2-description_analysis.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# NLP on description of the wine review"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "from nltk.corpus import stopwords\n",
    "from nltk.tokenize import word_tokenize\n",
    "from nltk.stem import PorterStemmer\n",
    "import string\n",
    "import nltk"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def filtered_sequence(input_sequence):\n",
    "    ps = PorterStemmer()\n",
    "    stop_words = set(stopwords.words('english'))\n",
    "\n",
    "    input_sequence = input_sequence.translate(str.maketrans('', '', string.punctuation))\n",
    "    sequence_tokens = word_tokenize(input_sequence)\n",
    "    filtered_sentence = [w for w in sequence_tokens if not w.lower() in stop_words]\n",
    "    filtered_sentence = [ps.stem(w) for w in filtered_sentence]\n",
    "\n",
    "    return filtered_sentence"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['sampl', 'sentenc', 'show', 'stop', 'word', 'filtrat']"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "example_sent = \"\"\"This is a sample sentence,\n",
    "                  showing off the stop words filtration.\"\"\"\n",
    "\n",
    "filtered_sequence(example_sent)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>country</th>\n",
       "      <th>description</th>\n",
       "      <th>designation</th>\n",
       "      <th>points</th>\n",
       "      <th>price</th>\n",
       "      <th>province</th>\n",
       "      <th>region_1</th>\n",
       "      <th>region_2</th>\n",
       "      <th>taster_name</th>\n",
       "      <th>taster_twitter_handle</th>\n",
       "      <th>title</th>\n",
       "      <th>variety</th>\n",
       "      <th>winery</th>\n",
       "      <th>polarity_text</th>\n",
       "      <th>subjectivity_text</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Italy</td>\n",
       "      <td>Aromas include tropical fruit, broom, brimston...</td>\n",
       "      <td>Vulkà Bianco</td>\n",
       "      <td>87</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Sicily &amp; Sardinia</td>\n",
       "      <td>Etna</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Kerin O’Keefe</td>\n",
       "      <td>@kerinokeefe</td>\n",
       "      <td>Nicosia 2013 Vulkà Bianco  (Etna)</td>\n",
       "      <td>White Blend</td>\n",
       "      <td>Nicosia</td>\n",
       "      <td>0.133333</td>\n",
       "      <td>0.733333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Portugal</td>\n",
       "      <td>This is ripe and fruity, a wine that is smooth...</td>\n",
       "      <td>Avidagos</td>\n",
       "      <td>87</td>\n",
       "      <td>15.0</td>\n",
       "      <td>Douro</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Roger Voss</td>\n",
       "      <td>@vossroger</td>\n",
       "      <td>Quinta dos Avidagos 2011 Avidagos Red (Douro)</td>\n",
       "      <td>Portuguese Red</td>\n",
       "      <td>Quinta dos Avidagos</td>\n",
       "      <td>0.220000</td>\n",
       "      <td>0.460000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>US</td>\n",
       "      <td>Tart and snappy, the flavors of lime flesh and...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>87</td>\n",
       "      <td>14.0</td>\n",
       "      <td>Oregon</td>\n",
       "      <td>Willamette Valley</td>\n",
       "      <td>Willamette Valley</td>\n",
       "      <td>Paul Gregutt</td>\n",
       "      <td>@paulgwine</td>\n",
       "      <td>Rainstorm 2013 Pinot Gris (Willamette Valley)</td>\n",
       "      <td>Pinot Gris</td>\n",
       "      <td>Rainstorm</td>\n",
       "      <td>0.025000</td>\n",
       "      <td>0.358333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>US</td>\n",
       "      <td>Pineapple rind, lemon pith and orange blossom ...</td>\n",
       "      <td>Reserve Late Harvest</td>\n",
       "      <td>87</td>\n",
       "      <td>13.0</td>\n",
       "      <td>Michigan</td>\n",
       "      <td>Lake Michigan Shore</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Alexander Peartree</td>\n",
       "      <td>NaN</td>\n",
       "      <td>St. Julian 2013 Reserve Late Harvest Riesling ...</td>\n",
       "      <td>Riesling</td>\n",
       "      <td>St. Julian</td>\n",
       "      <td>0.166667</td>\n",
       "      <td>0.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>US</td>\n",
       "      <td>Much like the regular bottling from 2012, this...</td>\n",
       "      <td>Vintner's Reserve Wild Child Block</td>\n",
       "      <td>87</td>\n",
       "      <td>65.0</td>\n",
       "      <td>Oregon</td>\n",
       "      <td>Willamette Valley</td>\n",
       "      <td>Willamette Valley</td>\n",
       "      <td>Paul Gregutt</td>\n",
       "      <td>@paulgwine</td>\n",
       "      <td>Sweet Cheeks 2012 Vintner's Reserve Wild Child...</td>\n",
       "      <td>Pinot Noir</td>\n",
       "      <td>Sweet Cheeks</td>\n",
       "      <td>0.306667</td>\n",
       "      <td>0.448718</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    country                                        description  \\\n",
       "0     Italy  Aromas include tropical fruit, broom, brimston...   \n",
       "1  Portugal  This is ripe and fruity, a wine that is smooth...   \n",
       "2        US  Tart and snappy, the flavors of lime flesh and...   \n",
       "3        US  Pineapple rind, lemon pith and orange blossom ...   \n",
       "4        US  Much like the regular bottling from 2012, this...   \n",
       "\n",
       "                          designation  points  price           province  \\\n",
       "0                        Vulkà Bianco      87    NaN  Sicily & Sardinia   \n",
       "1                            Avidagos      87   15.0              Douro   \n",
       "2                                 NaN      87   14.0             Oregon   \n",
       "3                Reserve Late Harvest      87   13.0           Michigan   \n",
       "4  Vintner's Reserve Wild Child Block      87   65.0             Oregon   \n",
       "\n",
       "              region_1           region_2         taster_name  \\\n",
       "0                 Etna                NaN       Kerin O’Keefe   \n",
       "1                  NaN                NaN          Roger Voss   \n",
       "2    Willamette Valley  Willamette Valley        Paul Gregutt   \n",
       "3  Lake Michigan Shore                NaN  Alexander Peartree   \n",
       "4    Willamette Valley  Willamette Valley        Paul Gregutt   \n",
       "\n",
       "  taster_twitter_handle                                              title  \\\n",
       "0          @kerinokeefe                  Nicosia 2013 Vulkà Bianco  (Etna)   \n",
       "1            @vossroger      Quinta dos Avidagos 2011 Avidagos Red (Douro)   \n",
       "2           @paulgwine       Rainstorm 2013 Pinot Gris (Willamette Valley)   \n",
       "3                   NaN  St. Julian 2013 Reserve Late Harvest Riesling ...   \n",
       "4           @paulgwine   Sweet Cheeks 2012 Vintner's Reserve Wild Child...   \n",
       "\n",
       "          variety               winery  polarity_text  subjectivity_text  \n",
       "0     White Blend              Nicosia       0.133333           0.733333  \n",
       "1  Portuguese Red  Quinta dos Avidagos       0.220000           0.460000  \n",
       "2      Pinot Gris            Rainstorm       0.025000           0.358333  \n",
       "3        Riesling           St. Julian       0.166667           0.333333  \n",
       "4      Pinot Noir         Sweet Cheeks       0.306667           0.448718  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('data/winedata.csv', index_col='index')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "df['Stem word desc'] = df['description'].apply(lambda x: filtered_sequence(x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0         [aroma, includ, tropic, fruit, broom, brimston...\n",
       "1         [ripe, fruiti, wine, smooth, still, structur, ...\n",
       "2         [tart, snappi, flavor, lime, flesh, rind, domi...\n",
       "3         [pineappl, rind, lemon, pith, orang, blossom, ...\n",
       "4         [much, like, regular, bottl, 2012, come, acros...\n",
       "                                ...                        \n",
       "129966    [note, honeysuckl, cantaloup, sweeten, delici,...\n",
       "129967    [citat, given, much, decad, bottl, age, prior,...\n",
       "129968    [welldrain, gravel, soil, give, wine, crisp, d...\n",
       "129969    [dri, style, pinot, gri, crisp, acid, also, we...\n",
       "129970    [big, rich, offdri, power, intens, spici, roun...\n",
       "Name: Stem word desc, Length: 129971, dtype: object"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Stem word desc']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "#count apparitions of each word in the description\n",
    "count = {}\n",
    "for i in df['Stem word desc']:\n",
    "    for j in i:\n",
    "        if j in count:\n",
    "            count[j] += 1\n",
    "        else:\n",
    "            count[j] = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('wine', 82799),\n",
       " ('flavor', 70022),\n",
       " ('fruit', 58680),\n",
       " ('aroma', 41019),\n",
       " ('finish', 40428),\n",
       " ('acid', 39249),\n",
       " ('palat', 38282),\n",
       " ('tannin', 32813),\n",
       " ('drink', 32635),\n",
       " ('cherri', 31641),\n",
       " ('ripe', 28737),\n",
       " ('black', 25422),\n",
       " ('note', 25248),\n",
       " ('dri', 24429),\n",
       " ('spice', 23000),\n",
       " ('rich', 21833),\n",
       " ('fresh', 21402),\n",
       " ('red', 19110),\n",
       " ('show', 18541),\n",
       " ('berri', 17827),\n",
       " ('oak', 17146),\n",
       " ('nose', 16934),\n",
       " ('offer', 16128),\n",
       " ('plum', 15498),\n",
       " ('textur', 15468),\n",
       " ('blend', 14961),\n",
       " ('blackberri', 14923),\n",
       " ('sweet', 14856),\n",
       " ('appl', 14615),\n",
       " ('balanc', 14454),\n",
       " ('soft', 14120),\n",
       " ('crisp', 13611),\n",
       " ('age', 13219),\n",
       " ('structur', 12928),\n",
       " ('white', 12476),\n",
       " ('fruiti', 11921),\n",
       " ('light', 11811),\n",
       " ('dark', 11414),\n",
       " ('hint', 11382),\n",
       " ('citru', 11375),\n",
       " ('bright', 11337),\n",
       " ('give', 11117),\n",
       " ('raspberri', 10848),\n",
       " ('miner', 10836),\n",
       " ('herb', 10809),\n",
       " ('cabernet', 10699),\n",
       " ('vanilla', 10690),\n",
       " ('well', 10618),\n",
       " ('touch', 10556),\n",
       " ('full', 10216),\n",
       " ('juici', 10157),\n",
       " ('pepper', 10083),\n",
       " ('good', 9572),\n",
       " ('year', 9549),\n",
       " ('concentr', 9390),\n",
       " ('firm', 9386),\n",
       " ('peach', 9369),\n",
       " ('green', 9241),\n",
       " ('feel', 8973),\n",
       " ('lemon', 8903),\n",
       " ('pear', 8720),\n",
       " ('toast', 8529),\n",
       " ('charact', 8451),\n",
       " ('complex', 8383),\n",
       " ('chocol', 8243),\n",
       " ('open', 8107),\n",
       " ('come', 7823),\n",
       " ('currant', 7699),\n",
       " ('sauvignon', 7534),\n",
       " ('spici', 7487),\n",
       " ('smooth', 7463),\n",
       " ('vineyard', 7232),\n",
       " ('pinot', 7075),\n",
       " ('make', 7048),\n",
       " ('round', 6995),\n",
       " ('eleg', 6903),\n",
       " ('bottl', 6888),\n",
       " ('like', 6865),\n",
       " ('fine', 6797),\n",
       " ('intens', 6793),\n",
       " ('tast', 6712),\n",
       " ('lead', 6706),\n",
       " ('tart', 6615),\n",
       " ('made', 6570),\n",
       " ('tannic', 6338),\n",
       " ('also', 6266),\n",
       " ('herbal', 6208),\n",
       " ('wood', 6193),\n",
       " ('delici', 6088),\n",
       " ('mouth', 6062),\n",
       " ('creami', 6003),\n",
       " ('licoric', 5979),\n",
       " ('bodi', 5921),\n",
       " ('bit', 5885),\n",
       " ('dens', 5879),\n",
       " ('long', 5816),\n",
       " ('still', 5806),\n",
       " ('merlot', 5784),\n",
       " ('power', 5721),\n",
       " ('orang', 5718),\n",
       " ('layer', 5711),\n",
       " ('bake', 5702),\n",
       " ('style', 5682),\n",
       " ('clean', 5631),\n",
       " ('there', 5629),\n",
       " ('earthi', 5595),\n",
       " ('grape', 5531),\n",
       " ('alongsid', 5391),\n",
       " ('lime', 5389),\n",
       " ('syrah', 5372),\n",
       " ('along', 5364),\n",
       " ('savori', 5303),\n",
       " ('leather', 5259),\n",
       " ('fullbodi', 5236),\n",
       " ('flower', 5215),\n",
       " ('tight', 5161),\n",
       " ('tobacco', 5151),\n",
       " ('honey', 5110),\n",
       " ('slightli', 5074),\n",
       " ('great', 5046),\n",
       " ('readi', 4987),\n",
       " ('one', 4949),\n",
       " ('chardonnay', 4886),\n",
       " ('deliv', 4779),\n",
       " ('yet', 4755),\n",
       " ('mouthfeel', 4735),\n",
       " ('nice', 4714),\n",
       " ('gener', 4713),\n",
       " ('strawberri', 4702),\n",
       " ('vintag', 4692),\n",
       " ('color', 4618),\n",
       " ('smoki', 4534),\n",
       " ('accent', 4533),\n",
       " ('cassi', 4506),\n",
       " ('live', 4500),\n",
       " ('new', 4476),\n",
       " ('time', 4452),\n",
       " ('apricot', 4337),\n",
       " ('attract', 4328),\n",
       " ('young', 4301),\n",
       " ('melon', 4269),\n",
       " ('pineappl', 4240),\n",
       " ('edg', 4182),\n",
       " ('refresh', 4166),\n",
       " ('scent', 4151),\n",
       " ('cola', 4146),\n",
       " ('grapefruit', 4131),\n",
       " ('bitter', 4118),\n",
       " ('coffe', 4103),\n",
       " ('smoke', 4097),\n",
       " ('yellow', 4095),\n",
       " ('clove', 4064),\n",
       " ('linger', 4054),\n",
       " ('produc', 3999),\n",
       " ('wild', 3954),\n",
       " ('floral', 3936),\n",
       " ('big', 3907),\n",
       " ('suggest', 3905),\n",
       " ('need', 3902),\n",
       " ('barrel', 3891),\n",
       " ('almost', 3879),\n",
       " ('littl', 3865),\n",
       " ('simpl', 3809),\n",
       " ('bring', 3767),\n",
       " ('easi', 3765),\n",
       " ('solid', 3750),\n",
       " ('tropic', 3735),\n",
       " ('follow', 3731),\n",
       " ('earth', 3719),\n",
       " ('perfum', 3698),\n",
       " ('core', 3695),\n",
       " ('candi', 3661),\n",
       " ('that', 3657),\n",
       " ('best', 3657),\n",
       " ('aromat', 3629),\n",
       " ('mix', 3592),\n",
       " ('stone', 3573),\n",
       " ('enjoy', 3556),\n",
       " ('matur', 3555),\n",
       " ('add', 3513),\n",
       " ('cinnamon', 3479),\n",
       " ('tone', 3465),\n",
       " ('plenti', 3464),\n",
       " ('lightli', 3462),\n",
       " ('blueberri', 3461),\n",
       " ('alcohol', 3458),\n",
       " ('toasti', 3424),\n",
       " ('seem', 3417),\n",
       " ('weight', 3392),\n",
       " ('tangi', 3369),\n",
       " ('noir', 3364),\n",
       " ('end', 3352),\n",
       " ('cranberri', 3342),\n",
       " ('delic', 3327),\n",
       " ('domin', 3297),\n",
       " ('impress', 3284),\n",
       " ('beauti', 3256),\n",
       " ('close', 3242),\n",
       " ('crush', 3241),\n",
       " ('almond', 3241),\n",
       " ('quit', 3240),\n",
       " ('pretti', 3225),\n",
       " ('provid', 3207),\n",
       " ('pair', 3196),\n",
       " ('glass', 3192),\n",
       " ('petit', 3167),\n",
       " ('develop', 3155),\n",
       " ('zest', 3114),\n",
       " ('roast', 3073),\n",
       " ('back', 3069),\n",
       " ('blanc', 3066),\n",
       " ('2018', 3054),\n",
       " ('whiff', 3037),\n",
       " ('lot', 3022),\n",
       " ('franc', 3009),\n",
       " ('cedar', 3006),\n",
       " ('silki', 2956),\n",
       " ('zesti', 2953),\n",
       " ('caramel', 2937),\n",
       " ('strong', 2912),\n",
       " ('meat', 2906),\n",
       " ('much', 2893),\n",
       " ('medium', 2880),\n",
       " ('oaki', 2857),\n",
       " ('mocha', 2848),\n",
       " ('express', 2835),\n",
       " ('aftertast', 2833),\n",
       " ('jammi', 2806),\n",
       " ('violet', 2739),\n",
       " ('warm', 2736),\n",
       " ('way', 2717),\n",
       " ('rose', 2698),\n",
       " ('varieti', 2695),\n",
       " ('lush', 2675),\n",
       " ('lean', 2652),\n",
       " ('mediumbodi', 2632),\n",
       " ('carri', 2627),\n",
       " ('anis', 2616),\n",
       " ('enough', 2598),\n",
       " ('although', 2596),\n",
       " ('cut', 2586),\n",
       " ('bold', 2580),\n",
       " ('subtl', 2569),\n",
       " ('riesl', 2568),\n",
       " ('depth', 2562),\n",
       " ('dusti', 2555),\n",
       " ('high', 2552),\n",
       " ('deep', 2543),\n",
       " ('mint', 2540),\n",
       " ('vibrant', 2537),\n",
       " ('love', 2511),\n",
       " ('keep', 2497),\n",
       " ('peel', 2492),\n",
       " ('frame', 2484),\n",
       " ('pepperi', 2482),\n",
       " ('lift', 2476),\n",
       " ('malbec', 2463),\n",
       " ('thick', 2463),\n",
       " ('combin', 2455),\n",
       " ('pure', 2452),\n",
       " ('polish', 2450),\n",
       " ('2017', 2442),\n",
       " ('togeth', 2434),\n",
       " ('right', 2421),\n",
       " ('even', 2415),\n",
       " ('hard', 2398),\n",
       " ('exot', 2394),\n",
       " ('espresso', 2393),\n",
       " ('butter', 2384),\n",
       " ('support', 2382),\n",
       " ('tangerin', 2351),\n",
       " ('jam', 2330),\n",
       " ('pack', 2328),\n",
       " ('first', 2326),\n",
       " ('appeal', 2315),\n",
       " ('rather', 2308),\n",
       " ('estat', 2303),\n",
       " ('element', 2294),\n",
       " ('heavi', 2286),\n",
       " ('cellar', 2280),\n",
       " ('price', 2278),\n",
       " ('integr', 2265),\n",
       " ('qualiti', 2264),\n",
       " ('wineri', 2249),\n",
       " ('bouquet', 2220),\n",
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       " ('weighti', 462),\n",
       " ('2025', 462),\n",
       " ('tongu', 461),\n",
       " ('waft', 460),\n",
       " ('sleek', 458),\n",
       " ('primari', 458),\n",
       " ('see', 458),\n",
       " ('due', 458),\n",
       " ('probabl', 457),\n",
       " ('larg', 457),\n",
       " ('place', 456),\n",
       " ('scorch', 454),\n",
       " ('notion', 454),\n",
       " ('massiv', 452),\n",
       " ('heart', 452),\n",
       " ('surpris', 451),\n",
       " ('grand', 451),\n",
       " ('italian', 450),\n",
       " ('aggress', 450),\n",
       " ('santa', 450),\n",
       " ('pipe', 449),\n",
       " ('oil', 449),\n",
       " ('success', 449),\n",
       " ('scratchi', 447),\n",
       " ('waxi', 447),\n",
       " ('barolo', 446),\n",
       " ('12', 446),\n",
       " ('manag', 446),\n",
       " ('breath', 445),\n",
       " ('singl', 445),\n",
       " ('pastri', 444),\n",
       " ('chicken', 443),\n",
       " ('2023', 443),\n",
       " ('coolclim', 443),\n",
       " ('block', 442),\n",
       " ('world', 442),\n",
       " ('pork', 441),\n",
       " ('captur', 441),\n",
       " ('northern', 441),\n",
       " ('barbera', 441),\n",
       " ('pop', 440),\n",
       " ('found', 440),\n",
       " ('entri', 438),\n",
       " ('onto', 438),\n",
       " ('cardamom', 438),\n",
       " ('flint', 438),\n",
       " ('briari', 438),\n",
       " ('forc', 437),\n",
       " ('plummi', 437),\n",
       " ('crème', 437),\n",
       " ('kind', 436),\n",
       " ('danc', 436),\n",
       " ('fruitforward', 435),\n",
       " ('nacion', 434),\n",
       " ('lamb', 434),\n",
       " ('notic', 433),\n",
       " ('sunni', 432),\n",
       " ('muscular', 431),\n",
       " ('underrip', 431),\n",
       " ('box', 430),\n",
       " ('healthi', 430),\n",
       " ('luxuri', 430),\n",
       " ('punch', 429),\n",
       " ('watermelon', 429),\n",
       " ('brawni', 428),\n",
       " ...]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "count_sorted = sorted(count.items(), key=lambda x: x[1], reverse=True)\n",
    "\n",
    "count_sorted"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('wine', 82799),\n",
       " ('flavor', 70022),\n",
       " ('fruit', 58680),\n",
       " ('aroma', 41019),\n",
       " ('finish', 40428),\n",
       " ('acid', 39249),\n",
       " ('palat', 38282),\n",
       " ('tannin', 32813),\n",
       " ('drink', 32635),\n",
       " ('cherri', 31641),\n",
       " ('ripe', 28737),\n",
       " ('black', 25422),\n",
       " ('note', 25248),\n",
       " ('dri', 24429),\n",
       " ('spice', 23000),\n",
       " ('rich', 21833),\n",
       " ('fresh', 21402),\n",
       " ('red', 19110),\n",
       " ('show', 18541),\n",
       " ('berri', 17827)]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#keep only the most frequent words\n",
    "count_sorted = count_sorted[:20]\n",
    "count_sorted"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['wine',\n",
       " 'flavor',\n",
       " 'fruit',\n",
       " 'aroma',\n",
       " 'finish',\n",
       " 'acid',\n",
       " 'palat',\n",
       " 'tannin',\n",
       " 'drink',\n",
       " 'cherri',\n",
       " 'ripe',\n",
       " 'black',\n",
       " 'note',\n",
       " 'dri',\n",
       " 'spice',\n",
       " 'rich',\n",
       " 'fresh',\n",
       " 'red',\n",
       " 'show',\n",
       " 'berri']"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#create a list of the most frequent words\n",
    "most_frequent_words = [i[0] for i in count_sorted]\n",
    "most_frequent_words"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0                 [aroma, fruit, dri, palat, dri, acid]\n",
       "1         [ripe, wine, tannin, red, berri, fruit, acid]\n",
       "2                          [flavor, acid, flavor, wine]\n",
       "3                          [aroma, palat, note, finish]\n",
       "4                                                [wine]\n",
       "                              ...                      \n",
       "129966                              [note, palat, acid]\n",
       "129967                   [drink, cherri, flavor, fruit]\n",
       "129968            [wine, dri, ripe, spice, wine, drink]\n",
       "129969          [dri, acid, spice, flavor, wine, drink]\n",
       "129970                             [rich, fruit, drink]\n",
       "Name: Stem word desc, Length: 129971, dtype: object"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#keep only the most frequent words in the description\n",
    "df['Stem word desc'] = df['Stem word desc'].apply(lambda x: [i for i in x if i in most_frequent_words])\n",
    "\n",
    "df['Stem word desc']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>country</th>\n",
       "      <th>description</th>\n",
       "      <th>designation</th>\n",
       "      <th>points</th>\n",
       "      <th>price</th>\n",
       "      <th>province</th>\n",
       "      <th>region_1</th>\n",
       "      <th>region_2</th>\n",
       "      <th>taster_name</th>\n",
       "      <th>taster_twitter_handle</th>\n",
       "      <th>...</th>\n",
       "      <th>ripe</th>\n",
       "      <th>black</th>\n",
       "      <th>note</th>\n",
       "      <th>dri</th>\n",
       "      <th>spice</th>\n",
       "      <th>rich</th>\n",
       "      <th>fresh</th>\n",
       "      <th>red</th>\n",
       "      <th>show</th>\n",
       "      <th>berri</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Italy</td>\n",
       "      <td>Aromas include tropical fruit, broom, brimston...</td>\n",
       "      <td>Vulkà Bianco</td>\n",
       "      <td>87</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Sicily &amp; Sardinia</td>\n",
       "      <td>Etna</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Kerin O’Keefe</td>\n",
       "      <td>@kerinokeefe</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Portugal</td>\n",
       "      <td>This is ripe and fruity, a wine that is smooth...</td>\n",
       "      <td>Avidagos</td>\n",
       "      <td>87</td>\n",
       "      <td>15.0</td>\n",
       "      <td>Douro</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Roger Voss</td>\n",
       "      <td>@vossroger</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>US</td>\n",
       "      <td>Tart and snappy, the flavors of lime flesh and...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>87</td>\n",
       "      <td>14.0</td>\n",
       "      <td>Oregon</td>\n",
       "      <td>Willamette Valley</td>\n",
       "      <td>Willamette Valley</td>\n",
       "      <td>Paul Gregutt</td>\n",
       "      <td>@paulgwine</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>US</td>\n",
       "      <td>Pineapple rind, lemon pith and orange blossom ...</td>\n",
       "      <td>Reserve Late Harvest</td>\n",
       "      <td>87</td>\n",
       "      <td>13.0</td>\n",
       "      <td>Michigan</td>\n",
       "      <td>Lake Michigan Shore</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Alexander Peartree</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>US</td>\n",
       "      <td>Much like the regular bottling from 2012, this...</td>\n",
       "      <td>Vintner's Reserve Wild Child Block</td>\n",
       "      <td>87</td>\n",
       "      <td>65.0</td>\n",
       "      <td>Oregon</td>\n",
       "      <td>Willamette Valley</td>\n",
       "      <td>Willamette Valley</td>\n",
       "      <td>Paul Gregutt</td>\n",
       "      <td>@paulgwine</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 36 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    country                                        description  \\\n",
       "0     Italy  Aromas include tropical fruit, broom, brimston...   \n",
       "1  Portugal  This is ripe and fruity, a wine that is smooth...   \n",
       "2        US  Tart and snappy, the flavors of lime flesh and...   \n",
       "3        US  Pineapple rind, lemon pith and orange blossom ...   \n",
       "4        US  Much like the regular bottling from 2012, this...   \n",
       "\n",
       "                          designation  points  price           province  \\\n",
       "0                        Vulkà Bianco      87    NaN  Sicily & Sardinia   \n",
       "1                            Avidagos      87   15.0              Douro   \n",
       "2                                 NaN      87   14.0             Oregon   \n",
       "3                Reserve Late Harvest      87   13.0           Michigan   \n",
       "4  Vintner's Reserve Wild Child Block      87   65.0             Oregon   \n",
       "\n",
       "              region_1           region_2         taster_name  \\\n",
       "0                 Etna                NaN       Kerin O’Keefe   \n",
       "1                  NaN                NaN          Roger Voss   \n",
       "2    Willamette Valley  Willamette Valley        Paul Gregutt   \n",
       "3  Lake Michigan Shore                NaN  Alexander Peartree   \n",
       "4    Willamette Valley  Willamette Valley        Paul Gregutt   \n",
       "\n",
       "  taster_twitter_handle  ... ripe black note  dri  spice rich  fresh  red  \\\n",
       "0          @kerinokeefe  ...    0     0    0    1      0    0      0    0   \n",
       "1            @vossroger  ...    1     0    0    0      0    0      0    1   \n",
       "2           @paulgwine   ...    0     0    0    0      0    0      0    0   \n",
       "3                   NaN  ...    0     0    1    0      0    0      0    0   \n",
       "4           @paulgwine   ...    0     0    0    0      0    0      0    0   \n",
       "\n",
       "   show  berri  \n",
       "0     0      0  \n",
       "1     0      1  \n",
       "2     0      0  \n",
       "3     0      0  \n",
       "4     0      0  \n",
       "\n",
       "[5 rows x 36 columns]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#create dummy variables for each word\n",
    "for i in most_frequent_words:\n",
    "    df[i] = df['Stem word desc'].apply(lambda x: 1 if i in x else 0)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "new_df = df.copy()\n",
    "new_df = new_df.iloc[:,15:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "new_df.to_csv('data/stem.csv')"
   ]
  }
 ],
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