EDA_Groupby Cuisines.ipynb

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   "source": [
    "Questions to be considered:\n",
    "\n",
    "\n",
    "1. Group the restaurants by cuisines\n",
    "2. Cuisines types: asian, european, north america, south america, other (cannot classify)\n",
    "3. EDA for each cuisine\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
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     "timestamp": 1575754940673,
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   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/Users/lisacombs/Documents/FALL2019/INTRO_DS/Project/notebooks\r\n"
     ]
    }
   ],
   "source": [
    "!pwd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "YShnvySPYDXW"
   },
   "outputs": [],
   "source": [
    "biz_file_path = '/Users/lisacombs/Documents/FALL2019/INTRO_DS/Project/clean_data/restaurant_open.csv'\n",
    "biz_att_file_path = '/Users/lisacombs/Documents/FALL2019/INTRO_DS/Project/raw_data/yelp_business_attributes.csv'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "6whDWpFmFmzj"
   },
   "outputs": [],
   "source": [
    "biz_df = pd.read_csv(biz_file_path)\n",
    "biz_att = pd.read_csv(biz_att_file_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "pU-lj6mpVq64"
   },
   "outputs": [],
   "source": [
    "data = pd.merge(biz_df,biz_att, on='business_id')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "kKcxAlxUFr__"
   },
   "outputs": [],
   "source": [
    "data.replace(to_replace='True', value = 1,inplace=True)\n",
    "data.replace(to_replace='False', value = 0,inplace=True)\n",
    "data.replace(to_replace='Na', value = 0.5,inplace=True) #only treat this as a categorical variable"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "C4MLdDy6duYe"
   },
   "outputs": [],
   "source": [
    "data.replace(to_replace= ['beer_and_wine',        'casual',          'free',\n",
    "            'full_bar',          'loud', 'outdoor',         'quiet',           'yes',      'yes_free', '1', '2'], value = 1,inplace=True)\n",
    "data.replace(to_replace=['no', 'none'], value = 0,inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "Wu0vf1K7SjlG"
   },
   "outputs": [],
   "source": [
    "vegas = data[data['city']=='Las Vegas']\n",
    "vegas.head()\n",
    "\n",
    "att = vegas.iloc[:,16:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "hCmqbRn9pTAU"
   },
   "outputs": [],
   "source": [
    "features = ['Unnamed: 0',\n",
    " 'business_id',\n",
    " 'name',\n",
    " 'neighborhood',\n",
    " 'address',\n",
    " 'city',\n",
    " 'state',\n",
    " 'postal_code',\n",
    " 'latitude',\n",
    " 'longitude',\n",
    " 'stars',\n",
    " 'review_count',\n",
    " 'is_open',\n",
    " 'categories',\n",
    " 'hours',]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "Ygu0_JRYb1_S"
   },
   "outputs": [],
   "source": [
    "d = att.apply(pd.value_counts)\n",
    "col_names = d.columns.tolist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "_LnHGAUHoeV_"
   },
   "outputs": [],
   "source": [
    "d = d.drop(columns ='HairSpecializesIn_coloring')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "Ncx3GEADh7KC"
   },
   "outputs": [],
   "source": [
    "col = d.loc[:,~(d == att.shape[0]).any()].columns.tolist()\n",
    "# d.loc[:,~(d == float(att.shape[0])).any()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "-ifL5jDhGBVP"
   },
   "outputs": [],
   "source": [
    "colnames = features + col\n",
    "dataclean = data[colnames]"
   ]
  },
  {
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   "execution_count": 14,
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       "    Unnamed: 0             business_id                       name  \\\n",
       "8           32  kgffcoxT6BQp-gJ-UQ7Czw                     Subway   \n",
       "9           33  0jtRI7hVMpQHpUVtUy4ITw     Omelet House Summerlin   \n",
       "32         141  zhxnD7J5_sCrKSw5cwI9dQ  Popeyes Louisiana Kitchen   \n",
       "34         143  2kWrSFkIes_d2BMg4YrRtA                  Pizza Hut   \n",
       "35         145  6llKs7K_tn8ChXcIM-oTvg               Sansei Japan   \n",
       "\n",
       "   neighborhood                     address       city state postal_code  \\\n",
       "8     Summerlin         2255 N Rampart Blvd  Las Vegas    NV       89128   \n",
       "9     Summerlin         2227 N Rampart Blvd  Las Vegas    NV       89128   \n",
       "32      Sunrise           4505 E Bonanza Rd  Las Vegas    NV       89110   \n",
       "34      Sunrise  560 N. Nellis Blvd, Ste E1  Las Vegas    NV       89110   \n",
       "35     Eastside        3480 S Maryland Pkwy  Las Vegas    NV       89169   \n",
       "\n",
       "     latitude   longitude  ...  BusinessAcceptsBitcoin  Open24Hours  BYOB  \\\n",
       "8   36.201794 -115.281981  ...                     0.5          0.5   0.5   \n",
       "9   36.201990 -115.283122  ...                     0.5          0.5   0.5   \n",
       "32  36.173140 -115.077945  ...                     0.5          0.5   0.5   \n",
       "34  36.169353 -115.061694  ...                     0.5          0.5   0.5   \n",
       "35  36.125934 -115.135253  ...                     0.5          0.5   0.5   \n",
       "\n",
       "   DietaryRestrictions_gluten-free DietaryRestrictions_vegan  \\\n",
       "8                              0.5                       0.5   \n",
       "9                              0.5                       0.5   \n",
       "32                             0.5                       0.5   \n",
       "34                             0.5                       0.5   \n",
       "35                             0.5                       0.5   \n",
       "\n",
       "    DietaryRestrictions_kosher  DietaryRestrictions_halal  \\\n",
       "8                          0.5                        0.5   \n",
       "9                          0.5                        0.5   \n",
       "32                         0.5                        0.5   \n",
       "34                         0.5                        0.5   \n",
       "35                         0.5                        0.5   \n",
       "\n",
       "    DietaryRestrictions_soy-free  DietaryRestrictions_vegetarian  AgesAllowed  \n",
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       "9                            0.5                             0.5          0.5  \n",
       "32                           0.5                             0.5          0.5  \n",
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     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vegas_clean = dataclean[dataclean['city']=='Las Vegas']\n",
    "vegas_clean.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
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     "base_uri": "https://localhost:8080/",
     "height": 53
    },
    "colab_type": "code",
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "'chinese|japanese|asian|indian|sushi|dim dum|cantonese|ramen|noodles|thai|vietnamese|filipino|korean|mediterranean|italian|greek|french|creperies|tapas bars|middle eastern|halal|pizza|sandwiches|delis|wraps|chicken wings|chicken shop|hot dogs|cheesesteaks|burgers|american|steak|southern|comfort food|cajun|creole|soul food|fast food|mexican|latin american|tex-mex|tacos|salvadoran'"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Group features by cuisines\n",
    "asian = 'chinese|japanese|asian|indian|sushi|dim dum|cantonese|ramen|noodles|thai|vietnamese|filipino|korean'\n",
    "european = 'mediterranean|italian|greek|french|creperies|tapas bars|middle eastern|halal' #remove 'tapas' \n",
    "namerica = 'pizza|sandwiches|delis|wraps|chicken wings|chicken shop|hot dogs|cheesesteaks|burgers|american|steak|southern|comfort food|cajun|creole|soul food|fast food'\n",
    "#remove 'barbeque' since a korean bbq has it and outperforms the class.\n",
    "samerica = 'mexican|latin american|tex-mex|tacos|salvadoran'\n",
    "other = asian +'|'+ european +'|'+ namerica +'|'+ samerica\n",
    "other"
   ]
  },
  {
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   "execution_count": 16,
   "metadata": {
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     "execution_count": 16,
     "metadata": {},
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   ],
   "source": [
    "only_desc = vegas_clean['categories'].str.lower()\n",
    "\n",
    "with_features = (vegas_clean\n",
    " .assign(asian     = only_desc.str.contains(asian))\n",
    " .assign(european = only_desc.str.contains(european))\n",
    " .assign(namerica    = only_desc.str.contains(namerica))\n",
    " .assign(samerica  = only_desc.str.contains(samerica))\n",
    " .assign(other = ~only_desc.str.contains(other)))\n",
    "\n",
    "with_features['class'] = with_features.iloc[:,-5:].sum(axis = 1)\n",
    "len(with_features.columns)"
   ]
  },
  {
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       "<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>Unnamed: 0</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>stars</th>\n",
       "      <th>review_count</th>\n",
       "      <th>is_open</th>\n",
       "      <th>BusinessAcceptsCreditCards</th>\n",
       "      <th>BusinessParking_garage</th>\n",
       "      <th>BusinessParking_street</th>\n",
       "      <th>BusinessParking_validated</th>\n",
       "      <th>...</th>\n",
       "      <th>Open24Hours</th>\n",
       "      <th>BYOB</th>\n",
       "      <th>DietaryRestrictions_gluten-free</th>\n",
       "      <th>DietaryRestrictions_vegan</th>\n",
       "      <th>DietaryRestrictions_kosher</th>\n",
       "      <th>DietaryRestrictions_halal</th>\n",
       "      <th>DietaryRestrictions_soy-free</th>\n",
       "      <th>DietaryRestrictions_vegetarian</th>\n",
       "      <th>AgesAllowed</th>\n",
       "      <th>class</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>count</td>\n",
       "      <td>710.000000</td>\n",
       "      <td>710.000000</td>\n",
       "      <td>710.000000</td>\n",
       "      <td>710.000000</td>\n",
       "      <td>710.000000</td>\n",
       "      <td>710.0</td>\n",
       "      <td>710.000000</td>\n",
       "      <td>710.000000</td>\n",
       "      <td>710.000000</td>\n",
       "      <td>710.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>710.0</td>\n",
       "      <td>710.000000</td>\n",
       "      <td>710.000000</td>\n",
       "      <td>710.000000</td>\n",
       "      <td>710.000000</td>\n",
       "      <td>710.000000</td>\n",
       "      <td>710.000000</td>\n",
       "      <td>710.000000</td>\n",
       "      <td>710.000000</td>\n",
       "      <td>710.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>mean</td>\n",
       "      <td>100284.973239</td>\n",
       "      <td>36.122102</td>\n",
       "      <td>-115.197656</td>\n",
       "      <td>3.704930</td>\n",
       "      <td>298.181690</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.496479</td>\n",
       "      <td>0.500704</td>\n",
       "      <td>0.174648</td>\n",
       "      <td>0.115493</td>\n",
       "      <td>...</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.500704</td>\n",
       "      <td>0.500704</td>\n",
       "      <td>0.497887</td>\n",
       "      <td>0.499296</td>\n",
       "      <td>0.497887</td>\n",
       "      <td>0.497887</td>\n",
       "      <td>0.499296</td>\n",
       "      <td>0.502113</td>\n",
       "      <td>1.236620</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>std</td>\n",
       "      <td>55198.026884</td>\n",
       "      <td>0.053408</td>\n",
       "      <td>0.062516</td>\n",
       "      <td>0.657958</td>\n",
       "      <td>384.157903</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.041841</td>\n",
       "      <td>0.018765</td>\n",
       "      <td>0.320533</td>\n",
       "      <td>0.246354</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.018765</td>\n",
       "      <td>0.032517</td>\n",
       "      <td>0.032455</td>\n",
       "      <td>0.032517</td>\n",
       "      <td>0.032455</td>\n",
       "      <td>0.032455</td>\n",
       "      <td>0.032517</td>\n",
       "      <td>0.032455</td>\n",
       "      <td>0.441577</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>min</td>\n",
       "      <td>145.000000</td>\n",
       "      <td>35.995198</td>\n",
       "      <td>-115.334601</td>\n",
       "      <td>1.500000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>25%</td>\n",
       "      <td>50621.000000</td>\n",
       "      <td>36.100515</td>\n",
       "      <td>-115.242993</td>\n",
       "      <td>3.500000</td>\n",
       "      <td>65.250000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>50%</td>\n",
       "      <td>104170.000000</td>\n",
       "      <td>36.125208</td>\n",
       "      <td>-115.197855</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>172.500000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>75%</td>\n",
       "      <td>150273.750000</td>\n",
       "      <td>36.144092</td>\n",
       "      <td>-115.153254</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>398.250000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>max</td>\n",
       "      <td>188497.000000</td>\n",
       "      <td>36.300480</td>\n",
       "      <td>-115.025515</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>3731.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.5</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 54 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          Unnamed: 0    latitude   longitude       stars  review_count  \\\n",
       "count     710.000000  710.000000  710.000000  710.000000    710.000000   \n",
       "mean   100284.973239   36.122102 -115.197656    3.704930    298.181690   \n",
       "std     55198.026884    0.053408    0.062516    0.657958    384.157903   \n",
       "min       145.000000   35.995198 -115.334601    1.500000      3.000000   \n",
       "25%     50621.000000   36.100515 -115.242993    3.500000     65.250000   \n",
       "50%    104170.000000   36.125208 -115.197855    4.000000    172.500000   \n",
       "75%    150273.750000   36.144092 -115.153254    4.000000    398.250000   \n",
       "max    188497.000000   36.300480 -115.025515    5.000000   3731.000000   \n",
       "\n",
       "       is_open  BusinessAcceptsCreditCards  BusinessParking_garage  \\\n",
       "count    710.0                  710.000000              710.000000   \n",
       "mean       1.0                    0.496479                0.500704   \n",
       "std        0.0                    0.041841                0.018765   \n",
       "min        1.0                    0.000000                0.500000   \n",
       "25%        1.0                    0.500000                0.500000   \n",
       "50%        1.0                    0.500000                0.500000   \n",
       "75%        1.0                    0.500000                0.500000   \n",
       "max        1.0                    0.500000                1.000000   \n",
       "\n",
       "       BusinessParking_street  BusinessParking_validated  ...  Open24Hours  \\\n",
       "count              710.000000                 710.000000  ...        710.0   \n",
       "mean                 0.174648                   0.115493  ...          0.5   \n",
       "std                  0.320533                   0.246354  ...          0.0   \n",
       "min                  0.000000                   0.000000  ...          0.5   \n",
       "25%                  0.000000                   0.000000  ...          0.5   \n",
       "50%                  0.000000                   0.000000  ...          0.5   \n",
       "75%                  0.500000                   0.000000  ...          0.5   \n",
       "max                  1.000000                   1.000000  ...          0.5   \n",
       "\n",
       "             BYOB  DietaryRestrictions_gluten-free  DietaryRestrictions_vegan  \\\n",
       "count  710.000000                       710.000000                 710.000000   \n",
       "mean     0.500704                         0.500704                   0.497887   \n",
       "std      0.018765                         0.032517                   0.032455   \n",
       "min      0.500000                         0.000000                   0.000000   \n",
       "25%      0.500000                         0.500000                   0.500000   \n",
       "50%      0.500000                         0.500000                   0.500000   \n",
       "75%      0.500000                         0.500000                   0.500000   \n",
       "max      1.000000                         1.000000                   0.500000   \n",
       "\n",
       "       DietaryRestrictions_kosher  DietaryRestrictions_halal  \\\n",
       "count                  710.000000                 710.000000   \n",
       "mean                     0.499296                   0.497887   \n",
       "std                      0.032517                   0.032455   \n",
       "min                      0.000000                   0.000000   \n",
       "25%                      0.500000                   0.500000   \n",
       "50%                      0.500000                   0.500000   \n",
       "75%                      0.500000                   0.500000   \n",
       "max                      1.000000                   0.500000   \n",
       "\n",
       "       DietaryRestrictions_soy-free  DietaryRestrictions_vegetarian  \\\n",
       "count                    710.000000                      710.000000   \n",
       "mean                       0.497887                        0.499296   \n",
       "std                        0.032455                        0.032517   \n",
       "min                        0.000000                        0.000000   \n",
       "25%                        0.500000                        0.500000   \n",
       "50%                        0.500000                        0.500000   \n",
       "75%                        0.500000                        0.500000   \n",
       "max                        0.500000                        1.000000   \n",
       "\n",
       "       AgesAllowed       class  \n",
       "count   710.000000  710.000000  \n",
       "mean      0.502113    1.236620  \n",
       "std       0.032455    0.441577  \n",
       "min       0.500000    1.000000  \n",
       "25%       0.500000    1.000000  \n",
       "50%       0.500000    1.000000  \n",
       "75%       0.500000    1.000000  \n",
       "max       1.000000    3.000000  \n",
       "\n",
       "[8 rows x 54 columns]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "with_features[with_features['asian']==True].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "Gf62UOTSXwAf"
   },
   "outputs": [],
   "source": [
    "#with_features[with_features['european']==True].describe()\n",
    "#with_features[with_features['namerica']==True].describe()\n",
    "#with_features[with_features['samerica']==True].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 33
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 32986,
     "status": "ok",
     "timestamp": 1575754948830,
     "user": {
      "displayName": "Emmy Phung",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AAuE7mB0XMWxbfbNKbYDfXLX0_DPwLUNj1CQ0JzU4Gcd=s64",
      "userId": "15191778731511742618"
     },
     "user_tz": 300
    },
    "id": "oOSL4XAYh94N",
    "outputId": "5b87e659-04a8-4489-8146-3519f3597154"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "387\n"
     ]
    }
   ],
   "source": [
    "# business_df['categories'].head()\n",
    "categories_df = with_features['categories'].str.split(',', expand = True)\n",
    "cat_ls = categories_df.values.flatten()\n",
    "cat_ls = list(filter(None, cat_ls)) \n",
    "cat_ls = np.unique(cat_ls)\n",
    "\n",
    "# # clean the words\n",
    "# leading whitespace \n",
    "cat_ls = [s.strip() for s in cat_ls] \n",
    "cat_ls = np.unique(cat_ls)\n",
    "print(len(cat_ls))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 33
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 32978,
     "status": "ok",
     "timestamp": 1575754948831,
     "user": {
      "displayName": "Emmy Phung",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AAuE7mB0XMWxbfbNKbYDfXLX0_DPwLUNj1CQ0JzU4Gcd=s64",
      "userId": "15191778731511742618"
     },
     "user_tz": 300
    },
    "id": "_SABg-jqjmtO",
    "outputId": "c34dc1f4-5c01-448f-bbf8-c185efc87ce7"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "351\n"
     ]
    }
   ],
   "source": [
    "#Remove the cuisine names from features\n",
    "cuisine_list = other.split('|')\n",
    "cuisine_list = [i.title() for i in cuisine_list ]\n",
    "cat_ls = [i for i in cat_ls if i not in cuisine_list]\n",
    "print(len(cat_ls))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 33
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 33187,
     "status": "ok",
     "timestamp": 1575754949049,
     "user": {
      "displayName": "Emmy Phung",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AAuE7mB0XMWxbfbNKbYDfXLX0_DPwLUNj1CQ0JzU4Gcd=s64",
      "userId": "15191778731511742618"
     },
     "user_tz": 300
    },
    "id": "pz-uFTuniBUE",
    "outputId": "ac654750-7a1d-4c95-bdee-06812b25b4ec"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "422"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# make empty columns\n",
    "for i in cat_ls:\n",
    "    with_features[i] = 0\n",
    "\n",
    "len(with_features.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 115
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 57989,
     "status": "ok",
     "timestamp": 1575754973860,
     "user": {
      "displayName": "Emmy Phung",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AAuE7mB0XMWxbfbNKbYDfXLX0_DPwLUNj1CQ0JzU4Gcd=s64",
      "userId": "15191778731511742618"
     },
     "user_tz": 300
    },
    "id": "FnJEwLiDiEdO",
    "outputId": "77f760c7-9734-4403-f5b5-0499450c0c9e"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3779, 422)"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# sort by largest categories?\n",
    "cats_df = with_features[with_features.columns[-387:]]\n",
    "\n",
    "for c in range(0,len(cat_ls)):\n",
    "  temp_c=str(cats_df.columns.tolist()[c])\n",
    "\n",
    "  for i in range(len(with_features['categories'])):\n",
    "    if temp_c in str(with_features['categories'].iloc[i]):\n",
    "      with_features[temp_c].iloc[i] = 1\n",
    "\n",
    "with_features.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 163
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 58560,
     "status": "ok",
     "timestamp": 1575754974441,
     "user": {
      "displayName": "Emmy Phung",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AAuE7mB0XMWxbfbNKbYDfXLX0_DPwLUNj1CQ0JzU4Gcd=s64",
      "userId": "15191778731511742618"
     },
     "user_tz": 300
    },
    "id": "uF2MLA31vawB",
    "outputId": "2e563d39-b99b-4c5a-9798-ede993a87071"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    3779.0\n",
       "mean        0.0\n",
       "std         0.0\n",
       "min         0.0\n",
       "25%         0.0\n",
       "50%         0.0\n",
       "75%         0.0\n",
       "max         0.0\n",
       "Name: Vegetarian, dtype: float64"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vegas_final = with_features.fillna(vegas_clean.mean())\n",
    "vegas_final['Vegetarian'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "45qEldZnnHqC"
   },
   "outputs": [],
   "source": [
    "vegas_final= vegas_final.rename(columns ={'Unnamed: 0': 'org_index'})\n",
    "vegas_final= vegas_final.drop(columns =['American (Traditional)', 'American (New)'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 33
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 60180,
     "status": "ok",
     "timestamp": 1575754976082,
     "user": {
      "displayName": "Emmy Phung",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AAuE7mB0XMWxbfbNKbYDfXLX0_DPwLUNj1CQ0JzU4Gcd=s64",
      "userId": "15191778731511742618"
     },
     "user_tz": 300
    },
    "id": "sc0oiGh1kNtT",
    "outputId": "271f0724-fc7d-4ce0-9439-da66560eec8c"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Check if there is null value\n",
    "def getDfSummary(input_data):\n",
    "    output_data=input_data.describe() \n",
    "    output_data.loc['number_distinct'] = input_data.nunique() \n",
    "    output_data.loc['number_nan'] = input_data.isna().sum()\n",
    "    output_data=output_data.drop('count', axis=0)\n",
    "    output_data=output_data.T\n",
    "    return output_data\n",
    "\n",
    "getDfSummary(vegas_final)['number_nan'].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 281
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 61090,
     "status": "ok",
     "timestamp": 1575754977002,
     "user": {
      "displayName": "Emmy Phung",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AAuE7mB0XMWxbfbNKbYDfXLX0_DPwLUNj1CQ0JzU4Gcd=s64",
      "userId": "15191778731511742618"
     },
     "user_tz": 300
    },
    "id": "C-1HaRIBeExc",
    "outputId": "bab7830f-de7b-4729-e9da-7aa66ecaf780"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0, 500)"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "vegas_final['review_count'].hist(bins=400)\n",
    "\n",
    "plt.xlim(0,500)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 285
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 61495,
     "status": "ok",
     "timestamp": 1575754977416,
     "user": {
      "displayName": "Emmy Phung",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AAuE7mB0XMWxbfbNKbYDfXLX0_DPwLUNj1CQ0JzU4Gcd=s64",
      "userId": "15191778731511742618"
     },
     "user_tz": 300
    },
    "id": "xZNHKPVMgmNS",
    "outputId": "7d6e2334-6387-4815-f083-1b825de1df07"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x12a324940>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "vegas_final['stars'].hist(bins=10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 98
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 61485,
     "status": "ok",
     "timestamp": 1575754977416,
     "user": {
      "displayName": "Emmy Phung",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AAuE7mB0XMWxbfbNKbYDfXLX0_DPwLUNj1CQ0JzU4Gcd=s64",
      "userId": "15191778731511742618"
     },
     "user_tz": 300
    },
    "id": "N7dVX0sjo3KC",
    "outputId": "ac026612-b99a-45de-9f00-262554eb081c"
   },
   "outputs": [],
   "source": [
    "#Create our target variable, named 'Sucess', Y = 1 if success, and = 0 otherwise\n",
    "vegas_final['success'] = 0\n",
    "success_list = vegas_final[(vegas_final['review_count']>100) & (vegas_final['stars']>4)].index.tolist()\n",
    "vegas_final['success'][success_list] = 1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "TpPvNK_TiqEp"
   },
   "source": [
    "**EDA by cuisines**\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 163
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 62499,
     "status": "ok",
     "timestamp": 1575754978439,
     "user": {
      "displayName": "Emmy Phung",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AAuE7mB0XMWxbfbNKbYDfXLX0_DPwLUNj1CQ0JzU4Gcd=s64",
      "userId": "15191778731511742618"
     },
     "user_tz": 300
    },
    "id": "ItK3_oD4om8U",
    "outputId": "32565381-dcd0-4e81-ade3-ad8aa7e61856"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    3779.0\n",
       "mean        0.0\n",
       "std         0.0\n",
       "min         0.0\n",
       "25%         0.0\n",
       "50%         0.0\n",
       "75%         0.0\n",
       "max         0.0\n",
       "Name: Vegan, dtype: float64"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vegas_final.describe()\n",
    "vegas_final['Vegan'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 160
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 62489,
     "status": "ok",
     "timestamp": 1575754978440,
     "user": {
      "displayName": "Emmy Phung",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AAuE7mB0XMWxbfbNKbYDfXLX0_DPwLUNj1CQ0JzU4Gcd=s64",
      "userId": "15191778731511742618"
     },
     "user_tz": 300
    },
    "id": "_Ozlkscwijfq",
    "outputId": "8cf46089-8b92-429c-ed13-f61fcd3a75e3"
   },
   "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>org_index</th>\n",
       "      <th>business_id</th>\n",
       "      <th>name</th>\n",
       "      <th>neighborhood</th>\n",
       "      <th>address</th>\n",
       "      <th>city</th>\n",
       "      <th>state</th>\n",
       "      <th>postal_code</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>...</th>\n",
       "      <th>Wholesale Stores</th>\n",
       "      <th>Wholesalers</th>\n",
       "      <th>Windshield Installation &amp; Repair</th>\n",
       "      <th>Wine &amp; Spirits</th>\n",
       "      <th>Wine Bars</th>\n",
       "      <th>Wineries</th>\n",
       "      <th>Women's Clothing</th>\n",
       "      <th>Yelp Events</th>\n",
       "      <th>Yoga</th>\n",
       "      <th>success</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>0 rows × 421 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [org_index, business_id, name, neighborhood, address, city, state, postal_code, latitude, longitude, stars, review_count, is_open, categories, hours, BusinessAcceptsCreditCards, BusinessParking_garage, BusinessParking_street, BusinessParking_validated, BusinessParking_lot, BusinessParking_valet, GoodForKids, WheelchairAccessible, BikeParking, Alcohol, HasTV, NoiseLevel, RestaurantsAttire, Music_dj, Caters, WiFi, RestaurantsReservations, RestaurantsTakeOut, HappyHour, GoodForDancing, RestaurantsTableService, OutdoorSeating, RestaurantsDelivery, BestNights_monday, BestNights_tuesday, BestNights_friday, BestNights_wednesday, BestNights_thursday, BestNights_sunday, BestNights_saturday, GoodForMeal_dessert, GoodForMeal_latenight, GoodForMeal_lunch, GoodForMeal_dinner, GoodForMeal_breakfast, GoodForMeal_brunch, CoatCheck, Smoking, DriveThru, DogsAllowed, BusinessAcceptsBitcoin, Open24Hours, BYOB, DietaryRestrictions_gluten-free, DietaryRestrictions_vegan, DietaryRestrictions_kosher, DietaryRestrictions_halal, DietaryRestrictions_soy-free, DietaryRestrictions_vegetarian, AgesAllowed, asian, european, namerica, samerica, other, class, Acai Bowls, Active Life, Acupuncture, Adult Entertainment, Afghan, African, Air Duct Cleaning, Aircraft Repairs, Airport Shuttles, Airport Terminals, Airports, Airsoft, Amusement Parks, Antiques, Appliances, Appliances & Repair, Aquarium Services, Aquariums, Arabian, Arcades, Argentine, Armenian, Art Galleries, Arts & Entertainment, Asian Fusion, Audio/Visual Equipment Rental, Auto Customization, Auto Glass Services, Auto Insurance, ...]\n",
       "Index: []\n",
       "\n",
       "[0 rows x 421 columns]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vegas_final[vegas_final['Vegan']==1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "N-z1mtNdqNml"
   },
   "outputs": [],
   "source": [
    "#Plot to compare the restaurants that have highest ratings (and total review counts) vs. lowest ones for each cuisine\n",
    "#Introduce the interaction term, 'total_stars' = 'review_count'*'stars'\n",
    "\n",
    "asian_df = vegas_final[vegas_final['asian']==True]\n",
    "european_df = vegas_final[vegas_final['european']==True]\n",
    "namerica_df = vegas_final[vegas_final['namerica']==True]\n",
    "samerica_df = vegas_final[vegas_final['samerica']==True]\n",
    "other_df = vegas_final[vegas_final['other']==True]\n",
    "\n",
    "def plot_totalstars (data):\n",
    "  fig,ax = plt.subplots(figsize =[6,6])\n",
    "  data['total_stars'] = data['stars']*data['review_count']\n",
    "  highstar = data[data['success']==1].sort_values(['total_stars'],ascending=False)\n",
    "  x = highstar['total_stars'].head(10)\n",
    "  y = highstar['name'].head(10)\n",
    "  plt.scatter(x,y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 1000
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 63762,
     "status": "ok",
     "timestamp": 1575754979725,
     "user": {
      "displayName": "Emmy Phung",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AAuE7mB0XMWxbfbNKbYDfXLX0_DPwLUNj1CQ0JzU4Gcd=s64",
      "userId": "15191778731511742618"
     },
     "user_tz": 300
    },
    "id": "9WZPEaZuxjW-",
    "outputId": "da316caf-1b9e-41f9-a376-e0375f3baad5"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Top 10 Un-classified Restaurants')"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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emd14QNJJwD3A+pLOkDQ/9ftR6jdG0h2S5km6RNKaqf0GSb+RdJekhyR9pqPiJH0DmAJ8MSKeT21nSNpT0iHASOB6Sdenbbukeu+VdG1uqE+m4z6a9iuNv2+qY66kv0gaktpfk/SrNM4dktbpi4vdl2Y1NjN1ZhPNrW0E0NzaxtSZTcxqbB7o0szM3jcHFNsMmNPBtjeBr0XElmRB5rg0YwJQB5wVEWOBtYDaiNgsIkYDp6c+ZwH/ExGbA03AUbmxh0bE1mQzIPn2vA2BE8nCyTPlGyPiBGAhsGNE7CipBjgV2CMitgC+nuu+CTAe2Bo4StIwSZ8AJgLbRcQYoB2YlPqvBtyRxrkJ+G4HNQ6Y6bMX0La4fam2tsXtTJ+9YIAqMjPrOw4o1hkBv5Y0D7gGqCW79QPwRETckR4/Cmws6U+SdgFekbQGUB0RN6Y+ZwKfzY09M/2eA4zq4PgtwL+Bb3Sz3m2AmyLiMYCIeDG37fKIWJRmYZ5L5/EFYCvgbklz0/ONU/+3gH90VqOkgyQ1SGpoaWnpZol9Z2FrW4/azcyWJw4odh/Zm3Qlk4AaYKs0w/AsMDxte73UKa0L2QK4Afg+8L/dOO6i9LudjtdCvQF8CThY0qQO+uQJiC6Olz+myNbejEk/dRFxdOqzOCKirP9SImJGRNRHRH1NTU03yutbI6uretRuZrY8cUCx64BVJL1zC0PSOEk7AGsAz0XEYkk7kt1yeQ9JawErRcTFwM+ALSPiZeCl3PqS/YAbK+3fmYhoAXYhm8kZX6HLq8Dq6fHtwA6SNkp1fbCL4a8F9pS0dqm/pIrnWESTx9dRNWzIUm1Vw4YweXzdAFVkZtZ3/C2eQS4iQtLXgD9ImkK27uRxsrUh9wGXSWoA5gIPdjBMLXC6pFLgnZp+7w+ckr4G/ChwYC9rfEzSfwBXSNq9bPMM4EpJT6d1KAcBM1MtzwE7dzLu/ZKOAK5O/ReTzQA90Zs6l7XSt3X8LR4zWxHp3VlsM+ut+vr6aGhoGOgyzMyWK5LmRER9pW2+xWNmZmaF44BiZmZmheOAYmZmZoXjgGJmZmaF44BiZmZmheOAYmZmZoXjgGJmZmaF44BiZmZmheOAYmZmZoXjgGJmZmaF44BiZmZmheOAYmZmZoXjgGJmZmaF44BiZmZmheOAYmZmZoXjgGJmZmaF44BiZmZmheOAYmZmZoXjgGJmZmaF44BiZmZmheOAYmZmZoXjgGJmZmaF44BiZmZmheOAYmZmZoXjgGJ9RtJPJd0naZ6kuZI+JelxSWtV6HtbPxz/aEnN6dhzJR2b21YjabGk7+Xa7kz9/i2pJbffKEnfktSUzmW+pK/2db1mZtaxoQNdgK0YJG0L7ApsGRGLUihZuaP+EfHpfirl+Ij4XYX2rwN3AHsDf0k1fApA0gFAfUT8ID1fD/gp2bm8LGkEUNNP9RbKrMZmps9ewMLWNkZWVzF5fB0TxtYOdFlmNgh5BsX6yrrA8xGxCCAino+IhaWNkqokXSXpu+n5a+n35yTdIOkiSQ9KOkeS0rbHJR0j6Z40m7GJpJUkPSypJvVZSdK/Ks3SlNkb+G9gPUldveOuDbwKvJbO5bWIeKzHV2Q5M6uxmakzm2hubSOA5tY2ps5sYlZj80CXZmaDkAOK9ZWrgfUlPSTpJEk75LaNAC4Dzo2IUyvsOxY4FPgksDGwXW7b8xGxJXAycFhELAHOBial7TsB90bE8+n5j3K3asYDSFof+HBE3AX8DZjYxbncCzwLPCbpdEm7desKLOemz15A2+L2pdraFrczffaCAarIzAYzBxTrExHxGrAVcBDQAlyQbp0A/B04PSLO6mD3uyLiqRQ+5gKjcttmpt9zcu2nAd9Mj78FnJ7rf3xEjEk/s1PbXmTBBOB8stmUzs6lHdgF2BN4CDhe0tHl/SQdJKlBUkNLS0tnQy4XFra29ajdzKw/OaBYn4mI9oi4ISKOAn4A7JE23Qp8qXTrpoJFucftLL02alF5e0Q8CTwr6fPAp4Aruyhtb+AASY8DlwJbSPpYF+cSEXFXREwjCzh7VOgzIyLqI6K+pmb5X6IysrqqR+1mZv3JAcX6hKS6sjf9McAT6fGRwAvASX14yP8lu9XztzTj0WFdwGoRURsRoyJiFFAKHR3tM1LSlrmm/LmssCaPr6Nq2JCl2qqGDWHy+LoBqsjMBjMHFOsrI4AzJd0vaR7ZepKjc9sPBYZL+m0fHe/SdMzTu+i3N3BJWdvFdH6bZxjwu7Rody7ZmpUf9rbQ5cWEsbVM2300tdVVCKitrmLa7qP9LR4zGxCKiIGuwazHJNWTrTf5zEDXAlBfXx8NDQ0DXYaZ2XJF0pyIqK+0zf8fFFvuSJoC/CfvfpPHzMxWML7FY8udiDg2IjaMiFsGuhYzM+sfDihmZmZWOA4oZmZmVjgOKGZmZlY4DihmZmZWOA4oZmZmVjgOKGZmZlY4DihmZmZWOA4oZmZmVjgOKGZmZlY4DihmZmZWOA4oZmZmVjgOKGZmZlY4DihmZmZWOA4oZmZmVjgOKGZmZlY4DihmZmZWOA4oZmZmVjgOKGZmZlY4DihmZmZWOA4oZmZmVjgOKGZmZlY4DihmZmZWOA4o1u8khaS/5p4PldQi6R/d2HdU2v8Xuba1JC2WdGJ/1Wwwq7GZ7Y69jo2mXM52x17HrMbmgS7JzAYRBxRbFl4HNpNUlZ7vDFR8t5M0tELzo8CuuedfB+7r0wptKbMam5k6s4nm1jYCaG5tY+rMJocUM1tmHFBsWbkS+Ep6vDdwXmmDpKMlzZB0NXBWhX3bgAck1afnE4G/5fbfTdKdkholXSNpndy4Z0q6WtLjknaX9FtJTZKukjQs9TtS0t2S5qc6lNoPkXS/pHmSzu/rC1Jk02cvoG1x+1JtbYvbmT57wQBVZGaDjQOKLSvnA3tJGg5sDtxZtn0r4KsRsU8X+68HtAMLc9tuAbaJiLGp3+G5bR8hC0ZfBc4Gro+I0WShpxSYToyIcRGxGVDFu7M1U4CxEbE5cHB5QZIOktQgqaGlpaXrK7AcWdja1qN2M7O+5oBiy0REzANGkc2eXFGhy6UR0dm731Vkt4b2Bi4o27YeMFtSEzAZ2DS37cqIWAw0AUPSOKTno9LjHdMMTBPw+dz+84BzJO0LvF3hnGZERH1E1NfU1HRS+vJnZHVVj9rNzPqaA4otS5cCvyN3eyfn9c52jIi3gDnAfwMXl23+E9ksyGjge8Dw3LZFaf8lwOKIiNS+BBiaZnROAvZM+5+a2/8rwJ/JZnfmdLA+ZoU0eXwdVcOGLNVWNWwIk8fXDVBFZjbYDJr/4FohnAa8HBFNkj7Xi/2PA26MiBfSMpGSNXh30e3+PRyzFEaelzQC2BO4SNJKwPoRcb2kW4B9gBFAay/qXu5MGFsLZGtRFra2MbK6isnj695pNzPrbw4otsxExFPAH9/H/vdR+ds7RwMXSmoG7gA26sGYrZJOJbvl8zhwd9o0BDhb0hqAgOMjYlCEk5IJY2sdSMxswOjdGW8z6636+vpoaGgY6DLMzJYrkuZERH2lbV6DYmZmZoXjgGJmZmaF44BiZmZmheOAYmZmZoXjgGJmZmaF44BiZmZmheOAYmZmZoXjgGJmZmaF44BiZmZmheOAYmZmZoXjgGJmZmaF44BiZmZmheOAYmZmZoXjgGJmZmaF44BiZmZmheOAYmZmZoXjgGJmZmaF44BiZmZmheOAYmZmZoXjgGJmZmaF44BiZmZmheOAYmZmZoXjgGJmZmaF44BiZmZmheOAYv1CUrukubmfKZ30PUDSie/jWJI0Q9L9kpokbdtJ3xskLZB0r6S7JY3JbbtCUnVv6xiMZjU2s92x17HRlMvZ7tjrmNXYPNAlmdkKYuhAF2ArrLaIGNN1tz6xPfAxYFOgCli9i/6TIqJB0oHAdGBngIj4cr9WuYKZ1djM1JlNtC1uB6C5tY2pM5sAmDC2diBLM7MVgGdQbJmSNE7SbWkG4y5JpTAxUtJVkh6W9Ntc/73TrMh8Sb/pYNi3gHWAYRHxRkQ8281ybgfeeSeV9LiktdLjn0l6UNI/JZ0n6bCen+2KbfrsBe+Ek5K2xe1Mn71ggCoysxWJA4r1l6qyWzwTJa0MXAD8MCK2AHYC2lL/McBEYDQwUdL6kkYCvwE+n7aPkzShwrGeBT4AnCFJPahxF2BWeaOkemAPYCywO1BfaWdJB0lqkNTQ0tLSg8OuGBa2tvWo3cysJxxQrL+0RcSY3M8FQB3wdETcDRARr0TE26n/tRHxckS8CdwPbAiMA26IiJbU7xzgsxWOdRHwBeAN4HgASSdJ+koHtZ0j6Sngf4A/Vdi+PfD3iGiLiFeByyoNEhEzIqI+Iupramq6vCArmpHVVT1qNzPrCQcUW5YERAfbFuUet5Otj+pyNkTS2sBaEbEA+B4wStJRZLMeN3Sw2yRgI+Bc4M8d1GldmDy+jqphQ5Zqqxo2hMnj6waoIjNbkTig2LL0INlak3EAklaX1NlC7TuBHSStJWkIsDdwY1mflmwo7RgR7cBBwA+BeyLi9Y4GjojFwBHANpI+Ubb5FmA3ScMljQA6mokZ1CaMrWXa7qOpra5CQG11FdN2H+0FsmbWJ/wtHusvVZLm5p5fFRFTJE0E/iSpimz9yU4dDRART0uaClxPNqtxRUT8vaxPSNoDOEHSqmS3eX4AHC5pz4i4qJPx2yQdBxwGfDvXfrekS4F7gSeABuDlHp39IDFhbK0DiZn1C0V0NONuNnhJGhERr6XQcxNwUETc01H/+vr6aGhoWHYFmpmtACTNiYiKX0TwDIpZZTMkfRIYDpzZWTgxM7O+54BiVkFE7DPQNZiZDWZeJGtmZmaF44BiZmZmheOAYmZmZoXjgGJmZmaF44BiZmZmheOAYmZmZoXjgGJmZmaF44BiZmZmheOAYmZmZoXjgGJmZmaF44BiZmZmheOAYmZmZoXjgGJmZmaF44BiZmZmheOAYmZmZoXjgGJmZmaF44BiZmZmheOAYmZmZoXjgGJmZmaF44BiZmZmheOAYmZmZoXjgGJmZmaF062AIum1/ji4pG0k3SlprqQHJB39PsaaLuk+SdP7oK6K5yupPdU6X9KFklbtoN8Vkqrfbx1lY64k6YR07CZJd0vaKG37yfsc+3FJa3XRZxVJs9KxGyVt3Enfb6V+81K9X03tB0ga+X5q7Q5JH09/g3+l19XfJK3Tg/1HSZrfnzUOFrMam9nu2OvYaMrlbHfsdcxqbB7oksxsOTF0gI9/JvCNiLhX0hCg7n2M9T2gJiIW9U1pFbVFxBgASecABwO/L22UJEAR8eV+OPZEYCSweUQskbQe8Hra9hPg1/1wzLxvAC9HxGhJawJRqVOq66fAlhHxsqQRQE3afAAwH1jYX0VKGg5cDvw4Ii5LbTumGp7N9RsaEW/3Vx2WhZOpM5toW9wOQHNrG1NnNgEwYWztQJZmZsuBbt/iUWZ67hP8xNy2yekT/TxJx6S21SRdLunetM/ECsOuDTwNEBHtEXF/bt/T0piNuU/goyTdLOme9PPp1H4psBpwp6SJkjaUdG2q51pJG6R+HbVvJOn2dLxfdPOS3Ax8NNX0gKSTgHuA9UszEmnbg5L+N12DcyTtJOlWSQ9L2rqz8y2zLvB0RCxJ1+upiHhJ0rFAVZrZOSeNt6+ku1LbX1L4Q9LJkhrSTNMxFf7GVZKukvTdCsd/C6iVpIh4KSJaO7guawOvAq+lOl+LiMck7QnUA+ekuqokfSGdb1M6/1VSHY9LOib9jZskbdKD67QPcHspnKQaro+I+WkG50JJlwFXSxqRXgel4+THGyrpzPRauUgdzJZZx6bPXvBOOClpW9zO9NkLBqgiM1ue9GQNyu7AGGALYCdguqR1JX0R+Biwddq+laTPArsACyNii4jYDLiqwpjHAwskXSLpe+nTL2SfwK+LiHHAjulYqwHPATtHxJZkMwonAETEf5BmNyLiAuBE4KyI2Bw4p9Svk/Y/Aien4z3T1YWQNBT4EtCUmurSuGMj4omy7h9N428ObEL2Bro9cBjZzEdn55v3N2C39OZ+nKSx6dyn5M59kqRPpGuzXZrtaQcmlY4TEfWplh0kbZ4bf8rRjSwAAB8RSURBVARwGXBuRJxa4bQfBbYCpnVxee4lm6l4TNLpknZLdV4ENACTUl0BnAFMjIjRZLN5/5kb5/n0dz45XavuXqfNgDmd1LctsH9EfB54E/haOs6OwHGSlPrVATPSa+UV4P+VDyTpoBT4GlpaWrq4LIPPwta2HrWbmeX1JKBsD5yXZjqeBW4ExgFfTD+NZDMIm5AFliZgJ0m/kfSZiHi5fMCI+DnZp+qryd64SyHmi8AUSXOBG4DhwAbAMOBUSU3AhcAnO6h1W+Dc9PivqfbO2rcDzsu1d6Qq1dQA/Bv4v9T+RETc0cE+j0VEU5r5uA+4NiKC7PqM6uJ83xERT5G9aU4FlgDXSvpCheN9gSxI3J3G+wJQWi/yDUn3kP2tNmXp6/d34PSIOKt8QElVZGFiU2CMpENT+xWSNi2rs50snO4JPAQcr8pri+rStXkoPT8T+Gxu+8z0ew49uE7d8M+IeLF0asCvJc0DrgFqgdJalScj4tb0+Gzefa28IyJmRER9RNTX1NSUbx70RlZX9ajdzCyvJ2tQ1En7tIj4y3s2SFsBXwamSbo6BZKlRMQjwMmSTgVaJH0ojblHRCwoG+9osk/nW5CFqze7WXvF9RJl7R31yXtnDUquJnh3LUgl+TUxS3LPl/Du9a94vu8pNltfcyVwpaRngQnAtWXdBJwZEVPL6tyIbCZiXLo1dAbZG3zJrcCXJJ2bAlTeaKAlIhZK2gO4RlIA1cD9FeoM4C7gLkn/BE4Hjq5QZ2dK16mdnl2n+4AdOtme/1tNIlubslVELJb0OO9ek/Jr0J3Xh+VMHl+31BoUgKphQ5g8/v0sNTOzwaInMyg3ARMlDZFUQ/Zp9y5gNvAtZYshkVQraW1l39Z4IyLOBn4HbFk+oKSv5KbUP0b2ZtSaxvyv0rbS7QxgDd5dh7EfMKSDWm8D9kqPJwG3dNF+a1n7stbR+b5D0pbpmiJpJbLbNKXbSYslDUuPrwX2lLR26vtBSRsCHyB7c35Z2TdavlR2iCOBF4CTKtT3MLCJpE0j4nXg28B04NLyMCNppKT833pMrs5XgdXT4weBUZI+mp7vRzYr15kurxPZDNmnJX0lV9MukkZX6LsG8FwKJzsCG+a2bSBp2/R4b959rVg3TRhby7TdR1NbXYWA2uoqpu0+2gtkzaxbupxBSestFgGXkN0iuZfs0+ThEfEM8Exa93B7et94DdiXbO3FdElLgMUsvb6gZD+yWwBvAG+TrU9oV7ZQ9Q/AvPRm9DiwK9mb58WSvg5cT8czF4cAp0maDLQAB3bR/kPgXEk/BC7u6pr0g47ON29tsttbq6Tnd5GtqQGYkfa9J61DOYJsEehKZNf++xFxh6RGshmGR8lCWblDya7PbyPi8FJjmnHZH/hrqu9lsiA3TdJNEXFbboxhwO9SmHqT7DofnLadAZwiqY3stXQgcGF6jd0NnPJ+r1NEtEnaFfiDpD+k859H9jcudw5wmaQGYC5ZaCp5ANhf0l/IAtrJXdRmFUwYW+tAYma9ovfO5pd1kLYATo2IrZdNSWbLn/r6+mhoaBjoMszMliuS5qQvb7xHp7d4JB1Mtnj0iP4ozMzMzKySTm/xRMQpdD3tbmZmZtan/G/xmJmZWeE4oJiZmVnhOKCYmZlZ4TigmJmZWeE4oJiZmVnhOKCYmZlZ4TigmJmZWeE4oJiZmVnhOKCYmZlZ4TigmJmZWeE4oJiZmVnhOKCYmZlZ4TigmJmZWeE4oJiZmVnhOKCYmZlZ4TigmJmZWeE4oJiZmVnhOKCYmZlZ4TigmJmZWeE4oJiZmVnhOKCYmZlZ4TigmJmZWeE4oPQzSe2S5kqaL+kySdVd9B8laX56/DlJ/0iP/0PSlB4e+6eS7pM0L9Xwqd6fyTtjvlNTL/YdJakt1XKvpNsk1fVijPm9Ob4NTrMam9nu2OvYaMrlbHfsdcxqbB7oksysGxxQ+l9bRIyJiM2AF4Hv92aQiLg0Io7tbn9J2wK7AltGxObATsCTvTl2H3skXY8tgDOBn3R3R0lD+q8sWxHNamxm6swmmlvbCKC5tY2pM5scUsyWAw4oy9btQC2AMtPTzEqTpImd7SjpAEknpsdnSDohzUA8KmnPCrusCzwfEYsAIuL5iFiY9n9c0q8l3S6pQdKWkmZLekTSwd2tT9I4SY2SNpa0mqTTJN2d2r7ajevxAeClNNYoSTdLuif9fDq1f07S9ZLOBZrSfkMlnZlmhi6StGrqu5WkGyXNSeezbq793nS+03MzVO9c0/T8H5I+lx5/MfW/R9KFkkZ043ysYKbPXkDb4val2toWtzN99oIBqsjMussBZRlJn/6/AFyamnYHxgBbkM1uTC+9oXbTusD2ZLMklWZWrgbWl/SQpJMk7VC2/cmI2Ba4GTgD2BPYBvh5d+pLAeIU4KsR8SjwU+C6iBgH7Jj6r1ahro+kWzyPAD8Gfp/anwN2jogtgYnACbl9tgZ+GhGfTM/rgBlpZugV4P9JGgb8CdgzIrYCTgN+lfqfDhySzrdLktYCjgB2SvU0pFrL+x2UAl5DS0tLd4a2ZWxha1uP2s2sOBxQ+l+VpLnAC8AHgX+m9u2B8yKiPSKeBW4ExvVg3FkRsSQi7gfWKd8YEa8BWwEHAS3ABZIOyHUpBaUm4M6IeDUiWoA30zqZzur7BDAD2C0i/p3avghMSed6AzAc2KBC3aVbPB8BDk3jAAwDTpXUBFwIfDK3z10R8Vju+ZMRcWt6fHaqtQ7YDPhnquEIYD1JawDVEXFj6v/XCjWV2yYd/9Y01v7AhuWdImJGRNRHRH1NTU03hrVlbWR1VY/azaw4hg50AYNAW0SMSW+U/yBbg3ICoPc57qLc44pjRUQ7WVi4Ib3x7082W5Lff0nZWEvIXhed1fc0WQAZCyzM1bBHRPRk7vxSstkNgB8Bz5LN2KwEvJnr93rZflHhuYD7ymdJUtgq71/yNkuH9OGl3YB/RsTe3TgHK7DJ4+uYOrNpqds8VcOGMHl8j9Zmm9kA8AzKMhIRLwOHAIel2xE3ARMlDZFUA3wWuKuvjiepTtLHck1jgCd6MERn9bUCXwF+XVqzAcwG/kuS0vHHduMY2wOPpMdrAE9HxBJgP6CzBbEbpEXAAHsDtwALgJpSu6RhkjaNiFbgZUnbp/6TcuM8DoyRtJKk9cluJQHcAWwn6aNprFUlfbwb52MFM2FsLdN2H01tdRUCaqurmLb7aCaMrR3o0sysC55BWYYiolHSvcBeZLcmtgXuJfuEf3hEPCNpVB8dbgTwpzSD8DbwL7LbPd11SQf1bZLO5VlJuwFXSvoW8AvgD8C8FFIeJ1sfU+4j6baJgLeA76T2k4CLJX0duJ73zprkPQDsL+kvwMPAyRHxVlosfEKarRqa6rkPOBA4TdIbZEGq5FbgMbLbXPOBe9K5taTbYedJWiX1PQJ4qItrZgU0YWytA4nZckgRHc1+m614UgD8R/rad5+pr6+PhoaGvhzSzGyFJ2lORNRX2uZbPGZmZlY4vsVjg0pEPE72bR8zMyswz6CYmZlZ4TigmJmZWeE4oJiZmVnhOKCYmZlZ4TigmJmZWeE4oJiZmVnhOKCYmZlZ4TigmJmZWeE4oJiZmVnhOKCYmZlZ4TigmJmZWeE4oJiZmVnhOKCYmZlZ4TigmJmZWeE4oJiZmVnhOKCYmZlZ4TigmJmZWeE4oJiZmVnhOKCYmZlZ4TigmJmZWeE4oJiZmVnhrFABRZlbJH0p1/YNSVf1crydJM1Kj38p6dAKfdaXdEE3xztb0oQK7dtJulPSXEkPSPpZL+v9oKSDK9XfXyStneqeK+kZSc2550M62Ge4pOc72Ha+pF17WMMPJC2QdJ+k73TS71hJT6XaHpR0giT15FhmZrZsDB3oAvpSRER6g75Q0vXAEOBXwC7d2V/SkIho7+ExnwQmVhhraES83c1hzgQmRMT89KZe15Macj4IHAyc0sv9l9Kdc4iI54Axqf8vgecj4g99cfzukFQF/AzYGGgD1u9il2Mj4sR0ne8AtgFu7+axevI3tUFkVmMz02cvYGFrGyOrq5g8vo4JY2sHuiyz5doKNYMCEBHzgcuA/wGOAs6KiEckXSZpTv5TtqShklrT7MhdwNaSvpI+jd8CfLVs+LGSrpf0sKRvpTE+KmluevydNAPwD+BKSStJOknS/ZIuA9bqoOwa4JlUf3tE3J/GW0vSpZLmSbpN0mapfanZnDQbsB5wLFCXZgiOTZtXlzQzndNZuX3GSboxXZMrJa2T2m+R9CtJNwE/SLM+f0zHf1TS13ry95B0Re66H1C27QRJjZJmS/pghX23kXRT2v8KSWtXOEQAKwMfjIglEfFEN0tbJe3Xmo71fUl3p2t9gaThqf18Sb+TdAPwi26fuA0asxqbmTqziebWNgJobm1j6swmZjU2D3RpZsu1FS6gJMcA+wBfAn6b2vaPiK2AccCPJa2Z2tcA7omIrYF7gb8AXwY+A4wsG3d0GnM74OelN/Uy2wL7RcTOwJ7ARsBmwH8Cn+6g3j8AD6cg8V1Jq6T2XwB3RsTmwNHAGV2c9xRgQUSMiYgpqW1L4PvAJ4FPpDf9VYA/Anuka3I2S7/5fiAiPpubCVk7nfMEYFoXNZTbNx1ja+B/JH0gtX8IuDEixgJzgJ/kd0oB4fdkM0tbAReQXYNyKwH3A3+XtEY36pmSAuVCYE5EPJDaz4+IcelaPwnsl9tnI+DzETG1G+PbIDN99gLaFi898dq2uJ3psxcMUEVmK4YVMqBExOtkb2h/jYhFqflHku4lm85fD/hIan8LuCQ9/iTwUEQ8EhEBnFM29KyIeDPd1riJLOyUuzoiXkqPPwuclz7ZPwXc0EG9R6WxrgG+CVyeNm0P/DX1uRoYKWm17lyDnDsi4ul062ouMAr4BLApcE16s57C0rdGzi8bY1Zk5gHdnrdO6zv+O13328iu+8Zp8yJgZnp8Ntm55m1G9ve4LtV4GJVv3xwHnAScTBZSVpH0TUkdzXYcGxFjgHXIrmdpRmhMmj1qAr5Odn1K/hYRSyqc30GSGiQ1tLS0dHQZbAW3sLWtR+1m1j0r1BqUMkvSD5J2IgsL20REW7p9Mzz1a0thpCToWPm2Sn1f70af9w4c8S/gX5JOBV5IswHlCzhLz99m6XA5nI4tyj1uJ/ubC5gXEZ/pYJ/yc8iP0ZNFpePJZpQ+FRFvSrqjk1rLr5OAxojYsRvHOCYinkkzWueRXZsjO9spIhZJmk02U3YJcBawU0Q8kNYxjcl1L78epTFmADMA6uvru/V3thXPyOoqmiuEkZHVVQNQjdmKY4WcQalgDeDFFE42pfLMB2S3Cj4uaaP06X/vsu0T0if0tcje2Bq6OO5NwF5pLUotsEOlTmndS+mN/+NkgeDVtP+k1Gcn4Kk0O/Q4sFVq35p3ZxZeBVbvoqbSedamfZG0croufW0N4IUUTkaT3W4qWYV31/jsA9xStu98YJSk0nmuLOmTFY7RCOyfHk8jm6XZAGjqrLB0vT8NPJIerwo8K2nlVI9Zt0weX0fVsKW/sFY1bAiTx/d2rbuZweAJKJcDq6ZbDUcCd1bqFBFvkH0L5krgZuDRsi53p223A0dFxLNdHPci4N9kb7YnkgWOSg4AFqRbGWcA+6RbCkcCn5Y0D/g5cGDqfyGwjqRG4NulOlM9DZKacotkK53nIrL1Mb9P16QR+FQX59IblwHV6Rg/Jbt+JS8A20q6h2x9ylJrWyKijexWywlp/3uoHCx/QHaN5pP9XS8GHgR+00FNpTUo88m+9fO/aQbtaLLAOTttM+uWCWNrmbb7aGqrqxBQW13FtN1H+1s8Zu+Tlr67YWa9UV9fHw0NXU2omZlZnqQ5EVFfadtgmUExMzOz5YgDipmZmRWOA4qZmZkVjgOKmZmZFY4DipmZmRWOA4qZmZkVjgOKmZmZFY4DipmZmRWOA4qZmZkVjgOKmZmZFY4DipmZmRWOA4qZmZkVjgOKmZmZFY4DipmZmRWOA4qZmZkVjgOKmZmZFY4DipmZmRWOA4qZmZkVjgOKmZmZFY4DipmZmRWOA4qZmZkVjgOKmZmZFY4DipmZmRWOA4qZmZkVjgOKFZqkdklzcz9T+mjcVSTNktQkqVHSxp30fVzSWn1xXDMz656hA12AWRfaImJMP4z7DeDliBgtaU0g+uEYNsjMamxm+uwFLGxtY2R1FZPH1zFhbO1Al2W2XHJAseWSpC8DvweeB+4BNo6IXSXVAOcCHwLuBnYBtoqI58uGeAuolaSIeGkZlm4rqFmNzUyd2UTb4nYAmlvbmDqzCcAhxawXfIvHiq6q7BbPREnDgb8AX4qI7YGaXP+jgOsiYkvgEmCDDsZ9FNgKmNafxdvgMX32gnfCSUnb4namz14wQBWZLd8cUKzo2iJiTO7nAmAT4NGIeCz1OS/Xf3vgfICIuAp4z+yIpCrgDGBTYIykQ1P7FZI27W5hkg6S1CCpoaWlpTfnZiuQha1tPWo3s845oNjySL3cVjIaaImIhcAewERJPwSqgfu7W0REzIiI+oior6mp6XoHW6GNrK7qUbuZdc4BxZZHDwIbSxqVnk/MbbuFbAEskr4IrFlh/4eBTSRtGhGvA98GpgOXRoQXy1qvTB5fR9WwIUu1VQ0bwuTxdQNUkdnyzYtkreiqJM3NPb8qIqZI+n/AVZKeB+7KbT8GOE/SROBG4Gng1fyAEfGSpP2Bv0oS8DIwCZgm6aaIuK0/T8hWTKWFsP4Wj1nfkD8w2vJI0oiIeC0FjD8DD0fE8ZJWAdoj4m1J2wIn99PXlJdSX18fDQ0N/X0YM7MViqQ5EVFfaZtnUGx59d00C7Iy0Ej2rR7IvrXzN0krkX2V+LsDVJ+Zmb0PDii2XIqI44HjK7Q/DIxd9hWZmVlf8iJZMzMzKxwHFDMzMyscBxQzMzMrHAcUMzMzKxwHFDMzMyscBxQzMzMrHAcUMzMzKxwHFDMzMyscBxQzMzMrHAcUMzMzKxwHFDMzMyscBxQzMzMrHAcUMzMzKxwHFDMzMyscBxQzMzMrHAcUMzMzKxwHFDMzMyscBxQzMzMrHAcUMzMzKxwHFDMzMyscBxQzMzMrHAcUMzMzKxwHlEFAUrukubmfKT3c/2hJh/Wgf42kOyU1SvpM2bZdU/u9ku6X9L2e1NIXNUo6WNI3O9n+OUn/6Iu6zMysd4YOdAG2TLRFxJje7CipN6+RLwAPRsT+ZWMNA2YAW0fEU5JWAUb1pq73IyJOWdbHNDNb0cxqbGb67AUsbG1jZHUVk8fXMWFsbZ+N7xmUQUzSkZLuljRf0gxJSu03SPq1pBuBH3ay/4aSrpU0L/3eQNIY4LfAl9NsTVVul9XJQvELABGxKCIWpLF2y826XCNpndR+tKTTUk2PSjokd/yfSlog6RqgLrWtLWlOeryFpJC0QXr+iKRV87Mtkj6ajnevpHskfSQNP0LSRZIelHRO6dqYmVkWTqbObKK5tY0AmlvbmDqziVmNzX12DAeUwaGq7BbPxNR+YkSMi4jNgCpg19w+1RGxQ0Qc18m4JwJnRcTmwDnACRExFzgSuCAixkREW6lzRLwIXAo8Iek8SZMklV6DtwDbRMRY4Hzg8NxxNgHGA1sDR0kaJmkrYC9gLLA7MC4d4zlguKQPAJ8BGoDPSNoQeC4i3ig7h3OAP0fEFsCngadT+1jgUOCTwMbAdp1cBzOzQWX67AW0LW5fqq1tcTvTZy/os2P4Fs/g0NEtnh0lHQ6sCnwQuA+4LG27oBvjbksWDgD+SjZz0qmI+I6k0cBOwGHAzsABwHrABZLWBVYGHsvtdnlELAIWSXoOWIcsfFxSChySLs31v40sUHwW+DWwCyDg5nwtklYHaiPiklTbm6kd4K6IeCo9n0t2K+qWsv0PAg4C2GCDDbo6dTOzFcbC1rYetfeGZ1AGKUnDgZOAPSNiNHAqMDzX5fVeDBvd6hTRFBHHk4WTPVLzn8hmdEYD3yurZVHucTvvBuuOjnczWYDZEPg7sAWwPXBTWb/Obtt0dMz8ecyIiPqIqK+pqelkKDOzFcvI6qoetfeGA8rgVQoAz0saAezZizFuI7vNAjCJshmGcpJGSPpcrmkM8ER6vAZQunm51OLaDtwEfE1SVZoJ2a1s277AwxGxBHgR+DJwa36AiHgFeErShFTfKpJW7caxzcwGtcnj66gaNmSptqphQ5g8vq7PjuFbPINDVbpNUXJVREyRdCrQBDwO3N2LcQ8BTpM0GWgBDuyiv4DDJf0FaCObpTkgbTsauFBSM3AHsFFnA0XE/2/v7mLlqsowjv+feGwBFWipKNpGqAkXcCPlWNGgUTBSqqHekJAQU8UbiyHSRE1JExO5ktZEQzSpJppYJdCqeEmkGgVMaMtp00IrHz39iBQagYAfV9jG14v1jmefYc/UMzPnzGp8fsnO7Fn7Y57zdvZ0zd5rZvZL2gEcoHRynmgsO5GXaTpnTP4ELI+IN1p29QXgR5LuBU4Dt57lbzAz+7/X+bTOfH6KRxH/01l5M+tjcnIypqamxh3DzOycImlfREy2LfMlHjMzM6uOOyhmZmZWHXdQzMzMrDruoJiZmVl13EExMzOz6riDYmZmZtVxB8XMzMyq4w6KmZmZVccdFDMzM6uOOyhmZmZWHX/VvdkISHqVmR8+XCjLgNcW+DHnovZ8UH9G5xte7Rlrzwfzm/EDEdH6c/DuoJidoyRN9foNixrUng/qz+h8w6s9Y+35YHwZfYnHzMzMquMOipmZmVXHHRSzc9ePxx3gLGrPB/VndL7h1Z6x9nwwpoweg2JmZmbV8RkUMzMzq447KGYVkbRR0mFJhyQ9KOk8SVdI2iPpiKQdkhbluovz/nQuv7yxn3uy/XlJNw2Z6aeSXpF0qNG2VNKuzLRL0pJsl6T787GflrSqsc36XP+IpPWN9mslPZPb3C9JI8i3VdJzmeE3ki5uLGutjaQ12TYtaVOjvbX+w+RrLPu6pJC0LO8veP36ZZR0V9bksKQtjfax11DShyTtlnRA0pSk1dk+jufgCkl/kPRs1upr2V7TcdIrYzXHyltEhCdPniqYgPcDx4Hz8/5O4It5e1u2bQM25PydwLacvw3YkfNXAQeBxcAVwFHgbUPk+gSwCjjUaNsCbMr5TcB9Ob8WeAQQcB2wJ9uXAsfydknOL8lle4GP5jaPADePIN9ngImcv6+Rr7U2OR0FVgKLcp2rGv8Ob6n/MPmyfQXwW8r35ywbV/361PBTwO+AxXn/0ppqCDza+Vuzbn8c43PwMmBVzr8LeCHrVNNx0itjNcdK9+QzKGZ1mQDOlzQBXACcAm4AfpXLfwZ8PufX5X1y+Y35rmod8FBEvBkRx4FpYPWggSLiceD1rubmY3dn2h7FbuBiSZcBNwG7IuL1iHgD2AWsyWUXRsSTUV7Vtjf2NXC+iHg0Is7k3d3A8ka+ttqsBqYj4lhE/At4CFiX9exV/4Hzpe8B3wSaAwEXvH59Mm4AvhMRb+Y6rzQy1lDDAC7M+YuAlxv5Fvo5eCoi9uf8P4FnKW84ajpOWjPWdKx0cwfFrBIR8RLwXeAvlI7J34F9wN8aLyAnKS985O2Lue2ZXP+SZnvLNqPynog4lY99Cri0O1PXY/drPznPWe+gvOMcJN8l9K7/wCTdArwUEQe7FtVUvyuBj+cp+8ckfXjAjPNSQ+BuYKukFynHzT0D5htpDVUutV4D7KHS46QrY1NVx4o7KGaVyOvT6yinU98HvAO4uWXVzjvutmvQ0ad9Icw107xmlbQZOAM80GmaY46R55N0AbAZ+Fbb4jnmmM/6TVAuM1wHfAPYme+Sa8m4AdgYESuAjcBPsn1s+SS9E/g1cHdE/KPfqnPMMu8ZazxW3EExq8engeMR8WpEnAYeBj5GOf07kessZ+ZU9knKOAZy+UWU0+D/bW/ZZlT+mqedydvO6f9ej92vfXlL+9BygOHngNvztPgg+V6jd/0H9UFKJ/SgpBO5z/2S3jtAvnmrX+774bwMsRf4N+U3WWqoIcB6yjEC8EtmLmOOpYaS3k75j/+BiOjkquo46ZGx3mNlmAEsnjx5Gt0EfAQ4TBl7Iso13LsoL77NgWd35vxXmT1IdmfOX83swW3HGGKQbO7zcmYPUNzK7MF/W3L+s8we/Lc325dSBgAvyek4sDSXPZXrdgb/rR1BvjXAn4F3d63XWhvK2YJj2dYZ+Hd1btNa/2HydS07wcwg2bHUr0cNvwLcm/NXUk7rq5YaUsZQfDLnbwT2jauGud124Ptd7dUcJ30yVnWszMowzMaePHka7QR8G3gOOAT8PF8cVlJG8E/nC0DnUxXn5f3pXL6ysZ/NlJH2zzPApzq6Mj1IGRNzmvLu6cuU682/B47kbedFVMAP87GfASYb+7kjs04DX2q0T+bfexT4AfkFkkPmm6b8h3ogp21nqw3lkxUv5LLNjfbW+g+Tr2v5CWY6KAtevz41XAT8Ive9H7ihphoC11PGaB2kjKW4dozPwesplzOebjzn1lLXcdIrYzXHSvfkb5I1MzOz6ngMipmZmVXHHRQzMzOrjjsoZmZmVh13UMzMzKw67qCYmZlZddxBMTMzs+q4g2JmZmbVcQfFzMzMqvMfNPHuTCYxIUQAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(1)\n",
    "plot_totalstars(asian_df)\n",
    "plt.title('Top 10 Asian Restaurants')\n",
    "\n",
    "plt.figure(2)\n",
    "plot_totalstars(european_df)\n",
    "plt.title('Top 10 European Restaurants')\n",
    "\n",
    "plt.figure(3)\n",
    "plot_totalstars(namerica_df)\n",
    "plt.title('Top 10 North American Restaurants')\n",
    "\n",
    "plt.figure(4)\n",
    "plot_totalstars(samerica_df)\n",
    "plt.title('Top 10 South American Restaurants')\n",
    "\n",
    "plt.figure(5)\n",
    "plot_totalstars(other_df)\n",
    "plt.title('Top 10 Un-classified Restaurants')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "TMWo5aItsfpq"
   },
   "outputs": [],
   "source": [
    "# lowstar = vegas_final[vegas_final['success']==0].sort_values(['total_stars'],ascending=True)\n",
    "# y2 = lowstar['stars'].head(15)\n",
    "# x2 = lowstar['name'].head(15)\n",
    "# plt.scatter(y2,x2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 336
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 64425,
     "status": "ok",
     "timestamp": 1575754980406,
     "user": {
      "displayName": "Emmy Phung",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AAuE7mB0XMWxbfbNKbYDfXLX0_DPwLUNj1CQ0JzU4Gcd=s64",
      "userId": "15191778731511742618"
     },
     "user_tz": 300
    },
    "id": "m4wtpelKNy1p",
    "outputId": "20154f61-f2c6-482d-8e17-5b469374a948"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x125192b00>"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1440x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Plot reviews and stars\n",
    "fig,ax = plt.subplots(figsize =[20,5])\n",
    "\n",
    "xA_stars, yA_reviews = vegas_final[vegas_final['asian']==True]['stars'].values, vegas_final[vegas_final['asian']==True]['review_count'].values\n",
    "xE_stars, yE_reviews = vegas_final[vegas_final['european']==True]['stars'].values, vegas_final[vegas_final['european']==True]['review_count'].values\n",
    "xNA_stars,yNA_reviews = vegas_final[vegas_final['namerica']==True]['stars'].values, vegas_final[vegas_final['namerica']==True]['review_count'].values\n",
    "xSA_stars, ySA_reviews = vegas_final[vegas_final['samerica']==True]['stars'].values,vegas_final[vegas_final['samerica']==True]['review_count'].values\n",
    "xO_stars,yO_reviews = vegas_final[vegas_final['other']==True]['stars'].values, vegas_final[vegas_final['other']==True]['review_count'].values\n",
    "\n",
    "\n",
    "plt.scatter(yE_reviews,xE_stars, marker='^',color = 'b')\n",
    "plt.scatter(yNA_reviews,xNA_stars, marker='>',color = 'g')\n",
    "plt.scatter(ySA_reviews,xSA_stars, marker='<',color = 'm')\n",
    "plt.scatter(yA_reviews, xA_stars,color = 'r')\n",
    "\n",
    "# plt.bar(yE_reviews,xE_stars,color = 'b')\n",
    "# plt.bar(yNA_reviews,xNA_stars,color = 'g')\n",
    "# plt.bar(ySA_reviews,xSA_stars,color = 'm')\n",
    "# plt.bar(yA_reviews, xA_stars,color = 'r')\n",
    "\n",
    "# for i, txt in enumerate(z_name):\n",
    "#   if (y_reviews.iloc[i]>2500 and x_stars.iloc[i]>=4.0):\n",
    "#     plt.annotate(txt, (y_reviews.iloc[i], x_stars.iloc[i]),xytext=(-5, 10), textcoords='offset points',ha = 'left',va='bottom', rotation=45 )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 1000
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 1039,
     "status": "ok",
     "timestamp": 1575755114137,
     "user": {
      "displayName": "Emmy Phung",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AAuE7mB0XMWxbfbNKbYDfXLX0_DPwLUNj1CQ0JzU4Gcd=s64",
      "userId": "15191778731511742618"
     },
     "user_tz": 300
    },
    "id": "ab12yuR30zCz",
    "outputId": "61a4c979-5cfd-4831-96ad-f1cb05371070"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Number of restaurants grouped by cuisine')"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(1)\n",
    "x = ['european','namerica','samerica','asian']\n",
    "y = [yE_reviews.mean(), yNA_reviews.mean(),ySA_reviews.mean(),yA_reviews.mean()]\n",
    "plt.bar(x,y)\n",
    "\n",
    "\n",
    "plt.figure(2)\n",
    "y2 = [yE_reviews.max(), yNA_reviews.max(),ySA_reviews.max(),yA_reviews.max()]\n",
    "plt.bar(x,y2)\n",
    "\n",
    "\n",
    "plt.figure(3)\n",
    "y3 = [xE_stars.mean(), xNA_stars.mean(), xSA_stars.mean(), xA_stars.mean()]\n",
    "plt.bar(x,y3)\n",
    "\n",
    "\n",
    "plt.figure(4)\n",
    "x = ['European','South America','Asian','North America','Others']\n",
    "y4 = [len(yE_reviews),len(ySA_reviews),len(yA_reviews),len(yNA_reviews), len(yO_reviews)]\n",
    "plt.bar(x,y4)\n",
    "plt.title('Number of restaurants grouped by cuisine')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 281
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 691,
     "status": "ok",
     "timestamp": 1575755834247,
     "user": {
      "displayName": "Emmy Phung",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AAuE7mB0XMWxbfbNKbYDfXLX0_DPwLUNj1CQ0JzU4Gcd=s64",
      "userId": "15191778731511742618"
     },
     "user_tz": 300
    },
    "id": "uVMOalBsRzzc",
    "outputId": "5b70736f-c6fe-4f32-9303-91df5913a5de"
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = ['European','South America','Asian','North America']\n",
    "df = pd.DataFrame([x,y,y3]).T\n",
    "\n",
    "df[1].plot(kind ='bar',color ='c')\n",
    "plt.ylabel('Number of reviews')\n",
    "df[2].plot(secondary_y=True)\n",
    "plt.ylabel('Average rating')\n",
    "# plt.title('Restaurants grouped by cuisine')\n",
    "plt.xticks(np.arange(4), x)\n",
    "plt.title('Average rating and review counts by cuisine')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 585
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 608,
     "status": "ok",
     "timestamp": 1575754997213,
     "user": {
      "displayName": "Emmy Phung",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AAuE7mB0XMWxbfbNKbYDfXLX0_DPwLUNj1CQ0JzU4Gcd=s64",
      "userId": "15191778731511742618"
     },
     "user_tz": 300
    },
    "id": "ZrlFhuF_NVa_",
    "outputId": "6c25bf31-7253-4edc-8429-b3606467adfd"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<BarContainer object of 5 artists>"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Compare average stars and reviews per cuisine group\n",
    "fig = plt.subplots(figsize =[5,5])\n",
    "\n",
    "x = [xA_stars.mean(), xE_stars.mean(),xNA_stars.mean(), xSA_stars.mean(), xO_stars.mean()]\n",
    "y = [yA_reviews.mean(),yE_reviews.mean(), yNA_reviews.mean(), ySA_reviews.mean(), yO_reviews.mean()]\n",
    "z = ['A','E','NA','SA','O']\n",
    "plt.figure(1)\n",
    "plt.bar(z,x)\n",
    "plt.figure(2)\n",
    "plt.bar(z,y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "bC_ENJGN_f2j"
   },
   "outputs": [],
   "source": [
    "vegas_final.replace(0.5, 0, inplace=True)\n",
    "\n",
    "#Export clean data to csv\n",
    "vegas_final.to_csv('/Users/lisacombs/Documents/FALL2019/INTRO_DS/Project/clean_data/vegas_cuisine.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "dqjcHP46ScdM"
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>org_index</th>\n",
       "      <th>business_id</th>\n",
       "      <th>name</th>\n",
       "      <th>neighborhood</th>\n",
       "      <th>address</th>\n",
       "      <th>city</th>\n",
       "      <th>state</th>\n",
       "      <th>postal_code</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>...</th>\n",
       "      <th>Wholesale Stores</th>\n",
       "      <th>Wholesalers</th>\n",
       "      <th>Windshield Installation &amp; Repair</th>\n",
       "      <th>Wine &amp; Spirits</th>\n",
       "      <th>Wine Bars</th>\n",
       "      <th>Wineries</th>\n",
       "      <th>Women's Clothing</th>\n",
       "      <th>Yelp Events</th>\n",
       "      <th>Yoga</th>\n",
       "      <th>success</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>32</td>\n",
       "      <td>kgffcoxT6BQp-gJ-UQ7Czw</td>\n",
       "      <td>Subway</td>\n",
       "      <td>Summerlin</td>\n",
       "      <td>2255 N Rampart Blvd</td>\n",
       "      <td>Las Vegas</td>\n",
       "      <td>NV</td>\n",
       "      <td>89128</td>\n",
       "      <td>36.201794</td>\n",
       "      <td>-115.281981</td>\n",
       "      <td>...</td>\n",
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       "      <td>Omelet House Summerlin</td>\n",
       "      <td>Summerlin</td>\n",
       "      <td>2227 N Rampart Blvd</td>\n",
       "      <td>Las Vegas</td>\n",
       "      <td>NV</td>\n",
       "      <td>89128</td>\n",
       "      <td>36.201990</td>\n",
       "      <td>-115.283122</td>\n",
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       "      <td>141</td>\n",
       "      <td>zhxnD7J5_sCrKSw5cwI9dQ</td>\n",
       "      <td>Popeyes Louisiana Kitchen</td>\n",
       "      <td>Sunrise</td>\n",
       "      <td>4505 E Bonanza Rd</td>\n",
       "      <td>Las Vegas</td>\n",
       "      <td>NV</td>\n",
       "      <td>89110</td>\n",
       "      <td>36.173140</td>\n",
       "      <td>-115.077945</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>34</td>\n",
       "      <td>143</td>\n",
       "      <td>2kWrSFkIes_d2BMg4YrRtA</td>\n",
       "      <td>Pizza Hut</td>\n",
       "      <td>Sunrise</td>\n",
       "      <td>560 N. Nellis Blvd, Ste E1</td>\n",
       "      <td>Las Vegas</td>\n",
       "      <td>NV</td>\n",
       "      <td>89110</td>\n",
       "      <td>36.169353</td>\n",
       "      <td>-115.061694</td>\n",
       "      <td>...</td>\n",
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       "      <td>145</td>\n",
       "      <td>6llKs7K_tn8ChXcIM-oTvg</td>\n",
       "      <td>Sansei Japan</td>\n",
       "      <td>Eastside</td>\n",
       "      <td>3480 S Maryland Pkwy</td>\n",
       "      <td>Las Vegas</td>\n",
       "      <td>NV</td>\n",
       "      <td>89169</td>\n",
       "      <td>36.125934</td>\n",
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       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 421 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    org_index             business_id                       name neighborhood  \\\n",
       "8          32  kgffcoxT6BQp-gJ-UQ7Czw                     Subway    Summerlin   \n",
       "9          33  0jtRI7hVMpQHpUVtUy4ITw     Omelet House Summerlin    Summerlin   \n",
       "32        141  zhxnD7J5_sCrKSw5cwI9dQ  Popeyes Louisiana Kitchen      Sunrise   \n",
       "34        143  2kWrSFkIes_d2BMg4YrRtA                  Pizza Hut      Sunrise   \n",
       "35        145  6llKs7K_tn8ChXcIM-oTvg               Sansei Japan     Eastside   \n",
       "\n",
       "                       address       city state postal_code   latitude  \\\n",
       "8          2255 N Rampart Blvd  Las Vegas    NV       89128  36.201794   \n",
       "9          2227 N Rampart Blvd  Las Vegas    NV       89128  36.201990   \n",
       "32           4505 E Bonanza Rd  Las Vegas    NV       89110  36.173140   \n",
       "34  560 N. Nellis Blvd, Ste E1  Las Vegas    NV       89110  36.169353   \n",
       "35        3480 S Maryland Pkwy  Las Vegas    NV       89169  36.125934   \n",
       "\n",
       "     longitude  ...  Wholesale Stores  Wholesalers  \\\n",
       "8  -115.281981  ...                 0            0   \n",
       "9  -115.283122  ...                 0            0   \n",
       "32 -115.077945  ...                 0            0   \n",
       "34 -115.061694  ...                 0            0   \n",
       "35 -115.135253  ...                 0            0   \n",
       "\n",
       "    Windshield Installation & Repair Wine & Spirits Wine Bars  Wineries  \\\n",
       "8                                  0              0         0         0   \n",
       "9                                  0              0         0         0   \n",
       "32                                 0              0         0         0   \n",
       "34                                 0              0         0         0   \n",
       "35                                 0              0         0         0   \n",
       "\n",
       "    Women's Clothing  Yelp Events  Yoga  success  \n",
       "8                  0            0     0        0  \n",
       "9                  0            0     0        0  \n",
       "32                 0            0     0        0  \n",
       "34                 0            0     0        0  \n",
       "35                 0            0     0        0  \n",
       "\n",
       "[5 rows x 421 columns]"
      ]
     },
     "execution_count": 39,
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    }
   ],
   "source": [
    "vegas_final.head(5)"
   ]
  }
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