\n",
       "\n",
       " control: a named list of control options. There are local options\n",
       "          which are evaluated for each document and global options\n",
       "          which are evaluated once for the constructed matrix.\n",
       "          Available local options are documented in 'termFreq' and are\n",
       "          internally delegated to a 'termFreq' call. Available global\n",
       "          options are:\n",
       "\n",
       "          'bounds' A list with a tag 'global' whose value must be an\n",
       "              integer vector of length 2. Terms that appear in less\n",
       "              documents than the lower bound 'bounds$global[1]' or in\n",
       "              more documents than the upper bound 'bounds$global[2]'\n",
       "              are discarded. Defaults to 'list(global = c(1, Inf))'\n",
       "              (i.e., every term will be used).\n",
       "\n",
       "          'weighting' A weighting function capable of handling a\n",
       "              'TermDocumentMatrix'. It defaults to 'weightTf' for term\n",
       "              frequency weighting. Available weighting functions\n",
       "              shipped with the 'tm' package are 'weightTf',\n",
       "              'weightTfIdf', 'weightBin', and 'weightSMART'.\n",
       "\n",
       "     ...: the additional argument 'weighting' (typically a\n",
       "          'WeightFunction') is allowed when coercing a simple triplet\n",
       "          matrix to a term-document or document-term matrix.\n",
       "\n",
       "_\bV_\ba_\bl_\bu_\be:\n",
       "\n",
       "     An object of class 'TermDocumentMatrix' or class\n",
       "     'DocumentTermMatrix' (both inheriting from a simple triplet matrix\n",
       "     in package 'slam') containing a sparse term-document matrix or\n",
       "     document-term matrix. The attribute 'Weighting' contains the\n",
       "     weighting applied to the matrix.\n",
       "\n",
       "_\bS_\be_\be _\bA_\bl_\bs_\bo:\n",
       "\n",
       "     'termFreq' for available local control options.\n",
       "\n",
       "_\bE_\bx_\ba_\bm_\bp_\bl_\be_\bs:\n",
       "\n",
       "     data(\"crude\")\n",
       "     tdm <- TermDocumentMatrix(crude,\n",
       "                               control = list(removePunctuation = TRUE,\n",
       "                                              stopwords = TRUE))\n",
       "     dtm <- DocumentTermMatrix(crude,\n",
       "                               control = list(weighting =\n",
       "                                              function(x)\n",
       "                                              weightTfIdf(x, normalize =\n",
       "                                                          FALSE),\n",
       "                                              stopwords = TRUE))\n",
       "     inspect(tdm[202:205, 1:5])\n",
       "     inspect(tdm[c(\"price\", \"texas\"), c(\"127\", \"144\", \"191\", \"194\")])\n",
       "     inspect(dtm[1:5, 273:276])\n",
       "     "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "?DocumentTermMatrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<<DocumentTermMatrix (documents: 49718, terms: 2886)>>\n",
       "Non-/sparse entries: 927832/142558316\n",
       "Sparsity           : 99%\n",
       "Maximal term length: 25\n",
       "Weighting          : term frequency (tf)"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ingredientsDTM"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Term frequency\n",
    "- https://ko.wikipedia.org/wiki/TF-IDF\n",
    "- TF(단어 빈도, term frequency)는 특정한 단어가 문서 내에 얼마나 자주 등장하는지를 나타내는 값으로, 이 값이 높을수록 문서에서 중요하다고 생각할 수 있다. 하지만 단어 자체가 문서군 내에서 자주 사용되는 경우, 이것은 그 단어가 흔하게 등장한다는 것을 의미한다. 이것을 DF(문서 빈도, document frequency)라고 하며, 이 값의 역수를 IDF(역문서 빈도, inverse document frequency)라고 한다. TF-IDF는 TF와 IDF를 곱한 값이다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "sparse <- removeSparseTerms(ingredientsDTM, 0.99)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<<DocumentTermMatrix (documents: 49718, terms: 250)>>\n",
       "Non-/sparse entries: 808758/11620742\n",
       "Sparsity           : 93%\n",
       "Maximal term length: 13\n",
       "Weighting          : term frequency (tf)"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sparse"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message:\n",
      "In read.dcf(file.path(p, \"DESCRIPTION\"), c(\"Package\", \"Version\")): 압축된 파일 'C:/Anaconda/R/library/jsonlite/DESCRIPTION'를 열 수 없습니다.  그 이유는 아마도 'No such file or directory'입니다Warning message:\n",
      "In find.package(if (is.null(package)) loadedNamespaces() else package, : there is no package called 'jsonlite'"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "<table width=\"100%\" summary=\"page for removeSparseTerms {tm}\"><tr><td>removeSparseTerms {tm}</td><td align=\"right\">R Documentation</td></tr></table>\n",
       "\n",
       "<h2>Remove Sparse Terms from a Term-Document Matrix</h2>\n",
       "\n",
       "<h3>Description</h3>\n",
       "\n",
       "<p>Remove sparse terms from a document-term or term-document matrix.\n",
       "</p>\n",
       "\n",
       "\n",
       "<h3>Usage</h3>\n",
       "\n",
       "<pre>\n",
       "removeSparseTerms(x, sparse)\n",
       "</pre>\n",
       "\n",
       "\n",
       "<h3>Arguments</h3>\n",
       "\n",
       "<table summary=\"R argblock\">\n",
       "<tr valign=\"top\"><td><code>x</code></td>\n",
       "<td>\n",
       "<p>A <code>DocumentTermMatrix</code> or a\n",
       "<code>TermDocumentMatrix</code>.</p>\n",
       "</td></tr>\n",
       "<tr valign=\"top\"><td><code>sparse</code></td>\n",
       "<td>\n",
       "<p>A numeric for the maximal allowed sparsity in the range from\n",
       "bigger zero to smaller one.</p>\n",
       "</td></tr>\n",
       "</table>\n",
       "\n",
       "\n",
       "<h3>Value</h3>\n",
       "\n",
       "<p>A term-document matrix where those terms from <code>x</code> are\n",
       "removed which have at least a <code>sparse</code> percentage of empty (i.e.,\n",
       "terms occurring 0 times in a document) elements. I.e., the resulting\n",
       "matrix contains only terms with a sparse factor of less than\n",
       "<code>sparse</code>.\n",
       "</p>\n",
       "\n",
       "\n",
       "<h3>Examples</h3>\n",
       "\n",
       "<pre>\n",
       "data(\"crude\")\n",
       "tdm &lt;- TermDocumentMatrix(crude)\n",
       "removeSparseTerms(tdm, 0.2)\n",
       "</pre>\n",
       "\n",
       "<hr><div align=\"center\">[Package <em>tm</em> version 0.6-2 ]</div>"
      ],
      "text/latex": [
       "\\inputencoding{utf8}\n",
       "\\HeaderA{removeSparseTerms}{Remove Sparse Terms from a Term-Document Matrix}{removeSparseTerms}\n",
       "%\n",
       "\\begin{Description}\\relax\n",
       "Remove sparse terms from a document-term or term-document matrix.\n",
       "\\end{Description}\n",
       "%\n",
       "\\begin{Usage}\n",
       "\\begin{verbatim}\n",
       "removeSparseTerms(x, sparse)\n",
       "\\end{verbatim}\n",
       "\\end{Usage}\n",
       "%\n",
       "\\begin{Arguments}\n",
       "\\begin{ldescription}\n",
       "\\item[\\code{x}] A \\code{\\LinkA{DocumentTermMatrix}{DocumentTermMatrix}} or a\n",
       "\\code{\\LinkA{TermDocumentMatrix}{TermDocumentMatrix}}.\n",
       "\\item[\\code{sparse}] A numeric for the maximal allowed sparsity in the range from\n",
       "bigger zero to smaller one.\n",
       "\\end{ldescription}\n",
       "\\end{Arguments}\n",
       "%\n",
       "\\begin{Value}\n",
       "A term-document matrix where those terms from \\code{x} are\n",
       "removed which have at least a \\code{sparse} percentage of empty (i.e.,\n",
       "terms occurring 0 times in a document) elements. I.e., the resulting\n",
       "matrix contains only terms with a sparse factor of less than\n",
       "\\code{sparse}.\n",
       "\\end{Value}\n",
       "%\n",
       "\\begin{Examples}\n",
       "\\begin{ExampleCode}\n",
       "data(\"crude\")\n",
       "tdm <- TermDocumentMatrix(crude)\n",
       "removeSparseTerms(tdm, 0.2)\n",
       "\\end{ExampleCode}\n",
       "\\end{Examples}"
      ],
      "text/plain": [
       "removeSparseTerms              package:tm              R Documentation\n",
       "\n",
       "_\bR_\be_\bm_\bo_\bv_\be _\bS_\bp_\ba_\br_\bs_\be _\bT_\be_\br_\bm_\bs _\bf_\br_\bo_\bm _\ba _\bT_\be_\br_\bm-_\bD_\bo_\bc_\bu_\bm_\be_\bn_\bt _\bM_\ba_\bt_\br_\bi_\bx\n",
       "\n",
       "_\bD_\be_\bs_\bc_\br_\bi_\bp_\bt_\bi_\bo_\bn:\n",
       "\n",
       "     Remove sparse terms from a document-term or term-document matrix.\n",
       "\n",
       "_\bU_\bs_\ba_\bg_\be:\n",
       "\n",
       "     removeSparseTerms(x, sparse)\n",
       "     \n",
       "_\bA_\br_\bg_\bu_\bm_\be_\bn_\bt_\bs:\n",
       "\n",
       "       x: A 'DocumentTermMatrix' or a 'TermDocumentMatrix'.\n",
       "\n",
       "  sparse: A numeric for the maximal allowed sparsity in the range from\n",
       "          bigger zero to smaller one.\n",
       "\n",
       "_\bV_\ba_\bl_\bu_\be:\n",
       "\n",
       "     A term-document matrix where those terms from 'x' are removed\n",
       "     which have at least a 'sparse' percentage of empty (i.e., terms\n",
       "     occurring 0 times in a document) elements. I.e., the resulting\n",
       "     matrix contains only terms with a sparse factor of less than\n",
       "     'sparse'.\n",
       "\n",
       "_\bE_\bx_\ba_\bm_\bp_\bl_\be_\bs:\n",
       "\n",
       "     data(\"crude\")\n",
       "     tdm <- TermDocumentMatrix(crude)\n",
       "     removeSparseTerms(tdm, 0.2)\n",
       "     "
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "?removeSparseTerms"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "ingredientsDTM <- as.data.frame(as.matrix(sparse))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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       "<thead><tr><th></th><th scope=col>all-purpos</th><th scope=col>allspic</th><th scope=col>almond</th><th scope=col>and</th><th scope=col>appl</th><th scope=col>avocado</th><th scope=col>babi</th><th scope=col>bacon</th><th scope=col>bake</th><th scope=col>balsam</th><th scope=col>basil</th><th scope=col>bay</th><th scope=col>bean</th><th scope=col>beansprout</th><th scope=col>beef</th><th scope=col>bell</th><th scope=col>black</th><th scope=col>boil</th><th scope=col>boneless</th><th scope=col>bread</th><th scope=col>breast</th><th scope=col>broccoli</th><th scope=col>broth</th><th scope=col>brown</th><th scope=col>butter</th><th scope=col>buttermilk</th><th scope=col>cabbag</th><th scope=col>canola</th><th scope=col>caper</th><th scope=col>cardamom</th><th scope=col>carrot</th><th scope=col>cayenn</th><th scope=col>celeri</th><th scope=col>cheddar</th><th scope=col>chees</th><th scope=col>cherri</th><th scope=col>chicken</th><th scope=col>chickpea</th><th scope=col>chile</th><th scope=col>chili</th><th scope=col>chines</th><th scope=col>chip</th><th scope=col>chipotl</th><th scope=col>chive</th><th scope=col>chocol</th><th scope=col>chop</th><th scope=col>cider</th><th scope=col>cilantro</th><th scope=col>cinnamon</th><th scope=col>clove</th><th scope=col>coars</th><th scope=col>coconut</th><th scope=col>cold</th><th scope=col>condens</th><th scope=col>confection</th><th scope=col>cook</th><th scope=col>coriand</th><th scope=col>corn</th><th scope=col>cornmeal</th><th scope=col>crack</th><th scope=col>cream</th><th scope=col>crumb</th><th scope=col>crumbl</th><th scope=col>crush</th><th scope=col>cucumb</th><th scope=col>cumin</th><th scope=col>curri</th><th scope=col>dark</th><th scope=col>dice</th><th scope=col>dijon</th><th scope=col>dill</th><th scope=col>dough</th><th scope=col>dress</th><th scope=col>dri</th><th scope=col>egg</th><th scope=col>eggplant</th><th scope=col>enchilada</th><th scope=col>extra-virgin</th><th scope=col>extract</th><th scope=col>fat</th><th scope=col>fennel</th><th scope=col>feta</th><th scope=col>fillet</th><th scope=col>fine</th><th scope=col>firm</th><th scope=col>fish</th><th scope=col>flake</th><th scope=col>flat</th><th scope=col>flour</th><th scope=col>free</th><th scope=col>fresh</th><th scope=col>frozen</th><th scope=col>garam</th><th scope=col>garlic</th><th scope=col>ginger</th><th scope=col>golden</th><th scope=col>granul</th><th scope=col>grate</th><th scope=col>greek</th><th scope=col>green</th><th scope=col>ground</th><th scope=col>halv</th><th scope=col>ham</th><th scope=col>heavi</th><th scope=col>hoisin</th><th scope=col>honey</th><th scope=col>hot</th><th scope=col>ice</th><th scope=col>italian</th><th scope=col>jack</th><th scope=col>jalapeno</th><th scope=col>juic</th><th scope=col>kalamata</th><th scope=col>kernel</th><th scope=col>ketchup</th><th scope=col>kosher</th><th scope=col>lamb</th><th scope=col>larg</th><th scope=col>leaf</th><th scope=col>lean</th><th scope=col>leav</th><th scope=col>leek</th><th scope=col>lemon</th><th scope=col>less</th><th scope=col>lettuc</th><th scope=col>light</th><th scope=col>lime</th><th scope=col>low</th><th scope=col>low-fat</th><th scope=col>masala</th><th scope=col>mayonais</th><th scope=col>meat</th><th scope=col>medium</th><th scope=col>mexican</th><th scope=col>milk</th><th scope=col>minc</th><th scope=col>mint</th><th scope=col>mirin</th><th scope=col>mix</th><th scope=col>monterey</th><th scope=col>mozzarella</th><th scope=col>mushroom</th><th scope=col>mustard</th><th scope=col>noodl</th><th scope=col>nutmeg</th><th scope=col>oil</th><th scope=col>oliv</th><th scope=col>onion</th><th scope=col>orang</th><th scope=col>oregano</th><th scope=col>oyster</th><th scope=col>paprika</th><th scope=col>parmesan</th><th scope=col>parsley</th><th scope=col>past</th><th scope=col>pasta</th><th scope=col>pea</th><th scope=col>peanut</th><th scope=col>pecan</th><th scope=col>peel</th><th scope=col>pepper</th><th scope=col>peppercorn</th><th scope=col>plain</th><th scope=col>plum</th><th scope=col>pork</th><th scope=col>potato</th><th scope=col>powder</th><th scope=col>purpl</th><th scope=col>raisin</th><th scope=col>red</th><th scope=col>reduc</th><th scope=col>rib</th><th scope=col>rice</th><th scope=col>ricotta</th><th scope=col>roast</th><th scope=col>root</th><th scope=col>rosemari</th><th scope=col>saffron</th><th scope=col>sage</th><th scope=col>salsa</th><th scope=col>salt</th><th scope=col>sauc</th><th scope=col>sausag</th><th scope=col>scallion</th><th scope=col>sea</th><th scope=col>season</th><th scope=col>seed</th><th scope=col>serrano</th><th scope=col>sesam</th><th scope=col>shallot</th><th scope=col>sharp</th><th scope=col>shell</th><th scope=col>sherri</th><th scope=col>shiitak</th><th scope=col>shoulder</th><th scope=col>shred</th><th scope=col>shrimp</th><th scope=col>skinless</th><th scope=col>slice</th><th scope=col>smoke</th><th scope=col>soda</th><th scope=col>sodium</th><th scope=col>soup</th><th scope=col>sour</th><th scope=col>soy</th><th scope=col>spaghetti</th><th scope=col>spinach</th><th scope=col>spray</th><th scope=col>sprig</th><th scope=col>spring</th><th scope=col>squash</th><th scope=col>starch</th><th scope=col>steak</th><th scope=col>stick</th><th scope=col>stock</th><th scope=col>sugar</th><th scope=col>sweet</th><th scope=col>sweeten</th><th scope=col>syrup</th><th scope=col>taco</th><th scope=col>thai</th><th scope=col>thigh</th><th scope=col>thyme</th><th scope=col>toast</th><th scope=col>tofu</th><th scope=col>tomato</th><th scope=col>tortilla</th><th scope=col>tumer</th><th scope=col>turkey</th><th scope=col>turmer</th><th scope=col>unsalt</th><th scope=col>unsweeten</th><th scope=col>vanilla</th><th scope=col>veget</th><th scope=col>vinegar</th><th scope=col>warm</th><th scope=col>water</th><th scope=col>wedg</th><th scope=col>wheat</th><th scope=col>whip</th><th scope=col>white</th><th scope=col>whole</th><th scope=col>wine</th><th scope=col>worcestershir</th><th scope=col>yeast</th><th scope=col>yellow</th><th scope=col>yogurt</th><th scope=col>yolk</th><th scope=col>zest</th><th scope=col>zucchini</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>1</th><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td></tr>\n",
       "\t<tr><th scope=row>2</th><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>2</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>2</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>2</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td></tr>\n",
       "\t<tr><th scope=row>3</th><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>2</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td></tr>\n",
       "\t<tr><th scope=row>4</th><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>1</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td></tr>\n",
       "\t<tr><th scope=row>5</th><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>2</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td></tr>\n",
       "\t<tr><th scope=row>6</th><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>2</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>2</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>2</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>2</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|llllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllll}\n",
       "  & all-purpos & allspic & almond & and & appl & avocado & babi & bacon & bake & balsam & basil & bay & bean & beansprout & beef & bell & black & boil & boneless & bread & breast & broccoli & broth & brown & butter & buttermilk & cabbag & canola & caper & cardamom & carrot & cayenn & celeri & cheddar & chees & cherri & chicken & chickpea & chile & chili & chines & chip & chipotl & chive & chocol & chop & cider & cilantro & cinnamon & clove & coars & coconut & cold & condens & confection & cook & coriand & corn & cornmeal & crack & cream & crumb & crumbl & crush & cucumb & cumin & curri & dark & dice & dijon & dill & dough & dress & dri & egg & eggplant & enchilada & extra-virgin & extract & fat & fennel & feta & fillet & fine & firm & fish & flake & flat & flour & free & fresh & frozen & garam & garlic & ginger & golden & granul & grate & greek & green & ground & halv & ham & heavi & hoisin & honey & hot & ice & italian & jack & jalapeno & juic & kalamata & kernel & ketchup & kosher & lamb & larg & leaf & lean & leav & leek & lemon & less & lettuc & light & lime & low & low-fat & masala & mayonais & meat & medium & mexican & milk & minc & mint & mirin & mix & monterey & mozzarella & mushroom & mustard & noodl & nutmeg & oil & oliv & onion & orang & oregano & oyster & paprika & parmesan & parsley & past & pasta & pea & peanut & pecan & peel & pepper & peppercorn & plain & plum & pork & potato & powder & purpl & raisin & red & reduc & rib & rice & ricotta & roast & root & rosemari & saffron & sage & salsa & salt & sauc & sausag & scallion & sea & season & seed & serrano & sesam & shallot & sharp & shell & sherri & shiitak & shoulder & shred & shrimp & skinless & slice & smoke & soda & sodium & soup & sour & soy & spaghetti & spinach & spray & sprig & spring & squash & starch & steak & stick & stock & sugar & sweet & sweeten & syrup & taco & thai & thigh & thyme & toast & tofu & tomato & tortilla & tumer & turkey & turmer & unsalt & unsweeten & vanilla & veget & vinegar & warm & water & wedg & wheat & whip & white & whole & wine & worcestershir & yeast & yellow & yogurt & yolk & zest & zucchini\\\\\n",
       "\\hline\n",
       "\t1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0\\\\\n",
       "\t2 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 2 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 2 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 2 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0\\\\\n",
       "\t3 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 2 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0\\\\\n",
       "\t4 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 1 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0\\\\\n",
       "\t5 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 1 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 2 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0\\\\\n",
       "\t6 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 1 & 0 & 0 & 0 & 2 & 0 & 0 & 0 & 0 & 0 & 2 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 2 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 2 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "  all-purpos allspic almond and appl avocado babi bacon bake balsam basil bay\n",
       "1          0       0      0   0    0       0    0     0    0      0     0   0\n",
       "2          0       0      0   0    0       0    0     0    0      0     0   0\n",
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       "6          0       0      0   0    0       0    0     0    1      0     0   0\n",
       "  bean beansprout beef bell black boil boneless bread breast broccoli broth\n",
       "1    1          0    0    0     1    0        0     0      0        0     0\n",
       "2    0          0    0    0     1    0        0     0      0        0     0\n",
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       "5    0          0    0    0     1    0        1     0      0        0     0\n",
       "6    0          0    0    0     0    0        0     0      0        0     0\n",
       "  brown butter buttermilk cabbag canola caper cardamom carrot cayenn celeri\n",
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       "2     0      0          0      0      0     0        0      0      0      0\n",
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       "  cheddar chees cherri chicken chickpea chile chili chines chip chipotl chive\n",
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       "  kernel ketchup kosher lamb larg leaf lean leav leek lemon less lettuc light\n",
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       "  lime low low-fat masala mayonais meat medium mexican milk minc mint mirin mix\n",
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       "  monterey mozzarella mushroom mustard noodl nutmeg oil oliv onion orang\n",
       "1        0          0        0       0     0      0   0    1     1     0\n",
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       "  oregano oyster paprika parmesan parsley past pasta pea peanut pecan peel\n",
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       "2       0      0       0        0       0    0     0   0      0     0    0\n",
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       "5       0      0       0        0       0    1     0   0      0     0    0\n",
       "6       0      0       0        0       0    0     0   0      0     0    0\n",
       "  pepper peppercorn plain plum pork potato powder purpl raisin red reduc rib\n",
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       "2      2          0     1    0    0      0      0     0      0   0     0   0\n",
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       "6      0          0     1    0    0      0      2     0      0   0     0   0\n",
       "  rice ricotta roast root rosemari saffron sage salsa salt sauc sausag scallion\n",
       "1    0       0     0    0        0       0    0     0    0    0      0        0\n",
       "2    0       0     0    0        0       0    0     0    1    0      0        0\n",
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       "6    0       0     0    1        0       0    0     0    1    0      0        0\n",
       "  sea season seed serrano sesam shallot sharp shell sherri shiitak shoulder\n",
       "1   0      1    0       0     0       0     0     0      0       0        0\n",
       "2   0      0    0       0     0       0     0     0      0       0        0\n",
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       "5   0      0    0       0     0       1     0     0      0       0        0\n",
       "6   0      0    0       0     0       0     0     0      0       0        0\n",
       "  shred shrimp skinless slice smoke soda sodium soup sour soy spaghetti spinach\n",
       "1     0      0        0     0     0    0      0    0    0   0         0       0\n",
       "2     0      0        0     0     0    0      0    0    0   0         0       0\n",
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       "6     0      0        0     0     0    0      0    0    0   0         0       0\n",
       "  spray sprig spring squash starch steak stick stock sugar sweet sweeten syrup\n",
       "1     0     0      0      0      0     0     0     0     0     0       0     0\n",
       "2     0     0      0      0      0     0     0     0     0     0       0     0\n",
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       "6     0     0      0      0      0     0     0     0     2     0       0     0\n",
       "  taco thai thigh thyme toast tofu tomato tortilla tumer turkey turmer unsalt\n",
       "1    0    0     0     0     0    0      1        0     0      0      0      0\n",
       "2    0    0     0     1     0    0      2        0     0      0      0      0\n",
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       "5    0    0     1     0     0    0      0        0     0      0      0      0\n",
       "6    0    0     0     0     0    0      0        0     0      0      0      0\n",
       "  unsweeten vanilla veget vinegar warm water wedg wheat whip white whole wine\n",
       "1         0       0     0       0    0     0    0     0    0     0     0    0\n",
       "2         0       0     1       0    0     0    0     0    0     0     0    0\n",
       "3         0       0     0       0    0     0    0     0    0     0     0    0\n",
       "4         0       0     1       0    0     1    0     1    0     0     0    0\n",
       "5         0       0     0       0    0     1    0     0    0     0     0    0\n",
       "6         0       1     0       0    0     0    0     0    0     0     0    0\n",
       "  worcestershir yeast yellow yogurt yolk zest zucchini\n",
       "1             0     0      0      0    0    0        0\n",
       "2             0     0      1      0    0    0        0\n",
       "3             0     0      1      0    0    0        0\n",
       "4             0     0      0      0    0    0        0\n",
       "5             0     0      0      1    0    0        0\n",
       "6             0     0      0      0    0    0        0"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "head(ingredientsDTM)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "ingredientsDTM_train <- ingredientsDTM[1:39774,]\n",
    "ingredientsDTM_test <- ingredientsDTM[39775:49718,]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<ol class=list-inline>\n",
       "\t<li>39774</li>\n",
       "\t<li>250</li>\n",
       "</ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 39774\n",
       "\\item 250\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 39774\n",
       "2. 250\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "[1] 39774   250"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/html": [
       "<ol class=list-inline>\n",
       "\t<li>9944</li>\n",
       "\t<li>250</li>\n",
       "</ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 9944\n",
       "\\item 250\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 9944\n",
       "2. 250\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "[1] 9944  250"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dim(ingredientsDTM_train)\n",
    "dim(ingredientsDTM_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "ingredientsDTM_train$cuisine <- as.factor(train$cuisine)\n",
    "ingredientsDTM_test$cuisine <- NA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th></th><th scope=col>all-purpos</th><th scope=col>allspic</th><th scope=col>almond</th><th scope=col>and</th><th scope=col>appl</th><th scope=col>avocado</th><th scope=col>babi</th><th scope=col>bacon</th><th scope=col>bake</th><th scope=col>balsam</th><th scope=col>basil</th><th scope=col>bay</th><th scope=col>bean</th><th scope=col>beansprout</th><th scope=col>beef</th><th scope=col>bell</th><th scope=col>black</th><th scope=col>boil</th><th scope=col>boneless</th><th scope=col>bread</th><th scope=col>breast</th><th scope=col>broccoli</th><th scope=col>broth</th><th scope=col>brown</th><th scope=col>butter</th><th scope=col>buttermilk</th><th scope=col>cabbag</th><th scope=col>canola</th><th scope=col>caper</th><th scope=col>cardamom</th><th scope=col>carrot</th><th scope=col>cayenn</th><th scope=col>celeri</th><th scope=col>cheddar</th><th scope=col>chees</th><th scope=col>cherri</th><th scope=col>chicken</th><th scope=col>chickpea</th><th scope=col>chile</th><th scope=col>chili</th><th scope=col>chines</th><th scope=col>chip</th><th scope=col>chipotl</th><th scope=col>chive</th><th scope=col>chocol</th><th scope=col>chop</th><th scope=col>cider</th><th scope=col>cilantro</th><th scope=col>cinnamon</th><th scope=col>clove</th><th scope=col>coars</th><th scope=col>coconut</th><th scope=col>cold</th><th scope=col>condens</th><th scope=col>confection</th><th scope=col>cook</th><th scope=col>coriand</th><th scope=col>corn</th><th scope=col>cornmeal</th><th scope=col>crack</th><th scope=col>cream</th><th scope=col>crumb</th><th scope=col>crumbl</th><th scope=col>crush</th><th scope=col>cucumb</th><th scope=col>cumin</th><th scope=col>curri</th><th scope=col>dark</th><th scope=col>dice</th><th scope=col>dijon</th><th scope=col>dill</th><th scope=col>dough</th><th scope=col>dress</th><th scope=col>dri</th><th scope=col>egg</th><th scope=col>eggplant</th><th scope=col>enchilada</th><th scope=col>extra-virgin</th><th scope=col>extract</th><th scope=col>fat</th><th scope=col>fennel</th><th scope=col>feta</th><th scope=col>fillet</th><th scope=col>fine</th><th scope=col>firm</th><th scope=col>fish</th><th scope=col>flake</th><th scope=col>flat</th><th scope=col>flour</th><th scope=col>free</th><th scope=col>fresh</th><th scope=col>frozen</th><th scope=col>garam</th><th scope=col>garlic</th><th scope=col>ginger</th><th scope=col>golden</th><th scope=col>granul</th><th scope=col>grate</th><th scope=col>greek</th><th scope=col>green</th><th scope=col>ground</th><th scope=col>halv</th><th scope=col>ham</th><th scope=col>heavi</th><th scope=col>hoisin</th><th scope=col>honey</th><th scope=col>hot</th><th scope=col>ice</th><th scope=col>italian</th><th scope=col>jack</th><th scope=col>jalapeno</th><th scope=col>juic</th><th scope=col>kalamata</th><th scope=col>kernel</th><th scope=col>ketchup</th><th scope=col>kosher</th><th scope=col>lamb</th><th scope=col>larg</th><th scope=col>leaf</th><th scope=col>lean</th><th scope=col>leav</th><th scope=col>leek</th><th scope=col>lemon</th><th scope=col>less</th><th scope=col>lettuc</th><th scope=col>light</th><th scope=col>lime</th><th scope=col>low</th><th scope=col>low-fat</th><th scope=col>masala</th><th scope=col>mayonais</th><th scope=col>meat</th><th scope=col>medium</th><th scope=col>mexican</th><th scope=col>milk</th><th scope=col>minc</th><th scope=col>mint</th><th scope=col>mirin</th><th scope=col>mix</th><th scope=col>monterey</th><th scope=col>mozzarella</th><th scope=col>mushroom</th><th scope=col>mustard</th><th scope=col>noodl</th><th scope=col>nutmeg</th><th scope=col>oil</th><th scope=col>oliv</th><th scope=col>onion</th><th scope=col>orang</th><th scope=col>oregano</th><th scope=col>oyster</th><th scope=col>paprika</th><th scope=col>parmesan</th><th scope=col>parsley</th><th scope=col>past</th><th scope=col>pasta</th><th scope=col>pea</th><th scope=col>peanut</th><th scope=col>pecan</th><th scope=col>peel</th><th scope=col>pepper</th><th scope=col>peppercorn</th><th scope=col>plain</th><th scope=col>plum</th><th scope=col>pork</th><th scope=col>potato</th><th scope=col>powder</th><th scope=col>purpl</th><th scope=col>raisin</th><th scope=col>red</th><th scope=col>reduc</th><th scope=col>rib</th><th scope=col>rice</th><th scope=col>ricotta</th><th scope=col>roast</th><th scope=col>root</th><th scope=col>rosemari</th><th scope=col>saffron</th><th scope=col>sage</th><th scope=col>salsa</th><th scope=col>salt</th><th scope=col>sauc</th><th scope=col>sausag</th><th scope=col>scallion</th><th scope=col>sea</th><th scope=col>season</th><th scope=col>seed</th><th scope=col>serrano</th><th scope=col>sesam</th><th scope=col>shallot</th><th scope=col>sharp</th><th scope=col>shell</th><th scope=col>sherri</th><th scope=col>shiitak</th><th scope=col>shoulder</th><th scope=col>shred</th><th scope=col>shrimp</th><th scope=col>skinless</th><th scope=col>slice</th><th scope=col>smoke</th><th scope=col>soda</th><th scope=col>sodium</th><th scope=col>soup</th><th scope=col>sour</th><th scope=col>soy</th><th scope=col>spaghetti</th><th scope=col>spinach</th><th scope=col>spray</th><th scope=col>sprig</th><th scope=col>spring</th><th scope=col>squash</th><th scope=col>starch</th><th scope=col>steak</th><th scope=col>stick</th><th scope=col>stock</th><th scope=col>sugar</th><th scope=col>sweet</th><th scope=col>sweeten</th><th scope=col>syrup</th><th scope=col>taco</th><th scope=col>thai</th><th scope=col>thigh</th><th scope=col>thyme</th><th scope=col>toast</th><th scope=col>tofu</th><th scope=col>tomato</th><th scope=col>tortilla</th><th scope=col>tumer</th><th scope=col>turkey</th><th scope=col>turmer</th><th scope=col>unsalt</th><th scope=col>unsweeten</th><th scope=col>vanilla</th><th scope=col>veget</th><th scope=col>vinegar</th><th scope=col>warm</th><th scope=col>water</th><th scope=col>wedg</th><th scope=col>wheat</th><th scope=col>whip</th><th scope=col>white</th><th scope=col>whole</th><th scope=col>wine</th><th scope=col>worcestershir</th><th scope=col>yeast</th><th scope=col>yellow</th><th scope=col>yogurt</th><th scope=col>yolk</th><th scope=col>zest</th><th scope=col>zucchini</th><th scope=col>cuisine</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>1</th><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>greek</td></tr>\n",
       "\t<tr><th scope=row>2</th><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>2</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>2</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>2</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>southern_us</td></tr>\n",
       "\t<tr><th scope=row>3</th><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>2</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>filipino</td></tr>\n",
       "\t<tr><th scope=row>4</th><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>1</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>indian</td></tr>\n",
       "\t<tr><th scope=row>5</th><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>2</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>indian</td></tr>\n",
       "\t<tr><th scope=row>6</th><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>2</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>2</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>2</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>2</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>jamaican</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllll}\n",
       "  & all-purpos & allspic & almond & and & appl & avocado & babi & bacon & bake & balsam & basil & bay & bean & beansprout & beef & bell & black & boil & boneless & bread & breast & broccoli & broth & brown & butter & buttermilk & cabbag & canola & caper & cardamom & carrot & cayenn & celeri & cheddar & chees & cherri & chicken & chickpea & chile & chili & chines & chip & chipotl & chive & chocol & chop & cider & cilantro & cinnamon & clove & coars & coconut & cold & condens & confection & cook & coriand & corn & cornmeal & crack & cream & crumb & crumbl & crush & cucumb & cumin & curri & dark & dice & dijon & dill & dough & dress & dri & egg & eggplant & enchilada & extra-virgin & extract & fat & fennel & feta & fillet & fine & firm & fish & flake & flat & flour & free & fresh & frozen & garam & garlic & ginger & golden & granul & grate & greek & green & ground & halv & ham & heavi & hoisin & honey & hot & ice & italian & jack & jalapeno & juic & kalamata & kernel & ketchup & kosher & lamb & larg & leaf & lean & leav & leek & lemon & less & lettuc & light & lime & low & low-fat & masala & mayonais & meat & medium & mexican & milk & minc & mint & mirin & mix & monterey & mozzarella & mushroom & mustard & noodl & nutmeg & oil & oliv & onion & orang & oregano & oyster & paprika & parmesan & parsley & past & pasta & pea & peanut & pecan & peel & pepper & peppercorn & plain & plum & pork & potato & powder & purpl & raisin & red & reduc & rib & rice & ricotta & roast & root & rosemari & saffron & sage & salsa & salt & sauc & sausag & scallion & sea & season & seed & serrano & sesam & shallot & sharp & shell & sherri & shiitak & shoulder & shred & shrimp & skinless & slice & smoke & soda & sodium & soup & sour & soy & spaghetti & spinach & spray & sprig & spring & squash & starch & steak & stick & stock & sugar & sweet & sweeten & syrup & taco & thai & thigh & thyme & toast & tofu & tomato & tortilla & tumer & turkey & turmer & unsalt & unsweeten & vanilla & veget & vinegar & warm & water & wedg & wheat & whip & white & whole & wine & worcestershir & yeast & yellow & yogurt & yolk & zest & zucchini & cuisine\\\\\n",
       "\\hline\n",
       "\t1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & greek\\\\\n",
       "\t2 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 2 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 2 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 2 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & southern_us\\\\\n",
       "\t3 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 2 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & filipino\\\\\n",
       "\t4 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 1 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & indian\\\\\n",
       "\t5 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 1 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 2 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & indian\\\\\n",
       "\t6 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 1 & 0 & 0 & 0 & 2 & 0 & 0 & 0 & 0 & 0 & 2 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 2 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 2 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & jamaican\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "  all-purpos allspic almond and appl avocado babi bacon bake balsam basil bay\n",
       "1          0       0      0   0    0       0    0     0    0      0     0   0\n",
       "2          0       0      0   0    0       0    0     0    0      0     0   0\n",
       "3          0       0      0   0    0       0    0     0    0      0     0   0\n",
       "4          0       0      0   0    0       0    0     0    0      0     0   0\n",
       "5          0       0      0   0    0       0    0     0    0      0     0   1\n",
       "6          0       0      0   0    0       0    0     0    1      0     0   0\n",
       "  bean beansprout beef bell black boil boneless bread breast broccoli broth\n",
       "1    1          0    0    0     1    0        0     0      0        0     0\n",
       "2    0          0    0    0     1    0        0     0      0        0     0\n",
       "3    0          0    0    0     0    0        0     0      1        0     0\n",
       "4    0          0    0    0     0    0        0     0      0        0     0\n",
       "5    0          0    0    0     1    0        1     0      0        0     0\n",
       "6    0          0    0    0     0    0        0     0      0        0     0\n",
       "  brown butter buttermilk cabbag canola caper cardamom carrot cayenn celeri\n",
       "1     0      0          0      0      0     0        0      0      0      0\n",
       "2     0      0          0      0      0     0        0      0      0      0\n",
       "3     0      1          0      0      0     0        0      0      0      0\n",
       "4     0      0          0      0      0     0        0      0      0      0\n",
       "5     0      1          0      0      0     0        0      0      1      0\n",
       "6     0      1          0      0      0     0        0      0      0      0\n",
       "  cheddar chees cherri chicken chickpea chile chili chines chip chipotl chive\n",
       "1       0     1      0       0        0     0     0      0    0       0     0\n",
       "2       0     0      0       0        0     0     0      0    0       0     0\n",
       "3       0     0      0       2        0     0     1      0    0       0     0\n",
       "4       0     0      0       0        0     0     0      0    0       0     0\n",
       "5       0     0      0       1        0     0     1      0    0       0     0\n",
       "6       0     0      0       0        0     0     0      0    0       0     0\n",
       "  chocol chop cider cilantro cinnamon clove coars coconut cold condens\n",
       "1      0    0     0        0        0     0     0       0    0       0\n",
       "2      0    0     0        0        0     0     0       0    0       0\n",
       "3      0    0     0        0        0     0     0       0    0       0\n",
       "4      0    0     0        0        0     0     0       0    0       0\n",
       "5      0    0     0        0        0     0     0       0    0       0\n",
       "6      0    0     0        0        1     0     0       0    0       0\n",
       "  confection cook coriand corn cornmeal crack cream crumb crumbl crush cucumb\n",
       "1          0    0       0    0        0     0     0     0      1     0      0\n",
       "2          0    0       0    1        0     0     0     0      0     0      0\n",
       "3          0    1       0    0        0     0     0     0      0     0      0\n",
       "4          0    0       0    0        0     0     0     0      0     0      0\n",
       "5          0    0       0    0        0     0     1     0      0     0      0\n",
       "6          0    0       0    0        0     0     0     0      0     0      0\n",
       "  cumin curri dark dice dijon dill dough dress dri egg eggplant enchilada\n",
       "1     0     0    0    0     0    0     0     0   0   0        0         0\n",
       "2     0     0    0    0     0    0     0     0   0   1        0         0\n",
       "3     0     0    0    0     0    0     0     0   0   1        0         0\n",
       "4     0     0    0    0     0    0     0     0   0   0        0         0\n",
       "5     1     0    0    0     0    0     0     0   0   0        0         0\n",
       "6     0     0    0    0     0    0     0     0   0   1        0         0\n",
       "  extra-virgin extract fat fennel feta fillet fine firm fish flake flat flour\n",
       "1            0       0   0      0    1      0    0    0    0     0    0     0\n",
       "2            0       0   0      0    0      0    0    0    0     0    0     1\n",
       "3            0       0   0      0    0      0    0    0    0     0    0     0\n",
       "4            0       0   0      0    0      0    0    0    0     0    0     0\n",
       "5            0       0   0      0    0      0    0    0    0     0    0     0\n",
       "6            0       1   0      0    0      0    0    0    0     0    0     1\n",
       "  free fresh frozen garam garlic ginger golden granul grate greek green ground\n",
       "1    0     0      0     0      1      0      0      0     0     0     0      0\n",
       "2    0     0      0     0      0      0      0      0     0     0     1      2\n",
       "3    0     0      0     0      1      0      0      0     0     0     1      0\n",
       "4    0     0      0     0      0      0      0      0     0     0     0      0\n",
       "5    0     0      0     1      1      0      0      0     0     0     0      1\n",
       "6    0     1      0     0      0      2      0      0     0     0     0      2\n",
       "  halv ham heavi hoisin honey hot ice italian jack jalapeno juic kalamata\n",
       "1    0   0     0      0     0   0   0       0    0        0    0        0\n",
       "2    0   0     0      0     0   0   0       0    0        0    0        0\n",
       "3    0   0     0      0     0   0   0       0    0        0    0        0\n",
       "4    0   0     0      0     0   0   0       0    0        0    0        0\n",
       "5    0   0     0      0     0   0   0       0    0        0    1        0\n",
       "6    0   0     0      0     0   0   0       0    0        0    0        0\n",
       "  kernel ketchup kosher lamb larg leaf lean leav leek lemon less lettuc light\n",
       "1      0       0      0    0    0    0    0    0    0     0    0      1     0\n",
       "2      0       0      0    0    0    0    0    0    0     0    0      0     0\n",
       "3      0       0      0    0    0    0    0    0    0     0    0      0     0\n",
       "4      0       0      0    0    0    0    0    0    0     0    0      0     0\n",
       "5      0       0      0    0    0    1    0    0    0     1    0      0     0\n",
       "6      0       0      0    0    0    0    0    0    0     0    0      0     0\n",
       "  lime low low-fat masala mayonais meat medium mexican milk minc mint mirin mix\n",
       "1    0   0       0      0        0    0      0       0    0    0    0     0   0\n",
       "2    0   0       0      0        0    0      0       0    1    0    0     0   0\n",
       "3    0   0       0      0        1    0      0       0    0    0    0     0   0\n",
       "4    0   0       0      0        0    0      0       0    0    0    0     0   0\n",
       "5    0   0       0      1        0    0      0       0    1    0    0     0   0\n",
       "6    0   0       0      0        0    0      0       0    1    0    0     0   0\n",
       "  monterey mozzarella mushroom mustard noodl nutmeg oil oliv onion orang\n",
       "1        0          0        0       0     0      0   0    1     1     0\n",
       "2        0          0        0       0     0      0   1    0     0     0\n",
       "3        0          0        0       0     0      0   1    0     1     0\n",
       "4        0          0        0       0     0      0   1    0     0     0\n",
       "5        0          0        0       0     0      0   1    0     1     0\n",
       "6        0          0        0       0     0      0   0    0     0     0\n",
       "  oregano oyster paprika parmesan parsley past pasta pea peanut pecan peel\n",
       "1       0      0       0        0       0    0     0   0      0     0    0\n",
       "2       0      0       0        0       0    0     0   0      0     0    0\n",
       "3       0      0       0        0       0    0     0   0      0     0    0\n",
       "4       0      0       0        0       0    0     0   0      0     0    0\n",
       "5       0      0       0        0       0    1     0   0      0     0    0\n",
       "6       0      0       0        0       0    0     0   0      0     0    0\n",
       "  pepper peppercorn plain plum pork potato powder purpl raisin red reduc rib\n",
       "1      1          0     0    0    0      0      0     1      0   0     0   0\n",
       "2      2          0     1    0    0      0      0     0      0   0     0   0\n",
       "3      1          0     0    0    0      0      1     0      0   0     0   0\n",
       "4      0          0     0    0    0      0      0     0      0   0     0   0\n",
       "5      2          0     0    0    0      0      1     0      0   0     0   0\n",
       "6      0          0     1    0    0      0      2     0      0   0     0   0\n",
       "  rice ricotta roast root rosemari saffron sage salsa salt sauc sausag scallion\n",
       "1    0       0     0    0        0       0    0     0    0    0      0        0\n",
       "2    0       0     0    0        0       0    0     0    1    0      0        0\n",
       "3    0       0     0    0        0       0    0     0    1    1      0        0\n",
       "4    0       0     0    0        0       0    0     0    1    0      0        0\n",
       "5    0       0     0    0        0       0    0     0    1    0      0        0\n",
       "6    0       0     0    1        0       0    0     0    1    0      0        0\n",
       "  sea season seed serrano sesam shallot sharp shell sherri shiitak shoulder\n",
       "1   0      1    0       0     0       0     0     0      0       0        0\n",
       "2   0      0    0       0     0       0     0     0      0       0        0\n",
       "3   0      0    0       0     0       0     0     0      0       0        0\n",
       "4   0      0    0       0     0       0     0     0      0       0        0\n",
       "5   0      0    0       0     0       1     0     0      0       0        0\n",
       "6   0      0    0       0     0       0     0     0      0       0        0\n",
       "  shred shrimp skinless slice smoke soda sodium soup sour soy spaghetti spinach\n",
       "1     0      0        0     0     0    0      0    0    0   0         0       0\n",
       "2     0      0        0     0     0    0      0    0    0   0         0       0\n",
       "3     0      0        0     0     0    0      0    0    0   1         0       0\n",
       "4     0      0        0     0     0    0      0    0    0   0         0       0\n",
       "5     0      0        1     0     0    0      0    0    0   0         0       0\n",
       "6     0      0        0     0     0    0      0    0    0   0         0       0\n",
       "  spray sprig spring squash starch steak stick stock sugar sweet sweeten syrup\n",
       "1     0     0      0      0      0     0     0     0     0     0       0     0\n",
       "2     0     0      0      0      0     0     0     0     0     0       0     0\n",
       "3     0     0      0      0      0     0     0     0     0     0       0     0\n",
       "4     0     0      0      0      0     0     0     0     0     0       0     0\n",
       "5     0     0      0      0      0     0     0     0     0     0       0     0\n",
       "6     0     0      0      0      0     0     0     0     2     0       0     0\n",
       "  taco thai thigh thyme toast tofu tomato tortilla tumer turkey turmer unsalt\n",
       "1    0    0     0     0     0    0      1        0     0      0      0      0\n",
       "2    0    0     0     1     0    0      2        0     0      0      0      0\n",
       "3    0    0     0     0     0    0      0        0     0      0      0      0\n",
       "4    0    0     0     0     0    0      0        0     0      0      0      0\n",
       "5    0    0     1     0     0    0      0        0     0      0      0      0\n",
       "6    0    0     0     0     0    0      0        0     0      0      0      0\n",
       "  unsweeten vanilla veget vinegar warm water wedg wheat whip white whole wine\n",
       "1         0       0     0       0    0     0    0     0    0     0     0    0\n",
       "2         0       0     1       0    0     0    0     0    0     0     0    0\n",
       "3         0       0     0       0    0     0    0     0    0     0     0    0\n",
       "4         0       0     1       0    0     1    0     1    0     0     0    0\n",
       "5         0       0     0       0    0     1    0     0    0     0     0    0\n",
       "6         0       1     0       0    0     0    0     0    0     0     0    0\n",
       "  worcestershir yeast yellow yogurt yolk zest zucchini     cuisine\n",
       "1             0     0      0      0    0    0        0       greek\n",
       "2             0     0      1      0    0    0        0 southern_us\n",
       "3             0     0      1      0    0    0        0    filipino\n",
       "4             0     0      0      0    0    0        0      indian\n",
       "5             0     0      0      1    0    0        0      indian\n",
       "6             0     0      0      0    0    0        0    jamaican"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "head(ingredientsDTM_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "inTrain <- createDataPartition(y = ingredientsDTM_train$cuisine, p = 0.6, list = FALSE)\n",
    "train_data <- ingredientsDTM_train[inTrain,]\n",
    "vaild_data <- ingredientsDTM_train[-inTrain,]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "test_data <- ingredientsDTM_test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<ol class=list-inline>\n",
       "\t<li>23871</li>\n",
       "\t<li>251</li>\n",
       "</ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 23871\n",
       "\\item 251\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 23871\n",
       "2. 251\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "[1] 23871   251"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/html": [
       "<ol class=list-inline>\n",
       "\t<li>15903</li>\n",
       "\t<li>251</li>\n",
       "</ol>\n"
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      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 15903\n",
       "\\item 251\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 15903\n",
       "2. 251\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "[1] 15903   251"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dim(train_data)\n",
    "dim(vaild_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "ingredients_sum <- apply(rbind(ingredientsDTM_train[,-251], ingredientsDTM_test[,-251]), 2, sum)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<dl class=dl-horizontal>\n",
       "\t<dt>all-purpos</dt>\n",
       "\t\t<dd>5820</dd>\n",
       "\t<dt>allspic</dt>\n",
       "\t\t<dd>682</dd>\n",
       "\t<dt>almond</dt>\n",
       "\t\t<dd>1452</dd>\n",
       "\t<dt>and</dt>\n",
       "\t\t<dd>622</dd>\n",
       "\t<dt>appl</dt>\n",
       "\t\t<dd>1036</dd>\n",
       "\t<dt>avocado</dt>\n",
       "\t\t<dd>1614</dd>\n",
       "</dl>\n"
      ],
      "text/latex": [
       "\\begin{description*}\n",
       "\\item[all-purpos] 5820\n",
       "\\item[allspic] 682\n",
       "\\item[almond] 1452\n",
       "\\item[and] 622\n",
       "\\item[appl] 1036\n",
       "\\item[avocado] 1614\n",
       "\\end{description*}\n"
      ],
      "text/markdown": [
       "all-purpos\n",
       ":   5820allspic\n",
       ":   682almond\n",
       ":   1452and\n",
       ":   622appl\n",
       ":   1036avocado\n",
       ":   1614\n",
       "\n"
      ],
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       "all-purpos    allspic     almond        and       appl    avocado \n",
       "      5820        682       1452        622       1036       1614 "
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "head(ingredients_sum)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "ingredients_sum <- ingredients_sum[order(ingredients_sum, decreasing=T)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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       "<ol class=list-inline>\n",
       "\t<li>\"pepper\"</li>\n",
       "\t<li>\"salt\"</li>\n",
       "\t<li>\"oil\"</li>\n",
       "\t<li>\"onion\"</li>\n",
       "\t<li>\"garlic\"</li>\n",
       "\t<li>\"fresh\"</li>\n",
       "\t<li>\"ground\"</li>\n",
       "\t<li>\"sauc\"</li>\n",
       "\t<li>\"sugar\"</li>\n",
       "\t<li>\"oliv\"</li>\n",
       "\t<li>\"chees\"</li>\n",
       "\t<li>\"chicken\"</li>\n",
       "\t<li>\"tomato\"</li>\n",
       "\t<li>\"black\"</li>\n",
       "\t<li>\"water\"</li>\n",
       "\t<li>\"red\"</li>\n",
       "\t<li>\"green\"</li>\n",
       "\t<li>\"egg\"</li>\n",
       "\t<li>\"flour\"</li>\n",
       "\t<li>\"powder\"</li>\n",
       "\t<li>\"butter\"</li>\n",
       "\t<li>\"dri\"</li>\n",
       "\t<li>\"chop\"</li>\n",
       "\t<li>\"clove\"</li>\n",
       "\t<li>\"white\"</li>\n",
       "\t<li>\"juic\"</li>\n",
       "\t<li>\"chili\"</li>\n",
       "\t<li>\"cream\"</li>\n",
       "\t<li>\"rice\"</li>\n",
       "\t<li>\"cilantro\"</li>\n",
       "\t<li>\"veget\"</li>\n",
       "\t<li>\"milk\"</li>\n",
       "\t<li>\"lemon\"</li>\n",
       "\t<li>\"leav\"</li>\n",
       "\t<li>\"larg\"</li>\n",
       "\t<li>\"ginger\"</li>\n",
       "\t<li>\"corn\"</li>\n",
       "\t<li>\"vinegar\"</li>\n",
       "\t<li>\"lime\"</li>\n",
       "\t<li>\"soy\"</li>\n",
       "\t<li>\"all-purpos\"</li>\n",
       "\t<li>\"cumin\"</li>\n",
       "\t<li>\"broth\"</li>\n",
       "\t<li>\"bell\"</li>\n",
       "\t<li>\"wine\"</li>\n",
       "\t<li>\"parsley\"</li>\n",
       "\t<li>\"seed\"</li>\n",
       "\t<li>\"bean\"</li>\n",
       "\t<li>\"cook\"</li>\n",
       "\t<li>\"sesam\"</li>\n",
       "\t<li>\"grate\"</li>\n",
       "\t<li>\"breast\"</li>\n",
       "\t<li>\"carrot\"</li>\n",
       "\t<li>\"kosher\"</li>\n",
       "\t<li>\"basil\"</li>\n",
       "\t<li>\"beef\"</li>\n",
       "\t<li>\"bake\"</li>\n",
       "\t<li>\"brown\"</li>\n",
       "\t<li>\"chile\"</li>\n",
       "\t<li>\"past\"</li>\n",
       "\t<li>\"unsalt\"</li>\n",
       "\t<li>\"potato\"</li>\n",
       "\t<li>\"parmesan\"</li>\n",
       "\t<li>\"oregano\"</li>\n",
       "\t<li>\"extra-virgin\"</li>\n",
       "\t<li>\"boneless\"</li>\n",
       "\t<li>\"shred\"</li>\n",
       "\t<li>\"tortilla\"</li>\n",
       "\t<li>\"cinnamon\"</li>\n",
       "\t<li>\"season\"</li>\n",
       "\t<li>\"thyme\"</li>\n",
       "\t<li>\"pork\"</li>\n",
       "\t<li>\"mushroom\"</li>\n",
       "\t<li>\"shrimp\"</li>\n",
       "\t<li>\"dice\"</li>\n",
       "\t<li>\"yellow\"</li>\n",
       "\t<li>\"bread\"</li>\n",
       "\t<li>\"skinless\"</li>\n",
       "\t<li>\"vanilla\"</li>\n",
       "\t<li>\"coconut\"</li>\n",
       "\t<li>\"sodium\"</li>\n",
       "\t<li>\"coriand\"</li>\n",
       "\t<li>\"celeri\"</li>\n",
       "\t<li>\"bay\"</li>\n",
       "\t<li>\"cayenn\"</li>\n",
       "\t<li>\"minc\"</li>\n",
       "\t<li>\"leaf\"</li>\n",
       "\t<li>\"crush\"</li>\n",
       "\t<li>\"whole\"</li>\n",
       "\t<li>\"spray\"</li>\n",
       "\t<li>\"flake\"</li>\n",
       "\t<li>\"sour\"</li>\n",
       "\t<li>\"scallion\"</li>\n",
       "\t<li>\"slice\"</li>\n",
       "\t<li>\"starch\"</li>\n",
       "\t<li>\"paprika\"</li>\n",
       "\t<li>\"stock\"</li>\n",
       "\t<li>\"hot\"</li>\n",
       "\t<li>\"purpl\"</li>\n",
       "\t<li>\"cheddar\"</li>\n",
       "\t<li>\"fish\"</li>\n",
       "\t<li>\"orang\"</li>\n",
       "\t<li>\"mustard\"</li>\n",
       "\t<li>\"jalapeno\"</li>\n",
       "\t<li>\"extract\"</li>\n",
       "\t<li>\"peanut\"</li>\n",
       "\t<li>\"curri\"</li>\n",
       "\t<li>\"sausag\"</li>\n",
       "\t<li>\"frozen\"</li>\n",
       "\t<li>\"sweet\"</li>\n",
       "\t<li>\"low\"</li>\n",
       "\t<li>\"shallot\"</li>\n",
       "\t<li>\"sea\"</li>\n",
       "\t<li>\"pea\"</li>\n",
       "\t<li>\"fat\"</li>\n",
       "\t<li>\"light\"</li>\n",
       "\t<li>\"mozzarella\"</li>\n",
       "\t<li>\"honey\"</li>\n",
       "\t<li>\"heavi\"</li>\n",
       "\t<li>\"noodl\"</li>\n",
       "\t<li>\"italian\"</li>\n",
       "\t<li>\"mint\"</li>\n",
       "\t<li>\"spinach\"</li>\n",
       "\t<li>\"salsa\"</li>\n",
       "\t<li>\"roast\"</li>\n",
       "\t<li>\"canola\"</li>\n",
       "\t<li>\"avocado\"</li>\n",
       "\t<li>\"peel\"</li>\n",
       "\t<li>\"cabbag\"</li>\n",
       "\t<li>\"pasta\"</li>\n",
       "\t<li>\"bacon\"</li>\n",
       "\t<li>\"lettuc\"</li>\n",
       "\t<li>\"yogurt\"</li>\n",
       "\t<li>\"cucumb\"</li>\n",
       "\t<li>\"almond\"</li>\n",
       "\t<li>\"yolk\"</li>\n",
       "\t<li>\"fillet\"</li>\n",
       "\t<li>\"flat\"</li>\n",
       "\t<li>\"whip\"</li>\n",
       "\t<li>\"masala\"</li>\n",
       "\t<li>\"nutmeg\"</li>\n",
       "\t<li>\"dark\"</li>\n",
       "\t<li>\"soda\"</li>\n",
       "\t<li>\"granul\"</li>\n",
       "\t<li>\"buttermilk\"</li>\n",
       "\t<li>\"crumb\"</li>\n",
       "\t<li>\"halv\"</li>\n",
       "\t<li>\"turmer\"</li>\n",
       "\t<li>\"plum\"</li>\n",
       "\t<li>\"rib\"</li>\n",
       "\t<li>\"jack\"</li>\n",
       "\t<li>\"garam\"</li>\n",
       "\t<li>\"steak\"</li>\n",
       "\t<li>\"zucchini\"</li>\n",
       "\t<li>\"fine\"</li>\n",
       "\t<li>\"zest\"</li>\n",
       "\t<li>\"plain\"</li>\n",
       "\t<li>\"toast\"</li>\n",
       "\t<li>\"mix\"</li>\n",
       "\t<li>\"chocol\"</li>\n",
       "\t<li>\"free\"</li>\n",
       "\t<li>\"smoke\"</li>\n",
       "\t<li>\"thigh\"</li>\n",
       "\t<li>\"peppercorn\"</li>\n",
       "\t<li>\"appl\"</li>\n",
       "\t<li>\"rosemari\"</li>\n",
       "\t<li>\"sprig\"</li>\n",
       "\t<li>\"mayonais\"</li>\n",
       "\t<li>\"babi\"</li>\n",
       "\t<li>\"tumer\"</li>\n",
       "\t<li>\"yeast\"</li>\n",
       "\t<li>\"stick\"</li>\n",
       "\t<li>\"reduc\"</li>\n",
       "\t<li>\"cardamom\"</li>\n",
       "\t<li>\"thai\"</li>\n",
       "\t<li>\"ricotta\"</li>\n",
       "\t<li>\"chines\"</li>\n",
       "\t<li>\"coars\"</li>\n",
       "\t<li>\"wedg\"</li>\n",
       "\t<li>\"raisin\"</li>\n",
       "\t<li>\"low-fat\"</li>\n",
       "\t<li>\"worcestershir\"</li>\n",
       "\t<li>\"ham\"</li>\n",
       "\t<li>\"cider\"</li>\n",
       "\t<li>\"feta\"</li>\n",
       "\t<li>\"fennel\"</li>\n",
       "\t<li>\"cherri\"</li>\n",
       "\t<li>\"kernel\"</li>\n",
       "\t<li>\"meat\"</li>\n",
       "\t<li>\"taco\"</li>\n",
       "\t<li>\"tofu\"</li>\n",
       "\t<li>\"sherri\"</li>\n",
       "\t<li>\"turkey\"</li>\n",
       "\t<li>\"chive\"</li>\n",
       "\t<li>\"wheat\"</li>\n",
       "\t<li>\"ice\"</li>\n",
       "\t<li>\"syrup\"</li>\n",
       "\t<li>\"eggplant\"</li>\n",
       "\t<li>\"pecan\"</li>\n",
       "\t<li>\"warm\"</li>\n",
       "\t<li>\"medium\"</li>\n",
       "\t<li>\"shiitak\"</li>\n",
       "\t<li>\"balsam\"</li>\n",
       "\t<li>\"monterey\"</li>\n",
       "\t<li>\"lamb\"</li>\n",
       "\t<li>\"oyster\"</li>\n",
       "\t<li>\"chipotl\"</li>\n",
       "\t<li>\"dijon\"</li>\n",
       "\t<li>\"root\"</li>\n",
       "\t<li>\"chip\"</li>\n",
       "\t<li>\"serrano\"</li>\n",
       "\t<li>\"lean\"</li>\n",
       "\t<li>\"less\"</li>\n",
       "\t<li>\"unsweeten\"</li>\n",
       "\t<li>\"allspic\"</li>\n",
       "\t<li>\"condens\"</li>\n",
       "\t<li>\"caper\"</li>\n",
       "\t<li>\"cold\"</li>\n",
       "\t<li>\"firm\"</li>\n",
       "\t<li>\"broccoli\"</li>\n",
       "\t<li>\"mexican\"</li>\n",
       "\t<li>\"ketchup\"</li>\n",
       "\t<li>\"boil\"</li>\n",
       "\t<li>\"cornmeal\"</li>\n",
       "\t<li>\"crumbl\"</li>\n",
       "\t<li>\"mirin\"</li>\n",
       "\t<li>\"and\"</li>\n",
       "\t<li>\"greek\"</li>\n",
       "\t<li>\"saffron\"</li>\n",
       "\t<li>\"spring\"</li>\n",
       "\t<li>\"soup\"</li>\n",
       "\t<li>\"sharp\"</li>\n",
       "\t<li>\"chickpea\"</li>\n",
       "\t<li>\"beansprout\"</li>\n",
       "\t<li>\"dough\"</li>\n",
       "\t<li>\"leek\"</li>\n",
       "\t<li>\"sage\"</li>\n",
       "\t<li>\"squash\"</li>\n",
       "\t<li>\"dill\"</li>\n",
       "\t<li>\"sweeten\"</li>\n",
       "\t<li>\"spaghetti\"</li>\n",
       "\t<li>\"dress\"</li>\n",
       "\t<li>\"shoulder\"</li>\n",
       "\t<li>\"golden\"</li>\n",
       "\t<li>\"hoisin\"</li>\n",
       "\t<li>\"enchilada\"</li>\n",
       "\t<li>\"kalamata\"</li>\n",
       "\t<li>\"crack\"</li>\n",
       "\t<li>\"shell\"</li>\n",
       "\t<li>\"confection\"</li>\n",
       "</ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item \"pepper\"\n",
       "\\item \"salt\"\n",
       "\\item \"oil\"\n",
       "\\item \"onion\"\n",
       "\\item \"garlic\"\n",
       "\\item \"fresh\"\n",
       "\\item \"ground\"\n",
       "\\item \"sauc\"\n",
       "\\item \"sugar\"\n",
       "\\item \"oliv\"\n",
       "\\item \"chees\"\n",
       "\\item \"chicken\"\n",
       "\\item \"tomato\"\n",
       "\\item \"black\"\n",
       "\\item \"water\"\n",
       "\\item \"red\"\n",
       "\\item \"green\"\n",
       "\\item \"egg\"\n",
       "\\item \"flour\"\n",
       "\\item \"powder\"\n",
       "\\item \"butter\"\n",
       "\\item \"dri\"\n",
       "\\item \"chop\"\n",
       "\\item \"clove\"\n",
       "\\item \"white\"\n",
       "\\item \"juic\"\n",
       "\\item \"chili\"\n",
       "\\item \"cream\"\n",
       "\\item \"rice\"\n",
       "\\item \"cilantro\"\n",
       "\\item \"veget\"\n",
       "\\item \"milk\"\n",
       "\\item \"lemon\"\n",
       "\\item \"leav\"\n",
       "\\item \"larg\"\n",
       "\\item \"ginger\"\n",
       "\\item \"corn\"\n",
       "\\item \"vinegar\"\n",
       "\\item \"lime\"\n",
       "\\item \"soy\"\n",
       "\\item \"all-purpos\"\n",
       "\\item \"cumin\"\n",
       "\\item \"broth\"\n",
       "\\item \"bell\"\n",
       "\\item \"wine\"\n",
       "\\item \"parsley\"\n",
       "\\item \"seed\"\n",
       "\\item \"bean\"\n",
       "\\item \"cook\"\n",
       "\\item \"sesam\"\n",
       "\\item \"grate\"\n",
       "\\item \"breast\"\n",
       "\\item \"carrot\"\n",
       "\\item \"kosher\"\n",
       "\\item \"basil\"\n",
       "\\item \"beef\"\n",
       "\\item \"bake\"\n",
       "\\item \"brown\"\n",
       "\\item \"chile\"\n",
       "\\item \"past\"\n",
       "\\item \"unsalt\"\n",
       "\\item \"potato\"\n",
       "\\item \"parmesan\"\n",
       "\\item \"oregano\"\n",
       "\\item \"extra-virgin\"\n",
       "\\item \"boneless\"\n",
       "\\item \"shred\"\n",
       "\\item \"tortilla\"\n",
       "\\item \"cinnamon\"\n",
       "\\item \"season\"\n",
       "\\item \"thyme\"\n",
       "\\item \"pork\"\n",
       "\\item \"mushroom\"\n",
       "\\item \"shrimp\"\n",
       "\\item \"dice\"\n",
       "\\item \"yellow\"\n",
       "\\item \"bread\"\n",
       "\\item \"skinless\"\n",
       "\\item \"vanilla\"\n",
       "\\item \"coconut\"\n",
       "\\item \"sodium\"\n",
       "\\item \"coriand\"\n",
       "\\item \"celeri\"\n",
       "\\item \"bay\"\n",
       "\\item \"cayenn\"\n",
       "\\item \"minc\"\n",
       "\\item \"leaf\"\n",
       "\\item \"crush\"\n",
       "\\item \"whole\"\n",
       "\\item \"spray\"\n",
       "\\item \"flake\"\n",
       "\\item \"sour\"\n",
       "\\item \"scallion\"\n",
       "\\item \"slice\"\n",
       "\\item \"starch\"\n",
       "\\item \"paprika\"\n",
       "\\item \"stock\"\n",
       "\\item \"hot\"\n",
       "\\item \"purpl\"\n",
       "\\item \"cheddar\"\n",
       "\\item \"fish\"\n",
       "\\item \"orang\"\n",
       "\\item \"mustard\"\n",
       "\\item \"jalapeno\"\n",
       "\\item \"extract\"\n",
       "\\item \"peanut\"\n",
       "\\item \"curri\"\n",
       "\\item \"sausag\"\n",
       "\\item \"frozen\"\n",
       "\\item \"sweet\"\n",
       "\\item \"low\"\n",
       "\\item \"shallot\"\n",
       "\\item \"sea\"\n",
       "\\item \"pea\"\n",
       "\\item \"fat\"\n",
       "\\item \"light\"\n",
       "\\item \"mozzarella\"\n",
       "\\item \"honey\"\n",
       "\\item \"heavi\"\n",
       "\\item \"noodl\"\n",
       "\\item \"italian\"\n",
       "\\item \"mint\"\n",
       "\\item \"spinach\"\n",
       "\\item \"salsa\"\n",
       "\\item \"roast\"\n",
       "\\item \"canola\"\n",
       "\\item \"avocado\"\n",
       "\\item \"peel\"\n",
       "\\item \"cabbag\"\n",
       "\\item \"pasta\"\n",
       "\\item \"bacon\"\n",
       "\\item \"lettuc\"\n",
       "\\item \"yogurt\"\n",
       "\\item \"cucumb\"\n",
       "\\item \"almond\"\n",
       "\\item \"yolk\"\n",
       "\\item \"fillet\"\n",
       "\\item \"flat\"\n",
       "\\item \"whip\"\n",
       "\\item \"masala\"\n",
       "\\item \"nutmeg\"\n",
       "\\item \"dark\"\n",
       "\\item \"soda\"\n",
       "\\item \"granul\"\n",
       "\\item \"buttermilk\"\n",
       "\\item \"crumb\"\n",
       "\\item \"halv\"\n",
       "\\item \"turmer\"\n",
       "\\item \"plum\"\n",
       "\\item \"rib\"\n",
       "\\item \"jack\"\n",
       "\\item \"garam\"\n",
       "\\item \"steak\"\n",
       "\\item \"zucchini\"\n",
       "\\item \"fine\"\n",
       "\\item \"zest\"\n",
       "\\item \"plain\"\n",
       "\\item \"toast\"\n",
       "\\item \"mix\"\n",
       "\\item \"chocol\"\n",
       "\\item \"free\"\n",
       "\\item \"smoke\"\n",
       "\\item \"thigh\"\n",
       "\\item \"peppercorn\"\n",
       "\\item \"appl\"\n",
       "\\item \"rosemari\"\n",
       "\\item \"sprig\"\n",
       "\\item \"mayonais\"\n",
       "\\item \"babi\"\n",
       "\\item \"tumer\"\n",
       "\\item \"yeast\"\n",
       "\\item \"stick\"\n",
       "\\item \"reduc\"\n",
       "\\item \"cardamom\"\n",
       "\\item \"thai\"\n",
       "\\item \"ricotta\"\n",
       "\\item \"chines\"\n",
       "\\item \"coars\"\n",
       "\\item \"wedg\"\n",
       "\\item \"raisin\"\n",
       "\\item \"low-fat\"\n",
       "\\item \"worcestershir\"\n",
       "\\item \"ham\"\n",
       "\\item \"cider\"\n",
       "\\item \"feta\"\n",
       "\\item \"fennel\"\n",
       "\\item \"cherri\"\n",
       "\\item \"kernel\"\n",
       "\\item \"meat\"\n",
       "\\item \"taco\"\n",
       "\\item \"tofu\"\n",
       "\\item \"sherri\"\n",
       "\\item \"turkey\"\n",
       "\\item \"chive\"\n",
       "\\item \"wheat\"\n",
       "\\item \"ice\"\n",
       "\\item \"syrup\"\n",
       "\\item \"eggplant\"\n",
       "\\item \"pecan\"\n",
       "\\item \"warm\"\n",
       "\\item \"medium\"\n",
       "\\item \"shiitak\"\n",
       "\\item \"balsam\"\n",
       "\\item \"monterey\"\n",
       "\\item \"lamb\"\n",
       "\\item \"oyster\"\n",
       "\\item \"chipotl\"\n",
       "\\item \"dijon\"\n",
       "\\item \"root\"\n",
       "\\item \"chip\"\n",
       "\\item \"serrano\"\n",
       "\\item \"lean\"\n",
       "\\item \"less\"\n",
       "\\item \"unsweeten\"\n",
       "\\item \"allspic\"\n",
       "\\item \"condens\"\n",
       "\\item \"caper\"\n",
       "\\item \"cold\"\n",
       "\\item \"firm\"\n",
       "\\item \"broccoli\"\n",
       "\\item \"mexican\"\n",
       "\\item \"ketchup\"\n",
       "\\item \"boil\"\n",
       "\\item \"cornmeal\"\n",
       "\\item \"crumbl\"\n",
       "\\item \"mirin\"\n",
       "\\item \"and\"\n",
       "\\item \"greek\"\n",
       "\\item \"saffron\"\n",
       "\\item \"spring\"\n",
       "\\item \"soup\"\n",
       "\\item \"sharp\"\n",
       "\\item \"chickpea\"\n",
       "\\item \"beansprout\"\n",
       "\\item \"dough\"\n",
       "\\item \"leek\"\n",
       "\\item \"sage\"\n",
       "\\item \"squash\"\n",
       "\\item \"dill\"\n",
       "\\item \"sweeten\"\n",
       "\\item \"spaghetti\"\n",
       "\\item \"dress\"\n",
       "\\item \"shoulder\"\n",
       "\\item \"golden\"\n",
       "\\item \"hoisin\"\n",
       "\\item \"enchilada\"\n",
       "\\item \"kalamata\"\n",
       "\\item \"crack\"\n",
       "\\item \"shell\"\n",
       "\\item \"confection\"\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. \"pepper\"\n",
       "2. \"salt\"\n",
       "3. \"oil\"\n",
       "4. \"onion\"\n",
       "5. \"garlic\"\n",
       "6. \"fresh\"\n",
       "7. \"ground\"\n",
       "8. \"sauc\"\n",
       "9. \"sugar\"\n",
       "10. \"oliv\"\n",
       "11. \"chees\"\n",
       "12. \"chicken\"\n",
       "13. \"tomato\"\n",
       "14. \"black\"\n",
       "15. \"water\"\n",
       "16. \"red\"\n",
       "17. \"green\"\n",
       "18. \"egg\"\n",
       "19. \"flour\"\n",
       "20. \"powder\"\n",
       "21. \"butter\"\n",
       "22. \"dri\"\n",
       "23. \"chop\"\n",
       "24. \"clove\"\n",
       "25. \"white\"\n",
       "26. \"juic\"\n",
       "27. \"chili\"\n",
       "28. \"cream\"\n",
       "29. \"rice\"\n",
       "30. \"cilantro\"\n",
       "31. \"veget\"\n",
       "32. \"milk\"\n",
       "33. \"lemon\"\n",
       "34. \"leav\"\n",
       "35. \"larg\"\n",
       "36. \"ginger\"\n",
       "37. \"corn\"\n",
       "38. \"vinegar\"\n",
       "39. \"lime\"\n",
       "40. \"soy\"\n",
       "41. \"all-purpos\"\n",
       "42. \"cumin\"\n",
       "43. \"broth\"\n",
       "44. \"bell\"\n",
       "45. \"wine\"\n",
       "46. \"parsley\"\n",
       "47. \"seed\"\n",
       "48. \"bean\"\n",
       "49. \"cook\"\n",
       "50. \"sesam\"\n",
       "51. \"grate\"\n",
       "52. \"breast\"\n",
       "53. \"carrot\"\n",
       "54. \"kosher\"\n",
       "55. \"basil\"\n",
       "56. \"beef\"\n",
       "57. \"bake\"\n",
       "58. \"brown\"\n",
       "59. \"chile\"\n",
       "60. \"past\"\n",
       "61. \"unsalt\"\n",
       "62. \"potato\"\n",
       "63. \"parmesan\"\n",
       "64. \"oregano\"\n",
       "65. \"extra-virgin\"\n",
       "66. \"boneless\"\n",
       "67. \"shred\"\n",
       "68. \"tortilla\"\n",
       "69. \"cinnamon\"\n",
       "70. \"season\"\n",
       "71. \"thyme\"\n",
       "72. \"pork\"\n",
       "73. \"mushroom\"\n",
       "74. \"shrimp\"\n",
       "75. \"dice\"\n",
       "76. \"yellow\"\n",
       "77. \"bread\"\n",
       "78. \"skinless\"\n",
       "79. \"vanilla\"\n",
       "80. \"coconut\"\n",
       "81. \"sodium\"\n",
       "82. \"coriand\"\n",
       "83. \"celeri\"\n",
       "84. \"bay\"\n",
       "85. \"cayenn\"\n",
       "86. \"minc\"\n",
       "87. \"leaf\"\n",
       "88. \"crush\"\n",
       "89. \"whole\"\n",
       "90. \"spray\"\n",
       "91. \"flake\"\n",
       "92. \"sour\"\n",
       "93. \"scallion\"\n",
       "94. \"slice\"\n",
       "95. \"starch\"\n",
       "96. \"paprika\"\n",
       "97. \"stock\"\n",
       "98. \"hot\"\n",
       "99. \"purpl\"\n",
       "100. \"cheddar\"\n",
       "101. \"fish\"\n",
       "102. \"orang\"\n",
       "103. \"mustard\"\n",
       "104. \"jalapeno\"\n",
       "105. \"extract\"\n",
       "106. \"peanut\"\n",
       "107. \"curri\"\n",
       "108. \"sausag\"\n",
       "109. \"frozen\"\n",
       "110. \"sweet\"\n",
       "111. \"low\"\n",
       "112. \"shallot\"\n",
       "113. \"sea\"\n",
       "114. \"pea\"\n",
       "115. \"fat\"\n",
       "116. \"light\"\n",
       "117. \"mozzarella\"\n",
       "118. \"honey\"\n",
       "119. \"heavi\"\n",
       "120. \"noodl\"\n",
       "121. \"italian\"\n",
       "122. \"mint\"\n",
       "123. \"spinach\"\n",
       "124. \"salsa\"\n",
       "125. \"roast\"\n",
       "126. \"canola\"\n",
       "127. \"avocado\"\n",
       "128. \"peel\"\n",
       "129. \"cabbag\"\n",
       "130. \"pasta\"\n",
       "131. \"bacon\"\n",
       "132. \"lettuc\"\n",
       "133. \"yogurt\"\n",
       "134. \"cucumb\"\n",
       "135. \"almond\"\n",
       "136. \"yolk\"\n",
       "137. \"fillet\"\n",
       "138. \"flat\"\n",
       "139. \"whip\"\n",
       "140. \"masala\"\n",
       "141. \"nutmeg\"\n",
       "142. \"dark\"\n",
       "143. \"soda\"\n",
       "144. \"granul\"\n",
       "145. \"buttermilk\"\n",
       "146. \"crumb\"\n",
       "147. \"halv\"\n",
       "148. \"turmer\"\n",
       "149. \"plum\"\n",
       "150. \"rib\"\n",
       "151. \"jack\"\n",
       "152. \"garam\"\n",
       "153. \"steak\"\n",
       "154. \"zucchini\"\n",
       "155. \"fine\"\n",
       "156. \"zest\"\n",
       "157. \"plain\"\n",
       "158. \"toast\"\n",
       "159. \"mix\"\n",
       "160. \"chocol\"\n",
       "161. \"free\"\n",
       "162. \"smoke\"\n",
       "163. \"thigh\"\n",
       "164. \"peppercorn\"\n",
       "165. \"appl\"\n",
       "166. \"rosemari\"\n",
       "167. \"sprig\"\n",
       "168. \"mayonais\"\n",
       "169. \"babi\"\n",
       "170. \"tumer\"\n",
       "171. \"yeast\"\n",
       "172. \"stick\"\n",
       "173. \"reduc\"\n",
       "174. \"cardamom\"\n",
       "175. \"thai\"\n",
       "176. \"ricotta\"\n",
       "177. \"chines\"\n",
       "178. \"coars\"\n",
       "179. \"wedg\"\n",
       "180. \"raisin\"\n",
       "181. \"low-fat\"\n",
       "182. \"worcestershir\"\n",
       "183. \"ham\"\n",
       "184. \"cider\"\n",
       "185. \"feta\"\n",
       "186. \"fennel\"\n",
       "187. \"cherri\"\n",
       "188. \"kernel\"\n",
       "189. \"meat\"\n",
       "190. \"taco\"\n",
       "191. \"tofu\"\n",
       "192. \"sherri\"\n",
       "193. \"turkey\"\n",
       "194. \"chive\"\n",
       "195. \"wheat\"\n",
       "196. \"ice\"\n",
       "197. \"syrup\"\n",
       "198. \"eggplant\"\n",
       "199. \"pecan\"\n",
       "200. \"warm\"\n",
       "201. \"medium\"\n",
       "202. \"shiitak\"\n",
       "203. \"balsam\"\n",
       "204. \"monterey\"\n",
       "205. \"lamb\"\n",
       "206. \"oyster\"\n",
       "207. \"chipotl\"\n",
       "208. \"dijon\"\n",
       "209. \"root\"\n",
       "210. \"chip\"\n",
       "211. \"serrano\"\n",
       "212. \"lean\"\n",
       "213. \"less\"\n",
       "214. \"unsweeten\"\n",
       "215. \"allspic\"\n",
       "216. \"condens\"\n",
       "217. \"caper\"\n",
       "218. \"cold\"\n",
       "219. \"firm\"\n",
       "220. \"broccoli\"\n",
       "221. \"mexican\"\n",
       "222. \"ketchup\"\n",
       "223. \"boil\"\n",
       "224. \"cornmeal\"\n",
       "225. \"crumbl\"\n",
       "226. \"mirin\"\n",
       "227. \"and\"\n",
       "228. \"greek\"\n",
       "229. \"saffron\"\n",
       "230. \"spring\"\n",
       "231. \"soup\"\n",
       "232. \"sharp\"\n",
       "233. \"chickpea\"\n",
       "234. \"beansprout\"\n",
       "235. \"dough\"\n",
       "236. \"leek\"\n",
       "237. \"sage\"\n",
       "238. \"squash\"\n",
       "239. \"dill\"\n",
       "240. \"sweeten\"\n",
       "241. \"spaghetti\"\n",
       "242. \"dress\"\n",
       "243. \"shoulder\"\n",
       "244. \"golden\"\n",
       "245. \"hoisin\"\n",
       "246. \"enchilada\"\n",
       "247. \"kalamata\"\n",
       "248. \"crack\"\n",
       "249. \"shell\"\n",
       "250. \"confection\"\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "  [1] \"pepper\"        \"salt\"          \"oil\"           \"onion\"        \n",
       "  [5] \"garlic\"        \"fresh\"         \"ground\"        \"sauc\"         \n",
       "  [9] \"sugar\"         \"oliv\"          \"chees\"         \"chicken\"      \n",
       " [13] \"tomato\"        \"black\"         \"water\"         \"red\"          \n",
       " [17] \"green\"         \"egg\"           \"flour\"         \"powder\"       \n",
       " [21] \"butter\"        \"dri\"           \"chop\"          \"clove\"        \n",
       " [25] \"white\"         \"juic\"          \"chili\"         \"cream\"        \n",
       " [29] \"rice\"          \"cilantro\"      \"veget\"         \"milk\"         \n",
       " [33] \"lemon\"         \"leav\"          \"larg\"          \"ginger\"       \n",
       " [37] \"corn\"          \"vinegar\"       \"lime\"          \"soy\"          \n",
       " [41] \"all-purpos\"    \"cumin\"         \"broth\"         \"bell\"         \n",
       " [45] \"wine\"          \"parsley\"       \"seed\"          \"bean\"         \n",
       " [49] \"cook\"          \"sesam\"         \"grate\"         \"breast\"       \n",
       " [53] \"carrot\"        \"kosher\"        \"basil\"         \"beef\"         \n",
       " [57] \"bake\"          \"brown\"         \"chile\"         \"past\"         \n",
       " [61] \"unsalt\"        \"potato\"        \"parmesan\"      \"oregano\"      \n",
       " [65] \"extra-virgin\"  \"boneless\"      \"shred\"         \"tortilla\"     \n",
       " [69] \"cinnamon\"      \"season\"        \"thyme\"         \"pork\"         \n",
       " [73] \"mushroom\"      \"shrimp\"        \"dice\"          \"yellow\"       \n",
       " [77] \"bread\"         \"skinless\"      \"vanilla\"       \"coconut\"      \n",
       " [81] \"sodium\"        \"coriand\"       \"celeri\"        \"bay\"          \n",
       " [85] \"cayenn\"        \"minc\"          \"leaf\"          \"crush\"        \n",
       " [89] \"whole\"         \"spray\"         \"flake\"         \"sour\"         \n",
       " [93] \"scallion\"      \"slice\"         \"starch\"        \"paprika\"      \n",
       " [97] \"stock\"         \"hot\"           \"purpl\"         \"cheddar\"      \n",
       "[101] \"fish\"          \"orang\"         \"mustard\"       \"jalapeno\"     \n",
       "[105] \"extract\"       \"peanut\"        \"curri\"         \"sausag\"       \n",
       "[109] \"frozen\"        \"sweet\"         \"low\"           \"shallot\"      \n",
       "[113] \"sea\"           \"pea\"           \"fat\"           \"light\"        \n",
       "[117] \"mozzarella\"    \"honey\"         \"heavi\"         \"noodl\"        \n",
       "[121] \"italian\"       \"mint\"          \"spinach\"       \"salsa\"        \n",
       "[125] \"roast\"         \"canola\"        \"avocado\"       \"peel\"         \n",
       "[129] \"cabbag\"        \"pasta\"         \"bacon\"         \"lettuc\"       \n",
       "[133] \"yogurt\"        \"cucumb\"        \"almond\"        \"yolk\"         \n",
       "[137] \"fillet\"        \"flat\"          \"whip\"          \"masala\"       \n",
       "[141] \"nutmeg\"        \"dark\"          \"soda\"          \"granul\"       \n",
       "[145] \"buttermilk\"    \"crumb\"         \"halv\"          \"turmer\"       \n",
       "[149] \"plum\"          \"rib\"           \"jack\"          \"garam\"        \n",
       "[153] \"steak\"         \"zucchini\"      \"fine\"          \"zest\"         \n",
       "[157] \"plain\"         \"toast\"         \"mix\"           \"chocol\"       \n",
       "[161] \"free\"          \"smoke\"         \"thigh\"         \"peppercorn\"   \n",
       "[165] \"appl\"          \"rosemari\"      \"sprig\"         \"mayonais\"     \n",
       "[169] \"babi\"          \"tumer\"         \"yeast\"         \"stick\"        \n",
       "[173] \"reduc\"         \"cardamom\"      \"thai\"          \"ricotta\"      \n",
       "[177] \"chines\"        \"coars\"         \"wedg\"          \"raisin\"       \n",
       "[181] \"low-fat\"       \"worcestershir\" \"ham\"           \"cider\"        \n",
       "[185] \"feta\"          \"fennel\"        \"cherri\"        \"kernel\"       \n",
       "[189] \"meat\"          \"taco\"          \"tofu\"          \"sherri\"       \n",
       "[193] \"turkey\"        \"chive\"         \"wheat\"         \"ice\"          \n",
       "[197] \"syrup\"         \"eggplant\"      \"pecan\"         \"warm\"         \n",
       "[201] \"medium\"        \"shiitak\"       \"balsam\"        \"monterey\"     \n",
       "[205] \"lamb\"          \"oyster\"        \"chipotl\"       \"dijon\"        \n",
       "[209] \"root\"          \"chip\"          \"serrano\"       \"lean\"         \n",
       "[213] \"less\"          \"unsweeten\"     \"allspic\"       \"condens\"      \n",
       "[217] \"caper\"         \"cold\"          \"firm\"          \"broccoli\"     \n",
       "[221] \"mexican\"       \"ketchup\"       \"boil\"          \"cornmeal\"     \n",
       "[225] \"crumbl\"        \"mirin\"         \"and\"           \"greek\"        \n",
       "[229] \"saffron\"       \"spring\"        \"soup\"          \"sharp\"        \n",
       "[233] \"chickpea\"      \"beansprout\"    \"dough\"         \"leek\"         \n",
       "[237] \"sage\"          \"squash\"        \"dill\"          \"sweeten\"      \n",
       "[241] \"spaghetti\"     \"dress\"         \"shoulder\"      \"golden\"       \n",
       "[245] \"hoisin\"        \"enchilada\"     \"kalamata\"      \"crack\"        \n",
       "[249] \"shell\"         \"confection\"   "
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "names(ingredients_sum)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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      "image/png": 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",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/svg+xml": {
       "isolated": true
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot(ingredients_sum[1:15], xaxt='n')\n",
    "axis(side=1, at=1:15, labels=names(ingredients_sum[1:15]), col.axis=\"blue\", cex.axis=0.5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/pdf": 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",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/svg+xml": {
       "isolated": true
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "barplot(ingredients_sum[1:15], las=2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 상위 15개 재료 \n",
    "- pepper, salt, oil, onion, garlic, fresh, ground, sauc, sugar, oliv, chees, chicken, tomato, black, water)\n",
    "- 후추, 소금, 기름, 양파, 마늘... "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/pdf": 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",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/svg+xml": {
       "isolated": true
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "barplot(ingredients_sum[30:50], las=2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th></th><th scope=col>Group.1</th><th scope=col>all-purpos</th><th scope=col>allspic</th><th scope=col>almond</th><th scope=col>and</th><th scope=col>appl</th><th scope=col>avocado</th><th scope=col>babi</th><th scope=col>bacon</th><th scope=col>bake</th><th scope=col>balsam</th><th scope=col>basil</th><th scope=col>bay</th><th scope=col>bean</th><th scope=col>beansprout</th><th scope=col>beef</th><th scope=col>bell</th><th scope=col>black</th><th scope=col>boil</th><th scope=col>boneless</th><th scope=col>bread</th><th scope=col>breast</th><th scope=col>broccoli</th><th scope=col>broth</th><th scope=col>brown</th><th scope=col>butter</th><th scope=col>buttermilk</th><th scope=col>cabbag</th><th scope=col>canola</th><th scope=col>caper</th><th scope=col>cardamom</th><th scope=col>carrot</th><th scope=col>cayenn</th><th scope=col>celeri</th><th scope=col>cheddar</th><th scope=col>chees</th><th scope=col>cherri</th><th scope=col>chicken</th><th scope=col>chickpea</th><th scope=col>chile</th><th scope=col>chili</th><th scope=col>chines</th><th scope=col>chip</th><th scope=col>chipotl</th><th scope=col>chive</th><th scope=col>chocol</th><th scope=col>chop</th><th scope=col>cider</th><th scope=col>cilantro</th><th scope=col>cinnamon</th><th scope=col>clove</th><th scope=col>coars</th><th scope=col>coconut</th><th scope=col>cold</th><th scope=col>condens</th><th scope=col>confection</th><th scope=col>cook</th><th scope=col>coriand</th><th scope=col>corn</th><th scope=col>cornmeal</th><th scope=col>crack</th><th scope=col>cream</th><th scope=col>crumb</th><th scope=col>crumbl</th><th scope=col>crush</th><th scope=col>cucumb</th><th scope=col>cumin</th><th scope=col>curri</th><th scope=col>dark</th><th scope=col>dice</th><th scope=col>dijon</th><th scope=col>dill</th><th scope=col>dough</th><th scope=col>dress</th><th scope=col>dri</th><th scope=col>egg</th><th scope=col>eggplant</th><th scope=col>enchilada</th><th scope=col>extra-virgin</th><th scope=col>extract</th><th scope=col>fat</th><th scope=col>fennel</th><th scope=col>feta</th><th scope=col>fillet</th><th scope=col>fine</th><th scope=col>firm</th><th scope=col>fish</th><th scope=col>flake</th><th scope=col>flat</th><th scope=col>flour</th><th scope=col>free</th><th scope=col>fresh</th><th scope=col>frozen</th><th scope=col>garam</th><th scope=col>garlic</th><th scope=col>ginger</th><th scope=col>golden</th><th scope=col>granul</th><th scope=col>grate</th><th scope=col>greek</th><th scope=col>green</th><th scope=col>ground</th><th scope=col>halv</th><th scope=col>ham</th><th scope=col>heavi</th><th scope=col>hoisin</th><th scope=col>honey</th><th scope=col>hot</th><th scope=col>ice</th><th scope=col>italian</th><th scope=col>jack</th><th scope=col>jalapeno</th><th scope=col>juic</th><th scope=col>kalamata</th><th scope=col>kernel</th><th scope=col>ketchup</th><th scope=col>kosher</th><th scope=col>lamb</th><th scope=col>larg</th><th scope=col>leaf</th><th scope=col>lean</th><th scope=col>leav</th><th scope=col>leek</th><th scope=col>lemon</th><th scope=col>less</th><th scope=col>lettuc</th><th scope=col>light</th><th scope=col>lime</th><th scope=col>low</th><th scope=col>low-fat</th><th scope=col>masala</th><th scope=col>mayonais</th><th scope=col>meat</th><th scope=col>medium</th><th scope=col>mexican</th><th scope=col>milk</th><th scope=col>minc</th><th scope=col>mint</th><th scope=col>mirin</th><th scope=col>mix</th><th scope=col>monterey</th><th scope=col>mozzarella</th><th scope=col>mushroom</th><th scope=col>mustard</th><th scope=col>noodl</th><th scope=col>nutmeg</th><th scope=col>oil</th><th scope=col>oliv</th><th scope=col>onion</th><th scope=col>orang</th><th scope=col>oregano</th><th scope=col>oyster</th><th scope=col>paprika</th><th scope=col>parmesan</th><th scope=col>parsley</th><th scope=col>past</th><th scope=col>pasta</th><th scope=col>pea</th><th scope=col>peanut</th><th scope=col>pecan</th><th scope=col>peel</th><th scope=col>pepper</th><th scope=col>peppercorn</th><th scope=col>plain</th><th scope=col>plum</th><th scope=col>pork</th><th scope=col>potato</th><th scope=col>powder</th><th scope=col>purpl</th><th scope=col>raisin</th><th scope=col>red</th><th scope=col>reduc</th><th scope=col>rib</th><th scope=col>rice</th><th scope=col>ricotta</th><th scope=col>roast</th><th scope=col>root</th><th scope=col>rosemari</th><th scope=col>saffron</th><th scope=col>sage</th><th scope=col>salsa</th><th scope=col>salt</th><th scope=col>sauc</th><th scope=col>sausag</th><th scope=col>scallion</th><th scope=col>sea</th><th scope=col>season</th><th scope=col>seed</th><th scope=col>serrano</th><th scope=col>sesam</th><th scope=col>shallot</th><th scope=col>sharp</th><th scope=col>shell</th><th scope=col>sherri</th><th scope=col>shiitak</th><th scope=col>shoulder</th><th scope=col>shred</th><th scope=col>shrimp</th><th scope=col>skinless</th><th scope=col>slice</th><th scope=col>smoke</th><th scope=col>soda</th><th scope=col>sodium</th><th scope=col>soup</th><th scope=col>sour</th><th scope=col>soy</th><th scope=col>spaghetti</th><th scope=col>spinach</th><th scope=col>spray</th><th scope=col>sprig</th><th scope=col>spring</th><th scope=col>squash</th><th scope=col>starch</th><th scope=col>steak</th><th scope=col>stick</th><th scope=col>stock</th><th scope=col>sugar</th><th scope=col>sweet</th><th scope=col>sweeten</th><th scope=col>syrup</th><th scope=col>taco</th><th scope=col>thai</th><th scope=col>thigh</th><th scope=col>thyme</th><th scope=col>toast</th><th scope=col>tofu</th><th scope=col>tomato</th><th scope=col>tortilla</th><th scope=col>tumer</th><th scope=col>turkey</th><th scope=col>turmer</th><th scope=col>unsalt</th><th scope=col>unsweeten</th><th scope=col>vanilla</th><th scope=col>veget</th><th scope=col>vinegar</th><th scope=col>warm</th><th scope=col>water</th><th scope=col>wedg</th><th scope=col>wheat</th><th scope=col>whip</th><th scope=col>white</th><th scope=col>whole</th><th scope=col>wine</th><th scope=col>worcestershir</th><th scope=col>yeast</th><th scope=col>yellow</th><th scope=col>yogurt</th><th scope=col>yolk</th><th scope=col>zest</th><th scope=col>zucchini</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>1</th><td>brazilian</td><td>18</td><td>1</td><td>24</td><td>2</td><td>10</td><td>10</td><td>3</td><td>30</td><td>19</td><td>0</td><td>2</td><td>54</td><td>71</td><td>0</td><td>31</td><td>80</td><td>133</td><td>4</td><td>16</td><td>13</td><td>17</td><td>0</td><td>33</td><td>21</td><td>83</td><td>2</td><td>0</td><td>13</td><td>1</td><td>0</td><td>26</td><td>23</td><td>7</td><td>5</td><td>56</td><td>5</td><td>76</td><td>0</td><td>23</td><td>41</td><td>0</td><td>4</td><td>5</td><td>2</td><td>35</td><td>76</td><td>2</td><td>88</td><td>14</td><td>92</td><td>7</td><td>142</td><td>12</td><td>68</td><td>1</td><td>28</td><td>22</td><td>34</td><td>4</td><td>3</td><td>35</td><td>9</td><td>0</td><td>32</td><td>2</td><td>29</td><td>2</td><td>5</td><td>21</td><td>4</td><td>0</td><td>1</td><td>0</td><td>62</td><td>105</td><td>0</td><td>0</td><td>13</td><td>18</td><td>5</td><td>3</td><td>0</td><td>25</td><td>8</td><td>0</td><td>27</td><td>33</td><td>10</td><td>73</td><td>5</td><td>133</td><td>32</td><td>1</td><td>194</td><td>31</td><td>1</td><td>21</td><td>21</td><td>0</td><td>85</td><td>126</td><td>3</td><td>17</td><td>7</td><td>0</td><td>12</td><td>22</td><td>57</td><td>5</td><td>3</td><td>19</td><td>104</td><td>0</td><td>4</td><td>1</td><td>22</td><td>2</td><td>33</td><td>33</td><td>1</td><td>63</td><td>2</td><td>37</td><td>3</td><td>1</td><td>16</td><td>164</td><td>10</td><td>5</td><td>1</td><td>10</td><td>3</td><td>10</td><td>0</td><td>229</td><td>15</td><td>7</td><td>0</td><td>6</td><td>2</td><td>5</td><td>2</td><td>5</td><td>0</td><td>5</td><td>247</td><td>145</td><td>226</td><td>50</td><td>14</td><td>1</td><td>19</td><td>24</td><td>55</td><td>21</td><td>1</td><td>16</td><td>10</td><td>3</td><td>6</td><td>310</td><td>1</td><td>3</td><td>9</td><td>35</td><td>26</td><td>63</td><td>8</td><td>6</td><td>86</td><td>2</td><td>18</td><td>63</td><td>0</td><td>11</td><td>4</td><td>2</td><td>3</td><td>1</td><td>7</td><td>246</td><td>35</td><td>30</td><td>8</td><td>19</td><td>7</td><td>26</td><td>7</td><td>2</td><td>5</td><td>1</td><td>2</td><td>3</td><td>0</td><td>9</td><td>15</td><td>58</td><td>10</td><td>22</td><td>16</td><td>8</td><td>16</td><td>2</td><td>6</td><td>3</td><td>0</td><td>6</td><td>3</td><td>1</td><td>4</td><td>2</td><td>22</td><td>12</td><td>4</td><td>29</td><td>150</td><td>18</td><td>61</td><td>16</td><td>0</td><td>1</td><td>6</td><td>13</td><td>5</td><td>1</td><td>133</td><td>1</td><td>3</td><td>5</td><td>4</td><td>26</td><td>29</td><td>28</td><td>46</td><td>26</td><td>2</td><td>112</td><td>15</td><td>3</td><td>4</td><td>91</td><td>15</td><td>30</td><td>2</td><td>6</td><td>34</td><td>3</td><td>22</td><td>8</td><td>3</td></tr>\n",
       "\t<tr><th scope=row>2</th><td>british</td><td>238</td><td>27</td><td>44</td><td>3</td><td>30</td><td>0</td><td>2</td><td>25</td><td>217</td><td>17</td><td>5</td><td>42</td><td>15</td><td>0</td><td>158</td><td>4</td><td>134</td><td>18</td><td>3</td><td>81</td><td>4</td><td>1</td><td>36</td><td>109</td><td>436</td><td>26</td><td>10</td><td>18</td><td>4</td><td>2</td><td>61</td><td>32</td><td>26</td><td>60</td><td>108</td><td>16</td><td>30</td><td>0</td><td>1</td><td>8</td><td>0</td><td>4</td><td>0</td><td>18</td><td>32</td><td>66</td><td>9</td><td>5</td><td>68</td><td>57</td><td>17</td><td>6</td><td>22</td><td>11</td><td>22</td><td>23</td><td>7</td><td>57</td><td>11</td><td>13</td><td>268</td><td>37</td><td>1</td><td>7</td><td>4</td><td>8</td><td>19</td><td>44</td><td>3</td><td>22</td><td>5</td><td>12</td><td>0</td><td>157</td><td>436</td><td>0</td><td>0</td><td>19</td><td>85</td><td>10</td><td>3</td><td>0</td><td>35</td><td>12</td><td>2</td><td>14</td><td>14</td><td>6</td><td>467</td><td>12</td><td>180</td><td>57</td><td>2</td><td>94</td><td>54</td><td>53</td><td>37</td><td>54</td><td>4</td><td>26</td><td>312</td><td>4</td><td>7</td><td>104</td><td>0</td><td>16</td><td>16</td><td>15</td><td>2</td><td>0</td><td>1</td><td>65</td><td>0</td><td>1</td><td>7</td><td>61</td><td>14</td><td>164</td><td>26</td><td>20</td><td>48</td><td>18</td><td>125</td><td>0</td><td>3</td><td>40</td><td>5</td><td>8</td><td>8</td><td>2</td><td>7</td><td>8</td><td>14</td><td>0</td><td>287</td><td>16</td><td>14</td><td>0</td><td>32</td><td>0</td><td>0</td><td>58</td><td>76</td><td>0</td><td>70</td><td>201</td><td>77</td><td>215</td><td>55</td><td>8</td><td>0</td><td>22</td><td>11</td><td>52</td><td>29</td><td>0</td><td>30</td><td>2</td><td>12</td><td>35</td><td>276</td><td>10</td><td>39</td><td>4</td><td>46</td><td>144</td><td>213</td><td>11</td><td>62</td><td>50</td><td>2</td><td>16</td><td>23</td><td>0</td><td>18</td><td>2</td><td>23</td><td>2</td><td>21</td><td>0</td><td>516</td><td>83</td><td>42</td><td>4</td><td>26</td><td>11</td><td>23</td><td>1</td><td>1</td><td>19</td><td>20</td><td>6</td><td>23</td><td>1</td><td>6</td><td>12</td><td>3</td><td>4</td><td>23</td><td>17</td><td>85</td><td>9</td><td>3</td><td>23</td><td>5</td><td>0</td><td>5</td><td>12</td><td>10</td><td>4</td><td>2</td><td>32</td><td>26</td><td>9</td><td>49</td><td>454</td><td>21</td><td>11</td><td>41</td><td>0</td><td>1</td><td>0</td><td>62</td><td>7</td><td>0</td><td>53</td><td>0</td><td>9</td><td>2</td><td>3</td><td>193</td><td>2</td><td>119</td><td>82</td><td>71</td><td>15</td><td>178</td><td>8</td><td>15</td><td>82</td><td>168</td><td>77</td><td>66</td><td>53</td><td>41</td><td>26</td><td>8</td><td>67</td><td>21</td><td>3</td></tr>\n",
       "\t<tr><th scope=row>3</th><td>cajun_creole</td><td>291</td><td>18</td><td>12</td><td>39</td><td>14</td><td>4</td><td>17</td><td>62</td><td>64</td><td>8</td><td>94</td><td>360</td><td>164</td><td>0</td><td>79</td><td>696</td><td>496</td><td>23</td><td>152</td><td>133</td><td>176</td><td>3</td><td>348</td><td>111</td><td>498</td><td>33</td><td>15</td><td>84</td><td>30</td><td>1</td><td>53</td><td>399</td><td>619</td><td>20</td><td>174</td><td>9</td><td>741</td><td>3</td><td>28</td><td>142</td><td>0</td><td>5</td><td>3</td><td>22</td><td>11</td><td>544</td><td>19</td><td>26</td><td>46</td><td>329</td><td>29</td><td>9</td><td>10</td><td>17</td><td>26</td><td>299</td><td>10</td><td>145</td><td>23</td><td>24</td><td>206</td><td>49</td><td>5</td><td>89</td><td>0</td><td>57</td><td>1</td><td>14</td><td>277</td><td>33</td><td>13</td><td>5</td><td>18</td><td>646</td><td>237</td><td>4</td><td>0</td><td>47</td><td>54</td><td>51</td><td>9</td><td>1</td><td>75</td><td>41</td><td>4</td><td>12</td><td>69</td><td>50</td><td>450</td><td>31</td><td>546</td><td>52</td><td>0</td><td>1003</td><td>6</td><td>6</td><td>51</td><td>58</td><td>0</td><td>913</td><td>679</td><td>61</td><td>94</td><td>74</td><td>0</td><td>14</td><td>286</td><td>15</td><td>45</td><td>16</td><td>50</td><td>196</td><td>3</td><td>27</td><td>23</td><td>108</td><td>0</td><td>223</td><td>158</td><td>13</td><td>297</td><td>7</td><td>253</td><td>24</td><td>40</td><td>42</td><td>23</td><td>76</td><td>17</td><td>0</td><td>80</td><td>73</td><td>109</td><td>2</td><td>165</td><td>121</td><td>3</td><td>0</td><td>46</td><td>8</td><td>11</td><td>83</td><td>133</td><td>6</td><td>26</td><td>821</td><td>402</td><td>1314</td><td>36</td><td>225</td><td>30</td><td>262</td><td>58</td><td>369</td><td>99</td><td>27</td><td>32</td><td>31</td><td>40</td><td>39</td><td>2326</td><td>17</td><td>6</td><td>26</td><td>61</td><td>58</td><td>450</td><td>38</td><td>9</td><td>555</td><td>36</td><td>183</td><td>537</td><td>1</td><td>33</td><td>0</td><td>27</td><td>2</td><td>16</td><td>2</td><td>993</td><td>665</td><td>463</td><td>97</td><td>36</td><td>631</td><td>34</td><td>4</td><td>1</td><td>23</td><td>7</td><td>15</td><td>8</td><td>1</td><td>6</td><td>25</td><td>473</td><td>125</td><td>100</td><td>198</td><td>26</td><td>107</td><td>35</td><td>25</td><td>14</td><td>5</td><td>18</td><td>75</td><td>26</td><td>2</td><td>8</td><td>28</td><td>16</td><td>6</td><td>148</td><td>310</td><td>76</td><td>7</td><td>18</td><td>1</td><td>0</td><td>55</td><td>428</td><td>8</td><td>1</td><td>673</td><td>6</td><td>1</td><td>62</td><td>1</td><td>119</td><td>3</td><td>74</td><td>313</td><td>72</td><td>24</td><td>340</td><td>16</td><td>5</td><td>41</td><td>371</td><td>77</td><td>105</td><td>195</td><td>56</td><td>146</td><td>3</td><td>34</td><td>13</td><td>13</td></tr>\n",
       "\t<tr><th scope=row>4</th><td>chinese</td><td>129</td><td>0</td><td>46</td><td>36</td><td>26</td><td>9</td><td>92</td><td>26</td><td>100</td><td>32</td><td>34</td><td>14</td><td>330</td><td>109</td><td>167</td><td>261</td><td>529</td><td>56</td><td>391</td><td>15</td><td>460</td><td>171</td><td>368</td><td>363</td><td>112</td><td>2</td><td>251</td><td>187</td><td>0</td><td>5</td><td>379</td><td>36</td><td>113</td><td>2</td><td>33</td><td>12</td><td>1330</td><td>1</td><td>147</td><td>588</td><td>604</td><td>0</td><td>1</td><td>63</td><td>4</td><td>217</td><td>47</td><td>245</td><td>65</td><td>497</td><td>44</td><td>44</td><td>91</td><td>9</td><td>9</td><td>355</td><td>50</td><td>1005</td><td>2</td><td>12</td><td>54</td><td>6</td><td>2</td><td>157</td><td>61</td><td>16</td><td>23</td><td>364</td><td>21</td><td>8</td><td>1</td><td>8</td><td>9</td><td>395</td><td>697</td><td>37</td><td>0</td><td>12</td><td>25</td><td>56</td><td>16</td><td>1</td><td>45</td><td>22</td><td>112</td><td>89</td><td>237</td><td>2</td><td>375</td><td>54</td><td>1048</td><td>95</td><td>1</td><td>1687</td><td>1483</td><td>7</td><td>52</td><td>29</td><td>1</td><td>987</td><td>788</td><td>73</td><td>30</td><td>6</td><td>326</td><td>257</td><td>109</td><td>11</td><td>3</td><td>0</td><td>20</td><td>222</td><td>0</td><td>9</td><td>131</td><td>187</td><td>11</td><td>256</td><td>16</td><td>42</td><td>155</td><td>29</td><td>106</td><td>43</td><td>91</td><td>298</td><td>79</td><td>304</td><td>1</td><td>1</td><td>12</td><td>47</td><td>62</td><td>1</td><td>74</td><td>325</td><td>14</td><td>27</td><td>33</td><td>0</td><td>1</td><td>357</td><td>39</td><td>320</td><td>10</td><td>3005</td><td>151</td><td>1300</td><td>192</td><td>2</td><td>352</td><td>14</td><td>4</td><td>17</td><td>227</td><td>7</td><td>246</td><td>473</td><td>0</td><td>202</td><td>1733</td><td>177</td><td>16</td><td>35</td><td>557</td><td>43</td><td>464</td><td>33</td><td>5</td><td>758</td><td>106</td><td>66</td><td>1249</td><td>1</td><td>131</td><td>141</td><td>1</td><td>0</td><td>3</td><td>1</td><td>1237</td><td>3450</td><td>30</td><td>608</td><td>69</td><td>38</td><td>325</td><td>15</td><td>1488</td><td>73</td><td>1</td><td>7</td><td>197</td><td>204</td><td>30</td><td>73</td><td>251</td><td>329</td><td>137</td><td>5</td><td>53</td><td>457</td><td>14</td><td>16</td><td>2244</td><td>24</td><td>36</td><td>52</td><td>15</td><td>171</td><td>6</td><td>952</td><td>131</td><td>50</td><td>229</td><td>1419</td><td>84</td><td>9</td><td>25</td><td>1</td><td>39</td><td>87</td><td>10</td><td>249</td><td>177</td><td>111</td><td>12</td><td>0</td><td>23</td><td>6</td><td>48</td><td>8</td><td>22</td><td>724</td><td>870</td><td>34</td><td>1129</td><td>10</td><td>24</td><td>6</td><td>867</td><td>28</td><td>693</td><td>39</td><td>33</td><td>83</td><td>2</td><td>21</td><td>33</td><td>32</td></tr>\n",
       "\t<tr><th scope=row>5</th><td>filipino</td><td>33</td><td>1</td><td>2</td><td>17</td><td>24</td><td>3</td><td>5</td><td>4</td><td>30</td><td>3</td><td>2</td><td>122</td><td>70</td><td>10</td><td>97</td><td>70</td><td>208</td><td>6</td><td>37</td><td>21</td><td>40</td><td>9</td><td>64</td><td>90</td><td>88</td><td>0</td><td>67</td><td>27</td><td>0</td><td>1</td><td>134</td><td>8</td><td>36</td><td>15</td><td>35</td><td>2</td><td>247</td><td>1</td><td>36</td><td>63</td><td>18</td><td>0</td><td>3</td><td>2</td><td>4</td><td>35</td><td>25</td><td>18</td><td>8</td><td>94</td><td>5</td><td>149</td><td>5</td><td>42</td><td>4</td><td>122</td><td>5</td><td>80</td><td>0</td><td>1</td><td>57</td><td>13</td><td>0</td><td>21</td><td>5</td><td>8</td><td>5</td><td>12</td><td>7</td><td>1</td><td>0</td><td>1</td><td>1</td><td>37</td><td>181</td><td>27</td><td>0</td><td>5</td><td>30</td><td>3</td><td>1</td><td>0</td><td>14</td><td>7</td><td>6</td><td>108</td><td>24</td><td>2</td><td>99</td><td>2</td><td>77</td><td>22</td><td>0</td><td>504</td><td>110</td><td>3</td><td>25</td><td>14</td><td>0</td><td>169</td><td>269</td><td>6</td><td>7</td><td>4</td><td>10</td><td>13</td><td>20</td><td>14</td><td>2</td><td>0</td><td>12</td><td>58</td><td>0</td><td>4</td><td>24</td><td>21</td><td>2</td><td>29</td><td>28</td><td>5</td><td>140</td><td>3</td><td>61</td><td>1</td><td>4</td><td>12</td><td>28</td><td>18</td><td>0</td><td>0</td><td>12</td><td>23</td><td>6</td><td>0</td><td>191</td><td>44</td><td>1</td><td>0</td><td>1</td><td>0</td><td>1</td><td>21</td><td>6</td><td>48</td><td>1</td><td>476</td><td>57</td><td>466</td><td>10</td><td>5</td><td>33</td><td>11</td><td>2</td><td>11</td><td>30</td><td>6</td><td>32</td><td>18</td><td>0</td><td>6</td><td>511</td><td>90</td><td>3</td><td>4</td><td>212</td><td>65</td><td>90</td><td>13</td><td>26</td><td>72</td><td>1</td><td>15</td><td>128</td><td>0</td><td>3</td><td>11</td><td>0</td><td>3</td><td>0</td><td>1</td><td>483</td><td>511</td><td>14</td><td>18</td><td>15</td><td>15</td><td>17</td><td>1</td><td>30</td><td>20</td><td>1</td><td>2</td><td>4</td><td>10</td><td>19</td><td>19</td><td>74</td><td>24</td><td>12</td><td>5</td><td>4</td><td>21</td><td>2</td><td>4</td><td>290</td><td>3</td><td>27</td><td>4</td><td>0</td><td>32</td><td>6</td><td>57</td><td>9</td><td>7</td><td>31</td><td>319</td><td>41</td><td>28</td><td>3</td><td>1</td><td>29</td><td>31</td><td>6</td><td>1</td><td>13</td><td>122</td><td>2</td><td>1</td><td>1</td><td>5</td><td>7</td><td>5</td><td>37</td><td>108</td><td>172</td><td>9</td><td>348</td><td>4</td><td>1</td><td>1</td><td>156</td><td>25</td><td>17</td><td>9</td><td>17</td><td>35</td><td>0</td><td>21</td><td>3</td><td>6</td></tr>\n",
       "\t<tr><th scope=row>6</th><td>french</td><td>594</td><td>38</td><td>176</td><td>16</td><td>127</td><td>3</td><td>42</td><td>145</td><td>129</td><td>35</td><td>159</td><td>303</td><td>246</td><td>0</td><td>172</td><td>112</td><td>725</td><td>52</td><td>80</td><td>265</td><td>109</td><td>13</td><td>305</td><td>113</td><td>1162</td><td>15</td><td>20</td><td>28</td><td>93</td><td>10</td><td>255</td><td>61</td><td>162</td><td>24</td><td>554</td><td>71</td><td>536</td><td>14</td><td>8</td><td>11</td><td>3</td><td>14</td><td>1</td><td>110</td><td>237</td><td>439</td><td>33</td><td>14</td><td>106</td><td>538</td><td>38</td><td>23</td><td>58</td><td>17</td><td>91</td><td>231</td><td>21</td><td>137</td><td>10</td><td>28</td><td>699</td><td>81</td><td>13</td><td>26</td><td>9</td><td>18</td><td>13</td><td>48</td><td>60</td><td>190</td><td>19</td><td>44</td><td>12</td><td>724</td><td>1194</td><td>42</td><td>0</td><td>256</td><td>292</td><td>171</td><td>101</td><td>7</td><td>150</td><td>100</td><td>17</td><td>41</td><td>24</td><td>127</td><td>803</td><td>90</td><td>1457</td><td>93</td><td>0</td><td>777</td><td>44</td><td>45</td><td>124</td><td>287</td><td>5</td><td>229</td><td>866</td><td>69</td><td>75</td><td>247</td><td>1</td><td>72</td><td>42</td><td>98</td><td>40</td><td>7</td><td>1</td><td>459</td><td>54</td><td>5</td><td>2</td><td>159</td><td>34</td><td>863</td><td>283</td><td>5</td><td>420</td><td>139</td><td>527</td><td>59</td><td>59</td><td>93</td><td>39</td><td>76</td><td>77</td><td>0</td><td>47</td><td>21</td><td>17</td><td>0</td><td>484</td><td>62</td><td>55</td><td>1</td><td>26</td><td>6</td><td>11</td><td>234</td><td>255</td><td>12</td><td>140</td><td>1026</td><td>945</td><td>754</td><td>237</td><td>48</td><td>9</td><td>38</td><td>115</td><td>491</td><td>98</td><td>11</td><td>29</td><td>8</td><td>23</td><td>92</td><td>1215</td><td>111</td><td>22</td><td>75</td><td>75</td><td>299</td><td>296</td><td>65</td><td>24</td><td>428</td><td>61</td><td>83</td><td>34</td><td>15</td><td>61</td><td>18</td><td>111</td><td>50</td><td>39</td><td>0</td><td>1644</td><td>96</td><td>31</td><td>18</td><td>211</td><td>21</td><td>84</td><td>2</td><td>4</td><td>322</td><td>7</td><td>31</td><td>76</td><td>22</td><td>24</td><td>52</td><td>48</td><td>56</td><td>143</td><td>32</td><td>18</td><td>121</td><td>22</td><td>56</td><td>7</td><td>4</td><td>38</td><td>203</td><td>189</td><td>3</td><td>30</td><td>93</td><td>61</td><td>21</td><td>122</td><td>1156</td><td>32</td><td>25</td><td>60</td><td>0</td><td>0</td><td>42</td><td>534</td><td>33</td><td>5</td><td>427</td><td>1</td><td>1</td><td>22</td><td>2</td><td>597</td><td>62</td><td>403</td><td>169</td><td>327</td><td>45</td><td>661</td><td>12</td><td>25</td><td>248</td><td>830</td><td>198</td><td>663</td><td>20</td><td>76</td><td>94</td><td>23</td><td>347</td><td>101</td><td>90</td></tr>\n",
       "\t<tr><th scope=row>7</th><td>greek</td><td>100</td><td>32</td><td>29</td><td>15</td><td>5</td><td>6</td><td>34</td><td>3</td><td>69</td><td>26</td><td>76</td><td>38</td><td>67</td><td>0</td><td>55</td><td>121</td><td>398</td><td>8</td><td>69</td><td>124</td><td>101</td><td>3</td><td>70</td><td>14</td><td>167</td><td>3</td><td>2</td><td>12</td><td>30</td><td>2</td><td>32</td><td>29</td><td>32</td><td>7</td><td>578</td><td>55</td><td>229</td><td>32</td><td>5</td><td>14</td><td>0</td><td>9</td><td>0</td><td>14</td><td>8</td><td>272</td><td>6</td><td>10</td><td>125</td><td>323</td><td>24</td><td>3</td><td>5</td><td>1</td><td>9</td><td>106</td><td>16</td><td>11</td><td>0</td><td>22</td><td>54</td><td>40</td><td>255</td><td>45</td><td>264</td><td>49</td><td>3</td><td>2</td><td>70</td><td>17</td><td>174</td><td>55</td><td>25</td><td>517</td><td>206</td><td>64</td><td>0</td><td>229</td><td>32</td><td>46</td><td>21</td><td>448</td><td>21</td><td>32</td><td>1</td><td>0</td><td>44</td><td>66</td><td>136</td><td>35</td><td>891</td><td>43</td><td>0</td><td>630</td><td>7</td><td>7</td><td>17</td><td>113</td><td>216</td><td>164</td><td>650</td><td>35</td><td>2</td><td>7</td><td>0</td><td>72</td><td>16</td><td>0</td><td>16</td><td>2</td><td>2</td><td>446</td><td>154</td><td>1</td><td>1</td><td>88</td><td>136</td><td>149</td><td>91</td><td>20</td><td>142</td><td>8</td><td>644</td><td>12</td><td>82</td><td>14</td><td>6</td><td>24</td><td>38</td><td>0</td><td>16</td><td>7</td><td>12</td><td>0</td><td>89</td><td>82</td><td>168</td><td>0</td><td>13</td><td>1</td><td>13</td><td>26</td><td>27</td><td>3</td><td>48</td><td>825</td><td>916</td><td>563</td><td>46</td><td>403</td><td>0</td><td>32</td><td>49</td><td>258</td><td>39</td><td>41</td><td>12</td><td>1</td><td>8</td><td>28</td><td>865</td><td>6</td><td>151</td><td>52</td><td>21</td><td>94</td><td>99</td><td>186</td><td>12</td><td>301</td><td>6</td><td>12</td><td>64</td><td>11</td><td>29</td><td>2</td><td>63</td><td>2</td><td>3</td><td>0</td><td>747</td><td>62</td><td>3</td><td>21</td><td>39</td><td>65</td><td>35</td><td>1</td><td>12</td><td>29</td><td>2</td><td>6</td><td>6</td><td>0</td><td>16</td><td>14</td><td>40</td><td>66</td><td>58</td><td>8</td><td>17</td><td>24</td><td>4</td><td>24</td><td>6</td><td>6</td><td>110</td><td>93</td><td>27</td><td>4</td><td>7</td><td>10</td><td>20</td><td>32</td><td>24</td><td>146</td><td>16</td><td>2</td><td>4</td><td>0</td><td>0</td><td>11</td><td>71</td><td>6</td><td>0</td><td>496</td><td>5</td><td>0</td><td>14</td><td>5</td><td>62</td><td>1</td><td>35</td><td>55</td><td>172</td><td>16</td><td>185</td><td>19</td><td>32</td><td>3</td><td>175</td><td>56</td><td>199</td><td>3</td><td>15</td><td>45</td><td>280</td><td>28</td><td>70</td><td>49</td></tr>\n",
       "\t<tr><th scope=row>8</th><td>indian</td><td>150</td><td>24</td><td>124</td><td>8</td><td>45</td><td>5</td><td>71</td><td>0</td><td>110</td><td>6</td><td>15</td><td>231</td><td>119</td><td>1</td><td>58</td><td>150</td><td>688</td><td>43</td><td>253</td><td>80</td><td>257</td><td>19</td><td>192</td><td>220</td><td>429</td><td>21</td><td>37</td><td>161</td><td>0</td><td>588</td><td>213</td><td>374</td><td>34</td><td>4</td><td>62</td><td>13</td><td>814</td><td>197</td><td>376</td><td>1544</td><td>2</td><td>3</td><td>2</td><td>7</td><td>5</td><td>763</td><td>28</td><td>1044</td><td>545</td><td>904</td><td>49</td><td>632</td><td>19</td><td>17</td><td>5</td><td>209</td><td>1155</td><td>90</td><td>1</td><td>22</td><td>286</td><td>27</td><td>3</td><td>137</td><td>97</td><td>1563</td><td>862</td><td>14</td><td>157</td><td>7</td><td>6</td><td>16</td><td>3</td><td>228</td><td>133</td><td>62</td><td>0</td><td>53</td><td>19</td><td>115</td><td>151</td><td>5</td><td>69</td><td>79</td><td>35</td><td>27</td><td>137</td><td>8</td><td>531</td><td>70</td><td>1665</td><td>170</td><td>864</td><td>1635</td><td>1475</td><td>52</td><td>19</td><td>95</td><td>141</td><td>931</td><td>2792</td><td>54</td><td>0</td><td>108</td><td>0</td><td>63</td><td>79</td><td>29</td><td>5</td><td>1</td><td>127</td><td>599</td><td>0</td><td>10</td><td>24</td><td>257</td><td>111</td><td>119</td><td>136</td><td>3</td><td>962</td><td>6</td><td>588</td><td>31</td><td>12</td><td>79</td><td>272</td><td>50</td><td>88</td><td>998</td><td>13</td><td>34</td><td>24</td><td>0</td><td>636</td><td>154</td><td>223</td><td>0</td><td>24</td><td>1</td><td>4</td><td>43</td><td>526</td><td>8</td><td>88</td><td>2031</td><td>424</td><td>1844</td><td>23</td><td>3</td><td>2</td><td>243</td><td>4</td><td>47</td><td>619</td><td>3</td><td>288</td><td>99</td><td>2</td><td>187</td><td>1648</td><td>162</td><td>414</td><td>74</td><td>26</td><td>480</td><td>1523</td><td>170</td><td>117</td><td>885</td><td>20</td><td>14</td><td>593</td><td>5</td><td>54</td><td>149</td><td>1</td><td>115</td><td>0</td><td>2</td><td>2402</td><td>141</td><td>1</td><td>36</td><td>116</td><td>16</td><td>1739</td><td>136</td><td>50</td><td>56</td><td>0</td><td>3</td><td>4</td><td>0</td><td>30</td><td>29</td><td>75</td><td>225</td><td>58</td><td>34</td><td>47</td><td>66</td><td>3</td><td>28</td><td>35</td><td>0</td><td>183</td><td>79</td><td>38</td><td>14</td><td>29</td><td>44</td><td>17</td><td>260</td><td>106</td><td>533</td><td>95</td><td>23</td><td>7</td><td>0</td><td>20</td><td>132</td><td>20</td><td>17</td><td>41</td><td>1259</td><td>8</td><td>509</td><td>11</td><td>732</td><td>89</td><td>45</td><td>18</td><td>744</td><td>153</td><td>60</td><td>967</td><td>49</td><td>85</td><td>23</td><td>247</td><td>187</td><td>55</td><td>2</td><td>73</td><td>221</td><td>576</td><td>3</td><td>22</td><td>43</td></tr>\n",
       "\t<tr><th scope=row>9</th><td>irish</td><td>219</td><td>20</td><td>13</td><td>15</td><td>31</td><td>2</td><td>11</td><td>63</td><td>255</td><td>6</td><td>3</td><td>51</td><td>10</td><td>0</td><td>120</td><td>11</td><td>142</td><td>14</td><td>4</td><td>37</td><td>5</td><td>0</td><td>61</td><td>75</td><td>334</td><td>96</td><td>88</td><td>4</td><td>4</td><td>5</td><td>121</td><td>11</td><td>42</td><td>39</td><td>83</td><td>12</td><td>66</td><td>0</td><td>2</td><td>3</td><td>0</td><td>11</td><td>1</td><td>20</td><td>37</td><td>86</td><td>16</td><td>5</td><td>43</td><td>59</td><td>9</td><td>4</td><td>9</td><td>7</td><td>16</td><td>69</td><td>2</td><td>43</td><td>0</td><td>6</td><td>174</td><td>11</td><td>2</td><td>7</td><td>5</td><td>3</td><td>0</td><td>19</td><td>11</td><td>14</td><td>7</td><td>6</td><td>3</td><td>110</td><td>215</td><td>0</td><td>0</td><td>12</td><td>43</td><td>35</td><td>7</td><td>0</td><td>8</td><td>15</td><td>6</td><td>1</td><td>4</td><td>9</td><td>341</td><td>23</td><td>181</td><td>22</td><td>0</td><td>107</td><td>26</td><td>14</td><td>41</td><td>44</td><td>2</td><td>71</td><td>222</td><td>5</td><td>15</td><td>46</td><td>0</td><td>12</td><td>8</td><td>10</td><td>5</td><td>0</td><td>3</td><td>50</td><td>0</td><td>0</td><td>2</td><td>33</td><td>41</td><td>107</td><td>31</td><td>3</td><td>54</td><td>41</td><td>61</td><td>8</td><td>3</td><td>21</td><td>7</td><td>10</td><td>44</td><td>0</td><td>8</td><td>17</td><td>0</td><td>0</td><td>186</td><td>8</td><td>10</td><td>0</td><td>20</td><td>0</td><td>3</td><td>26</td><td>44</td><td>0</td><td>39</td><td>138</td><td>65</td><td>238</td><td>45</td><td>4</td><td>3</td><td>16</td><td>7</td><td>83</td><td>23</td><td>1</td><td>23</td><td>5</td><td>7</td><td>16</td><td>284</td><td>14</td><td>11</td><td>3</td><td>25</td><td>274</td><td>165</td><td>3</td><td>50</td><td>71</td><td>10</td><td>13</td><td>2</td><td>0</td><td>11</td><td>2</td><td>19</td><td>0</td><td>11</td><td>1</td><td>462</td><td>42</td><td>31</td><td>14</td><td>17</td><td>9</td><td>42</td><td>0</td><td>4</td><td>11</td><td>12</td><td>2</td><td>8</td><td>2</td><td>13</td><td>23</td><td>0</td><td>3</td><td>16</td><td>12</td><td>122</td><td>18</td><td>1</td><td>32</td><td>7</td><td>0</td><td>7</td><td>62</td><td>13</td><td>7</td><td>1</td><td>13</td><td>7</td><td>6</td><td>49</td><td>306</td><td>12</td><td>8</td><td>11</td><td>0</td><td>0</td><td>0</td><td>69</td><td>5</td><td>0</td><td>44</td><td>1</td><td>1</td><td>4</td><td>0</td><td>87</td><td>10</td><td>51</td><td>71</td><td>41</td><td>7</td><td>121</td><td>4</td><td>55</td><td>36</td><td>101</td><td>69</td><td>30</td><td>23</td><td>6</td><td>27</td><td>12</td><td>18</td><td>20</td><td>4</td></tr>\n",
       "\t<tr><th scope=row>10</th><td>italian</td><td>919</td><td>12</td><td>266</td><td>168</td><td>34</td><td>25</td><td>237</td><td>231</td><td>305</td><td>372</td><td>2005</td><td>274</td><td>482</td><td>1</td><td>583</td><td>725</td><td>2473</td><td>82</td><td>406</td><td>880</td><td>550</td><td>192</td><td>1009</td><td>139</td><td>1660</td><td>48</td><td>48</td><td>45</td><td>311</td><td>9</td><td>434</td><td>65</td><td>428</td><td>116</td><td>5843</td><td>224</td><td>1835</td><td>41</td><td>41</td><td>107</td><td>3</td><td>28</td><td>6</td><td>128</td><td>210</td><td>1576</td><td>25</td><td>52</td><td>126</td><td>1965</td><td>156</td><td>23</td><td>64</td><td>51</td><td>95</td><td>819</td><td>20</td><td>218</td><td>78</td><td>117</td><td>994</td><td>399</td><td>133</td><td>878</td><td>40</td><td>37</td><td>9</td><td>37</td><td>513</td><td>107</td><td>24</td><td>223</td><td>130</td><td>2913</td><td>1793</td><td>228</td><td>0</td><td>1362</td><td>325</td><td>380</td><td>253</td><td>108</td><td>216</td><td>264</td><td>16</td><td>31</td><td>535</td><td>597</td><td>1361</td><td>247</td><td>4992</td><td>339</td><td>1</td><td>4173</td><td>42</td><td>70</td><td>114</td><td>2077</td><td>9</td><td>756</td><td>2981</td><td>237</td><td>97</td><td>377</td><td>0</td><td>131</td><td>249</td><td>56</td><td>1127</td><td>38</td><td>20</td><td>970</td><td>156</td><td>31</td><td>14</td><td>666</td><td>36</td><td>1291</td><td>729</td><td>163</td><td>1223</td><td>106</td><td>1401</td><td>177</td><td>74</td><td>82</td><td>50</td><td>326</td><td>189</td><td>1</td><td>63</td><td>77</td><td>92</td><td>2</td><td>737</td><td>388</td><td>169</td><td>0</td><td>97</td><td>22</td><td>1249</td><td>843</td><td>147</td><td>314</td><td>237</td><td>5183</td><td>4987</td><td>2717</td><td>289</td><td>987</td><td>9</td><td>89</td><td>2456</td><td>1746</td><td>450</td><td>1015</td><td>207</td><td>5</td><td>43</td><td>267</td><td>5668</td><td>38</td><td>34</td><td>380</td><td>231</td><td>286</td><td>723</td><td>351</td><td>85</td><td>2053</td><td>123</td><td>171</td><td>367</td><td>665</td><td>234</td><td>6</td><td>508</td><td>37</td><td>277</td><td>13</td><td>4897</td><td>1341</td><td>588</td><td>63</td><td>340</td><td>558</td><td>179</td><td>7</td><td>17</td><td>316</td><td>38</td><td>128</td><td>78</td><td>66</td><td>25</td><td>591</td><td>248</td><td>347</td><td>439</td><td>64</td><td>72</td><td>415</td><td>80</td><td>112</td><td>23</td><td>357</td><td>574</td><td>647</td><td>163</td><td>5</td><td>146</td><td>86</td><td>97</td><td>30</td><td>270</td><td>1378</td><td>199</td><td>16</td><td>35</td><td>0</td><td>2</td><td>65</td><td>524</td><td>63</td><td>17</td><td>3346</td><td>17</td><td>6</td><td>186</td><td>2</td><td>580</td><td>93</td><td>326</td><td>541</td><td>774</td><td>183</td><td>1483</td><td>63</td><td>173</td><td>279</td><td>1710</td><td>451</td><td>1521</td><td>60</td><td>248</td><td>366</td><td>34</td><td>226</td><td>272</td><td>340</td></tr>\n",
       "\t<tr><th scope=row>11</th><td>jamaican</td><td>42</td><td>195</td><td>3</td><td>6</td><td>8</td><td>6</td><td>7</td><td>10</td><td>49</td><td>1</td><td>8</td><td>21</td><td>60</td><td>0</td><td>59</td><td>74</td><td>222</td><td>6</td><td>35</td><td>35</td><td>41</td><td>1</td><td>29</td><td>109</td><td>92</td><td>2</td><td>10</td><td>10</td><td>1</td><td>2</td><td>49</td><td>50</td><td>16</td><td>2</td><td>17</td><td>4</td><td>178</td><td>0</td><td>59</td><td>57</td><td>5</td><td>4</td><td>3</td><td>7</td><td>4</td><td>70</td><td>17</td><td>34</td><td>127</td><td>145</td><td>6</td><td>140</td><td>32</td><td>10</td><td>1</td><td>46</td><td>20</td><td>24</td><td>13</td><td>5</td><td>24</td><td>31</td><td>0</td><td>16</td><td>1</td><td>30</td><td>76</td><td>44</td><td>16</td><td>6</td><td>2</td><td>7</td><td>1</td><td>163</td><td>65</td><td>1</td><td>0</td><td>6</td><td>23</td><td>11</td><td>0</td><td>0</td><td>11</td><td>11</td><td>0</td><td>13</td><td>34</td><td>3</td><td>111</td><td>5</td><td>226</td><td>6</td><td>2</td><td>313</td><td>124</td><td>1</td><td>12</td><td>32</td><td>1</td><td>109</td><td>542</td><td>13</td><td>5</td><td>2</td><td>0</td><td>8</td><td>63</td><td>10</td><td>1</td><td>0</td><td>30</td><td>136</td><td>0</td><td>1</td><td>33</td><td>33</td><td>1</td><td>24</td><td>9</td><td>9</td><td>59</td><td>1</td><td>23</td><td>1</td><td>6</td><td>26</td><td>153</td><td>17</td><td>2</td><td>3</td><td>9</td><td>17</td><td>4</td><td>0</td><td>146</td><td>31</td><td>2</td><td>0</td><td>9</td><td>0</td><td>4</td><td>5</td><td>17</td><td>3</td><td>120</td><td>270</td><td>73</td><td>374</td><td>47</td><td>7</td><td>1</td><td>28</td><td>2</td><td>15</td><td>16</td><td>1</td><td>19</td><td>8</td><td>8</td><td>14</td><td>616</td><td>10</td><td>11</td><td>5</td><td>32</td><td>53</td><td>202</td><td>26</td><td>11</td><td>123</td><td>2</td><td>3</td><td>67</td><td>0</td><td>9</td><td>16</td><td>6</td><td>0</td><td>8</td><td>2</td><td>419</td><td>173</td><td>0</td><td>113</td><td>21</td><td>52</td><td>19</td><td>5</td><td>2</td><td>9</td><td>0</td><td>1</td><td>4</td><td>0</td><td>1</td><td>7</td><td>20</td><td>32</td><td>15</td><td>6</td><td>14</td><td>17</td><td>2</td><td>9</td><td>81</td><td>0</td><td>14</td><td>16</td><td>11</td><td>8</td><td>6</td><td>11</td><td>9</td><td>7</td><td>38</td><td>204</td><td>27</td><td>12</td><td>8</td><td>0</td><td>0</td><td>17</td><td>296</td><td>3</td><td>0</td><td>85</td><td>5</td><td>15</td><td>3</td><td>13</td><td>19</td><td>16</td><td>37</td><td>121</td><td>90</td><td>5</td><td>210</td><td>5</td><td>2</td><td>3</td><td>91</td><td>10</td><td>24</td><td>10</td><td>12</td><td>35</td><td>2</td><td>2</td><td>7</td><td>5</td></tr>\n",
       "\t<tr><th scope=row>12</th><td>japanese</td><td>69</td><td>1</td><td>13</td><td>5</td><td>18</td><td>60</td><td>38</td><td>8</td><td>55</td><td>4</td><td>10</td><td>24</td><td>51</td><td>22</td><td>71</td><td>51</td><td>154</td><td>19</td><td>91</td><td>14</td><td>65</td><td>17</td><td>67</td><td>115</td><td>105</td><td>0</td><td>105</td><td>63</td><td>0</td><td>38</td><td>204</td><td>26</td><td>19</td><td>1</td><td>35</td><td>9</td><td>276</td><td>3</td><td>28</td><td>182</td><td>17</td><td>1</td><td>1</td><td>37</td><td>8</td><td>74</td><td>8</td><td>93</td><td>23</td><td>116</td><td>9</td><td>43</td><td>32</td><td>8</td><td>4</td><td>72</td><td>65</td><td>114</td><td>0</td><td>7</td><td>61</td><td>4</td><td>0</td><td>22</td><td>116</td><td>65</td><td>36</td><td>54</td><td>6</td><td>13</td><td>5</td><td>6</td><td>7</td><td>128</td><td>334</td><td>39</td><td>0</td><td>22</td><td>23</td><td>12</td><td>12</td><td>0</td><td>103</td><td>21</td><td>68</td><td>27</td><td>120</td><td>6</td><td>203</td><td>15</td><td>404</td><td>44</td><td>46</td><td>358</td><td>461</td><td>3</td><td>48</td><td>19</td><td>1</td><td>330</td><td>261</td><td>8</td><td>4</td><td>15</td><td>9</td><td>79</td><td>40</td><td>14</td><td>2</td><td>1</td><td>5</td><td>143</td><td>0</td><td>5</td><td>37</td><td>81</td><td>0</td><td>124</td><td>18</td><td>2</td><td>111</td><td>19</td><td>140</td><td>3</td><td>11</td><td>48</td><td>64</td><td>79</td><td>1</td><td>51</td><td>51</td><td>28</td><td>19</td><td>0</td><td>102</td><td>49</td><td>5</td><td>402</td><td>15</td><td>0</td><td>4</td><td>147</td><td>48</td><td>136</td><td>3</td><td>901</td><td>81</td><td>472</td><td>36</td><td>0</td><td>13</td><td>9</td><td>8</td><td>11</td><td>184</td><td>3</td><td>75</td><td>32</td><td>4</td><td>58</td><td>390</td><td>10</td><td>16</td><td>8</td><td>112</td><td>96</td><td>236</td><td>14</td><td>4</td><td>179</td><td>34</td><td>13</td><td>554</td><td>1</td><td>17</td><td>51</td><td>0</td><td>7</td><td>0</td><td>0</td><td>581</td><td>940</td><td>2</td><td>236</td><td>75</td><td>24</td><td>346</td><td>2</td><td>520</td><td>30</td><td>1</td><td>8</td><td>15</td><td>138</td><td>9</td><td>28</td><td>71</td><td>65</td><td>41</td><td>22</td><td>20</td><td>114</td><td>12</td><td>3</td><td>779</td><td>2</td><td>73</td><td>27</td><td>4</td><td>42</td><td>10</td><td>111</td><td>50</td><td>10</td><td>64</td><td>650</td><td>41</td><td>10</td><td>10</td><td>0</td><td>7</td><td>65</td><td>3</td><td>137</td><td>127</td><td>78</td><td>1</td><td>29</td><td>3</td><td>34</td><td>21</td><td>0</td><td>20</td><td>292</td><td>337</td><td>11</td><td>479</td><td>20</td><td>16</td><td>2</td><td>300</td><td>25</td><td>65</td><td>22</td><td>7</td><td>48</td><td>4</td><td>49</td><td>14</td><td>18</td></tr>\n",
       "\t<tr><th scope=row>13</th><td>korean</td><td>31</td><td>0</td><td>1</td><td>0</td><td>27</td><td>2</td><td>22</td><td>8</td><td>10</td><td>4</td><td>2</td><td>3</td><td>64</td><td>32</td><td>166</td><td>31</td><td>192</td><td>4</td><td>26</td><td>3</td><td>10</td><td>4</td><td>37</td><td>168</td><td>15</td><td>2</td><td>110</td><td>46</td><td>0</td><td>0</td><td>180</td><td>16</td><td>5</td><td>6</td><td>13</td><td>0</td><td>109</td><td>1</td><td>77</td><td>162</td><td>20</td><td>2</td><td>0</td><td>21</td><td>0</td><td>45</td><td>12</td><td>17</td><td>6</td><td>181</td><td>16</td><td>8</td><td>20</td><td>0</td><td>0</td><td>73</td><td>6</td><td>66</td><td>0</td><td>3</td><td>6</td><td>1</td><td>0</td><td>47</td><td>81</td><td>1</td><td>2</td><td>69</td><td>1</td><td>3</td><td>0</td><td>1</td><td>3</td><td>45</td><td>170</td><td>4</td><td>0</td><td>4</td><td>6</td><td>4</td><td>0</td><td>0</td><td>8</td><td>2</td><td>35</td><td>59</td><td>149</td><td>4</td><td>88</td><td>4</td><td>186</td><td>3</td><td>0</td><td>639</td><td>320</td><td>4</td><td>24</td><td>1</td><td>1</td><td>348</td><td>191</td><td>1</td><td>3</td><td>3</td><td>4</td><td>80</td><td>40</td><td>7</td><td>0</td><td>1</td><td>16</td><td>63</td><td>0</td><td>1</td><td>13</td><td>74</td><td>6</td><td>52</td><td>10</td><td>11</td><td>39</td><td>9</td><td>20</td><td>2</td><td>46</td><td>36</td><td>11</td><td>50</td><td>0</td><td>0</td><td>9</td><td>17</td><td>10</td><td>0</td><td>6</td><td>112</td><td>0</td><td>59</td><td>7</td><td>0</td><td>1</td><td>89</td><td>13</td><td>56</td><td>0</td><td>815</td><td>42</td><td>625</td><td>8</td><td>0</td><td>20</td><td>11</td><td>0</td><td>3</td><td>96</td><td>2</td><td>9</td><td>19</td><td>0</td><td>21</td><td>578</td><td>2</td><td>4</td><td>2</td><td>90</td><td>52</td><td>64</td><td>8</td><td>2</td><td>237</td><td>22</td><td>91</td><td>414</td><td>0</td><td>24</td><td>16</td><td>1</td><td>0</td><td>0</td><td>1</td><td>382</td><td>676</td><td>4</td><td>197</td><td>36</td><td>10</td><td>368</td><td>4</td><td>897</td><td>7</td><td>1</td><td>1</td><td>12</td><td>77</td><td>9</td><td>20</td><td>31</td><td>11</td><td>24</td><td>3</td><td>9</td><td>84</td><td>0</td><td>3</td><td>544</td><td>1</td><td>65</td><td>15</td><td>0</td><td>46</td><td>4</td><td>47</td><td>85</td><td>4</td><td>33</td><td>488</td><td>44</td><td>0</td><td>46</td><td>0</td><td>5</td><td>13</td><td>1</td><td>191</td><td>67</td><td>7</td><td>10</td><td>0</td><td>5</td><td>0</td><td>4</td><td>0</td><td>4</td><td>135</td><td>216</td><td>4</td><td>278</td><td>0</td><td>5</td><td>0</td><td>148</td><td>5</td><td>84</td><td>1</td><td>2</td><td>40</td><td>1</td><td>10</td><td>3</td><td>54</td></tr>\n",
       "\t<tr><th scope=row>14</th><td>mexican</td><td>330</td><td>66</td><td>83</td><td>86</td><td>92</td><td>1103</td><td>43</td><td>126</td><td>256</td><td>24</td><td>63</td><td>188</td><td>1710</td><td>0</td><td>839</td><td>928</td><td>2245</td><td>40</td><td>608</td><td>109</td><td>853</td><td>16</td><td>858</td><td>263</td><td>577</td><td>30</td><td>192</td><td>267</td><td>27</td><td>2</td><td>169</td><td>425</td><td>111</td><td>1135</td><td>2976</td><td>91</td><td>2473</td><td>16</td><td>1490</td><td>3039</td><td>0</td><td>444</td><td>505</td><td>24</td><td>129</td><td>2077</td><td>144</td><td>2794</td><td>319</td><td>1168</td><td>169</td><td>54</td><td>37</td><td>138</td><td>20</td><td>719</td><td>218</td><td>2152</td><td>42</td><td>49</td><td>1910</td><td>46</td><td>39</td><td>155</td><td>68</td><td>2061</td><td>6</td><td>47</td><td>806</td><td>19</td><td>16</td><td>48</td><td>124</td><td>835</td><td>654</td><td>4</td><td>400</td><td>206</td><td>104</td><td>292</td><td>6</td><td>42</td><td>115</td><td>144</td><td>18</td><td>24</td><td>134</td><td>26</td><td>1425</td><td>121</td><td>2684</td><td>356</td><td>0</td><td>3222</td><td>32</td><td>20</td><td>77</td><td>164</td><td>66</td><td>1946</td><td>3495</td><td>180</td><td>27</td><td>71</td><td>1</td><td>120</td><td>346</td><td>82</td><td>41</td><td>854</td><td>1175</td><td>1628</td><td>4</td><td>420</td><td>37</td><td>617</td><td>11</td><td>399</td><td>113</td><td>212</td><td>579</td><td>3</td><td>237</td><td>75</td><td>509</td><td>118</td><td>2286</td><td>195</td><td>111</td><td>0</td><td>166</td><td>124</td><td>58</td><td>500</td><td>449</td><td>274</td><td>50</td><td>1</td><td>343</td><td>530</td><td>95</td><td>151</td><td>50</td><td>24</td><td>15</td><td>2978</td><td>1846</td><td>4436</td><td>283</td><td>906</td><td>4</td><td>363</td><td>51</td><td>147</td><td>181</td><td>79</td><td>32</td><td>46</td><td>27</td><td>66</td><td>4689</td><td>55</td><td>71</td><td>190</td><td>396</td><td>230</td><td>2376</td><td>618</td><td>73</td><td>1175</td><td>189</td><td>48</td><td>520</td><td>16</td><td>247</td><td>4</td><td>16</td><td>7</td><td>7</td><td>1283</td><td>3920</td><td>1508</td><td>96</td><td>172</td><td>199</td><td>670</td><td>284</td><td>236</td><td>60</td><td>46</td><td>167</td><td>123</td><td>18</td><td>11</td><td>119</td><td>1456</td><td>178</td><td>487</td><td>328</td><td>168</td><td>38</td><td>293</td><td>206</td><td>1323</td><td>61</td><td>17</td><td>109</td><td>361</td><td>112</td><td>15</td><td>65</td><td>59</td><td>170</td><td>70</td><td>248</td><td>690</td><td>226</td><td>51</td><td>21</td><td>637</td><td>0</td><td>93</td><td>68</td><td>24</td><td>13</td><td>2868</td><td>2535</td><td>5</td><td>181</td><td>10</td><td>160</td><td>67</td><td>150</td><td>997</td><td>435</td><td>56</td><td>1099</td><td>256</td><td>114</td><td>72</td><td>1009</td><td>357</td><td>160</td><td>67</td><td>33</td><td>446</td><td>115</td><td>44</td><td>69</td><td>147</td></tr>\n",
       "\t<tr><th scope=row>15</th><td>moroccan</td><td>44</td><td>44</td><td>111</td><td>6</td><td>7</td><td>2</td><td>12</td><td>0</td><td>11</td><td>5</td><td>9</td><td>23</td><td>58</td><td>0</td><td>68</td><td>77</td><td>278</td><td>18</td><td>56</td><td>20</td><td>65</td><td>4</td><td>180</td><td>23</td><td>110</td><td>0</td><td>4</td><td>20</td><td>8</td><td>29</td><td>167</td><td>142</td><td>36</td><td>2</td><td>24</td><td>12</td><td>365</td><td>132</td><td>23</td><td>43</td><td>0</td><td>2</td><td>0</td><td>2</td><td>0</td><td>335</td><td>4</td><td>286</td><td>413</td><td>299</td><td>23</td><td>7</td><td>1</td><td>1</td><td>9</td><td>49</td><td>252</td><td>9</td><td>3</td><td>8</td><td>6</td><td>7</td><td>7</td><td>36</td><td>8</td><td>452</td><td>23</td><td>1</td><td>65</td><td>3</td><td>6</td><td>7</td><td>1</td><td>182</td><td>74</td><td>35</td><td>0</td><td>128</td><td>3</td><td>40</td><td>25</td><td>12</td><td>27</td><td>25</td><td>1</td><td>6</td><td>34</td><td>66</td><td>90</td><td>28</td><td>676</td><td>9</td><td>6</td><td>450</td><td>287</td><td>50</td><td>9</td><td>46</td><td>20</td><td>142</td><td>1370</td><td>43</td><td>0</td><td>1</td><td>0</td><td>117</td><td>21</td><td>2</td><td>6</td><td>0</td><td>2</td><td>259</td><td>23</td><td>0</td><td>2</td><td>95</td><td>170</td><td>63</td><td>79</td><td>3</td><td>96</td><td>4</td><td>449</td><td>29</td><td>5</td><td>4</td><td>20</td><td>41</td><td>5</td><td>6</td><td>7</td><td>14</td><td>2</td><td>0</td><td>20</td><td>34</td><td>118</td><td>0</td><td>8</td><td>0</td><td>1</td><td>6</td><td>9</td><td>5</td><td>32</td><td>638</td><td>658</td><td>496</td><td>89</td><td>12</td><td>1</td><td>243</td><td>3</td><td>242</td><td>80</td><td>5</td><td>15</td><td>4</td><td>0</td><td>41</td><td>685</td><td>8</td><td>17</td><td>23</td><td>6</td><td>78</td><td>77</td><td>67</td><td>97</td><td>186</td><td>7</td><td>17</td><td>19</td><td>2</td><td>18</td><td>8</td><td>6</td><td>126</td><td>0</td><td>1</td><td>601</td><td>25</td><td>11</td><td>5</td><td>42</td><td>6</td><td>140</td><td>2</td><td>20</td><td>30</td><td>0</td><td>5</td><td>10</td><td>0</td><td>33</td><td>1</td><td>8</td><td>51</td><td>32</td><td>31</td><td>0</td><td>59</td><td>1</td><td>4</td><td>4</td><td>2</td><td>12</td><td>43</td><td>29</td><td>2</td><td>44</td><td>0</td><td>13</td><td>72</td><td>103</td><td>130</td><td>104</td><td>0</td><td>3</td><td>0</td><td>0</td><td>52</td><td>22</td><td>14</td><td>1</td><td>308</td><td>0</td><td>112</td><td>8</td><td>73</td><td>47</td><td>1</td><td>6</td><td>118</td><td>41</td><td>20</td><td>253</td><td>17</td><td>12</td><td>2</td><td>66</td><td>28</td><td>51</td><td>0</td><td>20</td><td>66</td><td>34</td><td>8</td><td>32</td><td>40</td></tr>\n",
       "\t<tr><th scope=row>16</th><td>russian</td><td>123</td><td>8</td><td>26</td><td>4</td><td>31</td><td>2</td><td>0</td><td>11</td><td>74</td><td>4</td><td>6</td><td>39</td><td>18</td><td>0</td><td>72</td><td>18</td><td>106</td><td>14</td><td>7</td><td>41</td><td>13</td><td>0</td><td>42</td><td>15</td><td>213</td><td>12</td><td>70</td><td>9</td><td>10</td><td>6</td><td>80</td><td>9</td><td>40</td><td>4</td><td>68</td><td>9</td><td>43</td><td>1</td><td>2</td><td>9</td><td>0</td><td>1</td><td>0</td><td>14</td><td>17</td><td>59</td><td>14</td><td>9</td><td>34</td><td>69</td><td>11</td><td>1</td><td>19</td><td>10</td><td>13</td><td>15</td><td>6</td><td>16</td><td>1</td><td>4</td><td>183</td><td>24</td><td>0</td><td>1</td><td>20</td><td>5</td><td>0</td><td>10</td><td>11</td><td>9</td><td>111</td><td>4</td><td>2</td><td>91</td><td>280</td><td>2</td><td>0</td><td>6</td><td>44</td><td>4</td><td>6</td><td>2</td><td>17</td><td>13</td><td>0</td><td>4</td><td>6</td><td>11</td><td>237</td><td>0</td><td>160</td><td>10</td><td>0</td><td>88</td><td>9</td><td>16</td><td>19</td><td>10</td><td>2</td><td>51</td><td>159</td><td>6</td><td>13</td><td>18</td><td>0</td><td>22</td><td>17</td><td>4</td><td>2</td><td>0</td><td>2</td><td>64</td><td>1</td><td>0</td><td>9</td><td>23</td><td>3</td><td>121</td><td>23</td><td>8</td><td>39</td><td>9</td><td>101</td><td>0</td><td>2</td><td>8</td><td>0</td><td>4</td><td>7</td><td>2</td><td>31</td><td>11</td><td>2</td><td>0</td><td>98</td><td>10</td><td>4</td><td>0</td><td>5</td><td>0</td><td>4</td><td>47</td><td>17</td><td>8</td><td>8</td><td>173</td><td>66</td><td>209</td><td>14</td><td>2</td><td>0</td><td>20</td><td>2</td><td>59</td><td>19</td><td>1</td><td>20</td><td>0</td><td>0</td><td>14</td><td>213</td><td>12</td><td>15</td><td>4</td><td>26</td><td>128</td><td>82</td><td>8</td><td>40</td><td>57</td><td>5</td><td>16</td><td>20</td><td>3</td><td>4</td><td>9</td><td>3</td><td>4</td><td>1</td><td>0</td><td>345</td><td>32</td><td>10</td><td>9</td><td>14</td><td>7</td><td>43</td><td>0</td><td>0</td><td>9</td><td>1</td><td>0</td><td>2</td><td>2</td><td>2</td><td>9</td><td>4</td><td>7</td><td>15</td><td>15</td><td>24</td><td>8</td><td>7</td><td>127</td><td>3</td><td>0</td><td>4</td><td>6</td><td>2</td><td>0</td><td>0</td><td>14</td><td>9</td><td>8</td><td>20</td><td>251</td><td>18</td><td>3</td><td>6</td><td>0</td><td>0</td><td>1</td><td>11</td><td>5</td><td>2</td><td>82</td><td>1</td><td>1</td><td>6</td><td>0</td><td>94</td><td>7</td><td>63</td><td>91</td><td>74</td><td>22</td><td>167</td><td>2</td><td>8</td><td>18</td><td>95</td><td>28</td><td>38</td><td>6</td><td>57</td><td>9</td><td>13</td><td>36</td><td>10</td><td>2</td></tr>\n",
       "\t<tr><th scope=row>17</th><td>southern_us</td><td>1223</td><td>59</td><td>70</td><td>61</td><td>232</td><td>13</td><td>48</td><td>431</td><td>1240</td><td>31</td><td>82</td><td>192</td><td>157</td><td>0</td><td>86</td><td>303</td><td>866</td><td>65</td><td>130</td><td>258</td><td>145</td><td>13</td><td>390</td><td>627</td><td>2136</td><td>712</td><td>64</td><td>115</td><td>8</td><td>9</td><td>151</td><td>331</td><td>350</td><td>403</td><td>872</td><td>48</td><td>922</td><td>2</td><td>68</td><td>219</td><td>0</td><td>30</td><td>23</td><td>92</td><td>112</td><td>751</td><td>228</td><td>58</td><td>399</td><td>396</td><td>73</td><td>121</td><td>67</td><td>115</td><td>65</td><td>311</td><td>16</td><td>829</td><td>318</td><td>58</td><td>965</td><td>168</td><td>16</td><td>154</td><td>25</td><td>75</td><td>28</td><td>169</td><td>137</td><td>101</td><td>44</td><td>21</td><td>65</td><td>501</td><td>1688</td><td>3</td><td>1</td><td>98</td><td>591</td><td>119</td><td>13</td><td>4</td><td>73</td><td>98</td><td>77</td><td>7</td><td>166</td><td>47</td><td>1847</td><td>71</td><td>1026</td><td>168</td><td>2</td><td>987</td><td>116</td><td>41</td><td>289</td><td>231</td><td>14</td><td>789</td><td>1532</td><td>128</td><td>223</td><td>255</td><td>2</td><td>176</td><td>332</td><td>152</td><td>52</td><td>46</td><td>110</td><td>594</td><td>3</td><td>117</td><td>102</td><td>357</td><td>3</td><td>934</td><td>114</td><td>14</td><td>216</td><td>18</td><td>586</td><td>29</td><td>55</td><td>309</td><td>169</td><td>80</td><td>77</td><td>2</td><td>182</td><td>56</td><td>33</td><td>5</td><td>1117</td><td>106</td><td>109</td><td>0</td><td>164</td><td>19</td><td>13</td><td>77</td><td>336</td><td>5</td><td>221</td><td>1276</td><td>429</td><td>1365</td><td>205</td><td>55</td><td>28</td><td>270</td><td>136</td><td>286</td><td>36</td><td>18</td><td>210</td><td>175</td><td>429</td><td>37</td><td>2709</td><td>27</td><td>30</td><td>29</td><td>221</td><td>314</td><td>1414</td><td>95</td><td>48</td><td>559</td><td>57</td><td>134</td><td>154</td><td>1</td><td>87</td><td>7</td><td>54</td><td>1</td><td>79</td><td>18</td><td>3088</td><td>798</td><td>153</td><td>71</td><td>106</td><td>365</td><td>112</td><td>4</td><td>14</td><td>64</td><td>212</td><td>51</td><td>25</td><td>10</td><td>35</td><td>221</td><td>217</td><td>98</td><td>226</td><td>155</td><td>473</td><td>101</td><td>89</td><td>137</td><td>35</td><td>2</td><td>21</td><td>206</td><td>75</td><td>1</td><td>36</td><td>159</td><td>64</td><td>28</td><td>118</td><td>2319</td><td>316</td><td>125</td><td>271</td><td>2</td><td>0</td><td>49</td><td>259</td><td>29</td><td>0</td><td>469</td><td>9</td><td>9</td><td>49</td><td>12</td><td>660</td><td>69</td><td>778</td><td>658</td><td>459</td><td>31</td><td>895</td><td>27</td><td>47</td><td>243</td><td>837</td><td>328</td><td>161</td><td>182</td><td>40</td><td>377</td><td>37</td><td>146</td><td>102</td><td>14</td></tr>\n",
       "\t<tr><th scope=row>18</th><td>spanish</td><td>53</td><td>4</td><td>94</td><td>5</td><td>24</td><td>23</td><td>16</td><td>24</td><td>33</td><td>24</td><td>35</td><td>93</td><td>64</td><td>0</td><td>36</td><td>265</td><td>251</td><td>19</td><td>33</td><td>117</td><td>42</td><td>2</td><td>133</td><td>22</td><td>92</td><td>3</td><td>9</td><td>7</td><td>20</td><td>1</td><td>45</td><td>40</td><td>24</td><td>7</td><td>88</td><td>14</td><td>262</td><td>23</td><td>48</td><td>68</td><td>0</td><td>5</td><td>6</td><td>16</td><td>6</td><td>224</td><td>8</td><td>86</td><td>68</td><td>381</td><td>16</td><td>4</td><td>5</td><td>16</td><td>5</td><td>66</td><td>11</td><td>41</td><td>4</td><td>8</td><td>68</td><td>35</td><td>5</td><td>56</td><td>78</td><td>70</td><td>5</td><td>8</td><td>74</td><td>12</td><td>5</td><td>6</td><td>1</td><td>275</td><td>274</td><td>13</td><td>0</td><td>255</td><td>35</td><td>40</td><td>17</td><td>4</td><td>32</td><td>23</td><td>1</td><td>16</td><td>44</td><td>82</td><td>98</td><td>32</td><td>487</td><td>46</td><td>0</td><td>561</td><td>11</td><td>13</td><td>10</td><td>39</td><td>1</td><td>258</td><td>361</td><td>21</td><td>53</td><td>18</td><td>0</td><td>25</td><td>60</td><td>26</td><td>18</td><td>1</td><td>31</td><td>243</td><td>8</td><td>9</td><td>6</td><td>122</td><td>7</td><td>251</td><td>130</td><td>4</td><td>104</td><td>11</td><td>214</td><td>25</td><td>13</td><td>8</td><td>67</td><td>37</td><td>17</td><td>0</td><td>15</td><td>12</td><td>32</td><td>1</td><td>107</td><td>62</td><td>25</td><td>0</td><td>11</td><td>1</td><td>2</td><td>24</td><td>16</td><td>2</td><td>16</td><td>734</td><td>729</td><td>516</td><td>141</td><td>67</td><td>4</td><td>196</td><td>12</td><td>245</td><td>42</td><td>6</td><td>72</td><td>0</td><td>3</td><td>30</td><td>910</td><td>8</td><td>10</td><td>52</td><td>44</td><td>166</td><td>53</td><td>55</td><td>28</td><td>407</td><td>10</td><td>14</td><td>135</td><td>2</td><td>58</td><td>0</td><td>23</td><td>126</td><td>5</td><td>13</td><td>677</td><td>77</td><td>89</td><td>24</td><td>52</td><td>9</td><td>18</td><td>33</td><td>1</td><td>29</td><td>1</td><td>5</td><td>127</td><td>3</td><td>5</td><td>2</td><td>121</td><td>31</td><td>55</td><td>75</td><td>18</td><td>56</td><td>2</td><td>19</td><td>4</td><td>5</td><td>19</td><td>49</td><td>27</td><td>0</td><td>3</td><td>17</td><td>6</td><td>34</td><td>58</td><td>188</td><td>60</td><td>16</td><td>7</td><td>0</td><td>0</td><td>31</td><td>73</td><td>4</td><td>0</td><td>436</td><td>8</td><td>9</td><td>18</td><td>3</td><td>44</td><td>3</td><td>47</td><td>81</td><td>214</td><td>8</td><td>206</td><td>29</td><td>4</td><td>17</td><td>247</td><td>34</td><td>270</td><td>14</td><td>12</td><td>64</td><td>11</td><td>41</td><td>33</td><td>19</td></tr>\n",
       "\t<tr><th scope=row>19</th><td>thai</td><td>17</td><td>1</td><td>8</td><td>7</td><td>18</td><td>14</td><td>56</td><td>1</td><td>8</td><td>4</td><td>334</td><td>14</td><td>136</td><td>152</td><td>54</td><td>255</td><td>127</td><td>13</td><td>231</td><td>16</td><td>313</td><td>40</td><td>204</td><td>339</td><td>228</td><td>1</td><td>91</td><td>77</td><td>0</td><td>21</td><td>225</td><td>53</td><td>21</td><td>0</td><td>12</td><td>34</td><td>762</td><td>8</td><td>285</td><td>556</td><td>35</td><td>1</td><td>0</td><td>23</td><td>0</td><td>355</td><td>15</td><td>730</td><td>23</td><td>357</td><td>11</td><td>743</td><td>14</td><td>9</td><td>0</td><td>178</td><td>189</td><td>110</td><td>0</td><td>6</td><td>44</td><td>9</td><td>1</td><td>106</td><td>125</td><td>88</td><td>480</td><td>86</td><td>12</td><td>2</td><td>0</td><td>2</td><td>11</td><td>149</td><td>209</td><td>36</td><td>0</td><td>9</td><td>6</td><td>53</td><td>4</td><td>1</td><td>55</td><td>7</td><td>89</td><td>832</td><td>137</td><td>1</td><td>54</td><td>24</td><td>1325</td><td>28</td><td>2</td><td>957</td><td>521</td><td>10</td><td>30</td><td>33</td><td>2</td><td>575</td><td>389</td><td>55</td><td>0</td><td>8</td><td>17</td><td>80</td><td>66</td><td>10</td><td>2</td><td>1</td><td>84</td><td>590</td><td>0</td><td>4</td><td>30</td><td>84</td><td>3</td><td>147</td><td>18</td><td>11</td><td>527</td><td>7</td><td>151</td><td>21</td><td>77</td><td>184</td><td>1114</td><td>106</td><td>8</td><td>3</td><td>10</td><td>14</td><td>68</td><td>0</td><td>632</td><td>122</td><td>171</td><td>7</td><td>11</td><td>1</td><td>4</td><td>135</td><td>14</td><td>258</td><td>10</td><td>1057</td><td>125</td><td>699</td><td>38</td><td>4</td><td>46</td><td>19</td><td>2</td><td>8</td><td>570</td><td>5</td><td>89</td><td>625</td><td>0</td><td>111</td><td>962</td><td>38</td><td>5</td><td>11</td><td>83</td><td>49</td><td>175</td><td>84</td><td>6</td><td>831</td><td>58</td><td>17</td><td>653</td><td>0</td><td>183</td><td>82</td><td>0</td><td>2</td><td>1</td><td>2</td><td>585</td><td>1636</td><td>0</td><td>138</td><td>47</td><td>19</td><td>136</td><td>50</td><td>247</td><td>244</td><td>0</td><td>7</td><td>8</td><td>40</td><td>4</td><td>55</td><td>293</td><td>220</td><td>100</td><td>2</td><td>3</td><td>169</td><td>4</td><td>0</td><td>506</td><td>9</td><td>37</td><td>46</td><td>33</td><td>59</td><td>32</td><td>75</td><td>73</td><td>48</td><td>119</td><td>865</td><td>128</td><td>12</td><td>22</td><td>0</td><td>487</td><td>62</td><td>4</td><td>54</td><td>106</td><td>148</td><td>15</td><td>39</td><td>18</td><td>41</td><td>55</td><td>121</td><td>3</td><td>414</td><td>233</td><td>9</td><td>381</td><td>114</td><td>12</td><td>3</td><td>202</td><td>13</td><td>49</td><td>4</td><td>2</td><td>68</td><td>7</td><td>1</td><td>55</td><td>46</td></tr>\n",
       "\t<tr><th scope=row>20</th><td>vietnamese</td><td>12</td><td>4</td><td>4</td><td>4</td><td>11</td><td>14</td><td>20</td><td>2</td><td>9</td><td>1</td><td>162</td><td>9</td><td>84</td><td>127</td><td>110</td><td>40</td><td>190</td><td>5</td><td>66</td><td>10</td><td>69</td><td>11</td><td>78</td><td>99</td><td>63</td><td>0</td><td>61</td><td>85</td><td>0</td><td>16</td><td>254</td><td>10</td><td>15</td><td>0</td><td>2</td><td>2</td><td>238</td><td>0</td><td>170</td><td>251</td><td>36</td><td>1</td><td>1</td><td>9</td><td>0</td><td>160</td><td>9</td><td>336</td><td>54</td><td>207</td><td>9</td><td>62</td><td>13</td><td>18</td><td>1</td><td>71</td><td>83</td><td>60</td><td>0</td><td>13</td><td>7</td><td>2</td><td>0</td><td>34</td><td>158</td><td>9</td><td>30</td><td>35</td><td>8</td><td>1</td><td>6</td><td>1</td><td>5</td><td>69</td><td>94</td><td>6</td><td>0</td><td>5</td><td>4</td><td>14</td><td>10</td><td>0</td><td>19</td><td>7</td><td>38</td><td>490</td><td>41</td><td>1</td><td>59</td><td>5</td><td>563</td><td>7</td><td>0</td><td>542</td><td>228</td><td>4</td><td>24</td><td>16</td><td>1</td><td>210</td><td>271</td><td>7</td><td>5</td><td>2</td><td>63</td><td>33</td><td>58</td><td>10</td><td>3</td><td>1</td><td>61</td><td>257</td><td>0</td><td>2</td><td>6</td><td>92</td><td>2</td><td>47</td><td>22</td><td>3</td><td>284</td><td>4</td><td>60</td><td>6</td><td>120</td><td>39</td><td>373</td><td>32</td><td>2</td><td>0</td><td>33</td><td>32</td><td>45</td><td>0</td><td>64</td><td>86</td><td>180</td><td>6</td><td>8</td><td>1</td><td>0</td><td>48</td><td>3</td><td>177</td><td>2</td><td>528</td><td>43</td><td>413</td><td>14</td><td>0</td><td>28</td><td>6</td><td>1</td><td>5</td><td>65</td><td>0</td><td>17</td><td>170</td><td>0</td><td>34</td><td>499</td><td>25</td><td>2</td><td>6</td><td>166</td><td>15</td><td>77</td><td>45</td><td>0</td><td>176</td><td>20</td><td>12</td><td>477</td><td>0</td><td>79</td><td>27</td><td>0</td><td>0</td><td>0</td><td>0</td><td>400</td><td>941</td><td>11</td><td>100</td><td>20</td><td>11</td><td>68</td><td>37</td><td>147</td><td>158</td><td>0</td><td>3</td><td>2</td><td>27</td><td>16</td><td>44</td><td>135</td><td>50</td><td>44</td><td>0</td><td>5</td><td>65</td><td>5</td><td>1</td><td>236</td><td>4</td><td>8</td><td>19</td><td>31</td><td>63</td><td>8</td><td>66</td><td>65</td><td>63</td><td>51</td><td>546</td><td>26</td><td>20</td><td>4</td><td>0</td><td>134</td><td>18</td><td>0</td><td>37</td><td>55</td><td>58</td><td>3</td><td>13</td><td>6</td><td>19</td><td>33</td><td>5</td><td>4</td><td>171</td><td>195</td><td>24</td><td>298</td><td>43</td><td>8</td><td>0</td><td>141</td><td>11</td><td>33</td><td>1</td><td>2</td><td>69</td><td>2</td><td>7</td><td>5</td><td>3</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllll}\n",
       "  & Group.1 & all-purpos & allspic & almond & and & appl & avocado & babi & bacon & bake & balsam & basil & bay & bean & beansprout & beef & bell & black & boil & boneless & bread & breast & broccoli & broth & brown & butter & buttermilk & cabbag & canola & caper & cardamom & carrot & cayenn & celeri & cheddar & chees & cherri & chicken & chickpea & chile & chili & chines & chip & chipotl & chive & chocol & chop & cider & cilantro & cinnamon & clove & coars & coconut & cold & condens & confection & cook & coriand & corn & cornmeal & crack & cream & crumb & crumbl & crush & cucumb & cumin & curri & dark & dice & dijon & dill & dough & dress & dri & egg & eggplant & enchilada & extra-virgin & extract & fat & fennel & feta & fillet & fine & firm & fish & flake & flat & flour & free & fresh & frozen & garam & garlic & ginger & golden & granul & grate & greek & green & ground & halv & ham & heavi & hoisin & honey & hot & ice & italian & jack & jalapeno & juic & kalamata & kernel & ketchup & kosher & lamb & larg & leaf & lean & leav & leek & lemon & less & lettuc & light & lime & low & low-fat & masala & mayonais & meat & medium & mexican & milk & minc & mint & mirin & mix & monterey & mozzarella & mushroom & mustard & noodl & nutmeg & oil & oliv & onion & orang & oregano & oyster & paprika & parmesan & parsley & past & pasta & pea & peanut & pecan & peel & pepper & peppercorn & plain & plum & pork & potato & powder & purpl & raisin & red & reduc & rib & rice & ricotta & roast & root & rosemari & saffron & sage & salsa & salt & sauc & sausag & scallion & sea & season & seed & serrano & sesam & shallot & sharp & shell & sherri & shiitak & shoulder & shred & shrimp & skinless & slice & smoke & soda & sodium & soup & sour & soy & spaghetti & spinach & spray & sprig & spring & squash & starch & steak & stick & stock & sugar & sweet & sweeten & syrup & taco & thai & thigh & thyme & toast & tofu & tomato & tortilla & tumer & turkey & turmer & unsalt & unsweeten & vanilla & veget & vinegar & warm & water & wedg & wheat & whip & white & whole & wine & worcestershir & yeast & yellow & yogurt & yolk & zest & zucchini\\\\\n",
       "\\hline\n",
       "\t1 & brazilian & 18 & 1 & 24 & 2 & 10 & 10 & 3 & 30 & 19 & 0 & 2 & 54 & 71 & 0 & 31 & 80 & 133 & 4 & 16 & 13 & 17 & 0 & 33 & 21 & 83 & 2 & 0 & 13 & 1 & 0 & 26 & 23 & 7 & 5 & 56 & 5 & 76 & 0 & 23 & 41 & 0 & 4 & 5 & 2 & 35 & 76 & 2 & 88 & 14 & 92 & 7 & 142 & 12 & 68 & 1 & 28 & 22 & 34 & 4 & 3 & 35 & 9 & 0 & 32 & 2 & 29 & 2 & 5 & 21 & 4 & 0 & 1 & 0 & 62 & 105 & 0 & 0 & 13 & 18 & 5 & 3 & 0 & 25 & 8 & 0 & 27 & 33 & 10 & 73 & 5 & 133 & 32 & 1 & 194 & 31 & 1 & 21 & 21 & 0 & 85 & 126 & 3 & 17 & 7 & 0 & 12 & 22 & 57 & 5 & 3 & 19 & 104 & 0 & 4 & 1 & 22 & 2 & 33 & 33 & 1 & 63 & 2 & 37 & 3 & 1 & 16 & 164 & 10 & 5 & 1 & 10 & 3 & 10 & 0 & 229 & 15 & 7 & 0 & 6 & 2 & 5 & 2 & 5 & 0 & 5 & 247 & 145 & 226 & 50 & 14 & 1 & 19 & 24 & 55 & 21 & 1 & 16 & 10 & 3 & 6 & 310 & 1 & 3 & 9 & 35 & 26 & 63 & 8 & 6 & 86 & 2 & 18 & 63 & 0 & 11 & 4 & 2 & 3 & 1 & 7 & 246 & 35 & 30 & 8 & 19 & 7 & 26 & 7 & 2 & 5 & 1 & 2 & 3 & 0 & 9 & 15 & 58 & 10 & 22 & 16 & 8 & 16 & 2 & 6 & 3 & 0 & 6 & 3 & 1 & 4 & 2 & 22 & 12 & 4 & 29 & 150 & 18 & 61 & 16 & 0 & 1 & 6 & 13 & 5 & 1 & 133 & 1 & 3 & 5 & 4 & 26 & 29 & 28 & 46 & 26 & 2 & 112 & 15 & 3 & 4 & 91 & 15 & 30 & 2 & 6 & 34 & 3 & 22 & 8 & 3\\\\\n",
       "\t2 & british & 238 & 27 & 44 & 3 & 30 & 0 & 2 & 25 & 217 & 17 & 5 & 42 & 15 & 0 & 158 & 4 & 134 & 18 & 3 & 81 & 4 & 1 & 36 & 109 & 436 & 26 & 10 & 18 & 4 & 2 & 61 & 32 & 26 & 60 & 108 & 16 & 30 & 0 & 1 & 8 & 0 & 4 & 0 & 18 & 32 & 66 & 9 & 5 & 68 & 57 & 17 & 6 & 22 & 11 & 22 & 23 & 7 & 57 & 11 & 13 & 268 & 37 & 1 & 7 & 4 & 8 & 19 & 44 & 3 & 22 & 5 & 12 & 0 & 157 & 436 & 0 & 0 & 19 & 85 & 10 & 3 & 0 & 35 & 12 & 2 & 14 & 14 & 6 & 467 & 12 & 180 & 57 & 2 & 94 & 54 & 53 & 37 & 54 & 4 & 26 & 312 & 4 & 7 & 104 & 0 & 16 & 16 & 15 & 2 & 0 & 1 & 65 & 0 & 1 & 7 & 61 & 14 & 164 & 26 & 20 & 48 & 18 & 125 & 0 & 3 & 40 & 5 & 8 & 8 & 2 & 7 & 8 & 14 & 0 & 287 & 16 & 14 & 0 & 32 & 0 & 0 & 58 & 76 & 0 & 70 & 201 & 77 & 215 & 55 & 8 & 0 & 22 & 11 & 52 & 29 & 0 & 30 & 2 & 12 & 35 & 276 & 10 & 39 & 4 & 46 & 144 & 213 & 11 & 62 & 50 & 2 & 16 & 23 & 0 & 18 & 2 & 23 & 2 & 21 & 0 & 516 & 83 & 42 & 4 & 26 & 11 & 23 & 1 & 1 & 19 & 20 & 6 & 23 & 1 & 6 & 12 & 3 & 4 & 23 & 17 & 85 & 9 & 3 & 23 & 5 & 0 & 5 & 12 & 10 & 4 & 2 & 32 & 26 & 9 & 49 & 454 & 21 & 11 & 41 & 0 & 1 & 0 & 62 & 7 & 0 & 53 & 0 & 9 & 2 & 3 & 193 & 2 & 119 & 82 & 71 & 15 & 178 & 8 & 15 & 82 & 168 & 77 & 66 & 53 & 41 & 26 & 8 & 67 & 21 & 3\\\\\n",
       "\t3 & cajun_creole & 291 & 18 & 12 & 39 & 14 & 4 & 17 & 62 & 64 & 8 & 94 & 360 & 164 & 0 & 79 & 696 & 496 & 23 & 152 & 133 & 176 & 3 & 348 & 111 & 498 & 33 & 15 & 84 & 30 & 1 & 53 & 399 & 619 & 20 & 174 & 9 & 741 & 3 & 28 & 142 & 0 & 5 & 3 & 22 & 11 & 544 & 19 & 26 & 46 & 329 & 29 & 9 & 10 & 17 & 26 & 299 & 10 & 145 & 23 & 24 & 206 & 49 & 5 & 89 & 0 & 57 & 1 & 14 & 277 & 33 & 13 & 5 & 18 & 646 & 237 & 4 & 0 & 47 & 54 & 51 & 9 & 1 & 75 & 41 & 4 & 12 & 69 & 50 & 450 & 31 & 546 & 52 & 0 & 1003 & 6 & 6 & 51 & 58 & 0 & 913 & 679 & 61 & 94 & 74 & 0 & 14 & 286 & 15 & 45 & 16 & 50 & 196 & 3 & 27 & 23 & 108 & 0 & 223 & 158 & 13 & 297 & 7 & 253 & 24 & 40 & 42 & 23 & 76 & 17 & 0 & 80 & 73 & 109 & 2 & 165 & 121 & 3 & 0 & 46 & 8 & 11 & 83 & 133 & 6 & 26 & 821 & 402 & 1314 & 36 & 225 & 30 & 262 & 58 & 369 & 99 & 27 & 32 & 31 & 40 & 39 & 2326 & 17 & 6 & 26 & 61 & 58 & 450 & 38 & 9 & 555 & 36 & 183 & 537 & 1 & 33 & 0 & 27 & 2 & 16 & 2 & 993 & 665 & 463 & 97 & 36 & 631 & 34 & 4 & 1 & 23 & 7 & 15 & 8 & 1 & 6 & 25 & 473 & 125 & 100 & 198 & 26 & 107 & 35 & 25 & 14 & 5 & 18 & 75 & 26 & 2 & 8 & 28 & 16 & 6 & 148 & 310 & 76 & 7 & 18 & 1 & 0 & 55 & 428 & 8 & 1 & 673 & 6 & 1 & 62 & 1 & 119 & 3 & 74 & 313 & 72 & 24 & 340 & 16 & 5 & 41 & 371 & 77 & 105 & 195 & 56 & 146 & 3 & 34 & 13 & 13\\\\\n",
       "\t4 & chinese & 129 & 0 & 46 & 36 & 26 & 9 & 92 & 26 & 100 & 32 & 34 & 14 & 330 & 109 & 167 & 261 & 529 & 56 & 391 & 15 & 460 & 171 & 368 & 363 & 112 & 2 & 251 & 187 & 0 & 5 & 379 & 36 & 113 & 2 & 33 & 12 & 1330 & 1 & 147 & 588 & 604 & 0 & 1 & 63 & 4 & 217 & 47 & 245 & 65 & 497 & 44 & 44 & 91 & 9 & 9 & 355 & 50 & 1005 & 2 & 12 & 54 & 6 & 2 & 157 & 61 & 16 & 23 & 364 & 21 & 8 & 1 & 8 & 9 & 395 & 697 & 37 & 0 & 12 & 25 & 56 & 16 & 1 & 45 & 22 & 112 & 89 & 237 & 2 & 375 & 54 & 1048 & 95 & 1 & 1687 & 1483 & 7 & 52 & 29 & 1 & 987 & 788 & 73 & 30 & 6 & 326 & 257 & 109 & 11 & 3 & 0 & 20 & 222 & 0 & 9 & 131 & 187 & 11 & 256 & 16 & 42 & 155 & 29 & 106 & 43 & 91 & 298 & 79 & 304 & 1 & 1 & 12 & 47 & 62 & 1 & 74 & 325 & 14 & 27 & 33 & 0 & 1 & 357 & 39 & 320 & 10 & 3005 & 151 & 1300 & 192 & 2 & 352 & 14 & 4 & 17 & 227 & 7 & 246 & 473 & 0 & 202 & 1733 & 177 & 16 & 35 & 557 & 43 & 464 & 33 & 5 & 758 & 106 & 66 & 1249 & 1 & 131 & 141 & 1 & 0 & 3 & 1 & 1237 & 3450 & 30 & 608 & 69 & 38 & 325 & 15 & 1488 & 73 & 1 & 7 & 197 & 204 & 30 & 73 & 251 & 329 & 137 & 5 & 53 & 457 & 14 & 16 & 2244 & 24 & 36 & 52 & 15 & 171 & 6 & 952 & 131 & 50 & 229 & 1419 & 84 & 9 & 25 & 1 & 39 & 87 & 10 & 249 & 177 & 111 & 12 & 0 & 23 & 6 & 48 & 8 & 22 & 724 & 870 & 34 & 1129 & 10 & 24 & 6 & 867 & 28 & 693 & 39 & 33 & 83 & 2 & 21 & 33 & 32\\\\\n",
       "\t5 & filipino & 33 & 1 & 2 & 17 & 24 & 3 & 5 & 4 & 30 & 3 & 2 & 122 & 70 & 10 & 97 & 70 & 208 & 6 & 37 & 21 & 40 & 9 & 64 & 90 & 88 & 0 & 67 & 27 & 0 & 1 & 134 & 8 & 36 & 15 & 35 & 2 & 247 & 1 & 36 & 63 & 18 & 0 & 3 & 2 & 4 & 35 & 25 & 18 & 8 & 94 & 5 & 149 & 5 & 42 & 4 & 122 & 5 & 80 & 0 & 1 & 57 & 13 & 0 & 21 & 5 & 8 & 5 & 12 & 7 & 1 & 0 & 1 & 1 & 37 & 181 & 27 & 0 & 5 & 30 & 3 & 1 & 0 & 14 & 7 & 6 & 108 & 24 & 2 & 99 & 2 & 77 & 22 & 0 & 504 & 110 & 3 & 25 & 14 & 0 & 169 & 269 & 6 & 7 & 4 & 10 & 13 & 20 & 14 & 2 & 0 & 12 & 58 & 0 & 4 & 24 & 21 & 2 & 29 & 28 & 5 & 140 & 3 & 61 & 1 & 4 & 12 & 28 & 18 & 0 & 0 & 12 & 23 & 6 & 0 & 191 & 44 & 1 & 0 & 1 & 0 & 1 & 21 & 6 & 48 & 1 & 476 & 57 & 466 & 10 & 5 & 33 & 11 & 2 & 11 & 30 & 6 & 32 & 18 & 0 & 6 & 511 & 90 & 3 & 4 & 212 & 65 & 90 & 13 & 26 & 72 & 1 & 15 & 128 & 0 & 3 & 11 & 0 & 3 & 0 & 1 & 483 & 511 & 14 & 18 & 15 & 15 & 17 & 1 & 30 & 20 & 1 & 2 & 4 & 10 & 19 & 19 & 74 & 24 & 12 & 5 & 4 & 21 & 2 & 4 & 290 & 3 & 27 & 4 & 0 & 32 & 6 & 57 & 9 & 7 & 31 & 319 & 41 & 28 & 3 & 1 & 29 & 31 & 6 & 1 & 13 & 122 & 2 & 1 & 1 & 5 & 7 & 5 & 37 & 108 & 172 & 9 & 348 & 4 & 1 & 1 & 156 & 25 & 17 & 9 & 17 & 35 & 0 & 21 & 3 & 6\\\\\n",
       "\t6 & french & 594 & 38 & 176 & 16 & 127 & 3 & 42 & 145 & 129 & 35 & 159 & 303 & 246 & 0 & 172 & 112 & 725 & 52 & 80 & 265 & 109 & 13 & 305 & 113 & 1162 & 15 & 20 & 28 & 93 & 10 & 255 & 61 & 162 & 24 & 554 & 71 & 536 & 14 & 8 & 11 & 3 & 14 & 1 & 110 & 237 & 439 & 33 & 14 & 106 & 538 & 38 & 23 & 58 & 17 & 91 & 231 & 21 & 137 & 10 & 28 & 699 & 81 & 13 & 26 & 9 & 18 & 13 & 48 & 60 & 190 & 19 & 44 & 12 & 724 & 1194 & 42 & 0 & 256 & 292 & 171 & 101 & 7 & 150 & 100 & 17 & 41 & 24 & 127 & 803 & 90 & 1457 & 93 & 0 & 777 & 44 & 45 & 124 & 287 & 5 & 229 & 866 & 69 & 75 & 247 & 1 & 72 & 42 & 98 & 40 & 7 & 1 & 459 & 54 & 5 & 2 & 159 & 34 & 863 & 283 & 5 & 420 & 139 & 527 & 59 & 59 & 93 & 39 & 76 & 77 & 0 & 47 & 21 & 17 & 0 & 484 & 62 & 55 & 1 & 26 & 6 & 11 & 234 & 255 & 12 & 140 & 1026 & 945 & 754 & 237 & 48 & 9 & 38 & 115 & 491 & 98 & 11 & 29 & 8 & 23 & 92 & 1215 & 111 & 22 & 75 & 75 & 299 & 296 & 65 & 24 & 428 & 61 & 83 & 34 & 15 & 61 & 18 & 111 & 50 & 39 & 0 & 1644 & 96 & 31 & 18 & 211 & 21 & 84 & 2 & 4 & 322 & 7 & 31 & 76 & 22 & 24 & 52 & 48 & 56 & 143 & 32 & 18 & 121 & 22 & 56 & 7 & 4 & 38 & 203 & 189 & 3 & 30 & 93 & 61 & 21 & 122 & 1156 & 32 & 25 & 60 & 0 & 0 & 42 & 534 & 33 & 5 & 427 & 1 & 1 & 22 & 2 & 597 & 62 & 403 & 169 & 327 & 45 & 661 & 12 & 25 & 248 & 830 & 198 & 663 & 20 & 76 & 94 & 23 & 347 & 101 & 90\\\\\n",
       "\t7 & greek & 100 & 32 & 29 & 15 & 5 & 6 & 34 & 3 & 69 & 26 & 76 & 38 & 67 & 0 & 55 & 121 & 398 & 8 & 69 & 124 & 101 & 3 & 70 & 14 & 167 & 3 & 2 & 12 & 30 & 2 & 32 & 29 & 32 & 7 & 578 & 55 & 229 & 32 & 5 & 14 & 0 & 9 & 0 & 14 & 8 & 272 & 6 & 10 & 125 & 323 & 24 & 3 & 5 & 1 & 9 & 106 & 16 & 11 & 0 & 22 & 54 & 40 & 255 & 45 & 264 & 49 & 3 & 2 & 70 & 17 & 174 & 55 & 25 & 517 & 206 & 64 & 0 & 229 & 32 & 46 & 21 & 448 & 21 & 32 & 1 & 0 & 44 & 66 & 136 & 35 & 891 & 43 & 0 & 630 & 7 & 7 & 17 & 113 & 216 & 164 & 650 & 35 & 2 & 7 & 0 & 72 & 16 & 0 & 16 & 2 & 2 & 446 & 154 & 1 & 1 & 88 & 136 & 149 & 91 & 20 & 142 & 8 & 644 & 12 & 82 & 14 & 6 & 24 & 38 & 0 & 16 & 7 & 12 & 0 & 89 & 82 & 168 & 0 & 13 & 1 & 13 & 26 & 27 & 3 & 48 & 825 & 916 & 563 & 46 & 403 & 0 & 32 & 49 & 258 & 39 & 41 & 12 & 1 & 8 & 28 & 865 & 6 & 151 & 52 & 21 & 94 & 99 & 186 & 12 & 301 & 6 & 12 & 64 & 11 & 29 & 2 & 63 & 2 & 3 & 0 & 747 & 62 & 3 & 21 & 39 & 65 & 35 & 1 & 12 & 29 & 2 & 6 & 6 & 0 & 16 & 14 & 40 & 66 & 58 & 8 & 17 & 24 & 4 & 24 & 6 & 6 & 110 & 93 & 27 & 4 & 7 & 10 & 20 & 32 & 24 & 146 & 16 & 2 & 4 & 0 & 0 & 11 & 71 & 6 & 0 & 496 & 5 & 0 & 14 & 5 & 62 & 1 & 35 & 55 & 172 & 16 & 185 & 19 & 32 & 3 & 175 & 56 & 199 & 3 & 15 & 45 & 280 & 28 & 70 & 49\\\\\n",
       "\t8 & indian & 150 & 24 & 124 & 8 & 45 & 5 & 71 & 0 & 110 & 6 & 15 & 231 & 119 & 1 & 58 & 150 & 688 & 43 & 253 & 80 & 257 & 19 & 192 & 220 & 429 & 21 & 37 & 161 & 0 & 588 & 213 & 374 & 34 & 4 & 62 & 13 & 814 & 197 & 376 & 1544 & 2 & 3 & 2 & 7 & 5 & 763 & 28 & 1044 & 545 & 904 & 49 & 632 & 19 & 17 & 5 & 209 & 1155 & 90 & 1 & 22 & 286 & 27 & 3 & 137 & 97 & 1563 & 862 & 14 & 157 & 7 & 6 & 16 & 3 & 228 & 133 & 62 & 0 & 53 & 19 & 115 & 151 & 5 & 69 & 79 & 35 & 27 & 137 & 8 & 531 & 70 & 1665 & 170 & 864 & 1635 & 1475 & 52 & 19 & 95 & 141 & 931 & 2792 & 54 & 0 & 108 & 0 & 63 & 79 & 29 & 5 & 1 & 127 & 599 & 0 & 10 & 24 & 257 & 111 & 119 & 136 & 3 & 962 & 6 & 588 & 31 & 12 & 79 & 272 & 50 & 88 & 998 & 13 & 34 & 24 & 0 & 636 & 154 & 223 & 0 & 24 & 1 & 4 & 43 & 526 & 8 & 88 & 2031 & 424 & 1844 & 23 & 3 & 2 & 243 & 4 & 47 & 619 & 3 & 288 & 99 & 2 & 187 & 1648 & 162 & 414 & 74 & 26 & 480 & 1523 & 170 & 117 & 885 & 20 & 14 & 593 & 5 & 54 & 149 & 1 & 115 & 0 & 2 & 2402 & 141 & 1 & 36 & 116 & 16 & 1739 & 136 & 50 & 56 & 0 & 3 & 4 & 0 & 30 & 29 & 75 & 225 & 58 & 34 & 47 & 66 & 3 & 28 & 35 & 0 & 183 & 79 & 38 & 14 & 29 & 44 & 17 & 260 & 106 & 533 & 95 & 23 & 7 & 0 & 20 & 132 & 20 & 17 & 41 & 1259 & 8 & 509 & 11 & 732 & 89 & 45 & 18 & 744 & 153 & 60 & 967 & 49 & 85 & 23 & 247 & 187 & 55 & 2 & 73 & 221 & 576 & 3 & 22 & 43\\\\\n",
       "\t9 & irish & 219 & 20 & 13 & 15 & 31 & 2 & 11 & 63 & 255 & 6 & 3 & 51 & 10 & 0 & 120 & 11 & 142 & 14 & 4 & 37 & 5 & 0 & 61 & 75 & 334 & 96 & 88 & 4 & 4 & 5 & 121 & 11 & 42 & 39 & 83 & 12 & 66 & 0 & 2 & 3 & 0 & 11 & 1 & 20 & 37 & 86 & 16 & 5 & 43 & 59 & 9 & 4 & 9 & 7 & 16 & 69 & 2 & 43 & 0 & 6 & 174 & 11 & 2 & 7 & 5 & 3 & 0 & 19 & 11 & 14 & 7 & 6 & 3 & 110 & 215 & 0 & 0 & 12 & 43 & 35 & 7 & 0 & 8 & 15 & 6 & 1 & 4 & 9 & 341 & 23 & 181 & 22 & 0 & 107 & 26 & 14 & 41 & 44 & 2 & 71 & 222 & 5 & 15 & 46 & 0 & 12 & 8 & 10 & 5 & 0 & 3 & 50 & 0 & 0 & 2 & 33 & 41 & 107 & 31 & 3 & 54 & 41 & 61 & 8 & 3 & 21 & 7 & 10 & 44 & 0 & 8 & 17 & 0 & 0 & 186 & 8 & 10 & 0 & 20 & 0 & 3 & 26 & 44 & 0 & 39 & 138 & 65 & 238 & 45 & 4 & 3 & 16 & 7 & 83 & 23 & 1 & 23 & 5 & 7 & 16 & 284 & 14 & 11 & 3 & 25 & 274 & 165 & 3 & 50 & 71 & 10 & 13 & 2 & 0 & 11 & 2 & 19 & 0 & 11 & 1 & 462 & 42 & 31 & 14 & 17 & 9 & 42 & 0 & 4 & 11 & 12 & 2 & 8 & 2 & 13 & 23 & 0 & 3 & 16 & 12 & 122 & 18 & 1 & 32 & 7 & 0 & 7 & 62 & 13 & 7 & 1 & 13 & 7 & 6 & 49 & 306 & 12 & 8 & 11 & 0 & 0 & 0 & 69 & 5 & 0 & 44 & 1 & 1 & 4 & 0 & 87 & 10 & 51 & 71 & 41 & 7 & 121 & 4 & 55 & 36 & 101 & 69 & 30 & 23 & 6 & 27 & 12 & 18 & 20 & 4\\\\\n",
       "\t10 & italian & 919 & 12 & 266 & 168 & 34 & 25 & 237 & 231 & 305 & 372 & 2005 & 274 & 482 & 1 & 583 & 725 & 2473 & 82 & 406 & 880 & 550 & 192 & 1009 & 139 & 1660 & 48 & 48 & 45 & 311 & 9 & 434 & 65 & 428 & 116 & 5843 & 224 & 1835 & 41 & 41 & 107 & 3 & 28 & 6 & 128 & 210 & 1576 & 25 & 52 & 126 & 1965 & 156 & 23 & 64 & 51 & 95 & 819 & 20 & 218 & 78 & 117 & 994 & 399 & 133 & 878 & 40 & 37 & 9 & 37 & 513 & 107 & 24 & 223 & 130 & 2913 & 1793 & 228 & 0 & 1362 & 325 & 380 & 253 & 108 & 216 & 264 & 16 & 31 & 535 & 597 & 1361 & 247 & 4992 & 339 & 1 & 4173 & 42 & 70 & 114 & 2077 & 9 & 756 & 2981 & 237 & 97 & 377 & 0 & 131 & 249 & 56 & 1127 & 38 & 20 & 970 & 156 & 31 & 14 & 666 & 36 & 1291 & 729 & 163 & 1223 & 106 & 1401 & 177 & 74 & 82 & 50 & 326 & 189 & 1 & 63 & 77 & 92 & 2 & 737 & 388 & 169 & 0 & 97 & 22 & 1249 & 843 & 147 & 314 & 237 & 5183 & 4987 & 2717 & 289 & 987 & 9 & 89 & 2456 & 1746 & 450 & 1015 & 207 & 5 & 43 & 267 & 5668 & 38 & 34 & 380 & 231 & 286 & 723 & 351 & 85 & 2053 & 123 & 171 & 367 & 665 & 234 & 6 & 508 & 37 & 277 & 13 & 4897 & 1341 & 588 & 63 & 340 & 558 & 179 & 7 & 17 & 316 & 38 & 128 & 78 & 66 & 25 & 591 & 248 & 347 & 439 & 64 & 72 & 415 & 80 & 112 & 23 & 357 & 574 & 647 & 163 & 5 & 146 & 86 & 97 & 30 & 270 & 1378 & 199 & 16 & 35 & 0 & 2 & 65 & 524 & 63 & 17 & 3346 & 17 & 6 & 186 & 2 & 580 & 93 & 326 & 541 & 774 & 183 & 1483 & 63 & 173 & 279 & 1710 & 451 & 1521 & 60 & 248 & 366 & 34 & 226 & 272 & 340\\\\\n",
       "\t11 & jamaican & 42 & 195 & 3 & 6 & 8 & 6 & 7 & 10 & 49 & 1 & 8 & 21 & 60 & 0 & 59 & 74 & 222 & 6 & 35 & 35 & 41 & 1 & 29 & 109 & 92 & 2 & 10 & 10 & 1 & 2 & 49 & 50 & 16 & 2 & 17 & 4 & 178 & 0 & 59 & 57 & 5 & 4 & 3 & 7 & 4 & 70 & 17 & 34 & 127 & 145 & 6 & 140 & 32 & 10 & 1 & 46 & 20 & 24 & 13 & 5 & 24 & 31 & 0 & 16 & 1 & 30 & 76 & 44 & 16 & 6 & 2 & 7 & 1 & 163 & 65 & 1 & 0 & 6 & 23 & 11 & 0 & 0 & 11 & 11 & 0 & 13 & 34 & 3 & 111 & 5 & 226 & 6 & 2 & 313 & 124 & 1 & 12 & 32 & 1 & 109 & 542 & 13 & 5 & 2 & 0 & 8 & 63 & 10 & 1 & 0 & 30 & 136 & 0 & 1 & 33 & 33 & 1 & 24 & 9 & 9 & 59 & 1 & 23 & 1 & 6 & 26 & 153 & 17 & 2 & 3 & 9 & 17 & 4 & 0 & 146 & 31 & 2 & 0 & 9 & 0 & 4 & 5 & 17 & 3 & 120 & 270 & 73 & 374 & 47 & 7 & 1 & 28 & 2 & 15 & 16 & 1 & 19 & 8 & 8 & 14 & 616 & 10 & 11 & 5 & 32 & 53 & 202 & 26 & 11 & 123 & 2 & 3 & 67 & 0 & 9 & 16 & 6 & 0 & 8 & 2 & 419 & 173 & 0 & 113 & 21 & 52 & 19 & 5 & 2 & 9 & 0 & 1 & 4 & 0 & 1 & 7 & 20 & 32 & 15 & 6 & 14 & 17 & 2 & 9 & 81 & 0 & 14 & 16 & 11 & 8 & 6 & 11 & 9 & 7 & 38 & 204 & 27 & 12 & 8 & 0 & 0 & 17 & 296 & 3 & 0 & 85 & 5 & 15 & 3 & 13 & 19 & 16 & 37 & 121 & 90 & 5 & 210 & 5 & 2 & 3 & 91 & 10 & 24 & 10 & 12 & 35 & 2 & 2 & 7 & 5\\\\\n",
       "\t12 & japanese & 69 & 1 & 13 & 5 & 18 & 60 & 38 & 8 & 55 & 4 & 10 & 24 & 51 & 22 & 71 & 51 & 154 & 19 & 91 & 14 & 65 & 17 & 67 & 115 & 105 & 0 & 105 & 63 & 0 & 38 & 204 & 26 & 19 & 1 & 35 & 9 & 276 & 3 & 28 & 182 & 17 & 1 & 1 & 37 & 8 & 74 & 8 & 93 & 23 & 116 & 9 & 43 & 32 & 8 & 4 & 72 & 65 & 114 & 0 & 7 & 61 & 4 & 0 & 22 & 116 & 65 & 36 & 54 & 6 & 13 & 5 & 6 & 7 & 128 & 334 & 39 & 0 & 22 & 23 & 12 & 12 & 0 & 103 & 21 & 68 & 27 & 120 & 6 & 203 & 15 & 404 & 44 & 46 & 358 & 461 & 3 & 48 & 19 & 1 & 330 & 261 & 8 & 4 & 15 & 9 & 79 & 40 & 14 & 2 & 1 & 5 & 143 & 0 & 5 & 37 & 81 & 0 & 124 & 18 & 2 & 111 & 19 & 140 & 3 & 11 & 48 & 64 & 79 & 1 & 51 & 51 & 28 & 19 & 0 & 102 & 49 & 5 & 402 & 15 & 0 & 4 & 147 & 48 & 136 & 3 & 901 & 81 & 472 & 36 & 0 & 13 & 9 & 8 & 11 & 184 & 3 & 75 & 32 & 4 & 58 & 390 & 10 & 16 & 8 & 112 & 96 & 236 & 14 & 4 & 179 & 34 & 13 & 554 & 1 & 17 & 51 & 0 & 7 & 0 & 0 & 581 & 940 & 2 & 236 & 75 & 24 & 346 & 2 & 520 & 30 & 1 & 8 & 15 & 138 & 9 & 28 & 71 & 65 & 41 & 22 & 20 & 114 & 12 & 3 & 779 & 2 & 73 & 27 & 4 & 42 & 10 & 111 & 50 & 10 & 64 & 650 & 41 & 10 & 10 & 0 & 7 & 65 & 3 & 137 & 127 & 78 & 1 & 29 & 3 & 34 & 21 & 0 & 20 & 292 & 337 & 11 & 479 & 20 & 16 & 2 & 300 & 25 & 65 & 22 & 7 & 48 & 4 & 49 & 14 & 18\\\\\n",
       "\t13 & korean & 31 & 0 & 1 & 0 & 27 & 2 & 22 & 8 & 10 & 4 & 2 & 3 & 64 & 32 & 166 & 31 & 192 & 4 & 26 & 3 & 10 & 4 & 37 & 168 & 15 & 2 & 110 & 46 & 0 & 0 & 180 & 16 & 5 & 6 & 13 & 0 & 109 & 1 & 77 & 162 & 20 & 2 & 0 & 21 & 0 & 45 & 12 & 17 & 6 & 181 & 16 & 8 & 20 & 0 & 0 & 73 & 6 & 66 & 0 & 3 & 6 & 1 & 0 & 47 & 81 & 1 & 2 & 69 & 1 & 3 & 0 & 1 & 3 & 45 & 170 & 4 & 0 & 4 & 6 & 4 & 0 & 0 & 8 & 2 & 35 & 59 & 149 & 4 & 88 & 4 & 186 & 3 & 0 & 639 & 320 & 4 & 24 & 1 & 1 & 348 & 191 & 1 & 3 & 3 & 4 & 80 & 40 & 7 & 0 & 1 & 16 & 63 & 0 & 1 & 13 & 74 & 6 & 52 & 10 & 11 & 39 & 9 & 20 & 2 & 46 & 36 & 11 & 50 & 0 & 0 & 9 & 17 & 10 & 0 & 6 & 112 & 0 & 59 & 7 & 0 & 1 & 89 & 13 & 56 & 0 & 815 & 42 & 625 & 8 & 0 & 20 & 11 & 0 & 3 & 96 & 2 & 9 & 19 & 0 & 21 & 578 & 2 & 4 & 2 & 90 & 52 & 64 & 8 & 2 & 237 & 22 & 91 & 414 & 0 & 24 & 16 & 1 & 0 & 0 & 1 & 382 & 676 & 4 & 197 & 36 & 10 & 368 & 4 & 897 & 7 & 1 & 1 & 12 & 77 & 9 & 20 & 31 & 11 & 24 & 3 & 9 & 84 & 0 & 3 & 544 & 1 & 65 & 15 & 0 & 46 & 4 & 47 & 85 & 4 & 33 & 488 & 44 & 0 & 46 & 0 & 5 & 13 & 1 & 191 & 67 & 7 & 10 & 0 & 5 & 0 & 4 & 0 & 4 & 135 & 216 & 4 & 278 & 0 & 5 & 0 & 148 & 5 & 84 & 1 & 2 & 40 & 1 & 10 & 3 & 54\\\\\n",
       "\t14 & mexican & 330 & 66 & 83 & 86 & 92 & 1103 & 43 & 126 & 256 & 24 & 63 & 188 & 1710 & 0 & 839 & 928 & 2245 & 40 & 608 & 109 & 853 & 16 & 858 & 263 & 577 & 30 & 192 & 267 & 27 & 2 & 169 & 425 & 111 & 1135 & 2976 & 91 & 2473 & 16 & 1490 & 3039 & 0 & 444 & 505 & 24 & 129 & 2077 & 144 & 2794 & 319 & 1168 & 169 & 54 & 37 & 138 & 20 & 719 & 218 & 2152 & 42 & 49 & 1910 & 46 & 39 & 155 & 68 & 2061 & 6 & 47 & 806 & 19 & 16 & 48 & 124 & 835 & 654 & 4 & 400 & 206 & 104 & 292 & 6 & 42 & 115 & 144 & 18 & 24 & 134 & 26 & 1425 & 121 & 2684 & 356 & 0 & 3222 & 32 & 20 & 77 & 164 & 66 & 1946 & 3495 & 180 & 27 & 71 & 1 & 120 & 346 & 82 & 41 & 854 & 1175 & 1628 & 4 & 420 & 37 & 617 & 11 & 399 & 113 & 212 & 579 & 3 & 237 & 75 & 509 & 118 & 2286 & 195 & 111 & 0 & 166 & 124 & 58 & 500 & 449 & 274 & 50 & 1 & 343 & 530 & 95 & 151 & 50 & 24 & 15 & 2978 & 1846 & 4436 & 283 & 906 & 4 & 363 & 51 & 147 & 181 & 79 & 32 & 46 & 27 & 66 & 4689 & 55 & 71 & 190 & 396 & 230 & 2376 & 618 & 73 & 1175 & 189 & 48 & 520 & 16 & 247 & 4 & 16 & 7 & 7 & 1283 & 3920 & 1508 & 96 & 172 & 199 & 670 & 284 & 236 & 60 & 46 & 167 & 123 & 18 & 11 & 119 & 1456 & 178 & 487 & 328 & 168 & 38 & 293 & 206 & 1323 & 61 & 17 & 109 & 361 & 112 & 15 & 65 & 59 & 170 & 70 & 248 & 690 & 226 & 51 & 21 & 637 & 0 & 93 & 68 & 24 & 13 & 2868 & 2535 & 5 & 181 & 10 & 160 & 67 & 150 & 997 & 435 & 56 & 1099 & 256 & 114 & 72 & 1009 & 357 & 160 & 67 & 33 & 446 & 115 & 44 & 69 & 147\\\\\n",
       "\t15 & moroccan & 44 & 44 & 111 & 6 & 7 & 2 & 12 & 0 & 11 & 5 & 9 & 23 & 58 & 0 & 68 & 77 & 278 & 18 & 56 & 20 & 65 & 4 & 180 & 23 & 110 & 0 & 4 & 20 & 8 & 29 & 167 & 142 & 36 & 2 & 24 & 12 & 365 & 132 & 23 & 43 & 0 & 2 & 0 & 2 & 0 & 335 & 4 & 286 & 413 & 299 & 23 & 7 & 1 & 1 & 9 & 49 & 252 & 9 & 3 & 8 & 6 & 7 & 7 & 36 & 8 & 452 & 23 & 1 & 65 & 3 & 6 & 7 & 1 & 182 & 74 & 35 & 0 & 128 & 3 & 40 & 25 & 12 & 27 & 25 & 1 & 6 & 34 & 66 & 90 & 28 & 676 & 9 & 6 & 450 & 287 & 50 & 9 & 46 & 20 & 142 & 1370 & 43 & 0 & 1 & 0 & 117 & 21 & 2 & 6 & 0 & 2 & 259 & 23 & 0 & 2 & 95 & 170 & 63 & 79 & 3 & 96 & 4 & 449 & 29 & 5 & 4 & 20 & 41 & 5 & 6 & 7 & 14 & 2 & 0 & 20 & 34 & 118 & 0 & 8 & 0 & 1 & 6 & 9 & 5 & 32 & 638 & 658 & 496 & 89 & 12 & 1 & 243 & 3 & 242 & 80 & 5 & 15 & 4 & 0 & 41 & 685 & 8 & 17 & 23 & 6 & 78 & 77 & 67 & 97 & 186 & 7 & 17 & 19 & 2 & 18 & 8 & 6 & 126 & 0 & 1 & 601 & 25 & 11 & 5 & 42 & 6 & 140 & 2 & 20 & 30 & 0 & 5 & 10 & 0 & 33 & 1 & 8 & 51 & 32 & 31 & 0 & 59 & 1 & 4 & 4 & 2 & 12 & 43 & 29 & 2 & 44 & 0 & 13 & 72 & 103 & 130 & 104 & 0 & 3 & 0 & 0 & 52 & 22 & 14 & 1 & 308 & 0 & 112 & 8 & 73 & 47 & 1 & 6 & 118 & 41 & 20 & 253 & 17 & 12 & 2 & 66 & 28 & 51 & 0 & 20 & 66 & 34 & 8 & 32 & 40\\\\\n",
       "\t16 & russian & 123 & 8 & 26 & 4 & 31 & 2 & 0 & 11 & 74 & 4 & 6 & 39 & 18 & 0 & 72 & 18 & 106 & 14 & 7 & 41 & 13 & 0 & 42 & 15 & 213 & 12 & 70 & 9 & 10 & 6 & 80 & 9 & 40 & 4 & 68 & 9 & 43 & 1 & 2 & 9 & 0 & 1 & 0 & 14 & 17 & 59 & 14 & 9 & 34 & 69 & 11 & 1 & 19 & 10 & 13 & 15 & 6 & 16 & 1 & 4 & 183 & 24 & 0 & 1 & 20 & 5 & 0 & 10 & 11 & 9 & 111 & 4 & 2 & 91 & 280 & 2 & 0 & 6 & 44 & 4 & 6 & 2 & 17 & 13 & 0 & 4 & 6 & 11 & 237 & 0 & 160 & 10 & 0 & 88 & 9 & 16 & 19 & 10 & 2 & 51 & 159 & 6 & 13 & 18 & 0 & 22 & 17 & 4 & 2 & 0 & 2 & 64 & 1 & 0 & 9 & 23 & 3 & 121 & 23 & 8 & 39 & 9 & 101 & 0 & 2 & 8 & 0 & 4 & 7 & 2 & 31 & 11 & 2 & 0 & 98 & 10 & 4 & 0 & 5 & 0 & 4 & 47 & 17 & 8 & 8 & 173 & 66 & 209 & 14 & 2 & 0 & 20 & 2 & 59 & 19 & 1 & 20 & 0 & 0 & 14 & 213 & 12 & 15 & 4 & 26 & 128 & 82 & 8 & 40 & 57 & 5 & 16 & 20 & 3 & 4 & 9 & 3 & 4 & 1 & 0 & 345 & 32 & 10 & 9 & 14 & 7 & 43 & 0 & 0 & 9 & 1 & 0 & 2 & 2 & 2 & 9 & 4 & 7 & 15 & 15 & 24 & 8 & 7 & 127 & 3 & 0 & 4 & 6 & 2 & 0 & 0 & 14 & 9 & 8 & 20 & 251 & 18 & 3 & 6 & 0 & 0 & 1 & 11 & 5 & 2 & 82 & 1 & 1 & 6 & 0 & 94 & 7 & 63 & 91 & 74 & 22 & 167 & 2 & 8 & 18 & 95 & 28 & 38 & 6 & 57 & 9 & 13 & 36 & 10 & 2\\\\\n",
       "\t17 & southern_us & 1223 & 59 & 70 & 61 & 232 & 13 & 48 & 431 & 1240 & 31 & 82 & 192 & 157 & 0 & 86 & 303 & 866 & 65 & 130 & 258 & 145 & 13 & 390 & 627 & 2136 & 712 & 64 & 115 & 8 & 9 & 151 & 331 & 350 & 403 & 872 & 48 & 922 & 2 & 68 & 219 & 0 & 30 & 23 & 92 & 112 & 751 & 228 & 58 & 399 & 396 & 73 & 121 & 67 & 115 & 65 & 311 & 16 & 829 & 318 & 58 & 965 & 168 & 16 & 154 & 25 & 75 & 28 & 169 & 137 & 101 & 44 & 21 & 65 & 501 & 1688 & 3 & 1 & 98 & 591 & 119 & 13 & 4 & 73 & 98 & 77 & 7 & 166 & 47 & 1847 & 71 & 1026 & 168 & 2 & 987 & 116 & 41 & 289 & 231 & 14 & 789 & 1532 & 128 & 223 & 255 & 2 & 176 & 332 & 152 & 52 & 46 & 110 & 594 & 3 & 117 & 102 & 357 & 3 & 934 & 114 & 14 & 216 & 18 & 586 & 29 & 55 & 309 & 169 & 80 & 77 & 2 & 182 & 56 & 33 & 5 & 1117 & 106 & 109 & 0 & 164 & 19 & 13 & 77 & 336 & 5 & 221 & 1276 & 429 & 1365 & 205 & 55 & 28 & 270 & 136 & 286 & 36 & 18 & 210 & 175 & 429 & 37 & 2709 & 27 & 30 & 29 & 221 & 314 & 1414 & 95 & 48 & 559 & 57 & 134 & 154 & 1 & 87 & 7 & 54 & 1 & 79 & 18 & 3088 & 798 & 153 & 71 & 106 & 365 & 112 & 4 & 14 & 64 & 212 & 51 & 25 & 10 & 35 & 221 & 217 & 98 & 226 & 155 & 473 & 101 & 89 & 137 & 35 & 2 & 21 & 206 & 75 & 1 & 36 & 159 & 64 & 28 & 118 & 2319 & 316 & 125 & 271 & 2 & 0 & 49 & 259 & 29 & 0 & 469 & 9 & 9 & 49 & 12 & 660 & 69 & 778 & 658 & 459 & 31 & 895 & 27 & 47 & 243 & 837 & 328 & 161 & 182 & 40 & 377 & 37 & 146 & 102 & 14\\\\\n",
       "\t18 & spanish & 53 & 4 & 94 & 5 & 24 & 23 & 16 & 24 & 33 & 24 & 35 & 93 & 64 & 0 & 36 & 265 & 251 & 19 & 33 & 117 & 42 & 2 & 133 & 22 & 92 & 3 & 9 & 7 & 20 & 1 & 45 & 40 & 24 & 7 & 88 & 14 & 262 & 23 & 48 & 68 & 0 & 5 & 6 & 16 & 6 & 224 & 8 & 86 & 68 & 381 & 16 & 4 & 5 & 16 & 5 & 66 & 11 & 41 & 4 & 8 & 68 & 35 & 5 & 56 & 78 & 70 & 5 & 8 & 74 & 12 & 5 & 6 & 1 & 275 & 274 & 13 & 0 & 255 & 35 & 40 & 17 & 4 & 32 & 23 & 1 & 16 & 44 & 82 & 98 & 32 & 487 & 46 & 0 & 561 & 11 & 13 & 10 & 39 & 1 & 258 & 361 & 21 & 53 & 18 & 0 & 25 & 60 & 26 & 18 & 1 & 31 & 243 & 8 & 9 & 6 & 122 & 7 & 251 & 130 & 4 & 104 & 11 & 214 & 25 & 13 & 8 & 67 & 37 & 17 & 0 & 15 & 12 & 32 & 1 & 107 & 62 & 25 & 0 & 11 & 1 & 2 & 24 & 16 & 2 & 16 & 734 & 729 & 516 & 141 & 67 & 4 & 196 & 12 & 245 & 42 & 6 & 72 & 0 & 3 & 30 & 910 & 8 & 10 & 52 & 44 & 166 & 53 & 55 & 28 & 407 & 10 & 14 & 135 & 2 & 58 & 0 & 23 & 126 & 5 & 13 & 677 & 77 & 89 & 24 & 52 & 9 & 18 & 33 & 1 & 29 & 1 & 5 & 127 & 3 & 5 & 2 & 121 & 31 & 55 & 75 & 18 & 56 & 2 & 19 & 4 & 5 & 19 & 49 & 27 & 0 & 3 & 17 & 6 & 34 & 58 & 188 & 60 & 16 & 7 & 0 & 0 & 31 & 73 & 4 & 0 & 436 & 8 & 9 & 18 & 3 & 44 & 3 & 47 & 81 & 214 & 8 & 206 & 29 & 4 & 17 & 247 & 34 & 270 & 14 & 12 & 64 & 11 & 41 & 33 & 19\\\\\n",
       "\t19 & thai & 17 & 1 & 8 & 7 & 18 & 14 & 56 & 1 & 8 & 4 & 334 & 14 & 136 & 152 & 54 & 255 & 127 & 13 & 231 & 16 & 313 & 40 & 204 & 339 & 228 & 1 & 91 & 77 & 0 & 21 & 225 & 53 & 21 & 0 & 12 & 34 & 762 & 8 & 285 & 556 & 35 & 1 & 0 & 23 & 0 & 355 & 15 & 730 & 23 & 357 & 11 & 743 & 14 & 9 & 0 & 178 & 189 & 110 & 0 & 6 & 44 & 9 & 1 & 106 & 125 & 88 & 480 & 86 & 12 & 2 & 0 & 2 & 11 & 149 & 209 & 36 & 0 & 9 & 6 & 53 & 4 & 1 & 55 & 7 & 89 & 832 & 137 & 1 & 54 & 24 & 1325 & 28 & 2 & 957 & 521 & 10 & 30 & 33 & 2 & 575 & 389 & 55 & 0 & 8 & 17 & 80 & 66 & 10 & 2 & 1 & 84 & 590 & 0 & 4 & 30 & 84 & 3 & 147 & 18 & 11 & 527 & 7 & 151 & 21 & 77 & 184 & 1114 & 106 & 8 & 3 & 10 & 14 & 68 & 0 & 632 & 122 & 171 & 7 & 11 & 1 & 4 & 135 & 14 & 258 & 10 & 1057 & 125 & 699 & 38 & 4 & 46 & 19 & 2 & 8 & 570 & 5 & 89 & 625 & 0 & 111 & 962 & 38 & 5 & 11 & 83 & 49 & 175 & 84 & 6 & 831 & 58 & 17 & 653 & 0 & 183 & 82 & 0 & 2 & 1 & 2 & 585 & 1636 & 0 & 138 & 47 & 19 & 136 & 50 & 247 & 244 & 0 & 7 & 8 & 40 & 4 & 55 & 293 & 220 & 100 & 2 & 3 & 169 & 4 & 0 & 506 & 9 & 37 & 46 & 33 & 59 & 32 & 75 & 73 & 48 & 119 & 865 & 128 & 12 & 22 & 0 & 487 & 62 & 4 & 54 & 106 & 148 & 15 & 39 & 18 & 41 & 55 & 121 & 3 & 414 & 233 & 9 & 381 & 114 & 12 & 3 & 202 & 13 & 49 & 4 & 2 & 68 & 7 & 1 & 55 & 46\\\\\n",
       "\t20 & vietnamese & 12 & 4 & 4 & 4 & 11 & 14 & 20 & 2 & 9 & 1 & 162 & 9 & 84 & 127 & 110 & 40 & 190 & 5 & 66 & 10 & 69 & 11 & 78 & 99 & 63 & 0 & 61 & 85 & 0 & 16 & 254 & 10 & 15 & 0 & 2 & 2 & 238 & 0 & 170 & 251 & 36 & 1 & 1 & 9 & 0 & 160 & 9 & 336 & 54 & 207 & 9 & 62 & 13 & 18 & 1 & 71 & 83 & 60 & 0 & 13 & 7 & 2 & 0 & 34 & 158 & 9 & 30 & 35 & 8 & 1 & 6 & 1 & 5 & 69 & 94 & 6 & 0 & 5 & 4 & 14 & 10 & 0 & 19 & 7 & 38 & 490 & 41 & 1 & 59 & 5 & 563 & 7 & 0 & 542 & 228 & 4 & 24 & 16 & 1 & 210 & 271 & 7 & 5 & 2 & 63 & 33 & 58 & 10 & 3 & 1 & 61 & 257 & 0 & 2 & 6 & 92 & 2 & 47 & 22 & 3 & 284 & 4 & 60 & 6 & 120 & 39 & 373 & 32 & 2 & 0 & 33 & 32 & 45 & 0 & 64 & 86 & 180 & 6 & 8 & 1 & 0 & 48 & 3 & 177 & 2 & 528 & 43 & 413 & 14 & 0 & 28 & 6 & 1 & 5 & 65 & 0 & 17 & 170 & 0 & 34 & 499 & 25 & 2 & 6 & 166 & 15 & 77 & 45 & 0 & 176 & 20 & 12 & 477 & 0 & 79 & 27 & 0 & 0 & 0 & 0 & 400 & 941 & 11 & 100 & 20 & 11 & 68 & 37 & 147 & 158 & 0 & 3 & 2 & 27 & 16 & 44 & 135 & 50 & 44 & 0 & 5 & 65 & 5 & 1 & 236 & 4 & 8 & 19 & 31 & 63 & 8 & 66 & 65 & 63 & 51 & 546 & 26 & 20 & 4 & 0 & 134 & 18 & 0 & 37 & 55 & 58 & 3 & 13 & 6 & 19 & 33 & 5 & 4 & 171 & 195 & 24 & 298 & 43 & 8 & 0 & 141 & 11 & 33 & 1 & 2 & 69 & 2 & 7 & 5 & 3\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "        Group.1 all-purpos allspic almond and appl avocado babi bacon bake\n",
       "1     brazilian         18       1     24   2   10      10    3    30   19\n",
       "2       british        238      27     44   3   30       0    2    25  217\n",
       "3  cajun_creole        291      18     12  39   14       4   17    62   64\n",
       "4       chinese        129       0     46  36   26       9   92    26  100\n",
       "5      filipino         33       1      2  17   24       3    5     4   30\n",
       "6        french        594      38    176  16  127       3   42   145  129\n",
       "7         greek        100      32     29  15    5       6   34     3   69\n",
       "8        indian        150      24    124   8   45       5   71     0  110\n",
       "9         irish        219      20     13  15   31       2   11    63  255\n",
       "10      italian        919      12    266 168   34      25  237   231  305\n",
       "11     jamaican         42     195      3   6    8       6    7    10   49\n",
       "12     japanese         69       1     13   5   18      60   38     8   55\n",
       "13       korean         31       0      1   0   27       2   22     8   10\n",
       "14      mexican        330      66     83  86   92    1103   43   126  256\n",
       "15     moroccan         44      44    111   6    7       2   12     0   11\n",
       "16      russian        123       8     26   4   31       2    0    11   74\n",
       "17  southern_us       1223      59     70  61  232      13   48   431 1240\n",
       "18      spanish         53       4     94   5   24      23   16    24   33\n",
       "19         thai         17       1      8   7   18      14   56     1    8\n",
       "20   vietnamese         12       4      4   4   11      14   20     2    9\n",
       "   balsam basil bay bean beansprout beef bell black boil boneless bread breast\n",
       "1       0     2  54   71          0   31   80   133    4       16    13     17\n",
       "2      17     5  42   15          0  158    4   134   18        3    81      4\n",
       "3       8    94 360  164          0   79  696   496   23      152   133    176\n",
       "4      32    34  14  330        109  167  261   529   56      391    15    460\n",
       "5       3     2 122   70         10   97   70   208    6       37    21     40\n",
       "6      35   159 303  246          0  172  112   725   52       80   265    109\n",
       "7      26    76  38   67          0   55  121   398    8       69   124    101\n",
       "8       6    15 231  119          1   58  150   688   43      253    80    257\n",
       "9       6     3  51   10          0  120   11   142   14        4    37      5\n",
       "10    372  2005 274  482          1  583  725  2473   82      406   880    550\n",
       "11      1     8  21   60          0   59   74   222    6       35    35     41\n",
       "12      4    10  24   51         22   71   51   154   19       91    14     65\n",
       "13      4     2   3   64         32  166   31   192    4       26     3     10\n",
       "14     24    63 188 1710          0  839  928  2245   40      608   109    853\n",
       "15      5     9  23   58          0   68   77   278   18       56    20     65\n",
       "16      4     6  39   18          0   72   18   106   14        7    41     13\n",
       "17     31    82 192  157          0   86  303   866   65      130   258    145\n",
       "18     24    35  93   64          0   36  265   251   19       33   117     42\n",
       "19      4   334  14  136        152   54  255   127   13      231    16    313\n",
       "20      1   162   9   84        127  110   40   190    5       66    10     69\n",
       "   broccoli broth brown butter buttermilk cabbag canola caper cardamom carrot\n",
       "1         0    33    21     83          2      0     13     1        0     26\n",
       "2         1    36   109    436         26     10     18     4        2     61\n",
       "3         3   348   111    498         33     15     84    30        1     53\n",
       "4       171   368   363    112          2    251    187     0        5    379\n",
       "5         9    64    90     88          0     67     27     0        1    134\n",
       "6        13   305   113   1162         15     20     28    93       10    255\n",
       "7         3    70    14    167          3      2     12    30        2     32\n",
       "8        19   192   220    429         21     37    161     0      588    213\n",
       "9         0    61    75    334         96     88      4     4        5    121\n",
       "10      192  1009   139   1660         48     48     45   311        9    434\n",
       "11        1    29   109     92          2     10     10     1        2     49\n",
       "12       17    67   115    105          0    105     63     0       38    204\n",
       "13        4    37   168     15          2    110     46     0        0    180\n",
       "14       16   858   263    577         30    192    267    27        2    169\n",
       "15        4   180    23    110          0      4     20     8       29    167\n",
       "16        0    42    15    213         12     70      9    10        6     80\n",
       "17       13   390   627   2136        712     64    115     8        9    151\n",
       "18        2   133    22     92          3      9      7    20        1     45\n",
       "19       40   204   339    228          1     91     77     0       21    225\n",
       "20       11    78    99     63          0     61     85     0       16    254\n",
       "   cayenn celeri cheddar chees cherri chicken chickpea chile chili chines chip\n",
       "1      23      7       5    56      5      76        0    23    41      0    4\n",
       "2      32     26      60   108     16      30        0     1     8      0    4\n",
       "3     399    619      20   174      9     741        3    28   142      0    5\n",
       "4      36    113       2    33     12    1330        1   147   588    604    0\n",
       "5       8     36      15    35      2     247        1    36    63     18    0\n",
       "6      61    162      24   554     71     536       14     8    11      3   14\n",
       "7      29     32       7   578     55     229       32     5    14      0    9\n",
       "8     374     34       4    62     13     814      197   376  1544      2    3\n",
       "9      11     42      39    83     12      66        0     2     3      0   11\n",
       "10     65    428     116  5843    224    1835       41    41   107      3   28\n",
       "11     50     16       2    17      4     178        0    59    57      5    4\n",
       "12     26     19       1    35      9     276        3    28   182     17    1\n",
       "13     16      5       6    13      0     109        1    77   162     20    2\n",
       "14    425    111    1135  2976     91    2473       16  1490  3039      0  444\n",
       "15    142     36       2    24     12     365      132    23    43      0    2\n",
       "16      9     40       4    68      9      43        1     2     9      0    1\n",
       "17    331    350     403   872     48     922        2    68   219      0   30\n",
       "18     40     24       7    88     14     262       23    48    68      0    5\n",
       "19     53     21       0    12     34     762        8   285   556     35    1\n",
       "20     10     15       0     2      2     238        0   170   251     36    1\n",
       "   chipotl chive chocol chop cider cilantro cinnamon clove coars coconut cold\n",
       "1        5     2     35   76     2       88       14    92     7     142   12\n",
       "2        0    18     32   66     9        5       68    57    17       6   22\n",
       "3        3    22     11  544    19       26       46   329    29       9   10\n",
       "4        1    63      4  217    47      245       65   497    44      44   91\n",
       "5        3     2      4   35    25       18        8    94     5     149    5\n",
       "6        1   110    237  439    33       14      106   538    38      23   58\n",
       "7        0    14      8  272     6       10      125   323    24       3    5\n",
       "8        2     7      5  763    28     1044      545   904    49     632   19\n",
       "9        1    20     37   86    16        5       43    59     9       4    9\n",
       "10       6   128    210 1576    25       52      126  1965   156      23   64\n",
       "11       3     7      4   70    17       34      127   145     6     140   32\n",
       "12       1    37      8   74     8       93       23   116     9      43   32\n",
       "13       0    21      0   45    12       17        6   181    16       8   20\n",
       "14     505    24    129 2077   144     2794      319  1168   169      54   37\n",
       "15       0     2      0  335     4      286      413   299    23       7    1\n",
       "16       0    14     17   59    14        9       34    69    11       1   19\n",
       "17      23    92    112  751   228       58      399   396    73     121   67\n",
       "18       6    16      6  224     8       86       68   381    16       4    5\n",
       "19       0    23      0  355    15      730       23   357    11     743   14\n",
       "20       1     9      0  160     9      336       54   207     9      62   13\n",
       "   condens confection cook coriand corn cornmeal crack cream crumb crumbl crush\n",
       "1       68          1   28      22   34        4     3    35     9      0    32\n",
       "2       11         22   23       7   57       11    13   268    37      1     7\n",
       "3       17         26  299      10  145       23    24   206    49      5    89\n",
       "4        9          9  355      50 1005        2    12    54     6      2   157\n",
       "5       42          4  122       5   80        0     1    57    13      0    21\n",
       "6       17         91  231      21  137       10    28   699    81     13    26\n",
       "7        1          9  106      16   11        0    22    54    40    255    45\n",
       "8       17          5  209    1155   90        1    22   286    27      3   137\n",
       "9        7         16   69       2   43        0     6   174    11      2     7\n",
       "10      51         95  819      20  218       78   117   994   399    133   878\n",
       "11      10          1   46      20   24       13     5    24    31      0    16\n",
       "12       8          4   72      65  114        0     7    61     4      0    22\n",
       "13       0          0   73       6   66        0     3     6     1      0    47\n",
       "14     138         20  719     218 2152       42    49  1910    46     39   155\n",
       "15       1          9   49     252    9        3     8     6     7      7    36\n",
       "16      10         13   15       6   16        1     4   183    24      0     1\n",
       "17     115         65  311      16  829      318    58   965   168     16   154\n",
       "18      16          5   66      11   41        4     8    68    35      5    56\n",
       "19       9          0  178     189  110        0     6    44     9      1   106\n",
       "20      18          1   71      83   60        0    13     7     2      0    34\n",
       "   cucumb cumin curri dark dice dijon dill dough dress  dri  egg eggplant\n",
       "1       2    29     2    5   21     4    0     1     0   62  105        0\n",
       "2       4     8    19   44    3    22    5    12     0  157  436        0\n",
       "3       0    57     1   14  277    33   13     5    18  646  237        4\n",
       "4      61    16    23  364   21     8    1     8     9  395  697       37\n",
       "5       5     8     5   12    7     1    0     1     1   37  181       27\n",
       "6       9    18    13   48   60   190   19    44    12  724 1194       42\n",
       "7     264    49     3    2   70    17  174    55    25  517  206       64\n",
       "8      97  1563   862   14  157     7    6    16     3  228  133       62\n",
       "9       5     3     0   19   11    14    7     6     3  110  215        0\n",
       "10     40    37     9   37  513   107   24   223   130 2913 1793      228\n",
       "11      1    30    76   44   16     6    2     7     1  163   65        1\n",
       "12    116    65    36   54    6    13    5     6     7  128  334       39\n",
       "13     81     1     2   69    1     3    0     1     3   45  170        4\n",
       "14     68  2061     6   47  806    19   16    48   124  835  654        4\n",
       "15      8   452    23    1   65     3    6     7     1  182   74       35\n",
       "16     20     5     0   10   11     9  111     4     2   91  280        2\n",
       "17     25    75    28  169  137   101   44    21    65  501 1688        3\n",
       "18     78    70     5    8   74    12    5     6     1  275  274       13\n",
       "19    125    88   480   86   12     2    0     2    11  149  209       36\n",
       "20    158     9    30   35    8     1    6     1     5   69   94        6\n",
       "   enchilada extra-virgin extract fat fennel feta fillet fine firm fish flake\n",
       "1          0           13      18   5      3    0     25    8    0   27    33\n",
       "2          0           19      85  10      3    0     35   12    2   14    14\n",
       "3          0           47      54  51      9    1     75   41    4   12    69\n",
       "4          0           12      25  56     16    1     45   22  112   89   237\n",
       "5          0            5      30   3      1    0     14    7    6  108    24\n",
       "6          0          256     292 171    101    7    150  100   17   41    24\n",
       "7          0          229      32  46     21  448     21   32    1    0    44\n",
       "8          0           53      19 115    151    5     69   79   35   27   137\n",
       "9          0           12      43  35      7    0      8   15    6    1     4\n",
       "10         0         1362     325 380    253  108    216  264   16   31   535\n",
       "11         0            6      23  11      0    0     11   11    0   13    34\n",
       "12         0           22      23  12     12    0    103   21   68   27   120\n",
       "13         0            4       6   4      0    0      8    2   35   59   149\n",
       "14       400          206     104 292      6   42    115  144   18   24   134\n",
       "15         0          128       3  40     25   12     27   25    1    6    34\n",
       "16         0            6      44   4      6    2     17   13    0    4     6\n",
       "17         1           98     591 119     13    4     73   98   77    7   166\n",
       "18         0          255      35  40     17    4     32   23    1   16    44\n",
       "19         0            9       6  53      4    1     55    7   89  832   137\n",
       "20         0            5       4  14     10    0     19    7   38  490    41\n",
       "   flat flour free fresh frozen garam garlic ginger golden granul grate greek\n",
       "1    10    73    5   133     32     1    194     31      1     21    21     0\n",
       "2     6   467   12   180     57     2     94     54     53     37    54     4\n",
       "3    50   450   31   546     52     0   1003      6      6     51    58     0\n",
       "4     2   375   54  1048     95     1   1687   1483      7     52    29     1\n",
       "5     2    99    2    77     22     0    504    110      3     25    14     0\n",
       "6   127   803   90  1457     93     0    777     44     45    124   287     5\n",
       "7    66   136   35   891     43     0    630      7      7     17   113   216\n",
       "8     8   531   70  1665    170   864   1635   1475     52     19    95   141\n",
       "9     9   341   23   181     22     0    107     26     14     41    44     2\n",
       "10  597  1361  247  4992    339     1   4173     42     70    114  2077     9\n",
       "11    3   111    5   226      6     2    313    124      1     12    32     1\n",
       "12    6   203   15   404     44    46    358    461      3     48    19     1\n",
       "13    4    88    4   186      3     0    639    320      4     24     1     1\n",
       "14   26  1425  121  2684    356     0   3222     32     20     77   164    66\n",
       "15   66    90   28   676      9     6    450    287     50      9    46    20\n",
       "16   11   237    0   160     10     0     88      9     16     19    10     2\n",
       "17   47  1847   71  1026    168     2    987    116     41    289   231    14\n",
       "18   82    98   32   487     46     0    561     11     13     10    39     1\n",
       "19    1    54   24  1325     28     2    957    521     10     30    33     2\n",
       "20    1    59    5   563      7     0    542    228      4     24    16     1\n",
       "   green ground halv ham heavi hoisin honey hot ice italian jack jalapeno juic\n",
       "1     85    126    3  17     7      0    12  22  57       5    3       19  104\n",
       "2     26    312    4   7   104      0    16  16  15       2    0        1   65\n",
       "3    913    679   61  94    74      0    14 286  15      45   16       50  196\n",
       "4    987    788   73  30     6    326   257 109  11       3    0       20  222\n",
       "5    169    269    6   7     4     10    13  20  14       2    0       12   58\n",
       "6    229    866   69  75   247      1    72  42  98      40    7        1  459\n",
       "7    164    650   35   2     7      0    72  16   0      16    2        2  446\n",
       "8    931   2792   54   0   108      0    63  79  29       5    1      127  599\n",
       "9     71    222    5  15    46      0    12   8  10       5    0        3   50\n",
       "10   756   2981  237  97   377      0   131 249  56    1127   38       20  970\n",
       "11   109    542   13   5     2      0     8  63  10       1    0       30  136\n",
       "12   330    261    8   4    15      9    79  40  14       2    1        5  143\n",
       "13   348    191    1   3     3      4    80  40   7       0    1       16   63\n",
       "14  1946   3495  180  27    71      1   120 346  82      41  854     1175 1628\n",
       "15   142   1370   43   0     1      0   117  21   2       6    0        2  259\n",
       "16    51    159    6  13    18      0    22  17   4       2    0        2   64\n",
       "17   789   1532  128 223   255      2   176 332 152      52   46      110  594\n",
       "18   258    361   21  53    18      0    25  60  26      18    1       31  243\n",
       "19   575    389   55   0     8     17    80  66  10       2    1       84  590\n",
       "20   210    271    7   5     2     63    33  58  10       3    1       61  257\n",
       "   kalamata kernel ketchup kosher lamb larg leaf lean leav leek lemon less\n",
       "1         0      4       1     22    2   33   33    1   63    2    37    3\n",
       "2         0      1       7     61   14  164   26   20   48   18   125    0\n",
       "3         3     27      23    108    0  223  158   13  297    7   253   24\n",
       "4         0      9     131    187   11  256   16   42  155   29   106   43\n",
       "5         0      4      24     21    2   29   28    5  140    3    61    1\n",
       "6        54      5       2    159   34  863  283    5  420  139   527   59\n",
       "7       154      1       1     88  136  149   91   20  142    8   644   12\n",
       "8         0     10      24    257  111  119  136    3  962    6   588   31\n",
       "9         0      0       2     33   41  107   31    3   54   41    61    8\n",
       "10      156     31      14    666   36 1291  729  163 1223  106  1401  177\n",
       "11        0      1      33     33    1   24    9    9   59    1    23    1\n",
       "12        0      5      37     81    0  124   18    2  111   19   140    3\n",
       "13        0      1      13     74    6   52   10   11   39    9    20    2\n",
       "14        4    420      37    617   11  399  113  212  579    3   237   75\n",
       "15       23      0       2     95  170   63   79    3   96    4   449   29\n",
       "16        1      0       9     23    3  121   23    8   39    9   101    0\n",
       "17        3    117     102    357    3  934  114   14  216   18   586   29\n",
       "18        8      9       6    122    7  251  130    4  104   11   214   25\n",
       "19        0      4      30     84    3  147   18   11  527    7   151   21\n",
       "20        0      2       6     92    2   47   22    3  284    4    60    6\n",
       "   lettuc light lime low low-fat masala mayonais meat medium mexican milk minc\n",
       "1       1    16  164  10       5      1       10    3     10       0  229   15\n",
       "2       3    40    5   8       8      2        7    8     14       0  287   16\n",
       "3      40    42   23  76      17      0       80   73    109       2  165  121\n",
       "4      91   298   79 304       1      1       12   47     62       1   74  325\n",
       "5       4    12   28  18       0      0       12   23      6       0  191   44\n",
       "6      59    93   39  76      77      0       47   21     17       0  484   62\n",
       "7      82    14    6  24      38      0       16    7     12       0   89   82\n",
       "8      12    79  272  50      88    998       13   34     24       0  636  154\n",
       "9       3    21    7  10      44      0        8   17      0       0  186    8\n",
       "10     74    82   50 326     189      1       63   77     92       2  737  388\n",
       "11      6    26  153  17       2      3        9   17      4       0  146   31\n",
       "12     11    48   64  79       1     51       51   28     19       0  102   49\n",
       "13     46    36   11  50       0      0        9   17     10       0    6  112\n",
       "14    509   118 2286 195     111      0      166  124     58     500  449  274\n",
       "15      5     4   20  41       5      6        7   14      2       0   20   34\n",
       "16      2     8    0   4       7      2       31   11      2       0   98   10\n",
       "17     55   309  169  80      77      2      182   56     33       5 1117  106\n",
       "18     13     8   67  37      17      0       15   12     32       1  107   62\n",
       "19     77   184 1114 106       8      3       10   14     68       0  632  122\n",
       "20    120    39  373  32       2      0       33   32     45       0   64   86\n",
       "   mint mirin mix monterey mozzarella mushroom mustard noodl nutmeg  oil oliv\n",
       "1     7     0   6        2          5        2       5     0      5  247  145\n",
       "2    14     0  32        0          0       58      76     0     70  201   77\n",
       "3     3     0  46        8         11       83     133     6     26  821  402\n",
       "4    14    27  33        0          1      357      39   320     10 3005  151\n",
       "5     1     0   1        0          1       21       6    48      1  476   57\n",
       "6    55     1  26        6         11      234     255    12    140 1026  945\n",
       "7   168     0  13        1         13       26      27     3     48  825  916\n",
       "8   223     0  24        1          4       43     526     8     88 2031  424\n",
       "9    10     0  20        0          3       26      44     0     39  138   65\n",
       "10  169     0  97       22       1249      843     147   314    237 5183 4987\n",
       "11    2     0   9        0          4        5      17     3    120  270   73\n",
       "12    5   402  15        0          4      147      48   136      3  901   81\n",
       "13    0    59   7        0          1       89      13    56      0  815   42\n",
       "14   50     1 343      530         95      151      50    24     15 2978 1846\n",
       "15  118     0   8        0          1        6       9     5     32  638  658\n",
       "16    4     0   5        0          4       47      17     8      8  173   66\n",
       "17  109     0 164       19         13       77     336     5    221 1276  429\n",
       "18   25     0  11        1          2       24      16     2     16  734  729\n",
       "19  171     7  11        1          4      135      14   258     10 1057  125\n",
       "20  180     6   8        1          0       48       3   177      2  528   43\n",
       "   onion orang oregano oyster paprika parmesan parsley past pasta pea peanut\n",
       "1    226    50      14      1      19       24      55   21     1  16     10\n",
       "2    215    55       8      0      22       11      52   29     0  30      2\n",
       "3   1314    36     225     30     262       58     369   99    27  32     31\n",
       "4   1300   192       2    352      14        4      17  227     7 246    473\n",
       "5    466    10       5     33      11        2      11   30     6  32     18\n",
       "6    754   237      48      9      38      115     491   98    11  29      8\n",
       "7    563    46     403      0      32       49     258   39    41  12      1\n",
       "8   1844    23       3      2     243        4      47  619     3 288     99\n",
       "9    238    45       4      3      16        7      83   23     1  23      5\n",
       "10  2717   289     987      9      89     2456    1746  450  1015 207      5\n",
       "11   374    47       7      1      28        2      15   16     1  19      8\n",
       "12   472    36       0     13       9        8      11  184     3  75     32\n",
       "13   625     8       0     20      11        0       3   96     2   9     19\n",
       "14  4436   283     906      4     363       51     147  181    79  32     46\n",
       "15   496    89      12      1     243        3     242   80     5  15      4\n",
       "16   209    14       2      0      20        2      59   19     1  20      0\n",
       "17  1365   205      55     28     270      136     286   36    18 210    175\n",
       "18   516   141      67      4     196       12     245   42     6  72      0\n",
       "19   699    38       4     46      19        2       8  570     5  89    625\n",
       "20   413    14       0     28       6        1       5   65     0  17    170\n",
       "   pecan peel pepper peppercorn plain plum pork potato powder purpl raisin  red\n",
       "1      3    6    310          1     3    9   35     26     63     8      6   86\n",
       "2     12   35    276         10    39    4   46    144    213    11     62   50\n",
       "3     40   39   2326         17     6   26   61     58    450    38      9  555\n",
       "4      0  202   1733        177    16   35  557     43    464    33      5  758\n",
       "5      0    6    511         90     3    4  212     65     90    13     26   72\n",
       "6     23   92   1215        111    22   75   75    299    296    65     24  428\n",
       "7      8   28    865          6   151   52   21     94     99   186     12  301\n",
       "8      2  187   1648        162   414   74   26    480   1523   170    117  885\n",
       "9      7   16    284         14    11    3   25    274    165     3     50   71\n",
       "10    43  267   5668         38    34  380  231    286    723   351     85 2053\n",
       "11     8   14    616         10    11    5   32     53    202    26     11  123\n",
       "12     4   58    390         10    16    8  112     96    236    14      4  179\n",
       "13     0   21    578          2     4    2   90     52     64     8      2  237\n",
       "14    27   66   4689         55    71  190  396    230   2376   618     73 1175\n",
       "15     0   41    685          8    17   23    6     78     77    67     97  186\n",
       "16     0   14    213         12    15    4   26    128     82     8     40   57\n",
       "17   429   37   2709         27    30   29  221    314   1414    95     48  559\n",
       "18     3   30    910          8    10   52   44    166     53    55     28  407\n",
       "19     0  111    962         38     5   11   83     49    175    84      6  831\n",
       "20     0   34    499         25     2    6  166     15     77    45      0  176\n",
       "   reduc rib rice ricotta roast root rosemari saffron sage salsa salt sauc\n",
       "1      2  18   63       0    11    4        2       3    1     7  246   35\n",
       "2      2  16   23       0    18    2       23       2   21     0  516   83\n",
       "3     36 183  537       1    33    0       27       2   16     2  993  665\n",
       "4    106  66 1249       1   131  141        1       0    3     1 1237 3450\n",
       "5      1  15  128       0     3   11        0       3    0     1  483  511\n",
       "6     61  83   34      15    61   18      111      50   39     0 1644   96\n",
       "7      6  12   64      11    29    2       63       2    3     0  747   62\n",
       "8     20  14  593       5    54  149        1     115    0     2 2402  141\n",
       "9     10  13    2       0    11    2       19       0   11     1  462   42\n",
       "10   123 171  367     665   234    6      508      37  277    13 4897 1341\n",
       "11     2   3   67       0     9   16        6       0    8     2  419  173\n",
       "12    34  13  554       1    17   51        0       7    0     0  581  940\n",
       "13    22  91  414       0    24   16        1       0    0     1  382  676\n",
       "14   189  48  520      16   247    4       16       7    7  1283 3920 1508\n",
       "15     7  17   19       2    18    8        6     126    0     1  601   25\n",
       "16     5  16   20       3     4    9        3       4    1     0  345   32\n",
       "17    57 134  154       1    87    7       54       1   79    18 3088  798\n",
       "18    10  14  135       2    58    0       23     126    5    13  677   77\n",
       "19    58  17  653       0   183   82        0       2    1     2  585 1636\n",
       "20    20  12  477       0    79   27        0       0    0     0  400  941\n",
       "   sausag scallion sea season seed serrano sesam shallot sharp shell sherri\n",
       "1      30        8  19      7   26       7     2       5     1     2      3\n",
       "2      42        4  26     11   23       1     1      19    20     6     23\n",
       "3     463       97  36    631   34       4     1      23     7    15      8\n",
       "4      30      608  69     38  325      15  1488      73     1     7    197\n",
       "5      14       18  15     15   17       1    30      20     1     2      4\n",
       "6      31       18 211     21   84       2     4     322     7    31     76\n",
       "7       3       21  39     65   35       1    12      29     2     6      6\n",
       "8       1       36 116     16 1739     136    50      56     0     3      4\n",
       "9      31       14  17      9   42       0     4      11    12     2      8\n",
       "10    588       63 340    558  179       7    17     316    38   128     78\n",
       "11      0      113  21     52   19       5     2       9     0     1      4\n",
       "12      2      236  75     24  346       2   520      30     1     8     15\n",
       "13      4      197  36     10  368       4   897       7     1     1     12\n",
       "14     96      172 199    670  284     236    60      46   167   123     18\n",
       "15     11        5  42      6  140       2    20      30     0     5     10\n",
       "16     10        9  14      7   43       0     0       9     1     0      2\n",
       "17    153       71 106    365  112       4    14      64   212    51     25\n",
       "18     89       24  52      9   18      33     1      29     1     5    127\n",
       "19      0      138  47     19  136      50   247     244     0     7      8\n",
       "20     11      100  20     11   68      37   147     158     0     3      2\n",
       "   shiitak shoulder shred shrimp skinless slice smoke soda sodium soup sour\n",
       "1        0        9    15     58       10    22    16    8     16    2    6\n",
       "2        1        6    12      3        4    23    17   85      9    3   23\n",
       "3        1        6    25    473      125   100   198   26    107   35   25\n",
       "4      204       30    73    251      329   137     5   53    457   14   16\n",
       "5       10       19    19     74       24    12     5    4     21    2    4\n",
       "6       22       24    52     48       56   143    32   18    121   22   56\n",
       "7        0       16    14     40       66    58     8   17     24    4   24\n",
       "8        0       30    29     75      225    58    34   47     66    3   28\n",
       "9        2       13    23      0        3    16    12  122     18    1   32\n",
       "10      66       25   591    248      347   439    64   72    415   80  112\n",
       "11       0        1     7     20       32    15     6   14     17    2    9\n",
       "12     138        9    28     71       65    41    22   20    114   12    3\n",
       "13      77        9    20     31       11    24     3    9     84    0    3\n",
       "14      11      119  1456    178      487   328   168   38    293  206 1323\n",
       "15       0       33     1      8       51    32    31    0     59    1    4\n",
       "16       2        2     9      4        7    15    15   24      8    7  127\n",
       "17      10       35   221    217       98   226   155  473    101   89  137\n",
       "18       3        5     2    121       31    55    75   18     56    2   19\n",
       "19      40        4    55    293      220   100     2    3    169    4    0\n",
       "20      27       16    44    135       50    44     0    5     65    5    1\n",
       "    soy spaghetti spinach spray sprig spring squash starch steak stick stock\n",
       "1     3         0       6     3     1      4      2     22    12     4    29\n",
       "2     5         0       5    12    10      4      2     32    26     9    49\n",
       "3    14         5      18    75    26      2      8     28    16     6   148\n",
       "4  2244        24      36    52    15    171      6    952   131    50   229\n",
       "5   290         3      27     4     0     32      6     57     9     7    31\n",
       "6     7         4      38   203   189      3     30     93    61    21   122\n",
       "7     6         6     110    93    27      4      7     10    20    32    24\n",
       "8    35         0     183    79    38     14     29     44    17   260   106\n",
       "9     7         0       7    62    13      7      1     13     7     6    49\n",
       "10   23       357     574   647   163      5    146     86    97    30   270\n",
       "11   81         0      14    16    11      8      6     11     9     7    38\n",
       "12  779         2      73    27     4     42     10    111    50    10    64\n",
       "13  544         1      65    15     0     46      4     47    85     4    33\n",
       "14   61        17     109   361   112     15     65     59   170    70   248\n",
       "15    4         2      12    43    29      2     44      0    13    72   103\n",
       "16    3         0       4     6     2      0      0     14     9     8    20\n",
       "17   35         2      21   206    75      1     36    159    64    28   118\n",
       "18    4         5      19    49    27      0      3     17     6    34    58\n",
       "19  506         9      37    46    33     59     32     75    73    48   119\n",
       "20  236         4       8    19    31     63      8     66    65    63    51\n",
       "   sugar sweet sweeten syrup taco thai thigh thyme toast tofu tomato tortilla\n",
       "1    150    18      61    16    0    1     6    13     5    1    133        1\n",
       "2    454    21      11    41    0    1     0    62     7    0     53        0\n",
       "3    310    76       7    18    1    0    55   428     8    1    673        6\n",
       "4   1419    84       9    25    1   39    87    10   249  177    111       12\n",
       "5    319    41      28     3    1   29    31     6     1   13    122        2\n",
       "6   1156    32      25    60    0    0    42   534    33    5    427        1\n",
       "7    146    16       2     4    0    0    11    71     6    0    496        5\n",
       "8    533    95      23     7    0   20   132    20    17   41   1259        8\n",
       "9    306    12       8    11    0    0     0    69     5    0     44        1\n",
       "10  1378   199      16    35    0    2    65   524    63   17   3346       17\n",
       "11   204    27      12     8    0    0    17   296     3    0     85        5\n",
       "12   650    41      10    10    0    7    65     3   137  127     78        1\n",
       "13   488    44       0    46    0    5    13     1   191   67      7       10\n",
       "14   690   226      51    21  637    0    93    68    24   13   2868     2535\n",
       "15   130   104       0     3    0    0    52    22    14    1    308        0\n",
       "16   251    18       3     6    0    0     1    11     5    2     82        1\n",
       "17  2319   316     125   271    2    0    49   259    29    0    469        9\n",
       "18   188    60      16     7    0    0    31    73     4    0    436        8\n",
       "19   865   128      12    22    0  487    62     4    54  106    148       15\n",
       "20   546    26      20     4    0  134    18     0    37   55     58        3\n",
       "   tumer turkey turmer unsalt unsweeten vanilla veget vinegar warm water wedg\n",
       "1      3      5      4     26        29      28    46      26    2   112   15\n",
       "2      9      2      3    193         2     119    82      71   15   178    8\n",
       "3      1     62      1    119         3      74   313      72   24   340   16\n",
       "4      0     23      6     48         8      22   724     870   34  1129   10\n",
       "5      1      1      5      7         5      37   108     172    9   348    4\n",
       "6      1     22      2    597        62     403   169     327   45   661   12\n",
       "7      0     14      5     62         1      35    55     172   16   185   19\n",
       "8    509     11    732     89        45      18   744     153   60   967   49\n",
       "9      1      4      0     87        10      51    71      41    7   121    4\n",
       "10     6    186      2    580        93     326   541     774  183  1483   63\n",
       "11    15      3     13     19        16      37   121      90    5   210    5\n",
       "12    29      3     34     21         0      20   292     337   11   479   20\n",
       "13     0      5      0      4         0       4   135     216    4   278    0\n",
       "14     5    181     10    160        67     150   997     435   56  1099  256\n",
       "15   112      8     73     47         1       6   118      41   20   253   17\n",
       "16     1      6      0     94         7      63    91      74   22   167    2\n",
       "17     9     49     12    660        69     778   658     459   31   895   27\n",
       "18     9     18      3     44         3      47    81     214    8   206   29\n",
       "19    39     18     41     55       121       3   414     233    9   381  114\n",
       "20    13      6     19     33         5       4   171     195   24   298   43\n",
       "   wheat whip white whole wine worcestershir yeast yellow yogurt yolk zest\n",
       "1      3    4    91    15   30             2     6     34      3   22    8\n",
       "2     15   82   168    77   66            53    41     26      8   67   21\n",
       "3      5   41   371    77  105           195    56    146      3   34   13\n",
       "4     24    6   867    28  693            39    33     83      2   21   33\n",
       "5      1    1   156    25   17             9    17     35      0   21    3\n",
       "6     25  248   830   198  663            20    76     94     23  347  101\n",
       "7     32    3   175    56  199             3    15     45    280   28   70\n",
       "8     85   23   247   187   55             2    73    221    576    3   22\n",
       "9     55   36   101    69   30            23     6     27     12   18   20\n",
       "10   173  279  1710   451 1521            60   248    366     34  226  272\n",
       "11     2    3    91    10   24            10    12     35      2    2    7\n",
       "12    16    2   300    25   65            22     7     48      4   49   14\n",
       "13     5    0   148     5   84             1     2     40      1   10    3\n",
       "14   114   72  1009   357  160            67    33    446    115   44   69\n",
       "15    12    2    66    28   51             0    20     66     34    8   32\n",
       "16     8   18    95    28   38             6    57      9     13   36   10\n",
       "17    47  243   837   328  161           182    40    377     37  146  102\n",
       "18     4   17   247    34  270            14    12     64     11   41   33\n",
       "19    12    3   202    13   49             4     2     68      7    1   55\n",
       "20     8    0   141    11   33             1     2     69      2    7    5\n",
       "   zucchini\n",
       "1         3\n",
       "2         3\n",
       "3        13\n",
       "4        32\n",
       "5         6\n",
       "6        90\n",
       "7        49\n",
       "8        43\n",
       "9         4\n",
       "10      340\n",
       "11        5\n",
       "12       18\n",
       "13       54\n",
       "14      147\n",
       "15       40\n",
       "16        2\n",
       "17       14\n",
       "18       19\n",
       "19       46\n",
       "20        3"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "aggregate(ingredientsDTM_train[,c(1:250)], list(ingredientsDTM_train[,251]), sum)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th></th><th scope=col>Group.1</th><th scope=col>all-purpos</th><th scope=col>allspic</th><th scope=col>almond</th><th scope=col>and</th><th scope=col>appl</th><th scope=col>avocado</th><th scope=col>babi</th><th scope=col>bacon</th><th scope=col>bake</th><th scope=col>balsam</th><th scope=col>basil</th><th scope=col>bay</th><th scope=col>bean</th><th scope=col>beansprout</th><th scope=col>beef</th><th scope=col>bell</th><th scope=col>black</th><th scope=col>boil</th><th scope=col>boneless</th><th scope=col>bread</th><th scope=col>breast</th><th scope=col>broccoli</th><th scope=col>broth</th><th scope=col>brown</th><th scope=col>butter</th><th scope=col>buttermilk</th><th scope=col>cabbag</th><th scope=col>canola</th><th scope=col>caper</th><th scope=col>cardamom</th><th scope=col>carrot</th><th scope=col>cayenn</th><th scope=col>celeri</th><th scope=col>cheddar</th><th scope=col>chees</th><th scope=col>cherri</th><th scope=col>chicken</th><th scope=col>chickpea</th><th scope=col>chile</th><th scope=col>chili</th><th scope=col>chines</th><th scope=col>chip</th><th scope=col>chipotl</th><th scope=col>chive</th><th scope=col>chocol</th><th scope=col>chop</th><th scope=col>cider</th><th scope=col>cilantro</th><th scope=col>cinnamon</th><th scope=col>clove</th><th scope=col>coars</th><th scope=col>coconut</th><th scope=col>cold</th><th scope=col>condens</th><th scope=col>confection</th><th scope=col>cook</th><th scope=col>coriand</th><th scope=col>corn</th><th scope=col>cornmeal</th><th scope=col>crack</th><th scope=col>cream</th><th scope=col>crumb</th><th scope=col>crumbl</th><th scope=col>crush</th><th scope=col>cucumb</th><th scope=col>cumin</th><th scope=col>curri</th><th scope=col>dark</th><th scope=col>dice</th><th scope=col>dijon</th><th scope=col>dill</th><th scope=col>dough</th><th scope=col>dress</th><th scope=col>dri</th><th scope=col>egg</th><th scope=col>eggplant</th><th scope=col>enchilada</th><th scope=col>extra-virgin</th><th scope=col>extract</th><th scope=col>fat</th><th scope=col>fennel</th><th scope=col>feta</th><th scope=col>fillet</th><th scope=col>fine</th><th scope=col>firm</th><th scope=col>fish</th><th scope=col>flake</th><th scope=col>flat</th><th scope=col>flour</th><th scope=col>free</th><th scope=col>fresh</th><th scope=col>frozen</th><th scope=col>garam</th><th scope=col>garlic</th><th scope=col>ginger</th><th scope=col>golden</th><th scope=col>granul</th><th scope=col>grate</th><th scope=col>greek</th><th scope=col>green</th><th scope=col>ground</th><th scope=col>halv</th><th scope=col>ham</th><th scope=col>heavi</th><th scope=col>hoisin</th><th scope=col>honey</th><th scope=col>hot</th><th scope=col>ice</th><th scope=col>italian</th><th scope=col>jack</th><th scope=col>jalapeno</th><th scope=col>juic</th><th scope=col>kalamata</th><th scope=col>kernel</th><th scope=col>ketchup</th><th scope=col>kosher</th><th scope=col>lamb</th><th scope=col>larg</th><th scope=col>leaf</th><th scope=col>lean</th><th scope=col>leav</th><th scope=col>leek</th><th scope=col>lemon</th><th scope=col>less</th><th scope=col>lettuc</th><th scope=col>light</th><th scope=col>lime</th><th scope=col>low</th><th scope=col>low-fat</th><th scope=col>masala</th><th scope=col>mayonais</th><th scope=col>meat</th><th scope=col>medium</th><th scope=col>mexican</th><th scope=col>milk</th><th scope=col>minc</th><th scope=col>mint</th><th scope=col>mirin</th><th scope=col>mix</th><th scope=col>monterey</th><th scope=col>mozzarella</th><th scope=col>mushroom</th><th scope=col>mustard</th><th scope=col>noodl</th><th scope=col>nutmeg</th><th scope=col>oil</th><th scope=col>oliv</th><th scope=col>onion</th><th scope=col>orang</th><th scope=col>oregano</th><th scope=col>oyster</th><th scope=col>paprika</th><th scope=col>parmesan</th><th scope=col>parsley</th><th scope=col>past</th><th scope=col>pasta</th><th scope=col>pea</th><th scope=col>peanut</th><th scope=col>pecan</th><th scope=col>peel</th><th scope=col>pepper</th><th scope=col>peppercorn</th><th scope=col>plain</th><th scope=col>plum</th><th scope=col>pork</th><th scope=col>potato</th><th scope=col>powder</th><th scope=col>purpl</th><th scope=col>raisin</th><th scope=col>red</th><th scope=col>reduc</th><th scope=col>rib</th><th scope=col>rice</th><th scope=col>ricotta</th><th scope=col>roast</th><th scope=col>root</th><th scope=col>rosemari</th><th scope=col>saffron</th><th scope=col>sage</th><th scope=col>salsa</th><th scope=col>salt</th><th scope=col>sauc</th><th scope=col>sausag</th><th scope=col>scallion</th><th scope=col>sea</th><th scope=col>season</th><th scope=col>seed</th><th scope=col>serrano</th><th scope=col>sesam</th><th scope=col>shallot</th><th scope=col>sharp</th><th scope=col>shell</th><th scope=col>sherri</th><th scope=col>shiitak</th><th scope=col>shoulder</th><th scope=col>shred</th><th scope=col>shrimp</th><th scope=col>skinless</th><th scope=col>slice</th><th scope=col>smoke</th><th scope=col>soda</th><th scope=col>sodium</th><th scope=col>soup</th><th scope=col>sour</th><th scope=col>soy</th><th scope=col>spaghetti</th><th scope=col>spinach</th><th scope=col>spray</th><th scope=col>sprig</th><th scope=col>spring</th><th scope=col>squash</th><th scope=col>starch</th><th scope=col>steak</th><th scope=col>stick</th><th scope=col>stock</th><th scope=col>sugar</th><th scope=col>sweet</th><th scope=col>sweeten</th><th scope=col>syrup</th><th scope=col>taco</th><th scope=col>thai</th><th scope=col>thigh</th><th scope=col>thyme</th><th scope=col>toast</th><th scope=col>tofu</th><th scope=col>tomato</th><th scope=col>tortilla</th><th scope=col>tumer</th><th scope=col>turkey</th><th scope=col>turmer</th><th scope=col>unsalt</th><th scope=col>unsweeten</th><th scope=col>vanilla</th><th scope=col>veget</th><th scope=col>vinegar</th><th scope=col>warm</th><th scope=col>water</th><th scope=col>wedg</th><th scope=col>wheat</th><th scope=col>whip</th><th scope=col>white</th><th scope=col>whole</th><th scope=col>wine</th><th scope=col>worcestershir</th><th scope=col>yeast</th><th scope=col>yellow</th><th scope=col>yogurt</th><th scope=col>yolk</th><th scope=col>zest</th><th scope=col>zucchini</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>1</th><td>brazilian</td><td>0.0385439</td><td>0.002141328</td><td>0.05139186</td><td>0.004282655</td><td>0.02141328</td><td>0.02141328</td><td>0.006423983</td><td>0.06423983</td><td>0.04068522</td><td>0</td><td>0.004282655</td><td>0.1156317</td><td>0.1520343</td><td>0</td><td>0.06638116</td><td>0.1713062</td><td>0.2847966</td><td>0.00856531</td><td>0.03426124</td><td>0.02783726</td><td>0.03640257</td><td>0</td><td>0.07066381</td><td>0.04496788</td><td>0.1777302</td><td>0.004282655</td><td>0</td><td>0.02783726</td><td>0.002141328</td><td>0</td><td>0.05567452</td><td>0.04925054</td><td>0.01498929</td><td>0.01070664</td><td>0.1199143</td><td>0.01070664</td><td>0.1627409</td><td>0</td><td>0.04925054</td><td>0.08779443</td><td>0</td><td>0.00856531</td><td>0.01070664</td><td>0.004282655</td><td>0.07494647</td><td>0.1627409</td><td>0.004282655</td><td>0.1884368</td><td>0.02997859</td><td>0.1970021</td><td>0.01498929</td><td>0.3040685</td><td>0.02569593</td><td>0.1456103</td><td>0.002141328</td><td>0.05995717</td><td>0.04710921</td><td>0.07280514</td><td>0.00856531</td><td>0.006423983</td><td>0.07494647</td><td>0.01927195</td><td>0</td><td>0.06852248</td><td>0.004282655</td><td>0.0620985</td><td>0.004282655</td><td>0.01070664</td><td>0.04496788</td><td>0.00856531</td><td>0</td><td>0.002141328</td><td>0</td><td>0.1327623</td><td>0.2248394</td><td>0</td><td>0</td><td>0.02783726</td><td>0.0385439</td><td>0.01070664</td><td>0.006423983</td><td>0</td><td>0.05353319</td><td>0.01713062</td><td>0</td><td>0.05781585</td><td>0.07066381</td><td>0.02141328</td><td>0.1563169</td><td>0.01070664</td><td>0.2847966</td><td>0.06852248</td><td>0.002141328</td><td>0.4154176</td><td>0.06638116</td><td>0.002141328</td><td>0.04496788</td><td>0.04496788</td><td>0</td><td>0.1820128</td><td>0.2698073</td><td>0.006423983</td><td>0.03640257</td><td>0.01498929</td><td>0</td><td>0.02569593</td><td>0.04710921</td><td>0.1220557</td><td>0.01070664</td><td>0.006423983</td><td>0.04068522</td><td>0.2226981</td><td>0</td><td>0.00856531</td><td>0.002141328</td><td>0.04710921</td><td>0.004282655</td><td>0.07066381</td><td>0.07066381</td><td>0.002141328</td><td>0.1349036</td><td>0.004282655</td><td>0.07922912</td><td>0.006423983</td><td>0.002141328</td><td>0.03426124</td><td>0.3511777</td><td>0.02141328</td><td>0.01070664</td><td>0.002141328</td><td>0.02141328</td><td>0.006423983</td><td>0.02141328</td><td>0</td><td>0.490364</td><td>0.03211991</td><td>0.01498929</td><td>0</td><td>0.01284797</td><td>0.004282655</td><td>0.01070664</td><td>0.004282655</td><td>0.01070664</td><td>0</td><td>0.01070664</td><td>0.5289079</td><td>0.3104925</td><td>0.48394</td><td>0.1070664</td><td>0.02997859</td><td>0.002141328</td><td>0.04068522</td><td>0.05139186</td><td>0.117773</td><td>0.04496788</td><td>0.002141328</td><td>0.03426124</td><td>0.02141328</td><td>0.006423983</td><td>0.01284797</td><td>0.6638116</td><td>0.002141328</td><td>0.006423983</td><td>0.01927195</td><td>0.07494647</td><td>0.05567452</td><td>0.1349036</td><td>0.01713062</td><td>0.01284797</td><td>0.1841542</td><td>0.004282655</td><td>0.0385439</td><td>0.1349036</td><td>0</td><td>0.0235546</td><td>0.00856531</td><td>0.004282655</td><td>0.006423983</td><td>0.002141328</td><td>0.01498929</td><td>0.5267666</td><td>0.07494647</td><td>0.06423983</td><td>0.01713062</td><td>0.04068522</td><td>0.01498929</td><td>0.05567452</td><td>0.01498929</td><td>0.004282655</td><td>0.01070664</td><td>0.002141328</td><td>0.004282655</td><td>0.006423983</td><td>0</td><td>0.01927195</td><td>0.03211991</td><td>0.124197</td><td>0.02141328</td><td>0.04710921</td><td>0.03426124</td><td>0.01713062</td><td>0.03426124</td><td>0.004282655</td><td>0.01284797</td><td>0.006423983</td><td>0</td><td>0.01284797</td><td>0.006423983</td><td>0.002141328</td><td>0.00856531</td><td>0.004282655</td><td>0.04710921</td><td>0.02569593</td><td>0.00856531</td><td>0.0620985</td><td>0.3211991</td><td>0.0385439</td><td>0.130621</td><td>0.03426124</td><td>0</td><td>0.002141328</td><td>0.01284797</td><td>0.02783726</td><td>0.01070664</td><td>0.002141328</td><td>0.2847966</td><td>0.002141328</td><td>0.006423983</td><td>0.01070664</td><td>0.00856531</td><td>0.05567452</td><td>0.0620985</td><td>0.05995717</td><td>0.09850107</td><td>0.05567452</td><td>0.004282655</td><td>0.2398287</td><td>0.03211991</td><td>0.006423983</td><td>0.00856531</td><td>0.1948608</td><td>0.03211991</td><td>0.06423983</td><td>0.004282655</td><td>0.01284797</td><td>0.07280514</td><td>0.006423983</td><td>0.04710921</td><td>0.01713062</td><td>0.006423983</td></tr>\n",
       "\t<tr><th scope=row>2</th><td>british</td><td>0.2960199</td><td>0.03358209</td><td>0.05472637</td><td>0.003731343</td><td>0.03731343</td><td>0</td><td>0.002487562</td><td>0.03109453</td><td>0.2699005</td><td>0.02114428</td><td>0.006218905</td><td>0.05223881</td><td>0.01865672</td><td>0</td><td>0.1965174</td><td>0.004975124</td><td>0.1666667</td><td>0.02238806</td><td>0.003731343</td><td>0.1007463</td><td>0.004975124</td><td>0.001243781</td><td>0.04477612</td><td>0.1355721</td><td>0.5422886</td><td>0.03233831</td><td>0.01243781</td><td>0.02238806</td><td>0.004975124</td><td>0.002487562</td><td>0.07587065</td><td>0.039801</td><td>0.03233831</td><td>0.07462687</td><td>0.1343284</td><td>0.0199005</td><td>0.03731343</td><td>0</td><td>0.001243781</td><td>0.009950249</td><td>0</td><td>0.004975124</td><td>0</td><td>0.02238806</td><td>0.039801</td><td>0.08208955</td><td>0.01119403</td><td>0.006218905</td><td>0.08457711</td><td>0.07089552</td><td>0.02114428</td><td>0.007462687</td><td>0.02736318</td><td>0.01368159</td><td>0.02736318</td><td>0.02860697</td><td>0.008706468</td><td>0.07089552</td><td>0.01368159</td><td>0.01616915</td><td>0.3333333</td><td>0.0460199</td><td>0.001243781</td><td>0.008706468</td><td>0.004975124</td><td>0.009950249</td><td>0.02363184</td><td>0.05472637</td><td>0.003731343</td><td>0.02736318</td><td>0.006218905</td><td>0.01492537</td><td>0</td><td>0.1952736</td><td>0.5422886</td><td>0</td><td>0</td><td>0.02363184</td><td>0.1057214</td><td>0.01243781</td><td>0.003731343</td><td>0</td><td>0.04353234</td><td>0.01492537</td><td>0.002487562</td><td>0.01741294</td><td>0.01741294</td><td>0.007462687</td><td>0.5808458</td><td>0.01492537</td><td>0.2238806</td><td>0.07089552</td><td>0.002487562</td><td>0.1169154</td><td>0.06716418</td><td>0.0659204</td><td>0.0460199</td><td>0.06716418</td><td>0.004975124</td><td>0.03233831</td><td>0.3880597</td><td>0.004975124</td><td>0.008706468</td><td>0.1293532</td><td>0</td><td>0.0199005</td><td>0.0199005</td><td>0.01865672</td><td>0.002487562</td><td>0</td><td>0.001243781</td><td>0.08084577</td><td>0</td><td>0.001243781</td><td>0.008706468</td><td>0.07587065</td><td>0.01741294</td><td>0.2039801</td><td>0.03233831</td><td>0.02487562</td><td>0.05970149</td><td>0.02238806</td><td>0.1554726</td><td>0</td><td>0.003731343</td><td>0.04975124</td><td>0.006218905</td><td>0.009950249</td><td>0.009950249</td><td>0.002487562</td><td>0.008706468</td><td>0.009950249</td><td>0.01741294</td><td>0</td><td>0.3569652</td><td>0.0199005</td><td>0.01741294</td><td>0</td><td>0.039801</td><td>0</td><td>0</td><td>0.0721393</td><td>0.09452736</td><td>0</td><td>0.08706468</td><td>0.25</td><td>0.09577114</td><td>0.2674129</td><td>0.06840796</td><td>0.009950249</td><td>0</td><td>0.02736318</td><td>0.01368159</td><td>0.06467662</td><td>0.03606965</td><td>0</td><td>0.03731343</td><td>0.002487562</td><td>0.01492537</td><td>0.04353234</td><td>0.3432836</td><td>0.01243781</td><td>0.04850746</td><td>0.004975124</td><td>0.05721393</td><td>0.1791045</td><td>0.2649254</td><td>0.01368159</td><td>0.07711443</td><td>0.06218905</td><td>0.002487562</td><td>0.0199005</td><td>0.02860697</td><td>0</td><td>0.02238806</td><td>0.002487562</td><td>0.02860697</td><td>0.002487562</td><td>0.0261194</td><td>0</td><td>0.641791</td><td>0.1032338</td><td>0.05223881</td><td>0.004975124</td><td>0.03233831</td><td>0.01368159</td><td>0.02860697</td><td>0.001243781</td><td>0.001243781</td><td>0.02363184</td><td>0.02487562</td><td>0.007462687</td><td>0.02860697</td><td>0.001243781</td><td>0.007462687</td><td>0.01492537</td><td>0.003731343</td><td>0.004975124</td><td>0.02860697</td><td>0.02114428</td><td>0.1057214</td><td>0.01119403</td><td>0.003731343</td><td>0.02860697</td><td>0.006218905</td><td>0</td><td>0.006218905</td><td>0.01492537</td><td>0.01243781</td><td>0.004975124</td><td>0.002487562</td><td>0.039801</td><td>0.03233831</td><td>0.01119403</td><td>0.06094527</td><td>0.5646766</td><td>0.0261194</td><td>0.01368159</td><td>0.05099502</td><td>0</td><td>0.001243781</td><td>0</td><td>0.07711443</td><td>0.008706468</td><td>0</td><td>0.0659204</td><td>0</td><td>0.01119403</td><td>0.002487562</td><td>0.003731343</td><td>0.2400498</td><td>0.002487562</td><td>0.14801</td><td>0.10199</td><td>0.08830846</td><td>0.01865672</td><td>0.221393</td><td>0.009950249</td><td>0.01865672</td><td>0.10199</td><td>0.2089552</td><td>0.09577114</td><td>0.08208955</td><td>0.0659204</td><td>0.05099502</td><td>0.03233831</td><td>0.009950249</td><td>0.08333333</td><td>0.0261194</td><td>0.003731343</td></tr>\n",
       "\t<tr><th scope=row>3</th><td>cajun_creole</td><td>0.1882277</td><td>0.01164295</td><td>0.007761966</td><td>0.02522639</td><td>0.009055627</td><td>0.002587322</td><td>0.01099612</td><td>0.04010349</td><td>0.04139715</td><td>0.005174644</td><td>0.06080207</td><td>0.232859</td><td>0.1060802</td><td>0</td><td>0.05109961</td><td>0.450194</td><td>0.3208279</td><td>0.0148771</td><td>0.09831824</td><td>0.08602846</td><td>0.1138422</td><td>0.001940492</td><td>0.225097</td><td>0.07179819</td><td>0.3221216</td><td>0.02134541</td><td>0.009702458</td><td>0.05433376</td><td>0.01940492</td><td>0.0006468305</td><td>0.03428202</td><td>0.2580854</td><td>0.4003881</td><td>0.01293661</td><td>0.1125485</td><td>0.005821475</td><td>0.4793014</td><td>0.001940492</td><td>0.01811125</td><td>0.09184994</td><td>0</td><td>0.003234153</td><td>0.001940492</td><td>0.01423027</td><td>0.007115136</td><td>0.3518758</td><td>0.01228978</td><td>0.01681759</td><td>0.0297542</td><td>0.2128072</td><td>0.01875809</td><td>0.005821475</td><td>0.006468305</td><td>0.01099612</td><td>0.01681759</td><td>0.1934023</td><td>0.006468305</td><td>0.09379043</td><td>0.0148771</td><td>0.01552393</td><td>0.1332471</td><td>0.0316947</td><td>0.003234153</td><td>0.05756792</td><td>0</td><td>0.03686934</td><td>0.0006468305</td><td>0.009055627</td><td>0.1791721</td><td>0.02134541</td><td>0.008408797</td><td>0.003234153</td><td>0.01164295</td><td>0.4178525</td><td>0.1532988</td><td>0.002587322</td><td>0</td><td>0.03040103</td><td>0.03492885</td><td>0.03298836</td><td>0.005821475</td><td>0.0006468305</td><td>0.04851229</td><td>0.02652005</td><td>0.002587322</td><td>0.007761966</td><td>0.04463131</td><td>0.03234153</td><td>0.2910737</td><td>0.02005175</td><td>0.3531695</td><td>0.03363519</td><td>0</td><td>0.648771</td><td>0.003880983</td><td>0.003880983</td><td>0.03298836</td><td>0.03751617</td><td>0</td><td>0.5905563</td><td>0.4391979</td><td>0.03945666</td><td>0.06080207</td><td>0.04786546</td><td>0</td><td>0.009055627</td><td>0.1849935</td><td>0.009702458</td><td>0.02910737</td><td>0.01034929</td><td>0.03234153</td><td>0.1267788</td><td>0.001940492</td><td>0.01746442</td><td>0.0148771</td><td>0.0698577</td><td>0</td><td>0.1442432</td><td>0.1021992</td><td>0.008408797</td><td>0.1921087</td><td>0.004527814</td><td>0.1636481</td><td>0.01552393</td><td>0.02587322</td><td>0.02716688</td><td>0.0148771</td><td>0.04915912</td><td>0.01099612</td><td>0</td><td>0.05174644</td><td>0.04721863</td><td>0.07050453</td><td>0.001293661</td><td>0.106727</td><td>0.07826649</td><td>0.001940492</td><td>0</td><td>0.0297542</td><td>0.005174644</td><td>0.007115136</td><td>0.05368693</td><td>0.08602846</td><td>0.003880983</td><td>0.01681759</td><td>0.5310479</td><td>0.2600259</td><td>0.8499353</td><td>0.0232859</td><td>0.1455369</td><td>0.01940492</td><td>0.1694696</td><td>0.03751617</td><td>0.2386805</td><td>0.06403622</td><td>0.01746442</td><td>0.02069858</td><td>0.02005175</td><td>0.02587322</td><td>0.02522639</td><td>1.504528</td><td>0.01099612</td><td>0.003880983</td><td>0.01681759</td><td>0.03945666</td><td>0.03751617</td><td>0.2910737</td><td>0.02457956</td><td>0.005821475</td><td>0.3589909</td><td>0.0232859</td><td>0.11837</td><td>0.347348</td><td>0.0006468305</td><td>0.02134541</td><td>0</td><td>0.01746442</td><td>0.001293661</td><td>0.01034929</td><td>0.001293661</td><td>0.6423027</td><td>0.4301423</td><td>0.2994825</td><td>0.06274256</td><td>0.0232859</td><td>0.4081501</td><td>0.02199224</td><td>0.002587322</td><td>0.0006468305</td><td>0.0148771</td><td>0.004527814</td><td>0.009702458</td><td>0.005174644</td><td>0.0006468305</td><td>0.003880983</td><td>0.01617076</td><td>0.3059508</td><td>0.08085382</td><td>0.06468305</td><td>0.1280724</td><td>0.01681759</td><td>0.06921087</td><td>0.02263907</td><td>0.01617076</td><td>0.009055627</td><td>0.003234153</td><td>0.01164295</td><td>0.04851229</td><td>0.01681759</td><td>0.001293661</td><td>0.005174644</td><td>0.01811125</td><td>0.01034929</td><td>0.003880983</td><td>0.09573092</td><td>0.2005175</td><td>0.04915912</td><td>0.004527814</td><td>0.01164295</td><td>0.0006468305</td><td>0</td><td>0.03557568</td><td>0.2768435</td><td>0.005174644</td><td>0.0006468305</td><td>0.4353169</td><td>0.003880983</td><td>0.0006468305</td><td>0.04010349</td><td>0.0006468305</td><td>0.07697283</td><td>0.001940492</td><td>0.04786546</td><td>0.202458</td><td>0.0465718</td><td>0.01552393</td><td>0.2199224</td><td>0.01034929</td><td>0.003234153</td><td>0.02652005</td><td>0.2399741</td><td>0.04980595</td><td>0.06791721</td><td>0.126132</td><td>0.03622251</td><td>0.09443726</td><td>0.001940492</td><td>0.02199224</td><td>0.008408797</td><td>0.008408797</td></tr>\n",
       "\t<tr><th scope=row>4</th><td>chinese</td><td>0.04826038</td><td>0</td><td>0.01720913</td><td>0.01346801</td><td>0.009726899</td><td>0.003367003</td><td>0.03441826</td><td>0.009726899</td><td>0.03741115</td><td>0.01197157</td><td>0.01271979</td><td>0.005237561</td><td>0.1234568</td><td>0.04077815</td><td>0.06247662</td><td>0.0976431</td><td>0.197905</td><td>0.02095024</td><td>0.1462776</td><td>0.005611672</td><td>0.1720913</td><td>0.06397306</td><td>0.137673</td><td>0.1358025</td><td>0.04190049</td><td>0.000748223</td><td>0.09390198</td><td>0.06995885</td><td>0</td><td>0.001870557</td><td>0.1417883</td><td>0.01346801</td><td>0.0422746</td><td>0.000748223</td><td>0.01234568</td><td>0.004489338</td><td>0.4975683</td><td>0.0003741115</td><td>0.05499439</td><td>0.2199776</td><td>0.2259633</td><td>0</td><td>0.0003741115</td><td>0.02356902</td><td>0.001496446</td><td>0.08118219</td><td>0.01758324</td><td>0.09165731</td><td>0.02431725</td><td>0.1859334</td><td>0.01646091</td><td>0.01646091</td><td>0.03404415</td><td>0.003367003</td><td>0.003367003</td><td>0.1328096</td><td>0.01870557</td><td>0.375982</td><td>0.000748223</td><td>0.004489338</td><td>0.02020202</td><td>0.002244669</td><td>0.000748223</td><td>0.0587355</td><td>0.0228208</td><td>0.005985784</td><td>0.008604564</td><td>0.1361766</td><td>0.007856341</td><td>0.002992892</td><td>0.0003741115</td><td>0.002992892</td><td>0.003367003</td><td>0.147774</td><td>0.2607557</td><td>0.01384212</td><td>0</td><td>0.004489338</td><td>0.009352787</td><td>0.02095024</td><td>0.005985784</td><td>0.0003741115</td><td>0.01683502</td><td>0.008230453</td><td>0.04190049</td><td>0.03329592</td><td>0.08866442</td><td>0.000748223</td><td>0.1402918</td><td>0.02020202</td><td>0.3920688</td><td>0.03554059</td><td>0.0003741115</td><td>0.6311261</td><td>0.5548073</td><td>0.00261878</td><td>0.0194538</td><td>0.01084923</td><td>0.0003741115</td><td>0.369248</td><td>0.2947999</td><td>0.02731014</td><td>0.01122334</td><td>0.002244669</td><td>0.1219603</td><td>0.09614665</td><td>0.04077815</td><td>0.004115226</td><td>0.001122334</td><td>0</td><td>0.00748223</td><td>0.08305275</td><td>0</td><td>0.003367003</td><td>0.0490086</td><td>0.06995885</td><td>0.004115226</td><td>0.09577254</td><td>0.005985784</td><td>0.01571268</td><td>0.05798728</td><td>0.01084923</td><td>0.03965582</td><td>0.01608679</td><td>0.03404415</td><td>0.1114852</td><td>0.02955481</td><td>0.1137299</td><td>0.0003741115</td><td>0.0003741115</td><td>0.004489338</td><td>0.01758324</td><td>0.02319491</td><td>0.0003741115</td><td>0.02768425</td><td>0.1215862</td><td>0.005237561</td><td>0.01010101</td><td>0.01234568</td><td>0</td><td>0.0003741115</td><td>0.1335578</td><td>0.01459035</td><td>0.1197157</td><td>0.003741115</td><td>1.124205</td><td>0.05649083</td><td>0.4863449</td><td>0.07182941</td><td>0.000748223</td><td>0.1316872</td><td>0.005237561</td><td>0.001496446</td><td>0.006359895</td><td>0.08492331</td><td>0.00261878</td><td>0.09203143</td><td>0.1769547</td><td>0</td><td>0.07557052</td><td>0.6483352</td><td>0.06621773</td><td>0.005985784</td><td>0.0130939</td><td>0.2083801</td><td>0.01608679</td><td>0.1735877</td><td>0.01234568</td><td>0.001870557</td><td>0.2835765</td><td>0.03965582</td><td>0.02469136</td><td>0.4672652</td><td>0.0003741115</td><td>0.0490086</td><td>0.05274972</td><td>0.0003741115</td><td>0</td><td>0.001122334</td><td>0.0003741115</td><td>0.4627759</td><td>1.290685</td><td>0.01122334</td><td>0.2274598</td><td>0.02581369</td><td>0.01421624</td><td>0.1215862</td><td>0.005611672</td><td>0.5566779</td><td>0.02731014</td><td>0.0003741115</td><td>0.00261878</td><td>0.07369996</td><td>0.07631874</td><td>0.01122334</td><td>0.02731014</td><td>0.09390198</td><td>0.1230827</td><td>0.05125327</td><td>0.001870557</td><td>0.01982791</td><td>0.1709689</td><td>0.005237561</td><td>0.005985784</td><td>0.8395062</td><td>0.008978676</td><td>0.01346801</td><td>0.0194538</td><td>0.005611672</td><td>0.06397306</td><td>0.002244669</td><td>0.3561541</td><td>0.0490086</td><td>0.01870557</td><td>0.08567153</td><td>0.5308642</td><td>0.03142536</td><td>0.003367003</td><td>0.009352787</td><td>0.0003741115</td><td>0.01459035</td><td>0.0325477</td><td>0.003741115</td><td>0.09315376</td><td>0.06621773</td><td>0.04152637</td><td>0.004489338</td><td>0</td><td>0.008604564</td><td>0.002244669</td><td>0.01795735</td><td>0.002992892</td><td>0.008230453</td><td>0.2708567</td><td>0.325477</td><td>0.01271979</td><td>0.4223719</td><td>0.003741115</td><td>0.008978676</td><td>0.002244669</td><td>0.3243547</td><td>0.01047512</td><td>0.2592593</td><td>0.01459035</td><td>0.01234568</td><td>0.03105125</td><td>0.000748223</td><td>0.007856341</td><td>0.01234568</td><td>0.01197157</td></tr>\n",
       "\t<tr><th scope=row>5</th><td>filipino</td><td>0.04370861</td><td>0.001324503</td><td>0.002649007</td><td>0.02251656</td><td>0.03178808</td><td>0.00397351</td><td>0.006622517</td><td>0.005298013</td><td>0.0397351</td><td>0.00397351</td><td>0.002649007</td><td>0.1615894</td><td>0.09271523</td><td>0.01324503</td><td>0.1284768</td><td>0.09271523</td><td>0.2754967</td><td>0.00794702</td><td>0.04900662</td><td>0.02781457</td><td>0.05298013</td><td>0.01192053</td><td>0.08476821</td><td>0.1192053</td><td>0.1165563</td><td>0</td><td>0.08874172</td><td>0.03576159</td><td>0</td><td>0.001324503</td><td>0.1774834</td><td>0.01059603</td><td>0.04768212</td><td>0.01986755</td><td>0.04635762</td><td>0.002649007</td><td>0.3271523</td><td>0.001324503</td><td>0.04768212</td><td>0.08344371</td><td>0.02384106</td><td>0</td><td>0.00397351</td><td>0.002649007</td><td>0.005298013</td><td>0.04635762</td><td>0.03311258</td><td>0.02384106</td><td>0.01059603</td><td>0.1245033</td><td>0.006622517</td><td>0.197351</td><td>0.006622517</td><td>0.05562914</td><td>0.005298013</td><td>0.1615894</td><td>0.006622517</td><td>0.1059603</td><td>0</td><td>0.001324503</td><td>0.07549669</td><td>0.01721854</td><td>0</td><td>0.02781457</td><td>0.006622517</td><td>0.01059603</td><td>0.006622517</td><td>0.01589404</td><td>0.009271523</td><td>0.001324503</td><td>0</td><td>0.001324503</td><td>0.001324503</td><td>0.04900662</td><td>0.2397351</td><td>0.03576159</td><td>0</td><td>0.006622517</td><td>0.0397351</td><td>0.00397351</td><td>0.001324503</td><td>0</td><td>0.01854305</td><td>0.009271523</td><td>0.00794702</td><td>0.1430464</td><td>0.03178808</td><td>0.002649007</td><td>0.1311258</td><td>0.002649007</td><td>0.1019868</td><td>0.02913907</td><td>0</td><td>0.6675497</td><td>0.1456954</td><td>0.00397351</td><td>0.03311258</td><td>0.01854305</td><td>0</td><td>0.2238411</td><td>0.3562914</td><td>0.00794702</td><td>0.009271523</td><td>0.005298013</td><td>0.01324503</td><td>0.01721854</td><td>0.02649007</td><td>0.01854305</td><td>0.002649007</td><td>0</td><td>0.01589404</td><td>0.07682119</td><td>0</td><td>0.005298013</td><td>0.03178808</td><td>0.02781457</td><td>0.002649007</td><td>0.0384106</td><td>0.03708609</td><td>0.006622517</td><td>0.1854305</td><td>0.00397351</td><td>0.0807947</td><td>0.001324503</td><td>0.005298013</td><td>0.01589404</td><td>0.03708609</td><td>0.02384106</td><td>0</td><td>0</td><td>0.01589404</td><td>0.03046358</td><td>0.00794702</td><td>0</td><td>0.2529801</td><td>0.05827815</td><td>0.001324503</td><td>0</td><td>0.001324503</td><td>0</td><td>0.001324503</td><td>0.02781457</td><td>0.00794702</td><td>0.06357616</td><td>0.001324503</td><td>0.6304636</td><td>0.07549669</td><td>0.6172185</td><td>0.01324503</td><td>0.006622517</td><td>0.04370861</td><td>0.01456954</td><td>0.002649007</td><td>0.01456954</td><td>0.0397351</td><td>0.00794702</td><td>0.04238411</td><td>0.02384106</td><td>0</td><td>0.00794702</td><td>0.6768212</td><td>0.1192053</td><td>0.00397351</td><td>0.005298013</td><td>0.2807947</td><td>0.08609272</td><td>0.1192053</td><td>0.01721854</td><td>0.03443709</td><td>0.09536424</td><td>0.001324503</td><td>0.01986755</td><td>0.1695364</td><td>0</td><td>0.00397351</td><td>0.01456954</td><td>0</td><td>0.00397351</td><td>0</td><td>0.001324503</td><td>0.6397351</td><td>0.6768212</td><td>0.01854305</td><td>0.02384106</td><td>0.01986755</td><td>0.01986755</td><td>0.02251656</td><td>0.001324503</td><td>0.0397351</td><td>0.02649007</td><td>0.001324503</td><td>0.002649007</td><td>0.005298013</td><td>0.01324503</td><td>0.02516556</td><td>0.02516556</td><td>0.09801325</td><td>0.03178808</td><td>0.01589404</td><td>0.006622517</td><td>0.005298013</td><td>0.02781457</td><td>0.002649007</td><td>0.005298013</td><td>0.384106</td><td>0.00397351</td><td>0.03576159</td><td>0.005298013</td><td>0</td><td>0.04238411</td><td>0.00794702</td><td>0.07549669</td><td>0.01192053</td><td>0.009271523</td><td>0.0410596</td><td>0.4225166</td><td>0.05430464</td><td>0.03708609</td><td>0.00397351</td><td>0.001324503</td><td>0.0384106</td><td>0.0410596</td><td>0.00794702</td><td>0.001324503</td><td>0.01721854</td><td>0.1615894</td><td>0.002649007</td><td>0.001324503</td><td>0.001324503</td><td>0.006622517</td><td>0.009271523</td><td>0.006622517</td><td>0.04900662</td><td>0.1430464</td><td>0.2278146</td><td>0.01192053</td><td>0.4609272</td><td>0.005298013</td><td>0.001324503</td><td>0.001324503</td><td>0.2066225</td><td>0.03311258</td><td>0.02251656</td><td>0.01192053</td><td>0.02251656</td><td>0.04635762</td><td>0</td><td>0.02781457</td><td>0.00397351</td><td>0.00794702</td></tr>\n",
       "\t<tr><th scope=row>6</th><td>french</td><td>0.2244898</td><td>0.0143613</td><td>0.0665155</td><td>0.006046863</td><td>0.04799698</td><td>0.001133787</td><td>0.01587302</td><td>0.0547997</td><td>0.04875283</td><td>0.01322751</td><td>0.0600907</td><td>0.1145125</td><td>0.09297052</td><td>0</td><td>0.06500378</td><td>0.04232804</td><td>0.2739985</td><td>0.01965231</td><td>0.03023432</td><td>0.1001512</td><td>0.04119426</td><td>0.004913076</td><td>0.1152683</td><td>0.04270597</td><td>0.4391534</td><td>0.005668934</td><td>0.007558579</td><td>0.01058201</td><td>0.03514739</td><td>0.003779289</td><td>0.09637188</td><td>0.02305367</td><td>0.06122449</td><td>0.009070295</td><td>0.2093726</td><td>0.02683296</td><td>0.2025699</td><td>0.005291005</td><td>0.003023432</td><td>0.004157218</td><td>0.001133787</td><td>0.005291005</td><td>0.0003779289</td><td>0.04157218</td><td>0.08956916</td><td>0.1659108</td><td>0.01247166</td><td>0.005291005</td><td>0.04006047</td><td>0.2033258</td><td>0.0143613</td><td>0.008692366</td><td>0.02191988</td><td>0.006424792</td><td>0.03439153</td><td>0.08730159</td><td>0.007936508</td><td>0.05177627</td><td>0.003779289</td><td>0.01058201</td><td>0.2641723</td><td>0.03061224</td><td>0.004913076</td><td>0.009826153</td><td>0.003401361</td><td>0.006802721</td><td>0.004913076</td><td>0.01814059</td><td>0.02267574</td><td>0.0718065</td><td>0.00718065</td><td>0.01662887</td><td>0.004535147</td><td>0.2736206</td><td>0.4512472</td><td>0.01587302</td><td>0</td><td>0.09674981</td><td>0.1103553</td><td>0.06462585</td><td>0.03817082</td><td>0.002645503</td><td>0.05668934</td><td>0.03779289</td><td>0.006424792</td><td>0.01549509</td><td>0.009070295</td><td>0.04799698</td><td>0.3034769</td><td>0.03401361</td><td>0.5506425</td><td>0.03514739</td><td>0</td><td>0.2936508</td><td>0.01662887</td><td>0.0170068</td><td>0.04686319</td><td>0.1084656</td><td>0.001889645</td><td>0.08654573</td><td>0.3272865</td><td>0.0260771</td><td>0.02834467</td><td>0.09334845</td><td>0.0003779289</td><td>0.02721088</td><td>0.01587302</td><td>0.03703704</td><td>0.01511716</td><td>0.002645503</td><td>0.0003779289</td><td>0.1734694</td><td>0.02040816</td><td>0.001889645</td><td>0.0007558579</td><td>0.0600907</td><td>0.01284958</td><td>0.3261527</td><td>0.1069539</td><td>0.001889645</td><td>0.1587302</td><td>0.05253212</td><td>0.1991686</td><td>0.02229781</td><td>0.02229781</td><td>0.03514739</td><td>0.01473923</td><td>0.0287226</td><td>0.02910053</td><td>0</td><td>0.01776266</td><td>0.007936508</td><td>0.006424792</td><td>0</td><td>0.1829176</td><td>0.02343159</td><td>0.02078609</td><td>0.0003779289</td><td>0.009826153</td><td>0.002267574</td><td>0.004157218</td><td>0.08843537</td><td>0.09637188</td><td>0.004535147</td><td>0.05291005</td><td>0.3877551</td><td>0.3571429</td><td>0.2849584</td><td>0.08956916</td><td>0.01814059</td><td>0.003401361</td><td>0.0143613</td><td>0.04346183</td><td>0.1855631</td><td>0.03703704</td><td>0.004157218</td><td>0.01095994</td><td>0.003023432</td><td>0.008692366</td><td>0.03476946</td><td>0.4591837</td><td>0.04195011</td><td>0.008314437</td><td>0.02834467</td><td>0.02834467</td><td>0.1130008</td><td>0.111867</td><td>0.02456538</td><td>0.009070295</td><td>0.1617536</td><td>0.02305367</td><td>0.0313681</td><td>0.01284958</td><td>0.005668934</td><td>0.02305367</td><td>0.006802721</td><td>0.04195011</td><td>0.01889645</td><td>0.01473923</td><td>0</td><td>0.6213152</td><td>0.03628118</td><td>0.0117158</td><td>0.006802721</td><td>0.07974301</td><td>0.007936508</td><td>0.03174603</td><td>0.0007558579</td><td>0.001511716</td><td>0.1216931</td><td>0.002645503</td><td>0.0117158</td><td>0.0287226</td><td>0.008314437</td><td>0.009070295</td><td>0.01965231</td><td>0.01814059</td><td>0.02116402</td><td>0.05404384</td><td>0.01209373</td><td>0.006802721</td><td>0.0457294</td><td>0.008314437</td><td>0.02116402</td><td>0.002645503</td><td>0.001511716</td><td>0.0143613</td><td>0.07671958</td><td>0.07142857</td><td>0.001133787</td><td>0.01133787</td><td>0.03514739</td><td>0.02305367</td><td>0.007936508</td><td>0.04610733</td><td>0.4368859</td><td>0.01209373</td><td>0.009448224</td><td>0.02267574</td><td>0</td><td>0</td><td>0.01587302</td><td>0.2018141</td><td>0.01247166</td><td>0.001889645</td><td>0.1613757</td><td>0.0003779289</td><td>0.0003779289</td><td>0.008314437</td><td>0.0007558579</td><td>0.2256236</td><td>0.02343159</td><td>0.1523054</td><td>0.06386999</td><td>0.1235828</td><td>0.0170068</td><td>0.249811</td><td>0.004535147</td><td>0.009448224</td><td>0.09372638</td><td>0.313681</td><td>0.07482993</td><td>0.2505669</td><td>0.007558579</td><td>0.0287226</td><td>0.03552532</td><td>0.008692366</td><td>0.1311413</td><td>0.03817082</td><td>0.03401361</td></tr>\n",
       "\t<tr><th scope=row>7</th><td>greek</td><td>0.08510638</td><td>0.02723404</td><td>0.02468085</td><td>0.01276596</td><td>0.004255319</td><td>0.005106383</td><td>0.02893617</td><td>0.002553191</td><td>0.0587234</td><td>0.02212766</td><td>0.06468085</td><td>0.03234043</td><td>0.05702128</td><td>0</td><td>0.04680851</td><td>0.1029787</td><td>0.3387234</td><td>0.006808511</td><td>0.0587234</td><td>0.1055319</td><td>0.08595745</td><td>0.002553191</td><td>0.05957447</td><td>0.01191489</td><td>0.1421277</td><td>0.002553191</td><td>0.001702128</td><td>0.01021277</td><td>0.02553191</td><td>0.001702128</td><td>0.02723404</td><td>0.02468085</td><td>0.02723404</td><td>0.005957447</td><td>0.4919149</td><td>0.04680851</td><td>0.1948936</td><td>0.02723404</td><td>0.004255319</td><td>0.01191489</td><td>0</td><td>0.007659574</td><td>0</td><td>0.01191489</td><td>0.006808511</td><td>0.2314894</td><td>0.005106383</td><td>0.008510638</td><td>0.106383</td><td>0.2748936</td><td>0.02042553</td><td>0.002553191</td><td>0.004255319</td><td>0.0008510638</td><td>0.007659574</td><td>0.09021277</td><td>0.01361702</td><td>0.009361702</td><td>0</td><td>0.0187234</td><td>0.04595745</td><td>0.03404255</td><td>0.2170213</td><td>0.03829787</td><td>0.2246809</td><td>0.04170213</td><td>0.002553191</td><td>0.001702128</td><td>0.05957447</td><td>0.01446809</td><td>0.1480851</td><td>0.04680851</td><td>0.0212766</td><td>0.44</td><td>0.1753191</td><td>0.05446809</td><td>0</td><td>0.1948936</td><td>0.02723404</td><td>0.03914894</td><td>0.01787234</td><td>0.3812766</td><td>0.01787234</td><td>0.02723404</td><td>0.0008510638</td><td>0</td><td>0.03744681</td><td>0.05617021</td><td>0.1157447</td><td>0.02978723</td><td>0.7582979</td><td>0.03659574</td><td>0</td><td>0.5361702</td><td>0.005957447</td><td>0.005957447</td><td>0.01446809</td><td>0.09617021</td><td>0.1838298</td><td>0.1395745</td><td>0.5531915</td><td>0.02978723</td><td>0.001702128</td><td>0.005957447</td><td>0</td><td>0.0612766</td><td>0.01361702</td><td>0</td><td>0.01361702</td><td>0.001702128</td><td>0.001702128</td><td>0.3795745</td><td>0.1310638</td><td>0.0008510638</td><td>0.0008510638</td><td>0.07489362</td><td>0.1157447</td><td>0.1268085</td><td>0.07744681</td><td>0.01702128</td><td>0.1208511</td><td>0.006808511</td><td>0.5480851</td><td>0.01021277</td><td>0.06978723</td><td>0.01191489</td><td>0.005106383</td><td>0.02042553</td><td>0.03234043</td><td>0</td><td>0.01361702</td><td>0.005957447</td><td>0.01021277</td><td>0</td><td>0.07574468</td><td>0.06978723</td><td>0.1429787</td><td>0</td><td>0.01106383</td><td>0.0008510638</td><td>0.01106383</td><td>0.02212766</td><td>0.02297872</td><td>0.002553191</td><td>0.04085106</td><td>0.7021277</td><td>0.7795745</td><td>0.4791489</td><td>0.03914894</td><td>0.3429787</td><td>0</td><td>0.02723404</td><td>0.04170213</td><td>0.2195745</td><td>0.03319149</td><td>0.03489362</td><td>0.01021277</td><td>0.0008510638</td><td>0.006808511</td><td>0.02382979</td><td>0.7361702</td><td>0.005106383</td><td>0.1285106</td><td>0.04425532</td><td>0.01787234</td><td>0.08</td><td>0.08425532</td><td>0.1582979</td><td>0.01021277</td><td>0.2561702</td><td>0.005106383</td><td>0.01021277</td><td>0.05446809</td><td>0.009361702</td><td>0.02468085</td><td>0.001702128</td><td>0.05361702</td><td>0.001702128</td><td>0.002553191</td><td>0</td><td>0.6357447</td><td>0.05276596</td><td>0.002553191</td><td>0.01787234</td><td>0.03319149</td><td>0.05531915</td><td>0.02978723</td><td>0.0008510638</td><td>0.01021277</td><td>0.02468085</td><td>0.001702128</td><td>0.005106383</td><td>0.005106383</td><td>0</td><td>0.01361702</td><td>0.01191489</td><td>0.03404255</td><td>0.05617021</td><td>0.0493617</td><td>0.006808511</td><td>0.01446809</td><td>0.02042553</td><td>0.003404255</td><td>0.02042553</td><td>0.005106383</td><td>0.005106383</td><td>0.09361702</td><td>0.07914894</td><td>0.02297872</td><td>0.003404255</td><td>0.005957447</td><td>0.008510638</td><td>0.01702128</td><td>0.02723404</td><td>0.02042553</td><td>0.1242553</td><td>0.01361702</td><td>0.001702128</td><td>0.003404255</td><td>0</td><td>0</td><td>0.009361702</td><td>0.06042553</td><td>0.005106383</td><td>0</td><td>0.4221277</td><td>0.004255319</td><td>0</td><td>0.01191489</td><td>0.004255319</td><td>0.05276596</td><td>0.0008510638</td><td>0.02978723</td><td>0.04680851</td><td>0.146383</td><td>0.01361702</td><td>0.1574468</td><td>0.01617021</td><td>0.02723404</td><td>0.002553191</td><td>0.1489362</td><td>0.04765957</td><td>0.1693617</td><td>0.002553191</td><td>0.01276596</td><td>0.03829787</td><td>0.2382979</td><td>0.02382979</td><td>0.05957447</td><td>0.04170213</td></tr>\n",
       "\t<tr><th scope=row>8</th><td>indian</td><td>0.04995005</td><td>0.007992008</td><td>0.04129204</td><td>0.002664003</td><td>0.01498501</td><td>0.001665002</td><td>0.02364302</td><td>0</td><td>0.03663004</td><td>0.001998002</td><td>0.004995005</td><td>0.07692308</td><td>0.03962704</td><td>0.0003330003</td><td>0.01931402</td><td>0.04995005</td><td>0.2291042</td><td>0.01431901</td><td>0.08424908</td><td>0.02664003</td><td>0.08558109</td><td>0.006327006</td><td>0.06393606</td><td>0.07326007</td><td>0.1428571</td><td>0.006993007</td><td>0.01232101</td><td>0.05361305</td><td>0</td><td>0.1958042</td><td>0.07092907</td><td>0.1245421</td><td>0.01132201</td><td>0.001332001</td><td>0.02064602</td><td>0.004329004</td><td>0.2710623</td><td>0.06560107</td><td>0.1252081</td><td>0.5141525</td><td>0.0006660007</td><td>0.000999001</td><td>0.0006660007</td><td>0.002331002</td><td>0.001665002</td><td>0.2540793</td><td>0.009324009</td><td>0.3476523</td><td>0.1814852</td><td>0.3010323</td><td>0.01631702</td><td>0.2104562</td><td>0.006327006</td><td>0.005661006</td><td>0.001665002</td><td>0.06959707</td><td>0.3846154</td><td>0.02997003</td><td>0.0003330003</td><td>0.007326007</td><td>0.0952381</td><td>0.008991009</td><td>0.000999001</td><td>0.04562105</td><td>0.03230103</td><td>0.5204795</td><td>0.2870463</td><td>0.004662005</td><td>0.05228105</td><td>0.002331002</td><td>0.001998002</td><td>0.005328005</td><td>0.000999001</td><td>0.07592408</td><td>0.04428904</td><td>0.02064602</td><td>0</td><td>0.01764902</td><td>0.006327006</td><td>0.03829504</td><td>0.05028305</td><td>0.001665002</td><td>0.02297702</td><td>0.02630703</td><td>0.01165501</td><td>0.008991009</td><td>0.04562105</td><td>0.002664003</td><td>0.1768232</td><td>0.02331002</td><td>0.5544456</td><td>0.05661006</td><td>0.2877123</td><td>0.5444555</td><td>0.4911755</td><td>0.01731602</td><td>0.006327006</td><td>0.03163503</td><td>0.04695305</td><td>0.3100233</td><td>0.9297369</td><td>0.01798202</td><td>0</td><td>0.03596404</td><td>0</td><td>0.02097902</td><td>0.02630703</td><td>0.00965701</td><td>0.001665002</td><td>0.0003330003</td><td>0.04229104</td><td>0.1994672</td><td>0</td><td>0.003330003</td><td>0.007992008</td><td>0.08558109</td><td>0.03696304</td><td>0.03962704</td><td>0.04528805</td><td>0.000999001</td><td>0.3203463</td><td>0.001998002</td><td>0.1958042</td><td>0.01032301</td><td>0.003996004</td><td>0.02630703</td><td>0.09057609</td><td>0.01665002</td><td>0.02930403</td><td>0.3323343</td><td>0.004329004</td><td>0.01132201</td><td>0.007992008</td><td>0</td><td>0.2117882</td><td>0.05128205</td><td>0.07425907</td><td>0</td><td>0.007992008</td><td>0.0003330003</td><td>0.001332001</td><td>0.01431901</td><td>0.1751582</td><td>0.002664003</td><td>0.02930403</td><td>0.6763237</td><td>0.1411921</td><td>0.6140526</td><td>0.007659008</td><td>0.000999001</td><td>0.0006660007</td><td>0.08091908</td><td>0.001332001</td><td>0.01565102</td><td>0.2061272</td><td>0.000999001</td><td>0.0959041</td><td>0.03296703</td><td>0.0006660007</td><td>0.06227106</td><td>0.5487845</td><td>0.05394605</td><td>0.1378621</td><td>0.02464202</td><td>0.008658009</td><td>0.1598402</td><td>0.5071595</td><td>0.05661006</td><td>0.03896104</td><td>0.2947053</td><td>0.006660007</td><td>0.004662005</td><td>0.1974692</td><td>0.001665002</td><td>0.01798202</td><td>0.04961705</td><td>0.0003330003</td><td>0.03829504</td><td>0</td><td>0.0006660007</td><td>0.7998668</td><td>0.04695305</td><td>0.0003330003</td><td>0.01198801</td><td>0.03862804</td><td>0.005328005</td><td>0.5790876</td><td>0.04528805</td><td>0.01665002</td><td>0.01864802</td><td>0</td><td>0.000999001</td><td>0.001332001</td><td>0</td><td>0.00999001</td><td>0.00965701</td><td>0.02497502</td><td>0.07492507</td><td>0.01931402</td><td>0.01132201</td><td>0.01565102</td><td>0.02197802</td><td>0.000999001</td><td>0.009324009</td><td>0.01165501</td><td>0</td><td>0.06093906</td><td>0.02630703</td><td>0.01265401</td><td>0.004662005</td><td>0.00965701</td><td>0.01465201</td><td>0.005661006</td><td>0.08658009</td><td>0.03529804</td><td>0.1774892</td><td>0.03163503</td><td>0.007659008</td><td>0.002331002</td><td>0</td><td>0.006660007</td><td>0.04395604</td><td>0.006660007</td><td>0.005661006</td><td>0.01365301</td><td>0.4192474</td><td>0.002664003</td><td>0.1694972</td><td>0.003663004</td><td>0.2437562</td><td>0.02963703</td><td>0.01498501</td><td>0.005994006</td><td>0.2477522</td><td>0.05094905</td><td>0.01998002</td><td>0.3220113</td><td>0.01631702</td><td>0.02830503</td><td>0.007659008</td><td>0.08225108</td><td>0.06227106</td><td>0.01831502</td><td>0.0006660007</td><td>0.02430902</td><td>0.07359307</td><td>0.1918082</td><td>0.000999001</td><td>0.007326007</td><td>0.01431901</td></tr>\n",
       "\t<tr><th scope=row>9</th><td>irish</td><td>0.3283358</td><td>0.02998501</td><td>0.01949025</td><td>0.02248876</td><td>0.04647676</td><td>0.002998501</td><td>0.01649175</td><td>0.09445277</td><td>0.3823088</td><td>0.008995502</td><td>0.004497751</td><td>0.07646177</td><td>0.0149925</td><td>0</td><td>0.17991</td><td>0.01649175</td><td>0.2128936</td><td>0.02098951</td><td>0.005997001</td><td>0.05547226</td><td>0.007496252</td><td>0</td><td>0.09145427</td><td>0.1124438</td><td>0.5007496</td><td>0.143928</td><td>0.131934</td><td>0.005997001</td><td>0.005997001</td><td>0.007496252</td><td>0.1814093</td><td>0.01649175</td><td>0.06296852</td><td>0.05847076</td><td>0.1244378</td><td>0.017991</td><td>0.09895052</td><td>0</td><td>0.002998501</td><td>0.004497751</td><td>0</td><td>0.01649175</td><td>0.00149925</td><td>0.02998501</td><td>0.05547226</td><td>0.1289355</td><td>0.02398801</td><td>0.007496252</td><td>0.06446777</td><td>0.08845577</td><td>0.01349325</td><td>0.005997001</td><td>0.01349325</td><td>0.01049475</td><td>0.02398801</td><td>0.1034483</td><td>0.002998501</td><td>0.06446777</td><td>0</td><td>0.008995502</td><td>0.2608696</td><td>0.01649175</td><td>0.002998501</td><td>0.01049475</td><td>0.007496252</td><td>0.004497751</td><td>0</td><td>0.02848576</td><td>0.01649175</td><td>0.02098951</td><td>0.01049475</td><td>0.008995502</td><td>0.004497751</td><td>0.1649175</td><td>0.3223388</td><td>0</td><td>0</td><td>0.017991</td><td>0.06446777</td><td>0.05247376</td><td>0.01049475</td><td>0</td><td>0.011994</td><td>0.02248876</td><td>0.008995502</td><td>0.00149925</td><td>0.005997001</td><td>0.01349325</td><td>0.5112444</td><td>0.03448276</td><td>0.2713643</td><td>0.03298351</td><td>0</td><td>0.1604198</td><td>0.03898051</td><td>0.02098951</td><td>0.06146927</td><td>0.06596702</td><td>0.002998501</td><td>0.1064468</td><td>0.3328336</td><td>0.007496252</td><td>0.02248876</td><td>0.06896552</td><td>0</td><td>0.017991</td><td>0.011994</td><td>0.0149925</td><td>0.007496252</td><td>0</td><td>0.004497751</td><td>0.07496252</td><td>0</td><td>0</td><td>0.002998501</td><td>0.04947526</td><td>0.06146927</td><td>0.1604198</td><td>0.04647676</td><td>0.004497751</td><td>0.08095952</td><td>0.06146927</td><td>0.09145427</td><td>0.011994</td><td>0.004497751</td><td>0.03148426</td><td>0.01049475</td><td>0.0149925</td><td>0.06596702</td><td>0</td><td>0.011994</td><td>0.02548726</td><td>0</td><td>0</td><td>0.2788606</td><td>0.011994</td><td>0.0149925</td><td>0</td><td>0.02998501</td><td>0</td><td>0.004497751</td><td>0.03898051</td><td>0.06596702</td><td>0</td><td>0.05847076</td><td>0.2068966</td><td>0.09745127</td><td>0.3568216</td><td>0.06746627</td><td>0.005997001</td><td>0.004497751</td><td>0.02398801</td><td>0.01049475</td><td>0.1244378</td><td>0.03448276</td><td>0.00149925</td><td>0.03448276</td><td>0.007496252</td><td>0.01049475</td><td>0.02398801</td><td>0.4257871</td><td>0.02098951</td><td>0.01649175</td><td>0.004497751</td><td>0.03748126</td><td>0.4107946</td><td>0.2473763</td><td>0.004497751</td><td>0.07496252</td><td>0.1064468</td><td>0.0149925</td><td>0.01949025</td><td>0.002998501</td><td>0</td><td>0.01649175</td><td>0.002998501</td><td>0.02848576</td><td>0</td><td>0.01649175</td><td>0.00149925</td><td>0.6926537</td><td>0.06296852</td><td>0.04647676</td><td>0.02098951</td><td>0.02548726</td><td>0.01349325</td><td>0.06296852</td><td>0</td><td>0.005997001</td><td>0.01649175</td><td>0.017991</td><td>0.002998501</td><td>0.011994</td><td>0.002998501</td><td>0.01949025</td><td>0.03448276</td><td>0</td><td>0.004497751</td><td>0.02398801</td><td>0.017991</td><td>0.1829085</td><td>0.02698651</td><td>0.00149925</td><td>0.04797601</td><td>0.01049475</td><td>0</td><td>0.01049475</td><td>0.09295352</td><td>0.01949025</td><td>0.01049475</td><td>0.00149925</td><td>0.01949025</td><td>0.01049475</td><td>0.008995502</td><td>0.07346327</td><td>0.4587706</td><td>0.017991</td><td>0.011994</td><td>0.01649175</td><td>0</td><td>0</td><td>0</td><td>0.1034483</td><td>0.007496252</td><td>0</td><td>0.06596702</td><td>0.00149925</td><td>0.00149925</td><td>0.005997001</td><td>0</td><td>0.1304348</td><td>0.0149925</td><td>0.07646177</td><td>0.1064468</td><td>0.06146927</td><td>0.01049475</td><td>0.1814093</td><td>0.005997001</td><td>0.08245877</td><td>0.05397301</td><td>0.1514243</td><td>0.1034483</td><td>0.04497751</td><td>0.03448276</td><td>0.008995502</td><td>0.04047976</td><td>0.017991</td><td>0.02698651</td><td>0.02998501</td><td>0.005997001</td></tr>\n",
       "\t<tr><th scope=row>10</th><td>italian</td><td>0.1172493</td><td>0.001531003</td><td>0.03393723</td><td>0.02143404</td><td>0.004337841</td><td>0.003189589</td><td>0.03023731</td><td>0.0294718</td><td>0.03891299</td><td>0.04746109</td><td>0.2558051</td><td>0.0349579</td><td>0.06149528</td><td>0.0001275836</td><td>0.07438122</td><td>0.09249809</td><td>0.3155142</td><td>0.01046185</td><td>0.05179893</td><td>0.1122735</td><td>0.07017096</td><td>0.02449604</td><td>0.1287318</td><td>0.01773412</td><td>0.2117887</td><td>0.006124011</td><td>0.006124011</td><td>0.005741261</td><td>0.03967849</td><td>0.001148252</td><td>0.05537127</td><td>0.008292932</td><td>0.05460577</td><td>0.01479969</td><td>0.7454708</td><td>0.02857872</td><td>0.2341158</td><td>0.005230926</td><td>0.005230926</td><td>0.01365144</td><td>0.0003827507</td><td>0.00357234</td><td>0.0007655014</td><td>0.0163307</td><td>0.02679255</td><td>0.2010717</td><td>0.003189589</td><td>0.006634345</td><td>0.01607553</td><td>0.2507017</td><td>0.01990304</td><td>0.002934422</td><td>0.008165348</td><td>0.006506762</td><td>0.01212044</td><td>0.1044909</td><td>0.002551671</td><td>0.02781322</td><td>0.009951518</td><td>0.01492728</td><td>0.1268181</td><td>0.05090584</td><td>0.01696861</td><td>0.1120184</td><td>0.005103343</td><td>0.004720592</td><td>0.001148252</td><td>0.004720592</td><td>0.06545037</td><td>0.01365144</td><td>0.003062006</td><td>0.02845114</td><td>0.01658586</td><td>0.3716509</td><td>0.2287573</td><td>0.02908905</td><td>0</td><td>0.1737688</td><td>0.04146466</td><td>0.04848176</td><td>0.03227864</td><td>0.01377903</td><td>0.02755805</td><td>0.03368206</td><td>0.002041337</td><td>0.003955091</td><td>0.06825721</td><td>0.07616739</td><td>0.1736412</td><td>0.03151314</td><td>0.6368972</td><td>0.04325083</td><td>0.0001275836</td><td>0.5324062</td><td>0.00535851</td><td>0.00893085</td><td>0.01454453</td><td>0.2649911</td><td>0.001148252</td><td>0.09645318</td><td>0.3803266</td><td>0.03023731</td><td>0.01237561</td><td>0.048099</td><td>0</td><td>0.01671345</td><td>0.03176831</td><td>0.00714468</td><td>0.1437867</td><td>0.004848176</td><td>0.002551671</td><td>0.1237561</td><td>0.01990304</td><td>0.003955091</td><td>0.00178617</td><td>0.08497066</td><td>0.004593008</td><td>0.1647104</td><td>0.09300842</td><td>0.02079612</td><td>0.1560347</td><td>0.01352386</td><td>0.1787446</td><td>0.02258229</td><td>0.009441184</td><td>0.01046185</td><td>0.006379178</td><td>0.04159224</td><td>0.02411329</td><td>0.0001275836</td><td>0.008037765</td><td>0.009823935</td><td>0.01173769</td><td>0.0002551671</td><td>0.09402909</td><td>0.04950242</td><td>0.02156162</td><td>0</td><td>0.01237561</td><td>0.002806838</td><td>0.1593519</td><td>0.1075529</td><td>0.01875478</td><td>0.04006124</td><td>0.03023731</td><td>0.6612656</td><td>0.6362592</td><td>0.3466446</td><td>0.03687165</td><td>0.125925</td><td>0.001148252</td><td>0.01135494</td><td>0.3133452</td><td>0.2227609</td><td>0.05741261</td><td>0.1294973</td><td>0.0264098</td><td>0.0006379178</td><td>0.005486093</td><td>0.03406481</td><td>0.7231437</td><td>0.004848176</td><td>0.004337841</td><td>0.04848176</td><td>0.0294718</td><td>0.0364889</td><td>0.09224292</td><td>0.04478183</td><td>0.0108446</td><td>0.2619291</td><td>0.01569278</td><td>0.02181679</td><td>0.04682317</td><td>0.08484307</td><td>0.02985455</td><td>0.0007655014</td><td>0.06481245</td><td>0.004720592</td><td>0.03534065</td><td>0.001658586</td><td>0.6247767</td><td>0.1710896</td><td>0.07501914</td><td>0.008037765</td><td>0.04337841</td><td>0.07119163</td><td>0.02283746</td><td>0.000893085</td><td>0.002168921</td><td>0.04031641</td><td>0.004848176</td><td>0.0163307</td><td>0.009951518</td><td>0.008420515</td><td>0.003189589</td><td>0.07540189</td><td>0.03164072</td><td>0.0442715</td><td>0.05600919</td><td>0.008165348</td><td>0.009186017</td><td>0.05294718</td><td>0.01020669</td><td>0.01428936</td><td>0.002934422</td><td>0.04554733</td><td>0.07323297</td><td>0.08254657</td><td>0.02079612</td><td>0.0006379178</td><td>0.0186272</td><td>0.01097219</td><td>0.01237561</td><td>0.003827507</td><td>0.03444756</td><td>0.1758102</td><td>0.02538913</td><td>0.002041337</td><td>0.004465425</td><td>0</td><td>0.0002551671</td><td>0.008292932</td><td>0.06685379</td><td>0.008037765</td><td>0.002168921</td><td>0.4268946</td><td>0.002168921</td><td>0.0007655014</td><td>0.02373054</td><td>0.0002551671</td><td>0.07399847</td><td>0.01186527</td><td>0.04159224</td><td>0.06902271</td><td>0.09874968</td><td>0.02334779</td><td>0.1892064</td><td>0.008037765</td><td>0.02207196</td><td>0.03559582</td><td>0.2181679</td><td>0.05754019</td><td>0.1940546</td><td>0.007655014</td><td>0.03164072</td><td>0.04669559</td><td>0.004337841</td><td>0.02883389</td><td>0.03470273</td><td>0.04337841</td></tr>\n",
       "\t<tr><th scope=row>11</th><td>jamaican</td><td>0.07984791</td><td>0.3707224</td><td>0.005703422</td><td>0.01140684</td><td>0.01520913</td><td>0.01140684</td><td>0.01330798</td><td>0.01901141</td><td>0.09315589</td><td>0.001901141</td><td>0.01520913</td><td>0.03992395</td><td>0.1140684</td><td>0</td><td>0.1121673</td><td>0.1406844</td><td>0.4220532</td><td>0.01140684</td><td>0.06653992</td><td>0.06653992</td><td>0.07794677</td><td>0.001901141</td><td>0.05513308</td><td>0.2072243</td><td>0.1749049</td><td>0.003802281</td><td>0.01901141</td><td>0.01901141</td><td>0.001901141</td><td>0.003802281</td><td>0.09315589</td><td>0.09505703</td><td>0.03041825</td><td>0.003802281</td><td>0.03231939</td><td>0.007604563</td><td>0.338403</td><td>0</td><td>0.1121673</td><td>0.108365</td><td>0.009505703</td><td>0.007604563</td><td>0.005703422</td><td>0.01330798</td><td>0.007604563</td><td>0.1330798</td><td>0.03231939</td><td>0.06463878</td><td>0.2414449</td><td>0.2756654</td><td>0.01140684</td><td>0.2661597</td><td>0.0608365</td><td>0.01901141</td><td>0.001901141</td><td>0.08745247</td><td>0.03802281</td><td>0.04562738</td><td>0.02471483</td><td>0.009505703</td><td>0.04562738</td><td>0.05893536</td><td>0</td><td>0.03041825</td><td>0.001901141</td><td>0.05703422</td><td>0.1444867</td><td>0.08365019</td><td>0.03041825</td><td>0.01140684</td><td>0.003802281</td><td>0.01330798</td><td>0.001901141</td><td>0.3098859</td><td>0.1235741</td><td>0.001901141</td><td>0</td><td>0.01140684</td><td>0.04372624</td><td>0.02091255</td><td>0</td><td>0</td><td>0.02091255</td><td>0.02091255</td><td>0</td><td>0.02471483</td><td>0.06463878</td><td>0.005703422</td><td>0.2110266</td><td>0.009505703</td><td>0.4296578</td><td>0.01140684</td><td>0.003802281</td><td>0.595057</td><td>0.2357414</td><td>0.001901141</td><td>0.02281369</td><td>0.0608365</td><td>0.001901141</td><td>0.2072243</td><td>1.030418</td><td>0.02471483</td><td>0.009505703</td><td>0.003802281</td><td>0</td><td>0.01520913</td><td>0.1197719</td><td>0.01901141</td><td>0.001901141</td><td>0</td><td>0.05703422</td><td>0.2585551</td><td>0</td><td>0.001901141</td><td>0.06273764</td><td>0.06273764</td><td>0.001901141</td><td>0.04562738</td><td>0.01711027</td><td>0.01711027</td><td>0.1121673</td><td>0.001901141</td><td>0.04372624</td><td>0.001901141</td><td>0.01140684</td><td>0.04942966</td><td>0.2908745</td><td>0.03231939</td><td>0.003802281</td><td>0.005703422</td><td>0.01711027</td><td>0.03231939</td><td>0.007604563</td><td>0</td><td>0.2775665</td><td>0.05893536</td><td>0.003802281</td><td>0</td><td>0.01711027</td><td>0</td><td>0.007604563</td><td>0.009505703</td><td>0.03231939</td><td>0.005703422</td><td>0.2281369</td><td>0.513308</td><td>0.1387833</td><td>0.7110266</td><td>0.08935361</td><td>0.01330798</td><td>0.001901141</td><td>0.05323194</td><td>0.003802281</td><td>0.02851711</td><td>0.03041825</td><td>0.001901141</td><td>0.03612167</td><td>0.01520913</td><td>0.01520913</td><td>0.02661597</td><td>1.171103</td><td>0.01901141</td><td>0.02091255</td><td>0.009505703</td><td>0.0608365</td><td>0.1007605</td><td>0.3840304</td><td>0.04942966</td><td>0.02091255</td><td>0.2338403</td><td>0.003802281</td><td>0.005703422</td><td>0.1273764</td><td>0</td><td>0.01711027</td><td>0.03041825</td><td>0.01140684</td><td>0</td><td>0.01520913</td><td>0.003802281</td><td>0.7965779</td><td>0.3288973</td><td>0</td><td>0.2148289</td><td>0.03992395</td><td>0.09885932</td><td>0.03612167</td><td>0.009505703</td><td>0.003802281</td><td>0.01711027</td><td>0</td><td>0.001901141</td><td>0.007604563</td><td>0</td><td>0.001901141</td><td>0.01330798</td><td>0.03802281</td><td>0.0608365</td><td>0.02851711</td><td>0.01140684</td><td>0.02661597</td><td>0.03231939</td><td>0.003802281</td><td>0.01711027</td><td>0.1539924</td><td>0</td><td>0.02661597</td><td>0.03041825</td><td>0.02091255</td><td>0.01520913</td><td>0.01140684</td><td>0.02091255</td><td>0.01711027</td><td>0.01330798</td><td>0.07224335</td><td>0.3878327</td><td>0.0513308</td><td>0.02281369</td><td>0.01520913</td><td>0</td><td>0</td><td>0.03231939</td><td>0.5627376</td><td>0.005703422</td><td>0</td><td>0.161597</td><td>0.009505703</td><td>0.02851711</td><td>0.005703422</td><td>0.02471483</td><td>0.03612167</td><td>0.03041825</td><td>0.07034221</td><td>0.230038</td><td>0.1711027</td><td>0.009505703</td><td>0.3992395</td><td>0.009505703</td><td>0.003802281</td><td>0.005703422</td><td>0.1730038</td><td>0.01901141</td><td>0.04562738</td><td>0.01901141</td><td>0.02281369</td><td>0.06653992</td><td>0.003802281</td><td>0.003802281</td><td>0.01330798</td><td>0.009505703</td></tr>\n",
       "\t<tr><th scope=row>12</th><td>japanese</td><td>0.04848911</td><td>0.0007027407</td><td>0.009135629</td><td>0.003513703</td><td>0.01264933</td><td>0.04216444</td><td>0.02670415</td><td>0.005621926</td><td>0.03865074</td><td>0.002810963</td><td>0.007027407</td><td>0.01686578</td><td>0.03583978</td><td>0.0154603</td><td>0.04989459</td><td>0.03583978</td><td>0.1082221</td><td>0.01335207</td><td>0.0639494</td><td>0.00983837</td><td>0.04567814</td><td>0.01194659</td><td>0.04708363</td><td>0.08081518</td><td>0.07378777</td><td>0</td><td>0.07378777</td><td>0.04427266</td><td>0</td><td>0.02670415</td><td>0.1433591</td><td>0.01827126</td><td>0.01335207</td><td>0.0007027407</td><td>0.02459592</td><td>0.006324666</td><td>0.1939564</td><td>0.002108222</td><td>0.01967674</td><td>0.1278988</td><td>0.01194659</td><td>0.0007027407</td><td>0.0007027407</td><td>0.02600141</td><td>0.005621926</td><td>0.05200281</td><td>0.005621926</td><td>0.06535488</td><td>0.01616304</td><td>0.08151792</td><td>0.006324666</td><td>0.03021785</td><td>0.0224877</td><td>0.005621926</td><td>0.002810963</td><td>0.05059733</td><td>0.04567814</td><td>0.08011244</td><td>0</td><td>0.004919185</td><td>0.04286718</td><td>0.002810963</td><td>0</td><td>0.0154603</td><td>0.08151792</td><td>0.04567814</td><td>0.02529866</td><td>0.037948</td><td>0.004216444</td><td>0.009135629</td><td>0.003513703</td><td>0.004216444</td><td>0.004919185</td><td>0.08995081</td><td>0.2347154</td><td>0.02740689</td><td>0</td><td>0.0154603</td><td>0.01616304</td><td>0.008432888</td><td>0.008432888</td><td>0</td><td>0.07238229</td><td>0.01475755</td><td>0.04778637</td><td>0.018974</td><td>0.08432888</td><td>0.004216444</td><td>0.1426564</td><td>0.01054111</td><td>0.2839072</td><td>0.03092059</td><td>0.03232607</td><td>0.2515812</td><td>0.3239635</td><td>0.002108222</td><td>0.03373155</td><td>0.01335207</td><td>0.0007027407</td><td>0.2319044</td><td>0.1834153</td><td>0.005621926</td><td>0.002810963</td><td>0.01054111</td><td>0.006324666</td><td>0.05551651</td><td>0.02810963</td><td>0.00983837</td><td>0.001405481</td><td>0.0007027407</td><td>0.003513703</td><td>0.1004919</td><td>0</td><td>0.003513703</td><td>0.02600141</td><td>0.056922</td><td>0</td><td>0.08713985</td><td>0.01264933</td><td>0.001405481</td><td>0.07800422</td><td>0.01335207</td><td>0.0983837</td><td>0.002108222</td><td>0.007730148</td><td>0.03373155</td><td>0.0449754</td><td>0.05551651</td><td>0.0007027407</td><td>0.03583978</td><td>0.03583978</td><td>0.01967674</td><td>0.01335207</td><td>0</td><td>0.07167955</td><td>0.03443429</td><td>0.003513703</td><td>0.2825018</td><td>0.01054111</td><td>0</td><td>0.002810963</td><td>0.1033029</td><td>0.03373155</td><td>0.09557273</td><td>0.002108222</td><td>0.6331694</td><td>0.056922</td><td>0.3316936</td><td>0.02529866</td><td>0</td><td>0.009135629</td><td>0.006324666</td><td>0.005621926</td><td>0.007730148</td><td>0.1293043</td><td>0.002108222</td><td>0.05270555</td><td>0.0224877</td><td>0.002810963</td><td>0.04075896</td><td>0.2740689</td><td>0.007027407</td><td>0.01124385</td><td>0.005621926</td><td>0.07870696</td><td>0.06746311</td><td>0.1658468</td><td>0.00983837</td><td>0.002810963</td><td>0.1257906</td><td>0.02389318</td><td>0.009135629</td><td>0.3893183</td><td>0.0007027407</td><td>0.01194659</td><td>0.03583978</td><td>0</td><td>0.004919185</td><td>0</td><td>0</td><td>0.4082923</td><td>0.6605762</td><td>0.001405481</td><td>0.1658468</td><td>0.05270555</td><td>0.01686578</td><td>0.2431483</td><td>0.001405481</td><td>0.3654252</td><td>0.02108222</td><td>0.0007027407</td><td>0.005621926</td><td>0.01054111</td><td>0.09697822</td><td>0.006324666</td><td>0.01967674</td><td>0.04989459</td><td>0.04567814</td><td>0.02881237</td><td>0.0154603</td><td>0.01405481</td><td>0.08011244</td><td>0.008432888</td><td>0.002108222</td><td>0.547435</td><td>0.001405481</td><td>0.05130007</td><td>0.018974</td><td>0.002810963</td><td>0.02951511</td><td>0.007027407</td><td>0.07800422</td><td>0.03513703</td><td>0.007027407</td><td>0.0449754</td><td>0.4567814</td><td>0.02881237</td><td>0.007027407</td><td>0.007027407</td><td>0</td><td>0.004919185</td><td>0.04567814</td><td>0.002108222</td><td>0.09627547</td><td>0.08924807</td><td>0.05481377</td><td>0.0007027407</td><td>0.02037948</td><td>0.002108222</td><td>0.02389318</td><td>0.01475755</td><td>0</td><td>0.01405481</td><td>0.2052003</td><td>0.2368236</td><td>0.007730148</td><td>0.3366128</td><td>0.01405481</td><td>0.01124385</td><td>0.001405481</td><td>0.2108222</td><td>0.01756852</td><td>0.04567814</td><td>0.0154603</td><td>0.004919185</td><td>0.03373155</td><td>0.002810963</td><td>0.03443429</td><td>0.00983837</td><td>0.01264933</td></tr>\n",
       "\t<tr><th scope=row>13</th><td>korean</td><td>0.0373494</td><td>0</td><td>0.001204819</td><td>0</td><td>0.03253012</td><td>0.002409639</td><td>0.02650602</td><td>0.009638554</td><td>0.01204819</td><td>0.004819277</td><td>0.002409639</td><td>0.003614458</td><td>0.07710843</td><td>0.03855422</td><td>0.2</td><td>0.0373494</td><td>0.2313253</td><td>0.004819277</td><td>0.0313253</td><td>0.003614458</td><td>0.01204819</td><td>0.004819277</td><td>0.04457831</td><td>0.2024096</td><td>0.01807229</td><td>0.002409639</td><td>0.1325301</td><td>0.05542169</td><td>0</td><td>0</td><td>0.2168675</td><td>0.01927711</td><td>0.006024096</td><td>0.007228916</td><td>0.01566265</td><td>0</td><td>0.1313253</td><td>0.001204819</td><td>0.09277108</td><td>0.1951807</td><td>0.02409639</td><td>0.002409639</td><td>0</td><td>0.0253012</td><td>0</td><td>0.05421687</td><td>0.01445783</td><td>0.02048193</td><td>0.007228916</td><td>0.2180723</td><td>0.01927711</td><td>0.009638554</td><td>0.02409639</td><td>0</td><td>0</td><td>0.08795181</td><td>0.007228916</td><td>0.07951807</td><td>0</td><td>0.003614458</td><td>0.007228916</td><td>0.001204819</td><td>0</td><td>0.05662651</td><td>0.09759036</td><td>0.001204819</td><td>0.002409639</td><td>0.08313253</td><td>0.001204819</td><td>0.003614458</td><td>0</td><td>0.001204819</td><td>0.003614458</td><td>0.05421687</td><td>0.2048193</td><td>0.004819277</td><td>0</td><td>0.004819277</td><td>0.007228916</td><td>0.004819277</td><td>0</td><td>0</td><td>0.009638554</td><td>0.002409639</td><td>0.04216867</td><td>0.07108434</td><td>0.1795181</td><td>0.004819277</td><td>0.1060241</td><td>0.004819277</td><td>0.2240964</td><td>0.003614458</td><td>0</td><td>0.7698795</td><td>0.3855422</td><td>0.004819277</td><td>0.02891566</td><td>0.001204819</td><td>0.001204819</td><td>0.4192771</td><td>0.2301205</td><td>0.001204819</td><td>0.003614458</td><td>0.003614458</td><td>0.004819277</td><td>0.09638554</td><td>0.04819277</td><td>0.008433735</td><td>0</td><td>0.001204819</td><td>0.01927711</td><td>0.07590361</td><td>0</td><td>0.001204819</td><td>0.01566265</td><td>0.08915663</td><td>0.007228916</td><td>0.0626506</td><td>0.01204819</td><td>0.01325301</td><td>0.04698795</td><td>0.01084337</td><td>0.02409639</td><td>0.002409639</td><td>0.05542169</td><td>0.04337349</td><td>0.01325301</td><td>0.06024096</td><td>0</td><td>0</td><td>0.01084337</td><td>0.02048193</td><td>0.01204819</td><td>0</td><td>0.007228916</td><td>0.1349398</td><td>0</td><td>0.07108434</td><td>0.008433735</td><td>0</td><td>0.001204819</td><td>0.1072289</td><td>0.01566265</td><td>0.06746988</td><td>0</td><td>0.9819277</td><td>0.05060241</td><td>0.753012</td><td>0.009638554</td><td>0</td><td>0.02409639</td><td>0.01325301</td><td>0</td><td>0.003614458</td><td>0.1156627</td><td>0.002409639</td><td>0.01084337</td><td>0.02289157</td><td>0</td><td>0.0253012</td><td>0.6963855</td><td>0.002409639</td><td>0.004819277</td><td>0.002409639</td><td>0.1084337</td><td>0.0626506</td><td>0.07710843</td><td>0.009638554</td><td>0.002409639</td><td>0.2855422</td><td>0.02650602</td><td>0.1096386</td><td>0.4987952</td><td>0</td><td>0.02891566</td><td>0.01927711</td><td>0.001204819</td><td>0</td><td>0</td><td>0.001204819</td><td>0.460241</td><td>0.8144578</td><td>0.004819277</td><td>0.2373494</td><td>0.04337349</td><td>0.01204819</td><td>0.4433735</td><td>0.004819277</td><td>1.080723</td><td>0.008433735</td><td>0.001204819</td><td>0.001204819</td><td>0.01445783</td><td>0.09277108</td><td>0.01084337</td><td>0.02409639</td><td>0.0373494</td><td>0.01325301</td><td>0.02891566</td><td>0.003614458</td><td>0.01084337</td><td>0.1012048</td><td>0</td><td>0.003614458</td><td>0.6554217</td><td>0.001204819</td><td>0.07831325</td><td>0.01807229</td><td>0</td><td>0.05542169</td><td>0.004819277</td><td>0.05662651</td><td>0.1024096</td><td>0.004819277</td><td>0.03975904</td><td>0.5879518</td><td>0.05301205</td><td>0</td><td>0.05542169</td><td>0</td><td>0.006024096</td><td>0.01566265</td><td>0.001204819</td><td>0.2301205</td><td>0.08072289</td><td>0.008433735</td><td>0.01204819</td><td>0</td><td>0.006024096</td><td>0</td><td>0.004819277</td><td>0</td><td>0.004819277</td><td>0.1626506</td><td>0.260241</td><td>0.004819277</td><td>0.3349398</td><td>0</td><td>0.006024096</td><td>0</td><td>0.1783133</td><td>0.006024096</td><td>0.1012048</td><td>0.001204819</td><td>0.002409639</td><td>0.04819277</td><td>0.001204819</td><td>0.01204819</td><td>0.003614458</td><td>0.06506024</td></tr>\n",
       "\t<tr><th scope=row>14</th><td>mexican</td><td>0.05125815</td><td>0.01025163</td><td>0.0128922</td><td>0.01335819</td><td>0.01429015</td><td>0.1713265</td><td>0.006679093</td><td>0.0195713</td><td>0.0397639</td><td>0.003727866</td><td>0.009785648</td><td>0.02920162</td><td>0.2656104</td><td>0</td><td>0.13032</td><td>0.1441441</td><td>0.3487108</td><td>0.00621311</td><td>0.09443927</td><td>0.01693072</td><td>0.1324946</td><td>0.002485244</td><td>0.1332712</td><td>0.0408512</td><td>0.08962411</td><td>0.004659832</td><td>0.02982293</td><td>0.04147251</td><td>0.004193849</td><td>0.0003106555</td><td>0.02625039</td><td>0.06601429</td><td>0.01724138</td><td>0.176297</td><td>0.4622554</td><td>0.01413482</td><td>0.3841255</td><td>0.002485244</td><td>0.2314383</td><td>0.472041</td><td>0</td><td>0.06896552</td><td>0.07844051</td><td>0.003727866</td><td>0.02003728</td><td>0.3226157</td><td>0.02236719</td><td>0.4339857</td><td>0.04954955</td><td>0.1814228</td><td>0.02625039</td><td>0.008387698</td><td>0.005747126</td><td>0.02143523</td><td>0.003106555</td><td>0.1116806</td><td>0.03386145</td><td>0.3342653</td><td>0.006523765</td><td>0.007611059</td><td>0.296676</td><td>0.007145076</td><td>0.006057782</td><td>0.0240758</td><td>0.01056229</td><td>0.3201305</td><td>0.0009319664</td><td>0.007300404</td><td>0.1251942</td><td>0.002951227</td><td>0.002485244</td><td>0.007455732</td><td>0.01926064</td><td>0.1296987</td><td>0.1015843</td><td>0.000621311</td><td>0.0621311</td><td>0.03199751</td><td>0.01615409</td><td>0.0453557</td><td>0.0009319664</td><td>0.006523765</td><td>0.01786269</td><td>0.02236719</td><td>0.002795899</td><td>0.003727866</td><td>0.02081392</td><td>0.004038521</td><td>0.221342</td><td>0.01879466</td><td>0.4168997</td><td>0.05529668</td><td>0</td><td>0.500466</td><td>0.004970488</td><td>0.003106555</td><td>0.01196024</td><td>0.02547375</td><td>0.01025163</td><td>0.3022678</td><td>0.5428705</td><td>0.02795899</td><td>0.004193849</td><td>0.01102827</td><td>0.0001553277</td><td>0.01863933</td><td>0.0537434</td><td>0.01273687</td><td>0.006368437</td><td>0.1326499</td><td>0.1825101</td><td>0.2528736</td><td>0.000621311</td><td>0.06523765</td><td>0.005747126</td><td>0.09583722</td><td>0.001708605</td><td>0.06197577</td><td>0.01755203</td><td>0.03292948</td><td>0.08993476</td><td>0.0004659832</td><td>0.03681267</td><td>0.01164958</td><td>0.07906182</td><td>0.01832867</td><td>0.3550792</td><td>0.03028891</td><td>0.01724138</td><td>0</td><td>0.02578441</td><td>0.01926064</td><td>0.009009009</td><td>0.07766387</td><td>0.06974216</td><td>0.0425598</td><td>0.007766387</td><td>0.0001553277</td><td>0.05327742</td><td>0.0823237</td><td>0.01475614</td><td>0.02345449</td><td>0.007766387</td><td>0.003727866</td><td>0.002329916</td><td>0.462566</td><td>0.286735</td><td>0.6890339</td><td>0.04395775</td><td>0.1407269</td><td>0.000621311</td><td>0.05638397</td><td>0.007921715</td><td>0.02283318</td><td>0.02811432</td><td>0.01227089</td><td>0.004970488</td><td>0.007145076</td><td>0.004193849</td><td>0.01025163</td><td>0.7283318</td><td>0.008543026</td><td>0.01102827</td><td>0.02951227</td><td>0.06150979</td><td>0.03572538</td><td>0.3690587</td><td>0.09599254</td><td>0.01133893</td><td>0.1825101</td><td>0.02935694</td><td>0.007455732</td><td>0.08077043</td><td>0.002485244</td><td>0.03836595</td><td>0.000621311</td><td>0.002485244</td><td>0.001087294</td><td>0.001087294</td><td>0.1992855</td><td>0.6088847</td><td>0.2342342</td><td>0.01491146</td><td>0.02671637</td><td>0.03091022</td><td>0.1040696</td><td>0.04411308</td><td>0.03665735</td><td>0.009319664</td><td>0.007145076</td><td>0.02593973</td><td>0.01910531</td><td>0.002795899</td><td>0.001708605</td><td>0.018484</td><td>0.2261572</td><td>0.02764834</td><td>0.07564461</td><td>0.0509475</td><td>0.02609506</td><td>0.005902454</td><td>0.04551103</td><td>0.03199751</td><td>0.2054986</td><td>0.009474992</td><td>0.002640572</td><td>0.01693072</td><td>0.05607331</td><td>0.01739671</td><td>0.002329916</td><td>0.0100963</td><td>0.009164337</td><td>0.02640572</td><td>0.01087294</td><td>0.03852128</td><td>0.1071761</td><td>0.03510407</td><td>0.007921715</td><td>0.003261883</td><td>0.09894377</td><td>0</td><td>0.01444548</td><td>0.01056229</td><td>0.003727866</td><td>0.002019261</td><td>0.44548</td><td>0.3937558</td><td>0.0007766387</td><td>0.02811432</td><td>0.001553277</td><td>0.02485244</td><td>0.01040696</td><td>0.02329916</td><td>0.1548618</td><td>0.06756757</td><td>0.008698354</td><td>0.1707052</td><td>0.0397639</td><td>0.01770736</td><td>0.0111836</td><td>0.1567257</td><td>0.055452</td><td>0.02485244</td><td>0.01040696</td><td>0.005125815</td><td>0.06927617</td><td>0.01786269</td><td>0.006834421</td><td>0.01071761</td><td>0.02283318</td></tr>\n",
       "\t<tr><th scope=row>15</th><td>moroccan</td><td>0.05359318</td><td>0.05359318</td><td>0.135201</td><td>0.007308161</td><td>0.008526188</td><td>0.002436054</td><td>0.01461632</td><td>0</td><td>0.01339829</td><td>0.006090134</td><td>0.01096224</td><td>0.02801462</td><td>0.07064555</td><td>0</td><td>0.08282582</td><td>0.09378806</td><td>0.3386114</td><td>0.02192448</td><td>0.0682095</td><td>0.02436054</td><td>0.07917174</td><td>0.004872107</td><td>0.2192448</td><td>0.02801462</td><td>0.1339829</td><td>0</td><td>0.004872107</td><td>0.02436054</td><td>0.009744214</td><td>0.03532278</td><td>0.2034105</td><td>0.1729598</td><td>0.04384896</td><td>0.002436054</td><td>0.02923264</td><td>0.01461632</td><td>0.4445798</td><td>0.1607795</td><td>0.02801462</td><td>0.05237515</td><td>0</td><td>0.002436054</td><td>0</td><td>0.002436054</td><td>0</td><td>0.408039</td><td>0.004872107</td><td>0.3483557</td><td>0.5030451</td><td>0.36419</td><td>0.02801462</td><td>0.008526188</td><td>0.001218027</td><td>0.001218027</td><td>0.01096224</td><td>0.05968331</td><td>0.3069428</td><td>0.01096224</td><td>0.00365408</td><td>0.009744214</td><td>0.007308161</td><td>0.008526188</td><td>0.008526188</td><td>0.04384896</td><td>0.009744214</td><td>0.5505481</td><td>0.02801462</td><td>0.001218027</td><td>0.07917174</td><td>0.00365408</td><td>0.007308161</td><td>0.008526188</td><td>0.001218027</td><td>0.2216809</td><td>0.09013398</td><td>0.04263094</td><td>0</td><td>0.1559074</td><td>0.00365408</td><td>0.04872107</td><td>0.03045067</td><td>0.01461632</td><td>0.03288672</td><td>0.03045067</td><td>0.001218027</td><td>0.007308161</td><td>0.04141291</td><td>0.08038977</td><td>0.1096224</td><td>0.03410475</td><td>0.8233861</td><td>0.01096224</td><td>0.007308161</td><td>0.5481121</td><td>0.3495737</td><td>0.06090134</td><td>0.01096224</td><td>0.05602923</td><td>0.02436054</td><td>0.1729598</td><td>1.668697</td><td>0.05237515</td><td>0</td><td>0.001218027</td><td>0</td><td>0.1425091</td><td>0.02557856</td><td>0.002436054</td><td>0.007308161</td><td>0</td><td>0.002436054</td><td>0.3154689</td><td>0.02801462</td><td>0</td><td>0.002436054</td><td>0.1157125</td><td>0.2070646</td><td>0.07673569</td><td>0.09622412</td><td>0.00365408</td><td>0.1169306</td><td>0.004872107</td><td>0.546894</td><td>0.03532278</td><td>0.006090134</td><td>0.004872107</td><td>0.02436054</td><td>0.0499391</td><td>0.006090134</td><td>0.007308161</td><td>0.008526188</td><td>0.01705238</td><td>0.002436054</td><td>0</td><td>0.02436054</td><td>0.04141291</td><td>0.1437272</td><td>0</td><td>0.009744214</td><td>0</td><td>0.001218027</td><td>0.007308161</td><td>0.01096224</td><td>0.006090134</td><td>0.03897686</td><td>0.7771011</td><td>0.8014616</td><td>0.6041413</td><td>0.1084044</td><td>0.01461632</td><td>0.001218027</td><td>0.2959805</td><td>0.00365408</td><td>0.2947625</td><td>0.09744214</td><td>0.006090134</td><td>0.0182704</td><td>0.004872107</td><td>0</td><td>0.0499391</td><td>0.8343484</td><td>0.009744214</td><td>0.02070646</td><td>0.02801462</td><td>0.007308161</td><td>0.09500609</td><td>0.09378806</td><td>0.0816078</td><td>0.1181486</td><td>0.226553</td><td>0.008526188</td><td>0.02070646</td><td>0.02314251</td><td>0.002436054</td><td>0.02192448</td><td>0.009744214</td><td>0.007308161</td><td>0.1534714</td><td>0</td><td>0.001218027</td><td>0.7320341</td><td>0.03045067</td><td>0.01339829</td><td>0.006090134</td><td>0.05115713</td><td>0.007308161</td><td>0.1705238</td><td>0.002436054</td><td>0.02436054</td><td>0.0365408</td><td>0</td><td>0.006090134</td><td>0.01218027</td><td>0</td><td>0.04019488</td><td>0.001218027</td><td>0.009744214</td><td>0.06211937</td><td>0.03897686</td><td>0.03775883</td><td>0</td><td>0.07186358</td><td>0.001218027</td><td>0.004872107</td><td>0.004872107</td><td>0.002436054</td><td>0.01461632</td><td>0.05237515</td><td>0.03532278</td><td>0.002436054</td><td>0.05359318</td><td>0</td><td>0.01583435</td><td>0.08769793</td><td>0.1254568</td><td>0.1583435</td><td>0.1266748</td><td>0</td><td>0.00365408</td><td>0</td><td>0</td><td>0.06333739</td><td>0.02679659</td><td>0.01705238</td><td>0.001218027</td><td>0.3751523</td><td>0</td><td>0.136419</td><td>0.009744214</td><td>0.08891596</td><td>0.05724726</td><td>0.001218027</td><td>0.007308161</td><td>0.1437272</td><td>0.0499391</td><td>0.02436054</td><td>0.3081608</td><td>0.02070646</td><td>0.01461632</td><td>0.002436054</td><td>0.08038977</td><td>0.03410475</td><td>0.06211937</td><td>0</td><td>0.02436054</td><td>0.08038977</td><td>0.04141291</td><td>0.009744214</td><td>0.03897686</td><td>0.04872107</td></tr>\n",
       "\t<tr><th scope=row>16</th><td>russian</td><td>0.2515337</td><td>0.01635992</td><td>0.05316973</td><td>0.008179959</td><td>0.06339468</td><td>0.00408998</td><td>0</td><td>0.02249489</td><td>0.1513292</td><td>0.008179959</td><td>0.01226994</td><td>0.0797546</td><td>0.03680982</td><td>0</td><td>0.1472393</td><td>0.03680982</td><td>0.2167689</td><td>0.02862986</td><td>0.01431493</td><td>0.08384458</td><td>0.02658487</td><td>0</td><td>0.08588957</td><td>0.03067485</td><td>0.4355828</td><td>0.02453988</td><td>0.1431493</td><td>0.01840491</td><td>0.0204499</td><td>0.01226994</td><td>0.1635992</td><td>0.01840491</td><td>0.08179959</td><td>0.008179959</td><td>0.1390593</td><td>0.01840491</td><td>0.08793456</td><td>0.00204499</td><td>0.00408998</td><td>0.01840491</td><td>0</td><td>0.00204499</td><td>0</td><td>0.02862986</td><td>0.03476483</td><td>0.1206544</td><td>0.02862986</td><td>0.01840491</td><td>0.06952965</td><td>0.1411043</td><td>0.02249489</td><td>0.00204499</td><td>0.03885481</td><td>0.0204499</td><td>0.02658487</td><td>0.03067485</td><td>0.01226994</td><td>0.03271984</td><td>0.00204499</td><td>0.008179959</td><td>0.3742331</td><td>0.04907975</td><td>0</td><td>0.00204499</td><td>0.0408998</td><td>0.01022495</td><td>0</td><td>0.0204499</td><td>0.02249489</td><td>0.01840491</td><td>0.2269939</td><td>0.008179959</td><td>0.00408998</td><td>0.1860941</td><td>0.5725971</td><td>0.00408998</td><td>0</td><td>0.01226994</td><td>0.08997955</td><td>0.008179959</td><td>0.01226994</td><td>0.00408998</td><td>0.03476483</td><td>0.02658487</td><td>0</td><td>0.008179959</td><td>0.01226994</td><td>0.02249489</td><td>0.4846626</td><td>0</td><td>0.3271984</td><td>0.0204499</td><td>0</td><td>0.1799591</td><td>0.01840491</td><td>0.03271984</td><td>0.03885481</td><td>0.0204499</td><td>0.00408998</td><td>0.1042945</td><td>0.3251534</td><td>0.01226994</td><td>0.02658487</td><td>0.03680982</td><td>0</td><td>0.04498978</td><td>0.03476483</td><td>0.008179959</td><td>0.00408998</td><td>0</td><td>0.00408998</td><td>0.1308793</td><td>0.00204499</td><td>0</td><td>0.01840491</td><td>0.04703476</td><td>0.006134969</td><td>0.2474438</td><td>0.04703476</td><td>0.01635992</td><td>0.0797546</td><td>0.01840491</td><td>0.206544</td><td>0</td><td>0.00408998</td><td>0.01635992</td><td>0</td><td>0.008179959</td><td>0.01431493</td><td>0.00408998</td><td>0.06339468</td><td>0.02249489</td><td>0.00408998</td><td>0</td><td>0.200409</td><td>0.0204499</td><td>0.008179959</td><td>0</td><td>0.01022495</td><td>0</td><td>0.008179959</td><td>0.09611452</td><td>0.03476483</td><td>0.01635992</td><td>0.01635992</td><td>0.3537832</td><td>0.1349693</td><td>0.4274029</td><td>0.02862986</td><td>0.00408998</td><td>0</td><td>0.0408998</td><td>0.00408998</td><td>0.1206544</td><td>0.03885481</td><td>0.00204499</td><td>0.0408998</td><td>0</td><td>0</td><td>0.02862986</td><td>0.4355828</td><td>0.02453988</td><td>0.03067485</td><td>0.008179959</td><td>0.05316973</td><td>0.2617587</td><td>0.1676892</td><td>0.01635992</td><td>0.08179959</td><td>0.1165644</td><td>0.01022495</td><td>0.03271984</td><td>0.0408998</td><td>0.006134969</td><td>0.008179959</td><td>0.01840491</td><td>0.006134969</td><td>0.008179959</td><td>0.00204499</td><td>0</td><td>0.7055215</td><td>0.06543967</td><td>0.0204499</td><td>0.01840491</td><td>0.02862986</td><td>0.01431493</td><td>0.08793456</td><td>0</td><td>0</td><td>0.01840491</td><td>0.00204499</td><td>0</td><td>0.00408998</td><td>0.00408998</td><td>0.00408998</td><td>0.01840491</td><td>0.008179959</td><td>0.01431493</td><td>0.03067485</td><td>0.03067485</td><td>0.04907975</td><td>0.01635992</td><td>0.01431493</td><td>0.2597137</td><td>0.006134969</td><td>0</td><td>0.008179959</td><td>0.01226994</td><td>0.00408998</td><td>0</td><td>0</td><td>0.02862986</td><td>0.01840491</td><td>0.01635992</td><td>0.0408998</td><td>0.5132924</td><td>0.03680982</td><td>0.006134969</td><td>0.01226994</td><td>0</td><td>0</td><td>0.00204499</td><td>0.02249489</td><td>0.01022495</td><td>0.00408998</td><td>0.1676892</td><td>0.00204499</td><td>0.00204499</td><td>0.01226994</td><td>0</td><td>0.192229</td><td>0.01431493</td><td>0.1288344</td><td>0.1860941</td><td>0.1513292</td><td>0.04498978</td><td>0.3415133</td><td>0.00408998</td><td>0.01635992</td><td>0.03680982</td><td>0.194274</td><td>0.05725971</td><td>0.07770961</td><td>0.01226994</td><td>0.1165644</td><td>0.01840491</td><td>0.02658487</td><td>0.07361963</td><td>0.0204499</td><td>0.00408998</td></tr>\n",
       "\t<tr><th scope=row>17</th><td>southern_us</td><td>0.2831019</td><td>0.01365741</td><td>0.0162037</td><td>0.01412037</td><td>0.0537037</td><td>0.003009259</td><td>0.01111111</td><td>0.09976852</td><td>0.287037</td><td>0.007175926</td><td>0.01898148</td><td>0.04444444</td><td>0.03634259</td><td>0</td><td>0.01990741</td><td>0.07013889</td><td>0.200463</td><td>0.0150463</td><td>0.03009259</td><td>0.05972222</td><td>0.03356481</td><td>0.003009259</td><td>0.09027778</td><td>0.1451389</td><td>0.4944444</td><td>0.1648148</td><td>0.01481481</td><td>0.02662037</td><td>0.001851852</td><td>0.002083333</td><td>0.0349537</td><td>0.07662037</td><td>0.08101852</td><td>0.09328704</td><td>0.2018519</td><td>0.01111111</td><td>0.2134259</td><td>0.000462963</td><td>0.01574074</td><td>0.05069444</td><td>0</td><td>0.006944444</td><td>0.005324074</td><td>0.0212963</td><td>0.02592593</td><td>0.1738426</td><td>0.05277778</td><td>0.01342593</td><td>0.09236111</td><td>0.09166667</td><td>0.01689815</td><td>0.02800926</td><td>0.01550926</td><td>0.02662037</td><td>0.0150463</td><td>0.07199074</td><td>0.003703704</td><td>0.1918981</td><td>0.07361111</td><td>0.01342593</td><td>0.2233796</td><td>0.03888889</td><td>0.003703704</td><td>0.03564815</td><td>0.005787037</td><td>0.01736111</td><td>0.006481481</td><td>0.03912037</td><td>0.03171296</td><td>0.02337963</td><td>0.01018519</td><td>0.004861111</td><td>0.0150463</td><td>0.1159722</td><td>0.3907407</td><td>0.0006944444</td><td>0.0002314815</td><td>0.02268519</td><td>0.1368056</td><td>0.0275463</td><td>0.003009259</td><td>0.0009259259</td><td>0.01689815</td><td>0.02268519</td><td>0.01782407</td><td>0.00162037</td><td>0.03842593</td><td>0.01087963</td><td>0.4275463</td><td>0.01643519</td><td>0.2375</td><td>0.03888889</td><td>0.000462963</td><td>0.2284722</td><td>0.02685185</td><td>0.009490741</td><td>0.06689815</td><td>0.05347222</td><td>0.003240741</td><td>0.1826389</td><td>0.3546296</td><td>0.02962963</td><td>0.05162037</td><td>0.05902778</td><td>0.000462963</td><td>0.04074074</td><td>0.07685185</td><td>0.03518519</td><td>0.01203704</td><td>0.01064815</td><td>0.02546296</td><td>0.1375</td><td>0.0006944444</td><td>0.02708333</td><td>0.02361111</td><td>0.08263889</td><td>0.0006944444</td><td>0.2162037</td><td>0.02638889</td><td>0.003240741</td><td>0.05</td><td>0.004166667</td><td>0.1356481</td><td>0.006712963</td><td>0.01273148</td><td>0.07152778</td><td>0.03912037</td><td>0.01851852</td><td>0.01782407</td><td>0.000462963</td><td>0.04212963</td><td>0.01296296</td><td>0.007638889</td><td>0.001157407</td><td>0.2585648</td><td>0.02453704</td><td>0.02523148</td><td>0</td><td>0.03796296</td><td>0.004398148</td><td>0.003009259</td><td>0.01782407</td><td>0.07777778</td><td>0.001157407</td><td>0.05115741</td><td>0.2953704</td><td>0.09930556</td><td>0.3159722</td><td>0.0474537</td><td>0.01273148</td><td>0.006481481</td><td>0.0625</td><td>0.03148148</td><td>0.0662037</td><td>0.008333333</td><td>0.004166667</td><td>0.04861111</td><td>0.04050926</td><td>0.09930556</td><td>0.008564815</td><td>0.6270833</td><td>0.00625</td><td>0.006944444</td><td>0.006712963</td><td>0.05115741</td><td>0.07268519</td><td>0.3273148</td><td>0.02199074</td><td>0.01111111</td><td>0.1293981</td><td>0.01319444</td><td>0.03101852</td><td>0.03564815</td><td>0.0002314815</td><td>0.02013889</td><td>0.00162037</td><td>0.0125</td><td>0.0002314815</td><td>0.01828704</td><td>0.004166667</td><td>0.7148148</td><td>0.1847222</td><td>0.03541667</td><td>0.01643519</td><td>0.02453704</td><td>0.08449074</td><td>0.02592593</td><td>0.0009259259</td><td>0.003240741</td><td>0.01481481</td><td>0.04907407</td><td>0.01180556</td><td>0.005787037</td><td>0.002314815</td><td>0.008101852</td><td>0.05115741</td><td>0.05023148</td><td>0.02268519</td><td>0.05231481</td><td>0.03587963</td><td>0.1094907</td><td>0.02337963</td><td>0.02060185</td><td>0.03171296</td><td>0.008101852</td><td>0.000462963</td><td>0.004861111</td><td>0.04768519</td><td>0.01736111</td><td>0.0002314815</td><td>0.008333333</td><td>0.03680556</td><td>0.01481481</td><td>0.006481481</td><td>0.02731481</td><td>0.5368056</td><td>0.07314815</td><td>0.02893519</td><td>0.06273148</td><td>0.000462963</td><td>0</td><td>0.01134259</td><td>0.0599537</td><td>0.006712963</td><td>0</td><td>0.1085648</td><td>0.002083333</td><td>0.002083333</td><td>0.01134259</td><td>0.002777778</td><td>0.1527778</td><td>0.01597222</td><td>0.1800926</td><td>0.1523148</td><td>0.10625</td><td>0.007175926</td><td>0.2071759</td><td>0.00625</td><td>0.01087963</td><td>0.05625</td><td>0.19375</td><td>0.07592593</td><td>0.03726852</td><td>0.04212963</td><td>0.009259259</td><td>0.08726852</td><td>0.008564815</td><td>0.0337963</td><td>0.02361111</td><td>0.003240741</td></tr>\n",
       "\t<tr><th scope=row>18</th><td>spanish</td><td>0.05358948</td><td>0.004044489</td><td>0.0950455</td><td>0.005055612</td><td>0.02426694</td><td>0.02325581</td><td>0.01617796</td><td>0.02426694</td><td>0.03336704</td><td>0.02426694</td><td>0.03538928</td><td>0.09403438</td><td>0.06471183</td><td>0</td><td>0.0364004</td><td>0.2679474</td><td>0.2537917</td><td>0.01921132</td><td>0.03336704</td><td>0.1183013</td><td>0.04246714</td><td>0.002022245</td><td>0.1344793</td><td>0.02224469</td><td>0.09302326</td><td>0.003033367</td><td>0.009100101</td><td>0.007077856</td><td>0.02022245</td><td>0.001011122</td><td>0.04550051</td><td>0.04044489</td><td>0.02426694</td><td>0.007077856</td><td>0.08897877</td><td>0.01415571</td><td>0.2649141</td><td>0.02325581</td><td>0.04853387</td><td>0.06875632</td><td>0</td><td>0.005055612</td><td>0.006066734</td><td>0.01617796</td><td>0.006066734</td><td>0.2264914</td><td>0.008088979</td><td>0.08695652</td><td>0.06875632</td><td>0.3852376</td><td>0.01617796</td><td>0.004044489</td><td>0.005055612</td><td>0.01617796</td><td>0.005055612</td><td>0.06673407</td><td>0.01112235</td><td>0.04145602</td><td>0.004044489</td><td>0.008088979</td><td>0.06875632</td><td>0.03538928</td><td>0.005055612</td><td>0.05662285</td><td>0.07886754</td><td>0.07077856</td><td>0.005055612</td><td>0.008088979</td><td>0.07482305</td><td>0.01213347</td><td>0.005055612</td><td>0.006066734</td><td>0.001011122</td><td>0.2780586</td><td>0.2770475</td><td>0.01314459</td><td>0</td><td>0.2578362</td><td>0.03538928</td><td>0.04044489</td><td>0.01718908</td><td>0.004044489</td><td>0.03235592</td><td>0.02325581</td><td>0.001011122</td><td>0.01617796</td><td>0.04448938</td><td>0.08291203</td><td>0.09908999</td><td>0.03235592</td><td>0.4924166</td><td>0.04651163</td><td>0</td><td>0.5672396</td><td>0.01112235</td><td>0.01314459</td><td>0.01011122</td><td>0.03943377</td><td>0.001011122</td><td>0.2608696</td><td>0.3650152</td><td>0.02123357</td><td>0.05358948</td><td>0.0182002</td><td>0</td><td>0.02527806</td><td>0.06066734</td><td>0.02628918</td><td>0.0182002</td><td>0.001011122</td><td>0.03134479</td><td>0.2457027</td><td>0.008088979</td><td>0.009100101</td><td>0.006066734</td><td>0.1233569</td><td>0.007077856</td><td>0.2537917</td><td>0.1314459</td><td>0.004044489</td><td>0.1051567</td><td>0.01112235</td><td>0.2163802</td><td>0.02527806</td><td>0.01314459</td><td>0.008088979</td><td>0.0677452</td><td>0.03741153</td><td>0.01718908</td><td>0</td><td>0.01516684</td><td>0.01213347</td><td>0.03235592</td><td>0.001011122</td><td>0.1081901</td><td>0.06268959</td><td>0.02527806</td><td>0</td><td>0.01112235</td><td>0.001011122</td><td>0.002022245</td><td>0.02426694</td><td>0.01617796</td><td>0.002022245</td><td>0.01617796</td><td>0.7421638</td><td>0.7371082</td><td>0.5217391</td><td>0.1425683</td><td>0.0677452</td><td>0.004044489</td><td>0.19818</td><td>0.01213347</td><td>0.247725</td><td>0.04246714</td><td>0.006066734</td><td>0.07280081</td><td>0</td><td>0.003033367</td><td>0.03033367</td><td>0.9201213</td><td>0.008088979</td><td>0.01011122</td><td>0.05257836</td><td>0.04448938</td><td>0.1678463</td><td>0.05358948</td><td>0.05561173</td><td>0.02831143</td><td>0.4115268</td><td>0.01011122</td><td>0.01415571</td><td>0.1365015</td><td>0.002022245</td><td>0.0586451</td><td>0</td><td>0.02325581</td><td>0.1274014</td><td>0.005055612</td><td>0.01314459</td><td>0.6845298</td><td>0.07785642</td><td>0.08998989</td><td>0.02426694</td><td>0.05257836</td><td>0.009100101</td><td>0.0182002</td><td>0.03336704</td><td>0.001011122</td><td>0.02932255</td><td>0.001011122</td><td>0.005055612</td><td>0.1284125</td><td>0.003033367</td><td>0.005055612</td><td>0.002022245</td><td>0.1223458</td><td>0.03134479</td><td>0.05561173</td><td>0.07583418</td><td>0.0182002</td><td>0.05662285</td><td>0.002022245</td><td>0.01921132</td><td>0.004044489</td><td>0.005055612</td><td>0.01921132</td><td>0.04954499</td><td>0.0273003</td><td>0</td><td>0.003033367</td><td>0.01718908</td><td>0.006066734</td><td>0.03437816</td><td>0.0586451</td><td>0.190091</td><td>0.06066734</td><td>0.01617796</td><td>0.007077856</td><td>0</td><td>0</td><td>0.03134479</td><td>0.07381193</td><td>0.004044489</td><td>0</td><td>0.4408493</td><td>0.008088979</td><td>0.009100101</td><td>0.0182002</td><td>0.003033367</td><td>0.04448938</td><td>0.003033367</td><td>0.04752275</td><td>0.08190091</td><td>0.2163802</td><td>0.008088979</td><td>0.2082912</td><td>0.02932255</td><td>0.004044489</td><td>0.01718908</td><td>0.2497472</td><td>0.03437816</td><td>0.273003</td><td>0.01415571</td><td>0.01213347</td><td>0.06471183</td><td>0.01112235</td><td>0.04145602</td><td>0.03336704</td><td>0.01921132</td></tr>\n",
       "\t<tr><th scope=row>19</th><td>thai</td><td>0.01104613</td><td>0.0006497726</td><td>0.005198181</td><td>0.004548408</td><td>0.01169591</td><td>0.009096816</td><td>0.03638726</td><td>0.0006497726</td><td>0.005198181</td><td>0.00259909</td><td>0.217024</td><td>0.009096816</td><td>0.08836907</td><td>0.09876543</td><td>0.03508772</td><td>0.165692</td><td>0.08252112</td><td>0.008447044</td><td>0.1500975</td><td>0.01039636</td><td>0.2033788</td><td>0.0259909</td><td>0.1325536</td><td>0.2202729</td><td>0.1481481</td><td>0.0006497726</td><td>0.0591293</td><td>0.05003249</td><td>0</td><td>0.01364522</td><td>0.1461988</td><td>0.03443795</td><td>0.01364522</td><td>0</td><td>0.007797271</td><td>0.02209227</td><td>0.4951267</td><td>0.005198181</td><td>0.1851852</td><td>0.3612736</td><td>0.02274204</td><td>0.0006497726</td><td>0</td><td>0.01494477</td><td>0</td><td>0.2306693</td><td>0.009746589</td><td>0.474334</td><td>0.01494477</td><td>0.2319688</td><td>0.007147498</td><td>0.482781</td><td>0.009096816</td><td>0.005847953</td><td>0</td><td>0.1156595</td><td>0.122807</td><td>0.07147498</td><td>0</td><td>0.003898635</td><td>0.02858999</td><td>0.005847953</td><td>0.0006497726</td><td>0.06887589</td><td>0.08122157</td><td>0.05717999</td><td>0.3118908</td><td>0.05588044</td><td>0.007797271</td><td>0.001299545</td><td>0</td><td>0.001299545</td><td>0.007147498</td><td>0.09681611</td><td>0.1358025</td><td>0.02339181</td><td>0</td><td>0.005847953</td><td>0.003898635</td><td>0.03443795</td><td>0.00259909</td><td>0.0006497726</td><td>0.03573749</td><td>0.004548408</td><td>0.05782976</td><td>0.5406108</td><td>0.08901884</td><td>0.0006497726</td><td>0.03508772</td><td>0.01559454</td><td>0.8609487</td><td>0.01819363</td><td>0.001299545</td><td>0.6218324</td><td>0.3385315</td><td>0.006497726</td><td>0.01949318</td><td>0.0214425</td><td>0.001299545</td><td>0.3736192</td><td>0.2527615</td><td>0.03573749</td><td>0</td><td>0.005198181</td><td>0.01104613</td><td>0.05198181</td><td>0.04288499</td><td>0.006497726</td><td>0.001299545</td><td>0.0006497726</td><td>0.0545809</td><td>0.3833658</td><td>0</td><td>0.00259909</td><td>0.01949318</td><td>0.0545809</td><td>0.001949318</td><td>0.09551657</td><td>0.01169591</td><td>0.007147498</td><td>0.3424301</td><td>0.004548408</td><td>0.09811566</td><td>0.01364522</td><td>0.05003249</td><td>0.1195582</td><td>0.7238467</td><td>0.06887589</td><td>0.005198181</td><td>0.001949318</td><td>0.006497726</td><td>0.009096816</td><td>0.04418454</td><td>0</td><td>0.4106563</td><td>0.07927225</td><td>0.1111111</td><td>0.004548408</td><td>0.007147498</td><td>0.0006497726</td><td>0.00259909</td><td>0.0877193</td><td>0.009096816</td><td>0.1676413</td><td>0.006497726</td><td>0.6868096</td><td>0.08122157</td><td>0.454191</td><td>0.02469136</td><td>0.00259909</td><td>0.02988954</td><td>0.01234568</td><td>0.001299545</td><td>0.005198181</td><td>0.3703704</td><td>0.003248863</td><td>0.05782976</td><td>0.4061079</td><td>0</td><td>0.07212476</td><td>0.6250812</td><td>0.02469136</td><td>0.003248863</td><td>0.007147498</td><td>0.05393112</td><td>0.03183886</td><td>0.1137102</td><td>0.0545809</td><td>0.003898635</td><td>0.539961</td><td>0.03768681</td><td>0.01104613</td><td>0.4243015</td><td>0</td><td>0.1189084</td><td>0.05328135</td><td>0</td><td>0.001299545</td><td>0.0006497726</td><td>0.001299545</td><td>0.380117</td><td>1.063028</td><td>0</td><td>0.08966862</td><td>0.03053931</td><td>0.01234568</td><td>0.08836907</td><td>0.03248863</td><td>0.1604938</td><td>0.1585445</td><td>0</td><td>0.004548408</td><td>0.005198181</td><td>0.0259909</td><td>0.00259909</td><td>0.03573749</td><td>0.1903834</td><td>0.14295</td><td>0.06497726</td><td>0.001299545</td><td>0.001949318</td><td>0.1098116</td><td>0.00259909</td><td>0</td><td>0.3287849</td><td>0.005847953</td><td>0.02404159</td><td>0.02988954</td><td>0.0214425</td><td>0.03833658</td><td>0.02079272</td><td>0.04873294</td><td>0.0474334</td><td>0.03118908</td><td>0.07732294</td><td>0.5620533</td><td>0.08317089</td><td>0.007797271</td><td>0.014295</td><td>0</td><td>0.3164392</td><td>0.0402859</td><td>0.00259909</td><td>0.03508772</td><td>0.06887589</td><td>0.09616634</td><td>0.009746589</td><td>0.02534113</td><td>0.01169591</td><td>0.02664068</td><td>0.03573749</td><td>0.07862248</td><td>0.001949318</td><td>0.2690058</td><td>0.151397</td><td>0.005847953</td><td>0.2475634</td><td>0.07407407</td><td>0.007797271</td><td>0.001949318</td><td>0.1312541</td><td>0.008447044</td><td>0.03183886</td><td>0.00259909</td><td>0.001299545</td><td>0.04418454</td><td>0.004548408</td><td>0.0006497726</td><td>0.03573749</td><td>0.02988954</td></tr>\n",
       "\t<tr><th scope=row>20</th><td>vietnamese</td><td>0.01454545</td><td>0.004848485</td><td>0.004848485</td><td>0.004848485</td><td>0.01333333</td><td>0.0169697</td><td>0.02424242</td><td>0.002424242</td><td>0.01090909</td><td>0.001212121</td><td>0.1963636</td><td>0.01090909</td><td>0.1018182</td><td>0.1539394</td><td>0.1333333</td><td>0.04848485</td><td>0.230303</td><td>0.006060606</td><td>0.08</td><td>0.01212121</td><td>0.08363636</td><td>0.01333333</td><td>0.09454545</td><td>0.12</td><td>0.07636364</td><td>0</td><td>0.07393939</td><td>0.1030303</td><td>0</td><td>0.01939394</td><td>0.3078788</td><td>0.01212121</td><td>0.01818182</td><td>0</td><td>0.002424242</td><td>0.002424242</td><td>0.2884848</td><td>0</td><td>0.2060606</td><td>0.3042424</td><td>0.04363636</td><td>0.001212121</td><td>0.001212121</td><td>0.01090909</td><td>0</td><td>0.1939394</td><td>0.01090909</td><td>0.4072727</td><td>0.06545455</td><td>0.2509091</td><td>0.01090909</td><td>0.07515152</td><td>0.01575758</td><td>0.02181818</td><td>0.001212121</td><td>0.08606061</td><td>0.1006061</td><td>0.07272727</td><td>0</td><td>0.01575758</td><td>0.008484848</td><td>0.002424242</td><td>0</td><td>0.04121212</td><td>0.1915152</td><td>0.01090909</td><td>0.03636364</td><td>0.04242424</td><td>0.00969697</td><td>0.001212121</td><td>0.007272727</td><td>0.001212121</td><td>0.006060606</td><td>0.08363636</td><td>0.1139394</td><td>0.007272727</td><td>0</td><td>0.006060606</td><td>0.004848485</td><td>0.0169697</td><td>0.01212121</td><td>0</td><td>0.0230303</td><td>0.008484848</td><td>0.04606061</td><td>0.5939394</td><td>0.04969697</td><td>0.001212121</td><td>0.07151515</td><td>0.006060606</td><td>0.6824242</td><td>0.008484848</td><td>0</td><td>0.6569697</td><td>0.2763636</td><td>0.004848485</td><td>0.02909091</td><td>0.01939394</td><td>0.001212121</td><td>0.2545455</td><td>0.3284848</td><td>0.008484848</td><td>0.006060606</td><td>0.002424242</td><td>0.07636364</td><td>0.04</td><td>0.07030303</td><td>0.01212121</td><td>0.003636364</td><td>0.001212121</td><td>0.07393939</td><td>0.3115152</td><td>0</td><td>0.002424242</td><td>0.007272727</td><td>0.1115152</td><td>0.002424242</td><td>0.0569697</td><td>0.02666667</td><td>0.003636364</td><td>0.3442424</td><td>0.004848485</td><td>0.07272727</td><td>0.007272727</td><td>0.1454545</td><td>0.04727273</td><td>0.4521212</td><td>0.03878788</td><td>0.002424242</td><td>0</td><td>0.04</td><td>0.03878788</td><td>0.05454545</td><td>0</td><td>0.07757576</td><td>0.1042424</td><td>0.2181818</td><td>0.007272727</td><td>0.00969697</td><td>0.001212121</td><td>0</td><td>0.05818182</td><td>0.003636364</td><td>0.2145455</td><td>0.002424242</td><td>0.64</td><td>0.05212121</td><td>0.5006061</td><td>0.0169697</td><td>0</td><td>0.03393939</td><td>0.007272727</td><td>0.001212121</td><td>0.006060606</td><td>0.07878788</td><td>0</td><td>0.02060606</td><td>0.2060606</td><td>0</td><td>0.04121212</td><td>0.6048485</td><td>0.03030303</td><td>0.002424242</td><td>0.007272727</td><td>0.2012121</td><td>0.01818182</td><td>0.09333333</td><td>0.05454545</td><td>0</td><td>0.2133333</td><td>0.02424242</td><td>0.01454545</td><td>0.5781818</td><td>0</td><td>0.09575758</td><td>0.03272727</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0.4848485</td><td>1.140606</td><td>0.01333333</td><td>0.1212121</td><td>0.02424242</td><td>0.01333333</td><td>0.08242424</td><td>0.04484848</td><td>0.1781818</td><td>0.1915152</td><td>0</td><td>0.003636364</td><td>0.002424242</td><td>0.03272727</td><td>0.01939394</td><td>0.05333333</td><td>0.1636364</td><td>0.06060606</td><td>0.05333333</td><td>0</td><td>0.006060606</td><td>0.07878788</td><td>0.006060606</td><td>0.001212121</td><td>0.2860606</td><td>0.004848485</td><td>0.00969697</td><td>0.0230303</td><td>0.03757576</td><td>0.07636364</td><td>0.00969697</td><td>0.08</td><td>0.07878788</td><td>0.07636364</td><td>0.06181818</td><td>0.6618182</td><td>0.03151515</td><td>0.02424242</td><td>0.004848485</td><td>0</td><td>0.1624242</td><td>0.02181818</td><td>0</td><td>0.04484848</td><td>0.06666667</td><td>0.07030303</td><td>0.003636364</td><td>0.01575758</td><td>0.007272727</td><td>0.0230303</td><td>0.04</td><td>0.006060606</td><td>0.004848485</td><td>0.2072727</td><td>0.2363636</td><td>0.02909091</td><td>0.3612121</td><td>0.05212121</td><td>0.00969697</td><td>0</td><td>0.1709091</td><td>0.01333333</td><td>0.04</td><td>0.001212121</td><td>0.002424242</td><td>0.08363636</td><td>0.002424242</td><td>0.008484848</td><td>0.006060606</td><td>0.003636364</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllll}\n",
       "  & Group.1 & all-purpos & allspic & almond & and & appl & avocado & babi & bacon & bake & balsam & basil & bay & bean & beansprout & beef & bell & black & boil & boneless & bread & breast & broccoli & broth & brown & butter & buttermilk & cabbag & canola & caper & cardamom & carrot & cayenn & celeri & cheddar & chees & cherri & chicken & chickpea & chile & chili & chines & chip & chipotl & chive & chocol & chop & cider & cilantro & cinnamon & clove & coars & coconut & cold & condens & confection & cook & coriand & corn & cornmeal & crack & cream & crumb & crumbl & crush & cucumb & cumin & curri & dark & dice & dijon & dill & dough & dress & dri & egg & eggplant & enchilada & extra-virgin & extract & fat & fennel & feta & fillet & fine & firm & fish & flake & flat & flour & free & fresh & frozen & garam & garlic & ginger & golden & granul & grate & greek & green & ground & halv & ham & heavi & hoisin & honey & hot & ice & italian & jack & jalapeno & juic & kalamata & kernel & ketchup & kosher & lamb & larg & leaf & lean & leav & leek & lemon & less & lettuc & light & lime & low & low-fat & masala & mayonais & meat & medium & mexican & milk & minc & mint & mirin & mix & monterey & mozzarella & mushroom & mustard & noodl & nutmeg & oil & oliv & onion & orang & oregano & oyster & paprika & parmesan & parsley & past & pasta & pea & peanut & pecan & peel & pepper & peppercorn & plain & plum & pork & potato & powder & purpl & raisin & red & reduc & rib & rice & ricotta & roast & root & rosemari & saffron & sage & salsa & salt & sauc & sausag & scallion & sea & season & seed & serrano & sesam & shallot & sharp & shell & sherri & shiitak & shoulder & shred & shrimp & skinless & slice & smoke & soda & sodium & soup & sour & soy & spaghetti & spinach & spray & sprig & spring & squash & starch & steak & stick & stock & sugar & sweet & sweeten & syrup & taco & thai & thigh & thyme & toast & tofu & tomato & tortilla & tumer & turkey & turmer & unsalt & unsweeten & vanilla & veget & vinegar & warm & water & wedg & wheat & whip & white & whole & wine & worcestershir & yeast & yellow & yogurt & yolk & zest & zucchini\\\\\n",
       "\\hline\n",
       "\t1 & brazilian & 0.0385439 & 0.002141328 & 0.05139186 & 0.004282655 & 0.02141328 & 0.02141328 & 0.006423983 & 0.06423983 & 0.04068522 & 0 & 0.004282655 & 0.1156317 & 0.1520343 & 0 & 0.06638116 & 0.1713062 & 0.2847966 & 0.00856531 & 0.03426124 & 0.02783726 & 0.03640257 & 0 & 0.07066381 & 0.04496788 & 0.1777302 & 0.004282655 & 0 & 0.02783726 & 0.002141328 & 0 & 0.05567452 & 0.04925054 & 0.01498929 & 0.01070664 & 0.1199143 & 0.01070664 & 0.1627409 & 0 & 0.04925054 & 0.08779443 & 0 & 0.00856531 & 0.01070664 & 0.004282655 & 0.07494647 & 0.1627409 & 0.004282655 & 0.1884368 & 0.02997859 & 0.1970021 & 0.01498929 & 0.3040685 & 0.02569593 & 0.1456103 & 0.002141328 & 0.05995717 & 0.04710921 & 0.07280514 & 0.00856531 & 0.006423983 & 0.07494647 & 0.01927195 & 0 & 0.06852248 & 0.004282655 & 0.0620985 & 0.004282655 & 0.01070664 & 0.04496788 & 0.00856531 & 0 & 0.002141328 & 0 & 0.1327623 & 0.2248394 & 0 & 0 & 0.02783726 & 0.0385439 & 0.01070664 & 0.006423983 & 0 & 0.05353319 & 0.01713062 & 0 & 0.05781585 & 0.07066381 & 0.02141328 & 0.1563169 & 0.01070664 & 0.2847966 & 0.06852248 & 0.002141328 & 0.4154176 & 0.06638116 & 0.002141328 & 0.04496788 & 0.04496788 & 0 & 0.1820128 & 0.2698073 & 0.006423983 & 0.03640257 & 0.01498929 & 0 & 0.02569593 & 0.04710921 & 0.1220557 & 0.01070664 & 0.006423983 & 0.04068522 & 0.2226981 & 0 & 0.00856531 & 0.002141328 & 0.04710921 & 0.004282655 & 0.07066381 & 0.07066381 & 0.002141328 & 0.1349036 & 0.004282655 & 0.07922912 & 0.006423983 & 0.002141328 & 0.03426124 & 0.3511777 & 0.02141328 & 0.01070664 & 0.002141328 & 0.02141328 & 0.006423983 & 0.02141328 & 0 & 0.490364 & 0.03211991 & 0.01498929 & 0 & 0.01284797 & 0.004282655 & 0.01070664 & 0.004282655 & 0.01070664 & 0 & 0.01070664 & 0.5289079 & 0.3104925 & 0.48394 & 0.1070664 & 0.02997859 & 0.002141328 & 0.04068522 & 0.05139186 & 0.117773 & 0.04496788 & 0.002141328 & 0.03426124 & 0.02141328 & 0.006423983 & 0.01284797 & 0.6638116 & 0.002141328 & 0.006423983 & 0.01927195 & 0.07494647 & 0.05567452 & 0.1349036 & 0.01713062 & 0.01284797 & 0.1841542 & 0.004282655 & 0.0385439 & 0.1349036 & 0 & 0.0235546 & 0.00856531 & 0.004282655 & 0.006423983 & 0.002141328 & 0.01498929 & 0.5267666 & 0.07494647 & 0.06423983 & 0.01713062 & 0.04068522 & 0.01498929 & 0.05567452 & 0.01498929 & 0.004282655 & 0.01070664 & 0.002141328 & 0.004282655 & 0.006423983 & 0 & 0.01927195 & 0.03211991 & 0.124197 & 0.02141328 & 0.04710921 & 0.03426124 & 0.01713062 & 0.03426124 & 0.004282655 & 0.01284797 & 0.006423983 & 0 & 0.01284797 & 0.006423983 & 0.002141328 & 0.00856531 & 0.004282655 & 0.04710921 & 0.02569593 & 0.00856531 & 0.0620985 & 0.3211991 & 0.0385439 & 0.130621 & 0.03426124 & 0 & 0.002141328 & 0.01284797 & 0.02783726 & 0.01070664 & 0.002141328 & 0.2847966 & 0.002141328 & 0.006423983 & 0.01070664 & 0.00856531 & 0.05567452 & 0.0620985 & 0.05995717 & 0.09850107 & 0.05567452 & 0.004282655 & 0.2398287 & 0.03211991 & 0.006423983 & 0.00856531 & 0.1948608 & 0.03211991 & 0.06423983 & 0.004282655 & 0.01284797 & 0.07280514 & 0.006423983 & 0.04710921 & 0.01713062 & 0.006423983\\\\\n",
       "\t2 & british & 0.2960199 & 0.03358209 & 0.05472637 & 0.003731343 & 0.03731343 & 0 & 0.002487562 & 0.03109453 & 0.2699005 & 0.02114428 & 0.006218905 & 0.05223881 & 0.01865672 & 0 & 0.1965174 & 0.004975124 & 0.1666667 & 0.02238806 & 0.003731343 & 0.1007463 & 0.004975124 & 0.001243781 & 0.04477612 & 0.1355721 & 0.5422886 & 0.03233831 & 0.01243781 & 0.02238806 & 0.004975124 & 0.002487562 & 0.07587065 & 0.039801 & 0.03233831 & 0.07462687 & 0.1343284 & 0.0199005 & 0.03731343 & 0 & 0.001243781 & 0.009950249 & 0 & 0.004975124 & 0 & 0.02238806 & 0.039801 & 0.08208955 & 0.01119403 & 0.006218905 & 0.08457711 & 0.07089552 & 0.02114428 & 0.007462687 & 0.02736318 & 0.01368159 & 0.02736318 & 0.02860697 & 0.008706468 & 0.07089552 & 0.01368159 & 0.01616915 & 0.3333333 & 0.0460199 & 0.001243781 & 0.008706468 & 0.004975124 & 0.009950249 & 0.02363184 & 0.05472637 & 0.003731343 & 0.02736318 & 0.006218905 & 0.01492537 & 0 & 0.1952736 & 0.5422886 & 0 & 0 & 0.02363184 & 0.1057214 & 0.01243781 & 0.003731343 & 0 & 0.04353234 & 0.01492537 & 0.002487562 & 0.01741294 & 0.01741294 & 0.007462687 & 0.5808458 & 0.01492537 & 0.2238806 & 0.07089552 & 0.002487562 & 0.1169154 & 0.06716418 & 0.0659204 & 0.0460199 & 0.06716418 & 0.004975124 & 0.03233831 & 0.3880597 & 0.004975124 & 0.008706468 & 0.1293532 & 0 & 0.0199005 & 0.0199005 & 0.01865672 & 0.002487562 & 0 & 0.001243781 & 0.08084577 & 0 & 0.001243781 & 0.008706468 & 0.07587065 & 0.01741294 & 0.2039801 & 0.03233831 & 0.02487562 & 0.05970149 & 0.02238806 & 0.1554726 & 0 & 0.003731343 & 0.04975124 & 0.006218905 & 0.009950249 & 0.009950249 & 0.002487562 & 0.008706468 & 0.009950249 & 0.01741294 & 0 & 0.3569652 & 0.0199005 & 0.01741294 & 0 & 0.039801 & 0 & 0 & 0.0721393 & 0.09452736 & 0 & 0.08706468 & 0.25 & 0.09577114 & 0.2674129 & 0.06840796 & 0.009950249 & 0 & 0.02736318 & 0.01368159 & 0.06467662 & 0.03606965 & 0 & 0.03731343 & 0.002487562 & 0.01492537 & 0.04353234 & 0.3432836 & 0.01243781 & 0.04850746 & 0.004975124 & 0.05721393 & 0.1791045 & 0.2649254 & 0.01368159 & 0.07711443 & 0.06218905 & 0.002487562 & 0.0199005 & 0.02860697 & 0 & 0.02238806 & 0.002487562 & 0.02860697 & 0.002487562 & 0.0261194 & 0 & 0.641791 & 0.1032338 & 0.05223881 & 0.004975124 & 0.03233831 & 0.01368159 & 0.02860697 & 0.001243781 & 0.001243781 & 0.02363184 & 0.02487562 & 0.007462687 & 0.02860697 & 0.001243781 & 0.007462687 & 0.01492537 & 0.003731343 & 0.004975124 & 0.02860697 & 0.02114428 & 0.1057214 & 0.01119403 & 0.003731343 & 0.02860697 & 0.006218905 & 0 & 0.006218905 & 0.01492537 & 0.01243781 & 0.004975124 & 0.002487562 & 0.039801 & 0.03233831 & 0.01119403 & 0.06094527 & 0.5646766 & 0.0261194 & 0.01368159 & 0.05099502 & 0 & 0.001243781 & 0 & 0.07711443 & 0.008706468 & 0 & 0.0659204 & 0 & 0.01119403 & 0.002487562 & 0.003731343 & 0.2400498 & 0.002487562 & 0.14801 & 0.10199 & 0.08830846 & 0.01865672 & 0.221393 & 0.009950249 & 0.01865672 & 0.10199 & 0.2089552 & 0.09577114 & 0.08208955 & 0.0659204 & 0.05099502 & 0.03233831 & 0.009950249 & 0.08333333 & 0.0261194 & 0.003731343\\\\\n",
       "\t3 & cajun_creole & 0.1882277 & 0.01164295 & 0.007761966 & 0.02522639 & 0.009055627 & 0.002587322 & 0.01099612 & 0.04010349 & 0.04139715 & 0.005174644 & 0.06080207 & 0.232859 & 0.1060802 & 0 & 0.05109961 & 0.450194 & 0.3208279 & 0.0148771 & 0.09831824 & 0.08602846 & 0.1138422 & 0.001940492 & 0.225097 & 0.07179819 & 0.3221216 & 0.02134541 & 0.009702458 & 0.05433376 & 0.01940492 & 0.0006468305 & 0.03428202 & 0.2580854 & 0.4003881 & 0.01293661 & 0.1125485 & 0.005821475 & 0.4793014 & 0.001940492 & 0.01811125 & 0.09184994 & 0 & 0.003234153 & 0.001940492 & 0.01423027 & 0.007115136 & 0.3518758 & 0.01228978 & 0.01681759 & 0.0297542 & 0.2128072 & 0.01875809 & 0.005821475 & 0.006468305 & 0.01099612 & 0.01681759 & 0.1934023 & 0.006468305 & 0.09379043 & 0.0148771 & 0.01552393 & 0.1332471 & 0.0316947 & 0.003234153 & 0.05756792 & 0 & 0.03686934 & 0.0006468305 & 0.009055627 & 0.1791721 & 0.02134541 & 0.008408797 & 0.003234153 & 0.01164295 & 0.4178525 & 0.1532988 & 0.002587322 & 0 & 0.03040103 & 0.03492885 & 0.03298836 & 0.005821475 & 0.0006468305 & 0.04851229 & 0.02652005 & 0.002587322 & 0.007761966 & 0.04463131 & 0.03234153 & 0.2910737 & 0.02005175 & 0.3531695 & 0.03363519 & 0 & 0.648771 & 0.003880983 & 0.003880983 & 0.03298836 & 0.03751617 & 0 & 0.5905563 & 0.4391979 & 0.03945666 & 0.06080207 & 0.04786546 & 0 & 0.009055627 & 0.1849935 & 0.009702458 & 0.02910737 & 0.01034929 & 0.03234153 & 0.1267788 & 0.001940492 & 0.01746442 & 0.0148771 & 0.0698577 & 0 & 0.1442432 & 0.1021992 & 0.008408797 & 0.1921087 & 0.004527814 & 0.1636481 & 0.01552393 & 0.02587322 & 0.02716688 & 0.0148771 & 0.04915912 & 0.01099612 & 0 & 0.05174644 & 0.04721863 & 0.07050453 & 0.001293661 & 0.106727 & 0.07826649 & 0.001940492 & 0 & 0.0297542 & 0.005174644 & 0.007115136 & 0.05368693 & 0.08602846 & 0.003880983 & 0.01681759 & 0.5310479 & 0.2600259 & 0.8499353 & 0.0232859 & 0.1455369 & 0.01940492 & 0.1694696 & 0.03751617 & 0.2386805 & 0.06403622 & 0.01746442 & 0.02069858 & 0.02005175 & 0.02587322 & 0.02522639 & 1.504528 & 0.01099612 & 0.003880983 & 0.01681759 & 0.03945666 & 0.03751617 & 0.2910737 & 0.02457956 & 0.005821475 & 0.3589909 & 0.0232859 & 0.11837 & 0.347348 & 0.0006468305 & 0.02134541 & 0 & 0.01746442 & 0.001293661 & 0.01034929 & 0.001293661 & 0.6423027 & 0.4301423 & 0.2994825 & 0.06274256 & 0.0232859 & 0.4081501 & 0.02199224 & 0.002587322 & 0.0006468305 & 0.0148771 & 0.004527814 & 0.009702458 & 0.005174644 & 0.0006468305 & 0.003880983 & 0.01617076 & 0.3059508 & 0.08085382 & 0.06468305 & 0.1280724 & 0.01681759 & 0.06921087 & 0.02263907 & 0.01617076 & 0.009055627 & 0.003234153 & 0.01164295 & 0.04851229 & 0.01681759 & 0.001293661 & 0.005174644 & 0.01811125 & 0.01034929 & 0.003880983 & 0.09573092 & 0.2005175 & 0.04915912 & 0.004527814 & 0.01164295 & 0.0006468305 & 0 & 0.03557568 & 0.2768435 & 0.005174644 & 0.0006468305 & 0.4353169 & 0.003880983 & 0.0006468305 & 0.04010349 & 0.0006468305 & 0.07697283 & 0.001940492 & 0.04786546 & 0.202458 & 0.0465718 & 0.01552393 & 0.2199224 & 0.01034929 & 0.003234153 & 0.02652005 & 0.2399741 & 0.04980595 & 0.06791721 & 0.126132 & 0.03622251 & 0.09443726 & 0.001940492 & 0.02199224 & 0.008408797 & 0.008408797\\\\\n",
       "\t4 & chinese & 0.04826038 & 0 & 0.01720913 & 0.01346801 & 0.009726899 & 0.003367003 & 0.03441826 & 0.009726899 & 0.03741115 & 0.01197157 & 0.01271979 & 0.005237561 & 0.1234568 & 0.04077815 & 0.06247662 & 0.0976431 & 0.197905 & 0.02095024 & 0.1462776 & 0.005611672 & 0.1720913 & 0.06397306 & 0.137673 & 0.1358025 & 0.04190049 & 0.000748223 & 0.09390198 & 0.06995885 & 0 & 0.001870557 & 0.1417883 & 0.01346801 & 0.0422746 & 0.000748223 & 0.01234568 & 0.004489338 & 0.4975683 & 0.0003741115 & 0.05499439 & 0.2199776 & 0.2259633 & 0 & 0.0003741115 & 0.02356902 & 0.001496446 & 0.08118219 & 0.01758324 & 0.09165731 & 0.02431725 & 0.1859334 & 0.01646091 & 0.01646091 & 0.03404415 & 0.003367003 & 0.003367003 & 0.1328096 & 0.01870557 & 0.375982 & 0.000748223 & 0.004489338 & 0.02020202 & 0.002244669 & 0.000748223 & 0.0587355 & 0.0228208 & 0.005985784 & 0.008604564 & 0.1361766 & 0.007856341 & 0.002992892 & 0.0003741115 & 0.002992892 & 0.003367003 & 0.147774 & 0.2607557 & 0.01384212 & 0 & 0.004489338 & 0.009352787 & 0.02095024 & 0.005985784 & 0.0003741115 & 0.01683502 & 0.008230453 & 0.04190049 & 0.03329592 & 0.08866442 & 0.000748223 & 0.1402918 & 0.02020202 & 0.3920688 & 0.03554059 & 0.0003741115 & 0.6311261 & 0.5548073 & 0.00261878 & 0.0194538 & 0.01084923 & 0.0003741115 & 0.369248 & 0.2947999 & 0.02731014 & 0.01122334 & 0.002244669 & 0.1219603 & 0.09614665 & 0.04077815 & 0.004115226 & 0.001122334 & 0 & 0.00748223 & 0.08305275 & 0 & 0.003367003 & 0.0490086 & 0.06995885 & 0.004115226 & 0.09577254 & 0.005985784 & 0.01571268 & 0.05798728 & 0.01084923 & 0.03965582 & 0.01608679 & 0.03404415 & 0.1114852 & 0.02955481 & 0.1137299 & 0.0003741115 & 0.0003741115 & 0.004489338 & 0.01758324 & 0.02319491 & 0.0003741115 & 0.02768425 & 0.1215862 & 0.005237561 & 0.01010101 & 0.01234568 & 0 & 0.0003741115 & 0.1335578 & 0.01459035 & 0.1197157 & 0.003741115 & 1.124205 & 0.05649083 & 0.4863449 & 0.07182941 & 0.000748223 & 0.1316872 & 0.005237561 & 0.001496446 & 0.006359895 & 0.08492331 & 0.00261878 & 0.09203143 & 0.1769547 & 0 & 0.07557052 & 0.6483352 & 0.06621773 & 0.005985784 & 0.0130939 & 0.2083801 & 0.01608679 & 0.1735877 & 0.01234568 & 0.001870557 & 0.2835765 & 0.03965582 & 0.02469136 & 0.4672652 & 0.0003741115 & 0.0490086 & 0.05274972 & 0.0003741115 & 0 & 0.001122334 & 0.0003741115 & 0.4627759 & 1.290685 & 0.01122334 & 0.2274598 & 0.02581369 & 0.01421624 & 0.1215862 & 0.005611672 & 0.5566779 & 0.02731014 & 0.0003741115 & 0.00261878 & 0.07369996 & 0.07631874 & 0.01122334 & 0.02731014 & 0.09390198 & 0.1230827 & 0.05125327 & 0.001870557 & 0.01982791 & 0.1709689 & 0.005237561 & 0.005985784 & 0.8395062 & 0.008978676 & 0.01346801 & 0.0194538 & 0.005611672 & 0.06397306 & 0.002244669 & 0.3561541 & 0.0490086 & 0.01870557 & 0.08567153 & 0.5308642 & 0.03142536 & 0.003367003 & 0.009352787 & 0.0003741115 & 0.01459035 & 0.0325477 & 0.003741115 & 0.09315376 & 0.06621773 & 0.04152637 & 0.004489338 & 0 & 0.008604564 & 0.002244669 & 0.01795735 & 0.002992892 & 0.008230453 & 0.2708567 & 0.325477 & 0.01271979 & 0.4223719 & 0.003741115 & 0.008978676 & 0.002244669 & 0.3243547 & 0.01047512 & 0.2592593 & 0.01459035 & 0.01234568 & 0.03105125 & 0.000748223 & 0.007856341 & 0.01234568 & 0.01197157\\\\\n",
       "\t5 & filipino & 0.04370861 & 0.001324503 & 0.002649007 & 0.02251656 & 0.03178808 & 0.00397351 & 0.006622517 & 0.005298013 & 0.0397351 & 0.00397351 & 0.002649007 & 0.1615894 & 0.09271523 & 0.01324503 & 0.1284768 & 0.09271523 & 0.2754967 & 0.00794702 & 0.04900662 & 0.02781457 & 0.05298013 & 0.01192053 & 0.08476821 & 0.1192053 & 0.1165563 & 0 & 0.08874172 & 0.03576159 & 0 & 0.001324503 & 0.1774834 & 0.01059603 & 0.04768212 & 0.01986755 & 0.04635762 & 0.002649007 & 0.3271523 & 0.001324503 & 0.04768212 & 0.08344371 & 0.02384106 & 0 & 0.00397351 & 0.002649007 & 0.005298013 & 0.04635762 & 0.03311258 & 0.02384106 & 0.01059603 & 0.1245033 & 0.006622517 & 0.197351 & 0.006622517 & 0.05562914 & 0.005298013 & 0.1615894 & 0.006622517 & 0.1059603 & 0 & 0.001324503 & 0.07549669 & 0.01721854 & 0 & 0.02781457 & 0.006622517 & 0.01059603 & 0.006622517 & 0.01589404 & 0.009271523 & 0.001324503 & 0 & 0.001324503 & 0.001324503 & 0.04900662 & 0.2397351 & 0.03576159 & 0 & 0.006622517 & 0.0397351 & 0.00397351 & 0.001324503 & 0 & 0.01854305 & 0.009271523 & 0.00794702 & 0.1430464 & 0.03178808 & 0.002649007 & 0.1311258 & 0.002649007 & 0.1019868 & 0.02913907 & 0 & 0.6675497 & 0.1456954 & 0.00397351 & 0.03311258 & 0.01854305 & 0 & 0.2238411 & 0.3562914 & 0.00794702 & 0.009271523 & 0.005298013 & 0.01324503 & 0.01721854 & 0.02649007 & 0.01854305 & 0.002649007 & 0 & 0.01589404 & 0.07682119 & 0 & 0.005298013 & 0.03178808 & 0.02781457 & 0.002649007 & 0.0384106 & 0.03708609 & 0.006622517 & 0.1854305 & 0.00397351 & 0.0807947 & 0.001324503 & 0.005298013 & 0.01589404 & 0.03708609 & 0.02384106 & 0 & 0 & 0.01589404 & 0.03046358 & 0.00794702 & 0 & 0.2529801 & 0.05827815 & 0.001324503 & 0 & 0.001324503 & 0 & 0.001324503 & 0.02781457 & 0.00794702 & 0.06357616 & 0.001324503 & 0.6304636 & 0.07549669 & 0.6172185 & 0.01324503 & 0.006622517 & 0.04370861 & 0.01456954 & 0.002649007 & 0.01456954 & 0.0397351 & 0.00794702 & 0.04238411 & 0.02384106 & 0 & 0.00794702 & 0.6768212 & 0.1192053 & 0.00397351 & 0.005298013 & 0.2807947 & 0.08609272 & 0.1192053 & 0.01721854 & 0.03443709 & 0.09536424 & 0.001324503 & 0.01986755 & 0.1695364 & 0 & 0.00397351 & 0.01456954 & 0 & 0.00397351 & 0 & 0.001324503 & 0.6397351 & 0.6768212 & 0.01854305 & 0.02384106 & 0.01986755 & 0.01986755 & 0.02251656 & 0.001324503 & 0.0397351 & 0.02649007 & 0.001324503 & 0.002649007 & 0.005298013 & 0.01324503 & 0.02516556 & 0.02516556 & 0.09801325 & 0.03178808 & 0.01589404 & 0.006622517 & 0.005298013 & 0.02781457 & 0.002649007 & 0.005298013 & 0.384106 & 0.00397351 & 0.03576159 & 0.005298013 & 0 & 0.04238411 & 0.00794702 & 0.07549669 & 0.01192053 & 0.009271523 & 0.0410596 & 0.4225166 & 0.05430464 & 0.03708609 & 0.00397351 & 0.001324503 & 0.0384106 & 0.0410596 & 0.00794702 & 0.001324503 & 0.01721854 & 0.1615894 & 0.002649007 & 0.001324503 & 0.001324503 & 0.006622517 & 0.009271523 & 0.006622517 & 0.04900662 & 0.1430464 & 0.2278146 & 0.01192053 & 0.4609272 & 0.005298013 & 0.001324503 & 0.001324503 & 0.2066225 & 0.03311258 & 0.02251656 & 0.01192053 & 0.02251656 & 0.04635762 & 0 & 0.02781457 & 0.00397351 & 0.00794702\\\\\n",
       "\t6 & french & 0.2244898 & 0.0143613 & 0.0665155 & 0.006046863 & 0.04799698 & 0.001133787 & 0.01587302 & 0.0547997 & 0.04875283 & 0.01322751 & 0.0600907 & 0.1145125 & 0.09297052 & 0 & 0.06500378 & 0.04232804 & 0.2739985 & 0.01965231 & 0.03023432 & 0.1001512 & 0.04119426 & 0.004913076 & 0.1152683 & 0.04270597 & 0.4391534 & 0.005668934 & 0.007558579 & 0.01058201 & 0.03514739 & 0.003779289 & 0.09637188 & 0.02305367 & 0.06122449 & 0.009070295 & 0.2093726 & 0.02683296 & 0.2025699 & 0.005291005 & 0.003023432 & 0.004157218 & 0.001133787 & 0.005291005 & 0.0003779289 & 0.04157218 & 0.08956916 & 0.1659108 & 0.01247166 & 0.005291005 & 0.04006047 & 0.2033258 & 0.0143613 & 0.008692366 & 0.02191988 & 0.006424792 & 0.03439153 & 0.08730159 & 0.007936508 & 0.05177627 & 0.003779289 & 0.01058201 & 0.2641723 & 0.03061224 & 0.004913076 & 0.009826153 & 0.003401361 & 0.006802721 & 0.004913076 & 0.01814059 & 0.02267574 & 0.0718065 & 0.00718065 & 0.01662887 & 0.004535147 & 0.2736206 & 0.4512472 & 0.01587302 & 0 & 0.09674981 & 0.1103553 & 0.06462585 & 0.03817082 & 0.002645503 & 0.05668934 & 0.03779289 & 0.006424792 & 0.01549509 & 0.009070295 & 0.04799698 & 0.3034769 & 0.03401361 & 0.5506425 & 0.03514739 & 0 & 0.2936508 & 0.01662887 & 0.0170068 & 0.04686319 & 0.1084656 & 0.001889645 & 0.08654573 & 0.3272865 & 0.0260771 & 0.02834467 & 0.09334845 & 0.0003779289 & 0.02721088 & 0.01587302 & 0.03703704 & 0.01511716 & 0.002645503 & 0.0003779289 & 0.1734694 & 0.02040816 & 0.001889645 & 0.0007558579 & 0.0600907 & 0.01284958 & 0.3261527 & 0.1069539 & 0.001889645 & 0.1587302 & 0.05253212 & 0.1991686 & 0.02229781 & 0.02229781 & 0.03514739 & 0.01473923 & 0.0287226 & 0.02910053 & 0 & 0.01776266 & 0.007936508 & 0.006424792 & 0 & 0.1829176 & 0.02343159 & 0.02078609 & 0.0003779289 & 0.009826153 & 0.002267574 & 0.004157218 & 0.08843537 & 0.09637188 & 0.004535147 & 0.05291005 & 0.3877551 & 0.3571429 & 0.2849584 & 0.08956916 & 0.01814059 & 0.003401361 & 0.0143613 & 0.04346183 & 0.1855631 & 0.03703704 & 0.004157218 & 0.01095994 & 0.003023432 & 0.008692366 & 0.03476946 & 0.4591837 & 0.04195011 & 0.008314437 & 0.02834467 & 0.02834467 & 0.1130008 & 0.111867 & 0.02456538 & 0.009070295 & 0.1617536 & 0.02305367 & 0.0313681 & 0.01284958 & 0.005668934 & 0.02305367 & 0.006802721 & 0.04195011 & 0.01889645 & 0.01473923 & 0 & 0.6213152 & 0.03628118 & 0.0117158 & 0.006802721 & 0.07974301 & 0.007936508 & 0.03174603 & 0.0007558579 & 0.001511716 & 0.1216931 & 0.002645503 & 0.0117158 & 0.0287226 & 0.008314437 & 0.009070295 & 0.01965231 & 0.01814059 & 0.02116402 & 0.05404384 & 0.01209373 & 0.006802721 & 0.0457294 & 0.008314437 & 0.02116402 & 0.002645503 & 0.001511716 & 0.0143613 & 0.07671958 & 0.07142857 & 0.001133787 & 0.01133787 & 0.03514739 & 0.02305367 & 0.007936508 & 0.04610733 & 0.4368859 & 0.01209373 & 0.009448224 & 0.02267574 & 0 & 0 & 0.01587302 & 0.2018141 & 0.01247166 & 0.001889645 & 0.1613757 & 0.0003779289 & 0.0003779289 & 0.008314437 & 0.0007558579 & 0.2256236 & 0.02343159 & 0.1523054 & 0.06386999 & 0.1235828 & 0.0170068 & 0.249811 & 0.004535147 & 0.009448224 & 0.09372638 & 0.313681 & 0.07482993 & 0.2505669 & 0.007558579 & 0.0287226 & 0.03552532 & 0.008692366 & 0.1311413 & 0.03817082 & 0.03401361\\\\\n",
       "\t7 & greek & 0.08510638 & 0.02723404 & 0.02468085 & 0.01276596 & 0.004255319 & 0.005106383 & 0.02893617 & 0.002553191 & 0.0587234 & 0.02212766 & 0.06468085 & 0.03234043 & 0.05702128 & 0 & 0.04680851 & 0.1029787 & 0.3387234 & 0.006808511 & 0.0587234 & 0.1055319 & 0.08595745 & 0.002553191 & 0.05957447 & 0.01191489 & 0.1421277 & 0.002553191 & 0.001702128 & 0.01021277 & 0.02553191 & 0.001702128 & 0.02723404 & 0.02468085 & 0.02723404 & 0.005957447 & 0.4919149 & 0.04680851 & 0.1948936 & 0.02723404 & 0.004255319 & 0.01191489 & 0 & 0.007659574 & 0 & 0.01191489 & 0.006808511 & 0.2314894 & 0.005106383 & 0.008510638 & 0.106383 & 0.2748936 & 0.02042553 & 0.002553191 & 0.004255319 & 0.0008510638 & 0.007659574 & 0.09021277 & 0.01361702 & 0.009361702 & 0 & 0.0187234 & 0.04595745 & 0.03404255 & 0.2170213 & 0.03829787 & 0.2246809 & 0.04170213 & 0.002553191 & 0.001702128 & 0.05957447 & 0.01446809 & 0.1480851 & 0.04680851 & 0.0212766 & 0.44 & 0.1753191 & 0.05446809 & 0 & 0.1948936 & 0.02723404 & 0.03914894 & 0.01787234 & 0.3812766 & 0.01787234 & 0.02723404 & 0.0008510638 & 0 & 0.03744681 & 0.05617021 & 0.1157447 & 0.02978723 & 0.7582979 & 0.03659574 & 0 & 0.5361702 & 0.005957447 & 0.005957447 & 0.01446809 & 0.09617021 & 0.1838298 & 0.1395745 & 0.5531915 & 0.02978723 & 0.001702128 & 0.005957447 & 0 & 0.0612766 & 0.01361702 & 0 & 0.01361702 & 0.001702128 & 0.001702128 & 0.3795745 & 0.1310638 & 0.0008510638 & 0.0008510638 & 0.07489362 & 0.1157447 & 0.1268085 & 0.07744681 & 0.01702128 & 0.1208511 & 0.006808511 & 0.5480851 & 0.01021277 & 0.06978723 & 0.01191489 & 0.005106383 & 0.02042553 & 0.03234043 & 0 & 0.01361702 & 0.005957447 & 0.01021277 & 0 & 0.07574468 & 0.06978723 & 0.1429787 & 0 & 0.01106383 & 0.0008510638 & 0.01106383 & 0.02212766 & 0.02297872 & 0.002553191 & 0.04085106 & 0.7021277 & 0.7795745 & 0.4791489 & 0.03914894 & 0.3429787 & 0 & 0.02723404 & 0.04170213 & 0.2195745 & 0.03319149 & 0.03489362 & 0.01021277 & 0.0008510638 & 0.006808511 & 0.02382979 & 0.7361702 & 0.005106383 & 0.1285106 & 0.04425532 & 0.01787234 & 0.08 & 0.08425532 & 0.1582979 & 0.01021277 & 0.2561702 & 0.005106383 & 0.01021277 & 0.05446809 & 0.009361702 & 0.02468085 & 0.001702128 & 0.05361702 & 0.001702128 & 0.002553191 & 0 & 0.6357447 & 0.05276596 & 0.002553191 & 0.01787234 & 0.03319149 & 0.05531915 & 0.02978723 & 0.0008510638 & 0.01021277 & 0.02468085 & 0.001702128 & 0.005106383 & 0.005106383 & 0 & 0.01361702 & 0.01191489 & 0.03404255 & 0.05617021 & 0.0493617 & 0.006808511 & 0.01446809 & 0.02042553 & 0.003404255 & 0.02042553 & 0.005106383 & 0.005106383 & 0.09361702 & 0.07914894 & 0.02297872 & 0.003404255 & 0.005957447 & 0.008510638 & 0.01702128 & 0.02723404 & 0.02042553 & 0.1242553 & 0.01361702 & 0.001702128 & 0.003404255 & 0 & 0 & 0.009361702 & 0.06042553 & 0.005106383 & 0 & 0.4221277 & 0.004255319 & 0 & 0.01191489 & 0.004255319 & 0.05276596 & 0.0008510638 & 0.02978723 & 0.04680851 & 0.146383 & 0.01361702 & 0.1574468 & 0.01617021 & 0.02723404 & 0.002553191 & 0.1489362 & 0.04765957 & 0.1693617 & 0.002553191 & 0.01276596 & 0.03829787 & 0.2382979 & 0.02382979 & 0.05957447 & 0.04170213\\\\\n",
       "\t8 & indian & 0.04995005 & 0.007992008 & 0.04129204 & 0.002664003 & 0.01498501 & 0.001665002 & 0.02364302 & 0 & 0.03663004 & 0.001998002 & 0.004995005 & 0.07692308 & 0.03962704 & 0.0003330003 & 0.01931402 & 0.04995005 & 0.2291042 & 0.01431901 & 0.08424908 & 0.02664003 & 0.08558109 & 0.006327006 & 0.06393606 & 0.07326007 & 0.1428571 & 0.006993007 & 0.01232101 & 0.05361305 & 0 & 0.1958042 & 0.07092907 & 0.1245421 & 0.01132201 & 0.001332001 & 0.02064602 & 0.004329004 & 0.2710623 & 0.06560107 & 0.1252081 & 0.5141525 & 0.0006660007 & 0.000999001 & 0.0006660007 & 0.002331002 & 0.001665002 & 0.2540793 & 0.009324009 & 0.3476523 & 0.1814852 & 0.3010323 & 0.01631702 & 0.2104562 & 0.006327006 & 0.005661006 & 0.001665002 & 0.06959707 & 0.3846154 & 0.02997003 & 0.0003330003 & 0.007326007 & 0.0952381 & 0.008991009 & 0.000999001 & 0.04562105 & 0.03230103 & 0.5204795 & 0.2870463 & 0.004662005 & 0.05228105 & 0.002331002 & 0.001998002 & 0.005328005 & 0.000999001 & 0.07592408 & 0.04428904 & 0.02064602 & 0 & 0.01764902 & 0.006327006 & 0.03829504 & 0.05028305 & 0.001665002 & 0.02297702 & 0.02630703 & 0.01165501 & 0.008991009 & 0.04562105 & 0.002664003 & 0.1768232 & 0.02331002 & 0.5544456 & 0.05661006 & 0.2877123 & 0.5444555 & 0.4911755 & 0.01731602 & 0.006327006 & 0.03163503 & 0.04695305 & 0.3100233 & 0.9297369 & 0.01798202 & 0 & 0.03596404 & 0 & 0.02097902 & 0.02630703 & 0.00965701 & 0.001665002 & 0.0003330003 & 0.04229104 & 0.1994672 & 0 & 0.003330003 & 0.007992008 & 0.08558109 & 0.03696304 & 0.03962704 & 0.04528805 & 0.000999001 & 0.3203463 & 0.001998002 & 0.1958042 & 0.01032301 & 0.003996004 & 0.02630703 & 0.09057609 & 0.01665002 & 0.02930403 & 0.3323343 & 0.004329004 & 0.01132201 & 0.007992008 & 0 & 0.2117882 & 0.05128205 & 0.07425907 & 0 & 0.007992008 & 0.0003330003 & 0.001332001 & 0.01431901 & 0.1751582 & 0.002664003 & 0.02930403 & 0.6763237 & 0.1411921 & 0.6140526 & 0.007659008 & 0.000999001 & 0.0006660007 & 0.08091908 & 0.001332001 & 0.01565102 & 0.2061272 & 0.000999001 & 0.0959041 & 0.03296703 & 0.0006660007 & 0.06227106 & 0.5487845 & 0.05394605 & 0.1378621 & 0.02464202 & 0.008658009 & 0.1598402 & 0.5071595 & 0.05661006 & 0.03896104 & 0.2947053 & 0.006660007 & 0.004662005 & 0.1974692 & 0.001665002 & 0.01798202 & 0.04961705 & 0.0003330003 & 0.03829504 & 0 & 0.0006660007 & 0.7998668 & 0.04695305 & 0.0003330003 & 0.01198801 & 0.03862804 & 0.005328005 & 0.5790876 & 0.04528805 & 0.01665002 & 0.01864802 & 0 & 0.000999001 & 0.001332001 & 0 & 0.00999001 & 0.00965701 & 0.02497502 & 0.07492507 & 0.01931402 & 0.01132201 & 0.01565102 & 0.02197802 & 0.000999001 & 0.009324009 & 0.01165501 & 0 & 0.06093906 & 0.02630703 & 0.01265401 & 0.004662005 & 0.00965701 & 0.01465201 & 0.005661006 & 0.08658009 & 0.03529804 & 0.1774892 & 0.03163503 & 0.007659008 & 0.002331002 & 0 & 0.006660007 & 0.04395604 & 0.006660007 & 0.005661006 & 0.01365301 & 0.4192474 & 0.002664003 & 0.1694972 & 0.003663004 & 0.2437562 & 0.02963703 & 0.01498501 & 0.005994006 & 0.2477522 & 0.05094905 & 0.01998002 & 0.3220113 & 0.01631702 & 0.02830503 & 0.007659008 & 0.08225108 & 0.06227106 & 0.01831502 & 0.0006660007 & 0.02430902 & 0.07359307 & 0.1918082 & 0.000999001 & 0.007326007 & 0.01431901\\\\\n",
       "\t9 & irish & 0.3283358 & 0.02998501 & 0.01949025 & 0.02248876 & 0.04647676 & 0.002998501 & 0.01649175 & 0.09445277 & 0.3823088 & 0.008995502 & 0.004497751 & 0.07646177 & 0.0149925 & 0 & 0.17991 & 0.01649175 & 0.2128936 & 0.02098951 & 0.005997001 & 0.05547226 & 0.007496252 & 0 & 0.09145427 & 0.1124438 & 0.5007496 & 0.143928 & 0.131934 & 0.005997001 & 0.005997001 & 0.007496252 & 0.1814093 & 0.01649175 & 0.06296852 & 0.05847076 & 0.1244378 & 0.017991 & 0.09895052 & 0 & 0.002998501 & 0.004497751 & 0 & 0.01649175 & 0.00149925 & 0.02998501 & 0.05547226 & 0.1289355 & 0.02398801 & 0.007496252 & 0.06446777 & 0.08845577 & 0.01349325 & 0.005997001 & 0.01349325 & 0.01049475 & 0.02398801 & 0.1034483 & 0.002998501 & 0.06446777 & 0 & 0.008995502 & 0.2608696 & 0.01649175 & 0.002998501 & 0.01049475 & 0.007496252 & 0.004497751 & 0 & 0.02848576 & 0.01649175 & 0.02098951 & 0.01049475 & 0.008995502 & 0.004497751 & 0.1649175 & 0.3223388 & 0 & 0 & 0.017991 & 0.06446777 & 0.05247376 & 0.01049475 & 0 & 0.011994 & 0.02248876 & 0.008995502 & 0.00149925 & 0.005997001 & 0.01349325 & 0.5112444 & 0.03448276 & 0.2713643 & 0.03298351 & 0 & 0.1604198 & 0.03898051 & 0.02098951 & 0.06146927 & 0.06596702 & 0.002998501 & 0.1064468 & 0.3328336 & 0.007496252 & 0.02248876 & 0.06896552 & 0 & 0.017991 & 0.011994 & 0.0149925 & 0.007496252 & 0 & 0.004497751 & 0.07496252 & 0 & 0 & 0.002998501 & 0.04947526 & 0.06146927 & 0.1604198 & 0.04647676 & 0.004497751 & 0.08095952 & 0.06146927 & 0.09145427 & 0.011994 & 0.004497751 & 0.03148426 & 0.01049475 & 0.0149925 & 0.06596702 & 0 & 0.011994 & 0.02548726 & 0 & 0 & 0.2788606 & 0.011994 & 0.0149925 & 0 & 0.02998501 & 0 & 0.004497751 & 0.03898051 & 0.06596702 & 0 & 0.05847076 & 0.2068966 & 0.09745127 & 0.3568216 & 0.06746627 & 0.005997001 & 0.004497751 & 0.02398801 & 0.01049475 & 0.1244378 & 0.03448276 & 0.00149925 & 0.03448276 & 0.007496252 & 0.01049475 & 0.02398801 & 0.4257871 & 0.02098951 & 0.01649175 & 0.004497751 & 0.03748126 & 0.4107946 & 0.2473763 & 0.004497751 & 0.07496252 & 0.1064468 & 0.0149925 & 0.01949025 & 0.002998501 & 0 & 0.01649175 & 0.002998501 & 0.02848576 & 0 & 0.01649175 & 0.00149925 & 0.6926537 & 0.06296852 & 0.04647676 & 0.02098951 & 0.02548726 & 0.01349325 & 0.06296852 & 0 & 0.005997001 & 0.01649175 & 0.017991 & 0.002998501 & 0.011994 & 0.002998501 & 0.01949025 & 0.03448276 & 0 & 0.004497751 & 0.02398801 & 0.017991 & 0.1829085 & 0.02698651 & 0.00149925 & 0.04797601 & 0.01049475 & 0 & 0.01049475 & 0.09295352 & 0.01949025 & 0.01049475 & 0.00149925 & 0.01949025 & 0.01049475 & 0.008995502 & 0.07346327 & 0.4587706 & 0.017991 & 0.011994 & 0.01649175 & 0 & 0 & 0 & 0.1034483 & 0.007496252 & 0 & 0.06596702 & 0.00149925 & 0.00149925 & 0.005997001 & 0 & 0.1304348 & 0.0149925 & 0.07646177 & 0.1064468 & 0.06146927 & 0.01049475 & 0.1814093 & 0.005997001 & 0.08245877 & 0.05397301 & 0.1514243 & 0.1034483 & 0.04497751 & 0.03448276 & 0.008995502 & 0.04047976 & 0.017991 & 0.02698651 & 0.02998501 & 0.005997001\\\\\n",
       "\t10 & italian & 0.1172493 & 0.001531003 & 0.03393723 & 0.02143404 & 0.004337841 & 0.003189589 & 0.03023731 & 0.0294718 & 0.03891299 & 0.04746109 & 0.2558051 & 0.0349579 & 0.06149528 & 0.0001275836 & 0.07438122 & 0.09249809 & 0.3155142 & 0.01046185 & 0.05179893 & 0.1122735 & 0.07017096 & 0.02449604 & 0.1287318 & 0.01773412 & 0.2117887 & 0.006124011 & 0.006124011 & 0.005741261 & 0.03967849 & 0.001148252 & 0.05537127 & 0.008292932 & 0.05460577 & 0.01479969 & 0.7454708 & 0.02857872 & 0.2341158 & 0.005230926 & 0.005230926 & 0.01365144 & 0.0003827507 & 0.00357234 & 0.0007655014 & 0.0163307 & 0.02679255 & 0.2010717 & 0.003189589 & 0.006634345 & 0.01607553 & 0.2507017 & 0.01990304 & 0.002934422 & 0.008165348 & 0.006506762 & 0.01212044 & 0.1044909 & 0.002551671 & 0.02781322 & 0.009951518 & 0.01492728 & 0.1268181 & 0.05090584 & 0.01696861 & 0.1120184 & 0.005103343 & 0.004720592 & 0.001148252 & 0.004720592 & 0.06545037 & 0.01365144 & 0.003062006 & 0.02845114 & 0.01658586 & 0.3716509 & 0.2287573 & 0.02908905 & 0 & 0.1737688 & 0.04146466 & 0.04848176 & 0.03227864 & 0.01377903 & 0.02755805 & 0.03368206 & 0.002041337 & 0.003955091 & 0.06825721 & 0.07616739 & 0.1736412 & 0.03151314 & 0.6368972 & 0.04325083 & 0.0001275836 & 0.5324062 & 0.00535851 & 0.00893085 & 0.01454453 & 0.2649911 & 0.001148252 & 0.09645318 & 0.3803266 & 0.03023731 & 0.01237561 & 0.048099 & 0 & 0.01671345 & 0.03176831 & 0.00714468 & 0.1437867 & 0.004848176 & 0.002551671 & 0.1237561 & 0.01990304 & 0.003955091 & 0.00178617 & 0.08497066 & 0.004593008 & 0.1647104 & 0.09300842 & 0.02079612 & 0.1560347 & 0.01352386 & 0.1787446 & 0.02258229 & 0.009441184 & 0.01046185 & 0.006379178 & 0.04159224 & 0.02411329 & 0.0001275836 & 0.008037765 & 0.009823935 & 0.01173769 & 0.0002551671 & 0.09402909 & 0.04950242 & 0.02156162 & 0 & 0.01237561 & 0.002806838 & 0.1593519 & 0.1075529 & 0.01875478 & 0.04006124 & 0.03023731 & 0.6612656 & 0.6362592 & 0.3466446 & 0.03687165 & 0.125925 & 0.001148252 & 0.01135494 & 0.3133452 & 0.2227609 & 0.05741261 & 0.1294973 & 0.0264098 & 0.0006379178 & 0.005486093 & 0.03406481 & 0.7231437 & 0.004848176 & 0.004337841 & 0.04848176 & 0.0294718 & 0.0364889 & 0.09224292 & 0.04478183 & 0.0108446 & 0.2619291 & 0.01569278 & 0.02181679 & 0.04682317 & 0.08484307 & 0.02985455 & 0.0007655014 & 0.06481245 & 0.004720592 & 0.03534065 & 0.001658586 & 0.6247767 & 0.1710896 & 0.07501914 & 0.008037765 & 0.04337841 & 0.07119163 & 0.02283746 & 0.000893085 & 0.002168921 & 0.04031641 & 0.004848176 & 0.0163307 & 0.009951518 & 0.008420515 & 0.003189589 & 0.07540189 & 0.03164072 & 0.0442715 & 0.05600919 & 0.008165348 & 0.009186017 & 0.05294718 & 0.01020669 & 0.01428936 & 0.002934422 & 0.04554733 & 0.07323297 & 0.08254657 & 0.02079612 & 0.0006379178 & 0.0186272 & 0.01097219 & 0.01237561 & 0.003827507 & 0.03444756 & 0.1758102 & 0.02538913 & 0.002041337 & 0.004465425 & 0 & 0.0002551671 & 0.008292932 & 0.06685379 & 0.008037765 & 0.002168921 & 0.4268946 & 0.002168921 & 0.0007655014 & 0.02373054 & 0.0002551671 & 0.07399847 & 0.01186527 & 0.04159224 & 0.06902271 & 0.09874968 & 0.02334779 & 0.1892064 & 0.008037765 & 0.02207196 & 0.03559582 & 0.2181679 & 0.05754019 & 0.1940546 & 0.007655014 & 0.03164072 & 0.04669559 & 0.004337841 & 0.02883389 & 0.03470273 & 0.04337841\\\\\n",
       "\t11 & jamaican & 0.07984791 & 0.3707224 & 0.005703422 & 0.01140684 & 0.01520913 & 0.01140684 & 0.01330798 & 0.01901141 & 0.09315589 & 0.001901141 & 0.01520913 & 0.03992395 & 0.1140684 & 0 & 0.1121673 & 0.1406844 & 0.4220532 & 0.01140684 & 0.06653992 & 0.06653992 & 0.07794677 & 0.001901141 & 0.05513308 & 0.2072243 & 0.1749049 & 0.003802281 & 0.01901141 & 0.01901141 & 0.001901141 & 0.003802281 & 0.09315589 & 0.09505703 & 0.03041825 & 0.003802281 & 0.03231939 & 0.007604563 & 0.338403 & 0 & 0.1121673 & 0.108365 & 0.009505703 & 0.007604563 & 0.005703422 & 0.01330798 & 0.007604563 & 0.1330798 & 0.03231939 & 0.06463878 & 0.2414449 & 0.2756654 & 0.01140684 & 0.2661597 & 0.0608365 & 0.01901141 & 0.001901141 & 0.08745247 & 0.03802281 & 0.04562738 & 0.02471483 & 0.009505703 & 0.04562738 & 0.05893536 & 0 & 0.03041825 & 0.001901141 & 0.05703422 & 0.1444867 & 0.08365019 & 0.03041825 & 0.01140684 & 0.003802281 & 0.01330798 & 0.001901141 & 0.3098859 & 0.1235741 & 0.001901141 & 0 & 0.01140684 & 0.04372624 & 0.02091255 & 0 & 0 & 0.02091255 & 0.02091255 & 0 & 0.02471483 & 0.06463878 & 0.005703422 & 0.2110266 & 0.009505703 & 0.4296578 & 0.01140684 & 0.003802281 & 0.595057 & 0.2357414 & 0.001901141 & 0.02281369 & 0.0608365 & 0.001901141 & 0.2072243 & 1.030418 & 0.02471483 & 0.009505703 & 0.003802281 & 0 & 0.01520913 & 0.1197719 & 0.01901141 & 0.001901141 & 0 & 0.05703422 & 0.2585551 & 0 & 0.001901141 & 0.06273764 & 0.06273764 & 0.001901141 & 0.04562738 & 0.01711027 & 0.01711027 & 0.1121673 & 0.001901141 & 0.04372624 & 0.001901141 & 0.01140684 & 0.04942966 & 0.2908745 & 0.03231939 & 0.003802281 & 0.005703422 & 0.01711027 & 0.03231939 & 0.007604563 & 0 & 0.2775665 & 0.05893536 & 0.003802281 & 0 & 0.01711027 & 0 & 0.007604563 & 0.009505703 & 0.03231939 & 0.005703422 & 0.2281369 & 0.513308 & 0.1387833 & 0.7110266 & 0.08935361 & 0.01330798 & 0.001901141 & 0.05323194 & 0.003802281 & 0.02851711 & 0.03041825 & 0.001901141 & 0.03612167 & 0.01520913 & 0.01520913 & 0.02661597 & 1.171103 & 0.01901141 & 0.02091255 & 0.009505703 & 0.0608365 & 0.1007605 & 0.3840304 & 0.04942966 & 0.02091255 & 0.2338403 & 0.003802281 & 0.005703422 & 0.1273764 & 0 & 0.01711027 & 0.03041825 & 0.01140684 & 0 & 0.01520913 & 0.003802281 & 0.7965779 & 0.3288973 & 0 & 0.2148289 & 0.03992395 & 0.09885932 & 0.03612167 & 0.009505703 & 0.003802281 & 0.01711027 & 0 & 0.001901141 & 0.007604563 & 0 & 0.001901141 & 0.01330798 & 0.03802281 & 0.0608365 & 0.02851711 & 0.01140684 & 0.02661597 & 0.03231939 & 0.003802281 & 0.01711027 & 0.1539924 & 0 & 0.02661597 & 0.03041825 & 0.02091255 & 0.01520913 & 0.01140684 & 0.02091255 & 0.01711027 & 0.01330798 & 0.07224335 & 0.3878327 & 0.0513308 & 0.02281369 & 0.01520913 & 0 & 0 & 0.03231939 & 0.5627376 & 0.005703422 & 0 & 0.161597 & 0.009505703 & 0.02851711 & 0.005703422 & 0.02471483 & 0.03612167 & 0.03041825 & 0.07034221 & 0.230038 & 0.1711027 & 0.009505703 & 0.3992395 & 0.009505703 & 0.003802281 & 0.005703422 & 0.1730038 & 0.01901141 & 0.04562738 & 0.01901141 & 0.02281369 & 0.06653992 & 0.003802281 & 0.003802281 & 0.01330798 & 0.009505703\\\\\n",
       "\t12 & japanese & 0.04848911 & 0.0007027407 & 0.009135629 & 0.003513703 & 0.01264933 & 0.04216444 & 0.02670415 & 0.005621926 & 0.03865074 & 0.002810963 & 0.007027407 & 0.01686578 & 0.03583978 & 0.0154603 & 0.04989459 & 0.03583978 & 0.1082221 & 0.01335207 & 0.0639494 & 0.00983837 & 0.04567814 & 0.01194659 & 0.04708363 & 0.08081518 & 0.07378777 & 0 & 0.07378777 & 0.04427266 & 0 & 0.02670415 & 0.1433591 & 0.01827126 & 0.01335207 & 0.0007027407 & 0.02459592 & 0.006324666 & 0.1939564 & 0.002108222 & 0.01967674 & 0.1278988 & 0.01194659 & 0.0007027407 & 0.0007027407 & 0.02600141 & 0.005621926 & 0.05200281 & 0.005621926 & 0.06535488 & 0.01616304 & 0.08151792 & 0.006324666 & 0.03021785 & 0.0224877 & 0.005621926 & 0.002810963 & 0.05059733 & 0.04567814 & 0.08011244 & 0 & 0.004919185 & 0.04286718 & 0.002810963 & 0 & 0.0154603 & 0.08151792 & 0.04567814 & 0.02529866 & 0.037948 & 0.004216444 & 0.009135629 & 0.003513703 & 0.004216444 & 0.004919185 & 0.08995081 & 0.2347154 & 0.02740689 & 0 & 0.0154603 & 0.01616304 & 0.008432888 & 0.008432888 & 0 & 0.07238229 & 0.01475755 & 0.04778637 & 0.018974 & 0.08432888 & 0.004216444 & 0.1426564 & 0.01054111 & 0.2839072 & 0.03092059 & 0.03232607 & 0.2515812 & 0.3239635 & 0.002108222 & 0.03373155 & 0.01335207 & 0.0007027407 & 0.2319044 & 0.1834153 & 0.005621926 & 0.002810963 & 0.01054111 & 0.006324666 & 0.05551651 & 0.02810963 & 0.00983837 & 0.001405481 & 0.0007027407 & 0.003513703 & 0.1004919 & 0 & 0.003513703 & 0.02600141 & 0.056922 & 0 & 0.08713985 & 0.01264933 & 0.001405481 & 0.07800422 & 0.01335207 & 0.0983837 & 0.002108222 & 0.007730148 & 0.03373155 & 0.0449754 & 0.05551651 & 0.0007027407 & 0.03583978 & 0.03583978 & 0.01967674 & 0.01335207 & 0 & 0.07167955 & 0.03443429 & 0.003513703 & 0.2825018 & 0.01054111 & 0 & 0.002810963 & 0.1033029 & 0.03373155 & 0.09557273 & 0.002108222 & 0.6331694 & 0.056922 & 0.3316936 & 0.02529866 & 0 & 0.009135629 & 0.006324666 & 0.005621926 & 0.007730148 & 0.1293043 & 0.002108222 & 0.05270555 & 0.0224877 & 0.002810963 & 0.04075896 & 0.2740689 & 0.007027407 & 0.01124385 & 0.005621926 & 0.07870696 & 0.06746311 & 0.1658468 & 0.00983837 & 0.002810963 & 0.1257906 & 0.02389318 & 0.009135629 & 0.3893183 & 0.0007027407 & 0.01194659 & 0.03583978 & 0 & 0.004919185 & 0 & 0 & 0.4082923 & 0.6605762 & 0.001405481 & 0.1658468 & 0.05270555 & 0.01686578 & 0.2431483 & 0.001405481 & 0.3654252 & 0.02108222 & 0.0007027407 & 0.005621926 & 0.01054111 & 0.09697822 & 0.006324666 & 0.01967674 & 0.04989459 & 0.04567814 & 0.02881237 & 0.0154603 & 0.01405481 & 0.08011244 & 0.008432888 & 0.002108222 & 0.547435 & 0.001405481 & 0.05130007 & 0.018974 & 0.002810963 & 0.02951511 & 0.007027407 & 0.07800422 & 0.03513703 & 0.007027407 & 0.0449754 & 0.4567814 & 0.02881237 & 0.007027407 & 0.007027407 & 0 & 0.004919185 & 0.04567814 & 0.002108222 & 0.09627547 & 0.08924807 & 0.05481377 & 0.0007027407 & 0.02037948 & 0.002108222 & 0.02389318 & 0.01475755 & 0 & 0.01405481 & 0.2052003 & 0.2368236 & 0.007730148 & 0.3366128 & 0.01405481 & 0.01124385 & 0.001405481 & 0.2108222 & 0.01756852 & 0.04567814 & 0.0154603 & 0.004919185 & 0.03373155 & 0.002810963 & 0.03443429 & 0.00983837 & 0.01264933\\\\\n",
       "\t13 & korean & 0.0373494 & 0 & 0.001204819 & 0 & 0.03253012 & 0.002409639 & 0.02650602 & 0.009638554 & 0.01204819 & 0.004819277 & 0.002409639 & 0.003614458 & 0.07710843 & 0.03855422 & 0.2 & 0.0373494 & 0.2313253 & 0.004819277 & 0.0313253 & 0.003614458 & 0.01204819 & 0.004819277 & 0.04457831 & 0.2024096 & 0.01807229 & 0.002409639 & 0.1325301 & 0.05542169 & 0 & 0 & 0.2168675 & 0.01927711 & 0.006024096 & 0.007228916 & 0.01566265 & 0 & 0.1313253 & 0.001204819 & 0.09277108 & 0.1951807 & 0.02409639 & 0.002409639 & 0 & 0.0253012 & 0 & 0.05421687 & 0.01445783 & 0.02048193 & 0.007228916 & 0.2180723 & 0.01927711 & 0.009638554 & 0.02409639 & 0 & 0 & 0.08795181 & 0.007228916 & 0.07951807 & 0 & 0.003614458 & 0.007228916 & 0.001204819 & 0 & 0.05662651 & 0.09759036 & 0.001204819 & 0.002409639 & 0.08313253 & 0.001204819 & 0.003614458 & 0 & 0.001204819 & 0.003614458 & 0.05421687 & 0.2048193 & 0.004819277 & 0 & 0.004819277 & 0.007228916 & 0.004819277 & 0 & 0 & 0.009638554 & 0.002409639 & 0.04216867 & 0.07108434 & 0.1795181 & 0.004819277 & 0.1060241 & 0.004819277 & 0.2240964 & 0.003614458 & 0 & 0.7698795 & 0.3855422 & 0.004819277 & 0.02891566 & 0.001204819 & 0.001204819 & 0.4192771 & 0.2301205 & 0.001204819 & 0.003614458 & 0.003614458 & 0.004819277 & 0.09638554 & 0.04819277 & 0.008433735 & 0 & 0.001204819 & 0.01927711 & 0.07590361 & 0 & 0.001204819 & 0.01566265 & 0.08915663 & 0.007228916 & 0.0626506 & 0.01204819 & 0.01325301 & 0.04698795 & 0.01084337 & 0.02409639 & 0.002409639 & 0.05542169 & 0.04337349 & 0.01325301 & 0.06024096 & 0 & 0 & 0.01084337 & 0.02048193 & 0.01204819 & 0 & 0.007228916 & 0.1349398 & 0 & 0.07108434 & 0.008433735 & 0 & 0.001204819 & 0.1072289 & 0.01566265 & 0.06746988 & 0 & 0.9819277 & 0.05060241 & 0.753012 & 0.009638554 & 0 & 0.02409639 & 0.01325301 & 0 & 0.003614458 & 0.1156627 & 0.002409639 & 0.01084337 & 0.02289157 & 0 & 0.0253012 & 0.6963855 & 0.002409639 & 0.004819277 & 0.002409639 & 0.1084337 & 0.0626506 & 0.07710843 & 0.009638554 & 0.002409639 & 0.2855422 & 0.02650602 & 0.1096386 & 0.4987952 & 0 & 0.02891566 & 0.01927711 & 0.001204819 & 0 & 0 & 0.001204819 & 0.460241 & 0.8144578 & 0.004819277 & 0.2373494 & 0.04337349 & 0.01204819 & 0.4433735 & 0.004819277 & 1.080723 & 0.008433735 & 0.001204819 & 0.001204819 & 0.01445783 & 0.09277108 & 0.01084337 & 0.02409639 & 0.0373494 & 0.01325301 & 0.02891566 & 0.003614458 & 0.01084337 & 0.1012048 & 0 & 0.003614458 & 0.6554217 & 0.001204819 & 0.07831325 & 0.01807229 & 0 & 0.05542169 & 0.004819277 & 0.05662651 & 0.1024096 & 0.004819277 & 0.03975904 & 0.5879518 & 0.05301205 & 0 & 0.05542169 & 0 & 0.006024096 & 0.01566265 & 0.001204819 & 0.2301205 & 0.08072289 & 0.008433735 & 0.01204819 & 0 & 0.006024096 & 0 & 0.004819277 & 0 & 0.004819277 & 0.1626506 & 0.260241 & 0.004819277 & 0.3349398 & 0 & 0.006024096 & 0 & 0.1783133 & 0.006024096 & 0.1012048 & 0.001204819 & 0.002409639 & 0.04819277 & 0.001204819 & 0.01204819 & 0.003614458 & 0.06506024\\\\\n",
       "\t14 & mexican & 0.05125815 & 0.01025163 & 0.0128922 & 0.01335819 & 0.01429015 & 0.1713265 & 0.006679093 & 0.0195713 & 0.0397639 & 0.003727866 & 0.009785648 & 0.02920162 & 0.2656104 & 0 & 0.13032 & 0.1441441 & 0.3487108 & 0.00621311 & 0.09443927 & 0.01693072 & 0.1324946 & 0.002485244 & 0.1332712 & 0.0408512 & 0.08962411 & 0.004659832 & 0.02982293 & 0.04147251 & 0.004193849 & 0.0003106555 & 0.02625039 & 0.06601429 & 0.01724138 & 0.176297 & 0.4622554 & 0.01413482 & 0.3841255 & 0.002485244 & 0.2314383 & 0.472041 & 0 & 0.06896552 & 0.07844051 & 0.003727866 & 0.02003728 & 0.3226157 & 0.02236719 & 0.4339857 & 0.04954955 & 0.1814228 & 0.02625039 & 0.008387698 & 0.005747126 & 0.02143523 & 0.003106555 & 0.1116806 & 0.03386145 & 0.3342653 & 0.006523765 & 0.007611059 & 0.296676 & 0.007145076 & 0.006057782 & 0.0240758 & 0.01056229 & 0.3201305 & 0.0009319664 & 0.007300404 & 0.1251942 & 0.002951227 & 0.002485244 & 0.007455732 & 0.01926064 & 0.1296987 & 0.1015843 & 0.000621311 & 0.0621311 & 0.03199751 & 0.01615409 & 0.0453557 & 0.0009319664 & 0.006523765 & 0.01786269 & 0.02236719 & 0.002795899 & 0.003727866 & 0.02081392 & 0.004038521 & 0.221342 & 0.01879466 & 0.4168997 & 0.05529668 & 0 & 0.500466 & 0.004970488 & 0.003106555 & 0.01196024 & 0.02547375 & 0.01025163 & 0.3022678 & 0.5428705 & 0.02795899 & 0.004193849 & 0.01102827 & 0.0001553277 & 0.01863933 & 0.0537434 & 0.01273687 & 0.006368437 & 0.1326499 & 0.1825101 & 0.2528736 & 0.000621311 & 0.06523765 & 0.005747126 & 0.09583722 & 0.001708605 & 0.06197577 & 0.01755203 & 0.03292948 & 0.08993476 & 0.0004659832 & 0.03681267 & 0.01164958 & 0.07906182 & 0.01832867 & 0.3550792 & 0.03028891 & 0.01724138 & 0 & 0.02578441 & 0.01926064 & 0.009009009 & 0.07766387 & 0.06974216 & 0.0425598 & 0.007766387 & 0.0001553277 & 0.05327742 & 0.0823237 & 0.01475614 & 0.02345449 & 0.007766387 & 0.003727866 & 0.002329916 & 0.462566 & 0.286735 & 0.6890339 & 0.04395775 & 0.1407269 & 0.000621311 & 0.05638397 & 0.007921715 & 0.02283318 & 0.02811432 & 0.01227089 & 0.004970488 & 0.007145076 & 0.004193849 & 0.01025163 & 0.7283318 & 0.008543026 & 0.01102827 & 0.02951227 & 0.06150979 & 0.03572538 & 0.3690587 & 0.09599254 & 0.01133893 & 0.1825101 & 0.02935694 & 0.007455732 & 0.08077043 & 0.002485244 & 0.03836595 & 0.000621311 & 0.002485244 & 0.001087294 & 0.001087294 & 0.1992855 & 0.6088847 & 0.2342342 & 0.01491146 & 0.02671637 & 0.03091022 & 0.1040696 & 0.04411308 & 0.03665735 & 0.009319664 & 0.007145076 & 0.02593973 & 0.01910531 & 0.002795899 & 0.001708605 & 0.018484 & 0.2261572 & 0.02764834 & 0.07564461 & 0.0509475 & 0.02609506 & 0.005902454 & 0.04551103 & 0.03199751 & 0.2054986 & 0.009474992 & 0.002640572 & 0.01693072 & 0.05607331 & 0.01739671 & 0.002329916 & 0.0100963 & 0.009164337 & 0.02640572 & 0.01087294 & 0.03852128 & 0.1071761 & 0.03510407 & 0.007921715 & 0.003261883 & 0.09894377 & 0 & 0.01444548 & 0.01056229 & 0.003727866 & 0.002019261 & 0.44548 & 0.3937558 & 0.0007766387 & 0.02811432 & 0.001553277 & 0.02485244 & 0.01040696 & 0.02329916 & 0.1548618 & 0.06756757 & 0.008698354 & 0.1707052 & 0.0397639 & 0.01770736 & 0.0111836 & 0.1567257 & 0.055452 & 0.02485244 & 0.01040696 & 0.005125815 & 0.06927617 & 0.01786269 & 0.006834421 & 0.01071761 & 0.02283318\\\\\n",
       "\t15 & moroccan & 0.05359318 & 0.05359318 & 0.135201 & 0.007308161 & 0.008526188 & 0.002436054 & 0.01461632 & 0 & 0.01339829 & 0.006090134 & 0.01096224 & 0.02801462 & 0.07064555 & 0 & 0.08282582 & 0.09378806 & 0.3386114 & 0.02192448 & 0.0682095 & 0.02436054 & 0.07917174 & 0.004872107 & 0.2192448 & 0.02801462 & 0.1339829 & 0 & 0.004872107 & 0.02436054 & 0.009744214 & 0.03532278 & 0.2034105 & 0.1729598 & 0.04384896 & 0.002436054 & 0.02923264 & 0.01461632 & 0.4445798 & 0.1607795 & 0.02801462 & 0.05237515 & 0 & 0.002436054 & 0 & 0.002436054 & 0 & 0.408039 & 0.004872107 & 0.3483557 & 0.5030451 & 0.36419 & 0.02801462 & 0.008526188 & 0.001218027 & 0.001218027 & 0.01096224 & 0.05968331 & 0.3069428 & 0.01096224 & 0.00365408 & 0.009744214 & 0.007308161 & 0.008526188 & 0.008526188 & 0.04384896 & 0.009744214 & 0.5505481 & 0.02801462 & 0.001218027 & 0.07917174 & 0.00365408 & 0.007308161 & 0.008526188 & 0.001218027 & 0.2216809 & 0.09013398 & 0.04263094 & 0 & 0.1559074 & 0.00365408 & 0.04872107 & 0.03045067 & 0.01461632 & 0.03288672 & 0.03045067 & 0.001218027 & 0.007308161 & 0.04141291 & 0.08038977 & 0.1096224 & 0.03410475 & 0.8233861 & 0.01096224 & 0.007308161 & 0.5481121 & 0.3495737 & 0.06090134 & 0.01096224 & 0.05602923 & 0.02436054 & 0.1729598 & 1.668697 & 0.05237515 & 0 & 0.001218027 & 0 & 0.1425091 & 0.02557856 & 0.002436054 & 0.007308161 & 0 & 0.002436054 & 0.3154689 & 0.02801462 & 0 & 0.002436054 & 0.1157125 & 0.2070646 & 0.07673569 & 0.09622412 & 0.00365408 & 0.1169306 & 0.004872107 & 0.546894 & 0.03532278 & 0.006090134 & 0.004872107 & 0.02436054 & 0.0499391 & 0.006090134 & 0.007308161 & 0.008526188 & 0.01705238 & 0.002436054 & 0 & 0.02436054 & 0.04141291 & 0.1437272 & 0 & 0.009744214 & 0 & 0.001218027 & 0.007308161 & 0.01096224 & 0.006090134 & 0.03897686 & 0.7771011 & 0.8014616 & 0.6041413 & 0.1084044 & 0.01461632 & 0.001218027 & 0.2959805 & 0.00365408 & 0.2947625 & 0.09744214 & 0.006090134 & 0.0182704 & 0.004872107 & 0 & 0.0499391 & 0.8343484 & 0.009744214 & 0.02070646 & 0.02801462 & 0.007308161 & 0.09500609 & 0.09378806 & 0.0816078 & 0.1181486 & 0.226553 & 0.008526188 & 0.02070646 & 0.02314251 & 0.002436054 & 0.02192448 & 0.009744214 & 0.007308161 & 0.1534714 & 0 & 0.001218027 & 0.7320341 & 0.03045067 & 0.01339829 & 0.006090134 & 0.05115713 & 0.007308161 & 0.1705238 & 0.002436054 & 0.02436054 & 0.0365408 & 0 & 0.006090134 & 0.01218027 & 0 & 0.04019488 & 0.001218027 & 0.009744214 & 0.06211937 & 0.03897686 & 0.03775883 & 0 & 0.07186358 & 0.001218027 & 0.004872107 & 0.004872107 & 0.002436054 & 0.01461632 & 0.05237515 & 0.03532278 & 0.002436054 & 0.05359318 & 0 & 0.01583435 & 0.08769793 & 0.1254568 & 0.1583435 & 0.1266748 & 0 & 0.00365408 & 0 & 0 & 0.06333739 & 0.02679659 & 0.01705238 & 0.001218027 & 0.3751523 & 0 & 0.136419 & 0.009744214 & 0.08891596 & 0.05724726 & 0.001218027 & 0.007308161 & 0.1437272 & 0.0499391 & 0.02436054 & 0.3081608 & 0.02070646 & 0.01461632 & 0.002436054 & 0.08038977 & 0.03410475 & 0.06211937 & 0 & 0.02436054 & 0.08038977 & 0.04141291 & 0.009744214 & 0.03897686 & 0.04872107\\\\\n",
       "\t16 & russian & 0.2515337 & 0.01635992 & 0.05316973 & 0.008179959 & 0.06339468 & 0.00408998 & 0 & 0.02249489 & 0.1513292 & 0.008179959 & 0.01226994 & 0.0797546 & 0.03680982 & 0 & 0.1472393 & 0.03680982 & 0.2167689 & 0.02862986 & 0.01431493 & 0.08384458 & 0.02658487 & 0 & 0.08588957 & 0.03067485 & 0.4355828 & 0.02453988 & 0.1431493 & 0.01840491 & 0.0204499 & 0.01226994 & 0.1635992 & 0.01840491 & 0.08179959 & 0.008179959 & 0.1390593 & 0.01840491 & 0.08793456 & 0.00204499 & 0.00408998 & 0.01840491 & 0 & 0.00204499 & 0 & 0.02862986 & 0.03476483 & 0.1206544 & 0.02862986 & 0.01840491 & 0.06952965 & 0.1411043 & 0.02249489 & 0.00204499 & 0.03885481 & 0.0204499 & 0.02658487 & 0.03067485 & 0.01226994 & 0.03271984 & 0.00204499 & 0.008179959 & 0.3742331 & 0.04907975 & 0 & 0.00204499 & 0.0408998 & 0.01022495 & 0 & 0.0204499 & 0.02249489 & 0.01840491 & 0.2269939 & 0.008179959 & 0.00408998 & 0.1860941 & 0.5725971 & 0.00408998 & 0 & 0.01226994 & 0.08997955 & 0.008179959 & 0.01226994 & 0.00408998 & 0.03476483 & 0.02658487 & 0 & 0.008179959 & 0.01226994 & 0.02249489 & 0.4846626 & 0 & 0.3271984 & 0.0204499 & 0 & 0.1799591 & 0.01840491 & 0.03271984 & 0.03885481 & 0.0204499 & 0.00408998 & 0.1042945 & 0.3251534 & 0.01226994 & 0.02658487 & 0.03680982 & 0 & 0.04498978 & 0.03476483 & 0.008179959 & 0.00408998 & 0 & 0.00408998 & 0.1308793 & 0.00204499 & 0 & 0.01840491 & 0.04703476 & 0.006134969 & 0.2474438 & 0.04703476 & 0.01635992 & 0.0797546 & 0.01840491 & 0.206544 & 0 & 0.00408998 & 0.01635992 & 0 & 0.008179959 & 0.01431493 & 0.00408998 & 0.06339468 & 0.02249489 & 0.00408998 & 0 & 0.200409 & 0.0204499 & 0.008179959 & 0 & 0.01022495 & 0 & 0.008179959 & 0.09611452 & 0.03476483 & 0.01635992 & 0.01635992 & 0.3537832 & 0.1349693 & 0.4274029 & 0.02862986 & 0.00408998 & 0 & 0.0408998 & 0.00408998 & 0.1206544 & 0.03885481 & 0.00204499 & 0.0408998 & 0 & 0 & 0.02862986 & 0.4355828 & 0.02453988 & 0.03067485 & 0.008179959 & 0.05316973 & 0.2617587 & 0.1676892 & 0.01635992 & 0.08179959 & 0.1165644 & 0.01022495 & 0.03271984 & 0.0408998 & 0.006134969 & 0.008179959 & 0.01840491 & 0.006134969 & 0.008179959 & 0.00204499 & 0 & 0.7055215 & 0.06543967 & 0.0204499 & 0.01840491 & 0.02862986 & 0.01431493 & 0.08793456 & 0 & 0 & 0.01840491 & 0.00204499 & 0 & 0.00408998 & 0.00408998 & 0.00408998 & 0.01840491 & 0.008179959 & 0.01431493 & 0.03067485 & 0.03067485 & 0.04907975 & 0.01635992 & 0.01431493 & 0.2597137 & 0.006134969 & 0 & 0.008179959 & 0.01226994 & 0.00408998 & 0 & 0 & 0.02862986 & 0.01840491 & 0.01635992 & 0.0408998 & 0.5132924 & 0.03680982 & 0.006134969 & 0.01226994 & 0 & 0 & 0.00204499 & 0.02249489 & 0.01022495 & 0.00408998 & 0.1676892 & 0.00204499 & 0.00204499 & 0.01226994 & 0 & 0.192229 & 0.01431493 & 0.1288344 & 0.1860941 & 0.1513292 & 0.04498978 & 0.3415133 & 0.00408998 & 0.01635992 & 0.03680982 & 0.194274 & 0.05725971 & 0.07770961 & 0.01226994 & 0.1165644 & 0.01840491 & 0.02658487 & 0.07361963 & 0.0204499 & 0.00408998\\\\\n",
       "\t17 & southern_us & 0.2831019 & 0.01365741 & 0.0162037 & 0.01412037 & 0.0537037 & 0.003009259 & 0.01111111 & 0.09976852 & 0.287037 & 0.007175926 & 0.01898148 & 0.04444444 & 0.03634259 & 0 & 0.01990741 & 0.07013889 & 0.200463 & 0.0150463 & 0.03009259 & 0.05972222 & 0.03356481 & 0.003009259 & 0.09027778 & 0.1451389 & 0.4944444 & 0.1648148 & 0.01481481 & 0.02662037 & 0.001851852 & 0.002083333 & 0.0349537 & 0.07662037 & 0.08101852 & 0.09328704 & 0.2018519 & 0.01111111 & 0.2134259 & 0.000462963 & 0.01574074 & 0.05069444 & 0 & 0.006944444 & 0.005324074 & 0.0212963 & 0.02592593 & 0.1738426 & 0.05277778 & 0.01342593 & 0.09236111 & 0.09166667 & 0.01689815 & 0.02800926 & 0.01550926 & 0.02662037 & 0.0150463 & 0.07199074 & 0.003703704 & 0.1918981 & 0.07361111 & 0.01342593 & 0.2233796 & 0.03888889 & 0.003703704 & 0.03564815 & 0.005787037 & 0.01736111 & 0.006481481 & 0.03912037 & 0.03171296 & 0.02337963 & 0.01018519 & 0.004861111 & 0.0150463 & 0.1159722 & 0.3907407 & 0.0006944444 & 0.0002314815 & 0.02268519 & 0.1368056 & 0.0275463 & 0.003009259 & 0.0009259259 & 0.01689815 & 0.02268519 & 0.01782407 & 0.00162037 & 0.03842593 & 0.01087963 & 0.4275463 & 0.01643519 & 0.2375 & 0.03888889 & 0.000462963 & 0.2284722 & 0.02685185 & 0.009490741 & 0.06689815 & 0.05347222 & 0.003240741 & 0.1826389 & 0.3546296 & 0.02962963 & 0.05162037 & 0.05902778 & 0.000462963 & 0.04074074 & 0.07685185 & 0.03518519 & 0.01203704 & 0.01064815 & 0.02546296 & 0.1375 & 0.0006944444 & 0.02708333 & 0.02361111 & 0.08263889 & 0.0006944444 & 0.2162037 & 0.02638889 & 0.003240741 & 0.05 & 0.004166667 & 0.1356481 & 0.006712963 & 0.01273148 & 0.07152778 & 0.03912037 & 0.01851852 & 0.01782407 & 0.000462963 & 0.04212963 & 0.01296296 & 0.007638889 & 0.001157407 & 0.2585648 & 0.02453704 & 0.02523148 & 0 & 0.03796296 & 0.004398148 & 0.003009259 & 0.01782407 & 0.07777778 & 0.001157407 & 0.05115741 & 0.2953704 & 0.09930556 & 0.3159722 & 0.0474537 & 0.01273148 & 0.006481481 & 0.0625 & 0.03148148 & 0.0662037 & 0.008333333 & 0.004166667 & 0.04861111 & 0.04050926 & 0.09930556 & 0.008564815 & 0.6270833 & 0.00625 & 0.006944444 & 0.006712963 & 0.05115741 & 0.07268519 & 0.3273148 & 0.02199074 & 0.01111111 & 0.1293981 & 0.01319444 & 0.03101852 & 0.03564815 & 0.0002314815 & 0.02013889 & 0.00162037 & 0.0125 & 0.0002314815 & 0.01828704 & 0.004166667 & 0.7148148 & 0.1847222 & 0.03541667 & 0.01643519 & 0.02453704 & 0.08449074 & 0.02592593 & 0.0009259259 & 0.003240741 & 0.01481481 & 0.04907407 & 0.01180556 & 0.005787037 & 0.002314815 & 0.008101852 & 0.05115741 & 0.05023148 & 0.02268519 & 0.05231481 & 0.03587963 & 0.1094907 & 0.02337963 & 0.02060185 & 0.03171296 & 0.008101852 & 0.000462963 & 0.004861111 & 0.04768519 & 0.01736111 & 0.0002314815 & 0.008333333 & 0.03680556 & 0.01481481 & 0.006481481 & 0.02731481 & 0.5368056 & 0.07314815 & 0.02893519 & 0.06273148 & 0.000462963 & 0 & 0.01134259 & 0.0599537 & 0.006712963 & 0 & 0.1085648 & 0.002083333 & 0.002083333 & 0.01134259 & 0.002777778 & 0.1527778 & 0.01597222 & 0.1800926 & 0.1523148 & 0.10625 & 0.007175926 & 0.2071759 & 0.00625 & 0.01087963 & 0.05625 & 0.19375 & 0.07592593 & 0.03726852 & 0.04212963 & 0.009259259 & 0.08726852 & 0.008564815 & 0.0337963 & 0.02361111 & 0.003240741\\\\\n",
       "\t18 & spanish & 0.05358948 & 0.004044489 & 0.0950455 & 0.005055612 & 0.02426694 & 0.02325581 & 0.01617796 & 0.02426694 & 0.03336704 & 0.02426694 & 0.03538928 & 0.09403438 & 0.06471183 & 0 & 0.0364004 & 0.2679474 & 0.2537917 & 0.01921132 & 0.03336704 & 0.1183013 & 0.04246714 & 0.002022245 & 0.1344793 & 0.02224469 & 0.09302326 & 0.003033367 & 0.009100101 & 0.007077856 & 0.02022245 & 0.001011122 & 0.04550051 & 0.04044489 & 0.02426694 & 0.007077856 & 0.08897877 & 0.01415571 & 0.2649141 & 0.02325581 & 0.04853387 & 0.06875632 & 0 & 0.005055612 & 0.006066734 & 0.01617796 & 0.006066734 & 0.2264914 & 0.008088979 & 0.08695652 & 0.06875632 & 0.3852376 & 0.01617796 & 0.004044489 & 0.005055612 & 0.01617796 & 0.005055612 & 0.06673407 & 0.01112235 & 0.04145602 & 0.004044489 & 0.008088979 & 0.06875632 & 0.03538928 & 0.005055612 & 0.05662285 & 0.07886754 & 0.07077856 & 0.005055612 & 0.008088979 & 0.07482305 & 0.01213347 & 0.005055612 & 0.006066734 & 0.001011122 & 0.2780586 & 0.2770475 & 0.01314459 & 0 & 0.2578362 & 0.03538928 & 0.04044489 & 0.01718908 & 0.004044489 & 0.03235592 & 0.02325581 & 0.001011122 & 0.01617796 & 0.04448938 & 0.08291203 & 0.09908999 & 0.03235592 & 0.4924166 & 0.04651163 & 0 & 0.5672396 & 0.01112235 & 0.01314459 & 0.01011122 & 0.03943377 & 0.001011122 & 0.2608696 & 0.3650152 & 0.02123357 & 0.05358948 & 0.0182002 & 0 & 0.02527806 & 0.06066734 & 0.02628918 & 0.0182002 & 0.001011122 & 0.03134479 & 0.2457027 & 0.008088979 & 0.009100101 & 0.006066734 & 0.1233569 & 0.007077856 & 0.2537917 & 0.1314459 & 0.004044489 & 0.1051567 & 0.01112235 & 0.2163802 & 0.02527806 & 0.01314459 & 0.008088979 & 0.0677452 & 0.03741153 & 0.01718908 & 0 & 0.01516684 & 0.01213347 & 0.03235592 & 0.001011122 & 0.1081901 & 0.06268959 & 0.02527806 & 0 & 0.01112235 & 0.001011122 & 0.002022245 & 0.02426694 & 0.01617796 & 0.002022245 & 0.01617796 & 0.7421638 & 0.7371082 & 0.5217391 & 0.1425683 & 0.0677452 & 0.004044489 & 0.19818 & 0.01213347 & 0.247725 & 0.04246714 & 0.006066734 & 0.07280081 & 0 & 0.003033367 & 0.03033367 & 0.9201213 & 0.008088979 & 0.01011122 & 0.05257836 & 0.04448938 & 0.1678463 & 0.05358948 & 0.05561173 & 0.02831143 & 0.4115268 & 0.01011122 & 0.01415571 & 0.1365015 & 0.002022245 & 0.0586451 & 0 & 0.02325581 & 0.1274014 & 0.005055612 & 0.01314459 & 0.6845298 & 0.07785642 & 0.08998989 & 0.02426694 & 0.05257836 & 0.009100101 & 0.0182002 & 0.03336704 & 0.001011122 & 0.02932255 & 0.001011122 & 0.005055612 & 0.1284125 & 0.003033367 & 0.005055612 & 0.002022245 & 0.1223458 & 0.03134479 & 0.05561173 & 0.07583418 & 0.0182002 & 0.05662285 & 0.002022245 & 0.01921132 & 0.004044489 & 0.005055612 & 0.01921132 & 0.04954499 & 0.0273003 & 0 & 0.003033367 & 0.01718908 & 0.006066734 & 0.03437816 & 0.0586451 & 0.190091 & 0.06066734 & 0.01617796 & 0.007077856 & 0 & 0 & 0.03134479 & 0.07381193 & 0.004044489 & 0 & 0.4408493 & 0.008088979 & 0.009100101 & 0.0182002 & 0.003033367 & 0.04448938 & 0.003033367 & 0.04752275 & 0.08190091 & 0.2163802 & 0.008088979 & 0.2082912 & 0.02932255 & 0.004044489 & 0.01718908 & 0.2497472 & 0.03437816 & 0.273003 & 0.01415571 & 0.01213347 & 0.06471183 & 0.01112235 & 0.04145602 & 0.03336704 & 0.01921132\\\\\n",
       "\t19 & thai & 0.01104613 & 0.0006497726 & 0.005198181 & 0.004548408 & 0.01169591 & 0.009096816 & 0.03638726 & 0.0006497726 & 0.005198181 & 0.00259909 & 0.217024 & 0.009096816 & 0.08836907 & 0.09876543 & 0.03508772 & 0.165692 & 0.08252112 & 0.008447044 & 0.1500975 & 0.01039636 & 0.2033788 & 0.0259909 & 0.1325536 & 0.2202729 & 0.1481481 & 0.0006497726 & 0.0591293 & 0.05003249 & 0 & 0.01364522 & 0.1461988 & 0.03443795 & 0.01364522 & 0 & 0.007797271 & 0.02209227 & 0.4951267 & 0.005198181 & 0.1851852 & 0.3612736 & 0.02274204 & 0.0006497726 & 0 & 0.01494477 & 0 & 0.2306693 & 0.009746589 & 0.474334 & 0.01494477 & 0.2319688 & 0.007147498 & 0.482781 & 0.009096816 & 0.005847953 & 0 & 0.1156595 & 0.122807 & 0.07147498 & 0 & 0.003898635 & 0.02858999 & 0.005847953 & 0.0006497726 & 0.06887589 & 0.08122157 & 0.05717999 & 0.3118908 & 0.05588044 & 0.007797271 & 0.001299545 & 0 & 0.001299545 & 0.007147498 & 0.09681611 & 0.1358025 & 0.02339181 & 0 & 0.005847953 & 0.003898635 & 0.03443795 & 0.00259909 & 0.0006497726 & 0.03573749 & 0.004548408 & 0.05782976 & 0.5406108 & 0.08901884 & 0.0006497726 & 0.03508772 & 0.01559454 & 0.8609487 & 0.01819363 & 0.001299545 & 0.6218324 & 0.3385315 & 0.006497726 & 0.01949318 & 0.0214425 & 0.001299545 & 0.3736192 & 0.2527615 & 0.03573749 & 0 & 0.005198181 & 0.01104613 & 0.05198181 & 0.04288499 & 0.006497726 & 0.001299545 & 0.0006497726 & 0.0545809 & 0.3833658 & 0 & 0.00259909 & 0.01949318 & 0.0545809 & 0.001949318 & 0.09551657 & 0.01169591 & 0.007147498 & 0.3424301 & 0.004548408 & 0.09811566 & 0.01364522 & 0.05003249 & 0.1195582 & 0.7238467 & 0.06887589 & 0.005198181 & 0.001949318 & 0.006497726 & 0.009096816 & 0.04418454 & 0 & 0.4106563 & 0.07927225 & 0.1111111 & 0.004548408 & 0.007147498 & 0.0006497726 & 0.00259909 & 0.0877193 & 0.009096816 & 0.1676413 & 0.006497726 & 0.6868096 & 0.08122157 & 0.454191 & 0.02469136 & 0.00259909 & 0.02988954 & 0.01234568 & 0.001299545 & 0.005198181 & 0.3703704 & 0.003248863 & 0.05782976 & 0.4061079 & 0 & 0.07212476 & 0.6250812 & 0.02469136 & 0.003248863 & 0.007147498 & 0.05393112 & 0.03183886 & 0.1137102 & 0.0545809 & 0.003898635 & 0.539961 & 0.03768681 & 0.01104613 & 0.4243015 & 0 & 0.1189084 & 0.05328135 & 0 & 0.001299545 & 0.0006497726 & 0.001299545 & 0.380117 & 1.063028 & 0 & 0.08966862 & 0.03053931 & 0.01234568 & 0.08836907 & 0.03248863 & 0.1604938 & 0.1585445 & 0 & 0.004548408 & 0.005198181 & 0.0259909 & 0.00259909 & 0.03573749 & 0.1903834 & 0.14295 & 0.06497726 & 0.001299545 & 0.001949318 & 0.1098116 & 0.00259909 & 0 & 0.3287849 & 0.005847953 & 0.02404159 & 0.02988954 & 0.0214425 & 0.03833658 & 0.02079272 & 0.04873294 & 0.0474334 & 0.03118908 & 0.07732294 & 0.5620533 & 0.08317089 & 0.007797271 & 0.014295 & 0 & 0.3164392 & 0.0402859 & 0.00259909 & 0.03508772 & 0.06887589 & 0.09616634 & 0.009746589 & 0.02534113 & 0.01169591 & 0.02664068 & 0.03573749 & 0.07862248 & 0.001949318 & 0.2690058 & 0.151397 & 0.005847953 & 0.2475634 & 0.07407407 & 0.007797271 & 0.001949318 & 0.1312541 & 0.008447044 & 0.03183886 & 0.00259909 & 0.001299545 & 0.04418454 & 0.004548408 & 0.0006497726 & 0.03573749 & 0.02988954\\\\\n",
       "\t20 & vietnamese & 0.01454545 & 0.004848485 & 0.004848485 & 0.004848485 & 0.01333333 & 0.0169697 & 0.02424242 & 0.002424242 & 0.01090909 & 0.001212121 & 0.1963636 & 0.01090909 & 0.1018182 & 0.1539394 & 0.1333333 & 0.04848485 & 0.230303 & 0.006060606 & 0.08 & 0.01212121 & 0.08363636 & 0.01333333 & 0.09454545 & 0.12 & 0.07636364 & 0 & 0.07393939 & 0.1030303 & 0 & 0.01939394 & 0.3078788 & 0.01212121 & 0.01818182 & 0 & 0.002424242 & 0.002424242 & 0.2884848 & 0 & 0.2060606 & 0.3042424 & 0.04363636 & 0.001212121 & 0.001212121 & 0.01090909 & 0 & 0.1939394 & 0.01090909 & 0.4072727 & 0.06545455 & 0.2509091 & 0.01090909 & 0.07515152 & 0.01575758 & 0.02181818 & 0.001212121 & 0.08606061 & 0.1006061 & 0.07272727 & 0 & 0.01575758 & 0.008484848 & 0.002424242 & 0 & 0.04121212 & 0.1915152 & 0.01090909 & 0.03636364 & 0.04242424 & 0.00969697 & 0.001212121 & 0.007272727 & 0.001212121 & 0.006060606 & 0.08363636 & 0.1139394 & 0.007272727 & 0 & 0.006060606 & 0.004848485 & 0.0169697 & 0.01212121 & 0 & 0.0230303 & 0.008484848 & 0.04606061 & 0.5939394 & 0.04969697 & 0.001212121 & 0.07151515 & 0.006060606 & 0.6824242 & 0.008484848 & 0 & 0.6569697 & 0.2763636 & 0.004848485 & 0.02909091 & 0.01939394 & 0.001212121 & 0.2545455 & 0.3284848 & 0.008484848 & 0.006060606 & 0.002424242 & 0.07636364 & 0.04 & 0.07030303 & 0.01212121 & 0.003636364 & 0.001212121 & 0.07393939 & 0.3115152 & 0 & 0.002424242 & 0.007272727 & 0.1115152 & 0.002424242 & 0.0569697 & 0.02666667 & 0.003636364 & 0.3442424 & 0.004848485 & 0.07272727 & 0.007272727 & 0.1454545 & 0.04727273 & 0.4521212 & 0.03878788 & 0.002424242 & 0 & 0.04 & 0.03878788 & 0.05454545 & 0 & 0.07757576 & 0.1042424 & 0.2181818 & 0.007272727 & 0.00969697 & 0.001212121 & 0 & 0.05818182 & 0.003636364 & 0.2145455 & 0.002424242 & 0.64 & 0.05212121 & 0.5006061 & 0.0169697 & 0 & 0.03393939 & 0.007272727 & 0.001212121 & 0.006060606 & 0.07878788 & 0 & 0.02060606 & 0.2060606 & 0 & 0.04121212 & 0.6048485 & 0.03030303 & 0.002424242 & 0.007272727 & 0.2012121 & 0.01818182 & 0.09333333 & 0.05454545 & 0 & 0.2133333 & 0.02424242 & 0.01454545 & 0.5781818 & 0 & 0.09575758 & 0.03272727 & 0 & 0 & 0 & 0 & 0.4848485 & 1.140606 & 0.01333333 & 0.1212121 & 0.02424242 & 0.01333333 & 0.08242424 & 0.04484848 & 0.1781818 & 0.1915152 & 0 & 0.003636364 & 0.002424242 & 0.03272727 & 0.01939394 & 0.05333333 & 0.1636364 & 0.06060606 & 0.05333333 & 0 & 0.006060606 & 0.07878788 & 0.006060606 & 0.001212121 & 0.2860606 & 0.004848485 & 0.00969697 & 0.0230303 & 0.03757576 & 0.07636364 & 0.00969697 & 0.08 & 0.07878788 & 0.07636364 & 0.06181818 & 0.6618182 & 0.03151515 & 0.02424242 & 0.004848485 & 0 & 0.1624242 & 0.02181818 & 0 & 0.04484848 & 0.06666667 & 0.07030303 & 0.003636364 & 0.01575758 & 0.007272727 & 0.0230303 & 0.04 & 0.006060606 & 0.004848485 & 0.2072727 & 0.2363636 & 0.02909091 & 0.3612121 & 0.05212121 & 0.00969697 & 0 & 0.1709091 & 0.01333333 & 0.04 & 0.001212121 & 0.002424242 & 0.08363636 & 0.002424242 & 0.008484848 & 0.006060606 & 0.003636364\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "        Group.1 all-purpos      allspic      almond         and        appl\n",
       "1     brazilian 0.03854390 0.0021413276 0.051391863 0.004282655 0.021413276\n",
       "2       british 0.29601990 0.0335820896 0.054726368 0.003731343 0.037313433\n",
       "3  cajun_creole 0.18822768 0.0116429495 0.007761966 0.025226391 0.009055627\n",
       "4       chinese 0.04826038 0.0000000000 0.017209128 0.013468013 0.009726899\n",
       "5      filipino 0.04370861 0.0013245033 0.002649007 0.022516556 0.031788079\n",
       "6        french 0.22448980 0.0143613001 0.066515495 0.006046863 0.047996977\n",
       "7         greek 0.08510638 0.0272340426 0.024680851 0.012765957 0.004255319\n",
       "8        indian 0.04995005 0.0079920080 0.041292041 0.002664003 0.014985015\n",
       "9         irish 0.32833583 0.0299850075 0.019490255 0.022488756 0.046476762\n",
       "10      italian 0.11724930 0.0015310028 0.033937229 0.021434039 0.004337841\n",
       "11     jamaican 0.07984791 0.3707224335 0.005703422 0.011406844 0.015209125\n",
       "12     japanese 0.04848911 0.0007027407 0.009135629 0.003513703 0.012649332\n",
       "13       korean 0.03734940 0.0000000000 0.001204819 0.000000000 0.032530120\n",
       "14      mexican 0.05125815 0.0102516309 0.012892203 0.013358186 0.014290152\n",
       "15     moroccan 0.05359318 0.0535931790 0.135200974 0.007308161 0.008526188\n",
       "16      russian 0.25153374 0.0163599182 0.053169734 0.008179959 0.063394683\n",
       "17  southern_us 0.28310185 0.0136574074 0.016203704 0.014120370 0.053703704\n",
       "18      spanish 0.05358948 0.0040444894 0.095045501 0.005055612 0.024266936\n",
       "19         thai 0.01104613 0.0006497726 0.005198181 0.004548408 0.011695906\n",
       "20   vietnamese 0.01454545 0.0048484848 0.004848485 0.004848485 0.013333333\n",
       "       avocado        babi        bacon        bake      balsam       basil\n",
       "1  0.021413276 0.006423983 0.0642398287 0.040685225 0.000000000 0.004282655\n",
       "2  0.000000000 0.002487562 0.0310945274 0.269900498 0.021144279 0.006218905\n",
       "3  0.002587322 0.010996119 0.0401034929 0.041397154 0.005174644 0.060802070\n",
       "4  0.003367003 0.034418257 0.0097268986 0.037411149 0.011971568 0.012719790\n",
       "5  0.003973510 0.006622517 0.0052980132 0.039735099 0.003973510 0.002649007\n",
       "6  0.001133787 0.015873016 0.0547996977 0.048752834 0.013227513 0.060090703\n",
       "7  0.005106383 0.028936170 0.0025531915 0.058723404 0.022127660 0.064680851\n",
       "8  0.001665002 0.023643024 0.0000000000 0.036630037 0.001998002 0.004995005\n",
       "9  0.002998501 0.016491754 0.0944527736 0.382308846 0.008995502 0.004497751\n",
       "10 0.003189589 0.030237305 0.0294718040 0.038912988 0.047461087 0.255805052\n",
       "11 0.011406844 0.013307985 0.0190114068 0.093155894 0.001901141 0.015209125\n",
       "12 0.042164441 0.026704146 0.0056219255 0.038650738 0.002810963 0.007027407\n",
       "13 0.002409639 0.026506024 0.0096385542 0.012048193 0.004819277 0.002409639\n",
       "14 0.171326499 0.006679093 0.0195712954 0.039763902 0.003727866 0.009785648\n",
       "15 0.002436054 0.014616322 0.0000000000 0.013398295 0.006090134 0.010962241\n",
       "16 0.004089980 0.000000000 0.0224948875 0.151329243 0.008179959 0.012269939\n",
       "17 0.003009259 0.011111111 0.0997685185 0.287037037 0.007175926 0.018981481\n",
       "18 0.023255814 0.016177958 0.0242669363 0.033367037 0.024266936 0.035389282\n",
       "19 0.009096816 0.036387264 0.0006497726 0.005198181 0.002599090 0.217024042\n",
       "20 0.016969697 0.024242424 0.0024242424 0.010909091 0.001212121 0.196363636\n",
       "           bay       bean   beansprout       beef        bell      black\n",
       "1  0.115631692 0.15203426 0.0000000000 0.06638116 0.171306210 0.28479657\n",
       "2  0.052238806 0.01865672 0.0000000000 0.19651741 0.004975124 0.16666667\n",
       "3  0.232858991 0.10608021 0.0000000000 0.05109961 0.450194049 0.32082794\n",
       "4  0.005237561 0.12345679 0.0407781519 0.06247662 0.097643098 0.19790498\n",
       "5  0.161589404 0.09271523 0.0132450331 0.12847682 0.092715232 0.27549669\n",
       "6  0.114512472 0.09297052 0.0000000000 0.06500378 0.042328042 0.27399849\n",
       "7  0.032340426 0.05702128 0.0000000000 0.04680851 0.102978723 0.33872340\n",
       "8  0.076923077 0.03962704 0.0003330003 0.01931402 0.049950050 0.22910423\n",
       "9  0.076461769 0.01499250 0.0000000000 0.17991004 0.016491754 0.21289355\n",
       "10 0.034957897 0.06149528 0.0001275836 0.07438122 0.092498086 0.31551416\n",
       "11 0.039923954 0.11406844 0.0000000000 0.11216730 0.140684411 0.42205323\n",
       "12 0.016865777 0.03583978 0.0154602952 0.04989459 0.035839775 0.10822207\n",
       "13 0.003614458 0.07710843 0.0385542169 0.20000000 0.037349398 0.23132530\n",
       "14 0.029201615 0.26561044 0.0000000000 0.13031998 0.144144144 0.34871078\n",
       "15 0.028014616 0.07064555 0.0000000000 0.08282582 0.093788063 0.33861145\n",
       "16 0.079754601 0.03680982 0.0000000000 0.14723926 0.036809816 0.21676892\n",
       "17 0.044444444 0.03634259 0.0000000000 0.01990741 0.070138889 0.20046296\n",
       "18 0.094034378 0.06471183 0.0000000000 0.03640040 0.267947422 0.25379171\n",
       "19 0.009096816 0.08836907 0.0987654321 0.03508772 0.165692008 0.08252112\n",
       "20 0.010909091 0.10181818 0.1539393939 0.13333333 0.048484848 0.23030303\n",
       "          boil    boneless       bread      breast    broccoli      broth\n",
       "1  0.008565310 0.034261242 0.027837259 0.036402570 0.000000000 0.07066381\n",
       "2  0.022388060 0.003731343 0.100746269 0.004975124 0.001243781 0.04477612\n",
       "3  0.014877102 0.098318241 0.086028461 0.113842173 0.001940492 0.22509702\n",
       "4  0.020950243 0.146277591 0.005611672 0.172091283 0.063973064 0.13767303\n",
       "5  0.007947020 0.049006623 0.027814570 0.052980132 0.011920530 0.08476821\n",
       "6  0.019652305 0.030234316 0.100151172 0.041194255 0.004913076 0.11526833\n",
       "7  0.006808511 0.058723404 0.105531915 0.085957447 0.002553191 0.05957447\n",
       "8  0.014319014 0.084249084 0.026640027 0.085581086 0.006327006 0.06393606\n",
       "9  0.020989505 0.005997001 0.055472264 0.007496252 0.000000000 0.09145427\n",
       "10 0.010461853 0.051798928 0.112273539 0.070170962 0.024496045 0.12873182\n",
       "11 0.011406844 0.066539924 0.066539924 0.077946768 0.001901141 0.05513308\n",
       "12 0.013352073 0.063949403 0.009838370 0.045678145 0.011946592 0.04708363\n",
       "13 0.004819277 0.031325301 0.003614458 0.012048193 0.004819277 0.04457831\n",
       "14 0.006213110 0.094439267 0.016930724 0.132494564 0.002485244 0.13327120\n",
       "15 0.021924482 0.068209501 0.024360536 0.079171742 0.004872107 0.21924482\n",
       "16 0.028629857 0.014314928 0.083844581 0.026584867 0.000000000 0.08588957\n",
       "17 0.015046296 0.030092593 0.059722222 0.033564815 0.003009259 0.09027778\n",
       "18 0.019211325 0.033367037 0.118301314 0.042467139 0.002022245 0.13447927\n",
       "19 0.008447044 0.150097466 0.010396361 0.203378817 0.025990903 0.13255361\n",
       "20 0.006060606 0.080000000 0.012121212 0.083636364 0.013333333 0.09454545\n",
       "        brown     butter   buttermilk      cabbag      canola       caper\n",
       "1  0.04496788 0.17773019 0.0042826552 0.000000000 0.027837259 0.002141328\n",
       "2  0.13557214 0.54228856 0.0323383085 0.012437811 0.022388060 0.004975124\n",
       "3  0.07179819 0.32212160 0.0213454075 0.009702458 0.054333765 0.019404916\n",
       "4  0.13580247 0.04190049 0.0007482230 0.093901983 0.069958848 0.000000000\n",
       "5  0.11920530 0.11655629 0.0000000000 0.088741722 0.035761589 0.000000000\n",
       "6  0.04270597 0.43915344 0.0056689342 0.007558579 0.010582011 0.035147392\n",
       "7  0.01191489 0.14212766 0.0025531915 0.001702128 0.010212766 0.025531915\n",
       "8  0.07326007 0.14285714 0.0069930070 0.012321012 0.053613054 0.000000000\n",
       "9  0.11244378 0.50074963 0.1439280360 0.131934033 0.005997001 0.005997001\n",
       "10 0.01773412 0.21178872 0.0061240112 0.006124011 0.005741261 0.039678489\n",
       "11 0.20722433 0.17490494 0.0038022814 0.019011407 0.019011407 0.001901141\n",
       "12 0.08081518 0.07378777 0.0000000000 0.073787772 0.044272663 0.000000000\n",
       "13 0.20240964 0.01807229 0.0024096386 0.132530120 0.055421687 0.000000000\n",
       "14 0.04085120 0.08962411 0.0046598322 0.029822926 0.041472507 0.004193849\n",
       "15 0.02801462 0.13398295 0.0000000000 0.004872107 0.024360536 0.009744214\n",
       "16 0.03067485 0.43558282 0.0245398773 0.143149284 0.018404908 0.020449898\n",
       "17 0.14513889 0.49444444 0.1648148148 0.014814815 0.026620370 0.001851852\n",
       "18 0.02224469 0.09302326 0.0030333670 0.009100101 0.007077856 0.020222447\n",
       "19 0.22027290 0.14814815 0.0006497726 0.059129305 0.050032489 0.000000000\n",
       "20 0.12000000 0.07636364 0.0000000000 0.073939394 0.103030303 0.000000000\n",
       "       cardamom     carrot      cayenn      celeri      cheddar       chees\n",
       "1  0.0000000000 0.05567452 0.049250535 0.014989293 0.0107066381 0.119914347\n",
       "2  0.0024875622 0.07587065 0.039800995 0.032338308 0.0746268657 0.134328358\n",
       "3  0.0006468305 0.03428202 0.258085382 0.400388098 0.0129366106 0.112548512\n",
       "4  0.0018705574 0.14178825 0.013468013 0.042274598 0.0007482230 0.012345679\n",
       "5  0.0013245033 0.17748344 0.010596026 0.047682119 0.0198675497 0.046357616\n",
       "6  0.0037792895 0.09637188 0.023053666 0.061224490 0.0090702948 0.209372638\n",
       "7  0.0017021277 0.02723404 0.024680851 0.027234043 0.0059574468 0.491914894\n",
       "8  0.1958041958 0.07092907 0.124542125 0.011322011 0.0013320013 0.020646021\n",
       "9  0.0074962519 0.18140930 0.016491754 0.062968516 0.0584707646 0.124437781\n",
       "10 0.0011482521 0.05537127 0.008292932 0.054605767 0.0147996938 0.745470783\n",
       "11 0.0038022814 0.09315589 0.095057034 0.030418251 0.0038022814 0.032319392\n",
       "12 0.0267041462 0.14335910 0.018271258 0.013352073 0.0007027407 0.024595924\n",
       "13 0.0000000000 0.21686747 0.019277108 0.006024096 0.0072289157 0.015662651\n",
       "14 0.0003106555 0.02625039 0.066014290 0.017241379 0.1762969866 0.462255359\n",
       "15 0.0353227771 0.20341048 0.172959805 0.043848965 0.0024360536 0.029232643\n",
       "16 0.0122699387 0.16359918 0.018404908 0.081799591 0.0081799591 0.139059305\n",
       "17 0.0020833333 0.03495370 0.076620370 0.081018519 0.0932870370 0.201851852\n",
       "18 0.0010111223 0.04550051 0.040444894 0.024266936 0.0070778564 0.088978766\n",
       "19 0.0136452242 0.14619883 0.034437947 0.013645224 0.0000000000 0.007797271\n",
       "20 0.0193939394 0.30787879 0.012121212 0.018181818 0.0000000000 0.002424242\n",
       "        cherri    chicken     chickpea       chile       chili       chines\n",
       "1  0.010706638 0.16274090 0.0000000000 0.049250535 0.087794433 0.0000000000\n",
       "2  0.019900498 0.03731343 0.0000000000 0.001243781 0.009950249 0.0000000000\n",
       "3  0.005821475 0.47930142 0.0019404916 0.018111255 0.091849935 0.0000000000\n",
       "4  0.004489338 0.49756828 0.0003741115 0.054994388 0.219977553 0.2259633371\n",
       "5  0.002649007 0.32715232 0.0013245033 0.047682119 0.083443709 0.0238410596\n",
       "6  0.026832955 0.20256992 0.0052910053 0.003023432 0.004157218 0.0011337868\n",
       "7  0.046808511 0.19489362 0.0272340426 0.004255319 0.011914894 0.0000000000\n",
       "8  0.004329004 0.27106227 0.0656010656 0.125208125 0.514152514 0.0006660007\n",
       "9  0.017991004 0.09895052 0.0000000000 0.002998501 0.004497751 0.0000000000\n",
       "10 0.028578719 0.23411585 0.0052309263 0.005230926 0.013651442 0.0003827507\n",
       "11 0.007604563 0.33840304 0.0000000000 0.112167300 0.108365019 0.0095057034\n",
       "12 0.006324666 0.19395643 0.0021082221 0.019676739 0.127898805 0.0119465917\n",
       "13 0.000000000 0.13132530 0.0012048193 0.092771084 0.195180723 0.0240963855\n",
       "14 0.014134824 0.38412550 0.0024852439 0.231438335 0.472041007 0.0000000000\n",
       "15 0.014616322 0.44457978 0.1607795371 0.028014616 0.052375152 0.0000000000\n",
       "16 0.018404908 0.08793456 0.0020449898 0.004089980 0.018404908 0.0000000000\n",
       "17 0.011111111 0.21342593 0.0004629630 0.015740741 0.050694444 0.0000000000\n",
       "18 0.014155713 0.26491405 0.0232558140 0.048533873 0.068756320 0.0000000000\n",
       "19 0.022092268 0.49512671 0.0051981806 0.185185185 0.361273554 0.0227420403\n",
       "20 0.002424242 0.28848485 0.0000000000 0.206060606 0.304242424 0.0436363636\n",
       "           chip      chipotl       chive      chocol       chop       cider\n",
       "1  0.0085653105 0.0107066381 0.004282655 0.074946467 0.16274090 0.004282655\n",
       "2  0.0049751244 0.0000000000 0.022388060 0.039800995 0.08208955 0.011194030\n",
       "3  0.0032341527 0.0019404916 0.014230272 0.007115136 0.35187581 0.012289780\n",
       "4  0.0000000000 0.0003741115 0.023569024 0.001496446 0.08118219 0.017583240\n",
       "5  0.0000000000 0.0039735099 0.002649007 0.005298013 0.04635762 0.033112583\n",
       "6  0.0052910053 0.0003779289 0.041572184 0.089569161 0.16591081 0.012471655\n",
       "7  0.0076595745 0.0000000000 0.011914894 0.006808511 0.23148936 0.005106383\n",
       "8  0.0009990010 0.0006660007 0.002331002 0.001665002 0.25407925 0.009324009\n",
       "9  0.0164917541 0.0014992504 0.029985007 0.055472264 0.12893553 0.023988006\n",
       "10 0.0035723399 0.0007655014 0.016330697 0.026792549 0.20107170 0.003189589\n",
       "11 0.0076045627 0.0057034221 0.013307985 0.007604563 0.13307985 0.032319392\n",
       "12 0.0007027407 0.0007027407 0.026001405 0.005621926 0.05200281 0.005621926\n",
       "13 0.0024096386 0.0000000000 0.025301205 0.000000000 0.05421687 0.014457831\n",
       "14 0.0689655172 0.0784405095 0.003727866 0.020037279 0.32261572 0.022367195\n",
       "15 0.0024360536 0.0000000000 0.002436054 0.000000000 0.40803898 0.004872107\n",
       "16 0.0020449898 0.0000000000 0.028629857 0.034764826 0.12065440 0.028629857\n",
       "17 0.0069444444 0.0053240741 0.021296296 0.025925926 0.17384259 0.052777778\n",
       "18 0.0050556117 0.0060667341 0.016177958 0.006066734 0.22649141 0.008088979\n",
       "19 0.0006497726 0.0000000000 0.014944769 0.000000000 0.23066927 0.009746589\n",
       "20 0.0012121212 0.0012121212 0.010909091 0.000000000 0.19393939 0.010909091\n",
       "      cilantro    cinnamon      clove       coars     coconut        cold\n",
       "1  0.188436831 0.029978587 0.19700214 0.014989293 0.304068522 0.025695931\n",
       "2  0.006218905 0.084577114 0.07089552 0.021144279 0.007462687 0.027363184\n",
       "3  0.016817594 0.029754204 0.21280724 0.018758085 0.005821475 0.006468305\n",
       "4  0.091657314 0.024317247 0.18593341 0.016460905 0.016460905 0.034044145\n",
       "5  0.023841060 0.010596026 0.12450331 0.006622517 0.197350993 0.006622517\n",
       "6  0.005291005 0.040060469 0.20332577 0.014361300 0.008692366 0.021919879\n",
       "7  0.008510638 0.106382979 0.27489362 0.020425532 0.002553191 0.004255319\n",
       "8  0.347652348 0.181485181 0.30103230 0.016317016 0.210456210 0.006327006\n",
       "9  0.007496252 0.064467766 0.08845577 0.013493253 0.005997001 0.013493253\n",
       "10 0.006634345 0.016075529 0.25070171 0.019903036 0.002934422 0.008165348\n",
       "11 0.064638783 0.241444867 0.27566540 0.011406844 0.266159696 0.060836502\n",
       "12 0.065354884 0.016163036 0.08151792 0.006324666 0.030217850 0.022487702\n",
       "13 0.020481928 0.007228916 0.21807229 0.019277108 0.009638554 0.024096386\n",
       "14 0.433985710 0.049549550 0.18142280 0.026250388 0.008387698 0.005747126\n",
       "15 0.348355664 0.503045067 0.36419001 0.028014616 0.008526188 0.001218027\n",
       "16 0.018404908 0.069529652 0.14110429 0.022494888 0.002044990 0.038854806\n",
       "17 0.013425926 0.092361111 0.09166667 0.016898148 0.028009259 0.015509259\n",
       "18 0.086956522 0.068756320 0.38523761 0.016177958 0.004044489 0.005055612\n",
       "19 0.474333983 0.014944769 0.23196881 0.007147498 0.482781027 0.009096816\n",
       "20 0.407272727 0.065454545 0.25090909 0.010909091 0.075151515 0.015757576\n",
       "        condens  confection       cook     coriand        corn     cornmeal\n",
       "1  0.1456102784 0.002141328 0.05995717 0.047109208 0.072805139 0.0085653105\n",
       "2  0.0136815920 0.027363184 0.02860697 0.008706468 0.070895522 0.0136815920\n",
       "3  0.0109961190 0.016817594 0.19340233 0.006468305 0.093790427 0.0148771022\n",
       "4  0.0033670034 0.003367003 0.13280958 0.018705574 0.375982043 0.0007482230\n",
       "5  0.0556291391 0.005298013 0.16158940 0.006622517 0.105960265 0.0000000000\n",
       "6  0.0064247921 0.034391534 0.08730159 0.007936508 0.051776266 0.0037792895\n",
       "7  0.0008510638 0.007659574 0.09021277 0.013617021 0.009361702 0.0000000000\n",
       "8  0.0056610057 0.001665002 0.06959707 0.384615385 0.029970030 0.0003330003\n",
       "9  0.0104947526 0.023988006 0.10344828 0.002998501 0.064467766 0.0000000000\n",
       "10 0.0065067619 0.012120439 0.10449094 0.002551671 0.027813218 0.0099515182\n",
       "11 0.0190114068 0.001901141 0.08745247 0.038022814 0.045627376 0.0247148289\n",
       "12 0.0056219255 0.002810963 0.05059733 0.045678145 0.080112439 0.0000000000\n",
       "13 0.0000000000 0.000000000 0.08795181 0.007228916 0.079518072 0.0000000000\n",
       "14 0.0214352283 0.003106555 0.11168065 0.033861448 0.334265300 0.0065237651\n",
       "15 0.0012180268 0.010962241 0.05968331 0.306942753 0.010962241 0.0036540804\n",
       "16 0.0204498978 0.026584867 0.03067485 0.012269939 0.032719836 0.0020449898\n",
       "17 0.0266203704 0.015046296 0.07199074 0.003703704 0.191898148 0.0736111111\n",
       "18 0.0161779575 0.005055612 0.06673407 0.011122346 0.041456016 0.0040444894\n",
       "19 0.0058479532 0.000000000 0.11565952 0.122807018 0.071474984 0.0000000000\n",
       "20 0.0218181818 0.001212121 0.08606061 0.100606061 0.072727273 0.0000000000\n",
       "         crack       cream       crumb       crumbl       crush      cucumb\n",
       "1  0.006423983 0.074946467 0.019271949 0.0000000000 0.068522484 0.004282655\n",
       "2  0.016169154 0.333333333 0.046019900 0.0012437811 0.008706468 0.004975124\n",
       "3  0.015523933 0.133247089 0.031694696 0.0032341527 0.057567917 0.000000000\n",
       "4  0.004489338 0.020202020 0.002244669 0.0007482230 0.058735503 0.022820801\n",
       "5  0.001324503 0.075496689 0.017218543 0.0000000000 0.027814570 0.006622517\n",
       "6  0.010582011 0.264172336 0.030612245 0.0049130763 0.009826153 0.003401361\n",
       "7  0.018723404 0.045957447 0.034042553 0.2170212766 0.038297872 0.224680851\n",
       "8  0.007326007 0.095238095 0.008991009 0.0009990010 0.045621046 0.032301032\n",
       "9  0.008995502 0.260869565 0.016491754 0.0029985007 0.010494753 0.007496252\n",
       "10 0.014927277 0.126818066 0.050905843 0.0169686144 0.112018372 0.005103343\n",
       "11 0.009505703 0.045627376 0.058935361 0.0000000000 0.030418251 0.001901141\n",
       "12 0.004919185 0.042867182 0.002810963 0.0000000000 0.015460295 0.081517920\n",
       "13 0.003614458 0.007228916 0.001204819 0.0000000000 0.056626506 0.097590361\n",
       "14 0.007611059 0.296675986 0.007145076 0.0060577819 0.024075800 0.010562286\n",
       "15 0.009744214 0.007308161 0.008526188 0.0085261876 0.043848965 0.009744214\n",
       "16 0.008179959 0.374233129 0.049079755 0.0000000000 0.002044990 0.040899796\n",
       "17 0.013425926 0.223379630 0.038888889 0.0037037037 0.035648148 0.005787037\n",
       "18 0.008088979 0.068756320 0.035389282 0.0050556117 0.056622851 0.078867543\n",
       "19 0.003898635 0.028589994 0.005847953 0.0006497726 0.068875893 0.081221572\n",
       "20 0.015757576 0.008484848 0.002424242 0.0000000000 0.041212121 0.191515152\n",
       "         cumin        curri        dark        dice       dijon         dill\n",
       "1  0.062098501 0.0042826552 0.010706638 0.044967880 0.008565310 0.0000000000\n",
       "2  0.009950249 0.0236318408 0.054726368 0.003731343 0.027363184 0.0062189055\n",
       "3  0.036869340 0.0006468305 0.009055627 0.179172057 0.021345408 0.0084087969\n",
       "4  0.005985784 0.0086045642 0.136176581 0.007856341 0.002992892 0.0003741115\n",
       "5  0.010596026 0.0066225166 0.015894040 0.009271523 0.001324503 0.0000000000\n",
       "6  0.006802721 0.0049130763 0.018140590 0.022675737 0.071806500 0.0071806500\n",
       "7  0.041702128 0.0025531915 0.001702128 0.059574468 0.014468085 0.1480851064\n",
       "8  0.520479520 0.2870462870 0.004662005 0.052281052 0.002331002 0.0019980020\n",
       "9  0.004497751 0.0000000000 0.028485757 0.016491754 0.020989505 0.0104947526\n",
       "10 0.004720592 0.0011482521 0.004720592 0.065450370 0.013651442 0.0030620056\n",
       "11 0.057034221 0.1444866920 0.083650190 0.030418251 0.011406844 0.0038022814\n",
       "12 0.045678145 0.0252986648 0.037947997 0.004216444 0.009135629 0.0035137034\n",
       "13 0.001204819 0.0024096386 0.083132530 0.001204819 0.003614458 0.0000000000\n",
       "14 0.320130475 0.0009319664 0.007300404 0.125194160 0.002951227 0.0024852439\n",
       "15 0.550548112 0.0280146163 0.001218027 0.079171742 0.003654080 0.0073081608\n",
       "16 0.010224949 0.0000000000 0.020449898 0.022494888 0.018404908 0.2269938650\n",
       "17 0.017361111 0.0064814815 0.039120370 0.031712963 0.023379630 0.0101851852\n",
       "18 0.070778564 0.0050556117 0.008088979 0.074823054 0.012133468 0.0050556117\n",
       "19 0.057179987 0.3118908382 0.055880442 0.007797271 0.001299545 0.0000000000\n",
       "20 0.010909091 0.0363636364 0.042424242 0.009696970 0.001212121 0.0072727273\n",
       "         dough       dress        dri        egg     eggplant    enchilada\n",
       "1  0.002141328 0.000000000 0.13276231 0.22483940 0.0000000000 0.0000000000\n",
       "2  0.014925373 0.000000000 0.19527363 0.54228856 0.0000000000 0.0000000000\n",
       "3  0.003234153 0.011642950 0.41785252 0.15329884 0.0025873221 0.0000000000\n",
       "4  0.002992892 0.003367003 0.14777404 0.26075571 0.0138421250 0.0000000000\n",
       "5  0.001324503 0.001324503 0.04900662 0.23973510 0.0357615894 0.0000000000\n",
       "6  0.016628874 0.004535147 0.27362056 0.45124717 0.0158730159 0.0000000000\n",
       "7  0.046808511 0.021276596 0.44000000 0.17531915 0.0544680851 0.0000000000\n",
       "8  0.005328005 0.000999001 0.07592408 0.04428904 0.0206460206 0.0000000000\n",
       "9  0.008995502 0.004497751 0.16491754 0.32233883 0.0000000000 0.0000000000\n",
       "10 0.028451135 0.016585864 0.37165093 0.22875734 0.0290890533 0.0000000000\n",
       "11 0.013307985 0.001901141 0.30988593 0.12357414 0.0019011407 0.0000000000\n",
       "12 0.004216444 0.004919185 0.08995081 0.23471539 0.0274068869 0.0000000000\n",
       "13 0.001204819 0.003614458 0.05421687 0.20481928 0.0048192771 0.0000000000\n",
       "14 0.007455732 0.019260640 0.12969866 0.10158434 0.0006213110 0.0621310966\n",
       "15 0.008526188 0.001218027 0.22168088 0.09013398 0.0426309379 0.0000000000\n",
       "16 0.008179959 0.004089980 0.18609407 0.57259714 0.0040899796 0.0000000000\n",
       "17 0.004861111 0.015046296 0.11597222 0.39074074 0.0006944444 0.0002314815\n",
       "18 0.006066734 0.001011122 0.27805865 0.27704752 0.0131445905 0.0000000000\n",
       "19 0.001299545 0.007147498 0.09681611 0.13580247 0.0233918129 0.0000000000\n",
       "20 0.001212121 0.006060606 0.08363636 0.11393939 0.0072727273 0.0000000000\n",
       "   extra-virgin     extract         fat       fennel         feta      fillet\n",
       "1   0.027837259 0.038543897 0.010706638 0.0064239829 0.0000000000 0.053533191\n",
       "2   0.023631841 0.105721393 0.012437811 0.0037313433 0.0000000000 0.043532338\n",
       "3   0.030401035 0.034928849 0.032988357 0.0058214748 0.0006468305 0.048512290\n",
       "4   0.004489338 0.009352787 0.020950243 0.0059857838 0.0003741115 0.016835017\n",
       "5   0.006622517 0.039735099 0.003973510 0.0013245033 0.0000000000 0.018543046\n",
       "6   0.096749811 0.110355253 0.064625850 0.0381708239 0.0026455026 0.056689342\n",
       "7   0.194893617 0.027234043 0.039148936 0.0178723404 0.3812765957 0.017872340\n",
       "8   0.017649018 0.006327006 0.038295038 0.0502830503 0.0016650017 0.022977023\n",
       "9   0.017991004 0.064467766 0.052473763 0.0104947526 0.0000000000 0.011994003\n",
       "10  0.173768819 0.041464659 0.048481756 0.0322786425 0.0137790253 0.027558051\n",
       "11  0.011406844 0.043726236 0.020912548 0.0000000000 0.0000000000 0.020912548\n",
       "12  0.015460295 0.016163036 0.008432888 0.0084328883 0.0000000000 0.072382291\n",
       "13  0.004819277 0.007228916 0.004819277 0.0000000000 0.0000000000 0.009638554\n",
       "14  0.031997515 0.016154085 0.045355701 0.0009319664 0.0065237651 0.017862690\n",
       "15  0.155907430 0.003654080 0.048721072 0.0304506699 0.0146163216 0.032886724\n",
       "16  0.012269939 0.089979550 0.008179959 0.0122699387 0.0040899796 0.034764826\n",
       "17  0.022685185 0.136805556 0.027546296 0.0030092593 0.0009259259 0.016898148\n",
       "18  0.257836198 0.035389282 0.040444894 0.0171890799 0.0040444894 0.032355915\n",
       "19  0.005847953 0.003898635 0.034437947 0.0025990903 0.0006497726 0.035737492\n",
       "20  0.006060606 0.004848485 0.016969697 0.0121212121 0.0000000000 0.023030303\n",
       "          fine         firm        fish       flake         flat      flour\n",
       "1  0.017130621 0.0000000000 0.057815846 0.070663812 0.0214132762 0.15631692\n",
       "2  0.014925373 0.0024875622 0.017412935 0.017412935 0.0074626866 0.58084577\n",
       "3  0.026520052 0.0025873221 0.007761966 0.044631307 0.0323415265 0.29107374\n",
       "4  0.008230453 0.0419004863 0.033295922 0.088664422 0.0007482230 0.14029181\n",
       "5  0.009271523 0.0079470199 0.143046358 0.031788079 0.0026490066 0.13112583\n",
       "6  0.037792895 0.0064247921 0.015495087 0.009070295 0.0479969766 0.30347695\n",
       "7  0.027234043 0.0008510638 0.000000000 0.037446809 0.0561702128 0.11574468\n",
       "8  0.026307026 0.0116550117 0.008991009 0.045621046 0.0026640027 0.17682318\n",
       "9  0.022488756 0.0089955022 0.001499250 0.005997001 0.0134932534 0.51124438\n",
       "10 0.033682062 0.0020413371 0.003955091 0.068257208 0.0761673896 0.17364124\n",
       "11 0.020912548 0.0000000000 0.024714829 0.064638783 0.0057034221 0.21102662\n",
       "12 0.014757554 0.0477863668 0.018973999 0.084328883 0.0042164441 0.14265636\n",
       "13 0.002409639 0.0421686747 0.071084337 0.179518072 0.0048192771 0.10602410\n",
       "14 0.022367195 0.0027958993 0.003727866 0.020813917 0.0040385213 0.22134203\n",
       "15 0.030450670 0.0012180268 0.007308161 0.041412911 0.0803897686 0.10962241\n",
       "16 0.026584867 0.0000000000 0.008179959 0.012269939 0.0224948875 0.48466258\n",
       "17 0.022685185 0.0178240741 0.001620370 0.038425926 0.0108796296 0.42754630\n",
       "18 0.023255814 0.0010111223 0.016177958 0.044489383 0.0829120324 0.09908999\n",
       "19 0.004548408 0.0578297596 0.540610786 0.089018843 0.0006497726 0.03508772\n",
       "20 0.008484848 0.0460606061 0.593939394 0.049696970 0.0012121212 0.07151515\n",
       "          free     fresh      frozen        garam    garlic      ginger\n",
       "1  0.010706638 0.2847966 0.068522484 0.0021413276 0.4154176 0.066381156\n",
       "2  0.014925373 0.2238806 0.070895522 0.0024875622 0.1169154 0.067164179\n",
       "3  0.020051746 0.3531695 0.033635188 0.0000000000 0.6487710 0.003880983\n",
       "4  0.020202020 0.3920688 0.035540591 0.0003741115 0.6311261 0.554807333\n",
       "5  0.002649007 0.1019868 0.029139073 0.0000000000 0.6675497 0.145695364\n",
       "6  0.034013605 0.5506425 0.035147392 0.0000000000 0.2936508 0.016628874\n",
       "7  0.029787234 0.7582979 0.036595745 0.0000000000 0.5361702 0.005957447\n",
       "8  0.023310023 0.5544456 0.056610057 0.2877122877 0.5444555 0.491175491\n",
       "9  0.034482759 0.2713643 0.032983508 0.0000000000 0.1604198 0.038980510\n",
       "10 0.031513141 0.6368972 0.043250829 0.0001275836 0.5324062 0.005358510\n",
       "11 0.009505703 0.4296578 0.011406844 0.0038022814 0.5950570 0.235741445\n",
       "12 0.010541110 0.2839072 0.030920590 0.0323260717 0.2515812 0.323963457\n",
       "13 0.004819277 0.2240964 0.003614458 0.0000000000 0.7698795 0.385542169\n",
       "14 0.018794657 0.4168997 0.055296676 0.0000000000 0.5004660 0.004970488\n",
       "15 0.034104750 0.8233861 0.010962241 0.0073081608 0.5481121 0.349573691\n",
       "16 0.000000000 0.3271984 0.020449898 0.0000000000 0.1799591 0.018404908\n",
       "17 0.016435185 0.2375000 0.038888889 0.0004629630 0.2284722 0.026851852\n",
       "18 0.032355915 0.4924166 0.046511628 0.0000000000 0.5672396 0.011122346\n",
       "19 0.015594542 0.8609487 0.018193632 0.0012995452 0.6218324 0.338531514\n",
       "20 0.006060606 0.6824242 0.008484848 0.0000000000 0.6569697 0.276363636\n",
       "        golden      granul       grate        greek      green    ground\n",
       "1  0.002141328 0.044967880 0.044967880 0.0000000000 0.18201285 0.2698073\n",
       "2  0.065920398 0.046019900 0.067164179 0.0049751244 0.03233831 0.3880597\n",
       "3  0.003880983 0.032988357 0.037516171 0.0000000000 0.59055627 0.4391979\n",
       "4  0.002618780 0.019453797 0.010849233 0.0003741115 0.36924804 0.2947999\n",
       "5  0.003973510 0.033112583 0.018543046 0.0000000000 0.22384106 0.3562914\n",
       "6  0.017006803 0.046863190 0.108465608 0.0018896447 0.08654573 0.3272865\n",
       "7  0.005957447 0.014468085 0.096170213 0.1838297872 0.13957447 0.5531915\n",
       "8  0.017316017 0.006327006 0.031635032 0.0469530470 0.31002331 0.9297369\n",
       "9  0.020989505 0.061469265 0.065967016 0.0029985007 0.10644678 0.3328336\n",
       "10 0.008930850 0.014544527 0.264991069 0.0011482521 0.09645318 0.3803266\n",
       "11 0.001901141 0.022813688 0.060836502 0.0019011407 0.20722433 1.0304183\n",
       "12 0.002108222 0.033731553 0.013352073 0.0007027407 0.23190443 0.1834153\n",
       "13 0.004819277 0.028915663 0.001204819 0.0012048193 0.41927711 0.2301205\n",
       "14 0.003106555 0.011960236 0.025473750 0.0102516309 0.30226779 0.5428705\n",
       "15 0.060901340 0.010962241 0.056029233 0.0243605359 0.17295981 1.6686967\n",
       "16 0.032719836 0.038854806 0.020449898 0.0040899796 0.10429448 0.3251534\n",
       "17 0.009490741 0.066898148 0.053472222 0.0032407407 0.18263889 0.3546296\n",
       "18 0.013144590 0.010111223 0.039433771 0.0010111223 0.26086957 0.3650152\n",
       "19 0.006497726 0.019493177 0.021442495 0.0012995452 0.37361923 0.2527615\n",
       "20 0.004848485 0.029090909 0.019393939 0.0012121212 0.25454545 0.3284848\n",
       "          halv         ham       heavi       hoisin       honey        hot\n",
       "1  0.006423983 0.036402570 0.014989293 0.0000000000 0.025695931 0.04710921\n",
       "2  0.004975124 0.008706468 0.129353234 0.0000000000 0.019900498 0.01990050\n",
       "3  0.039456662 0.060802070 0.047865459 0.0000000000 0.009055627 0.18499353\n",
       "4  0.027310138 0.011223345 0.002244669 0.1219603442 0.096146652 0.04077815\n",
       "5  0.007947020 0.009271523 0.005298013 0.0132450331 0.017218543 0.02649007\n",
       "6  0.026077098 0.028344671 0.093348450 0.0003779289 0.027210884 0.01587302\n",
       "7  0.029787234 0.001702128 0.005957447 0.0000000000 0.061276596 0.01361702\n",
       "8  0.017982018 0.000000000 0.035964036 0.0000000000 0.020979021 0.02630703\n",
       "9  0.007496252 0.022488756 0.068965517 0.0000000000 0.017991004 0.01199400\n",
       "10 0.030237305 0.012375606 0.048099005 0.0000000000 0.016713447 0.03176831\n",
       "11 0.024714829 0.009505703 0.003802281 0.0000000000 0.015209125 0.11977186\n",
       "12 0.005621926 0.002810963 0.010541110 0.0063246662 0.055516514 0.02810963\n",
       "13 0.001204819 0.003614458 0.003614458 0.0048192771 0.096385542 0.04819277\n",
       "14 0.027958993 0.004193849 0.011028270 0.0001553277 0.018639329 0.05374340\n",
       "15 0.052375152 0.000000000 0.001218027 0.0000000000 0.142509135 0.02557856\n",
       "16 0.012269939 0.026584867 0.036809816 0.0000000000 0.044989775 0.03476483\n",
       "17 0.029629630 0.051620370 0.059027778 0.0004629630 0.040740741 0.07685185\n",
       "18 0.021233569 0.053589484 0.018200202 0.0000000000 0.025278059 0.06066734\n",
       "19 0.035737492 0.000000000 0.005198181 0.0110461339 0.051981806 0.04288499\n",
       "20 0.008484848 0.006060606 0.002424242 0.0763636364 0.040000000 0.07030303\n",
       "           ice     italian         jack     jalapeno       juic     kalamata\n",
       "1  0.122055675 0.010706638 0.0064239829 0.0406852248 0.22269807 0.0000000000\n",
       "2  0.018656716 0.002487562 0.0000000000 0.0012437811 0.08084577 0.0000000000\n",
       "3  0.009702458 0.029107374 0.0103492885 0.0323415265 0.12677878 0.0019404916\n",
       "4  0.004115226 0.001122334 0.0000000000 0.0074822297 0.08305275 0.0000000000\n",
       "5  0.018543046 0.002649007 0.0000000000 0.0158940397 0.07682119 0.0000000000\n",
       "6  0.037037037 0.015117158 0.0026455026 0.0003779289 0.17346939 0.0204081633\n",
       "7  0.000000000 0.013617021 0.0017021277 0.0017021277 0.37957447 0.1310638298\n",
       "8  0.009657010 0.001665002 0.0003330003 0.0422910423 0.19946720 0.0000000000\n",
       "9  0.014992504 0.007496252 0.0000000000 0.0044977511 0.07496252 0.0000000000\n",
       "10 0.007144680 0.143786680 0.0048481756 0.0025516713 0.12375606 0.0199030365\n",
       "11 0.019011407 0.001901141 0.0000000000 0.0570342205 0.25855513 0.0000000000\n",
       "12 0.009838370 0.001405481 0.0007027407 0.0035137034 0.10049192 0.0000000000\n",
       "13 0.008433735 0.000000000 0.0012048193 0.0192771084 0.07590361 0.0000000000\n",
       "14 0.012736875 0.006368437 0.1326498913 0.1825100963 0.25287356 0.0006213110\n",
       "15 0.002436054 0.007308161 0.0000000000 0.0024360536 0.31546894 0.0280146163\n",
       "16 0.008179959 0.004089980 0.0000000000 0.0040899796 0.13087935 0.0020449898\n",
       "17 0.035185185 0.012037037 0.0106481481 0.0254629630 0.13750000 0.0006944444\n",
       "18 0.026289181 0.018200202 0.0010111223 0.0313447927 0.24570273 0.0080889788\n",
       "19 0.006497726 0.001299545 0.0006497726 0.0545808967 0.38336582 0.0000000000\n",
       "20 0.012121212 0.003636364 0.0012121212 0.0739393939 0.31151515 0.0000000000\n",
       "         kernel      ketchup     kosher         lamb       larg        leaf\n",
       "1  0.0085653105 0.0021413276 0.04710921 0.0042826552 0.07066381 0.070663812\n",
       "2  0.0012437811 0.0087064677 0.07587065 0.0174129353 0.20398010 0.032338308\n",
       "3  0.0174644243 0.0148771022 0.06985770 0.0000000000 0.14424321 0.102199224\n",
       "4  0.0033670034 0.0490086046 0.06995885 0.0041152263 0.09577254 0.005985784\n",
       "5  0.0052980132 0.0317880795 0.02781457 0.0026490066 0.03841060 0.037086093\n",
       "6  0.0018896447 0.0007558579 0.06009070 0.0128495843 0.32615268 0.106953893\n",
       "7  0.0008510638 0.0008510638 0.07489362 0.1157446809 0.12680851 0.077446809\n",
       "8  0.0033300033 0.0079920080 0.08558109 0.0369630370 0.03962704 0.045288045\n",
       "9  0.0000000000 0.0029985007 0.04947526 0.0614692654 0.16041979 0.046476762\n",
       "10 0.0039550906 0.0017861699 0.08497066 0.0045930084 0.16471039 0.093008421\n",
       "11 0.0019011407 0.0627376426 0.06273764 0.0019011407 0.04562738 0.017110266\n",
       "12 0.0035137034 0.0260014055 0.05692200 0.0000000000 0.08713985 0.012649332\n",
       "13 0.0012048193 0.0156626506 0.08915663 0.0072289157 0.06265060 0.012048193\n",
       "14 0.0652376514 0.0057471264 0.09583722 0.0017086052 0.06197577 0.017552035\n",
       "15 0.0000000000 0.0024360536 0.11571255 0.2070645554 0.07673569 0.096224117\n",
       "16 0.0000000000 0.0184049080 0.04703476 0.0061349693 0.24744376 0.047034765\n",
       "17 0.0270833333 0.0236111111 0.08263889 0.0006944444 0.21620370 0.026388889\n",
       "18 0.0091001011 0.0060667341 0.12335693 0.0070778564 0.25379171 0.131445905\n",
       "19 0.0025990903 0.0194931774 0.05458090 0.0019493177 0.09551657 0.011695906\n",
       "20 0.0024242424 0.0072727273 0.11151515 0.0024242424 0.05696970 0.026666667\n",
       "          lean       leav         leek      lemon        less      lettuc\n",
       "1  0.002141328 0.13490364 0.0042826552 0.07922912 0.006423983 0.002141328\n",
       "2  0.024875622 0.05970149 0.0223880597 0.15547264 0.000000000 0.003731343\n",
       "3  0.008408797 0.19210867 0.0045278137 0.16364812 0.015523933 0.025873221\n",
       "4  0.015712682 0.05798728 0.0108492331 0.03965582 0.016086794 0.034044145\n",
       "5  0.006622517 0.18543046 0.0039735099 0.08079470 0.001324503 0.005298013\n",
       "6  0.001889645 0.15873016 0.0525321240 0.19916856 0.022297808 0.022297808\n",
       "7  0.017021277 0.12085106 0.0068085106 0.54808511 0.010212766 0.069787234\n",
       "8  0.000999001 0.32034632 0.0019980020 0.19580420 0.010323010 0.003996004\n",
       "9  0.004497751 0.08095952 0.0614692654 0.09145427 0.011994003 0.004497751\n",
       "10 0.020796121 0.15603470 0.0135238581 0.17874458 0.022582291 0.009441184\n",
       "11 0.017110266 0.11216730 0.0019011407 0.04372624 0.001901141 0.011406844\n",
       "12 0.001405481 0.07800422 0.0133520731 0.09838370 0.002108222 0.007730148\n",
       "13 0.013253012 0.04698795 0.0108433735 0.02409639 0.002409639 0.055421687\n",
       "14 0.032929481 0.08993476 0.0004659832 0.03681267 0.011649581 0.079061820\n",
       "15 0.003654080 0.11693057 0.0048721072 0.54689403 0.035322777 0.006090134\n",
       "16 0.016359918 0.07975460 0.0184049080 0.20654397 0.000000000 0.004089980\n",
       "17 0.003240741 0.05000000 0.0041666667 0.13564815 0.006712963 0.012731481\n",
       "18 0.004044489 0.10515672 0.0111223458 0.21638018 0.025278059 0.013144590\n",
       "19 0.007147498 0.34243015 0.0045484081 0.09811566 0.013645224 0.050032489\n",
       "20 0.003636364 0.34424242 0.0048484848 0.07272727 0.007272727 0.145454545\n",
       "         light        lime         low      low-fat       masala    mayonais\n",
       "1  0.034261242 0.351177730 0.021413276 0.0107066381 0.0021413276 0.021413276\n",
       "2  0.049751244 0.006218905 0.009950249 0.0099502488 0.0024875622 0.008706468\n",
       "3  0.027166882 0.014877102 0.049159120 0.0109961190 0.0000000000 0.051746442\n",
       "4  0.111485223 0.029554807 0.113729892 0.0003741115 0.0003741115 0.004489338\n",
       "5  0.015894040 0.037086093 0.023841060 0.0000000000 0.0000000000 0.015894040\n",
       "6  0.035147392 0.014739229 0.028722600 0.0291005291 0.0000000000 0.017762661\n",
       "7  0.011914894 0.005106383 0.020425532 0.0323404255 0.0000000000 0.013617021\n",
       "8  0.026307026 0.090576091 0.016650017 0.0293040293 0.3323343323 0.004329004\n",
       "9  0.031484258 0.010494753 0.014992504 0.0659670165 0.0000000000 0.011994003\n",
       "10 0.010461853 0.006379178 0.041592243 0.0241132942 0.0001275836 0.008037765\n",
       "11 0.049429658 0.290874525 0.032319392 0.0038022814 0.0057034221 0.017110266\n",
       "12 0.033731553 0.044975404 0.055516514 0.0007027407 0.0358397751 0.035839775\n",
       "13 0.043373494 0.013253012 0.060240964 0.0000000000 0.0000000000 0.010843373\n",
       "14 0.018328674 0.355079217 0.030288910 0.0172413793 0.0000000000 0.025784405\n",
       "15 0.004872107 0.024360536 0.049939099 0.0060901340 0.0073081608 0.008526188\n",
       "16 0.016359918 0.000000000 0.008179959 0.0143149284 0.0040899796 0.063394683\n",
       "17 0.071527778 0.039120370 0.018518519 0.0178240741 0.0004629630 0.042129630\n",
       "18 0.008088979 0.067745197 0.037411527 0.0171890799 0.0000000000 0.015166835\n",
       "19 0.119558155 0.723846654 0.068875893 0.0051981806 0.0019493177 0.006497726\n",
       "20 0.047272727 0.452121212 0.038787879 0.0024242424 0.0000000000 0.040000000\n",
       "          meat      medium      mexican        milk       minc        mint\n",
       "1  0.006423983 0.021413276 0.0000000000 0.490364026 0.03211991 0.014989293\n",
       "2  0.009950249 0.017412935 0.0000000000 0.356965174 0.01990050 0.017412935\n",
       "3  0.047218629 0.070504528 0.0012936611 0.106727038 0.07826649 0.001940492\n",
       "4  0.017583240 0.023194912 0.0003741115 0.027684250 0.12158623 0.005237561\n",
       "5  0.030463576 0.007947020 0.0000000000 0.252980132 0.05827815 0.001324503\n",
       "6  0.007936508 0.006424792 0.0000000000 0.182917611 0.02343159 0.020786092\n",
       "7  0.005957447 0.010212766 0.0000000000 0.075744681 0.06978723 0.142978723\n",
       "8  0.011322011 0.007992008 0.0000000000 0.211788212 0.05128205 0.074259074\n",
       "9  0.025487256 0.000000000 0.0000000000 0.278860570 0.01199400 0.014992504\n",
       "10 0.009823935 0.011737688 0.0002551671 0.094029089 0.04950242 0.021561623\n",
       "11 0.032319392 0.007604563 0.0000000000 0.277566540 0.05893536 0.003802281\n",
       "12 0.019676739 0.013352073 0.0000000000 0.071679550 0.03443429 0.003513703\n",
       "13 0.020481928 0.012048193 0.0000000000 0.007228916 0.13493976 0.000000000\n",
       "14 0.019260640 0.009009009 0.0776638708 0.069742156 0.04255980 0.007766387\n",
       "15 0.017052375 0.002436054 0.0000000000 0.024360536 0.04141291 0.143727162\n",
       "16 0.022494888 0.004089980 0.0000000000 0.200408998 0.02044990 0.008179959\n",
       "17 0.012962963 0.007638889 0.0011574074 0.258564815 0.02453704 0.025231481\n",
       "18 0.012133468 0.032355915 0.0010111223 0.108190091 0.06268959 0.025278059\n",
       "19 0.009096816 0.044184535 0.0000000000 0.410656270 0.07927225 0.111111111\n",
       "20 0.038787879 0.054545455 0.0000000000 0.077575758 0.10424242 0.218181818\n",
       "          mirin         mix     monterey   mozzarella    mushroom     mustard\n",
       "1  0.0000000000 0.012847966 0.0042826552 0.0107066381 0.004282655 0.010706638\n",
       "2  0.0000000000 0.039800995 0.0000000000 0.0000000000 0.072139303 0.094527363\n",
       "3  0.0000000000 0.029754204 0.0051746442 0.0071151358 0.053686934 0.086028461\n",
       "4  0.0101010101 0.012345679 0.0000000000 0.0003741115 0.133557800 0.014590348\n",
       "5  0.0000000000 0.001324503 0.0000000000 0.0013245033 0.027814570 0.007947020\n",
       "6  0.0003779289 0.009826153 0.0022675737 0.0041572184 0.088435374 0.096371882\n",
       "7  0.0000000000 0.011063830 0.0008510638 0.0110638298 0.022127660 0.022978723\n",
       "8  0.0000000000 0.007992008 0.0003330003 0.0013320013 0.014319014 0.175158175\n",
       "9  0.0000000000 0.029985007 0.0000000000 0.0044977511 0.038980510 0.065967016\n",
       "10 0.0000000000 0.012375606 0.0028068385 0.1593518755 0.107552947 0.018754784\n",
       "11 0.0000000000 0.017110266 0.0000000000 0.0076045627 0.009505703 0.032319392\n",
       "12 0.2825017569 0.010541110 0.0000000000 0.0028109628 0.103302881 0.033731553\n",
       "13 0.0710843373 0.008433735 0.0000000000 0.0012048193 0.107228916 0.015662651\n",
       "14 0.0001553277 0.053277415 0.0823237030 0.0147561354 0.023454489 0.007766387\n",
       "15 0.0000000000 0.009744214 0.0000000000 0.0012180268 0.007308161 0.010962241\n",
       "16 0.0000000000 0.010224949 0.0000000000 0.0081799591 0.096114519 0.034764826\n",
       "17 0.0000000000 0.037962963 0.0043981481 0.0030092593 0.017824074 0.077777778\n",
       "18 0.0000000000 0.011122346 0.0010111223 0.0020222447 0.024266936 0.016177958\n",
       "19 0.0045484081 0.007147498 0.0006497726 0.0025990903 0.087719298 0.009096816\n",
       "20 0.0072727273 0.009696970 0.0012121212 0.0000000000 0.058181818 0.003636364\n",
       "         noodl      nutmeg       oil       oliv     onion       orang\n",
       "1  0.000000000 0.010706638 0.5289079 0.31049251 0.4839400 0.107066381\n",
       "2  0.000000000 0.087064677 0.2500000 0.09577114 0.2674129 0.068407960\n",
       "3  0.003880983 0.016817594 0.5310479 0.26002587 0.8499353 0.023285899\n",
       "4  0.119715675 0.003741115 1.1242050 0.05649083 0.4863449 0.071829405\n",
       "5  0.063576159 0.001324503 0.6304636 0.07549669 0.6172185 0.013245033\n",
       "6  0.004535147 0.052910053 0.3877551 0.35714286 0.2849584 0.089569161\n",
       "7  0.002553191 0.040851064 0.7021277 0.77957447 0.4791489 0.039148936\n",
       "8  0.002664003 0.029304029 0.6763237 0.14119214 0.6140526 0.007659008\n",
       "9  0.000000000 0.058470765 0.2068966 0.09745127 0.3568216 0.067466267\n",
       "10 0.040061240 0.030237305 0.6612656 0.63625925 0.3466446 0.036871651\n",
       "11 0.005703422 0.228136882 0.5133080 0.13878327 0.7110266 0.089353612\n",
       "12 0.095572734 0.002108222 0.6331694 0.05692200 0.3316936 0.025298665\n",
       "13 0.067469880 0.000000000 0.9819277 0.05060241 0.7530120 0.009638554\n",
       "14 0.003727866 0.002329916 0.4625660 0.28673501 0.6890339 0.043957751\n",
       "15 0.006090134 0.038976857 0.7771011 0.80146163 0.6041413 0.108404385\n",
       "16 0.016359918 0.016359918 0.3537832 0.13496933 0.4274029 0.028629857\n",
       "17 0.001157407 0.051157407 0.2953704 0.09930556 0.3159722 0.047453704\n",
       "18 0.002022245 0.016177958 0.7421638 0.73710819 0.5217391 0.142568251\n",
       "19 0.167641326 0.006497726 0.6868096 0.08122157 0.4541910 0.024691358\n",
       "20 0.214545455 0.002424242 0.6400000 0.05212121 0.5006061 0.016969697\n",
       "       oregano       oyster     paprika    parmesan     parsley        past\n",
       "1  0.029978587 0.0021413276 0.040685225 0.051391863 0.117773019 0.044967880\n",
       "2  0.009950249 0.0000000000 0.027363184 0.013681592 0.064676617 0.036069652\n",
       "3  0.145536869 0.0194049159 0.169469599 0.037516171 0.238680466 0.064036223\n",
       "4  0.000748223 0.1316872428 0.005237561 0.001496446 0.006359895 0.084923307\n",
       "5  0.006622517 0.0437086093 0.014569536 0.002649007 0.014569536 0.039735099\n",
       "6  0.018140590 0.0034013605 0.014361300 0.043461829 0.185563114 0.037037037\n",
       "7  0.342978723 0.0000000000 0.027234043 0.041702128 0.219574468 0.033191489\n",
       "8  0.000999001 0.0006660007 0.080919081 0.001332001 0.015651016 0.206127206\n",
       "9  0.005997001 0.0044977511 0.023988006 0.010494753 0.124437781 0.034482759\n",
       "10 0.125924981 0.0011482521 0.011354937 0.313345241 0.222760908 0.057412605\n",
       "11 0.013307985 0.0019011407 0.053231939 0.003802281 0.028517110 0.030418251\n",
       "12 0.000000000 0.0091356290 0.006324666 0.005621926 0.007730148 0.129304287\n",
       "13 0.000000000 0.0240963855 0.013253012 0.000000000 0.003614458 0.115662651\n",
       "14 0.140726934 0.0006213110 0.056383970 0.007921715 0.022833178 0.028114321\n",
       "15 0.014616322 0.0012180268 0.295980512 0.003654080 0.294762485 0.097442144\n",
       "16 0.004089980 0.0000000000 0.040899796 0.004089980 0.120654397 0.038854806\n",
       "17 0.012731481 0.0064814815 0.062500000 0.031481481 0.066203704 0.008333333\n",
       "18 0.067745197 0.0040444894 0.198179980 0.012133468 0.247724975 0.042467139\n",
       "19 0.002599090 0.0298895387 0.012345679 0.001299545 0.005198181 0.370370370\n",
       "20 0.000000000 0.0339393939 0.007272727 0.001212121 0.006060606 0.078787879\n",
       "         pasta         pea       peanut        pecan        peel    pepper\n",
       "1  0.002141328 0.034261242 0.0214132762 0.0064239829 0.012847966 0.6638116\n",
       "2  0.000000000 0.037313433 0.0024875622 0.0149253731 0.043532338 0.3432836\n",
       "3  0.017464424 0.020698577 0.0200517464 0.0258732212 0.025226391 1.5045278\n",
       "4  0.002618780 0.092031425 0.1769547325 0.0000000000 0.075570520 0.6483352\n",
       "5  0.007947020 0.042384106 0.0238410596 0.0000000000 0.007947020 0.6768212\n",
       "6  0.004157218 0.010959940 0.0030234316 0.0086923658 0.034769463 0.4591837\n",
       "7  0.034893617 0.010212766 0.0008510638 0.0068085106 0.023829787 0.7361702\n",
       "8  0.000999001 0.095904096 0.0329670330 0.0006660007 0.062271062 0.5487845\n",
       "9  0.001499250 0.034482759 0.0074962519 0.0104947526 0.023988006 0.4257871\n",
       "10 0.129497321 0.026409798 0.0006379178 0.0054860934 0.034064812 0.7231437\n",
       "11 0.001901141 0.036121673 0.0152091255 0.0152091255 0.026615970 1.1711027\n",
       "12 0.002108222 0.052705552 0.0224877020 0.0028109628 0.040758960 0.2740689\n",
       "13 0.002409639 0.010843373 0.0228915663 0.0000000000 0.025301205 0.6963855\n",
       "14 0.012270892 0.004970488 0.0071450761 0.0041938490 0.010251631 0.7283318\n",
       "15 0.006090134 0.018270402 0.0048721072 0.0000000000 0.049939099 0.8343484\n",
       "16 0.002044990 0.040899796 0.0000000000 0.0000000000 0.028629857 0.4355828\n",
       "17 0.004166667 0.048611111 0.0405092593 0.0993055556 0.008564815 0.6270833\n",
       "18 0.006066734 0.072800809 0.0000000000 0.0030333670 0.030333670 0.9201213\n",
       "19 0.003248863 0.057829760 0.4061078622 0.0000000000 0.072124756 0.6250812\n",
       "20 0.000000000 0.020606061 0.2060606061 0.0000000000 0.041212121 0.6048485\n",
       "    peppercorn       plain        plum        pork     potato     powder\n",
       "1  0.002141328 0.006423983 0.019271949 0.074946467 0.05567452 0.13490364\n",
       "2  0.012437811 0.048507463 0.004975124 0.057213930 0.17910448 0.26492537\n",
       "3  0.010996119 0.003880983 0.016817594 0.039456662 0.03751617 0.29107374\n",
       "4  0.066217733 0.005985784 0.013093902 0.208380097 0.01608679 0.17358773\n",
       "5  0.119205298 0.003973510 0.005298013 0.280794702 0.08609272 0.11920530\n",
       "6  0.041950113 0.008314437 0.028344671 0.028344671 0.11300076 0.11186697\n",
       "7  0.005106383 0.128510638 0.044255319 0.017872340 0.08000000 0.08425532\n",
       "8  0.053946054 0.137862138 0.024642025 0.008658009 0.15984016 0.50715951\n",
       "9  0.020989505 0.016491754 0.004497751 0.037481259 0.41079460 0.24737631\n",
       "10 0.004848176 0.004337841 0.048481756 0.029471804 0.03648890 0.09224292\n",
       "11 0.019011407 0.020912548 0.009505703 0.060836502 0.10076046 0.38403042\n",
       "12 0.007027407 0.011243851 0.005621926 0.078706957 0.06746311 0.16584680\n",
       "13 0.002409639 0.004819277 0.002409639 0.108433735 0.06265060 0.07710843\n",
       "14 0.008543026 0.011028270 0.029512271 0.061509786 0.03572538 0.36905871\n",
       "15 0.009744214 0.020706456 0.028014616 0.007308161 0.09500609 0.09378806\n",
       "16 0.024539877 0.030674847 0.008179959 0.053169734 0.26175869 0.16768916\n",
       "17 0.006250000 0.006944444 0.006712963 0.051157407 0.07268519 0.32731481\n",
       "18 0.008088979 0.010111223 0.052578362 0.044489383 0.16784631 0.05358948\n",
       "19 0.024691358 0.003248863 0.007147498 0.053931124 0.03183886 0.11371020\n",
       "20 0.030303030 0.002424242 0.007272727 0.201212121 0.01818182 0.09333333\n",
       "         purpl      raisin        red       reduc         rib        rice\n",
       "1  0.017130621 0.012847966 0.18415418 0.004282655 0.038543897 0.134903640\n",
       "2  0.013681592 0.077114428 0.06218905 0.002487562 0.019900498 0.028606965\n",
       "3  0.024579560 0.005821475 0.35899094 0.023285899 0.118369987 0.347347995\n",
       "4  0.012345679 0.001870557 0.28357651 0.039655817 0.024691358 0.467265245\n",
       "5  0.017218543 0.034437086 0.09536424 0.001324503 0.019867550 0.169536424\n",
       "6  0.024565382 0.009070295 0.16175359 0.023053666 0.031368103 0.012849584\n",
       "7  0.158297872 0.010212766 0.25617021 0.005106383 0.010212766 0.054468085\n",
       "8  0.056610057 0.038961039 0.29470529 0.006660007 0.004662005 0.197469197\n",
       "9  0.004497751 0.074962519 0.10644678 0.014992504 0.019490255 0.002998501\n",
       "10 0.044781832 0.010844603 0.26192906 0.015692779 0.021816790 0.046823169\n",
       "11 0.049429658 0.020912548 0.23384030 0.003802281 0.005703422 0.127376426\n",
       "12 0.009838370 0.002810963 0.12579058 0.023893183 0.009135629 0.389318342\n",
       "13 0.009638554 0.002409639 0.28554217 0.026506024 0.109638554 0.498795181\n",
       "14 0.095992544 0.011338925 0.18251010 0.029356943 0.007455732 0.080770426\n",
       "15 0.081607795 0.118148599 0.22655298 0.008526188 0.020706456 0.023142509\n",
       "16 0.016359918 0.081799591 0.11656442 0.010224949 0.032719836 0.040899796\n",
       "17 0.021990741 0.011111111 0.12939815 0.013194444 0.031018519 0.035648148\n",
       "18 0.055611729 0.028311426 0.41152679 0.010111223 0.014155713 0.136501517\n",
       "19 0.054580897 0.003898635 0.53996101 0.037686810 0.011046134 0.424301494\n",
       "20 0.054545455 0.000000000 0.21333333 0.024242424 0.014545455 0.578181818\n",
       "        ricotta       roast         root     rosemari      saffron         sage\n",
       "1  0.0000000000 0.023554604 0.0085653105 0.0042826552 0.0064239829 0.0021413276\n",
       "2  0.0000000000 0.022388060 0.0024875622 0.0286069652 0.0024875622 0.0261194030\n",
       "3  0.0006468305 0.021345408 0.0000000000 0.0174644243 0.0012936611 0.0103492885\n",
       "4  0.0003741115 0.049008605 0.0527497194 0.0003741115 0.0000000000 0.0011223345\n",
       "5  0.0000000000 0.003973510 0.0145695364 0.0000000000 0.0039735099 0.0000000000\n",
       "6  0.0056689342 0.023053666 0.0068027211 0.0419501134 0.0188964475 0.0147392290\n",
       "7  0.0093617021 0.024680851 0.0017021277 0.0536170213 0.0017021277 0.0025531915\n",
       "8  0.0016650017 0.017982018 0.0496170496 0.0003330003 0.0382950383 0.0000000000\n",
       "9  0.0000000000 0.016491754 0.0029985007 0.0284857571 0.0000000000 0.0164917541\n",
       "10 0.0848430722 0.029854555 0.0007655014 0.0648124522 0.0047205920 0.0353406481\n",
       "11 0.0000000000 0.017110266 0.0304182510 0.0114068441 0.0000000000 0.0152091255\n",
       "12 0.0007027407 0.011946592 0.0358397751 0.0000000000 0.0049191848 0.0000000000\n",
       "13 0.0000000000 0.028915663 0.0192771084 0.0012048193 0.0000000000 0.0000000000\n",
       "14 0.0024852439 0.038365952 0.0006213110 0.0024852439 0.0010872942 0.0010872942\n",
       "15 0.0024360536 0.021924482 0.0097442144 0.0073081608 0.1534713764 0.0000000000\n",
       "16 0.0061349693 0.008179959 0.0184049080 0.0061349693 0.0081799591 0.0020449898\n",
       "17 0.0002314815 0.020138889 0.0016203704 0.0125000000 0.0002314815 0.0182870370\n",
       "18 0.0020222447 0.058645096 0.0000000000 0.0232558140 0.1274014156 0.0050556117\n",
       "19 0.0000000000 0.118908382 0.0532813515 0.0000000000 0.0012995452 0.0006497726\n",
       "20 0.0000000000 0.095757576 0.0327272727 0.0000000000 0.0000000000 0.0000000000\n",
       "          salsa      salt       sauc       sausag    scallion        sea\n",
       "1  0.0149892934 0.5267666 0.07494647 0.0642398287 0.017130621 0.04068522\n",
       "2  0.0000000000 0.6417910 0.10323383 0.0522388060 0.004975124 0.03233831\n",
       "3  0.0012936611 0.6423027 0.43014230 0.2994825356 0.062742561 0.02328590\n",
       "4  0.0003741115 0.4627759 1.29068462 0.0112233446 0.227459783 0.02581369\n",
       "5  0.0013245033 0.6397351 0.67682119 0.0185430464 0.023841060 0.01986755\n",
       "6  0.0000000000 0.6213152 0.03628118 0.0117157974 0.006802721 0.07974301\n",
       "7  0.0000000000 0.6357447 0.05276596 0.0025531915 0.017872340 0.03319149\n",
       "8  0.0006660007 0.7998668 0.04695305 0.0003330003 0.011988012 0.03862804\n",
       "9  0.0014992504 0.6926537 0.06296852 0.0464767616 0.020989505 0.02548726\n",
       "10 0.0016585864 0.6247767 0.17108956 0.0750191375 0.008037765 0.04337841\n",
       "11 0.0038022814 0.7965779 0.32889734 0.0000000000 0.214828897 0.03992395\n",
       "12 0.0000000000 0.4082923 0.66057625 0.0014054814 0.165846803 0.05270555\n",
       "13 0.0012048193 0.4602410 0.81445783 0.0048192771 0.237349398 0.04337349\n",
       "14 0.1992854924 0.6088847 0.23423423 0.0149114632 0.026716372 0.03091022\n",
       "15 0.0012180268 0.7320341 0.03045067 0.0133982948 0.006090134 0.05115713\n",
       "16 0.0000000000 0.7055215 0.06543967 0.0204498978 0.018404908 0.02862986\n",
       "17 0.0041666667 0.7148148 0.18472222 0.0354166667 0.016435185 0.02453704\n",
       "18 0.0131445905 0.6845298 0.07785642 0.0899898888 0.024266936 0.05257836\n",
       "19 0.0012995452 0.3801170 1.06302794 0.0000000000 0.089668616 0.03053931\n",
       "20 0.0000000000 0.4848485 1.14060606 0.0133333333 0.121212121 0.02424242\n",
       "        season       seed      serrano        sesam     shallot        sharp\n",
       "1  0.014989293 0.05567452 0.0149892934 0.0042826552 0.010706638 0.0021413276\n",
       "2  0.013681592 0.02860697 0.0012437811 0.0012437811 0.023631841 0.0248756219\n",
       "3  0.408150065 0.02199224 0.0025873221 0.0006468305 0.014877102 0.0045278137\n",
       "4  0.014216236 0.12158623 0.0056116723 0.5566778900 0.027310138 0.0003741115\n",
       "5  0.019867550 0.02251656 0.0013245033 0.0397350993 0.026490066 0.0013245033\n",
       "6  0.007936508 0.03174603 0.0007558579 0.0015117158 0.121693122 0.0026455026\n",
       "7  0.055319149 0.02978723 0.0008510638 0.0102127660 0.024680851 0.0017021277\n",
       "8  0.005328005 0.57908758 0.0452880453 0.0166500167 0.018648019 0.0000000000\n",
       "9  0.013493253 0.06296852 0.0000000000 0.0059970015 0.016491754 0.0179910045\n",
       "10 0.071191631 0.02283746 0.0008930850 0.0021689206 0.040316407 0.0048481756\n",
       "11 0.098859316 0.03612167 0.0095057034 0.0038022814 0.017110266 0.0000000000\n",
       "12 0.016865777 0.24314828 0.0014054814 0.3654251581 0.021082221 0.0007027407\n",
       "13 0.012048193 0.44337349 0.0048192771 1.0807228916 0.008433735 0.0012048193\n",
       "14 0.104069587 0.04411308 0.0366573470 0.0093196645 0.007145076 0.0259397328\n",
       "15 0.007308161 0.17052375 0.0024360536 0.0243605359 0.036540804 0.0000000000\n",
       "16 0.014314928 0.08793456 0.0000000000 0.0000000000 0.018404908 0.0020449898\n",
       "17 0.084490741 0.02592593 0.0009259259 0.0032407407 0.014814815 0.0490740741\n",
       "18 0.009100101 0.01820020 0.0333670374 0.0010111223 0.029322548 0.0010111223\n",
       "19 0.012345679 0.08836907 0.0324886290 0.1604938272 0.158544509 0.0000000000\n",
       "20 0.013333333 0.08242424 0.0448484848 0.1781818182 0.191515152 0.0000000000\n",
       "         shell      sherri      shiitak    shoulder       shred      shrimp\n",
       "1  0.004282655 0.006423983 0.0000000000 0.019271949 0.032119914 0.124197002\n",
       "2  0.007462687 0.028606965 0.0012437811 0.007462687 0.014925373 0.003731343\n",
       "3  0.009702458 0.005174644 0.0006468305 0.003880983 0.016170763 0.305950841\n",
       "4  0.002618780 0.073699963 0.0763187430 0.011223345 0.027310138 0.093901983\n",
       "5  0.002649007 0.005298013 0.0132450331 0.025165563 0.025165563 0.098013245\n",
       "6  0.011715797 0.028722600 0.0083144369 0.009070295 0.019652305 0.018140590\n",
       "7  0.005106383 0.005106383 0.0000000000 0.013617021 0.011914894 0.034042553\n",
       "8  0.000999001 0.001332001 0.0000000000 0.009990010 0.009657010 0.024975025\n",
       "9  0.002998501 0.011994003 0.0029985007 0.019490255 0.034482759 0.000000000\n",
       "10 0.016330697 0.009951518 0.0084205154 0.003189589 0.075401888 0.031640725\n",
       "11 0.001901141 0.007604563 0.0000000000 0.001901141 0.013307985 0.038022814\n",
       "12 0.005621926 0.010541110 0.0969782150 0.006324666 0.019676739 0.049894589\n",
       "13 0.001204819 0.014457831 0.0927710843 0.010843373 0.024096386 0.037349398\n",
       "14 0.019105312 0.002795899 0.0017086052 0.018484001 0.226157192 0.027648338\n",
       "15 0.006090134 0.012180268 0.0000000000 0.040194884 0.001218027 0.009744214\n",
       "16 0.000000000 0.004089980 0.0040899796 0.004089980 0.018404908 0.008179959\n",
       "17 0.011805556 0.005787037 0.0023148148 0.008101852 0.051157407 0.050231481\n",
       "18 0.005055612 0.128412538 0.0030333670 0.005055612 0.002022245 0.122345804\n",
       "19 0.004548408 0.005198181 0.0259909032 0.002599090 0.035737492 0.190383366\n",
       "20 0.003636364 0.002424242 0.0327272727 0.019393939 0.053333333 0.163636364\n",
       "      skinless      slice       smoke        soda     sodium        soup\n",
       "1  0.021413276 0.04710921 0.034261242 0.017130621 0.03426124 0.004282655\n",
       "2  0.004975124 0.02860697 0.021144279 0.105721393 0.01119403 0.003731343\n",
       "3  0.080853816 0.06468305 0.128072445 0.016817594 0.06921087 0.022639069\n",
       "4  0.123082679 0.05125327 0.001870557 0.019827909 0.17096895 0.005237561\n",
       "5  0.031788079 0.01589404 0.006622517 0.005298013 0.02781457 0.002649007\n",
       "6  0.021164021 0.05404384 0.012093726 0.006802721 0.04572940 0.008314437\n",
       "7  0.056170213 0.04936170 0.006808511 0.014468085 0.02042553 0.003404255\n",
       "8  0.074925075 0.01931402 0.011322011 0.015651016 0.02197802 0.000999001\n",
       "9  0.004497751 0.02398801 0.017991004 0.182908546 0.02698651 0.001499250\n",
       "10 0.044271498 0.05600919 0.008165348 0.009186017 0.05294718 0.010206685\n",
       "11 0.060836502 0.02851711 0.011406844 0.026615970 0.03231939 0.003802281\n",
       "12 0.045678145 0.02881237 0.015460295 0.014054814 0.08011244 0.008432888\n",
       "13 0.013253012 0.02891566 0.003614458 0.010843373 0.10120482 0.000000000\n",
       "14 0.075644610 0.05094750 0.026095061 0.005902454 0.04551103 0.031997515\n",
       "15 0.062119367 0.03897686 0.037758831 0.000000000 0.07186358 0.001218027\n",
       "16 0.014314928 0.03067485 0.030674847 0.049079755 0.01635992 0.014314928\n",
       "17 0.022685185 0.05231481 0.035879630 0.109490741 0.02337963 0.020601852\n",
       "18 0.031344793 0.05561173 0.075834176 0.018200202 0.05662285 0.002022245\n",
       "19 0.142949968 0.06497726 0.001299545 0.001949318 0.10981157 0.002599090\n",
       "20 0.060606061 0.05333333 0.000000000 0.006060606 0.07878788 0.006060606\n",
       "          sour         soy   spaghetti     spinach       spray       sprig\n",
       "1  0.012847966 0.006423983 0.000000000 0.012847966 0.006423983 0.002141328\n",
       "2  0.028606965 0.006218905 0.000000000 0.006218905 0.014925373 0.012437811\n",
       "3  0.016170763 0.009055627 0.003234153 0.011642950 0.048512290 0.016817594\n",
       "4  0.005985784 0.839506173 0.008978676 0.013468013 0.019453797 0.005611672\n",
       "5  0.005298013 0.384105960 0.003973510 0.035761589 0.005298013 0.000000000\n",
       "6  0.021164021 0.002645503 0.001511716 0.014361300 0.076719577 0.071428571\n",
       "7  0.020425532 0.005106383 0.005106383 0.093617021 0.079148936 0.022978723\n",
       "8  0.009324009 0.011655012 0.000000000 0.060939061 0.026307026 0.012654013\n",
       "9  0.047976012 0.010494753 0.000000000 0.010494753 0.092953523 0.019490255\n",
       "10 0.014289360 0.002934422 0.045547334 0.073232968 0.082546568 0.020796121\n",
       "11 0.017110266 0.153992395 0.000000000 0.026615970 0.030418251 0.020912548\n",
       "12 0.002108222 0.547434996 0.001405481 0.051300070 0.018973999 0.002810963\n",
       "13 0.003614458 0.655421687 0.001204819 0.078313253 0.018072289 0.000000000\n",
       "14 0.205498602 0.009474992 0.002640572 0.016930724 0.056073315 0.017396707\n",
       "15 0.004872107 0.004872107 0.002436054 0.014616322 0.052375152 0.035322777\n",
       "16 0.259713701 0.006134969 0.000000000 0.008179959 0.012269939 0.004089980\n",
       "17 0.031712963 0.008101852 0.000462963 0.004861111 0.047685185 0.017361111\n",
       "18 0.019211325 0.004044489 0.005055612 0.019211325 0.049544995 0.027300303\n",
       "19 0.000000000 0.328784925 0.005847953 0.024041585 0.029889539 0.021442495\n",
       "20 0.001212121 0.286060606 0.004848485 0.009696970 0.023030303 0.037575758\n",
       "         spring      squash      starch       steak       stick      stock\n",
       "1  0.0085653105 0.004282655 0.047109208 0.025695931 0.008565310 0.06209850\n",
       "2  0.0049751244 0.002487562 0.039800995 0.032338308 0.011194030 0.06094527\n",
       "3  0.0012936611 0.005174644 0.018111255 0.010349288 0.003880983 0.09573092\n",
       "4  0.0639730640 0.002244669 0.356154134 0.049008605 0.018705574 0.08567153\n",
       "5  0.0423841060 0.007947020 0.075496689 0.011920530 0.009271523 0.04105960\n",
       "6  0.0011337868 0.011337868 0.035147392 0.023053666 0.007936508 0.04610733\n",
       "7  0.0034042553 0.005957447 0.008510638 0.017021277 0.027234043 0.02042553\n",
       "8  0.0046620047 0.009657010 0.014652015 0.005661006 0.086580087 0.03529804\n",
       "9  0.0104947526 0.001499250 0.019490255 0.010494753 0.008995502 0.07346327\n",
       "10 0.0006379178 0.018627201 0.010972187 0.012375606 0.003827507 0.03444756\n",
       "11 0.0152091255 0.011406844 0.020912548 0.017110266 0.013307985 0.07224335\n",
       "12 0.0295151089 0.007027407 0.078004216 0.035137034 0.007027407 0.04497540\n",
       "13 0.0554216867 0.004819277 0.056626506 0.102409639 0.004819277 0.03975904\n",
       "14 0.0023299161 0.010096303 0.009164337 0.026405716 0.010872942 0.03852128\n",
       "15 0.0024360536 0.053593179 0.000000000 0.015834348 0.087697929 0.12545676\n",
       "16 0.0000000000 0.000000000 0.028629857 0.018404908 0.016359918 0.04089980\n",
       "17 0.0002314815 0.008333333 0.036805556 0.014814815 0.006481481 0.02731481\n",
       "18 0.0000000000 0.003033367 0.017189080 0.006066734 0.034378160 0.05864510\n",
       "19 0.0383365822 0.020792723 0.048732943 0.047433398 0.031189084 0.07732294\n",
       "20 0.0763636364 0.009696970 0.080000000 0.078787879 0.076363636 0.06181818\n",
       "       sugar      sweet     sweeten       syrup         taco         thai\n",
       "1  0.3211991 0.03854390 0.130620985 0.034261242 0.0000000000 0.0021413276\n",
       "2  0.5646766 0.02611940 0.013681592 0.050995025 0.0000000000 0.0012437811\n",
       "3  0.2005175 0.04915912 0.004527814 0.011642950 0.0006468305 0.0000000000\n",
       "4  0.5308642 0.03142536 0.003367003 0.009352787 0.0003741115 0.0145903479\n",
       "5  0.4225166 0.05430464 0.037086093 0.003973510 0.0013245033 0.0384105960\n",
       "6  0.4368859 0.01209373 0.009448224 0.022675737 0.0000000000 0.0000000000\n",
       "7  0.1242553 0.01361702 0.001702128 0.003404255 0.0000000000 0.0000000000\n",
       "8  0.1774892 0.03163503 0.007659008 0.002331002 0.0000000000 0.0066600067\n",
       "9  0.4587706 0.01799100 0.011994003 0.016491754 0.0000000000 0.0000000000\n",
       "10 0.1758102 0.02538913 0.002041337 0.004465425 0.0000000000 0.0002551671\n",
       "11 0.3878327 0.05133080 0.022813688 0.015209125 0.0000000000 0.0000000000\n",
       "12 0.4567814 0.02881237 0.007027407 0.007027407 0.0000000000 0.0049191848\n",
       "13 0.5879518 0.05301205 0.000000000 0.055421687 0.0000000000 0.0060240964\n",
       "14 0.1071761 0.03510407 0.007921715 0.003261883 0.0989437714 0.0000000000\n",
       "15 0.1583435 0.12667479 0.000000000 0.003654080 0.0000000000 0.0000000000\n",
       "16 0.5132924 0.03680982 0.006134969 0.012269939 0.0000000000 0.0000000000\n",
       "17 0.5368056 0.07314815 0.028935185 0.062731481 0.0004629630 0.0000000000\n",
       "18 0.1900910 0.06066734 0.016177958 0.007077856 0.0000000000 0.0000000000\n",
       "19 0.5620533 0.08317089 0.007797271 0.014294997 0.0000000000 0.3164392463\n",
       "20 0.6618182 0.03151515 0.024242424 0.004848485 0.0000000000 0.1624242424\n",
       "         thigh       thyme       toast         tofu      tomato     tortilla\n",
       "1  0.012847966 0.027837259 0.010706638 0.0021413276 0.284796574 0.0021413276\n",
       "2  0.000000000 0.077114428 0.008706468 0.0000000000 0.065920398 0.0000000000\n",
       "3  0.035575679 0.276843467 0.005174644 0.0006468305 0.435316947 0.0038809832\n",
       "4  0.032547699 0.003741115 0.093153760 0.0662177329 0.041526375 0.0044893378\n",
       "5  0.041059603 0.007947020 0.001324503 0.0172185430 0.161589404 0.0026490066\n",
       "6  0.015873016 0.201814059 0.012471655 0.0018896447 0.161375661 0.0003779289\n",
       "7  0.009361702 0.060425532 0.005106383 0.0000000000 0.422127660 0.0042553191\n",
       "8  0.043956044 0.006660007 0.005661006 0.0136530137 0.419247419 0.0026640027\n",
       "9  0.000000000 0.103448276 0.007496252 0.0000000000 0.065967016 0.0014992504\n",
       "10 0.008292932 0.066853789 0.008037765 0.0021689206 0.426894616 0.0021689206\n",
       "11 0.032319392 0.562737643 0.005703422 0.0000000000 0.161596958 0.0095057034\n",
       "12 0.045678145 0.002108222 0.096275474 0.0892480675 0.054813774 0.0007027407\n",
       "13 0.015662651 0.001204819 0.230120482 0.0807228916 0.008433735 0.0120481928\n",
       "14 0.014445480 0.010562286 0.003727866 0.0020192606 0.445479963 0.3937558248\n",
       "15 0.063337393 0.026796590 0.017052375 0.0012180268 0.375152253 0.0000000000\n",
       "16 0.002044990 0.022494888 0.010224949 0.0040899796 0.167689162 0.0020449898\n",
       "17 0.011342593 0.059953704 0.006712963 0.0000000000 0.108564815 0.0020833333\n",
       "18 0.031344793 0.073811931 0.004044489 0.0000000000 0.440849343 0.0080889788\n",
       "19 0.040285900 0.002599090 0.035087719 0.0688758934 0.096166342 0.0097465887\n",
       "20 0.021818182 0.000000000 0.044848485 0.0666666667 0.070303030 0.0036363636\n",
       "          tumer      turkey       turmer      unsalt    unsweeten     vanilla\n",
       "1  0.0064239829 0.010706638 0.0085653105 0.055674518 0.0620985011 0.059957173\n",
       "2  0.0111940299 0.002487562 0.0037313433 0.240049751 0.0024875622 0.148009950\n",
       "3  0.0006468305 0.040103493 0.0006468305 0.076972833 0.0019404916 0.047865459\n",
       "4  0.0000000000 0.008604564 0.0022446689 0.017957351 0.0029928919 0.008230453\n",
       "5  0.0013245033 0.001324503 0.0066225166 0.009271523 0.0066225166 0.049006623\n",
       "6  0.0003779289 0.008314437 0.0007558579 0.225623583 0.0234315949 0.152305367\n",
       "7  0.0000000000 0.011914894 0.0042553191 0.052765957 0.0008510638 0.029787234\n",
       "8  0.1694971695 0.003663004 0.2437562438 0.029637030 0.0149850150 0.005994006\n",
       "9  0.0014992504 0.005997001 0.0000000000 0.130434783 0.0149925037 0.076461769\n",
       "10 0.0007655014 0.023730544 0.0002551671 0.073998469 0.0118652718 0.041592243\n",
       "11 0.0285171103 0.005703422 0.0247148289 0.036121673 0.0304182510 0.070342205\n",
       "12 0.0203794800 0.002108222 0.0238931834 0.014757554 0.0000000000 0.014054814\n",
       "13 0.0000000000 0.006024096 0.0000000000 0.004819277 0.0000000000 0.004819277\n",
       "14 0.0007766387 0.028114321 0.0015532774 0.024852439 0.0104069587 0.023299161\n",
       "15 0.1364190012 0.009744214 0.0889159562 0.057247259 0.0012180268 0.007308161\n",
       "16 0.0020449898 0.012269939 0.0000000000 0.192229039 0.0143149284 0.128834356\n",
       "17 0.0020833333 0.011342593 0.0027777778 0.152777778 0.0159722222 0.180092593\n",
       "18 0.0091001011 0.018200202 0.0030333670 0.044489383 0.0030333670 0.047522750\n",
       "19 0.0253411306 0.011695906 0.0266406758 0.035737492 0.0786224821 0.001949318\n",
       "20 0.0157575758 0.007272727 0.0230303030 0.040000000 0.0060606061 0.004848485\n",
       "        veget    vinegar        warm     water        wedg       wheat\n",
       "1  0.09850107 0.05567452 0.004282655 0.2398287 0.032119914 0.006423983\n",
       "2  0.10199005 0.08830846 0.018656716 0.2213930 0.009950249 0.018656716\n",
       "3  0.20245796 0.04657180 0.015523933 0.2199224 0.010349288 0.003234153\n",
       "4  0.27085672 0.32547699 0.012719790 0.4223719 0.003741115 0.008978676\n",
       "5  0.14304636 0.22781457 0.011920530 0.4609272 0.005298013 0.001324503\n",
       "6  0.06386999 0.12358277 0.017006803 0.2498110 0.004535147 0.009448224\n",
       "7  0.04680851 0.14638298 0.013617021 0.1574468 0.016170213 0.027234043\n",
       "8  0.24775225 0.05094905 0.019980020 0.3220113 0.016317016 0.028305028\n",
       "9  0.10644678 0.06146927 0.010494753 0.1814093 0.005997001 0.082458771\n",
       "10 0.06902271 0.09874968 0.023347793 0.1892064 0.008037765 0.022071957\n",
       "11 0.23003802 0.17110266 0.009505703 0.3992395 0.009505703 0.003802281\n",
       "12 0.20520028 0.23682361 0.007730148 0.3366128 0.014054814 0.011243851\n",
       "13 0.16265060 0.26024096 0.004819277 0.3349398 0.000000000 0.006024096\n",
       "14 0.15486176 0.06756757 0.008698354 0.1707052 0.039763902 0.017707363\n",
       "15 0.14372716 0.04993910 0.024360536 0.3081608 0.020706456 0.014616322\n",
       "16 0.18609407 0.15132924 0.044989775 0.3415133 0.004089980 0.016359918\n",
       "17 0.15231481 0.10625000 0.007175926 0.2071759 0.006250000 0.010879630\n",
       "18 0.08190091 0.21638018 0.008088979 0.2082912 0.029322548 0.004044489\n",
       "19 0.26900585 0.15139701 0.005847953 0.2475634 0.074074074 0.007797271\n",
       "20 0.20727273 0.23636364 0.029090909 0.3612121 0.052121212 0.009696970\n",
       "          whip      white       whole       wine worcestershir       yeast\n",
       "1  0.008565310 0.19486081 0.032119914 0.06423983  0.0042826552 0.012847966\n",
       "2  0.101990050 0.20895522 0.095771144 0.08208955  0.0659203980 0.050995025\n",
       "3  0.026520052 0.23997413 0.049805951 0.06791721  0.1261319534 0.036222510\n",
       "4  0.002244669 0.32435466 0.010475122 0.25925926  0.0145903479 0.012345679\n",
       "5  0.001324503 0.20662252 0.033112583 0.02251656  0.0119205298 0.022516556\n",
       "6  0.093726379 0.31368103 0.074829932 0.25056689  0.0075585790 0.028722600\n",
       "7  0.002553191 0.14893617 0.047659574 0.16936170  0.0025531915 0.012765957\n",
       "8  0.007659008 0.08225108 0.062271062 0.01831502  0.0006660007 0.024309024\n",
       "9  0.053973013 0.15142429 0.103448276 0.04497751  0.0344827586 0.008995502\n",
       "10 0.035595815 0.21816790 0.057540189 0.19405461  0.0076550140 0.031640725\n",
       "11 0.005703422 0.17300380 0.019011407 0.04562738  0.0190114068 0.022813688\n",
       "12 0.001405481 0.21082221 0.017568517 0.04567814  0.0154602952 0.004919185\n",
       "13 0.000000000 0.17831325 0.006024096 0.10120482  0.0012048193 0.002409639\n",
       "14 0.011183597 0.15672569 0.055452004 0.02485244  0.0104069587 0.005125815\n",
       "15 0.002436054 0.08038977 0.034104750 0.06211937  0.0000000000 0.024360536\n",
       "16 0.036809816 0.19427403 0.057259714 0.07770961  0.0122699387 0.116564417\n",
       "17 0.056250000 0.19375000 0.075925926 0.03726852  0.0421296296 0.009259259\n",
       "18 0.017189080 0.24974722 0.034378160 0.27300303  0.0141557128 0.012133468\n",
       "19 0.001949318 0.13125406 0.008447044 0.03183886  0.0025990903 0.001299545\n",
       "20 0.000000000 0.17090909 0.013333333 0.04000000  0.0012121212 0.002424242\n",
       "       yellow      yogurt         yolk        zest    zucchini\n",
       "1  0.07280514 0.006423983 0.0471092077 0.017130621 0.006423983\n",
       "2  0.03233831 0.009950249 0.0833333333 0.026119403 0.003731343\n",
       "3  0.09443726 0.001940492 0.0219922380 0.008408797 0.008408797\n",
       "4  0.03105125 0.000748223 0.0078563412 0.012345679 0.011971568\n",
       "5  0.04635762 0.000000000 0.0278145695 0.003973510 0.007947020\n",
       "6  0.03552532 0.008692366 0.1311413454 0.038170824 0.034013605\n",
       "7  0.03829787 0.238297872 0.0238297872 0.059574468 0.041702128\n",
       "8  0.07359307 0.191808192 0.0009990010 0.007326007 0.014319014\n",
       "9  0.04047976 0.017991004 0.0269865067 0.029985007 0.005997001\n",
       "10 0.04669559 0.004337841 0.0288338862 0.034702730 0.043378413\n",
       "11 0.06653992 0.003802281 0.0038022814 0.013307985 0.009505703\n",
       "12 0.03373155 0.002810963 0.0344342937 0.009838370 0.012649332\n",
       "13 0.04819277 0.001204819 0.0120481928 0.003614458 0.065060241\n",
       "14 0.06927617 0.017862690 0.0068344206 0.010717614 0.022833178\n",
       "15 0.08038977 0.041412911 0.0097442144 0.038976857 0.048721072\n",
       "16 0.01840491 0.026584867 0.0736196319 0.020449898 0.004089980\n",
       "17 0.08726852 0.008564815 0.0337962963 0.023611111 0.003240741\n",
       "18 0.06471183 0.011122346 0.0414560162 0.033367037 0.019211325\n",
       "19 0.04418454 0.004548408 0.0006497726 0.035737492 0.029889539\n",
       "20 0.08363636 0.002424242 0.0084848485 0.006060606 0.003636364"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "aggregate(ingredientsDTM_train[,c(1:250)], list(ingredientsDTM_train[,251]), mean)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "ingredientsDTM_train_korea <- ingredientsDTM_train[ingredientsDTM_train$cuisine == \"korean\",]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th></th><th scope=col>all-purpos</th><th scope=col>allspic</th><th scope=col>almond</th><th scope=col>and</th><th scope=col>appl</th><th scope=col>avocado</th><th scope=col>babi</th><th scope=col>bacon</th><th scope=col>bake</th><th scope=col>balsam</th><th scope=col>basil</th><th scope=col>bay</th><th scope=col>bean</th><th scope=col>beansprout</th><th scope=col>beef</th><th scope=col>bell</th><th scope=col>black</th><th scope=col>boil</th><th scope=col>boneless</th><th scope=col>bread</th><th scope=col>breast</th><th scope=col>broccoli</th><th scope=col>broth</th><th scope=col>brown</th><th scope=col>butter</th><th scope=col>buttermilk</th><th scope=col>cabbag</th><th scope=col>canola</th><th scope=col>caper</th><th scope=col>cardamom</th><th scope=col>carrot</th><th scope=col>cayenn</th><th scope=col>celeri</th><th scope=col>cheddar</th><th scope=col>chees</th><th scope=col>cherri</th><th scope=col>chicken</th><th scope=col>chickpea</th><th scope=col>chile</th><th scope=col>chili</th><th scope=col>chines</th><th scope=col>chip</th><th scope=col>chipotl</th><th scope=col>chive</th><th scope=col>chocol</th><th scope=col>chop</th><th scope=col>cider</th><th scope=col>cilantro</th><th scope=col>cinnamon</th><th scope=col>clove</th><th scope=col>coars</th><th scope=col>coconut</th><th scope=col>cold</th><th scope=col>condens</th><th scope=col>confection</th><th scope=col>cook</th><th scope=col>coriand</th><th scope=col>corn</th><th scope=col>cornmeal</th><th scope=col>crack</th><th scope=col>cream</th><th scope=col>crumb</th><th scope=col>crumbl</th><th scope=col>crush</th><th scope=col>cucumb</th><th scope=col>cumin</th><th scope=col>curri</th><th scope=col>dark</th><th scope=col>dice</th><th scope=col>dijon</th><th scope=col>dill</th><th scope=col>dough</th><th scope=col>dress</th><th scope=col>dri</th><th scope=col>egg</th><th scope=col>eggplant</th><th scope=col>enchilada</th><th scope=col>extra-virgin</th><th scope=col>extract</th><th scope=col>fat</th><th scope=col>fennel</th><th scope=col>feta</th><th scope=col>fillet</th><th scope=col>fine</th><th scope=col>firm</th><th scope=col>fish</th><th scope=col>flake</th><th scope=col>flat</th><th scope=col>flour</th><th scope=col>free</th><th scope=col>fresh</th><th scope=col>frozen</th><th scope=col>garam</th><th scope=col>garlic</th><th scope=col>ginger</th><th scope=col>golden</th><th scope=col>granul</th><th scope=col>grate</th><th scope=col>greek</th><th scope=col>green</th><th scope=col>ground</th><th scope=col>halv</th><th scope=col>ham</th><th scope=col>heavi</th><th scope=col>hoisin</th><th scope=col>honey</th><th scope=col>hot</th><th scope=col>ice</th><th scope=col>italian</th><th scope=col>jack</th><th scope=col>jalapeno</th><th scope=col>juic</th><th scope=col>kalamata</th><th scope=col>kernel</th><th scope=col>ketchup</th><th scope=col>kosher</th><th scope=col>lamb</th><th scope=col>larg</th><th scope=col>leaf</th><th scope=col>lean</th><th scope=col>leav</th><th scope=col>leek</th><th scope=col>lemon</th><th scope=col>less</th><th scope=col>lettuc</th><th scope=col>light</th><th scope=col>lime</th><th scope=col>low</th><th scope=col>low-fat</th><th scope=col>masala</th><th scope=col>mayonais</th><th scope=col>meat</th><th scope=col>medium</th><th scope=col>mexican</th><th scope=col>milk</th><th scope=col>minc</th><th scope=col>mint</th><th scope=col>mirin</th><th scope=col>mix</th><th scope=col>monterey</th><th scope=col>mozzarella</th><th scope=col>mushroom</th><th scope=col>mustard</th><th scope=col>noodl</th><th scope=col>nutmeg</th><th scope=col>oil</th><th scope=col>oliv</th><th scope=col>onion</th><th scope=col>orang</th><th scope=col>oregano</th><th scope=col>oyster</th><th scope=col>paprika</th><th scope=col>parmesan</th><th scope=col>parsley</th><th scope=col>past</th><th scope=col>pasta</th><th scope=col>pea</th><th scope=col>peanut</th><th scope=col>pecan</th><th scope=col>peel</th><th scope=col>pepper</th><th scope=col>peppercorn</th><th scope=col>plain</th><th scope=col>plum</th><th scope=col>pork</th><th scope=col>potato</th><th scope=col>powder</th><th scope=col>purpl</th><th scope=col>raisin</th><th scope=col>red</th><th scope=col>reduc</th><th scope=col>rib</th><th scope=col>rice</th><th scope=col>ricotta</th><th scope=col>roast</th><th scope=col>root</th><th scope=col>rosemari</th><th scope=col>saffron</th><th scope=col>sage</th><th scope=col>salsa</th><th scope=col>salt</th><th scope=col>sauc</th><th scope=col>sausag</th><th scope=col>scallion</th><th scope=col>sea</th><th scope=col>season</th><th scope=col>seed</th><th scope=col>serrano</th><th scope=col>sesam</th><th scope=col>shallot</th><th scope=col>sharp</th><th scope=col>shell</th><th scope=col>sherri</th><th scope=col>shiitak</th><th scope=col>shoulder</th><th scope=col>shred</th><th scope=col>shrimp</th><th scope=col>skinless</th><th scope=col>slice</th><th scope=col>smoke</th><th scope=col>soda</th><th scope=col>sodium</th><th scope=col>soup</th><th scope=col>sour</th><th scope=col>soy</th><th scope=col>spaghetti</th><th scope=col>spinach</th><th scope=col>spray</th><th scope=col>sprig</th><th scope=col>spring</th><th scope=col>squash</th><th scope=col>starch</th><th scope=col>steak</th><th scope=col>stick</th><th scope=col>stock</th><th scope=col>sugar</th><th scope=col>sweet</th><th scope=col>sweeten</th><th scope=col>syrup</th><th scope=col>taco</th><th scope=col>thai</th><th scope=col>thigh</th><th scope=col>thyme</th><th scope=col>toast</th><th scope=col>tofu</th><th scope=col>tomato</th><th scope=col>tortilla</th><th scope=col>tumer</th><th scope=col>turkey</th><th scope=col>turmer</th><th scope=col>unsalt</th><th scope=col>unsweeten</th><th scope=col>vanilla</th><th scope=col>veget</th><th scope=col>vinegar</th><th scope=col>warm</th><th scope=col>water</th><th scope=col>wedg</th><th scope=col>wheat</th><th scope=col>whip</th><th scope=col>white</th><th scope=col>whole</th><th scope=col>wine</th><th scope=col>worcestershir</th><th scope=col>yeast</th><th scope=col>yellow</th><th scope=col>yogurt</th><th scope=col>yolk</th><th scope=col>zest</th><th scope=col>zucchini</th><th scope=col>cuisine</th></tr></thead>\n",
       "<tbody>\n",
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       "\t<tr><th scope=row>105</th><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>korean</td></tr>\n",
       "\t<tr><th scope=row>110</th><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>1</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>korean</td></tr>\n",
       "\t<tr><th scope=row>141</th><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>korean</td></tr>\n",
       "\t<tr><th scope=row>158</th><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>1</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>2</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>korean</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllll}\n",
       "  & all-purpos & allspic & almond & and & appl & avocado & babi & bacon & bake & balsam & basil & bay & bean & beansprout & beef & bell & black & boil & boneless & bread & breast & broccoli & broth & brown & butter & buttermilk & cabbag & canola & caper & cardamom & carrot & cayenn & celeri & cheddar & chees & cherri & chicken & chickpea & chile & chili & chines & chip & chipotl & chive & chocol & chop & cider & cilantro & cinnamon & clove & coars & coconut & cold & condens & confection & cook & coriand & corn & cornmeal & crack & cream & crumb & crumbl & crush & cucumb & cumin & curri & dark & dice & dijon & dill & dough & dress & dri & egg & eggplant & enchilada & extra-virgin & extract & fat & fennel & feta & fillet & fine & firm & fish & flake & flat & flour & free & fresh & frozen & garam & garlic & ginger & golden & granul & grate & greek & green & ground & halv & ham & heavi & hoisin & honey & hot & ice & italian & jack & jalapeno & juic & kalamata & kernel & ketchup & kosher & lamb & larg & leaf & lean & leav & leek & lemon & less & lettuc & light & lime & low & low-fat & masala & mayonais & meat & medium & mexican & milk & minc & mint & mirin & mix & monterey & mozzarella & mushroom & mustard & noodl & nutmeg & oil & oliv & onion & orang & oregano & oyster & paprika & parmesan & parsley & past & pasta & pea & peanut & pecan & peel & pepper & peppercorn & plain & plum & pork & potato & powder & purpl & raisin & red & reduc & rib & rice & ricotta & roast & root & rosemari & saffron & sage & salsa & salt & sauc & sausag & scallion & sea & season & seed & serrano & sesam & shallot & sharp & shell & sherri & shiitak & shoulder & shred & shrimp & skinless & slice & smoke & soda & sodium & soup & sour & soy & spaghetti & spinach & spray & sprig & spring & squash & starch & steak & stick & stock & sugar & sweet & sweeten & syrup & taco & thai & thigh & thyme & toast & tofu & tomato & tortilla & tumer & turkey & turmer & unsalt & unsweeten & vanilla & veget & vinegar & warm & water & wedg & wheat & whip & white & whole & wine & worcestershir & yeast & yellow & yogurt & yolk & zest & zucchini & cuisine\\\\\n",
       "\\hline\n",
       "\t67 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 2 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 1 & 0 & 0 & 1 & 0 & 2 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & korean\\\\\n",
       "\t89 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & korean\\\\\n",
       "\t105 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 1 & 0 & 0 & 1 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & korean\\\\\n",
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       "\t158 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 1 & 0 & 0 & 1 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 2 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & korean\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "    all-purpos allspic almond and appl avocado babi bacon bake balsam basil bay\n",
       "67           0       0      0   0    0       0    0     0    0      0     0   0\n",
       "89           0       0      0   0    0       0    0     0    0      0     0   0\n",
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       "158          0       0      0   0    0       0    0     0    0      0     0   0\n",
       "    bean beansprout beef bell black boil boneless bread breast broccoli broth\n",
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       "89     0          0    0    0     0    0        0     0      0        0     0\n",
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       "    brown butter buttermilk cabbag canola caper cardamom carrot cayenn celeri\n",
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       "89      0      0          0      0      0     0        0      0      0      0\n",
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       "141     0      0          0      0      0     0        0      0      0      0\n",
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       "    cheddar chees cherri chicken chickpea chile chili chines chip chipotl chive\n",
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       "89        0     0      0       0        0     0     0      0    0       0     0\n",
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       "    chocol chop cider cilantro cinnamon clove coars coconut cold condens\n",
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       "    confection cook coriand corn cornmeal crack cream crumb crumbl crush cucumb\n",
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       "    cumin curri dark dice dijon dill dough dress dri egg eggplant enchilada\n",
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       "    free fresh frozen garam garlic ginger golden granul grate greek green\n",
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       "    ground halv ham heavi hoisin honey hot ice italian jack jalapeno juic\n",
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       "    kalamata kernel ketchup kosher lamb larg leaf lean leav leek lemon less\n",
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       "    lettuc light lime low low-fat masala mayonais meat medium mexican milk minc\n",
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       "158      0     0    0   0       0      0        0    0      0       0    0    0\n",
       "    mint mirin mix monterey mozzarella mushroom mustard noodl nutmeg oil oliv\n",
       "67     0     0   0        0          0        0       0     0      0   1    0\n",
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       "141    0     0   0        0          0        0       0     0      0   1    0\n",
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       "    onion orang oregano oyster paprika parmesan parsley past pasta pea peanut\n",
       "67      0     0       0      0       0        0       0    0     0   0      0\n",
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       "141     1     0       0      0       0        0       0    0     0   0      0\n",
       "158     0     0       0      0       0        0       0    1     0   0      0\n",
       "    pecan peel pepper peppercorn plain plum pork potato powder purpl raisin red\n",
       "67      0    0      0          0     0    0    0      0      0     0      0   0\n",
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       "    reduc rib rice ricotta roast root rosemari saffron sage salsa salt sauc\n",
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       "158     0   0    0       0     0    0        0       0    0     0    1    1\n",
       "    sausag scallion sea season seed serrano sesam shallot sharp shell sherri\n",
       "67       0        1   0      0    1       0     2       0     0     0      0\n",
       "89       0        0   0      0    0       0     0       0     0     0      0\n",
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       "141      0        0   0      0    0       0     1       0     0     0      0\n",
       "158      0        0   0      0    0       0     0       0     0     0      0\n",
       "    shiitak shoulder shred shrimp skinless slice smoke soda sodium soup sour\n",
       "67        1        0     0      0        0     0     0    0      0    0    0\n",
       "89        0        0     0      0        0     0     0    0      0    0    0\n",
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       "    soy spaghetti spinach spray sprig spring squash starch steak stick stock\n",
       "67    1         0       0     0     0      0      0      0     1     0     0\n",
       "89    0         0       0     0     0      0      0      0     0     0     0\n",
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       "141   0         0       0     0     0      0      0      0     0     0     0\n",
       "158   1         0       0     0     0      0      0      0     0     0     0\n",
       "    sugar sweet sweeten syrup taco thai thigh thyme toast tofu tomato tortilla\n",
       "67      1     0       0     0    0    0     0     0     0    0      0        0\n",
       "89      0     0       0     0    0    0     0     0     0    0      0        0\n",
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       "141     0     0       0     0    0    0     0     0     0    0      0        0\n",
       "158     1     0       0     0    0    0     0     0     0    0      0        0\n",
       "    tumer turkey turmer unsalt unsweeten vanilla veget vinegar warm water wedg\n",
       "67      0      0      0      0         0       0     0       1    0     0    0\n",
       "89      0      0      0      0         0       0     0       0    0     1    0\n",
       "105     0      0      0      0         0       0     0       0    0     0    0\n",
       "110     0      0      0      0         0       0     0       0    0     1    0\n",
       "141     0      0      0      0         0       0     0       0    0     0    0\n",
       "158     0      0      0      0         0       0     0       0    0     0    0\n",
       "    wheat whip white whole wine worcestershir yeast yellow yogurt yolk zest\n",
       "67      0    0     0     0    0             0     0      0      0    0    0\n",
       "89      0    0     0     0    0             0     0      0      0    0    0\n",
       "105     0    0     0     0    0             0     0      0      0    0    0\n",
       "110     0    0     0     0    0             0     0      0      0    0    0\n",
       "141     0    0     0     0    0             0     0      0      0    0    0\n",
       "158     0    0     0     0    0             0     0      0      0    0    0\n",
       "    zucchini cuisine\n",
       "67         0  korean\n",
       "89         0  korean\n",
       "105        0  korean\n",
       "110        0  korean\n",
       "141        0  korean\n",
       "158        0  korean"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "head(ingredientsDTM_train_korea)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "ingredients_korea_sum <- apply(ingredientsDTM_train_korea[,-251], 2, sum)\n",
    "ingredients_korea_mean <- apply(ingredientsDTM_train_korea[,-251], 2, mean)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "ingredients_korea_sum <- ingredients_korea_sum[order(ingredients_korea_sum, decreasing=T)]\n",
    "ingredients_korea_mean <- ingredients_korea_mean[order(ingredients_korea_mean, decreasing=T)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/pdf": 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",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/svg+xml": {
       "isolated": true
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "barplot(ingredients_korea_sum[1:30], las=2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<ol class=list-inline>\n",
       "\t<li>\"sesam\"</li>\n",
       "\t<li>\"oil\"</li>\n",
       "\t<li>\"sauc\"</li>\n",
       "\t<li>\"garlic\"</li>\n",
       "\t<li>\"onion\"</li>\n",
       "\t<li>\"pepper\"</li>\n",
       "\t<li>\"soy\"</li>\n",
       "\t<li>\"sugar\"</li>\n",
       "\t<li>\"rice\"</li>\n",
       "\t<li>\"salt\"</li>\n",
       "\t<li>\"seed\"</li>\n",
       "\t<li>\"green\"</li>\n",
       "\t<li>\"ginger\"</li>\n",
       "\t<li>\"water\"</li>\n",
       "\t<li>\"red\"</li>\n",
       "\t<li>\"vinegar\"</li>\n",
       "\t<li>\"scallion\"</li>\n",
       "\t<li>\"black\"</li>\n",
       "\t<li>\"ground\"</li>\n",
       "\t<li>\"toast\"</li>\n",
       "\t<li>\"fresh\"</li>\n",
       "\t<li>\"clove\"</li>\n",
       "\t<li>\"carrot\"</li>\n",
       "\t<li>\"egg\"</li>\n",
       "\t<li>\"brown\"</li>\n",
       "\t<li>\"beef\"</li>\n",
       "\t<li>\"chili\"</li>\n",
       "\t<li>\"flake\"</li>\n",
       "\t<li>\"white\"</li>\n",
       "\t<li>\"veget\"</li>\n",
       "\t<li>\"minc\"</li>\n",
       "\t<li>\"cabbag\"</li>\n",
       "\t<li>\"chicken\"</li>\n",
       "\t<li>\"past\"</li>\n",
       "\t<li>\"rib\"</li>\n",
       "\t<li>\"pork\"</li>\n",
       "\t<li>\"mushroom\"</li>\n",
       "\t<li>\"flour\"</li>\n",
       "\t<li>\"steak\"</li>\n",
       "\t<li>\"sodium\"</li>\n",
       "\t<li>\"wine\"</li>\n",
       "\t<li>\"cucumb\"</li>\n",
       "\t<li>\"honey\"</li>\n",
       "\t<li>\"chile\"</li>\n",
       "\t<li>\"shiitak\"</li>\n",
       "\t<li>\"kosher\"</li>\n",
       "\t<li>\"cook\"</li>\n",
       "\t<li>\"dark\"</li>\n",
       "\t<li>\"tofu\"</li>\n",
       "\t<li>\"corn\"</li>\n",
       "\t<li>\"spinach\"</li>\n",
       "\t<li>\"bean\"</li>\n",
       "\t<li>\"powder\"</li>\n",
       "\t<li>\"juic\"</li>\n",
       "\t<li>\"fish\"</li>\n",
       "\t<li>\"mirin\"</li>\n",
       "\t<li>\"noodl\"</li>\n",
       "\t<li>\"zucchini\"</li>\n",
       "\t<li>\"larg\"</li>\n",
       "\t<li>\"potato\"</li>\n",
       "\t<li>\"low\"</li>\n",
       "\t<li>\"crush\"</li>\n",
       "\t<li>\"starch\"</li>\n",
       "\t<li>\"canola\"</li>\n",
       "\t<li>\"lettuc\"</li>\n",
       "\t<li>\"spring\"</li>\n",
       "\t<li>\"syrup\"</li>\n",
       "\t<li>\"chop\"</li>\n",
       "\t<li>\"dri\"</li>\n",
       "\t<li>\"sweet\"</li>\n",
       "\t<li>\"oliv\"</li>\n",
       "\t<li>\"hot\"</li>\n",
       "\t<li>\"yellow\"</li>\n",
       "\t<li>\"leav\"</li>\n",
       "\t<li>\"broth\"</li>\n",
       "\t<li>\"light\"</li>\n",
       "\t<li>\"sea\"</li>\n",
       "\t<li>\"firm\"</li>\n",
       "\t<li>\"stock\"</li>\n",
       "\t<li>\"beansprout\"</li>\n",
       "\t<li>\"all-purpos\"</li>\n",
       "\t<li>\"bell\"</li>\n",
       "\t<li>\"shrimp\"</li>\n",
       "\t<li>\"appl\"</li>\n",
       "\t<li>\"boneless\"</li>\n",
       "\t<li>\"granul\"</li>\n",
       "\t<li>\"roast\"</li>\n",
       "\t<li>\"slice\"</li>\n",
       "\t<li>\"babi\"</li>\n",
       "\t<li>\"reduc\"</li>\n",
       "\t<li>\"chive\"</li>\n",
       "\t<li>\"peel\"</li>\n",
       "\t<li>\"chines\"</li>\n",
       "\t<li>\"cold\"</li>\n",
       "\t<li>\"lemon\"</li>\n",
       "\t<li>\"oyster\"</li>\n",
       "\t<li>\"shred\"</li>\n",
       "\t<li>\"peanut\"</li>\n",
       "\t<li>\"cilantro\"</li>\n",
       "\t<li>\"meat\"</li>\n",
       "\t<li>\"cayenn\"</li>\n",
       "\t<li>\"coars\"</li>\n",
       "\t<li>\"jalapeno\"</li>\n",
       "\t<li>\"root\"</li>\n",
       "\t<li>\"butter\"</li>\n",
       "\t<li>\"spray\"</li>\n",
       "\t<li>\"chees\"</li>\n",
       "\t<li>\"ketchup\"</li>\n",
       "\t<li>\"mustard\"</li>\n",
       "\t<li>\"thigh\"</li>\n",
       "\t<li>\"cider\"</li>\n",
       "\t<li>\"sherri\"</li>\n",
       "\t<li>\"lean\"</li>\n",
       "\t<li>\"lime\"</li>\n",
       "\t<li>\"paprika\"</li>\n",
       "\t<li>\"skinless\"</li>\n",
       "\t<li>\"bake\"</li>\n",
       "\t<li>\"breast\"</li>\n",
       "\t<li>\"leaf\"</li>\n",
       "\t<li>\"medium\"</li>\n",
       "\t<li>\"season\"</li>\n",
       "\t<li>\"tortilla\"</li>\n",
       "\t<li>\"yolk\"</li>\n",
       "\t<li>\"leek\"</li>\n",
       "\t<li>\"mayonais\"</li>\n",
       "\t<li>\"pea\"</li>\n",
       "\t<li>\"shoulder\"</li>\n",
       "\t<li>\"soda\"</li>\n",
       "\t<li>\"bacon\"</li>\n",
       "\t<li>\"coconut\"</li>\n",
       "\t<li>\"fillet\"</li>\n",
       "\t<li>\"orang\"</li>\n",
       "\t<li>\"purpl\"</li>\n",
       "\t<li>\"ice\"</li>\n",
       "\t<li>\"mix\"</li>\n",
       "\t<li>\"shallot\"</li>\n",
       "\t<li>\"tomato\"</li>\n",
       "\t<li>\"cheddar\"</li>\n",
       "\t<li>\"cinnamon\"</li>\n",
       "\t<li>\"coriand\"</li>\n",
       "\t<li>\"cream\"</li>\n",
       "\t<li>\"extract\"</li>\n",
       "\t<li>\"lamb\"</li>\n",
       "\t<li>\"milk\"</li>\n",
       "\t<li>\"celeri\"</li>\n",
       "\t<li>\"thai\"</li>\n",
       "\t<li>\"turkey\"</li>\n",
       "\t<li>\"wheat\"</li>\n",
       "\t<li>\"whole\"</li>\n",
       "\t<li>\"balsam\"</li>\n",
       "\t<li>\"boil\"</li>\n",
       "\t<li>\"broccoli\"</li>\n",
       "\t<li>\"eggplant\"</li>\n",
       "\t<li>\"extra-virgin\"</li>\n",
       "\t<li>\"fat\"</li>\n",
       "\t<li>\"flat\"</li>\n",
       "\t<li>\"free\"</li>\n",
       "\t<li>\"golden\"</li>\n",
       "\t<li>\"hoisin\"</li>\n",
       "\t<li>\"plain\"</li>\n",
       "\t<li>\"sausag\"</li>\n",
       "\t<li>\"serrano\"</li>\n",
       "\t<li>\"squash\"</li>\n",
       "\t<li>\"stick\"</li>\n",
       "\t<li>\"unsalt\"</li>\n",
       "\t<li>\"vanilla\"</li>\n",
       "\t<li>\"warm\"</li>\n",
       "\t<li>\"bay\"</li>\n",
       "\t<li>\"bread\"</li>\n",
       "\t<li>\"crack\"</li>\n",
       "\t<li>\"dijon\"</li>\n",
       "\t<li>\"dress\"</li>\n",
       "\t<li>\"frozen\"</li>\n",
       "\t<li>\"ham\"</li>\n",
       "\t<li>\"heavi\"</li>\n",
       "\t<li>\"parsley\"</li>\n",
       "\t<li>\"smoke\"</li>\n",
       "\t<li>\"sour\"</li>\n",
       "\t<li>\"zest\"</li>\n",
       "\t<li>\"avocado\"</li>\n",
       "\t<li>\"basil\"</li>\n",
       "\t<li>\"buttermilk\"</li>\n",
       "\t<li>\"chip\"</li>\n",
       "\t<li>\"curri\"</li>\n",
       "\t<li>\"fine\"</li>\n",
       "\t<li>\"less\"</li>\n",
       "\t<li>\"pasta\"</li>\n",
       "\t<li>\"peppercorn\"</li>\n",
       "\t<li>\"plum\"</li>\n",
       "\t<li>\"raisin\"</li>\n",
       "\t<li>\"yeast\"</li>\n",
       "\t<li>\"almond\"</li>\n",
       "\t<li>\"chickpea\"</li>\n",
       "\t<li>\"crumb\"</li>\n",
       "\t<li>\"cumin\"</li>\n",
       "\t<li>\"dice\"</li>\n",
       "\t<li>\"dough\"</li>\n",
       "\t<li>\"grate\"</li>\n",
       "\t<li>\"greek\"</li>\n",
       "\t<li>\"halv\"</li>\n",
       "\t<li>\"jack\"</li>\n",
       "\t<li>\"kernel\"</li>\n",
       "\t<li>\"mozzarella\"</li>\n",
       "\t<li>\"rosemari\"</li>\n",
       "\t<li>\"salsa\"</li>\n",
       "\t<li>\"sharp\"</li>\n",
       "\t<li>\"shell\"</li>\n",
       "\t<li>\"spaghetti\"</li>\n",
       "\t<li>\"thyme\"</li>\n",
       "\t<li>\"worcestershir\"</li>\n",
       "\t<li>\"yogurt\"</li>\n",
       "\t<li>\"allspic\"</li>\n",
       "\t<li>\"and\"</li>\n",
       "\t<li>\"caper\"</li>\n",
       "\t<li>\"cardamom\"</li>\n",
       "\t<li>\"cherri\"</li>\n",
       "\t<li>\"chipotl\"</li>\n",
       "\t<li>\"chocol\"</li>\n",
       "\t<li>\"condens\"</li>\n",
       "\t<li>\"confection\"</li>\n",
       "\t<li>\"cornmeal\"</li>\n",
       "\t<li>\"crumbl\"</li>\n",
       "\t<li>\"dill\"</li>\n",
       "\t<li>\"enchilada\"</li>\n",
       "\t<li>\"fennel\"</li>\n",
       "\t<li>\"feta\"</li>\n",
       "\t<li>\"garam\"</li>\n",
       "\t<li>\"italian\"</li>\n",
       "\t<li>\"kalamata\"</li>\n",
       "\t<li>\"low-fat\"</li>\n",
       "\t<li>\"masala\"</li>\n",
       "\t<li>\"mexican\"</li>\n",
       "\t<li>\"mint\"</li>\n",
       "\t<li>\"monterey\"</li>\n",
       "\t<li>\"nutmeg\"</li>\n",
       "\t<li>\"oregano\"</li>\n",
       "\t<li>\"parmesan\"</li>\n",
       "\t<li>\"pecan\"</li>\n",
       "\t<li>\"ricotta\"</li>\n",
       "\t<li>\"saffron\"</li>\n",
       "\t<li>\"sage\"</li>\n",
       "\t<li>\"soup\"</li>\n",
       "\t<li>\"sprig\"</li>\n",
       "\t<li>\"sweeten\"</li>\n",
       "\t<li>\"taco\"</li>\n",
       "\t<li>\"tumer\"</li>\n",
       "\t<li>\"turmer\"</li>\n",
       "\t<li>\"unsweeten\"</li>\n",
       "\t<li>\"wedg\"</li>\n",
       "\t<li>\"whip\"</li>\n",
       "</ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item \"sesam\"\n",
       "\\item \"oil\"\n",
       "\\item \"sauc\"\n",
       "\\item \"garlic\"\n",
       "\\item \"onion\"\n",
       "\\item \"pepper\"\n",
       "\\item \"soy\"\n",
       "\\item \"sugar\"\n",
       "\\item \"rice\"\n",
       "\\item \"salt\"\n",
       "\\item \"seed\"\n",
       "\\item \"green\"\n",
       "\\item \"ginger\"\n",
       "\\item \"water\"\n",
       "\\item \"red\"\n",
       "\\item \"vinegar\"\n",
       "\\item \"scallion\"\n",
       "\\item \"black\"\n",
       "\\item \"ground\"\n",
       "\\item \"toast\"\n",
       "\\item \"fresh\"\n",
       "\\item \"clove\"\n",
       "\\item \"carrot\"\n",
       "\\item \"egg\"\n",
       "\\item \"brown\"\n",
       "\\item \"beef\"\n",
       "\\item \"chili\"\n",
       "\\item \"flake\"\n",
       "\\item \"white\"\n",
       "\\item \"veget\"\n",
       "\\item \"minc\"\n",
       "\\item \"cabbag\"\n",
       "\\item \"chicken\"\n",
       "\\item \"past\"\n",
       "\\item \"rib\"\n",
       "\\item \"pork\"\n",
       "\\item \"mushroom\"\n",
       "\\item \"flour\"\n",
       "\\item \"steak\"\n",
       "\\item \"sodium\"\n",
       "\\item \"wine\"\n",
       "\\item \"cucumb\"\n",
       "\\item \"honey\"\n",
       "\\item \"chile\"\n",
       "\\item \"shiitak\"\n",
       "\\item \"kosher\"\n",
       "\\item \"cook\"\n",
       "\\item \"dark\"\n",
       "\\item \"tofu\"\n",
       "\\item \"corn\"\n",
       "\\item \"spinach\"\n",
       "\\item \"bean\"\n",
       "\\item \"powder\"\n",
       "\\item \"juic\"\n",
       "\\item \"fish\"\n",
       "\\item \"mirin\"\n",
       "\\item \"noodl\"\n",
       "\\item \"zucchini\"\n",
       "\\item \"larg\"\n",
       "\\item \"potato\"\n",
       "\\item \"low\"\n",
       "\\item \"crush\"\n",
       "\\item \"starch\"\n",
       "\\item \"canola\"\n",
       "\\item \"lettuc\"\n",
       "\\item \"spring\"\n",
       "\\item \"syrup\"\n",
       "\\item \"chop\"\n",
       "\\item \"dri\"\n",
       "\\item \"sweet\"\n",
       "\\item \"oliv\"\n",
       "\\item \"hot\"\n",
       "\\item \"yellow\"\n",
       "\\item \"leav\"\n",
       "\\item \"broth\"\n",
       "\\item \"light\"\n",
       "\\item \"sea\"\n",
       "\\item \"firm\"\n",
       "\\item \"stock\"\n",
       "\\item \"beansprout\"\n",
       "\\item \"all-purpos\"\n",
       "\\item \"bell\"\n",
       "\\item \"shrimp\"\n",
       "\\item \"appl\"\n",
       "\\item \"boneless\"\n",
       "\\item \"granul\"\n",
       "\\item \"roast\"\n",
       "\\item \"slice\"\n",
       "\\item \"babi\"\n",
       "\\item \"reduc\"\n",
       "\\item \"chive\"\n",
       "\\item \"peel\"\n",
       "\\item \"chines\"\n",
       "\\item \"cold\"\n",
       "\\item \"lemon\"\n",
       "\\item \"oyster\"\n",
       "\\item \"shred\"\n",
       "\\item \"peanut\"\n",
       "\\item \"cilantro\"\n",
       "\\item \"meat\"\n",
       "\\item \"cayenn\"\n",
       "\\item \"coars\"\n",
       "\\item \"jalapeno\"\n",
       "\\item \"root\"\n",
       "\\item \"butter\"\n",
       "\\item \"spray\"\n",
       "\\item \"chees\"\n",
       "\\item \"ketchup\"\n",
       "\\item \"mustard\"\n",
       "\\item \"thigh\"\n",
       "\\item \"cider\"\n",
       "\\item \"sherri\"\n",
       "\\item \"lean\"\n",
       "\\item \"lime\"\n",
       "\\item \"paprika\"\n",
       "\\item \"skinless\"\n",
       "\\item \"bake\"\n",
       "\\item \"breast\"\n",
       "\\item \"leaf\"\n",
       "\\item \"medium\"\n",
       "\\item \"season\"\n",
       "\\item \"tortilla\"\n",
       "\\item \"yolk\"\n",
       "\\item \"leek\"\n",
       "\\item \"mayonais\"\n",
       "\\item \"pea\"\n",
       "\\item \"shoulder\"\n",
       "\\item \"soda\"\n",
       "\\item \"bacon\"\n",
       "\\item \"coconut\"\n",
       "\\item \"fillet\"\n",
       "\\item \"orang\"\n",
       "\\item \"purpl\"\n",
       "\\item \"ice\"\n",
       "\\item \"mix\"\n",
       "\\item \"shallot\"\n",
       "\\item \"tomato\"\n",
       "\\item \"cheddar\"\n",
       "\\item \"cinnamon\"\n",
       "\\item \"coriand\"\n",
       "\\item \"cream\"\n",
       "\\item \"extract\"\n",
       "\\item \"lamb\"\n",
       "\\item \"milk\"\n",
       "\\item \"celeri\"\n",
       "\\item \"thai\"\n",
       "\\item \"turkey\"\n",
       "\\item \"wheat\"\n",
       "\\item \"whole\"\n",
       "\\item \"balsam\"\n",
       "\\item \"boil\"\n",
       "\\item \"broccoli\"\n",
       "\\item \"eggplant\"\n",
       "\\item \"extra-virgin\"\n",
       "\\item \"fat\"\n",
       "\\item \"flat\"\n",
       "\\item \"free\"\n",
       "\\item \"golden\"\n",
       "\\item \"hoisin\"\n",
       "\\item \"plain\"\n",
       "\\item \"sausag\"\n",
       "\\item \"serrano\"\n",
       "\\item \"squash\"\n",
       "\\item \"stick\"\n",
       "\\item \"unsalt\"\n",
       "\\item \"vanilla\"\n",
       "\\item \"warm\"\n",
       "\\item \"bay\"\n",
       "\\item \"bread\"\n",
       "\\item \"crack\"\n",
       "\\item \"dijon\"\n",
       "\\item \"dress\"\n",
       "\\item \"frozen\"\n",
       "\\item \"ham\"\n",
       "\\item \"heavi\"\n",
       "\\item \"parsley\"\n",
       "\\item \"smoke\"\n",
       "\\item \"sour\"\n",
       "\\item \"zest\"\n",
       "\\item \"avocado\"\n",
       "\\item \"basil\"\n",
       "\\item \"buttermilk\"\n",
       "\\item \"chip\"\n",
       "\\item \"curri\"\n",
       "\\item \"fine\"\n",
       "\\item \"less\"\n",
       "\\item \"pasta\"\n",
       "\\item \"peppercorn\"\n",
       "\\item \"plum\"\n",
       "\\item \"raisin\"\n",
       "\\item \"yeast\"\n",
       "\\item \"almond\"\n",
       "\\item \"chickpea\"\n",
       "\\item \"crumb\"\n",
       "\\item \"cumin\"\n",
       "\\item \"dice\"\n",
       "\\item \"dough\"\n",
       "\\item \"grate\"\n",
       "\\item \"greek\"\n",
       "\\item \"halv\"\n",
       "\\item \"jack\"\n",
       "\\item \"kernel\"\n",
       "\\item \"mozzarella\"\n",
       "\\item \"rosemari\"\n",
       "\\item \"salsa\"\n",
       "\\item \"sharp\"\n",
       "\\item \"shell\"\n",
       "\\item \"spaghetti\"\n",
       "\\item \"thyme\"\n",
       "\\item \"worcestershir\"\n",
       "\\item \"yogurt\"\n",
       "\\item \"allspic\"\n",
       "\\item \"and\"\n",
       "\\item \"caper\"\n",
       "\\item \"cardamom\"\n",
       "\\item \"cherri\"\n",
       "\\item \"chipotl\"\n",
       "\\item \"chocol\"\n",
       "\\item \"condens\"\n",
       "\\item \"confection\"\n",
       "\\item \"cornmeal\"\n",
       "\\item \"crumbl\"\n",
       "\\item \"dill\"\n",
       "\\item \"enchilada\"\n",
       "\\item \"fennel\"\n",
       "\\item \"feta\"\n",
       "\\item \"garam\"\n",
       "\\item \"italian\"\n",
       "\\item \"kalamata\"\n",
       "\\item \"low-fat\"\n",
       "\\item \"masala\"\n",
       "\\item \"mexican\"\n",
       "\\item \"mint\"\n",
       "\\item \"monterey\"\n",
       "\\item \"nutmeg\"\n",
       "\\item \"oregano\"\n",
       "\\item \"parmesan\"\n",
       "\\item \"pecan\"\n",
       "\\item \"ricotta\"\n",
       "\\item \"saffron\"\n",
       "\\item \"sage\"\n",
       "\\item \"soup\"\n",
       "\\item \"sprig\"\n",
       "\\item \"sweeten\"\n",
       "\\item \"taco\"\n",
       "\\item \"tumer\"\n",
       "\\item \"turmer\"\n",
       "\\item \"unsweeten\"\n",
       "\\item \"wedg\"\n",
       "\\item \"whip\"\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. \"sesam\"\n",
       "2. \"oil\"\n",
       "3. \"sauc\"\n",
       "4. \"garlic\"\n",
       "5. \"onion\"\n",
       "6. \"pepper\"\n",
       "7. \"soy\"\n",
       "8. \"sugar\"\n",
       "9. \"rice\"\n",
       "10. \"salt\"\n",
       "11. \"seed\"\n",
       "12. \"green\"\n",
       "13. \"ginger\"\n",
       "14. \"water\"\n",
       "15. \"red\"\n",
       "16. \"vinegar\"\n",
       "17. \"scallion\"\n",
       "18. \"black\"\n",
       "19. \"ground\"\n",
       "20. \"toast\"\n",
       "21. \"fresh\"\n",
       "22. \"clove\"\n",
       "23. \"carrot\"\n",
       "24. \"egg\"\n",
       "25. \"brown\"\n",
       "26. \"beef\"\n",
       "27. \"chili\"\n",
       "28. \"flake\"\n",
       "29. \"white\"\n",
       "30. \"veget\"\n",
       "31. \"minc\"\n",
       "32. \"cabbag\"\n",
       "33. \"chicken\"\n",
       "34. \"past\"\n",
       "35. \"rib\"\n",
       "36. \"pork\"\n",
       "37. \"mushroom\"\n",
       "38. \"flour\"\n",
       "39. \"steak\"\n",
       "40. \"sodium\"\n",
       "41. \"wine\"\n",
       "42. \"cucumb\"\n",
       "43. \"honey\"\n",
       "44. \"chile\"\n",
       "45. \"shiitak\"\n",
       "46. \"kosher\"\n",
       "47. \"cook\"\n",
       "48. \"dark\"\n",
       "49. \"tofu\"\n",
       "50. \"corn\"\n",
       "51. \"spinach\"\n",
       "52. \"bean\"\n",
       "53. \"powder\"\n",
       "54. \"juic\"\n",
       "55. \"fish\"\n",
       "56. \"mirin\"\n",
       "57. \"noodl\"\n",
       "58. \"zucchini\"\n",
       "59. \"larg\"\n",
       "60. \"potato\"\n",
       "61. \"low\"\n",
       "62. \"crush\"\n",
       "63. \"starch\"\n",
       "64. \"canola\"\n",
       "65. \"lettuc\"\n",
       "66. \"spring\"\n",
       "67. \"syrup\"\n",
       "68. \"chop\"\n",
       "69. \"dri\"\n",
       "70. \"sweet\"\n",
       "71. \"oliv\"\n",
       "72. \"hot\"\n",
       "73. \"yellow\"\n",
       "74. \"leav\"\n",
       "75. \"broth\"\n",
       "76. \"light\"\n",
       "77. \"sea\"\n",
       "78. \"firm\"\n",
       "79. \"stock\"\n",
       "80. \"beansprout\"\n",
       "81. \"all-purpos\"\n",
       "82. \"bell\"\n",
       "83. \"shrimp\"\n",
       "84. \"appl\"\n",
       "85. \"boneless\"\n",
       "86. \"granul\"\n",
       "87. \"roast\"\n",
       "88. \"slice\"\n",
       "89. \"babi\"\n",
       "90. \"reduc\"\n",
       "91. \"chive\"\n",
       "92. \"peel\"\n",
       "93. \"chines\"\n",
       "94. \"cold\"\n",
       "95. \"lemon\"\n",
       "96. \"oyster\"\n",
       "97. \"shred\"\n",
       "98. \"peanut\"\n",
       "99. \"cilantro\"\n",
       "100. \"meat\"\n",
       "101. \"cayenn\"\n",
       "102. \"coars\"\n",
       "103. \"jalapeno\"\n",
       "104. \"root\"\n",
       "105. \"butter\"\n",
       "106. \"spray\"\n",
       "107. \"chees\"\n",
       "108. \"ketchup\"\n",
       "109. \"mustard\"\n",
       "110. \"thigh\"\n",
       "111. \"cider\"\n",
       "112. \"sherri\"\n",
       "113. \"lean\"\n",
       "114. \"lime\"\n",
       "115. \"paprika\"\n",
       "116. \"skinless\"\n",
       "117. \"bake\"\n",
       "118. \"breast\"\n",
       "119. \"leaf\"\n",
       "120. \"medium\"\n",
       "121. \"season\"\n",
       "122. \"tortilla\"\n",
       "123. \"yolk\"\n",
       "124. \"leek\"\n",
       "125. \"mayonais\"\n",
       "126. \"pea\"\n",
       "127. \"shoulder\"\n",
       "128. \"soda\"\n",
       "129. \"bacon\"\n",
       "130. \"coconut\"\n",
       "131. \"fillet\"\n",
       "132. \"orang\"\n",
       "133. \"purpl\"\n",
       "134. \"ice\"\n",
       "135. \"mix\"\n",
       "136. \"shallot\"\n",
       "137. \"tomato\"\n",
       "138. \"cheddar\"\n",
       "139. \"cinnamon\"\n",
       "140. \"coriand\"\n",
       "141. \"cream\"\n",
       "142. \"extract\"\n",
       "143. \"lamb\"\n",
       "144. \"milk\"\n",
       "145. \"celeri\"\n",
       "146. \"thai\"\n",
       "147. \"turkey\"\n",
       "148. \"wheat\"\n",
       "149. \"whole\"\n",
       "150. \"balsam\"\n",
       "151. \"boil\"\n",
       "152. \"broccoli\"\n",
       "153. \"eggplant\"\n",
       "154. \"extra-virgin\"\n",
       "155. \"fat\"\n",
       "156. \"flat\"\n",
       "157. \"free\"\n",
       "158. \"golden\"\n",
       "159. \"hoisin\"\n",
       "160. \"plain\"\n",
       "161. \"sausag\"\n",
       "162. \"serrano\"\n",
       "163. \"squash\"\n",
       "164. \"stick\"\n",
       "165. \"unsalt\"\n",
       "166. \"vanilla\"\n",
       "167. \"warm\"\n",
       "168. \"bay\"\n",
       "169. \"bread\"\n",
       "170. \"crack\"\n",
       "171. \"dijon\"\n",
       "172. \"dress\"\n",
       "173. \"frozen\"\n",
       "174. \"ham\"\n",
       "175. \"heavi\"\n",
       "176. \"parsley\"\n",
       "177. \"smoke\"\n",
       "178. \"sour\"\n",
       "179. \"zest\"\n",
       "180. \"avocado\"\n",
       "181. \"basil\"\n",
       "182. \"buttermilk\"\n",
       "183. \"chip\"\n",
       "184. \"curri\"\n",
       "185. \"fine\"\n",
       "186. \"less\"\n",
       "187. \"pasta\"\n",
       "188. \"peppercorn\"\n",
       "189. \"plum\"\n",
       "190. \"raisin\"\n",
       "191. \"yeast\"\n",
       "192. \"almond\"\n",
       "193. \"chickpea\"\n",
       "194. \"crumb\"\n",
       "195. \"cumin\"\n",
       "196. \"dice\"\n",
       "197. \"dough\"\n",
       "198. \"grate\"\n",
       "199. \"greek\"\n",
       "200. \"halv\"\n",
       "201. \"jack\"\n",
       "202. \"kernel\"\n",
       "203. \"mozzarella\"\n",
       "204. \"rosemari\"\n",
       "205. \"salsa\"\n",
       "206. \"sharp\"\n",
       "207. \"shell\"\n",
       "208. \"spaghetti\"\n",
       "209. \"thyme\"\n",
       "210. \"worcestershir\"\n",
       "211. \"yogurt\"\n",
       "212. \"allspic\"\n",
       "213. \"and\"\n",
       "214. \"caper\"\n",
       "215. \"cardamom\"\n",
       "216. \"cherri\"\n",
       "217. \"chipotl\"\n",
       "218. \"chocol\"\n",
       "219. \"condens\"\n",
       "220. \"confection\"\n",
       "221. \"cornmeal\"\n",
       "222. \"crumbl\"\n",
       "223. \"dill\"\n",
       "224. \"enchilada\"\n",
       "225. \"fennel\"\n",
       "226. \"feta\"\n",
       "227. \"garam\"\n",
       "228. \"italian\"\n",
       "229. \"kalamata\"\n",
       "230. \"low-fat\"\n",
       "231. \"masala\"\n",
       "232. \"mexican\"\n",
       "233. \"mint\"\n",
       "234. \"monterey\"\n",
       "235. \"nutmeg\"\n",
       "236. \"oregano\"\n",
       "237. \"parmesan\"\n",
       "238. \"pecan\"\n",
       "239. \"ricotta\"\n",
       "240. \"saffron\"\n",
       "241. \"sage\"\n",
       "242. \"soup\"\n",
       "243. \"sprig\"\n",
       "244. \"sweeten\"\n",
       "245. \"taco\"\n",
       "246. \"tumer\"\n",
       "247. \"turmer\"\n",
       "248. \"unsweeten\"\n",
       "249. \"wedg\"\n",
       "250. \"whip\"\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "  [1] \"sesam\"         \"oil\"           \"sauc\"          \"garlic\"       \n",
       "  [5] \"onion\"         \"pepper\"        \"soy\"           \"sugar\"        \n",
       "  [9] \"rice\"          \"salt\"          \"seed\"          \"green\"        \n",
       " [13] \"ginger\"        \"water\"         \"red\"           \"vinegar\"      \n",
       " [17] \"scallion\"      \"black\"         \"ground\"        \"toast\"        \n",
       " [21] \"fresh\"         \"clove\"         \"carrot\"        \"egg\"          \n",
       " [25] \"brown\"         \"beef\"          \"chili\"         \"flake\"        \n",
       " [29] \"white\"         \"veget\"         \"minc\"          \"cabbag\"       \n",
       " [33] \"chicken\"       \"past\"          \"rib\"           \"pork\"         \n",
       " [37] \"mushroom\"      \"flour\"         \"steak\"         \"sodium\"       \n",
       " [41] \"wine\"          \"cucumb\"        \"honey\"         \"chile\"        \n",
       " [45] \"shiitak\"       \"kosher\"        \"cook\"          \"dark\"         \n",
       " [49] \"tofu\"          \"corn\"          \"spinach\"       \"bean\"         \n",
       " [53] \"powder\"        \"juic\"          \"fish\"          \"mirin\"        \n",
       " [57] \"noodl\"         \"zucchini\"      \"larg\"          \"potato\"       \n",
       " [61] \"low\"           \"crush\"         \"starch\"        \"canola\"       \n",
       " [65] \"lettuc\"        \"spring\"        \"syrup\"         \"chop\"         \n",
       " [69] \"dri\"           \"sweet\"         \"oliv\"          \"hot\"          \n",
       " [73] \"yellow\"        \"leav\"          \"broth\"         \"light\"        \n",
       " [77] \"sea\"           \"firm\"          \"stock\"         \"beansprout\"   \n",
       " [81] \"all-purpos\"    \"bell\"          \"shrimp\"        \"appl\"         \n",
       " [85] \"boneless\"      \"granul\"        \"roast\"         \"slice\"        \n",
       " [89] \"babi\"          \"reduc\"         \"chive\"         \"peel\"         \n",
       " [93] \"chines\"        \"cold\"          \"lemon\"         \"oyster\"       \n",
       " [97] \"shred\"         \"peanut\"        \"cilantro\"      \"meat\"         \n",
       "[101] \"cayenn\"        \"coars\"         \"jalapeno\"      \"root\"         \n",
       "[105] \"butter\"        \"spray\"         \"chees\"         \"ketchup\"      \n",
       "[109] \"mustard\"       \"thigh\"         \"cider\"         \"sherri\"       \n",
       "[113] \"lean\"          \"lime\"          \"paprika\"       \"skinless\"     \n",
       "[117] \"bake\"          \"breast\"        \"leaf\"          \"medium\"       \n",
       "[121] \"season\"        \"tortilla\"      \"yolk\"          \"leek\"         \n",
       "[125] \"mayonais\"      \"pea\"           \"shoulder\"      \"soda\"         \n",
       "[129] \"bacon\"         \"coconut\"       \"fillet\"        \"orang\"        \n",
       "[133] \"purpl\"         \"ice\"           \"mix\"           \"shallot\"      \n",
       "[137] \"tomato\"        \"cheddar\"       \"cinnamon\"      \"coriand\"      \n",
       "[141] \"cream\"         \"extract\"       \"lamb\"          \"milk\"         \n",
       "[145] \"celeri\"        \"thai\"          \"turkey\"        \"wheat\"        \n",
       "[149] \"whole\"         \"balsam\"        \"boil\"          \"broccoli\"     \n",
       "[153] \"eggplant\"      \"extra-virgin\"  \"fat\"           \"flat\"         \n",
       "[157] \"free\"          \"golden\"        \"hoisin\"        \"plain\"        \n",
       "[161] \"sausag\"        \"serrano\"       \"squash\"        \"stick\"        \n",
       "[165] \"unsalt\"        \"vanilla\"       \"warm\"          \"bay\"          \n",
       "[169] \"bread\"         \"crack\"         \"dijon\"         \"dress\"        \n",
       "[173] \"frozen\"        \"ham\"           \"heavi\"         \"parsley\"      \n",
       "[177] \"smoke\"         \"sour\"          \"zest\"          \"avocado\"      \n",
       "[181] \"basil\"         \"buttermilk\"    \"chip\"          \"curri\"        \n",
       "[185] \"fine\"          \"less\"          \"pasta\"         \"peppercorn\"   \n",
       "[189] \"plum\"          \"raisin\"        \"yeast\"         \"almond\"       \n",
       "[193] \"chickpea\"      \"crumb\"         \"cumin\"         \"dice\"         \n",
       "[197] \"dough\"         \"grate\"         \"greek\"         \"halv\"         \n",
       "[201] \"jack\"          \"kernel\"        \"mozzarella\"    \"rosemari\"     \n",
       "[205] \"salsa\"         \"sharp\"         \"shell\"         \"spaghetti\"    \n",
       "[209] \"thyme\"         \"worcestershir\" \"yogurt\"        \"allspic\"      \n",
       "[213] \"and\"           \"caper\"         \"cardamom\"      \"cherri\"       \n",
       "[217] \"chipotl\"       \"chocol\"        \"condens\"       \"confection\"   \n",
       "[221] \"cornmeal\"      \"crumbl\"        \"dill\"          \"enchilada\"    \n",
       "[225] \"fennel\"        \"feta\"          \"garam\"         \"italian\"      \n",
       "[229] \"kalamata\"      \"low-fat\"       \"masala\"        \"mexican\"      \n",
       "[233] \"mint\"          \"monterey\"      \"nutmeg\"        \"oregano\"      \n",
       "[237] \"parmesan\"      \"pecan\"         \"ricotta\"       \"saffron\"      \n",
       "[241] \"sage\"          \"soup\"          \"sprig\"         \"sweeten\"      \n",
       "[245] \"taco\"          \"tumer\"         \"turmer\"        \"unsweeten\"    \n",
       "[249] \"wedg\"          \"whip\"         "
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "names(ingredients_korea_sum)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 한국 재료\n",
    "- \"SESAM(참깨)\" \"기름\" \"sauc(소스)\" \"마늘\", \"양파\" \"고추\" \"콩\" \"설탕\" \"쌀\", \"소금\" \"씨\" \"녹색\" \"생강\" \"물\" \"빨간색\" \"식초\" \"scallion(파) \"\"땅 \"\"토스트 \"\"신선한 \"\"정향 \"\"당근 \"\"달걀 \"\"갈색 \"\"쇠고기 \"\"고추 \"\"찌 \"\"화이트 \"\"veget\", \"MINC \"\"cabbag \"\"닭 \"\" \"블랙\" 과거 \",\"갈비 \"\"돼지 고기 \",\"버섯 \",\"밀가루 \"\"스테이크 \"\"나트륨 \"\"와인 \"\"cucumb \"\"꿀 \"\"칠레 \"\"shiitak \"\"정결 한 \"\"요리 \"\"어두운 \"\"두부 \"\"옥수수 \" \"시금치\" \"콩\" \"분말\"..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/pdf": 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      "image/jpeg": 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",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/svg+xml": {
       "isolated": true
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "barplot(ingredients_korea_mean[1:30], las=2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "cartModelFit <- rpart(cuisine ~ ., data = train_data, method = \"class\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "n= 23871 \n",
       "\n",
       "node), split, n, loss, yval, (yprob)\n",
       "      * denotes terminal node\n",
       "\n",
       "  1) root 23871 19168 italian (0.012 0.02 0.039 0.067 0.019 0.067 0.03 0.075 0.017 0.2 0.013 0.036 0.021 0.16 0.021 0.012 0.11 0.025 0.039 0.021)  \n",
       "    2) tortilla< 0.5 22273 17583 italian (0.013 0.022 0.042 0.072 0.02 0.071 0.031 0.081 0.018 0.21 0.014 0.038 0.022 0.1 0.022 0.013 0.12 0.026 0.041 0.022)  \n",
       "      4) parmesan>=0.5 1714   277 italian (0.0053 0.0018 0.023 0.00058 0.0012 0.037 0.015 0.0018 0.0018 0.84 0.00058 0.0035 0 0.016 0.0018 0.00058 0.047 0.0041 0.00058 0) *\n",
       "      5) parmesan< 0.5 20559 17306 italian (0.013 0.023 0.043 0.078 0.022 0.074 0.033 0.087 0.019 0.16 0.015 0.041 0.024 0.11 0.024 0.014 0.12 0.028 0.044 0.024)  \n",
       "       10) soy>=0.5 2731  1525 chinese (0.00037 0.00073 0.0026 0.44 0.062 0.0015 0.0015 0.0084 0.0011 0.004 0.019 0.17 0.11 0.0088 0.0011 0.00073 0.0092 0.0011 0.11 0.048) *\n",
       "       11) soy< 0.5 17828 14586 italian (0.015 0.027 0.049 0.022 0.016 0.085 0.038 0.099 0.022 0.18 0.015 0.022 0.01 0.13 0.027 0.016 0.14 0.033 0.035 0.02)  \n",
       "         22) masala>=0.5 614    41 indian (0.0016 0.0033 0 0.0016 0 0 0 0.93 0 0.0016 0.0016 0.047 0 0 0.0065 0.0016 0.0016 0 0 0) *\n",
       "         23) masala< 0.5 17214 13973 italian (0.016 0.028 0.051 0.023 0.016 0.088 0.039 0.07 0.023 0.19 0.015 0.021 0.01 0.13 0.028 0.017 0.14 0.034 0.036 0.021)  \n",
       "           46) cilantro< 0.5 15174 11953 italian (0.015 0.031 0.057 0.024 0.018 0.1 0.044 0.055 0.026 0.21 0.016 0.023 0.012 0.092 0.022 0.019 0.16 0.035 0.022 0.015)  \n",
       "             92) oliv>=0.5 4373  2479 italian (0.01 0.011 0.046 0.0037 0.0059 0.096 0.1 0.023 0.0073 0.43 0.0048 0.0032 0.0016 0.067 0.043 0.0053 0.048 0.081 0.0059 0.0027) *\n",
       "             93) oliv< 0.5 10801  8557 southern_us (0.017 0.039 0.062 0.032 0.023 0.1 0.021 0.068 0.033 0.12 0.021 0.031 0.016 0.1 0.013 0.024 0.21 0.016 0.029 0.02)  \n",
       "              186) cumin< 0.5 10103  7888 southern_us (0.018 0.042 0.064 0.034 0.025 0.11 0.021 0.045 0.036 0.13 0.021 0.033 0.017 0.083 0.0092 0.026 0.22 0.017 0.03 0.021) *\n",
       "              187) cumin>=0.5 698   421 indian (0.0072 0.0043 0.029 0 0.0029 0.0086 0.01 0.4 0 0.0014 0.016 0.011 0 0.38 0.073 0 0.042 0.0057 0.014 0.0014) *\n",
       "           47) cilantro>=0.5 2040  1150 mexican (0.021 0.00098 0.0064 0.015 0.00098 0.0034 0.00098 0.18 0.00098 0.0098 0.0054 0.0059 0.0025 0.44 0.075 0.002 0.013 0.023 0.13 0.066) *\n",
       "    3) tortilla>=0.5 1598    70 mexican (0.00063 0 0.0019 0.005 0.0013 0 0.0031 0.0038 0 0.0081 0.0019 0.00063 0.005 0.96 0 0 0.0025 0.0025 0.0056 0.0019) *"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cartModelFit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/pdf": 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",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/svg+xml": {
       "isolated": true
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "prp(cartModelFit)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "~~~~\n",
    "tortilla : 옥수수\n",
    "paramesan : 치즈\n",
    "soy : 대두\n",
    "mirin : 미림 (일본 술의 한 종류, 조미료)\n",
    "masala (향신료)\n",
    "- Garam masala (from Hindi: गरम मसाला, garam (\"hot\") and masala (a mixture of spices)) is a blend of ground spices common in North Indian and other South Asian cuisines.[1] It is used alone or with other seasonings. The word garam refers to \"heat\" in the Ayurvedic sense of the word, meaning \"to heat the body\" as these spices, in the Ayurvedic system of medicine, elevate body temperature.\n",
    "cilantro : 고수 (미나리과 살이풀)\n",
    "oliv : 올리브\n",
    "~~~~\n",
    "\n",
    "## masala\n",
    "![](https://upload.wikimedia.org/wikipedia/commons/thumb/5/58/Garammasalaphoto.jpg/250px-Garammasalaphoto.jpg)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "cartPredict <- predict(cartModelFit, newdata = vaild_data, type = \"class\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<dl class=dl-horizontal>\n",
       "\t<dt>5</dt>\n",
       "\t\t<dd>indian</dd>\n",
       "\t<dt>7</dt>\n",
       "\t\t<dd>mexican</dd>\n",
       "\t<dt>9</dt>\n",
       "\t\t<dd>mexican</dd>\n",
       "\t<dt>12</dt>\n",
       "\t\t<dd>chinese</dd>\n",
       "\t<dt>14</dt>\n",
       "\t\t<dd>mexican</dd>\n",
       "\t<dt>15</dt>\n",
       "\t\t<dd>italian</dd>\n",
       "</dl>\n"
      ],
      "text/latex": [
       "\\begin{description*}\n",
       "\\item[5] indian\n",
       "\\item[7] mexican\n",
       "\\item[9] mexican\n",
       "\\item[12] chinese\n",
       "\\item[14] mexican\n",
       "\\item[15] italian\n",
       "\\end{description*}\n"
      ],
      "text/markdown": [
       "5\n",
       ":   indian7\n",
       ":   mexican9\n",
       ":   mexican12\n",
       ":   chinese14\n",
       ":   mexican15\n",
       ":   italian\n",
       "\n"
      ],
      "text/plain": [
       "      5       7       9      12      14      15 \n",
       " indian mexican mexican chinese mexican italian \n",
       "20 Levels: brazilian british cajun_creole chinese filipino french ... vietnamese"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "head(cartPredict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "cartCM <- confusionMatrix(cartPredict, vaild_data$cuisine)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Confusion Matrix and Statistics\n",
       "\n",
       "              Reference\n",
       "Prediction     brazilian british cajun_creole chinese filipino french greek\n",
       "  brazilian            0       0            0       0        0      0     0\n",
       "  british              0       0            0       0        0      0     0\n",
       "  cajun_creole         0       0            0       0        0      0     0\n",
       "  chinese              1       3            5     821      118      3     2\n",
       "  filipino             0       0            0       0        0      0     0\n",
       "  french               0       0            0       0        0      0     0\n",
       "  greek                0       0            0       0        0      0     0\n",
       "  indian               0       3           17       1        1      2    10\n",
       "  irish                0       0            0       0        0      0     0\n",
       "  italian             55      29          163      14        8    369   307\n",
       "  jamaican             0       0            0       0        0      0     0\n",
       "  japanese             0       0            0       0        0      0     0\n",
       "  korean               0       0            0       0        0      0     0\n",
       "  mexican             37       2           12      26        6      7     7\n",
       "  moroccan             0       0            0       0        0      0     0\n",
       "  russian              0       0            0       0        0      0     0\n",
       "  southern_us         93     284          421     207      169    677   144\n",
       "  spanish              0       0            0       0        0      0     0\n",
       "  thai                 0       0            0       0        0      0     0\n",
       "  vietnamese           0       0            0       0        0      0     0\n",
       "              Reference\n",
       "Prediction     indian irish italian jamaican japanese korean mexican moroccan\n",
       "  brazilian         0     0       0        0        0      0       0        0\n",
       "  british           0     0       0        0        0      0       0        0\n",
       "  cajun_creole      0     0       0        0        0      0       0        0\n",
       "  chinese          10     4       8       28      301    218      12        1\n",
       "  filipino          0     0       0        0        0      0       0        0\n",
       "  french            0     0       0        0        0      0       0        0\n",
       "  greek             0     0       0        0        0      0       0        0\n",
       "  indian          547     2      10        8       31      0     174       26\n",
       "  irish             0     0       0        0        0      0       0        0\n",
       "  italian          82    29    2209       23       17      7     226      129\n",
       "  jamaican          0     0       0        0        0      0       0        0\n",
       "  japanese          0     0       0        0        0      0       0        0\n",
       "  korean            0     0       0        0        0      0       0        0\n",
       "  mexican         242     3      23       16       16      2    1597      123\n",
       "  moroccan          0     0       0        0        0      0       0        0\n",
       "  russian           0     0       0        0        0      0       0        0\n",
       "  southern_us     320   228     885      135      204    105     566       49\n",
       "  spanish           0     0       0        0        0      0       0        0\n",
       "  thai              0     0       0        0        0      0       0        0\n",
       "  vietnamese        0     0       0        0        0      0       0        0\n",
       "              Reference\n",
       "Prediction     russian southern_us spanish thai vietnamese\n",
       "  brazilian          0           0       0    0          0\n",
       "  british            0           0       0    0          0\n",
       "  cajun_creole       0           0       0    0          0\n",
       "  chinese            1          10       1  187         99\n",
       "  filipino           0           0       0    0          0\n",
       "  french             0           0       0    0          0\n",
       "  greek              0           0       0    0          0\n",
       "  indian             2          21       5   14          1\n",
       "  irish              0           0       0    0          0\n",
       "  italian           36         202     237    7          3\n",
       "  jamaican           0           0       0    0          0\n",
       "  japanese           0           0       0    0          0\n",
       "  korean             0           0       0    0          0\n",
       "  mexican            5          30      34  201         95\n",
       "  moroccan           0           0       0    0          0\n",
       "  russian            0           0       0    0          0\n",
       "  southern_us      151        1465     118  206        132\n",
       "  spanish            0           0       0    0          0\n",
       "  thai               0           0       0    0          0\n",
       "  vietnamese         0           0       0    0          0\n",
       "\n",
       "Overall Statistics\n",
       "                                          \n",
       "               Accuracy : 0.4175          \n",
       "                 95% CI : (0.4098, 0.4252)\n",
       "    No Information Rate : 0.1971          \n",
       "    P-Value [Acc > NIR] : < 2.2e-16       \n",
       "                                          \n",
       "                  Kappa : 0.3277          \n",
       " Mcnemar's Test P-Value : NA              \n",
       "\n",
       "Statistics by Class:\n",
       "\n",
       "                     Class: brazilian Class: british Class: cajun_creole\n",
       "Sensitivity                    0.0000        0.00000             0.00000\n",
       "Specificity                    1.0000        1.00000             1.00000\n",
       "Pos Pred Value                    NaN            NaN                 NaN\n",
       "Neg Pred Value                 0.9883        0.97982             0.96114\n",
       "Prevalence                     0.0117        0.02018             0.03886\n",
       "Detection Rate                 0.0000        0.00000             0.00000\n",
       "Detection Prevalence           0.0000        0.00000             0.00000\n",
       "Balanced Accuracy              0.5000        0.50000             0.50000\n",
       "                     Class: chinese Class: filipino Class: french Class: greek\n",
       "Sensitivity                 0.76801         0.00000       0.00000      0.00000\n",
       "Specificity                 0.93178         1.00000       1.00000      1.00000\n",
       "Pos Pred Value              0.44790             NaN           NaN          NaN\n",
       "Neg Pred Value              0.98237         0.98101       0.93347      0.97045\n",
       "Prevalence                  0.06722         0.01899       0.06653      0.02955\n",
       "Detection Rate              0.05163         0.00000       0.00000      0.00000\n",
       "Detection Prevalence        0.11526         0.00000       0.00000      0.00000\n",
       "Balanced Accuracy           0.84989         0.50000       0.50000      0.50000\n",
       "                     Class: indian Class: irish Class: italian Class: jamaican\n",
       "Sensitivity                0.45545      0.00000         0.7046         0.00000\n",
       "Specificity                0.97769      1.00000         0.8478         1.00000\n",
       "Pos Pred Value             0.62514          NaN         0.5320             NaN\n",
       "Neg Pred Value             0.95648      0.98327         0.9212         0.98679\n",
       "Prevalence                 0.07552      0.01673         0.1971         0.01321\n",
       "Detection Rate             0.03440      0.00000         0.1389         0.00000\n",
       "Detection Prevalence       0.05502      0.00000         0.2611         0.00000\n",
       "Balanced Accuracy          0.71657      0.50000         0.7762         0.50000\n",
       "                     Class: japanese Class: korean Class: mexican\n",
       "Sensitivity                  0.00000       0.00000         0.6202\n",
       "Specificity                  1.00000       1.00000         0.9334\n",
       "Pos Pred Value                   NaN           NaN         0.6429\n",
       "Neg Pred Value               0.96422       0.97912         0.9271\n",
       "Prevalence                   0.03578       0.02088         0.1619\n",
       "Detection Rate               0.00000       0.00000         0.1004\n",
       "Detection Prevalence         0.00000       0.00000         0.1562\n",
       "Balanced Accuracy            0.50000       0.50000         0.7768\n",
       "                     Class: moroccan Class: russian Class: southern_us\n",
       "Sensitivity                  0.00000        0.00000            0.84780\n",
       "Specificity                  1.00000        1.00000            0.64063\n",
       "Pos Pred Value                   NaN            NaN            0.22336\n",
       "Neg Pred Value               0.97937        0.98774            0.97185\n",
       "Prevalence                   0.02063        0.01226            0.10866\n",
       "Detection Rate               0.00000        0.00000            0.09212\n",
       "Detection Prevalence         0.00000        0.00000            0.41244\n",
       "Balanced Accuracy            0.50000        0.50000            0.74422\n",
       "                     Class: spanish Class: thai Class: vietnamese\n",
       "Sensitivity                 0.00000     0.00000           0.00000\n",
       "Specificity                 1.00000     1.00000           1.00000\n",
       "Pos Pred Value                  NaN         NaN               NaN\n",
       "Neg Pred Value              0.97516     0.96133           0.97925\n",
       "Prevalence                  0.02484     0.03867           0.02075\n",
       "Detection Rate              0.00000     0.00000           0.00000\n",
       "Detection Prevalence        0.00000     0.00000           0.00000\n",
       "Balanced Accuracy           0.50000     0.50000           0.50000"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cartCM"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "package 'rJava' successfully unpacked and MD5 sums checked\n",
      "\n",
      "The downloaded binary packages are in\n",
      "\tC:\\Users\\syleeie\\RtmpKcFXpv\\downloaded_packages\n"
     ]
    }
   ],
   "source": [
    "install.packages(\"rJava\", dependencies=T, repos='http://cran.rstudio.com/') "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "package 'AUC' successfully unpacked and MD5 sums checked\n",
      "\n",
      "The downloaded binary packages are in\n",
      "\tC:\\Users\\syleeie\\RtmpKcFXpv\\downloaded_packages\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "also installing the dependencies 'jsonlite', 'stringi', 'rjson', 'htmlwidgets', 'rstudioapi', 'stringr', 'visNetwork', 'lmtest', 'DiagrammeR', 'Ckmeans.1d.dp', 'vcd'\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "package 'jsonlite' successfully unpacked and MD5 sums checked\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message:\n",
      ": cannot remove prior installation of package 'jsonlite'"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "package 'stringi' successfully unpacked and MD5 sums checked\n",
      "package 'rjson' successfully unpacked and MD5 sums checked\n",
      "package 'htmlwidgets' successfully unpacked and MD5 sums checked\n",
      "package 'rstudioapi' successfully unpacked and MD5 sums checked\n",
      "package 'stringr' successfully unpacked and MD5 sums checked\n",
      "package 'visNetwork' successfully unpacked and MD5 sums checked\n",
      "package 'lmtest' successfully unpacked and MD5 sums checked\n",
      "package 'DiagrammeR' successfully unpacked and MD5 sums checked\n",
      "package 'Ckmeans.1d.dp' successfully unpacked and MD5 sums checked\n",
      "package 'vcd' successfully unpacked and MD5 sums checked\n",
      "package 'xgboost' successfully unpacked and MD5 sums checked\n",
      "\n",
      "The downloaded binary packages are in\n",
      "\tC:\\Users\\syleeie\\RtmpKcFXpv\\downloaded_packages\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "also installing the dependency 'RUnit'\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "package 'RUnit' successfully unpacked and MD5 sums checked\n",
      "package 'RSofia' successfully unpacked and MD5 sums checked\n",
      "\n",
      "The downloaded binary packages are in\n",
      "\tC:\\Users\\syleeie\\RtmpKcFXpv\\downloaded_packages\n",
      "package 'extraTrees' successfully unpacked and MD5 sums checked\n",
      "\n",
      "The downloaded binary packages are in\n",
      "\tC:\\Users\\syleeie\\RtmpKcFXpv\\downloaded_packages\n"
     ]
    }
   ],
   "source": [
    "install.packages(\"AUC\", dependencies=T, repos='http://cran.rstudio.com/') \n",
    "install.packages(\"xgboost\", dependencies=T, repos='http://cran.rstudio.com/') \n",
    "install.packages(\"RSofia\", dependencies=T, repos='http://cran.rstudio.com/') \n",
    "install.packages(\"extraTrees\", dependencies=T, repos='http://cran.rstudio.com/') "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "library(rJava)\n",
    "library(extraTrees)\n",
    "library(xgboost)\n",
    "library(RSofia)\n",
    "library(AUC)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "cartPredict <- predict(cartModelFit, newdata = vaild_data, type = \"prob\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th></th><th scope=col>brazilian</th><th scope=col>british</th><th scope=col>cajun_creole</th><th scope=col>chinese</th><th scope=col>filipino</th><th scope=col>french</th><th scope=col>greek</th><th scope=col>indian</th><th scope=col>irish</th><th scope=col>italian</th><th scope=col>jamaican</th><th scope=col>japanese</th><th scope=col>korean</th><th scope=col>mexican</th><th scope=col>moroccan</th><th scope=col>russian</th><th scope=col>southern_us</th><th scope=col>spanish</th><th scope=col>thai</th><th scope=col>vietnamese</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>5</th><td>0.001628664</td><td>0.003257329</td><td>0.000000000</td><td>0.001628664</td><td>0.000000000</td><td>0.000000000</td><td>0.000000000</td><td>0.933224756</td><td>0.000000000</td><td>0.001628664</td><td>0.001628664</td><td>0.047231270</td><td>0.000000000</td><td>0.000000000</td><td>0.006514658</td><td>0.001628664</td><td>0.001628664</td><td>0.000000000</td><td>0.000000000</td><td>0.000000000</td></tr>\n",
       "\t<tr><th scope=row>7</th><td>0.0205882353</td><td>0.0009803922</td><td>0.0063725490</td><td>0.0147058824</td><td>0.0009803922</td><td>0.0034313725</td><td>0.0009803922</td><td>0.1779411765</td><td>0.0009803922</td><td>0.0098039216</td><td>0.0053921569</td><td>0.0058823529</td><td>0.0024509804</td><td>0.4362745098</td><td>0.0745098039</td><td>0.0019607843</td><td>0.0127450980</td><td>0.0230392157</td><td>0.1348039216</td><td>0.0661764706</td></tr>\n",
       "\t<tr><th scope=row>9</th><td>0.0006257822</td><td>0.0000000000</td><td>0.0018773467</td><td>0.0050062578</td><td>0.0012515645</td><td>0.0000000000</td><td>0.0031289111</td><td>0.0037546934</td><td>0.0000000000</td><td>0.0081351690</td><td>0.0018773467</td><td>0.0006257822</td><td>0.0050062578</td><td>0.9561952441</td><td>0.0000000000</td><td>0.0000000000</td><td>0.0025031289</td><td>0.0025031289</td><td>0.0056320401</td><td>0.0018773467</td></tr>\n",
       "\t<tr><th scope=row>12</th><td>0.0003661662</td><td>0.0007323325</td><td>0.0025631637</td><td>0.4415964848</td><td>0.0618820945</td><td>0.0014646650</td><td>0.0014646650</td><td>0.0084218235</td><td>0.0010984987</td><td>0.0040278286</td><td>0.0190406445</td><td>0.1662394727</td><td>0.1135115342</td><td>0.0087879897</td><td>0.0010984987</td><td>0.0007323325</td><td>0.0091541560</td><td>0.0010984987</td><td>0.1091175394</td><td>0.0476016111</td></tr>\n",
       "\t<tr><th scope=row>14</th><td>0.0205882353</td><td>0.0009803922</td><td>0.0063725490</td><td>0.0147058824</td><td>0.0009803922</td><td>0.0034313725</td><td>0.0009803922</td><td>0.1779411765</td><td>0.0009803922</td><td>0.0098039216</td><td>0.0053921569</td><td>0.0058823529</td><td>0.0024509804</td><td>0.4362745098</td><td>0.0745098039</td><td>0.0019607843</td><td>0.0127450980</td><td>0.0230392157</td><td>0.1348039216</td><td>0.0661764706</td></tr>\n",
       "\t<tr><th scope=row>15</th><td>0.0052508751</td><td>0.0017502917</td><td>0.0233372229</td><td>0.0005834306</td><td>0.0011668611</td><td>0.0367561260</td><td>0.0145857643</td><td>0.0017502917</td><td>0.0017502917</td><td>0.8383897316</td><td>0.0005834306</td><td>0.0035005834</td><td>0.0000000000</td><td>0.0163360560</td><td>0.0017502917</td><td>0.0005834306</td><td>0.0472578763</td><td>0.0040840140</td><td>0.0005834306</td><td>0.0000000000</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|llllllllllllllllllll}\n",
       "  & brazilian & british & cajun_creole & chinese & filipino & french & greek & indian & irish & italian & jamaican & japanese & korean & mexican & moroccan & russian & southern_us & spanish & thai & vietnamese\\\\\n",
       "\\hline\n",
       "\t5 & 0.001628664 & 0.003257329 & 0.000000000 & 0.001628664 & 0.000000000 & 0.000000000 & 0.000000000 & 0.933224756 & 0.000000000 & 0.001628664 & 0.001628664 & 0.047231270 & 0.000000000 & 0.000000000 & 0.006514658 & 0.001628664 & 0.001628664 & 0.000000000 & 0.000000000 & 0.000000000\\\\\n",
       "\t7 & 0.0205882353 & 0.0009803922 & 0.0063725490 & 0.0147058824 & 0.0009803922 & 0.0034313725 & 0.0009803922 & 0.1779411765 & 0.0009803922 & 0.0098039216 & 0.0053921569 & 0.0058823529 & 0.0024509804 & 0.4362745098 & 0.0745098039 & 0.0019607843 & 0.0127450980 & 0.0230392157 & 0.1348039216 & 0.0661764706\\\\\n",
       "\t9 & 0.0006257822 & 0.0000000000 & 0.0018773467 & 0.0050062578 & 0.0012515645 & 0.0000000000 & 0.0031289111 & 0.0037546934 & 0.0000000000 & 0.0081351690 & 0.0018773467 & 0.0006257822 & 0.0050062578 & 0.9561952441 & 0.0000000000 & 0.0000000000 & 0.0025031289 & 0.0025031289 & 0.0056320401 & 0.0018773467\\\\\n",
       "\t12 & 0.0003661662 & 0.0007323325 & 0.0025631637 & 0.4415964848 & 0.0618820945 & 0.0014646650 & 0.0014646650 & 0.0084218235 & 0.0010984987 & 0.0040278286 & 0.0190406445 & 0.1662394727 & 0.1135115342 & 0.0087879897 & 0.0010984987 & 0.0007323325 & 0.0091541560 & 0.0010984987 & 0.1091175394 & 0.0476016111\\\\\n",
       "\t14 & 0.0205882353 & 0.0009803922 & 0.0063725490 & 0.0147058824 & 0.0009803922 & 0.0034313725 & 0.0009803922 & 0.1779411765 & 0.0009803922 & 0.0098039216 & 0.0053921569 & 0.0058823529 & 0.0024509804 & 0.4362745098 & 0.0745098039 & 0.0019607843 & 0.0127450980 & 0.0230392157 & 0.1348039216 & 0.0661764706\\\\\n",
       "\t15 & 0.0052508751 & 0.0017502917 & 0.0233372229 & 0.0005834306 & 0.0011668611 & 0.0367561260 & 0.0145857643 & 0.0017502917 & 0.0017502917 & 0.8383897316 & 0.0005834306 & 0.0035005834 & 0.0000000000 & 0.0163360560 & 0.0017502917 & 0.0005834306 & 0.0472578763 & 0.0040840140 & 0.0005834306 & 0.0000000000\\\\\n",
       "\\end{tabular}\n"
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      "text/plain": [
       "      brazilian      british cajun_creole      chinese     filipino      french\n",
       "5  0.0016286645 0.0032573290  0.000000000 0.0016286645 0.0000000000 0.000000000\n",
       "7  0.0205882353 0.0009803922  0.006372549 0.0147058824 0.0009803922 0.003431373\n",
       "9  0.0006257822 0.0000000000  0.001877347 0.0050062578 0.0012515645 0.000000000\n",
       "12 0.0003661662 0.0007323325  0.002563164 0.4415964848 0.0618820945 0.001464665\n",
       "14 0.0205882353 0.0009803922  0.006372549 0.0147058824 0.0009803922 0.003431373\n",
       "15 0.0052508751 0.0017502917  0.023337223 0.0005834306 0.0011668611 0.036756126\n",
       "          greek      indian        irish     italian     jamaican     japanese\n",
       "5  0.0000000000 0.933224756 0.0000000000 0.001628664 0.0016286645 0.0472312704\n",
       "7  0.0009803922 0.177941176 0.0009803922 0.009803922 0.0053921569 0.0058823529\n",
       "9  0.0031289111 0.003754693 0.0000000000 0.008135169 0.0018773467 0.0006257822\n",
       "12 0.0014646650 0.008421824 0.0010984987 0.004027829 0.0190406445 0.1662394727\n",
       "14 0.0009803922 0.177941176 0.0009803922 0.009803922 0.0053921569 0.0058823529\n",
       "15 0.0145857643 0.001750292 0.0017502917 0.838389732 0.0005834306 0.0035005834\n",
       "        korean    mexican    moroccan      russian southern_us     spanish\n",
       "5  0.000000000 0.00000000 0.006514658 0.0016286645 0.001628664 0.000000000\n",
       "7  0.002450980 0.43627451 0.074509804 0.0019607843 0.012745098 0.023039216\n",
       "9  0.005006258 0.95619524 0.000000000 0.0000000000 0.002503129 0.002503129\n",
       "12 0.113511534 0.00878799 0.001098499 0.0007323325 0.009154156 0.001098499\n",
       "14 0.002450980 0.43627451 0.074509804 0.0019607843 0.012745098 0.023039216\n",
       "15 0.000000000 0.01633606 0.001750292 0.0005834306 0.047257876 0.004084014\n",
       "           thai  vietnamese\n",
       "5  0.0000000000 0.000000000\n",
       "7  0.1348039216 0.066176471\n",
       "9  0.0056320401 0.001877347\n",
       "12 0.1091175394 0.047601611\n",
       "14 0.1348039216 0.066176471\n",
       "15 0.0005834306 0.000000000"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "head(cartPredict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "also installing the dependencies 'misc3d', 'rgl', 'multicool', 'ks', 'logcondens', 'doParallel'\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "package 'misc3d' successfully unpacked and MD5 sums checked\n",
      "package 'rgl' successfully unpacked and MD5 sums checked\n",
      "package 'multicool' successfully unpacked and MD5 sums checked\n",
      "package 'ks' successfully unpacked and MD5 sums checked\n",
      "package 'logcondens' successfully unpacked and MD5 sums checked\n",
      "package 'doParallel' successfully unpacked and MD5 sums checked\n",
      "package 'pROC' successfully unpacked and MD5 sums checked\n",
      "\n",
      "The downloaded binary packages are in\n",
      "\tC:\\Users\\syleeie\\RtmpKcFXpv\\downloaded_packages\n"
     ]
    }
   ],
   "source": [
    "install.packages(\"pROC\", dependencies=T, repos='http://cran.rstudio.com/') "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Type 'citation(\"pROC\")' for a citation.\n",
      "\n",
      "Attaching package: 'pROC'\n",
      "\n",
      "The following objects are masked from 'package:AUC':\n",
      "\n",
      "    auc, roc\n",
      "\n",
      "The following objects are masked from 'package:stats':\n",
      "\n",
      "    cov, smooth, var\n",
      "\n"
     ]
    }
   ],
   "source": [
    "library(pROC)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " Factor w/ 20 levels \"brazilian\",\"british\",..: 8 18 14 4 14 10 2 10 19 10 ...\n"
     ]
    }
   ],
   "source": [
    "str(vaild_data$cuisine)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<ol class=list-inline>\n",
       "\t<li>\"brazilian\"</li>\n",
       "\t<li>\"british\"</li>\n",
       "\t<li>\"cajun_creole\"</li>\n",
       "\t<li>\"chinese\"</li>\n",
       "\t<li>\"filipino\"</li>\n",
       "\t<li>\"french\"</li>\n",
       "\t<li>\"greek\"</li>\n",
       "\t<li>\"indian\"</li>\n",
       "\t<li>\"irish\"</li>\n",
       "\t<li>\"italian\"</li>\n",
       "\t<li>\"jamaican\"</li>\n",
       "\t<li>\"japanese\"</li>\n",
       "\t<li>\"korean\"</li>\n",
       "\t<li>\"mexican\"</li>\n",
       "\t<li>\"moroccan\"</li>\n",
       "\t<li>\"russian\"</li>\n",
       "\t<li>\"southern_us\"</li>\n",
       "\t<li>\"spanish\"</li>\n",
       "\t<li>\"thai\"</li>\n",
       "\t<li>\"vietnamese\"</li>\n",
       "</ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item \"brazilian\"\n",
       "\\item \"british\"\n",
       "\\item \"cajun_creole\"\n",
       "\\item \"chinese\"\n",
       "\\item \"filipino\"\n",
       "\\item \"french\"\n",
       "\\item \"greek\"\n",
       "\\item \"indian\"\n",
       "\\item \"irish\"\n",
       "\\item \"italian\"\n",
       "\\item \"jamaican\"\n",
       "\\item \"japanese\"\n",
       "\\item \"korean\"\n",
       "\\item \"mexican\"\n",
       "\\item \"moroccan\"\n",
       "\\item \"russian\"\n",
       "\\item \"southern_us\"\n",
       "\\item \"spanish\"\n",
       "\\item \"thai\"\n",
       "\\item \"vietnamese\"\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. \"brazilian\"\n",
       "2. \"british\"\n",
       "3. \"cajun_creole\"\n",
       "4. \"chinese\"\n",
       "5. \"filipino\"\n",
       "6. \"french\"\n",
       "7. \"greek\"\n",
       "8. \"indian\"\n",
       "9. \"irish\"\n",
       "10. \"italian\"\n",
       "11. \"jamaican\"\n",
       "12. \"japanese\"\n",
       "13. \"korean\"\n",
       "14. \"mexican\"\n",
       "15. \"moroccan\"\n",
       "16. \"russian\"\n",
       "17. \"southern_us\"\n",
       "18. \"spanish\"\n",
       "19. \"thai\"\n",
       "20. \"vietnamese\"\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       " [1] \"brazilian\"    \"british\"      \"cajun_creole\" \"chinese\"      \"filipino\"    \n",
       " [6] \"french\"       \"greek\"        \"indian\"       \"irish\"        \"italian\"     \n",
       "[11] \"jamaican\"     \"japanese\"     \"korean\"       \"mexican\"      \"moroccan\"    \n",
       "[16] \"russian\"      \"southern_us\"  \"spanish\"      \"thai\"         \"vietnamese\"  "
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "levels(vaild_data$cuisine)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "cartPredict_Prob <- apply(cartPredict, 1, which.max)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<dl class=dl-horizontal>\n",
       "\t<dt>5</dt>\n",
       "\t\t<dd>8</dd>\n",
       "\t<dt>7</dt>\n",
       "\t\t<dd>14</dd>\n",
       "\t<dt>9</dt>\n",
       "\t\t<dd>14</dd>\n",
       "\t<dt>12</dt>\n",
       "\t\t<dd>4</dd>\n",
       "\t<dt>14</dt>\n",
       "\t\t<dd>14</dd>\n",
       "\t<dt>15</dt>\n",
       "\t\t<dd>10</dd>\n",
       "</dl>\n"
      ],
      "text/latex": [
       "\\begin{description*}\n",
       "\\item[5] 8\n",
       "\\item[7] 14\n",
       "\\item[9] 14\n",
       "\\item[12] 4\n",
       "\\item[14] 14\n",
       "\\item[15] 10\n",
       "\\end{description*}\n"
      ],
      "text/markdown": [
       "5\n",
       ":   87\n",
       ":   149\n",
       ":   1412\n",
       ":   414\n",
       ":   1415\n",
       ":   10\n",
       "\n"
      ],
      "text/plain": [
       " 5  7  9 12 14 15 \n",
       " 8 14 14  4 14 10 "
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "head(cartPredict_Prob)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\n",
       "Call:\n",
       "multiclass.roc.default(response = vaild_data$cuisine, predictor = cartPredict_Prob,     levels = levels(vaild_data$cuisine), percent = TRUE)\n",
       "\n",
       "Data: cartPredict_Prob with 20 levels of vaild_data$cuisine: brazilian, british, cajun_creole, chinese, filipino, french, greek, indian, irish, italian, jamaican, japanese, korean, mexican, moroccan, russian, southern_us, spanish, thai, vietnamese.\n",
       "Multi-class area under the curve: 65.14%"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "multiclass.roc(response=vaild_data$cuisine,  predictor=cartPredict_Prob, levels=levels(vaild_data$cuisine),percent=TRUE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "cartPredict_test <- predict(cartModelFit, newdata = test_data, type = \"class\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<dl class=dl-horizontal>\n",
       "\t<dt>39775</dt>\n",
       "\t\t<dd>southern_us</dd>\n",
       "\t<dt>39776</dt>\n",
       "\t\t<dd>southern_us</dd>\n",
       "\t<dt>39777</dt>\n",
       "\t\t<dd>italian</dd>\n",
       "\t<dt>39778</dt>\n",
       "\t\t<dd>southern_us</dd>\n",
       "\t<dt>39779</dt>\n",
       "\t\t<dd>italian</dd>\n",
       "\t<dt>39780</dt>\n",
       "\t\t<dd>southern_us</dd>\n",
       "</dl>\n"
      ],
      "text/latex": [
       "\\begin{description*}\n",
       "\\item[39775] southern_us\n",
       "\\item[39776] southern_us\n",
       "\\item[39777] italian\n",
       "\\item[39778] southern_us\n",
       "\\item[39779] italian\n",
       "\\item[39780] southern_us\n",
       "\\end{description*}\n"
      ],
      "text/markdown": [
       "39775\n",
       ":   southern_us39776\n",
       ":   southern_us39777\n",
       ":   italian39778\n",
       ":   southern_us39779\n",
       ":   italian39780\n",
       ":   southern_us\n",
       "\n"
      ],
      "text/plain": [
       "      39775       39776       39777       39778       39779       39780 \n",
       "southern_us southern_us     italian southern_us     italian southern_us \n",
       "20 Levels: brazilian british cajun_creole chinese filipino french ... vietnamese"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "head(cartPredict_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<ol class=list-inline>\n",
       "\t<li>18009</li>\n",
       "\t<li>28583</li>\n",
       "\t<li>41580</li>\n",
       "\t<li>29752</li>\n",
       "\t<li>35687</li>\n",
       "\t<li>38527</li>\n",
       "</ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 18009\n",
       "\\item 28583\n",
       "\\item 41580\n",
       "\\item 29752\n",
       "\\item 35687\n",
       "\\item 38527\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 18009\n",
       "2. 28583\n",
       "3. 41580\n",
       "4. 29752\n",
       "5. 35687\n",
       "6. 38527\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "[1] 18009 28583 41580 29752 35687 38527"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "head(test$id)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "test_predict <- data.frame(id = test$id, cuisine = cartPredict_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th></th><th scope=col>id</th><th scope=col>cuisine</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>39775</th><td>18009</td><td>southern_us</td></tr>\n",
       "\t<tr><th scope=row>39776</th><td>28583</td><td>southern_us</td></tr>\n",
       "\t<tr><th scope=row>39777</th><td>41580</td><td>italian</td></tr>\n",
       "\t<tr><th scope=row>39778</th><td>29752</td><td>southern_us</td></tr>\n",
       "\t<tr><th scope=row>39779</th><td>35687</td><td>italian</td></tr>\n",
       "\t<tr><th scope=row>39780</th><td>38527</td><td>southern_us</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|ll}\n",
       "  & id & cuisine\\\\\n",
       "\\hline\n",
       "\t39775 & 18009 & southern_us\\\\\n",
       "\t39776 & 28583 & southern_us\\\\\n",
       "\t39777 & 41580 & italian\\\\\n",
       "\t39778 & 29752 & southern_us\\\\\n",
       "\t39779 & 35687 & italian\\\\\n",
       "\t39780 & 38527 & southern_us\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "         id     cuisine\n",
       "39775 18009 southern_us\n",
       "39776 28583 southern_us\n",
       "39777 41580     italian\n",
       "39778 29752 southern_us\n",
       "39779 35687     italian\n",
       "39780 38527 southern_us"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "head(test_predict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "submission <- left_join(sample_sub, test_predict, by=\"id\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th></th><th scope=col>id</th><th scope=col>cuisine.x</th><th scope=col>cuisine.y</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>1</th><td>35203</td><td>italian</td><td>southern_us</td></tr>\n",
       "\t<tr><th scope=row>2</th><td>17600</td><td>italian</td><td>mexican</td></tr>\n",
       "\t<tr><th scope=row>3</th><td>35200</td><td>italian</td><td>southern_us</td></tr>\n",
       "\t<tr><th scope=row>4</th><td>17602</td><td>italian</td><td>mexican</td></tr>\n",
       "\t<tr><th scope=row>5</th><td>17605</td><td>italian</td><td>indian</td></tr>\n",
       "\t<tr><th scope=row>6</th><td>17604</td><td>italian</td><td>chinese</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lll}\n",
       "  & id & cuisine.x & cuisine.y\\\\\n",
       "\\hline\n",
       "\t1 & 35203 & italian & southern_us\\\\\n",
       "\t2 & 17600 & italian & mexican\\\\\n",
       "\t3 & 35200 & italian & southern_us\\\\\n",
       "\t4 & 17602 & italian & mexican\\\\\n",
       "\t5 & 17605 & italian & indian\\\\\n",
       "\t6 & 17604 & italian & chinese\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "     id cuisine.x   cuisine.y\n",
       "1 35203   italian southern_us\n",
       "2 17600   italian     mexican\n",
       "3 35200   italian southern_us\n",
       "4 17602   italian     mexican\n",
       "5 17605   italian      indian\n",
       "6 17604   italian     chinese"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "head(submission)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "submission <- submission[,-2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th></th><th scope=col>id</th><th scope=col>cuisine.y</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>1</th><td>35203</td><td>southern_us</td></tr>\n",
       "\t<tr><th scope=row>2</th><td>17600</td><td>mexican</td></tr>\n",
       "\t<tr><th scope=row>3</th><td>35200</td><td>southern_us</td></tr>\n",
       "\t<tr><th scope=row>4</th><td>17602</td><td>mexican</td></tr>\n",
       "\t<tr><th scope=row>5</th><td>17605</td><td>indian</td></tr>\n",
       "\t<tr><th scope=row>6</th><td>17604</td><td>chinese</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|ll}\n",
       "  & id & cuisine.y\\\\\n",
       "\\hline\n",
       "\t1 & 35203 & southern_us\\\\\n",
       "\t2 & 17600 & mexican\\\\\n",
       "\t3 & 35200 & southern_us\\\\\n",
       "\t4 & 17602 & mexican\\\\\n",
       "\t5 & 17605 & indian\\\\\n",
       "\t6 & 17604 & chinese\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "     id   cuisine.y\n",
       "1 35203 southern_us\n",
       "2 17600     mexican\n",
       "3 35200 southern_us\n",
       "4 17602     mexican\n",
       "5 17605      indian\n",
       "6 17604     chinese"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "head(submission)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "colnames(submission) <- c(\"id\", \"cuisine\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th></th><th scope=col>id</th><th scope=col>cuisine</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>1</th><td>35203</td><td>southern_us</td></tr>\n",
       "\t<tr><th scope=row>2</th><td>17600</td><td>mexican</td></tr>\n",
       "\t<tr><th scope=row>3</th><td>35200</td><td>southern_us</td></tr>\n",
       "\t<tr><th scope=row>4</th><td>17602</td><td>mexican</td></tr>\n",
       "\t<tr><th scope=row>5</th><td>17605</td><td>indian</td></tr>\n",
       "\t<tr><th scope=row>6</th><td>17604</td><td>chinese</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|ll}\n",
       "  & id & cuisine\\\\\n",
       "\\hline\n",
       "\t1 & 35203 & southern_us\\\\\n",
       "\t2 & 17600 & mexican\\\\\n",
       "\t3 & 35200 & southern_us\\\\\n",
       "\t4 & 17602 & mexican\\\\\n",
       "\t5 & 17605 & indian\\\\\n",
       "\t6 & 17604 & chinese\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "     id     cuisine\n",
       "1 35203 southern_us\n",
       "2 17600     mexican\n",
       "3 35200 southern_us\n",
       "4 17602     mexican\n",
       "5 17605      indian\n",
       "6 17604     chinese"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "head(submission)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "write.csv(submission, file = 'cart_submission.csv', row.names = F)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 첫번째 submission 결과\n",
    "<img src=\"cart_submission.jpg\" alt=\"alt text\" title=\"Title\"/>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "library(extraTrees)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### RandomForest 일종의 트리. \n",
    "- thresholds를 트리마다 랜덤하게 선택 (feautre를 나무마다 다르게 선택)\n",
    "![](http://www.iis.ee.ic.ac.uk/icvl/iccv09_tutorial_files/random_forest_new2.png)\n",
    "### http://scikit-learn.org/stable/modules/ensemble.html"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "extraTreesModelFit <- extraTrees(train_data[,-251], train_data[,251], ntree=100, numThreads=4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "ExtraTrees:\n",
       " - # of trees: 100\n",
       " - node size:  1\n",
       " - # of dim:   250\n",
       " - # of tries: 15\n",
       " - type:       factor (classification)\n",
       " - multi-task: no"
      ]
     },
     "execution_count": 113,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "extraTreesModelFit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "ename": "ERROR",
     "evalue": "Error in .jcall(et$jobject, \"Lorg/extratrees/data/Matrix;\", \"getAllValues\", : java.lang.NullPointerException\n",
     "output_type": "error",
     "traceback": [
      "Error in .jcall(et$jobject, \"Lorg/extratrees/data/Matrix;\", \"getAllValues\", : java.lang.NullPointerException\n"
     ]
    }
   ],
   "source": [
    "vaild_label_extra <- predict(extraTreesModelFit, vaild_data[,-251], probability=T)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>brazilian</th><th scope=col>british</th><th scope=col>cajun_creole</th><th scope=col>chinese</th><th scope=col>filipino</th><th scope=col>french</th><th scope=col>greek</th><th scope=col>indian</th><th scope=col>irish</th><th scope=col>italian</th><th scope=col>jamaican</th><th scope=col>japanese</th><th scope=col>korean</th><th scope=col>mexican</th><th scope=col>moroccan</th><th scope=col>russian</th><th scope=col>southern_us</th><th scope=col>spanish</th><th scope=col>thai</th><th scope=col>vietnamese</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>0.00</td><td>0.00</td><td>0.00</td><td>0.00</td><td>0.00</td><td>0.01</td><td>0.00</td><td>0.89</td><td>0.00</td><td>0.01</td><td>0.00</td><td>0.00</td><td>0.00</td><td>0.05</td><td>0.00</td><td>0.01</td><td>0.03</td><td>0.00</td><td>0.00</td><td>0.00</td></tr>\n",
       "\t<tr><td>0.12</td><td>0.02</td><td>0.07</td><td>0.02</td><td>0.01</td><td>0.01</td><td>0.00</td><td>0.00</td><td>0.00</td><td>0.14</td><td>0.00</td><td>0.01</td><td>0.01</td><td>0.43</td><td>0.07</td><td>0.00</td><td>0.04</td><td>0.03</td><td>0.02</td><td>0.00</td></tr>\n",
       "\t<tr><td>0.01</td><td>0.00</td><td>0.00</td><td>0.00</td><td>0.00</td><td>0.00</td><td>0.00</td><td>0.00</td><td>0.00</td><td>0.00</td><td>0.00</td><td>0.00</td><td>0.00</td><td>0.98</td><td>0.00</td><td>0.00</td><td>0.01</td><td>0.00</td><td>0.00</td><td>0.00</td></tr>\n",
       "\t<tr><td>0.00</td><td>0.00</td><td>0.00</td><td>0.89</td><td>0.00</td><td>0.01</td><td>0.00</td><td>0.00</td><td>0.00</td><td>0.01</td><td>0.00</td><td>0.04</td><td>0.01</td><td>0.01</td><td>0.00</td><td>0.00</td><td>0.00</td><td>0.00</td><td>0.01</td><td>0.02</td></tr>\n",
       "\t<tr><td>0.00</td><td>0.00</td><td>0.00</td><td>0.00</td><td>0.00</td><td>0.02</td><td>0.01</td><td>0.06</td><td>0.00</td><td>0.00</td><td>0.03</td><td>0.01</td><td>0.00</td><td>0.76</td><td>0.10</td><td>0.00</td><td>0.01</td><td>0.00</td><td>0.00</td><td>0.00</td></tr>\n",
       "\t<tr><td>0.00</td><td>0.00</td><td>0.01</td><td>0.00</td><td>0.00</td><td>0.05</td><td>0.00</td><td>0.00</td><td>0.08</td><td>0.65</td><td>0.00</td><td>0.00</td><td>0.00</td><td>0.02</td><td>0.00</td><td>0.00</td><td>0.19</td><td>0.00</td><td>0.00</td><td>0.00</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{llllllllllllllllllll}\n",
       " brazilian & british & cajun_creole & chinese & filipino & french & greek & indian & irish & italian & jamaican & japanese & korean & mexican & moroccan & russian & southern_us & spanish & thai & vietnamese\\\\\n",
       "\\hline\n",
       "\t 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.01 & 0.00 & 0.89 & 0.00 & 0.01 & 0.00 & 0.00 & 0.00 & 0.05 & 0.00 & 0.01 & 0.03 & 0.00 & 0.00 & 0.00\\\\\n",
       "\t 0.12 & 0.02 & 0.07 & 0.02 & 0.01 & 0.01 & 0.00 & 0.00 & 0.00 & 0.14 & 0.00 & 0.01 & 0.01 & 0.43 & 0.07 & 0.00 & 0.04 & 0.03 & 0.02 & 0.00\\\\\n",
       "\t 0.01 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.98 & 0.00 & 0.00 & 0.01 & 0.00 & 0.00 & 0.00\\\\\n",
       "\t 0.00 & 0.00 & 0.00 & 0.89 & 0.00 & 0.01 & 0.00 & 0.00 & 0.00 & 0.01 & 0.00 & 0.04 & 0.01 & 0.01 & 0.00 & 0.00 & 0.00 & 0.00 & 0.01 & 0.02\\\\\n",
       "\t 0.00 & 0.00 & 0.00 & 0.00 & 0.00 & 0.02 & 0.01 & 0.06 & 0.00 & 0.00 & 0.03 & 0.01 & 0.00 & 0.76 & 0.10 & 0.00 & 0.01 & 0.00 & 0.00 & 0.00\\\\\n",
       "\t 0.00 & 0.00 & 0.01 & 0.00 & 0.00 & 0.05 & 0.00 & 0.00 & 0.08 & 0.65 & 0.00 & 0.00 & 0.00 & 0.02 & 0.00 & 0.00 & 0.19 & 0.00 & 0.00 & 0.00\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "1. 0\n",
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       "4. 0\n",
       "5. 0\n",
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       "7. 0\n",
       "8. 0.02\n",
       "9. 0\n",
       "10. 0\n",
       "11. 0\n",
       "12. 0\n",
       "13. 0\n",
       "14. 0.07\n",
       "15. 0\n",
       "16. 0\n",
       "17. 0\n",
       "18. 0.01\n",
       "19. 0\n",
       "20. 0.02\n",
       "21. 0\n",
       "22. 0.89\n",
       "23. 0\n",
       "24. 0\n",
       "25. 0\n",
       "26. 0.01\n",
       "27. 0\n",
       "28. 0\n",
       "29. 0\n",
       "30. 0\n",
       "31. 0.01\n",
       "32. 0.01\n",
       "33. 0\n",
       "34. 0.01\n",
       "35. 0.02\n",
       "36. 0.05\n",
       "37. 0\n",
       "38. 0\n",
       "39. 0\n",
       "40. 0\n",
       "41. 0.01\n",
       "42. 0\n",
       "43. 0.89\n",
       "44. 0\n",
       "45. 0\n",
       "46. 0\n",
       "47. 0.06\n",
       "48. 0\n",
       "49. 0\n",
       "50. 0\n",
       "51. 0\n",
       "52. 0\n",
       "53. 0\n",
       "54. 0.08\n",
       "55. 0.01\n",
       "56. 0.14\n",
       "57. 0\n",
       "58. 0.01\n",
       "59. 0\n",
       "60. 0.65\n",
       "61. 0\n",
       "62. 0\n",
       "63. 0\n",
       "64. 0\n",
       "65. 0.03\n",
       "66. 0\n",
       "67. 0\n",
       "68. 0.01\n",
       "69. 0\n",
       "70. 0.04\n",
       "71. 0.01\n",
       "72. 0\n",
       "73. 0\n",
       "74. 0.01\n",
       "75. 0\n",
       "76. 0.01\n",
       "77. 0\n",
       "78. 0\n",
       "79. 0.05\n",
       "80. 0.43\n",
       "81. 0.98\n",
       "82. 0.01\n",
       "83. 0.76\n",
       "84. 0.02\n",
       "85. 0\n",
       "86. 0.07\n",
       "87. 0\n",
       "88. 0\n",
       "89. 0.1\n",
       "90. 0\n",
       "91. 0.01\n",
       "92. 0\n",
       "93. 0\n",
       "94. 0\n",
       "95. 0\n",
       "96. 0\n",
       "97. 0.03\n",
       "98. 0.04\n",
       "99. 0.01\n",
       "100. 0\n",
       "101. 0.01\n",
       "102. 0.19\n",
       "103. 0\n",
       "104. 0.03\n",
       "105. 0\n",
       "106. 0\n",
       "107. 0\n",
       "108. 0\n",
       "109. 0\n",
       "110. 0.02\n",
       "111. 0\n",
       "112. 0.01\n",
       "113. 0\n",
       "114. 0\n",
       "115. 0\n",
       "116. 0\n",
       "117. 0\n",
       "118. 0.02\n",
       "119. 0\n",
       "120. 0\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "     brazilian british cajun_creole chinese filipino french greek indian irish\n",
       "[1,]      0.00    0.00         0.00    0.00     0.00   0.01  0.00   0.89  0.00\n",
       "[2,]      0.12    0.02         0.07    0.02     0.01   0.01  0.00   0.00  0.00\n",
       "[3,]      0.01    0.00         0.00    0.00     0.00   0.00  0.00   0.00  0.00\n",
       "[4,]      0.00    0.00         0.00    0.89     0.00   0.01  0.00   0.00  0.00\n",
       "[5,]      0.00    0.00         0.00    0.00     0.00   0.02  0.01   0.06  0.00\n",
       "[6,]      0.00    0.00         0.01    0.00     0.00   0.05  0.00   0.00  0.08\n",
       "     italian jamaican japanese korean mexican moroccan russian southern_us\n",
       "[1,]    0.01     0.00     0.00   0.00    0.05     0.00    0.01        0.03\n",
       "[2,]    0.14     0.00     0.01   0.01    0.43     0.07    0.00        0.04\n",
       "[3,]    0.00     0.00     0.00   0.00    0.98     0.00    0.00        0.01\n",
       "[4,]    0.01     0.00     0.04   0.01    0.01     0.00    0.00        0.00\n",
       "[5,]    0.00     0.03     0.01   0.00    0.76     0.10    0.00        0.01\n",
       "[6,]    0.65     0.00     0.00   0.00    0.02     0.00    0.00        0.19\n",
       "     spanish thai vietnamese\n",
       "[1,]    0.00 0.00       0.00\n",
       "[2,]    0.03 0.02       0.00\n",
       "[3,]    0.00 0.00       0.00\n",
       "[4,]    0.00 0.01       0.02\n",
       "[5,]    0.00 0.00       0.00\n",
       "[6,]    0.00 0.00       0.00"
      ]
     },
     "execution_count": 119,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "head(vaild_label_extra) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "ename": "ERROR",
     "evalue": "Error in .jarray(m): java.lang.OutOfMemoryError: Java heap space\n",
     "output_type": "error",
     "traceback": [
      "Error in .jarray(m): java.lang.OutOfMemoryError: Java heap space\n"
     ]
    }
   ],
   "source": [
    "vaild_label_extra2 <- predict(extraTreesModelFit, vaild_data[,-251], probability=F)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "extraCM <- confusionMatrix(vaild_label_extra2, vaild_data$cuisine)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Confusion Matrix and Statistics\n",
       "\n",
       "              Reference\n",
       "Prediction     brazilian british cajun_creole chinese filipino french greek\n",
       "  brazilian           81       2            1       0        7      1     0\n",
       "  british              0      98            1       1        6     10     3\n",
       "  cajun_creole         5       1          388       1        1     12     3\n",
       "  chinese              0       2            3     913       46      4     0\n",
       "  filipino             1       0            0       8      154      1     2\n",
       "  french               6      45           19       8        7    535    16\n",
       "  greek                0       3            2       1        1      7   298\n",
       "  indian               6      11            3       4       11      2    13\n",
       "  irish                0      18            0       0        2     10     1\n",
       "  italian             31      38           58      15        8    307   103\n",
       "  jamaican             2       2            1       2        0      2     0\n",
       "  japanese             0       1            3      38        1      4     1\n",
       "  korean               0       1            1      20        1      0     0\n",
       "  mexican             29       7           41      11       12     20     9\n",
       "  moroccan             1       2            2       0        0      6     7\n",
       "  russian              2       2            2       0        2      4     0\n",
       "  southern_us         14      86           88      22       25    121    11\n",
       "  spanish              1       1            5       1        1     11     3\n",
       "  thai                 7       0            0      18       16      1     0\n",
       "  vietnamese           0       1            0       6        1      0     0\n",
       "              Reference\n",
       "Prediction     indian irish italian jamaican japanese korean mexican moroccan\n",
       "  brazilian         1     2       0        3        1      0       8        0\n",
       "  british           1    15      15        1        2      3       3        1\n",
       "  cajun_creole      2     2      10        4        4      1       7        4\n",
       "  chinese           5     1       5        3      105     63       1        3\n",
       "  filipino          1     1       3        2        3      5       1        0\n",
       "  french            8    35     124        1       16      0      20        9\n",
       "  greek             8     0      33        0        0      0       4        4\n",
       "  indian         1070     6       7       12       56      2      14       37\n",
       "  irish             1    98       4        0        1      0       1        1\n",
       "  italian          14    28    2738        8       14      1      52       24\n",
       "  jamaican          6     0       3      110        0      0       4        0\n",
       "  japanese          9     3       4        2      308     33       9        0\n",
       "  korean            0     1       0        0       20    200       4        1\n",
       "  mexican          35     5      66       25       11      7    2368       20\n",
       "  moroccan         16     1       5        3        0      0       7      212\n",
       "  russian           2     2       7        1        2      1       0        0\n",
       "  southern_us       7    65      92       29       16      5      60        8\n",
       "  spanish           2     1      15        2        0      0       8        2\n",
       "  thai             12     0       1        4        8      7       2        1\n",
       "  vietnamese        1     0       3        0        2      4       2        1\n",
       "              Reference\n",
       "Prediction     russian southern_us spanish thai vietnamese\n",
       "  brazilian          0           4       2    4          2\n",
       "  british            5          11       2    0          0\n",
       "  cajun_creole       0          75       5    2          0\n",
       "  chinese            1          10       2   49         42\n",
       "  filipino           1           5       2    0          2\n",
       "  french            36          73      29    1          1\n",
       "  greek              6           5       5    0          0\n",
       "  indian             6          15       5   37         11\n",
       "  irish              2           9       0    0          0\n",
       "  italian           39         145     110    9          2\n",
       "  jamaican           0           2       0    1          1\n",
       "  japanese           1           5       0    3          7\n",
       "  korean             0           1       0    3          2\n",
       "  mexican           13          87      56   13          8\n",
       "  moroccan           0           6       3    1          0\n",
       "  russian           56           6       2    0          0\n",
       "  southern_us       27        1256      20    3          4\n",
       "  spanish            2          10     150    0          0\n",
       "  thai               0           2       2  464         92\n",
       "  vietnamese         0           1       0   25        156\n",
       "\n",
       "Overall Statistics\n",
       "                                          \n",
       "               Accuracy : 0.7328          \n",
       "                 95% CI : (0.7258, 0.7396)\n",
       "    No Information Rate : 0.1971          \n",
       "    P-Value [Acc > NIR] : < 2.2e-16       \n",
       "                                          \n",
       "                  Kappa : 0.6993          \n",
       " Mcnemar's Test P-Value : NA              \n",
       "\n",
       "Statistics by Class:\n",
       "\n",
       "                     Class: brazilian Class: british Class: cajun_creole\n",
       "Sensitivity                  0.435484       0.305296             0.62783\n",
       "Specificity                  0.997582       0.994866             0.99091\n",
       "Pos Pred Value               0.680672       0.550562             0.73624\n",
       "Neg Pred Value               0.993348       0.985819             0.98504\n",
       "Prevalence                   0.011696       0.020185             0.03886\n",
       "Detection Rate               0.005093       0.006162             0.02440\n",
       "Detection Prevalence         0.007483       0.011193             0.03314\n",
       "Balanced Accuracy            0.716533       0.650081             0.80937\n",
       "                     Class: chinese Class: filipino Class: french Class: greek\n",
       "Sensitivity                 0.85407        0.509934       0.50567      0.63404\n",
       "Specificity                 0.97674        0.997564       0.96942      0.99488\n",
       "Pos Pred Value              0.72576        0.802083       0.54095      0.79045\n",
       "Neg Pred Value              0.98935        0.990580       0.96493      0.98892\n",
       "Prevalence                  0.06722        0.018990       0.06653      0.02955\n",
       "Detection Rate              0.05741        0.009684       0.03364      0.01874\n",
       "Detection Prevalence        0.07910        0.012073       0.06219      0.02371\n",
       "Balanced Accuracy           0.91541        0.753749       0.73754      0.81446\n",
       "                     Class: indian Class: irish Class: italian Class: jamaican\n",
       "Sensitivity                0.89092     0.368421         0.8734        0.523810\n",
       "Specificity                0.98245     0.996802         0.9212        0.998343\n",
       "Pos Pred Value             0.80572     0.662162         0.7313        0.808824\n",
       "Neg Pred Value             0.99101     0.989337         0.9673        0.993658\n",
       "Prevalence                 0.07552     0.016726         0.1971        0.013205\n",
       "Detection Rate             0.06728     0.006162         0.1722        0.006917\n",
       "Detection Prevalence       0.08351     0.009306         0.2354        0.008552\n",
       "Balanced Accuracy          0.93669     0.682612         0.8973        0.761076\n",
       "                     Class: japanese Class: korean Class: mexican\n",
       "Sensitivity                  0.54130       0.60241         0.9196\n",
       "Specificity                  0.99191       0.99647         0.9644\n",
       "Pos Pred Value               0.71296       0.78431         0.8329\n",
       "Neg Pred Value               0.98313       0.99156         0.9842\n",
       "Prevalence                   0.03578       0.02088         0.1619\n",
       "Detection Rate               0.01937       0.01258         0.1489\n",
       "Detection Prevalence         0.02716       0.01603         0.1788\n",
       "Balanced Accuracy            0.76661       0.79944         0.9420\n",
       "                     Class: moroccan Class: russian Class: southern_us\n",
       "Sensitivity                  0.64634       0.287179            0.72685\n",
       "Specificity                  0.99615       0.997772            0.95041\n",
       "Pos Pred Value               0.77941       0.615385            0.64114\n",
       "Neg Pred Value               0.99258       0.991209            0.96615\n",
       "Prevalence                   0.02063       0.012262            0.10866\n",
       "Detection Rate               0.01333       0.003521            0.07898\n",
       "Detection Prevalence         0.01710       0.005722            0.12318\n",
       "Balanced Accuracy            0.82124       0.642476            0.83863\n",
       "                     Class: spanish Class: thai Class: vietnamese\n",
       "Sensitivity                0.379747     0.75447          0.472727\n",
       "Specificity                0.995809     0.98868          0.996982\n",
       "Pos Pred Value             0.697674     0.72841          0.768473\n",
       "Neg Pred Value             0.984383     0.99011          0.988917\n",
       "Prevalence                 0.024838     0.03867          0.020751\n",
       "Detection Rate             0.009432     0.02918          0.009809\n",
       "Detection Prevalence       0.013519     0.04006          0.012765\n",
       "Balanced Accuracy          0.687778     0.87158          0.734855"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "extraCM"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "extraPredict_Prob <- apply(vaild_label_extra, 1, which.max)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\n",
       "Call:\n",
       "multiclass.roc.default(response = vaild_data$cuisine, predictor = extraPredict_Prob,     levels = levels(vaild_data$cuisine), percent = TRUE)\n",
       "\n",
       "Data: extraPredict_Prob with 20 levels of vaild_data$cuisine: brazilian, british, cajun_creole, chinese, filipino, french, greek, indian, irish, italian, jamaican, japanese, korean, mexican, moroccan, russian, southern_us, spanish, thai, vietnamese.\n",
       "Multi-class area under the curve: 73.82%"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "multiclass.roc(response=vaild_data$cuisine, predictor=extraPredict_Prob, levels=levels(vaild_data$cuisine),percent=TRUE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "extraPredict_test <- predict(extraTreesModelFit, newdata = test_data[,-251], probability=F)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<ol class=list-inline>\n",
       "\t<li>southern_us</li>\n",
       "\t<li>southern_us</li>\n",
       "\t<li>italian</li>\n",
       "\t<li>cajun_creole</li>\n",
       "\t<li>italian</li>\n",
       "\t<li>southern_us</li>\n",
       "</ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item southern_us\n",
       "\\item southern_us\n",
       "\\item italian\n",
       "\\item cajun_creole\n",
       "\\item italian\n",
       "\\item southern_us\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. southern_us\n",
       "2. southern_us\n",
       "3. italian\n",
       "4. cajun_creole\n",
       "5. italian\n",
       "6. southern_us\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "[1] southern_us  southern_us  italian      cajun_creole italian     \n",
       "[6] southern_us \n",
       "20 Levels: brazilian british cajun_creole chinese filipino french ... vietnamese"
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "head(extraPredict_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "extra_test_predict <- data.frame(id = test$id, cuisine = extraPredict_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th></th><th scope=col>id</th><th scope=col>cuisine</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>1</th><td>18009</td><td>southern_us</td></tr>\n",
       "\t<tr><th scope=row>2</th><td>28583</td><td>southern_us</td></tr>\n",
       "\t<tr><th scope=row>3</th><td>41580</td><td>italian</td></tr>\n",
       "\t<tr><th scope=row>4</th><td>29752</td><td>cajun_creole</td></tr>\n",
       "\t<tr><th scope=row>5</th><td>35687</td><td>italian</td></tr>\n",
       "\t<tr><th scope=row>6</th><td>38527</td><td>southern_us</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|ll}\n",
       "  & id & cuisine\\\\\n",
       "\\hline\n",
       "\t1 & 18009 & southern_us\\\\\n",
       "\t2 & 28583 & southern_us\\\\\n",
       "\t3 & 41580 & italian\\\\\n",
       "\t4 & 29752 & cajun_creole\\\\\n",
       "\t5 & 35687 & italian\\\\\n",
       "\t6 & 38527 & southern_us\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "     id      cuisine\n",
       "1 18009  southern_us\n",
       "2 28583  southern_us\n",
       "3 41580      italian\n",
       "4 29752 cajun_creole\n",
       "5 35687      italian\n",
       "6 38527  southern_us"
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "head(extra_test_predict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th></th><th scope=col>id</th><th scope=col>cuisine</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>39775</th><td>18009</td><td>southern_us</td></tr>\n",
       "\t<tr><th scope=row>39776</th><td>28583</td><td>southern_us</td></tr>\n",
       "\t<tr><th scope=row>39777</th><td>41580</td><td>italian</td></tr>\n",
       "\t<tr><th scope=row>39778</th><td>29752</td><td>southern_us</td></tr>\n",
       "\t<tr><th scope=row>39779</th><td>35687</td><td>italian</td></tr>\n",
       "\t<tr><th scope=row>39780</th><td>38527</td><td>southern_us</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|ll}\n",
       "  & id & cuisine\\\\\n",
       "\\hline\n",
       "\t39775 & 18009 & southern_us\\\\\n",
       "\t39776 & 28583 & southern_us\\\\\n",
       "\t39777 & 41580 & italian\\\\\n",
       "\t39778 & 29752 & southern_us\\\\\n",
       "\t39779 & 35687 & italian\\\\\n",
       "\t39780 & 38527 & southern_us\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "         id     cuisine\n",
       "39775 18009 southern_us\n",
       "39776 28583 southern_us\n",
       "39777 41580     italian\n",
       "39778 29752 southern_us\n",
       "39779 35687     italian\n",
       "39780 38527 southern_us"
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "head(test_predict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "submission <- left_join(sample_sub, extra_test_predict, by=\"id\")\n",
    "submission <- submission[,-2]\n",
    "colnames(submission) <- c(\"id\", \"cuisine\")\n",
    "write.csv(submission, file = 'extra_submission.csv', row.names = F)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 두번째 submission 결과\n",
    "<img src=\"extra_submission.jpg\" alt=\"alt text\" title=\"Title\"/>"
   ]
  }
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