02-EDA.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Importing Dependencies"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To start our analysis we need to import our dependencies to assist with analysing the data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Load dataset and save as 'wine' variable"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "After importing all dependencies we load our dataset called wine."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "wine = pd.read_json('./wine-reviews/winemag-data-130k-v2.json', dtype='unicode');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Reviewing dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>country</th>\n",
       "      <th>description</th>\n",
       "      <th>designation</th>\n",
       "      <th>points</th>\n",
       "      <th>price</th>\n",
       "      <th>province</th>\n",
       "      <th>region_1</th>\n",
       "      <th>region_2</th>\n",
       "      <th>taster_name</th>\n",
       "      <th>taster_twitter_handle</th>\n",
       "      <th>title</th>\n",
       "      <th>variety</th>\n",
       "      <th>winery</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Italy</td>\n",
       "      <td>Aromas include tropical fruit, broom, brimston...</td>\n",
       "      <td>Vulkà Bianco</td>\n",
       "      <td>87</td>\n",
       "      <td>nan</td>\n",
       "      <td>Sicily &amp; Sardinia</td>\n",
       "      <td>Etna</td>\n",
       "      <td>None</td>\n",
       "      <td>Kerin O’Keefe</td>\n",
       "      <td>@kerinokeefe</td>\n",
       "      <td>Nicosia 2013 Vulkà Bianco  (Etna)</td>\n",
       "      <td>White Blend</td>\n",
       "      <td>Nicosia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Portugal</td>\n",
       "      <td>This is ripe and fruity, a wine that is smooth...</td>\n",
       "      <td>Avidagos</td>\n",
       "      <td>87</td>\n",
       "      <td>15.0</td>\n",
       "      <td>Douro</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Roger Voss</td>\n",
       "      <td>@vossroger</td>\n",
       "      <td>Quinta dos Avidagos 2011 Avidagos Red (Douro)</td>\n",
       "      <td>Portuguese Red</td>\n",
       "      <td>Quinta dos Avidagos</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>US</td>\n",
       "      <td>Tart and snappy, the flavors of lime flesh and...</td>\n",
       "      <td>None</td>\n",
       "      <td>87</td>\n",
       "      <td>14.0</td>\n",
       "      <td>Oregon</td>\n",
       "      <td>Willamette Valley</td>\n",
       "      <td>Willamette Valley</td>\n",
       "      <td>Paul Gregutt</td>\n",
       "      <td>@paulgwine</td>\n",
       "      <td>Rainstorm 2013 Pinot Gris (Willamette Valley)</td>\n",
       "      <td>Pinot Gris</td>\n",
       "      <td>Rainstorm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>US</td>\n",
       "      <td>Pineapple rind, lemon pith and orange blossom ...</td>\n",
       "      <td>Reserve Late Harvest</td>\n",
       "      <td>87</td>\n",
       "      <td>13.0</td>\n",
       "      <td>Michigan</td>\n",
       "      <td>Lake Michigan Shore</td>\n",
       "      <td>None</td>\n",
       "      <td>Alexander Peartree</td>\n",
       "      <td>None</td>\n",
       "      <td>St. Julian 2013 Reserve Late Harvest Riesling ...</td>\n",
       "      <td>Riesling</td>\n",
       "      <td>St. Julian</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>US</td>\n",
       "      <td>Much like the regular bottling from 2012, this...</td>\n",
       "      <td>Vintner's Reserve Wild Child Block</td>\n",
       "      <td>87</td>\n",
       "      <td>65.0</td>\n",
       "      <td>Oregon</td>\n",
       "      <td>Willamette Valley</td>\n",
       "      <td>Willamette Valley</td>\n",
       "      <td>Paul Gregutt</td>\n",
       "      <td>@paulgwine</td>\n",
       "      <td>Sweet Cheeks 2012 Vintner's Reserve Wild Child...</td>\n",
       "      <td>Pinot Noir</td>\n",
       "      <td>Sweet Cheeks</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    country                                        description  \\\n",
       "0     Italy  Aromas include tropical fruit, broom, brimston...   \n",
       "1  Portugal  This is ripe and fruity, a wine that is smooth...   \n",
       "2        US  Tart and snappy, the flavors of lime flesh and...   \n",
       "3        US  Pineapple rind, lemon pith and orange blossom ...   \n",
       "4        US  Much like the regular bottling from 2012, this...   \n",
       "\n",
       "                          designation points price           province  \\\n",
       "0                        Vulkà Bianco     87   nan  Sicily & Sardinia   \n",
       "1                            Avidagos     87  15.0              Douro   \n",
       "2                                None     87  14.0             Oregon   \n",
       "3                Reserve Late Harvest     87  13.0           Michigan   \n",
       "4  Vintner's Reserve Wild Child Block     87  65.0             Oregon   \n",
       "\n",
       "              region_1           region_2         taster_name  \\\n",
       "0                 Etna               None       Kerin O’Keefe   \n",
       "1                 None               None          Roger Voss   \n",
       "2    Willamette Valley  Willamette Valley        Paul Gregutt   \n",
       "3  Lake Michigan Shore               None  Alexander Peartree   \n",
       "4    Willamette Valley  Willamette Valley        Paul Gregutt   \n",
       "\n",
       "  taster_twitter_handle                                              title  \\\n",
       "0          @kerinokeefe                  Nicosia 2013 Vulkà Bianco  (Etna)   \n",
       "1            @vossroger      Quinta dos Avidagos 2011 Avidagos Red (Douro)   \n",
       "2           @paulgwine       Rainstorm 2013 Pinot Gris (Willamette Valley)   \n",
       "3                  None  St. Julian 2013 Reserve Late Harvest Riesling ...   \n",
       "4           @paulgwine   Sweet Cheeks 2012 Vintner's Reserve Wild Child...   \n",
       "\n",
       "          variety               winery  \n",
       "0     White Blend              Nicosia  \n",
       "1  Portuguese Red  Quinta dos Avidagos  \n",
       "2      Pinot Gris            Rainstorm  \n",
       "3        Riesling           St. Julian  \n",
       "4      Pinot Noir         Sweet Cheeks  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wine.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Looking at data index to see how many rows the dataset contains"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "RangeIndex(start=0, stop=129971, step=1)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wine.index"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Looking at data column names and how many columns are in the dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['country', 'description', 'designation', 'points', 'price', 'province',\n",
       "       'region_1', 'region_2', 'taster_name', 'taster_twitter_handle', 'title',\n",
       "       'variety', 'winery'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wine.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Reviewing shape of dataset to see the amount of rows and columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(129971, 13)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wine.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Reviewing data types to understand the various types of data are within the dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 129971 entries, 0 to 129970\n",
      "Data columns (total 13 columns):\n",
      "country                  129971 non-null object\n",
      "description              129971 non-null object\n",
      "designation              129971 non-null object\n",
      "points                   129971 non-null object\n",
      "price                    129971 non-null object\n",
      "province                 129971 non-null object\n",
      "region_1                 129971 non-null object\n",
      "region_2                 129971 non-null object\n",
      "taster_name              129971 non-null object\n",
      "taster_twitter_handle    129971 non-null object\n",
      "title                    129971 non-null object\n",
      "variety                  129971 non-null object\n",
      "winery                   129971 non-null object\n",
      "dtypes: object(13)\n",
      "memory usage: 12.9+ MB\n"
     ]
    }
   ],
   "source": [
    "wine.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Reviewing if there are any null values or values without any input"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "country                  0\n",
       "description              0\n",
       "designation              0\n",
       "points                   0\n",
       "price                    0\n",
       "province                 0\n",
       "region_1                 0\n",
       "region_2                 0\n",
       "taster_name              0\n",
       "taster_twitter_handle    0\n",
       "title                    0\n",
       "variety                  0\n",
       "winery                   0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wine.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "What are the total unique categories?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total Unique Countries: 44\n",
      "Total Unique Designations: 37980\n",
      "Total Unique Province: 426\n",
      "Total Unique Region 1: 1230\n",
      "Total Unique Region 2: 18\n",
      "Total Unique Variety: 708\n"
     ]
    }
   ],
   "source": [
    "print('Total Unique Countries:', len(wine['country'].unique().tolist()))\n",
    "print('Total Unique Designations:', len(wine['designation'].unique().tolist()))\n",
    "print('Total Unique Province:', len(wine['province'].unique().tolist()))\n",
    "print('Total Unique Region 1:', len(wine['region_1'].unique().tolist()))\n",
    "print('Total Unique Region 2:', len(wine['region_2'].unique().tolist()))\n",
    "print('Total Unique Variety:', len(wine['variety'].unique().tolist()))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Changing points and price columns to integar and float after noticing that those values were not the appropriate dtype. This will assist with further analysis to understand the relationships between variables."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>country</th>\n",
       "      <th>description</th>\n",
       "      <th>designation</th>\n",
       "      <th>points</th>\n",
       "      <th>price</th>\n",
       "      <th>province</th>\n",
       "      <th>region_1</th>\n",
       "      <th>region_2</th>\n",
       "      <th>taster_name</th>\n",
       "      <th>taster_twitter_handle</th>\n",
       "      <th>title</th>\n",
       "      <th>variety</th>\n",
       "      <th>winery</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Italy</td>\n",
       "      <td>Aromas include tropical fruit, broom, brimston...</td>\n",
       "      <td>Vulkà Bianco</td>\n",
       "      <td>87</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Sicily &amp; Sardinia</td>\n",
       "      <td>Etna</td>\n",
       "      <td>None</td>\n",
       "      <td>Kerin O’Keefe</td>\n",
       "      <td>@kerinokeefe</td>\n",
       "      <td>Nicosia 2013 Vulkà Bianco  (Etna)</td>\n",
       "      <td>White Blend</td>\n",
       "      <td>Nicosia</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      ],
      "text/plain": [
       "  country                                        description   designation  \\\n",
       "0   Italy  Aromas include tropical fruit, broom, brimston...  Vulkà Bianco   \n",
       "\n",
       "   points  price           province region_1 region_2    taster_name  \\\n",
       "0      87    NaN  Sicily & Sardinia     Etna     None  Kerin O’Keefe   \n",
       "\n",
       "  taster_twitter_handle                              title      variety  \\\n",
       "0          @kerinokeefe  Nicosia 2013 Vulkà Bianco  (Etna)  White Blend   \n",
       "\n",
       "    winery  \n",
       "0  Nicosia  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wine['points'] = wine.points.astype(int)\n",
    "wine['price'] = wine.price.astype(float)\n",
    "wine.head(1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Confirming updated dtypes were changed from the function above"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "country                   object\n",
       "description               object\n",
       "designation               object\n",
       "points                     int64\n",
       "price                    float64\n",
       "province                  object\n",
       "region_1                  object\n",
       "region_2                  object\n",
       "taster_name               object\n",
       "taster_twitter_handle     object\n",
       "title                     object\n",
       "variety                   object\n",
       "winery                    object\n",
       "dtype: object"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wine.dtypes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Rechecking if there are any null values after dtype change from object to integar and float"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "country                     0\n",
       "description                 0\n",
       "designation                 0\n",
       "points                      0\n",
       "price                    8996\n",
       "province                    0\n",
       "region_1                    0\n",
       "region_2                    0\n",
       "taster_name                 0\n",
       "taster_twitter_handle       0\n",
       "title                       0\n",
       "variety                     0\n",
       "winery                      0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wine.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Currently looking for duplicate wines. \n",
    "No duplicates due to designation and variety"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>country</th>\n",
       "      <th>description</th>\n",
       "      <th>designation</th>\n",
       "      <th>points</th>\n",
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       "      <th>province</th>\n",
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       "      <th>taster_twitter_handle</th>\n",
       "      <th>title</th>\n",
       "      <th>variety</th>\n",
       "      <th>winery</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>93375</th>\n",
       "      <td>Spain</td>\n",
       "      <td>Dusty notes of citrus fruits are mild but frie...</td>\n",
       "      <td>Brut</td>\n",
       "      <td>87</td>\n",
       "      <td>16.0</td>\n",
       "      <td>Catalonia</td>\n",
       "      <td>Cava</td>\n",
       "      <td>None</td>\n",
       "      <td>Michael Schachner</td>\n",
       "      <td>@wineschach</td>\n",
       "      <td>1+1=3 NV Brut Sparkling (Cava)</td>\n",
       "      <td>Sparkling Blend</td>\n",
       "      <td>1+1=3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56109</th>\n",
       "      <td>Spain</td>\n",
       "      <td>Clean, fresh apple aromas and a minerally, cit...</td>\n",
       "      <td>Cygnus Brut Nature Reserva Made With Organic G...</td>\n",
       "      <td>89</td>\n",
       "      <td>20.0</td>\n",
       "      <td>Catalonia</td>\n",
       "      <td>Cava</td>\n",
       "      <td>None</td>\n",
       "      <td>Michael Schachner</td>\n",
       "      <td>@wineschach</td>\n",
       "      <td>1+1=3 NV Cygnus Brut Nature Reserva Made With ...</td>\n",
       "      <td>Sparkling Blend</td>\n",
       "      <td>1+1=3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100235</th>\n",
       "      <td>US</td>\n",
       "      <td>Merlot, Cabernet and Syrah form the core of th...</td>\n",
       "      <td>Hot To Trot</td>\n",
       "      <td>86</td>\n",
       "      <td>10.0</td>\n",
       "      <td>Washington</td>\n",
       "      <td>Columbia Valley (WA)</td>\n",
       "      <td>Columbia Valley</td>\n",
       "      <td>Paul Gregutt</td>\n",
       "      <td>@paulgwine</td>\n",
       "      <td>14 Hands 2011 Hot To Trot Red (Columbia Valley...</td>\n",
       "      <td>Red Blend</td>\n",
       "      <td>14 Hands</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68750</th>\n",
       "      <td>US</td>\n",
       "      <td>In just a few years 14 Hands Riesling producti...</td>\n",
       "      <td>None</td>\n",
       "      <td>88</td>\n",
       "      <td>10.0</td>\n",
       "      <td>Washington</td>\n",
       "      <td>Washington</td>\n",
       "      <td>Washington Other</td>\n",
       "      <td>Paul Gregutt</td>\n",
       "      <td>@paulgwine</td>\n",
       "      <td>14 Hands 2013 Riesling (Washington)</td>\n",
       "      <td>Riesling</td>\n",
       "      <td>14 Hands</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57235</th>\n",
       "      <td>US</td>\n",
       "      <td>Dried herb and wood spice aromas are followed ...</td>\n",
       "      <td>The Reserve</td>\n",
       "      <td>90</td>\n",
       "      <td>30.0</td>\n",
       "      <td>Washington</td>\n",
       "      <td>Horse Heaven Hills</td>\n",
       "      <td>Columbia Valley</td>\n",
       "      <td>Sean P. Sullivan</td>\n",
       "      <td>@wawinereport</td>\n",
       "      <td>14 Hands 2013 The Reserve Cabernet Sauvignon (...</td>\n",
       "      <td>Cabernet Sauvignon</td>\n",
       "      <td>14 Hands</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26499</th>\n",
       "      <td>US</td>\n",
       "      <td>Aromas are light, with notes of matchstick, he...</td>\n",
       "      <td>Limited Release Kentucky Derby</td>\n",
       "      <td>87</td>\n",
       "      <td>12.0</td>\n",
       "      <td>Washington</td>\n",
       "      <td>Columbia Valley (WA)</td>\n",
       "      <td>Columbia Valley</td>\n",
       "      <td>Sean P. Sullivan</td>\n",
       "      <td>@wawinereport</td>\n",
       "      <td>14 Hands 2014 Limited Release Kentucky Derby R...</td>\n",
       "      <td>Red Blend</td>\n",
       "      <td>14 Hands</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116037</th>\n",
       "      <td>US</td>\n",
       "      <td>The aromas of barrel spice, toast, herb and pl...</td>\n",
       "      <td>None</td>\n",
       "      <td>88</td>\n",
       "      <td>12.0</td>\n",
       "      <td>Washington</td>\n",
       "      <td>Columbia Valley (WA)</td>\n",
       "      <td>Columbia Valley</td>\n",
       "      <td>Sean P. Sullivan</td>\n",
       "      <td>@wawinereport</td>\n",
       "      <td>14 Hands 2015 Cabernet Sauvignon (Columbia Val...</td>\n",
       "      <td>Cabernet Sauvignon</td>\n",
       "      <td>14 Hands</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108391</th>\n",
       "      <td>US</td>\n",
       "      <td>Light aromas of lemon, apple, pineapple, toast...</td>\n",
       "      <td>Brut Méthode Champenoise</td>\n",
       "      <td>87</td>\n",
       "      <td>15.0</td>\n",
       "      <td>Washington</td>\n",
       "      <td>Columbia Valley (WA)</td>\n",
       "      <td>Columbia Valley</td>\n",
       "      <td>Sean P. Sullivan</td>\n",
       "      <td>@wawinereport</td>\n",
       "      <td>14 Hands NV Brut Méthode Champenoise Sparkling...</td>\n",
       "      <td>Sparkling Blend</td>\n",
       "      <td>14 Hands</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73229</th>\n",
       "      <td>US</td>\n",
       "      <td>This is the inaugural release from this Oregon...</td>\n",
       "      <td>Proprietary</td>\n",
       "      <td>92</td>\n",
       "      <td>75.0</td>\n",
       "      <td>Oregon</td>\n",
       "      <td>Walla Walla Valley (OR)</td>\n",
       "      <td>Oregon Other</td>\n",
       "      <td>Sean P. Sullivan</td>\n",
       "      <td>@wawinereport</td>\n",
       "      <td>18401 Cellars 2013 Proprietary Red (Walla Wall...</td>\n",
       "      <td>Bordeaux-style Red Blend</td>\n",
       "      <td>18401 Cellars</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92133</th>\n",
       "      <td>Portugal</td>\n",
       "      <td>With aromas of superripe fruit, this wood aged...</td>\n",
       "      <td>Vinhas Velhas Branco</td>\n",
       "      <td>90</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Douro</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Roger Voss</td>\n",
       "      <td>@vossroger</td>\n",
       "      <td>1912 Winemakers 2011 Vinhas Velhas Branco Whit...</td>\n",
       "      <td>Portuguese White</td>\n",
       "      <td>1912 Winemakers</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>123570</th>\n",
       "      <td>US</td>\n",
       "      <td>A blend of 70% Cabernet Franc and 30% Merlot, ...</td>\n",
       "      <td>None</td>\n",
       "      <td>83</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Michigan</td>\n",
       "      <td>Old Mission Peninsula</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>2 Lads 2009 Cabernet Franc-Merlot (Old Mission...</td>\n",
       "      <td>Cabernet Franc-Merlot</td>\n",
       "      <td>2 Lads</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107357</th>\n",
       "      <td>US</td>\n",
       "      <td>An earthy geranium note lingers above a core o...</td>\n",
       "      <td>None</td>\n",
       "      <td>87</td>\n",
       "      <td>29.0</td>\n",
       "      <td>Michigan</td>\n",
       "      <td>Old Mission Peninsula</td>\n",
       "      <td>None</td>\n",
       "      <td>Alexander Peartree</td>\n",
       "      <td>None</td>\n",
       "      <td>2 Lads 2013 Pinot Noir (Old Mission Peninsula)</td>\n",
       "      <td>Pinot Noir</td>\n",
       "      <td>2 Lads</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125397</th>\n",
       "      <td>Australia</td>\n",
       "      <td>Vanilla, cedar and plum notes benefit from a d...</td>\n",
       "      <td>None</td>\n",
       "      <td>88</td>\n",
       "      <td>15.0</td>\n",
       "      <td>South Australia</td>\n",
       "      <td>South Australia</td>\n",
       "      <td>None</td>\n",
       "      <td>Joe Czerwinski</td>\n",
       "      <td>@JoeCz</td>\n",
       "      <td>2 Up 2014 Shiraz (South Australia)</td>\n",
       "      <td>Shiraz</td>\n",
       "      <td>2 Up</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106179</th>\n",
       "      <td>US</td>\n",
       "      <td>Subtle notes of bramble, smoke and raspberry e...</td>\n",
       "      <td>None</td>\n",
       "      <td>86</td>\n",
       "      <td>28.0</td>\n",
       "      <td>New York</td>\n",
       "      <td>Finger Lakes</td>\n",
       "      <td>Finger Lakes</td>\n",
       "      <td>Anna Lee C. Iijima</td>\n",
       "      <td>None</td>\n",
       "      <td>240 Days 2015 Rosé (Finger Lakes)</td>\n",
       "      <td>Rosé</td>\n",
       "      <td>240 Days</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72010</th>\n",
       "      <td>US</td>\n",
       "      <td>All estate fruit goes into this reserve, which...</td>\n",
       "      <td>Limited Reserve</td>\n",
       "      <td>88</td>\n",
       "      <td>45.0</td>\n",
       "      <td>Oregon</td>\n",
       "      <td>Southern Oregon</td>\n",
       "      <td>Southern Oregon</td>\n",
       "      <td>Paul Gregutt</td>\n",
       "      <td>@paulgwine</td>\n",
       "      <td>2Hawk 2014 Limited Reserve Tempranillo (Southe...</td>\n",
       "      <td>Tempranillo</td>\n",
       "      <td>2Hawk</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124803</th>\n",
       "      <td>US</td>\n",
       "      <td>Reserve is rarely a word found in front of ros...</td>\n",
       "      <td>Reserve</td>\n",
       "      <td>88</td>\n",
       "      <td>15.0</td>\n",
       "      <td>Idaho</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Paul Gregutt</td>\n",
       "      <td>@paulgwine</td>\n",
       "      <td>3 Horse Ranch Vineyards 2011 Reserve Rosé</td>\n",
       "      <td>Rosé</td>\n",
       "      <td>3 Horse Ranch Vineyards</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70727</th>\n",
       "      <td>US</td>\n",
       "      <td>Cocoa, bittersweet chocolate, herb, wood spice...</td>\n",
       "      <td>None</td>\n",
       "      <td>87</td>\n",
       "      <td>23.0</td>\n",
       "      <td>Washington</td>\n",
       "      <td>Washington</td>\n",
       "      <td>Washington Other</td>\n",
       "      <td>Sean P. Sullivan</td>\n",
       "      <td>@wawinereport</td>\n",
       "      <td>3 Horse Ranch Vineyards 2013 Cabernet Sauvigno...</td>\n",
       "      <td>Cabernet Sauvignon</td>\n",
       "      <td>3 Horse Ranch Vineyards</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76084</th>\n",
       "      <td>US</td>\n",
       "      <td>One of the first bottles to bear the name of t...</td>\n",
       "      <td>Single Vineyard</td>\n",
       "      <td>88</td>\n",
       "      <td>30.0</td>\n",
       "      <td>Idaho</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Sean P. Sullivan</td>\n",
       "      <td>@wawinereport</td>\n",
       "      <td>3 Horse Ranch Vineyards 2014 Single Vineyard S...</td>\n",
       "      <td>Syrah</td>\n",
       "      <td>3 Horse Ranch Vineyards</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110206</th>\n",
       "      <td>New Zealand</td>\n",
       "      <td>A hint of stuck flint adds a touch of complexi...</td>\n",
       "      <td>None</td>\n",
       "      <td>87</td>\n",
       "      <td>14.0</td>\n",
       "      <td>Marlborough</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Joe Czerwinski</td>\n",
       "      <td>@JoeCz</td>\n",
       "      <td>3 Stones 2009 Sauvignon Blanc (Marlborough)</td>\n",
       "      <td>Sauvignon Blanc</td>\n",
       "      <td>3 Stones</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57492</th>\n",
       "      <td>US</td>\n",
       "      <td>This blend of Merlot, Cabernet Sauvignon, Syra...</td>\n",
       "      <td>None</td>\n",
       "      <td>87</td>\n",
       "      <td>25.0</td>\n",
       "      <td>Washington</td>\n",
       "      <td>Columbia Valley (WA)</td>\n",
       "      <td>Columbia Valley</td>\n",
       "      <td>Sean P. Sullivan</td>\n",
       "      <td>@wawinereport</td>\n",
       "      <td>4 Cellars 2014 Red (Columbia Valley (WA))</td>\n",
       "      <td>Red Blend</td>\n",
       "      <td>4 Cellars</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21553</th>\n",
       "      <td>Australia</td>\n",
       "      <td>Light, fresh and silky—just what might be expe...</td>\n",
       "      <td>None</td>\n",
       "      <td>87</td>\n",
       "      <td>18.0</td>\n",
       "      <td>Tasmania</td>\n",
       "      <td>Tasmania</td>\n",
       "      <td>None</td>\n",
       "      <td>Joe Czerwinski</td>\n",
       "      <td>@JoeCz</td>\n",
       "      <td>42°S 2008 Pinot Noir (Tasmania)</td>\n",
       "      <td>Pinot Noir</td>\n",
       "      <td>42°S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117812</th>\n",
       "      <td>US</td>\n",
       "      <td>This muted, tannic Cabernet spent 20 months in...</td>\n",
       "      <td>Flagstone</td>\n",
       "      <td>86</td>\n",
       "      <td>59.0</td>\n",
       "      <td>California</td>\n",
       "      <td>Napa Valley</td>\n",
       "      <td>Napa</td>\n",
       "      <td>Virginie Boone</td>\n",
       "      <td>@vboone</td>\n",
       "      <td>6 North 2009 Flagstone Cabernet Sauvignon (Nap...</td>\n",
       "      <td>Cabernet Sauvignon</td>\n",
       "      <td>6 North</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119356</th>\n",
       "      <td>US</td>\n",
       "      <td>The blend is 60% Grenache from the Stone Tree ...</td>\n",
       "      <td>Una Notte</td>\n",
       "      <td>87</td>\n",
       "      <td>30.0</td>\n",
       "      <td>Washington</td>\n",
       "      <td>Columbia Valley (WA)</td>\n",
       "      <td>Columbia Valley</td>\n",
       "      <td>Paul Gregutt</td>\n",
       "      <td>@paulgwine</td>\n",
       "      <td>:Nota Bene 2010 Una Notte Red (Columbia Valley...</td>\n",
       "      <td>Rhône-style Red Blend</td>\n",
       "      <td>:Nota Bene</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106214</th>\n",
       "      <td>US</td>\n",
       "      <td>A blend of Cabernet Sauvignon, Merlot and Cabe...</td>\n",
       "      <td>Ciel du Cheval</td>\n",
       "      <td>86</td>\n",
       "      <td>40.0</td>\n",
       "      <td>Washington</td>\n",
       "      <td>Red Mountain</td>\n",
       "      <td>Columbia Valley</td>\n",
       "      <td>Sean P. Sullivan</td>\n",
       "      <td>@wawinereport</td>\n",
       "      <td>:Nota Bene 2011 Ciel du Cheval Red (Red Mountain)</td>\n",
       "      <td>Bordeaux-style Red Blend</td>\n",
       "      <td>:Nota Bene</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82071</th>\n",
       "      <td>US</td>\n",
       "      <td>This 100% varietal wine offers aromas of barre...</td>\n",
       "      <td>Ciel du Cheval Vineyard</td>\n",
       "      <td>88</td>\n",
       "      <td>40.0</td>\n",
       "      <td>Washington</td>\n",
       "      <td>Red Mountain</td>\n",
       "      <td>Columbia Valley</td>\n",
       "      <td>Sean P. Sullivan</td>\n",
       "      <td>@wawinereport</td>\n",
       "      <td>:Nota Bene 2011 Ciel du Cheval Vineyard Syrah ...</td>\n",
       "      <td>Syrah</td>\n",
       "      <td>:Nota Bene</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126614</th>\n",
       "      <td>US</td>\n",
       "      <td>This wine is half Cabernet Sauvignon, with the...</td>\n",
       "      <td>Arianses Vineyard</td>\n",
       "      <td>88</td>\n",
       "      <td>30.0</td>\n",
       "      <td>Washington</td>\n",
       "      <td>Wahluke Slope</td>\n",
       "      <td>Columbia Valley</td>\n",
       "      <td>Sean P. Sullivan</td>\n",
       "      <td>@wawinereport</td>\n",
       "      <td>:Nota Bene 2012 Arianses Vineyard Red (Wahluke...</td>\n",
       "      <td>Bordeaux-style Red Blend</td>\n",
       "      <td>:Nota Bene</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126596</th>\n",
       "      <td>US</td>\n",
       "      <td>Grenache makes up nearly three-quarters of thi...</td>\n",
       "      <td>Una Notte</td>\n",
       "      <td>88</td>\n",
       "      <td>30.0</td>\n",
       "      <td>Washington</td>\n",
       "      <td>Columbia Valley (WA)</td>\n",
       "      <td>Columbia Valley</td>\n",
       "      <td>Sean P. Sullivan</td>\n",
       "      <td>@wawinereport</td>\n",
       "      <td>:Nota Bene 2012 Una Notte Red (Columbia Valley...</td>\n",
       "      <td>Rhône-style Red Blend</td>\n",
       "      <td>:Nota Bene</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60595</th>\n",
       "      <td>US</td>\n",
       "      <td>This blend of Cabernet Sauvignon (34%), Merlot...</td>\n",
       "      <td>Arianses Vineyard</td>\n",
       "      <td>88</td>\n",
       "      <td>30.0</td>\n",
       "      <td>Washington</td>\n",
       "      <td>Wahluke Slope</td>\n",
       "      <td>Columbia Valley</td>\n",
       "      <td>Sean P. Sullivan</td>\n",
       "      <td>@wawinereport</td>\n",
       "      <td>:Nota Bene 2013 Arianses Vineyard Red (Wahluke...</td>\n",
       "      <td>Bordeaux-style Red Blend</td>\n",
       "      <td>:Nota Bene</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60596</th>\n",
       "      <td>US</td>\n",
       "      <td>Cabernet Sauvignon (54%) takes the lead in thi...</td>\n",
       "      <td>Ciel du Cheval Vineyard</td>\n",
       "      <td>88</td>\n",
       "      <td>40.0</td>\n",
       "      <td>Washington</td>\n",
       "      <td>Red Mountain</td>\n",
       "      <td>Columbia Valley</td>\n",
       "      <td>Sean P. Sullivan</td>\n",
       "      <td>@wawinereport</td>\n",
       "      <td>:Nota Bene 2013 Ciel du Cheval Vineyard Red (R...</td>\n",
       "      <td>Bordeaux-style Red Blend</td>\n",
       "      <td>:Nota Bene</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>115430</th>\n",
       "      <td>US</td>\n",
       "      <td>Vanilla, coconut and baking spice aromas are a...</td>\n",
       "      <td>Ciel du Cheval Vineyard</td>\n",
       "      <td>87</td>\n",
       "      <td>40.0</td>\n",
       "      <td>Washington</td>\n",
       "      <td>Red Mountain</td>\n",
       "      <td>Columbia Valley</td>\n",
       "      <td>Sean P. Sullivan</td>\n",
       "      <td>@wawinereport</td>\n",
       "      <td>:Nota Bene 2013 Ciel du Cheval Vineyard Syrah ...</td>\n",
       "      <td>Syrah</td>\n",
       "      <td>:Nota Bene</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93378</th>\n",
       "      <td>US</td>\n",
       "      <td>Very focused Key-lime aromas meet with strongl...</td>\n",
       "      <td>Estate</td>\n",
       "      <td>93</td>\n",
       "      <td>36.0</td>\n",
       "      <td>California</td>\n",
       "      <td>Sta. Rita Hills</td>\n",
       "      <td>Central Coast</td>\n",
       "      <td>Matt Kettmann</td>\n",
       "      <td>@mattkettmann</td>\n",
       "      <td>Zotovich Cellars 2013 Estate Chardonnay (Sta. ...</td>\n",
       "      <td>Chardonnay</td>\n",
       "      <td>Zotovich Cellars</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65142</th>\n",
       "      <td>Italy</td>\n",
       "      <td>Made with the Friulano grape (with small perce...</td>\n",
       "      <td>Vigne</td>\n",
       "      <td>87</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Northeastern Italy</td>\n",
       "      <td>Collio</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Zuani 2011 Vigne White (Collio)</td>\n",
       "      <td>White Blend</td>\n",
       "      <td>Zuani</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85567</th>\n",
       "      <td>Italy</td>\n",
       "      <td>Made with the Friulano grape (with small perce...</td>\n",
       "      <td>Vigne</td>\n",
       "      <td>87</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Northeastern Italy</td>\n",
       "      <td>Collio</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Zuani 2011 Vigne White (Collio)</td>\n",
       "      <td>White Blend</td>\n",
       "      <td>Zuani</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89122</th>\n",
       "      <td>Argentina</td>\n",
       "      <td>Warm, rich aromas of wild berry carry a hint o...</td>\n",
       "      <td>Q</td>\n",
       "      <td>88</td>\n",
       "      <td>20.0</td>\n",
       "      <td>Mendoza Province</td>\n",
       "      <td>Mendoza</td>\n",
       "      <td>None</td>\n",
       "      <td>Michael Schachner</td>\n",
       "      <td>@wineschach</td>\n",
       "      <td>Zuccardi 2007 Q Cabernet Sauvignon (Mendoza)</td>\n",
       "      <td>Cabernet Sauvignon</td>\n",
       "      <td>Zuccardi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35273</th>\n",
       "      <td>Argentina</td>\n",
       "      <td>Tropical fruit and vanilla-cookie aromas come ...</td>\n",
       "      <td>Serie A</td>\n",
       "      <td>84</td>\n",
       "      <td>15.0</td>\n",
       "      <td>Mendoza Province</td>\n",
       "      <td>Uco Valley</td>\n",
       "      <td>None</td>\n",
       "      <td>Michael Schachner</td>\n",
       "      <td>@wineschach</td>\n",
       "      <td>Zuccardi 2012 Serie A Chardonnay (Uco Valley)</td>\n",
       "      <td>Chardonnay</td>\n",
       "      <td>Zuccardi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125678</th>\n",
       "      <td>Argentina</td>\n",
       "      <td>Bold, jumpy, reduced aromas of plum and berry ...</td>\n",
       "      <td>Serie A Santa Rosa</td>\n",
       "      <td>86</td>\n",
       "      <td>15.0</td>\n",
       "      <td>Mendoza Province</td>\n",
       "      <td>Mendoza</td>\n",
       "      <td>None</td>\n",
       "      <td>Michael Schachner</td>\n",
       "      <td>@wineschach</td>\n",
       "      <td>Zuccardi 2012 Serie A Santa Rosa Bonarda (Mend...</td>\n",
       "      <td>Bonarda</td>\n",
       "      <td>Zuccardi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>123301</th>\n",
       "      <td>Argentina</td>\n",
       "      <td>Wiry plum and raspberry aromas are jumpy and a...</td>\n",
       "      <td>Serie A</td>\n",
       "      <td>87</td>\n",
       "      <td>15.0</td>\n",
       "      <td>Mendoza Province</td>\n",
       "      <td>Valle de Uco</td>\n",
       "      <td>None</td>\n",
       "      <td>Michael Schachner</td>\n",
       "      <td>@wineschach</td>\n",
       "      <td>Zuccardi 2013 Serie A Cabernet Sauvignon (Vall...</td>\n",
       "      <td>Cabernet Sauvignon</td>\n",
       "      <td>Zuccardi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21139</th>\n",
       "      <td>Argentina</td>\n",
       "      <td>Aromas of oak, mint and cola accent earthy bla...</td>\n",
       "      <td>Q</td>\n",
       "      <td>88</td>\n",
       "      <td>20.0</td>\n",
       "      <td>Mendoza Province</td>\n",
       "      <td>Valle de Uco</td>\n",
       "      <td>None</td>\n",
       "      <td>Michael Schachner</td>\n",
       "      <td>@wineschach</td>\n",
       "      <td>Zuccardi 2014 Q Malbec (Valle de Uco)</td>\n",
       "      <td>Malbec</td>\n",
       "      <td>Zuccardi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96588</th>\n",
       "      <td>Spain</td>\n",
       "      <td>This is flat and lemony on the nose, with a hi...</td>\n",
       "      <td>None</td>\n",
       "      <td>84</td>\n",
       "      <td>26.0</td>\n",
       "      <td>Northern Spain</td>\n",
       "      <td>Getariako Txakolina</td>\n",
       "      <td>None</td>\n",
       "      <td>Michael Schachner</td>\n",
       "      <td>@wineschach</td>\n",
       "      <td>Zudugarai 2011 White (Getariako Txakolina)</td>\n",
       "      <td>White Blend</td>\n",
       "      <td>Zudugarai</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125015</th>\n",
       "      <td>Spain</td>\n",
       "      <td>Aromas of children's vitamins, corn stalk and ...</td>\n",
       "      <td>None</td>\n",
       "      <td>89</td>\n",
       "      <td>25.0</td>\n",
       "      <td>Northern Spain</td>\n",
       "      <td>Getariako Txakolina</td>\n",
       "      <td>None</td>\n",
       "      <td>Michael Schachner</td>\n",
       "      <td>@wineschach</td>\n",
       "      <td>Zudugarai 2014 Hondarrabi Zuri (Getariako Txak...</td>\n",
       "      <td>Hondarrabi Zuri</td>\n",
       "      <td>Zudugarai</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49266</th>\n",
       "      <td>Austria</td>\n",
       "      <td>There is impressive balance here—rich apple an...</td>\n",
       "      <td>Aussere Bergen</td>\n",
       "      <td>92</td>\n",
       "      <td>23.0</td>\n",
       "      <td>Niederösterreich</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Roger Voss</td>\n",
       "      <td>@vossroger</td>\n",
       "      <td>Zull 2010 Aussere Bergen Grüner Veltliner (Nie...</td>\n",
       "      <td>Grüner Veltliner</td>\n",
       "      <td>Zull</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83815</th>\n",
       "      <td>France</td>\n",
       "      <td>Exquisitely fragrant notes of ripe, aromatic a...</td>\n",
       "      <td>Clos Liebenberg</td>\n",
       "      <td>93</td>\n",
       "      <td>57.0</td>\n",
       "      <td>Alsace</td>\n",
       "      <td>Crémant d'Alsace</td>\n",
       "      <td>None</td>\n",
       "      <td>Anne Krebiehl MW</td>\n",
       "      <td>@AnneInVino</td>\n",
       "      <td>Zusslin 2012 Clos Liebenberg Sparkling (Créman...</td>\n",
       "      <td>Sparkling Blend</td>\n",
       "      <td>Zusslin</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31687</th>\n",
       "      <td>US</td>\n",
       "      <td>You can smell the extreme alcohol level on thi...</td>\n",
       "      <td>Alisos Vineyard</td>\n",
       "      <td>82</td>\n",
       "      <td>37.0</td>\n",
       "      <td>California</td>\n",
       "      <td>Santa Barbara County</td>\n",
       "      <td>Central Coast</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>a-non-ah-mus 2010 Alisos Vineyard Syrah (Santa...</td>\n",
       "      <td>Syrah</td>\n",
       "      <td>a-non-ah-mus</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95841</th>\n",
       "      <td>US</td>\n",
       "      <td>Currently, this Syrah has tough tannins that s...</td>\n",
       "      <td>Larner Vineyard</td>\n",
       "      <td>87</td>\n",
       "      <td>30.0</td>\n",
       "      <td>California</td>\n",
       "      <td>Santa Barbara County</td>\n",
       "      <td>Central Coast</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>db Winery 2010 Larner Vineyard Syrah (Santa Ba...</td>\n",
       "      <td>Syrah</td>\n",
       "      <td>db Winery</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76938</th>\n",
       "      <td>US</td>\n",
       "      <td>This outstanding value is sharp and precise, i...</td>\n",
       "      <td>La Sorella</td>\n",
       "      <td>91</td>\n",
       "      <td>25.0</td>\n",
       "      <td>Oregon</td>\n",
       "      <td>Willamette Valley</td>\n",
       "      <td>Willamette Valley</td>\n",
       "      <td>Paul Gregutt</td>\n",
       "      <td>@paulgwine</td>\n",
       "      <td>de Lancellotti 2014 La Sorella Pinot Noir (Wil...</td>\n",
       "      <td>Pinot Noir</td>\n",
       "      <td>de Lancellotti</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55932</th>\n",
       "      <td>South Africa</td>\n",
       "      <td>An elegant and refined Chenin that shows super...</td>\n",
       "      <td>None</td>\n",
       "      <td>91</td>\n",
       "      <td>29.0</td>\n",
       "      <td>Stellenbosch</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Lauren Buzzeo</td>\n",
       "      <td>@laurbuzz</td>\n",
       "      <td>de Trafford 2009 Chenin Blanc (Stellenbosch)</td>\n",
       "      <td>Chenin Blanc</td>\n",
       "      <td>de Trafford</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117036</th>\n",
       "      <td>US</td>\n",
       "      <td>This blend of 52% Syrah, 25% Grenache and 23% ...</td>\n",
       "      <td>Sisu</td>\n",
       "      <td>93</td>\n",
       "      <td>45.0</td>\n",
       "      <td>California</td>\n",
       "      <td>Paso Robles</td>\n",
       "      <td>Central Coast</td>\n",
       "      <td>Matt Kettmann</td>\n",
       "      <td>@mattkettmann</td>\n",
       "      <td>kukkula 2012 Sisu Red (Paso Robles)</td>\n",
       "      <td>Rhône-style Red Blend</td>\n",
       "      <td>kukkula</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32963</th>\n",
       "      <td>US</td>\n",
       "      <td>A bit lighter in color than other Rhône blends...</td>\n",
       "      <td>Aatto</td>\n",
       "      <td>90</td>\n",
       "      <td>40.0</td>\n",
       "      <td>California</td>\n",
       "      <td>Adelaida District</td>\n",
       "      <td>Central Coast</td>\n",
       "      <td>Matt Kettmann</td>\n",
       "      <td>@mattkettmann</td>\n",
       "      <td>kukkula 2013 Aatto Red (Adelaida District)</td>\n",
       "      <td>Rhône-style Red Blend</td>\n",
       "      <td>kukkula</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100706</th>\n",
       "      <td>Hungary</td>\n",
       "      <td>This gold-colored Furmint has aromas of lemon ...</td>\n",
       "      <td>None</td>\n",
       "      <td>89</td>\n",
       "      <td>22.0</td>\n",
       "      <td>Tokaj</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Jeff Jenssen</td>\n",
       "      <td>@worldwineguys</td>\n",
       "      <td>majoros 2013 Furmint (Tokaj)</td>\n",
       "      <td>Furmint</td>\n",
       "      <td>majoros</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126699</th>\n",
       "      <td>Chile</td>\n",
       "      <td>Made for Oops by VIA Wines, this oddball Chard...</td>\n",
       "      <td>None</td>\n",
       "      <td>85</td>\n",
       "      <td>12.0</td>\n",
       "      <td>Central Valley</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Michael Schachner</td>\n",
       "      <td>@wineschach</td>\n",
       "      <td>oops 2007 Chardonnay (Central Valley)</td>\n",
       "      <td>Chardonnay</td>\n",
       "      <td>oops</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106477</th>\n",
       "      <td>Chile</td>\n",
       "      <td>This wine varies in quality and perception bas...</td>\n",
       "      <td>None</td>\n",
       "      <td>85</td>\n",
       "      <td>11.0</td>\n",
       "      <td>Central Valley</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Michael Schachner</td>\n",
       "      <td>@wineschach</td>\n",
       "      <td>oops 2009 Sauvignon Blanc (Central Valley)</td>\n",
       "      <td>Sauvignon Blanc</td>\n",
       "      <td>oops</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>114581</th>\n",
       "      <td>Chile</td>\n",
       "      <td>Although it's not very aromatic, the nose on t...</td>\n",
       "      <td>None</td>\n",
       "      <td>86</td>\n",
       "      <td>10.0</td>\n",
       "      <td>Central Valley</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Michael Schachner</td>\n",
       "      <td>@wineschach</td>\n",
       "      <td>oops 2011 Chardonnay (Central Valley)</td>\n",
       "      <td>Chardonnay</td>\n",
       "      <td>oops</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62029</th>\n",
       "      <td>US</td>\n",
       "      <td>In much the same mold as its companion, the gh...</td>\n",
       "      <td>None</td>\n",
       "      <td>86</td>\n",
       "      <td>13.0</td>\n",
       "      <td>Washington</td>\n",
       "      <td>Columbia Valley (WA)</td>\n",
       "      <td>Columbia Valley</td>\n",
       "      <td>Paul Gregutt</td>\n",
       "      <td>@paulgwine</td>\n",
       "      <td>the Ghost of 413 2010 Red (Columbia Valley (WA))</td>\n",
       "      <td>Red Blend</td>\n",
       "      <td>the Ghost of 413</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>120934</th>\n",
       "      <td>Argentina</td>\n",
       "      <td>This is rough and gritty smelling, with burnt,...</td>\n",
       "      <td>Sustainably Farmed</td>\n",
       "      <td>82</td>\n",
       "      <td>10.0</td>\n",
       "      <td>Mendoza Province</td>\n",
       "      <td>Mendoza</td>\n",
       "      <td>None</td>\n",
       "      <td>Michael Schachner</td>\n",
       "      <td>@wineschach</td>\n",
       "      <td>Árido 2010 Sustainably Farmed Malbec (Mendoza)</td>\n",
       "      <td>Malbec</td>\n",
       "      <td>Árido</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96807</th>\n",
       "      <td>US</td>\n",
       "      <td>This is one of the best Bordeaux blends now av...</td>\n",
       "      <td>Ensemble Lock Vineyard</td>\n",
       "      <td>90</td>\n",
       "      <td>42.0</td>\n",
       "      <td>California</td>\n",
       "      <td>Paso Robles</td>\n",
       "      <td>Central Coast</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Écluse 2010 Ensemble Lock Vineyard Red (Paso R...</td>\n",
       "      <td>Bordeaux-style Red Blend</td>\n",
       "      <td>Écluse</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117040</th>\n",
       "      <td>US</td>\n",
       "      <td>A nontraditional blend of 44% Zinfandel, 31% S...</td>\n",
       "      <td>Improv</td>\n",
       "      <td>93</td>\n",
       "      <td>38.0</td>\n",
       "      <td>California</td>\n",
       "      <td>Paso Robles</td>\n",
       "      <td>Central Coast</td>\n",
       "      <td>Matt Kettmann</td>\n",
       "      <td>@mattkettmann</td>\n",
       "      <td>Écluse 2013 Improv Red (Paso Robles)</td>\n",
       "      <td>Red Blend</td>\n",
       "      <td>Écluse</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45355</th>\n",
       "      <td>US</td>\n",
       "      <td>Inky dark in the glass, this blend of 48% Syra...</td>\n",
       "      <td>Rendition</td>\n",
       "      <td>92</td>\n",
       "      <td>38.0</td>\n",
       "      <td>California</td>\n",
       "      <td>Paso Robles</td>\n",
       "      <td>Central Coast</td>\n",
       "      <td>Matt Kettmann</td>\n",
       "      <td>@mattkettmann</td>\n",
       "      <td>Écluse 2013 Rendition Red (Paso Robles)</td>\n",
       "      <td>Rhône-style Red Blend</td>\n",
       "      <td>Écluse</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81242</th>\n",
       "      <td>France</td>\n",
       "      <td>The brothers are better known for their Cornas...</td>\n",
       "      <td>Les Coteaux</td>\n",
       "      <td>90</td>\n",
       "      <td>39.0</td>\n",
       "      <td>Rhône Valley</td>\n",
       "      <td>Saint-Joseph</td>\n",
       "      <td>None</td>\n",
       "      <td>Joe Czerwinski</td>\n",
       "      <td>@JoeCz</td>\n",
       "      <td>Éric &amp; Jöel Durand 2010 Les Coteaux  (Saint-Jo...</td>\n",
       "      <td>Syrah</td>\n",
       "      <td>Éric &amp; Jöel Durand</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80322</th>\n",
       "      <td>Argentina</td>\n",
       "      <td>Scratchy aromas of raspberry and licorice gumd...</td>\n",
       "      <td>Made With Organically Grown Grapes</td>\n",
       "      <td>85</td>\n",
       "      <td>11.0</td>\n",
       "      <td>Mendoza Province</td>\n",
       "      <td>Mendoza</td>\n",
       "      <td>None</td>\n",
       "      <td>Michael Schachner</td>\n",
       "      <td>@wineschach</td>\n",
       "      <td>Öko 2013 Made With Organically Grown Grapes Ma...</td>\n",
       "      <td>Malbec</td>\n",
       "      <td>Öko</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95773</th>\n",
       "      <td>US</td>\n",
       "      <td>Pretty and deep, this has notes of juicy boyse...</td>\n",
       "      <td>None</td>\n",
       "      <td>90</td>\n",
       "      <td>35.0</td>\n",
       "      <td>Washington</td>\n",
       "      <td>Columbia Valley (WA)</td>\n",
       "      <td>Columbia Valley</td>\n",
       "      <td>Paul Gregutt</td>\n",
       "      <td>@paulgwine</td>\n",
       "      <td>àMaurice 2009 Malbec (Columbia Valley (WA))</td>\n",
       "      <td>Malbec</td>\n",
       "      <td>àMaurice</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>11131 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             country                                        description  \\\n",
       "93375          Spain  Dusty notes of citrus fruits are mild but frie...   \n",
       "56109          Spain  Clean, fresh apple aromas and a minerally, cit...   \n",
       "100235            US  Merlot, Cabernet and Syrah form the core of th...   \n",
       "68750             US  In just a few years 14 Hands Riesling producti...   \n",
       "57235             US  Dried herb and wood spice aromas are followed ...   \n",
       "26499             US  Aromas are light, with notes of matchstick, he...   \n",
       "116037            US  The aromas of barrel spice, toast, herb and pl...   \n",
       "108391            US  Light aromas of lemon, apple, pineapple, toast...   \n",
       "73229             US  This is the inaugural release from this Oregon...   \n",
       "92133       Portugal  With aromas of superripe fruit, this wood aged...   \n",
       "123570            US  A blend of 70% Cabernet Franc and 30% Merlot, ...   \n",
       "107357            US  An earthy geranium note lingers above a core o...   \n",
       "125397     Australia  Vanilla, cedar and plum notes benefit from a d...   \n",
       "106179            US  Subtle notes of bramble, smoke and raspberry e...   \n",
       "72010             US  All estate fruit goes into this reserve, which...   \n",
       "124803            US  Reserve is rarely a word found in front of ros...   \n",
       "70727             US  Cocoa, bittersweet chocolate, herb, wood spice...   \n",
       "76084             US  One of the first bottles to bear the name of t...   \n",
       "110206   New Zealand  A hint of stuck flint adds a touch of complexi...   \n",
       "57492             US  This blend of Merlot, Cabernet Sauvignon, Syra...   \n",
       "21553      Australia  Light, fresh and silky—just what might be expe...   \n",
       "117812            US  This muted, tannic Cabernet spent 20 months in...   \n",
       "119356            US  The blend is 60% Grenache from the Stone Tree ...   \n",
       "106214            US  A blend of Cabernet Sauvignon, Merlot and Cabe...   \n",
       "82071             US  This 100% varietal wine offers aromas of barre...   \n",
       "126614            US  This wine is half Cabernet Sauvignon, with the...   \n",
       "126596            US  Grenache makes up nearly three-quarters of thi...   \n",
       "60595             US  This blend of Cabernet Sauvignon (34%), Merlot...   \n",
       "60596             US  Cabernet Sauvignon (54%) takes the lead in thi...   \n",
       "115430            US  Vanilla, coconut and baking spice aromas are a...   \n",
       "...              ...                                                ...   \n",
       "93378             US  Very focused Key-lime aromas meet with strongl...   \n",
       "65142          Italy  Made with the Friulano grape (with small perce...   \n",
       "85567          Italy  Made with the Friulano grape (with small perce...   \n",
       "89122      Argentina  Warm, rich aromas of wild berry carry a hint o...   \n",
       "35273      Argentina  Tropical fruit and vanilla-cookie aromas come ...   \n",
       "125678     Argentina  Bold, jumpy, reduced aromas of plum and berry ...   \n",
       "123301     Argentina  Wiry plum and raspberry aromas are jumpy and a...   \n",
       "21139      Argentina  Aromas of oak, mint and cola accent earthy bla...   \n",
       "96588          Spain  This is flat and lemony on the nose, with a hi...   \n",
       "125015         Spain  Aromas of children's vitamins, corn stalk and ...   \n",
       "49266        Austria  There is impressive balance here—rich apple an...   \n",
       "83815         France  Exquisitely fragrant notes of ripe, aromatic a...   \n",
       "31687             US  You can smell the extreme alcohol level on thi...   \n",
       "95841             US  Currently, this Syrah has tough tannins that s...   \n",
       "76938             US  This outstanding value is sharp and precise, i...   \n",
       "55932   South Africa  An elegant and refined Chenin that shows super...   \n",
       "117036            US  This blend of 52% Syrah, 25% Grenache and 23% ...   \n",
       "32963             US  A bit lighter in color than other Rhône blends...   \n",
       "100706       Hungary  This gold-colored Furmint has aromas of lemon ...   \n",
       "126699         Chile  Made for Oops by VIA Wines, this oddball Chard...   \n",
       "106477         Chile  This wine varies in quality and perception bas...   \n",
       "114581         Chile  Although it's not very aromatic, the nose on t...   \n",
       "62029             US  In much the same mold as its companion, the gh...   \n",
       "120934     Argentina  This is rough and gritty smelling, with burnt,...   \n",
       "96807             US  This is one of the best Bordeaux blends now av...   \n",
       "117040            US  A nontraditional blend of 44% Zinfandel, 31% S...   \n",
       "45355             US  Inky dark in the glass, this blend of 48% Syra...   \n",
       "81242         France  The brothers are better known for their Cornas...   \n",
       "80322      Argentina  Scratchy aromas of raspberry and licorice gumd...   \n",
       "95773             US  Pretty and deep, this has notes of juicy boyse...   \n",
       "\n",
       "                                              designation  points  price  \\\n",
       "93375                                                Brut      87   16.0   \n",
       "56109   Cygnus Brut Nature Reserva Made With Organic G...      89   20.0   \n",
       "100235                                        Hot To Trot      86   10.0   \n",
       "68750                                                None      88   10.0   \n",
       "57235                                         The Reserve      90   30.0   \n",
       "26499                      Limited Release Kentucky Derby      87   12.0   \n",
       "116037                                               None      88   12.0   \n",
       "108391                           Brut Méthode Champenoise      87   15.0   \n",
       "73229                                         Proprietary      92   75.0   \n",
       "92133                                Vinhas Velhas Branco      90    NaN   \n",
       "123570                                               None      83    NaN   \n",
       "107357                                               None      87   29.0   \n",
       "125397                                               None      88   15.0   \n",
       "106179                                               None      86   28.0   \n",
       "72010                                     Limited Reserve      88   45.0   \n",
       "124803                                            Reserve      88   15.0   \n",
       "70727                                                None      87   23.0   \n",
       "76084                                     Single Vineyard      88   30.0   \n",
       "110206                                               None      87   14.0   \n",
       "57492                                                None      87   25.0   \n",
       "21553                                                None      87   18.0   \n",
       "117812                                          Flagstone      86   59.0   \n",
       "119356                                          Una Notte      87   30.0   \n",
       "106214                                     Ciel du Cheval      86   40.0   \n",
       "82071                             Ciel du Cheval Vineyard      88   40.0   \n",
       "126614                                  Arianses Vineyard      88   30.0   \n",
       "126596                                          Una Notte      88   30.0   \n",
       "60595                                   Arianses Vineyard      88   30.0   \n",
       "60596                             Ciel du Cheval Vineyard      88   40.0   \n",
       "115430                            Ciel du Cheval Vineyard      87   40.0   \n",
       "...                                                   ...     ...    ...   \n",
       "93378                                              Estate      93   36.0   \n",
       "65142                                               Vigne      87    NaN   \n",
       "85567                                               Vigne      87    NaN   \n",
       "89122                                                   Q      88   20.0   \n",
       "35273                                             Serie A      84   15.0   \n",
       "125678                                 Serie A Santa Rosa      86   15.0   \n",
       "123301                                            Serie A      87   15.0   \n",
       "21139                                                   Q      88   20.0   \n",
       "96588                                                None      84   26.0   \n",
       "125015                                               None      89   25.0   \n",
       "49266                                      Aussere Bergen      92   23.0   \n",
       "83815                                     Clos Liebenberg      93   57.0   \n",
       "31687                                     Alisos Vineyard      82   37.0   \n",
       "95841                                     Larner Vineyard      87   30.0   \n",
       "76938                                          La Sorella      91   25.0   \n",
       "55932                                                None      91   29.0   \n",
       "117036                                               Sisu      93   45.0   \n",
       "32963                                               Aatto      90   40.0   \n",
       "100706                                               None      89   22.0   \n",
       "126699                                               None      85   12.0   \n",
       "106477                                               None      85   11.0   \n",
       "114581                                               None      86   10.0   \n",
       "62029                                                None      86   13.0   \n",
       "120934                                 Sustainably Farmed      82   10.0   \n",
       "96807                              Ensemble Lock Vineyard      90   42.0   \n",
       "117040                                             Improv      93   38.0   \n",
       "45355                                           Rendition      92   38.0   \n",
       "81242                                         Les Coteaux      90   39.0   \n",
       "80322                  Made With Organically Grown Grapes      85   11.0   \n",
       "95773                                                None      90   35.0   \n",
       "\n",
       "                  province                 region_1           region_2  \\\n",
       "93375            Catalonia                     Cava               None   \n",
       "56109            Catalonia                     Cava               None   \n",
       "100235          Washington     Columbia Valley (WA)    Columbia Valley   \n",
       "68750           Washington               Washington   Washington Other   \n",
       "57235           Washington       Horse Heaven Hills    Columbia Valley   \n",
       "26499           Washington     Columbia Valley (WA)    Columbia Valley   \n",
       "116037          Washington     Columbia Valley (WA)    Columbia Valley   \n",
       "108391          Washington     Columbia Valley (WA)    Columbia Valley   \n",
       "73229               Oregon  Walla Walla Valley (OR)       Oregon Other   \n",
       "92133                Douro                     None               None   \n",
       "123570            Michigan    Old Mission Peninsula               None   \n",
       "107357            Michigan    Old Mission Peninsula               None   \n",
       "125397     South Australia          South Australia               None   \n",
       "106179            New York             Finger Lakes       Finger Lakes   \n",
       "72010               Oregon          Southern Oregon    Southern Oregon   \n",
       "124803               Idaho                     None               None   \n",
       "70727           Washington               Washington   Washington Other   \n",
       "76084                Idaho                     None               None   \n",
       "110206         Marlborough                     None               None   \n",
       "57492           Washington     Columbia Valley (WA)    Columbia Valley   \n",
       "21553             Tasmania                 Tasmania               None   \n",
       "117812          California              Napa Valley               Napa   \n",
       "119356          Washington     Columbia Valley (WA)    Columbia Valley   \n",
       "106214          Washington             Red Mountain    Columbia Valley   \n",
       "82071           Washington             Red Mountain    Columbia Valley   \n",
       "126614          Washington            Wahluke Slope    Columbia Valley   \n",
       "126596          Washington     Columbia Valley (WA)    Columbia Valley   \n",
       "60595           Washington            Wahluke Slope    Columbia Valley   \n",
       "60596           Washington             Red Mountain    Columbia Valley   \n",
       "115430          Washington             Red Mountain    Columbia Valley   \n",
       "...                    ...                      ...                ...   \n",
       "93378           California          Sta. Rita Hills      Central Coast   \n",
       "65142   Northeastern Italy                   Collio               None   \n",
       "85567   Northeastern Italy                   Collio               None   \n",
       "89122     Mendoza Province                  Mendoza               None   \n",
       "35273     Mendoza Province               Uco Valley               None   \n",
       "125678    Mendoza Province                  Mendoza               None   \n",
       "123301    Mendoza Province             Valle de Uco               None   \n",
       "21139     Mendoza Province             Valle de Uco               None   \n",
       "96588       Northern Spain      Getariako Txakolina               None   \n",
       "125015      Northern Spain      Getariako Txakolina               None   \n",
       "49266     Niederösterreich                     None               None   \n",
       "83815               Alsace         Crémant d'Alsace               None   \n",
       "31687           California     Santa Barbara County      Central Coast   \n",
       "95841           California     Santa Barbara County      Central Coast   \n",
       "76938               Oregon        Willamette Valley  Willamette Valley   \n",
       "55932         Stellenbosch                     None               None   \n",
       "117036          California              Paso Robles      Central Coast   \n",
       "32963           California        Adelaida District      Central Coast   \n",
       "100706               Tokaj                     None               None   \n",
       "126699      Central Valley                     None               None   \n",
       "106477      Central Valley                     None               None   \n",
       "114581      Central Valley                     None               None   \n",
       "62029           Washington     Columbia Valley (WA)    Columbia Valley   \n",
       "120934    Mendoza Province                  Mendoza               None   \n",
       "96807           California              Paso Robles      Central Coast   \n",
       "117040          California              Paso Robles      Central Coast   \n",
       "45355           California              Paso Robles      Central Coast   \n",
       "81242         Rhône Valley             Saint-Joseph               None   \n",
       "80322     Mendoza Province                  Mendoza               None   \n",
       "95773           Washington     Columbia Valley (WA)    Columbia Valley   \n",
       "\n",
       "               taster_name taster_twitter_handle  \\\n",
       "93375    Michael Schachner           @wineschach   \n",
       "56109    Michael Schachner           @wineschach   \n",
       "100235        Paul Gregutt           @paulgwine    \n",
       "68750         Paul Gregutt           @paulgwine    \n",
       "57235     Sean P. Sullivan         @wawinereport   \n",
       "26499     Sean P. Sullivan         @wawinereport   \n",
       "116037    Sean P. Sullivan         @wawinereport   \n",
       "108391    Sean P. Sullivan         @wawinereport   \n",
       "73229     Sean P. Sullivan         @wawinereport   \n",
       "92133           Roger Voss            @vossroger   \n",
       "123570                None                  None   \n",
       "107357  Alexander Peartree                  None   \n",
       "125397      Joe Czerwinski                @JoeCz   \n",
       "106179  Anna Lee C. Iijima                  None   \n",
       "72010         Paul Gregutt           @paulgwine    \n",
       "124803        Paul Gregutt           @paulgwine    \n",
       "70727     Sean P. Sullivan         @wawinereport   \n",
       "76084     Sean P. Sullivan         @wawinereport   \n",
       "110206      Joe Czerwinski                @JoeCz   \n",
       "57492     Sean P. Sullivan         @wawinereport   \n",
       "21553       Joe Czerwinski                @JoeCz   \n",
       "117812      Virginie Boone               @vboone   \n",
       "119356        Paul Gregutt           @paulgwine    \n",
       "106214    Sean P. Sullivan         @wawinereport   \n",
       "82071     Sean P. Sullivan         @wawinereport   \n",
       "126614    Sean P. Sullivan         @wawinereport   \n",
       "126596    Sean P. Sullivan         @wawinereport   \n",
       "60595     Sean P. Sullivan         @wawinereport   \n",
       "60596     Sean P. Sullivan         @wawinereport   \n",
       "115430    Sean P. Sullivan         @wawinereport   \n",
       "...                    ...                   ...   \n",
       "93378        Matt Kettmann         @mattkettmann   \n",
       "65142                 None                  None   \n",
       "85567                 None                  None   \n",
       "89122    Michael Schachner           @wineschach   \n",
       "35273    Michael Schachner           @wineschach   \n",
       "125678   Michael Schachner           @wineschach   \n",
       "123301   Michael Schachner           @wineschach   \n",
       "21139    Michael Schachner           @wineschach   \n",
       "96588    Michael Schachner           @wineschach   \n",
       "125015   Michael Schachner           @wineschach   \n",
       "49266           Roger Voss            @vossroger   \n",
       "83815     Anne Krebiehl MW           @AnneInVino   \n",
       "31687                 None                  None   \n",
       "95841                 None                  None   \n",
       "76938         Paul Gregutt           @paulgwine    \n",
       "55932        Lauren Buzzeo             @laurbuzz   \n",
       "117036       Matt Kettmann         @mattkettmann   \n",
       "32963        Matt Kettmann         @mattkettmann   \n",
       "100706        Jeff Jenssen        @worldwineguys   \n",
       "126699   Michael Schachner           @wineschach   \n",
       "106477   Michael Schachner           @wineschach   \n",
       "114581   Michael Schachner           @wineschach   \n",
       "62029         Paul Gregutt           @paulgwine    \n",
       "120934   Michael Schachner           @wineschach   \n",
       "96807                 None                  None   \n",
       "117040       Matt Kettmann         @mattkettmann   \n",
       "45355        Matt Kettmann         @mattkettmann   \n",
       "81242       Joe Czerwinski                @JoeCz   \n",
       "80322    Michael Schachner           @wineschach   \n",
       "95773         Paul Gregutt           @paulgwine    \n",
       "\n",
       "                                                    title  \\\n",
       "93375                      1+1=3 NV Brut Sparkling (Cava)   \n",
       "56109   1+1=3 NV Cygnus Brut Nature Reserva Made With ...   \n",
       "100235  14 Hands 2011 Hot To Trot Red (Columbia Valley...   \n",
       "68750                 14 Hands 2013 Riesling (Washington)   \n",
       "57235   14 Hands 2013 The Reserve Cabernet Sauvignon (...   \n",
       "26499   14 Hands 2014 Limited Release Kentucky Derby R...   \n",
       "116037  14 Hands 2015 Cabernet Sauvignon (Columbia Val...   \n",
       "108391  14 Hands NV Brut Méthode Champenoise Sparkling...   \n",
       "73229   18401 Cellars 2013 Proprietary Red (Walla Wall...   \n",
       "92133   1912 Winemakers 2011 Vinhas Velhas Branco Whit...   \n",
       "123570  2 Lads 2009 Cabernet Franc-Merlot (Old Mission...   \n",
       "107357     2 Lads 2013 Pinot Noir (Old Mission Peninsula)   \n",
       "125397                 2 Up 2014 Shiraz (South Australia)   \n",
       "106179                  240 Days 2015 Rosé (Finger Lakes)   \n",
       "72010   2Hawk 2014 Limited Reserve Tempranillo (Southe...   \n",
       "124803          3 Horse Ranch Vineyards 2011 Reserve Rosé   \n",
       "70727   3 Horse Ranch Vineyards 2013 Cabernet Sauvigno...   \n",
       "76084   3 Horse Ranch Vineyards 2014 Single Vineyard S...   \n",
       "110206        3 Stones 2009 Sauvignon Blanc (Marlborough)   \n",
       "57492           4 Cellars 2014 Red (Columbia Valley (WA))   \n",
       "21553                     42°S 2008 Pinot Noir (Tasmania)   \n",
       "117812  6 North 2009 Flagstone Cabernet Sauvignon (Nap...   \n",
       "119356  :Nota Bene 2010 Una Notte Red (Columbia Valley...   \n",
       "106214  :Nota Bene 2011 Ciel du Cheval Red (Red Mountain)   \n",
       "82071   :Nota Bene 2011 Ciel du Cheval Vineyard Syrah ...   \n",
       "126614  :Nota Bene 2012 Arianses Vineyard Red (Wahluke...   \n",
       "126596  :Nota Bene 2012 Una Notte Red (Columbia Valley...   \n",
       "60595   :Nota Bene 2013 Arianses Vineyard Red (Wahluke...   \n",
       "60596   :Nota Bene 2013 Ciel du Cheval Vineyard Red (R...   \n",
       "115430  :Nota Bene 2013 Ciel du Cheval Vineyard Syrah ...   \n",
       "...                                                   ...   \n",
       "93378   Zotovich Cellars 2013 Estate Chardonnay (Sta. ...   \n",
       "65142                     Zuani 2011 Vigne White (Collio)   \n",
       "85567                     Zuani 2011 Vigne White (Collio)   \n",
       "89122        Zuccardi 2007 Q Cabernet Sauvignon (Mendoza)   \n",
       "35273       Zuccardi 2012 Serie A Chardonnay (Uco Valley)   \n",
       "125678  Zuccardi 2012 Serie A Santa Rosa Bonarda (Mend...   \n",
       "123301  Zuccardi 2013 Serie A Cabernet Sauvignon (Vall...   \n",
       "21139               Zuccardi 2014 Q Malbec (Valle de Uco)   \n",
       "96588          Zudugarai 2011 White (Getariako Txakolina)   \n",
       "125015  Zudugarai 2014 Hondarrabi Zuri (Getariako Txak...   \n",
       "49266   Zull 2010 Aussere Bergen Grüner Veltliner (Nie...   \n",
       "83815   Zusslin 2012 Clos Liebenberg Sparkling (Créman...   \n",
       "31687   a-non-ah-mus 2010 Alisos Vineyard Syrah (Santa...   \n",
       "95841   db Winery 2010 Larner Vineyard Syrah (Santa Ba...   \n",
       "76938   de Lancellotti 2014 La Sorella Pinot Noir (Wil...   \n",
       "55932        de Trafford 2009 Chenin Blanc (Stellenbosch)   \n",
       "117036                kukkula 2012 Sisu Red (Paso Robles)   \n",
       "32963          kukkula 2013 Aatto Red (Adelaida District)   \n",
       "100706                       majoros 2013 Furmint (Tokaj)   \n",
       "126699              oops 2007 Chardonnay (Central Valley)   \n",
       "106477         oops 2009 Sauvignon Blanc (Central Valley)   \n",
       "114581              oops 2011 Chardonnay (Central Valley)   \n",
       "62029    the Ghost of 413 2010 Red (Columbia Valley (WA))   \n",
       "120934     Árido 2010 Sustainably Farmed Malbec (Mendoza)   \n",
       "96807   Écluse 2010 Ensemble Lock Vineyard Red (Paso R...   \n",
       "117040               Écluse 2013 Improv Red (Paso Robles)   \n",
       "45355             Écluse 2013 Rendition Red (Paso Robles)   \n",
       "81242   Éric & Jöel Durand 2010 Les Coteaux  (Saint-Jo...   \n",
       "80322   Öko 2013 Made With Organically Grown Grapes Ma...   \n",
       "95773         àMaurice 2009 Malbec (Columbia Valley (WA))   \n",
       "\n",
       "                         variety                   winery  \n",
       "93375            Sparkling Blend                    1+1=3  \n",
       "56109            Sparkling Blend                    1+1=3  \n",
       "100235                 Red Blend                 14 Hands  \n",
       "68750                   Riesling                 14 Hands  \n",
       "57235         Cabernet Sauvignon                 14 Hands  \n",
       "26499                  Red Blend                 14 Hands  \n",
       "116037        Cabernet Sauvignon                 14 Hands  \n",
       "108391           Sparkling Blend                 14 Hands  \n",
       "73229   Bordeaux-style Red Blend            18401 Cellars  \n",
       "92133           Portuguese White          1912 Winemakers  \n",
       "123570     Cabernet Franc-Merlot                   2 Lads  \n",
       "107357                Pinot Noir                   2 Lads  \n",
       "125397                    Shiraz                     2 Up  \n",
       "106179                      Rosé                 240 Days  \n",
       "72010                Tempranillo                    2Hawk  \n",
       "124803                      Rosé  3 Horse Ranch Vineyards  \n",
       "70727         Cabernet Sauvignon  3 Horse Ranch Vineyards  \n",
       "76084                      Syrah  3 Horse Ranch Vineyards  \n",
       "110206           Sauvignon Blanc                 3 Stones  \n",
       "57492                  Red Blend                4 Cellars  \n",
       "21553                 Pinot Noir                     42°S  \n",
       "117812        Cabernet Sauvignon                  6 North  \n",
       "119356     Rhône-style Red Blend               :Nota Bene  \n",
       "106214  Bordeaux-style Red Blend               :Nota Bene  \n",
       "82071                      Syrah               :Nota Bene  \n",
       "126614  Bordeaux-style Red Blend               :Nota Bene  \n",
       "126596     Rhône-style Red Blend               :Nota Bene  \n",
       "60595   Bordeaux-style Red Blend               :Nota Bene  \n",
       "60596   Bordeaux-style Red Blend               :Nota Bene  \n",
       "115430                     Syrah               :Nota Bene  \n",
       "...                          ...                      ...  \n",
       "93378                 Chardonnay         Zotovich Cellars  \n",
       "65142                White Blend                    Zuani  \n",
       "85567                White Blend                    Zuani  \n",
       "89122         Cabernet Sauvignon                 Zuccardi  \n",
       "35273                 Chardonnay                 Zuccardi  \n",
       "125678                   Bonarda                 Zuccardi  \n",
       "123301        Cabernet Sauvignon                 Zuccardi  \n",
       "21139                     Malbec                 Zuccardi  \n",
       "96588                White Blend                Zudugarai  \n",
       "125015           Hondarrabi Zuri                Zudugarai  \n",
       "49266           Grüner Veltliner                     Zull  \n",
       "83815            Sparkling Blend                  Zusslin  \n",
       "31687                      Syrah             a-non-ah-mus  \n",
       "95841                      Syrah                db Winery  \n",
       "76938                 Pinot Noir           de Lancellotti  \n",
       "55932               Chenin Blanc              de Trafford  \n",
       "117036     Rhône-style Red Blend                  kukkula  \n",
       "32963      Rhône-style Red Blend                  kukkula  \n",
       "100706                   Furmint                  majoros  \n",
       "126699                Chardonnay                     oops  \n",
       "106477           Sauvignon Blanc                     oops  \n",
       "114581                Chardonnay                     oops  \n",
       "62029                  Red Blend         the Ghost of 413  \n",
       "120934                    Malbec                    Árido  \n",
       "96807   Bordeaux-style Red Blend                   Écluse  \n",
       "117040                 Red Blend                   Écluse  \n",
       "45355      Rhône-style Red Blend                   Écluse  \n",
       "81242                      Syrah       Éric & Jöel Durand  \n",
       "80322                     Malbec                      Öko  \n",
       "95773                     Malbec                 àMaurice  \n",
       "\n",
       "[11131 rows x 13 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wine[wine.duplicated(['title'])].sort_values('title')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Ploting the top 15 region_1 that produce the most wine\n",
    "\n",
    "If you refer to the chart below you'll notice that there are an enormous amount of wine that haven't been categorized to a region_1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "wine.region_1.value_counts().head(10).plot(kind='bar');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "After removing all wines without a region_1 assigned you'll notice in the bar plot below the top 10 region_1 with Napa Valley being the region_1 that produces the most wine."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "wine.loc[wine['region_1'] != 'None', :].region_1.value_counts().head(15).plot(kind='bar');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Ploting the top 15 region_2 that produce the most wine\n",
    "\n",
    "If you refer to the chart below you'll notice that there are an enormous amount of wine that haven't been categorized to a region_2. Similar to Region_1."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "wine.region_2.value_counts().plot(kind='bar');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "After removing all wines without a region_2 assigned you'll notice in the bar plot below the top 10 region_2 with Central Coast being the region_2 that produces the most wine."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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A/fLNNYE/D/IlXgs8Wqi5ozluk7FHW9wmY4+2uE3GHm1xm4w9EuKuFhHjB/PAkVI+YzawStvtCcCDfR8UEVOBqUMNLml6REzuvnljI26TsUdb3CZjj7a4TcYebXGbjD3a4o6UbqUbgUmSVpe0MLA7cO4wt8nM7FVrRFw5RMRLkv4fcBEwDjghIu4Y5maZmb1qjYjkABARFwAXNBR+yF1RYzRuk7FHW9wmY4+2uE3GHm1xm4w9quKOiAFpMzMbWUbKmIOZmY0gTg42YkhaQNJmw90OG1mUrDLvR1pJYzI55HUT8zw2Ukj6f5KWHe52DIWksyTtIKnYeygiXgG+WyrecMgJbqnhbse8SJouaf/R8L6L1Pf9v6XjSnr/QF8F4l86mGNDjDlO0iV1YgzWmEwOwKGDPDZSvB64UdLpuQChmngRSa+TtGrrq2a4Y4EPAzMlHSlprQJNBLhY0gea+BlI+rakpSQtJOlSSY9K+kiBuL/OcZcA7gT+LOng+i3u9Rolf3eQpouvRHrfnSZpmxI/c0mLSPqwpP+W9NXWV/3mcp2kjQrEabdj/toXOB7YM38dB3T9vpC0qKTlgNdKWlbScvlrIuln3rWIeBl4VtLSdeIMxpgakJa0HbA98CHgN213LQWsExEbF3qdHYB1gUVbxyLi8JoxBWwN7ANMBk4Hjo+Iv9aJm2O/j3RGvhLwCLAacFdErFsg9tLAHsCXSCVQ/gf4VUS82GW8p4ElgJeB5wCRTh5rn41LujUi3ippF2Bn4LPA5RHxlkJx9wTeBnwRuCki3lygzY397nL8BYD3kpL9K8AJwDER8ViX8S4EngRuIv0OAYiIWleEku4kVUW4F3iGnvdFiZ/xecAnIuKhfHtF4CcR0dXVg6QDgc+QfmcP5LYCPAX8T0T8uGZ7Twc2AaaRfhYARMQBdeL2NWKmshbyIDAdeB/pzdnyNOmDoDZJPwMWB95FOsP4IHBD3bgREZL+AfwDeAlYFjhT0rSI+ELN8EeQ3kyXRMQGkt5F+kCvRdLypDOsjwK3AKcAmwN7A+/sJmZEvKZuuwawUP53e+DUiHis0AXKQpIWIiWcH0fEi5JKnXU18rsDkPRm0snI9sBZ9Pz+LgPe2mXYCRGxbYn29bFdAzFbJrYSQ/Yw8KZug0XEMcAxkj4dET+q3bqq8/NXsyJizH0BC7V9vyzw5oKxb+vz75LAxTVjHkBKZhcBu7baT+r2+2uBNk/P//4JWCB/f0PNmL8ldaEcCqzY6fW6jCtSwvlKvr0Kqc5Wid/dkcDdpES2EDAeuL5A3ANIZ4gX5PavBvyhUJuL/+5yjJuAS0ldg4v0/d3WiDsVWL/E/71D7M2BffL344HVC8X9cf7b+w/Sic3vgR8ViLsr8Jr8/Zfz38yGhdq8GLBmEz/nua/RZPDh+gKuIHUlLQfcl/8Qvlco9vX53+tIl42LADNrxjycVBCr031rF2jzJTmJ/Rg4FTgGuLZmzC0b+t0dS9rb4658e1ngxoLxlwXG5e+XAF7f0P9jwUJxWr+7H5X63eW4b2jo/30n8AKpKOZtwAzyiVTNuFOA3wF/ybdXAq4p2O73A9/PX7sUitk6gdwc+ANpG4ISJyM75p/vPfn2W4FzS/8ux9SYQ4ukWyJdgn8cWCUipki6Lcr0T36F9Ie6FelDLIDjIuIrNeNuDkyKiBMljQeWjIh76rY3x14CeJ50VrsnsDRwSkT8s0bMxYGDgFUjYj9Jk0hnMufVbOvNEbFh63eYj/0pao4LNNFmSQcNdH9EfK+buH1eo/jvLsddAfgmsFJEbKe0udamEXF8zbirdToeEX+vGfdWYAPg5rb3RZG/6aa0fQ59C5gREb9uf1/XiHsTsCVwRdvPYkZErF+g2XON1dlKC+ZBpQ8BtT6s+oqIIyLiiYg4i9R9sFaBxDCFNIjZmlG1EPCrei3tERHPkC7DtwceA06v++ECnEg6Q2ytS5gNfL1mTIAXlXYGTH1MKVG+UiAulG/za+bxVVtEPBNphsripDPnX5F/NjX9gtSV0po98xfSIGotOQksQ89MoGXqJobshUhnsq33xRIFYpJjvV/STElPSnpK0tOSnioQ+gFJPyd9Dl0gaRHKfOa+FBFP9jlW/Cx/rA1ItxxOeuNfHRE3SnoDMLNE4PzBtQMwkfzzk1T3LHEX8lkRQEQ8KKnYwGy+gvoqaaBRwI8kHR4RJ9QIu0ZE7CZpD4CIeK7Q9NMfAmcDr5P0DdKA/5cLxIXCbY6IrxVqV78k/Sfp/fwcKUmK9EHwhpqhXxsRp0s6FOYWv3x5Xk+alzxT5xOk/nWAX0maGvUHZk/PH7TLSPoE8DHSzLgSvg3sGBF3FYrX8iFgW+DoiHgin7CWmOJ8u6QPA+Py1e8BwLUF4vYyJpNDRJwBnNF2+2/ABwqF/x3pMn8G5c5oX4iIaM1wKXlWlB0MbNC6WsizjK4lTVvs1guSFqPnTG4N4F91GxoRp+TL5q1IH4Q7F/yjLdpmST8c6P4oM7Xw88C6EVF6k5hn8vug9bPYhDQFta59gbfnq1UkHQX8kdQV27WIOFrSe0jTQdcEvhoR0+o2Nnu4gcRARDwL/La1RiUfvrtA6E+Tpo7/izQOdRFpVltRYzI5SFqU9CbtuxbhYwXCT2ign7PJsyJI3SdPt91+mt7bsnZjCnAhsIqkU4B3kGZ7lDCT9CHQujJbNSLuKxC3dJtvmvdDavsr8GwDcQ8i7ZmyhqRrSN2OHywQV7Stb8jfF5kvnJNBqYTQbrqk35BWYc89WYiI3/b/lHnrsEZlVVJyqLVGJSedL+WvxozVAekzSL+ED5MuyfckzX45sEDso4BLI+LiurH6xH0PaRGcgIsKnhUh6WRgfeAc0pniTqS1GX+B7gdO85nnJqQ2X1fi7FbSp0kf4g/T88ESpRJyE21ukqQNSGMl19P7g6v2VYmkBUln4QL+HF0uXOwT8yDSdNCz86GdgV9ExA9qxn0/cBTwOlJ7Sy6OPLHD4ah7MinpT6SB415rVCJiv3k8dV5x30S6opxI2wl+RGxZJ27ldcZocmjNErgtIt6cFyhdVOKHl1fX/oo0sPQiBd+kTckD3v0aSt+5pA3nEevmwcbqJ/4sUrdE3QHzTrEPj4ivtt1eAPhlROzZZbwfRMRnJP2ODgOCEfG+7ls79zVuAK6mTzdmRJzUZbwBV/3WPVvOr7EhafqmgKsi4pYCMWfRzLhAY5S378xJYoOIeEXSDVGzUkOO9zOqq9CLXsmOyW4l0oc2wBOS1iOtOp5YKPZ3gU1JU9NqZValUhGdYhRNOIUHTgcqgxCkM6U67qdM33cnq0o6NCK+lWeOnEGeBNClX+Z/j67ftH69FBEDTpkdoh0HuC/oGUjuilJNoXvzV+vYQgWuShoZF4BGu6GfkLQkaY3DKZIeIVU/qOuliDi2QJwBjdUrh4+TygG8mXRJviRpxe3PC8S+CNguUgXRUSFPB/0C1Td/0cvQOtrWDKxL6uo4n97dKCXWDIhUImIGqfzJ7yPi+3XjNinP2Po7aSJE+8+jq9pHTZN0L2lV++Okk5xlgIdIfe6fGOrZbduVzr+TClQWHRfIr9FIN3TpNSo58UKanfQIqeuusffEmEwOTZL0C9I0wt9T88Or7ZfdUalftqSLSYUIPw98ktQnPCcivthFrEa6JebR9RVRo7Bhn66whYCfA9eQKnGW6Ap7B3AYad3LgvRc+dWdboqkTgshu46thhfuKdUeOzsiLsq3tyZN5zydVNDv7UOM12k8oKX2uEB+jSa7oVcAWtVkb4iIR2rEuod0dddpgL/I+63dmOxWUqoUehjwb/nQFcARHRaOdOOe/LVw/qrjJgb4ZVN/LnvL8hFxvKQDI+JK4EpJV3YZq5FuiVbXl6Rd81TkuVR/L46+XWGPA+vk4yW6wo4nFXbs1QdcQkSsXjIehRbnDWByRHyydSMiLpb0zYg4KHflDUlE7AMpAUfENe335aRcQiPd0JI+BHyH9PnTWl90cESc2U281ntB0qIR8Xyf11q087O6NyavHCSdBdwOtAbtPgq8JboswdvPa7yGlK3/r1TMpki6LiI2yV1iPyRVrz0zItYY5qZVKJfPmNexkUTS9UM9Ix5C7IWATwFb5ENXAD8vMbOoCfkq9VLgtHxoN+A9pKuHG7v9PTb5vuinG/qrEfGzmnH/BLyndbWQu3cvifol4ufL38iYvHIgrYRtX/T2NaXaLLXlM4tfkor6IelRYK+IuKNm3GWBSfQeE7iqTsw2X89XU58jLUZaigIlzFVwXwv17MWxcp/FZUtRZhCv9Tol29z6Y7xc0ndIV03tXY21uquyY0ldYT/Ntz+aj328TtAGB2E/TJqK3Nq57ep8bBxpxfBQ27kpqdzJ+D5dYkvlmLVFxHH52yspd7UOqYpuezfSP6lRPkPS64GVgcXyFOdWj8NSpPIqRY3V5PCcpM0j4mqYe/n5XKHYU4GDIuLyHPudpAVrXe99nM9cDgQmALeS5uH/kfrdHQBET2G5J0kDsbWp/L4WD5K6ZUbTXhx9u6smt31forsKYKM+Z5qX5TPSun5JGoTdhrZB2LpB87qRT0tassNV9awuQi5MOpNfkN5dYk9Rc9Fe0+MvwIX5av3UfHs30lhlt7YhLdqcALS37Sngv2vE7Wisdiu9BTiZNDsAUh/zf0RE7T8qdagQ2unYEGPOIA1aXRdpR7G1gK9FxG412zrQ9owREV0vuW8bvGv9uyRpH4Ctu42Z4y5J6u8N0l4Wzw/8jCHFbqrNb4hUomXAY13GvhnYNfKOgEp1ws6s24XQ1CCspM1IiXfJiFg1/y3+Z0T8V824q5KKRkbk0hx1zWMSRJEp4HkCR/uaj7Pn8ZTBxPxApMKfjRqTVw45CbxFeaP3iChRYbHlb0plu1tz3D9CGqCu4/mIeF4SkhaJiLslrVkzJrRtIdhmCVJ3wvLUq8fSuhJ7VtJKpEvmrgdPlVbrfpO0M9l9pMvvCXm2ypcK9bEXbXObM4G+H9ZnkLYMretgUrfV32DuRkL7FIjb1Fqg75POcM+F9LcoaYuBnzIwSZ8iVSxeIt/+P+CoiPjpgE+ch8Lrf+aS9EZghYi4Js/e+20+voWkNaLG1r/5d7WTUsHEIO2fcXREzCjR9nZjKjnky8QnI9ekbyUFpZIM46LmEv7sY8DXSL9wAVdR/491tqRlSP200yQ9TupmqSXa9u3NA+gHktp6GgMvZhuM83Kbv0NaSBbUqwf1HVK3wRsi4mmAnNyPzl+1S59QuM35Cm9dYOk+U3yXoq0fv46IuFR53wnS++3uiKhd4BCYmse5vkz6IF8SqFV6viUi7lfvYrddz+CS9GVSl+07W1di+erpGEnLRUTtMvGSvk0q3f4cqfbWW4DPRES3ZfN/QOdunmfzfQPN+BuonTuR/ha+mf8V6QTkt5I+HxHndNfcfl5vLHUrSbqdtA3fC32OL0KaKTFiNwZpkfTvpO6wC/v+P7qMtxypyNqepNlbx0TE4zXiVVa75p/vonWmCkuaCbwp+rwhlUqk3x0Rk7qN3c/rLUL6AF8rIq7vMsZOpNpB7yOfKWdPA6dFRJEyyrmrZiK96+ic3GWsFSLi4RLt6if+maT+8B+Txs4OIE1v3b3LeH8mzTTsO3VzMeBPEdH1Xs9tsW7N3bm7kH6fnwUu77arWNLtEbFeP/d1vSlPHmvaKSLu7XN8InBO3VlQfY2pKwdSf2TlAzUi/iWV2UleBYteSTof+DXwv61+1LwOoYg8g+b99OzrW2La7QOSziENsl0eyb+oX647+iaGfPBl5VLmJbXarLQ6dtV5Pb6fGOcA50jaNCL+WLSBmaRfAmuQJiq0zsCDNKbWjT/lMa5TgbPqJPR+fJK0lenKpGrAFwP71wnYadwp0l4cpaoULJT/3R44NSIeq/lxMdBV42I14i7UNzEARMS9ecyoqLGWHDqeGSmtUizlDFLRq+Oov+BpKrA78ANJl5H+YC8occWQfY70of1l4Ettb/g6tZvWJs0S+Qpwcj5TPLXbs+82d0raq+8ZsaSPUKYGfn9KnDTcL+lsUgnwIE3fPDAiZheIPRlYp1Pi7NLKwLtJ77tvSfoj6X13bkTUmtGXr/I+Gl0WMuySxnPwAAAZMklEQVTHbElbRcSlfV5rS1JZjhJ+J+luUrfSfymtR6gzEeJGSZ+IiF5dlpL2pV6Z9xfVoXy90tasxaZ7z407xrqV9iJdxn6OnoJqbyPt9PST6LKSZZ/XuCkiSgw0tsdcjNQ1sTupqN8FpA/cJmrXF5MHdXcltft1pK6UrmrMS1qZNI7zHD0rxzcinWntEhEPFGl09XXvi4iurhzaYkwjXQG2T1LYMyLeU6B9ZwAHRESpD8L22AsD25F+f+8ilaKv9cEu6YqIeGeB5rXirUsqNX81vd8X7yB1sdRaX9T2OssCT+Ur1cWBpSLiH13GWoFU9+gFepLBZNK03F1qxN2Z9Fn2TXr/LA4BvhgR/zvA04f+emMpOcDcxVSHAOuRfnh3AEdGRJ35xe3xD6PBoleS3kwaG3hzRBRZ5NOkPB30/aRxjRUjotZVWj4jXJd0Rn9H3zPGLmN2LKmdX2PLiKi18546T2++NSLeWidujnM58FbSeoz291vtcuA5/iRgD1JCeybyhvU14n2DNGb2G9pmy0WNBYFKC/Y+TNv7glTArtY0ZzVcvlxp/4bW2MMdEXFZnXg55ltIJ7+tn8XtwHejwDT9ymuNteTQNBUuhJZjrkBaPbo7sCKp6+rUiCiyqru0/Me6I+lD5R2kGR6nARdHRNHaQiXkQf5+1R3nkXQJ8At6FjvtAewTEVvViZtjd2x7nTYrrRnYjdTOJUi/u9OiQEnsnMz6im7G5Jqm+VDUbzRzchhGSluC7kGapvhb0h/oNQM/a3hJ+jWpz/oq0ofKeXXP4Ea7/GH7Y1KXIKSKrwdGxN8LxS9Z2fNa0rjDGaT32/QCTbQxyMlhiFSwEFo+czmVVIxrVOwPIWlv0qrip+f5YKtN1cqe/wZ0XdkzX4lcVXCAuz32eqRFe+vS8AIta56TwxBJOo409a294uvLEVGrEJqNXpImkAoaFp+tpIYqe5bWtkDrW8B0ehZoHQoUX6BlzRtTyUHNF9JqpLaS9ZC0CemDdm3S7I5xpIHSWlum5mmWR0bEwfVbWYnd5GylXoumlPa9/lO3C6ma0vQCLTW4oVJT8oD3UaSZfKLeFPL2uOOBT1Bda1V0jGSsrXNoeiMTgJfVVh8lL+UfcYOwo9iPSQPzZ5Cm/+0FvLFu0DxF8W2S1ECXyviIaB/c/IWkzxSK3amy5wWFYpfU9AKtxjZU6mfW0pOkfeK7Ht8hTTvdscRAfx/nkPalvoQGP3vGVHKIhgpp9dFeCA1S9i5RCA1Jr6N3bf37Bnj4sMpzwT8HrBoRn8hTIteMnvLgXYuIWZLG5ZlPJ+ZB1BJuIa1oPoPe0yzr7kP8aF6s1z5bqat9gvuKiIPVu7Ln1KhR2bPBq+umF2g9WWo6egf7kiYTtGZavRO4DniTpMMj4pf9PXEeHm4gMQAsHl1s8TtUYyo5tKiBjUwkbQTcHz2F0P6TNGvnYqDWHGNJ7yMVwluJtIZiNVJt/XXrxG3YiaSzuNYMndmks/26yeHZvDjrVqWCaA+Rq3EWsBzpQ7t9WmXXW5u2+Rjpiuf7Od61+VgREfFbSVeRBqPrnjA0dXU9BbhEUscFWgXiN7mh0ivA2q3KCnl22LHA20mz8oaUHNquRKZL+g2poGZ7m+u+386TtH1ENHoFOabGHFrymeHdpIUzczcyiYiuK3sq1dV/d6S6K1uQpnF+mrRAae2I6HrjkdxfuyVpoHGDvHhmj4jYr9uYTZM0PSImK+8LkI/VHnvJZ5qPkAb9P0taUPXTiOhmo5hRS9J5wCERcbukFUkr/qeTdir7nyhTYbioJhdoNbl+osO4jkhdSuu1v7+HEK/R9ROSniadML1AT+n12mMZfY3JKwfgjRGxq6SdIuKkPDf/opoxx7Wtgt6NdHl/FnCW6m9B+mJE/FPSApIWiIjLJR1VM2bTXshlPwJA0hrUL75H29qA50il0YtRKpp4LKnW/np5Nfr7osuyz5IujrxRkKRDI+JbBZu7ekTcnr/fB5gWEXsplV6/hlT6uWtNXF3nJLBXnXYNELvIDob9+ENOxmfk2x8ArpK0BPDEUINFxD6QBtH7rlvKA+u1RMT8GFvtfj/TEa7vRiZLU38jk3FKG9IAbAW0L4Wvm2SfyGUorgJOkXQMDRTSKuww0sroVSSdQtpUvuvuA0mn539nSLqt71eRFqe9Gw4lvz8i4jbS4He3xrd9v2uNOJ20r5vZijwIndeXlFgT80vg9aSNea4kbT05YteuSFpa0vckTc9f31XaF72E/Ukr3N8KbECqeLt/RDxTMyn9aJDHhkzS+yQdnb/eWyJmX2P1yqGJjUxOBa6U9CjprPYPAEq7PtUte7wTqQrkZ0ldYEuTusNGrIi4WNJNpJr9Is3rf7RGyFaXXyNv9GzxiLhBvcsx10nCTfbJ3q+0SdVs0i5zF8LcIo0lZv80cXXdpBNI3VQfyrc/Shr3GrA+0mDk2Wtn5q/aJG1K2qBofJ8JAEuRpmbXjX8kaTznlHzoQEmbR8QhdWO3G3PJIc8DfyrShjZXkfpoa4uIb0i6lFT76OK26ZALkMYe6sRu386zduXY+UHSpZFqB53f4diQRa46WqrkRD8ezd1fra6wD1Kv7PMbJJ1LSo6t7+eKesXx9iWdILwb2C0iWt0bm5A+FOtqapvQpqwRER9ou/21At25QCPrERYmnZAuSO8JAE+Ryt3XtT3w1lZVBUknkWbiOTkMJCJekfT/gNMbiH1dh2N/6TaepKsjYvM8wBTkNyX135yNyX3ViwOvzVdnrdPwpUizrerGb2ThULY/aQ+NtSQ9QNr7+yM14u3U9v3RdRrWV55f/8n2Y5JeHxGX0zPlso5GtglVcwu0nstnx1fn13kHPXuC11V0PUJEXCnpatIGW01Nr18GaI2Blupe62XMJYdsmqTPUy0bXKSsdikRsXn+d74MMBXyn8BnSIngJnqSw1PATwrEb2rhEJH2IH53HmhcIGrWh4qCu/YN0gWkLqZamrq6zppaoPUp4KQ8ziDSB+N/FIpdfD1CXnS5XMmYbb4F3JJncIlU563TntW1jNWprMXLajdN0oakhU4BXB0RtwxzkwYk6YCI+GGfY4tE2n6zTtxrIqL2jI5+YndaAPYkcFOM0PLo7bqZVjlArKsiYot5P3LIcYvsYzFA/KUAIuKpgjGPIQ3OF12PIOm7wCTSLKiSiy7J05s3IiWH66PLDYQGfI0xmhwWjeqG5JVjI4Wkr5Jmu7TeNDsDZ3Q7xXJ+kHRzRGw4r2NdxG3kDzXH/jWpJMfv8qEdgBuBtUg/72/XfY0mSfqviPhpoVhfIXXLFL26lvR14NrSC7SaTOz9rEsosR6hqbiVsb064339vs4YTQ6NfHA1RdJdwAat5JVnpNwcEWsPb8uqJL2etB/Ar0iLDNvHHH4WEWvVjN/IH1SOfRHwgYj4v3x7SdIMlV1IHzLr1H2NpqhwaZWmrq7Vs0DrX6RB71LF5kZ1Yi+hbbzvclKJj/a/vd+X/rwYU2MObR9ci0nagN4/vMWHrWHzdi/pD791ZbMI8Ndha83AtiH19U4A2uvwPEXNfk+lyqm3RcT368QZwKqkVaUtLwKrRcRzkrruDsuDsF8E1qH3B3iJ1btNlVZZu9PVdZ2ASnOE162buPqxPLBhW2KfQkrsW5DGvrpODmqo5HoDcdvH+9rLhpQa7+tlTCUH+v/gepoGBmzqkvQj0pvmX8AdSqWfA3gP6Y004kTESaSBwQ/kFeIlY7+cPwybSg6/Bq6T1NpbYEfg1DxAfWeNuKeQumd2IM0w2huYU6ehbY4gTV/tVVqlQNxrqQ5udzo2aBERks4m7eNQWiOJPTuR9N5oLWT8SD5Wt+R60bgRcQxwjKRPR0SRxXQDGavdSsU/uJqgtKtav/IH8YiUr9K+AawUEdtJWgfYNCKOrxm3+Ab1feJPJp3JiTTwX3ubTEk3RcTbJN0WEW/Ox66MiAH3rh5k7FYNqz+Ruh5fkXRDRGzcZbymuwV/AvwiIm6sE6dD3K+Quv/aE/u5pKuqqRGxZ43YlUH0EgPrDcZtqsR4L2PtyqHlPEkfpjrXekStOh7JH/6DcGL++lK+/RfSB3qt5EBaWQq9V4gHvSup1nEL8CD5faEOZaa70FpQ9pCkHXL8CTVjtrRKq/yBVFrlEeqt6m766vpdwCcl3UtK7q0xhzfXCRoRR0i6gJ7S5Z9sS+xdJ4asqZLrTcVtqsR4L2P1yuFC8kwG2uZaR8R3h61RA1CqjXIE1V2uRtwiuBZJN0bERupdlbXRaYx1KZWjmAI8THpfFPngyr+/PwCrkPqYlwK+FhHnDvjEwcVegjQWJXpKq5wSEbU+ZJq6ulaqqlsRBVa+S9ocmBQRJ+ZxniUjotPA+lDjrkoqub4pPSXXDygw6N8p7oF1fxaSfgd8PKolxj9O2h98vTrxW8bqlcOEiNh2uBsxBD8g1YiZEaMnWz8jaXl6SlFsQv0aU+RFTlNIA42QisIdHhG1Y5PqN61Z94O1XR5EnxRpk6MnSWfOxUTEM7kraGPSwq+LCrW/kavriPh7pw/xWi1l7gD0ZGBN0hXrQqSusRJVTu8DepU6UdrJr1bl205xC5nYSgzZI8CbIm0n8GJ/TxqqsZocrpW0fkTMGO6GDNL9wO2jKDEAHETq811D0jWkCqUl6sY0VmCN9HMukWTmanoQXdLHga+SqgAL+FHuOjihZuhz6Lm6rl1qvaXBD/FdSBVTbwaIiAeVypc35SC6TA553VJ/IiKO6K5JcxUtMd6fsdqtdCdp3+F7SG/8It0HTVHaZe4I0lly+8KvbrdsnC+USpivSfr5/jkiap+1NDWIl+McT2rv+RT8OTc5iC7pz8BmrauFfLV2bUSsWTPu7aW6H/rEvZX8Id7W3Xhb3b+91iB8a71S/iD8Y1N/05Luj4hVunzu5zocXoI0VrB8RNS6kspThj9A28QK4KzSJ5dj9cphu+FuwBB9A/g/0hz5hYe5LYOSu1O2p6dbYmtJJRJakwXW7stfC1P259zkIPpseu+z8DTpCqiupq6uX8hTWlvdjaW2eD1d0s+BZSR9grQN6/8Uit1J1x+07WOb+ermQNKGTaeRZlfVa1iULTHenzF55QDNDV41oTVdcbjbMRR55sjzwAzaNp+JmlUolbaaPJmeSpOPA3tH2phnxFEqYvfBiCheBTjHPxlYn9QNFKRKsDeQZod1nYyburpWKng5iTSX/1ukD/Ffl5iXL+k9wNa5rRdFxLSa8VrVkCt3AYtFRNcnz0pF9w4iTSI4CTgmUqHD2tRs5eKe1xmLyaG93zMi3iRpJdIS+0YKutWltHnHZRFx8XC3ZbBKdBX0iXdgRByjvLWiChZYk/SDiPhMnuVRecNHvX0XGitil2NPGej+bpNxw7OKSn+Ij8tx3l23bfODpO+QxsimAj+JvKq7YPxZNFS5uNfrjNHk0Ei/Z1PUUD2aJintcX1pqYTWGldQAzWwJL0tIm6S1HFRWtQsva2Gitg1bZRdXZ8LfLTQrLVGSXqF9Lf8Er1PRkrVmWqscnG7sTrm0FS/ZyNidO3n0HIdcHbuVimR0O7KC6fGq/ee0SW6O+ZAo/svtIoC7t92LCiwT0L+0P4CqZZSsbpNTc0qarDL43lghlKJmfYEfEDNuMVFxAINv8R0Sb+hgcrF7cZqcpjfg1e1SOrYJRERV83vtgzBd0mLe4qszYiIPfJ8/osoPzf8f8k1gySdFb23m6wtIlYvGa+PVt2m91K2blNTU0Ob2qzpfNq2pH2VWwp4ltR11xL0lPwvYkwmh4g4Ovd7PkU6M/pq3X7Phh3c9v2ipAVPN1GuZEQTZlJ4bUakDUveUipeG7V9X3zDJ0mLkwYfV42I/SRNIo13nVcg/PIRcXwek7kSuFJSiSugpq6ui++qlv2GNIAewF9jhO7NMj9ExD7z43XGVHKQ9EZghYi4JieDafn4FpLWiIgRWQY7InZsvy1pFWqUIJ5PHgKukPR7CqwZkHR6RHxI0gw699PW6VaKfr4v5URSMm9NaZ1NWqBUIjk0Vbep6NW1eorBFe3yyGtpvpnb93dgAWCC0r4fXyqxtma0kPSFiPi2eqo591K6i21MJQfSisZOxcOezfft2OG+kWg2UHyBUmH35K9SawYOzP++t0Csvt4i6SnyFMX8PZTrD18jInaTtAcp4HN5oVIJX1cqKfI5euo2fbZu0Aaurtv/tkp2eXwHeA2weuQ9v/NMtqPz14EDPHesaV2R1a4kPBhjarbSQKs+Jc2IiPXnd5sGo8+ZwALAW4F7I+Ijw9cqGyxJ1wJbAdfk1btrAKdGl2W1m9R+dd3n+BbAA3WvrltTked1bAjxZpLqBkWf4+OAuyNiUvettYGMtSuHgXayWmy+tWLo2s8EXiJ9sHT1xzS/lJ5FM48FSSN6Wi+pUOCFwCqSTiHN+PmPOgHVXH2epq+uf0R1w6BOxwYrOo1rRappNXbObIdA0puAz1Mtmlh0jHKsJYcbJX0iInr1nUral9QnPCLF6NzXoegsmlE6nReAiJgm6WbSjm0ilWV+tGbYZzocm1ufh1SLqxsTo8Nq84iYLmlilzGRtClpzGW8pIPa7loKGNdtXOBOSXtFxMl9Xu8jwN014o5mZwA/A46jbUuC0sZat9IKwNmk7QRbyWAyqU98lzwbZsToMPg69y5GcKFAoNHdz3Ks19H7iqSJfYlrkbRWRNwtqeNZcZTbva5Vn2df4HTgu9Hljl+SZkXEG4d63yDi/jtp05lPkj64Wp4GfhcRM7uMuzJpvOI50t90ABuRegJ2iYgHuok7mrX+9hp/nbGUHFqU9tltjT3cERGXDWd7+tNfCYOWEqUMmiLpuojYRNJFwA9Js2jOjIg1asZ9H2kNxUqkOvWrAXdFxLp121yapKl56urlHe6OAgvVitfnkXQqqVRLp6vrrSNit5rxV2vifStpS1IXpkh/05eWfo2RLr8fAA4g/W2cTe8ZYUVX5I/J5DAa5auejfLNG7o9M5xf1NDuZ0p7JW8JXBIRG+REv0dE7Fe3zaNJU/V5mr66zomy0xjBSF6zMypIuof0s+00Ey4iougaHieHEUDSh0hT9q4g/eL/DTg4IhotyTsSKVeozUlig4h4RbmW/3C3rS+lfTjub32gStqLVGf/78Bhdc7k5kN9nkauriW1d3csSvp5vBQRXygR3+YfJ4cRIH8Qvqd1tZBnAl0SEU2sFq6lvwU4LXUX4ki6BNiZVO75taTL540iYrMBnzgM8iD0uyNtz7gFqV7/p0lTkdeOiBI74416JceiDCTtClwYEU9L+jJpJtgREXFLydcZa7OVRqsF+nQj/ZO03mEkanoBzk6kwcfPkvral6b3Jjojybi2q4PdgKkRcRZwllJl4Fedtn5xSO/htwGvH6bmjFVfiYgzlKrqbkNaDPgz4O0lX8TJYWS4MA/snppv7wb8fhjb06+mpt12WJz1CnBSPiNfhpQwR5pxkhaMiJdIi+Dax0VerX9brRlFInWJ3UOaZWXltKav7gAcGxHnSDqs9Iu8Wt/AI0pEHJxr02xO+qOaGhFnD3OzOlI/G+a0RPcb54zG0ienkgrhPUq62vkDzE10I37fgSZEsxVqLXkg18V6N3CUpEVooKfBYw7DqOlSBk1QPxvmtESXeyaM4tInmwArAhdHxDP52JtIG+cUWecwmkhaCPgU0CpDfwXw81dTgbymKVUB3pZULn+mpBWB9aPwTpJODsNI0nnAf/ddsSppMjAl+lRrHcuaWpxl85ek40gbB7W6Hz8KvBwRHx++Vo1NTS8UdbfS8GqklEGT1H9pbQBqrOoelaVPrGKjPrPsLsuz8ayQDgtFVyWVEim6UNTJYXiNxkKBTZXW/gxp29E96bA4q/BrWXNeVtveKZLeQIP1f16ljiDV8eq1ULT0izg5DK/ReLa8m6RrgFvyLJ0iIuJhYLM+i7POH6mlT6xfBwOXS/obaXLFasB82bnsVeTFiPinpAUkLRARl0s6qvSLeMxhGI22QoEAko4mVd9cC7gNuBa4Bvhj6douNjrl2TNrkpLD3RHxr3k8xYZgfi0UdXIYAUZLocB2khYmJbLNgE3z1xMRsc6wNsyGRZOlRKw3pf2+nycl39ZC0VMiouhaICcH64rS1pWbkja22ZS0UG1GzKfNz21kcSmR5kn6DOkqvWiXbn885mBDImkqaVbE08D1pG6l79UtJW2jnkuJNG8CcAywlqTGu3RHav0eG7lWBRYB/gE8AMwGnhjWFtlIME5S62RzK6C9a9QnoQVExOfzuMLrSdUEHgM+Btwu6c7Sr+dfmg1JRGwrSaSrh82AzwHrSXqMdAYzZVgbaMPFpUTmn8VI+6csnb8eBGaUfhGPOVjXJE0gjTlsRlr3sHxELDO8rbLh4lIizerQpXsdcF1TXbq+crAhkXQAKRm8A3iR3OcJnEADZy82ekTEdR2O/WU42jJGtbp0ZzIfunR95WBDIul75IGwiHhouNtj9mrSp0t3M9IU+Ea6dJ0czMxGmfnRpevkYGY2CgzQpXsNaY3RKyVfz2MOZmajw0TgTOCz86NL11cOZmZW4UVwZmZW4eRgZmYVTg5mZlbh5GBmZhVODmZmVvH/AdCjcvukf9VpAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "wine.loc[wine['region_2'] != 'None', :].region_2.value_counts().head(15).plot(kind='bar');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Ploting the top 15 countries that produce the most wine\n",
    "The U.S. produces the most wine be a large margin with over 50k."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "wine.country.value_counts().head(15).plot(kind='bar');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Ploting the top 15 provinces that produce the most wine\n",
    "It appears that California produces the most wine with over 35k. The next closest province is Washington with close to 10k."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "wine.province.value_counts().head(15).plot(kind='bar');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Ploting the top 15 varieties that produce the most wine\n",
    "It appears that Pinot Noir produces the most wine with over 12k. Chardonnay comes second with slightly less than 12k followed by Cabernet Sauvignon with less than 10k."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "wine.variety.value_counts().head(15).plot(kind='bar');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Wine Summary Statistics\n",
    "The average points review for all wines is 88 out of 100 while the average price is $35. The cheapest wine is $4 while the lowest review is 80 out of 100. Conversely, the most expensive wine is $3300 while the highest review is 100.\n",
    "\n",
    "There's also a high standard deviation for price which indicates large distribution."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'wine' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-1-aec4e2afa535>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mwine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdescribe\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m: name 'wine' is not defined"
     ]
    }
   ],
   "source": [
    "wine.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Point review summary stats for a bottle of wine by country\n",
    "The table below describes the count of wines, the average review, and quartiles information per country. For example, the U.S. has 54,504 wines that average a point review of 88. The minimum review in the U.S. is 80 while the maximum is 100."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "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>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>country</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>US</th>\n",
       "      <td>54504.0</td>\n",
       "      <td>88.563720</td>\n",
       "      <td>3.114840</td>\n",
       "      <td>80.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>91.00</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>France</th>\n",
       "      <td>22093.0</td>\n",
       "      <td>88.845109</td>\n",
       "      <td>3.044423</td>\n",
       "      <td>80.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>91.00</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Italy</th>\n",
       "      <td>19540.0</td>\n",
       "      <td>88.562231</td>\n",
       "      <td>2.649756</td>\n",
       "      <td>80.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>90.00</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Spain</th>\n",
       "      <td>6645.0</td>\n",
       "      <td>87.288337</td>\n",
       "      <td>3.066284</td>\n",
       "      <td>80.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>89.00</td>\n",
       "      <td>98.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Portugal</th>\n",
       "      <td>5691.0</td>\n",
       "      <td>88.250220</td>\n",
       "      <td>2.996122</td>\n",
       "      <td>80.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>90.00</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Chile</th>\n",
       "      <td>4472.0</td>\n",
       "      <td>86.493515</td>\n",
       "      <td>2.692959</td>\n",
       "      <td>80.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>88.00</td>\n",
       "      <td>95.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Argentina</th>\n",
       "      <td>3800.0</td>\n",
       "      <td>86.710263</td>\n",
       "      <td>3.179627</td>\n",
       "      <td>80.0</td>\n",
       "      <td>84.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>89.00</td>\n",
       "      <td>97.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Austria</th>\n",
       "      <td>3345.0</td>\n",
       "      <td>90.101345</td>\n",
       "      <td>2.499799</td>\n",
       "      <td>82.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>92.00</td>\n",
       "      <td>98.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Australia</th>\n",
       "      <td>2329.0</td>\n",
       "      <td>88.580507</td>\n",
       "      <td>2.989900</td>\n",
       "      <td>80.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>91.00</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Germany</th>\n",
       "      <td>2165.0</td>\n",
       "      <td>89.851732</td>\n",
       "      <td>2.469351</td>\n",
       "      <td>81.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>91.00</td>\n",
       "      <td>98.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>New Zealand</th>\n",
       "      <td>1419.0</td>\n",
       "      <td>88.303030</td>\n",
       "      <td>2.435008</td>\n",
       "      <td>80.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>90.00</td>\n",
       "      <td>95.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Africa</th>\n",
       "      <td>1401.0</td>\n",
       "      <td>88.056388</td>\n",
       "      <td>2.435826</td>\n",
       "      <td>82.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>90.00</td>\n",
       "      <td>95.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Israel</th>\n",
       "      <td>505.0</td>\n",
       "      <td>88.471287</td>\n",
       "      <td>2.478412</td>\n",
       "      <td>80.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>90.00</td>\n",
       "      <td>94.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Greece</th>\n",
       "      <td>466.0</td>\n",
       "      <td>87.283262</td>\n",
       "      <td>2.185293</td>\n",
       "      <td>82.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>89.00</td>\n",
       "      <td>93.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Canada</th>\n",
       "      <td>257.0</td>\n",
       "      <td>89.369650</td>\n",
       "      <td>2.384752</td>\n",
       "      <td>82.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>91.00</td>\n",
       "      <td>94.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hungary</th>\n",
       "      <td>146.0</td>\n",
       "      <td>89.191781</td>\n",
       "      <td>2.686659</td>\n",
       "      <td>81.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>90.00</td>\n",
       "      <td>97.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bulgaria</th>\n",
       "      <td>141.0</td>\n",
       "      <td>87.936170</td>\n",
       "      <td>2.077817</td>\n",
       "      <td>80.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>89.00</td>\n",
       "      <td>91.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Romania</th>\n",
       "      <td>120.0</td>\n",
       "      <td>86.400000</td>\n",
       "      <td>1.716945</td>\n",
       "      <td>82.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>87.25</td>\n",
       "      <td>92.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Uruguay</th>\n",
       "      <td>109.0</td>\n",
       "      <td>86.752294</td>\n",
       "      <td>2.687957</td>\n",
       "      <td>80.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>88.00</td>\n",
       "      <td>92.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Turkey</th>\n",
       "      <td>90.0</td>\n",
       "      <td>88.088889</td>\n",
       "      <td>1.975379</td>\n",
       "      <td>84.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>90.00</td>\n",
       "      <td>92.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Slovenia</th>\n",
       "      <td>87.0</td>\n",
       "      <td>88.068966</td>\n",
       "      <td>1.730661</td>\n",
       "      <td>82.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>89.00</td>\n",
       "      <td>92.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Georgia</th>\n",
       "      <td>86.0</td>\n",
       "      <td>87.686047</td>\n",
       "      <td>2.087845</td>\n",
       "      <td>82.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>89.00</td>\n",
       "      <td>92.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>England</th>\n",
       "      <td>74.0</td>\n",
       "      <td>91.581081</td>\n",
       "      <td>1.843216</td>\n",
       "      <td>89.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>93.00</td>\n",
       "      <td>95.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Croatia</th>\n",
       "      <td>73.0</td>\n",
       "      <td>87.219178</td>\n",
       "      <td>2.399344</td>\n",
       "      <td>81.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>89.00</td>\n",
       "      <td>91.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mexico</th>\n",
       "      <td>70.0</td>\n",
       "      <td>85.257143</td>\n",
       "      <td>2.722348</td>\n",
       "      <td>80.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>87.00</td>\n",
       "      <td>92.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                count       mean       std   min   25%   50%    75%    max\n",
       "country                                                                   \n",
       "US            54504.0  88.563720  3.114840  80.0  86.0  88.0  91.00  100.0\n",
       "France        22093.0  88.845109  3.044423  80.0  87.0  89.0  91.00  100.0\n",
       "Italy         19540.0  88.562231  2.649756  80.0  87.0  88.0  90.00  100.0\n",
       "Spain          6645.0  87.288337  3.066284  80.0  85.0  87.0  89.00   98.0\n",
       "Portugal       5691.0  88.250220  2.996122  80.0  86.0  88.0  90.00  100.0\n",
       "Chile          4472.0  86.493515  2.692959  80.0  85.0  86.0  88.00   95.0\n",
       "Argentina      3800.0  86.710263  3.179627  80.0  84.0  87.0  89.00   97.0\n",
       "Austria        3345.0  90.101345  2.499799  82.0  88.0  90.0  92.00   98.0\n",
       "Australia      2329.0  88.580507  2.989900  80.0  87.0  89.0  91.00  100.0\n",
       "Germany        2165.0  89.851732  2.469351  81.0  88.0  90.0  91.00   98.0\n",
       "New Zealand    1419.0  88.303030  2.435008  80.0  87.0  88.0  90.00   95.0\n",
       "South Africa   1401.0  88.056388  2.435826  82.0  86.0  88.0  90.00   95.0\n",
       "Israel          505.0  88.471287  2.478412  80.0  87.0  89.0  90.00   94.0\n",
       "Greece          466.0  87.283262  2.185293  82.0  86.0  87.0  89.00   93.0\n",
       "Canada          257.0  89.369650  2.384752  82.0  88.0  90.0  91.00   94.0\n",
       "Hungary         146.0  89.191781  2.686659  81.0  88.0  89.0  90.00   97.0\n",
       "Bulgaria        141.0  87.936170  2.077817  80.0  87.0  89.0  89.00   91.0\n",
       "Romania         120.0  86.400000  1.716945  82.0  85.0  86.0  87.25   92.0\n",
       "Uruguay         109.0  86.752294  2.687957  80.0  85.0  87.0  88.00   92.0\n",
       "Turkey           90.0  88.088889  1.975379  84.0  87.0  88.0  90.00   92.0\n",
       "Slovenia         87.0  88.068966  1.730661  82.0  87.0  88.0  89.00   92.0\n",
       "Georgia          86.0  87.686047  2.087845  82.0  87.0  88.0  89.00   92.0\n",
       "England          74.0  91.581081  1.843216  89.0  90.0  91.0  93.00   95.0\n",
       "Croatia          73.0  87.219178  2.399344  81.0  86.0  88.0  89.00   91.0\n",
       "Mexico           70.0  85.257143  2.722348  80.0  83.0  85.0  87.00   92.0"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wine.groupby('country').points.describe().sort_values(['count','mean'], ascending=False).head(25)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Price summary stats for a bottle of wine by country\n",
    "The table below describes the count of wines, the average price, and price quartiles information per country. For example, the U.S. has about 54k wines that average a price of $36. The minimum price in the U.S. is $4 while the maximum is $2013."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>country</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>US</th>\n",
       "      <td>54265.0</td>\n",
       "      <td>36.573464</td>\n",
       "      <td>27.088857</td>\n",
       "      <td>4.0</td>\n",
       "      <td>20.00</td>\n",
       "      <td>30.0</td>\n",
       "      <td>45.00</td>\n",
       "      <td>2013.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>France</th>\n",
       "      <td>17776.0</td>\n",
       "      <td>41.139120</td>\n",
       "      <td>73.769404</td>\n",
       "      <td>5.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>25.0</td>\n",
       "      <td>43.00</td>\n",
       "      <td>3300.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Italy</th>\n",
       "      <td>16914.0</td>\n",
       "      <td>39.663770</td>\n",
       "      <td>38.052479</td>\n",
       "      <td>5.0</td>\n",
       "      <td>18.00</td>\n",
       "      <td>28.0</td>\n",
       "      <td>50.00</td>\n",
       "      <td>900.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Spain</th>\n",
       "      <td>6573.0</td>\n",
       "      <td>28.215275</td>\n",
       "      <td>34.662397</td>\n",
       "      <td>4.0</td>\n",
       "      <td>13.00</td>\n",
       "      <td>18.0</td>\n",
       "      <td>30.00</td>\n",
       "      <td>770.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Portugal</th>\n",
       "      <td>4875.0</td>\n",
       "      <td>26.218256</td>\n",
       "      <td>41.175241</td>\n",
       "      <td>5.0</td>\n",
       "      <td>12.00</td>\n",
       "      <td>16.0</td>\n",
       "      <td>28.00</td>\n",
       "      <td>1000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Chile</th>\n",
       "      <td>4416.0</td>\n",
       "      <td>20.786458</td>\n",
       "      <td>21.929371</td>\n",
       "      <td>5.0</td>\n",
       "      <td>12.00</td>\n",
       "      <td>15.0</td>\n",
       "      <td>20.00</td>\n",
       "      <td>400.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Argentina</th>\n",
       "      <td>3756.0</td>\n",
       "      <td>24.510117</td>\n",
       "      <td>23.430122</td>\n",
       "      <td>4.0</td>\n",
       "      <td>12.00</td>\n",
       "      <td>17.0</td>\n",
       "      <td>25.00</td>\n",
       "      <td>230.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Austria</th>\n",
       "      <td>2799.0</td>\n",
       "      <td>30.762772</td>\n",
       "      <td>27.224797</td>\n",
       "      <td>7.0</td>\n",
       "      <td>18.00</td>\n",
       "      <td>25.0</td>\n",
       "      <td>36.50</td>\n",
       "      <td>1100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Australia</th>\n",
       "      <td>2294.0</td>\n",
       "      <td>35.437663</td>\n",
       "      <td>49.049458</td>\n",
       "      <td>5.0</td>\n",
       "      <td>15.00</td>\n",
       "      <td>21.0</td>\n",
       "      <td>38.00</td>\n",
       "      <td>850.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Germany</th>\n",
       "      <td>2120.0</td>\n",
       "      <td>42.257547</td>\n",
       "      <td>62.860308</td>\n",
       "      <td>5.0</td>\n",
       "      <td>18.00</td>\n",
       "      <td>26.0</td>\n",
       "      <td>42.00</td>\n",
       "      <td>775.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>New Zealand</th>\n",
       "      <td>1378.0</td>\n",
       "      <td>26.931785</td>\n",
       "      <td>17.101083</td>\n",
       "      <td>7.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>30.00</td>\n",
       "      <td>130.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Africa</th>\n",
       "      <td>1293.0</td>\n",
       "      <td>24.668987</td>\n",
       "      <td>21.843064</td>\n",
       "      <td>5.0</td>\n",
       "      <td>13.00</td>\n",
       "      <td>19.0</td>\n",
       "      <td>29.00</td>\n",
       "      <td>330.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Israel</th>\n",
       "      <td>489.0</td>\n",
       "      <td>31.768916</td>\n",
       "      <td>18.898287</td>\n",
       "      <td>8.0</td>\n",
       "      <td>18.00</td>\n",
       "      <td>25.0</td>\n",
       "      <td>40.00</td>\n",
       "      <td>150.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Greece</th>\n",
       "      <td>461.0</td>\n",
       "      <td>22.364425</td>\n",
       "      <td>10.610780</td>\n",
       "      <td>8.0</td>\n",
       "      <td>15.00</td>\n",
       "      <td>19.0</td>\n",
       "      <td>26.00</td>\n",
       "      <td>79.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Canada</th>\n",
       "      <td>254.0</td>\n",
       "      <td>35.712598</td>\n",
       "      <td>19.658148</td>\n",
       "      <td>12.0</td>\n",
       "      <td>21.00</td>\n",
       "      <td>30.0</td>\n",
       "      <td>40.75</td>\n",
       "      <td>120.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hungary</th>\n",
       "      <td>145.0</td>\n",
       "      <td>40.648276</td>\n",
       "      <td>69.451075</td>\n",
       "      <td>10.0</td>\n",
       "      <td>19.00</td>\n",
       "      <td>25.0</td>\n",
       "      <td>39.00</td>\n",
       "      <td>764.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bulgaria</th>\n",
       "      <td>141.0</td>\n",
       "      <td>14.645390</td>\n",
       "      <td>9.508744</td>\n",
       "      <td>8.0</td>\n",
       "      <td>10.00</td>\n",
       "      <td>13.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Romania</th>\n",
       "      <td>120.0</td>\n",
       "      <td>15.241667</td>\n",
       "      <td>30.286863</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.00</td>\n",
       "      <td>9.0</td>\n",
       "      <td>12.00</td>\n",
       "      <td>320.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Uruguay</th>\n",
       "      <td>109.0</td>\n",
       "      <td>26.403670</td>\n",
       "      <td>18.483786</td>\n",
       "      <td>10.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>29.00</td>\n",
       "      <td>130.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Turkey</th>\n",
       "      <td>90.0</td>\n",
       "      <td>24.633333</td>\n",
       "      <td>13.799894</td>\n",
       "      <td>14.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>27.75</td>\n",
       "      <td>120.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Georgia</th>\n",
       "      <td>84.0</td>\n",
       "      <td>19.321429</td>\n",
       "      <td>7.642873</td>\n",
       "      <td>9.0</td>\n",
       "      <td>13.00</td>\n",
       "      <td>17.5</td>\n",
       "      <td>25.00</td>\n",
       "      <td>40.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Slovenia</th>\n",
       "      <td>80.0</td>\n",
       "      <td>24.812500</td>\n",
       "      <td>13.982895</td>\n",
       "      <td>7.0</td>\n",
       "      <td>15.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>30.00</td>\n",
       "      <td>90.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Croatia</th>\n",
       "      <td>71.0</td>\n",
       "      <td>25.450704</td>\n",
       "      <td>12.993173</td>\n",
       "      <td>12.0</td>\n",
       "      <td>16.50</td>\n",
       "      <td>20.0</td>\n",
       "      <td>27.50</td>\n",
       "      <td>65.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mexico</th>\n",
       "      <td>70.0</td>\n",
       "      <td>26.785714</td>\n",
       "      <td>17.755091</td>\n",
       "      <td>8.0</td>\n",
       "      <td>15.25</td>\n",
       "      <td>22.0</td>\n",
       "      <td>29.50</td>\n",
       "      <td>108.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>England</th>\n",
       "      <td>69.0</td>\n",
       "      <td>51.681159</td>\n",
       "      <td>14.858641</td>\n",
       "      <td>25.0</td>\n",
       "      <td>43.00</td>\n",
       "      <td>50.0</td>\n",
       "      <td>60.00</td>\n",
       "      <td>95.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                count       mean        std   min    25%   50%    75%     max\n",
       "country                                                                      \n",
       "US            54265.0  36.573464  27.088857   4.0  20.00  30.0  45.00  2013.0\n",
       "France        17776.0  41.139120  73.769404   5.0  16.00  25.0  43.00  3300.0\n",
       "Italy         16914.0  39.663770  38.052479   5.0  18.00  28.0  50.00   900.0\n",
       "Spain          6573.0  28.215275  34.662397   4.0  13.00  18.0  30.00   770.0\n",
       "Portugal       4875.0  26.218256  41.175241   5.0  12.00  16.0  28.00  1000.0\n",
       "Chile          4416.0  20.786458  21.929371   5.0  12.00  15.0  20.00   400.0\n",
       "Argentina      3756.0  24.510117  23.430122   4.0  12.00  17.0  25.00   230.0\n",
       "Austria        2799.0  30.762772  27.224797   7.0  18.00  25.0  36.50  1100.0\n",
       "Australia      2294.0  35.437663  49.049458   5.0  15.00  21.0  38.00   850.0\n",
       "Germany        2120.0  42.257547  62.860308   5.0  18.00  26.0  42.00   775.0\n",
       "New Zealand    1378.0  26.931785  17.101083   7.0  16.00  20.0  30.00   130.0\n",
       "South Africa   1293.0  24.668987  21.843064   5.0  13.00  19.0  29.00   330.0\n",
       "Israel          489.0  31.768916  18.898287   8.0  18.00  25.0  40.00   150.0\n",
       "Greece          461.0  22.364425  10.610780   8.0  15.00  19.0  26.00    79.0\n",
       "Canada          254.0  35.712598  19.658148  12.0  21.00  30.0  40.75   120.0\n",
       "Hungary         145.0  40.648276  69.451075  10.0  19.00  25.0  39.00   764.0\n",
       "Bulgaria        141.0  14.645390   9.508744   8.0  10.00  13.0  16.00   100.0\n",
       "Romania         120.0  15.241667  30.286863   4.0   7.00   9.0  12.00   320.0\n",
       "Uruguay         109.0  26.403670  18.483786  10.0  16.00  20.0  29.00   130.0\n",
       "Turkey           90.0  24.633333  13.799894  14.0  17.00  20.0  27.75   120.0\n",
       "Georgia          84.0  19.321429   7.642873   9.0  13.00  17.5  25.00    40.0\n",
       "Slovenia         80.0  24.812500  13.982895   7.0  15.00  20.0  30.00    90.0\n",
       "Croatia          71.0  25.450704  12.993173  12.0  16.50  20.0  27.50    65.0\n",
       "Mexico           70.0  26.785714  17.755091   8.0  15.25  22.0  29.50   108.0\n",
       "England          69.0  51.681159  14.858641  25.0  43.00  50.0  60.00    95.0"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wine.groupby('country').price.describe().sort_values(['count','mean'], ascending=False).head(25)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Point review stats for a bottle of wine by province\n",
    "The table below describes the count of wines, the average point review, and review quartiles information per province. For example, the California has about 36k wines that average a review of 88. The minimum reivew in California is 80 while the maximum is 100."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "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>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>province</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>California</th>\n",
       "      <td>36247.0</td>\n",
       "      <td>88.627776</td>\n",
       "      <td>3.254020</td>\n",
       "      <td>80.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Washington</th>\n",
       "      <td>8639.0</td>\n",
       "      <td>88.947216</td>\n",
       "      <td>2.654835</td>\n",
       "      <td>80.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bordeaux</th>\n",
       "      <td>5941.0</td>\n",
       "      <td>88.658980</td>\n",
       "      <td>3.252326</td>\n",
       "      <td>80.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tuscany</th>\n",
       "      <td>5897.0</td>\n",
       "      <td>89.074614</td>\n",
       "      <td>2.644699</td>\n",
       "      <td>80.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Oregon</th>\n",
       "      <td>5373.0</td>\n",
       "      <td>89.051926</td>\n",
       "      <td>2.802526</td>\n",
       "      <td>80.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Burgundy</th>\n",
       "      <td>3980.0</td>\n",
       "      <td>89.569347</td>\n",
       "      <td>3.110104</td>\n",
       "      <td>81.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Northern Spain</th>\n",
       "      <td>3851.0</td>\n",
       "      <td>87.417035</td>\n",
       "      <td>3.153075</td>\n",
       "      <td>80.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>98.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Piedmont</th>\n",
       "      <td>3729.0</td>\n",
       "      <td>89.536873</td>\n",
       "      <td>2.822597</td>\n",
       "      <td>82.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mendoza Province</th>\n",
       "      <td>3264.0</td>\n",
       "      <td>86.826593</td>\n",
       "      <td>3.233570</td>\n",
       "      <td>80.0</td>\n",
       "      <td>84.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>97.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Veneto</th>\n",
       "      <td>2716.0</td>\n",
       "      <td>87.715022</td>\n",
       "      <td>2.446437</td>\n",
       "      <td>80.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>96.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>New York</th>\n",
       "      <td>2688.0</td>\n",
       "      <td>87.178571</td>\n",
       "      <td>2.248457</td>\n",
       "      <td>80.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>94.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Alsace</th>\n",
       "      <td>2440.0</td>\n",
       "      <td>89.372131</td>\n",
       "      <td>2.965298</td>\n",
       "      <td>80.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>97.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Northeastern Italy</th>\n",
       "      <td>2138.0</td>\n",
       "      <td>87.995790</td>\n",
       "      <td>2.188471</td>\n",
       "      <td>81.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>97.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Loire Valley</th>\n",
       "      <td>1856.0</td>\n",
       "      <td>88.493534</td>\n",
       "      <td>2.748773</td>\n",
       "      <td>80.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sicily &amp; Sardinia</th>\n",
       "      <td>1797.0</td>\n",
       "      <td>88.109071</td>\n",
       "      <td>2.412918</td>\n",
       "      <td>81.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>97.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Champagne</th>\n",
       "      <td>1613.0</td>\n",
       "      <td>90.234966</td>\n",
       "      <td>2.702121</td>\n",
       "      <td>82.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Southwest France</th>\n",
       "      <td>1503.0</td>\n",
       "      <td>88.607452</td>\n",
       "      <td>2.896850</td>\n",
       "      <td>80.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>96.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Australia</th>\n",
       "      <td>1349.0</td>\n",
       "      <td>89.037806</td>\n",
       "      <td>2.894161</td>\n",
       "      <td>80.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Southern Italy</th>\n",
       "      <td>1349.0</td>\n",
       "      <td>87.838399</td>\n",
       "      <td>2.471315</td>\n",
       "      <td>81.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>97.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Provence</th>\n",
       "      <td>1346.0</td>\n",
       "      <td>88.210253</td>\n",
       "      <td>2.400975</td>\n",
       "      <td>81.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>95.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Douro</th>\n",
       "      <td>1281.0</td>\n",
       "      <td>89.126464</td>\n",
       "      <td>2.871399</td>\n",
       "      <td>81.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Central Italy</th>\n",
       "      <td>1233.0</td>\n",
       "      <td>87.391727</td>\n",
       "      <td>2.384643</td>\n",
       "      <td>80.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>96.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Catalonia</th>\n",
       "      <td>1164.0</td>\n",
       "      <td>87.452749</td>\n",
       "      <td>2.845159</td>\n",
       "      <td>80.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>96.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rhône Valley</th>\n",
       "      <td>1081.0</td>\n",
       "      <td>89.007401</td>\n",
       "      <td>2.735897</td>\n",
       "      <td>81.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>98.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Beaujolais</th>\n",
       "      <td>1044.0</td>\n",
       "      <td>87.954981</td>\n",
       "      <td>2.546760</td>\n",
       "      <td>82.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>94.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      count       mean       std   min   25%   50%   75%  \\\n",
       "province                                                                   \n",
       "California          36247.0  88.627776  3.254020  80.0  86.0  89.0  91.0   \n",
       "Washington           8639.0  88.947216  2.654835  80.0  87.0  89.0  91.0   \n",
       "Bordeaux             5941.0  88.658980  3.252326  80.0  86.0  88.0  91.0   \n",
       "Tuscany              5897.0  89.074614  2.644699  80.0  87.0  89.0  91.0   \n",
       "Oregon               5373.0  89.051926  2.802526  80.0  87.0  89.0  91.0   \n",
       "Burgundy             3980.0  89.569347  3.110104  81.0  87.0  90.0  92.0   \n",
       "Northern Spain       3851.0  87.417035  3.153075  80.0  85.0  87.0  90.0   \n",
       "Piedmont             3729.0  89.536873  2.822597  82.0  87.0  89.0  92.0   \n",
       "Mendoza Province     3264.0  86.826593  3.233570  80.0  84.0  87.0  89.0   \n",
       "Veneto               2716.0  87.715022  2.446437  80.0  86.0  87.0  89.0   \n",
       "New York             2688.0  87.178571  2.248457  80.0  86.0  87.0  89.0   \n",
       "Alsace               2440.0  89.372131  2.965298  80.0  87.0  89.0  92.0   \n",
       "Northeastern Italy   2138.0  87.995790  2.188471  81.0  87.0  88.0  90.0   \n",
       "Loire Valley         1856.0  88.493534  2.748773  80.0  86.0  88.0  91.0   \n",
       "Sicily & Sardinia    1797.0  88.109071  2.412918  81.0  87.0  88.0  90.0   \n",
       "Champagne            1613.0  90.234966  2.702121  82.0  88.0  90.0  92.0   \n",
       "Southwest France     1503.0  88.607452  2.896850  80.0  86.0  88.0  91.0   \n",
       "South Australia      1349.0  89.037806  2.894161  80.0  87.0  89.0  91.0   \n",
       "Southern Italy       1349.0  87.838399  2.471315  81.0  86.0  88.0  89.0   \n",
       "Provence             1346.0  88.210253  2.400975  81.0  87.0  88.0  90.0   \n",
       "Douro                1281.0  89.126464  2.871399  81.0  87.0  89.0  91.0   \n",
       "Central Italy        1233.0  87.391727  2.384643  80.0  86.0  87.0  89.0   \n",
       "Catalonia            1164.0  87.452749  2.845159  80.0  86.0  87.0  89.0   \n",
       "Rhône Valley         1081.0  89.007401  2.735897  81.0  87.0  89.0  91.0   \n",
       "Beaujolais           1044.0  87.954981  2.546760  82.0  86.0  88.0  90.0   \n",
       "\n",
       "                      max  \n",
       "province                   \n",
       "California          100.0  \n",
       "Washington          100.0  \n",
       "Bordeaux            100.0  \n",
       "Tuscany             100.0  \n",
       "Oregon               99.0  \n",
       "Burgundy             99.0  \n",
       "Northern Spain       98.0  \n",
       "Piedmont             99.0  \n",
       "Mendoza Province     97.0  \n",
       "Veneto               96.0  \n",
       "New York             94.0  \n",
       "Alsace               97.0  \n",
       "Northeastern Italy   97.0  \n",
       "Loire Valley         99.0  \n",
       "Sicily & Sardinia    97.0  \n",
       "Champagne           100.0  \n",
       "Southwest France     96.0  \n",
       "South Australia      99.0  \n",
       "Southern Italy       97.0  \n",
       "Provence             95.0  \n",
       "Douro               100.0  \n",
       "Central Italy        96.0  \n",
       "Catalonia            96.0  \n",
       "Rhône Valley         98.0  \n",
       "Beaujolais           94.0  "
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wine.groupby('province').points.describe().sort_values(['count','mean'], ascending=False).head(25)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Price stats for a bottle of wine by province\n",
    "The table below describes the count of wines, the average price, and price quartiles information per province. For example, the California has about 36k wines that average a price of $39.\n",
    "The minimum price in the California is $4 while the maximum is $2013.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "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>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>province</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>California</th>\n",
       "      <td>36104.0</td>\n",
       "      <td>39.041048</td>\n",
       "      <td>30.259982</td>\n",
       "      <td>4.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>48.00</td>\n",
       "      <td>2013.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Washington</th>\n",
       "      <td>8583.0</td>\n",
       "      <td>32.436444</td>\n",
       "      <td>18.559569</td>\n",
       "      <td>6.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>40.00</td>\n",
       "      <td>240.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Oregon</th>\n",
       "      <td>5359.0</td>\n",
       "      <td>36.545064</td>\n",
       "      <td>20.224731</td>\n",
       "      <td>5.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>48.00</td>\n",
       "      <td>275.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tuscany</th>\n",
       "      <td>5128.0</td>\n",
       "      <td>47.683697</td>\n",
       "      <td>47.274103</td>\n",
       "      <td>6.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>60.00</td>\n",
       "      <td>900.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bordeaux</th>\n",
       "      <td>4002.0</td>\n",
       "      <td>38.911794</td>\n",
       "      <td>108.573516</td>\n",
       "      <td>6.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>33.00</td>\n",
       "      <td>3300.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Northern Spain</th>\n",
       "      <td>3797.0</td>\n",
       "      <td>30.771925</td>\n",
       "      <td>38.876613</td>\n",
       "      <td>5.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>32.00</td>\n",
       "      <td>600.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mendoza Province</th>\n",
       "      <td>3226.0</td>\n",
       "      <td>25.053317</td>\n",
       "      <td>24.044538</td>\n",
       "      <td>4.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>26.00</td>\n",
       "      <td>230.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Burgundy</th>\n",
       "      <td>3106.0</td>\n",
       "      <td>71.058274</td>\n",
       "      <td>101.446213</td>\n",
       "      <td>9.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>43.0</td>\n",
       "      <td>78.00</td>\n",
       "      <td>2500.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Piedmont</th>\n",
       "      <td>3089.0</td>\n",
       "      <td>54.957268</td>\n",
       "      <td>43.568957</td>\n",
       "      <td>7.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>70.00</td>\n",
       "      <td>595.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>New York</th>\n",
       "      <td>2676.0</td>\n",
       "      <td>22.826233</td>\n",
       "      <td>10.638814</td>\n",
       "      <td>7.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>26.00</td>\n",
       "      <td>125.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Veneto</th>\n",
       "      <td>2315.0</td>\n",
       "      <td>34.007343</td>\n",
       "      <td>35.032538</td>\n",
       "      <td>5.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>40.00</td>\n",
       "      <td>530.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Alsace</th>\n",
       "      <td>2147.0</td>\n",
       "      <td>30.376805</td>\n",
       "      <td>16.978224</td>\n",
       "      <td>8.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>35.00</td>\n",
       "      <td>197.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Northeastern Italy</th>\n",
       "      <td>1986.0</td>\n",
       "      <td>27.047835</td>\n",
       "      <td>17.234206</td>\n",
       "      <td>7.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>30.00</td>\n",
       "      <td>170.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Loire Valley</th>\n",
       "      <td>1598.0</td>\n",
       "      <td>25.998123</td>\n",
       "      <td>24.071499</td>\n",
       "      <td>8.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>30.00</td>\n",
       "      <td>800.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sicily &amp; Sardinia</th>\n",
       "      <td>1559.0</td>\n",
       "      <td>27.623477</td>\n",
       "      <td>19.508465</td>\n",
       "      <td>5.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>35.00</td>\n",
       "      <td>320.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Champagne</th>\n",
       "      <td>1383.0</td>\n",
       "      <td>79.461316</td>\n",
       "      <td>66.436349</td>\n",
       "      <td>10.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>84.50</td>\n",
       "      <td>800.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Southwest France</th>\n",
       "      <td>1335.0</td>\n",
       "      <td>24.235955</td>\n",
       "      <td>24.217107</td>\n",
       "      <td>7.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>25.00</td>\n",
       "      <td>400.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Australia</th>\n",
       "      <td>1331.0</td>\n",
       "      <td>38.811420</td>\n",
       "      <td>57.445127</td>\n",
       "      <td>7.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>40.00</td>\n",
       "      <td>850.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Catalonia</th>\n",
       "      <td>1153.0</td>\n",
       "      <td>28.466609</td>\n",
       "      <td>34.018135</td>\n",
       "      <td>6.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>31.00</td>\n",
       "      <td>770.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Provence</th>\n",
       "      <td>1139.0</td>\n",
       "      <td>22.654083</td>\n",
       "      <td>11.895551</td>\n",
       "      <td>9.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>25.00</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Douro</th>\n",
       "      <td>1134.0</td>\n",
       "      <td>29.141975</td>\n",
       "      <td>29.228535</td>\n",
       "      <td>7.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>33.00</td>\n",
       "      <td>450.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Southern Italy</th>\n",
       "      <td>1131.0</td>\n",
       "      <td>27.802829</td>\n",
       "      <td>18.703959</td>\n",
       "      <td>5.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>33.00</td>\n",
       "      <td>180.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Central Italy</th>\n",
       "      <td>1100.0</td>\n",
       "      <td>25.437273</td>\n",
       "      <td>20.420036</td>\n",
       "      <td>6.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>30.00</td>\n",
       "      <td>375.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rhône Valley</th>\n",
       "      <td>1042.0</td>\n",
       "      <td>38.641075</td>\n",
       "      <td>37.751141</td>\n",
       "      <td>7.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>49.75</td>\n",
       "      <td>500.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mosel</th>\n",
       "      <td>1023.0</td>\n",
       "      <td>35.380254</td>\n",
       "      <td>40.699811</td>\n",
       "      <td>5.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>40.00</td>\n",
       "      <td>448.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      count       mean         std   min   25%   50%    75%  \\\n",
       "province                                                                      \n",
       "California          36104.0  39.041048   30.259982   4.0  22.0  33.0  48.00   \n",
       "Washington           8583.0  32.436444   18.559569   6.0  20.0  29.0  40.00   \n",
       "Oregon               5359.0  36.545064   20.224731   5.0  22.0  30.0  48.00   \n",
       "Tuscany              5128.0  47.683697   47.274103   6.0  21.0  35.0  60.00   \n",
       "Bordeaux             4002.0  38.911794  108.573516   6.0  15.0  20.0  33.00   \n",
       "Northern Spain       3797.0  30.771925   38.876613   5.0  13.0  19.0  32.00   \n",
       "Mendoza Province     3226.0  25.053317   24.044538   4.0  12.0  17.0  26.00   \n",
       "Burgundy             3106.0  71.058274  101.446213   9.0  26.0  43.0  78.00   \n",
       "Piedmont             3089.0  54.957268   43.568957   7.0  27.0  49.0  70.00   \n",
       "New York             2676.0  22.826233   10.638814   7.0  16.0  20.0  26.00   \n",
       "Veneto               2315.0  34.007343   35.032538   5.0  16.0  21.0  40.00   \n",
       "Alsace               2147.0  30.376805   16.978224   8.0  19.0  25.0  35.00   \n",
       "Northeastern Italy   1986.0  27.047835   17.234206   7.0  17.0  22.0  30.00   \n",
       "Loire Valley         1598.0  25.998123   24.071499   8.0  16.0  22.0  30.00   \n",
       "Sicily & Sardinia    1559.0  27.623477   19.508465   5.0  15.0  22.0  35.00   \n",
       "Champagne            1383.0  79.461316   66.436349  10.0  49.0  60.0  84.50   \n",
       "Southwest France     1335.0  24.235955   24.217107   7.0  13.0  18.0  25.00   \n",
       "South Australia      1331.0  38.811420   57.445127   7.0  17.0  22.0  40.00   \n",
       "Catalonia            1153.0  28.466609   34.018135   6.0  14.0  19.0  31.00   \n",
       "Provence             1139.0  22.654083   11.895551   9.0  15.0  20.0  25.00   \n",
       "Douro                1134.0  29.141975   29.228535   7.0  14.0  20.0  33.00   \n",
       "Southern Italy       1131.0  27.802829   18.703959   5.0  16.0  21.0  33.00   \n",
       "Central Italy        1100.0  25.437273   20.420036   6.0  15.0  19.0  30.00   \n",
       "Rhône Valley         1042.0  38.641075   37.751141   7.0  15.0  25.0  49.75   \n",
       "Mosel                1023.0  35.380254   40.699811   5.0  17.0  26.0  40.00   \n",
       "\n",
       "                       max  \n",
       "province                    \n",
       "California          2013.0  \n",
       "Washington           240.0  \n",
       "Oregon               275.0  \n",
       "Tuscany              900.0  \n",
       "Bordeaux            3300.0  \n",
       "Northern Spain       600.0  \n",
       "Mendoza Province     230.0  \n",
       "Burgundy            2500.0  \n",
       "Piedmont             595.0  \n",
       "New York             125.0  \n",
       "Veneto               530.0  \n",
       "Alsace               197.0  \n",
       "Northeastern Italy   170.0  \n",
       "Loire Valley         800.0  \n",
       "Sicily & Sardinia    320.0  \n",
       "Champagne            800.0  \n",
       "Southwest France     400.0  \n",
       "South Australia      850.0  \n",
       "Catalonia            770.0  \n",
       "Provence             100.0  \n",
       "Douro                450.0  \n",
       "Southern Italy       180.0  \n",
       "Central Italy        375.0  \n",
       "Rhône Valley         500.0  \n",
       "Mosel                448.0  "
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wine.groupby('province').price.describe().sort_values(['count','mean'], ascending=False).head(25)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Point review stats for a bottle of wine by variety\n",
    "The table below describes the count of wines, the average point review, and review quartiles information per variety. For example, the Pinot Noir has about 13k wines that average a review of 89. The minimum reivew for Pinot Noir is 80 while the maximum is 99."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "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>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>variety</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Pinot Noir</th>\n",
       "      <td>13272.0</td>\n",
       "      <td>89.411468</td>\n",
       "      <td>3.123967</td>\n",
       "      <td>80.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Chardonnay</th>\n",
       "      <td>11753.0</td>\n",
       "      <td>88.340083</td>\n",
       "      <td>3.231557</td>\n",
       "      <td>80.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cabernet Sauvignon</th>\n",
       "      <td>9472.0</td>\n",
       "      <td>88.607580</td>\n",
       "      <td>3.316328</td>\n",
       "      <td>80.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Red Blend</th>\n",
       "      <td>8946.0</td>\n",
       "      <td>88.380282</td>\n",
       "      <td>2.776897</td>\n",
       "      <td>80.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bordeaux-style Red Blend</th>\n",
       "      <td>6915.0</td>\n",
       "      <td>89.106435</td>\n",
       "      <td>3.136137</td>\n",
       "      <td>80.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Riesling</th>\n",
       "      <td>5189.0</td>\n",
       "      <td>89.450183</td>\n",
       "      <td>2.862513</td>\n",
       "      <td>80.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>98.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sauvignon Blanc</th>\n",
       "      <td>4967.0</td>\n",
       "      <td>87.429636</td>\n",
       "      <td>2.685680</td>\n",
       "      <td>80.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>96.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Syrah</th>\n",
       "      <td>4142.0</td>\n",
       "      <td>89.286577</td>\n",
       "      <td>3.037114</td>\n",
       "      <td>80.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rosé</th>\n",
       "      <td>3564.0</td>\n",
       "      <td>86.846240</td>\n",
       "      <td>2.526633</td>\n",
       "      <td>80.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>96.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Merlot</th>\n",
       "      <td>3102.0</td>\n",
       "      <td>87.208575</td>\n",
       "      <td>2.967417</td>\n",
       "      <td>80.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Nebbiolo</th>\n",
       "      <td>2804.0</td>\n",
       "      <td>90.251070</td>\n",
       "      <td>2.717213</td>\n",
       "      <td>80.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zinfandel</th>\n",
       "      <td>2714.0</td>\n",
       "      <td>87.828666</td>\n",
       "      <td>3.111240</td>\n",
       "      <td>80.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>97.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sangiovese</th>\n",
       "      <td>2707.0</td>\n",
       "      <td>88.550794</td>\n",
       "      <td>2.767257</td>\n",
       "      <td>80.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Malbec</th>\n",
       "      <td>2652.0</td>\n",
       "      <td>87.983032</td>\n",
       "      <td>3.102440</td>\n",
       "      <td>80.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>97.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Portuguese Red</th>\n",
       "      <td>2466.0</td>\n",
       "      <td>88.810624</td>\n",
       "      <td>2.973620</td>\n",
       "      <td>81.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>White Blend</th>\n",
       "      <td>2360.0</td>\n",
       "      <td>87.352966</td>\n",
       "      <td>2.685980</td>\n",
       "      <td>80.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>97.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sparkling Blend</th>\n",
       "      <td>2153.0</td>\n",
       "      <td>88.045053</td>\n",
       "      <td>2.853993</td>\n",
       "      <td>80.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>98.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tempranillo</th>\n",
       "      <td>1810.0</td>\n",
       "      <td>87.514365</td>\n",
       "      <td>3.073822</td>\n",
       "      <td>80.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>97.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rhône-style Red Blend</th>\n",
       "      <td>1471.0</td>\n",
       "      <td>89.153637</td>\n",
       "      <td>2.821839</td>\n",
       "      <td>80.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>98.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pinot Gris</th>\n",
       "      <td>1455.0</td>\n",
       "      <td>88.496220</td>\n",
       "      <td>2.631119</td>\n",
       "      <td>80.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>96.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Champagne Blend</th>\n",
       "      <td>1396.0</td>\n",
       "      <td>89.663324</td>\n",
       "      <td>2.953130</td>\n",
       "      <td>80.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cabernet Franc</th>\n",
       "      <td>1353.0</td>\n",
       "      <td>88.150776</td>\n",
       "      <td>2.721170</td>\n",
       "      <td>80.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>97.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Grüner Veltliner</th>\n",
       "      <td>1345.0</td>\n",
       "      <td>89.980669</td>\n",
       "      <td>2.324414</td>\n",
       "      <td>82.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>96.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Portuguese White</th>\n",
       "      <td>1159.0</td>\n",
       "      <td>86.930975</td>\n",
       "      <td>2.385274</td>\n",
       "      <td>80.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>95.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bordeaux-style White Blend</th>\n",
       "      <td>1066.0</td>\n",
       "      <td>88.690432</td>\n",
       "      <td>3.325226</td>\n",
       "      <td>81.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                              count       mean       std   min   25%   50%  \\\n",
       "variety                                                                      \n",
       "Pinot Noir                  13272.0  89.411468  3.123967  80.0  87.0  90.0   \n",
       "Chardonnay                  11753.0  88.340083  3.231557  80.0  86.0  88.0   \n",
       "Cabernet Sauvignon           9472.0  88.607580  3.316328  80.0  86.0  88.0   \n",
       "Red Blend                    8946.0  88.380282  2.776897  80.0  87.0  88.0   \n",
       "Bordeaux-style Red Blend     6915.0  89.106435  3.136137  80.0  87.0  89.0   \n",
       "Riesling                     5189.0  89.450183  2.862513  80.0  87.0  90.0   \n",
       "Sauvignon Blanc              4967.0  87.429636  2.685680  80.0  86.0  87.0   \n",
       "Syrah                        4142.0  89.286577  3.037114  80.0  87.0  90.0   \n",
       "Rosé                         3564.0  86.846240  2.526633  80.0  85.0  87.0   \n",
       "Merlot                       3102.0  87.208575  2.967417  80.0  85.0  87.0   \n",
       "Nebbiolo                     2804.0  90.251070  2.717213  80.0  88.0  90.0   \n",
       "Zinfandel                    2714.0  87.828666  3.111240  80.0  86.0  88.0   \n",
       "Sangiovese                   2707.0  88.550794  2.767257  80.0  87.0  88.0   \n",
       "Malbec                       2652.0  87.983032  3.102440  80.0  86.0  88.0   \n",
       "Portuguese Red               2466.0  88.810624  2.973620  81.0  87.0  88.0   \n",
       "White Blend                  2360.0  87.352966  2.685980  80.0  86.0  87.0   \n",
       "Sparkling Blend              2153.0  88.045053  2.853993  80.0  86.0  88.0   \n",
       "Tempranillo                  1810.0  87.514365  3.073822  80.0  85.0  87.0   \n",
       "Rhône-style Red Blend        1471.0  89.153637  2.821839  80.0  87.0  89.0   \n",
       "Pinot Gris                   1455.0  88.496220  2.631119  80.0  87.0  88.0   \n",
       "Champagne Blend              1396.0  89.663324  2.953130  80.0  88.0  90.0   \n",
       "Cabernet Franc               1353.0  88.150776  2.721170  80.0  86.0  88.0   \n",
       "Grüner Veltliner             1345.0  89.980669  2.324414  82.0  88.0  90.0   \n",
       "Portuguese White             1159.0  86.930975  2.385274  80.0  85.0  87.0   \n",
       "Bordeaux-style White Blend   1066.0  88.690432  3.325226  81.0  86.0  88.0   \n",
       "\n",
       "                             75%    max  \n",
       "variety                                  \n",
       "Pinot Noir                  92.0   99.0  \n",
       "Chardonnay                  91.0  100.0  \n",
       "Cabernet Sauvignon          91.0  100.0  \n",
       "Red Blend                   90.0   99.0  \n",
       "Bordeaux-style Red Blend    91.0  100.0  \n",
       "Riesling                    91.0   98.0  \n",
       "Sauvignon Blanc             89.0   96.0  \n",
       "Syrah                       92.0  100.0  \n",
       "Rosé                        88.0   96.0  \n",
       "Merlot                      89.0  100.0  \n",
       "Nebbiolo                    92.0   99.0  \n",
       "Zinfandel                   90.0   97.0  \n",
       "Sangiovese                  90.0  100.0  \n",
       "Malbec                      90.0   97.0  \n",
       "Portuguese Red              91.0  100.0  \n",
       "White Blend                 89.0   97.0  \n",
       "Sparkling Blend             90.0   98.0  \n",
       "Tempranillo                 90.0   97.0  \n",
       "Rhône-style Red Blend       91.0   98.0  \n",
       "Pinot Gris                  90.0   96.0  \n",
       "Champagne Blend             92.0  100.0  \n",
       "Cabernet Franc              90.0   97.0  \n",
       "Grüner Veltliner            92.0   96.0  \n",
       "Portuguese White            88.0   95.0  \n",
       "Bordeaux-style White Blend  91.0  100.0  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wine.groupby('variety').points.describe().sort_values(['count'], ascending=False).head(25)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Price stats for a bottle of wine by variety\n",
    "The table below describes the count of wines, the average price, and price quartiles information per province. For example, the Pinot Noir has about 12k wines that average a price of $47. The minimum price in the Pinot Noir is $5 while the maximum is $2500."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>variety</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Pinot Noir</th>\n",
       "      <td>12787.0</td>\n",
       "      <td>47.528897</td>\n",
       "      <td>47.609434</td>\n",
       "      <td>5.0</td>\n",
       "      <td>28.00</td>\n",
       "      <td>42.0</td>\n",
       "      <td>55.0</td>\n",
       "      <td>2500.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Chardonnay</th>\n",
       "      <td>11080.0</td>\n",
       "      <td>34.522022</td>\n",
       "      <td>42.245055</td>\n",
       "      <td>4.0</td>\n",
       "      <td>18.00</td>\n",
       "      <td>26.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>2013.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cabernet Sauvignon</th>\n",
       "      <td>9386.0</td>\n",
       "      <td>47.940017</td>\n",
       "      <td>41.157236</td>\n",
       "      <td>4.0</td>\n",
       "      <td>20.00</td>\n",
       "      <td>37.0</td>\n",
       "      <td>65.0</td>\n",
       "      <td>625.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Red Blend</th>\n",
       "      <td>8476.0</td>\n",
       "      <td>35.881194</td>\n",
       "      <td>30.318077</td>\n",
       "      <td>5.0</td>\n",
       "      <td>18.00</td>\n",
       "      <td>28.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>500.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bordeaux-style Red Blend</th>\n",
       "      <td>5340.0</td>\n",
       "      <td>47.210861</td>\n",
       "      <td>92.810629</td>\n",
       "      <td>7.0</td>\n",
       "      <td>19.75</td>\n",
       "      <td>30.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>3300.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Riesling</th>\n",
       "      <td>4972.0</td>\n",
       "      <td>32.000402</td>\n",
       "      <td>43.061291</td>\n",
       "      <td>5.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>22.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>775.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sauvignon Blanc</th>\n",
       "      <td>4783.0</td>\n",
       "      <td>20.228518</td>\n",
       "      <td>9.871627</td>\n",
       "      <td>5.0</td>\n",
       "      <td>14.00</td>\n",
       "      <td>18.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>135.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Syrah</th>\n",
       "      <td>4086.0</td>\n",
       "      <td>39.137788</td>\n",
       "      <td>27.324629</td>\n",
       "      <td>4.0</td>\n",
       "      <td>25.00</td>\n",
       "      <td>35.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>750.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rosé</th>\n",
       "      <td>3262.0</td>\n",
       "      <td>18.506438</td>\n",
       "      <td>16.325324</td>\n",
       "      <td>5.0</td>\n",
       "      <td>13.00</td>\n",
       "      <td>16.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>800.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Merlot</th>\n",
       "      <td>3062.0</td>\n",
       "      <td>29.543436</td>\n",
       "      <td>33.340882</td>\n",
       "      <td>4.0</td>\n",
       "      <td>15.00</td>\n",
       "      <td>24.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>625.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zinfandel</th>\n",
       "      <td>2708.0</td>\n",
       "      <td>29.492245</td>\n",
       "      <td>12.355957</td>\n",
       "      <td>5.0</td>\n",
       "      <td>20.00</td>\n",
       "      <td>28.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Malbec</th>\n",
       "      <td>2593.0</td>\n",
       "      <td>29.926726</td>\n",
       "      <td>26.745024</td>\n",
       "      <td>5.0</td>\n",
       "      <td>15.00</td>\n",
       "      <td>22.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>400.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sangiovese</th>\n",
       "      <td>2377.0</td>\n",
       "      <td>45.279344</td>\n",
       "      <td>42.948850</td>\n",
       "      <td>6.0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>32.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>800.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Nebbiolo</th>\n",
       "      <td>2331.0</td>\n",
       "      <td>65.609610</td>\n",
       "      <td>42.919491</td>\n",
       "      <td>12.0</td>\n",
       "      <td>43.00</td>\n",
       "      <td>56.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>595.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Portuguese Red</th>\n",
       "      <td>2196.0</td>\n",
       "      <td>24.819217</td>\n",
       "      <td>25.539475</td>\n",
       "      <td>5.0</td>\n",
       "      <td>12.00</td>\n",
       "      <td>17.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>450.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>White Blend</th>\n",
       "      <td>2172.0</td>\n",
       "      <td>23.240792</td>\n",
       "      <td>17.177683</td>\n",
       "      <td>4.0</td>\n",
       "      <td>14.00</td>\n",
       "      <td>19.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>375.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sparkling Blend</th>\n",
       "      <td>2027.0</td>\n",
       "      <td>29.611248</td>\n",
       "      <td>20.195462</td>\n",
       "      <td>5.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>24.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>250.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tempranillo</th>\n",
       "      <td>1789.0</td>\n",
       "      <td>31.150922</td>\n",
       "      <td>33.722227</td>\n",
       "      <td>4.0</td>\n",
       "      <td>14.00</td>\n",
       "      <td>22.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>600.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rhône-style Red Blend</th>\n",
       "      <td>1405.0</td>\n",
       "      <td>34.925267</td>\n",
       "      <td>24.985511</td>\n",
       "      <td>7.0</td>\n",
       "      <td>20.00</td>\n",
       "      <td>30.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>500.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pinot Gris</th>\n",
       "      <td>1391.0</td>\n",
       "      <td>23.074047</td>\n",
       "      <td>13.712080</td>\n",
       "      <td>9.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>19.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>135.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cabernet Franc</th>\n",
       "      <td>1305.0</td>\n",
       "      <td>34.836782</td>\n",
       "      <td>21.381867</td>\n",
       "      <td>10.0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>29.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>180.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Champagne Blend</th>\n",
       "      <td>1211.0</td>\n",
       "      <td>70.744839</td>\n",
       "      <td>60.345480</td>\n",
       "      <td>7.0</td>\n",
       "      <td>40.00</td>\n",
       "      <td>55.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>600.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Grüner Veltliner</th>\n",
       "      <td>1145.0</td>\n",
       "      <td>27.780786</td>\n",
       "      <td>35.222941</td>\n",
       "      <td>9.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>22.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>1100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pinot Grigio</th>\n",
       "      <td>1002.0</td>\n",
       "      <td>16.541916</td>\n",
       "      <td>7.027187</td>\n",
       "      <td>4.0</td>\n",
       "      <td>11.25</td>\n",
       "      <td>15.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>70.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Portuguese White</th>\n",
       "      <td>986.0</td>\n",
       "      <td>15.344828</td>\n",
       "      <td>9.282633</td>\n",
       "      <td>5.0</td>\n",
       "      <td>10.00</td>\n",
       "      <td>12.5</td>\n",
       "      <td>18.0</td>\n",
       "      <td>95.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                            count       mean        std   min    25%   50%  \\\n",
       "variety                                                                      \n",
       "Pinot Noir                12787.0  47.528897  47.609434   5.0  28.00  42.0   \n",
       "Chardonnay                11080.0  34.522022  42.245055   4.0  18.00  26.0   \n",
       "Cabernet Sauvignon         9386.0  47.940017  41.157236   4.0  20.00  37.0   \n",
       "Red Blend                  8476.0  35.881194  30.318077   5.0  18.00  28.0   \n",
       "Bordeaux-style Red Blend   5340.0  47.210861  92.810629   7.0  19.75  30.0   \n",
       "Riesling                   4972.0  32.000402  43.061291   5.0  16.00  22.0   \n",
       "Sauvignon Blanc            4783.0  20.228518   9.871627   5.0  14.00  18.0   \n",
       "Syrah                      4086.0  39.137788  27.324629   4.0  25.00  35.0   \n",
       "Rosé                       3262.0  18.506438  16.325324   5.0  13.00  16.0   \n",
       "Merlot                     3062.0  29.543436  33.340882   4.0  15.00  24.0   \n",
       "Zinfandel                  2708.0  29.492245  12.355957   5.0  20.00  28.0   \n",
       "Malbec                     2593.0  29.926726  26.745024   5.0  15.00  22.0   \n",
       "Sangiovese                 2377.0  45.279344  42.948850   6.0  22.00  32.0   \n",
       "Nebbiolo                   2331.0  65.609610  42.919491  12.0  43.00  56.0   \n",
       "Portuguese Red             2196.0  24.819217  25.539475   5.0  12.00  17.0   \n",
       "White Blend                2172.0  23.240792  17.177683   4.0  14.00  19.0   \n",
       "Sparkling Blend            2027.0  29.611248  20.195462   5.0  16.00  24.0   \n",
       "Tempranillo                1789.0  31.150922  33.722227   4.0  14.00  22.0   \n",
       "Rhône-style Red Blend      1405.0  34.925267  24.985511   7.0  20.00  30.0   \n",
       "Pinot Gris                 1391.0  23.074047  13.712080   9.0  16.00  19.0   \n",
       "Cabernet Franc             1305.0  34.836782  21.381867  10.0  22.00  29.0   \n",
       "Champagne Blend            1211.0  70.744839  60.345480   7.0  40.00  55.0   \n",
       "Grüner Veltliner           1145.0  27.780786  35.222941   9.0  16.00  22.0   \n",
       "Pinot Grigio               1002.0  16.541916   7.027187   4.0  11.25  15.0   \n",
       "Portuguese White            986.0  15.344828   9.282633   5.0  10.00  12.5   \n",
       "\n",
       "                           75%     max  \n",
       "variety                                 \n",
       "Pinot Noir                55.0  2500.0  \n",
       "Chardonnay                40.0  2013.0  \n",
       "Cabernet Sauvignon        65.0   625.0  \n",
       "Red Blend                 45.0   500.0  \n",
       "Bordeaux-style Red Blend  50.0  3300.0  \n",
       "Riesling                  34.0   775.0  \n",
       "Sauvignon Blanc           24.0   135.0  \n",
       "Syrah                     45.0   750.0  \n",
       "Rosé                      20.0   800.0  \n",
       "Merlot                    35.0   625.0  \n",
       "Zinfandel                 36.0   100.0  \n",
       "Malbec                    35.0   400.0  \n",
       "Sangiovese                58.0   800.0  \n",
       "Nebbiolo                  77.0   595.0  \n",
       "Portuguese Red            28.0   450.0  \n",
       "White Blend               27.0   375.0  \n",
       "Sparkling Blend           38.0   250.0  \n",
       "Tempranillo               35.0   600.0  \n",
       "Rhône-style Red Blend     44.0   500.0  \n",
       "Pinot Gris                25.0   135.0  \n",
       "Cabernet Franc            40.0   180.0  \n",
       "Champagne Blend           80.0   600.0  \n",
       "Grüner Veltliner          31.0  1100.0  \n",
       "Pinot Grigio              20.0    70.0  \n",
       "Portuguese White          18.0    95.0  "
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wine.groupby('variety').price.describe().sort_values(['count'], ascending=False).head(25)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Sorting wine by points and price\n",
    "After reviewing the table below, you'll see that the most expensive wine with a 100 point review is Château Lafite Rothschild 2010 Pauillac from France."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>country</th>\n",
       "      <th>description</th>\n",
       "      <th>designation</th>\n",
       "      <th>points</th>\n",
       "      <th>price</th>\n",
       "      <th>province</th>\n",
       "      <th>region_1</th>\n",
       "      <th>region_2</th>\n",
       "      <th>taster_name</th>\n",
       "      <th>taster_twitter_handle</th>\n",
       "      <th>title</th>\n",
       "      <th>variety</th>\n",
       "      <th>winery</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>111753</th>\n",
       "      <td>France</td>\n",
       "      <td>Almost black in color, this stunning wine is g...</td>\n",
       "      <td>None</td>\n",
       "      <td>100</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>Bordeaux</td>\n",
       "      <td>Pauillac</td>\n",
       "      <td>None</td>\n",
       "      <td>Roger Voss</td>\n",
       "      <td>@vossroger</td>\n",
       "      <td>Château Lafite Rothschild 2010  Pauillac</td>\n",
       "      <td>Bordeaux-style Red Blend</td>\n",
       "      <td>Château Lafite Rothschild</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111755</th>\n",
       "      <td>France</td>\n",
       "      <td>This is the finest Cheval Blanc for many years...</td>\n",
       "      <td>None</td>\n",
       "      <td>100</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>Bordeaux</td>\n",
       "      <td>Saint-Émilion</td>\n",
       "      <td>None</td>\n",
       "      <td>Roger Voss</td>\n",
       "      <td>@vossroger</td>\n",
       "      <td>Château Cheval Blanc 2010  Saint-Émilion</td>\n",
       "      <td>Bordeaux-style Red Blend</td>\n",
       "      <td>Château Cheval Blanc</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>122935</th>\n",
       "      <td>France</td>\n",
       "      <td>Full of ripe fruit, opulent and concentrated, ...</td>\n",
       "      <td>None</td>\n",
       "      <td>100</td>\n",
       "      <td>848.0</td>\n",
       "      <td>Bordeaux</td>\n",
       "      <td>Pessac-Léognan</td>\n",
       "      <td>None</td>\n",
       "      <td>Roger Voss</td>\n",
       "      <td>@vossroger</td>\n",
       "      <td>Château Haut-Brion 2014  Pessac-Léognan</td>\n",
       "      <td>Bordeaux-style White Blend</td>\n",
       "      <td>Château Haut-Brion</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>114972</th>\n",
       "      <td>Portugal</td>\n",
       "      <td>A powerful and ripe wine, strongly influenced ...</td>\n",
       "      <td>Nacional Vintage</td>\n",
       "      <td>100</td>\n",
       "      <td>650.0</td>\n",
       "      <td>Port</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Roger Voss</td>\n",
       "      <td>@vossroger</td>\n",
       "      <td>Quinta do Noval 2011 Nacional Vintage  (Port)</td>\n",
       "      <td>Port</td>\n",
       "      <td>Quinta do Noval</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89729</th>\n",
       "      <td>France</td>\n",
       "      <td>This new release from a great vintage for Char...</td>\n",
       "      <td>Le Mesnil Blanc de Blancs Brut</td>\n",
       "      <td>100</td>\n",
       "      <td>617.0</td>\n",
       "      <td>Champagne</td>\n",
       "      <td>Champagne</td>\n",
       "      <td>None</td>\n",
       "      <td>Roger Voss</td>\n",
       "      <td>@vossroger</td>\n",
       "      <td>Salon 2006 Le Mesnil Blanc de Blancs Brut Char...</td>\n",
       "      <td>Chardonnay</td>\n",
       "      <td>Salon</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45781</th>\n",
       "      <td>Italy</td>\n",
       "      <td>This gorgeous, fragrant wine opens with classi...</td>\n",
       "      <td>Riserva</td>\n",
       "      <td>100</td>\n",
       "      <td>550.0</td>\n",
       "      <td>Tuscany</td>\n",
       "      <td>Brunello di Montalcino</td>\n",
       "      <td>None</td>\n",
       "      <td>Kerin O’Keefe</td>\n",
       "      <td>@kerinokeefe</td>\n",
       "      <td>Biondi Santi 2010 Riserva  (Brunello di Montal...</td>\n",
       "      <td>Sangiovese</td>\n",
       "      <td>Biondi Santi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39286</th>\n",
       "      <td>Italy</td>\n",
       "      <td>A perfect wine from a classic vintage, the 200...</td>\n",
       "      <td>Masseto</td>\n",
       "      <td>100</td>\n",
       "      <td>460.0</td>\n",
       "      <td>Tuscany</td>\n",
       "      <td>Toscana</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Tenuta dell'Ornellaia 2007 Masseto Merlot (Tos...</td>\n",
       "      <td>Merlot</td>\n",
       "      <td>Tenuta dell'Ornellaia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42197</th>\n",
       "      <td>Portugal</td>\n",
       "      <td>This is the latest release of what has long be...</td>\n",
       "      <td>Barca-Velha</td>\n",
       "      <td>100</td>\n",
       "      <td>450.0</td>\n",
       "      <td>Douro</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Roger Voss</td>\n",
       "      <td>@vossroger</td>\n",
       "      <td>Casa Ferreirinha 2008 Barca-Velha Red (Douro)</td>\n",
       "      <td>Portuguese Red</td>\n",
       "      <td>Casa Ferreirinha</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>118058</th>\n",
       "      <td>US</td>\n",
       "      <td>This wine dazzles with perfection. Sourced fro...</td>\n",
       "      <td>La Muse</td>\n",
       "      <td>100</td>\n",
       "      <td>450.0</td>\n",
       "      <td>California</td>\n",
       "      <td>Sonoma County</td>\n",
       "      <td>Sonoma</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Verité 2007 La Muse Red (Sonoma County)</td>\n",
       "      <td>Bordeaux-style Red Blend</td>\n",
       "      <td>Verité</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111756</th>\n",
       "      <td>France</td>\n",
       "      <td>A hugely powerful wine, full of dark, brooding...</td>\n",
       "      <td>None</td>\n",
       "      <td>100</td>\n",
       "      <td>359.0</td>\n",
       "      <td>Bordeaux</td>\n",
       "      <td>Saint-Julien</td>\n",
       "      <td>None</td>\n",
       "      <td>Roger Voss</td>\n",
       "      <td>@vossroger</td>\n",
       "      <td>Château Léoville Las Cases 2010  Saint-Julien</td>\n",
       "      <td>Bordeaux-style Red Blend</td>\n",
       "      <td>Château Léoville Las Cases</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>345</th>\n",
       "      <td>Australia</td>\n",
       "      <td>This wine contains some material over 100 year...</td>\n",
       "      <td>Rare</td>\n",
       "      <td>100</td>\n",
       "      <td>350.0</td>\n",
       "      <td>Victoria</td>\n",
       "      <td>Rutherglen</td>\n",
       "      <td>None</td>\n",
       "      <td>Joe Czerwinski</td>\n",
       "      <td>@JoeCz</td>\n",
       "      <td>Chambers Rosewood Vineyards NV Rare Muscat (Ru...</td>\n",
       "      <td>Muscat</td>\n",
       "      <td>Chambers Rosewood Vineyards</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111754</th>\n",
       "      <td>Italy</td>\n",
       "      <td>It takes only a few moments before you appreci...</td>\n",
       "      <td>Cerretalto</td>\n",
       "      <td>100</td>\n",
       "      <td>270.0</td>\n",
       "      <td>Tuscany</td>\n",
       "      <td>Brunello di Montalcino</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Casanova di Neri 2007 Cerretalto  (Brunello di...</td>\n",
       "      <td>Sangiovese Grosso</td>\n",
       "      <td>Casanova di Neri</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36528</th>\n",
       "      <td>France</td>\n",
       "      <td>This is a fabulous wine from the greatest Cham...</td>\n",
       "      <td>Brut</td>\n",
       "      <td>100</td>\n",
       "      <td>259.0</td>\n",
       "      <td>Champagne</td>\n",
       "      <td>Champagne</td>\n",
       "      <td>None</td>\n",
       "      <td>Roger Voss</td>\n",
       "      <td>@vossroger</td>\n",
       "      <td>Krug 2002 Brut  (Champagne)</td>\n",
       "      <td>Champagne Blend</td>\n",
       "      <td>Krug</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89728</th>\n",
       "      <td>France</td>\n",
       "      <td>This latest incarnation of the famous brand is...</td>\n",
       "      <td>Cristal Vintage Brut</td>\n",
       "      <td>100</td>\n",
       "      <td>250.0</td>\n",
       "      <td>Champagne</td>\n",
       "      <td>Champagne</td>\n",
       "      <td>None</td>\n",
       "      <td>Roger Voss</td>\n",
       "      <td>@vossroger</td>\n",
       "      <td>Louis Roederer 2008 Cristal Vintage Brut  (Cha...</td>\n",
       "      <td>Champagne Blend</td>\n",
       "      <td>Louis Roederer</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7335</th>\n",
       "      <td>Italy</td>\n",
       "      <td>Thick as molasses and dark as caramelized brow...</td>\n",
       "      <td>Occhio di Pernice</td>\n",
       "      <td>100</td>\n",
       "      <td>210.0</td>\n",
       "      <td>Tuscany</td>\n",
       "      <td>Vin Santo di Montepulciano</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Avignonesi 1995 Occhio di Pernice  (Vin Santo ...</td>\n",
       "      <td>Prugnolo Gentile</td>\n",
       "      <td>Avignonesi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45798</th>\n",
       "      <td>US</td>\n",
       "      <td>Tasted in a flight of great and famous Napa wi...</td>\n",
       "      <td>None</td>\n",
       "      <td>100</td>\n",
       "      <td>200.0</td>\n",
       "      <td>California</td>\n",
       "      <td>Napa Valley</td>\n",
       "      <td>Napa</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Cardinale 2006 Cabernet Sauvignon (Napa Valley)</td>\n",
       "      <td>Cabernet Sauvignon</td>\n",
       "      <td>Cardinale</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58352</th>\n",
       "      <td>France</td>\n",
       "      <td>This is a magnificently solid wine, initially ...</td>\n",
       "      <td>None</td>\n",
       "      <td>100</td>\n",
       "      <td>150.0</td>\n",
       "      <td>Bordeaux</td>\n",
       "      <td>Saint-Julien</td>\n",
       "      <td>None</td>\n",
       "      <td>Roger Voss</td>\n",
       "      <td>@vossroger</td>\n",
       "      <td>Château Léoville Barton 2010  Saint-Julien</td>\n",
       "      <td>Bordeaux-style Red Blend</td>\n",
       "      <td>Château Léoville Barton</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113929</th>\n",
       "      <td>US</td>\n",
       "      <td>In 2005 Charles Smith introduced three high-en...</td>\n",
       "      <td>Royal City</td>\n",
       "      <td>100</td>\n",
       "      <td>80.0</td>\n",
       "      <td>Washington</td>\n",
       "      <td>Columbia Valley (WA)</td>\n",
       "      <td>Columbia Valley</td>\n",
       "      <td>Paul Gregutt</td>\n",
       "      <td>@paulgwine</td>\n",
       "      <td>Charles Smith 2006 Royal City Syrah (Columbia ...</td>\n",
       "      <td>Syrah</td>\n",
       "      <td>Charles Smith</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>123545</th>\n",
       "      <td>US</td>\n",
       "      <td>Initially a rather subdued Frog; as if it has ...</td>\n",
       "      <td>Bionic Frog</td>\n",
       "      <td>100</td>\n",
       "      <td>80.0</td>\n",
       "      <td>Washington</td>\n",
       "      <td>Walla Walla Valley (WA)</td>\n",
       "      <td>Columbia Valley</td>\n",
       "      <td>Paul Gregutt</td>\n",
       "      <td>@paulgwine</td>\n",
       "      <td>Cayuse 2008 Bionic Frog Syrah (Walla Walla Val...</td>\n",
       "      <td>Syrah</td>\n",
       "      <td>Cayuse</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56953</th>\n",
       "      <td>Australia</td>\n",
       "      <td>This inky, embryonic wine deserves to be cella...</td>\n",
       "      <td>Grange</td>\n",
       "      <td>99</td>\n",
       "      <td>850.0</td>\n",
       "      <td>South Australia</td>\n",
       "      <td>South Australia</td>\n",
       "      <td>None</td>\n",
       "      <td>Joe Czerwinski</td>\n",
       "      <td>@JoeCz</td>\n",
       "      <td>Penfolds 2010 Grange Shiraz (South Australia)</td>\n",
       "      <td>Shiraz</td>\n",
       "      <td>Penfolds</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36529</th>\n",
       "      <td>France</td>\n",
       "      <td>Pure Chardonnay from the walled vineyard in th...</td>\n",
       "      <td>Clos du Mesnil Brut Blanc de Blancs</td>\n",
       "      <td>99</td>\n",
       "      <td>800.0</td>\n",
       "      <td>Champagne</td>\n",
       "      <td>Champagne</td>\n",
       "      <td>None</td>\n",
       "      <td>Roger Voss</td>\n",
       "      <td>@vossroger</td>\n",
       "      <td>Krug 2002 Clos du Mesnil Brut Blanc de Blancs ...</td>\n",
       "      <td>Chardonnay</td>\n",
       "      <td>Krug</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44994</th>\n",
       "      <td>Italy</td>\n",
       "      <td>This stunning wine is all about extreme elegan...</td>\n",
       "      <td>Cà d'Morissio Riserva</td>\n",
       "      <td>99</td>\n",
       "      <td>595.0</td>\n",
       "      <td>Piedmont</td>\n",
       "      <td>Barolo</td>\n",
       "      <td>None</td>\n",
       "      <td>Kerin O’Keefe</td>\n",
       "      <td>@kerinokeefe</td>\n",
       "      <td>Mascarello Giuseppe e Figlio 2008 Cà d'Morissi...</td>\n",
       "      <td>Nebbiolo</td>\n",
       "      <td>Mascarello Giuseppe e Figlio</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98375</th>\n",
       "      <td>France</td>\n",
       "      <td>In this great year for white Burgundy, Bâtard-...</td>\n",
       "      <td>None</td>\n",
       "      <td>99</td>\n",
       "      <td>560.0</td>\n",
       "      <td>Burgundy</td>\n",
       "      <td>Bâtard-Montrachet</td>\n",
       "      <td>None</td>\n",
       "      <td>Roger Voss</td>\n",
       "      <td>@vossroger</td>\n",
       "      <td>Domaine Leflaive 2010  Bâtard-Montrachet</td>\n",
       "      <td>Chardonnay</td>\n",
       "      <td>Domaine Leflaive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60880</th>\n",
       "      <td>Italy</td>\n",
       "      <td>This is an elegant Nebbiolo-based wine and arg...</td>\n",
       "      <td>Sorì Tildìn</td>\n",
       "      <td>99</td>\n",
       "      <td>440.0</td>\n",
       "      <td>Piedmont</td>\n",
       "      <td>Langhe</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Gaja 2007 Sorì Tildìn Nebbiolo (Langhe)</td>\n",
       "      <td>Nebbiolo</td>\n",
       "      <td>Gaja</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60881</th>\n",
       "      <td>Italy</td>\n",
       "      <td>Always a standout among Gaja's five single-vin...</td>\n",
       "      <td>Sorì San Lorenzo</td>\n",
       "      <td>99</td>\n",
       "      <td>440.0</td>\n",
       "      <td>Piedmont</td>\n",
       "      <td>Langhe</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Gaja 2007 Sorì San Lorenzo Nebbiolo (Langhe)</td>\n",
       "      <td>Nebbiolo</td>\n",
       "      <td>Gaja</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56043</th>\n",
       "      <td>Portugal</td>\n",
       "      <td>This is the latest release of Portugal's most ...</td>\n",
       "      <td>Barca Velha</td>\n",
       "      <td>99</td>\n",
       "      <td>426.0</td>\n",
       "      <td>Douro</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Roger Voss</td>\n",
       "      <td>@vossroger</td>\n",
       "      <td>Casa Ferreirinha 2004 Barca Velha Red (Douro)</td>\n",
       "      <td>Portuguese Red</td>\n",
       "      <td>Casa Ferreirinha</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39287</th>\n",
       "      <td>Italy</td>\n",
       "      <td>Here's a “wow” wine you won't easily forget. M...</td>\n",
       "      <td>Messorio</td>\n",
       "      <td>99</td>\n",
       "      <td>320.0</td>\n",
       "      <td>Tuscany</td>\n",
       "      <td>Toscana</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Le Macchiole 2007 Messorio Merlot (Toscana)</td>\n",
       "      <td>Merlot</td>\n",
       "      <td>Le Macchiole</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109427</th>\n",
       "      <td>Australia</td>\n",
       "      <td>This wine is dark brown in hue with a greenish...</td>\n",
       "      <td>Rare</td>\n",
       "      <td>99</td>\n",
       "      <td>300.0</td>\n",
       "      <td>Victoria</td>\n",
       "      <td>Rutherglen</td>\n",
       "      <td>None</td>\n",
       "      <td>Joe Czerwinski</td>\n",
       "      <td>@JoeCz</td>\n",
       "      <td>Chambers Rosewood Vineyards NV Rare Muscadelle...</td>\n",
       "      <td>Muscadelle</td>\n",
       "      <td>Chambers Rosewood Vineyards</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116140</th>\n",
       "      <td>US</td>\n",
       "      <td>This blend from individual blocks includes 94%...</td>\n",
       "      <td>ERA</td>\n",
       "      <td>99</td>\n",
       "      <td>300.0</td>\n",
       "      <td>California</td>\n",
       "      <td>Napa Valley</td>\n",
       "      <td>Napa</td>\n",
       "      <td>Virginie Boone</td>\n",
       "      <td>@vboone</td>\n",
       "      <td>Alpha Omega 2012 ERA Red (Napa Valley)</td>\n",
       "      <td>Bordeaux-style Red Blend</td>\n",
       "      <td>Alpha Omega</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>121884</th>\n",
       "      <td>US</td>\n",
       "      <td>This is an absolutely beautiful wine to drink ...</td>\n",
       "      <td>IX Estate</td>\n",
       "      <td>99</td>\n",
       "      <td>290.0</td>\n",
       "      <td>California</td>\n",
       "      <td>Napa Valley</td>\n",
       "      <td>Napa</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Colgin 2008 IX Estate Red (Napa Valley)</td>\n",
       "      <td>Red Blend</td>\n",
       "      <td>Colgin</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82746</th>\n",
       "      <td>Argentina</td>\n",
       "      <td>Yellow and chunky, and definitely on the way t...</td>\n",
       "      <td>1492 White</td>\n",
       "      <td>80</td>\n",
       "      <td>8.0</td>\n",
       "      <td>Mendoza Province</td>\n",
       "      <td>Mendoza</td>\n",
       "      <td>None</td>\n",
       "      <td>Michael Schachner</td>\n",
       "      <td>@wineschach</td>\n",
       "      <td>Cristobal 1492 2009 1492 White White (Mendoza)</td>\n",
       "      <td>White Blend</td>\n",
       "      <td>Cristobal 1492</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83847</th>\n",
       "      <td>Spain</td>\n",
       "      <td>This smells like compost. It feels hard and cl...</td>\n",
       "      <td>Manon</td>\n",
       "      <td>80</td>\n",
       "      <td>8.0</td>\n",
       "      <td>Central Spain</td>\n",
       "      <td>Vino de la Tierra de Castilla</td>\n",
       "      <td>None</td>\n",
       "      <td>Michael Schachner</td>\n",
       "      <td>@wineschach</td>\n",
       "      <td>Mano A Mano 2009 Manon Tempranillo (Vino de la...</td>\n",
       "      <td>Tempranillo</td>\n",
       "      <td>Mano A Mano</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>86712</th>\n",
       "      <td>US</td>\n",
       "      <td>A pop style of pink wine that the Peter Mondav...</td>\n",
       "      <td>Willow Springs White</td>\n",
       "      <td>80</td>\n",
       "      <td>8.0</td>\n",
       "      <td>California</td>\n",
       "      <td>California</td>\n",
       "      <td>California Other</td>\n",
       "      <td>Jim Gordon</td>\n",
       "      <td>@gordone_cellars</td>\n",
       "      <td>CK Mondavi 2013 Willow Springs White Zinfandel...</td>\n",
       "      <td>Zinfandel</td>\n",
       "      <td>CK Mondavi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90904</th>\n",
       "      <td>Spain</td>\n",
       "      <td>Strange yeasty unfocused aromas are unclean. T...</td>\n",
       "      <td>None</td>\n",
       "      <td>80</td>\n",
       "      <td>8.0</td>\n",
       "      <td>Northern Spain</td>\n",
       "      <td>Cariñena</td>\n",
       "      <td>None</td>\n",
       "      <td>Michael Schachner</td>\n",
       "      <td>@wineschach</td>\n",
       "      <td>Hawthorne Ridge 2013 Chardonnay (Cariñena)</td>\n",
       "      <td>Chardonnay</td>\n",
       "      <td>Hawthorne Ridge</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90933</th>\n",
       "      <td>Spain</td>\n",
       "      <td>Raisin and funky leather are the prime aromas ...</td>\n",
       "      <td>Valdemoreda</td>\n",
       "      <td>80</td>\n",
       "      <td>8.0</td>\n",
       "      <td>Northern Spain</td>\n",
       "      <td>Rioja</td>\n",
       "      <td>None</td>\n",
       "      <td>Michael Schachner</td>\n",
       "      <td>@wineschach</td>\n",
       "      <td>Bodegas del Mundo 2010 Valdemoreda  (Rioja)</td>\n",
       "      <td>Tempranillo</td>\n",
       "      <td>Bodegas del Mundo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98548</th>\n",
       "      <td>Spain</td>\n",
       "      <td>This is dark in color, with apple cider aromas...</td>\n",
       "      <td>Valdemoreda Blanco</td>\n",
       "      <td>80</td>\n",
       "      <td>8.0</td>\n",
       "      <td>Northern Spain</td>\n",
       "      <td>Rioja</td>\n",
       "      <td>None</td>\n",
       "      <td>Michael Schachner</td>\n",
       "      <td>@wineschach</td>\n",
       "      <td>Bodegas del Mundo 2012 Valdemoreda Blanco Viur...</td>\n",
       "      <td>Viura</td>\n",
       "      <td>Bodegas del Mundo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99994</th>\n",
       "      <td>Argentina</td>\n",
       "      <td>Could the scent of microwaved popcorn be any s...</td>\n",
       "      <td>None</td>\n",
       "      <td>80</td>\n",
       "      <td>8.0</td>\n",
       "      <td>Mendoza Province</td>\n",
       "      <td>Mendoza</td>\n",
       "      <td>None</td>\n",
       "      <td>Michael Schachner</td>\n",
       "      <td>@wineschach</td>\n",
       "      <td>Bodega Norton 1999 Chardonnay (Mendoza)</td>\n",
       "      <td>Chardonnay</td>\n",
       "      <td>Bodega Norton</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99995</th>\n",
       "      <td>Chile</td>\n",
       "      <td>This one has bland aromatics, with only a touc...</td>\n",
       "      <td>None</td>\n",
       "      <td>80</td>\n",
       "      <td>8.0</td>\n",
       "      <td>Curicó Valley</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Michael Schachner</td>\n",
       "      <td>@wineschach</td>\n",
       "      <td>Millaman 2000 Chardonnay (Curicó Valley)</td>\n",
       "      <td>Chardonnay</td>\n",
       "      <td>Millaman</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109326</th>\n",
       "      <td>Portugal</td>\n",
       "      <td>This is a light, fruity and off-dry wine. It h...</td>\n",
       "      <td>None</td>\n",
       "      <td>80</td>\n",
       "      <td>8.0</td>\n",
       "      <td>Vinho Verde</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Roger Voss</td>\n",
       "      <td>@vossroger</td>\n",
       "      <td>Mapreco 2014 White (Vinho Verde)</td>\n",
       "      <td>Portuguese White</td>\n",
       "      <td>Mapreco</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109402</th>\n",
       "      <td>Argentina</td>\n",
       "      <td>Rubbery on the nose, then sharp in the mouth, ...</td>\n",
       "      <td>None</td>\n",
       "      <td>80</td>\n",
       "      <td>8.0</td>\n",
       "      <td>Mendoza Province</td>\n",
       "      <td>Mendoza</td>\n",
       "      <td>None</td>\n",
       "      <td>Michael Schachner</td>\n",
       "      <td>@wineschach</td>\n",
       "      <td>Finca El Origen 2010 Syrah (Mendoza)</td>\n",
       "      <td>Syrah</td>\n",
       "      <td>Finca El Origen</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117137</th>\n",
       "      <td>Argentina</td>\n",
       "      <td>This sweet Moscato is barely acceptable and it...</td>\n",
       "      <td>None</td>\n",
       "      <td>80</td>\n",
       "      <td>8.0</td>\n",
       "      <td>Mendoza Province</td>\n",
       "      <td>Mendoza</td>\n",
       "      <td>None</td>\n",
       "      <td>Michael Schachner</td>\n",
       "      <td>@wineschach</td>\n",
       "      <td>Twisted 2012 Moscato (Mendoza)</td>\n",
       "      <td>Moscato</td>\n",
       "      <td>Twisted</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>123540</th>\n",
       "      <td>Chile</td>\n",
       "      <td>Less adequate than in the past. The wine lacks...</td>\n",
       "      <td>120</td>\n",
       "      <td>80</td>\n",
       "      <td>8.0</td>\n",
       "      <td>Central Valley</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Michael Schachner</td>\n",
       "      <td>@wineschach</td>\n",
       "      <td>Santa Rita 2010 120 Sauvignon Blanc (Central V...</td>\n",
       "      <td>Sauvignon Blanc</td>\n",
       "      <td>Santa Rita</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125825</th>\n",
       "      <td>Spain</td>\n",
       "      <td>Strawberry and raspberry aromas set up a reedy...</td>\n",
       "      <td>Valdemoreda Rosado</td>\n",
       "      <td>80</td>\n",
       "      <td>8.0</td>\n",
       "      <td>Northern Spain</td>\n",
       "      <td>Rioja</td>\n",
       "      <td>None</td>\n",
       "      <td>Michael Schachner</td>\n",
       "      <td>@wineschach</td>\n",
       "      <td>Bodegas del Mundo 2011 Valdemoreda Rosado Garn...</td>\n",
       "      <td>Garnacha</td>\n",
       "      <td>Bodegas del Mundo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13782</th>\n",
       "      <td>Chile</td>\n",
       "      <td>Yeasty, melony and smelling like yellow mustar...</td>\n",
       "      <td>Left Coast</td>\n",
       "      <td>80</td>\n",
       "      <td>7.0</td>\n",
       "      <td>Chile</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Michael Schachner</td>\n",
       "      <td>@wineschach</td>\n",
       "      <td>flipflop NV Left Coast Moscato (Chile)</td>\n",
       "      <td>Moscato</td>\n",
       "      <td>flipflop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34500</th>\n",
       "      <td>Chile</td>\n",
       "      <td>Average peach and apple aromas are as good as ...</td>\n",
       "      <td>Un-Oaked</td>\n",
       "      <td>80</td>\n",
       "      <td>7.0</td>\n",
       "      <td>Colchagua Valley</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Michael Schachner</td>\n",
       "      <td>@wineschach</td>\n",
       "      <td>La Playa 2009 Un-Oaked Chardonnay (Colchagua V...</td>\n",
       "      <td>Chardonnay</td>\n",
       "      <td>La Playa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36194</th>\n",
       "      <td>Chile</td>\n",
       "      <td>Tropical, citrusy aromas are about as good as ...</td>\n",
       "      <td>None</td>\n",
       "      <td>80</td>\n",
       "      <td>7.0</td>\n",
       "      <td>Central Valley</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Michael Schachner</td>\n",
       "      <td>@wineschach</td>\n",
       "      <td>Beach Kite 2012 Moscato (Central Valley)</td>\n",
       "      <td>Moscato</td>\n",
       "      <td>Beach Kite</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54292</th>\n",
       "      <td>Spain</td>\n",
       "      <td>Dusty apple and papaya aromas lack fortitude. ...</td>\n",
       "      <td>None</td>\n",
       "      <td>80</td>\n",
       "      <td>7.0</td>\n",
       "      <td>Central Spain</td>\n",
       "      <td>La Mancha</td>\n",
       "      <td>None</td>\n",
       "      <td>Michael Schachner</td>\n",
       "      <td>@wineschach</td>\n",
       "      <td>Despierta 2014 Chardonnay (La Mancha)</td>\n",
       "      <td>Chardonnay</td>\n",
       "      <td>Despierta</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75555</th>\n",
       "      <td>Spain</td>\n",
       "      <td>This affordable sparkler starts off with odd, ...</td>\n",
       "      <td>Carta Nevada Brut</td>\n",
       "      <td>80</td>\n",
       "      <td>7.0</td>\n",
       "      <td>Catalonia</td>\n",
       "      <td>Penedès</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Freixenet NV Carta Nevada Brut  (Penedès)</td>\n",
       "      <td>Champagne Blend</td>\n",
       "      <td>Freixenet</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87123</th>\n",
       "      <td>Spain</td>\n",
       "      <td>An unclean nose smells cheesy. This is flabby ...</td>\n",
       "      <td>None</td>\n",
       "      <td>80</td>\n",
       "      <td>7.0</td>\n",
       "      <td>Levante</td>\n",
       "      <td>Valencia</td>\n",
       "      <td>None</td>\n",
       "      <td>Michael Schachner</td>\n",
       "      <td>@wineschach</td>\n",
       "      <td>Torre Oria 2014 Shiraz-Tempranillo (Valencia)</td>\n",
       "      <td>Shiraz-Tempranillo</td>\n",
       "      <td>Torre Oria</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93690</th>\n",
       "      <td>US</td>\n",
       "      <td>Barely drinkable, although you'll get by at bi...</td>\n",
       "      <td>None</td>\n",
       "      <td>80</td>\n",
       "      <td>7.0</td>\n",
       "      <td>California</td>\n",
       "      <td>California</td>\n",
       "      <td>California Other</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Backhouse 2010 Pinot Noir (California)</td>\n",
       "      <td>Pinot Noir</td>\n",
       "      <td>Backhouse</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102480</th>\n",
       "      <td>Chile</td>\n",
       "      <td>This has overripe tropical-fruit aromas on the...</td>\n",
       "      <td>Gaucho Andino</td>\n",
       "      <td>80</td>\n",
       "      <td>7.0</td>\n",
       "      <td>Maule Valley</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Michael Schachner</td>\n",
       "      <td>@wineschach</td>\n",
       "      <td>Aguirre 2014 Gaucho Andino Chardonnay (Maule V...</td>\n",
       "      <td>Chardonnay</td>\n",
       "      <td>Aguirre</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125773</th>\n",
       "      <td>US</td>\n",
       "      <td>Cheese, milkweed and straw make for an unattra...</td>\n",
       "      <td>None</td>\n",
       "      <td>80</td>\n",
       "      <td>7.0</td>\n",
       "      <td>Oregon</td>\n",
       "      <td>Willamette Valley</td>\n",
       "      <td>Willamette Valley</td>\n",
       "      <td>Michael Schachner</td>\n",
       "      <td>@wineschach</td>\n",
       "      <td>Montinore 2000 Müller-Thurgau (Willamette Valley)</td>\n",
       "      <td>Müller-Thurgau</td>\n",
       "      <td>Montinore</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125774</th>\n",
       "      <td>US</td>\n",
       "      <td>The “Reserve” on the label is hardly appropria...</td>\n",
       "      <td>Reserve</td>\n",
       "      <td>80</td>\n",
       "      <td>7.0</td>\n",
       "      <td>California</td>\n",
       "      <td>Monterey</td>\n",
       "      <td>Central Coast</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Turning Leaf 2001 Reserve Riesling (Monterey)</td>\n",
       "      <td>Riesling</td>\n",
       "      <td>Turning Leaf</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34501</th>\n",
       "      <td>Chile</td>\n",
       "      <td>Neutral aromas, sour apple and citrus flavors,...</td>\n",
       "      <td>None</td>\n",
       "      <td>80</td>\n",
       "      <td>6.0</td>\n",
       "      <td>Curicó Valley</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Michael Schachner</td>\n",
       "      <td>@wineschach</td>\n",
       "      <td>Quasar 2009 Chardonnay (Curicó Valley)</td>\n",
       "      <td>Chardonnay</td>\n",
       "      <td>Quasar</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81390</th>\n",
       "      <td>Spain</td>\n",
       "      <td>Very light, even thin, this white lacks the st...</td>\n",
       "      <td>Mediterranean White</td>\n",
       "      <td>80</td>\n",
       "      <td>6.0</td>\n",
       "      <td>Catalonia</td>\n",
       "      <td>Catalonia</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>René Barbier NV Mediterranean White White (Cat...</td>\n",
       "      <td>White Blend</td>\n",
       "      <td>René Barbier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99996</th>\n",
       "      <td>Chile</td>\n",
       "      <td>The nose is sulphuric and a bit barnyardy, whi...</td>\n",
       "      <td>Estate</td>\n",
       "      <td>80</td>\n",
       "      <td>6.0</td>\n",
       "      <td>Maipo Valley</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Michael Schachner</td>\n",
       "      <td>@wineschach</td>\n",
       "      <td>Santa Alicia 2001 Estate Chardonnay (Maipo Val...</td>\n",
       "      <td>Chardonnay</td>\n",
       "      <td>Santa Alicia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23437</th>\n",
       "      <td>Argentina</td>\n",
       "      <td>Candied plum and red berry aromas smell like r...</td>\n",
       "      <td>Estate Bottled</td>\n",
       "      <td>80</td>\n",
       "      <td>5.0</td>\n",
       "      <td>Mendoza Province</td>\n",
       "      <td>Mendoza</td>\n",
       "      <td>None</td>\n",
       "      <td>Michael Schachner</td>\n",
       "      <td>@wineschach</td>\n",
       "      <td>Terrenal 2013 Estate Bottled Malbec (Mendoza)</td>\n",
       "      <td>Malbec</td>\n",
       "      <td>Terrenal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125826</th>\n",
       "      <td>Argentina</td>\n",
       "      <td>While this smells floral and candied, the pala...</td>\n",
       "      <td>None</td>\n",
       "      <td>80</td>\n",
       "      <td>5.0</td>\n",
       "      <td>Mendoza Province</td>\n",
       "      <td>Mendoza</td>\n",
       "      <td>None</td>\n",
       "      <td>Michael Schachner</td>\n",
       "      <td>@wineschach</td>\n",
       "      <td>Toca Diamonte 2010 Malbec (Mendoza)</td>\n",
       "      <td>Malbec</td>\n",
       "      <td>Toca Diamonte</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117025</th>\n",
       "      <td>Portugal</td>\n",
       "      <td>A curious sauerkraut perfume leads to a hard e...</td>\n",
       "      <td>None</td>\n",
       "      <td>80</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Lisboa</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Roger Voss</td>\n",
       "      <td>@vossroger</td>\n",
       "      <td>Quinta do Pinto 2008 Touriga Nacional (Lisboa)</td>\n",
       "      <td>Touriga Nacional</td>\n",
       "      <td>Quinta do Pinto</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>123541</th>\n",
       "      <td>Italy</td>\n",
       "      <td>This Valpolicella blend opens with an aged, br...</td>\n",
       "      <td>Corte Antica</td>\n",
       "      <td>80</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Veneto</td>\n",
       "      <td>Valpolicella Classico Superiore</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Cantine Benedetti 2008 Corte Antica  (Valpolic...</td>\n",
       "      <td>Corvina, Rondinella, Molinara</td>\n",
       "      <td>Cantine Benedetti</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>129971 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          country                                        description  \\\n",
       "111753     France  Almost black in color, this stunning wine is g...   \n",
       "111755     France  This is the finest Cheval Blanc for many years...   \n",
       "122935     France  Full of ripe fruit, opulent and concentrated, ...   \n",
       "114972   Portugal  A powerful and ripe wine, strongly influenced ...   \n",
       "89729      France  This new release from a great vintage for Char...   \n",
       "45781       Italy  This gorgeous, fragrant wine opens with classi...   \n",
       "39286       Italy  A perfect wine from a classic vintage, the 200...   \n",
       "42197    Portugal  This is the latest release of what has long be...   \n",
       "118058         US  This wine dazzles with perfection. Sourced fro...   \n",
       "111756     France  A hugely powerful wine, full of dark, brooding...   \n",
       "345     Australia  This wine contains some material over 100 year...   \n",
       "111754      Italy  It takes only a few moments before you appreci...   \n",
       "36528      France  This is a fabulous wine from the greatest Cham...   \n",
       "89728      France  This latest incarnation of the famous brand is...   \n",
       "7335        Italy  Thick as molasses and dark as caramelized brow...   \n",
       "45798          US  Tasted in a flight of great and famous Napa wi...   \n",
       "58352      France  This is a magnificently solid wine, initially ...   \n",
       "113929         US  In 2005 Charles Smith introduced three high-en...   \n",
       "123545         US  Initially a rather subdued Frog; as if it has ...   \n",
       "56953   Australia  This inky, embryonic wine deserves to be cella...   \n",
       "36529      France  Pure Chardonnay from the walled vineyard in th...   \n",
       "44994       Italy  This stunning wine is all about extreme elegan...   \n",
       "98375      France  In this great year for white Burgundy, Bâtard-...   \n",
       "60880       Italy  This is an elegant Nebbiolo-based wine and arg...   \n",
       "60881       Italy  Always a standout among Gaja's five single-vin...   \n",
       "56043    Portugal  This is the latest release of Portugal's most ...   \n",
       "39287       Italy  Here's a “wow” wine you won't easily forget. M...   \n",
       "109427  Australia  This wine is dark brown in hue with a greenish...   \n",
       "116140         US  This blend from individual blocks includes 94%...   \n",
       "121884         US  This is an absolutely beautiful wine to drink ...   \n",
       "...           ...                                                ...   \n",
       "82746   Argentina  Yellow and chunky, and definitely on the way t...   \n",
       "83847       Spain  This smells like compost. It feels hard and cl...   \n",
       "86712          US  A pop style of pink wine that the Peter Mondav...   \n",
       "90904       Spain  Strange yeasty unfocused aromas are unclean. T...   \n",
       "90933       Spain  Raisin and funky leather are the prime aromas ...   \n",
       "98548       Spain  This is dark in color, with apple cider aromas...   \n",
       "99994   Argentina  Could the scent of microwaved popcorn be any s...   \n",
       "99995       Chile  This one has bland aromatics, with only a touc...   \n",
       "109326   Portugal  This is a light, fruity and off-dry wine. It h...   \n",
       "109402  Argentina  Rubbery on the nose, then sharp in the mouth, ...   \n",
       "117137  Argentina  This sweet Moscato is barely acceptable and it...   \n",
       "123540      Chile  Less adequate than in the past. The wine lacks...   \n",
       "125825      Spain  Strawberry and raspberry aromas set up a reedy...   \n",
       "13782       Chile  Yeasty, melony and smelling like yellow mustar...   \n",
       "34500       Chile  Average peach and apple aromas are as good as ...   \n",
       "36194       Chile  Tropical, citrusy aromas are about as good as ...   \n",
       "54292       Spain  Dusty apple and papaya aromas lack fortitude. ...   \n",
       "75555       Spain  This affordable sparkler starts off with odd, ...   \n",
       "87123       Spain  An unclean nose smells cheesy. This is flabby ...   \n",
       "93690          US  Barely drinkable, although you'll get by at bi...   \n",
       "102480      Chile  This has overripe tropical-fruit aromas on the...   \n",
       "125773         US  Cheese, milkweed and straw make for an unattra...   \n",
       "125774         US  The “Reserve” on the label is hardly appropria...   \n",
       "34501       Chile  Neutral aromas, sour apple and citrus flavors,...   \n",
       "81390       Spain  Very light, even thin, this white lacks the st...   \n",
       "99996       Chile  The nose is sulphuric and a bit barnyardy, whi...   \n",
       "23437   Argentina  Candied plum and red berry aromas smell like r...   \n",
       "125826  Argentina  While this smells floral and candied, the pala...   \n",
       "117025   Portugal  A curious sauerkraut perfume leads to a hard e...   \n",
       "123541      Italy  This Valpolicella blend opens with an aged, br...   \n",
       "\n",
       "                                designation  points   price          province  \\\n",
       "111753                                 None     100  1500.0          Bordeaux   \n",
       "111755                                 None     100  1500.0          Bordeaux   \n",
       "122935                                 None     100   848.0          Bordeaux   \n",
       "114972                     Nacional Vintage     100   650.0              Port   \n",
       "89729        Le Mesnil Blanc de Blancs Brut     100   617.0         Champagne   \n",
       "45781                               Riserva     100   550.0           Tuscany   \n",
       "39286                               Masseto     100   460.0           Tuscany   \n",
       "42197                           Barca-Velha     100   450.0             Douro   \n",
       "118058                              La Muse     100   450.0        California   \n",
       "111756                                 None     100   359.0          Bordeaux   \n",
       "345                                    Rare     100   350.0          Victoria   \n",
       "111754                           Cerretalto     100   270.0           Tuscany   \n",
       "36528                                  Brut     100   259.0         Champagne   \n",
       "89728                  Cristal Vintage Brut     100   250.0         Champagne   \n",
       "7335                      Occhio di Pernice     100   210.0           Tuscany   \n",
       "45798                                  None     100   200.0        California   \n",
       "58352                                  None     100   150.0          Bordeaux   \n",
       "113929                           Royal City     100    80.0        Washington   \n",
       "123545                          Bionic Frog     100    80.0        Washington   \n",
       "56953                                Grange      99   850.0   South Australia   \n",
       "36529   Clos du Mesnil Brut Blanc de Blancs      99   800.0         Champagne   \n",
       "44994                 Cà d'Morissio Riserva      99   595.0          Piedmont   \n",
       "98375                                  None      99   560.0          Burgundy   \n",
       "60880                           Sorì Tildìn      99   440.0          Piedmont   \n",
       "60881                      Sorì San Lorenzo      99   440.0          Piedmont   \n",
       "56043                           Barca Velha      99   426.0             Douro   \n",
       "39287                              Messorio      99   320.0           Tuscany   \n",
       "109427                                 Rare      99   300.0          Victoria   \n",
       "116140                                  ERA      99   300.0        California   \n",
       "121884                            IX Estate      99   290.0        California   \n",
       "...                                     ...     ...     ...               ...   \n",
       "82746                            1492 White      80     8.0  Mendoza Province   \n",
       "83847                                 Manon      80     8.0     Central Spain   \n",
       "86712                  Willow Springs White      80     8.0        California   \n",
       "90904                                  None      80     8.0    Northern Spain   \n",
       "90933                           Valdemoreda      80     8.0    Northern Spain   \n",
       "98548                    Valdemoreda Blanco      80     8.0    Northern Spain   \n",
       "99994                                  None      80     8.0  Mendoza Province   \n",
       "99995                                  None      80     8.0     Curicó Valley   \n",
       "109326                                 None      80     8.0       Vinho Verde   \n",
       "109402                                 None      80     8.0  Mendoza Province   \n",
       "117137                                 None      80     8.0  Mendoza Province   \n",
       "123540                                  120      80     8.0    Central Valley   \n",
       "125825                   Valdemoreda Rosado      80     8.0    Northern Spain   \n",
       "13782                            Left Coast      80     7.0             Chile   \n",
       "34500                              Un-Oaked      80     7.0  Colchagua Valley   \n",
       "36194                                  None      80     7.0    Central Valley   \n",
       "54292                                  None      80     7.0     Central Spain   \n",
       "75555                     Carta Nevada Brut      80     7.0         Catalonia   \n",
       "87123                                  None      80     7.0           Levante   \n",
       "93690                                  None      80     7.0        California   \n",
       "102480                        Gaucho Andino      80     7.0      Maule Valley   \n",
       "125773                                 None      80     7.0            Oregon   \n",
       "125774                              Reserve      80     7.0        California   \n",
       "34501                                  None      80     6.0     Curicó Valley   \n",
       "81390                   Mediterranean White      80     6.0         Catalonia   \n",
       "99996                                Estate      80     6.0      Maipo Valley   \n",
       "23437                        Estate Bottled      80     5.0  Mendoza Province   \n",
       "125826                                 None      80     5.0  Mendoza Province   \n",
       "117025                                 None      80     NaN            Lisboa   \n",
       "123541                         Corte Antica      80     NaN            Veneto   \n",
       "\n",
       "                               region_1           region_2        taster_name  \\\n",
       "111753                         Pauillac               None         Roger Voss   \n",
       "111755                    Saint-Émilion               None         Roger Voss   \n",
       "122935                   Pessac-Léognan               None         Roger Voss   \n",
       "114972                             None               None         Roger Voss   \n",
       "89729                         Champagne               None         Roger Voss   \n",
       "45781            Brunello di Montalcino               None      Kerin O’Keefe   \n",
       "39286                           Toscana               None               None   \n",
       "42197                              None               None         Roger Voss   \n",
       "118058                    Sonoma County             Sonoma               None   \n",
       "111756                     Saint-Julien               None         Roger Voss   \n",
       "345                          Rutherglen               None     Joe Czerwinski   \n",
       "111754           Brunello di Montalcino               None               None   \n",
       "36528                         Champagne               None         Roger Voss   \n",
       "89728                         Champagne               None         Roger Voss   \n",
       "7335         Vin Santo di Montepulciano               None               None   \n",
       "45798                       Napa Valley               Napa               None   \n",
       "58352                      Saint-Julien               None         Roger Voss   \n",
       "113929             Columbia Valley (WA)    Columbia Valley       Paul Gregutt   \n",
       "123545          Walla Walla Valley (WA)    Columbia Valley       Paul Gregutt   \n",
       "56953                   South Australia               None     Joe Czerwinski   \n",
       "36529                         Champagne               None         Roger Voss   \n",
       "44994                            Barolo               None      Kerin O’Keefe   \n",
       "98375                 Bâtard-Montrachet               None         Roger Voss   \n",
       "60880                            Langhe               None               None   \n",
       "60881                            Langhe               None               None   \n",
       "56043                              None               None         Roger Voss   \n",
       "39287                           Toscana               None               None   \n",
       "109427                       Rutherglen               None     Joe Czerwinski   \n",
       "116140                      Napa Valley               Napa     Virginie Boone   \n",
       "121884                      Napa Valley               Napa               None   \n",
       "...                                 ...                ...                ...   \n",
       "82746                           Mendoza               None  Michael Schachner   \n",
       "83847     Vino de la Tierra de Castilla               None  Michael Schachner   \n",
       "86712                        California   California Other         Jim Gordon   \n",
       "90904                          Cariñena               None  Michael Schachner   \n",
       "90933                             Rioja               None  Michael Schachner   \n",
       "98548                             Rioja               None  Michael Schachner   \n",
       "99994                           Mendoza               None  Michael Schachner   \n",
       "99995                              None               None  Michael Schachner   \n",
       "109326                             None               None         Roger Voss   \n",
       "109402                          Mendoza               None  Michael Schachner   \n",
       "117137                          Mendoza               None  Michael Schachner   \n",
       "123540                             None               None  Michael Schachner   \n",
       "125825                            Rioja               None  Michael Schachner   \n",
       "13782                              None               None  Michael Schachner   \n",
       "34500                              None               None  Michael Schachner   \n",
       "36194                              None               None  Michael Schachner   \n",
       "54292                         La Mancha               None  Michael Schachner   \n",
       "75555                           Penedès               None               None   \n",
       "87123                          Valencia               None  Michael Schachner   \n",
       "93690                        California   California Other               None   \n",
       "102480                             None               None  Michael Schachner   \n",
       "125773                Willamette Valley  Willamette Valley  Michael Schachner   \n",
       "125774                         Monterey      Central Coast               None   \n",
       "34501                              None               None  Michael Schachner   \n",
       "81390                         Catalonia               None               None   \n",
       "99996                              None               None  Michael Schachner   \n",
       "23437                           Mendoza               None  Michael Schachner   \n",
       "125826                          Mendoza               None  Michael Schachner   \n",
       "117025                             None               None         Roger Voss   \n",
       "123541  Valpolicella Classico Superiore               None               None   \n",
       "\n",
       "       taster_twitter_handle  \\\n",
       "111753            @vossroger   \n",
       "111755            @vossroger   \n",
       "122935            @vossroger   \n",
       "114972            @vossroger   \n",
       "89729             @vossroger   \n",
       "45781           @kerinokeefe   \n",
       "39286                   None   \n",
       "42197             @vossroger   \n",
       "118058                  None   \n",
       "111756            @vossroger   \n",
       "345                   @JoeCz   \n",
       "111754                  None   \n",
       "36528             @vossroger   \n",
       "89728             @vossroger   \n",
       "7335                    None   \n",
       "45798                   None   \n",
       "58352             @vossroger   \n",
       "113929           @paulgwine    \n",
       "123545           @paulgwine    \n",
       "56953                 @JoeCz   \n",
       "36529             @vossroger   \n",
       "44994           @kerinokeefe   \n",
       "98375             @vossroger   \n",
       "60880                   None   \n",
       "60881                   None   \n",
       "56043             @vossroger   \n",
       "39287                   None   \n",
       "109427                @JoeCz   \n",
       "116140               @vboone   \n",
       "121884                  None   \n",
       "...                      ...   \n",
       "82746            @wineschach   \n",
       "83847            @wineschach   \n",
       "86712       @gordone_cellars   \n",
       "90904            @wineschach   \n",
       "90933            @wineschach   \n",
       "98548            @wineschach   \n",
       "99994            @wineschach   \n",
       "99995            @wineschach   \n",
       "109326            @vossroger   \n",
       "109402           @wineschach   \n",
       "117137           @wineschach   \n",
       "123540           @wineschach   \n",
       "125825           @wineschach   \n",
       "13782            @wineschach   \n",
       "34500            @wineschach   \n",
       "36194            @wineschach   \n",
       "54292            @wineschach   \n",
       "75555                   None   \n",
       "87123            @wineschach   \n",
       "93690                   None   \n",
       "102480           @wineschach   \n",
       "125773           @wineschach   \n",
       "125774                  None   \n",
       "34501            @wineschach   \n",
       "81390                   None   \n",
       "99996            @wineschach   \n",
       "23437            @wineschach   \n",
       "125826           @wineschach   \n",
       "117025            @vossroger   \n",
       "123541                  None   \n",
       "\n",
       "                                                    title  \\\n",
       "111753           Château Lafite Rothschild 2010  Pauillac   \n",
       "111755           Château Cheval Blanc 2010  Saint-Émilion   \n",
       "122935            Château Haut-Brion 2014  Pessac-Léognan   \n",
       "114972      Quinta do Noval 2011 Nacional Vintage  (Port)   \n",
       "89729   Salon 2006 Le Mesnil Blanc de Blancs Brut Char...   \n",
       "45781   Biondi Santi 2010 Riserva  (Brunello di Montal...   \n",
       "39286   Tenuta dell'Ornellaia 2007 Masseto Merlot (Tos...   \n",
       "42197       Casa Ferreirinha 2008 Barca-Velha Red (Douro)   \n",
       "118058            Verité 2007 La Muse Red (Sonoma County)   \n",
       "111756      Château Léoville Las Cases 2010  Saint-Julien   \n",
       "345     Chambers Rosewood Vineyards NV Rare Muscat (Ru...   \n",
       "111754  Casanova di Neri 2007 Cerretalto  (Brunello di...   \n",
       "36528                         Krug 2002 Brut  (Champagne)   \n",
       "89728   Louis Roederer 2008 Cristal Vintage Brut  (Cha...   \n",
       "7335    Avignonesi 1995 Occhio di Pernice  (Vin Santo ...   \n",
       "45798     Cardinale 2006 Cabernet Sauvignon (Napa Valley)   \n",
       "58352          Château Léoville Barton 2010  Saint-Julien   \n",
       "113929  Charles Smith 2006 Royal City Syrah (Columbia ...   \n",
       "123545  Cayuse 2008 Bionic Frog Syrah (Walla Walla Val...   \n",
       "56953       Penfolds 2010 Grange Shiraz (South Australia)   \n",
       "36529   Krug 2002 Clos du Mesnil Brut Blanc de Blancs ...   \n",
       "44994   Mascarello Giuseppe e Figlio 2008 Cà d'Morissi...   \n",
       "98375            Domaine Leflaive 2010  Bâtard-Montrachet   \n",
       "60880             Gaja 2007 Sorì Tildìn Nebbiolo (Langhe)   \n",
       "60881        Gaja 2007 Sorì San Lorenzo Nebbiolo (Langhe)   \n",
       "56043       Casa Ferreirinha 2004 Barca Velha Red (Douro)   \n",
       "39287         Le Macchiole 2007 Messorio Merlot (Toscana)   \n",
       "109427  Chambers Rosewood Vineyards NV Rare Muscadelle...   \n",
       "116140             Alpha Omega 2012 ERA Red (Napa Valley)   \n",
       "121884            Colgin 2008 IX Estate Red (Napa Valley)   \n",
       "...                                                   ...   \n",
       "82746      Cristobal 1492 2009 1492 White White (Mendoza)   \n",
       "83847   Mano A Mano 2009 Manon Tempranillo (Vino de la...   \n",
       "86712   CK Mondavi 2013 Willow Springs White Zinfandel...   \n",
       "90904          Hawthorne Ridge 2013 Chardonnay (Cariñena)   \n",
       "90933         Bodegas del Mundo 2010 Valdemoreda  (Rioja)   \n",
       "98548   Bodegas del Mundo 2012 Valdemoreda Blanco Viur...   \n",
       "99994             Bodega Norton 1999 Chardonnay (Mendoza)   \n",
       "99995            Millaman 2000 Chardonnay (Curicó Valley)   \n",
       "109326                   Mapreco 2014 White (Vinho Verde)   \n",
       "109402               Finca El Origen 2010 Syrah (Mendoza)   \n",
       "117137                     Twisted 2012 Moscato (Mendoza)   \n",
       "123540  Santa Rita 2010 120 Sauvignon Blanc (Central V...   \n",
       "125825  Bodegas del Mundo 2011 Valdemoreda Rosado Garn...   \n",
       "13782              flipflop NV Left Coast Moscato (Chile)   \n",
       "34500   La Playa 2009 Un-Oaked Chardonnay (Colchagua V...   \n",
       "36194            Beach Kite 2012 Moscato (Central Valley)   \n",
       "54292               Despierta 2014 Chardonnay (La Mancha)   \n",
       "75555           Freixenet NV Carta Nevada Brut  (Penedès)   \n",
       "87123       Torre Oria 2014 Shiraz-Tempranillo (Valencia)   \n",
       "93690              Backhouse 2010 Pinot Noir (California)   \n",
       "102480  Aguirre 2014 Gaucho Andino Chardonnay (Maule V...   \n",
       "125773  Montinore 2000 Müller-Thurgau (Willamette Valley)   \n",
       "125774      Turning Leaf 2001 Reserve Riesling (Monterey)   \n",
       "34501              Quasar 2009 Chardonnay (Curicó Valley)   \n",
       "81390   René Barbier NV Mediterranean White White (Cat...   \n",
       "99996   Santa Alicia 2001 Estate Chardonnay (Maipo Val...   \n",
       "23437       Terrenal 2013 Estate Bottled Malbec (Mendoza)   \n",
       "125826                Toca Diamonte 2010 Malbec (Mendoza)   \n",
       "117025     Quinta do Pinto 2008 Touriga Nacional (Lisboa)   \n",
       "123541  Cantine Benedetti 2008 Corte Antica  (Valpolic...   \n",
       "\n",
       "                              variety                        winery  \n",
       "111753       Bordeaux-style Red Blend     Château Lafite Rothschild  \n",
       "111755       Bordeaux-style Red Blend          Château Cheval Blanc  \n",
       "122935     Bordeaux-style White Blend            Château Haut-Brion  \n",
       "114972                           Port               Quinta do Noval  \n",
       "89729                      Chardonnay                         Salon  \n",
       "45781                      Sangiovese                  Biondi Santi  \n",
       "39286                          Merlot         Tenuta dell'Ornellaia  \n",
       "42197                  Portuguese Red              Casa Ferreirinha  \n",
       "118058       Bordeaux-style Red Blend                        Verité  \n",
       "111756       Bordeaux-style Red Blend    Château Léoville Las Cases  \n",
       "345                            Muscat   Chambers Rosewood Vineyards  \n",
       "111754              Sangiovese Grosso              Casanova di Neri  \n",
       "36528                 Champagne Blend                          Krug  \n",
       "89728                 Champagne Blend                Louis Roederer  \n",
       "7335                 Prugnolo Gentile                    Avignonesi  \n",
       "45798              Cabernet Sauvignon                     Cardinale  \n",
       "58352        Bordeaux-style Red Blend       Château Léoville Barton  \n",
       "113929                          Syrah                 Charles Smith  \n",
       "123545                          Syrah                        Cayuse  \n",
       "56953                          Shiraz                      Penfolds  \n",
       "36529                      Chardonnay                          Krug  \n",
       "44994                        Nebbiolo  Mascarello Giuseppe e Figlio  \n",
       "98375                      Chardonnay              Domaine Leflaive  \n",
       "60880                        Nebbiolo                          Gaja  \n",
       "60881                        Nebbiolo                          Gaja  \n",
       "56043                  Portuguese Red              Casa Ferreirinha  \n",
       "39287                          Merlot                  Le Macchiole  \n",
       "109427                     Muscadelle   Chambers Rosewood Vineyards  \n",
       "116140       Bordeaux-style Red Blend                   Alpha Omega  \n",
       "121884                      Red Blend                        Colgin  \n",
       "...                               ...                           ...  \n",
       "82746                     White Blend                Cristobal 1492  \n",
       "83847                     Tempranillo                   Mano A Mano  \n",
       "86712                       Zinfandel                    CK Mondavi  \n",
       "90904                      Chardonnay               Hawthorne Ridge  \n",
       "90933                     Tempranillo             Bodegas del Mundo  \n",
       "98548                           Viura             Bodegas del Mundo  \n",
       "99994                      Chardonnay                 Bodega Norton  \n",
       "99995                      Chardonnay                      Millaman  \n",
       "109326               Portuguese White                       Mapreco  \n",
       "109402                          Syrah               Finca El Origen  \n",
       "117137                        Moscato                       Twisted  \n",
       "123540                Sauvignon Blanc                    Santa Rita  \n",
       "125825                       Garnacha             Bodegas del Mundo  \n",
       "13782                         Moscato                      flipflop  \n",
       "34500                      Chardonnay                      La Playa  \n",
       "36194                         Moscato                    Beach Kite  \n",
       "54292                      Chardonnay                     Despierta  \n",
       "75555                 Champagne Blend                     Freixenet  \n",
       "87123              Shiraz-Tempranillo                    Torre Oria  \n",
       "93690                      Pinot Noir                     Backhouse  \n",
       "102480                     Chardonnay                       Aguirre  \n",
       "125773                 Müller-Thurgau                     Montinore  \n",
       "125774                       Riesling                  Turning Leaf  \n",
       "34501                      Chardonnay                        Quasar  \n",
       "81390                     White Blend                  René Barbier  \n",
       "99996                      Chardonnay                  Santa Alicia  \n",
       "23437                          Malbec                      Terrenal  \n",
       "125826                         Malbec                 Toca Diamonte  \n",
       "117025               Touriga Nacional               Quinta do Pinto  \n",
       "123541  Corvina, Rondinella, Molinara             Cantine Benedetti  \n",
       "\n",
       "[129971 rows x 13 columns]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wine.sort_values(['points', 'price'], ascending=False)  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Points stats for a bottle of wine by region_1\n",
    "\n",
    "The table below describes the count of wines, the average point review, and review quartiles information per region_1. For example, Napa Valley has about 4480k wines that average a review of 89. The minimum reivew for Pinot Noir is 80 while the maximum is 100."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>region_1</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>None</th>\n",
       "      <td>21247.0</td>\n",
       "      <td>88.241022</td>\n",
       "      <td>2.949357</td>\n",
       "      <td>80.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Napa Valley</th>\n",
       "      <td>4480.0</td>\n",
       "      <td>89.043750</td>\n",
       "      <td>3.188694</td>\n",
       "      <td>80.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Columbia Valley (WA)</th>\n",
       "      <td>4124.0</td>\n",
       "      <td>88.718477</td>\n",
       "      <td>2.573591</td>\n",
       "      <td>80.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Russian River Valley</th>\n",
       "      <td>3091.0</td>\n",
       "      <td>89.525720</td>\n",
       "      <td>3.196514</td>\n",
       "      <td>80.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>98.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>California</th>\n",
       "      <td>2629.0</td>\n",
       "      <td>85.680107</td>\n",
       "      <td>2.731097</td>\n",
       "      <td>80.0</td>\n",
       "      <td>84.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>97.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Paso Robles</th>\n",
       "      <td>2350.0</td>\n",
       "      <td>87.892340</td>\n",
       "      <td>3.134678</td>\n",
       "      <td>80.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>96.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mendoza</th>\n",
       "      <td>2301.0</td>\n",
       "      <td>86.501086</td>\n",
       "      <td>3.203480</td>\n",
       "      <td>80.0</td>\n",
       "      <td>84.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>97.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Willamette Valley</th>\n",
       "      <td>2301.0</td>\n",
       "      <td>89.083877</td>\n",
       "      <td>2.671818</td>\n",
       "      <td>80.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>97.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Alsace</th>\n",
       "      <td>2163.0</td>\n",
       "      <td>89.472954</td>\n",
       "      <td>3.025422</td>\n",
       "      <td>80.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>97.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Champagne</th>\n",
       "      <td>1613.0</td>\n",
       "      <td>90.234966</td>\n",
       "      <td>2.702121</td>\n",
       "      <td>82.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Barolo</th>\n",
       "      <td>1599.0</td>\n",
       "      <td>90.836148</td>\n",
       "      <td>2.653436</td>\n",
       "      <td>83.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>93.0</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Finger Lakes</th>\n",
       "      <td>1565.0</td>\n",
       "      <td>87.094569</td>\n",
       "      <td>2.131844</td>\n",
       "      <td>80.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>94.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sonoma Coast</th>\n",
       "      <td>1474.0</td>\n",
       "      <td>89.970149</td>\n",
       "      <td>2.999738</td>\n",
       "      <td>81.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brunello di Montalcino</th>\n",
       "      <td>1470.0</td>\n",
       "      <td>90.468027</td>\n",
       "      <td>2.560898</td>\n",
       "      <td>83.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rioja</th>\n",
       "      <td>1469.0</td>\n",
       "      <td>87.713410</td>\n",
       "      <td>3.005937</td>\n",
       "      <td>80.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>97.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sonoma County</th>\n",
       "      <td>1246.0</td>\n",
       "      <td>87.392456</td>\n",
       "      <td>2.892879</td>\n",
       "      <td>80.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Toscana</th>\n",
       "      <td>1197.0</td>\n",
       "      <td>89.193818</td>\n",
       "      <td>2.772752</td>\n",
       "      <td>81.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Walla Walla Valley (WA)</th>\n",
       "      <td>1066.0</td>\n",
       "      <td>90.284240</td>\n",
       "      <td>2.594482</td>\n",
       "      <td>83.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Chianti Classico</th>\n",
       "      <td>1062.0</td>\n",
       "      <td>88.680791</td>\n",
       "      <td>2.363480</td>\n",
       "      <td>81.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>96.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Santa Barbara County</th>\n",
       "      <td>1000.0</td>\n",
       "      <td>88.432000</td>\n",
       "      <td>3.025645</td>\n",
       "      <td>80.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>96.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Carneros</th>\n",
       "      <td>999.0</td>\n",
       "      <td>88.771772</td>\n",
       "      <td>2.927987</td>\n",
       "      <td>80.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>97.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Yakima Valley</th>\n",
       "      <td>997.0</td>\n",
       "      <td>88.789368</td>\n",
       "      <td>2.658201</td>\n",
       "      <td>81.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>95.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sta. Rita Hills</th>\n",
       "      <td>975.0</td>\n",
       "      <td>90.734359</td>\n",
       "      <td>2.659723</td>\n",
       "      <td>82.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>93.0</td>\n",
       "      <td>96.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dry Creek Valley</th>\n",
       "      <td>939.0</td>\n",
       "      <td>87.822151</td>\n",
       "      <td>2.855679</td>\n",
       "      <td>80.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>94.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sicilia</th>\n",
       "      <td>925.0</td>\n",
       "      <td>87.438919</td>\n",
       "      <td>2.136520</td>\n",
       "      <td>81.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>94.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           count       mean       std   min   25%   50%   75%  \\\n",
       "region_1                                                                        \n",
       "None                     21247.0  88.241022  2.949357  80.0  86.0  88.0  90.0   \n",
       "Napa Valley               4480.0  89.043750  3.188694  80.0  87.0  89.0  91.0   \n",
       "Columbia Valley (WA)      4124.0  88.718477  2.573591  80.0  87.0  89.0  91.0   \n",
       "Russian River Valley      3091.0  89.525720  3.196514  80.0  87.0  90.0  92.0   \n",
       "California                2629.0  85.680107  2.731097  80.0  84.0  85.0  87.0   \n",
       "Paso Robles               2350.0  87.892340  3.134678  80.0  86.0  88.0  90.0   \n",
       "Mendoza                   2301.0  86.501086  3.203480  80.0  84.0  86.0  89.0   \n",
       "Willamette Valley         2301.0  89.083877  2.671818  80.0  87.0  89.0  91.0   \n",
       "Alsace                    2163.0  89.472954  3.025422  80.0  87.0  89.0  92.0   \n",
       "Champagne                 1613.0  90.234966  2.702121  82.0  88.0  90.0  92.0   \n",
       "Barolo                    1599.0  90.836148  2.653436  83.0  89.0  91.0  93.0   \n",
       "Finger Lakes              1565.0  87.094569  2.131844  80.0  86.0  87.0  89.0   \n",
       "Sonoma Coast              1474.0  89.970149  2.999738  81.0  88.0  90.0  92.0   \n",
       "Brunello di Montalcino    1470.0  90.468027  2.560898  83.0  89.0  90.0  92.0   \n",
       "Rioja                     1469.0  87.713410  3.005937  80.0  86.0  88.0  90.0   \n",
       "Sonoma County             1246.0  87.392456  2.892879  80.0  85.0  87.0  90.0   \n",
       "Toscana                   1197.0  89.193818  2.772752  81.0  87.0  89.0  91.0   \n",
       "Walla Walla Valley (WA)   1066.0  90.284240  2.594482  83.0  88.0  91.0  92.0   \n",
       "Chianti Classico          1062.0  88.680791  2.363480  81.0  87.0  89.0  90.0   \n",
       "Santa Barbara County      1000.0  88.432000  3.025645  80.0  86.0  88.0  91.0   \n",
       "Carneros                   999.0  88.771772  2.927987  80.0  87.0  89.0  91.0   \n",
       "Yakima Valley              997.0  88.789368  2.658201  81.0  87.0  89.0  91.0   \n",
       "Sta. Rita Hills            975.0  90.734359  2.659723  82.0  89.0  91.0  93.0   \n",
       "Dry Creek Valley           939.0  87.822151  2.855679  80.0  86.0  88.0  90.0   \n",
       "Sicilia                    925.0  87.438919  2.136520  81.0  86.0  87.0  89.0   \n",
       "\n",
       "                           max  \n",
       "region_1                        \n",
       "None                     100.0  \n",
       "Napa Valley              100.0  \n",
       "Columbia Valley (WA)     100.0  \n",
       "Russian River Valley      98.0  \n",
       "California                97.0  \n",
       "Paso Robles               96.0  \n",
       "Mendoza                   97.0  \n",
       "Willamette Valley         97.0  \n",
       "Alsace                    97.0  \n",
       "Champagne                100.0  \n",
       "Barolo                    99.0  \n",
       "Finger Lakes              94.0  \n",
       "Sonoma Coast              99.0  \n",
       "Brunello di Montalcino   100.0  \n",
       "Rioja                     97.0  \n",
       "Sonoma County            100.0  \n",
       "Toscana                  100.0  \n",
       "Walla Walla Valley (WA)  100.0  \n",
       "Chianti Classico          96.0  \n",
       "Santa Barbara County      96.0  \n",
       "Carneros                  97.0  \n",
       "Yakima Valley             95.0  \n",
       "Sta. Rita Hills           96.0  \n",
       "Dry Creek Valley          94.0  \n",
       "Sicilia                   94.0  "
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wine.groupby('region_1').points.describe().sort_values(['count'], ascending=False).head(25)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Price stats for a bottle of wine by region_1\n",
    "The table below describes the count of wines, the average price, and price quartiles information per province. For example, Napa Valley has about 4475k wines that average a price of $43. The minimum price in Napa Valley is $10 while the maximum is $625."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "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>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>region_1</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>None</th>\n",
       "      <td>19575.0</td>\n",
       "      <td>27.214253</td>\n",
       "      <td>35.047968</td>\n",
       "      <td>4.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>1100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Napa Valley</th>\n",
       "      <td>4475.0</td>\n",
       "      <td>55.272179</td>\n",
       "      <td>43.827594</td>\n",
       "      <td>10.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>65.0</td>\n",
       "      <td>625.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Columbia Valley (WA)</th>\n",
       "      <td>4109.0</td>\n",
       "      <td>28.731321</td>\n",
       "      <td>16.376142</td>\n",
       "      <td>6.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>240.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Russian River Valley</th>\n",
       "      <td>3090.0</td>\n",
       "      <td>41.225566</td>\n",
       "      <td>16.617025</td>\n",
       "      <td>10.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>125.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>California</th>\n",
       "      <td>2627.0</td>\n",
       "      <td>16.090217</td>\n",
       "      <td>11.229409</td>\n",
       "      <td>4.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>17.5</td>\n",
       "      <td>175.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Paso Robles</th>\n",
       "      <td>2327.0</td>\n",
       "      <td>34.362699</td>\n",
       "      <td>22.127570</td>\n",
       "      <td>9.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>41.5</td>\n",
       "      <td>750.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Willamette Valley</th>\n",
       "      <td>2296.0</td>\n",
       "      <td>35.038328</td>\n",
       "      <td>18.063609</td>\n",
       "      <td>5.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>275.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mendoza</th>\n",
       "      <td>2275.0</td>\n",
       "      <td>22.831648</td>\n",
       "      <td>21.764799</td>\n",
       "      <td>4.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>225.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Alsace</th>\n",
       "      <td>1897.0</td>\n",
       "      <td>31.172905</td>\n",
       "      <td>17.701750</td>\n",
       "      <td>8.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>197.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Finger Lakes</th>\n",
       "      <td>1556.0</td>\n",
       "      <td>20.424165</td>\n",
       "      <td>8.340890</td>\n",
       "      <td>9.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sonoma Coast</th>\n",
       "      <td>1467.0</td>\n",
       "      <td>46.561691</td>\n",
       "      <td>18.476473</td>\n",
       "      <td>12.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>150.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rioja</th>\n",
       "      <td>1453.0</td>\n",
       "      <td>31.099794</td>\n",
       "      <td>32.990446</td>\n",
       "      <td>6.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>350.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Champagne</th>\n",
       "      <td>1383.0</td>\n",
       "      <td>79.461316</td>\n",
       "      <td>66.436349</td>\n",
       "      <td>10.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>84.5</td>\n",
       "      <td>800.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Barolo</th>\n",
       "      <td>1360.0</td>\n",
       "      <td>74.495588</td>\n",
       "      <td>37.390645</td>\n",
       "      <td>16.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>66.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>595.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sonoma County</th>\n",
       "      <td>1245.0</td>\n",
       "      <td>30.498795</td>\n",
       "      <td>34.666014</td>\n",
       "      <td>9.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>450.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brunello di Montalcino</th>\n",
       "      <td>1211.0</td>\n",
       "      <td>76.795211</td>\n",
       "      <td>54.763151</td>\n",
       "      <td>25.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>65.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>900.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Toscana</th>\n",
       "      <td>1079.0</td>\n",
       "      <td>54.943466</td>\n",
       "      <td>62.279530</td>\n",
       "      <td>6.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>65.0</td>\n",
       "      <td>625.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Walla Walla Valley (WA)</th>\n",
       "      <td>1061.0</td>\n",
       "      <td>44.941565</td>\n",
       "      <td>22.020967</td>\n",
       "      <td>14.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>175.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Carneros</th>\n",
       "      <td>999.0</td>\n",
       "      <td>38.759760</td>\n",
       "      <td>17.204428</td>\n",
       "      <td>10.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>120.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Santa Barbara County</th>\n",
       "      <td>994.0</td>\n",
       "      <td>30.921529</td>\n",
       "      <td>13.090739</td>\n",
       "      <td>10.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>95.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Yakima Valley</th>\n",
       "      <td>984.0</td>\n",
       "      <td>29.900407</td>\n",
       "      <td>15.603631</td>\n",
       "      <td>7.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>120.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sta. Rita Hills</th>\n",
       "      <td>971.0</td>\n",
       "      <td>46.733265</td>\n",
       "      <td>15.499715</td>\n",
       "      <td>12.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>55.0</td>\n",
       "      <td>150.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dry Creek Valley</th>\n",
       "      <td>936.0</td>\n",
       "      <td>30.679487</td>\n",
       "      <td>10.328396</td>\n",
       "      <td>10.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>75.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Chianti Classico</th>\n",
       "      <td>927.0</td>\n",
       "      <td>31.874865</td>\n",
       "      <td>21.288400</td>\n",
       "      <td>7.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>250.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Santa Ynez Valley</th>\n",
       "      <td>806.0</td>\n",
       "      <td>33.272953</td>\n",
       "      <td>14.680445</td>\n",
       "      <td>12.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>110.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           count       mean        std   min   25%   50%  \\\n",
       "region_1                                                                   \n",
       "None                     19575.0  27.214253  35.047968   4.0  13.0  19.0   \n",
       "Napa Valley               4475.0  55.272179  43.827594  10.0  28.0  44.0   \n",
       "Columbia Valley (WA)      4109.0  28.731321  16.376142   6.0  17.0  25.0   \n",
       "Russian River Valley      3090.0  41.225566  16.617025  10.0  28.0  40.0   \n",
       "California                2627.0  16.090217  11.229409   4.0  10.0  13.0   \n",
       "Paso Robles               2327.0  34.362699  22.127570   9.0  22.0  30.0   \n",
       "Willamette Valley         2296.0  35.038328  18.063609   5.0  20.0  30.0   \n",
       "Mendoza                   2275.0  22.831648  21.764799   4.0  12.0  15.0   \n",
       "Alsace                    1897.0  31.172905  17.701750   8.0  19.0  26.0   \n",
       "Finger Lakes              1556.0  20.424165   8.340890   9.0  15.0  18.0   \n",
       "Sonoma Coast              1467.0  46.561691  18.476473  12.0  33.0  45.0   \n",
       "Rioja                     1453.0  31.099794  32.990446   6.0  14.0  20.0   \n",
       "Champagne                 1383.0  79.461316  66.436349  10.0  49.0  60.0   \n",
       "Barolo                    1360.0  74.495588  37.390645  16.0  50.0  66.0   \n",
       "Sonoma County             1245.0  30.498795  34.666014   9.0  18.0  23.0   \n",
       "Brunello di Montalcino    1211.0  76.795211  54.763151  25.0  50.0  65.0   \n",
       "Toscana                   1079.0  54.943466  62.279530   6.0  20.0  37.0   \n",
       "Walla Walla Valley (WA)   1061.0  44.941565  22.020967  14.0  30.0  40.0   \n",
       "Carneros                   999.0  38.759760  17.204428  10.0  26.0  35.0   \n",
       "Santa Barbara County       994.0  30.921529  13.090739  10.0  21.0  28.0   \n",
       "Yakima Valley              984.0  29.900407  15.603631   7.0  19.0  26.0   \n",
       "Sta. Rita Hills            971.0  46.733265  15.499715  12.0  36.0  45.0   \n",
       "Dry Creek Valley           936.0  30.679487  10.328396  10.0  24.0  30.0   \n",
       "Chianti Classico           927.0  31.874865  21.288400   7.0  20.0  27.0   \n",
       "Santa Ynez Valley          806.0  33.272953  14.680445  12.0  22.0  30.0   \n",
       "\n",
       "                          75%     max  \n",
       "region_1                               \n",
       "None                     30.0  1100.0  \n",
       "Napa Valley              65.0   625.0  \n",
       "Columbia Valley (WA)     35.0   240.0  \n",
       "Russian River Valley     50.0   125.0  \n",
       "California               17.5   175.0  \n",
       "Paso Robles              41.5   750.0  \n",
       "Willamette Valley        45.0   275.0  \n",
       "Mendoza                  24.0   225.0  \n",
       "Alsace                   37.0   197.0  \n",
       "Finger Lakes             24.0   100.0  \n",
       "Sonoma Coast             58.0   150.0  \n",
       "Rioja                    35.0   350.0  \n",
       "Champagne                84.5   800.0  \n",
       "Barolo                   89.0   595.0  \n",
       "Sonoma County            35.0   450.0  \n",
       "Brunello di Montalcino   85.0   900.0  \n",
       "Toscana                  65.0   625.0  \n",
       "Walla Walla Valley (WA)  54.0   175.0  \n",
       "Carneros                 48.0   120.0  \n",
       "Santa Barbara County     37.0    95.0  \n",
       "Yakima Valley            36.0   120.0  \n",
       "Sta. Rita Hills          55.0   150.0  \n",
       "Dry Creek Valley         37.0    75.0  \n",
       "Chianti Classico         36.0   250.0  \n",
       "Santa Ynez Valley        40.0   110.0  "
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wine.groupby('region_1').price.describe().sort_values(['count'], ascending=False).head(25)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Show the average of price and point review of all wines in US with a point rating over 90\n",
    "We can leverage this function for multiple countries of interest."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "points    92.309150\n",
       "price     53.658814\n",
       "dtype: float64"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wine[(wine['country'] == 'US') & (wine['points'] > 90)].mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Are wine points and price correlated?\n",
    "It may appear that point reviews and price are somewhat positively correlated, however, there are some outliers."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "wine.plot(kind='scatter', x='points', y='price', figsize=(10,5), s=85);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### For each combination of country, region 1, and variety show me the summary stats\n",
    "So, for a Bonarda wine within Agrelo region of Argentina the average cost of a wine is $17.85. The chaepest is $15 and the most expensive is $23. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "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></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>region_1</th>\n",
       "      <th>variety</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"8\" valign=\"top\">Agrelo</th>\n",
       "      <th>Bonarda</th>\n",
       "      <td>7.0</td>\n",
       "      <td>17.857143</td>\n",
       "      <td>3.078342</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.00</td>\n",
       "      <td>18.0</td>\n",
       "      <td>19.50</td>\n",
       "      <td>23.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bordeaux-style Red Blend</th>\n",
       "      <td>2.0</td>\n",
       "      <td>34.500000</td>\n",
       "      <td>21.920310</td>\n",
       "      <td>19.0</td>\n",
       "      <td>26.75</td>\n",
       "      <td>34.5</td>\n",
       "      <td>42.25</td>\n",
       "      <td>50.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cabernet Franc</th>\n",
       "      <td>5.0</td>\n",
       "      <td>40.800000</td>\n",
       "      <td>44.308013</td>\n",
       "      <td>20.0</td>\n",
       "      <td>20.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>24.00</td>\n",
       "      <td>120.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cabernet Sauvignon</th>\n",
       "      <td>12.0</td>\n",
       "      <td>20.250000</td>\n",
       "      <td>6.716669</td>\n",
       "      <td>15.0</td>\n",
       "      <td>16.50</td>\n",
       "      <td>19.5</td>\n",
       "      <td>20.50</td>\n",
       "      <td>40.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Chardonnay</th>\n",
       "      <td>2.0</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>4.242641</td>\n",
       "      <td>12.0</td>\n",
       "      <td>13.50</td>\n",
       "      <td>15.0</td>\n",
       "      <td>16.50</td>\n",
       "      <td>18.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Malbec</th>\n",
       "      <td>18.0</td>\n",
       "      <td>32.944444</td>\n",
       "      <td>23.002486</td>\n",
       "      <td>15.0</td>\n",
       "      <td>18.25</td>\n",
       "      <td>20.0</td>\n",
       "      <td>35.00</td>\n",
       "      <td>80.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Petit Verdot</th>\n",
       "      <td>2.0</td>\n",
       "      <td>39.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>39.0</td>\n",
       "      <td>39.00</td>\n",
       "      <td>39.0</td>\n",
       "      <td>39.00</td>\n",
       "      <td>39.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Red Blend</th>\n",
       "      <td>2.0</td>\n",
       "      <td>59.500000</td>\n",
       "      <td>13.435029</td>\n",
       "      <td>50.0</td>\n",
       "      <td>54.75</td>\n",
       "      <td>59.5</td>\n",
       "      <td>64.25</td>\n",
       "      <td>69.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"6\" valign=\"top\">Alto Valle del Río Negro</th>\n",
       "      <th>Cabernet Franc</th>\n",
       "      <td>3.0</td>\n",
       "      <td>22.333333</td>\n",
       "      <td>5.773503</td>\n",
       "      <td>19.0</td>\n",
       "      <td>19.00</td>\n",
       "      <td>19.0</td>\n",
       "      <td>24.00</td>\n",
       "      <td>29.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Chardonnay</th>\n",
       "      <td>7.0</td>\n",
       "      <td>17.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>17.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>17.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>17.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Malbec</th>\n",
       "      <td>6.0</td>\n",
       "      <td>17.833333</td>\n",
       "      <td>6.145459</td>\n",
       "      <td>10.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>17.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>29.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pinot Noir</th>\n",
       "      <td>6.0</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>20.0</td>\n",
       "      <td>20.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>20.00</td>\n",
       "      <td>20.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Red Blend</th>\n",
       "      <td>1.0</td>\n",
       "      <td>25.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>25.0</td>\n",
       "      <td>25.00</td>\n",
       "      <td>25.0</td>\n",
       "      <td>25.00</td>\n",
       "      <td>25.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sauvignon Blanc</th>\n",
       "      <td>1.0</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12.0</td>\n",
       "      <td>12.00</td>\n",
       "      <td>12.0</td>\n",
       "      <td>12.00</td>\n",
       "      <td>12.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Altos de Mendoza</th>\n",
       "      <th>Malbec</th>\n",
       "      <td>1.0</td>\n",
       "      <td>35.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>35.0</td>\n",
       "      <td>35.00</td>\n",
       "      <td>35.0</td>\n",
       "      <td>35.00</td>\n",
       "      <td>35.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"14\" valign=\"top\">Argentina</th>\n",
       "      <th>Bonarda</th>\n",
       "      <td>3.0</td>\n",
       "      <td>16.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.50</td>\n",
       "      <td>16.0</td>\n",
       "      <td>16.50</td>\n",
       "      <td>17.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bordeaux-style Red Blend</th>\n",
       "      <td>1.0</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.00</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.00</td>\n",
       "      <td>50.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cabernet Sauvignon</th>\n",
       "      <td>4.0</td>\n",
       "      <td>13.250000</td>\n",
       "      <td>3.095696</td>\n",
       "      <td>9.0</td>\n",
       "      <td>12.00</td>\n",
       "      <td>14.0</td>\n",
       "      <td>15.25</td>\n",
       "      <td>16.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cabernet Sauvignon-Syrah</th>\n",
       "      <td>1.0</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.0</td>\n",
       "      <td>9.00</td>\n",
       "      <td>9.0</td>\n",
       "      <td>9.00</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Chardonnay</th>\n",
       "      <td>2.0</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>2.828427</td>\n",
       "      <td>9.0</td>\n",
       "      <td>10.00</td>\n",
       "      <td>11.0</td>\n",
       "      <td>12.00</td>\n",
       "      <td>13.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Malbec</th>\n",
       "      <td>10.0</td>\n",
       "      <td>30.700000</td>\n",
       "      <td>29.070986</td>\n",
       "      <td>9.0</td>\n",
       "      <td>13.50</td>\n",
       "      <td>17.0</td>\n",
       "      <td>36.50</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Malbec-Bonarda</th>\n",
       "      <td>1.0</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.0</td>\n",
       "      <td>8.00</td>\n",
       "      <td>8.0</td>\n",
       "      <td>8.00</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Malbec-Cabernet Sauvignon</th>\n",
       "      <td>1.0</td>\n",
       "      <td>39.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>39.0</td>\n",
       "      <td>39.00</td>\n",
       "      <td>39.0</td>\n",
       "      <td>39.00</td>\n",
       "      <td>39.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Moscato</th>\n",
       "      <td>1.0</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.0</td>\n",
       "      <td>8.00</td>\n",
       "      <td>8.0</td>\n",
       "      <td>8.00</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Red Blend</th>\n",
       "      <td>1.0</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>20.0</td>\n",
       "      <td>20.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>20.00</td>\n",
       "      <td>20.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sauvignon Blanc</th>\n",
       "      <td>1.0</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.00</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.00</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sparkling Blend</th>\n",
       "      <td>5.0</td>\n",
       "      <td>19.600000</td>\n",
       "      <td>11.523888</td>\n",
       "      <td>8.0</td>\n",
       "      <td>12.00</td>\n",
       "      <td>14.0</td>\n",
       "      <td>32.00</td>\n",
       "      <td>32.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Syrah</th>\n",
       "      <td>2.0</td>\n",
       "      <td>19.000000</td>\n",
       "      <td>8.485281</td>\n",
       "      <td>13.0</td>\n",
       "      <td>16.00</td>\n",
       "      <td>19.0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>25.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Torrontés</th>\n",
       "      <td>3.0</td>\n",
       "      <td>13.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>9.0</td>\n",
       "      <td>11.00</td>\n",
       "      <td>13.0</td>\n",
       "      <td>15.00</td>\n",
       "      <td>17.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Buenos Aires</th>\n",
       "      <th>Chardonnay</th>\n",
       "      <td>1.0</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>20.0</td>\n",
       "      <td>20.00</td>\n",
       "      <td>20.0</td>\n",
       "      <td>20.00</td>\n",
       "      <td>20.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"6\" valign=\"top\">Uco Valley</th>\n",
       "      <th>Syrah-Malbec</th>\n",
       "      <td>1.0</td>\n",
       "      <td>14.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14.0</td>\n",
       "      <td>14.00</td>\n",
       "      <td>14.0</td>\n",
       "      <td>14.00</td>\n",
       "      <td>14.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tempranillo</th>\n",
       "      <td>5.0</td>\n",
       "      <td>12.400000</td>\n",
       "      <td>1.949359</td>\n",
       "      <td>11.0</td>\n",
       "      <td>11.00</td>\n",
       "      <td>11.0</td>\n",
       "      <td>14.00</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tempranillo-Malbec</th>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Torrontés</th>\n",
       "      <td>4.0</td>\n",
       "      <td>13.250000</td>\n",
       "      <td>2.362908</td>\n",
       "      <td>10.0</td>\n",
       "      <td>12.25</td>\n",
       "      <td>14.0</td>\n",
       "      <td>15.00</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Viognier</th>\n",
       "      <td>5.0</td>\n",
       "      <td>15.400000</td>\n",
       "      <td>4.219005</td>\n",
       "      <td>12.0</td>\n",
       "      <td>12.00</td>\n",
       "      <td>13.0</td>\n",
       "      <td>20.00</td>\n",
       "      <td>20.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>White Blend</th>\n",
       "      <td>1.0</td>\n",
       "      <td>23.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>23.0</td>\n",
       "      <td>23.00</td>\n",
       "      <td>23.0</td>\n",
       "      <td>23.00</td>\n",
       "      <td>23.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"14\" valign=\"top\">Valle de Uco</th>\n",
       "      <th>Bordeaux-style Red Blend</th>\n",
       "      <td>3.0</td>\n",
       "      <td>80.000000</td>\n",
       "      <td>34.641016</td>\n",
       "      <td>60.0</td>\n",
       "      <td>60.00</td>\n",
       "      <td>60.0</td>\n",
       "      <td>90.00</td>\n",
       "      <td>120.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cabernet Franc</th>\n",
       "      <td>2.0</td>\n",
       "      <td>57.500000</td>\n",
       "      <td>24.748737</td>\n",
       "      <td>40.0</td>\n",
       "      <td>48.75</td>\n",
       "      <td>57.5</td>\n",
       "      <td>66.25</td>\n",
       "      <td>75.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cabernet Sauvignon</th>\n",
       "      <td>8.0</td>\n",
       "      <td>16.625000</td>\n",
       "      <td>3.502550</td>\n",
       "      <td>10.0</td>\n",
       "      <td>15.00</td>\n",
       "      <td>17.0</td>\n",
       "      <td>19.25</td>\n",
       "      <td>20.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Chardonnay</th>\n",
       "      <td>4.0</td>\n",
       "      <td>26.250000</td>\n",
       "      <td>15.924300</td>\n",
       "      <td>16.0</td>\n",
       "      <td>18.25</td>\n",
       "      <td>19.5</td>\n",
       "      <td>27.50</td>\n",
       "      <td>50.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Malbec</th>\n",
       "      <td>40.0</td>\n",
       "      <td>38.275000</td>\n",
       "      <td>23.697871</td>\n",
       "      <td>10.0</td>\n",
       "      <td>19.00</td>\n",
       "      <td>30.0</td>\n",
       "      <td>50.00</td>\n",
       "      <td>95.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Malbec-Cabernet Sauvignon</th>\n",
       "      <td>1.0</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.00</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.00</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Malbec-Petit Verdot</th>\n",
       "      <td>2.0</td>\n",
       "      <td>49.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>49.0</td>\n",
       "      <td>49.00</td>\n",
       "      <td>49.0</td>\n",
       "      <td>49.00</td>\n",
       "      <td>49.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pinot Gris</th>\n",
       "      <td>2.0</td>\n",
       "      <td>11.500000</td>\n",
       "      <td>0.707107</td>\n",
       "      <td>11.0</td>\n",
       "      <td>11.25</td>\n",
       "      <td>11.5</td>\n",
       "      <td>11.75</td>\n",
       "      <td>12.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Red Blend</th>\n",
       "      <td>11.0</td>\n",
       "      <td>36.272727</td>\n",
       "      <td>20.823501</td>\n",
       "      <td>13.0</td>\n",
       "      <td>24.00</td>\n",
       "      <td>29.0</td>\n",
       "      <td>45.50</td>\n",
       "      <td>75.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rosado</th>\n",
       "      <td>2.0</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>12.0</td>\n",
       "      <td>12.00</td>\n",
       "      <td>12.0</td>\n",
       "      <td>12.00</td>\n",
       "      <td>12.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rosé</th>\n",
       "      <td>2.0</td>\n",
       "      <td>22.000000</td>\n",
       "      <td>4.242641</td>\n",
       "      <td>19.0</td>\n",
       "      <td>20.50</td>\n",
       "      <td>22.0</td>\n",
       "      <td>23.50</td>\n",
       "      <td>25.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sauvignon Blanc</th>\n",
       "      <td>1.0</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11.0</td>\n",
       "      <td>11.00</td>\n",
       "      <td>11.0</td>\n",
       "      <td>11.00</td>\n",
       "      <td>11.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sparkling Blend</th>\n",
       "      <td>3.0</td>\n",
       "      <td>17.666667</td>\n",
       "      <td>2.309401</td>\n",
       "      <td>15.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>19.0</td>\n",
       "      <td>19.00</td>\n",
       "      <td>19.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Torrontés</th>\n",
       "      <td>2.0</td>\n",
       "      <td>19.500000</td>\n",
       "      <td>0.707107</td>\n",
       "      <td>19.0</td>\n",
       "      <td>19.25</td>\n",
       "      <td>19.5</td>\n",
       "      <td>19.75</td>\n",
       "      <td>20.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"7\" valign=\"top\">Vista Flores</th>\n",
       "      <th>Bordeaux-style Red Blend</th>\n",
       "      <td>2.0</td>\n",
       "      <td>25.000000</td>\n",
       "      <td>7.071068</td>\n",
       "      <td>20.0</td>\n",
       "      <td>22.50</td>\n",
       "      <td>25.0</td>\n",
       "      <td>27.50</td>\n",
       "      <td>30.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cabernet Sauvignon</th>\n",
       "      <td>3.0</td>\n",
       "      <td>15.333333</td>\n",
       "      <td>2.081666</td>\n",
       "      <td>13.0</td>\n",
       "      <td>14.50</td>\n",
       "      <td>16.0</td>\n",
       "      <td>16.50</td>\n",
       "      <td>17.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Malbec</th>\n",
       "      <td>5.0</td>\n",
       "      <td>19.400000</td>\n",
       "      <td>11.631853</td>\n",
       "      <td>13.0</td>\n",
       "      <td>13.00</td>\n",
       "      <td>14.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>40.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pinot Noir</th>\n",
       "      <td>2.0</td>\n",
       "      <td>17.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>17.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>17.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>17.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sparkling Blend</th>\n",
       "      <td>2.0</td>\n",
       "      <td>17.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>17.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>17.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>17.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Viognier</th>\n",
       "      <td>4.0</td>\n",
       "      <td>12.750000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>12.0</td>\n",
       "      <td>12.75</td>\n",
       "      <td>13.0</td>\n",
       "      <td>13.00</td>\n",
       "      <td>13.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>White Blend</th>\n",
       "      <td>2.0</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>30.0</td>\n",
       "      <td>30.00</td>\n",
       "      <td>30.0</td>\n",
       "      <td>30.00</td>\n",
       "      <td>30.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">Zonda Valley</th>\n",
       "      <th>Chardonnay</th>\n",
       "      <td>1.0</td>\n",
       "      <td>17.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>17.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>17.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>17.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Malbec</th>\n",
       "      <td>1.0</td>\n",
       "      <td>17.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>17.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>17.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>17.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Syrah</th>\n",
       "      <td>1.0</td>\n",
       "      <td>17.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>17.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>17.0</td>\n",
       "      <td>17.00</td>\n",
       "      <td>17.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>311 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                    count       mean  \\\n",
       "region_1                 variety                                       \n",
       "Agrelo                   Bonarda                      7.0  17.857143   \n",
       "                         Bordeaux-style Red Blend     2.0  34.500000   \n",
       "                         Cabernet Franc               5.0  40.800000   \n",
       "                         Cabernet Sauvignon          12.0  20.250000   \n",
       "                         Chardonnay                   2.0  15.000000   \n",
       "                         Malbec                      18.0  32.944444   \n",
       "                         Petit Verdot                 2.0  39.000000   \n",
       "                         Red Blend                    2.0  59.500000   \n",
       "Alto Valle del Río Negro Cabernet Franc               3.0  22.333333   \n",
       "                         Chardonnay                   7.0  17.000000   \n",
       "                         Malbec                       6.0  17.833333   \n",
       "                         Pinot Noir                   6.0  20.000000   \n",
       "                         Red Blend                    1.0  25.000000   \n",
       "                         Sauvignon Blanc              1.0  12.000000   \n",
       "Altos de Mendoza         Malbec                       1.0  35.000000   \n",
       "Argentina                Bonarda                      3.0  16.000000   \n",
       "                         Bordeaux-style Red Blend     1.0  50.000000   \n",
       "                         Cabernet Sauvignon           4.0  13.250000   \n",
       "                         Cabernet Sauvignon-Syrah     1.0   9.000000   \n",
       "                         Chardonnay                   2.0  11.000000   \n",
       "                         Malbec                      10.0  30.700000   \n",
       "                         Malbec-Bonarda               1.0   8.000000   \n",
       "                         Malbec-Cabernet Sauvignon    1.0  39.000000   \n",
       "                         Moscato                      1.0   8.000000   \n",
       "                         Red Blend                    1.0  20.000000   \n",
       "                         Sauvignon Blanc              1.0  15.000000   \n",
       "                         Sparkling Blend              5.0  19.600000   \n",
       "                         Syrah                        2.0  19.000000   \n",
       "                         Torrontés                    3.0  13.000000   \n",
       "Buenos Aires             Chardonnay                   1.0  20.000000   \n",
       "...                                                   ...        ...   \n",
       "Uco Valley               Syrah-Malbec                 1.0  14.000000   \n",
       "                         Tempranillo                  5.0  12.400000   \n",
       "                         Tempranillo-Malbec           0.0        NaN   \n",
       "                         Torrontés                    4.0  13.250000   \n",
       "                         Viognier                     5.0  15.400000   \n",
       "                         White Blend                  1.0  23.000000   \n",
       "Valle de Uco             Bordeaux-style Red Blend     3.0  80.000000   \n",
       "                         Cabernet Franc               2.0  57.500000   \n",
       "                         Cabernet Sauvignon           8.0  16.625000   \n",
       "                         Chardonnay                   4.0  26.250000   \n",
       "                         Malbec                      40.0  38.275000   \n",
       "                         Malbec-Cabernet Sauvignon    1.0  15.000000   \n",
       "                         Malbec-Petit Verdot          2.0  49.000000   \n",
       "                         Pinot Gris                   2.0  11.500000   \n",
       "                         Red Blend                   11.0  36.272727   \n",
       "                         Rosado                       2.0  12.000000   \n",
       "                         Rosé                         2.0  22.000000   \n",
       "                         Sauvignon Blanc              1.0  11.000000   \n",
       "                         Sparkling Blend              3.0  17.666667   \n",
       "                         Torrontés                    2.0  19.500000   \n",
       "Vista Flores             Bordeaux-style Red Blend     2.0  25.000000   \n",
       "                         Cabernet Sauvignon           3.0  15.333333   \n",
       "                         Malbec                       5.0  19.400000   \n",
       "                         Pinot Noir                   2.0  17.000000   \n",
       "                         Sparkling Blend              2.0  17.000000   \n",
       "                         Viognier                     4.0  12.750000   \n",
       "                         White Blend                  2.0  30.000000   \n",
       "Zonda Valley             Chardonnay                   1.0  17.000000   \n",
       "                         Malbec                       1.0  17.000000   \n",
       "                         Syrah                        1.0  17.000000   \n",
       "\n",
       "                                                          std   min    25%  \\\n",
       "region_1                 variety                                             \n",
       "Agrelo                   Bonarda                     3.078342  15.0  15.00   \n",
       "                         Bordeaux-style Red Blend   21.920310  19.0  26.75   \n",
       "                         Cabernet Franc             44.308013  20.0  20.00   \n",
       "                         Cabernet Sauvignon          6.716669  15.0  16.50   \n",
       "                         Chardonnay                  4.242641  12.0  13.50   \n",
       "                         Malbec                     23.002486  15.0  18.25   \n",
       "                         Petit Verdot                0.000000  39.0  39.00   \n",
       "                         Red Blend                  13.435029  50.0  54.75   \n",
       "Alto Valle del Río Negro Cabernet Franc              5.773503  19.0  19.00   \n",
       "                         Chardonnay                  0.000000  17.0  17.00   \n",
       "                         Malbec                      6.145459  10.0  17.00   \n",
       "                         Pinot Noir                  0.000000  20.0  20.00   \n",
       "                         Red Blend                        NaN  25.0  25.00   \n",
       "                         Sauvignon Blanc                  NaN  12.0  12.00   \n",
       "Altos de Mendoza         Malbec                           NaN  35.0  35.00   \n",
       "Argentina                Bonarda                     1.000000  15.0  15.50   \n",
       "                         Bordeaux-style Red Blend         NaN  50.0  50.00   \n",
       "                         Cabernet Sauvignon          3.095696   9.0  12.00   \n",
       "                         Cabernet Sauvignon-Syrah         NaN   9.0   9.00   \n",
       "                         Chardonnay                  2.828427   9.0  10.00   \n",
       "                         Malbec                     29.070986   9.0  13.50   \n",
       "                         Malbec-Bonarda                   NaN   8.0   8.00   \n",
       "                         Malbec-Cabernet Sauvignon        NaN  39.0  39.00   \n",
       "                         Moscato                          NaN   8.0   8.00   \n",
       "                         Red Blend                        NaN  20.0  20.00   \n",
       "                         Sauvignon Blanc                  NaN  15.0  15.00   \n",
       "                         Sparkling Blend            11.523888   8.0  12.00   \n",
       "                         Syrah                       8.485281  13.0  16.00   \n",
       "                         Torrontés                   4.000000   9.0  11.00   \n",
       "Buenos Aires             Chardonnay                       NaN  20.0  20.00   \n",
       "...                                                       ...   ...    ...   \n",
       "Uco Valley               Syrah-Malbec                     NaN  14.0  14.00   \n",
       "                         Tempranillo                 1.949359  11.0  11.00   \n",
       "                         Tempranillo-Malbec               NaN   NaN    NaN   \n",
       "                         Torrontés                   2.362908  10.0  12.25   \n",
       "                         Viognier                    4.219005  12.0  12.00   \n",
       "                         White Blend                      NaN  23.0  23.00   \n",
       "Valle de Uco             Bordeaux-style Red Blend   34.641016  60.0  60.00   \n",
       "                         Cabernet Franc             24.748737  40.0  48.75   \n",
       "                         Cabernet Sauvignon          3.502550  10.0  15.00   \n",
       "                         Chardonnay                 15.924300  16.0  18.25   \n",
       "                         Malbec                     23.697871  10.0  19.00   \n",
       "                         Malbec-Cabernet Sauvignon        NaN  15.0  15.00   \n",
       "                         Malbec-Petit Verdot         0.000000  49.0  49.00   \n",
       "                         Pinot Gris                  0.707107  11.0  11.25   \n",
       "                         Red Blend                  20.823501  13.0  24.00   \n",
       "                         Rosado                      0.000000  12.0  12.00   \n",
       "                         Rosé                        4.242641  19.0  20.50   \n",
       "                         Sauvignon Blanc                  NaN  11.0  11.00   \n",
       "                         Sparkling Blend             2.309401  15.0  17.00   \n",
       "                         Torrontés                   0.707107  19.0  19.25   \n",
       "Vista Flores             Bordeaux-style Red Blend    7.071068  20.0  22.50   \n",
       "                         Cabernet Sauvignon          2.081666  13.0  14.50   \n",
       "                         Malbec                     11.631853  13.0  13.00   \n",
       "                         Pinot Noir                  0.000000  17.0  17.00   \n",
       "                         Sparkling Blend             0.000000  17.0  17.00   \n",
       "                         Viognier                    0.500000  12.0  12.75   \n",
       "                         White Blend                 0.000000  30.0  30.00   \n",
       "Zonda Valley             Chardonnay                       NaN  17.0  17.00   \n",
       "                         Malbec                           NaN  17.0  17.00   \n",
       "                         Syrah                            NaN  17.0  17.00   \n",
       "\n",
       "                                                     50%    75%    max  \n",
       "region_1                 variety                                        \n",
       "Agrelo                   Bonarda                    18.0  19.50   23.0  \n",
       "                         Bordeaux-style Red Blend   34.5  42.25   50.0  \n",
       "                         Cabernet Franc             20.0  24.00  120.0  \n",
       "                         Cabernet Sauvignon         19.5  20.50   40.0  \n",
       "                         Chardonnay                 15.0  16.50   18.0  \n",
       "                         Malbec                     20.0  35.00   80.0  \n",
       "                         Petit Verdot               39.0  39.00   39.0  \n",
       "                         Red Blend                  59.5  64.25   69.0  \n",
       "Alto Valle del Río Negro Cabernet Franc             19.0  24.00   29.0  \n",
       "                         Chardonnay                 17.0  17.00   17.0  \n",
       "                         Malbec                     17.0  17.00   29.0  \n",
       "                         Pinot Noir                 20.0  20.00   20.0  \n",
       "                         Red Blend                  25.0  25.00   25.0  \n",
       "                         Sauvignon Blanc            12.0  12.00   12.0  \n",
       "Altos de Mendoza         Malbec                     35.0  35.00   35.0  \n",
       "Argentina                Bonarda                    16.0  16.50   17.0  \n",
       "                         Bordeaux-style Red Blend   50.0  50.00   50.0  \n",
       "                         Cabernet Sauvignon         14.0  15.25   16.0  \n",
       "                         Cabernet Sauvignon-Syrah    9.0   9.00    9.0  \n",
       "                         Chardonnay                 11.0  12.00   13.0  \n",
       "                         Malbec                     17.0  36.50  100.0  \n",
       "                         Malbec-Bonarda              8.0   8.00    8.0  \n",
       "                         Malbec-Cabernet Sauvignon  39.0  39.00   39.0  \n",
       "                         Moscato                     8.0   8.00    8.0  \n",
       "                         Red Blend                  20.0  20.00   20.0  \n",
       "                         Sauvignon Blanc            15.0  15.00   15.0  \n",
       "                         Sparkling Blend            14.0  32.00   32.0  \n",
       "                         Syrah                      19.0  22.00   25.0  \n",
       "                         Torrontés                  13.0  15.00   17.0  \n",
       "Buenos Aires             Chardonnay                 20.0  20.00   20.0  \n",
       "...                                                  ...    ...    ...  \n",
       "Uco Valley               Syrah-Malbec               14.0  14.00   14.0  \n",
       "                         Tempranillo                11.0  14.00   15.0  \n",
       "                         Tempranillo-Malbec          NaN    NaN    NaN  \n",
       "                         Torrontés                  14.0  15.00   15.0  \n",
       "                         Viognier                   13.0  20.00   20.0  \n",
       "                         White Blend                23.0  23.00   23.0  \n",
       "Valle de Uco             Bordeaux-style Red Blend   60.0  90.00  120.0  \n",
       "                         Cabernet Franc             57.5  66.25   75.0  \n",
       "                         Cabernet Sauvignon         17.0  19.25   20.0  \n",
       "                         Chardonnay                 19.5  27.50   50.0  \n",
       "                         Malbec                     30.0  50.00   95.0  \n",
       "                         Malbec-Cabernet Sauvignon  15.0  15.00   15.0  \n",
       "                         Malbec-Petit Verdot        49.0  49.00   49.0  \n",
       "                         Pinot Gris                 11.5  11.75   12.0  \n",
       "                         Red Blend                  29.0  45.50   75.0  \n",
       "                         Rosado                     12.0  12.00   12.0  \n",
       "                         Rosé                       22.0  23.50   25.0  \n",
       "                         Sauvignon Blanc            11.0  11.00   11.0  \n",
       "                         Sparkling Blend            19.0  19.00   19.0  \n",
       "                         Torrontés                  19.5  19.75   20.0  \n",
       "Vista Flores             Bordeaux-style Red Blend   25.0  27.50   30.0  \n",
       "                         Cabernet Sauvignon         16.0  16.50   17.0  \n",
       "                         Malbec                     14.0  17.00   40.0  \n",
       "                         Pinot Noir                 17.0  17.00   17.0  \n",
       "                         Sparkling Blend            17.0  17.00   17.0  \n",
       "                         Viognier                   13.0  13.00   13.0  \n",
       "                         White Blend                30.0  30.00   30.0  \n",
       "Zonda Valley             Chardonnay                 17.0  17.00   17.0  \n",
       "                         Malbec                     17.0  17.00   17.0  \n",
       "                         Syrah                      17.0  17.00   17.0  \n",
       "\n",
       "[311 rows x 8 columns]"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wine[wine['country'] == 'Argentina'].groupby(['region_1','variety'])['price'].describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Reviewing top 10 lists for top 3 Countries\n",
    "This function can be leveraged for all countries, if needed.\n",
    "\n",
    "#### US\n",
    "In the US, Pinot Noir is the most popular variety of wine."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "wine[wine['country'] == 'US']['variety'].value_counts().head(10).plot(kind='bar');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Napa Valley is the top region in the US that produces the most wine."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "wine[wine['country'] == 'US']['region_1'].value_counts().head(10).plot(kind='bar');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Most of all the wine in the US is produced in the California."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "wine[wine['country'] == 'US']['province'].value_counts().head(10).plot(kind='bar');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### France\n",
    "In France, Bordeaux-style Red Blends are the most popular variety of wine."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "wine[wine['country'] == 'France']['variety'].value_counts().head(10).plot(kind='bar');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Alsace is the top region in France that produces the most wine."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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uSa03wozL7+fdlDe61YHVgF/Y/kvjGFaVtC7wKuD9jfseeDtwnKRBSZp1gT1bB2F7v9Z9wmQmgCskvQaYIWlj4K2Uq5zWDqLc5q8v6WuUq6u/axmA7Y9LeiHwB0pl1X+1fXrLGKprgbMlncRQErTd+nb/cOA6ynDDuZIeR/lv09K4/H5eCHwH2BJ4JHC4pN1t794whg9QqgKcZ/tCSY8Hftawf2q/T6b8fQi42vbdLWMAkPQlphTGrPG9bqT9TtpO4DqD/35gp9p0KvBB2/+vg1geCWxD+cU633bTMrN1xc8Ng397vSNZx/Z1jeM4aLp22x9oGcd0JK1q+56G/Y3F76ek2bbnTmnb2/bRjfqfAbzV9r+36G8psWxLGYa774LY9lcax/DKoYerUebvrrf91pH2O2kJYJxIeizwOBb+xTq3Yf9zgW3r4TvUAnw/tL1lqximxLMm4OFJt0b9vtb2VyW9c7rnW92J1De9j9huOvG8mFimXYVl+1cNYzjL9o6t+ltMDEcDG1Em5u+tzR71G+/S1KWp37f9vFH2M3FDQJJOB/aw/fv6eC3gGNsvahzHv1HGEq8EBmOrBpolAGDVwZs/gO27ahJoStJTgaMpE11I+h2wT4NCgAODye/mK6CG2b63TjKOg5Mov4+iXHFuSDl86SkNY/iRpM8C36SuVAOwfXHDGGZTFgeM25XwxpRFCiM1cQkAWHvw5g9g+zZJj+ogjpdTVr60nvgddrOkl9k+EUDSrnRz2tERwDttn1Xj2IEyGb1ti85tH14/dz7kBPykLvs8joXf9L7dMgjbTxt+XFfCvLFlDCz4/3/wUJspK2FauQJ4NHBDwz4XIekOFiRkA7+l7OEZqUlMAH+RtMHgVrZO9HWR3a+lbLzqMgG8CfhavcoSZTXOPh3E8eDBmz+A7bNbLkmV9JklPd/4dn94ud99IQBNE8BUti+W1HRosOvhn2pt4KeSLmDhBQovaxmE7U7uTicxAbwfOE/SOfXxc1lwxnBLdwKXSDqDhX+xmr3Z2P45sI2kh1Dme+5o1fcU10r6F8owEMBrgV807P+ihn0tVp0DuGxMJj6H50NWAbYAbm4cw8Moq+WeW5vOAQ623XLJ8JyGfS1W3QX8t8CGtg+pczSPtn3BSPsdv6GvFSdpbRasvvnv1qtvagz7Ttdu+6iGMTwIeCWLrnA4eHHfM6I41qIs+duO8v/kXGCO7dtaxjEUz0MpE33NE+I4THzWOIZXZt1DWR57fMvVSJKOpwzBDP4m9gaeYXvkO2DHjaTDKHOFz7O9Sf2bOW3UCzYmNQGsRZlEWW3Q1nL1zbiQdAplA9ZFLFjhgO1PdBZUhyTNppToWJOSiH4PvM52szsESR8CHka3E59jQdIltjdbWtuIY9gGOBTYBHgg5aTCP9puWidK0sW2t5D0E9ub17ZLbT9jlP1O3BCQpNdTSg+sR1natQ3w37SdWELS5Sw693A7MJey7vuWBmGsZ3vnBv1MS9KnbL9d0neZfpNL03FW4EjgH2z/oMa3HSUhtCxLMQ4Tn0iaCfwzZdXP8IVSyzj+JGk72+fVmJ5N+zIMn6WcTX4cZUXQPpSLx9burkOEg8oBM1mwenBkJi4BUN78t6RsvNqx7vLrYvXHf1Guur9eH7+actV5O/BlSq2PUfuRpKfZvrxBX9MZjPl/vKP+p7pj8OYPYPu8uvqimXEY/qm+RrkLeQllscC+NJ4DqP1+pc4FCLiVxrvlAWzPkzTDpSrnlyR1sTP7M8AJwKPqXeLuwP8adacTNwQk6ULbW0q6BNja9p9b31bWOH5o+9nTtUm6fOoyvBHF8FPgCZQJ1z9Tl5h1VIitM0PFvvamVHr8BuVKa0/gNtvN6tBIWgf438BjbO+iUpb5Wba/2CqGGsdFtp8p6bLB74Okc2xv3zKO2u9DAVwKw7Xu+1xKAbr/pCy9vAH4u1EPvSwmlicDz6f8nZ5h+6pR9zmJdwDzJT0c+D/A6ZJuo1Q6bO0hkra2/WMASVsBD6nPtSo9sEujfqa1mGGw+zRMRFPnPIYnQFtfAX2ZMuw0SDr/Q7kSb5oAqFVqgRsk/Q3lb2S9lgFMXaSgWiCv8SKFvSnj/m8B3kGpkPrKJX7HSiTpobb/oFIS+ybKxcnguUfYvnWk/U/aHcAwSdtTJtxOGd4R26jvLSljzg+hZPQ/AK+n7Az+G9vHNopjO2Bj21+q44oPsd1kCWbdg7FYtn/ZIo5xMnSHOjzZ18Ud6kuAH1De8A4FHgp8YLBpsFEMvV+kIOl7tl8i6RcsfDEyuFt//Cj7n7g7AJWyy/PrDlxRri7WAJomANsXAk8bjG8O704GWr35H0SZ2HoS5apzcCJYk7rv4/gGX692p058trzi/KNKkcDBZN82dFAq2/bgQJ7bga7mJTpbpDAud6f1zV/A9i3rMA1MXAIAjgdmS3oC5bb6RMpE7ItbBzL8ZtPR7e1uwObAxbXv61UKsjUh6Tzb2w1tc7/vqRJO86V2n6dcDOxIGfPdHRjpRptpvJPyO7mRpB8CM2scTUl6InAYpTrsU1WOY3yZ7Zan1nW5SKHp8axLYtuSTgCa14maxATwF9v3SNoN+JTtQyX9pHUQY/Jmc1f95erkRDDb29XPnRZhG7Kt7afXic8PSPoEjUsw1JIL27Og/vw17qD+PKUW07spZyRg+zJJX6fBsaVDV9+rAvtJupbGixSmuzutG0hvcTfj4udL2rKOHDQziQngbkl7UZa1DZZaPqCDODp/s2F8TgQbbM5bn4V3JLfe/DRYY36npMdQavJs2DIASW8GvuZaCVXlMPS9bP9HyziANWxfoIVPJmu1OKHzq+869PYRytLTQyhLltcGVpG0j+1TGoe0I/AmSddRNgg2SYaTmAD2o6wv/pDtX6gcivLVDuLo/M3GY3IimKRDKOu7r2Xh0thNNz8B36srxD5GGRYz5e6spTfY/tzggUu12jcArRPA7+p82eDucHcaVcScevWtUq13tcW8fFQ+C7yPskjkTGAX2+fXpZjfoJzm11InK/YmehVQl1SKnx1KWdf7Ocof2hds/2vDGN4BHGd7fqs+FxPHNcDTWq/EWpK6BHE1ty08hqTLKPVuBm+8gwJxLevwo3L84hGUncm3UfaKvNYNT4uT9DLKEt3HUJZAPg64qsV/i+GVV5Kusr3J0HP3rdBqqYsVexNzB7CEWX1R5gWabuywfUj98nhJ36ODNxvK0r5TJd0KHAN8y/aNjWOAUvDr4ZQ/8k5pyvF/klof/3cqZWju85Tf1zfR/moT29cCL6jzQqu4m0qxh1BKtXzf9uaSdgT2atT3cJmFqeUnmlwVS3rK0FBgJyv2JuYOYDFrzkXZ3PI+201XAUlaDfgHSgVMA+cBh7mbs4mfTtn1+krKEtkXNO5/NuUA8ivosOa6xuD4P5Wj/t7Igh2fpwH/WcsQtOh/2mMxB9zoeMway1zbsyVdCmxu+y+SLrC9VYO+72XBWPvqlPLt1Mer2R75vKGkFwPPtX2gSuWCzYGLh/aH3LdLe1Qm5g5geFxR0mbAa4BXUW5tj+8gpK8Ad1CGgaBc2RwN7NFBLDdRtrnfAnRxOtpRwL8Bl9OgwNUSdH78n+2/UJZfHtZRCIMVWU+i1MwabPx6KW2PKwX4vcpZFedSDi66iUYT0bZntOhnKTGcXBMRdLRib5LuAJ5IKbi2F+WN7pvAu2wvcTfqCONZpJTrdG0jjuHvKVf+M4FvAd+0/dNW/Q/F0UmNmWniOA54q+3Ojv9TqXg5hzLevSqNdnxOE8dpwCsHQz91f8hxLTZm1T0661DuxP5EOZDmbyn/TU5yw/Lc40LSuyhVSF8IfJiyYu/rtg9d4jeuoIm5AwCupmxtf6nteXDfJGhXfiJpG9vn11i2Bn7YOIbHAW+3fUnjfqe6SNKHKVebw0NATZaBakE56jXp/vi/L1JqzixU/qADG7Dw7vi7KHMjLXyKMiw7OA/hL8BRdahwDm0q5Y6VKSv2nkijFXuTlABeSbkDOKvWGDmGcnXVla2BfSQNtndvAFw1mKxutNnlQEnPkPSW2vQD25eOut9pDFZUbDPU1nIZ6ImUK84fTGnfHvhNoxgGbrf9X437nM7RwAV1B6opu8ZbnVY3y/ZlUxttz5U0q1EM4+hyynyE69cjNzFDQAN17OzllKGg51F+qU+wfVrjODovhCbprZTzkAcb0HYDjhj1beW4qauw3jf1TadecR5ku9kVp6SPUKpPfpsO7oamxLIF8Jz68FzbTXbMS5pn+wn397kRxbLp1GFRSTvYPrtVDLXP1wP/StmTIMrFycG2jxxpv5OWAIaplFjdA9jTbU86GvTf6e7Xuub8WYNb7Zoc/7vF3Uft71O2316/fpvtTw8992Xbf9cojitsP3UxzzU5m2Gov7OmaXbL38+6Eumyxf03adD/N4AzbX9hSvv+wE6292wYyxWUu6GPUjajfRSYbftZrWKocVxDqR5wS338SOBHtp80yn4naQhoES61tA+vH00N7X79OQvWFbfe/SoWHme+lwbDYpI2r1eTzx1q3hf49NDjlofSLGmX6erNomA8TgSryy0vlbSBO6hACbwdOEHS31LmQqCs0Hog5S61pa0pK9R+RJkj+hqNquVOMZ+yanDgDuDXo+50ohNAx14FbNTx7tcvAT+u47xQhsZaHDzybknHTGnrcj7mQklvWMwVZ/MVJ+q+JDXAusCVdUJ8+HD6kU+I182I29aNX4O7kJNsnznqvqdxN2Ul0uqU/x+/qEt1W/sN5W/1O5QLxV0pczTvhNHtz0gCGJ3Od7/a/qSksymb0QTs12Kc1/Zr6vDbjDoMtgqlyNZaLEgELddhj80Vp8ajSix0c072QmyfBUw3JNbShZRNilsCjwQOl7S77dYlun9ePwa+Uz+PtJLuRM8BdKnr3a9dj/PWGK6jLPGb7uq/i7Xvw1ecV3ZxxTnY3Tn0+SHAt23v1EEs61De+AAusN15qY7WJM22PXdK2962j+4qppZyBzA6ne5+HYNxXmzP6qLfxRmTK86pVWJvpXGVWABJr6JURT2bkqAPlfRu299qHUvHbpK0wZS2c1oHURcHLHI1PurFAUkAo/M725/pOIbOxnkXR9Ic23O66n8MDEpSf5QFw1GtS1JDOZR+y8FVf60++X3KjvE+OYnyxivKHMCGwDWUOZqW3jX09WqUfU0jL4uRBDA6ne5+rTof553Gyyi7PXtF0pbAr12rxNahn8spO9j/vYOQVpky5HMLZa6mV6YuAa57I97YQRxTFyP8UNLI70SSAEan092vkl4OPAG43PapLfpcRl2uBurS4cALACQ9l3Ia1T8Cm1Hq8reedDxF0qmUw0+g1Iw6uXEMY8flyM4tl/7KlasumhhYhXI+8KNH3m8mgSePpP+g3ML+iFJ2+LtecD5BF/E82/YP69er1PmJ+9r6YLgQoKTPATcPhsI0dDhJ45hewYIVYufaPmEp3zJxtHB57FWALYBH2n5R4zh+wYKhqHsoVYwPtn3eSPtNAhidrtZ7192Nz7B9r6Q1KDWAnjnqfpcQz8W2t1ha2ySr/082s32PpKuBA2yfO3iu49VaXR6G3imVg1gG7gGuA453B+d2dCFDQCPS8Xrvu1wPGLF9p6ROhl0kPYty5ODMKVdaD6XtPoBx8A3gHEm/o6wE+gHcVxq52UlxGr/D0Dtlu9N5sqG5od/Wx/tQJoB/Ccyp1QxG138Pk34TXa73lnQnMG/wkHIK1jwW1J5vVQtoe2AHyrGHnx966g7KsNTPWsQxLuqb77rAaUP1mZ5IOfu1VWnsuSw4DP0IphyG7g7Owu1SXf30zyx6p95qru5i4AW2b61zQ8ewYG5ok1FvSMsdwOhMXe99C+3We2+y9JeMnu1zKFe9X25R/XTcuZ4NMaXtfxqHseqgMq6kgwcx2b66oxvFrn2NcnjUSygXKvsCNzfsf8bQVf6elGq9x1POEh/5OR5JAKMzWO/9MeBiygRPk/XeY/hm+yBJRzB0GDu0u8qKhXR+GPqYeaTtL9ZqtYMLlpYbwWZIWtX2PZQFGwcMPTfy9+ckgBEZWnVzvEo9+tVsNxvrHTPHUYaA/pNuT8EKeIakP1APQ69fw4KNUH07N3cVAAAHn0lEQVRzd/18Q120cT2wXsP+O50byhzACEnalkWver/SWUAdkXRRl6uQIhZH0ksob7rrA4dSFih8wPaJDWPobG4oCWBEJB1NmXy9hAVXvbb91sZxrA5sYPualv1OiWEOpSrqCSy8K3qkKxwiYsmSAEZE0lXApl2urZb0UuDjwANtbyhpM8rmkqa1gOoml6maVwONmKpeaR8GrGP7qZKeDrzM9gc7Dq2J3tX+aOgKGmzlXoo5wFbA7wFsX0IZkmrK9obTfOTNP8bBF4D3UucCXM6NfnWnETWUSeCVTNJ3Kasp1gR+WitxNj8PoLrH9u1dLe+T9DzbZ9aSA4uw/e3p2iMaWsP2BVP+RkZehXMqdXQ4fRLAyncisA51Nn/I9pRj31q6QtJrKEvNNgbeSqkP1Mr2wJnAS6d5zkASQHTtd5I2oi6BlbQ7cEMHcRxb5w0XOpweGOnh9JkDWMnqks/31VvJ4fbZwEG2p3szHFUsa1Dqvu9EWeZ3KnBIX+qcRCyNpMdTdkRvC9xGKcL2WtvXNY7jwZQDpJ7JgsPp/80jPp84dwAr36ypb/4AtudKmtUyENt3UhLA+1v2O52uCuNFLInta4EX1DfgVWzf0VEonRxOnwSw8i1pM83qLQIYmoeYVgergMblIPQIYJEy0MPtANj+ZNOAOjqcPglg5btQ0htsf2G4UdL+LDgCcNQ+Xj+/grIS6av18V6UcretbTtUGO8Dkj5Bxv+jW2vWz0+ivOkONn69FDi3g3j294LD6X8L7Cpp71F3mjmAlUzSOpQNT3ex4A1/NvBAYLdB2ddGsZxr+7lLa2sQx49tby3pfEpSupVyUtnGLeOImErSacArB0M/ktYEjrO9c+M4ph5MD4DtX42y39wBrGS2bwS2lbQjMDjk4yTbZ3YQzkxJj6/jnEjaEJjZQRzjchB6xFQbUC7WBu6ig70ydHQ4fRLAiNg+Czir4zDeAZwt6dr6eBYLVxscKY3fQegRUx0NXCDpBMob8G7AUa2DcEeH02cIaMJJehDw5Prwatt/XtLrV3LfnR52EbEs6pvtc+rDc23/pMt4Blocm5oEECMzjgehRwxIWgW4rMvzmIdi6eRw+tQCilGaIWkwzPh8yq7ggQw/RqfqOvtLFzcB29iaQx8PoswJ7DrqTvNHGKM0FgehRyzBusCVtWbXHweNrffKdHU4fYaAJpikZwOX2P6jpNdSbis/3fLIyHE4CD1icSRtP117PR6yZRydHE6fBDDBJF0GPAN4OmW1wxeBV9ie9pc+oo/q3p0t68MLbN/UQQynUQ6nfxdDh9Pbfs8o+80cwGS7px5Isyvlyv/TLNgBGdF7kl5FKUuyB/Aq4Me1Imhrj7T9ReBu2+fYfh2wzag7zRzAZLtD0nuBvYHnSJoBPKDjmCLGyfuBLQdX/XUo5vvAtxrH0cnh9EkAk21P4DXA62z/tq52+FjHMUWMk1WmDPncQjcjIx+U9DDgn1hwOP07Rt1p5gAmnKTHARvb/n49H2BGhyVvI8aKpI9R5si+UZv2pOwNGOnY+7hIAphgkt5AKf3wCNsb1VPBPm/7+R2HFjE26pGl21Hq8Jxr+4QOYujkcPokgAkm6RLKofA/tr15bbt8at2RiABJawO3uIM3RUnnAO8GDh/6W71i1LuUswposv3Z9n2VDuuu3GT86D1J20g6W9K3JW0u6QrgCuBGSU1LQVdr2J56SNLID6fPJPBkO0fS+4DVJb0Q+Afgux3HFDEOPgu8D3gYpUTJLrbPl/RkynzAKY3j6eRw+gwBTbBa7Gp/hg6Fn3pSWUQfDRcjlHSV7U2GnvvJYBimYTydHE6fO4DJ9o9189d9b/qS3lbbIvps+MD1P015rvlVcVeH0+cOYIJNV0+8i6ubiHEj6V5K8TcBqwN3Dp4CVrPdZMPk4g6nHxj14fS5A5hAkvaibADbUNKJQ089lLLRJaLXbM/oOoaq08Ppcwcwgermrw2BDwMHDj11B2WTy8hXF0TEsuvqcPrcAUygWu75l8CzplQ6vCpv/hFjqZPD6bMPYAJJekz9vAfjUekwIpZscDj9HEkHAT+mweH0GQKaMJK2Avaz/feSLgVeOLXS4eCc3ogYH10cTp8hoMkzC7imfj0ulQ4jYjGmHE7f9JS8JIAJY/tYSS+qD0+RdCoLVzr8r24ii4jp2P6LpEslbWD7Vy37zhDQhBuHSocRsWSSzqQs1mh6OH0SwASS9ARKWdkfTml/LvAb2z/vJrKImE5Xh9NnPHgyfYqy5n+qO+tzETFG6hv91ZSNYWtSlmyP9M0fkgAm1Szbl01ttD2XBmuLI+L+6epw+kwCT6bVlvDc6s2iiIhl1cnh9LkDmEwX1uMgFyJpf+CiDuKJiCXrZMl2JoEnUC3/cAJlO/ngDX828EBgN9u/7Sq2iFhUV4fTJwFMMEk7AoMzRa+0fWaX8UTE4nWxZDsJICJijLQ8nD5zABERHen6cPrcAUREdETSXBYcTn8EUw6nH/XpfbkDiIjozqq2T7N9HPBb2+cD2L66RedJABER3en0cPoMAUVEdKTrw+mTACIieipDQBERPZUEEBHRU0kAERE9lQQQEdFTSQARET31/wFhqOiqUDWSHQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "wine[wine['country'] == 'France']['region_1'].value_counts().head(10).plot(kind='bar');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Most of all the wine in France is produced in the Bordeaux."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "wine[wine['country'] == 'France']['province'].value_counts().head(10).plot(kind='bar');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Italy\n",
    "In Italy, Red Blends are the most popular variety of wine."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "wine[wine['country'] == 'Italy']['variety'].value_counts().head(10).plot(kind='bar');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Barolo is the top region in Italy that produces the most wine."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "wine[wine['country'] == 'Italy']['region_1'].value_counts().head(10).plot(kind='bar');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Most of all the wine in Italy is produced in the Tuscany."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "wine[wine['country'] == 'Italy']['province'].value_counts().head(10).plot(kind='bar');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}