{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Scotch Whiskey Data Exploration Notebook\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Setup polars\n",
    "\n",
    "Just increasing the size of the output to be able to read it easier.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "polars.config.Config"
      ]
     },
     "execution_count": 161,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import polars as pl\n",
    "\n",
    "pl.Config.set_fmt_str_lengths(900)\n",
    "pl.Config.set_tbl_width_chars(900)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Extract data from placemat\n",
    "\n",
    "I manually input the data from the placemat into the list of dictionaries below. Where I made edits I also commented why the edits were made.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "metadata": {},
   "outputs": [],
   "source": [
    "placement_data = [\n",
    "    # 1998\n",
    "    {\"tasting_year\": 1998, \"rank\": 1, \"name\": \"Macallan (12)\"},\n",
    "    {\"tasting_year\": 1998, \"rank\": 2, \"name\": \"Glenrothes (15)\"},\n",
    "    {\"tasting_year\": 1998, \"rank\": 3, \"name\": \"Bowmore (15)\"},\n",
    "    {\"tasting_year\": 1998, \"rank\": 4, \"name\": \"Glenkinchie (10)\"},\n",
    "    {\"tasting_year\": 1998, \"rank\": 5, \"name\": \"Talisker (10)\"},\n",
    "    # 1999\n",
    "    {\"tasting_year\": 1999, \"rank\": 1, \"name\": \"Glenmorangie (18)\"},\n",
    "    {\"tasting_year\": 1999, \"rank\": 2, \"name\": \"Macallan (18)\"},\n",
    "    {\"tasting_year\": 1999, \"rank\": 3, \"name\": \"Tobermory (Ledaig 1974)\"},\n",
    "    {\"tasting_year\": 1999, \"rank\": 4, \"name\": \"Scapa (12)\"},\n",
    "    {\"tasting_year\": 1999, \"rank\": 5, \"name\": \"Bunnahabhain (12)\"},\n",
    "    # 2000\n",
    "    {\"tasting_year\": 2000, \"rank\": 1, \"name\": \"Glenmorangie (1971)\"},\n",
    "    {\"tasting_year\": 2000, \"rank\": 2, \"name\": \"Highland Park (12)\"},\n",
    "    {\"tasting_year\": 2000, \"rank\": 3, \"name\": \"Balvenie (15)\"},\n",
    "    {\"tasting_year\": 2000, \"rank\": 4, \"name\": \"Dalwhinnie (15)\"},\n",
    "    # Assume Bowmaore was a typo and should be Bowmore.\n",
    "    {\"tasting_year\": 2000, \"rank\": 5, \"name\": \"Bowmore (12)\"},\n",
    "    # 2001\n",
    "    {\"tasting_year\": 2001, \"rank\": 1, \"name\": \"Macallan (25)\"},\n",
    "    {\"tasting_year\": 2001, \"rank\": 2, \"name\": \"Glengoyne (17)\"},\n",
    "    {\"tasting_year\": 2001, \"rank\": 3, \"name\": \"Knockando (12)\"},\n",
    "    {\"tasting_year\": 2001, \"rank\": 4, \"name\": \"Oban (14)\"},\n",
    "    {\"tasting_year\": 2001, \"rank\": 5, \"name\": \"Talisker (10)\"},\n",
    "    # 2002\n",
    "    {\"tasting_year\": 2002, \"rank\": 1, \"name\": \"Highland Park (1977)\"},\n",
    "    {\"tasting_year\": 2002, \"rank\": 2, \"name\": \"Coleburn (21)\"},\n",
    "    {\"tasting_year\": 2002, \"rank\": 3, \"name\": \"Glenglassaugh (1974)\"},\n",
    "    {\"tasting_year\": 2002, \"rank\": 4, \"name\": \"Lagavulin (16)\"},\n",
    "    {\"tasting_year\": 2002, \"rank\": 5, \"name\": \"Glenkinchie (Distiller's Edition)\"},\n",
    "    # 2003\n",
    "    {\"tasting_year\": 2003, \"rank\": 1, \"name\": \"Glenfiddich (21)\"},\n",
    "    {\"tasting_year\": 2003, \"rank\": 2, \"name\": \"Teaninich (21)\"},\n",
    "    {\"tasting_year\": 2003, \"rank\": 3, \"name\": \"St. Magdalene (25)\"},\n",
    "    {\"tasting_year\": 2003, \"rank\": 4, \"name\": \"Ardbeg (17)\"},\n",
    "    {\"tasting_year\": 2003, \"rank\": 5, \"name\": \"Linkwood (25)\"},\n",
    "    # 2004\n",
    "    {\"tasting_year\": 2004, \"rank\": 1, \"name\": \"Balvenie (25)\"},\n",
    "    {\"tasting_year\": 2004, \"rank\": 2, \"name\": \"Macallan (1841 Replica)\"},\n",
    "    {\"tasting_year\": 2004, \"rank\": 3, \"name\": \"Provenance (10)\"},\n",
    "    {\"tasting_year\": 2004, \"rank\": 4, \"name\": \"Bowmore (10)\"},\n",
    "    {\"tasting_year\": 2004, \"rank\": 5, \"name\": \"Old Pulteney (12)\"},\n",
    "    # 2005\n",
    "    {\"tasting_year\": 2005, \"rank\": 1, \"name\": \"Highland Park (25)\"},\n",
    "    {\"tasting_year\": 2005, \"rank\": 2, \"name\": \"Glen Ord (12)\"},\n",
    "    {\"tasting_year\": 2005, \"rank\": 3, \"name\": \"Inverleven (1986)\"},\n",
    "    {\"tasting_year\": 2005, \"rank\": 4, \"name\": \"Tobermory (Mull Village 10)\"},\n",
    "    {\"tasting_year\": 2005, \"rank\": 5, \"name\": \"Caol Ila (Cask Strength)\"},\n",
    "    # 2006\n",
    "    {\"tasting_year\": 2006, \"rank\": 1, \"name\": \"Poit Dhubh (12)\"},\n",
    "    {\"tasting_year\": 2006, \"rank\": 2, \"name\": \"Balblair (16)\"},\n",
    "    {\"tasting_year\": 2006, \"rank\": 3, \"name\": \"Glenburgie (Glencraig 29)\"},\n",
    "    {\"tasting_year\": 2006, \"rank\": 4, \"name\": \"Auchentoshan (21)\"},\n",
    "    {\"tasting_year\": 2006, \"rank\": 5, \"name\": \"Fettercairn (13)\"},\n",
    "    # 2007\n",
    "    {\"tasting_year\": 2007, \"rank\": 1, \"name\": \"Macallan (35)\"},\n",
    "    {\"tasting_year\": 2007, \"rank\": 2, \"name\": \"Jura (Superstition ?)\"},\n",
    "    {\"tasting_year\": 2007, \"rank\": 3, \"name\": \"Highland Park (30)\"},\n",
    "    {\"tasting_year\": 2007, \"rank\": 4, \"name\": \"Glen Ord (25)\"},\n",
    "    {\"tasting_year\": 2007, \"rank\": 5, \"name\": \"St. Magdalene (1975)\"},\n",
    "    # 2008\n",
    "    {\"tasting_year\": 2008, \"rank\": 1, \"name\": \"Glenfarclas (30)\"},\n",
    "    {\"tasting_year\": 2008, \"rank\": 2, \"name\": \"Scapa (26)\"},\n",
    "    {\"tasting_year\": 2008, \"rank\": 3, \"name\": \"Pittyvaich (1976)\"},\n",
    "    {\"tasting_year\": 2008, \"rank\": 4, \"name\": \"Auchentoshan (18)\"},\n",
    "    {\"tasting_year\": 2008, \"rank\": 5, \"name\": \"Arran (?)\"},\n",
    "    # 2009\n",
    "    {\"tasting_year\": 2009, \"rank\": 1, \"name\": \"Glenmorangie (25)\"},\n",
    "    # TODO: Is Glenrothes and Glenrothes the same?\n",
    "    {\"tasting_year\": 2009, \"rank\": 2, \"name\": \"Glenrothes (18)\"},\n",
    "    {\"tasting_year\": 2009, \"rank\": 3, \"name\": \"Brora (24)\"},\n",
    "    {\"tasting_year\": 2009, \"rank\": 4, \"name\": \"Glenfarclas (Blairfindy 31)\"},\n",
    "    {\"tasting_year\": 2009, \"rank\": 5, \"name\": \"Arran (10 Burns' 250th Anniversary)\"},\n",
    "    # 2010\n",
    "    {\"tasting_year\": 2010, \"rank\": 1, \"name\": \"Glenlivet (XXV)\"},\n",
    "    {\"tasting_year\": 2010, \"rank\": 2, \"name\": \"Tamdhu (18)\"},\n",
    "    {\"tasting_year\": 2010, \"rank\": 3, \"name\": \"Rosebank (18)\"},\n",
    "    {\"tasting_year\": 2010, \"rank\": 4, \"name\": \"Port Ellen (1982)\"},\n",
    "    {\"tasting_year\": 2010, \"rank\": 5, \"name\": \"Old Pulteney (17)\"},\n",
    "    # 2011\n",
    "    {\"tasting_year\": 2011, \"rank\": 1, \"name\": \"Bruichladdich (16)\"},\n",
    "    {\"tasting_year\": 2011, \"rank\": 2, \"name\": \"Glen Ord (Singleton 12)\"},\n",
    "    {\"tasting_year\": 2011, \"rank\": 3, \"name\": \"Glenfarclas (40)\"},\n",
    "    {\"tasting_year\": 2011, \"rank\": 4, \"name\": \"Scapa (16)\"},\n",
    "    {\"tasting_year\": 2011, \"rank\": 5, \"name\": \"Bladnoch (1992)\"},\n",
    "    # 2012\n",
    "    {\"tasting_year\": 2012, \"rank\": 1, \"name\": \"Macallan (1969)\"},\n",
    "    {\"tasting_year\": 2012, \"rank\": 2, \"name\": \"Balblair (1989)\"},\n",
    "    {\"tasting_year\": 2012, \"rank\": 3, \"name\": \"Balvenie (21)\"},\n",
    "    {\"tasting_year\": 2012, \"rank\": 4, \"name\": \"Highland Park (12)\"},\n",
    "    {\"tasting_year\": 2012, \"rank\": 5, \"name\": \"Tobermory (15)\"},\n",
    "    # 2013\n",
    "    {\"tasting_year\": 2013, \"rank\": 1, \"name\": \"Glengoyne (21)\"},\n",
    "    {\"tasting_year\": 2013, \"rank\": 2, \"name\": \"Glen Keith (1968)\"},\n",
    "    {\"tasting_year\": 2013, \"rank\": 3, \"name\": \"Glen Grant (1974)\"},\n",
    "    {\"tasting_year\": 2013, \"rank\": 4, \"name\": \"Jura (Prophency ?)\"},\n",
    "    {\"tasting_year\": 2013, \"rank\": 5, \"name\": \"Linkwood (12)\"},\n",
    "    # 2014\n",
    "    {\"tasting_year\": 2014, \"rank\": 1, \"name\": \"Glenfiddich (30)\"},\n",
    "    {\"tasting_year\": 2014, \"rank\": 2, \"name\": \"Highland Park (Loki)\"},\n",
    "    {\"tasting_year\": 2014, \"rank\": 3, \"name\": \"Littlemill (21)\"},\n",
    "    {\"tasting_year\": 2014, \"rank\": 4, \"name\": \"Mackinlay Shackleton\"},\n",
    "    {\"tasting_year\": 2014, \"rank\": 5, \"name\": \"Kilchoman (3)\"},\n",
    "    # 2015\n",
    "    {\"tasting_year\": 2015, \"rank\": 1, \"name\": \"Arbelour (18)\"},\n",
    "    {\"tasting_year\": 2015, \"rank\": 2, \"name\": \"Glenmorangie (Signet)\"},\n",
    "    {\"tasting_year\": 2015, \"rank\": 3, \"name\": \"Macallan (Ruby)\"},\n",
    "    {\"tasting_year\": 2015, \"rank\": 4, \"name\": \"Tomatin (1989)\"},\n",
    "    {\"tasting_year\": 2015, \"rank\": 5, \"name\": \"Bunnahabhain (XXV)\"},\n",
    "    # 2016\n",
    "    {\"tasting_year\": 2016, \"rank\": 1, \"name\": \"Dalmore (King Alex III)\"},\n",
    "    {\"tasting_year\": 2016, \"rank\": 2, \"name\": \"Mortlach (Rare Old)\"},\n",
    "    {\"tasting_year\": 2016, \"rank\": 3, \"name\": \"Lismore (21)\"},\n",
    "    {\"tasting_year\": 2016, \"rank\": 4, \"name\": \"Cragganmore (25)\"},\n",
    "    {\"tasting_year\": 2016, \"rank\": 5, \"name\": \"Ardbeg (Corryvrechan)\"},\n",
    "    # 2017\n",
    "    {\"tasting_year\": 2017, \"rank\": 1, \"name\": \"Glendronach (21)\"},\n",
    "    {\"tasting_year\": 2017, \"rank\": 2, \"name\": \"Bowmore (23)\"},\n",
    "    {\"tasting_year\": 2017, \"rank\": 3, \"name\": \"Glenfarclas (12)\"},\n",
    "    {\"tasting_year\": 2017, \"rank\": 4, \"name\": \"Talisker (25)\"},\n",
    "    {\"tasting_year\": 2017, \"rank\": 5, \"name\": \"Tomintoul (16)\"},\n",
    "    # 2018\n",
    "    {\"tasting_year\": 2018, \"rank\": 1, \"name\": \"Craigellachie (23)\"},\n",
    "    {\"tasting_year\": 2018, \"rank\": 2, \"name\": \"Royal Brackla (21)\"},\n",
    "    # Singleton, not Singletone\n",
    "    {\"tasting_year\": 2018, \"rank\": 3, \"name\": \"Glen Ord (Singleton Tailfire)\"},\n",
    "    {\"tasting_year\": 2018, \"rank\": 4, \"name\": \"Benriach (1997)\"},\n",
    "    {\"tasting_year\": 2018, \"rank\": 5, \"name\": \"Bruichladdich (Black Art)\"},\n",
    "    # 2019\n",
    "    {\"tasting_year\": 2019, \"rank\": 1, \"name\": \"Blair Athol (23)\"},\n",
    "    {\"tasting_year\": 2019, \"rank\": 2, \"name\": \"Longmorn (16)\"},\n",
    "    {\"tasting_year\": 2019, \"rank\": 3, \"name\": \"Arran (Sauternes)\"},\n",
    "    {\"tasting_year\": 2019, \"rank\": 4, \"name\": \"Glenfiddich (Winter Storm)\"},\n",
    "    {\"tasting_year\": 2019, \"rank\": 5, \"name\": \"Kilkerran (12)\"},\n",
    "    # 2020 - COVID\n",
    "    # 2021 - COVID\n",
    "    # 2022\n",
    "    {\"tasting_year\": 2022, \"rank\": 1, \"name\": \"Tullibardine (20)\"},\n",
    "    {\"tasting_year\": 2022, \"rank\": 2, \"name\": \"Aberfeldy (19)\"},\n",
    "    {\"tasting_year\": 2022, \"rank\": 3, \"name\": \"Deanston (18)\"},\n",
    "    {\"tasting_year\": 2022, \"rank\": 4, \"name\": \"Jura (Tastival 2017)\"},\n",
    "    {\"tasting_year\": 2022, \"rank\": 5, \"name\": \"Glen Grant (18)\"},\n",
    "    # 2023\n",
    "    {\"tasting_year\": 2023, \"rank\": 1, \"name\": \"Glenfiddich (23)\"},\n",
    "    {\"tasting_year\": 2023, \"rank\": 2, \"name\": \"Bladnoch (Talia)\"},\n",
    "    {\"tasting_year\": 2023, \"rank\": 3, \"name\": \"Bunnahabhain (12)\"},\n",
    "    {\"tasting_year\": 2023, \"rank\": 4, \"name\": \"Highland Park (15)\"},\n",
    "    {\"tasting_year\": 2023, \"rank\": 5, \"name\": \"Ben Nevis (6)\"},\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Convert the list of dictionaries to a DataFrame.\n",
    "scotch_yearly_rankings = pl.DataFrame(placement_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Extract more information from the column.\n",
    "scotch_yearly_rankings = scotch_yearly_rankings.with_columns(\n",
    "    pl.col(\"name\").str.extract(r\"([\\.\\w\\s]+) \", 1).alias(\"distillery\"),\n",
    "    pl.col(\"name\")\n",
    "    .str.extract(r\"([1-4]?[0-9])\", 1)\n",
    "    .cast(pl.Int32)\n",
    "    .alias(\"age_statement\"),\n",
    "    pl.col(\"name\").str.extract(r\"(\\d{4})\", 1).cast(pl.Int32).alias(\"bottling_year\"),\n",
    "    pl.col(\"name\").str.extract(r\"(\\(.*\\))\", 1).alias(\"metadata\"),\n",
    "    (6 - pl.col(\"rank\")).alias(\"stars\"),\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Extract distillery info from Wikipedia\n",
    "\n",
    "We want more information about each distillery for our analysis. Wikipedia includes a table which of existing and past dead Scotch distilleries. It's not a complete list, but it's enough to get started with.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "metadata": {},
   "outputs": [],
   "source": [
    "from urllib.parse import urljoin\n",
    "\n",
    "import requests\n",
    "\n",
    "base_url = \"https://en.wikipedia.org/\"\n",
    "path = \"/wiki/List_of_whisky_distilleries_in_Scotland\"\n",
    "response = requests.get(urljoin(base_url, path))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 166,
   "metadata": {},
   "outputs": [],
   "source": [
    "from bs4 import BeautifulSoup\n",
    "\n",
    "soup = BeautifulSoup(response.text, \"html.parser\")\n",
    "distilleries_table = soup.find(\"table\", {\"class\": \"wikitable\"})\n",
    "distilleries_rows = distilleries_table.find(\"tbody\").find_all(\"tr\")\n",
    "\n",
    "distillery_data = []\n",
    "for row in distilleries_rows:\n",
    "    cells = row.find_all(\"td\")\n",
    "    if not cells:\n",
    "        continue\n",
    "\n",
    "    distillery_data.append(\n",
    "        {\n",
    "            \"distillery\": cells[0].text.strip(),\n",
    "            \"location\": cells[1].text.strip(),\n",
    "            \"region\": cells[2].text.strip(),\n",
    "            \"founded\": cells[3].text.strip(),\n",
    "            \"owner\": cells[4].text.strip(),\n",
    "        }\n",
    "    )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Some distilleries are missing from the Wikipedia page. For those, I manually searched\n",
    "# online to find the missing information.\n",
    "manually_added_distilleries = [\n",
    "    {\n",
    "        \"distillery\": \"Old Pulteney\",\n",
    "        \"location\": \"Wick\",\n",
    "        \"region\": \"Highland\",\n",
    "        \"founded\": \"1826\",\n",
    "        \"owner\": \"Inver House Distillers\",\n",
    "    },\n",
    "    {\"distillery\": \"Poit Dhubh\", \"location\": \"Isle of Skye\", \"region\": \"Island\"},\n",
    "    {\n",
    "        \"distillery\": \"Lismore\",\n",
    "        \"region\": \"Speyside\",\n",
    "    },\n",
    "    {\n",
    "        \"distillery\": \"Provenance\",\n",
    "        \"region\": \"Unknown\",\n",
    "    },\n",
    "    {\n",
    "        \"distillery\": \"Mull Village\",\n",
    "        \"region\": \"Island\",\n",
    "    },\n",
    "    {\n",
    "        \"distillery\": \"Mackinlay\",\n",
    "        \"region\": \"Highland\",\n",
    "        \"founded\": \"1847\",\n",
    "    },\n",
    "    {\n",
    "        \"distillery\": \"Arbelour\",\n",
    "        \"location\": \"Arbelour\",\n",
    "        \"region\": \"Speyside\",\n",
    "        \"founded\": \"1879\",\n",
    "        \"owner\": \"Chivas Brothers\",\n",
    "    },\n",
    "    {\n",
    "        \"distillery\": \"Benriach\",\n",
    "        \"location\": \"Moray\",\n",
    "        \"region\": \"Speyside\",\n",
    "        \"founded\": \"1898\",\n",
    "        \"owner\": \"Brown-Forman\",\n",
    "    },\n",
    "    {\n",
    "        \"distillery\": \"Kilkerran\",\n",
    "        \"location\": \"Campbeltown\",\n",
    "        \"region\": \"Campbeltown\",\n",
    "        \"founded\": \"1872\",\n",
    "        \"owner\": \"Mitchell's Glengyle Ltd\",\n",
    "    },\n",
    "    {\n",
    "        \"distillery\": \"Aberfeldy\",\n",
    "        \"location\": \"Aberfeldy\",\n",
    "        \"region\": \"Highland\",\n",
    "        \"founded\": \"1896\",\n",
    "        \"owner\": \"Bacardi\",\n",
    "    },\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "metadata": {},
   "outputs": [],
   "source": [
    "dead_distilleries = []\n",
    "\n",
    "soup = BeautifulSoup(response.text, \"html.parser\")\n",
    "dead_distilleries_table = soup.find_all(\"table\", {\"class\": \"wikitable\"})[2]\n",
    "dead_distillery_rows = dead_distilleries_table.find(\"tbody\").find_all(\"tr\")\n",
    "for row in dead_distillery_rows:\n",
    "    cells = row.find_all(\"td\")\n",
    "    if not cells:\n",
    "        continue\n",
    "\n",
    "    dead_distilleries.append(\n",
    "        {\n",
    "            \"distillery\": cells[0].text.strip(),\n",
    "            \"location\": cells[1].text.strip(),\n",
    "            \"region\": cells[2].text.strip(),\n",
    "            \"year_closed\": cells[3].text.strip(),\n",
    "        }\n",
    "    )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Combine all the distillery data into a single DataFrame.\n",
    "distilleries_df = pl.DataFrame(\n",
    "    distillery_data + dead_distilleries + manually_added_distilleries,\n",
    "    infer_schema_length=1000,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Join distillery info with placemat data\n",
    "\n",
    "With the distillery data, we can now join it with the data from the placemat.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 170,
   "metadata": {},
   "outputs": [],
   "source": [
    "enhanced_df = scotch_yearly_rankings.join(distilleries_df, on=\"distillery\", how=\"left\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Start exploring the data\n",
    "\n",
    "This is the fun part! Used seaborn to create the plots.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 171,
   "metadata": {},
   "outputs": [],
   "source": [
    "import seaborn as sns\n",
    "\n",
    "sns.set_theme()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/4l/q3fxbjh106d0tz36zw1smt480000gn/T/ipykernel_83160/1441878289.py:2: DeprecationWarning: `groupby` is deprecated. It has been renamed to `group_by`.\n",
      "  enhanced_df.groupby(\"region\")\n"
     ]
    }
   ],
   "source": [
    "region_aggregate = (\n",
    "    enhanced_df.groupby(\"region\")\n",
    "    .agg(\n",
    "        pl.col(\"distillery\").count().alias(\"count\"),\n",
    "        pl.col(\"stars\").mean().alias(\"stars_mean\"),\n",
    "        pl.col(\"stars\").sum().alias(\"stars_total\"),\n",
    "    )\n",
    "    .sort(\"stars_mean\", descending=True)\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# | label: region-star-mean\n",
    "# | fig-cap: >\n",
    "# |   Average stars per Scotch whiskey region.\n",
    "ax = sns.barplot(data=region_aggregate, x=\"region\", y=\"stars_mean\")\n",
    "ax.set_ylim(0, 5)\n",
    "ax.set_title(\"Average stars per region\")\n",
    "for i in ax.containers:\n",
    "    ax.bar_label(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "metadata": {},
   "outputs": [],
   "source": [
    "distillery_aggregate = enhanced_df.group_by(\"distillery\").agg(\n",
    "    pl.col(\"stars\").mean().alias(\"stars_mean\"),\n",
    "    pl.col(\"stars\").sum().alias(\"stars_total\"),\n",
    "    pl.col(\"stars\").count().alias(\"count\"),\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# | label: top-5-distilleries-by-stars-total\n",
    "# | fig-cap: >\n",
    "# |   Number of stars earned for each distillery in descending order.\n",
    "top_5_distilleries_by_stars_total = distillery_aggregate.sort(\n",
    "    \"stars_total\", descending=True\n",
    ").head(5)\n",
    "\n",
    "ax = sns.barplot(\n",
    "    data=top_5_distilleries_by_stars_total, x=\"distillery\", y=\"stars_total\"\n",
    ")\n",
    "ax.set_title(\"Sum of stars for each distillery\")\n",
    "for i in ax.containers:\n",
    "    ax.bar_label(i)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "personal-blog-6MsEDCzj-py3.11",
   "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": "3.11.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}