Taste in Alcohol.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# People's Taste in Alcohol\n",
    "## An exploration of beer and wine ratings\n",
    "\n",
    "## Author: Yordan Darakchiev"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Abstract\n",
    "TODO"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Getting data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "beer_reviews = pd.read_csv(\"data/beer_reviews.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "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>brewery_id</th>\n",
       "      <th>brewery_name</th>\n",
       "      <th>review_time</th>\n",
       "      <th>review_overall</th>\n",
       "      <th>review_aroma</th>\n",
       "      <th>review_appearance</th>\n",
       "      <th>review_profilename</th>\n",
       "      <th>beer_style</th>\n",
       "      <th>review_palate</th>\n",
       "      <th>review_taste</th>\n",
       "      <th>beer_name</th>\n",
       "      <th>beer_abv</th>\n",
       "      <th>beer_beerid</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10325</td>\n",
       "      <td>Vecchio Birraio</td>\n",
       "      <td>1234817823</td>\n",
       "      <td>1.5</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>stcules</td>\n",
       "      <td>Hefeweizen</td>\n",
       "      <td>1.5</td>\n",
       "      <td>1.5</td>\n",
       "      <td>Sausa Weizen</td>\n",
       "      <td>5.0</td>\n",
       "      <td>47986</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10325</td>\n",
       "      <td>Vecchio Birraio</td>\n",
       "      <td>1235915097</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>3.0</td>\n",
       "      <td>stcules</td>\n",
       "      <td>English Strong Ale</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Red Moon</td>\n",
       "      <td>6.2</td>\n",
       "      <td>48213</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>10325</td>\n",
       "      <td>Vecchio Birraio</td>\n",
       "      <td>1235916604</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>3.0</td>\n",
       "      <td>stcules</td>\n",
       "      <td>Foreign / Export Stout</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Black Horse Black Beer</td>\n",
       "      <td>6.5</td>\n",
       "      <td>48215</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>10325</td>\n",
       "      <td>Vecchio Birraio</td>\n",
       "      <td>1234725145</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>stcules</td>\n",
       "      <td>German Pilsener</td>\n",
       "      <td>2.5</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Sausa Pils</td>\n",
       "      <td>5.0</td>\n",
       "      <td>47969</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1075</td>\n",
       "      <td>Caldera Brewing Company</td>\n",
       "      <td>1293735206</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.0</td>\n",
       "      <td>johnmichaelsen</td>\n",
       "      <td>American Double / Imperial IPA</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.5</td>\n",
       "      <td>Cauldron DIPA</td>\n",
       "      <td>7.7</td>\n",
       "      <td>64883</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   brewery_id             brewery_name  review_time  review_overall  \\\n",
       "0       10325          Vecchio Birraio   1234817823             1.5   \n",
       "1       10325          Vecchio Birraio   1235915097             3.0   \n",
       "2       10325          Vecchio Birraio   1235916604             3.0   \n",
       "3       10325          Vecchio Birraio   1234725145             3.0   \n",
       "4        1075  Caldera Brewing Company   1293735206             4.0   \n",
       "\n",
       "   review_aroma  review_appearance review_profilename  \\\n",
       "0           2.0                2.5            stcules   \n",
       "1           2.5                3.0            stcules   \n",
       "2           2.5                3.0            stcules   \n",
       "3           3.0                3.5            stcules   \n",
       "4           4.5                4.0     johnmichaelsen   \n",
       "\n",
       "                       beer_style  review_palate  review_taste  \\\n",
       "0                      Hefeweizen            1.5           1.5   \n",
       "1              English Strong Ale            3.0           3.0   \n",
       "2          Foreign / Export Stout            3.0           3.0   \n",
       "3                 German Pilsener            2.5           3.0   \n",
       "4  American Double / Imperial IPA            4.0           4.5   \n",
       "\n",
       "                beer_name  beer_abv  beer_beerid  \n",
       "0            Sausa Weizen       5.0        47986  \n",
       "1                Red Moon       6.2        48213  \n",
       "2  Black Horse Black Beer       6.5        48215  \n",
       "3              Sausa Pils       5.0        47969  \n",
       "4           Cauldron DIPA       7.7        64883  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "beer_reviews.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1586614, 13)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "beer_reviews.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "beer_reviews = beer_reviews[[\"beer_beerid\", \"brewery_id\", \"brewery_name\",\n",
    "                            \"review_profilename\", \"review_time\",\n",
    "                            \"beer_style\", \"beer_name\", \"beer_abv\",\n",
    "                            \"review_overall\", \"review_aroma\", \"review_appearance\", \"review_palate\", \"review_taste\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "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>beer_beerid</th>\n",
       "      <th>brewery_id</th>\n",
       "      <th>brewery_name</th>\n",
       "      <th>review_profilename</th>\n",
       "      <th>review_time</th>\n",
       "      <th>beer_style</th>\n",
       "      <th>beer_name</th>\n",
       "      <th>beer_abv</th>\n",
       "      <th>review_overall</th>\n",
       "      <th>review_aroma</th>\n",
       "      <th>review_appearance</th>\n",
       "      <th>review_palate</th>\n",
       "      <th>review_taste</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>47986</td>\n",
       "      <td>10325</td>\n",
       "      <td>Vecchio Birraio</td>\n",
       "      <td>stcules</td>\n",
       "      <td>1234817823</td>\n",
       "      <td>Hefeweizen</td>\n",
       "      <td>Sausa Weizen</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.5</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>1.5</td>\n",
       "      <td>1.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>48213</td>\n",
       "      <td>10325</td>\n",
       "      <td>Vecchio Birraio</td>\n",
       "      <td>stcules</td>\n",
       "      <td>1235915097</td>\n",
       "      <td>English Strong Ale</td>\n",
       "      <td>Red Moon</td>\n",
       "      <td>6.2</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>48215</td>\n",
       "      <td>10325</td>\n",
       "      <td>Vecchio Birraio</td>\n",
       "      <td>stcules</td>\n",
       "      <td>1235916604</td>\n",
       "      <td>Foreign / Export Stout</td>\n",
       "      <td>Black Horse Black Beer</td>\n",
       "      <td>6.5</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>47969</td>\n",
       "      <td>10325</td>\n",
       "      <td>Vecchio Birraio</td>\n",
       "      <td>stcules</td>\n",
       "      <td>1234725145</td>\n",
       "      <td>German Pilsener</td>\n",
       "      <td>Sausa Pils</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>2.5</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>64883</td>\n",
       "      <td>1075</td>\n",
       "      <td>Caldera Brewing Company</td>\n",
       "      <td>johnmichaelsen</td>\n",
       "      <td>1293735206</td>\n",
       "      <td>American Double / Imperial IPA</td>\n",
       "      <td>Cauldron DIPA</td>\n",
       "      <td>7.7</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>52159</td>\n",
       "      <td>1075</td>\n",
       "      <td>Caldera Brewing Company</td>\n",
       "      <td>oline73</td>\n",
       "      <td>1325524659</td>\n",
       "      <td>Herbed / Spiced Beer</td>\n",
       "      <td>Caldera Ginger Beer</td>\n",
       "      <td>4.7</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>3.5</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>52159</td>\n",
       "      <td>1075</td>\n",
       "      <td>Caldera Brewing Company</td>\n",
       "      <td>Reidrover</td>\n",
       "      <td>1318991115</td>\n",
       "      <td>Herbed / Spiced Beer</td>\n",
       "      <td>Caldera Ginger Beer</td>\n",
       "      <td>4.7</td>\n",
       "      <td>3.5</td>\n",
       "      <td>3.5</td>\n",
       "      <td>3.5</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>52159</td>\n",
       "      <td>1075</td>\n",
       "      <td>Caldera Brewing Company</td>\n",
       "      <td>alpinebryant</td>\n",
       "      <td>1306276018</td>\n",
       "      <td>Herbed / Spiced Beer</td>\n",
       "      <td>Caldera Ginger Beer</td>\n",
       "      <td>4.7</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>3.5</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>52159</td>\n",
       "      <td>1075</td>\n",
       "      <td>Caldera Brewing Company</td>\n",
       "      <td>LordAdmNelson</td>\n",
       "      <td>1290454503</td>\n",
       "      <td>Herbed / Spiced Beer</td>\n",
       "      <td>Caldera Ginger Beer</td>\n",
       "      <td>4.7</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>3.5</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>52159</td>\n",
       "      <td>1075</td>\n",
       "      <td>Caldera Brewing Company</td>\n",
       "      <td>augustgarage</td>\n",
       "      <td>1285632924</td>\n",
       "      <td>Herbed / Spiced Beer</td>\n",
       "      <td>Caldera Ginger Beer</td>\n",
       "      <td>4.7</td>\n",
       "      <td>4.5</td>\n",
       "      <td>3.5</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>436</td>\n",
       "      <td>163</td>\n",
       "      <td>Amstel Brouwerij B. V.</td>\n",
       "      <td>fodeeoz</td>\n",
       "      <td>1010963392</td>\n",
       "      <td>Light Lager</td>\n",
       "      <td>Amstel Light</td>\n",
       "      <td>3.5</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>2.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>52159</td>\n",
       "      <td>1075</td>\n",
       "      <td>Caldera Brewing Company</td>\n",
       "      <td>MadeInOregon</td>\n",
       "      <td>1283154365</td>\n",
       "      <td>Herbed / Spiced Beer</td>\n",
       "      <td>Caldera Ginger Beer</td>\n",
       "      <td>4.7</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>52159</td>\n",
       "      <td>1075</td>\n",
       "      <td>Caldera Brewing Company</td>\n",
       "      <td>rawthar</td>\n",
       "      <td>1277557990</td>\n",
       "      <td>Herbed / Spiced Beer</td>\n",
       "      <td>Caldera Ginger Beer</td>\n",
       "      <td>4.7</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>52159</td>\n",
       "      <td>1075</td>\n",
       "      <td>Caldera Brewing Company</td>\n",
       "      <td>Halcyondays</td>\n",
       "      <td>1275779250</td>\n",
       "      <td>Herbed / Spiced Beer</td>\n",
       "      <td>Caldera Ginger Beer</td>\n",
       "      <td>4.7</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.5</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>52159</td>\n",
       "      <td>1075</td>\n",
       "      <td>Caldera Brewing Company</td>\n",
       "      <td>RangerClegg</td>\n",
       "      <td>1273109020</td>\n",
       "      <td>Herbed / Spiced Beer</td>\n",
       "      <td>Caldera Ginger Beer</td>\n",
       "      <td>4.7</td>\n",
       "      <td>3.5</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>10789</td>\n",
       "      <td>1075</td>\n",
       "      <td>Caldera Brewing Company</td>\n",
       "      <td>Beerandraiderfan</td>\n",
       "      <td>1316025612</td>\n",
       "      <td>Oatmeal Stout</td>\n",
       "      <td>Caldera Oatmeal Stout</td>\n",
       "      <td>7.2</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>10789</td>\n",
       "      <td>1075</td>\n",
       "      <td>Caldera Brewing Company</td>\n",
       "      <td>RedDiamond</td>\n",
       "      <td>1103502339</td>\n",
       "      <td>Oatmeal Stout</td>\n",
       "      <td>Caldera Oatmeal Stout</td>\n",
       "      <td>7.2</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.5</td>\n",
       "      <td>2.5</td>\n",
       "      <td>2.5</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>12386</td>\n",
       "      <td>1075</td>\n",
       "      <td>Caldera Brewing Company</td>\n",
       "      <td>beerguy101</td>\n",
       "      <td>1062311123</td>\n",
       "      <td>American Pale Lager</td>\n",
       "      <td>Caldera OBF 15</td>\n",
       "      <td>5.6</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>436</td>\n",
       "      <td>163</td>\n",
       "      <td>Amstel Brouwerij B. V.</td>\n",
       "      <td>jdhilt</td>\n",
       "      <td>1010861086</td>\n",
       "      <td>Light Lager</td>\n",
       "      <td>Amstel Light</td>\n",
       "      <td>3.5</td>\n",
       "      <td>2.5</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>58046</td>\n",
       "      <td>1075</td>\n",
       "      <td>Caldera Brewing Company</td>\n",
       "      <td>UCLABrewN84</td>\n",
       "      <td>1325478004</td>\n",
       "      <td>Rauchbier</td>\n",
       "      <td>Rauch Ür Bock</td>\n",
       "      <td>7.4</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>58046</td>\n",
       "      <td>1075</td>\n",
       "      <td>Caldera Brewing Company</td>\n",
       "      <td>zaphodchak</td>\n",
       "      <td>1325360812</td>\n",
       "      <td>Rauchbier</td>\n",
       "      <td>Rauch Ür Bock</td>\n",
       "      <td>7.4</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>58046</td>\n",
       "      <td>1075</td>\n",
       "      <td>Caldera Brewing Company</td>\n",
       "      <td>Tilley4</td>\n",
       "      <td>1322506304</td>\n",
       "      <td>Rauchbier</td>\n",
       "      <td>Rauch Ür Bock</td>\n",
       "      <td>7.4</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>58046</td>\n",
       "      <td>1075</td>\n",
       "      <td>Caldera Brewing Company</td>\n",
       "      <td>mikedrinksbeer2</td>\n",
       "      <td>1320494397</td>\n",
       "      <td>Rauchbier</td>\n",
       "      <td>Rauch Ür Bock</td>\n",
       "      <td>7.4</td>\n",
       "      <td>4.5</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>58046</td>\n",
       "      <td>1075</td>\n",
       "      <td>Caldera Brewing Company</td>\n",
       "      <td>dbmernin83</td>\n",
       "      <td>1320140421</td>\n",
       "      <td>Rauchbier</td>\n",
       "      <td>Rauch Ür Bock</td>\n",
       "      <td>7.4</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>58046</td>\n",
       "      <td>1075</td>\n",
       "      <td>Caldera Brewing Company</td>\n",
       "      <td>titosupertramp</td>\n",
       "      <td>1319847514</td>\n",
       "      <td>Rauchbier</td>\n",
       "      <td>Rauch Ür Bock</td>\n",
       "      <td>7.4</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>58046</td>\n",
       "      <td>1075</td>\n",
       "      <td>Caldera Brewing Company</td>\n",
       "      <td>optimator13</td>\n",
       "      <td>1318802642</td>\n",
       "      <td>Rauchbier</td>\n",
       "      <td>Rauch Ür Bock</td>\n",
       "      <td>7.4</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>3.5</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>58046</td>\n",
       "      <td>1075</td>\n",
       "      <td>Caldera Brewing Company</td>\n",
       "      <td>Blakaeris</td>\n",
       "      <td>1318290101</td>\n",
       "      <td>Rauchbier</td>\n",
       "      <td>Rauch Ür Bock</td>\n",
       "      <td>7.4</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>58046</td>\n",
       "      <td>1075</td>\n",
       "      <td>Caldera Brewing Company</td>\n",
       "      <td>bashiba</td>\n",
       "      <td>1318289482</td>\n",
       "      <td>Rauchbier</td>\n",
       "      <td>Rauch Ür Bock</td>\n",
       "      <td>7.4</td>\n",
       "      <td>4.5</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>58046</td>\n",
       "      <td>1075</td>\n",
       "      <td>Caldera Brewing Company</td>\n",
       "      <td>Klym</td>\n",
       "      <td>1316405909</td>\n",
       "      <td>Rauchbier</td>\n",
       "      <td>Rauch Ür Bock</td>\n",
       "      <td>7.4</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>3.5</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>58046</td>\n",
       "      <td>1075</td>\n",
       "      <td>Caldera Brewing Company</td>\n",
       "      <td>flexabull</td>\n",
       "      <td>1315696563</td>\n",
       "      <td>Rauchbier</td>\n",
       "      <td>Rauch Ür Bock</td>\n",
       "      <td>7.4</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</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>1586584</th>\n",
       "      <td>34215</td>\n",
       "      <td>14359</td>\n",
       "      <td>The Defiant Brewing Company</td>\n",
       "      <td>dherling</td>\n",
       "      <td>1166930040</td>\n",
       "      <td>Extra Special / Strong Bitter (ESB)</td>\n",
       "      <td>Big Thumper Ale</td>\n",
       "      <td>5.8</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1586585</th>\n",
       "      <td>34215</td>\n",
       "      <td>14359</td>\n",
       "      <td>The Defiant Brewing Company</td>\n",
       "      <td>tgbljb</td>\n",
       "      <td>1165710255</td>\n",
       "      <td>Extra Special / Strong Bitter (ESB)</td>\n",
       "      <td>Big Thumper Ale</td>\n",
       "      <td>5.8</td>\n",
       "      <td>3.5</td>\n",
       "      <td>3.5</td>\n",
       "      <td>3.5</td>\n",
       "      <td>3.5</td>\n",
       "      <td>3.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1586586</th>\n",
       "      <td>34215</td>\n",
       "      <td>14359</td>\n",
       "      <td>The Defiant Brewing Company</td>\n",
       "      <td>cbl2</td>\n",
       "      <td>1165708674</td>\n",
       "      <td>Extra Special / Strong Bitter (ESB)</td>\n",
       "      <td>Big Thumper Ale</td>\n",
       "      <td>5.8</td>\n",
       "      <td>3.5</td>\n",
       "      <td>3.5</td>\n",
       "      <td>3.5</td>\n",
       "      <td>3.5</td>\n",
       "      <td>3.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1586587</th>\n",
       "      <td>36555</td>\n",
       "      <td>14359</td>\n",
       "      <td>The Defiant Brewing Company</td>\n",
       "      <td>BBM</td>\n",
       "      <td>1177842168</td>\n",
       "      <td>Maibock / Helles Bock</td>\n",
       "      <td>Maibock</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1586588</th>\n",
       "      <td>62147</td>\n",
       "      <td>14359</td>\n",
       "      <td>The Defiant Brewing Company</td>\n",
       "      <td>Buddha22</td>\n",
       "      <td>1295399777</td>\n",
       "      <td>Belgian IPA</td>\n",
       "      <td>Bear Mountain Ale</td>\n",
       "      <td>8.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1586589</th>\n",
       "      <td>62147</td>\n",
       "      <td>14359</td>\n",
       "      <td>The Defiant Brewing Company</td>\n",
       "      <td>JohnQVegas</td>\n",
       "      <td>1294005929</td>\n",
       "      <td>Belgian IPA</td>\n",
       "      <td>Bear Mountain Ale</td>\n",
       "      <td>8.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.5</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1586590</th>\n",
       "      <td>62147</td>\n",
       "      <td>14359</td>\n",
       "      <td>The Defiant Brewing Company</td>\n",
       "      <td>cpanossian</td>\n",
       "      <td>1287628639</td>\n",
       "      <td>Belgian IPA</td>\n",
       "      <td>Bear Mountain Ale</td>\n",
       "      <td>8.0</td>\n",
       "      <td>1.5</td>\n",
       "      <td>3.5</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1586591</th>\n",
       "      <td>62147</td>\n",
       "      <td>14359</td>\n",
       "      <td>The Defiant Brewing Company</td>\n",
       "      <td>claspada</td>\n",
       "      <td>1285616583</td>\n",
       "      <td>Belgian IPA</td>\n",
       "      <td>Bear Mountain Ale</td>\n",
       "      <td>8.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1586592</th>\n",
       "      <td>41749</td>\n",
       "      <td>14359</td>\n",
       "      <td>The Defiant Brewing Company</td>\n",
       "      <td>RblWthACoz</td>\n",
       "      <td>1209864382</td>\n",
       "      <td>Irish Red Ale</td>\n",
       "      <td>Irish Amber</td>\n",
       "      <td>5.2</td>\n",
       "      <td>4.5</td>\n",
       "      <td>3.5</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1586593</th>\n",
       "      <td>41749</td>\n",
       "      <td>14359</td>\n",
       "      <td>The Defiant Brewing Company</td>\n",
       "      <td>yelterdow</td>\n",
       "      <td>1206241317</td>\n",
       "      <td>Irish Red Ale</td>\n",
       "      <td>Irish Amber</td>\n",
       "      <td>5.2</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1586594</th>\n",
       "      <td>38160</td>\n",
       "      <td>14359</td>\n",
       "      <td>The Defiant Brewing Company</td>\n",
       "      <td>maddogruss</td>\n",
       "      <td>1186979266</td>\n",
       "      <td>American Porter</td>\n",
       "      <td>Highland Porter</td>\n",
       "      <td>6.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1586595</th>\n",
       "      <td>71234</td>\n",
       "      <td>14359</td>\n",
       "      <td>The Defiant Brewing Company</td>\n",
       "      <td>JerzDevl2000</td>\n",
       "      <td>1311205969</td>\n",
       "      <td>Hefeweizen</td>\n",
       "      <td>Baron Von Weizen</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1586596</th>\n",
       "      <td>48360</td>\n",
       "      <td>14359</td>\n",
       "      <td>The Defiant Brewing Company</td>\n",
       "      <td>hoppymcgee</td>\n",
       "      <td>1287951067</td>\n",
       "      <td>Belgian Strong Pale Ale</td>\n",
       "      <td>Resolution #2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1586597</th>\n",
       "      <td>48360</td>\n",
       "      <td>14359</td>\n",
       "      <td>The Defiant Brewing Company</td>\n",
       "      <td>WesWes</td>\n",
       "      <td>1241906223</td>\n",
       "      <td>Belgian Strong Pale Ale</td>\n",
       "      <td>Resolution #2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1586598</th>\n",
       "      <td>48360</td>\n",
       "      <td>14359</td>\n",
       "      <td>The Defiant Brewing Company</td>\n",
       "      <td>Slatetank</td>\n",
       "      <td>1236550020</td>\n",
       "      <td>Belgian Strong Pale Ale</td>\n",
       "      <td>Resolution #2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1586599</th>\n",
       "      <td>43233</td>\n",
       "      <td>14359</td>\n",
       "      <td>The Defiant Brewing Company</td>\n",
       "      <td>Lenny2884</td>\n",
       "      <td>1213497070</td>\n",
       "      <td>American Double / Imperial IPA</td>\n",
       "      <td>Double IPA</td>\n",
       "      <td>9.0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1586600</th>\n",
       "      <td>33061</td>\n",
       "      <td>14359</td>\n",
       "      <td>The Defiant Brewing Company</td>\n",
       "      <td>ummswimmin</td>\n",
       "      <td>1317599053</td>\n",
       "      <td>Pumpkin Ale</td>\n",
       "      <td>The Horseman's Ale</td>\n",
       "      <td>5.2</td>\n",
       "      <td>3.5</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1586601</th>\n",
       "      <td>33061</td>\n",
       "      <td>14359</td>\n",
       "      <td>The Defiant Brewing Company</td>\n",
       "      <td>pzrhsau</td>\n",
       "      <td>1291257338</td>\n",
       "      <td>Pumpkin Ale</td>\n",
       "      <td>The Horseman's Ale</td>\n",
       "      <td>5.2</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1586602</th>\n",
       "      <td>33061</td>\n",
       "      <td>14359</td>\n",
       "      <td>The Defiant Brewing Company</td>\n",
       "      <td>asabreed</td>\n",
       "      <td>1291054144</td>\n",
       "      <td>Pumpkin Ale</td>\n",
       "      <td>The Horseman's Ale</td>\n",
       "      <td>5.2</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1586603</th>\n",
       "      <td>33061</td>\n",
       "      <td>14359</td>\n",
       "      <td>The Defiant Brewing Company</td>\n",
       "      <td>infi</td>\n",
       "      <td>1289366204</td>\n",
       "      <td>Pumpkin Ale</td>\n",
       "      <td>The Horseman's Ale</td>\n",
       "      <td>5.2</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1586604</th>\n",
       "      <td>33061</td>\n",
       "      <td>14359</td>\n",
       "      <td>The Defiant Brewing Company</td>\n",
       "      <td>njmoons</td>\n",
       "      <td>1288890206</td>\n",
       "      <td>Pumpkin Ale</td>\n",
       "      <td>The Horseman's Ale</td>\n",
       "      <td>5.2</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>3.5</td>\n",
       "      <td>3.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1586605</th>\n",
       "      <td>33061</td>\n",
       "      <td>14359</td>\n",
       "      <td>The Defiant Brewing Company</td>\n",
       "      <td>NyackNicky</td>\n",
       "      <td>1163291143</td>\n",
       "      <td>Pumpkin Ale</td>\n",
       "      <td>The Horseman's Ale</td>\n",
       "      <td>5.2</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1586606</th>\n",
       "      <td>33061</td>\n",
       "      <td>14359</td>\n",
       "      <td>The Defiant Brewing Company</td>\n",
       "      <td>blitheringidiot</td>\n",
       "      <td>1162871808</td>\n",
       "      <td>Pumpkin Ale</td>\n",
       "      <td>The Horseman's Ale</td>\n",
       "      <td>5.2</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1586607</th>\n",
       "      <td>33061</td>\n",
       "      <td>14359</td>\n",
       "      <td>The Defiant Brewing Company</td>\n",
       "      <td>PopeDX</td>\n",
       "      <td>1162865640</td>\n",
       "      <td>Pumpkin Ale</td>\n",
       "      <td>The Horseman's Ale</td>\n",
       "      <td>5.2</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.5</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1586608</th>\n",
       "      <td>33061</td>\n",
       "      <td>14359</td>\n",
       "      <td>The Defiant Brewing Company</td>\n",
       "      <td>treehugger02010</td>\n",
       "      <td>1162685856</td>\n",
       "      <td>Pumpkin Ale</td>\n",
       "      <td>The Horseman's Ale</td>\n",
       "      <td>5.2</td>\n",
       "      <td>3.5</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1586609</th>\n",
       "      <td>33061</td>\n",
       "      <td>14359</td>\n",
       "      <td>The Defiant Brewing Company</td>\n",
       "      <td>maddogruss</td>\n",
       "      <td>1162684892</td>\n",
       "      <td>Pumpkin Ale</td>\n",
       "      <td>The Horseman's Ale</td>\n",
       "      <td>5.2</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1586610</th>\n",
       "      <td>33061</td>\n",
       "      <td>14359</td>\n",
       "      <td>The Defiant Brewing Company</td>\n",
       "      <td>yelterdow</td>\n",
       "      <td>1161048566</td>\n",
       "      <td>Pumpkin Ale</td>\n",
       "      <td>The Horseman's Ale</td>\n",
       "      <td>5.2</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1586611</th>\n",
       "      <td>33061</td>\n",
       "      <td>14359</td>\n",
       "      <td>The Defiant Brewing Company</td>\n",
       "      <td>TongoRad</td>\n",
       "      <td>1160702513</td>\n",
       "      <td>Pumpkin Ale</td>\n",
       "      <td>The Horseman's Ale</td>\n",
       "      <td>5.2</td>\n",
       "      <td>4.5</td>\n",
       "      <td>3.5</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1586612</th>\n",
       "      <td>33061</td>\n",
       "      <td>14359</td>\n",
       "      <td>The Defiant Brewing Company</td>\n",
       "      <td>dherling</td>\n",
       "      <td>1160023044</td>\n",
       "      <td>Pumpkin Ale</td>\n",
       "      <td>The Horseman's Ale</td>\n",
       "      <td>5.2</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1586613</th>\n",
       "      <td>33061</td>\n",
       "      <td>14359</td>\n",
       "      <td>The Defiant Brewing Company</td>\n",
       "      <td>cbl2</td>\n",
       "      <td>1160005319</td>\n",
       "      <td>Pumpkin Ale</td>\n",
       "      <td>The Horseman's Ale</td>\n",
       "      <td>5.2</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1586614 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         beer_beerid  brewery_id                 brewery_name  \\\n",
       "0              47986       10325              Vecchio Birraio   \n",
       "1              48213       10325              Vecchio Birraio   \n",
       "2              48215       10325              Vecchio Birraio   \n",
       "3              47969       10325              Vecchio Birraio   \n",
       "4              64883        1075      Caldera Brewing Company   \n",
       "5              52159        1075      Caldera Brewing Company   \n",
       "6              52159        1075      Caldera Brewing Company   \n",
       "7              52159        1075      Caldera Brewing Company   \n",
       "8              52159        1075      Caldera Brewing Company   \n",
       "9              52159        1075      Caldera Brewing Company   \n",
       "10               436         163       Amstel Brouwerij B. V.   \n",
       "11             52159        1075      Caldera Brewing Company   \n",
       "12             52159        1075      Caldera Brewing Company   \n",
       "13             52159        1075      Caldera Brewing Company   \n",
       "14             52159        1075      Caldera Brewing Company   \n",
       "15             10789        1075      Caldera Brewing Company   \n",
       "16             10789        1075      Caldera Brewing Company   \n",
       "17             12386        1075      Caldera Brewing Company   \n",
       "18               436         163       Amstel Brouwerij B. V.   \n",
       "19             58046        1075      Caldera Brewing Company   \n",
       "20             58046        1075      Caldera Brewing Company   \n",
       "21             58046        1075      Caldera Brewing Company   \n",
       "22             58046        1075      Caldera Brewing Company   \n",
       "23             58046        1075      Caldera Brewing Company   \n",
       "24             58046        1075      Caldera Brewing Company   \n",
       "25             58046        1075      Caldera Brewing Company   \n",
       "26             58046        1075      Caldera Brewing Company   \n",
       "27             58046        1075      Caldera Brewing Company   \n",
       "28             58046        1075      Caldera Brewing Company   \n",
       "29             58046        1075      Caldera Brewing Company   \n",
       "...              ...         ...                          ...   \n",
       "1586584        34215       14359  The Defiant Brewing Company   \n",
       "1586585        34215       14359  The Defiant Brewing Company   \n",
       "1586586        34215       14359  The Defiant Brewing Company   \n",
       "1586587        36555       14359  The Defiant Brewing Company   \n",
       "1586588        62147       14359  The Defiant Brewing Company   \n",
       "1586589        62147       14359  The Defiant Brewing Company   \n",
       "1586590        62147       14359  The Defiant Brewing Company   \n",
       "1586591        62147       14359  The Defiant Brewing Company   \n",
       "1586592        41749       14359  The Defiant Brewing Company   \n",
       "1586593        41749       14359  The Defiant Brewing Company   \n",
       "1586594        38160       14359  The Defiant Brewing Company   \n",
       "1586595        71234       14359  The Defiant Brewing Company   \n",
       "1586596        48360       14359  The Defiant Brewing Company   \n",
       "1586597        48360       14359  The Defiant Brewing Company   \n",
       "1586598        48360       14359  The Defiant Brewing Company   \n",
       "1586599        43233       14359  The Defiant Brewing Company   \n",
       "1586600        33061       14359  The Defiant Brewing Company   \n",
       "1586601        33061       14359  The Defiant Brewing Company   \n",
       "1586602        33061       14359  The Defiant Brewing Company   \n",
       "1586603        33061       14359  The Defiant Brewing Company   \n",
       "1586604        33061       14359  The Defiant Brewing Company   \n",
       "1586605        33061       14359  The Defiant Brewing Company   \n",
       "1586606        33061       14359  The Defiant Brewing Company   \n",
       "1586607        33061       14359  The Defiant Brewing Company   \n",
       "1586608        33061       14359  The Defiant Brewing Company   \n",
       "1586609        33061       14359  The Defiant Brewing Company   \n",
       "1586610        33061       14359  The Defiant Brewing Company   \n",
       "1586611        33061       14359  The Defiant Brewing Company   \n",
       "1586612        33061       14359  The Defiant Brewing Company   \n",
       "1586613        33061       14359  The Defiant Brewing Company   \n",
       "\n",
       "        review_profilename  review_time                           beer_style  \\\n",
       "0                  stcules   1234817823                           Hefeweizen   \n",
       "1                  stcules   1235915097                   English Strong Ale   \n",
       "2                  stcules   1235916604               Foreign / Export Stout   \n",
       "3                  stcules   1234725145                      German Pilsener   \n",
       "4           johnmichaelsen   1293735206       American Double / Imperial IPA   \n",
       "5                  oline73   1325524659                 Herbed / Spiced Beer   \n",
       "6                Reidrover   1318991115                 Herbed / Spiced Beer   \n",
       "7             alpinebryant   1306276018                 Herbed / Spiced Beer   \n",
       "8            LordAdmNelson   1290454503                 Herbed / Spiced Beer   \n",
       "9             augustgarage   1285632924                 Herbed / Spiced Beer   \n",
       "10                 fodeeoz   1010963392                          Light Lager   \n",
       "11            MadeInOregon   1283154365                 Herbed / Spiced Beer   \n",
       "12                 rawthar   1277557990                 Herbed / Spiced Beer   \n",
       "13             Halcyondays   1275779250                 Herbed / Spiced Beer   \n",
       "14             RangerClegg   1273109020                 Herbed / Spiced Beer   \n",
       "15        Beerandraiderfan   1316025612                        Oatmeal Stout   \n",
       "16              RedDiamond   1103502339                        Oatmeal Stout   \n",
       "17              beerguy101   1062311123                  American Pale Lager   \n",
       "18                  jdhilt   1010861086                          Light Lager   \n",
       "19             UCLABrewN84   1325478004                            Rauchbier   \n",
       "20              zaphodchak   1325360812                            Rauchbier   \n",
       "21                 Tilley4   1322506304                            Rauchbier   \n",
       "22         mikedrinksbeer2   1320494397                            Rauchbier   \n",
       "23              dbmernin83   1320140421                            Rauchbier   \n",
       "24          titosupertramp   1319847514                            Rauchbier   \n",
       "25             optimator13   1318802642                            Rauchbier   \n",
       "26               Blakaeris   1318290101                            Rauchbier   \n",
       "27                 bashiba   1318289482                            Rauchbier   \n",
       "28                    Klym   1316405909                            Rauchbier   \n",
       "29               flexabull   1315696563                            Rauchbier   \n",
       "...                    ...          ...                                  ...   \n",
       "1586584           dherling   1166930040  Extra Special / Strong Bitter (ESB)   \n",
       "1586585             tgbljb   1165710255  Extra Special / Strong Bitter (ESB)   \n",
       "1586586               cbl2   1165708674  Extra Special / Strong Bitter (ESB)   \n",
       "1586587                BBM   1177842168                Maibock / Helles Bock   \n",
       "1586588           Buddha22   1295399777                          Belgian IPA   \n",
       "1586589         JohnQVegas   1294005929                          Belgian IPA   \n",
       "1586590         cpanossian   1287628639                          Belgian IPA   \n",
       "1586591           claspada   1285616583                          Belgian IPA   \n",
       "1586592         RblWthACoz   1209864382                        Irish Red Ale   \n",
       "1586593          yelterdow   1206241317                        Irish Red Ale   \n",
       "1586594         maddogruss   1186979266                      American Porter   \n",
       "1586595       JerzDevl2000   1311205969                           Hefeweizen   \n",
       "1586596         hoppymcgee   1287951067              Belgian Strong Pale Ale   \n",
       "1586597             WesWes   1241906223              Belgian Strong Pale Ale   \n",
       "1586598          Slatetank   1236550020              Belgian Strong Pale Ale   \n",
       "1586599          Lenny2884   1213497070       American Double / Imperial IPA   \n",
       "1586600         ummswimmin   1317599053                          Pumpkin Ale   \n",
       "1586601            pzrhsau   1291257338                          Pumpkin Ale   \n",
       "1586602           asabreed   1291054144                          Pumpkin Ale   \n",
       "1586603               infi   1289366204                          Pumpkin Ale   \n",
       "1586604            njmoons   1288890206                          Pumpkin Ale   \n",
       "1586605         NyackNicky   1163291143                          Pumpkin Ale   \n",
       "1586606    blitheringidiot   1162871808                          Pumpkin Ale   \n",
       "1586607             PopeDX   1162865640                          Pumpkin Ale   \n",
       "1586608    treehugger02010   1162685856                          Pumpkin Ale   \n",
       "1586609         maddogruss   1162684892                          Pumpkin Ale   \n",
       "1586610          yelterdow   1161048566                          Pumpkin Ale   \n",
       "1586611           TongoRad   1160702513                          Pumpkin Ale   \n",
       "1586612           dherling   1160023044                          Pumpkin Ale   \n",
       "1586613               cbl2   1160005319                          Pumpkin Ale   \n",
       "\n",
       "                      beer_name  beer_abv  review_overall  review_aroma  \\\n",
       "0                  Sausa Weizen       5.0             1.5           2.0   \n",
       "1                      Red Moon       6.2             3.0           2.5   \n",
       "2        Black Horse Black Beer       6.5             3.0           2.5   \n",
       "3                    Sausa Pils       5.0             3.0           3.0   \n",
       "4                 Cauldron DIPA       7.7             4.0           4.5   \n",
       "5           Caldera Ginger Beer       4.7             3.0           3.5   \n",
       "6           Caldera Ginger Beer       4.7             3.5           3.5   \n",
       "7           Caldera Ginger Beer       4.7             3.0           2.5   \n",
       "8           Caldera Ginger Beer       4.7             4.0           3.0   \n",
       "9           Caldera Ginger Beer       4.7             4.5           3.5   \n",
       "10                 Amstel Light       3.5             3.0           2.0   \n",
       "11          Caldera Ginger Beer       4.7             5.0           5.0   \n",
       "12          Caldera Ginger Beer       4.7             4.0           4.0   \n",
       "13          Caldera Ginger Beer       4.7             4.0           4.5   \n",
       "14          Caldera Ginger Beer       4.7             3.5           4.0   \n",
       "15        Caldera Oatmeal Stout       7.2             3.0           3.0   \n",
       "16        Caldera Oatmeal Stout       7.2             2.0           1.5   \n",
       "17               Caldera OBF 15       5.6             4.0           3.0   \n",
       "18                 Amstel Light       3.5             2.5           3.0   \n",
       "19                Rauch Ür Bock       7.4             4.5           4.5   \n",
       "20                Rauch Ür Bock       7.4             4.0           4.0   \n",
       "21                Rauch Ür Bock       7.4             4.0           4.5   \n",
       "22                Rauch Ür Bock       7.4             4.5           5.0   \n",
       "23                Rauch Ür Bock       7.4             4.0           4.5   \n",
       "24                Rauch Ür Bock       7.4             4.5           4.5   \n",
       "25                Rauch Ür Bock       7.4             5.0           5.0   \n",
       "26                Rauch Ür Bock       7.4             4.5           4.5   \n",
       "27                Rauch Ür Bock       7.4             4.5           5.0   \n",
       "28                Rauch Ür Bock       7.4             4.5           4.5   \n",
       "29                Rauch Ür Bock       7.4             4.5           4.5   \n",
       "...                         ...       ...             ...           ...   \n",
       "1586584         Big Thumper Ale       5.8             4.5           4.0   \n",
       "1586585         Big Thumper Ale       5.8             3.5           3.5   \n",
       "1586586         Big Thumper Ale       5.8             3.5           3.5   \n",
       "1586587                 Maibock       NaN             3.5           4.5   \n",
       "1586588       Bear Mountain Ale       8.0             2.0           2.5   \n",
       "1586589       Bear Mountain Ale       8.0             1.0           4.0   \n",
       "1586590       Bear Mountain Ale       8.0             1.5           3.5   \n",
       "1586591       Bear Mountain Ale       8.0             1.0           2.0   \n",
       "1586592             Irish Amber       5.2             4.5           3.5   \n",
       "1586593             Irish Amber       5.2             4.5           4.0   \n",
       "1586594         Highland Porter       6.0             3.0           3.5   \n",
       "1586595        Baron Von Weizen       5.0             4.0           3.5   \n",
       "1586596           Resolution #2       NaN             4.0           3.0   \n",
       "1586597           Resolution #2       NaN             4.5           4.5   \n",
       "1586598           Resolution #2       NaN             4.0           4.0   \n",
       "1586599              Double IPA       9.0             3.5           4.5   \n",
       "1586600      The Horseman's Ale       5.2             3.5           4.0   \n",
       "1586601      The Horseman's Ale       5.2             4.5           4.0   \n",
       "1586602      The Horseman's Ale       5.2             4.0           4.0   \n",
       "1586603      The Horseman's Ale       5.2             4.0           4.5   \n",
       "1586604      The Horseman's Ale       5.2             4.0           4.5   \n",
       "1586605      The Horseman's Ale       5.2             5.0           5.0   \n",
       "1586606      The Horseman's Ale       5.2             5.0           4.5   \n",
       "1586607      The Horseman's Ale       5.2             5.0           5.0   \n",
       "1586608      The Horseman's Ale       5.2             3.5           4.0   \n",
       "1586609      The Horseman's Ale       5.2             5.0           4.0   \n",
       "1586610      The Horseman's Ale       5.2             4.0           5.0   \n",
       "1586611      The Horseman's Ale       5.2             4.5           3.5   \n",
       "1586612      The Horseman's Ale       5.2             4.0           4.5   \n",
       "1586613      The Horseman's Ale       5.2             5.0           4.5   \n",
       "\n",
       "         review_appearance  review_palate  review_taste  \n",
       "0                      2.5            1.5           1.5  \n",
       "1                      3.0            3.0           3.0  \n",
       "2                      3.0            3.0           3.0  \n",
       "3                      3.5            2.5           3.0  \n",
       "4                      4.0            4.0           4.5  \n",
       "5                      3.5            3.0           3.5  \n",
       "6                      3.5            4.0           4.0  \n",
       "7                      3.5            2.0           3.5  \n",
       "8                      3.5            3.5           4.0  \n",
       "9                      5.0            4.0           4.0  \n",
       "10                     3.0            2.5           2.5  \n",
       "11                     4.0            4.0           4.0  \n",
       "12                     4.0            3.5           4.0  \n",
       "13                     3.0            2.5           3.0  \n",
       "14                     3.0            3.0           4.0  \n",
       "15                     2.5            3.0           3.0  \n",
       "16                     2.5            2.5           2.0  \n",
       "17                     4.0            4.0           4.0  \n",
       "18                     3.0            2.0           2.0  \n",
       "19                     3.0            4.0           4.5  \n",
       "20                     4.0            3.0           4.0  \n",
       "21                     4.0            3.5           4.0  \n",
       "22                     4.5            4.0           4.5  \n",
       "23                     4.0            4.0           4.5  \n",
       "24                     4.0            4.0           4.5  \n",
       "25                     3.5            3.5           5.0  \n",
       "26                     4.0            4.0           4.5  \n",
       "27                     4.0            4.0           4.0  \n",
       "28                     3.5            4.0           4.5  \n",
       "29                     4.0            4.0           4.0  \n",
       "...                    ...            ...           ...  \n",
       "1586584                4.0            4.0           4.0  \n",
       "1586585                3.5            3.5           3.5  \n",
       "1586586                3.5            3.5           3.5  \n",
       "1586587                4.0            4.5           4.0  \n",
       "1586588                3.0            2.0           2.5  \n",
       "1586589                4.5            3.0           1.0  \n",
       "1586590                4.0            3.0           1.5  \n",
       "1586591                3.0            2.0           1.0  \n",
       "1586592                4.0            4.0           4.5  \n",
       "1586593                4.5            4.0           4.0  \n",
       "1586594                4.0            4.0           4.0  \n",
       "1586595                4.0            4.0           4.0  \n",
       "1586596                5.0            4.0           3.5  \n",
       "1586597                4.0            4.0           4.0  \n",
       "1586598                3.5            4.0           4.5  \n",
       "1586599                4.0            4.0           4.0  \n",
       "1586600                3.5            3.0           3.5  \n",
       "1586601                4.0            4.5           4.0  \n",
       "1586602                4.0            4.0           4.0  \n",
       "1586603                4.0            4.0           4.0  \n",
       "1586604                4.5            3.5           3.5  \n",
       "1586605                5.0            5.0           5.0  \n",
       "1586606                4.0            5.0           5.0  \n",
       "1586607                4.5            5.0           4.5  \n",
       "1586608                4.0            3.5           3.0  \n",
       "1586609                3.5            4.0           4.0  \n",
       "1586610                2.5            2.0           4.0  \n",
       "1586611                3.0            3.5           4.0  \n",
       "1586612                4.5            4.5           4.5  \n",
       "1586613                4.5            4.5           4.5  \n",
       "\n",
       "[1586614 rows x 13 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "beer_reviews"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "beer_beerid             int64\n",
       "brewery_id              int64\n",
       "brewery_name           object\n",
       "review_profilename     object\n",
       "review_time             int64\n",
       "beer_style             object\n",
       "beer_name              object\n",
       "beer_abv              float64\n",
       "review_overall        float64\n",
       "review_aroma          float64\n",
       "review_appearance     float64\n",
       "review_palate         float64\n",
       "review_taste          float64\n",
       "dtype: object"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "beer_reviews.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    1234817823\n",
       "1    1235915097\n",
       "2    1235916604\n",
       "3    1234725145\n",
       "4    1293735206\n",
       "Name: review_time, dtype: int64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "beer_reviews.review_time.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "beer_reviews.review_time = pd.to_datetime(beer_reviews.review_time, unit = \"s\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "beer_beerid                    int64\n",
       "brewery_id                     int64\n",
       "brewery_name                  object\n",
       "review_profilename            object\n",
       "review_time           datetime64[ns]\n",
       "beer_style                    object\n",
       "beer_name                     object\n",
       "beer_abv                     float64\n",
       "review_overall               float64\n",
       "review_aroma                 float64\n",
       "review_appearance            float64\n",
       "review_palate                float64\n",
       "review_taste                 float64\n",
       "dtype: object"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "beer_reviews.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(Timestamp('1996-08-22 00:00:01'), Timestamp('2012-01-11 12:35:48'))"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "beer_reviews.review_time.min(), beer_reviews.review_time.max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "review_time\n",
       "1996         1\n",
       "1998       133\n",
       "1999        86\n",
       "2000       119\n",
       "2001      1999\n",
       "2002     23140\n",
       "2003     56958\n",
       "2004     69701\n",
       "2005     89116\n",
       "2006    129648\n",
       "2007    142404\n",
       "2008    210099\n",
       "2009    243402\n",
       "2010    277072\n",
       "2011    333072\n",
       "2012      9664\n",
       "dtype: int64"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "review_counts_by_year = beer_reviews.groupby(beer_reviews.review_time.dt.year).size()\n",
    "review_counts_by_year"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'beer_reviews' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-5-193ccd1acc27>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mmin_year\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmax_year\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mbeer_reviews\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mreview_time\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmin\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0myear\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mbeer_reviews\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mreview_time\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmax\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0myear\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      2\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      3\u001b[0m \u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfigure\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfigsize\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m(\u001b[0m\u001b[1;36m12\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m6\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      4\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      5\u001b[0m \u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mhistogram\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mreview_counts_by_year\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mindex\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mreview_counts_by_year\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0malign\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'center'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mNameError\u001b[0m: name 'beer_reviews' is not defined"
     ]
    }
   ],
   "source": [
    "min_year, max_year = beer_reviews.review_time.min().year, beer_reviews.review_time.max().year\n",
    "\n",
    "plt.figure(figsize = (12, 6))\n",
    "\n",
    "plt.histogram(review_counts_by_year.index, review_counts_by_year, align='center')\n",
    "\n",
    "plt.title(\"Number of ratings per year\")\n",
    "plt.xlabel(\"Year\")\n",
    "plt.ylabel(\"Ratings\")\n",
    "plt.xticks(range(min_year, max_year + 1), rotation='vertical')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "review_time\n",
       "1     142123\n",
       "2     122020\n",
       "3     130983\n",
       "4     121689\n",
       "5     127503\n",
       "6     120425\n",
       "7     128448\n",
       "8     136001\n",
       "9     129376\n",
       "10    135975\n",
       "11    140558\n",
       "12    151513\n",
       "dtype: int64"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "review_counts_by_month = beer_reviews.groupby(beer_reviews.review_time.dt.month).size()\n",
    "review_counts_by_month"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x234824284e0>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (12, 6))\n",
    "\n",
    "plt.bar(review_counts_by_month.index, review_counts_by_month)\n",
    "\n",
    "plt.title(\"Number of ratings per month\")\n",
    "plt.xlabel(\"Month\")\n",
    "plt.ylabel(\"Ratings\")\n",
    "plt.xticks(range(1, 12 + 1))\n",
    "# plt.yscale(\"log\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "beer_reviews_by_day = beer_reviews.groupby(beer_reviews.review_time.dt.date).size()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Yordan\\Anaconda3\\lib\\site-packages\\pandas\\plotting\\_converter.py:129: FutureWarning: Using an implicitly registered datetime converter for a matplotlib plotting method. The converter was registered by pandas on import. Future versions of pandas will require you to explicitly register matplotlib converters.\n",
      "\n",
      "To register the converters:\n",
      "\t>>> from pandas.plotting import register_matplotlib_converters\n",
      "\t>>> register_matplotlib_converters()\n",
      "  warnings.warn(msg, FutureWarning)\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x234825701d0>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (15, 6))\n",
    "plt.plot(beer_reviews_by_day.index, beer_reviews_by_day)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "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",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>beer_beerid</th>\n",
       "      <td>1586614.0</td>\n",
       "      <td>21712.794279</td>\n",
       "      <td>21818.335997</td>\n",
       "      <td>3.00</td>\n",
       "      <td>1717.0</td>\n",
       "      <td>13906.0</td>\n",
       "      <td>39441.0</td>\n",
       "      <td>77317.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>brewery_id</th>\n",
       "      <td>1586614.0</td>\n",
       "      <td>3130.099202</td>\n",
       "      <td>5578.103987</td>\n",
       "      <td>1.00</td>\n",
       "      <td>143.0</td>\n",
       "      <td>429.0</td>\n",
       "      <td>2372.0</td>\n",
       "      <td>28003.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>beer_abv</th>\n",
       "      <td>1518829.0</td>\n",
       "      <td>7.042387</td>\n",
       "      <td>2.322526</td>\n",
       "      <td>0.01</td>\n",
       "      <td>5.2</td>\n",
       "      <td>6.5</td>\n",
       "      <td>8.5</td>\n",
       "      <td>57.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>review_overall</th>\n",
       "      <td>1586614.0</td>\n",
       "      <td>3.815581</td>\n",
       "      <td>0.720622</td>\n",
       "      <td>0.00</td>\n",
       "      <td>3.5</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.5</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>review_aroma</th>\n",
       "      <td>1586614.0</td>\n",
       "      <td>3.735636</td>\n",
       "      <td>0.697617</td>\n",
       "      <td>1.00</td>\n",
       "      <td>3.5</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>review_appearance</th>\n",
       "      <td>1586614.0</td>\n",
       "      <td>3.841642</td>\n",
       "      <td>0.616093</td>\n",
       "      <td>0.00</td>\n",
       "      <td>3.5</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>review_palate</th>\n",
       "      <td>1586614.0</td>\n",
       "      <td>3.743701</td>\n",
       "      <td>0.682218</td>\n",
       "      <td>1.00</td>\n",
       "      <td>3.5</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>review_taste</th>\n",
       "      <td>1586614.0</td>\n",
       "      <td>3.792860</td>\n",
       "      <td>0.731970</td>\n",
       "      <td>1.00</td>\n",
       "      <td>3.5</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.5</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       count          mean           std   min     25%  \\\n",
       "beer_beerid        1586614.0  21712.794279  21818.335997  3.00  1717.0   \n",
       "brewery_id         1586614.0   3130.099202   5578.103987  1.00   143.0   \n",
       "beer_abv           1518829.0      7.042387      2.322526  0.01     5.2   \n",
       "review_overall     1586614.0      3.815581      0.720622  0.00     3.5   \n",
       "review_aroma       1586614.0      3.735636      0.697617  1.00     3.5   \n",
       "review_appearance  1586614.0      3.841642      0.616093  0.00     3.5   \n",
       "review_palate      1586614.0      3.743701      0.682218  1.00     3.5   \n",
       "review_taste       1586614.0      3.792860      0.731970  1.00     3.5   \n",
       "\n",
       "                       50%      75%      max  \n",
       "beer_beerid        13906.0  39441.0  77317.0  \n",
       "brewery_id           429.0   2372.0  28003.0  \n",
       "beer_abv               6.5      8.5     57.7  \n",
       "review_overall         4.0      4.5      5.0  \n",
       "review_aroma           4.0      4.0      5.0  \n",
       "review_appearance      4.0      4.0      5.0  \n",
       "review_palate          4.0      4.0      5.0  \n",
       "review_taste           4.0      4.5      5.0  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "beer_reviews.describe().T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "beer_beerid           False\n",
       "brewery_id            False\n",
       "brewery_name           True\n",
       "review_profilename     True\n",
       "review_time           False\n",
       "beer_style            False\n",
       "beer_name             False\n",
       "beer_abv               True\n",
       "review_overall        False\n",
       "review_aroma          False\n",
       "review_appearance     False\n",
       "review_palate         False\n",
       "review_taste          False\n",
       "dtype: bool"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "beer_reviews.isna().any()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "beer_beerid           0.000000\n",
       "brewery_id            0.000000\n",
       "brewery_name          0.000945\n",
       "review_profilename    0.021934\n",
       "review_time           0.000000\n",
       "beer_style            0.000000\n",
       "beer_name             0.000000\n",
       "beer_abv              4.272306\n",
       "review_overall        0.000000\n",
       "review_aroma          0.000000\n",
       "review_appearance     0.000000\n",
       "review_palate         0.000000\n",
       "review_taste          0.000000\n",
       "dtype: float64"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "beer_reviews.isna().sum() / len(beer_reviews) * 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>beer_beerid</th>\n",
       "      <th>brewery_id</th>\n",
       "      <th>brewery_name</th>\n",
       "      <th>review_profilename</th>\n",
       "      <th>review_time</th>\n",
       "      <th>beer_style</th>\n",
       "      <th>beer_name</th>\n",
       "      <th>beer_abv</th>\n",
       "      <th>review_overall</th>\n",
       "      <th>review_aroma</th>\n",
       "      <th>review_appearance</th>\n",
       "      <th>review_palate</th>\n",
       "      <th>review_taste</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>273</th>\n",
       "      <td>21241</td>\n",
       "      <td>1075</td>\n",
       "      <td>Caldera Brewing Company</td>\n",
       "      <td>RedDiamond</td>\n",
       "      <td>2004-12-21 22:29:55</td>\n",
       "      <td>American Stout</td>\n",
       "      <td>Cauldron Espresso Stout</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>430</th>\n",
       "      <td>20689</td>\n",
       "      <td>850</td>\n",
       "      <td>Moon River Brewing Company</td>\n",
       "      <td>cMonkey</td>\n",
       "      <td>2005-03-13 17:48:30</td>\n",
       "      <td>Scotch Ale / Wee Heavy</td>\n",
       "      <td>The Highland Stagger</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.5</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.5</td>\n",
       "      <td>3.5</td>\n",
       "      <td>3.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>603</th>\n",
       "      <td>20689</td>\n",
       "      <td>850</td>\n",
       "      <td>Moon River Brewing Company</td>\n",
       "      <td>aracauna</td>\n",
       "      <td>2004-11-09 22:20:19</td>\n",
       "      <td>Scotch Ale / Wee Heavy</td>\n",
       "      <td>The Highland Stagger</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>3.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>733</th>\n",
       "      <td>54723</td>\n",
       "      <td>1075</td>\n",
       "      <td>Caldera Brewing Company</td>\n",
       "      <td>plaid75</td>\n",
       "      <td>2009-12-13 03:12:01</td>\n",
       "      <td>American IPA</td>\n",
       "      <td>Alpha Beta</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>798</th>\n",
       "      <td>42964</td>\n",
       "      <td>1075</td>\n",
       "      <td>Caldera Brewing Company</td>\n",
       "      <td>grumpy</td>\n",
       "      <td>2008-05-31 02:34:28</td>\n",
       "      <td>American Double / Imperial Stout</td>\n",
       "      <td>Imperial Stout</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     beer_beerid  brewery_id                brewery_name review_profilename  \\\n",
       "273        21241        1075     Caldera Brewing Company         RedDiamond   \n",
       "430        20689         850  Moon River Brewing Company            cMonkey   \n",
       "603        20689         850  Moon River Brewing Company           aracauna   \n",
       "733        54723        1075     Caldera Brewing Company            plaid75   \n",
       "798        42964        1075     Caldera Brewing Company             grumpy   \n",
       "\n",
       "            review_time                        beer_style  \\\n",
       "273 2004-12-21 22:29:55                    American Stout   \n",
       "430 2005-03-13 17:48:30            Scotch Ale / Wee Heavy   \n",
       "603 2004-11-09 22:20:19            Scotch Ale / Wee Heavy   \n",
       "733 2009-12-13 03:12:01                      American IPA   \n",
       "798 2008-05-31 02:34:28  American Double / Imperial Stout   \n",
       "\n",
       "                   beer_name  beer_abv  review_overall  review_aroma  \\\n",
       "273  Cauldron Espresso Stout       NaN             3.0           3.0   \n",
       "430     The Highland Stagger       NaN             3.5           4.0   \n",
       "603     The Highland Stagger       NaN             4.0           3.5   \n",
       "733               Alpha Beta       NaN             4.0           4.0   \n",
       "798           Imperial Stout       NaN             4.5           4.5   \n",
       "\n",
       "     review_appearance  review_palate  review_taste  \n",
       "273                3.0            4.0           3.0  \n",
       "430                4.5            3.5           3.5  \n",
       "603                4.0            3.5           3.5  \n",
       "733                4.0            4.0           4.0  \n",
       "798                4.0            4.0           4.5  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "beers_with_missing_abv = beer_reviews[beer_reviews.beer_abv.isnull()]\n",
    "beers_with_missing_abv.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total number of breweries: 5743\n",
      "Number of breweries with missing data for beer ABV: 2779\n"
     ]
    }
   ],
   "source": [
    "print(\"Total number of breweries: {}\".format(len(beer_reviews.brewery_name.unique())))\n",
    "print(\"Number of breweries with missing data for beer ABV: {}\".format(len(beers_with_missing_abv.brewery_name.unique())))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Timestamp('2012-01-11 06:35:37')"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "beers_with_missing_abv.review_time.max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "beers_with_known_abv = beer_reviews[~beer_reviews.beer_abv.isnull()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x234824ab080>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(beers_with_known_abv.beer_abv, bins = 30)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(beer_reviews[beer_reviews.beer_abv == 0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "LOW_ALCOHOL_THRESHOLD = 20\n",
    "beers_with_low_abv = beer_reviews[beer_reviews.beer_abv <= LOW_ALCOHOL_THRESHOLD]\n",
    "beers_with_high_abv = beer_reviews[beer_reviews.beer_abv > LOW_ALCOHOL_THRESHOLD]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2348506ef28>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(beers_with_high_abv.beer_abv)\n",
    "plt.show()"
   ]
  },
  {
   "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>beer_beerid</th>\n",
       "      <th>brewery_id</th>\n",
       "      <th>brewery_name</th>\n",
       "      <th>review_profilename</th>\n",
       "      <th>review_time</th>\n",
       "      <th>beer_style</th>\n",
       "      <th>beer_name</th>\n",
       "      <th>beer_abv</th>\n",
       "      <th>review_overall</th>\n",
       "      <th>review_aroma</th>\n",
       "      <th>review_appearance</th>\n",
       "      <th>review_palate</th>\n",
       "      <th>review_taste</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>12919</th>\n",
       "      <td>73368</td>\n",
       "      <td>6513</td>\n",
       "      <td>Schorschbräu</td>\n",
       "      <td>kappldav123</td>\n",
       "      <td>2011-09-23 12:28:21</td>\n",
       "      <td>Eisbock</td>\n",
       "      <td>Schorschbräu Schorschbock 57%</td>\n",
       "      <td>57.7</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       beer_beerid  brewery_id  brewery_name review_profilename  \\\n",
       "12919        73368        6513  Schorschbräu        kappldav123   \n",
       "\n",
       "              review_time beer_style                      beer_name  beer_abv  \\\n",
       "12919 2011-09-23 12:28:21    Eisbock  Schorschbräu Schorschbock 57%      57.7   \n",
       "\n",
       "       review_overall  review_aroma  review_appearance  review_palate  \\\n",
       "12919             4.0           4.0                4.0            4.0   \n",
       "\n",
       "       review_taste  \n",
       "12919           3.5  "
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "beer_reviews[beer_reviews.beer_abv == beer_reviews.beer_abv.max()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "7.0318344954258745"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "beers_with_low_abv.beer_abv.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    5.0\n",
       "dtype: float64"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "beers_with_low_abv.beer_abv.mode()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6.5"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "beers_with_low_abv.beer_abv.median()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.164489621689754"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "beers_with_low_abv.beer_abv.skew()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "56857"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(beer_reviews.beer_name.unique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "14110"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(beers_with_missing_abv.beer_name.unique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1207080      Almost Heaven Amber Ale\n",
       "981049                  Bayern Amber\n",
       "1092885            Frundsberg Dunkel\n",
       "1067137         Boscos London Porter\n",
       "585407     Chief Wawatam Steam Lager\n",
       "Name: beer_name, dtype: object"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "beers_with_missing_abv.beer_name.sample(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "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>beer_beerid</th>\n",
       "      <th>brewery_id</th>\n",
       "      <th>brewery_name</th>\n",
       "      <th>review_profilename</th>\n",
       "      <th>review_time</th>\n",
       "      <th>beer_style</th>\n",
       "      <th>beer_name</th>\n",
       "      <th>beer_abv</th>\n",
       "      <th>review_overall</th>\n",
       "      <th>review_aroma</th>\n",
       "      <th>review_appearance</th>\n",
       "      <th>review_palate</th>\n",
       "      <th>review_taste</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>98517</th>\n",
       "      <td>75763</td>\n",
       "      <td>27632</td>\n",
       "      <td>Aztec Brewing Company</td>\n",
       "      <td>HopHead84</td>\n",
       "      <td>2011-11-27 17:32:36</td>\n",
       "      <td>Baltic Porter</td>\n",
       "      <td>Eclipse</td>\n",
       "      <td>6.4</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>717336</th>\n",
       "      <td>28720</td>\n",
       "      <td>10193</td>\n",
       "      <td>Blindmans Brewery</td>\n",
       "      <td>wl0307</td>\n",
       "      <td>2006-03-03 01:54:26</td>\n",
       "      <td>English Porter</td>\n",
       "      <td>Eclipse</td>\n",
       "      <td>4.2</td>\n",
       "      <td>3.5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>3.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1249958</th>\n",
       "      <td>43459</td>\n",
       "      <td>944</td>\n",
       "      <td>Commonwealth Brewery Ltd.</td>\n",
       "      <td>wcudwight</td>\n",
       "      <td>2008-06-30 04:06:02</td>\n",
       "      <td>American Adjunct Lager</td>\n",
       "      <td>Eclipse</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.5</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>2.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1249968</th>\n",
       "      <td>43459</td>\n",
       "      <td>944</td>\n",
       "      <td>Commonwealth Brewery Ltd.</td>\n",
       "      <td>KeefD</td>\n",
       "      <td>2008-11-14 21:17:11</td>\n",
       "      <td>American Adjunct Lager</td>\n",
       "      <td>Eclipse</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1427497</th>\n",
       "      <td>61110</td>\n",
       "      <td>235</td>\n",
       "      <td>Northampton Brewery</td>\n",
       "      <td>MA08</td>\n",
       "      <td>2010-08-24 18:45:31</td>\n",
       "      <td>American Black Ale</td>\n",
       "      <td>Eclipse</td>\n",
       "      <td>4.9</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1427498</th>\n",
       "      <td>61110</td>\n",
       "      <td>235</td>\n",
       "      <td>Northampton Brewery</td>\n",
       "      <td>connecticutpoet</td>\n",
       "      <td>2010-08-17 03:08:52</td>\n",
       "      <td>American Black Ale</td>\n",
       "      <td>Eclipse</td>\n",
       "      <td>4.9</td>\n",
       "      <td>3.5</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>3.5</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         beer_beerid  brewery_id               brewery_name  \\\n",
       "98517          75763       27632      Aztec Brewing Company   \n",
       "717336         28720       10193          Blindmans Brewery   \n",
       "1249958        43459         944  Commonwealth Brewery Ltd.   \n",
       "1249968        43459         944  Commonwealth Brewery Ltd.   \n",
       "1427497        61110         235        Northampton Brewery   \n",
       "1427498        61110         235        Northampton Brewery   \n",
       "\n",
       "        review_profilename         review_time              beer_style  \\\n",
       "98517            HopHead84 2011-11-27 17:32:36           Baltic Porter   \n",
       "717336              wl0307 2006-03-03 01:54:26          English Porter   \n",
       "1249958          wcudwight 2008-06-30 04:06:02  American Adjunct Lager   \n",
       "1249968              KeefD 2008-11-14 21:17:11  American Adjunct Lager   \n",
       "1427497               MA08 2010-08-24 18:45:31      American Black Ale   \n",
       "1427498    connecticutpoet 2010-08-17 03:08:52      American Black Ale   \n",
       "\n",
       "        beer_name  beer_abv  review_overall  review_aroma  review_appearance  \\\n",
       "98517     Eclipse       6.4             4.0           4.0                4.0   \n",
       "717336    Eclipse       4.2             3.5           4.5                4.0   \n",
       "1249958   Eclipse       NaN             2.5           3.0                2.0   \n",
       "1249968   Eclipse       NaN             4.0           2.5                3.0   \n",
       "1427497   Eclipse       4.9             4.0           3.0                2.5   \n",
       "1427498   Eclipse       4.9             3.5           3.0                3.5   \n",
       "\n",
       "         review_palate  review_taste  \n",
       "98517              4.0           4.0  \n",
       "717336             3.5           3.5  \n",
       "1249958            2.5           2.5  \n",
       "1249968            4.0           3.0  \n",
       "1427497            3.0           4.0  \n",
       "1427498            3.5           3.0  "
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "beer_reviews[beer_reviews.beer_name == \"Eclipse\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "66055"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(beer_reviews.beer_beerid.unique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "beer_style\n",
       "American IPA                        117586\n",
       "American Double / Imperial IPA       85977\n",
       "American Pale Ale (APA)              63469\n",
       "Russian Imperial Stout               54129\n",
       "American Double / Imperial Stout     50705\n",
       "American Porter                      50477\n",
       "American Amber / Red Ale             45751\n",
       "Belgian Strong Dark Ale              37743\n",
       "Fruit / Vegetable Beer               33861\n",
       "American Strong Ale                  31945\n",
       "dtype: int64"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top_beer_styles = beer_reviews.groupby(\"beer_style\").size().sort_values(ascending = False).head(10)\n",
    "top_beer_styles"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAhMAAAEWCAYAAADchhUKAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvNQv5yAAAIABJREFUeJzs3XmYHWWd9//3J4GEJSvrtAykIQYwkphdYgDDIoKigERJGx1QEBkHgjjI4A8XIjyKMPOwDIjE/NhmkEUDijCGIJtsknTWTiIwQsJgBkUkNBBihOT7/FH3IZXDOX26+/TpTnc+r+vqq+vcda9VgfrWXffpUkRgZmZm1l69uroDZmZm1r05mDAzM7OqOJgwMzOzqjiYMDMzs6o4mDAzM7OqOJgwMzOzqjiYMDPrYpJ+K+lzXd0Ps/ZyMGFmPYakN3I/GyWty32e1sFtTZP0RGpjTon94yUtlvSmpHmSDujI9s22JA4mzKzHiIh+hR/gf4BP5NJu7uDm/gL8G/B/i3dI2h74BTATGAz8FLhT0jYd3Ic26er2redyMGFmWw1J20u6WtKLkv4g6VJJ26Z9R0n6vaQZkl6R9JykT5erKyLmRMTPgBdL7P4I8NeI+GFErCcLOvoDB7XQvf0kLZDULGm2pIG5fh8s6UlJr0paKGlSbt9Okm6S9EdJL0j6jqRead/pkh5IY14DnCdpf0mPpnb+LOmmthxDs1IcTJjZ1mQGMBIYAYwFJgPn5vbXA32AvwNOA26UtHc72nk/sKTwISI2AstSejn/AEwD9kh9+DcASfXAz4HzgZ2AbwI/lzQ4lbsZaAb2ASYAxwGfz9V7CLAY2CXV+f1U3yBgL+DadozPbDMOJsxsazIN+E5EvBwRfwIuYvML79vAjIj4W0T8Gvg1MKUd7fQju8DnNZPNTpRzfUQ8FRFvAN8BGlL6ScAdEfHriNgYEf8FrACOlDSELFj4WkS8GREvAlcCU3P1PhcRP46IDRGxDniLLGj6u4hYFxGPtWN8ZptxMGFmWwVJIptxeD6X/DzZTEDBnyPir0X739OO5t4ABhSlDQBeb6HMC0Xt7pAedQwBPpcecbwq6VVgXOrXEGA74M+5fVcAu5epF+BsYAdgkaSl/haJdQQHE2a2VYjsFcl/JLsAF+wFrM593kXSdkX7/7cdzS0HPlD4kNYwHJDSy9mzqN03I6KZLBiYFRGDcj87RsRlad8bwODcvgERMSZX12avho6I1RHxRaAOmA5cJ2mvdozR7B0OJsxsa3IL8B1JO0vajWwdwn/m9m8LfEtSH0mHkS2knF2qIkm9U+CxDdBL0na5b0vcB2yfFkD2JZsNWAs82kLfTpa0r6R+wAXAbSn9RuDTkg5PbW6ftv8uIlYCvwUukdRfUi9JwySVXegp6URJ70nB1asp+e0W+mVWkYMJM9uafJtsvcFyskWJjwGX5PavIruw/hG4DvhCRDxXpq4vAeuAy8iCjnXAVQBpbcKxwOlkF+ypwHER0dJF+z/Igp3VwEbgn1NdzwEnkC0efZnsEchZbPr/dwPZYsqngFfIgpD8Y45iE4EFkt4g+8rqaRHRntkXs3coC07NzLZuko4CroqI93Z1X8y6G89MmJmZWVUcTJiZmVlV/JjDzMzMquKZCTMzM6uKX/piPcouu+wS9fX1Xd0NM7NuZcGCBS9HxK7tLe9gwnqU+vp6Ghsbu7obZmbdiqTnK+cqz485zMzMrCoOJszMzKwqDibMzMysKg4mzMzMrCoOJszMzKwqDibMzMysKg4mzMzMrCoOJszMzKwq/qNV1qM0rW6m/rx7urobZmadatXFH+/S9j0zYWZmZlVxMGFmZmZVcTBhZmZmVXEwYWZmZlVxMNENSTpeUkjav4ZtjJN0ZQ3rnyzp7rR9sqQ/S1osaYWkLxXl/YWkJ2rVFzMzq46Die6pAXgUmFqLyiVtExGNETG9FvWXcVtEjAImA9+TtHvqyyBgDDBI0t6d2B8zM2slBxPdjKR+wCTgFHLBRLrTf1jS7ZKekXSxpGmS5klqkjQ05dtV0mxJ89PPpJR+gaSZkuYCNxXNHPSTdH2qZ6mkE1L6NZIaJS2XNCPXl1WSZkhamMq0egYlIl4CngWGpKQTgF8Ct1Kj4MnMzKrjYKL7OQ6YExHPAK9IGpPb9wHgLGAE8Hlg34iYAMwCzkx5rgAui4jxZBfqWbnyY4FjI+KzRW1+C2iOiBERMRJ4IKWfHxHjgJHAhyWNzJV5OSLGANcA57R2cJL2AfYBfp+SGoBb0k9DmTKnpaCmccObza1tyszMOoj/aFX30wBcnrZvTZ8Xps/zI+JFAEnPAnNTehNwaNo+AhguqVDfAEn90/ZdEbGuRJtHkJsViIg1afMzkk4j+3dUBwwHlqZ9d6TfC4BPtWJcJ0o6CFgPfDkiXkmPOt4LPBoRIeltSQdExLJ8wYiYCcwE6Fs3LFrRlpmZdSAHE92IpJ2Bw4ADJAXQGwhJ56Ys63PZN+Y+b2TTue4FTCwOGlJwsbZc08BmF+m0fuEcYHxErJF0A7BdLkuh7Q207t/ZbRFxRlHaicBgYGXq3wCyoOabrajPzMw6iR9zdC9TgJsiYkhE1EfEnsBK4KA21DEXeOeiLWlUO8oMJruwrwWa0wzC0W3oQ2s1AEelsdaTPYbxugkzsy2Mg4nupQG4syhtNlC8xqEl04FxaSHlCuD0VpS5CBgsaZmkJcChEbEEWAQsB64DHmtDHyqSVA/sBfy2kBYRK4HXJH2wI9syM7PqKMKPmK3n6Fs3LOpOurxyRjOzHqTaF31JWpAW1LeLZybMzMysKg4mzMzMrCr+Nof1KCP2GEhjldN9ZmbWNp6ZMDMzs6o4mDAzM7OqOJgwMzOzqnjNhPUoTaubqT/vnq7uhpmVUe1XGG3L5JkJMzMzq4qDCTMzM6uKgwkzMzOrioMJMzMzq0qHBxOSjpcUkvbv6LpzbYyTdGUN658sqVnSIklPS/qNpGOqrO/uMvtWSdqljfU1SDq/tW3USmvOQ7l+5dMlnSzpz5IWS1oh6UtFeX8h6YmO7b2ZmXWUWsxMNACPUqNXRUvaJiIaI2J6LerPeSQiRkfEfmRv2rxK0uE1brO1jgLmdGUHanAebouIUcBk4HvpteZIGgSMAQZJ2ruD2jIzsw7UocGEpH7AJOAUcsFEugt9WNLtkp6RdLGkaZLmSWqSNDTl21XSbEnz08+klH6BpJmS5gI3Fd3V9pN0fapnqaQTUvo1kholLZc0I9eXVZJmSFqYylScQYmIxcB3gTNSHUMk3Z/au1/SXin9BklTcm29katmgKQ70533jyS969hL+lw6JoslXSupd4k8AkYBC1s4DxdIulHS3DTeT0m6JI13jqRtc8fiB6nNeZLeW8V5mCDp8TSb87ik/Sod11Ii4iXgWWBISjoB+CVwKzUKUM3MrDodPTNxHDAnIp4BXpE0JrfvA8BZwAjg88C+ETEBmAWcmfJcAVwWEePJLiKzcuXHAsdGxGeL2vwW0BwRIyJiJPBASj8/vU51JPBhSSNzZV6OiDHANcA5rRzbQqAQeFwF3JTauxlozSOXCcA/k41/KPCp/E5J7wNOBCalO/QNwLQS9YwGlkTld8cPBT4OHAv8J/BgRIwA1qX0gtfSebgKKLy7uz3n4SngkIgYDXwb+F6F/pUkaR9gH+D3KakBuCX9NJQpc1oKHBs3vNncnmbNzKwKHf1HqxrYdEG6NX0u3EHPj4gXASQ9C8xN6U3AoWn7CGB4dvMNZHfz/dP2XRGxrkSbR5C7Y42INWnzM5JOIxtjHTAcWJr23ZF+L6Doot4C5bYn5sr9B3BJK8rPi4jnACTdAhwE/Cy3/3CyC/X8NP7tgZdK1HMU8KtWtPeriHhLUhPQm02PRZqA+ly+W3K/L0vb7TkPA4EbJQ0DAti2FX3MO1HSQcB64MsR8Up61PFe4NGICElvSzogIpblC0bETGAmQN+6YZWCLDMz62AdFkxI2hk4DDhAUpBdwELSuSnL+lz2jbnPG3P96AVMLL5YpYva2nJNk1288vn3JptxGB8RayTdAGyXy1JoewOtPwajgd+V2Vdo/23SbE96HNGnRJ5ynwXcGBHfqNCPI8lmCypZDxARGyW9lZvJyB/v4n4UtttzHi4km/04XlI98FAr+ph3W0ScUZR2IjAYWJnaHkAWOH6zjXWbmVkNdeRjjilkU/9DIqI+IvYEVpLdgbfWXNK6BABJo9pRZjDZRWct0Jzubo9uQx/eJT0i+RZwdUp6nE2zIdPIFpwCrCKbXYDs8UL+7nyCpL3TWokTc2UK7gemSNottbmTpCH5DJIGAttExF+qGU+RE3O/C9+YaM95GAisTtsnd1DfGoCj0r+nerJj63UTZmZbmI4MJhqAO4vSZgPFz9ZbMh0YlxY2rgBOb0WZi4DBkpZJWgIcGhFLgEXAcuA64LE29KHg4LSY8GmyIGJ6RNyf6+cXJC0lW/9xVkr/Mdn6jHnAB9n8Lv4J4GJgGVmQtdmxiogVZHfcc1O995E9nsn7CPDrdoylJX0lPZnGcHZKa895uAT4vqTHyGalqpJmN/YCfltIi4iVwGuSPlht/WZm1nFUeR2fbSkkzQJmRcRvK2ZuXX2rgHER8XJH1Lcl6Fs3LOpOurxyRjPrEn7R15ZJ0oL0pYV28VtDu5GIOLWr+2BmZlbMwcRWLK1DMDMzq4rfzWFmZmZV8cyE9Sgj9hhIo5/Jmpl1Ks9MmJmZWVUcTJiZmVlVHEyYmZlZVbxmwnqUptXN1J93T1d3w6xV/DcXrKfwzISZmZlVxcGEmZmZVcXBhJmZmVXFwYSZmZlVpccGE5KOlxSS9q9hG+MkXVnD+idLak5vL/2dpO9UyF8vaVk72nnXsWpPXZK2l/SwpN65tLMl/TW9Pr2Q1uK4JF0haXV6XXsh7RhJM9o6NjMzq70eG0yQvRL9UWBqLSqXtE1ENEbE9FrUn/NIRIwGxgGfkzS2Bm101LH6InBHRGwoqns+cHxR3pLjSgHE8cALwCG5/PcAn5S0Q5V9NDOzDtYjgwlJ/YBJwCnkLpDpjvhhSbdLekbSxZKmSZonqUnS0JRvV0mzJc1PP5NS+gWSZkqaC9yU6ru70Kak61M9SyWdkNKvkdQoaXn+zlrSKkkzJC1MZVqcQYmItcACYGiaNXgklV0o6UMljkFvSZem/i+V9OW2HKv21AVMA36RKzcU6Ad8kyyoaHFcKelQYBlwTb5MRATwEHBMmbbNzKyL9MhgAjgOmBMRzwCvSBqT2/cB4CxgBPB5YN+ImADMAs5Mea4ALouI8cAJaV/BWODYiPhsUZvfApojYkREjAQeSOnnp3fEjwQ+LGlkrszLETGG7MJ5TksDkrQzcCCwHHgJ+EgqeyJQ6lHLKak/44HxwJck7V0iX0vHqtV1SeoD7BMRq3LJDcAtwCPAfpJ2qzCufJk7gWMkbZvL3ggcXKKO01LA1rjhzeYS3Tczs1rqqcFEA3Br2r6Vze+K50fEixGxHngWmJvSm4D6tH0EcJWkxcBdwABJ/dO+uyJiXYk2jwCuLnyIiDVp8zOSFgKLgPcDw3Nl7ki/F+TaLnawpEWpnxdHxHJgW+DHkpqAnxbVWXAk8A9pDE8COwPDSuRr6Vi1pa5dgFeL0qYCt0bERrKxfrqlcaWA5GPAzyPitdTWkbkyLwHvKe5cRMyMiHERMa73DgOLd5uZWY31uL+Ame50DwMOkBRAbyAknZuyrM9l35j7vJFNx6MXMLE4aJAEsLZc00AU5d+bbMZhfESskXQDsF0uS6HtDZQ/F49ERPHU/tnAn8hmWXoBfy3TnzMj4t4y9bbmWLW6LmAdubGlGZhhwH3puPUBnmNTwFVqXEcBA4GmVGYH4E2y9RKk+ksFcmZm1oV64szEFOCmiBgSEfURsSewEjioDXXMBc4ofJA0qh1lBgMDyIKPZkm7A0e3oQ8tGQi8mO74P08WBBS7F/jHwmMCSftK2rEoT2uPVcW60kxMb0mFgKIBuCDVWx8R7wH2kDSkhXE1AKcWygB7A0fmFl3uS7aewszMtiA9MZhoIHvenjcbKF7j0JLpwLi02HAFcHorylwEDJa0TNIS4NCIWEL2eGM5cB3wWBv60JIfAidJ+i3ZBbbUbMksYAWwMH3F81rePfvR2mPVmrogC6gKgcjUEnXfSflFnjsAH2XTLERhceajwCdS0qH5/WZmtmVQtkjerHqSRgNfi4jP16Du3YGfRMThLeXrWzcs6k66vKObN6sJv+jLthSSFqQvC7RLT5yZsC4SEYuAB5X7o1UdaC/gn2tQr5mZVanHLcC0rhUR19Wo3vm1qNfMzKrnYMJ6lBF7DKTRU8dmZp3KjznMzMysKg4mzMzMrCoOJszMzKwqXjNhPUrT6mbqz/OforDq+WubZq3nmQkzMzOrioMJMzMzq4qDCTMzM6uKgwkzMzOrylYbTEjaIGlxejHXLyUN6sC6x0m6soPqekhSu/9eejvbnCVpeIU8Jfsl6RhJiyQtkbRC0pdT+nGV6qzQ3ihJH2tveTMzq52tNpgA1kXEqIg4AHgF+KeOqjgiGiNiekfV15kk9Y6IUyNiRTvKbgvMBD4RER8ARgMPpd3HAe0OJoBRgIMJM7Mt0NYcTOQ9AewBIGmypLsLOyRdJenktH1xutteKulfU9qnC68dl/Sb4jokTZD0eLpbf1zSfin9ZEl3SJoj6b8lXVKpk5LekPQDSQsk/TrV/ZCk5yR9MlfvL1K9T0v6Tq785yTNSzMy1xZeyJXq/a6kJ4GJ+VkHSddIapS0XNKMCl3sT/Z1478ARMT6iHha0oeATwKXpraHppmG36Zjeaekwam9fNu7SFolqQ/wXeDEVP7ESsfKzMw6z1YfTKQL6uHAXRXy7QQcD7w/IkYCF6Vd3wY+mu7EP1mi6FPAIRExOuX9Xm7fKOBEYATZhXLPCt3dEXgoIsYCr6c+fCT167u5fBOAaan+T6fHLu9LbU2KiFHAhpSnUO+yiPhgRDxa1Ob56bW0I4EPSxpZrnMR8QrZcXxe0i2SpknqFRGPp/Svp9mgZ4GbgH9Jx7IJ+E4L9f6N7Njdlsrflt8v6bQU8DRueLO5XDVmZlYjW/Mfrdpe0mKgHlgA3Fch/2vAX4FZku4BCrMXjwE3SLoduKNEuYHAjZKGAQFsm9t3f0Q0A0haAQwBXmihD38D5qTtJmB9RLwlqSmNo+C+iPhLqvcO4CDgbWAsMF8SwPbASyn/BmB2mTY/I+k0sn8rdWSPKpaW62BEnCppBHAEcA5ZsHNyPo+kgcCgiHg4Jd0I/LSFcbcoImaSPV6hb92waG89ZmbWPlvzzMS6dIc+BOjDpjUTb7P5cdkOICLeJrvjn032/H9OSj8d+CawJ7BY0s5F7VwIPJjWZnyiUF+yPre9gcrB3VsRUbhYbiyUj4iNRWWLL6gBCLgx3dmPioj9IuKCtP+vEbGhuDFJe5MFBIenGYR7ivpfUkQ0RcRlZIHECZXyF8kf/4ptmZlZ19uagwkA0szAdOCctIDweWC4pL7pDvpwAEn9gIER8V/AV8keISBpaEQ8GRHfBl4mCyryBgKr0/bJtR5P8hFJO0nanizweQy4H5giaTfIHttIGlKhngHAWqBZ0u7A0S1lltRP0uRc0iiy4wnZY5n+8M4xXyPp4LTv80BhlmIV2QwKwJRcXe+UNzOzLctWH0wARMQiYAkwNSJeAG4nm8q/GViUsvUH7pa0lOzCd3ZKv1RSk6RlwG9SPXmXAN+X9BjQu7YjecejwH8Ai4HZ6dslK8hmUOamMdxH9tiirIhYQjb+5cB1ZEFJSwScmxZ+LgZmsCmAuhX4elqIOhQ4iezYLSULOgprPv4V+EdJjwO75Op+kCzI8wJMM7MtjDbNmltPkL55Mi4izujqvnSFvnXDou6ky7u6G9YD+EVftjWRtCAttm8Xz0yYmZlZVbbmb3P0SBFxA3BDF3fDzMy2Ig4mrEcZscdAGj09bWbWqfyYw8zMzKriYMLMzMyq4mDCzMzMquI1E9ajNK1upv68e7q6G7aF89c+zTqWZybMzMysKg4mzMzMrCoOJszMzKwqDibMzMysKq0KJiQdLykk7V+rjkgaJ+nKGtY/WVJzetHU05J+I+mYKuu7u8y+VZJ2KbWvhfoaJJ3f2jZqpTXnoVy/JO0g6ebCi88kPZreJDpI0leq7NdXJe1QTR1mZlYbrZ2ZaCB7E+XUWnRC0jbpzZbTa1F/ziMRMToi9iN77fhVkg6vcZutdRQwpys70AHn4SzgTxExIiIOAE4B3gIGAVUFE2SvfXcwYWa2BaoYTEjqB0wiuzBMzaVPlvSwpNslPSPpYknTJM1Ld6ZDU75dJc2WND/9TErpF0iaKWkucFP+bjfdzV6f6lkq6YSUfo2kRknLJc3I9WWVpBmSFqYyFWdQImIx2Wuvz0h1DJF0f2rvfkl7pfQbJE3JtfVGrpoBku6UtELSjyS963hK+lw6JoslXSvpXa8hlySy13AvbOE8XCDpRklz03g/JemSNN45krbNHYsfpDbnSXpvFedhgqTH02zO45L2q3BY64DVuWP8dESsBy4GhqZjcKkyl6bZiyalV4oXz3hIukrSyZKmA+8BHpT0YIU+mJlZJ2vNzMRxwJyIeAZ4RdKY3L4PkN2NjgA+D+wbEROAWcCZKc8VwGURMR44Ie0rGAscGxGfLWrzW0BzusMdCTyQ0s9Pr0gdCXxY0shcmZcjYgxwDXBOK8YF2cW7EHhcBdyU2rsZaM0jlwnAP5ONfyjwqfxOSe8DTgQmRcQoYAMwrUQ9o4ElUfl98EOBjwPHAv8JPBgRI4B1Kb3gtXQergIK7+Nuz3l4CjgkIkYD3wa+V6F/1wH/IukJSRdJGpbSzwOejYhREfF1suM0iuzfzxHApZLqylUaEVcC/wscGhGHFu+XdFoKMhs3vNlcoYtmZtbRWvNHqxrYdEG6NX0u3EHPj4gXASQ9C8xN6U1A4X/6RwDDs5tvILub75+274qIdSXaPILcLEhErEmbn5F0Wup3HTAcWJr23ZF+L6Doot4C5bYn5sr9B3BJK8rPi4jnACTdAhwE/Cy3/3CyC/X8NP7tgZdK1HMU8KtWtPeriHhLUhPQm02PRZqA+ly+W3K/L0vb7TkPA4EbU1AQwLYtdS4iFkvaBzgytTdf0kSyYCfvIOCWiNgA/EnSw8B44LWW6m+h3ZnATIC+dcMqBWRmZtbBWgwmJO0MHAYcICnILmAh6dyUZX0u+8bc5425unsBE4svVumitrZc02QXr3z+vclmHMZHxBpJNwDb5bIU2t5QaVw5o4HfldlXaP9t0gxOehzRp0Secp8F3BgR36jQjyPJZgsqWQ8QERslvZWbycgf7+J+FLbbcx4uJJv9OF5SPfBQpQ5GxBtkgd0dkjYCHwNmF2XTuwpm3jnWyXZl8pmZ2Rak0mOOKWRT/0Mioj4i9gRWkt1ZttZc0roEAEmj2lFmMDCA7KLXLGl34Og29OFd0iOSbwFXp6TH2TQbMo1swSnAKrLZBcgeL+TvzidI2jutlTgxV6bgfmCKpN1SmztJGlLUj4HANhHxl2rGU+TE3O8n0nZ7zsNANq2BOLlSZkmT0rlCUh+ymaPngdeB/rmsvwFOlNRb0q7AIcC8lHe4pL7puOQXxxbXYWZmW4hKwUQDcGdR2myg+Nl6S6YD49LCxhXA6a0ocxEwOC3QW0L2rHwJsAhYTvZs/rE29KHg4LSY8GmyIGJ6RNyf6+cXJC0lW/9xVkr/Mdn6jHnAB9n8Lv4JssWFy8iCrM2OVUSsAL4JzE313kf2eCbvI8Cv2zGWlvSV9GQaw9kprT3n4RLg+5IeI5uVqmQo8HB6DLMIaARmp0DpsXQ+LyU7TkuBJWTrYc6NiD9GxAvA7WnfzamOgpnAr7wA08xsy6PKa/6sliTNAmZFxG87qL5VwLiIeLkj6utu+tYNi7qTLq+c0bZqftGX2eYkLUhfcGgXvzW0i0XEqV3dBzMzs2o4mOhhIqK+q/tgZmZbFwcT1qOM2GMgjZ7CNjPrVH7Rl5mZmVXFwYSZmZlVxcGEmZmZVcVrJqxHaVrdTP1593R1N2wL5q+FmnU8z0yYmZlZVRxMmJmZWVUcTJiZmVlVHEyYmZlZVRxMdBFJx0sKSfvXsI1xkq6sYf2TJTWnl6f9TtJ32li+XlJbXhpnZmZbIAcTXaeB7JXlUytlbA9J20REY0RMr0X9OY9ExGhgHPA5SWMrFYCsf0A9bXsDLZJa8/ZSMzPrRA4muoCkfsAk4BRywUS6039Y0u2SnpF0saRpkuZJapI0NOXbVdJsSfPTz6SUfoGkmZLmAjel+u4utCnp+lTPUkknpPRrJDVKWi5pRq4vqyTNkLQwlWlxBiUi1gILgKGStsu1tUjSoanOkyX9VNIvgblkr28/WNJiSWdL6i3p0jSmpZK+nDsuD0r6CdDUMWfBzMw6iv/ORNc4DpgTEc9IekXSmIhYmPZ9AHgf8ArwHNnrySdIOgs4E/gqcAVwWUQ8Kmkv4N5UBmAscFBErJM0Odfmt4DmiBgBIGlwSj8/Il5Jd/z3SxoZEUvTvpcjYoykrwDnAGXfcCppZ+BA4ELgnwAiYkQKQuZK2jdlnQiMTG1OBs6JiGNSHaelPo6X1Bd4LAVGABOAAyJiZYm2TwNOA+g9YNdyXTQzsxpxMNE1GoDL0/at6XMhmJgfES8CSHqW7A4esjvyQ9P2EcBwSYX6Bkjqn7bvioh1Jdo8gtwsSESsSZufSRfjbYA6YDhQCCbuSL8XAJ8qM5aDJS0CNgIXR8RySRcB/57aeUrS80AhmLgvIl4pU9eRwEhJU9LngcAw4G/AvFKBRGpjJjAToG/dsChTt5mZ1YiDiU6W7uAPAw6QFEBvICSdm7Ksz2XfmPu8kU3nqxcwsThoSMHF2nJNA5tdaCXtTTbjMD4i1ki6Adgul6XQ9gbK/1t5pDCzUNRWOeX6Vyh3ZkTcW9TPyRXKmZlZF/Kaic43BbgpIoZERH1E7AmsBA5qQx1zgTMKHySNakeZwcAAsot0s6TdgaPb0IeW/AaYltrZF9gLeLpEvteB/rnP9wL/KGnbQllJO3ZQn8zMrEbq6j31AAAeFklEQVQcTHS+BuDOorTZtO1bDdOBcWmR4grg9FaUuQgYLGmZpCXAoRGxBFgELAeuAx5rQx9a8kOgt6Qm4Dbg5IhYXyLfUuBtSUsknQ3MAlYACyUtA67Fs2dmZls8RfgRs/UcfeuGRd1Jl1fOaFstv+jL7N0kLYiIce0t75kJMzMzq4qDCTMzM6uKn0dbjzJij4E0ehrbzKxTeWbCzMzMquJgwszMzKriYMLMzMyq4jUT1qM0rW6m/rx7urob1kn8NU+zLYNnJszMzKwqDibMzMysKg4mzMzMrCoOJszMzKwq3S6YkHS8pJC0fw3bGCfpylrVn2vnCkmrJbX5PEhaJWmXDu7PHEl7FKXdIGmlpMXphVyHt7HO+vTSrnL7z5b0V0kDc2mTJd3d9hGYmVlX6HbBBNlbNx8FptaicknbRERjREyvRf25dnoBxwMvAIfUsq0Sbb/rWzyStgd2iojVJYp8PSJGAV8FftTB3WkA5pMdCzMz64a6VTAhqR8wCTiFXDCR7mQflnS7pGckXSxpmqR5kpokDU35dpU0W9L89DMppV8gaaakucBN+TtjSf0kXZ/qWSrphJR+jaRGScslzcj1ZZWkGZIWpjLlZlAOBZYB15BdUAvlL5B0o6S5qa5PSbok1TVH0ra5Or6exjhP0nvbMsYS/ZkMPFThFDwBvDNzIWlsOu4LJN0rqS6XvkTSE8A/lassnZd+wDfzx6Aoz46SrktjWSTp2Ap9NDOzTtatggngOGBORDwDvCJpTG7fB4CzgBHA54F9I2ICMAs4M+W5ArgsIsYDJ6R9BWOBYyPis0VtfgtojogRETESeCCln59e1zoS+LCkkbkyL0fEGLJA4ZwyY2kAbgHuBI4pChKGAh8HjgX+E3gwIkYA61J6wWtpjFcBhfdut2eMAEcDc8r0teAo4OcAqb//DkyJiLHAdcD/SfmuB6ZHxMQK9RWOwSPAfpJ2K5HnfOCBNJ5DgUsl7ZjPIOm0FNg1bnizuUKTZmbW0brbH61qYNNF89b0eWH6PD8iXgSQ9CwwN6U3kV2EAI4Ahksq1DdAUv+0fVdErCvR5hHkZkEiYk3a/Iyk08iOYR0wHFia9t2Rfi8APlVcoaQ+wMeAsyPidUlPAkcChb+29KuIeEtSE9CbTRf5JqA+V9Utud+XVTFGyGZ8ygU+l0q6BNgNODCl7QccANyX2uoNvJjWPgyKiIdTvv8gC1RKmQocHxEbJd0BfBq4uijPkcAnJRX6th2wF/C7QoaImAnMBOhbNyzKtGVmZjXSbYIJSTsDhwEHSAqyi1dIOjdlWZ/LvjH3eSObxtkLmFh8QU0Xw7XlmgY2u0BJ2pvswjs+ItZIuoHsIldQaHsDpY/xUcBAoCm1vQPwJpuCifUA6SL7VkQU2s+PhaJ+FbbbPEZJ+wAvRMTfSu0Hvk4WIE0HbiSb4RCwvHj2QdKgon6VlGZyhrEpGOkDPMe7gwkBJ0TE05XqNDOzrtGdHnNMAW6KiCERUR8RewIrgYPaUMdc4IzCB0mj2lFmMDCA7MLcLGl3yt95l9MAnJrGUQ/sDRwpaYc21nNi7vcTZfrbmjFWfMQRERvJHqH0kvRR4GlgV0kTUzvbSnp/RLxKdlwK52VamSobgAsKxyAi3gPsIWlIUb57gTOVIg5Jo1sxHjMz60TdKZhoIFtfkDcbKPX8v5zpwLi0kHIFcHorylwEDJa0TNIS4NCIWAIsApaTrRV4rLUdSAHDR9k0C0FErCX7hsonWj2STN/0iOQs4OyU1p4xHkXl9RKkGZKLgHPTLMYU4AfpuCwGPpSyfgG4Oi3ALPdYZSrvPp938u5v6VwIbAssVfYV0wsrD8fMzDqTNs2g29ZIUl/gsbSYtNvrWzcs6k66vHJG6xH8oi+zjiFpQTXXgW6zZsJqIyLWAz0ikDAzs67RnR5zmJmZ2RbIMxPWo4zYYyCNnvo2M+tUnpkwMzOzqjiYMDMzs6o4mDAzM7OqeM2E9ShNq5upP++eyhmt0/lrnGY9l2cmzMzMrCoOJszMzKwqDibMzMysKg4mzMzMrCo9OpiQtEHSYklLJC2U9KFWlHmjFXlmSRreAf3bQdLNkprSi8QeldRP0iBJX6m2/nb0p17SOkmLJP1O0jxJJ7WjnsmS7m5l3iskrZbUK5d2sqSr2tqumZl1jZ7+bY51ETEKIL02+/vAh6utNCJOrbaO5CzgTxExAkDSfsBbwC7AV4AfFheQ1DsiNnRQ+6U8GxGjU1v7AHdI6hUR17emsKRW/5tKAcTxwAvAIcBDbe+umZl1tR49M1FkALCm8EHS1yXNT6/qnlGcWVIvST+UtFzS3ZL+S9KUtO8hSePS9jWSGlO+GbnyqyTNSDMiTZL2L9GnOmB14UNEPJ1evHUxMDTNqlya7vQflPQToCnV/7U0m7FM0ldTWn2aUfhx6s9cSdunfePTWJ9IdS6rdMAi4jnga2SvNUfSBEmPp5mLx1PwU5hJ+KmkXwJzi47j+JR/nxJNHAosA64he8X8u0jaVdLsdK7mS5pUqd9mZta5enowsX26ID8FzAIuBJB0JDAMmACMAsZKOqSo7KeAemAEcCowsUwb56fXto4EPixpZG7fyxExhuxieU6JstcB/5Iu8BdJGpbSzyObIRgVEV9PaRNSW8MljQW+AHwQOBD4kqTRKd8w4OqIeD/wKnBCSr8eOD0iJgJtmdlYCBQCoaeAQ9LMxbeB7+XyTQROiojDCgnpsdKPgGNTYFKsAbgFuBM4RtK2JfJcAVwWEePTWGa1oe9mZtYJenowsS5dkPcHjgJukiTgyPSziE0Xy2FFZQ8CfhoRGyPij8CDZdr4jKSFqa73A/m1FHek3wvIApPNRMRiYB/gUmAnYL6k95VpZ15ErMz17c6IWBsRb6R2Dk77VqZ632lX0iCgf0Q8ntJ/UqaNUpTbHgj8NM1qXEY23oL7IuKV3Of3ATOBT0TE/7yrUqkP8DHg5xHxGvAk2TkpdgRwlaTFwF3AAEn9i+o6Lc0ONW54s7kNQzMzs47Q09dMvCMinpC0C7Ar2QXy+xFxbQtF1MK+LIO0N9mMw/iIWCPpBmC7XJb16fcGyhzrXDBwh6SNZBfY2SWyrm1l39bntjcA21fIX8lo4Hdp+0LgwYg4XlI9m69xWLt5MV4kOxajgf8tUe9RZMFJUxbfsQPwJlD85yt7ARMjYl25DkbETLLAhb51w6LSgMzMrGP19JmJd6Q1C72BvwD3Al+U1C/t20PSbkVFHgVOSGsndgcml6h2ANlFtDnlObqNfZokaXDa7kM2q/E88DrQv4WivwGOS98G2ZFsEeMj5TJHxBrgdUkHpqSprexfPfCvwL+npIFsWuNxcoXirwIfB74naXKJ/Q3AqRFRHxH1wN7AkZJ2KMo3Fzgj16dRrem7mZl1np4+M7F9mh6H7O78pPRNiLnpccIT6a74DeBzwEu5srOBw8kWCD5DNg2/2Rx6RCyRtAhYDjwHPNbG/g0FrkmPXnqR3ZXPjoiQ9Fh6nPAriu7WI2JhmgWZl5JmRcSidPEv5xTgx5LWks0olHseMDSNaTuyoObfc9/kuAS4UdLXgAcqDS4i/iTpE8CvJH0xIp6E7CuxwEeBL+fyrpX0KPCJomqmA1dLWkr27/U3wOmV2jYzs86jCM8KlyOpX0S8IWlnsgv3pLR+otspjCVtnwfURcRZXdytDte3bljUnXR5V3fDSvCLvsy2XJIWpC8TtEtPn5mo1t1p8WIf4MLuGkgkH5f0DbJz/jyVH1OYmZm1ioOJFkTE5K7uQ0eJiNuA27q6H2Zm1vNsNQswzczMrDY8M2E9yog9BtLoZ/NmZp3KMxNmZmZWFQcTZmZmVhUHE2ZmZlYVr5mwHqVpdTP15xX/RW6rFf/tCDMDz0yYmZlZlRxMmJmZWVUcTJiZmVlVHEyYmZlZVRxMAJI2SFqc+6lvY/lZkoan7f+vQt5vSJqW+1wv6Q+SehXlWyxpQlv60Yp+tti3XL43yqTfIGlKG9q7QNLqNJanJF1TPE4zM+v+/D/2zLqIGJX7WZXfKanFb71ExKkRsSJ9rHTBPhKYmyu7CngBODjX3v5A/4iY967S1WlVMNHBLouIUcBwYATw4WorrHQ+zMysczmYKEPSyZJ+KumXwFxJkyXdndt/laST0/ZDksZJuhjYPt2J31yizgFAn4j4c9GuW4Cpuc9TUxqSdpU0W9L89DMpl36fpIWSrpX0vKRd0r7PSZqX+nGtpN6l+ibp55IWSFou6bSivv5bqvt+SbuWGMtYSQ+n8vdKqqtwSPsA2wFrUvmhkuak8o+kAKql8V4gaaakucBNFdoyM7NO5GAiU7jILpZ0Zy59InBSRBzWmkoi4jw2zXJMK5HlCOD+Eum3A8fl7rhPBG5N21eQ3d2PB04AZqX07wAPRMQY4E5gLwBJ70vlJ6UZgQ3AtDJ9+2JEjAXGAdMl7ZzSdwQWprofTm29Q9K2wL8DU1L564D/U+awnC1pMfAi8ExELE7pM4EzU/lzgB9WGC/AWODYiPhsUX9Ok9QoqXHDm81lumFmZrXi6eLMunThLXZfRLzSge0cBVxfnBgRf5S0HDhc0p+AtyJiWdp9BDBcUiH7AEn9gYOA41P5OZLWpP2Hk11056cy2wMvlenPdEnHp+09gWHAX4CNbHpd+X8CdxSV2w84ALgvtdGbLFgo5bKI+NcUgPxM0lTgbuBDwE9z4+pbYbwAd0XEuuIGImImWXBC37phUaYfZmZWIw4mWrY2t/02m8/kbNeO+iYA/1hmX+FRx5/SdkEvYGLxRVS5q20RATdGxDda6oikyWQX7okR8aakhyg/puILtIDlETGxpTY2qyDiLUlzgEOA/wJeLRPAlRsvbH4+zMxsC+HHHK33PNkdc19JA8lmAEp5K92Fb0bS+4GnImJDmXKzgY+x+SMOyBZrnpGrp3ABfhT4TEo7Ehic0u8HpkjaLe3bSdKQEn0bCKxJgcT+wIG5NnsBhW9tfDa1lfc0sKukiamNbdP4ykrBz4eAZyPiNWClpE8X9kn6QIXxmpnZFsrBRCtFxAtkaxuWAjcDi8pknQksLbEA82hgTgv1vwr8FvhTRKzM7ZoOjJO0VNIK4PSUPgM4UtLCVPeLwOvpWyXfJFs0uhS4Dygsjsz3bQ6wTcpzYWq7YC3wfkkLgMOA7xb19W9kwcYPJC0BFpMFCqUU1kwsI5sJK6yNmAacksovB46tMF4zM9tCKcKPmDuDpPuAf4iIcmsL2lpfX2BDRLydZgiuKfPYYKvSt25Y1J10eVd3Y6vhF32Z9QySFkTEuPaW95qJThIRH+ngKvcCblf2R6D+Bnypg+s3MzNrFQcT3VRE/Dcwuqv7YWZm5mDCepQRewyk0VPvZmadygswzczMrCoOJszMzKwqDibMzMysKl4zYT1K0+pm6s+7p6u70SP5a6BmVo5nJszMzKwqDibMzMysKg4mzMzMrCoOJszMzKwqDiZaQdLxkiK9XbNWbYyTdGUN699B0s2SmiQtk/SopH6SBkn6Sq3abUW/zpb01/Qm1kLaZEl3d1WfzMysbRxMtE4D2Wu4p9aicknbRERjREyvRf3JWWRvJB0REQcApwBvAYOAksGEpN417E9BAzAfOL4T2jIzsxpwMFGBpH7AJLKL79Rc+mRJD0u6XdIzki6WNE3SvHT3PzTl21XSbEnz08+klH6BpJmS5gI35e/G04zB9amepZJOSOnXSGqUtFzSjFxfVkmaIWlhKlNqBqUOWF34EBFPR8R64GJgqKTFki5N/XhQ0k+AplT/19JsxjJJX01p9ZJ+J+nHqT9zJW2f9o1P/X4i1bmszLEdCvQje2V6Q5k8O0q6Lh27RZKOLZXPzMy6joOJyo4D5kTEM8Arksbk9n2A7I5/BPB5YN+ImADMAs5Mea4ALouI8cAJaV/BWODYiPhsUZvfAprTLMJI4IGUfn56RexI4MOSRubKvBwRY4BrgHNKjOM64F/SBf4iScNS+nnAsxExKiK+ntImpLaGSxoLfAH4IHAg8CVJhReMDQOujoj3A6+m8QFcD5weEROBDSX6UtAA3AI8AuwnabcSec4HHkjH71DgUkk75jNIOi0FWY0b3mxuoTkzM6sFBxOVNQC3pu1b2fwOen5EvJju8J8F5qb0JqA+bR8BXCVpMXAXMEBS/7TvrohYV6LNI4CrCx8iYk3a/IykhcAi4P3A8FyZO9LvBbm23xERi4F9gEuBnYD5kt5XZszzImJl2j4IuDMi1kbEG6mdg9O+laned9qVNAjoHxGPp/SflGkDspmeWyNiY6r30yXyHAmcl47fQ8B2ZK9fz49tZkSMi4hxvXcYWKIKMzOrJf8FzBZI2hk4DDhAUgC9gZB0bsqyPpd9Y+7zRjYd217AxOKgQRLA2nJNA1GUf2+yGYfxEbFG0g1kF9aCQtsbKHNec8HAHZI2Ah8DZpfImu+XyvQx32ah3e0r5N9UaTarMgy4Lx2LPsBz5IKoXPsnRMTTranXzMw6n2cmWjYFuCkihkREfUTsCawku1tvrbnAGYUPkka1o8xgYADZRb5Z0u7A0W3oA5ImpXqQ1IdsVuN54HWgfwtFfwMcl74NsiPZQslHymVOsyivSzowJZVbtNoAXJCOa31EvAfYQ9KQonz3AmcqRRy5RyxmZraFcDDRsgbgzqK02UDxGoeWTAfGpQWJK4DTW1HmImBwWvC4BDg0IpaQPd5YTrb+4bE29AFgKPCwpKZUTyMwOyL+AjyW2rq0uFBELARuAOYBTwKzImJRhbZOAWZKeoJsZqHUQoapvPvY3sm7g48LgW2BpWkh54UV2jYzs06miKicy6wNJPVLj1SQdB5QFxFndUbbfeuGRd1Jl3dGU1sdv+jLrOeStCAt8G8Xr5mwWvi4pG+Q/ft6Hji5a7tjZma15GDCOlxE3Abc1tX9MDOzzuFgwnqUEXsMpNHT8WZmncoLMM3MzKwqDibMzMysKg4mzMzMrCoOJszMzKwqDibMzMysKg4mzMzMrCoOJszMzKwqDibMzMysKg4mzMzMrCp+0Zf1KJJeB57u6n7UyC7Ay13diRrwuLoXj6v7ac3YhkTEru1twH9O23qap6t5892WTFJjTxybx9W9eFzdT2eMzY85zMzMrCoOJszMzKwqDiasp5nZ1R2ooZ46No+re/G4up+aj80LMM3MzKwqnpkwMzOzqjiYMDMzs6o4mLAeQ9JRkp6W9HtJ53V1f0qRtKekByX9TtJySWel9J0k3Sfpv9PvwSldkq5MY1oqaUyurpNS/v+WdFIufaykplTmSknqxPH1lrRI0t3p896Snkx9vE1Sn5TeN33+fdpfn6vjGyn9aUkfzaV3yfmVNEjSzyQ9lc7bxJ5wviSdnf4NLpN0i6Ttuuv5knSdpJckLcul1fwclWujxuO6NP1bXCrpTkmDcvvadC7ac77Ligj/+Kfb/wC9gWeBfYA+wBJgeFf3q0Q/64Axabs/8AwwHLgEOC+lnwf8IG1/DPgVIOBA4MmUvhPwXPo9OG0PTvvmARNTmV8BR3fi+L4G/AS4O32+HZiatn8E/GPa/grwo7Q9FbgtbQ9P564vsHc6p7278vwCNwKnpu0+wKDufr6APYCVwPa583Rydz1fwCHAGGBZLq3m56hcGzUe15HANmn7B7lxtflctPV8t9jXzviP0T/+qfVP+g/93tznbwDf6Op+taLfvwA+QvZXO+tSWh3ZH98CuBZoyOV/Ou1vAK7NpV+b0uqAp3Lpm+Wr8Vj+HrgfOAy4O/2P9+Xc//jeOUfAvcDEtL1Nyqfi81bI11XnFxhAdtFVUXq3Pl9kwcQLZBfObdL5+mh3Pl9APZtfdGt+jsq1UctxFe07Hri51DGudC7a899nS/30Yw7rKQr/cyz4Q0rbYqWpw9HAk8DuEfEiQPq9W8pWblwtpf+hRHpnuBw4F9iYPu8MvBoRb5foyzv9T/ubU/62jrfW9gH+DFyv7PHNLEk70s3PV0SsBv4V+B/gRbLjv4Duf77yOuMclWujs3yRbKYE2j6u9vz3WZaDCespSj1n3mK/9yypHzAb+GpEvNZS1hJp0Y70mpJ0DPBSRCzIJ7fQl24xLrK7sjHANRExGlhLNp1dTrcYV3q2fyzZdPh7gB2Bo1voS7cYVyv1iLFIOh94G7i5kFQiW3vH1eYxO5iwnuIPwJ65z38P/G8X9aVFkrYlCyRujog7UvKfJNWl/XXASym93LhaSv/7Eum1Ngn4pKRVwK1kjzouBwZJKrwDKN+Xd/qf9g8EXqHt4621PwB/iIgn0+efkQUX3f18HQGsjIg/R8RbwB3Ah+j+5yuvM85RuTZqKi0OPQaYFulZBG0f18u0/XyX5WDCeor5wLC0OrkP2aKhu7q4T++SVoH//8DvIuL/5nbdBRRWj59EtpaikP4PaQX6gUBzmk69FzhS0uB0l3kk2fPOF4HXJR2Y2vqHXF01ExHfiIi/j4h6smP/QERMAx4EppQZV2G8U1L+SOlT02ryvYFhZIvfuuT8RsQfgRck7ZeSDgdW0M3PF9njjQMl7ZDaLYyrW5+vIp1xjsq1UTOSjgL+BfhkRLyZ29Wmc5HOX1vPd3m1XBDjH/905g/ZKu1nyFYun9/V/SnTx4PIpguXAovTz8fInkfeD/x3+r1Tyi/g6jSmJmBcrq4vAr9PP1/IpY8DlqUyV1Fh4VQNxjiZTd/m2Cf9D+33wE+Bvil9u/T592n/Prny56e+P03umw1ddX7h/7V3byFWVXEcx78/rXyoIFIKmodCuxmCgTgPXbxk2EuQhBaiROlDmmlFFkgXMogykSIptATtQqHQ9SEYodREh0Yx0bArVk9CQhIYKIr/Hv7ryO7MGZ2ZrdXB3wcOcy5r/9c6Z8PZ/7P2nvXnRmBn2WefkFf6t/3+ApYC35e+3yX/C6At9xfwAXntxzHyV/Xcf2Mf9dXHWX5fP5PXMzS+P1YNdl8MZn/3dfNy2mZmZlaLT3OYmZlZLU4mzMzMrBYnE2ZmZlaLkwkzMzOrxcmEmZmZ1eJkwszajqSQtKLyeLGk585Q7HWSpp++Ze1+ZiirkG46C7G3n+mYZqfiZMLM2tFR4G5JI/7rgVRJGjqA5nOBhyJi8hmKd1JE3DSY7cwGy8mEmbWj48CbwGPNLzTPLEg6XP5OkrRF0gZJP0p6SdIsST2S9koaVQlzu6Stpd2dZfuhkpZL2iFpj6QHK3E3SXqfXASpeTwzS/xvJS0rzz1LLmC2StLypva94kmaXca5W9LqMpb5kl6ubHe/pJXV91zuP1EZ89Ly3JOSFpX7r0j6styfIum9En9dGfNeSb0+Z7Oq807fxMzsf+l1YE/1gNoPY4HRZJ2B/cCaiOiU9AiwEHi0tLsKmAiMAjZJuppcRvnPiBgvaRiwTdLG0r4TGBMRv1Q7k3QFsAwYBxwCNkqaFhHPS7oNWBwRO1uM82Q8SaOBe4GbI+KYpDeAWWSdkG6yUiulzQtN/U8ll1XuJFd+/EzSBOAr4HHgNXJ1x2HKmjG3AFvJVT87ImJMiXNJfz5cO3d5ZsLM2lJktdV3gEUD2GxHRByIiKPk0sKNZGAvmUA0bIiIExHxE5l0XE/WarhP0m6ybPxw8kAN0NOcSBTjgc2RBbUaFR4n9GOc1XhTyGRkR+l7Crm88UFgf6kZMRy4DtjWFGdquX0D7Crv4xqy3Pg4SReTp4y6yaTiVjKZ2A+MlLSy1II4VWVbM89MmFlbe5U8SK6tPHec8kOpFGa6oPLa0cr9E5XHJ/jn92FznYFGyeaFEdFVfUHSJLI0eSutSjn3RzWegLcjYkmLduuBe8gaGx9H7/oIAl6MiNW9BpYVXh8AtpN1RyaTMzHfRURIGgvcASwofcwZ5Huxc4BnJsysbUXEH8AG8mLGhl/JX/IAdwHnDyL0DElDynUUI8nCSV3A/HI6AEnXSrrwNHG+BiZKGlEuppwJbBngWL4Apku6rPR7qaQry2sfAdNK3PUttu0C5ki6qGzb0YhDnupYXP5uBeYBu0siMQIYEhEfAs+QZdfN+uSZCTNrdyuAhyuP3wI+ldRDHoj7mjU4lR/Ig/7lwLyIOCJpDXkqZFeZ8ThIHsj7FBEHJC0hSz0L+DwiBlSmOiL2SXqavN5iCFlBcgHwW0QckrQPuCEielpsu7Fcc9GdQ+YwMBv4nUwgngK6I+IvSUfKcwAdwNrSH0CrWRGzk1w11MzMzGrxaQ4zMzOrxcmEmZmZ1eJkwszMzGpxMmFmZma1OJkwMzOzWpxMmJmZWS1OJszMzKyWvwFx3SfkV46DFgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2348584beb8>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.barh(range(len(top_beer_styles.index)), top_beer_styles)\n",
    "\n",
    "plt.title(\"Top 10 beers\")\n",
    "plt.xlabel(\"Number of reviews\")\n",
    "plt.yticks(range(len(top_beer_styles)), top_beer_styles.index)\n",
    "plt.gca().invert_yaxis()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [],
   "source": [
    "# \"review_overall\", \"review_aroma\", \"review_appearance\", \"review_palate\", \"review_taste\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_rating_histogram(column_name, show = True):\n",
    "    alpha = 1 if show else 0.5\n",
    "    plt.hist(beer_reviews[\"review_\" + column_name], bins = 11, label = column_name, alpha = alpha)\n",
    "\n",
    "    plt.title(\"Distribution of {} rating\".format(column_name))\n",
    "    plt.xlabel(\"Rating\")\n",
    "    plt.ylabel(\"Count\")\n",
    "    plt.legend()\n",
    "    if show:\n",
    "        plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2348777cef0>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x23487659198>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x234841165f8>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZsAAAEWCAYAAACwtjr+AAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvNQv5yAAAH41JREFUeJzt3XuYVNWZ7/HvD2iDyk0BPQhom4hPNGRiFBWHkxmNieIl4pyJBk+MmGMOT9QkZhyNaKImBhOczDGOueAxSkDjNSaOqHgX48TjDbwrRgneWgx3EERQ8D1/7NValtXd1U2vKmh+n+fZT++99tprvbWh6+2196pdigjMzMxy6lbvAMzMrOtzsjEzs+ycbMzMLDsnGzMzy87JxszMsnOyMTOz7JxsbKMh6RJJZ3dSWztKWiWpe9q+T9I3OqPt1N5tksZ1Vnvt6HeipMWS/lbrvmtN0lcl3VnvOKxzyJ+zsVqQ9DKwPbAOWA88B1wBXBoR73WgrW9ExN3tOOY+4HcRcVl7+krH/hDYJSKObe+xnUnSUOAFYKeIWFhh//4Ur3FIJ/Q1FWiKiB9saFtV9tcIvAQ0RMS6WvRpteWRjdXSlyKiN7ATMAk4A7i8szuR1KOz29xI7AQsqZRoNnbNI0zbjEWEFy/ZF+Bl4AtlZfsA7wHD0/ZUYGJaHwDcAiwHlgL/RfHH0ZXpmLeBVcD3gEYggBOAV4H7S8p6pPbuA34KPAKsAG4Ctk379qf4K/4j8QKjgXeAd1N/T5a094203g34AfAKsJBixNY37WuOY1yKbTHw/VbOU990/KLU3g9S+19Ir/m9FMfUsuO2Ltu/CtghneMH03l8A/glsEU6RsDPU8wrgKeA4cD49HrfSe3cnOrvAPwhxfYS8J1WXsdUYDIwA3grxX8Y8DjwJvAa8MOS+q+m89Qc+37A8cCfS+oE8E3gRWAZ8Cs+uDrTHfg/6fy+BHyr9N/fS/2XugfgZfNYqJBsUvmrwIlpfSofJJufApcADWn5XMkby4faKnlDvyK96W5J5WTzenoz3Tq9af4u7dufFpJNWv9hc92S/ffxQbL5X8Bc4ONAL+CPwJVlsf0mxfUZYC2wWwvn6QqKRNg7HfsCcEJLcZYdW+l17AWMBHqk9uYA3037DgZmA/0oEs9uwKDyf4u03S3VPQfYIr3WecDBLcQylSKBjUrH9kzxfTpt/x2wADiy7Dz1KGnjeD6abG5J8e5IkfRGp33fpLg0OwTYBri7vD0v9V18Gc3qbT6wbYXyd4FBFPcn3o2I/4r0rtKKH0bEWxHxdgv7r4yIZyLiLeBs4OhOurzzVeDCiJgXEauAM4GxZZfzfhQRb0fEk8CTFEnnQ1IsXwHOjIiVEfEyxV/rX+toYBExOyIeioh1qb3/C/xj2v0uRVL7JEUinxMRb7TQ1N7AwIg4LyLeiYh5FAl0bCvd3xQRD0TEexGxJiLui4in0/ZTwDUlsVRrUkQsj4hXgZnAHqn8aOA/IqIpIpZRXKa1jYiTjdXbYIrLZOV+RjFauFPSPEkTqmjrtXbsf4VixDSgqihbt0Nqr7TtHhQTIpqVzh5bTTECKjeAYtRQ3tbgjgYmaVdJt0j6m6Q3gZ+kfoiIeykuq/0KWCDpUkl9WmhqJ2AHScubF+AsPvway33o30PSvpJmSlokaQXFaKS957+l87hDWX9t/V+wGnOysbqRtDfFG+mfy/elv+z/NSI+DnwJOFXSgc27W2iyrZHP0JL1HSn+sl9McU9hq5K4ugMD29HufIo349K211FcJmqPxSmm8rZer/L4SnFOBp4HhkVEH4oEofcPiLg4IvYCPgXsCpzeQluvAS9FRL+SpXdEHNqOeK4GpgNDI6IvxWVStVC3vd6guITWbGhLFa0+nGys5iT1kXQ4cC3FvZCnK9Q5XNIukkRxQ3l9WqB4E/94B7o+VtLukrYCzgNuiIj1FPdFeko6TFIDxU35j5UctwBolNTS78s1wL9I2llSL4rRw3XRzim8KZbrgfMl9Za0E3Aq8Lsqm1gA9JfUt6SsN8X5WyXpk8CJzTsk7Z1GGw0UCXcNLZ/jR4A3JZ0haUtJ3SUNT38wVKs3sDQi1kjaB/ifJfsWUUxu6Mi/KxTn7RRJgyX1o5jpaBsRJxurpZslraT4K/n7wIXA11uoO4ziJu8qitlUv46I+9K+nwI/SJdzTmtH/1dS3Lj+G8UN6+8ARMQK4CTgMopRxFtAU8lxv08/l0h6rEK7U1Lb91PMhFoDfLsdcZX6dup/HsWI7+rUfpsi4nmKxDcvnZsdgNMo3tRXUtxjua7kkD6pbBnF5bolwL+nfZcDu6d2/jMlwi9R3CN5iWIUdhnF7LlqnQScl/4PnEORIJpjXw2cDzyQ+hzZjnZJr+NOihl1j1PMgmv+TJdtBPyhTjPrciQdAlwSETu1WdlqwiMbM9vkpUt7h0rqIWkwcC5wY73jsg94ZGNmm7x0H+5PFNO43wZuBU6JiDfrGpi9z8nGzMyy82U0MzPLrqs+sLDdBgwYEI2NjfUOw8xskzJ79uzFETGwrXpONkljYyOzZs2qdxhmZpsUSa+0XcuX0czMrAacbMzMLDsnGzMzy873bMzM2undd9+lqamJNWvW1DuUmunZsydDhgyhoaGhQ8c72ZiZtVNTUxO9e/emsbGR4lmxXVtEsGTJEpqamth555071IYvo5mZtdOaNWvo37//ZpFoACTRv3//DRrJOdmYmXXA5pJomm3o63WyMTOz7HzPxsxsAzVOuLVT23t50mFt1lm+fDlXX301J510Urvbv+iiixg/fjxbbbVV25U7iZONmW1yOvvNvS3VvPnX2vLly/n1r3/d4WRz7LHHOtmYmVnrJkyYwF//+lf22GMPDjjgAJ566imWLVvGu+++y8SJExkzZgxvvfUWRx99NE1NTaxfv56zzz6bBQsWMH/+fA444AAGDBjAzJkzufPOOzn33HNZu3Ytn/jEJ/jtb39Lr169OjVeJxszs03QpEmTeOaZZ3jiiSdYt24dq1evpk+fPixevJiRI0dyxBFHcPvtt7PDDjtw663FSHDFihX07duXCy+8kJkzZzJgwAAWL17MxIkTufvuu9l666254IILuPDCCznnnHM6NV4nGzOzTVxEcNZZZ3H//ffTrVs3Xn/9dRYsWMCnP/1pTjvtNM444wwOP/xwPve5z33k2IceeojnnnuOUaNGAfDOO++w3377dXqMTjZmZpu4q666ikWLFjF79mwaGhpobGxkzZo17LrrrsyePZsZM2Zw5plnctBBB31kxBIRfPGLX+Saa67JGqOnPpuZbYJ69+7NypUrgeLy2HbbbUdDQwMzZ87klVeKp/7Pnz+frbbaimOPPZbTTjuNxx577CPHjhw5kgceeIC5c+cCsHr1al544YVOj9cjGzOzDVSP2Wr9+/dn1KhRDB8+nL333pvnn3+eESNGsMcee/DJT34SgKeffprTTz+dbt260dDQwOTJkwEYP348hxxyCIMGDWLmzJlMnTqVY445hrVr1wIwceJEdt11106NVxHRqQ1uqkaMGBH+8jSzTUO9pz7PmTOH3XbbraYxbAwqvW5JsyNiRFvH+jKamZll52RjZmbZOdmYmXXA5nYLYkNfr5ONmVk79ezZkyVLlmw2Caf5+2x69uzZ4TayzkaT9DKwElgPrIuIEZK2Ba4DGoGXgaMjYpmK51f/B3AosBo4PiIeS+2MA36Qmp0YEdNS+V7AVGBLYAZwSkRES33kfK1mtvkYMmQITU1NLFq0qN6h1EzzN3V2VC2mPh8QEYtLticA90TEJEkT0vYZwCHAsLTsC0wG9k2J41xgBBDAbEnTU/KYDIwHHqJINqOB21rpw8xsgzU0NHT4Gys3V/W4jDYGmJbWpwFHlpRfEYWHgH6SBgEHA3dFxNKUYO4CRqd9fSLiwSjGsleUtVWpDzMzq4PcySaAOyXNljQ+lW0fEW8ApJ/bpfLBwGslxzalstbKmyqUt9aHmZnVQe7LaKMiYr6k7YC7JD3fSt1K3zkaHSivWkqA4wF23HHH9hxqZmbtkHVkExHz08+FwI3APsCCdAmM9HNhqt4EDC05fAgwv43yIRXKaaWP8vgujYgRETFi4MCBHX2ZZmbWhmzJRtLWkno3rwMHAc8A04Fxqdo44Ka0Ph04ToWRwIp0CewO4CBJ20jaJrVzR9q3UtLINJPtuLK2KvVhZmZ1kPMy2vbAjUUeoAdwdUTcLulR4HpJJwCvAkel+jMopj3PpZj6/HWAiFgq6cfAo6neeRGxNK2fyAdTn29LC8CkFvowM7M6yJZsImIe8JkK5UuAAyuUB3ByC21NAaZUKJ8FDK+2DzMzqw8/QcDMzLJzsjEzs+ycbMzMLDsnGzMzy87JxszMsnOyMTOz7JxszMwsOycbMzPLzsnGzMyyc7IxM7PsnGzMzCw7JxszM8vOycbMzLJzsjEzs+ycbMzMLDsnGzMzy87JxszMsnOyMTOz7JxszMwsOycbMzPLzsnGzMyyc7IxM7PsnGzMzCw7JxszM8vOycbMzLJzsjEzs+ycbMzMLDsnGzMzy87JxszMsnOyMTOz7LInG0ndJT0u6Za0vbOkhyW9KOk6SVuk8o+l7blpf2NJG2em8r9IOrikfHQqmytpQkl5xT7MzKw+ajGyOQWYU7J9AfDziBgGLANOSOUnAMsiYhfg56keknYHxgKfAkYDv04JrDvwK+AQYHfgmFS3tT7MzKwOsiYbSUOAw4DL0raAzwM3pCrTgCPT+pi0Tdp/YKo/Brg2ItZGxEvAXGCftMyNiHkR8Q5wLTCmjT7MzKwOco9sLgK+B7yXtvsDyyNiXdpuAgan9cHAawBp/4pU//3ysmNaKm+tjw+RNF7SLEmzFi1a1NHXaGZmbciWbCQdDiyMiNmlxRWqRhv7Oqv8o4URl0bEiIgYMXDgwEpVzMysE/TI2PYo4AhJhwI9gT4UI51+knqkkccQYH6q3wQMBZok9QD6AktLypuVHlOpfHErfZiZWR1kG9lExJkRMSQiGilu8N8bEV8FZgJfTtXGATel9elpm7T/3oiIVD42zVbbGRgGPAI8CgxLM8+2SH1MT8e01IeZmdVBPT5ncwZwqqS5FPdXLk/llwP9U/mpwASAiHgWuB54DrgdODki1qdRy7eAOyhmu12f6rbWh5mZ1UHOy2jvi4j7gPvS+jyKmWTlddYAR7Vw/PnA+RXKZwAzKpRX7MPMzOrDTxAwM7PsnGzMzCw7JxszM8vOycbMzLJzsjEzs+ycbMzMLDsnGzMzy87JxszMsnOyMTOz7JxszMwsOycbMzPLzsnGzMyyc7IxM7PsnGzMzCw7JxszM8vOycbMzLJzsjEzs+ycbMzMLLuafC20mdmmrHHCrTXt7+VJh9W0v1rwyMbMzLJzsjEzs+ycbMzMLDsnGzMzy84TBMy6KN/Uto2JRzZmZpadk42ZmWVXVbKRNKqaMjMzs0qqHdn8osoyMzOzj2h1goCk/YC/BwZKOrVkVx+ge87AzMys62hrZLMF0IsiKfUuWd4EvtzagZJ6SnpE0pOSnpX0o1S+s6SHJb0o6TpJW6Tyj6XtuWl/Y0lbZ6byv0g6uKR8dCqbK2lCSXnFPszMrD5aHdlExJ+AP0maGhGvtLPttcDnI2KVpAbgz5JuA04Ffh4R10q6BDgBmJx+LouIXSSNBS4AviJpd2As8ClgB+BuSbumPn4FfBFoAh6VND0inkvHVurDzMzqoNp7Nh+TdKmkOyXd27y0dkAUVqXNhrQE8HnghlQ+DTgyrY9J26T9B0pSKr82ItZGxEvAXGCftMyNiHkR8Q5wLTAmHdNSH2ZmVgfVfqjz98AlwGXA+mobl9QdmA3sQjEK+SuwPCLWpSpNwOC0Phh4DSAi1klaAfRP5Q+VNFt6zGtl5fumY1rqozy+8cB4gB133LHal2VmZu1UbbJZFxHtvgwVEeuBPST1A24EdqtULf1UC/taKq80KmutfqX4LgUuBRgxYkTFOmZmtuGqvYx2s6STJA2StG3zUm0nEbEcuA8YCfST1JzkhgDz03oTMBQg7e8LLC0tLzumpfLFrfRhZmZ1UG2yGQecDvw/istis4FZrR0gaWAa0SBpS+ALwBxgJh/MZBsH3JTWp6dt0v57IyJS+dg0W21nYBjwCPAoMCzNPNuCYhLB9HRMS32YmVkdVHUZLSJ27kDbg4Bp6b5NN+D6iLhF0nPAtZImAo8Dl6f6lwNXSppLMaIZm/p+VtL1wHPAOuDkdHkOSd8C7qD4zM+UiHg2tXVGC32YmVkdVJVsJB1XqTwirmjpmIh4CvhshfJ5FDPJysvXAEe10Nb5wPkVymcAM6rtw8zM6qPaCQJ7l6z3BA4EHgNaTDZmZmbNqr2M9u3SbUl9gSuzRGRmZl1OR79iYDXFjXozM7M2VXvP5mY++KxKd4rPy1yfKygzM+taqr1n8+8l6+uAVyKiKUM8ZmbWBVV1GS09kPN5iic+bwO8kzMoMzPrWqr9ps6jKT5IeRRwNPCwpFa/YsDMzKxZtZfRvg/sHRELoXg6AHA3HzxZ2czMrEXVzkbr1pxokiXtONbMzDZz1Y5sbpd0B3BN2v4KFT65b2ZmVkmryUbSLsD2EXG6pP8B/HeKR/g/CFxVg/jMzKwLaOtS2EXASoCI+GNEnBoR/0Ixqrkod3BmZtY1tJVsGtMDNT8kImYBjVkiMjOzLqetZNOzlX1bdmYgZmbWdbWVbB6V9L/LCyWdQPEFamZmZm1qazbad4EbJX2VD5LLCGAL4J9yBmZmZl1Hq8kmIhYAfy/pAGB4Kr41Iu7NHpmZmXUZ1X6fzUxgZuZYzMysi/JTAMzMLDsnGzMzy87JxszMsnOyMTOz7JxszMwsOycbMzPLzsnGzMyyc7IxM7PsnGzMzCw7JxszM8vOycbMzLLLlmwkDZU0U9IcSc9KOiWVbyvpLkkvpp/bpHJJuljSXElPSdqzpK1xqf6LksaVlO8l6el0zMWS1FofZmZWHzlHNuuAf42I3YCRwMmSdgcmAPdExDDgnrQNcAgwLC3jgclQJA7gXGBfYB/g3JLkMTnVbT5udCpvqQ8zM6uDbMkmIt6IiMfS+kpgDjAYGANMS9WmAUem9THAFVF4COgnaRBwMHBXRCyNiGXAXcDotK9PRDwYEQFcUdZWpT7MzKwOanLPRlIj8FngYWD7iHgDioQEbJeqDQZeKzmsKZW1Vt5UoZxW+iiPa7ykWZJmLVq0qKMvz8zM2pA92UjqBfwB+G5EvNla1Qpl0YHyqkXEpRExIiJGDBw4sD2HmplZO2RNNpIaKBLNVRHxx1S8IF0CI/1cmMqbgKElhw8B5rdRPqRCeWt9mJlZHeScjSbgcmBORFxYsms60DyjbBxwU0n5cWlW2khgRboEdgdwkKRt0sSAg4A70r6Vkkamvo4ra6tSH2ZmVgdVfS10B40CvgY8LemJVHYWMAm4XtIJwKvAUWnfDOBQYC6wGvg6QEQslfRj4NFU77yIWJrWTwSmAlsCt6WFVvowM7M6yJZsIuLPVL6vAnBghfoBnNxCW1OAKRXKZwHDK5QvqdSHmZnVh58gYGZm2TnZmJlZdk42ZmaWnZONmZll52RjZmbZOdmYmVl2TjZmZpZdzg91mlmJxgm31jsEs7rxyMbMzLJzsjEzs+ycbMzMLDsnGzMzy87JxszMsnOyMTOz7JxszMwsOycbMzPLzsnGzMyyc7IxM7PsnGzMzCw7JxszM8vOycbMzLJzsjEzs+ycbMzMLDsnGzMzy87JxszMsnOyMTOz7JxszMwsOycbMzPLzsnGzMyyy5ZsJE2RtFDSMyVl20q6S9KL6ec2qVySLpY0V9JTkvYsOWZcqv+ipHEl5XtJejodc7EktdaHmZnVT86RzVRgdFnZBOCeiBgG3JO2AQ4BhqVlPDAZisQBnAvsC+wDnFuSPCanus3HjW6jDzMzq5NsySYi7geWlhWPAaal9WnAkSXlV0ThIaCfpEHAwcBdEbE0IpYBdwGj074+EfFgRARwRVlblfowM7M6qfU9m+0j4g2A9HO7VD4YeK2kXlMqa628qUJ5a32YmVmdbCwTBFShLDpQ3r5OpfGSZkmatWjRovYebmZmVap1slmQLoGRfi5M5U3A0JJ6Q4D5bZQPqVDeWh8fERGXRsSIiBgxcODADr8oMzNrXa2TzXSgeUbZOOCmkvLj0qy0kcCKdAnsDuAgSdukiQEHAXekfSsljUyz0I4ra6tSH2ZmVic9cjUs6Rpgf2CApCaKWWWTgOslnQC8ChyVqs8ADgXmAquBrwNExFJJPwYeTfXOi4jmSQcnUsx42xK4LS200oeZmdVJtmQTEce0sOvACnUDOLmFdqYAUyqUzwKGVyhfUqkPMzOrn41lgoCZmXVh2UY2ZmbWMY0Tbq1ZXy9POqwm/XhkY2Zm2TnZmJlZdk42ZmaWnZONmZll52RjZmbZeTaabdZqOevHbHPmkY2ZmWXnZGNmZtk52ZiZWXZONmZmlp2TjZmZZedkY2Zm2TnZmJlZdk42ZmaWnZONmZll5ycIWKtq/Qn7Wn23hpnVlkc2ZmaWnZONmZll52RjZmbZOdmYmVl2TjZmZpadk42ZmWXnZGNmZtk52ZiZWXZONmZmlp2fILAJqvWn+s3MNpRHNmZmlp1HNp3AIw0zs9Z12ZGNpNGS/iJprqQJ9Y7HzGxz1iWTjaTuwK+AQ4DdgWMk7V7fqMzMNl9dMtkA+wBzI2JeRLwDXAuMqXNMZmabra56z2Yw8FrJdhOwb3klSeOB8WlzlaS/dLC/AcDiDh6b0yYXly6ocSQftsmdrzr7UFx1/rcrtUmcr42FLtjguHaqplJXTTaqUBYfKYi4FLh0gzuTZkXEiA1tp7M5rvZxXO3juNpnc4+rq15GawKGlmwPAebXKRYzs81eV002jwLDJO0saQtgLDC9zjGZmW22uuRltIhYJ+lbwB1Ad2BKRDybscsNvhSXieNqH8fVPo6rfTbruBTxkVsZZmZmnaqrXkYzM7ONiJONmZll52RTJUlTJC2U9EwL+yXp4vR4nKck7bmRxLW/pBWSnkjLOTWKa6ikmZLmSHpW0ikV6tT8nFUZV83PmaSekh6R9GSK60cV6nxM0nXpfD0sqXEjiet4SYtKztc3csdV0nd3SY9LuqXCvpqfryrjqsv5kvSypKdTn7Mq7M/7+xgRXqpYgH8A9gSeaWH/ocBtFJ/xGQk8vJHEtT9wSx3O1yBgz7TeG3gB2L3e56zKuGp+ztI56JXWG4CHgZFldU4CLknrY4HrNpK4jgd+Wev/Y6nvU4GrK/171eN8VRlXXc4X8DIwoJX9WX8fPbKpUkTcDyxtpcoY4IooPAT0kzRoI4irLiLijYh4LK2vBOZQPNmhVM3PWZVx1Vw6B6vSZkNaymfvjAGmpfUbgAMlVfoAc63jqgtJQ4DDgMtaqFLz81VlXBurrL+PTjadp9Ijcur+Jpbsly6D3CbpU7XuPF2++CzFX8Wl6nrOWokL6nDO0qWXJ4CFwF0R0eL5ioh1wAqg/0YQF8A/p0svN0gaWmF/DhcB3wPea2F/Xc5XFXFBfc5XAHdKmq3iUV3lsv4+Otl0nqoekVMHjwE7RcRngF8A/1nLziX1Av4AfDci3izfXeGQmpyzNuKqyzmLiPURsQfFEy/2kTS8rEpdzlcVcd0MNEbE3wF388FoIhtJhwMLI2J2a9UqlGU9X1XGVfPzlYyKiD0pnoZ/sqR/KNuf9Xw52XSejfIRORHxZvNlkIiYATRIGlCLviU1ULyhXxURf6xQpS7nrK246nnOUp/LgfuA0WW73j9fknoAfanhJdSW4oqIJRGxNm3+BtirBuGMAo6Q9DLFU90/L+l3ZXXqcb7ajKtO54uImJ9+LgRupHg6fqmsv49ONp1nOnBcmtExElgREW/UOyhJ/635OrWkfSj+zZfUoF8BlwNzIuLCFqrV/JxVE1c9zpmkgZL6pfUtgS8Az5dVmw6MS+tfBu6NdGe3nnGVXdc/guI+WFYRcWZEDImIRoqb//dGxLFl1Wp+vqqJqx7nS9LWkno3rwMHAeUzWLP+PnbJx9XkIOkaillKAyQ1AedS3CwlIi4BZlDM5pgLrAa+vpHE9WXgREnrgLeBsbl/4ZJRwNeAp9P1foCzgB1LYqvHOasmrnqcs0HANBVf/NcNuD4ibpF0HjArIqZTJMkrJc2l+At9bOaYqo3rO5KOANaluI6vQVwVbQTnq5q46nG+tgduTH9D9QCujojbJX0TavP76MfVmJlZdr6MZmZm2TnZmJlZdk42ZmaWnZONmZll52RjZmbZOdmY1YCk9elpu89Iurn5syut1O8n6aSS7R0k3ZA/UrM8PPXZrAYkrYqIXml9GvBCRJzfSv1GiicGlz8axmyT5JGNWe09SHrAoaReku6R9JiK7xoZk+pMAj6RRkM/k9So9J1FKr4P5Y+Sbpf0oqR/a25Y0gmSXpB0n6TfSPplzV+dWQV+goBZDaVP4h9I8el2gDXAP0XEm+n5aw9Jmg5MAIanB2A2j3RK7UHxxOq1wF8k/QJYD5xN8f1GK4F7gSezviCzKjnZmNXGlunxOI3AbOCuVC7gJ+kJvO9RjHi2r6K9eyJiBYCk54CdgAHAnyJiaSr/PbBrZ74Is47yZTSz2ng7jVJ2ArYATk7lXwUGAnul/QuAnlW0t7ZkfT3FH47ZvxjMrKOcbMxqKI1GvgOclr7qoC/F95+8K+kAimQExWWw3u1s/hHgHyVtkx6p/8+dFbfZhnKyMauxiHic4l7KWOAqYISkWRSjnOdTnSXAA2mq9M+qbPd14CcU3zx6N/AcxbdTmtWdpz6bdSGSekXEqjSyuRGYEhE31jsuM49szLqWH6aJCM8AL1HjrwE3a4lHNmZmlp1HNmZmlp2TjZmZZedkY2Zm2TnZmJlZdk42ZmaW3f8HlnADd49C2VIAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x234a56ac278>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_rating_histogram(\"aroma\")\n",
    "plot_rating_histogram(\"appearance\")\n",
    "plot_rating_histogram(\"palate\")\n",
    "plot_rating_histogram(\"taste\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x234a536d9b0>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_rating_histogram(\"aroma\", show = False)\n",
    "plot_rating_histogram(\"appearance\", show = False)\n",
    "plot_rating_histogram(\"palate\", show = False)\n",
    "plot_rating_histogram(\"taste\", show = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "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>beer_beerid</th>\n",
       "      <th>brewery_id</th>\n",
       "      <th>brewery_name</th>\n",
       "      <th>review_profilename</th>\n",
       "      <th>review_time</th>\n",
       "      <th>beer_style</th>\n",
       "      <th>beer_name</th>\n",
       "      <th>beer_abv</th>\n",
       "      <th>review_overall</th>\n",
       "      <th>review_aroma</th>\n",
       "      <th>review_appearance</th>\n",
       "      <th>review_palate</th>\n",
       "      <th>review_taste</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>37234</th>\n",
       "      <td>3806</td>\n",
       "      <td>1413</td>\n",
       "      <td>Desert Edge Brewery</td>\n",
       "      <td>beernut7</td>\n",
       "      <td>2002-08-24 14:01:10</td>\n",
       "      <td>Czech Pilsener</td>\n",
       "      <td>Pub Pils</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39648</th>\n",
       "      <td>3804</td>\n",
       "      <td>1413</td>\n",
       "      <td>Desert Edge Brewery</td>\n",
       "      <td>beernut7</td>\n",
       "      <td>2002-08-25 09:19:18</td>\n",
       "      <td>Irish Dry Stout</td>\n",
       "      <td>Latter Days Stout</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39667</th>\n",
       "      <td>3810</td>\n",
       "      <td>1413</td>\n",
       "      <td>Desert Edge Brewery</td>\n",
       "      <td>beernut7</td>\n",
       "      <td>2002-08-25 09:14:49</td>\n",
       "      <td>American Pale Ale (APA)</td>\n",
       "      <td>Utah Pale Ale</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>653695</th>\n",
       "      <td>3788</td>\n",
       "      <td>1412</td>\n",
       "      <td>Red Rock Brewing Company</td>\n",
       "      <td>beernut7</td>\n",
       "      <td>2002-08-22 09:17:39</td>\n",
       "      <td>Hefeweizen</td>\n",
       "      <td>Red Rock Bavarian Weiss</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>653706</th>\n",
       "      <td>3787</td>\n",
       "      <td>1412</td>\n",
       "      <td>Red Rock Brewing Company</td>\n",
       "      <td>beernut7</td>\n",
       "      <td>2002-08-22 09:22:22</td>\n",
       "      <td>American Amber / Red Ale</td>\n",
       "      <td>Red Rock Amber Ale</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>3.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>653726</th>\n",
       "      <td>3822</td>\n",
       "      <td>1412</td>\n",
       "      <td>Red Rock Brewing Company</td>\n",
       "      <td>beernut7</td>\n",
       "      <td>2002-08-22 09:15:37</td>\n",
       "      <td>German Pilsener</td>\n",
       "      <td>Red Rock Pilsner</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>653740</th>\n",
       "      <td>3786</td>\n",
       "      <td>1412</td>\n",
       "      <td>Red Rock Brewing Company</td>\n",
       "      <td>beernut7</td>\n",
       "      <td>2002-08-22 09:20:39</td>\n",
       "      <td>Dunkelweizen</td>\n",
       "      <td>Red Rock Dunkel Weizen</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        beer_beerid  brewery_id              brewery_name review_profilename  \\\n",
       "37234          3806        1413       Desert Edge Brewery           beernut7   \n",
       "39648          3804        1413       Desert Edge Brewery           beernut7   \n",
       "39667          3810        1413       Desert Edge Brewery           beernut7   \n",
       "653695         3788        1412  Red Rock Brewing Company           beernut7   \n",
       "653706         3787        1412  Red Rock Brewing Company           beernut7   \n",
       "653726         3822        1412  Red Rock Brewing Company           beernut7   \n",
       "653740         3786        1412  Red Rock Brewing Company           beernut7   \n",
       "\n",
       "               review_time                beer_style                beer_name  \\\n",
       "37234  2002-08-24 14:01:10            Czech Pilsener                 Pub Pils   \n",
       "39648  2002-08-25 09:19:18           Irish Dry Stout        Latter Days Stout   \n",
       "39667  2002-08-25 09:14:49   American Pale Ale (APA)            Utah Pale Ale   \n",
       "653695 2002-08-22 09:17:39                Hefeweizen  Red Rock Bavarian Weiss   \n",
       "653706 2002-08-22 09:22:22  American Amber / Red Ale       Red Rock Amber Ale   \n",
       "653726 2002-08-22 09:15:37           German Pilsener         Red Rock Pilsner   \n",
       "653740 2002-08-22 09:20:39              Dunkelweizen   Red Rock Dunkel Weizen   \n",
       "\n",
       "        beer_abv  review_overall  review_aroma  review_appearance  \\\n",
       "37234        4.0             0.0           2.0                0.0   \n",
       "39648        4.0             0.0           4.0                0.0   \n",
       "39667        4.0             0.0           3.0                0.0   \n",
       "653695       4.0             0.0           2.0                0.0   \n",
       "653706       4.0             0.0           3.0                0.0   \n",
       "653726       4.0             0.0           2.0                0.0   \n",
       "653740       4.0             0.0           2.0                0.0   \n",
       "\n",
       "        review_palate  review_taste  \n",
       "37234             3.0           2.0  \n",
       "39648             2.0           2.0  \n",
       "39667             2.0           2.0  \n",
       "653695            2.5           2.0  \n",
       "653706            2.5           3.5  \n",
       "653726            3.0           1.5  \n",
       "653740            2.5           2.0  "
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "beer_reviews[beer_reviews.review_appearance == 0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "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>beer_beerid</th>\n",
       "      <th>brewery_id</th>\n",
       "      <th>brewery_name</th>\n",
       "      <th>review_profilename</th>\n",
       "      <th>review_time</th>\n",
       "      <th>beer_style</th>\n",
       "      <th>beer_name</th>\n",
       "      <th>beer_abv</th>\n",
       "      <th>review_overall</th>\n",
       "      <th>review_aroma</th>\n",
       "      <th>review_appearance</th>\n",
       "      <th>review_palate</th>\n",
       "      <th>review_taste</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>37234</th>\n",
       "      <td>3806</td>\n",
       "      <td>1413</td>\n",
       "      <td>Desert Edge Brewery</td>\n",
       "      <td>beernut7</td>\n",
       "      <td>2002-08-24 14:01:10</td>\n",
       "      <td>Czech Pilsener</td>\n",
       "      <td>Pub Pils</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39648</th>\n",
       "      <td>3804</td>\n",
       "      <td>1413</td>\n",
       "      <td>Desert Edge Brewery</td>\n",
       "      <td>beernut7</td>\n",
       "      <td>2002-08-25 09:19:18</td>\n",
       "      <td>Irish Dry Stout</td>\n",
       "      <td>Latter Days Stout</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39667</th>\n",
       "      <td>3810</td>\n",
       "      <td>1413</td>\n",
       "      <td>Desert Edge Brewery</td>\n",
       "      <td>beernut7</td>\n",
       "      <td>2002-08-25 09:14:49</td>\n",
       "      <td>American Pale Ale (APA)</td>\n",
       "      <td>Utah Pale Ale</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>653695</th>\n",
       "      <td>3788</td>\n",
       "      <td>1412</td>\n",
       "      <td>Red Rock Brewing Company</td>\n",
       "      <td>beernut7</td>\n",
       "      <td>2002-08-22 09:17:39</td>\n",
       "      <td>Hefeweizen</td>\n",
       "      <td>Red Rock Bavarian Weiss</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>653706</th>\n",
       "      <td>3787</td>\n",
       "      <td>1412</td>\n",
       "      <td>Red Rock Brewing Company</td>\n",
       "      <td>beernut7</td>\n",
       "      <td>2002-08-22 09:22:22</td>\n",
       "      <td>American Amber / Red Ale</td>\n",
       "      <td>Red Rock Amber Ale</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>3.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>653726</th>\n",
       "      <td>3822</td>\n",
       "      <td>1412</td>\n",
       "      <td>Red Rock Brewing Company</td>\n",
       "      <td>beernut7</td>\n",
       "      <td>2002-08-22 09:15:37</td>\n",
       "      <td>German Pilsener</td>\n",
       "      <td>Red Rock Pilsner</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>653740</th>\n",
       "      <td>3786</td>\n",
       "      <td>1412</td>\n",
       "      <td>Red Rock Brewing Company</td>\n",
       "      <td>beernut7</td>\n",
       "      <td>2002-08-22 09:20:39</td>\n",
       "      <td>Dunkelweizen</td>\n",
       "      <td>Red Rock Dunkel Weizen</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        beer_beerid  brewery_id              brewery_name review_profilename  \\\n",
       "37234          3806        1413       Desert Edge Brewery           beernut7   \n",
       "39648          3804        1413       Desert Edge Brewery           beernut7   \n",
       "39667          3810        1413       Desert Edge Brewery           beernut7   \n",
       "653695         3788        1412  Red Rock Brewing Company           beernut7   \n",
       "653706         3787        1412  Red Rock Brewing Company           beernut7   \n",
       "653726         3822        1412  Red Rock Brewing Company           beernut7   \n",
       "653740         3786        1412  Red Rock Brewing Company           beernut7   \n",
       "\n",
       "               review_time                beer_style                beer_name  \\\n",
       "37234  2002-08-24 14:01:10            Czech Pilsener                 Pub Pils   \n",
       "39648  2002-08-25 09:19:18           Irish Dry Stout        Latter Days Stout   \n",
       "39667  2002-08-25 09:14:49   American Pale Ale (APA)            Utah Pale Ale   \n",
       "653695 2002-08-22 09:17:39                Hefeweizen  Red Rock Bavarian Weiss   \n",
       "653706 2002-08-22 09:22:22  American Amber / Red Ale       Red Rock Amber Ale   \n",
       "653726 2002-08-22 09:15:37           German Pilsener         Red Rock Pilsner   \n",
       "653740 2002-08-22 09:20:39              Dunkelweizen   Red Rock Dunkel Weizen   \n",
       "\n",
       "        beer_abv  review_overall  review_aroma  review_appearance  \\\n",
       "37234        4.0             0.0           2.0                0.0   \n",
       "39648        4.0             0.0           4.0                0.0   \n",
       "39667        4.0             0.0           3.0                0.0   \n",
       "653695       4.0             0.0           2.0                0.0   \n",
       "653706       4.0             0.0           3.0                0.0   \n",
       "653726       4.0             0.0           2.0                0.0   \n",
       "653740       4.0             0.0           2.0                0.0   \n",
       "\n",
       "        review_palate  review_taste  \n",
       "37234             3.0           2.0  \n",
       "39648             2.0           2.0  \n",
       "39667             2.0           2.0  \n",
       "653695            2.5           2.0  \n",
       "653706            2.5           3.5  \n",
       "653726            3.0           1.5  \n",
       "653740            2.5           2.0  "
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "beer_reviews[beer_reviews.review_overall == 0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [],
   "source": [
    "beer_reviews = beer_reviews[beer_reviews.review_overall > 0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x234a59622b0>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x234857ac9e8>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x234a5864a58>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x234a5beb710>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_rating_histogram(\"aroma\")\n",
    "plot_rating_histogram(\"appearance\")\n",
    "plot_rating_histogram(\"palate\")\n",
    "plot_rating_histogram(\"taste\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZsAAAEWCAYAAACwtjr+AAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvNQv5yAAAIABJREFUeJzt3Xt8FdW5//HPA0SjchWCPzBoaIuXAooQBLUqiCJaFFsvxWoFtU0Vb7Tq8VYvtdjS1uMFK3ioUsCiYmk5UosX1FCPFpQEUVFEqaJGKEbudw08vz9mBbdhZ2cnZvYO4ft+vfYrs59Zs9aagewna2btGXN3RERE4tQk2x0QEZHGT8lGRERip2QjIiKxU7IREZHYKdmIiEjslGxERCR2SjbSYJjZA2Z2cz3VdYCZbTCzpuH9bDP7cX3UHep7ysyG1Vd9tWh3lJl9Zmb/yXTbmWZm55nZs9nuh9QP0/dsJBPMbCmwH1ABbAPeBiYD4919ex3q+rG7P1eLbWYDf3b3B2vTVtj2NuBb7n5+bbetT2bWCXgXONDdP02yvh/RPubXQ1sTgTJ3/8XXrSvN9gqAD4Acd6/IRJuSWRrZSCad5u4tgAOB0cB1wEP13YiZNavvOhuIA4GVyRJNQ1c5wpTdmLvrpVfsL2ApcGKV2JHAdqBbeD8RGBWW2wFPAmuAVcD/Ef1x9HDYZjOwAfgvoABw4GLgI+DFhFizUN9s4DfAq8Ba4Alg37CuH9Ff8Tv1FxgEfA58Edp7PaG+H4flJsAvgA+BT4lGbK3Cusp+DAt9+wy4KcVxahW2Lw/1/SLUf2LY5+2hHxOrbLdPlfUbgI7hGM8Jx3E58Adgj7CNAXeHPq8F3gC6AUVhfz8P9fw9lO8I/DX07QPgyhT7MREYB8wENob+fxd4DVgHfAzcllD+o3CcKvt+FDAceCmhjAOXAO8Bq4H7+fLsTFPgv8Px/QC4PPHfX6/sv7LeAb12jxdJkk2IfwRcGpYn8mWy+Q3wAJATXscmfLB8pa6ED/TJ4UN3L5Inm0/Ch+k+4UPzz2FdP6pJNmH5tsqyCetn82WyuQhYAnwDaA78DXi4St/+GPp1OLAVOLSa4zSZKBG2CNu+C1xcXT+rbJtsP3oBfYFmob5FwMiw7mSgFGhNlHgOBTpU/bcI75uEsrcAe4R9fR84uZq+TCRKYMeEbXND/7qH94cBK4AzqhynZgl1DGfnZPNk6O8BRElvUFh3CdGp2XygDfBc1fr0yu5Lp9Ek25YB+yaJfwF0ILo+8YW7/5+HT5UUbnP3je6+uZr1D7v7QnffCNwMnFNPp3fOA+5y9/fdfQNwAzC0yum8X7r7Znd/HXidKOl8RejLD4Ab3H29uy8l+mv9R3XtmLuXuvtcd68I9f0PcHxY/QVRUjuEKJEvcvfl1VTVG8hz99vd/XN3f58ogQ5N0fwT7v6yu2939y3uPtvd3wzv3wAeTehLuka7+xp3/wgoBnqE+DnAve5e5u6riU7TSgOiZCPZtj/RabKqfk80WnjWzN43s+vTqOvjWqz/kGjE1C6tXqbWMdSXWHczogkRlRJnj20iGgFV1Y5o1FC1rv3r2jEzO8jMnjSz/5jZOuDXoR3c/QWi02r3AyvMbLyZtaymqgOBjma2pvIF3MhX97Gqr/x7mFkfMys2s3IzW0s0Gqnt8a/uOHas0l5N/xckw5RsJGvMrDfRB+lLVdeFv+yvdvdvAKcBPzezAZWrq6myppFPp4TlA4j+sv+M6JrC3gn9agrk1aLeZUQfxol1VxCdJqqNz0Kfqtb1SZrbJ+vnOOAdoIu7tyRKELZjA/cx7t4L6AocBFxbTV0fAx+4e+uEVwt3P7UW/XkEmAF0cvdWRKdJrZqytbWc6BRapU7VFZTsULKRjDOzlmY2GHiM6FrIm0nKDDazb5mZEV1Q3hZeEH2If6MOTZ9vZt82s72B24Fp7r6N6LpIrpl918xyiC7K75mw3QqgwMyq+315FPiZmXU2s+ZEo4epXsspvKEvjwN3mFkLMzsQ+Dnw5zSrWAG0NbNWCbEWRMdvg5kdAlxaucLMeofRRg5Rwt1C9cf4VWCdmV1nZnuZWVMz6xb+YEhXC2CVu28xsyOBHyasKyea3FCXf1eIjttVZra/mbUmmukoDYiSjWTS381sPdFfyTcBdwEXVlO2C9FF3g1Es6nGuvvssO43wC/C6ZxratH+w0QXrv9DdMH6SgB3XwuMAB4kGkVsBMoStvtL+LnSzOYnqXdCqPtFoplQW4AratGvRFeE9t8nGvE9Euqvkbu/Q5T43g/HpiNwDdGH+nqiayxTEzZpGWKriU7XrQTuDOseAr4d6vnfkAhPI7pG8gHRKOxBotlz6RoB3B7+D9xClCAq+74JuAN4ObTZtxb1EvbjWaIZda8RzYKr/E6XNAD6UqeINDpmdgrwgLsfWGNhyQiNbERklxdO7Z1qZs3MbH/gVmB6tvslX9LIRkR2eeE63D+JpnFvBv4BXOXu67LaMdlByUZERGKn02giIhK72G5YaGYH89WZL98gmoEyOcQLiG4Jco67rw5TXO8FTiX6stZwd58f6hpGNB0VoltoTArxXkSzi/Yimn1ylbu7me2brI1U/W3Xrp0XFBR8nV0WEdntlJaWfubueTWVy8hptPAluU+APsBlRHPtR4dvhbdx9+vM7FSiaZ+nhnL3unufkDhKgEKiL36VAr1CgnoVuAqYS5Rsxrj7U2b2u2RtpOpjYWGhl5SUxLH7IiKNlpmVunthTeUydRptAPBvd/8QGAJMCvFJwBlheQgw2SNzgdZm1oHoZoGz3H1VGJ3MAgaFdS3dfU64Z9bkKnUla0NERLIgU8lmKNGXzQD2q7zZX/jZPsT356v3MyoLsVTxsiTxVG18hZkVmVmJmZWUl5fXcddERKQmsScbM9sDOJ0vv4VdbdEkMa9DPG3uPt7dC929MC+vxlOOIiJSR5l4ouEpwHx3r7wp4Qoz6+Duy8OpsMqnDpbx1Zvn5RPd4LCM6DkYifHZIZ6fpHyqNmrliy++oKysjC1bttRlc6mj3Nxc8vPzycnJyXZXRKSeZCLZnMuXp9AguuvrMKLnTQwjelBUZfxyM3uMaILA2pAsngF+bWZtQrmBRM/7WGVm68M9lF4BLgDuq6GNWikrK6NFixYUFBQQTZaTuLk7K1eupKysjM6dO2e7OyJST2I9jRa+1XsS0ZMLK40GTjKz98K6yocczSS6+eASopvqjQBw91XAr4B54XV7iEF0B9sHwzb/Bp6qoY1a2bJlC23btlWiySAzo23bthpNijQysY5swp1c21aJrSSanVa1rBNNi05WzwSS3PnW3UuIHvNbNZ60jbpQosk8HXORxkd3EBARkdhl4ppNo3H3rHfrtb6fnXRQvdYnItJQKdns4rZt20bTpk2z3Q2RzCr+TWbb639DZttrhHQarYE744wz6NWrF127dmX8+PEANG/enFtuuYU+ffowZ84cnn/+eY444gi6d+/ORRddxNatWwEoKCjgxhtv5KijjqKwsJD58+dz8skn881vfpMHHngAgA0bNjBgwAB69uxJ9+7deeKJOk3cExFJScmmgZswYQKlpaWUlJQwZswYVq5cycaNG+nWrRuvvPIKhYWFDB8+nKlTp/Lmm29SUVHBuHHjdmzfqVMn5syZw7HHHsvw4cOZNm0ac+fO5ZZbbgGi77RMnz6d+fPnU1xczNVXX40eOyEi9U3JpoEbM2YMhx9+OH379uXjjz/mvffeo2nTppx55pkALF68mM6dO3PQQdH1n2HDhvHiiy/u2P70008HoHv37vTp04cWLVqQl5dHbm4ua9aswd258cYbOeywwzjxxBP55JNPWLFixc4dERH5GnTNpgGbPXs2zz33HHPmzGHvvfemX79+bNmyhdzc3B3XaWoahey5554ANGnSZMdy5fuKigqmTJlCeXk5paWl5OTkUFBQoO+4iEi908imAVu7di1t2rRh77335p133mHu3Lk7lTnkkENYunQpS5YsAeDhhx/m+OOPr1Ub7du3Jycnh+LiYj788MN667+ISCWNbGoh01OVBw0axAMPPMBhhx3GwQcfTN++fXcqk5uby5/+9CfOPvtsKioq6N27N5dccknabZx33nmcdtppFBYW0qNHDw455JD63AURESBDD0/bFSR7eNqiRYs49NBDs9Sj3ZuOvaSkqc8NRkN7eJqIiOzGlGxERCR2SjYiIhI7JRsREYmdko2IiMROyUZERGKn79nURn1Pt9R0ShHZTWhkIylt27Yt210QkUZAyaaBq+4RA1dffTU9e/ZkwIABlJeXA9CvXz9GjhzJ0UcfTbdu3Xj11VcB2LhxIxdddBG9e/fmiCOO2PEYgaVLl3LsscfSs2dPevbsyb/+9S8guidb//79+eEPf0j37t2r7UdlX2666aYdNwutvInnihUr+N73vsfhhx/O4YcfvqPuP//5zxx55JH06NGDn/70p0pmIrsJJZsGrrpHDPTs2ZP58+dz/PHH88tf/nJH+Y0bN/Kvf/2LsWPHctFFFwFwxx13cMIJJzBv3jyKi4u59tpr2bhxI+3bt2fWrFnMnz+fqVOncuWVV+6o59VXX+WOO+7g7bffrrYfle317duX119/neOOO44//vGPAFx55ZUcf/zxvP7668yfP5+uXbuyaNEipk6dyssvv8yCBQto2rQpU6ZMydShFJEs0jWbBm7MmDFMnz4dYMcjBpo0acIPfvADAM4//3y+//3v7yh/7rnnAnDcccexbt061qxZw7PPPsuMGTO48847AdiyZQsfffQRHTt25PLLL9/xwf/uu18+9vrII4+kc+fOKfvRtm1b9thjDwYPHgxAr169mDVrFgAvvPACkydPBqBp06a0atWKhx9+mNLSUnr37g3A5s2bad++ff0fNBFpcGJNNmbWGngQ6AY4cBGwGJgKFABLgXPcfbWZGXAvcCqwCRju7vNDPcOAX4RqR7n7pBDvBUwE9gJmAle5u5vZvsnaiHNf41DdIwaqig7dzsuV792dv/71rxx88MFfWXfbbbex33778frrr7N9+3Zyc3N3rNtnn33S6kdOTs6ONps2bUpFRUW1++PuDBs2jN/8JsP3tRKRrIt7ZHMv8LS7n2VmewB7AzcCz7v7aDO7HrgeuA44BegSXn2AcUCfkDhuBQqJElapmc0IyWMcUATMJUo2g4CnQp3J2tilVPeIge3btzNt2jSGDh3KI488wne+850d20ydOpX+/fvz0ksv0apVK1q1asXJJ5/Mfffdx3333YeZ8dprr3HEEUewdu1a8vPzadKkCZMmTar2+kk6jzqoasCAAYwbN46RI0eybds2Nm7cyIABAxgyZAg/+9nPaN++PatWrWL9+vUceOCB9XPAZLcxds0bGW1vREZba5xiSzZm1hI4DhgO4O6fA5+b2RCgXyg2CZhNlAiGAJM9ug31XDNrbWYdQtlZ7r4q1DsLGGRms4GW7j4nxCcDZxAlm+ra+HoyPFW5ukcM7LPPPrz11lv06tWLVq1aMXXq1B3btGnThqOPPpp169YxYcIEAG6++WZGjhzJYYcdhrtTUFDAk08+yYgRIzjzzDP5y1/+Qv/+/b8ymkmnH6nce++9FBUV8dBDD9G0aVPGjRvHUUcdxahRoxg4cCDbt28nJyeH+++/X8lGZDcQ2yMGzKwHMB54GzgcKAWuAj5x99YJ5Va7exszexIY7e4vhfjzRAmiH5Dr7qNC/GZgM1ECGe3uJ4b4scB17j7YzNYkayNVf3elRww0b96cDRs27BTv168fd955J4WFNd7tu8FrqMdeGoax08/NaHsjvvdoRtvblTSERww0A3oC49z9CGAj0ems6liSmNchnjYzKzKzEjMrqZw+LCIi9S/OZFMGlLn7K+H9NKLksyKcHiP8/DShfKeE7fOBZTXE85PESdHGV7j7eHcvdPfCvLy8Ou1kNiQb1UB0Ib8xjGpEpPGJLdm4+3+Aj82scgrUAKJTajOAYSE2DHgiLM8ALrBIX2Ctuy8HngEGmlkbM2sDDASeCevWm1nfMJPtgip1JWtDRESyIO7ZaFcAU8JMtPeBC4kS3ONmdjHwEXB2KDuTaNrzEqKpzxcCuPsqM/sVMC+Uu71ysgBwKV9OfX4qvABGV9OGiIhkQazJxt0XEE1ZrmpAkrIOXFZNPROACUniJUTf4akaX5msDRERyQ7drkZERGKn29XUwtgFY+u1vhE96v+rYsOHD2fw4MGcddZZ1ZaZOHEiAwcOpGPHjvXevohIMhrZ7IYmTpzIsmXLai4oIlJPlGwauKVLl3LIIYcwbNgwDjvsMM466yw2bdrE7bffTu/evenWrRtFRUUk+3JusjLTpk2jpKSE8847jx49erB582ZKS0s5/vjj6dWrFyeffDLLly/Pwp6KSGOmZLMLWLx4MUVFRbzxxhu0bNmSsWPHcvnllzNv3jwWLlzI5s2befLJJ3faLlmZs846i8LCQqZMmcKCBQto1qwZV1xxBdOmTaO0tJSLLrqIm266KQt7KSKNma7Z7AI6derEMcccA0SPFBgzZgydO3fmd7/7HZs2bWLVqlV07dqV00477SvbFRcX11hm8eLFLFy4kJNOOgmInszZoUOHzOyYiOw2lGx2AckeGzBixAhKSkro1KkTt912206PHtiyZUuNZSC67X/Xrl2ZM2dOrPsgIrs3nUbbBXz00Uc7ksGjjz6645EC7dq1Y8OGDUybNm2nbSoTS7IyLVq0YP369QAcfPDBlJeX76j/iy++4K233op1f0Rk96ORTS3EMVU5HYceeiiTJk3ipz/9KV26dOHSSy9l9erVdO/enYKCgh1PvkzUunVrfvKTnyQtM3z4cC655BL22msv5syZw7Rp07jyyitZu3YtFRUVjBw5kq5du2ZyF0Vq5eM1m7PdBaml2B4xsKtpqI8YWLp0KYMHD2bhwoVZ7UemNYRjLw3XDX86I6Pt/ebC/81oe7uShvCIAREREUDJpsErKCjY7UY1ItL46JqNiOxyDn/ps8w2eGFmm2uMNLIREZHYKdmIiEjslGxERCR2umZTC+X3/aFe68u74vKU69esWcMjjzzCiBG1/37PPffcQ1FREXvvvXdduyciUm80smnA1qxZw9ixdXuGzj333MOmTZvquUciInWjkU0Ddv311/Pvf/+bHj160L9/f9544w1Wr17NF198wahRoxgyZAgbN27knHPOoaysjG3btnHzzTezYsUKli1bRv/+/WnXrh3FxcU8++yz3HrrrWzdupVvfvOb/OlPf6J58+bZ3kUR2U0o2TRgo0ePZuHChSxYsICKigo2bdpEy5Yt+eyzz+jbty+nn346Tz/9NB07duQf//gHAGvXrqVVq1bcddddFBcX065dOz777DNGjRrFc889xz777MNvf/tb7rrrLm655ZYs76GI7C6UbHYR7s6NN97Iiy++SJMmTfjkk09YsWIF3bt355prruG6665j8ODBHHvssTttO3fuXN5+++0djyn4/PPPOeqoozK9CyKyG1Oy2UVMmTKF8vJySktLycnJoaCggC1btnDQQQdRWlrKzJkzueGGGxg4cOBOIxZ356STTuLRRx/NUu9FZHcX6wQBM1tqZm+a2QIzKwmxfc1slpm9F362CXEzszFmtsTM3jCzngn1DAvl3zOzYQnxXqH+JWFbS9XGribxUQBr166lffv25OTkUFxczIcffgjAsmXL2HvvvTn//PO55pprmD9//k7b9u3bl5dffpklS5YAsGnTJt59990s7JGI7K4yMbLp7+6J95a4Hnje3Ueb2fXh/XXAKUCX8OoDjAP6mNm+wK1AIeBAqZnNcPfVoUwRMBeYCQwCnkrRxtdS01Tl+ta2bVuOOeYYunXrRu/evXnnnXcoLCykR48eHHLIIQC8+eabXHvttTRp0oScnBzGjRsHQFFREaeccgodOnSguLiYiRMncu6557J161YARo0axUEHHZTR/RGR3Vesjxgws6VAYWKyMbPFQD93X25mHYDZ7n6wmf1PWH40sVzly91/GuL/A8wOr2J3PyTEz60sV10bqfraUB8xsLvSsZdUHrv4Oxltb+hDL2W0vV1JQ3nEgAPPmlmpmRWF2H7uvhwg/Gwf4vsDHydsWxZiqeJlSeKp2vgKMysysxIzKykvL6/jLoqISE3iPo12jLsvM7P2wCwzeydFWUsS8zrE0+bu44HxEI1sarOtiIikL9aRjbsvCz8/BaYDRwIrwqktws9PQ/EyoFPC5vnAshri+UnipGijLvtQ102ljnTMRRqf2JKNme1jZi0ql4GBwEJgBlA5o2wY8ERYngFcEGal9QXWhlNgzwADzaxNmFU2EHgmrFtvZn3DLLQLqtSVrI1ayc3NZeXKlfrwyyB3Z+XKleTm5ma7KyJSj+I8jbYfMD3MRm4GPOLuT5vZPOBxM7sY+Ag4O5SfCZwKLAE2ER5X5O6rzOxXwLxQ7nZ3XxWWLwUmAnsRzUJ7KsRHV9NGreTn51NWVoau52RWbm4u+fn5NRcUkV1GbMnG3d8HDk8SXwkMSBJ34LJq6poATEgSLwG6pdtGbeXk5NC5c+evW42IyG5Pd30WEZHYKdmIiEjslGxERCR2SjYiIhI7JRsREYmdko2IiMROyUZERGKnZCMiIrFTshERkdgp2YiISOyUbEREJHZKNiIiEjslGxERiZ2SjYiIxE7JRkREYqdkIyIisVOyERGR2CnZiIhI7JRsREQkdko2IiISOyUbERGJnZKNiIjELvZkY2ZNzew1M3syvO9sZq+Y2XtmNtXM9gjxPcP7JWF9QUIdN4T4YjM7OSE+KMSWmNn1CfGkbYiISHZkYmRzFbAo4f1vgbvdvQuwGrg4xC8GVrv7t4C7QznM7NvAUKArMAgYGxJYU+B+4BTg28C5oWyqNkREJAtiTTZmlg98F3gwvDfgBGBaKDIJOCMsDwnvCesHhPJDgMfcfau7fwAsAY4MryXu/r67fw48BgypoQ0REcmCuEc29wD/BWwP79sCa9y9IrwvA/YPy/sDHwOE9WtD+R3xKttUF0/VxleYWZGZlZhZSXl5eV33UUREahBbsjGzwcCn7l6aGE5S1GtYV1/xnYPu49290N0L8/LykhUREZF6kFayMbNj0olVcQxwupktJTrFdQLRSKe1mTULZfKBZWG5DOgU6m4GtAJWJcarbFNd/LMUbYiISBakO7K5L83YDu5+g7vnu3sB0QX+F9z9PKAYOCsUGwY8EZZnhPeE9S+4u4f40DBbrTPQBXgVmAd0CTPP9ghtzAjbVNeGiIhkQbNUK83sKOBoIM/Mfp6wqiXQtI5tXgc8ZmajgNeAh0L8IeBhM1tCNKIZCuDub5nZ48DbQAVwmbtvC/27HHgm9GWCu79VQxsiIpIFKZMNsAfQPJRrkRBfx5cjhxq5+2xgdlh+n2gmWdUyW4Czq9n+DuCOJPGZwMwk8aRtiIhIdqRMNu7+T+CfZjbR3T/MUJ9ERKSRqWlkU2lPMxsPFCRu4+4nxNEpERFpXNJNNn8BHiD6cua2+LojIiKNUbrJpsLdx8XaExERabTSnfr8dzMbYWYdzGzfylesPRMRkUYj3ZFN5fdfrk2IOfCN+u2OiNSXu2e9m9H2fnbSQRltT3YtaSUbd+8cd0dERKTxSivZmNkFyeLuPrl+uyMiIo1RuqfReics5wIDgPmAko2IiNQo3dNoVyS+N7NWwMOx9EhERBqduj5iYBPRDTFFRERqlO41m7/z5TNhmgKHAo/H1SkREWlc0r1mc2fCcgXwobuXxdAfERFphNK9ZvNPM9uPLycKvBdfl0SkPsxfNzXDLd6c4fZkV5LuabRzgN8TPSbAgPvM7Fp3nxZj30REGoTy+/6Q0fbyrrg8o+1lQrqn0W4Cerv7pwBmlgc8ByjZiIhIjdKdjdakMtEEK2uxrYiI7ObSHdk8bWbPAI+G9z8gyRMyRaThOPb5NzLb4JmZbU52LSmTjZl9C9jP3a81s+8D3yG6ZjMHmJKB/omISCNQ08jmHuBGAHf/G/A3ADMrDOtOi7V3IlJnLbcuz3YXRHao6bpLgbvvNBZ39xKiR0SLiIjUqKZkk5ti3V6pNjSzXDN71cxeN7O3zOyXId7ZzF4xs/fMbKqZ7RHie4b3S8L6goS6bgjxxWZ2ckJ8UIgtMbPrE+JJ2xARkeyoKdnMM7OfVA2a2cVAaQ3bbgVOcPfDgR7AIDPrC/wWuNvduwCrgYtD+YuB1e7+LeDuUA4z+zYwFOgKDALGmllTM2sK3A+cAnwbODeUJUUbIiKSBTUlm5HAhWY228z+O7z+CfwYuCrVhh7ZEN7mhJcDJ/Dl93MmAWeE5SHhPWH9ADOzEH/M3be6+wfAEuDI8Fri7u+7++fAY8CQsE11bYiISBaknCDg7iuAo82sP9AthP/h7i+kU3kYfZQC3yIahfwbWOPuFaFIGbB/WN4f+Di0W2Fma4G2IT43odrEbT6uEu8TtqmuDRERyYJ0741WDBTXtnJ33wb0MLPWwHSiu0XvVCz8tGrWVRdPNipLVX4nZlYEFAEccMAByYqIiEg9yMhdANx9DdF91foCrc2sMsnlA8vCchnQCSCsbwWsSoxX2aa6+Gcp2qjar/HuXujuhXl5eV9nF0VEJIXYko2Z5YURDWa2F3AisIhohHRWKDYMeCIszwjvCetfcHcP8aFhtlpnooe2vQrMA7qEmWd7EE0imBG2qa4NERHJgnRvV1MXHYBJ4bpNE+Bxd3/SzN4GHjOzUcBrwEOh/EPAw2a2hGhEMxTA3d8ys8eBt4mepXNZOD2HmV0OPEP0QLcJ7v5WqOu6atoQEam9pf+X4QZ337s+11r4MugRSeLvE80kqxrfApxdTV13AHckic8kyT3aqmtDRESyQ3duFhGR2CnZiIhI7JRsREQkdnFOEBARaRTKVm/OaHuN8YsYGtmIiEjslGxERCR2SjYiIhI7JRsREYmdko2IiMROs9FERGqw2FZltL2dbr3SCGhkIyIisVOyERGR2CnZiIhI7JRsREQkdko2IiISOyUbERGJnZKNiIjETslGRERip2QjIiKxU7IREZHYKdmIiEjslGxERCTLZYknAAAMAElEQVR2sSUbM+tkZsVmtsjM3jKzq0J8XzObZWbvhZ9tQtzMbIyZLTGzN8ysZ0Jdw0L598xsWEK8l5m9GbYZY2aWqg0REcmOOO/6XAFc7e7zzawFUGpms4DhwPPuPtrMrgeuB64DTgG6hFcfYBzQx8z2BW4FCgEP9cxw99WhTBEwF5gJDAKeCnUma0Mka8YuGJvR9vbNaGsiqcU2snH35e4+PyyvBxYB+wNDgEmh2CTgjLA8BJjskblAazPrAJwMzHL3VSHBzAIGhXUt3X2OuzswuUpdydoQEZEsyMjzbMysgOgRDa8A+7n7cogSkpm1D8X2Bz5O2KwsxFLFy5LESdFG1X4VEY2MOOCAA+q4dyLpmfPvlRlt77sZbU0ktdgnCJhZc+CvwEh3X5eqaJKY1yGeNncf7+6F7l6Yl5dXm01FRKQWYk02ZpZDlGimuPvfQnhFOAVG+PlpiJcBnRI2zweW1RDPTxJP1YaIiGRBnLPRDHgIWOTudyWsmgFUzigbBjyREL8gzErrC6wNp8KeAQaaWZswq2wg8ExYt97M+oa2LqhSV7I2REQkC+K8ZnMM8CPgTTNbEGI3AqOBx83sYuAj4OywbiZwKrAE2ARcCODuq8zsV8C8UO52d698IPilwERgL6JZaE+FeHVtiIhIFsSWbNz9JZJfVwEYkKS8A5dVU9cEYEKSeAnQLUl8ZbI2REQkO3QHARERiZ2SjYiIxE7JRkREYqdkIyIisVOyERGR2GXkdjUiAt+d+Uy2uyCSNRrZiIhI7JRsREQkdko2IiISOyUbERGJnZKNiIjETslGRERip2QjIiKxU7IREZHYKdmIiEjslGxERCR2SjYiIhI7JRsREYmdko2IiMROyUZERGKnZCMiIrFTshERkdjFlmzMbIKZfWpmCxNi+5rZLDN7L/xsE+JmZmPMbImZvWFmPRO2GRbKv2dmwxLivczszbDNGDOzVG2IiEj2xDmymQgMqhK7Hnje3bsAz4f3AKcAXcKrCBgHUeIAbgX6AEcCtyYkj3GhbOV2g2poQ0REsiS2ZOPuLwKrqoSHAJPC8iTgjIT4ZI/MBVqbWQfgZGCWu69y99XALGBQWNfS3ee4uwOTq9SVrA0REcmSTF+z2c/dlwOEn+1DfH/g44RyZSGWKl6WJJ6qjZ2YWZGZlZhZSXl5eZ13SkREUmsoEwQsSczrEK8Vdx/v7oXuXpiXl1fbzUVEJE2ZTjYrwikwws9PQ7wM6JRQLh9YVkM8P0k8VRsiIpIlmU42M4DKGWXDgCcS4heEWWl9gbXhFNgzwEAzaxMmBgwEngnr1ptZ3zAL7YIqdSVrQ0REsqRZXBWb2aNAP6CdmZURzSobDTxuZhcDHwFnh+IzgVOBJcAm4EIAd19lZr8C5oVyt7t75aSDS4lmvO0FPBVepGhDRESyJLZk4+7nVrNqQJKyDlxWTT0TgAlJ4iVAtyTxlcnaEBHZVZTf94eMtZV3xeUZaaehTBAQEZFGTMlGRERip2QjIiKxU7IREZHYxTZBQGRX8Pef/TLbXRDZLSjZyG5t+daFNReqJy0z1pLs6speezZjbeWRmdloSjYiIg3MYqt6D+P4HJGhdnTNRkREYqdkIyIisVOyERGR2CnZiIhI7JRsREQkdpqNJill+nsop919a0bbE5HMULKRlDL5PZRsaLl1eba7ILJb0Gk0ERGJnZKNiIjETslGRERip2s2kpKuaYhIfdDIRkREYqdkIyIisdNptF1Q+X1/yHYXRERqRclmFzR90T8z1paewSIi9aHRJhszGwTcCzQFHnT30XG1pZGGiEhqjTLZmFlT4H7gJKAMmGdmM9z97Tjay+RIAzRDTER2PY0y2QBHAkvc/X0AM3sMGALEkmz04S8ikpq5e7b7UO/M7CxgkLv/OLz/EdDH3S+vUq4IKApvDwYW17HJdsBnddw2TupX7ahftaN+1U5j7deB7p5XU6HGOrKxJLGdsqq7jwfGf+3GzErcvfDr1lPf1K/aUb9qR/2qnd29X431ezZlQKeE9/nAsiz1RURkt9dYk808oIuZdTazPYChwIws90lEZLfVKE+juXuFmV0OPEM09XmCu78VY5Nf+1RcTNSv2lG/akf9qp3dul+NcoKAiIg0LI31NJqIiDQgSjYiIhI7JZs0mdkEM/vUzBZWs97MbIyZLTGzN8ysZwPpVz8zW2tmC8Lrlgz1q5OZFZvZIjN7y8yuSlIm48cszX5l/JiZWa6ZvWpmr4d+/TJJmT3NbGo4Xq+YWUED6ddwMytPOF4/jrtfCW03NbPXzOzJJOsyfrzS7FdWjpeZLTWzN0ObJUnWx/v76O56pfECjgN6AgurWX8q8BTRd3z6Aq80kH71A57MwvHqAPQMyy2Ad4FvZ/uYpdmvjB+zcAyah+Uc4BWgb5UyI4AHwvJQYGoD6ddw4A+Z/j8W2v458Eiyf69sHK80+5WV4wUsBdqlWB/r76NGNmly9xeBVSmKDAEme2Qu0NrMOjSAfmWFuy939/lheT2wCNi/SrGMH7M0+5Vx4RhsCG9zwqvq7J0hwKSwPA0YYGbJvsCc6X5lhZnlA98FHqymSMaPV5r9aqhi/X1Usqk/+wMfJ7wvowF8iAVHhdMgT5lZ10w3Hk5fHEH0V3GirB6zFP2CLByzcOplAfApMMvdqz1e7l4BrAXaNoB+AZwZTr1MM7NOSdbH4R7gv4Dt1azPyvFKo1+QnePlwLNmVmrRrbqqivX3Ucmm/qR1i5wsmE9076LDgfuA/81k42bWHPgrMNLd11VdnWSTjByzGvqVlWPm7tvcvQfRHS+ONLNuVYpk5Xil0a+/AwXufhjwHF+OJmJjZoOBT929NFWxJLFYj1ea/cr48QqOcfeewCnAZWZ2XJX1sR4vJZv60yBvkePu6ypPg7j7TCDHzNplom0zyyH6QJ/i7n9LUiQrx6ymfmXzmIU21wCzgUFVVu04XmbWDGhFBk+hVtcvd1/p7lvD2z8CvTLQnWOA081sKfAYcIKZ/blKmWwcrxr7laXjhbsvCz8/BaYT3R0/Uay/j0o29WcGcEGY0dEXWOvuWX/2gJn9v8rz1GZ2JNG/+coMtGvAQ8Aid7+rmmIZP2bp9Csbx8zM8sysdVjeCzgReKdKsRnAsLB8FvCChyu72exXlfP6pxNdB4uVu9/g7vnuXkB08f8Fdz+/SrGMH690+pWN42Vm+5hZi8plYCBQdQZrrL+PjfJ2NXEws0eJZim1M7My4Faii6W4+wPATKLZHEuATcCFDaRfZwGXmlkFsBkYGvcvXHAM8CPgzXC+H+BG4ICEvmXjmKXTr2wcsw7AJIse/NcEeNzdnzSz24ESd59BlCQfNrMlRH+hD425T+n260ozOx2oCP0anoF+JdUAjlc6/crG8doPmB7+hmoGPOLuT5vZJZCZ30fdrkZERGKn02giIhI7JRsREYmdko2IiMROyUZERGKnZCMiIrFTshHJADPbFu62u9DM/l753ZUU5Vub2YiE9x3NbFr8PRWJh6Y+i2SAmW1w9+ZheRLwrrvfkaJ8AdEdg6veGkZkl6SRjUjmzSHc4NDMmpvZ82Y236JnjQwJZUYD3wyjod+bWYGFZxZZ9DyUv5nZ02b2npn9rrJiM7vYzN41s9lm9kcz+0PG904kCd1BQCSDwjfxBxB9ux1gC/A9d18X7r8218xmANcD3cINMCtHOol6EN2xeiuw2MzuA7YBNxM932g98ALweqw7JJImJRuRzNgr3B6nACgFZoW4Ab8Od+DdTjTi2S+N+p5397UAZvY2cCDQDvinu68K8b8AB9XnTojUlU6jiWTG5jBKORDYA7gsxM8D8oBeYf0KIDeN+rYmLG8j+sMx9geDidSVko1IBoXRyJXANeFRB62Inn/yhZn1J0pGEJ0Ga1HL6l8FjjezNuGW+mfWV79Fvi4lG5EMc/fXiK6lDAWmAIVmVkI0ynknlFkJvBymSv8+zXo/AX5N9OTR54C3iZ5OKZJ1mvos0oiYWXN33xBGNtOBCe4+Pdv9EtHIRqRxuS1MRFgIfECGHwMuUh2NbEREJHYa2YiISOyUbEREJHZKNiIiEjslGxERiZ2SjYiIxO7/A7EycJUX/jNqAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x23484c81240>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_rating_histogram(\"aroma\", show = False)\n",
    "plot_rating_histogram(\"appearance\", show = False)\n",
    "plot_rating_histogram(\"palate\", show = False)\n",
    "plot_rating_histogram(\"taste\", show = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x23484385780>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_rating_histogram(\"overall\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x234828049e8>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_rating_histogram(\"aroma\", show = False)\n",
    "plot_rating_histogram(\"appearance\", show = False)\n",
    "plot_rating_histogram(\"palate\", show = False)\n",
    "plot_rating_histogram(\"taste\", show = False)\n",
    "plot_rating_histogram(\"overall\", show = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "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>review_overall</th>\n",
       "      <th>review_aroma</th>\n",
       "      <th>review_appearance</th>\n",
       "      <th>review_palate</th>\n",
       "      <th>review_taste</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>review_overall</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.616017</td>\n",
       "      <td>0.501661</td>\n",
       "      <td>0.701920</td>\n",
       "      <td>0.789822</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>review_aroma</th>\n",
       "      <td>0.616017</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.561036</td>\n",
       "      <td>0.616946</td>\n",
       "      <td>0.716774</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>review_appearance</th>\n",
       "      <td>0.501661</td>\n",
       "      <td>0.561036</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.566637</td>\n",
       "      <td>0.546972</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>review_palate</th>\n",
       "      <td>0.701920</td>\n",
       "      <td>0.616946</td>\n",
       "      <td>0.566637</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.734132</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>review_taste</th>\n",
       "      <td>0.789822</td>\n",
       "      <td>0.716774</td>\n",
       "      <td>0.546972</td>\n",
       "      <td>0.734132</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   review_overall  review_aroma  review_appearance  \\\n",
       "review_overall           1.000000      0.616017           0.501661   \n",
       "review_aroma             0.616017      1.000000           0.561036   \n",
       "review_appearance        0.501661      0.561036           1.000000   \n",
       "review_palate            0.701920      0.616946           0.566637   \n",
       "review_taste             0.789822      0.716774           0.546972   \n",
       "\n",
       "                   review_palate  review_taste  \n",
       "review_overall          0.701920      0.789822  \n",
       "review_aroma            0.616946      0.716774  \n",
       "review_appearance       0.566637      0.546972  \n",
       "review_palate           1.000000      0.734132  \n",
       "review_taste            0.734132      1.000000  "
      ]
     },
     "execution_count": 108,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "beer_reviews[[\"review_overall\", \"review_aroma\", \"review_appearance\", \"review_palate\", \"review_taste\"]].corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "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>review_aroma</th>\n",
       "      <th>1.0</th>\n",
       "      <th>1.5</th>\n",
       "      <th>2.0</th>\n",
       "      <th>2.5</th>\n",
       "      <th>3.0</th>\n",
       "      <th>3.5</th>\n",
       "      <th>4.0</th>\n",
       "      <th>4.5</th>\n",
       "      <th>5.0</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>review_overall</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",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1.0</th>\n",
       "      <td>3397</td>\n",
       "      <td>2051</td>\n",
       "      <td>2486</td>\n",
       "      <td>1005</td>\n",
       "      <td>982</td>\n",
       "      <td>475</td>\n",
       "      <td>428</td>\n",
       "      <td>97</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.5</th>\n",
       "      <td>1271</td>\n",
       "      <td>3080</td>\n",
       "      <td>3731</td>\n",
       "      <td>1782</td>\n",
       "      <td>1487</td>\n",
       "      <td>861</td>\n",
       "      <td>574</td>\n",
       "      <td>144</td>\n",
       "      <td>45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2.0</th>\n",
       "      <td>1064</td>\n",
       "      <td>3279</td>\n",
       "      <td>10935</td>\n",
       "      <td>7491</td>\n",
       "      <td>7400</td>\n",
       "      <td>4252</td>\n",
       "      <td>2910</td>\n",
       "      <td>730</td>\n",
       "      <td>164</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2.5</th>\n",
       "      <td>401</td>\n",
       "      <td>1567</td>\n",
       "      <td>8149</td>\n",
       "      <td>14617</td>\n",
       "      <td>16157</td>\n",
       "      <td>9771</td>\n",
       "      <td>5995</td>\n",
       "      <td>1522</td>\n",
       "      <td>344</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3.0</th>\n",
       "      <td>401</td>\n",
       "      <td>1345</td>\n",
       "      <td>8749</td>\n",
       "      <td>20223</td>\n",
       "      <td>56557</td>\n",
       "      <td>44179</td>\n",
       "      <td>26879</td>\n",
       "      <td>6106</td>\n",
       "      <td>1205</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3.5</th>\n",
       "      <td>114</td>\n",
       "      <td>547</td>\n",
       "      <td>3816</td>\n",
       "      <td>11226</td>\n",
       "      <td>56768</td>\n",
       "      <td>113878</td>\n",
       "      <td>90173</td>\n",
       "      <td>22399</td>\n",
       "      <td>2896</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4.0</th>\n",
       "      <td>135</td>\n",
       "      <td>447</td>\n",
       "      <td>3442</td>\n",
       "      <td>7535</td>\n",
       "      <td>45824</td>\n",
       "      <td>144134</td>\n",
       "      <td>265930</td>\n",
       "      <td>101293</td>\n",
       "      <td>14024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4.5</th>\n",
       "      <td>21</td>\n",
       "      <td>131</td>\n",
       "      <td>810</td>\n",
       "      <td>1917</td>\n",
       "      <td>11819</td>\n",
       "      <td>41363</td>\n",
       "      <td>138681</td>\n",
       "      <td>106127</td>\n",
       "      <td>23516</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5.0</th>\n",
       "      <td>69</td>\n",
       "      <td>77</td>\n",
       "      <td>444</td>\n",
       "      <td>563</td>\n",
       "      <td>3034</td>\n",
       "      <td>6399</td>\n",
       "      <td>25812</td>\n",
       "      <td>33032</td>\n",
       "      <td>21890</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "review_aroma     1.0   1.5    2.0    2.5    3.0     3.5     4.0     4.5    5.0\n",
       "review_overall                                                                \n",
       "1.0             3397  2051   2486   1005    982     475     428      97     33\n",
       "1.5             1271  3080   3731   1782   1487     861     574     144     45\n",
       "2.0             1064  3279  10935   7491   7400    4252    2910     730    164\n",
       "2.5              401  1567   8149  14617  16157    9771    5995    1522    344\n",
       "3.0              401  1345   8749  20223  56557   44179   26879    6106   1205\n",
       "3.5              114   547   3816  11226  56768  113878   90173   22399   2896\n",
       "4.0              135   447   3442   7535  45824  144134  265930  101293  14024\n",
       "4.5               21   131    810   1917  11819   41363  138681  106127  23516\n",
       "5.0               69    77    444    563   3034    6399   25812   33032  21890"
      ]
     },
     "execution_count": 110,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "review_overall_vs_aroma_crosstab = pd.crosstab(beer_reviews.review_overall, beer_reviews.review_aroma)\n",
    "review_overall_vs_aroma_crosstab"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x234a5b312e8>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (10, 8))\n",
    "ax = sns.heatmap(review_overall_vs_aroma_crosstab, annot = True, cmap = \"coolwarm\")\n",
    "ax.invert_yaxis()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x234bd291828>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "review_overall_vs_appearance_crosstab = pd.crosstab(beer_reviews.review_overall, beer_reviews.review_appearance)\n",
    "plt.figure(figsize = (10, 8))\n",
    "ax = sns.heatmap(review_overall_vs_appearance_crosstab, annot = True, cmap = \"coolwarm\")\n",
    "ax.invert_yaxis()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [],
   "source": [
    "wine_reviews = pd.read_csv(\"data/winemag-data_first150k.csv\", index_col = 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "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>variety</th>\n",
       "      <th>winery</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>US</td>\n",
       "      <td>This tremendous 100% varietal wine hails from ...</td>\n",
       "      <td>Martha's Vineyard</td>\n",
       "      <td>96</td>\n",
       "      <td>235.0</td>\n",
       "      <td>California</td>\n",
       "      <td>Napa Valley</td>\n",
       "      <td>Napa</td>\n",
       "      <td>Cabernet Sauvignon</td>\n",
       "      <td>Heitz</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Spain</td>\n",
       "      <td>Ripe aromas of fig, blackberry and cassis are ...</td>\n",
       "      <td>Carodorum Selección Especial Reserva</td>\n",
       "      <td>96</td>\n",
       "      <td>110.0</td>\n",
       "      <td>Northern Spain</td>\n",
       "      <td>Toro</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Tinta de Toro</td>\n",
       "      <td>Bodega Carmen Rodríguez</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>US</td>\n",
       "      <td>Mac Watson honors the memory of a wine once ma...</td>\n",
       "      <td>Special Selected Late Harvest</td>\n",
       "      <td>96</td>\n",
       "      <td>90.0</td>\n",
       "      <td>California</td>\n",
       "      <td>Knights Valley</td>\n",
       "      <td>Sonoma</td>\n",
       "      <td>Sauvignon Blanc</td>\n",
       "      <td>Macauley</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>US</td>\n",
       "      <td>This spent 20 months in 30% new French oak, an...</td>\n",
       "      <td>Reserve</td>\n",
       "      <td>96</td>\n",
       "      <td>65.0</td>\n",
       "      <td>Oregon</td>\n",
       "      <td>Willamette Valley</td>\n",
       "      <td>Willamette Valley</td>\n",
       "      <td>Pinot Noir</td>\n",
       "      <td>Ponzi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>France</td>\n",
       "      <td>This is the top wine from La Bégude, named aft...</td>\n",
       "      <td>La Brûlade</td>\n",
       "      <td>95</td>\n",
       "      <td>66.0</td>\n",
       "      <td>Provence</td>\n",
       "      <td>Bandol</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Provence red blend</td>\n",
       "      <td>Domaine de la Bégude</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  country                                        description  \\\n",
       "0      US  This tremendous 100% varietal wine hails from ...   \n",
       "1   Spain  Ripe aromas of fig, blackberry and cassis are ...   \n",
       "2      US  Mac Watson honors the memory of a wine once ma...   \n",
       "3      US  This spent 20 months in 30% new French oak, an...   \n",
       "4  France  This is the top wine from La Bégude, named aft...   \n",
       "\n",
       "                            designation  points  price        province  \\\n",
       "0                     Martha's Vineyard      96  235.0      California   \n",
       "1  Carodorum Selección Especial Reserva      96  110.0  Northern Spain   \n",
       "2         Special Selected Late Harvest      96   90.0      California   \n",
       "3                               Reserve      96   65.0          Oregon   \n",
       "4                            La Brûlade      95   66.0        Provence   \n",
       "\n",
       "            region_1           region_2             variety  \\\n",
       "0        Napa Valley               Napa  Cabernet Sauvignon   \n",
       "1               Toro                NaN       Tinta de Toro   \n",
       "2     Knights Valley             Sonoma     Sauvignon Blanc   \n",
       "3  Willamette Valley  Willamette Valley          Pinot Noir   \n",
       "4             Bandol                NaN  Provence red blend   \n",
       "\n",
       "                    winery  \n",
       "0                    Heitz  \n",
       "1  Bodega Carmen Rodríguez  \n",
       "2                 Macauley  \n",
       "3                    Ponzi  \n",
       "4     Domaine de la Bégude  "
      ]
     },
     "execution_count": 123,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wine_reviews.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(150930, 10)"
      ]
     },
     "execution_count": 125,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wine_reviews.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "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",
       "variety         object\n",
       "winery          object\n",
       "dtype: object"
      ]
     },
     "execution_count": 124,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wine_reviews.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "variety\n",
       "Chardonnay                  14482\n",
       "Pinot Noir                  14291\n",
       "Cabernet Sauvignon          12800\n",
       "Red Blend                   10062\n",
       "Bordeaux-style Red Blend     7347\n",
       "Sauvignon Blanc              6320\n",
       "Syrah                        5825\n",
       "Riesling                     5524\n",
       "Merlot                       5070\n",
       "Zinfandel                    3799\n",
       "dtype: int64"
      ]
     },
     "execution_count": 129,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top_wine_styles = wine_reviews.groupby(\"variety\").size().sort_values(ascending = False).head(10)\n",
    "top_wine_styles"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x234d58266a0>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.barh(range(len(top_wine_styles.index)), top_wine_styles)\n",
    "\n",
    "plt.title(\"Top 10 wines\")\n",
    "plt.xlabel(\"Number of reviews\")\n",
    "plt.yticks(range(len(top_wine_styles)), top_wine_styles.index)\n",
    "plt.gca().invert_yaxis()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x234d5ab3780>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(wine_reviews.points, bins = 20)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "87.8884184721394"
      ]
     },
     "execution_count": 137,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wine_reviews.points.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "88.0"
      ]
     },
     "execution_count": 138,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wine_reviews.points.median()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    87\n",
       "dtype: int64"
      ]
     },
     "execution_count": 139,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wine_reviews.points.mode()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.14283263376595492"
      ]
     },
     "execution_count": 140,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wine_reviews.points.skeww()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x234dda5d9e8>"
      ]
     },
     "execution_count": 145,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x234dcff7e48>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(wine_reviews.points, wine_reviews.price, alpha = 0.2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "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>variety</th>\n",
       "      <th>winery</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>34920</th>\n",
       "      <td>France</td>\n",
       "      <td>A big, powerful wine that sums up the richness...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>99</td>\n",
       "      <td>2300.0</td>\n",
       "      <td>Bordeaux</td>\n",
       "      <td>Pauillac</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Bordeaux-style Red Blend</td>\n",
       "      <td>Château Latour</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      country                                        description designation  \\\n",
       "34920  France  A big, powerful wine that sums up the richness...         NaN   \n",
       "\n",
       "       points   price  province  region_1 region_2                   variety  \\\n",
       "34920      99  2300.0  Bordeaux  Pauillac      NaN  Bordeaux-style Red Blend   \n",
       "\n",
       "               winery  \n",
       "34920  Château Latour  "
      ]
     },
     "execution_count": 143,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wine_reviews[wine_reviews.price == wine_reviews.price.max()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "metadata": {},
   "outputs": [],
   "source": [
    "highest_rated_wines = wine_reviews[wine_reviews.points == wine_reviews.points.max()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "24"
      ]
     },
     "execution_count": 148,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(highest_rated_wines)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 152,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAD8CAYAAABn919SAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvNQv5yAAADalJREFUeJzt3W2MpfVZgPHrdrdAoa0s7lC3LDhgCAkxUcjEQDGNgUIpENCED0tapbVmE41Kq6YuIbHxG2jTVBNTuqFUokhbt2gJVJFQGmNiVmd5XViQBbawFLpDGqmpiUB6++H8Bw7T2ZdznmfPOXN7/ZLJnPOch33u+Wfm4sxzXiYyE0nS2vcT0x5AktQPgy5JRRh0SSrCoEtSEQZdkoow6JJUhEGXpCIMuiQVYdAlqYj1kzzYxo0bc35+fpKHlKQ1b9euXa9k5tzh9pto0Ofn51lcXJzkISVpzYuI7xzJfp5ykaQiDLokFWHQJakIgy5JRRh0SSrisEGPiFsj4kBE7B7adlJE3BcRT7fPG47umJKkwzmSe+h/BVy6Yts24P7MPBO4v12XJE3RYYOemf8CfH/F5quA29rl24Bf6XkuSdKIxj2H/t7MfAmgfT65v5EkSeM46q8UjYitwFaA00477Wgfrnfz2+6Z2rH33Xj51I4tae0Z9x769yJiE0D7fOBgO2bm9sxcyMyFubnDvhWBJGlM4wb9LuDadvla4Bv9jCNJGteRPG3xDuDfgLMiYn9EfAK4Ebg4Ip4GLm7XJUlTdNhz6Jl5zUFuuqjnWSRJHfhKUUkqwqBLUhEGXZKKMOiSVIRBl6QiDLokFWHQJakIgy5JRRh0SSrCoEtSEQZdkoow6JJUhEGXpCIMuiQVYdAlqQiDLklFGHRJKsKgS1IRBl2SijDoklSEQZekIgy6JBVh0CWpCIMuSUUYdEkqwqBLUhEGXZKKMOiSVIRBl6QiDLokFWHQJakIgy5JRXQKekR8KiIej4jdEXFHRBzX12CSpNGMHfSIOAX4PWAhM38OWAds6WswSdJoup5yWQ+8MyLWA8cD3+0+kiRpHGMHPTNfBD4LPA+8BLyamf/c12CSpNF0OeWyAbgKOB14H3BCRHx0lf22RsRiRCwuLS2NP6kk6ZC6nHL5IPBcZi5l5uvAncD7V+6UmdszcyEzF+bm5jocTpJ0KF2C/jxwXkQcHxEBXATs6WcsSdKoupxD3wnsAB4EHmv/1vae5pIkjWh9l/84Mz8DfKanWSRJHfhKUUkqwqBLUhEGXZKKMOiSVIRBl6QiDLokFWHQJakIgy5JRRh0SSrCoEtSEQZdkoow6JJUhEGXpCIMuiQVYdAlqQiDLklFdPoDF5M0v+2eaY8gSTPNe+iSVIRBl6QiDLokFWHQJakIgy5JRRh0SSrCoEtSEQZdkoow6JJUhEGXpCIMuiQVYdAlqQiDLklFGHRJKsKgS1IRBl2SiugU9Ig4MSJ2RMSTEbEnIs7vazBJ0mi6/sWiPwf+KTOvjohjgON7mEmSNIaxgx4R7wE+AHwMIDNfA17rZyxJ0qi6nHI5A1gCvhwRD0XELRFxQk9zSZJG1CXo64FzgS9k5jnAD4FtK3eKiK0RsRgRi0tLSx0OJ0k6lC5B3w/sz8yd7foOBoF/m8zcnpkLmbkwNzfX4XCSpEMZO+iZ+TLwQkSc1TZdBDzRy1SSpJF1fZbL7wK3t2e4PAt8vPtIkqRxdAp6Zj4MLPQ0iySpA18pKklFGHRJKsKgS1IRBl2SijDoklSEQZekIgy6JBVh0CWpCIMuSUUYdEkqwqBLUhEGXZKKMOiSVIRBl6QiDLokFWHQJakIgy5JRRh0SSrCoEtSEQZdkoow6JJUhEGXpCIMuiQVYdAlqQiDLklFGHRJKsKgS1IRBl2SijDoklSEQZekIgy6JBVh0CWpiM5Bj4h1EfFQRNzdx0CSpPH0cQ/9OmBPD/+OJKmDTkGPiM3A5cAt/YwjSRpX13vonwc+Dfyoh1kkSR2MHfSIuAI4kJm7DrPf1ohYjIjFpaWlcQ8nSTqMLvfQLwCujIh9wFeACyPib1bulJnbM3MhMxfm5uY6HE6SdChjBz0zr8/MzZk5D2wBvpWZH+1tMknSSHweuiQVsb6PfyQzvw18u49/S5I0Hu+hS1IRBl2SijDoklSEQZekIgy6JBVh0CWpCIMuSUUYdEkqwqBLUhEGXZKKMOiSVIRBl6QiDLokFWHQJakIgy5JRRh0SSqilz9woaNjfts9Uznuvhsvn8pxpaOt+s+U99AlqQiDLklFGHRJKsKgS1IRBl2SijDoklSEQZekIgy6JBVh0CWpCIMuSUUYdEkqwqBLUhEGXZKKMOiSVIRBl6QiDLokFTF20CPi1Ih4ICL2RMTjEXFdn4NJkkbT5S8WvQH8QWY+GBHvBnZFxH2Z+URPs0mSRjD2PfTMfCkzH2yX/xvYA5zS12CSpNH0cg49IuaBc4Cdq9y2NSIWI2JxaWmpj8NJklbROegR8S7g68AnM/MHK2/PzO2ZuZCZC3Nzc10PJ0k6iE5Bj4h3MIj57Zl5Zz8jSZLG0eVZLgF8CdiTmZ/rbyRJ0ji63EO/APg14MKIeLh9XNbTXJKkEY39tMXM/FcgepxFktSBrxSVpCIMuiQVYdAlqQiDLklFGHRJKsKgS1IRBl2SijDoklSEQZekIgy6JBVh0CWpCIMuSUUYdEkqwqBLUhEGXZKKGPv90KVK5rfdM7Vj77vx8qkdW7V4D12SijDoklSEQZekIgy6JBVh0CWpCIMuSUUYdEkqwqBLUhEGXZKKMOiSVIRBl6QiDLokFWHQJakIgy5JRRh0SSrCoEtSEZ2CHhGXRsRTEbE3Irb1NZQkaXRjBz0i1gF/CXwYOBu4JiLO7mswSdJoutxD/0Vgb2Y+m5mvAV8BrupnLEnSqLoE/RTghaHr+9s2SdIUdPkj0bHKtvyxnSK2Alvb1f+NiN0djjktG4FXpj3EiMaeOW7qeZLRrMW1hrW53v/v1npa4qbOM//MkezUJej7gVOHrm8Gvrtyp8zcDmwHiIjFzFzocMypWItzr8WZwbknaS3ODGtz7knN3OWUy38AZ0bE6RFxDLAFuKufsSRJoxr7HnpmvhERvwPcC6wDbs3Mx3ubTJI0ki6nXMjMbwLfHOE/2d7leFO0FudeizODc0/SWpwZ1ubcE5k5Mn/scUxJ0hrkS/8lqYiJBX1W3yYgIk6NiAciYk9EPB4R17XtJ0XEfRHxdPu8oW2PiPiL9nU8GhHnTnH2dRHxUETc3a6fHhE728xfbQ9WExHHtut72+3zU5z5xIjYERFPtjU/f42s9afa98fuiLgjIo6bxfWOiFsj4sDw04PHWd+IuLbt/3REXDuFmf+sfY88GhF/HxEnDt12fZv5qYj40ND2iTZmtbmHbvvDiMiI2NiuT2atM/OofzB40PQZ4AzgGOAR4OxJHPsIZtsEnNsuvxv4TwZvZfCnwLa2fRtwU7t8GfCPDJ6Hfx6wc4qz/z7wt8Dd7frXgC3t8s3Ab7XLvw3c3C5vAb46xZlvA36zXT4GOHHW15rBC+aeA945tM4fm8X1Bj4AnAvsHto20voCJwHPts8b2uUNE575EmB9u3zT0Mxnt34cC5zeurJuGo1Zbe62/VQGTxb5DrBxkms9qW+y84F7h65fD1w/qW/yEWf9BnAx8BSwqW3bBDzVLn8RuGZo/zf3m/Ccm4H7gQuBu9s3yitDPwRvrnn75jq/XV7f9ospzPyeFsZYsX3W13r5VdEntfW7G/jQrK43ML8ijiOtL3AN8MWh7W/bbxIzr7jtV4Hb2+W3tWN5rafVmNXmBnYAPw/s462gT2StJ3XKZU28TUD71fgcYCfw3sx8CaB9PrntNitfy+eBTwM/atd/CvivzHxjlbnenLnd/mrbf9LOAJaAL7dTRbdExAnM+Fpn5ovAZ4HngZcYrN8uZn+9l426vjOx7kN+g8G9W5jxmSPiSuDFzHxkxU0TmXtSQT+itwmYpoh4F/B14JOZ+YND7brKtol+LRFxBXAgM3cNb15l1zyC2yZpPYNfUb+QmecAP2RwCuBgZmLuds75Kga/4r8POIHBu4yuNGvrfTgHm3Nm5o+IG4A3gNuXN62y20zMHBHHAzcAf7zazats633uSQX9iN4mYFoi4h0MYn57Zt7ZNn8vIja12zcBB9r2WfhaLgCujIh9DN7l8kIG99hPjIjl1xYMz/XmzO32nwS+P8mBh+bYn5k72/UdDAI/y2sN8EHgucxcyszXgTuB9zP7671s1PWdiXVvDxBeAXwk2/mIQ8w2CzP/LIP/6T/SfjY3Aw9GxE8fYr5e555U0Gf2bQIiIoAvAXsy83NDN90FLD/ifC2Dc+vL23+9PWp9HvDq8q+zk5KZ12fm5sycZ7CW38rMjwAPAFcfZOblr+Xqtv/E73Fl5svACxFxVtt0EfAEM7zWzfPAeRFxfPt+WZ57ptd7yKjrey9wSURsaL+dXNK2TUxEXAr8EXBlZv7P0E13AVvaM4lOB84E/p0ZaExmPpaZJ2fmfPvZ3M/gCRcvM6m1PtoPGgyd7L+MwTNIngFumNRxj2CuX2LwK86jwMPt4zIG5zzvB55un09q+weDP+zxDPAYsDDl+X+Zt57lcgaDb+69wN8Bx7btx7Xre9vtZ0xx3l8AFtt6/wODR/Znfq2BPwGeBHYDf83gWRYzt97AHQzO87/OICifGGd9GZy33ts+Pj6FmfcyOLe8/DN589D+N7SZnwI+PLR9oo1Zbe4Vt+/jrQdFJ7LWvlJUkorwlaKSVIRBl6QiDLokFWHQJakIgy5JRRh0SSrCoEtSEQZdkor4P7g+0HzXv36TAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x234dd1a42b0>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(highest_rated_wines.price)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 153,
   "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>variety</th>\n",
       "      <th>winery</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2145</th>\n",
       "      <td>France</td>\n",
       "      <td>Full of ripe fruit, opulent and concentrated, ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>100</td>\n",
       "      <td>848.0</td>\n",
       "      <td>Bordeaux</td>\n",
       "      <td>Pessac-Léognan</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Bordeaux-style White Blend</td>\n",
       "      <td>Château Haut-Brion</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26296</th>\n",
       "      <td>France</td>\n",
       "      <td>A wine that has created its own universe. It h...</td>\n",
       "      <td>Clos du Mesnil</td>\n",
       "      <td>100</td>\n",
       "      <td>1400.0</td>\n",
       "      <td>Champagne</td>\n",
       "      <td>Champagne</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Chardonnay</td>\n",
       "      <td>Krug</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51886</th>\n",
       "      <td>France</td>\n",
       "      <td>A wine that has created its own universe. It h...</td>\n",
       "      <td>Clos du Mesnil</td>\n",
       "      <td>100</td>\n",
       "      <td>1400.0</td>\n",
       "      <td>Champagne</td>\n",
       "      <td>Champagne</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Chardonnay</td>\n",
       "      <td>Krug</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83536</th>\n",
       "      <td>France</td>\n",
       "      <td>A wine that has created its own universe. It h...</td>\n",
       "      <td>Clos du Mesnil</td>\n",
       "      <td>100</td>\n",
       "      <td>1400.0</td>\n",
       "      <td>Champagne</td>\n",
       "      <td>Champagne</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Chardonnay</td>\n",
       "      <td>Krug</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      country                                        description  \\\n",
       "2145   France  Full of ripe fruit, opulent and concentrated, ...   \n",
       "26296  France  A wine that has created its own universe. It h...   \n",
       "51886  France  A wine that has created its own universe. It h...   \n",
       "83536  France  A wine that has created its own universe. It h...   \n",
       "\n",
       "          designation  points   price   province        region_1 region_2  \\\n",
       "2145              NaN     100   848.0   Bordeaux  Pessac-Léognan      NaN   \n",
       "26296  Clos du Mesnil     100  1400.0  Champagne       Champagne      NaN   \n",
       "51886  Clos du Mesnil     100  1400.0  Champagne       Champagne      NaN   \n",
       "83536  Clos du Mesnil     100  1400.0  Champagne       Champagne      NaN   \n",
       "\n",
       "                          variety              winery  \n",
       "2145   Bordeaux-style White Blend  Château Haut-Brion  \n",
       "26296                  Chardonnay                Krug  \n",
       "51886                  Chardonnay                Krug  \n",
       "83536                  Chardonnay                Krug  "
      ]
     },
     "execution_count": 153,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "highest_rated_wines[highest_rated_wines.price > 600]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Australia\n",
      "19355     300.0\n",
      "84035     300.0\n",
      "119195    300.0\n",
      "Name: price, dtype: float64\n",
      "France\n",
      "26296    1400.0\n",
      "51886    1400.0\n",
      "83536    1400.0\n",
      "Name: price, dtype: float64\n",
      "France\n",
      "2145    848.0\n",
      "Name: price, dtype: float64\n",
      "Italy\n",
      "24151     460.0\n",
      "41521     460.0\n",
      "119521    460.0\n",
      "Name: price, dtype: float64\n",
      "Italy\n",
      "111087    210.0\n",
      "138867    210.0\n",
      "Name: price, dtype: float64\n",
      "Italy\n",
      "28954    195.0\n",
      "78004    195.0\n",
      "Name: price, dtype: float64\n",
      "US\n",
      "92916    215.0\n",
      "Name: price, dtype: float64\n",
      "US\n",
      "98647     100.0\n",
      "122767    100.0\n",
      "Name: price, dtype: float64\n",
      "US\n",
      "114272    245.0\n",
      "143522    245.0\n",
      "Name: price, dtype: float64\n",
      "US\n",
      "19354     65.0\n",
      "84034     65.0\n",
      "119194    65.0\n",
      "Name: price, dtype: float64\n",
      "US\n",
      "89399     200.0\n",
      "137099    200.0\n",
      "Name: price, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "for (country, description), data in highest_rated_wines.groupby([\"country\", \"description\"]):\n",
    "    print(country)\n",
    "    print(data.price)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "metadata": {},
   "outputs": [],
   "source": [
    "top_rated_wines = wine_reviews[wine_reviews.points > 95]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['US', 'Spain', 'France', 'Italy', 'Australia', 'Austria',\n",
       "       'Portugal', 'Hungary', 'Germany', 'Argentina'], dtype=object)"
      ]
     },
     "execution_count": 162,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top_rated_wines.country.unique()"
   ]
  },
  {
   "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": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}