coffee_advent_calendar_onyx_2023.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "18651c9c-5234-414c-b690-41ec85d9bec2",
   "metadata": {
    "tags": []
   },
   "source": [
    "# Onyx Advent Calendar 2023\n",
    "\n",
    "I was mainly interested in the different grinders for which they provide settings for each coffee. Beyond that I looked for some patterns in the recipes, without finding much.\n",
    "\n",
    "The base recipe was always the same, 25gr coffee and 400ml water, poured as follows:\n",
    "* Bloom with 50ml\n",
    "* 0:30 strong center pour to 200ml\n",
    "* 1:30 spiral pour to 300ml\n",
    "* 2:00 spiral pour to 400ml\n",
    "\n",
    "The other parameters we scrape from the website below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "548a28a7-b588-4091-9089-317597d23572",
   "metadata": {},
   "outputs": [],
   "source": [
    "from bs4 import BeautifulSoup\n",
    "import matplotlib.pyplot as plt\n",
    "import requests\n",
    "import pandas as pd\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "354b65b8-51a1-4e92-8d1c-1be10e96212f",
   "metadata": {},
   "outputs": [],
   "source": [
    "%load_ext blackcellmagic"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "96e9200e-dcd5-4e7f-9c11-9b23ee9b056b",
   "metadata": {},
   "outputs": [],
   "source": [
    "page = requests.get(\"https://onyxcoffeelab.com/products/2023-advent-calendar\")\n",
    "soup = BeautifulSoup(page.text)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "f03f990e-82ef-4347-ba4f-9e116d4de426",
   "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>Name</th>\n",
       "      <th>Variety</th>\n",
       "      <th>Elevation</th>\n",
       "      <th>Region</th>\n",
       "      <th>Process</th>\n",
       "      <th>Filter</th>\n",
       "      <th>Temperature</th>\n",
       "      <th>Microns</th>\n",
       "      <th>Mahlkonig EK43</th>\n",
       "      <th>Baratza Encore</th>\n",
       "      <th>Baratza Vario+</th>\n",
       "      <th>Comandante C40</th>\n",
       "      <th>Fellow Ode Gen 2</th>\n",
       "      <th>Drain</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Framily</td>\n",
       "      <td>Heirloom</td>\n",
       "      <td>2000</td>\n",
       "      <td>Yirgacheffe</td>\n",
       "      <td>Washed</td>\n",
       "      <td>v60 Cone Filter</td>\n",
       "      <td>95.555556</td>\n",
       "      <td>570</td>\n",
       "      <td>8.2</td>\n",
       "      <td>13</td>\n",
       "      <td>5v</td>\n",
       "      <td>19</td>\n",
       "      <td>3.66</td>\n",
       "      <td>0 days 00:03:40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Ethiopia Hambela Bishan Fugu</td>\n",
       "      <td>Heirloom</td>\n",
       "      <td>2000</td>\n",
       "      <td>Guji</td>\n",
       "      <td>Washed</td>\n",
       "      <td>Kalita 185 Filter</td>\n",
       "      <td>95.000000</td>\n",
       "      <td>756</td>\n",
       "      <td>11.0</td>\n",
       "      <td>21</td>\n",
       "      <td>8q</td>\n",
       "      <td>25</td>\n",
       "      <td>5.00</td>\n",
       "      <td>0 days 00:03:11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Kenya Gichathaini AA</td>\n",
       "      <td>SL28 SL34 &amp; Batian</td>\n",
       "      <td>1800</td>\n",
       "      <td>Nyeri</td>\n",
       "      <td>Washed</td>\n",
       "      <td>Cone filter</td>\n",
       "      <td>95.000000</td>\n",
       "      <td>682</td>\n",
       "      <td>10.0</td>\n",
       "      <td>18</td>\n",
       "      <td>7o</td>\n",
       "      <td>23</td>\n",
       "      <td>4.00</td>\n",
       "      <td>0 days 00:03:30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Colombia Aponte Village</td>\n",
       "      <td>Caturra Bourbon &amp; Castillo</td>\n",
       "      <td>2100</td>\n",
       "      <td>Narino</td>\n",
       "      <td>Honey</td>\n",
       "      <td>v60 Cone Filter</td>\n",
       "      <td>96.111111</td>\n",
       "      <td>653</td>\n",
       "      <td>9.5</td>\n",
       "      <td>17</td>\n",
       "      <td>7e</td>\n",
       "      <td>22</td>\n",
       "      <td>4.30</td>\n",
       "      <td>0 days 00:02:50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Mexico Puebla Zapotitlan #2</td>\n",
       "      <td>Bourbon &amp; Typica</td>\n",
       "      <td>1650</td>\n",
       "      <td>Puebla</td>\n",
       "      <td>Washed</td>\n",
       "      <td>Kalita 185 Flat Filter</td>\n",
       "      <td>96.111111</td>\n",
       "      <td>515</td>\n",
       "      <td>7.5</td>\n",
       "      <td>11</td>\n",
       "      <td>5e</td>\n",
       "      <td>17</td>\n",
       "      <td>3.30</td>\n",
       "      <td>0 days 00:03:10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Costa Rica Las Lajas Black Honey</td>\n",
       "      <td>Catuai</td>\n",
       "      <td>1600</td>\n",
       "      <td>Alajuela</td>\n",
       "      <td>Honey</td>\n",
       "      <td>Kalita 185 Flat Filter</td>\n",
       "      <td>96.111111</td>\n",
       "      <td>490</td>\n",
       "      <td>7.1</td>\n",
       "      <td>10</td>\n",
       "      <td>4s</td>\n",
       "      <td>16</td>\n",
       "      <td>3.00</td>\n",
       "      <td>0 days 00:02:45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Burundi Long Miles Gaharo Hill</td>\n",
       "      <td>Red Bourbon</td>\n",
       "      <td>1950</td>\n",
       "      <td>Kayanza</td>\n",
       "      <td>Washed</td>\n",
       "      <td>v60 Cone Filter</td>\n",
       "      <td>94.444444</td>\n",
       "      <td>528</td>\n",
       "      <td>7.5</td>\n",
       "      <td>12</td>\n",
       "      <td>5i</td>\n",
       "      <td>18</td>\n",
       "      <td>3.30</td>\n",
       "      <td>0 days 00:04:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Guatemala Finca Travesia Natural</td>\n",
       "      <td>Bourbon Catuai &amp; Caturra</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Antigua</td>\n",
       "      <td>Natural</td>\n",
       "      <td>Kalita 185 Filter</td>\n",
       "      <td>94.444444</td>\n",
       "      <td>490</td>\n",
       "      <td>7.1</td>\n",
       "      <td>10</td>\n",
       "      <td>4s</td>\n",
       "      <td>16</td>\n",
       "      <td>3.00</td>\n",
       "      <td>0 days 00:02:50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>El Salvador Santa Rosa Honey</td>\n",
       "      <td>Pacamara</td>\n",
       "      <td>1800</td>\n",
       "      <td>Chalatenango</td>\n",
       "      <td>Honey</td>\n",
       "      <td>Kalita Flat Filter</td>\n",
       "      <td>95.555556</td>\n",
       "      <td>610</td>\n",
       "      <td>8.8</td>\n",
       "      <td>15</td>\n",
       "      <td>6m</td>\n",
       "      <td>20</td>\n",
       "      <td>4.00</td>\n",
       "      <td>0 days 00:02:55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Kenya Muthingini AA</td>\n",
       "      <td>SL28 SL34 &amp; Batian</td>\n",
       "      <td>1800</td>\n",
       "      <td>Kirinyaga</td>\n",
       "      <td>Washed</td>\n",
       "      <td>Kalita 185 Flat Filter</td>\n",
       "      <td>96.111111</td>\n",
       "      <td>721</td>\n",
       "      <td>10.5</td>\n",
       "      <td>20</td>\n",
       "      <td>8f</td>\n",
       "      <td>24</td>\n",
       "      <td>5.00</td>\n",
       "      <td>0 days 00:03:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>El Salvador Santa Rosa</td>\n",
       "      <td>Pacamara</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Chalatenango</td>\n",
       "      <td>Washed</td>\n",
       "      <td>Kalita Flat Filter</td>\n",
       "      <td>94.444444</td>\n",
       "      <td>569</td>\n",
       "      <td>8.2</td>\n",
       "      <td>13</td>\n",
       "      <td>5v</td>\n",
       "      <td>19</td>\n",
       "      <td>3.66</td>\n",
       "      <td>0 days 00:03:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Ethiopia Gedeb Beriti Natural</td>\n",
       "      <td>Heirloom</td>\n",
       "      <td>2000</td>\n",
       "      <td>Gedeb</td>\n",
       "      <td>Natural</td>\n",
       "      <td>V60 Cone Filter</td>\n",
       "      <td>96.111111</td>\n",
       "      <td>515</td>\n",
       "      <td>7.5</td>\n",
       "      <td>11</td>\n",
       "      <td>5e</td>\n",
       "      <td>17</td>\n",
       "      <td>3.30</td>\n",
       "      <td>0 days 00:03:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Krampus PB</td>\n",
       "      <td>SL28 SL34 &amp; Batian</td>\n",
       "      <td>1800</td>\n",
       "      <td>Kirinyaga</td>\n",
       "      <td>Washed</td>\n",
       "      <td>Flat Kalita Filter</td>\n",
       "      <td>93.333333</td>\n",
       "      <td>550</td>\n",
       "      <td>8.0</td>\n",
       "      <td>13</td>\n",
       "      <td>5p</td>\n",
       "      <td>18</td>\n",
       "      <td>3.66</td>\n",
       "      <td>0 days 00:03:05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Panama Creativa Giovana Boutet Anaerobic</td>\n",
       "      <td>Cataui</td>\n",
       "      <td>1500</td>\n",
       "      <td>Alto Quiel</td>\n",
       "      <td>Anaerobic &amp; Natural</td>\n",
       "      <td>Cone Filter</td>\n",
       "      <td>93.333333</td>\n",
       "      <td>490</td>\n",
       "      <td>7.1</td>\n",
       "      <td>10</td>\n",
       "      <td>4s</td>\n",
       "      <td>16</td>\n",
       "      <td>3.00</td>\n",
       "      <td>0 days 00:03:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Kenya Kagunyu AA Natural</td>\n",
       "      <td>SL28 SL34 &amp; Batian</td>\n",
       "      <td>1900</td>\n",
       "      <td>Nyeri</td>\n",
       "      <td>Natural</td>\n",
       "      <td>Cone Filter</td>\n",
       "      <td>96.111111</td>\n",
       "      <td>562</td>\n",
       "      <td>8.2</td>\n",
       "      <td>13</td>\n",
       "      <td>5t</td>\n",
       "      <td>19</td>\n",
       "      <td>3.00</td>\n",
       "      <td>0 days 00:03:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Ethiopia Gedeb Gotiti</td>\n",
       "      <td>Heirloom</td>\n",
       "      <td>2050</td>\n",
       "      <td>Gedeb</td>\n",
       "      <td>Washed</td>\n",
       "      <td>Cone Filter</td>\n",
       "      <td>95.555556</td>\n",
       "      <td>632</td>\n",
       "      <td>9.2</td>\n",
       "      <td>16</td>\n",
       "      <td>6u</td>\n",
       "      <td>21</td>\n",
       "      <td>4.30</td>\n",
       "      <td>0 days 00:03:40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Mexico Finca Las Chicharras Natural</td>\n",
       "      <td>Bourbon &amp; Typica</td>\n",
       "      <td>1500</td>\n",
       "      <td>Jaltenango</td>\n",
       "      <td>Natural</td>\n",
       "      <td>Cone Filter</td>\n",
       "      <td>95.000000</td>\n",
       "      <td>584</td>\n",
       "      <td>8.5</td>\n",
       "      <td>14</td>\n",
       "      <td>6e</td>\n",
       "      <td>19</td>\n",
       "      <td>4.00</td>\n",
       "      <td>0 days 00:03:10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Burundi Long Miles Gaharo Natural</td>\n",
       "      <td>Red Bourbon</td>\n",
       "      <td>1950</td>\n",
       "      <td>Kayanza</td>\n",
       "      <td>Natural</td>\n",
       "      <td>Cone Filter</td>\n",
       "      <td>95.000000</td>\n",
       "      <td>730</td>\n",
       "      <td>10.6</td>\n",
       "      <td>20</td>\n",
       "      <td>8h</td>\n",
       "      <td>24</td>\n",
       "      <td>5.00</td>\n",
       "      <td>0 days 00:03:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Honduras San Andres Lempa</td>\n",
       "      <td>Caturra &amp; Bourbon</td>\n",
       "      <td>1650</td>\n",
       "      <td>Lempira</td>\n",
       "      <td>Washed</td>\n",
       "      <td>Flat Filter</td>\n",
       "      <td>95.555556</td>\n",
       "      <td>618</td>\n",
       "      <td>9.0</td>\n",
       "      <td>16</td>\n",
       "      <td>6p</td>\n",
       "      <td>21</td>\n",
       "      <td>4.00</td>\n",
       "      <td>0 days 00:03:30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Ethiopia Yirgacheffe Halo Lot #8</td>\n",
       "      <td>Heirloom</td>\n",
       "      <td>2050</td>\n",
       "      <td>Yirgacheffe</td>\n",
       "      <td>Washed</td>\n",
       "      <td>Flat Filter</td>\n",
       "      <td>95.555556</td>\n",
       "      <td>687</td>\n",
       "      <td>10.0</td>\n",
       "      <td>18</td>\n",
       "      <td>7p</td>\n",
       "      <td>23</td>\n",
       "      <td>4.60</td>\n",
       "      <td>0 days 00:03:45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Guatemala Las Nueces</td>\n",
       "      <td>Pacas</td>\n",
       "      <td>2000</td>\n",
       "      <td>Nuevo Oriente &amp; Jalapa</td>\n",
       "      <td>Washed</td>\n",
       "      <td>Cone Filter</td>\n",
       "      <td>96.111111</td>\n",
       "      <td>687</td>\n",
       "      <td>10.0</td>\n",
       "      <td>18</td>\n",
       "      <td>7p</td>\n",
       "      <td>23</td>\n",
       "      <td>4.60</td>\n",
       "      <td>0 days 00:03:55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Bolivia Caranavi Matriarcas Project</td>\n",
       "      <td>Bourbon</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Caranavi</td>\n",
       "      <td>Washed</td>\n",
       "      <td>Cone Filter</td>\n",
       "      <td>95.555556</td>\n",
       "      <td>687</td>\n",
       "      <td>10.0</td>\n",
       "      <td>18</td>\n",
       "      <td>7p</td>\n",
       "      <td>23</td>\n",
       "      <td>4.60</td>\n",
       "      <td>0 days 00:03:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Ethiopia Guji Bale Mountain Natural</td>\n",
       "      <td>Heirloom</td>\n",
       "      <td>2000</td>\n",
       "      <td>Guji</td>\n",
       "      <td>Natural</td>\n",
       "      <td>Cone Filter</td>\n",
       "      <td>95.555556</td>\n",
       "      <td>442</td>\n",
       "      <td>6.5</td>\n",
       "      <td>8</td>\n",
       "      <td>4c</td>\n",
       "      <td>15</td>\n",
       "      <td>2.00</td>\n",
       "      <td>0 days 00:04:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Colombia Huila Finca Samboni Gesha</td>\n",
       "      <td>Gesha</td>\n",
       "      <td>1850</td>\n",
       "      <td>Huila</td>\n",
       "      <td>Anaerobic Washed</td>\n",
       "      <td>Flat Filter</td>\n",
       "      <td>95.000000</td>\n",
       "      <td>515</td>\n",
       "      <td>7.5</td>\n",
       "      <td>11</td>\n",
       "      <td>5e</td>\n",
       "      <td>17</td>\n",
       "      <td>3.30</td>\n",
       "      <td>0 days 00:03:40</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                        Name                     Variety  \\\n",
       "1                                    Framily                    Heirloom   \n",
       "2               Ethiopia Hambela Bishan Fugu                    Heirloom   \n",
       "3                       Kenya Gichathaini AA          SL28 SL34 & Batian   \n",
       "4                    Colombia Aponte Village  Caturra Bourbon & Castillo   \n",
       "5                Mexico Puebla Zapotitlan #2            Bourbon & Typica   \n",
       "6           Costa Rica Las Lajas Black Honey                      Catuai   \n",
       "7             Burundi Long Miles Gaharo Hill                 Red Bourbon   \n",
       "8           Guatemala Finca Travesia Natural    Bourbon Catuai & Caturra   \n",
       "9               El Salvador Santa Rosa Honey                    Pacamara   \n",
       "10                       Kenya Muthingini AA          SL28 SL34 & Batian   \n",
       "11                    El Salvador Santa Rosa                    Pacamara   \n",
       "12             Ethiopia Gedeb Beriti Natural                    Heirloom   \n",
       "13                                Krampus PB          SL28 SL34 & Batian   \n",
       "14  Panama Creativa Giovana Boutet Anaerobic                      Cataui   \n",
       "15                  Kenya Kagunyu AA Natural          SL28 SL34 & Batian   \n",
       "16                     Ethiopia Gedeb Gotiti                    Heirloom   \n",
       "17       Mexico Finca Las Chicharras Natural            Bourbon & Typica   \n",
       "18         Burundi Long Miles Gaharo Natural                 Red Bourbon   \n",
       "19                 Honduras San Andres Lempa           Caturra & Bourbon   \n",
       "20          Ethiopia Yirgacheffe Halo Lot #8                    Heirloom   \n",
       "21                      Guatemala Las Nueces                       Pacas   \n",
       "22       Bolivia Caranavi Matriarcas Project                     Bourbon   \n",
       "23       Ethiopia Guji Bale Mountain Natural                    Heirloom   \n",
       "24        Colombia Huila Finca Samboni Gesha                       Gesha   \n",
       "\n",
       "   Elevation                  Region              Process  \\\n",
       "1       2000             Yirgacheffe               Washed   \n",
       "2       2000                    Guji               Washed   \n",
       "3       1800                   Nyeri               Washed   \n",
       "4       2100                  Narino                Honey   \n",
       "5       1650                  Puebla               Washed   \n",
       "6       1600                Alajuela                Honey   \n",
       "7       1950                 Kayanza               Washed   \n",
       "8        NaN                 Antigua              Natural   \n",
       "9       1800            Chalatenango                Honey   \n",
       "10      1800               Kirinyaga               Washed   \n",
       "11       NaN            Chalatenango               Washed   \n",
       "12      2000                   Gedeb              Natural   \n",
       "13      1800               Kirinyaga               Washed   \n",
       "14      1500              Alto Quiel  Anaerobic & Natural   \n",
       "15      1900                   Nyeri              Natural   \n",
       "16      2050                   Gedeb               Washed   \n",
       "17      1500              Jaltenango              Natural   \n",
       "18      1950                 Kayanza              Natural   \n",
       "19      1650                 Lempira               Washed   \n",
       "20      2050             Yirgacheffe               Washed   \n",
       "21      2000  Nuevo Oriente & Jalapa               Washed   \n",
       "22       NaN                Caranavi               Washed   \n",
       "23      2000                    Guji              Natural   \n",
       "24      1850                   Huila     Anaerobic Washed   \n",
       "\n",
       "                    Filter  Temperature  Microns  Mahlkonig EK43  \\\n",
       "1          v60 Cone Filter    95.555556      570             8.2   \n",
       "2        Kalita 185 Filter    95.000000      756            11.0   \n",
       "3              Cone filter    95.000000      682            10.0   \n",
       "4          v60 Cone Filter    96.111111      653             9.5   \n",
       "5   Kalita 185 Flat Filter    96.111111      515             7.5   \n",
       "6   Kalita 185 Flat Filter    96.111111      490             7.1   \n",
       "7          v60 Cone Filter    94.444444      528             7.5   \n",
       "8        Kalita 185 Filter    94.444444      490             7.1   \n",
       "9       Kalita Flat Filter    95.555556      610             8.8   \n",
       "10  Kalita 185 Flat Filter    96.111111      721            10.5   \n",
       "11      Kalita Flat Filter    94.444444      569             8.2   \n",
       "12         V60 Cone Filter    96.111111      515             7.5   \n",
       "13      Flat Kalita Filter    93.333333      550             8.0   \n",
       "14             Cone Filter    93.333333      490             7.1   \n",
       "15             Cone Filter    96.111111      562             8.2   \n",
       "16             Cone Filter    95.555556      632             9.2   \n",
       "17             Cone Filter    95.000000      584             8.5   \n",
       "18             Cone Filter    95.000000      730            10.6   \n",
       "19             Flat Filter    95.555556      618             9.0   \n",
       "20             Flat Filter    95.555556      687            10.0   \n",
       "21             Cone Filter    96.111111      687            10.0   \n",
       "22             Cone Filter    95.555556      687            10.0   \n",
       "23             Cone Filter    95.555556      442             6.5   \n",
       "24             Flat Filter    95.000000      515             7.5   \n",
       "\n",
       "    Baratza Encore Baratza Vario+  Comandante C40  Fellow Ode Gen 2  \\\n",
       "1               13             5v              19              3.66   \n",
       "2               21             8q              25              5.00   \n",
       "3               18             7o              23              4.00   \n",
       "4               17             7e              22              4.30   \n",
       "5               11             5e              17              3.30   \n",
       "6               10             4s              16              3.00   \n",
       "7               12             5i              18              3.30   \n",
       "8               10             4s              16              3.00   \n",
       "9               15             6m              20              4.00   \n",
       "10              20             8f              24              5.00   \n",
       "11              13             5v              19              3.66   \n",
       "12              11             5e              17              3.30   \n",
       "13              13             5p              18              3.66   \n",
       "14              10             4s              16              3.00   \n",
       "15              13             5t              19              3.00   \n",
       "16              16             6u              21              4.30   \n",
       "17              14             6e              19              4.00   \n",
       "18              20             8h              24              5.00   \n",
       "19              16             6p              21              4.00   \n",
       "20              18             7p              23              4.60   \n",
       "21              18             7p              23              4.60   \n",
       "22              18             7p              23              4.60   \n",
       "23               8             4c              15              2.00   \n",
       "24              11             5e              17              3.30   \n",
       "\n",
       "             Drain  \n",
       "1  0 days 00:03:40  \n",
       "2  0 days 00:03:11  \n",
       "3  0 days 00:03:30  \n",
       "4  0 days 00:02:50  \n",
       "5  0 days 00:03:10  \n",
       "6  0 days 00:02:45  \n",
       "7  0 days 00:04:00  \n",
       "8  0 days 00:02:50  \n",
       "9  0 days 00:02:55  \n",
       "10 0 days 00:03:00  \n",
       "11 0 days 00:03:00  \n",
       "12 0 days 00:03:25  \n",
       "13 0 days 00:03:05  \n",
       "14 0 days 00:03:00  \n",
       "15 0 days 00:03:15  \n",
       "16 0 days 00:03:40  \n",
       "17 0 days 00:03:10  \n",
       "18 0 days 00:03:15  \n",
       "19 0 days 00:03:30  \n",
       "20 0 days 00:03:45  \n",
       "21 0 days 00:03:55  \n",
       "22 0 days 00:03:25  \n",
       "23 0 days 00:04:00  \n",
       "24 0 days 00:03:40  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "recipes = []\n",
    "for coffee in soup.find_all(\"div\", {\"class\": \"pop-left\"}):\n",
    "    data = {\n",
    "        \"Name\": coffee.h2.string,\n",
    "    }\n",
    "\n",
    "    for span in coffee.find(\"div\", {\"class\": \"features\"}).find_all(\"span\"):\n",
    "        feature, value = span.string.split(\": \")\n",
    "        if feature != \"Origin\":\n",
    "            data[feature] = value\n",
    "\n",
    "    setup_ps = coffee.find(\"div\", {\"class\": \"box-setup\"}).find_all(\"p\")\n",
    "    data[\"Filter\"] = setup_ps[0].string[11:]\n",
    "    temperature_in_F = float(setup_ps[2].string.split()[-1][:-2])\n",
    "    data[\"Temperature\"] = (temperature_in_F - 32) / 1.8\n",
    "\n",
    "    for line in coffee.find(\"div\", {\"class\": \"box-grind\"}).p.text.split(\"\\n\"):\n",
    "        grind, grinder = line.split(\" \", maxsplit=1)\n",
    "        if grinder == \"um\":\n",
    "            grinder = \"Microns\"\n",
    "        elif grinder == \"EK43\":\n",
    "            grinder = \"Mahlkonig EK43\"\n",
    "        elif grinder == \"Baratza Vario/Forte\":\n",
    "            grinder = \"Baratza Vario+\"\n",
    "        elif grinder == \"2/3 Fellow Ode Gen 2\":\n",
    "            grinder = \"Fellow Ode Gen 2\"\n",
    "        data[grinder] = grind\n",
    "    data[\"Drain\"] = (\n",
    "        coffee.find(\"div\", {\"class\": \"box-brew\"})\n",
    "        .p.text.split(\"\\n\")[-1]\n",
    "        .split()[0]\n",
    "        .replace(\"~\", \"\")\n",
    "    )\n",
    "    recipes.append(data)\n",
    "\n",
    "recipes = pd.DataFrame(recipes)\n",
    "recipes.index += 1\n",
    "recipes[\"Elevation\"] = recipes[\"Elevation\"].str[:-5]\n",
    "int_grinders = [\n",
    "    \"Microns\",\n",
    "    \"Baratza Encore\",\n",
    "    \"Comandante C40\",\n",
    "]\n",
    "recipes[int_grinders] = recipes[int_grinders].astype(int)\n",
    "float_grinders = [\n",
    "    \"Mahlkonig EK43\",\n",
    "    \"Fellow Ode Gen 2\",\n",
    "]\n",
    "recipes[float_grinders] = recipes[float_grinders].astype(float)\n",
    "recipes[\"Drain\"] = pd.to_timedelta(\"00:\" + recipes[\"Drain\"])\n",
    "recipes.to_csv(\"data/onyx_coffee_advent_calendar_2023.csv\")\n",
    "recipes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "1071c52a-62db-4196-9448-c9cdea7ea6b6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x900 with 30 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "grinds = int_grinders + float_grinders\n",
    "\n",
    "sns.pairplot(recipes[grinds])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a774bd6f-416a-4170-9c6a-973f20cc9277",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "3304be0b-a66e-4085-8cbb-0f83245d6ce7",
   "metadata": {},
   "outputs": [],
   "source": [
    "simple_recipes = recipes.copy()\n",
    "simple_recipes[\"Process\"] = simple_recipes[\"Process\"].apply(\n",
    "    lambda process: \"Washed\" if process == \"Washed\" else \"Processed\"\n",
    ")\n",
    "simple_recipes[\"Filter\"] = simple_recipes[\"Filter\"].apply(\n",
    "    lambda filter_: \"Cone filter\" if \"one\" in filter_ else \"Kalita filter\"\n",
    ")\n",
    "simple_recipes[\"Drain [min]\"] = simple_recipes[\"Drain\"] / pd.to_timedelta(\"1min\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "d74e96ad-b78b-4a71-bc80-bdd3cc74d0d3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def plot_correlation(x, y):\n",
    "    for (process, filter_), group in simple_recipes.groupby([\"Process\", \"Filter\"]):\n",
    "        plt.scatter(\n",
    "            group[x],\n",
    "            group[y],\n",
    "            color=\"tab:blue\" if process == \"Washed\" else \"tab:orange\",\n",
    "            marker=\"v\" if filter_ == \"Cone filter\" else \"*\",\n",
    "            label=f\"{process}, {filter_}\",\n",
    "        )\n",
    "    plt.gca().set_xlabel(x)\n",
    "    plt.gca().set_ylabel(y)\n",
    "    plt.legend(frameon=False, bbox_to_anchor=(1.05, 1), loc=\"upper left\")\n",
    "    sns.despine()\n",
    "    plt.show()\n",
    "\n",
    "\n",
    "plot_correlation(\"Drain [min]\", \"Microns\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "88505ee5-a4a8-4c03-be44-cbf6e9cad932",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_correlation(\"Drain [min]\", \"Temperature\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "142b2230-9481-4ae6-a128-52a42ed1cac3",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "0b34a236-38da-44a4-a1cf-64fcd62e2e85",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def plot_strips(by):\n",
    "    parameters = [\"Temperature\", \"Microns\", \"Drain [min]\"]\n",
    "    fig, axs = plt.subplots(nrows=len(parameters))\n",
    "    for ax, parameter in zip(axs, parameters):\n",
    "        data = (\n",
    "            simple_recipes[[by, parameter]]\n",
    "            .melt(id_vars=by, var_name=\"Parameter\")\n",
    "            .rename(columns={\"value\": parameter})\n",
    "        )\n",
    "        sns.swarmplot(data=data, x=parameter, y=by, ax=ax)\n",
    "        ax.set_ylabel(\"\")\n",
    "\n",
    "    sns.despine(fig)\n",
    "    plt.tight_layout()\n",
    "    plt.show()\n",
    "\n",
    "\n",
    "plot_strips(\"Process\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "62bdb4db-1716-4897-9295-29752b277139",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
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   ],
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    "plot_strips(\"Process\")"
   ]
  },
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   "execution_count": null,
   "id": "57e48e95-330f-4129-b3d1-067b2448b3ee",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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