yelp_mine_reviews_bag_of_words.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Project Goal: \n",
    "Extract YELP reviews for top 100 businesses in San Francisco and use bag-of-words to find the top words used in total reviews for each business."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import requests\n",
    "from scrapy.selector import Selector\n",
    "from scrapy.http import HtmlResponse"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "HTML_list = []\n",
    "for i in np.arange(0,110,10):\n",
    "    url = 'https://www.yelp.com/search?find_loc=San+Francisco,+CA,+USA&start=%s&cflt=restaurants' %i\n",
    "    #print url\n",
    "    response = requests.get(url)\n",
    "    HTML_list.append(response.text)\n",
    "\n",
    "results_list = []\n",
    "for page in HTML_list:\n",
    "    results = Selector(text=page).xpath(\"//span[@class='indexed-biz-name']/a[@class='biz-name js-analytics-click']/span\")\n",
    "    results_list.append(results)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "name_list = []\n",
    "for result in results_list:\n",
    "        for name in result:\n",
    "            name_list.append(name.xpath(\"text()\").extract())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[u'Brenda\\u2019s French Soul Food']"
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "name_list[10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "name_list = pd.Series(name_list)\n",
    "name_list = name_list.apply(lambda x: x[0].encode('ascii', 'ignore').rstrip().lstrip().replace(' ','-').replace('.','').replace(\"\\u2019\",''))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0                              Ichido\n",
       "1                             Dakshin\n",
       "2                        b-Patisserie\n",
       "3                    Cuisine-of-Nepal\n",
       "4                              Bodega\n",
       "5                         Casa-Flores\n",
       "6                             Tacorea\n",
       "7                             Frances\n",
       "8                           Sugarfoot\n",
       "9               State-Bird-Provisions\n",
       "10           Brendas-French-Soul-Food\n",
       "11                               Nopa\n",
       "12                          Buzzworks\n",
       "13                         Kebab-King\n",
       "14                            Paprika\n",
       "15        Chicks-and-Love-Pizza-Patio\n",
       "16           Italian-Homemade-Company\n",
       "17                             Bodega\n",
       "18                        El-Farolito\n",
       "19                       Rove-Kitchen\n",
       "20                       No-No-Burger\n",
       "21                                Lol\n",
       "22                            Ro-Cafe\n",
       "23                            Pokihub\n",
       "24                         Kebab-King\n",
       "25                            Hogwash\n",
       "26                       The-Chairman\n",
       "27                         Chez-Maman\n",
       "28                          Nightbird\n",
       "29                            20-Spot\n",
       "                    ...              \n",
       "80             Junior-Barbecue-Burger\n",
       "81                          Lous-Cafe\n",
       "82                               Plow\n",
       "83     Farmhouse-Kitchen-Thai-Cuisine\n",
       "84                     Elephant-Sushi\n",
       "85                        Poke-Delish\n",
       "86                         DragonEats\n",
       "87                           Garajito\n",
       "88             Woodhouse-Fish-Company\n",
       "89           Old-Jerusalem-Restaurant\n",
       "90                         Sotto-Mare\n",
       "91             Dotties-True-Blue-Cafe\n",
       "92               Hog-Island-Oyster-Co\n",
       "93           Nobhill-Pizza-&-Shawerma\n",
       "94                            Beretta\n",
       "95             An-Japanese-Restaurant\n",
       "96                      The-Spice-Jar\n",
       "97                            Stuffed\n",
       "98                             Lavash\n",
       "99                    Limn-Rotisserie\n",
       "100                            Bouche\n",
       "101                          Prubechu\n",
       "102                       La-Taqueria\n",
       "103                       Cordon-Bleu\n",
       "104               Two-Sons-Sandwiches\n",
       "105                     Yemen-Kitchen\n",
       "106                  The-Monks-Kettle\n",
       "107                     Ben-Thai-Cafe\n",
       "108                    Universal-Cafe\n",
       "109                      farm-:-table\n",
       "dtype: object"
      ]
     },
     "execution_count": 106,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "name_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Please only run this frame once to avoid hitting the site too hard all at once\n",
    "def yelp_func(search_key):\n",
    "    import requests\n",
    "\n",
    "    # Search parameters -- for convenience \n",
    "\n",
    "    # Search and location get replaced in the next few lines\n",
    "\n",
    "    HTML_list = []\n",
    "\n",
    "    for i in [\"?start=%d\" %d for d in range(0,140,20)]:\n",
    "        url = search_key+\"%s\" %i\n",
    "        #print url\n",
    "        response = requests.get(url)\n",
    "        HTML_list.append(response.text)\n",
    "\n",
    "    reviews_list = []\n",
    "    from scrapy.selector import Selector\n",
    "    from scrapy.http import HtmlResponse\n",
    "\n",
    "    results_list = []\n",
    "    for page in HTML_list:\n",
    "    # This xpath query will find the number of total results\n",
    "        results = Selector(text=page).xpath(\"//div[@class='review-wrapper']/div[@class='review-content']/p\")\n",
    "        results_list.append(results)\n",
    "\n",
    "    for result in results_list:\n",
    "        for review in result:\n",
    "            reviews_list.append(review.xpath(\"text()\").extract())\n",
    "    #total_results = int(results[0].extract())\n",
    "    #total_results\n",
    "\n",
    "\n",
    "    southern_pacific = []\n",
    "    for i in reviews_list:\n",
    "        southern_pacific.append(i)\n",
    "\n",
    "    import re\n",
    "    from nltk.corpus import stopwords # Import the stop word list\n",
    "\n",
    "    def review_to_words( raw_review ):\n",
    "        # Function to convert a raw review to a string of words\n",
    "        # The input is a single string (a raw movie review), and \n",
    "        # the output is a single string (a preprocessed movie review)\n",
    "\n",
    "        letters_only = re.sub(\"[^a-zA-Z]\", \" \", raw_review) \n",
    "        #\n",
    "        # 3. Convert to lower case, split into individual words\n",
    "        words = letters_only.lower().split()                             \n",
    "        #\n",
    "        # 4. In Python, searching a set is much faster than searching\n",
    "        #   a list, so convert the stop words to a set\n",
    "\n",
    "        stops = set(stopwords.words(\"english\"))                  \n",
    "        # \n",
    "        # 5. Remove stop words\n",
    "        meaningful_words = [w for w in words if not w in stops]   \n",
    "        #\n",
    "        # 6. Join the words back into one string separated by space, \n",
    "        # and return the result.\n",
    "        return( \" \".join( meaningful_words ))  \n",
    "\n",
    "    clean_train_reviews = []\n",
    "    for i in southern_pacific:\n",
    "        clean_train_reviews.append(review_to_words(str(i)))\n",
    "\n",
    "    print \"Creating the bag of words...\\n\"\n",
    "    from sklearn.feature_extraction.text import CountVectorizer\n",
    "\n",
    "    # Initialize the \"CountVectorizer\" object, which is scikit-learn's\n",
    "    # bag of words tool.  \n",
    "    vectorizer = CountVectorizer(analyzer = \"word\",   \\\n",
    "                                 tokenizer = None,    \\\n",
    "                                 preprocessor = None, \\\n",
    "                                 stop_words = None,   \\\n",
    "                                 max_features = 5000) \n",
    "\n",
    "    # fit_transform() does two functions: First, it fits the model\n",
    "    # and learns the vocabulary; second, it transforms our training data\n",
    "    # into feature vectors. The input to fit_transform should be a list of \n",
    "    # strings.\n",
    "    train_data_features = vectorizer.fit_transform(clean_train_reviews)\n",
    "\n",
    "    # Numpy arrays are easy to work with, so convert the result to an \n",
    "    # array\n",
    "    train_data_features = train_data_features.toarray()\n",
    "\n",
    "    # Take a look at the words in the vocabulary\n",
    "    vocab = vectorizer.get_feature_names()\n",
    "\n",
    "\n",
    "    import numpy as np\n",
    "\n",
    "    # Sum up the counts of each vocabulary word\n",
    "    dist = np.sum(train_data_features, axis=0)\n",
    "\n",
    "    # For each, print the vocabulary word and the number of times it \n",
    "    # appears in the training set\n",
    "\n",
    "    count_list = []\n",
    "    word_list = []\n",
    "    for tag, count in zip(vocab, dist):\n",
    "        #print count, tag\n",
    "        count_list.append(count)\n",
    "        word_list.append(tag)\n",
    "\n",
    "    import pandas as pd\n",
    "    word_df = pd.DataFrame({'word': word_list,'count': count_list})\n",
    "    \n",
    "    return word_df\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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     ]
    }
   ],
   "source": [
    "cloud_list_dict = {}\n",
    "for i in name_list:\n",
    "    try:\n",
    "        cloud_list_dict[i] = yelp_func('https://www.yelp.com/biz/%s-san-francisco' %i)\n",
    "    except: \n",
    "        continue\n",
    "      "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>word</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>ability</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>abroad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>absolute</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>absolutely</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>accommodating</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1</td>\n",
       "      <td>accompany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1</td>\n",
       "      <td>according</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1</td>\n",
       "      <td>accordingly</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1</td>\n",
       "      <td>acidity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1</td>\n",
       "      <td>actual</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>1</td>\n",
       "      <td>address</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2</td>\n",
       "      <td>adds</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2</td>\n",
       "      <td>advance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2</td>\n",
       "      <td>adventure</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2</td>\n",
       "      <td>adventures</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>4</td>\n",
       "      <td>adventurous</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>1</td>\n",
       "      <td>affordable</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>1</td>\n",
       "      <td>afterward</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>1</td>\n",
       "      <td>agreed</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>1</td>\n",
       "      <td>alas</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>1</td>\n",
       "      <td>allowed</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>1</td>\n",
       "      <td>allows</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2</td>\n",
       "      <td>almond</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2</td>\n",
       "      <td>almost</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>4</td>\n",
       "      <td>already</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>12</td>\n",
       "      <td>also</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>1</td>\n",
       "      <td>alternative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>4</td>\n",
       "      <td>always</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>1</td>\n",
       "      <td>amazed</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>26</td>\n",
       "      <td>amazing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1258</th>\n",
       "      <td>8</td>\n",
       "      <td>wine</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1259</th>\n",
       "      <td>1</td>\n",
       "      <td>wines</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1260</th>\n",
       "      <td>3</td>\n",
       "      <td>wish</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1261</th>\n",
       "      <td>1</td>\n",
       "      <td>wished</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1262</th>\n",
       "      <td>3</td>\n",
       "      <td>without</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1263</th>\n",
       "      <td>8</td>\n",
       "      <td>wonderful</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1264</th>\n",
       "      <td>2</td>\n",
       "      <td>wonderfully</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1265</th>\n",
       "      <td>1</td>\n",
       "      <td>wood</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1266</th>\n",
       "      <td>1</td>\n",
       "      <td>word</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1267</th>\n",
       "      <td>7</td>\n",
       "      <td>work</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1268</th>\n",
       "      <td>2</td>\n",
       "      <td>working</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1269</th>\n",
       "      <td>6</td>\n",
       "      <td>world</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1270</th>\n",
       "      <td>2</td>\n",
       "      <td>worried</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1271</th>\n",
       "      <td>3</td>\n",
       "      <td>worth</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1272</th>\n",
       "      <td>8</td>\n",
       "      <td>would</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1273</th>\n",
       "      <td>2</td>\n",
       "      <td>wow</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1274</th>\n",
       "      <td>2</td>\n",
       "      <td>wrong</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1275</th>\n",
       "      <td>108</td>\n",
       "      <td>xa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1276</th>\n",
       "      <td>6</td>\n",
       "      <td>xe</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1277</th>\n",
       "      <td>2</td>\n",
       "      <td>xfbl</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1278</th>\n",
       "      <td>1</td>\n",
       "      <td>yang</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1279</th>\n",
       "      <td>1</td>\n",
       "      <td>year</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1280</th>\n",
       "      <td>1</td>\n",
       "      <td>years</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1281</th>\n",
       "      <td>1</td>\n",
       "      <td>yellowtail</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1282</th>\n",
       "      <td>1</td>\n",
       "      <td>yelp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1283</th>\n",
       "      <td>1</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1284</th>\n",
       "      <td>1</td>\n",
       "      <td>yet</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1285</th>\n",
       "      <td>1</td>\n",
       "      <td>yin</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1286</th>\n",
       "      <td>1</td>\n",
       "      <td>yolk</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1287</th>\n",
       "      <td>1</td>\n",
       "      <td>yum</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1288 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      count           word\n",
       "0         1        ability\n",
       "1         1         abroad\n",
       "2         1       absolute\n",
       "3         4     absolutely\n",
       "4         1  accommodating\n",
       "5         1      accompany\n",
       "6         1      according\n",
       "7         1    accordingly\n",
       "8         1        acidity\n",
       "9         1         actual\n",
       "10        1        address\n",
       "11        2           adds\n",
       "12        2        advance\n",
       "13        2      adventure\n",
       "14        2     adventures\n",
       "15        4    adventurous\n",
       "16        1     affordable\n",
       "17        1      afterward\n",
       "18        1         agreed\n",
       "19        1           alas\n",
       "20        1        allowed\n",
       "21        1         allows\n",
       "22        2         almond\n",
       "23        2         almost\n",
       "24        4        already\n",
       "25       12           also\n",
       "26        1    alternative\n",
       "27        4         always\n",
       "28        1         amazed\n",
       "29       26        amazing\n",
       "...     ...            ...\n",
       "1258      8           wine\n",
       "1259      1          wines\n",
       "1260      3           wish\n",
       "1261      1         wished\n",
       "1262      3        without\n",
       "1263      8      wonderful\n",
       "1264      2    wonderfully\n",
       "1265      1           wood\n",
       "1266      1           word\n",
       "1267      7           work\n",
       "1268      2        working\n",
       "1269      6          world\n",
       "1270      2        worried\n",
       "1271      3          worth\n",
       "1272      8          would\n",
       "1273      2            wow\n",
       "1274      2          wrong\n",
       "1275    108             xa\n",
       "1276      6             xe\n",
       "1277      2           xfbl\n",
       "1278      1           yang\n",
       "1279      1           year\n",
       "1280      1          years\n",
       "1281      1     yellowtail\n",
       "1282      1           yelp\n",
       "1283      1            yes\n",
       "1284      1            yet\n",
       "1285      1            yin\n",
       "1286      1           yolk\n",
       "1287      1            yum\n",
       "\n",
       "[1288 rows x 2 columns]"
      ]
     },
     "execution_count": 146,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cloud_list_dict['Ichido']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "https://www.yelp.com/biz/Ichido-san-francisco\n",
      "https://www.yelp.com/biz/Dakshin-san-francisco\n",
      "https://www.yelp.com/biz/b-Patisserie-san-francisco\n",
      "https://www.yelp.com/biz/Cuisine-of-Nepal-san-francisco\n",
      "https://www.yelp.com/biz/Bodega-san-francisco\n",
      "https://www.yelp.com/biz/Casa-Flores-san-francisco\n",
      "https://www.yelp.com/biz/Tacorea-san-francisco\n",
      "https://www.yelp.com/biz/Frances-san-francisco\n",
      "https://www.yelp.com/biz/Sugarfoot-san-francisco\n",
      "https://www.yelp.com/biz/State-Bird-Provisions-san-francisco\n",
      "https://www.yelp.com/biz/Brendas-French-Soul-Food-san-francisco\n",
      "https://www.yelp.com/biz/Nopa-san-francisco\n",
      "https://www.yelp.com/biz/Buzzworks-san-francisco\n",
      "https://www.yelp.com/biz/Kebab-King-san-francisco\n",
      "https://www.yelp.com/biz/Paprika-san-francisco\n",
      "https://www.yelp.com/biz/Chicks-and-Love-Pizza-Patio-san-francisco\n",
      "https://www.yelp.com/biz/Italian-Homemade-Company-san-francisco\n",
      "https://www.yelp.com/biz/Bodega-san-francisco\n",
      "https://www.yelp.com/biz/El-Farolito-san-francisco\n",
      "https://www.yelp.com/biz/Rove-Kitchen-san-francisco\n",
      "https://www.yelp.com/biz/No-No-Burger-san-francisco\n",
      "https://www.yelp.com/biz/Lol-san-francisco\n",
      "https://www.yelp.com/biz/Ro-Cafe-san-francisco\n",
      "https://www.yelp.com/biz/Pokihub-san-francisco\n",
      "https://www.yelp.com/biz/Kebab-King-san-francisco\n",
      "https://www.yelp.com/biz/Hogwash-san-francisco\n",
      "https://www.yelp.com/biz/The-Chairman-san-francisco\n",
      "https://www.yelp.com/biz/Chez-Maman-san-francisco\n",
      "https://www.yelp.com/biz/Nightbird-san-francisco\n",
      "https://www.yelp.com/biz/20-Spot-san-francisco\n",
      "https://www.yelp.com/biz/The-Italian-Homemade-Company-san-francisco\n",
      "https://www.yelp.com/biz/Suppenkche-san-francisco\n",
      "https://www.yelp.com/biz/Garaje-san-francisco\n",
      "https://www.yelp.com/biz/Chicks-and-Love-Pizza-Patio-san-francisco\n",
      "https://www.yelp.com/biz/Kokkari-Estiatorio-san-francisco\n",
      "https://www.yelp.com/biz/Dinosaurs-san-francisco\n",
      "https://www.yelp.com/biz/Zazie-san-francisco\n",
      "https://www.yelp.com/biz/Hoffmanns-Grill-&-Rotisserie-san-francisco\n",
      "https://www.yelp.com/biz/Cafe-de-Casa-san-francisco\n",
      "https://www.yelp.com/biz/Tasty-Pot-san-francisco\n",
      "https://www.yelp.com/biz/Dinosaurs-san-francisco\n",
      "https://www.yelp.com/biz/Hoffmanns-Grill-&-Rotisserie-san-francisco\n",
      "https://www.yelp.com/biz/Zazie-san-francisco\n",
      "https://www.yelp.com/biz/Kitchen-Istanbul-san-francisco\n",
      "https://www.yelp.com/biz/Box-Kitchen-san-francisco\n",
      "https://www.yelp.com/biz/Fat-Angel-san-francisco\n",
      "https://www.yelp.com/biz/Hopwater-Distribution-san-francisco\n",
      "https://www.yelp.com/biz/PianoFight-san-francisco\n",
      "https://www.yelp.com/biz/HRD-san-francisco\n",
      "https://www.yelp.com/biz/Nightbird-san-francisco\n",
      "https://www.yelp.com/biz/HRD-san-francisco\n",
      "https://www.yelp.com/biz/Kitchen-Istanbul-san-francisco\n",
      "https://www.yelp.com/biz/Dancing-Bull-san-francisco\n",
      "https://www.yelp.com/biz/La-Fusin-san-francisco\n",
      "https://www.yelp.com/biz/The-House-san-francisco\n",
      "https://www.yelp.com/biz/Scullery-san-francisco\n",
      "https://www.yelp.com/biz/PianoFight-san-francisco\n",
      "https://www.yelp.com/biz/Wooly-Pig-Cafe-san-francisco\n",
      "https://www.yelp.com/biz/Rooster-&-Rice-san-francisco\n",
      "https://www.yelp.com/biz/Stones-Throw-san-francisco\n",
      "https://www.yelp.com/biz/Birba-san-francisco\n",
      "https://www.yelp.com/biz/Street-Taco-san-francisco\n",
      "https://www.yelp.com/biz/Old-Skool-Cafe-san-francisco\n",
      "https://www.yelp.com/biz/The-Codmother-Fish-and-Chips-san-francisco\n",
      "https://www.yelp.com/biz/Bayshore-Taqueria-san-francisco\n",
      "https://www.yelp.com/biz/Bite-san-francisco\n",
      "https://www.yelp.com/biz/Leopolds-san-francisco\n",
      "https://www.yelp.com/biz/Sweet-Maple-san-francisco\n",
      "https://www.yelp.com/biz/Keeva-Indian-Kitchen-san-francisco\n",
      "https://www.yelp.com/biz/Lous-Cafe-san-francisco\n",
      "https://www.yelp.com/biz/Parada-22-san-francisco\n",
      "https://www.yelp.com/biz/Noeteca-Wine-Bar-san-francisco\n",
      "https://www.yelp.com/biz/FOB-Kitchen-san-francisco\n",
      "https://www.yelp.com/biz/Bayshore-Taqueria-san-francisco\n",
      "https://www.yelp.com/biz/Souvla-san-francisco\n",
      "https://www.yelp.com/biz/DragonEats-san-francisco\n",
      "https://www.yelp.com/biz/Keeva-Indian-Kitchen-san-francisco\n",
      "https://www.yelp.com/biz/Azucar-Lounge-san-francisco\n",
      "https://www.yelp.com/biz/Reems-san-francisco\n",
      "https://www.yelp.com/biz/Tselogs-SF-san-francisco\n",
      "https://www.yelp.com/biz/Junior-Barbecue-Burger-san-francisco\n",
      "https://www.yelp.com/biz/Lous-Cafe-san-francisco\n",
      "https://www.yelp.com/biz/Plow-san-francisco\n",
      "https://www.yelp.com/biz/Farmhouse-Kitchen-Thai-Cuisine-san-francisco\n",
      "https://www.yelp.com/biz/Elephant-Sushi-san-francisco\n",
      "https://www.yelp.com/biz/Poke-Delish-san-francisco\n",
      "https://www.yelp.com/biz/DragonEats-san-francisco\n",
      "https://www.yelp.com/biz/Garajito-san-francisco\n",
      "https://www.yelp.com/biz/Woodhouse-Fish-Company-san-francisco\n",
      "https://www.yelp.com/biz/Old-Jerusalem-Restaurant-san-francisco\n",
      "https://www.yelp.com/biz/Sotto-Mare-san-francisco\n",
      "https://www.yelp.com/biz/Dotties-True-Blue-Cafe-san-francisco\n",
      "https://www.yelp.com/biz/Hog-Island-Oyster-Co-san-francisco\n",
      "https://www.yelp.com/biz/Nobhill-Pizza-&-Shawerma-san-francisco\n",
      "https://www.yelp.com/biz/Beretta-san-francisco\n",
      "https://www.yelp.com/biz/An-Japanese-Restaurant-san-francisco\n",
      "https://www.yelp.com/biz/The-Spice-Jar-san-francisco\n",
      "https://www.yelp.com/biz/Stuffed-san-francisco\n",
      "https://www.yelp.com/biz/Lavash-san-francisco\n",
      "https://www.yelp.com/biz/Limn-Rotisserie-san-francisco\n",
      "https://www.yelp.com/biz/Bouche-san-francisco\n",
      "https://www.yelp.com/biz/Prubechu-san-francisco\n",
      "https://www.yelp.com/biz/La-Taqueria-san-francisco\n",
      "https://www.yelp.com/biz/Cordon-Bleu-san-francisco\n",
      "https://www.yelp.com/biz/Two-Sons-Sandwiches-san-francisco\n",
      "https://www.yelp.com/biz/Yemen-Kitchen-san-francisco\n",
      "https://www.yelp.com/biz/The-Monks-Kettle-san-francisco\n",
      "https://www.yelp.com/biz/Ben-Thai-Cafe-san-francisco\n",
      "https://www.yelp.com/biz/Universal-Cafe-san-francisco\n",
      "https://www.yelp.com/biz/farm-:-table-san-francisco\n"
     ]
    }
   ],
   "source": [
    "for i in name_list:\n",
    "    print 'https://www.yelp.com/biz/%s-san-francisco' %i"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "new_cloud = cloud_list_dict"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>word</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>ability</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>abroad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>absolute</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>absolutely</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>accommodating</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1</td>\n",
       "      <td>accompany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1</td>\n",
       "      <td>according</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1</td>\n",
       "      <td>accordingly</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1</td>\n",
       "      <td>acidity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1</td>\n",
       "      <td>actual</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>1</td>\n",
       "      <td>address</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2</td>\n",
       "      <td>adds</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2</td>\n",
       "      <td>advance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2</td>\n",
       "      <td>adventure</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2</td>\n",
       "      <td>adventures</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>4</td>\n",
       "      <td>adventurous</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>1</td>\n",
       "      <td>affordable</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>1</td>\n",
       "      <td>afterward</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>1</td>\n",
       "      <td>agreed</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>1</td>\n",
       "      <td>alas</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>1</td>\n",
       "      <td>allowed</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>1</td>\n",
       "      <td>allows</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2</td>\n",
       "      <td>almond</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2</td>\n",
       "      <td>almost</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>4</td>\n",
       "      <td>already</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>12</td>\n",
       "      <td>also</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>1</td>\n",
       "      <td>alternative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>4</td>\n",
       "      <td>always</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>1</td>\n",
       "      <td>amazed</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>26</td>\n",
       "      <td>amazing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1258</th>\n",
       "      <td>8</td>\n",
       "      <td>wine</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1259</th>\n",
       "      <td>1</td>\n",
       "      <td>wines</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1260</th>\n",
       "      <td>3</td>\n",
       "      <td>wish</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1261</th>\n",
       "      <td>1</td>\n",
       "      <td>wished</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1262</th>\n",
       "      <td>3</td>\n",
       "      <td>without</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1263</th>\n",
       "      <td>8</td>\n",
       "      <td>wonderful</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1264</th>\n",
       "      <td>2</td>\n",
       "      <td>wonderfully</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1265</th>\n",
       "      <td>1</td>\n",
       "      <td>wood</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1266</th>\n",
       "      <td>1</td>\n",
       "      <td>word</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1267</th>\n",
       "      <td>7</td>\n",
       "      <td>work</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1268</th>\n",
       "      <td>2</td>\n",
       "      <td>working</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1269</th>\n",
       "      <td>6</td>\n",
       "      <td>world</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1270</th>\n",
       "      <td>2</td>\n",
       "      <td>worried</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1271</th>\n",
       "      <td>3</td>\n",
       "      <td>worth</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1272</th>\n",
       "      <td>8</td>\n",
       "      <td>would</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1273</th>\n",
       "      <td>2</td>\n",
       "      <td>wow</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1274</th>\n",
       "      <td>2</td>\n",
       "      <td>wrong</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1275</th>\n",
       "      <td>108</td>\n",
       "      <td>xa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1276</th>\n",
       "      <td>6</td>\n",
       "      <td>xe</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1277</th>\n",
       "      <td>2</td>\n",
       "      <td>xfbl</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1278</th>\n",
       "      <td>1</td>\n",
       "      <td>yang</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1279</th>\n",
       "      <td>1</td>\n",
       "      <td>year</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1280</th>\n",
       "      <td>1</td>\n",
       "      <td>years</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1281</th>\n",
       "      <td>1</td>\n",
       "      <td>yellowtail</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1282</th>\n",
       "      <td>1</td>\n",
       "      <td>yelp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1283</th>\n",
       "      <td>1</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1284</th>\n",
       "      <td>1</td>\n",
       "      <td>yet</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1285</th>\n",
       "      <td>1</td>\n",
       "      <td>yin</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1286</th>\n",
       "      <td>1</td>\n",
       "      <td>yolk</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1287</th>\n",
       "      <td>1</td>\n",
       "      <td>yum</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1288 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      count           word\n",
       "0         1        ability\n",
       "1         1         abroad\n",
       "2         1       absolute\n",
       "3         4     absolutely\n",
       "4         1  accommodating\n",
       "5         1      accompany\n",
       "6         1      according\n",
       "7         1    accordingly\n",
       "8         1        acidity\n",
       "9         1         actual\n",
       "10        1        address\n",
       "11        2           adds\n",
       "12        2        advance\n",
       "13        2      adventure\n",
       "14        2     adventures\n",
       "15        4    adventurous\n",
       "16        1     affordable\n",
       "17        1      afterward\n",
       "18        1         agreed\n",
       "19        1           alas\n",
       "20        1        allowed\n",
       "21        1         allows\n",
       "22        2         almond\n",
       "23        2         almost\n",
       "24        4        already\n",
       "25       12           also\n",
       "26        1    alternative\n",
       "27        4         always\n",
       "28        1         amazed\n",
       "29       26        amazing\n",
       "...     ...            ...\n",
       "1258      8           wine\n",
       "1259      1          wines\n",
       "1260      3           wish\n",
       "1261      1         wished\n",
       "1262      3        without\n",
       "1263      8      wonderful\n",
       "1264      2    wonderfully\n",
       "1265      1           wood\n",
       "1266      1           word\n",
       "1267      7           work\n",
       "1268      2        working\n",
       "1269      6          world\n",
       "1270      2        worried\n",
       "1271      3          worth\n",
       "1272      8          would\n",
       "1273      2            wow\n",
       "1274      2          wrong\n",
       "1275    108             xa\n",
       "1276      6             xe\n",
       "1277      2           xfbl\n",
       "1278      1           yang\n",
       "1279      1           year\n",
       "1280      1          years\n",
       "1281      1     yellowtail\n",
       "1282      1           yelp\n",
       "1283      1            yes\n",
       "1284      1            yet\n",
       "1285      1            yin\n",
       "1286      1           yolk\n",
       "1287      1            yum\n",
       "\n",
       "[1288 rows x 2 columns]"
      ]
     },
     "execution_count": 149,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_cloud['Ichido']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 181,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# extract 20 top words\n",
    "short_cloud = {}\n",
    "for i in new_cloud:\n",
    "    try:\n",
    "        new_cloud[i] = new_cloud[i].set_index('word').drop('xa').reset_index().sort_values('count', ascending = False)   \n",
    "        short_cloud = new_cloud[i][0:20]\n",
    "    except:\n",
    "        new_cloud[i] = new_cloud[i].sort_values('count', ascending = False)\n",
    "        short_cloud[i] = new_cloud[i][0:20]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 183,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['20-Spot',\n",
       " 'Parada-22',\n",
       " 'Stuffed',\n",
       " 'Nopa',\n",
       " 'Two-Sons-Sandwiches',\n",
       " 'Reems',\n",
       " 'An-Japanese-Restaurant',\n",
       " 'State-Bird-Provisions',\n",
       " 'Buzzworks',\n",
       " 'Bodega',\n",
       " 'Garaje',\n",
       " 'Sugarfoot',\n",
       " 'Souvla',\n",
       " 'HRD',\n",
       " 'Prubechu',\n",
       " 'Kitchen-Istanbul',\n",
       " 'Birba',\n",
       " 'Cafe-de-Casa',\n",
       " 'Garajito',\n",
       " 'Bite',\n",
       " 'Brendas-French-Soul-Food',\n",
       " 'Azucar-Lounge',\n",
       " 'Wooly-Pig-Cafe',\n",
       " 'Kokkari-Estiatorio',\n",
       " 'Universal-Cafe',\n",
       " 'Hopwater-Distribution',\n",
       " 'Bouche',\n",
       " 'Hogwash',\n",
       " 'Italian-Homemade-Company',\n",
       " 'The-Codmother-Fish-and-Chips',\n",
       " 'Cuisine-of-Nepal',\n",
       " 'The-House',\n",
       " 'DragonEats',\n",
       " 'El-Farolito',\n",
       " 'Zazie',\n",
       " 'Farmhouse-Kitchen-Thai-Cuisine',\n",
       " 'Tacorea',\n",
       " 'Plow',\n",
       " 'Lol',\n",
       " 'Elephant-Sushi',\n",
       " 'Bayshore-Taqueria',\n",
       " 'Rove-Kitchen',\n",
       " 'Dotties-True-Blue-Cafe',\n",
       " 'Sotto-Mare',\n",
       " 'Dancing-Bull',\n",
       " 'Stones-Throw',\n",
       " 'Junior-Barbecue-Burger',\n",
       " 'The-Spice-Jar',\n",
       " 'The-Chairman',\n",
       " 'Chicks-and-Love-Pizza-Patio',\n",
       " 'Nightbird',\n",
       " 'Tasty-Pot',\n",
       " 'Paprika',\n",
       " 'No-No-Burger',\n",
       " 'Fat-Angel',\n",
       " 'Kebab-King',\n",
       " 'Lavash',\n",
       " 'Old-Jerusalem-Restaurant',\n",
       " 'Casa-Flores',\n",
       " 'Box-Kitchen',\n",
       " 'Sweet-Maple',\n",
       " 'b-Patisserie',\n",
       " 'Beretta',\n",
       " 'Dakshin',\n",
       " 'Leopolds',\n",
       " 'Chez-Maman',\n",
       " 'Woodhouse-Fish-Company',\n",
       " 'The-Monks-Kettle',\n",
       " 'Scullery',\n",
       " 'Ben-Thai-Cafe',\n",
       " 'PianoFight',\n",
       " 'Cordon-Bleu',\n",
       " 'Hog-Island-Oyster-Co',\n",
       " 'Frances',\n",
       " 'Dinosaurs',\n",
       " 'Ro-Cafe',\n",
       " 'Yemen-Kitchen',\n",
       " 'The-Italian-Homemade-Company',\n",
       " 'Poke-Delish',\n",
       " 'Tselogs-SF',\n",
       " 'Old-Skool-Cafe',\n",
       " 'Keeva-Indian-Kitchen',\n",
       " 'Street-Taco',\n",
       " 'Pokihub',\n",
       " 'FOB-Kitchen',\n",
       " 'Ichido',\n",
       " 'Lous-Cafe',\n",
       " 'La-Taqueria']"
      ]
     },
     "execution_count": 183,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "short_cloud.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 211,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# create initial df\n",
    "final_cloud_df = pd.DataFrame({'Ichido' : short_cloud['Ichido']['word'],'Ichido_count' : short_cloud['Ichido']['count']})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 212,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(20, 2)"
      ]
     },
     "execution_count": 212,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "final_cloud_df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 213,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "20-Spot [u'wine' u'place' u'spot' u'great' u'food'] 2124    186\n",
      "1376    103\n",
      "1806     99\n",
      "816      94\n",
      "732      80\n",
      "Name: count, dtype: int64\n",
      "Parada-22 [u'food' u'puerto' u'good' u'place' u'rican'] 740     326\n",
      "1508    186\n",
      "825     176\n",
      "1424    165\n",
      "1613    149\n",
      "Name: count, dtype: int64\n",
      "Stuffed [u'pierogi' u'food' u'place' u'pierogis' u'good'] 1279    121\n",
      "658     109\n",
      "1290    107\n",
      "1282     75\n",
      "734      75\n",
      "Name: count, dtype: int64\n",
      "Nopa [u'pork' u'good' u'food' u'nopa' u'chop'] 2054    137\n",
      "1193    135\n",
      "1091    129\n",
      "1793    124\n",
      "502      93\n",
      "Name: count, dtype: int64\n",
      "Two-Sons-Sandwiches [u'sandwich' u'sandwiches' u'great' u'place' u'good'] 1077    128\n",
      "1078    113\n",
      "535      77\n",
      "933      67\n",
      "527      47\n",
      "Name: count, dtype: int64\n",
      "Reems [u'reem' u'food' u'man' u'bread' u'market'] 545    32\n",
      "255    28\n",
      "391    19\n",
      "81     19\n",
      "401    18\n",
      "Name: count, dtype: int64\n",
      "An-Japanese-Restaurant [u'sushi' u'omakase' u'nigiri' u'fish' u'chef'] 1443    109\n",
      "981      86\n",
      "950      62\n",
      "515      44\n",
      "219      44\n",
      "Name: count, dtype: int64\n",
      "State-Bird-Provisions [u'food' u'like' u'dish' u'dishes' u'good'] 1247    275\n",
      "1809    259\n",
      "918     250\n",
      "919     237\n",
      "1381    229\n",
      "Name: count, dtype: int64\n",
      "Buzzworks [u'beer' u'place' u'bar' u'great' u'selection'] 64     51\n",
      "680    42\n",
      "54     31\n",
      "393    28\n",
      "786    27\n",
      "Name: count, dtype: int64\n",
      "Bodega [u'love' u'really' u'cigarettes' u'could' u'described'] 15    2\n",
      "18    2\n",
      "1     1\n",
      "2     1\n",
      "3     1\n",
      "Name: count, dtype: int64\n",
      "Garaje [u'food' u'place' u'good' u'taco' u'beer'] 841     272\n",
      "1575    262\n",
      "928     247\n",
      "2080    170\n",
      "187     159\n",
      "Name: count, dtype: int64\n",
      "Sugarfoot [u'grits' u'sugarfoot' u'bacon' u'food' u'best'] 297    102\n",
      "612     26\n",
      "39      25\n",
      "252     19\n",
      "52      15\n",
      "Name: count, dtype: int64\n",
      "Souvla [u'greek' u'salad' u'yogurt' u'lamb' u'sandwich'] 842     192\n",
      "1596    164\n",
      "2206    163\n",
      "1043    114\n",
      "1609    109\n",
      "Name: count, dtype: int64\n",
      "HRD [u'burrito' u'food' u'good' u'place' u'spicy'] 268     227\n",
      "778     142\n",
      "853     115\n",
      "1452    112\n",
      "1821    107\n",
      "Name: count, dtype: int64\n",
      "Prubechu [u'food' u'menu' u'tasting' u'dish' u'coconut'] 1008    197\n",
      "1577    153\n",
      "2530    135\n",
      "713      93\n",
      "460      90\n",
      "Name: count, dtype: int64\n",
      "Kitchen-Istanbul [u'food' u'good' u'service' u'place' u'turkish'] 667     131\n",
      "738     100\n",
      "1503     83\n",
      "1274     70\n",
      "1787     67\n",
      "Name: count, dtype: int64\n",
      "Birba [u'wine' u'great' u'food' u'place' u'bar'] 897    55\n",
      "345    34\n",
      "298    30\n",
      "573    20\n",
      "56     20\n",
      "Name: count, dtype: int64\n",
      "Cafe-de-Casa [u'coffee' u'brazilian' u'place' u'food' u'acai'] 219    77\n",
      "137    67\n",
      "884    62\n",
      "469    60\n",
      "5      56\n",
      "Name: count, dtype: int64\n",
      "Garajito [u'place' u'like' u'garaje' u'pop' u'pork'] 364    9\n",
      "267    9\n",
      "201    8\n",
      "372    7\n",
      "374    7\n",
      "Name: count, dtype: int64\n",
      "Bite [u'sandwich' u'good' u'sandwiches' u'place' u'bite'] 1246    196\n",
      "626     119\n",
      "1247     98\n",
      "1078     83\n",
      "130      83\n",
      "Name: count, dtype: int64\n",
      "Brendas-French-Soul-Food [u'grits' u'food' u'good' u'beignets' u'crawfish'] 942    172\n",
      "818    164\n",
      "916    143\n",
      "177    137\n",
      "470    133\n",
      "Name: count, dtype: int64\n",
      "Azucar-Lounge [u'tacos' u'food' u'place' u'good' u'great'] 2211    143\n",
      "859     104\n",
      "1617    102\n",
      "949      94\n",
      "960      88\n",
      "Name: count, dtype: int64\n",
      "Wooly-Pig-Cafe [u'sandwich' u'pig' u'wooly' u'pork' u'sandwiches'] 1468    198\n",
      "1284    138\n",
      "1961    137\n",
      "1310    107\n",
      "1470     92\n",
      "Name: count, dtype: int64\n",
      "Kokkari-Estiatorio [u'lamb' u'food' u'good' u'kokkari' u'grilled'] 1432    177\n",
      "1036    142\n",
      "1155    141\n",
      "1419    110\n",
      "1188    106\n",
      "Name: count, dtype: int64\n",
      "Universal-Cafe [u'brunch' u'wait' u'toast' u'good' u'place'] 255     147\n",
      "2215     94\n",
      "2081     90\n",
      "863      82\n",
      "1482     80\n",
      "Name: count, dtype: int64\n",
      "Hopwater-Distribution [u'beer' u'food' u'good' u'great' u'place'] 153     182\n",
      "711     154\n",
      "796     115\n",
      "811     109\n",
      "1324    107\n",
      "Name: count, dtype: int64\n",
      "Bouche [u'food' u'place' u'good' u'french' u'great'] 878     223\n",
      "1647    180\n",
      "975     158\n",
      "910     158\n",
      "986     150\n",
      "Name: count, dtype: int64\n",
      "Hogwash [u'beer' u'sausage' u'great' u'good' u'food'] 122     136\n",
      "1507    130\n",
      "760     108\n",
      "748     105\n",
      "656      98\n",
      "Name: count, dtype: int64\n",
      "Italian-Homemade-Company [u'pasta' u'sauce' u'place' u'food' u'italian'] 1185    166\n",
      "1434    147\n",
      "1238    113\n",
      "629     112\n",
      "852     110\n",
      "Name: count, dtype: int64\n",
      "The-Codmother-Fish-and-Chips [u'fish' u'chips' u'food' u'fries' u'good'] 618    383\n",
      "284    207\n",
      "643    123\n",
      "668    117\n",
      "713     92\n",
      "Name: count, dtype: int64\n",
      "Cuisine-of-Nepal [u'food' u'curry' u'us' u'chicken' u'delicious'] 557     138\n",
      "328      74\n",
      "1581     71\n",
      "228      71\n",
      "352      65\n",
      "Name: count, dtype: int64\n",
      "The-House [u'noodles' u'good' u'food' u'sauce' u'place'] 1473    193\n",
      "976     173\n",
      "891     172\n",
      "1914    161\n",
      "1646    132\n",
      "Name: count, dtype: int64\n",
      "DragonEats [u'mi' u'fresh' u'banh' u'good' u'food'] 824    103\n",
      "492     97\n",
      "89      78\n",
      "544     73\n",
      "481     68\n",
      "Name: count, dtype: int64\n",
      "El-Farolito [u'burrito' u'super' u'food' u'place' u'good'] 209     180\n",
      "1752    120\n",
      "689      99\n",
      "1319     92\n",
      "763      89\n",
      "Name: count, dtype: int64\n",
      "Zazie [u'brunch' u'wait' u'zazie' u'eggs' u'food'] 298     162\n",
      "2492    144\n",
      "2617    132\n",
      "702     125\n",
      "882     121\n",
      "Name: count, dtype: int64\n",
      "Farmhouse-Kitchen-Thai-Cuisine [u'thai' u'chicken' u'food' u'rice' u'curry'] 2448    234\n",
      "381     205\n",
      "923     164\n",
      "1995    155\n",
      "559     144\n",
      "Name: count, dtype: int64\n",
      "Tacorea [u'burrito' u'place' u'food' u'spicy' u'korean'] 249     500\n",
      "1625    240\n",
      "830     234\n",
      "2050    211\n",
      "1197    195\n",
      "Name: count, dtype: int64\n",
      "Plow [u'plow' u'wait' u'pancakes' u'potatoes' u'lemon'] 1540    232\n",
      "2255    201\n",
      "1459    170\n",
      "1567    159\n",
      "1146    136\n",
      "Name: count, dtype: int64\n",
      "Lol [u'food' u'good' u'place' u'taco' u'tacos'] 868     139\n",
      "954     111\n",
      "1635    102\n",
      "2162     91\n",
      "2166     83\n",
      "Name: count, dtype: int64\n",
      "Elephant-Sushi [u'sushi' u'roll' u'wait' u'place' u'good'] 1972    392\n",
      "1662    203\n",
      "2171    193\n",
      "1464    185\n",
      "837     150\n",
      "Name: count, dtype: int64\n",
      "Bayshore-Taqueria [u'food' u'burrito' u'good' u'place' u'great'] 549     106\n",
      "176      81\n",
      "614      75\n",
      "1049     75\n",
      "628      68\n",
      "Name: count, dtype: int64\n",
      "Rove-Kitchen [u'burger' u'chicken' u'sandwich' u'fried' u'food'] 279     223\n",
      "352     214\n",
      "1840    157\n",
      "869     141\n",
      "840     102\n",
      "Name: count, dtype: int64\n",
      "Dotties-True-Blue-Cafe [u'food' u'wait' u'line' u'good' u'got'] 866     150\n",
      "2425    142\n",
      "1248    138\n",
      "951     128\n",
      "960     106\n",
      "Name: count, dtype: int64\n",
      "Sotto-Mare [u'seafood' u'cioppino' u'place' u'good' u'food'] 1556    162\n",
      "326     160\n",
      "1326     96\n",
      "795      95\n",
      "718      75\n",
      "Name: count, dtype: int64\n",
      "Dancing-Bull [u'meat' u'bulgogi' u'place' u'beef' u'service'] 740     106\n",
      "156      66\n",
      "919      62\n",
      "110      57\n",
      "1107     54\n",
      "Name: count, dtype: int64\n",
      "Stones-Throw [u'food' u'good' u'great' u'potato' u'pasta'] 1064    132\n",
      "1170    127\n",
      "1191    111\n",
      "2000    109\n",
      "1883    103\n",
      "Name: count, dtype: int64\n",
      "Junior-Barbecue-Burger [u'burger' u'junior' u'burgers' u'back' u'get'] 90     120\n",
      "417     56\n",
      "91      45\n",
      "34      31\n",
      "315     29\n",
      "Name: count, dtype: int64\n",
      "The-Spice-Jar [u'good' u'ramen' u'food' u'place' u'asian'] 860     113\n",
      "1582    111\n",
      "773     107\n",
      "1476    104\n",
      "108      67\n",
      "Name: count, dtype: int64\n",
      "The-Chairman [u'pork' u'belly' u'steamed' u'buns' u'bun'] 1345    265\n",
      "155     175\n",
      "1716    161\n",
      "222     149\n",
      "220     138\n",
      "Name: count, dtype: int64\n",
      "Chicks-and-Love-Pizza-Patio [u'pizza' u'chicks' u'love' u'fresh' u'market'] 693    102\n",
      "147     60\n",
      "546     55\n",
      "375     44\n",
      "563     39\n",
      "Name: count, dtype: int64\n",
      "Nightbird [u'menu' u'course' u'corn' u'food' u'restaurant'] 701    33\n",
      "261    29\n",
      "255    25\n",
      "461    23\n",
      "934    22\n",
      "Name: count, dtype: int64\n",
      "Tasty-Pot [u'pot' u'soup' u'hot' u'good' u'tasty'] 867     141\n",
      "1089     79\n",
      "550      67\n",
      "496      64\n",
      "1161     61\n",
      "Name: count, dtype: int64\n",
      "Paprika [u'food' u'goulash' u'good' u'paprika' u'great'] 629     129\n",
      "709     121\n",
      "703     100\n",
      "1177     97\n",
      "725      85\n",
      "Name: count, dtype: int64\n",
      "No-No-Burger [u'burger' u'vegan' u'burgers' u'good' u'fries'] 218     320\n",
      "1880    132\n",
      "220      95\n",
      "735      83\n",
      "688      74\n",
      "Name: count, dtype: int64\n",
      "Fat-Angel [u'place' u'cheese' u'food' u'beer' u'good'] 1524    126\n",
      "350     106\n",
      "792     101\n",
      "170      96\n",
      "876      93\n",
      "Name: count, dtype: int64\n",
      "Kebab-King [u'food' u'great' u'chicken' u'naan' u'service'] 459     143\n",
      "516      84\n",
      "184      84\n",
      "765      83\n",
      "1048     56\n",
      "Name: count, dtype: int64\n",
      "Lavash [u'food' u'lavash' u'place' u'persian' u'good'] 746     332\n",
      "1108    204\n",
      "1454    184\n",
      "1432    170\n",
      "835     169\n",
      "Name: count, dtype: int64\n",
      "Old-Jerusalem-Restaurant [u'food' u'hummus' u'good' u'place' u'chicken'] 582     148\n",
      "777     133\n",
      "667     102\n",
      "1220     73\n",
      "235      64\n",
      "Name: count, dtype: int64\n",
      "Casa-Flores [u'vanessa' u'food' u'dinner' u'julian' u'great'] 734    74\n",
      "257    40\n",
      "168    36\n",
      "368    32\n",
      "298    26\n",
      "Name: count, dtype: int64\n",
      "Box-Kitchen [u'food' u'burger' u'box' u'good' u'place'] 646     169\n",
      "201     149\n",
      "173     148\n",
      "727     107\n",
      "1274    105\n",
      "Name: count, dtype: int64\n",
      "Sweet-Maple [u'bacon' u'sweet' u'wait' u'good' u'toast'] 138     304\n",
      "2139    162\n",
      "2365    145\n",
      "940     114\n",
      "2237    112\n",
      "Name: count, dtype: int64\n",
      "b-Patisserie [u'macaroons' u'line' u'belinda' u'flavors' u'flavor'] 149    13\n",
      "142     8\n",
      "22      8\n",
      "97      6\n",
      "96      6\n",
      "Name: count, dtype: int64\n",
      "Beretta [u'pizza' u'good' u'food' u'great' u'place'] 1735    174\n",
      "1012    120\n",
      "919     108\n",
      "1028    101\n",
      "1739     92\n",
      "Name: count, dtype: int64\n",
      "Dakshin [u'food' u'indian' u'dosa' u'good' u'great'] 233    43\n",
      "300    36\n",
      "171    34\n",
      "266    25\n",
      "271    22\n",
      "Name: count, dtype: int64\n",
      "Leopolds [u'food' u'great' u'beer' u'place' u'good'] 768     209\n",
      "871     155\n",
      "162     154\n",
      "1432    133\n",
      "860     133\n",
      "Name: count, dtype: int64\n",
      "Chez-Maman [u'french' u'burger' u'good' u'food' u'place'] 776     134\n",
      "262     120\n",
      "841      97\n",
      "755      86\n",
      "1489     81\n",
      "Name: count, dtype: int64\n",
      "Woodhouse-Fish-Company [u'lobster' u'roll' u'crab' u'good' u'fish'] 1038    425\n",
      "1482    371\n",
      "424     259\n",
      "796     233\n",
      "699     185\n",
      "Name: count, dtype: int64\n",
      "The-Monks-Kettle [u'beer' u'food' u'good' u'place' u'great'] 186     214\n",
      "842     129\n",
      "933     111\n",
      "1565    108\n",
      "949      99\n",
      "Name: count, dtype: int64\n",
      "Scullery [u'coffee' u'toast' u'great' u'place' u'avocado'] 129    55\n",
      "706    38\n",
      "289    28\n",
      "504    24\n",
      "38     14\n",
      "Name: count, dtype: int64\n",
      "Ben-Thai-Cafe [u'thai' u'food' u'curry' u'good' u'great'] 1313    174\n",
      "491     116\n",
      "288      78\n",
      "543      76\n",
      "558      75\n",
      "Name: count, dtype: int64\n",
      "PianoFight [u'place' u'great' u'show' u'bar' u'food'] 1082    89\n",
      "637     83\n",
      "1301    72\n",
      "111     70\n",
      "554     61\n",
      "Name: count, dtype: int64\n",
      "Cordon-Bleu [u'food' u'chicken' u'place' u'meat' u'sauce'] 644     147\n",
      "258     138\n",
      "1254    122\n",
      "1051    120\n",
      "1444    116\n",
      "Name: count, dtype: int64\n",
      "Hog-Island-Oyster-Co [u'oysters' u'chowder' u'clam' u'oyster' u'good'] 1535    300\n",
      "395     181\n",
      "407     142\n",
      "1534    119\n",
      "947     109\n",
      "Name: count, dtype: int64\n",
      "Frances [u'good' u'frances' u'food' u'beignets' u'bacon'] 1154    137\n",
      "1061    117\n",
      "1035    111\n",
      "230      95\n",
      "175      90\n",
      "Name: count, dtype: int64\n",
      "Dinosaurs [u'sandwich' u'mi' u'banh' u'sandwiches' u'pork'] 1364    162\n",
      "985     133\n",
      "126     107\n",
      "1365    104\n",
      "1214    100\n",
      "Name: count, dtype: int64\n",
      "Ro-Cafe [u'cafe' u'coffee' u'food' u'place' u'good'] 58     133\n",
      "75     126\n",
      "158    126\n",
      "331    105\n",
      "176     98\n",
      "Name: count, dtype: int64\n",
      "Yemen-Kitchen [u'food' u'bread' u'lamb' u'good' u'yemen'] 396     76\n",
      "109     53\n",
      "572     37\n",
      "446     37\n",
      "1240    36\n",
      "Name: count, dtype: int64\n",
      "The-Italian-Homemade-Company [u'pasta' u'sauce' u'place' u'food' u'italian'] 1185    166\n",
      "1434    147\n",
      "1238    113\n",
      "629     112\n",
      "852     110\n",
      "Name: count, dtype: int64\n",
      "Poke-Delish [u'poke' u'fish' u'bowl' u'food' u'fresh'] 1094    219\n",
      "531     106\n",
      "158     104\n",
      "546      62\n",
      "558      59\n",
      "Name: count, dtype: int64\n",
      "Tselogs-SF [u'food' u'chicken' u'place' u'good' u'filipino'] 526     120\n",
      "210      81\n",
      "1009     80\n",
      "580      68\n",
      "501      67\n",
      "Name: count, dtype: int64\n",
      "Old-Skool-Cafe [u'food' u'great' u'good' u'place' u'chicken'] 940     188\n",
      "1065    128\n",
      "1044    122\n",
      "1768    110\n",
      "409     103\n",
      "Name: count, dtype: int64\n",
      "Keeva-Indian-Kitchen [u'food' u'indian' u'chicken' u'delicious' u'curry'] 417    76\n",
      "547    64\n",
      "173    40\n",
      "274    29\n",
      "239    27\n",
      "Name: count, dtype: int64\n",
      "Street-Taco [u'tacos' u'place' u'good' u'food' u'burrito'] 1329    117\n",
      "984      89\n",
      "577      85\n",
      "512      83\n",
      "175      75\n",
      "Name: count, dtype: int64\n",
      "Pokihub [u'poke' u'place' u'bowl' u'fresh' u'fish'] 612    63\n",
      "604    58\n",
      "87     55\n",
      "326    46\n",
      "302    38\n",
      "Name: count, dtype: int64\n",
      "FOB-Kitchen [u'food' u'filipino' u'fob' u'rice' u'kitchen'] 423    87\n",
      "400    69\n",
      "419    48\n",
      "959    47\n",
      "600    43\n",
      "Name: count, dtype: int64\n",
      "Lous-Cafe [u'sandwich' u'sandwiches' u'lou' u'good' u'place'] 1379    191\n",
      "1380    136\n",
      "915     103\n",
      "682      76\n",
      "1190     72\n",
      "Name: count, dtype: int64\n",
      "La-Taqueria [u'burrito' u'tacos' u'food' u'place' u'taco'] 270     258\n",
      "2174    140\n",
      "825     139\n",
      "1607    124\n",
      "2171    122\n",
      "Name: count, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "# append to df\n",
    "for i in short_cloud:\n",
    "    if i != 'Ichido':\n",
    "        #short_cloud[i].sort_values('count', ascending = False, inplace = True)\n",
    "        print i, np.array(short_cloud[i]['word'])[0:5], pd.Series(short_cloud[i]['count'])[0:5]\n",
    "        final_cloud_df[i] = short_cloud[i]['word'].tolist()\n",
    "        final_cloud_df[i+'_count'] = short_cloud[i]['count'].tolist()\n",
    "    else:\n",
    "        continue"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 214,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Ichido</th>\n",
       "      <th>Ichido_count</th>\n",
       "      <th>20-Spot</th>\n",
       "      <th>20-Spot_count</th>\n",
       "      <th>Parada-22</th>\n",
       "      <th>Parada-22_count</th>\n",
       "      <th>Stuffed</th>\n",
       "      <th>Stuffed_count</th>\n",
       "      <th>Nopa</th>\n",
       "      <th>Nopa_count</th>\n",
       "      <th>...</th>\n",
       "      <th>Street-Taco</th>\n",
       "      <th>Street-Taco_count</th>\n",
       "      <th>Pokihub</th>\n",
       "      <th>Pokihub_count</th>\n",
       "      <th>FOB-Kitchen</th>\n",
       "      <th>FOB-Kitchen_count</th>\n",
       "      <th>Lous-Cafe</th>\n",
       "      <th>Lous-Cafe_count</th>\n",
       "      <th>La-Taqueria</th>\n",
       "      <th>La-Taqueria_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>482</th>\n",
       "      <td>geoff</td>\n",
       "      <td>56</td>\n",
       "      <td>wine</td>\n",
       "      <td>186</td>\n",
       "      <td>food</td>\n",
       "      <td>326</td>\n",
       "      <td>pierogi</td>\n",
       "      <td>121</td>\n",
       "      <td>pork</td>\n",
       "      <td>137</td>\n",
       "      <td>...</td>\n",
       "      <td>tacos</td>\n",
       "      <td>117</td>\n",
       "      <td>poke</td>\n",
       "      <td>63</td>\n",
       "      <td>food</td>\n",
       "      <td>87</td>\n",
       "      <td>sandwich</td>\n",
       "      <td>191</td>\n",
       "      <td>burrito</td>\n",
       "      <td>258</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>379</th>\n",
       "      <td>experience</td>\n",
       "      <td>46</td>\n",
       "      <td>place</td>\n",
       "      <td>103</td>\n",
       "      <td>puerto</td>\n",
       "      <td>186</td>\n",
       "      <td>food</td>\n",
       "      <td>109</td>\n",
       "      <td>good</td>\n",
       "      <td>135</td>\n",
       "      <td>...</td>\n",
       "      <td>place</td>\n",
       "      <td>89</td>\n",
       "      <td>place</td>\n",
       "      <td>58</td>\n",
       "      <td>filipino</td>\n",
       "      <td>69</td>\n",
       "      <td>sandwiches</td>\n",
       "      <td>136</td>\n",
       "      <td>tacos</td>\n",
       "      <td>140</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>682</th>\n",
       "      <td>meal</td>\n",
       "      <td>37</td>\n",
       "      <td>spot</td>\n",
       "      <td>99</td>\n",
       "      <td>good</td>\n",
       "      <td>176</td>\n",
       "      <td>place</td>\n",
       "      <td>107</td>\n",
       "      <td>food</td>\n",
       "      <td>129</td>\n",
       "      <td>...</td>\n",
       "      <td>good</td>\n",
       "      <td>85</td>\n",
       "      <td>bowl</td>\n",
       "      <td>55</td>\n",
       "      <td>fob</td>\n",
       "      <td>48</td>\n",
       "      <td>lou</td>\n",
       "      <td>103</td>\n",
       "      <td>food</td>\n",
       "      <td>139</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>446</th>\n",
       "      <td>food</td>\n",
       "      <td>37</td>\n",
       "      <td>great</td>\n",
       "      <td>94</td>\n",
       "      <td>place</td>\n",
       "      <td>165</td>\n",
       "      <td>pierogis</td>\n",
       "      <td>75</td>\n",
       "      <td>nopa</td>\n",
       "      <td>124</td>\n",
       "      <td>...</td>\n",
       "      <td>food</td>\n",
       "      <td>83</td>\n",
       "      <td>fresh</td>\n",
       "      <td>46</td>\n",
       "      <td>rice</td>\n",
       "      <td>47</td>\n",
       "      <td>good</td>\n",
       "      <td>76</td>\n",
       "      <td>place</td>\n",
       "      <td>124</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>297</th>\n",
       "      <td>dinner</td>\n",
       "      <td>35</td>\n",
       "      <td>food</td>\n",
       "      <td>80</td>\n",
       "      <td>rican</td>\n",
       "      <td>149</td>\n",
       "      <td>good</td>\n",
       "      <td>75</td>\n",
       "      <td>chop</td>\n",
       "      <td>93</td>\n",
       "      <td>...</td>\n",
       "      <td>burrito</td>\n",
       "      <td>75</td>\n",
       "      <td>fish</td>\n",
       "      <td>38</td>\n",
       "      <td>kitchen</td>\n",
       "      <td>43</td>\n",
       "      <td>place</td>\n",
       "      <td>72</td>\n",
       "      <td>taco</td>\n",
       "      <td>122</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>277</th>\n",
       "      <td>delicious</td>\n",
       "      <td>34</td>\n",
       "      <td>good</td>\n",
       "      <td>76</td>\n",
       "      <td>rice</td>\n",
       "      <td>132</td>\n",
       "      <td>like</td>\n",
       "      <td>73</td>\n",
       "      <td>table</td>\n",
       "      <td>93</td>\n",
       "      <td>...</td>\n",
       "      <td>taco</td>\n",
       "      <td>71</td>\n",
       "      <td>spicy</td>\n",
       "      <td>35</td>\n",
       "      <td>lumpia</td>\n",
       "      <td>43</td>\n",
       "      <td>sauce</td>\n",
       "      <td>71</td>\n",
       "      <td>taqueria</td>\n",
       "      <td>113</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>763</th>\n",
       "      <td>one</td>\n",
       "      <td>33</td>\n",
       "      <td>bar</td>\n",
       "      <td>71</td>\n",
       "      <td>plantains</td>\n",
       "      <td>130</td>\n",
       "      <td>one</td>\n",
       "      <td>66</td>\n",
       "      <td>like</td>\n",
       "      <td>91</td>\n",
       "      <td>...</td>\n",
       "      <td>meat</td>\n",
       "      <td>50</td>\n",
       "      <td>good</td>\n",
       "      <td>34</td>\n",
       "      <td>good</td>\n",
       "      <td>38</td>\n",
       "      <td>time</td>\n",
       "      <td>65</td>\n",
       "      <td>super</td>\n",
       "      <td>110</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>176</th>\n",
       "      <td>chef</td>\n",
       "      <td>32</td>\n",
       "      <td>like</td>\n",
       "      <td>57</td>\n",
       "      <td>beans</td>\n",
       "      <td>123</td>\n",
       "      <td>great</td>\n",
       "      <td>54</td>\n",
       "      <td>one</td>\n",
       "      <td>89</td>\n",
       "      <td>...</td>\n",
       "      <td>street</td>\n",
       "      <td>50</td>\n",
       "      <td>salmon</td>\n",
       "      <td>34</td>\n",
       "      <td>place</td>\n",
       "      <td>31</td>\n",
       "      <td>get</td>\n",
       "      <td>62</td>\n",
       "      <td>one</td>\n",
       "      <td>107</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>225</th>\n",
       "      <td>course</td>\n",
       "      <td>28</td>\n",
       "      <td>menu</td>\n",
       "      <td>47</td>\n",
       "      <td>great</td>\n",
       "      <td>120</td>\n",
       "      <td>back</td>\n",
       "      <td>52</td>\n",
       "      <td>time</td>\n",
       "      <td>87</td>\n",
       "      <td>...</td>\n",
       "      <td>salsa</td>\n",
       "      <td>45</td>\n",
       "      <td>rice</td>\n",
       "      <td>34</td>\n",
       "      <td>like</td>\n",
       "      <td>30</td>\n",
       "      <td>bread</td>\n",
       "      <td>58</td>\n",
       "      <td>good</td>\n",
       "      <td>105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>amazing</td>\n",
       "      <td>26</td>\n",
       "      <td>little</td>\n",
       "      <td>45</td>\n",
       "      <td>cha</td>\n",
       "      <td>110</td>\n",
       "      <td>stuffed</td>\n",
       "      <td>52</td>\n",
       "      <td>great</td>\n",
       "      <td>79</td>\n",
       "      <td>...</td>\n",
       "      <td>one</td>\n",
       "      <td>45</td>\n",
       "      <td>really</td>\n",
       "      <td>29</td>\n",
       "      <td>great</td>\n",
       "      <td>28</td>\n",
       "      <td>line</td>\n",
       "      <td>53</td>\n",
       "      <td>la</td>\n",
       "      <td>103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>561</th>\n",
       "      <td>ichido</td>\n",
       "      <td>25</td>\n",
       "      <td>love</td>\n",
       "      <td>45</td>\n",
       "      <td>pork</td>\n",
       "      <td>106</td>\n",
       "      <td>really</td>\n",
       "      <td>50</td>\n",
       "      <td>dish</td>\n",
       "      <td>77</td>\n",
       "      <td>...</td>\n",
       "      <td>haight</td>\n",
       "      <td>44</td>\n",
       "      <td>like</td>\n",
       "      <td>26</td>\n",
       "      <td>bar</td>\n",
       "      <td>25</td>\n",
       "      <td>order</td>\n",
       "      <td>52</td>\n",
       "      <td>get</td>\n",
       "      <td>93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1211</th>\n",
       "      <td>us</td>\n",
       "      <td>25</td>\n",
       "      <td>would</td>\n",
       "      <td>44</td>\n",
       "      <td>like</td>\n",
       "      <td>106</td>\n",
       "      <td>cheese</td>\n",
       "      <td>50</td>\n",
       "      <td>brunch</td>\n",
       "      <td>76</td>\n",
       "      <td>...</td>\n",
       "      <td>really</td>\n",
       "      <td>44</td>\n",
       "      <td>pokihub</td>\n",
       "      <td>25</td>\n",
       "      <td>brunch</td>\n",
       "      <td>24</td>\n",
       "      <td>go</td>\n",
       "      <td>45</td>\n",
       "      <td>best</td>\n",
       "      <td>91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>304</th>\n",
       "      <td>dish</td>\n",
       "      <td>24</td>\n",
       "      <td>service</td>\n",
       "      <td>44</td>\n",
       "      <td>delicious</td>\n",
       "      <td>94</td>\n",
       "      <td>bacon</td>\n",
       "      <td>42</td>\n",
       "      <td>place</td>\n",
       "      <td>76</td>\n",
       "      <td>...</td>\n",
       "      <td>great</td>\n",
       "      <td>43</td>\n",
       "      <td>definitely</td>\n",
       "      <td>23</td>\n",
       "      <td>adobo</td>\n",
       "      <td>23</td>\n",
       "      <td>great</td>\n",
       "      <td>45</td>\n",
       "      <td>like</td>\n",
       "      <td>89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>430</th>\n",
       "      <td>fish</td>\n",
       "      <td>22</td>\n",
       "      <td>back</td>\n",
       "      <td>44</td>\n",
       "      <td>get</td>\n",
       "      <td>91</td>\n",
       "      <td>delicious</td>\n",
       "      <td>42</td>\n",
       "      <td>reservation</td>\n",
       "      <td>73</td>\n",
       "      <td>...</td>\n",
       "      <td>ordered</td>\n",
       "      <td>41</td>\n",
       "      <td>tuna</td>\n",
       "      <td>23</td>\n",
       "      <td>garlic</td>\n",
       "      <td>23</td>\n",
       "      <td>special</td>\n",
       "      <td>43</td>\n",
       "      <td>burritos</td>\n",
       "      <td>88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>483</th>\n",
       "      <td>geoffrey</td>\n",
       "      <td>19</td>\n",
       "      <td>time</td>\n",
       "      <td>42</td>\n",
       "      <td>really</td>\n",
       "      <td>91</td>\n",
       "      <td>beer</td>\n",
       "      <td>42</td>\n",
       "      <td>dinner</td>\n",
       "      <td>73</td>\n",
       "      <td>...</td>\n",
       "      <td>get</td>\n",
       "      <td>41</td>\n",
       "      <td>friendly</td>\n",
       "      <td>22</td>\n",
       "      <td>try</td>\n",
       "      <td>21</td>\n",
       "      <td>crunch</td>\n",
       "      <td>42</td>\n",
       "      <td>asada</td>\n",
       "      <td>85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>507</th>\n",
       "      <td>great</td>\n",
       "      <td>17</td>\n",
       "      <td>really</td>\n",
       "      <td>42</td>\n",
       "      <td>ordered</td>\n",
       "      <td>88</td>\n",
       "      <td>also</td>\n",
       "      <td>39</td>\n",
       "      <td>get</td>\n",
       "      <td>72</td>\n",
       "      <td>...</td>\n",
       "      <td>mexican</td>\n",
       "      <td>40</td>\n",
       "      <td>sauce</td>\n",
       "      <td>21</td>\n",
       "      <td>love</td>\n",
       "      <td>21</td>\n",
       "      <td>dutch</td>\n",
       "      <td>38</td>\n",
       "      <td>line</td>\n",
       "      <td>83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92</th>\n",
       "      <td>best</td>\n",
       "      <td>16</td>\n",
       "      <td>well</td>\n",
       "      <td>41</td>\n",
       "      <td>plate</td>\n",
       "      <td>88</td>\n",
       "      <td>polish</td>\n",
       "      <td>39</td>\n",
       "      <td>came</td>\n",
       "      <td>71</td>\n",
       "      <td>...</td>\n",
       "      <td>super</td>\n",
       "      <td>40</td>\n",
       "      <td>food</td>\n",
       "      <td>18</td>\n",
       "      <td>ordered</td>\n",
       "      <td>20</td>\n",
       "      <td>try</td>\n",
       "      <td>38</td>\n",
       "      <td>carne</td>\n",
       "      <td>82</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>160</th>\n",
       "      <td>caught</td>\n",
       "      <td>16</td>\n",
       "      <td>small</td>\n",
       "      <td>40</td>\n",
       "      <td>chicken</td>\n",
       "      <td>88</td>\n",
       "      <td>go</td>\n",
       "      <td>38</td>\n",
       "      <td>really</td>\n",
       "      <td>70</td>\n",
       "      <td>...</td>\n",
       "      <td>pretty</td>\n",
       "      <td>39</td>\n",
       "      <td>clean</td>\n",
       "      <td>18</td>\n",
       "      <td>pork</td>\n",
       "      <td>20</td>\n",
       "      <td>like</td>\n",
       "      <td>38</td>\n",
       "      <td>go</td>\n",
       "      <td>79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>991</th>\n",
       "      <td>served</td>\n",
       "      <td>16</td>\n",
       "      <td>night</td>\n",
       "      <td>38</td>\n",
       "      <td>would</td>\n",
       "      <td>83</td>\n",
       "      <td>pierogies</td>\n",
       "      <td>38</td>\n",
       "      <td>burger</td>\n",
       "      <td>68</td>\n",
       "      <td>...</td>\n",
       "      <td>order</td>\n",
       "      <td>37</td>\n",
       "      <td>go</td>\n",
       "      <td>17</td>\n",
       "      <td>menu</td>\n",
       "      <td>20</td>\n",
       "      <td>got</td>\n",
       "      <td>37</td>\n",
       "      <td>meat</td>\n",
       "      <td>71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>848</th>\n",
       "      <td>pork</td>\n",
       "      <td>15</td>\n",
       "      <td>also</td>\n",
       "      <td>37</td>\n",
       "      <td>love</td>\n",
       "      <td>83</td>\n",
       "      <td>two</td>\n",
       "      <td>36</td>\n",
       "      <td>would</td>\n",
       "      <td>67</td>\n",
       "      <td>...</td>\n",
       "      <td>asada</td>\n",
       "      <td>35</td>\n",
       "      <td>toppings</td>\n",
       "      <td>17</td>\n",
       "      <td>authentic</td>\n",
       "      <td>19</td>\n",
       "      <td>lunch</td>\n",
       "      <td>37</td>\n",
       "      <td>carnitas</td>\n",
       "      <td>67</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>20 rows × 176 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          Ichido  Ichido_count  20-Spot  20-Spot_count  Parada-22  \\\n",
       "482        geoff            56     wine            186       food   \n",
       "379   experience            46    place            103     puerto   \n",
       "682         meal            37     spot             99       good   \n",
       "446         food            37    great             94      place   \n",
       "297       dinner            35     food             80      rican   \n",
       "277    delicious            34     good             76       rice   \n",
       "763          one            33      bar             71  plantains   \n",
       "176         chef            32     like             57      beans   \n",
       "225       course            28     menu             47      great   \n",
       "29       amazing            26   little             45        cha   \n",
       "561       ichido            25     love             45       pork   \n",
       "1211          us            25    would             44       like   \n",
       "304         dish            24  service             44  delicious   \n",
       "430         fish            22     back             44        get   \n",
       "483     geoffrey            19     time             42     really   \n",
       "507        great            17   really             42    ordered   \n",
       "92          best            16     well             41      plate   \n",
       "160       caught            16    small             40    chicken   \n",
       "991       served            16    night             38      would   \n",
       "848         pork            15     also             37       love   \n",
       "\n",
       "      Parada-22_count    Stuffed  Stuffed_count         Nopa  Nopa_count  \\\n",
       "482               326    pierogi            121         pork         137   \n",
       "379               186       food            109         good         135   \n",
       "682               176      place            107         food         129   \n",
       "446               165   pierogis             75         nopa         124   \n",
       "297               149       good             75         chop          93   \n",
       "277               132       like             73        table          93   \n",
       "763               130        one             66         like          91   \n",
       "176               123      great             54          one          89   \n",
       "225               120       back             52         time          87   \n",
       "29                110    stuffed             52        great          79   \n",
       "561               106     really             50         dish          77   \n",
       "1211              106     cheese             50       brunch          76   \n",
       "304                94      bacon             42        place          76   \n",
       "430                91  delicious             42  reservation          73   \n",
       "483                91       beer             42       dinner          73   \n",
       "507                88       also             39          get          72   \n",
       "92                 88     polish             39         came          71   \n",
       "160                88         go             38       really          70   \n",
       "991                83  pierogies             38       burger          68   \n",
       "848                83        two             36        would          67   \n",
       "\n",
       "            ...         Street-Taco  Street-Taco_count     Pokihub  \\\n",
       "482         ...               tacos                117        poke   \n",
       "379         ...               place                 89       place   \n",
       "682         ...                good                 85        bowl   \n",
       "446         ...                food                 83       fresh   \n",
       "297         ...             burrito                 75        fish   \n",
       "277         ...                taco                 71       spicy   \n",
       "763         ...                meat                 50        good   \n",
       "176         ...              street                 50      salmon   \n",
       "225         ...               salsa                 45        rice   \n",
       "29          ...                 one                 45      really   \n",
       "561         ...              haight                 44        like   \n",
       "1211        ...              really                 44     pokihub   \n",
       "304         ...               great                 43  definitely   \n",
       "430         ...             ordered                 41        tuna   \n",
       "483         ...                 get                 41    friendly   \n",
       "507         ...             mexican                 40       sauce   \n",
       "92          ...               super                 40        food   \n",
       "160         ...              pretty                 39       clean   \n",
       "991         ...               order                 37          go   \n",
       "848         ...               asada                 35    toppings   \n",
       "\n",
       "      Pokihub_count FOB-Kitchen  FOB-Kitchen_count   Lous-Cafe  \\\n",
       "482              63        food                 87    sandwich   \n",
       "379              58    filipino                 69  sandwiches   \n",
       "682              55         fob                 48         lou   \n",
       "446              46        rice                 47        good   \n",
       "297              38     kitchen                 43       place   \n",
       "277              35      lumpia                 43       sauce   \n",
       "763              34        good                 38        time   \n",
       "176              34       place                 31         get   \n",
       "225              34        like                 30       bread   \n",
       "29               29       great                 28        line   \n",
       "561              26         bar                 25       order   \n",
       "1211             25      brunch                 24          go   \n",
       "304              23       adobo                 23       great   \n",
       "430              23      garlic                 23     special   \n",
       "483              22         try                 21      crunch   \n",
       "507              21        love                 21       dutch   \n",
       "92               18     ordered                 20         try   \n",
       "160              18        pork                 20        like   \n",
       "991              17        menu                 20         got   \n",
       "848              17   authentic                 19       lunch   \n",
       "\n",
       "      Lous-Cafe_count La-Taqueria  La-Taqueria_count  \n",
       "482               191     burrito                258  \n",
       "379               136       tacos                140  \n",
       "682               103        food                139  \n",
       "446                76       place                124  \n",
       "297                72        taco                122  \n",
       "277                71    taqueria                113  \n",
       "763                65       super                110  \n",
       "176                62         one                107  \n",
       "225                58        good                105  \n",
       "29                 53          la                103  \n",
       "561                52         get                 93  \n",
       "1211               45        best                 91  \n",
       "304                45        like                 89  \n",
       "430                43    burritos                 88  \n",
       "483                42       asada                 85  \n",
       "507                38        line                 83  \n",
       "92                 38       carne                 82  \n",
       "160                38          go                 79  \n",
       "991                37        meat                 71  \n",
       "848                37    carnitas                 67  \n",
       "\n",
       "[20 rows x 176 columns]"
      ]
     },
     "execution_count": 214,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "final_cloud_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 216,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "final_cloud_df.to_csv('./cloud_yelp_csv.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 218,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(20, 176)"
      ]
     },
     "execution_count": 218,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "final_cloud_df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
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    "name": "ipython",
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   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.12"
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